get_rprofs

Utilities in this directory extract Reynolds-averaged radial profiles from PHLEGETHON snapshot files (grid_nXXXXX.h5).

Files:

  • extract_rprofs.py: reads snapshot dumps and writes one radial-profile archive per dump. This module cotains the backend.

  • submit_rprofs.py: helper for Slurm batch submission in chunks. The configuration of the extraction is set here.

  • get_rprofs.job: Slurm job template rewritten by submit_rprofs.py before each submission.

Requirements

  1. PHLEGETHON Python paths available (example):

export PYTHONPATH=$PYTHONPATH:/path/to/phlegethon/python/
export PYTHONPATH=$PYTHONPATH:/path/to/phlegethon/miscellaneous/eos/

  1. EOS data path available through PHLEGETHONDATA (or use default ../../data/):

export PHLEGETHONDATA=/path/to/phlegethon/data/

Input Expectations

  • Snapshots must be named grid_nXXXXX.h5.

  • grid_n00000.h5 must exist (used to read metadata and static geometry fields).

  • The snapshot path argument is to be passed with a trailing slash, for example /path/to/snaps/.

Run Directly

From this directory:

python3 extract_rprofs.py <dump1> <dump2> <delta_dump> <make_coarse> <snapshots_path/> <output_dir>

Arguments:

  • dump1: first dump index (inclusive).

  • dump2: last dump index (exclusive).

  • delta_dump: stride between processed dumps.

  • make_coarse: 0 for no rebinning, 1 for x2 coarsening in each active dimension.

  • snapshots_path/: path to grid_nXXXXX.h5 files (include trailing /).

  • output_dir: directory where RPROFS_<nth snapshot>.npz files are written.

Example:

python3 extract_rprofs.py 0 200 1 0 /scratch/run01/ /scratch/run01/rprofs

Slurm Workflow (submit_rprofs.py)

submit_rprofs.py splits the available snapshots into chunks and submits one Slurm job per chunk.

  1. Edit the variables at the top of submit_rprofs.py:

    • path_to_sim: snapshot directory containing grid_nXXXXX.h5 files.

    • path_to_output: output directory for RPROFS_*.npz files.

    • pycmd: path to extract_rprofs.py used in submitted jobs.

    • ntasks: number of chunks/jobs used to split the dump range.

    • ncores_per_task: core count requested per submitted job.

    • delta: dump stride passed to the extractor.

    • rebin: rebin toggle (0 off, 1 on for x2 coarsening).

    • partition: Slurm partition name (#SBATCH -p).

  2. Check get_rprofs.job for any site-specific directives (time limit, account, etc.).

  3. Run:

python3 submit_rprofs.py

Notes:

  • submit_rprofs.py rewrites #SBATCH -p, #SBATCH -n, and the python3 ... line in get_rprofs.job for each submitted chunk.

Output

For each processed dump, the script writes:

  • RPROFS_<nth snapshot>.npz

Stored fields include:

  • time: simulation time for the snapshot.

  • geometry: geometry string from the grid metadata.

  • use_internal_boundaries: boundary mode flag.

  • sdims: number of spatial dimensions.

  • dd: dictionary of radial mean profiles and correlations (thermodynamic, velocity, gravity, diffusion, reaction/source terms, optional MHD and network terms when present).

Computed profiles (dd keys, physical names + formulas):

Here, \(\langle \cdot \rangle\) is the radial Reynolds average, \(i\) indexes species/reactions, and \(h = e_{\mathrm{int}} + P/\rho\). All formulas below use inline $...$ math syntax supported by GitHub Markdown.

  • r: radial coordinate, \(r\).

  • area: shell/annulus area, \(A(r)\).

  • gr_bar: radial gravitational acceleration, \(\langle g_r \rangle\).

  • epot_bar: gravitational potential, \(\langle \Phi \rangle\).

  • kappa_bar: opacity, \(\langle \kappa \rangle\).

  • edot_bar: external/source heating-cooling rate density, \(\langle \dot{e} \rangle\).

  • rho_bar: mass density, \(\langle \rho \rangle\).

  • P_bar: pressure, \(\langle P \rangle\).

  • T_bar: temperature, \(\langle T \rangle\).

  • s_bar: specific entropy, \(\langle s \rangle\).

  • abar_bar: mean mass number (Abar), \(\langle \bar{A} \rangle\).

  • Ye_bar: electron fraction, \(\langle Y_e \rangle\).

  • zbar_bar: mean charge number (Zbar), \(\langle \bar{Z} \rangle = \langle Y_e\bar{A} \rangle\).

  • rho_rho_bar: density second moment, \(\langle \rho^2 \rangle\).

  • T_T_bar: temperature second moment, \(\langle T^2 \rangle\).

  • P_P_bar: pressure second moment, \(\langle P^2 \rangle\).

  • s_s_bar: entropy second moment, \(\langle s^2 \rangle\).

  • abs_vel_bar: speed magnitude, \(\langle |\mathbf{v}| \rangle\).

  • abs_vh_bar: tangential speed magnitude, \(\langle |\mathbf{v}_h| \rangle\).

  • rho_vr_bar: radial mass flux, \(\langle \rho v_r \rangle\).

  • rho_eint_bar: internal energy density, \(\langle \rho e_{\mathrm{int}} \rangle\).

  • rho_ekin_bar: kinetic energy density, \(\langle \rho e_{\mathrm{kin}} \rangle\).

  • rho_etot_bar: total energy density, \(\langle \rho e_{\mathrm{tot}} \rangle\).

  • rho_h_bar: enthalpy density, \(\langle \rho h \rangle\).

  • rho_s_bar: entropy density proxy, \(\langle \rho s \rangle\).

  • rho_eint_vr_bar: radial internal-energy flux, \(\langle \rho e_{\mathrm{int}} v_r \rangle\).

  • rho_ekin_vr_bar: radial kinetic-energy flux, \(\langle \rho e_{\mathrm{kin}} v_r \rangle\).

  • rho_etot_vr_bar: radial total-energy flux, \(\langle \rho e_{\mathrm{tot}} v_r \rangle\).

  • rho_h_vr_bar: radial enthalpy flux, \(\langle \rho h v_r \rangle\).

  • rho_s_vr_bar: radial entropy flux proxy, \(\langle \rho s v_r \rangle\).

  • div_vel_bar: velocity divergence, \(\langle \nabla \cdot \mathbf{v} \rangle\).

  • P_div_vel_bar: compressional work term, \(\langle P\,\nabla \cdot \mathbf{v} \rangle\).

  • iT_bar: inverse temperature, \(\langle T^{-1} \rangle\).

  • vr_bar: radial velocity, \(\langle v_r \rangle\).

  • abar_vr_bar: radial transport of Abar, \(\langle \bar{A} v_r \rangle\).

  • zbar_vr_bar: radial transport of Zbar, \(\langle \bar{Z} v_r \rangle\).

  • P_vr_bar: pressure-velocity correlation, \(\langle P v_r \rangle\).

  • T_vr_bar: temperature-velocity correlation, \(\langle T v_r \rangle\).

  • rhovel_g_bar: gravitational power density, \(\langle \rho\,(\mathbf{g}\cdot\mathbf{v}) \rangle\).

  • vel_g_bar: specific gravitational power, \(\langle \mathbf{g}\cdot\mathbf{v} \rangle\).

  • dTdr_bar: radial temperature gradient, \(\langle \partial_r T \rangle\).

  • Krad_bar: radiative conductivity, \(\langle K_{\mathrm{rad}} \rangle\).

  • Krad_dTdr_bar: conductive transport term, \(\langle K_{\mathrm{rad}}\,\partial_r T \rangle\).

  • div_frad_iT_bar: radiative heating/cooling over temperature, \(\langle \frac{\nabla\cdot\mathbf{F}_{\mathrm{rad}}}{T} \rangle\).

  • edot_nuc_bar: nuclear heating rate density, \(\langle \dot{e}_{\mathrm{nuc}} \rangle\).

  • edot_reacs_bar: per-reaction heating rate density (array), \(\langle \dot{e}_{\mathrm{reac},i} \rangle\).

  • edot_neu_bar: neutrino cooling/heating rate density, \(\langle \dot{e}_{\nu} \rangle\).

  • edot_nuc_iT_bar: nuclear heating over temperature, \(\langle \frac{\dot{e}_{\mathrm{nuc}}}{T} \rangle\).

  • edot_neu_iT_bar: neutrino term over temperature, \(\langle \frac{\dot{e}_{\nu}}{T} \rangle\).

  • edot_tot_iT_bar: total source term over temperature, \(\langle \frac{\dot{e}_{\mathrm{nuc}}+\dot{e}_{\nu}}{T} \rangle\).

  • eps_nuc_bar: specific nuclear heating rate, \(\langle \epsilon_{\mathrm{nuc}} \rangle\).

  • eps_reacs_bar: per-reaction specific heating rate (array), \(\langle \epsilon_{\mathrm{reac},i} \rangle\).

  • eps_neu_bar: specific neutrino cooling/heating rate, \(\langle \epsilon_{\nu} \rangle\).

  • eps_nuc_iT_bar: specific nuclear term over temperature, \(\langle \frac{\epsilon_{\mathrm{nuc}}}{T} \rangle\).

  • eps_neu_iT_bar: specific neutrino term over temperature, \(\langle \frac{\epsilon_{\nu}}{T} \rangle\).

  • eps_tot_iT_bar: total specific source term over temperature, \(\langle \frac{\epsilon_{\mathrm{nuc}}+\epsilon_{\nu}}{T} \rangle\).

  • rho_X_bar: species mass density (array over species), \(\langle \rho X_i \rangle\).

  • rho_X_X_bar: species density second moment (array over species), \(\langle \rho X_i^2 \rangle\).

  • rho_X_X_vr_bar: radial transport of species second moment (array over species), \(\langle \rho X_i^2 v_r \rangle\).

  • rho_X_vr_bar: radial species mass flux (array over species), \(\langle \rho X_i v_r \rangle\).

  • rho_dXdt_bar: species source term density (array over species), \(\langle \rho\,\dot{X}_i \rangle\).

  • rho_X_dXdt_bar: species production/destruction correlation (array over species), \(\langle \rho X_i\dot{X}_i \rangle\).

  • rho_vr_vr_bar: radial Reynolds stress component, \(\langle \rho v_r^2 \rangle\).

  • rho_vt1_bar: tangential momentum density (component 1), \(\langle \rho v_{t1} \rangle\).

  • rho_vt1_vt1_bar: tangential Reynolds stress (component 1), \(\langle \rho v_{t1}^2 \rangle\).

  • rho_vt2_bar: tangential momentum density (component 2, 3D), \(\langle \rho v_{t2} \rangle\).

  • rho_vt2_vt2_bar: tangential Reynolds stress (component 2, 3D), \(\langle \rho v_{t2}^2 \rangle\).

  • emag_bar: magnetic energy density, \(\langle e_{\mathrm{mag}} \rangle = \langle \frac{|\mathbf{B}|^2}{2} \rangle\).

  • abs_br_bar: radial magnetic-field strength, \(\langle |B_r| \rangle\).

  • abs_bh_bar: tangential magnetic-field strength, \(\langle |\mathbf{B}_h| \rangle\).

Quick check:

import numpy as np

f = np.load("RPROFS_100.npz", allow_pickle=True)
print(f["time"], f["geometry"], f["sdims"])
dd = f["dd"].item()
print(dd.keys())