我有一组数据，想要将它们以散点图的形式展示。我希望每个点都被绘制成大小为dx的正方形。
x = [0.5,0.1,0.3]
y = [0.2,0.7,0.8]
z = [10.,15.,12.]
dx = [0.05,0.2,0.1]
scatter(x,y,c=z,s=dx,marker='s')
将用户数据坐标系转换为显示坐标系。
使用edgecolors='none'来绘制没有边框线的面。
import numpy as np
fig = figure()
ax = fig.add_subplot(111)
dx_in_points = np.diff(ax.transData.transform(zip([0]*len(dx), dx)))
scatter(x,y,c=z,s=dx_in_points**2,marker='s', edgecolors='none')
我认为通过使用一组补丁可以做得更好。根据文档：
这个（PatchCollection）可以更容易地将颜色映射分配给异构的补丁集合。
这也可能会提高绘图速度，因为 PatchCollection 比大量补丁的绘制速度更快。
假设您希望绘制一个散点图，其中包含以数据单位给定半径的圆形：
def circles(x, y, s, c='b', vmin=None, vmax=None, **kwargs):
"""
Make a scatter of circles plot of x vs y, where x and y are sequence
like objects of the same lengths. 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 circle in data unit.
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, a*0.2, c=a, alpha=0.5, edgecolor='none')
plt.colorbar()
License
--------
This code is under [The BSD 3-Clause License]
(http://opensource.org/licenses/BSD-3-Clause)
"""
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Circle
from matplotlib.collections import PatchCollection
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'))
patches = [Circle((x_, y_), s_) for x_, y_, s_ in np.broadcast(x, y, s)]
collection = PatchCollection(patches, **kwargs)
if c is not None:
collection.set_array(np.asarray(c))
collection.set_clim(vmin, vmax)
ax = plt.gca()
ax.add_collection(collection)
ax.autoscale_view()
if c is not None:
plt.sci(collection)
return collection
scatter函数的所有参数和关键字（除了marker）都能以类似的方式工作。我写了一个gist，包括圆形、椭圆形和正方形/矩形。如果你想要其他形状的集合，可以自己修改。
如果你想要绘制色条，只需运行colorbar()或将返回的集合对象传递给colorbar函数。
一个例子：
from pylab import *
figure(figsize=(6,4))
ax = subplot(aspect='equal')
#plot a set of circle
a = arange(11)
out = circles(a, a, a*0.2, c=a, alpha=0.5, ec='none')
colorbar()
#plot one circle (the lower-right one)
circles(1, 0, 0.4, 'r', ls='--', lw=5, fc='none', transform=ax.transAxes)
xlim(0,10)
ylim(0,10)
输出：
如果你想要随着图形大小调整大小的标记，可以使用patches：
from matplotlib import pyplot as plt
from matplotlib.patches import Rectangle
x = [0.5, 0.1, 0.3]
y = [0.2 ,0.7, 0.8]
z = [10, 15, 12]
dx = [0.05, 0.2, 0.1]
cmap = plt.cm.hot
fig = plt.figure()
ax = fig.add_subplot(111, aspect='equal')
for x, y, c, h in zip(x, y, z, dx):
ax.add_artist(Rectangle(xy=(x, y),
color=cmap(c**2), # I did c**2 to get nice colors from your numbers
width=h, height=h)) # Gives a square of area h*h
plt.show()
注意：
(x,y) 为中心，而是以其左下角的坐标表示。我这样做是为了简化代码。你应该使用 (x + dx/2, y + dx/2)。z**2 来给出颜色。你也应该根据自己的需求进行适当调整。最后针对你的第二个问题，你可以通过传递关键字参数 edgecolor 或 edgecolors 来获取散点标记的边框。这两个参数都接受 matplotlib 的颜色参数或 RGBA 元组的序列。如果将参数设置为 'None'，则不绘制边框。
edgecolors参数的？ - Dror