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upper = np.nanpercentile(self.image[:, :, order[color]], self.multicolormax[color].get())
self.image[np.where(self.image[:, :, order[color]] < lower)] = lower
self.image[np.where(self.image[:, :, order[color]] > upper)] = upper
# image values must be between (0,1) so scale image
for color, index in order.items():
self.image[:, :, index] /= np.nanmax(self.image[:, :, index])"
124,"def configure_singlecolor_image(self, scale=False):
""""""
configures the single color image according to the requested parameters
:return: nothing, just updates self.image
""""""
# determine which channel to use
self.image = self.data[self.singlecolorvar.get()]
# scale the image by requested power
self.image = np.power(self.image, self.singlecolorpower.get())
# adjust the percentile thresholds
lower = np.nanpercentile(self.image, self.singlecolormin.get())
upper = np.nanpercentile(self.image, self.singlecolormax.get())
self.image[self.image < lower] = lower
self.image[self.image > upper] = upper
# image values must be between (0,1) so scale image
self.image /= np.nanmax(self.image)"
125,"def updateArray(self, array, indices, value):
""""""
updates array so that pixels at indices take on value
:param array: (m,n) array to adjust
:param indices: flattened image indices to change value
:param value: new value to assign
:return: the changed (m,n) array
""""""
lin = np.arange(array.size)
new_array = array.flatten()
new_array[lin[indices]] = value
return new_array.reshape(array.shape)"
126,"def onlasso(self, verts):
""""""
Main function to control the action of the lasso, allows user to draw on data image and adjust thematic map
:param verts: the vertices selected by the lasso
:return: nothin, but update the selection array so lassoed region now has the selected theme, redraws canvas
""""""
p = path.Path(verts)
ind = p.contains_points(self.pix, radius=1)
self.history.append(self.selection_array.copy())
self.selection_array = self.updateArray(self.selection_array,
ind,
self.solar_class_var.get())
self.mask.set_data(self.selection_array)
self.fig.canvas.draw_idle()"
127,"def make_canvas_frame(self):
"""""" Create the data and thematic map images for the first time """"""
self.fig, (self.imageax, self.previewax) = plt.subplots(ncols=2,
figsize=self.canvas_size,
sharex=True, sharey=True,
gridspec_kw=self.subplot_grid_spec)
self.canvas = FigureCanvasTkAgg(self.fig, master=self.canvas_frame)
self.canvas.mpl_connect('button_press_event', self.onclick)
self.canvas.mpl_connect('key_press_event', self.onpress)
# set up the channel data view
self.configure_threecolor_image()
self.imageplot = self.imageax.imshow(self.image)
self.imageax.set_xlim([0, self.shape[0]])
self.imageax.set_ylim([0, self.shape[0]])
self.imageax.set_axis_off()
self.history.append(self.selection_array)
cmap = self.config.solar_cmap
self.mask = self.previewax.imshow(self.selection_array,
origin='lower',
interpolation='nearest',
cmap=cmap,
vmin=-1, vmax=max([num for _, num in self.config.solar_classes])+1)
self.previewax.set_xlim([0, self.shape[0]])
self.previewax.set_ylim([0, self.shape[0]])
self.previewax.set_aspect(""equal"")
self.previewax.set_axis_off()
# add selection layer for lasso
self.pix = np.arange(self.shape[0]) # assumes square image
xv, yv = np.meshgrid(self.pix, self.pix)
self.pix = np.vstack((xv.flatten(), yv.flatten())).T
lineprops = dict(color=self.config.default['lasso_color'],
linewidth=self.config.default['lasso_width'])
self.lasso = LassoSelector(self.imageax, self.onlasso, lineprops=lineprops)
# display everything
self.canvas.show()
self.canvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=True)
self.canvas._tkcanvas.pack(side=tk.TOP, fill=tk.BOTH, expand=True)
# add the tool bar
self.toolbarcenterframe = tk.LabelFrame(self.canvas_frame,
borderwidth=0,
text=""Draw: unlabeled"",
relief=tk.FLAT,