#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Mar 25 10:04:06 2021

@author: lucasdaniele
"""

from scipy.io import wavfile
import matplotlib.pyplot as plt
import numpy as np
import frequency_estimator as f0
import os


def listen(nom,sampleRate, data):
    wavfile.write(nom, sampleRate, data.real)
    
def aff(titre,x,y):
    if(len(x)==len(y)):
        plt.plot(x, y.real, "-")
    else:
        plt.plot(y.real, "-")
    plt.title(titre)
    plt.show()

def decouperExtraits(data, seuil, dureeSilence, sampleRate, sampleRateChoosen):
    DATA=[]
    onAir=False
    step=int(np.round(sampleRateChoosen*dureeSilence))
    echelle = sampleRate/sampleRateChoosen
    dureeExtrait = len(data)/sampleRate
    k=0
    d=0
    f=0
    for i in range(0,int(np.round(dureeExtrait)*sampleRateChoosen-step)-1000):
        if (i%40000==0):
            afficherAvancement(i,int(np.round(dureeExtrait)*sampleRateChoosen-step)-1000)
        if ((abs(data[int(np.round(i*echelle))])<seuil) & onAir):
            if(k<step):
                k+=1
            else:
                k=0
                onAir=False
                f=int(np.round(i*echelle))
                DATA.append([d,f])
                d=0
                f=0
        else:
            if(abs(data[int(np.round(i*echelle))])>=seuil):
                if(not(onAir)):
                    onAir=True
                    d=int(np.round(i*echelle))
                k=0
    if(d>0):
        DATA.append([d,len(data)-1])
    return DATA    

def afficherAvancement(t,T):
    os.system('clear')
    barre = "|"
    for i in range(int(np.round(np.round(t/T,2)*50))):
        barre += "#"
    for i in range(50-int(np.round(np.round(t/T,2)*50))):
        barre += "_"
    barre +="| "
    barre += str(np.round(t/T,2)) + " %"
    print(barre)
        
def garderUniquementCris(sampleRate,tMin, tMax, fMin, fMax, f0Func, dataCut, data):
    nSamplesMin = tMin*sampleRate 
    nSamplesMax = tMax*sampleRate
    res=[]
    freqs=[]
    for i in range(len(dataCut)):
        d=dataCut[i][0]
        f=dataCut[i][1]
        if((f-d>nSamplesMin) & (f-d<nSamplesMax)):
            freq = np.round(f0Func(np.asarray(data[d:f]),sampleRate))
            if((freq>fMin) & (freq<fMax)):
                quantiteDeSonA5Pourcents = np.sum(abs(data[d:d+int(np.round(0.05*(f-d)))]))
                quantiteDeSon = np.sum(abs(data[d:f]))
                if (quantiteDeSonA5Pourcents / quantiteDeSon > 0.065):
                    res.append(dataCut[i])
                    freqs.append(freq)
                    
                    listen("output/cri"+str(i)+".wav", sampleRate, np.asarray(data[d:f]))
                    print("*************************")
                    print("* enregistrement: " + str(i))
                    print("*************************")
                    print("*   f0 -> " + str(freq))
                    print("*   duration -> " + str((f-d)/sampleRate))  
                    print("*   quantité de son à 5% -> " + str(np.sum(abs(data[d:d+int(np.round(0.05*(f-d)))]))/np.sum(abs(data[d:f]))))    
                    print("*************************")
                    print("")
                    print("_________________________")
                    print("")
    
    return res, freqs