Question

基本上，我想制作类似下面的内容（三角形不是正方形，通常与plt.matshow一起使用）。

可以从四个2D数组开始，每个数组代表一组三角形颜色的值：right，left，bottom，top：

import numpy as np
right=np.random.randn(8, 8)
left=np.random.randn(8, 8)
bottom=np.random.randn(8, 8)
top=np.random.randn(8, 8)

但我不知道密谋......

Answer 1

您可能确实使用tripcolor绘制了一组三角形。在下面的代码中，函数quatromatrix将4个2D数组值作为输入进行色彩映射，创建三角形并重新排列颜色以适合各自的位置。因此，它非常类似于绘制4个imshow图。

import matplotlib.pyplot as plt
import numpy as np

def quatromatrix(left, bottom, right, top, ax=None, triplotkw={},tripcolorkw={}):
    if not ax: ax=plt.gca()
    n = left.shape[0]; m=left.shape[1]

    a = np.array([[0,0],[0,1],[.5,.5],[1,0],[1,1]])
    tr = np.array([[0,1,2], [0,2,3],[2,3,4],[1,2,4]])

    A = np.zeros((n*m*5,2))
    Tr = np.zeros((n*m*4,3))

    for i in range(n):
        for j in range(m):
            k = i*m+j
            A[k*5:(k+1)*5,:] = np.c_[a[:,0]+j, a[:,1]+i]
            Tr[k*4:(k+1)*4,:] = tr + k*5

    C = np.c_[ left.flatten(), bottom.flatten(), 
              right.flatten(), top.flatten()   ].flatten()

    triplot = ax.triplot(A[:,0], A[:,1], Tr, **triplotkw)
    tripcolor = ax.tripcolor(A[:,0], A[:,1], Tr, facecolors=C, **tripcolorkw)
    return tripcolor


right=np.random.randn(8, 8)
left=np.random.randn(8, 8)
bottom=np.random.randn(8, 8)
top=np.random.randn(8, 8)

fig, ax=plt.subplots()

quatromatrix(left, bottom, right, top, ax=ax,
             triplotkw={"color":"k", "lw":1},
             tripcolorkw={"cmap": "plasma"}) 

ax.margins(0)
ax.set_aspect("equal")

Answer 2

请参阅matplotlib文档here中的示例matplotlib.pyplot.tripcolor(*args, **kwargs)。以下是您需要的简化版本：

import matplotlib.pyplot as plt
import numpy as np

xy = np.asarray([
    [-0.01, 0.872], [-0.080, 0.883], [-0.069, 0.888], [-0.054, 0.890]])

x = xy[:, 0]*180/3.14159
y = xy[:, 1]*180/3.14159

triangles = np.asarray([[3, 2,  0]  , [3,  1, 2],   [ 0, 2,  1] , 
                        [0,  1, 2]])

xmid = x[triangles].mean(axis=1)
ymid = y[triangles].mean(axis=1)
x0 = -5
y0 = 52
zfaces = np.exp(-0.01*((xmid - x0)*(xmid - x0) + 
                (ymid - y0)*(ymid - y0)))


plt.figure()
plt.gca().set_aspect('equal')
plt.tripcolor(x, y, triangles, facecolors=zfaces, edgecolors='k')
plt.colorbar()
plt.title('tripcolor of user-specified triangulation')
plt.xlabel('Longitude (degrees)')
plt.ylabel('Latitude (degrees)')

plt.show()

你应该得到以下图片：

Answer 3

我使用ImportanceOfBeingErnest的代码绘制了一个强化学习项目的Q表-我想了解它，所以我仔细阅读了它并使其更加清晰。只需用您自己的数据（上，下，左，右）替换即可。

def showQVals(self):
    fig, ax = plt.subplots()

    rows = self.level.NUM_ROWS
    cols = self.level.NUM_COLUMNS

    up = self.q[:,Action.UP].reshape(rows, cols)
    down = self.q[:,Action.DOWN].reshape(rows, cols)
    right = self.q[:,Action.RIGHT].reshape(rows, cols)
    left = self.q[:,Action.LEFT].reshape(rows, cols)

    vertDims = np.array([[0,0],[0,1],[.5,.5],[1,0],[1,1]])
    UP = [1,2,4]
    DOWN = [0,2,3]
    RIGHT = [2,3,4]
    LEFT = [0,1,2]
    triDims = np.array([DOWN, UP, RIGHT, LEFT])

    verts = np.zeros((rows*cols*5,2))
    tris = np.zeros((rows*cols*4,3))

    for row in range(rows): #i
        for col in range(cols): #j
            cell = row*cols+col

            #assign slices to the newly constructed verts and tris
            verts[cell*5:(cell+1)*5,:] = np.c_[vertDims[:,0]+col, vertDims[:,1]+row]
            tris[cell*4:(cell+1)*4,:] = triDims + cell*5

    C = np.c_[ up.flatten(), down.flatten(), 
            right.flatten(), left.flatten()   ].flatten()

    ax.invert_yaxis()
    ax.set_title('Q Values')

    triplot = ax.triplot(verts[:,0], verts[:,1], tris)
    tripcolor = ax.tripcolor(verts[:,0], verts[:,1], tris, facecolors=C)

    fig.colorbar(tripcolor)
    plt.show()

q table figure based off of grid map

类似于plt.matshow，但有三角形

3 个答案: