mot.cl_routines package¶
Submodules¶
mot.cl_routines.numerical_hessian module¶
Module contents¶
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mot.cl_routines.
compute_log_likelihood
(ll_func, parameters, data=None, cl_runtime_info=None)[source]¶ Calculate and return the log likelihood of the given model for the given parameters.
This calculates the log likelihoods for every problem in the model (typically after optimization), or a log likelihood for every sample of every model (typically after sample). In the case of the first (after optimization), the parameters must be an (d, p) array for d problems and p parameters. In the case of the second (after sample), you must provide this function with a matrix of shape (d, p, n) with d problems, p parameters and n samples.
Parameters: - ll_func (mot.lib.cl_function.CLFunction) –
The log-likelihood function. A CL function with the signature:
double <func_name>(local const mot_float_type* const x, void* data);
- parameters (ndarray) – The parameters to use in the evaluation of the model. This is either an (d, p) matrix or (d, p, n) matrix with d problems, p parameters and n samples.
- data (mot.lib.kernel_data.KernelData) – the user provided data for the
void* data
pointer. - cl_runtime_info (mot.configuration.CLRuntimeInfo) – the runtime information
Returns: per problem the log likelihood, or, per problem and per sample the log likelihood.
Return type: ndarray
- ll_func (mot.lib.cl_function.CLFunction) –
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mot.cl_routines.
compute_objective_value
(objective_func, parameters, data=None, cl_runtime_info=None)[source]¶ Calculate and return the objective function value of the given model for the given parameters.
Parameters: - objective_func (mot.lib.cl_function.CLFunction) –
A CL function with the signature:
double <func_name>(local const mot_float_type* const x, void* data, local mot_float_type* objective_list);
- parameters (ndarray) – The parameters to use in the evaluation of the model, an (d, p) matrix with d problems and p parameters.
- data (mot.lib.kernel_data.KernelData) – the user provided data for the
void* data
pointer. - cl_runtime_info (mot.configuration.CLRuntimeInfo) – the runtime information
Returns: vector matrix with per problem the objective function value
Return type: ndarray
- objective_func (mot.lib.cl_function.CLFunction) –