matplotlib（5）-- 等高線contourf、contour；imshow() ; colorbar(); 3D數據處理

import matplotlib.pyplot as plt
import numpy as np

#定義計算高度的函數
def f(x,y):
    return (1 - x/2 + x**5 +y**3) * np.exp(-x**2 - y**2)

n = 256
x = np.linspace(-3, 3, n)
y = np.linspace(-3, 3, n)
#核心函數是plt.contourf()，但在這個函數中輸入的參數是x,y對應的網格數據以及此網格對應的高度值
#因此我們調用np.meshgrid(x,y)把x,y值轉換成網格數據
X, Y = np.meshgrid(x, y)

#plt.contourf 與 plt.contour 區別：
# f：filled，也即對等高線間的填充區域進行填充（使用不同的顏色）
# contourf：將不會再繪制等高線（顯然不同的顏色分界就表示等高線本身）

#use plt.contourf to filling contours(輪廓)
#X, Y and value for (X ,Y) point
plt.contourf(X, Y,f(X, Y), 8, alpha = 0.75, cmap = plt.get_cmap('rainbow'))

#use plt.contour to add contour lines
C = plt.contour(X, Y,f(X, Y), 8, colors = "black", linewidth = .5)
#關於cmap顏色選擇，參考 https://matplotlib.org/examples/color/colormaps_reference.html

#adding label(為等高線上注明等高線的含義)
plt.clabel(C, inline = True, fontsize = 10)

plt.xticks(())
plt.yticks(())

plt.show()

 

import matplotlib.pyplot as plt
import numpy as np

# image data
a = np.array([0.313660827978, 0.365348418405, 0.423733120134,
              0.365348418405, 0.439599930621, 0.525083754405,
              0.423733120134, 0.525083754405, 0.651536351379]).reshape(3,3)

#reshape（）是數組對象中的方法，用於改變數組的形狀。具體用法參考博文：https://blog.csdn.net/qq_28618765/article/details/78083895

#plt.imshow()參數設置參考 https://matplotlib.org/api/_as_gen/matplotlib.pyplot.imshow.html
plt.imshow(a, interpolation='nearest', cmap='cool', origin='upper')
#參數interpolation為邊界的模糊度或者圖片的模糊度，參考博文 https://blog.csdn.net/qq_41634283/article/details/84933753
#參數origin： {'upper', 'lower'}, optional
    # 將數組的[0,0]索引放置在軸的左上角或左下角。約定“上”通常用於矩陣和圖像。如果未給出，則使用rcparams[“image.origin”]，默認為“upper”。

plt.colorbar(shrink=.92)
#給figure添加顏色條或者漸變條，參考博文 https://www.jianshu.com/p/d97c1d2e274f
#colorbar()參數設置參考https://matplotlib.org/api/_as_gen/matplotlib.pyplot.colorbar.html

plt.xticks(())
plt.yticks(())

plt.show()

 

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D        #導入繪制3D數據的模塊

fig = plt.figure()
ax = Axes3D(fig)
# X, Y value
X = np.arange(-4, 4, 0.25)
Y = np.arange(-4, 4, 0.25)
X, Y = np.meshgrid(X, Y)  #np.meshgrid(x,y)把x,y值轉換成網格數據
# height value
Z = np.sin(np.sqrt(X ** 2 + Y ** 2))

ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=plt.get_cmap('rainbow'), edgecolor = "black")
#plot_surfac()參數設置參考 https://matplotlib.org/mpl_toolkits/mplot3d/tutorial.html
# *X*, *Y*, *Z*:Data values as 2D arrays
# *rstride* :Array row stride (step size), defaults to 10
# *cstride*:Array column stride (step size), defaults to 10
#  *cmap*:A colormap for the surface patches.
ax.contourf(X, Y, Z, zdir = "z", offset = -2, cmap = "rainbow" )

ax.set_zlim(-2, 2)

plt.show()