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Updated calibration

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This commit is contained in:
Sam Perry
2020-01-07 17:22:14 +00:00
parent fce5c03258
commit fe2e87bebf
5 changed files with 183 additions and 369 deletions
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calibration/calc_cal_coef.py
-1
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@@ -22,7 +22,6 @@ def main():
v = np.array(v)
v = v/(v.max()*2)
v[np.isnan(v)] = 0.0
out = {}
for key, val in zip(vals.keys(), v):
out_file = './out/calibration_coefficients/{}_cal_coef.npy'.format(key)
np.save(out_file, val)
calibration/calibration_patch.maxpat
+178 -256
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calibration/gen_calibration_stimulus.py
-73
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@@ -1,73 +0,0 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import sys
sys.path.insert(0, "../matrix_test/helper_modules")
import numpy as np
from pathops import dir_must_exist
from filesystem import globDir
from pysndfile import sndio
import os
from signalops import block_process_wav
from shutil import copyfile
def calc_potential_max(wavs, noise_filepath, out_dir, out_name):
max_wav_samp = 0
max_wav_rms = 0
for wav in wavs:
x, fs, enc = sndio.read(wav)
max_wav_samp = np.max([max_wav_samp, np.max(np.abs(x))])
max_wav_rms = np.max([max_wav_rms, np.sqrt(np.mean(x**2))])
x, fs, enc = sndio.read(noise_filepath)
noise_rms = np.sqrt(np.mean(x**2))
max_noise_samp = max(np.abs(x))
snr = 5.
snr_fs = 10**(-snr/20)
max_noise_samp *= max_wav_rms/noise_rms
max_sampl = max_wav_samp+(max_noise_samp*snr_fs)
reduction_coef = 1.0/max_sampl
np.save(os.path.join(out_dir, "{}.npy".format(out_name)), reduction_coef)
return reduction_coef
def main():
'''
'''
da_files = ["../da_stim/stimulus/3000_da.wav"]
story_dir = "../eeg_story_stim/stimulus"
mat_dir = "../matrix_test/speech_components"
noise_file = "../matrix_test/behavioural_stim/stimulus/wav/noise/noise_norm.wav"
da_noise_file = "../da_stim/noise/wav/noise/noise_norm.wav"
story_wavs = globDir(story_dir, '*.wav')
mat_wavs = globDir(mat_dir, '*.wav')
out_dir = "./out"
out_red_dir = os.path.join(out_dir, 'reduction_coefficients')
out_stim_dir = os.path.join(out_dir, 'stimulus')
dir_must_exist(out_dir)
dir_must_exist(out_red_dir)
dir_must_exist(out_stim_dir)
story_coef = calc_potential_max(story_wavs, noise_file, out_red_dir, "story_red_coef")
mat_coef = calc_potential_max(mat_wavs, noise_file, out_red_dir, "mat_red_coef")
da_coef = calc_potential_max(da_files, da_noise_file, out_red_dir, "da_red_coef")
mat_cal_stim = "../matrix_test/long_concat_stim/out/stim/stim_0.wav"
da_cal_stim = "../da_stim/stimulus/wav/10min_da.wav"
click_cal_stim = "../click_stim/click_3000_20Hz.wav"
story_cal_stim = "../eeg_story_stim/stimulus/odin_1_1.wav"
mat_out_stim = os.path.join(out_stim_dir, "mat_cal_stim.wav")
click_out_stim = os.path.join(out_stim_dir, "click_cal_stim.wav")
da_out_stim = os.path.join(out_stim_dir, "da_cal_stim.wav")
story_out_stim = os.path.join(out_stim_dir, "story_cal_stim.wav")
block_process_wav(mat_cal_stim, mat_out_stim, lambda x: x * mat_coef)
block_process_wav(story_cal_stim, story_out_stim, lambda x: x * story_coef)
block_process_wav(da_cal_stim, da_out_stim, lambda x: x * da_coef)
copyfile(click_cal_stim, click_out_stim)
if __name__ == "__main__":
main()
calibration/gen_calibration_tone.py
-38
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@@ -1,38 +0,0 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import sys
sys.path.insert(0, "../matrix_test/helper_modules")
import numpy as np
from pathops import dir_must_exist
from filesystem import globDir
from pysndfile import sndio
import os
from signalops import block_process_wav
import matplotlib.pyplot as plt
def main():
'''
'''
fs = 44100
f = 1000.0
n = np.arange(fs * 60 * 5)
y = np.sin(2*np.pi*f*n/fs)
coef = np.load('./out/calibration_coefficients/click_cal_coef.npy')
y *= coef
dir_must_exist('./out/calibrated_stim/')
sndio.write("./out/calibrated_stim/1k_tone.wav", y, fs, format='wav', enc='pcm16')
coef = np.load('./out/calibration_coefficients/da_cal_coef.npy')
y, fs, enc = sndio.read('./out/stimulus/da_cal_stim.wav')
sndio.write('./out/calibrated_stim/da_cal_stim.wav', y*coef, fs, format='wav', enc='pcm16')
coef = np.load('./out/calibration_coefficients/mat_cal_coef.npy')
y, fs, enc = sndio.read('./out/stimulus/mat_cal_stim.wav')
sndio.write('./out/calibrated_stim/mat_cal_stim.wav', y*coef, fs, format='wav', enc='pcm16')
coef = np.load('./out/calibration_coefficients/story_cal_coef.npy')
y, fs, enc = sndio.read('./out/stimulus/story_cal_stim.wav')
sndio.write('./out/calibrated_stim/story_cal_stim.wav', y*coef, fs, format='wav', enc='pcm16')
if __name__ == "__main__":
main()
matrix_test_thread.py
+5 -1
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@@ -12,6 +12,7 @@ from shutil import copy2
import sys
import traceback
from loggerops import log_exceptions
from scipy.io import loadmat
from pysndfile import sndio, PySndfile
from matrix_test.helper_modules.filesystem import globDir
@@ -375,6 +376,8 @@ class MatTestThread(BaseThread):
# list
listAudiofiles = globDir(os.path.join(self.listDir, lists[ind]), "*.wav")
listCSV = globDir(os.path.join(self.listDir, lists[ind]), "*.csv")
levels = globDir(os.path.join(self.listDir, lists[ind]), "*.mat")
with open(listCSV[0]) as csv_file:
csv_reader = csv.reader(csv_file)
# Allocate empty lists to store audio samples, RMS and words of
@@ -383,8 +386,9 @@ class MatTestThread(BaseThread):
self.listsRMS.append([])
self.listsString.append([])
# Get data for each sentence
for fp, words in zip(listAudiofiles, csv_reader):
for fp, words, level_file in zip(listAudiofiles, csv_reader, levels):
# Read in audio file and calculate it's RMS
level = loadmat(level_file)
x, self.fs, _ = sndio.read(fp)
x_rms = np.sqrt(np.mean(x**2))
self.lists[-1].append(x)