Merge branch 'master' into feat/property_fields_container

examples/05-file-IO/02-hdf5_serialize_and_read.py

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+"""
+.. _ref_basic_hdf5:
+
+HDF5 export and import operations
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+This example shows you how to use the HDF5 format to export results
+and meshed regions in an H5 file.
+It also demonstrates how to read results and meshed regions from the
+created H5 file.
+
+First, it exports all the results for all time frequencies,
+then it exports all the time sets for the results, per time set.
+Finally, it reads the results and compares them.
+For the example to run correctly, ensure you do not have an existing H5 file.
+
+"""
+
+###############################################################################
+# Import modules, instantiate model and create temporary folder
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+# Import the ``dpf-core`` module and its examples files.
+
+import ansys.dpf.core as dpf
+from ansys.dpf.core import examples
+
+###############################################################################
+# Instantiate the model and the provider operators:
+
+model = dpf.Model(examples.download_transient_result())
+streams_cont = model.metadata.streams_provider.outputs.streams_container
+time_freq_op = dpf.operators.metadata.time_freq_provider(streams_container=streams_cont)
+time_freq_support = time_freq_op.outputs.time_freq_support()
+time_freqs = time_freq_support.time_frequencies
+
+result_names_on_all_time_steps = []
+result_names_time_per_time = []
+
+num_res = len(model.results)
+num_sets = len(time_freqs.data)
+
+###############################################################################
+# Define a temporary folder for outputs:
+tmpdir = dpf.core.make_tmp_dir_server(dpf.SERVER)
+files = [
+    dpf.path_utilities.join(tmpdir, "file_on_all_time_steps.h5"),
+    dpf.path_utilities.join(tmpdir, "file_time_per_time.h5"),
+]
+
+###############################################################################
+# Use H5 serialization operator
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+# Export all results on all time frequencies:
+h5_serialization_op_all_times = dpf.operators.serialization.hdf5dpf_generate_result_file()
+h5_serialization_op_all_times.inputs.filename.connect(files[0])
+h5_serialization_op_all_times.inputs.mesh_provider_out.connect(model.metadata.meshed_region)
+h5_serialization_op_all_times.inputs.time_freq_support_out.connect(time_freq_support)
+
+for i, res in enumerate(model.results):
+    res_name = "result_" + res().name
+    result_names_on_all_time_steps.append(res_name)
+    h5_serialization_op_all_times.connect(2 * i + 4, res_name)
+    h5_serialization_op_all_times.connect(2 * i + 5, res.on_all_time_freqs())
+
+h5_all_times_ds = h5_serialization_op_all_times.outputs.data_sources()
+
+###############################################################################
+# Export all the results, time set per time set:
+h5_serialization_op_set_per_set = dpf.operators.serialization.hdf5dpf_generate_result_file()
+h5_serialization_op_set_per_set.inputs.filename.connect(files[1])
+h5_serialization_op_set_per_set.inputs.mesh_provider_out.connect(model.metadata.meshed_region)
+h5_serialization_op_set_per_set.inputs.time_freq_support_out.connect(time_freq_support)
+
+for j, freq in enumerate(time_freqs.data):
+    for i, res in enumerate(model.results):
+        res_name = "result_" + res().name + "_time_" + str(freq)
+        result_names_time_per_time.append(res_name)
+        h5_serialization_op_set_per_set.connect(2 * (j * num_res + i) + 4, res_name)
+        h5_serialization_op_set_per_set.connect(
+            2 * (j * num_res + i) + 5, res.on_time_scoping(j + 1).eval()
+        )
+
+h5_set_per_set_ds = h5_serialization_op_set_per_set.outputs.data_sources()
+
+###############################################################################
+# Use H5 reading operator
+# ~~~~~~~~~~~~~~~~~~~~~~~
+# Read the results from all time steps files:
+h5_stream_prov_op = dpf.operators.metadata.streams_provider()
+h5_stream_prov_op.inputs.data_sources.connect(h5_all_times_ds)
+res_deser_all_times_list = []
+h5_read_op = dpf.operators.serialization.hdf5dpf_custom_read()
+h5_read_op.inputs.streams.connect(h5_stream_prov_op.outputs)
+for i, res_name in enumerate(result_names_on_all_time_steps):
+    h5_read_op.inputs.result_name.connect(res_name)
+    res_deser = h5_read_op.outputs.field_or_fields_container_as_fields_container()
+    res_deser_all_times_list.append(res_deser)
+
+###############################################################################
+# Read the meshed region from all time steps file:
+mesh_prov_op = dpf.operators.mesh.mesh_provider()
+mesh_prov_op.inputs.streams_container.connect(h5_stream_prov_op.outputs)
+mesh_deser_all_times = mesh_prov_op.outputs.mesh()
+
+###############################################################################
+# Read the results from the time set per set file:
+h5_stream_prov_op_2 = dpf.operators.metadata.streams_provider()
+h5_stream_prov_op_2.inputs.data_sources.connect(h5_set_per_set_ds)
+res_deser_set_per_set_list = []
+h5_read_op_2 = dpf.operators.serialization.hdf5dpf_custom_read()
+h5_read_op_2.inputs.streams.connect(h5_stream_prov_op_2.outputs)
+for i, res_name in enumerate(result_names_time_per_time):
+    h5_read_op_2.inputs.result_name.connect(res_name)
+    res_deser = h5_read_op_2.outputs.field_or_fields_container_as_fields_container()
+    res_deser_set_per_set_list.append(res_deser)
+
+###############################################################################
+# Read the meshed region from all time steps files:
+mesh_prov_op_2 = dpf.operators.mesh.mesh_provider()
+mesh_prov_op_2.inputs.streams_container.connect(h5_stream_prov_op_2.outputs)
+mesh_deser_set_per_set = mesh_prov_op_2.outputs.mesh()
+
+###############################################################################
+# Compare results
+# ~~~~~~~~~~~~~~~
+
+###############################################################################
+# Print global data:
+print("Number of results is: " + str(num_res))
+print("Number of time sets is: " + str(num_sets))
+print("Results names for 'all time steps' file: ")
+print(result_names_on_all_time_steps)
+print("Results names for 'set per set' file: ")
+print(result_names_time_per_time)
+
+###############################################################################
+# compare first result at second time set:
+fc_all_steps_first_step_first_res = res_deser_all_times_list[0].get_field_by_time_id(2)  # set 1
+mesh_deser_all_times.plot(fc_all_steps_first_step_first_res)
+
+mesh_deser_set_per_set.plot(res_deser_set_per_set_list[num_res * 1 + 0])
+
+###############################################################################
+# compare 4th result at 6 time set:
+to_nodal_op = dpf.operators.averaging.to_nodal_fc()
+
+fc_all_steps_first_step_first_res = res_deser_all_times_list[3].get_field_by_time_id(6)  # set 6
+mesh_deser_all_times.plot(
+    dpf.operators.averaging.to_nodal(fc_all_steps_first_step_first_res).outputs.field()
+)
+
+mesh_deser_set_per_set.plot(
+    dpf.operators.averaging.to_nodal(res_deser_set_per_set_list[num_res * 5 + 3]).outputs.field()
+)