def _create_plot(self, max, min, dataobj, title):
x = dataobj[:, 0]
y = dataobj[:, 1]
if y.max() > max:
max = y.max()
if y.min() < min:
min = y.min()
if self.sample_size > 1:
y2 = dataobj[:, 6]
y3 = dataobj[:, 7]
if y3.max() > max:
max = y3.max()
if y2.min() < min:
min = y2.min()
plotdata = ArrayPlotData(x=x, y=y, y2=y2, y3=y3)
else:
plotdata = ArrayPlotData(x=x, y=y)
plot = Plot(plotdata)
plot.plot(("x", "y"), type="line", color="blue")
if self.sample_size > 1:
plot.plot(("x", "y2"), type="line", color="red")
plot.plot(("x", "y3"), type="line", color="red")
# plot.padding_right = 45
# plot.padding_left = 25
# plot.padding_top = 25
# plot.padding_bottom = 25
plot.title = title
plot.title_font = "Arial 10"
return plot, max, min
def _create_plot(self, max, min, dataobj, title):
x = dataobj[:,0]
y = dataobj[:,1]
if y.max()>max:
max = y.max()
if y.min()<min:
min = y.min()
if self.sample_size>1:
y2 = dataobj[:,6]
y3 = dataobj[:,7]
if y3.max()>max:
max = y3.max()
if y2.min()<min:
min = y2.min()
plotdata = ArrayPlotData(x=x, y=y, y2=y2, y3=y3)
else:
plotdata = ArrayPlotData(x=x, y=y)
plot = Plot(plotdata)
plot.plot(("x", "y"), type="line", color="blue")
if self.sample_size>1:
plot.plot(("x", "y2"), type="line", color="red")
plot.plot(("x", "y3"), type="line", color="red")
plot.title = title
plot.title_font = 'Arial 10'
return plot, max, min
def create_hplot(self, key=None, mini=False):
if mini:
hpc = HPlotContainer(bgcolor='darkgrey',
height=MINI_HEIGHT,
resizable='h',
padding=HPLOT_PADDING
)
else:
hpc = HPlotContainer(bgcolor='lightgrey',
padding=HPLOT_PADDING,
resizable='hv'
)
# make slice plot for showing intesity profile of main plot
#************************************************************
slice_plot = Plot(self.data,
width=SLICE_PLOT_WIDTH,
orientation="v",
resizable="v",
padding=MAIN_PADDING,
padding_left=MAIN_PADDING_LEFT,
padding_bottom=MAIN_PADDING_BOTTOM,
bgcolor='beige',
origin='top left'
)
mini_slice = Plot(self.data,
width=SLICE_PLOT_WIDTH,
orientation="v",
resizable="v",
padding=MAIN_PADDING,
padding_left=MAIN_PADDING_LEFT,
padding_bottom=MAIN_PADDING_BOTTOM,
bgcolor='beige',
origin='top left'
)
slice_plot.x_axis.visible = True
slice_key = key + '_slice'
ydata_key = key + '_y'
slice_plot.plot((ydata_key, slice_key), name=slice_key)
# make plot to show line at depth of cursor. y values constant
slice_depth_key = key + '_depth'
slice_plot.plot(('slice_depth_depth', 'slice_depth_y'),
name=slice_depth_key, color='red')
self.update_slice_depth_line_plot(slice_plot, depth=0)
# make main plot for editing depth lines
#************************************************************
main = Plot(self.data,
border_visible=True,
bgcolor='beige',
origin='top left',
padding=MAIN_PADDING,
padding_left=MAIN_PADDING_LEFT,
padding_bottom=MAIN_PADDING_BOTTOM
)
if mini:
#main.padding = MINI_PADDING
main.padding_bottom = MINI_PADDING_BOTTOM
# add intensity img to plot and get reference for line inspector
#************************************************************
img_plot = main.img_plot(key, name=key,
xbounds=self.model.xbounds[key],
ybounds=self.model.ybounds[key],
colormap=self._cmap
)[0]
# add line plots: use method since these may change
#************************************************************
self.update_line_plots(key, main, update=True)
self.plot_mask_array(key, main)
# set slice plot index range to follow main plot value range
#************************************************************
slice_plot.index_range = main.value_range
# add vertical core lines to main plots and slices
#************************************************************
# save pos and distance in session dict for view info and control
for core in self.model.core_samples:
# add boundarys to slice plot
self.plot_core_depths(slice_plot, core, ref_depth_line=None)
# add positions to main plots
self.plot_core(main, core, ref_depth_line=None)
# now add tools depending if it is a mini plot or not
#************************************************************
if mini:
# add range selection tool only
# first add a reference line to attach it to
reference = self.make_reference_plot()
main.add(reference)
main.plots['reference'] = [reference]
# attache range selector to this plot
range_tool = RangeSelection(reference)
reference.tools.append(range_tool)
range_overlay = RangeSelectionOverlay(reference,
metadata_name="selections")
reference.overlays.append(range_overlay)
range_tool.on_trait_change(self._range_selection_handler,
"selection")
# add zoombox to mini plot
main.plot(('zoombox_x', 'zoombox_y'), type='polygon',
face_color=ZOOMBOX_COLOR, alpha=ZOOMBOX_ALPHA)
# add to hplot and dict
hpc.add(main, mini_slice)
self.hplot_dict['mini'] = hpc
else:
# add zoom tools
zoom = ZoomTool(main, tool_mode='box', axis='both', alpha=0.5,
drag_button="left")
main.tools.append(zoom)
main.overlays.append(zoom)
self.zoom_tools[key] = zoom
main.value_mapper.on_trait_change(self.zoom_all_value, 'updated')
main.index_mapper.on_trait_change(self.zoom_all_index, 'updated')
# add line inspector and attach to freeze tool
#*********************************************
line_inspector = LineInspector(component=img_plot,
axis='index_x',
inspect_mode="indexed",
is_interactive=True,
write_metadata=True,
metadata_name='x_slice',
is_listener=True,
color="white")
img_plot.overlays.append(line_inspector)
self.inspector_freeze_tool.tool_set.add(line_inspector)
# add listener for changes to metadata made by line inspector
#************************************************************
img_plot.on_trait_change(self.metadata_changed, 'index.metadata')
# set slice plot index range to follow main plot value range
#************************************************************
slice_plot.index_range = main.value_range
# add clickable legend ; must update legend when depth_dict updated
#******************************************************************
legend = Legend(component=main, padding=0,
align="ur", font='modern 8')
legend_highlighter = LegendHighlighter(legend,
drag_button="right")
legend.tools.append(legend_highlighter)
self.legend_dict[key] = [legend, legend_highlighter]
self.update_legend_plots(legend, main)
legend.visible = False
main.overlays.append(legend)
legend_highlighter.on_trait_change(self.legend_moved, '_drag_state')
# add pan tool
pan_tool = PanTool(main, drag_button="right")
main.tools.append(pan_tool)
self.pan_tool_dict[key] = pan_tool
# add main and slice plot to hplot container and dict
#****************************************************
main.title = 'frequency = {} kHz'.format(key)
main.title_font = TITLE_FONT
hpc.add(main, slice_plot)
self.hplot_dict[key] = hpc
return hpc
def create_hplot(self, key=None, mini=False):
if mini:
hpc = HPlotContainer(bgcolor='darkgrey',
height=MINI_HEIGHT,
resizable='h',
padding=0)
else:
hpc = HPlotContainer(bgcolor='lightgrey',
padding=HPLOT_PADDING,
resizable='hv')
# make slice plot for showing intesity profile of main plot
#************************************************************
slice_plot = Plot(self.data,
width=SLICE_PLOT_WIDTH,
orientation="v",
resizable="v",
padding=MAIN_PADDING,
padding_left=MAIN_PADDING_LEFT,
bgcolor='beige',
origin='top left')
slice_plot.x_axis.visible = False
slice_key = key + '_slice'
ydata_key = key + '_y'
slice_plot.plot((ydata_key, slice_key), name=slice_key)
# make main plot for editing depth lines
#************************************************************
main = Plot(
self.data,
border_visible=True,
bgcolor='beige',
origin='top left',
padding=MAIN_PADDING,
padding_left=MAIN_PADDING_LEFT,
)
if mini:
main.padding = MINI_PADDING
# add intensity img to plot and get reference for line inspector
#************************************************************
img_plot = main.img_plot(key,
name=key,
xbounds=self.model.xbounds[key],
ybounds=self.model.ybounds[key],
colormap=self._cmap)[0]
# add line plots: use method since these may change
#************************************************************
self.update_line_plots(key, main, update=True)
# set slice plot index range to follow main plot value range
#************************************************************
slice_plot.index_range = main.value_range
# add vertical core lines to main plots and slices
#************************************************************
# save pos and distance in session dict for view info and control
for core in self.model.core_samples:
loc_index, loc, dist = self.model.core_info_dict[core.core_id]
# add boundarys to slice plot
ref_line = self.model.final_lake_depth
self.plot_core_depths(slice_plot, core, ref_line, loc_index)
# add positions to main plots
self.plot_core(main, core, ref_line, loc_index, loc)
# now add tools depending if it is a mini plot or not
#************************************************************
if mini:
# add range selection tool only
# first add a reference line to attach it to
reference = self.make_reference_plot()
main.add(reference)
# attache range selector to this plot
range_tool = RangeSelection(reference)
reference.tools.append(range_tool)
range_overlay = RangeSelectionOverlay(reference,
metadata_name="selections")
reference.overlays.append(range_overlay)
range_tool.on_trait_change(self._range_selection_handler,
"selection")
# add zoombox to mini plot
main.plot(('zoombox_x', 'zoombox_y'),
type='polygon',
face_color=ZOOMBOX_COLOR,
alpha=ZOOMBOX_ALPHA)
# add to hplot and dict
hpc.add(main)
self.hplot_dict['mini'] = hpc
else:
# add zoom tools
main.tools.append(PanTool(main))
zoom = ZoomTool(main, tool_mode='box', axis='both', alpha=0.5)
main.tools.append(zoom)
main.overlays.append(zoom)
main.value_mapper.on_trait_change(self.zoom_all_value, 'updated')
main.index_mapper.on_trait_change(self.zoom_all_index, 'updated')
# add line inspector and attach to freeze tool
#*********************************************
line_inspector = LineInspector(component=img_plot,
axis='index_x',
inspect_mode="indexed",
is_interactive=True,
write_metadata=True,
metadata_name='x_slice',
is_listener=True,
color="white")
img_plot.overlays.append(line_inspector)
self.inspector_freeze_tool.tool_set.add(line_inspector)
# add listener for changes to metadata made by line inspector
#************************************************************
img_plot.on_trait_change(self.metadata_changed, 'index.metadata')
# set slice plot index range to follow main plot value range
#************************************************************
slice_plot.index_range = main.value_range
# add clickable legend ; must update legend when depth_dict updated
#******************************************************************
legend = Legend(component=main,
padding=0,
align="ur",
font='modern 8')
legend_highlighter = LegendHighlighter(legend, drag_button="right")
legend.tools.append(legend_highlighter)
self.update_legend_plots(legend, main)
legend.visible = False
self.legend_dict[key] = [legend, legend_highlighter]
main.overlays.append(legend)
# add main and slice plot to hplot container and dict
#****************************************************
main.title = 'frequency = {} kHz'.format(key)
main.title_font = TITLE_FONT
hpc.add(main, slice_plot)
self.hplot_dict[key] = hpc
return hpc