在子图中的matplotlib轴上旋转变换

Question

我正在尝试创建一个四面板图，其中左下方面板包含散点图，其他三个面板包含直方图。左上角将是散射的x维度上的标准直方图，右下角将是y维度的90°旋转直方图。这两个在matplotlib中都很容易做到。

我遇到了第三个直方图的问题，这是图的右上角的45°旋转图，给出了x和y点之间差异的分布。我之前通过在Illustrator中手动旋转和重新缩放轴来制作这些数字，但似乎matplotlib应该能够生成已经使用子绘图轴上的变换方法旋转的图形。

我认为以下内容可能有效：

import matplotlib.pyplot as plt
from matplotlib.transforms import Affine2D

fig, ax = plt.subplots(nrows=2, ncols=2, squeeze=True, sharex=False, 
                       sharey=False, figsize=(8,8))
ax[0,1].text(0.5,0.5,'I should be rotated',ha='center',va='center')
t = ax[0,1].get_transform()
ax[0,1].set_transform(t.transform(Affine2D().rotate_deg(45)))

plt.show()

在这里，我试图从轴获取变换，修改它，然后将其替换回轴对象。但是，此代码无效。任何帮助将不胜感激。

根据ImportanceOfBeingErnest的建议在评论中编辑：

我看了一下Floating Axes演示，现在有了这个：

from matplotlib.transforms import Affine2D
import mpl_toolkits.axisartist.floating_axes as floating_axes
import matplotlib.pyplot as plt

def setup_axes(fig, rect, rotation, axisScale):
    tr = Affine2D().scale(axisScale[0], axisScale[1]).rotate_deg(rotation)

    grid_helper = floating_axes.GridHelperCurveLinear(tr, extremes=(-0.5, 3.5, 0, 4))

    ax = floating_axes.FloatingSubplot(fig, rect, grid_helper=grid_helper)
    fig.add_subplot(ax)
    aux_ax = ax.get_aux_axes(tr)

    return ax, aux_ax

fig  = plt.figure(1, figsize=(8, 8))
axes = []
axisOrientation = [0, 0, 270, -45]
axisScale = [[1,1],[2,1],[2,1],[2,1]]
axisPosition = [223,221,224,222]

for i in range(0, len(axisOrientation)):
    ax, aux_ax = setup_axes(fig, axisPosition[i], axisOrientation[i], axisScale[i])
    axes.append(aux_ax)
fig.subplots_adjust(wspace=-0.2, hspace=-0.2, left=0.00, right=0.99, top=0.99, bottom=0.0)
plt.show()

这让我更接近我想要的东西：

我将尝试将散点图和直方图添加到这些轴。

Answer 1

下面的代码实现了我原本想要的，除了我正在寻找一种方法来将右上角的数字转换为更靠近左下角的散点图。这是一个较小的问题，因此我可以将其作为一个新问题发布。

from matplotlib.transforms import Affine2D
import mpl_toolkits.axisartist.floating_axes as floating_axes
import matplotlib.pyplot as plt

def setup_axes(fig, rect, rotation, axisScale, axisLimits, doShift):
    tr_rot = Affine2D().scale(axisScale[0], axisScale[1]).rotate_deg(rotation)

    # This seems to do nothing
    if doShift:
        tr_trn = Affine2D().translate(-90,-5)
    else:
        tr_trn = Affine2D().translate(0,0)

    tr = tr_rot + tr_trn

    grid_helper = floating_axes.GridHelperCurveLinear(tr, extremes=axisLimits)

    ax = floating_axes.FloatingSubplot(fig, rect, grid_helper=grid_helper)
    fig.add_subplot(ax)
    aux_ax = ax.get_aux_axes(tr)

    return ax, aux_ax

fig  = plt.figure(1, figsize=(8, 8))
axes = []
axisOrientation = [0, 0, 270, -45]
axisScale = [[1,1],[6,1],[6,1],[6,1]]
axisPosition = [223,221,224,222]
axisLimits = [(-0.5, 4.5, -0.5, 4.5),
              (-0.5, 4.5, 0, 12),
              (-0.5, 4.5, 0, 12),
              (-3.5, 3.5, 0, 12)]
doShift = [False, False, False, True]

label_axes = []
for i in range(0, len(axisOrientation)):
    ax, aux_ax = setup_axes(fig, axisPosition[i], axisOrientation[i], 
                            axisScale[i], axisLimits[i], doShift[i])
    axes.append(aux_ax)
    label_axes.append(ax)

numPoints = 100
x = []
y = []
for i in range(0,numPoints):
    x.append(np.random.rand() + i/100.0)
    y.append(np.random.rand() + i/100.0 + np.mod(i,2)*2)

axes[0].plot(x,y,ls='none',marker='x')
label_axes[0].axis["bottom"].label.set_text('Variable 1')
label_axes[0].axis["left"].label.set_text('Variable 2')

b = np.linspace(-0.5,4.5,50)
axes[1].hist(x, bins = b)
axes[2].hist(y, bins = b)
b = np.linspace(-3.5,3.5,50)
axes[3].hist(np.array(x)-np.array(y), bins=b)

for i in range(1,len(label_axes)):
    for axisLoc in ['top','left','right']:
        label_axes[i].axis[axisLoc].set_visible(False)
    label_axes[i].axis['bottom'].toggle(ticklabels=False)    

fig.subplots_adjust(wspace=-0.30, hspace=-0.30, left=0.00, right=0.99, top=0.99, bottom=0.0)
plt.show()