在一个子blot2grid中生成迭代子批

Question

我想要一个分为4个扇区的窗口：在（0,0）一个imshow图像（ax1）；（1,0）一个使用twinx（）图像分割窗口的子图（ax2&ax3）；（1,1）一个常规的绘图图像（ax4）；以及一个迭代的绘图部分（0,1），它应该给出一个比另一个（ax5）一个的“数量_个子图”。希望没有xticklabels，只有最后一个。

This is how the frame should look like before the iterative subplot creation.

我的问题：当迭代在窗口的右上角空间创建子窗口时，子批距该空间越远，并消除了ax4

This is how the window looks after the "for" cyle for the subplot creation

下面您将看到我使用的代码的简化，这样您可以更好地看到它。我已经用随机数代替了我的实验数据，这样你就可以很容易地复制了。

你能告诉我我做错了什么吗？我仍然不能控制python中的所有处理程序。几年前我曾经在matlab中做过类似的事情。

    import matplotlib.pyplot as plt
    from matplotlib.gridspec import GridSpec
    import numpy as np
    import pdb

    pos = [1,2,3,4,5]
    N = 50
    x = np.random.rand(N)
    y = np.random.rand(N)

    xx = np.linspace(0, 20, 1000)

    fig1 = plt.figure()
    number_of_subplots = len(pos) #number between 1-7
    ax1 = plt.subplot2grid((number_of_subplots+1,2),(0,0),rowspan = number_of_subplots-1) # Here the idea is to "dinamically" create the division of the grid, making space at the bottom of it for the image in the bottom left.
    ax1.scatter(x,y)

    ax2 = plt.subplot2grid((number_of_subplots+1,2),(number_of_subplots-1,0), rowspan = 2)
    ax2.plot(xx,np.sin(xx),label = 'sin(x)',color = 'b')
    ax3 = ax2.twinx()
    ax3.plot(xx,np.cos(xx), label = 'cos(x)', color = 'r')

    ax4 = plt.subplot2grid((number_of_subplots+1,2),(number_of_subplots-1,1), rowspan = 2)
    ax4.plot(xx,np.tan(xx), label = 'tan(x)', color = 'g')

    for i,v in enumerate(xrange(number_of_subplots)):
            v = v+1
            ax5 = plt.subplot2grid((number_of_subplots+1,2),(v-1,1))
            ax5.plot(np.sin(xx+3.1416*v/2)) # Grafica los perfiles, asociandoles el mismo color que para los cortes en la imagen 2D
            if (i % 2 == 0): #Even
                    ax5.yaxis.tick_left()
            else:
                    ax5.yaxis.tick_right()
    plt.draw()
    plt.show()

Answer 1

通过使用GridSpec解决了这个问题。下面是给出以下解决方案的代码实现。在

This is the correct way the image should look like and the implementation is below on the code.

    import matplotlib.pyplot as plt
    import matplotlib.gridspec as gridspec
    import numpy as np
    import pdb

    pos = [1,2,3,4,5]

    N = 50
    x = np.random.rand(N)
    y = np.random.rand(N)

    xx = np.linspace(0, 20, 1000)

    number_of_subplots = len(pos) #number between 1-7

    fig1 = plt.figure()

    gs0 = gridspec.GridSpec(2,2,height_ratios=[3,1],hspace=0.1)
    ax1 = plt.subplot(gs0[0,0])
    ax2 = plt.subplot(gs0[-1,0])
    ax4 = plt.subplot(gs0[-1,-1])

    gs2 = gridspec.GridSpecFromSubplotSpec(number_of_subplots, 1, subplot_spec=gs0[1],wspace=0.0, hspace=0.0)

    ax1.scatter(x,y)

    ax2.plot(xx,np.sin(xx),label = 'sin(x)',color = 'b')
    ax3 = ax2.twinx()
    ax3.plot(xx,np.cos(xx), label = 'cos(x)', color = 'r')

    ax4.plot(xx,np.tan(xx), label = 'tan(x)', color = 'g')

    for i in enumerate(xrange(number_of_subplots)):
            ax5 = plt.subplot(gs2[i,:])
            ax5.plot(np.sin(xx+3.1416*i/2)) 
            if (i % 2 == 0): #Even
                    ax5.yaxis.tick_left()
            else:
                    ax5.yaxis.tick_right()
    plt.draw()
    plt.show()