def populate_plots(self):
self.screenplot = self.screen.img_plot("img",
xbounds="xbounds", ybounds="ybounds",
interpolation="nearest",
colormap=color_map_name_dict[self.colormap],
)[0]
self.set_invert()
self.grid = self.screenplot.index
self.gridm = self.screenplot.index_mapper
t = ImageInspectorTool(self.screenplot)
self.screen.tools.append(t)
self.screenplot.overlays.append(ImageInspectorOverlay(
component=self.screenplot, image_inspector=t,
border_size=0, bgcolor="transparent", align="ur",
tooltip_mode=False, font="modern 10"))
self.horiz.plot(("x", "imx"), type="line", color="red")
self.vert.plot(("y", "imy"), type="line", color="red")
self.horiz.plot(("x", "gx"), type="line", color="blue")
self.vert.plot(("y", "gy"), type="line", color="blue")
self.asum.plot(("a", "ima"), type="line", color="red")
self.bsum.plot(("b", "imb"), type="line", color="red")
self.asum.plot(("a", "ga"), type="line", color="blue")
self.bsum.plot(("b", "gb"), type="line", color="blue")
for p in [("ell1_x", "ell1_y"), ("ell3_x", "ell3_y"),
("a_x", "a_y"), ("b_x", "b_y")]:
self.screen.plot(p, type="line", color="green", alpha=.5)
for r, s in [("x", self.horiz), ("y", self.vert),
("a", self.asum), ("b", self.bsum)]:
for p in "0 p m".split():
q = ("%s%s_mark" % (r, p), "%s_bar" % r)
s.plot(q, type="line", color="green")
def setUp(self):
# Control the pixel size of the plot to know where the tiles are:
self.plot.bounds = [100, 100]
self.plot._window = self.create_mock_window()
renderer = self.plot.plots["plot0"][0]
self.tool = ImageInspectorTool(component=renderer)
self.overlay = ImageInspectorOverlay(component=renderer,
image_inspector=self.tool)
self.overlay2 = CustomImageInspectorOverlay(component=renderer,
image_inspector=self.tool)
self.plot.active_tool = self.tool
self.plot.do_layout()
self.insp_event = None
z = sin(x) * y
# Create a pseudo-color-map
pcolor(x, y, z, name='sin_x_times_y')
# Change the color mapping
colormap(jet)
# Add some titles
title("pseudo colormap image plot")
# From the current plot object, grab the first plot
img_plot = curplot().plots['sin_x_times_y'][0]
# Add a custom tool - in this case, an ImageInspector
from chaco.tools.api import ImageInspectorTool, ImageInspectorOverlay
tool = ImageInspectorTool(img_plot)
img_plot.tools.append(tool)
overlay = ImageInspectorOverlay(img_plot,
image_inspector=tool,
bgcolor="white",
border_visible=True)
img_plot.overlays.append(overlay)
# If running this from the command line and outside of a wxPython
# application or process, the show() command is necessary to keep
# the plot from disappearing instantly. If a wxPython mainloop
# is already running, then this command is not necessary.
show()
def __init__(self, **kwtraits):
super(ResultExplorer, self).__init__(**kwtraits)
# containers
bgcolor = "sys_window" #(212/255.,208/255.,200/255.) # Windows standard background
self.plot_container = container = VPlotContainer(use_backbuffer=True,
padding=0,
fill_padding=False,
valign="center",
bgcolor=bgcolor)
subcontainer = HPlotContainer(use_backbuffer=True,
padding=0,
fill_padding=False,
halign="center",
bgcolor=bgcolor)
# freqs
self.synth = FreqSelector(parent=self)
# data source
self.plot_data = pd = ArrayPlotData()
self.set_result_data()
self.set_pict()
# map plot
self.map_plot = Plot(pd, padding=40)
self.map_plot.img_plot("image", name="image")
imgp = self.map_plot.img_plot("map_data", name="map", colormap=jet)[0]
self.imgp = imgp
t1 = self.map_plot.plot(("xpoly", "ypoly"),
name="sector",
type="polygon")
t1[0].face_color = (0, 0, 0, 0) # set face color to transparent
# map plot tools and overlays
imgtool = ImageInspectorTool(imgp)
imgp.tools.append(imgtool)
overlay = ImageInspectorOverlay(component=imgp,
image_inspector=imgtool,
bgcolor="white",
border_visible=True)
self.map_plot.overlays.append(overlay)
self.zoom = RectZoomSelect(self.map_plot,
drag_button='right',
always_on=True,
tool_mode='box')
self.map_plot.overlays.append(self.zoom)
self.map_plot.tools.append(PanTool(self.map_plot))
# colorbar
colormap = imgp.color_mapper
self.drange = colormap.range
self.drange.low_setting = "track"
self.colorbar = cb = ColorBar(
index_mapper=LinearMapper(range=colormap.range),
color_mapper=colormap,
plot=self.map_plot,
orientation='v',
resizable='v',
width=10,
padding=20)
# colorbar tools and overlays
range_selection = RangeSelection(component=cb)
cb.tools.append(range_selection)
cb.overlays.append(
RangeSelectionOverlay(component=cb,
border_color="white",
alpha=0.8,
fill_color=bgcolor))
range_selection.listeners.append(imgp)
# spectrum plot
self.spec_plot = Plot(pd, padding=25)
px = self.spec_plot.plot(("freqs", "spectrum"),
name="spectrum",
index_scale="log")[0]
self.yrange = self.spec_plot.value_range
px.index_mapper = MyLogMapper(range=self.spec_plot.index_range)
# spectrum plot tools
self.cursor = CursorTool(
px) #, drag_button="left", color='blue', show_value_line=False)
px.overlays.append(self.cursor)
self.cursor.current_position = 0.3, 0.5
px.index_mapper.map_screen(0.5)
# self.map_plot.tools.append(SaveTool(self.map_plot, filename='pic.png'))
# layout
self.set_map_details()
self.reset_sector()
subcontainer.add(self.map_plot)
subcontainer.add(self.colorbar)
# subcontainer.tools.append(SaveTool(subcontainer, filename='pic.png'))
container.add(self.spec_plot)
container.add(subcontainer)
container.tools.append(SaveTool(container, filename='pic.pdf'))
self.last_valid_digest = self.Beamformer.ext_digest