├── .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
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/_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 |
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/_doc/api/modules/index.rst:
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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 |
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/_doc/api/modules/kppv.rst:
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1 | mlstatpy.ml.kppv
2 | ================
3 |
4 | .. automodule:: mlstatpy.ml.kppv
5 | :members:
6 |
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/_doc/api/modules/kppv_laesa.rst:
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1 | mlstatpy.ml.kppv_laesa
2 | ======================
3 |
4 | .. automodule:: mlstatpy.ml.kppv_laesa
5 | :members:
6 |
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/_doc/api/modules/logreg.rst:
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1 | mlstatpy.ml.logreg
2 | ==================
3 |
4 | .. automodule:: mlstatpy.ml.logreg
5 | :members:
6 |
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/_doc/api/modules/neural_tree.rst:
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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 |
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/_doc/api/modules/poulet.rst:
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1 | mlstatpy.garden.poulet
2 | ======================
3 |
4 | .. automodule:: mlstatpy.garden.poulet
5 | :members:
6 |
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/_doc/api/modules/roc.rst:
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1 | mlstatpy.ml.roc
2 | ===============
3 |
4 | .. automodule:: mlstatpy.ml.roc
5 | :members:
6 |
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/_doc/api/modules/sgd.rst:
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1 | mlstatpy.optim.sgd
2 | ==================
3 |
4 | .. automodule:: mlstatpy.optim.sgd
5 | :members:
6 |
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/_doc/api/optim.rst:
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1 |
2 | Optimisation
3 | ================
4 |
5 | Gradient
6 | ++++++++
7 |
8 | .. autoclass:: mlstatpy.optim.sgd.SGDOptimizer
9 | :noindex:
10 |
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/_doc/api/text.rst:
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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 |
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1 |
2 | .. _l-k-algo:
3 |
4 | ###########
5 | Algorithmes
6 | ###########
7 |
8 | Le machine learning propose un grand nombre
9 | de modèles pour des problèmes standardisés.
10 | Au delà, il faut savoir être inventifs,
11 | c'est-à-dire la grande majorité des cas.
12 |
13 | .. toctree::
14 | :maxdepth: 1
15 |
16 | edit_distance
17 | graph_distance
18 | gest
19 |
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1 |
2 | ##########
3 | Clustering
4 | ##########
5 |
6 | .. toctree::
7 | :maxdepth: 1
8 |
9 | kmeans
10 | gauss_mixture
11 | kohonen
12 |
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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 |
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1 |
2 | #########
3 | Métriques
4 | #########
5 |
6 | .. toctree::
7 | :maxdepth: 1
8 |
9 | roc
10 | pvalues
11 |
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/_doc/c_ml/index.rst:
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1 |
2 | .. _l-model-ml:
3 |
4 | ############
5 | Non linéaire
6 | ############
7 |
8 | Les paragraphes suivant abordent de façon plutôt théorique
9 | des modèles de machine learning.
10 |
11 | .. toctree::
12 | :maxdepth: 1
13 |
14 | rn/rn
15 | kppv
16 | missing_values_mf
17 | ../notebooks/ml/neural_tree
18 | ../notebooks/ml/neural_tree_onnx
19 | ../notebooks/ml/neural_tree_cost
20 |
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/_doc/c_ml/index_reg_lin.rst:
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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 |
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/_doc/c_ml/index_reg_log.rst:
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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 |
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1 |
2 | ===================
3 | Réseaux de neurones
4 | ===================
5 |
6 | Ce chapitre aborde les réseaux de neurones au travers de deux utilisations courantes,
7 | la :ref:`régression `
8 | et la :ref:`classification `
9 | et une qui l'est moins,
10 | l'`analyse en composantes principales `_
11 | ou :ref:`ACP `
12 | sans oublier les méthodes d'estimation des paramètres qui les composent,
13 | à savoir optimisations du premier et second ordre
14 | (:ref:`rn_optim_premier_ordre` et :ref:`rn_optim_second_ordre`)
15 | ainsi qu'une méthode permettant de supprimer des coefficients inutiles
16 | :ref:`selection_connexion`.
17 |
18 | .. toctree::
19 | :maxdepth: 2
20 |
21 | rn_1_def
22 | rn_2_reg
23 | rn_3_clas
24 | rn_4_densite
25 | rn_5_newton
26 | rn_6_apprentissage
27 | rn_7_clas2
28 | rn_8_prol
29 | rn_9_auto
30 | rn_biblio
31 |
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/_doc/c_nlp/completion.rst:
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1 |
2 | .. _l-completion0:
3 |
4 | ==========
5 | Complétion
6 | ==========
7 |
8 | .. index:: complétion, whoosh
9 |
10 | La `complétion `_ est un méchanisme
11 | qui permet à un utilisateur de saisir les mots de sa recherche avec moins
12 | de caractères qu'elle n'en contient. 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 |
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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 |
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/_doc/defthe_index.rst:
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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 |
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/_doc/examples/README.txt:
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1 | .. _examples-gallery:
2 |
3 | Gallery of examples
4 | ===================
5 |
6 |
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/_doc/glossary.rst:
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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 |
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/_doc/i_ex.rst:
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1 |
2 | .. _l-EX2:
3 |
4 | Examples
5 | ========
6 |
7 | .. exreflist::
8 | :contents:
9 |
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/_doc/index.rst:
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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 |
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/_doc/license.rst:
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1 | .. _l-license:
2 |
3 | License
4 | =======
5 |
6 | .. literalinclude:: LICENSE.txt
7 | :language: none
8 |
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/_doc/notebooks/README.txt:
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1 | Galleries
2 | =========
3 |
4 |
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/_doc/notebooks/dsgarden/index.rst:
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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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1 | Images
2 | ======
3 |
4 | .. nbgallery::
5 | :caption: Notebooks Gallery
6 | :name: rst-nb-gallery-image
7 | :glob:
8 |
9 | *
10 |
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/_doc/notebooks/index.rst:
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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 |
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/_doc/notebooks/metric/index.rst:
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1 | Métriques
2 | =========
3 |
4 | .. nbgallery::
5 | :caption: Notebooks Gallery
6 | :name: rst-nb-gallery-metric
7 | :glob:
8 |
9 | *
10 |
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/_doc/notebooks/ml/index.rst:
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1 | Machine Learning
2 | ================
3 |
4 | .. nbgallery::
5 | :caption: Notebooks Gallery
6 | :name: rst-nb-gallery-ml
7 | :glob:
8 |
9 | *
10 |
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/_doc/notebooks/nlp/index.rst:
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1 | NLP - Natural Language Processing
2 | =================================
3 |
4 | .. nbgallery::
5 | :caption: Notebooks Gallery
6 | :name: rst-nb-gallery-nlp
7 | :glob:
8 |
9 | *
10 |
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/_todo/clas_supervise/clas_super_biblio.tex:
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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 |
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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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/_todo/edit_distance/edit_bibliographie.tex:
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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{Damerau1964}{1964} {F. 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 |
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/_todo/hmm/fig_grmat.tex:
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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 |
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/_todo/hmm/fig_grmat2.tex:
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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 $0,3$}}
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17 | \put(-5,25) {\makebox(3,3){\small $0,6$}}
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39 |
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/_todo/ngrams/ngrams_biblio.tex:
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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 |
12 | \bibitemstyle{B�chet2004}{2004}{F. 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 |
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/_todo/space_metric/fig_cah.tex:
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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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/_todo/space_metric/fig_ray.tex:
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1 | \input{../../common/figure_begin.tex}
2 |
3 | \begin{picture}(50,30)(-5,-5)
4 |
5 | \put(5,15) {\circle{4}}
6 | \put(35,15){\circle{4}}
7 | \put(20,6) {\circle{4}}
8 |
9 | \put(4,13) {\makebox(3,3){\tiny x}}
10 | \put(34,13){\makebox(3,3){\tiny y}}
11 | \put(19,5) {\makebox(3,3){\tiny z}}
12 |
13 | \put(1,10) {\framebox(38,15)}
14 | \put(12,18){\makebox(15,5){\tiny $A=\acc{x,y}$}}
15 | \put(1,-5) {\makebox(15,5){\tiny $B=\acc{x,y,z}$}}
16 | \end{picture}
17 |
18 | \input{../../common/figure_end.tex}
19 |
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/_todo/space_metric/fig_try1.tex:
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1 | \input{../../common/figure_begin.tex}
2 |
3 |
4 | \unitlength 1mm
5 | \begin{picture}(40,33)(0,0)
6 | \put(0, 1) {\framebox(7,7){$x$}}
7 | \put(23, 1) {\framebox(7,7){$y$}}
8 | \put(33, 1) {\framebox(7,7){$z$}}
9 |
10 | \put(3, 8) {\line(0,1){2}}
11 | \put(27, 8) {\line(0,1){2}}
12 | \put(3, 10) {\line(1,0){24}}
13 | \put(15,10) {\line(0,1){2}}
14 |
15 | \put(10,12) {\framebox(10,7){$x,y$}}
16 |
17 | \put(37,8) {\line(0,1){13}}
18 | \put(15,19) {\line(0,1){2}}
19 | \put(15,21) {\line(1,0){22}}
20 | \put(26,21) {\line(0,1){2}}
21 |
22 | \put(20,23) {\framebox(12,7){$x,y,z$}}
23 |
24 | \end{picture}
25 |
26 | \input{../../common/figure_end.tex}
27 |
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/_todo/space_metric/fig_try2.tex:
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1 | \input{../../common/figure_begin.tex}
2 |
3 |
4 | \unitlength 1mm
5 | \begin{picture}(40,33)(0,0)
6 | \put(0, 1) {\framebox(7,7){$x$}}
7 | \put(23, 1) {\framebox(7,7){$y$}}
8 | \put(33, 1) {\framebox(7,7){$z$}}
9 |
10 | \put(27, 8) {\line(0,1){2}}
11 | \put(37, 8) {\line(0,1){2}}
12 | \put(27,10) {\line(1,0){10}}
13 | \put(32,10) {\line(0,1){2}}
14 |
15 | \put(27,12) {\framebox(10,7){$x,y$}}
16 |
17 | \put(3, 8) {\line(0,1){13}}
18 | \put(32,19) {\line(0,1){2}}
19 | \put(3, 21) {\line(1,0){29}}
20 | \put(17,21) {\line(0,1){2}}
21 |
22 | \put(11,23) {\framebox(12,7){$x,y,z$}}
23 | \end{picture}
24 |
25 |
26 | \input{../../common/figure_end.tex}
27 |
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https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/_todo/space_metric/image/rnd.png
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/_todo/space_metric/image/rtree1.png:
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https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/_todo/space_metric/image/rtree1.png
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/_todo/space_metric/image/rtree2.png:
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https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/_todo/space_metric/image/rtree2.png
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/_todo/squelette/fig_8mask1.tex:
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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 |
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/_todo/squelette/fig_8mask2.tex:
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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(35,35) {\line(1,1){10}}
19 | \put(35,45) {\line(1,-1){10}}
20 |
21 | \put(25,35) {\line(1,1){10}}
22 | \put(25,45) {\line(1,-1){10}}
23 |
24 | \put(15,35) {\line(1,1){10}}
25 | \put(15,45) {\line(1,-1){10}}
26 |
27 | \end{picture}
28 |
29 | \input{../../common/figure_end.tex}
30 |
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/_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 |
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/_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 |
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/_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 |
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/_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:
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/_todo/squelette/image/choi.png:
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--------------------------------------------------------------------------------
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/_todo/squelette/image/cross4.png:
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/_todo/squelette/image/kalmar1.png:
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/_todo/squelette/image/lhomer.png:
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/_todo/squelette/image/nuage.png:
--------------------------------------------------------------------------------
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/_todo/squelette/image/sing.png:
--------------------------------------------------------------------------------
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--------------------------------------------------------------------------------
/_todo/squelette/image/sixstop.png:
--------------------------------------------------------------------------------
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/_todo/squelette/image/ske_appari.png:
--------------------------------------------------------------------------------
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/_todo/squelette/image/ske_barbule1.png:
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/_todo/squelette/squelette_chapter.tex:
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1 |
2 | %-------------------------------------------------------------------------------------------------------------------------------------------------------------------
3 | \chapter{Squelettisation}
4 | %-------------------------------------------------------------------------------------------------------------------------------------------------------------------
5 |
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/_todo/squelette/squelette_titre.tex:
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/_todo/svm/svm_biblio.tex:
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https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/_todo/svm/svm_biblio.tex
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/_unittests/ut_data/test_wikipedia_dump.py:
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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 |
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/_unittests/ut_garden/test_poulet.py:
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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 |
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/_unittests/ut_graph/data/graph.gv:
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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 | }
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/_unittests/ut_image/data/eglise_zoom2.jpg:
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https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/_unittests/ut_image/data/eglise_zoom2.jpg
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/_unittests/ut_image/data/gradient--2.png:
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/_unittests/ut_image/data/gradient--2b.png:
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/_unittests/ut_image/test_binom.py:
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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 |
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/_unittests/ut_image/test_geometrie.py:
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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 |
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/_unittests/ut_image/test_random_image.py:
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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 |
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/_unittests/ut_ml/test_logreg.py:
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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 |
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/_unittests/ut_ml/test_nuage_points.py:
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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 |
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/_unittests/ut_nlp/test_completion_longer.py:
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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 |
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/_unittests/ut_nlp/test_completion_profiling.py:
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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 |
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/_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 |
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/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 |
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/mlstatpy/data/__init__.py:
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https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/mlstatpy/data/__init__.py
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/mlstatpy/data/data_exceptions.py:
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1 | class DataException(Exception):
2 | """
3 | raised when retrieving data
4 | """
5 |
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/mlstatpy/garden/__init__.py:
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https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/mlstatpy/garden/__init__.py
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/mlstatpy/graph/__init__.py:
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1 | from .graph_distance import GraphDistance
2 |
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/mlstatpy/image/__init__.py:
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https://raw.githubusercontent.com/sdpython/mlstatpy/3acae45b6ef87821b87f38e0b5cae07273802135/mlstatpy/image/__init__.py
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/mlstatpy/image/detection_segment/__init__.py:
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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 |
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/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 |
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/mlstatpy/ml/__init__.py:
--------------------------------------------------------------------------------
1 | from .roc import ROC
2 | from .voronoi import voronoi_estimation_from_lr
3 |
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/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 |
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/mlstatpy/optim/__init__.py:
--------------------------------------------------------------------------------
1 | from .sgd import SGDOptimizer
2 |
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/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 |
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/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 |
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/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 |
--------------------------------------------------------------------------------