A one-dimensional polynomial class.
A convenience class, used to encapsulate “natural” operations on polynomials so that said operations may take on their customary form in code (see Examples).
Parameters : | c_or_r : array_like
r : bool, optional
variable : str, optional
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Examples
Construct the polynomial :
>>> p = np.poly1d([1, 2, 3])
>>> print np.poly1d(p)
2
1 x + 2 x + 3
Evaluate the polynomial at :
>>> p(0.5)
4.25
Find the roots:
>>> p.r
array([-1.+1.41421356j, -1.-1.41421356j])
>>> p(p.r)
array([ -4.44089210e-16+0.j, -4.44089210e-16+0.j])
These numbers in the previous line represent (0, 0) to machine precision
Show the coefficients:
>>> p.c
array([1, 2, 3])
Display the order (the leading zero-coefficients are removed):
>>> p.order
2
Show the coefficient of the k-th power in the polynomial (which is equivalent to p.c[-(i+1)]):
>>> p[1]
2
Polynomials can be added, subtracted, multiplied, and divided (returns quotient and remainder):
>>> p * p
poly1d([ 1, 4, 10, 12, 9])
>>> (p**3 + 4) / p
(poly1d([ 1., 4., 10., 12., 9.]), poly1d([ 4.]))
asarray(p) gives the coefficient array, so polynomials can be used in all functions that accept arrays:
>>> p**2 # square of polynomial
poly1d([ 1, 4, 10, 12, 9])
>>> np.square(p) # square of individual coefficients
array([1, 4, 9])
The variable used in the string representation of p can be modified, using the variable parameter:
>>> p = np.poly1d([1,2,3], variable='z')
>>> print p
2
1 z + 2 z + 3
Construct a polynomial from its roots:
>>> np.poly1d([1, 2], True)
poly1d([ 1, -3, 2])
This is the same polynomial as obtained by:
>>> np.poly1d([1, -1]) * np.poly1d([1, -2])
poly1d([ 1, -3, 2])
Attributes
coeffs | |
order | |
variable |
Methods
__call__(val) | |
deriv([m]) | Return a derivative of this polynomial. |
integ([m, k]) | Return an antiderivative (indefinite integral) of this polynomial. |