using ones_like, random seed

langmm · Jul 13, 2023 · 0a548b9 · 0a548b9
1 parent bb5d5b4
commit 0a548b9
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Showing 2 changed files with 10 additions and 9 deletions.
diff --git a/doc/source/examining/Loading_Generic_Array_Data.ipynb b/doc/source/examining/Loading_Generic_Array_Data.ipynb
@@ -718,10 +718,10 @@
     "arr = prng.random(size=(64, 64, 64))\n",
     "data = {\n",
     "    \"density\": (arr, \"g/cm**3\"),\n",
-    "    \"H_p0_fraction\": (0.37 * np.ones(arr.shape), \"dimensionless\"),\n",
-    "    \"H_p1_fraction\": (0.37 * np.ones(arr.shape), \"dimensionless\"),\n",
-    "    \"He_fraction\": (0.24 * np.ones(arr.shape), \"dimensionless\"),\n",
-    "    \"CO_fraction\": (0.02 * np.ones(arr.shape), \"dimensionless\"),\n",
+    "    \"H_p0_fraction\": (0.37 * np.ones_like(arr), \"dimensionless\"),\n",
+    "    \"H_p1_fraction\": (0.37 * np.ones_like(arr), \"dimensionless\"),\n",
+    "    \"He_fraction\": (0.24 * np.ones_like(arr), \"dimensionless\"),\n",
+    "    \"CO_fraction\": (0.02 * np.ones_like(arr), \"dimensionless\"),\n",
     "}\n",
     "bbox = np.array([[-1.5, 1.5], [-1.5, 1.5], [-1.5, 1.5]])\n",
     "ds = yt.load_uniform_grid(data, arr.shape, length_unit=\"Mpc\", bbox=bbox, nprocs=64)\n",

diff --git a/yt/frontends/stream/tests/test_stream_species.py b/yt/frontends/stream/tests/test_stream_species.py
@@ -5,14 +5,15 @@
 
 
 def test_stream_species():
-    arr = np.random.uniform(size=(32, 32, 32))
+    prng = np.random.default_rng(seed=42)
+    arr = prng.uniform(size=(32, 32, 32))
 
     data = {
         "density": (arr, "g/cm**3"),
-        "H_p0_fraction": (0.37 * np.ones(arr.shape), "dimensionless"),
-        "H_p1_fraction": (0.37 * np.ones(arr.shape), "dimensionless"),
-        "He_fraction": (0.24 * np.ones(arr.shape), "dimensionless"),
-        "CO_fraction": (0.02 * np.ones(arr.shape), "dimensionless"),
+        "H_p0_fraction": (0.37 * np.ones_like(arr), "dimensionless"),
+        "H_p1_fraction": (0.37 * np.ones_like(arr), "dimensionless"),
+        "He_fraction": (0.24 * np.ones_like(arr), "dimensionless"),
+        "CO_fraction": (0.02 * np.ones_like(arr), "dimensionless"),
     }
     bbox = np.array([[-1.5, 1.5], [-1.5, 1.5], [-1.5, 1.5]])
     ds = load_uniform_grid(data, arr.shape, length_unit="Mpc", bbox=bbox, nprocs=64)