The BasisModel class is a base level class defining general methods that are used by all implemented basis models. More...

Inheritance diagram for intprim.basis.basis_model.BasisModel:

Public Member Functions
def	__init__ (self, degree, observed_dof_names)
	Initialization method for the BasisModel class. More...

def	get_block_diagonal_basis_matrix (self, x, out_array=None, start_row=0, start_col=0)
	Gets the block diagonal basis matrix for the given phase value(s). More...

def	get_block_diagonal_basis_matrix_derivative (self, x, out_array=None, start_row=0, start_col=0)
	Gets the block diagonal basis derivative matrix for the given phase value(s). More...

def	get_weighted_vector_derivative (self, x, weights, out_array=None, start_row=0, start_col=0)
	Gets the weighted vector derivatives corresponding to this basis model for the given basis state. More...

def	fit_basis_functions_linear_closed_form (self, x, y)
	Fits the given trajectory to this basis model via least squares. More...

def	apply_coefficients (self, x, coefficients, deriv=False)
	Applies the given weights to this basis model. More...

def	plot (self)

def	plot_derivative (self)

def	plot_weighted (self, coefficients, coefficient_names)

def	observed_to_state_indices (self, observed_indices)

def	observed_indices_related (self, observed_indices)

def	__init__ (self, degree, observed_dof_names)
	Initialization method for the BasisModel class. More...

def	get_block_diagonal_basis_matrix (self, x, out_array=None, start_row=0, start_col=0)
	Gets the block diagonal basis matrix for the given phase value(s). More...

def	get_block_diagonal_basis_matrix_derivative (self, x, out_array=None, start_row=0, start_col=0)
	Gets the block diagonal basis derivative matrix for the given phase value(s). More...

def	get_weighted_vector_derivative (self, x, weights, out_array=None, start_row=0, start_col=0)
	Gets the weighted vector derivatives corresponding to this basis model for the given basis state. More...

def	fit_basis_functions_linear_closed_form (self, x, y)
	Fits the given trajectory to this basis model via least squares. More...

def	apply_coefficients (self, x, coefficients, deriv=False)
	Applies the given weights to this basis model. More...

def	plot (self)

def	plot_derivative (self)

def	plot_weighted (self, coefficients, coefficient_names)

def	observed_to_state_indices (self, observed_indices)

def	observed_indices_related (self, observed_indices)

Public Attributes
	observed_dof_names

	num_observed_dof

	block_prototype

Detailed Description

The BasisModel class is a base level class defining general methods that are used by all implemented basis models.

This class corresponds to a shared basis space for 1 or more degrees of freedom. That is, every DoF modeled by this basis space uses the same set of basis functions with the same set of parameters.

Constructor & Destructor Documentation

def intprim.basis.basis_model.BasisModel.__init__	(	self,
		degree,
		observed_dof_names
	)

Initialization method for the BasisModel class.

Parameters

degree	The degree of this basis model. Corresponds to the number of basis functions distributed throughout the domain.
observed_dof_names	The names for the observed degrees of freedom that use this basis space. The length is used to compute the number of observed degrees of freedom.

def intprim.basis.basis_model.BasisModel.__init__	(	self,
		degree,
		observed_dof_names
	)

Initialization method for the BasisModel class.

Parameters

degree	The degree of this basis model. Corresponds to the number of basis functions distributed throughout the domain.
observed_dof_names	The names for the observed degrees of freedom that use this basis space. The length is used to compute the number of observed degrees of freedom.

Member Function Documentation

def intprim.basis.basis_model.BasisModel.apply_coefficients	(	self,
		x,
		coefficients,
		deriv = `False`
	)

Applies the given weights to this basis model.

Projects a basis state to the measurement space.

Parameters

x	Scalar of vector of dimension T containing the phase values to project at.
coefficients	Vector of dimension degree * num_observed_dof containing the basis weights.
deriv	True to use basis function derivative, False to use regular basis functions.

Returns: Vector of dimension num_observed_dof or matrix of dimension num_observed_dof x T if multiple phase values are given.

def intprim.basis.basis_model.BasisModel.apply_coefficients	(	self,
		x,
		coefficients,
		deriv = `False`
	)

Applies the given weights to this basis model.

Projects a basis state to the measurement space.

Parameters

x	Scalar of vector of dimension T containing the phase values to project at.
coefficients	Vector of dimension degree * num_observed_dof containing the basis weights.
deriv	True to use basis function derivative, False to use regular basis functions.

Returns: Vector of dimension num_observed_dof or matrix of dimension num_observed_dof x T if multiple phase values are given.

def intprim.basis.basis_model.BasisModel.fit_basis_functions_linear_closed_form	(	self,
		x,
		y
	)

Fits the given trajectory to this basis model via least squares.

Parameters

x	Vector of dimension T containing the phase values of the trajectory.
y	Matrix of dimension num_observed_dof x T containing the observations of the trajectory.
coefficients	Vector of dimension degree * num_observed_dof containing the fitted basis weights.

def intprim.basis.basis_model.BasisModel.fit_basis_functions_linear_closed_form	(	self,
		x,
		y
	)

Fits the given trajectory to this basis model via least squares.

Parameters

x	Vector of dimension T containing the phase values of the trajectory.
y	Matrix of dimension num_observed_dof x T containing the observations of the trajectory.
coefficients	Vector of dimension degree * num_observed_dof containing the fitted basis weights.

def intprim.basis.basis_model.BasisModel.get_block_diagonal_basis_matrix	(	self,
		x,
		out_array = `None`,
		start_row = `0`,
		start_col = `0`
	)

Gets the block diagonal basis matrix for the given phase value(s).

Used to transform vectors from the basis space to the measurement space.

Parameters

x	Scalar of vector of dimension T containing the phase values to use in the creation of the block diagonal matrix.
out_array	Matrix of dimension greater to or equal than (degree * num_observed_dof * T) x num_observed_dof in which the results are stored. If none, an internal matrix is used.
start_row	A row offset to apply to results in the block diagonal matrix.
start_col	A column offset to apply to results in the block diagonal matrix.

Returns: block_matrix Matrix of dimension greater to or equal than (degree * num_observed_dof * T) x num_observed_dof containing the block diagonal matrix.

def intprim.basis.basis_model.BasisModel.get_block_diagonal_basis_matrix	(	self,
		x,
		out_array = `None`,
		start_row = `0`,
		start_col = `0`
	)

Gets the block diagonal basis matrix for the given phase value(s).

Used to transform vectors from the basis space to the measurement space.

Parameters

x	Scalar of vector of dimension T containing the phase values to use in the creation of the block diagonal matrix.
out_array	Matrix of dimension greater to or equal than (degree * num_observed_dof * T) x num_observed_dof in which the results are stored. If none, an internal matrix is used.
start_row	A row offset to apply to results in the block diagonal matrix.
start_col	A column offset to apply to results in the block diagonal matrix.

Returns: block_matrix Matrix of dimension greater to or equal than (degree * num_observed_dof * T) x num_observed_dof containing the block diagonal matrix.

def intprim.basis.basis_model.BasisModel.get_block_diagonal_basis_matrix_derivative	(	self,
		x,
		out_array = `None`,
		start_row = `0`,
		start_col = `0`
	)

Gets the block diagonal basis derivative matrix for the given phase value(s).

Used to transform vectors from the derivative basis space to the measurement space.

Parameters

x	Scalar containing the phase value to use in the creation of the block diagonal matrix.
out_array	Matrix of dimension greater to or equal than (degree * num_observed_dof) x num_observed_dof in which the results are stored. If none, an internal matrix is used.
start_row	A row offset to apply to results in the block diagonal matrix.
start_col	A column offset to apply to results in the block diagonal matrix.

Returns: block_matrix Matrix of dimension greater to or equal than (degree * num_observed_dof) x num_observed_dof containing the block diagonal matrix.

def intprim.basis.basis_model.BasisModel.get_block_diagonal_basis_matrix_derivative	(	self,
		x,
		out_array = `None`,
		start_row = `0`,
		start_col = `0`
	)

Gets the block diagonal basis derivative matrix for the given phase value(s).

Used to transform vectors from the derivative basis space to the measurement space.

Parameters

x	Scalar containing the phase value to use in the creation of the block diagonal matrix.
out_array	Matrix of dimension greater to or equal than (degree * num_observed_dof) x num_observed_dof in which the results are stored. If none, an internal matrix is used.
start_row	A row offset to apply to results in the block diagonal matrix.
start_col	A column offset to apply to results in the block diagonal matrix.

Returns: block_matrix Matrix of dimension greater to or equal than (degree * num_observed_dof) x num_observed_dof containing the block diagonal matrix.

def intprim.basis.basis_model.BasisModel.get_weighted_vector_derivative	(	self,
		x,
		weights,
		out_array = `None`,
		start_row = `0`,
		start_col = `0`
	)

Gets the weighted vector derivatives corresponding to this basis model for the given basis state.

Parameters

x	Scalar containing the phase value to use in the creation of the block diagonal matrix.
weights	Vector of dimension degree * num_observed_dof containing the weights for this basis model.
out_array	Matrix of dimension greater to or equal than 1 x degree in which the results are stored. If none, an internal matrix is used.
start_row	A row offset to apply to results in the block diagonal matrix.
start_col	A column offset to apply to results in the block diagonal matrix.

Returns: block_matrix Matrix of dimension greater to or equal than (degree * num_observed_dof) x num_observed_dof containing the block diagonal matrix.

def intprim.basis.basis_model.BasisModel.get_weighted_vector_derivative	(	self,
		x,
		weights,
		out_array = `None`,
		start_row = `0`,
		start_col = `0`
	)

Gets the weighted vector derivatives corresponding to this basis model for the given basis state.

Parameters

x	Scalar containing the phase value to use in the creation of the block diagonal matrix.
weights	Vector of dimension degree * num_observed_dof containing the weights for this basis model.
out_array	Matrix of dimension greater to or equal than 1 x degree in which the results are stored. If none, an internal matrix is used.
start_row	A row offset to apply to results in the block diagonal matrix.
start_col	A column offset to apply to results in the block diagonal matrix.

Returns: block_matrix Matrix of dimension greater to or equal than (degree * num_observed_dof) x num_observed_dof containing the block diagonal matrix.

def intprim.basis.basis_model.BasisModel.plot ( self )

Plots the unweighted linear basis model.

def intprim.basis.basis_model.BasisModel.plot ( self )

Plots the unweighted linear basis model.

def intprim.basis.basis_model.BasisModel.plot_derivative ( self )

Plots the unweighted linear basis model.

def intprim.basis.basis_model.BasisModel.plot_derivative ( self )

Plots the unweighted linear basis model.

def intprim.basis.basis_model.BasisModel.plot_weighted	(	self,
		coefficients,
		coefficient_names
	)

Plots the weighted linear basis model.

def intprim.basis.basis_model.BasisModel.plot_weighted	(	self,
		coefficients,
		coefficient_names
	)

Plots the weighted linear basis model.

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

/home/joe/LibraryPythonPkg/intprim/build/lib.linux-x86_64-2.7/intprim/basis/basis_model.py

Public Member Functions

Public Attributes

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation