Source code for silx.gui.plot.ScatterView

# coding: utf-8
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"""A widget dedicated to display scatter plots

It is based on a :class:`~silx.gui.plot.PlotWidget` with additional tools
for scatter plots.
"""

__authors__ = ["T. Vincent"]
__license__ = "MIT"
__date__ = "14/06/2018"


import logging
import weakref

import numpy

from . import items
from . import PlotWidget
from . import tools
from .actions import histogram as actions_histogram
from .tools.profile import ScatterProfileToolBar
from .ColorBar import ColorBarWidget
from .ScatterMaskToolsWidget import ScatterMaskToolsWidget

from ..widgets.BoxLayoutDockWidget import BoxLayoutDockWidget
from .. import qt, icons
from ...utils.proxy import docstring
from ...utils.weakref import WeakMethodProxy


_logger = logging.getLogger(__name__)


[docs]class ScatterView(qt.QMainWindow): """Main window with a PlotWidget and tools specific for scatter plots. :param parent: The parent of this widget :param backend: The backend to use for the plot (default: matplotlib). See :class:`~silx.gui.plot.PlotWidget` for the list of supported backend. :type backend: Union[str,~silx.gui.plot.backends.BackendBase.BackendBase] """ _SCATTER_LEGEND = ' ' """Legend used for the scatter item""" def __init__(self, parent=None, backend=None): super(ScatterView, self).__init__(parent=parent) if parent is not None: # behave as a widget self.setWindowFlags(qt.Qt.Widget) else: self.setWindowTitle('ScatterView') # Create plot widget plot = PlotWidget(parent=self, backend=backend) self._plot = weakref.ref(plot) # Add an empty scatter self.__createEmptyScatter() # Create colorbar widget with white background self._colorbar = ColorBarWidget(parent=self, plot=plot) self._colorbar.setAutoFillBackground(True) palette = self._colorbar.palette() palette.setColor(qt.QPalette.Window, qt.Qt.white) self._colorbar.setPalette(palette) # Create PositionInfo widget self.__lastPickingPos = None self.__pickingCache = None self._positionInfo = tools.PositionInfo( plot=plot, converters=(('X', WeakMethodProxy(self._getPickedX)), ('Y', WeakMethodProxy(self._getPickedY)), ('Data', WeakMethodProxy(self._getPickedValue)), ('Index', WeakMethodProxy(self._getPickedIndex)))) # Combine plot, position info and colorbar into central widget gridLayout = qt.QGridLayout() gridLayout.setSpacing(0) gridLayout.setContentsMargins(0, 0, 0, 0) gridLayout.addWidget(plot, 0, 0) gridLayout.addWidget(self._colorbar, 0, 1) gridLayout.addWidget(self._positionInfo, 1, 0, 1, -1) gridLayout.setRowStretch(0, 1) gridLayout.setColumnStretch(0, 1) centralWidget = qt.QWidget(self) centralWidget.setLayout(gridLayout) self.setCentralWidget(centralWidget) # Create mask tool dock widget self._maskToolsWidget = ScatterMaskToolsWidget(parent=self, plot=plot) self._maskDock = BoxLayoutDockWidget() self._maskDock.setWindowTitle('Scatter Mask') self._maskDock.setWidget(self._maskToolsWidget) self._maskDock.setVisible(False) self.addDockWidget(qt.Qt.BottomDockWidgetArea, self._maskDock) self._maskAction = self._maskDock.toggleViewAction() self._maskAction.setIcon(icons.getQIcon('image-mask')) self._maskAction.setToolTip("Display/hide mask tools") self._intensityHistoAction = actions_histogram.PixelIntensitiesHistoAction(plot=plot, parent=self) # Create toolbars self._interactiveModeToolBar = tools.InteractiveModeToolBar( parent=self, plot=plot) self._scatterToolBar = tools.ScatterToolBar( parent=self, plot=plot) self._scatterToolBar.addAction(self._maskAction) self._scatterToolBar.addAction(self._intensityHistoAction) self._profileToolBar = ScatterProfileToolBar(parent=self, plot=plot) self._outputToolBar = tools.OutputToolBar(parent=self, plot=plot) # Activate shortcuts in PlotWindow widget: for toolbar in (self._interactiveModeToolBar, self._scatterToolBar, self._profileToolBar, self._outputToolBar): self.addToolBar(toolbar) for action in toolbar.actions(): self.addAction(action) def __createEmptyScatter(self): """Create an empty scatter item that is used to display the data :rtype: ~silx.gui.plot.items.Scatter """ plot = self.getPlotWidget() plot.addScatter(x=(), y=(), value=(), legend=self._SCATTER_LEGEND) scatter = plot._getItem( kind='scatter', legend=self._SCATTER_LEGEND) # Profile is not selectable, # so it does not interfere with profile interaction scatter._setSelectable(False) return scatter def _pickScatterData(self, x, y): """Get data and index and value of top most scatter plot at position (x, y) :param float x: X position in plot coordinates :param float y: Y position in plot coordinates :return: The data index and value at that point or None """ pickingPos = x, y if self.__lastPickingPos != pickingPos: self.__pickingCache = None self.__lastPickingPos = pickingPos plot = self.getPlotWidget() if plot is not None: pixelPos = plot.dataToPixel(x, y) if pixelPos is not None: # Start from top-most item result = plot._pickTopMost( pixelPos[0], pixelPos[1], lambda item: isinstance(item, items.Scatter)) if result is not None: item = result.getItem() if item.getVisualization() is items.Scatter.Visualization.BINNED_STATISTIC: # Get highest index of closest points selected = result.getIndices(copy=False)[::-1] dataIndex = selected[numpy.argmin( (item.getXData(copy=False)[selected] - x)**2 + (item.getYData(copy=False)[selected] - y)**2)] else: # Get last index # with matplotlib it should be the top-most point dataIndex = result.getIndices(copy=False)[-1] self.__pickingCache = ( dataIndex, item.getXData(copy=False)[dataIndex], item.getYData(copy=False)[dataIndex], item.getValueData(copy=False)[dataIndex]) return self.__pickingCache def _getPickedIndex(self, x, y): """Get data index of top most scatter plot at position (x, y) :param float x: X position in plot coordinates :param float y: Y position in plot coordinates :return: The data index at that point or '-' """ picking = self._pickScatterData(x, y) return '-' if picking is None else picking[0] def _getPickedX(self, x, y): """Returns X position snapped to scatter plot when close enough :param float x: :param float y: :rtype: float """ picking = self._pickScatterData(x, y) return x if picking is None else picking[1] def _getPickedY(self, x, y): """Returns Y position snapped to scatter plot when close enough :param float x: :param float y: :rtype: float """ picking = self._pickScatterData(x, y) return y if picking is None else picking[2] def _getPickedValue(self, x, y): """Get data value of top most scatter plot at position (x, y) :param float x: X position in plot coordinates :param float y: Y position in plot coordinates :return: The data value at that point or '-' """ picking = self._pickScatterData(x, y) return '-' if picking is None else picking[3] def _mouseInPlotArea(self, x, y): """Clip mouse coordinates to plot area coordinates :param float x: X position in pixels :param float y: Y position in pixels :return: (x, y) in data coordinates """ plot = self.getPlotWidget() left, top, width, height = plot.getPlotBoundsInPixels() xPlot = numpy.clip(x, left, left + width - 1) yPlot = numpy.clip(y, top, top + height - 1) return xPlot, yPlot
[docs] def getPlotWidget(self): """Returns the :class:`~silx.gui.plot.PlotWidget` this window is based on. :rtype: ~silx.gui.plot.PlotWidget """ return self._plot()
[docs] def getPositionInfoWidget(self): """Returns the widget display mouse coordinates information. :rtype: ~silx.gui.plot.tools.PositionInfo """ return self._positionInfo
[docs] def getMaskToolsWidget(self): """Returns the widget controlling mask drawing :rtype: ~silx.gui.plot.ScatterMaskToolsWidget """ return self._maskToolsWidget
[docs] def getInteractiveModeToolBar(self): """Returns QToolBar controlling interactive mode. :rtype: ~silx.gui.plot.tools.InteractiveModeToolBar """ return self._interactiveModeToolBar
[docs] def getScatterToolBar(self): """Returns QToolBar providing scatter plot tools. :rtype: ~silx.gui.plot.tools.ScatterToolBar """ return self._scatterToolBar
[docs] def getScatterProfileToolBar(self): """Returns QToolBar providing scatter profile tools. :rtype: ~silx.gui.plot.tools.profile.ScatterProfileToolBar """ return self._profileToolBar
[docs] def getOutputToolBar(self): """Returns QToolBar containing save, copy and print actions :rtype: ~silx.gui.plot.tools.OutputToolBar """ return self._outputToolBar
[docs] def setColormap(self, colormap=None): """Set the colormap for the displayed scatter and the default plot colormap. :param ~silx.gui.colors.Colormap colormap: The description of the colormap. """ self.getScatterItem().setColormap(colormap) # Resilient to call to PlotWidget API (e.g., clear) self.getPlotWidget().setDefaultColormap(colormap)
[docs] def getColormap(self): """Return the colormap object in use. :return: Colormap currently in use :rtype: ~silx.gui.colors.Colormap """ return self.getScatterItem().getColormap()
# Control displayed scatter plot
[docs] def setData(self, x, y, value, xerror=None, yerror=None, alpha=None, copy=True): """Set the data of the scatter plot. To reset the scatter plot, set x, y and value to None. :param Union[numpy.ndarray,None] x: X coordinates. :param Union[numpy.ndarray,None] y: Y coordinates. :param Union[numpy.ndarray,None] value: The data corresponding to the value of the data points. :param xerror: Values with the uncertainties on the x values. If it is an array, it can either be a 1D array of same length as the data or a 2D array with 2 rows of same length as the data: row 0 for positive errors, row 1 for negative errors. :type xerror: A float, or a numpy.ndarray of float32. :param yerror: Values with the uncertainties on the y values :type yerror: A float, or a numpy.ndarray of float32. See xerror. :param alpha: Values with the transparency (between 0 and 1) :type alpha: A float, or a numpy.ndarray of float32 :param bool copy: True make a copy of the data (default), False to use provided arrays. """ x = () if x is None else x y = () if y is None else y value = () if value is None else value self.getScatterItem().setData( x=x, y=y, value=value, xerror=xerror, yerror=yerror, alpha=alpha, copy=copy)
[docs] @docstring(items.Scatter) def getData(self, *args, **kwargs): return self.getScatterItem().getData(*args, **kwargs)
[docs] def getScatterItem(self): """Returns the plot item displaying the scatter data. This allows to set the style of the displayed scatter. :rtype: ~silx.gui.plot.items.Scatter """ plot = self.getPlotWidget() scatter = plot._getItem(kind='scatter', legend=self._SCATTER_LEGEND) if scatter is None: # Resilient to call to PlotWidget API (e.g., clear) scatter = self.__createEmptyScatter() return scatter
# Convenient proxies
[docs] @docstring(PlotWidget) def getXAxis(self, *args, **kwargs): return self.getPlotWidget().getXAxis(*args, **kwargs)
[docs] @docstring(PlotWidget) def getYAxis(self, *args, **kwargs): return self.getPlotWidget().getYAxis(*args, **kwargs)
[docs] @docstring(PlotWidget) def setGraphTitle(self, *args, **kwargs): return self.getPlotWidget().setGraphTitle(*args, **kwargs)
[docs] @docstring(PlotWidget) def getGraphTitle(self, *args, **kwargs): return self.getPlotWidget().getGraphTitle(*args, **kwargs)
[docs] @docstring(PlotWidget) def resetZoom(self, *args, **kwargs): return self.getPlotWidget().resetZoom(*args, **kwargs)
[docs] @docstring(ScatterMaskToolsWidget) def getSelectionMask(self, *args, **kwargs): return self.getMaskToolsWidget().getSelectionMask(*args, **kwargs)
[docs] @docstring(ScatterMaskToolsWidget) def setSelectionMask(self, *args, **kwargs): return self.getMaskToolsWidget().setSelectionMask(*args, **kwargs)