Python散点图。标记的大小和样式
我有一组数据要显示为散点图。我希望将每个点绘制为大小为Python散点图。标记的大小和样式,python,plot,matplotlib,scatter,Python,Plot,Matplotlib,Scatter,我有一组数据要显示为散点图。我希望将每个点绘制为大小为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') 问题是散射函数读取的大小s位于点^2。我想要的是用面积dx^2的平方表示每个点，其中这个面积是以“实”单位表示的，
dx 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')
s我还有一个问题。散布函数用黑色边框绘制标记，我如何删除此选项而完全没有边框 如果您希望标记根据地物大小调整大小，可以使用面片：
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()
（x，y）（x+dx/2，y+dx/2）最后是你的第二个问题。您可以使用关键字参数
edgecoloredgecolorsimport 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')
我认为我们可以通过收集补丁做得更好。 根据文件： 此（PatchCollection）使将颜色贴图分配给异构对象变得更容易 补丁的集合 这也可以提高绘图速度，因为PatchCollection将 绘制速度比绘制大量面片快 假设要以数据单位绘制具有给定半径的圆的散布：
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
scattermarkercolorbar（）colorbarfrom 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)
这不会按照OP的要求以绘图单位绘制正方形，而是固定大小的正方形，不会调整大小（例如，通过手动更改图框大小。这可能是一个愚蠢的问题。但是，如果dx不是数组，但每个点（x、y、z）都相同，如何更改上面的代码。此外，我真的需要使用add_子绘图吗？您如何找到
edgecolorsscatter