matplotlib:两行之间的连续颜色图填充 [英] matplotlib: continuous colormap fill between two lines

问题描述

可以在行之间填充颜色:

http://matplotlib.sourceforge.net/examples/pylab_examples/fill_between_demo.html

也可以对一行使用连续的颜色图:

http://matplotlib.sourceforge.net/examples/pylab_examples/multicolored_line.html

是否可以(并且相当容易)对两行之间的彩色填充使用连续的颜色图?例如，基于x处的两条线之间的差异(或基于另一组数据)，颜色填充可能会沿着x发生变化.

解决方案

我找到了解决此问题的方法.它建立在精妙而又狡猾的解决方案.您创建了一个由许多小盒子组成的2D网格.这不是最快的解决方案，但它应该非常灵活(比将imshow应用于补丁的解决方案要强得多).

import numpy as np
import pylab as plt

#Plot a rectangle
def rect(ax, x, y, w, h, c,**kwargs):
    #Varying only in x
    if len(c.shape) is 1:
        rect = plt.Rectangle((x, y), w, h, color=c, ec=c,**kwargs)
        ax.add_patch(rect)
    #Varying in x and y
    else:
        #Split into a number of bins
        N = c.shape[0]
        hb = h/float(N); yl = y
        for i in range(N):
            yl += hb
            rect = plt.Rectangle((x, yl), w, hb, 
                                 color=c[i,:], ec=c[i,:],**kwargs)
            ax.add_patch(rect)

#Fill a contour between two lines
def rainbow_fill_between(ax, X, Y1, Y2, colors=None, 
                         cmap=plt.get_cmap("Reds"),**kwargs):
    plt.plot(X,Y1,lw=0)  # Plot so the axes scale correctly

    dx = X[1]-X[0]
    N  = X.size

    #Pad a float or int to same size as x
    if (type(Y2) is float or type(Y2) is int):
        Y2 = np.array([Y2]*N)

    #No colors -- specify linear
    if colors is None:
        colors = []
        for n in range(N):
            colors.append(cmap(n/float(N)))
    #Varying only in x
    elif len(colors.shape) is 1:
        colors = cmap((colors-colors.min())
                      /(colors.max()-colors.min()))
    #Varying only in x and y
    else:
        cnp = np.array(colors)
        colors = np.empty([colors.shape[0],colors.shape[1],4])
        for i in range(colors.shape[0]):
            for j in range(colors.shape[1]):
                colors[i,j,:] = cmap((cnp[i,j]-cnp[:,:].min())
                                    /(cnp[:,:].max()-cnp[:,:].min()))

    colors = np.array(colors)

    #Create the patch objects
    for (color,x,y1,y2) in zip(colors,X,Y1,Y2):
        rect(ax,x,y2,dx,y1-y2,color,**kwargs)


# Some Test data    
X = np.linspace(0,10,100)
Y1 = .25*X**2 - X
Y2 = X
g = np.exp(-.3*(X-5)**2)

#Plot fill and curves changing in x only
fig, axs =plt.subplots(1,2)
colors = g
rainbow_fill_between(axs[0],X,Y1,Y2,colors=colors)
axs[0].plot(X,Y1,'k-',lw=4)
axs[0].plot(X,Y2,'k-',lw=4)

#Plot fill and curves changing in x and y
colors = np.outer(g,g)
rainbow_fill_between(axs[1],X,Y1,Y2,colors=colors)
axs[1].plot(X,Y1,'k-',lw=4)
axs[1].plot(X,Y2,'k-',lw=4)
plt.show()

结果是，

It's possible to fill between lines with a color:

http://matplotlib.sourceforge.net/examples/pylab_examples/fill_between_demo.html

It's also possible to use a continuous colormap for a line:

http://matplotlib.sourceforge.net/examples/pylab_examples/multicolored_line.html

Is it possible (and reasonably easy) to use a continuous colormap for the colored fill between two lines? For example, the color fill may change along x based on the difference between the two lines at x (or based on another set of data).

解决方案

I found a solution to this problem. It builds on the brilliant but hacky solution of @Hooked. You create a 2D grid filed from lots of small boxes. It's not the fastest solution but it should be pretty flexible (more so than solutions which apply imshow to the patches).

import numpy as np
import pylab as plt

#Plot a rectangle
def rect(ax, x, y, w, h, c,**kwargs):
    #Varying only in x
    if len(c.shape) is 1:
        rect = plt.Rectangle((x, y), w, h, color=c, ec=c,**kwargs)
        ax.add_patch(rect)
    #Varying in x and y
    else:
        #Split into a number of bins
        N = c.shape[0]
        hb = h/float(N); yl = y
        for i in range(N):
            yl += hb
            rect = plt.Rectangle((x, yl), w, hb, 
                                 color=c[i,:], ec=c[i,:],**kwargs)
            ax.add_patch(rect)

#Fill a contour between two lines
def rainbow_fill_between(ax, X, Y1, Y2, colors=None, 
                         cmap=plt.get_cmap("Reds"),**kwargs):
    plt.plot(X,Y1,lw=0)  # Plot so the axes scale correctly

    dx = X[1]-X[0]
    N  = X.size

    #Pad a float or int to same size as x
    if (type(Y2) is float or type(Y2) is int):
        Y2 = np.array([Y2]*N)

    #No colors -- specify linear
    if colors is None:
        colors = []
        for n in range(N):
            colors.append(cmap(n/float(N)))
    #Varying only in x
    elif len(colors.shape) is 1:
        colors = cmap((colors-colors.min())
                      /(colors.max()-colors.min()))
    #Varying only in x and y
    else:
        cnp = np.array(colors)
        colors = np.empty([colors.shape[0],colors.shape[1],4])
        for i in range(colors.shape[0]):
            for j in range(colors.shape[1]):
                colors[i,j,:] = cmap((cnp[i,j]-cnp[:,:].min())
                                    /(cnp[:,:].max()-cnp[:,:].min()))

    colors = np.array(colors)

    #Create the patch objects
    for (color,x,y1,y2) in zip(colors,X,Y1,Y2):
        rect(ax,x,y2,dx,y1-y2,color,**kwargs)


# Some Test data    
X = np.linspace(0,10,100)
Y1 = .25*X**2 - X
Y2 = X
g = np.exp(-.3*(X-5)**2)

#Plot fill and curves changing in x only
fig, axs =plt.subplots(1,2)
colors = g
rainbow_fill_between(axs[0],X,Y1,Y2,colors=colors)
axs[0].plot(X,Y1,'k-',lw=4)
axs[0].plot(X,Y2,'k-',lw=4)

#Plot fill and curves changing in x and y
colors = np.outer(g,g)
rainbow_fill_between(axs[1],X,Y1,Y2,colors=colors)
axs[1].plot(X,Y1,'k-',lw=4)
axs[1].plot(X,Y2,'k-',lw=4)
plt.show()

The result is,

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