polyval(p, x)
This forms part of the old polynomial API. Since version 1.4, the new polynomial API defined in :None:None:`numpy.polynomial` is preferred. A summary of the differences can be found in the :None:doc:`transition guide </reference/routines.polynomials>`.
If p is of length N, this function returns the value:
p[0]*x**(N-1) + p[1]*x**(N-2) + ... + p[N-2]*x + p[N-1]
If x is a sequence, then p(x)
is returned for each element of x
. If x is another polynomial then the composite polynomial p(x(t))
is returned.
Horner's scheme is used to evaluate the polynomial. Even so, for polynomials of high degree the values may be inaccurate due to rounding errors. Use carefully.
If x is a subtype of ndarray
the return value will be of the same type.
1D array of polynomial coefficients (including coefficients equal to zero) from highest degree to the constant term, or an instance of poly1d.
A number, an array of numbers, or an instance of poly1d, at which to evaluate p.
If x is a poly1d instance, the result is the composition of the two polynomials, i.e., x is "substituted" in p and the simplified result is returned. In addition, the type of x - array_like or poly1d - governs the type of the output: x array_like => :None:None:`values` array_like, x a poly1d object => :None:None:`values` is also.
Evaluate a polynomial at specific values.
poly1d
A polynomial class.
>>> np.polyval([3,0,1], 5) # 3 * 5**2 + 0 * 5**1 + 1 76
>>> np.polyval([3,0,1], np.poly1d(5)) poly1d([76])
>>> np.polyval(np.poly1d([3,0,1]), 5) 76
>>> np.polyval(np.poly1d([3,0,1]), np.poly1d(5)) poly1d([76])See :
The following pages refer to to this document either explicitly or contain code examples using this.
numpy.roots
numpy.polynomial.polynomial.polyfit
numpy.polynomial.polynomial.polygrid2d
numpy.ma.extras.polyfit
numpy.poly
numpy.polynomial.polynomial.polyvalfromroots
numpy.polyfit
numpy.polymul
numpy.polynomial.polynomial.polygrid3d
numpy.vectorize
numpy.polynomial.polynomial.polyval2d
numpy.polydiv
numpy.polyadd
numpy.polynomial.polynomial.polyval3d
numpy.polysub
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