Ellipse的Edgecolor作为第三个变量的函数

Question

我希望椭圆的edgecolor是第三个变量的函数。让我们假设第三个变量叫做通量。如果变量＆＃39; flux＆＃39;的值很高，我希望椭圆的边缘颜色为深蓝色，如果值很低，我希望颜色为黄色。任何中间值都应该是这些颜色的混合。我希望这个颜色渐变在图的z轴上可见，具有最高和最低值。我尝试引用此链接Matplotlib scatterplot; colour as a function of a third variable，但这似乎并不适用于我的情况。我正在读取从文本文件中绘制椭圆所需的参数，如下所示：

149.20562 2.29594 0.00418 0.00310 83.40 1.15569 

149.23158 1.99783 0.00437 0.00319 90.30 3.46331 

149.23296 2.45440 0.00349 0.00264 120.30 2.15457 

第五列是名为＆＃39; flux＆＃39;必须根据其绘制颜色渐变。

这是我尝试的一个例子。

import matplotlib.pyplot as plt
import numpy as np
import math
import astropy.io.ascii as asciitable
from matplotlib.patches import Ellipse
ax = plt.gca()
path="/users/xxxx/Desktop/"
plt.xlim([149,151.3])
plt.ylim([1,3.3])
fw=open(path + 'data_plot.txt', 'r')
data = asciitable.read(path+ "data_plot.txt") 
np.array(data)
for i in range(len(data)):
    ra,dec,maj,minor,ang,flux =data[i][0],data[i][1],data[i][2],data[i][3],data[i][4],data[i][5]
    ellipse = Ellipse(xy=(ra, dec), width=maj, height=minor, angle=ang, edgecolor=flux, lw=3, fc='None')
    ax.add_patch(ellipse) 


plt.xlabel('Right Ascention')
plt.ylabel('Declination')
plt.title('abc') 
plt.savefig(path+'abc.eps')

正如所料，这并没有奏效。这是我的错误日志。

runfile('/users/vishnu/.spyder2-py3/radio_sources.py',   wdir='/users/vishnu/.spyder2-py3')


    Traceback (most recent call last):

  File "<ipython-input-695-a0011c0326f5>", line 1, in <module>
    runfile('/users/vishnu/.spyder2-py3/radio_sources.py', wdir='/users/vishnu/.spyder2-py3')

  File "/users/vishnu/anaconda3/lib/python3.5/site-packages/spyderlib/widgets/externalshell/sitecustomize.py", line 699, in runfile
    execfile(filename, namespace)

  File "/users/vishnu/anaconda3/lib/python3.5/site-packages/spyderlib/widgets/externalshell/sitecustomize.py", line 88, in execfile
    exec(compile(open(filename, 'rb').read(), filename, 'exec'), namespace)

  File "/users/vishnu/.spyder2-py3/radio_sources.py", line 63, in <module>
    ellipse = Ellipse(xy=(ra, dec), width=maj, height=minor, angle=ang, edgecolor=flux, lw=3, fc='None')

  File "/users/vishnu/anaconda3/lib/python3.5/site-packages/matplotlib/patches.py", line 1378, in __init__
    Patch.__init__(self, **kwargs)

  File "/users/vishnu/anaconda3/lib/python3.5/site-packages/matplotlib/patches.py", line 111, in __init__
    self.set_edgecolor(edgecolor)

  File "/users/vishnu/anaconda3/lib/python3.5/site-packages/matplotlib/patches.py", line 277, in set_edgecolor
    self._edgecolor = colors.colorConverter.to_rgba(color, self._alpha)

  File "/users/vishnu/anaconda3/lib/python3.5/site-packages/matplotlib/colors.py", line 376, in to_rgba
    'to_rgba: Invalid rgba arg "%s"\n%s' % (str(arg), exc))

ValueError: to_rgba: Invalid rgba arg "1.15569"
to_rgb: Invalid rgb arg "1.15569"
cannot convert argument to rgb sequence

Answer 1

您只需将flux的值更改为matplotlib颜色即可。我们可以使用色图来执行此操作，或者在您的情况下，您可以使用flux来定义颜色，假设有一些最小值和最大值。

由于黄色只是红色和绿色的混合，我们可以使用1减去R和G通道的归一化通量，并使用标准化通量作为RGB元组的B通道来制作matplotlib颜色。

# Change these based on your definition of a 'high' value and a 'low' value (or the min/max of the data)
minflux = data[:][5].min()
maxflux = data[:][5].max()

for i in range(len(data)):
    ra,dec,maj,minor,ang,flux =data[i][0],data[i][1],data[i][2],data[i][3],data[i][4],data[i][5]

    # Normalise the flux value to the range 0-1
    normflux = (flux - minflux) / (maxflux - minflux)
    # RGB tuple. This will be yellow for min value and blue for max value
    fluxcolor = (1.-normflux, 1.-normflux, normflux)

    ellipse = Ellipse(xy=(ra, dec), width=maj, height=minor, angle=ang, edgecolor=fluxcolor, lw=3, fc='None')
    ax.add_patch(ellipse) 

以下是检查其有效的最小示例：

import matplotlib.pyplot as plt
from matplotlib.patches import Ellipse
import numpy as np

fig,ax = plt.subplots(1)

minflux = 0.
maxflux = 10.

for i in range(10):

    flux = float(i)

    normflux = (flux - minflux) / (maxflux - minflux)
    fluxcolor = (1.-normflux, 1.-normflux, normflux)

    ell = Ellipse(xy=(i+1,0.5), width=0.5, height=0.3, angle=90., edgecolor=fluxcolor, lw=3, fc='None')

    ax.add_patch(ell)

ax.set_xlim(0,11)
plt.show()

要添加颜色条，也许 最简单的方法是使用色彩映射而不是上面显示的方法。在这种情况下，我们还可以使用PatchCollection将所有椭圆添加到轴，然后将集合的数组设置为通量值以定义它们的颜色。

例如：

import matplotlib.pyplot as plt
from matplotlib.patches import Ellipse
import numpy as np

import matplotlib.colors as colors
from matplotlib.collections import PatchCollection

# Define our colormap here. 
# Want red and green to be 1 at 0, and 0 at 1. Blue to be 0 at 0, and 1 at 1.
cdict = {'red':  ((0.0,1.0,1.0),
                  (1.0,0.0,0.0)),
        'green': ((0.0,1.0,1.0),
                  (1.0,0.0,0.0)),
        'blue':  ((0.0,0.0,0.0),
                  (1.0,1.0,1.0))
        }
# Use that dictionary to define the Linear SegmentedColormap
YlBu = colors.LinearSegmentedColormap('YlBu',cdict)

# Create figure
fig,ax = plt.subplots(1)

# Set the aspect ratio
ax.set_aspect('equal')

# We will populate these lists as we loop over our ellipses
ellipses = []
fluxes = []

for i in range(9):

    # Use i as a dummy value for our flux
    flux = float(i)

    # Store the fluxes. You have this already in your data array
    fluxes.append(flux)

    # Angle is in degrees
    angle = float(i) * 45.

    # Create the ellipse patch. Don't add to the axes yet
    ell = Ellipse(xy=(i,2.), width=0.8, height=0.2, angle=angle)

    # Just add it to this list
    ellipses.append(ell)

# Now, create a patch collection from the ellipses. 
# Turn off facecolor, and set the colormap to the one we created earlier
pc = PatchCollection(ellipses,False,lw=3,cmap=YlBu,facecolor='None')

# Set the color array here.
pc.set_array(np.array(fluxes))

# Now we add the collection to the axes
ax.add_collection(pc)

# And create a colorbar
fig.colorbar(pc,orientation='horizontal')

# Set the axes limits
ax.set_xlim(-1,9)
ax.set_ylim(0,4)

plt.show()