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Get reduced matrices and make export#
This example shows how to get reduced matrices and export them to HDF5 and CSV files.
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()
Total running time of the script: (0 minutes 3.892 seconds)