不同刻度的叠加图

Question

到目前为止，我有以下代码：

colors = ('k','r','b')
ax = []
for i in range(3):
    ax.append(plt.axes())
    plt.plot(datamatrix[:,0],datamatrix[:,i],colors[i]+'o')
    ax[i].set(autoscale_on=True)

我在每个坐标轴上都设置了 autoscale_on=True 这个选项，以为每个图表应该有自己的y轴范围，但看起来它们都共享了同样的值（即使它们的坐标轴不同）。我该如何设置它们的范围，以显示每个 datamatrix[:,i] 的数据范围（是不是只需要明确调用 .set_ylim() 呢）？另外，我还想为第三个变量（datamatrix[:,2]）创建一个偏移的y轴，这可能是需要的。谢谢大家。

Answer 1

感谢Joe Kington的回答，我找到了一个解决方案，可以让所有额外的y轴都在图表的左侧。

不过我还是想知道怎么才能正确地做到这一点，因为这只是一个变通的方法：

import matplotlib.pyplot as plt
import numpy as np
# To make things reproducible...
np.random.seed(1977)

fig, ax = plt.subplots()

# Twin the x-axis twice to make independent y-axes.
axes = [ax, ax.twinx(), ax.twinx()]

# Make some space on the right side for the extra y-axis.
fig.subplots_adjust(right=0.75)

# Move the last y-axis spine over to the right by 20% of the width of the axes
axes[1].spines['right'].set_position(('axes', -0.25))
axes[2].spines['right'].set_position(('axes', -0.5))

# To make the border of the right-most axis visible, we need to turn the frame
# on. This hides the other plots, however, so we need to turn its fill off.
axes[-1].set_frame_on(True)
axes[-1].patch.set_visible(False)

# And finally we get to plot things...
colors = ('Green', 'Red', 'Blue')
intAxNo = 0
for ax, color in zip(axes, colors):
    intAxNo += 1
    data = np.random.random(1) * np.random.random(10)
    ax.plot(data, marker='o', linestyle='none', color=color)
    if (intAxNo > 1):
        if (intAxNo == 2):
            ax.set_ylabel('%s Thing' % color, color=color, labelpad = -40 )
        elif (intAxNo == 3):
            ax.set_ylabel('%s Thing' % color, color=color, labelpad = -45 )
        ax.get_yaxis().set_tick_params(direction='out')
    else:
        ax.set_ylabel('%s Thing' % color, color=color, labelpad = +0 )

    ax.tick_params(axis='y', colors=color)
axes[0].set_xlabel('X-axis')


plt.show()

Answer 2

快速搭建一个可以在同一个x轴上显示多个y轴的图表，参考了@joe-kington的回答：

# d = Pandas Dataframe, 
# ys = [ [cols in the same y], [cols in the same y], [cols in the same y], .. ] 
def chart(d,ys):

    from itertools import cycle
    fig, ax = plt.subplots()

    axes = [ax]
    for y in ys[1:]:
        # Twin the x-axis twice to make independent y-axes.
        axes.append(ax.twinx())

    extra_ys =  len(axes[2:])

    # Make some space on the right side for the extra y-axes.
    if extra_ys>0:
        temp = 0.85
        if extra_ys<=2:
            temp = 0.75
        elif extra_ys<=4:
            temp = 0.6
        if extra_ys>5:
            print 'you are being ridiculous'
        fig.subplots_adjust(right=temp)
        right_additive = (0.98-temp)/float(extra_ys)
    # Move the last y-axis spine over to the right by x% of the width of the axes
    i = 1.
    for ax in axes[2:]:
        ax.spines['right'].set_position(('axes', 1.+right_additive*i))
        ax.set_frame_on(True)
        ax.patch.set_visible(False)
        ax.yaxis.set_major_formatter(matplotlib.ticker.OldScalarFormatter())
        i +=1.
    # To make the border of the right-most axis visible, we need to turn the frame
    # on. This hides the other plots, however, so we need to turn its fill off.

    cols = []
    lines = []
    line_styles = cycle(['-','-','-', '--', '-.', ':', '.', ',', 'o', 'v', '^', '<', '>',
               '1', '2', '3', '4', 's', 'p', '*', 'h', 'H', '+', 'x', 'D', 'd', '|', '_'])
    colors = cycle(matplotlib.rcParams['axes.color_cycle'])
    for ax,y in zip(axes,ys):
        ls=line_styles.next()
        if len(y)==1:
            col = y[0]
            cols.append(col)
            color = colors.next()
            lines.append(ax.plot(d[col],linestyle =ls,label = col,color=color))
            ax.set_ylabel(col,color=color)
            #ax.tick_params(axis='y', colors=color)
            ax.spines['right'].set_color(color)
        else:
            for col in y:
                color = colors.next()
                lines.append(ax.plot(d[col],linestyle =ls,label = col,color=color))
                cols.append(col)
            ax.set_ylabel(', '.join(y))
            #ax.tick_params(axis='y')
    axes[0].set_xlabel(d.index.name)
    lns = lines[0]
    for l in lines[1:]:
        lns +=l
    labs = [l.get_label() for l in lns]
    axes[0].legend(lns, labs, loc=0)

    plt.show()

Answer 3

听起来你想要的是子图... 你现在的做法有点不太对劲（或者说我对你的代码片段感到很困惑）。

试试下面这种方式：

import matplotlib.pyplot as plt
import numpy as np

fig, axes = plt.subplots(nrows=3)

colors = ('k', 'r', 'b')
for ax, color in zip(axes, colors):
    data = np.random.random(1) * np.random.random(10)
    ax.plot(data, marker='o', linestyle='none', color=color)

plt.show()

补充：

如果你不想要子图，那么你的代码片段就更有道理了。

你试图把三个坐标轴放在同一个位置上。Matplotlib发现这个位置已经有一个子图了，所以每次都返回同一个坐标轴对象。换句话说，如果你查看你的列表ax，你会发现它们都是同一个对象。

如果你真的想这样做，你需要在每次添加坐标轴时，把fig._seen重置为空字典。不过，你可能并不想这样做。

与其把三个独立的图重叠在一起，不如看看使用twinx这个方法。

例如：

import matplotlib.pyplot as plt
import numpy as np
# To make things reproducible...
np.random.seed(1977)

fig, ax = plt.subplots()

# Twin the x-axis twice to make independent y-axes.
axes = [ax, ax.twinx(), ax.twinx()]

# Make some space on the right side for the extra y-axis.
fig.subplots_adjust(right=0.75)

# Move the last y-axis spine over to the right by 20% of the width of the axes
axes[-1].spines['right'].set_position(('axes', 1.2))

# To make the border of the right-most axis visible, we need to turn the frame
# on. This hides the other plots, however, so we need to turn its fill off.
axes[-1].set_frame_on(True)
axes[-1].patch.set_visible(False)

# And finally we get to plot things...
colors = ('Green', 'Red', 'Blue')
for ax, color in zip(axes, colors):
    data = np.random.random(1) * np.random.random(10)
    ax.plot(data, marker='o', linestyle='none', color=color)
    ax.set_ylabel('%s Thing' % color, color=color)
    ax.tick_params(axis='y', colors=color)
axes[0].set_xlabel('X-axis')

plt.show()