[RF][PyROOT] Fix RooDataSet.from_numpy() for contiguous input arrays

Closes root-project#13605.

bindings/pyroot/pythonizations/python/ROOT/_pythonization/_roofit/_roodataset.py

@@ -99,7 +99,6 @@ def log_warning(s):
         range_mask = np.ones_like(list(data.values())[0], dtype=bool)
 
         def in_range(arr, variable):
-
             # For categories, we need to check whether the elements of the
             # array are in the set of category state indices
             if variable.isCategory():
@@ -117,30 +116,27 @@ def select_range_and_change_type(arr, dtype):
             if range_mask is not None:
                 arr = arr[range_mask]
             arr = arr if arr.dtype == dtype else np.array(arr, dtype=dtype)
-            return arr
-
-        for real in dataset.store().realStoreList():
-            vec = real.data()
-            arg = real.bufArg()
-            arr = select_range_and_change_type(data[arg.GetName()], np.float64)
-
-            vec.resize(len(arr))
-
-            beg = arr.ctypes.data_as(ctypes.POINTER(ctypes.c_double))
-            void_p = ctypes.cast(beg, ctypes.c_voidp).value + 8 * len(arr)
-            end = ctypes.cast(void_p, ctypes.POINTER(ctypes.c_double))
-            ROOT.std.copy(beg, end, vec.begin())
-
-        for cat in dataset.store().catStoreList():
-            vec = cat.data()
-            arg = cat.bufArg()
-            arr = select_range_and_change_type(data[arg.GetName()], np.int32)
-            vec.resize(len(arr))
-
-            beg = arr.ctypes.data_as(ctypes.POINTER(ctypes.c_int))
-            void_p = ctypes.cast(beg, ctypes.c_voidp).value + 4 * len(arr)
-            end = ctypes.cast(void_p, ctypes.POINTER(ctypes.c_int))
-            ROOT.std.copy(beg, end, vec.begin())
+            # Make sure that the array is contiguous to we can std::copy() it.
+            # In the implementation of ascontiguousarray(), no copy is done if
+            # the array is already contiguous, which is exactly what we want.
+            return np.ascontiguousarray(arr)
+
+        def copy_to_dataset(store_list, np_type, c_type, type_size_in_bytes):
+            for real in store_list:
+                vec = real.data()
+                arg = real.bufArg()
+                arr = select_range_and_change_type(data[arg.GetName()], np_type)
+
+                vec.resize(len(arr))
+
+                beg = arr.ctypes.data_as(ctypes.POINTER(c_type))
+                n_bytes = type_size_in_bytes * len(arr)
+                void_p = ctypes.cast(beg, ctypes.c_voidp).value + n_bytes
+                end = ctypes.cast(void_p, ctypes.POINTER(c_type))
+                ROOT.std.copy(beg, end, vec.begin())
+
+        copy_to_dataset(dataset.store().realStoreList(), np.float64, ctypes.c_double, 8)
+        copy_to_dataset(dataset.store().catStoreList(), np.int32, ctypes.c_int, 4)
 
         dataset.store().recomputeSumWeight()
 

bindings/pyroot/pythonizations/test/roofit/roodataset_numpy.py

@@ -143,6 +143,41 @@ def test_ignoring_out_of_range(self):
 
         self.assertEqual(dataset_numpy.numEntries(), n_in_range)
 
+    def test_non_contiguous_arrays(self):
+        """Test whether the import also works with non-continguous arrays.
+        Covers GitHub issue #1360.
+        """
+
+        import itertools
+
+        obs_1 = ROOT.RooRealVar("obs_1", "obs_1", 70, 70, 190)
+        obs_1.setBins(30)
+        obs_2 = ROOT.RooRealVar("obs_2", "obs_2", 100, 100, 180)
+        obs_2.setBins(80)
+
+        val_obs_1 = []
+        val_obs_2 = []
+        for i in range(obs_1.numBins()):
+            obs_1.setBin(i)
+            val_obs_1.append(obs_1.getVal())
+        for i in range(obs_2.numBins()):
+            obs_2.setBin(i)
+            val_obs_2.append(obs_2.getVal())
+
+        # so that all combination of values are in the dataset
+        val_cart_product = np.array(list(itertools.product(val_obs_1, val_obs_2)))
+        data = {"obs_1": val_cart_product[:, 0], "obs_2": val_cart_product[:, 1]}
+
+        # To make sure the array is really not C-contiguous
+        assert data["obs_1"].flags["C_CONTIGUOUS"] == False
+
+        dataset = ROOT.RooDataSet.from_numpy(data, ROOT.RooArgSet(obs_1, obs_2))
+
+        data_roundtripped = dataset.to_numpy()
+
+        np.testing.assert_equal(data["obs_1"], data_roundtripped["obs_1"])
+        np.testing.assert_equal(data["obs_2"], data_roundtripped["obs_2"])
+
 
 if __name__ == "__main__":
     unittest.main()