Use MNMG version of ECG in python layer instead, and remove legacy ECG and Louvain

cpp/CMakeLists.txt

@@ -275,8 +275,6 @@ set(CUGRAPH_SOURCES
     src/community/ecg_mg_v64_e64.cu
     src/community/ecg_mg_v32_e32.cu
     src/community/ecg_mg_v32_e64.cu
-    src/community/legacy/louvain.cu
-    src/community/legacy/ecg.cu
     src/community/egonet_sg_v64_e64.cu
     src/community/egonet_sg_v32_e32.cu
     src/community/egonet_sg_v32_e64.cu
@@ -639,7 +637,6 @@ add_library(cugraph_c
         src/c_api/induced_subgraph.cpp
         src/c_api/capi_helper.cu
         src/c_api/legacy_spectral.cpp
-        src/c_api/legacy_ecg.cpp
         src/c_api/graph_helper_sg.cu
         src/c_api/graph_helper_mg.cu
         src/c_api/graph_generators.cpp

cpp/include/cugraph/algorithms.hpp

@@ -544,14 +544,6 @@ std::pair<size_t, weight_t> louvain(
   weight_t threshold  = weight_t{1e-7},
   weight_t resolution = weight_t{1});
 
-template <typename vertex_t, typename edge_t, typename weight_t>
-std::pair<size_t, weight_t> louvain(
-  raft::handle_t const& handle,
-  legacy::GraphCSRView<vertex_t, edge_t, weight_t> const& graph_view,
-  vertex_t* clustering,
-  size_t max_level    = 100,
-  weight_t resolution = weight_t{1});
-
 /**
  * @brief      Louvain implementation, returning dendrogram
  *
@@ -727,38 +719,6 @@ std::pair<size_t, weight_t> leiden(
   weight_t resolution = weight_t{1},
   weight_t theta      = weight_t{1});
 
-/**
- * @brief Computes the ecg clustering of the given graph.
- *
- * ECG runs truncated Louvain on an ensemble of permutations of the input graph,
- * then uses the ensemble partitions to determine weights for the input graph.
- * The final result is found by running full Louvain on the input graph using
- * the determined weights. See https://arxiv.org/abs/1809.05578 for further
- * information.
- *
- * @throws     cugraph::logic_error when an error occurs.
- *
- * @tparam vertex_t                  Type of vertex identifiers. Supported value : int (signed,
- * 32-bit)
- * @tparam edge_t                    Type of edge identifiers.  Supported value : int (signed,
- * 32-bit)
- * @tparam weight_t                  Type of edge weights. Supported values : float or double.
- *
- * @param[in]  handle                Library handle (RAFT). If a communicator is set in the handle,
- * @param[in]  graph_coo             input graph object (COO)
- * @param[in]  graph_csr             input graph object (CSR)
- * @param[in]  min_weight            The minimum weight parameter
- * @param[in]  ensemble_size         The ensemble size parameter
- * @param[out] clustering            A device pointer to array where the partitioning should be
- * written
- */
-template <typename vertex_t, typename edge_t, typename weight_t>
-void ecg(raft::handle_t const& handle,
-         legacy::GraphCSRView<vertex_t, edge_t, weight_t> const& graph,
-         weight_t min_weight,
-         vertex_t ensemble_size,
-         vertex_t* clustering);
-
 /**
  * @brief Computes the ecg clustering of the given graph.
  *

cpp/include/cugraph_c/community_algorithms.h

@@ -212,37 +212,6 @@ cugraph_error_code_t cugraph_ecg(const cugraph_resource_handle_t* handle,
                                  cugraph_hierarchical_clustering_result_t** result,
                                  cugraph_error_t** error);
 
-/**
- * @brief     Compute ECG clustering of the given graph
- *
- * ECG runs truncated Louvain on an ensemble of permutations of the input graph,
- * then uses the ensemble partitions to determine weights for the input graph.
- * The final result is found by running full Louvain on the input graph using
- * the determined weights. See https://arxiv.org/abs/1809.05578 for further
- * information.
- *
- * NOTE: This currently wraps the legacy ECG clustering implementation which is only
- * available in Single GPU implementation.
- *
- * @param [in]  handle          Handle for accessing resources
- * @param [in]  graph           Pointer to graph.  NOTE: Graph might be modified if the storage
- * @param [in]  min_weight      The minimum weight parameter
- * @param [in]  ensemble_size   The ensemble size parameter
- * @param [in]  do_expensive_check
- *                              A flag to run expensive checks for input arguments (if set to true)
- * @param [out] result          The result from the clustering algorithm
- * @param [out] error           Pointer to an error object storing details of any error.  Will
- *                              be populated if error code is not CUGRAPH_SUCCESS
- * @return error code
- */
-cugraph_error_code_t cugraph_legacy_ecg(const cugraph_resource_handle_t* handle,
-                                        cugraph_graph_t* graph,
-                                        double min_weight,
-                                        size_t ensemble_size,
-                                        bool_t do_expensive_check,
-                                        cugraph_hierarchical_clustering_result_t** result,
-                                        cugraph_error_t** error);
-
 /**
  * @brief   Extract ego graphs
  *