diff --git a/bilby/gw/result.py b/bilby/gw/result.py
index 8f405cc99ec7623a98e3f193706061c59728e6fe..ed9125a94840b6f48518d0761ba18c3dc675f08c 100644
--- a/bilby/gw/result.py
+++ b/bilby/gw/result.py
@@ -289,6 +289,18 @@ class CompactBinaryCoalescenceResult(CoreResult):
waveforms to have ~4000 entries. This should be sufficient for decent
resolution.
"""
+
+ if format == "html":
+ try:
+ import plotly.graph_objects as go
+ from plotly.offline import plot
+ from plotly.subplots import make_subplots
+ except ImportError:
+ logger.warning(
+ "HTML plotting requested, but plotly cannot be imported, "
+ "falling back to png format for waveform plot.")
+ format = "png"
+
if isinstance(interferometer, str):
interferometer = get_empty_interferometer(interferometer)
interferometer.set_strain_data_from_zero_noise(
@@ -317,6 +329,9 @@ class CompactBinaryCoalescenceResult(CoreResult):
if end_time is None:
end_time = 0.2
end_time = np.mean(self.posterior.geocent_time) + end_time
+ if format == "html":
+ start_time = - np.inf
+ end_time = np.inf
time_idxs = (
(interferometer.time_array >= start_time) &
(interferometer.time_array <= end_time)
@@ -329,7 +344,7 @@ class CompactBinaryCoalescenceResult(CoreResult):
logger.debug("Downsampling frequency mask to {} values".format(
len(frequency_idxs))
)
- plot_times = interferometer.time_array[time_idxs]
+ plot_times = interferometer.time_array[time_idxs] - interferometer.strain_data.start_time
plot_frequencies = interferometer.frequency_array[frequency_idxs]
waveform_generator = WaveformGenerator(
@@ -338,25 +353,73 @@ class CompactBinaryCoalescenceResult(CoreResult):
frequency_domain_source_model=self.frequency_domain_source_model,
parameter_conversion=self.parameter_conversion,
waveform_arguments=self.waveform_arguments)
- fig, axs = plt.subplots(2, 1)
+
+ if format == "html":
+ fig = make_subplots(
+ rows=2, cols=1,
+ row_heights=[0.5, 0.5],
+ )
+ fig.update_layout(
+ template='plotly_white',
+ font=dict(
+ family="Computer Modern",
+ )
+ )
+ else:
+ fig, axs = plt.subplots(2, 1)
+
if self.injection_parameters is not None:
try:
hf_inj = waveform_generator.frequency_domain_strain(
self.injection_parameters)
hf_inj_det = interferometer.get_detector_response(
hf_inj, self.injection_parameters)
- axs[0].loglog(
- plot_frequencies,
- asd_from_freq_series(
- hf_inj_det[frequency_idxs],
- 1 / interferometer.strain_data.duration),
- color='k', label='injected', linestyle='--')
- axs[1].plot(
- plot_times,
- infft(hf_inj_det /
- interferometer.amplitude_spectral_density_array,
- self.sampling_frequency)[time_idxs],
- color='k', linestyle='--')
+ ht_inj_det = infft(
+ hf_inj_det /
+ interferometer.amplitude_spectral_density_array,
+ self.sampling_frequency)[time_idxs],
+ if format == "html":
+ fig.add_trace(
+ go.Scatter(
+ x=plot_frequencies,
+ y=asd_from_freq_series(
+ hf_inj_det[frequency_idxs],
+ 1 / interferometer.strain_data.duration),
+ fill=None,
+ mode='lines',
+ line_color='black',
+ name="Injection",
+ legendgroup='injection',
+ ),
+ row=1,
+ col=1,
+ )
+ fig.add_trace(
+ go.Scatter(
+ x=plot_times, y=ht_inj_det,
+ fill=None,
+ mode='lines',
+ line_color='black',
+ name="Injection",
+ legendgroup='injection',
+ showlegend=False,
+ ),
+ row=2,
+ col=1,
+ )
+ else:
+ axs[0].loglog(
+ plot_frequencies,
+ asd_from_freq_series(
+ hf_inj_det[frequency_idxs],
+ 1 / interferometer.strain_data.duration),
+ color='k', label='injected', linestyle='--')
+ axs[1].plot(
+ plot_times,
+ infft(hf_inj_det /
+ interferometer.amplitude_spectral_density_array,
+ self.sampling_frequency)[time_idxs],
+ color='k', linestyle='--')
logger.debug('Plotted injection.')
except IndexError:
logger.info('Failed to plot injection.')
@@ -386,64 +449,203 @@ class CompactBinaryCoalescenceResult(CoreResult):
)
)
- axs[0].loglog(
- plot_frequencies,
- np.median(fd_waveforms, axis=0), color='r', label='Median')
- axs[0].fill_between(
- plot_frequencies,
- np.percentile(fd_waveforms, lower_percentile, axis=0),
- np.percentile(fd_waveforms, upper_percentile, axis=0),
- color='r', label='{} % Interval'.format(
- int(upper_percentile - lower_percentile)),
- alpha=0.3)
- axs[1].plot(
- plot_times, np.median(td_waveforms, axis=0),
- color='r')
- axs[1].fill_between(
- plot_times, np.percentile(
- td_waveforms, lower_percentile, axis=0),
- np.percentile(td_waveforms, upper_percentile, axis=0), color='r',
- alpha=0.3)
-
- try:
+ if format == "html":
+ fig.add_trace(
+ go.Scatter(
+ x=plot_frequencies, y=np.median(fd_waveforms, axis=0),
+ fill=None,
+ mode='lines', line_color='crimson',
+ opacity=1,
+ name="Median reconstructed",
+ legendgroup='median',
+ ),
+ row=1,
+ col=1,
+ )
+ fig.add_trace(
+ go.Scatter(
+ x=plot_frequencies, y=np.percentile(fd_waveforms, lower_percentile, axis=0),
+ fill=None,
+ mode='lines',
+ line_color='crimson',
+ opacity=0.1,
+ name="{:.2f}% credible interval".format(upper_percentile - lower_percentile),
+ legendgroup='uncertainty',
+ ),
+ row=1,
+ col=1,
+ )
+ fig.add_trace(
+ go.Scatter(
+ x=plot_frequencies, y=np.percentile(fd_waveforms, upper_percentile, axis=0),
+ fill='tonexty',
+ mode='lines',
+ line_color='crimson',
+ opacity=0.1,
+ name="{:.2f}% credible interval".format(upper_percentile - lower_percentile),
+ legendgroup='uncertainty',
+ showlegend=False,
+ ),
+ row=1,
+ col=1,
+ )
+ fig.add_trace(
+ go.Scatter(
+ x=plot_times, y=np.median(td_waveforms, axis=0),
+ fill=None,
+ mode='lines', line_color='crimson',
+ opacity=1,
+ name="Median reconstructed",
+ legendgroup='median',
+ showlegend=False,
+ ),
+ row=2,
+ col=1,
+ )
+ fig.add_trace(
+ go.Scatter(
+ x=plot_times, y=np.percentile(td_waveforms, lower_percentile, axis=0),
+ fill=None,
+ mode='lines',
+ line_color='crimson',
+ opacity=0.1,
+ name="{:.2f}% credible interval".format(upper_percentile - lower_percentile),
+ legendgroup='uncertainty',
+ showlegend=False,
+ ),
+ row=2,
+ col=1,
+ )
+ fig.add_trace(
+ go.Scatter(
+ x=plot_times, y=np.percentile(td_waveforms, upper_percentile, axis=0),
+ fill='tonexty',
+ mode='lines',
+ line_color='crimson',
+ opacity=0.1,
+ name="{:.2f}% credible interval".format(upper_percentile - lower_percentile),
+ legendgroup='uncertainty',
+ showlegend=False,
+ ),
+ row=2,
+ col=1,
+ )
+ else:
axs[0].loglog(
plot_frequencies,
- asd_from_freq_series(
- interferometer.frequency_domain_strain[frequency_idxs],
- 1 / interferometer.strain_data.duration),
- color='b', label='Data', alpha=0.3)
- axs[0].loglog(
+ np.median(fd_waveforms, axis=0), color='r', label='Median')
+ axs[0].fill_between(
plot_frequencies,
- interferometer.amplitude_spectral_density_array[frequency_idxs],
- color='b', label='PSD')
+ np.percentile(fd_waveforms, lower_percentile, axis=0),
+ np.percentile(fd_waveforms, upper_percentile, axis=0),
+ color='r', label='{} % Interval'.format(
+ int(upper_percentile - lower_percentile)),
+ alpha=0.3)
axs[1].plot(
- plot_times, infft(
- interferometer.whitened_frequency_domain_strain,
- sampling_frequency=interferometer.strain_data.sampling_frequency)[time_idxs],
- color='b', alpha=0.3)
+ plot_times, np.median(td_waveforms, axis=0),
+ color='r')
+ axs[1].fill_between(
+ plot_times, np.percentile(
+ td_waveforms, lower_percentile, axis=0),
+ np.percentile(td_waveforms, upper_percentile, axis=0), color='r',
+ alpha=0.3)
+
+ try:
+ if format == "html":
+ fig.add_trace(
+ go.Scatter(
+ x=plot_frequencies,
+ y=asd_from_freq_series(
+ interferometer.frequency_domain_strain[frequency_idxs],
+ 1 / interferometer.strain_data.duration
+ ),
+ fill=None,
+ mode='lines', line_color='darkblue',
+ opacity=0.5,
+ name="Data",
+ legendgroup='data',
+ ),
+ row=1,
+ col=1,
+ )
+ fig.add_trace(
+ go.Scatter(
+ x=plot_frequencies,
+ y=interferometer.amplitude_spectral_density_array[frequency_idxs],
+ fill=None,
+ mode='lines', line_color='darkblue',
+ opacity=0.8,
+ name="ASD",
+ legendgroup='asd',
+ ),
+ row=1,
+ col=1,
+ )
+ fig.add_trace(
+ go.Scatter(
+ x=plot_times,
+ y=infft(
+ interferometer.whitened_frequency_domain_strain,
+ sampling_frequency=interferometer.strain_data.sampling_frequency)[time_idxs],
+ fill=None,
+ mode='lines', line_color='darkblue',
+ opacity=0.5,
+ name="Data",
+ legendgroup='data',
+ showlegend=False,
+ ),
+ row=2,
+ col=1,
+ )
+ else:
+ axs[0].loglog(
+ plot_frequencies,
+ asd_from_freq_series(
+ interferometer.frequency_domain_strain[frequency_idxs],
+ 1 / interferometer.strain_data.duration),
+ color='b', label='Data', alpha=0.3)
+ axs[0].loglog(
+ plot_frequencies,
+ interferometer.amplitude_spectral_density_array[frequency_idxs],
+ color='b', label='PSD')
+ axs[1].plot(
+ plot_times, infft(
+ interferometer.whitened_frequency_domain_strain,
+ sampling_frequency=interferometer.strain_data.sampling_frequency)[time_idxs],
+ color='b', alpha=0.3)
logger.debug('Plotted interferometer data.')
except AttributeError:
pass
- axs[0].set_xlim(interferometer.minimum_frequency,
- interferometer.maximum_frequency)
- axs[1].set_xlim(start_time, end_time)
+ if format == "html":
+ fig.update_xaxes(title_text="Frequency [Hz]", type="log", row=1)
+ fig.update_xaxes(title_text="Time [s] - {}".format(
+ interferometer.strain_data.start_time), type="linear", row=2)
+ fig.update_yaxes(
+ title_text="$\mathrm{ASD}\,\left[\mathrm{Hz}^{-1/2}\\right]$", type="log", row=1)
+ fig.update_yaxes(title_text="Whitened Strain", type="linear", row=2)
+ else:
+ axs[0].set_xlim(interferometer.minimum_frequency,
+ interferometer.maximum_frequency)
+ axs[1].set_xlim(start_time, end_time)
- axs[0].set_xlabel('$f$ [$Hz$]')
- axs[1].set_xlabel('$t$ [$s$]')
- axs[0].set_ylabel('$\\tilde{h}(f)$ [Hz$^{-\\frac{1}{2}}$]')
- axs[1].set_ylabel('Whitened strain')
- axs[0].legend(loc='lower left')
+ axs[0].set_xlabel('$f$ [$Hz$]')
+ axs[1].set_xlabel('$t$ [$s$]')
+ axs[0].set_ylabel('$\\tilde{h}(f)$ [Hz$^{-\\frac{1}{2}}$]')
+ axs[1].set_ylabel('Whitened strain')
+ axs[0].legend(loc='lower left')
- plt.tight_layout()
if save:
filename = os.path.join(
self.outdir,
self.label + '_{}_waveform.{}'.format(
interferometer.name, format))
- plt.savefig(filename, format=format, dpi=600)
+ if format == 'html':
+ plot(fig, filename=filename, include_mathjax='cdn', auto_open=False)
+ else:
+ plt.savefig(filename, format=format, dpi=600)
+ plt.close()
logger.debug("Figure saved to {}".format(filename))
- plt.close()
else:
return fig
diff --git a/optional_requirements.txt b/optional_requirements.txt
index 243f6563c97a0fa6c40b01fd0282340fc8bc65f7..cd16a99f5eef1d8839dffb60db9623b4771b04e3 100644
--- a/optional_requirements.txt
+++ b/optional_requirements.txt
@@ -2,3 +2,4 @@ astropy
lalsuite
gwpy
theano
+plotly