Source code for plugins.polynomial

#
##
##  This file is part of pyFormex 1.0.7  (Mon Jun 17 12:20:39 CEST 2019)
##  pyFormex is a tool for generating, manipulating and transforming 3D
##  geometrical models by sequences of mathematical operations.
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##  Copyright 2004-2019 (C) Benedict Verhegghe (benedict.verhegghe@ugent.be)
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#

"""Polynomials

This module defines the class Polynomial, representing a polynomial
in n variables.
"""

from __future__ import absolute_import, division, print_function
from pyformex import zip

import numpy as np
from pyformex import arraytools as at


[docs]class Polynomial(object): """A polynomial in ndim dimensions. Parameters: - `exp`: (nterms,ndim) int array with the exponents of each of the ndim variables in the nterms terms of the polynomial. - `coeff`: (nterms,) float array with the coefficients of the terms. If not specified, all coefficients are set to 1. Example: >>> p = Polynomial([(0,0),(1,0),(1,1),(0,2)],(2,3,-1,-1)) >>> print(p.atoms()) ['1', 'x', 'x*y', 'y**2'] >>> print(p.human()) 2.0 + 3.0*x -1.0*x*y -1.0*y**2 >>> print(p.evalAtoms([[1,2],[3,0],[2,1]])) [[ 1. 1. 2. 4.] [ 1. 3. 0. 0.] [ 1. 2. 2. 1.]] >>> print(p.eval([[1,2],[3,0],[2,1]])) [ -1. 11. 5.] """ def __init__(self, exp, coeff=None): """Create an n-d polynomial""" self.exp = at.checkArray(exp, kind='i', ndim=2) if coeff is None: self.coeff = np.ones(self.nterms) else: self.coeff = at.checkArray(coeff, (self.nterms,), 'f', 'i') @property def nterms(self): return self.exp.shape[0] @property def ndim(self): return self.exp.shape[1]
[docs] def degrees(self): """Return the degree of the polynomial in each of the dimensions. The degree is the maximal exponent for each of the dimensions. """ return self.exp.max(axis=0)
[docs] def degree(self): """Return the total degree of the polynomial. The degree is the sum of the degrees for all dimensions. """ return self.degrees().sum()
[docs] def evalAtoms1(self, x): """Evaluate the monomials at the given points x is an (npoints,ndim) array of points where the polynomial is to be evaluated. The result is an (npoints,nterms) array of values. """ x = at.checkArray(x, (-1, self.ndim), 'f', 'i') maxd = self.degrees() mon = [at.powers(x[:, j], maxd[j]) for j in range(self.ndim)] terms = [[mon[j][e[j]] for j in range(self.ndim)] for e in self.exp] terms = np.dstack([np.column_stack([mon[j][e[j]] for j in range(self.ndim)]) for e in self.exp]) return terms.prod(axis=1)
#### ALTERNATIVE evalAtoms # This implementation first computes the monomial strings and # then evals the strins. It is currrently faster than evalAtoms.
[docs] def evalAtoms(self, x): """Evaluate the monomials at the given points x is an (npoints,ndim) array of points where the polynomial is to be evaluated. The result is an (npoints,nterms) array of values. """ x = at.checkArray(x, (-1, self.ndim), 'f', 'i') symbol = 'xyz' g = dict([(symbol[i], x[:, i]) for i in range(self.ndim)]) atoms = self.atoms(symbol) aa = np.zeros((len(x), len(atoms)), at.Float) for k, a in enumerate(atoms): aa[:, k] = eval(a, g) return aa
[docs] def eval(self, x): """Evaluate the polynomial at the given points x is an (npoints,ndim) array of points where the polynomial is to be evaluated. The result is an (npoints,) array of values. """ terms = self.evalAtoms(x) return (self.coeff*terms).sum(axis=-1)
[docs] def atoms(self, symbol='xyz'): """Return a human representation of the monomials""" return [monomial(e, symbol) for e in self.exp]
[docs] def human(self, symbol='xyz'): """Return a human representation""" mon = self.atoms(symbol) mon = [str(c)+'*'+m if c != 1 else m for c, m in zip(self.coeff, mon)] return ' + '.join(mon).replace('*1', '').replace('+ -', '-')
[docs]def polynomial(atoms, x, y=0, z=0): """Build a matrix of functions of coords. - `atoms`: a list of text strings representing a mathematical function of `x`, and possibly of `y` and `z`. - `x`, `y`, `z`: a list of x- (and optionally y-, z-) values at which the `atoms` will be evaluated. The lists should have the same length. Returns a matrix with `nvalues` rows and `natoms` colums. """ aa = np.zeros((len(x), len(atoms)), Float) for k, a in enumerate(atoms): aa[:, k] = eval(a) return aa
[docs]def monomial(exp, symbol='xyz'): """Compute the monomials for the given exponents - `exp`: a tuple of integer exponents - `symbol`: a string of at least the same length as `exp` Returns a string representation of a monomial created by raising the symbols to the corresponding exponent. Example: >>> monomial((2,1)) 'x**2*y' """ factor = lambda sym, exp: '1' if exp == 0 else sym if exp == 1 else sym+'**'+str(exp) factors = [factor(symbol[i], j) for i, j in enumerate(exp)] # Join and sanitize (note we do not have '**1') return '*'.join(factors).replace('1*', '').replace('*1', '')
# End