Replace ripser.py and robinhood submodules with giotto-ph dependency

.gitmodules

@@ -1,6 +1,3 @@
-[submodule "gtda/externals/ripser"]
-	path = gtda/externals/ripser
-	url = https://github.com/scikit-tda/ripser.py.git
 [submodule "gtda/externals/gudhi-devel"]
 	path = gtda/externals/gudhi-devel
 	url = https://github.com/giotto-ai/gudhi-devel
@@ -14,6 +11,3 @@
 [submodule "gtda/externals/pybind11"]
 	path = gtda/externals/pybind11
 	url = https://github.com/pybind/pybind11
-[submodule "gtda/externals/robinhood"]
-	path = gtda/externals/robinhood
-	url = https://github.com/martinus/robin-hood-hashing

CMakeLists.txt

@@ -9,59 +9,9 @@ include_directories(${Boost_INCLUDE_DIRS})
 
 find_package(OpenMP)
 
-set(RIPSER_SRC_DIR "gtda/externals/ripser")
 set(GUDHI_SRC_DIR "gtda/externals/gudhi-devel/src")
 set(HERA_DIR "gtda/externals/hera")
 set(EIGEN_DIR "gtda/externals/eigen")
-set(ROBINHOOD_DIR "gtda/externals/robinhood")
-
-#######################################################################
-#                               Ripser                                #
-#######################################################################
-
-pybind11_add_module(gtda_ripser MODULE "${BINDINGS_DIR}/ripser_bindings.cpp")
-set_property(TARGET gtda_ripser PROPERTY CXX_STANDARD 14)
-
-if(OpenMP_FOUND)
-  target_link_libraries(gtda_ripser PRIVATE OpenMP::OpenMP_CXX)
-endif()
-
-target_compile_definitions(gtda_ripser PRIVATE ASSEMBLE_REDUCTION_MATRIX=1)
-target_include_directories(gtda_ripser PRIVATE "${RIPSER_SRC_DIR}/ripser")
-target_compile_definitions(gtda_ripser PRIVATE USE_ROBINHOOD_HASHMAP=1)
-target_include_directories(gtda_ripser PRIVATE "${ROBINHOOD_DIR}/src/include")
-
-if(MSVC)
-    target_compile_options(gtda_ripser PUBLIC $<$<CONFIG:RELEASE>: /Wall /O2>)
-    target_compile_options(gtda_ripser PUBLIC $<$<CONFIG:DEBUG>:/O1 /DEBUG:FULL /Zi /Zo>)
-else()
-    target_compile_options(gtda_ripser PUBLIC $<$<CONFIG:RELEASE>: -O3>)
-    target_compile_options(gtda_ripser PUBLIC $<$<CONFIG:DEBUG>: -O2 -ggdb -D_GLIBCXX_DEBUG>)
-endif()
-
-#######################################################################
-#                     Ripser - Coefficient enable                     #
-#######################################################################
-
-pybind11_add_module(gtda_ripser_coeff MODULE "${BINDINGS_DIR}/ripser_bindings.cpp")
-set_property(TARGET gtda_ripser_coeff PROPERTY CXX_STANDARD 14)
-
-if(OpenMP_FOUND)
-  target_link_libraries(gtda_ripser_coeff PRIVATE OpenMP::OpenMP_CXX)
-endif()
-
-target_compile_definitions(gtda_ripser_coeff PRIVATE USE_COEFFICIENTS=1 ASSEMBLE_REDUCTION_MATRIX=1)
-target_include_directories(gtda_ripser_coeff PRIVATE "${RIPSER_SRC_DIR}/ripser")
-target_compile_definitions(gtda_ripser_coeff PRIVATE USE_ROBINHOOD_HASHMAP=1)
-target_include_directories(gtda_ripser_coeff PRIVATE "${ROBINHOOD_DIR}/src/include")
-
-if(MSVC)
-    target_compile_options(gtda_ripser_coeff PUBLIC $<$<CONFIG:RELEASE>: /Wall /O2>)
-    target_compile_options(gtda_ripser_coeff PUBLIC $<$<CONFIG:DEBUG>:/O1 /DEBUG:FULL /Zi /Zo>)
-else()
-    target_compile_options(gtda_ripser_coeff PUBLIC $<$<CONFIG:RELEASE>: -O3>)
-    target_compile_options(gtda_ripser_coeff PUBLIC $<$<CONFIG:DEBUG>: -O2 -ggdb -D_GLIBCXX_DEBUG>)
-endif()
 
 #######################################################################
 #                             Wasserstein                             #
@@ -338,29 +288,3 @@ else()
     target_compile_options(gtda_cech_complex PUBLIC $<$<CONFIG:RELEASE>: -Ofast -shared -pthread -fPIC -fwrapv -Wall -fno-strict-aliasing -frounding-math>)
     target_compile_options(gtda_cech_complex PUBLIC $<$<CONFIG:DEBUG>:-O2 -ggdb -D_GLIBCXX_DEBUG>)
 endif()
-
-#######################################################################
-#                              Collapser                              #
-#######################################################################
-
-pybind11_add_module(gtda_collapser MODULE "${BINDINGS_DIR}/collapser_bindings.cpp")
-set_property(TARGET gtda_collapser PROPERTY CXX_STANDARD 14)
-
-if(OpenMP_FOUND)
-    target_link_libraries(gtda_collapser PRIVATE OpenMP::OpenMP_CXX)
-endif()
-
-target_link_libraries(gtda_collapser LINK_PUBLIC ${Boost_LIBRARIES})
-target_compile_definitions(gtda_collapser PRIVATE BOOST_RESULT_OF_USE_DECLTYPE=1 BOOST_ALL_NO_LIB=1 BOOST_SYSTEM_NO_DEPRECATED=1)
-
-target_include_directories(gtda_collapser PRIVATE "${GUDHI_SRC_DIR}/common/include")
-target_include_directories(gtda_collapser PRIVATE "${GUDHI_SRC_DIR}/Collapse/include")
-target_include_directories(gtda_collapser PRIVATE "${EIGEN_DIR}")
-
-if(MSVC)
-    target_compile_options(gtda_collapser PUBLIC $<$<CONFIG:RELEASE>: /O2 /Wall /fp:strict>)
-    target_compile_options(gtda_collapser PUBLIC $<$<CONFIG:DEBUG>:/O1 /DEBUG:FULL /Zi /Zo>)
-else()
-    target_compile_options(gtda_collapser PUBLIC $<$<CONFIG:RELEASE>: -Ofast -shared -pthread -fPIC -fwrapv -Wall -fno-strict-aliasing -frounding-math>)
-    target_compile_options(gtda_collapser PUBLIC $<$<CONFIG:DEBUG>:-O2 -ggdb -D_GLIBCXX_DEBUG>)
-endif()

azure-pipelines.yml

@@ -46,7 +46,7 @@ jobs:
 
   - task: Cache@2
     inputs:
-      key: '"ccache-wheels-v2021.07.27" | $(Agent.OS) | "$(python.version)"'
+      key: '"ccache-wheels-v2021.12.29" | $(Agent.OS) | "$(python.version)"'
       path: $(CCACHE_DIR)
     displayName: ccache
 
@@ -146,7 +146,7 @@ jobs:
 
   - task: Cache@2
     inputs:
-      key: '"ccache-v2021.07.27" | $(Agent.OS) | "$(python.version)"'
+      key: '"ccache-v2021.12.29" | $(Agent.OS) | "$(python.version)"'
       path: $(CCACHE_DIR)
     displayName: ccache
 

examples/persistent_homology_graphs.ipynb

@@ -507,9 +507,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "X_ggd = GraphGeodesicDistance(directed=True, unweighted=True).fit_transform([directed_circle])\n",
@@ -651,13 +649,13 @@
     "- Persistence diagrams are great for data exploration, but to feed their content to machine learning algorithms one must make sure the algorithm used is **independent of the relative ordering** of the birth-death pairs in each homology dimension. [gtda.diagrams](https://giotto-ai.github.io/gtda-docs/latest/modules/diagrams.html) contains a suite of vector representations, feature extraction methods and kernel methods that convert persistence diagrams into data structures ready for machine learning algorithms. Simple examples of their use are contained in [Topological feature extraction using VietorisRipsPersistence and PersistenceEntropy](https://giotto-ai.github.io/gtda-docs/latest/notebooks/vietoris_rips_quickstart.html), [Classifying 3D shapes](https://giotto-ai.github.io/gtda-docs/latest/notebooks/classifying_shapes.html) and [Lorenz attractor](https://giotto-ai.github.io/gtda-docs/latest/notebooks/lorenz_attractor.html).\n",
     "- In addition to ``GraphGeodesicDistance``, [gtda.graphs](https://giotto-ai.github.io/gtda-docs/latest/modules/graphs.html) also contains transformers for the creation of graphs from point cloud or time series data.\n",
     "- Despite the name, [gtda.point_clouds](https://giotto-ai.github.io/gtda-docs/latest/modules/point_clouds.html) contains transformers for the alteration of distance matrices (which are just adjacency matrices of weighted graphs) as a preprocessing step for persistent homology.\n",
-    "- ``VietorisRipsPersistence`` builds on the [ripser.py](https://ripser.scikit-tda.org/index.html) project. Its website contains two tutorials on additional ways in which graphs can be constructed from [time series data](https://ripser.scikit-tda.org/notebooks/Lower%20Star%20Time%20Series.html) or [image data](https://ripser.scikit-tda.org/notebooks/Lower%20Star%20Image%20Filtrations.html), and fed to the clique complex filtration construction. With a few simple modifications, the code can be adapted to the API of ``VietorisRipsPersistence``."
+    "- ``VietorisRipsPersistence`` builds on the [giotto-ph](https://github.com/giotto-ai/giotto-ph) and [ripser.py](https://ripser.scikit-tda.org/index.html) projects. The latter's website contains two tutorials on additional ways in which graphs can be constructed from [time series data](https://ripser.scikit-tda.org/notebooks/Lower%20Star%20Time%20Series.html) or [image data](https://ripser.scikit-tda.org/notebooks/Lower%20Star%20Image%20Filtrations.html), and fed to the clique complex filtration construction. With a few simple modifications, the code can be adapted to the API of ``VietorisRipsPersistence``."
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -671,7 +669,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.5"
+   "version": "3.9.2"
   }
  },
  "nbformat": 4,

gtda/externals/__init__.py

@@ -3,23 +3,17 @@
 
 from .modules.gtda_bottleneck import bottleneck_distance
 from .modules.gtda_wasserstein import wasserstein_distance
-from .modules.gtda_collapser import flag_complex_collapse_edges_dense, \
-    flag_complex_collapse_edges_sparse, flag_complex_collapse_edges_coo
-from .python import ripser, SparseRipsComplex, CechComplex, CubicalComplex, \
+from .python import SparseRipsComplex, CechComplex, CubicalComplex, \
     PeriodicCubicalComplex, SimplexTree, WitnessComplex, StrongWitnessComplex
 
 __all__ = [
     'bottleneck_distance',
     'wasserstein_distance',
-    'ripser',
     'SparseRipsComplex',
     'CechComplex',
     'CubicalComplex',
     'PeriodicCubicalComplex',
     'SimplexTree',
     'WitnessComplex',
-    'StrongWitnessComplex',
-    'flag_complex_collapse_edges_dense',
-    'flag_complex_collapse_edges_sparse',
-    'flag_complex_collapse_edges_coo'
+    'StrongWitnessComplex'
     ]

gtda/externals/python/__init__.py

@@ -1,4 +1,3 @@
-from .ripser_interface import ripser
 from .cubical_complex_interface import CubicalComplex
 from .simplex_tree_interface import SimplexTree
 from .periodic_cubical_complex_interface import PeriodicCubicalComplex