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femap-neutral-parser-0.9.0
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FEMAP neutral file parser
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | femap-neutral-parser-0.9.0 |
| نام | femap-neutral-parser |
| نسخه کتابخانه | 0.9.0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Nicolas Cordier |
| ایمیل نویسنده | nicolas.cordier@numeric-gmbh.ch |
| آدرس صفحه اصلی | https://framagit.org/numenic/femap_neutral_parser |
| آدرس اینترنتی | https://pypi.org/project/femap-neutral-parser/ |
| مجوز | MIT license |
====================
FEMAP neutral Parser
====================
FEMAP neutral file parser
* Free software: MIT license
Features and limitations
========================
Parse and render FEMAP neutral files. For now, three blocks are interpreted:
* Block 100 "Neutral File Header"
* Block 450 "Output Sets"
* Block 451 "Output Data Vectors"
Usage
=====
To use FEMAP neutral Parser in a project::
>>> from femap_neutral_parser import Parser
To instantiate a new parser, just pass a file path::
>>> neu = Parser("tests/data/mystran_00.NEU")
To have a list of available blocks::
>>> neu.available_blocks()
{'header': 100, 'output_sets': 450, '_output_vectors': 451}
Or maybe in a more human-friendly way is to use `info()` method, which prints
available results and outputs::
>>> neu.info()
<BLANKLINE>
Analysis
========
* subcase 1: Analyse. NASTRAN SPC 1 - lc1. test (MYSTRAN::Static)
* subcase 2: Analyse. NASTRAN SPC 1 - lc2. test (MYSTRAN::Static)
<BLANKLINE>
Outputs
=======
access to one of them using `._output_vectors[<title>][<SubcaseID>]['record']
<BLANKLINE>
* displacements::t_total -> RSS translation
* displacements::t1 -> T1 translation
* displacements::t2 -> T2 translation
* ...
* cbar_stress::min_comb_a -> BAR EndA Min Stress
* cbar_stress::min_comb_b -> BAR EndB Min Stress
Access available blocs by attribute::
>>> from pprint import pprint as pp
>>> pp(neu.output_sets)
{1: {'anal_type': 'Static',
'from_prog': 'Unknown',
'integer_format': None,
'notes': '',
'process_type': None,
'title': 'Analyse. NASTRAN SPC 1 - lc1. test',
'value': 0.0},
2: {'anal_type': 'Static',
'from_prog': 'Unknown',
'integer_format': None,
'notes': '',
'process_type': None,
'title': 'Analyse. NASTRAN SPC 1 - lc2. test',
'value': 0.0}}
Low-level data access
---------------------
Under the hood, output vectors (block451) are organized as nested dictionaries ``[<vector title>][<LCID>]``::
>>> pp(neu._output_vectors["displacements::t_total"][2])
{'abs_max': 2.578386,
'calc_warn': True,
'cent_total': True,
'comp_dir': 1,
'component_vec': [10002.0,
10003.0,
10004.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0],
'id_max': 7,
'id_min': 1,
'max_val': 2.578386,
'min_val': 0.0,
'record': array([( 1, 0.000000e+00), ( 2, 2.045391e-01), ( 3, 0.000000e+00),
( 4, 1.468270e-02), ( 5, 9.231050e-05), ( 6, 6.276400e-01),
( 7, 2.578386e+00), ( 8, 1.025100e-01), ( 9, 2.578363e+00),
(10, 1.916094e+00), (11, 1.100510e+00), (12, 2.389742e+00)],
dtype=[('NodeID', '<i8'), ('displacements::t_total', '<f8')]),
'vecID': 10001}
Aggregated Outputs
------------------
Slightly highest level than `_output_vectors` access, aggregated output is available using `Parser.vectors()` method. For example, to get all outputs for translations vectors::
>>> arr = neu.vectors(("displacements::t1", "displacements::t2", "displacements::t3"))
>>> arr
rec.array([( 1, 0. , 0., 0.000000e+00, 1),
( 2, -0.1870816 , 0., 0.000000e+00, 1),
...
(11, 0. , 0., -1.100510e+00, 2),
(12, 0. , 0., -2.389742e+00, 2)],
dtype=[('NodeID', '<i8'), ('displacements::t1', '<f8'), ('displacements::t2', '<f8'), ('displacements::t3', '<f8'), ('SubcaseID', '<i8')])
Returned value is a numpy structured array (`<https://numpy.org/doc/stable/user/basics.rec.html>`_). If Pandas is available, you can request to have a DataFrame instead::
>>> neu.vectors(("displacements::t1", "displacements::t2", "displacements::t3"), asdf=True)
displacements::t1 displacements::t2 displacements::t3
SubcaseID NodeID
1 1 0.000000 0.0 0.000000
2 -0.187082 0.0 0.000000
...
11 0.000000 0.0 -0.956073
12 0.000000 0.0 -1.602912
2 1 0.000000 0.0 0.000000
2 -0.204539 0.0 0.000000
...
11 0.000000 0.0 -1.100510
12 0.000000 0.0 -2.389742
You can also request sub-cases IDs, or request raw headers::
>>> neu.vectors(("displacements::t1", "displacements::t2", "displacements::t3"), asdf=True, raw=True,
... SubcaseIDs=2)
T1 translation T2 translation T3 translation
SubcaseID NodeID
2 1 0.000000 0.0 0.000000
2 -0.204539 0.0 0.000000
...
11 0.000000 0.0 -1.100510
12 0.000000 0.0 -2.389742
High-Level access
-----------------
At highest level, you can use the `get` method that already organize vectors for you::
>>> neu.get(what="displacements", asdf=True)
t1 t2 t3 r1 r2 r3
SubcaseID NodeID
1 1 0.000000 0.0 0.000000 -0.000432 0.008923 4.699029e-03
2 -0.187082 0.0 0.000000 0.000432 0.008923 4.666047e-03
...
2 1 0.000000 0.0 0.000000 -0.000007 0.009755 5.137517e-03
2 -0.204539 0.0 0.000000 0.000007 0.009755 5.101457e-03
...
11 0.000000 0.0 -1.100510 0.000000 0.010988 1.006013e-06
12 0.000000 0.0 -2.389742 0.000000 0.004149 1.360364e-08
One can get the list of high-level shortcuts using ``Parser.get_vectors()`` which
will return a ``set`` of available headers::
>>> neu.get_vectors() == {
... 'elem_gpf',
... 'force_vectors',
... 'displacements',
... 'summed_gpf',
... 'mpc_forces',
... 'constraint_gpf',
... 'cbar_force',
... 'cbar_stress',
... 'cbush_force',
... 'cbush_stress',
... 'cbar_ms',
... 'applied_gpf',
... 'spc_forces',
... 'cbeam_force'
... }
True
Requirements
============
Beside Python>=3.8, only `numpy` is required. `numpy` arrays are released as
`<https://numpy.org/doc/stable/user/basics.rec.html>`_, which makes conversions
to Pandas a breeze.
If Pandas is installed (which is advised), the `asdf` parameters are valid.
Testing
=======
For testing, making docs or coding, all the dev requirements are provided in `requirements_dev.txt`.
From a blank virtual environment, clone this repo::
git clone https://framagit.org/numenic/femap_neutral_parser.git
Create a Python virtual environment, and activate it::
python -m venv fnp
source fnp/bin/activate
Install requirements::
cd femap_neutral_parser
pip install -r requirements.txt # install numpy
pip install -r requirements_dev.txt
pip install -e . # install femap-neutral-parser in new venv
Now testing::
make test # or make coverage
Building docs::
make docs
History
=======
0.8.3 (2021-09-12)
------------------
Major internal refactoring
* ``output_vectors`` becomes internal (``_output_vectors``). The recommended ways to access data is now ``Parser.vectors()`` or ``Parser.get()`` at a higher level.
* no more ``autotranslate`` initialisation parameter. Everything is harmonized under the hood.
0.6.0 (2021-07-12)
------------------
* add engineering shortcuts
* harmonize NodeID and SubcaseID with ``pynastran``
* vectors are now case insensible
0.5.0 (2021-04-16)
------------------
* improve parsing speed on large files
0.4.0 (2021-04-16)
------------------
add:
* ``Parser.info()``
* ``Parser.vectors()``
0.3.0 (2021-04-16)
------------------
* add ``Parser.info()`` and ``Parser.vectors()``
* update documentation
* add info() ``doprint`` option
0.2.0 - 0.3.0 (2021-04-16)
--------------------------
* Update Documentation
0.1.0 (2021-03-24)
------------------
First release on PyPI.
نیازمندی
| مقدار | نام |
|---|---|
| - | pandas |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.8 | Python |
نحوه نصب
نصب پکیج whl femap-neutral-parser-0.9.0:
pip install femap-neutral-parser-0.9.0.whl
نصب پکیج tar.gz femap-neutral-parser-0.9.0:
pip install femap-neutral-parser-0.9.0.tar.gz