Python HPlotContainer.remove方法代码示例

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

#.........这里部分代码省略.........
            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=(-1,1)
        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):
        peaks=[]
        progress = ProgressDialog(title="Peak finder progress", message="Finding peaks on %s images"%self.numfiles, max=self.numfiles, show_time=True, can_cancel=False)
        progress.open()
        for idx in xrange(self.numfiles):
            self.controller.set_active_index(idx)
            self.data = self.controller.get_active_image()[:]
            self.CC = cv_funcs.xcorr(self.template, self.data)
            # peak finder needs peaks greater than 1.  Multiply by 255 to scale them.
            pks=pc.two_dim_findpeaks(self.CC*255, peak_width=self.peak_width, medfilt_radius=None)
            pks[:,2]=pks[:,2]/255.
            peaks.append(pks)
            progress.update(idx+1)
        #ipdb.set_trace()
        self.peaks=peaks
        self.redraw_plots()
        
    def mask_peaks(self,idx):
        thresh=self.cbar_selection.selection
        if thresh==[]:
            thresh=(-1,1)
        mpeaks=np.ma.asarray(self.peaks[idx])
        mpeaks[:,2]=np.ma.masked_outside(mpeaks[:,2],thresh[0],thresh[1])
        return mpeaks

    @on_trait_change("peaks")
    def redraw_plots(self):
        oldplot=self.img_plot
        self.container.remove(oldplot)
        newplot=self.render_image()
        self.container.add(newplot)
        self.img_plot=newplot

        try:
            # if these haven't been created before, this will fail.  wrap in try to prevent that.
            oldscat=self.scatplot
            self.container.remove(oldscat)
            oldcolorbar = self.colorbar
            self.img_container.remove(oldcolorbar)
        except:
            pass

        if self.numpeaks_img>0:
            newscat=self.render_scatplot()
            self.container.add(newscat)
            self.scatplot=newscat
            colorbar = self.draw_colorbar()
            self.img_container.add(colorbar)
            self.colorbar=colorbar

        self.container.request_redraw()
        self.img_container.request_redraw()

    def crop_cells(self):
        print "cropping cells..."
        for idx in xrange(self.numfiles):
            # filter the peaks that are outside the selected threshold
            self.controller.set_active_index(idx)
            self.data = self.controller.get_active_image()
            self.name = self.controller.get_active_name()
            peaks=np.ma.compress_rows(self.mask_peaks(idx))
            tmp_sz=self.tmp_size
            data=np.zeros((peaks.shape[0],tmp_sz,tmp_sz))
            if data.shape[0] >0:
                for i in xrange(peaks.shape[0]):
                    # crop the cells from the given locations
                    data[i,:,:]=self.data[peaks[i,1]:peaks[i,1]+tmp_sz, 
                                      peaks[i,0]:peaks[i,0]+tmp_sz]
                # send the data to the controller for storage in the chest
                self.controller.add_cells(name = self.name, data = data,
                                      locations = peaks)

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

#.........这里部分代码省略.........
        from hyperspy import peak_char as pc
        peaks=[]
        """from hyperspy.misc.progressbar import ProgressBar, \
            Percentage, RotatingMarker, ETA, Bar
        widgets = ['Locating peaks: ', Percentage(), ' ', Bar(marker=RotatingMarker()),
                   ' ', ETA()]
        pbar = ProgressBar(widgets=widgets, maxval=100).start()"""
        progress = ProgressDialog(title="Peak finder progress", message="Finding peaks on %s images"%self.numfiles, max=self.numfiles, show_time=True, can_cancel=False)
        progress.open()
        for idx in xrange(self.numfiles):
            #pbar.update(float(idx)/self.numfiles*100)
            self.CC = cv_funcs.xcorr(self.sig.data[self.tmp_img_idx,
                                                   self.top:self.top+self.tmp_size,
                                                   self.left:self.left+self.tmp_size],
                                               self.sig.data[idx,:,:])
            # peak finder needs peaks greater than 1.  Multiply by 255 to scale them.
            pks=pc.two_dim_findpeaks(self.CC*255, peak_width=self.peak_width, medfilt_radius=None)
            pks[:,2]=pks[:,2]/255.
            peaks.append(pks)
            progress.update(idx+1)
        #pbar.finish()
        self.peaks=peaks
        
    def mask_peaks(self,idx):
        thresh=self.cbar_selection.selection
        if thresh==[]:
            thresh=(0,1)
        mpeaks=np.ma.asarray(self.peaks[idx])
        mpeaks[:,2]=np.ma.masked_outside(mpeaks[:,2],thresh[0],thresh[1])
        return mpeaks

    @on_trait_change("peaks")
    def redraw_plots(self):
        oldplot=self.img_plot
        self.container.remove(oldplot)
        newplot=self.render_image()
        self.container.add(newplot)
        self.img_plot=newplot

        try:
            # if these haven't been created before, this will fail.  wrap in try to prevent that.
            oldscat=self.scatplot
            self.container.remove(oldscat)
            oldcolorbar = self.colorbar
            self.img_container.remove(oldcolorbar)
        except:
            pass

        if self.numpeaks_img>0:
            newscat=self.render_scatplot()
            self.container.add(newscat)
            self.scatplot=newscat
            colorbar = self.draw_colorbar()
            self.img_container.add(colorbar)
            self.colorbar=colorbar

        self.container.request_redraw()
        self.img_container.request_redraw()

    def crop_cells_stack(self):
        from hyperspy.signals.aggregate import AggregateCells
        if self.numfiles==1:
            self.crop_sig=self.crop_cells()
            return
        else:
            crop_agg=[]
            for idx in xrange(self.numfiles):
                peaks=np.ma.compress_rows(self.mask_peaks(idx))
                if peaks.any():
                    crop_agg.append(self.crop_cells(idx))
            self.crop_sig=AggregateCells(*crop_agg)
            return

    def crop_cells(self,idx=0):
        print "cropping cells..."
        from hyperspy.signals.image import Image
        # filter the peaks that are outside the selected threshold
        peaks=np.ma.compress_rows(self.mask_peaks(idx))
        tmp_sz=self.tmp_size
        data=np.zeros((peaks.shape[0],tmp_sz,tmp_sz))
        if not hasattr(self.sig.mapped_parameters,"original_files"):
            parent=self.sig
        else:
            parent=self.sig.mapped_parameters.original_files[self.titles[idx]]
        pmp=parent.mapped_parameters
        positions=np.zeros((peaks.shape[0],1),dtype=[('filename','a256'),('id','i4'),('position','f4',(1,2))])
        for i in xrange(peaks.shape[0]):
            # crop the cells from the given locations
            data[i,:,:]=self.sig.data[idx,peaks[i,1]:peaks[i,1]+tmp_sz,peaks[i,0]:peaks[i,0]+tmp_sz]
            positions[i]=(self.titles[idx],i,peaks[i,:2])
            crop_sig=Image({'data':data,
                            'mapped_parameters':{
                               'title':'Cropped cells from %s'%self.titles[idx],
                               'record_by':'image',
                               'locations':positions,
                               'original_files':{pmp.title:parent},
                               }
                            })
            
        return crop_sig