Python HPlotContainer.request_redraw方法代码示例

# 需要导入模块: from enthought.chaco.api import HPlotContainer [as 别名]
# 或者: from enthought.chaco.api.HPlotContainer import request_redraw [as 别名]

#.........这里部分代码省略.........

        self.pd.set_data("line_index2", array([]))
        self.pd.set_data("line_value2", array([]))
        self.pd.set_data("scatter_index2", array([]))
        self.pd.set_data("scatter_value2", array([]))
        self.pd.set_data("scatter_color2", array([]))

        self.cross_plot2 = Plot(self.pd, width = 140, orientation="v", resizable="v", padding=20, padding_bottom=160)
        self.cross_plot2.plot(("line_index2", "line_value2"),
                             line_style="dot")
        self.cross_plot2.plot(("scatter_index2","scatter_value2","scatter_color2"),
                             type="cmap_scatter",
                             name="dot",
                             color_mapper=self._cmap(image_value_range),
                             marker="circle",
                             marker_size=8)

        self.cross_plot2.index_range = self.polyplot.index_range.y_range



        # Create a container and add components
        self.container = HPlotContainer(padding=40, fill_padding=True,
                                        bgcolor = "white", use_backbuffer=False)
        inner_cont = VPlotContainer(padding=0, use_backbuffer=True)
        inner_cont.add(self.cross_plot)
        inner_cont.add(contour_container)
        self.container.add(self.colorbar)
        self.container.add(inner_cont)
        self.container.add(self.cross_plot2)


    def update(self, model):
        self.minz = model.minz
        self.maxz = model.maxz
        self.colorbar.index_mapper.range.low = self.minz
        self.colorbar.index_mapper.range.high = self.maxz
        self._image_index.set_data(model.xs, model.ys)
        self._image_value.data = model.zs
        self.pd.set_data("line_index", model.xs)
        self.pd.set_data("line_index2", model.ys)
        self.container.invalidate_draw()
        self.container.request_redraw()


    #---------------------------------------------------------------------------
    # Event handlers
    #---------------------------------------------------------------------------

    def _metadata_changed(self, old, new):
        """ This function takes out a cross section from the image data, based
        on the line inspector selections, and updates the line and scatter
        plots."""

        self.cross_plot.value_range.low = self.minz
        self.cross_plot.value_range.high = self.maxz
        self.cross_plot2.value_range.low = self.minz
        self.cross_plot2.value_range.high = self.maxz
        if self._image_index.metadata.has_key("selections"):
            x_ndx, y_ndx = self._image_index.metadata["selections"]
            if y_ndx and x_ndx:
                self.pd.set_data("line_value",
                                 self._image_value.data[y_ndx,:])
                self.pd.set_data("line_value2",
                                 self._image_value.data[:,x_ndx])
                xdata, ydata = self._image_index.get_data()
                xdata, ydata = xdata.get_data(), ydata.get_data()
                self.pd.set_data("scatter_index", array([xdata[x_ndx]]))
                self.pd.set_data("scatter_index2", array([ydata[y_ndx]]))
                self.pd.set_data("scatter_value",
                    array([self._image_value.data[y_ndx, x_ndx]]))
                self.pd.set_data("scatter_value2",
                    array([self._image_value.data[y_ndx, x_ndx]]))
                self.pd.set_data("scatter_color",
                    array([self._image_value.data[y_ndx, x_ndx]]))
                self.pd.set_data("scatter_color2",
                    array([self._image_value.data[y_ndx, x_ndx]]))
        else:
            self.pd.set_data("scatter_value", array([]))
            self.pd.set_data("scatter_value2", array([]))
            self.pd.set_data("line_value", array([]))
            self.pd.set_data("line_value2", array([]))

    def _colormap_changed(self):
        self._cmap = color_map_name_dict[self.colormap]
        if hasattr(self, "polyplot"):
            value_range = self.polyplot.color_mapper.range
            self.polyplot.color_mapper = self._cmap(value_range)
            value_range = self.cross_plot.color_mapper.range
            self.cross_plot.color_mapper = self._cmap(value_range)
            # FIXME: change when we decide how best to update plots using
            # the shared colormap in plot object
            self.cross_plot.plots["dot"][0].color_mapper = self._cmap(value_range)
            self.cross_plot2.plots["dot"][0].color_mapper = self._cmap(value_range)
            self.container.request_redraw()

    def _num_levels_changed(self):
        if self.num_levels > 3:
            self.polyplot.levels = self.num_levels
            self.lineplot.levels = self.num_levels

# 需要导入模块: from enthought.chaco.api import HPlotContainer [as 别名]
# 或者: from enthought.chaco.api.HPlotContainer import request_redraw [as 别名]

#.........这里部分代码省略.........
        
    @on_trait_change('left, top, tmp_size')
    def update_tmp_plot(self):
        self.tmp_plotdata.set_data("imagedata", 
                                   self.sig.data[self.top:self.top+self.tmp_size,self.left:self.left+self.tmp_size,self.img_idx])
        grid_data_source = self.tmp_plot.range2d.sources[0]
        grid_data_source.set_data(np.arange(self.tmp_size), np.arange(self.tmp_size))
        self.tmp_img_idx=self.img_idx
        return

    @on_trait_change('left, top, tmp_size')
    def update_CC(self):
        if self.ShowCC:
            self.CC = cv_funcs.xcorr(self.sig.data[self.top:self.top+self.tmp_size,
                                                   self.left:self.left+self.tmp_size,self.tmp_img_idx],
                                     self.sig.data[:,:,self.img_idx])
            self.img_plotdata.set_data("imagedata",self.CC)
            grid_data_source = self.img_plot.range2d.sources[0]
            grid_data_source.set_data(np.arange(self.CC.shape[1]), 
                                      np.arange(self.CC.shape[0]))
        if self.numpeaks_total>0:
            self.peaks=[np.array([[0,0,-1]])]

    @on_trait_change('cbar_selection:selection')
    def update_thresh(self):
        try:
            thresh=self.cbar_selection.selection
            self.thresh=thresh
            self.cmap_renderer.color_data.metadata['selections']=thresh
            self.thresh_lower=thresh[0]
            self.thresh_upper=thresh[1]
            #cmap_renderer.color_data.metadata['selection_masks']=self.thresh
            self.cmap_renderer.color_data.metadata_changed={'selections':thresh}
            self.container.request_redraw()
            self.img_container.request_redraw()
        except:
            pass

    @on_trait_change('thresh_upper,thresh_lower')
    def manual_thresh_update(self):
        self.thresh=[self.thresh_lower,self.thresh_upper]
        self.cmap_renderer.color_data.metadata['selections']=self.thresh
        self.cmap_renderer.color_data.metadata_changed={'selections':self.thresh}
        self.container.request_redraw()
        self.img_container.request_redraw()

    @on_trait_change('peaks,cbar_selection:selection,img_idx')
    def calc_numpeaks(self):
        try:
            thresh=self.cbar_selection.selection
            self.thresh=thresh
        except:
            thresh=[]
        if thresh==[] or thresh==() or thresh==None:
            thresh=(0,1)
        self.numpeaks_total=int(np.sum([np.sum(np.ma.masked_inside(self.peaks[i][:,2],thresh[0],thresh[1]).mask) for i in xrange(len(self.peaks))]))
        try:
            self.numpeaks_img=int(np.sum(np.ma.masked_inside(self.peaks[self.img_idx][:,2],thresh[0],thresh[1]).mask))
        except:
            self.numpeaks_img=0

    @on_trait_change('findpeaks')
    def locate_peaks(self):
        from hyperspy import peak_char as pc
        peaks=[]
        for idx in xrange(self.numfiles):