# /*##########################################################################
#
# Copyright (c) 2004-2023 European Synchrotron Radiation Facility
#
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# furnished to do so, subject to the following conditions:
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"""Matplotlib Plot backend."""
from __future__ import annotations
__authors__ = ["V.A. Sole", "T. Vincent, H. Payno"]
__license__ = "MIT"
__date__ = "21/12/2018"
import logging
import datetime as dt
from typing import Tuple, Union
import numpy
from packaging.version import Version
_logger = logging.getLogger(__name__)
from ... import qt
# First of all init matplotlib and set its backend
from ...utils.matplotlib import (
DefaultTickFormatter,
FigureCanvasQTAgg,
qFontToFontProperties,
)
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, 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,
formatDatetimes,
timestamp,
)
from ...qt import inspect as qt_inspect
from .... import config
from silx.gui.colors import RGBAColorType
_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 == "\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
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)
[docs]
class SecondEdgeColorPatchMixIn:
"""Mix-in class to add a second color for patches with dashed lines"""
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self._second_edgecolor = None
[docs]
def set_second_edgecolor(self, color):
"""Set the second color used to fill dashed edges"""
self._second_edgecolor = color
[docs]
def get_second_edgecolor(self):
"""Returns the second color used to fill dashed edges"""
return self._second_edgecolor
def draw(self, renderer):
linestyle = self.get_linestyle()
if linestyle == "solid" or self.get_second_edgecolor() is None:
super().draw(renderer)
return
edgecolor = self.get_edgecolor()
hatch = self.get_hatch()
self.set_linestyle("solid")
self.set_edgecolor(self.get_second_edgecolor())
self.set_hatch(None)
super().draw(renderer)
self.set_linestyle(linestyle)
self.set_edgecolor(edgecolor)
self.set_hatch(hatch)
super().draw(renderer)
[docs]
class Rectangle2EdgeColor(SecondEdgeColorPatchMixIn, Rectangle):
"""Rectangle patch with a second edge color for dashed line"""
[docs]
class Polygon2EdgeColor(SecondEdgeColorPatchMixIn, Polygon):
"""Polygon patch with a second edge color for dashed line"""
[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, 0.0), silx_scale=(1.0, 1.0), **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.asarray(A)
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 = Version(matplotlib.__version__)
self.fig = Figure(
tight_layout=config._MPL_TIGHT_LAYOUT,
)
self.fig.set_facecolor("w")
if config._MPL_TIGHT_LAYOUT:
self.ax = self.fig.add_subplot(label="left")
else:
self.ax = self.fig.add_axes([0.15, 0.15, 0.75, 0.75], 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)
# Configure axes tick label formatter
for axis in (self.ax.yaxis, self.ax.xaxis, self.ax2.yaxis, self.ax2.xaxis):
axis.set_major_formatter(DefaultTickFormatter())
self.ax2.set_autoscaley_on(True)
# this works but the figure color is left
if self._matplotlibVersion < 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,
gapcolor,
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) / 255.0
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 / 255.0
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,
)
if gapcolor is not None and self._matplotlibVersion >= Version("3.6.0"):
for line2d in curveList:
line2d.set_gapcolor(gapcolor)
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] < 0.0:
xmin, xmax = xmax, xmin
ymin = origin[1]
ymax = ymin + scale[1] * height
if scale[1] < 0.0:
ymin, ymax = ymax, ymin
image.set_extent((xmin, xmax, ymin, ymax))
# Set image data
if scale[0] < 0.0 or scale[1] < 0.0:
# For negative scale, step by -1
xstep = 1 if scale[0] >= 0.0 else -1
ystep = 1 if scale[1] >= 0.0 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.asarray(color)
assert color.ndim == 2 and len(color) == len(x)
if color.dtype not in [numpy.float32, numpy.float64]:
color = color.astype(numpy.float32) / 255.0
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, gapcolor
):
if gapcolor is not None and shape not in (
"rectangle",
"polygon",
"polylines",
):
_logger.warning(
"gapcolor not implemented for %s with matplotlib backend", shape
)
xView = numpy.asarray(x)
yView = numpy.asarray(y)
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 = Rectangle2EdgeColor(
xy=(xMin, yMin),
width=w,
height=h,
fill=False,
color=color,
linestyle=linestyle,
linewidth=linewidth,
)
item.set_second_edgecolor(gapcolor)
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 = Polygon2EdgeColor(
points,
closed=closed,
fill=False,
color=color,
linestyle=linestyle,
linewidth=linewidth,
)
item.set_second_edgecolor(gapcolor)
if fill and shape == "polygon":
item.set_hatch("/")
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,
font,
bgcolor: RGBAColorType | None,
):
textArtist = None
fontProperties = None if font is None else qFontToFontProperties(font)
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
if bgcolor is None:
bgcolor = "none"
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=10.0
)[-1]
if text is not None:
textArtist = _TextWithOffset(
x,
y,
text,
color=color,
backgroundcolor=bgcolor,
horizontalalignment="left",
fontproperties=fontProperties,
)
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,
1.0,
text,
color=color,
backgroundcolor=bgcolor,
horizontalalignment="left",
verticalalignment="top",
fontproperties=fontProperties,
)
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(
1.0,
y,
text,
color=color,
backgroundcolor=bgcolor,
horizontalalignment="right",
verticalalignment="top",
fontproperties=fontProperties,
)
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.
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 = 1.0 + 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
def __initXAxisFormatterAndLocator(self):
if self.ax.xaxis.get_scale() != "linear":
return # Do not override formatter and locator
if not self.isXAxisTimeSeries():
self.ax.xaxis.set_major_formatter(DefaultTickFormatter())
return
# 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())
)
[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
self.__initXAxisFormatterAndLocator()
[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 >= 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()
xscale = "log" if flag else "linear"
self.ax2.set_xscale(xscale)
self.ax.set_xscale(xscale)
self.__initXAxisFormatterAndLocator()
[docs]
def setYAxisLogarithmic(self, flag):
# Workaround for matplotlib 2.0 issue with negative bounds
# before switching to log scale
if flag and self._matplotlibVersion >= 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()
if flag:
self.ax2.set_yscale("log")
self.ax.set_yscale("log")
return
self.ax2.set_yscale("linear")
self.ax2.yaxis.set_major_formatter(DefaultTickFormatter())
self.ax.set_yscale("linear")
self.ax.yaxis.set_major_formatter(DefaultTickFormatter())
[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 isYRightAxisVisible(self):
return self.ax2.yaxis.get_visible()
[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 1.0
def _mplToQtPosition(
self, x: Union[float, numpy.ndarray], y: Union[float, numpy.ndarray]
) -> Tuple[Union[float, numpy.ndarray], Union[float, numpy.ndarray]]:
"""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
points = numpy.transpose((x, y))
displayPos = ax.transData.transform(points).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 = 1.0 - left - right, 1.0 - top - bottom
position = left, bottom, width, height
istight = config._MPL_TIGHT_LAYOUT and (left, top, right, bottom) != (
0,
0,
0,
0,
)
if self._matplotlibVersion >= Version("3.6"):
self.fig.set_layout_engine("tight" if istight else None)
else:
self.fig.set_tight_layout(True if istight else None)
# Toggle display of axes and viewbox rect
isFrameOn = position != (0.0, 0.0, 1.0, 1.0)
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 < 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(BackendMatplotlib, FigureCanvasQTAgg):
"""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 != 0.0 else 1.0
# 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.
"""
if self.size().isEmpty():
return # Skip rendering of 0-sized canvas
self.updateZOrder()
if not qt_inspect.isValid(self):
_logger.info("draw requested but widget no longer exists")
return
# Starting with mpl 2.1.0, toggling autoscale raises a ValueError
# in some situations. See #1081, #1136, #1163,
if self._matplotlibVersion >= 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 Version("1.5") <= self._matplotlibVersion < 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))
