raab/GP2023_chirp_detection
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improved introplot

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weygoldt 2023-03-29 12:57:02 +02:00
parent 677c29b77f
commit a7a3b26883
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3 changed files with 47 additions and 48 deletions
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2
.python-version
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@ -1 +1 @@
chirpdetection chirpdet

93
code/plot_introduction_specs.py
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@ -17,9 +17,9 @@ def main():
data = LoadData(datapath) data = LoadData(datapath)
# good chirp times for data: 2022-06-02-10_00 # good chirp times for data: 2022-06-02-10_00
window_start_seconds = 3 * 60 * 60 + 6 * 60 + 43.5 + 9 + 6.24 window_start_seconds = 3 * 60 * 60 + 6 * 60 + 43.5 + 9 + 6.20
window_start_index = window_start_seconds * data.raw_rate window_start_index = window_start_seconds * data.raw_rate
window_duration_seconds = 0.2 window_duration_seconds = 0.4
window_duration_index = window_duration_seconds * data.raw_rate window_duration_index = window_duration_seconds * data.raw_rate
timescaler = 1000 timescaler = 1000
@ -27,8 +27,8 @@ def main():
raw = data.raw[window_start_index:window_start_index + raw = data.raw[window_start_index:window_start_index +
window_duration_index, 10] window_duration_index, 10]
fig, ax = plt.subplots( fig, (ax1, ax2) = plt.subplots(
1, 1, figsize=(14 * ps.cm, 6*ps.cm), sharex=True, sharey=True) 1, 2, figsize=(21 * ps.cm, 8*ps.cm), sharex=True, sharey=True)
# plot instantaneous frequency # plot instantaneous frequency
filtered1 = bandpass_filter( filtered1 = bandpass_filter(
@ -41,12 +41,9 @@ def main():
freqtime2, freq2 = instantaneous_frequency( freqtime2, freq2 = instantaneous_frequency(
filtered2, data.raw_rate, smoothing_window=3) filtered2, data.raw_rate, smoothing_window=3)
ax.plot(freqtime1*timescaler, freq1, color=ps.g, ax1.plot(freqtime1*timescaler, freq1, color=ps.g, lw=2, label="Fish 1")
lw=2, label="Fish 1") ax1.plot(freqtime2*timescaler, freq2, color=ps.gray,
ax.plot(freqtime2*timescaler, freq2, color=ps.gray,
lw=2, label="Fish 2") lw=2, label="Fish 2")
ax.legend(bbox_to_anchor=(0, 1.02, 1, 0.2), loc="lower center",
mode="normal", borderaxespad=0, ncol=2)
# ax.legend(bbox_to_anchor=(1.04, 1), borderaxespad=0) # ax.legend(bbox_to_anchor=(1.04, 1), borderaxespad=0)
# # ps.hide_xax(ax1) # # ps.hide_xax(ax1)
@ -62,7 +59,7 @@ def main():
fmask = np.zeros(spec_freqs.shape, dtype=bool) fmask = np.zeros(spec_freqs.shape, dtype=bool)
fmask[(spec_freqs > ylims[0]) & (spec_freqs < ylims[1])] = True fmask[(spec_freqs > ylims[0]) & (spec_freqs < ylims[1])] = True
ax.imshow( ax1.imshow(
decibel(spec_power[fmask, :]), decibel(spec_power[fmask, :]),
extent=[ extent=[
spec_times[0]*timescaler, spec_times[0]*timescaler,
@ -77,47 +74,49 @@ def main():
# vmin=-100, # vmin=-100,
# vmax=-80, # vmax=-80,
) )
# ps.hide_xax(ax2)
# # plot coarse spectrogram # # plot coarse spectrogram
# spec_power, spec_freqs, spec_times = spectrogram( spec_power, spec_freqs, spec_times = spectrogram(
# raw, raw,
# ratetime=data.raw_rate, ratetime=data.raw_rate,
# freq_resolution=10, freq_resolution=15,
# overlap_frac=0.3, overlap_frac=0.3,
# ) )
# fmask = np.zeros(spec_freqs.shape, dtype=bool) fmask = np.zeros(spec_freqs.shape, dtype=bool)
# fmask[(spec_freqs > ylims[0]) & (spec_freqs < ylims[1])] = True fmask[(spec_freqs > ylims[0]) & (spec_freqs < ylims[1])] = True
# ax3.imshow( ax2.imshow(
# decibel(spec_power[fmask, :]), decibel(spec_power[fmask, :]),
# extent=[ extent=[
# spec_times[0]*timescaler, spec_times[0]*timescaler,
# spec_times[-1]*timescaler, spec_times[-1]*timescaler,
# spec_freqs[fmask][0], spec_freqs[fmask][0],
# spec_freqs[fmask][-1], spec_freqs[fmask][-1],
# ], ],
# aspect="auto", aspect="auto",
# origin="lower", origin="lower",
# interpolation="gaussian", interpolation="gaussian",
# alpha=1, alpha=1,
# ) )
# # ps.hide_xax(ax3) # ps.hide_xax(ax3)
ax2.plot(freqtime1*timescaler, freq1, color=ps.g, lw=2, label="_")
ax.set_xlabel("Time [ms]") ax2.plot(freqtime2*timescaler, freq2, color=ps.gray,
ax.set_ylabel("Frequency [Hz]") lw=2, label="_")
# ax.set_yticks(np.arange(400, 1201, 400)) ax2.set_xlim(75, 200)
# ax.spines.left.set_bounds((400, 1200)) ax1.set_ylim(400, 1200)
# ax2.set_yticks(np.arange(400, 1201, 400))
# ax2.spines.left.set_bounds((400, 1200)) fig.supxlabel("Time [ms]", fontsize=14)
# ax3.set_yticks(np.arange(400, 1201, 400)) fig.supylabel("Frequency [Hz]", fontsize=14)
# ax3.spines.left.set_bounds((400, 1200))
handles, labels = ax1.get_legend_handles_labels()
plt.subplots_adjust(left=0.17, right=0.98, top=0.87, ax2.legend(handles, labels, bbox_to_anchor=(1.04, 1), loc="upper left", ncol=1,)
bottom=0.24, hspace=0.35)
ps.letter_subplots(xoffset=[-0.27, -0.1], yoffset=1.05)
plt.subplots_adjust(left=0.12, right=0.85, top=0.89,
bottom=0.18, hspace=0.35)
plt.savefig('../poster/figs/introplot.pdf') plt.savefig('../poster/figs/introplot.pdf')
plt.show()
if __name__ == '__main__': if __name__ == '__main__':

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poster/figs/introplot.pdf
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