CompoundAudioPlayer.py

import pyaudio
import numpy as np


sound2 = [ 
80.30,
81.76,
82.77,
83.33,
83.49,
83.36,
83.04,
82.65,
82.31,
82.07,
81.94,
81.84,
81.63,
81.20,
80.50,
79.59,
78.62,
77.75,
77.15,
76.85,
76.79,
76.82,
76.77,
76.55,
76.16,
75.68,
75.24,
74.94,
74.82,
74.84,
74.94,
75.07,
75.25,
75.51,
75.91,
76.47,
77.13,
77.72,
78.03,
77.95,
77.52,
76.95,
76.42,
76.04,
75.81,
75.70,
75.61,
75.50,
75.36,
75.19,
75.04,
74.90,
74.79,
74.67,
74.53,
74.39,
74.29,
74.27,
74.35,
74.51,
74.71,
74.86,
74.89,
74.81,
74.63,
74.44,
74.32,
74.28,
74.33,
74.40,
74.45,
74.43,
74.33,
74.21,
74.09,
74.01,
73.98,
73.95,
73.91,
73.84,
73.77,
73.72,
73.74,
73.84,
74.02,
74.23,
74.43,
74.59,
74.69,
74.77,
74.86,
74.97,
75.10,
75.24,
75.34,
75.39,
75.39,
75.37,
75.35,
75.36,
75.42,
75.52,
75.63,
75.76,
75.88,
76.00,
76.11,
76.20,
76.27,
76.32,
76.33,
76.31,
76.29,
76.28,
76.29,
76.33,
76.38,
76.42,
76.42,
76.39,
76.33,
76.27,
76.23,
76.22,
76.25,
76.30,
76.36,
76.45,
76.55,
76.68,
76.81,
76.93,
77.02,
77.05,
77.03,
76.94,
76.83,
76.71,
76.61,
76.55,
76.53,
76.52,
76.52,
76.51,
76.50,
76.47,
76.43,
76.39,
76.34,
76.28,
76.20,
76.12,
76.05,
76.00,
75.96,
75.92,
75.88,
75.82,
75.74,
75.64,
75.55,
75.48,
75.43,
75.40,
75.37,
75.33,
75.26,
75.17,
75.05,
74.93,
74.81,
74.70,
74.60,
74.49,
74.39,
74.28,
74.19,
74.12,
74.08,
74.07,
74.07,
74.07,
74.09,
74.10,
74.12,
74.16,
74.20,
74.23,
74.26,
74.25,
74.21,
74.15,
74.08,
74.00,
73.94,
73.90,
73.86,
73.82,
73.77,
73.72,
73.68,
73.64,
73.61,
73.57,
73.53,
73.48,
73.41,
73.34,
73.27,
73.22,
73.20,
73.19,
73.19,
73.19,
73.18,
73.15,
73.13,
73.10,
73.08,
73.05,
73.02,
72.98,
72.93,
72.86,
72.79,
72.74,
72.69,
72.65,
72.61,
72.58,
72.53,
72.48,
72.43,
72.38,
72.32,
72.26,
72.20,
72.12,
72.03,
71.93,
71.84,
71.76,
71.68,
71.61,
71.54,
71.47,
71.42,
71.39,
71.39,
71.42,
71.48,
71.55,
71.63,
71.70,
71.77,
71.83,
71.89,
71.95,
72.01,
72.06,
72.10,
72.12,
72.12,
72.10,
72.09,
72.08,
72.09,
72.10,
72.13,
72.16,
72.19,
72.23,
72.27,
72.31,
72.36,
72.40,
72.44,
72.46,
72.47,
72.48,
72.49,
72.50,
72.50,
72.51,
72.51,
72.50,
72.49,
72.47,
72.45,
72.42,
72.38,
72.31,
72.23,
72.13,
72.02,
71.91,
71.80,
71.70,
71.60,
71.49,
71.38,
71.27,
71.16,
71.05,
70.95,
70.85,
70.75,
70.65,
70.54,
70.44,
70.34,
70.26,
70.18,
70.11,
70.04,
69.96,
69.86,
69.76,
69.66,
69.56,
69.48,
69.42,
69.35,
69.29,
69.22,
69.16,
69.11,
69.09,
69.10,
69.15,
69.23,
69.34,
69.48,
69.64,
69.83,
70.04,
70.28,
70.52,
70.75,
70.96,
71.16,
71.33,
71.50,
71.68,
71.85,
72.03,
72.19,
72.33,
72.44,
72.51,
72.56,
72.59,
72.60,
72.61,
72.61,
72.60,
72.58,
72.56,
72.53,
72.51,
72.49,
72.48,
72.48,
72.48,
72.47,
72.48,
72.48,
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73.00,
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73.27,
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73.51,
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74.04,
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74.81,
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74.90,
74.91,
74.91,
74.90,
74.89,
74.87,
74.87,
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74.92,
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75.03,
75.10,
75.16,
75.22,
75.27,
75.32,
75.35,
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75.39,
75.40,
75.41,
75.44,
75.49,
75.55,
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76.09,
76.23,
76.38,
76.54,
76.71,
76.89,
77.07,
77.25,
77.42,
77.60,
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77.94,
78.10,
78.26,
78.40,
78.52,
78.63,
78.74,
78.85,
78.95,
79.06,
79.16,
79.26,
79.36,
79.45,
79.54,
79.64,
79.73,
79.83,
79.93,
80.03,
80.12,
80.22,
80.32,
80.42,
80.53,
80.63,
80.73,
80.81,
80.88,
80.94,
80.98,
81.01,
81.04,
81.06,
81.07,
81.08,
81.09,
81.09,
81.10,
81.11,
81.12,
81.14,
81.15,
81.17,
81.19,
81.21,
81.23,
81.27,
81.31,
81.34,
81.37,
81.38,
81.37,
81.35,
81.32,
81.28,
81.23,
81.18,
81.13,
81.08,
81.02,
80.96,
80.90,
80.84,
80.79,
80.74,
80.69,
80.65,
80.60,
80.57,
80.54,
80.52,
80.52,
80.52,
80.53,
80.55,
80.58,
80.61,
80.65,
80.71,
80.77,
80.83,
80.90,
80.96,
81.03,
81.11,
81.19,
81.29,
81.41,
81.56,
81.75,
81.97,
82.20,
82.44,
82.65,
82.82,
82.97,
83.10,
83.23,
83.36,
83.51,
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84.07,
84.28,
84.51,
84.73,
84.96,
85.17,
85.39,
85.60,
85.80,
85.99,
86.18,
86.36,
86.53,
86.68,
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86.97,
87.09,
87.21,
87.32,
87.42,
87.51,
87.60,
87.68,
87.75,
87.82,
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87.93,
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88.03,
88.07,
88.12,
88.15,
88.19,
88.22,
88.25,
88.28,
88.31,
88.34,
88.37,
88.39,
88.42,
88.44,
88.45,
88.47,
88.48,
88.49,
88.51,
88.53,
88.56,
88.58,
88.61,
88.64,
88.68,
88.71,
88.74,
88.77,
88.81,
88.84,
88.87,
88.90,
88.93,
88.97,
89.00,
89.04,
89.08,
89.12,
89.16,
89.21,
89.25,
89.29,
89.33,
89.37,
89.41,
89.45,
89.49,
89.54,
89.58,
89.63,
89.69,
89.75,
89.82,
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90.05,
90.13,
90.22,
90.31,
90.39,
90.48,
90.57,
90.66,
90.75,
90.85,
90.96,
91.07,
91.18,
91.30,
91.41,
91.53,
91.65,
91.76,
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92.06,
92.14,
92.22,
92.30,
92.38,
92.48,
92.57,
92.68,
92.79,
92.90,
93.00,
93.10,
93.20,
93.29,
93.37,
93.44,
93.51,
93.58,
93.64,
93.70,
93.76,
93.82,
93.88,
93.94,
93.99,
94.05,
94.10,
94.15,
94.20,
94.25,
94.31,
94.36,
94.42,
94.47,
94.52,
94.56,
94.60,
94.64,
94.68,
94.71,
94.75,
94.79,
94.83,
94.87,
94.91,
94.96,
95.00,
95.04,
95.08,
95.11,
95.14,
95.17,
95.19,
95.21,
95.24,
95.26,
95.29,
95.32,
95.35,
95.38,
95.41,
95.45,
95.48,
95.51,
95.54,
95.57,
95.60,
95.62,
95.65,
95.68,
95.70,
95.73,
95.75,
95.78,
95.81,
95.84,
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95.90,
95.93,
95.95,
95.98,
96.01,
96.03,
96.04,
96.06,
96.08,
96.10,
96.11,
96.14,
96.16,
96.19,
96.21,
96.24,
96.27,
96.30,
96.33,
96.36,
96.38,
96.39,
96.41,
96.42,
96.43,
96.44,
96.46,
96.48,
96.51,
96.54,
96.57,
96.60,
96.63,
96.65,
96.67,
96.69,
96.71,
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96.77,
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96.82,
96.85,
96.87,
96.90,
96.92,
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96.99,
97.01,
97.03,
97.04,
97.06,
97.08,
97.09,
97.11,
97.13,
97.15,
97.17,
97.19,
97.21,
97.22,
97.24,
97.25,
97.26,
97.27,
97.28,
97.29,
97.30,
97.31,
97.32,
97.34,
97.35,
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97.35,
97.35,
97.34,
97.34,
97.34,
97.34,
97.34,
97.33,
97.33,
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97.33,
97.32,
97.32,
97.31,
97.30,
97.29,
97.27,
97.26,
97.24,
97.21,
97.19,
97.16,
97.13,
97.10,
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97.06,
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96.96,
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96.32,
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96.28,
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96.19,
96.16,
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96.11,
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58.26,
58.29,
58.34,
58.42,
58.51,
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58.95,
59.15,
59.36,
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62.01,
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62.18,
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# Define the FTIR spectrum
# spectrum = [0.1, 0.2, 0.3, 0.4, 0.5, 0.4, 0.3, 0.2]
spectrum = sound2

len = sound2.__len__();

# Define the audio parameters
samplerate = 44100  # Hz
duration = 1 # seconds
frequency = 440  # Hz

# Create the audio stream
p = pyaudio.PyAudio()
stream = p.open(format=pyaudio.paFloat32,
                channels=1,
                rate=samplerate,
                output=True)

# Generate the sound wave
# t = np.linspace(0, duration, duration * samplerate, False)
t = np.linspace(0, len, 4500, False)
# t = np.linspace(0, duration, 100, False)
signal = np.sin(frequency * 2 * np.pi * t)

# Sonify the spectrum
for intensity in spectrum:
    frequency = intensity * 1000  # Scale the intensity to a frequency range
    signal = np.sin(frequency * 2 * np.pi * t)
    stream.write(signal.astype(np.float32).tobytes())

# Stop the audio stream
stream.stop_stream()
stream.close()
p.terminate()