Merge branch 'master' of https://github.com/pyansys/DPF-Core

Author: cbellot000

ansys/dpf/core/mesh_scoping_factory.py

@@ -14,16 +14,16 @@ def nodal_scoping(node_ids, server=None):
 
     Parameters
     ----------
-    node_ids : List of int
+    node_ids : list[int]
         List of IDs for the nodes.
-    server : ansys.dpf.core.server, optional
+    server : DpfServer, optional
         Server with the channel connected to the remote or local instance.
         The default is ``None``, in which case an attempt is made to use the
         global server.
 
     Returns
     -------
-    scoping : ansys.dpf.core.Scoping
+    scoping : Scoping
     """
     scoping = Scoping(server=server, ids=node_ids, location=locations.nodal)
     return scoping
@@ -34,16 +34,16 @@ def elemental_scoping(element_ids, server=None):
 
     Parameters
     ----------
-    element_ids : List of int
+    element_ids : list[int]
         List of IDs for the elements.
-    server : ansys.dpf.core.server, optional
+    server : DpfServer, optional
         Server with the channel connected to the remote or local instance.
         The default is ``None``, in which case an attempt is made to use the
         global server.
 
     Returns
     -------
-    scoping : ansys.dpf.core.Scoping
+    scoping : Scoping
     """
     scoping = Scoping(server=server, ids=element_ids, location=locations.elemental)
     return scoping
@@ -56,13 +56,13 @@ def named_selection_scoping(named_selection_name, model, server=None):
     ----------
     named_selection_name : str
         Name of the named selection.
-    server : ansys.dpf.core.server, optional
+    server : DpfServer, optional
         Server with the channel connected to the remote or local instance.
         The default is ``None``, in which case an attempt is made to use the
         global server.
 
     Returns
     -------
-    scoping : ansys.dpf.core.Scoping
+    scoping : Scoping
     """
     return model.metadata.named_selection(named_selection_name)

ansys/dpf/core/time_freq_scoping_factory.py

@@ -8,7 +8,7 @@
 from ansys.dpf.core import Scoping
 from ansys.dpf.core import errors as dpf_errors
 from ansys.dpf.core.common import locations
-
+from ansys.dpf.core.model import Model
 
 def scoping_by_load_step(load_step, server=None):
     """Create a specific ``ansys.dpf.core.Scoping`` for a given load step.
@@ -19,15 +19,15 @@ def scoping_by_load_step(load_step, server=None):
     Parameters
     ----------
     load_step : int
-        Load step ID of the specific time frequency scoiping.
-     server : ansys.dpf.core.server, optional
+        Load step ID of the specific time frequency scoping.
+     server : DpfServer, optional
         Server with the channel connected to the remote or local instance.
         The default is ``None``, in which case an attempt is made to use the
         global server.
 
     Returns
     -------
-    scoping : ansys.dpf.core.Scoping
+    scoping : Scoping
         Scoping targeting one load step.
     """
     scoping = Scoping(server=server, ids=[load_step], location=locations.time_freq_step)
@@ -42,16 +42,16 @@ def scoping_by_load_steps(load_steps, server=None):
 
     Parameters
     ----------
-    load_steps : list of int
+    load_steps : list[int]
         List of load steps IDs of the specific time frequency scoping.
-    server : ansys.dpf.core.server, optional
+    server : DpfServer, optional
         Server with the channel connected to the remote or local instance.
         The default is ``None``, in which case an attempt is made to use the
         global server.
 
     Returns
     -------
-    scoping : ansys.dpf.core.Scoping
+    scoping : Scoping
         Scoping targeting several load_steps.
     """
     if not isinstance(load_steps, list):
@@ -70,14 +70,14 @@ def scoping_by_set(cumulative_set, server=None):
     ----------
     cumulative_set : int
         Cumulative index of the set.
-    server : ansys.dpf.core.server, optional
+    server : DpfServer, optional
         Server with the channel connected to the remote or local instance.
         The default is ``None``, in which case an attempt is made to use the
         global server.
 
     Returns
     -------
-    scoping : ansys.dpf.core.Scoping
+    scoping : Scoping
         Scoping targeting one set (referenced by cumulative index).
     """
     scoping = Scoping(server=server, ids=[cumulative_set], location=locations.time_freq)
@@ -92,16 +92,16 @@ def scoping_by_sets(cumulative_sets, server=None):
 
     Parameters
     ----------
-    cumulative_sets : list of int
+    cumulative_sets : list[int]
         List of cumulative indices of the sets.
-     server : ansys.dpf.core.server, optional
+     server : DpfServer, optional
         Server with the channel connected to the remote or local instance.
         The default is ``None``, in which case an attempt is made to use the
         global server.
 
     Returns
     -------
-    scoping : ansys.dpf.core.Scoping
+    scoping : Scoping
         Scoping targeting severals sets (referenced by cumulative indices).
     """
     if not isinstance(cumulative_sets, list):
@@ -111,7 +111,7 @@ def scoping_by_sets(cumulative_sets, server=None):
 
 
 def scoping_by_step_and_substep(
-    load_step_id, subset_id, time_freq_support, server=None
+        load_step_id, subset_id, time_freq_support
 ):
     """Create a specific :class:`ansys.dpf.core.Scoping` for a given step and subset.
 
@@ -124,19 +124,18 @@ def scoping_by_step_and_substep(
         ID of the load step.
     subset_id : int
         ID of the subset.
-    time_freq_support : ansys.dpf.core.TimeFreqSupport
-    server : ansys.dpf.core.server, optional
-        Server with the channel connected to the remote or local instance.
-        The default is ``None``, in which case an attempt is made to use the
-        global server.
+    time_freq_support : TimeFreqSupport
 
     Returns
     -------
-    scoping : ansys.dpf.core.Scoping
+    scoping : Scoping
         Scoping based on a given step and substep of a time frequency support.
     """
     set_index = time_freq_support.get_cumulative_index(load_step_id - 1, subset_id - 1)
-    scoping = Scoping(ids=[set_index + 1], location=locations.time_freq)
+    scoping = Scoping(
+        ids=[set_index + 1],
+        location=locations.time_freq,
+        server=time_freq_support._server)
     return scoping
 
 
@@ -152,16 +151,37 @@ def scoping_by_step_and_substep_from_model(load_step_id, subset_id, model, serve
         ID of the step.
     subset_id : int
         ID of the subset.
-    time_freq_support : ansys.dpf.core.TimeFreqSupport()
-    server : ansys.dpf.core.server, optional
+    model : Model
+    server : DpfServer, optional
         Server with the channel connected to the remote or local instance.
         The default is ``None``, in which case an attempt is made to use the
         global server.
 
     Returns
     -------
-    scoping : ansys.dpf.core.Scoping
+    scoping : Scoping
         Scoping based on a given step/substep of a model's time_freq_support."""
     return scoping_by_step_and_substep(
         load_step_id, subset_id, model.metadata.time_freq_support
     )
+
+
+def scoping_on_all_time_freqs(tf_support_or_model):
+    """Create a specific :class:`ansys.dpf.core.Scoping` with all time or
+    frequency sets of a :class:`ansys.dpf.core.TimeFreqSupport` or a class:`ansys.dpf.core.Model`
+
+    Parameters
+    ----------
+    tf_support_or_model : TimeFreqSupport, Model
+
+    Returns
+    -------
+    scoping : Scoping
+        Scoping with all time or frequency sets IDs.
+    """
+    if isinstance(tf_support_or_model, Model):
+        tf_support_or_model = tf_support_or_model.metadata.time_freq_support
+    return Scoping(
+        ids=range(1, len(tf_support_or_model.time_frequencies) + 1),
+        location=locations.time_freq,
+        server=tf_support_or_model._server)

examples/00-basic/01-basic_operators.py

@@ -59,7 +59,7 @@
 mm_op = dpf.Operator("min_max_fc")
 mm_op.inputs.connect(norm_op.outputs)
 
-# Finally, get the value of the maximum displacement
+# Finally, get the value of the maximum displacement.
 field_max = mm_op.outputs.field_max()
 print(field_max)
 print(field_max.data)
@@ -78,8 +78,8 @@
 # Create the displacement operator directly from the ``results`` property:
 disp_op = model.results.displacement()
 
-# Out of convenience, the operators module contains available operators
-# Those operators can be created in chain to create a workflow in one line
+# Out of convenience, the ``operators`` module contains available operators.
+# These operators can be chained to create a workflow in one line.
 from ansys.dpf.core import operators
 
 mm_op = operators.min_max.min_max_fc(operators.math.norm_fc(disp_op))
@@ -103,7 +103,7 @@
 
 ###############################################################################
 # Instead of using a ``model`` class instance, use a
-# datasources object directly. The ``DataSources`` constructor input is a path.
+# ``DdataSources`` object directly. The ``DataSources`` constructor input is a path.
 ds = dpf.DataSources(examples.static_rst)
 print(examples.static_rst)
 

examples/00-basic/02-basic_field_containers.py

@@ -4,7 +4,7 @@
 Field and Field Containers Overview
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 In DPF, the field is the main simulation data container. During a numerical
-simulations, result data is defined by values associated to entities
+simulation, result data is defined by values associated to entities
 (scoping). These entities are a subset of a model (support).
 
 Because field data is always associated to its scoping and support,
@@ -14,7 +14,7 @@
 tensor, stress or strain equivalent, or minimum or maximum
 over time of any result. A field can be defined on a complete model or
 on only certain entities of the model based on its scoping. The data
-is stored as a vector of double values and each elementary entity has
+is stored as a vector of double values, and each elementary entity has
 a number of components. For example, a displacement will have three
 components, and a symmetrical stress matrix will have six components.
 

examples/00-basic/07-use_result_helpers.py

@@ -3,7 +3,7 @@
 
 Use Result Helpers to Load Custom Data
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-The ``Result`` class, which are instances created by the ``Model``, give
+The ``Result`` class, which is an instance created by the ``Model``, gives
 access to helpers for requesting results on specific mesh and time scopings.
 With these helpers, working on a custom spatial and temporal subset of the
 model is straightforward.

tests/test_factories.py

@@ -242,6 +242,16 @@ def test_scoping_by_step_and_substep_from_model(plate_msup):
     assert scop.location == locations.time_freq
 
 
+def test_scoping_on_all_freqs(plate_msup):
+    model = Model(plate_msup)
+    scop = time_freq_scoping_factory.scoping_on_all_time_freqs(model)
+    assert scop is not None
+    assert np.allclose(scop.ids, range(1, 21))
+    scop = time_freq_scoping_factory.scoping_on_all_time_freqs(model.metadata.time_freq_support)
+    assert scop is not None
+    assert np.allclose(scop.ids, range(1, 21))
+
+
 def test_nodal_scoping():
     scop = mesh_scoping_factory.nodal_scoping([2, 5, 10])
     assert scop is not None