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marker-transforms
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‎doc/users/next_whats_new/2020-03-16_markerstyle_normalization.rst‎

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Allow for custom marker scaling
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-------------------------------
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`~.markers.MarkerStyle` gained a keyword argument *normalization*, which may be
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set to *"none"* to allow for custom paths to not be scaled.::
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MarkerStyle(Path(...), normalization="none")
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`~.markers.MarkerStyle` also gained a `~.markers.MarkerStyle`.set_transform`
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method to set affine transformations to existing markers.::
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m = MarkerStyle("d")
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m.set_transform(m.get_transform() + Affine2D().rotate_deg(30))

‎examples/lines_bars_and_markers/scatter_piecharts.py‎

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Scatter plot with pie chart markers
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===================================
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This example makes custom 'pie charts' as the markers for a scatter plot.
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Thanks to Manuel Metz for the example.
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This example shows two methods to make custom 'pie charts' as the markers
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for a scatter plot.
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"""
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##########################################################################
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# Manually creating marker vertices
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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#
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import numpy as np
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import matplotlib.pyplot as plt
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# first define the ratios
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# first define the cumulative ratios
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r1 = 0.2 # 20%
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r2 = r1 + 0.4 # 40%
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@@ -36,10 +40,55 @@
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s3 = np.abs(xy3).max()
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fig, ax = plt.subplots()
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ax.scatter(range(3), range(3), marker=xy1, s=s1**2 * sizes, facecolor='blue')
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ax.scatter(range(3), range(3), marker=xy2, s=s2**2 * sizes, facecolor='green')
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ax.scatter(range(3), range(3), marker=xy3, s=s3**2 * sizes, facecolor='red')
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ax.scatter(range(3), range(3), marker=xy1, s=s1**2 * sizes, facecolor='C0')
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ax.scatter(range(3), range(3), marker=xy2, s=s2**2 * sizes, facecolor='C1')
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ax.scatter(range(3), range(3), marker=xy3, s=s3**2 * sizes, facecolor='C2')
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plt.show()
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##########################################################################
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# Using wedges as markers
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# ~~~~~~~~~~~~~~~~~~~~~~~
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#
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# An alternative is to create custom markers from the `~.path.Path` of a
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# `~.patches.Wedge`, which might be more versatile.
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#
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import numpy as np
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import matplotlib.pyplot as plt
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from matplotlib.patches import Wedge
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from matplotlib.markers import MarkerStyle
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# first define the ratios
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r1 = 0.2 # 20%
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r2 = r1 + 0.3 # 50%
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r3 = 1 - r1 - r2 # 30%
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def markers_from_ratios(ratios, width=1):
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markers = []
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angles = 360*np.concatenate(([0], np.cumsum(ratios)))
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for i in range(len(angles)-1):
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# create a Wedge within the unit square in between the given angles...
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w = Wedge((0, 0), 0.5, angles[i], angles[i+1], width=width/2)
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# ... and create a custom Marker from its path.
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markers.append(MarkerStyle(w.get_path(), normalization="none"))
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return markers
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# define some sizes of the scatter marker
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sizes = np.array([100, 200, 400, 800])
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# collect the markers and some colors
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markers = markers_from_ratios([r1, r2, r3], width=0.6)
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colors = plt.cm.tab10.colors[:len(markers)]
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fig, ax = plt.subplots()
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for marker, color in zip(markers, colors):
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ax.scatter(range(len(sizes)), range(len(sizes)), marker=marker, s=sizes,
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edgecolor="none", facecolor=color)
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ax.margins(0.1)
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plt.show()
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#############################################################################
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import matplotlib
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matplotlib.axes.Axes.scatter
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matplotlib.pyplot.scatter
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matplotlib.patches.Wedge
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matplotlib.markers.MarkerStyle

‎lib/matplotlib/markers.py‎

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@@ -201,7 +201,8 @@ class MarkerStyle:
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# TODO: Is this ever used as a non-constant?
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_point_size_reduction = 0.5
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def __init__(self, marker=None, fillstyle=None):
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def __init__(self, marker=None, fillstyle=None, *,
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normalization="classic"):
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"""
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Attributes
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----------
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Parameters
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----------
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marker : str or array-like, optional, default: None
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marker : str, array-like, `~.path.Path`, or `~.markers.MarkerStyle`, \
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default: None
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See the descriptions of possible markers in the module docstring.
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fillstyle : str, optional, default: 'full'
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'full', 'left", 'right', 'bottom', 'top', 'none'
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normalization : str, {'classic', 'none'}, optional, default: "classic"
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The normalization of the marker size. Only applies to custom paths
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that are provided as array of vertices or `~.path.Path`.
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Can take two values:
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*'classic'*, being the default, makes sure the marker path is
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normalized to fit within a unit-square by affine scaling.
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*'none'*, in which case no scaling is performed on the marker path.
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"""
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if normalization not in ["classic", "none"]:
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raise ValueError("normalization={!r} is not valid; it must be "
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"'classic' or 'none'".format(normalization))
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self._normalize = normalization
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self._marker_function = None
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self.set_fillstyle(fillstyle)
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self.set_marker(marker)
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def get_transform(self):
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return self._transform.frozen()
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def set_transform(self, transform):
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"""
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Sets the transform of the marker. This is the transform by which the
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marker path is transformed.
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"""
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self._transform = transform
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def get_alt_path(self):
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return self._alt_path
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self._filled = False
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def _set_custom_marker(self, path):
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rescale = np.max(np.abs(path.vertices)) # max of x's and y's.
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self._transform = Affine2D().scale(0.5 / rescale)
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if self._normalize == "classic":
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rescale = np.max(np.abs(path.vertices)) # max of x's and y's.
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self._transform = Affine2D().scale(0.5 / rescale)
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self._path = path
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def _set_path_marker(self):
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def _set_mathtext_path(self):
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"""
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Draws mathtext markers '$...$' using TextPath object.
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Submitted by tcb
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"""
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from matplotlib.text import TextPath
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‎lib/matplotlib/tests/test_marker.py‎

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import numpy as np
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from matplotlib import markers
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from matplotlib.path import Path
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from matplotlib.transforms import Affine2D
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import matplotlib.pyplot as plt
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from matplotlib.testing.decorators import check_figures_equal
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import pytest
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path = Path([[0, 0], [1, 0]], [Path.MOVETO, Path.LINETO])
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# Checking this doesn't fail.
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marker_style.set_marker(path)
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@check_figures_equal(extensions=["png"])
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def test_marker_normalization(fig_test, fig_ref):
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plt.style.use("mpl20")
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ax = fig_ref.subplots()
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ax.margins(0.3)
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ax.scatter([0, 1], [0, 0], s=400, marker="s", c="C2")
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ax = fig_test.subplots()
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ax.margins(0.3)
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# test normalize
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p = Path([[0, 0], [1, 0], [1, 1], [0, 1], [0, 0]], closed=True)
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p1 = p.transformed(Affine2D().translate(-.5, -.5).scale(20))
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m1 = markers.MarkerStyle(p1, normalization="none")
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ax.scatter([0], [0], s=1, marker=m1, c="C2")
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# test transform
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m2 = markers.MarkerStyle("s")
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m2.set_transform(m2.get_transform() + Affine2D().scale(20))
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ax.scatter([1], [0], s=1, marker=m2, c="C2")

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