Index

A

ANN (class in pypr.ann.ann), [1]

B

boxpierce() (in module pypr.stattest.ljungbox), [1]

C

cfCovarianceFunction (class in pypr.gp.covar_funcs) cfJitter (class in pypr.gp.covar_funcs) cfNoise (class in pypr.gp.covar_funcs) cfSquaredExponentialARD (class in pypr.gp.covar_funcs) cfSquaredExponentialIso (class in pypr.gp.covar_funcs)

cfSum (class in pypr.gp.covar_funcs) clear_temp() (pypr.gp.covar_funcs.cfCovarianceFunction method) (pypr.gp.covar_funcs.cfSquaredExponentialARD method) (pypr.gp.covar_funcs.cfSum method) cond_dist() (in module pypr.clustering.gmm), [1] Cov_problem, [1]

D

derivative() (pypr.gp.covar_funcs.cfCovarianceFunction method) (pypr.gp.covar_funcs.cfJitter method) (pypr.gp.covar_funcs.cfNoise method) (pypr.gp.covar_funcs.cfSquaredExponentialARD method) (pypr.gp.covar_funcs.cfSquaredExponentialIso method) (pypr.gp.covar_funcs.cfSum method)

df() (pypr.gp.GaussianProcess.GPR method), [1]

E

em() (in module pypr.clustering.gmm), [1] em_gm() (in module pypr.clustering.gmm), [1] err_func() (pypr.helpers.modelwithdata.ModelWithData method)

err_func_d() (pypr.helpers.modelwithdata.ModelWithData method) error_with_weight_penalty() (pypr.ann.ann.WeightDecayANN method) eval() (pypr.gp.covar_funcs.cfCovarianceFunction method) (pypr.gp.covar_funcs.cfJitter method) (pypr.gp.covar_funcs.cfNoise method) (pypr.gp.covar_funcs.cfSquaredExponentialARD method) (pypr.gp.covar_funcs.cfSquaredExponentialIso method) (pypr.gp.covar_funcs.cfSum method)

F

f() (pypr.gp.GaussianProcess.GPR method), [1] find_centroids() (in module pypr.clustering.kmeans), [1] find_density_diff() (in module pypr.clustering.gmm), [1] find_distance() (in module pypr.clustering.kmeans), [1] find_flat_weight_no() (pypr.ann.ann.ANN method), [1] find_hyperparameters() (pypr.gp.GaussianProcess.GPR method), [1] find_intra_cluster_variance() (in module pypr.clustering.kmeans), [1]

find_likelihood_der() (pypr.gp.GaussianProcess method) (pypr.gp.GaussianProcess.GaussianProcess method), [1] find_membership() (in module pypr.clustering.kmeans), [1] find_weight() (pypr.ann.ann.ANN method), [1] fit_data() (pypr.gp.GaussianProcess method) (pypr.gp.GaussianProcess.GaussianProcess method), [1] forward() (pypr.ann.ann.ANN method), [1] forward_get_all() (pypr.ann.ann.ANN method), [1]

G

gauss_ellipse_2d() (in module pypr.clustering.gmm), [1] GaussianProcess (class in pypr.gp) (class in pypr.gp.GaussianProcess), [1] generate() (pypr.gp.GaussianProcess method) (pypr.gp.GaussianProcess.GaussianProcess method), [1] get_af_summed_weighs() (pypr.ann.ann.ANN method), [1] get_base_error_func() (pypr.ann.ann.ANN method), [1] get_eig() (pypr.preprocessing.PCA method) (pypr.preprocessing.pca.PCA method) get_error_func() (pypr.ann.ann.ANN method), [1] (pypr.ann.ann.WeightDecayANN method), [1] get_flat_weight() (pypr.ann.ann.ANN method), [1] get_flat_weights() (pypr.ann.ann.ANN method), [1] get_num_layers() (pypr.ann.ann.ANN method), [1] get_parameters() (pypr.helpers.modelwithdata.ModelWithData method)

get_params() (pypr.gp.covar_funcs.cfCovarianceFunction method) (pypr.gp.covar_funcs.cfJitter method) (pypr.gp.covar_funcs.cfNoise method) (pypr.gp.covar_funcs.cfSquaredExponentialARD method) (pypr.gp.covar_funcs.cfSquaredExponentialIso method) (pypr.gp.covar_funcs.cfSum method) get_weight_copy() (pypr.ann.ann.ANN method), [1] gm_assign_to_cluster() (in module pypr.clustering.gmm), [1] gm_log_likelihood() (in module pypr.clustering.gmm), [1] gmm_em_continue() (in module pypr.clustering.gmm), [1] gmm_init() (in module pypr.clustering.gmm), [1] gmm_pdf() (in module pypr.clustering.gmm), [1], [2] GPR (class in pypr.gp.GaussianProcess), [1] gradient() (pypr.ann.ann.ANN method), [1] (pypr.ann.ann.WeightDecayANN method) gradient_descent_train() (pypr.ann.ann.ANN method), [1]

I

invtransform() (pypr.preprocessing.Normalizer method) (pypr.preprocessing.PCA method) (pypr.preprocessing.normalizer.Normalizer method) (pypr.preprocessing.pca.PCA method)

K

k_fold_cross_validation() (in module pypr.helpers.helpers)

kmeans() (in module pypr.clustering.kmeans), [1]

L

lbqtest() (in module pypr.stattest.ljungbox), [1] ljungbox() (in module pypr.stattest.ljungbox), [1], [2]

logmulnormpdf() (in module pypr.clustering.gmm), [1]

M

marg_dist() (in module pypr.clustering.gmm), [1] minimize() (in module pypr.optimization), [1] (in module pypr.optimization.minimize) ModelWithData (class in pypr.helpers.modelwithdata)

MSE() (in module pypr.helpers.helpers) mulnormpdf() (in module pypr.clustering.gmm), [1]

N

Normalizer (class in pypr.preprocessing) (class in pypr.preprocessing.normalizer)

P

PCA (class in pypr.preprocessing) (class in pypr.preprocessing.pca) plot_gpr() (in module pypr.gp.plot_gp) predict() (in module pypr.clustering.gmm), [1] (pypr.gp.GaussianProcess.GPR method), [1] pypr.__init__ (module) pypr.ann (module) pypr.ann.activation_functions (module), [1] pypr.ann.ann (module), [1] pypr.ann.error_functions (module), [1] pypr.clustering (module) pypr.clustering.gmm (module), [1], [2], [3] pypr.clustering.kmeans (module), [1] pypr.gp (module) pypr.gp.covar_funcs (module) pypr.gp.GaussianProcess (module), [1] pypr.gp.gp_unit_tests (module)

pypr.gp.info (module) pypr.gp.plot_gp (module) pypr.helpers (module), [1] pypr.helpers.helpers (module) pypr.helpers.modelwithdata (module) pypr.helpers.wrappers (module), [1] pypr.optimization (module) pypr.optimization.minimize (module) pypr.preprocessing (module) pypr.preprocessing.normalizer (module) pypr.preprocessing.pca (module) pypr.stattest (module) pypr.stattest.ljungbox (module), [1], [2], [3] pypr.version (module)

R

regression() (pypr.gp.GaussianProcess method) (pypr.gp.GaussianProcess.GaussianProcess method), [1] RMSE() (in module pypr.helpers.helpers)

rosenbrock() (in module pypr.optimization.minimize) rosenbrock_d() (in module pypr.optimization.minimize)

S

sac() (in module pypr.stattest.ljungbox), [1], [2] sample_gaussian_mixture() (in module pypr.clustering.gmm), [1], [2] set_flat_weight() (pypr.ann.ann.ANN method), [1] set_flat_weights() (pypr.ann.ann.ANN method), [1] set_parameters() (pypr.helpers.modelwithdata.ModelWithData method)

set_params() (pypr.gp.covar_funcs.cfCovarianceFunction method) (pypr.gp.covar_funcs.cfJitter method) (pypr.gp.covar_funcs.cfNoise method) (pypr.gp.covar_funcs.cfSquaredExponentialARD method) (pypr.gp.covar_funcs.cfSquaredExponentialIso method) (pypr.gp.covar_funcs.cfSum method) setUp() (pypr.gp.gp_unit_tests.TestSequenceFunctions method) shuffle() (in module pypr.helpers.helpers) shuffle_rows() (in module pypr.helpers.helpers) sq_dist() (in module pypr.gp.covar_funcs)

T

test_cfNoise_derivative() (pypr.gp.gp_unit_tests.TestSequenceFunctions method) test_cfSquaredExponential_derivative() (pypr.gp.gp_unit_tests.TestSequenceFunctions method) test_cfSquaredExponentialARD_der() (pypr.gp.gp_unit_tests.TestSequenceFunctions method) test_cfSquaredExponentialArd_eval() (pypr.gp.gp_unit_tests.TestSequenceFunctions method) test_cfSquaredExponentialIso_eval() (pypr.gp.gp_unit_tests.TestSequenceFunctions method) test_generate() (pypr.gp.gp_unit_tests.TestSequenceFunctions method) test_GPR_partial_derivatives() (pypr.gp.gp_unit_tests.TestSequenceFunctions method) test_init_params() (pypr.gp.gp_unit_tests.TestSequenceFunctions method)

test_nllikeliness_and_der() (pypr.gp.gp_unit_tests.TestSequenceFunctions method) test_optimization() (pypr.gp.gp_unit_tests.TestSequenceFunctions method) test_regression() (pypr.gp.gp_unit_tests.TestSequenceFunctions method) test_set_params() (pypr.gp.gp_unit_tests.TestSequenceFunctions method) test_sq_dist() (pypr.gp.gp_unit_tests.TestSequenceFunctions method) test_sum_derivative() (pypr.gp.gp_unit_tests.TestSequenceFunctions method) TestSequenceFunctions (class in pypr.gp.gp_unit_tests) transform() (pypr.preprocessing.Normalizer method) (pypr.preprocessing.PCA method) (pypr.preprocessing.normalizer.Normalizer method) (pypr.preprocessing.pca.PCA method)

W

WeightDecayANN (class in pypr.ann.ann), [1]

wrap_model() (in module pypr.helpers.wrappers), [1]