Update NumPy and Numba versions

For Python3.12 support. Fix `argsort()` with `kind="stable"` for newer NumPy. Update migration tests to use `np.int64`.
InstituteforDiseaseModeling · Nov 18, 2024 · 126c051 · 126c051
1 parent 4617038
commit 126c051
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Showing 3 changed files with 9 additions and 9 deletions.
diff --git a/pyproject.toml b/pyproject.toml
@@ -31,8 +31,8 @@ classifiers = [
 ]
 dependencies = [
     "click",  # ==8.1.7",
-    "numpy",  # ==1.26.2",
-    "numba",  # ==0.58.1",
+    "numpy>=1.26.4,<2.0.0",
+    "numba>=0.59.1",
     "polars",  # ==0.19.19",
     "tqdm",  # ==4.66.1",
     "matplotlib",

diff --git a/src/laser_core/migration.py b/src/laser_core/migration.py
@@ -321,7 +321,7 @@ def radiation(pops, distances, k, include_home, **params):
     # We will just use the "truthiness" of include_home (could be boolean, could be 0/1)
 
     network = np.zeros_like(distances)
-    sort_indices = np.argsort(distances, axis=1, stable=True)
+    sort_indices = np.argsort(distances, axis=1, kind="stable")
     unsort_indices = np.argsort(sort_indices, axis=1)
 
     for i in range(len(pops)):

diff --git a/tests/test_migration.py b/tests/test_migration.py
@@ -131,7 +131,7 @@ def test_stouffer_exclude_home(self):
         for i in range(network.shape[0]):
             for j in range(network.shape[1]):
                 if i != j:
-                    mysum = 0
+                    mysum = np.int64(0)
                     for m in range(len(self.pops)):
                         if (m != i) and (self.distances[i][m] <= self.distances[i][j]):
                             mysum = mysum + self.pops[m]
@@ -147,7 +147,7 @@ def test_stouffer_include_home(self):
         for i in range(network.shape[0]):
             for j in range(network.shape[1]):
                 if i != j:
-                    mysum = 0
+                    mysum = np.int64(0)
                     for m in range(len(self.pops)):
                         if self.distances[i][m] <= self.distances[i][j]:
                             mysum = mysum + self.pops[m]
@@ -168,7 +168,7 @@ def test_stouffer_equidistant_nodes(self):
         for i in range(network.shape[0]):
             for j in range(network.shape[1]):
                 if i != j:
-                    mysum = 0
+                    mysum = np.int64(0)
                     for m in range(len(pops)):
                         if distances[i][m] <= distances[i][j]:
                             mysum = mysum + pops[m]
@@ -184,7 +184,7 @@ def test_radiation_exclude_home(self):
         for i in range(network.shape[0]):
             for j in range(network.shape[1]):
                 if i != j:
-                    mysum = 0
+                    mysum = np.int64(0)
                     for m in range(len(self.pops)):
                         if (m != i) and (self.distances[i][m] <= self.distances[i][j]):
                             mysum = mysum + self.pops[m]
@@ -200,7 +200,7 @@ def test_radiation_include_home(self):
         for i in range(network.shape[0]):
             for j in range(network.shape[1]):
                 if i != j:
-                    mysum = 0
+                    mysum = np.int64(0)
                     for m in range(len(self.pops)):
                         if self.distances[i][m] <= self.distances[i][j]:
                             mysum = mysum + self.pops[m]
@@ -221,7 +221,7 @@ def test_radiation_equidistant_nodes(self):
         for i in range(network.shape[0]):
             for j in range(network.shape[1]):
                 if i != j:
-                    mysum = 0
+                    mysum = np.int64(0)
                     for m in range(len(pops)):
                         if (m != i) and (distances[i][m] <= distances[i][j]):
                             mysum = mysum + pops[m]