Index of values


C
calc [Interfaces.Sigs.Deriv.Deriv.Trained]
calc model ~targets
calc [Interfaces.Sigs.Deriv.Deriv.Model]
calc inputs ~sigma2
calc [Interfaces.Sigs.Deriv.Deriv.Inputs]
calc inducing points
calc [Interfaces.Sigs.Deriv.Deriv.Inducing]
calc kernel inducing_points
calc [Interfaces.Sigs.Eval.Cov_sampler]
calc ?predictive mean variance
calc [Interfaces.Sigs.Eval.Sampler]
calc ?predictive mean variance
calc [Interfaces.Sigs.Eval.Covariances]
calc co_variance_predictor ~sigma2 inputs
calc [Interfaces.Sigs.Eval.Variances]
calc co_variance_predictor ~sigma2 inputs
calc [Interfaces.Sigs.Eval.Variance]
calc co_variance_predictor ~sigma2 input
calc [Interfaces.Sigs.Eval.Co_variance_predictor]
calc kernel inducing_points co_variance_coeffs
calc [Interfaces.Sigs.Eval.Means]
calc mean_predictor inputs
calc [Interfaces.Sigs.Eval.Mean]
calc mean_predictor input
calc [Interfaces.Sigs.Eval.Mean_predictor]
calc inducing_points ~coeffs
calc [Interfaces.Sigs.Eval.Stats]
calc trained
calc [Interfaces.Sigs.Eval.Trained]
calc model ~targets
calc [Interfaces.Sigs.Eval.Model]
calc inputs ~sigma2
calc [Interfaces.Sigs.Eval.Inputs]
create points inducing
calc [Interfaces.Sigs.Eval.Input]
calc inducing point
calc [Interfaces.Sigs.Eval.Inducing]
calc kernel inducing_points
calc_co_variance_coeffs [Interfaces.Sigs.Eval.Model]
calc_co_variance_coeffs model
calc_cross [Interfaces.Specs.Eval.Inputs]
calc_cross kernel ~inputs ~inducing
calc_deriv_cross [Interfaces.Specs.Deriv.Inputs]
calc_deriv_cross cross hyper
calc_deriv_diag [Interfaces.Specs.Deriv.Inputs]
calc_deriv_diag diag hyper
calc_deriv_upper [Interfaces.Specs.Deriv.Inducing]
calc_deriv_upper upper hyper
calc_diag [Interfaces.Specs.Eval.Inputs]
calc_diag kernel inputs
calc_eval [Interfaces.Sigs.Deriv.Deriv.Trained]
calc_eval trained
calc_eval [Interfaces.Sigs.Deriv.Deriv.Model]
calc_eval model
calc_eval [Interfaces.Sigs.Deriv.Deriv.Inputs]
calc_eval inputs
calc_eval [Interfaces.Sigs.Deriv.Deriv.Inducing]
calc_eval inducing
calc_log_evidence [Interfaces.Sigs.Deriv.Deriv.Trained]
calc_log_evidence hyper_t hyper
calc_log_evidence [Interfaces.Sigs.Deriv.Deriv.Model]
calc_log_evidence hyper_t hyper
calc_log_evidence [Interfaces.Sigs.Eval.Trained]
calc_log_evidence trained
calc_log_evidence [Interfaces.Sigs.Eval.Model]
calc_log_evidence model
calc_log_evidence_sigma2 [Interfaces.Sigs.Deriv.Deriv.Trained]
calc_log_evidence_sigma2 trained
calc_log_evidence_sigma2 [Interfaces.Sigs.Deriv.Deriv.Model]
calc_log_evidence_sigma2 model
calc_mad [Interfaces.Sigs.Eval.Stats]
calc_mad trained
calc_maxad [Interfaces.Sigs.Eval.Stats]
calc_mad trained
calc_mean_coeffs [Interfaces.Sigs.Eval.Trained]
calc_mean_coeffs trained
calc_model [Interfaces.Sigs.Eval.Co_variance_predictor]
calc_model model
calc_model_inputs [Interfaces.Sigs.Eval.Covariances]
calc_model_inputs model
calc_model_inputs [Interfaces.Sigs.Eval.Variances]
calc_model_inputs model
calc_mpi_criterion [Interfaces.Sigs.Optimizer.Optimizer]
calc_mpi_deriv [Interfaces.Sigs.Optimizer.Optimizer]
calc_mse [Interfaces.Sigs.Eval.Stats]
calc_mse trained
calc_msll [Interfaces.Sigs.Eval.Stats]
calc_msll trained
calc_n_samples [Interfaces.Sigs.Eval.Stats]
calc_n_samples trained
calc_rmse [Interfaces.Sigs.Eval.Stats]
calc_sse trained
calc_shared_cross [Interfaces.Specs.Deriv.Inputs]
calc_shared_cross kernel ~inputs ~inducing
calc_shared_diag [Interfaces.Specs.Deriv.Inputs]
calc_shared_diag kernel inputs
calc_shared_upper [Interfaces.Specs.Deriv.Inducing]
calc_shared_upper kernel inducing
calc_smse [Interfaces.Sigs.Eval.Stats]
calc_smse trained
calc_sse [Interfaces.Sigs.Eval.Stats]
calc_sse trained
calc_target_variance [Interfaces.Sigs.Eval.Stats]
calc_target_variance trained
calc_trained [Interfaces.Sigs.Eval.Mean_predictor]
calc_trained trained
calc_upper [Interfaces.Specs.Eval.Inputs]
calc_upper kernel inputs
calc_upper [Interfaces.Specs.Eval.Inducing]
calc_upper kernel inducing
check_deriv_hyper [Interfaces.Sigs.Deriv.Deriv.Test]
check_deriv_hyper ?eps ?tol kernel inducing_points points hyper will raise Failure if the derivative code provided in the specification of the covariance function given parameter hyper, the kernel, inducing_points and input points exceeds the tolerance tol when compared to finite differences using epsilon eps.
check_sparse_col_mat_sane [Gpr_utils]
check_sparse_row_mat_sane [Gpr_utils]
check_sparse_vec_sane [Gpr_utils]
cholesky_jitter [Gpr_utils]
choose_cols [Gpr_utils]
choose_n_first_inputs [Interfaces.Sigs.Eval.Inducing]
choose_n_first_inputs kernel inputs ~n_inducing
choose_n_random_inputs [Interfaces.Sigs.Eval.Inducing]
choose_n_random_inputs ?rnd_state kernel inputs ~n_inducing
choose_subset [Interfaces.Specs.Eval.Inputs]
choose_subset inputs indexes
copy [Block_diag]
copy bm
create [Cov_se_fat.Params]
create [Block_diag]
create mats
create [Interfaces.Sigs.Optimizer.Optimizer]
create [Interfaces.Sigs.Deriv.Deriv.Optim.SMD]
create [Interfaces.Sigs.Deriv.Deriv.Optim.SGD]
create [Interfaces.Specs.Eval.Inputs]
create inputs
create [Interfaces.Specs.Kernel]
create params
create [Gpr_utils.Int_vec]
create_default_kernel [Interfaces.Sigs.Eval.Inputs]
create_default_kernel points
create_default_kernel_params [Interfaces.Specs.Eval.Inputs]
create_default_kernel_params inputs ~n_inducing
create_inducing [Interfaces.Specs.Eval.Inputs]
create_inducing kernel inputs

D
debug [Gpr_utils]
default_rng [Gpr_utils]
dim [Gpr_utils.Int_vec]

E
eval [Interfaces.Specs.Eval.Input]
eval kernel input inducing
eval_one [Interfaces.Specs.Eval.Input]
eval_one kernel point

G
get [Interfaces.Sigs.Eval.Covariances]
get ?predictive covariances
get [Interfaces.Sigs.Eval.Variances]
get ?predictive variances
get [Interfaces.Sigs.Eval.Variance]
get ?predictive variance
get [Interfaces.Sigs.Eval.Means]
get means
get [Interfaces.Sigs.Eval.Mean]
get mean
get_all [Interfaces.Specs.Deriv.Hyper]
get_all kernel inducing inputs
get_coeffs [Interfaces.Sigs.Eval.Mean_predictor]
get_coeffs mean_predictor
get_eta [Interfaces.Sigs.Deriv.Deriv.Optim.SMD]
get_eta [Interfaces.Sigs.Deriv.Deriv.Optim.SGD]
get_inducing [Interfaces.Sigs.Eval.Mean_predictor]
get_inducing mean_predictor
get_inducing [Interfaces.Sigs.Eval.Model]
get_inputs model
get_inputs [Interfaces.Sigs.Eval.Model]
get_inputs model
get_kernel [Interfaces.Sigs.Eval.Model]
get_kernel model
get_model [Interfaces.Sigs.Eval.Trained]
get_model trained
get_n_points [Interfaces.Specs.Eval.Inputs]
get_n_points inputs
get_n_points [Interfaces.Specs.Eval.Inducing]
get_n_points inducing
get_nu [Interfaces.Sigs.Deriv.Deriv.Optim.SMD]
get_params [Interfaces.Specs.Kernel]
get_params kernel
get_points [Interfaces.Sigs.Eval.Inputs]
get_points kernel inputs
get_points [Interfaces.Sigs.Eval.Inducing]
get_points kernel inducing
get_sigma2 [Interfaces.Sigs.Eval.Model]
get_sigma2 model
get_step [Interfaces.Sigs.Deriv.Deriv.Optim.SGD]
get_targets [Interfaces.Sigs.Eval.Trained]
get_targets trained
get_trained [Interfaces.Sigs.Deriv.Deriv.Optim.SMD]
get_trained [Interfaces.Sigs.Deriv.Deriv.Optim.SGD]
get_value [Interfaces.Specs.Optimizer.Inputs]
get_value inputs var
get_value [Interfaces.Specs.Optimizer.Input]
get_value input var
get_value [Interfaces.Specs.Deriv.Hyper]
get_value kernel inducing inputs hyper
get_variances [Interfaces.Sigs.Eval.Covariances]
get_variances covariances
get_vars [Interfaces.Specs.Optimizer.Inputs]
get_vars inputs
get_vars [Interfaces.Specs.Optimizer.Input]
get_vars input
gradient_norm [Interfaces.Sigs.Deriv.Deriv.Optim.SMD]
gradient_norm [Interfaces.Sigs.Deriv.Deriv.Optim.SGD]

I
ichol [Gpr_utils]

L
learn [Interfaces.Sigs.Optimizer.Optimizer]
log_2pi [Gpr_utils]
log_det [Gpr_utils]

P
pi [Gpr_utils]
potrf [Block_diag]
potrf ?jitter bm perform Cholesky factorization on block diagonal matrix bm using Cholesky jitter if given.
potri [Block_diag]
potri ?jitter ?factorize bm invert block diagonal matrix bm using its Cholesky factor.
prepare_hyper [Interfaces.Sigs.Deriv.Deriv.Trained]
prepare_hyper trained
prepare_hyper [Interfaces.Sigs.Deriv.Deriv.Model]
prepare_hyper model
print_float [Gpr_utils]
print_int [Gpr_utils]
print_mat [Gpr_utils]
print_vec [Gpr_utils]

S
sample [Interfaces.Sigs.Eval.Cov_sampler]
sample ?rng sampler
sample [Interfaces.Sigs.Eval.Sampler]
sample ?rng sampler
samples [Interfaces.Sigs.Eval.Cov_sampler]
samples ?rng sampler ~n
samples [Interfaces.Sigs.Eval.Sampler]
samples ?rng sampler ~n
self_test [Interfaces.Sigs.Deriv.Deriv.Test]
self_test ?eps ?tol kernel inducing_points points ~sigma2 ~targets hyper will raise Failure if the internal derivative code for the log evidence given parameter hyper, the kernel, inducing_points, input points, noise level sigma2 and targets exceeds the tolerance tol when compared to finite differences using epsilon eps.
set_values [Interfaces.Specs.Optimizer.Inputs]
set_values inputs vars values
set_values [Interfaces.Specs.Optimizer.Input]
set_values input vars values
set_values [Interfaces.Specs.Deriv.Hyper]
set_values kernel inducing inputs hypers values
solve_tri [Gpr_utils]
step [Interfaces.Sigs.Deriv.Deriv.Optim.SMD]
step [Interfaces.Sigs.Deriv.Deriv.Optim.SGD]
sub [Gpr_utils.Int_vec]
sum_mat [Gpr_utils]
sum_symm_mat [Gpr_utils]
symm2_sparse_trace [Gpr_utils]

T
test [Interfaces.Sigs.Deriv.Deriv.Optim.SMD]
test [Interfaces.Sigs.Deriv.Deriv.Optim.SGD]
timing [Gpr_utils]
train [Interfaces.Sigs.Deriv.Deriv.Optim.Gsl]
train ?step ?tol ?epsabs ?report_trained_model ?report_gradient_norm ?kernel ?sigma2 ?inducing ?n_rand_inducing ?learn_sigma2 ?hypers ~inputs ~targets () takes the optional initial optimizer step size step, the optimizer line search tolerance tol, the minimum gradient norm epsabs to achieve by the optimizer, callbacks for reporting intermediate results report_trained_model and report_gradient_norm, an optional kernel, noise level sigma2, inducing inputs inducing, number of randomly chosen inducing inputs n_rand_inducing, a flag for whether the noise level should be learnt learn_sigma2, an array of optional hyper parameters hypers which should be optimized, and the inputs and targets.

U
update_sigma2 [Interfaces.Sigs.Deriv.Deriv.Model]
update_sigma2 model sigma2
update_sigma2 [Interfaces.Sigs.Eval.Model]
update_sigma2 model sigma2

V
version [Version]

W
weighted_eval [Interfaces.Specs.Eval.Inputs]
weighted_eval kernel ~inputs ~inducing ~coeffs
weighted_eval [Interfaces.Specs.Eval.Input]
weighted_eval kernel input inducing ~coeffs