Extract and explore results metadata

MAPDL LS-DYNA FLUENT CFX

This tutorial shows how to extract and explore results metadata from a result file.

Get the result file

Import a result file. For this tutorial, use one available in the examples module. For more information about how to import your own result file in DPF, see the Import a result file in DPF tutorial.

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

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

# Define the result file path
result_file_path_1 = examples.download_transient_result()

# Create the model
model_1 = dpf.Model(data_sources=result_file_path_1)

Explore the results general metadata

Use the ResultInfo object and its methods to explore the general results metadata before extracting results. This metadata includes:

• Analysis type

• Physics type

• Number of results

• Unit system

• Solver version, date, and time

• Job name

result_info_1 = model_1.metadata.result_info

# Get the analysis type
analysis_type = result_info_1.analysis_type
print("Analysis type: ", analysis_type, "\n")

# Get the physics type
physics_type = result_info_1.physics_type
print("Physics type: ", physics_type, "\n")

# Get the number of available results
number_of_results = result_info_1.n_results
print("Number of available results: ", number_of_results, "\n")

# Get the unit system
unit_system = result_info_1.unit_system
print("Unit system: ", unit_system, "\n")

# Get the solver version, date, and time
solver_version = result_info_1.solver_version
solver_date = result_info_1.solver_date
solver_time = result_info_1.solver_time
print("Solver version: ", solver_version, "\n")
print("Solver date: ", solver_date, "\n")
print("Solver time: ", solver_time, "\n")

# Get the job name
job_name = result_info_1.job_name
print("Job name: ", job_name, "\n")

Analysis type:  static

Physics type:  mechanical

Number of available results:  21

Unit system:  MKS: m, kg, N, s, V, A, degC

Solver version:  17.0

Solver date:  20150331

Solver time:  93417

Job name:  cp55

Explore a result’s metadata

When you extract a result from a result file, DPF stores it in a Field. This Field contains metadata describing the result, including:

• Location

• Scoping (type and quantity of entities)

• Elementary data count (number of entities, i.e. how many data vectors)

• Components count (vectors dimension)

• Shape of the stored data (tuple of elementary data count and components count)

• Fields size (length of the entire data vector)

• Units of the data

Extract the displacement results.

disp_results = model_1.results.displacement.eval()
disp_field = disp_results[0]

Explore the displacement results metadata.

# Get the location of the displacement data
location = disp_field.location
print("Location: ", location, "\n")

# Get the displacement Field scoping
scoping = disp_field.scoping
print("Scoping: ", "\n", scoping, "\n")

# Get the displacement Field scoping ids
scoping_ids = disp_field.scoping.ids
print("Scoping ids: ", scoping_ids, "\n")

# Get the displacement Field elementary data count
elementary_data_count = disp_field.elementary_data_count
print("Elementary data count: ", elementary_data_count, "\n")

# Get the displacement Field components count
components_count = disp_field.component_count
print("Components count: ", components_count, "\n")

# Get the displacement Field size
field_size = disp_field.size
print("Size: ", field_size, "\n")

# Get the displacement Field shape
shape = disp_field.shape
print("Shape: ", shape, "\n")

# Get the displacement Field unit
unit = disp_field.unit
print("Unit: ", unit, "\n")

Location:  Nodal

Scoping:
 DPF  Scoping:
  with Nodal location and 3820 entities


Scoping ids:  [ 525  534  533 ... 3469 3817 3825]

Elementary data count:  3820

Components count:  3

Size:  11460

Shape:  (3820, 3)

Unit:  m