Deploying to main from @ pyt-team/TopoModelX@62ee00c 🚀

pyt-team · Oct 9, 2023 · 8c0d6fb · 8c0d6fb
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diff --git a/topomodelx/.doctrees/environment.pickle b/topomodelx/.doctrees/environment.pickle
diff --git a/topomodelx/.doctrees/nbsphinx/notebooks/cell/can_train.ipynb b/topomodelx/.doctrees/nbsphinx/notebooks/cell/can_train.ipynb
@@ -124,7 +124,8 @@
     "import torch.nn.functional as F\n",
     "\n",
     "\n",
-    "from topomodelx.nn.cell.can import CAN"
+    "from topomodelx.nn.cell.can import CAN\n",
+    "from topomodelx.utils.sparse import from_sparse"
    ]
   },
   {
@@ -253,14 +254,12 @@
     "    adjacency_0_list.append(adjacency_0)\n",
     "\n",
     "    lower_neighborhood_t = cell_complex.down_laplacian_matrix(rank=1)\n",
-    "    lower_neighborhood_t = torch.from_numpy(lower_neighborhood_t.todense()).to_sparse()\n",
+    "    lower_neighborhood_t = from_sparse(lower_neighborhood_t)\n",
     "    lower_neighborhood_list.append(lower_neighborhood_t)\n",
     "\n",
     "    try:\n",
     "        upper_neighborhood_t = cell_complex.up_laplacian_matrix(rank=1)\n",
-    "        upper_neighborhood_t = torch.from_numpy(\n",
-    "            upper_neighborhood_t.todense()\n",
-    "        ).to_sparse()\n",
+    "        upper_neighborhood_t = from_sparse(upper_neighborhood_t)\n",
     "    except:\n",
     "        upper_neighborhood_t = np.zeros(\n",
     "            (lower_neighborhood_t.shape[0], lower_neighborhood_t.shape[0])\n",

diff --git a/topomodelx/.doctrees/nbsphinx/notebooks/cell/ccxn_train.ipynb b/topomodelx/.doctrees/nbsphinx/notebooks/cell/ccxn_train.ipynb
@@ -65,7 +65,8 @@
     "import toponetx.datasets as datasets\n",
     "\n",
     "\n",
-    "from topomodelx.nn.cell.ccxn import CCXN"
+    "from topomodelx.nn.cell.ccxn import CCXN\n",
+    "from topomodelx.utils.sparse import from_sparse"
    ]
   },
   {
@@ -194,8 +195,8 @@
     "\n",
     "    incidence_2_t = cell_complex.incidence_matrix(rank=2).T\n",
     "    adjacency_0 = cell_complex.adjacency_matrix(rank=0)\n",
-    "    incidence_2_t = torch.from_numpy(incidence_2_t.todense()).to_sparse()\n",
-    "    adjacency_0 = torch.from_numpy(adjacency_0.todense()).to_sparse()\n",
+    "    incidence_2_t = from_sparse(incidence_2_t)\n",
+    "    adjacency_0 = from_sparse(adjacency_0)\n",
     "    incidence_2_t_list.append(incidence_2_t)\n",
     "    adjacency_0_list.append(adjacency_0)"
    ]

diff --git a/topomodelx/.doctrees/nbsphinx/notebooks/cell/cwn_train.ipynb b/topomodelx/.doctrees/nbsphinx/notebooks/cell/cwn_train.ipynb
@@ -61,7 +61,8 @@
     "\n",
     "import toponetx.datasets as datasets\n",
     "\n",
-    "from topomodelx.nn.cell.cwn import CWN"
+    "from topomodelx.nn.cell.cwn import CWN\n",
+    "from topomodelx.utils.sparse import from_sparse"
    ]
   },
   {
@@ -222,9 +223,9 @@
     "    adjacency_1 = cell_complex.adjacency_matrix(rank=1)\n",
     "    incidence_1_t = cell_complex.incidence_matrix(rank=1).T\n",
     "\n",
-    "    incidence_2 = torch.from_numpy(incidence_2.todense()).to_sparse()\n",
-    "    adjacency_1 = torch.from_numpy(adjacency_1.todense()).to_sparse()\n",
-    "    incidence_1_t = torch.from_numpy(incidence_1_t.todense()).to_sparse()\n",
+    "    incidence_2 = from_sparse(incidence_2)\n",
+    "    adjacency_1 = from_sparse(adjacency_1)\n",
+    "    incidence_1_t = from_sparse(incidence_1_t)\n",
     "\n",
     "    incidence_2_list.append(incidence_2)\n",
     "    adjacency_1_list.append(adjacency_1)\n",

diff --git a/topomodelx/.doctrees/nbsphinx/notebooks/hypergraph/allset_train.ipynb b/topomodelx/.doctrees/nbsphinx/notebooks/hypergraph/allset_train.ipynb
@@ -59,7 +59,8 @@
     "from sklearn.model_selection import train_test_split\n",
     "import toponetx.datasets as datasets\n",
     "\n",
-    "from topomodelx.nn.hypergraph.allset import AllSet"
+    "from topomodelx.nn.hypergraph.allset import AllSet\n",
+    "from topomodelx.utils.sparse import from_sparse"
    ]
   },
   {
@@ -196,7 +197,7 @@
     "incidence_1_list = []\n",
     "for simplex in simplexes:\n",
     "    incidence_1 = simplex.incidence_matrix(rank=1, signed=False)\n",
-    "    # incidence_1 = torch.from_numpy(incidence_1.todense()).to_sparse()\n",
+    "    # incidence_1 = from_sparse(incidence_1)\n",
     "    # incidence_1_list.append(incidence_1)\n",
     "    hg = simplex.to_hypergraph()\n",
     "    hg_list.append(hg)\n",
@@ -205,7 +206,7 @@
     "# Extract hypergraphs incident matrices from collected hypergraphs\n",
     "for hg in hg_list:\n",
     "    incidence_1 = hg.incidence_matrix()\n",
-    "    incidence_1 = torch.from_numpy(incidence_1.todense()).to_sparse()\n",
+    "    incidence_1 = from_sparse(incidence_1)\n",
     "    incidence_1_list.append(incidence_1)"
    ]
   },

diff --git a/topomodelx/.doctrees/nbsphinx/notebooks/hypergraph/allset_transformer_train.ipynb b/topomodelx/.doctrees/nbsphinx/notebooks/hypergraph/allset_transformer_train.ipynb
@@ -91,6 +91,7 @@
     "from sklearn.model_selection import train_test_split\n",
     "\n",
     "from topomodelx.nn.hypergraph.allset_transformer import AllSetTransformer\n",
+    "from topomodelx.utils.sparse import from_sparse\n",
     "\n",
     "# %load_ext autoreload\n",
     "# %autoreload 2"
@@ -236,7 +237,7 @@
     "# Extract hypergraphs incident matrices from collected hypergraphs\n",
     "for hg in hg_list:\n",
     "    incidence_1 = hg.incidence_matrix()\n",
-    "    incidence_1 = torch.from_numpy(incidence_1.todense()).to_sparse()\n",
+    "    incidence_1 = from_sparse(incidence_1)\n",
     "    incidence_1_list.append(incidence_1)"
    ]
   },

diff --git a/topomodelx/.doctrees/nbsphinx/notebooks/hypergraph/dhgcn_train.ipynb b/topomodelx/.doctrees/nbsphinx/notebooks/hypergraph/dhgcn_train.ipynb
@@ -26,7 +26,8 @@
     "from sklearn.model_selection import train_test_split\n",
     "\n",
     "import toponetx.datasets as datasets\n",
-    "from topomodelx.nn.hypergraph.dhgcn import DHGCN"
+    "from topomodelx.nn.hypergraph.dhgcn import DHGCN\n",
+    "from topomodelx.utils.sparse import from_sparse"
    ]
   },
   {
@@ -204,7 +205,7 @@
     "incidence_1_list = []\n",
     "for simplex in simplexes:\n",
     "    incidence_1 = simplex.incidence_matrix(rank=1, signed=False)\n",
-    "    incidence_1 = torch.from_numpy(incidence_1.todense()).to_sparse()\n",
+    "    incidence_1 = from_sparse(incidence_1)\n",
     "    incidence_1_list.append(incidence_1)\n",
     "    hg = simplex.to_hypergraph()\n",
     "    hg_list.append(hg)"

diff --git a/topomodelx/.doctrees/nbsphinx/notebooks/hypergraph/hnhn_train.ipynb b/topomodelx/.doctrees/nbsphinx/notebooks/hypergraph/hnhn_train.ipynb
@@ -44,7 +44,8 @@
     "import toponetx.datasets.graph as graph\n",
     "from topomodelx.nn.hypergraph.hnhn_layer import HNHNLayer\n",
     "import matplotlib.pyplot as plt\n",
-    "from topomodelx.nn.hypergraph.hnhn import HNHN, HNHNNetwork"
+    "from topomodelx.nn.hypergraph.hnhn import HNHN, HNHNNetwork\n",
+    "from topomodelx.utils.sparse import from_sparse"
    ]
   },
   {
@@ -119,7 +120,7 @@
    ],
    "source": [
     "incidence_1 = dataset_sim.incidence_matrix(rank=1, signed=False)\n",
-    "incidence_1 = torch.from_numpy(incidence_1.todense()).to_sparse()\n",
+    "incidence_1 = from_sparse(incidence_1)\n",
     "print(f\"The incidence matrix B1 has shape: {incidence_1.shape}.\")"
    ]
   },

diff --git a/topomodelx/.doctrees/nbsphinx/notebooks/hypergraph/hypergat_train.ipynb b/topomodelx/.doctrees/nbsphinx/notebooks/hypergraph/hypergat_train.ipynb
@@ -59,7 +59,8 @@
     "import toponetx.datasets as datasets\n",
     "from sklearn.model_selection import train_test_split\n",
     "\n",
-    "from topomodelx.nn.hypergraph.hypergat import HyperGAT"
+    "from topomodelx.nn.hypergraph.hypergat import HyperGAT\n",
+    "from topomodelx.utils.sparse import from_sparse"
    ]
   },
   {
@@ -177,7 +178,7 @@
     "# Extract hypergraphs incident matrices from collected hypergraphs\n",
     "for hg in hg_list:\n",
     "    incidence_1 = hg.incidence_matrix()\n",
-    "    incidence_1 = torch.from_numpy(incidence_1.todense()).to_sparse()\n",
+    "    incidence_1 = from_sparse(incidence_1)\n",
     "    incidence_1_list.append(incidence_1)"
    ]
   },

diff --git a/topomodelx/.doctrees/nbsphinx/notebooks/hypergraph/hypersage_train.ipynb b/topomodelx/.doctrees/nbsphinx/notebooks/hypergraph/hypersage_train.ipynb
@@ -46,7 +46,8 @@
     "import toponetx.datasets as datasets\n",
     "from sklearn.model_selection import train_test_split\n",
     "\n",
-    "from topomodelx.nn.hypergraph.hypersage import HyperSAGE"
+    "from topomodelx.nn.hypergraph.hypersage import HyperSAGE\n",
+    "from topomodelx.utils.sparse import from_sparse"
    ]
   },
   {
@@ -164,7 +165,7 @@
     "# Extract hypergraphs incident matrices from collected hypergraphs\n",
     "for hg in hg_list:\n",
     "    incidence_1 = hg.incidence_matrix()\n",
-    "    incidence_1 = torch.from_numpy(incidence_1.todense()).to_sparse()\n",
+    "    incidence_1 = from_sparse(incidence_1)\n",
     "    incidence_1_list.append(incidence_1)"
    ]
   },

diff --git a/topomodelx/.doctrees/nbsphinx/notebooks/hypergraph/unigin_train.ipynb b/topomodelx/.doctrees/nbsphinx/notebooks/hypergraph/unigin_train.ipynb
@@ -12,7 +12,8 @@
     "from torch_geometric.datasets import TUDataset\n",
     "from torch_geometric.utils.convert import to_networkx\n",
     "from toponetx.classes.simplicial_complex import SimplicialComplex\n",
-    "from topomodelx.nn.hypergraph.unigin import UniGIN"
+    "from topomodelx.nn.hypergraph.unigin import UniGIN\n",
+    "from topomodelx.utils.sparse import from_sparse"
    ]
   },
   {
@@ -58,7 +59,7 @@
     "incidence_1_list = []\n",
     "for hg in hg_list:\n",
     "    incidence_1 = hg.incidence_matrix()\n",
-    "    incidence_1 = torch.from_numpy(incidence_1.todense()).to_sparse()\n",
+    "    incidence_1 = from_sparse(incidence_1)\n",
     "    incidence_1_list.append(incidence_1)"
    ]
   },

diff --git a/topomodelx/.doctrees/nbsphinx/notebooks/simplicial/dist2cycle_train.ipynb b/topomodelx/.doctrees/nbsphinx/notebooks/simplicial/dist2cycle_train.ipynb
@@ -38,6 +38,7 @@
     "import toponetx.datasets.graph as graph\n",
     "\n",
     "from topomodelx.nn.simplicial.dist2cycle import Dist2Cycle\n",
+    "from topomodelx.utils.sparse import from_sparse\n",
     "import numpy.linalg as npla"
    ]
   },
@@ -101,8 +102,8 @@
     "incidence_1 = dataset.incidence_matrix(rank=1)\n",
     "adjacency_0 = dataset.adjacency_matrix(rank=0)\n",
     "\n",
-    "incidence_1 = torch.from_numpy(incidence_1.todense()).to_sparse()\n",
-    "adjacency_0 = torch.from_numpy(adjacency_0.todense()).to_sparse()\n",
+    "incidence_1 = from_sparse(incidence_1)\n",
+    "adjacency_0 = from_sparse(adjacency_0)\n",
     "\n",
     "print(f\"The incidence matrix B1 has shape: {incidence_1.shape}.\")\n",
     "print(f\"The adjacency matrix A0 has shape: {adjacency_0.shape}.\")"

diff --git a/topomodelx/.doctrees/nbsphinx/notebooks/simplicial/hsn_train.ipynb b/topomodelx/.doctrees/nbsphinx/notebooks/simplicial/hsn_train.ipynb
@@ -42,7 +42,8 @@
     "\n",
     "import toponetx.datasets.graph as graph\n",
     "\n",
-    "from topomodelx.nn.simplicial.hsn import HSN"
+    "from topomodelx.nn.simplicial.hsn import HSN\n",
+    "from topomodelx.utils.sparse import from_sparse"
    ]
   },
   {
@@ -103,8 +104,8 @@
     "incidence_1 = dataset.incidence_matrix(rank=1)\n",
     "adjacency_0 = dataset.adjacency_matrix(rank=0)\n",
     "\n",
-    "incidence_1 = torch.from_numpy(incidence_1.todense()).to_sparse()\n",
-    "adjacency_0 = torch.from_numpy(adjacency_0.todense()).to_sparse()\n",
+    "incidence_1 = from_sparse(incidence_1)\n",
+    "adjacency_0 = from_sparse(adjacency_0)\n",
     "\n",
     "print(f\"The incidence matrix B1 has shape: {incidence_1.shape}.\")\n",
     "print(f\"The adjacency matrix A0 has shape: {adjacency_0.shape}.\")"

diff --git a/topomodelx/.doctrees/nbsphinx/notebooks/simplicial/san_train.ipynb b/topomodelx/.doctrees/nbsphinx/notebooks/simplicial/san_train.ipynb
@@ -84,6 +84,7 @@
     "from torch_geometric.utils.convert import to_networkx\n",
     "\n",
     "from topomodelx.nn.simplicial.san import SAN\n",
+    "from topomodelx.utils.sparse import from_sparse\n",
     "\n",
     "%load_ext autoreload\n",
     "%autoreload 2"
@@ -201,18 +202,14 @@
     "simplex_order_k = 1\n",
     "# Down laplacian\n",
     "try:\n",
-    "    laplacian_down = torch.from_numpy(\n",
-    "        dataset.down_laplacian_matrix(rank=simplex_order_k).todense()\n",
-    "    ).to_sparse()\n",
+    "    laplacian_down = from_sparse(dataset.down_laplacian_matrix(rank=simplex_order_k))\n",
     "except ValueError:\n",
     "    laplacian_down = torch.zeros(\n",
     "        (dataset.shape[simplex_order_k], dataset.shape[simplex_order_k])\n",
     "    ).to_sparse()\n",
     "# Up laplacian\n",
     "try:\n",
-    "    laplacian_up = torch.from_numpy(\n",
-    "        dataset.up_laplacian_matrix(rank=simplex_order_k).todense()\n",
-    "    ).to_sparse()\n",
+    "    laplacian_up = from_sparse(dataset.up_laplacian_matrix(rank=simplex_order_k))\n",
     "except ValueError:\n",
     "    laplacian_up = torch.zeros(\n",
     "        (dataset.shape[simplex_order_k], dataset.shape[simplex_order_k])\n",
@@ -288,7 +285,7 @@
    },
    "outputs": [],
    "source": [
-    "incidence_0_1 = torch.from_numpy(dataset.incidence_matrix(1).todense()).to_sparse()"
+    "incidence_0_1 = from_sparse(dataset.incidence_matrix(1))"
    ]
   },
   {

diff --git a/topomodelx/.doctrees/nbsphinx/notebooks/simplicial/sca_cmps_train.ipynb b/topomodelx/.doctrees/nbsphinx/notebooks/simplicial/sca_cmps_train.ipynb
@@ -34,7 +34,8 @@
     "import toponetx.datasets as datasets\n",
     "from sklearn.model_selection import train_test_split\n",
     "\n",
-    "from topomodelx.nn.simplicial.sca_cmps import SCACMPS"
+    "from topomodelx.nn.simplicial.sca_cmps import SCACMPS\n",
+    "from topomodelx.utils.sparse import from_sparse"
    ]
   },
   {
@@ -159,10 +160,10 @@
     "    incidence_1_t = sc.incidence_matrix(rank=1).T\n",
     "    incidence_2_t = sc.incidence_matrix(rank=2).T\n",
     "\n",
-    "    laplacian_down_1 = torch.from_numpy(laplacian_down_1.todense()).to_sparse()\n",
-    "    laplacian_down_2 = torch.from_numpy(laplacian_down_2.todense()).to_sparse()\n",
-    "    incidence_1_t = torch.from_numpy(incidence_1_t.todense()).to_sparse()\n",
-    "    incidence_2_t = torch.from_numpy(incidence_2_t.todense()).to_sparse()\n",
+    "    laplacian_down_1 = from_sparse(laplacian_down_1)\n",
+    "    laplacian_down_2 = from_sparse(laplacian_down_2)\n",
+    "    incidence_1_t = from_sparse(incidence_1_t)\n",
+    "    incidence_2_t = from_sparse(incidence_2_t)\n",
     "\n",
     "    laplacian_down_1_list.append(laplacian_down_1)\n",
     "    laplacian_down_2_list.append(laplacian_down_2)\n",

diff --git a/topomodelx/.doctrees/nbsphinx/notebooks/simplicial/sccn_train.ipynb b/topomodelx/.doctrees/nbsphinx/notebooks/simplicial/sccn_train.ipynb
@@ -44,7 +44,8 @@
     "\n",
     "import toponetx.datasets.graph as graph\n",
     "\n",
-    "from topomodelx.nn.simplicial.sccn import SCCN"
+    "from topomodelx.nn.simplicial.sccn import SCCN\n",
+    "from topomodelx.utils.sparse import from_sparse"
    ]
   },
   {
@@ -131,7 +132,7 @@
    ],
    "source": [
     "def sparse_to_torch(X):\n",
-    "    return torch.from_numpy(X.todense()).to_sparse()\n",
+    "    return from_sparse(X)\n",
     "\n",
     "\n",
     "incidences = {\n",

diff --git a/topomodelx/.doctrees/nbsphinx/notebooks/simplicial/sccnn_train.ipynb b/topomodelx/.doctrees/nbsphinx/notebooks/simplicial/sccnn_train.ipynb
@@ -67,7 +67,8 @@
     "import numpy as np\n",
     "from sklearn.model_selection import train_test_split\n",
     "import toponetx.datasets as datasets\n",
-    "from topomodelx.nn.simplicial.sccnn import SCCNN, SCCNNComplex"
+    "from topomodelx.nn.simplicial.sccnn import SCCNN, SCCNNComplex\n",
+    "from topomodelx.utils.sparse import from_sparse"
    ]
   },
   {
@@ -164,12 +165,12 @@
     "    laplacian_up_1 = simplex.up_laplacian_matrix(rank=1)\n",
     "    laplacian_2 = simplex.hodge_laplacian_matrix(rank=2)\n",
     "\n",
-    "    incidence_1 = torch.from_numpy(incidence_1.todense()).to_sparse()\n",
-    "    incidence_2 = torch.from_numpy(incidence_2.todense()).to_sparse()\n",
-    "    laplacian_0 = torch.from_numpy(laplacian_0.todense()).to_sparse()\n",
-    "    laplacian_down_1 = torch.from_numpy(laplacian_down_1.todense()).to_sparse()\n",
-    "    laplacian_up_1 = torch.from_numpy(laplacian_up_1.todense()).to_sparse()\n",
-    "    laplacian_2 = torch.from_numpy(laplacian_2.todense()).to_sparse()\n",
+    "    incidence_1 = from_sparse(incidence_1)\n",
+    "    incidence_2 = from_sparse(incidence_2)\n",
+    "    laplacian_0 = from_sparse(laplacian_0)\n",
+    "    laplacian_down_1 = from_sparse(laplacian_down_1)\n",
+    "    laplacian_up_1 = from_sparse(laplacian_up_1)\n",
+    "    laplacian_2 = from_sparse(laplacian_2)\n",
     "\n",
     "    incidence_1_list.append(incidence_1)\n",
     "    incidence_2_list.append(incidence_2)\n",
@@ -526,14 +527,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "laplacian_0 = torch.from_numpy(laplacian_0.todense()).to_sparse()\n",
-    "laplacian_down_1 = torch.from_numpy(laplacian_down_1.todense()).to_sparse()\n",
-    "laplacian_up_1 = torch.from_numpy(laplacian_up_1.todense()).to_sparse()\n",
-    "laplacian_down_2 = torch.from_numpy(laplacian_down_2.todense()).to_sparse()\n",
-    "laplacian_up_2 = torch.from_numpy(laplacian_up_2.todense()).to_sparse()\n",
-    "\n",
-    "incidence_1 = torch.from_numpy(incidence_1.todense()).to_sparse()\n",
-    "incidence_2 = torch.from_numpy(incidence_2.todense()).to_sparse()"
+    "laplacian_0 = from_sparse(laplacian_0)\n",
+    "laplacian_down_1 = from_sparse(laplacian_down_1)\n",
+    "laplacian_up_1 = from_sparse(laplacian_up_1)\n",
+    "laplacian_down_2 = from_sparse(laplacian_down_2)\n",
+    "laplacian_up_2 = from_sparse(laplacian_up_2)\n",
+    "\n",
+    "incidence_1 = from_sparse(incidence_1)\n",
+    "incidence_2 = from_sparse(incidence_2)"
    ]
   },
   {