Python Matplotlib 将 numpy 矩阵绘制为 0 索引
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Matplotlib plot numpy matrix as 0 index
提问by GarethPrice
I prepare a numpy matrix then use matplotlib to plot the matrix, such as:
我准备了一个 numpy 矩阵，然后使用 matplotlib 绘制矩阵，例如：
>>> import numpy
>>> import matplotlib.pylab as plt
>>> m = [[0.0, 1.47, 2.43, 3.44, 1.08, 2.83, 1.08, 2.13, 2.11, 3.7], [1.47, 0.0, 1.5, 2.39, 2.11, 2.4, 2.11, 1.1, 1.1, 3.21], [2.43, 1.5, 0.0, 1.22, 2.69, 1.33, 3.39, 2.15, 2.12, 1.87], [3.44, 2.39, 1.22, 0.0, 3.45, 2.22, 4.34, 2.54, 3.04, 2.28], [1.08, 2.11, 2.69, 3.45, 0.0, 3.13, 1.76, 2.46, 3.02, 3.85], [2.83, 2.4, 1.33, 2.22, 3.13, 0.0, 3.83, 3.32, 2.73, 0.95], [1.08, 2.11, 3.39, 4.34, 1.76, 3.83, 0.0, 2.47, 2.44, 4.74], [2.13, 1.1, 2.15, 2.54, 2.46, 3.32, 2.47, 0.0, 1.78, 4.01], [2.11, 1.1, 2.12, 3.04, 3.02, 2.73, 2.44, 1.78, 0.0, 3.57], [3.7, 3.21, 1.87, 2.28, 3.85, 0.95, 4.74, 4.01, 3.57, 0.0]]
>>> matrix = numpy.matrix(m)
>>> matrix
matrix([
[ 0. , 1.47, 2.43, 3.44, 1.08, 2.83, 1.08, 2.13, 2.11, 3.7 ],
[ 1.47, 0. , 1.5 , 2.39, 2.11, 2.4 , 2.11, 1.1 , 1.1 , 3.21],
[ 2.43, 1.5 , 0. , 1.22, 2.69, 1.33, 3.39, 2.15, 2.12, 1.87],
[ 3.44, 2.39, 1.22, 0. , 3.45, 2.22, 4.34, 2.54, 3.04, 2.28],
[ 1.08, 2.11, 2.69, 3.45, 0. , 3.13, 1.76, 2.46, 3.02, 3.85],
[ 2.83, 2.4 , 1.33, 2.22, 3.13, 0. , 3.83, 3.32, 2.73, 0.95],
[ 1.08, 2.11, 3.39, 4.34, 1.76, 3.83, 0. , 2.47, 2.44, 4.74],
[ 2.13, 1.1 , 2.15, 2.54, 2.46, 3.32, 2.47, 0. , 1.78, 4.01],
[ 2.11, 1.1 , 2.12, 3.04, 3.02, 2.73, 2.44, 1.78, 0. , 3.57],
[ 3.7 , 3.21, 1.87, 2.28, 3.85, 0.95, 4.74, 4.01, 3.57, 0. ]
])
>>> fig = plt.figure()
>>> ax = fig.add_subplot(1,1,1)
>>> ax.set_aspect('equal')
>>> plt.imshow(matrix, interpolation='nearest', cmap=plt.cm.ocean)
>>> plt.colorbar()
>>> plt.show()
The plot shows like this:
情节显示如下：
This is fine, except for the fact that I would like my axes to go from 1-10, rather than 0-9 (derived from python's 0 indexing)
这很好，除了我希望我的轴从 1-10 而不是 0-9（派生自 python 的 0 索引）
Is there a simple way to do this?
有没有一种简单的方法可以做到这一点？
Many thanks!!
非常感谢！！
采纳答案by Dan
You can use the extentoptional parameter to the plt.imshow()function, which is documented here. Like this:
您可以使用该函数的extent可选参数plt.imshow()，此处记录了该参数。像这样：
#All the stuff earlier in the program
plt.imshow(matrix, interpolation='nearest', cmap=plt.cm.ocean, extent=(0.5,10.5,0.5,10.5))
plt.colorbar()
plt.show()
For a matrix with an arbitrary shape, you could change this code to something like this:
对于具有任意形状的矩阵，您可以将此代码更改为如下所示：
#All the stuff earlier in the program
plt.imshow(matrix, interpolation='nearest', cmap=plt.cm.ocean,
extent=(0.5,numpy.shape(matrix)[0]+0.5,0.5,numpy.shape(matrix)[1]+0.5))
plt.colorbar()
plt.show()
This produces a plot that looks like this:
这会产生一个如下所示的图：
回答by Christian
To get the desired output add these lines after your code, but beforeplt.show():
要获得所需的输出，请在代码之后但之前添加这些行plt.show()：
...
labels = [0, 1, 3, 5, 7, 9]
ax.set_xticklabels(labels)
plt.show()
Note that x-axis and y-axis are in the range [-0.5, 9.5]not int [0, 9]
请注意，x 轴和 y 轴[-0.5, 9.5]不在 int的范围内[0, 9]
Edit:
编辑：
To do it in a more flexible way (in fact, another way of the showed above):
要以更灵活的方式进行（实际上是上面显示的另一种方式）：
labels = range(0, len(m[0]))
plt.xticks(labels)
plt.show()
Output:
输出：
