util.py

#!/usr/bin/env python
# coding: utf-8

# In[ ]:


import os
import sys
from random import randint
import random
import time
import uuid
from datetime import datetime
import math
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import logging
import logging.handlers
import pickle
from contextlib import contextmanager

tokens = ["0","1","2","3","4","5","6","7","8","9","A","B","C","D","E","F","G","H","I","J","K","L","M",
    "N","O","P","Q","R","S","T","U","V","W","X","Y","Z","0","1","2","3","4","5","6","7","8","9"]
numTokens = tokens[:10]
alphaTokens = tokens[10:36]
loCaseChars = ["a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k","l","m","n","o",
"p","q","r","s","t","u","v","w","x","y","z"]

typeInt = "int"
typeFloat = "float"
typeString = "string"

secInMinute = 60
secInHour = 60 * 60
secInDay = 24 * secInHour
secInWeek = 7 * secInDay
secInYear = 365 * secInDay
secInMonth = secInYear / 12

minInHour = 60
minInDay = 24 * minInHour

ftPerYard = 3
ftPerMile = ftPerYard * 1760


def genID(size):
    """
    generates ID

    Parameters
        size : size of ID
    """
    id = ""
    for i in range(size):
        id = id + selectRandomFromList(tokens)
    return id

def genIdList(numId, idSize):
    """
    generate list of IDs

    Parameters:
        numId: number of Ids
        idSize: ID size
    """
    iDs = []
    for i in range(numId):
        iDs.append(genID(idSize))
    return iDs

def genNumID(size):
    """
    generates ID consisting of digits onl

    Parameters
        size : size of ID
    """
    id = ""
    for i in range(size):
        id = id + selectRandomFromList(numTokens)
    return id

def genLowCaseID(size):
    """
    generates ID consisting of lower case chars

    Parameters
        size : size of ID
    """
    id = ""
    for i in range(size):
        id = id + selectRandomFromList(loCaseChars)
    return id

def genNumIdList(numId, idSize):
    """
    generate list of numeric IDs

    Parameters:
        numId: number of Ids
        idSize: ID size
    """
    iDs = []
    for i in range(numId):
        iDs.append(genNumID(idSize))
    return iDs

def genNameInitial():
    """
    generate name initial
    """
    return selectRandomFromList(alphaTokens) + selectRandomFromList(alphaTokens)

def genPhoneNum(arCode):
    """
    generates phone number

    Parameters
        arCode: area code
    """
    phNum = genNumID(7)
    return arCode + str(phNum)

def selectRandomFromList(ldata):
    """
    select an element randomly from a lis

    Parameters
        ldata : list data
    """
    return ldata[randint(0, len(ldata)-1)]

def selectOtherRandomFromList(ldata, cval):
    """
    select an element randomly from a list excluding the given one

    Parameters
        ldata : list data
        cval : value to be excluded
    """
    nval = selectRandomFromList(ldata)
    while nval == cval:
        nval = selectRandomFromList(ldata)
    return nval

def selectRandomSubListFromList(ldata, num):
    """
    generates random sublist from a list without replacemment

    Parameters
        ldata : list data
        num : output list size
    """
    assertLesser(num, len(ldata), "size of sublist to be sampled greater than or equal to main list")
    i = randint(0, len(ldata)-1)
    sel = ldata[i]
    selSet = {i}
    selList = [sel]
    while (len(selSet) < num):
        i = randint(0, len(ldata)-1)
        if (i not in selSet):
            sel = ldata[i]
            selSet.add(i)
            selList.append(sel)
    return selList

def selectRandomSubListFromListWithRepl(ldata, num):
    """
    generates random sublist from a list with replacemment

    Parameters
        ldata : list data
        num : output list size
    """
    return list(map(lambda i : selectRandomFromList(ldata), range(num)))

def selectRandomFromDict(ddata):
    """
    select an element randomly from a dictionary

    Parameters
        ddata : dictionary data
    """
    dkeys = list(ddata.keys())
    dk = selectRandomFromList(dkeys)
    el = (dk, ddata[dk])
    return el

def setListRandomFromList(ldata, ldataRepl):
    """
    sets some elents in the first list randomly with elements from the second list

    Parameters
        ldata : list data
        ldataRepl : list with replacement data
    """
    l = len(ldata)
    selSet = set()
    for d in ldataRepl:
        i = randint(0, l-1)
        while i in selSet:
            i = randint(0, l-1)
        ldata[i] = d
        selSet.add(i)

def genIpAddress():
    """
    generates IP address
    """
    i1 = randint(0,256)
    i2 = randint(0,256)
    i3 = randint(0,256)
    i4 = randint(0,256)
    ip = "%d.%d.%d.%d" %(i1,i2,i3,i4)
    return ip

def curTimeMs():
    """
    current time in ms
    """
    return int((datetime.utcnow() - datetime(1970,1,1)).total_seconds() * 1000)

def secDegPolyFit(x1, y1, x2, y2, x3, y3):
    """
    second deg polynomial 	

    Parameters
        x1 : 1st point x
        y1 : 1st point y
        x2 : 2nd point x
        y2 : 2nd point y
        x3 : 3rd point x
        y3 : 3rd point y
    """
    t = (y1 - y2) / (x1 - x2)
    a = t - (y2 - y3) / (x2 - x3)
    a = a / (x1 - x3)
    b = t - a * (x1 + x2)
    c = y1 - a * x1 * x1 - b * x1
    return (a, b, c)

def range_limit(val, minv, maxv):
    """
    range limit a value

    Parameters
        val : data value
        minv : minimum
        maxv : maximum
    """
    if (val < minv):
        val = minv
    elif (val > maxv):
        val = maxv
    return val

def isInRange(val, minv, maxv):
    """
    checks if within range

    Parameters
        val : data value
        minv : minimum
        maxv : maximum
    """
    return val >= minv and val <= maxv

def stripFileLines(filePath, offset):
    """
    strips number of chars from both ends

    Parameters
        filePath : file path
        offset : offset from both ends of  line 
    """
    fp = open(filePath, "r")
    for line in fp:
        stripped = line[offset:len(line) - 1 - offset]
        print (stripped)
    fp.close()

def genLatLong(lat1, long1, lat2, long2):
    """
    generate lat log within limits

    Parameters
        lat1 : lat of 1st point
        long1 : long of 1st point
        lat2 : lat of 2nd point
        long2 : long of 2nd point
    """
    lat = lat1 + (lat2 - lat1) * random.random()
    longg = long1 + (long2 - long1) * random.random()
    return (lat, longg)

def geoDistance(lat1, long1, lat2, long2):
    """
    find geo distance in ft

    Parameters
        lat1 : lat of 1st point
        long1 : long of 1st point
        lat2 : lat of 2nd point
        long2 : long of 2nd point
    """
    latDiff = math.radians(lat1 - lat2)
    longDiff = math.radians(long1 - long2)
    l1 = math.sin(latDiff/2.0)
    l2 = math.sin(longDiff/2.0)
    l3 = math.cos(math.radians(lat1))
    l4 = math.cos(math.radians(lat2))
    a = l1 * l1 + l3 * l4 * l2 * l2
    l5 = math.sqrt(a)
    l6 = math.sqrt(1.0 - a)
    c = 2.0 * math.atan2(l5, l6)
    r = 6371008.8 * 3.280840
    return c * r

def minLimit(val, limit):
    """
    min limit
    Parameters
    """
    if (val < limit):
        val = limit
    return val;

def maxLimit(val, limit):
    """
    max limit
    Parameters
    """
    if (val > limit):
        val = limit
    return val;

def rangeSample(val, minLim, maxLim):
    """
    if out side range sample within range

    Parameters
        val : value
        minLim : minimum
        maxLim : maximum
    """
    if val < minLim or val > maxLim:
        val = randint(minLim, maxLim)
    return val

def genRandomIntListWithinRange(size, minLim, maxLim):
    """
    random unique list of integers within range

    Parameters
        size : size of returned list
        minLim : minimum
        maxLim : maximum
    """
    values = set()
    for i in range(size):
        val = randint(minLim, maxLim)
        while val not in values:
            values.add(val)
    return list(values)

def preturbScalar(value, vrange):
    """
    preturbs a mutiplicative value within range

    Parameters
        value : data value
        vrange : value delta  fraction
    """
    scale = 1.0 - vrange + 2 * vrange * random.random() 
    return value * scale

def preturbScalarAbs(value, vrange):
    """
    preturbs an absolute value within range

    Parameters
        value : data value
        vrange : value delta  absolute
    """
    delta = - vrange + 2.0 * vrange * random.random() 
    return value + delta

def preturbVector(values, vrange):
    """
    preturbs a list within range

    Parameters
        values : list data
        vrange : value delta  fraction
    """
    nValues = list(map(lambda va: preturbScalar(va, vrange), values))
    return nValues

def randomShiftVector(values, smin, smax):
    """
    shifts  a list by a random quanity with a range

    Parameters
        values : list data
        smin : samplinf minimum
        smax : sampling maximum
    """
    shift = np.random.uniform(smin, smax)
    return list(map(lambda va: va + shift, values))

def floatRange(beg, end, incr):
    """
    generates float range

    Parameters
        beg :range begin
        end: range end
        incr : range increment
    """
    return list(np.arange(beg, end, incr))

def shuffle(values, *numShuffles):
    """
    in place shuffling with swap of pairs

    Parameters
        values : list data
        numShuffles : parameter list for number of shuffles
    """
    size = len(values)
    if len(numShuffles) == 0:
        numShuffle = int(size / 2)
    elif len(numShuffles) == 1:
        numShuffle = numShuffles[0]
    else:
        numShuffle = randint(numShuffles[0], numShuffles[1])
    print("numShuffle {}".format(numShuffle))
    for i in range(numShuffle):
        first = random.randint(0, size - 1)
        second = random.randint(0, size - 1)
        while first == second:
            second = random.randint(0, size - 1)
        tmp = values[first]
        values[first] = values[second]
        values[second] = tmp


def splitList(itms, numGr):
    """
    splits a list into sub lists of approximately equal size, with items in sublists randomly chod=sen

    Parameters
        itms ; list of values		
        numGr : no of groups
    """
    tcount = len(itms)
    cItems = list(itms)
    sz = int(len(cItems) / numGr)
    groups = list()
    count = 0
    for i in range(numGr):
        if (i == numGr - 1):
            csz = tcount - count
        else:
            csz = sz + randint(-2, 2)
            count += csz
        gr = list()
        for  j in range(csz):
            it = selectRandomFromList(cItems)
            gr.append(it)
            cItems.remove(it)
        groups.append(gr)
    return groups

def multVector(values, vrange):
    """
    multiplies a list within value  range

    Parameters
        values : list of values
        vrange : fraction of vaue to be used to update
    """
    scale = 1.0 - vrange + 2 * vrange * random.random()
    nValues = list(map(lambda va: va * scale, values))
    return nValues

def weightedAverage(values, weights):
    """
    calculates weighted average

    Parameters
        values : list of values
        weights : list of weights
    """		
    assert len(values) == len(weights), "values and weights should be same size"
    vw = zip(values, weights)
    wva = list(map(lambda e : e[0] * e[1], vw))
    #wa = sum(x * y for x, y in vw) / sum(weights)
    wav = sum(wva) / sum(weights)
    return wav

def extractFields(line, delim, keepIndices):
    """
    breaks a line into fields and keeps only specified fileds and returns new line

    Parameters
        line ; deli separated string
        delim : delemeter
        keepIndices : list of indexes to fields to be retained
    """
    items = line.split(delim)
    newLine = []
    for i in keepIndices:
        newLine.append(line[i])
    return delim.join(newLine)

def remFields(line, delim, remIndices):
    """
    removes fields from delim separated string

    Parameters
        line ; delemeter separated string
        delim : delemeter
        remIndices : list of indexes to fields to be removed
    """
    items = line.split(delim)
    newLine = []
    for i in range(len(items)):
        if not arrayContains(remIndices, i):
            newLine.append(line[i])
    return delim.join(newLine)

def extractList(data, indices):
    """
    extracts list from another list, given indices

    Parameters
        remIndices : list data
        indices : list of indexes to fields to be retained
    """
    if areAllFieldsIncluded(data, indices):
        exList = data.copy()
        #print("all indices")
    else:
        exList = list()
        le = len(data)
        for i in indices:
            assert i < le , "index {} out of bound {}".format(i, le)
            exList.append(data[i])

    return exList

def arrayContains(arr, item):
    """
    checks if array contains an item 

    Parameters
        arr : list data
        item : item to search
    """
    contains = True
    try:
        arr.index(item)
    except ValueError:
        contains = False
    return contains

def strToIntArray(line, delim=","):
    """
    int array from delim separated string

    Parameters
        line ; delemeter separated string
    """
    arr = line.split(delim)
    return [int(a) for a in arr]

def strToFloatArray(line, delim=","):
    """
    float array from delim separated string

    Parameters
        line ; delemeter separated string
    """
    arr = line.split(delim)
    return [float(a) for a in arr]

def strListOrRangeToIntArray(line):
    """
    int array from delim separated string or range

    Parameters
        line ; delemeter separated string
    """
    varr = line.split(",")
    if (len(varr) > 1):
        iarr =  list(map(lambda v: int(v), varr))
    else:
        vrange = line.split(":")
        if (len(vrange) == 2):
            lo = int(vrange[0])
            hi = int(vrange[1])
            iarr = list(range(lo, hi+1))
        else:
            iarr = [int(line)]
    return iarr

def toStr(val, precision):
    """
    converts any type to string	

    Parameters
        val : value
        precision ; precision for float value
    """
    if type(val) == float or type(val) == np.float64 or type(val) == np.float32:
        format = "%" + ".%df" %(precision)
        sVal = format %(val)
    else:
        sVal = str(val)
    return sVal

def toStrFromList(values, precision, delim=","):
    """
    converts list of any type to delim separated string

    Parameters
        values : list data
        precision ; precision for float value
        delim : delemeter
    """
    sValues = list(map(lambda v: toStr(v, precision), values))
    return delim.join(sValues)

def toIntList(values):
    """
    convert to int list

    Parameters
        values : list data
    """
    return list(map(lambda va: int(va), values))

def toFloatList(values):
    """
    convert to float list

    Parameters
        values : list data
    """
    return list(map(lambda va: float(va), values))

def toStrList(values, precision=None):
    """
    convert to string list

    Parameters
        values : list data
        precision ; precision for float value
    """
    return list(map(lambda va: toStr(va, precision), values))

def toIntFromBoolean(value):
    """
    convert to int

    Parameters
        value : boolean value
    """
    ival = 1 if value else 0
    return ival

def typedValue(val, dtype=None):
    """
    return typed value given string, discovers data type if not specified

    Parameters
        val : value
        dtype : data type
    """
    tVal = None

    if dtype is not None:
        if dtype == "num":
            dtype = "int" if dtype.find(".") == -1 else "float"

        if dtype == "int":
            tVal = int(val)
        elif dtype == "float":
            tVal = float(val)
        elif dtype == "bool":
            tVal = bool(val)
        else:
            tVal = val
    else:
        if type(val) == str:
            lVal = val.lower()

            #int
            done = True
            try:
                tVal = int(val)
            except ValueError:
                done = False

            #float
            if not done:
                done = True
                try:
                    tVal = float(val)
                except ValueError:
                    done = False

            #boolean
            if not done:
                done = True
                if lVal == "true":
                    tVal = True
                elif lVal == "false":
                    tVal = False
                else:
                    done = False
            #None		
            if not done:
                if lVal == "none":
                    tVal = None
                else:
                    tVal = val
        else:
            tVal = val

    return tVal

def getAllFiles(dirPath):
    """
    get all files recursively

    Parameters
        dirPath : directory path
    """
    filePaths = []
    for (thisDir, subDirs, fileNames) in os.walk(dirPath):
        for fileName in fileNames:
            filePaths.append(os.path.join(thisDir, fileName))
    filePaths.sort()
    return filePaths

def getFileContent(fpath, verbose=False):
    """
    get file contents in directory

    Parameters
        fpath ; directory path
        verbose : verbosity flag
    """
    # dcument list
    docComplete  = []
    filePaths = getAllFiles(fpath)

    # read files
    for filePath in filePaths:
        if verbose:
            print("next file " + filePath)
        with open(filePath, 'r') as contentFile:
            content = contentFile.read()
            docComplete.append(content)
    return (docComplete, filePaths)

def getOneFileContent(fpath):
    """
    get one file contents

    Parameters
        fpath : file path
    """
    with open(fpath, 'r') as contentFile:
        docStr = contentFile.read()
    return docStr

def getFileLines(dirPath, delim=","):
    """
    get lines from a file

    Parameters
        dirPath : file path
        delim : delemeter
    """
    lines = list()
    for li in fileRecGen(dirPath, delim):
        lines.append(li)
    return lines

def getFileSampleLines(dirPath, percen, delim=","):
    """
    get sampled lines from a file

    Parameters
        dirPath : file path
        percen : sampling percentage
        delim : delemeter
    """
    lines = list()
    for li in fileRecGen(dirPath, delim):
        if randint(0, 100) < percen:
            lines.append(li)
    return lines

def getFileColumnAsString(dirPath, index, delim=","):
    """
    get string column from a file

    Parameters
        dirPath : file path
        index : index
        delim : delemeter
    """
    fields = list()
    for rec in fileRecGen(dirPath, delim):
        fields.append(rec[index])
    #print(fields)	
    return fields

def getFileColumnsAsString(dirPath, indexes, delim=","):
    """
    get multiple string columns from a file

    Parameters
        dirPath : file path
        indexes : indexes of columns
        delim : delemeter
    """
    nindex = len(indexes)
    columns = list(map(lambda i : list(), range(nindex)))
    for rec in fileRecGen(dirPath, delim):
        for i in range(nindex):
            columns[i].append(rec[indexes[i]])
    return columns

def getFileColumnAsFloat(dirPath, index, delim=","):
    """
    get float fileds from a file

    Parameters
        dirPath : file path
        index : index
        delim : delemeter
    """
    #print("{}  {}".format(dirPath, index))
    fields = getFileColumnAsString(dirPath, index, delim)
    return list(map(lambda v:float(v), fields))

def getFileColumnAsInt(dirPath, index, delim=","):
    """
    get float fileds from a file

    Parameters
        dirPath : file path
        index : index
        delim : delemeter
    """
    fields = getFileColumnAsString(dirPath, index, delim)
    return list(map(lambda v:int(v), fields))

def getFileAsIntMatrix(dirPath, columns, delim=","):
    """
    extracts int matrix from csv file given column indices with each row being  concatenation of 
    extracted column values row size = num of columns

    Parameters
        dirPath : file path
        columns : indexes of columns
        delim : delemeter
    """
    mat = list()
    for rec in  fileSelFieldsRecGen(dirPath, columns, delim):
        mat.append(asIntList(rec))
    return mat

def getFileAsFloatMatrix(dirPath, columns, delim=","):
    """
    extracts float matrix from csv file given column indices with each row being concatenation of  
    extracted column values row size = num of columns
    Parameters
        dirPath : file path
        columns : indexes of columns
        delim : delemeter
    """
    mat = list()
    for rec in  fileSelFieldsRecGen(dirPath, columns, delim):
        mat.append(asFloatList(rec))
    return mat

def getFileAsFloatColumn(dirPath):
    """
    grt float list from a file with one float per row
    Parameters
        dirPath : file path
    """
    flist = list()
    for rec in fileRecGen(dirPath, None):
        flist.append(float(rec))
    return flist

def getFileAsFiltFloatMatrix(dirPath, filt, columns, delim=","):
    """
    extracts float matrix from csv file given row filter and column indices with each row being 
    concatenation of  extracted column values row size = num of columns
    Parameters
        dirPath : file path
        columns : indexes of columns
        filt : row filter lambda
        delim : delemeter
    """
    mat = list()
    for rec in  fileFiltSelFieldsRecGen(dirPath, filt, columns, delim):
        mat.append(asFloatList(rec))
    return mat

def getFileAsTypedRecords(dirPath, types, delim=","):
    """
    extracts typed records from csv file with each row being concatenation of  
    extracted column values 
    Parameters
        dirPath : file path
        types : data types
        delim : delemeter
    """
    (dtypes, cvalues) = extractTypesFromString(types)
    tdata = list()
    for rec in  fileRecGen(dirPath, delim):
        trec = list()
        for index, value in enumerate(rec):
            value = __convToTyped(index, value, dtypes)
            trec.append(value)
        tdata.append(trec)
    return tdata


def getFileColsAsTypedRecords(dirPath, columns, types, delim=","):
    """
    extracts typed records from csv file given column indices with each row being concatenation of  
    extracted column values 
    Parameters
    Parameters
        dirPath : file path
        columns : column indexes
        types : data types
        delim : delemeter
    """
    (dtypes, cvalues) = extractTypesFromString(types)
    tdata = list()
    for rec in  fileSelFieldsRecGen(dirPath, columns, delim):
        trec = list()
        for indx, value in enumerate(rec):
            tindx = columns[indx]
            value = __convToTyped(tindx, value, dtypes)
            trec.append(value)
        tdata.append(trec)
    return tdata

def getFileColumnsMinMax(dirPath, columns, dtype, delim=","):
    """
    extracts numeric matrix from csv file given column indices. For each column return min and max
    Parameters
        dirPath : file path
        columns : column indexes
        dtype : data type
        delim : delemeter
    """
    dtypes = list(map(lambda c : str(c) + ":" + dtype, columns))
    dtypes = ",".join(dtypes)
    #print(dtypes)

    tdata = getFileColsAsTypedRecords(dirPath, columns, dtypes, delim)
    minMax = list()
    ncola = len(tdata[0])
    ncole = len(columns)
    assertEqual(ncola, ncole, "actual no of columns different from expected")

    for ci in range(ncole):	
        vmin = sys.float_info.max
        vmax = sys.float_info.min
        for r in tdata:
            cv = r[ci]
            vmin = cv if cv < vmin else vmin
            vmax = cv if cv > vmax else vmax
        mm = (vmin, vmax, vmax - vmin)
        minMax.append(mm)

    return minMax


def getRecAsTypedRecord(rec, types, delim=None):
    """
    converts record to  typed records 
    Parameters
        rec : delemeter separate string or list of string
        types : field  data types
        delim : delemeter
    """	
    if delim is not None:
        rec = rec.split(delim)
    (dtypes, cvalues) = extractTypesFromString(types)
    #print(types)
    #print(dtypes)
    trec = list()
    for ind, value in enumerate(rec):
        tvalue = __convToTyped(ind, value, dtypes)
        trec.append(tvalue)
    return trec

def __convToTyped(index, value, dtypes):
    """
    convert to typed value 
    Parameters
        index : index in type list
        value : data value
        dtypes : data type list
    """
    #print(index, value)
    dtype = dtypes[index]
    tvalue = value
    if dtype == "int":
        tvalue = int(value)
    elif dtype == "float":
        tvalue = float(value)
    return tvalue



def extractTypesFromString(types):
    """
    extracts column data types and set values for categorical variables 
    Parameters
        types : encoded type information
    """
    ftypes = types.split(",")
    dtypes = dict()
    cvalues = dict()
    for ftype in ftypes:
        items = ftype.split(":") 
        cindex = int(items[0])
        dtype = items[1]
        dtypes[cindex] = dtype
        if len(items) == 3:
            sitems = items[2].split()
            cvalues[cindex] = sitems
    return (dtypes, cvalues)

def getMultipleFileAsInttMatrix(dirPathWithCol,  delim=","):
    """
    extracts int matrix from from csv files given column index for each file. 
    num of columns  = number of rows in each file and num of rows = number of files
    Parameters
        dirPathWithCol: list of file path and collumn index pair
        delim : delemeter
    """
    mat = list()
    minLen = -1
    for path, col in dirPathWithCol:
        colVals = getFileColumnAsInt(path, col, delim)
        if minLen < 0 or len(colVals) < minLen:
            minLen = len(colVals)
        mat.append(colVals)

    #make all same length
    mat = list(map(lambda li:li[:minLen], mat))
    return mat

def getMultipleFileAsFloatMatrix(dirPathWithCol,  delim=","):
    """
    extracts float matrix from from csv files given column index for each file. 
    num of columns  = number of rows in each file and num of rows = number of files
    Parameters
        dirPathWithCol: list of file path and collumn index pair
        delim : delemeter
    """
    mat = list()
    minLen = -1
    for path, col in dirPathWithCol:
        colVals = getFileColumnAsFloat(path, col, delim)
        if minLen < 0 or len(colVals) < minLen:
            minLen = len(colVals)
        mat.append(colVals)

    #make all same length
    mat = list(map(lambda li:li[:minLen], mat))
    return mat

def writeStrListToFile(ldata, filePath, delem=","):
    """
    writes list of dlem separated string or list of list of string to afile

    Parameters
        ldata : list data
        filePath : file path
        delim : delemeter
    """
    with open(filePath, "w") as fh:
        for r in ldata:
            if type(r) == list:
                r = delem.join(r)
            fh.write(r + "\n")

def writeFloatListToFile(ldata, prec, filePath):
    """
    writes float list to file, one value per line

    Parameters
        ldata : list data
        prec : precision
        filePath : file path
    """
    with open(filePath, "w") as fh:
        for d in ldata:
            fh.write(formatFloat(prec, d) + "\n")


def takeFirst(elems):
    """
    return fisrt item
    Parameters
        elems : list of data 
    """
    return elems[0]

def takeSecond(elems):
    """
    return 2nd element
    Parameters
        elems : list of data 
    """
    return elems[1]

def takeThird(elems):
    """
    returns 3rd element
    Parameters
        elems : list of data 
    """
    return elems[2]

def addToKeyedCounter(dCounter, key, count=1):
    """
    add to to keyed counter
    Parameters
        dCounter : dictionary of counters
        key : dictionary key
        count : count to add
    """
    curCount = dCounter.get(key, 0)
    dCounter[key] = curCount + count

def incrKeyedCounter(dCounter, key):
    """
    increment keyed counter
    Parameters
        dCounter : dictionary of counters
        key : dictionary key
    """
    addToKeyedCounter(dCounter, key, 1)

def appendKeyedList(dList, key, elem):
    """
    keyed list
    Parameters
        dList : dictionary of lists
        key : dictionary key
        elem : value to append
    """
    curList = dList.get(key, [])
    curList.append(elem)
    dList[key] = curList

def isNumber(st):
    """
    Returns True is string is a number
    Parameters
        st : string value
    """
    return st.replace('.','',1).isdigit()

def removeNan(values):
    """
    removes nan from list
    Parameters
        values : list data
    """
    return list(filter(lambda v: not math.isnan(v), values))

def fileRecGen(filePath, delim = ","):
    """
    file record generator
    Parameters
        filePath ; file path
        delim : delemeter
    """
    with open(filePath, "r") as fp:
        for line in fp:	
            line = line[:-1]
            if delim is not None:
                line = line.split(delim)
            yield line

def fileSelFieldsRecGen(dirPath, columns, delim=","):
    """
    file record generator given column indices 
    Parameters
        filePath ; file path
        columns : column indexes as int array or coma separated string
        delim : delemeter
    """
    if type(columns) == str:
        columns = strToIntArray(columns, delim)
    for rec in fileRecGen(dirPath, delim):
        extracted = extractList(rec, columns)
        yield extracted

def fileFiltRecGen(filePath, filt, delim = ","):
    """
    file record generator with  row filter applied
    Parameters
        filePath ; file path
        filt : row filter
        delim : delemeter
    """
    with open(filePath, "r") as fp:
        for line in fp:	
            line = line[:-1]
            if delim is not None:
                line = line.split(delim)
            if filt(line):
                yield line

def fileFiltSelFieldsRecGen(filePath, filt, columns, delim = ","):
    """
    file record generator with  row and column filter applied
    Parameters
        filePath ; file path
        filt : row filter
        columns : column indexes as int array or coma separated string
        delim : delemeter
    """
    columns = strToIntArray(columns, delim)
    with open(filePath, "r") as fp:
        for line in fp:	
            line = line[:-1]
            if delim is not None:
                line = line.split(delim)
            if filt(line):
                selected = extractList(line, columns)
                yield selected

def fileTypedRecGen(filePath, ftypes, delim = ","):
    """
    file typed record generator
    Parameters
        filePath ; file path
        ftypes : list of field types
        delim : delemeter
    """
    with open(filePath, "r") as fp:
        for line in fp:	
            line = line[:-1]
            line = line.split(delim)
            for i in range(0, len(ftypes), 2):
                ci = ftypes[i]
                dtype = ftypes[i+1]
                assertLesser(ci, len(line), "index out of bound")
                if dtype == "int":
                    line[ci] = int(line[ci])
                elif dtype == "float":
                    line[ci] = float(line[ci])
                else:
                    exitWithMsg("invalid data type")
            yield line

def fileMutatedFieldsRecGen(dirPath, mutator, delim=","):
    """
    file record generator with some columns mutated 
    Parameters
        dirPath ; file path
        mutator : row field mutator
        delim : delemeter
    """
    for rec in fileRecGen(dirPath, delim):
        mutated = mutator(rec)
        yield mutated

def tableSelFieldsFilter(tdata, columns):
    """
    gets tabular data for selected columns 
    Parameters
        tdata : tabular data
        columns : column indexes
    """
    if areAllFieldsIncluded(tdata[0], columns):
        ntdata = tdata
    else:
        ntdata = list()
        for rec in tdata:
            #print(rec)
            #print(columns)
            nrec = extractList(rec, columns)
            ntdata.append(nrec)
    return ntdata


def areAllFieldsIncluded(ldata, columns):
    """
    return True id all indexes are in the columns
    Parameters
        ldata : list data
        columns : column indexes
    """
    return list(range(len(ldata))) == columns

def asIntList(items):
    """
    returns int list
    Parameters
        items : list data
    """
    return [int(i) for i in items]

def asFloatList(items):
    """
    returns float list
    Parameters
        items : list data
    """
    return [float(i) for i in items]

def pastTime(interval, unit):
    """
    current and past time
    Parameters
        interval : time interval
        unit: time unit
    """
    curTime = int(time.time())
    if unit == "d":
        pastTime = curTime - interval * secInDay
    elif unit == "h":
        pastTime = curTime - interval * secInHour
    elif unit == "m":
        pastTime = curTime - interval * secInMinute
    else:
        raise ValueError("invalid time unit " + unit)
    return (curTime, pastTime)

def minuteAlign(ts):
    """
    minute aligned time	
    Parameters
        ts : time stamp in sec
    """
    return int((ts / secInMinute)) * secInMinute

def multMinuteAlign(ts, min):
    """
    multi minute aligned time	
    Parameters
        ts : time stamp in sec
        min : minute value
    """
    intv = secInMinute * min
    return int((ts / intv)) * intv

def hourAlign(ts):
    """
    hour aligned time
    Parameters
        ts : time stamp in sec
    """
    return int((ts / secInHour)) * secInHour

def hourOfDayAlign(ts, hour):
    """
    hour of day aligned time
    Parameters
        ts : time stamp in sec
        hour : hour of day
    """
    day = int(ts / secInDay)
    return (24 * day + hour) * secInHour

def dayAlign(ts):
    """
    day aligned time
    Parameters
        ts : time stamp in sec
    """
    return int(ts / secInDay) * secInDay

def timeAlign(ts, unit):
    """
    boundary alignment of time
    Parameters
        ts : time stamp in sec
        unit : unit of time
    """
    alignedTs = 0
    if unit == "s":
        alignedTs = ts
    elif unit == "m":
        alignedTs = minuteAlign(ts)
    elif unit == "h":
        alignedTs = hourAlign(ts)
    elif unit == "d":
        alignedTs = dayAlign(ts)
    else:
        raise ValueError("invalid time unit")
    return alignedTs

def monthOfYear(ts):
    """
    month of year
    Parameters
        ts : time stamp in sec
    """
    rem = ts % secInYear
    dow = int(rem / secInMonth)
    return dow

def dayOfWeek(ts):
    """
    day of week
    Parameters
        ts : time stamp in sec
    """
    rem = ts % secInWeek
    dow = int(rem / secInDay)
    return dow

def hourOfDay(ts):
    """
    hour of day
    Parameters
        ts : time stamp in sec
    """
    rem = ts % secInDay
    hod = int(rem / secInHour)
    return hod

def processCmdLineArgs(expectedTypes, usage):
    """
    process command line args and returns args as typed values
    Parameters
        expectedTypes : expected data types of arguments
        usage : usage message string
    """
    args = []
    numComLineArgs = len(sys.argv)
    numExpected = len(expectedTypes)
    if (numComLineArgs - 1 == len(expectedTypes)):
        try:
            for i in range(0, numExpected):
                if (expectedTypes[i] == typeInt):
                    args.append(int(sys.argv[i+1]))
                elif (expectedTypes[i] == typeFloat):
                    args.append(float(sys.argv[i+1]))
                elif (expectedTypes[i] == typeString):
                    args.append(sys.argv[i+1])
        except ValueError:
            print ("expected number of command line arguments found but there is type mis match")
            sys.exit(1)
    else:
        print ("expected number of command line arguments not found")
        print (usage)
        sys.exit(1)
    return args

def mutateString(val, numMutate, ctype):
    """
    mutate string multiple times
    Parameters
        val : string value
        numMutate : num of mutations
        ctype : type of character to mutate with
    """
    mutations = set()
    count = 0
    while count < numMutate:
        j = randint(0, len(val)-1)
        if j not in mutations:
            if ctype == "alpha":
                ch = selectRandomFromList(alphaTokens)
            elif ctype == "num":
                ch = selectRandomFromList(numTokens)
            elif ctype == "any":
                ch = selectRandomFromList(tokens)
            val = val[:j] + ch + val[j+1:]
            mutations.add(j)
            count += 1
    return val

def mutateList(values, numMutate, vmin, vmax):
    """
    mutate list multiple times
    Parameters
        values : list value
        numMutate : num of mutations
        vmin : minimum of value range
        vmax : maximum of value range
    """
    mutations = set()
    count = 0
    while count < numMutate:
        j = randint(0, len(values)-1)
        if j not in mutations:
            values[j] = np.random.uniform(vmin, vmax)
            count += 1
    return values


def swap(values, first, second):
    """
    swap two elements
    Parameters
        values : list value
        first : first swap position
        second : second swap position
    """
    t = values[first]
    values[first] = values[second]
    values[second] = t

def swapBetweenLists(values1, values2):
    """
    swap two elements between 2 lists
    Parameters
        values1 : first list of values
        values2 : second list of values
    """
    p1 = randint(0, len(values1)-1)
    p2 = randint(0, len(values2)-1)
    tmp = values1[p1]
    values1[p1] = values2[p2]
    values2[p2] = tmp

def safeAppend(values, value):
    """
    append only if not None
    Parameters
        values : list value
        value : value to append
    """
    if value is not None:
        values.append(value)

def getAllIndex(ldata, fldata):
    """
    get ALL indexes of list elements
    Parameters
        ldata : list data to find index in
        fldata : list data for values for index look up
    """
    return list(map(lambda e : fldata.index(e), ldata))

def findIntersection(lOne, lTwo):
    """
    find intersection elements between 2 lists
    Parameters
        lOne : first list of data
        lTwo : second list of data
    """
    sOne = set(lOne)
    sTwo = set(lTwo)
    sInt = sOne.intersection(sTwo)
    return list(sInt)

def isIntvOverlapped(rOne, rTwo):
    """
    checks overlap between 2 intervals
    Parameters
        rOne : first interval boundaries
        rTwo : second interval boundaries
    """
    clear = rOne[1] <=  rTwo[0] or rOne[0] >=  rTwo[1] 
    return not clear

def isIntvLess(rOne, rTwo):
    """
    checks if first iterval is less than second
    Parameters
        rOne : first interval boundaries
        rTwo : second interval boundaries
    """
    less = rOne[1] <=  rTwo[0] 
    return less

def findRank(e, values):
    """
    find rank of value in a list
    Parameters
        e : value to compare with
        values : list data
    """
    count =  1
    for ve in values:
        if ve < e:
            count += 1
    return count

def findRanks(toBeRanked, values):
    """
    find ranks of values in one list in another list
    Parameters
        toBeRanked : list of values for which ranks are found
        values : list in which rank is found : 
    """
    return list(map(lambda e: findRank(e, values), toBeRanked))

def formatFloat(prec, value, label = None):
    """
    formats a float with optional label
    Parameters
        prec : precision
        value : data value
        label : label for data
    """
    st = (label + " ") if label else ""
    formatter = "{:." + str(prec) + "f}" 
    return st + formatter.format(value)

def formatAny(value, label = None):
    """
    formats any obkect with optional label
    Parameters
        value : data value
        label : label for data
    """
    st = (label + " ") if label else ""
    return st + str(value)

def printList(values):
    """
    pretty print list
    Parameters
        values : list of values
    """
    for v in values:
        print(v)

def printMap(values, klab, vlab, precision, offset=16):
    """
    pretty print hash map
    Parameters
        values : dictionary of values
        klab : label for key
        vlab : label for value
        precision : precision
        offset : left justify offset
    """
    print(klab.ljust(offset, " ") + vlab)
    for k in values.keys():
        v = values[k]
        ks = toStr(k, precision).ljust(offset, " ")
        vs = toStr(v, precision)
        print(ks +  vs)

def printPairList(values, lab1, lab2, precision, offset=16):
    """
    pretty print list of pairs
    Parameters
        values : dictionary of values
        lab1 : first label
        lab2 : second label
        precision : precision
        offset : left justify offset
    """
    print(lab1.ljust(offset, " ") + lab2)
    for (v1, v2) in values:
        sv1 = toStr(v1, precision).ljust(offset, " ")
        sv2 = toStr(v2, precision)
        print(sv1 + sv2)

def createMap(*values):
    """
    create disctionary with results
    Parameters
        values : sequence of key value pairs
    """
    result = dict()
    for i in range(0, len(values), 2):
        result[values[i]] = values[i+1]
    return result

def getColMinMax(table, col):
    """
    return min, max values of a column
    Parameters
        table : tabular data
        col : column index
    """
    vmin = None
    vmax = None
    for rec in table:
        value = rec[col]
        if vmin is None:
            vmin = value
            vmax = value
        else:
            if value < vmin:
                vmin = value
            elif value > vmax:
                vmax = value
    return (vmin, vmax, vmax - vmin)

def createLogger(name, logFilePath, logLevName):
    """
    creates logger
    Parameters
        name : logger name
        logFilePath : log file path
        logLevName : log level
    """
    logger = logging.getLogger(name)
    fHandler = logging.handlers.RotatingFileHandler(logFilePath, maxBytes=1048576, backupCount=4)
    logLev = logLevName.lower()
    if logLev == "debug":
        logLevel = logging.DEBUG
    elif logLev == "info":
        logLevel = logging.INFO
    elif logLev == "warning":
        logLevel = logging.WARNING
    elif logLev == "error":
        logLevel = logging.ERROR
    elif logLev == "critical":
        logLevel = logging.CRITICAL
    else:
        raise ValueError("invalid log level name " + logLevelName)
    fHandler.setLevel(logLevel)
    fFormat = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
    fHandler.setFormatter(fFormat)
    logger.addHandler(fHandler)
    logger.setLevel(logLevel)
    return logger

@contextmanager
def suppressStdout():
    """
    suppress stdout
    Parameters
    """
    with open(os.devnull, "w") as devnull:
        oldStdout = sys.stdout
        sys.stdout = devnull
        try:  
            yield
        finally:
            sys.stdout = oldStdout

def exitWithMsg(msg):
    """
    print message and exit
    Parameters
        msg : message
    """
    print(msg + " -- quitting")
    sys.exit(0)

def drawLine(data, yscale=None):
    """
    line plot
    Parameters
        data : list data
        yscale : y axis scale
    """
    plt.plot(data)
    if yscale:
        step = int(yscale / 10)
        step = int(step / 10) * 10
        plt.yticks(range(0, yscale, step))
    plt.show()

def drawPlot(x, y, xlabel, ylabel):
    """
    line plot
    Parameters
        x : x values
        y : y values
        xlabel : x axis label
        ylabel : y axis label
    """
    plt.plot(x,y)
    plt.xlabel(xlabel)
    plt.ylabel(ylabel)
    plt.show()

def drawPairPlot(x, y1, y2, xlabel,ylabel, y1label, y2label):
    """
    line plot of 2 lines
    Parameters
        x : x values
        y1 : first y values
        y2 : second y values
        xlabel : x labbel
        ylabel : y label
        y1label : first plot label
        y2label : second plot label
    """
    plt.plot(x, y1, label = y1label)
    plt.plot(x, y2, label = y2label)
    plt.xlabel(xlabel)
    plt.ylabel(ylabel)
    plt.legend()
    plt.show()

def drawHist(ldata, myTitle, myXlabel, myYlabel, nbins=10):
    """
    draw histogram
    Parameters
        ldata : list data
        myTitle : title
        myXlabel : x label
        myYlabel : y label 
        nbins : num of bins
    """
    plt.hist(ldata, bins=nbins, density=True)
    plt.title(myTitle)
    plt.xlabel(myXlabel)
    plt.ylabel(myYlabel)
    plt.show()

def saveObject(obj, filePath):
    """
    saves an object
    Parameters
        obj : object
        filePath : file path for saved object
    """
    with open(filePath, "wb") as outfile:
        pickle.dump(obj,outfile)

def restoreObject(filePath):
    """
    restores an object
    Parameters
        filePath : file path to restore object from
    """
    with open(filePath, "rb") as infile:
        obj = pickle.load(infile)
    return obj

def isNumeric(data):
    """
    true if all elements int or float
    Parameters
        data : numeric data list
    """
    if type(data) == list or type(data) == np.ndarray:
        col = pd.Series(data)
    else:
        col = data
    return col.dtype == np.int32 or col.dtype == np.int64 or col.dtype == np.float32 or col.dtype == np.float64

def isInteger(data):
    """
    true if all elements int 
    Parameters
        data : numeric data list
    """
    if type(data) == list or type(data) == np.ndarray:
        col = pd.Series(data)
    else:
        col = data
    return col.dtype == np.int32 or col.dtype == np.int64

def isFloat(data):
    """
    true if all elements  float
    Parameters
        data : numeric data list
    """
    if type(data) == list or type(data) == np.ndarray:
        col = pd.Series(data)
    else:
        col = data
    return col.dtype == np.float32 or col.dtype == np.float64

def isBinary(data):
    """
    true if all elements either 0 or 1
    Parameters
        data : binary data
    """
    re = next((d for d in data if not (type(d) == int and (d == 0 or d == 1))), None)
    return (re is None)

def isCategorical(data):
    """
    true if all elements int or string
    Parameters
        data : data value
    """
    re = next((d for d in data if not (type(d) == int or type(d) == str)), None)
    return (re is None)

def assertEqual(value, veq, msg):
    """
    assert equal to
    Parameters
        value : value
        veq : value to be equated with
        msg : error msg
    """
    assert value == veq , msg

def assertGreater(value, vmin, msg):
    """
    assert greater than 
    Parameters
        value : value
        vmin : minimum value
        msg : error msg
    """
    assert value > vmin , msg

def assertGreaterEqual(value, vmin, msg):
    """
    assert greater than 
    Parameters
        value : value
        vmin : minimum value
        msg : error msg
    """
    assert value >= vmin , msg

def assertLesser(value, vmax, msg):
    """
    assert less than
    Parameters
        value : value
        vmax : maximum value
        msg : error msg
    """
    assert value < vmax , msg

def assertLesserEqual(value, vmax, msg):
    """
    assert less than
    Parameters
        value : value
        vmax : maximum value
        msg : error msg
    """
    assert value <= vmax , msg

def assertWithinRange(value, vmin, vmax, msg):
    """
    assert within range
    Parameters
        value : value
        vmin : minimum value
        vmax : maximum value
        msg : error msg
    """
    assert value >= vmin and value <= vmax, msg

def assertInList(value, values, msg):
    """
    assert contains in a list
    Parameters
        value ; balue to check for inclusion
        values : list data
        msg : error msg
    """
    assert value in values, msg

def maxListDist(l1, l2):
    """
    maximum list element difference between 2 lists
    Parameters
        l1 : first list data
        l2 : second list data
    """
    dist = max(list(map(lambda v : abs(v[0] - v[1]), zip(l1, l2))))	
    return dist

def fileLineCount(fPath):
    """ 
    number of lines ina file 
    Parameters
        fPath : file path
    """
    with open(fPath) as f:
        for i, li in enumerate(f):
            pass
    return (i + 1)

def getAlphaNumCharCount(sdata):
    """ 
    number of alphabetic and numeric charcters in a string 
    Parameters
        sdata : string data
    """
    acount = 0
    ncount = 0
    scount = 0
    ocount = 0
    assertEqual(type(sdata), str, "input must be string")
    for c in sdata:
        if c.isnumeric():
            ncount += 1
        elif c.isalpha():
            acount += 1
        elif c.isspace():
            scount += 1
        else:
            ocount += 1
    r = (acount, ncount, ocount)
    return r

class StepFunction:
    """
    step function
    Parameters
    """
    def __init__(self,  *values):
        """
        initilizer

        Parameters
            values : list of tuples, wich each tuple containing 2 x values and corresponding y value
        """
        self.points = values

    def find(self, x):
        """
        finds step function value

        Parameters
            x : x value
        """
        found = False
        y = 0
        for p in self.points:
            if (x >= p[0] and x < p[1]):
                y = p[2]
                found = True
                break

        if not found:
            l = len(self.points)
            if (x < self.points[0][0]):
                y = self.points[0][2]
            elif (x > self.points[l-1][1]):
                y = self.points[l-1][2]
        return y


class DummyVarGenerator:
    """
    dummy variable generator for categorical variable
    """
    def __init__(self,  rowSize, catValues, trueVal, falseVal, delim=None):
        """
        initilizer

        Parameters
            rowSize : row size
            catValues : dictionary with field index as key and list of categorical values as value
            trueVal : true value, typically "1"
            falseval : false value , typically "0"
            delim : field delemeter
        """
        self.rowSize = rowSize
        self.catValues = catValues
        numCatVar = len(catValues)
        colCount = 0
        for v in self.catValues.values():
            colCount += len(v)
        self.newRowSize = rowSize - numCatVar + colCount
        #print ("new row size {}".format(self.newRowSize))
        self.trueVal = trueVal
        self.falseVal = falseVal
        self.delim = delim

    def processRow(self, row):
        """
        encodes categorical variables, returning as delemeter separate dstring or list

        Parameters
            row : row either delemeter separated string or list
        """
        if self.delim is not None:
            rowArr = row.split(self.delim)
            msg = "row does not have expected number of columns found " + str(len(rowArr)) + " expected " + str(self.rowSize)
            assert len(rowArr) == self.rowSize, msg
        else:
            rowArr = row

        newRowArr = []
        for i in range(len(rowArr)):
            curVal = rowArr[i]
            if (i in self.catValues):
                values = self.catValues[i]
                for val in values:
                    if val == curVal:
                        newVal = self.trueVal
                    else:
                        newVal = self.falseVal
                    newRowArr.append(newVal)
            else:
                newRowArr.append(curVal)
        assert len(newRowArr) == self.newRowSize, "invalid new row size " + str(len(newRowArr)) + " expected " + str(self.newRowSize)
        encRow = self.delim.join(newRowArr) if self.delim is not None else newRowArr
        return encRow