Note
Click here to download the full example code
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 1.188 seconds)