PyNeb  1.1.2 PyNeb Reference Manua
pyneb.utils.polyutils Namespace Reference

## Classes

class  PolyBase

class  PolyDomainError

class  PolyError

class  RankWarning

## Functions

def any (iterable)

def trimseq (seq)

def as_series

def trimcoef

def getdomain (x)

def mapparms (old, new)

def mapdomain (x, old, new)

list __all__

## Detailed Description

Utililty objects for the polynomial modules.

This module provides: error and warning objects; a polynomial base class;
and some routines used in both the polynomial and chebyshev modules.

Error objects
-------------
- PolyError -- base class for this sub-package's errors.
- PolyDomainError -- raised when domains are "mismatched."

Warning objects
---------------
- RankWarning -- raised by a least-squares fit when a rank-deficient
matrix is encountered.

Base class
----------
- PolyBase -- The base class for the Polynomial and Chebyshev
classes.

Functions
---------
- as_series -- turns a list of array_likes into 1-D arrays of common
type.
- trimseq -- removes trailing zeros.
- trimcoef -- removes trailing coefficients that are less than a given
magnitude (thereby removing the corresponding terms).
- getdomain -- returns a domain appropriate for a given set of abscissae.
- mapdomain -- maps points between domains.
- mapparms -- parameters of the linear map between domains.

## Function Documentation

 def pyneb.utils.polyutils.any ( iterable )
 def pyneb.utils.polyutils.as_series ( alist, trim = True )
Return argument as a list of 1-d arrays.

The returned list contains array(s) of dtype double, complex double, or
object.  A 1-d argument of shape (N,) is parsed into N arrays of
size one; a 2-d argument of shape (M,N) is parsed into M arrays
of size N (i.e., is "parsed by row"); and a higher dimensional array
raises a Value Error if it is not first reshaped into either a 1-d or 2-d
array.

Parameters
----------
a : array_like
A 1- or 2-d array_like
trim : boolean, optional
When True, trailing zeros are removed from the inputs.
When False, the inputs are passed through intact.

Returns
-------
[a1, a2,...] : list of 1d-arrays
A copy of the input data as a list of 1-d arrays.

Raises
------
ValueError :
Raised when as_series cannot convert its input to 1-d arrays, or at
least one of the resulting arrays is empty.

Examples
--------
>>> from numpy import polynomial as P
>>> a = np.arange(4)
>>> P.as_series(a)
[array([ 0.]), array([ 1.]), array([ 2.]), array([ 3.])]
>>> b = np.arange(6).reshape((2,3))
>>> P.as_series(b)
[array([ 0.,  1.,  2.]), array([ 3.,  4.,  5.])]
 def pyneb.utils.polyutils.getdomain ( x )
Return a domain suitable for given abscissae.

Find a domain suitable for a polynomial or Chebyshev series
defined at the values supplied.

Parameters
----------
x : array_like
1-d array of abscissae whose domain will be determined.

Returns
-------
domain : ndarray
1-d array containing two values.  If the inputs are complex, then
the two returned points are the lower left and upper right corners
of the smallest rectangle (aligned with the axes) in the complex
plane containing the points x. If the inputs are real, then the
two points are the ends of the smallest interval containing the
points x.

--------
mapparms, mapdomain

Examples
--------
>>> from numpy.polynomial import polyutils as pu
>>> points = np.arange(4)**2 - 5; points
array([-5, -4, -1,  4])
>>> pu.getdomain(points)
array([-5.,  4.])
>>> c = np.exp(complex(0,1)*np.pi*np.arange(12)/6) # unit circle
>>> pu.getdomain(c)
array([-1.-1.j,  1.+1.j])
 def pyneb.utils.polyutils.mapdomain ( x, old, new )
Apply linear map to input points.

The linear map offset + scale*x that maps the domain old to
the domain new is applied to the points x.

Parameters
----------
x : array_like
Points to be mapped. If x is a subtype of ndarray the subtype
will be preserved.
old, new : array_like
The two domains that determine the map.  Each must (successfully)
convert to 1-d arrays containing precisely two values.

Returns
-------
x_out : ndarray
Array of points of the same shape as x, after application of the
linear map between the two domains.

--------
getdomain, mapparms

Notes
-----
Effectively, this implements:

.. math ::
x\\_out = new[0] + m(x - old[0])

where

.. math ::
m = \\frac{new[1]-new[0]}{old[1]-old[0]}

Examples
--------
>>> from numpy import polynomial as P
>>> old_domain = (-1,1)
>>> new_domain = (0,2*np.pi)
>>> x = np.linspace(-1,1,6); x
array([-1. , -0.6, -0.2,  0.2,  0.6,  1. ])
>>> x_out = P.mapdomain(x, old_domain, new_domain); x_out
array([ 0.        ,  1.25663706,  2.51327412,  3.76991118,  5.02654825,
6.28318531])
>>> x - P.mapdomain(x_out, new_domain, old_domain)
array([ 0.,  0.,  0.,  0.,  0.,  0.])

Also works for complex numbers (and thus can be used to map any line in
the complex plane to any other line therein).

>>> i = complex(0,1)
>>> old = (-1 - i, 1 + i)
>>> new = (-1 + i, 1 - i)
>>> z = np.linspace(old[0], old[1], 6); z
array([-1.0-1.j , -0.6-0.6j, -0.2-0.2j,  0.2+0.2j,  0.6+0.6j,  1.0+1.j ])
>>> new_z = P.mapdomain(z, old, new); new_z
array([-1.0+1.j , -0.6+0.6j, -0.2+0.2j,  0.2-0.2j,  0.6-0.6j,  1.0-1.j ])
 def pyneb.utils.polyutils.mapparms ( old, new )
Linear map parameters between domains.

Return the parameters of the linear map offset + scale*x that maps
old to new such that old[i] -> new[i], i = 0, 1.

Parameters
----------
old, new : array_like
Domains. Each domain must (successfully) convert to a 1-d array
containing precisely two values.

Returns
-------
offset, scale : scalars
The map L(x) = offset + scale*x maps the first domain to the
second.

--------
getdomain, mapdomain

Notes
-----
Also works for complex numbers, and thus can be used to calculate the
parameters required to map any line in the complex plane to any other
line therein.

Examples
--------
>>> from numpy import polynomial as P
>>> P.mapparms((-1,1),(-1,1))
(0.0, 1.0)
>>> P.mapparms((1,-1),(-1,1))
(0.0, -1.0)
>>> i = complex(0,1)
>>> P.mapparms((-i,-1),(1,i))
((1+1j), (1+0j))
 def pyneb.utils.polyutils.trimcoef ( c, tol = 0 )
Remove "small" "trailing" coefficients from a polynomial.

"Small" means "small in absolute value" and is controlled by the
parameter tol; "trailing" means highest order coefficient(s), e.g., in
[0, 1, 1, 0, 0] (which represents 0 + x + x**2 + 0*x**3 + 0*x**4)
both the 3-rd and 4-th order coefficients would be "trimmed."

Parameters
----------
c : array_like
1-d array of coefficients, ordered from lowest order to highest.
tol : number, optional
Trailing (i.e., highest order) elements with absolute value less
than or equal to tol (default value is zero) are removed.

Returns
-------
trimmed : ndarray
1-d array with trailing zeros removed.  If the resulting series
would be empty, a series containing a single zero is returned.

Raises
------
ValueError
If tol < 0

--------
trimseq

Examples
--------
>>> from numpy import polynomial as P
>>> P.trimcoef((0,0,3,0,5,0,0))
array([ 0.,  0.,  3.,  0.,  5.])
>>> P.trimcoef((0,0,1e-3,0,1e-5,0,0),1e-3) # item == tol is trimmed
array([ 0.])
>>> i = complex(0,1) # works for complex
>>> P.trimcoef((3e-4,1e-3*(1-i),5e-4,2e-5*(1+i)), 1e-3)
array([ 0.0003+0.j   ,  0.0010-0.001j])
 def pyneb.utils.polyutils.trimseq ( seq )
Remove small Poly series coefficients.

Parameters
----------
seq : sequence
Sequence of Poly series coefficients. This routine fails for
empty sequences.

Returns
-------
series : sequence
Subsequence with trailing zeros removed. If the resulting sequence
would be empty, return the first element. The returned sequence may
or may not be a view.

Notes
-----
Do not lose the type info if the sequence contains unknown objects.

## Variable Documentation

 list __all__
Initial value:
1 = ['RankWarning', 'PolyError', 'PolyDomainError', 'PolyBase',
2  'as_series', 'trimseq', 'trimcoef', 'getdomain', 'mapdomain',
3  'mapparms']