在 Python 中使用複數點陣列生成切比雪夫多項式的範德蒙矩陣


要生成切比雪夫多項式的範德蒙矩陣,請在 Python Numpy 中使用 chebyshev.chebvander()。該方法返回範德蒙矩陣。返回矩陣的形狀為 x.shape + (deg + 1,),其中最後一個索引是相應切比雪夫多項式的次數。dtype 將與轉換後的 x 相同。

引數 a 是點陣列。dtype 會根據是否有任何元素為複數而轉換為 float64 或 complex128。如果 x 是標量,則將其轉換為一維陣列。引數 deg 是結果矩陣的次數。

步驟

首先,匯入所需的庫 -

import numpy as np
from numpy.polynomial import chebyshev as C

建立陣列 -

x = np.array([-2.+2.j, -1.+2.j, 0.+2.j, 1.+2.j, 2.+2.j])

顯示陣列 -

print("Our Array...\n",x)

檢查維度 -

print("\nDimensions of our Array...\n",x.ndim)

獲取資料型別 -

print("\nDatatype of our Array object...\n",x.dtype)

獲取形狀 -

print("\nShape of our Array object...\n",x.shape)

要生成切比雪夫多項式的範德蒙矩陣,請使用 chebyshev.chebvander() -

print("\nResult...\n",C.chebvander(x, 2))

示例

import numpy as np
from numpy.polynomial import chebyshev as C

# Create an array
x = np.array([-2.+2.j, -1.+2.j, 0.+2.j, 1.+2.j, 2.+2.j])

# Display the array
print("Our Array...\n",x)

# Check the Dimensions
print("\nDimensions of our Array...\n",x.ndim)

# Get the Datatype
print("\nDatatype of our Array object...\n",x.dtype)

# Get the Shape
print("\nShape of our Array object...\n",x.shape)

# To generate a Vandermonde matrix of the Chebyshev polynomial, use the chebyshev.chebvander() in Python Numpy
# The method returns the Vandermonde matrix. The shape of the returned matrix is x.shape + (deg + 1,), where The last index is the degree of the corresponding Chebyshev polynomial. The dtype will be the same as the converted x.
# The parameter, a is Array of points. The dtype is converted to float64 or complex128 depending on whether any of the elements are complex. If x is scalar it is converted to a 1-D array.
# The parameter, deg is the degree of the resulting matrix
print("\nResult...\n",C.chebvander(x, 2))

輸出

Our Array...
[-2.+2.j -1.+2.j 0.+2.j 1.+2.j 2.+2.j]

Dimensions of our Array...
1

Datatype of our Array object...
complex128

Shape of our Array object...
(5,)

Result...
[[ 1. +0.j -2. +2.j -1.-16.j]
[ 1. +0.j -1. +2.j -7. -8.j]
[ 1. +0.j 0. +2.j -9. +0.j]
[ 1. +0.j 1. +2.j -7. +8.j]
[ 1. +0.j 2. +2.j -1.+16.j]]

更新於: 2022年2月28日

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