matplotlib教程學習筆記
如何使用tight_layout?
tight_layout作用於ticklabels, axis, labels, titles等Artist
簡單的例子
import matplotlib.pyplot as plt
import numpy as np
下面的例子和constrained_layout中的是一樣的,notebook沒有顯示出其中的問題,就是labels被遮擋了
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,每次作圖,我們都需要通過使用plt.tight_layout()函數來激活,我們也可以通過
fig.set_tight_layout(True)使得每次作圖都會自動tight布局,當然,還可以通過將
figure.autolayout rcParam設置為True來實現。
有多個plots的時候,會出現重疊的現象,通過tight_layout可以解決
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()

tight_layout可以通過參數pad, w_pad, h_pad來設置一些布局的細節
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依舊能夠工作
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()

對subplot2grid也有效,注意subplot2grid參數為:
shape: e.g. (3, 3) 表示\(3 \times 3\)個格子
loc: e.g. (0, 1) 表示從第一行第二列個格子開始
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 擁有自己的tight_layout()方法, 當然,plt.tight_layout也是有效的
import matplotlib.gridspec as gridspec
plt.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參數,表示一個外界的框框
默認是(0, 0, 1, 1)
(x1, y1, x2, y2)
(x1, y1)矩形限制框左下角點
(x2, y2)矩形限制框右上角點
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])

這個功能可以很好的用在分割圖形,以及分塊操作上
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 ::
#為了讓倆塊圖形上下一致,需要進行下面的操作
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和右邊的邊邊不齊,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()

有些時候,我們不希望legend也在tight_layout的掌控范圍之內,這個時候,我們可以設置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
沒看懂
from mpl_toolkits.axes_grid1 import Grid
plt.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_locatable
plt.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()

