Export data contained in a DataFrame to a new format

In this script a static simulation is used as an example to show how to export data from a DataFrame to another format.

Perform required imports

Perform required imports. # This example uses a supplied file that you can get by importing the DPF examples package.

from ansys.dpf import post
from ansys.dpf.post import examples

Get Simulation object

Get the Simulation object that allows access to the result. The Simulation object must be instantiated with the path for the result file. For example, "C:/Users/user/my_result.rst" on Windows or "/home/user/my_result.rst" on Linux.

example_path = examples.download_crankshaft()
# to automatically detect the simulation type, use:
simulation = post.load_simulation(example_path)

# to enable auto-completion, use the equivalent:
simulation = post.StaticMechanicalSimulation(example_path)

# print the simulation to get an overview of what's available
print(simulation)

Static Mechanical Simulation.


Data Sources
------------------------------
/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/ansys/dpf/core/examples/result_files/crankshaft/crankshaft.rst

DPF Model
------------------------------
Static analysis
Unit system: MKS: m, kg, N, s, V, A, degC
Physics Type: Mechanical
Available results:
     -  displacement: Nodal Displacement
     -  velocity: Nodal Velocity
     -  acceleration: Nodal Acceleration
     -  reaction_force: Nodal Force
     -  stress: ElementalNodal Stress
     -  elemental_volume: Elemental Volume
     -  stiffness_matrix_energy: Elemental Energy-stiffness matrix
     -  artificial_hourglass_energy: Elemental Hourglass Energy
     -  thermal_dissipation_energy: Elemental thermal dissipation energy
     -  kinetic_energy: Elemental Kinetic Energy
     -  co_energy: Elemental co-energy
     -  incremental_energy: Elemental incremental energy
     -  elastic_strain: ElementalNodal Strain
     -  element_euler_angles: ElementalNodal Element Euler Angles
     -  structural_temperature: ElementalNodal Structural temperature
------------------------------
DPF  Meshed Region:
  69762 nodes
  39315 elements
  Unit: m
  With solid (3D) elements
------------------------------
DPF  Time/Freq Support:
  Number of sets: 3
Cumulative     Time (s)       LoadStep       Substep
1              1.000000       1              1
2              2.000000       1              2
3              3.000000       1              3

Extract elemental nodal stress

stress = simulation.stress_nodal(all_sets=True)
print(stress)

            results      S (Pa)
            set_ids           1           2           3
node_ids components
    4872         XX  1.8630e+05 -2.6097e+05 -1.4740e+06
                 YY  8.2844e+06  2.8386e+07  5.9846e+07
                 ZZ -1.3700e+07 -7.9701e+06  1.7550e+07
                 XY  5.9991e+05  6.6079e+05 -7.5702e+05
                 YZ -1.9344e+08 -3.8683e+08 -5.7889e+08
                 XZ -6.2727e+06 -2.8690e+06  1.0085e+07
     ...        ...         ...         ...         ...

Export to a numpy.ndarray

# To export to a numpy.ndarray, the DataFrame must contain data only for a single combination
# of values for column labels.

# select one step as our dataframe contains data for several
stress_1 = stress.select(set_ids=1)
print(stress_1)

# export it as a numpy.ndarray
stress_1_array = stress_1.array
print(stress_1_array)

             results      S (Pa)
             set_ids           1
 node_ids components
     4872         XX  1.8630e+05
                  YY  8.2844e+06
                  ZZ -1.3700e+07
                  XY  5.9991e+05
                  YZ -1.9344e+08
                  XZ -6.2727e+06
      ...        ...         ...

[[ 1.86304666e+05  8.28436396e+06 -1.37003496e+07  5.99907420e+05
  -1.93439042e+08 -6.27268473e+06]
 [-4.26076223e+05  4.27353118e+06  3.61489620e+05  1.27870163e+07
  -1.64836014e+08  3.78081724e+05]
 [ 4.36222667e+06  2.02005176e+07  3.49514000e+07  5.31671006e+07
  -1.69700130e+08  4.16285682e+06]
 ...
 [ 2.43008628e+06  3.45306104e+05 -6.96869804e+07 -1.88974926e+06
   1.78308703e+08  3.70653393e+07]
 [-3.15639127e+06 -4.87652891e+07 -1.52290762e+08  3.59354599e+07
   1.97891422e+08  2.65947999e+07]
 [ 6.32054643e+05 -3.24065639e+07 -1.18464495e+08  4.38019212e+07
   2.00763823e+08  2.51322083e+07]]