import copy import numpy import pylab import functools from PyQt4 import QtGui from PyQt4 import QtCore DEFAULT_CMAP = pylab.cm.jet from mpl_toolkits.mplot3d import Axes3D from sas.sascalc.dataloader.manipulations import CircularAverage from sas.qtgui.Plotting.PlotterData import Data1D from sas.qtgui.Plotting.PlotterData import Data2D import sas.qtgui.Plotting.PlotUtilities as PlotUtilities import sas.qtgui.Utilities.GuiUtils as GuiUtils from sas.qtgui.Plotting.PlotterBase import PlotterBase from sas.qtgui.Plotting.ColorMap import ColorMap from sas.qtgui.Plotting.BoxSum import BoxSum from sas.qtgui.Plotting.SlicerParameters import SlicerParameters from sas.qtgui.Plotting.Binder import BindArtist # TODO: move to sas.qtgui namespace from sas.qtgui.Plotting.Slicers.BoxSlicer import BoxInteractorX from sas.qtgui.Plotting.Slicers.BoxSlicer import BoxInteractorY from sas.qtgui.Plotting.Slicers.AnnulusSlicer import AnnulusInteractor from sas.qtgui.Plotting.Slicers.SectorSlicer import SectorInteractor from sas.qtgui.Plotting.Slicers.BoxSum import BoxSumCalculator # Minimum value of Z for which we will present data. MIN_Z = -32 class Plotter2DWidget(PlotterBase): """ 2D Plot widget for use with a QDialog """ def __init__(self, parent=None, manager=None, quickplot=False, dimension=2): self.dimension = dimension super(Plotter2DWidget, self).__init__(parent, manager=manager, quickplot=quickplot) self.cmap = DEFAULT_CMAP.name # Default scale self.scale = 'log_{10}' # to set the order of lines drawn first. self.slicer_z = 5 # Reference to the current slicer self.slicer = None self.slicer_widget = None # Create Artist and bind it self.connect = BindArtist(self.figure) self.vmin = None self.vmax = None self.manager = manager @property def data(self): return self._data @data.setter def data(self, data=None): """ data setter """ self._data = data self.qx_data = data.qx_data self.qy_data = data.qy_data self.xmin = data.xmin self.xmax = data.xmax self.ymin = data.ymin self.ymax = data.ymax self.zmin = data.zmin self.zmax = data.zmax self.label = data.name self.xLabel = "%s(%s)"%(data._xaxis, data._xunit) self.yLabel = "%s(%s)"%(data._yaxis, data._yunit) self.title(title=data.title) @property def item(self): ''' getter for this plot's QStandardItem ''' return self._item @item.setter def item(self, item=None): ''' setter for this plot's QStandardItem ''' self._item = item def plot(self, data=None, marker=None, show_colorbar=True): """ Plot 2D self._data marker - unused """ # Assing data if isinstance(data, Data2D): self.data = data assert self._data # Toggle the scale zmin_2D_temp, zmax_2D_temp = self.calculateDepth() # Prepare and show the plot self.showPlot(data=self.data.data, qx_data=self.qx_data, qy_data=self.qy_data, xmin=self.xmin, xmax=self.xmax, ymin=self.ymin, ymax=self.ymax, cmap=self.cmap, zmin=zmin_2D_temp, zmax=zmax_2D_temp, show_colorbar=show_colorbar) def calculateDepth(self): """ Re-calculate the plot depth parameters depending on the scale """ # Toggle the scale zmin_temp = self.zmin zmax_temp = self.zmax # self.scale predefined in the baseclass if self.scale == 'log_{10}': if self.zmin is not None: zmin_temp = numpy.power(10, self.zmin) if self.zmax is not None: zmax_temp = numpy.power(10, self.zmax) else: if self.zmin is not None: # min log value: no log(negative) zmin_temp = MIN_Z if self.zmin <= 0 else numpy.log10(self.zmin) if self.zmax is not None: zmax_temp = numpy.log10(self.zmax) return (zmin_temp, zmax_temp) def createContextMenu(self): """ Define common context menu and associated actions for the MPL widget """ self.defaultContextMenu() self.contextMenu.addSeparator() self.actionDataInfo = self.contextMenu.addAction("&DataInfo") self.actionDataInfo.triggered.connect( functools.partial(self.onDataInfo, self.data)) self.actionSavePointsAsFile = self.contextMenu.addAction("&Save Points as a File") self.actionSavePointsAsFile.triggered.connect( functools.partial(self.onSavePoints, self.data)) self.contextMenu.addSeparator() self.actionCircularAverage = self.contextMenu.addAction("&Perform Circular Average") self.actionCircularAverage.triggered.connect(self.onCircularAverage) self.actionSectorView = self.contextMenu.addAction("&Sector [Q View]") self.actionSectorView.triggered.connect(self.onSectorView) self.actionAnnulusView = self.contextMenu.addAction("&Annulus [Phi View]") self.actionAnnulusView.triggered.connect(self.onAnnulusView) self.actionBoxSum = self.contextMenu.addAction("&Box Sum") self.actionBoxSum.triggered.connect(self.onBoxSum) self.actionBoxAveragingX = self.contextMenu.addAction("&Box Averaging in Qx") self.actionBoxAveragingX.triggered.connect(self.onBoxAveragingX) self.actionBoxAveragingY = self.contextMenu.addAction("&Box Averaging in Qy") self.actionBoxAveragingY.triggered.connect(self.onBoxAveragingY) # Additional items for slicer interaction if self.slicer: self.actionClearSlicer = self.contextMenu.addAction("&Clear Slicer") self.actionClearSlicer.triggered.connect(self.onClearSlicer) if self.slicer.__class__.__name__ != "BoxSumCalculator": self.actionEditSlicer = self.contextMenu.addAction("&Edit Slicer Parameters") self.actionEditSlicer.triggered.connect(self.onEditSlicer) self.contextMenu.addSeparator() self.actionColorMap = self.contextMenu.addAction("&2D Color Map") self.actionColorMap.triggered.connect(self.onColorMap) self.contextMenu.addSeparator() self.actionChangeScale = self.contextMenu.addAction("Toggle Linear/Log Scale") self.actionChangeScale.triggered.connect(self.onToggleScale) def createContextMenuQuick(self): """ Define context menu and associated actions for the quickplot MPL widget """ self.defaultContextMenu() if self.dimension == 2: self.actionToggleGrid = self.contextMenu.addAction("Toggle Grid On/Off") self.contextMenu.addSeparator() self.actionChangeScale = self.contextMenu.addAction("Toggle Linear/Log Scale") # Define the callbacks self.actionChangeScale.triggered.connect(self.onToggleScale) if self.dimension == 2: self.actionToggleGrid.triggered.connect(self.onGridToggle) def onToggleScale(self, event): """ Toggle axis and replot image """ # self.scale predefined in the baseclass if self.scale == 'log_{10}': self.scale = 'linear' else: self.scale = 'log_{10}' self.plot() def onClearSlicer(self): """ Remove all sclicers from the chart """ if self.slicer is None: return self.slicer.clear() self.canvas.draw() self.slicer = None def onEditSlicer(self): """ Present a small dialog for manipulating the current slicer """ assert self.slicer # Only show the dialog if not currently shown if self.slicer_widget: return def slicer_closed(): # Need to disconnect the signal!! self.slicer_widget.close_signal.disconnect() # reset slicer_widget on "Edit Slicer Parameters" window close self.slicer_widget = None self.param_model = self.slicer.model() # Pass the model to the Slicer Parameters widget self.slicer_widget = SlicerParameters(model=self.param_model, validate_method=self.slicer.validate) self.slicer_widget.close_signal.connect(slicer_closed) # Add the plot to the workspace self.manager.parent.workspace().addWindow(self.slicer_widget) self.slicer_widget.show() def onCircularAverage(self): """ Perform circular averaging on Data2D """ # Find the best number of bins npt = numpy.sqrt(len(self.data.data[numpy.isfinite(self.data.data)])) npt = numpy.floor(npt) # compute the maximum radius of data2D self.qmax = max(numpy.fabs(self.data.xmax), numpy.fabs(self.data.xmin)) self.ymax = max(numpy.fabs(self.data.ymax), numpy.fabs(self.data.ymin)) self.radius = numpy.sqrt(numpy.power(self.qmax, 2) + numpy.power(self.ymax, 2)) #Compute beam width bin_width = (self.qmax + self.qmax) / npt # Create data1D circular average of data2D circle = CircularAverage(r_min=0, r_max=self.radius, bin_width=bin_width) circ = circle(self.data) dxl = circ.dxl if hasattr(circ, "dxl") else None dxw = circ.dxw if hasattr(circ, "dxw") else None new_plot = Data1D(x=circ.x, y=circ.y, dy=circ.dy, dx=circ.dx) new_plot.dxl = dxl new_plot.dxw = dxw new_plot.name = new_plot.title = "Circ avg " + self.data.name new_plot.source = self.data.source new_plot.interactive = True new_plot.detector = self.data.detector # Define axes if not done yet. new_plot.xaxis("\\rm{Q}", "A^{-1}") if hasattr(self.data, "scale") and \ self.data.scale == 'linear': new_plot.ytransform = 'y' new_plot.yaxis("\\rm{Residuals} ", "normalized") else: new_plot.yaxis("\\rm{Intensity} ", "cm^{-1}") new_plot.group_id = "2daverage" + self.data.name new_plot.id = "Circ avg " + self.data.name new_plot.is_data = True GuiUtils.updateModelItemWithPlot(self._item, new_plot, new_plot.id) self.manager.communicator.plotUpdateSignal.emit([new_plot]) def setSlicer(self, slicer): """ Clear the previous slicer and create a new one. slicer: slicer class to create """ # Clear current slicer if self.slicer is not None: self.slicer.clear() # Create a new slicer self.slicer_z += 1 self.slicer = slicer(self, self.ax, item=self._item, zorder=self.slicer_z) self.ax.set_ylim(self.data.ymin, self.data.ymax) self.ax.set_xlim(self.data.xmin, self.data.xmax) # Draw slicer self.figure.canvas.draw() self.slicer.update() # Reset the model on the Edit slicer parameters widget self.param_model = self.slicer.model() if self.slicer_widget: self.slicer_widget.setModel(self.param_model) def onSectorView(self): """ Perform sector averaging on Q and draw sector slicer """ self.setSlicer(slicer=SectorInteractor) def onAnnulusView(self): """ Perform sector averaging on Phi and draw annulus slicer """ self.setSlicer(slicer=AnnulusInteractor) def onBoxSum(self): """ Perform 2D Data averaging Qx and Qy. Display box slicer details. """ self.onClearSlicer() self.slicer_z += 1 self.slicer = BoxSumCalculator(self, self.ax, zorder=self.slicer_z) self.ax.set_ylim(self.data.ymin, self.data.ymax) self.ax.set_xlim(self.data.xmin, self.data.xmax) self.figure.canvas.draw() self.slicer.update() # Get the BoxSumCalculator model. self.box_sum_model = self.slicer.model() # Pass the BoxSumCalculator model to the BoxSum widget self.boxwidget = BoxSum(self, model=self.box_sum_model) # Add the plot to the workspace self.manager.parent.workspace().addWindow(self.boxwidget) self.boxwidget.show() def onBoxAveragingX(self): """ Perform 2D data averaging on Qx Create a new slicer. """ self.setSlicer(slicer=BoxInteractorX) def onBoxAveragingY(self): """ Perform 2D data averaging on Qy Create a new slicer . """ self.setSlicer(slicer=BoxInteractorY) def onColorMap(self): """ Display the color map dialog and modify the plot's map accordingly """ color_map_dialog = ColorMap(self, cmap=self.cmap, vmin=self.vmin, vmax=self.vmax, data=self.data) color_map_dialog.apply_signal.connect(self.onApplyMap) if color_map_dialog.exec_() == QtGui.QDialog.Accepted: self.onApplyMap(color_map_dialog.norm(), color_map_dialog.cmap()) def onApplyMap(self, v_values, cmap): """ Update the chart color map based on data passed from the widget """ self.cmap = str(cmap) self.vmin, self.vmax = v_values # Redraw the chart with new cmap self.plot() def showPlot(self, data, qx_data, qy_data, xmin, xmax, ymin, ymax, zmin, zmax, label='data2D', cmap=DEFAULT_CMAP, show_colorbar=True): """ Render and show the current data """ self.qx_data = qx_data self.qy_data = qy_data self.xmin = xmin self.xmax = xmax self.ymin = ymin self.ymax = ymax self.zmin = zmin self.zmax = zmax # If we don't have any data, skip. if data is None: return if data.ndim == 0: return elif data.ndim == 1: output = PlotUtilities.build_matrix(data, self.qx_data, self.qy_data) else: output = copy.deepcopy(data) zmin_temp = self.zmin # check scale if self.scale == 'log_{10}': try: if self.zmin <= 0 and len(output[output > 0]) > 0: zmin_temp = self.zmin output[output > 0] = numpy.log10(output[output > 0]) elif self.zmin <= 0: zmin_temp = self.zmin output[output > 0] = numpy.zeros(len(output)) output[output <= 0] = MIN_Z else: zmin_temp = self.zmin output[output > 0] = numpy.log10(output[output > 0]) except: #Too many problems in 2D plot with scale output[output > 0] = numpy.log10(output[output > 0]) pass self.cmap = cmap if self.dimension != 3: #Re-adjust colorbar self.figure.subplots_adjust(left=0.2, right=.8, bottom=.2) zmax_temp = self.zmax if self.vmin is not None: zmin_temp = self.vmin zmax_temp = self.vmax im = self.ax.imshow(output, interpolation='nearest', # origin='lower', vmin=zmin_temp, vmax=zmax_temp, cmap=self.cmap, extent=(self.xmin, self.xmax, self.ymin, self.ymax)) cbax = self.figure.add_axes([0.84, 0.2, 0.02, 0.7]) # Current labels for axes self.ax.set_ylabel(self.y_label) self.ax.set_xlabel(self.x_label) # Title only for regular charts if not self.quickplot: self.ax.set_title(label=self._title) if cbax is None: ax.set_frame_on(False) cb = self.figure.colorbar(im, shrink=0.8, aspect=20) else: cb = self.figure.colorbar(im, cax=cbax) cb.update_bruteforce(im) cb.set_label('$' + self.scale + '$') self.vmin = cb.vmin self.vmax = cb.vmax if show_colorbar is False: cb.remove() else: # clear the previous 2D from memory self.figure.clear() self.figure.subplots_adjust(left=0.1, right=.8, bottom=.1) data_x, data_y = numpy.meshgrid(self._data.x_bins[0:-1], self._data.y_bins[0:-1]) ax = Axes3D(self.figure) # Disable rotation for large sets. # TODO: Define "large" for a dataset SET_TOO_LARGE = 500 if len(data_x) > SET_TOO_LARGE: ax.disable_mouse_rotation() self.figure.canvas.resizing = False im = ax.plot_surface(data_x, data_y, output, rstride=1, cstride=1, cmap=cmap, linewidth=0, antialiased=False) self.ax.set_axis_off() if self.dimension != 3: self.figure.canvas.draw_idle() else: self.figure.canvas.draw() def update(self): self.figure.canvas.draw() def draw(self): self.figure.canvas.draw() def replacePlot(self, id, new_plot): """ Replace data in current chart. This effectively refreshes the chart with changes to one of its plots """ self.plot(data=new_plot) class Plotter2D(QtGui.QDialog, Plotter2DWidget): """ Plotter widget implementation """ def __init__(self, parent=None, quickplot=False, dimension=2): QtGui.QDialog.__init__(self) Plotter2DWidget.__init__(self, manager=parent, quickplot=quickplot, dimension=dimension) icon = QtGui.QIcon() icon.addPixmap(QtGui.QPixmap(":/res/ball.ico"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.setWindowIcon(icon)