def _plot(self, x, y, z, scale):
self.data_x, self.data_z, self.scale = x, z, scale
if self.container.components:
self.colors = map(lambda plot: plot.color, self.container.components)
if self.last_flip_order != self.flip_order:
self.colors.reverse()
self.container.remove(*self.container.components)
# Use a custom renderer so plot lines are clickable
self.chaco_plot = Plot(self.data,
renderer_map={ 'line': ClickableLinePlot })
self.chaco_plot.bgcolor = 'white'
self.value_mapper = None
self.index_mapper = None
if len(self.data_x) == len(self.colors):
colors = self.colors[:]
else:
colors = ['black'] * len(self.data_x)
if self.flip_order:
z = z[::-1]
spacing = (z.max(axis=1) - z.min(axis=1)).min() * self.value_range
offset = spacing * self.offset
for i, (x_row, z_row) in enumerate(zip(x, z)):
self.data.set_data('data_x_' + str(i), x_row)
self.data.set_data('data_y_offset_' + str(i), z_row * self.value_range + offset * i)
plots = self.chaco_plot.plot(('data_x_' + str(i), 'data_y_offset_' + str(i)), color=colors[i], type='line')
plot = plots[0]
self.container.add(plot)
# Required for double-clicking plots
plot.index.sort_order = 'ascending'
plot.value.sort_order = 'ascending'
if self.value_mapper is None:
self.index_mapper = plot.index_mapper
self.value_mapper = plot.value_mapper
else:
plot.value_mapper = self.value_mapper
self.value_mapper.range.add(plot.value)
plot.index_mapper = self.index_mapper
self.index_mapper.range.add(plot.index)
range = self.value_mapper.range
range.high = (range.high - range.low) * self.value_range + range.low
self.x_axis.mapper = self.index_mapper
self.y_axis.mapper = self.value_mapper
self.y_axis.title = 'Normalized intensity (%s)' % \
get_value_scale_label(scale)
self.zoom_tool = ClickUndoZoomTool(
plot, tool_mode="box", always_on=True, pointer="cross",
drag_button=settings.zoom_button,
undo_button=settings.undo_button,
)
plot.overlays.append(self.zoom_tool)
self.last_flip_order = self.flip_order
return self.container
def _plot(self, x, y, z, scale):
self.data_x, self.data_z, self.scale = x, z, scale
if self.container.components:
self.colors = map(lambda plot: plot.color, self.container.components)
if self.last_flip_order != self.flip_order:
self.colors.reverse()
self.container.remove(*self.container.components)
# Use a custom renderer so plot lines are clickable
self.chaco_plot = Plot(self.data, renderer_map={"line": ClickableLinePlot})
self.chaco_plot.bgcolor = "white"
self.value_mapper = None
self.index_mapper = None
if len(self.data_x) == len(self.colors):
colors = self.colors[:]
else:
colors = ["black"] * len(self.data_x)
if self.flip_order:
z = z[::-1]
spacing = (z.max(axis=1) - z.min(axis=1)).min() * self.value_range
offset = spacing * self.offset
for i, (x_row, z_row) in enumerate(zip(x, z)):
self.data.set_data("data_x_" + str(i), x_row)
self.data.set_data("data_y_offset_" + str(i), z_row * self.value_range + offset * i)
plots = self.chaco_plot.plot(("data_x_" + str(i), "data_y_offset_" + str(i)), color=colors[i], type="line")
plot = plots[0]
self.container.add(plot)
# Required for double-clicking plots
plot.index.sort_order = "ascending"
plot.value.sort_order = "ascending"
if self.value_mapper is None:
self.index_mapper = plot.index_mapper
self.value_mapper = plot.value_mapper
else:
plot.value_mapper = self.value_mapper
self.value_mapper.range.add(plot.value)
plot.index_mapper = self.index_mapper
self.index_mapper.range.add(plot.index)
range = self.value_mapper.range
range.high = (range.high - range.low) * self.value_range + range.low
self.x_axis.mapper = self.index_mapper
self.y_axis.mapper = self.value_mapper
self.y_axis.title = "Normalized intensity (%s)" % get_value_scale_label(scale)
self.zoom_tool = ClickUndoZoomTool(
plot,
tool_mode="box",
always_on=True,
pointer="cross",
drag_button=settings.zoom_button,
undo_button=settings.undo_button,
)
plot.overlays.append(self.zoom_tool)
self.last_flip_order = self.flip_order
return self.container
def _setup_plot_tools(self, plot):
"""Sets up the background, and several tools on a plot"""
plot.bgcolor = "white"
# The ZoomTool tool is stateful and allows drawing a zoom
# box to select a zoom region.
self.zoom_tool = ClickUndoZoomTool(plot,
#self.zoom_tool = ZoomTool(plot,
x_min_zoom_factor=-inf, y_min_zoom_factor=-inf,
tool_mode="box", always_on=True,
drag_button=settings.zoom_button,
# undo_button=settings.undo_button,
zoom_to_mouse=True)
# The PanTool allows panning around the plot
self.pan_tool = KeyboardPanTool(plot, drag_button=settings.pan_button,
history_tool=self.zoom_tool)
plot.tools.append(self.pan_tool)
plot.overlays.append(self.zoom_tool)
x_crossline = LineInspector(component=plot,
axis='index_x',
inspect_mode="indexed",
is_listener=False,
draw_mode='overlay',
color="grey")
y_crossline = LineInspector(component=plot,
axis='index_y',
inspect_mode="indexed",
color="grey",
draw_mode='overlay',
is_listener=False)
plot.overlays.append(x_crossline)
plot.overlays.append(y_crossline)
self.crosslines = (x_crossline, y_crossline)
# The RangeSelectionTool tool is stateful and allows selection of a candidate
# range for dataseries alignment.
# plot.overlays.append(RangeSelectionOverlay(component=plot))
tool = SimpleInspectorTool(plot)
plot.tools.append(tool)
overlay = SimpleInspectorOverlay(component=plot, inspector=tool, align="lr")
def formatter(**kw):
return '(%.2f, %.2f)' % (kw['x'], kw['y'])
overlay.field_formatters = [[formatter]]
overlay.alternate_position = (-25, -25)
plot.overlays.append(overlay)
self.pointer_tool = PointerControlTool(component=plot, pointer='arrow')
plot.tools.append(self.pointer_tool)
def __init__(self, *args, **kwargs):
self.pairs = [
DatasetPair(first=d1, second=d2)
for d1, d2 in kwargs['dataset_pairs']
]
self.pairs.sort(key=lambda pair: pair.first.name)
self.range = kwargs.pop('range')
super(PeakFitWindow, self).__init__(*args, **kwargs)
self.table_editor.on_select = self._selection_changed
self.selected = self.pairs[0] if self.pairs else None
self.data = ArrayPlotData()
self.plot = Plot(self.data)
self.zoom_tool = ClickUndoZoomTool(self.plot,
tool_mode="box",
always_on=True,
drag_button=settings.zoom_button,
undo_button=settings.undo_button,
zoom_to_mouse=True)
self.plot.overlays.append(self.zoom_tool)
for pair in self.pairs:
self._plot_dataset(pair.first)
self._plot_dataset(pair.second, offset=pair.peak_diff)
self.plot.request_redraw()
class StackedPlot(ChacoPlot):
offset = Range(0.0, 1.0, 0.015)
value_range = Range(0.01, 1.05, 1.00)
flip_order = Bool(False)
def _get_traits_group(self):
return VGroup(
HGroup(Item("flip_order"), Item("offset"), Item("value_range")),
UItem("component", editor=ComponentEditor()),
)
def __init__(self):
super(StackedPlot, self).__init__()
self.container = OverlayPlotContainer(
bgcolor="white", use_backbuffer=True, border_visible=True, padding=50, padding_left=110, fill_padding=True
)
self.data = ArrayPlotData()
self.chaco_plot = None
self.value_mapper = None
self.index_mapper = None
self.x_axis = PlotAxis(
component=self.container,
orientation="bottom",
title=u"Angle (2\u0398)",
title_font=settings.axis_title_font,
tick_label_font=settings.tick_font,
)
y_axis_title = "Normalized intensity (%s)" % get_value_scale_label("linear")
self.y_axis = PlotAxis(
component=self.container,
orientation="left",
title=y_axis_title,
title_font=settings.axis_title_font,
tick_label_font=settings.tick_font,
)
self.container.overlays.extend([self.x_axis, self.y_axis])
self.container.tools.append(TraitsTool(self.container, classes=[LinePlot, PlotAxis]))
self.colors = []
self.last_flip_order = self.flip_order
@on_trait_change("offset, value_range, flip_order")
def _replot_data(self):
self._plot(self.data_x, None, self.data_z, self.scale)
self.container.request_redraw()
def _prepare_data(self, datasets):
interpolate = True
stack = stack_datasets(datasets)
if interpolate:
(x, z) = interpolate_datasets(stack, points=4800)
x = array([x] * len(datasets))
else:
x, z = map(np.transpose, np.transpose(stack))
return x, None, z
def _plot(self, x, y, z, scale):
self.data_x, self.data_z, self.scale = x, z, scale
if self.container.components:
self.colors = map(lambda plot: plot.color, self.container.components)
if self.last_flip_order != self.flip_order:
self.colors.reverse()
self.container.remove(*self.container.components)
# Use a custom renderer so plot lines are clickable
self.chaco_plot = Plot(self.data, renderer_map={"line": ClickableLinePlot})
self.chaco_plot.bgcolor = "white"
self.value_mapper = None
self.index_mapper = None
if len(self.data_x) == len(self.colors):
colors = self.colors[:]
else:
colors = ["black"] * len(self.data_x)
if self.flip_order:
z = z[::-1]
spacing = (z.max(axis=1) - z.min(axis=1)).min() * self.value_range
offset = spacing * self.offset
for i, (x_row, z_row) in enumerate(zip(x, z)):
self.data.set_data("data_x_" + str(i), x_row)
self.data.set_data("data_y_offset_" + str(i), z_row * self.value_range + offset * i)
plots = self.chaco_plot.plot(("data_x_" + str(i), "data_y_offset_" + str(i)), color=colors[i], type="line")
plot = plots[0]
self.container.add(plot)
# Required for double-clicking plots
plot.index.sort_order = "ascending"
plot.value.sort_order = "ascending"
if self.value_mapper is None:
self.index_mapper = plot.index_mapper
self.value_mapper = plot.value_mapper
else:
plot.value_mapper = self.value_mapper
self.value_mapper.range.add(plot.value)
plot.index_mapper = self.index_mapper
self.index_mapper.range.add(plot.index)
range = self.value_mapper.range
range.high = (range.high - range.low) * self.value_range + range.low
self.x_axis.mapper = self.index_mapper
self.y_axis.mapper = self.value_mapper
self.y_axis.title = "Normalized intensity (%s)" % get_value_scale_label(scale)
self.zoom_tool = ClickUndoZoomTool(
plot,
tool_mode="box",
always_on=True,
pointer="cross",
drag_button=settings.zoom_button,
undo_button=settings.undo_button,
)
plot.overlays.append(self.zoom_tool)
self.last_flip_order = self.flip_order
return self.container
def _reset_view(self):
self.zoom_tool.revert_history_all()
def _plot(self, x, y, z, scale):
pd = ArrayPlotData()
pd.set_data("imagedata", z)
plot = Plot(pd, padding_left=60, fill_padding=True)
plot.bgcolor = "white"
cmap = fix(jet, (0, z.max()))
origin = "bottom left" # origin = 'top left' # to flip y-axis
plot.img_plot(
"imagedata",
name="surface2d",
xbounds=(np.min(x), np.max(x)),
ybounds=(1.0, y[-1, -1]),
colormap=cmap,
hide_grids=True,
interpolation="nearest",
origin=origin,
)
plot.default_origin = origin
plot.x_axis.title = u"Angle (2\u0398)"
tick_font = settings.tick_font
plot.x_axis.title_font = settings.axis_title_font
plot.y_axis.title_font = settings.axis_title_font
plot.x_axis.tick_label_font = tick_font
plot.y_axis.tick_label_font = tick_font
plot.y_axis.title = "Dataset"
plot.y_axis.tick_interval = 1.0
actual_plot = plot.plots["surface2d"][0]
self.plot_zoom_tool = ClickUndoZoomTool(
plot,
tool_mode="box",
always_on=True,
pointer="cross",
drag_button=settings.zoom_button,
undo_button=settings.undo_button,
x_min_zoom_factor=-np.inf,
y_min_zoom_factor=-np.inf,
)
plot.overlays.append(self.plot_zoom_tool)
plot.tools.append(TraitsTool(plot))
# Add a color bar
colormap = actual_plot.color_mapper
colorbar = ColorBar(
index_mapper=LinearMapper(range=colormap.range),
color_mapper=colormap,
plot=actual_plot,
orientation="v",
resizable="v",
width=30,
padding=40,
padding_top=50,
fill_padding=True,
)
colorbar._axis.title_font = settings.axis_title_font
colorbar._axis.tick_label_font = settings.tick_font
# Add pan and zoom tools to the colorbar
self.colorbar_zoom_tool = ClickUndoZoomTool(
colorbar,
axis="index",
tool_mode="range",
always_on=True,
drag_button=settings.zoom_button,
undo_button=settings.undo_button,
)
pan_tool = PanToolWithHistory(
colorbar,
history_tool=self.colorbar_zoom_tool,
constrain_direction="y",
constrain=True,
drag_button=settings.pan_button,
)
colorbar.tools.append(pan_tool)
colorbar.overlays.append(self.colorbar_zoom_tool)
# Add a label to the top of the color bar
colorbar_label = PlotLabel(
u"Intensity\n{:^9}".format("(" + get_value_scale_label(scale) + ")"),
component=colorbar,
font=settings.axis_title_font,
)
colorbar.overlays.append(colorbar_label)
colorbar.tools.append(TraitsTool(colorbar))
# Add the plot and colorbar side-by-side
container = HPlotContainer(use_backbuffer=True)
container.add(plot)
container.add(colorbar)
return container
class StackedPlot(ChacoPlot):
offset = Range(0.0, 1.0, 0.015)
value_range = Range(0.01, 1.05, 1.00)
flip_order = Bool(False)
def _get_traits_group(self):
return VGroup(
HGroup(
Item('flip_order'),
Item('offset'),
Item('value_range'),
),
UItem('component', editor=ComponentEditor()),
)
def __init__(self):
super(StackedPlot, self).__init__()
self.container = OverlayPlotContainer(bgcolor='white',
use_backbuffer=True,
border_visible=True,
padding=50,
padding_left=110,
fill_padding=True
)
self.data = ArrayPlotData()
self.chaco_plot = None
self.value_mapper = None
self.index_mapper = None
self.x_axis = MyPlotAxis(component=self.container,
orientation='bottom',
title=u'Angle (2\u0398)',
title_font=settings.axis_title_font,
tick_label_font=settings.tick_font)
y_axis_title = 'Normalized intensity (%s)' % get_value_scale_label('linear')
self.y_axis = MyPlotAxis(component=self.container,
orientation='left',
title=y_axis_title,
title_font=settings.axis_title_font,
tick_label_font=settings.tick_font)
self.container.overlays.extend([self.x_axis, self.y_axis])
self.container.tools.append(
TraitsTool(self.container, classes=[LinePlot,MyPlotAxis]))
self.colors = []
self.last_flip_order = self.flip_order
@on_trait_change('offset, value_range, flip_order')
def _replot_data(self):
self._plot(self.data_x, None, self.data_z, self.scale)
self.container.request_redraw()
# def _prepare_data(self, datasets):
def _prepare_data(self, stack):
# stack = stack_datasets(datasets)
x = stack[:,:,0]
z = stack[:,:,2]
return x, None, z
def _plot(self, x, y, z, scale):
self.data_x, self.data_z, self.scale = x, z, scale
if self.container.components:
self.colors = map(lambda plot: plot.color, self.container.components)
if self.last_flip_order != self.flip_order:
self.colors.reverse()
self.container.remove(*self.container.components)
# Use a custom renderer so plot lines are clickable
self.chaco_plot = Plot(self.data,
renderer_map={ 'line': ClickableLinePlot })
self.chaco_plot.bgcolor = 'white'
self.value_mapper = None
self.index_mapper = None
if len(self.data_x) == len(self.colors):
colors = self.colors[:]
else:
colors = ['black'] * len(self.data_x)
if self.flip_order:
z = z[::-1]
spacing = (z.max(axis=1) - z.min(axis=1)).min() * self.value_range
offset = spacing * self.offset
for i, (x_row, z_row) in enumerate(zip(x, z)):
self.data.set_data('data_x_' + str(i), x_row)
self.data.set_data('data_y_offset_' + str(i), z_row * self.value_range + offset * i)
plots = self.chaco_plot.plot(('data_x_' + str(i), 'data_y_offset_' + str(i)), color=colors[i], type='line')
plot = plots[0]
self.container.add(plot)
# Required for double-clicking plots
plot.index.sort_order = 'ascending'
plot.value.sort_order = 'ascending'
if self.value_mapper is None:
self.index_mapper = plot.index_mapper
self.value_mapper = plot.value_mapper
else:
plot.value_mapper = self.value_mapper
self.value_mapper.range.add(plot.value)
plot.index_mapper = self.index_mapper
self.index_mapper.range.add(plot.index)
range = self.value_mapper.range
range.high = (range.high - range.low) * self.value_range + range.low
self.x_axis.mapper = self.index_mapper
self.y_axis.mapper = self.value_mapper
self.y_axis.title = 'Normalized intensity (%s)' % \
get_value_scale_label(scale)
self.zoom_tool = ClickUndoZoomTool(
plot, tool_mode="box", always_on=True, pointer="cross",
drag_button=settings.zoom_button,
undo_button=settings.undo_button,
)
plot.overlays.append(self.zoom_tool)
self.last_flip_order = self.flip_order
return self.container
def _reset_view(self):
self.zoom_tool.revert_history_all()
def _plot(self, x, y, z, scale):
pd = ArrayPlotData()
# pd.set_data("imagedata", z)
plot = Plot(pd, padding_left=60, fill_padding=True)
plot.bgcolor = 'white'
cmap = fix(jet, (0, z.max()))
plot.default_origin = 'bottom left' # origin = 'top left' # to flip y-axis
fid = FunctionImageData(func=self._prepare_data_for_window, data_range=plot.range2d)
pd.set_data("imagedata", fid)
self.img_plot = plot.img_plot("imagedata", name="surface2d",
xbounds=(np.min(x), np.max(x)),
ybounds=(1.0, y[-1,-1]),
colormap=cmap, hide_grids=True, interpolation='nearest'
# origin=origin,
)[0]
#plot.default_origin = origin
plot.x_axis = MyPlotAxis(component=plot, orientation='bottom')
plot.y_axis = MyPlotAxis(component=plot, orientation='left')
plot.x_axis.title = u'Angle (2\u0398)'
tick_font = settings.tick_font
plot.x_axis.title_font = settings.axis_title_font
plot.y_axis.title_font = settings.axis_title_font
plot.x_axis.tick_label_font = tick_font
plot.y_axis.tick_label_font = tick_font
plot.y_axis.title = "Dataset"
# if <10 datasets we want to reduce down the tickmarks to multiples
if len(y)<10:
plot.y_axis.tick_interval = 1.0
else:
plot.y_axis.tick_interval = len(y)/10
actual_plot = plot.plots["surface2d"][0]
self.plot_zoom_tool = ClickUndoZoomTool(
plot, always_on=True, pointer="cross",
tool_mode="range",
axis="index",
drag_button=settings.zoom_button,
undo_button=settings.undo_button,
x_min_zoom_factor=-np.inf, y_min_zoom_factor=-np.inf,
)
plot.overlays.append(self.plot_zoom_tool)
plot.tools.append(TraitsTool(plot))
# Add a color bar
colormap = actual_plot.color_mapper
colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
color_mapper=colormap,
plot=actual_plot,
orientation='v',
resizable='v',
width=30,
padding=40,
padding_top=50,
fill_padding=True)
colorbar._axis.title_font = settings.axis_title_font
colorbar._axis.tick_label_font = settings.tick_font
# Add pan and zoom tools to the colorbar
self.colorbar_zoom_tool = ClickUndoZoomTool(colorbar,
axis="index",
tool_mode="range",
always_on=True,
drag_button=settings.zoom_button,
undo_button=settings.undo_button)
pan_tool = PanToolWithHistory(colorbar,
history_tool=self.colorbar_zoom_tool,
constrain_direction="y", constrain=True,
drag_button=settings.pan_button)
colorbar.tools.append(pan_tool)
colorbar.overlays.append(self.colorbar_zoom_tool)
# Add a label to the top of the color bar
colorbar_label = PlotLabel(
u'Intensity\n{:^9}'.format('(' + get_value_scale_label(scale) + ')'),
component=colorbar,
font=settings.axis_title_font,
)
colorbar.overlays.append(colorbar_label)
colorbar.tools.append(TraitsTool(colorbar))
# Add the plot and colorbar side-by-side
container = HPlotContainer(use_backbuffer=True)
container.add(plot)
container.add(colorbar)
self.twod_plot = plot
return container
class Surface2DPlot(ChacoPlot):
# The chaco window is updated based on the current zoom level as described here
# http://www.digipedia.pl/usenet/thread/15882/127/
# and here:
# http://blog.powersoffour.org/2d-data-visualization-of-amr-with-matplotlib
# and here:
# http://svn.enzotools.org/yt/trunk/yt/extensions/image_panner/pan_and_scan_widget.py
twod_plot = Instance(Component)
img_plot = Instance(Component)
sidelength = Int(1000)
# def _prepare_data(self, datasets):
def _prepare_data(self, stack):
'''
This is called as the 2d chaco plot window is being set up. The return values
are not used for plotting but are used for getting the tick marker scales and
colorbar scale.
I bin it down to a small arbitrary number of bins to keep things fast.
'''
self.update_content = True
self.loop1 = True
# stack = stack_datasets(datasets)
self.dataset_stack = stack
BINS = 4
xi, yi, zi = bin_data(stack, BINS)
return xi, yi, zi
def _prepare_data_for_window(self, xlow, xhigh, ylow, yhigh):
'''
This is called every time the chaco window is rendered and it dynamically
computes and returns the data corresponding to the window limits. This allows
rendering to stay relatively fast since data is binned down to a resolution
roughly matching what the window can usefully display.
'''
#if not self.update_content:
if not self.loop1:
return self.zi
stack = self.dataset_stack.copy()
# deal with restricted y-range
if ylow < 1 or ylow >= yhigh:
ylow = 1
if yhigh > stack.shape[0] or yhigh <= ylow:
yhigh = stack.shape[0]
stack = stack[int(np.round(ylow-1)):int(np.round(yhigh))]
if stack[0,0,0] > stack[0,-1,0]:
stack = stack[:,::-1,:]
# get a typical interval
interval = np.median(np.diff(stack[0,:10,0]))
# get a region a couple of samples bigger on each side of the window to allow for
# misalignment
xs = stack[:,:,0]
xlow_expanded = xs[0,0] - interval*2
xhigh_expanded = xs[0,-1] + interval*2
column_mask = (xs[0]>=xlow_expanded) & (xs[0]<=xhigh_expanded)
stack = stack[:,column_mask][np.newaxis].reshape(xs.shape[0],-1,3)
# regrid all rows - use an interval half that of the original interval to minimise interpolation errors
first_row = regrid_data(stack[0], start=xlow_expanded, end=xhigh_expanded, interval=interval/2)
new_stack = np.empty((xs.shape[0], first_row.shape[0], 3))
new_stack[0] = first_row
for i, stack_row in enumerate(stack[1:]):
new_stack[i+1] = regrid_data(stack_row, start=xlow_expanded, end=xhigh_expanded, interval=interval/2)
# new_stack is the regridded version so window it properly
xs = new_stack[:,:,0]
zs = new_stack[:,:,1]
mask = (xs[0]>=xlow) & (xs[0]<=xhigh)
zs = zs[:,mask].reshape(zs.shape[0],-1)
YBINS = zs.shape[0]*10
BINS = min(5000, zs.shape[1])
zi = congrid(zs, (YBINS, BINS), method='neighbour', minusone=True)
zi = np.clip(zi, 1, zi.max())
self.zi = zi
self.loop1=False
return zi
@on_trait_change('twod_plot.range2d.updated')
def _update_ranges(self):
self.update_content = not self.update_content
if self.img_plot is not None:
low_xy = self.twod_plot.range2d.low
high_xy = self.twod_plot.range2d.high
self.img_plot.index.set_data(
np.linspace(low_xy[0], high_xy[0], self.sidelength),
np.linspace(low_xy[1], high_xy[1], self.sidelength),
('ascending', 'ascending'),
)
def _plot(self, x, y, z, scale):
pd = ArrayPlotData()
# pd.set_data("imagedata", z)
plot = Plot(pd, padding_left=60, fill_padding=True)
plot.bgcolor = 'white'
cmap = fix(jet, (0, z.max()))
plot.default_origin = 'bottom left' # origin = 'top left' # to flip y-axis
fid = FunctionImageData(func=self._prepare_data_for_window, data_range=plot.range2d)
pd.set_data("imagedata", fid)
self.img_plot = plot.img_plot("imagedata", name="surface2d",
xbounds=(np.min(x), np.max(x)),
ybounds=(1.0, y[-1,-1]),
colormap=cmap, hide_grids=True, interpolation='nearest'
# origin=origin,
)[0]
#plot.default_origin = origin
plot.x_axis = MyPlotAxis(component=plot, orientation='bottom')
plot.y_axis = MyPlotAxis(component=plot, orientation='left')
plot.x_axis.title = u'Angle (2\u0398)'
tick_font = settings.tick_font
plot.x_axis.title_font = settings.axis_title_font
plot.y_axis.title_font = settings.axis_title_font
plot.x_axis.tick_label_font = tick_font
plot.y_axis.tick_label_font = tick_font
plot.y_axis.title = "Dataset"
# if <10 datasets we want to reduce down the tickmarks to multiples
if len(y)<10:
plot.y_axis.tick_interval = 1.0
else:
plot.y_axis.tick_interval = len(y)/10
actual_plot = plot.plots["surface2d"][0]
self.plot_zoom_tool = ClickUndoZoomTool(
plot, always_on=True, pointer="cross",
tool_mode="range",
axis="index",
drag_button=settings.zoom_button,
undo_button=settings.undo_button,
x_min_zoom_factor=-np.inf, y_min_zoom_factor=-np.inf,
)
plot.overlays.append(self.plot_zoom_tool)
plot.tools.append(TraitsTool(plot))
# Add a color bar
colormap = actual_plot.color_mapper
colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
color_mapper=colormap,
plot=actual_plot,
orientation='v',
resizable='v',
width=30,
padding=40,
padding_top=50,
fill_padding=True)
colorbar._axis.title_font = settings.axis_title_font
colorbar._axis.tick_label_font = settings.tick_font
# Add pan and zoom tools to the colorbar
self.colorbar_zoom_tool = ClickUndoZoomTool(colorbar,
axis="index",
tool_mode="range",
always_on=True,
drag_button=settings.zoom_button,
undo_button=settings.undo_button)
pan_tool = PanToolWithHistory(colorbar,
history_tool=self.colorbar_zoom_tool,
constrain_direction="y", constrain=True,
drag_button=settings.pan_button)
colorbar.tools.append(pan_tool)
colorbar.overlays.append(self.colorbar_zoom_tool)
# Add a label to the top of the color bar
colorbar_label = PlotLabel(
u'Intensity\n{:^9}'.format('(' + get_value_scale_label(scale) + ')'),
component=colorbar,
font=settings.axis_title_font,
)
colorbar.overlays.append(colorbar_label)
colorbar.tools.append(TraitsTool(colorbar))
# Add the plot and colorbar side-by-side
container = HPlotContainer(use_backbuffer=True)
container.add(plot)
container.add(colorbar)
self.twod_plot = plot
return container
def _reset_view(self):
self.plot_zoom_tool.revert_history_all()
self.colorbar_zoom_tool.revert_history_all()
self.update_content = True
class StackedPlot(ChacoPlot):
offset = Range(0.0, 1.0, 0.015)
value_range = Range(0.01, 1.05, 1.00)
flip_order = Bool(False)
def _get_traits_group(self):
return VGroup(
HGroup(
Item('flip_order'),
Item('offset'),
Item('value_range'),
),
UItem('component', editor=ComponentEditor()),
)
def __init__(self):
super(StackedPlot, self).__init__()
self.container = OverlayPlotContainer(bgcolor='white',
use_backbuffer=True,
border_visible=True,
padding=50,
padding_left=110,
fill_padding=True
)
self.data = ArrayPlotData()
self.chaco_plot = None
self.value_mapper = None
self.index_mapper = None
self.x_axis = PlotAxis(component=self.container,
orientation='bottom',
title=u'Angle (2\u0398)',
title_font=settings.axis_title_font,
tick_label_font=settings.tick_font)
y_axis_title = 'Normalized intensity (%s)' % get_value_scale_label('linear')
self.y_axis = PlotAxis(component=self.container,
orientation='left',
title=y_axis_title,
title_font=settings.axis_title_font,
tick_label_font=settings.tick_font)
self.container.overlays.extend([self.x_axis, self.y_axis])
self.container.tools.append(
TraitsTool(self.container, classes=[LinePlot,PlotAxis]))
self.colors = []
self.last_flip_order = self.flip_order
@on_trait_change('offset, value_range, flip_order')
def _replot_data(self):
self._plot(self.data_x, None, self.data_z, self.scale)
self.container.request_redraw()
def _prepare_data(self, datasets):
interpolate = True
stack = stack_datasets(datasets)
if interpolate:
(x, z) = interpolate_datasets(stack, points=4800)
x = array([x] * len(datasets))
else:
x, z = map(np.transpose, np.transpose(stack))
return x, None, z
def _plot(self, x, y, z, scale):
self.data_x, self.data_z, self.scale = x, z, scale
if self.container.components:
self.colors = map(lambda plot: plot.color, self.container.components)
if self.last_flip_order != self.flip_order:
self.colors.reverse()
self.container.remove(*self.container.components)
# Use a custom renderer so plot lines are clickable
self.chaco_plot = Plot(self.data,
renderer_map={ 'line': ClickableLinePlot })
self.chaco_plot.bgcolor = 'white'
self.value_mapper = None
self.index_mapper = None
if len(self.data_x) == len(self.colors):
colors = self.colors[:]
else:
colors = ['black'] * len(self.data_x)
if self.flip_order:
z = z[::-1]
spacing = (z.max(axis=1) - z.min(axis=1)).min() * self.value_range
offset = spacing * self.offset
for i, (x_row, z_row) in enumerate(zip(x, z)):
self.data.set_data('data_x_' + str(i), x_row)
self.data.set_data('data_y_offset_' + str(i), z_row * self.value_range + offset * i)
plots = self.chaco_plot.plot(('data_x_' + str(i), 'data_y_offset_' + str(i)), color=colors[i], type='line')
plot = plots[0]
self.container.add(plot)
# Required for double-clicking plots
plot.index.sort_order = 'ascending'
plot.value.sort_order = 'ascending'
if self.value_mapper is None:
self.index_mapper = plot.index_mapper
self.value_mapper = plot.value_mapper
else:
plot.value_mapper = self.value_mapper
self.value_mapper.range.add(plot.value)
plot.index_mapper = self.index_mapper
self.index_mapper.range.add(plot.index)
range = self.value_mapper.range
range.high = (range.high - range.low) * self.value_range + range.low
self.x_axis.mapper = self.index_mapper
self.y_axis.mapper = self.value_mapper
self.y_axis.title = 'Normalized intensity (%s)' % \
get_value_scale_label(scale)
self.zoom_tool = ClickUndoZoomTool(
plot, tool_mode="box", always_on=True, pointer="cross",
drag_button=settings.zoom_button,
undo_button=settings.undo_button,
)
plot.overlays.append(self.zoom_tool)
self.last_flip_order = self.flip_order
return self.container
def _reset_view(self):
self.zoom_tool.revert_history_all()
def _plot(self, x, y, z, scale):
pd = ArrayPlotData()
pd.set_data("imagedata", z)
plot = Plot(pd, padding_left=60, fill_padding=True)
plot.bgcolor = 'white'
cmap = fix(jet, (0, z.max()))
origin = 'bottom left' # origin = 'top left' # to flip y-axis
plot.img_plot("imagedata", name="surface2d",
xbounds=(np.min(x), np.max(x)),
ybounds=(1.0, y[-1,-1]),
colormap=cmap, hide_grids=True, interpolation='nearest',
origin=origin,
)
plot.default_origin = origin
plot.x_axis.title = u'Angle (2\u0398)'
tick_font = settings.tick_font
plot.x_axis.title_font = settings.axis_title_font
plot.y_axis.title_font = settings.axis_title_font
plot.x_axis.tick_label_font = tick_font
plot.y_axis.tick_label_font = tick_font
plot.y_axis.title = "Dataset"
plot.y_axis.tick_interval = 1.0
actual_plot = plot.plots["surface2d"][0]
self.plot_zoom_tool = ClickUndoZoomTool(
plot, tool_mode="box", always_on=True, pointer="cross",
drag_button=settings.zoom_button,
undo_button=settings.undo_button,
x_min_zoom_factor=-np.inf, y_min_zoom_factor=-np.inf,
)
plot.overlays.append(self.plot_zoom_tool)
plot.tools.append(TraitsTool(plot))
# Add a color bar
colormap = actual_plot.color_mapper
colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
color_mapper=colormap,
plot=actual_plot,
orientation='v',
resizable='v',
width=30,
padding=40,
padding_top=50,
fill_padding=True)
colorbar._axis.title_font = settings.axis_title_font
colorbar._axis.tick_label_font = settings.tick_font
# Add pan and zoom tools to the colorbar
self.colorbar_zoom_tool = ClickUndoZoomTool(colorbar,
axis="index",
tool_mode="range",
always_on=True,
drag_button=settings.zoom_button,
undo_button=settings.undo_button)
pan_tool = PanToolWithHistory(colorbar,
history_tool=self.colorbar_zoom_tool,
constrain_direction="y", constrain=True,
drag_button=settings.pan_button)
colorbar.tools.append(pan_tool)
colorbar.overlays.append(self.colorbar_zoom_tool)
# Add a label to the top of the color bar
colorbar_label = PlotLabel(
u'Intensity\n{:^9}'.format('(' + get_value_scale_label(scale) + ')'),
component=colorbar,
font=settings.axis_title_font,
)
colorbar.overlays.append(colorbar_label)
colorbar.tools.append(TraitsTool(colorbar))
# Add the plot and colorbar side-by-side
container = HPlotContainer(use_backbuffer=True)
container.add(plot)
container.add(colorbar)
return container
class Surface2DPlot(ChacoPlot):
# The chaco window is updated based on the current zoom level as described here
# http://www.digipedia.pl/usenet/thread/15882/127/
# and here:
# http://blog.powersoffour.org/2d-data-visualization-of-amr-with-matplotlib
# and here:
# http://svn.enzotools.org/yt/trunk/yt/extensions/image_panner/pan_and_scan_widget.py
twod_plot = Instance(Component)
img_plot = Instance(Component)
sidelength = Int(1000)
# def _prepare_data(self, datasets):
def _prepare_data(self, stack):
'''
This is called as the 2d chaco plot window is being set up. The return values
are not used for plotting but are used for getting the tick marker scales and
colorbar scale.
I bin it down to a small arbitrary number of bins to keep things fast.
'''
self.update_content = True
self.loop1 = True
# stack = stack_datasets(datasets)
self.dataset_stack = stack
BINS = 4
xi, yi, zi = bin_data(stack, BINS)
return xi, yi, zi
def _prepare_data_for_window(self, xlow, xhigh, ylow, yhigh):
'''
This is called every time the chaco window is rendered and it dynamically
computes and returns the data corresponding to the window limits. This allows
rendering to stay relatively fast since data is binned down to a resolution
roughly matching what the window can usefully display.
'''
#if not self.update_content:
if not self.loop1:
return self.zi
stack = self.dataset_stack.copy()
# deal with restricted y-range
if ylow < 1 or ylow >= yhigh:
ylow = 1
if yhigh > stack.shape[0] or yhigh <= ylow:
yhigh = stack.shape[0]
stack = stack[int(np.round(ylow - 1)):int(np.round(yhigh))]
if stack[0, 0, 0] > stack[0, -1, 0]:
stack = stack[:, ::-1, :]
# get a typical interval
interval = np.median(np.diff(stack[0, :10, 0]))
# get a region a couple of samples bigger on each side of the window to allow for
# misalignment
xs = stack[:, :, 0]
xlow_expanded = xs[0, 0] - interval * 2
xhigh_expanded = xs[0, -1] + interval * 2
column_mask = (xs[0] >= xlow_expanded) & (xs[0] <= xhigh_expanded)
stack = stack[:, column_mask][np.newaxis].reshape(xs.shape[0], -1, 3)
# regrid all rows - use an interval half that of the original interval to minimise interpolation errors
first_row = regrid_data(stack[0],
start=xlow_expanded,
end=xhigh_expanded,
interval=interval / 2)
new_stack = np.empty((xs.shape[0], first_row.shape[0], 3))
new_stack[0] = first_row
for i, stack_row in enumerate(stack[1:]):
new_stack[i + 1] = regrid_data(stack_row,
start=xlow_expanded,
end=xhigh_expanded,
interval=interval / 2)
# new_stack is the regridded version so window it properly
xs = new_stack[:, :, 0]
zs = new_stack[:, :, 1]
mask = (xs[0] >= xlow) & (xs[0] <= xhigh)
zs = zs[:, mask].reshape(zs.shape[0], -1)
YBINS = zs.shape[0] * 10
BINS = min(5000, zs.shape[1])
zi = congrid(zs, (YBINS, BINS), method='neighbour', minusone=True)
zi = np.clip(zi, 1, zi.max())
self.zi = zi
self.loop1 = False
return zi
@on_trait_change('twod_plot.range2d.updated')
def _update_ranges(self):
self.update_content = not self.update_content
if self.img_plot is not None:
low_xy = self.twod_plot.range2d.low
high_xy = self.twod_plot.range2d.high
self.img_plot.index.set_data(
np.linspace(low_xy[0], high_xy[0], self.sidelength),
np.linspace(low_xy[1], high_xy[1], self.sidelength),
('ascending', 'ascending'),
)
def _plot(self, x, y, z, scale):
pd = ArrayPlotData()
# pd.set_data("imagedata", z)
plot = Plot(pd, padding_left=60, fill_padding=True)
plot.bgcolor = 'white'
cmap = fix(jet, (0, z.max()))
plot.default_origin = 'bottom left' # origin = 'top left' # to flip y-axis
fid = FunctionImageData(func=self._prepare_data_for_window,
data_range=plot.range2d)
pd.set_data("imagedata", fid)
self.img_plot = plot.img_plot("imagedata",
name="surface2d",
xbounds=(np.min(x), np.max(x)),
ybounds=(1.0, y[-1, -1]),
colormap=cmap,
hide_grids=True,
interpolation='nearest'
# origin=origin,
)[0]
#plot.default_origin = origin
plot.x_axis = MyPlotAxis(component=plot, orientation='bottom')
plot.y_axis = MyPlotAxis(component=plot, orientation='left')
plot.x_axis.title = u'Angle (2\u0398)'
tick_font = settings.tick_font
plot.x_axis.title_font = settings.axis_title_font
plot.y_axis.title_font = settings.axis_title_font
plot.x_axis.tick_label_font = tick_font
plot.y_axis.tick_label_font = tick_font
plot.y_axis.title = "Dataset"
# if <10 datasets we want to reduce down the tickmarks to multiples
if len(y) < 10:
plot.y_axis.tick_interval = 1.0
else:
plot.y_axis.tick_interval = len(y) / 10
actual_plot = plot.plots["surface2d"][0]
self.plot_zoom_tool = ClickUndoZoomTool(
plot,
always_on=True,
pointer="cross",
tool_mode="range",
axis="index",
drag_button=settings.zoom_button,
undo_button=settings.undo_button,
x_min_zoom_factor=-np.inf,
y_min_zoom_factor=-np.inf,
)
plot.overlays.append(self.plot_zoom_tool)
plot.tools.append(TraitsTool(plot))
# Add a color bar
colormap = actual_plot.color_mapper
colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
color_mapper=colormap,
plot=actual_plot,
orientation='v',
resizable='v',
width=30,
padding=40,
padding_top=50,
fill_padding=True)
colorbar._axis.title_font = settings.axis_title_font
colorbar._axis.tick_label_font = settings.tick_font
# Add pan and zoom tools to the colorbar
self.colorbar_zoom_tool = ClickUndoZoomTool(
colorbar,
axis="index",
tool_mode="range",
always_on=True,
drag_button=settings.zoom_button,
undo_button=settings.undo_button)
pan_tool = PanToolWithHistory(colorbar,
history_tool=self.colorbar_zoom_tool,
constrain_direction="y",
constrain=True,
drag_button=settings.pan_button)
colorbar.tools.append(pan_tool)
colorbar.overlays.append(self.colorbar_zoom_tool)
# Add a label to the top of the color bar
colorbar_label = PlotLabel(
u'Intensity\n{:^9}'.format('(' + get_value_scale_label(scale) +
')'),
component=colorbar,
font=settings.axis_title_font,
)
colorbar.overlays.append(colorbar_label)
colorbar.tools.append(TraitsTool(colorbar))
# Add the plot and colorbar side-by-side
container = HPlotContainer(use_backbuffer=True)
container.add(plot)
container.add(colorbar)
self.twod_plot = plot
return container
def _reset_view(self):
self.plot_zoom_tool.revert_history_all()
self.colorbar_zoom_tool.revert_history_all()
self.update_content = True
