plt.subplot_adjust（）无法正常工作

Question

我正在像这样绘制一些密度图：

import matplotlib.pyplot as plt
import numpy as np
from sklearn.metrics import r2_score
import matplotlib
from scipy import stats
import matplotlib.gridspec as gridspec
from mpl_toolkits.axes_grid1.inset_locator import InsetPosition
from matplotlib.ticker import FormatStrFormatter
import matplotlib.cm as cm
from scipy.ndimage.filters import gaussian_filter
import random

matplotlib.rcParams.update({'font.size': 16})
matplotlib.rcParams['xtick.direction'] = 'in'
matplotlib.rcParams['ytick.direction'] = 'in'

x = random.sample(range(1, 10001), 1000)
y = random.sample(range(1, 10001), 1000)



def myplot(x, y, s, bins=1000):
    heatmap, xedges, yedges = np.histogram2d(x, y, bins=bins)
    heatmap = gaussian_filter(heatmap, sigma=s)

    extent = [xedges[0], xedges[-1], yedges[0], yedges[-1]]
    return heatmap.T, extent
cmap = cm.YlOrRd

fig, (ax, ax1, cax) = plt.subplots(ncols = 3, figsize = (15, 5),
                       gridspec_kw={"width_ratios":[1,1, 0.5]})
img, extent = myplot(x, y, 20)
im = ax.imshow(img, extent = extent, origin = 'lower', cmap = cmap)
ax.text(0.05, 0.92, '$R^2$ = {}'.format(np.round(r2_score(x, y), 2)), fontsize=14, color = 'k', transform = ax.transAxes)
ax.plot(ax.get_xlim(), ax.get_ylim(), ls="--", c=".3")
ax.set_xlabel("Black Sky")
ax.set_ylabel("Blue Sky")

img2, extent2 = myplot(x, y, 20)
ax1.imshow(img2, extent = extent2, origin = 'lower', cmap = cmap)
ax1.text(0.05, 0.92, '$R^2$ = {}'.format(np.round(r2_score(x, y), 2)), fontsize=14, color = 'k', transform = ax1.transAxes)
ax1.axes.get_yaxis().set_visible(False)
ax1.yaxis.set_ticks([])
ax1.plot(ax1.get_xlim(), ax1.get_ylim(), ls="--", c=".3")
ax1.set_xlabel("White Sky")


ip = InsetPosition(ax1, [1.05,0,0.05,1]) 

cax.set_axes_locator(ip)

fig.colorbar(im, cax=cax, ax=[ax,ax1], use_gridspec = True)

plt.subplots_adjust(wspace=0.1, hspace=0)

这给了我这样的情节：

无论我将wspace更改为何种情节，都保持不变。我认为这是因为当我在ax1中旋转y轴时，我只是将文本设置为空白，而不是一起删除y轴。有没有一种方法可以使图形之间的宽度间距更接近？

Answer 1

如前所述，wspace设置图之间的最小距离。在长宽比轴相等的情况下，此距离可能更大。然后将取决于图形大小，图形外观和图像外观。

A。使用自动宽高比

您可以在aspect = "auto"图中设置imshow

ax.imshow(..., aspect = "auto")

B。调整子图参数

您可以将left或right子图参数设置为较小的值。例如

plt.subplots_adjust(wspace=0.0, hspace=0, right=0.7)

C。调整图形大小

使用较小的图形宽度（更接近实际的图像宽高比）也会减少图形周围的空白。

例如，使图形仅宽11英​​寸，并在右侧使用5％的填充，

plt.subplots(..., figsize = (11, 5))
plt.subplots_adjust(wspace=0.0, hspace=0, right=.95)