Merge branch 'master' into alex
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commit
41b75f1a68
@ -187,22 +187,9 @@ def main(datapath: str) -> None:
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# start_index = t0 * data.samplerate
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# start_index = t0 * data.samplerate
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# stop_index = (t0 + dt) * data.samplerate
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# stop_index = (t0 + dt) * data.samplerate
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fig, axs = plt.subplots(
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7,
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2,
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figsize=(20 / 2.54, 12 / 2.54),
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constrained_layout=True,
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sharex=True,
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sharey='row',
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)
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# iterate through all fish
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# iterate through all fish
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for i, track_id in enumerate(np.unique(ident[~np.isnan(ident)])[:2]):
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for i, track_id in enumerate(np.unique(ident[~np.isnan(ident)])[:2]):
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# load region of interest of raw data file
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data_oi = data[start_index:stop_index, :]
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time_oi = raw_time[start_index:stop_index]
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# get indices for time array in time window
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# get indices for time array in time window
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window_index = np.arange(len(idx))[
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window_index = np.arange(len(idx))[
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(ident == track_id) & (time[idx] >= t0) & (
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(ident == track_id) & (time[idx] >= t0) & (
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@ -220,10 +207,25 @@ def main(datapath: str) -> None:
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if len(freq_temp) < expected_duration * 0.9:
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if len(freq_temp) < expected_duration * 0.9:
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continue
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continue
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fig, axs = plt.subplots(
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7,
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config.electrodes,
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figsize=(20 / 2.54, 12 / 2.54),
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constrained_layout=True,
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sharex=True,
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sharey='row',
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)
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# get best electrode
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# get best electrode
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electrode = np.argsort(np.nanmean(powers_temp, axis=0))[-1]
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best_electrodes = np.argsort(np.nanmean(
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powers_temp, axis=0))[-config.electrodes:]
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# <------------------------------------------ Iterate through electrodes
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# <------------------------------------------ Iterate through electrodes
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for i, electrode in enumerate(best_electrodes):
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# load region of interest of raw data file
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data_oi = data[start_index:stop_index, :]
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time_oi = raw_time[start_index:stop_index]
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# plot wavetracker tracks to spectrogram
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# plot wavetracker tracks to spectrogram
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# for track_id in np.unique(ident): # <---------- Find freq gaps later
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# for track_id in np.unique(ident): # <---------- Find freq gaps later
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# here
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# here
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@ -424,7 +426,8 @@ def main(datapath: str) -> None:
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axs[3, i].set_title("Fitered above")
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axs[3, i].set_title("Fitered above")
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axs[4, i].set_title("Filtered envelope of baseline envelope")
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axs[4, i].set_title("Filtered envelope of baseline envelope")
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axs[5, i].set_title("Search envelope")
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axs[5, i].set_title("Search envelope")
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axs[6, i].set_title("Filtered absolute instantaneous frequency")
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axs[6, i].set_title(
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"Filtered absolute instantaneous frequency")
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plt.show()
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plt.show()
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@ -1,6 +1,7 @@
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# Duration and overlap of the analysis window in seconds
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# Duration and overlap of the analysis window in seconds
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window: 5
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window: 5
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overlap: 0.5
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overlap: 1
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edges: 0.25
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# Number of electrodes to go over
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# Number of electrodes to go over
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electrodes: 3
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electrodes: 3
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