def _replot(self):
self.TracePlot = Plot(self.plot_data, width=500, height=500, resizable='hv')
self.TracePlot.legend.align = 'll'
n=0
if self.c_enable0:
self.TracePlot.plot(('t','y0'), type='line', color='blue', name='channel 0')
n+=1
if self.c_enable1:
self.TracePlot.plot(('t','y1'), type='line', color='red', name='channel 1')
n+=1
if self.c_enable2:
self.TracePlot.plot(('t','y2'), type='line', color='green', name='channel 2')
n+=1
if self.c_enable3:
self.TracePlot.plot(('t','y3'), type='line', color='black', name='channel 3')
n+=1
if self.c_enable4:
self.TracePlot.plot(('t','y4'), type='line', color='blue', name='channel 4')
n+=1
if self.c_enable5:
self.TracePlot.plot(('t','y5'), type='line', color='red', name='channel 5')
n+=1
if self.c_enable6:
self.TracePlot.plot(('t','y6'), type='line', color='green', name='channel 6')
n+=1
if self.c_enable7:
self.TracePlot.plot(('t','y7'), type='line', color='black', name='channel 7')
if n > 1:
self.TracePlot.legend.visible = True
else:
self.TracePlot.legend.visible = False
def _create_plot(self):
plot_data = ArrayPlotData(image=self.image)
plot = Plot(plot_data, width=500, height=500, resizable='hv', aspect_ratio=1.0, padding=8, padding_left=32, padding_bottom=32)
plot.img_plot('image', colormap=RdBu_r, xbounds=(self.X[0],self.X[-1]), ybounds=(self.Y[0],self.Y[-1]), name='image')
image = plot.plots['image'][0]
image.x_mapper.domain_limits = (self.imager.get_x_range()[0],self.imager.get_x_range()[1])
image.y_mapper.domain_limits = (self.imager.get_y_range()[0],self.imager.get_y_range()[1])
zoom = AspectZoomTool(image, enable_wheel=False)
cursor = CursorTool2D(image, drag_button='left', color='yellow', marker_size=1.0, line_width=1.0 )
image.overlays.append(cursor)
image.overlays.append(zoom)
colormap = image.color_mapper
colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
color_mapper=colormap,
plot=plot,
orientation='v',
resizable='v',
width=16,
height=320,
padding=8,
padding_left=32)
container = HPlotContainer()
container.add(plot)
container.add(colorbar)
z_label = PlotLabel(text='z=0.0', color='red', hjustify='left', vjustify='bottom', position=[10,10])
container.overlays.append(z_label)
container.tools.append(SaveTool(container))
self.plot_data = plot_data
self.scan_plot = image
self.cursor = cursor
self.zoom = zoom
self.figure = plot
self.figure_container = container
self.sync_trait('z_label_text', z_label, 'text')
def _create_line_plot(self):
line_data = ArrayPlotData(current=np.array(()), frequency=np.array(()),)
plot = Plot(line_data, padding=8, padding_left=64, padding_bottom=36)
plot.plot(('current','frequency'), color='blue', name='zeeman')
plot.index_axis.title = 'current [mA]'
plot.value_axis.title = 'frequency [MHz]'
plot.tools.append(SaveTool(plot))
self.line_data = line_data
self.line_plot = plot
def _figure_image_default(self):
plot = Plot(self.plot_data_image,
width=100,
height=100,
padding=8,
padding_left=48,
padding_bottom=32)
plot.img_plot('image', colormap=RdBu_r, name='image')
plot.aspect_ratio = 1
plot.index_mapper.domain_limits = (self.imager.get_x_range()[0],
self.imager.get_x_range()[1])
plot.value_mapper.domain_limits = (self.imager.get_y_range()[0],
self.imager.get_y_range()[1])
plot_fit = Plot(self.plot_data_image,
width=100,
height=100,
padding=8,
padding_left=48,
padding_bottom=32)
plot_fit.img_plot('fit', colormap=RdBu_r, name='fit')
plot_fit.aspect_ratio = 1
plot_fit.index_mapper.domain_limits = (self.imager.get_x_range()[0],
self.imager.get_x_range()[1])
plot_fit.value_mapper.domain_limits = (self.imager.get_y_range()[0],
self.imager.get_y_range()[1])
container = HPlotContainer()
image = plot.plots['image'][0]
colormap = image.color_mapper
colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
color_mapper=colormap,
plot=plot,
orientation='v',
resizable='v',
width=16,
height=320,
padding=8,
padding_left=32)
container = HPlotContainer()
container.add(plot)
container.add(plot_fit)
container.add(colorbar)
container.overlays.append(self.image_label)
container.tools.append(SaveTool(container))
return container
def _create_line_plot(self):
line_data = ArrayPlotData(
index=np.array((0, 1)),
spin_state=np.array((0, 0)),
)
plot = Plot(line_data, padding=8, padding_left=64, padding_bottom=36)
plot.plot(('index', 'spin_state'), color='blue', name='spin_state')
plot.index_axis.title = 'time [micro s]'
plot.value_axis.title = 'spin state'
plot.tools.append(SaveTool(plot))
self.line_data = line_data
self.line_plot = plot
def _figure_line_default(self):
plot = Plot(self.plot_data_line,
width=100,
height=100,
padding=8,
padding_left=64,
padding_bottom=32)
plot.plot(('x', 'y'), color='blue')
plot.plot(('x', 'fit'), color='red')
plot.index_axis.title = 'z [micron]'
plot.value_axis.title = 'Fluorescence [ counts / s ]'
plot.tools.append(SaveTool(plot))
return plot
def _create_matrix_plot(self):
matrix_data = ArrayPlotData(image=np.zeros((2, 2)))
matrix_plot = Plot(matrix_data,
padding=8,
padding_left=64,
padding_bottom=32)
matrix_plot.index_axis.title = 'time bins'
matrix_plot.value_axis.title = 'tau'
matrix_plot.img_plot('image',
xbounds=(self.tau[0], self.tau[-1]),
ybounds=(0, self.n_lines),
colormap=Spectral)
matrix_plot.tools.append(SaveTool(matrix_plot))
self.matrix_data = matrix_data
self.matrix_plot = matrix_plot
def _create_pulse_plot(self):
pulse_data = ArrayPlotData(x=np.array((0., 100)), y=np.array((0, 1)))
plot = Plot(pulse_data, padding=8, padding_left=64, padding_bottom=36)
line = plot.plot(('x', 'y'), style='line', color='blue',
name='data')[0]
plot.index_axis.title = 'time bins'
plot.value_axis.title = 'intensity'
edge_marker = LinePlot(
index=ArrayDataSource(np.array((0, 0))),
value=ArrayDataSource(np.array((0, 1e9))),
color='red',
index_mapper=LinearMapper(range=plot.index_range),
value_mapper=LinearMapper(range=plot.value_range),
name='marker')
plot.add(edge_marker)
plot.tools.append(SaveTool(plot))
self.pulse_data = pulse_data
self.pulse_plot = plot
def _create_line_plot(self):
line_data = ArrayPlotData(index=np.array((0, 1)),
spin_state=np.array((0, 0)),
fit=np.array((0, 0)))
plot = Plot(line_data, padding=8, padding_left=64, padding_bottom=36)
plot.plot(('index', 'spin_state'), color='blue', name='spin_state')
plot.plot(('index', 'fit'), color='red', name='fit')
plot.index_axis.title = 'time [micro s]'
plot.value_axis.title = 'spin state'
plot.overlays.insert(
0,
PlotLabel(text=self.label_text,
hjustify='left',
vjustify='bottom',
position=[64, 32]))
plot.tools.append(SaveTool(plot))
self.line_data = line_data
self.line_plot = plot
def _create_matrix_plot(self):
matrix_data = ArrayPlotData(image=np.zeros((2, 2)))
plot = Plot(matrix_data,
width=500,
height=500,
resizable='hv',
padding=8,
padding_left=48,
padding_bottom=36)
plot.index_axis.title = 'time [ns]'
plot.value_axis.title = 'laser pulse #'
plot.img_plot('image',
xbounds=(0, 1),
ybounds=(0, 1),
colormap=Spectral)[0]
plot.tools.append(SaveTool(plot))
self.matrix_data = matrix_data
self.matrix_plot = plot
def _create_line_plot(self):
line_data = ArrayPlotData(index=np.array((0, 1)),
counts=np.array((0, 0)),
pulse_indices=np.array((0, 0)),
pulse_values=np.array((0, 0)))
plot = Plot(line_data, padding=8, padding_left=64, padding_bottom=36)
plot.plot(('index', 'counts'), color='blue', name='counts')
plot.plot(('pulse_indices', 'pulse_values'),
type='scatter',
marker='circle',
color='none',
outline_color='red',
line_width=1.0,
name='pulses')
plot.index_axis.title = 'time [ns]'
plot.value_axis.title = 'spin state'
#plot.overlays.insert(0, PlotLabel(text=self.label_text, hjustify='left', vjustify='bottom', position=[64,32]) )
self.line_data = line_data
self.line_plot = plot
def _figure_drift_default(self):
plot = Plot(self.plot_data_drift,
width=100,
height=100,
padding=8,
padding_left=64,
padding_bottom=32)
plot.plot(('t', 'x'), type='line', color='blue', name='x')
plot.plot(('t', 'y'), type='line', color='red', name='y')
plot.plot(('t', 'z'), type='line', color='green', name='z')
bottom_axis = PlotAxis(
plot,
orientation="bottom",
tick_generator=ScalesTickGenerator(scale=CalendarScaleSystem()))
plot.index_axis = bottom_axis
plot.index_axis.title = 'time'
plot.value_axis.title = 'drift [micron]'
plot.legend.visible = True
plot.tools.append(SaveTool(plot))
return plot
def _create_plot(self):
plot_data = ArrayPlotData(image=self.image)
plot = Plot(plot_data,
width=500,
height=500,
resizable='hv',
aspect_ratio=1.0,
padding=8,
padding_left=32,
padding_bottom=32)
plot.img_plot('image',
colormap=jet,
xbounds=(self.X[0], self.X[-1]),
ybounds=(self.Y[0], self.Y[-1]),
name='image')
image = plot.plots['image'][0]
bwplot_data = ArrayPlotData(bwimage=self.bwimage)
bwplot = Plot(bwplot_data,
width=500,
height=500,
resizable='hv',
aspect_ratio=1.0,
padding=8,
padding_left=32,
padding_bottom=32)
bwplot.img_plot('bwimage',
colormap=jet,
xbounds=(self.X[0], self.X[-1]),
ybounds=(self.Y[0], self.Y[-1]),
name='bwimage')
bwimage = bwplot.plots['bwimage'][0]
image.x_mapper.domain_limits = (self.confocal.scanner.getXRange()[0],
self.confocal.scanner.getXRange()[1])
image.y_mapper.domain_limits = (self.confocal.scanner.getYRange()[0],
self.confocal.scanner.getYRange()[1])
bwimage.x_mapper.domain_limits = (self.confocal.scanner.getXRange()[0],
self.confocal.scanner.getXRange()[1])
bwimage.y_mapper.domain_limits = (self.confocal.scanner.getYRange()[0],
self.confocal.scanner.getYRange()[1])
colormap = image.color_mapper
colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
color_mapper=colormap,
plot=plot,
orientation='v',
resizable='v',
width=16,
height=320,
padding=8,
padding_left=32)
container = HPlotContainer()
container.add(plot)
container.add(colorbar)
container.add(bwplot)
container.tools.append(SaveTool(container))
self.plot_data = plot_data
self.scan_plot = image
self.figure = plot
self.bwplot_data = bwplot_data
self.bwscan_plot = bwimage
self.bwfigure = bwplot
self.figure_container = container
def _create_plot(self):
plot_data = ArrayPlotData(image=self.image)
plot = Plot(plot_data,
width=500,
height=500,
resizable='hv',
aspect_ratio=1.0,
padding=8,
padding_left=32,
padding_bottom=32)
plot.img_plot('image',
colormap=jet,
xbounds=(self.X[0], self.X[-1]),
ybounds=(self.Y[0], self.Y[-1]),
name='image')
image = plot.plots['image'][0]
fitplot_data = ArrayPlotData(fitimage=self.fitimage)
fitplot = Plot(fitplot_data,
width=500,
height=500,
resizable='hv',
aspect_ratio=1.0,
padding=8,
padding_left=32,
padding_bottom=32)
fitplot.img_plot('fitimage',
colormap=jet,
xbounds=(self.Xfit[0], self.Xfit[-1]),
ybounds=(self.Yfit[0], self.Yfit[-1]),
name='fitimage')
fitplot.overlays.insert(
0,
PlotLabel(text=self.label_text,
hjustify='right',
vjustify='bottom',
position=[880, 590]))
fitimage = fitplot.plots['fitimage'][0]
image.x_mapper.domain_limits = (self.confocal.scanner.getXRange()[0],
self.confocal.scanner.getXRange()[1])
image.y_mapper.domain_limits = (self.confocal.scanner.getYRange()[0],
self.confocal.scanner.getYRange()[1])
fitimage.x_mapper.domain_limits = (
self.confocal.scanner.getXRange()[0],
self.confocal.scanner.getXRange()[1])
fitimage.y_mapper.domain_limits = (
self.confocal.scanner.getYRange()[0],
self.confocal.scanner.getYRange()[1])
colormap = image.color_mapper
colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
color_mapper=colormap,
plot=plot,
orientation='v',
resizable='v',
width=16,
height=320,
padding=8,
padding_left=32)
container = HPlotContainer()
container.add(plot)
container.add(colorbar)
container.add(fitplot)
container.tools.append(SaveTool(container))
self.plot_data = plot_data
self.scan_plot = image
self.figure = plot
self.fitplot_data = fitplot_data
self.fitscan_plot = fitimage
self.fitfigure = fitplot
self.figure_container = container
def _TracePlot_default(self):
plot = Plot(self.plot_data, width=500, height=500, resizable='hv')
plot.plot(('t', 'y0'), type='line', color='black')
plot.tools.append(SaveTool(plot))
return plot
