Hermite 다항식과 x, y, z 샘플 포인트의 의사 Vandermonde 행렬을 생성하려면 Python Numpy에서 hermite.hermvander3d()를 사용합니다. 이 메서드는 의사 Vandermondematrix를 반환합니다. 매개변수 x, y, z는 모두 같은 모양의 점 좌표 배열입니다. dtypes는 요소가 복잡한지 여부에 따라 float64 또는 complex128로 변환됩니다. 스칼라는 1차원 배열로 변환됩니다. 매개변수 deg는 [x_deg, y_deg, z_deg] 형식의 최대 각도 목록입니다.
단계
먼저 필요한 라이브러리를 가져옵니다 -
import numpy as np from numpy.polynomial import hermite as H
numpy.array() 메서드를 사용하여 동일한 모양의 점 좌표 배열을 만듭니다. -
x = np.array([1, 2]) y = np.array([3, 4]) z = np.array([5, 6])
배열 표시 -
print("Array1...\n",x) print("\nArray2...\n",y) print("\nArray3...\n",z)
데이터 유형 표시 -
print("\nArray1 datatype...\n",x.dtype) print("\nArray2 datatype...\n",y.dtype) print("\nArray3 datatype...\n",z.dtype)
두 어레이의 차원을 확인하십시오 -
print("\nDimensions of Array1...\n",x.ndim) print("\nDimensions of Array2...\n",y.ndim) print("\nDimensions of Array3...\n",z.ndim)
두 배열의 모양을 확인하십시오 -
print("\nShape of Array1...\n",x.shape) print("\nShape of Array2...\n",y.shape) print("\nShape of Array3...\n",z.shape)
# Hermite 다항식과 x, y, z 샘플 포인트의 의사 Vandermonde 행렬을 생성하려면 hermite.hermvander3d() -
x_deg, y_deg, z_deg = 2, 3, 4 print("\nResult...\n",H.hermvander3d(x,y,z, [x_deg, y_deg, z_deg]))
예시
import numpy as np from numpy.polynomial import hermite as H # Create arrays of point coordinates, all of the same shape using the numpy.array() method x = np.array([1, 2]) y = np.array([3, 4]) z = np.array([5, 6]) # Display the arrays print("Array1...\n",x) print("\nArray2...\n",y) print("\nArray3...\n",z) # Display the datatype print("\nArray1 datatype...\n",x.dtype) print("\nArray2 datatype...\n",y.dtype) print("\nArray3 datatype...\n",z.dtype) # Check the Dimensions of both the arrays print("\nDimensions of Array1...\n",x.ndim) print("\nDimensions of Array2...\n",y.ndim) print("\nDimensions of Array3...\n",z.ndim) # Check the Shape of both the arrays print("\nShape of Array1...\n",x.shape) print("\nShape of Array2...\n",y.shape) print("\nShape of Array3...\n",z.shape) # To generate a pseudo Vandermonde matrix of the Hermite polynomial and x, y, z sample points, use the hermite.hermvander3d() in Python Numpy # The method returns the pseudo-Vandermonde matrix. x_deg, y_deg, z_deg = 2, 3, 4 print("\nResult...\n",H.hermvander3d(x,y,z, [x_deg, y_deg, z_deg]))
출력
Array1... [1 2] Array2... [3 4] Array3... [5 6] Array1 datatype... int64 Array2 datatype... int64 Array3 datatype... int64 Dimensions of Array1... 1 Dimensions of Array2... 1 Dimensions of Array3... 1 Shape of Array1... (2,) Shape of Array2... (2,) Shape of Array3... (2,) Result... [[1.0000000e+00 1.0000000e+01 9.8000000e+01 9.4000000e+02 8.8120000e+03 6.0000000e+00 6.0000000e+01 5.8800000e+02 5.6400000e+03 5.2872000e+04 3.4000000e+01 3.4000000e+02 3.3320000e+03 3.1960000e+04 2.9960800e+05 1.8000000e+02 1.8000000e+03 1.7640000e+04 1.6920000e+05 1.5861600e+06 2.0000000e+00 2.0000000e+01 1.9600000e+02 1.8800000e+03 1.7624000e+04 1.2000000e+01 1.2000000e+02 1.1760000e+03 1.1280000e+04 1.0574400e+05 6.8000000e+01 6.8000000e+02 6.6640000e+03 6.3920000e+04 5.9921600e+05 3.6000000e+02 3.6000000e+03 3.5280000e+04 3.3840000e+05 3.1723200e+06 2.0000000e+00 2.0000000e+01 1.9600000e+02 1.8800000e+03 1.7624000e+04 1.2000000e+01 1.2000000e+02 1.1760000e+03 1.1280000e+04 1.0574400e+05 6.8000000e+01 6.8000000e+02 6.6640000e+03 6.3920000e+04 5.9921600e+05 3.6000000e+02 3.6000000e+03 3.5280000e+04 3.3840000e+05 3.1723200e+06] [1.0000000e+00 1.2000000e+01 1.4200000e+02 1.6560000e+03 1.9020000e+04 8.0000000e+00 9.6000000e+01 1.1360000e+03 1.3248000e+04 1.5216000e+05 6.2000000e+01 7.4400000e+02 8.8040000e+03 1.0267200e+05 1.1792400e+06 4.6400000e+02 5.5680000e+03 6.5888000e+04 7.6838400e+05 8.8252800e+06 4.0000000e+00 4.8000000e+01 5.6800000e+02 6.6240000e+03 7.6080000e+04 3.2000000e+01 3.8400000e+02 4.5440000e+03 5.2992000e+04 6.0864000e+05 2.4800000e+02 2.9760000e+03 3.5216000e+04 4.1068800e+05 4.7169600e+06 1.8560000e+03 2.2272000e+04 2.6355200e+05 3.0735360e+06 3.5301120e+07 1.4000000e+01 1.6800000e+02 1.9880000e+03 2.3184000e+04 2.6628000e+05 1.1200000e+02 1.3440000e+03 1.5904000e+04 1.8547200e+05 2.1302400e+06 8.6800000e+02 1.0416000e+04 1.2325600e+05 1.4374080e+06 1.6509360e+07 6.4960000e+03 7.7952000e+04 9.2243200e+05 1.0757376e+07 1.2355392e+08]]