src/TMIDIX.py

#! /usr/bin/python3

import os
import re
import json
import math
import tqdm
import copy
import psutil
import shutil
import random
import hashlib
import secrets
import statistics
import multiprocessing
from src import MIDI

from array import array
from pathlib import Path
from fnmatch import fnmatch
from collections import Counter
from collections import defaultdict
from collections import OrderedDict
from difflib import SequenceMatcher as SM
from operator import itemgetter
from itertools import product, combinations, groupby

###################################################################################

# TMIDI X Code is below

###################################################################################

def Optimus_MIDI_TXT_Processor(MIDI_file, 
                              line_by_line_output=True, 
                              chordify_TXT=False,
                              dataset_MIDI_events_time_denominator=1,
                              output_velocity=True,
                              output_MIDI_channels = False, 
                              MIDI_channel=0, 
                              MIDI_patch=[0, 1], 
                              char_offset = 30000,
                              transpose_by = 0,
                              flip=False, 
                              melody_conditioned_encoding=False,
                              melody_pitch_baseline = 0,
                              number_of_notes_to_sample = -1,
                              sampling_offset_from_start = 0,
                              karaoke=False,
                              karaoke_language_encoding='utf-8',
                              song_name='Song',
                              perfect_timings=False,
                              musenet_encoding=False,
                              transform=0,
                              zero_token=False,
                              reset_timings=False):

    '''Project Los Angeles
       Tegridy Code 2021'''
  
###########

    debug = False

    ev = 0

    chords_list_final = []
    chords_list = []
    events_matrix = []
    melody = []
    melody1 = []

    itrack = 1

    min_note = 0
    max_note = 0
    ev = 0
    patch = 0

    score = []
    rec_event = []

    txt = ''
    txtc = ''
    chords = []
    melody_chords = []

    karaoke_events_matrix = []
    karaokez = []

    sample = 0
    start_sample = 0

    bass_melody = []

    INTS = []
    bints = 0

###########    

    def list_average(num):
      sum_num = 0
      for t in num:
          sum_num = sum_num + t           

      avg = sum_num / len(num)
      return avg

###########

    #print('Loading MIDI file...')
    midi_file = open(MIDI_file, 'rb')
    if debug: print('Processing File:', MIDI_file)
    
    try:
      opus = MIDI.midi2opus(midi_file.read())
    
    except:
      print('Problematic MIDI. Skipping...')
      print('File name:', MIDI_file)
      midi_file.close()
      return txt, melody, chords
         
    midi_file.close()

    score1 = MIDI.to_millisecs(opus)
    score2 = MIDI.opus2score(score1)

    # score2 = MIDI.opus2score(opus) # TODO Improve score timings when it will be possible.
    
    if MIDI_channel == 16: # Process all MIDI channels
      score = score2
    
    if MIDI_channel >= 0 and MIDI_channel <= 15: # Process only a selected single MIDI channel
      score = MIDI.grep(score2, [MIDI_channel])
    
    if MIDI_channel == -1: # Process all channels except drums (except channel 9)
      score = MIDI.grep(score2, [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15])   
    
    #print('Reading all MIDI events from the MIDI file...')
    while itrack < len(score):
      for event in score[itrack]:
        
        if perfect_timings:
          if event[0] == 'note':
            event[1] = round(event[1], -1)
            event[2] = round(event[2], -1)

        if event[0] == 'text_event' or event[0] == 'lyric' or event[0] == 'note':
          if perfect_timings:
            event[1] = round(event[1], -1)
          karaokez.append(event)
        
        if event[0] == 'text_event' or event[0] == 'lyric':
          if perfect_timings:
            event[1] = round(event[1], -1)
          try:
            event[2] = str(event[2].decode(karaoke_language_encoding, 'replace')).replace('/', '').replace(' ', '').replace('\\', '')
          except:
            event[2] = str(event[2]).replace('/', '').replace(' ', '').replace('\\', '')
            continue
          karaoke_events_matrix.append(event)

        if event[0] == 'patch_change':
          patch = event[3]

        if event[0] == 'note' and patch in MIDI_patch:
          if len(event) == 6: # Checking for bad notes...
              eve = copy.deepcopy(event)
              
              eve[1] = int(event[1] / dataset_MIDI_events_time_denominator)
              eve[2] = int(event[2] / dataset_MIDI_events_time_denominator)
              
              eve[4] = int(event[4] + transpose_by)
              
              if flip == True:
                eve[4] = int(127 - (event[4] + transpose_by)) 
              
              if number_of_notes_to_sample > -1:
                if sample <= number_of_notes_to_sample:
                  if start_sample >= sampling_offset_from_start:
                    events_matrix.append(eve)
                    sample += 1
                    ev += 1
                  else:
                    start_sample += 1

              else:
                events_matrix.append(eve)
                ev += 1
                start_sample += 1
                
      itrack +=1 # Going to next track...

    #print('Doing some heavy pythonic sorting...Please stand by...')

    fn = os.path.basename(MIDI_file)
    song_name = song_name.replace(' ', '_').replace('=', '_').replace('\'', '-')
    if song_name == 'Song':
      sng_name = fn.split('.')[0].replace(' ', '_').replace('=', '_').replace('\'', '-')
      song_name = sng_name

    # Zero token
    if zero_token:
      txt += chr(char_offset) + chr(char_offset)
      if output_MIDI_channels:
        txt += chr(char_offset)
      if output_velocity:
        txt += chr(char_offset) + chr(char_offset)     
      else:
        txt += chr(char_offset)

      txtc += chr(char_offset) + chr(char_offset)
      if output_MIDI_channels:
        txtc += chr(char_offset)
      if output_velocity:
        txtc += chr(char_offset) + chr(char_offset)      
      else:
        txtc += chr(char_offset)
      
      txt += '=' + song_name + '_with_' + str(len(events_matrix)-1) + '_notes'
      txtc += '=' + song_name + '_with_' + str(len(events_matrix)-1) + '_notes'
    
    else:
      # Song stamp
      txt += 'SONG=' + song_name + '_with_' + str(len(events_matrix)-1) + '_notes'
      txtc += 'SONG=' + song_name + '_with_' + str(len(events_matrix)-1) + '_notes'

    if line_by_line_output:
      txt += chr(10)
      txtc += chr(10)
    else:
      txt += chr(32)
      txtc += chr(32)

    #print('Sorting input by start time...')
    events_matrix.sort(key=lambda x: x[1]) # Sorting input by start time    
    
    #print('Timings converter')
    if reset_timings:
      ev_matrix = Tegridy_Timings_Converter(events_matrix)[0]
    else:
      ev_matrix = events_matrix
    
    chords.extend(ev_matrix)
    #print(chords)

    #print('Extracting melody...')
    melody_list = []

    #print('Grouping by start time. This will take a while...')
    values = set(map(lambda x:x[1], ev_matrix)) # Non-multithreaded function version just in case

    groups = [[y for y in ev_matrix if y[1]==x and len(y) == 6] for x in values] # Grouping notes into chords while discarting bad notes...
  
    #print('Sorting events...')
    for items in groups:
        
        items.sort(reverse=True, key=lambda x: x[4]) # Sorting events by pitch
        
        if melody_conditioned_encoding: items[0][3] = 0 # Melody should always bear MIDI Channel 0 for code to work
        
        melody_list.append(items[0]) # Creating final melody list
        melody_chords.append(items) # Creating final chords list
        bass_melody.append(items[-1]) # Creating final bass melody list
    
    # [WIP] Melody-conditioned chords list
    if melody_conditioned_encoding == True:
      if not karaoke:
   
        previous_event = copy.deepcopy(melody_chords[0][0])

        for ev in melody_chords:
          hp = True
          ev.sort(reverse=False, key=lambda x: x[4]) # Sorting chord events by pitch
          for event in ev:
          
            # Computing events details
            start_time = int(abs(event[1] - previous_event[1]))
            
            duration = int(previous_event[2])

            if hp == True:
              if int(previous_event[4]) >= melody_pitch_baseline:
                channel = int(0)
                hp = False
              else:
                channel = int(previous_event[3]+1)
                hp = False  
            else:
              channel = int(previous_event[3]+1)
              hp = False

            pitch = int(previous_event[4])

            velocity = int(previous_event[5])

            # Writing INTergerS...
            try:
              INTS.append([(start_time)+char_offset, (duration)+char_offset, channel+char_offset, pitch+char_offset, velocity+char_offset])
            except:
              bints += 1

            # Converting to TXT if possible...
            try:
              txtc += str(chr(start_time + char_offset))
              txtc += str(chr(duration + char_offset))
              txtc += str(chr(pitch + char_offset))
              if output_velocity:
                txtc += str(chr(velocity + char_offset))
              if output_MIDI_channels:
                txtc += str(chr(channel + char_offset))

              if line_by_line_output:
              

                txtc += chr(10)
              else:

                txtc += chr(32)

              previous_event = copy.deepcopy(event)
            
            except:
              # print('Problematic MIDI event! Skipping...')
              continue

        if not line_by_line_output:
          txtc += chr(10)

        txt = txtc
        chords = melody_chords
    
    # Default stuff (not melody-conditioned/not-karaoke)
    else:      
      if not karaoke:
        melody_chords.sort(reverse=False, key=lambda x: x[0][1])
        mel_chords = []
        for mc in melody_chords:
          mel_chords.extend(mc)

        if transform != 0: 
          chords = Tegridy_Transform(mel_chords, transform)
        else:
          chords = mel_chords

        # TXT Stuff
        previous_event = copy.deepcopy(chords[0])
        for event in chords:

          # Computing events details
          start_time = int(abs(event[1] - previous_event[1]))
          
          duration = int(previous_event[2])

          channel = int(previous_event[3])

          pitch = int(previous_event[4] + transpose_by)
          if flip == True:
            pitch = 127 - int(previous_event[4] + transpose_by)

          velocity = int(previous_event[5])

          # Writing INTergerS...
          try:
            INTS.append([(start_time)+char_offset, (duration)+char_offset, channel+char_offset, pitch+char_offset, velocity+char_offset])
          except:
            bints += 1

          # Converting to TXT if possible...
          try:
            txt += str(chr(start_time + char_offset))
            txt += str(chr(duration + char_offset))
            txt += str(chr(pitch + char_offset))
            if output_velocity:
              txt += str(chr(velocity + char_offset))
            if output_MIDI_channels:
              txt += str(chr(channel + char_offset))


            if chordify_TXT == True and int(event[1] - previous_event[1]) == 0:
              txt += ''      
            else:     
              if line_by_line_output:
                txt += chr(10)
              else:
                txt += chr(32) 
            
            previous_event = copy.deepcopy(event)
          
          except:
            # print('Problematic MIDI event. Skipping...')
            continue

        if not line_by_line_output:
          txt += chr(10)      

    # Karaoke stuff
    if karaoke:

      melody_chords.sort(reverse=False, key=lambda x: x[0][1])
      mel_chords = []
      for mc in melody_chords:
        mel_chords.extend(mc)

      if transform != 0: 
        chords = Tegridy_Transform(mel_chords, transform)
      else:
        chords = mel_chords

      previous_event = copy.deepcopy(chords[0])
      for event in chords:

        # Computing events details
        start_time = int(abs(event[1] - previous_event[1]))
        
        duration = int(previous_event[2])

        channel = int(previous_event[3])

        pitch = int(previous_event[4] + transpose_by)

        velocity = int(previous_event[5])

        # Converting to TXT
        txt += str(chr(start_time + char_offset))
        txt += str(chr(duration + char_offset))
        txt += str(chr(pitch + char_offset))

        txt += str(chr(velocity + char_offset))
        txt += str(chr(channel + char_offset))     

        if start_time > 0:
          for k in karaoke_events_matrix:
            if event[1] == k[1]:
              txt += str('=')
              txt += str(k[2])          
              break

        if line_by_line_output:
          txt += chr(10)
        else:
          txt += chr(32) 
        
        previous_event = copy.deepcopy(event)
      
      if not line_by_line_output:
        txt += chr(10)

    # Final processing code...
    # =======================================================================

    # Helper aux/backup function for Karaoke
    karaokez.sort(reverse=False, key=lambda x: x[1])  

    # MuseNet sorting
    if musenet_encoding and not melody_conditioned_encoding and not karaoke:
      chords.sort(key=lambda x: (x[1], x[3]))
    
    # Final melody sort
    melody_list.sort()

    # auxs for future use
    aux1 = [None]
    aux2 = [None]

    return txt, melody_list, chords, bass_melody, karaokez, INTS, aux1, aux2 # aux1 and aux2 are not used atm

###################################################################################

def Optimus_TXT_to_Notes_Converter(Optimus_TXT_String,
                                    line_by_line_dataset = True,
                                    has_velocities = True,
                                    has_MIDI_channels = True,
                                    dataset_MIDI_events_time_denominator = 1,
                                    char_encoding_offset = 30000,
                                    save_only_first_composition = True,
                                    simulate_velocity=True,
                                    karaoke=False,
                                    zero_token=False):

    '''Project Los Angeles
       Tegridy Code 2020'''

    print('Tegridy Optimus TXT to Notes Converter')
    print('Converting TXT to Notes list...Please wait...')

    song_name = ''

    if line_by_line_dataset:
      input_string = Optimus_TXT_String.split('\n')
    else:
      input_string = Optimus_TXT_String.split(' ')

    if line_by_line_dataset:
      name_string = Optimus_TXT_String.split('\n')[0].split('=')
    else:
      name_string = Optimus_TXT_String.split(' ')[0].split('=')

    # Zero token
    zt = ''

    zt += chr(char_encoding_offset) + chr(char_encoding_offset)
    
    if has_MIDI_channels:
      zt += chr(char_encoding_offset)
    
    if has_velocities:
      zt += chr(char_encoding_offset) + chr(char_encoding_offset)     
    
    else:
      zt += chr(char_encoding_offset)

    if zero_token:
      if name_string[0] == zt:
        song_name = name_string[1]
    
    else:
      if name_string[0] == 'SONG':
        song_name = name_string[1]

    output_list = []
    st = 0

    for i in range(2, len(input_string)-1):

      if save_only_first_composition:
        if zero_token:
          if input_string[i].split('=')[0] == zt:

            song_name = name_string[1]
            break
        
        else:
          if input_string[i].split('=')[0] == 'SONG':

            song_name = name_string[1]
            break
      try:
        istring = input_string[i]

        if has_MIDI_channels == False:
          step = 4          

        if has_MIDI_channels == True:
          step = 5

        if has_velocities == False:
          step -= 1

        st += int(ord(istring[0]) - char_encoding_offset) * dataset_MIDI_events_time_denominator

        if not karaoke:
          for s in range(0, len(istring), step):
              if has_MIDI_channels==True:
                if step > 3 and len(istring) > 2:
                      out = []       
                      out.append('note')

                      out.append(st) # Start time

                      out.append(int(ord(istring[s+1]) - char_encoding_offset) * dataset_MIDI_events_time_denominator) # Duration

                      if has_velocities:
                        out.append(int(ord(istring[s+4]) - char_encoding_offset)) # Channel
                      else:
                        out.append(int(ord(istring[s+3]) - char_encoding_offset)) # Channel  

                      out.append(int(ord(istring[s+2]) - char_encoding_offset)) # Pitch

                      if simulate_velocity:
                        if s == 0:
                          sim_vel = int(ord(istring[s+2]) - char_encoding_offset)
                        out.append(sim_vel) # Simulated Velocity (= highest note's pitch)
                      else:                      
                        out.append(int(ord(istring[s+3]) - char_encoding_offset)) # Velocity

              if has_MIDI_channels==False:
                if step > 3 and len(istring) > 2:
                      out = []       
                      out.append('note')

                      out.append(st) # Start time
                      out.append(int(ord(istring[s+1]) - char_encoding_offset) * dataset_MIDI_events_time_denominator) # Duration
                      out.append(0) # Channel
                      out.append(int(ord(istring[s+2]) - char_encoding_offset)) # Pitch

                      if simulate_velocity:
                        if s == 0:
                          sim_vel = int(ord(istring[s+2]) - char_encoding_offset)
                        out.append(sim_vel) # Simulated Velocity (= highest note's pitch)
                      else:                      
                        out.append(int(ord(istring[s+3]) - char_encoding_offset)) # Velocity

              if step == 3 and len(istring) > 2:
                      out = []       
                      out.append('note')

                      out.append(st) # Start time
                      out.append(int(ord(istring[s+1]) - char_encoding_offset) * dataset_MIDI_events_time_denominator) # Duration
                      out.append(0) # Channel
                      out.append(int(ord(istring[s+2]) - char_encoding_offset)) # Pitch

                      out.append(int(ord(istring[s+2]) - char_encoding_offset)) # Velocity = Pitch

              output_list.append(out)

        if karaoke:
          try:
              out = []       
              out.append('note')

              out.append(st) # Start time
              out.append(int(ord(istring[1]) - char_encoding_offset) * dataset_MIDI_events_time_denominator) # Duration
              out.append(int(ord(istring[4]) - char_encoding_offset)) # Channel
              out.append(int(ord(istring[2]) - char_encoding_offset)) # Pitch

              if simulate_velocity:
                if s == 0:
                  sim_vel = int(ord(istring[2]) - char_encoding_offset)
                out.append(sim_vel) # Simulated Velocity (= highest note's pitch)
              else:                      
                out.append(int(ord(istring[3]) - char_encoding_offset)) # Velocity
              output_list.append(out)
              out = []
              if istring.split('=')[1] != '':
                out.append('lyric')
                out.append(st)
                out.append(istring.split('=')[1])
                output_list.append(out)
          except:
            continue


      except:
        print('Bad note string:', istring)
        continue

    # Simple error control just in case
    S = []
    for x in output_list:
      if len(x) == 6 or len(x) == 3:
        S.append(x)

    output_list.clear()    
    output_list = copy.deepcopy(S)


    print('Task complete! Enjoy! :)')

    return output_list, song_name

###################################################################################

def Optimus_Data2TXT_Converter(data,
                              dataset_time_denominator=1,
                              transpose_by = 0,
                              char_offset = 33,
                              line_by_line_output = True,
                              output_velocity = False,
                              output_MIDI_channels = False):


  '''Input: data as a flat chords list of flat chords lists

  Output: TXT string
          INTs

  Project Los Angeles
  Tegridy Code 2021'''

  txt = ''
  TXT = ''

  quit = False
  counter = 0

  INTs = []
  INTs_f = []

  for d in tqdm.tqdm(sorted(data)):

    if quit == True:
      break

    txt = 'SONG=' + str(counter)
    counter += 1

    if line_by_line_output:
      txt += chr(10)
    else:
      txt += chr(32)
      
    INTs = []

    # TXT Stuff
    previous_event = copy.deepcopy(d[0])
    for event in sorted(d):

      # Computing events details
      start_time = int(abs(event[1] - previous_event[1]) / dataset_time_denominator)
      
      duration = int(previous_event[2] / dataset_time_denominator)

      channel = int(previous_event[3])

      pitch = int(previous_event[4] + transpose_by)

      velocity = int(previous_event[5])

      INTs.append([start_time, duration, pitch])

      # Converting to TXT if possible...
      try:
        txt += str(chr(start_time + char_offset))
        txt += str(chr(duration + char_offset))
        txt += str(chr(pitch + char_offset))
        if output_velocity:
          txt += str(chr(velocity + char_offset))
        if output_MIDI_channels:
          txt += str(chr(channel + char_offset))
    
        if line_by_line_output:
          txt += chr(10)
        else:
          txt += chr(32) 
        
        previous_event = copy.deepcopy(event)
      except KeyboardInterrupt:
        quit = True
        break
      except:
        print('Problematic MIDI data. Skipping...')
        continue

    if not line_by_line_output:
      txt += chr(10)
    
    TXT += txt
    INTs_f.extend(INTs)

  return TXT, INTs_f

###################################################################################

def Optimus_Squash(chords_list, simulate_velocity=True, mono_compression=False):

  '''Input: Flat chords list
            Simulate velocity or not
            Mono-compression enabled or disabled
            
            Default is almost lossless 25% compression, otherwise, lossy 50% compression (mono-compression)

     Output: Squashed chords list
             Resulting compression level

             Please note that if drums are passed through as is

     Project Los Angeles
     Tegridy Code 2021'''

  output = []
  ptime = 0
  vel = 0
  boost = 15
  stptc = []
  ocount = 0
  rcount = 0

  for c in chords_list:
    
    cc = copy.deepcopy(c)
    ocount += 1
    
    if [cc[1], cc[3], (cc[4] % 12) + 60] not in stptc:
      stptc.append([cc[1], cc[3], (cc[4] % 12) + 60])

      if cc[3] != 9:
        cc[4] = (c[4] % 12) + 60

      if simulate_velocity and c[1] != ptime:
        vel = c[4] + boost
      
      if cc[3] != 9:
        cc[5] = vel

      if mono_compression:
        if c[1] != ptime:
          output.append(cc)
          rcount += 1  
      else:
        output.append(cc)
        rcount += 1
      
      ptime = c[1]

  output.sort(key=lambda x: (x[1], x[4]))

  comp_level = 100 - int((rcount * 100) / ocount)

  return output, comp_level

###################################################################################

def Optimus_Signature(chords_list, calculate_full_signature=False):

    '''Optimus Signature

    ---In the name of the search for a perfect score slice signature---
     
    Input: Flat chords list to evaluate

    Output: Full Optimus Signature as a list
            Best/recommended Optimus Signature as a list

    Project Los Angeles
    Tegridy Code 2021'''
    
    # Pitches

    ## StDev
    if calculate_full_signature:
      psd = statistics.stdev([int(y[4]) for y in chords_list])
    else:
      psd = 0

    ## Median
    pmh = statistics.median_high([int(y[4]) for y in chords_list])
    pm = statistics.median([int(y[4]) for y in chords_list])
    pml = statistics.median_low([int(y[4]) for y in chords_list])
    
    ## Mean
    if calculate_full_signature:
      phm = statistics.harmonic_mean([int(y[4]) for y in chords_list])
    else:
      phm = 0

    # Durations
    dur = statistics.median([int(y[2]) for y in chords_list])

    # Velocities

    vel = statistics.median([int(y[5]) for y in chords_list])

    # Beats
    mtds = statistics.median([int(abs(chords_list[i-1][1]-chords_list[i][1])) for i in range(1, len(chords_list))])
    if calculate_full_signature:
      hmtds = statistics.harmonic_mean([int(abs(chords_list[i-1][1]-chords_list[i][1])) for i in range(1, len(chords_list))])
    else:
      hmtds = 0

    # Final Optimus signatures
    full_Optimus_signature = [round(psd), round(pmh), round(pm), round(pml), round(phm), round(dur), round(vel), round(mtds), round(hmtds)]
    ########################    PStDev     PMedianH    PMedian    PMedianL    PHarmoMe    Duration    Velocity      Beat       HarmoBeat

    best_Optimus_signature = [round(pmh), round(pm), round(pml), round(dur, -1), round(vel, -1), round(mtds, -1)]
    ########################   PMedianH    PMedian    PMedianL      Duration        Velocity          Beat
    
    # Return...
    return full_Optimus_signature, best_Optimus_signature
    

###################################################################################
#
# TMIDI 2.0 Helper functions
#
###################################################################################

def Tegridy_FastSearch(needle, haystack, randomize = False):

  '''

  Input: Needle iterable
         Haystack iterable
         Randomize search range (this prevents determinism)

  Output: Start index of the needle iterable in a haystack iterable
          If nothing found, -1 is returned

  Project Los Angeles
  Tegridy Code 2021'''

  need = copy.deepcopy(needle)

  try:
    if randomize:
      idx = haystack.index(need, secrets.randbelow(len(haystack)-len(need)))
    else:
      idx = haystack.index(need)

  except KeyboardInterrupt:
    return -1

  except:
    return -1
    
  return idx

###################################################################################

def Tegridy_Chord_Match(chord1, chord2, match_type=2):

    '''Tegridy Chord Match
     
    Input: Two chords to evaluate
           Match type: 2 = duration, channel, pitch, velocity
                       3 = channel, pitch, velocity
                       4 = pitch, velocity
                       5 = velocity

    Output: Match rating (0-100)
            NOTE: Match rating == -1 means identical source chords
            NOTE: Match rating == 100 means mutual shortest chord

    Project Los Angeles
    Tegridy Code 2021'''

    match_rating = 0

    if chord1 == []:
      return 0
    if chord2 == []:
      return 0

    if chord1 == chord2:
      return -1

    else:
      zipped_pairs = list(zip(chord1, chord2))
      zipped_diff = abs(len(chord1) - len(chord2))

      short_match = [False]
      for pair in zipped_pairs:
        cho1 = ' '.join([str(y) for y in pair[0][match_type:]])
        cho2 = ' '.join([str(y) for y in pair[1][match_type:]])
        if cho1 == cho2:
          short_match.append(True)
        else:
          short_match.append(False)
      
      if True in short_match:
        return 100

      pairs_ratings = []

      for pair in zipped_pairs:
        cho1 = ' '.join([str(y) for y in pair[0][match_type:]])
        cho2 = ' '.join([str(y) for y in pair[1][match_type:]])
        pairs_ratings.append(SM(None, cho1, cho2).ratio())

      match_rating = sum(pairs_ratings) / len(pairs_ratings) * 100

      return match_rating

###################################################################################

def Tegridy_Last_Chord_Finder(chords_list):

    '''Tegridy Last Chord Finder
     
    Input: Flat chords list

    Output: Last detected chord of the chords list
            Last chord start index in the original chords list
            First chord end index in the original chords list

    Project Los Angeles
    Tegridy Code 2021'''

    chords = []
    cho = []

    ptime = 0

    i = 0

    pc_idx = 0
    fc_idx = 0

    chords_list.sort(reverse=False, key=lambda x: x[1])
    
    for cc in chords_list:

      if cc[1] == ptime:
        
        cho.append(cc)

        ptime = cc[1]

      else:
        if pc_idx == 0: 
          fc_idx = chords_list.index(cc)
        pc_idx = chords_list.index(cc)
        
        chords.append(cho)
        
        cho = []
      
        cho.append(cc)
        
        ptime = cc[1]
        
        i += 1
      
    if cho != []: 
      chords.append(cho)
      i += 1
     
    return chords_list[pc_idx:], pc_idx, fc_idx

###################################################################################

def Tegridy_Chords_Generator(chords_list, shuffle_pairs = True, remove_single_notes=False):

    '''Tegridy Score Chords Pairs Generator
     
    Input: Flat chords list
           Shuffle pairs (recommended)

    Output: List of chords
            
            Average time(ms) per chord
            Average time(ms) per pitch
            Average chords delta time

            Average duration
            Average channel
            Average pitch
            Average velocity

    Project Los Angeles
    Tegridy Code 2021'''

    chords = []
    cho = []

    i = 0

    # Sort by start time
    chords_list.sort(reverse=False, key=lambda x: x[1])

    # Main loop
    pcho = chords_list[0]
    for cc in chords_list:
      if cc[1] == pcho[1]:
        
        cho.append(cc)
        pcho = copy.deepcopy(cc)

      else:
        if not remove_single_notes:
          chords.append(cho)
          cho = []
          cho.append(cc)
          pcho = copy.deepcopy(cc)
          
          i += 1
        else:
          if len(cho) > 1:
            chords.append(cho)
          cho = []
          cho.append(cc)
          pcho = copy.deepcopy(cc)
            
          i += 1  
    
    # Averages
    t0 = chords[0][0][1]
    t1 = chords[-1][-1][1]
    tdel = abs(t1 - t0)
    avg_ms_per_chord = int(tdel / i)
    avg_ms_per_pitch = int(tdel / len(chords_list))

    # Delta time
    tds = [int(abs(chords_list[i-1][1]-chords_list[i][1]) / 1) for i in range(1, len(chords_list))]
    if len(tds) != 0: avg_delta_time = int(sum(tds) / len(tds))

    # Chords list attributes
    p = int(sum([int(y[4]) for y in chords_list]) / len(chords_list))
    d = int(sum([int(y[2]) for y in chords_list]) / len(chords_list))
    c = int(sum([int(y[3]) for y in chords_list]) / len(chords_list))
    v = int(sum([int(y[5]) for y in chords_list]) / len(chords_list))

    # Final shuffle
    if shuffle_pairs:
      random.shuffle(chords)

    return chords, [avg_ms_per_chord, avg_ms_per_pitch, avg_delta_time], [d, c, p, v]

###################################################################################

def Tegridy_Chords_List_Music_Features(chords_list, st_dur_div = 1, pitch_div = 1, vel_div = 1):

    '''Tegridy Chords List Music Features
     
    Input: Flat chords list

    Output: A list of the extracted chords list's music features

    Project Los Angeles
    Tegridy Code 2021'''

    chords_list1 = [x for x in chords_list if x]
    chords_list1.sort(reverse=False, key=lambda x: x[1])
    
    # Features extraction code

    melody_list = []
    bass_melody = []
    melody_chords = []
    mel_avg_tds = []
    mel_chrd_avg_tds = []
    bass_melody_avg_tds = []

    #print('Grouping by start time. This will take a while...')
    values = set(map(lambda x:x[1], chords_list1)) # Non-multithreaded function version just in case

    groups = [[y for y in chords_list1 if y[1]==x and len(y) == 6] for x in values] # Grouping notes into chords while discarting bad notes...

    #print('Sorting events...')
    for items in groups:
        items.sort(reverse=True, key=lambda x: x[4]) # Sorting events by pitch
        melody_list.append(items[0]) # Creating final melody list
        melody_chords.append(items) # Creating final chords list
        bass_melody.append(items[-1]) # Creating final bass melody list

    #print('Final sorting by start time...')      
    melody_list.sort(reverse=False, key=lambda x: x[1]) # Sorting events by start time
    melody_chords.sort(reverse=False, key=lambda x: x[0][1]) # Sorting events by start time
    bass_melody.sort(reverse=False, key=lambda x: x[1]) # Sorting events by start time

    # Extracting music features from the chords list
    
    # Melody features
    mel_avg_pitch = int(sum([y[4] for y in melody_list]) / len(melody_list) / pitch_div)
    mel_avg_dur = int(sum([int(y[2] / st_dur_div) for y in melody_list]) / len(melody_list))
    mel_avg_vel = int(sum([int(y[5] / vel_div) for y in melody_list]) / len(melody_list))
    mel_avg_chan = int(sum([int(y[3]) for y in melody_list]) / len(melody_list))
    
    mel_tds = [int(abs(melody_list[i-1][1]-melody_list[i][1])) for i in range(1, len(melody_list))]
    if len(mel_tds) != 0: mel_avg_tds = int(sum(mel_tds) / len(mel_tds) / st_dur_div)
    
    melody_features = [mel_avg_tds, mel_avg_dur, mel_avg_chan, mel_avg_pitch, mel_avg_vel]

    # Chords list features
    mel_chrd_avg_pitch = int(sum([y[4] for y in chords_list1]) / len(chords_list1) / pitch_div)
    mel_chrd_avg_dur = int(sum([int(y[2] / st_dur_div) for y in chords_list1]) / len(chords_list1))
    mel_chrd_avg_vel = int(sum([int(y[5] / vel_div) for y in chords_list1]) / len(chords_list1))
    mel_chrd_avg_chan = int(sum([int(y[3]) for y in chords_list1]) / len(chords_list1))
    
    mel_chrd_tds = [int(abs(chords_list1[i-1][1]-chords_list1[i][1])) for i in range(1, len(chords_list1))]
    if len(mel_tds) != 0: mel_chrd_avg_tds = int(sum(mel_chrd_tds) / len(mel_chrd_tds) / st_dur_div)
    
    chords_list_features = [mel_chrd_avg_tds, mel_chrd_avg_dur, mel_chrd_avg_chan, mel_chrd_avg_pitch, mel_chrd_avg_vel]

    # Bass melody features
    bass_melody_avg_pitch = int(sum([y[4] for y in bass_melody]) / len(bass_melody) / pitch_div)
    bass_melody_avg_dur = int(sum([int(y[2] / st_dur_div) for y in bass_melody]) / len(bass_melody))
    bass_melody_avg_vel = int(sum([int(y[5] / vel_div) for y in bass_melody]) / len(bass_melody))
    bass_melody_avg_chan = int(sum([int(y[3]) for y in bass_melody]) / len(bass_melody))
    
    bass_melody_tds = [int(abs(bass_melody[i-1][1]-bass_melody[i][1])) for i in range(1, len(bass_melody))]
    if len(bass_melody_tds) != 0: bass_melody_avg_tds = int(sum(bass_melody_tds) / len(bass_melody_tds) / st_dur_div)
    
    bass_melody_features = [bass_melody_avg_tds, bass_melody_avg_dur, bass_melody_avg_chan, bass_melody_avg_pitch, bass_melody_avg_vel]
    
    # A list to return all features
    music_features = []

    music_features.extend([len(chords_list1)]) # Count of the original chords list notes
    
    music_features.extend(melody_features) # Extracted melody features
    music_features.extend(chords_list_features) # Extracted chords list features
    music_features.extend(bass_melody_features) # Extracted bass melody features
    music_features.extend([sum([y[4] for y in chords_list1])]) # Sum of all pitches in the original chords list

    return music_features

###################################################################################

def Tegridy_Transform(chords_list, to_pitch=60, to_velocity=-1):

    '''Tegridy Transform
     
    Input: Flat chords list
           Desired average pitch (-1 == no change)
           Desired average velocity (-1 == no change)

    Output: Transformed flat chords list

    Project Los Angeles
    Tegridy Code 2021'''

    transformed_chords_list = []

    chords_list.sort(reverse=False, key=lambda x: x[1])

    chords_list_features = Optimus_Signature(chords_list)[1]

    pitch_diff = int((chords_list_features[0] + chords_list_features[1] + chords_list_features[2]) / 3) - to_pitch
    velocity_diff = chords_list_features[4] - to_velocity

    for c in chords_list:
      cc = copy.deepcopy(c)
      if c[3] != 9: # Except the drums
        if to_pitch != -1: 
          cc[4] = c[4] - pitch_diff
        
        if to_velocity != -1: 
          cc[5] = c[5] - velocity_diff
      
      transformed_chords_list.append(cc)

    return transformed_chords_list

###################################################################################

def Tegridy_MIDI_Zip_Notes_Summarizer(chords_list, match_type = 4):

    '''Tegridy MIDI Zip Notes Summarizer
     
    Input: Flat chords list / SONG
           Match type according to 'note' event of MIDI.py

    Output: Summarized chords list
            Number of summarized notes
            Number of dicarted notes

    Project Los Angeles
    Tegridy Code 2021'''

    i = 0
    j = 0
    out1 = []
    pout = []
 

    for o in chords_list:

      # MIDI Zip

      if o[match_type:] not in pout:
        pout.append(o[match_type:])
        
        out1.append(o)
        j += 1
      
      else:
        i += 1

    return out1, i

###################################################################################

def Tegridy_Score_Chords_Pairs_Generator(chords_list, shuffle_pairs = True, remove_single_notes=False):

    '''Tegridy Score Chords Pairs Generator
     
    Input: Flat chords list
           Shuffle pairs (recommended)

    Output: Score chords pairs list
            Number of created pairs
            Number of detected chords

    Project Los Angeles
    Tegridy Code 2021'''

    chords = []
    cho = []

    i = 0
    j = 0

    chords_list.sort(reverse=False, key=lambda x: x[1])
    pcho = chords_list[0]
    for cc in chords_list:
      if cc[1] == pcho[1]:
        
        cho.append(cc)
        pcho = copy.deepcopy(cc)

      else:
        if not remove_single_notes:
          chords.append(cho)
          cho = []
          cho.append(cc)
          pcho = copy.deepcopy(cc)
          
          i += 1
        else:
          if len(cho) > 1:
            chords.append(cho)
          cho = []
          cho.append(cc)
          pcho = copy.deepcopy(cc)
            
          i += 1  
    
    chords_pairs = []
    for i in range(len(chords)-1):
      chords_pairs.append([chords[i], chords[i+1]])
      j += 1
    if shuffle_pairs: random.shuffle(chords_pairs)

    return chords_pairs, j, i

###################################################################################

def Tegridy_Sliced_Score_Pairs_Generator(chords_list, number_of_miliseconds_per_slice=2000, shuffle_pairs = False):

    '''Tegridy Sliced Score Pairs Generator
     
    Input: Flat chords list
           Number of miliseconds per slice

    Output: Sliced score pairs list
            Number of created slices

    Project Los Angeles
    Tegridy Code 2021'''

    chords = []
    cho = []

    time = number_of_miliseconds_per_slice 

    i = 0

    chords_list1 = [x for x in chords_list if x]
    chords_list1.sort(reverse=False, key=lambda x: x[1])
    pcho = chords_list1[0]
    for cc in chords_list1[1:]:

      if cc[1] <= time:
        
        cho.append(cc)

      else:
        if cho != [] and pcho != []: chords.append([pcho, cho])
        pcho = copy.deepcopy(cho)
        cho = []
        cho.append(cc)
        time += number_of_miliseconds_per_slice
        i += 1
      
    if cho != [] and pcho != []: 
      chords.append([pcho, cho])
      pcho = copy.deepcopy(cho)
      i += 1
    
    if shuffle_pairs: random.shuffle(chords)

    return chords, i

###################################################################################

def Tegridy_Timings_Converter(chords_list, 
                              max_delta_time = 1000, 
                              fixed_start_time = 250, 
                              start_time = 0,
                              start_time_multiplier = 1,
                              durations_multiplier = 1):

    '''Tegridy Timings Converter
     
    Input: Flat chords list
           Max delta time allowed between notes
           Fixed start note time for excessive gaps

    Output: Converted flat chords list

    Project Los Angeles
    Tegridy Code 2021'''

    song = chords_list

    song1 = []

    p = song[0]

    p[1] = start_time

    time = start_time

    delta = [0]

    for i in range(len(song)):
      if song[i][0] == 'note':
        ss = copy.deepcopy(song[i])
        if song[i][1] != p[1]:
          
          if abs(song[i][1] - p[1]) > max_delta_time:
            time += fixed_start_time
          else:
            time += abs(song[i][1] - p[1])
            delta.append(abs(song[i][1] - p[1]))

          ss[1] = int(round(time * start_time_multiplier, -1))
          ss[2] = int(round(song[i][2] * durations_multiplier, -1))
          song1.append(ss)
          
          p = copy.deepcopy(song[i])
        else:
          
          ss[1] = int(round(time * start_time_multiplier, -1))
          ss[2] = int(round(song[i][2] * durations_multiplier, -1))
          song1.append(ss)
          
          p = copy.deepcopy(song[i])
      
      else:
        ss = copy.deepcopy(song[i])
        ss[1] = time
        song1.append(ss)
        
    average_delta_st = int(sum(delta) / len(delta))
    average_duration = int(sum([y[2] for y in song1 if y[0] == 'note']) / len([y[2] for y in song1 if y[0] == 'note']))

    song1.sort(reverse=False, key=lambda x: x[1])

    return song1, time, average_delta_st, average_duration

###################################################################################

def Tegridy_Score_Slicer(chords_list, number_of_miliseconds_per_slice=2000, overlap_notes = 0, overlap_chords=False):

    '''Tegridy Score Slicer
     
    Input: Flat chords list
           Number of miliseconds per slice

    Output: Sliced chords list
            Number of created slices

    Project Los Angeles
    Tegridy Code 2021'''

    chords = []
    cho = []

    time = number_of_miliseconds_per_slice
    ptime = 0

    i = 0

    pc_idx = 0

    chords_list.sort(reverse=False, key=lambda x: x[1])
    
    for cc in chords_list:

      if cc[1] <= time:
        
        cho.append(cc)

        if ptime != cc[1]:
          pc_idx = cho.index(cc)

        ptime = cc[1]


      else:

        if overlap_chords:
          chords.append(cho)
          cho.extend(chords[-1][pc_idx:])
        
        else:
          chords.append(cho[:pc_idx])
        
        cho = []
      
        cho.append(cc)
        
        time += number_of_miliseconds_per_slice
        ptime = cc[1]
        
        i += 1
      
    if cho != []: 
      chords.append(cho)
      i += 1
    
    return [x for x in chords if x], i

###################################################################################

def Tegridy_TXT_Tokenizer(input_TXT_string, line_by_line_TXT_string=True):

    '''Tegridy TXT Tokenizer
     
    Input: TXT String

    Output: Tokenized TXT string + forward and reverse dics
    
    Project Los Angeles
    Tegridy Code 2021'''

    print('Tegridy TXT Tokenizer')

    if line_by_line_TXT_string:
      T = input_TXT_string.split()
    else:
      T = input_TXT_string.split(' ')

    DIC = dict(zip(T, range(len(T))))
    RDIC = dict(zip(range(len(T)), T))

    TXTT = ''

    for t in T:
      try:
        TXTT += chr(DIC[t])
      except:
        print('Error. Could not finish.')
        return TXTT, DIC, RDIC
    
    print('Done!')
    
    return TXTT, DIC, RDIC

###################################################################################

def Tegridy_TXT_DeTokenizer(input_Tokenized_TXT_string, RDIC):

    '''Tegridy TXT Tokenizer
     
    Input: Tokenized TXT String
           

    Output: DeTokenized TXT string
    
    Project Los Angeles
    Tegridy Code 2021'''

    print('Tegridy TXT DeTokenizer')

    Q = list(input_Tokenized_TXT_string)
    c = 0
    RTXT = ''
    for q in Q:
      try:
        RTXT += RDIC[ord(q)] + chr(10)
      except:
        c+=1

    print('Number of errors:', c)

    print('Done!')

    return RTXT

###################################################################################

def Tegridy_List_Slicer(input_list, slices_length_in_notes=20):

  '''Input: List to slice
            Desired slices length in notes
     
     Output: Sliced list of lists
     
     Project Los Angeles
     Tegridy Code 2021'''

  for i in range(0, len(input_list), slices_length_in_notes):
     yield input_list[i:i + slices_length_in_notes]
    
###################################################################################    
    
def Tegridy_Split_List(list_to_split, split_value=0):
    
    # src courtesy of www.geeksforgeeks.org
  
    # using list comprehension + zip() + slicing + enumerate()
    # Split list into lists by particular value
    size = len(list_to_split)
    idx_list = [idx + 1 for idx, val in
                enumerate(list_to_split) if val == split_value]


    res = [list_to_split[i: j] for i, j in
            zip([0] + idx_list, idx_list + 
            ([size] if idx_list[-1] != size else []))]
  
    # print result
    # print("The list after splitting by a value : " + str(res))
    
    return res

###################################################################################

# Binary chords functions

def tones_chord_to_bits(chord, reverse=True):

    bits = [0] * 12

    for num in chord:
        bits[num] = 1
    
    if reverse:
      bits.reverse()
      return bits
    
    else:
      return bits

def bits_to_tones_chord(bits):
    return [i for i, bit in enumerate(bits) if bit == 1]

def shift_bits(bits, n):
    return bits[-n:] + bits[:-n]

def bits_to_int(bits, shift_bits_value=0):
    bits = shift_bits(bits, shift_bits_value)
    result = 0
    for bit in bits:
        result = (result << 1) | bit
    
    return result

def int_to_bits(n):
    bits = [0] * 12
    for i in range(12):
        bits[11 - i] = n % 2
        n //= 2
    
    return bits

def bad_chord(chord):
    bad = any(b - a == 1 for a, b in zip(chord, chord[1:]))
    if (0 in chord) and (11 in chord):
      bad = True
    
    return bad

def pitches_chord_to_int(pitches_chord, tones_transpose_value=0):

    pitches_chord = [x for x in pitches_chord if 0 < x < 128]

    if not (-12 < tones_transpose_value < 12):
      tones_transpose_value = 0

    tones_chord = sorted(list(set([c % 12 for c in sorted(list(set(pitches_chord)))])))
    bits = tones_chord_to_bits(tones_chord)
    integer = bits_to_int(bits, shift_bits_value=tones_transpose_value)

    return integer

def int_to_pitches_chord(integer, chord_base_pitch=60): 
    if 0 < integer < 4096:
      bits = int_to_bits(integer)
      tones_chord = bits_to_tones_chord(bits)
      if not bad_chord(tones_chord):
        pitches_chord = [t+chord_base_pitch for t in tones_chord]
        return [pitches_chord, tones_chord]
      
      else:
        return 0 # Bad chord code
    
    else:
      return -1 # Bad integer code

###################################################################################

def validate_pitches_chord(pitches_chord, return_sorted = True):

    pitches_chord = sorted(list(set([x for x in pitches_chord if 0 < x < 128])))

    tones_chord = sorted(list(set([c % 12 for c in sorted(list(set(pitches_chord)))])))

    if not bad_chord(tones_chord):
      if return_sorted:
        pitches_chord.sort(reverse=True)
      return pitches_chord
    
    else:
      if 0 in tones_chord and 11 in tones_chord:
        tones_chord.remove(0)

      fixed_tones = [[a, b] for a, b in zip(tones_chord, tones_chord[1:]) if b-a != 1]

      fixed_tones_chord = []
      for f in fixed_tones:
        fixed_tones_chord.extend(f)
      fixed_tones_chord = list(set(fixed_tones_chord))
      
      fixed_pitches_chord = []

      for p in pitches_chord:
        if (p % 12) in fixed_tones_chord:
          fixed_pitches_chord.append(p)

      if return_sorted:
        fixed_pitches_chord.sort(reverse=True)

    return fixed_pitches_chord

def validate_pitches(chord, channel_to_check = 0, return_sorted = True):

    pitches_chord = sorted(list(set([x[4] for x in chord if 0 < x[4] < 128 and x[3] == channel_to_check])))

    if pitches_chord:

      tones_chord = sorted(list(set([c % 12 for c in sorted(list(set(pitches_chord)))])))

      if not bad_chord(tones_chord):
        if return_sorted:
          chord.sort(key = lambda x: x[4], reverse=True)
        return chord
      
      else:
        if 0 in tones_chord and 11 in tones_chord:
          tones_chord.remove(0)

        fixed_tones = [[a, b] for a, b in zip(tones_chord, tones_chord[1:]) if b-a != 1]

        fixed_tones_chord = []
        for f in fixed_tones:
          fixed_tones_chord.extend(f)
        fixed_tones_chord = list(set(fixed_tones_chord))
        
        fixed_chord = []

        for c in chord:
          if c[3] == channel_to_check:
            if (c[4] % 12) in fixed_tones_chord:
              fixed_chord.append(c)
          else:
            fixed_chord.append(c)

        if return_sorted:
          fixed_chord.sort(key = lambda x: x[4], reverse=True)
      
        return fixed_chord 

    else:
      chord.sort(key = lambda x: x[4], reverse=True)
      return chord

def adjust_score_velocities(score,
                            max_velocity,
                            adj_per_channel=False,
                            adj_in_place=True
                           ):
  
    if adj_in_place:
        buf = score
        
    else:
        buf = copy.deepcopy(score)

    notes = [evt for evt in buf if evt[0] == 'note']
    
    if not notes:
        return buf

    if adj_per_channel:
        channel_max = {}
        
        for _, _, _, ch, _, vel, _ in notes:
            channel_max[ch] = max(channel_max.get(ch, 0), vel)

        channel_factor = {
            ch: (max_velocity / vmax if vmax > 0 else 1.0)
            for ch, vmax in channel_max.items()
        }

        for evt in buf:
            if evt[0] == 'note':
                ch = evt[3]
                factor = channel_factor.get(ch, 1.0)
                new_vel = int(evt[5] * factor)
                evt[5] = max(1, min(127, new_vel))

    else:
        global_max = max(vel for _, _, _, _, _, vel, _ in notes)
        factor = max_velocity / global_max if global_max > 0 else 1.0

        for evt in buf:
            if evt[0] == 'note':
                new_vel = int(evt[5] * factor)
                evt[5] = max(1, min(127, new_vel))

    if not adj_in_place:
        return buf

def chordify_score(score,
                  return_choridfied_score=True,
                  return_detected_score_information=False
                  ):

    if score:
    
      num_tracks = 1
      single_track_score = []
      score_num_ticks = 0

      if type(score[0]) == int and len(score) > 1:

        score_type = 'MIDI_PY'
        score_num_ticks = score[0]

        while num_tracks < len(score):
            for event in score[num_tracks]:
              single_track_score.append(event)
            num_tracks += 1
      
      else:
        score_type = 'CUSTOM'
        single_track_score = score

      if single_track_score and single_track_score[0]:
        
        try:

          if type(single_track_score[0][0]) == str or single_track_score[0][0] == 'note':
            single_track_score.sort(key = lambda x: x[1])
            score_timings = [s[1] for s in single_track_score]
          else:
            score_timings = [s[0] for s in single_track_score]

          is_score_time_absolute = lambda sct: all(x <= y for x, y in zip(sct, sct[1:]))

          score_timings_type = ''

          if is_score_time_absolute(score_timings):
            score_timings_type = 'ABS'

            chords = []
            cho = []

            if score_type == 'MIDI_PY':
              pe = single_track_score[0]
            else:
              pe = single_track_score[0]

            for e in single_track_score:
              
              if score_type == 'MIDI_PY':
                time = e[1]
                ptime = pe[1]
              else:
                time = e[0]
                ptime = pe[0]

              if time == ptime:
                cho.append(e)
              
              else:
                if len(cho) > 0:
                  chords.append(cho)
                cho = []
                cho.append(e)

              pe = e

            if len(cho) > 0:
              chords.append(cho)

          else:
            score_timings_type = 'REL'
            
            chords = []
            cho = []

            for e in single_track_score:
              
              if score_type == 'MIDI_PY':
                time = e[1]
              else:
                time = e[0]

              if time == 0:
                cho.append(e)
              
              else:
                if len(cho) > 0:
                  chords.append(cho)
                cho = []
                cho.append(e)

            if len(cho) > 0:
              chords.append(cho)

          requested_data = []

          if return_detected_score_information:
            
            detected_score_information = []

            detected_score_information.append(['Score type', score_type])
            detected_score_information.append(['Score timings type', score_timings_type])
            detected_score_information.append(['Score tpq', score_num_ticks])
            detected_score_information.append(['Score number of tracks', num_tracks])
            
            requested_data.append(detected_score_information)

          if return_choridfied_score and return_detected_score_information:
            requested_data.append(chords)

          if return_choridfied_score and not return_detected_score_information:
            requested_data.extend(chords)

          return requested_data

        except Exception as e:
          print('Error!')
          print('Check score for consistency and compatibility!')
          print('Exception detected:', e)

      else:
        return None

    else:
      return None

def fix_monophonic_score_durations(monophonic_score,
                                   min_notes_gap=1,
                                   min_notes_dur=1
                                   ):
  
    fixed_score = []

    if monophonic_score[0][0] == 'note':

      for i in range(len(monophonic_score)-1):
        note = monophonic_score[i]

        nmt = monophonic_score[i+1][1]

        if note[1]+note[2] >= nmt:
          note_dur = max(1, nmt-note[1]-min_notes_gap)
        else:
          note_dur = note[2]

        new_note = [note[0], note[1], note_dur] + note[3:]
        
        if new_note[2] >= min_notes_dur:
            fixed_score.append(new_note)
      
      if monophonic_score[-1][2] >= min_notes_dur:
          fixed_score.append(monophonic_score[-1])

    elif type(monophonic_score[0][0]) == int:

      for i in range(len(monophonic_score)-1):
        note = monophonic_score[i]

        nmt = monophonic_score[i+1][0]

        if note[0]+note[1] >= nmt:
          note_dur = max(1, nmt-note[0]-min_notes_gap)
        else:
          note_dur = note[1]
          
        new_note = [note[0], note_dur] + note[2:]
        
        if new_note[1] >= min_notes_dur:
            fixed_score.append(new_note)
      
      if monophonic_score[-1][1] >= min_notes_dur:
          fixed_score.append(monophonic_score[-1]) 

    return fixed_score

###################################################################################


ALL_CHORDS = [[0], [7], [5], [9], [2], [4], [11], [10], [8], [6], [3], [1], [0, 9], [2, 5],
              [4, 7], [7, 10], [2, 11], [0, 3], [6, 9], [1, 4], [8, 11], [5, 8], [1, 10],
              [3, 6], [0, 4], [5, 9], [7, 11], [0, 7], [0, 5], [2, 10], [2, 7], [2, 9],
              [2, 6], [4, 11], [4, 9], [3, 7], [5, 10], [1, 9], [0, 8], [6, 11], [3, 11],
              [4, 8], [3, 10], [3, 8], [1, 5], [1, 8], [1, 6], [6, 10], [3, 9], [4, 10],
              [1, 7], [0, 6], [2, 8], [5, 11], [5, 7], [0, 10], [0, 2], [9, 11], [7, 9],
              [2, 4], [4, 6], [3, 5], [8, 10], [6, 8], [1, 3], [1, 11], [2, 7, 11],
              [0, 4, 7], [0, 5, 9], [2, 6, 9], [2, 5, 10], [1, 4, 9], [4, 8, 11], [3, 7, 10],
              [0, 3, 8], [3, 6, 11], [1, 5, 8], [1, 6, 10], [0, 4, 9], [2, 5, 9], [4, 7, 11],
              [2, 7, 10], [2, 6, 11], [0, 3, 7], [0, 5, 8], [1, 4, 8], [1, 6, 9], [3, 8, 11],
              [1, 5, 10], [3, 6, 10], [2, 5, 11], [4, 7, 10], [3, 6, 9], [0, 6, 9],
              [0, 3, 9], [2, 8, 11], [2, 5, 8], [1, 7, 10], [1, 4, 7], [0, 3, 6], [1, 4, 10],
              [5, 8, 11], [2, 5, 7], [0, 7, 10], [0, 2, 9], [0, 3, 5], [6, 9, 11], [4, 7, 9],
              [2, 4, 11], [5, 8, 10], [1, 3, 10], [1, 4, 6], [3, 6, 8], [1, 8, 11],
              [5, 7, 11], [0, 4, 10], [3, 5, 9], [0, 2, 6], [1, 7, 9], [0, 7, 9], [5, 7, 10],
              [2, 8, 10], [3, 9, 11], [0, 2, 5], [2, 4, 8], [2, 4, 7], [0, 2, 7], [2, 7, 9],
              [4, 9, 11], [4, 6, 9], [1, 3, 7], [2, 4, 9], [0, 5, 7], [0, 3, 10], [2, 9, 11],
              [0, 5, 10], [0, 6, 8], [4, 6, 10], [4, 6, 11], [1, 4, 11], [6, 8, 11],
              [1, 5, 11], [1, 6, 11], [1, 8, 10], [1, 6, 8], [3, 5, 8], [3, 8, 10],
              [1, 3, 8], [3, 5, 10], [1, 3, 6], [2, 5, 7, 10], [0, 3, 7, 10], [1, 4, 8, 11],
              [2, 4, 7, 11], [0, 4, 7, 9], [0, 2, 5, 9], [2, 6, 9, 11], [1, 5, 8, 10],
              [0, 3, 5, 8], [3, 6, 8, 11], [1, 3, 6, 10], [1, 4, 6, 9], [1, 5, 9], [0, 4, 8],
              [2, 6, 10], [3, 7, 11], [0, 3, 6, 9], [2, 5, 8, 11], [1, 4, 7, 10],
              [2, 5, 7, 11], [0, 2, 6, 9], [0, 4, 7, 10], [2, 4, 8, 11], [0, 3, 5, 9],
              [1, 4, 7, 9], [3, 6, 9, 11], [2, 5, 8, 10], [1, 4, 6, 10], [0, 3, 6, 8],
              [1, 3, 7, 10], [1, 5, 8, 11], [2, 4, 10], [5, 9, 11], [1, 5, 7], [0, 2, 8],
              [0, 4, 6], [1, 7, 11], [3, 7, 9], [1, 3, 9], [7, 9, 11], [5, 7, 9], [0, 6, 10],
              [0, 2, 10], [2, 6, 8], [0, 2, 4], [4, 8, 10], [1, 9, 11], [2, 4, 6],
              [3, 5, 11], [3, 5, 7], [0, 8, 10], [4, 6, 8], [1, 3, 11], [6, 8, 10],
              [1, 3, 5], [0, 2, 5, 10], [0, 5, 7, 9], [0, 3, 8, 10], [0, 2, 4, 7],
              [4, 6, 8, 11], [3, 5, 7, 10], [2, 7, 9, 11], [2, 4, 6, 9], [1, 6, 8, 10],
              [1, 4, 9, 11], [1, 3, 5, 8], [1, 3, 6, 11], [2, 5, 9, 11], [2, 4, 7, 10],
              [0, 2, 5, 8], [1, 5, 7, 10], [0, 4, 6, 9], [1, 3, 6, 9], [0, 3, 6, 10],
              [2, 6, 8, 11], [0, 2, 7, 9], [1, 4, 8, 10], [0, 3, 7, 9], [3, 5, 8, 11],
              [0, 5, 7, 10], [0, 2, 5, 7], [1, 4, 7, 11], [2, 4, 7, 9], [0, 3, 5, 10],
              [4, 6, 9, 11], [1, 4, 6, 11], [2, 4, 9, 11], [1, 6, 8, 11], [1, 3, 6, 8],
              [1, 3, 8, 10], [3, 5, 8, 10], [4, 7, 9, 11], [0, 2, 7, 10], [2, 5, 7, 9],
              [0, 2, 4, 9], [1, 6, 9, 11], [2, 4, 6, 11], [0, 3, 5, 7], [0, 5, 8, 10],
              [1, 4, 6, 8], [1, 3, 5, 10], [1, 3, 8, 11], [3, 6, 8, 10], [0, 2, 5, 7, 10],
              [0, 2, 4, 7, 9], [0, 2, 5, 7, 9], [1, 3, 7, 9], [1, 4, 6, 9, 11],
              [1, 3, 6, 8, 11], [3, 5, 9, 11], [1, 3, 6, 8, 10], [1, 4, 6, 8, 11],
              [1, 3, 5, 8, 10], [2, 4, 6, 9, 11], [2, 4, 8, 10], [2, 4, 7, 9, 11],
              [0, 3, 5, 7, 10], [1, 5, 7, 11], [0, 2, 6, 8], [0, 3, 5, 8, 10], [0, 4, 6, 10],
              [1, 3, 5, 9], [1, 5, 7, 9], [2, 6, 8, 10], [3, 7, 9, 11], [0, 2, 4, 8],
              [0, 4, 6, 8], [0, 4, 8, 10], [2, 4, 6, 10], [1, 3, 7, 11], [0, 2, 6, 10],
              [1, 5, 9, 11], [3, 5, 7, 11], [1, 7, 9, 11], [0, 2, 4, 6], [1, 3, 9, 11],
              [0, 2, 4, 10], [5, 7, 9, 11], [2, 4, 6, 8], [0, 2, 8, 10], [3, 5, 7, 9],
              [1, 3, 5, 7], [4, 6, 8, 10], [0, 6, 8, 10], [1, 3, 5, 11], [0, 3, 6, 8, 10],
              [0, 2, 4, 6, 9], [1, 4, 7, 9, 11], [2, 4, 6, 8, 11], [1, 3, 6, 9, 11],
              [1, 3, 5, 8, 11], [0, 2, 5, 8, 10], [1, 4, 6, 8, 10], [0, 3, 5, 7, 9],
              [2, 5, 7, 9, 11], [1, 3, 5, 7, 10], [0, 2, 4, 7, 10], [1, 3, 5, 7, 9],
              [1, 3, 5, 9, 11], [1, 5, 7, 9, 11], [1, 3, 7, 9, 11], [3, 5, 7, 9, 11],
              [2, 4, 6, 8, 10], [0, 4, 6, 8, 10], [0, 2, 6, 8, 10], [1, 3, 5, 7, 11],
              [0, 2, 4, 8, 10], [0, 2, 4, 6, 8], [0, 2, 4, 6, 10], [0, 2, 4, 6, 8, 10],
              [1, 3, 5, 7, 9, 11]]

def find_exact_match_variable_length(list_of_lists, target_list, uncertain_indices):
    # Infer possible values for each uncertain index
    possible_values = {idx: set() for idx in uncertain_indices}
    for sublist in list_of_lists:
        for idx in uncertain_indices:
            if idx < len(sublist):
                possible_values[idx].add(sublist[idx])
    
    # Generate all possible combinations for the uncertain elements
    uncertain_combinations = product(*(possible_values[idx] for idx in uncertain_indices))
    
    for combination in uncertain_combinations:
        # Create a copy of the target list and update the uncertain elements
        test_list = target_list[:]
        for idx, value in zip(uncertain_indices, combination):
            test_list[idx] = value
        
        # Check if the modified target list is an exact match in the list of lists
        # Only consider sublists that are at least as long as the target list
        for sublist in list_of_lists:
            if len(sublist) >= len(test_list) and sublist[:len(test_list)] == test_list:
                return sublist  # Return the matching sublist
    
    return None  # No exact match found


def advanced_validate_chord_pitches(chord, channel_to_check = 0, return_sorted = True):

    pitches_chord = sorted(list(set([x[4] for x in chord if 0 < x[4] < 128 and x[3] == channel_to_check])))

    if pitches_chord:

      tones_chord = sorted(list(set([c % 12 for c in sorted(list(set(pitches_chord)))])))

      if not bad_chord(tones_chord):
        if return_sorted:
          chord.sort(key = lambda x: x[4], reverse=True)
        return chord

      else:
        bad_chord_indices = list(set([i for s in [[tones_chord.index(a), tones_chord.index(b)] for a, b in zip(tones_chord, tones_chord[1:]) if b-a == 1] for i in s]))
        
        good_tones_chord = find_exact_match_variable_length(ALL_CHORDS, tones_chord, bad_chord_indices)
        
        if good_tones_chord is not None:
        
          fixed_chord = []

          for c in chord:
            if c[3] == channel_to_check:
              if (c[4] % 12) in good_tones_chord:
                fixed_chord.append(c)
            else:
              fixed_chord.append(c)

          if return_sorted:
            fixed_chord.sort(key = lambda x: x[4], reverse=True)

        else:

          if 0 in tones_chord and 11 in tones_chord:
            tones_chord.remove(0)

          fixed_tones = [[a, b] for a, b in zip(tones_chord, tones_chord[1:]) if b-a != 1]

          fixed_tones_chord = []
          for f in fixed_tones:
            fixed_tones_chord.extend(f)
          fixed_tones_chord = list(set(fixed_tones_chord))
          
          fixed_chord = []

          for c in chord:
            if c[3] == channel_to_check:
              if (c[4] % 12) in fixed_tones_chord:
                fixed_chord.append(c)
            else:
              fixed_chord.append(c)

          if return_sorted:
            fixed_chord.sort(key = lambda x: x[4], reverse=True)     
      
      return fixed_chord 

    else:
      chord.sort(key = lambda x: x[4], reverse=True)
      return chord

###################################################################################

def analyze_score_pitches(score, channels_to_analyze=[0]):

  analysis = {}

  score_notes = [s for s in score if s[3] in channels_to_analyze]

  cscore = chordify_score(score_notes)

  chords_tones = []

  all_tones = []

  all_chords_good = True

  bad_chords = []

  for c in cscore:
    tones = sorted(list(set([t[4] % 12 for t in c])))
    chords_tones.append(tones)
    all_tones.extend(tones)

    if tones not in ALL_CHORDS:
      all_chords_good = False
      bad_chords.append(tones)

  analysis['Number of notes'] = len(score_notes)
  analysis['Number of chords'] = len(cscore)
  analysis['Score tones'] = sorted(list(set(all_tones)))
  analysis['Shortest chord'] = sorted(min(chords_tones, key=len))
  analysis['Longest chord'] = sorted(max(chords_tones, key=len))
  analysis['All chords good'] = all_chords_good
  analysis['Bad chords'] = bad_chords

  return analysis

###################################################################################

ALL_CHORDS_GROUPED = [[[0], [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11]],
                      [[0, 2], [0, 3], [0, 4], [0, 5], [0, 6], [0, 7], [0, 8], [0, 9], [0, 10],
                        [1, 3], [1, 4], [1, 5], [1, 6], [1, 7], [1, 8], [1, 9], [1, 10], [1, 11],
                        [2, 4], [2, 5], [2, 6], [2, 7], [2, 8], [2, 9], [2, 10], [2, 11], [3, 5],
                        [3, 6], [3, 7], [3, 8], [3, 9], [3, 10], [3, 11], [4, 6], [4, 7], [4, 8],
                        [4, 9], [4, 10], [4, 11], [5, 7], [5, 8], [5, 9], [5, 10], [5, 11], [6, 8],
                        [6, 9], [6, 10], [6, 11], [7, 9], [7, 10], [7, 11], [8, 10], [8, 11],
                        [9, 11]],
                      [[0, 2, 4], [0, 2, 5], [0, 3, 5], [0, 2, 6], [0, 3, 6], [0, 4, 6], [0, 2, 7],
                        [0, 3, 7], [0, 4, 7], [0, 5, 7], [0, 2, 8], [0, 3, 8], [0, 4, 8], [0, 5, 8],
                        [0, 6, 8], [0, 2, 9], [0, 3, 9], [0, 4, 9], [0, 5, 9], [0, 6, 9], [0, 7, 9],
                        [0, 2, 10], [0, 3, 10], [0, 4, 10], [0, 5, 10], [0, 6, 10], [0, 7, 10],
                        [0, 8, 10], [1, 3, 5], [1, 3, 6], [1, 4, 6], [1, 3, 7], [1, 4, 7], [1, 5, 7],
                        [1, 3, 8], [1, 4, 8], [1, 5, 8], [1, 6, 8], [1, 3, 9], [1, 4, 9], [1, 5, 9],
                        [1, 6, 9], [1, 7, 9], [1, 3, 10], [1, 4, 10], [1, 5, 10], [1, 6, 10],
                        [1, 7, 10], [1, 8, 10], [1, 3, 11], [1, 4, 11], [1, 5, 11], [1, 6, 11],
                        [1, 7, 11], [1, 8, 11], [1, 9, 11], [2, 4, 6], [2, 4, 7], [2, 5, 7],
                        [2, 4, 8], [2, 5, 8], [2, 6, 8], [2, 4, 9], [2, 5, 9], [2, 6, 9], [2, 7, 9],
                        [2, 4, 10], [2, 5, 10], [2, 6, 10], [2, 7, 10], [2, 8, 10], [2, 4, 11],
                        [2, 5, 11], [2, 6, 11], [2, 7, 11], [2, 8, 11], [2, 9, 11], [3, 5, 7],
                        [3, 5, 8], [3, 6, 8], [3, 5, 9], [3, 6, 9], [3, 7, 9], [3, 5, 10], [3, 6, 10],
                        [3, 7, 10], [3, 8, 10], [3, 5, 11], [3, 6, 11], [3, 7, 11], [3, 8, 11],
                        [3, 9, 11], [4, 6, 8], [4, 6, 9], [4, 7, 9], [4, 6, 10], [4, 7, 10],
                        [4, 8, 10], [4, 6, 11], [4, 7, 11], [4, 8, 11], [4, 9, 11], [5, 7, 9],
                        [5, 7, 10], [5, 8, 10], [5, 7, 11], [5, 8, 11], [5, 9, 11], [6, 8, 10],
                        [6, 8, 11], [6, 9, 11], [7, 9, 11]],
                      [[0, 2, 4, 6], [0, 2, 4, 7], [0, 2, 5, 7], [0, 3, 5, 7], [0, 2, 4, 8],
                        [0, 2, 5, 8], [0, 2, 6, 8], [0, 3, 5, 8], [0, 3, 6, 8], [0, 4, 6, 8],
                        [0, 2, 4, 9], [0, 2, 5, 9], [0, 2, 6, 9], [0, 2, 7, 9], [0, 3, 5, 9],
                        [0, 3, 6, 9], [0, 3, 7, 9], [0, 4, 6, 9], [0, 4, 7, 9], [0, 5, 7, 9],
                        [0, 2, 4, 10], [0, 2, 5, 10], [0, 2, 6, 10], [0, 2, 7, 10], [0, 2, 8, 10],
                        [0, 3, 5, 10], [0, 3, 6, 10], [0, 3, 7, 10], [0, 3, 8, 10], [0, 4, 6, 10],
                        [0, 4, 7, 10], [0, 4, 8, 10], [0, 5, 7, 10], [0, 5, 8, 10], [0, 6, 8, 10],
                        [1, 3, 5, 7], [1, 3, 5, 8], [1, 3, 6, 8], [1, 4, 6, 8], [1, 3, 5, 9],
                        [1, 3, 6, 9], [1, 3, 7, 9], [1, 4, 6, 9], [1, 4, 7, 9], [1, 5, 7, 9],
                        [1, 3, 5, 10], [1, 3, 6, 10], [1, 3, 7, 10], [1, 3, 8, 10], [1, 4, 6, 10],
                        [1, 4, 7, 10], [1, 4, 8, 10], [1, 5, 7, 10], [1, 5, 8, 10], [1, 6, 8, 10],
                        [1, 3, 5, 11], [1, 3, 6, 11], [1, 3, 7, 11], [1, 3, 8, 11], [1, 3, 9, 11],
                        [1, 4, 6, 11], [1, 4, 7, 11], [1, 4, 8, 11], [1, 4, 9, 11], [1, 5, 7, 11],
                        [1, 5, 8, 11], [1, 5, 9, 11], [1, 6, 8, 11], [1, 6, 9, 11], [1, 7, 9, 11],
                        [2, 4, 6, 8], [2, 4, 6, 9], [2, 4, 7, 9], [2, 5, 7, 9], [2, 4, 6, 10],
                        [2, 4, 7, 10], [2, 4, 8, 10], [2, 5, 7, 10], [2, 5, 8, 10], [2, 6, 8, 10],
                        [2, 4, 6, 11], [2, 4, 7, 11], [2, 4, 8, 11], [2, 4, 9, 11], [2, 5, 7, 11],
                        [2, 5, 8, 11], [2, 5, 9, 11], [2, 6, 8, 11], [2, 6, 9, 11], [2, 7, 9, 11],
                        [3, 5, 7, 9], [3, 5, 7, 10], [3, 5, 8, 10], [3, 6, 8, 10], [3, 5, 7, 11],
                        [3, 5, 8, 11], [3, 5, 9, 11], [3, 6, 8, 11], [3, 6, 9, 11], [3, 7, 9, 11],
                        [4, 6, 8, 10], [4, 6, 8, 11], [4, 6, 9, 11], [4, 7, 9, 11], [5, 7, 9, 11]],
                      [[0, 2, 4, 6, 8], [0, 2, 4, 6, 9], [0, 2, 4, 7, 9], [0, 2, 5, 7, 9],
                        [0, 3, 5, 7, 9], [0, 2, 4, 6, 10], [0, 2, 4, 7, 10], [0, 2, 4, 8, 10],
                        [0, 2, 5, 7, 10], [0, 2, 5, 8, 10], [0, 2, 6, 8, 10], [0, 3, 5, 7, 10],
                        [0, 3, 5, 8, 10], [0, 3, 6, 8, 10], [0, 4, 6, 8, 10], [1, 3, 5, 7, 9],
                        [1, 3, 5, 7, 10], [1, 3, 5, 8, 10], [1, 3, 6, 8, 10], [1, 4, 6, 8, 10],
                        [1, 3, 5, 7, 11], [1, 3, 5, 8, 11], [1, 3, 5, 9, 11], [1, 3, 6, 8, 11],
                        [1, 3, 6, 9, 11], [1, 3, 7, 9, 11], [1, 4, 6, 8, 11], [1, 4, 6, 9, 11],
                        [1, 4, 7, 9, 11], [1, 5, 7, 9, 11], [2, 4, 6, 8, 10], [2, 4, 6, 8, 11],
                        [2, 4, 6, 9, 11], [2, 4, 7, 9, 11], [2, 5, 7, 9, 11], [3, 5, 7, 9, 11]],
                      [[0, 2, 4, 6, 8, 10], [1, 3, 5, 7, 9, 11]]]

def group_sublists_by_length(lst):
    unique_lengths = sorted(list(set(map(len, lst))), reverse=True)
    return [[x for x in lst if len(x) == i] for i in unique_lengths]

def pitches_to_tones_chord(pitches):
  return sorted(set([p % 12 for p in pitches]))

def tones_chord_to_pitches(tones_chord, base_pitch=60):
  return [t+base_pitch for t in tones_chord if 0 <= t < 12]

###################################################################################

def advanced_score_processor(raw_score, 
                             patches_to_analyze=list(range(129)), 
                             return_score_analysis=False,
                             return_enhanced_score=False,
                             return_enhanced_score_notes=False,
                             return_enhanced_monophonic_melody=False,
                             return_chordified_enhanced_score=False,
                             return_chordified_enhanced_score_with_lyrics=False,
                             return_score_tones_chords=False,
                             return_text_and_lyric_events=False,
                             apply_sustain=False  
                            ):

  '''TMIDIX Advanced Score Processor'''

  # Score data types detection

  if raw_score and type(raw_score) == list:

      num_ticks = 0
      num_tracks = 1

      basic_single_track_score = []

      if type(raw_score[0]) != int:
        if len(raw_score[0]) < 5 and type(raw_score[0][0]) != str:
          return ['Check score for errors and compatibility!']

        else:
          basic_single_track_score = copy.deepcopy(raw_score)
      
      else:
        num_ticks = raw_score[0]
        while num_tracks < len(raw_score):
            for event in raw_score[num_tracks]:
              ev = copy.deepcopy(event)
              basic_single_track_score.append(ev)
            num_tracks += 1

      for e in basic_single_track_score:

          if e[0] == 'note':
              e[3] = e[3] % 16
              e[4] = e[4] % 128
              e[5] = e[5] % 128

          if e[0] == 'patch_change':
              e[2] = e[2] % 16
              e[3] = e[3] % 128

      if apply_sustain:
          apply_sustain_to_ms_score([1000, basic_single_track_score])
          
      basic_single_track_score.sort(key=lambda x: x[4] if x[0] == 'note' else 128, reverse=True)
      basic_single_track_score.sort(key=lambda x: x[1])

      enhanced_single_track_score = []
      patches = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
      all_score_patches = []
      num_patch_changes = 0

      for event in basic_single_track_score:
        if event[0] == 'patch_change':
              patches[event[2]] = event[3]
              enhanced_single_track_score.append(event)
              num_patch_changes += 1

        if event[0] == 'note':            
            if event[3] != 9:
              event.extend([patches[event[3]]])
              all_score_patches.extend([patches[event[3]]])
            else:
              event.extend([128])
              all_score_patches.extend([128])

            if enhanced_single_track_score:
                if (event[1] == enhanced_single_track_score[-1][1]):
                    if ([event[3], event[4]] != enhanced_single_track_score[-1][3:5]):
                        enhanced_single_track_score.append(event)
                else:
                    enhanced_single_track_score.append(event)

            else:
                enhanced_single_track_score.append(event)

        if event[0] not in ['note', 'patch_change']:
          enhanced_single_track_score.append(event)

      enhanced_single_track_score.sort(key=lambda x: x[6] if x[0] == 'note' else -1)
      enhanced_single_track_score.sort(key=lambda x: x[4] if x[0] == 'note' else 128, reverse=True)
      enhanced_single_track_score.sort(key=lambda x: x[1])

      # Analysis and chordification

      cscore = []
      cescore = []
      chords_tones = []
      tones_chords = []
      all_tones = []
      all_chords_good = True
      bad_chords = []
      bad_chords_count = 0
      score_notes = []
      score_pitches = []
      score_patches = []
      num_text_events = 0
      num_lyric_events = 0
      num_other_events = 0
      text_and_lyric_events = []
      text_and_lyric_events_latin = None

      analysis = {}

      score_notes = [s for s in enhanced_single_track_score if s[0] == 'note' and s[6] in patches_to_analyze]
      score_patches = [sn[6] for sn in score_notes]

      if return_text_and_lyric_events:
        text_and_lyric_events = [e for e in enhanced_single_track_score if e[0] in ['text_event', 'lyric']]
        
        if text_and_lyric_events:
          text_and_lyric_events_latin = True
          for e in text_and_lyric_events:
            try:
              tle = str(e[2].decode())
            except:
              tle = str(e[2])

            for c in tle:
              if not 0 <= ord(c) < 128:
                text_and_lyric_events_latin = False

      if (return_chordified_enhanced_score or return_score_analysis) and any(elem in patches_to_analyze for elem in score_patches):

        cescore = chordify_score([num_ticks, enhanced_single_track_score])

        if return_score_analysis:

          cscore = chordify_score(score_notes)
          
          score_pitches = [sn[4] for sn in score_notes]
          
          text_events = [e for e in enhanced_single_track_score if e[0] == 'text_event']
          num_text_events = len(text_events)

          lyric_events = [e for e in enhanced_single_track_score if e[0] == 'lyric']
          num_lyric_events = len(lyric_events)

          other_events = [e for e in enhanced_single_track_score if e[0] not in ['note', 'patch_change', 'text_event', 'lyric']]
          num_other_events = len(other_events)
          
          for c in cscore:
            tones = sorted(set([t[4] % 12 for t in c if t[3] != 9]))

            if tones:
              chords_tones.append(tones)
              all_tones.extend(tones)

              if tones not in ALL_CHORDS:
                all_chords_good = False
                bad_chords.append(tones)
                bad_chords_count += 1
          
          analysis['Number of ticks per quarter note'] = num_ticks
          analysis['Number of tracks'] = num_tracks
          analysis['Number of all events'] = len(enhanced_single_track_score)
          analysis['Number of patch change events'] = num_patch_changes
          analysis['Number of text events'] = num_text_events
          analysis['Number of lyric events'] = num_lyric_events
          analysis['All text and lyric events Latin'] = text_and_lyric_events_latin
          analysis['Number of other events'] = num_other_events
          analysis['Number of score notes'] = len(score_notes)
          analysis['Number of score chords'] = len(cscore)
          analysis['Score patches'] = sorted(set(score_patches))
          analysis['Score pitches'] = sorted(set(score_pitches))
          analysis['Score tones'] = sorted(set(all_tones))
          if chords_tones:
            analysis['Shortest chord'] = sorted(min(chords_tones, key=len))
            analysis['Longest chord'] = sorted(max(chords_tones, key=len))
          analysis['All chords good'] = all_chords_good
          analysis['Number of bad chords'] = bad_chords_count
          analysis['Bad chords'] = sorted([list(c) for c in set(tuple(bc) for bc in bad_chords)])

      else:
        analysis['Error'] = 'Provided score does not have specified patches to analyse'
        analysis['Provided patches to analyse'] = sorted(patches_to_analyze)
        analysis['Patches present in the score'] = sorted(set(all_score_patches))

      if return_enhanced_monophonic_melody:

        score_notes_copy = copy.deepcopy(score_notes)
        chordified_score_notes = chordify_score(score_notes_copy)

        melody = [c[0] for c in chordified_score_notes]

        fixed_melody = []

        for i in range(len(melody)-1):
          note = melody[i]
          nmt = melody[i+1][1]

          if note[1]+note[2] >= nmt:
            note_dur = nmt-note[1]-1
          else:
            note_dur = note[2]

          melody[i][2] = note_dur

          fixed_melody.append(melody[i])
        fixed_melody.append(melody[-1])

      if return_score_tones_chords:
        cscore = chordify_score(score_notes)
        for c in cscore:
          tones_chord = sorted(set([t[4] % 12 for t in c if t[3] != 9]))
          if tones_chord:
            tones_chords.append(tones_chord)

      if return_chordified_enhanced_score_with_lyrics:
        score_with_lyrics = [e for e in enhanced_single_track_score if e[0] in ['note', 'text_event', 'lyric']]
        chordified_enhanced_score_with_lyrics = chordify_score(score_with_lyrics)
      
      # Returned data

      requested_data = []

      if return_score_analysis and analysis:
        requested_data.append([[k, v] for k, v in analysis.items()])

      if return_enhanced_score and enhanced_single_track_score:
        requested_data.append([num_ticks, enhanced_single_track_score])

      if return_enhanced_score_notes and score_notes:
        requested_data.append(score_notes)

      if return_enhanced_monophonic_melody and fixed_melody:
        requested_data.append(fixed_melody)
        
      if return_chordified_enhanced_score and cescore:
        requested_data.append(cescore)

      if return_chordified_enhanced_score_with_lyrics and chordified_enhanced_score_with_lyrics:
        requested_data.append(chordified_enhanced_score_with_lyrics)

      if return_score_tones_chords and tones_chords:
        requested_data.append(tones_chords)

      if return_text_and_lyric_events and text_and_lyric_events:
        requested_data.append(text_and_lyric_events)

      return requested_data
  
  else:
    return ['Check score for errors and compatibility!']

###################################################################################

def replace_bad_tones_chord(bad_tones_chord):
  bad_chord_p = [0] * 12
  for b in bad_tones_chord:
    bad_chord_p[b] = 1

  match_ratios = []
  good_chords = []
  for c in ALL_CHORDS:
    good_chord_p = [0] * 12
    for cc in c:
      good_chord_p[cc] = 1

    good_chords.append(good_chord_p)
    match_ratios.append(sum(i == j for i, j in zip(good_chord_p, bad_chord_p)) / len(good_chord_p))

  best_good_chord = good_chords[match_ratios.index(max(match_ratios))]

  replaced_chord = []
  for i in range(len(best_good_chord)):
    if best_good_chord[i] == 1:
     replaced_chord.append(i)

  return [replaced_chord, max(match_ratios)]

###################################################################################

def check_and_fix_chord(chord, 
                        channel_index=3,
                        pitch_index=4
                        ):

    tones_chord = sorted(set([t[pitch_index] % 12 for t in chord if t[channel_index] != 9]))

    notes_events = [t for t in chord if t[channel_index] != 9]
    notes_events.sort(key=lambda x: x[pitch_index], reverse=True)

    drums_events = [t for t in chord if t[channel_index] == 9]

    checked_and_fixed_chord = []

    if tones_chord:
        
        new_tones_chord = advanced_check_and_fix_tones_chord(tones_chord, high_pitch=notes_events[0][pitch_index])

        if new_tones_chord != tones_chord:

          if len(notes_events) > 1:
              checked_and_fixed_chord.extend([notes_events[0]])
              for cc in notes_events[1:]:
                  if cc[channel_index] != 9:
                      if (cc[pitch_index] % 12) in new_tones_chord:
                          checked_and_fixed_chord.extend([cc])
              checked_and_fixed_chord.extend(drums_events)
          else:
              checked_and_fixed_chord.extend([notes_events[0]])
        else:
          checked_and_fixed_chord.extend(chord)
    else:
        checked_and_fixed_chord.extend(chord)

    checked_and_fixed_chord.sort(key=lambda x: x[pitch_index], reverse=True)

    return checked_and_fixed_chord

###################################################################################

def find_similar_tones_chord(tones_chord, 
                             max_match_threshold=1, 
                             randomize_chords_matches=False, 
                             custom_chords_list=[]):
  chord_p = [0] * 12
  for b in tones_chord:
    chord_p[b] = 1

  match_ratios = []
  good_chords = []

  if custom_chords_list:
    CHORDS = copy.deepcopy([list(x) for x in set(tuple(t) for t in custom_chords_list)])
  else:
    CHORDS = copy.deepcopy(ALL_CHORDS)

  if randomize_chords_matches:
    random.shuffle(CHORDS)

  for c in CHORDS:
    good_chord_p = [0] * 12
    for cc in c:
      good_chord_p[cc] = 1

    good_chords.append(good_chord_p)
    match_ratio = sum(i == j for i, j in zip(good_chord_p, chord_p)) / len(good_chord_p)
    if match_ratio < max_match_threshold:
      match_ratios.append(match_ratio)
    else:
      match_ratios.append(0)

  best_good_chord = good_chords[match_ratios.index(max(match_ratios))]

  similar_chord = []
  for i in range(len(best_good_chord)):
    if best_good_chord[i] == 1:
     similar_chord.append(i)

  return [similar_chord, max(match_ratios)]

###################################################################################

def generate_tones_chords_progression(number_of_chords_to_generate=100, 
                                      start_tones_chord=[], 
                                      custom_chords_list=[]):

  if start_tones_chord:
    start_chord = start_tones_chord
  else:
    start_chord = random.choice(ALL_CHORDS)

  chord = []

  chords_progression = [start_chord]

  for i in range(number_of_chords_to_generate):
    if not chord:
      chord = start_chord

    if custom_chords_list:
      chord = find_similar_tones_chord(chord, randomize_chords_matches=True, custom_chords_list=custom_chords_list)[0]
    else:
      chord = find_similar_tones_chord(chord, randomize_chords_matches=True)[0]
    
    chords_progression.append(chord)

  return chords_progression

###################################################################################

def ascii_texts_search(texts = ['text1', 'text2', 'text3'],
                       search_query = 'Once upon a time...',
                       deterministic_matching = False
                       ):

    texts_copy = texts

    if not deterministic_matching:
      texts_copy = copy.deepcopy(texts)
      random.shuffle(texts_copy)

    clean_texts = []

    for t in texts_copy:
      text_words_list = [at.split(chr(32)) for at in t.split(chr(10))]
      
      clean_text_words_list = []
      for twl in text_words_list:
        for w in twl:
          clean_text_words_list.append(''.join(filter(str.isalpha, w.lower())))
          
      clean_texts.append(clean_text_words_list)

    text_search_query = [at.split(chr(32)) for at in search_query.split(chr(10))]
    clean_text_search_query = []
    for w in text_search_query:
      for ww in w:
        clean_text_search_query.append(''.join(filter(str.isalpha, ww.lower())))

    if clean_texts[0] and clean_text_search_query:
      texts_match_ratios = []
      words_match_indexes = []
      for t in clean_texts:
        word_match_count = 0
        wmis = []

        for c in clean_text_search_query:
          if c in t:
            word_match_count += 1
            wmis.append(t.index(c))
          else:
            wmis.append(-1)

        words_match_indexes.append(wmis)
        words_match_indexes_consequtive = all(abs(b) - abs(a) == 1 for a, b in zip(wmis, wmis[1:]))
        words_match_indexes_consequtive_ratio = sum([abs(b) - abs(a) == 1 for a, b in zip(wmis, wmis[1:])]) / len(wmis)

        if words_match_indexes_consequtive:
          texts_match_ratios.append(word_match_count / len(clean_text_search_query))
        else:
          texts_match_ratios.append(((word_match_count / len(clean_text_search_query)) + words_match_indexes_consequtive_ratio) / 2)

      if texts_match_ratios:
        max_text_match_ratio = max(texts_match_ratios)
        max_match_ratio_text = texts_copy[texts_match_ratios.index(max_text_match_ratio)]
        max_text_words_match_indexes = words_match_indexes[texts_match_ratios.index(max_text_match_ratio)]

      return [max_match_ratio_text, max_text_match_ratio, max_text_words_match_indexes]
    
    else:
      return None

###################################################################################

def ascii_text_words_counter(ascii_text):

    text_words_list = [at.split(chr(32)) for at in ascii_text.split(chr(10))]

    clean_text_words_list = []
    for twl in text_words_list:
      for w in twl:
        wo = ''
        for ww in w.lower():
          if 96 < ord(ww) < 123:
            wo += ww
        if wo != '':
          clean_text_words_list.append(wo)

    words = {}
    for i in clean_text_words_list:
        words[i] = words.get(i, 0) + 1

    words_sorted = dict(sorted(words.items(), key=lambda item: item[1], reverse=True))

    return len(clean_text_words_list), words_sorted, clean_text_words_list
    
###################################################################################

def check_and_fix_tones_chord(tones_chord, use_full_chords=True):

  tones_chord_combs = [list(comb) for i in range(len(tones_chord), 0, -1) for comb in combinations(tones_chord, i)]

  if use_full_chords:
    CHORDS = ALL_CHORDS_FULL

  else:
    CHORDS = ALL_CHORDS_SORTED

  for c in tones_chord_combs:
    if c in CHORDS:
      checked_tones_chord = c
      break

  return sorted(checked_tones_chord)

###################################################################################

def find_closest_tone(tones, tone):
  return min(tones, key=lambda x:abs(x-tone))

###################################################################################

def advanced_check_and_fix_tones_chord(tones_chord, high_pitch=0, use_full_chords=True):

  tones_chord_combs = [list(comb) for i in range(len(tones_chord), 0, -1) for comb in combinations(tones_chord, i)]

  if use_full_chords:
    CHORDS = ALL_CHORDS_FULL

  else:
    CHORDS = ALL_CHORDS_SORTED

  for c in tones_chord_combs:
    if c in CHORDS:
      tchord = c

  if 0 < high_pitch < 128 and len(tchord) == 1:
    tchord = [high_pitch % 12]

  return tchord

###################################################################################

def create_similarity_matrix(list_of_values, matrix_length=0):

    counts = Counter(list_of_values).items()

    if matrix_length > 0:
      sim_matrix = [0] * max(matrix_length, len(list_of_values))
    else:
      sim_matrix = [0] * len(counts)

    for c in counts:
      sim_matrix[c[0]] = c[1]

    similarity_matrix = [[0] * len(sim_matrix) for _ in range(len(sim_matrix))]

    for i in range(len(sim_matrix)):
      for j in range(len(sim_matrix)):
        if max(sim_matrix[i], sim_matrix[j]) != 0:
          similarity_matrix[i][j] = min(sim_matrix[i], sim_matrix[j]) / max(sim_matrix[i], sim_matrix[j])

    return similarity_matrix, sim_matrix

###################################################################################

def ceil_with_precision(value, decimal_places):
    factor = 10 ** decimal_places
    return math.ceil(value * factor) / factor

###################################################################################

def augment_enhanced_score_notes(enhanced_score_notes,
                                  timings_divider=16,
                                  full_sorting=True,
                                  timings_shift=0,
                                  pitch_shift=0,
                                  ceil_timings=False,
                                  round_timings=False,
                                  legacy_timings=True,
                                  sort_drums_last=False,
                                  even_timings=False
                                ):

    esn = copy.deepcopy(enhanced_score_notes)

    pe = enhanced_score_notes[0]

    abs_time = max(0, int(enhanced_score_notes[0][1] / timings_divider))

    for i, e in enumerate(esn):
      
      dtime = (e[1] / timings_divider) - (pe[1] / timings_divider)

      if round_timings:
        dtime = round(dtime)
      
      else:
        if ceil_timings:
          dtime = math.ceil(dtime)
        
        else:
          dtime = int(dtime)

      if legacy_timings:
        abs_time = int(e[1] / timings_divider) + timings_shift

      else:
        abs_time += dtime

      e[1] = max(0, abs_time + timings_shift)

      if round_timings:
        e[2] = max(1, round(e[2] / timings_divider)) + timings_shift
      
      else:
        if ceil_timings:
          e[2] = max(1, math.ceil(e[2] / timings_divider)) + timings_shift
        else:
          e[2] = max(1, int(e[2] / timings_divider)) + timings_shift
      
      e[4] = max(1, min(127, e[4] + pitch_shift))

      pe = enhanced_score_notes[i]
      
      
    if even_timings:
        
      for e in esn:
          if e[1] % 2 != 0:
              e[1] += 1
          
          if e[2] % 2 != 0:
              e[2] += 1

    if full_sorting:

      # Sorting by patch, reverse pitch and start-time
      esn.sort(key=lambda x: x[6])
      esn.sort(key=lambda x: x[4], reverse=True)
      esn.sort(key=lambda x: x[1])
      
    if sort_drums_last:
        esn.sort(key=lambda x: (x[1], -x[4], x[6]) if x[6] != 128 else (x[1], x[6], -x[4]))

    return esn

###################################################################################

def stack_list(lst, base=12):
    return sum(j * base**i for i, j in enumerate(lst[::-1]))

def destack_list(num, base=12):
    lst = []
    while num:
        lst.append(num % base)
        num //= base
    return lst[::-1]

###################################################################################

def extract_melody(chordified_enhanced_score, 
                    melody_range=[48, 84], 
                    melody_channel=0,
                    melody_patch=0,
                    melody_velocity=0,
                    stacked_melody=False,
                    stacked_melody_base_pitch=60
                  ):

    if stacked_melody:

      
      all_pitches_chords = []
      for e in chordified_enhanced_score:
        all_pitches_chords.append(sorted(set([p[4] for p in e]), reverse=True))
      
      melody_score = []
      for i, chord in enumerate(chordified_enhanced_score):

        if melody_velocity > 0:
          vel = melody_velocity
        else:
          vel = chord[0][5]

        melody_score.append(['note', chord[0][1], chord[0][2], melody_channel, stacked_melody_base_pitch+(stack_list([p % 12 for p in all_pitches_chords[i]]) % 12), vel, melody_patch])
  
    else:

      melody_score = copy.deepcopy([c[0] for c in chordified_enhanced_score if c[0][3] != 9])
      
      for e in melody_score:
        
          e[3] = melody_channel

          if melody_velocity > 0:
            e[5] = melody_velocity

          e[6] = melody_patch

          if e[4] < melody_range[0]:
              e[4] = (e[4] % 12) + melody_range[0]
              
          if e[4] >= melody_range[1]:
              e[4] = (e[4] % 12) + (melody_range[1]-12)

    return fix_monophonic_score_durations(melody_score)

###################################################################################

def flip_enhanced_score_notes(enhanced_score_notes):

    min_pitch = min([e[4] for e in enhanced_score_notes if e[3] != 9])

    fliped_score_pitches = [127 - e[4]for e in enhanced_score_notes if e[3] != 9]

    delta_min_pitch = min_pitch - min([p for p in fliped_score_pitches])

    output_score = copy.deepcopy(enhanced_score_notes)

    for e in output_score:
        if e[3] != 9:
            e[4] = (127 - e[4]) + delta_min_pitch

    return output_score

###################################################################################

ALL_CHORDS_SORTED = [[0], [0, 2], [0, 3], [0, 4], [0, 2, 4], [0, 5], [0, 2, 5], [0, 3, 5], [0, 6],
                    [0, 2, 6], [0, 3, 6], [0, 4, 6], [0, 2, 4, 6], [0, 7], [0, 2, 7], [0, 3, 7],
                    [0, 4, 7], [0, 5, 7], [0, 2, 4, 7], [0, 2, 5, 7], [0, 3, 5, 7], [0, 8],
                    [0, 2, 8], [0, 3, 8], [0, 4, 8], [0, 5, 8], [0, 6, 8], [0, 2, 4, 8],
                    [0, 2, 5, 8], [0, 2, 6, 8], [0, 3, 5, 8], [0, 3, 6, 8], [0, 4, 6, 8],
                    [0, 2, 4, 6, 8], [0, 9], [0, 2, 9], [0, 3, 9], [0, 4, 9], [0, 5, 9], [0, 6, 9],
                    [0, 7, 9], [0, 2, 4, 9], [0, 2, 5, 9], [0, 2, 6, 9], [0, 2, 7, 9],
                    [0, 3, 5, 9], [0, 3, 6, 9], [0, 3, 7, 9], [0, 4, 6, 9], [0, 4, 7, 9],
                    [0, 5, 7, 9], [0, 2, 4, 6, 9], [0, 2, 4, 7, 9], [0, 2, 5, 7, 9],
                    [0, 3, 5, 7, 9], [0, 10], [0, 2, 10], [0, 3, 10], [0, 4, 10], [0, 5, 10],
                    [0, 6, 10], [0, 7, 10], [0, 8, 10], [0, 2, 4, 10], [0, 2, 5, 10],
                    [0, 2, 6, 10], [0, 2, 7, 10], [0, 2, 8, 10], [0, 3, 5, 10], [0, 3, 6, 10],
                    [0, 3, 7, 10], [0, 3, 8, 10], [0, 4, 6, 10], [0, 4, 7, 10], [0, 4, 8, 10],
                    [0, 5, 7, 10], [0, 5, 8, 10], [0, 6, 8, 10], [0, 2, 4, 6, 10],
                    [0, 2, 4, 7, 10], [0, 2, 4, 8, 10], [0, 2, 5, 7, 10], [0, 2, 5, 8, 10],
                    [0, 2, 6, 8, 10], [0, 3, 5, 7, 10], [0, 3, 5, 8, 10], [0, 3, 6, 8, 10],
                    [0, 4, 6, 8, 10], [0, 2, 4, 6, 8, 10], [1], [1, 3], [1, 4], [1, 5], [1, 3, 5],
                    [1, 6], [1, 3, 6], [1, 4, 6], [1, 7], [1, 3, 7], [1, 4, 7], [1, 5, 7],
                    [1, 3, 5, 7], [1, 8], [1, 3, 8], [1, 4, 8], [1, 5, 8], [1, 6, 8], [1, 3, 5, 8],
                    [1, 3, 6, 8], [1, 4, 6, 8], [1, 9], [1, 3, 9], [1, 4, 9], [1, 5, 9], [1, 6, 9],
                    [1, 7, 9], [1, 3, 5, 9], [1, 3, 6, 9], [1, 3, 7, 9], [1, 4, 6, 9],
                    [1, 4, 7, 9], [1, 5, 7, 9], [1, 3, 5, 7, 9], [1, 10], [1, 3, 10], [1, 4, 10],
                    [1, 5, 10], [1, 6, 10], [1, 7, 10], [1, 8, 10], [1, 3, 5, 10], [1, 3, 6, 10],
                    [1, 3, 7, 10], [1, 3, 8, 10], [1, 4, 6, 10], [1, 4, 7, 10], [1, 4, 8, 10],
                    [1, 5, 7, 10], [1, 5, 8, 10], [1, 6, 8, 10], [1, 3, 5, 7, 10],
                    [1, 3, 5, 8, 10], [1, 3, 6, 8, 10], [1, 4, 6, 8, 10], [1, 11], [1, 3, 11],
                    [1, 4, 11], [1, 5, 11], [1, 6, 11], [1, 7, 11], [1, 8, 11], [1, 9, 11],
                    [1, 3, 5, 11], [1, 3, 6, 11], [1, 3, 7, 11], [1, 3, 8, 11], [1, 3, 9, 11],
                    [1, 4, 6, 11], [1, 4, 7, 11], [1, 4, 8, 11], [1, 4, 9, 11], [1, 5, 7, 11],
                    [1, 5, 8, 11], [1, 5, 9, 11], [1, 6, 8, 11], [1, 6, 9, 11], [1, 7, 9, 11],
                    [1, 3, 5, 7, 11], [1, 3, 5, 8, 11], [1, 3, 5, 9, 11], [1, 3, 6, 8, 11],
                    [1, 3, 6, 9, 11], [1, 3, 7, 9, 11], [1, 4, 6, 8, 11], [1, 4, 6, 9, 11],
                    [1, 4, 7, 9, 11], [1, 5, 7, 9, 11], [1, 3, 5, 7, 9, 11], [2], [2, 4], [2, 5],
                    [2, 6], [2, 4, 6], [2, 7], [2, 4, 7], [2, 5, 7], [2, 8], [2, 4, 8], [2, 5, 8],
                    [2, 6, 8], [2, 4, 6, 8], [2, 9], [2, 4, 9], [2, 5, 9], [2, 6, 9], [2, 7, 9],
                    [2, 4, 6, 9], [2, 4, 7, 9], [2, 5, 7, 9], [2, 10], [2, 4, 10], [2, 5, 10],
                    [2, 6, 10], [2, 7, 10], [2, 8, 10], [2, 4, 6, 10], [2, 4, 7, 10],
                    [2, 4, 8, 10], [2, 5, 7, 10], [2, 5, 8, 10], [2, 6, 8, 10], [2, 4, 6, 8, 10],
                    [2, 11], [2, 4, 11], [2, 5, 11], [2, 6, 11], [2, 7, 11], [2, 8, 11],
                    [2, 9, 11], [2, 4, 6, 11], [2, 4, 7, 11], [2, 4, 8, 11], [2, 4, 9, 11],
                    [2, 5, 7, 11], [2, 5, 8, 11], [2, 5, 9, 11], [2, 6, 8, 11], [2, 6, 9, 11],
                    [2, 7, 9, 11], [2, 4, 6, 8, 11], [2, 4, 6, 9, 11], [2, 4, 7, 9, 11],
                    [2, 5, 7, 9, 11], [3], [3, 5], [3, 6], [3, 7], [3, 5, 7], [3, 8], [3, 5, 8],
                    [3, 6, 8], [3, 9], [3, 5, 9], [3, 6, 9], [3, 7, 9], [3, 5, 7, 9], [3, 10],
                    [3, 5, 10], [3, 6, 10], [3, 7, 10], [3, 8, 10], [3, 5, 7, 10], [3, 5, 8, 10],
                    [3, 6, 8, 10], [3, 11], [3, 5, 11], [3, 6, 11], [3, 7, 11], [3, 8, 11],
                    [3, 9, 11], [3, 5, 7, 11], [3, 5, 8, 11], [3, 5, 9, 11], [3, 6, 8, 11],
                    [3, 6, 9, 11], [3, 7, 9, 11], [3, 5, 7, 9, 11], [4], [4, 6], [4, 7], [4, 8],
                    [4, 6, 8], [4, 9], [4, 6, 9], [4, 7, 9], [4, 10], [4, 6, 10], [4, 7, 10],
                    [4, 8, 10], [4, 6, 8, 10], [4, 11], [4, 6, 11], [4, 7, 11], [4, 8, 11],
                    [4, 9, 11], [4, 6, 8, 11], [4, 6, 9, 11], [4, 7, 9, 11], [5], [5, 7], [5, 8],
                    [5, 9], [5, 7, 9], [5, 10], [5, 7, 10], [5, 8, 10], [5, 11], [5, 7, 11],
                    [5, 8, 11], [5, 9, 11], [5, 7, 9, 11], [6], [6, 8], [6, 9], [6, 10],
                    [6, 8, 10], [6, 11], [6, 8, 11], [6, 9, 11], [7], [7, 9], [7, 10], [7, 11],
                    [7, 9, 11], [8], [8, 10], [8, 11], [9], [9, 11], [10], [11]]

###################################################################################

MIDI_Instruments_Families = {
                            0: 'Piano Family',
                            1: 'Chromatic Percussion Family',
                            2: 'Organ Family',
                            3: 'Guitar Family',
                            4: 'Bass Family',
                            5: 'Strings Family',
                            6: 'Ensemble Family',
                            7: 'Brass Family',
                            8: 'Reed Family',
                            9: 'Pipe Family',
                            10: 'Synth Lead Family',
                            11: 'Synth Pad Family',
                            12: 'Synth Effects Family',
                            13: 'Ethnic Family',
                            14: 'Percussive Family',
                            15: 'Sound Effects Family',
                            16: 'Drums Family',
                            -1: 'Unknown Family',
                            }

###################################################################################

def patch_to_instrument_family(MIDI_patch, drums_patch=128):

  if 0 <= MIDI_patch < 128:
    return MIDI_patch // 8, MIDI_Instruments_Families[MIDI_patch // 8]

  elif MIDI_patch == drums_patch:
    return MIDI_patch // 8, MIDI_Instruments_Families[16]

  else:
    return -1, MIDI_Instruments_Families[-1]

###################################################################################

def patch_list_from_enhanced_score_notes(enhanced_score_notes, 
                                         default_patch=0, 
                                         drums_patch=9,
                                         verbose=False
                                         ):

  patches = [-1] * 16

  for idx, e in enumerate(enhanced_score_notes):
    if e[0] == 'note':
      if e[3] != 9:
          if patches[e[3]] == -1:
              patches[e[3]] = e[6]
          else:
              if patches[e[3]] != e[6]:
                if e[6] in patches:
                  e[3] = patches.index(e[6])
                else:
                  if -1 in patches:
                      patches[patches.index(-1)] = e[6]
                  else:
                    patches[-1] = e[6]

                    if verbose:
                      print('=' * 70)
                      print('WARNING! Composition has more than 15 patches!')
                      print('Conflict note number:', idx)
                      print('Conflict channel number:', e[3])
                      print('Conflict patch number:', e[6])

  patches = [p if p != -1 else default_patch for p in patches]

  patches[9] = drums_patch

  if verbose:
    print('=' * 70)
    print('Composition patches')
    print('=' * 70)
    for c, p in enumerate(patches):
      print('Cha', str(c).zfill(2), '---', str(p).zfill(3), MIDI.Number2patch[p])
    print('=' * 70)

  return patches

###################################################################################

def patch_enhanced_score_notes(escore_notes,
                               default_patch=0,
                               reserved_patch=-1,
                               reserved_patch_channel=-1,
                               drums_patch=9,
                               verbose=False
                              ):
  
    #===========================================================================

    enhanced_score_notes = copy.deepcopy(escore_notes)

    #===========================================================================
  
    enhanced_score_notes_with_patch_changes = []

    patches = [-1] * 16

    if -1 < reserved_patch < 128 and -1 < reserved_patch_channel < 128:
        patches[reserved_patch_channel] = reserved_patch

    overflow_idx = -1

    for idx, e in enumerate(enhanced_score_notes):
        if e[0] == 'note':
            if e[3] != 9:
                if -1 < reserved_patch < 128 and -1 < reserved_patch_channel < 128:
                    if e[6] == reserved_patch:
                        e[3] = reserved_patch_channel
                    
                if patches[e[3]] == -1:
                    patches[e[3]] = e[6]
                
                else:
                    if patches[e[3]] != e[6]:
                        if e[6] in patches:
                            e[3] = patches.index(e[6])
                        
                        else:
                            if -1 in patches:
                                patches[patches.index(-1)] = e[6]
                            
                            else:
                                overflow_idx = idx
                                break

        enhanced_score_notes_with_patch_changes.append(e)

    #===========================================================================

    overflow_patches = []
    overflow_channels = [-1] * 16
    overflow_channels[9] = drums_patch

    if -1 < reserved_patch < 128 and -1 < reserved_patch_channel < 128:
        overflow_channels[reserved_patch_channel] = reserved_patch

    if overflow_idx != -1:
        for idx, e in enumerate(enhanced_score_notes[overflow_idx:]):
            if e[0] == 'note':
                if e[3] != 9:
                    if e[6] not in overflow_channels:
                        
                        if -1 in overflow_channels:
                            free_chan = overflow_channels.index(-1)
                            overflow_channels[free_chan] = e[6]
                            e[3] = free_chan

                            enhanced_score_notes_with_patch_changes.append(['patch_change', e[1], e[3], e[6]])
                            
                            overflow_patches.append(e[6])
                
                        else:
                            overflow_channels = [-1] * 16
                            overflow_channels[9] = drums_patch
                            
                            if -1 < reserved_patch < 128 and -1 < reserved_patch_channel < 128:
                                overflow_channels[reserved_patch_channel] = reserved_patch
                                e[3] = reserved_patch_channel

                            if e[6] != reserved_patch:

                                free_chan = overflow_channels.index(-1)
                                e[3] = free_chan
                                    
                            overflow_channels[e[3]] = e[6]                            

                            enhanced_score_notes_with_patch_changes.append(['patch_change', e[1], e[3], e[6]])
                            
                            overflow_patches.append(e[6])

                    else:
                        e[3] = overflow_channels.index(e[6])

            enhanced_score_notes_with_patch_changes.append(e)

    #===========================================================================

    patches = [p if p != -1 else default_patch for p in patches]

    patches[9] = drums_patch

    #===========================================================================

    overflow_patches = ordered_set(overflow_patches)

    #===========================================================================

    if verbose:
      print('=' * 70)
      print('Main composition patches')
      print('=' * 70)
      for c, p in enumerate(patches):
        print('Cha', str(c).zfill(2), '---', str(p).zfill(3), MIDI.Number2patch[p])
      print('=' * 70)

      if overflow_patches:
        print('Extra composition patches')
        print('=' * 70)
        for c, p in enumerate(overflow_patches):
          print(str(p).zfill(3), MIDI.Number2patch[p])
        print('=' * 70)

    #===========================================================================

    return enhanced_score_notes_with_patch_changes, patches, overflow_patches

###################################################################################

def create_enhanced_monophonic_melody(monophonic_melody):

    enhanced_monophonic_melody = []

    for i, note in enumerate(monophonic_melody[:-1]):

      enhanced_monophonic_melody.append(note)

      if note[1]+note[2] < monophonic_melody[i+1][1]:
        
        delta_time = monophonic_melody[i+1][1] - (note[1]+note[2])
        enhanced_monophonic_melody.append(['silence', note[1]+note[2], delta_time, note[3], 0, 0, note[6]])
        
    enhanced_monophonic_melody.append(monophonic_melody[-1])

    return enhanced_monophonic_melody

###################################################################################

def frame_monophonic_melody(monophonic_melody, min_frame_time_threshold=10):

    mzip = list(zip(monophonic_melody[:-1], monophonic_melody[1:]))

    times_counts = Counter([(b[1]-a[1]) for a, b in mzip]).most_common()

    mc_time = next((item for item, count in times_counts if item >= min_frame_time_threshold), min_frame_time_threshold)

    times = [(b[1]-a[1]) // mc_time for a, b in mzip] + [monophonic_melody[-1][2] // mc_time]

    framed_melody = []

    for i, note in enumerate(monophonic_melody):
      
      stime = note[1]
      count = times[i]
      
      if count != 0:
        for j in range(count):

          new_note = copy.deepcopy(note)
          new_note[1] = stime + (j * mc_time)
          new_note[2] = mc_time
          framed_melody.append(new_note)
      
      else:
        framed_melody.append(note)

    return [framed_melody, mc_time]

###################################################################################

def delta_score_notes(score_notes, 
                      timings_clip_value=255, 
                      even_timings=False,
                      compress_timings=False
                      ):

  delta_score = []

  pe = score_notes[0]

  for n in score_notes:

    note = copy.deepcopy(n)

    time =  n[1] - pe[1]
    dur = n[2]

    if even_timings:
      if time != 0 and time % 2 != 0:
        time += 1
      if dur % 2 != 0:
        dur += 1

    time = max(0, min(timings_clip_value, time))
    dur = max(0, min(timings_clip_value, dur))

    if compress_timings:
      time /= 2
      dur /= 2

    note[1] = int(time)
    note[2] = int(dur)

    delta_score.append(note)

    pe = n

  return delta_score

###################################################################################

def check_and_fix_chords_in_chordified_score(chordified_score,
                                             channels_index=3,
                                             pitches_index=4
                                             ):
  fixed_chordified_score = []

  bad_chords_counter = 0

  for c in chordified_score:

    tones_chord = sorted(set([t[pitches_index] % 12 for t in c if t[channels_index] != 9]))

    if tones_chord:

        if tones_chord not in ALL_CHORDS_SORTED:
          bad_chords_counter += 1

        while tones_chord not in ALL_CHORDS_SORTED:
          tones_chord.pop(0)

    new_chord = []

    c.sort(key = lambda x: x[pitches_index], reverse=True)

    for e in c:
      if e[channels_index] != 9:
        if e[pitches_index] % 12 in tones_chord:
          new_chord.append(e)

      else:
        new_chord.append(e)

    fixed_chordified_score.append(new_chord)

  return fixed_chordified_score, bad_chords_counter

###################################################################################

def advanced_check_and_fix_chords_in_chordified_score(chordified_score,
                                                      channels_index=3,
                                                      pitches_index=4,
                                                      patches_index=6,
                                                      use_filtered_chords=False,
                                                      use_full_chords=False,
                                                      remove_duplicate_pitches=True,
                                                      fix_bad_tones_chords=False,
                                                      fix_bad_pitches=False,
                                                      skip_drums=False
                                                      ):
  fixed_chordified_score = []

  bad_chords_counter = 0
  duplicate_pitches_counter = 0

  if use_filtered_chords:
    CHORDS = ALL_CHORDS_FILTERED
  else:
    CHORDS = ALL_CHORDS_SORTED

  if use_full_chords:
    CHORDS = ALL_CHORDS_FULL

  for c in chordified_score:

    chord = copy.deepcopy(c)

    if remove_duplicate_pitches:

      chord.sort(key = lambda x: x[pitches_index], reverse=True)

      seen = set()
      ddchord = []

      for cc in chord:
        if cc[channels_index] != 9:

          if tuple([cc[pitches_index], cc[patches_index]]) not in seen:
            ddchord.append(cc)
            seen.add(tuple([cc[pitches_index], cc[patches_index]]))
          else:
            duplicate_pitches_counter += 1
        
        else:
          ddchord.append(cc)
      
      chord = copy.deepcopy(ddchord)
      
    tones_chord = sorted(set([t[pitches_index] % 12 for t in chord if t[channels_index] != 9]))

    if tones_chord:

        if tones_chord not in CHORDS:
          
          pitches_chord = sorted(set([p[pitches_index] for p in c if p[channels_index] != 9]), reverse=True)
          
          if len(tones_chord) == 2:
            tones_counts = Counter([p % 12 for p in pitches_chord]).most_common()

            if tones_counts[0][1] > 1:
              good_tone = tones_counts[0][0]
              bad_tone = tones_counts[1][0]
            
            elif tones_counts[1][1] > 1:
              good_tone = tones_counts[1][0]
              bad_tone = tones_counts[0][0]
            
            else:
              good_tone = pitches_chord[0] % 12
              bad_tone = [t for t in tones_chord if t != good_tone][0]

            tones_chord = [good_tone]

            if fix_bad_tones_chords:

              if good_tone > bad_tone:

                if sorted([good_tone, (12+(bad_tone+1)) % 12]) in CHORDS:
                  tones_chord = sorted([good_tone, (12+(bad_tone-1)) % 12])

                elif sorted([good_tone, (12+(bad_tone-1)) % 12]) in CHORDS:
                  tones_chord = sorted([good_tone, (12+(bad_tone+1)) % 12])

              else:

                if sorted([good_tone, (12+(bad_tone-1)) % 12]) in CHORDS:
                  tones_chord = sorted([good_tone, (12+(bad_tone-1)) % 12])

                elif sorted([good_tone, (12+(bad_tone+1)) % 12]) in CHORDS:
                  tones_chord = sorted([good_tone, (12+(bad_tone+1)) % 12])          

          if len(tones_chord) > 2:
            tones_chord_combs = [list(comb) for i in range(len(tones_chord)-1, 0, -1) for comb in combinations(tones_chord, i)]

            for co in tones_chord_combs:
              if co in CHORDS:
                break

            if fix_bad_tones_chords:

              dt_chord = list(set(co) ^ set(tones_chord))

              for t in dt_chord:
                tones_chord.append((12+(t+1)) % 12)
                tones_chord.append((12+(t-1)) % 12)

              ex_tones_chord = sorted(set(tones_chord))

              tones_chord_combs = [list(comb) for i in range(4, 0, -2) for comb in combinations(ex_tones_chord, i) if all(t in list(comb) for t in co)]
              
              for eco in tones_chord_combs:
                if eco in CHORDS:
                  tones_chord = eco
                  break              

            else:
              tones_chord = co

          if len(tones_chord) == 1:
            tones_chord = [pitches_chord[0] % 12]
            
          bad_chords_counter += 1

    chord.sort(key = lambda x: x[pitches_index], reverse=True)

    new_chord = set()
    pipa = []

    for e in chord:
      if e[channels_index] != 9:
        if e[pitches_index] % 12 in tones_chord:
          new_chord.add(tuple(e))
          pipa.append([e[pitches_index], e[patches_index]])

        elif (e[pitches_index]+1) % 12 in tones_chord:
          e[pitches_index] += 1
          new_chord.add(tuple(e))
          pipa.append([e[pitches_index], e[patches_index]])

        elif (e[pitches_index]-1) % 12 in tones_chord:
          e[pitches_index] -= 1
          new_chord.add(tuple(e))
          pipa.append([e[pitches_index], e[patches_index]])

    if fix_bad_pitches:

      bad_chord = set()

      for e in chord:
        if e[channels_index] != 9:
          
          if e[pitches_index] % 12 not in tones_chord:
            bad_chord.add(tuple(e))
          
          elif (e[pitches_index]+1) % 12 not in tones_chord:
            bad_chord.add(tuple(e))
          
          elif (e[pitches_index]-1) % 12 not in tones_chord:
            bad_chord.add(tuple(e))
      
      for bc in bad_chord:

        bc = list(bc)

        tone = find_closest_tone(tones_chord, bc[pitches_index] % 12)

        new_pitch =  ((bc[pitches_index] // 12) * 12) + tone

        if [new_pitch, bc[patches_index]] not in pipa:
          bc[pitches_index] = new_pitch
          new_chord.add(tuple(bc))
          pipa.append([[new_pitch], bc[patches_index]])

    if not skip_drums:
      for e in c:
        if e[channels_index] == 9:
          new_chord.add(tuple(e))

    new_chord = [list(e) for e in new_chord]

    new_chord.sort(key = lambda x: (-x[pitches_index], x[patches_index]))

    fixed_chordified_score.append(new_chord)

  return fixed_chordified_score, bad_chords_counter, duplicate_pitches_counter

###################################################################################

def score_chord_to_tones_chord(chord,
                               transpose_value=0,
                               channels_index=3,
                               pitches_index=4):

  return sorted(set([(p[4]+transpose_value) % 12 for p in chord if p[channels_index] != 9]))

###################################################################################

def grouped_set(seq):
  return [k for k, v in groupby(seq)]

###################################################################################

def ordered_set(seq):
  dic = {}
  return [k for k, v in dic.fromkeys(seq).items()]

###################################################################################

def add_melody_to_enhanced_score_notes(enhanced_score_notes,
                                      melody_start_time=0,
                                      melody_start_chord=0,
                                      melody_notes_min_duration=-1,
                                      melody_notes_max_duration=255,
                                      melody_duration_overlap_tolerance=4,
                                      melody_avg_duration_divider=2,
                                      melody_base_octave=5,
                                      melody_channel=3,
                                      melody_patch=40,
                                      melody_max_velocity=110,
                                      acc_max_velocity=90,
                                      pass_drums=True,
                                      return_melody=False
                                      ):
  
    if pass_drums:
      score = copy.deepcopy(enhanced_score_notes)
    else:
      score = [e for e in copy.deepcopy(enhanced_score_notes) if e[3] !=9]

    if melody_notes_min_duration > 0:
      min_duration = melody_notes_min_duration
    else:
      durs = [d[2] for d in score]
      min_duration = Counter(durs).most_common()[0][0]

    adjust_score_velocities(score, acc_max_velocity)

    cscore = chordify_score([1000, score])

    melody_score = []
    acc_score = []

    pt = melody_start_time

    for c in cscore[:melody_start_chord]:
      acc_score.extend(c)

    for c in cscore[melody_start_chord:]:

      durs = [d[2] if d[3] != 9 else -1 for d in c]

      if not all(d == -1 for d in durs):
        ndurs = [d for d in durs if d != -1]
        avg_dur = (sum(ndurs) / len(ndurs)) / melody_avg_duration_divider
        best_dur = min(durs, key=lambda x:abs(x-avg_dur))
        pidx = durs.index(best_dur)

        cc = copy.deepcopy(c[pidx])

        if c[0][1] >= pt - melody_duration_overlap_tolerance and best_dur >= min_duration:

          cc[3] = melody_channel
          cc[4] = (c[pidx][4] % 24)
          cc[5] = 100 + ((c[pidx][4] % 12) * 2)
          cc[6] = melody_patch

          melody_score.append(cc)
          acc_score.extend(c)

          pt = c[0][1]+c[pidx][2]

        else:
          acc_score.extend(c)

      else:
        acc_score.extend(c)

    values = [e[4] % 24 for e in melody_score]
    smoothed = [values[0]]
    for i in range(1, len(values)):
        if abs(smoothed[-1] - values[i]) >= 12:
            if smoothed[-1] < values[i]:
                smoothed.append(values[i] - 12)
            else:
                smoothed.append(values[i] + 12)
        else:
            smoothed.append(values[i])

    smoothed_melody = copy.deepcopy(melody_score)

    for i, e in enumerate(smoothed_melody):
      e[4] = (melody_base_octave * 12) + smoothed[i]

    for i, m in enumerate(smoothed_melody[1:]):
      if m[1] - smoothed_melody[i][1] < melody_notes_max_duration:
        smoothed_melody[i][2] = m[1] - smoothed_melody[i][1]

    adjust_score_velocities(smoothed_melody, melody_max_velocity)

    if return_melody:
      final_score = sorted(smoothed_melody, key=lambda x: (x[1], -x[4]))

    else:
      final_score = sorted(smoothed_melody + acc_score, key=lambda x: (x[1], -x[4]))

    return final_score
    
###################################################################################

def find_paths(list_of_lists, path=[]):
    if not list_of_lists:
        return [path]
    return [p for sublist in list_of_lists[0] for p in find_paths(list_of_lists[1:], path+[sublist])]

###################################################################################

def recalculate_score_timings(score, 
                              start_time=0, 
                              timings_index=1
                              ):

  rscore = copy.deepcopy(score)

  pe = rscore[0]

  abs_time = start_time

  for e in rscore:

    dtime = e[timings_index] - pe[timings_index]
    pe = copy.deepcopy(e)
    abs_time += dtime
    e[timings_index] = abs_time
    
  return rscore

###################################################################################

WHITE_NOTES = [0, 2, 4, 5, 7, 9, 11]
BLACK_NOTES = [1, 3, 6, 8, 10]

###################################################################################

ALL_CHORDS_FILTERED = [[0], [0, 3], [0, 3, 5], [0, 3, 5, 8], [0, 3, 5, 9], [0, 3, 5, 10], [0, 3, 7],
                      [0, 3, 7, 10], [0, 3, 8], [0, 3, 9], [0, 3, 10], [0, 4], [0, 4, 6],
                      [0, 4, 6, 9], [0, 4, 6, 10], [0, 4, 7], [0, 4, 7, 10], [0, 4, 8], [0, 4, 9],
                      [0, 4, 10], [0, 5], [0, 5, 8], [0, 5, 9], [0, 5, 10], [0, 6], [0, 6, 9],
                      [0, 6, 10], [0, 7], [0, 7, 10], [0, 8], [0, 9], [0, 10], [1], [1, 4],
                      [1, 4, 6], [1, 4, 6, 9], [1, 4, 6, 10], [1, 4, 6, 11], [1, 4, 7],
                      [1, 4, 7, 10], [1, 4, 7, 11], [1, 4, 8], [1, 4, 8, 11], [1, 4, 9], [1, 4, 10],
                      [1, 4, 11], [1, 5], [1, 5, 8], [1, 5, 8, 11], [1, 5, 9], [1, 5, 10],
                      [1, 5, 11], [1, 6], [1, 6, 9], [1, 6, 10], [1, 6, 11], [1, 7], [1, 7, 10],
                      [1, 7, 11], [1, 8], [1, 8, 11], [1, 9], [1, 10], [1, 11], [2], [2, 5],
                      [2, 5, 8], [2, 5, 8, 11], [2, 5, 9], [2, 5, 10], [2, 5, 11], [2, 6], [2, 6, 9],
                      [2, 6, 10], [2, 6, 11], [2, 7], [2, 7, 10], [2, 7, 11], [2, 8], [2, 8, 11],
                      [2, 9], [2, 10], [2, 11], [3], [3, 5], [3, 5, 8], [3, 5, 8, 11], [3, 5, 9],
                      [3, 5, 10], [3, 5, 11], [3, 7], [3, 7, 10], [3, 7, 11], [3, 8], [3, 8, 11],
                      [3, 9], [3, 10], [3, 11], [4], [4, 6], [4, 6, 9], [4, 6, 10], [4, 6, 11],
                      [4, 7], [4, 7, 10], [4, 7, 11], [4, 8], [4, 8, 11], [4, 9], [4, 10], [4, 11],
                      [5], [5, 8], [5, 8, 11], [5, 9], [5, 10], [5, 11], [6], [6, 9], [6, 10],
                      [6, 11], [7], [7, 10], [7, 11], [8], [8, 11], [9], [10], [11]]

###################################################################################

def harmonize_enhanced_melody_score_notes(enhanced_melody_score_notes):
  
  mel_tones = [e[4] % 12 for e in enhanced_melody_score_notes]

  cur_chord = []

  song = []

  for i, m in enumerate(mel_tones):
    cur_chord.append(m)
    cc = sorted(set(cur_chord))

    if cc in ALL_CHORDS_FULL:
      song.append(cc)

    else:
      while sorted(set(cur_chord)) not in ALL_CHORDS_FULL:
        cur_chord.pop(0)
      cc = sorted(set(cur_chord))
      song.append(cc)

  return song

###################################################################################

def split_melody(enhanced_melody_score_notes, 
                 split_time=-1, 
                 max_score_time=255
                 ):

  mel_chunks = []

  if split_time == -1:

    durs = [max(0, min(max_score_time, e[2])) for e in enhanced_melody_score_notes]
    stime = max(durs)
    
  else:
    stime = split_time

  pe = enhanced_melody_score_notes[0]
  chu = []
  
  for e in enhanced_melody_score_notes:
    dtime = max(0, min(max_score_time, e[1]-pe[1]))

    if dtime > stime:
      if chu:
        mel_chunks.append(chu)
      chu = []
      chu.append(e)
    else:
      chu.append(e)

    pe = e

  if chu:
    mel_chunks.append(chu)

  return mel_chunks, [[m[0][1], m[-1][1]] for m in mel_chunks], len(mel_chunks)

###################################################################################

def flatten(list_of_lists):
  return [x for y in list_of_lists for x in y]

###################################################################################

def enhanced_delta_score_notes(enhanced_score_notes,
                               start_time=0,
                               max_score_time=255
                               ):

  delta_score = []

  pe = ['note', max(0, enhanced_score_notes[0][1]-start_time)]

  for e in enhanced_score_notes:

    dtime = max(0, min(max_score_time, e[1]-pe[1]))
    dur = max(1, min(max_score_time, e[2]))
    cha = max(0, min(15, e[3]))
    ptc = max(1, min(127, e[4]))
    vel = max(1, min(127, e[5]))
    pat = max(0, min(128, e[6]))

    delta_score.append([dtime, dur, cha, ptc, vel, pat])

    pe = e

  return delta_score

###################################################################################

def basic_enhanced_delta_score_notes_tokenizer(enhanced_delta_score_notes,
                                              tokenize_start_times=True,
                                              tokenize_durations=True,
                                              tokenize_channels=True,
                                              tokenize_pitches=True,
                                              tokenize_velocities=True,
                                              tokenize_patches=True,
                                              score_timings_range=256,
                                              max_seq_len=-1,
                                              seq_pad_value=-1
                                              ):
  
  
  
  score_tokens_ints_seq = []

  tokens_shifts = [-1] * 7

  for d in enhanced_delta_score_notes:

    seq = []
    shift = 0

    if tokenize_start_times:
      seq.append(d[0])
      tokens_shifts[0] = shift
      shift += score_timings_range

    if tokenize_durations:
      seq.append(d[1]+shift)
      tokens_shifts[1] = shift
      shift += score_timings_range

    if tokenize_channels:
      tokens_shifts[2] = shift
      seq.append(d[2]+shift)
      shift += 16
    
    if tokenize_pitches:
      tokens_shifts[3] = shift
      seq.append(d[3]+shift)
      shift += 128
    
    if tokenize_velocities:
      tokens_shifts[4] = shift
      seq.append(d[4]+shift)
      shift += 128

    if tokenize_patches:
      tokens_shifts[5] = shift
      seq.append(d[5]+shift)
      shift += 129

    tokens_shifts[6] = shift
    score_tokens_ints_seq.append(seq)

  final_score_tokens_ints_seq = flatten(score_tokens_ints_seq)

  if max_seq_len > -1:
    final_score_tokens_ints_seq = final_score_tokens_ints_seq[:max_seq_len]

  if seq_pad_value > -1:
    final_score_tokens_ints_seq += [seq_pad_value] * (max_seq_len - len(final_score_tokens_ints_seq))

  return [score_tokens_ints_seq,
          final_score_tokens_ints_seq, 
          tokens_shifts,
          seq_pad_value, 
          max_seq_len,
          len(score_tokens_ints_seq),
          len(final_score_tokens_ints_seq)
          ]

###################################################################################

def basic_enhanced_delta_score_notes_detokenizer(tokenized_seq, 
                                                 tokens_shifts, 
                                                 timings_multiplier=16
                                                 ):

  song_f = []

  time = 0
  dur = 16
  channel = 0
  pitch = 60
  vel = 90
  pat = 0

  note_seq_len = len([t for t in tokens_shifts if t > -1])-1
  tok_shifts_idxs = [i for i in range(len(tokens_shifts[:-1])) if tokens_shifts[i] > - 1]

  song = []

  for i in range(0, len(tokenized_seq), note_seq_len):
    note = tokenized_seq[i:i+note_seq_len]
    song.append(note)

  for note in song:
    for i, idx in enumerate(tok_shifts_idxs):
      if idx == 0:
        time += (note[i]-tokens_shifts[0]) * timings_multiplier
      elif idx == 1:
        dur = (note[i]-tokens_shifts[1]) * timings_multiplier
      elif idx == 2:
        channel = (note[i]-tokens_shifts[2])
      elif idx == 3:
        pitch = (note[i]-tokens_shifts[3])
      elif idx == 4:
        vel = (note[i]-tokens_shifts[4])
      elif idx == 5:
        pat = (note[i]-tokens_shifts[5])

    song_f.append(['note', time, dur, channel, pitch, vel, pat ])

  return song_f

###################################################################################

def enhanced_chord_to_chord_token(enhanced_chord, 
                                  channels_index=3, 
                                  pitches_index=4, 
                                  use_filtered_chords=False,
                                  use_full_chords=True
                                  ):
  
  bad_chords_counter = 0
  duplicate_pitches_counter = 0

  if use_filtered_chords:
    CHORDS = ALL_CHORDS_FILTERED
  else:
    CHORDS = ALL_CHORDS_SORTED

  if use_full_chords:
    CHORDS = ALL_CHORDS_FULL

  tones_chord = sorted(set([t[pitches_index] % 12 for t in enhanced_chord if t[channels_index] != 9]))

  original_tones_chord = copy.deepcopy(tones_chord)

  if tones_chord:

      if tones_chord not in CHORDS:
        
        pitches_chord = sorted(set([p[pitches_index] for p in enhanced_chord if p[channels_index] != 9]), reverse=True)
        
        if len(tones_chord) == 2:
          tones_counts = Counter([p % 12 for p in pitches_chord]).most_common()

          if tones_counts[0][1] > 1:
            tones_chord = [tones_counts[0][0]]
          elif tones_counts[1][1] > 1:
            tones_chord = [tones_counts[1][0]]
          else:
            tones_chord = [pitches_chord[0] % 12]

        else:
          tones_chord_combs = [list(comb) for i in range(len(tones_chord)-2, 0, -1) for comb in combinations(tones_chord, i+1)]

          for co in tones_chord_combs:
            if co in CHORDS:
              tones_chord = co
              break

  if use_filtered_chords:
    chord_token = ALL_CHORDS_FILTERED.index(tones_chord)
  else:
    chord_token = ALL_CHORDS_SORTED.index(tones_chord)

  return [chord_token, tones_chord, original_tones_chord, sorted(set(original_tones_chord) ^ set(tones_chord))]

###################################################################################

def enhanced_chord_to_tones_chord(enhanced_chord):
  return sorted(set([t[4] % 12 for t in enhanced_chord if t[3] != 9]))

###################################################################################

def md5_hash(file_path_or_data=None, original_md5_hash=None):

  if type(file_path_or_data) == str:

    with open(file_path_or_data, 'rb') as file_to_check:
      data = file_to_check.read()
      
      if data:
        md5 = hashlib.md5(data).hexdigest()

  else:
    if file_path_or_data:
      md5 = hashlib.md5(file_path_or_data).hexdigest()

  if md5:

    if original_md5_hash:

      if md5 == original_md5_hash:
        check = True
      else:
        check = False
        
    else:
      check = None

    return [md5, check]

  else:

    md5 = None
    check = None

    return [md5, check]

###################################################################################

ALL_PITCHES_CHORDS_FILTERED = [[67], [64], [62], [69], [60], [65], [59], [70], [66], [63], [68], [61],
                              [64, 60], [67, 64], [65, 62], [62, 59], [69, 65], [60, 57], [66, 62], [59, 55],
                              [62, 57], [67, 62], [64, 59], [64, 60, 55], [60, 55], [65, 60], [64, 61],
                              [69, 64], [66, 62, 57], [69, 66], [62, 59, 55], [64, 60, 57], [62, 58],
                              [65, 60, 57], [70, 67], [67, 63], [64, 61, 57], [61, 57], [63, 60], [68, 64],
                              [65, 62, 58], [65, 62, 57], [59, 56], [63, 58], [68, 65], [59, 54, 47, 35],
                              [70, 65], [66, 61], [64, 59, 56], [65, 61], [64, 59, 55], [63, 59], [61, 58],
                              [68, 63], [60, 56], [67, 63, 60], [67, 63, 58], [66, 62, 59], [61, 56],
                              [70, 66], [67, 62, 58], [63, 60, 56], [65, 61, 56], [66, 61, 58], [66, 61, 57],
                              [65, 60, 56], [65, 61, 58], [65, 59], [68, 64, 61], [66, 60], [64, 58],
                              [62, 56], [63, 57], [61, 55], [66, 64], [60, 58], [65, 63], [63, 59, 56],
                              [65, 62, 59], [61, 59], [66, 60, 57], [64, 61, 55], [64, 58, 55], [62, 59, 56],
                              [64, 60, 58], [63, 60, 57], [64, 60, 58, 55], [65, 62, 56], [64, 61, 58],
                              [66, 64, 59], [60, 58, 55], [65, 63, 60], [63, 57, 53], [65, 63, 60, 57],
                              [65, 59, 56], [63, 60, 58, 55], [67, 61, 58], [64, 61, 57, 54], [64, 61, 59],
                              [70, 65, 60], [68, 65, 63, 60], [63, 60, 58], [65, 63, 58], [69, 66, 64],
                              [64, 60, 54], [64, 60, 57, 54], [66, 64, 61], [66, 61, 59], [67, 63, 59],
                              [65, 61, 57], [68, 65, 63], [64, 61, 59, 56], [65, 61, 59], [66, 64, 61, 58],
                              [64, 61, 58, 55], [64, 60, 56], [65, 61, 59, 56], [66, 62, 58], [61, 59, 56],
                              [64, 58, 54], [63, 59, 53], [65, 62, 59, 56], [61, 59, 55], [64, 61, 59, 55],
                              [68, 65, 63, 59], [70, 66, 60], [65, 63, 60, 58], [64, 61, 59, 54],
                              [70, 64, 60, 54]]

###################################################################################

ALL_PITCHES_CHORDS_SORTED = [[60], [62, 60], [63, 60], [64, 60], [64, 62, 60], [65, 60], [65, 62, 60],
                            [65, 63, 60], [66, 60], [66, 62, 60], [66, 63, 60], [64, 60, 54],
                            [64, 60, 54, 50], [60, 55], [67, 62, 60], [67, 63, 60], [64, 60, 55],
                            [65, 60, 55], [64, 62, 60, 55], [67, 65, 62, 60], [67, 65, 63, 60], [60, 56],
                            [62, 60, 56], [63, 60, 56], [64, 60, 56], [65, 60, 56], [66, 60, 56],
                            [72, 68, 64, 62], [65, 62, 60, 56], [66, 62, 60, 56], [68, 65, 63, 60],
                            [68, 66, 63, 60], [60, 44, 42, 40], [88, 80, 74, 66, 60, 56], [60, 57],
                            [62, 60, 57], [63, 60, 57], [64, 60, 57], [65, 60, 57], [66, 60, 57],
                            [67, 60, 57], [64, 62, 60, 57], [65, 62, 60, 57], [69, 66, 62, 60],
                            [67, 62, 60, 57], [65, 63, 60, 57], [66, 63, 60, 57], [67, 63, 60, 57],
                            [64, 60, 57, 54], [67, 64, 60, 57], [67, 65, 60, 57], [69, 64, 60, 54, 38],
                            [67, 64, 62, 60, 57], [67, 65, 62, 60, 57], [67, 65, 63, 60, 57], [60, 58],
                            [62, 60, 58], [63, 60, 58], [64, 60, 58], [70, 65, 60], [70, 66, 60],
                            [60, 58, 55], [70, 60, 56], [74, 64, 60, 58], [65, 62, 60, 58],
                            [70, 66, 62, 60], [62, 60, 58, 55], [72, 68, 62, 58], [65, 63, 60, 58],
                            [70, 66, 63, 60], [63, 60, 58, 55], [70, 63, 60, 56], [70, 64, 60, 54],
                            [64, 60, 58, 55], [68, 64, 60, 58], [65, 60, 58, 55], [70, 65, 60, 56],
                            [70, 66, 60, 56], [78, 76, 74, 72, 70, 66], [67, 64, 62, 58, 36],
                            [74, 68, 64, 58, 48], [65, 62, 58, 55, 36], [65, 62, 60, 56, 46],
                            [72, 66, 62, 56, 46], [79, 65, 63, 58, 53, 36], [65, 60, 56, 51, 46, 41],
                            [70, 66, 63, 60, 44], [68, 66, 64, 58, 56, 48],
                            [94, 92, 90, 88, 86, 84, 82, 80, 78, 76, 74, 72, 70, 68, 66, 64, 62, 60, 58,
                              56, 54, 52, 50, 48, 46, 44, 42, 40, 38, 36, 34, 32, 30, 28, 26, 24],
                            [61], [63, 61], [64, 61], [65, 61], [65, 63, 61], [66, 61], [66, 63, 61],
                            [66, 64, 61], [61, 55], [67, 63, 61], [64, 61, 55], [65, 61, 55],
                            [65, 61, 55, 39], [61, 56], [63, 61, 56], [68, 64, 61], [65, 61, 56],
                            [66, 61, 56], [68, 65, 63, 61], [54, 49, 44, 39], [68, 64, 61, 42], [61, 57],
                            [63, 61, 57], [64, 61, 57], [65, 61, 57], [66, 61, 57], [67, 61, 57],
                            [69, 65, 63, 61], [66, 63, 61, 57], [67, 63, 61, 57], [64, 61, 57, 54],
                            [67, 64, 61, 57], [65, 61, 55, 45], [67, 65, 63, 61, 57], [61, 58],
                            [63, 61, 58], [64, 61, 58], [65, 61, 58], [66, 61, 58], [67, 61, 58],
                            [61, 58, 56], [65, 63, 61, 58], [66, 63, 61, 58], [67, 63, 61, 58],
                            [63, 61, 58, 56], [66, 64, 61, 58], [64, 61, 58, 55], [68, 64, 61, 58],
                            [65, 61, 58, 55], [65, 61, 58, 56], [58, 54, 49, 44], [70, 65, 61, 55, 39],
                            [80, 68, 65, 63, 61, 58], [63, 58, 54, 49, 44, 39], [73, 68, 64, 58, 54],
                            [61, 59], [63, 61, 59], [64, 61, 59], [65, 61, 59], [66, 61, 59], [61, 59, 55],
                            [61, 59, 56], [61, 59, 57], [63, 59, 53, 49], [66, 63, 61, 59],
                            [71, 67, 63, 61], [63, 61, 59, 56], [61, 57, 51, 47], [64, 61, 59, 54],
                            [64, 61, 59, 55], [64, 61, 59, 56], [64, 61, 59, 57], [65, 61, 59, 55],
                            [65, 61, 59, 56], [69, 65, 61, 59], [66, 61, 59, 56], [71, 66, 61, 57],
                            [71, 67, 61, 57], [67, 63, 59, 53, 49], [68, 65, 63, 59, 37],
                            [65, 63, 61, 59, 57], [66, 63, 61, 59, 56], [73, 69, 66, 63, 59],
                            [79, 75, 73, 61, 59, 33], [61, 56, 52, 47, 42, 35], [76, 73, 69, 66, 35],
                            [71, 67, 64, 61, 57], [73, 71, 69, 67, 65],
                            [95, 93, 91, 89, 87, 85, 83, 81, 79, 77, 75, 73, 71, 69, 67, 65, 63, 61, 59,
                              57, 55, 53, 51, 49, 47, 45, 43, 41, 39, 37, 35, 33, 31, 29, 27, 25],
                            [62], [64, 62], [65, 62], [66, 62], [66, 64, 62], [67, 62], [67, 64, 62],
                            [67, 65, 62], [62, 56], [68, 64, 62], [65, 62, 56], [66, 62, 56],
                            [66, 62, 56, 52], [62, 57], [50, 45, 40], [65, 62, 57], [66, 62, 57],
                            [55, 50, 45], [66, 64, 62, 57], [55, 50, 45, 40], [69, 67, 65, 62], [62, 58],
                            [64, 62, 58], [65, 62, 58], [66, 62, 58], [67, 62, 58], [62, 58, 56],
                            [66, 64, 62, 58], [67, 64, 62, 58], [64, 62, 58, 56], [65, 62, 58, 55],
                            [65, 62, 58, 56], [66, 62, 58, 56], [66, 64, 58, 44, 38], [62, 59],
                            [64, 62, 59], [65, 62, 59], [66, 62, 59], [62, 59, 55], [62, 59, 56],
                            [62, 59, 57], [66, 64, 62, 59], [67, 64, 62, 59], [64, 62, 59, 56],
                            [64, 62, 59, 57], [67, 65, 62, 59], [65, 62, 59, 56], [69, 65, 62, 59],
                            [66, 62, 59, 56], [69, 66, 62, 59], [59, 55, 50, 45], [64, 62, 59, 56, 54],
                            [69, 66, 62, 59, 40], [64, 59, 55, 50, 45, 40], [69, 65, 62, 59, 55], [63],
                            [65, 63], [66, 63], [67, 63], [67, 65, 63], [68, 63], [68, 65, 63],
                            [68, 66, 63], [63, 57], [63, 57, 53], [66, 63, 57], [67, 63, 57],
                            [67, 63, 57, 53], [63, 58], [65, 63, 58], [66, 63, 58], [67, 63, 58],
                            [68, 63, 58], [67, 65, 63, 58], [63, 58, 56, 53], [70, 68, 66, 63], [63, 59],
                            [63, 59, 53], [66, 63, 59], [67, 63, 59], [63, 59, 56], [63, 59, 57],
                            [63, 59, 55, 53], [68, 65, 63, 59], [69, 65, 63, 59], [66, 63, 59, 56],
                            [66, 63, 59, 57], [67, 63, 59, 57], [67, 63, 59, 57, 41], [64], [66, 64],
                            [67, 64], [68, 64], [68, 66, 64], [69, 64], [69, 66, 64], [69, 67, 64],
                            [64, 58], [64, 58, 54], [64, 58, 55], [68, 64, 58], [68, 64, 58, 42], [64, 59],
                            [66, 64, 59], [64, 59, 55], [64, 59, 56], [64, 59, 57], [64, 59, 56, 54],
                            [64, 59, 57, 54], [69, 64, 59, 55], [65], [67, 65], [68, 65], [69, 65],
                            [69, 67, 65], [70, 65], [65, 58, 55], [70, 68, 65], [65, 59], [65, 59, 55],
                            [65, 59, 56], [59, 57, 53], [69, 65, 59, 55], [66], [68, 66], [69, 66],
                            [70, 66], [80, 70, 54], [59, 54, 47, 35], [66, 59, 56], [71, 69, 66], [67],
                            [69, 67], [70, 67], [59, 55], [71, 69, 67], [68], [70, 68], [59, 56], [69],
                            [71, 69], [70], [59]]

###################################################################################

def sort_list_by_other(list1, list2):
    return sorted(list1, key=lambda x: list2.index(x) if x in list2 else len(list2))

###################################################################################

ALL_CHORDS_PAIRS_SORTED = [[[0], [0, 4, 7]], [[0, 2], [0, 4, 7]], [[0, 3], [0, 3, 7]],
                          [[0, 4], [0, 4, 7]], [[0, 2, 4], [0, 2, 4, 7]], [[0, 5], [0, 5, 9]],
                          [[0, 2, 5], [0, 2, 5, 9]], [[0, 3, 5], [0, 3, 5, 9]], [[0, 6], [0, 2, 6, 9]],
                          [[0, 2, 6], [0, 2, 6, 9]], [[0, 3, 6], [0, 3, 6, 8]],
                          [[0, 4, 6], [0, 4, 6, 9]], [[0, 2, 4, 6], [0, 2, 4, 6, 9]],
                          [[0, 7], [0, 4, 7]], [[0, 2, 7], [0, 2, 4, 7]], [[0, 3, 7], [0, 3, 7, 10]],
                          [[0, 4, 7], [0, 4, 7, 9]], [[0, 5, 7], [0, 5, 7, 9]],
                          [[0, 2, 4, 7], [0, 2, 4, 7, 9]], [[0, 2, 5, 7], [0, 2, 5, 7, 9]],
                          [[0, 3, 5, 7], [0, 3, 5, 7, 10]], [[0, 8], [0, 3, 8]],
                          [[0, 2, 8], [0, 2, 5, 8]], [[0, 3, 8], [0, 3, 5, 8]],
                          [[0, 4, 8], [2, 4, 8, 11]], [[0, 5, 8], [0, 3, 5, 8]],
                          [[0, 6, 8], [0, 3, 6, 8]], [[0, 2, 4, 8], [0, 2, 4, 6, 8]],
                          [[0, 2, 5, 8], [0, 2, 5, 8, 10]], [[0, 2, 6, 8], [0, 2, 6, 8, 10]],
                          [[0, 3, 5, 8], [0, 3, 5, 8, 10]], [[0, 3, 6, 8], [0, 3, 6, 8, 10]],
                          [[0, 4, 6, 8], [2, 4, 6, 8, 11]], [[0, 2, 4, 6, 8], [2, 4, 6, 8, 11]],
                          [[0, 9], [0, 4, 9]], [[0, 2, 9], [0, 2, 6, 9]], [[0, 3, 9], [0, 3, 5, 9]],
                          [[0, 4, 9], [0, 4, 7, 9]], [[0, 5, 9], [0, 2, 5, 9]],
                          [[0, 6, 9], [0, 2, 6, 9]], [[0, 7, 9], [0, 4, 7, 9]],
                          [[0, 2, 4, 9], [0, 2, 4, 7, 9]], [[0, 2, 5, 9], [0, 2, 5, 7, 9]],
                          [[0, 2, 6, 9], [0, 2, 4, 6, 9]], [[0, 2, 7, 9], [0, 2, 4, 7, 9]],
                          [[0, 3, 5, 9], [0, 3, 5, 7, 9]], [[0, 3, 6, 9], [0, 2, 4, 6, 9]],
                          [[0, 3, 7, 9], [0, 3, 5, 7, 9]], [[0, 4, 6, 9], [0, 2, 4, 6, 9]],
                          [[0, 4, 7, 9], [0, 2, 4, 7, 9]], [[0, 5, 7, 9], [0, 2, 5, 7, 9]],
                          [[0, 2, 4, 6, 9], [2, 4, 6, 9, 11]], [[0, 2, 4, 7, 9], [2, 4, 7, 9, 11]],
                          [[0, 2, 5, 7, 9], [2, 5, 7, 9, 11]], [[0, 3, 5, 7, 9], [2, 4, 6, 8, 11]],
                          [[0, 10], [2, 5, 10]], [[0, 2, 10], [0, 2, 5, 10]],
                          [[0, 3, 10], [0, 3, 7, 10]], [[0, 4, 10], [0, 4, 7, 10]],
                          [[0, 5, 10], [0, 2, 5, 10]], [[0, 6, 10], [0, 3, 6, 10]],
                          [[0, 7, 10], [0, 4, 7, 10]], [[0, 8, 10], [0, 3, 8, 10]],
                          [[0, 2, 4, 10], [0, 2, 4, 7, 10]], [[0, 2, 5, 10], [0, 2, 5, 7, 10]],
                          [[0, 2, 6, 10], [0, 2, 6, 8, 10]], [[0, 2, 7, 10], [0, 2, 5, 7, 10]],
                          [[0, 2, 8, 10], [0, 2, 5, 8, 10]], [[0, 3, 5, 10], [0, 3, 5, 7, 10]],
                          [[0, 3, 6, 10], [0, 3, 6, 8, 10]], [[0, 3, 7, 10], [0, 3, 5, 7, 10]],
                          [[0, 3, 8, 10], [0, 3, 5, 8, 10]], [[0, 4, 6, 10], [0, 2, 4, 6, 10]],
                          [[0, 4, 7, 10], [0, 2, 4, 7, 10]], [[0, 4, 8, 10], [0, 2, 4, 8, 10]],
                          [[0, 5, 7, 10], [0, 3, 5, 7, 10]], [[0, 5, 8, 10], [0, 3, 5, 8, 10]],
                          [[0, 6, 8, 10], [0, 3, 6, 8, 10]], [[0, 2, 4, 6, 10], [0, 2, 4, 8, 10]],
                          [[0, 2, 4, 7, 10], [1, 3, 6, 9, 11]], [[0, 2, 4, 8, 10], [1, 3, 7, 9, 11]],
                          [[0, 2, 5, 7, 10], [0, 3, 5, 7, 10]], [[0, 2, 5, 8, 10], [1, 4, 7, 9, 11]],
                          [[0, 2, 6, 8, 10], [2, 4, 6, 8, 10]], [[0, 3, 5, 7, 10], [0, 2, 5, 7, 10]],
                          [[0, 3, 5, 8, 10], [1, 3, 5, 8, 10]], [[0, 3, 6, 8, 10], [1, 3, 6, 8, 10]],
                          [[0, 4, 6, 8, 10], [0, 2, 4, 6, 9]],
                          [[0, 2, 4, 6, 8, 10], [1, 3, 5, 7, 9, 11]], [[1], [1, 8]], [[1, 3], [1, 5, 8]],
                          [[1, 4], [1, 4, 9]], [[1, 5], [1, 5, 8]], [[1, 3, 5], [1, 3, 5, 10]],
                          [[1, 6], [1, 6, 10]], [[1, 3, 6], [1, 3, 6, 10]], [[1, 4, 6], [1, 4, 6, 9]],
                          [[1, 7], [1, 4, 7]], [[1, 3, 7], [1, 3, 7, 10]], [[1, 4, 7], [1, 4, 7, 9]],
                          [[1, 5, 7], [1, 5, 7, 10]], [[1, 3, 5, 7], [1, 3, 5, 7, 10]],
                          [[1, 8], [1, 5, 8]], [[1, 3, 8], [1, 3, 5, 8]], [[1, 4, 8], [1, 4, 8, 11]],
                          [[1, 5, 8], [1, 5, 8, 10]], [[1, 6, 8], [1, 3, 6, 8]],
                          [[1, 3, 5, 8], [1, 3, 5, 8, 10]], [[1, 3, 6, 8], [1, 3, 6, 8, 10]],
                          [[1, 4, 6, 8], [1, 4, 6, 8, 11]], [[1, 9], [1, 4, 9]],
                          [[1, 3, 9], [1, 3, 6, 9]], [[1, 4, 9], [1, 4, 6, 9]],
                          [[1, 5, 9], [0, 3, 5, 9]], [[1, 6, 9], [1, 4, 6, 9]],
                          [[1, 7, 9], [1, 4, 7, 9]], [[1, 3, 5, 9], [0, 3, 5, 7, 9]],
                          [[1, 3, 6, 9], [1, 3, 6, 9, 11]], [[1, 3, 7, 9], [1, 3, 5, 7, 9]],
                          [[1, 4, 6, 9], [1, 4, 6, 9, 11]], [[1, 4, 7, 9], [1, 4, 7, 9, 11]],
                          [[1, 5, 7, 9], [1, 3, 7, 9, 11]], [[1, 3, 5, 7, 9], [2, 4, 6, 8, 11]],
                          [[1, 10], [1, 5, 10]], [[1, 3, 10], [1, 3, 7, 10]],
                          [[1, 4, 10], [1, 4, 6, 10]], [[1, 5, 10], [1, 5, 8, 10]],
                          [[1, 6, 10], [1, 4, 6, 10]], [[1, 7, 10], [1, 3, 7, 10]],
                          [[1, 8, 10], [1, 5, 8, 10]], [[1, 3, 5, 10], [1, 3, 5, 8, 10]],
                          [[1, 3, 6, 10], [1, 3, 6, 8, 10]], [[1, 3, 7, 10], [1, 3, 5, 7, 10]],
                          [[1, 3, 8, 10], [1, 3, 5, 8, 10]], [[1, 4, 6, 10], [1, 4, 6, 8, 10]],
                          [[1, 4, 7, 10], [0, 2, 4, 7, 10]], [[1, 4, 8, 10], [1, 4, 6, 8, 10]],
                          [[1, 5, 7, 10], [1, 3, 5, 7, 10]], [[1, 5, 8, 10], [1, 3, 5, 8, 10]],
                          [[1, 6, 8, 10], [1, 3, 6, 8, 10]], [[1, 3, 5, 7, 10], [2, 4, 6, 8, 11]],
                          [[1, 3, 5, 8, 10], [0, 3, 5, 8, 10]], [[1, 3, 6, 8, 10], [0, 3, 6, 8, 10]],
                          [[1, 4, 6, 8, 10], [0, 3, 5, 7, 9]], [[1, 11], [2, 6, 11]],
                          [[1, 3, 11], [1, 3, 6, 11]], [[1, 4, 11], [1, 4, 8, 11]],
                          [[1, 5, 11], [1, 5, 8, 11]], [[1, 6, 11], [1, 4, 6, 11]],
                          [[1, 7, 11], [1, 4, 7, 11]], [[1, 8, 11], [1, 4, 8, 11]],
                          [[1, 9, 11], [1, 4, 9, 11]], [[1, 3, 5, 11], [1, 3, 5, 8, 11]],
                          [[1, 3, 6, 11], [1, 3, 6, 8, 11]], [[1, 3, 7, 11], [1, 3, 7, 9, 11]],
                          [[1, 3, 8, 11], [1, 3, 6, 8, 11]], [[1, 3, 9, 11], [1, 3, 6, 9, 11]],
                          [[1, 4, 6, 11], [1, 4, 6, 9, 11]], [[1, 4, 7, 11], [1, 4, 7, 9, 11]],
                          [[1, 4, 8, 11], [1, 4, 6, 8, 11]], [[1, 4, 9, 11], [1, 4, 6, 9, 11]],
                          [[1, 5, 7, 11], [0, 4, 6, 8, 10]], [[1, 5, 8, 11], [1, 3, 5, 8, 11]],
                          [[1, 5, 9, 11], [1, 5, 7, 9, 11]], [[1, 6, 8, 11], [1, 3, 6, 8, 11]],
                          [[1, 6, 9, 11], [1, 4, 6, 9, 11]], [[1, 7, 9, 11], [1, 4, 7, 9, 11]],
                          [[1, 3, 5, 7, 11], [0, 2, 4, 6, 8]], [[1, 3, 5, 8, 11], [0, 2, 4, 7, 10]],
                          [[1, 3, 5, 9, 11], [1, 3, 7, 9, 11]], [[1, 3, 6, 8, 11], [1, 4, 6, 8, 11]],
                          [[1, 3, 6, 9, 11], [0, 2, 5, 8, 10]], [[1, 3, 7, 9, 11], [1, 3, 6, 9, 11]],
                          [[1, 4, 6, 8, 11], [1, 4, 6, 9, 11]], [[1, 4, 6, 9, 11], [2, 4, 6, 9, 11]],
                          [[1, 4, 7, 9, 11], [2, 4, 7, 9, 11]], [[1, 5, 7, 9, 11], [2, 4, 7, 9, 11]],
                          [[1, 3, 5, 7, 9, 11], [0, 2, 4, 6, 8, 10]], [[2], [2, 9]], [[2, 4], [2, 6, 9]],
                          [[2, 5], [2, 5, 9]], [[2, 6], [2, 6, 9]], [[2, 4, 6], [2, 4, 6, 9]],
                          [[2, 7], [2, 7, 11]], [[2, 4, 7], [2, 4, 7, 11]], [[2, 5, 7], [2, 5, 7, 11]],
                          [[2, 8], [4, 8, 11]], [[2, 4, 8], [2, 4, 8, 11]], [[2, 5, 8], [2, 5, 8, 10]],
                          [[2, 6, 8], [2, 6, 8, 11]], [[2, 4, 6, 8], [2, 4, 6, 8, 11]],
                          [[2, 9], [2, 6, 9]], [[2, 4, 9], [2, 4, 6, 9]], [[2, 5, 9], [0, 2, 5, 9]],
                          [[2, 6, 9], [2, 6, 9, 11]], [[2, 7, 9], [2, 7, 9, 11]],
                          [[2, 4, 6, 9], [2, 4, 6, 9, 11]], [[2, 4, 7, 9], [2, 4, 7, 9, 11]],
                          [[2, 5, 7, 9], [0, 2, 5, 7, 9]], [[2, 10], [2, 5, 10]],
                          [[2, 4, 10], [2, 4, 7, 10]], [[2, 5, 10], [2, 5, 7, 10]],
                          [[2, 6, 10], [1, 4, 6, 10]], [[2, 7, 10], [2, 5, 7, 10]],
                          [[2, 8, 10], [2, 5, 8, 10]], [[2, 4, 6, 10], [0, 2, 4, 6, 10]],
                          [[2, 4, 7, 10], [0, 2, 4, 7, 10]], [[2, 4, 8, 10], [2, 4, 7, 9, 11]],
                          [[2, 5, 7, 10], [0, 2, 5, 7, 10]], [[2, 5, 8, 10], [0, 2, 5, 8, 10]],
                          [[2, 6, 8, 10], [1, 3, 5, 7, 10]], [[2, 4, 6, 8, 10], [0, 2, 6, 8, 10]],
                          [[2, 11], [2, 7, 11]], [[2, 4, 11], [2, 4, 8, 11]],
                          [[2, 5, 11], [2, 5, 7, 11]], [[2, 6, 11], [2, 6, 9, 11]],
                          [[2, 7, 11], [2, 4, 7, 11]], [[2, 8, 11], [2, 4, 8, 11]],
                          [[2, 9, 11], [2, 6, 9, 11]], [[2, 4, 6, 11], [2, 4, 6, 9, 11]],
                          [[2, 4, 7, 11], [2, 4, 7, 9, 11]], [[2, 4, 8, 11], [2, 4, 6, 8, 11]],
                          [[2, 4, 9, 11], [2, 4, 7, 9, 11]], [[2, 5, 7, 11], [2, 5, 7, 9, 11]],
                          [[2, 5, 8, 11], [1, 3, 5, 8, 11]], [[2, 5, 9, 11], [2, 5, 7, 9, 11]],
                          [[2, 6, 8, 11], [2, 4, 6, 8, 11]], [[2, 6, 9, 11], [2, 4, 6, 9, 11]],
                          [[2, 7, 9, 11], [2, 4, 7, 9, 11]], [[2, 4, 6, 8, 11], [2, 4, 6, 9, 11]],
                          [[2, 4, 6, 9, 11], [2, 4, 7, 9, 11]], [[2, 4, 7, 9, 11], [0, 2, 4, 7, 9]],
                          [[2, 5, 7, 9, 11], [2, 4, 7, 9, 11]], [[3], [3, 10]], [[3, 5], [3, 7, 10]],
                          [[3, 6], [3, 6, 11]], [[3, 7], [3, 7, 10]], [[3, 5, 7], [3, 5, 7, 10]],
                          [[3, 8], [0, 3, 8]], [[3, 5, 8], [0, 3, 5, 8]], [[3, 6, 8], [0, 3, 6, 8]],
                          [[3, 9], [0, 3, 9]], [[3, 5, 9], [0, 3, 5, 9]], [[3, 6, 9], [3, 6, 9, 11]],
                          [[3, 7, 9], [0, 3, 7, 9]], [[3, 5, 7, 9], [0, 3, 5, 7, 9]],
                          [[3, 10], [3, 7, 10]], [[3, 5, 10], [3, 5, 7, 10]],
                          [[3, 6, 10], [1, 3, 6, 10]], [[3, 7, 10], [0, 3, 7, 10]],
                          [[3, 8, 10], [0, 3, 8, 10]], [[3, 5, 7, 10], [0, 3, 5, 7, 10]],
                          [[3, 5, 8, 10], [0, 3, 5, 8, 10]], [[3, 6, 8, 10], [1, 3, 6, 8, 10]],
                          [[3, 11], [3, 6, 11]], [[3, 5, 11], [3, 5, 8, 11]],
                          [[3, 6, 11], [3, 6, 9, 11]], [[3, 7, 11], [2, 5, 7, 11]],
                          [[3, 8, 11], [3, 6, 8, 11]], [[3, 9, 11], [3, 6, 9, 11]],
                          [[3, 5, 7, 11], [3, 5, 7, 9, 11]], [[3, 5, 8, 11], [1, 3, 5, 8, 11]],
                          [[3, 5, 9, 11], [3, 5, 7, 9, 11]], [[3, 6, 8, 11], [1, 3, 6, 8, 11]],
                          [[3, 6, 9, 11], [1, 3, 6, 9, 11]], [[3, 7, 9, 11], [2, 4, 7, 9, 11]],
                          [[3, 5, 7, 9, 11], [2, 5, 7, 9, 11]], [[4], [4, 11]], [[4, 6], [4, 7, 11]],
                          [[4, 7], [0, 4, 7]], [[4, 8], [4, 8, 11]], [[4, 6, 8], [4, 6, 8, 11]],
                          [[4, 9], [1, 4, 9]], [[4, 6, 9], [1, 4, 6, 9]], [[4, 7, 9], [1, 4, 7, 9]],
                          [[4, 10], [4, 7, 10]], [[4, 6, 10], [1, 4, 6, 10]],
                          [[4, 7, 10], [0, 4, 7, 10]], [[4, 8, 10], [1, 4, 8, 10]],
                          [[4, 6, 8, 10], [1, 4, 6, 8, 10]], [[4, 11], [4, 8, 11]],
                          [[4, 6, 11], [4, 6, 8, 11]], [[4, 7, 11], [2, 4, 7, 11]],
                          [[4, 8, 11], [2, 4, 8, 11]], [[4, 9, 11], [2, 4, 9, 11]],
                          [[4, 6, 8, 11], [1, 4, 6, 8, 11]], [[4, 6, 9, 11], [2, 4, 6, 9, 11]],
                          [[4, 7, 9, 11], [2, 4, 7, 9, 11]], [[5], [0, 5, 9]], [[5, 7], [0, 4, 7]],
                          [[5, 8], [0, 5, 8]], [[5, 9], [0, 5, 9]], [[5, 7, 9], [0, 4, 7, 9]],
                          [[5, 10], [2, 5, 10]], [[5, 7, 10], [2, 5, 7, 10]],
                          [[5, 8, 10], [2, 5, 8, 10]], [[5, 11], [0, 5, 9]], [[5, 7, 11], [2, 5, 7, 11]],
                          [[5, 8, 11], [1, 5, 8, 11]], [[5, 9, 11], [2, 5, 9, 11]],
                          [[5, 7, 9, 11], [2, 5, 7, 9, 11]], [[6], [1, 6]], [[6, 8], [1, 5, 8]],
                          [[6, 9], [2, 6, 9]], [[6, 10], [1, 6, 10]], [[6, 8, 10], [1, 5, 8, 10]],
                          [[6, 11], [3, 6, 11]], [[6, 8, 11], [3, 6, 8, 11]],
                          [[6, 9, 11], [3, 6, 9, 11]], [[7], [2, 7, 11]], [[7, 9], [2, 6, 9]],
                          [[7, 10], [2, 7, 10]], [[7, 11], [2, 7, 11]], [[7, 9, 11], [2, 7, 9, 11]],
                          [[8], [3, 8]], [[8, 10], [3, 7, 10]], [[8, 11], [4, 8, 11]], [[9], [4, 9]],
                          [[9, 11], [4, 8, 11]], [[10], [2, 5, 10]], [[11], [6, 11]]]

###################################################################################

ALL_CHORDS_PAIRS_FILTERED = [[[0], [0, 4, 7]], [[0, 3], [0, 3, 7]], [[0, 3, 5], [0, 3, 5, 9]],
                            [[0, 3, 5, 8], [0, 3, 7, 10]], [[0, 3, 5, 9], [0, 3, 7, 10]],
                            [[0, 3, 5, 10], [0, 3, 5, 9]], [[0, 3, 7], [0, 3, 7, 10]],
                            [[0, 3, 7, 10], [0, 3, 5, 9]], [[0, 3, 8], [0, 3, 5, 8]],
                            [[0, 3, 9], [0, 3, 5, 9]], [[0, 3, 10], [0, 3, 7, 10]], [[0, 4], [0, 4, 7]],
                            [[0, 4, 6], [0, 4, 6, 9]], [[0, 4, 6, 9], [1, 4, 6, 9]],
                            [[0, 4, 6, 10], [0, 4, 7, 10]], [[0, 4, 7], [0, 4, 7, 10]],
                            [[0, 4, 7, 10], [1, 4, 7, 10]], [[0, 4, 8], [0, 4, 7, 10]],
                            [[0, 4, 9], [0, 4, 6, 9]], [[0, 4, 10], [0, 4, 7, 10]], [[0, 5], [0, 5, 9]],
                            [[0, 5, 8], [0, 3, 5, 8]], [[0, 5, 9], [0, 3, 5, 9]],
                            [[0, 5, 10], [0, 3, 5, 10]], [[0, 6], [0, 6, 9]], [[0, 6, 9], [0, 4, 6, 9]],
                            [[0, 6, 10], [0, 4, 7, 10]], [[0, 7], [0, 4, 7]], [[0, 7, 10], [0, 4, 7, 10]],
                            [[0, 8], [0, 3, 8]], [[0, 9], [0, 4, 9]], [[0, 10], [2, 5, 10]], [[1], [1, 8]],
                            [[1, 4], [1, 4, 9]], [[1, 4, 6], [1, 4, 6, 9]], [[1, 4, 6, 9], [1, 4, 8, 11]],
                            [[1, 4, 6, 10], [0, 3, 5, 9]], [[1, 4, 6, 11], [1, 4, 6, 9]],
                            [[1, 4, 7], [1, 4, 7, 10]], [[1, 4, 7, 10], [0, 4, 7, 10]],
                            [[1, 4, 7, 11], [1, 4, 6, 10]], [[1, 4, 8], [1, 4, 8, 11]],
                            [[1, 4, 8, 11], [1, 4, 6, 9]], [[1, 4, 9], [1, 4, 6, 9]],
                            [[1, 4, 10], [1, 4, 6, 10]], [[1, 4, 11], [1, 4, 8, 11]], [[1, 5], [1, 5, 8]],
                            [[1, 5, 8], [1, 5, 8, 11]], [[1, 5, 8, 11], [2, 5, 8, 11]],
                            [[1, 5, 9], [0, 3, 5, 9]], [[1, 5, 10], [0, 4, 7, 10]],
                            [[1, 5, 11], [1, 5, 8, 11]], [[1, 6], [1, 6, 10]], [[1, 6, 9], [1, 4, 6, 9]],
                            [[1, 6, 10], [1, 4, 6, 10]], [[1, 6, 11], [1, 4, 6, 11]], [[1, 7], [1, 4, 7]],
                            [[1, 7, 10], [1, 4, 7, 10]], [[1, 7, 11], [1, 4, 7, 11]], [[1, 8], [1, 5, 8]],
                            [[1, 8, 11], [1, 4, 8, 11]], [[1, 9], [1, 4, 9]], [[1, 10], [1, 5, 10]],
                            [[1, 11], [2, 6, 11]], [[2], [2, 9]], [[2, 5], [2, 5, 9]],
                            [[2, 5, 8], [2, 5, 8, 11]], [[2, 5, 8, 11], [1, 4, 7, 10]],
                            [[2, 5, 9], [0, 3, 5, 9]], [[2, 5, 10], [0, 3, 5, 9]],
                            [[2, 5, 11], [2, 5, 8, 11]], [[2, 6], [2, 6, 9]], [[2, 6, 9], [1, 4, 6, 9]],
                            [[2, 6, 10], [1, 4, 6, 10]], [[2, 6, 11], [1, 4, 6, 10]], [[2, 7], [2, 7, 11]],
                            [[2, 7, 10], [0, 4, 7, 10]], [[2, 7, 11], [1, 4, 6, 9]], [[2, 8], [4, 8, 11]],
                            [[2, 8, 11], [2, 5, 8, 11]], [[2, 9], [2, 6, 9]], [[2, 10], [2, 5, 10]],
                            [[2, 11], [2, 7, 11]], [[3], [3, 10]], [[3, 5], [3, 7, 10]],
                            [[3, 5, 8], [0, 3, 5, 8]], [[3, 5, 8, 11], [2, 5, 8, 11]],
                            [[3, 5, 9], [0, 3, 5, 9]], [[3, 5, 10], [0, 3, 5, 10]],
                            [[3, 5, 11], [3, 5, 8, 11]], [[3, 7], [3, 7, 10]], [[3, 7, 10], [0, 3, 7, 10]],
                            [[3, 7, 11], [0, 3, 7, 10]], [[3, 8], [0, 3, 8]], [[3, 8, 11], [3, 5, 8, 11]],
                            [[3, 9], [0, 3, 9]], [[3, 10], [3, 7, 10]], [[3, 11], [3, 8, 11]],
                            [[4], [4, 11]], [[4, 6], [4, 7, 11]], [[4, 6, 9], [1, 4, 6, 9]],
                            [[4, 6, 10], [1, 4, 6, 10]], [[4, 6, 11], [1, 4, 6, 11]], [[4, 7], [0, 4, 7]],
                            [[4, 7, 10], [0, 4, 7, 10]], [[4, 7, 11], [1, 4, 7, 11]], [[4, 8], [4, 8, 11]],
                            [[4, 8, 11], [1, 4, 8, 11]], [[4, 9], [1, 4, 9]], [[4, 10], [4, 7, 10]],
                            [[4, 11], [4, 8, 11]], [[5], [0, 5, 9]], [[5, 8], [0, 5, 8]],
                            [[5, 8, 11], [1, 5, 8, 11]], [[5, 9], [0, 5, 9]], [[5, 10], [2, 5, 10]],
                            [[5, 11], [0, 5, 9]], [[6], [1, 6]], [[6, 9], [2, 6, 9]],
                            [[6, 10], [1, 6, 10]], [[6, 11], [2, 6, 11]], [[7], [2, 7, 11]],
                            [[7, 10], [2, 7, 10]], [[7, 11], [2, 7, 11]], [[8], [3, 8]],
                            [[8, 11], [4, 8, 11]], [[9], [4, 9]], [[10], [2, 5, 10]], [[11], [6, 11]]]

###################################################################################

ALL_CHORDS_TRIPLETS_SORTED = [[[0], [0, 4, 7], [0]], [[0, 2], [0, 4, 7], [0]], [[0, 3], [0, 3, 7], [0]],
                              [[0, 4], [0, 4, 7], [0, 4]], [[0, 2, 4], [0, 2, 4, 7], [0]],
                              [[0, 5], [0, 5, 9], [0, 5]], [[0, 2, 5], [0, 2, 5, 9], [0, 2, 5]],
                              [[0, 3, 5], [0, 3, 5, 9], [0, 3, 5]], [[0, 6], [0, 2, 6, 9], [2]],
                              [[0, 2, 6], [0, 2, 6, 9], [0, 2, 6]], [[0, 3, 6], [0, 3, 6, 8], [0, 3, 6]],
                              [[0, 4, 6], [0, 4, 6, 9], [0, 4, 6]],
                              [[0, 2, 4, 6], [0, 2, 4, 6, 9], [0, 2, 4, 6]], [[0, 7], [0, 4, 7], [0, 7]],
                              [[0, 2, 7], [0, 2, 4, 7], [0, 2, 7]], [[0, 3, 7], [0, 3, 7, 10], [0, 3, 7]],
                              [[0, 4, 7], [0, 4, 7, 9], [0, 4, 7]], [[0, 5, 7], [0, 5, 7, 9], [0, 5, 7]],
                              [[0, 2, 4, 7], [0, 2, 4, 7, 9], [0, 2, 4, 7]],
                              [[0, 2, 5, 7], [0, 2, 5, 7, 9], [0, 2, 5, 7]],
                              [[0, 3, 5, 7], [0, 3, 5, 7, 10], [0, 3, 5, 7]], [[0, 8], [0, 3, 8], [8]],
                              [[0, 2, 8], [0, 2, 5, 8], [0, 2, 8]], [[0, 3, 8], [0, 3, 5, 8], [0, 3, 8]],
                              [[0, 4, 8], [2, 4, 8, 11], [0, 4, 9]], [[0, 5, 8], [0, 3, 5, 8], [0, 5, 8]],
                              [[0, 6, 8], [0, 3, 6, 8], [0, 6, 8]],
                              [[0, 2, 4, 8], [0, 2, 4, 6, 8], [0, 2, 4, 8]],
                              [[0, 2, 5, 8], [0, 2, 5, 8, 10], [0, 2, 5, 8]],
                              [[0, 2, 6, 8], [0, 2, 6, 8, 10], [0, 2, 6, 8]],
                              [[0, 3, 5, 8], [0, 3, 5, 8, 10], [0, 3, 5, 8]],
                              [[0, 3, 6, 8], [0, 3, 6, 8, 10], [0, 3, 6, 8]],
                              [[0, 4, 6, 8], [2, 4, 6, 8, 11], [2, 6, 8, 11]],
                              [[0, 2, 4, 6, 8], [2, 4, 6, 8, 11], [2, 6, 8, 11]], [[0, 9], [0, 4, 9], [9]],
                              [[0, 2, 9], [0, 2, 6, 9], [0, 2, 9]], [[0, 3, 9], [0, 3, 5, 9], [0, 3, 9]],
                              [[0, 4, 9], [0, 4, 7, 9], [0, 4, 9]], [[0, 5, 9], [0, 2, 5, 9], [0, 5, 9]],
                              [[0, 6, 9], [0, 2, 6, 9], [0, 6, 9]], [[0, 7, 9], [0, 4, 7, 9], [0, 7, 9]],
                              [[0, 2, 4, 9], [0, 2, 4, 7, 9], [0, 2, 4, 9]],
                              [[0, 2, 5, 9], [0, 2, 5, 7, 9], [0, 2, 5, 9]],
                              [[0, 2, 6, 9], [0, 2, 4, 6, 9], [0, 2, 6, 9]],
                              [[0, 2, 7, 9], [0, 2, 4, 7, 9], [0, 2, 7, 9]],
                              [[0, 3, 5, 9], [0, 3, 5, 7, 9], [0, 3, 5, 9]],
                              [[0, 3, 6, 9], [0, 2, 4, 6, 9], [4, 6, 9]],
                              [[0, 3, 7, 9], [0, 3, 5, 7, 9], [0, 3, 7, 9]],
                              [[0, 4, 6, 9], [0, 2, 4, 6, 9], [0, 4, 6, 9]],
                              [[0, 4, 7, 9], [0, 2, 4, 7, 9], [0, 4, 7, 9]],
                              [[0, 5, 7, 9], [0, 2, 5, 7, 9], [0, 5, 7, 9]],
                              [[0, 2, 4, 6, 9], [2, 4, 6, 9, 11], [0, 2, 4, 6, 9]],
                              [[0, 2, 4, 7, 9], [2, 4, 7, 9, 11], [0, 2, 4, 7, 9]],
                              [[0, 2, 5, 7, 9], [2, 5, 7, 9, 11], [7]],
                              [[0, 3, 5, 7, 9], [2, 4, 6, 8, 11], [1, 4, 6, 8, 10]],
                              [[0, 10], [2, 5, 10], [10]], [[0, 2, 10], [0, 2, 5, 10], [10]],
                              [[0, 3, 10], [0, 3, 7, 10], [0, 3, 10]],
                              [[0, 4, 10], [0, 4, 7, 10], [0, 4, 10]],
                              [[0, 5, 10], [0, 2, 5, 10], [0, 5, 10]],
                              [[0, 6, 10], [0, 3, 6, 10], [0, 6, 10]],
                              [[0, 7, 10], [0, 4, 7, 10], [0, 7, 10]], [[0, 8, 10], [0, 3, 8, 10], [8]],
                              [[0, 2, 4, 10], [0, 2, 4, 7, 10], [0, 4, 10]],
                              [[0, 2, 5, 10], [0, 2, 5, 7, 10], [0, 2, 5, 10]],
                              [[0, 2, 6, 10], [0, 2, 6, 8, 10], [8]],
                              [[0, 2, 7, 10], [0, 2, 5, 7, 10], [2, 7, 10]],
                              [[0, 2, 8, 10], [0, 2, 5, 8, 10], [8, 10]],
                              [[0, 3, 5, 10], [0, 3, 5, 7, 10], [0, 3, 5, 10]],
                              [[0, 3, 6, 10], [0, 3, 6, 8, 10], [0, 3, 6, 10]],
                              [[0, 3, 7, 10], [0, 3, 5, 7, 10], [0, 3, 7, 10]],
                              [[0, 3, 8, 10], [0, 3, 5, 8, 10], [0, 3, 8, 10]],
                              [[0, 4, 6, 10], [0, 2, 4, 6, 10], [2]],
                              [[0, 4, 7, 10], [0, 2, 4, 7, 10], [0, 4, 7, 10]],
                              [[0, 4, 8, 10], [0, 2, 4, 8, 10], [0, 4, 8, 10]],
                              [[0, 5, 7, 10], [0, 3, 5, 7, 10], [0, 5, 7, 10]],
                              [[0, 5, 8, 10], [0, 3, 5, 8, 10], [10]],
                              [[0, 6, 8, 10], [0, 3, 6, 8, 10], [6]],
                              [[0, 2, 4, 6, 10], [0, 2, 4, 8, 10], [0, 2, 6, 8, 10]],
                              [[0, 2, 4, 7, 10], [1, 3, 6, 9, 11], [0, 2, 5, 8, 10]],
                              [[0, 2, 4, 8, 10], [1, 3, 7, 9, 11], [0, 2, 6, 8, 10]],
                              [[0, 2, 5, 7, 10], [0, 3, 5, 7, 10], [5, 10]],
                              [[0, 2, 5, 8, 10], [1, 4, 7, 9, 11], [8]],
                              [[0, 2, 6, 8, 10], [2, 4, 6, 8, 10], [0, 2, 6, 8, 10]],
                              [[0, 3, 5, 7, 10], [0, 2, 5, 7, 10], [9]],
                              [[0, 3, 5, 8, 10], [1, 3, 5, 8, 10], [0, 3, 5, 8, 10]],
                              [[0, 3, 6, 8, 10], [1, 3, 6, 8, 10], [0, 3, 6, 8, 10]],
                              [[0, 4, 6, 8, 10], [0, 2, 4, 6, 9], [1, 3, 5, 8, 10]],
                              [[0, 2, 4, 6, 8, 10], [1, 3, 5, 7, 9, 11], [0, 2, 4, 6, 8, 10]],
                              [[1], [1, 8], [1]], [[1, 3], [1, 5, 8], [1]], [[1, 4], [1, 4, 9], [9]],
                              [[1, 5], [1, 5, 8], [1, 5]], [[1, 3, 5], [1, 3, 5, 10], [1, 3, 5]],
                              [[1, 6], [1, 6, 10], [1, 6]], [[1, 3, 6], [1, 3, 6, 10], [1, 3, 6]],
                              [[1, 4, 6], [1, 4, 6, 9], [1, 4, 6]], [[1, 7], [1, 4, 7], [1, 7]],
                              [[1, 3, 7], [1, 3, 7, 10], [1, 3, 7]], [[1, 4, 7], [1, 4, 7, 9], [1, 4, 7]],
                              [[1, 5, 7], [1, 5, 7, 10], [1, 5, 7]], [[1, 3, 5, 7], [1, 3, 5, 7, 10], [7]],
                              [[1, 8], [1, 5, 8], [1, 8]], [[1, 3, 8], [1, 3, 5, 8], [1, 3, 8]],
                              [[1, 4, 8], [1, 4, 8, 11], [1, 4, 8]], [[1, 5, 8], [1, 5, 8, 10], [1, 5, 8]],
                              [[1, 6, 8], [1, 3, 6, 8], [1, 6, 8]],
                              [[1, 3, 5, 8], [1, 3, 5, 8, 10], [1, 3, 5, 8]],
                              [[1, 3, 6, 8], [1, 3, 6, 8, 10], [1, 3, 6, 8]],
                              [[1, 4, 6, 8], [1, 4, 6, 8, 11], [1, 4, 6, 8]], [[1, 9], [1, 4, 9], [9]],
                              [[1, 3, 9], [1, 3, 6, 9], [1, 3, 9]], [[1, 4, 9], [1, 4, 6, 9], [1, 4, 9]],
                              [[1, 5, 9], [0, 3, 5, 9], [0, 5, 9]], [[1, 6, 9], [1, 4, 6, 9], [1, 6, 9]],
                              [[1, 7, 9], [1, 4, 7, 9], [1, 7, 9]],
                              [[1, 3, 5, 9], [0, 3, 5, 7, 9], [1, 5, 9]],
                              [[1, 3, 6, 9], [1, 3, 6, 9, 11], [1, 3, 6, 9]],
                              [[1, 3, 7, 9], [1, 3, 5, 7, 9], [1, 7]],
                              [[1, 4, 6, 9], [1, 4, 6, 9, 11], [1, 4, 6, 9]],
                              [[1, 4, 7, 9], [1, 4, 7, 9, 11], [1, 4, 7, 9]],
                              [[1, 5, 7, 9], [1, 3, 7, 9, 11], [1, 5, 7, 9]],
                              [[1, 3, 5, 7, 9], [2, 4, 6, 8, 11], [9]], [[1, 10], [1, 5, 10], [10]],
                              [[1, 3, 10], [1, 3, 7, 10], [1, 3, 10]],
                              [[1, 4, 10], [1, 4, 6, 10], [1, 4, 10]],
                              [[1, 5, 10], [1, 5, 8, 10], [1, 5, 10]],
                              [[1, 6, 10], [1, 4, 6, 10], [1, 6, 10]],
                              [[1, 7, 10], [1, 3, 7, 10], [1, 7, 10]], [[1, 8, 10], [1, 5, 8, 10], [10]],
                              [[1, 3, 5, 10], [1, 3, 5, 8, 10], [1, 3, 5, 10]],
                              [[1, 3, 6, 10], [1, 3, 6, 8, 10], [1, 3, 6, 10]],
                              [[1, 3, 7, 10], [1, 3, 5, 7, 10], [1, 3, 7, 10]],
                              [[1, 3, 8, 10], [1, 3, 5, 8, 10], [1, 3, 8, 10]],
                              [[1, 4, 6, 10], [1, 4, 6, 8, 10], [1, 4, 6, 10]],
                              [[1, 4, 7, 10], [0, 2, 4, 7, 10], [0, 4, 7, 10]],
                              [[1, 4, 8, 10], [1, 4, 6, 8, 10], [1, 4, 8, 10]],
                              [[1, 5, 7, 10], [1, 3, 5, 7, 10], [1, 5, 7, 10]],
                              [[1, 5, 8, 10], [1, 3, 5, 8, 10], [1, 5, 8, 10]],
                              [[1, 6, 8, 10], [1, 3, 6, 8, 10], [1, 6, 8, 10]],
                              [[1, 3, 5, 7, 10], [2, 4, 6, 8, 11], [0, 3, 5, 7, 9]],
                              [[1, 3, 5, 8, 10], [0, 3, 5, 8, 10], [6, 8, 10]],
                              [[1, 3, 6, 8, 10], [0, 3, 6, 8, 10], [8]],
                              [[1, 4, 6, 8, 10], [0, 3, 5, 7, 9], [2, 4, 6, 8, 11]],
                              [[1, 11], [2, 6, 11], [11]], [[1, 3, 11], [1, 3, 6, 11], [11]],
                              [[1, 4, 11], [1, 4, 8, 11], [1]], [[1, 5, 11], [1, 5, 8, 11], [1, 5, 11]],
                              [[1, 6, 11], [1, 4, 6, 11], [1, 6, 11]],
                              [[1, 7, 11], [1, 4, 7, 11], [1, 7, 11]],
                              [[1, 8, 11], [1, 4, 8, 11], [1, 8, 11]], [[1, 9, 11], [1, 4, 9, 11], [9]],
                              [[1, 3, 5, 11], [1, 3, 5, 8, 11], [1, 3, 5, 11]],
                              [[1, 3, 6, 11], [1, 3, 6, 8, 11], [1, 3, 6, 11]],
                              [[1, 3, 7, 11], [1, 3, 7, 9, 11], [0]],
                              [[1, 3, 8, 11], [1, 3, 6, 8, 11], [1, 3, 8, 11]],
                              [[1, 3, 9, 11], [1, 3, 6, 9, 11], [1, 3, 9, 11]],
                              [[1, 4, 6, 11], [1, 4, 6, 9, 11], [1, 4, 6, 11]],
                              [[1, 4, 7, 11], [1, 4, 7, 9, 11], [1, 4, 7, 11]],
                              [[1, 4, 8, 11], [1, 4, 6, 8, 11], [1, 4, 8, 11]],
                              [[1, 4, 9, 11], [1, 4, 6, 9, 11], [1, 4, 9, 11]],
                              [[1, 5, 7, 11], [0, 4, 6, 8, 10], [5, 7, 9, 11]],
                              [[1, 5, 8, 11], [1, 3, 5, 8, 11], [1, 5, 8, 11]],
                              [[1, 5, 9, 11], [1, 5, 7, 9, 11], [9]],
                              [[1, 6, 8, 11], [1, 3, 6, 8, 11], [1, 6, 8, 11]],
                              [[1, 6, 9, 11], [1, 4, 6, 9, 11], [1, 6, 9, 11]],
                              [[1, 7, 9, 11], [1, 4, 7, 9, 11], [1, 7, 9, 11]],
                              [[1, 3, 5, 7, 11], [0, 2, 4, 6, 8], [7, 9]],
                              [[1, 3, 5, 8, 11], [0, 2, 4, 7, 10], [1, 3, 6, 9, 11]],
                              [[1, 3, 5, 9, 11], [1, 3, 7, 9, 11], [0, 2, 6, 8, 10]],
                              [[1, 3, 6, 8, 11], [1, 4, 6, 8, 11], [6, 8, 11]],
                              [[1, 3, 6, 9, 11], [0, 2, 5, 8, 10], [1, 4, 7, 9, 11]],
                              [[1, 3, 7, 9, 11], [1, 3, 6, 9, 11], [11]],
                              [[1, 4, 6, 8, 11], [1, 4, 6, 9, 11], [9, 11]],
                              [[1, 4, 6, 9, 11], [2, 4, 6, 9, 11], [1, 4, 6, 9, 11]],
                              [[1, 4, 7, 9, 11], [2, 4, 7, 9, 11], [7, 9, 11]],
                              [[1, 5, 7, 9, 11], [2, 4, 7, 9, 11], [5, 7, 9]],
                              [[1, 3, 5, 7, 9, 11], [0, 2, 4, 6, 8, 10], [1, 3, 5, 7, 9, 11]],
                              [[2], [2, 9], [2]], [[2, 4], [2, 6, 9], [2]], [[2, 5], [2, 5, 9], [2]],
                              [[2, 6], [2, 6, 9], [2]], [[2, 4, 6], [2, 4, 6, 9], [2, 4, 6]],
                              [[2, 7], [2, 7, 11], [2, 7]], [[2, 4, 7], [2, 4, 7, 11], [2, 4, 7]],
                              [[2, 5, 7], [2, 5, 7, 11], [2, 5, 7]], [[2, 8], [4, 8, 11], [4]],
                              [[2, 4, 8], [2, 4, 8, 11], [2, 4, 8]], [[2, 5, 8], [2, 5, 8, 10], [2, 5, 8]],
                              [[2, 6, 8], [2, 6, 8, 11], [2, 6, 8]],
                              [[2, 4, 6, 8], [2, 4, 6, 8, 11], [2, 4, 6, 8]], [[2, 9], [2, 6, 9], [2, 9]],
                              [[2, 4, 9], [2, 4, 6, 9], [2, 4, 9]], [[2, 5, 9], [0, 2, 5, 9], [2, 5, 9]],
                              [[2, 6, 9], [2, 6, 9, 11], [2, 6, 9]], [[2, 7, 9], [2, 7, 9, 11], [2, 7, 9]],
                              [[2, 4, 6, 9], [2, 4, 6, 9, 11], [2, 4, 6, 9]],
                              [[2, 4, 7, 9], [2, 4, 7, 9, 11], [2, 4, 7, 9]],
                              [[2, 5, 7, 9], [0, 2, 5, 7, 9], [2, 5, 7, 9]], [[2, 10], [2, 5, 10], [10]],
                              [[2, 4, 10], [2, 4, 7, 10], [2, 4, 10]],
                              [[2, 5, 10], [2, 5, 7, 10], [2, 5, 10]],
                              [[2, 6, 10], [1, 4, 6, 10], [1, 6, 10]],
                              [[2, 7, 10], [2, 5, 7, 10], [2, 7, 10]],
                              [[2, 8, 10], [2, 5, 8, 10], [2, 8, 10]],
                              [[2, 4, 6, 10], [0, 2, 4, 6, 10], [2, 4, 6, 10]],
                              [[2, 4, 7, 10], [0, 2, 4, 7, 10], [2, 4, 7, 10]],
                              [[2, 4, 8, 10], [2, 4, 7, 9, 11], [2, 4, 7, 11]],
                              [[2, 5, 7, 10], [0, 2, 5, 7, 10], [2, 5, 7, 10]],
                              [[2, 5, 8, 10], [0, 2, 5, 8, 10], [2, 5, 8, 10]],
                              [[2, 6, 8, 10], [1, 3, 5, 7, 10], [1, 7]],
                              [[2, 4, 6, 8, 10], [0, 2, 6, 8, 10], [2, 4, 6, 8, 10]],
                              [[2, 11], [2, 7, 11], [7]], [[2, 4, 11], [2, 4, 8, 11], [2, 4, 11]],
                              [[2, 5, 11], [2, 5, 7, 11], [2, 5, 11]],
                              [[2, 6, 11], [2, 6, 9, 11], [2, 6, 11]],
                              [[2, 7, 11], [2, 4, 7, 11], [2, 7, 11]],
                              [[2, 8, 11], [2, 4, 8, 11], [2, 8, 11]],
                              [[2, 9, 11], [2, 6, 9, 11], [2, 9, 11]],
                              [[2, 4, 6, 11], [2, 4, 6, 9, 11], [2, 4, 6, 11]],
                              [[2, 4, 7, 11], [2, 4, 7, 9, 11], [2, 4, 7, 11]],
                              [[2, 4, 8, 11], [2, 4, 6, 8, 11], [2, 4, 8, 11]],
                              [[2, 4, 9, 11], [2, 4, 7, 9, 11], [2, 4, 9, 11]],
                              [[2, 5, 7, 11], [2, 5, 7, 9, 11], [2, 5, 7, 11]],
                              [[2, 5, 8, 11], [1, 3, 5, 8, 11], [1, 5, 8, 11]],
                              [[2, 5, 9, 11], [2, 5, 7, 9, 11], [2, 5, 9, 11]],
                              [[2, 6, 8, 11], [2, 4, 6, 8, 11], [2, 6, 8, 11]],
                              [[2, 6, 9, 11], [2, 4, 6, 9, 11], [2, 6, 9, 11]],
                              [[2, 7, 9, 11], [2, 4, 7, 9, 11], [2, 7, 9, 11]],
                              [[2, 4, 6, 8, 11], [2, 4, 6, 9, 11], [2, 4, 6, 8, 11]],
                              [[2, 4, 6, 9, 11], [2, 4, 7, 9, 11], [2, 7, 9]],
                              [[2, 4, 7, 9, 11], [0, 2, 4, 7, 9], [11]],
                              [[2, 5, 7, 9, 11], [2, 4, 7, 9, 11], [2, 7, 9, 11]], [[3], [3, 10], [3]],
                              [[3, 5], [3, 7, 10], [3]], [[3, 6], [3, 6, 11], [11]],
                              [[3, 7], [3, 7, 10], [3]], [[3, 5, 7], [3, 5, 7, 10], [3, 5, 7]],
                              [[3, 8], [0, 3, 8], [3, 8]], [[3, 5, 8], [0, 3, 5, 8], [8]],
                              [[3, 6, 8], [0, 3, 6, 8], [3, 6, 8]], [[3, 9], [0, 3, 9], [3, 9]],
                              [[3, 5, 9], [0, 3, 5, 9], [3, 5, 9]], [[3, 6, 9], [3, 6, 9, 11], [3, 6, 9]],
                              [[3, 7, 9], [0, 3, 7, 9], [3, 7, 9]],
                              [[3, 5, 7, 9], [0, 3, 5, 7, 9], [0, 3, 5, 9]], [[3, 10], [3, 7, 10], [3, 10]],
                              [[3, 5, 10], [3, 5, 7, 10], [3, 5, 10]],
                              [[3, 6, 10], [1, 3, 6, 10], [3, 6, 10]],
                              [[3, 7, 10], [0, 3, 7, 10], [3, 7, 10]],
                              [[3, 8, 10], [0, 3, 8, 10], [3, 8, 10]],
                              [[3, 5, 7, 10], [0, 3, 5, 7, 10], [3, 5, 7, 10]],
                              [[3, 5, 8, 10], [0, 3, 5, 8, 10], [3, 5, 8, 10]],
                              [[3, 6, 8, 10], [1, 3, 6, 8, 10], [3, 6, 8, 10]], [[3, 11], [3, 6, 11], [11]],
                              [[3, 5, 11], [3, 5, 8, 11], [3, 5, 11]],
                              [[3, 6, 11], [3, 6, 9, 11], [3, 6, 11]],
                              [[3, 7, 11], [2, 5, 7, 11], [2, 7, 11]],
                              [[3, 8, 11], [3, 6, 8, 11], [3, 8, 11]],
                              [[3, 9, 11], [3, 6, 9, 11], [3, 9, 11]],
                              [[3, 5, 7, 11], [3, 5, 7, 9, 11], [3, 5, 7, 11]],
                              [[3, 5, 8, 11], [1, 3, 5, 8, 11], [3, 5, 8, 11]],
                              [[3, 5, 9, 11], [3, 5, 7, 9, 11], [5, 7, 9, 11]],
                              [[3, 6, 8, 11], [1, 3, 6, 8, 11], [3, 6, 8, 11]],
                              [[3, 6, 9, 11], [1, 3, 6, 9, 11], [3, 6, 9, 11]],
                              [[3, 7, 9, 11], [2, 4, 7, 9, 11], [7, 9, 11]],
                              [[3, 5, 7, 9, 11], [2, 5, 7, 9, 11], [2, 5, 7, 11]], [[4], [4, 11], [4]],
                              [[4, 6], [4, 7, 11], [4]], [[4, 7], [0, 4, 7], [0]], [[4, 8], [4, 8, 11], [4]],
                              [[4, 6, 8], [4, 6, 8, 11], [4]], [[4, 9], [1, 4, 9], [4, 9]],
                              [[4, 6, 9], [1, 4, 6, 9], [4, 6, 9]], [[4, 7, 9], [1, 4, 7, 9], [4, 7, 9]],
                              [[4, 10], [4, 7, 10], [4, 10]], [[4, 6, 10], [1, 4, 6, 10], [4, 6, 10]],
                              [[4, 7, 10], [0, 4, 7, 10], [4, 7, 10]], [[4, 8, 10], [1, 4, 8, 10], [1]],
                              [[4, 6, 8, 10], [1, 4, 6, 8, 10], [6]], [[4, 11], [4, 8, 11], [4, 11]],
                              [[4, 6, 11], [4, 6, 8, 11], [4, 6, 11]],
                              [[4, 7, 11], [2, 4, 7, 11], [4, 7, 11]],
                              [[4, 8, 11], [2, 4, 8, 11], [4, 8, 11]],
                              [[4, 9, 11], [2, 4, 9, 11], [4, 9, 11]],
                              [[4, 6, 8, 11], [1, 4, 6, 8, 11], [4, 6, 8, 11]],
                              [[4, 6, 9, 11], [2, 4, 6, 9, 11], [4, 6, 9, 11]],
                              [[4, 7, 9, 11], [2, 4, 7, 9, 11], [4, 7, 9, 11]], [[5], [0, 5, 9], [5]],
                              [[5, 7], [0, 4, 7], [0]], [[5, 8], [0, 5, 8], [5]], [[5, 9], [0, 5, 9], [5]],
                              [[5, 7, 9], [0, 4, 7, 9], [5]], [[5, 10], [2, 5, 10], [5, 10]],
                              [[5, 7, 10], [2, 5, 7, 10], [7]], [[5, 8, 10], [2, 5, 8, 10], [5, 8, 10]],
                              [[5, 11], [0, 5, 9], [5]], [[5, 7, 11], [2, 5, 7, 11], [5, 7, 11]],
                              [[5, 8, 11], [1, 5, 8, 11], [5, 8, 11]],
                              [[5, 9, 11], [2, 5, 9, 11], [5, 9, 11]],
                              [[5, 7, 9, 11], [2, 5, 7, 9, 11], [5, 7, 9]], [[6], [1, 6], [6]],
                              [[6, 8], [1, 5, 8], [8]], [[6, 9], [2, 6, 9], [2]], [[6, 10], [1, 6, 10], [6]],
                              [[6, 8, 10], [1, 5, 8, 10], [6, 8, 10]], [[6, 11], [3, 6, 11], [6, 11]],
                              [[6, 8, 11], [3, 6, 8, 11], [6, 8, 11]],
                              [[6, 9, 11], [3, 6, 9, 11], [6, 9, 11]], [[7], [2, 7, 11], [7]],
                              [[7, 9], [2, 6, 9], [2]], [[7, 10], [2, 7, 10], [7]],
                              [[7, 11], [2, 7, 11], [7]], [[7, 9, 11], [2, 7, 9, 11], [7, 9, 11]],
                              [[8], [3, 8], [8]], [[8, 10], [3, 7, 10], [3]], [[8, 11], [4, 8, 11], [4]],
                              [[9], [4, 9], [9]], [[9, 11], [4, 8, 11], [4]], [[10], [2, 5, 10], [10]],
                              [[11], [6, 11], [11]]]

###################################################################################

ALL_CHORDS_TRIPLETS_FILTERED = [[[0], [0, 4, 7], [7]], [[0, 3], [0, 3, 7], [0]],
                                [[0, 3, 5], [0, 3, 5, 9], [5]], [[0, 3, 5, 8], [0, 3, 7, 10], [0]],
                                [[0, 3, 5, 9], [0, 3, 7, 10], [10]], [[0, 3, 5, 10], [0, 3, 5, 9], [5]],
                                [[0, 3, 7], [0, 3, 7, 10], [0]], [[0, 3, 7, 10], [0, 3, 5, 9], [2, 5, 10]],
                                [[0, 3, 8], [0, 3, 5, 8], [8]], [[0, 3, 9], [0, 3, 5, 9], [5]],
                                [[0, 3, 10], [0, 3, 7, 10], [0]], [[0, 4], [0, 4, 7], [0]],
                                [[0, 4, 6], [0, 4, 6, 9], [4]], [[0, 4, 6, 9], [1, 4, 6, 9], [9]],
                                [[0, 4, 6, 10], [0, 4, 7, 10], [0, 4, 10]], [[0, 4, 7], [0, 4, 7, 10], [0]],
                                [[0, 4, 7, 10], [1, 4, 7, 10], [0]], [[0, 4, 8], [0, 4, 7, 10], [0, 5, 8]],
                                [[0, 4, 9], [0, 4, 6, 9], [9]], [[0, 4, 10], [0, 4, 7, 10], [0]],
                                [[0, 5], [0, 5, 9], [5]], [[0, 5, 8], [0, 3, 5, 8], [5]],
                                [[0, 5, 9], [0, 3, 5, 9], [5]], [[0, 5, 10], [0, 3, 5, 10], [10]],
                                [[0, 6], [0, 6, 9], [9]], [[0, 6, 9], [0, 4, 6, 9], [6]],
                                [[0, 6, 10], [0, 4, 7, 10], [10]], [[0, 7], [0, 4, 7], [0]],
                                [[0, 7, 10], [0, 4, 7, 10], [0]], [[0, 8], [0, 3, 8], [8]],
                                [[0, 9], [0, 4, 9], [9]], [[0, 10], [2, 5, 10], [10]], [[1], [1, 8], [8]],
                                [[1, 4], [1, 4, 9], [9]], [[1, 4, 6], [1, 4, 6, 9], [6]],
                                [[1, 4, 6, 9], [1, 4, 8, 11], [4]], [[1, 4, 6, 10], [0, 3, 5, 9], [5]],
                                [[1, 4, 6, 11], [1, 4, 6, 9], [6]], [[1, 4, 7], [1, 4, 7, 10], [10]],
                                [[1, 4, 7, 10], [0, 4, 7, 10], [0]],
                                [[1, 4, 7, 11], [1, 4, 6, 10], [1, 6, 10]], [[1, 4, 8], [1, 4, 8, 11], [1]],
                                [[1, 4, 8, 11], [1, 4, 6, 9], [1, 4, 9]], [[1, 4, 9], [1, 4, 6, 9], [9]],
                                [[1, 4, 10], [1, 4, 6, 10], [6]], [[1, 4, 11], [1, 4, 8, 11], [1]],
                                [[1, 5], [1, 5, 8], [1]], [[1, 5, 8], [1, 5, 8, 11], [1]],
                                [[1, 5, 8, 11], [2, 5, 8, 11], [1]], [[1, 5, 9], [0, 3, 5, 9], [0, 5, 9]],
                                [[1, 5, 10], [0, 4, 7, 10], [0]], [[1, 5, 11], [1, 5, 8, 11], [11]],
                                [[1, 6], [1, 6, 10], [6]], [[1, 6, 9], [1, 4, 6, 9], [6]],
                                [[1, 6, 10], [1, 4, 6, 10], [6]], [[1, 6, 11], [1, 4, 6, 11], [11]],
                                [[1, 7], [1, 4, 7], [4]], [[1, 7, 10], [1, 4, 7, 10], [4]],
                                [[1, 7, 11], [1, 4, 7, 11], [7]], [[1, 8], [1, 5, 8], [1]],
                                [[1, 8, 11], [1, 4, 8, 11], [1]], [[1, 9], [1, 4, 9], [9]],
                                [[1, 10], [1, 5, 10], [10]], [[1, 11], [2, 6, 11], [11]], [[2], [2, 9], [9]],
                                [[2, 5], [2, 5, 9], [2]], [[2, 5, 8], [2, 5, 8, 11], [2]],
                                [[2, 5, 8, 11], [1, 4, 7, 10], [0, 3, 8]],
                                [[2, 5, 9], [0, 3, 5, 9], [2, 5, 10]], [[2, 5, 10], [0, 3, 5, 9], [2, 10]],
                                [[2, 5, 11], [2, 5, 8, 11], [8]], [[2, 6], [2, 6, 9], [2]],
                                [[2, 6, 9], [1, 4, 6, 9], [1, 4, 9]], [[2, 6, 10], [1, 4, 6, 10], [1, 6, 10]],
                                [[2, 6, 11], [1, 4, 6, 10], [1, 6, 10]], [[2, 7], [2, 7, 11], [7]],
                                [[2, 7, 10], [0, 4, 7, 10], [0]], [[2, 7, 11], [1, 4, 6, 9], [1, 4, 9]],
                                [[2, 8], [4, 8, 11], [4]], [[2, 8, 11], [2, 5, 8, 11], [4]],
                                [[2, 9], [2, 6, 9], [2]], [[2, 10], [2, 5, 10], [10]],
                                [[2, 11], [2, 7, 11], [7]], [[3], [3, 10], [10]], [[3, 5], [3, 7, 10], [3]],
                                [[3, 5, 8], [0, 3, 5, 8], [8]], [[3, 5, 8, 11], [2, 5, 8, 11], [2]],
                                [[3, 5, 9], [0, 3, 5, 9], [5]], [[3, 5, 10], [0, 3, 5, 10], [5, 10]],
                                [[3, 5, 11], [3, 5, 8, 11], [5]], [[3, 7], [3, 7, 10], [3]],
                                [[3, 7, 10], [0, 3, 7, 10], [10]], [[3, 7, 11], [0, 3, 7, 10], [3, 7, 10]],
                                [[3, 8], [0, 3, 8], [8]], [[3, 8, 11], [3, 5, 8, 11], [11]],
                                [[3, 9], [0, 3, 9], [9]], [[3, 10], [3, 7, 10], [3]],
                                [[3, 11], [3, 8, 11], [8]], [[4], [4, 11], [11]], [[4, 6], [4, 7, 11], [4]],
                                [[4, 6, 9], [1, 4, 6, 9], [9]], [[4, 6, 10], [1, 4, 6, 10], [6]],
                                [[4, 6, 11], [1, 4, 6, 11], [11]], [[4, 7], [0, 4, 7], [0]],
                                [[4, 7, 10], [0, 4, 7, 10], [0]], [[4, 7, 11], [1, 4, 7, 11], [11]],
                                [[4, 8], [4, 8, 11], [4]], [[4, 8, 11], [1, 4, 8, 11], [4]],
                                [[4, 9], [1, 4, 9], [9]], [[4, 10], [4, 7, 10], [7]],
                                [[4, 11], [4, 8, 11], [4]], [[5], [0, 5, 9], [0]], [[5, 8], [0, 5, 8], [5]],
                                [[5, 8, 11], [1, 5, 8, 11], [1]], [[5, 9], [0, 5, 9], [5]],
                                [[5, 10], [2, 5, 10], [10]], [[5, 11], [0, 5, 9], [5]], [[6], [1, 6], [1]],
                                [[6, 9], [2, 6, 9], [2]], [[6, 10], [1, 6, 10], [6]],
                                [[6, 11], [2, 6, 11], [11]], [[7], [2, 7, 11], [2]],
                                [[7, 10], [2, 7, 10], [7]], [[7, 11], [2, 7, 11], [7]], [[8], [3, 8], [3]],
                                [[8, 11], [4, 8, 11], [4]], [[9], [4, 9], [4]], [[10], [2, 5, 10], [5]],
                                [[11], [6, 11], [6]]]

###################################################################################

def pitches_to_tones(pitches):
  return [p % 12 for p in pitches]

###################################################################################

def tones_to_pitches(tones, base_octave=5):
  return [(base_octave * 12) + t for t in tones]

###################################################################################

def find_closest_value(lst, val):

  closest_value = min(lst, key=lambda x: abs(val - x))
  closest_value_indexes = [i for i in range(len(lst)) if lst[i] == closest_value]
  
  return [closest_value, abs(val - closest_value), closest_value_indexes]

###################################################################################

def transpose_tones_chord(tones_chord, transpose_value=0):
  return sorted([((60+t)+transpose_value) % 12 for t in sorted(set(tones_chord))])

###################################################################################

def transpose_tones(tones, transpose_value=0):
  return [((60+t)+transpose_value) % 12 for t in tones]

###################################################################################

def transpose_pitches_chord(pitches_chord, transpose_value=0):
  return [max(1, min(127, p+transpose_value)) for p in sorted(set(pitches_chord), reverse=True)]

###################################################################################

def transpose_pitches(pitches, transpose_value=0):
  return [max(1, min(127, p+transpose_value)) for p in pitches]

###################################################################################

def reverse_enhanced_score_notes(escore_notes):

  score = recalculate_score_timings(escore_notes)

  ematrix = escore_notes_to_escore_matrix(score, reverse_matrix=True)
  e_score = escore_matrix_to_original_escore_notes(ematrix)

  reversed_score = recalculate_score_timings(e_score)

  return reversed_score

###################################################################################

def count_patterns(lst, sublist):
    count = 0
    idx = 0
    for i in range(len(lst) - len(sublist) + 1):
        if lst[idx:idx + len(sublist)] == sublist:
            count += 1
            idx += len(sublist)
        else:
          idx += 1
    return count

###################################################################################

def find_lrno_patterns(seq):

  all_seqs = Counter()

  max_pat_len = math.ceil(len(seq) / 2)

  num_iter = 0

  for i in range(len(seq)):
    for j in range(i+1, len(seq)+1):
      if j-i <= max_pat_len:
        all_seqs[tuple(seq[i:j])] += 1
        num_iter += 1

  max_count = 0
  max_len = 0

  for val, count in all_seqs.items():

    if max_len < len(val):
      max_count = max(2, count)

    if count > 1:
      max_len = max(max_len, len(val))
      pval = val

  max_pats = []

  for val, count in all_seqs.items():
    if count == max_count and len(val) == max_len:
      max_pats.append(val)

  found_patterns = []

  for pat in max_pats:
    count = count_patterns(seq, list(pat))
    if count > 1:
      found_patterns.append([count, len(pat), pat])

  return found_patterns

###################################################################################

def delta_pitches(escore_notes, pitches_index=4):

  pitches = [p[pitches_index] for p in escore_notes]
  
  return [a-b for a, b in zip(pitches[:-1], pitches[1:])]

###################################################################################

def split_list(lst, val):
    return [lst[i:j] for i, j in zip([0] + [k + 1 for k, x in enumerate(lst) if x == val], [k for k, x in enumerate(lst) if x == val] + [len(lst)]) if j > i]

###################################################################################

def even_timings(escore_notes, 
                 times_idx=1, 
                 durs_idx=2
                 ):

  esn = copy.deepcopy(escore_notes)

  for e in esn:

    if e[times_idx] != 0:
      if e[times_idx] % 2 != 0:
        e[times_idx] += 1

    if e[durs_idx] % 2 != 0:
      e[durs_idx] += 1

  return esn

###################################################################################

def delta_score_to_abs_score(delta_score_notes, 
                            times_idx=1
                            ):

  abs_score = copy.deepcopy(delta_score_notes)

  abs_time = 0

  for i, e in enumerate(delta_score_notes):

    dtime = e[times_idx]
    
    abs_time += dtime

    abs_score[i][times_idx] = abs_time
    
  return abs_score

###################################################################################


def adjust_numbers_to_sum(numbers, target_sum):

  current_sum = sum(numbers)
  difference = target_sum - current_sum

  non_zero_elements = [(i, num) for i, num in enumerate(numbers) if num != 0]

  total_non_zero = sum(num for _, num in non_zero_elements)

  increments = []
  for i, num in non_zero_elements:
      proportion = num / total_non_zero
      increment = proportion * difference
      increments.append(increment)

  for idx, (i, num) in enumerate(non_zero_elements):
      numbers[i] += int(round(increments[idx]))

  current_sum = sum(numbers)
  difference = target_sum - current_sum
  non_zero_indices = [i for i, num in enumerate(numbers) if num != 0]

  for i in range(abs(difference)):
      numbers[non_zero_indices[i % len(non_zero_indices)]] += 1 if difference > 0 else -1

  return numbers

###################################################################################

def find_next_bar(escore_notes, bar_time, start_note_idx, cur_bar):
  for e in escore_notes[start_note_idx:]:
    if e[1] // bar_time > cur_bar:
      return e, escore_notes.index(e)

###################################################################################

def align_escore_notes_to_bars(escore_notes,
                               bar_time=4000,
                               trim_durations=False,
                               split_durations=False,
                               even_timings=False
                               ):

  #=============================================================================
    
  escore = copy.deepcopy(escore_notes)
  
  if even_timings:
      for e in escore:
          if e[1] % 2 != 0:
              e[1] += 1
          
          if e[2] % 2 != 0:
              e[2] += 1

  aligned_escore_notes = copy.deepcopy(escore)

  abs_time = 0
  nidx = 0
  delta = 0
  bcount = 0
  next_bar = [0]

  #=============================================================================

  while next_bar:

    next_bar = find_next_bar(escore, bar_time, nidx, bcount)

    if next_bar:
      gescore_notes = escore[nidx:next_bar[1]]
    
    else:
      gescore_notes = escore[nidx:]

    original_timings = [delta] + [(b[1]-a[1]) for a, b in zip(gescore_notes[:-1], gescore_notes[1:])]
    adj_timings = adjust_numbers_to_sum(original_timings, bar_time)

    for t in adj_timings:

      abs_time += t

      aligned_escore_notes[nidx][1] = abs_time
      aligned_escore_notes[nidx][2] -= int(bar_time // 200)

      nidx += 1

    if next_bar:
      delta = escore[next_bar[1]][1]-escore[next_bar[1]-1][1]
      
    bcount += 1

  #=============================================================================

  aligned_adjusted_escore_notes = []
  bcount = 0

  for a in aligned_escore_notes:
    bcount = a[1] // bar_time
    nbtime = bar_time * (bcount+1)

    if a[1]+a[2] > nbtime and a[3] != 9:
      if trim_durations or split_durations:
        ddiff = ((a[1]+a[2])-nbtime)
        aa = copy.deepcopy(a)
        aa[2] = a[2] - ddiff
        aligned_adjusted_escore_notes.append(aa)

        if split_durations:
          aaa = copy.deepcopy(a)
          aaa[1] = a[1]+aa[2]
          aaa[2] = ddiff

          aligned_adjusted_escore_notes.append(aaa)

      else:
        aligned_adjusted_escore_notes.append(a)

    else:
      aligned_adjusted_escore_notes.append(a)

  #=============================================================================

  return aligned_adjusted_escore_notes

###################################################################################

def normalize_chord_durations(chord, 
                              dur_idx=2, 
                              norm_factor=100
                              ):

  nchord = copy.deepcopy(chord)
  
  for c in nchord:
    c[dur_idx] = int(round(max(1 / norm_factor, c[dur_idx] // norm_factor) * norm_factor))

  return nchord

###################################################################################

def normalize_chordified_score_durations(chordified_score, 
                                         dur_idx=2, 
                                         norm_factor=100
                                         ):

  ncscore = copy.deepcopy(chordified_score)
  
  for cc in ncscore:
    for c in cc:
      c[dur_idx] = int(round(max(1 / norm_factor, c[dur_idx] // norm_factor) * norm_factor))

  return ncscore

###################################################################################

def horizontal_ordered_list_search(list_of_lists, 
                                    query_list, 
                                    start_idx=0,
                                    end_idx=-1
                                    ):

  lol = list_of_lists

  results = []

  if start_idx > 0:
    lol = list_of_lists[start_idx:]

  if start_idx == -1:
    idx = -1
    for i, l in enumerate(list_of_lists):
      try:
        idx = l.index(query_list[0])
        lol = list_of_lists[i:]
        break
      except:
        continue

    if idx == -1:
      results.append(-1)
      return results
    else:
      results.append(i)

  if end_idx != -1:
    lol = list_of_lists[start_idx:start_idx+max(end_idx, len(query_list))]

  for i, q in enumerate(query_list):
    try:
      idx = lol[i].index(q)
      results.append(idx)
    except:
      results.append(-1)
      return results

  return results

###################################################################################

def escore_notes_to_escore_matrix(escore_notes,
                                  alt_velocities=False,
                                  flip_matrix=False,
                                  reverse_matrix=False
                                  ):

  last_time = escore_notes[-1][1]
  last_notes = [e for e in escore_notes if e[1] == last_time]
  max_last_dur = max([e[2] for e in last_notes])

  time_range = last_time+max_last_dur

  channels_list = sorted(set([e[3] for e in escore_notes]))

  escore_matrixes = []

  for cha in channels_list:

    escore_matrix = [[[-1, -1]] * 128 for _ in range(time_range)]

    pe = escore_notes[0]

    for i, note in enumerate(escore_notes):

        etype, time, duration, channel, pitch, velocity, patch = note

        time = max(0, time)
        duration = max(1, duration)
        channel = max(0, min(15, channel))
        pitch = max(0, min(127, pitch))
        velocity = max(0, min(127, velocity))
        patch = max(0, min(128, patch))

        if alt_velocities:
            velocity -= (i % 2)

        if channel == cha:

          for t in range(time, min(time + duration, time_range)):

            escore_matrix[t][pitch] = [velocity, patch]

        pe = note

    if flip_matrix:

      temp_matrix = []

      for m in escore_matrix:
        temp_matrix.append(m[::-1])

      escore_matrix = temp_matrix

    if reverse_matrix:
      escore_matrix = escore_matrix[::-1]

    escore_matrixes.append(escore_matrix)

  return [channels_list, escore_matrixes]

###################################################################################

def escore_matrix_to_merged_escore_notes(full_escore_matrix,
                                        max_note_duration=4000
                                        ):

  merged_escore_notes = []

  mat_channels_list = full_escore_matrix[0]
  
  for m, cha in enumerate(mat_channels_list):

    escore_matrix = full_escore_matrix[1][m]

    result = []

    for j in range(len(escore_matrix[0])):

        count = 1

        for i in range(1, len(escore_matrix)):

          if escore_matrix[i][j] != [-1, -1] and escore_matrix[i][j][1] == escore_matrix[i-1][j][1] and count < max_note_duration:
              count += 1

          else:
              if count > 1:  
                result.append([i-count, count, j, escore_matrix[i-1][j]])

              count = 1

        if count > 1:
            result.append([len(escore_matrix)-count, count, j, escore_matrix[-1][j]])

    result.sort(key=lambda x: (x[0], -x[2]))

    for r in result:
      merged_escore_notes.append(['note', r[0], r[1], cha, r[2], r[3][0], r[3][1]])

  return sorted(merged_escore_notes, key=lambda x: (x[1], -x[4], x[6]))

###################################################################################

def escore_matrix_to_original_escore_notes(full_escore_matrix):

  merged_escore_notes = []

  mat_channels_list = full_escore_matrix[0]

  for m, cha in enumerate(mat_channels_list):

    escore_matrix = full_escore_matrix[1][m]

    result = []

    for j in range(len(escore_matrix[0])):

        count = 1

        for i in range(1, len(escore_matrix)):

          if escore_matrix[i][j] != [-1, -1] and escore_matrix[i][j] == escore_matrix[i-1][j]:
              count += 1

          else:
              if count > 1:
                result.append([i-count, count, j, escore_matrix[i-1][j]])

              count = 1

        if count > 1:
            result.append([len(escore_matrix)-count, count, j, escore_matrix[-1][j]])

    result.sort(key=lambda x: (x[0], -x[2]))

    for r in result:
      merged_escore_notes.append(['note', r[0], r[1], cha, r[2], r[3][0], r[3][1]])

  return sorted(merged_escore_notes, key=lambda x: (x[1], -x[4], x[6]))

###################################################################################

def escore_notes_to_binary_matrix(escore_notes, 
                                  channel=0, 
                                  patch=0,
                                  flip_matrix=False,
                                  reverse_matrix=False
                                  ):

  escore = [e for e in escore_notes if e[3] == channel and e[6] == patch]

  if escore:
    last_time = escore[-1][1]
    last_notes = [e for e in escore if e[1] == last_time]
    max_last_dur = max([e[2] for e in last_notes])

    time_range = last_time+max_last_dur

    escore_matrix = []

    escore_matrix = [[0] * 128 for _ in range(time_range)]

    for note in escore:

        etype, time, duration, chan, pitch, velocity, pat = note

        time = max(0, time)
        duration = max(1, duration)
        chan = max(0, min(15, chan))
        pitch = max(0, min(127, pitch))
        velocity = max(0, min(127, velocity))
        pat = max(0, min(128, pat))

        if channel == chan and patch == pat:

          for t in range(time, min(time + duration, time_range)):

            escore_matrix[t][pitch] = 1

    if flip_matrix:

      temp_matrix = []

      for m in escore_matrix:
        temp_matrix.append(m[::-1])

      escore_matrix = temp_matrix

    if reverse_matrix:
      escore_matrix = escore_matrix[::-1]

    return escore_matrix

  else:
    return None

###################################################################################

def binary_matrix_to_original_escore_notes(binary_matrix, 
                                           channel=0, 
                                           patch=0, 
                                           velocity=-1
                                           ):

  result = []

  for j in range(len(binary_matrix[0])):

      count = 1

      for i in range(1, len(binary_matrix)):

        if binary_matrix[i][j] != 0 and binary_matrix[i][j] == binary_matrix[i-1][j]:
            count += 1

        else:
          if count > 1:
            result.append([i-count, count, j, binary_matrix[i-1][j]])
          
          else:
            if binary_matrix[i-1][j] != 0:
              result.append([i-count, count, j, binary_matrix[i-1][j]])

          count = 1

      if count > 1:
          result.append([len(binary_matrix)-count, count, j, binary_matrix[-1][j]])
      
      else:
        if binary_matrix[i-1][j] != 0:
          result.append([i-count, count, j, binary_matrix[i-1][j]])

  result.sort(key=lambda x: (x[0], -x[2]))

  original_escore_notes = []

  vel = velocity

  for r in result:
    
    if velocity == -1:
      vel = max(40, r[2])

    original_escore_notes.append(['note', r[0], r[1], channel, r[2], vel, patch])

  return sorted(original_escore_notes, key=lambda x: (x[1], -x[4], x[6]))

###################################################################################

def escore_notes_averages(escore_notes, 
                          times_index=1, 
                          durs_index=2,
                          chans_index=3, 
                          ptcs_index=4, 
                          vels_index=5,
                          average_drums=False,
                          score_is_delta=False,
                          return_ptcs_and_vels=False
                          ):
  
  if score_is_delta:
    if average_drums:
      times = [e[times_index] for e in escore_notes if e[times_index] != 0]
    else:
      times = [e[times_index] for e in escore_notes if e[times_index] != 0 and e[chans_index] != 9]

  else:
    descore_notes = delta_score_notes(escore_notes)
    if average_drums:
      times = [e[times_index] for e in descore_notes if e[times_index] != 0]
    else:
      times = [e[times_index] for e in descore_notes if e[times_index] != 0 and e[chans_index] != 9]
      
  if average_drums:
    durs = [e[durs_index] for e in escore_notes]
  else:
    durs = [e[durs_index] for e in escore_notes if e[chans_index] != 9]

  if len(times) == 0:
      times = [0]
      
  if len(durs) == 0:
      durs = [0]

  if return_ptcs_and_vels:
    if average_drums:
      ptcs = [e[ptcs_index] for e in escore_notes]
      vels = [e[vels_index] for e in escore_notes]
    else:
      ptcs = [e[ptcs_index] for e in escore_notes if e[chans_index] != 9]
      vels = [e[vels_index] for e in escore_notes if e[chans_index] != 9]
      
    if len(ptcs) == 0:
        ptcs = [0]
      
    if len(vels) == 0:
        vels = [0]

    return [sum(times) / len(times), sum(durs) / len(durs), sum(ptcs) / len(ptcs), sum(vels) / len(vels)]
  
  else:
    return [sum(times) / len(times), sum(durs) / len(durs)]

###################################################################################

def adjust_escore_notes_timings(escore_notes, 
                                adj_k=1, 
                                times_index=1, 
                                durs_index=2, 
                                score_is_delta=False, 
                                return_delta_scpre=False
                                ):

  if score_is_delta:
    adj_escore_notes = copy.deepcopy(escore_notes)
  else:
    adj_escore_notes = delta_score_notes(escore_notes)

  for e in adj_escore_notes:

    if e[times_index] != 0:
      e[times_index] = max(1, round(e[times_index] * adj_k))

    e[durs_index] = max(1, round(e[durs_index] * adj_k))

  if return_delta_scpre:
    return adj_escore_notes

  else:
    return delta_score_to_abs_score(adj_escore_notes)

###################################################################################

def escore_notes_delta_times(escore_notes,
                             times_index=1
                             ):

  descore_notes = delta_score_notes(escore_notes)

  return [e[times_index] for e in descore_notes]

###################################################################################

def escore_notes_durations(escore_notes,
                            durs_index=1
                            ):

  descore_notes = delta_score_notes(escore_notes)

  return [e[durs_index] for e in descore_notes]

###################################################################################

def ordered_lists_match_ratio(src_list, trg_list):

  zlist = list(zip(src_list, trg_list))

  return sum([a == b for a, b in zlist]) / len(list(zlist))

###################################################################################

def lists_intersections(src_list, trg_list):
  return list(set(src_list) & set(trg_list))

###################################################################################

def transpose_escore_notes(escore_notes, 
                            transpose_value=0, 
                            channel_index=3, 
                            pitches_index=4
                            ):

  tr_escore_notes = copy.deepcopy(escore_notes)

  for e in tr_escore_notes:
    if e[channel_index] != 9:
      e[pitches_index] = max(1, min(127, e[pitches_index] + transpose_value))

  return tr_escore_notes

###################################################################################

def transpose_escore_notes_to_pitch(escore_notes, 
                                    target_pitch_value=60, 
                                    channel_index=3, 
                                    pitches_index=4
                                    ):

  tr_escore_notes = copy.deepcopy(escore_notes)

  transpose_delta = int(round(target_pitch_value)) - int(round(escore_notes_averages(escore_notes, return_ptcs_and_vels=True)[2]))

  for e in tr_escore_notes:
    if e[channel_index] != 9:
      e[pitches_index] = max(1, min(127, e[pitches_index] + transpose_delta))

  return tr_escore_notes

###################################################################################

CHORDS_TYPES = ['WHITE', 'BLACK', 'UNKNOWN', 'MIXED WHITE', 'MIXED BLACK', 'MIXED GRAY']

###################################################################################

def tones_chord_type(tones_chord, 
                     return_chord_type_index=True,
                     use_filtered_chords=False,
                     use_full_chords=True
                     ):

  WN = WHITE_NOTES
  BN = BLACK_NOTES
  MX = WHITE_NOTES + BLACK_NOTES

  if use_filtered_chords:
    CHORDS = ALL_CHORDS_FILTERED
  
  else:
    CHORDS = ALL_CHORDS_SORTED

  if use_full_chords:
    CHORDS = ALL_CHORDS_FULL

  tones_chord = sorted(tones_chord)

  ctype = 'UNKNOWN'

  if tones_chord in CHORDS:

    if sorted(set(tones_chord) & set(WN)) == tones_chord:
      ctype = 'WHITE'

    elif sorted(set(tones_chord) & set(BN)) == tones_chord:
      ctype = 'BLACK'

    if len(tones_chord) > 1 and sorted(set(tones_chord) & set(MX)) == tones_chord:

      if len(sorted(set(tones_chord) & set(WN))) == len(sorted(set(tones_chord) & set(BN))):
        ctype = 'MIXED GRAY'

      elif len(sorted(set(tones_chord) & set(WN))) > len(sorted(set(tones_chord) & set(BN))):
        ctype = 'MIXED WHITE'

      elif len(sorted(set(tones_chord) & set(WN))) < len(sorted(set(tones_chord) & set(BN))):
        ctype = 'MIXED BLACK'

  if return_chord_type_index:
    return CHORDS_TYPES.index(ctype)

  else:
    return ctype

###################################################################################

def tone_type(tone, 
              return_tone_type_index=True
              ):

  tone = tone % 12

  if tone in BLACK_NOTES:
    if return_tone_type_index:
      return CHORDS_TYPES.index('BLACK')
    else:
      return "BLACK"

  else:
    if return_tone_type_index:
      return CHORDS_TYPES.index('WHITE')
    else:
      return "WHITE"

###################################################################################

def lists_sym_differences(src_list, trg_list):
  return list(set(src_list) ^ set(trg_list))

###################################################################################

def lists_differences(long_list, short_list):
  return list(set(long_list) - set(short_list))

###################################################################################

def find_best_tones_chord(src_tones_chords,
                          trg_tones_chords,
                          find_longest=True
                          ):

  not_seen_trg_chords = []

  max_len = 0

  for tc in trg_tones_chords:
    if sorted(tc) in src_tones_chords:
      not_seen_trg_chords.append(sorted(tc))
      max_len = max(max_len, len(tc))

  if not not_seen_trg_chords:
    max_len = len(max(trg_tones_chords, key=len))
    not_seen_trg_chords = trg_tones_chords

  if find_longest:
    return random.choice([c for c in not_seen_trg_chords if len(c) == max_len])

  else:
    return random.choice(not_seen_trg_chords)

###################################################################################

def find_matching_tones_chords(tones_chord,
                               matching_chord_length=-1,
                               match_chord_type=True,
                               use_filtered_chords=True,
                               use_full_chords=True
                               ):

  if use_filtered_chords:
    CHORDS = ALL_CHORDS_FILTERED
  else:
    CHORDS = ALL_CHORDS_SORTED

  if use_full_chords:
    CHORDS = ALL_CHORDS_FULL

  tones_chord = sorted(tones_chord)

  tclen = len(tones_chord)

  tctype = tones_chord_type(tones_chord, use_filtered_chords=use_filtered_chords)

  matches = []

  for tc in CHORDS:

    if matching_chord_length == -1:
      if len(tc) > tclen:
        if sorted(lists_intersections(tc, tones_chord)) == tones_chord:
          if match_chord_type:
            if tones_chord_type(tc, use_filtered_chords=use_filtered_chords) == tctype:
              tcdiffs = lists_differences(tc, tones_chord)
              if all(tone_type(d) == tctype % 3 for d in tcdiffs):
                matches.append(tc)
          else:
            matches.append(tc)

    else:

      if len(tc) == max(tclen, matching_chord_length):
        if sorted(lists_intersections(tc, tones_chord)) == tones_chord:
          if match_chord_type:
            if tones_chord_type(tc, use_filtered_chords=use_filtered_chords) == tctype:
              tcdiffs = lists_differences(tc, tones_chord)
              if all(tone_type(d) == tctype % 3 for d in tcdiffs):
                matches.append(tc)
          else:
            matches.append(tc)

  return sorted(matches, key=len)

###################################################################################

def adjust_list_of_values_to_target_average(list_of_values, 
                                            trg_avg, 
                                            min_value, 
                                            max_value
                                            ):

    filtered_values = [value for value in list_of_values if min_value <= value <= max_value]

    if not filtered_values:
        return list_of_values

    current_avg = sum(filtered_values) / len(filtered_values)
    scale_factor = trg_avg / current_avg

    adjusted_values = [value * scale_factor for value in filtered_values]

    total_difference = trg_avg * len(filtered_values) - sum(adjusted_values)
    adjustment_per_value = total_difference / len(filtered_values)

    final_values = [value + adjustment_per_value for value in adjusted_values]

    while abs(sum(final_values) / len(final_values) - trg_avg) > 1e-6:
        total_difference = trg_avg * len(final_values) - sum(final_values)
        adjustment_per_value = total_difference / len(final_values)
        final_values = [value + adjustment_per_value for value in final_values]

    final_values = [round(value) for value in final_values]

    adjusted_values = copy.deepcopy(list_of_values)

    j = 0

    for i in range(len(adjusted_values)):
        if min_value <= adjusted_values[i] <= max_value:
            adjusted_values[i] = final_values[j]
            j += 1

    return adjusted_values

###################################################################################

def adjust_escore_notes_to_average(escore_notes,
                                   trg_avg,
                                   min_value=1,
                                   max_value=4000,
                                   times_index=1,
                                   durs_index=2,
                                   score_is_delta=False,
                                   return_delta_scpre=False
                                   ):
    if score_is_delta:
      delta_escore_notes = copy.deepcopy(escore_notes)

    else:
      delta_escore_notes = delta_score_notes(escore_notes)

    times = [[e[times_index], e[durs_index]] for e in delta_escore_notes]

    filtered_values = [value for value in times if min_value <= value[0] <= max_value]

    if not filtered_values:
        return escore_notes

    current_avg = sum([v[0] for v in filtered_values]) / len([v[0] for v in filtered_values])
    scale_factor = trg_avg / current_avg

    adjusted_values = [[value[0] * scale_factor, value[1] * scale_factor] for value in filtered_values]

    total_difference = trg_avg * len([v[0] for v in filtered_values]) - sum([v[0] for v in adjusted_values])
    adjustment_per_value = total_difference / len(filtered_values)

    final_values = [[value[0] + adjustment_per_value, value[1] + adjustment_per_value] for value in adjusted_values]

    while abs(sum([v[0] for v in final_values]) / len(final_values) - trg_avg) > 1e-6:
        total_difference = trg_avg * len(final_values) - sum([v[0] for v in final_values])
        adjustment_per_value = total_difference / len(final_values)
        final_values = [[value[0] + adjustment_per_value, value[1] + adjustment_per_value] for value in final_values]

    final_values = [[round(value[0]), round(value[1])] for value in final_values]

    adjusted_delta_score = copy.deepcopy(delta_escore_notes)

    j = 0

    for i in range(len(adjusted_delta_score)):
        if min_value <= adjusted_delta_score[i][1] <= max_value:
            adjusted_delta_score[i][times_index] = final_values[j][0]
            adjusted_delta_score[i][durs_index] = final_values[j][1]
            j += 1

    adjusted_escore_notes = delta_score_to_abs_score(adjusted_delta_score)

    if return_delta_scpre:
      return adjusted_delta_score

    else:
      return adjusted_escore_notes

###################################################################################

def harmonize_enhanced_melody_score_notes_to_ms_SONG(escore_notes,
                                                      melody_velocity=-1,
                                                      melody_channel=3,
                                                      melody_patch=40,
                                                      melody_base_octave=4,
                                                      harmonized_tones_chords_velocity=-1,
                                                      harmonized_tones_chords_channel=0,
                                                      harmonized_tones_chords_patch=0
                                                    ):

  harmonized_tones_chords = harmonize_enhanced_melody_score_notes(escore_notes)

  harm_escore_notes = []

  time = 0

  for i, note in enumerate(escore_notes):

    time = note[1]
    dur = note[2]
    ptc = note[4]

    if melody_velocity == -1:
      vel = int(110 + ((ptc % 12) * 1.5))
    else:
      vel = melody_velocity

    harm_escore_notes.append(['note', time, dur, melody_channel, ptc, vel, melody_patch])

    for t in harmonized_tones_chords[i]:

      ptc = (melody_base_octave * 12) + t

      if harmonized_tones_chords_velocity == -1:
        vel = int(80 + ((ptc % 12) * 1.5))
      else:
        vel = harmonized_tones_chords_velocity

      harm_escore_notes.append(['note', time, dur, harmonized_tones_chords_channel, ptc, vel, harmonized_tones_chords_patch])

  return sorted(harm_escore_notes, key=lambda x: (x[1], -x[4], x[6]))

###################################################################################

def check_and_fix_pitches_chord(pitches_chord,
                                remove_duplicate_pitches=True,
                                use_filtered_chords=False,
                                use_full_chords=True,
                                fix_bad_pitches=False,
                                ):
  
  if remove_duplicate_pitches:
    pitches_chord = sorted(set(pitches_chord), reverse=True)
  else:
    pitches_chord = sorted(pitches_chord, reverse=True)

  if use_filtered_chords:
    CHORDS = ALL_CHORDS_FILTERED
  else:
    CHORDS = ALL_CHORDS_SORTED

  if use_full_chords:
    CHORDS = ALL_CHORDS_FULL

  chord = copy.deepcopy(pitches_chord)
    
  tones_chord = sorted(set([t % 12 for t in chord]))

  if tones_chord:

      if tones_chord not in CHORDS:
        
        if len(tones_chord) == 2:
          tones_counts = Counter([p % 12 for p in pitches_chord]).most_common()

          if tones_counts[0][1] > 1:
            tones_chord = [tones_counts[0][0]]
          
          elif tones_counts[1][1] > 1:
            tones_chord = [tones_counts[1][0]]
          
          else:
            tones_chord = [pitches_chord[0] % 12]

        else:
          tones_chord_combs = [list(comb) for i in range(len(tones_chord)-1, 0, -1) for comb in combinations(tones_chord, i)]

          for co in tones_chord_combs:
            if co in CHORDS:
              tones_chord = co
              break

          if len(tones_chord) == 1:
            tones_chord = [pitches_chord[0] % 12]
              
  chord.sort(reverse=True)

  new_chord = set()
  pipa = []

  for e in chord:
    if e % 12 in tones_chord:
      new_chord.add(tuple([e]))
      pipa.append(e)

    elif (e+1) % 12 in tones_chord:
      e += 1
      new_chord.add(tuple([e]))
      pipa.append(e)

    elif (e-1) % 12 in tones_chord:
      e -= 1
      new_chord.add(tuple([e]))
      pipa.append(e)

  if fix_bad_pitches:

    bad_chord = set()

    for e in chord:
    
      if e % 12 not in tones_chord:
        bad_chord.add(tuple([e]))
      
      elif (e+1) % 12 not in tones_chord:
        bad_chord.add(tuple([e]))
      
      elif (e-1) % 12 not in tones_chord:
        bad_chord.add(tuple([e]))
          
    for bc in bad_chord:

      bc = list(bc)

      tone = find_closest_tone(tones_chord, bc[0] % 12)

      new_pitch = ((bc[0] // 12) * 12) + tone

      if new_pitch not in pipa:
        new_chord.add(tuple([new_pitch]))
        pipa.append(new_pitch)

  new_pitches_chord = [e[0] for e in new_chord]

  return sorted(new_pitches_chord, reverse=True)

###################################################################################

ALL_CHORDS_TRANS = [[0], [0, 4], [0, 4, 7], [0, 4, 8], [0, 5], [0, 6], [0, 7], [0, 8], [1], [1, 5],
                    [1, 5, 9], [1, 6], [1, 7], [1, 8], [1, 9], [2], [2, 6], [2, 6, 10], [2, 7],
                    [2, 8], [2, 9], [2, 10], [3], [3, 7], [3, 7, 11], [3, 8], [3, 9], [3, 10],
                    [3, 11], [4], [4, 7], [4, 7, 11], [4, 8], [4, 9], [4, 10], [4, 11], [5],
                    [5, 9], [5, 10], [5, 11], [6], [6, 10], [6, 11], [7], [7, 11], [8], [9], [10],
                    [11]]

###################################################################################

def minkowski_distance(x, y, p=3, pad_value=float('inf')):

    if len(x) != len(y):
      return -1
    
    distance = 0
    
    for i in range(len(x)):

        if x[i] == pad_value or y[i] == pad_value:
          continue

        distance += abs(x[i] - y[i]) ** p

    return distance ** (1 / p)

###################################################################################

def dot_product(x, y, pad_value=None):
    return sum(xi * yi for xi, yi in zip(x, y) if xi != pad_value and yi != pad_value)

def norm(vector, pad_value=None):
    return sum(xi ** 2 for xi in vector if xi != pad_value) ** 0.5

def cosine_similarity(x, y, pad_value=None):
    if len(x) != len(y):
        return -1
    
    dot_prod = dot_product(x, y, pad_value)
    norm_x = norm(x, pad_value)
    norm_y = norm(y, pad_value)
    
    if norm_x == 0 or norm_y == 0:
        return 0.0
    
    return dot_prod / (norm_x * norm_y)

###################################################################################

def hamming_distance(arr1, arr2, pad_value):
    return sum(el1 != el2 for el1, el2 in zip(arr1, arr2) if el1 != pad_value and el2 != pad_value)

###################################################################################

def jaccard_similarity(arr1, arr2, pad_value):
    intersection = sum(el1 and el2 for el1, el2 in zip(arr1, arr2) if el1 != pad_value and el2 != pad_value)
    union = sum((el1 or el2) for el1, el2 in zip(arr1, arr2) if el1 != pad_value or el2 != pad_value)
    return intersection / union if union != 0 else 0

###################################################################################

def pearson_correlation(arr1, arr2, pad_value):
    filtered_pairs = [(el1, el2) for el1, el2 in zip(arr1, arr2) if el1 != pad_value and el2 != pad_value]
    if not filtered_pairs:
        return 0
    n = len(filtered_pairs)
    sum1 = sum(el1 for el1, el2 in filtered_pairs)
    sum2 = sum(el2 for el1, el2 in filtered_pairs)
    sum1_sq = sum(el1 ** 2 for el1, el2 in filtered_pairs)
    sum2_sq = sum(el2 ** 2 for el1, el2 in filtered_pairs)
    p_sum = sum(el1 * el2 for el1, el2 in filtered_pairs)
    num = p_sum - (sum1 * sum2 / n)
    den = ((sum1_sq - sum1 ** 2 / n) * (sum2_sq - sum2 ** 2 / n)) ** 0.5
    if den == 0:
        return 0
    return num / den

###################################################################################

def calculate_combined_distances(array_of_arrays,
                                  combine_hamming_distance=True,
                                  combine_jaccard_similarity=True, 
                                  combine_pearson_correlation=True,
                                  pad_value=None
                                  ):

  binary_arrays = array_of_arrays
  binary_array_len = len(binary_arrays)

  hamming_distances = [[0] * binary_array_len for _ in range(binary_array_len)]
  jaccard_similarities = [[0] * binary_array_len for _ in range(binary_array_len)]
  pearson_correlations = [[0] * binary_array_len for _ in range(binary_array_len)]

  for i in range(binary_array_len):
      for j in range(i + 1, binary_array_len):
          hamming_distances[i][j] = hamming_distance(binary_arrays[i], binary_arrays[j], pad_value)
          hamming_distances[j][i] = hamming_distances[i][j]
          
          jaccard_similarities[i][j] = jaccard_similarity(binary_arrays[i], binary_arrays[j], pad_value)
          jaccard_similarities[j][i] = jaccard_similarities[i][j]
          
          pearson_correlations[i][j] = pearson_correlation(binary_arrays[i], binary_arrays[j], pad_value)
          pearson_correlations[j][i] = pearson_correlations[i][j]

  max_hamming = max(max(row) for row in hamming_distances)
  min_hamming = min(min(row) for row in hamming_distances)
  normalized_hamming = [[(val - min_hamming) / (max_hamming - min_hamming) for val in row] for row in hamming_distances]

  max_jaccard = max(max(row) for row in jaccard_similarities)
  min_jaccard = min(min(row) for row in jaccard_similarities)
  normalized_jaccard = [[(val - min_jaccard) / (max_jaccard - min_jaccard) for val in row] for row in jaccard_similarities]

  max_pearson = max(max(row) for row in pearson_correlations)
  min_pearson = min(min(row) for row in pearson_correlations)
  normalized_pearson = [[(val - min_pearson) / (max_pearson - min_pearson) for val in row] for row in pearson_correlations]

  selected_metrics = 0

  if combine_hamming_distance:
    selected_metrics += normalized_hamming[i][j]
  
  if combine_jaccard_similarity:
    selected_metrics += (1 - normalized_jaccard[i][j])

  if combine_pearson_correlation:
    selected_metrics += (1 - normalized_pearson[i][j])

  combined_metric = [[selected_metrics for i in range(binary_array_len)] for j in range(binary_array_len)]

  return combined_metric

###################################################################################

def tones_chords_to_bits(tones_chords):

  bits_tones_chords = []

  for c in tones_chords:

    c.sort()

    bits = tones_chord_to_bits(c)

    bits_tones_chords.append(bits)

  return bits_tones_chords

###################################################################################

def tones_chords_to_ints(tones_chords):

  ints_tones_chords = []

  for c in tones_chords:

    c.sort()

    bits = tones_chord_to_bits(c)

    number = bits_to_int(bits)

    ints_tones_chords.append(number)

  return ints_tones_chords

###################################################################################

def tones_chords_to_types(tones_chords, 
                          return_chord_type_index=False
                          ):

  types_tones_chords = []

  for c in tones_chords:

    c.sort()

    ctype = tones_chord_type(c, return_chord_type_index=return_chord_type_index)

    types_tones_chords.append(ctype)

  return types_tones_chords

###################################################################################

def morph_tones_chord(tones_chord, 
                      trg_tone, 
                      use_filtered_chords=True,
                      use_full_chords=True
                      ):

  src_tones_chord = sorted(sorted(set(tones_chord)) + [trg_tone])

  combs = [list(comb) for i in range(len(src_tones_chord), 0, -1) for comb in combinations(src_tones_chord, i) if trg_tone in list(comb)]

  matches = []

  if use_filtered_chords:
    CHORDS = ALL_CHORDS_FILTERED
  
  else:
    CHORDS = ALL_CHORDS_SORTED

  if use_full_chords:
    CHORDS = ALL_CHORDS_FULL

  for c in combs:
    if sorted(set(c)) in CHORDS:
      matches.append(sorted(set(c)))

  max_len = len(max(matches, key=len))

  return random.choice([m for m in matches if len(m) == max_len])

###################################################################################

def compress_binary_matrix(binary_matrix, 
                           only_compress_zeros=False,
                           return_compression_ratio=False
                           ):

  compressed_bmatrix = []

  zm = [0] * len(binary_matrix[0])
  pm = [0] * len(binary_matrix[0])

  mcount = 0

  for m in binary_matrix:
    
    if only_compress_zeros:
      if m != zm:
        compressed_bmatrix.append(m)
        mcount += 1
    
    else:
      if m != pm:
        compressed_bmatrix.append(m)
        mcount += 1
    
    pm = m

  if return_compression_ratio:
    return [compressed_bmatrix, mcount / len(binary_matrix)]

  else:
    return compressed_bmatrix

###################################################################################

def solo_piano_escore_notes(escore_notes,
                            channels_index=3,
                            pitches_index=4,
                            patches_index=6,
                            keep_drums=False,
                            ):
  """
  A modified version of TMIDIX.solo_piano_escore_notes that preserves the
  original MIDI channel of each note. This allows stereo panning information,
  which is often channel-dependent, to be maintained during the conversion
  to a solo piano performance.
  """
  cscore = chordify_score([1000, escore_notes])

  sp_escore_notes = []

  for c in cscore:
    # --- Use a set to store (pitch, channel) tuples for uniqueness ---
    seen_notes = set()
    chord = []

    for cc in c:

      if cc[channels_index] != 9: # If not a drum channel
        # Create a unique identifier for each note using both pitch and channel
        note_id = (cc[pitches_index], cc[channels_index])
        
        # Check if this specific pitch-channel combination has been seen
        if note_id not in seen_notes:
            # The original function forced the channel to 0, destroying stereo separation.
            # We comment out that line and ONLY change the instrument patch.
            # cc[channels_index] = 0  <-- THIS LINE IS REMOVED

            # Force the instrument patch to 0 (Acoustic Grand Piano)
            cc[patches_index] = 0 # Set patch to Grand Piano
        
            chord.append(cc)
            seen_notes.add(note_id) # Add the unique ID to the set
      
      else: # If it is a drum channel
        if keep_drums:
          # Apply the same logic for drums to be safe
          drum_id = (cc[pitches_index] + 128, cc[channels_index])
          if drum_id not in seen_notes:
              chord.append(cc)
              seen_notes.add(drum_id)

    sp_escore_notes.append(chord)

  return flatten(sp_escore_notes)

###################################################################################

def strip_drums_from_escore_notes(escore_notes, 
                                  channels_index=3
                                  ):
  
  return [e for e in escore_notes if e[channels_index] != 9]

###################################################################################

def fixed_escore_notes_timings(escore_notes,
                               fixed_durations=False,
                               fixed_timings_multiplier=1,
                               custom_fixed_time=-1,
                               custom_fixed_dur=-1
                               ):

  fixed_timings_escore_notes = delta_score_notes(escore_notes, even_timings=True)

  mode_time = round(Counter([e[1] for e in fixed_timings_escore_notes if e[1] != 0]).most_common()[0][0] * fixed_timings_multiplier)

  if mode_time % 2 != 0:
    mode_time += 1

  mode_dur = round(Counter([e[2] for e in fixed_timings_escore_notes if e[2] != 0]).most_common()[0][0] * fixed_timings_multiplier)

  if mode_dur % 2 != 0:
    mode_dur += 1

  for e in fixed_timings_escore_notes:
    if e[1] != 0:
      
      if custom_fixed_time > 0:
        e[1] = custom_fixed_time
      
      else:
        e[1] = mode_time

    if fixed_durations:
      
      if custom_fixed_dur > 0:
        e[2] = custom_fixed_dur
      
      else:
        e[2] = mode_dur

  return delta_score_to_abs_score(fixed_timings_escore_notes)

###################################################################################

def cubic_kernel(x):
    abs_x = abs(x)
    if abs_x <= 1:
        return 1.5 * abs_x**3 - 2.5 * abs_x**2 + 1
    elif abs_x <= 2:
        return -0.5 * abs_x**3 + 2.5 * abs_x**2 - 4 * abs_x + 2
    else:
        return 0

###################################################################################

def resize_matrix(matrix, new_height, new_width):
    old_height = len(matrix)
    old_width = len(matrix[0])
    resized_matrix = [[0] * new_width for _ in range(new_height)]
    
    for i in range(new_height):
        for j in range(new_width):
            old_i = i * old_height / new_height
            old_j = j * old_width / new_width
            
            value = 0
            total_weight = 0
            for m in range(-1, 3):
                for n in range(-1, 3):
                    i_m = min(max(int(old_i) + m, 0), old_height - 1)
                    j_n = min(max(int(old_j) + n, 0), old_width - 1)
                    
                    if matrix[i_m][j_n] == 0:
                        continue
                    
                    weight = cubic_kernel(old_i - i_m) * cubic_kernel(old_j - j_n)
                    value += matrix[i_m][j_n] * weight
                    total_weight += weight
            
            if total_weight > 0:
                value /= total_weight
            
            resized_matrix[i][j] = int(value > 0.5)
    
    return resized_matrix

###################################################################################

def square_binary_matrix(binary_matrix, 
                         matrix_size=128,
                         use_fast_squaring=False,
                         return_plot_points=False
                         ):

  if use_fast_squaring:

    step = round(len(binary_matrix) / matrix_size)

    samples = []

    for i in range(0, len(binary_matrix), step):
      samples.append(tuple([tuple(d) for d in binary_matrix[i:i+step]]))

    resized_matrix = []

    zmatrix = [[0] * matrix_size]

    for s in samples:

      samples_counts = Counter(s).most_common()

      best_sample = tuple([0] * matrix_size)
      pm = tuple(zmatrix[0])

      for sc in samples_counts:
        if sc[0] != tuple(zmatrix[0]) and sc[0] != pm:
          best_sample = sc[0]
          pm = sc[0]
          break
        
        pm = sc[0]

      resized_matrix.append(list(best_sample))

    resized_matrix = resized_matrix[:matrix_size]
    resized_matrix += zmatrix * (matrix_size - len(resized_matrix))
    
  else:
    resized_matrix = resize_matrix(binary_matrix, matrix_size, matrix_size)

  points = [(i, j) for i in range(matrix_size) for j in range(matrix_size) if resized_matrix[i][j] == 1]

  if return_plot_points:
    return [resized_matrix, points]

  else:
    return resized_matrix

###################################################################################

def mean(matrix):
    return sum(sum(row) for row in matrix) / (len(matrix) * len(matrix[0]))

###################################################################################

def variance(matrix, mean_value):
    return sum(sum((element - mean_value) ** 2 for element in row) for row in matrix) / (len(matrix) * len(matrix[0]))
    
###################################################################################

def covariance(matrix1, matrix2, mean1, mean2):
    return sum(sum((matrix1[i][j] - mean1) * (matrix2[i][j] - mean2) for j in range(len(matrix1[0]))) for i in range(len(matrix1))) / (len(matrix1) * len(matrix1[0]))

###################################################################################

def ssim_index(matrix1, matrix2, bit_depth=1):

    if len(matrix1) != len(matrix2) and len(matrix1[0]) != len(matrix2[0]):
      return -1

    K1, K2 = 0.01, 0.03
    L = bit_depth
    C1 = (K1 * L) ** 2
    C2 = (K2 * L) ** 2
    
    mu1 = mean(matrix1)
    mu2 = mean(matrix2)
    
    sigma1_sq = variance(matrix1, mu1)
    sigma2_sq = variance(matrix2, mu2)
    
    sigma12 = covariance(matrix1, matrix2, mu1, mu2)
    
    ssim = ((2 * mu1 * mu2 + C1) * (2 * sigma12 + C2)) / ((mu1 ** 2 + mu2 ** 2 + C1) * (sigma1_sq + sigma2_sq + C2))
    
    return ssim

###################################################################################

def find_most_similar_matrix(array_of_matrices, 
                             trg_matrix,
                             matrices_bit_depth=1,
                             return_most_similar_index=False
                             ):
   
    max_ssim = -float('inf')
    most_similar_index = -1

    for i, matrix in enumerate(array_of_matrices):

        ssim = ssim_index(matrix, trg_matrix, bit_depth=matrices_bit_depth)
        
        if ssim > max_ssim:
            max_ssim = ssim
            most_similar_index = i
    
    if return_most_similar_index:
      return most_similar_index
    
    else:
      return array_of_matrices[most_similar_index]

###################################################################################

def chord_to_pchord(chord):

  pchord = []

  for cc in chord:
    if cc[3] != 9:
      pchord.append(cc[4])

  return pchord

###################################################################################

def summarize_escore_notes(escore_notes, 
                           summary_length_in_chords=128, 
                           preserve_timings=True,
                           preserve_durations=False,
                           time_threshold=12,
                           min_sum_chord_len=2,
                           use_tones_chords=True
                           ):

    cscore = chordify_score([d[1:] for d in delta_score_notes(escore_notes)])

    summary_length_in_chords = min(len(cscore), summary_length_in_chords)

    ltthresh = time_threshold // 2
    uttresh = time_threshold * 2

    mc_time = Counter([c[0][0] for c in cscore if c[0][2] != 9 and ltthresh < c[0][0] < uttresh]).most_common()[0][0]

    pchords = []

    for c in cscore:
      if use_tones_chords:
        pchords.append([c[0][0]] + pitches_to_tones_chord(chord_to_pchord(c)))
        
      else:
        pchords.append([c[0][0]] + chord_to_pchord(c))

    step = round(len(pchords) / summary_length_in_chords)

    samples = []

    for i in range(0, len(pchords), step):
      samples.append(tuple([tuple(d) for d in pchords[i:i+step]]))

    summarized_escore_notes = []

    for i, s in enumerate(samples):

      best_chord = list([v[0] for v in Counter(s).most_common() if v[0][0] == mc_time and len(v[0]) > min_sum_chord_len])

      if not best_chord:
        best_chord = list([v[0] for v in Counter(s).most_common() if len(v[0]) > min_sum_chord_len])
        
        if not best_chord:
          best_chord = list([Counter(s).most_common()[0][0]])

      chord = copy.deepcopy(cscore[[ss for ss in s].index(best_chord[0])+(i*step)])

      if preserve_timings:

        if not preserve_durations:

          if i > 0:

            pchord = summarized_escore_notes[-1]

            for pc in pchord:
              pc[1] = min(pc[1], chord[0][0])

      else:

        chord[0][0] = 1

        for c in chord:
          c[1] = 1  

      summarized_escore_notes.append(chord)

    summarized_escore_notes = summarized_escore_notes[:summary_length_in_chords]

    return [['note'] + d for d in delta_score_to_abs_score(flatten(summarized_escore_notes), times_idx=0)]

###################################################################################

def compress_patches_in_escore_notes(escore_notes,
                                     num_patches=4,
                                     group_patches=False
                                     ):

  if num_patches > 4:
    n_patches = 4
  elif num_patches < 1:
    n_patches = 1
  else:
    n_patches = num_patches

  if group_patches:
    patches_set = sorted(set([e[6] for e in escore_notes]))
    trg_patch_list = []
    seen = []
    for p in patches_set:
      if p // 8 not in seen:
        trg_patch_list.append(p)
        seen.append(p // 8)

    trg_patch_list = sorted(trg_patch_list)

  else:
    trg_patch_list = sorted(set([e[6] for e in escore_notes]))

  if 128 in trg_patch_list and n_patches > 1:
    trg_patch_list = trg_patch_list[:n_patches-1] + [128]
  else:
    trg_patch_list = trg_patch_list[:n_patches]

  new_escore_notes = []

  for e in escore_notes:
    if e[6] in trg_patch_list:
      new_escore_notes.append(e)

  return new_escore_notes

###################################################################################

def compress_patches_in_escore_notes_chords(escore_notes,
                                            max_num_patches_per_chord=4,
                                            group_patches=True,
                                            root_grouped_patches=False
                                            ):

  if max_num_patches_per_chord > 4:
    n_patches = 4
  elif max_num_patches_per_chord < 1:
    n_patches = 1
  else:
    n_patches = max_num_patches_per_chord

  cscore = chordify_score([1000, sorted(escore_notes, key=lambda x: (x[1], x[6]))])

  new_escore_notes = []

  for c in cscore:

    if group_patches:
      patches_set = sorted(set([e[6] for e in c]))
      trg_patch_list = []
      seen = []
      for p in patches_set:
        if p // 8 not in seen:
          trg_patch_list.append(p)
          seen.append(p // 8)

      trg_patch_list = sorted(trg_patch_list)

    else:
      trg_patch_list = sorted(set([e[6] for e in c]))

    if 128 in trg_patch_list and n_patches > 1:
      trg_patch_list = trg_patch_list[:n_patches-1] + [128]
    else:
      trg_patch_list = trg_patch_list[:n_patches]

    for ccc in c:

      cc = copy.deepcopy(ccc)

      if group_patches:
        if cc[6] // 8 in [t // 8 for t in trg_patch_list]:
          if root_grouped_patches:
            cc[6] = (cc[6] // 8) * 8
          new_escore_notes.append(cc)

      else:
        if cc[6] in trg_patch_list:
          new_escore_notes.append(cc)

  return new_escore_notes

###################################################################################

def escore_notes_to_image_matrix(escore_notes,
                                  num_img_channels=3,
                                  filter_out_zero_rows=False,
                                  filter_out_duplicate_rows=False,
                                  flip_matrix=False,
                                  reverse_matrix=False
                                  ):

  escore_notes = sorted(escore_notes, key=lambda x: (x[1], x[6]))

  if num_img_channels > 1:
    n_mat_channels = 3
  else:
    n_mat_channels = 1

  if escore_notes:
    last_time = escore_notes[-1][1]
    last_notes = [e for e in escore_notes if e[1] == last_time]
    max_last_dur = max([e[2] for e in last_notes])

    time_range = last_time+max_last_dur

    escore_matrix = []

    escore_matrix = [[0] * 128 for _ in range(time_range)]

    for note in escore_notes:

        etype, time, duration, chan, pitch, velocity, pat = note

        time = max(0, time)
        duration = max(2, duration)
        chan = max(0, min(15, chan))
        pitch = max(0, min(127, pitch))
        velocity = max(0, min(127, velocity))
        patch = max(0, min(128, pat))

        if chan != 9:
          pat = patch + 128
        else:
          pat = 127

        seen_pats = []

        for t in range(time, min(time + duration, time_range)):

          mat_value = escore_matrix[t][pitch]

          mat_value_0 = (mat_value // (256 * 256)) % 256
          mat_value_1 = (mat_value // 256) % 256

          cur_num_chans = 0

          if 0 < mat_value < 256 and pat not in seen_pats:
            cur_num_chans = 1
          elif 256 < mat_value < (256 * 256) and pat not in seen_pats:
            cur_num_chans = 2

          if cur_num_chans < n_mat_channels:

            if n_mat_channels == 1:

              escore_matrix[t][pitch] = pat
              seen_pats.append(pat)

            elif n_mat_channels == 3:

              if cur_num_chans == 0:
                escore_matrix[t][pitch] = pat
                seen_pats.append(pat)
              elif cur_num_chans == 1:
                escore_matrix[t][pitch] = (256 * 256 * mat_value_0) + (256 * pat)
                seen_pats.append(pat)
              elif cur_num_chans == 2:
                escore_matrix[t][pitch] = (256 * 256 * mat_value_0) + (256 * mat_value_1) + pat
                seen_pats.append(pat)

    if filter_out_zero_rows:
      escore_matrix = [e for e in escore_matrix if sum(e) != 0]

    if filter_out_duplicate_rows:

      dd_escore_matrix = []

      pr = [-1] * 128
      for e in escore_matrix:
        if e != pr:
          dd_escore_matrix.append(e)
          pr = e
      
      escore_matrix = dd_escore_matrix

    if flip_matrix:

      temp_matrix = []

      for m in escore_matrix:
        temp_matrix.append(m[::-1])

      escore_matrix = temp_matrix

    if reverse_matrix:
      escore_matrix = escore_matrix[::-1]

    return escore_matrix

  else:
    return None

###################################################################################

def find_value_power(value, number):
    return math.floor(math.log(value, number))

###################################################################################

def image_matrix_to_original_escore_notes(image_matrix,
                                          velocity=-1
                                          ):

  result = []

  for j in range(len(image_matrix[0])):

      count = 1

      for i in range(1, len(image_matrix)):

        if image_matrix[i][j] != 0 and image_matrix[i][j] == image_matrix[i-1][j]:
            count += 1

        else:
          if count > 1:
            result.append([i-count, count, j, image_matrix[i-1][j]])

          else:
            if image_matrix[i-1][j] != 0:
              result.append([i-count, count, j, image_matrix[i-1][j]])

          count = 1

      if count > 1:
          result.append([len(image_matrix)-count, count, j, image_matrix[-1][j]])

      else:
        if image_matrix[i-1][j] != 0:
          result.append([i-count, count, j, image_matrix[i-1][j]])

  result.sort(key=lambda x: (x[0], -x[2]))

  original_escore_notes = []

  vel = velocity

  for r in result:

    if velocity == -1:
      vel = max(40, r[2])

    ptc0 = 0
    ptc1 = 0
    ptc2 = 0

    if find_value_power(r[3], 256) == 0:
      ptc0 = r[3] % 256

    elif find_value_power(r[3], 256) == 1:
      ptc0 = r[3] // 256
      ptc1 = (r[3] // 256) % 256

    elif find_value_power(r[3], 256) == 2:
      ptc0 = (r[3] // 256) // 256
      ptc1 = (r[3] // 256) % 256
      ptc2 = r[3] % 256

    ptcs = [ptc0, ptc1, ptc2]
    patches = [p for p in ptcs if p != 0]

    for i, p in enumerate(patches):

      if p < 128:
        patch = 128
        channel = 9

      else:
        patch = p % 128
        chan = p // 8

        if chan == 9:
          chan += 1

        channel = min(15, chan)

      original_escore_notes.append(['note', r[0], r[1], channel, r[2], vel, patch])

  output_score = sorted(original_escore_notes, key=lambda x: (x[1], -x[4], x[6]))

  adjust_score_velocities(output_score, 127)

  return output_score

###################################################################################

def escore_notes_delta_times(escore_notes, 
                             timings_index=1, 
                             channels_index=3, 
                             omit_zeros=False, 
                             omit_drums=False
                            ):

  if omit_drums:

    score = [e for e in escore_notes if e[channels_index] != 9]
    dtimes = [score[0][timings_index]] + [b[timings_index]-a[timings_index] for a, b in zip(score[:-1], score[1:])]

  else:
    dtimes = [escore_notes[0][timings_index]] + [b[timings_index]-a[timings_index] for a, b in zip(escore_notes[:-1], escore_notes[1:])]
  
  if omit_zeros:
    dtimes = [d for d in dtimes if d != 0]
  
  return dtimes

###################################################################################

def monophonic_check(escore_notes, times_index=1):
  return len(escore_notes) == len(set([e[times_index] for e in escore_notes]))

###################################################################################

def count_escore_notes_patches(escore_notes, patches_index=6):
  return [list(c) for c in Counter([e[patches_index] for e in escore_notes]).most_common()]

###################################################################################

def escore_notes_medley(list_of_escore_notes, 
                        list_of_labels=None,
                        pause_time_value=255
                        ):

  if list_of_labels is not None:
    labels = [str(l) for l in list_of_labels] + ['No label'] * (len(list_of_escore_notes)-len(list_of_labels))

  medley = []

  time = 0

  for i, m in enumerate(list_of_escore_notes):

    if list_of_labels is not None:
      medley.append(['text_event', time, labels[i]])

    pe = m[0]

    for mm in m:

      time += mm[1] - pe[1]

      mmm = copy.deepcopy(mm)
      mmm[1] = time

      medley.append(mmm)

      pe = mm

    time += pause_time_value

  return medley

###################################################################################

def proportions_counter(list_of_values):

  counts = Counter(list_of_values).most_common()
  clen = sum([c[1] for c in counts])

  return [[c[0], c[1], c[1] / clen] for c in counts]

###################################################################################

def smooth_escore_notes(escore_notes):

  values = [e[4] % 24 for e in escore_notes]

  smoothed = [values[0]]

  for i in range(1, len(values)):
      if abs(smoothed[-1] - values[i]) >= 12:
          if smoothed[-1] < values[i]:
              smoothed.append(values[i] - 12)
          else:
              smoothed.append(values[i] + 12)
      else:
          smoothed.append(values[i])

  smoothed_score = copy.deepcopy(escore_notes)

  for i, e in enumerate(smoothed_score):
    esn_octave = escore_notes[i][4] // 12
    e[4] = (esn_octave * 12) + smoothed[i]

  return smoothed_score

###################################################################################

def add_base_to_escore_notes(escore_notes,
                             base_octave=2, 
                             base_channel=2, 
                             base_patch=35, 
                             base_max_velocity=120,
                             return_base=False
                             ):
  

  score = copy.deepcopy(escore_notes)

  cscore = chordify_score([1000, score])

  base_score = []

  for c in cscore:
    chord = sorted([e for e in c if e[3] != 9], key=lambda x: x[4], reverse=True)
    base_score.append(chord[-1])

  base_score = smooth_escore_notes(base_score)

  for e in base_score:
    e[3] = base_channel
    e[4] = (base_octave * 12) + (e[4] % 12)
    e[5] = e[4]
    e[6] = base_patch

  adjust_score_velocities(base_score, base_max_velocity)

  if return_base:
    final_score = sorted(base_score, key=lambda x: (x[1], -x[4], x[6]))

  else:
    final_score = sorted(escore_notes + base_score, key=lambda x: (x[1], -x[4], x[6]))

  return final_score

###################################################################################

def add_drums_to_escore_notes(escore_notes, 
                              heavy_drums_pitches=[36, 38, 47],
                              heavy_drums_velocity=110,
                              light_drums_pitches=[51, 54],
                              light_drums_velocity=127,
                              drums_max_velocity=127,
                              drums_ratio_time_divider=4,
                              return_drums=False
                              ):

  score = copy.deepcopy([e for e in escore_notes if e[3] != 9])

  cscore = chordify_score([1000, score])

  drums_score = []

  for c in cscore:
    min_dur = max(1, min([e[2] for e in c]))
    if not (c[0][1] % drums_ratio_time_divider):
      drum_note = ['note', c[0][1], min_dur, 9, heavy_drums_pitches[c[0][4] % len(heavy_drums_pitches)], heavy_drums_velocity, 128]
    else:
      drum_note = ['note', c[0][1], min_dur, 9, light_drums_pitches[c[0][4] % len(light_drums_pitches)], light_drums_velocity, 128]
    drums_score.append(drum_note)

  adjust_score_velocities(drums_score, drums_max_velocity)

  if return_drums:
    final_score = sorted(drums_score, key=lambda x: (x[1], -x[4], x[6]))

  else:
    final_score = sorted(score + drums_score, key=lambda x: (x[1], -x[4], x[6]))

  return final_score

###################################################################################

def find_pattern_start_indexes(values, pattern):

  start_indexes = []

  count = 0

  for i in range(len(values)- len(pattern)):
    chunk = values[i:i+len(pattern)]

    if chunk == pattern:
      start_indexes.append(i)

  return start_indexes

###################################################################################

def escore_notes_lrno_pattern(escore_notes, mode='chords'):

  cscore = chordify_score([1000, escore_notes])

  checked_cscore = advanced_check_and_fix_chords_in_chordified_score(cscore)

  chords_toks = []
  chords_idxs = []

  for i, c in enumerate(checked_cscore[0]):

    pitches = sorted([p[4] for p in c if p[3] != 9], reverse=True)
    tchord = pitches_to_tones_chord(pitches)

    if tchord:
      
      if mode == 'chords':
        token = ALL_CHORDS_FULL.index(tchord)
      
      elif mode == 'high pitches':
        token = pitches[0]

      elif mode == 'high pitches tones':
        token = pitches[0] % 12

      else:
        token = ALL_CHORDS_FULL.index(tchord)

      chords_toks.append(token)
      chords_idxs.append(i)

  lrno_pats = find_lrno_patterns(chords_toks)

  if lrno_pats:

    lrno_pattern = list(lrno_pats[0][2])

    start_idx = chords_idxs[find_pattern_start_indexes(chords_toks, lrno_pattern)[0]]
    end_idx = chords_idxs[start_idx + len(lrno_pattern)]

    return recalculate_score_timings(flatten(cscore[start_idx:end_idx]))

  else:
    return None

###################################################################################

def chordified_score_pitches(chordified_score, 
                             mode='dominant',
                             return_tones=False,
                             omit_drums=True,
                             score_patch=-1,
                             channels_index=3,
                             pitches_index=4,
                             patches_index=6                          
                            ):

  results = []

  for c in chordified_score:
    
    if -1 < score_patch < 128:
      ptcs = sorted([e[pitches_index] for e in c if e[channels_index] != 9 and e[patches_index] == score_patch], reverse=True)
    
    else:
      ptcs = sorted([e[pitches_index] for e in c if e[channels_index] != 9], reverse=True)

    if ptcs:

      if mode == 'dominant':
        
        mtone = statistics.mode([p % 12 for p in ptcs])
        
        if return_tones:
          results.append(mtone)
        
        else:
          results.append(sorted(set([p for p in ptcs if p % 12 == mtone]), reverse=True))
      
      elif mode == 'high':
        
        if return_tones:
          results.append(ptcs[0] % 12)

        else:
          results.append([ptcs[0]])

      elif mode == 'base':

        if return_tones:
          results.append(ptcs[-1] % 12)

        else:
          results.append([ptcs[-1]])

      elif mode == 'average':

        if return_tones:
          results.append(statistics.mean(ptcs) % 12)

        else:
          results.append([statistics.mean(ptcs)])

      else:

        mtone = statistics.mode([p % 12 for p in ptcs])
        
        if return_tones:
          results.append(mtone)
        
        else:
          results.append(sorted(set([p for p in ptcs if p % 12 == mtone]), reverse=True))

    else:

      if not omit_drums:
        
        if return_tones:
          results.append(-1)
        
        else:
          results.append([-1])

  return results
  
###################################################################################

def escore_notes_times_tones(escore_notes, 
                             tones_mode='dominant', 
                             return_abs_times=True,
                             omit_drums=False
                             ):

  cscore = chordify_score([1000, escore_notes])
  
  tones = chordified_score_pitches(cscore, return_tones=True, mode=tones_mode, omit_drums=omit_drums)

  if return_abs_times:
    times = sorted([c[0][1] for c in cscore])
  
  else:
    times = escore_notes_delta_times(escore_notes, omit_zeros=True, omit_drums=omit_drums)
    
    if len(times) != len(tones):
      times = [0] + times

  return [[t, to] for t, to in zip(times, tones)]

###################################################################################

def escore_notes_middle(escore_notes, 
                        length=10, 
                        use_chords=True
                        ):

  if use_chords:
    score = chordify_score([1000, escore_notes])

  else:
    score = escore_notes

  middle_idx = len(score) // 2

  slen = min(len(score) // 2, length // 2)

  start_idx = middle_idx - slen
  end_idx = middle_idx + slen

  if use_chords:
    return flatten(score[start_idx:end_idx])

  else:
    return score[start_idx:end_idx]

###################################################################################

ALL_CHORDS_FULL = [[0], [0, 3], [0, 3, 5], [0, 3, 5, 8], [0, 3, 5, 9], [0, 3, 5, 10], [0, 3, 6],
                  [0, 3, 6, 9], [0, 3, 6, 10], [0, 3, 7], [0, 3, 7, 10], [0, 3, 8], [0, 3, 9],
                  [0, 3, 10], [0, 4], [0, 4, 6], [0, 4, 6, 9], [0, 4, 6, 10], [0, 4, 7],
                  [0, 4, 7, 10], [0, 4, 8], [0, 4, 9], [0, 4, 10], [0, 5], [0, 5, 8], [0, 5, 9],
                  [0, 5, 10], [0, 6], [0, 6, 9], [0, 6, 10], [0, 7], [0, 7, 10], [0, 8], [0, 9],
                  [0, 10], [1], [1, 4], [1, 4, 6], [1, 4, 6, 9], [1, 4, 6, 10], [1, 4, 6, 11],
                  [1, 4, 7], [1, 4, 7, 10], [1, 4, 7, 11], [1, 4, 8], [1, 4, 8, 11], [1, 4, 9],
                  [1, 4, 10], [1, 4, 11], [1, 5], [1, 5, 8], [1, 5, 8, 11], [1, 5, 9],
                  [1, 5, 10], [1, 5, 11], [1, 6], [1, 6, 9], [1, 6, 10], [1, 6, 11], [1, 7],
                  [1, 7, 10], [1, 7, 11], [1, 8], [1, 8, 11], [1, 9], [1, 10], [1, 11], [2],
                  [2, 5], [2, 5, 8], [2, 5, 8, 11], [2, 5, 9], [2, 5, 10], [2, 5, 11], [2, 6],
                  [2, 6, 9], [2, 6, 10], [2, 6, 11], [2, 7], [2, 7, 10], [2, 7, 11], [2, 8],
                  [2, 8, 11], [2, 9], [2, 10], [2, 11], [3], [3, 5], [3, 5, 8], [3, 5, 8, 11],
                  [3, 5, 9], [3, 5, 10], [3, 5, 11], [3, 6], [3, 6, 9], [3, 6, 10], [3, 6, 11],
                  [3, 7], [3, 7, 10], [3, 7, 11], [3, 8], [3, 8, 11], [3, 9], [3, 10], [3, 11],
                  [4], [4, 6], [4, 6, 9], [4, 6, 10], [4, 6, 11], [4, 7], [4, 7, 10], [4, 7, 11],
                  [4, 8], [4, 8, 11], [4, 9], [4, 10], [4, 11], [5], [5, 8], [5, 8, 11], [5, 9],
                  [5, 10], [5, 11], [6], [6, 9], [6, 10], [6, 11], [7], [7, 10], [7, 11], [8],
                  [8, 11], [9], [10], [11]]

###################################################################################

def escore_notes_to_parsons_code(escore_notes,
                                 times_index=1,
                                 pitches_index=4,
                                 return_as_list=False
                                 ):
  
  parsons = "*"
  parsons_list = []

  prev = ['note', -1, -1, -1, -1, -1, -1]

  for e in escore_notes:
    if e[times_index] != prev[times_index]:

      if e[pitches_index] > prev[pitches_index]:
          parsons += "U"
          parsons_list.append(1)

      elif e[pitches_index] < prev[pitches_index]:
          parsons += "D"
          parsons_list.append(-1)

      elif e[pitches_index] == prev[pitches_index]:
          parsons += "R"
          parsons_list.append(0)
      
      prev = e

  if return_as_list:
    return parsons_list
  
  else:
    return parsons

###################################################################################

def all_consequtive(list_of_values):
  return all(b > a for a, b in zip(list_of_values[:-1], list_of_values[1:]))

###################################################################################

def escore_notes_patches(escore_notes, patches_index=6):
  return sorted(set([e[patches_index] for e in escore_notes]))

###################################################################################

def build_suffix_array(lst):

    n = len(lst)

    suffixes = [(lst[i:], i) for i in range(n)]
    suffixes.sort()
    suffix_array = [suffix[1] for suffix in suffixes]

    return suffix_array

###################################################################################

def build_lcp_array(lst, suffix_array):

    n = len(lst)
    rank = [0] * n
    lcp = [0] * n

    for i, suffix in enumerate(suffix_array):
      rank[suffix] = i

    h = 0

    for i in range(n):
      if rank[i] > 0:

        j = suffix_array[rank[i] - 1]

        while i + h < n and j + h < n and lst[i + h] == lst[j + h]:
          h += 1

        lcp[rank[i]] = h

        if h > 0:
          h -= 1

    return lcp

###################################################################################

def find_lrno_pattern_fast(lst):
    n = len(lst)
    if n == 0:
      return []

    suffix_array = build_suffix_array(lst)
    lcp_array = build_lcp_array(lst, suffix_array)

    max_len = 0
    start_index = 0

    for i in range(1, n):
      if lcp_array[i] > max_len:
        if suffix_array[i] + lcp_array[i] <= suffix_array[i - 1] or suffix_array[i - 1] + lcp_array[i - 1] <= suffix_array[i]:
          max_len = lcp_array[i]
          start_index = suffix_array[i]

    return lst[start_index:start_index + max_len]

###################################################################################

def find_chunk_indexes(original_list, chunk, ignore_index=-1):

  chunk_length = len(chunk)

  for i in range(len(original_list) - chunk_length + 1):

    chunk_index = 0
    start_index = ignore_index

    for j in range(i, len(original_list)):
      if original_list[j] == chunk[chunk_index]:

        if start_index == ignore_index:
          start_index = j

        chunk_index += 1

        if chunk_index == chunk_length:
          return [start_index, j]

      elif original_list[j] != ignore_index:
        break

  return None

###################################################################################

def escore_notes_lrno_pattern_fast(escore_notes, 
                                   channels_index=3, 
                                   pitches_index=4, 
                                   zero_start_time=True
                                  ):

  cscore = chordify_score([1000, escore_notes])

  score_chords = []

  for c in cscore:

    tchord = sorted(set([e[pitches_index] % 12 for e in c if e[channels_index] != 9]))

    chord_tok = -1

    if tchord:

      if tchord not in ALL_CHORDS_FULL:
        tchord = check_and_fix_tones_chord(tchord)

      chord_tok = ALL_CHORDS_FULL.index(tchord)

    score_chords.append(chord_tok)

  schords = [c for c in score_chords if c != -1]

  lrno = find_lrno_pattern_fast(schords)

  if lrno:

    sidx, eidx = find_chunk_indexes(score_chords, lrno)

    escore_notes_lrno_pattern = flatten(cscore[sidx:eidx+1])

    if escore_notes_lrno_pattern is not None:

      if zero_start_time:
        return recalculate_score_timings(escore_notes_lrno_pattern)

      else:
        return escore_notes_lrno_pattern

    else:
      return None
  
  else:
    return None

###################################################################################

def escore_notes_durations_counter(escore_notes, 
                                   min_duration=0, 
                                   durations_index=2, 
                                   channels_index=3
                                   ):
  
  escore = [e for e in escore_notes if e[channels_index] != 9]
  durs = [e[durations_index] for e in escore if e[durations_index] >= min_duration]
  zero_durs = sum([1 for e in escore if e[durations_index] == 0])
  
  return [len(durs), len(escore), zero_durs, Counter(durs).most_common()]

###################################################################################

def count_bad_chords_in_chordified_score(chordified_score,  
                                         pitches_index=4,
                                         patches_index=6,
                                         max_patch=127, 
                                         use_full_chords=False
                                         ):

  if use_full_chords:
    CHORDS = ALL_CHORDS_FULL

  else:
    CHORDS = ALL_CHORDS_SORTED

  bad_chords_count = 0

  for c in chordified_score:

    cpitches = [e[pitches_index] for e in c if e[patches_index] <= max_patch]
    tones_chord = sorted(set([p % 12 for p in cpitches]))

    if tones_chord:
      if tones_chord not in CHORDS:
        bad_chords_count += 1

  return [bad_chords_count, len(chordified_score)]

###################################################################################

def needleman_wunsch_aligner(seq1,
                             seq2,
                             align_idx,
                             gap_penalty=-1,
                             match_score=2,
                             mismatch_penalty=-1
                             ):
    
    n = len(seq1)
    m = len(seq2)
    
    score_matrix = [[0] * (m + 1) for _ in range(n + 1)]

    for i in range(1, n + 1):
        score_matrix[i][0] = gap_penalty * i
    for j in range(1, m + 1):
        score_matrix[0][j] = gap_penalty * j

    for i in range(1, n + 1):
        for j in range(1, m + 1):
            match = score_matrix[i-1][j-1] + (match_score if seq1[i-1][align_idx] == seq2[j-1][align_idx] else mismatch_penalty)
            delete = score_matrix[i-1][j] + gap_penalty
            insert = score_matrix[i][j-1] + gap_penalty
            score_matrix[i][j] = max(match, delete, insert)

    align1, align2 = [], []
    i, j = n, m
    
    while i > 0 and j > 0:
        
        score = score_matrix[i][j]
        score_diag = score_matrix[i-1][j-1]
        score_up = score_matrix[i-1][j]
        score_left = score_matrix[i][j-1]

        if score == score_diag + (match_score if seq1[i-1][align_idx] == seq2[j-1][align_idx] else mismatch_penalty):
            align1.append(seq1[i-1])
            align2.append(seq2[j-1])
            i -= 1
            j -= 1
        elif score == score_up + gap_penalty:
            align1.append(seq1[i-1])
            align2.append([None] * 6)
            i -= 1
        elif score == score_left + gap_penalty:
            align1.append([None] * 6)
            align2.append(seq2[j-1])
            j -= 1

    while i > 0:
        align1.append(seq1[i-1])
        align2.append([None] * 6)
        i -= 1
    while j > 0:
        align1.append([None] * 6)
        align2.append(seq2[j-1])
        j -= 1

    align1.reverse()
    align2.reverse()

    return align1, align2

###################################################################################

def align_escore_notes_to_escore_notes(src_escore_notes,
                                       trg_escore_notes,
                                       recalculate_scores_timings=True,
                                       pitches_idx=4
                                       ):
    
    if recalculate_scores_timings:
        src_escore_notes = recalculate_score_timings(src_escore_notes)
        trg_escore_notes = recalculate_score_timings(trg_escore_notes)
        
    src_align1, trg_align2 = needleman_wunsch_aligner(src_escore_notes, trg_escore_notes, pitches_idx)

    aligned_scores = [[al[0], al[1]] for al in zip(src_align1, trg_align2) if al[0][0] is not None and al[1][0] is not None]
    
    return aligned_scores

###################################################################################

def t_to_n(arr, si, t):

    ct = 0
    ci = si
    
    while ct + arr[ci][1] < t and ci < len(arr)-1:
        ct += arr[ci][1]
        ci += 1

    return ci+1

###################################################################################

def max_sum_chunk_idxs(arr, t=255):

    n = t_to_n(arr, 0, t)
    
    if n > len(arr):
        return [0, n]

    max_sum = 0
    max_sum_start_index = 0
    
    max_sum_start_idxs = [0, len(arr), sum([a[0] for a in arr])]

    for i in range(len(arr)):

        n = t_to_n(arr, i, t)

        current_sum  = sum([a[0] for a in arr[i:n]])
        current_time = sum([a[1] for a in arr[i:n]])

        if current_sum > max_sum and current_time <= t:
            max_sum = current_sum
            max_sum_start_idxs = [i, n, max_sum]

    return max_sum_start_idxs

###################################################################################

def find_highest_density_escore_notes_chunk(escore_notes, max_chunk_time=512):

    dscore = delta_score_notes(escore_notes)
    
    cscore = chordify_score([d[1:] for d in dscore])

    notes_counts = [[len(c), c[0][0]] for c in cscore]

    msc_idxs = max_sum_chunk_idxs(notes_counts, max_chunk_time)

    chunk_dscore = [['note'] + c for c in flatten(cscore[msc_idxs[0]:msc_idxs[1]])]

    chunk_escore = recalculate_score_timings(delta_score_to_abs_score(chunk_dscore))
    
    return chunk_escore

###################################################################################

def advanced_add_drums_to_escore_notes(escore_notes,
                                       main_beat_min_dtime=5,
                                       main_beat_dtime_thres=1,
                                       drums_durations_value=2,
                                       drums_pitches_velocities=[(36, 100), 
                                                                 (38, 100), 
                                                                 (41, 125)],
                                       recalculate_score_timings=True,
                                       intro_drums_count=4,
                                       intro_drums_time_k=4,
                                       intro_drums_pitch_velocity=[37, 110]
                                      ):

    #===========================================================
    
    new_dscore = delta_score_notes(escore_notes)

    times = [d[1] for d in new_dscore if d[1] != 0]

    time = [c[0] for c in Counter(times).most_common() if c[0] >= main_beat_min_dtime][0]

    #===========================================================

    if intro_drums_count > 0:

        drums_score = []

        for i in range(intro_drums_count):

            if i == 0:
                dtime = 0

            else:
                dtime = time
            
            drums_score.append(['note', 
                                dtime * intro_drums_time_k, 
                                drums_durations_value, 
                                9, 
                                intro_drums_pitch_velocity[0], 
                                intro_drums_pitch_velocity[1], 
                                128]
                              )
            
        new_dscore[0][1] = time * intro_drums_time_k

        new_dscore = drums_score + new_dscore

    #===========================================================

    for e in new_dscore:
    
        if abs(e[1] - time) == main_beat_dtime_thres:
            e[1] = time

        if recalculate_score_timings:
        
            if e[1] % time != 0 and e[1] > time:
                if e[1] % time < time // 2:
                    e[1] -= e[1] % time
        
                else:
                    e[1] += time - (e[1] % time)

    #===========================================================

    drums_score = []
    
    dtime = 0
    
    idx = 0
    
    for i, e in enumerate(new_dscore):
        
        drums_score.append(e)
        
        dtime += e[1]

        if e[1] != 0:
            idx += 1

        if i >= intro_drums_count:
    
            if (e[1] % time == 0 and e[1] != 0) or i == 0:
                
                if idx % 2 == 0 and e[1] != 0:
                    drums_score.append(['note', 
                                        0, 
                                        drums_durations_value, 
                                        9, 
                                        drums_pitches_velocities[0][0], 
                                        drums_pitches_velocities[0][1], 
                                        128]
                                      )
                    
                if idx % 2 != 0 and e[1] != 0:
                    drums_score.append(['note', 
                                        0, 
                                        drums_durations_value, 
                                        9, 
                                        drums_pitches_velocities[1][0], 
                                        drums_pitches_velocities[1][1], 
                                        128]
                                      )
        
                if idx % 4 == 0 and e[1] != 0:
                    drums_score.append(['note', 
                                        0, 
                                        drums_durations_value, 
                                        9, 
                                        drums_pitches_velocities[2][0], 
                                        drums_pitches_velocities[2][1], 
                                        128]
                                      )

    #===========================================================
    
    return delta_score_to_abs_score(drums_score)

###################################################################################

MIDI_TEXT_EVENTS = ['text_event',
                    'copyright_text_event',
                    'track_name',
                    'instrument_name',
                    'lyric',
                    'marker',
                    'cue_point',
                    'text_event_08',
                    'text_event_09',
                    'text_event_0a',
                    'text_event_0b',
                    'text_event_0c',
                    'text_event_0d',
                    'text_event_0e',
                    'text_event_0f'
                  ]

###################################################################################

def get_md5_hash(data):
    return hashlib.md5(data).hexdigest()

###################################################################################

def is_valid_md5_hash(string):
    return bool(re.match(r'^[a-fA-F0-9]{32}$', string))

###################################################################################

def clean_string(original_string,
                 regex=r'[^a-zA-Z0-9 ]',
                 remove_duplicate_spaces=True,
                 title=False
                ):
    
    cstr1 = re.sub(regex, '', original_string)

    if title:
        cstr1 = cstr1.title()

    if remove_duplicate_spaces:
        return re.sub(r'[ ]+', ' ', cstr1).strip()

    else:
        return cstr1
    
###################################################################################
    
def encode_to_ord(text, chars_range=[], sub_char='', chars_shift=0):

    if not chars_range:
        chars_range = [32] + list(range(65, 91)) + list(range(97, 123))

    if sub_char:
        chars_range.append(ord(sub_char))

    chars_range = sorted(set(chars_range))

    encoded = []
    
    for char in text:
        if ord(char) in chars_range:
            encoded.append(chars_range.index(ord(char)) + chars_shift)
            
        else:
            if sub_char:
                encoded.append(chars_range.index(ord(sub_char)) + chars_shift)
        
    
    return [encoded, chars_range]

###################################################################################

def decode_from_ord(ord_list, chars_range=[], sub_char='', chars_shift=0):

    if not chars_range:
        chars_range = [32] + list(range(65, 91)) + list(range(97, 123))

    if sub_char:
        chars_range.append(ord(sub_char))

    chars_range = sorted(set(chars_range))
        
    return ''.join(chr(chars_range[num-chars_shift]) if 0 <= num-chars_shift < len(chars_range) else sub_char for num in ord_list)

###################################################################################

def lists_similarity(list1, list2, by_elements=True, by_sum=True):
    
    if len(list1) != len(list2):
        return -1
    
    element_ratios = []
    total_counts1 = sum(list1)
    total_counts2 = sum(list2)

    for a, b in zip(list1, list2):
        if a == 0 and b == 0:
            element_ratios.append(1)
        elif a == 0 or b == 0:
            element_ratios.append(0)
        else:
            element_ratios.append(min(a, b) / max(a, b))

    average_element_ratio = sum(element_ratios) / len(element_ratios)

    total_counts_ratio = min(total_counts1, total_counts2) / max(total_counts1, total_counts2)

    if by_elements and by_sum:
        return (average_element_ratio + total_counts_ratio) / 2

    elif by_elements and not by_sum:
        return average_element_ratio

    elif not by_elements and by_sum:
        return total_counts_ratio

    else:
        return -1

###################################################################################

def find_indexes(lst, value, mode='equal', dual_mode=True):

    indexes = []

    if mode == 'equal' or dual_mode:    
        indexes.extend([index for index, elem in enumerate(lst) if elem == value])

    if mode == 'smaller':
        indexes.extend([index for index, elem in enumerate(lst) if elem < value])

    if mode == 'larger':
        indexes.extend([index for index, elem in enumerate(lst) if elem > value])

    return sorted(set(indexes))

###################################################################################

NUMERALS = ["one", "two", "three", "four", 
            "five", "six", "seven", "eight", 
            "nine", "ten", "eleven", "twelve", 
            "thirteen", "fourteen", "fifteen", "sixteen"
           ]

SEMITONES = ["C", "C#", "D", "D#", "E", "F", "F#", "G", "G#", "A", "A#", "B"]

BASIC_SCALES = ['Major', 'Minor']

###################################################################################

def alpha_str(string):
    astr = re.sub(r'[^a-zA-Z ()0-9]', '', string).strip()
    return re.sub(r'\s+', ' ', astr).strip()

###################################################################################

def escore_notes_to_text_description(escore_notes, 
                                     song_name='', 
                                     artist_name='',
                                     timings_divider=16,
                                    ):

    #==============================================================================

    song_time_min = (escore_notes[-1][1] * timings_divider) / 1000 / 60

    if song_time_min < 1.5:
        song_length = 'short'
    
    elif 1.5 <= song_time_min < 2.5:
        song_length = 'average'
    
    elif song_time_min >= 2.5:
        song_length = 'long'

    #==============================================================================

    escore_times = [e[1] for e in escore_notes if e[3] != 9]
    
    comp_type = ''

    if len(escore_times) > 0:
        if len(escore_times) == len(set(escore_times)):
            comp_type = 'monophonic melody'
            ctype = 'melody'
        
        elif len(escore_times) >= len(set(escore_times)) and 1 in Counter(escore_times).values():
            comp_type = 'melody and accompaniment'
            ctype = 'song'
        
        elif len(escore_times) >= len(set(escore_times)) and 1 not in Counter(escore_times).values():
            comp_type = 'accompaniment'
            ctype = 'song'
    
    else:
        comp_type = 'drum track'
        ctype = 'drum track'

    #==============================================================================

    all_patches = [e[6] for e in escore_notes]

    patches = ordered_set(all_patches)[:16]
    
    instruments = [alpha_str(MIDI.Number2patch[p]) for p in patches if p < 128]
    
    if instruments:

        nd_patches_counts = Counter([p for p in all_patches if p < 128]).most_common()

        dominant_instrument = alpha_str(MIDI.Number2patch[nd_patches_counts[0][0]])

    if 128 in patches:
        drums_present = True

        drums_pitches = [e[4] for e in escore_notes if e[3] == 9]

        most_common_drums = [alpha_str(MIDI.Notenum2percussion[p[0]]) for p in Counter(drums_pitches).most_common(3) if p[0] in MIDI.Notenum2percussion]

    else:
        drums_present = False

    #==============================================================================

    pitches = [e[4] for e in escore_notes if e[3] != 9]
    
    key = ''
    
    if pitches:
        key = SEMITONES[statistics.mode(pitches) % 12]

    #==============================================================================
    
    scale = ''
    mood = ''
    
    if pitches:
    
        result = escore_notes_scale(escore_notes)
        
        scale = result[0]
        mood = result[1].split(' ')[0].lower()

    #==============================================================================
    
    if pitches:
    
        escore_averages = escore_notes_averages(escore_notes, return_ptcs_and_vels=True)

        if escore_averages[0] < (128 / timings_divider):
            rythm = 'fast'
        
        elif (128 / timings_divider) <= escore_averages[0] <= (192 / timings_divider):
            rythm = 'average'
        
        elif escore_averages[0] > (192 / timings_divider):
            rythm = 'slow'
        
        if escore_averages[1] < (256 / timings_divider):
            tempo = 'fast'
        
        elif (256 / timings_divider) <= escore_averages[1] <= (384 / timings_divider):
            tempo = 'average'
        
        elif escore_averages[1] > (384 / timings_divider):
            tempo = 'slow'
        
        if escore_averages[2] < 50:
            tone = 'bass'
        
        elif 50 <= escore_averages[2] <= 70:
            tone = 'midrange'
        
        elif escore_averages[2] > 70:
            tone = 'treble'
        
        if escore_averages[3] < 64:
            dynamics = 'quiet'
        
        elif 64 <= escore_averages[3] <= 96:
            dynamics = 'average'
        
        elif escore_averages[3] > 96:
            dynamics = 'loud'

    #==============================================================================
            
    mono_melodies = escore_notes_monoponic_melodies([e for e in escore_notes if e[6] < 88])
 
    lead_melodies = []
    base_melodies = []
 
    if mono_melodies:
            
        for mel in mono_melodies:
            
            escore_avgs = escore_notes_pitches_range(escore_notes, range_patch = mel[0])
            
            if mel[0] in LEAD_INSTRUMENTS and escore_avgs[3] > 60:
                lead_melodies.append([MIDI.Number2patch[mel[0]], mel[1]])

            elif mel[0] in BASE_INSTRUMENTS and escore_avgs[3] <= 60:
                base_melodies.append([MIDI.Number2patch[mel[0]], mel[1]])
    
        if lead_melodies:
            lead_melodies.sort(key=lambda x: x[1], reverse=True)
            
        if base_melodies:
            base_melodies.sort(key=lambda x: x[1], reverse=True)

    #==============================================================================
        
    description = ''

    if song_name != '':
        description = 'The song "' + song_name + '"'
    
    if artist_name != '':
        description += ' by ' + artist_name

    if song_name != '' or artist_name != '':
        description += '.'
        description += '\n'
    
    description += 'The song is '

    if song_length != 'average':
        description += 'a ' + song_length

    else:
        description += 'an ' + song_length

    description += ' duration '

    description += comp_type + ' composition'

    if comp_type != 'drum track':

        if drums_present:
            description += ' with drums'
    
        else:
            description += ' without drums'
    
        if key and scale:
            description += ' in ' + key + ' ' + scale

    description += '.'

    description += '\n'
    
    if pitches:
        
        if comp_type not in ['monophonic melody', 'drum track']:

            description += 'This ' + mood + ' song has '
                
        elif comp_type == 'monophonic melody':
            
            description += 'This ' + mood + ' melody has '
            
        else:
            description += 'TThis drum track has '
            
        description += rythm + ' rythm, '
        description += tempo + ' tempo, '
        description += tone + ' tone and '
        description += dynamics + ' dynamics.'

        description += '\n'
        
        if instruments:
            
            if comp_type not in ['monophonic melody', 'drum track']:
                
                description += 'The song '
                
                if len(instruments) > 1:
                
                    description += 'features ' + NUMERALS[max(0, min(15, len(instruments)-1))] + ' instruments: '
                    description += ', '.join(instruments[:-1]) + ' and ' + instruments[-1] + '.'
                    
                else:
                    description += 'features one instrument: ' + instruments[0] + '.'
                    
                
                description += '\n'
                
                if instruments[0] != dominant_instrument:
                    description += 'The song opens with ' + instruments[0]

                    description += ' and primarily performed on ' + dominant_instrument + '.'
                    
                else:
                    description += 'The song opens with and performed on ' + instruments[0] + '.'
                    
                description += '\n'
                    
    if lead_melodies or base_melodies:
        
        tm_count = len(lead_melodies + base_melodies)
        
        if tm_count == 1:
            
            if lead_melodies:
                description += 'The song has one distinct lead melody played on ' + lead_melodies[0][0] + '.'
                
            else:
                description += 'The song has one distinct base melody played on ' + base_melodies[0][0] + '.'
            
            description += '\n'
            
        else:
            
            if lead_melodies and not base_melodies:
                
                if len(lead_melodies) == 1:
                    mword = 'melody'
                    
                else:
                    mword = 'melodies'
            
                description += 'The song has ' + NUMERALS[len(lead_melodies)-1] + ' distinct lead ' + mword + ' played on '
                
                if len(lead_melodies) > 1:               
                    description += ', '.join([l[0] for l in lead_melodies[:-1]]) + ' and ' + lead_melodies[-1][0] + '.'
                    
                else:
                    description += lead_melodies[0][0] + '.'
                    
                description += '\n'
            
            elif base_melodies and not lead_melodies:
                
                if len(base_melodies) == 1:
                    mword = 'melody'
                    
                else:
                    mword = 'melodies'
        
                description += 'The song has ' + NUMERALS[len(base_melodies)-1] + ' distinct base ' + mword + ' played on '
                
                if len(base_melodies) > 1:               
                    description += ', '.join([b[0] for b in base_melodies[:-1]]) + ' and ' + base_melodies[-1][0] + '.'
                    
                else:
                    description += base_melodies[0][0] + '.'
                
                description += '\n'        

            elif lead_melodies and base_melodies:
                
                if len(lead_melodies) == 1:
                    lmword = 'melody'
                    
                else:
                    lmword = 'melodies'
        
                description += 'The song has ' + NUMERALS[len(lead_melodies)-1] + ' distinct lead ' + lmword + ' played on '
                
                if len(lead_melodies) > 1:               
                    description += ', '.join([l[0] for l in lead_melodies[:-1]]) + ' and ' + lead_melodies[-1][0] + '.'
                    
                else:
                    description += lead_melodies[0][0] + '.'
                    
                if len(base_melodies) == 1:
                    bmword = 'melody'
                    
                else:
                    bmword = 'melodies'
        
                description += ' And ' + NUMERALS[len(base_melodies)-1] + ' distinct base ' + bmword + ' played on '
                
                if len(base_melodies) > 1:               
                    description += ', '.join([b[0] for b in base_melodies[:-1]]) + ' and ' + base_melodies[-1][0] + '.'
                    
                else:
                    description += base_melodies[0][0] + '.'
                
                description += '\n'

    if drums_present and most_common_drums:
        
        if len(most_common_drums) > 1:
            description += 'The drum track has predominant '
            description += ', '.join(most_common_drums[:-1]) + ' and ' + most_common_drums[-1] + '.'
            
        else:
            description += 'The drum track is a solo '
            description += most_common_drums[0] + '.'

        description += '\n'
        
    #==============================================================================

    return description

###################################################################################

#==================================================================================
#
# Below constants code is a courtesy of MidiTok
#
# Retrieved on 12/29/2024
#
# https://github.com/Natooz/MidiTok/blob/main/src/miditok/constants.py
#
#==================================================================================

MIDI_FILES_EXTENSIONS = [".mid", ".midi", ".kar", ".MID", ".MIDI", ".KAR"]

# The recommended pitches for piano in the GM2 specs are from 21 to 108
PIANO_PITCH_RANGE = range(21, 109)

# Chord params
# "chord_unknown" specifies the range of number of notes that can form "unknown" chords
# (that do not fit in "chord_maps") to add in tokens.
# Known chord maps, with 0 as root note
BASIC_CHORDS_MAP = {
    "min": (0, 3, 7),
    "maj": (0, 4, 7),
    "dim": (0, 3, 6),
    "aug": (0, 4, 8),
    "sus2": (0, 2, 7),
    "sus4": (0, 5, 7),
    "7dom": (0, 4, 7, 10),
    "7min": (0, 3, 7, 10),
    "7maj": (0, 4, 7, 11),
    "7halfdim": (0, 3, 6, 10),
    "7dim": (0, 3, 6, 9),
    "7aug": (0, 4, 8, 11),
    "9maj": (0, 4, 7, 10, 14),
    "9min": (0, 4, 7, 10, 13),
    }

# Drums
# Recommended range from the GM2 specs
DRUMS_PITCH_RANGE = range(27, 90)

# Used with chords
PITCH_CLASSES = ["C", "C#", "D", "D#", "E", "F", "F#", "G", "G#", "A", "A#", "B"]

# http://newt.phys.unsw.edu.au/jw/notes.html
# https://www.midi.org/specifications

# index i = program i+1 in the GM2 specs (7. Appendix A)
# index i = program i as retrieved by packages
MIDI_INSTRUMENTS = [
    # Piano
    {"name": "Acoustic Grand Piano", "pitch_range": range(21, 109)},
    {"name": "Bright Acoustic Piano", "pitch_range": range(21, 109)},
    {"name": "Electric Grand Piano", "pitch_range": range(21, 109)},
    {"name": "Honky-tonk Piano", "pitch_range": range(21, 109)},
    {"name": "Electric Piano 1", "pitch_range": range(28, 104)},
    {"name": "Electric Piano 2", "pitch_range": range(28, 104)},
    {"name": "Harpsichord", "pitch_range": range(41, 90)},
    {"name": "Clavi", "pitch_range": range(36, 97)},
    # Chromatic Percussion
    {"name": "Celesta", "pitch_range": range(60, 109)},
    {"name": "Glockenspiel", "pitch_range": range(72, 109)},
    {"name": "Music Box", "pitch_range": range(60, 85)},
    {"name": "Vibraphone", "pitch_range": range(53, 90)},
    {"name": "Marimba", "pitch_range": range(48, 85)},
    {"name": "Xylophone", "pitch_range": range(65, 97)},
    {"name": "Tubular Bells", "pitch_range": range(60, 78)},
    {"name": "Dulcimer", "pitch_range": range(60, 85)},
    # Organs
    {"name": "Drawbar Organ", "pitch_range": range(36, 97)},
    {"name": "Percussive Organ", "pitch_range": range(36, 97)},
    {"name": "Rock Organ", "pitch_range": range(36, 97)},
    {"name": "Church Organ", "pitch_range": range(21, 109)},
    {"name": "Reed Organ", "pitch_range": range(36, 97)},
    {"name": "Accordion", "pitch_range": range(53, 90)},
    {"name": "Harmonica", "pitch_range": range(60, 85)},
    {"name": "Tango Accordion", "pitch_range": range(53, 90)},
    # Guitars
    {"name": "Acoustic Guitar (nylon)", "pitch_range": range(40, 85)},
    {"name": "Acoustic Guitar (steel)", "pitch_range": range(40, 85)},
    {"name": "Electric Guitar (jazz)", "pitch_range": range(40, 87)},
    {"name": "Electric Guitar (clean)", "pitch_range": range(40, 87)},
    {"name": "Electric Guitar (muted)", "pitch_range": range(40, 87)},
    {"name": "Overdriven Guitar", "pitch_range": range(40, 87)},
    {"name": "Distortion Guitar", "pitch_range": range(40, 87)},
    {"name": "Guitar Harmonics", "pitch_range": range(40, 87)},
    # Bass
    {"name": "Acoustic Bass", "pitch_range": range(28, 56)},
    {"name": "Electric Bass (finger)", "pitch_range": range(28, 56)},
    {"name": "Electric Bass (pick)", "pitch_range": range(28, 56)},
    {"name": "Fretless Bass", "pitch_range": range(28, 56)},
    {"name": "Slap Bass 1", "pitch_range": range(28, 56)},
    {"name": "Slap Bass 2", "pitch_range": range(28, 56)},
    {"name": "Synth Bass 1", "pitch_range": range(28, 56)},
    {"name": "Synth Bass 2", "pitch_range": range(28, 56)},
    # Strings & Orchestral instruments
    {"name": "Violin", "pitch_range": range(55, 94)},
    {"name": "Viola", "pitch_range": range(48, 85)},
    {"name": "Cello", "pitch_range": range(36, 73)},
    {"name": "Contrabass", "pitch_range": range(28, 56)},
    {"name": "Tremolo Strings", "pitch_range": range(28, 94)},
    {"name": "Pizzicato Strings", "pitch_range": range(28, 94)},
    {"name": "Orchestral Harp", "pitch_range": range(23, 104)},
    {"name": "Timpani", "pitch_range": range(36, 58)},
    # Ensembles
    {"name": "String Ensembles 1", "pitch_range": range(28, 97)},
    {"name": "String Ensembles 2", "pitch_range": range(28, 97)},
    {"name": "SynthStrings 1", "pitch_range": range(36, 97)},
    {"name": "SynthStrings 2", "pitch_range": range(36, 97)},
    {"name": "Choir Aahs", "pitch_range": range(48, 80)},
    {"name": "Voice Oohs", "pitch_range": range(48, 80)},
    {"name": "Synth Voice", "pitch_range": range(48, 85)},
    {"name": "Orchestra Hit", "pitch_range": range(48, 73)},
    # Brass
    {"name": "Trumpet", "pitch_range": range(58, 95)},
    {"name": "Trombone", "pitch_range": range(34, 76)},
    {"name": "Tuba", "pitch_range": range(29, 56)},
    {"name": "Muted Trumpet", "pitch_range": range(58, 83)},
    {"name": "French Horn", "pitch_range": range(41, 78)},
    {"name": "Brass Section", "pitch_range": range(36, 97)},
    {"name": "Synth Brass 1", "pitch_range": range(36, 97)},
    {"name": "Synth Brass 2", "pitch_range": range(36, 97)},
    # Reed
    {"name": "Soprano Sax", "pitch_range": range(54, 88)},
    {"name": "Alto Sax", "pitch_range": range(49, 81)},
    {"name": "Tenor Sax", "pitch_range": range(42, 76)},
    {"name": "Baritone Sax", "pitch_range": range(37, 69)},
    {"name": "Oboe", "pitch_range": range(58, 92)},
    {"name": "English Horn", "pitch_range": range(52, 82)},
    {"name": "Bassoon", "pitch_range": range(34, 73)},
    {"name": "Clarinet", "pitch_range": range(50, 92)},
    # Pipe
    {"name": "Piccolo", "pitch_range": range(74, 109)},
    {"name": "Flute", "pitch_range": range(60, 97)},
    {"name": "Recorder", "pitch_range": range(60, 97)},
    {"name": "Pan Flute", "pitch_range": range(60, 97)},
    {"name": "Blown Bottle", "pitch_range": range(60, 97)},
    {"name": "Shakuhachi", "pitch_range": range(55, 85)},
    {"name": "Whistle", "pitch_range": range(60, 97)},
    {"name": "Ocarina", "pitch_range": range(60, 85)},
    # Synth Lead
    {"name": "Lead 1 (square)", "pitch_range": range(21, 109)},
    {"name": "Lead 2 (sawtooth)", "pitch_range": range(21, 109)},
    {"name": "Lead 3 (calliope)", "pitch_range": range(36, 97)},
    {"name": "Lead 4 (chiff)", "pitch_range": range(36, 97)},
    {"name": "Lead 5 (charang)", "pitch_range": range(36, 97)},
    {"name": "Lead 6 (voice)", "pitch_range": range(36, 97)},
    {"name": "Lead 7 (fifths)", "pitch_range": range(36, 97)},
    {"name": "Lead 8 (bass + lead)", "pitch_range": range(21, 109)},
    # Synth Pad
    {"name": "Pad 1 (new age)", "pitch_range": range(36, 97)},
    {"name": "Pad 2 (warm)", "pitch_range": range(36, 97)},
    {"name": "Pad 3 (polysynth)", "pitch_range": range(36, 97)},
    {"name": "Pad 4 (choir)", "pitch_range": range(36, 97)},
    {"name": "Pad 5 (bowed)", "pitch_range": range(36, 97)},
    {"name": "Pad 6 (metallic)", "pitch_range": range(36, 97)},
    {"name": "Pad 7 (halo)", "pitch_range": range(36, 97)},
    {"name": "Pad 8 (sweep)", "pitch_range": range(36, 97)},
    # Synth SFX
    {"name": "FX 1 (rain)", "pitch_range": range(36, 97)},
    {"name": "FX 2 (soundtrack)", "pitch_range": range(36, 97)},
    {"name": "FX 3 (crystal)", "pitch_range": range(36, 97)},
    {"name": "FX 4 (atmosphere)", "pitch_range": range(36, 97)},
    {"name": "FX 5 (brightness)", "pitch_range": range(36, 97)},
    {"name": "FX 6 (goblins)", "pitch_range": range(36, 97)},
    {"name": "FX 7 (echoes)", "pitch_range": range(36, 97)},
    {"name": "FX 8 (sci-fi)", "pitch_range": range(36, 97)},
    # Ethnic Misc.
    {"name": "Sitar", "pitch_range": range(48, 78)},
    {"name": "Banjo", "pitch_range": range(48, 85)},
    {"name": "Shamisen", "pitch_range": range(50, 80)},
    {"name": "Koto", "pitch_range": range(55, 85)},
    {"name": "Kalimba", "pitch_range": range(48, 80)},
    {"name": "Bag pipe", "pitch_range": range(36, 78)},
    {"name": "Fiddle", "pitch_range": range(55, 97)},
    {"name": "Shanai", "pitch_range": range(48, 73)},
    # Percussive
    {"name": "Tinkle Bell", "pitch_range": range(72, 85)},
    {"name": "Agogo", "pitch_range": range(60, 73)},
    {"name": "Steel Drums", "pitch_range": range(52, 77)},
    {"name": "Woodblock", "pitch_range": range(128)},
    {"name": "Taiko Drum", "pitch_range": range(128)},
    {"name": "Melodic Tom", "pitch_range": range(128)},
    {"name": "Synth Drum", "pitch_range": range(128)},
    {"name": "Reverse Cymbal", "pitch_range": range(128)},
    # SFX
    {"name": "Guitar Fret Noise, Guitar Cutting Noise", "pitch_range": range(128)},
    {"name": "Breath Noise, Flute Key Click", "pitch_range": range(128)},
    {
        "name": "Seashore, Rain, Thunder, Wind, Stream, Bubbles",
        "pitch_range": range(128),
    },
    {"name": "Bird Tweet, Dog, Horse Gallop", "pitch_range": range(128)},
    {
        "name": "Telephone Ring, Door Creaking, Door, Scratch, Wind Chime",
        "pitch_range": range(128),
    },
    {"name": "Helicopter, Car Sounds", "pitch_range": range(128)},
    {
        "name": "Applause, Laughing, Screaming, Punch, Heart Beat, Footstep",
        "pitch_range": range(128),
    },
    {"name": "Gunshot, Machine Gun, Lasergun, Explosion", "pitch_range": range(128)},
]

INSTRUMENTS_CLASSES = [
    {"name": "Piano", "program_range": range(8)},  # 0
    {"name": "Chromatic Percussion", "program_range": range(8, 16)},
    {"name": "Organ", "program_range": range(16, 24)},
    {"name": "Guitar", "program_range": range(24, 32)},
    {"name": "Bass", "program_range": range(32, 40)},
    {"name": "Strings", "program_range": range(40, 48)},  # 5
    {"name": "Ensemble", "program_range": range(48, 56)},
    {"name": "Brass", "program_range": range(56, 64)},
    {"name": "Reed", "program_range": range(64, 72)},
    {"name": "Pipe", "program_range": range(72, 80)},
    {"name": "Synth Lead", "program_range": range(80, 88)},  # 10
    {"name": "Synth Pad", "program_range": range(88, 96)},
    {"name": "Synth Effects", "program_range": range(96, 104)},
    {"name": "Ethnic", "program_range": range(104, 112)},
    {"name": "Percussive", "program_range": range(112, 120)},
    {"name": "Sound Effects", "program_range": range(120, 128)},  # 15
    {"name": "Drums", "program_range": range(-1, 0)},
]

# To easily get the class index of any instrument program
CLASS_OF_INST = [
    i
    for i, inst_class in enumerate(INSTRUMENTS_CLASSES)
    for _ in inst_class["program_range"]
]

# index i = program i+1 in the GM2 specs (8. Appendix B)
# index i = program i retrieved by packages
DRUMS_SETS = {
    0: "Standard",
    8: "Room",
    16: "Power",
    24: "Electronic",
    25: "Analog",
    32: "Jazz",
    40: "Brush",
    48: "Orchestra",
    56: "SFX",
}

# Control changes list (without specifications):
# https://www.midi.org/specifications-old/item/table-3-control-change-messages-data-bytes-2
# Undefined and general control changes are not considered here
# All these attributes can take values from 0 to 127, with some of them being on/off
CONTROL_CHANGES = {
    # MSB
    0: "Bank Select",
    1: "Modulation Depth",
    2: "Breath Controller",
    4: "Foot Controller",
    5: "Portamento Time",
    6: "Data Entry",
    7: "Channel Volume",
    8: "Balance",
    10: "Pan",
    11: "Expression Controller",
    # LSB
    32: "Bank Select",
    33: "Modulation Depth",
    34: "Breath Controller",
    36: "Foot Controller",
    37: "Portamento Time",
    38: "Data Entry",
    39: "Channel Volume",
    40: "Balance",
    42: "Pan",
    43: "Expression Controller",
    # On / Off control changes, ≤63 off, ≥64 on
    64: "Damper Pedal",
    65: "Portamento",
    66: "Sostenuto",
    67: "Soft Pedal",
    68: "Legato Footswitch",
    69: "Hold 2",
    # Continuous controls
    70: "Sound Variation",
    71: "Timbre/Harmonic Intensity",
    72: "Release Time",
    73: "Attack Time",
    74: "Brightness",
    75: "Decay Time",
    76: "Vibrato Rate",
    77: "Vibrato Depth",
    78: "Vibrato Delay",
    84: "Portamento Control",
    88: "High Resolution Velocity Prefix",
    # Effects depths
    91: "Reverb Depth",
    92: "Tremolo Depth",
    93: "Chorus Depth",
    94: "Celeste Depth",
    95: "Phaser Depth",
    # Registered parameters numbers
    96: "Data Increment",
    97: "Data Decrement",
    #  98: 'Non-Registered Parameter Number (NRPN) - LSB',
    #  99: 'Non-Registered Parameter Number (NRPN) - MSB',
    100: "Registered Parameter Number (RPN) - LSB",
    101: "Registered Parameter Number (RPN) - MSB",
    # Channel mode controls
    120: "All Sound Off",
    121: "Reset All Controllers",
    122: "Local Control On/Off",
    123: "All Notes Off",
    124: "Omni Mode Off",  # + all notes off
    125: "Omni Mode On",  # + all notes off
    126: "Mono Mode On",  # + poly off, + all notes off
    127: "Poly Mode On",  # + mono off, +all notes off
}

###################################################################################

def patches_onset_times(escore_notes, times_idx=1, patches_idx=6):
    
    patches = [e[patches_idx] for e in escore_notes]

    patches_oset = ordered_set(patches)

    patches_onset_times = []

    for p in patches_oset:
        for e in escore_notes:
            if e[patches_idx] == p:
                patches_onset_times.append([p, e[times_idx]])
                break

    return patches_onset_times

###################################################################################

def count_escore_notes_patches(escore_notes, patches_idx=6):

    patches = [e[patches_idx] for e in escore_notes]

    return Counter(patches).most_common()

###################################################################################

def escore_notes_monoponic_melodies(escore_notes,
                                    bad_notes_ratio=0.0,
                                    times_idx=1,
                                    patches_idx=6
                                    ):

    patches = escore_notes_patches(escore_notes, patches_index=patches_idx)

    monophonic_melodies = []

    for p in patches:
        patch_score = [e for e in escore_notes if e[patches_idx] == p]

        ps_times = [e[times_idx] for e in patch_score]

        if len(ps_times) <= len(set(ps_times)) * (1+bad_notes_ratio):
            monophonic_melodies.append([p, len(patch_score)])
            
    return monophonic_melodies

###################################################################################


def group_by_threshold(data, threshold, groupby_idx):

    data.sort(key=itemgetter(groupby_idx))

    grouped_data = []
    cluster = []

    for i, item in enumerate(data):
        if not cluster:
            cluster.append(item)
        elif abs(item[groupby_idx] - cluster[-1][groupby_idx]) <= threshold:
            cluster.append(item)
        else:
            grouped_data.append(cluster)
            cluster = [item]
    
    if cluster:
        grouped_data.append(cluster)
        
    return grouped_data

###################################################################################

def split_escore_notes_by_time(escore_notes, time_threshold=256):

    dscore = delta_score_notes(escore_notes, timings_clip_value=time_threshold-1)

    score_chunks = []

    ctime = 0
    pchunk_idx = 0

    for i, e in enumerate(dscore):
        
        ctime += e[1]

        if ctime >= time_threshold:
            score_chunks.append(escore_notes[pchunk_idx:i])
            pchunk_idx = i
            ctime = 0

    return score_chunks

###################################################################################

def escore_notes_grouped_patches(escore_notes, time_threshold=256):
    
    split_score_chunks = split_escore_notes_by_time(escore_notes,
                                                    time_threshold=time_threshold
                                                    )

    chunks_patches = []

    for s in split_score_chunks:
        chunks_patches.append(escore_notes_patches(s))

    return chunks_patches

###################################################################################

def computeLPSArray(pattern, M, lps):
    length = 0
    i = 1
    
    lps[0] = 0
    
    while i < M:
        if pattern[i] == pattern[length]:
            length += 1
            lps[i] = length
            i += 1
        else:
            if length != 0:
                length = lps[length-1]
            else:
                lps[i] = 0
                i += 1
                
###################################################################################

def find_pattern_idxs(sub_pattern, pattern):

    lst = pattern
    pattern = sub_pattern
    
    M = len(pattern)
    N = len(lst)
    
    lps = [0] * M
    j = 0  # index for pattern[]

    computeLPSArray(pattern, M, lps)
    
    i = 0  # index for lst[]
    indexes = []
    
    while i < N:
        if pattern[j] == lst[i]:
            i += 1
            j += 1
        
        if j == M:
            end_index = i - 1
            start_index = end_index - M + 1
            indexes.append((start_index, end_index))
            j = lps[j-1]
        elif i < N and pattern[j] != lst[i]:
            if j != 0:
                j = lps[j-1]
            else:
                i += 1
                
    return indexes

###################################################################################

def escore_notes_patch_lrno_patterns(escore_notes, 
                                     patch=0, 
                                     zero_score_timings=False,
                                     pitches_idx=4,
                                     patches_idx=6
                                    ):

    patch_escore = [e for e in escore_notes if e[patches_idx] == patch]

    if patch_escore:
        
        patch_cscore = chordify_score([1000, patch_escore])
    
        patch_tscore = []
    
        for c in patch_cscore:
    
            tones_chord = sorted(set([p[pitches_idx] % 12 for p in c]))
    
            if tones_chord not in ALL_CHORDS_SORTED:
                tnoes_chord = check_and_fix_tones_chord(tones_chord)
    
            patch_tscore.append(ALL_CHORDS_SORTED.index(tones_chord))
    
        pattern = find_lrno_pattern_fast(patch_tscore)
    
        patterns_idxs = find_pattern_idxs(pattern, patch_tscore)
    
        patch_lrno_scores = []
    
        for idxs in patterns_idxs:
            
            score = patch_escore[idxs[0]:idxs[1]]
            
            if zero_score_timings:
                score = recalculate_score_timings(score)
                
            patch_lrno_scores.append(score)
    
        return patch_lrno_scores
        
    else:
        return []

###################################################################################

ALL_BASE_CHORDS_SORTED = [[0], [0, 2], [0, 2, 4], [0, 2, 4, 6], [0, 2, 4, 6, 8], [0, 2, 4, 6, 8, 10],
                         [0, 2, 4, 6, 9], [0, 2, 4, 6, 10], [0, 2, 4, 7], [0, 2, 4, 7, 9],
                         [0, 2, 4, 7, 10], [0, 2, 4, 8], [0, 2, 4, 8, 10], [0, 2, 4, 9], [0, 2, 4, 10],
                         [0, 2, 5], [0, 2, 5, 7], [0, 2, 5, 7, 9], [0, 2, 5, 7, 10], [0, 2, 5, 8],
                         [0, 2, 5, 8, 10], [0, 2, 5, 9], [0, 2, 5, 10], [0, 2, 6], [0, 2, 6, 8],
                         [0, 2, 6, 8, 10], [0, 2, 6, 9], [0, 2, 6, 10], [0, 2, 7], [0, 2, 7, 9],
                         [0, 2, 7, 10], [0, 2, 8], [0, 2, 8, 10], [0, 2, 9], [0, 2, 10], [0, 3],
                         [0, 3, 5], [0, 3, 5, 7], [0, 3, 5, 7, 9], [0, 3, 5, 7, 10], [0, 3, 5, 8],
                         [0, 3, 5, 8, 10], [0, 3, 5, 9], [0, 3, 5, 10], [0, 3, 6], [0, 3, 6, 8],
                         [0, 3, 6, 8, 10], [0, 3, 6, 9], [0, 3, 6, 10], [0, 3, 7], [0, 3, 7, 9],
                         [0, 3, 7, 10], [0, 3, 8], [0, 3, 8, 10], [0, 3, 9], [0, 3, 10], [0, 4],
                         [0, 4, 6], [0, 4, 6, 8], [0, 4, 6, 8, 10], [0, 4, 6, 9], [0, 4, 6, 10],
                         [0, 4, 7], [0, 4, 7, 9], [0, 4, 7, 10], [0, 4, 8], [0, 4, 8, 10], [0, 4, 9],
                         [0, 4, 10], [0, 5], [0, 5, 7], [0, 5, 7, 9], [0, 5, 7, 10], [0, 5, 8],
                         [0, 5, 8, 10], [0, 5, 9], [0, 5, 10], [0, 6], [0, 6, 8], [0, 6, 8, 10],
                         [0, 6, 9], [0, 6, 10], [0, 7], [0, 7, 9], [0, 7, 10], [0, 8], [0, 8, 10],
                         [0, 9], [0, 10]]

###################################################################################

MAJOR_SCALE_CHORDS_COUNTS = [[317, 6610], [320, 6468], [267, 6460], [89, 6329], [301, 6228], [178, 6201],
                             [0, 5822], [314, 5805], [309, 5677], [319, 5545], [288, 5494], [233, 5395],
                             [112, 2232], [194, 1956], [127, 1935], [216, 1884], [256, 1871], [283, 1815],
                             [201, 1768], [16, 1756], [105, 1743], [38, 1727], [23, 1718], [249, 1386],
                             [272, 796], [91, 770], [191, 740], [303, 735], [181, 718], [306, 717],
                             [235, 703], [183, 690], [94, 686], [13, 686], [269, 677], [280, 675],
                             [102, 665], [92, 662], [293, 659], [212, 658], [114, 656], [37, 653],
                             [180, 651], [215, 644], [316, 640], [290, 636], [5, 636], [110, 625],
                             [270, 625], [3, 624], [238, 615], [123, 609], [34, 591], [254, 584],
                             [258, 571], [126, 567], [2, 559], [246, 556], [104, 556], [203, 550],
                             [291, 537], [311, 522], [304, 520], [193, 509], [236, 496], [199, 493],
                             [15, 468], [25, 452], [312, 444], [282, 443], [248, 433], [21, 408],
                             [268, 281], [179, 273], [144, 259], [90, 252], [162, 250], [234, 250],
                             [1, 246], [221, 214], [73, 213], [43, 213], [45, 213], [134, 212], [318, 210],
                             [119, 210], [159, 209], [120, 209], [302, 207], [310, 201], [289, 195],
                             [42, 193], [264, 193], [220, 185], [131, 183], [55, 180], [315, 180],
                             [132, 176], [30, 174], [31, 172], [209, 171], [227, 169], [217, 163],
                             [223, 159], [70, 158], [39, 157], [36, 153], [214, 142], [196, 141],
                             [285, 141], [8, 137], [208, 133], [125, 133], [147, 130], [186, 130],
                             [97, 130], [49, 130], [58, 130], [128, 130], [138, 128], [241, 125],
                             [228, 124], [263, 120], [251, 120], [275, 119], [296, 118], [259, 116],
                             [99, 114], [10, 113], [50, 111], [273, 111], [139, 111], [298, 106], [18, 105],
                             [153, 105], [7, 101], [277, 101], [243, 99], [96, 99], [9, 96], [160, 96],
                             [188, 95], [115, 94], [24, 93], [107, 92], [204, 90], [150, 90], [148, 84],
                             [202, 83], [213, 82], [187, 82], [35, 80], [113, 79], [98, 78], [239, 77],
                             [59, 77], [26, 76], [281, 76], [184, 75], [64, 75], [124, 75], [71, 75],
                             [257, 75], [95, 74], [294, 73], [192, 70], [247, 70], [61, 67], [307, 66],
                             [242, 65], [218, 65], [146, 64], [276, 63], [6, 63], [68, 60], [284, 59],
                             [103, 59], [297, 56], [14, 56], [185, 55], [57, 55], [40, 55], [129, 54],
                             [274, 52], [308, 52], [46, 51], [224, 49], [240, 47], [135, 46], [17, 45],
                             [295, 45], [106, 45], [48, 44], [157, 44], [206, 43], [195, 42], [158, 42],
                             [69, 41], [117, 41], [225, 40], [222, 37], [226, 35], [261, 34], [164, 32],
                             [75, 32], [28, 32], [11, 32], [250, 31], [44, 30], [137, 28], [47, 26],
                             [133, 26], [255, 25], [182, 24], [136, 24], [197, 23], [93, 23], [237, 22],
                             [287, 22], [165, 22], [79, 21], [271, 21], [109, 21], [253, 20], [76, 20],
                             [168, 19], [155, 19], [149, 19], [108, 19], [4, 18], [51, 18], [292, 18],
                             [198, 18], [41, 17], [286, 17], [19, 17], [219, 17], [173, 17], [66, 16],
                             [54, 16], [229, 16], [140, 16], [175, 15], [171, 15], [82, 15], [130, 15],
                             [20, 15], [230, 15], [244, 14], [145, 14], [84, 14], [305, 14], [278, 14],
                             [86, 13], [60, 13], [232, 12], [100, 12], [141, 12], [52, 12], [189, 12],
                             [252, 12], [56, 11], [53, 11], [143, 10], [151, 10], [154, 10], [163, 9],
                             [116, 9], [27, 9], [65, 9], [313, 9], [205, 9], [170, 8], [62, 8], [299, 7],
                             [142, 7], [231, 7], [156, 6], [22, 6], [63, 6], [152, 6], [77, 5], [67, 5],
                             [166, 5], [174, 5], [85, 4], [72, 4], [190, 4], [111, 4], [101, 4], [200, 4],
                             [12, 4], [245, 3], [300, 3], [279, 3], [81, 2], [210, 2], [32, 2], [265, 2],
                             [260, 2], [74, 2], [161, 1], [207, 1], [29, 1], [118, 1], [262, 1], [121, 1]]

###################################################################################

MINOR_SCALE_CHORDS_COUNTS = [[267, 10606], [89, 10562], [301, 10522], [320, 10192], [178, 10191],
                             [317, 10153], [233, 10101], [314, 10065], [288, 9914], [0, 9884], [309, 9694],
                             [319, 9648], [114, 1963], [193, 1778], [25, 1705], [104, 1689], [248, 1671],
                             [282, 1614], [283, 1610], [127, 1530], [203, 1525], [37, 1508], [215, 1473],
                             [105, 1465], [38, 1462], [258, 1445], [112, 1419], [94, 1413], [280, 1391],
                             [194, 1388], [126, 1384], [16, 1374], [272, 1370], [23, 1364], [238, 1351],
                             [306, 1342], [303, 1340], [5, 1338], [183, 1334], [102, 1333], [290, 1322],
                             [269, 1312], [191, 1311], [249, 1305], [15, 1291], [246, 1290], [316, 1288],
                             [13, 1279], [216, 1278], [235, 1275], [256, 1268], [311, 1241], [293, 1228],
                             [91, 1219], [180, 1173], [34, 1167], [2, 1138], [212, 1131], [123, 1118],
                             [201, 1103], [270, 1017], [304, 961], [181, 958], [92, 943], [3, 940],
                             [236, 932], [254, 923], [291, 921], [110, 920], [21, 911], [312, 891],
                             [199, 832], [268, 431], [179, 395], [234, 395], [302, 385], [144, 368],
                             [90, 365], [289, 362], [310, 352], [318, 350], [1, 332], [55, 323], [315, 322],
                             [8, 307], [162, 304], [97, 302], [186, 302], [241, 300], [10, 299], [217, 289],
                             [275, 275], [128, 267], [73, 266], [243, 265], [125, 262], [296, 259],
                             [298, 251], [36, 250], [39, 250], [99, 249], [214, 231], [119, 230],
                             [120, 227], [188, 227], [159, 226], [264, 225], [263, 225], [138, 223],
                             [31, 222], [227, 219], [134, 216], [277, 214], [70, 210], [209, 207],
                             [30, 203], [49, 186], [46, 185], [45, 184], [221, 172], [281, 170], [96, 169],
                             [131, 169], [224, 165], [148, 159], [59, 157], [43, 157], [7, 157], [247, 155],
                             [208, 153], [132, 152], [274, 150], [223, 149], [135, 148], [273, 148],
                             [240, 137], [220, 132], [185, 131], [239, 131], [42, 130], [147, 119],
                             [213, 117], [307, 115], [24, 112], [95, 108], [192, 107], [150, 106],
                             [294, 105], [106, 104], [58, 102], [103, 102], [17, 100], [129, 100], [61, 99],
                             [9, 98], [139, 96], [295, 96], [284, 96], [146, 96], [218, 95], [184, 94],
                             [308, 87], [195, 87], [40, 86], [14, 85], [50, 82], [250, 82], [285, 81],
                             [57, 79], [259, 79], [6, 79], [276, 78], [228, 78], [35, 76], [187, 75],
                             [242, 73], [206, 73], [160, 72], [113, 72], [117, 72], [261, 72], [98, 71],
                             [202, 70], [115, 70], [158, 69], [71, 68], [48, 67], [28, 67], [204, 66],
                             [157, 64], [124, 63], [257, 59], [196, 59], [69, 59], [68, 57], [251, 55],
                             [225, 50], [137, 50], [107, 49], [165, 49], [297, 48], [64, 46], [153, 45],
                             [226, 44], [198, 44], [287, 43], [26, 43], [219, 41], [253, 40], [109, 40],
                             [66, 39], [47, 39], [41, 39], [76, 38], [11, 38], [136, 38], [130, 36],
                             [155, 35], [18, 31], [93, 31], [20, 30], [271, 29], [4, 28], [292, 28],
                             [237, 27], [182, 26], [62, 26], [164, 25], [151, 25], [108, 25], [286, 24],
                             [145, 24], [305, 24], [75, 24], [56, 23], [149, 23], [252, 23], [197, 23],
                             [255, 23], [313, 21], [60, 18], [244, 17], [278, 17], [189, 17], [100, 16],
                             [299, 15], [200, 13], [175, 13], [111, 13], [22, 13], [170, 12], [232, 11],
                             [86, 11], [141, 11], [52, 11], [65, 10], [173, 10], [133, 10], [222, 10],
                             [143, 10], [154, 9], [82, 8], [19, 8], [85, 8], [44, 8], [84, 8], [163, 7],
                             [205, 7], [230, 7], [54, 7], [174, 7], [116, 7], [27, 7], [171, 7], [229, 6],
                             [81, 5], [79, 4], [142, 4], [231, 4], [210, 3], [168, 3], [53, 3], [51, 3],
                             [74, 3], [265, 3], [260, 3], [152, 2], [245, 2], [279, 2], [190, 2], [12, 2],
                             [101, 2], [262, 1], [63, 1], [72, 1], [207, 1], [166, 1], [83, 1], [176, 1],
                             [118, 1], [67, 1], [172, 1], [29, 1], [121, 1], [77, 1], [266, 1], [156, 1],
                             [211, 1], [300, 1], [87, 1], [140, 1], [161, 1]]

###################################################################################

def get_weighted_score(src_order, trg_order):
    
    score = 0
    
    for i, (item, count) in enumerate(src_order):
        if item in trg_order:
            score += count * abs(i - trg_order.index(item))
            
        else:
            score += count * len(trg_order)
            
    return score

###################################################################################

def escore_notes_scale(escore_notes,
                       score_mult_factor=3,
                       start_note=0,
                       num_notes=-1,
                       return_scale_indexes=False
                      ):

    trg_chords = []

    for i in range(-score_mult_factor, score_mult_factor):

        trans_escore_notes = transpose_escore_notes(escore_notes[start_note:start_note+num_notes], i)
    
        cscore = chordify_score([1000, trans_escore_notes])
    
        tones_chords = []
    
        for c in cscore:
    
            seen = []
            pitches = []
            
            for e in c:
                
                if e[4] not in seen:
                    pitches.append(e[4])
                    seen.append(e[4])
                    
            if pitches:
                
                tones_chord = sorted(set([p % 12 for p in pitches]))
    
                if tones_chord not in ALL_CHORDS_SORTED:
                    tones_chord = check_and_fix_tones_chord(tones_chord)
                
                tones_chords.append(ALL_CHORDS_SORTED.index(tones_chord))
                
        if tones_chords:
            trg_chords.extend(tones_chords)
    
    #========================================================================
            
    scales_results = []
    
    #========================================================================
    
    if trg_chords:
    
        #========================================================================

        src_order = Counter(trg_chords).most_common()       
       
        trg1_items = [item for item, count in MAJOR_SCALE_CHORDS_COUNTS]
        trg2_items = [item for item, count in MINOR_SCALE_CHORDS_COUNTS]
        

        trg1_score = get_weighted_score(src_order, trg1_items)
        trg2_score = get_weighted_score(src_order, trg2_items)

        #========================================================================
        
        if trg1_score <= trg2_score:
            
            if return_scale_indexes:
                scales_results.append(1)

            else:
                scales_results.append('Major')
            
        else:
            if return_scale_indexes:
                scales_results.append(0)
                
            else:
                scales_results.append('Minor')
            
        #========================================================================
                
        best_match = None
        best_score = float('inf')
        
        for trg_order in ALL_MOOD_TYPES:

            trg_items = [item for item, count in trg_order]

            trg_score = get_weighted_score(src_order, trg_items)

            if trg_score < best_score:
                best_score = trg_score

                if return_scale_indexes:
                    best_match = ALL_MOOD_TYPES.index(trg_order)

                else:
                    best_match = ALL_MOOD_TYPES_LABELS[ALL_MOOD_TYPES.index(trg_order)]
                    
        scales_results.append(best_match)
            
    else:
        if return_scale_indexes:
            scales_results.extend([-1, -1])
            
        else:
            scales_results.extend(['Unknown', 'Unknown'])
            
    return scales_results
        
###################################################################################

HAPPY_MAJOR = [(317, 1916), (89, 1876), (320, 1840), (267, 1817), (301, 1795), (178, 1750),
             (314, 1725), (0, 1691), (319, 1658), (288, 1624), (309, 1599), (233, 1559),
             (112, 1050), (127, 972), (201, 884), (194, 879), (216, 860), (38, 831),
             (256, 828), (23, 822), (105, 820), (283, 756), (16, 734), (249, 622),
             (91, 254), (303, 242), (34, 237), (316, 235), (110, 235), (123, 234),
             (212, 230), (92, 225), (181, 225), (114, 219), (272, 218), (290, 213),
             (235, 208), (180, 207), (269, 206), (2, 201), (3, 199), (203, 198), (37, 195),
             (254, 191), (199, 189), (311, 189), (293, 187), (5, 186), (270, 185),
             (183, 184), (291, 183), (94, 183), (25, 182), (304, 181), (258, 176),
             (215, 173), (191, 172), (193, 168), (104, 167), (282, 164), (238, 162),
             (248, 157), (15, 156), (13, 156), (126, 153), (21, 150), (102, 150),
             (306, 150), (312, 144), (280, 141), (236, 139), (162, 116), (120, 114),
             (246, 113), (134, 109), (43, 108), (221, 105), (264, 103), (73, 100),
             (159, 98), (42, 95), (45, 94), (220, 93), (131, 91), (119, 91), (227, 90),
             (209, 88), (70, 86), (144, 86), (31, 85), (223, 84), (58, 82), (1, 80),
             (132, 79), (30, 76), (90, 75), (268, 75), (259, 74), (234, 72), (179, 72),
             (147, 70), (318, 69), (208, 67), (315, 66), (55, 66), (49, 64), (310, 63),
             (138, 62), (214, 61), (263, 60), (204, 59), (302, 58), (196, 58), (115, 56),
             (107, 53), (18, 53), (153, 52), (289, 52), (9, 50), (10, 50), (217, 49),
             (243, 48), (39, 48), (99, 48), (7, 47), (188, 46), (26, 46), (68, 46),
             (36, 45), (125, 43), (202, 43), (285, 42), (24, 42), (277, 41), (98, 40),
             (251, 39), (113, 39), (8, 38), (128, 38), (187, 37), (35, 36), (213, 36),
             (97, 35), (186, 35), (61, 34), (150, 34), (160, 33), (124, 32), (96, 32),
             (257, 32), (275, 31), (241, 31), (296, 30), (64, 30), (297, 29), (298, 29),
             (117, 29), (46, 28), (273, 28), (206, 28), (157, 27), (242, 26), (224, 26),
             (185, 26), (222, 26), (59, 25), (135, 24), (158, 23), (28, 23), (294, 22),
             (69, 22), (276, 21), (274, 21), (225, 21), (148, 20), (50, 20), (48, 20),
             (281, 19), (139, 19), (307, 19), (228, 19), (75, 18), (164, 18), (44, 18),
             (133, 18), (79, 17), (184, 17), (57, 17), (240, 17), (239, 17), (295, 17),
             (247, 16), (95, 16), (261, 15), (308, 15), (287, 14), (76, 14), (165, 14),
             (175, 14), (82, 14), (284, 14), (71, 14), (253, 12), (155, 12), (86, 12),
             (4, 12), (93, 12), (171, 12), (137, 12), (66, 11), (232, 11), (168, 11),
             (103, 11), (192, 11), (54, 10), (145, 10), (40, 10), (51, 10), (182, 10),
             (226, 10), (14, 10), (129, 9), (218, 9), (146, 9), (237, 9), (19, 9), (108, 9),
             (197, 9), (140, 8), (229, 8), (6, 7), (17, 7), (56, 6), (106, 6), (271, 6),
             (109, 6), (163, 5), (143, 5), (65, 5), (154, 5), (27, 5), (116, 5), (205, 5),
             (195, 5), (250, 5), (198, 5), (41, 5), (136, 5), (47, 4), (52, 4), (141, 4),
             (230, 4), (84, 4), (173, 4), (255, 4), (11, 4), (100, 4), (189, 4), (244, 4),
             (278, 4), (219, 3), (20, 3), (286, 3), (130, 3), (170, 3), (151, 3), (53, 2),
             (77, 2), (166, 2), (67, 2), (156, 2), (63, 2), (60, 2), (292, 2), (62, 2),
             (142, 1), (231, 1), (85, 1), (174, 1), (81, 1), (152, 1), (262, 1), (72, 1),
             (161, 1), (29, 1), (118, 1), (207, 1), (149, 1), (300, 1), (299, 1), (252, 1)]

###################################################################################

MELANCHOLIC_MAJOR = [(317, 451), (301, 430), (89, 426), (320, 419), (267, 416), (178, 415),
                     (314, 401), (319, 400), (0, 394), (309, 390), (288, 389), (233, 365),
                     (37, 224), (215, 207), (258, 203), (126, 191), (114, 185), (203, 183),
                     (283, 141), (127, 131), (38, 127), (216, 115), (194, 113), (112, 112),
                     (23, 109), (105, 105), (249, 103), (16, 99), (306, 96), (256, 92), (13, 87),
                     (280, 86), (181, 86), (102, 85), (92, 84), (104, 84), (15, 84), (191, 83),
                     (246, 83), (270, 81), (94, 74), (3, 73), (238, 72), (272, 72), (236, 72),
                     (201, 72), (183, 70), (293, 66), (193, 63), (254, 63), (212, 61), (282, 60),
                     (123, 58), (5, 57), (25, 55), (291, 53), (34, 52), (316, 50), (304, 48),
                     (91, 47), (2, 47), (110, 46), (248, 45), (303, 38), (311, 38), (45, 36),
                     (180, 35), (199, 34), (235, 33), (162, 33), (221, 33), (21, 32), (144, 32),
                     (132, 31), (179, 29), (90, 29), (43, 29), (217, 29), (312, 28), (39, 28),
                     (128, 28), (302, 27), (268, 27), (36, 27), (125, 27), (269, 26), (134, 26),
                     (234, 26), (73, 25), (318, 25), (55, 25), (1, 24), (290, 23), (8, 22),
                     (310, 22), (315, 22), (97, 20), (186, 20), (241, 20), (275, 20), (296, 20),
                     (289, 20), (119, 18), (298, 18), (31, 17), (6, 17), (95, 17), (184, 17),
                     (273, 17), (223, 16), (276, 15), (120, 15), (239, 15), (30, 15), (208, 14),
                     (59, 14), (159, 13), (146, 13), (42, 13), (209, 13), (26, 13), (264, 13),
                     (147, 13), (187, 13), (242, 13), (115, 12), (220, 12), (70, 12), (226, 12),
                     (47, 12), (148, 12), (24, 11), (49, 11), (131, 10), (227, 10), (214, 10),
                     (136, 9), (225, 9), (69, 9), (138, 9), (158, 9), (106, 9), (98, 9), (257, 8),
                     (263, 8), (297, 8), (50, 8), (204, 8), (259, 8), (7, 8), (294, 8), (281, 8),
                     (9, 8), (113, 7), (202, 7), (17, 7), (124, 7), (213, 7), (57, 7), (96, 7),
                     (247, 7), (285, 6), (185, 6), (130, 6), (219, 6), (218, 6), (58, 6), (139, 5),
                     (35, 5), (240, 5), (195, 5), (250, 5), (20, 5), (284, 5), (150, 5), (261, 5),
                     (48, 5), (107, 4), (196, 4), (251, 4), (292, 4), (41, 4), (228, 4), (61, 4),
                     (71, 4), (160, 4), (109, 4), (103, 4), (192, 4), (206, 4), (137, 4), (274, 3),
                     (18, 3), (305, 3), (295, 3), (93, 3), (308, 3), (182, 3), (237, 3), (271, 3),
                     (198, 3), (168, 3), (51, 3), (140, 3), (229, 3), (54, 3), (155, 3), (10, 3),
                     (99, 3), (157, 2), (64, 2), (143, 2), (224, 2), (253, 2), (307, 2), (66, 2),
                     (40, 2), (129, 2), (188, 2), (11, 2), (243, 2), (28, 1), (117, 1), (4, 1),
                     (313, 1), (62, 1), (151, 1), (56, 1), (135, 1), (46, 1), (165, 1), (79, 1),
                     (299, 1), (60, 1), (149, 1), (22, 1), (111, 1), (200, 1)]

###################################################################################

MELANCHOLIC_MINOR = [(89, 3681), (267, 3628), (317, 3472), (301, 3408), (320, 3290), (178, 3261),
                     (314, 3261), (288, 3206), (0, 3140), (233, 3050), (319, 2894), (309, 2841),
                     (114, 570), (283, 559), (104, 544), (193, 529), (215, 509), (37, 507),
                     (127, 482), (126, 468), (38, 456), (282, 432), (248, 417), (25, 415),
                     (194, 414), (216, 412), (112, 411), (258, 407), (23, 403), (105, 399),
                     (249, 399), (303, 387), (203, 386), (15, 366), (256, 356), (16, 351),
                     (290, 343), (316, 343), (269, 332), (235, 323), (91, 312), (311, 296),
                     (272, 286), (34, 273), (94, 271), (180, 269), (212, 265), (123, 260),
                     (306, 259), (270, 254), (102, 246), (201, 246), (238, 246), (280, 242),
                     (110, 236), (183, 236), (191, 232), (293, 230), (5, 228), (2, 228), (291, 226),
                     (304, 225), (13, 219), (312, 207), (21, 207), (181, 203), (92, 195),
                     (246, 192), (3, 191), (254, 181), (236, 173), (199, 155), (268, 124),
                     (179, 114), (144, 103), (90, 103), (302, 102), (318, 101), (234, 99),
                     (289, 86), (1, 84), (310, 83), (31, 79), (120, 79), (55, 78), (315, 72),
                     (162, 72), (264, 71), (73, 70), (209, 69), (159, 61), (227, 61), (263, 60),
                     (49, 58), (138, 57), (119, 51), (273, 49), (70, 49), (10, 47), (8, 44),
                     (97, 44), (186, 44), (241, 44), (275, 44), (99, 44), (146, 43), (239, 42),
                     (296, 39), (214, 39), (217, 39), (95, 38), (148, 37), (36, 36), (281, 34),
                     (307, 33), (125, 33), (218, 32), (59, 31), (134, 31), (160, 31), (184, 31),
                     (129, 29), (208, 29), (223, 29), (71, 29), (30, 29), (96, 27), (147, 27),
                     (228, 27), (57, 27), (6, 27), (284, 26), (50, 26), (139, 26), (247, 24),
                     (24, 24), (250, 24), (115, 24), (204, 24), (259, 24), (9, 23), (240, 23),
                     (274, 23), (220, 23), (58, 23), (103, 22), (40, 22), (131, 22), (243, 22),
                     (106, 22), (285, 22), (46, 22), (295, 21), (308, 21), (221, 21), (14, 20),
                     (45, 20), (42, 20), (195, 20), (294, 19), (188, 19), (277, 19), (185, 18),
                     (192, 18), (17, 18), (135, 18), (224, 18), (7, 17), (61, 17), (150, 16),
                     (225, 14), (69, 14), (158, 14), (128, 14), (257, 14), (149, 13), (64, 13),
                     (298, 13), (39, 13), (213, 12), (113, 12), (43, 11), (132, 11), (28, 11),
                     (35, 10), (124, 10), (47, 10), (136, 10), (41, 10), (130, 10), (157, 10),
                     (202, 10), (165, 10), (66, 9), (155, 9), (219, 9), (153, 9), (18, 9), (255, 9),
                     (11, 9), (60, 8), (22, 8), (111, 8), (107, 8), (299, 7), (143, 7), (232, 7),
                     (86, 7), (175, 7), (276, 6), (313, 6), (56, 6), (62, 6), (278, 6), (151, 6),
                     (26, 6), (117, 6), (206, 6), (196, 6), (98, 5), (187, 5), (242, 5), (200, 5),
                     (109, 5), (198, 5), (229, 5), (54, 5), (305, 5), (261, 5), (48, 5), (76, 5),
                     (226, 5), (145, 4), (20, 4), (251, 4), (68, 4), (292, 4), (253, 4), (287, 4),
                     (244, 3), (4, 3), (189, 3), (93, 2), (182, 2), (237, 2), (297, 2), (100, 2),
                     (173, 2), (53, 2), (142, 2), (231, 2), (85, 2), (174, 2), (271, 2), (137, 2),
                     (82, 2), (171, 2), (164, 1), (44, 1), (133, 1), (222, 1), (163, 1), (65, 1),
                     (154, 1), (27, 1), (116, 1), (205, 1)]

###################################################################################

NEUTRAL_MAJOR = [(320, 574), (89, 542), (0, 535), (317, 488), (319, 458), (314, 439),
                 (178, 424), (267, 405), (233, 375), (301, 330), (309, 321), (288, 287),
                 (283, 77), (112, 76), (38, 71), (23, 67), (216, 61), (127, 59), (291, 54),
                 (316, 52), (269, 51), (290, 51), (34, 50), (303, 50), (110, 49), (280, 47),
                 (13, 45), (311, 44), (306, 43), (238, 43), (272, 43), (3, 42), (21, 42),
                 (16, 41), (270, 41), (183, 39), (102, 39), (92, 39), (312, 37), (105, 37),
                 (194, 37), (199, 35), (191, 35), (246, 35), (5, 35), (181, 34), (304, 34),
                 (94, 33), (293, 31), (91, 29), (268, 27), (236, 27), (256, 27), (144, 24),
                 (90, 24), (179, 23), (234, 23), (302, 23), (235, 23), (2, 23), (318, 22),
                 (1, 22), (254, 22), (123, 22), (315, 22), (212, 22), (249, 22), (8, 21),
                 (97, 21), (186, 21), (241, 21), (289, 21), (180, 21), (310, 21), (201, 21),
                 (104, 20), (214, 19), (55, 18), (296, 17), (275, 17), (36, 17), (125, 17),
                 (193, 16), (58, 16), (147, 16), (10, 15), (37, 14), (215, 14), (15, 14),
                 (25, 14), (114, 14), (217, 13), (282, 12), (259, 12), (9, 12), (98, 12),
                 (187, 12), (99, 11), (126, 10), (248, 10), (188, 10), (243, 10), (277, 10),
                 (264, 10), (96, 10), (73, 10), (162, 10), (43, 10), (128, 10), (203, 8),
                 (150, 8), (221, 8), (39, 8), (24, 8), (113, 8), (274, 6), (295, 6), (308, 6),
                 (159, 6), (258, 6), (120, 6), (42, 6), (131, 6), (220, 6), (30, 6), (132, 6),
                 (7, 6), (298, 6), (119, 6), (228, 4), (185, 4), (71, 4), (240, 4), (160, 4),
                 (153, 4), (18, 4), (61, 4), (35, 4), (285, 4), (209, 4), (95, 4), (307, 4),
                 (146, 4), (184, 4), (239, 4), (202, 4), (247, 4), (273, 4), (257, 4), (281, 4),
                 (64, 2), (156, 2), (50, 2), (63, 2), (45, 2), (139, 2), (152, 2), (134, 2),
                 (124, 2), (107, 2), (12, 2), (11, 2), (223, 2), (213, 2), (196, 2), (101, 2),
                 (31, 2), (251, 2), (190, 2), (106, 2), (40, 2), (195, 2), (6, 2), (129, 2),
                 (250, 2), (218, 2), (284, 2), (294, 2), (57, 2), (59, 2), (148, 2)]

###################################################################################

NEUTRAL_MINOR = [(317, 530), (301, 499), (267, 454), (309, 438), (314, 422), (288, 420),
                 (178, 415), (320, 414), (89, 399), (319, 383), (0, 341), (233, 307),
                 (215, 133), (37, 127), (212, 123), (193, 121), (123, 121), (34, 119),
                 (191, 117), (126, 115), (104, 108), (112, 107), (272, 105), (23, 102),
                 (15, 96), (127, 92), (38, 87), (283, 85), (102, 84), (91, 83), (94, 83),
                 (306, 82), (216, 80), (2, 80), (280, 79), (293, 78), (5, 78), (13, 77),
                 (183, 76), (114, 74), (316, 69), (105, 68), (180, 64), (201, 62), (256, 58),
                 (16, 56), (246, 55), (203, 55), (303, 52), (194, 52), (282, 49), (311, 49),
                 (248, 47), (238, 43), (258, 41), (249, 39), (7, 32), (10, 29), (96, 29),
                 (25, 28), (125, 27), (214, 27), (36, 26), (134, 23), (99, 22), (310, 22),
                 (270, 21), (291, 20), (223, 20), (302, 20), (213, 19), (185, 19), (217, 19),
                 (3, 19), (221, 19), (45, 18), (268, 16), (289, 16), (235, 15), (179, 14),
                 (234, 14), (181, 14), (312, 13), (240, 13), (21, 13), (274, 13), (110, 13),
                 (92, 13), (236, 13), (31, 13), (120, 13), (304, 12), (269, 11), (113, 11),
                 (150, 10), (43, 10), (132, 10), (68, 9), (157, 9), (202, 9), (55, 9), (144, 9),
                 (315, 9), (318, 9), (42, 9), (131, 9), (188, 8), (70, 8), (159, 8), (241, 7),
                 (275, 7), (296, 7), (8, 7), (290, 7), (97, 7), (186, 7), (24, 7), (119, 7),
                 (227, 7), (254, 6), (219, 6), (35, 6), (273, 6), (124, 6), (294, 6), (247, 6),
                 (220, 6), (281, 6), (208, 6), (46, 6), (61, 6), (243, 5), (199, 5), (128, 5),
                 (30, 5), (11, 5), (218, 5), (192, 5), (162, 5), (257, 5), (138, 5), (264, 5),
                 (148, 4), (41, 4), (130, 4), (39, 4), (307, 4), (40, 4), (129, 4), (17, 4),
                 (106, 4), (195, 4), (224, 4), (135, 4), (209, 4), (276, 3), (297, 3), (26, 3),
                 (115, 3), (277, 3), (20, 3), (109, 3), (198, 3), (6, 3), (298, 3), (95, 3),
                 (184, 3), (1, 3), (165, 3), (66, 3), (155, 3), (73, 3), (69, 3), (158, 3),
                 (71, 3), (160, 3), (64, 3), (153, 3), (18, 3), (107, 3), (187, 2), (242, 2),
                 (59, 2), (239, 2), (226, 2), (163, 2), (14, 2), (65, 2), (263, 2), (103, 2),
                 (154, 2), (49, 2), (27, 2), (253, 2), (116, 2), (287, 2), (205, 2), (4, 1),
                 (93, 1), (182, 1), (237, 1), (271, 1), (292, 1), (222, 1), (19, 1), (108, 1),
                 (197, 1), (57, 1), (146, 1), (143, 1), (211, 1), (232, 1), (266, 1), (47, 1),
                 (86, 1), (87, 1), (136, 1), (175, 1), (176, 1), (225, 1), (82, 1), (83, 1),
                 (171, 1), (172, 1), (117, 1), (206, 1), (261, 1), (48, 1), (137, 1), (90, 1),
                 (204, 1), (250, 1), (259, 1), (284, 1)]

###################################################################################

SAD_MAJOR = [(267, 46), (301, 45), (178, 43), (89, 37), (288, 35), (233, 35), (215, 34),
             (317, 32), (320, 32), (309, 30), (314, 24), (0, 22), (319, 21), (114, 19),
             (203, 19), (258, 19), (37, 19), (193, 18), (126, 18), (15, 17), (104, 17),
             (248, 16), (282, 16), (112, 13), (134, 13), (105, 10), (221, 10), (194, 10),
             (45, 10), (162, 8), (43, 8), (201, 8), (132, 8), (256, 8), (16, 8), (127, 7),
             (283, 6), (38, 6), (306, 5), (223, 5), (216, 5), (31, 5), (23, 5), (120, 5),
             (272, 4), (123, 4), (293, 4), (119, 3), (181, 3), (125, 3), (94, 3), (236, 3),
             (212, 3), (183, 3), (270, 3), (2, 3), (238, 3), (291, 3), (91, 3), (304, 3),
             (209, 3), (312, 3), (264, 3), (163, 2), (148, 2), (157, 2), (316, 2), (217, 2),
             (13, 2), (65, 2), (208, 2), (7, 2), (214, 2), (34, 2), (36, 2), (102, 2),
             (154, 2), (249, 2), (263, 2), (96, 2), (10, 2), (191, 2), (27, 2), (49, 2),
             (99, 2), (116, 2), (138, 2), (180, 2), (205, 2), (227, 2), (235, 2), (226, 1),
             (298, 1), (307, 1), (213, 1), (159, 1), (292, 1), (144, 1), (147, 1), (290, 1),
             (47, 1), (39, 1), (40, 1), (42, 1), (305, 1), (68, 1), (1, 1), (9, 1),
             (303, 1), (136, 1), (128, 1), (129, 1), (131, 1), (313, 1), (90, 1), (98, 1),
             (311, 1), (225, 1), (218, 1), (185, 1), (220, 1), (62, 1), (179, 1), (187, 1),
             (59, 1), (246, 1), (69, 1), (57, 1), (247, 1), (240, 1), (30, 1), (151, 1),
             (188, 1), (239, 1), (234, 1), (242, 1), (280, 1), (158, 1), (146, 1), (281, 1),
             (274, 1), (56, 1), (243, 1), (273, 1), (268, 1), (276, 1)]

###################################################################################

SAD_MINOR = [(178, 1800), (267, 1764), (233, 1727), (309, 1671), (288, 1644), (0, 1610),
             (301, 1580), (320, 1532), (89, 1512), (317, 1454), (319, 1417), (314, 1383),
             (272, 238), (269, 232), (183, 230), (180, 224), (212, 219), (34, 217),
             (238, 217), (311, 214), (2, 212), (5, 210), (303, 208), (293, 206), (91, 202),
             (94, 202), (235, 200), (13, 199), (290, 198), (316, 192), (3, 190), (306, 188),
             (280, 187), (193, 185), (291, 184), (123, 183), (191, 182), (37, 179),
             (199, 172), (102, 169), (181, 164), (110, 163), (92, 163), (246, 161),
             (21, 157), (236, 156), (312, 154), (270, 146), (203, 146), (15, 144),
             (126, 135), (25, 135), (114, 135), (304, 132), (215, 131), (104, 131),
             (254, 130), (38, 124), (112, 124), (282, 123), (216, 114), (23, 111),
             (127, 102), (201, 101), (16, 100), (283, 96), (248, 96), (289, 92), (268, 92),
             (194, 92), (258, 91), (310, 87), (105, 86), (302, 81), (179, 77), (234, 77),
             (249, 76), (256, 76), (318, 60), (315, 57), (1, 53), (8, 49), (186, 47),
             (90, 47), (97, 47), (224, 47), (55, 46), (241, 46), (275, 46), (296, 45),
             (45, 43), (144, 42), (46, 38), (274, 37), (42, 36), (135, 36), (134, 34),
             (217, 31), (214, 30), (59, 30), (61, 30), (240, 28), (148, 28), (70, 28),
             (159, 28), (73, 27), (49, 27), (277, 26), (295, 26), (308, 26), (138, 26),
             (227, 26), (223, 25), (10, 25), (120, 25), (221, 24), (31, 24), (128, 24),
             (185, 23), (39, 23), (99, 23), (36, 23), (150, 21), (243, 21), (162, 21),
             (7, 20), (206, 18), (298, 18), (96, 18), (125, 18), (284, 16), (198, 16),
             (209, 16), (264, 16), (43, 16), (14, 15), (213, 15), (132, 15), (158, 14),
             (28, 14), (188, 13), (117, 13), (35, 13), (253, 12), (103, 12), (192, 12),
             (220, 12), (30, 12), (225, 11), (69, 11), (287, 11), (131, 11), (24, 10),
             (119, 10), (208, 10), (261, 9), (48, 9), (76, 9), (165, 9), (9, 9), (66, 9),
             (4, 9), (195, 8), (250, 8), (58, 8), (147, 8), (247, 8), (281, 8), (47, 7),
             (219, 7), (20, 7), (109, 7), (56, 7), (242, 6), (204, 6), (259, 6), (137, 6),
             (226, 6), (292, 6), (93, 6), (62, 6), (98, 6), (151, 6), (187, 5), (115, 5),
             (273, 5), (294, 5), (17, 5), (130, 5), (106, 5), (145, 5), (313, 5), (182, 5),
             (239, 5), (237, 5), (276, 4), (6, 4), (41, 4), (57, 4), (113, 4), (124, 4),
             (146, 4), (271, 4), (18, 4), (297, 3), (40, 3), (129, 3), (19, 3), (68, 3),
             (95, 3), (108, 3), (157, 3), (184, 3), (197, 3), (232, 3), (86, 3), (175, 3),
             (82, 3), (228, 3), (71, 3), (160, 3), (64, 3), (153, 3), (26, 2), (307, 2),
             (60, 2), (218, 2), (222, 2), (305, 2), (202, 2), (263, 2), (11, 2), (136, 2),
             (171, 2), (79, 2), (244, 1), (278, 1), (299, 1), (149, 1), (22, 1), (257, 1),
             (252, 1), (286, 1), (75, 1), (77, 1), (54, 1), (166, 1), (143, 1), (67, 1),
             (156, 1), (63, 1), (152, 1), (107, 1), (196, 1), (251, 1), (285, 1), (50, 1)]

###################################################################################

UPLIFTING_MAJOR = [(267, 3776), (317, 3723), (301, 3628), (320, 3603), (178, 3569), (89, 3448),
                 (309, 3337), (314, 3216), (0, 3180), (288, 3159), (233, 3061), (319, 3008),
                 (112, 981), (194, 917), (256, 916), (16, 874), (216, 843), (283, 835),
                 (201, 783), (105, 771), (127, 766), (23, 715), (38, 692), (249, 637),
                 (272, 459), (191, 448), (91, 437), (235, 437), (306, 423), (303, 404),
                 (280, 400), (13, 396), (183, 394), (269, 394), (94, 393), (102, 389),
                 (180, 386), (293, 371), (181, 370), (5, 358), (290, 348), (212, 342),
                 (238, 335), (246, 324), (270, 315), (92, 314), (3, 310), (254, 308),
                 (316, 301), (110, 295), (123, 291), (2, 285), (104, 268), (236, 255),
                 (304, 254), (311, 250), (34, 250), (193, 244), (291, 244), (199, 235),
                 (312, 232), (114, 219), (215, 216), (248, 205), (37, 201), (25, 201),
                 (15, 197), (126, 195), (282, 191), (21, 184), (258, 167), (268, 151),
                 (179, 148), (203, 142), (234, 128), (90, 123), (1, 119), (144, 116),
                 (289, 102), (302, 99), (228, 97), (310, 95), (318, 94), (119, 92), (159, 91),
                 (285, 89), (139, 85), (162, 83), (50, 81), (73, 78), (42, 78), (196, 77),
                 (30, 76), (131, 75), (251, 75), (220, 73), (39, 72), (55, 71), (45, 71),
                 (315, 70), (217, 70), (120, 69), (227, 67), (264, 64), (209, 63), (31, 63),
                 (134, 62), (36, 62), (273, 61), (70, 60), (43, 58), (221, 58), (8, 56),
                 (160, 55), (138, 55), (192, 55), (97, 54), (186, 54), (241, 53), (71, 53),
                 (49, 53), (128, 53), (132, 52), (223, 52), (298, 52), (296, 51), (275, 51),
                 (208, 50), (263, 50), (99, 50), (214, 50), (277, 50), (153, 49), (96, 48),
                 (148, 48), (218, 47), (14, 46), (18, 45), (103, 44), (281, 44), (150, 43),
                 (125, 43), (10, 43), (247, 42), (294, 41), (64, 41), (307, 40), (40, 40),
                 (129, 40), (239, 40), (7, 38), (284, 38), (243, 38), (146, 37), (6, 37),
                 (95, 37), (184, 37), (213, 36), (188, 36), (35, 35), (59, 35), (124, 34),
                 (107, 33), (24, 32), (17, 31), (257, 31), (147, 30), (195, 30), (202, 29),
                 (308, 28), (106, 28), (57, 28), (276, 26), (115, 26), (58, 26), (61, 25),
                 (9, 25), (242, 25), (113, 25), (11, 24), (204, 23), (259, 22), (46, 22),
                 (274, 21), (255, 21), (135, 21), (224, 21), (240, 20), (295, 19), (187, 19),
                 (250, 19), (48, 19), (297, 19), (185, 18), (26, 17), (149, 17), (98, 16),
                 (261, 14), (197, 14), (286, 14), (75, 14), (164, 14), (68, 13), (157, 13),
                 (173, 13), (271, 12), (137, 12), (226, 12), (44, 12), (230, 11), (109, 11),
                 (117, 11), (206, 11), (292, 11), (182, 11), (222, 11), (252, 11), (244, 10),
                 (278, 10), (84, 10), (305, 10), (198, 10), (237, 10), (108, 10), (60, 10),
                 (53, 9), (136, 9), (158, 9), (225, 9), (69, 9), (47, 9), (287, 8), (41, 8),
                 (100, 8), (189, 8), (52, 8), (141, 8), (28, 8), (219, 8), (19, 8), (93, 8),
                 (133, 8), (165, 7), (313, 7), (20, 7), (76, 6), (142, 6), (231, 6), (253, 6),
                 (130, 6), (151, 5), (51, 5), (140, 5), (229, 5), (168, 5), (4, 5), (299, 5),
                 (22, 5), (170, 5), (155, 4), (62, 4), (145, 4), (174, 4), (66, 3), (56, 3),
                 (72, 3), (54, 3), (143, 3), (154, 3), (85, 3), (77, 3), (166, 3), (67, 3),
                 (152, 3), (245, 3), (279, 3), (111, 3), (200, 3), (171, 3), (79, 3), (210, 2),
                 (265, 2), (74, 2), (163, 2), (65, 2), (27, 2), (116, 2), (205, 2), (260, 2),
                 (32, 2), (156, 2), (63, 2), (300, 2), (12, 2), (101, 2), (190, 2), (232, 1),
                 (121, 1), (81, 1), (86, 1), (175, 1), (82, 1)]

###################################################################################

UPLIFTING_MINOR = [(301, 5035), (233, 5017), (314, 4999), (89, 4970), (320, 4956), (319, 4954),
                 (0, 4793), (267, 4760), (309, 4744), (178, 4715), (317, 4697), (288, 4644),
                 (114, 1184), (25, 1127), (248, 1111), (282, 1010), (193, 943), (203, 938),
                 (105, 912), (104, 906), (258, 906), (280, 883), (246, 882), (283, 870),
                 (16, 867), (94, 857), (127, 854), (238, 845), (102, 834), (194, 830), (5, 822),
                 (306, 813), (38, 795), (183, 792), (249, 791), (13, 784), (191, 780),
                 (256, 778), (112, 777), (290, 774), (23, 748), (272, 741), (235, 737),
                 (269, 737), (293, 714), (215, 700), (37, 695), (201, 694), (303, 693),
                 (15, 685), (316, 684), (311, 682), (216, 672), (126, 666), (91, 622), (2, 618),
                 (180, 616), (254, 606), (270, 596), (304, 592), (236, 590), (181, 577),
                 (92, 572), (34, 558), (123, 554), (3, 540), (21, 534), (212, 524), (312, 517),
                 (110, 508), (199, 500), (291, 491), (128, 224), (243, 217), (298, 217),
                 (144, 214), (90, 214), (39, 210), (8, 207), (162, 206), (234, 205), (97, 204),
                 (186, 204), (241, 203), (217, 200), (268, 199), (10, 198), (1, 192), (55, 190),
                 (179, 190), (188, 187), (125, 184), (315, 184), (302, 182), (318, 180),
                 (275, 178), (296, 168), (289, 168), (277, 166), (73, 166), (36, 165),
                 (119, 162), (263, 161), (99, 160), (310, 160), (30, 157), (214, 135),
                 (138, 135), (264, 133), (159, 129), (134, 128), (131, 127), (227, 125),
                 (70, 125), (281, 122), (43, 120), (46, 119), (209, 118), (247, 117),
                 (132, 116), (120, 110), (221, 108), (208, 108), (31, 106), (45, 103), (49, 99),
                 (224, 96), (96, 95), (59, 94), (220, 91), (148, 90), (135, 90), (7, 88),
                 (273, 88), (147, 84), (239, 82), (274, 77), (307, 76), (294, 75), (223, 75),
                 (240, 73), (17, 73), (106, 73), (192, 72), (213, 71), (185, 71), (58, 71),
                 (24, 71), (139, 70), (103, 66), (9, 66), (276, 65), (42, 65), (129, 64),
                 (95, 64), (187, 63), (242, 60), (98, 60), (150, 59), (285, 58), (40, 57),
                 (261, 57), (184, 57), (218, 56), (50, 55), (195, 55), (284, 53), (48, 52),
                 (196, 52), (117, 52), (251, 50), (295, 49), (202, 49), (250, 49), (146, 48),
                 (259, 48), (228, 48), (206, 48), (14, 48), (57, 47), (35, 47), (61, 46),
                 (6, 45), (113, 45), (124, 43), (157, 42), (28, 42), (137, 41), (68, 41),
                 (297, 40), (308, 40), (257, 39), (115, 38), (158, 38), (107, 37), (204, 35),
                 (160, 35), (71, 33), (26, 32), (226, 31), (69, 31), (153, 30), (165, 27),
                 (64, 27), (287, 26), (136, 25), (109, 25), (225, 24), (164, 24), (76, 24),
                 (286, 23), (75, 23), (155, 23), (11, 22), (252, 22), (253, 22), (93, 22),
                 (271, 22), (47, 21), (108, 21), (41, 21), (198, 20), (197, 19), (237, 19),
                 (219, 19), (182, 18), (66, 18), (130, 17), (292, 17), (305, 17), (20, 16),
                 (145, 15), (4, 15), (18, 15), (255, 14), (100, 14), (189, 14), (62, 14),
                 (244, 13), (151, 13), (170, 12), (52, 11), (141, 11), (278, 10), (313, 10),
                 (56, 10), (149, 9), (133, 9), (84, 8), (173, 8), (60, 8), (200, 8), (65, 7),
                 (299, 7), (230, 7), (44, 7), (154, 6), (85, 6), (222, 6), (174, 5), (81, 5),
                 (111, 5), (163, 4), (27, 4), (116, 4), (205, 4), (19, 4), (22, 4), (210, 3),
                 (265, 3), (74, 3), (168, 3), (51, 3), (260, 3), (12, 2), (101, 2), (190, 2),
                 (245, 2), (279, 2), (142, 2), (231, 2), (175, 2), (82, 2), (171, 2), (79, 2),
                 (152, 1), (140, 1), (229, 1), (54, 1), (143, 1), (53, 1), (121, 1), (300, 1),
                 (262, 1), (72, 1), (161, 1), (29, 1), (118, 1), (207, 1)]

###################################################################################

ALL_MOOD_TYPES = [HAPPY_MAJOR,
                  UPLIFTING_MAJOR,
                  UPLIFTING_MINOR, 
                  NEUTRAL_MAJOR,
                  NEUTRAL_MINOR,
                  MELANCHOLIC_MAJOR,
                  MELANCHOLIC_MINOR,
                  SAD_MAJOR,
                  SAD_MINOR
                 ]

###################################################################################

ALL_MOOD_TYPES_LABELS = ['Happy Major',
                         'Uplifting Major',
                         'Uplifting Minor',
                         'Neutral Major',
                         'Neutral Minor',
                         'Melancholic Major',
                         'Melancholic Minor',
                         'Sad Major',
                         'Sad Minor'
                        ]

###################################################################################

LEAD_INSTRUMENTS = [0, 1, 2, 3, 4, 5, 6, 7, # Piano
                    8, 9, 10, 11, 12, 13, 14, 15, # Chromatic Percussion
                    16, 17, 18, 19, 20, 21, 22, 23, # Organ
                    24, 25, 26, 27, 28, 29, 30, 31, # Guitar
                    40, 41, 46, # Strings
                    52, 53, 54, # Ensemble
                    56, 57, 59, 60, # Brass
                    64, 65, 66, 67, 68, 69, 70, 71, # Reed
                    72, 73, 74, 75, 76, 77, 78, 79, # Pipe
                    80, 81, 87 # Synth Lead
                   ]

###################################################################################

BASE_INSTRUMENTS = [32, 33, 34, 35, 36, 37, 38, 39, # Bass
                    42, 43, # Strings
                    58, 61, 62, 63, # Brass
                    87 # Synth Lead
                   ]

###################################################################################

def escore_notes_pitches_range(escore_notes,
                               range_patch=-1,
                               pitches_idx=4,
                               patches_idx=6
                               ):

    pitches = []
    
    if -1 < range_patch < 129:
        pitches = [e[pitches_idx] for e in escore_notes if e[patches_idx] == range_patch]

    else:
        pitches = [e[pitches_idx] for e in escore_notes]

    if pitches:
        min_pitch = min(pitches)
        avg_pitch = sum(pitches) / len(pitches)
        mode_pitch = statistics.mode(pitches)
        max_pitch = max(pitches)

        return [max_pitch-min_pitch, min_pitch, max_pitch, avg_pitch, mode_pitch]

    else:
        return [ -1] * 6

###################################################################################

def escore_notes_core(escore_notes, core_len=128):

    cscore = chordify_score([1000, escore_notes])

    chords = []
    chords_idxs = []
    
    for i, c in enumerate(cscore):
        
        pitches = [e[4] for e in c if e[3] != 9]

        if pitches:
            tones_chord = sorted(set([p % 12 for p in pitches]))

            if tones_chord not in ALL_CHORDS_SORTED:
                tones_chord = check_and_fix_tones_chord(tones_chord)

            chords.append(ALL_CHORDS_SORTED.index(tones_chord))
            chords_idxs.append(i)

    mid = len(chords_idxs) // 2
    clen = core_len // 2
    
    sidx = chords_idxs[mid-clen]
    eidx = chords_idxs[mid+clen]

    core_chords = chords[mid-clen:mid+clen]
    core_score = flatten(cscore[sidx:eidx])
    
    return core_score, core_chords

###################################################################################

def multiprocessing_wrapper(function, data_list, verbose=True):
    
    with multiprocessing.Pool() as pool:
        
        results = []
        
        for result in tqdm.tqdm(pool.imap_unordered(function, data_list),
                                total=len(data_list),
                                disable=not verbose
                                ):
            
            results.append(result)
            
    return results

###################################################################################

def rle_encode_ones(matrix, div_mod=-1):
    
    flat_list = [val for row in matrix for val in row]
    
    encoding = []
    i = 0
    
    while i < len(flat_list):
        
        if flat_list[i] == 1:
            
            start_index = i
            count = 1
            i += 1
            
            while i < len(flat_list) and flat_list[i] == 1:
                count += 1
                i += 1
            
            if div_mod > 0:
                encoding.append((start_index // div_mod, start_index % div_mod))
                
            else:
                encoding.append(start_index)
            
        else:
            i += 1
            
    return encoding

###################################################################################

def rle_decode_ones(encoding, size=(128, 128)):
    
    flat_list = [0] * (size[0] * size[1])
    
    for start_index in encoding:
        flat_list[start_index] = 1
        
    matrix = [flat_list[i * size[1]:(i + 1) * size[1]] for i in range(size[0])]
    
    return matrix

###################################################################################

def vertical_list_search(list_of_lists, trg_list):

    src_list = list_of_lists
    
    if not src_list or not trg_list:
        return []
    
    num_rows = len(src_list)
    k = len(trg_list)
    
    row_sets = [set(row) for row in src_list]
    
    results = []
    
    for start in range(num_rows - k + 1):
        valid = True
        
        for offset, target in enumerate(trg_list):

            if target not in row_sets[start + offset]:
                valid = False
                break
                
        if valid:
            results.append(list(range(start, start + k)))
            
    return results
    
###################################################################################

def smooth_values(values, window_size=3):

    smoothed = []
    
    for i in range(len(values)):

        start = max(0, i - window_size // 2)
        end = min(len(values), i + window_size // 2 + 1)
        
        window = values[start:end]
        
        smoothed.append(int(sum(window) / len(window)))
        
    return smoothed

###################################################################################

def is_mostly_wide_peaks_and_valleys(values, 
                                     min_range=32, 
                                     threshold=0.7, 
                                     smoothing_window=5
                                    ):

    if not values:
        return False

    smoothed_values = smooth_values(values, smoothing_window)

    value_range = max(smoothed_values) - min(smoothed_values)
    
    if value_range < min_range:
        return False

    if all(v == smoothed_values[0] for v in smoothed_values):
        return False

    trend_types = []
    
    for i in range(1, len(smoothed_values)):
        if smoothed_values[i] > smoothed_values[i - 1]:
            trend_types.append(1)
            
        elif smoothed_values[i] < smoothed_values[i - 1]:
            trend_types.append(-1)
            
        else:
            trend_types.append(0)

    trend_count = trend_types.count(1) + trend_types.count(-1)

    proportion = trend_count / len(trend_types)

    return proportion >= threshold

###################################################################################

def system_memory_utilization(return_dict=False):

    if return_dict:
        return dict(psutil.virtual_memory()._asdict())

    else:
        print('RAM memory % used:', psutil.virtual_memory()[2])
        print('RAM Used (GB):', psutil.virtual_memory()[3]/(1024**3))

###################################################################################

def system_cpus_utilization(return_dict=False):

    if return_dict:
        return {'num_cpus': psutil.cpu_count(),
                'cpus_util': psutil.cpu_percent()
                }

    else:
        print('Number of CPUs:', psutil.cpu_count())
        print('CPUs utilization:', psutil.cpu_percent())

###################################################################################

def create_files_list(datasets_paths=['./'],
                      files_exts=['.mid', '.midi', '.kar', '.MID', '.MIDI', '.KAR'],
                      max_num_files_per_dir=-1,
                      randomize_dir_files=False,
                      max_total_files=-1,
                      randomize_files_list=True,
                      check_for_dupes=False,
                      use_md5_hashes=False,
                      return_dupes=False,
                      verbose=True
                     ):
    
    if verbose:
        print('=' * 70)
        print('Searching for files...')
        print('This may take a while on a large dataset in particular...')
        print('=' * 70)

    files_exts = tuple(files_exts)
    
    filez_set = defaultdict(None)
    dupes_list = []
 
    for dataset_addr in datasets_paths:
        
        print('=' * 70)
        print('Processing', dataset_addr)
        print('=' * 70)
        
        for dirpath, dirnames, filenames in tqdm.tqdm(os.walk(dataset_addr), disable=not verbose):
                
                if randomize_dir_files:
                    random.shuffle(filenames)
                    
                if max_num_files_per_dir > 0:
                    max_num_files = max_num_files_per_dir
                    
                else:
                    max_num_files = len(filenames)
                    
                for file in filenames[:max_num_files]:
                    if file.endswith(files_exts):
                        if check_for_dupes:
                        
                            if use_md5_hashes:
                                md5_hash = hashlib.md5(open(os.path.join(dirpath, file), 'rb').read()).hexdigest()
                                
                                if md5_hash not in filez_set:
                                    filez_set[md5_hash] = os.path.join(dirpath, file)
                                
                                else:
                                    dupes_list.append(os.path.join(dirpath, file))
                                    
                            else:
                                if file not in filez_set:
                                    filez_set[file] = os.path.join(dirpath, file)
                                
                                else:
                                    dupes_list.append(os.path.join(dirpath, file))
                        else:
                            fpath = os.path.join(dirpath, file)
                            filez_set[fpath] = fpath                              

    filez = list(filez_set.values())

    if verbose:
        print('Done!')
        print('=' * 70)
    
    if filez:
        if randomize_files_list:
            
            if verbose:
                print('Randomizing file list...')
                
            random.shuffle(filez)
            
            if verbose:
                print('Done!')
                print('=' * 70)
                
        if verbose:
            print('Found', len(filez), 'files.')
            print('Skipped', len(dupes_list), 'duplicate files.')
            print('=' * 70)
 
    else:
        if verbose:
            print('Could not find any files...')
            print('Please check dataset dirs and files extensions...')
            print('=' * 70)
    
    if max_total_files > 0:     
        if return_dupes:
            return filez[:max_total_files], dupes_list
        
        else:
            return filez[:max_total_files]
    
    else:
        if return_dupes:
            return filez, dupes_list
        
        else:
            return filez

###################################################################################

def has_consecutive_trend(nums, count):
    
    if len(nums) < count:
        return False
    
    increasing_streak = 1
    decreasing_streak = 1

    for i in range(1, len(nums)):
        if nums[i] > nums[i - 1]:
            increasing_streak += 1
            decreasing_streak = 1
            
        elif nums[i] < nums[i - 1]:
            decreasing_streak += 1
            increasing_streak = 1
            
        else:
            increasing_streak = decreasing_streak = 1
        
        if increasing_streak == count or decreasing_streak == count:
            return True
    
    return False

###################################################################################

def escore_notes_primary_features(escore_notes):

    #=================================================================

    def mean(values):
        return sum(values) / len(values) if values else None

    def std(values):
        if not values:
            return None
        m = mean(values)
        return math.sqrt(sum((x - m) ** 2 for x in values) / len(values)) if m is not None else None

    def skew(values):
        if not values:
            return None
        m = mean(values)
        s = std(values)
        if s is None or s == 0:
            return None
        return sum(((x - m) / s) ** 3 for x in values) / len(values)

    def kurtosis(values):
        if not values:
            return None
        m = mean(values)
        s = std(values)
        if s is None or s == 0:
            return None
        return sum(((x - m) / s) ** 4 for x in values) / len(values) - 3

    def median(values):
        if not values:
            return None
        srt = sorted(values)
        n = len(srt)
        mid = n // 2
        if n % 2 == 0:
            return (srt[mid - 1] + srt[mid]) / 2.0
        return srt[mid]

    def percentile(values, p):
        if not values:
            return None
        srt = sorted(values)
        n = len(srt)
        k = (n - 1) * p / 100.0
        f = int(k)
        c = k - f
        if f + 1 < n:
            return srt[f] * (1 - c) + srt[f + 1] * c
        return srt[f]

    def diff(values):
        if not values or len(values) < 2:
            return []
        return [values[i + 1] - values[i] for i in range(len(values) - 1)]

    def mad(values):
        if not values:
            return None
        m = median(values)
        return median([abs(x - m) for x in values])

    def entropy(values):
        if not values:
            return None
        freq = {}
        for v in values:
            freq[v] = freq.get(v, 0) + 1
        total = len(values)
        ent = 0.0
        for count in freq.values():
            p_val = count / total
            ent -= p_val * math.log2(p_val)
        return ent

    def mode(values):
        if not values:
            return None
        freq = {}
        for v in values:
            freq[v] = freq.get(v, 0) + 1
        max_count = max(freq.values())
        modes = [k for k, count in freq.items() if count == max_count]
        return min(modes)


    #=================================================================
    
    sp_score = solo_piano_escore_notes(escore_notes)

    dscore = delta_score_notes(sp_score)
    
    seq = []
    
    for d in dscore:
        seq.extend([d[1], d[2], d[4]])

    #=================================================================

    n = len(seq)
    if n % 3 != 0:
        seq = seq[: n - (n % 3)]
    arr = [seq[i:i + 3] for i in range(0, len(seq), 3)]

    #=================================================================
    
    features = {}

    delta_times = [row[0] for row in arr]
    if delta_times:
        features['delta_times_mean'] = mean(delta_times)
        features['delta_times_std'] = std(delta_times)
        features['delta_times_min'] = min(delta_times)
        features['delta_times_max'] = max(delta_times)
        features['delta_times_skew'] = skew(delta_times)
        features['delta_times_kurtosis'] = kurtosis(delta_times)
        delta_zero_count = sum(1 for x in delta_times if x == 0)
        features['delta_times_zero_ratio'] = delta_zero_count / len(delta_times)
        nonzero_dt = [x for x in delta_times if x != 0]
        if nonzero_dt:
            features['delta_times_nonzero_mean'] = mean(nonzero_dt)
            features['delta_times_nonzero_std'] = std(nonzero_dt)
        else:
            features['delta_times_nonzero_mean'] = None
            features['delta_times_nonzero_std'] = None
        features['delta_times_mad'] = mad(delta_times)
        features['delta_times_cv'] = (features['delta_times_std'] / features['delta_times_mean']
                                      if features['delta_times_mean'] and features['delta_times_mean'] != 0 else None)
        features['delta_times_entropy'] = entropy(delta_times)
        features['delta_times_range'] = max(delta_times) - min(delta_times)
        features['delta_times_median'] = median(delta_times)
        features['delta_times_quantile_25'] = percentile(delta_times, 25)
        features['delta_times_quantile_75'] = percentile(delta_times, 75)
        if (features['delta_times_quantile_25'] is not None and features['delta_times_quantile_75'] is not None):
            features['delta_times_iqr'] = features['delta_times_quantile_75'] - features['delta_times_quantile_25']
        else:
            features['delta_times_iqr'] = None
    else:
        for key in ['delta_times_mean', 'delta_times_std', 'delta_times_min', 'delta_times_max',
                    'delta_times_skew', 'delta_times_kurtosis', 'delta_times_zero_ratio',
                    'delta_times_nonzero_mean', 'delta_times_nonzero_std', 'delta_times_mad',
                    'delta_times_cv', 'delta_times_entropy', 'delta_times_range', 'delta_times_median',
                    'delta_times_quantile_25', 'delta_times_quantile_75', 'delta_times_iqr']:
            features[key] = None

    #=================================================================

    durations = [row[1] for row in arr]
    if durations:
        features['durations_mean'] = mean(durations)
        features['durations_std'] = std(durations)
        features['durations_min'] = min(durations)
        features['durations_max'] = max(durations)
        features['durations_skew'] = skew(durations)
        features['durations_kurtosis'] = kurtosis(durations)
        features['durations_mad'] = mad(durations)
        features['durations_cv'] = (features['durations_std'] / features['durations_mean']
                                    if features['durations_mean'] and features['durations_mean'] != 0 else None)
        features['durations_entropy'] = entropy(durations)
        features['durations_range'] = max(durations) - min(durations)
        features['durations_median'] = median(durations)
        features['durations_quantile_25'] = percentile(durations, 25)
        features['durations_quantile_75'] = percentile(durations, 75)
        if features['durations_quantile_25'] is not None and features['durations_quantile_75'] is not None:
            features['durations_iqr'] = features['durations_quantile_75'] - features['durations_quantile_25']
        else:
            features['durations_iqr'] = None
    else:
        for key in ['durations_mean', 'durations_std', 'durations_min', 'durations_max',
                    'durations_skew', 'durations_kurtosis', 'durations_mad', 'durations_cv',
                    'durations_entropy', 'durations_range', 'durations_median', 'durations_quantile_25',
                    'durations_quantile_75', 'durations_iqr']:
            features[key] = None

    #=================================================================

    pitches = [row[2] for row in arr]
    if pitches:
        features['pitches_mean'] = mean(pitches)
        features['pitches_std'] = std(pitches)
        features['pitches_min'] = min(pitches)
        features['pitches_max'] = max(pitches)
        features['pitches_skew'] = skew(pitches)
        features['pitches_kurtosis'] = kurtosis(pitches)
        features['pitches_range'] = max(pitches) - min(pitches)
        features['pitches_median'] = median(pitches)
        features['pitches_quantile_25'] = percentile(pitches, 25)
        features['pitches_quantile_75'] = percentile(pitches, 75)
        if len(pitches) > 1:
            dps = diff(pitches)
            features['pitches_diff_mean'] = mean(dps)
            features['pitches_diff_std'] = std(dps)
        else:
            features['pitches_diff_mean'] = None
            features['pitches_diff_std'] = None
        features['pitches_mad'] = mad(pitches)
        if len(pitches) > 2:
            peaks = sum(1 for i in range(1, len(pitches)-1)
                        if pitches[i] > pitches[i-1] and pitches[i] > pitches[i+1])
            valleys = sum(1 for i in range(1, len(pitches)-1)
                          if pitches[i] < pitches[i-1] and pitches[i] < pitches[i+1])
        else:
            peaks, valleys = None, None
        features['pitches_peak_count'] = peaks
        features['pitches_valley_count'] = valleys
        if len(pitches) > 1:
            x = list(range(len(pitches)))
            denominator = (len(x) * sum(xi ** 2 for xi in x) - sum(x) ** 2)
            if denominator != 0:
                slope = (len(x) * sum(x[i] * pitches[i] for i in range(len(x))) -
                         sum(x) * sum(pitches)) / denominator
            else:
                slope = None
            features['pitches_trend_slope'] = slope
        else:
            features['pitches_trend_slope'] = None

        features['pitches_unique_count'] = len(set(pitches))
        pitch_class_hist = {i: 0 for i in range(12)}
        for p in pitches:
            pitch_class_hist[p % 12] += 1
        total_pitch = len(pitches)
        for i in range(12):
            features[f'pitches_pc_{i}'] = (pitch_class_hist[i] / total_pitch) if total_pitch > 0 else None

        max_asc = 0
        cur_asc = 0
        max_desc = 0
        cur_desc = 0
        for i in range(1, len(pitches)):
            if pitches[i] > pitches[i-1]:
                cur_asc += 1
                max_asc = max(max_asc, cur_asc)
                cur_desc = 0
            elif pitches[i] < pitches[i-1]:
                cur_desc += 1
                max_desc = max(max_desc, cur_desc)
                cur_asc = 0
            else:
                cur_asc = 0
                cur_desc = 0
        features['pitches_max_consecutive_ascending'] = max_asc if pitches else None
        features['pitches_max_consecutive_descending'] = max_desc if pitches else None
        p_intervals = diff(pitches)
        features['pitches_median_diff'] = median(p_intervals) if p_intervals else None
        if p_intervals:
            dc = sum(1 for i in range(1, len(p_intervals))
                     if (p_intervals[i] > 0 and p_intervals[i-1] < 0) or (p_intervals[i] < 0 and p_intervals[i-1] > 0))
            features['pitches_direction_changes'] = dc
        else:
            features['pitches_direction_changes'] = None
    else:
        for key in (['pitches_mean', 'pitches_std', 'pitches_min', 'pitches_max', 'pitches_skew',
                     'pitches_kurtosis', 'pitches_range', 'pitches_median', 'pitches_quantile_25',
                     'pitches_quantile_75', 'pitches_diff_mean', 'pitches_diff_std', 'pitches_mad',
                     'pitches_peak_count', 'pitches_valley_count', 'pitches_trend_slope',
                     'pitches_unique_count', 'pitches_max_consecutive_ascending', 'pitches_max_consecutive_descending',
                     'pitches_median_diff', 'pitches_direction_changes'] +
                    [f'pitches_pc_{i}' for i in range(12)]):
            features[key] = None

    #=================================================================

    overall = [x for row in arr for x in row]
    if overall:
        features['overall_mean'] = mean(overall)
        features['overall_std'] = std(overall)
        features['overall_min'] = min(overall)
        features['overall_max'] = max(overall)
        features['overall_cv'] = (features['overall_std'] / features['overall_mean']
                                  if features['overall_mean'] and features['overall_mean'] != 0 else None)
    else:
        for key in ['overall_mean', 'overall_std', 'overall_min', 'overall_max', 'overall_cv']:
            features[key] = None

    #=================================================================

    onsets = []
    cumulative = 0
    for dt in delta_times:
        onsets.append(cumulative)
        cumulative += dt
    if onsets and durations:
        overall_piece_duration = onsets[-1] + durations[-1]
    else:
        overall_piece_duration = None
    features['overall_piece_duration'] = overall_piece_duration
    features['overall_notes_density'] = (len(arr) / overall_piece_duration
                                         if overall_piece_duration and overall_piece_duration > 0 else None)
    features['rhythm_ratio'] = (features['durations_mean'] / features['delta_times_mean']
                                if features['delta_times_mean'] and features['delta_times_mean'] != 0 else None)
    features['overall_sum_delta_times'] = (sum(delta_times) if delta_times else None)
    features['overall_sum_durations'] = (sum(durations) if durations else None)
    features['overall_voicing_ratio'] = (sum(durations) / overall_piece_duration
                                         if overall_piece_duration and durations else None)
    features['overall_onset_std'] = std(onsets) if onsets else None

    #=================================================================

    chords_raw = []
    chords_pc = []
    current_group = []
    for i, note in enumerate(arr):
        dt = note[0]
        if i == 0:
            current_group = [i]
        else:
            if dt == 0:
                current_group.append(i)
            else:
                if len(current_group) >= 2:
                    chord_notes = [arr[j][2] for j in current_group]
                    chords_raw.append(tuple(sorted(chord_notes)))
                    chords_pc.append(tuple(sorted(set(p % 12 for p in chord_notes))))

                current_group = [i]

    if current_group and len(current_group) >= 2:
        chord_notes = [arr[j][2] for j in current_group]
        chords_raw.append(tuple(sorted(chord_notes)))
        chords_pc.append(tuple(sorted(set(p % 12 for p in chord_notes))))
    
    if chords_raw:
        chord_count = len(chords_raw)
        features['chords_count'] = chord_count
        features['chords_density'] = (chord_count / overall_piece_duration
                                      if overall_piece_duration and chord_count is not None else None)
        chord_sizes = [len(ch) for ch in chords_raw]
        features['chords_size_mean'] = mean(chord_sizes)
        features['chords_size_std'] = std(chord_sizes)
        features['chords_size_min'] = min(chord_sizes) if chord_sizes else None
        features['chords_size_max'] = max(chord_sizes) if chord_sizes else None
        features['chords_unique_raw_count'] = len(set(chords_raw))
        features['chords_unique_pc_count'] = len(set(chords_pc))
        features['chords_entropy_raw'] = entropy(chords_raw)
        features['chords_entropy_pc'] = entropy(chords_pc)
        if len(chords_raw) > 1:
            rep_raw = sum(1 for i in range(1, len(chords_raw)) if chords_raw[i] == chords_raw[i - 1])
            features['chords_repeat_ratio_raw'] = rep_raw / (len(chords_raw) - 1)
        else:
            features['chords_repeat_ratio_raw'] = None
        if len(chords_pc) > 1:
            rep_pc = sum(1 for i in range(1, len(chords_pc)) if chords_pc[i] == chords_pc[i - 1])
            features['chords_repeat_ratio_pc'] = rep_pc / (len(chords_pc) - 1)
        else:
            features['chords_repeat_ratio_pc'] = None
        if len(chords_raw) > 1:
            bigrams_raw = [(chords_raw[i], chords_raw[i + 1]) for i in range(len(chords_raw) - 1)]
            features['chords_bigram_entropy_raw'] = entropy(bigrams_raw)
        else:
            features['chords_bigram_entropy_raw'] = None
        if len(chords_pc) > 1:
            bigrams_pc = [(chords_pc[i], chords_pc[i + 1]) for i in range(len(chords_pc) - 1)]
            features['chords_bigram_entropy_pc'] = entropy(bigrams_pc)
        else:
            features['chords_bigram_entropy_pc'] = None
        features['chords_mode_raw'] = mode(chords_raw)
        features['chords_mode_pc'] = mode(chords_pc)
        if chords_pc:
            pc_sizes = [len(ch) for ch in chords_pc]
            features['chords_pc_size_mean'] = mean(pc_sizes)
        else:
            features['chords_pc_size_mean'] = None
    else:
        for key in ['chords_count', 'chords_density', 'chords_size_mean', 'chords_size_std',
                    'chords_size_min', 'chords_size_max', 'chords_unique_raw_count', 'chords_unique_pc_count',
                    'chords_entropy_raw', 'chords_entropy_pc', 'chords_repeat_ratio_raw', 'chords_repeat_ratio_pc',
                    'chords_bigram_entropy_raw', 'chords_bigram_entropy_pc', 'chords_mode_raw', 'chords_mode_pc',
                    'chords_pc_size_mean']:
            features[key] = None

    #=================================================================

    if delta_times:
        med_dt = features['delta_times_median']
        iqr_dt = features['delta_times_iqr']
        threshold_a = med_dt + 1.5 * iqr_dt if med_dt is not None and iqr_dt is not None else None
        threshold_b = percentile(delta_times, 90)
        if threshold_a is not None and threshold_b is not None:
            phrase_threshold = max(threshold_a, threshold_b)
        elif threshold_a is not None:
            phrase_threshold = threshold_a
        elif threshold_b is not None:
            phrase_threshold = threshold_b
        else:
            phrase_threshold = None
    else:
        phrase_threshold = None

    phrases = []
    current_phrase = []
    if onsets:
        current_phrase.append(0)
        for i in range(len(onsets) - 1):
            gap = onsets[i + 1] - onsets[i]
            if phrase_threshold is not None and gap > phrase_threshold:
                phrases.append(current_phrase)
                current_phrase = []
            current_phrase.append(i + 1)
        if current_phrase:
            phrases.append(current_phrase)
    if phrases:
        phrase_note_counts = []
        phrase_durations = []
        phrase_densities = []
        phrase_mean_pitches = []
        phrase_pitch_ranges = []
        phrase_start_times = []
        phrase_end_times = []
        for phrase in phrases:
            note_count = len(phrase)
            phrase_note_counts.append(note_count)
            ph_start = onsets[phrase[0]]
            ph_end = onsets[phrase[-1]] + durations[phrase[-1]]
            phrase_start_times.append(ph_start)
            phrase_end_times.append(ph_end)
            ph_duration = ph_end - ph_start
            phrase_durations.append(ph_duration)
            density = note_count / ph_duration if ph_duration > 0 else None
            phrase_densities.append(density)
            ph_pitches = [pitches[i] for i in phrase if i < len(pitches)]
            phrase_mean_pitches.append(mean(ph_pitches) if ph_pitches else None)
            phrase_pitch_ranges.append((max(ph_pitches) - min(ph_pitches)) if ph_pitches else None)
        if len(phrases) > 1:
            phrase_gaps = []
            for i in range(len(phrases) - 1):
                gap = phrase_start_times[i + 1] - phrase_end_times[i]
                phrase_gaps.append(gap if gap > 0 else 0)
        else:
            phrase_gaps = []
        features['phrases_count'] = len(phrases)
        features['phrases_avg_note_count'] = mean(phrase_note_counts) if phrase_note_counts else None
        features['phrases_std_note_count'] = std(phrase_note_counts) if phrase_note_counts else None
        features['phrases_min_note_count'] = min(phrase_note_counts) if phrase_note_counts else None
        features['phrases_max_note_count'] = max(phrase_note_counts) if phrase_note_counts else None
        features['phrases_avg_duration'] = mean(phrase_durations) if phrase_durations else None
        features['phrases_std_duration'] = std(phrase_durations) if phrase_durations else None
        features['phrases_min_duration'] = min(phrase_durations) if phrase_durations else None
        features['phrases_max_duration'] = max(phrase_durations) if phrase_durations else None
        features['phrases_avg_density'] = mean(phrase_densities) if phrase_densities else None
        features['phrases_std_density'] = std(phrase_densities) if phrase_densities else None
        features['phrases_avg_mean_pitch'] = mean(phrase_mean_pitches) if phrase_mean_pitches else None
        features['phrases_avg_pitch_range'] = mean(phrase_pitch_ranges) if phrase_pitch_ranges else None
        if phrase_gaps:
            features['phrases_avg_gap'] = mean(phrase_gaps)
            features['phrases_std_gap'] = std(phrase_gaps)
            features['phrases_min_gap'] = min(phrase_gaps)
            features['phrases_max_gap'] = max(phrase_gaps)
        else:
            features['phrases_avg_gap'] = None
            features['phrases_std_gap'] = None
            features['phrases_min_gap'] = None
            features['phrases_max_gap'] = None
        features['phrases_threshold'] = phrase_threshold
    else:
        for key in ['phrases_count', 'phrases_avg_note_count', 'phrases_std_note_count',
                    'phrases_min_note_count', 'phrases_max_note_count', 'phrases_avg_duration',
                    'phrases_std_duration', 'phrases_min_duration', 'phrases_max_duration',
                    'phrases_avg_density', 'phrases_std_density', 'phrases_avg_mean_pitch',
                    'phrases_avg_pitch_range', 'phrases_avg_gap', 'phrases_std_gap',
                    'phrases_min_gap', 'phrases_max_gap', 'phrases_threshold']:
            features[key] = None

    #=================================================================

    return features

###################################################################################

def winsorized_normalize(data, new_range=(0, 255), clip=1.5):

    #=================================================================

    new_min, new_max = new_range

    #=================================================================

    def percentile(values, p):
        
        srt = sorted(values)
        n = len(srt)
        if n == 1:
            return srt[0]
        k = (n - 1) * p / 100.0
        f = int(k)
        c = k - f
        if f + 1 < n:
            return srt[f] * (1 - c) + srt[f + 1] * c
            
        return srt[f]

    #=================================================================

    q1 = percentile(data, 25)
    q3 = percentile(data, 75)
    iqr = q3 - q1

    lower_bound_w = q1 - clip * iqr
    upper_bound_w = q3 + clip * iqr

    data_min = min(data)
    data_max = max(data)
    effective_low = max(lower_bound_w, data_min)
    effective_high = min(upper_bound_w, data_max)

    #=================================================================

    if effective_high == effective_low:
        
        if data_max == data_min:
            return [int(new_min)] * len(data)
            
        normalized = [(x - data_min) / (data_max - data_min) for x in data]
        
        return [int(round(new_min + norm * (new_max - new_min))) for norm in normalized]

    #=================================================================

    clipped = [x if x >= effective_low else effective_low for x in data]
    clipped = [x if x <= effective_high else effective_high for x in clipped]

    normalized = [(x - effective_low) / (effective_high - effective_low) for x in clipped]

    #=================================================================
    
    return [int(round(new_min + norm * (new_max - new_min))) for norm in normalized]

###################################################################################

def tokenize_features_to_ints_winsorized(features, new_range=(0, 255), clip=1.5, none_token=-1):

    values = []    
    tokens = []

    #=================================================================

    def process_value(val):
        
        if isinstance(val, (int, float)):
            return int(round(abs(val)))
            
        elif isinstance(val, (list, tuple)):
            return int(round(abs(sum(val) / len(val))))
            
        else:
            return int(abs(hash(val)) % (10 ** 8))

    #=================================================================

    for key in sorted(features.keys()):
        
        value = features[key]
        
        if value is None:
            tokens.append(none_token)
            values.append(none_token)
            
        else:
            tokens.append(process_value(value))
            
            if isinstance(value, (list, tuple)):
                values.append(sum(value) / len(value))
                
            else:
                values.append(value)

    #=================================================================
    
    norm_tokens = winsorized_normalize(tokens, new_range, clip)

    #=================================================================

    return values, tokens, norm_tokens

###################################################################################

def write_jsonl(records_dicts_list, 
                file_name='data', 
                file_ext='.jsonl', 
                file_mode='w', 
                line_sep='\n', 
                verbose=True
               ):

    if verbose:
        print('=' * 70)
        print('Writing', len(records_dicts_list), 'records to jsonl file...')
        print('=' * 70)

    if not os.path.splitext(file_name)[1]:
        file_name += file_ext

    l_count = 0

    with open(file_name, mode=file_mode) as f:
        for record in tqdm.tqdm(records_dicts_list, disable=not verbose):
            f.write(json.dumps(record) + line_sep)
            l_count += 1

    f.close()

    if verbose:
        print('=' * 70)
        print('Written total of', l_count, 'jsonl records.')
        print('=' * 70)
        print('Done!')
        print('=' * 70)

###################################################################################
        
def read_jsonl(file_name='data', 
               file_ext='.jsonl', 
               verbose=True
              ):

    if verbose:
        print('=' * 70)
        print('Reading jsonl file...')
        print('=' * 70)

    if not os.path.splitext(file_name)[1]:
        file_name += file_ext

    with open(file_name, 'r') as f:

        records = []
        gl_count = 0
        
        for i, line in tqdm.tqdm(enumerate(f), disable=not verbose):
            
            try:
                record = json.loads(line)
                records.append(record)
                gl_count += 1

            except KeyboardInterrupt:
                if verbose:
                    print('=' * 70)
                    print('Stoping...')
                    print('=' * 70)
                    
                f.close()
    
                return records
               
            except json.JSONDecodeError:
                if verbose:
                    print('=' * 70)
                    print('[ERROR] Line', i, 'is corrupted! Skipping it...')
                    print('=' * 70)
                    
                continue
                
    f.close()
    
    if verbose:
        print('=' * 70)
        print('Loaded total of', gl_count, 'jsonl records.')
        print('=' * 70)
        print('Done!')
        print('=' * 70)

    return records

###################################################################################

def read_jsonl_lines(lines_indexes_list, 
                     file_name='data', 
                     file_ext='.jsonl', 
                     verbose=True
                    ):

    if verbose:
        print('=' * 70)
        print('Reading jsonl file...')
        print('=' * 70)

    if not os.path.splitext(file_name)[1]:
        file_name += file_ext

    records = []
    l_count = 0

    lines_indexes_list.sort(reverse=True)

    with open(file_name, 'r') as f:
        for current_line_number, line in tqdm.tqdm(enumerate(f)):

            try:
                if current_line_number in lines_indexes_list:
                    record = json.loads(line)
                    records.append(record)
                    lines_indexes_list = lines_indexes_list[:-1]
                    l_count += 1

                if not lines_indexes_list:
                    break

            except KeyboardInterrupt:
                if verbose:
                    print('=' * 70)
                    print('Stoping...')
                    print('=' * 70)
                    
                f.close()
    
                return records
               
            except json.JSONDecodeError:
                if verbose:
                    print('=' * 70)
                    print('[ERROR] Line', current_line_number, 'is corrupted! Skipping it...')
                    print('=' * 70)
                    
                continue

    f.close()
    
    if verbose:
        print('=' * 70)
        print('Loaded total of', l_count, 'jsonl records.')
        print('=' * 70)
        print('Done!')
        print('=' * 70)

    return records

###################################################################################

def compute_base(x: int, n: int) -> int:

    if x < 0:
        raise ValueError("x must be non-negative.")
    if x == 0:
        return 2 
        
    b = max(2, int(x ** (1 / n)))
    
    if b ** n <= x:
        b += 1
        
    return b

###################################################################################

def encode_int_auto(x: int, n: int) -> tuple[int, list[int]]:
   
    base = compute_base(x, n)
    digits = [0] * n
    
    for i in range(n - 1, -1, -1):
        digits[i] = x % base
        x //= base
        
    return base, digits

###################################################################################

def decode_int_auto(base: int, digits: list[int]) -> int:
   
    x = 0
    for digit in digits:
        if digit < 0 or digit >= base:
            raise ValueError(f"Each digit must be in the range 0 to {base - 1}. Invalid digit: {digit}")
            
        x = x * base + digit
        
    return x

###################################################################################

def encode_int_manual(x, base, n):

    digits = [0] * n
    
    for i in range(n - 1, -1, -1):
        digits[i] = x % base
        x //= base

    return digits

###################################################################################

def escore_notes_pitches_chords_signature(escore_notes, 
                                          max_patch=128, 
                                          sort_by_counts=False, 
                                          use_full_chords=False
                                         ):
    
    if use_full_chords:
        CHORDS = ALL_CHORDS_FULL
        
    else:
        CHORDS = ALL_CHORDS_SORTED
    
    max_patch = max(0, min(128, max_patch))

    escore_notes = [e for e in escore_notes if e[6] <= max_patch]

    if escore_notes:

        cscore = chordify_score([1000, escore_notes])
        
        sig = []
        dsig = []
        
        drums_offset = len(CHORDS) + 128
        
        bad_chords_counter = 0
        
        for c in cscore:
            
            all_pitches = [e[4] if e[3] != 9 else e[4]+128 for e in c]
            chord = sorted(set(all_pitches))
        
            pitches = sorted([p for p in chord if p < 128], reverse=True)
            drums = [(d+drums_offset)-128 for d in chord if d > 127]
        
            if pitches:
              if len(pitches) > 1:
                tones_chord = sorted(set([p % 12 for p in pitches]))
                     
                try:
                    sig_token = CHORDS.index(tones_chord) + 128
                except:
                    checked_tones_chord = check_and_fix_tones_chord(tones_chord, use_full_chords=use_full_chords)
                    sig_token = CHORDS.index(checked_tones_chord) + 128
                    bad_chords_counter += 1
                    
              elif len(pitches) == 1:
                sig_token = pitches[0]
        
              sig.append(sig_token)
        
            if drums:
              dsig.extend(drums)
        
        sig_p = {}
        
        for item in sig+dsig:
            
            if item in sig_p:
                sig_p[item] += 1
        
            else:
                sig_p[item] = 1
        
        sig_p[-1] = bad_chords_counter
        
        fsig = [list(v) for v in sig_p.items()]
    
        if sort_by_counts:
            fsig.sort(key=lambda x: x[1], reverse=True)
    
        return fsig

    else:
        return []

###################################################################################

def compute_sustain_intervals(events):

    intervals = []
    pedal_on = False
    current_start = None
    
    for t, cc in events:
        if not pedal_on and cc >= 64:

            pedal_on = True
            current_start = t
        elif pedal_on and cc < 64:

            pedal_on = False
            intervals.append((current_start, t))
            current_start = None

    if pedal_on:
        intervals.append((current_start, float('inf')))

    merged = []
    
    for interval in intervals:
        if merged and interval[0] <= merged[-1][1]:
            merged[-1] = (merged[-1][0], max(merged[-1][1], interval[1]))
        else:
            merged.append(interval)
    return merged

###################################################################################

def apply_sustain_to_ms_score(score):

    sustain_by_channel = {}
    
    for track in score[1:]:
        for event in track:
            if event[0] == 'control_change' and event[3] == 64:
                channel = event[2]
                sustain_by_channel.setdefault(channel, []).append((event[1], event[4]))
    
    sustain_intervals_by_channel = {}
    
    for channel, events in sustain_by_channel.items():
        events.sort(key=lambda x: x[0])
        sustain_intervals_by_channel[channel] = compute_sustain_intervals(events)
    
    global_max_off = 0
    
    for track in score[1:]:
        for event in track:
            if event[0] == 'note':
                global_max_off = max(global_max_off, event[1] + event[2])
                
    for channel, intervals in sustain_intervals_by_channel.items():
        updated_intervals = []
        for start, end in intervals:
            if end == float('inf'):
                end = global_max_off
            updated_intervals.append((start, end))
        sustain_intervals_by_channel[channel] = updated_intervals
        
    if sustain_intervals_by_channel:
        
        for track in score[1:]:
            for event in track:
                if event[0] == 'note':
                    start = event[1]
                    nominal_dur = event[2]
                    nominal_off = start + nominal_dur
                    channel = event[3]
                    
                    intervals = sustain_intervals_by_channel.get(channel, [])
                    effective_off = nominal_off
        
                    for intv_start, intv_end in intervals:
                        if intv_start < nominal_off < intv_end:
                            effective_off = intv_end
                            break
                    
                    effective_dur = effective_off - start
                    
                    event[2] = effective_dur

    return score
    
###################################################################################

def copy_file(src_file: str, trg_dir: str, add_subdir: bool = False, verbose: bool = False):
   
    src_path = Path(src_file)
    target_directory = Path(trg_dir)

    if not src_path.is_file():
        if verbose:
            print("Source file does not exist or is not a file.")
        
        return None

    target_directory.mkdir(parents=True, exist_ok=True)
    
    if add_subdir:
        first_letter = src_path.name[0]
        target_directory = target_directory / first_letter
        target_directory.mkdir(parents=True, exist_ok=True)

    destination = target_directory / src_path.name

    try:
        shutil.copy2(src_path, destination)

    except:
        if verbose:
            print('File could not be copied!')
            
        return None
    
    if verbose:
        print('File copied!')

    return None

###################################################################################

def escore_notes_even_timings(escore_notes, in_place=True):

    if in_place:
        for e in escore_notes:
            if e[1] % 2 != 0:
                e[1] += 1
    
            if e[2] % 2 != 0:
                e[2] += 1

        return []

    else:
        escore = copy.deepcopy(escore_notes)
        
        for e in escore:
            if e[1] % 2 != 0:
                e[1] += 1
    
            if e[2] % 2 != 0:
                e[2] += 1

        return escore

###################################################################################

def both_chords(chord1, chord2, merge_threshold=2):
    
    if len(chord1) > 1 and len(chord2) > 0 and chord2[0][1]-chord1[0][1] <= merge_threshold:
        return True
    
    elif len(chord1) > 0 and len(chord2) > 1 and chord2[0][1]-chord1[0][1] <= merge_threshold:
        return True

    else:
        return False

def merge_chords(chord1, chord2, sort_drums_last=False):

    mchord = chord1

    seen = []

    for e in chord2:
        if tuple([e[4], e[6]]) not in seen:
            mchord.append(e)
            seen.append(tuple([e[4], e[6]]))

    for e in mchord[1:]:
        e[1] = mchord[0][1]
    
    if sort_drums_last:
        mchord.sort(key=lambda x: (-x[4], x[6]) if x[6] != 128 else (x[6], -x[4]))

    else:
        mchord.sort(key=lambda x: (-x[4], x[6]))

    return mchord
    
def merge_escore_notes(escore_notes, merge_threshold=2, sort_drums_last=False):

    cscore = chordify_score([1000, escore_notes])
    
    merged_chords = []
    merged_chord = cscore[0]
    
    for i in range(1, len(cscore)):

        cchord = cscore[i]

        if both_chords(merged_chord, cchord, merge_threshold=merge_threshold):
            merged_chord = merge_chords(merged_chord, cchord, sort_drums_last=sort_drums_last)

        else:
            merged_chords.append(merged_chord)
            merged_chord = cchord
            
    return flatten(merged_chords)

###################################################################################

def solo_piano_escore_notes_tokenized(escore_notes,
                                      compress_start_times=True,
                                      encode_velocities=False,
                                      verbose=False
                                      ):

    if verbose:
        print('=' * 70)
        print('Encoding MIDI...')
    
    sp_escore_notes = solo_piano_escore_notes(escore_notes)
    zscore = recalculate_score_timings(sp_escore_notes)
    dscore = delta_score_notes(zscore, timings_clip_value=127)
    
    score = []
    
    notes_counter = 0
    chords_counter = 1
    
    for i, e in enumerate(dscore):
        
        dtime = e[1]
        dur = e[2]
        ptc = e[4]
        vel = e[5]

        if compress_start_times:
            
            if i == 0:
                score.extend([0, dur+128, ptc+256])
                
                if encode_velocities:
                    score.append(vel+384)
                    
            else:
                if dtime == 0:
                    score.extend([dur+128, ptc+256])

                else:
                    score.extend([dtime, dur+128, ptc+256])
                    
                if encode_velocities:
                    score.append(vel+384)
                    
            if dtime != 0:
                chords_counter += 1

        else:
            score.extend([dtime, dur+128, ptc+256])

            if encode_velocities:
                score.append(vel+384)

            if dtime != 0:
                chords_counter += 1
                
        notes_counter += 1

    if verbose:
        print('Done!')
        print('=' * 70)
        
        print('Source MIDI composition has', len(zscore), 'notes')
        print('Source MIDI composition has', len([d[1] for d in dscore if d[1] !=0 ])+1, 'chords')
        print('-' * 70)
        print('Encoded sequence has', notes_counter, 'pitches')
        print('Encoded sequence has', chords_counter, 'chords')
        print('-' * 70)
        print('Final encoded sequence has', len(score), 'tokens')
        print('=' * 70)
        
    return score

###################################################################################

def equalize_closest_elements_dynamic(seq,
                                      min_val=128,
                                      max_val=256,
                                      splitting_factor=1.5,
                                      tightness_threshold=0.15
                                      ):

    candidates = [(i, x) for i, x in enumerate(seq) if min_val <= x <= max_val]
    
    if len(candidates) < 2:
        return seq.copy()

    sorted_candidates = sorted(candidates, key=lambda pair: pair[1])
    candidate_values = [val for _, val in sorted_candidates]
    
    differences = [candidate_values[i+1] - candidate_values[i] for i in range(len(candidate_values)-1)]
    
    def median(lst):
        
        n = len(lst)
        sorted_lst = sorted(lst)
        mid = n // 2
        
        if n % 2 == 0:
            return (sorted_lst[mid - 1] + sorted_lst[mid]) / 2.0
            
        else:
            return sorted_lst[mid]
    
    med_diff = median(differences)

    split_indices = [i for i, diff in enumerate(differences) if diff > splitting_factor * med_diff]
    
    clusters = []
    
    if split_indices:
        start = 0
        for split_index in split_indices:
            clusters.append(sorted_candidates[start:split_index+1])
            start = split_index + 1
        clusters.append(sorted_candidates[start:])
        
    else:
        clusters = [sorted_candidates]
    

    valid_clusters = [cluster for cluster in clusters if len(cluster) >= 2]
    if not valid_clusters:
        return seq.copy()

    def cluster_spread(cluster):
        values = [val for (_, val) in cluster]
        return max(values) - min(values)
    
    valid_clusters.sort(key=lambda cluster: (len(cluster), -cluster_spread(cluster)), reverse=True)
    selected_cluster = valid_clusters[0]

    allowed_range_width = max_val - min_val
    spread = cluster_spread(selected_cluster)
    ratio = spread / allowed_range_width
    
    if ratio > tightness_threshold:
        return seq.copy()

    cluster_values = [val for (_, val) in selected_cluster]
    equal_value = sum(cluster_values) // len(cluster_values)
    

    result = list(seq)
    for idx, _ in selected_cluster:
        result[idx] = equal_value
    
    return result

###################################################################################

def chunk_list(lst, chunk_size):
    return [lst[i:i + chunk_size] for i in range(0, len(lst), chunk_size)]

###################################################################################

def compress_tokens_sequence(seq, 
                             min_val=128, 
                             max_val=256, 
                             group_size=2, 
                             splitting_factor=1.5, 
                             tightness_threshold=0.15
                            ):
    
    comp_seq = equalize_closest_elements_dynamic(seq, 
                                                 min_val, 
                                                 max_val, 
                                                 splitting_factor=splitting_factor, 
                                                 tightness_threshold=tightness_threshold
                                                 )

    seq_split = sorted(chunk_list(comp_seq, group_size), key=lambda x: (-x[0], -x[1]))

    seq_grouped = [[[k]] + [vv[1:] for vv in v] for k, v in groupby(seq_split, key=lambda x: x[0])]

    return flatten(flatten(sorted(seq_grouped, key=lambda x: -x[1][0])))

###################################################################################

def merge_adjacent_pairs(values_counts):
   
    merged = []
    i = 0
    
    while i < len(values_counts):

        if i < len(values_counts) - 1:
            value1, count1 = values_counts[i]
            value2, count2 = values_counts[i + 1]
            
            if value2 - value1 == 1:
                if count2 > count1:
                    merged_value = value2
                    
                else:
                    merged_value = value1

                merged_count = count1 + count2
                merged.append((merged_value, merged_count))

                i += 2
                
                continue

        merged.append(values_counts[i])
        
        i += 1
        
    return merged

###################################################################################

def merge_escore_notes_start_times(escore_notes, num_merges=1):

    new_dscore = delta_score_notes(escore_notes)

    times = [e[1] for e in new_dscore if e[1] != 0]
    times_counts = sorted(Counter(times).most_common())

    prev_counts = []
    new_times_counts = times_counts
    
    mcount = 0
    
    while prev_counts != new_times_counts:
        prev_counts = new_times_counts
        new_times_counts = merge_adjacent_pairs(new_times_counts)
        
        mcount += 1

        if mcount == num_merges:
            break

    gtimes = [r[0] for r in new_times_counts]

    for e in new_dscore:
        if e[1] > 0:
            e[1] = find_closest_value(gtimes, e[1])[0]
            e[2] -= num_merges

    return delta_score_to_abs_score(new_dscore)

###################################################################################

def multi_instrumental_escore_notes_tokenized(escore_notes, compress_seq=False):

    melody_chords = []

    pe = escore_notes[0]
    
    for i, e in enumerate(escore_notes):
    
        dtime = max(0, min(255, e[1]-pe[1]))
        
        dur = max(0, min(255, e[2]))
        
        cha = max(0, min(15, e[3]))
    
        if cha == 9:
          pat = 128
        
        else:
          pat = max(0, min(127, e[6]))
        
        ptc = max(0, min(127, e[4]))
        
        vel = max(8, min(127, e[5]))
        velocity = round(vel / 15)-1
        
        dur_vel = (8 * dur) + velocity
        pat_ptc = (129 * pat) + ptc

        if compress_seq:
            if dtime != 0 or i == 0:
                melody_chords.extend([dtime, dur_vel+256, pat_ptc+2304])

            else:
                melody_chords.extend([dur_vel+256, pat_ptc+2304])

        else:
            melody_chords.extend([dtime, dur_vel+256, pat_ptc+2304])
        
        pe = e

    return melody_chords

###################################################################################

def merge_counts(data, return_lists=True):
    
    merged = defaultdict(int)
    
    for value, count in data:
        merged[value] += count

    if return_lists:
        return [[k, v] for k, v in merged.items()]

    else:
        return list(merged.items())
    
###################################################################################

def convert_escore_notes_pitches_chords_signature(signature, convert_to_full_chords=True):

    if convert_to_full_chords:
        SRC_CHORDS = ALL_CHORDS_SORTED
        TRG_CHORDS = ALL_CHORDS_FULL

    else:
        SRC_CHORDS = ALL_CHORDS_FULL
        TRG_CHORDS = ALL_CHORDS_SORTED

    cdiff = len(TRG_CHORDS) - len(SRC_CHORDS)

    pitches_counts = [c for c in signature if -1 < c[0] < 128]
    chords_counts = [c for c in signature if 127 < c[0] < len(SRC_CHORDS)+128]
    drums_counts = [[c[0]+cdiff, c[1]] for c in signature if len(SRC_CHORDS)+127 < c[0] < len(SRC_CHORDS)+256]
    bad_chords_count = [c for c in signature if c[0] == -1]

    new_chords_counts = []
    
    for c in chords_counts:
        tones_chord = SRC_CHORDS[c[0]-128]

        if tones_chord not in TRG_CHORDS:
            tones_chord = check_and_fix_tones_chord(tones_chord, use_full_chords=convert_to_full_chords)
            bad_chords_count[0][1] += 1
            
        new_chords_counts.append([TRG_CHORDS.index(tones_chord)+128, c[1]])

    return pitches_counts + merge_counts(new_chords_counts) + drums_counts + bad_chords_count

###################################################################################

def convert_bytes_in_nested_list(lst, 
                                 encoding='utf-8', 
                                 errors='ignore',
                                 return_changed_events_count=False
                                ):
    
    new_list = []

    ce_count = 0
    
    for item in lst:
        if isinstance(item, list):
            new_list.append(convert_bytes_in_nested_list(item))
            
        elif isinstance(item, bytes):
            new_list.append(item.decode(encoding, errors=errors))
            ce_count += 1
            
        else:
            new_list.append(item)
            
    if return_changed_events_count:       
        return new_list, ce_count

    else:
        return new_list

###################################################################################

def mult_pitches(pitches, min_oct=4, max_oct=6):
    
    tones_chord = sorted(set([p % 12 for p in pitches]))

    mult_ptcs = []

    for t in tones_chord:
        for i in range(min_oct, max_oct):
            mult_ptcs.append((i*12)+t)

    return mult_ptcs

###################################################################################

def find_next(pitches, cur_ptc):

    i = 0

    for i, p in enumerate(pitches):
        if p != cur_ptc:
            break

    return i

###################################################################################

def ordered_groups_unsorted(data, key_index):
   
    def keyfunc(sublist):
        return sublist[key_index]
    
    groups = []
    
    for key, group in groupby(data, key=keyfunc):
        groups.append((key, list(group)))
        
    return groups

###################################################################################

def ordered_groups(data, ptc_idx, pat_idx):
    
    groups = OrderedDict()
    
    for sublist in data:
        key = tuple([sublist[ptc_idx], sublist[pat_idx]])
        
        if key not in groups:
            groups[key] = []
            
        groups[key].append(sublist)
    
    return list(groups.items())

###################################################################################

def merge_melody_notes(escore_notes, pitches_idx=4, max_dur=255, last_dur=128):

    groups = ordered_groups_unsorted(escore_notes, pitches_idx)

    merged_melody_notes = []

    for i, (k, g) in enumerate(groups[:-1]):
        
        if len(g) == 1:
            merged_melody_notes.extend(g)

        else:
            dur = min(max_dur, groups[i+1][1][0][1] - g[0][1])
            
            merged_melody_notes.append(['note',
                                        g[0][1],
                                        dur,
                                        g[0][3],
                                        g[0][4],
                                        g[0][5],
                                        g[0][6]
                                       ])
 
    merged_melody_notes.append(['note',
                                groups[-1][1][0][1],
                                last_dur,
                                groups[-1][1][0][3],
                                groups[-1][1][0][4],
                                groups[-1][1][0][5],
                                groups[-1][1][0][6]
                               ])
            
    return merged_melody_notes

###################################################################################

def add_expressive_melody_to_enhanced_score_notes(escore_notes,
                                                  melody_start_chord=0,
                                                  melody_prime_pitch=60,
                                                  melody_step=1,
                                                  melody_channel=3,
                                                  melody_patch=40,
                                                  melody_notes_max_duration=255,
                                                  melody_last_note_dur=128,
                                                  melody_clip_max_min_durs=[],
                                                  melody_max_velocity=120,
                                                  acc_max_velocity=90,
                                                  return_melody=False
                                                  ):


    score = copy.deepcopy(escore_notes)

    adjust_score_velocities(score, acc_max_velocity)

    cscore = chordify_score([1000, score])

    melody_pitches = [melody_prime_pitch]
    
    for i, c in enumerate(cscore[melody_start_chord:]):
        
        if i % melody_step == 0:
        
            pitches = [e[4] for e in c if e[3] != 9]
        
            if pitches:
                cptc = find_closest_value(mult_pitches(pitches), melody_pitches[-1])[0]
                melody_pitches.append(cptc)
    
    song_f = []
    mel_f = []
    
    idx = 1
    
    for i, c in enumerate(cscore[:-melody_step]):
        pitches = [e[4] for e in c if e[3] != 9]
    
        if pitches and i >= melody_start_chord and i % melody_step == 0:
            dur = min(cscore[i+melody_step][0][1] - c[0][1], melody_notes_max_duration)
            
            mel_f.append(['note', 
                          c[0][1], 
                          dur, 
                          melody_channel, 
                          60+(melody_pitches[idx] % 24), 
                          100 + ((melody_pitches[idx] % 12) * 2), 
                          melody_patch
                         ])
            idx += 1
            
        song_f.extend(c)
        
    song_f.extend(flatten(cscore[-melody_step:]))
    
    if len(melody_clip_max_min_durs) == 2:
        for e in mel_f:
            if e[2] >= melody_clip_max_min_durs[0]:
                e[2] = melody_clip_max_min_durs[1]

    adjust_score_velocities(mel_f, melody_max_velocity)
    
    merged_melody_notes = merge_melody_notes(mel_f,
                                             max_dur=melody_notes_max_duration,
                                             last_dur=melody_last_note_dur
                                             )

    song_f = sorted(merged_melody_notes + song_f,
                    key=lambda x: x[1]
                   )

    if return_melody:
        return mel_f

    else:
        return song_f

###################################################################################
    
def list_md5_hash(ints_list):
    
    arr = array('H', ints_list)
    binary_data = arr.tobytes()
    
    return hashlib.md5(binary_data).hexdigest()

###################################################################################

def fix_escore_notes_durations(escore_notes,
                               min_notes_gap=1,
                               min_notes_dur=1,
                               times_idx=1,
                               durs_idx=2,
                               channels_idx = 3, 
                               pitches_idx=4,
                               patches_idx=6
                              ):

    notes = [e for e in escore_notes if e[channels_idx] != 9]
    drums = [e for e in escore_notes if e[channels_idx] == 9]
    
    escore_groups = ordered_groups(notes, pitches_idx, patches_idx)

    merged_score = []

    for k, g in escore_groups:
        if len(g) > 2:
            fg = fix_monophonic_score_durations(g, 
                                                min_notes_gap=min_notes_gap, 
                                                min_notes_dur=min_notes_dur
                                               )
            merged_score.extend(fg)

        elif len(g) == 2:

            if g[0][times_idx]+g[0][durs_idx] >= g[1][times_idx]:
                g[0][durs_idx] = max(1, g[1][times_idx] - g[0][times_idx] - min_notes_gap)
                
            merged_score.extend(g)

        else:
            merged_score.extend(g)

    return sorted(merged_score + drums, key=lambda x: x[times_idx])

###################################################################################

def create_nested_chords_tree(chords_list):
    
    tree = {}
    
    for chord in chords_list:
        
        node = tree
        
        for semitone in chord:
            if semitone not in node:
                node[semitone] = {}
                
            node = node[semitone]
            
        node.setdefault(-1, []).append(chord)
        
    return tree

###################################################################################

def get_chords_with_prefix(nested_chords_tree, prefix):
   
    node = nested_chords_tree
    
    for semitone in prefix:
        if semitone in node:
            node = node[semitone]
            
        else:
            return []

    collected_chords = []
    
    def recursive_collect(subnode):
        if -1 in subnode:
            collected_chords.extend(subnode[-1])
            
        for key, child in subnode.items():
            if key != -1:
                recursive_collect(child)
                
    recursive_collect(node)
    
    return collected_chords

###################################################################################

def get_chords_by_semitones(chords_list, chord_semitones):

    query_set = set(chord_semitones)
    results = []

    for chord in chords_list:
        
        chord_set = set(chord)
        
        if query_set.issubset(chord_set):
            results.append(sorted(set(chord)))
            
    return results

###################################################################################

def remove_duplicate_pitches_from_escore_notes(escore_notes, 
                                               pitches_idx=4, 
                                               patches_idx=6, 
                                               return_dupes_count=False
                                              ):
    
    cscore = chordify_score([1000, escore_notes])

    new_escore = []

    bp_count = 0

    for c in cscore:
        
        cho = []
        seen = []

        for cc in c:
            if [cc[pitches_idx], cc[patches_idx]] not in seen:
                cho.append(cc)
                seen.append([cc[pitches_idx], cc[patches_idx]])

            else:
                bp_count += 1

        new_escore.extend(cho)
        
    if return_dupes_count:
        return bp_count
        
    else:
        return new_escore

###################################################################################
    
def chunks_shuffle(lst,
                   min_len=1,
                   max_len=3,
                   seed=None
                   ):
    
    rnd = random.Random(seed)
    chunks = []
    i, n = 0, len(lst)

    while i < n:
        size = rnd.randint(min_len, max_len)
        size = min(size, n - i)
        chunks.append(lst[i : i + size])
        i += size

    rnd.shuffle(chunks)

    flattened = []
    for chunk in chunks:
        flattened.extend(chunk)

    return flattened

###################################################################################
    
def find_deepest_midi_dirs(roots,
                           marker_file="midi_score.mid",
                           suffixes=None,
                           randomize=False,
                           seed=None,
                           verbose=False
                          ):
    
    try:
        iter(roots)
        if isinstance(roots, (str, Path)):
            root_list = [roots]
        else:
            root_list = list(roots)
            
    except TypeError:
        root_list = [roots]

    if isinstance(marker_file, (list, tuple)):
        patterns = [p.lower() for p in marker_file if p]
        
    else:
        patterns = [marker_file.lower()] if marker_file else []

    allowed = {s.lower() for s in (suffixes or ['.mid', '.midi', '.kar'])}

    if verbose:
        print("Settings:")
        print("  Roots:", [str(r) for r in root_list])
        print("  Marker patterns:", patterns or "<no marker filter>")
        print("  Allowed suffixes:", allowed)
        print(f"  Randomize={randomize}, Seed={seed}")

    results = defaultdict(list)
    rng = random.Random(seed)

    for root in root_list:

        root_path = Path(root)
        
        if not root_path.is_dir():
            print(f"Warning: '{root_path}' is not a valid directory, skipping.")
            continue

        if verbose:
            print(f"\nScanning root: {str(root_path)}")

        all_dirs = list(root_path.rglob("*"))
        dirs_iter = tqdm.tqdm(all_dirs, desc=f"Dirs in {root_path.name}", disable=not verbose)

        for dirpath in dirs_iter:
            if not dirpath.is_dir():
                continue

            children = list(dirpath.iterdir())
            if any(child.is_dir() for child in children):
                if verbose:
                    print(f"Skipping non-leaf: {str(dirpath)}")
                continue

            files = [f for f in children if f.is_file()]
            names = [f.name.lower() for f in files]

            if patterns:
                matched = any(fnmatch(name, pat) for name in names for pat in patterns)
                if not matched:
                    if verbose:
                        print(f"No marker in: {str(dirpath)}")
                    continue
                    
                if verbose:
                    print(f"Marker found in: {str(dirpath)}")
                    
            else:
                if verbose:
                    print(f"Including leaf (no marker): {str(dirpath)}")

            for f in files:
                if f.suffix.lower() in allowed:
                    results[str(dirpath)].append(str(f))
                    
                    if verbose:
                        print(f"  Collected: {f.name}")

    all_leaves = list(results.keys())
    if randomize:
        if verbose:
            print("\nShuffling leaf directories")
            
        rng.shuffle(all_leaves)
        
    else:
        all_leaves.sort()

    final_dict = {}
    
    for leaf in all_leaves:
        file_list = results[leaf][:]
        if randomize:
            if verbose:
                print(f"Shuffling files in: {leaf}")
                
            rng.shuffle(file_list)
            
        else:
            file_list.sort()
            
        final_dict[leaf] = file_list

    if verbose:
        print("\nScan complete. Found directories:")
        for d, fl in final_dict.items():
            print(f"  {d} -> {len(fl)} files")

    return final_dict

###################################################################################

PERCUSSION_GROUPS = {
    
    1: {  # Bass Drums
        35: 'Acoustic Bass Drum',
        36: 'Bass Drum 1',
    },
    2: {  # Stick
        37: 'Side Stick',
    },
    3: {  # Snares
        38: 'Acoustic Snare',
        40: 'Electric Snare',
    },
    4: {  # Claps
        39: 'Hand Clap',
    },
    5: {  # Floor Toms
        41: 'Low Floor Tom',
        43: 'High Floor Tom',
    },
    6: {  # Hi-Hats
        42: 'Closed Hi-Hat',
        44: 'Pedal Hi-Hat',
        46: 'Open Hi-Hat',
    },
    7: {  # Toms
        45: 'Low Tom',
        47: 'Low-Mid Tom',
        48: 'Hi-Mid Tom',
        50: 'High Tom',
    },
    8: {  # Cymbals
        49: 'Crash Cymbal 1',
        51: 'Ride Cymbal 1',
        52: 'Chinese Cymbal',
        55: 'Splash Cymbal',
        57: 'Crash Cymbal 2',
        59: 'Ride Cymbal 2',
    },
    9: {  # Bells
        53: 'Ride Bell',
    },
    10: {  # Tambourine
        54: 'Tambourine',
    },
    11: {  # Cowbell
        56: 'Cowbell',
    },
    12: {  # Vibraslap
        58: 'Vibraslap',
    },
    13: {  # Bongos
        60: 'Hi Bongo',
        61: 'Low Bongo',
    },
    14: {  # Congas
        62: 'Mute Hi Conga',
        63: 'Open Hi Conga',
        64: 'Low Conga',
    },
    15: {  # Timbales
        65: 'High Timbale',
        66: 'Low Timbale',
    },
    16: {  # Agogô
        67: 'High Agogo',
        68: 'Low Agogo',
    },
    17: {  # Cabasa
        69: 'Cabasa',
    },
    18: {  # Maracas
        70: 'Maracas',
    },
    19: {  # Whistles
        71: 'Short Whistle',
        72: 'Long Whistle',
    },
    20: {  # Guiros
        73: 'Short Guiro',
        74: 'Long Guiro',
    },
    21: {  # Claves
        75: 'Claves',
    },
    22: {  # Wood Blocks
        76: 'Hi Wood Block',
        77: 'Low Wood Block',
    },
    23: {  # Cuica
        78: 'Mute Cuica',
        79: 'Open Cuica',
    },
    24: {  # Triangles
        80: 'Mute Triangle',
        81: 'Open Triangle',
    },
}

###################################################################################

print('Module loaded!')
print('=' * 70)
print('Enjoy! :)')
print('=' * 70)

###################################################################################
# This is the end of the TMIDI X Python module
###################################################################################