# 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.
##  Project page:  http://savannah.nongnu.org/projects/pyformex/
##  Copyright 2004-2019 (C) Benedict Verhegghe (benedict.verhegghe@ugent.be)
##
##  This program is free software: you can redistribute it and/or modify
##  the Free Software Foundation, either version 3 of the License, or
##  (at your option) any later version.
##
##  This program is distributed in the hope that it will be useful,
##  but WITHOUT ANY WARRANTY; without even the implied warranty of
##  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
##  GNU General Public License for more details.
##
##  You should have received a copy of the GNU General Public License
##  along with this program.  If not, see http://www.gnu.org/licenses/.
##
#

"""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
```