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#!/usr/bin/env python3
import sounddevice as sd
import matplotlib.pyplot as plt
import numpy as np
import platform
import csv
def find_windows_input_device(name_hint, channels, preferred_apis=None):
"""Pick a Windows input device index from query_devices() output."""
preferred_apis = preferred_apis or []
name_hint = name_hint.lower()
candidates = []
for index in range(len(sd.query_devices())):
device_info = sd.query_devices(index)
max_input_channels = int(device_info.get('max_input_channels', 0))
if max_input_channels < channels:
continue
device_name = str(device_info.get('name', '')).lower()
if name_hint not in device_name:
continue
score = 0
# Prefer exact channel matches (for example 1ch source over a 4ch source).
if max_input_channels == channels:
score += 100
else:
score += 10
hostapi_index = int(device_info.get('hostapi', -1))
api_name = ''
if hostapi_index >= 0:
hostapi_info = sd.query_hostapis(hostapi_index)
api_name = str(hostapi_info.get('name', '')).lower()
for priority, api_hint in enumerate(preferred_apis):
if api_hint in api_name:
score += 50 - priority
break
candidates.append((score, index))
if not candidates:
raise ValueError(
'No input device matching hint="{}" with at least {} channels'.format(name_hint, channels)
)
return max(candidates, key=lambda item: item[0])[1]
if __name__ == '__main__':
# If you got "ValueError: No input device matching", that is because your PC name example device
# differently from tested list below. Uncomment the next line to see full list and try to pick correct one
# print(sd.query_devices())
fs = 48000 # Sample rate
duration = 3 # Duration of recording
if platform.system() == 'Windows':
# Match by substring to support names like "Microphone (2- MicNode)".
device = find_windows_input_device('micnode', channels=1, preferred_apis=['wasapi', 'mme', 'wdm-ks'])
elif platform.system() == 'Darwin':
device = 'MicNode'
else:
device ='default'
myrecording = sd.rec(int(duration * fs), samplerate=fs, channels=1, dtype='int16', device=device)
print('Waiting...')
sd.wait() # Wait until recording is finished
print('Done!')
time = np.arange(0, duration, 1 / fs) # time vector
plt.plot(time, myrecording)
plt.xlabel('Time [s]')
plt.ylabel('Amplitude')
plt.title('MicNode')
plt.show()
samples = np.array(myrecording)
np.savetxt('Output.csv', samples, delimiter=",", fmt='%s')
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