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 the Premium ServerContext. For more information, see Server context.

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

import os
import tempfile

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


dpf.set_default_server_context(dpf.AvailableServerContexts.premium)

tmpdir = tempfile.mkdtemp()

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]])

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(os.path.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(os.path.join(tmpdir, "matrices.csv"))
csv_op.run()

Total running time of the script: ( 0 minutes 0.407 seconds)

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