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@syrte
Last active Sep 24, 2020
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Plot a collection of patches (circles, ellipses, rectangles), similar to `plt.scatter` but the size of patches are in data unit.
from __future__ import division, print_function, absolute_import
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Arc
from matplotlib.collections import PatchCollection
__all__ = ['arcs']
def arcs(x, y, w, h=None, rot=0.0, theta1=0.0, theta2=360.0,
c='b', vmin=None, vmax=None, **kwargs):
"""
Make a scatter plot of Arcs.
Parameters
----------
x, y : scalar or array_like, shape (n, )
Center of ellipses.
w, h : scalar or array_like, shape (n, )
Total length (diameter) of horizontal/vertical axis.
`h` is set to be equal to `w` by default, ie. circle.
rot : scalar or array_like, shape (n, )
Rotation in degrees (anti-clockwise).
c : color or sequence of color, optional, default : 'b'
`c` can be a single color format string, or a sequence of color
specifications of length `N`, or a sequence of `N` numbers to be
mapped to colors using the `cmap` and `norm` specified via kwargs.
Note that `c` should not be a single numeric RGB or RGBA sequence
because that is indistinguishable from an array of values
to be colormapped. (If you insist, use `color` instead.)
`c` can be a 2-D array in which the rows are RGB or RGBA, however.
vmin, vmax : scalar, optional, default: None
`vmin` and `vmax` are used in conjunction with `norm` to normalize
luminance data. If either are `None`, the min and max of the
color array is used.
kwargs : `~matplotlib.collections.Collection` properties
Eg. alpha, edgecolor(ec), facecolor(fc), linewidth(lw), linestyle(ls),
norm, cmap, transform, etc.
Returns
-------
paths : `~matplotlib.collections.PathCollection`
Examples
--------
a = np.arange(11)
arcs(a, a, w=4, h=a, rot=a*30, theta1=0.0, theta2=180.0,
c=a, alpha=0.5, ec='none')
plt.colorbar()
License
--------
This code is under [The BSD 3-Clause License]
(http://opensource.org/licenses/BSD-3-Clause)
"""
if np.isscalar(c):
kwargs.setdefault('color', c)
c = None
if 'fc' in kwargs:
kwargs.setdefault('facecolor', kwargs.pop('fc'))
if 'ec' in kwargs:
kwargs.setdefault('edgecolor', kwargs.pop('ec'))
if 'ls' in kwargs:
kwargs.setdefault('linestyle', kwargs.pop('ls'))
if 'lw' in kwargs:
kwargs.setdefault('linewidth', kwargs.pop('lw'))
# You can set `facecolor` with an array for each patch,
# while you can only set `facecolors` with a value for all.
if h is None:
h = w
zipped = np.broadcast(x, y, w, h, rot, theta1, theta2)
patches = [Arc((x_, y_), w_, h_, rot_, t1_, t2_)
for x_, y_, w_, h_, rot_, t1_, t2_ in zipped]
collection = PatchCollection(patches, **kwargs)
if c is not None:
c = np.broadcast_to(c, zipped.shape).ravel()
collection.set_array(c)
collection.set_clim(vmin, vmax)
ax = plt.gca()
ax.add_collection(collection)
ax.autoscale_view()
plt.draw_if_interactive()
if c is not None:
plt.sci(collection)
return collection
from __future__ import division, print_function, absolute_import
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Circle, Ellipse, Rectangle
from matplotlib.collections import PatchCollection
__all__ = ['circles', 'ellipses', 'rectangles']
def circles(x, y, s, c='b', vmin=None, vmax=None, **kwargs):
"""
Make a scatter plot of circles.
Similar to plt.scatter, but the size of circles are in data scale.
Parameters
----------
x, y : scalar or array_like, shape (n, )
Input data
s : scalar or array_like, shape (n, )
Radius of circles.
c : color or sequence of color, optional, default : 'b'
`c` can be a single color format string, or a sequence of color
specifications of length `N`, or a sequence of `N` numbers to be
mapped to colors using the `cmap` and `norm` specified via kwargs.
Note that `c` should not be a single numeric RGB or RGBA sequence
because that is indistinguishable from an array of values
to be colormapped. (If you insist, use `color` instead.)
`c` can be a 2-D array in which the rows are RGB or RGBA, however.
vmin, vmax : scalar, optional, default: None
`vmin` and `vmax` are used in conjunction with `norm` to normalize
luminance data. If either are `None`, the min and max of the
color array is used.
kwargs : `~matplotlib.collections.Collection` properties
Eg. alpha, edgecolor(ec), facecolor(fc), linewidth(lw), linestyle(ls),
norm, cmap, transform, etc.
Returns
-------
paths : `~matplotlib.collections.PathCollection`
Examples
--------
a = np.arange(11)
circles(a, a, s=a*0.2, c=a, alpha=0.5, ec='none')
plt.colorbar()
License
--------
This code is under [The BSD 3-Clause License]
(http://opensource.org/licenses/BSD-3-Clause)
"""
if np.isscalar(c):
kwargs.setdefault('color', c)
c = None
if 'fc' in kwargs:
kwargs.setdefault('facecolor', kwargs.pop('fc'))
if 'ec' in kwargs:
kwargs.setdefault('edgecolor', kwargs.pop('ec'))
if 'ls' in kwargs:
kwargs.setdefault('linestyle', kwargs.pop('ls'))
if 'lw' in kwargs:
kwargs.setdefault('linewidth', kwargs.pop('lw'))
# You can set `facecolor` with an array for each patch,
# while you can only set `facecolors` with a value for all.
zipped = np.broadcast(x, y, s)
patches = [Circle((x_, y_), s_)
for x_, y_, s_ in zipped]
collection = PatchCollection(patches, **kwargs)
if c is not None:
c = np.broadcast_to(c, zipped.shape).ravel()
collection.set_array(c)
collection.set_clim(vmin, vmax)
ax = plt.gca()
ax.add_collection(collection)
ax.autoscale_view()
plt.draw_if_interactive()
if c is not None:
plt.sci(collection)
return collection
def ellipses(x, y, w, h=None, rot=0.0, c='b', vmin=None, vmax=None, **kwargs):
"""
Make a scatter plot of ellipses.
Parameters
----------
x, y : scalar or array_like, shape (n, )
Center of ellipses.
w, h : scalar or array_like, shape (n, )
Total length (diameter) of horizontal/vertical axis.
`h` is set to be equal to `w` by default, ie. circle.
rot : scalar or array_like, shape (n, )
Rotation in degrees (anti-clockwise).
c : color or sequence of color, optional, default : 'b'
`c` can be a single color format string, or a sequence of color
specifications of length `N`, or a sequence of `N` numbers to be
mapped to colors using the `cmap` and `norm` specified via kwargs.
Note that `c` should not be a single numeric RGB or RGBA sequence
because that is indistinguishable from an array of values
to be colormapped. (If you insist, use `color` instead.)
`c` can be a 2-D array in which the rows are RGB or RGBA, however.
vmin, vmax : scalar, optional, default: None
`vmin` and `vmax` are used in conjunction with `norm` to normalize
luminance data. If either are `None`, the min and max of the
color array is used.
kwargs : `~matplotlib.collections.Collection` properties
Eg. alpha, edgecolor(ec), facecolor(fc), linewidth(lw), linestyle(ls),
norm, cmap, transform, etc.
Returns
-------
paths : `~matplotlib.collections.PathCollection`
Examples
--------
a = np.arange(11)
ellipses(a, a, w=4, h=a, rot=a*30, c=a, alpha=0.5, ec='none')
plt.colorbar()
License
--------
This code is under [The BSD 3-Clause License]
(http://opensource.org/licenses/BSD-3-Clause)
"""
if np.isscalar(c):
kwargs.setdefault('color', c)
c = None
if 'fc' in kwargs:
kwargs.setdefault('facecolor', kwargs.pop('fc'))
if 'ec' in kwargs:
kwargs.setdefault('edgecolor', kwargs.pop('ec'))
if 'ls' in kwargs:
kwargs.setdefault('linestyle', kwargs.pop('ls'))
if 'lw' in kwargs:
kwargs.setdefault('linewidth', kwargs.pop('lw'))
# You can set `facecolor` with an array for each patch,
# while you can only set `facecolors` with a value for all.
if h is None:
h = w
zipped = np.broadcast(x, y, w, h, rot)
patches = [Ellipse((x_, y_), w_, h_, rot_)
for x_, y_, w_, h_, rot_ in zipped]
collection = PatchCollection(patches, **kwargs)
if c is not None:
c = np.broadcast_to(c, zipped.shape).ravel()
collection.set_array(c)
collection.set_clim(vmin, vmax)
ax = plt.gca()
ax.add_collection(collection)
ax.autoscale_view()
plt.draw_if_interactive()
if c is not None:
plt.sci(collection)
return collection
def rectangles(x, y, w, h=None, rot=0.0, c='b', vmin=None, vmax=None, **kwargs):
"""
Make a scatter plot of rectangles.
Parameters
----------
x, y : scalar or array_like, shape (n, )
Center of rectangles.
w, h : scalar or array_like, shape (n, )
Width, Height.
`h` is set to be equal to `w` by default, ie. squares.
rot : scalar or array_like, shape (n, )
Rotation in degrees (anti-clockwise).
c : color or sequence of color, optional, default : 'b'
`c` can be a single color format string, or a sequence of color
specifications of length `N`, or a sequence of `N` numbers to be
mapped to colors using the `cmap` and `norm` specified via kwargs.
Note that `c` should not be a single numeric RGB or RGBA sequence
because that is indistinguishable from an array of values
to be colormapped. (If you insist, use `color` instead.)
`c` can be a 2-D array in which the rows are RGB or RGBA, however.
vmin, vmax : scalar, optional, default: None
`vmin` and `vmax` are used in conjunction with `norm` to normalize
luminance data. If either are `None`, the min and max of the
color array is used.
kwargs : `~matplotlib.collections.Collection` properties
Eg. alpha, edgecolor(ec), facecolor(fc), linewidth(lw), linestyle(ls),
norm, cmap, transform, etc.
Returns
-------
paths : `~matplotlib.collections.PathCollection`
Examples
--------
a = np.arange(11)
rectangles(a, a, w=5, h=6, rot=a*30, c=a, alpha=0.5, ec='none')
plt.colorbar()
License
--------
This code is under [The BSD 3-Clause License]
(http://opensource.org/licenses/BSD-3-Clause)
"""
if np.isscalar(c):
kwargs.setdefault('color', c)
c = None
if 'fc' in kwargs:
kwargs.setdefault('facecolor', kwargs.pop('fc'))
if 'ec' in kwargs:
kwargs.setdefault('edgecolor', kwargs.pop('ec'))
if 'ls' in kwargs:
kwargs.setdefault('linestyle', kwargs.pop('ls'))
if 'lw' in kwargs:
kwargs.setdefault('linewidth', kwargs.pop('lw'))
# You can set `facecolor` with an array for each patch,
# while you can only set `facecolors` with a value for all.
if h is None:
h = w
d = np.sqrt(np.square(w) + np.square(h)) / 2.
t = np.deg2rad(rot) + np.arctan2(h, w)
x, y = x - d * np.cos(t), y - d * np.sin(t)
zipped = np.broadcast(x, y, w, h, rot)
patches = [Rectangle((x_, y_), w_, h_, rot_)
for x_, y_, w_, h_, rot_ in zipped]
collection = PatchCollection(patches, **kwargs)
if c is not None:
c = np.broadcast_to(c, zipped.shape).ravel()
collection.set_array(c)
collection.set_clim(vmin, vmax)
ax = plt.gca()
ax.add_collection(collection)
ax.autoscale_view()
plt.draw_if_interactive()
if c is not None:
plt.sci(collection)
return collection
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