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%matplotlib inline
import matplotlib.pyplot as plt

from scipy import signal
import sounddevice as sd
import numpy as np
from scipy.io.wavfile import write
from time import sleep

Test recording / playing sounds



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duration = 12
fs = 44100
myrecording = sd.rec(duration * fs, samplerate=fs, channels=1)
print("Done!")



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sd.play(myrecording, fs)



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print(type(myrecording))
print(len(myrecording))
print(myrecording)
plt.plot(myrecording)
plt.show()



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for i in range(myrecording.size):
    if myrecording[i] < 0:
        myrecording[i] = 0
plt.plot(myrecording)
plt.show()



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def find_start(array):
    avg = []
    for i in range(array.size - 1470):
        avg.append(np.mean(array[i:i+1470]))
    
    cross = np.mean(avg)
    print(cross)
    
    for i in range(len(avg)):
        if avg[i] > cross:
            return array[i:]
    
    return array


test = find_start(myrecording)
plt.plot(test)



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print(test.size)
i=4
plt.plot(test[i*14700:(i+1)*14700])
np.mean(test[i*14700:(i+1)*14700])



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avg = []
for i in range(int(test.size/14700)):
    avg.append(np.mean(test[i*14700:(i+1)*14700]))
plt.plot(avg)

Test generating sounds



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def zero_or_one(tone_array, i, one_tone, zero_tone):
    
    if i == 0:
        tone_array = np.concatenate((tone_array, zero_tone))
        print("zero")
    else:
        tone_array = np.concatenate((tone_array, zero_tone))
        tone_array = np.concatenate((tone_array, one_tone))
        print("one")
        
    return tone_array



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sd.default.samplerate = 44100

time = .3
frequency = 440

# Generate time of samples between 0 and time seconds
samples = np.arange(44100 * time) / 44100.0
# Recall that a sinusoidal wave of frequency f has formula w(t) = A*sin(2*pi*f*t)

one_tone = 10000 * np.sin(2 * np.pi * frequency * samples)
zero_tone = samples * 0

# Convert it to wav format (16 bits)



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#start with one
tone_array = one_tone

for i in [1,1,0,1,1,1,1,0,1,0,0,1,0,0,1]:
    tone_array = zero_or_one(tone_array, i, one_tone, zero_tone)

#end with one
tone_array = zero_or_one(tone_array, 1, one_tone, zero_tone)

tone_array = np.array(tone_array, dtype=np.int16)









    



one
one
zero
one
one
one
one
zero
one
zero
zero
one
zero
zero
one
one



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sd.play(tone_array, blocking=True)
plt.plot(tone_array)









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[<matplotlib.lines.Line2D at 0x7f3f2e9f1128>]



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np.mean(myrecording)



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