From 9a7ac66f4a2890c0fb755a1d7365f65a659972d7 Mon Sep 17 00:00:00 2001
From: weygoldt <88969563+weygoldt@users.noreply.github.com>
Date: Sun, 22 Jan 2023 00:52:22 +0100
Subject: [PATCH] plot looks better now
---
code/chirpdetection.py | 188 ++++++++++++++++++++++++++------------
code/modules/plotstyle.py | 28 ++++--
2 files changed, 149 insertions(+), 67 deletions(-)
diff --git a/code/chirpdetection.py b/code/chirpdetection.py
index cb3831f..348851a 100755
--- a/code/chirpdetection.py
+++ b/code/chirpdetection.py
@@ -43,10 +43,12 @@ class PlotBuffer:
time: np.ndarray
baseline: np.ndarray
+ baseline_envelope_unfiltered: np.ndarray
baseline_envelope: np.ndarray
baseline_peaks: np.ndarray
search_frequency: float
search: np.ndarray
+ search_envelope_unfiltered: np.ndarray
search_envelope: np.ndarray
search_peaks: np.ndarray
@@ -92,92 +94,144 @@ class PlotBuffer:
self.time = self.time - self.t0
self.frequency_time = self.frequency_time - self.t0
- chirps = np.ararray(chirps) - self.t0
+ chirps = np.asarray(chirps) - self.t0
+ self.t0_old = self.t0
self.t0 = 0
fig = plt.figure(
- figsize=(16 / 2.54, 24 / 2.54), constrained_layout=True
+ figsize=(16 / 2.54, 20 / 2.54)
)
- grid = gr.GridSpec(
- 9, 1, figure=fig, height_ratios=[4, 0.5, 1, 1, 1, 0.5, 1, 1, 1]
+ gs0 = gr.GridSpec(
+ 6, 1, figure=fig, height_ratios=[1, 0.05, 1, 0.05, 1, 0.05]
)
+ gs1 = gs0[0].subgridspec(1, 1)
+ gs2 = gs0[2].subgridspec(3, 1)
+ gs3 = gs0[4].subgridspec(3, 1)
+ gs4 = gs0[5].subgridspec(1, 1)
- ax0 = fig.add_subplot(grid[0, 0])
- ax1 = fig.add_subplot(grid[2, 0], sharex=ax0)
- ax2 = fig.add_subplot(grid[3, 0], sharex=ax0)
- ax3 = fig.add_subplot(grid[4, 0], sharex=ax0)
- ax4 = fig.add_subplot(grid[6, 0], sharex=ax0)
- ax5 = fig.add_subplot(grid[7, 0], sharex=ax0)
- ax6 = fig.add_subplot(grid[8, 0], sharex=ax0)
+ ax0 = fig.add_subplot(gs1[0, 0])
+ ax1 = fig.add_subplot(gs2[0, 0], sharex=ax0)
+ ax2 = fig.add_subplot(gs2[1, 0], sharex=ax0)
+ ax3 = fig.add_subplot(gs2[2, 0], sharex=ax0)
+ ax4 = fig.add_subplot(gs3[0, 0], sharex=ax0)
+ ax5 = fig.add_subplot(gs3[1, 0], sharex=ax0)
+ ax6 = fig.add_subplot(gs3[2, 0], sharex=ax0)
+ ax7 = fig.add_subplot(gs4[0, 0], sharex=ax0)
+
+ # ax_leg = fig.add_subplot(gs0[1, 0])
+
+ waveform_scaler = 1000
# plot spectrogram
- plot_spectrogram(ax0, data_oi, self.data.raw_rate, self.t0)
-
- ax0.fill_between(
- np.arange(self.t0, self.t0 + self.dt, 1 / self.data.raw_rate),
- q50 - self.config.minimal_bandwidth / 2,
- q50 + self.config.minimal_bandwidth / 2,
- color=ps.black,
- lw=0,
- alpha=0.2,
+ _ = plot_spectrogram(
+ ax0,
+ data_oi,
+ self.data.raw_rate,
+ self.t0,
+ [np.max(self.frequency) - 200, np.max(self.frequency) + 200]
)
- ax0.fill_between(
- np.arange(self.t0, self.t0 + self.dt, 1 / self.data.raw_rate),
- search_lower,
- search_upper,
- color=ps.black,
- lw=0,
- alpha=0.2,
- )
+ # ax0.fill_between(
+ # np.arange(self.t0, self.t0 + self.dt, 1 / self.data.raw_rate),
+ # q50 - self.config.minimal_bandwidth / 2,
+ # q50 + self.config.minimal_bandwidth / 2,
+ # color=ps.black,
+ # lw=1,
+ # ls="dashed",
+ # alpha=0.5,
+ # )
+
+ # ax0.fill_between(
+ # np.arange(self.t0, self.t0 + self.dt, 1 / self.data.raw_rate),
+ # search_lower,
+ # search_upper,
+ # color=ps.black,
+ # lw=1,
+ # ls="dashed",
+ # alpha=0.5,
+ # )
+ # ax0.axhline(q50, spec_times[0], spec_times[-1],
+ # color=ps.gblue1, lw=2, ls="dashed")
+ # ax0.axhline(q50 + self.search_frequency,
+ # spec_times[0], spec_times[-1],
+ # color=ps.gblue2, lw=2, ls="dashed")
for chirp in chirps:
ax0.scatter(
- chirp, np.median(self.frequency), c=ps.black, marker="x"
+ chirp, np.median(self.frequency) + 150, c=ps.black, marker="v"
)
# plot waveform of filtered signal
- ax1.plot(self.time, norm(self.baseline))
+ ax1.plot(self.time, self.baseline * waveform_scaler,
+ c=ps.gray, lw=2, alpha=0.5)
+ ax1.plot(self.time, self.baseline_envelope_unfiltered *
+ waveform_scaler, c=ps.gblue1, lw=2, label="baseline envelope")
# plot waveform of filtered search signal
- ax2.plot(self.time, norm(self.search))
+ ax2.plot(self.time, self.search * waveform_scaler,
+ c=ps.gray, lw=2, alpha=0.5)
+ ax2.plot(self.time, self.search_envelope_unfiltered *
+ waveform_scaler, c=ps.gblue2, lw=2, label="search envelope")
# plot baseline instantaneous frequency
- ax3.plot(self.frequency_time, self.frequency)
+ ax3.plot(self.frequency_time, self.frequency,
+ c=ps.gblue3, lw=2, label="baseline inst. freq.")
# plot filtered and rectified envelope
- ax4.plot(self.time, self.baseline_envelope)
+ ax4.plot(self.time, self.baseline_envelope, c=ps.gblue1, lw=2)
ax4.scatter(
(self.time)[self.baseline_peaks],
self.baseline_envelope[self.baseline_peaks],
c=ps.red,
+ zorder=10,
)
# plot envelope of search signal
- ax5.plot(self.time, self.search_envelope)
+ ax5.plot(self.time, self.search_envelope, c=ps.gblue2, lw=2)
ax5.scatter(
(self.time)[self.search_peaks],
self.search_envelope[self.search_peaks],
c=ps.red,
+ zorder=10,
)
# plot filtered instantaneous frequency
- ax6.plot(self.frequency_time, self.frequency_filtered)
+ ax6.plot(self.frequency_time,
+ self.frequency_filtered, c=ps.gblue3, lw=2)
ax6.scatter(
self.frequency_time[self.frequency_peaks],
self.frequency_filtered[self.frequency_peaks],
c=ps.red,
+ zorder=10,
)
- ax0.set_ylim(
- np.max(self.frequency) - 200, top=np.max(self.frequency) + 400
- )
- ax0.set_title("Spectrogram of raw data")
- ax1.set_title("Extracted features")
- ax4.set_title("Filtered and rectified features")
- ax6.set_xlabel("Time [s]")
- ax0.set_xlim(0, 5)
+ ax0.set_ylabel("frequency [Hz]")
+ ax1.set_ylabel("a.u.")
+ ax2.set_ylabel("a.u.")
+ ax3.set_ylabel("Hz")
+ ax5.set_ylabel("a.u.")
+ ax7.set_xlabel("time [s]")
+
+ ps.hide_xax(ax0)
+ ps.hide_xax(ax1)
+ ps.hide_xax(ax2)
+ ps.hide_xax(ax3)
+ ps.hide_xax(ax4)
+ ps.hide_xax(ax5)
+ ps.hide_xax(ax6)
+ ps.hide_yax(ax7)
+
+ ps.letter_subplots([ax0, ax1, ax4], xoffset=-0.21)
+
+ ax7.set_xticks(np.arange(0, 5.5, 1))
+ ax7.spines.bottom.set_bounds((0, 5))
+
+ ax0.set_ymargin(0)
+ plt.subplots_adjust(left=0.19, right=0.99,
+ top=0.98, bottom=0.08, hspace=0.15)
+ fig.align_labels()
+ ax0.autoscale(enable=True)
if plot == "show":
plt.show()
@@ -187,13 +241,17 @@ class PlotBuffer:
self.config.outputdir + self.data.datapath.split("/")[-2] + "/"
)
- plt.savefig(f"{out}{self.track_id}_{self.t0}.pdf")
+ plt.savefig(f"{out}{self.track_id}_{self.t0_old}.pdf")
plt.close()
def plot_spectrogram(
- axis, signal: np.ndarray, samplerate: float, window_start_seconds: float
-) -> None:
+ axis,
+ signal: np.ndarray,
+ samplerate: float,
+ window_start_seconds: float,
+ ylims: list[float]
+) -> np.ndarray:
"""
Plot a spectrogram of a signal.
@@ -219,18 +277,24 @@ def plot_spectrogram(
overlap_frac=0.5,
)
+ fmask = np.zeros(spec_freqs.shape, dtype=bool)
+ fmask[(spec_freqs > ylims[0]) & (spec_freqs < ylims[1])] = True
+
axis.imshow(
- decibel(spec_power),
+ decibel(spec_power[fmask, :]),
extent=[
spec_times[0] + window_start_seconds,
spec_times[-1] + window_start_seconds,
- spec_freqs[0],
- spec_freqs[-1],
+ spec_freqs[fmask][0],
+ spec_freqs[fmask][-1],
],
aspect="auto",
origin="lower",
interpolation="gaussian",
+ alpha=1,
)
+ axis.use_sticky_edges = False
+ return spec_times
def extract_frequency_bands(
@@ -477,16 +541,16 @@ def main(datapath: str, plot: str) -> None:
raw_time = np.arange(data.raw.shape[0]) / data.raw_rate
# good chirp times for data: 2022-06-02-10_00
- # window_start_seconds = (3 * 60 * 60 + 6 * 60 + 43.5) * data.raw_rate
- # window_duration_seconds = 60 * data.raw_rate
+ window_start_index = (3 * 60 * 60 + 6 * 60 + 43.5) * data.raw_rate
+ window_duration_index = 60 * data.raw_rate
# t0 = 0
# dt = data.raw.shape[0]
# window_start_seconds = (23495 + ((28336-23495)/3)) * data.raw_rate
# window_duration_seconds = (28336 - 23495) * data.raw_rate
- window_start_index = 0
- window_duration_index = data.raw.shape[0]
+ # window_start_index = 0
+ # window_duration_index = data.raw.shape[0]
# generate starting points of rolling window
window_start_indices = np.arange(
@@ -648,11 +712,12 @@ def main(datapath: str, plot: str) -> None:
# band envelope correspond to troughs in the baseline envelope
# during chirps
- search_envelope = envelope(
+ search_envelope_unfiltered = envelope(
signal=searchband,
samplerate=data.raw_rate,
cutoff_frequency=config.search_envelope_cutoff,
)
+ search_envelope = search_envelope_unfiltered
# compute instantaneous frequency of the baseline band to find
# anomalies during a chirp, i.e. a frequency jump upwards or
@@ -706,8 +771,10 @@ def main(datapath: str, plot: str) -> None:
)
current_raw_time = current_raw_time[no_edges]
baselineband = baselineband[no_edges]
+ baseline_envelope_unfiltered = baseline_envelope_unfiltered[no_edges]
searchband = searchband[no_edges]
baseline_envelope = baseline_envelope[no_edges]
+ search_envelope_unfiltered = search_envelope_unfiltered[no_edges]
search_envelope = search_envelope[no_edges]
# get instantaneous frequency withoup edges
@@ -822,11 +889,13 @@ def main(datapath: str, plot: str) -> None:
track_id=track_id,
data=data,
time=current_raw_time,
+ baseline_envelope_unfiltered=baseline_envelope_unfiltered,
baseline=baselineband,
baseline_envelope=baseline_envelope,
baseline_peaks=baseline_peak_indices,
search_frequency=search_frequency,
search=searchband,
+ search_envelope_unfiltered=search_envelope_unfiltered,
search_envelope=search_envelope,
search_peaks=search_peak_indices,
frequency_time=baseline_frequency_time,
@@ -864,9 +933,8 @@ def main(datapath: str, plot: str) -> None:
multiwindow_ids.append(track_id)
logger.info(
- "Found %d chirps for fish %d"
- % len(multielectrode_chirps_validated),
- track_id,
+ f"Found {len(multielectrode_chirps_validated)}"
+ f" chirps for fish {track_id} in this window!"
)
# if chirps are detected and the plot flag is set, plot the
# chirps, otheswise try to delete the buffer if it exists
@@ -930,7 +998,7 @@ def main(datapath: str, plot: str) -> None:
if __name__ == "__main__":
# datapath = "/home/weygoldt/Data/uni/chirpdetection/GP2023_chirp_detection/data/mount_data/2020-05-13-10_00/"
- # datapath = "../data/2022-06-02-10_00/"
+ datapath = "../data/2022-06-02-10_00/"
# datapath = "/home/weygoldt/Data/uni/efishdata/2016-colombia/fishgrid/2016-04-09-22_25/"
- datapath = "/home/weygoldt/Data/uni/chirpdetection/GP2023_chirp_detection/data/mount_data/2020-03-13-10_00/"
- main(datapath, plot="show")
+ # datapath = "/home/weygoldt/Data/uni/chirpdetection/GP2023_chirp_detection/data/mount_data/2020-03-13-10_00/"
+ main(datapath, plot="save")
diff --git a/code/modules/plotstyle.py b/code/modules/plotstyle.py
index 9e382a7..2325f62 100644
--- a/code/modules/plotstyle.py
+++ b/code/modules/plotstyle.py
@@ -30,10 +30,14 @@ def PlotStyle() -> None:
purple = "#cba6f7"
pink = "#f5c2e7"
lavender = "#b4befe"
+ gblue1 = "#8cb8ff"
+ gblue2 = "#7cdcdc"
+ gblue3 = "#82e896"
@classmethod
def lims(cls, track1, track2):
- """Helper function to get frequency y axis limits from two fundamental frequency tracks.
+ """Helper function to get frequency y axis limits from two
+ fundamental frequency tracks.
Args:
track1 (array): First track
@@ -91,6 +95,16 @@ def PlotStyle() -> None:
ax.tick_params(left=False, labelleft=False)
ax.patch.set_visible(False)
+ @classmethod
+ def hide_xax(cls, ax):
+ ax.xaxis.set_visible(False)
+ ax.spines["bottom"].set_visible(False)
+
+ @classmethod
+ def hide_yax(cls, ax):
+ ax.yaxis.set_visible(False)
+ ax.spines["left"].set_visible(False)
+
@classmethod
def set_boxplot_color(cls, bp, color):
plt.setp(bp["boxes"], color=color)
@@ -216,8 +230,8 @@ def PlotStyle() -> None:
plt.rc("figure", titlesize=BIGGER_SIZE) # fontsize of the figure title
plt.rcParams["image.cmap"] = 'cmo.haline'
- # plt.rcParams["axes.xmargin"] = 0.1
- # plt.rcParams["axes.ymargin"] = 0.15
+ plt.rcParams["axes.xmargin"] = 0.05
+ plt.rcParams["axes.ymargin"] = 0.1
plt.rcParams["axes.titlelocation"] = "left"
plt.rcParams["axes.titlesize"] = BIGGER_SIZE
# plt.rcParams["axes.titlepad"] = -10
@@ -230,9 +244,9 @@ def PlotStyle() -> None:
plt.rcParams["legend.borderaxespad"] = 0.5
plt.rcParams["legend.fancybox"] = False
- # specify the custom font to use
- plt.rcParams["font.family"] = "sans-serif"
- plt.rcParams["font.sans-serif"] = "Helvetica Now Text"
+ # # specify the custom font to use
+ # plt.rcParams["font.family"] = "sans-serif"
+ # plt.rcParams["font.sans-serif"] = "Helvetica Now Text"
# dark mode modifications
plt.rcParams["boxplot.flierprops.color"] = white
@@ -271,7 +285,7 @@ def PlotStyle() -> None:
plt.rcParams["ytick.color"] = gray # color of the ticks
plt.rcParams["grid.color"] = dark_gray # grid color
plt.rcParams["figure.facecolor"] = black # figure face color
- plt.rcParams["figure.edgecolor"] = "#555169" # figure edge color
+ plt.rcParams["figure.edgecolor"] = black # figure edge color
plt.rcParams["savefig.facecolor"] = black # figure face color when saving
return style