Source code for silx.gui.plot.backends.BackendMatplotlib

# coding: utf-8
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"""Matplotlib Plot backend."""

from __future__ import division

__authors__ = ["V.A. Sole", "T. Vincent, H. Payno"]
__license__ = "MIT"
__date__ = "21/12/2018"


import logging
import datetime as dt
from typing import Tuple
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 ...utils.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.text import Text
from matplotlib.collections import PathCollection, LineCollection
from matplotlib.ticker import Formatter, ScalarFormatter, Locator
from matplotlib.tri import Triangulation
from matplotlib.collections import TriMesh
from matplotlib import path as mpath

from . import BackendBase
from .. import items
from .._utils import FLOAT32_MINPOS
from .._utils.dtime_ticklayout import calcTicks, bestFormatString, timestamp
from ...qt import inspect as qt_inspect

_PATCH_LINESTYLE = {
    "-": 'solid',
    "--": 'dashed',
    '-.': 'dashdot',
    ':': 'dotted',
    '': "solid",
    None: "solid",
}
"""Patches do not uses the same matplotlib syntax"""

_MARKER_PATHS = {}
"""Store cached extra marker paths"""

_SPECIAL_MARKERS = {
    'tickleft': 0,
    'tickright': 1,
    'tickup': 2,
    'tickdown': 3,
    'caretleft': 4,
    'caretright': 5,
    'caretup': 6,
    'caretdown': 7,
}


[docs]def normalize_linestyle(linestyle): """Normalize known old-style linestyle, else return the provided value.""" return _PATCH_LINESTYLE.get(linestyle, linestyle)
[docs]def get_path_from_symbol(symbol): """Get the path representation of a symbol, else None if it is not provided. :param str symbol: Symbol description used by silx :rtype: Union[None,matplotlib.path.Path] """ if symbol == u'\u2665': path = _MARKER_PATHS.get(symbol, None) if path is not None: return path vertices = numpy.array([ [0,-99], [31,-73], [47,-55], [55,-46], [63,-37], [94,-2], [94,33], [94,69], [71,89], [47,89], [24,89], [8,74], [0,58], [-8,74], [-24,89], [-47,89], [-71,89], [-94,69], [-94,33], [-94,-2], [-63,-37], [-55,-46], [-47,-55], [-31,-73], [0,-99], [0,-99]]) codes = [mpath.Path.CURVE4] * len(vertices) codes[0] = mpath.Path.MOVETO codes[-1] = mpath.Path.CLOSEPOLY path = mpath.Path(vertices, codes) _MARKER_PATHS[symbol] = path return path return None
[docs]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)
[docs] 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) try: dtMin = dt.datetime.fromtimestamp(vmin, tz=self.tz) dtMax = dt.datetime.fromtimestamp(vmax, tz=self.tz) except ValueError: _logger.warning("Data range cannot be displayed with time axis") return [] 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
[docs]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 _PickableContainer(Container): """Artists container with a :meth:`contains` method""" def __init__(self, *args, **kwargs): Container.__init__(self, *args, **kwargs) self.__zorder = None @property def axes(self): """Mimin Artist.axes""" for child in self.get_children(): if hasattr(child, 'axes'): return child.axes return None def draw(self, *args, **kwargs): """artist-like draw to broadcast draw to children""" for child in self.get_children(): child.draw(*args, **kwargs) def get_zorder(self): """Mimic Artist.get_zorder""" return self.__zorder def set_zorder(self, z): """Mimic Artist.set_zorder to broadcast to children""" if z != self.__zorder: self.__zorder = z for child in self.get_children(): child.set_zorder(z) def contains(self, mouseevent): """Mimic Artist.contains, and call it on all children. :param mouseevent: :return: Picking status and associated information as a dict :rtype: (bool,dict) """ # Goes through children from front to back and return first picked one. for child in reversed(self.get_children()): picked, info = child.contains(mouseevent) if picked: return picked, info return False, {} class _TextWithOffset(Text): """Text object which can be displayed at a specific position of the plot, but with a pixel offset""" def __init__(self, *args, **kwargs): Text.__init__(self, *args, **kwargs) self.pixel_offset = (0, 0) self.__cache = None def draw(self, renderer): self.__cache = None return Text.draw(self, renderer) def __get_xy(self): if self.__cache is not None: return self.__cache align = self.get_horizontalalignment() if align == "left": xoffset = self.pixel_offset[0] elif align == "right": xoffset = -self.pixel_offset[0] else: xoffset = 0 align = self.get_verticalalignment() if align == "top": yoffset = -self.pixel_offset[1] elif align == "bottom": yoffset = self.pixel_offset[1] else: yoffset = 0 trans = self.get_transform() x = super(_TextWithOffset, self).convert_xunits(self._x) y = super(_TextWithOffset, self).convert_xunits(self._y) pos = x, y try: invtrans = trans.inverted() except numpy.linalg.LinAlgError: # Cannot inverse transform, fallback: pos without offset self.__cache = None return pos proj = trans.transform_point(pos) proj = proj + numpy.array((xoffset, yoffset)) pos = invtrans.transform_point(proj) self.__cache = pos return pos def convert_xunits(self, x): """Return the pixel position of the annotated point.""" return self.__get_xy()[0] def convert_yunits(self, y): """Return the pixel position of the annotated point.""" return self.__get_xy()[1] class _MarkerContainer(_PickableContainer): """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, symbol, x, y, yAxis): self.line = artists[0] self.text = artists[1] if len(artists) > 1 else None self.symbol = symbol self.x = x self.y = y self.yAxis = yAxis _PickableContainer.__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, yinverted): """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 upper limit :param yinverted: True if the y axis is inverted """ 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 not None: if self.symbol is None: valign = 'baseline' else: if yinverted: valign = 'bottom' else: valign = 'top' self.text.set_verticalalignment(valign) elif self.y is None: # vertical line # Always display it on top center = (ymax + ymin) * 0.5 pos = (ymax - ymin) * 0.5 * 0.99 if yinverted: pos = -pos self.text.set_y(center + pos) elif self.x is None: # Horizontal line delta = abs(xmax - xmin) if xmin > xmax: xmax = xmin xmax -= 0.005 * delta self.text.set_x(xmax) def contains(self, mouseevent): """Mimic Artist.contains, and call it on the line Artist. :param mouseevent: :return: Picking status and associated information as a dict :rtype: (bool,dict) """ return self.line.contains(mouseevent) class _DoubleColoredLinePatch(matplotlib.patches.Patch): """Matplotlib patch to display any patch using double color.""" def __init__(self, patch): super(_DoubleColoredLinePatch, self).__init__() self.__patch = patch self.linebgcolor = None def __getattr__(self, name): return getattr(self.__patch, name) def draw(self, renderer): oldLineStype = self.__patch.get_linestyle() if self.linebgcolor is not None and oldLineStype != "solid": oldLineColor = self.__patch.get_edgecolor() oldHatch = self.__patch.get_hatch() self.__patch.set_linestyle("solid") self.__patch.set_edgecolor(self.linebgcolor) self.__patch.set_hatch(None) self.__patch.draw(renderer) self.__patch.set_linestyle(oldLineStype) self.__patch.set_edgecolor(oldLineColor) self.__patch.set_hatch(oldHatch) self.__patch.draw(renderer) def set_transform(self, transform): self.__patch.set_transform(transform) def get_path(self): return self.__patch.get_path() def contains(self, mouseevent, radius=None): return self.__patch.contains(mouseevent, radius) def contains_point(self, point, radius=None): return self.__patch.contains_point(point, radius)
[docs]class Image(AxesImage): """An AxesImage with a fast path for uint8 RGBA images. :param List[float] silx_origin: (ox, oy) Offset of the image. :param List[float] silx_scale: (sx, sy) Scale of the image. """ def __init__(self, *args, silx_origin=(0., 0.), silx_scale=(1., 1.), **kwargs): super().__init__(*args, **kwargs) self.__silx_origin = silx_origin self.__silx_scale = silx_scale
[docs] def contains(self, mouseevent): """Overridden to fill 'ind' with row and column""" inside, info = super().contains(mouseevent) if inside: x, y = mouseevent.xdata, mouseevent.ydata ox, oy = self.__silx_origin sx, sy = self.__silx_scale height, width = self.get_size() column = numpy.clip(int((x - ox) / sx), 0, width - 1) row = numpy.clip(int((y - oy) / sy), 0, height - 1) info['ind'] = (row,), (column,) return inside, info
[docs] def set_data(self, A): """Overridden to add a fast path for RGBA unit8 images""" A = numpy.array(A, copy=False) if A.ndim != 3 or A.shape[2] != 4 or A.dtype != numpy.uint8: super(Image, self).set_data(A) else: # Call AxesImage.set_data with small data to set attributes super(Image, self).set_data(numpy.zeros((2, 2, 4), dtype=A.dtype)) self._A = A # Override stored data
[docs]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") # Make sure background of Axes is displayed self.ax2.patch.set_visible(False) self.ax.patch.set_visible(True) # Set axis zorder=0.5 so grid is displayed at 0.5 self.ax.set_axisbelow(True) # disable the use of offsets try: axes = [ self.ax.get_yaxis().get_major_formatter(), self.ax.get_xaxis().get_major_formatter(), self.ax2.get_yaxis().get_major_formatter(), self.ax2.get_xaxis().get_major_formatter(), ] for axis in axes: axis.set_useOffset(False) axis.set_scientific(False) except: _logger.warning('Cannot disabled axes offsets in %s ' % matplotlib.__version__) self.ax2.set_autoscaley_on(True) # 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._background = None self._colormaps = {} self._graphCursor = tuple() self._enableAxis('right', False) self._isXAxisTimeSeries = False
[docs] def getItemsFromBackToFront(self, condition=None): """Order as BackendBase + take into account matplotlib Axes structure""" def axesOrder(item): if item.isOverlay(): return 2 elif isinstance(item, items.YAxisMixIn) and item.getYAxis() == 'right': return 1 else: return 0 return sorted( BackendBase.BackendBase.getItemsFromBackToFront( self, condition=condition), key=axesOrder)
def _overlayItems(self): """Generator of backend renderer for overlay items""" for item in self._plot.getItems(): if (item.isOverlay() and item.isVisible() and item._backendRenderer is not None): yield item._backendRenderer def _hasOverlays(self): """Returns whether there is an overlay layer or not. The overlay layers contains overlay items and the crosshair. :rtype: bool """ if self._graphCursor: return True # There is the crosshair for item in self._overlayItems(): return True # There is at least one overlay item return False # Add methods def _getMarkerFromSymbol(self, symbol): """Returns a marker that can be displayed by matplotlib. :param str symbol: A symbol description used by silx :rtype: Union[str,int,matplotlib.path.Path] """ path = get_path_from_symbol(symbol) if path is not None: return path num = _SPECIAL_MARKERS.get(symbol, None) if num is not None: return num # This symbol must be supported by matplotlib return symbol
[docs] def addCurve(self, x, y, color, symbol, linewidth, linestyle, yaxis, xerror, yerror, fill, alpha, symbolsize, baseline): for parameter in (x, y, color, symbol, linewidth, linestyle, yaxis, 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.float64) / 255. if yaxis == "right": axes = self.ax2 self._enableAxis("right", True) else: axes = self.ax pickradius = 3 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 # Nx1 error array deprecated in matplotlib >=3.1 (removed in 3.3) if (isinstance(xerror, numpy.ndarray) and xerror.ndim == 2 and xerror.shape[1] == 1): xerror = numpy.ravel(xerror) if (isinstance(yerror, numpy.ndarray) and yerror.ndim == 2 and yerror.shape[1] == 1): yerror = numpy.ravel(yerror) errorbars = axes.errorbar(x, y, 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.float64]: 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, linestyle=linestyle, color=actualColor[0], linewidth=linewidth, picker=True, pickradius=pickradius, marker=None) artists += list(curveList) marker = self._getMarkerFromSymbol(symbol) scatter = axes.scatter(x, y, color=actualColor, marker=marker, picker=True, pickradius=pickradius, s=symbolsize**2) artists.append(scatter) if fill: if baseline is None: _baseline = FLOAT32_MINPOS else: _baseline = baseline artists.append(axes.fill_between( x, _baseline, y, facecolor=actualColor[0], linestyle='')) else: # Curve curveList = axes.plot(x, y, linestyle=linestyle, color=color, linewidth=linewidth, marker=symbol, picker=True, pickradius=pickradius, markersize=symbolsize) artists += list(curveList) if fill: if baseline is None: _baseline = FLOAT32_MINPOS else: _baseline = baseline artists.append( axes.fill_between(x, _baseline, y, facecolor=color)) for artist in artists: if alpha < 1: artist.set_alpha(alpha) return _PickableContainer(artists)
[docs] def addImage(self, data, origin, scale, 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, origin, scale): 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] # All image are shown as RGBA image image = Image(self.ax, interpolation='nearest', picker=True, origin='lower', silx_origin=origin, silx_scale=scale) 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 data.ndim == 2: # Data image, convert to RGBA image data = colormap.applyToData(data) elif data.dtype == numpy.uint16: # Normalize uint16 data to have a similar behavior as opengl backend data = data.astype(numpy.float32) data /= 65535 image.set_data(data) self.ax.add_artist(image) return image
[docs] def addTriangles(self, x, y, triangles, color, alpha): for parameter in (x, y, triangles, color, alpha): assert parameter is not None color = numpy.array(color, copy=False) assert color.ndim == 2 and len(color) == len(x) if color.dtype not in [numpy.float32, numpy.float64]: color = color.astype(numpy.float32) / 255. collection = TriMesh( Triangulation(x, y, triangles), alpha=alpha, pickradius=0) # 0 enables picking on filled triangle collection.set_color(color) self.ax.add_collection(collection) return collection
[docs] def addShape(self, x, y, shape, color, fill, overlay, linestyle, linewidth, linebgcolor): if (linebgcolor is not None and shape not in ('rectangle', 'polygon', 'polylines')): _logger.warning( 'linebgcolor not implemented for %s with matplotlib backend', shape) xView = numpy.array(x, copy=False) yView = numpy.array(y, copy=False) linestyle = normalize_linestyle(linestyle) if shape == "line": item = self.ax.plot(x, y, color=color, linestyle=linestyle, linewidth=linewidth, marker=None)[0] elif shape == "hline": if hasattr(y, "__len__"): y = y[-1] item = self.ax.axhline(y, color=color, linestyle=linestyle, linewidth=linewidth) elif shape == "vline": if hasattr(x, "__len__"): x = x[-1] item = self.ax.axvline(x, color=color, linestyle=linestyle, linewidth=linewidth) 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, linestyle=linestyle, linewidth=linewidth) if fill: item.set_hatch('.') if linestyle != "solid" and linebgcolor is not None: item = _DoubleColoredLinePatch(item) item.linebgcolor = linebgcolor 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, color=color, linestyle=linestyle, linewidth=linewidth) if fill and shape == 'polygon': item.set_hatch('/') if linestyle != "solid" and linebgcolor is not None: item = _DoubleColoredLinePatch(item) item.linebgcolor = linebgcolor self.ax.add_patch(item) else: raise NotImplementedError("Unsupported item shape %s" % shape) if overlay: item.set_animated(True) return item
[docs] def addMarker(self, x, y, text, color, symbol, linestyle, linewidth, constraint, yaxis): textArtist = None xmin, xmax = self.getGraphXLimits() ymin, ymax = self.getGraphYLimits(axis=yaxis) if yaxis == 'left': ax = self.ax elif yaxis == 'right': ax = self.ax2 else: assert(False) marker = self._getMarkerFromSymbol(symbol) if x is not None and y is not None: line = ax.plot(x, y, linestyle=" ", color=color, marker=marker, markersize=10.)[-1] if text is not None: textArtist = _TextWithOffset(x, y, text, color=color, horizontalalignment='left') if symbol is not None: textArtist.pixel_offset = 10, 3 elif x is not None: line = ax.axvline(x, color=color, linewidth=linewidth, linestyle=linestyle) if text is not None: # Y position will be updated in updateMarkerText call textArtist = _TextWithOffset(x, 1., text, color=color, horizontalalignment='left', verticalalignment='top') textArtist.pixel_offset = 5, 3 elif y is not None: line = ax.axhline(y, color=color, linewidth=linewidth, linestyle=linestyle) if text is not None: # X position will be updated in updateMarkerText call textArtist = _TextWithOffset(1., y, text, color=color, horizontalalignment='right', verticalalignment='top') textArtist.pixel_offset = 5, 3 else: raise RuntimeError('A marker must at least have one coordinate') line.set_picker(True) line.set_pickradius(5) # All markers are overlays line.set_animated(True) if textArtist is not None: ax.add_artist(textArtist) textArtist.set_animated(True) artists = [line] if textArtist is None else [line, textArtist] container = _MarkerContainer(artists, symbol, x, y, yaxis) container.updateMarkerText(xmin, xmax, ymin, ymax, self.isYAxisInverted()) return container
def _updateMarkers(self): xmin, xmax = self.ax.get_xbound() ymin1, ymax1 = self.ax.get_ybound() ymin2, ymax2 = self.ax2.get_ybound() yinverted = self.isYAxisInverted() for item in self._overlayItems(): if isinstance(item, _MarkerContainer): if item.yAxis == 'left': item.updateMarkerText(xmin, xmax, ymin1, ymax1, yinverted) else: item.updateMarkerText(xmin, xmax, ymin2, ymax2, yinverted) # Remove methods
[docs] def remove(self, item): try: item.remove() except ValueError: pass # Already removed e.g., in set[X|Y]AxisLogarithmic
# Interaction methods
[docs] 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: lineh, linev = self._graphCursor lineh.remove() linev.remove() self._graphCursor = tuple()
# Active curve
[docs] 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.
[docs] 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)
[docs] def replot(self): """Do not perform rendering. Override in subclass to actually draw something. """ with self._plot._paintContext(): self._replot()
def _replot(self): """Call from subclass :meth:`replot` to handle updates""" # 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 _drawOverlays(self): """Draw overlays if any.""" def condition(item): return (item.isVisible() and item._backendRenderer is not None and item.isOverlay()) for item in self.getItemsFromBackToFront(condition=condition): if (isinstance(item, items.YAxisMixIn) and item.getYAxis() == 'right'): axes = self.ax2 else: axes = self.ax axes.draw_artist(item._backendRenderer) for item in self._graphCursor: self.ax.draw_artist(item)
[docs] def updateZOrder(self): """Reorder all items with z order from 0 to 1""" items = self.getItemsFromBackToFront( lambda item: item.isVisible() and item._backendRenderer is not None) count = len(items) for index, item in enumerate(items): if item.getZValue() < 0.5: # Make sure matplotlib z order is below the grid (with z=0.5) zorder = 0.5 * index / count else: # Make sure matplotlib z order is above the grid (> 0.5) zorder = 1. + index / count if zorder != item._backendRenderer.get_zorder(): item._backendRenderer.set_zorder(zorder)
[docs] def saveGraph(self, fileName, fileFormat, dpi): self.updateZOrder() # 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
[docs] def setGraphTitle(self, title): self.ax.set_title(title)
[docs] def setGraphXLabel(self, label): self.ax.set_xlabel(label)
[docs] def setGraphYLabel(self, label, axis): axes = self.ax if axis == 'left' else self.ax2 axes.set_ylabel(label)
# Graph limits
[docs] 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()
[docs] def getGraphXLimits(self): if self._dirtyLimits and self.isKeepDataAspectRatio(): self.ax.apply_aspect() self.ax2.apply_aspect() self._dirtyLimits = False return self.ax.get_xbound()
[docs] def setGraphXLimits(self, xmin, xmax): self._dirtyLimits = True self.ax.set_xlim(min(xmin, xmax), max(xmin, xmax)) self._updateMarkers()
[docs] 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.ax.apply_aspect() self.ax2.apply_aspect() self._dirtyLimits = False return ax.get_ybound()
[docs] 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
[docs] def setXAxisTimeZone(self, tz): super(BackendMatplotlib, self).setXAxisTimeZone(tz) # Make new formatter and locator with the time zone. self.setXAxisTimeSeries(self.isXAxisTimeSeries())
[docs] def isXAxisTimeSeries(self): return self._isXAxisTimeSeries
[docs] 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)
[docs] 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')
[docs] 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')
[docs] def setYAxisInverted(self, flag): if self.ax.yaxis_inverted() != bool(flag): self.ax.invert_yaxis() self._updateMarkers()
[docs] def isYAxisInverted(self): return self.ax.yaxis_inverted()
[docs] def isKeepDataAspectRatio(self): return self.ax.get_aspect() in (1.0, 'equal')
[docs] def setKeepDataAspectRatio(self, flag): self.ax.set_aspect(1.0 if flag else 'auto') self.ax2.set_aspect(1.0 if flag else 'auto')
[docs] 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 _getDevicePixelRatio(self) -> float: """Compatibility wrapper for devicePixelRatioF""" return 1. def _mplToQtPosition(self, x: float, y: float) -> Tuple[float, float]: """Convert matplotlib "display" space coord to Qt widget logical pixel """ ratio = self._getDevicePixelRatio() # Convert from matplotlib origin (bottom) to Qt origin (top) # and apply device pixel ratio return x / ratio, (self.fig.get_window_extent().height - y) / ratio def _qtToMplPosition(self, x: float, y: float) -> Tuple[float, float]: """Convert Qt widget logical pixel to matplotlib "display" space coord """ ratio = self._getDevicePixelRatio() # Apply device pixel ration and # convert from Qt origin (top) to matplotlib origin (bottom) return x * ratio, self.fig.get_window_extent().height - (y * ratio)
[docs] def dataToPixel(self, x, y, axis): ax = self.ax2 if axis == "right" else self.ax displayPos = ax.transData.transform_point((x, y)).transpose() return self._mplToQtPosition(*displayPos)
[docs] def pixelToData(self, x, y, axis): ax = self.ax2 if axis == "right" else self.ax displayPos = self._qtToMplPosition(x, y) return tuple(ax.transData.inverted().transform_point(displayPos))
[docs] def getPlotBoundsInPixels(self): bbox = self.ax.get_window_extent() # Warning this is not returning int... ratio = self._getDevicePixelRatio() return tuple(int(value / ratio) for value in ( bbox.xmin, self.fig.get_window_extent().height - bbox.ymax, bbox.width, bbox.height))
[docs] def setAxesMargins(self, left: float, top: float, right: float, bottom: float): width, height = 1. - left - right, 1. - top - bottom position = left, bottom, width, height # Toggle display of axes and viewbox rect isFrameOn = position != (0., 0., 1., 1.) self.ax.set_frame_on(isFrameOn) self.ax2.set_frame_on(isFrameOn) self.ax.set_position(position) self.ax2.set_position(position) self._synchronizeBackgroundColors() self._synchronizeForegroundColors() self._plot._setDirtyPlot()
def _synchronizeBackgroundColors(self): backgroundColor = self._plot.getBackgroundColor().getRgbF() dataBackgroundColor = self._plot.getDataBackgroundColor() if dataBackgroundColor.isValid(): dataBackgroundColor = dataBackgroundColor.getRgbF() else: dataBackgroundColor = backgroundColor if self.ax.get_frame_on(): self.fig.patch.set_facecolor(backgroundColor) if self._matplotlibVersion < _parse_version('2'): self.ax.set_axis_bgcolor(dataBackgroundColor) else: self.ax.set_facecolor(dataBackgroundColor) else: self.fig.patch.set_facecolor(dataBackgroundColor) def _synchronizeForegroundColors(self): foregroundColor = self._plot.getForegroundColor().getRgbF() gridColor = self._plot.getGridColor() if gridColor.isValid(): gridColor = gridColor.getRgbF() else: gridColor = foregroundColor for axes in (self.ax, self.ax2): if axes.get_frame_on(): axes.spines['bottom'].set_color(foregroundColor) axes.spines['top'].set_color(foregroundColor) axes.spines['right'].set_color(foregroundColor) axes.spines['left'].set_color(foregroundColor) axes.tick_params(axis='x', colors=foregroundColor) axes.tick_params(axis='y', colors=foregroundColor) axes.yaxis.label.set_color(foregroundColor) axes.xaxis.label.set_color(foregroundColor) axes.title.set_color(foregroundColor) for line in axes.get_xgridlines(): line.set_color(gridColor) for line in axes.get_ygridlines(): line.set_color(gridColor) # axes.grid().set_markeredgecolor(gridColor)
[docs] def setBackgroundColors(self, backgroundColor, dataBackgroundColor): self._synchronizeBackgroundColors()
[docs] def setForegroundColors(self, foregroundColor, gridColor): self._synchronizeForegroundColors()
[docs]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( self.__deferredReplot, 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)
[docs] def postRedisplay(self): self._sigPostRedisplay.emit()
def __deferredReplot(self): # Since this is deferred, makes sure it is still needed plot = self._plotRef() if (plot is not None and plot._getDirtyPlot() and plot.getBackend() is self): self.replot() def _getDevicePixelRatio(self) -> float: """Compatibility wrapper for devicePixelRatioF""" if hasattr(self, 'devicePixelRatioF'): ratio = self.devicePixelRatioF() else: # Qt < 5.6 compatibility ratio = float(self.devicePixelRatio()) # Safety net: avoid returning 0 return ratio if ratio != 0. else 1. # Mouse event forwarding _MPL_TO_PLOT_BUTTONS = {1: 'left', 2: 'middle', 3: 'right'} def _onMousePress(self, event): button = self._MPL_TO_PLOT_BUTTONS.get(event.button, None) if button is not None: x, y = self._mplToQtPosition(event.x, event.y) self._plot.onMousePress(int(x), int(y), button) def _onMouseMove(self, event): x, y = self._mplToQtPosition(event.x, event.y) if self._graphCursor: position = self._plot.pixelToData( x, y, axis='left', check=True) lineh, linev = self._graphCursor if position is not None: linev.set_visible(True) linev.set_xdata((position[0], position[0])) lineh.set_visible(True) lineh.set_ydata((position[1], position[1])) self._plot._setDirtyPlot(overlayOnly=True) elif lineh.get_visible(): lineh.set_visible(False) linev.set_visible(False) self._plot._setDirtyPlot(overlayOnly=True) # onMouseMove must trigger replot if dirty flag is raised self._plot.onMouseMove(int(x), int(y)) def _onMouseRelease(self, event): button = self._MPL_TO_PLOT_BUTTONS.get(event.button, None) if button is not None: x, y = self._mplToQtPosition(event.x, event.y) self._plot.onMouseRelease(int(x), int(y), button) def _onMouseWheel(self, event): x, y = self._mplToQtPosition(event.x, event.y) self._plot.onMouseWheel(int(x), int(y), event.step)
[docs] def leaveEvent(self, event): """QWidget event handler""" try: plot = self._plot except RuntimeError: pass else: plot.onMouseLeaveWidget()
# picking
[docs] def pickItem(self, x, y, item): xDisplay, yDisplay = self._qtToMplPosition(x, y) mouseEvent = MouseEvent( 'button_press_event', self, int(xDisplay), int(yDisplay)) # Override axes and data position with the axes mouseEvent.inaxes = item.axes mouseEvent.xdata, mouseEvent.ydata = self.pixelToData( x, y, axis='left' if item.axes is self.ax else 'right') picked, info = item.contains(mouseEvent) if not picked: return None elif isinstance(item, TriMesh): # Convert selected triangle to data point indices triangulation = item._triangulation indices = triangulation.get_masked_triangles()[info['ind'][0]] # Sort picked triangle points by distance to mouse # from furthest to closest to put closest point last # This is to be somewhat consistent with last scatter point # being the top one. xdata, ydata = self.pixelToData(x, y, axis='left') dists = ((triangulation.x[indices] - xdata) ** 2 + (triangulation.y[indices] - ydata) ** 2) return indices[numpy.flip(numpy.argsort(dists), axis=0)] else: # Returns indices if any return info.get('ind', ())
# replot control
[docs] 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._hasOverlays(): # This is needed with matplotlib 1.5.x and 2.0.x self._plot._setDirtyPlot()
[docs] 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. """ self.updateZOrder() # 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._hasOverlays(): # 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()
[docs] def replot(self): if not qt_inspect.isValid(self): _logger.info("replot requested but widget no longer exists") return with self._plot._paintContext(): 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._hasOverlays(): 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, }
[docs] def setGraphCursorShape(self, cursor): if cursor is None: FigureCanvasQTAgg.unsetCursor(self) else: cursor = self._QT_CURSORS[cursor] FigureCanvasQTAgg.setCursor(self, qt.QCursor(cursor))