Write/load and upload/download a result file

ansys.dpf.core module is able to upload files to the server machine, and download files from there.

This example shows how to write and upload files on the server machine, then how to download it back on the cient side.

The result fields container will be exported under .csv format.

Let’s first load a Model from the Examples provided by ansys.dpf.core module.

from ansys.dpf import core
from ansys.dpf.core import examples

model = core.Model(examples.simple_bar)
mesh = model.metadata.meshed_region

Get the result

Get the result fields container and plot (in order to compare later)

displacement_operator = model.results.displacement()
fc_out = displacement_operator.outputs.fields_container()
mesh.plot(fc_out)

Out:

[(4.199214280684376, 5.199214280684376, 4.199214280684376),
 (0.5, 1.5, 0.5),
 (0.0, 0.0, 1.0)]

Export result

Let’s get the result fields container and export it using .csv format.

import os
file_path = os.getcwd() + '\\simple_bar_fc.csv'

export_csv_operator = core.operators.serialization.field_to_csv()
export_csv_operator.inputs.field_or_fields_container.connect(fc_out)
export_csv_operator.inputs.file_path.connect(file_path)
export_csv_operator.run()

Upload .csv result file

Let’s upload the simple_bar_fc.csv file on the server side. The upload_file_in_tmp_folder() method will be used here, because we assume we don’t know the server machine architecture. However, the upload_file() method can be used the same way will a know “server file path”.

server_file_path = core.upload_file_in_tmp_folder(file_path)
print(server_file_path)

# remove file to avoid polluting
os.remove(file_path)

Out:

C:\Users\VSSADM~1\AppData\Local\Temp\dataProcessingTemp4740\simple_bar_fc.csv

Download .csv result file

Let’s now download the simple_bar_fc.csv file.

downloaded_client_file_path = os.getcwd() + '\\simple_bar_fc_downloaded.csv'
core.download_file(server_file_path, downloaded_client_file_path)

Load .csv result file as operators input

Let’s now load the fields container contained in the .csv file.

my_data_sources = core.DataSources(downloaded_client_file_path)
import_csv_operator = core.operators.serialization.csv_to_field()
import_csv_operator.inputs.data_sources.connect(my_data_sources)
downloaded_fc_out = import_csv_operator.outputs.fields_container()
mesh.plot(downloaded_fc_out)

# remove file to avoid polluting
os.remove(downloaded_client_file_path)

Make operations over the imported fields container

This fields container can be used as it was introduced in the basics examples.

min_max_op = core.operators.min_max.min_max_fc()
min_max_op.inputs.fields_container.connect(downloaded_fc_out)
min_field = min_max_op.outputs.field_min()
min_field.data

Out:

array([[-8.202171e-07, -6.265107e-06, -2.444680e-05]])

Create your own entities to use dpf’s operators Bring Field’s data locally to improve performances