improved introplot

.python-version

@@ -1 +1 @@
-chirpdetection
+chirpdet

code/plot_introduction_specs.py

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