Organize in submodules
This commit is contained in:
Noe Brucy
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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# This file is part of the 'astrophysix' Python package.
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#
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# Copyright © Commissariat a l'Energie Atomique et aux Energies Alternatives (CEA)
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#
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# FREE SOFTWARE LICENCING
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# -----------------------
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# This software is governed by the CeCILL license under French law and abiding by the rules of distribution of free
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# software. You can use, modify and/or redistribute the software under the terms of the CeCILL license as circulated by
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# CEA, CNRS and INRIA at the following URL: "http://www.cecill.info". As a counterpart to the access to the source code
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# and rights to copy, modify and redistribute granted by the license, users are provided only with a limited warranty
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# and the software's author, the holder of the economic rights, and the successive licensors have only limited
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# liability. In this respect, the user's attention is drawn to the risks associated with loading, using, modifying
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# and/or developing or reproducing the software by the user in light of its specific status of free software, that may
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# mean that it is complicated to manipulate, and that also therefore means that it is reserved for developers and
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# experienced professionals having in-depth computer knowledge. Users are therefore encouraged to load and test the
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# software's suitability as regards their requirements in conditions enabling the security of their systems and/or data
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# to be ensured and, more generally, to use and operate it in the same conditions as regards security. The fact that
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# you are presently reading this means that you have had knowledge of the CeCILL license and that you accept its terms.
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#
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#
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# COMMERCIAL SOFTWARE LICENCING
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# -----------------------------
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# You can obtain this software from CEA under other licencing terms for commercial purposes. For this you will need to
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# negotiate a specific contract with a legal representative of CEA.
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#
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from __future__ import print_function, unicode_literals
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import os
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import numpy as N
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from astrophysix import units as U
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from astrophysix.simdm import Project, ProjectCategory, SimulationStudy
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from astrophysix.simdm.datafiles import Datafile, PlotInfo, PlotType
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from astrophysix.simdm.experiment import (
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AppliedAlgorithm,
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ParameterSetting,
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ParameterVisibility,
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ResolvedPhysicalProcess,
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Simulation,
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)
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from astrophysix.simdm.protocol import (
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Algorithm,
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AlgoType,
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InputParameter,
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PhysicalProcess,
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Physics,
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SimulationCode,
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)
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from astrophysix.simdm.results import GenericResult, Snapshot
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from astrophysix.utils.file import FileType
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# ----------------------------------------------- Project creation --------------------------------------------------- #
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# Available project categories are :
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# - ProjectCategory.SolarMHD
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# - ProjectCategory.PlanetaryAtmospheres
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# - ProjectCategory.StarPlanetInteractions
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# - ProjectCategory.StarFormation
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# - ProjectCategory.Supernovae
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# - ProjectCategory.GalaxyFormation
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# - ProjectCategory.GalaxyMergers
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# - ProjectCategory.Cosmology
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proj = Project(
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category=ProjectCategory.StarFormation,
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project_title="Ismfeed",
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alias="ismfeed",
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short_description="Impact of feedback and turbulence on star formation",
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general_description="""Impact of feedback and turbulence on star formation. The simulation presented here are described in Brucy et al. 2020, ApJL, L38""",
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data_description="The data available in this project...",
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directory_path="~nbrucy/simus/ismfeed",
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)
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print(proj)
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# -------------------------------------------------------------------------------------------------------------------- #
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# --------------------------------------- Simulation code definition ------------------------------------------------- #
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ramses = SimulationCode(
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name="Ramses 3 (MHD)",
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code_name="Ramses",
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code_version="3.10.1",
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alias="RAMSES_3",
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url="https://www.ics.uzh.ch/~teyssier/ramses/RAMSES.html",
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description="Ramses MHD code",
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)
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# => Add algorithms : available algorithm types are :
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# - AlgoType.AdaptiveMeshRefinement
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# - AlgoType.VoronoiMovingMesh
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# - AlgoType.SmoothParticleHydrodynamics
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# - AlgoType.Godunov
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# - AlgoType.PoissonMultigrid
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# - AlgoType.PoissonConjugateGradient
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# - AlgoType.ParticleMesh
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# - AlgoType.FriendOfFriend
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# - AlgoType.HLLCRiemann
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# - AlgoType.RayTracer
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# amr = ramses.algorithms.add(Algorithm(algo_type=AlgoType.AdaptiveMeshRefinement, description="AMR"))
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ramses.algorithms.add(
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Algorithm(algo_type=AlgoType.Godunov, description="Godunov scheme")
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)
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ramses.algorithms.add(
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Algorithm(algo_type=AlgoType.HLLCRiemann, description="HLLC Riemann solver")
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)
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ramses.algorithms.add(
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Algorithm(
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algo_type=AlgoType.PoissonMultigrid, description="Multigrid Poisson solver"
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)
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)
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ramses.algorithms.add(
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Algorithm(algo_type=AlgoType.ParticleMesh, description="PM solver")
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)
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# => Add input parameters
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ramses.input_parameters.add(
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InputParameter(
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key="amr_params/levelmin",
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name="Lmin",
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description="min. level of AMR refinement",
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)
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)
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ramses.input_parameters.add(
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InputParameter(
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key="amr_params/levelmax",
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name="Lmax",
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description="max. level of AMR refinement",
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)
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)
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ramses.input_parameters.add(
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InputParameter(
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key="turb_params/turb_rms", name="f_rms", description="Amplitude of the driving"
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)
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)
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ramses.input_parameters.add(
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InputParameter(
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key="cloud_params/dens0", name="n_0", description="Midplane density in cm**-3"
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)
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)
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ramses.input_parameters.add(
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InputParameter(
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key="cloud_params/bx_bound",
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name="bx_bound",
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description="imposed magnetic field at the x boundary (1 implies that the magnetic pressure is equal to thermal pressure in WNM, which corresponds to about 5muG)",
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)
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)
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# => Add physical processes : available physics are :
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# - Physics.SelfGravity
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# - Physics.Hydrodynamics
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# - Physics.MHD
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# - Physics.StarFormation
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# - Physics.SupernovaeFeedback
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# - Physics.AGNFeedback
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# - Physics.MolecularCooling
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ramses.physical_processes.add(
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PhysicalProcess(
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physics=Physics.StarFormation,
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description="Star Formation is triggered when density overpass",
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)
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)
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ramses.physical_processes.add(
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PhysicalProcess(
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physics=Physics.MHD, description="Magneto-hydrodynamical equations are solved"
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)
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)
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ramses.physical_processes.add(
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PhysicalProcess(physics=Physics.SelfGravity, description="Self-Gravity is applied.")
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)
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ramses.physical_processes.add(
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PhysicalProcess(physics=Physics.SupernovaeFeedback, description="SN feedback")
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)
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# -------------------------------------------------------------------------------------------------------------------- #
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# -------------------------------------------- Simulation setup ------------------------------------------------------ #
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simu = Simulation(
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simu_code=ramses,
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name="Noturb_1",
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alias="noturb_1",
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description="Simulation without turbulence",
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directory_path="~nbrucy/simus/turb/",
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)
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proj.simulations.add(simu)
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# Add applied algorithms implementation details. Warning : corresponding algorithms must have been added in the 'ramses'
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# simulation code.
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# simu.applied_algorithms.add(AppliedAlgorithm(algorithm=amr, details="My AMR implementation [Teyssier 2002]"))
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# simu.applied_algorithms.add(AppliedAlgorithm(algorithm=ramses.algorithms[AlgoType.HLLCRiemann.name],
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# details="My Riemann solver implementation [Teyssier 2002]"))
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# Add parameter setting. Warning : corresponding input parameter must have been added in the 'ramses' simulation code.
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# Available parameter visibility options are :
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# - ParameterVisibility.NOT_DISPLAYED
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# - ParameterVisibility.ADVANCED_DISPLAY
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# - ParameterVisibility.BASIC_DISPLAY
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simu.parameter_settings.add(
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ParameterSetting(
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input_param=ramses.input_parameters["levelmin"],
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value=8,
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visibility=ParameterVisibility.BASIC_DISPLAY,
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)
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)
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simu.parameter_settings.add(
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ParameterSetting(
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input_param=lmax, value=12, visibility=ParameterVisibility.BASIC_DISPLAY
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)
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)
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# Add resolved physical process implementation details. Warning : corresponding physical process must have been added to
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# the 'ramses' simulation code
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simu.resolved_physics.add(
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ResolvedPhysicalProcess(
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physics=ramses.physical_processes[Physics.StarFormation.name],
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details="Star formation specific implementation",
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)
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)
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simu.resolved_physics.add(
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ResolvedPhysicalProcess(
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physics=grav, details="self-gravity specific implementation"
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)
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)
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# -------------------------------------------------------------------------------------------------------------------- #
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# -------------------------------------- Simulation generic result and snapshots ------------------------------------- #
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# Generic result
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gres = GenericResult(
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name="Key result 1 !",
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description="My description",
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directory_path="/my/path/to/result",
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)
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simu.generic_results.add(gres)
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# Simulation snapshot
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# In one-line
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sn = simu.snapshots.add(
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Snapshot(
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name="My best snapshot !",
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description="My first snapshot description",
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time=(125, U.kyr),
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physical_size=(250.0, U.kpc),
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directory_path="/path/to/snapshot1",
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data_reference="OUTPUT_00056",
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)
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)
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# Or create snapshot, then add it to the simulation
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sn2 = Snapshot(
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name="My second best snapshot !",
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description="My second snapshot description",
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time=(0.26, U.Myr),
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physical_size=(0.25, U.Mpc),
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directory_path="/path/to/snapshot2",
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data_reference="OUTPUT_00158",
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)
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simu.snapshots.add(sn2)
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# -------------------------------------------------------------------------------------------------------------------- #
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# ---------------------------------------------------- Result datafiles ---------------------------------------------- #
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# Datafile creation
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imf_df = sn.datafiles.add(
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Datafile(
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name="Initial mass function plot",
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description="This is my plot detailed description",
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)
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)
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# Add attached files to a datafile (1 per file type). Available file types are :
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# - FileType.HDF5_FILE
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# - FileType.PNG_FILE
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# - FileType.JPEG_FILE
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# - FileType.FITS_FILE
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# - FileType.TARGZ_FILE
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# - FileType.PICKLE_FILE
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# - FileType.JSON_FILE
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# - FileType.CSV_FILE
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# - FileType.ASCII_FILE
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imf_df[FileType.PNG_FILE] = os.path.join(
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"/data", "io", "datafiles", "plot_image_IMF.png"
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)
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imf_df[FileType.JPEG_FILE] = os.path.join(
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"/data", "io", "datafiles", "plot_with_legend.jpg"
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)
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imf_df[FileType.FITS_FILE] = os.path.join(
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"/data", "io", "datafiles", "cassiopea_A_0.5-1.5keV.fits"
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)
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imf_df[FileType.TARGZ_FILE] = os.path.join("/data", "io", "datafiles", "archive.tar.gz")
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imf_df[FileType.JSON_FILE] = os.path.join(
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"/data", "io", "datafiles", "test_header_249.json"
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)
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imf_df[FileType.ASCII_FILE] = os.path.join("/data", "io", "datafiles", "abstract.txt")
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imf_df[FileType.HDF5_FILE] = os.path.join("/data", "io", "HDF5", "study.h5")
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imf_df[FileType.PICKLE_FILE] = os.path.join(
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"/data", "io", "datafiles", "dict_saved.pkl"
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)
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# Datafile plot information (for plot future updates and online interactive visualisation on Galactica web pages).
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# Available plot types are :
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# - LINE_PLOT
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# - SCATTER_PLOT
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# - HISTOGRAM
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# - HISTOGRAM_2D
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# - IMAGE
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# - MAP_2D
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imf_df.plot_info = PlotInfo(
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plot_type=PlotType.LINE_PLOT,
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xaxis_values=N.array([10.0, 20.0, 30.0, 40.0, 50.0]),
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yaxis_values=N.array([1.256, 2.456, 3.921, 4.327, 5.159]),
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xaxis_log_scale=False,
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yaxis_log_scale=False,
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xaxis_label="Mass",
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yaxis_label="Probability",
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xaxis_unit=U.Msun,
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plot_title="Initial mass function",
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yaxis_unit=U.Mpc,
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)
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# -------------------------------------------------------------------------------------------------------------------- #
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# Save study in HDF5 file
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study = SimulationStudy(project=proj)
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study.save_HDF5("./frig_study.h5")
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# Eventually reload it from HDF5 file to edit its content
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# study = SimulationStudy.load_HDF5("./frig_study.h5")
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