# coding: utf-8
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# Copyright (c) 2004-2018 European Synchrotron Radiation Facility
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"""Matplotlib Plot backend."""
from __future__ import division
__authors__ = ["V.A. Sole", "T. Vincent, H. Payno"]
__license__ = "MIT"
__date__ = "18/10/2017"
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 ..matplotlib.ModestImage import ModestImage
from . import BackendBase
from .._utils import FLOAT32_MINPOS
from .._utils.dtime_ticklayout import calcTicks, bestFormatString, timestamp
[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)
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 _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)
[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")
# 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, 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)
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)
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)
[docs] 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)
[docs] 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()
[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(
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 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)
[docs] 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)
[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.
"""
# 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 = {
None: qt.Qt.ArrowCursor,
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):
cursor = self._QT_CURSORS[cursor]
FigureCanvasQTAgg.setCursor(self, qt.QCursor(cursor))
