Pre-move to big mac commit

da_stim/gen_da.py

@@ -9,13 +9,16 @@ import pdb
 import matplotlib.pyplot as plt
 from pathops import dir_must_exist
 from signalops import gen_trigger
+import resampy
 
 def gen_da_stim(n, outpath):
     da_file = './BioMAP_da-40ms.wav'
     da_stim, fs, enc, fmt = sndio.read(da_file, return_format=True)
     prestim_size = 0.0158
-    full_stim_size = 0.09174311926605504
-    da_size = 0.04
+    # Repetition rate in Hz
+    repetition_rate = 10.9
+    full_stim_size = 1./repetition_rate
+    da_size = da_stim.size / fs
     prestim = np.zeros(int(fs*prestim_size))
     poststim = np.zeros(int(fs*((full_stim_size-prestim_size)-da_size)))
     y_part = np.concatenate([prestim, da_stim, poststim])
@@ -30,7 +33,8 @@ def gen_da_stim(n, outpath):
     trigger = gen_trigger(idx, 2., 0.01, fs)
 
     y = np.vstack((y_l, y_r, trigger))
-    sndio.write(outpath, y.T, rate = fs, format = fmt, enc=enc)
+    y = resampy.resample(y, fs, 44100).T
+    sndio.write(outpath, y, rate = 44100, format = fmt, enc=enc)
     return outpath
 
 

da_test_thread.py

@@ -13,7 +13,7 @@ from shutil import copy2
 from test_base import BaseThread
 
 from matrix_test.helper_modules.signalops import play_wav, block_mix_wavs
-from pathops import dir_must_exist
+from pathops import dir_must_exist, delete_if_exists
 from scipy.special import logit
 from config import socketio
 import csv
@@ -59,7 +59,8 @@ class DaTestThread(BaseThread):
         self.nTrials = nTrials
         self.trial_ind = 0
         self._stopevent = Event()
-        self.si = np.array([20.0, 35.0, 50.0, 65.0, 80.0, 90.0])
+        # (Completely clean stimulus added by default later)
+        self.si = np.array([19.0, 50.0, 81.0, 90.0])
 
         super(DaTestThread, self).__init__(self.test_name,
                                            sessionFilepath=sessionFilepath,
@@ -132,20 +133,23 @@ class DaTestThread(BaseThread):
         x = logit(self.si * 0.01)
         snrs = (x/(4*s_50))+srt_50
         snrs = np.append(snrs, np.inf)
+        self.si = np.append(self.si, np.inf)
+
         self.snr_fs = 10**(-snrs/20)
         self.snr_fs[self.snr_fs == np.inf] = 0.
         if (self.snr_fs == -np.inf).any():
             raise ValueError("Noise infinitely louder than signal for an SNR (SNRs: {})".format(self.snr_fs))
 
 
-        wavs = globDir(self.stim_folder, "3000_da.wav") * len(self.si)
-        rms_files = globDir(self.stim_folder, "overall_da_rms.npy") * len(self.si)
+        wavs = globDir(self.stim_folder, "3000_da.wav") * len(snrs)
+        rms_files = globDir(self.stim_folder, "overall_da_rms.npy") * len(snrs)
 
         self.socketio.emit('test_stim_load', namespace='/main')
         # Add noise to audio files at set SNRs and write to participant
         # directory
         self.data_path = self.participant.data_paths[self.test_name]
         out_dir = os.path.join(self.data_path, "stimulus")
+        delete_if_exists(out_dir)
         out_info = os.path.join(out_dir, "stim_info.csv")
         dir_must_exist(out_dir)
 
@@ -157,7 +161,6 @@ class DaTestThread(BaseThread):
                 out_wavpath =  os.path.join(out_dir, fp)
                 stim_rms = np.load(rms)
                 match_ratio = stim_rms/self.noise_rms
-                set_trace()
                 block_mix_wavs(wav, self.noise_path, out_wavpath,
                                1.*self.reduction_coef,
                                snr_fs*match_ratio*self.reduction_coef,

matrix_test/helper_modules/generate_matrix_plots.py

@@ -54,10 +54,12 @@ def logisticFuncLiklihood(args):
     with np.errstate(divide='raise'):
         try:
             a = np.concatenate(res)
-            a[a == 0] = a.max()
+            a[a == 0] = np.finfo(float).eps
             out = -np.sum(np.log(a))
         except:
             set_trace()
+    if out == 0.:
+        pdb.set_trace()
     return out
 
 
@@ -69,6 +71,7 @@ def fitLogistic():
     wordsCorrect = wordsCorrect[:trialN].astype(float)
     trackSNR = snrTrack[:trialN]
     res = minimize(logisticFuncLiklihood, np.array([np.mean(trackSNR),1.0]))
+    pdb.set_trace()
     percent_correct = (np.sum(wordsCorrect, axis=1)/wordsCorrect.shape[1])*100.
     sortedSNRind = np.argsort(-trackSNR)
     sortedSNR = trackSNR[sortedSNRind]

matrix_test_thread.py

@@ -136,7 +136,7 @@ class MatTestThread(BaseThread):
         Main loop for iteratively finding the SRT
         '''
         self.waitForPageLoad()
-        while not self.finishTest and not self._stopevent.isSet():
+        while not self.finishTest and not self._stopevent.isSet() and len(self.availableSentenceInds):
             self.plotSNR()
             self.y = self.generateTrial(self.snr)
             self.playStimulus(self.y, self.fs)
@@ -205,7 +205,7 @@ class MatTestThread(BaseThread):
         with np.errstate(divide='raise'):
             try:
                 a = np.concatenate(res)
-                a[a == 0] = a.max()
+                a[a == 0] = np.finfo(float).eps
                 out = -np.sum(np.log(a))
             except:
                 set_trace()
@@ -402,7 +402,6 @@ class MatTestThread(BaseThread):
         y = x_noise
         # Set speech to start 500ms after the noise, scaled to the desired SNR
         sigStart = round(self.fs/2.)
-        set_trace()
         y[sigStart:sigStart+x.size] += x*snr_fs
         y *= self.reduction_coef
         return y

participant.py

@@ -2,9 +2,19 @@ from pathops import dir_must_exist
 import os
 import dill
 import numpy as np
+import pdb
 
 from config import server, socketio, participants
 
+def set_trace():
+    import logging
+    log = logging.getLogger('werkzeug')
+    log.setLevel(logging.ERROR)
+    log = logging.getLogger('engineio')
+    log.setLevel(logging.ERROR)
+    pdb.set_trace()
+
+
 def find_participants(folder='./participant_data/'):
     '''
     Returns a tuple of (participant number, participant filepath) for every
@@ -25,7 +35,7 @@ def gen_participant_num(participants, N = 100):
     taken_nums = []
     for part_key in participants.keys():
         participant = participants[part_key]
-        taken_nums.append(participant['info']['number'])
+        taken_nums.append(int(participant['info']['number'][0]))
     n = 0
     num_found = False
     while not num_found:

route.py

@@ -108,6 +108,13 @@ def create_participant_page():
     part_num = gen_participant_num(participants)
     return render_template("create_participant.html", num=part_num)
 
+def set_trace():
+    import logging
+    log = logging.getLogger('werkzeug')
+    log.setLevel(logging.ERROR)
+    log = logging.getLogger('engineio')
+    log.setLevel(logging.ERROR)
+    pdb.set_trace()
 @server.route('/participant/create/submit', methods=["POST"])
 def create_participant_submit():
     data = request.form

templates/index.html

@@ -48,7 +48,7 @@
 
 <body class = "body">
     <nav id="main-nav" class="navbar navbar-expand-lg navbar-light bg-light">
-    <a class="navbar-brand" href="home">BPLabs v0.1</a>
+    <a class="navbar-brand" href="/home">BPLabs v0.1</a>
     <button class="navbar-toggler" type="button" data-toggle="collapse" data-target="#navbarSupportedContent" aria-controls="navbarSupportedContent" aria-expanded="false" aria-label="Toggle navigation">
         <span class="navbar-toggler-icon"></span>
     </button>
@@ -56,7 +56,7 @@
         <div class="collapse navbar-collapse" id="navbarSupportedContent">
             <ul class="navbar-nav mr-auto">
             <li class="nav-item active">
-                <a class="nav-link" href="home">Home<span class="sr-only">(current)</span></a>
+                <a class="nav-link" href="/home">Home<span class="sr-only">(current)</span></a>
             </li>
             <li class="nav-item dropdown">
                 <a class="nav-link dropdown-toggle" href="#" id="navbarDropdown" role="button" data-toggle="dropdown" aria-haspopup="true" aria-expanded="false">

test_base.py

@@ -265,7 +265,6 @@ class BaseThread(Thread):
         Restore thread state from a saved session filepath
         '''
         with open(filepath, 'rb') as f:
-            set_trace()
             self.__dict__.update(dill.load(f))