Python中的 numpy.poly1d()
numpy.poly1d()函数有助于定义多项式函数。它使得在多项式上应用“自然运算”变得容易。
Syntax: numpy.poly1d(arr, root, var)
Parameters :
arr : [array_like] The polynomial coefficients are given in decreasing order of powers. If the second parameter (root) is set to True then array values are the roots of the polynomial equation.
root : [bool, optional] True means polynomial roots. Default is False.
var : variable like x, y, z that we need in polynomial [default is x].
Arguments :
c : Polynomial coefficient.
coef : Polynomial coefficient.
coefficients : Polynomial coefficient.
order : Order or degree of polynomial.
o : Order or degree of polynomial.
r : Polynomial root.
roots : Polynomial root.
Return: Polynomial and the operation applied
For example: poly1d(3, 2, 6) = 3x2 + 2x + 6
poly1d([1, 2, 3], True) = (x-1)(x-2)(x-3) = x3 – 6x2 + 11x -6
代码 1:解释 poly1d() 及其参数
# Python code explaining
# numpy.poly1d()
# importing libraries
import numpy as np
# Constructing polynomial
p1 = np.poly1d([1, 2])
p2 = np.poly1d([4, 9, 5, 4])
print ("P1 : ", p1)
print ("\n p2 : \n", p2)
# Solve for x = 2
print ("\n\np1 at x = 2 : ", p1(2))
print ("p2 at x = 2 : ", p2(2))
# Finding Roots
print ("\n\nRoots of P1 : ", p1.r)
print ("Roots of P2 : ", p2.r)
# Finding Coefficients
print ("\n\nCoefficients of P1 : ", p1.c)
print ("Coefficients of P2 : ", p2.coeffs)
# Finding Order
print ("\n\nOrder / Degree of P1 : ", p1.o)
print ("Order / Degree of P2 : ", p2.order)
输出 :
P1 :
1 x + 2
p2 :
3 2
4 x + 9 x + 5 x + 4
p1 at x = 2 : 4
p2 at x = 2 : 82
Roots of P1 : [-2.]
Roots of P2 : [-1.86738371+0.j -0.19130814+0.70633545j -0.19130814-0.70633545j]
Coefficients of P1 : [1 2]
Coefficients of P2 : [4 9 5 4]
Order / Degree of P1 : 1
Order / Degree of P2 : 3
代码 2:多项式的基本数学运算
# Python code explaining
# numpy.poly1d()
# importing libraries
import numpy as np
# Constructing polynomial
p1 = np.poly1d([1, 2])
p2 = np.poly1d([4, 9, 5, 4])
print ("P1 : ", p1)
print ("\n p2 : \n", p2)
print ("\n\np1 ^ 2 : \n", p1**2)
print ("p2 ^ 2 : \n", np.square(p2))
p3 = np.poly1d([1, 2], variable = 'y')
print ("\n\np3 : ", p3)
print ("\n\np1 * p2 : \n", p1 * p2)
print ("\nMultiplying two polynimials : \n",
np.poly1d([1, -1]) * np.poly1d([1, -2]))
输出 :
P1 :
1 x + 2
p2 :
3 2
4 x + 9 x + 5 x + 4
p1 ^ 2 :
2
1 x + 4 x + 4
p2 ^ 2 :
[16 81 25 16]
p3 :
1 y + 2
p1 * p2 :
4 3 2
4 x + 17 x + 23 x + 14 x + 8
Multiplying two polynimials :
2
1 x - 3 x + 2