Nettoyage + optimisation frs hps

cells.py

@@ -12,7 +12,7 @@ import numpy as np
 import matplotlib.pyplot as plt
 import fcts as fcts
 import importlib
-import frequency_estimator.frequency_estimator as f0
+import frequency_estimator as f0
 importlib.reload(fcts)
 importlib.reload(f0)
 
@@ -21,8 +21,8 @@ importlib.reload(f0)
 # Extraction des données
 ################################################
 #%%
-bEnSec = (0*60+0)
-duree = 500
+bEnSec = (0*60)
+duree = 60
 
 samplerate, dataLR = wavfile.read("input/male.wav")#On lit le fichier qui a des infos oreille gauche, oreille droite
 dataL = dataLR[:,0]#On recupère que le son de l'oreille gauche
@@ -44,20 +44,18 @@ fcts.listen("output/extrait.wav", samplerate, data)
 ################################################
 #%%
 dataCut = fcts.decouperExtraits(data)
-print(str(len(dataCut))+" cris")
+print(str(len(dataCut))+" cuts")
 
 ################################################
 # Support temporel uniquement cris
 ################################################
 #%%
-dataCutCris = fcts.garderUniquementCris(samplerate,0.5,1.5,250,2000,f0.freq_from_HPS, dataCut)
-freqArray = []
+dataCutCris, freqArray = fcts.garderUniquementCris(samplerate,0.5,1.5,250,450,f0.freq_from_HPS, dataCut)
 for i in range(len(dataCutCris)):   
-    fcts.aff("cri"+str(i), t, np.asarray(dataCutCris[i]))
+    #fcts.aff("cri"+str(i), t, np.asarray(dataCutCris[i]))
     fcts.listen("output/cri"+str(i)+".wav", samplerate, np.asarray(dataCutCris[i]))
     print("enregistrement: " + str(i))
-    print(np.round(f0.freq_from_HPS(np.asarray(dataCutCris[i]),samplerate)))
-    freqArray.append(f0.freq_from_HPS(np.asarray(dataCutCris[i]),samplerate))
+    print(np.round(freqArray[i]))
     print("________________")
 
 print(np.mean(freqArray))

fcts.py

@@ -9,7 +9,7 @@ Created on Thu Mar 25 10:04:06 2021
 from scipy.io import wavfile
 import matplotlib.pyplot as plt
 import numpy as np
-import frequency_estimator.frequency_estimator as f0
+import frequency_estimator as f0
 
 
 def listen(nom,sampleRate, data):
@@ -54,13 +54,15 @@ def garderUniquementCris(sampleRate,tMin, tMax, fMin, fMax, f0Func, dataCut):
     nSamplesMin = tMin*sampleRate 
     nSamplesMax = tMax*sampleRate
     res=[]
+    freqs=[]
     for i in range(len(dataCut)):
         if((len(dataCut[i])>nSamplesMin) & (len(dataCut[i])<nSamplesMax)):
             freq = np.round(f0Func(np.asarray(dataCut[i]),sampleRate))
             if((freq>fMin) & (freq<fMax)):
                 res.append(dataCut[i])
+                freqs.append(freq)
     
-    return res
+    return res, freqs
 
     
     

frequency_estimator.py

@@ -9,7 +9,7 @@ try:
 except ImportError:
     from scikits.audiolab import flacread
 
-from frequency_estimator.parabolic import parabolic
+from parabolic import parabolic
 
 
 def freq_from_crossings(sig, fs):