use np.concatenate

tests/kernelcreation/test_functions.py

@@ -56,7 +56,7 @@ def function_domain(function_name, dtype):
         case (
             "exp" | "sin" | "cos" | "sinh" | "cosh" | "atan" | "abs" | "floor" | "ceil"
         ):
-            return np.concat(
+            return np.concatenate(
                 [
                     [0.0, -1.0, 1.0],
                     rng.uniform(-0.1, 0.1, 5),
@@ -65,21 +65,21 @@ def function_domain(function_name, dtype):
                 ]
             ).astype(dtype)
         case "tan":
-            return np.concat(
+            return np.concatenate(
                 [
                     [0.0, -1.0, 1.0],
                     rng.uniform(-np.pi / 2.0 + eps, np.pi / 2.0 - eps, 13),
                 ]
             ).astype(dtype)
         case "asin" | "acos":
-            return np.concat(
+            return np.concatenate(
                 [
                     [0.0, 1.0, -1.0],
                     rng.uniform(-1.0, 1.0, 13),
                 ]
             ).astype(dtype)
         case "log" | "sqrt":
-            return np.concat(
+            return np.concatenate(
                 [
                     [1.0],
                     rng.uniform(eps, 0.1, 7),
@@ -88,13 +88,13 @@ def function_domain(function_name, dtype):
                 ]
             ).astype(dtype)
         case "min" | "max" | "atan2":
-            return np.concat(
+            return np.concatenate(
                 [
                     rng.uniform(-0.1, 0.1, 8),
                     rng.uniform(-5.0, 5.0, 8),
                     rng.uniform(-10, 10, 8),
                 ]
-            ).astype(dtype), np.concat(
+            ).astype(dtype), np.concatenate(
                 [
                     rng.uniform(-0.1, 0.1, 8),
                     rng.uniform(-5.0, 5.0, 8),
@@ -104,13 +104,13 @@ def function_domain(function_name, dtype):
                 dtype
             )
         case "pow":
-            return np.concat(
+            return np.concatenate(
                 [
                     [0., 1., 1.],
                     rng.uniform(-1., 1., 8),
                     rng.uniform(0., 5., 8),
                 ]
-            ).astype(dtype), np.concat(
+            ).astype(dtype), np.concatenate(
                 [
                     [1., 0., 2.],
                     np.arange(2., 10., 1.),