# coding: utf-8 # /*########################################################################## # # Copyright (c) 2004-2018 European Synchrotron Radiation Facility # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE. # # ###########################################################################*/ """Matplotlib Plot backend.""" from __future__ import division __authors__ = ["V.A. Sole", "T. Vincent, H. Payno"] __license__ = "MIT" __date__ = "01/08/2018" import logging import datetime as dt import numpy from pkg_resources import parse_version as _parse_version _logger = logging.getLogger(__name__) from ... import qt # First of all init matplotlib and set its backend from ..matplotlib import FigureCanvasQTAgg import matplotlib from matplotlib.container import Container from matplotlib.figure import Figure from matplotlib.patches import Rectangle, Polygon from matplotlib.image import AxesImage from matplotlib.backend_bases import MouseEvent from matplotlib.lines import Line2D from matplotlib.collections import PathCollection, LineCollection from matplotlib.ticker import Formatter, ScalarFormatter, Locator from ....third_party.modest_image import ModestImage from . import BackendBase from .._utils import FLOAT32_MINPOS from .._utils.dtime_ticklayout import calcTicks, bestFormatString, timestamp class NiceDateLocator(Locator): """ Matplotlib Locator that uses Nice Numbers algorithm (adapted to dates) to find the tick locations. This results in the same number behaviour as when using the silx Open GL backend. Expects the data to be posix timestampes (i.e. seconds since 1970) """ def __init__(self, numTicks=5, tz=None): """ :param numTicks: target number of ticks :param datetime.tzinfo tz: optional time zone. None is local time. """ super(NiceDateLocator, self).__init__() self.numTicks = numTicks self._spacing = None self._unit = None self.tz = tz @property def spacing(self): """ The current spacing. Will be updated when new tick value are made""" return self._spacing @property def unit(self): """ The current DtUnit. Will be updated when new tick value are made""" return self._unit def __call__(self): """Return the locations of the ticks""" vmin, vmax = self.axis.get_view_interval() return self.tick_values(vmin, vmax) def tick_values(self, vmin, vmax): """ Calculates tick values """ if vmax < vmin: vmin, vmax = vmax, vmin # vmin and vmax should be timestamps (i.e. seconds since 1 Jan 1970) dtMin = dt.datetime.fromtimestamp(vmin, tz=self.tz) dtMax = dt.datetime.fromtimestamp(vmax, tz=self.tz) dtTicks, self._spacing, self._unit = \ calcTicks(dtMin, dtMax, self.numTicks) # Convert datetime back to time stamps. ticks = [timestamp(dtTick) for dtTick in dtTicks] return ticks class NiceAutoDateFormatter(Formatter): """ Matplotlib FuncFormatter that is linked to a NiceDateLocator and gives the best possible formats given the locators current spacing an date unit. """ def __init__(self, locator, tz=None): """ :param niceDateLocator: a NiceDateLocator object :param datetime.tzinfo tz: optional time zone. None is local time. """ super(NiceAutoDateFormatter, self).__init__() self.locator = locator self.tz = tz @property def formatString(self): if self.locator.spacing is None or self.locator.unit is None: # Locator has no spacing or units yet. Return elaborate fmtString return "Y-%m-%d %H:%M:%S" else: return bestFormatString(self.locator.spacing, self.locator.unit) def __call__(self, x, pos=None): """Return the format for tick val *x* at position *pos* Expects x to be a POSIX timestamp (seconds since 1 Jan 1970) """ dateTime = dt.datetime.fromtimestamp(x, tz=self.tz) tickStr = dateTime.strftime(self.formatString) return tickStr class _MarkerContainer(Container): """Marker artists container supporting draw/remove and text position update :param artists: Iterable with either one Line2D or a Line2D and a Text. The use of an iterable if enforced by Container being a subclass of tuple that defines a specific __new__. :param x: X coordinate of the marker (None for horizontal lines) :param y: Y coordinate of the marker (None for vertical lines) """ def __init__(self, artists, x, y): self.line = artists[0] self.text = artists[1] if len(artists) > 1 else None self.x = x self.y = y Container.__init__(self, artists) def draw(self, *args, **kwargs): """artist-like draw to broadcast draw to line and text""" self.line.draw(*args, **kwargs) if self.text is not None: self.text.draw(*args, **kwargs) def updateMarkerText(self, xmin, xmax, ymin, ymax): """Update marker text position and visibility according to plot limits :param xmin: X axis lower limit :param xmax: X axis upper limit :param ymin: Y axis lower limit :param ymax: Y axis upprt limit """ if self.text is not None: visible = ((self.x is None or xmin <= self.x <= xmax) and (self.y is None or ymin <= self.y <= ymax)) self.text.set_visible(visible) if self.x is not None and self.y is None: # vertical line delta = abs(ymax - ymin) if ymin > ymax: ymax = ymin ymax -= 0.005 * delta self.text.set_y(ymax) if self.x is None and self.y is not None: # Horizontal line delta = abs(xmax - xmin) if xmin > xmax: xmax = xmin xmax -= 0.005 * delta self.text.set_x(xmax) class BackendMatplotlib(BackendBase.BackendBase): """Base class for Matplotlib backend without a FigureCanvas. For interactive on screen plot, see :class:`BackendMatplotlibQt`. See :class:`BackendBase.BackendBase` for public API documentation. """ def __init__(self, plot, parent=None): super(BackendMatplotlib, self).__init__(plot, parent) # matplotlib is handling keep aspect ratio at draw time # When keep aspect ratio is on, and one changes the limits and # ask them *before* next draw has been performed he will get the # limits without applying keep aspect ratio. # This attribute is used to ensure consistent values returned # when getting the limits at the expense of a replot self._dirtyLimits = True self._axesDisplayed = True self._matplotlibVersion = _parse_version(matplotlib.__version__) self.fig = Figure() self.fig.set_facecolor("w") self.ax = self.fig.add_axes([.15, .15, .75, .75], label="left") self.ax2 = self.ax.twinx() self.ax2.set_label("right") # disable the use of offsets try: self.ax.get_yaxis().get_major_formatter().set_useOffset(False) self.ax.get_xaxis().get_major_formatter().set_useOffset(False) self.ax2.get_yaxis().get_major_formatter().set_useOffset(False) self.ax2.get_xaxis().get_major_formatter().set_useOffset(False) except: _logger.warning('Cannot disabled axes offsets in %s ' \ % matplotlib.__version__) # critical for picking!!!! self.ax2.set_zorder(0) self.ax2.set_autoscaley_on(True) self.ax.set_zorder(1) # this works but the figure color is left if self._matplotlibVersion < _parse_version('2'): self.ax.set_axis_bgcolor('none') else: self.ax.set_facecolor('none') self.fig.sca(self.ax) self._overlays = set() self._background = None self._colormaps = {} self._graphCursor = tuple() self._enableAxis('right', False) self._isXAxisTimeSeries = False # Add methods def addCurve(self, x, y, legend, color, symbol, linewidth, linestyle, yaxis, xerror, yerror, z, selectable, fill, alpha, symbolsize): for parameter in (x, y, legend, color, symbol, linewidth, linestyle, yaxis, z, selectable, fill, alpha, symbolsize): assert parameter is not None assert yaxis in ('left', 'right') if (len(color) == 4 and type(color[3]) in [type(1), numpy.uint8, numpy.int8]): color = numpy.array(color, dtype=numpy.float) / 255. if yaxis == "right": axes = self.ax2 self._enableAxis("right", True) else: axes = self.ax picker = 3 if selectable else None artists = [] # All the artists composing the curve # First add errorbars if any so they are behind the curve if xerror is not None or yerror is not None: if hasattr(color, 'dtype') and len(color) == len(x): errorbarColor = 'k' else: errorbarColor = color # On Debian 7 at least, Nx1 array yerr does not seems supported if (isinstance(yerror, numpy.ndarray) and yerror.ndim == 2 and yerror.shape[1] == 1 and len(x) != 1): yerror = numpy.ravel(yerror) errorbars = axes.errorbar(x, y, label=legend, xerr=xerror, yerr=yerror, linestyle=' ', color=errorbarColor) artists += list(errorbars.get_children()) if hasattr(color, 'dtype') and len(color) == len(x): # scatter plot if color.dtype not in [numpy.float32, numpy.float]: actualColor = color / 255. else: actualColor = color if linestyle not in ["", " ", None]: # scatter plot with an actual line ... # we need to assign a color ... curveList = axes.plot(x, y, label=legend, linestyle=linestyle, color=actualColor[0], linewidth=linewidth, picker=picker, marker=None) artists += list(curveList) scatter = axes.scatter(x, y, label=legend, color=actualColor, marker=symbol, picker=picker, s=symbolsize**2) artists.append(scatter) if fill: artists.append(axes.fill_between( x, FLOAT32_MINPOS, y, facecolor=actualColor[0], linestyle='')) else: # Curve curveList = axes.plot(x, y, label=legend, linestyle=linestyle, color=color, linewidth=linewidth, marker=symbol, picker=picker, markersize=symbolsize) artists += list(curveList) if fill: artists.append( axes.fill_between(x, FLOAT32_MINPOS, y, facecolor=color)) for artist in artists: artist.set_zorder(z) if alpha < 1: artist.set_alpha(alpha) return Container(artists) def addImage(self, data, legend, origin, scale, z, selectable, draggable, colormap, alpha): # Non-uniform image # http://wiki.scipy.org/Cookbook/Histograms # Non-linear axes # http://stackoverflow.com/questions/11488800/non-linear-axes-for-imshow-in-matplotlib for parameter in (data, legend, origin, scale, z, selectable, draggable): assert parameter is not None origin = float(origin[0]), float(origin[1]) scale = float(scale[0]), float(scale[1]) height, width = data.shape[0:2] picker = (selectable or draggable) # Debian 7 specific support # No transparent colormap with matplotlib < 1.2.0 # Add support for transparent colormap for uint8 data with # colormap with 256 colors, linear norm, [0, 255] range if self._matplotlibVersion < _parse_version('1.2.0'): if (len(data.shape) == 2 and colormap.getName() is None and colormap.getColormapLUT() is not None): colors = colormap.getColormapLUT() if (colors.shape[-1] == 4 and not numpy.all(numpy.equal(colors[3], 255))): # This is a transparent colormap if (colors.shape == (256, 4) and colormap.getNormalization() == 'linear' and not colormap.isAutoscale() and colormap.getVMin() == 0 and colormap.getVMax() == 255 and data.dtype == numpy.uint8): # Supported case, convert data to RGBA data = colors[data.reshape(-1)].reshape( data.shape + (4,)) else: _logger.warning( 'matplotlib %s does not support transparent ' 'colormap.', matplotlib.__version__) if ((height * width) > 5.0e5 and origin == (0., 0.) and scale == (1., 1.)): imageClass = ModestImage else: imageClass = AxesImage # All image are shown as RGBA image image = imageClass(self.ax, label="__IMAGE__" + legend, interpolation='nearest', picker=picker, zorder=z, origin='lower') if alpha < 1: image.set_alpha(alpha) # Set image extent xmin = origin[0] xmax = xmin + scale[0] * width if scale[0] < 0.: xmin, xmax = xmax, xmin ymin = origin[1] ymax = ymin + scale[1] * height if scale[1] < 0.: ymin, ymax = ymax, ymin image.set_extent((xmin, xmax, ymin, ymax)) # Set image data if scale[0] < 0. or scale[1] < 0.: # For negative scale, step by -1 xstep = 1 if scale[0] >= 0. else -1 ystep = 1 if scale[1] >= 0. else -1 data = data[::ystep, ::xstep] if self._matplotlibVersion < _parse_version('2.1'): # matplotlib 1.4.2 do not support float128 dtype = data.dtype if dtype.kind == "f" and dtype.itemsize >= 16: _logger.warning("Your matplotlib version do not support " "float128. Data converted to float64.") data = data.astype(numpy.float64) if data.ndim == 2: # Data image, convert to RGBA image data = colormap.applyToData(data) image.set_data(data) self.ax.add_artist(image) return image def addItem(self, x, y, legend, shape, color, fill, overlay, z): xView = numpy.array(x, copy=False) yView = numpy.array(y, copy=False) if shape == "line": item = self.ax.plot(x, y, label=legend, color=color, linestyle='-', marker=None)[0] elif shape == "hline": if hasattr(y, "__len__"): y = y[-1] item = self.ax.axhline(y, label=legend, color=color) elif shape == "vline": if hasattr(x, "__len__"): x = x[-1] item = self.ax.axvline(x, label=legend, color=color) elif shape == 'rectangle': xMin = numpy.nanmin(xView) xMax = numpy.nanmax(xView) yMin = numpy.nanmin(yView) yMax = numpy.nanmax(yView) w = xMax - xMin h = yMax - yMin item = Rectangle(xy=(xMin, yMin), width=w, height=h, fill=False, color=color) if fill: item.set_hatch('.') self.ax.add_patch(item) elif shape in ('polygon', 'polylines'): points = numpy.array((xView, yView)).T if shape == 'polygon': closed = True else: # shape == 'polylines' closed = numpy.all(numpy.equal(points[0], points[-1])) item = Polygon(points, closed=closed, fill=False, label=legend, color=color) if fill and shape == 'polygon': item.set_hatch('/') self.ax.add_patch(item) else: raise NotImplementedError("Unsupported item shape %s" % shape) item.set_zorder(z) if overlay: item.set_animated(True) self._overlays.add(item) return item def addMarker(self, x, y, legend, text, color, selectable, draggable, symbol, linestyle, linewidth, constraint): legend = "__MARKER__" + legend textArtist = None xmin, xmax = self.getGraphXLimits() ymin, ymax = self.getGraphYLimits(axis='left') if x is not None and y is not None: line = self.ax.plot(x, y, label=legend, linestyle=" ", color=color, marker=symbol, markersize=10.)[-1] if text is not None: if symbol is None: valign = 'baseline' else: valign = 'top' text = " " + text textArtist = self.ax.text(x, y, text, color=color, horizontalalignment='left', verticalalignment=valign) elif x is not None: line = self.ax.axvline(x, label=legend, color=color, linewidth=linewidth, linestyle=linestyle) if text is not None: # Y position will be updated in updateMarkerText call textArtist = self.ax.text(x, 1., " " + text, color=color, horizontalalignment='left', verticalalignment='top') elif y is not None: line = self.ax.axhline(y, label=legend, color=color, linewidth=linewidth, linestyle=linestyle) if text is not None: # X position will be updated in updateMarkerText call textArtist = self.ax.text(1., y, " " + text, color=color, horizontalalignment='right', verticalalignment='top') else: raise RuntimeError('A marker must at least have one coordinate') if selectable or draggable: line.set_picker(5) # All markers are overlays line.set_animated(True) if textArtist is not None: textArtist.set_animated(True) artists = [line] if textArtist is None else [line, textArtist] container = _MarkerContainer(artists, x, y) container.updateMarkerText(xmin, xmax, ymin, ymax) self._overlays.add(container) return container def _updateMarkers(self): xmin, xmax = self.ax.get_xbound() ymin, ymax = self.ax.get_ybound() for item in self._overlays: if isinstance(item, _MarkerContainer): item.updateMarkerText(xmin, xmax, ymin, ymax) # Remove methods def remove(self, item): # Warning: It also needs to remove extra stuff if added as for markers self._overlays.discard(item) try: item.remove() except ValueError: pass # Already removed e.g., in set[X|Y]AxisLogarithmic # Interaction methods def setGraphCursor(self, flag, color, linewidth, linestyle): if flag: lineh = self.ax.axhline( self.ax.get_ybound()[0], visible=False, color=color, linewidth=linewidth, linestyle=linestyle) lineh.set_animated(True) linev = self.ax.axvline( self.ax.get_xbound()[0], visible=False, color=color, linewidth=linewidth, linestyle=linestyle) linev.set_animated(True) self._graphCursor = lineh, linev else: if self._graphCursor is not None: lineh, linev = self._graphCursor lineh.remove() linev.remove() self._graphCursor = tuple() # Active curve def setCurveColor(self, curve, color): # Store Line2D and PathCollection for artist in curve.get_children(): if isinstance(artist, (Line2D, LineCollection)): artist.set_color(color) elif isinstance(artist, PathCollection): artist.set_facecolors(color) artist.set_edgecolors(color) else: _logger.warning( 'setActiveCurve ignoring artist %s', str(artist)) # Misc. def getWidgetHandle(self): return self.fig.canvas def _enableAxis(self, axis, flag=True): """Show/hide Y axis :param str axis: Axis name: 'left' or 'right' :param bool flag: Default, True """ assert axis in ('right', 'left') axes = self.ax2 if axis == 'right' else self.ax axes.get_yaxis().set_visible(flag) def replot(self): """Do not perform rendering. Override in subclass to actually draw something. """ # TODO images, markers? scatter plot? move in remove? # Right Y axis only support curve for now # Hide right Y axis if no line is present self._dirtyLimits = False if not self.ax2.lines: self._enableAxis('right', False) def saveGraph(self, fileName, fileFormat, dpi): # fileName can be also a StringIO or file instance if dpi is not None: self.fig.savefig(fileName, format=fileFormat, dpi=dpi) else: self.fig.savefig(fileName, format=fileFormat) self._plot._setDirtyPlot() # Graph labels def setGraphTitle(self, title): self.ax.set_title(title) def setGraphXLabel(self, label): self.ax.set_xlabel(label) def setGraphYLabel(self, label, axis): axes = self.ax if axis == 'left' else self.ax2 axes.set_ylabel(label) # Graph limits def setLimits(self, xmin, xmax, ymin, ymax, y2min=None, y2max=None): # Let matplotlib taking care of keep aspect ratio if any self._dirtyLimits = True self.ax.set_xlim(min(xmin, xmax), max(xmin, xmax)) if y2min is not None and y2max is not None: if not self.isYAxisInverted(): self.ax2.set_ylim(min(y2min, y2max), max(y2min, y2max)) else: self.ax2.set_ylim(max(y2min, y2max), min(y2min, y2max)) if not self.isYAxisInverted(): self.ax.set_ylim(min(ymin, ymax), max(ymin, ymax)) else: self.ax.set_ylim(max(ymin, ymax), min(ymin, ymax)) self._updateMarkers() def getGraphXLimits(self): if self._dirtyLimits and self.isKeepDataAspectRatio(): self.replot() # makes sure we get the right limits return self.ax.get_xbound() def setGraphXLimits(self, xmin, xmax): self._dirtyLimits = True self.ax.set_xlim(min(xmin, xmax), max(xmin, xmax)) self._updateMarkers() def getGraphYLimits(self, axis): assert axis in ('left', 'right') ax = self.ax2 if axis == 'right' else self.ax if not ax.get_visible(): return None if self._dirtyLimits and self.isKeepDataAspectRatio(): self.replot() # makes sure we get the right limits return ax.get_ybound() def setGraphYLimits(self, ymin, ymax, axis): ax = self.ax2 if axis == 'right' else self.ax if ymax < ymin: ymin, ymax = ymax, ymin self._dirtyLimits = True if self.isKeepDataAspectRatio(): # matplotlib keeps limits of shared axis when keeping aspect ratio # So x limits are kept when changing y limits.... # Change x limits first by taking into account aspect ratio # and then change y limits.. so matplotlib does not need # to make change (to y) to keep aspect ratio xmin, xmax = ax.get_xbound() curYMin, curYMax = ax.get_ybound() newXRange = (xmax - xmin) * (ymax - ymin) / (curYMax - curYMin) xcenter = 0.5 * (xmin + xmax) ax.set_xlim(xcenter - 0.5 * newXRange, xcenter + 0.5 * newXRange) if not self.isYAxisInverted(): ax.set_ylim(ymin, ymax) else: ax.set_ylim(ymax, ymin) self._updateMarkers() # Graph axes def setXAxisTimeZone(self, tz): super(BackendMatplotlib, self).setXAxisTimeZone(tz) # Make new formatter and locator with the time zone. self.setXAxisTimeSeries(self.isXAxisTimeSeries()) def isXAxisTimeSeries(self): return self._isXAxisTimeSeries def setXAxisTimeSeries(self, isTimeSeries): self._isXAxisTimeSeries = isTimeSeries if self._isXAxisTimeSeries: # We can't use a matplotlib.dates.DateFormatter because it expects # the data to be in datetimes. Silx works internally with # timestamps (floats). locator = NiceDateLocator(tz=self.getXAxisTimeZone()) self.ax.xaxis.set_major_locator(locator) self.ax.xaxis.set_major_formatter( NiceAutoDateFormatter(locator, tz=self.getXAxisTimeZone())) else: try: scalarFormatter = ScalarFormatter(useOffset=False) except: _logger.warning('Cannot disabled axes offsets in %s ' % matplotlib.__version__) scalarFormatter = ScalarFormatter() self.ax.xaxis.set_major_formatter(scalarFormatter) def setXAxisLogarithmic(self, flag): # Workaround for matplotlib 2.1.0 when one tries to set an axis # to log scale with both limits <= 0 # In this case a draw with positive limits is needed first if flag and self._matplotlibVersion >= _parse_version('2.1.0'): xlim = self.ax.get_xlim() if xlim[0] <= 0 and xlim[1] <= 0: self.ax.set_xlim(1, 10) self.draw() self.ax2.set_xscale('log' if flag else 'linear') self.ax.set_xscale('log' if flag else 'linear') def setYAxisLogarithmic(self, flag): # Workaround for matplotlib 2.0 issue with negative bounds # before switching to log scale if flag and self._matplotlibVersion >= _parse_version('2.0.0'): redraw = False for axis, dataRangeIndex in ((self.ax, 1), (self.ax2, 2)): ylim = axis.get_ylim() if ylim[0] <= 0 or ylim[1] <= 0: dataRange = self._plot.getDataRange()[dataRangeIndex] if dataRange is None: dataRange = 1, 100 # Fallback axis.set_ylim(*dataRange) redraw = True if redraw: self.draw() self.ax2.set_yscale('log' if flag else 'linear') self.ax.set_yscale('log' if flag else 'linear') def setYAxisInverted(self, flag): if self.ax.yaxis_inverted() != bool(flag): self.ax.invert_yaxis() def isYAxisInverted(self): return self.ax.yaxis_inverted() def isKeepDataAspectRatio(self): return self.ax.get_aspect() in (1.0, 'equal') def setKeepDataAspectRatio(self, flag): self.ax.set_aspect(1.0 if flag else 'auto') self.ax2.set_aspect(1.0 if flag else 'auto') def setGraphGrid(self, which): self.ax.grid(False, which='both') # Disable all grid first if which is not None: self.ax.grid(True, which=which) # Data <-> Pixel coordinates conversion def _mplQtYAxisCoordConversion(self, y): """Qt origin (top) to/from matplotlib origin (bottom) conversion. :rtype: float """ height = self.fig.get_window_extent().height return height - y def dataToPixel(self, x, y, axis): ax = self.ax2 if axis == "right" else self.ax pixels = ax.transData.transform_point((x, y)) xPixel, yPixel = pixels.T # Convert from matplotlib origin (bottom) to Qt origin (top) yPixel = self._mplQtYAxisCoordConversion(yPixel) return xPixel, yPixel def pixelToData(self, x, y, axis, check): ax = self.ax2 if axis == "right" else self.ax # Convert from Qt origin (top) to matplotlib origin (bottom) y = self._mplQtYAxisCoordConversion(y) inv = ax.transData.inverted() x, y = inv.transform_point((x, y)) if check: xmin, xmax = self.getGraphXLimits() ymin, ymax = self.getGraphYLimits(axis=axis) if x > xmax or x < xmin or y > ymax or y < ymin: return None # (x, y) is out of plot area return x, y def getPlotBoundsInPixels(self): bbox = self.ax.get_window_extent() # Warning this is not returning int... return (bbox.xmin, self._mplQtYAxisCoordConversion(bbox.ymax), bbox.width, bbox.height) def setAxesDisplayed(self, displayed): """Display or not the axes. :param bool displayed: If `True` axes are displayed. If `False` axes are not anymore visible and the margin used for them is removed. """ BackendBase.BackendBase.setAxesDisplayed(self, displayed) if displayed: # show axes and viewbox rect self.ax.set_axis_on() self.ax2.set_axis_on() # set the default margins self.ax.set_position([.15, .15, .75, .75]) self.ax2.set_position([.15, .15, .75, .75]) else: # hide axes and viewbox rect self.ax.set_axis_off() self.ax2.set_axis_off() # remove external margins self.ax.set_position([0, 0, 1, 1]) self.ax2.set_position([0, 0, 1, 1]) self._plot._setDirtyPlot() class BackendMatplotlibQt(FigureCanvasQTAgg, BackendMatplotlib): """QWidget matplotlib backend using a QtAgg canvas. It adds fast overlay drawing and mouse event management. """ _sigPostRedisplay = qt.Signal() """Signal handling automatic asynchronous replot""" def __init__(self, plot, parent=None): BackendMatplotlib.__init__(self, plot, parent) FigureCanvasQTAgg.__init__(self, self.fig) self.setParent(parent) self._limitsBeforeResize = None FigureCanvasQTAgg.setSizePolicy( self, qt.QSizePolicy.Expanding, qt.QSizePolicy.Expanding) FigureCanvasQTAgg.updateGeometry(self) # Make postRedisplay asynchronous using Qt signal self._sigPostRedisplay.connect( super(BackendMatplotlibQt, self).postRedisplay, qt.Qt.QueuedConnection) self._picked = None self.mpl_connect('button_press_event', self._onMousePress) self.mpl_connect('button_release_event', self._onMouseRelease) self.mpl_connect('motion_notify_event', self._onMouseMove) self.mpl_connect('scroll_event', self._onMouseWheel) def contextMenuEvent(self, event): """Override QWidget.contextMenuEvent to implement the context menu""" # Makes sure it is overridden (issue with PySide) BackendBase.BackendBase.contextMenuEvent(self, event) def postRedisplay(self): self._sigPostRedisplay.emit() # Mouse event forwarding _MPL_TO_PLOT_BUTTONS = {1: 'left', 2: 'middle', 3: 'right'} def _onMousePress(self, event): self._plot.onMousePress( event.x, self._mplQtYAxisCoordConversion(event.y), self._MPL_TO_PLOT_BUTTONS[event.button]) def _onMouseMove(self, event): if self._graphCursor: lineh, linev = self._graphCursor if event.inaxes != self.ax and lineh.get_visible(): lineh.set_visible(False) linev.set_visible(False) self._plot._setDirtyPlot(overlayOnly=True) else: linev.set_visible(True) linev.set_xdata((event.xdata, event.xdata)) lineh.set_visible(True) lineh.set_ydata((event.ydata, event.ydata)) self._plot._setDirtyPlot(overlayOnly=True) # onMouseMove must trigger replot if dirty flag is raised self._plot.onMouseMove( event.x, self._mplQtYAxisCoordConversion(event.y)) def _onMouseRelease(self, event): self._plot.onMouseRelease( event.x, self._mplQtYAxisCoordConversion(event.y), self._MPL_TO_PLOT_BUTTONS[event.button]) def _onMouseWheel(self, event): self._plot.onMouseWheel( event.x, self._mplQtYAxisCoordConversion(event.y), event.step) def leaveEvent(self, event): """QWidget event handler""" self._plot.onMouseLeaveWidget() # picking def _onPick(self, event): # TODO not very nice and fragile, find a better way? # Make a selection according to kind if self._picked is None: _logger.error('Internal picking error') return label = event.artist.get_label() if label.startswith('__MARKER__'): self._picked.append({'kind': 'marker', 'legend': label[10:]}) elif label.startswith('__IMAGE__'): self._picked.append({'kind': 'image', 'legend': label[9:]}) else: # it's a curve, item have no picker for now if not isinstance(event.artist, (PathCollection, Line2D)): _logger.info('Unsupported artist, ignored') return self._picked.append({'kind': 'curve', 'legend': label, 'indices': event.ind}) def pickItems(self, x, y, kinds): self._picked = [] # Weird way to do an explicit picking: Simulate a button press event mouseEvent = MouseEvent('button_press_event', self, x, self._mplQtYAxisCoordConversion(y)) cid = self.mpl_connect('pick_event', self._onPick) self.fig.pick(mouseEvent) self.mpl_disconnect(cid) picked = [p for p in self._picked if p['kind'] in kinds] self._picked = None return picked # replot control def resizeEvent(self, event): # Store current limits self._limitsBeforeResize = ( self.ax.get_xbound(), self.ax.get_ybound(), self.ax2.get_ybound()) FigureCanvasQTAgg.resizeEvent(self, event) if self.isKeepDataAspectRatio() or self._overlays or self._graphCursor: # This is needed with matplotlib 1.5.x and 2.0.x self._plot._setDirtyPlot() def _drawOverlays(self): """Draw overlays if any.""" if self._overlays or self._graphCursor: # There is some overlays or crosshair # This assume that items are only on left/bottom Axes for item in self._overlays: self.ax.draw_artist(item) for item in self._graphCursor: self.ax.draw_artist(item) def draw(self): """Overload draw It performs a full redraw (including overlays) of the plot. It also resets background and emit limits changed signal. This is directly called by matplotlib for widget resize. """ # Starting with mpl 2.1.0, toggling autoscale raises a ValueError # in some situations. See #1081, #1136, #1163, if self._matplotlibVersion >= _parse_version("2.0.0"): try: FigureCanvasQTAgg.draw(self) except ValueError as err: _logger.debug( "ValueError caught while calling FigureCanvasQTAgg.draw: " "'%s'", err) else: FigureCanvasQTAgg.draw(self) if self._overlays or self._graphCursor: # Save background self._background = self.copy_from_bbox(self.fig.bbox) else: self._background = None # Reset background # Check if limits changed due to a resize of the widget if self._limitsBeforeResize is not None: xLimits, yLimits, yRightLimits = self._limitsBeforeResize self._limitsBeforeResize = None if (xLimits != self.ax.get_xbound() or yLimits != self.ax.get_ybound()): self._updateMarkers() if xLimits != self.ax.get_xbound(): self._plot.getXAxis()._emitLimitsChanged() if yLimits != self.ax.get_ybound(): self._plot.getYAxis(axis='left')._emitLimitsChanged() if yRightLimits != self.ax2.get_ybound(): self._plot.getYAxis(axis='right')._emitLimitsChanged() self._drawOverlays() def replot(self): BackendMatplotlib.replot(self) dirtyFlag = self._plot._getDirtyPlot() if dirtyFlag == 'overlay': # Only redraw overlays using fast rendering path if self._background is None: self._background = self.copy_from_bbox(self.fig.bbox) self.restore_region(self._background) self._drawOverlays() self.blit(self.fig.bbox) elif dirtyFlag: # Need full redraw self.draw() # Workaround issue of rendering overlays with some matplotlib versions if (_parse_version('1.5') <= self._matplotlibVersion < _parse_version('2.1') and not hasattr(self, '_firstReplot')): self._firstReplot = False if self._overlays or self._graphCursor: qt.QTimer.singleShot(0, self.draw) # Request async draw # cursor _QT_CURSORS = { BackendBase.CURSOR_DEFAULT: qt.Qt.ArrowCursor, BackendBase.CURSOR_POINTING: qt.Qt.PointingHandCursor, BackendBase.CURSOR_SIZE_HOR: qt.Qt.SizeHorCursor, BackendBase.CURSOR_SIZE_VER: qt.Qt.SizeVerCursor, BackendBase.CURSOR_SIZE_ALL: qt.Qt.SizeAllCursor, } def setGraphCursorShape(self, cursor): if cursor is None: FigureCanvasQTAgg.unsetCursor(self) else: cursor = self._QT_CURSORS[cursor] FigureCanvasQTAgg.setCursor(self, qt.QCursor(cursor))