wip

pyphare/pyphare/core/operators.py

@@ -1,20 +1,39 @@
 import numpy as np
 from pyphare.pharesee.hierarchy import PatchLevel, Patch, FieldData
-from pyphare.pharesee.hierarchy import ScalarField, VectorField#, TensorField
+from pyphare.pharesee.hierarchy import ScalarField, VectorField  # TensorField
+from pyphare.pharesee.hierarchy import compute_hier_from
+from pyphare.pharesee.hierarchy import rename
 
 
-def _compute_dot_product(patchdatas, **kwargs):
+def _compute_dot_product(patch_datas, **kwargs):
 
-    pd_attrs = []
+    ref_name = next(iter(patch_datas.keys()))
 
-    return tuple(pd_attrs)
+    dset = patch_datas["left_x"].dataset[:] * patch_datas["right_x"].dataset[:]\
+         + patch_datas["left_y"].dataset[:] * patch_datas["right_y"].dataset[:]\
+         + patch_datas["left_z"].dataset[:] * patch_datas["right_z"].dataset[:]
 
+    return ({"name": 'scalar', "data": dset, "centering": patch_datas[ref_name].centerings},)
 
-def dot(hier_a, hier_b):
 
-    # doit utiliser un compute_hier_from
+def dot(hier_left, hier_right, **kwargs):
+    # keep original names of each hier TODO
+    if isinstance(hier_left, VectorField) and isinstance(hier_right, VectorField):
+        names_left = ['left_x', 'left_y', 'left_z']
+        names_right = ['right_x', 'right_y', 'right_z']
 
-    return hier_a
+    else:
+        raise RuntimeError("type of hierarchy not yet considered")
+
+    hl = rename(hier_left, names_left)
+    hr = rename(hier_right, names_right)
+
+    h = compute_hier_from(_compute_dot_product, (hl, hr),)
+
+    return ScalarField(h.patch_levels, h.domain_box,
+                       refinement_ratio=h.refinement_ratio,
+                       time=h.times()[0],
+                       data_files=h.data_files)
 
 
 def sqrt(hier):
@@ -37,7 +56,8 @@ def sqrt(hier):
                 new_pd = {}
 
                 dset = np.sqrt(np.asarray(patch.patch_datas['scalar'].dataset))
-                new_pd[ScalarField.name] = FieldData(layout, 'scalar', dset, centering=patch.patch_datas['scalar'].centerings)
+                new_pd[ScalarField.name] = FieldData(layout, 'scalar', dset,
+                        centering=patch.patch_datas['scalar'].centerings)
                 new_patches[ilvl].append(Patch(new_pd, patch.id))
 
             new_patch_level[ilvl] = PatchLevel(ilvl, new_patches[ilvl])

pyphare/pyphare/pharesee/hierarchy.py

@@ -1198,6 +1198,20 @@ def __rmul__(self, operand):
         return self.__mul__(operand)
 
 
+def _compute_rename(patch_datas, **kwargs):
+    new_names = kwargs["names"]
+    pd_attrs = []
+
+    for name, new_name in zip(patch_datas.keys(), new_names):
+        pd_attrs.append({"name": new_name,
+                         "data": patch_datas[name].dataset,
+                         "centering": patch_datas[name].centerings})
+
+    return tuple(pd_attrs)
+
+
+def rename(hierarchy, names):
+    return compute_hier_from(_compute_rename, hierarchy, names=names,)
 
 
 def amr_grid(hierarchy, time):

pyphare/pyphare/pharesee/run.py

@@ -281,7 +281,7 @@ def _compute_to_primal(patchdatas, **kwargs):
     pd_attrs = []
     for i, (name, pd_name) in enumerate(kwargs.items()):
         pd = patchdatas[pd_name]
-        ds_shape = list(pd.dataset.shape)
+        # ds_shape = list(pd.dataset.shape)
 
         if pd_name in ['Fx', 'Fy', 'Fz', 'Vx', 'Vy', 'Vz', 'rho', 'tags']:
             pass
@@ -297,13 +297,13 @@ def _compute_to_primal(patchdatas, **kwargs):
             dataset[i] = _compute_Ey_to_primal(pd, nb_ghosts=nb_ghosts)
         elif pd_name == "Ez":
             dataset[i] = _compute_Ez_to_primal(pd, nb_ghosts=nb_ghosts)
-        elif pd_name == "Jx": # TODO same centering as Ex... only for Yee !
+        elif pd_name == "Jx":  # TODO same centering as Ex... only for Yee !
             dataset[i] = _compute_Ex_to_primal(pd, nb_ghosts=nb_ghosts)
-        elif pd_name == "Jy": # TODO same centering as Ey... only for Yee !
+        elif pd_name == "Jy":  # TODO same centering as Ey... only for Yee !
             dataset[i] = _compute_Ey_to_primal(pd, nb_ghosts=nb_ghosts)
-        elif pd_name == "Jz": # TODO same centering as Ez... only for Yee !
+        elif pd_name == "Jz":  # TODO same centering as Ez... only for Yee !
             dataset[i] = _compute_Ez_to_primal(pd, nb_ghosts=nb_ghosts)
-        else: # TODO need to figure out what to do for pressure, of each specie
+        else:  # TODO need to figure out what to do for pressure of each specie
             raise RuntimeError("patchdata name unknown")
         pd_attrs.append({"name": name, "data": dataset[i], "centering": centerings})
         # break