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python - matplotlib.pyplot 二维参数的颜色图图例

问题描述

我正在同一轴上绘制一系列均方位移 (MSD) 对数图，用于模拟自推进粒子。Dtrans = [0.1, 0.3, 1.0, 3.0, 10]模拟以传递标准偏差和旋转标准偏差的不同值运行，Drot = [0.1, 0.3, 1.0, 3.0, 10, 30, 100, 300]总共进行 5 × 8 = 40 次模拟。这是我目前拥有的：

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as colors
import matplotlib.cm as cmx
import itertools

# List of colour maps
cmaps = ['YlOrRd', 'Greens', 'Blues', 'Purples','RdPu']

nparticles = 5
npts=1000
step=1000
dt = 0.0001

Drot = [0.1, 0.3, 1.0, 3.0, 10, 30, 100, 300]
Dtrans = [0.1, 0.3, 1.0, 3.0, 10]

plt.figure()
plt.title('MSD against time')
plt.xlabel('Time')
plt.ylabel('MSD')

# Time steps along horizontal axis:
timeval = np.linspace(0,dt*step*(npts-1),npts)

# For each value of Dtrans
for d1 in range(len(Dtrans)):

    # Choose a colour map:
    colourmap = plt.get_cmap(cmaps[d1])
    # Limit it to the middle 60%
    colourmap = colors.ListedColormap(colourmap(np.linspace(0.2, 0.8, 256)))

    # Get a colour from the map for each value of Drot:
    values = range(len(Drot))
    cNorm = colors.Normalize(vmin=0,vmax=values[-1])
    scalarMap=cmx.ScalarMappable(norm=cNorm,cmap=colourmap)

    for d2 in range(len(Drot)):
        Dr = Drot[d2]
        Dt = Dtrans[d1]
        MSD = np.zeros((npts,))

        x = np.zeros((npts,nparticles))
        y = np.zeros((npts,nparticles))
        for k in range(npts):
            data0=np.loadtxt(open("./Lowdensity/Drot_"+str(Dr)+"/Dtrans_"+str(Dt)+"/ParticleData/ParticleData"+str(k*step)+".csv",'rb'),delimiter=',')
            x0,y0= data0[:nparticles,1],data0[:nparticles,2]
            x[k,:]=x0
            y[k,:]=y0

        for k in range(npts):
            MSD[k] = np.mean(np.mean((x[k:npts,:] - x[0:(npts-k),:])**2 + (y[k:npts,:] - y[0:(npts-k),:])**2,axis=0))

        colorVal = scalarMap.to_rgba(values[d2])

        plt.loglog(timeval,MSD,color=colorVal)
        plt.legend([('Dtrans='+str(i)+', Drot='+str(j)) for [i,j] in np.array(list(itertools.product(Dtrans,Drot)))])

#plt.loglog(timeval, MSDthry(timeval, 0.5, 100, 70, dt*step*npts))
plt.show()

MSD 与时间的对数图与令人讨厌的传说

颜色图效果很好，但我目前的传说真的很可怕，不适合情节。理想情况下，我希望图例是垂直排列的五个颜色条，Dtrans值沿垂直轴，Drot值水平。我该如何实施？谢谢！

标签： pythonmatplotlibcolorbarcolormapcolor-mapping

解决方案

也许一张桌子可以完成这项工作：

#initialyze an array at the beginning 
colorsarray = np.empty([5,5] )
for d1 in range(len(Dtrans)):
    ...     
    colorVal = scalarMap.to_rgba(values[d2]) 
    colorsarray[d1, d2] =colorVal

    plt.loglog(timeval,MSD,color=colorVal) 


tab=plt.table(cellText="" , colLabels=Dtrans, 
    rowLabels=Drot, colWidths = [0.2,0.2], 
    loc='higher left', cellColours=colorsarray )
plt.show()

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