英文:
Color plot from 3D arrays
问题
我有一个包含数组的NumPy数组，例如：
Y[:,0] 是表示x轴坐标的列表。对于这个轴上的每个点，由索引 indx 标记，存在以下情况：
Y[indx,1][0] 是y轴坐标的列表，而
Yindx,1 是z轴数据的列表。
我现在可以使用下面的代码绘制3D线条数组。但是，我想绘制一个2D图，其中z数据代表x和y坐标上的颜色映射（类似于小波变换图的输出）。
#虚拟数据
Y=[0]*10
for i in range(10):
temp=np.array([[indx,np.cos(indx)] for indx in range(50)])
Y[i]=np.array([i,temp.transpose()])
Y=np.array(Y,dtype=object)
#在3D中绘制
ax = plt.figure().add_subplot(projection='3d')
for indx in range(len(Y[:,0])):
ax.plot(Y[indx,1][0], Y[indx,1][1], zs=Y[:,0][indx], zdir='x')
这给我了一个3D图。我如何获得我描述的2D图？
英文:
I have a numpy array of arrays such as:
Y[:,0] is a list representing the x axis coordinates. For each point on this axis, marked by the index indx, there is
Y[indx,1][0] is a list of y axis coordinates, and
Yindx,1 is a list of of the z axis data
I can now use the code below to plot an array of lines in 3D. However, I would like to plot a 2D plot where the z data represents a color map on the x and y coordinates (something that looks like the output of a wavelet transform plot).
#dummy data
Y=[0]*10
for i in range(10):
temp=np.array([[indx,np.cos(indx)] for indx in range(50)])
Y[i]=np.array([i,temp.transpose()])
Y=np.array(Y,dtype=object)
#plotting in 3D
ax = plt.figure().add_subplot(projection='3d')
for indx in range(len(Y[:,0])):
ax.plot(Y[indx,1][0], Y[indx,1][1], zs=Y[:,0][indx], zdir='x')
This gives me the 3D plot. How can I get the 2D plot as I described?
答案1
得分: 2
y轴坐标对于每个x轴坐标是否相同，例如 Y[0,1][0] = Y[1,1][0]？此外，y轴坐标是否均匀间隔？下面的解决方案假设这两者为真。
解决方案
创建一个与每个 (x, y) 位置相关联的z值数组。然后调用 plt.imshow(...)，将新数组作为参数。甚至可以包括一个色标！
注意：使用虚拟数据时，颜色图谱并不令人印象深刻，但它确实适当显示了你要求的图。
代码
# 虚拟数据
Y=[0]*10
for i in range(10):
temp=np.array([[indx,np.cos(indx)] for indx in range(50)])
Y[i]=np.array([i,temp.transpose()],dtype=object)
Y=np.array(Y,dtype=object)
xVals = Y.T[0] # x轴坐标（未使用，但是是一个有用的信息）
yVals = Y.T[1][1][0].astype(int) # y轴坐标作为整数数组（也未使用）
# 创建zVals数组
zVals = np.concatenate(Y.T[1])[1::2]
# 在3D中绘制
fig = plt.figure()
ax3d = fig.add_subplot(211,projection='3d')
for indx in range(len(Y[:,0])):
ax3d.plot(Y[indx,1][0], Y[indx,1][1], zs=Y[:,0][indx], zdir='x')
# 在2D中绘制
ax = fig.add_subplot(212)
im = plt.imshow(zVals)
cb = plt.colorbar()
英文:
Are the y-coordinates going to be the same for every x-coordinate e.g. Y[0,1][0] = Y[1,1][0]? Also, will the y-coordinates be evenly spaced? The solution below assumes both of these to be true.
Solution
Create an array of z-values associated with each (x,y) location. Then call plt.imshow(...) using the new array as an argument. You can even include a colorbar!
Note: The colormap is nothing impressive when using the dummy data, but it appropriately shows the plot you asked for.
Code
#dummy data
Y=[0]*10
for i in range(10):
temp=np.array([[indx,np.cos(indx)] for indx in range(50)])
Y[i]=np.array([i,temp.transpose()],dtype=object)
Y=np.array(Y,dtype=object)
xVals = Y.T[0] # x axis coordinates (not used, but a useful piece of information)
yVals = Y.T[1][1][0].astype(int) # y axis coordinates as an integer array (also not used)
# create the array of zVals
zVals = np.concatenate(Y.T[1])[1::2]
#plotting in 3D
fig = plt.figure()
ax3d = fig.add_subplot(211,projection='3d')
for indx in range(len(Y[:,0])):
ax3d.plot(Y[indx,1][0], Y[indx,1][1], zs=Y[:,0][indx], zdir='x')
#plotting in 2D
ax = fig.add_subplot(212)
im = plt.imshow(zVals)
cb = plt.colorbar()
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