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1 parent 5e3cfca commit 262f494Copy full SHA for 262f494
wfdb/io/convert/edf.py
@@ -413,14 +413,16 @@ def read_edf(
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temp_sig_data = temp_all_sigs[i].flatten()
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if samps_per_frame[i] == 1:
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- sig_data[:, i] = (temp_sig_data.astype(np.int64) - baseline[i]) / adc_gain_all[i]
+ sig_data[:, i] = (
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+ temp_sig_data.astype(np.int64) - baseline[i]
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+ ) / adc_gain_all[i]
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else:
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for j in range(sig_len):
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start_ind = j * samps_per_frame[i]
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stop_ind = start_ind + samps_per_frame[i]
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sig_data[j, i] = np.mean(
- temp_sig_data[start_ind:stop_ind].astype(np.int64) - baseline[i]
- / adc_gain_all[i]
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+ temp_sig_data[start_ind:stop_ind].astype(np.int64)
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+ - baseline[i] / adc_gain_all[i]
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)
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# This is the closest I can get to the original implementation
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