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McFAST v0.1.11
Utilities and accelerated functions designed for use by the McFACTS team at CUNY.
Functions currently fully tested for integration:
- tau_inc_dyn_helper
- tau_ecc_dyn_helper
- gw_strain_helper
- analytical_kick_velocity_helper
- merged_orb_ecc_helper
- torque_mig_timescale_helper
- generate_r
- shock_luminosity_helper
- jet_luminosity_helper
- encounters_prograde_sweep_helper
- si_from_r_g_helper
- r_g_from_units_helper
- r_schwarzschild_of_m_helper
- bh_near_smbh
- gw_hardening
Functions currently in testing for integration: star_wind_mass_loss_helper accrete_star_mass_helper
Example: Tau Incline/Eccentricity
In order to accelerate the tau_inc_dyn and tau_ecc_dyn functions in mcfacts/physics/disk_capture.py, we provide tau_inc_dyn_helper and tau_ecc_dyn_helper functions that perform the vectorized array calculations in an optimized Rust function. The example implementation for tau_inc_dyn_optimized follows: it has the same call signature, takes the same inputs, and provides the same output as tau_inc_dyn, but is 2-3x faster.
This function and its ecc variant can be further optimized by speeding up or eliminating the calls to si_from_r_g, which now make up the bulk of the runtime in each function (approximately 2/3rds).
In particular, the tau_semi_lat functionality in tau_ecc_dyn is sped up at least 120x, with tau_semi_lat initially being timed at 6 seconds, while the tau_ecc_dyn_helper functionality that subsumes it is timed at 0.05 seconds.
def tau_inc_dyn_optimized(smbh_mass, disk_bh_retro_orbs_a, disk_bh_retro_masses, omega, ecc, inc, disk_surf_density_func, r_g_in_meters):
"""Computes inclination damping timescale from actual variables; used only for scaling.
Uses Rust-accelerated helper functions for the calculation: compare to tau_inc_dyn
"""
# throw most things into SI units (that's right, ENGINEER UNITS!)
# or more locally convenient variable names
SI_smbh_mass = smbh_mass * u.Msun.to("kg") # kg
SI_semi_maj_axis = si_from_r_g(smbh_mass, disk_bh_retro_orbs_a, r_g_defined=r_g_in_meters).to("m").value
SI_orbiter_mass = disk_bh_retro_masses * u.Msun.to("kg") # kg
cos_omega = np.cos(omega)
disk_surf_res = disk_surf_density_func(disk_bh_retro_orbs_a)
tau_i_dyn = tau_inc_dyn_helper(SI_smbh_mass, SI_orbiter_mass, ecc, inc, cos_omega, disk_surf_res, SI_semi_maj_axis)
assert np.isfinite(tau_i_dyn).all(), \
"Finite check failure: tau_i_dyn"
return tau_i_dyn
Merge Tree
For M. McCarthy's black hole merge tracking feature.
import mcfast
from mcfast import MergeForest
# creates a forest of all black holes
forest = MergeForest("./data/", "galaxy_state_*")
bh_uuid: str = "2b422064-0a84-4687-a542-395dcb61cd4f"
# get the immediate child of a given UUID, if the UUID is valid
descendant_uuid = forest.get_descendant(bh_uuid)
# get the immediate parents of a given UUID, if the UUID is valid
(parent1_uuid, parent2_uuid) = forest.get_parents(bh_uuid)
# get the full ancestry list of a given UUID (in DFS order),
# assuming the UUID has ancestors
ancestor_list = forest.get_ancestors(bh_uuid)
# get the full list of black holes between the UUID and
# the final product (root)
descent_path = forest.get_lineage_to_root(bh_uuid)
# get the generation of a given UUID, where an initialized BH is generation 0
# note: implementation doesn't fully line up with existing
# reference implementation, under review
generation = forest.get_generation(bh_uuid)
# get all 'root' black holes (products remaining at the final tick)
roots = forest.roots()
# get all 'leaf' black holes (initialized BHs with no ancestors)
leaves = forest.leaves()
# get all 'singleton' black holes (neither ancestors nor children)
singletons = forest.singletons()
if forest.contains(bh_uuid):
print("It exists!")
else:
print("It doesn't exist!")
# get total number of nodes in the 'forest'
total = len(forest)
# serialize and deserialize with pickle
import pickle
# Save now
with open("forest.pkl", "wb") as f:
pickle.dump(forest, f)
# Load later
with open("forest.pkl", "rb") as f:
restored = pickle.load(f)
# sample: 330-node forest serializes down to 16kb
1 maintainer
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| Download URL | mcfast-0.1.11-cp310-cp310-macosx_11_0_arm64.whl |
|---|---|
| Size | 444.6 kB |
| Tags | CPython 3.10 macOS 11.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
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twine/7.0.0 CPython/3.13.14
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Transparency logRelease files / mcfast-0.1.11-cp310-cp310-macosx_10_12_x86_64.whl
Inconsistent provenance
This file belongs to a release with inconsistent provenance: the files in this release originate from different repositories or configurations.
We recommend inspecting each repository and configuration before proceeding. View details.
| Download URL | mcfast-0.1.11-cp310-cp310-macosx_10_12_x86_64.whl |
|---|---|
| Size | 456.7 kB |
| Tags | CPython 3.10 macOS 10.12+ x86-64 |
|
SHA-256 checksum How to use checksums |
85991009585847721a0203d544391ec3488ef32a5aa082f9aba27a53d088695f
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|
BLAKE2b-256 checksum How to use checksums |
0fc8039a3454196f1fafa7ca24340c0c9cb7756d0cafd3a0f420829c21a32ef4
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
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Transparency logSecurity for mcfast 0.1.11
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
Inconsistent provenance
The release files originate from multiple, inconsistent configurations.
While this could reflect a legitimate choice by the project maintainers, it may also indicate that the release has been compromised.
Configuration
- 5 files mac.yml
- 4 files windows.yml
- 4 files mac_x86.yml
- 4 files ubuntu.yml
Attestation for mcfast-0.1.11.tar.gz
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 9, 2026.
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