summaryrefslogtreecommitdiff
path: root/src
diff options
context:
space:
mode:
authorROUVREAU Vincent <vincent.rouvreau@inria.fr>2020-01-27 10:40:34 +0100
committerROUVREAU Vincent <vincent.rouvreau@inria.fr>2020-01-27 10:40:34 +0100
commitc7b70317b643b2eb9c603602da9c979388829821 (patch)
treeb6902eb51b29d0033f086f80ba3cb5d82c11c9d8 /src
parent6e9211cccad31145a5675a33689b167008ac1ffa (diff)
parent5d5f40493ce60f2a606793645bf713c60fb5284d (diff)
Merge branch 'master' into print_warnings_to_stderr
Diffstat (limited to 'src')
-rw-r--r--src/cmake/modules/GUDHI_user_version_target.cmake2
-rw-r--r--src/common/doc/main_page.md276
-rw-r--r--src/python/doc/diagram_readers_ref.rst (renamed from src/python/doc/reader_utils_ref.rst)10
-rw-r--r--src/python/doc/index.rst44
-rw-r--r--src/python/doc/point_cloud.rst22
-rw-r--r--src/python/doc/point_cloud_sum.inc15
-rwxr-xr-xsrc/python/example/alpha_complex_from_points_example.py7
-rw-r--r--src/python/gudhi/alpha_complex.pyx13
-rw-r--r--src/python/gudhi/cubical_complex.pyx2
-rw-r--r--src/python/gudhi/euclidean_strong_witness_complex.pyx4
-rw-r--r--src/python/gudhi/euclidean_witness_complex.pyx4
-rw-r--r--src/python/gudhi/nerve_gic.pyx12
-rw-r--r--src/python/gudhi/off_reader.pyx4
-rw-r--r--src/python/gudhi/periodic_cubical_complex.pyx2
-rw-r--r--src/python/gudhi/reader_utils.pyx16
-rw-r--r--src/python/gudhi/rips_complex.pyx2
-rw-r--r--src/python/gudhi/simplex_tree.pxd2
-rw-r--r--src/python/gudhi/simplex_tree.pyx2
-rw-r--r--src/python/gudhi/strong_witness_complex.pyx4
-rw-r--r--src/python/gudhi/subsampling.pyx26
-rw-r--r--src/python/gudhi/tangential_complex.pyx2
-rw-r--r--src/python/gudhi/witness_complex.pyx4
-rw-r--r--src/python/include/Alpha_complex_interface.h10
-rw-r--r--src/python/setup.py.in4
-rwxr-xr-xsrc/python/test/test_alpha_complex.py37
25 files changed, 302 insertions, 224 deletions
diff --git a/src/cmake/modules/GUDHI_user_version_target.cmake b/src/cmake/modules/GUDHI_user_version_target.cmake
index 4fa74330..0b361a0f 100644
--- a/src/cmake/modules/GUDHI_user_version_target.cmake
+++ b/src/cmake/modules/GUDHI_user_version_target.cmake
@@ -33,8 +33,6 @@ add_custom_command(TARGET user_version PRE_BUILD COMMAND ${CMAKE_COMMAND} -E
copy_directory ${CMAKE_CURRENT_BINARY_DIR}/biblio ${GUDHI_USER_VERSION_DIR}/biblio)
add_custom_command(TARGET user_version PRE_BUILD COMMAND ${CMAKE_COMMAND} -E
- copy ${CMAKE_SOURCE_DIR}/Conventions.txt ${GUDHI_USER_VERSION_DIR}/Conventions.txt)
-add_custom_command(TARGET user_version PRE_BUILD COMMAND ${CMAKE_COMMAND} -E
copy ${CMAKE_SOURCE_DIR}/README.md ${GUDHI_USER_VERSION_DIR}/README.md)
add_custom_command(TARGET user_version PRE_BUILD COMMAND ${CMAKE_COMMAND} -E
copy ${CMAKE_SOURCE_DIR}/LICENSE ${GUDHI_USER_VERSION_DIR}/LICENSE)
diff --git a/src/common/doc/main_page.md b/src/common/doc/main_page.md
index 0b4bfb7a..6ea10b88 100644
--- a/src/common/doc/main_page.md
+++ b/src/common/doc/main_page.md
@@ -4,8 +4,8 @@
\image html "Gudhi_banner.png"
<br><br><br><br>
-## Complexes {#Complexes}
-### Cubical complex
+## Data structures for cell complexes {#Complexes}
+### Cubical complexes
<table>
<tr>
@@ -29,246 +29,269 @@
</tr>
</table>
-### Simplicial complex
-
-#### Alpha complex
+### Simplicial complexes
+#### Simplex tree
<table>
<tr>
<td width="35%" rowspan=2>
- \image html "alpha_complex_representation.png"
+ \image html "Simplex_tree_representation.png"
</td>
<td width="50%">
- Alpha complex is a simplicial complex constructed from the finite cells of a Delaunay Triangulation.<br>
- The filtration value of each simplex is computed as the square of the circumradius of the simplex if the
- circumsphere is empty (the simplex is then said to be Gabriel), and as the minimum of the filtration
- values of the codimension 1 cofaces that make it not Gabriel otherwise.
- All simplices that have a filtration value \f$ > \alpha^2 \f$ are removed from the Delaunay complex
- when creating the simplicial complex if it is specified.<br>
- For performances reasons, it is advised to use \ref cgal &ge; 5.0.0.
+ The simplex tree is an efficient and flexible
+ data structure for representing general (filtered) simplicial complexes. The data structure
+ is described in \cite boissonnatmariasimplextreealgorithmica .
</td>
<td width="15%">
- <b>Author:</b> Vincent Rouvreau<br>
- <b>Introduced in:</b> GUDHI 1.3.0<br>
- <b>Copyright:</b> MIT [(GPL v3)](../../licensing/)<br>
- <b>Requires:</b> \ref eigen &ge; 3.1.0 and \ref cgal &ge; 4.11.0
+ <b>Author:</b> Cl&eacute;ment Maria<br>
+ <b>Introduced in:</b> GUDHI 1.0.0<br>
+ <b>Copyright:</b> MIT<br>
</td>
</tr>
<tr>
<td colspan=2 height="25">
- <b>User manual:</b> \ref alpha_complex
+ <b>User manual:</b> \ref simplex_tree
</td>
</tr>
</table>
-#### Čech complex
+#### Toplex Map
<table>
- <tr>
+ <tr>
<td width="35%" rowspan=2>
- \image html "cech_complex_representation.png"
+ \image html "map.png"
</td>
<td width="50%">
- The Čech complex is a simplicial complex constructed from a proximity graph.
- The set of all simplices is filtered by the radius of their minimal enclosing ball.
+ The Toplex map data structure is composed firstly of a raw storage of toplices (the maximal simplices)
+ and secondly of a map which associate any vertex to a set of pointers toward all toplices
+ containing this vertex.
</td>
<td width="15%">
- <b>Author:</b> Vincent Rouvreau<br>
- <b>Introduced in:</b> GUDHI 2.2.0<br>
- <b>Copyright:</b> MIT [(GPL v3)](../../licensing/)<br>
- <b>Includes:</b> [Miniball](https://people.inf.ethz.ch/gaertner/subdir/software/miniball.html)<br>
+ <b>Author:</b> Fran&ccedil;ois Godi<br>
+ <b>Introduced in:</b> GUDHI 2.1.0<br>
+ <b>Copyright:</b> MIT<br>
</td>
</tr>
<tr>
<td colspan=2 height="25">
- <b>User manual:</b> \ref cech_complex
+ <b>User manual:</b> \ref toplex_map
</td>
</tr>
</table>
-#### Rips complex
+#### Skeleton blocker
<table>
<tr>
<td width="35%" rowspan=2>
- \image html "rips_complex_representation.png"
+ \image html "ds_representation.png"
</td>
<td width="50%">
- Rips complex is a simplicial complex constructed from a one skeleton graph.<br>
- The filtration value of each edge is computed from a user-given distance function and is inserted until a
- user-given threshold value.<br>
- This complex can be built from a point cloud and a distance function, or from a distance matrix.
+ The Skeleton-Blocker data-structure proposes a light encoding for simplicial complexes by storing only an *implicit*
+ representation of its simplices \cite socg_blockers_2011,\cite blockers2012. Intuitively, it just stores the
+ 1-skeleton of a simplicial complex with a graph and the set of its "missing faces" that is very small in practice.
+ This data-structure handles all simplicial complexes operations such as simplex enumeration or simplex removal but
+ operations that are particularly efficient are operations that do not require simplex enumeration such as edge
+ iteration, link computation or simplex contraction.
</td>
<td width="15%">
- <b>Author:</b> Cl&eacute;ment Maria, Pawel Dlotko, Vincent Rouvreau, Marc Glisse<br>
- <b>Introduced in:</b> GUDHI 2.0.0<br>
+ <b>Author:</b> David Salinas<br>
+ <b>Introduced in:</b> GUDHI 1.1.0<br>
<b>Copyright:</b> MIT<br>
</td>
</tr>
<tr>
<td colspan=2 height="25">
- <b>User manual:</b> \ref rips_complex
+ <b>User manual:</b> \ref skbl
</td>
</tr>
</table>
-#### Witness complex
+#### Basic operation: contraction
<table>
<tr>
<td width="35%" rowspan=2>
- \image html "Witness_complex_representation.png"
+ \image html "sphere_contraction_representation.png"
</td>
<td width="50%">
- Witness complex \f$ Wit(W,L) \f$ is a simplicial complex defined on two sets of points in \f$\mathbb{R}^D\f$.
- The data structure is described in \cite boissonnatmariasimplextreealgorithmica .
+ The purpose of this package is to offer a user-friendly interface for edge contraction simplification of huge
+ simplicial complexes. It uses the \ref skbl data-structure whose size remains small during simplification of most
+ used geometrical complexes of topological data analysis such as the Rips or the Delaunay complexes. In practice,
+ the size of this data-structure is even much lower than the total number of simplices.
</td>
<td width="15%">
- <b>Author:</b> Siargey Kachanovich<br>
- <b>Introduced in:</b> GUDHI 1.3.0<br>
- <b>Copyright:</b> MIT ([GPL v3](../../licensing/) for Euclidean version)<br>
- <b>Euclidean version requires:</b> \ref eigen &ge; 3.1.0 and \ref cgal &ge; 4.11.0
+ <b>Author:</b> David Salinas<br>
+ <b>Introduced in:</b> GUDHI 1.1.0<br>
+ <b>Copyright:</b> MIT [(LGPL v3)](../../licensing/)<br>
+ <b>Requires:</b> \ref cgal &ge; 4.11.0
</td>
</tr>
<tr>
<td colspan=2 height="25">
- <b>User manual:</b> \ref witness_complex
+ <b>User manual:</b> \ref contr
</td>
</tr>
</table>
-### Cover Complexes
+## Filtrations and reconstructions {#FiltrationsReconstructions}
+### Alpha complex
+
<table>
<tr>
<td width="35%" rowspan=2>
- \image html "gicvisu.jpg"
+ \image html "alpha_complex_representation.png"
</td>
<td width="50%">
- Nerves and Graph Induced Complexes are cover complexes, i.e. simplicial complexes that provably contain
- topological information about the input data. They can be computed with a cover of the
- data, that comes i.e. from the preimage of a family of intervals covering the image
- of a scalar-valued function defined on the data. <br>
+ Alpha complex is a simplicial complex constructed from the finite cells of a Delaunay Triangulation.<br>
+ The filtration value of each simplex is computed as the square of the circumradius of the simplex if the
+ circumsphere is empty (the simplex is then said to be Gabriel), and as the minimum of the filtration
+ values of the codimension 1 cofaces that make it not Gabriel otherwise.
+ All simplices that have a filtration value \f$ > \alpha^2 \f$ are removed from the Delaunay complex
+ when creating the simplicial complex if it is specified.<br>
+ For performances reasons, it is advised to use \ref cgal &ge; 5.0.0.
</td>
<td width="15%">
- <b>Author:</b> Mathieu Carri&egrave;re<br>
- <b>Introduced in:</b> GUDHI 2.1.0<br>
+ <b>Author:</b> Vincent Rouvreau<br>
+ <b>Introduced in:</b> GUDHI 1.3.0<br>
<b>Copyright:</b> MIT [(GPL v3)](../../licensing/)<br>
- <b>Requires:</b> \ref cgal &ge; 4.11.0
+ <b>Requires:</b> \ref eigen &ge; 3.1.0 and \ref cgal &ge; 4.11.0
</td>
</tr>
<tr>
<td colspan=2 height="25">
- <b>User manual:</b> \ref cover_complex
+ <b>User manual:</b> \ref alpha_complex
</td>
</tr>
</table>
-## Data structures and basic operations {#DataStructuresAndBasicOperations}
+### Čech complex
-### Data structures
+<table>
+ <tr>
+ <td width="35%" rowspan=2>
+ \image html "cech_complex_representation.png"
+ </td>
+ <td width="50%">
+ The Čech complex is a simplicial complex constructed from a proximity graph.
+ The set of all simplices is filtered by the radius of their minimal enclosing ball.
+ </td>
+ <td width="15%">
+ <b>Author:</b> Vincent Rouvreau<br>
+ <b>Introduced in:</b> GUDHI 2.2.0<br>
+ <b>Copyright:</b> MIT [(GPL v3)](../../licensing/)<br>
+ <b>Includes:</b> [Miniball](https://people.inf.ethz.ch/gaertner/subdir/software/miniball.html)<br>
+ </td>
+ </tr>
+ <tr>
+ <td colspan=2 height="25">
+ <b>User manual:</b> \ref cech_complex
+ </td>
+ </tr>
+</table>
+
+### Rips complex
-#### Simplex tree
<table>
<tr>
<td width="35%" rowspan=2>
- \image html "Simplex_tree_representation.png"
+ \image html "rips_complex_representation.png"
</td>
<td width="50%">
- The simplex tree is an efficient and flexible
- data structure for representing general (filtered) simplicial complexes. The data structure
- is described in \cite boissonnatmariasimplextreealgorithmica .
+ Rips complex is a simplicial complex constructed from a one skeleton graph.<br>
+ The filtration value of each edge is computed from a user-given distance function and is inserted until a
+ user-given threshold value.<br>
+ This complex can be built from a point cloud and a distance function, or from a distance matrix.
</td>
<td width="15%">
- <b>Author:</b> Cl&eacute;ment Maria<br>
- <b>Introduced in:</b> GUDHI 1.0.0<br>
+ <b>Author:</b> Cl&eacute;ment Maria, Pawel Dlotko, Vincent Rouvreau, Marc Glisse<br>
+ <b>Introduced in:</b> GUDHI 2.0.0<br>
<b>Copyright:</b> MIT<br>
</td>
</tr>
<tr>
<td colspan=2 height="25">
- <b>User manual:</b> \ref simplex_tree
+ <b>User manual:</b> \ref rips_complex
</td>
</tr>
</table>
-#### Skeleton blocker
+### Witness complex
<table>
<tr>
<td width="35%" rowspan=2>
- \image html "ds_representation.png"
+ \image html "Witness_complex_representation.png"
</td>
<td width="50%">
- The Skeleton-Blocker data-structure proposes a light encoding for simplicial complexes by storing only an *implicit*
- representation of its simplices \cite socg_blockers_2011,\cite blockers2012. Intuitively, it just stores the
- 1-skeleton of a simplicial complex with a graph and the set of its "missing faces" that is very small in practice.
- This data-structure handles all simplicial complexes operations such as simplex enumeration or simplex removal but
- operations that are particularly efficient are operations that do not require simplex enumeration such as edge
- iteration, link computation or simplex contraction.
+ Witness complex \f$ Wit(W,L) \f$ is a simplicial complex defined on two sets of points in \f$\mathbb{R}^D\f$.
+ The data structure is described in \cite boissonnatmariasimplextreealgorithmica .
</td>
<td width="15%">
- <b>Author:</b> David Salinas<br>
- <b>Introduced in:</b> GUDHI 1.1.0<br>
- <b>Copyright:</b> MIT<br>
+ <b>Author:</b> Siargey Kachanovich<br>
+ <b>Introduced in:</b> GUDHI 1.3.0<br>
+ <b>Copyright:</b> MIT ([GPL v3](../../licensing/) for Euclidean version)<br>
+ <b>Euclidean version requires:</b> \ref eigen &ge; 3.1.0 and \ref cgal &ge; 4.11.0
</td>
</tr>
<tr>
<td colspan=2 height="25">
- <b>User manual:</b> \ref skbl
+ <b>User manual:</b> \ref witness_complex
</td>
</tr>
</table>
-#### Toplex Map
-
+### Cover Complexes
<table>
<tr>
<td width="35%" rowspan=2>
- \image html "map.png"
+ \image html "gicvisu.jpg"
</td>
<td width="50%">
- The Toplex map data structure is composed firstly of a raw storage of toplices (the maximal simplices)
- and secondly of a map which associate any vertex to a set of pointers toward all toplices
- containing this vertex.
+ Nerves and Graph Induced Complexes are cover complexes, i.e. simplicial complexes that provably contain
+ topological information about the input data. They can be computed with a cover of the
+ data, that comes i.e. from the preimage of a family of intervals covering the image
+ of a scalar-valued function defined on the data. <br>
</td>
<td width="15%">
- <b>Author:</b> Fran&ccedil;ois Godi<br>
+ <b>Author:</b> Mathieu Carri&egrave;re<br>
<b>Introduced in:</b> GUDHI 2.1.0<br>
- <b>Copyright:</b> MIT<br>
+ <b>Copyright:</b> MIT [(GPL v3)](../../licensing/)<br>
+ <b>Requires:</b> \ref cgal &ge; 4.11.0
</td>
</tr>
<tr>
<td colspan=2 height="25">
- <b>User manual:</b> \ref toplex_map
+ <b>User manual:</b> \ref cover_complex
</td>
</tr>
</table>
-### Basic operations
-
-#### Contraction
+### Tangential complex
<table>
<tr>
<td width="35%" rowspan=2>
- \image html "sphere_contraction_representation.png"
+ \image html "tc_examples.png"
</td>
<td width="50%">
- The purpose of this package is to offer a user-friendly interface for edge contraction simplification of huge
- simplicial complexes. It uses the \ref skbl data-structure whose size remains small during simplification of most
- used geometrical complexes of topological data analysis such as the Rips or the Delaunay complexes. In practice,
- the size of this data-structure is even much lower than the total number of simplices.
+ A Tangential Delaunay complex is a <a target="_blank" href="https://en.wikipedia.org/wiki/Simplicial_complex">simplicial complex</a>
+ designed to reconstruct a \f$ k \f$-dimensional manifold embedded in \f$ d \f$-dimensional Euclidean space.
+ The input is a point sample coming from an unknown manifold.
+ The running time depends only linearly on the extrinsic dimension \f$ d \f$
+ and exponentially on the intrinsic dimension \f$ k \f$.
</td>
<td width="15%">
- <b>Author:</b> David Salinas<br>
- <b>Introduced in:</b> GUDHI 1.1.0<br>
- <b>Copyright:</b> MIT [(LGPL v3)](../../licensing/)<br>
- <b>Requires:</b> \ref cgal &ge; 4.11.0
+ <b>Author:</b> Cl&eacute;ment Jamin<br>
+ <b>Introduced in:</b> GUDHI 2.0.0<br>
+ <b>Copyright:</b> MIT [(GPL v3)](../../licensing/)<br>
+ <b>Requires:</b> \ref eigen &ge; 3.1.0 and \ref cgal &ge; 4.11.0
</td>
</tr>
<tr>
<td colspan=2 height="25">
- <b>User manual:</b> \ref contr
+ <b>User manual:</b> \ref tangential_complex
</td>
</tr>
</table>
@@ -305,36 +328,6 @@
</tr>
</table>
-## Manifold reconstruction {#ManifoldReconstruction}
-
-### Tangential complex
-
-<table>
- <tr>
- <td width="35%" rowspan=2>
- \image html "tc_examples.png"
- </td>
- <td width="50%">
- A Tangential Delaunay complex is a <a target="_blank" href="https://en.wikipedia.org/wiki/Simplicial_complex">simplicial complex</a>
- designed to reconstruct a \f$ k \f$-dimensional manifold embedded in \f$ d \f$-dimensional Euclidean space.
- The input is a point sample coming from an unknown manifold.
- The running time depends only linearly on the extrinsic dimension \f$ d \f$
- and exponentially on the intrinsic dimension \f$ k \f$.
- </td>
- <td width="15%">
- <b>Author:</b> Cl&eacute;ment Jamin<br>
- <b>Introduced in:</b> GUDHI 2.0.0<br>
- <b>Copyright:</b> MIT [(GPL v3)](../../licensing/)<br>
- <b>Requires:</b> \ref eigen &ge; 3.1.0 and \ref cgal &ge; 4.11.0
- </td>
- </tr>
- <tr>
- <td colspan=2 height="25">
- <b>User manual:</b> \ref tangential_complex
- </td>
- </tr>
-</table>
-
## Topological descriptors tools {#TopologicalDescriptorsTools}
### Bottleneck distance
@@ -390,3 +383,26 @@
</td>
</tr>
</table>
+
+## Point cloud utilities {#PointCloudUtils}
+
+<table>
+ <tr>
+ <td width="35%" rowspan=2>
+ \f$(x_1,\ldots,x_d)\f$
+ </td>
+ <td width="50%">
+ This contains various tools to handle point clouds: spatial searching, subsampling, etc.
+ </td>
+ <td width="15%">
+ <b>Author:</b> Clément Jamin<br>
+ <b>Introduced in:</b> GUDHI 1.3.0<br>
+ <b>Copyright:</b> MIT [(GPL v3)](../../licensing/)<br>
+ </td>
+ </tr>
+ <tr>
+ <td colspan=2 height="25">
+ <b>Manuals:</b> \ref spatial_searching, \ref subsampling
+ </td>
+ </tr>
+</table>
diff --git a/src/python/doc/reader_utils_ref.rst b/src/python/doc/diagram_readers_ref.rst
index b8977a5a..c79daf9c 100644
--- a/src/python/doc/reader_utils_ref.rst
+++ b/src/python/doc/diagram_readers_ref.rst
@@ -2,13 +2,9 @@
.. To get rid of WARNING: document isn't included in any toctree
-=============================
-Reader utils reference manual
-=============================
-
-.. autofunction:: gudhi.read_points_from_off_file
-
-.. autofunction:: gudhi.read_lower_triangular_matrix_from_csv_file
+================================
+Diagram readers reference manual
+================================
.. autofunction:: gudhi.read_persistence_intervals_grouped_by_dimension
diff --git a/src/python/doc/index.rst b/src/python/doc/index.rst
index c36a578f..3387a64f 100644
--- a/src/python/doc/index.rst
+++ b/src/python/doc/index.rst
@@ -6,8 +6,8 @@ GUDHI Python modules documentation
:alt: Gudhi banner
:figclass: align-center
-Complexes
-*********
+Data structures for cell complexes
+**********************************
Cubical complexes
=================
@@ -17,18 +17,26 @@ Cubical complexes
Simplicial complexes
====================
+Simplex tree
+------------
+
+.. include:: simplex_tree_sum.inc
+
+Filtrations and reconstructions
+*******************************
+
Alpha complex
--------------
+=============
.. include:: alpha_complex_sum.inc
Rips complex
-------------
+============
.. include:: rips_complex_sum.inc
Witness complex
----------------
+===============
.. include:: witness_complex_sum.inc
@@ -37,16 +45,10 @@ Cover complexes
.. include:: nerve_gic_complex_sum.inc
-Data structures and basic operations
-************************************
-
-Data structures
-===============
-
-Simplex tree
-------------
+Tangential complex
+==================
-.. include:: simplex_tree_sum.inc
+.. include:: tangential_complex_sum.inc
Topological descriptors computation
***********************************
@@ -56,15 +58,6 @@ Persistence cohomology
.. include:: persistent_cohomology_sum.inc
-Manifold reconstruction
-***********************
-
-Tangential complex
-==================
-
-.. include:: tangential_complex_sum.inc
-
-
Topological descriptors tools
*****************************
@@ -88,6 +81,11 @@ Persistence graphical tools
.. include:: persistence_graphical_tools_sum.inc
+Point cloud utilities
+*********************
+
+.. include:: point_cloud_sum.inc
+
Bibliography
************
diff --git a/src/python/doc/point_cloud.rst b/src/python/doc/point_cloud.rst
new file mode 100644
index 00000000..d668428a
--- /dev/null
+++ b/src/python/doc/point_cloud.rst
@@ -0,0 +1,22 @@
+:orphan:
+
+.. To get rid of WARNING: document isn't included in any toctree
+
+============================
+Point cloud utilities manual
+============================
+
+File Readers
+------------
+
+.. autofunction:: gudhi.read_points_from_off_file
+
+.. autofunction:: gudhi.read_lower_triangular_matrix_from_csv_file
+
+Subsampling
+-----------
+
+.. automodule:: gudhi.subsampling
+ :members:
+ :special-members:
+ :show-inheritance:
diff --git a/src/python/doc/point_cloud_sum.inc b/src/python/doc/point_cloud_sum.inc
new file mode 100644
index 00000000..85d52de7
--- /dev/null
+++ b/src/python/doc/point_cloud_sum.inc
@@ -0,0 +1,15 @@
+.. table::
+ :widths: 30 50 20
+
+ +----------------------------------------------------------------+------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------+
+ | | :math:`(x_1, x_2, \ldots, x_d)` | Utilities to process point clouds: read from file, subsample, etc. | :Author: Vincent Rouvreau |
+ | | :math:`(y_1, y_2, \ldots, y_d)` | | |
+ | | | :Introduced in: GUDHI 2.0.0 |
+ | | | |
+ | | | :Copyright: MIT (`GPL v3 </licensing/>`_) |
+ | | Parts of this package require CGAL. | |
+ | | | :Requires: `Eigen <installation.html#eigen>`__ :math:`\geq` 3.1.0 and `CGAL <installation.html#cgal>`__ :math:`\geq` 4.11.0 |
+ | | | |
+ +----------------------------------------------------------------+------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------+
+ | * :doc:`point_cloud` |
+ +----------------------------------------------------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
diff --git a/src/python/example/alpha_complex_from_points_example.py b/src/python/example/alpha_complex_from_points_example.py
index a746998c..844d7a82 100755
--- a/src/python/example/alpha_complex_from_points_example.py
+++ b/src/python/example/alpha_complex_from_points_example.py
@@ -52,4 +52,9 @@ print("star([0])=", simplex_tree.get_star([0]))
print("coface([0], 1)=", simplex_tree.get_cofaces([0], 1))
print("point[0]=", alpha_complex.get_point(0))
-print("point[5]=", alpha_complex.get_point(5))
+try:
+ print("point[5]=", alpha_complex.get_point(5))
+except IndexError:
+ pass
+else:
+ assert False
diff --git a/src/python/gudhi/alpha_complex.pyx b/src/python/gudhi/alpha_complex.pyx
index 4ff37437..dab4b56f 100644
--- a/src/python/gudhi/alpha_complex.pyx
+++ b/src/python/gudhi/alpha_complex.pyx
@@ -26,11 +26,11 @@ __license__ = "GPL v3"
cdef extern from "Alpha_complex_interface.h" namespace "Gudhi":
cdef cppclass Alpha_complex_interface "Gudhi::alpha_complex::Alpha_complex_interface":
- Alpha_complex_interface(vector[vector[double]] points)
+ Alpha_complex_interface(vector[vector[double]] points) except +
# bool from_file is a workaround for cython to find the correct signature
- Alpha_complex_interface(string off_file, bool from_file)
- vector[double] get_point(int vertex)
- void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square)
+ Alpha_complex_interface(string off_file, bool from_file) except +
+ vector[double] get_point(int vertex) except +
+ void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square) except +
# AlphaComplex python interface
cdef class AlphaComplex:
@@ -71,7 +71,7 @@ cdef class AlphaComplex:
def __cinit__(self, points = None, off_file = ''):
if off_file:
if os.path.isfile(off_file):
- self.thisptr = new Alpha_complex_interface(str.encode(off_file), True)
+ self.thisptr = new Alpha_complex_interface(off_file.encode('utf-8'), True)
else:
print("file " + off_file + " not found.")
else:
@@ -98,8 +98,7 @@ cdef class AlphaComplex:
:rtype: list of float
:returns: the point.
"""
- cdef vector[double] point = self.thisptr.get_point(vertex)
- return point
+ return self.thisptr.get_point(vertex)
def create_simplex_tree(self, max_alpha_square = float('inf')):
"""
diff --git a/src/python/gudhi/cubical_complex.pyx b/src/python/gudhi/cubical_complex.pyx
index 28913a32..1dd30b4e 100644
--- a/src/python/gudhi/cubical_complex.pyx
+++ b/src/python/gudhi/cubical_complex.pyx
@@ -87,7 +87,7 @@ cdef class CubicalComplex:
elif ((dimensions is None) and (top_dimensional_cells is None)
and (perseus_file != '')):
if os.path.isfile(perseus_file):
- self.thisptr = new Bitmap_cubical_complex_base_interface(str.encode(perseus_file))
+ self.thisptr = new Bitmap_cubical_complex_base_interface(perseus_file.encode('utf-8'))
else:
print("file " + perseus_file + " not found.", file=sys.stderr)
else:
diff --git a/src/python/gudhi/euclidean_strong_witness_complex.pyx b/src/python/gudhi/euclidean_strong_witness_complex.pyx
index 9889f92c..aca6084e 100644
--- a/src/python/gudhi/euclidean_strong_witness_complex.pyx
+++ b/src/python/gudhi/euclidean_strong_witness_complex.pyx
@@ -22,9 +22,9 @@ __license__ = "GPL v3"
cdef extern from "Euclidean_strong_witness_complex_interface.h" namespace "Gudhi":
cdef cppclass Euclidean_strong_witness_complex_interface "Gudhi::witness_complex::Euclidean_strong_witness_complex_interface":
Euclidean_strong_witness_complex_interface(vector[vector[double]] landmarks, vector[vector[double]] witnesses)
- void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square)
+ void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square) except +
void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square,
- unsigned limit_dimension)
+ unsigned limit_dimension) except +
vector[double] get_point(unsigned vertex)
# EuclideanStrongWitnessComplex python interface
diff --git a/src/python/gudhi/euclidean_witness_complex.pyx b/src/python/gudhi/euclidean_witness_complex.pyx
index e3ce0e82..fb0c2201 100644
--- a/src/python/gudhi/euclidean_witness_complex.pyx
+++ b/src/python/gudhi/euclidean_witness_complex.pyx
@@ -22,9 +22,9 @@ __license__ = "GPL v3"
cdef extern from "Euclidean_witness_complex_interface.h" namespace "Gudhi":
cdef cppclass Euclidean_witness_complex_interface "Gudhi::witness_complex::Euclidean_witness_complex_interface":
Euclidean_witness_complex_interface(vector[vector[double]] landmarks, vector[vector[double]] witnesses)
- void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square)
+ void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square) except +
void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square,
- unsigned limit_dimension)
+ unsigned limit_dimension) except +
vector[double] get_point(unsigned vertex)
# EuclideanWitnessComplex python interface
diff --git a/src/python/gudhi/nerve_gic.pyx b/src/python/gudhi/nerve_gic.pyx
index 5eb9be0d..022466c5 100644
--- a/src/python/gudhi/nerve_gic.pyx
+++ b/src/python/gudhi/nerve_gic.pyx
@@ -182,7 +182,7 @@ cdef class CoverComplex:
:returns: Read file status.
"""
if os.path.isfile(off_file):
- return self.thisptr.read_point_cloud(str.encode(off_file))
+ return self.thisptr.read_point_cloud(off_file.encode('utf-8'))
else:
print("file " + off_file + " not found.", file=sys.stderr)
return False
@@ -214,7 +214,7 @@ cdef class CoverComplex:
:type color_file_name: string
"""
if os.path.isfile(color_file_name):
- self.thisptr.set_color_from_file(str.encode(color_file_name))
+ self.thisptr.set_color_from_file(color_file_name.encode('utf-8'))
else:
print("file " + color_file_name + " not found.", file=sys.stderr)
@@ -235,7 +235,7 @@ cdef class CoverComplex:
:type cover_file_name: string
"""
if os.path.isfile(cover_file_name):
- self.thisptr.set_cover_from_file(str.encode(cover_file_name))
+ self.thisptr.set_cover_from_file(cover_file_name.encode('utf-8'))
else:
print("file " + cover_file_name + " not found.", file=sys.stderr)
@@ -268,7 +268,7 @@ cdef class CoverComplex:
:type func_file_name: string
"""
if os.path.isfile(func_file_name):
- self.thisptr.set_function_from_file(str.encode(func_file_name))
+ self.thisptr.set_function_from_file(func_file_name.encode('utf-8'))
else:
print("file " + func_file_name + " not found.", file=sys.stderr)
@@ -309,7 +309,7 @@ cdef class CoverComplex:
:type graph_file_name: string
"""
if os.path.isfile(graph_file_name):
- self.thisptr.set_graph_from_file(str.encode(graph_file_name))
+ self.thisptr.set_graph_from_file(graph_file_name.encode('utf-8'))
else:
print("file " + graph_file_name + " not found.", file=sys.stderr)
@@ -370,7 +370,7 @@ cdef class CoverComplex:
:param type: either "GIC" or "Nerve".
:type type: string
"""
- self.thisptr.set_type(str.encode(type))
+ self.thisptr.set_type(type.encode('utf-8'))
def set_verbose(self, verbose):
"""Specifies whether the program should display information or not.
diff --git a/src/python/gudhi/off_reader.pyx b/src/python/gudhi/off_reader.pyx
index ef8f420a..0a828b83 100644
--- a/src/python/gudhi/off_reader.pyx
+++ b/src/python/gudhi/off_reader.pyx
@@ -28,11 +28,11 @@ def read_points_from_off_file(off_file=''):
:type off_file: string
:returns: The point set.
- :rtype: vector[vector[double]]
+ :rtype: List[List[float]]
"""
if off_file:
if os.path.isfile(off_file):
- return read_points_from_OFF_file(str.encode(off_file))
+ return read_points_from_OFF_file(off_file.encode('utf-8'))
else:
print("file " + off_file + " not found.", file=sys.stderr)
return []
diff --git a/src/python/gudhi/periodic_cubical_complex.pyx b/src/python/gudhi/periodic_cubical_complex.pyx
index 4ec06524..fd08b976 100644
--- a/src/python/gudhi/periodic_cubical_complex.pyx
+++ b/src/python/gudhi/periodic_cubical_complex.pyx
@@ -95,7 +95,7 @@ cdef class PeriodicCubicalComplex:
elif ((dimensions is None) and (top_dimensional_cells is None)
and (periodic_dimensions is None) and (perseus_file != '')):
if os.path.isfile(perseus_file):
- self.thisptr = new Periodic_cubical_complex_base_interface(str.encode(perseus_file))
+ self.thisptr = new Periodic_cubical_complex_base_interface(perseus_file.encode('utf-8'))
else:
print("file " + perseus_file + " not found.", file=sys.stderr)
else:
diff --git a/src/python/gudhi/reader_utils.pyx b/src/python/gudhi/reader_utils.pyx
index 345c92f8..fe1c3a2e 100644
--- a/src/python/gudhi/reader_utils.pyx
+++ b/src/python/gudhi/reader_utils.pyx
@@ -34,30 +34,30 @@ def read_lower_triangular_matrix_from_csv_file(csv_file='', separator=';'):
:type separator: char
:returns: The lower triangular matrix.
- :rtype: vector[vector[double]]
+ :rtype: List[List[float]]
"""
if csv_file:
if path.isfile(csv_file):
- return read_matrix_from_csv_file(str.encode(csv_file), ord(separator[0]))
+ return read_matrix_from_csv_file(csv_file.encode('utf-8'), ord(separator[0]))
print("file " + csv_file + " not set or not found.")
return []
def read_persistence_intervals_grouped_by_dimension(persistence_file=''):
"""Reads a file containing persistence intervals.
Each line might contain 2, 3 or 4 values: [[field] dimension] birth death
- The return value is an `map[dim, vector[pair[birth, death]]]`
- where `dim` is an `int`, `birth` a `double`, and `death` a `double`.
+ The return value is a `dict(dim, list(tuple(birth, death)))`
+ where `dim` is an `int`, `birth` a `float`, and `death` a `float`.
Note: the function does not check that birth <= death.
:param persistence_file: A persistence file style name.
:type persistence_file: string
:returns: The persistence pairs grouped by dimension.
- :rtype: map[int, vector[pair[double, double]]]
+ :rtype: Dict[int, List[Tuple[float, float]]]
"""
if persistence_file:
if path.isfile(persistence_file):
- return read_pers_intervals_grouped_by_dimension(str.encode(persistence_file))
+ return read_pers_intervals_grouped_by_dimension(persistence_file.encode('utf-8'))
print("file " + persistence_file + " not set or not found.")
return []
@@ -80,7 +80,7 @@ def read_persistence_intervals_in_dimension(persistence_file='', only_this_dim=-
"""
if persistence_file:
if path.isfile(persistence_file):
- return np_array(read_pers_intervals_in_dimension(str.encode(
- persistence_file), only_this_dim))
+ return np_array(read_pers_intervals_in_dimension(persistence_file.encode(
+ 'utf-8'), only_this_dim))
print("file " + persistence_file + " not set or not found.")
return []
diff --git a/src/python/gudhi/rips_complex.pyx b/src/python/gudhi/rips_complex.pyx
index 722cdcdc..deb8057a 100644
--- a/src/python/gudhi/rips_complex.pyx
+++ b/src/python/gudhi/rips_complex.pyx
@@ -28,7 +28,7 @@ cdef extern from "Rips_complex_interface.h" namespace "Gudhi":
void init_matrix(vector[vector[double]] values, double threshold)
void init_points_sparse(vector[vector[double]] values, double threshold, double sparse)
void init_matrix_sparse(vector[vector[double]] values, double threshold, double sparse)
- void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, int dim_max)
+ void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, int dim_max) except +
# RipsComplex python interface
cdef class RipsComplex:
diff --git a/src/python/gudhi/simplex_tree.pxd b/src/python/gudhi/simplex_tree.pxd
index 1066d44b..96d14079 100644
--- a/src/python/gudhi/simplex_tree.pxd
+++ b/src/python/gudhi/simplex_tree.pxd
@@ -39,7 +39,7 @@ cdef extern from "Simplex_tree_interface.h" namespace "Gudhi":
vector[pair[vector[int], double]] get_star(vector[int] simplex)
vector[pair[vector[int], double]] get_cofaces(vector[int] simplex,
int dimension)
- void expansion(int max_dim)
+ void expansion(int max_dim) except +
void remove_maximal_simplex(vector[int] simplex)
bool prune_above_filtration(double filtration)
bool make_filtration_non_decreasing()
diff --git a/src/python/gudhi/simplex_tree.pyx b/src/python/gudhi/simplex_tree.pyx
index 85d25492..b18627c4 100644
--- a/src/python/gudhi/simplex_tree.pyx
+++ b/src/python/gudhi/simplex_tree.pyx
@@ -508,7 +508,7 @@ cdef class SimplexTree:
"""
if self.pcohptr != NULL:
if persistence_file != '':
- self.pcohptr.write_output_diagram(str.encode(persistence_file))
+ self.pcohptr.write_output_diagram(persistence_file.encode('utf-8'))
else:
print("persistence_file must be specified")
else:
diff --git a/src/python/gudhi/strong_witness_complex.pyx b/src/python/gudhi/strong_witness_complex.pyx
index 2c33c3f2..9f89d3ae 100644
--- a/src/python/gudhi/strong_witness_complex.pyx
+++ b/src/python/gudhi/strong_witness_complex.pyx
@@ -22,9 +22,9 @@ __license__ = "MIT"
cdef extern from "Strong_witness_complex_interface.h" namespace "Gudhi":
cdef cppclass Strong_witness_complex_interface "Gudhi::witness_complex::Strong_witness_complex_interface":
Strong_witness_complex_interface(vector[vector[pair[size_t, double]]] nearest_landmark_table)
- void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square)
+ void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square) except +
void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square,
- unsigned limit_dimension)
+ unsigned limit_dimension) except +
# StrongWitnessComplex python interface
cdef class StrongWitnessComplex:
diff --git a/src/python/gudhi/subsampling.pyx b/src/python/gudhi/subsampling.pyx
index b1812087..f77c6f75 100644
--- a/src/python/gudhi/subsampling.pyx
+++ b/src/python/gudhi/subsampling.pyx
@@ -33,13 +33,15 @@ def choose_n_farthest_points(points=None, off_file='', nb_points=0, starting_poi
The iteration starts with the landmark `starting point`.
:param points: The input point set.
- :type points: vector[vector[double]].
+ :type points: Iterable[Iterable[float]].
Or
:param off_file: An OFF file style name.
:type off_file: string
+ And in both cases
+
:param nb_points: Number of points of the subsample.
:type nb_points: unsigned.
:param starting_point: The iteration starts with the landmark `starting \
@@ -47,15 +49,15 @@ def choose_n_farthest_points(points=None, off_file='', nb_points=0, starting_poi
index is chosen randomly.
:type starting_point: unsigned.
:returns: The subsample point set.
- :rtype: vector[vector[double]]
+ :rtype: List[List[float]].
"""
if off_file:
if os.path.isfile(off_file):
if starting_point == '':
- return subsampling_n_farthest_points_from_file(str.encode(off_file),
+ return subsampling_n_farthest_points_from_file(off_file.encode('utf-8'),
nb_points)
else:
- return subsampling_n_farthest_points_from_file(str.encode(off_file),
+ return subsampling_n_farthest_points_from_file(off_file.encode('utf-8'),
nb_points,
starting_point)
else:
@@ -74,21 +76,23 @@ def pick_n_random_points(points=None, off_file='', nb_points=0):
"""Subsample a point set by picking random vertices.
:param points: The input point set.
- :type points: vector[vector[double]].
+ :type points: Iterable[Iterable[float]].
Or
:param off_file: An OFF file style name.
:type off_file: string
+ And in both cases
+
:param nb_points: Number of points of the subsample.
:type nb_points: unsigned.
:returns: The subsample point set.
- :rtype: vector[vector[double]]
+ :rtype: List[List[float]]
"""
if off_file:
if os.path.isfile(off_file):
- return subsampling_n_random_points_from_file(str.encode(off_file),
+ return subsampling_n_random_points_from_file(off_file.encode('utf-8'),
nb_points)
else:
print("file " + off_file + " not found.")
@@ -103,22 +107,24 @@ def sparsify_point_set(points=None, off_file='', min_squared_dist=0.0):
between any two points is greater than or equal to min_squared_dist.
:param points: The input point set.
- :type points: vector[vector[double]].
+ :type points: Iterable[Iterable[float]].
Or
:param off_file: An OFF file style name.
:type off_file: string
+ And in both cases
+
:param min_squared_dist: Minimum squared distance separating the output \
points.
:type min_squared_dist: float.
:returns: The subsample point set.
- :rtype: vector[vector[double]]
+ :rtype: List[List[float]]
"""
if off_file:
if os.path.isfile(off_file):
- return subsampling_sparsify_points_from_file(str.encode(off_file),
+ return subsampling_sparsify_points_from_file(off_file.encode('utf-8'),
min_squared_dist)
else:
print("file " + off_file + " not found.")
diff --git a/src/python/gudhi/tangential_complex.pyx b/src/python/gudhi/tangential_complex.pyx
index 0083033c..6391488c 100644
--- a/src/python/gudhi/tangential_complex.pyx
+++ b/src/python/gudhi/tangential_complex.pyx
@@ -66,7 +66,7 @@ cdef class TangentialComplex:
def __cinit__(self, intrisic_dim, points=None, off_file=''):
if off_file:
if os.path.isfile(off_file):
- self.thisptr = new Tangential_complex_interface(intrisic_dim, str.encode(off_file), True)
+ self.thisptr = new Tangential_complex_interface(intrisic_dim, off_file.encode('utf-8'), True)
else:
print("file " + off_file + " not found.")
else:
diff --git a/src/python/gudhi/witness_complex.pyx b/src/python/gudhi/witness_complex.pyx
index b032a5a1..e589d006 100644
--- a/src/python/gudhi/witness_complex.pyx
+++ b/src/python/gudhi/witness_complex.pyx
@@ -22,9 +22,9 @@ __license__ = "MIT"
cdef extern from "Witness_complex_interface.h" namespace "Gudhi":
cdef cppclass Witness_complex_interface "Gudhi::witness_complex::Witness_complex_interface":
Witness_complex_interface(vector[vector[pair[size_t, double]]] nearest_landmark_table)
- void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square)
+ void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square) except +
void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square,
- unsigned limit_dimension)
+ unsigned limit_dimension) except +
# WitnessComplex python interface
cdef class WitnessComplex:
diff --git a/src/python/include/Alpha_complex_interface.h b/src/python/include/Alpha_complex_interface.h
index e9bbadb0..8614eee3 100644
--- a/src/python/include/Alpha_complex_interface.h
+++ b/src/python/include/Alpha_complex_interface.h
@@ -50,13 +50,9 @@ class Alpha_complex_interface {
std::vector<double> get_point(int vh) {
std::vector<double> vd;
- try {
- Point_d const& ph = alpha_complex_->get_point(vh);
- for (auto coord = ph.cartesian_begin(); coord != ph.cartesian_end(); coord++)
- vd.push_back(CGAL::to_double(*coord));
- } catch (std::out_of_range const&) {
- // std::out_of_range is thrown in case not found. Other exceptions must be re-thrown
- }
+ Point_d const& ph = alpha_complex_->get_point(vh);
+ for (auto coord = ph.cartesian_begin(); coord != ph.cartesian_end(); coord++)
+ vd.push_back(CGAL::to_double(*coord));
return vd;
}
diff --git a/src/python/setup.py.in b/src/python/setup.py.in
index 24d05025..9c2124f4 100644
--- a/src/python/setup.py.in
+++ b/src/python/setup.py.in
@@ -11,6 +11,7 @@
from setuptools import setup, Extension
from Cython.Build import cythonize
from numpy import get_include as numpy_get_include
+import sys
__author__ = "Vincent Rouvreau"
__copyright__ = "Copyright (C) 2016 Inria"
@@ -38,7 +39,8 @@ for module in modules:
libraries=libraries,
library_dirs=library_dirs,
include_dirs=include_dirs,
- runtime_library_dirs=runtime_library_dirs,))
+ runtime_library_dirs=runtime_library_dirs,
+ cython_directives = {'language_level': str(sys.version_info[0])},))
setup(
name = 'gudhi',
diff --git a/src/python/test/test_alpha_complex.py b/src/python/test/test_alpha_complex.py
index 712a50b6..3761fe16 100755
--- a/src/python/test/test_alpha_complex.py
+++ b/src/python/test/test_alpha_complex.py
@@ -11,8 +11,13 @@
from gudhi import AlphaComplex, SimplexTree
import math
import numpy as np
-import itertools
import pytest
+try:
+ # python3
+ from itertools import zip_longest
+except ImportError:
+ # python2
+ from itertools import izip_longest as zip_longest
__author__ = "Vincent Rouvreau"
__copyright__ = "Copyright (C) 2016 Inria"
@@ -60,8 +65,18 @@ def test_infinite_alpha():
assert point_list[1] == alpha_complex.get_point(1)
assert point_list[2] == alpha_complex.get_point(2)
assert point_list[3] == alpha_complex.get_point(3)
- assert alpha_complex.get_point(4) == []
- assert alpha_complex.get_point(125) == []
+ try:
+ alpha_complex.get_point(4) == []
+ except IndexError:
+ pass
+ else:
+ assert False
+ try:
+ alpha_complex.get_point(125) == []
+ except IndexError:
+ pass
+ else:
+ assert False
def test_filtered_alpha():
@@ -77,8 +92,18 @@ def test_filtered_alpha():
assert point_list[1] == filtered_alpha.get_point(1)
assert point_list[2] == filtered_alpha.get_point(2)
assert point_list[3] == filtered_alpha.get_point(3)
- assert filtered_alpha.get_point(4) == []
- assert filtered_alpha.get_point(125) == []
+ try:
+ filtered_alpha.get_point(4) == []
+ except IndexError:
+ pass
+ else:
+ assert False
+ try:
+ filtered_alpha.get_point(125) == []
+ except IndexError:
+ pass
+ else:
+ assert False
assert simplex_tree.get_filtration() == [
([0], 0.0),
@@ -114,6 +139,6 @@ def test_safe_alpha_persistence_comparison():
diag1 = simplex_tree1.persistence()
diag2 = simplex_tree2.persistence()
- for (first_p, second_p) in itertools.zip_longest(diag1, diag2):
+ for (first_p, second_p) in zip_longest(diag1, diag2):
assert first_p[0] == pytest.approx(second_p[0])
assert first_p[1] == pytest.approx(second_p[1])