Remove numpy from dependencies

Author: vadyushkins

cfpq_data/graphs/generators/fast_labeled_binomial_graph.py

@@ -5,9 +5,7 @@
 import random
 from typing import Union, Iterable
 
-import numpy as np
 from networkx import MultiDiGraph, fast_gnp_random_graph
-from numpy.random import RandomState
 from tqdm import tqdm
 
 __all__ = ["fast_labeled_binomial_graph"]
@@ -16,7 +14,7 @@
 def fast_labeled_binomial_graph(
     number_of_nodes: int,
     edge_probability: float,
-    seed: Union[int, RandomState, None] = None,
+    seed: Union[int, None] = None,
     edge_labels: Iterable[str] = "a",
     verbose: bool = True,
 ) -> MultiDiGraph:
@@ -83,9 +81,8 @@ def fast_labeled_binomial_graph(
     )
 
     random.seed(seed)
-    np.random.seed(seed)
 
     for edge in tqdm(g.edges, disable=not verbose, desc="Generation..."):
-        g.edges[edge]["label"] = np.random.choice(list(edge_labels))
+        g.edges[edge]["label"] = random.choice(list(edge_labels))
 
     return g

cfpq_data/graphs/generators/labeled_barabasi_albert_graph.py

@@ -8,9 +8,7 @@
 import random
 from typing import Iterable, Union
 
-import numpy as np
 from networkx import MultiDiGraph, barabasi_albert_graph
-from numpy.random import RandomState
 from tqdm import tqdm
 
 __all__ = ["labeled_barabasi_albert_graph"]
@@ -19,7 +17,7 @@
 def labeled_barabasi_albert_graph(
     number_of_nodes: int,
     number_of_edges: int,
-    seed: Union[int, RandomState, None] = None,
+    seed: Union[int, None] = None,
     edge_labels: Iterable[str] = "abcd",
     verbose: bool = True,
 ) -> MultiDiGraph:
@@ -78,10 +76,9 @@ def labeled_barabasi_albert_graph(
     )
 
     random.seed(seed)
-    np.random.seed(seed)
 
     for edge in tqdm(g.edges, disable=not verbose, desc="Generation..."):
-        label = np.random.choice(list(edge_labels))
+        label = random.choice(list(edge_labels))
         g.edges[edge]["label"] = label
 
     return g

cfpq_data/graphs/generators/labeled_binomial_graph.py

@@ -5,9 +5,7 @@
 import random
 from typing import Union, Iterable
 
-import numpy as np
 from networkx import MultiDiGraph, gnp_random_graph
-from numpy.random import RandomState
 from tqdm import tqdm
 
 __all__ = ["labeled_binomial_graph"]
@@ -16,7 +14,7 @@
 def labeled_binomial_graph(
     number_of_nodes: int,
     edge_probability: float,
-    seed: Union[int, RandomState, None] = None,
+    seed: Union[int, None] = None,
     edge_labels: Iterable[str] = "a",
     verbose: bool = True,
 ) -> MultiDiGraph:
@@ -75,9 +73,8 @@ def labeled_binomial_graph(
     )
 
     random.seed(seed)
-    np.random.seed(seed)
 
     for edge in tqdm(g.edges, disable=not verbose, desc="Generation..."):
-        g.edges[edge]["label"] = np.random.choice(list(edge_labels))
+        g.edges[edge]["label"] = random.choice(list(edge_labels))
 
     return g

cfpq_data/graphs/generators/labeled_scale_free_graph.py

@@ -4,9 +4,7 @@
 import random
 from typing import Union, Iterable
 
-import numpy as np
 from networkx import MultiDiGraph, scale_free_graph
-from numpy.random import RandomState
 from tqdm import tqdm
 
 __all__ = ["labeled_scale_free_graph"]
@@ -19,7 +17,7 @@ def labeled_scale_free_graph(
     gamma: float = 0.05,
     delta_in: float = 0.2,
     delta_out: float = 0,
-    seed: Union[int, RandomState, None] = None,
+    seed: Union[int, None] = None,
     edge_labels: Iterable[str] = "abcd",
     verbose: bool = True,
 ) -> MultiDiGraph:
@@ -67,7 +65,7 @@ def labeled_scale_free_graph(
     >>> g.number_of_nodes()
     42
     >>> g.number_of_edges()
-    88
+    81
 
     Returns
     -------
@@ -98,10 +96,9 @@ def labeled_scale_free_graph(
     )
 
     random.seed(seed)
-    np.random.seed(seed)
 
     for edge in tqdm(g.edges, disable=not verbose, desc="Generation..."):
-        label = np.random.choice(list(edge_labels))
+        label = random.choice(list(edge_labels))
         g.edges[edge]["label"] = label
 
     return g

tests/graphs/generators/test_fast_labeled_binomial_graph.py

@@ -1,13 +1,11 @@
 import random
 
-import numpy as np
 import pytest
 
 import cfpq_data
 
 seed = 42
 random.seed(seed)
-np.random.seed(seed)
 
 g1 = cfpq_data.fast_labeled_binomial_graph(29, 0.1, seed=seed, verbose=False)
 g2 = cfpq_data.fast_labeled_binomial_graph(42, 0.1, seed=seed, verbose=False)

tests/graphs/generators/test_labeled_barabasi_albert_graph.py

@@ -1,13 +1,11 @@
 import random
 
-import numpy as np
 import pytest
 
 import cfpq_data
 
 seed = 42
 random.seed(seed)
-np.random.seed(seed)
 
 g1 = cfpq_data.labeled_barabasi_albert_graph(100, 1, seed=seed, verbose=False)
 g2 = cfpq_data.labeled_barabasi_albert_graph(100, 3, seed=seed, verbose=False)

tests/graphs/generators/test_labeled_binomial_graph.py

@@ -1,13 +1,11 @@
 import random
 
-import numpy as np
 import pytest
 
 import cfpq_data
 
 seed = 42
 random.seed(seed)
-np.random.seed(seed)
 
 g1 = cfpq_data.labeled_binomial_graph(42, 0.42, seed=seed, verbose=False)
 g2 = cfpq_data.labeled_binomial_graph(42, 0.73, seed=seed, verbose=False)

tests/graphs/generators/test_labeled_scale_free_graph.py

@@ -1,20 +1,18 @@
 import random
 
-import numpy as np
 import pytest
 
 import cfpq_data
 
 seed = 42
 random.seed(seed)
-np.random.seed(seed)
 
 g1 = cfpq_data.labeled_scale_free_graph(29, seed=seed, verbose=False)
 g2 = cfpq_data.labeled_scale_free_graph(42, seed=seed, verbose=False)
 
 
 @pytest.mark.parametrize(
-    "graph,expected_nodes,expected_edges", [(g1, 29, 56), (g2, 42, 88)]
+    "graph,expected_nodes,expected_edges", [(g1, 29, 54), (g2, 42, 81)]
 )
 def test_labeled_scale_free_graph(graph, expected_nodes, expected_edges):
     assert (

tests/graphs/readwrite/test_txt.py

@@ -3,14 +3,12 @@
 import random
 
 import networkx as nx
-import numpy as np
 import pytest
 
 import cfpq_data
 
 seed = 42
 random.seed(seed)
-np.random.seed(seed)
 
 g1 = cfpq_data.labeled_binomial_graph(42, 0.42, seed=seed, verbose=False)
 g2 = cfpq_data.labeled_binomial_graph(42, 0.73, seed=seed, verbose=False)

tests/graphs/utils/test_change_edges.py

@@ -1,13 +1,11 @@
 import random
 
-import numpy as np
 import pytest
 
 import cfpq_data
 
 seed = 42
 random.seed(seed)
-np.random.seed(seed)
 
 g1 = cfpq_data.labeled_barabasi_albert_graph(
     42, 3, seed, edge_labels="a", verbose=False