def _plot_default(self):
self.data = self._data_default()
plot = Plot(self.data)
for ii, s_name in enumerate(self._samples):
color = COLORS[ii % len(self._samples)]
plot.plot(('bins',s_name), name=s_name,
type='filled_line',
edge_color=color,
face_color=color,
alpha=0.5,
bgcolor='white',
render_style='hold') # render_style determines whether interpolate
plot.index = plot._get_or_create_datasource('bins') #set index name manually so range selection works
plot.index_scale = 'log'
plot.title = 'Fermi Plot'
plot.padding = 50
plot.legend.visible = True
plot.tools.append(PanTool(plot))
plot.active_tool = RangeSelection(plot)
plot.overlays.append(RangeSelectionOverlay(component=plot))
zoom = ZoomTool(component=plot, tool_mode='box', always_on=False)
plot.overlays.append(zoom)
return plot
def _plot_default(self):
self.data = self._data_default()
plot = Plot(self.data)
for ii, s_name in enumerate(self._samples):
color = COLORS[ii % len(self._samples)]
plot.plot(
("bins", s_name),
name=s_name,
type="filled_line",
edge_color=color,
face_color=color,
alpha=0.5,
bgcolor="white",
render_style="hold",
) # render_style determines whether interpolate
plot.index = plot._get_or_create_datasource("bins") # set index name manually so range selection works
plot.index_scale = "log"
plot.title = "Fermi Plot"
plot.padding = 50
plot.legend.visible = True
plot.tools.append(PanTool(plot))
plot.active_tool = RangeSelection(plot)
plot.overlays.append(RangeSelectionOverlay(component=plot))
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
return plot
def _fft_plot_default(self):
plot = Plot(self.rms_data)
plot.index_range.low_setting = 1e3
plot.index_range.high_setting = 20e3
plot.value_range.low_setting = 10
plot.value_range.high_setting = 80
plot.plot(('frequency', 'psd'))
plot.index_scale = 'log'
return plot
def update_plots(self, waveforms, results):
mic_psd = db(psd(waveforms, self.model.fs, 'hanning')).mean(axis=0)
results['ref_mic_psd'] = mic_psd[1]
results['exp_mic_psd'] = mic_psd[0]
results['freq_psd'] = psd_freq(waveforms, self.model.fs)
result = MicToneCalibrationResult(**results)
frequency = results['frequency']
ds = ArrayPlotData(freq_psd=results['freq_psd'],
exp_mic_psd=results['exp_mic_psd'],
ref_mic_psd=results['ref_mic_psd'],
time=results['time'],
exp_mic_waveform=results['exp_mic_waveform'],
ref_mic_waveform=results['ref_mic_waveform'])
# Set up the waveform plot
container = HPlotContainer(bgcolor='white', padding=10)
plot = Plot(ds)
plot.plot(('time', 'ref_mic_waveform'), color='black')
plot.index_range.low_setting = self.model.trim
plot.index_range.high_setting = 5.0/frequency+self.model.trim
container.add(plot)
plot = Plot(ds)
plot.plot(('time', 'exp_mic_waveform'), color='red')
plot.index_range.low_setting = self.model.trim
plot.index_range.high_setting = 5.0/frequency+self.model.trim
container.add(plot)
result.waveform_plots = container
# Set up the spectrum plot
plot = Plot(ds)
plot.plot(('freq_psd', 'ref_mic_psd'), color='black')
plot.plot(('freq_psd', 'exp_mic_psd'), color='red')
plot.index_scale = 'log'
plot.title = 'Microphone response'
plot.padding = 50
plot.index_range.low_setting = 100
plot.tools.append(PanTool(plot))
zoom = ZoomTool(component=plot, tool_mode='box', always_on=False)
plot.overlays.append(zoom)
result.spectrum_plots = plot
# Plot the fundamental (i.e. the tone) and first even/odd harmonics
harmonic_container = HPlotContainer(resizable='hv', bgcolor='white',
fill_padding=True, padding=10)
for i in range(3):
f_harmonic = results['exp_harmonics'][i]['frequency']
plot = Plot(ds)
plot.plot(('freq_psd', 'ref_mic_psd'), color='black')
plot.plot(('freq_psd', 'exp_mic_psd'), color='red')
plot.index_range.low_setting = f_harmonic-500
plot.index_range.high_setting = f_harmonic+500
plot.origin_axis_visible = True
plot.padding_left = 10
plot.padding_right = 10
plot.border_visible = True
plot.title = 'F{}'.format(i+1)
harmonic_container.add(plot)
result.harmonic_plots = harmonic_container
self.model.tone_data.append(result)
# Update the master overview
self.model.measured_freq.append(results['frequency'])
self.model.measured_spl.append(results['output_spl'])
self.model.exp_mic_sens.append(results['exp_mic_sens'])
for mic in ('ref', 'exp'):
for h in range(3):
v = results['{}_harmonics'.format(mic)][h]['mic_rms']
name = 'measured_{}_f{}'.format(mic, h+1)
getattr(self.model, name).append(v)
v = results['{}_thd'.format(mic)]
getattr(self.model, 'measured_{}_thd'.format(mic)).append(v)
ds = ArrayPlotData(
frequency=self.model.measured_freq,
spl=self.model.measured_spl,
measured_exp_thd=self.model.measured_exp_thd,
measured_ref_thd=self.model.measured_ref_thd,
exp_mic_sens=self.model.exp_mic_sens,
)
container = VPlotContainer(padding=10, bgcolor='white',
fill_padding=True, resizable='hv')
plot = Plot(ds)
plot.plot(('frequency', 'spl'), color='black')
plot.plot(('frequency', 'spl'), color='black', type='scatter')
plot.index_scale = 'log'
plot.title = 'Speaker output (dB SPL)'
container.add(plot)
plot = Plot(ds)
plot.plot(('frequency', 'measured_ref_thd'), color='black')
plot.plot(('frequency', 'measured_ref_thd'), color='black', type='scatter')
plot.plot(('frequency', 'measured_exp_thd'), color='red')
plot.plot(('frequency', 'measured_exp_thd'), color='red', type='scatter')
plot.index_scale = 'log'
plot.title = 'Total harmonic distortion (frac)'
container.add(plot)
plot = Plot(ds)
plot.plot(('frequency', 'exp_mic_sens'), color='red')
plot.plot(('frequency', 'exp_mic_sens'), color='red', type='scatter')
plot.index_scale = 'log'
plot.title = 'Experiment mic. sensitivity V (dB re Pa)'
container.add(plot)
self.model.spl_plots = container
