# -*- coding: utf-8 -*-
"""
Created on Fri Mar 10 15:10:36 2023

@author: BorowyP
"""

import os

import matplotlib.pyplot as plt

import numpy as np
import pandas as pd

import hvplot.pandas

import holoviews as hv

from holoviews.operation.timeseries import rolling, rolling_outlier_std

import xarray as xr
import panel as pn

import panel.widgets as pnw



import hvplot.xarray

cwd = os.getcwd()
print(cwd)
print(os.listdir(cwd))
os.chdir('hemi_fotos')
pic_cwd = os.getcwd()
print(pic_cwd)
os.listdir(pic_cwd)

os.chdir(pic_cwd)
#os.listdir()
list_pictures_files = os.listdir()

rgb_list = []

for i in range(len(list_pictures_files)):
    im = plt.imread(list_pictures_files[i])
    x = np.arange(len(im[0]))
    y = np.arange(len(im))
    channel = np.arange(3)
    im_xr = xr.DataArray(im,coords={'y': y,'x': x,'channel': channel},dims=["y", "x", "channel"])
    rgb_list.append(im_xr)
    #print(str(list_pictures_files[i]) + ' ' + 
    #      'y-Achse: ' + ' ' + str(len(im)) + ', ' + 
    #      'x-Achse: ' + ' ' + str(len(im[0])) + ', ' + 'channel: ' + ' ' + str(len(im[0][0])))
    #print(' ')

x = np.arange(len(rgb_list[0][0]))
y = np.arange(len(rgb_list[0]))
channel = np.arange(3)

Stndrt = np.array([
    'Krausnick K',
    'Glienig K',
    'Glienig nK',
    'Halbe K',
    'Halbe nK',
    'Hangelsberg K',
    'Hangelsberg nK',
    'Spreeau K',
    'Spreeau nK',
    'Groß Liebitz K',
    'Groß Liebitz nK'
])




xar = xr.DataArray(rgb_list, 
                   dims=(
                       
                       'Standort',
                       "y", 
                       "x", 
                       "channel")
                   , 
                   coords={
                       "x": x,
                       "y": y,
                       "channel": channel,
                       'Standort' : Stndrt,
                       
                   },
                  name="rgb")




fisheye = xar.hvplot.rgb(x='x', y='y', bands='channel', data_aspect=1, flip_yaxis=True, xaxis=False, yaxis=None, width=500)


os.chdir(cwd)


df = pd.read_csv(
        'Hemisphere_totals_holzdeko.csv' ,
        encoding_errors='ignore', 
        sep=';', 
        #skiprows=[5,10], 
        header=0, 
        decimal=','
           )

df['transmission'] = df['transmission'].str.strip('%') #  entfernt Character '%'
df['transm_gaps'] = df['transm_gaps'].str.strip('%')
df['openness'] = df['openness'].str.strip('%')
df['openn_gaps'] = df['openn_gaps'].str.strip('%')

df['transmission'] = df['transmission'].replace(',', '.', regex=True) # wandelt , in . um
df['transm_gaps'] = df['transm_gaps'].replace(',', '.', regex=True)
df['openness'] = df['openness'].replace(',', '.', regex=True)
df['openn_gaps'] = df['openn_gaps'].replace(',', '.', regex=True)

df['transmission'] = df['transmission'].astype('float64', copy=False)
df['transm_gaps'] = df['transm_gaps'].astype('float64', copy=False)
df['openness'] = df['openness'].astype('float64', copy=False)
df['openn_gaps'] = df['openn_gaps'].astype('float64', copy=False)



params = pn.widgets.RadioButtonGroup(
    name='param',
    options=['white',
             'black',
             'transmission',
             'transm_gaps',
             'openness',
             'openn_gaps'
             ], 
    button_type='success')

data_inter = df.interactive()

mean_param = (
    data_inter
    .groupby(['Standort', 'k_nk']).mean()
    
)

mean_param_plot = mean_param[params].hvplot(x='Standort', y=params, by='k_nk', kind='bar', 
                        title=params, xlabel='Standort')





param_discription = pd.DataFrame({'white': ['white pixels (sky)'],
                                 'black' : ['black pixels (canopy)'],
                                 'transmission' : ['light transmission in 2D (azimutal equidistant projection of the hemisphere)'],
                                 'transm_gaps' : ['large gaps of transmission'],
                                 'openness' : ['canopy openness in 3D, also called sky view factor (solid angles of the hemisphere)'],
                                 'openn_gaps' : ['large gaps of openness']})

param_discription = param_discription.interactive()

param_discription = param_discription[params].values[0]



os.chdir(cwd)
hd_logo = pn.pane.PNG('HD_Logo.png', width=100)
lfe_logo = pn.pane.PNG('LFE_Logo.png', width=100)
fnr_logo = pn.pane.PNG('fnr_logo.png', width=100)

template = pn.template.FastListTemplate(
    title='Auswertung Hemisfere', 
    sidebar=[hd_logo,
             pn.pane.Markdown("## Einstellungen"),
             #'Standort',Stndrt,
             #'gekalkt/ungekalkt', yaxis,
             lfe_logo,
             fnr_logo
             #'Boden',
             #'Gekalkt/ungekalkt', yaxis,
            ], 
    main=[pn.pane.Markdown("## Hemisfere"),
          fisheye,#.panel(),
          #params,
          param_discription,
          mean_param_plot.panel(),
          
    #accent_base_color="#88d8b0",
    #header_background="#88d8b0",
         ])




template.servable();

print('fertig!')
# To launch this dashboard as a web server, we can simply run 
# cd C:\Users\BorowyP\Desktop\Dashboard-Preasi\hemisfer

# panel serve 2023_02_10_hemi_dashboard.ipynb --autoreload