Import a result file in DPF#

MAPDL LS-DYNA FLUENT CFX

This tutorial shows how to import a result file in DPF.

There are two approaches to import a result file in DPF:

Using the DataSources object
Using the Model object

Note

The |Model| extracts a large amount of information by default (results, mesh and analysis data). If using this helper takes a long time for processing the code, mind using a |DataSources| object and instantiating operators directly with it.

Download tutorial as Python script Download tutorial as Jupyter notebook

Define the result file path#

Both approaches need a file path to be defined. For this tutorial, you can use a result file available in the |Examples| module.

MAPDL

# Import the ``ansys.dpf.core`` module
from ansys.dpf import core as dpf
# Import the examples module
from ansys.dpf.core import examples
# Import the operators module
from ansys.dpf.core import operators as ops

# Define the .rst result file path
result_file_path_11 = examples.find_static_rst()

# Define the modal superposition harmonic analysis (.mode, .rfrq and .rst) result files paths
result_file_path_12 = examples.download_msup_files_to_dict()


# Print the result files paths
print("Result file path 11:", "\n",result_file_path_11, "\n")
print("Result files paths 12:", "\n",result_file_path_12, "\n")

Result file path 11: 
 D:\a\pydpf-core\pydpf-core\.tox\doc-html\Lib\site-packages\ansys\dpf\core\examples\result_files\static.rst 

Result files paths 12: 
 {'rfrq': 'D:\\a\\pydpf-core\\pydpf-core\\.tox\\doc-html\\Lib\\site-packages\\ansys\\dpf\\core\\examples\\result_files\\msup\\file.rfrq', 'mode': 'D:\\a\\pydpf-core\\pydpf-core\\.tox\\doc-html\\Lib\\site-packages\\ansys\\dpf\\core\\examples\\result_files\\msup\\file.mode', 'rst': 'D:\\a\\pydpf-core\\pydpf-core\\.tox\\doc-html\\Lib\\site-packages\\ansys\\dpf\\core\\examples\\result_files\\msup\\file.rst'} 

LSDYNA

# Import the ``ansys.dpf.core`` module
from ansys.dpf import core as dpf
# Import the examples module
from ansys.dpf.core import examples
# Import the operators module
from ansys.dpf.core import operators as ops

# Define the .d3plot result files paths
result_file_path_21 = examples.download_d3plot_beam()

# Define the .binout result file path
result_file_path_22 = examples.download_binout_matsum()

# Print the result files paths
print("Result files paths 21:", "\n",result_file_path_21, "\n")
print("Result file path 22:", "\n",result_file_path_22, "\n")

Result files paths 21: 
 ['D:\\a\\pydpf-core\\pydpf-core\\.tox\\doc-html\\Lib\\site-packages\\ansys\\dpf\\core\\examples\\result_files\\d3plot_beam\\d3plot', 'D:\\a\\pydpf-core\\pydpf-core\\.tox\\doc-html\\Lib\\site-packages\\ansys\\dpf\\core\\examples\\result_files\\d3plot_beam\\d3plot01', 'D:\\a\\pydpf-core\\pydpf-core\\.tox\\doc-html\\Lib\\site-packages\\ansys\\dpf\\core\\examples\\result_files\\d3plot_beam\\d3plot02', 'D:\\a\\pydpf-core\\pydpf-core\\.tox\\doc-html\\Lib\\site-packages\\ansys\\dpf\\core\\examples\\result_files\\d3plot_beam\\file.actunits'] 

Result file path 22: 
 D:\a\pydpf-core\pydpf-core\.tox\doc-html\Lib\site-packages\ansys\dpf\core\examples\result_files\binout\binout_matsum 

Fluent

# Import the ``ansys.dpf.core`` module
from ansys.dpf import core as dpf
# Import the examples module
from ansys.dpf.core import examples
# Import the operators module
from ansys.dpf.core import operators as ops

# Define the project .flprj result file path
result_file_path_31 = examples.download_fluent_axial_comp()["flprj"]

# Define the CFF .cas.h5/.dat.h5 result files paths
result_file_path_32 = examples.download_fluent_axial_comp()

# Print the result files paths
print("Result file path 31:", "\n",result_file_path_31, "\n")
print("Result files paths 32:", "\n",result_file_path_32, "\n")

Result file path 31: 
 D:\a\pydpf-core\pydpf-core\.tox\doc-html\Lib\site-packages\ansys\dpf\core\examples\result_files\fluent-axial_comp\axial_comp_reduced.flprj 

Result files paths 32: 
 {'flprj': 'D:\\a\\pydpf-core\\pydpf-core\\.tox\\doc-html\\Lib\\site-packages\\ansys\\dpf\\core\\examples\\result_files\\fluent-axial_comp\\axial_comp_reduced.flprj', 'cas': ['D:\\a\\pydpf-core\\pydpf-core\\.tox\\doc-html\\Lib\\site-packages\\ansys\\dpf\\core\\examples\\result_files\\fluent-axial_comp\\axial_comp-1-01438.cas.h5', 'D:\\a\\pydpf-core\\pydpf-core\\.tox\\doc-html\\Lib\\site-packages\\ansys\\dpf\\core\\examples\\result_files\\fluent-axial_comp\\axial_comp-1-01439.cas.h5', 'D:\\a\\pydpf-core\\pydpf-core\\.tox\\doc-html\\Lib\\site-packages\\ansys\\dpf\\core\\examples\\result_files\\fluent-axial_comp\\axial_comp-1-01440.cas.h5'], 'dat': ['D:\\a\\pydpf-core\\pydpf-core\\.tox\\doc-html\\Lib\\site-packages\\ansys\\dpf\\core\\examples\\result_files\\fluent-axial_comp\\axial_comp-1-01438.dat.h5', 'D:\\a\\pydpf-core\\pydpf-core\\.tox\\doc-html\\Lib\\site-packages\\ansys\\dpf\\core\\examples\\result_files\\fluent-axial_comp\\axial_comp-1-01439.dat.h5', 'D:\\a\\pydpf-core\\pydpf-core\\.tox\\doc-html\\Lib\\site-packages\\ansys\\dpf\\core\\examples\\result_files\\fluent-axial_comp\\axial_comp-1-01440.dat.h5']} 

CFX

# Import the ``ansys.dpf.core`` module
from ansys.dpf import core as dpf
# Import the examples module
from ansys.dpf.core import examples
# Import the operators module
from ansys.dpf.core import operators as ops

# Define the project .res result file path
result_file_path_41 = examples.download_cfx_mixing_elbow()

# Define the CFF .cas.cff/.dat.cff result files paths
result_file_path_42 = examples.download_cfx_heating_coil()

# Print the result files paths
print("Result file path 41:", "\n",result_file_path_41, "\n")
print("Result files paths 42:", "\n",result_file_path_42, "\n")

Result file path 41: 
 D:\a\pydpf-core\pydpf-core\.tox\doc-html\Lib\site-packages\ansys\dpf\core\examples\result_files\cfx-mixing_elbow\InjectMixer.res 

Result files paths 42: 
 {'cas': 'D:\\a\\pydpf-core\\pydpf-core\\.tox\\doc-html\\Lib\\site-packages\\ansys\\dpf\\core\\examples\\result_files\\cfx-heating_coil\\def.cas.cff', 'dat': 'D:\\a\\pydpf-core\\pydpf-core\\.tox\\doc-html\\Lib\\site-packages\\ansys\\dpf\\core\\examples\\result_files\\cfx-heating_coil\\def.dat.cff'} 

Use a |DataSources|#

The |DataSources| object manages paths to their files. Use this object to declare data inputs for PyDPF-Core APIs.

MAPDL

a) `.rst` result file

Create the |DataSources| object and give the path to the result file to the ‘result_path’ argument.

# Create the DataSources object
# Use the ``result_path`` argument and give the result file path
ds_11 = dpf.DataSources(result_path=result_file_path_11)

b) `.mode`, `.rfrq` and `.rst` result files

In the modal superposition, modal coefficients are multiplied by mode shapes (of a previous modal analysis) to analyse a structure under given boundary conditions in a range of frequencies. Doing this expansion “on demand” in DPF instead of in the solver reduces the size of the result files.

The expansion is recursive in DPF: first the modal response is read. Then, upstream mode shapes are found in the |DataSources|, where they are read and expanded. Upstream refers to a source that provides data to a particular process.

To create a recursive workflow add the upstream |DataSources| object, that contains the upstream data files, to the main |DataSources| object.

# Create the main DataSources object
ds_12 = dpf.DataSources()
# Define the main result file path
ds_12.set_result_file_path(filepath=result_file_path_12["rfrq"], key='rfrq')

# Create the upstream DataSources object with the main upstream file path
upstream_ds_12 = dpf.DataSources(result_path=result_file_path_12["mode"])
# Add the additional upstream file path to the upstream DataSources object
upstream_ds_12.add_file_path(filepath=result_file_path_12["rst"])

# Add the upstream DataSources to the main DataSources object
ds_12.add_upstream(upstream_data_sources=upstream_ds_12)

LSDYNA

a) `.d3plot` result file

The d3plot file does not contain information related to units. In this case, as the simulation was run through Mechanical, a file.actunits file is produced. If this file is supplemented in the |DataSources|, the units will be correctly fetched for all results in the file as well as for the mesh.

Thus, we must use the set_result_file_path() and the add_file_path() methods to add the main and the additional result file to the |DataSources| object.

# Create the DataSources object
ds_21 = dpf.DataSources()

# Define the main result file path
ds_21.set_result_file_path(filepath=result_file_path_21[0], key="d3plot")

# Add the additional file path related to the units
ds_21.add_file_path(filepath=result_file_path_21[3], key="actunits")

b) `.binout` result file

The extension key `.binout` is not explicitly specified in the result file. Thus, we use the set_result_file_path() method and give the extension key to the ‘key’ argument to correctly add the result file path to the |DataSources| object.

# Create the DataSources object
ds_22 = dpf.DataSources()

# Define the path to the result file
# Use the ``key`` argument and give the file extension key
ds_22.set_result_file_path(filepath=result_file_path_22, key="binout")

Fluent

a) `.flprj` result file

Create the |DataSources| object and give the path to the result file to the ‘result_path’ argument.

# Create the DataSources object
# Use the ``result_path`` argument and give the result file path
ds_31 = dpf.DataSources(result_path=result_file_path_31)

b) `.cas.h5`, `.dat.h5` result files

Here, we have a main and an additional result file with two extensions keys.

Thus, you must use the set_result_file_path() and the add_file_path() methods to add the main and additional result file to the |DataSources| object and explicitly give the first extension key to their ‘key’ argument.

# Create the DataSources object
ds_32 = dpf.DataSources()

# Define the path to the main result file
# Use the ``key`` argument and give the first extension key
ds_32.set_result_file_path(filepath=result_file_path_32['cas'][0], key="cas")

# Add the additional result file path to the DataSources
# Use the ``key`` argument and give the first extension key
ds_32.add_file_path(filepath=result_file_path_32['dat'][0], key="dat")

CFX

a) `.res` result file

Create the |DataSources| object and give the path to the result file to the ‘result_path’ argument.

# Create the DataSources object
# Use the ``result_path`` argument and give the result file path
ds_41 = dpf.DataSources(result_path=result_file_path_41)

b) `.cas.cff`, `.dat.cff` result files

Here, we have a main and an additional result file with two extensions keys.

Thus, you must use the set_result_file_path() and the add_file_path() methods to add the main and additional result file to the |DataSources| object. Also, you must explicitly give the first extension keys to the ‘key’ argument.

# Create the DataSources object
ds_42 = dpf.DataSources()

# Define the path to the main result file
# Use the ``key`` argument and give the first extension key
ds_42.set_result_file_path(filepath=result_file_path_42["cas"], key="cas")

# Add the additional result file path to the DataSources
# Use the ``key`` argument and give the first extension key
ds_42.add_file_path(filepath=result_file_path_42["dat"], key="dat")

Use a |Model|#

The Model class creates and evaluates common readers for the files it is given, such as a mesh provider, a result info provider, and a streams provider. It provides dynamically built methods to extract the results available in the files, as well as many shortcuts to facilitate exploration of the available data.

To create a |Model| you can provide to the ‘data_sources’ argument.:

The result file path, in the case you are working with a single result file that has an explicit extension key;
A |DataSources| object.

MAPDL

a) `.rst` result file

# Create the model with the result file path
model_11 = dpf.Model(data_sources=result_file_path_11)

# Create the model with the DataSources object
model_12 = dpf.Model(data_sources=ds_11)

b) `.mode`, `.rfrq` and `.rst` result files

# Create the model with the DataSources object
model_13 = dpf.Model(data_sources=ds_12)

LSDYNA

a) `.d3plot` result file

# Create the model with the DataSources object
model_21 = dpf.Model(data_sources=ds_21)

b) `.binout` result file

# Create the model with the DataSources object
model_22 = dpf.Model(data_sources=ds_22)

Fluent

a) `.flprj` result file

# Create the model with the result file path
model_31 = dpf.Model(data_sources=result_file_path_31)

# Create the model with the DataSources object
model_32 = dpf.Model(data_sources=ds_31)

b) `.cas.h5`, `.dat.h5` result files

# Create the model with the DataSources object
model_33 = dpf.Model(data_sources=ds_32)

CFX

a) `.res` result file

# Create the model with the result file path
model_41 = dpf.Model(data_sources=result_file_path_41)

# Create the model with the DataSources object
model_42 = dpf.Model(data_sources=ds_41)

b) `.cas.cff`, `.dat.cff` result files

# Create the model with the DataSources object
model_43 = dpf.Model(data_sources=ds_42)