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9099792947
* Provide MonteCarloGenerate capability
Intermediate commit, this squash represents all of Isaac Reaves' work
during his Fall 2022 Pathways internship tour
[skip ci]
* TrickOps: Add phase, [min-max] range, and overhaul YAML verification
* Add new "phase:" mechanism to TrickOps Runs and Builds to support
project-specific constraints on build and run ordering
- phase defaults to zero if not specified and must be between -1000
and 1000 if given.
- jobs can now optionally be requested by their phase or phase range
- See trickops/README.md for details
* Add [min-max] notation capability to run: entries and compare: entries
- [min-max] ranges provide definition of a set of runs using a common
numbering scheme in the YAML file, greatly reducing YAML file size
for monte-carlo and other zero-padded run numbering use cases
- See trickops/README.md for details
* YAML parsing changes
- Overhaul the logic which verifies YAML files for the expected
TrickOps format. This is now done in TrickWorkflowYamlVerifier and
provides much more robust error checking than previous approach
- .yaml_requirements.yml now provides the required types, ranges, and
default values as applicable to expected entries in YAML files
- valgrind: is now an sub-option to run: entries, not its own section
Users should now list their runs normallly and define their flags in
in that run's valgrind: subsection
- parallel_safety is now a per-sim parameter and not global. Users
should move their global config to the sim layer
- self.config_errors is now a list of errors. Users should now
check for empty list when using instead of True/False
* Robustify the get_koviz_report_jobs unit test to work whether koviz
exists on PATH or not
* Adjust trickops.py to use the new phase and range features
- Make it more configurable on the command-line via argparse
- Move SIM_mc_generation tests into test_sims.yml
[skip ci]
* Code review and cleanup from PR #1389
Documentation:
* Adjust documentation to fit suggested symlinked approach. Also
cleaned up duplicate images and old documentation.
* Moved the verification section out of markdown and into a PDF since it
heavily leverages formatting not available in markdown.
* Clarify a couple points on the Darwin Trick install guide
* Update wiki to clarify that data recording strings is not supported
MCG Code:
* Replace MonteCarloVariableRandomNormal::is_near_equal with new
Trick::dbl_is_near from trick team
MCG Testing:
* Reduce the set of SIM_mc_generation comparisons. After discussion
the trick team, we are choosing to remove all comparisons to
verif_data/ which contain random-generated numbers since
these tests cannot pass across all supported trick platforms.
* Fix the wrong rule on exlcuding -Werror for Darwin builds
of SIM_mc_generation
* Remove data recording of strings in SIM_mc_generation
Trickops:
* Replace build_command with build_args per discussion w/ Trick team
Since we only support arguments to trick-CP, replace the build_command
yaml entry with build_args
* Disable var server connection by default in SingleRun if TrickWorkflow.quiet
is True
* Guard against multiple Job starts
* Remove SimulationJob inheritance layer since old monte-carlo wasn't
and never will be supported by TrickOps
* Ignore IOError raise from variable_server that looks like "The remote
endpoint has closed the connection". This appears to occur when
SingleRun jobs attempt to connect to the var server for a sim that
terminates very early
[skip ci]
* Adjust phasing of old/new MCG initialize functions
* Clarify failure message in generate_dispersions if new/old MC are both
used.
* Adjust the phasing order of MCG intialize method to be before
legacy MC initialized. Without this, monte-carlo dry run completes with
success before the check in generate_dispersions() can run
* Add -Wno-stringop-truncation to S_override.mk for SIM_mc_generation
since gcc 8+ warns about SWIG generated content in top.cpp
* Introduce MonteCarloGenerationHelper python class
This new class provides an easy-to-use interface for MCG sim-module
users:
1. Run generation
2. Getting an sbatch array job suitable for SLURM
3. Getting a list of SingleRun() instances for generated runs, to be
executed locally if desired
---------
Co-authored-by: Dan Jordan <daniel.d.jordan@nasa.gov>
49 lines
2.4 KiB
Python
49 lines
2.4 KiB
Python
# The Monte Carlo tool uses a double execution of the S-main:
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# - pass #1 uses the scenario input.py file to process the variables identified
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# for dispersion. A specified number, N, of values {v_1, ..., v_N} is
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# generated for each variable v, with the values constrained by the specified
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# distribution of v; N is specified in the input file.
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# A set of N files, {RUN_1/monte_input.py, ... , RUN_N/monte_input.py} is
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# created, with each file containing one of the set of values for each
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# variable. Once these files are generated, the simulation is complete for
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# pass #1 and it terminates.
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# - pass #2 uses one of the generated files (monte_input.py) as the input file
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# for a regular execution of the simulation. There will typically be many
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# executions of the sim, one for each of the generated monte_input.py files.
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# This input file provides one example of how to test this two-pass process,
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# although it is admittedly a bit convoluted and hard to read. TODO: Once
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# TrickOps is capable of operating with this monte-carlo implementation, that
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# framework can manage both the generation and local execution of generated
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# monte_input.py files, removing the need for this type of "sim that launches a
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# sim" test methodology -Jordan 10/2022
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# For the purpose of expedient testing, we generate and run only 2 files.
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# This is sufficient to demonstrate "multiple" without unnecessarily
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# burning CPU time.
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import os
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exename = "S_main_" + os.getenv("TRICK_HOST_CPU") + ".exe"
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# Pass #1 Generate the set of scenarios with unique dispersions
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print("Processing Pass #1 for run RUN_nominal")
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input_file = "RUN_nominal/input_a.py"
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ret = os.system("./" + exename + " " + input_file)
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if ret != 0:
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trick.exec_terminate_with_return(1, "double_pass.py", 34, "Error running " + input_file)
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# Pass #2 Run the scenarios. Logged data will go into each scenario's folder
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print("")
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print("")
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print("Processing Pass #2 for run RUN_nominal")
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for ii in range(2):
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input_file = "MONTE_RUN_nominal"+"/RUN_00%d/monte_input_a.py" %ii
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print ("**************** %s" %input_file)
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ret = os.system("./" + exename + " " + input_file)
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if ret != 0:
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trick.exec_terminate_with_return(1, "double_pass.py", 43, "Error running " + input_file)
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# To be compatible with our current unit-sim framework, this file has to be a
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# simulation input file. Therefore it needs a stop time so it doesn't run forever.
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trick.stop(0.0)
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