The MixtureModel class is an extension of BasisModel to multiple basis spaces for multiple degrees of freedom. More...

Inheritance diagram for intprim.basis.mixture_model.MixtureModel:

Public Member Functions
def	__init__ (self, basis_models)
	Initialization method for the MixtureModel 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	observed_to_state_indices (self, observed_indices)

def	observed_indices_related (self, observed_indices)

def	__init__ (self, basis_models)
	Initialization method for the MixtureModel 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	observed_to_state_indices (self, observed_indices)

def	observed_indices_related (self, observed_indices)

Public Member Functions inherited from intprim.basis.basis_model.BasisModel
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

	observed_dof_to_model_map

	observed_dof_to_degree_map

	basis_models

	model_degrees

	block_prototype

Public Attributes inherited from intprim.basis.basis_model.BasisModel
	observed_dof_names

	num_observed_dof

	block_prototype

Detailed Description

The MixtureModel class is an extension of BasisModel to multiple basis spaces for multiple degrees of freedom.

This allows a user to define separate models for each degree of freedom. For example, in a 3 DoF model the first 2 DoFs might both belong to a GaussianModel while the 3rd belongs to a SigmoidalModel.

Constructor & Destructor Documentation

def intprim.basis.mixture_model.MixtureModel.__init__	(	self,
		basis_models
	)

Initialization method for the MixtureModel class.

Parameters

basis_models array-like, shape(num_basis_models, ). Contains a list of (non-MixtureModel) basis models that are encapsulated in this model.

def intprim.basis.mixture_model.MixtureModel.__init__	(	self,
		basis_models
	)

Initialization method for the MixtureModel class.

Parameters

basis_models array-like, shape(num_basis_models, ). Contains a list of (non-MixtureModel) basis models that are encapsulated in this model.

Member Function Documentation

def intprim.basis.mixture_model.MixtureModel.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.mixture_model.MixtureModel.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.mixture_model.MixtureModel.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.mixture_model.MixtureModel.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.mixture_model.MixtureModel.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.mixture_model.MixtureModel.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.mixture_model.MixtureModel.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.mixture_model.MixtureModel.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.mixture_model.MixtureModel.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.mixture_model.MixtureModel.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.

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

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

Public Member Functions

Public Attributes

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation