__init__.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
 
 
 
import math
 
from ROOT import gSystem
import collections
 
from ROOT import Belle2  # make Belle2 namespace available
 
gSystem.Load('libtracking_trackFindingCDC')
 
 
class CDCSVGPlotter:
 
    """
    Helper class to generated the svg image from the various tracking objects.
    This is a tiny wrapper around the TrackFindingCDC.EventDataPlotter.
    """
 
    def __init__(self, animate=False):
        """
        Constructor methode.
        @param animate switch indicating if an animated SVG should be generated
        """
        top = -112
        left = -112
        right = 112
        bottom = 112
 
        default_bound = Belle2.TrackFindingCDC.BoundingBox(left, bottom, right, top)
        default_width = 1120
        default_height = 1120
 
        
        self.animateanimate = animate
        
        self.eventdata_plottereventdata_plotter = Belle2.TrackFindingCDC.EventDataPlotter(self.animateanimate)
 
        self.eventdata_plottereventdata_plotter.setBoundingBox(default_bound)
        self.eventdata_plottereventdata_plotter.setCanvasHeight(default_height)
        self.eventdata_plottereventdata_plotter.setCanvasWidth(default_width)
 
    def clone(self):
        """
        Make a copy of the current status of the plotter.
        """
        cloned_plotter = CDCSVGPlotter(self.animateanimate)
        cloned_plotter.eventdata_plotter = Belle2.TrackFindingCDC.EventDataPlotter(self.eventdata_plottereventdata_plotter)
        return cloned_plotter
 
    def styling_to_attribute_map(self, **styling):
        """
        Transfer the styling information to the attribute map
        """
        attribute_map = Belle2.TrackFindingCDC.PrimitivePlotter.AttributeMap()
 
        for key, value in list(styling.items()):
            attribute_map[str(key)] = str(value)
 
        return attribute_map
 
    def draw_superlayer_boundaries(self, **styling):
        """
        Draw the CDC superlayer boundaries
        """
        attribute_map = self.styling_to_attribute_mapstyling_to_attribute_map(**styling)
        self.eventdata_plottereventdata_plotter.drawSuperLayerBoundaries(attribute_map)
 
    def draw_interaction_point(self):
        """
        Draw the interaction point
        """
        self.eventdata_plottereventdata_plotter.drawInteractionPoint()
 
    def draw_outer_cdc_wall(self, **styling):
        """
        Draw the CDC outer wall
        """
        attribute_map = self.styling_to_attribute_mapstyling_to_attribute_map(**styling)
        self.eventdata_plottereventdata_plotter.drawOuterCDCWall(attribute_map)
 
    def draw_inner_cdc_wall(self, **styling):
        """
        Draw the CDC inner wall
        """
        attribute_map = self.styling_to_attribute_mapstyling_to_attribute_map(**styling)
        self.eventdata_plottereventdata_plotter.drawInnerCDCWall(attribute_map)
 
    @staticmethod
    def unpack_attributes(styling, i_obj=0, obj=None):
        """Mapping function to unpack the attributes from the attribute maps. Mechanism and interface inspired by d3.js"""
        result = {}
        for (key, value) in list(styling.items()):
            if isinstance(value, collections.Callable):
                result[key] = value(i_obj, obj)
            elif isinstance(value, str):
                result[key] = value
            elif hasattr(value, '__getitem__'):
                result[key] = value[i_obj % len(value)]
            else:
                result[key] = value
        return result
 
    def draw_iterable(self, iterable, **styling):
        """
        Draw one or more items with the specified styling
        """
        draw = self.drawdraw
        unpack_attributes = self.unpack_attributesunpack_attributes
        for (i_obj, obj) in enumerate(iterable):
            obj_styling = unpack_attributes(styling, i_obj, obj)
            draw(obj, **obj_styling)
 
    def draw_storevector(self, storeobj_name, **styling):
        """
        Draw information in a vector from the DataStore with the specified styling
        """
        print('Drawing vector from DataStore:', storeobj_name, end=' ')
        print()
        pystoreobj = Belle2.PyStoreObj(storeobj_name)
 
        if pystoreobj:
            # Wrapper around std::vector like
            wrapped_vector = pystoreobj.obj()
            vector = wrapped_vector.get()
 
            print('with', vector.size(), 'entries')
            print('Attributes are')
            for (key, value) in list(styling.items()):
                print(str(key), ':', str(value))
 
            self.draw_iterabledraw_iterable(vector, **styling)
 
        else:
            print("### not present in the DataStore")
            print("Current content of the DataStore")
            print("StoreArrays:")
            Belle2.PyStoreArray.printList()
            print("StoreObjPtr:")
            Belle2.PyStoreObj.printList()
 
    def draw_storearray(self, storearray_name, **styling):
        """
        Draw information from a StoreArray with the specified styling
        """
        print('Drawing StoreArray:', storearray_name, end=' ')
        print()
        storearray = Belle2.PyStoreArray(storearray_name)
        if storearray:
            print('with', storearray.getEntries(), 'entries')
            print('Attributes are')
            for (key, value) in list(styling.items()):
                print(str(key), ':', str(value))
 
            self.draw_iterabledraw_iterable(storearray, **styling)
 
        else:
            print("### not present in the DataStore")
            print("Current content of the DataStore")
            print("StoreArrays:")
            Belle2.PyStoreArray.printList()
            print("StoreObjPtr:")
            Belle2.PyStoreObj.printList()
 
    def draw(self, obj, **styling):
        """
        Draw an object with the specified styling
        """
        attribute_map = self.styling_to_attribute_mapstyling_to_attribute_map(**styling)
        self.eventdata_plottereventdata_plotter.draw(obj, attribute_map)
 
    def saveSVGFile(self, svgFileName='display.svg'):
        """
        Save the current dom object representation to disk.
        """
 
        eventdata_plotter = self.eventdata_plottereventdata_plotter
 
        boundingBox = eventdata_plotter.getBoundingBox()
 
        height = boundingBox.getHeight()
        width = boundingBox.getWidth()
 
        totalPoints = 1120 * 1120
        svgHeight = round(math.sqrt(totalPoints * float(height) / width))
        svgWidth = round(math.sqrt(totalPoints * float(width) / height))
 
        eventdata_plotter.setCanvasHeight(svgHeight)
        eventdata_plotter.setCanvasWidth(svgWidth)
 
        return eventdata_plotter.save(svgFileName)
 
    def savePNGFile(self, pngFileName='display.png'):
        """
        Save the current dom object representation to disk as a png.
        """
 
        import cairosvg
        import os
 
        temp_file_name = "tmp.svg"
        eventdata_plotter = self.eventdata_plottereventdata_plotter
 
        boundingBox = eventdata_plotter.getBoundingBox()
 
        height = boundingBox.getHeight()
        width = boundingBox.getWidth()
 
        totalPoints = 1120 * 1120
        svgHeight = round(math.sqrt(totalPoints * float(height) / width))
        svgWidth = round(math.sqrt(totalPoints * float(width) / height))
 
        eventdata_plotter.setCanvasHeight(svgHeight)
        eventdata_plotter.setCanvasWidth(svgWidth)
 
        eventdata_plotter.save(temp_file_name)
 
        with open(temp_file_name, "r") as temp_file:
            with open(pngFileName, "w") as output_file:
                svg_code = temp_file.read()
                cairosvg.svg2png(bytestring=svg_code, write_to=output_file)
 
        os.remove(temp_file_name)