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test_commands.py
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test_commands.py
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# Copyright (C) 2016 - 2024 ANSYS, Inc. and/or its affiliates.
# SPDX-License-Identifier: MIT
#
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
import inspect
import numpy as np
import pytest
from ansys.mapdl.core import examples
from ansys.mapdl.core.commands import (
CMD_BC_LISTING,
CMD_LISTING,
BoundaryConditionsListingOutput,
CommandListingOutput,
CommandOutput,
Commands,
StringWithLiteralRepr,
)
from ansys.mapdl.core.examples import verif_files
from conftest import has_dependency, requires
if has_dependency("pandas"):
import pandas as pd
LIST_OF_INQUIRE_FUNCTIONS = [
"ndinqr",
"elmiqr",
"kpinqr",
"lsinqr",
"arinqr",
"vlinqr",
"rlinqr",
"gapiqr",
"masiqr",
"ceinqr",
"cpinqr",
"csyiqr",
"etyiqr",
"foriqr",
"sectinqr",
"mpinqr",
"dget",
"fget",
"erinqr",
]
# Generic args
ARGS_INQ_FUNC = {
"node": 1,
"key": 0,
"ielem": 1,
"knmi": 1,
"line": 1,
"anmi": 1,
"vnmi": 1,
"nreal": 1,
"ngap": 1,
"nce": 1,
"ncp": 1,
"ncsy": 1,
"itype": 1,
"nsect": 1,
"mat": 1,
"iprop": 1,
"idf": 1,
"kcmplx": 1,
}
set_list_0 = """***** INDEX OF DATA SETS ON RESULTS FILE *****
SET TIME/FREQ LOAD STEP SUBSTEP CUMULATIVE
1 0.20000 1 1 3
2 0.40000 1 2 5
3 0.70000 1 3 7
4 1.0000 1 4 9"""
set_list_1 = """***** INDEX OF DATA SETS ON RESULTS FILE *****
SET TIME/FREQ LOAD STEP SUBSTEP CUMULATIVE
1 0.10000E-02 1 10 10
2 0.20000E-02 2 1 11
3 0.30000E-02 2 2 12
4 0.40000E-02 2 3 13
5 0.50000E-02 2 4 14
6 0.60000E-02 2 5 15
"""
PRNSOL_OUT = """PRINT F REACTION SOLUTIONS PER NODE
1 0.1287512532E+008 0.4266737217E+007
2 -0.1512012179E+007 0.2247558576E+007
3 -0.7065315064E+007 -0.4038004530E+007
4 -0.4297798077E+007 -0.2476291263E+007"""
PRNSOL_OUT_LONG = """PRINT F REACTION SOLUTIONS PER NODE
*** ANSYS - ENGINEERING ANALYSIS SYSTEM RELEASE 2021 R2 21.2 ***
DISTRIBUTED Ansys Mechanical Enterprise
00000000 VERSION=LINUX x64 15:56:42 JAN 13, 2022 CP= 0.665
***** POST1 TOTAL REACTION SOLUTION LISTING *****
LOAD STEP= 1 SUBSTEP= 1
TIME= 1.0000 LOAD CASE= 0
THE FOLLOWING X,Y,Z SOLUTIONS ARE IN THE GLOBAL COORDINATE SYSTEM
NODE FX FY
1 0.12875E+008 0.42667E+007
2 -0.15120E+007 0.22476E+007
3 -0.70653E+007-0.40380E+007
4 -0.42978E+007-0.24763E+007
TOTAL VALUES
VALUE -0.37253E-008 0.46566E-009
"""
DLIST_RESULT = [
["1", "UX", "0.00000000", "0.00000000"],
["1", "UY", "0.00000000", "0.00000000"],
["1", "UZ", "0.00000000", "0.00000000"],
["1", "TEMP", "300.000000", "0.00000000"],
["2", "UX", "0.00000000", "0.00000000"],
["2", "UY", "0.00000000", "0.00000000"],
["2", "UZ", "0.00000000", "0.00000000"],
["2", "TEMP", "300.000000", "0.00000000"],
["3", "UX", "0.00000000", "0.00000000"],
["3", "UY", "0.00000000", "0.00000000"],
["3", "UZ", "0.00000000", "0.00000000"],
["3", "TEMP", "300.000000", "0.00000000"],
["4", "UX", "0.00000000", "0.00000000"],
["4", "UY", "0.00000000", "0.00000000"],
["4", "UZ", "0.00000000", "0.00000000"],
["4", "TEMP", "300.000000", "0.00000000"],
["5", "UX", "0.00000000", "0.00000000"],
["5", "UY", "0.00000000", "0.00000000"],
["5", "UZ", "0.00000000", "0.00000000"],
["5", "TEMP", "300.000000", "0.00000000"],
["6", "UX", "0.00000000", "0.00000000"],
["6", "UY", "0.00000000", "0.00000000"],
["6", "UZ", "0.00000000", "0.00000000"],
["6", "TEMP", "300.000000", "0.00000000"],
["7", "UX", "0.00000000", "0.00000000"],
["7", "UY", "0.00000000", "0.00000000"],
["7", "UZ", "0.00000000", "0.00000000"],
["7", "TEMP", "300.000000", "0.00000000"],
["8", "UX", "0.00000000", "0.00000000"],
["8", "UY", "0.00000000", "0.00000000"],
["8", "UZ", "0.00000000", "0.00000000"],
["8", "TEMP", "300.000000", "0.00000000"],
["9", "UX", "0.00000000", "0.00000000"],
["9", "UY", "0.00000000", "0.00000000"],
["9", "UZ", "0.00000000", "0.00000000"],
["9", "TEMP", "300.000000", "0.00000000"],
["10", "UX", "0.00000000", "0.00000000"],
["10", "UY", "0.00000000", "0.00000000"],
["10", "UZ", "0.00000000", "0.00000000"],
["10", "TEMP", "300.000000", "0.00000000"],
["11", "UX", "0.00000000", "0.00000000"],
["11", "UY", "0.00000000", "0.00000000"],
["11", "UZ", "0.00000000", "0.00000000"],
["11", "TEMP", "300.000000", "0.00000000"],
["12", "UX", "0.00000000", "0.00000000"],
["12", "UY", "0.00000000", "0.00000000"],
["12", "UZ", "0.00000000", "0.00000000"],
["12", "TEMP", "300.000000", "0.00000000"],
["13", "UX", "0.00000000", "0.00000000"],
["13", "UY", "0.00000000", "0.00000000"],
["13", "UZ", "0.00000000", "0.00000000"],
["13", "TEMP", "300.000000", "0.00000000"],
["146", "UX", "0.00000000", "0.00000000"],
["146", "UY", "0.00000000", "0.00000000"],
["146", "UZ", "0.00000000", "0.00000000"],
["146", "TEMP", "300.000000", "0.00000000"],
["158", "UX", "0.00000000", "0.00000000"],
["158", "UY", "0.00000000", "0.00000000"],
["158", "UZ", "0.00000000", "0.00000000"],
["158", "TEMP", "300.000000", "0.00000000"],
["159", "UX", "0.00000000", "0.00000000"],
["159", "UY", "0.00000000", "0.00000000"],
["159", "UZ", "0.00000000", "0.00000000"],
["159", "TEMP", "300.000000", "0.00000000"],
["160", "UX", "0.00000000", "0.00000000"],
["160", "UY", "0.00000000", "0.00000000"],
["160", "UZ", "0.00000000", "0.00000000"],
["160", "TEMP", "300.000000", "0.00000000"],
["161", "UX", "0.00000000", "0.00000000"],
["161", "UY", "0.00000000", "0.00000000"],
["161", "UZ", "0.00000000", "0.00000000"],
["161", "TEMP", "300.000000", "0.00000000"],
["162", "UX", "0.00000000", "0.00000000"],
["162", "UY", "0.00000000", "0.00000000"],
["162", "UZ", "0.00000000", "0.00000000"],
["162", "TEMP", "300.000000", "0.00000000"],
["163", "UX", "0.00000000", "0.00000000"],
["163", "UY", "0.00000000", "0.00000000"],
["163", "UZ", "0.00000000", "0.00000000"],
["163", "TEMP", "300.000000", "0.00000000"],
["164", "UX", "0.00000000", "0.00000000"],
["164", "UY", "0.00000000", "0.00000000"],
["164", "UZ", "0.00000000", "0.00000000"],
["164", "TEMP", "300.000000", "0.00000000"],
["165", "UX", "0.00000000", "0.00000000"],
["165", "UY", "0.00000000", "0.00000000"],
["165", "UZ", "0.00000000", "0.00000000"],
["165", "TEMP", "300.000000", "0.00000000"],
["166", "UX", "0.00000000", "0.00000000"],
["166", "UY", "0.00000000", "0.00000000"],
["166", "UZ", "0.00000000", "0.00000000"],
["166", "TEMP", "300.000000", "0.00000000"],
["167", "UX", "0.00000000", "0.00000000"],
["167", "UY", "0.00000000", "0.00000000"],
["167", "UZ", "0.00000000", "0.00000000"],
["167", "TEMP", "300.000000", "0.00000000"],
["168", "UX", "0.00000000", "0.00000000"],
["168", "UY", "0.00000000", "0.00000000"],
["168", "UZ", "0.00000000", "0.00000000"],
["168", "TEMP", "300.000000", "0.00000000"],
["169", "UX", "0.00000000", "0.00000000"],
["169", "UY", "0.00000000", "0.00000000"],
["169", "UZ", "0.00000000", "0.00000000"],
["169", "TEMP", "300.000000", "0.00000000"],
["171", "UX", "0.00000000", "0.00000000"],
["171", "UY", "0.00000000", "0.00000000"],
["171", "UZ", "0.00000000", "0.00000000"],
["171", "TEMP", "300.000000", "0.00000000"],
["172", "UX", "0.00000000", "0.00000000"],
["172", "UY", "0.00000000", "0.00000000"],
["172", "UZ", "0.00000000", "0.00000000"],
["172", "TEMP", "300.000000", "0.00000000"],
["173", "UX", "0.00000000", "0.00000000"],
["173", "UY", "0.00000000", "0.00000000"],
["173", "UZ", "0.00000000", "0.00000000"],
["173", "TEMP", "300.000000", "0.00000000"],
["174", "UX", "0.00000000", "0.00000000"],
["174", "UY", "0.00000000", "0.00000000"],
["174", "UZ", "0.00000000", "0.00000000"],
["174", "TEMP", "300.000000", "0.00000000"],
["175", "UX", "0.00000000", "0.00000000"],
["175", "UY", "0.00000000", "0.00000000"],
["175", "UZ", "0.00000000", "0.00000000"],
["175", "TEMP", "300.000000", "0.00000000"],
["176", "UX", "0.00000000", "0.00000000"],
["176", "UY", "0.00000000", "0.00000000"],
["176", "UZ", "0.00000000", "0.00000000"],
["176", "TEMP", "300.000000", "0.00000000"],
["177", "UX", "0.00000000", "0.00000000"],
["177", "UY", "0.00000000", "0.00000000"],
["177", "UZ", "0.00000000", "0.00000000"],
["177", "TEMP", "300.000000", "0.00000000"],
["178", "UX", "0.00000000", "0.00000000"],
["178", "UY", "0.00000000", "0.00000000"],
["178", "UZ", "0.00000000", "0.00000000"],
["178", "TEMP", "300.000000", "0.00000000"],
["179", "UX", "0.00000000", "0.00000000"],
["179", "UY", "0.00000000", "0.00000000"],
["179", "UZ", "0.00000000", "0.00000000"],
["179", "TEMP", "300.000000", "0.00000000"],
["314", "UX", "0.00000000", "0.00000000"],
["314", "UY", "0.00000000", "0.00000000"],
["314", "UZ", "0.00000000", "0.00000000"],
["314", "TEMP", "300.000000", "0.00000000"],
["315", "UX", "0.00000000", "0.00000000"],
["315", "UY", "0.00000000", "0.00000000"],
["315", "UZ", "0.00000000", "0.00000000"],
["315", "TEMP", "300.000000", "0.00000000"],
["316", "UX", "0.00000000", "0.00000000"],
["316", "UY", "0.00000000", "0.00000000"],
["316", "UZ", "0.00000000", "0.00000000"],
["316", "TEMP", "300.000000", "0.00000000"],
["317", "UX", "0.00000000", "0.00000000"],
["317", "UY", "0.00000000", "0.00000000"],
["317", "UZ", "0.00000000", "0.00000000"],
["317", "TEMP", "300.000000", "0.00000000"],
["318", "UX", "0.00000000", "0.00000000"],
["318", "UY", "0.00000000", "0.00000000"],
["318", "UZ", "0.00000000", "0.00000000"],
["318", "TEMP", "300.000000", "0.00000000"],
["319", "UX", "0.00000000", "0.00000000"],
["319", "UY", "0.00000000", "0.00000000"],
["319", "UZ", "0.00000000", "0.00000000"],
["319", "TEMP", "300.000000", "0.00000000"],
["320", "UX", "0.00000000", "0.00000000"],
["320", "UY", "0.00000000", "0.00000000"],
["320", "UZ", "0.00000000", "0.00000000"],
["320", "TEMP", "300.000000", "0.00000000"],
["321", "UX", "0.00000000", "0.00000000"],
["321", "UY", "0.00000000", "0.00000000"],
["321", "UZ", "0.00000000", "0.00000000"],
["321", "TEMP", "300.000000", "0.00000000"],
["322", "UX", "0.00000000", "0.00000000"],
["322", "UY", "0.00000000", "0.00000000"],
["322", "UZ", "0.00000000", "0.00000000"],
["322", "TEMP", "300.000000", "0.00000000"],
["323", "UX", "0.00000000", "0.00000000"],
["323", "UY", "0.00000000", "0.00000000"],
["323", "UZ", "0.00000000", "0.00000000"],
["323", "TEMP", "300.000000", "0.00000000"],
["324", "UX", "0.00000000", "0.00000000"],
["324", "UY", "0.00000000", "0.00000000"],
["324", "UZ", "0.00000000", "0.00000000"],
["324", "TEMP", "300.000000", "0.00000000"],
["330", "UX", "0.00000000", "0.00000000"],
["330", "UY", "0.00000000", "0.00000000"],
["330", "UZ", "0.00000000", "0.00000000"],
["330", "TEMP", "300.000000", "0.00000000"],
["331", "UX", "0.00000000", "0.00000000"],
["331", "UY", "0.00000000", "0.00000000"],
["331", "UZ", "0.00000000", "0.00000000"],
["331", "TEMP", "300.000000", "0.00000000"],
["332", "UX", "0.00000000", "0.00000000"],
["332", "UY", "0.00000000", "0.00000000"],
["332", "UZ", "0.00000000", "0.00000000"],
["332", "TEMP", "300.000000", "0.00000000"],
["334", "UX", "0.00000000", "0.00000000"],
["334", "UY", "0.00000000", "0.00000000"],
["334", "UZ", "0.00000000", "0.00000000"],
["334", "TEMP", "300.000000", "0.00000000"],
["335", "UX", "0.00000000", "0.00000000"],
["335", "UY", "0.00000000", "0.00000000"],
["335", "UZ", "0.00000000", "0.00000000"],
["335", "TEMP", "300.000000", "0.00000000"],
["336", "UX", "0.00000000", "0.00000000"],
["336", "UY", "0.00000000", "0.00000000"],
["336", "UZ", "0.00000000", "0.00000000"],
["336", "TEMP", "300.000000", "0.00000000"],
["340", "UX", "0.00000000", "0.00000000"],
["340", "UY", "0.00000000", "0.00000000"],
["340", "UZ", "0.00000000", "0.00000000"],
["340", "TEMP", "300.000000", "0.00000000"],
["341", "UX", "0.00000000", "0.00000000"],
["341", "UY", "0.00000000", "0.00000000"],
["341", "UZ", "0.00000000", "0.00000000"],
["341", "TEMP", "300.000000", "0.00000000"],
["342", "UX", "0.00000000", "0.00000000"],
["342", "UY", "0.00000000", "0.00000000"],
["342", "UZ", "0.00000000", "0.00000000"],
["342", "TEMP", "300.000000", "0.00000000"],
["343", "UX", "0.00000000", "0.00000000"],
["343", "UY", "0.00000000", "0.00000000"],
["343", "UZ", "0.00000000", "0.00000000"],
["343", "TEMP", "300.000000", "0.00000000"],
["348", "UX", "0.00000000", "0.00000000"],
["348", "UY", "0.00000000", "0.00000000"],
["348", "UZ", "0.00000000", "0.00000000"],
["348", "TEMP", "300.000000", "0.00000000"],
["349", "UX", "0.00000000", "0.00000000"],
["349", "UY", "0.00000000", "0.00000000"],
["349", "UZ", "0.00000000", "0.00000000"],
["349", "TEMP", "300.000000", "0.00000000"],
["350", "UX", "0.00000000", "0.00000000"],
["350", "UY", "0.00000000", "0.00000000"],
["350", "UZ", "0.00000000", "0.00000000"],
["350", "TEMP", "300.000000", "0.00000000"],
["351", "UX", "0.00000000", "0.00000000"],
["351", "UY", "0.00000000", "0.00000000"],
["351", "UZ", "0.00000000", "0.00000000"],
["351", "TEMP", "300.000000", "0.00000000"],
["352", "UX", "0.00000000", "0.00000000"],
["352", "UY", "0.00000000", "0.00000000"],
["352", "UZ", "0.00000000", "0.00000000"],
["352", "TEMP", "300.000000", "0.00000000"],
["353", "UX", "0.00000000", "0.00000000"],
["353", "UY", "0.00000000", "0.00000000"],
["353", "UZ", "0.00000000", "0.00000000"],
["353", "TEMP", "300.000000", "0.00000000"],
["354", "UX", "0.00000000", "0.00000000"],
["354", "UY", "0.00000000", "0.00000000"],
["354", "UZ", "0.00000000", "0.00000000"],
["354", "TEMP", "300.000000", "0.00000000"],
["355", "UX", "0.00000000", "0.00000000"],
["355", "UY", "0.00000000", "0.00000000"],
["355", "UZ", "0.00000000", "0.00000000"],
["355", "TEMP", "300.000000", "0.00000000"],
["356", "UX", "0.00000000", "0.00000000"],
["356", "UY", "0.00000000", "0.00000000"],
["356", "UZ", "0.00000000", "0.00000000"],
["356", "TEMP", "300.000000", "0.00000000"],
["357", "UX", "0.00000000", "0.00000000"],
["357", "UY", "0.00000000", "0.00000000"],
["357", "UZ", "0.00000000", "0.00000000"],
["357", "TEMP", "300.000000", "0.00000000"],
["358", "UX", "0.00000000", "0.00000000"],
["358", "UY", "0.00000000", "0.00000000"],
["358", "UZ", "0.00000000", "0.00000000"],
["358", "TEMP", "300.000000", "0.00000000"],
["359", "UX", "0.00000000", "0.00000000"],
["359", "UY", "0.00000000", "0.00000000"],
["359", "UZ", "0.00000000", "0.00000000"],
["359", "TEMP", "300.000000", "0.00000000"],
["360", "UX", "0.00000000", "0.00000000"],
["360", "UY", "0.00000000", "0.00000000"],
["360", "UZ", "0.00000000", "0.00000000"],
["360", "TEMP", "300.000000", "0.00000000"],
["361", "UX", "0.00000000", "0.00000000"],
["361", "UY", "0.00000000", "0.00000000"],
["361", "UZ", "0.00000000", "0.00000000"],
["361", "TEMP", "300.000000", "0.00000000"],
["362", "UX", "0.00000000", "0.00000000"],
["362", "UY", "0.00000000", "0.00000000"],
["362", "UZ", "0.00000000", "0.00000000"],
["362", "TEMP", "300.000000", "0.00000000"],
["363", "UX", "0.00000000", "0.00000000"],
["363", "UY", "0.00000000", "0.00000000"],
["363", "UZ", "0.00000000", "0.00000000"],
["363", "TEMP", "300.000000", "0.00000000"],
["364", "UX", "0.00000000", "0.00000000"],
["364", "UY", "0.00000000", "0.00000000"],
["364", "UZ", "0.00000000", "0.00000000"],
["364", "TEMP", "300.000000", "0.00000000"],
["365", "UX", "0.00000000", "0.00000000"],
["365", "UY", "0.00000000", "0.00000000"],
["365", "UZ", "0.00000000", "0.00000000"],
["365", "TEMP", "300.000000", "0.00000000"],
["366", "UX", "0.00000000", "0.00000000"],
["366", "UY", "0.00000000", "0.00000000"],
["366", "UZ", "0.00000000", "0.00000000"],
["366", "TEMP", "300.000000", "0.00000000"],
["520", "UX", "0.00000000", "0.00000000"],
["520", "UY", "0.00000000", "0.00000000"],
["520", "UZ", "0.00000000", "0.00000000"],
["520", "TEMP", "300.000000", "0.00000000"],
["572", "UX", "0.00000000", "0.00000000"],
["572", "UY", "0.00000000", "0.00000000"],
["572", "UZ", "0.00000000", "0.00000000"],
["572", "TEMP", "300.000000", "0.00000000"],
["573", "UX", "0.00000000", "0.00000000"],
["573", "UY", "0.00000000", "0.00000000"],
["573", "UZ", "0.00000000", "0.00000000"],
["573", "TEMP", "300.000000", "0.00000000"],
["574", "UX", "0.00000000", "0.00000000"],
["574", "UY", "0.00000000", "0.00000000"],
["574", "UZ", "0.00000000", "0.00000000"],
["574", "TEMP", "300.000000", "0.00000000"],
["575", "UX", "0.00000000", "0.00000000"],
["575", "UY", "0.00000000", "0.00000000"],
["575", "UZ", "0.00000000", "0.00000000"],
["575", "TEMP", "300.000000", "0.00000000"],
["576", "UX", "0.00000000", "0.00000000"],
["576", "UY", "0.00000000", "0.00000000"],
["576", "UZ", "0.00000000", "0.00000000"],
["576", "TEMP", "300.000000", "0.00000000"],
["628", "UX", "0.00000000", "0.00000000"],
["628", "UY", "0.00000000", "0.00000000"],
["628", "UZ", "0.00000000", "0.00000000"],
["628", "TEMP", "300.000000", "0.00000000"],
["645", "UX", "0.00000000", "0.00000000"],
["645", "UY", "0.00000000", "0.00000000"],
["645", "UZ", "0.00000000", "0.00000000"],
["645", "TEMP", "300.000000", "0.00000000"],
["708", "UX", "0.00000000", "0.00000000"],
["708", "UY", "0.00000000", "0.00000000"],
["708", "UZ", "0.00000000", "0.00000000"],
["708", "TEMP", "300.000000", "0.00000000"],
["709", "UX", "0.00000000", "0.00000000"],
["709", "UY", "0.00000000", "0.00000000"],
["709", "UZ", "0.00000000", "0.00000000"],
["709", "TEMP", "300.000000", "0.00000000"],
["710", "UX", "0.00000000", "0.00000000"],
["710", "UY", "0.00000000", "0.00000000"],
["710", "UZ", "0.00000000", "0.00000000"],
["710", "TEMP", "300.000000", "0.00000000"],
["711", "UX", "0.00000000", "0.00000000"],
["711", "UY", "0.00000000", "0.00000000"],
["711", "UZ", "0.00000000", "0.00000000"],
["711", "TEMP", "300.000000", "0.00000000"],
["712", "UX", "0.00000000", "0.00000000"],
["712", "UY", "0.00000000", "0.00000000"],
["712", "UZ", "0.00000000", "0.00000000"],
["712", "TEMP", "300.000000", "0.00000000"],
["713", "UX", "0.00000000", "0.00000000"],
["713", "UY", "0.00000000", "0.00000000"],
["713", "UZ", "0.00000000", "0.00000000"],
["713", "TEMP", "300.000000", "0.00000000"],
["757", "UX", "0.00000000", "0.00000000"],
["757", "UY", "0.00000000", "0.00000000"],
["757", "UZ", "0.00000000", "0.00000000"],
["757", "TEMP", "300.000000", "0.00000000"],
["758", "UX", "0.00000000", "0.00000000"],
["758", "UY", "0.00000000", "0.00000000"],
["758", "UZ", "0.00000000", "0.00000000"],
["758", "TEMP", "300.000000", "0.00000000"],
["784", "UX", "0.00000000", "0.00000000"],
["784", "UY", "0.00000000", "0.00000000"],
["784", "UZ", "0.00000000", "0.00000000"],
["784", "TEMP", "300.000000", "0.00000000"],
["785", "UX", "0.00000000", "0.00000000"],
["785", "UY", "0.00000000", "0.00000000"],
["785", "UZ", "0.00000000", "0.00000000"],
["785", "TEMP", "300.000000", "0.00000000"],
["831", "UX", "0.00000000", "0.00000000"],
["831", "UY", "0.00000000", "0.00000000"],
["831", "UZ", "0.00000000", "0.00000000"],
["831", "TEMP", "300.000000", "0.00000000"],
["832", "UX", "0.00000000", "0.00000000"],
["832", "UY", "0.00000000", "0.00000000"],
["832", "UZ", "0.00000000", "0.00000000"],
["832", "TEMP", "300.000000", "0.00000000"],
["833", "UX", "0.00000000", "0.00000000"],
["833", "UY", "0.00000000", "0.00000000"],
["833", "UZ", "0.00000000", "0.00000000"],
["833", "TEMP", "300.000000", "0.00000000"],
["835", "UX", "0.00000000", "0.00000000"],
["835", "UY", "0.00000000", "0.00000000"],
["835", "UZ", "0.00000000", "0.00000000"],
]
CMD_DOC_STRING_INJECTOR = CMD_LISTING.copy()
CMD_DOC_STRING_INJECTOR.extend(CMD_BC_LISTING)
@pytest.fixture(scope="module")
def plastic_solve(mapdl):
mapdl.mute = True
mapdl.finish()
mapdl.clear()
mapdl.input(examples.verif_files.vmfiles["vm273"])
mapdl.post1()
mapdl.set(1, 2)
mapdl.mute = False
@pytest.fixture(scope="module")
def beam_solve(mapdl):
mapdl.mute = True
mapdl.finish()
mapdl.clear()
mapdl.input(examples.verif_files.vmfiles["vm10"])
mapdl.post1()
mapdl.set(1, 2)
mapdl.mute = False
def test_cmd_class():
output = """This is the output.
This is the second line.
These are numbers 1234567890.
These are symbols !"£$%^^@~+_@~€
This is for the format: {format1}-{format2}-{format3}"""
cmd = "/INPUT"
cmd_out = CommandOutput(output, cmd=cmd)
assert isinstance(cmd_out, (str, CommandOutput))
assert isinstance(cmd_out[1:], (str, CommandOutput))
assert isinstance(cmd_out.splitlines(), list)
assert isinstance(cmd_out.splitlines()[0], (str, CommandOutput))
assert isinstance(cmd_out.replace("a", "c"), (str, CommandOutput))
assert isinstance(cmd_out.partition("g"), tuple)
assert isinstance(cmd_out.split("g"), list)
def test_cmd_class_prnsol_short():
cmd = "PRRSOL,F"
out = CommandListingOutput(PRNSOL_OUT, cmd=cmd)
out_list = out.to_list()
out_array = out.to_array()
assert isinstance(out, CommandListingOutput)
assert isinstance(out_list, list)
assert out_list
assert isinstance(out_array, np.ndarray) and out_array.size != 0
if has_dependency("pandas"):
out_df = out.to_dataframe()
assert isinstance(out_df, pd.DataFrame) and not out_df.empty
def test_cmd_class_dlist_vm(mapdl, cleared):
# Run only the first 100 lines of VM223
with open(verif_files.vmfiles["vm223"]) as fid:
cmds = fid.read()
mapdl.finish()
ind = cmds.find("NSEL,ALL")
mapdl.input_strings(cmds[:ind])
mapdl.allsel("all")
out = mapdl.dlist()
out_list = out.to_list()
def are_the_same_result():
for el1, el2 in zip(out_list, DLIST_RESULT):
for el11, el22 in zip(el1, el2):
if el11 != el22:
return False
return True
assert isinstance(out, BoundaryConditionsListingOutput)
assert isinstance(out_list, list)
assert out_list
assert are_the_same_result()
@pytest.mark.parametrize("func", LIST_OF_INQUIRE_FUNCTIONS)
def test_inquire_functions(mapdl, func):
func_ = getattr(mapdl, func)
func_args = inspect.getfullargspec(func_).args
args = [
ARGS_INQ_FUNC[each_arg] for each_arg in func_args if each_arg not in ["self"]
]
output = func_(*args)
if "GRPC" in mapdl.name:
assert isinstance(output, (float, int))
else:
assert isinstance(output, str)
assert "=" in output
@pytest.mark.parametrize(
"func,args",
[("prnsol", ("U", "X")), ("presol", ("S", "X")), ("presol", ("S", "ALL"))],
)
def test_output_listing(mapdl, plastic_solve, func, args):
mapdl.post1()
func_ = getattr(mapdl, func)
out = func_(*args)
out_list = out.to_list()
out_array = out.to_array()
assert isinstance(out, CommandListingOutput)
assert isinstance(out_list, list) and out_list
assert isinstance(out_array, np.ndarray) and out_array.size != 0
if has_dependency("pandas"):
out_df = out.to_dataframe()
assert isinstance(out_df, pd.DataFrame) and not out_df.empty
@pytest.mark.parametrize("func", ["dlist", "flist"])
def test_bclist(mapdl, beam_solve, func):
func_ = getattr(mapdl, func)
out = func_()
out_list = out.to_list()
assert isinstance(out, BoundaryConditionsListingOutput)
assert isinstance(out_list, list) and out_list
with pytest.raises(ValueError):
out.to_array()
if has_dependency("pandas"):
out_df = out.to_dataframe()
assert isinstance(out_df, pd.DataFrame) and not out_df.empty
@pytest.mark.parametrize("method", CMD_DOC_STRING_INJECTOR)
def test_docstring_injector(mapdl, method):
"""Check if the docstring has been injected."""
for name in dir(mapdl):
if name[0:4].upper() == method and name in dir(
Commands
): # avoid matching Mapdl properties which starts with same letters as MAPDL commands.
func = mapdl.__getattribute__(name)
# If '__func__' not present (AttributeError) very likely it has not
# been wrapped.
docstring = func.__doc__
assert "Returns" in docstring
assert "to_list()" in docstring
assert "to_array()" in docstring
assert "to_dataframe()" in docstring
def test_string_with_literal():
base_ = "asdf\nasdf"
output = StringWithLiteralRepr(base_)
assert output.__repr__() == output
assert output.__repr__() == base_
assert len(output.split()) == 2
@requires("pandas")
@pytest.mark.parametrize("output,last_element", [(set_list_0, 9), (set_list_1, 15)])
def test_magicwords(output, last_element):
magicwords = ["SET"]
obj = CommandListingOutput(
output,
magicwords=magicwords,
columns_names=[
"SET",
"TIME/FREQ",
"LOAD STEP",
"SUBSTEP",
"CUMULATIVE",
],
)
assert obj.to_list() is not None
assert obj.to_array() is not None
assert obj.to_dataframe() is not None
arr = obj.to_array()
assert arr[-1, -1] == last_element
def test_nlist_to_array(mapdl, beam_solve):
# This kinternal include the internal points, so it matches the
# number of nodes with midside nodes.
nlist = mapdl.nlist(kinternal="internal")
assert isinstance(nlist.to_list(), list)
assert isinstance(nlist.to_array(), np.ndarray)
# above asserts should be removed once fixed the midside issue.
assert len(nlist.to_list()) == len(mapdl.mesh.nodes)
assert len(nlist.to_array()) == len(mapdl.mesh.nodes)
assert np.allclose(nlist.to_array()[:, 1:4], mapdl.mesh.nodes)
def test_cmlist(mapdl):
mapdl.clear()
mapdl.prep7()
# setup the full file
mapdl.block(0, 1, 0, 1, 0, 1)
mapdl.et(1, 186)
mapdl.esize(0.5)
mapdl.vmesh("all")
mapdl.cm("myComp", "node")
mapdl.cm("_myComp", "node")
mapdl.cm("_myComp_", "node")
cmlist = mapdl.cmlist()
assert "MYCOMP" in cmlist
cmlist_all = mapdl.cmlist("all")
assert "_MYCOMP_" in cmlist_all
assert "_MYCOMP" in cmlist_all
assert "MYCOMP" in cmlist_all
assert ["MYCOMP"] == mapdl.cmlist().to_list()
assert "_MYCOMP_" in cmlist_all.to_list()
assert "_MYCOMP" in cmlist_all.to_list()
assert "MYCOMP" in cmlist_all.to_list()
assert len(cmlist_all.to_array()) == len(cmlist_all.to_list())
for each_ in cmlist_all.to_list():
assert each_ in cmlist_all
class Test_bc_cmdlist_solid:
def solid_model(self, mapdl):
# Solid model (Geometry)
mapdl.clear()
mapdl.prep7()
# Define keypoints, lines and area
# --------------------
mapdl.k(1, 0, 0)
mapdl.k(2, 1, 0)
mapdl.k(3, 1, 1)
mapdl.l(1, 2)
mapdl.l(2, 3)
mapdl.l(3, 1)
mapdl.a(1, 2, 3)
# Define a material
# --------------------
mapdl.mp("EX", 1, 30e6)
mapdl.mp("NUXY", 1, 0.25) # Poisson's Ratio
# Define section
# --------------------
mapdl.et(1, "PLANE183")
mapdl.keyopt(1, 1, 0)
mapdl.keyopt(1, 3, 3)
mapdl.keyopt(1, 6, 0)
mapdl.r(1, 0.01)
@requires("pandas")
def test_dklist(self, mapdl):
df_dk = pd.DataFrame(
{
"KEYPOINT": [1],
"LABEL": ["UX"],
"REAL": [0.0],
"IMAG": [0.0],
"EXP KEY": ["0"],
}
)
self.solid_model(mapdl)
mapdl.dk(1, "UX", 0)
dklist_result = mapdl.dklist().to_dataframe()
assert not dklist_result.empty
assert dklist_result.compare(df_dk).empty
@requires("pandas")
def test_dllist(self, mapdl):
df_dl = pd.DataFrame(
{
"LINE": [2, 2],
"LABEL": ["UX", "UY"],
"REAL": [0.0, 0.0],
"IMAG": [0.0, 0.0],
"NAREA": ["0", "0"],
}
)
self.solid_model(mapdl)
mapdl.dl(2, 1, "ALL", 0)
dllist_result = mapdl.dllist().to_dataframe()
assert not dllist_result.empty
assert dllist_result.compare(df_dl).empty
@requires("pandas")
def test_dalist(self, mapdl):
df_da = pd.DataFrame(
{
"AREA": [1],
"LABEL": ["UZ"],
"REAL": [0.0],
"IMAG": [0.0],
}
)
self.solid_model(mapdl)
mapdl.da(1, "UZ", 0)
dalist_result = mapdl.dalist().to_dataframe()
assert not dalist_result.empty
assert dalist_result.compare(df_da).empty
@requires("pandas")
def test_fklist(self, mapdl):
df_fk = pd.DataFrame(
{
"KEYPOINT": [2, 3],
"LABEL": ["FY", "FY"],
"REAL": [200.0, 100.0],
"IMAG": [0.0, 0.0],
}
)
self.solid_model(mapdl)
mapdl.fk(2, "FY", 200)
mapdl.fk(3, "FY", 100)
fklist_result = mapdl.fklist().to_dataframe()
assert not fklist_result.empty
assert fklist_result.compare(df_fk).empty
@requires("pandas")
def test_sfllist(self, mapdl):
df_sfl = pd.DataFrame(
{
"LINE": [2, 3],
"LABEL": ["PRES", "PRES"],
"VALI": [50.0, 50.0],
"VALJ": [500.0, 500.0],
}
)
self.solid_model(mapdl)
mapdl.sfl(2, "PRES", 50, 500)
mapdl.sfl(3, "PRES", 50, 500)
sfllist_result = mapdl.sfllist().to_dataframe()
assert not sfllist_result.empty
assert sfllist_result.compare(df_sfl).empty
@requires("pandas")
def test_bfklist(self, mapdl):
df_bfk = pd.DataFrame(
{
"KEYPOINT": [2],
"LABEL": ["TEMP"],
"VALUE": [10.0],
}
)
self.solid_model(mapdl)
mapdl.bfk(2, "TEMP", 10)
bfklist_result = mapdl.bfklist().to_dataframe()
assert not bfklist_result.empty
assert bfklist_result.compare(df_bfk).empty
@requires("pandas")
def test_bfllist(self, mapdl):
df_bfl = pd.DataFrame(
{
"LINE": [3],
"LABEL": ["TEMP"],
"VALUE": [15.0],
}
)
self.solid_model(mapdl)
mapdl.bfl(3, "TEMP", 15)
bfllist_result = mapdl.bfllist().to_dataframe()
assert not bfllist_result.empty
assert bfllist_result.compare(df_bfl).empty
@requires("pandas")
def test_bfalist(self, mapdl):
df_bfa = pd.DataFrame(
{
"AREA": [1],
"LABEL": ["TEMP"],
"VALUE": [20.0],
}
)
self.solid_model(mapdl)
mapdl.bfa(1, "TEMP", 20)
bfalist_result = mapdl.bfalist().to_dataframe()
assert not bfalist_result.empty
assert bfalist_result.compare(df_bfa).empty
class Test_bc_cmdlist_model:
def solid_model(self, mapdl):
# Solid model (Geometry)
mapdl.clear()
mapdl.prep7()
# Define keypoints, lines and area
# --------------------
mapdl.k(1, 0, 0)
mapdl.k(2, 1, 0)
mapdl.k(3, 1, 1)
mapdl.l(1, 2)
mapdl.l(2, 3)
mapdl.l(3, 1)
mapdl.a(1, 2, 3)
# Define a material
# --------------------
mapdl.mp("EX", 1, 30e6)
mapdl.mp("NUXY", 1, 0.25) # Poisson's Ratio
# Define section
# --------------------
mapdl.et(1, "PLANE183")
mapdl.keyopt(1, 1, 0)
mapdl.keyopt(1, 3, 3)
mapdl.keyopt(1, 6, 0)
mapdl.r(1, 0.01)
def fe_model(self, mapdl):
# FE model (Mesh)
self.solid_model(mapdl)