我有分散的数据,我正在将其插入到网格数据中。然后我用contourf函数绘制所有东西。最后,我只想在定义的圆圈内绘制所有内容。其他一切都应该是白色的,但我不知道如何实现这一点。有一种简单的方法可以做到这一点吗?
这是我的代码:
import numpy as np
import matplotlib.pyplot as plt
from scipy.interpolate import griddata
def func(x, y):
return x*(1-x)*np.cos(4*np.pi*x) * np.sin(4*np.pi*y**2)**2
grid_x, grid_y = np.mgrid[0:1:100j, 0:1:200j]
points = np.random.rand(1000, 2)
values = func(points[:,0], points[:,1])
grid_z0 = griddata(points, values, (grid_x, grid_y), method='nearest')
plt.contourf(grid_x,grid_y,grid_z0)
plt.savefig("plot_data_in_circle.png")
这就是它应该是这样的:
答案 0 :(得分:2)
这可以通过创建Circle
补丁,然后将其设置为clip_path
来完成。
要使用clip_path
,通常会存储要应用裁剪的艺术家,然后使用.set_clip_path
。在这种情况下,由于您使用的是contourf
,因此没有方法.set_clip_path
,因此我们必须迭代与contourf
返回的PathCollections
一起存储的QuadContourSet
},并使用set_clip_path
method设置每个剪辑路径。
import numpy as np
import matplotlib.pyplot as plt
from scipy.interpolate import griddata
import matplotlib.patches as patches
def func(x, y):
return x*(1-x)*np.cos(4*np.pi*x) * np.sin(4*np.pi*y**2)**2
grid_x, grid_y = np.mgrid[0:1:100j, 0:1:200j]
points = np.random.rand(1000, 2)
values = func(points[:,0], points[:,1])
grid_z0 = griddata(points, values, (grid_x, grid_y), method='nearest')
fig, ax = plt.subplots()
cs = ax.contourf(grid_x,grid_y,grid_z0)
circ = patches.Circle((0.6, 0.4), 0.3, transform=ax.transData)
for coll in cs.collections:
coll.set_clip_path(circ)
plt.show()