目录
教程学习笔记
如何使用tight_layout？
tight_layout作用于ticklabels, axis, labels, titles等Artist
简单的例子
import matplotlib.pyplot as pltimport numpy as np
下面的例子和constrained_layout中的是一样的，notebook没有显示出其中的问题，就是labels被遮挡了
plt.rcParams['savefig.facecolor'] = "0.8"def example_plot(ax, fontsize=12): ax.plot([1, 2]) ax.locator_params(nbins=3) ax.set_xlabel('x-label', fontsize=fontsize) ax.set_ylabel('y-label', fontsize=fontsize) ax.set_title('Title', fontsize=fontsize)plt.close('all')fig, ax = plt.subplots()example_plot(ax, fontsize=24) 
fig, ax = plt.subplots()example_plot(ax, fontsize=24)plt.tight_layout()
注意到，每次作图，我们都需要通过使用plt.tight_layout()函数来激活，我们也可以通过
fig.set_tight_layout(True)使得每次作图都会自动tight布局，当然，还可以通过将 figure.autolayout rcParam设置为True来实现。有多个plots的时候，会出现重叠的现象，通过tight_layout可以解决
plt.close('all')fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(nrows=2, ncols=2)example_plot(ax1)example_plot(ax2)example_plot(ax3)example_plot(ax4) 
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(nrows=2, ncols=2)example_plot(ax1)example_plot(ax2)example_plot(ax3)example_plot(ax4)plt.tight_layout()
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(nrows=2, ncols=2)example_plot(ax1)example_plot(ax2)example_plot(ax3)example_plot(ax4)plt.tight_layout(pad=0.4, w_pad=0.5, h_pad=2)
即使subplots的大小不一致，tight_layout依旧能够工作
plt.close('all')fig = plt.figure()ax1 = plt.subplot(221)ax2 = plt.subplot(223)ax3 = plt.subplot(122)example_plot(ax1)example_plot(ax2)example_plot(ax3)plt.tight_layout() 
对subplot2grid也有效，注意subplot2grid参数为:
shape: e.g. (3, 3) 表示\(3 \times 3\)个格子loc: e.g. (0, 1) 表示从第一行第二列个格子开始
rowspan: 跨行
colspan: 跨列
plt.close('all')fig = plt.figure()ax1 = plt.subplot2grid((3, 3), (0, 0))ax2 = plt.subplot2grid((3, 3), (0, 1), colspan=2)ax3 = plt.subplot2grid((3, 3), (1, 0), colspan=2, rowspan=2)ax4 = plt.subplot2grid((3, 3), (1, 2), rowspan=2)example_plot(ax1)example_plot(ax2)example_plot(ax3)example_plot(ax4)plt.tight_layout() 
arr = np.arange(100).reshape((10, 10))plt.close('all')fig = plt.figure(figsize=(5, 4))ax = plt.subplot(111)im = ax.imshow(arr, interpolation="none")plt.tight_layout() 
Use with GridSpec
Gridspec 拥有自己的tight_layout()方法， 当然，plt.tight_layout也是有效的
import matplotlib.gridspec as gridspecplt.close('all')fig = plt.figure()gs1 = gridspec.GridSpec(2, 1)ax1 = fig.add_subplot(gs1[0])ax2 = fig.add_subplot(gs1[1])example_plot(ax1)example_plot(ax2)gs1.tight_layout(fig) 
gs.tight_layout提供rect参数，表示一个外界的框框
默认是(0, 0, 1, 1) (x1, y1, x2, y2)(x1, y1)矩形限制框左下角点
(x2, y2)矩形限制框右上角点
fig = plt.figure()gs1 = gridspec.GridSpec(2, 1)ax1 = fig.add_subplot(gs1[0])ax2 = fig.add_subplot(gs1[1])example_plot(ax1)example_plot(ax2)gs1.tight_layout(fig, rect=[0, 0, 0.5, 1])
这个功能可以很好的用在分割图形，以及分块操作上
fig = plt.figure()gs1 = gridspec.GridSpec(2, 1)ax1 = fig.add_subplot(gs1[0])ax2 = fig.add_subplot(gs1[1])example_plot(ax1)example_plot(ax2)gs1.tight_layout(fig, rect=[0, 0, 0.5, 1])gs2 = gridspec.GridSpec(3, 1)for ss in gs2: ax = fig.add_subplot(ss) example_plot(ax) ax.set_title("") ax.set_xlabel("")ax.set_xlabel("x-label", fontsize=12)gs2.tight_layout(fig, rect=[0.5, 0, 1, 1], h_pad=0.5)# We may try to match the top and bottom of two grids ::#为了让俩块图形上下一致，需要进行下面的操作top = min(gs1.top, gs2.top)bottom = max(gs1.bottom, gs2.bottom)gs1.update(top=top, bottom=bottom)gs2.update(top=top, bottom=bottom)plt.show() 
但是呢，Title和右边的边边不齐，所以框框是不包含title的？
fig = plt.gcf()gs1 = gridspec.GridSpec(2, 1)ax1 = fig.add_subplot(gs1[0])ax2 = fig.add_subplot(gs1[1])example_plot(ax1)example_plot(ax2)gs1.tight_layout(fig, rect=[0, 0, 0.5, 1])gs2 = gridspec.GridSpec(3, 1)for ss in gs2: ax = fig.add_subplot(ss) example_plot(ax) ax.set_title("") ax.set_xlabel("")ax.set_xlabel("x-label", fontsize=12)gs2.tight_layout(fig, rect=[0.5, 0, 1, 1], h_pad=0.5)top = min(gs1.top, gs2.top)bottom = max(gs1.bottom, gs2.bottom)gs1.update(top=top, bottom=bottom)gs2.update(top=top, bottom=bottom)top = min(gs1.top, gs2.top)bottom = max(gs1.bottom, gs2.bottom)gs1.tight_layout(fig, rect=[None, 0 + (bottom-gs1.bottom), 0.5, 1 - (gs1.top-top)])gs2.tight_layout(fig, rect=[0.5, 0 + (bottom-gs2.bottom), None, 1 - (gs2.top-top)], h_pad=0.5) 
Legend and Annotations
fig, ax = plt.subplots(figsize=(4, 3))lines = ax.plot(range(10), label='A simple plot')ax.legend(bbox_to_anchor=(0.7, 0.5), loc='center left',)fig.tight_layout()plt.show()
有些时候，我们不希望legend也在tight_layout的掌控范围之内，这个时候，我们可以设置leg.set_in_layout(False)
fig, ax = plt.subplots(figsize=(4, 3))lines = ax.plot(range(10), label='B simple plot')leg = ax.legend(bbox_to_anchor=(0.7, 0.5), loc='center left',)leg.set_in_layout(False)fig.tight_layout()plt.show()
Use with AxesGrid1
没看懂
from mpl_toolkits.axes_grid1 import Gridplt.close('all')fig = plt.figure()grid = Grid(fig, rect=111, nrows_ncols=(2, 2), axes_pad=0.25, label_mode='L', )for ax in grid: example_plot(ax)ax.title.set_visible(False)plt.tight_layout() 
Colorbar
plt.close('all')arr = np.arange(100).reshape((10, 10))fig = plt.figure(figsize=(4, 4))im = plt.imshow(arr, interpolation="none")plt.colorbar(im, use_gridspec=True)plt.close('all')arr = np.arange(100).reshape((10, 10))fig = plt.figure(figsize=(4, 4))im = plt.imshow(arr, interpolation="none")plt.colorbar(im, use_gridspec=True)plt.tight_layout() 
from mpl_toolkits.axes_grid1 import make_axes_locatableplt.close('all')arr = np.arange(100).reshape((10, 10))fig = plt.figure(figsize=(4, 4))im = plt.imshow(arr, interpolation="none")divider = make_axes_locatable(plt.gca())cax = divider.append_axes("right", "5%", pad="3%")plt.colorbar(im, cax=cax)plt.tight_layout() 