An algorithm that applies a convolution along the time axis. More...

#include <teca_time_axis_convolution.h>

Inheritance diagram for teca_time_axis_convolution:

Collaboration diagram for teca_time_axis_convolution:

Public Member Functions
std::shared_ptr< teca_time_axis_convolution >	shared_from_this ()

std::shared_ptr< teca_time_axis_convolution const >	shared_from_this () const

	teca_time_axis_convolution (const teca_time_axis_convolution &src)=delete

	teca_time_axis_convolution (teca_time_axis_convolution &&src)=delete

teca_time_axis_convolution &	operator= (const teca_time_axis_convolution &src)=delete

teca_time_axis_convolution &	operator= (teca_time_axis_convolution &&src)=delete

const char *	get_class_name () const override

use_high_pass
When set the internally generated weights will be converted to a high_pass filter during weight generation. This option has no affect on user provided kernel weights.
void	set_use_high_pass (const int &v)

const int &	get_use_high_pass () const

kernel_width
The number of samples to use when generating kernel weights. This option has no affect on user provided kernel weights.
void	set_kernel_width (const unsigned int &v)

const unsigned int &	get_kernel_width () const

kernel_weights
Set the kernel weights explicitly. The number of weights defines the stencil width and must be odd for a centered stencil.
size_t	get_number_of_kernel_weights ()

void	append_kernel_weight (const double &v)

void	set_kernel_weight (size_t i, const double &v)

void	set_kernel_weights (const std::vector< double > &v)

void	set_kernel_weights (const std::initializer_list< double > &&l)

const double &	get_kernel_weight (size_t i) const

const std::vector< double > &	get_kernel_weights () const

void	clear_kernel_weights ()

int	set_constant_kernel_weights (unsigned int width)
	generate constant convolution kernel weights with the given filter width More...

int	set_gaussian_kernel_weights (unsigned int width, int high_pass=0, double a=1.0, double B=0.0, double c=0.55)

int	set_kernel_weights (const std::string &name, unsigned int width, int high_pass)

kernel_name
set the name of the user provided kernel, or the kernel to generate.
void	set_kernel_name (const std::string &v)

const std::string &	get_kernel_name () const

variable_postfix
a string to be appended to the name of each output variable setting this to an empty string will result in the damped array replacing the input array in the output. default is an empty string ""
void	set_variable_postfix (const std::string &v)

const std::string &	get_variable_postfix () const

Public Member Functions inherited from teca_algorithm
	teca_algorithm (const teca_algorithm &src)=delete

	teca_algorithm (teca_algorithm &&src)=delete

teca_algorithm &	operator= (const teca_algorithm &src)=delete

teca_algorithm &	operator= (teca_algorithm &&src)=delete

void	set_communicator (MPI_Comm comm)

MPI_Comm	get_communicator ()
	get the active communicator More...

virtual teca_algorithm_output_port	get_output_port (unsigned int port=0)

void	set_input_connection (const teca_algorithm_output_port &port)
	set an input to this algorithm More...

virtual void	set_input_connection (unsigned int id, const teca_algorithm_output_port &port)
	set an input to this algorithm More...

virtual void	remove_input_connection (unsigned int id)
	remove input connections More...

void	clear_input_connections ()
	remove all input connections More...

const_p_teca_dataset	get_output_data (unsigned int port=0)

void	pop_cache (unsigned int port=0, int top=0)

void	set_cache_size (unsigned int n)
	set the cache size. the default is 1. (threadsafe) More...

virtual int	update ()
	execute the pipeline from this instance up. More...

virtual int	update (unsigned int port)
	execute the pipeline from this instance up. More...

virtual teca_metadata	update_metadata (unsigned int port=0)
	get meta data considering this instance up. More...

void	set_executive (p_teca_algorithm_executive exe)
	set the executive More...

p_teca_algorithm_executive	get_executive ()
	get the executive More...

virtual void	to_stream (std::ostream &s) const

virtual void	from_stream (std::istream &s)
	deserialize from the stream. More...

void	set_verbose (const int &v)

const int &	get_verbose () const

Static Public Member Functions
static p_teca_time_axis_convolution	New ()

stencil_type
Select which time steps are convolved. The default stencil is backward.
enum	{ backward, centered, forward }

void	set_stencil_type (const int &v)

const int &	get_stencil_type () const

void	set_stencil_type_to_forward ()
	convolve with time steps after the active step More...

void	set_stencil_type_to_backward ()
	convolve with time steps before the active step More...

void	set_stencil_type_to_centered ()
	convolve with time steps centered on the active step More...

int	set_stencil_type (const std::string &type)
	set the stencil type from a string More...

std::string	get_stencil_type_name ()
	get the stencil as a string More...

Additional Inherited Members
Protected Member Functions inherited from teca_algorithm
void	set_number_of_input_connections (unsigned int n)

void	set_number_of_output_ports (unsigned int n)

virtual void	set_modified ()

void	set_modified (unsigned int port)
	an overload to set_modified by port More...

virtual teca_metadata	get_cache_key (unsigned int port, const teca_metadata &request) const

virtual teca_metadata	get_output_metadata (teca_algorithm_output_port &current)

virtual const_p_teca_dataset	request_data (teca_algorithm_output_port &port, const teca_metadata &request)

virtual int	validate_cache (teca_algorithm_output_port &current)

virtual void	clear_modified (teca_algorithm_output_port current)

const_p_teca_dataset	get_output_data (unsigned int port, const teca_metadata &request)

int	cache_output_data (unsigned int port, const teca_metadata &request, const_p_teca_dataset &data)

void	clear_cache (unsigned int port)
	clear the cache on the given output port More...

unsigned int	get_number_of_input_connections ()
	get the number of input connections More...

teca_algorithm_output_port &	get_input_connection (unsigned int i)

void	clear_modified (unsigned int port)
	clear the modified flag on the i'th output More...

int	get_modified (unsigned int port) const
	return the output port's modified flag value More...

Protected Attributes inherited from teca_algorithm
int	verbose

Detailed Description

An algorithm that applies a convolution along the time axis.

Supports constant, Gaussian, and explicitly provided convolution kernels of arbitrary width applied over forward, backward, or centered stencils.

A number of options are provided for specifying kernel weights.

User provided kernels can be explicitly specified via the combination of ::set_kernel_weights and ::set_kernel_name.
The kernel can be generated at run time by providing a kernel name, width, and flag selecting either a high or low pass filter via the combination of ::set_kernel_name, ::set_kernel_width, and ::set_use_high_pass. In this case default kernel parameters are used.
The kernel can be generated with explicitly provided kernel parameters.

Member Enumeration Documentation

◆ anonymous enum

anonymous enum

Enumerator

centered

convolve with time steps before the active step

forward

convolve with time steps centered on the active step

convolve with time steps after the active step

Member Function Documentation

◆ append_kernel_weight()

void teca_time_axis_convolution::append_kernel_weight ( const double & v )

inline

append to the kernel_weight algorithm vector property

◆ clear_kernel_weights()

void teca_time_axis_convolution::clear_kernel_weights ( )

inline

clear the kernel_weight algorithm vector property

◆ get_class_name()

const char* teca_time_axis_convolution::get_class_name ( ) const

inlineoverridevirtual

returns the name of the class

Implements teca_algorithm.

◆ get_kernel_name()

const std::string& teca_time_axis_convolution::get_kernel_name ( ) const

inline

Get the value of the kernel_name algorithm property

◆ get_kernel_weight()

const double& teca_time_axis_convolution::get_kernel_weight ( size_t i ) const

inline

get the i-th element of the kernel_weight algorithm vector property

◆ get_kernel_weights()

const std::vector< double >& teca_time_axis_convolution::get_kernel_weights ( ) const

inline

get the kernel_weight algorithm vector property

◆ get_kernel_width()

const unsigned int& teca_time_axis_convolution::get_kernel_width ( ) const

inline

Get the value of the kernel_width algorithm property

◆ get_number_of_kernel_weights()

size_t teca_time_axis_convolution::get_number_of_kernel_weights ( )

inline

get the size of the kernel_weight algorithm vector property

◆ get_stencil_type()

const int& teca_time_axis_convolution::get_stencil_type ( ) const

inline

Get the value of the stencil_type algorithm property

◆ get_stencil_type_name()

std::string teca_time_axis_convolution::get_stencil_type_name ( )

get the stencil as a string

◆ get_use_high_pass()

const int& teca_time_axis_convolution::get_use_high_pass ( ) const

inline

Get the value of the use_high_pass algorithm property

◆ get_variable_postfix()

const std::string& teca_time_axis_convolution::get_variable_postfix ( ) const

inline

Get the value of the variable_postfix algorithm property

◆ New()

static p_teca_time_axis_convolution teca_time_axis_convolution::New ( )

inlinestatic

Returns an instance of teca_time_axis_convolution

◆ set_constant_kernel_weights()

int teca_time_axis_convolution::set_constant_kernel_weights ( unsigned int width )

generate constant convolution kernel weights with the given filter width

◆ set_gaussian_kernel_weights()

int teca_time_axis_convolution::set_gaussian_kernel_weights	(	unsigned int	width,
		int	high_pass = `0`,
		double	a = `1.0`,
		double	B = `0.0`,
		double	c = `0.55`
	)

generate Gaussian convolution kernel weights with the given filter width.

Parameters

[in]	width	the number of samples in the generated kernel
[in]	high_pass	transform the weights for use in a high pass filter.
[in]	a	peak height of the Gaussian
[in]	B	center of the Gaussian (note coordinates range from -1 to 1.
[in]	c	width of the Gaussian

◆ set_kernel_name()

void teca_time_axis_convolution::set_kernel_name ( const std::string & v )

inline

Set the value of the kernel_name algorithm property

◆ set_kernel_weight()

void teca_time_axis_convolution::set_kernel_weight	(	size_t	i,
		const double &	v
	)

inline

set the i-th element of the kernel_weight algorithm vector property

◆ set_kernel_weights() [1/3]

void teca_time_axis_convolution::set_kernel_weights ( const std::initializer_list< double > && l )

inline

set the kernel_weight algorithm vector property

◆ set_kernel_weights() [2/3]

int teca_time_axis_convolution::set_kernel_weights	(	const std::string &	name,
		unsigned int	width,
		int	high_pass
	)

set the kernel weights from a string name the kernel type. Default kernel weight generator parameters are used.

Parameters

[in]	name	the name of the kernel to generate. (gaussian, or constant)
[in]	width	the width of the kernel.
[in]	high_pass	convert the weights for use as a high pass filter.

◆ set_kernel_weights() [3/3]

void teca_time_axis_convolution::set_kernel_weights ( const std::vector< double > & v )

inline

set the kernel_weight algorithm vector property

◆ set_kernel_width()

void teca_time_axis_convolution::set_kernel_width ( const unsigned int & v )

inline

Set the value of the kernel_width algorithm property

◆ set_stencil_type() [1/2]

void teca_time_axis_convolution::set_stencil_type ( const int & v )

inline

Set the value of the stencil_type algorithm property

◆ set_stencil_type() [2/2]

int teca_time_axis_convolution::set_stencil_type ( const std::string & type )

set the stencil type from a string

◆ set_stencil_type_to_backward()

void teca_time_axis_convolution::set_stencil_type_to_backward ( )

inline

convolve with time steps before the active step

◆ set_stencil_type_to_centered()

void teca_time_axis_convolution::set_stencil_type_to_centered ( )

inline

convolve with time steps centered on the active step

◆ set_stencil_type_to_forward()

void teca_time_axis_convolution::set_stencil_type_to_forward ( )

inline

convolve with time steps after the active step

◆ set_use_high_pass()

void teca_time_axis_convolution::set_use_high_pass ( const int & v )

inline

Set the value of the use_high_pass algorithm property

◆ set_variable_postfix()

void teca_time_axis_convolution::set_variable_postfix ( const std::string & v )

inline

Set the value of the variable_postfix algorithm property

◆ shared_from_this() [1/2]

std::shared_ptr< teca_time_axis_convolution > teca_time_axis_convolution::shared_from_this ( )

inline

Enables the static constructor

◆ shared_from_this() [2/2]

std::shared_ptr< teca_time_axis_convolution const> teca_time_axis_convolution::shared_from_this ( ) const

inline

Enables the static constructor

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

stable/alg/teca_time_axis_convolution.h

Public Member Functions

Static Public Member Functions

stencil_type

Additional Inherited Members

Detailed Description

Member Enumeration Documentation

◆ anonymous enum

Member Function Documentation

◆ append_kernel_weight()

◆ clear_kernel_weights()

◆ get_class_name()

◆ get_kernel_name()

◆ get_kernel_weight()

◆ get_kernel_weights()

◆ get_kernel_width()

◆ get_number_of_kernel_weights()

◆ get_stencil_type()

◆ get_stencil_type_name()

◆ get_use_high_pass()

◆ get_variable_postfix()

◆ New()

◆ set_constant_kernel_weights()

◆ set_gaussian_kernel_weights()

◆ set_kernel_name()

◆ set_kernel_weight()

◆ set_kernel_weights() [1/3]

◆ set_kernel_weights() [2/3]

◆ set_kernel_weights() [3/3]

◆ set_kernel_width()

◆ set_stencil_type() [1/2]

◆ set_stencil_type() [2/2]

◆ set_stencil_type_to_backward()

◆ set_stencil_type_to_centered()

◆ set_stencil_type_to_forward()

◆ set_use_high_pass()

◆ set_variable_postfix()

◆ shared_from_this() [1/2]

◆ shared_from_this() [2/2]