多维插值interp2d
interp2d
class scipy.interpolate.interp2d(x, y, z,
kind='linear',
copy=True,
bounds_error=False,
fill_value=None
)
参数：
x, y, z :
array_like
If the points lie on a regular grid, x can specify the column coordinates and y the row coordinates, for example:
>>> x = [0,1,2]; y = [0,3]; z = [[1,2,3], [4,5,6]]
If x and y are multi-dimensional, they are flattened before use.
kind：
{‘linear’, ‘cubic’, ‘quintic’}, optional
# 生成数据
import numpy as np
def func(x,y):
return (x+y)*np.exp(-5*(x**2+y**2))
x,y=np.mgrid[-1:1:8j,-1:1:8j]
z=func(x,y)
# 插值
from scipy import interpolate
func=interpolate.interp2d(x,y,z,kind='cubic')
xnew=np.linspace(-1,1,100)
ynew=np.linspace(-1,1,100)
znew=func(xnew,ynew)#xnew, ynew是一维的，输出znew是二维的
xnew,ynew=np.mgrid[-1:1:100j,-1:1:100j]#统一变成二维，便于下一步画图
# 画图
import mpl_toolkits.mplot3d
import matplotlib.pyplot as plt
ax=plt.subplot(111,projection='3d')
ax.plot_surface(xnew,ynew,znew)
ax.scatter(x,y,z,c='r',marker='^')
plt.show()
二维插值 Rbf
二维径向基函数插值
# 随机生成点，并计算函数值
import numpy as np
def func(x,y):
return (x+y)*np.exp(-5*(x**2+y**2))
x=np.random.uniform(low=-1,high=1,size=100)
y=np.random.uniform(low=-1,high=1,size=100)
z=func(x,y)
# 插值
from scipy import interpolate
func=interpolate.Rbf(x,y,z,function='multiquadric')
xnew,ynew=np.mgrid[-1:1:100j,-1:1:100j]
znew=func(xnew,ynew)#输入输出都是二维
# 画图
import mpl_toolkits.mplot3d
import matplotlib.pyplot as plt
ax=plt.subplot(111,projection='3d')
ax.plot_surface(xnew,ynew,znew)
ax.scatter(x,y,z,c='r',marker='^')
plt.show()
