plot subset
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@ -102,7 +102,7 @@ class ChirpPlotBuffer:
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self.t0 = 0
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fig = plt.figure(
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figsize=(14 / 2.54, 20 / 2.54)
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figsize=(14 * ps.cm, 18 * ps.cm)
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)
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gs0 = gr.GridSpec(
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@ -652,16 +652,16 @@ def chirpdetection(datapath: str, plot: str, debug: str = 'false') -> None:
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raw_time = np.arange(data.raw.shape[0]) / data.raw_rate
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# good chirp times for data: 2022-06-02-10_00
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window_start_index = (3 * 60 * 60 + 6 * 60 + 43.5) * data.raw_rate
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window_duration_index = 60 * data.raw_rate
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# window_start_index = (3 * 60 * 60 + 6 * 60 + 43.5) * data.raw_rate
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# window_duration_index = 60 * data.raw_rate
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# t0 = 0
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# dt = data.raw.shape[0]
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# window_start_seconds = (23495 + ((28336-23495)/3)) * data.raw_rate
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# window_duration_seconds = (28336 - 23495) * data.raw_rate
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# window_start_index = 0
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# window_duration_index = data.raw.shape[0]
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window_start_index = 0
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window_duration_index = data.raw.shape[0]
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# generate starting points of rolling window
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window_start_indices = np.arange(
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@ -675,7 +675,7 @@ def chirpdetection(datapath: str, plot: str, debug: str = 'false') -> None:
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multiwindow_chirps = []
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multiwindow_ids = []
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for st, window_start_index in enumerate(window_start_indices):
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for st, window_start_index in enumerate(window_start_indices[3175:]):
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logger.info(f"Processing window {st+1} of {len(window_start_indices)}")
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@ -10,7 +10,7 @@ from IPython import embed
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def main(datapaths):
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for path in datapaths:
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chirpdetection(path, plot='false')
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chirpdetection(path, plot='show')
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if __name__ == '__main__':
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@ -45,6 +45,7 @@ if __name__ == '__main__':
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recs = pd.DataFrame(columns=['recording'], data=valid_datasets)
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recs.to_csv('../recs.csv', index=False)
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datapaths = ['../data/mount_data/2020-03-25-10_00/']
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main(datapaths)
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# window 1524 + 244 in dataset index 4 is nice example
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