Get reduced matrices and make export

This example shows how to get reduced matrices and export them to HDF5 and CSV files.

Note

This example requires DPF 6.0 (DPF 2023 R2) or above. For more information, see Compatibility.

Import the dpf-core module and its examples files, and then create a temporary directory.

from ansys.dpf import core as dpf
from ansys.dpf.core import examples, operators as ops

Create the operator and connect data sources.

ds = dpf.DataSources(examples.download_sub_file())

matrices_provider = ops.result.cms_matrices_provider()
matrices_provider.inputs.data_sources.connect(ds)

Get result fields container that contains the reduced matrices.

fields = matrices_provider.outputs.fields_container()

len(fields)

fields[0].data

DPFArray([[ 5.53476768e+11, -2.29728435e+10,  2.29728435e+10, ...,
            0.00000000e+00,  0.00000000e+00,  2.91225427e+05]],
         shape=(1, 60516))

Define a temporary folder for outputs

tmpdir = dpf.core.make_tmp_dir_server(dpf.SERVER)

Export the result fields container to an HDF5 file.

h5_op = ops.serialization.serialize_to_hdf5()
h5_op.inputs.data1.connect(matrices_provider.outputs)
h5_op.inputs.file_path.connect(dpf.path_utilities.join(tmpdir, "matrices.h5"))
h5_op.run()

Export the result fields container to a CSV file.

csv_op = ops.serialization.field_to_csv()
csv_op.inputs.field_or_fields_container.connect(matrices_provider.outputs)
csv_op.inputs.file_path.connect(dpf.path_utilities.join(tmpdir, "matrices.csv"))
csv_op.run()