Time Series Class. More...

#include <TimeSeries.hpp>

Public Types
typedef std::vector< T >::iterator	iterator

typedef std::vector< T >::const_iterator	const_iterator

typedef const T &	const_reference

typedef T &	reference

typedef T	value_type

Public Member Functions
	TimeSeries (const std::vector< T > &inp)

	TimeSeries (const uint size, const T *array)

	TimeSeries (const TimeSeries< T > &inp)

	TimeSeries (const uint n)

	TimeSeries (const uint n, const T val)

void	resize (const uint n, const T val=(T) 0.0)
	Resize the TimeSeries by calling the underlying vector's resize.

	TimeSeries (const std::string &filename, const int col=2)

void	init (void)

void	zero (void)

T &	operator[] (const unsigned int i)

const T &	operator[] (const unsigned int i) const

unsigned int	size (void) const

TimeSeries< T >	operator+= (const T val)

TimeSeries< T >	operator+= (const TimeSeries< T > &rhs)

TimeSeries< T >	operator+ (const T val) const

TimeSeries< T >	operator+ (const TimeSeries< T > &rhs) const

TimeSeries< T >	operator-= (const T val)

TimeSeries< T >	operator-= (const TimeSeries< T > &rhs)

TimeSeries< T >	operator- (const T val) const

TimeSeries< T >	operator- (const TimeSeries< T > &rhs) const

TimeSeries< T >	operator- () const

TimeSeries< T >	*operator=** (const T val)

TimeSeries< T >	operator* (const T val) const

TimeSeries< T >	*operator=** (const TimeSeries< T > &rhs)

TimeSeries< T >	operator* (const TimeSeries< T > &rhs) const

TimeSeries< T >	operator/= (const T val)

TimeSeries< T >	operator/ (const T val) const

TimeSeries< T >	operator/= (const TimeSeries< T > &rhs)

TimeSeries< T >	operator/ (const TimeSeries< T > &rhs) const

TimeSeries< T >	copy (void) const

void	set_skip (unsigned int num_points)

T	average (void) const
	Return average of time series.

T	weighted_average (const std::vector< double > &w) const
	Return weighted average.

T	variance (void) const
	Return variance of time series.

T	weighted_variance (const std::vector< double > &w) const
	Return weighted variance.

T	stdev (void) const
	Return standard deviation of time series.

T	stdev (const std::vector< double > &w) const
	Return weighted standard deviation of time series.

T	sterr (void) const

TimeSeries< T >	running_average (void) const

TimeSeries< T >	windowed_average (const uint window) const

T	block_var (const int num_blocks) const

TimeSeries< T >	correl (const int max_time, const int interval=1, const bool normalize=true, T tol=1.0e-8) const

void	push_back (const T &x)

iterator	begin ()

iterator	end ()

const_iterator	begin () const

const_iterator	end () const

Friends
TimeSeries< T >	operator+ (const T lhs, const TimeSeries< T > &rhs)

TimeSeries< T >	operator- (const T lhs, const TimeSeries< T > &rhs)

TimeSeries< T >	operator* (const T lhs, const TimeSeries< T > &rhs)

TimeSeries< T >	operator/ (const T lhs, const TimeSeries< T > &rhs)

Detailed Description

template<class T>
class loos::TimeSeries< T >

Time Series Class.

This class provides basic operations on a time series, such as averaging, standard deviation, etc

One can do standard arimethic operations on time series combined with scalars or other timeseries (as long as the two time series are the same length).

Constructor & Destructor Documentation

◆ TimeSeries()

template<class T >

loos::TimeSeries< T >::TimeSeries	(	const std::string &	filename,
		const int	col = 2 )

inline

Read a simple text file and create a timeseries The file is assumed to be simple columnated data. Blank lines and lines starting with "#" are ignored.

Member Function Documentation

◆ block_var()

template<class T >

T loos::TimeSeries< T >::block_var ( const int num_blocks ) const

inline

Return the variance of the block average for the time series. Divides the timeseries into num_blocks equally sized blocks (discarding the remaining blocks at the end), computes the average for each block, and returns the variance of the averages. This is useful for doing Flyvjberg and Petersen-style block averaging. Flyvbjerg, H. & Petersen, H. G. J. Chem. Phys., 1989, 91, 461-466

◆ running_average()

template<class T >

TimeSeries< T > loos::TimeSeries< T >::running_average ( void ) const

inline

Return a new timeseries of the same size as the current one, containing the running average of the time series

◆ set_skip()

template<class T >

void loos::TimeSeries< T >::set_skip ( unsigned int num_points )

inline

Remove num_points from the front of the time series, as you would to eliminate the equilibration time

◆ sterr()

template<class T >

T loos::TimeSeries< T >::sterr ( void ) const

inline

Return standard error of time series. This assumes all points are statistically independent Otherwise, needs to be multiplied by the square root of the correlation time, in units of the step interval for the time series

◆ windowed_average()

template<class T >

TimeSeries< T > loos::TimeSeries< T >::windowed_average ( const uint window ) const

inline

Return a new timeseries containing the windowed average. ith value of the new time series = 1/window * sum(data[i:i+window]). NOTE: The present algorithm is relatively fast, but can be prone to roundoff.

The documentation for this class was generated from the following file:

src/TimeSeries.hpp

Public Types

Public Member Functions

Friends

Detailed Description

Constructor & Destructor Documentation

◆ TimeSeries()

Member Function Documentation

◆ block_var()

◆ running_average()

◆ set_skip()

◆ sterr()

◆ windowed_average()