Note
Go to the end to download the full example code.
Field and field containers overview#
In DPF, the field is the main simulation data container. During a numerical simulation, the result data is defined by values associated to entities (scoping). These entities are a subset of a model (support).
Because the field data is always associated to its scoping and support, the field is a self-describing piece of data. A field is also defined by its parameters, such as dimensionality, unit, and location. For example, a field can describe any of the following:
Displacement vector
Norm, stress, or strain tensor
Stress or strain equivalent
Minimum or maximum over time of any result.
A field can be defined on a complete model or on only certain entities of the model based on its scoping. The data is stored as a vector of double values, and each elementary entity has a number of components. For example, a displacement has three components, and a symmetrical stress matrix has six components.
In DPF, a fields container is simply a collection of fields that can be indexed, just like a Python list. Operators applied to a fields container have each individual field operated on. Fields containers are outputs from operators.
# First, import necessary modules
import numpy as np
from ansys.dpf import core as dpf
from ansys.dpf.core import examples
Create a model object to establish a connection with an example result file and then extract:
model = dpf.Model(examples.find_static_rst())
print(model)
DPF Model
------------------------------
Static analysis
Unit system: MKS: m, kg, N, s, V, A, degC
Physics Type: Mechanical
Available results:
- displacement: Nodal Displacement
- 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:
81 nodes
8 elements
Unit: m
With solid (3D) elements
------------------------------
DPF Time/Freq Support:
Number of sets: 1
Cumulative Time (s) LoadStep Substep
1 1.000000 1 1
Create the displacement operator directly from the results
property and extract the displacement fields container:
disp_op = model.results.displacement()
fields = disp_op.outputs.fields_container()
print(fields)
DPF displacement(s)Fields Container
with 1 field(s)
defined on labels: time
with:
- field 0 {time: 1} with Nodal location, 3 components and 81 entities.
A field can be extracted from a fields container by simply indexing the requested field:
field = fields[0]
print(field)
DPF displacement_1.s Field
Location: Nodal
Unit: m
81 entities
Data: 3 components and 81 elementary data
Nodal
IDs data(m)
------------ ----------
1 -3.319046e-22 -6.935660e-09 -3.286174e-22
26 2.230265e-09 -7.142140e-09 -2.920779e-22
14 0.000000e+00 0.000000e+00 0.000000e+00
...
Extract data from a field#
You can extract all the data from a given field using the data
property. This returns a numpy array.
print(field.data)
[[-3.31904602e-22 -6.93565975e-09 -3.28617350e-22]
[ 2.23026491e-09 -7.14214033e-09 -2.92077883e-22]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[-3.01173895e-22 -7.14214033e-09 -2.23026491e-09]
[ 2.09077164e-09 -7.33058082e-09 -2.09077164e-09]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[ 1.06212713e-09 -6.89858785e-09 -3.77906905e-22]
[ 1.89019831e-09 -3.34398104e-09 1.43440783e-23]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[-2.71912713e-23 -2.92690969e-09 -2.33676924e-23]
[ 1.01364486e-09 -7.10540890e-09 -2.14726184e-09]
[ 1.89155604e-09 -3.73823999e-09 -1.89155604e-09]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[ 7.64096553e-24 -3.34398104e-09 -1.89019831e-09]
[-3.81104389e-22 -6.89858785e-09 -1.06212713e-09]
[ 2.14726184e-09 -7.10540890e-09 -1.01364486e-09]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[-9.53485079e-23 -7.14214033e-09 2.23026491e-09]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[ 2.09077164e-09 -7.33058082e-09 2.09077164e-09]
[ 1.18477336e-22 -3.34398104e-09 1.89019831e-09]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[ 1.89155604e-09 -3.73823999e-09 1.89155604e-09]
[ 1.01364486e-09 -7.10540890e-09 2.14726184e-09]
[-2.61320844e-22 -6.89858785e-09 1.06212713e-09]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[ 2.14726184e-09 -7.10540890e-09 1.01364486e-09]
[-1.54190337e-21 -1.42766633e-08 -1.53720678e-21]
[ 2.25103522e-09 -1.43688328e-08 -1.55960665e-21]
[-1.55180700e-21 -1.43688328e-08 -2.25103522e-09]
[ 2.25860708e-09 -1.44669483e-08 -2.25860708e-09]
[-1.02704768e-21 -1.05919802e-08 -1.01743770e-21]
[ 1.16452955e-09 -1.44002311e-08 -1.52834607e-21]
[ 2.29356739e-09 -1.07400000e-08 -1.07537743e-21]
[-1.08050063e-21 -1.07400000e-08 -2.29356739e-09]
[ 1.16046741e-09 -1.44722939e-08 -2.25762828e-09]
[ 2.26430754e-09 -1.08989140e-08 -2.26430754e-09]
[-1.50544246e-21 -1.44002311e-08 -1.16452955e-09]
[ 2.25762828e-09 -1.44722939e-08 -1.16046741e-09]
[ 2.25860708e-09 -1.44669483e-08 2.25860708e-09]
[-1.24684037e-21 -1.43688328e-08 2.25103522e-09]
[ 2.26430754e-09 -1.08989140e-08 2.26430754e-09]
[ 1.16046741e-09 -1.44722939e-08 2.25762828e-09]
[-8.03413897e-22 -1.07400000e-08 2.29356739e-09]
[ 2.25762828e-09 -1.44722939e-08 1.16046741e-09]
[-1.35051199e-21 -1.44002311e-08 1.16452955e-09]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[-2.23026491e-09 -7.14214033e-09 -9.66448574e-23]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[-2.09077164e-09 -7.33058082e-09 -2.09077164e-09]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[-1.89019831e-09 -3.34398104e-09 1.19096032e-22]
[-1.06212713e-09 -6.89858785e-09 -2.59300974e-22]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[-1.89155604e-09 -3.73823999e-09 -1.89155604e-09]
[-1.01364486e-09 -7.10540890e-09 -2.14726184e-09]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[-2.14726184e-09 -7.10540890e-09 -1.01364486e-09]
[-2.09077164e-09 -7.33058082e-09 2.09077164e-09]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[-1.01364486e-09 -7.10540890e-09 2.14726184e-09]
[-1.89155604e-09 -3.73823999e-09 1.89155604e-09]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[-2.14726184e-09 -7.10540890e-09 1.01364486e-09]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[-2.25103522e-09 -1.43688328e-08 -1.20291800e-21]
[-2.25860708e-09 -1.44669483e-08 -2.25860708e-09]
[-2.29356739e-09 -1.07400000e-08 -7.91446544e-22]
[-1.16452955e-09 -1.44002311e-08 -1.32988359e-21]
[-2.26430754e-09 -1.08989140e-08 -2.26430754e-09]
[-1.16046741e-09 -1.44722939e-08 -2.25762828e-09]
[-2.25762828e-09 -1.44722939e-08 -1.16046741e-09]
[-2.25860708e-09 -1.44669483e-08 2.25860708e-09]
[-1.16046741e-09 -1.44722939e-08 2.25762828e-09]
[-2.26430754e-09 -1.08989140e-08 2.26430754e-09]
[-2.25762828e-09 -1.44722939e-08 1.16046741e-09]]
While it might seem preferable to work entirely within numpy,
DPF runs outside of Python and potentially even on a
remote machine. Therefore, the transfer of unnecessary data between
the DPF instance and the Python client leads to inefficient
operations on large models. Instead, you should use DPF operators to
assemble the necessary data before recalling the data from DPF.
For example, if you want the maximum displacement for a given result, use the min/max operator:
min_max_op = dpf.operators.min_max.min_max(field)
print(min_max_op.outputs.field_max().data)
# Out of conveience, you can simply take the max of the field with:
print(field.max().data)
# The above yields a result identical to:
print(np.max(field.data, axis=0))
[2.29356739e-09 0.00000000e+00 2.29356739e-09]
[2.29356739e-09 0.00000000e+00 2.29356739e-09]
[2.29356739e-09 0.00000000e+00 2.29356739e-09]
Note that the numpy array does not retain any information about the
field it describes. Using the DPF max operator of the field does
retain this information.
max_field = field.max()
print(max_field)
DPF displacement_1.s Field
Location: Nodal
Unit: m
3 entities
Data: 1 components and 3 elementary data
IDs data(m)
------------ ----------
75 2.293567e-09
66 0.000000e+00
40 2.293567e-09
Total running time of the script: (0 minutes 0.047 seconds)