├── .github └── workflows │ ├── black-ruff.yml │ ├── check-urls.yml │ ├── codeql.yml │ ├── documentation.yml │ ├── rstcheck.yml │ └── wheels-any.yml ├── .gitignore ├── .local.jenkins.lin.yml ├── CHANGELOGS.rst ├── LICENSE.txt ├── MANIFEST.in ├── README.rst ├── _doc ├── _static │ ├── git_logo.png │ └── project_ico.png ├── api │ ├── data.rst │ ├── graph.rst │ ├── image.rst │ ├── index.rst │ ├── ml.rst │ ├── modules │ │ ├── completion.rst │ │ ├── completion_simple.rst │ │ ├── graph_distance.rst │ │ ├── index.rst │ │ ├── kppv.rst │ │ ├── kppv_laesa.rst │ │ ├── logreg.rst │ │ ├── neural_tree.rst │ │ ├── poulet.rst │ │ ├── roc.rst │ │ └── sgd.rst │ ├── optim.rst │ └── text.rst ├── c_algo │ ├── bruit.png │ ├── edit_distance.rst │ ├── gest.rst │ ├── gradient--1.png │ ├── gradient-0.png │ ├── graph_distance.rst │ ├── images │ │ ├── graphmerge1.png │ │ └── graphmergeall.png │ ├── index.rst │ └── seg.png ├── c_clus │ ├── gauss_mixture.rst │ ├── images │ │ ├── class6.png │ │ ├── class_4.png │ │ ├── class_4_db.png │ │ ├── cm.png │ │ ├── herbin1.png │ │ ├── herbin2.png │ │ ├── kohov.png │ │ ├── koth1.png │ │ ├── koth2.png │ │ ├── liu3.png │ │ ├── zhang1.png │ │ ├── zhangc1.png │ │ ├── zhangc2.png │ │ └── zhangc3.png │ ├── index.rst │ ├── kmeans.rst │ └── kohonen.rst ├── c_garden │ ├── file_dattente.rst │ ├── images │ │ ├── poishis.png │ │ ├── poishist2.png │ │ ├── poishist3.png │ │ ├── poisson.png │ │ ├── poissonb.png │ │ ├── poissonb2.png │ │ ├── poissond.png │ │ └── poulet10.png │ ├── index.rst │ ├── quantization.rst │ └── strategie_avec_alea.rst ├── c_metric │ ├── images │ │ ├── pvaluescor.png │ │ └── pvaluescor2.png │ ├── index.rst │ ├── pvalues.rst │ ├── roc.rst │ └── rocimg │ │ ├── Roccurves.png │ │ ├── lecture_5_curve.png │ │ ├── lecture_intervalle.png │ │ ├── roc_1.png │ │ ├── roc_100.png │ │ ├── roc_3.png │ │ ├── roc_p100.png │ │ ├── rocwi.png │ │ ├── rocwi2.png │ │ ├── score_dist_1.png │ │ └── score_dist_2.png ├── c_ml │ ├── index.rst │ ├── index_reg_lin.rst │ ├── index_reg_log.rst │ ├── knnimg │ │ ├── btree.png │ │ ├── classif.png │ │ ├── rtree1.png │ │ └── rtree2.png │ ├── kppv.rst │ ├── l1l2.rst │ ├── lr_trees.rst │ ├── lr_voronoi.rst │ ├── lrtreesimg │ │ ├── bayes.png │ │ ├── hb.png │ │ └── mloc.png │ ├── lrvor │ │ ├── Coloured_Voronoi_2D.png │ │ ├── biss.png │ │ ├── hexa.png │ │ ├── hexa2.png │ │ ├── iris.png │ │ ├── partabc.png │ │ ├── vor2.png │ │ ├── vor4.png │ │ └── zoneangle.png │ ├── mfimg │ │ └── plan.jpg │ ├── missing_values_mf.rst │ ├── piecewise.rst │ ├── piecewise │ │ ├── piecenaive.png │ │ ├── piecenaive2.png │ │ └── voisin.png │ ├── qureg │ │ ├── mediane1.png │ │ ├── mediane2.png │ │ └── q02.png │ ├── regression_quantile.rst │ ├── rn │ │ ├── rn.rst │ │ ├── rn_1_def.rst │ │ ├── rn_2_reg.rst │ │ ├── rn_3_clas.rst │ │ ├── rn_4_densite.rst │ │ ├── rn_5_newton.rst │ │ ├── rn_6_apprentissage.rst │ │ ├── rn_7_clas2.rst │ │ ├── rn_8_prol.rst │ │ ├── rn_9_auto.rst │ │ ├── rn_biblio.rst │ │ └── rnimg │ │ │ ├── Conjugate_gradient_illustration.png │ │ │ ├── Roccurves.bmp │ │ │ ├── acp_inertie.png │ │ │ ├── backp.png │ │ │ ├── classificationnd.png │ │ │ ├── classificationnt.png │ │ │ ├── errapptest.png │ │ │ ├── errminloc.png │ │ │ ├── neurone2.jpg │ │ │ ├── regressionl.png │ │ │ ├── regressionnc.png │ │ │ ├── regressionnd.png │ │ │ ├── regressionnu.png │ │ │ ├── rn_clad.png │ │ │ ├── rn_courbe.png │ │ │ ├── rn_densite_idee.png │ │ │ ├── rn_diabolo.png │ │ │ ├── rn_gradient.png │ │ │ ├── rn_graphe_trans_1.png │ │ │ ├── rn_graphe_trans_2.png │ │ │ ├── rn_graphe_trans_3.png │ │ │ ├── rn_neurone.png │ │ │ └── selection_connexion.png │ └── survival_analysis.rst ├── c_nlp │ ├── completion.rst │ ├── completion_digression.rst │ ├── completion_fausse.rst │ ├── completion_formalisation.rst │ ├── completion_img │ │ ├── algocomp.png │ │ ├── comp.png │ │ ├── trieex.png │ │ └── wiki.png │ ├── completion_implementation.rst │ ├── completion_metrique.rst │ ├── completion_optimisation.rst │ ├── completion_propriete.rst │ └── index.rst ├── conf.py ├── defthe_index.rst ├── examples │ ├── README.txt │ └── plot_logistic_decision.py ├── glossary.rst ├── i_ex.rst ├── index.rst ├── license.rst └── notebooks │ ├── README.txt │ ├── dsgarden │ ├── classification_multiple.ipynb │ ├── correlation_non_lineaire.ipynb │ ├── discret_gradient.ipynb │ ├── file_dattente_ex.ipynb │ ├── index.rst │ ├── quantile_regression_example.ipynb │ ├── quantization_f8.ipynb │ ├── regression_lineaire.ipynb │ └── split_train_test.ipynb │ ├── image │ ├── eglise_zoom2.jpg │ ├── img.png │ ├── index.rst │ └── segment_detection.ipynb │ ├── index.rst │ ├── metric │ ├── index.rst │ ├── pvalues_examples.ipynb │ └── roc_example.ipynb │ ├── ml │ ├── index.rst │ ├── logreg_voronoi.ipynb │ ├── mf_acp.ipynb │ ├── neural_tree.ipynb │ ├── neural_tree_cost.ipynb │ ├── neural_tree_onnx.ipynb │ ├── piecewise_linear_regression.ipynb │ ├── regression_no_inversion.ipynb │ ├── reseau_neurones.ipynb │ ├── survival.ipynb │ └── valeurs_manquantes_mf.ipynb │ └── nlp │ ├── completion_profiling.ipynb │ ├── completion_simple.ipynb │ ├── completion_trie.ipynb │ ├── completion_trie_long.ipynb │ ├── images │ ├── completion.jpg │ ├── completion.png │ ├── func_info.jpg │ ├── func_info.png │ ├── vprof.gif │ ├── vprof.jpg │ └── vprof.png │ └── index.rst ├── _todo ├── clas_supervise │ ├── clas_super_biblio.tex │ └── clas_supervise.tex ├── classification │ ├── classification.tex │ ├── classification_bibliographie.tex │ ├── fig_cah.tex │ └── image │ │ ├── band21.png │ │ ├── band22.png │ │ ├── band23.png │ │ ├── band24.png │ │ ├── band25.png │ │ ├── band26.png │ │ ├── cah_ex.png │ │ ├── class6.png │ │ ├── class_4.png │ │ ├── class_4_db.png │ │ ├── cm.png │ │ ├── herbin1.png │ │ ├── herbin2.png │ │ ├── kohov.png │ │ ├── koth1.png │ │ ├── koth2.png │ │ ├── liu3.png │ │ ├── zhang1.png │ │ ├── zhangc1.png │ │ ├── zhangc2.png │ │ └── zhangc3.png ├── dessin1 │ ├── edition.ppt │ ├── edition_arbre.png │ ├── edition_arbre_3d.png │ ├── edition_arbre_niveau.png │ ├── edition_arbre_niveau_coupe.png │ ├── edition_espace_liste.png │ ├── graphem_erreur.png │ ├── général.ppt │ ├── hmm.ppt │ ├── hmm_ambiguite1.png │ ├── hmm_ambiguite2.png │ ├── hmm_exemple_decroissance.png │ ├── hmm_exemple_structure_10_C.png │ ├── hmm_exemple_structure_11_A.png │ ├── hmm_exemple_structure_12_B.png │ ├── hmm_exemple_structure_13_C.png │ ├── hmm_exemple_structure_14_D.png │ ├── hmm_exemple_structure_2.png │ ├── hmm_exemple_structure_3.png │ ├── hmm_exemple_structure_4.png │ ├── hmm_exemple_structure_5.png │ ├── hmm_exemple_structure_6_A.png │ ├── hmm_exemple_structure_7_B.png │ ├── hmm_exemple_structure_8_C.png │ ├── hmm_exemple_structure_9_D.png │ ├── image.ppt │ └── rn.ppt ├── dessin2 │ ├── acp_compression.png │ ├── acp_inertie.png │ ├── acp_inertie_carac.png │ ├── article_bi_lettre_at.png │ ├── article_bi_lettre_at_gr.png │ ├── article_dessin_1.png │ ├── article_dessin_2.png │ ├── article_dessin_3.png │ ├── article_dessin_4.png │ ├── article_dessin_6.png │ ├── article_dessin_7.png │ ├── article_dessin_8.png │ ├── article_dessin_9.png │ ├── caracteristique.png │ ├── chaine_markov_cachee_exemple.png │ ├── chaine_markov_etat_sortie.png │ ├── chaine_markov_exemple.png │ ├── classificationnd.png │ ├── classificationnt.png │ ├── edition_distance_demonstration.gif │ ├── edition_distance_demonstration.jpg │ ├── edition_distance_demonstration.png │ ├── edition_distance_demonstration.tif │ ├── edition_distance_ordins.png │ ├── edition_distance_parti_suc.png │ ├── edition_distance_partition.png │ ├── edition_distance_probleme.png │ ├── errapptest.png │ ├── errminloc.png │ ├── graphem_err_seg.png │ ├── graphem_sequence_lettre.png │ ├── grapheme.jpg │ ├── grapheme.png │ ├── grapheme_decoupe.jpg │ ├── grapheme_decoupe.png │ ├── hmm_alphabet_best_path.png │ ├── hmm_alphabet_schema.png │ ├── hmm_association_etat_obs_ex1.png │ ├── hmm_association_etat_obs_ex2.png │ ├── hmm_baumwelch_idee.png │ ├── hmm_distribution_etat1.png │ ├── hmm_distribution_etat2.png │ ├── hmm_duplication_1.png │ ├── hmm_duplication_2.png │ ├── hmm_duplication_3.png │ ├── hmm_duplication_cycle_100.png │ ├── hmm_duplication_emission_100.png │ ├── hmm_emission_ordre2.png │ ├── hmm_emission_ordre2_1.png │ ├── hmm_equivalence_theoreme1.png │ ├── hmm_equivalence_theoreme2.png │ ├── hmm_err_seg_sol1.png │ ├── hmm_err_seg_sol2.png │ ├── hmm_err_seg_sol3.png │ ├── hmm_etat_ne_equi1.png │ ├── hmm_etat_ne_equi2.png │ ├── hmm_etat_ne_ex_debut.png │ ├── hmm_etat_ne_ex_fin.png │ ├── hmm_etat_ne_srec1.png │ ├── hmm_etat_ne_srec2.png │ ├── hmm_etat_non_emetteur.png │ ├── hmm_etat_non_emetteur_alpha.png │ ├── hmm_etat_non_emetteur_dis.png │ ├── hmm_etat_presque_recurrent.png │ ├── hmm_exemple_final1.png │ ├── hmm_exemple_final1_iter1.png │ ├── hmm_exemple_final1_iter2.png │ ├── hmm_exemple_structure_1.png │ ├── hmm_factorisation_modele1.png │ ├── hmm_factorisation_modele2.png │ ├── hmm_groupe_1.png │ ├── hmm_groupe_2.png │ ├── hmm_hnn.png │ ├── hmm_imbrique.png │ ├── hmm_imbrique_schema_ab.png │ ├── hmm_impasse_1.png │ ├── hmm_impasse_2.png │ ├── hmm_iohmm.png │ ├── hmm_modele_dico.png │ ├── hmm_modele_mot1.png │ ├── hmm_modele_mot2.png │ ├── hmm_modele_non_minimal.png │ ├── hmm_modele_non_optimal.png │ ├── hmm_modele_oui_optimal.png │ ├── hmm_mot_bilettre.png │ ├── hmm_mot_bilettre_ce.png │ ├── hmm_mot_bilettre_ce_s.png │ ├── hmm_reciproque_1.png │ ├── hmm_reciproque_2.png │ ├── hmm_rejet_systeme.png │ ├── hmm_rn_ambigu.png │ ├── hmm_selection_croissance.png │ ├── hmm_viterbi_argmax.png │ ├── image_distance_droite.png │ ├── image_mot.png │ ├── image_mot_graphem_2.png │ ├── image_mot_statistique.png │ ├── imagemg.png │ ├── intro_apprentissage.png │ ├── mod_err_test_l_complex.png │ ├── mod_err_test_l_donnes.png │ ├── modele_test_courbe_reel1.png │ ├── modele_test_courbe_reel2.png │ ├── modele_test_exemple1.png │ ├── modele_test_exemple2.png │ ├── modele_test_exemple3.png │ ├── regressionl.png │ ├── regressionnc.png │ ├── regressionnd.png │ ├── regressionnu.png │ ├── rn_clad.png │ ├── rn_courbe.png │ ├── rn_densite_idee.png │ ├── rn_diabolo.png │ ├── rn_gradient.png │ ├── rn_graphe_trans_1.png │ ├── rn_graphe_trans_2.png │ ├── rn_graphe_trans_3.png │ ├── rn_neurone.png │ ├── selection_connexion.png │ ├── selection_emmanuel1.png │ └── selection_emmanuel2.png ├── edit_distance │ ├── edit_bibliographie.tex │ └── edit_distance.tex ├── hmm │ ├── fig_grmat.tex │ ├── fig_grmat2.tex │ ├── fig_hmarkov.tex │ ├── fig_markov.tex │ ├── hmm.tex │ ├── hmm_bibliographie.tex │ ├── hmm_chapter.tex │ └── hmm_titre.tex ├── image │ ├── image.tex │ ├── image │ │ ├── abusl.png │ │ ├── accentd.png │ │ ├── attitude1.png │ │ ├── attitude1.tif │ │ ├── attitude2.png │ │ ├── attitude2.tif │ │ ├── being.png │ │ ├── cheng.png │ │ ├── cloud_1.png │ │ ├── cloud_2.png │ │ ├── cloud_3.png │ │ ├── conal1.png │ │ ├── conal2.png │ │ ├── cutcut.png │ │ ├── cutwang.png │ │ ├── cutwang2.png │ │ ├── desol.png │ │ ├── droit_sec.png │ │ ├── epais.png │ │ ├── epaisseur.xls │ │ ├── failure.png │ │ ├── finalgrm1.png │ │ ├── finalgrm2.png │ │ ├── finalgrm3.png │ │ ├── finalgrm4.png │ │ ├── finalgrm5.png │ │ ├── global.png │ │ ├── grm_cut.png │ │ ├── grm_noel.png │ │ ├── grm_seg.png │ │ ├── grm_seg_bound.png │ │ ├── grm_seg_bound2.png │ │ ├── grmcut1.png │ │ ├── grmres.png │ │ ├── grmvalno.png │ │ ├── grtemp1.png │ │ ├── grtemp2.png │ │ ├── grtemp3.png │ │ ├── grtemp4.png │ │ ├── hawang1.png │ │ ├── hawang2.png │ │ ├── hawang3.png │ │ ├── histo_incl.png │ │ ├── histo_seg1.png │ │ ├── histo_seg2.png │ │ ├── histo_word.png │ │ ├── histo_wori.png │ │ ├── imslant.png │ │ ├── imslant_.png │ │ ├── imslants.png │ │ ├── koholine1.png │ │ ├── koholine2.png │ │ ├── lahs_black.png │ │ ├── lahsene.png │ │ ├── mbruit.png │ │ ├── nettoy.png │ │ ├── nettoy2.png │ │ ├── ppt.ppt │ │ ├── reser.png │ │ ├── restaure.png │ │ ├── restaure_au.png │ │ ├── restm.png │ │ ├── seg_appui_bad.png │ │ ├── seg_dir_gra.png │ │ ├── seggrm1.png │ │ ├── segline1.png │ │ ├── segline2.png │ │ ├── segline3.png │ │ ├── segline_appui.png │ │ ├── segline_appui2.png │ │ ├── segline_bad.png │ │ ├── slantst.png │ │ ├── smoothbo.png │ │ ├── smoothsaid.png │ │ ├── souligne.png │ │ ├── valaccent.png │ │ ├── valaccent2.png │ │ ├── valaccent3.png │ │ ├── valaccent4.png │ │ ├── valaccent5.png │ │ ├── valaccent6.png │ │ ├── valleyt.png │ │ ├── voronoi0.png │ │ ├── voronoi1.png │ │ ├── voronoi10.png │ │ ├── voronoi11.png │ │ └── voronoi2.png │ └── image_article.tex ├── ngrams │ ├── ngrams.tex │ └── ngrams_biblio.tex ├── segment_detection │ └── presentation.pdf ├── space_metric │ ├── fig_cah.tex │ ├── fig_ray.tex │ ├── fig_try1.tex │ ├── fig_try2.tex │ ├── image │ │ ├── btree.png │ │ ├── dhaes.png │ │ ├── rnd.png │ │ ├── rtree1.png │ │ └── rtree2.png │ ├── space_metric.tex │ └── space_metric_biblio.tex ├── squelette │ ├── fig_8mask1.tex │ ├── fig_8mask2.tex │ ├── fig_8mask3.tex │ ├── fig_8mask4.tex │ ├── fig_8mask5.tex │ ├── fig_8mask6.tex │ ├── fig_8mask7.tex │ ├── fig_choi.tex │ ├── fig_circle.tex │ ├── fig_conf1.tex │ ├── fig_conf2.tex │ ├── fig_freeman.tex │ ├── fig_mask1.tex │ ├── fig_mask2.tex │ ├── fig_maskfail.tex │ ├── fig_maskfail2.tex │ ├── fig_masksp1.tex │ ├── fig_masksp2.tex │ ├── fig_neib.tex │ ├── fig_nmask1.tex │ ├── fig_nmask2.tex │ ├── fig_nmask3.tex │ ├── image │ │ ├── abus.png │ │ ├── choi.png │ │ ├── cross1.png │ │ ├── cross2.png │ │ ├── cross3.png │ │ ├── cross4.png │ │ ├── image.ppt │ │ ├── kalmar1.png │ │ ├── kalmar2.png │ │ ├── lhomer.png │ │ ├── lhomer3.png │ │ ├── lhomer4.png │ │ ├── nuage.png │ │ ├── sing.png │ │ ├── sixstop.png │ │ ├── ske_appari.png │ │ ├── ske_barbule1.png │ │ ├── ske_barbule2.png │ │ ├── ske_bis.png │ │ ├── ske_connexe.png │ │ ├── ske_continu.png │ │ ├── ske_decentre.png │ │ ├── ske_example.png │ │ ├── ske_notcenter.png │ │ ├── ske_prenom.png │ │ ├── ske_veccorde.png │ │ ├── ske_vector.png │ │ ├── ske_voronoi.png │ │ ├── skevect2.png │ │ ├── su1.png │ │ ├── su2.png │ │ ├── su3.png │ │ ├── su4.png │ │ ├── su5.png │ │ ├── zhangs1.png │ │ ├── zhangs2.png │ │ └── zhangs3.png │ ├── squelette.tex │ ├── squelette_article.tex │ ├── squelette_chapter.tex │ └── squelette_titre.tex └── svm │ ├── image │ └── non.png │ ├── svm.tex │ └── svm_biblio.tex ├── _unittests ├── ut_data │ └── test_wikipedia_dump.py ├── ut_garden │ └── test_poulet.py ├── ut_graph │ ├── data │ │ └── graph.gv │ └── test_graph_distance.py ├── ut_image │ ├── data │ │ ├── eglise_zoom2.jpg │ │ ├── gradient--2.png │ │ └── gradient--2b.png │ ├── test_binom.py │ ├── test_geometrie.py │ ├── test_random_image.py │ └── test_segments.py ├── ut_ml │ ├── test_logreg.py │ ├── test_matrices.py │ ├── test_neural_tree.py │ ├── test_nuage_points.py │ ├── test_roc.py │ └── test_voronoi.py ├── ut_nlp │ ├── data │ │ ├── sample1000.txt │ │ ├── sample10000.txt │ │ ├── sample20000.txt │ │ ├── sample300.txt │ │ ├── sample_alpha_2.txt │ │ └── wikititles.txt │ ├── test_completion.py │ ├── test_completion_longer.py │ ├── test_completion_mks.py │ ├── test_completion_profiling.py │ ├── test_completion_simple.py │ └── test_completion_simple_optim.py ├── ut_optim │ └── test_optim.py └── ut_xrun_doc │ ├── test_documentation_examples.py │ ├── test_documentation_notebook.py │ ├── test_measure_time.py │ └── test_normalize_notebook.py ├── mlstatpy ├── __init__.py ├── data │ ├── __init__.py │ ├── data_exceptions.py │ └── wikipedia.py ├── ext_test_case.py ├── garden │ ├── __init__.py │ └── poulet.py ├── graph │ ├── __init__.py │ └── graph_distance.py ├── image │ ├── __init__.py │ └── detection_segment │ │ ├── __init__.py │ │ ├── detection_nfa.py │ │ ├── detection_segment.py │ │ ├── detection_segment_bord.py │ │ ├── detection_segment_segangle.py │ │ ├── geometrie.py │ │ ├── queue_binom.py │ │ └── random_image.py ├── ml │ ├── __init__.py │ ├── _neural_tree_api.py │ ├── _neural_tree_node.py │ ├── kppv.py │ ├── kppv_laesa.py │ ├── logreg.py │ ├── matrices.py │ ├── neural_tree.py │ ├── roc.py │ └── voronoi.py ├── nlp │ ├── __init__.py │ ├── completion.py │ ├── completion_simple.py │ └── normalize.py ├── optim │ ├── __init__.py │ └── sgd.py └── render_js_dot.py ├── pyproject.toml ├── requirements-dev.txt ├── requirements.txt ├── setup.cfg └── setup.py /.github/workflows/black-ruff.yml: -------------------------------------------------------------------------------- 1 | name: Black + Ruff Format Checker 2 | on: [push, pull_request] 3 | jobs: 4 | black-format-check: 5 | runs-on: ubuntu-latest 6 | steps: 7 | - uses: actions/checkout@v2 8 | - uses: psf/black@stable 9 | with: 10 | options: "--diff --check" 11 | src: "." 12 | ruff-format-check: 13 | runs-on: ubuntu-latest 14 | steps: 15 | - uses: actions/checkout@v3 16 | - uses: chartboost/ruff-action@v1 17 | -------------------------------------------------------------------------------- /.github/workflows/check-urls.yml: -------------------------------------------------------------------------------- 1 | name: Check URLs 2 | 3 | on: 4 | pull_request: 5 | branches: [main] 6 | schedule: 7 | # ┌───────────── minute (0 - 59) 8 | # │ ┌───────────── hour (0 - 23) 9 | # │ │ ┌───────────── day of the month (1 - 31) 10 | # │ │ │ ┌───────────── month (1 - 12 or JAN-DEC) 11 | # │ │ │ │ ┌───────────── day of the week (0 - 6 or SUN-SAT) 12 | # │ │ │ │ │ 13 | # │ │ │ │ │ 14 | # │ │ │ │ │ 15 | # * * * * * 16 | - cron: '30 1 * * 0' 17 | 18 | jobs: 19 | build: 20 | runs-on: ubuntu-latest 21 | 22 | steps: 23 | - uses: actions/checkout@v3 24 | 25 | - name: urls-checker-code 26 | uses: urlstechie/urlchecker-action@master 27 | with: 28 | subfolder: mlstatpy 29 | file_types: .md,.py,.rst,.ipynb 30 | print_all: false 31 | timeout: 5 32 | retry_count# : 3 33 | # exclude_urls: https://dumps.wikimedia.org/other/pageviews/%Y/%Y-%m/pageviews-%Y%m%d-%H0000.gz,https://dumps.wikimedia.org/frwiki/latest/latest-all-titles-in-ns0.gz 34 | exclude_patterns: https://dumps.wikimedia.org/ 35 | # force_pass : true 36 | 37 | - name: urls-checker-docs 38 | uses: urlstechie/urlchecker-action@master 39 | with: 40 | subfolder: _doc 41 | file_types: .md,.py,.rst,.ipynb 42 | print_all: false 43 | timeout: 5 44 | retry_count# : 3 45 | exclude_urls: https://hal.archives-ouvertes.fr/hal-00990252/document,https://github.com/onnx/models/raw/main/vision/classification/mobilenet/model/mobilenetv2-12.onnx,https://arxiv.org/ftp/arxiv/papers/1510/1510.04863.pdf,https://hal.science/hal-01125940 46 | exclude_patterns: https://www.data.gouv.fr/fr/datasets/r/e3d83ab3-dc52-4c99-abaf-8a38050cc68c,https://github.com/onnx/models/raw/main/vision/classification/mobilenet/model/mobilenetv2-12.onnx 47 | # force_pass : true 48 | -------------------------------------------------------------------------------- /.github/workflows/codeql.yml: -------------------------------------------------------------------------------- 1 | name: "Code Scanning - Action" 2 | 3 | on: 4 | push: 5 | branches: [main] 6 | pull_request: 7 | branches: [main] 8 | schedule: 9 | # ┌───────────── minute (0 - 59) 10 | # │ ┌───────────── hour (0 - 23) 11 | # │ │ ┌───────────── day of the month (1 - 31) 12 | # │ │ │ ┌───────────── month (1 - 12 or JAN-DEC) 13 | # │ │ │ │ ┌───────────── day of the week (0 - 6 or SUN-SAT) 14 | # │ │ │ │ │ 15 | # │ │ │ │ │ 16 | # │ │ │ │ │ 17 | # * * * * * 18 | - cron: '30 1 * * 0' 19 | 20 | jobs: 21 | CodeQL-Build: 22 | # CodeQL runs on ubuntu-latest, windows-latest, and macos-latest 23 | runs-on: ubuntu-latest 24 | 25 | permissions: 26 | # required for all workflows 27 | security-events: write 28 | 29 | # only required for workflows in private repositories 30 | actions: read 31 | contents: read 32 | 33 | steps: 34 | - name: Checkout repository 35 | uses: actions/checkout@v3 36 | 37 | # Initializes the CodeQL tools for scanning. 38 | - name: Initialize CodeQL 39 | uses: github/codeql-action/init@v2 40 | # Override language selection by uncommenting this and choosing your languages 41 | # with: 42 | # languages: go, javascript, csharp, python, cpp, java, ruby 43 | 44 | # Autobuild attempts to build any compiled languages (C/C++, C#, Go, or Java). 45 | # If this step fails, then you should remove it and run the build manually (see below). 46 | - name: Autobuild 47 | uses: github/codeql-action/autobuild@v2 48 | 49 | # ℹ️ Command-line programs to run using the OS shell. 50 | # 📚 See https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#jobsjob_idstepsrun 51 | 52 | # ✏️ If the Autobuild fails above, remove it and uncomment the following 53 | # three lines and modify them (or add more) to build your code if your 54 | # project uses a compiled language 55 | 56 | #- run: | 57 | # make bootstrap 58 | # make release 59 | 60 | - name: Perform CodeQL Analysis 61 | uses: github/codeql-action/analyze@v2 62 | -------------------------------------------------------------------------------- /.github/workflows/rstcheck.yml: -------------------------------------------------------------------------------- 1 | name: RST Check 2 | 3 | on: [push, pull_request] 4 | 5 | jobs: 6 | build_wheels: 7 | name: rstcheck ${{ matrix.os }} 8 | runs-on: ${{ matrix.os }} 9 | strategy: 10 | matrix: 11 | os: [ubuntu-latest] 12 | 13 | steps: 14 | - uses: actions/checkout@v3 15 | 16 | - uses: actions/setup-python@v4 17 | with: 18 | python-version: '3.11' 19 | 20 | - name: Install requirements 21 | run: python -m pip install -r requirements.txt 22 | 23 | - name: Install rstcheck 24 | run: python -m pip install sphinx tomli rstcheck[toml,sphinx] 25 | 26 | - name: rstcheck 27 | run: rstcheck -r _doc mlstatpy 28 | -------------------------------------------------------------------------------- /.github/workflows/wheels-any.yml: -------------------------------------------------------------------------------- 1 | name: Build Any Wheel 2 | 3 | on: 4 | push: 5 | branches: 6 | - main 7 | - 'releases/**' 8 | 9 | jobs: 10 | build_wheels: 11 | name: Build wheels on ${{ matrix.os }} 12 | runs-on: ${{ matrix.os }} 13 | strategy: 14 | matrix: 15 | os: [ubuntu-latest] 16 | 17 | steps: 18 | - uses: actions/checkout@v3 19 | 20 | - uses: actions/setup-python@v4 21 | with: 22 | python-version: '3.11' 23 | 24 | - name: build wheel 25 | run: python -m pip wheel . 26 | 27 | - uses: actions/upload-artifact@v4 28 | with: 29 | path: ./mlstatpy*.whl 30 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | *.dot 2 | *.dylib 3 | *.prof 4 | *.pyc 5 | *.pyd 6 | *.so 7 | *.gv 8 | *.gv.* 9 | *.jpg 10 | .coverage 11 | .eggs/* 12 | _cache/* 13 | build/* 14 | dist/* 15 | *egg-info/* 16 | onnxruntime_profile* 17 | prof 18 | temp_* 19 | .ipynb_checkpoints 20 | _doc/CHANGELOGS.rst 21 | _doc/sg_execution_times.rst 22 | _doc/LICENSE.txt 23 | _doc/auto_examples/* 24 | _doc/examples/_cache/* 25 | _doc/examples/onnxruntime_profile* 26 | _doc/examples/plot_*.png 27 | _doc/examples/plot_*.xlsx 28 | _doc/examples/data/*.optimized.onnx 29 | _doc/examples/*.html 30 | _doc/_static/require.js 31 | _doc/_static/viz.js 32 | _unittests/ut__main/*.png 33 | _unittests/ut__main/_cache/* 34 | _unittests/ut__main/*.html 35 | _unittests/.hypothesis/* 36 | _doc/notebooks/ml/*.onnx 37 | _doc/notebooks/dsgarden/*.onnx 38 | _doc/notebooks/nlp/frwiki-* 39 | _doc/notebooks/nlp/sample*.txt 40 | frwiki-* 41 | mobilenetv2-12.onnx 42 | sample1000.txt -------------------------------------------------------------------------------- /.local.jenkins.lin.yml: -------------------------------------------------------------------------------- 1 | 2 | language: python 3 | 4 | python: 5 | - { PATH: "{{Python39}}", VERSION: 3.9, DIST: std, PYINT: python3.9 } 6 | 7 | virtualenv: 8 | - path: {{ospathjoin(root_path, pickname("$NAME_JENKINS", project_name + "_$VERSION_$DIST_$NAME"), "_venv")}} 9 | 10 | install: 11 | - $PYINT -m pip install --upgrade pip 12 | - $PYINT -m pip install --upgrade --no-cache-dir --no-deps --index http://localhost:8067/simple/ scikit-learn>=0.24 --extra-index-url=https://pypi.python.org/simple/ 13 | - $PYINT -m pip install --upgrade --no-cache-dir --no-deps --index http://localhost:8067/simple/ mlinsights>=0.3 --extra-index-url=https://pypi.python.org/simple/ 14 | - $PYINT -m pip install -r requirements.txt 15 | - $PYINT -m pip install -r requirements-dev.txt 16 | - $PYINT --version 17 | - $PYINT -m pip freeze 18 | 19 | script: 20 | - { CMD: "$PYINT -m pytest _unittests --durations=10 --ignore-glob=**LONG*.py", NAME: "UT", TIMEOUT: 3000 } 21 | - { CMD: "$PYINT -m pytest _unittests/ut_run_long --durations=10", NAME: "UT", TIMEOUT: 7200 } 22 | 23 | after_script: 24 | - $PYINT -u setup.py bdist_wheel 25 | - if [ ${VERSION} == "3.9" and ${DIST} != "conda" and ${NAME} == "UT" ] then cp dist/*.whl {{root_path}}/../local_pypi/local_pypi_server fi 26 | 27 | documentation: 28 | - if [ ${NAME} == "UT" ] then $PYINT -u setup.py build_sphinx --layout=html fi 29 | - if [ ${NAME} == "UT" ] then cp -R -f _doc/sphinxdoc/build/html dist/html fi 30 | # - if [ ${NAME} == "UT" ] then cp -R -f _doc/sphinxdoc/build/elatex/*.pdf dist/html fi 31 | -------------------------------------------------------------------------------- /CHANGELOGS.rst: -------------------------------------------------------------------------------- 1 | Change Logs 2 | =========== 3 | 4 | 0.5.0 5 | +++++ 6 | 7 | 0.4.0 8 | +++++ 9 | 10 | * :pr:`42`: quantization 11 | * :pr:`39`: refactoring, use black, better documentation 12 | * :pr:`32`: Improves usability of distance_matching_graphs_paths (2021-08-10) 13 | * :pr:`31`: Links to notebooks are broken, notebooks slides are not working. (2021-03-31) 14 | * :pr:`30`: Fixes #26, implements a compact architecture (2021-01-23) 15 | * :pr:`26`: Aborder les régressions logistiques sous forme d'arbres (2021-01-23) 16 | * :pr:`27`: Convertir un arbre de décision en réseaux de neurones et apprendre (2020-08-31) 17 | * :pr:`25`: k-means norme L1 (2020-01-13) 18 | * :pr:`23`: uses function dtrtri to invert an upper triangular matrix in function linear_regression (2019-07-21) 19 | * :pr:`21`: implements streaming linear regression (2019-05-05) 20 | * :pr:`19`: removes dependency on line_profiler, not maintained anymore (2019-04-09) 21 | * :pr:`17`: move to CI to python 3.7 (2019-04-09) 22 | * :pr:`15`: add page on quantile regression + notebook (2019-02-02) 23 | * :pr:`2`: [won't fix] réseaux de neurones, utiliser des notations matricielles (2018-06-17) 24 | * :pr:`13`: fix bug: ValueError: label should be list-like and same length as y in ROC.plot (2018-05-17) 25 | * :pr:`12`: implements voronoi inference from a logistic regression solved with a linear regression (2018-05-08) 26 | * :pr:`11`: logistic regression and voronoi (2018-05-01) 27 | * :pr:`10`: add code on segment detection written a while ago (2018-04-18) 28 | * :pr:`9`: fix unittest on wikipedia_dump after a change on wikipedia website (2018-04-01) 29 | * :pr:`4`: implémentation la complétion en C++ (2016-09-25) 30 | * :pr:`1`: ajouter les petits exposés finance... (2016-06-29) 31 | -------------------------------------------------------------------------------- /LICENSE.txt: -------------------------------------------------------------------------------- 1 | Copyright (c) 2016-2024, Xavier Dupré 2 | 3 | Permission is hereby granted, free of charge, to any person obtaining a copy 4 | of this software and associated documentation files (the "Software"), to deal 5 | in the Software without restriction, including without limitation the rights 6 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 7 | copies of the Software, and to permit persons to whom the Software is 8 | furnished to do so, subject to the following conditions: 9 | 10 | The above copyright notice and this permission notice shall be included in 11 | all copies or substantial portions of the Software. 12 | 13 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 14 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 15 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 16 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 17 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 18 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN 19 | THE SOFTWARE. -------------------------------------------------------------------------------- /MANIFEST.in: -------------------------------------------------------------------------------- 1 | recursive-include onnx_extended *.c *.cpp *.h *.pyx *.pxd *.pxi *.py 2 | include pyproject.toml 3 | include MANIFEST.in 4 | include setup.cfg 5 | prune _doc 6 | prune _todo 7 | prune _unittests 8 | prune bin 9 | prune .circleci 10 | exclude *.bat 11 | exclude *.yml 12 | exclude *.git* 13 | -------------------------------------------------------------------------------- /README.rst: -------------------------------------------------------------------------------- 1 | 2 | .. image:: https://github.com/sdpython/sphinx-runpython/raw/main/_doc/_static/logo.png 3 | :width: 120 4 | 5 | mlstatpy: détours mathématiques autour du machine learning 6 | ========================================================== 7 | 8 | .. image:: https://ci.appveyor.com/api/projects/status/5env33qptorgshaq?svg=true 9 | :target: https://ci.appveyor.com/project/sdpython/mlstatpy 10 | :alt: Build Status Windows 11 | 12 | .. image:: https://circleci.com/gh/sdpython/mlstatpy/tree/main.svg?style=svg 13 | :target: https://circleci.com/gh/sdpython/mlstatpy/tree/main 14 | 15 | .. image:: https://badge.fury.io/py/mlstatpy.svg 16 | :target: https://pypi.org/project/mlstatpy/ 17 | 18 | .. image:: https://img.shields.io/badge/license-MIT-blue.svg 19 | :alt: MIT License 20 | :target: https://opensource.org/license/MIT/ 21 | 22 | .. image:: https://codecov.io/github/sdpython/mlstatpy/coverage.svg 23 | :target: https://codecov.io/github/sdpython/mlstatpy/ 24 | 25 | .. image:: http://img.shields.io/github/issues/sdpython/mlstatpy.png 26 | :alt: GitHub Issues 27 | :target: https://github.com/sdpython/mlstatpy/issues 28 | 29 | Le module contient essentiellement des digressions mathématiques 30 | autour du machine learning. Parmi les choses intéressantes, 31 | une courbe *ROC* avec intervalle de confiance, détection 32 | automatique de segment dans une image, un algorithme 33 | d'autocomplétion, une distance d'édition entre graphes, 34 | des petites choses pour les données de Wikipedia, 35 | un algorithme de conversion d'un arbre de décision en 36 | réseaux de neurones. 37 | 38 | The package mostly contains documentation. It also implements 39 | some code rarely needed such as ROC curve with bandwidth, 40 | automated segment detection in a image, some simple autocomplete 41 | algorithm, a graph edit distance, some helpers on Wikipedia data, 42 | an algorithm to convert decision trees into neural network. 43 | 44 | * `documentation `_ 45 | -------------------------------------------------------------------------------- /_doc/_static/git_logo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/_doc/_static/git_logo.png -------------------------------------------------------------------------------- /_doc/_static/project_ico.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/_doc/_static/project_ico.png -------------------------------------------------------------------------------- /_doc/api/data.rst: -------------------------------------------------------------------------------- 1 | 2 | Source de données 3 | ================= 4 | 5 | Wikipédia 6 | +++++++++ 7 | 8 | .. autofunction:: mlstatpy.data.wikipedia.download_dump 9 | 10 | .. autofunction:: mlstatpy.data.wikipedia.download_pageviews 11 | 12 | .. autofunction:: mlstatpy.data.wikipedia.download_titles 13 | 14 | .. autofunction:: mlstatpy.data.wikipedia.enumerate_titles 15 | -------------------------------------------------------------------------------- /_doc/api/graph.rst: -------------------------------------------------------------------------------- 1 | 2 | Graphes 3 | ======= 4 | 5 | Distance 6 | ++++++++ 7 | 8 | .. autoclass:: mlstatpy.graph.graph_distance.GraphDistance 9 | :members: distance_matching_graphs_paths 10 | :noindex: 11 | -------------------------------------------------------------------------------- /_doc/api/image.rst: -------------------------------------------------------------------------------- 1 | 2 | Image 3 | ===== 4 | 5 | Conversion 6 | ++++++++++ 7 | 8 | .. autofunction:: mlstatpy.image.detection_segment.detection_segment.convert_array2PIL 9 | 10 | .. autofunction:: mlstatpy.image.detection_segment.detection_segment.convert_PIL2array 11 | 12 | Images aléatoires 13 | +++++++++++++++++ 14 | 15 | .. autofunction:: mlstatpy.image.detection_segment.random_image.random_noise_image 16 | 17 | .. autofunction:: mlstatpy.image.detection_segment.random_image.random_segment_image 18 | 19 | Segments 20 | ++++++++ 21 | 22 | .. autofunction:: mlstatpy.image.detection_segment.detection_segment.detect_segments 23 | 24 | .. autofunction:: mlstatpy.image.detection_segment.detection_segment.plot_segments 25 | -------------------------------------------------------------------------------- /_doc/api/index.rst: -------------------------------------------------------------------------------- 1 | 2 | API 3 | === 4 | 5 | .. toctree:: 6 | :maxdepth: 2 7 | 8 | ml 9 | optim 10 | text 11 | data 12 | graph 13 | image 14 | modules/index 15 | -------------------------------------------------------------------------------- /_doc/api/ml.rst: -------------------------------------------------------------------------------- 1 | 2 | Machine Learning 3 | ================ 4 | 5 | Matrices 6 | ++++++++ 7 | 8 | .. autofunction:: mlstatpy.ml.matrices.gram_schmidt 9 | 10 | .. autofunction:: mlstatpy.ml.matrices.linear_regression 11 | 12 | .. autofunction:: mlstatpy.ml.matrices.streaming_gram_schmidt_update 13 | 14 | .. autofunction:: mlstatpy.ml.matrices.streaming_gram_schmidt 15 | 16 | .. autofunction:: mlstatpy.ml.matrices.streaming_linear_regression_update 17 | 18 | .. autofunction:: mlstatpy.ml.matrices.streaming_linear_regression 19 | 20 | .. autofunction:: mlstatpy.ml.matrices.streaming_linear_regression_gram_schmidt_update 21 | 22 | .. autofunction:: mlstatpy.ml.matrices.streaming_linear_regression_gram_schmidt 23 | 24 | Métriques 25 | +++++++++ 26 | 27 | .. autoclass:: mlstatpy.ml.roc.ROC 28 | :noindex: 29 | 30 | .. autofunction:: mlstatpy.ml.voronoi.voronoi_estimation_from_lr 31 | 32 | Plus proches voisins 33 | ++++++++++++++++++++ 34 | 35 | .. autoclass:: mlstatpy.ml.kppv.NuagePoints 36 | :noindex: 37 | 38 | .. autoclass:: mlstatpy.ml.kppv_laesa.NuagePointsLaesa 39 | :noindex: 40 | 41 | Tree and neural networks 42 | ++++++++++++++++++++++++ 43 | 44 | .. autoclass:: mlstatpy.ml._neural_tree_node.NeuralTreeNode 45 | :noindex: 46 | 47 | .. autoclass:: mlstatpy.ml.neural_tree.NeuralTreeNet 48 | :noindex: 49 | 50 | .. autoclass:: mlstatpy.ml.neural_tree.BaseNeuralTreeNet 51 | :noindex: 52 | 53 | .. autoclass:: mlstatpy.ml.neural_tree.NeuralTreeNetClassifier 54 | :noindex: 55 | 56 | .. autoclass:: mlstatpy.ml.neural_tree.NeuralTreeNetRegressor 57 | :noindex: 58 | -------------------------------------------------------------------------------- /_doc/api/modules/completion.rst: -------------------------------------------------------------------------------- 1 | mlstatpy.nlp.completion 2 | ======================= 3 | 4 | .. automodule:: mlstatpy.nlp.completion 5 | :members: 6 | -------------------------------------------------------------------------------- /_doc/api/modules/completion_simple.rst: -------------------------------------------------------------------------------- 1 | mlstatpy.nlp.completion_simple 2 | ============================== 3 | 4 | .. automodule:: mlstatpy.nlp.completion_simple 5 | :members: 6 | -------------------------------------------------------------------------------- /_doc/api/modules/graph_distance.rst: -------------------------------------------------------------------------------- 1 | mlstatpy.graph.graph_distance 2 | ============================= 3 | 4 | .. automodule:: mlstatpy.graph.graph_distance 5 | :members: 6 | -------------------------------------------------------------------------------- /_doc/api/modules/index.rst: -------------------------------------------------------------------------------- 1 | ======= 2 | Modules 3 | ======= 4 | 5 | .. toctree:: 6 | :maxdepth: 1 7 | 8 | poulet 9 | graph_distance 10 | kppv 11 | kppv_laesa 12 | logreg 13 | neural_tree 14 | roc 15 | completion 16 | completion_simple 17 | sgd 18 | -------------------------------------------------------------------------------- /_doc/api/modules/kppv.rst: -------------------------------------------------------------------------------- 1 | mlstatpy.ml.kppv 2 | ================ 3 | 4 | .. automodule:: mlstatpy.ml.kppv 5 | :members: 6 | -------------------------------------------------------------------------------- /_doc/api/modules/kppv_laesa.rst: -------------------------------------------------------------------------------- 1 | mlstatpy.ml.kppv_laesa 2 | ====================== 3 | 4 | .. automodule:: mlstatpy.ml.kppv_laesa 5 | :members: 6 | -------------------------------------------------------------------------------- /_doc/api/modules/logreg.rst: -------------------------------------------------------------------------------- 1 | mlstatpy.ml.logreg 2 | ================== 3 | 4 | .. automodule:: mlstatpy.ml.logreg 5 | :members: 6 | -------------------------------------------------------------------------------- /_doc/api/modules/neural_tree.rst: -------------------------------------------------------------------------------- 1 | mlstatpy.ml.neural_tree 2 | ======================= 3 | 4 | .. automodule:: mlstatpy.ml.neural_tree 5 | :members: 6 | 7 | .. automodule:: mlstatpy.ml._neural_tree_node 8 | :members: NeuralTreeNode 9 | 10 | .. automodule:: mlstatpy.ml._neural_tree_api 11 | :members: _TrainingAPI 12 | -------------------------------------------------------------------------------- /_doc/api/modules/poulet.rst: -------------------------------------------------------------------------------- 1 | mlstatpy.garden.poulet 2 | ====================== 3 | 4 | .. automodule:: mlstatpy.garden.poulet 5 | :members: 6 | -------------------------------------------------------------------------------- /_doc/api/modules/roc.rst: -------------------------------------------------------------------------------- 1 | mlstatpy.ml.roc 2 | =============== 3 | 4 | .. automodule:: mlstatpy.ml.roc 5 | :members: 6 | -------------------------------------------------------------------------------- /_doc/api/modules/sgd.rst: -------------------------------------------------------------------------------- 1 | mlstatpy.optim.sgd 2 | ================== 3 | 4 | .. automodule:: mlstatpy.optim.sgd 5 | :members: 6 | -------------------------------------------------------------------------------- /_doc/api/optim.rst: -------------------------------------------------------------------------------- 1 | 2 | Optimisation 3 | ================ 4 | 5 | Gradient 6 | ++++++++ 7 | 8 | .. autoclass:: mlstatpy.optim.sgd.SGDOptimizer 9 | :noindex: 10 | -------------------------------------------------------------------------------- /_doc/api/text.rst: -------------------------------------------------------------------------------- 1 | Traitement du langage naturel 2 | ============================= 3 | 4 | Complétion 5 | ++++++++++ 6 | 7 | .. autoclass:: mlstatpy.nlp.completion_simple.CompletionElement 8 | :members: 9 | :noindex: 10 | 11 | .. autoclass:: mlstatpy.nlp.completion_simple.CompletionSystem 12 | :members: 13 | :noindex: 14 | 15 | Normalisation 16 | +++++++++++++ 17 | 18 | .. autofunction:: mlstatpy.data.wikipedia.normalize_wiki_text 19 | 20 | .. autofunction:: mlstatpy.nlp.normalize.remove_diacritics 21 | -------------------------------------------------------------------------------- /_doc/c_algo/bruit.png: -------------------------------------------------------------------------------- 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-------------------------------------------------------------------------------- /_doc/c_garden/index.rst: -------------------------------------------------------------------------------- 1 | 2 | ############## 3 | Pérégrinations 4 | ############## 5 | 6 | Ce sont quelques notebooks sur des points particuliers 7 | qui surgissent au quotidien quand on traite des données. 8 | Souvent plus pratiques que théoriques, c'est l'occasion de 9 | découvrir quelques poussières sous le tapis. 10 | 11 | .. toctree:: 12 | :maxdepth: 1 13 | 14 | ../notebooks/dsgarden/split_train_test 15 | ../notebooks/dsgarden/correlation_non_lineaire 16 | file_dattente 17 | strategie_avec_alea 18 | ../notebooks/dsgarden/discret_gradient 19 | quantization 20 | ../notebooks/dsgarden/classification_multiple 21 | 22 | -------------------------------------------------------------------------------- /_doc/c_metric/images/pvaluescor.png: -------------------------------------------------------------------------------- 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missing_values_mf 17 | ../notebooks/ml/neural_tree 18 | ../notebooks/ml/neural_tree_onnx 19 | ../notebooks/ml/neural_tree_cost 20 | -------------------------------------------------------------------------------- /_doc/c_ml/index_reg_lin.rst: -------------------------------------------------------------------------------- 1 | 2 | .. _l-reglin-variations: 3 | 4 | ################### 5 | Régression linéaire 6 | ################### 7 | 8 | La `régression linéaire `_ 9 | est le modèle prédictif le plus simple et celui qu'on préfère 10 | quand il marche car il est facilement interprétable à l'inverse 11 | des modèles non linéaires qui gardent leurs secrets si on s'en tient 12 | seulement à leurs coefficients. Concrètement, on dispose d'un nuage 13 | de point :math:`(X_i, y_i)` où :math:`X_i \in \mathbb{R}^d` est un vecteur 14 | de dimension *d* et :math:`y_i \in \mathbb{R}` un réel. La régression 15 | linéaire consiste à construire une fonction prédictive 16 | :math:`\hat{y_i} = f(X_i) = = X_i \beta` où 17 | :math:`\beta` est un vecteur de dimension *d*. Dans le cas le plus 18 | courant, on modélise les données de telle sorte que : 19 | :math:`y_i = X_i \beta + \epsilon_i` où :math:`\epsilon_i` 20 | suit une loi normale de moyenne nulle et de variance :math:`\sigma`. 21 | Sous cette hypothèse, il 'agit de trouver le vecteur :math:`\beta` 22 | qui minimise la vraisemblance du modèle, ce qui revient à résoudre 23 | le problème d'optimisation : 24 | 25 | .. math:: 26 | 27 | \min_\beta \sum_i (y_i - X_i \beta)^2 28 | 29 | En dérivant, on sait exprimer explicitement la solution. 30 | On note :math:`X = (X_1, ..., X_i, ...)` la matrice où chaque ligne 31 | est une observation :math:`X_i` et :math:`y = (y_1, ..., y_i, ...)`. 32 | :math:`X'` est la transposée de *X*. Alors : 33 | 34 | .. math:: 35 | 36 | \beta_* = (X'X)^{-1}X'y 37 | 38 | Les chapitres suivants explorent d'autres aspects de ce problèmes 39 | comme la régression quantile, la régression linéaire par morceaux, 40 | ou encore l'expression de :math:`\beta` sans calculer de matrice inverse 41 | ni de valeurs propres. 42 | 43 | .. toctree:: 44 | :maxdepth: 1 45 | 46 | ../notebooks/dsgarden/regression_lineaire 47 | regression_quantile 48 | piecewise 49 | l1l2 50 | -------------------------------------------------------------------------------- /_doc/c_ml/index_reg_log.rst: -------------------------------------------------------------------------------- 1 | 2 | .. _l-reglog-variations: 3 | 4 | ##################### 5 | Régression logistique 6 | ##################### 7 | 8 | La `régression logistique `_ 9 | est le modèle prédictif le plus simple et celui qu'on préfère 10 | quand il marche car il est facilement interprétable à l'inverse 11 | des modèles non linéaires qui gardent leurs secrets si on s'en tient 12 | seulement à leurs coefficients. Concrètement, on dispose d'un nuage 13 | de point :math:`(X_i, y_i)` où :math:`X_i \in \mathbb{R}^d` est un vecteur 14 | de dimension *d* et :math:`y_i \in \acc{0, 1}` un entier binaire. 15 | Le problème de la régression linéaire consiste à 16 | construire une fonction prédictive 17 | :math:`\hat{y_i} = f(X_i) = = X_i \beta` où 18 | :math:`\beta` est un vecteur de dimension *d* 19 | (voir `classification 20 | `_). 21 | Le signe de la fonction :math:`f(X_i)` 22 | indique la classe de l'observation :math:`X_i` et la valeur 23 | :math:`\frac{1}{1 + e^{f(X)}}` la probabilité d'être dans la classe 1. 24 | 25 | .. toctree:: 26 | :maxdepth: 1 27 | 28 | lr_voronoi 29 | lr_trees 30 | ../notebooks/ml/reseau_neurones 31 | survival_analysis 32 | -------------------------------------------------------------------------------- /_doc/c_ml/knnimg/btree.png: -------------------------------------------------------------------------------- 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L'utilisateur saisit plus rapidement. 13 | 14 | .. image:: completion_img/wiki.png 15 | 16 | Si ces outils sont appréciables du point de vue utilisateurs, 17 | ils le sont tout autant côté site web en réduisant la variabilité dans 18 | le texte saisie, en particulier les fautes d'orthographes. L'utilisateur 19 | a besoin de moins de requêtes pour trouver son produits et cela diminue 20 | d'autant la charge du serveur qui lui fournit ses résultats. 21 | 22 | Ce chapitre aborde différentes problématiques liées à ce genre de systèmes 23 | qui sont présents partout sur Internet, 24 | moteurs de recherches, sites de ventes en ligne, journaux... 25 | Il existe de nombreuses librairies qui les implémentent. 26 | La plus connue en Python est `whoosh `_. 27 | 28 | Quelques éléments de codes sont disponibles dans le module 29 | :mod:`completion ` et le notebook 30 | :ref:`/notebooks/nlp/completion_trie.ipynb`. Vous pouvez également lire 31 | `How to Write a Spelling Corrector `_ 32 | de `Peter Norvig `_ et découvrir le sujet 33 | avec `On User Interactions with Query Auto-Completion 34 | `_ 35 | de Bhaskar Mitra, Milad Shokouhi, Filip Radlinski, Katja Hofmann. 36 | 37 | .. toctree:: 38 | :maxdepth: 1 39 | 40 | completion_formalisation 41 | completion_fausse 42 | completion_metrique 43 | completion_propriete 44 | completion_optimisation 45 | completion_implementation 46 | completion_digression 47 | 48 | Notebooks associés : 49 | 50 | .. toctree:: 51 | 52 | ../notebooks/nlp/completion_trie 53 | ../notebooks/nlp/completion_profiling 54 | ../notebooks/nlp/completion_trie_long 55 | ../notebooks/nlp/completion_simple 56 | -------------------------------------------------------------------------------- /_doc/c_nlp/completion_img/algocomp.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/_doc/c_nlp/completion_img/algocomp.png -------------------------------------------------------------------------------- /_doc/c_nlp/completion_img/comp.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/_doc/c_nlp/completion_img/comp.png -------------------------------------------------------------------------------- /_doc/c_nlp/completion_img/trieex.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/_doc/c_nlp/completion_img/trieex.png -------------------------------------------------------------------------------- /_doc/c_nlp/completion_img/wiki.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/_doc/c_nlp/completion_img/wiki.png -------------------------------------------------------------------------------- /_doc/c_nlp/index.rst: -------------------------------------------------------------------------------- 1 | 2 | ### 3 | NLP 4 | ### 5 | 6 | NLP ou Natural Language Processing 7 | u `traitement du langage naturel 8 | `_. 10 | 11 | .. toctree:: 12 | :maxdepth: 1 13 | 14 | completion 15 | -------------------------------------------------------------------------------- /_doc/defthe_index.rst: -------------------------------------------------------------------------------- 1 | 2 | Listes des définitions et théorèmes 3 | =================================== 4 | 5 | Corollaires 6 | +++++++++++ 7 | 8 | .. mathdeflist:: 9 | :tag: Corollaire 10 | 11 | Définitions 12 | +++++++++++ 13 | 14 | .. mathdeflist:: 15 | :tag: Définition 16 | 17 | Lemmes 18 | ++++++ 19 | 20 | .. mathdeflist:: 21 | :tag: Lemme 22 | 23 | Figures 24 | +++++++ 25 | 26 | .. mathdeflist:: 27 | :tag: Figure 28 | 29 | Problèmes 30 | +++++++++ 31 | 32 | .. mathdeflist:: 33 | :tag: Problème 34 | 35 | Propriétés 36 | ++++++++++ 37 | 38 | .. mathdeflist:: 39 | :tag: Problème 40 | 41 | Tables 42 | ++++++ 43 | 44 | .. mathdeflist:: 45 | :tag: Table 46 | 47 | Théorèmes 48 | +++++++++ 49 | 50 | .. mathdeflist:: 51 | :tag: Théorème 52 | -------------------------------------------------------------------------------- /_doc/examples/README.txt: -------------------------------------------------------------------------------- 1 | .. _examples-gallery: 2 | 3 | Gallery of examples 4 | =================== 5 | 6 | -------------------------------------------------------------------------------- /_doc/glossary.rst: -------------------------------------------------------------------------------- 1 | 2 | .. index:: glossary 3 | 4 | Glossary 5 | ======== 6 | 7 | .. glossary:: 8 | 9 | ml 10 | Raccourci pour `Machine Learning `_. 11 | 12 | NLP 13 | Raccourci pour `Natural Language Processing `_. 14 | 15 | outlier 16 | Point aberrant. C'est une observation qui est à l'écart des autres observations 17 | du jeu de données de façon évidente. Il perturbe l'apprentissage d'une prédiction. 18 | -------------------------------------------------------------------------------- /_doc/i_ex.rst: -------------------------------------------------------------------------------- 1 | 2 | .. _l-EX2: 3 | 4 | Examples 5 | ======== 6 | 7 | .. exreflist:: 8 | :contents: 9 | -------------------------------------------------------------------------------- /_doc/index.rst: -------------------------------------------------------------------------------- 1 | 2 | *en construction permanente* 3 | 4 | .. |gitlogo| image:: _static/git_logo.png 5 | :height: 20 6 | 7 | Les maths d'abord, la programmation ensuite 8 | =========================================== 9 | 10 | Le livre `The Elements of Statistical Learning `_ 11 | est considéré comme la bible en matière de machine learning. Ce site aborde des sujets connexes. 12 | Le site est aussi disponible (format brut de fonderie) sur 13 | `GitHub/mlstatpy `_ |gitlogo|. 14 | 15 | .. toctree:: 16 | :maxdepth: 1 17 | :caption: Mathematics 18 | 19 | c_clus/index 20 | c_ml/index 21 | c_ml/index_reg_lin 22 | c_ml/index_reg_log 23 | c_nlp/index 24 | c_metric/index 25 | c_algo/index 26 | c_garden/index 27 | 28 | .. toctree:: 29 | :maxdepth: 1 30 | :caption: Examples 31 | 32 | api/index 33 | i_ex 34 | defthe_index 35 | auto_examples/index 36 | notebooks/index 37 | 38 | .. toctree:: 39 | :maxdepth: 1 40 | :caption: More 41 | 42 | glossary 43 | CHANGELOGS 44 | license 45 | genindex 46 | modindex 47 | search 48 | 49 | On fait beaucoup de choses avec l'informatique mais en pratique 50 | on doit maintenir, on doit réécrire sans cesse. 51 | Faire un peu de théorie ça repose. 52 | 53 | Xavier Dupré 54 | 55 | .. only:: html 56 | 57 | .. image:: https://ci.appveyor.com/api/projects/status/5env33qptorgshaq?svg=true 58 | :target: https://ci.appveyor.com/project/sdpython/mlstatpy 59 | :alt: Build Status Windows 60 | 61 | .. image:: https://circleci.com/gh/sdpython/mlstatpy/tree/main.svg?style=svg 62 | :target: https://circleci.com/gh/sdpython/mlstatpy/tree/main 63 | 64 | .. image:: https://badge.fury.io/py/mlstatpy.svg 65 | :target: https://pypi.org/project/mlstatpy/ 66 | 67 | .. image:: https://img.shields.io/badge/license-MIT-blue.svg 68 | :alt: MIT License 69 | :target: https://opensource.org/license/MIT/ 70 | 71 | .. image:: https://codecov.io/github/sdpython/mlstatpy/coverage.svg 72 | :target: https://codecov.io/github/sdpython/mlstatpy 73 | 74 | .. image:: http://img.shields.io/github/issues/sdpython/mlstatpy.png 75 | :alt: GitHub Issues 76 | :target: https://github.com/sdpython/mlstatpy/issues 77 | 78 | Older versions 79 | ++++++++++++++ 80 | 81 | * `0.4.0 <../v0.4.0/index.html>`_ 82 | -------------------------------------------------------------------------------- /_doc/license.rst: -------------------------------------------------------------------------------- 1 | .. _l-license: 2 | 3 | License 4 | ======= 5 | 6 | .. literalinclude:: LICENSE.txt 7 | :language: none 8 | -------------------------------------------------------------------------------- /_doc/notebooks/README.txt: -------------------------------------------------------------------------------- 1 | Galleries 2 | ========= 3 | 4 | -------------------------------------------------------------------------------- /_doc/notebooks/dsgarden/index.rst: -------------------------------------------------------------------------------- 1 | Le petit coin des data scientists 2 | ================================= 3 | 4 | Ce sont quelques notebooks sur des points particuliers 5 | qui surgissent au quotidien quand on traite des données. 6 | 7 | .. nbgallery:: 8 | :caption: Notebooks Gallery 9 | :name: rst-nb-gallery-dsgarden 10 | :glob: 11 | 12 | * 13 | 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-------------------------------------------------------------------------------- /_doc/notebooks/index.rst: -------------------------------------------------------------------------------- 1 | Galleries de notebooks 2 | ====================== 3 | 4 | .. toctree:: 5 | :maxdepth: 2 6 | 7 | dsgarden/index 8 | image/index 9 | metric/index 10 | ml/index 11 | nlp/index 12 | -------------------------------------------------------------------------------- /_doc/notebooks/metric/index.rst: -------------------------------------------------------------------------------- 1 | Métriques 2 | ========= 3 | 4 | .. nbgallery:: 5 | :caption: Notebooks Gallery 6 | :name: rst-nb-gallery-metric 7 | :glob: 8 | 9 | * 10 | -------------------------------------------------------------------------------- /_doc/notebooks/ml/index.rst: -------------------------------------------------------------------------------- 1 | Machine Learning 2 | ================ 3 | 4 | .. nbgallery:: 5 | :caption: Notebooks Gallery 6 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-------------------------------------------------------------------------------- 1 | % ins�re une entr�e dans la bibliographie 2 | % 1 - identifiant 3 | % 2 - ann�e 4 | % 3 - auteurs 5 | % 4 - titre 6 | % 5 - revue 7 | % 6 - volume 8 | % 7 - page d�but 9 | % 8 - page fin 10 | 11 | \bibitemstyle{Chang1974} {1974} {C. L. Chang} 12 | {Finding prototypes for nearest neighbor classifiers} 13 | {IEEE Transactions on Computer}{23(11)}{1179}{1184} 14 | 15 | \bibitemstyle{Hart1968} {1968} {P. E. Hart} 16 | {The Condensed nearest neighbor rule} 17 | {IEEE Transactions on Information Theory}{14}{515}{516} 18 | 19 | \bibitemstyle{Bezdek2001} {2001} {J.C. Bezdek, L.I. Kuncheva} 20 | {Nearest prototype classifier designs: An experimental study} 21 | {International Journal of Intelligent Systems}{16(12)}{1445}{1473} 22 | 23 | \bibitemstyle{Frasconi1997} {1997} {P. Frasconi, M. Gori, G. Soda} 24 | {Links between LVQ and Backpropagation} 25 | {Pattern Recognition Letters}{18}{303}{310} 26 | 27 | \bibitemstyle{Kim2003} {2003} {Sang-Woon Kim, B.J. Oommen} 28 | {Enhancing prototype reduction schemes with LVQ3-type} 29 | {Pattern Recognition}{36}{1083}{1093} 30 | 31 | \bibitemstyle{Kohonen1982} {1982} {T. Kohonen} 32 | {Self-organized formation of topologically correct feature maps} 33 | {Biol. Cybernet.}{43}{59}{69} 34 | 35 | \bibitemstyle{Kohonen1995} {1995} {T. Kohonen} 36 | {Self-organizing Map} 37 | {Springer, Berlin}{}{0}{} 38 | 39 | \bibitemstyle{Linde1980} {1980} {Y. Linde, A. Buzo, R. M. Gray} 40 | {An algorithm for vector quantizer design} 41 | {IEEE Transactions on Commun.}{28}{84}{95} 42 | 43 | \bibitemstyle{Vakil2003} {2003} {Mohhamad-Taghi Vakil-Baghmisheh, Nikola Pavesic} 44 | {Premature clustering phenomenon and new training algorithms for LVQ} 45 | {Pattern Recognition}{36}{1901}{1912} 46 | 47 | \bibitemstyle{Vapnik1998} {1998} {V. N. Vapnik} 48 | {Statistical Learning Theory} 49 | {Wiley, New York}{}{0}{} 50 | 51 | -------------------------------------------------------------------------------- /_todo/classification/fig_cah.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | 4 | \unitlength 1mm 5 | \begin{picture}(76,67)(3,3) 6 | 7 | \put(5, 5) {\framebox(7,7){$x_1$}} 8 | \put(17, 5) {\framebox(7,7){$x_2$}} 9 | \put(29, 5) {\framebox(7,7){$x_3$}} 10 | \put(41, 5) {\framebox(7,7){$x_4$}} 11 | \put(53, 5) {\framebox(7,7){$x_5$}} 12 | 13 | \put(20,18) {\framebox(12,7){$x_2,x_3$}} 14 | 15 | \put(44,31) {\framebox(12,7){$x_4,x_5$}} 16 | 17 | \put(8, 44) {\framebox(18,7){$x_1,x_2,x_3$}} 18 | 19 | \put(16,57) {\framebox(34,7){$x_1,x_2,x_3,x_4,x_5$}} 20 | 21 | \put(68,9) {\framebox(10,7){$P_1$}} 22 | \put(68,24) {\framebox(10,7){$P_2$}} 23 | \put(68,35) {\framebox(10,7){$P_3$}} 24 | \put(68,48) {\framebox(10,7){$P_4$}} 25 | \put(68,61) {\framebox(10,7){$P_5$}} 26 | 27 | \put(20,12) {\line(0,1){4}} 28 | \put(32,12) {\line(0,1){4}} 29 | \put(20,16) {\line(1,0){12}} 30 | \put(26,16) {\line(0,1){2}} 31 | 32 | \put(44,12) {\line(0,1){17}} 33 | \put(56,12) {\line(0,1){17}} 34 | \put(44,29) {\line(1,0){12}} 35 | \put(50,29) {\line(0,1){2}} 36 | 37 | \put(8,12) {\line(0,1){30}} 38 | \put(26,25) {\line(0,1){17}} 39 | \put(8,42) {\line(1,0){18}} 40 | \put(16,42) {\line(0,1){2}} 41 | 42 | \put(16,51) {\line(0,1){4}} 43 | \put(50,38) {\line(0,1){17}} 44 | \put(16,55) {\line(1,0){34}} 45 | \put(33,55) {\line(0,1){2}} 46 | 47 | \put(33,64) {\line(0,1){3}} 48 | 49 | \multido{\i=33+2}{18}{ \put(\i,66) {\line(1,0){1}}} 50 | 51 | \multido{\i=16+2}{26}{ \put(\i,53) {\line(1,0){1}}} 52 | 53 | \multido{\i=8+2} {30} { \put(\i,40) {\line(1,0){1}}} 54 | \multido{\i=8+2} {30} { \put(\i,27) {\line(1,0){1}}} 55 | \multido{\i=8+2} {30} { \put(\i,14) {\line(1,0){1}}} 56 | 57 | 58 | \end{picture} 59 | 60 | \input{../../common/figure_end.tex} 61 | 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J. Damerau} 12 | {A technique for computer detection and correction of spelling errors} 13 | {Commun. ACM}{7(3)}{171}{176} 14 | 15 | \bibitemstyle{Kripasundar1996}{1996} {V. Kripasunder, G. Seni, R. K. Srihari} 16 | {Generating edit distance to incorporate domain information} 17 | {CEDAR/SUNY}{}{0}{} 18 | 19 | \bibitemstyle{Levenstein1966}{1966} {V. I. Levenstein} 20 | {Binary codes capables of correctiong deletions, insertions, and reversals} 21 | {Soviet Physics Doklady}{10(8)}{707}{710} 22 | 23 | \bibitemstyle{Seni1996}{1996} {Giovanni Seni, V. Kripasundar, Rohini K. Srihari} 24 | {Generalizing edit distance to incorporate domain information: handwritten text recognition as a case study} 25 | {Pattern Recognition}{29}{405}{414} 26 | 27 | \bibitemstyle{Waard1995}{1995} {W. P. de Waard} 28 | {An optimised minimal edit distance for hand-written word recognition} 29 | {Pattern Recognition Letters}{1995}{1091}{1096} 30 | 31 | \bibitemstyle{Wagner1974}{1974} {R. A. Wagner, M. Fisher} 32 | {The string-to-string correction problem} 33 | {Journal of the ACM}{21}{168}{178} 34 | 35 | 36 | -------------------------------------------------------------------------------- /_todo/hmm/fig_grmat.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | 4 | \begin{picture}(60,45)(0,0) 5 | \put(10,10) {\circle{20}} 6 | \put(8,8) {\makebox(3,3){\small $0$}} 7 | \put(60,10) {\circle{20}} 8 | \put(58,8) {\makebox(3,3){\small $1$}} 9 | 10 | \put(17,17) {\vector(1,0){34}} 11 | \put(53,3) {\vector(-1,0){34}} 12 | \arcup{10}{26}{12} 13 | \arcup{60}{26}{12} 14 | 15 | \put(38,19) {\makebox(3,3){\small $0,3$}} 16 | \put(38,6) {\makebox(3,3){\small $0,5$}} 17 | \put(20,30) {\makebox(3,3){\small $0,7$}} 18 | \put(70,30) {\makebox(3,3){\small $0,5$}} 19 | 20 | \end{picture} 21 | 22 | \input{../../common/figure_end.tex} 23 | -------------------------------------------------------------------------------- /_todo/hmm/fig_grmat2.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | 4 | \begin{picture}(90,70)(0,0) 5 | \put(10,10) {\circle{20}} 6 | \put(8,8) {\makebox(3,3){\small $0$}} 7 | \put(60,10) {\circle{20}} 8 | \put(58,8) {\makebox(3,3){\small $1$}} 9 | 10 | \put(17,17) {\vector(1,0){34}} 11 | \put(53,3) {\vector(-1,0){34}} 12 | \arcup{10}{26}{12} 13 | \arcup{60}{26}{12} 14 | 15 | \put(38,19) {\makebox(3,3){\small $0,3$}} 16 | \put(38,6) {\makebox(3,3){\small $0,4$}} 17 | \put(-5,25) {\makebox(3,3){\small $0,6$}} 18 | \put(75,25) {\makebox(3,3){\small $0,4$}} 19 | 20 | \put(35,50) {\circle{20}} 21 | \put(35,-30) {\circle{20}} 22 | \put(34,49) {\makebox(3,3){\small $E$}} 23 | \put(34,-31) {\makebox(3,3){\small $S$}} 24 | 25 | \put(33,40) {\vector(-1,-1){20}} 26 | \put(37,40) {\vector(1,-1){20}} 27 | \put(10,0) {\vector(1,-1){20}} 28 | \put(60,0) {\vector(-1,-1){20}} 29 | 30 | \put(17,35) 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B�chet, R. De Mori, D. Janiszek} 13 | {Data augmentation and language model adaptation using singular value decomposition} 14 | {Pattern Recognition Letters}{24}{15}{19} 15 | 16 | \bibitemstyle{Bicego2003}{2003}{Manuele Bicego, Vittorio Murino, Mario A.T. Figueiredo} 17 | {A sequential pruning strategy for the selection of the number of states in hidden Markov Models} 18 | {Pattern Recognition Letters}{24}{1395}{1407} 19 | 20 | \bibitemstyle{Govindaraju2002} {2002} {Venu Govindaraju, Peter Slav\'ik, Hanhong Xue} 21 | {Use of Lexicon Density in Evaluating Word Recognizers} 22 | {IEEE Pattern Analysis and Machine Intelligence}{24(6)}{789}{800} 23 | 24 | \bibitemstyle{Perraud2003} {2003} {Freddy Perraud, Christian Viard-Gaudin, Emmanuel Morin, Pierre-Michel Lallican} 25 | {N-Gram and N-Class Models for On line Handwriting Recognition} 26 | {Internation Conference on Document Analysis and Recognition}{}{1053}{1057} 27 | 28 | \bibitemstyle{Yamamoto2003} {2003} {Hirofumi Yamamoto, Shuntara Isogai, Yoshinori Sagisaka} 29 | {Multi-class composite N-gram language model} 30 | {Speech Communication}{}{0}{� para�tre} 31 | 32 | -------------------------------------------------------------------------------- /_todo/segment_detection/presentation.pdf: 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-------------------------------------------------------------------------------- /_todo/space_metric/image/rtree2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/_todo/space_metric/image/rtree2.png -------------------------------------------------------------------------------- /_todo/squelette/fig_8mask1.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | \begin{picture}(35,40)(10,10) 4 | 5 | \put(15,15) {\line(0,1){30}} 6 | \put(25,15) {\line(0,1){30}} 7 | \put(35,15) {\line(0,1){30}} 8 | \put(45,15) {\line(0,1){30}} 9 | 10 | \put(15,15) {\line(1,0){30}} 11 | \put(15,25) {\line(1,0){30}} 12 | \put(15,35) {\line(1,0){30}} 13 | \put(15,45) {\line(1,0){30}} 14 | 15 | \put(25,25) {\line(1,1){10}} 16 | \put(25,35) {\line(1,-1){10}} 17 | 18 | \put(35,25) {\line(1,1){10}} 19 | 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\put(25,45) {\line(1,-1){10}} 23 | 24 | \put(15,35) {\line(1,1){10}} 25 | \put(15,45) {\line(1,-1){10}} 26 | 27 | \end{picture} 28 | 29 | \input{../../common/figure_end.tex} 30 | -------------------------------------------------------------------------------- /_todo/squelette/fig_8mask3.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | \begin{picture}(35,40)(10,10) 4 | 5 | \put(15,15) {\line(0,1){30}} 6 | \put(25,15) {\line(0,1){30}} 7 | \put(35,15) {\line(0,1){30}} 8 | \put(45,15) {\line(0,1){30}} 9 | 10 | \put(15,15) {\line(1,0){30}} 11 | \put(15,25) {\line(1,0){30}} 12 | \put(15,35) {\line(1,0){30}} 13 | \put(15,45) {\line(1,0){30}} 14 | 15 | \put(25,25) {\line(1,1){10}} 16 | \put(25,35) {\line(1,-1){10}} 17 | 18 | \put(35,25) {\line(1,1){10}} 19 | \put(35,35) {\line(1,-1){10}} 20 | 21 | \put(35,35) {\line(1,1){10}} 22 | \put(35,45) {\line(1,-1){10}} 23 | 24 | \put(25,35) {\line(1,1){10}} 25 | \put(25,45) {\line(1,-1){10}} 26 | 27 | \put(15,35) {\line(1,1){10}} 28 | \put(15,45) {\line(1,-1){10}} 29 | 30 | \end{picture} 31 | 32 | \input{../../common/figure_end.tex} 33 | -------------------------------------------------------------------------------- /_todo/squelette/fig_8mask4.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | \begin{picture}(35,40)(10,10) 4 | 5 | \put(15,15) {\line(0,1){30}} 6 | \put(25,15) {\line(0,1){30}} 7 | \put(35,15) {\line(0,1){30}} 8 | \put(45,15) {\line(0,1){30}} 9 | 10 | \put(15,15) {\line(1,0){30}} 11 | \put(15,25) {\line(1,0){30}} 12 | \put(15,35) {\line(1,0){30}} 13 | \put(15,45) {\line(1,0){30}} 14 | 15 | \put(25,25) {\line(1,1){10}} 16 | \put(25,35) {\line(1,-1){10}} 17 | 18 | \put(35,25) {\line(1,1){10}} 19 | \put(35,35) {\line(1,-1){10}} 20 | 21 | \put(35,35) {\line(1,1){10}} 22 | \put(35,45) {\line(1,-1){10}} 23 | 24 | \put(25,35) {\line(1,1){10}} 25 | \put(25,45) {\line(1,-1){10}} 26 | 27 | \put(15,35) {\line(1,1){10}} 28 | \put(15,45) {\line(1,-1){10}} 29 | 30 | \put(15,25) {\line(1,1){10}} 31 | \put(15,35) {\line(1,-1){10}} 32 | 33 | \end{picture} 34 | 35 | \input{../../common/figure_end.tex} 36 | -------------------------------------------------------------------------------- /_todo/squelette/fig_8mask5.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | 4 | \begin{picture}(35,40)(10,10) 5 | 6 | \put(15,15) {\line(0,1){30}} 7 | \put(25,15) {\line(0,1){30}} 8 | \put(35,15) {\line(0,1){30}} 9 | \put(45,15) {\line(0,1){30}} 10 | 11 | \put(15,15) {\line(1,0){30}} 12 | \put(15,25) {\line(1,0){30}} 13 | \put(15,35) {\line(1,0){30}} 14 | \put(15,45) {\line(1,0){30}} 15 | 16 | \put(25,25) {\line(1,1){10}} 17 | \put(25,35) {\line(1,-1){10}} 18 | 19 | \put(35,35) {\line(1,1){10}} 20 | \put(35,45) {\line(1,-1){10}} 21 | 22 | \put(25,35) {\line(1,1){10}} 23 | \put(25,45) {\line(1,-1){10}} 24 | 25 | \put(15,35) {\line(1,1){10}} 26 | \put(15,45) {\line(1,-1){10}} 27 | 28 | \put(15,25) {\line(1,1){10}} 29 | \put(15,35) {\line(1,-1){10}} 30 | 31 | \put(15,15) {\line(1,1){10}} 32 | \put(15,25) {\line(1,-1){10}} 33 | 34 | \end{picture} 35 | 36 | \input{../../common/figure_end.tex} 37 | -------------------------------------------------------------------------------- /_todo/squelette/fig_8mask6.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | \begin{picture}(35,40)(10,10) 4 | 5 | \put(15,15) {\line(0,1){30}} 6 | \put(25,15) {\line(0,1){30}} 7 | \put(35,15) {\line(0,1){30}} 8 | \put(45,15) {\line(0,1){30}} 9 | 10 | \put(15,15) {\line(1,0){30}} 11 | \put(15,25) {\line(1,0){30}} 12 | \put(15,35) {\line(1,0){30}} 13 | \put(15,45) {\line(1,0){30}} 14 | 15 | \put(25,25) {\line(1,1){10}} 16 | \put(25,35) {\line(1,-1){10}} 17 | 18 | \put(35,25) {\line(1,1){10}} 19 | \put(35,35) {\line(1,-1){10}} 20 | 21 | \put(35,35) {\line(1,1){10}} 22 | \put(35,45) {\line(1,-1){10}} 23 | 24 | \put(25,35) {\line(1,1){10}} 25 | \put(25,45) {\line(1,-1){10}} 26 | 27 | \put(15,35) {\line(1,1){10}} 28 | \put(15,45) {\line(1,-1){10}} 29 | 30 | \put(15,25) {\line(1,1){10}} 31 | \put(15,35) {\line(1,-1){10}} 32 | 33 | \put(15,15) {\line(1,1){10}} 34 | \put(15,25) {\line(1,-1){10}} 35 | 36 | \end{picture} 37 | 38 | \input{../../common/figure_end.tex} 39 | -------------------------------------------------------------------------------- /_todo/squelette/fig_8mask7.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | \begin{picture}(35,40)(10,10) 4 | 5 | \put(15,15) {\line(0,1){30}} 6 | \put(25,15) {\line(0,1){30}} 7 | \put(35,15) {\line(0,1){30}} 8 | \put(45,15) {\line(0,1){30}} 9 | 10 | \put(15,15) {\line(1,0){30}} 11 | \put(15,25) {\line(1,0){30}} 12 | \put(15,35) {\line(1,0){30}} 13 | \put(15,45) {\line(1,0){30}} 14 | 15 | \put(25,25) {\line(1,1){10}} 16 | \put(25,35) {\line(1,-1){10}} 17 | 18 | \put(35,25) {\line(1,1){10}} 19 | \put(35,35) {\line(1,-1){10}} 20 | 21 | \put(35,35) {\line(1,1){10}} 22 | \put(35,45) {\line(1,-1){10}} 23 | 24 | \put(25,35) {\line(1,1){10}} 25 | \put(25,45) {\line(1,-1){10}} 26 | 27 | \put(15,35) {\line(1,1){10}} 28 | \put(15,45) {\line(1,-1){10}} 29 | 30 | \put(15,25) {\line(1,1){10}} 31 | \put(15,35) {\line(1,-1){10}} 32 | 33 | \put(15,15) {\line(1,1){10}} 34 | \put(15,25) {\line(1,-1){10}} 35 | 36 | \put(35,15) {\line(1,1){10}} 37 | \put(35,25) {\line(1,-1){10}} 38 | 39 | \end{picture} 40 | 41 | \input{../../common/figure_end.tex} 42 | -------------------------------------------------------------------------------- /_todo/squelette/fig_choi.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | 4 | \begin{picture}(190,100)(-25,-8) 5 | 6 | \put(1,1) {\line(1,0){140}} 7 | \put(1,80) {\line(4,-1){140}} 8 | \put(1,40) {\line(8,-1){140}} 9 | \put(130,-8) {\makebox(3,3){\small bord inf�rieur}} 10 | \put(130,60) {\makebox(3,3){\small bord sup�rieur}} 11 | \put(-10,40) {\makebox(3,3){\small squelette}} 12 | 13 | \put(15,50) {\line(1,0){12}} 14 | \put(15,54) {\line(1,0){12}} 15 | \put(15,58) {\line(1,0){12}} 16 | \put(15,62) {\line(1,0){12}} 17 | \put(15,50) {\line(0,1){12}} 18 | \put(19,50) {\line(0,1){12}} 19 | \put(23,50) {\line(0,1){12}} 20 | \put(28,50) {\line(0,1){12}} 21 | 22 | \put(17,60) {\line(1,8){2}} 23 | %\put(21,56) {\vector(1,8){2.3}} 24 | \put(25,52) {\line(1,8){2.65}} 25 | 26 | \put(35,30) {\line(1,0){12}} 27 | \put(35,34) {\line(1,0){12}} 28 | \put(35,38) {\line(1,0){12}} 29 | \put(35,42) {\line(1,0){12}} 30 | \put(35,30) {\line(0,1){12}} 31 | \put(39,30) {\line(0,1){12}} 32 | \put(43,30) {\line(0,1){12}} 33 | \put(48,30) {\line(0,1){12}} 34 | 35 | \put(37,40) {\line(1,8){3.9}} 36 | %\put(21,56) {\vector(1,8){2.3}} 37 | \put(41,32) {\line(0,-1){32}} 38 | 39 | \put(52,40) {\makebox(3,3){\small $B$}} 40 | \put(32,60) {\makebox(3,3){\small $A$}} 41 | 42 | \end{picture} 43 | 44 | \input{../../common/figure_end.tex} 45 | -------------------------------------------------------------------------------- /_todo/squelette/fig_circle.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | \begin{picture}(32,20)(0,0) 4 | \put(10,10) {\circle{16}} 5 | \put(26,10){\circle{16}} 6 | \end{picture} 7 | 8 | \input{../../common/figure_end.tex} 9 | -------------------------------------------------------------------------------- /_todo/squelette/fig_conf1.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | \begin{picture}(55,60)(10,10) 4 | 5 | \put(15,15) {\line(0,1){50}} 6 | \put(25,15) {\line(0,1){50}} 7 | \put(35,15) {\line(0,1){50}} 8 | \put(45,15) {\line(0,1){50}} 9 | \put(55,15) {\line(0,1){50}} 10 | \put(65,15) {\line(0,1){50}} 11 | 12 | \put(15,15) {\line(1,0){50}} 13 | \put(15,25) {\line(1,0){50}} 14 | \put(15,35) {\line(1,0){50}} 15 | \put(15,45) {\line(1,0){50}} 16 | \put(15,55) {\line(1,0){50}} 17 | \put(15,65) {\line(1,0){50}} 18 | 19 | \put(35,35) {\line(1,1){10}} 20 | \put(35,45) {\line(1,-1){10}} 21 | 22 | \put(45,35) {\line(1,1){10}} 23 | \put(45,45) {\line(1,-1){10}} 24 | 25 | \put(35,45) {\line(1,1){10}} 26 | \put(35,55) {\line(1,-1){10}} 27 | 28 | \put(25,25) {\line(1,1){10}} 29 | \put(25,35) {\line(1,-1){10}} 30 | \end{picture} 31 | 32 | \input{../../common/figure_end.tex} 33 | -------------------------------------------------------------------------------- /_todo/squelette/fig_conf2.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | \begin{picture}(55,60)(10,10) 4 | 5 | \put(15,15) {\line(0,1){50}} 6 | \put(25,15) {\line(0,1){50}} 7 | \put(35,15) {\line(0,1){50}} 8 | \put(45,15) {\line(0,1){50}} 9 | \put(55,15) {\line(0,1){50}} 10 | \put(65,15) {\line(0,1){50}} 11 | 12 | \put(15,15) {\line(1,0){50}} 13 | \put(15,25) {\line(1,0){50}} 14 | \put(15,35) {\line(1,0){50}} 15 | \put(15,45) {\line(1,0){50}} 16 | \put(15,55) {\line(1,0){50}} 17 | \put(15,65) {\line(1,0){50}} 18 | 19 | \put(35,35) {\line(1,1){10}} 20 | \put(35,45) {\line(1,-1){10}} 21 | 22 | \put(45,25) {\line(1,1){10}} 23 | \put(45,35) {\line(1,-1){10}} 24 | 25 | \put(35,45) {\line(1,1){10}} 26 | \put(35,55) {\line(1,-1){10}} 27 | 28 | \put(25,25) {\line(1,1){10}} 29 | \put(25,35) {\line(1,-1){10}} 30 | \end{picture} 31 | 32 | \input{../../common/figure_end.tex} 33 | 34 | -------------------------------------------------------------------------------- /_todo/squelette/fig_freeman.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | 4 | \begin{picture}(60,45)(0,20) 5 | \put(35,30) {\vector(1,0){15}} 6 | \put(35,35) {\vector(1,1){15}} 7 | \put(30,35) {\vector(0,1){15}} 8 | \put(25,35) {\vector(-1,1){15}} 9 | \put(25,30) {\vector(-1,0){15}} 10 | \put(25,25) {\vector(-1,-1){15}} 11 | \put(30,25) {\vector(0,-1){15}} 12 | \put(35,25) {\vector(1,-1){15}} 13 | 14 | \put(55,28) {\makebox(3,3){$0$}} 15 | \put(55,55) {\makebox(3,3){$1$}} 16 | \put(28,55) {\makebox(3,3){$2$}} 17 | \put(5,55) {\makebox(3,3){$3$}} 18 | \put(5,28) {\makebox(3,3){$4$}} 19 | \put(5,4) {\makebox(3,3){$5$}} 20 | \put(28,4) {\makebox(3,3){$6$}} 21 | \put(55,4) {\makebox(3,3){$7$}} 22 | 23 | \end{picture} 24 | 25 | 26 | \input{../../common/figure_end.tex} 27 | -------------------------------------------------------------------------------- /_todo/squelette/fig_mask1.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | 4 | \begin{picture}(35,40)(10,10) 5 | 6 | \put(15,15) {\line(0,1){30}} 7 | \put(25,15) {\line(0,1){30}} 8 | \put(35,15) {\line(0,1){30}} 9 | \put(45,15) {\line(0,1){30}} 10 | 11 | \put(15,15) {\line(1,0){30}} 12 | \put(15,25) {\line(1,0){30}} 13 | \put(15,35) {\line(1,0){30}} 14 | \put(15,45) {\line(1,0){30}} 15 | 16 | \put(15,25) {\line(1,1){10}} 17 | \put(25,25) {\line(1,1){10}} 18 | \put(35,25) {\line(1,1){10}} 19 | 20 | \put(15,35) {\line(1,-1){10}} 21 | \put(25,35) {\line(1,-1){10}} 22 | \put(35,35) {\line(1,-1){10}} 23 | 24 | \put(25,15) {\line(1,1){10}} 25 | \put(25,25) {\line(1,1){10}} 26 | \put(25,35) {\line(1,1){10}} 27 | 28 | \put(35,15) {\line(-1,1){10}} 29 | \put(35,25) {\line(-1,1){10}} 30 | \put(35,35) {\line(-1,1){10}} 31 | 32 | \end{picture} 33 | 34 | \input{../../common/figure_end.tex} 35 | -------------------------------------------------------------------------------- /_todo/squelette/fig_mask2.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | \begin{picture}(35,40)(10,10) 4 | 5 | \put(15,15) {\line(0,1){30}} 6 | \put(25,15) {\line(0,1){30}} 7 | \put(35,15) {\line(0,1){30}} 8 | \put(45,15) {\line(0,1){30}} 9 | 10 | \put(15,15) {\line(1,0){30}} 11 | \put(15,25) {\line(1,0){30}} 12 | \put(15,35) {\line(1,0){30}} 13 | \put(15,45) {\line(1,0){30}} 14 | 15 | \put(15,15) {\line(1,1){10}} 16 | \put(25,15) {\line(1,1){10}} 17 | \put(35,15) {\line(1,1){10}} 18 | 19 | \put(15,25) {\line(1,1){10}} 20 | \put(25,25) {\line(1,1){10}} 21 | \put(35,25) {\line(1,1){10}} 22 | 23 | \put(15,35) {\line(1,1){10}} 24 | \put(25,35) {\line(1,1){10}} 25 | \put(35,35) {\line(1,1){10}} 26 | 27 | \put(15,25) {\line(1,-1){10}} 28 | \put(25,25) {\line(1,-1){10}} 29 | \put(35,25) {\line(1,-1){10}} 30 | 31 | \put(15,35) {\line(1,-1){10}} 32 | \put(25,35) {\line(1,-1){10}} 33 | \put(35,35) {\line(1,-1){10}} 34 | 35 | \put(15,45) {\line(1,-1){10}} 36 | \put(25,45) {\line(1,-1){10}} 37 | \put(35,45) {\line(1,-1){10}} 38 | 39 | \end{picture} 40 | 41 | \input{../../common/figure_end.tex} 42 | -------------------------------------------------------------------------------- /_todo/squelette/fig_maskfail.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | \begin{picture}(100,70)(0,10) 4 | 5 | \put(5, 15) {\line(0,1){60}} 6 | \put(15,15) {\line(0,1){60}} 7 | \put(25,15) {\line(0,1){60}} 8 | \put(35,15) {\line(0,1){60}} 9 | \put(45,15) {\line(0,1){60}} 10 | \put(55,15) {\line(0,1){60}} 11 | \put(65,15) {\line(0,1){60}} 12 | \put(75,15) {\line(0,1){60}} 13 | \put(85,15) {\line(0,1){60}} 14 | \put(95,15) {\line(0,1){60}} 15 | 16 | \put(5,15) {\line(1,0){90}} 17 | \put(5,25) {\line(1,0){90}} 18 | \put(5,35) {\line(1,0){90}} 19 | \put(5,45) {\line(1,0){90}} 20 | \put(5,55) {\line(1,0){90}} 21 | \put(5,65) {\line(1,0){90}} 22 | \put(5,75) {\line(1,0){90}} 23 | 24 | \put(15,25) {\line(1,1){10}} 25 | \put(15,35) {\line(1,-1){10}} 26 | \put(25,25) {\line(1,1){10}} 27 | \put(25,35) {\line(1,-1){10}} 28 | \put(35,25) {\line(1,1){10}} 29 | \put(35,35) {\line(1,-1){10}} 30 | \put(45,25) {\line(1,1){10}} 31 | \put(45,35) {\line(1,-1){10}} 32 | \put(55,25) {\line(1,1){10}} 33 | \put(55,35) {\line(1,-1){10}} 34 | \put(65,25) {\line(1,1){10}} 35 | \put(65,35) {\line(1,-1){10}} 36 | \put(75,25) {\line(1,1){10}} 37 | \put(75,35) {\line(1,-1){10}} 38 | 39 | \put(15,55) {\line(1,1){10}} 40 | \put(15,65) {\line(1,-1){10}} 41 | \put(25,55) {\line(1,1){10}} 42 | \put(25,65) {\line(1,-1){10}} 43 | \put(35,55) {\line(1,1){10}} 44 | \put(35,65) {\line(1,-1){10}} 45 | \put(45,55) {\line(1,1){10}} 46 | \put(45,65) {\line(1,-1){10}} 47 | \put(45,45) {\line(1,1){10}} 48 | \put(45,55) {\line(1,-1){10}} 49 | 50 | \put(55,45) {\line(1,1){10}} 51 | \put(55,55) {\line(1,-1){10}} 52 | \put(65,45) {\line(1,1){10}} 53 | \put(65,55) {\line(1,-1){10}} 54 | \put(75,45) {\line(1,1){10}} 55 | \put(75,55) {\line(1,-1){10}} 56 | 57 | \put(45,35) {\line(1,1){10}} 58 | \put(45,45) {\line(1,-1){10}} 59 | \put(55,35) {\line(1,1){10}} 60 | \put(55,45) {\line(1,-1){10}} 61 | 62 | \end{picture} 63 | 64 | \input{../../common/figure_end.tex} 65 | -------------------------------------------------------------------------------- /_todo/squelette/fig_maskfail2.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | 4 | \begin{picture}(90,90)(10,10) 5 | 6 | \put(15,15) {\line(0,1){80}} 7 | \put(25,15) {\line(0,1){80}} 8 | \put(35,15) {\line(0,1){80}} 9 | \put(45,15) {\line(0,1){80}} 10 | \put(55,15) {\line(0,1){80}} 11 | \put(65,15) {\line(0,1){80}} 12 | \put(75,15) {\line(0,1){80}} 13 | \put(85,15) {\line(0,1){80}} 14 | \put(95,15) {\line(0,1){80}} 15 | 16 | \put(15,15) {\line(1,0){80}} 17 | \put(15,25) {\line(1,0){80}} 18 | \put(15,35) {\line(1,0){80}} 19 | \put(15,45) {\line(1,0){80}} 20 | \put(15,55) {\line(1,0){80}} 21 | \put(15,65) {\line(1,0){80}} 22 | \put(15,75) {\line(1,0){80}} 23 | \put(15,85) {\line(1,0){80}} 24 | \put(15,95) {\line(1,0){80}} 25 | 26 | \put(45,25) {\line(1,1){10}} 27 | \put(45,35) {\line(1,-1){10}} 28 | \put(45,35) {\line(1,1){10}} 29 | \put(45,45) {\line(1,-1){10}} 30 | \put(45,45) {\line(1,1){10}} 31 | \put(45,55) {\line(1,-1){10}} 32 | \put(45,55) {\line(1,1){10}} 33 | \put(45,65) {\line(1,-1){10}} 34 | 35 | \put(55,45) {\line(1,1){10}} 36 | \put(55,55) {\line(1,-1){10}} 37 | \put(55,55) {\line(1,1){10}} 38 | \put(55,65) {\line(1,-1){10}} 39 | \put(55,65) {\line(1,1){10}} 40 | \put(55,75) {\line(1,-1){10}} 41 | \put(55,75) {\line(1,1){10}} 42 | \put(55,85) {\line(1,-1){10}} 43 | 44 | \put(25,55) {\line(1,1){10}} 45 | \put(25,65) {\line(1,-1){10}} 46 | \put(35,55) {\line(1,1){10}} 47 | \put(35,65) {\line(1,-1){10}} 48 | 49 | \put(65,45) {\line(1,1){10}} 50 | \put(65,55) {\line(1,-1){10}} 51 | \put(75,45) {\line(1,1){10}} 52 | \put(75,55) {\line(1,-1){10}} 53 | 54 | 55 | \end{picture} 56 | 57 | \input{../../common/figure_end.tex} 58 | -------------------------------------------------------------------------------- /_todo/squelette/fig_masksp1.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | \begin{picture}(35,40)(10,10) 4 | 5 | \put(15,15) {\line(0,1){30}} 6 | \put(25,15) {\line(0,1){30}} 7 | \put(35,15) {\line(0,1){30}} 8 | \put(45,15) {\line(0,1){30}} 9 | 10 | \put(15,15) {\line(1,0){30}} 11 | \put(15,25) {\line(1,0){30}} 12 | \put(15,35) {\line(1,0){30}} 13 | \put(15,45) {\line(1,0){30}} 14 | 15 | \put(25,25) {\line(1,1){10}} 16 | \put(25,35) {\line(1,-1){10}} 17 | 18 | \put(35,25) {\line(1,1){10}} 19 | \put(35,35) {\line(1,-1){10}} 20 | 21 | \put(25,35) {\line(1,1){10}} 22 | \put(25,45) {\line(1,-1){10}} 23 | 24 | \put(15,25) {\line(1,1){10}} 25 | \put(15,35) {\line(1,-1){10}} 26 | 27 | \put(40,18) {\makebox(3,3){$?$}} 28 | \put(20,18) {\makebox(3,3){$?$}} 29 | 30 | \end{picture} 31 | 32 | \input{../../common/figure_end.tex} 33 | -------------------------------------------------------------------------------- /_todo/squelette/fig_masksp2.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | 4 | \begin{picture}(35,40)(10,10) 5 | 6 | \put(15,15) {\line(0,1){30}} 7 | \put(25,15) {\line(0,1){30}} 8 | \put(35,15) {\line(0,1){30}} 9 | \put(45,15) {\line(0,1){30}} 10 | 11 | \put(15,15) {\line(1,0){30}} 12 | \put(15,25) {\line(1,0){30}} 13 | \put(15,35) {\line(1,0){30}} 14 | \put(15,45) {\line(1,0){30}} 15 | 16 | \put(25,25) {\line(1,1){10}} 17 | \put(25,35) {\line(1,-1){10}} 18 | 19 | \put(35,25) {\line(1,1){10}} 20 | \put(35,35) {\line(1,-1){10}} 21 | 22 | \put(25,35) {\line(1,1){10}} 23 | \put(25,45) {\line(1,-1){10}} 24 | 25 | \put(40,38) {\makebox(3,3){$?$}} 26 | \put(20,38) {\makebox(3,3){$?$}} 27 | \put(40,18) {\makebox(3,3){$?$}} 28 | \put(20,28) {\makebox(3,3){$?$}} 29 | \put(30,18) {\makebox(3,3){$?$}} 30 | 31 | \end{picture} 32 | 33 | \input{../../common/figure_end.tex} 34 | -------------------------------------------------------------------------------- /_todo/squelette/fig_neib.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | \begin{picture}(75,80)(0,0) 4 | \put(15,15) {\line(1,0){50}} 5 | \put(15,15) {\line(0,1){50}} 6 | \put(65,65) {\line(-1,0){50}} 7 | \put(65,65) {\line(0,-1){50}} 8 | \put(5,5) {\makebox(3,3){$\vecteurim{-n}{-n}$}} 9 | \put(70,70) {\makebox(3,3){$\vecteurim{n}{n}$}} 10 | 11 | \put(15,35) {\line(1,0){30}} 12 | \put(65,45) {\line(-1,0){30}} 13 | \put(35,35) {\line(0,1){10}} 14 | \put(45,35) {\line(0,1){10}} 15 | 16 | \put(38,22) {\makebox(3,3){$V_b\pa{n}$}} 17 | \put(38,52) {\makebox(3,3){$V_h\pa{n}$}} 18 | 19 | \end{picture} 20 | 21 | \input{../../common/figure_end.tex} 22 | -------------------------------------------------------------------------------- /_todo/squelette/fig_nmask1.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | \begin{picture}(35,40)(10,10) 4 | 5 | \put(15,15) {\line(0,1){30}} 6 | \put(25,15) {\line(0,1){30}} 7 | \put(35,15) {\line(0,1){30}} 8 | \put(45,15) {\line(0,1){30}} 9 | 10 | \put(15,15) {\line(1,0){30}} 11 | \put(15,25) {\line(1,0){30}} 12 | \put(15,35) {\line(1,0){30}} 13 | \put(15,45) {\line(1,0){30}} 14 | 15 | \put(25,25) {\line(1,1){10}} 16 | \put(25,35) {\line(1,-1){10}} 17 | 18 | \put(35,25) {\line(1,1){10}} 19 | \put(35,35) {\line(1,-1){10}} 20 | 21 | %\put(35,35) {\line(1,1){10}} 22 | %\put(35,45) {\line(1,-1){10}} 23 | 24 | \put(25,35) {\line(1,1){10}} 25 | \put(25,45) {\line(1,-1){10}} 26 | 27 | \end{picture} 28 | 29 | \input{../../common/figure_end.tex} 30 | -------------------------------------------------------------------------------- /_todo/squelette/fig_nmask2.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | \begin{picture}(35,40)(10,10) 4 | 5 | \put(15,15) {\line(0,1){30}} 6 | \put(25,15) {\line(0,1){30}} 7 | \put(35,15) {\line(0,1){30}} 8 | \put(45,15) {\line(0,1){30}} 9 | 10 | \put(15,15) {\line(1,0){30}} 11 | \put(15,25) {\line(1,0){30}} 12 | \put(15,35) {\line(1,0){30}} 13 | \put(15,45) {\line(1,0){30}} 14 | 15 | \put(25,25) {\line(1,1){10}} 16 | \put(25,35) {\line(1,-1){10}} 17 | 18 | \put(35,25) {\line(1,1){10}} 19 | \put(35,35) {\line(1,-1){10}} 20 | 21 | \put(35,35) {\line(1,1){10}} 22 | \put(35,45) {\line(1,-1){10}} 23 | 24 | \put(25,35) {\line(1,1){10}} 25 | \put(25,45) {\line(1,-1){10}} 26 | 27 | \end{picture} 28 | 29 | \input{../../common/figure_end.tex} 30 | 31 | -------------------------------------------------------------------------------- /_todo/squelette/fig_nmask3.tex: -------------------------------------------------------------------------------- 1 | \input{../../common/figure_begin.tex} 2 | 3 | 4 | \begin{picture}(90,60)(10,30) 5 | 6 | \put(15,35) {\line(0,1){40}} 7 | \put(25,35) {\line(0,1){40}} 8 | \put(35,35) {\line(0,1){40}} 9 | \put(45,35) {\line(0,1){40}} 10 | \put(55,35) {\line(0,1){40}} 11 | \put(65,35) {\line(0,1){40}} 12 | \put(75,35) {\line(0,1){40}} 13 | \put(85,35) {\line(0,1){40}} 14 | \put(95,35) {\line(0,1){40}} 15 | 16 | \put(15,35) {\line(1,0){80}} 17 | \put(15,45) {\line(1,0){80}} 18 | \put(15,55) {\line(1,0){80}} 19 | \put(15,65) {\line(1,0){80}} 20 | \put(15,75) {\line(1,0){80}} 21 | 22 | \put(25,55) {\line(1,1){10}} 23 | \put(25,65) {\line(1,-1){10}} 24 | \put(35,55) {\line(1,1){10}} 25 | \put(35,65) {\line(1,-1){10}} 26 | \put(45,55) {\line(1,1){10}} 27 | \put(45,65) {\line(1,-1){10}} 28 | \put(55,55) {\line(1,1){10}} 29 | \put(55,65) {\line(1,-1){10}} 30 | \put(65,55) {\line(1,1){10}} 31 | \put(65,65) {\line(1,-1){10}} 32 | \put(75,55) {\line(1,1){10}} 33 | \put(75,65) {\line(1,-1){10}} 34 | 35 | \put(25,45) {\line(1,1){10}} 36 | \put(25,55) {\line(1,-1){10}} 37 | \put(35,45) {\line(1,1){10}} 38 | \put(35,55) {\line(1,-1){10}} 39 | \put(45,45) {\line(1,1){10}} 40 | \put(45,55) {\line(1,-1){10}} 41 | \put(55,45) {\line(1,1){10}} 42 | \put(55,55) {\line(1,-1){10}} 43 | \put(65,45) {\line(1,1){10}} 44 | \put(65,55) {\line(1,-1){10}} 45 | 46 | \end{picture} 47 | 48 | \input{../../common/figure_end.tex} 49 | -------------------------------------------------------------------------------- /_todo/squelette/image/abus.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/_todo/squelette/image/abus.png 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-------------------------------------------------------------------------------- /_todo/squelette/squelette_chapter.tex: -------------------------------------------------------------------------------- 1 | 2 | %------------------------------------------------------------------------------------------------------------------------------------------------------------------- 3 | \chapter{Squelettisation} 4 | %------------------------------------------------------------------------------------------------------------------------------------------------------------------- 5 | -------------------------------------------------------------------------------- /_todo/squelette/squelette_titre.tex: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/_todo/squelette/squelette_titre.tex -------------------------------------------------------------------------------- /_todo/svm/image/non.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/_todo/svm/image/non.png -------------------------------------------------------------------------------- /_todo/svm/svm_biblio.tex: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/_todo/svm/svm_biblio.tex -------------------------------------------------------------------------------- /_unittests/ut_data/test_wikipedia_dump.py: -------------------------------------------------------------------------------- 1 | import unittest 2 | from mlstatpy.ext_test_case import get_temp_folder, ExtTestCase 3 | from mlstatpy.data.wikipedia import download_dump 4 | 5 | 6 | class TestWikipediaDump(ExtTestCase): 7 | def test_wikipedia_dump(self): 8 | temp = get_temp_folder(__file__, "temp_wikipedia_abstract_gz") 9 | name = download_dump( 10 | "fr", "latest-page.sql.gz-rss.xml", folder=temp, unzip=False 11 | ) 12 | # print(name) 13 | self.assertTrue(name is not None) 14 | self.assertExists(name) 15 | 16 | def test_wikipedia_dump_zipped(self): 17 | temp = get_temp_folder(__file__, "temp_wikipedia_dump_gz") 18 | name = download_dump("fr", "latest-site_stats.sql.gz", folder=temp, unzip=True) 19 | # print(name) 20 | self.assertTrue(name is not None) 21 | self.assertExists(name) 22 | self.assertTrue(not name.endswith("gz")) 23 | 24 | 25 | if __name__ == "__main__": 26 | unittest.main() 27 | -------------------------------------------------------------------------------- /_unittests/ut_garden/test_poulet.py: -------------------------------------------------------------------------------- 1 | import unittest 2 | from mlstatpy.garden.poulet import ( 3 | maximum, 4 | find_maximum, 5 | histogramme_poisson_melange, 6 | proba_poisson_melange, 7 | ) 8 | 9 | 10 | class TestPoulet(unittest.TestCase): 11 | def test_poulet1(self): 12 | res = maximum(2, 5, 1, 80) 13 | m = find_maximum(res) 14 | self.assertEqual(m, (86, 228.50205712688214)) 15 | self.assertEqual( 16 | res[:3], [(0, 0.0), (1, 2.9999999999999942), (2, 5.9999999999999885)] 17 | ) 18 | 19 | def test_poulet2(self): 20 | h = histogramme_poisson_melange([48, 10, 4], [1, 2, 3]) 21 | self.assertTrue(max(h) > 0.01) 22 | self.assertEqual(h[:4], [0.0, 0.0, 0.0, 0.0]) 23 | 24 | def test_poulet3(self): 25 | h = proba_poisson_melange([48, 10, 4], [1, 2, 3], 20) 26 | self.assertEqual(h, 0) 27 | h = proba_poisson_melange([48, 10, 4], [1, 2, 3], 40) 28 | self.assertTrue(h < 0.1) 29 | 30 | 31 | if __name__ == "__main__": 32 | unittest.main() 33 | -------------------------------------------------------------------------------- /_unittests/ut_graph/data/graph.gv: -------------------------------------------------------------------------------- 1 | digraph{ 2 | "e" [label="e"]; 3 | "f" [label="f"]; 4 | "00" [label="00"]; 5 | "c" [label="c"]; 6 | "a" [label="a"]; 7 | "d" [label="d"]; 8 | "b" [label="b"]; 9 | "11" [label="11"]; 10 | "h" [label="h"]; 11 | "aa" [label="aa"]; 12 | "g" [label="g"]; 13 | "e" -> "f" [label=""]; 14 | "g" -> "11" [label=""]; 15 | "b" -> "c" [label=""]; 16 | "f" -> "h" [label=""]; 17 | "a" -> "g" [label=""]; 18 | "b" -> "f" [label=""]; 19 | "b" -> "d" [label=""]; 20 | "f" -> "g" [label=""]; 21 | "aa" -> "h" [label=""]; 22 | "00" -> "a" [label=""]; 23 | "a" -> "b" [label=""]; 24 | "d" -> "g" [label=""]; 25 | "00" -> "aa" [label=""]; 26 | "b" -> "g" [label=""]; 27 | "d" -> "h" [label=""]; 28 | "d" -> "e" [label=""]; 29 | "aa" -> "c" [label=""]; 30 | "h" -> "11" [label=""]; 31 | "c" -> "d" [label=""]; 32 | } -------------------------------------------------------------------------------- /_unittests/ut_image/data/eglise_zoom2.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/_unittests/ut_image/data/eglise_zoom2.jpg -------------------------------------------------------------------------------- /_unittests/ut_image/data/gradient--2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/_unittests/ut_image/data/gradient--2.png -------------------------------------------------------------------------------- /_unittests/ut_image/data/gradient--2b.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/_unittests/ut_image/data/gradient--2b.png -------------------------------------------------------------------------------- /_unittests/ut_image/test_binom.py: -------------------------------------------------------------------------------- 1 | import unittest 2 | from mlstatpy.image.detection_segment import tabule_queue_binom 3 | 4 | 5 | class TestQueueBinom(unittest.TestCase): 6 | def test_queue(self): 7 | b = tabule_queue_binom(2, 2) 8 | self.assertEqual( 9 | b, 10 | { 11 | (0, 1): 0.0, 12 | (1, 2): 0.0, 13 | (0, 0): 1.0, 14 | (2, 3): 0.0, 15 | (2, 0): 1.0, 16 | (1, 0): 1.0, 17 | (2, 2): 4.0, 18 | (1, 1): 2.0, 19 | (2, 1): 0.0, 20 | }, 21 | ) 22 | 23 | 24 | if __name__ == "__main__": 25 | unittest.main() 26 | -------------------------------------------------------------------------------- /_unittests/ut_image/test_geometrie.py: -------------------------------------------------------------------------------- 1 | import unittest 2 | import math 3 | from mlstatpy.image.detection_segment import Point, Segment 4 | 5 | 6 | class TestGeometrie(unittest.TestCase): 7 | def test_point(self): 8 | p = Point(2, 2) 9 | pp = Point(3, 5) 10 | pp += p 11 | pp += p 12 | self.assertEqual(p, Point(2, 2)) 13 | self.assertEqual(pp, Point(7, 9)) 14 | pp -= p 15 | self.assertEqual(pp, Point(5, 7)) 16 | pp.scalairek(0.5) 17 | self.assertEqual(pp, Point(2.5, 3.5)) 18 | ar = pp.arrondi() 19 | self.assertEqual(ar, Point(3, 4)) 20 | sc = ar.scalaire(ar) 21 | no = ar.norme() ** 2 22 | self.assertEqual(sc, no) 23 | a = Point(1, 1).angle() 24 | b = Point(-1, 1).angle() 25 | d = b - a 26 | dd = d - math.pi / 2 27 | assert abs(dd) < 1e-5 28 | seg = Segment(Point(0, 0), p) 29 | self.assertEqual(str(seg), "[(0,0),(2,2)]") 30 | n = seg.directeur().norme() 31 | assert abs(n - 1) < 1e-8 32 | d = seg.directeur() 33 | n = seg.normal() 34 | s = d.scalaire(n) 35 | assert abs(s) < 1e-8 36 | 37 | 38 | if __name__ == "__main__": 39 | unittest.main() 40 | -------------------------------------------------------------------------------- /_unittests/ut_image/test_random_image.py: -------------------------------------------------------------------------------- 1 | import os 2 | import unittest 3 | import numpy 4 | from mlstatpy.ext_test_case import ExtTestCase, get_temp_folder 5 | from mlstatpy.image.detection_segment.random_image import ( 6 | random_noise_image, 7 | random_segment_image, 8 | ) 9 | from mlstatpy.image.detection_segment import convert_array2PIL, convert_PIL2array 10 | from mlstatpy.image.detection_segment.detection_segment import detect_segments 11 | 12 | 13 | class TestRandomImage(ExtTestCase): 14 | def test_random_noise_image(self): 15 | img = random_noise_image((100, 100), 0.1) 16 | total = img.sum() 17 | self.assertGreater(total, 0) 18 | self.assertLesser(total, 3000) 19 | 20 | def test_random_segment_image(self): 21 | img = random_noise_image((12, 10), 0.0) 22 | seg = random_segment_image(img, lmin=0.5, density=2.0) 23 | total = img.sum() 24 | self.assertGreater(total, 0) 25 | self.assertLesser(total, 3000) 26 | self.assertIsInstance(seg, dict) 27 | 28 | fimg = img.astype(numpy.float32) 29 | img255 = (-fimg + 1) * 255 30 | timg255 = img255.astype(numpy.uint8) 31 | pil = convert_array2PIL(timg255) 32 | img2 = convert_PIL2array(pil) 33 | temp = get_temp_folder(__file__, "temp_random_segment_image") 34 | outfile = os.path.join(temp, "img.png") 35 | pil.save(outfile) 36 | self.assertEqual(timg255, img2) 37 | 38 | pil2 = convert_array2PIL(img, mode="binary") 39 | img3 = convert_PIL2array(pil2) 40 | self.assertEqual(timg255, img3) 41 | 42 | for _ in range(100): 43 | seg = random_segment_image(img, lmin=0.5, density=2.0) 44 | self.assertGreater(seg["x1"], 0) 45 | self.assertGreater(seg["y1"], 0) 46 | self.assertGreater(seg["x2"], 0) 47 | self.assertGreater(seg["y2"], 0) 48 | 49 | def test_segment_random_image(self): 50 | img = random_noise_image((100, 100)) 51 | random_segment_image(img, density=3.0, lmin=0.3) 52 | random_segment_image(img, density=5.0, lmin=0.3) 53 | random_segment_image(img, density=5.0, lmin=0.3) 54 | seg = detect_segments(img, seuil_nfa=10, seuil_norme=1, verbose=0) 55 | # self.assertNotEmpty(seg) 56 | self.assertTrue(seg is not None) 57 | 58 | 59 | if __name__ == "__main__": 60 | unittest.main() 61 | -------------------------------------------------------------------------------- /_unittests/ut_ml/test_logreg.py: -------------------------------------------------------------------------------- 1 | import unittest 2 | from mlstatpy.ext_test_case import ExtTestCase 3 | from mlstatpy.ml.logreg import criteria, criteria2, random_set_1d, plot_ds 4 | 5 | 6 | class TestLogReg(ExtTestCase): 7 | def test_criteria(self): 8 | for b in [2, 3, 4]: 9 | with self.subTest(kind=b): 10 | X, y = random_set_1d(1000, b) 11 | df = criteria(X, y) 12 | self.assertEqual(df.shape, (998, 8)) 13 | self.assertRaise(lambda: random_set_1d(1000, 0), ValueError) 14 | 15 | def test_criteria_plot(self): 16 | X1, y1 = random_set_1d(1000, 2) 17 | X2, y2 = random_set_1d(1000, 3) 18 | df1 = criteria(X1, y1) 19 | df2 = criteria(X2, y2) 20 | 21 | import matplotlib.pyplot as plt 22 | 23 | _, ax = plt.subplots(1, 2, figsize=(12, 6), sharey=True) 24 | plot_ds(X1, y1, ax=ax[0], title="easy") 25 | plot_ds(X2, y2, ax=ax[1], title="difficult") 26 | df1.plot(x="X", y=["Gini", "Gain", "p1", "p2"], ax=ax[0], lw=5.0) 27 | df2.plot(x="X", y=["Gini", "Gain", "p1", "p2"], ax=ax[1], lw=5.0) 28 | plt.clf() 29 | 30 | def test_criteria2(self): 31 | X1, y1 = random_set_1d(1000, 2) 32 | df1 = criteria2(X1, y1) 33 | self.assertEqual(df1.shape[0], 998) 34 | 35 | 36 | if __name__ == "__main__": 37 | unittest.main() 38 | -------------------------------------------------------------------------------- /_unittests/ut_ml/test_nuage_points.py: -------------------------------------------------------------------------------- 1 | import unittest 2 | import numpy 3 | from numpy.testing import assert_array_equal 4 | from mlstatpy.ext_test_case import ExtTestCase, ignore_warnings 5 | from sklearn.neighbors import NearestNeighbors 6 | from mlstatpy.ml.kppv import NuagePoints 7 | from mlstatpy.ml.kppv_laesa import NuagePointsLaesa 8 | 9 | 10 | class TestNuagePoints(ExtTestCase): 11 | @ignore_warnings(DeprecationWarning) 12 | def test_nuage_points_1d(self): 13 | X = numpy.array([[0], [3], [1]]) 14 | neigh = NearestNeighbors(n_neighbors=1) 15 | neigh.fit(X) 16 | dist, y = neigh.kneighbors(X) 17 | 18 | nuage = NuagePoints() 19 | nuage.fit(X) 20 | dist2, y2 = nuage.kneighbors(X) 21 | 22 | assert_array_equal(y.ravel(), y2.ravel()) 23 | assert_array_equal(dist.ravel(), dist2.ravel()) 24 | 25 | @ignore_warnings(DeprecationWarning) 26 | def test_nuage_points_1d_leasa(self): 27 | X = numpy.array([[0], [3], [1]]) 28 | neigh = NearestNeighbors(n_neighbors=1) 29 | neigh.fit(X) 30 | dist, y = neigh.kneighbors(X) 31 | 32 | nuage = NuagePointsLaesa(2) 33 | nuage.fit(X) 34 | dist2, y2 = nuage.kneighbors(X) 35 | 36 | assert_array_equal(y.ravel(), y2.ravel()) 37 | assert_array_equal(dist.ravel(), dist2.ravel()) 38 | 39 | @ignore_warnings(DeprecationWarning) 40 | def test_nuage_points_2d(self): 41 | X = numpy.array([[0, 0], [3, 3], [1, 1]]) 42 | neigh = NearestNeighbors(n_neighbors=1) 43 | neigh.fit(X) 44 | dist, y = neigh.kneighbors(X) 45 | 46 | nuage = NuagePoints() 47 | nuage.fit(X) 48 | dist2, y2 = nuage.kneighbors(X) 49 | 50 | assert_array_equal(y.ravel(), y2.ravel()) 51 | assert_array_equal(dist.ravel(), dist2.ravel()) 52 | 53 | @ignore_warnings(DeprecationWarning) 54 | def test_nuage_points_2d_leasa(self): 55 | X = numpy.array([[0, 0], [3, 3], [1, 1]]) 56 | neigh = NearestNeighbors(n_neighbors=1) 57 | neigh.fit(X) 58 | dist, y = neigh.kneighbors(X) 59 | 60 | for k in [1, 2, 3]: 61 | nuage = NuagePointsLaesa(k) 62 | nuage.fit(X) 63 | dist2, y2 = nuage.kneighbors(X) 64 | 65 | assert_array_equal(y.ravel(), y2.ravel()) 66 | assert_array_equal(dist.ravel(), dist2.ravel()) 67 | 68 | 69 | if __name__ == "__main__": 70 | unittest.main() 71 | -------------------------------------------------------------------------------- /_unittests/ut_nlp/test_completion_longer.py: -------------------------------------------------------------------------------- 1 | import os 2 | import unittest 3 | from mlstatpy.nlp.completion import CompletionTrieNode 4 | 5 | 6 | class TestCompletionLonger(unittest.TestCase): 7 | def test_check_bug_about_mergeing_completions(self): 8 | data = os.path.join( 9 | os.path.abspath(os.path.dirname(__file__)), "data", "sample20000.txt" 10 | ) 11 | with open(data, "r", encoding="utf-8") as f: 12 | lines = [_.strip("\n\r\t ") for _ in f.readlines()] 13 | queries = [(None, _) for _ in lines] 14 | # print("build trie") 15 | trie = CompletionTrieNode.build(queries) 16 | # print( 17 | # len(queries), 18 | # len(set(_[1] for _ in queries)), 19 | # len(list(trie.leaves())), 20 | # len(set(trie.leaves())), 21 | # ) 22 | assert "Cannes 2005" in set(_[1] for _ in queries) 23 | assert "Cannes 2005" in set(_.value for _ in trie.leaves()) 24 | # print("bug precompute") 25 | trie.precompute_stat() 26 | # print("bug checking") 27 | find = trie.find("Cann") 28 | sug = find.stat.completions 29 | self.assertEqual(len(sug), 2) 30 | leave = trie.find("Cannes 2005") 31 | 32 | sugg = leave.all_mks_completions() 33 | assert len(sugg) > 0 34 | verif = 0 35 | for p, sug in sugg: 36 | if p.value.startswith("Cannes"): 37 | for s in sug: 38 | if s[1].value == "Cannes 2005": 39 | verif += 1 40 | if verif == 0: 41 | raise AssertionError(leave.str_all_completions(use_precompute=True)) 42 | 43 | sugg = leave.all_completions() 44 | assert len(sugg) > 0 45 | verif = 0 46 | for p, sug in sugg: 47 | if p.value.startswith("Cannes"): 48 | for s in sug: 49 | if s == "Cannes 2005": 50 | verif += 1 51 | if verif == 0: 52 | raise AssertionError(leave.str_all_completions(use_precompute=False)) 53 | 54 | 55 | if __name__ == "__main__": 56 | unittest.main() 57 | -------------------------------------------------------------------------------- /_unittests/ut_nlp/test_completion_profiling.py: -------------------------------------------------------------------------------- 1 | """ 2 | https://dumps.wikimedia.org/frwiki/latest/frwiki-latest-all-titles.gz 3 | https://dumps.wikimedia.org/frwiki/latest/frwiki-latest-all-titles-in-ns0.gz 4 | """ 5 | 6 | import os 7 | import unittest 8 | import cProfile 9 | import pstats 10 | import io 11 | from mlstatpy.ext_test_case import get_temp_folder 12 | from mlstatpy.nlp.completion import CompletionTrieNode 13 | 14 | 15 | class TestCompletionProfiling(unittest.TestCase): 16 | def gain_dynamique_moyen_par_mot(self, queries, weights): 17 | per = list(zip(weights, queries)) 18 | total = sum(weights) * 1.0 19 | trie = CompletionTrieNode.build([(None, q) for _, q in per]) 20 | trie.precompute_stat() 21 | trie.update_stat_dynamic() 22 | wks = [(w, p, len(w) - trie.min_keystroke0(w)[0]) for p, w in per] 23 | wks_dyn = [(w, p, len(w) - trie.min_dynamic_keystroke(w)[0]) for p, w in per] 24 | wks_dyn2 = [(w, p, len(w) - trie.min_dynamic_keystroke2(w)[0]) for p, w in per] 25 | gain = sum(g * p / total for w, p, g in wks) 26 | gain_dyn = sum(g * p / total for w, p, g in wks_dyn) 27 | gain_dyn2 = sum(g * p / total for w, p, g in wks_dyn2) 28 | ave_length = sum(len(w) * p / total for p, w in per) 29 | return gain, gain_dyn, gain_dyn2, ave_length 30 | 31 | def test_profiling(self): 32 | temp = get_temp_folder(__file__, "temp_profiling") 33 | data = os.path.join(temp, "..", "data", "sample1000.txt") 34 | with open(data, "r", encoding="utf-8") as f: 35 | lines = [_.strip(" \n\r\t") for _ in f.readlines()] 36 | 37 | def profile_exe(): 38 | res = self.gain_dynamique_moyen_par_mot(lines, [1.0] * len(lines)) 39 | return res 40 | 41 | def prof(n, show): 42 | pr = cProfile.Profile() 43 | pr.enable() 44 | profile_exe() 45 | pr.disable() 46 | s = io.StringIO() 47 | ps = pstats.Stats(pr, stream=s).sort_stats("cumulative") 48 | ps.print_stats() 49 | rem = os.path.normpath(os.path.join(temp, "..", "..", "..")) 50 | res = s.getvalue().replace(rem, "") 51 | if show: 52 | print(res) 53 | with open(os.path.join(temp, "profiling%d.txt" % n), "w") as f: 54 | f.write(res) 55 | 56 | prof(1, show=False) 57 | # prof(2, show=True) 58 | 59 | 60 | if __name__ == "__main__": 61 | unittest.main() 62 | -------------------------------------------------------------------------------- /_unittests/ut_xrun_doc/test_measure_time.py: -------------------------------------------------------------------------------- 1 | import unittest 2 | from math import cos 3 | from mlstatpy.ext_test_case import ExtTestCase, measure_time 4 | 5 | 6 | class TestMeasureTime(ExtTestCase): 7 | def test_measure_time(self): 8 | res = measure_time(lambda: cos(5)) 9 | self.assertIsInstance(res, dict) 10 | self.assertIn("average", res) 11 | 12 | 13 | if __name__ == "__main__": 14 | unittest.main(verbosity=2) 15 | -------------------------------------------------------------------------------- /mlstatpy/__init__.py: -------------------------------------------------------------------------------- 1 | __version__ = "0.5.0" 2 | __author__ = "Xavier Dupré" 3 | __github__ = "https://github.com/sdpython/mlstatpy" 4 | __url__ = "https://sdpython.github.io/doc/mlstatpy/dev/" 5 | __license__ = "MIT License" 6 | -------------------------------------------------------------------------------- /mlstatpy/data/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/mlstatpy/data/__init__.py -------------------------------------------------------------------------------- /mlstatpy/data/data_exceptions.py: -------------------------------------------------------------------------------- 1 | class DataException(Exception): 2 | """ 3 | raised when retrieving data 4 | """ 5 | -------------------------------------------------------------------------------- /mlstatpy/garden/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/mlstatpy/garden/__init__.py -------------------------------------------------------------------------------- /mlstatpy/graph/__init__.py: -------------------------------------------------------------------------------- 1 | from .graph_distance import GraphDistance 2 | -------------------------------------------------------------------------------- /mlstatpy/image/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/mlstatpy/image/__init__.py -------------------------------------------------------------------------------- /mlstatpy/image/detection_segment/__init__.py: -------------------------------------------------------------------------------- 1 | from .detection_segment import ( 2 | detect_segments, 3 | plot_segments, 4 | compute_gradient, 5 | plot_gradient, 6 | ) 7 | from .detection_segment import convert_array2PIL, convert_PIL2array 8 | from .geometrie import Point, Segment 9 | from .queue_binom import tabule_queue_binom 10 | from .random_image import random_noise_image, random_segment_image 11 | -------------------------------------------------------------------------------- /mlstatpy/image/detection_segment/queue_binom.py: -------------------------------------------------------------------------------- 1 | def tabule_queue_binom(n, p): 2 | """ 3 | Retourne un dictionnaire dont la clé est couple d'entiers *(a,b)* 4 | si *t* est le resultat, alors :math:`t=[(a,b)]` est la probabilité 5 | qu'il y ait *b* événements parmi *a* sachant que la probabilité d'un 6 | événement est *p* : :math:`t [ (a,b) ] = C_a^b p^b (1-p)^ {(a-b)}` 7 | 8 | Pour aller plus vite, ces probabilités sont estimées par récurrence : 9 | 10 | * :math:`\\forall m, \\; t [(m,0)] = 1.0` 11 | * :math:`\\forall m, \\; t [(m,m+1)] = 0.0` 12 | et :math:`t[(m,k)] = p * t [ (m-1, k-1)] + (1-p) * t [ (m-1,k) ]` 13 | 14 | Cette fonction calcule tous les coefficients :math:`t [ (a,b) ]` pour une 15 | probabilité :math:`p` donnée et :math:`b \\leqslant a \\leqslant n`. 16 | 17 | Ces probabilités sont stockées dans un dictionnaire car s'ils étaient 18 | stockées dans une matrice, celle-ci serait triangulaire inférieure. 19 | """ 20 | t = {} 21 | t[(0, 0)] = 1.0 22 | t[(0, 1)] = 0.0 23 | for m in range(1, n + 1): 24 | t[(m, 0)] = 1.0 25 | t[(m, m + 1)] = 0.0 26 | for k in range(1, m + 1): 27 | t[(m, k)] = p * t[(m - 1, k - 1)] + (1 - p) * t[(m - 1, k)] 28 | return t 29 | -------------------------------------------------------------------------------- /mlstatpy/ml/__init__.py: -------------------------------------------------------------------------------- 1 | from .roc import ROC 2 | from .voronoi import voronoi_estimation_from_lr 3 | -------------------------------------------------------------------------------- /mlstatpy/nlp/__init__.py: -------------------------------------------------------------------------------- 1 | from .completion import CompletionTrieNode 2 | from .completion_simple import CompletionElement, CompletionSystem 3 | from .normalize import remove_diacritics 4 | -------------------------------------------------------------------------------- /mlstatpy/nlp/normalize.py: -------------------------------------------------------------------------------- 1 | import unicodedata 2 | 3 | 4 | def remove_diacritics(input_str): 5 | """ 6 | Removes diacritics. 7 | 8 | :param input_str: string to clean 9 | :return: cleaned string 10 | 11 | Example:: 12 | 13 | enguérand --> enguerand 14 | """ 15 | nkfd_form = unicodedata.normalize("NFKD", input_str) 16 | only_ascii = nkfd_form.encode("ASCII", "ignore") 17 | return only_ascii.decode("utf8") 18 | -------------------------------------------------------------------------------- /mlstatpy/optim/__init__.py: -------------------------------------------------------------------------------- 1 | from .sgd import SGDOptimizer 2 | -------------------------------------------------------------------------------- /requirements-dev.txt: -------------------------------------------------------------------------------- 1 | astroid 2 | black 3 | blockdiag 4 | coverage 5 | Cython 6 | cytoolz 7 | dill 8 | furo 9 | graphviz 10 | hummingbird-ml 11 | ijson 12 | importlib_metadata 13 | ipykernel 14 | ipython 15 | isort 16 | jdcal 17 | jupyter_sphinx 18 | jupyter 19 | jupyter-black 20 | lifelines 21 | matplotlib 22 | memory_profiler 23 | mlinsights 24 | nbconvert 25 | nbsphinx 26 | notebook 27 | onnx-array-api 28 | onnx-extended 29 | onnxruntime>=1.12 30 | pandas 31 | pillow 32 | psutil 33 | pybind11 34 | pydata_sphinx_theme 35 | pyinstrument 36 | pytest 37 | ruff 38 | seaborn 39 | snakeviz 40 | scikit-learn>=1.1 41 | skl2onnx 42 | sphinx 43 | sphinx-gallery 44 | sphinx-issues 45 | sphinxcontrib-blockdiag 46 | git+https://github.com/sdpython/sphinx-runpython.git 47 | stack_data 48 | statsmodels 49 | tqdm 50 | traitlets 51 | vprof 52 | wheel 53 | xgboost 54 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | mlinsights>=0.2 2 | onnxruntime>=1.12 3 | skl2onnx 4 | -------------------------------------------------------------------------------- /setup.cfg: -------------------------------------------------------------------------------- 1 | [options] 2 | packages = find: 3 | 4 | [options.packages.find] 5 | include = mlstatpy* 6 | -------------------------------------------------------------------------------- /setup.py: -------------------------------------------------------------------------------- 1 | import os 2 | from setuptools import setup 3 | 4 | ###################### 5 | # beginning of setup 6 | ###################### 7 | 8 | 9 | here = os.path.dirname(__file__) 10 | if here == "": 11 | here = "." 12 | package_data = {"mlstatpy": ["*.txt"]} 13 | 14 | try: 15 | with open(os.path.join(here, "requirements.txt"), "r") as f: 16 | requirements = f.read().strip(" \n\r\t").split("\n") 17 | except FileNotFoundError: 18 | requirements = [] 19 | if not requirements or requirements == [""]: 20 | requirements = ["numpy", "mlinsight", "onnxruntime", "skl2onnx"] 21 | 22 | try: 23 | with open(os.path.join(here, "README.rst"), "r", encoding="utf-8") as f: 24 | long_description = "mlstatpy:" + f.read().split("mlstatpy:")[1] 25 | except FileNotFoundError: 26 | long_description = "" 27 | 28 | version_str = "0.1.0" 29 | with open(os.path.join(here, "mlstatpy/__init__.py"), "r") as f: 30 | line = [ 31 | _ 32 | for _ in [_.strip("\r\n ") for _ in f.readlines()] 33 | if _.startswith("__version__") 34 | ] 35 | if line: 36 | version_str = line[0].split("=")[1].strip('" ') 37 | 38 | # see https://pypi.org/classifiers/ 39 | setup( 40 | name="mlstatpy", 41 | version=version_str, 42 | description="Points de détails liés au machine learning", 43 | long_description=long_description, 44 | author="Xavier Dupré", 45 | author_email="xavier.dupre@gmail.com", 46 | url="https://github.com/sdpython/mlstatpy", 47 | package_data=package_data, 48 | setup_requires=["numpy"], 49 | install_requires=requirements, 50 | classifiers=[ 51 | "Intended Audience :: Science/Research", 52 | "Intended Audience :: Education", 53 | "License :: OSI Approved :: MIT License", 54 | "Programming Language :: Python", 55 | "Topic :: Scientific/Engineering", 56 | "Topic :: Scientific/Engineering :: Mathematics", 57 | "Topic :: Education", 58 | "Development Status :: 5 - Production/Stable", 59 | "Operating System :: OS Independent", 60 | "Programming Language :: Python :: 3", 61 | "Programming Language :: Python :: 3.9", 62 | "Programming Language :: Python :: 3.10", 63 | "Programming Language :: Python :: 3.11", 64 | ], 65 | ) 66 | --------------------------------------------------------------------------------