Data Analysis Routines

These modules provide basic data analysis or data fitting functionality.

linefit

Fit a line to a data set with optional weights.

Returns the parameters of the model, bo, b1: Y = b0 + b1* X

author:  Nadia Dencheva version:  ‘1.0 (2007-02-20)’

pytools.linefit.linefit(x, y, weights=None)

Parameters :  

y: 1D numpy array :

The data to be fitted

x: 1D numpy array :

The x values of the y array. x and y must have the same shape.

weights: 1D numpy array, must have the same shape as x and y :

weight values

Examples

>>> x=N.array([-5, -4 ,-3 ,-2 ,-1, 0, 1, 2, 3, 4, 5])
>>> y=N.array([1, 5, 4, 7, 10, 8, 9, 13, 14, 13, 18])
>>> around(linefit(x,y), decimals=5)
array([ 9.27273,  1.43636])
>>> x=N.array([1.3,1.3,2.0,2.0,2.7,3.3,3.3,3.7,3.7,4.,4.,4.,4.7,4.7,5.,5.3,5.3,5.3,5.7,6.,6.,6.3,6.7])
>>> y = N.array([2.3,1.8,2.8,1.5,2.2,3.8,1.8,3.7,1.7,2.8,2.8,2.2,3.2,1.9,1.8,3.5,2.8,2.1,3.4,3.2,3.,3.,5.9])
>>> around(linefit(x,y), decimals=5)
array([ 1.42564,  0.31579])

nmpfit

Python/Numeric version of this module was called mpfit. This version was modified to use numpy.

xyinterp

Module:  xyinterp.py

Interpolates y based on the given xval.

x and y are a pair of independent/dependent variable arrays that must be the same length. The x array must also be sorted. xval is a user-specified value. This routine looks up xval in the x array and uses that information to properly interpolate the value in the y array.

author:  Vicki Laidler version:  ‘0.1 (2006-07-06)’

pytools.xyinterp.xyinterp(x, y, xval)

Purpose :  Interpolates y based on the given xval.

x and y are a pair of independent/dependent variable arrays that must be the same length. The x array must also be sorted. xval is a user-specified value. This routine looks up xval in the x array and uses that information to properly interpolate the value in the y array.

Parameters :  

x: 1D numpy array :

independent variable array: MUST BE SORTED

y: 1D numpy array :

dependent variable array

xval: float :

the x value at which you want to know the value of y

Returns :  

y: float :

the value of y corresponding to xval

Raises :  

ValueError: :

If arrays are unequal length; or x array is unsorted; or if xval falls outside the bounds of x (extrapolation is unsupported

:version: 0.1 last modified 2006-07-06 :

See also

numpy

Notes

Use the searchsorted method on the X array to determine the bin in which xval falls; then use that information to compute the corresponding y value.

gfit

Return the gaussian fit of a 1D array.

Uses mpfit.py - a python implementation of the Levenberg-Marquardt least-squares minimization, based on MINPACK-1. See nmpfit.py for the history of this module (fortran -> idl -> python). nmpfit.py is a version of mpfit.py which uses numarray.

@author: Nadia Dencheva @version: ‘1.0 (2007-02-20)’

pytools.gfit.gfit1d(y, x=None, err=None, weights=None, par=None, parinfo=None, maxiter=200, quiet=0)

Return the gaussian fit as an object.

Parameters :  

y: 1D Numarray array :

The data to be fitted

x: 1D Numarray array :

(optional) The x values of the y array. x and y must have the same shape.

err: 1D Numarray array :

(optional) 1D array with measurement errors, must be the same shape as y

weights: 1D Numarray array :

(optiional) 1D array with weights, must be the same shape as y

par: List :

(optional) Starting values for the parameters to be fitted

parinfo: Dictionary of lists :

(optional) provides additional information for the parameters. For a detailed description see nmpfit.py. Parinfo can be used to limit parameters or keep some of them fixed.

maxiter: number :

Maximum number of iterations to perform Default: 200

quiet: number :

if set to 1, nmpfit does not print to the screen Default: 0

Examples

>>> x=N.arange(10,20, 0.1)
>>> y= 10*N.e**(-(x-15)**2/4)
>>> print gfit1d(y,x=x, maxiter=20,quiet=1).params
[ 10.          15.           1.41421356]

Image Combination Modules

The numcombine module serves as a limited replacement for IRAF’s ‘imcombine’ task.

class pytools.numcombine.numCombine(numarrayObjectList, numarrayMaskList=None, combinationType='median', nlow=0, nhigh=0, nkeep=1, upper=None, lower=None)

A lite version of the imcombine IRAF task