Numpy2.0 support (#86)

* Numpy2.0 support * Steven comments * enlarge the range --------- Co-authored-by: Steven <[email protected]>
causalens · Oct 22, 2024 · e0d7d2c · e0d7d2c
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diff --git a/changelog.md b/changelog.md
@@ -1,5 +1,9 @@
 # Changelog
 
+## NEXT
+
+- Added support for `numpy < 3.0.0` for Python versions `>= 3.10`.
+
 ## 0.5.6
 
 - Added the `cai_causal_graph.causal_graph.CausalGraph.get_nodes_between` method, which returns the set of all nodes

diff --git a/pyproject.toml b/pyproject.toml
@@ -56,7 +56,10 @@ packages = [{include = "cai_causal_graph"}]
 mypy-extensions = "^1.0.0"
 # networkx 3.3 broke how get_all_simple_paths works so want to bound for now.
 networkx = ">=3.0.0, <3.3.0"
-numpy = "^1.20.0"
+numpy = [
+    {version = ">=1.18.0, <3.0.0", python = ">=3.10"},
+    {version = ">=1.18.0, <2.0.0", python = "<3.10"}
+]
 pandas = ">=1.0.0, <3.0.0"
 python = ">=3.9.0, <3.13.0"
 

diff --git a/tests/test_conversions.py b/tests/test_conversions.py
@@ -61,7 +61,7 @@ def _graph_to_adjmat(graph: networkx.DiGraph) -> numpy.ndarray:
     p = float(degree) / (d - 1)
 
     # note that we need to pass an int seed to erdos_renyi_graph(), which we extract from the current rng state
-    rng_state = rng.__getstate__()['state']['state']
+    rng_state = rng.bit_generator.state['state']['state']
 
     # generate graph, using a faster algorithm if graph is sparse, or deliberately specified
     sparsity_threshold = 0.1