def _signals_plot_default(self):
print('_signals_plot_default')
"""Create the Plot instance."""
plot = Plot()
plot.add(self.signals_renderer)
x_axis = PlotAxis(component=plot,
mapper=self.signals_renderer.index_mapper,
orientation='bottom')
# y_axis = PlotAxis(component=plot,
# mapper=self.signals_renderer.value_mapper,
# orientation='left')
plot.overlays.extend([x_axis])
plot.origin_axis_visible = False
plot.padding_top = 0
plot.padding_left = 0
plot.padding_right = 0
plot.padding_bottom = 50
plot.border_visible = False
plot.bgcolor = "white"
plot.use_downsampling = True
return plot
def _plot_default(self):
data = self.data < self.limit
pd = self.pd = ArrayPlotData(imagedata=data,orig=self.data)
plot1 = Plot(pd, default_origin='top left')
plot2 = Plot(pd, default_origin='top left')
img_plot1 = plot1.img_plot("imagedata",colormap=gray,padding=0)[0]
img_plot2 = plot2.img_plot("orig",colormap=gray,padding=0)[0]
container = HPlotContainer(plot1,plot2)
container.spacing=0
plot1.padding_right=0
plot2.padding_left=0
plot2.y_axis.orientation= 'right'
return container
def __init__(self):
# Create the data and the PlotData object
x = linspace(-14, 14, 100)
y = sin(x) * x**3
plotdata = ArrayPlotData(x=x, y=y)
# Create the scatter plot
scatter = Plot(plotdata)
scatter.plot(("x", "y"), type="scatter", color="blue")
# Create the line plot
line = Plot(plotdata)
line.plot(("x", "y"), type="line", color="blue")
# Create a horizontal container and put the two plots inside it
container = HPlotContainer(scatter, line)
container.spacing = 0
scatter.padding_right = 0
line.padding_left = 0
line.y_axis.orientation = "right"
self.plot = container
def _plot_default(self):
# Create the data and the PlotData object
x = linspace(-14, 14, 100)
y = sin(x) * x**3
plotdata = ArrayPlotData(x = x, y = y)
# Create the scatter plot
scatter = Plot(plotdata)
scatter.plot(("x", "y"), type="scatter", color="blue")
# Create the line plot
line = Plot(plotdata)
line.plot(("x", "y"), type="line", color="blue")
# Create a horizontal container and put the two plots inside it
container = HPlotContainer(scatter, line)
container.spacing = 0
scatter.padding_right = 0
line.padding_left = 0
line.y_axis.orientation = "right"
return container
def _plot_default(self):
x = linspace(-14, 14, 100)
y = sin(x) * x**3
plotdata = ArrayPlotData(x=x, y=y)
scatter = Plot(plotdata)
scatter.plot(("x", "y"), type="scatter", color="blue")
line = Plot(plotdata)
line.plot(("x", "y"), type="line", color="blue")
container = HPlotContainer(scatter, line)
container.spacing = 0
scatter.padding_right = 0
line.padding_left = 0
line.y_axis_orientation = "right"
return container
def __init__(self):
super(ContainerExample, self).__init__()
x = linspace(-14, 14, 100)
y = sin(x) * x ** 3
plotdata = ArrayPlotData(x=x, y=y)
scatter = Plot(plotdata)
scatter.plot(("x", "y"), type="scatter", color="blue")
line = Plot(plotdata)
line.plot(("x", "y"), type="line", color="blue")
container = HPlotContainer(scatter, line)
#Making the plots touch in the middle
container.spacing = 0
scatter.padding_right = 0
line.padding_left = 0
line.y_axis.orientation = "right"
self.plot = container
def _create_plot_component():
army_lat = np.column_stack([army['start_lat'],
army['end_lat']]).reshape(-1)
army_lon = np.column_stack([army['start_lon'],
army['end_lon']]).reshape(-1)
plot_data = ArrayPlotData(
army_lon=army_lon,
army_lat=army_lat,
army_size=army['size'],
army_color=army['direction'] * army["group"],
towns_lat=towns['lat'],
towns_lon=towns['lon'],
towns=towns['town'],
temp_lon=temperatures['lon'],
temp=temperatures['temp'],
temp_date=temperatures['date'],
)
map_plot = Plot(plot_data)
map_plot.x_grid = None
map_plot.y_grid = None
map_plot.x_axis.orientation = 'top'
map_plot.x_axis.title = 'Longitude'
map_plot.y_axis.title = 'Latitude'
map_plot.title = "Minard's Map of Napoleon's Russian Campaign"
map_plot._title.overlay_position = "inside top"
map_plot._title.hjustify = "left"
map_plot._title.vjustify = "bottom"
map_plot.plot(
("army_lon", "army_lat", "army_color", "army_size"),
type="cmap_segment",
name="my_plot",
color_mapper=viridis,
border_visible=True,
bgcolor="white",
size_min=1.0,
size_max=128.0,
)
map_plot.plot(
("towns_lon", "towns_lat"),
type="scatter",
)
map_plot.plot(
("towns_lon", "towns_lat", "towns"),
type="text",
text_margin=4,
h_position='right',
text_offset=(4, 0),
)
map_plot.plot_1d(
('temp_lon'),
type='line_scatter_1d',
alpha=0.5,
line_style='dot',
)
map_plot.index_range.high_setting = 38
map_plot.index_range.low_setting = 23
map_plot.value_range.high_setting = 56.0
map_plot.value_range.low_setting = 53.5
map_plot.tools.extend([
PanTool(map_plot),
ZoomTool(map_plot),
])
temp_plot = Plot(plot_data, height=100)
temp_plot.index_range = map_plot.index_range
temp_plot.x_grid = None
temp_plot.x_axis = None
temp_plot.y_axis.orientation = 'right'
temp_plot.y_axis.title = u'Temp (°Re)'
temp_plot.plot(
('temp_lon', 'temp'),
type='line',
)
temp_plot.plot_1d(
('temp_lon'),
type='line_scatter_1d',
alpha=0.5,
line_style='dot',
)
temp_plot.plot_1d(
('temp_lon', 'temp_date'),
type='textplot_1d',
alpha=0.5,
line_style='dot',
alignment='bottom',
)
temp_plot.value_range.high_setting = 5
temp_plot.value_range.low_setting = -35
container = VPlotContainer(temp_plot, map_plot)
container.spacing = 0
map_plot.padding_bottom = 0
map_plot.padding_left = 70
map_plot.padding_right = 70
map_plot.padding_top = 50
temp_plot.padding_top = 0
temp_plot.padding_bottom = 15
temp_plot.padding_right = 70
temp_plot.padding_left = 70
temp_plot.height = 100
temp_plot.resizable = 'h'
return container
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
