Methods

Summary

method class parent truncated documentation
__add__ Point ajoute un vecteur a celui-ci
__eq__ Point retourne True si les deux points self et a sont egaux, False sinon
__getitem__ GraphDistance returns a vertex or an edge if no vertex with the given index was found
__getitem__ CompletionSystem return elements[i]
__iadd__ Point ajoute un vecteur a celui-ci
__init__ Edge constructor
__init__ GraphDistance constructor
__init__ Vertex constructor
__init__ Point constructeur
__init__ Segment constructeur, pour éviter des erreurs d’etourderie, on crée des copies des extrémités a et b, comme ce sont des classes, …
__init__ NuagePoints constructeur
__init__ NuagePointsLaesa Construit la classe
__init__ MlGridBenchMark initialisation
__init__ ROC Initialisation with a dataframe and two or three columns:
__init__ CompletionTrieNode  
__init__ CompletionElement constructor
__init__ CompletionSystem fill the completion system
__iter__ CompletionTrieNode iterates on all nodes (sorted)
__iter__ CompletionSystem iterates over elements
__len__ ROC usual
__len__ CompletionSystem number of elements
__repr__ Edge usual
__repr__ GraphDistance usual
__repr__ Vertex usual
__repr__ Point usuel
__repr__ ROC show first elements, precision rate
__repr__ CompletionElement usual
__str__ Edge usual
__str__ GraphDistance usual
__str__ Vertex usual
__str__ Point permet d’afficher un point avec l’instruction print
__str__ Segment permet d’afficher le segment avec l’instruction print
__str__ ROC show first elements, precision rate
__str__ CompletionTrieNode usual
__sub__ Point soustraction de deux de vecteurs
_add CompletionTrieNode add a child
_private__init__ GraphDistance  
_private_string_path_matching GraphDistance  
all_completions CompletionTrieNode retrieve all completions for a node, the method does not need precompute_stat() to be run first
all_mks_completions CompletionTrieNode retrieve all completions for a node, the method assumes precompute_stat() was run
angle Point retourne l’angle du vecteur
arrondi Point retourne les coordonnées arrondies à l’entier le plus proche
auc ROC computes the area under the curve
auc_interval ROC Determines a confidence interval for the AUC with bootstrap.
bench_experiment MlGridBenchMark Calls meth fit.
clean_dead_ends GraphDistance  
common_paths GraphDistance  
compare_with_trie CompletionSystem compare the results with the other implementation
compute_metrics CompletionSystem Compute the metric for the completion itself.
compute_predecessor GraphDistance usual
compute_roc_curve ROC Computes a ROC curve with nb points avec nb, if nb == -1, there are as many as points as the data contains, if *bootstrap …
compute_successor GraphDistance  
confusion ROC Computes the confusion matrix for a specific score or all if score is None.
connect_root_and_leave GraphDistance  
directeur Segment retourne le vecteur directeur du segment, ce vecteur est norme
distance NuagePoints Retourne une distance entre deux éléments.
distance_matching_graphs_paths GraphDistance Computes an alignment between two graphs.
draw_vertices_edges GraphDistance  
edit_distance_path GraphDistance Tries to align two paths from two graphs.
end MlGridBenchMark nothing to do
enumerate_all_paths GraphDistance  
enumerate_test_metric CompletionSystem Evaluate the completion set on a set of queries, the function returns a list of CompletionElement with the three …
find CompletionTrieNode returns the node which holds all completions starting with a given prefix
find CompletionSystem not very efficient, find an item in a the list
fit NuagePoints Follows sklearn API.
fit NuagePointsLaesa Follows sklearn API.
fit MlGridBenchMark Train a model.
get_matching_functions GraphDistance returns default matching functions between two vertices and two edges
get_order_vertices GraphDistance  
graphs MlGridBenchMark Plot multiples graphs.
init_metrics CompletionElement initiate the metrics
is_edge Edge returns True
is_edge Vertex returns False
is_vertex Edge returns False
is_vertex Vertex returns True
items CompletionTrieNode iterates on children, iterates on weight, key, child
items CompletionSystem iterate on (e.value, e)
items_list CompletionTrieNode all children nodes inluding itself in a list
iter_leaves CompletionTrieNode iterators on leaves sorted per weight, yield weight, value
kneighbors NuagePoints Return the k nearest neighbors.
label NuagePoints Retourne le label de l’object d’indice i.
leaves CompletionTrieNode iterators on leaves
min_dynamic_keystroke CompletionTrieNode returns the dynamic minimum keystrokes for a word,
min_dynamic_keystroke2 CompletionTrieNode returns the modified dynamic minimum keystrokes for a word,
min_keystroke CompletionTrieNode Returns the minimum keystrokes for a word without optimisation, this function should be used if you only have a couple of …
min_keystroke0 CompletionTrieNode returns the minimum keystrokes for a word
normal Segment retourne le vecteur normal du segment, ce vecteur est norme
normalise Point normalise le vecteur, sa norme devient 1
norme Point retourne la norme
plot ROC Plot a ROC curve.
plot_graphs MlGridBenchMark Plots all graphs in the same graphs.
ppv NuagePoints Retourne l’élément le plus proche de obj et sa distance avec obj.
ppv NuagePointsLaesa Retourne l’élément le plus proche de obj et sa distance avec obj, utilise la sélection à l’aide pivots
precision ROC Computes the precision.
precompute_stat CompletionTrieNode computes and stores list of completions for each node, computes mks
predict_score_experiment MlGridBenchMark Calls method score.
preprocess_dataset MlGridBenchMark split the dataset into train and test
private_count_left_right GraphDistance  
private_kruskal_matrix GraphDistance  
random_cloud ROC resample among the data
roc_intersect ROC ROC curve is defined by a set of points. This function interpolates those points to determine y for any x.
roc_intersect_interval ROC computes a confidence interval for the value returned by roc_intersect().
scalaire Point calcule le produit scalaire
scalairek Point mulitplication par un scalaire
score MlGridBenchMark Score a model
selection_pivots NuagePointsLaesa Sélectionne nb pivots aléatoirements.
sort_values CompletionSystem sort the elements by value
sort_weight CompletionSystem sort the elements by value
str_all_completions CompletionTrieNode builds a string with all completions for all prefixes along the paths
str_all_completions CompletionElement builds a string with all completions for all prefixes along the paths, this is only available if parameter completions
str_mks CompletionElement return a string with metric information
str_mks0 CompletionElement return a string with metric information
test_metric CompletionSystem evaluate the completion set on a set of queries, the function returns a dictionary with the aggregated metrics and some …
to_dict CompletionSystem return a dictionary
tuples CompletionSystem iterate on (e.weight, e.value)
unsorted_iter CompletionTrieNode iterates on all nodes
update_metrics CompletionElement update the metrics
update_stat_dynamic CompletionTrieNode must be called after precompute_stat() and computes dynamic mks (see Dynamic Minimum Keystroke)