[英]How to rotate a Subplot by 45 degree in Matplotlib?
我正在嘗試探索一個旋轉 45 度的正方形的子圖 2 地塊。
import matplotlib.pyplot as plt
from matplotlib import colors
import numpy as np
data = np.random.rand(10, 10) * 20
# create discrete colormap
cmap = colors.ListedColormap(['red', 'blue','green'])
bounds = [0,5,10,15]
norm = colors.BoundaryNorm(bounds, cmap.N)
fig, ax= plt.subplots(1,2)
ax[0].imshow(data, cmap=cmap, norm=norm)
# draw gridlines
ax[0].grid(which='major', axis='both', linestyle='-', color='k', linewidth=0)
ax[0].set_xticks(np.arange(-.5, 10, 1));
ax[0].set_yticks(np.arange(-.5, 10, 1));
ax[1].imshow(data, cmap=cmap, norm=norm)
# draw gridlines
ax[1].grid(which='major', axis='both', linestyle='-', color='k', linewidth=0)
ax[1].set_xticks(np.arange(-.5, 10, 1));
ax[1].set_yticks(np.arange(-.5, 10, 1));
plt.show()
實際結果是:-
我試圖在 Matplotlib 文檔中找到。 仍然沒有得到。 有什么幫助嗎?
請注意,這不是重復的
有沒有辦法將 matplotlib plot 旋轉 45 度?
提到的 URL 用於 plot。 解決方案是旋轉圖像。 然而,這與子圖有關。 我想旋轉 PLOT 而不是整個圖像。
基於此鏈接和有關floating_axes
的文檔,您可以嘗試以下操作:
from mpl_toolkits.axisartist.grid_finder import DictFormatter
import matplotlib.pyplot as plt
from matplotlib.transforms import Affine2D
import mpl_toolkits.axisartist.floating_axes as floating_axes
from matplotlib import colors
import numpy as np
def setup_axes1(fig, rect, angle):
tr = Affine2D().scale(2, 2).rotate_deg(angle)
#We create dictionarys to keep the xticks and yticks after the rotation
dictio={i:str(val) for i,val in enumerate(np.arange(-.5, 10, 1).tolist())}
reversedictio={i:dictio[val] for i,val in enumerate(list(reversed(sorted(dictio.keys()))))}
grid_helper = floating_axes.GridHelperCurveLinear(
tr, extremes=(-0.5, 9.5,-0.5, 9.5), tick_formatter1= DictFormatter(dictio),
tick_formatter2=DictFormatter(reversedictio))
ax1 = floating_axes.FloatingSubplot(fig, rect, grid_helper=grid_helper)
fig.add_subplot(ax1)
aux_ax = ax1.get_aux_axes(tr)
grid_helper.grid_finder.grid_locator1._nbins = 10 #Number of rows
grid_helper.grid_finder.grid_locator2._nbins = 10 #Number of columns
return aux_ax
fig1, axes=plt.subplots(2,figsize=(20,20))
plt.rcParams.update({'font.size': 27})
#We erase the first previous axes
fig1.delaxes(axes[0])
fig1.delaxes(axes[1])
data = np.random.rand(10, 10) * 20
#We create the floating_axes
ax0 = setup_axes1(fig1, 121,-45)
ax1 = setup_axes1(fig1, 122,-45)
# create discrete colormap
cmap = colors.ListedColormap(['red', 'blue','green'])
bounds = [0,5,10,15]
norm = colors.BoundaryNorm(bounds, cmap.N)
ax0.imshow(data, cmap=cmap, norm=norm,interpolation="nearest")
# draw gridlines
ax0.grid(which='major', axis='both', linestyle='-', color='k', linewidth=0)
ax1.imshow(data, cmap=cmap, norm=norm,interpolation="nearest")
# draw gridlines
ax1.grid(which='major', axis='both', linestyle='-', color='k', linewidth=0)
plt.show()
Output:
或者,作為另一種選擇,我找到了一種“棘手”的方法,它是關於捕獲緩沖區中的數字,將它們旋轉 -45 度,然后將它們合並成一個圖像,因為你有相同的兩個圖片,你可以試試這樣的:
import matplotlib
import io
from PIL import Image
import matplotlib.pyplot as plt
from matplotlib import colors
import numpy as np
##PLOTING THE FIGURE##
data = np.random.rand(10, 10) * 20
# create discrete colormap
cmap = colors.ListedColormap(['red', 'blue','green'])
bounds = [0,5,10,15]
norm = colors.BoundaryNorm(bounds, cmap.N)
#We change style values to get the image with better quality
plt.rcParams.update({'font.size': 46})
plt.figure(figsize=(20,20))
plt.imshow(data, cmap=cmap, norm=norm)
# draw gridlines
plt.grid(which='major', axis='both', linestyle='-', color='k', linewidth=0)
plt.gca().set_xticks(np.arange(-.5, 10, 1));
plt.gca().set_yticks(np.arange(-.5, 10, 1));
##SAVING THE FIGURE INTO AN IMAGE##
#We save the current figure as a Image
buf = io.BytesIO()
plt.savefig(buf, format='png',bbox_inches='tight')
buf.seek(0)
im = Image.open(buf) #We open the current image saved in the buffer
#We rotate the image and fill the background with white
img_01=im.rotate(-45, Image.NEAREST, expand = 1, fillcolor = (255,255,255))
buf.close()
##MERGING THE TWO FIGURES##
new_im = Image.new('RGB', (2*img_01.size[0]+20,img_01.size[1]), 'white')
mouse_mask = img_01.convert('RGBA')
new_im.paste(img_01, (0,0))
new_im.paste(img_01, (img_01.size[0]+8,0))
new_im.save("merged_images.png", 'PNG') #Important(just to clarify): save the image, since the buffer is renewed every time you run the script
new_im.show()
我通過這些鏈接幫助自己:
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