Numerical Tools

Interface with the GNU Scientific Library. More...

Data Fitting
template<class T1, class T2>
Array< double > &	linfit (Array< T1 > &x, Array< T2 > &y)
	Linear regression.
template<class T1, class T2, class T3>
Array< double > &	linfit (Array< T1 > &x, Array< T2 > &y, Array< T3 > &w)
	Weighted linear regression.
template<class T1, class T2, class T3>
Array< double > &	linfit2D (Array< T1 > &x, Array< T2 > &y, Array< T3 > &z)
	2D linear regression.
template<class T1, class T2>
Array< double > &	polyfit (Array< T1 > &x, Array< T2 > &y, int n)
	Polynomial fit.
Fourrier transform and filtering
template<typename T>
Array< complex< T > > &	fft_1D (Array< complex< T > > &cplxt, int direction=1)
	Return the complex fft (1D) of the complex array cplxt. Uses the mixed-radix algorithm. Works only with double, so far.
template<typename T>
Array< complex< T > > &	fft_2D (Array< complex< T > > &cplxt, int direction=1)
	Return the complex fft (1D or 2D) of the complex array cplxt. Uses the mixed-radix algorithm. Works only with double, so far.
template<typename T>
Array< complex< T > > &	lowPassFirstOrder (long n, T tau)
	Creates a low pass filter, returns the transfer function.
template<typename T>
Array< complex< T > > &	highPassFirstOrder (long n, T tau)
	Creates a high pass filter, returns the transfer function.
template<typename T>
Array< complex< T > > &	GaussianFilter (long n, T tau)
	Creates a low pass filter, returns the transfer function.
template<typename T>
Array< T > &	filter_1D (Array< T > &t, Array< complex< double > > &filt)
	Filters a 1D signal with the provided filter transfer function.
template<typename T>
Array< T > &	smooth (Array< T > &t, T tau)
	Smooth a 1D signal with a gaussian filter. It works properly at the boundaries.

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Detailed Description

Interface with the GNU Scientific Library.

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Function Documentation

template<class T1, class T2, class T3>

Array<double>& linfit	(	Array< T1 > &	x,
		Array< T2 > &	y,
		Array< T3 > &	w
	)			[inline]

Weighted linear regression.

/*Linear regression on the set of point defined by x & y: y=a+b*x

Parameters:

	x	: x Array,
	y	: y Array,
	w	: weigths.

Returns an Array containing [a b sum_sq ...]

template<class T1, class T2>

Array<double>& linfit	(	Array< T1 > &	x,
		Array< T2 > &	y
	)			[inline]

Linear regression.

Linear regression on the set of point defined by x & y: y=a+b*x

Parameters:

	x	: x Array,
	y	: y Array.

Returns an Array containing [a b sum_sq ...]

template<class T1, class T2, class T3>

Array<double>& linfit2D	(	Array< T1 > &	x,
		Array< T2 > &	y,
		Array< T3 > &	z
	)			[inline]

2D linear regression.

/*Linear regression on the set of point defined by (x,y,z): z=a+b*x+c*y

Parameters:

	x	: x coordinates,
	y	: y coordinates,
	z	: z coordinates.

Returns an Array containing [a b c sum_sq]

template<class T1, class T2>

Array<double>& polyfit	(	Array< T1 > &	x,
		Array< T2 > &	y,
		int	n
	)			[inline]

Polynomial fit.

/*Linear regression on the set of point defined by x & y: y=c[0]+c[1]*x+...+c[n]*x^n

Parameters:

	x	: x Array,
	y	: y Array,
	n	: order of the polynome

Returns an Array containing [c[0]... c[n]]