Merge pull request #46 from pyt-team/frantzen/toponetx-imports

Adapt to new TopoNetX import convention

topoembedx/classes/cell2vec.py

@@ -1,10 +1,11 @@
 """Cell2Vec: a class that extends the Node2Vec class."""
+
 from typing import Literal
 
 import networkx as nx
 import numpy as np
+import toponetx as tnx
 from karateclub import Node2Vec
-from toponetx.classes import Complex
 
 from topoembedx.neighborhood import neighborhood_from_complex
 
@@ -54,7 +55,7 @@ class Cell2Vec(Node2Vec):
 
     def fit(
         self,
-        complex: Complex,
+        complex: tnx.Complex,
         neighborhood_type: Literal["adj", "coadj"] = "adj",
         neighborhood_dim={"rank": 0, "via_rank": -1},
     ) -> None:

topoembedx/classes/cell_diff2vec.py

@@ -1,10 +1,11 @@
 """Class CellDiff2Vec."""
+
 from typing import Literal
 
 import networkx as nx
 import numpy as np
+import toponetx as tnx
 from karateclub import Diff2Vec
-from toponetx.classes.complex import Complex
 
 from topoembedx.neighborhood import neighborhood_from_complex
 
@@ -39,7 +40,7 @@ class CellDiff2Vec(Diff2Vec):
 
     def fit(
         self,
-        complex: Complex,
+        complex: tnx.Complex,
         neighborhood_type: Literal["adj", "coadj"] = "adj",
         neighborhood_dim={"rank": 0, "via_rank": -1},
     ) -> None:

topoembedx/classes/deepcell.py

@@ -1,10 +1,11 @@
 """DeepCell class for embedding complex networks using DeepWalk."""
+
 from typing import Literal
 
 import networkx as nx
 import numpy as np
+import toponetx as tnx
 from karateclub import DeepWalk
-from toponetx.classes import Complex
 
 from topoembedx.neighborhood import neighborhood_from_complex
 
@@ -39,7 +40,7 @@ class DeepCell(DeepWalk):
 
     def fit(
         self,
-        complex: Complex,
+        complex: tnx.Complex,
         neighborhood_type: Literal["adj", "coadj"] = "adj",
         neighborhood_dim={"rank": 0, "via_rank": -1},
     ) -> None:

topoembedx/classes/higher_order_laplacian_eigenmaps.py

@@ -1,10 +1,11 @@
 """Higher Order Laplacian Eigenmaps."""
+
 from typing import Literal
 
 import networkx as nx
 import numpy as np
+import toponetx as tnx
 from karateclub import LaplacianEigenmaps
-from toponetx.classes import Complex
 
 from topoembedx.neighborhood import neighborhood_from_complex
 
@@ -36,7 +37,7 @@ def __init__(
 
     def fit(
         self,
-        complex: Complex,
+        complex: tnx.Complex,
         neighborhood_type: Literal["adj", "coadj"] = "adj",
         neighborhood_dim={"rank": 0, "via_rank": -1},
     ) -> None:

topoembedx/classes/hoglee.py

@@ -1,10 +1,11 @@
 """Higher Order Geometric Laplacian EigenMaps (HOGLEE) class."""
+
 from typing import Literal
 
 import networkx as nx
 import numpy as np
+import toponetx as tnx
 from karateclub import GLEE
-from toponetx.classes import Complex
 
 from topoembedx.neighborhood import neighborhood_from_complex
 
@@ -25,7 +26,7 @@ class HOGLEE(GLEE):
 
     def fit(
         self,
-        complex: Complex,
+        complex: tnx.Complex,
         neighborhood_type: Literal["adj", "coadj"] = "adj",
         neighborhood_dim={"rank": 0, "via_rank": -1},
     ) -> None:

topoembedx/classes/hope.py

@@ -1,9 +1,10 @@
 """Higher Order Laplacian Positional Encoder (HOPE) class."""
+
 from typing import Literal, overload
 
 import numpy as np
+import toponetx as tnx
 from scipy import sparse
-from toponetx.classes import Complex
 
 from topoembedx.neighborhood import neighborhood_from_complex
 
@@ -113,7 +114,7 @@ def _laplacian_pe(
 
     def fit(
         self,
-        complex: Complex,
+        complex: tnx.Complex,
         neighborhood_type: Literal["adj", "coadj"] = "adj",
         neighborhood_dim: dict = {"rank": 0, "to_rank": -1},
     ) -> None:

topoembedx/neighborhood.py

@@ -1,19 +1,13 @@
 """Functions for computing neighborhoods of a complex."""
+
 from typing import Literal
 
 import numpy as np
-from toponetx.classes import (
-    CellComplex,
-    ColoredHyperGraph,
-    CombinatorialComplex,
-    Complex,
-    PathComplex,
-    SimplicialComplex,
-)
+import toponetx as tnx
 
 
 def neighborhood_from_complex(
-    complex: Complex,
+    complex: tnx.Complex,
     neighborhood_type: Literal["adj", "coadj"] = "adj",
     neighborhood_dim={"rank": 0, "via_rank": -1},
 ) -> tuple[list, np.ndarray]:
@@ -65,12 +59,12 @@ def neighborhood_from_complex(
             f"Input neighborhood_type must be `adj` or `coadj`, got {neighborhood_type}."
         )
 
-    if isinstance(complex, SimplicialComplex | CellComplex | PathComplex):
+    if isinstance(complex, tnx.SimplicialComplex | tnx.CellComplex | tnx.PathComplex):
         if neighborhood_type == "adj":
             ind, A = complex.adjacency_matrix(neighborhood_dim["rank"], index=True)
         else:
             ind, A = complex.coadjacency_matrix(neighborhood_dim["rank"], index=True)
-    elif isinstance(complex, CombinatorialComplex | ColoredHyperGraph):
+    elif isinstance(complex, tnx.CombinatorialComplex | tnx.ColoredHyperGraph):
         if neighborhood_type == "adj":
             ind, A = complex.adjacency_matrix(
                 neighborhood_dim["rank"], neighborhood_dim["via_rank"], index=True