Changelog

0.6.10

Add support for Numpy 2.0 #278
Improve performance of function attribute_extrema() #273

0.6.8

Add support for Python 3.12 and remove Python 3.7 #272
Fix bug with empty graphs in function bipartite_graph_matching() for minimum cost matching in bipartite graphs #270
Fix bug in function ultrametric_open() #268

0.6.7

Add function is_bipartite_graph() #265
Add function bipartite_graph_matching() for minimum cost matching in bipartite graphs #265
Add function match_pixels_image_2d() to compute the optimal matching between the pixels/contours of 2 images #265
Add “similarity” mode in Dasgupta quality measure dasgupta_cost() #264
Add to_undirected_graph() to the tree class #263
Add option to use a preexisting graph in graph_4_adjacency_2_khalimsky() #262

0.6.6

Add support for Python 3.11 #261
Improve notebooks section of the doc and add new notebooks on 3D mesh processing: *Watershed on a mesh with IGL* and *Watershed on a mesh with Trimesh* #258
Fix unwanted behavior in reconstruct_leaf_data() #254
Fix crash when creating an empty tree in Python #252

0.6.5

Add support for Python 3.10, remove support of Python 3.6 #243
Add an optional condition to the tree propagate and accumulate function see documentation Conditional sequential propagate and accumulate propagate_sequential_and_accumulate() #241

0.6.4

Add function to compute the line graph of a graph line_graph() #239
Add function to extract a subtree from a tree sub_tree() #238
Add new fast lowest common ancestor algorithm lowest_common_ancestor_preprocess() with \(O(n)\) time preprocessing and average \(O(1)\) time query (based on sparse table with blocks). The expected speedup is comprised between 1.2 and 1.8 compared to the previous method (parse table without block wich is still available). #237
Add options to set a global thread number limit set_num_threads() #234

0.6.2

Add support for Python 3.9, remove support of Python 3.5 #233

0.6.1

Breaking changes

C++ only: the children relation of trees is not computed automatically anymore, a call to the member function compute_children is required before accessing to any children information of a tree, see documentation Children relation #228

Other changes

Function bpt_canonical() can now process a graph given as a edge list (arrays of source and target vertices) #230
Add functions sources() and targets() to the classes UndirectedGraph and Tree which will returns views whenever possible #230
Add options for memory pre-allocation in UndirectedGraph constructor #232
Improve performance of regular grid graphs #231
Improve memory usage of marginal accumulators #228
Remove the need of the children relation anymore of trees in several functions #228
Bugfix: Regular grid graph will now always fulfils the CptGridGraph concept #229

0.6.0

Breaking changes

The functions filter_non_relevant_node_from_tree(), filter_small_nodes_from_tree(), and filter_weak_frontier_nodes_from_tree() now return canonized tree by default (old behaviour is obtained with the argument canonize_tree=False) #221
C++ only: the function bpt_canonical does not compute an explicit representation of the minimum spanning tree. The mst can still be reconstructed with the field mst_edge_map in the result using the new function subgraph_spanning f50ebc8
C++ only: fields of the class regular_graph are now private with public const accessors #211

Other changes

Major Python classes (Trees, graphs, …) are now pickable #212 and #214
Python classes now support dynamic attributes and higra attributes are now stored directly in the objects dictionaries with a direct access as class members. #209 and #210
Function bpt_canonical() now supports: construction of the tree based on an arbitrary given ordering, avoid the explicit computation of the minimum spanning tree, multidimentional edge weights (with lexicographic sorting). The documentation has also been improved. #222
Fast lowest ancestor computation is now better integrated to the Tree class. Calling lowest_common_ancestor_preprocess() will now make any call to lowest_common_ancestor() to use the pre-processing #216
Add parallel sorting functions sort() and arg_sort() (also support lexicographic ordering). #219
Add function subgraph() to extract the subgraph induced by a set of edges from an undirected graph 4cfa9ac
Functions for watershed hierarchies in Python can now return the non canonized tree (option canonize_tree=False) #220
Function canonize_hierarchy() can now return the node_map which associates any node of the canonized tree to a node of the original tree. 5701d29
Fix bug in filter_small_nodes_from_tree() when the base graph is a region adjacency graph #215

0.5.3

Fix bug in watershed_hierarchy_by_attribute(): on some conditions a large minima could be split in two or more regions. #205

0.5.2

Add function tree_monotonic_regression(): perform regression on a tree with an increasingness constraint #198
Add attribute attribute_moment_of_inertia(): first Hu moment on hierarchies constructed on 2d pixel graphs. #197
Add attribute attribute_topological_height(): number of edges on the longest path from a node to the leaf. #194
Improve support for regular graphs: add functions as_explicit_graph() (convert an implicit graph to an explicit graph), mask_2_neighbours() (create an neighbour list from an adjacency mask), get_nd_regular_graph() and get_nd_regular_implicit_graph() (create a regular implicit or explicit regular graph) #204
Improve conversions functions between adjacency matrices and undirected graphs: improve functions adjacency_matrix_2_undirected_graph() and undirected_graph_2_adjacency_matrix() (support for Scipy sparse matrix), and make_graph_from_points() (add symmetrization strategies). #201
Improve documentation of binary_partition_tree(), fix typos in Trees, add section Troubleshooting. #199 #196
Add altitudes increasingness assertions in several functions #193
Fix incorrect overload resolution in as_explicit_graph() when seeds are not of type np.int64 #203
Fix incorrect number of regions computation in fragmentation curves when ground-truth labels are not contiguous Hierarchy fragmentation curve #200
Fix delinearize_vertex_weights() not supporting Numpy arrays as shapes. #188
Fix save_tree() incorrectly failing with no tree attributes. #181

0.5.1

Decrease ABI compatibility of linux wheels to 8 (G++ 4.9) #177

0.5.0

Breaking change

Removed overload of function weight_graph() taking a custom weighting function. An equivalent, and much efficient, behavior can be achieved be applying a vectorized function on the edge list (see edge_list()) 5914574
Removed support for Python 3.4 #174

Other changes

Add support for Python 3.8 #174
Fix and add more efficient implementation of seeded watershed labelisation labelisation_seeded_watershed() #173
Parallelize several algorithms with Intel TBB (parallel sort, hierarchy construction, fast LCA, graph weighting) #168 #169
Add support for Intel Threading Building Blocks (TBB), see usage in Installation #168 #175
Update third party libs #170
Fix agglomerative clustering when the input graph has duplicated edges Binary partition hierarchy #167
Fix missing overloads for unsigned types in weight_graph() #166
Fix a bug in hierarchical watershed when leaves had non zero values Watershed hierarchy #165

0.4.5

Add new notebook: *Visualizing hierarchical image segmentations* #159
Add hierarchical cost function tree_sampling_divergence() #158
Add attribute attribute_tree_sampling_probability() 9faf740
Add attribute attribute_children_pair_sum_product() 0c6c958
Improvements in documentation #157
Add hierarchy algorithm component_tree_multivariate_tree_of_shapes_image2d() #156
Fix return policy in parents(), now returns a non writable reference e3eb5aa
Add option to deactivate immersion in tree of shapes 9efb6b6
Add algorithm tree_fusion_depth_map() 11e4f53

0.4.4

Fix codecov incorrectly including third party libs #152
Add hierarchical cost dasgupta_cost() #151
Add new attribute attribute_child_number() #149
Fix bug in simplify_tree() #148 and #150
Add argmin and argmax accumulators #146
Add new notebooks: PRL article illustrations and Astromical object detection with the Max-Tree #145 and #155
Documentation improvements #143, #153, #154
Update third party libs #141

0.4.2

Breaking change

Rename function attribute_mean_weights into attribute_mean_vertex_weights() #136

Other changes

Add SoftwareX illustrations notebook #140
Replace specialized C++ bindings for hierarchical watershed by a generic calls to watershed_hierarchy_by_attribute() #139
Fix inconsistency between Python and C++ definitions of attribute_volume() #138
Separate code and documentation on graph and tree attributes #137
Fix bug in attribute_mean_vertex_weights() #136

0.4.1

Add function accumulate_on_contours(). #134
Better handling of null perimeter in attribute_contour_strength(). #133
Add links to Python notebooks in the documentation. #132
Fix bug in common_type() support for bool type was missing. #131
Fix bug in attribute_contour_length() with tree of shapes when interpolated are removed. #129

0.4.0

Breaking change

Refactor attributes related to perimeter: there is now a single homogeneous function attribute_contour_length() that replaces attribute_perimeter_length, attribute_perimeter_length_component_tree, and attribute_perimeter_length_partition_tree #121 and #124
Add decorator auto_cache() for auto-caching of function results which replaces the decorator data_provider. #122 and #127

Other changes

Add a Cookiecutter project for c++ higra extension development Higra-cppextension-cookiecutter
Add more documentation for installation and compiling #123
Fix bug with integer data in attribute_gaussian_region_weights_model() #126
Fix bug in graph associated to the component_tree_tree_of_shapes_image2d() #120
Improve algorithm for attribute_extrema() #119
Moved repository to higra Github organization #118

0.3.8

Add attributes: attribute_height(), attribute_extrema(), attribute_extinction_value(), and attribute_dynamics() #110
Fix tree category propagation #109

0.3.7

Hardening: add range checks in various Python bindings #107
Bundle Higra and third party libraries into pip wheel for easy C++ extension development: get_include(), get_lib_include(), get_lib_cmake() #106
Make deleted_nodes parameter of reconstruct_leaf_data() optional #105