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_downloads/5dbab7913e2369375757c80cc6cc682b/load-analog-data.py
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import numpy as np | ||
import matplotlib.pyplot as plt | ||
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# Load data from AnalogIO workflow | ||
suffix = '2024-04-11T12_24_25'; # Change to match file names' suffix | ||
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analog_time = np.fromfile('analog-clock_' + suffix + '.raw', dtype=np.uint64) / 250e6 | ||
analog_data = np.fromfile('analog-data_' + suffix + '.raw', dtype=np.float32) | ||
analog_data = np.reshape(analog_data, (-1, 12)) | ||
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# plot the first 100k samples on each channel (1 second of data) | ||
plt.close('all') | ||
plt.plot(analog_time[0:100000], analog_data[0:100000, :]) |
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Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,14 @@ | ||
import numpy as np | ||
import matplotlib.pyplot as plt | ||
|
||
# Load data from AnalogIO workflow | ||
suffix = '2024-04-11T12_24_25'; # Change to match file names' suffix | ||
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||
analog_time = np.fromfile('analog-clock_' + suffix + '.raw', dtype=np.uint64) / 250e6 | ||
analog_data = np.fromfile('analog-data_' + suffix + '.raw', dtype=np.float32) | ||
analog_data = np.reshape(analog_data, (-1, 12)) | ||
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# plot the first 100k samples on each channel (1 second of data) | ||
plt.close('all') | ||
plt.plot(analog_time[0:100000], analog_data[0:100000, :]) |
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