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pyAutoMR

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The method used by this program is quite similar to MOKIT. However, we try to do everything with PySCF and without Gaussian.

This program aims to do:

  • HF guess strategy
  • automatic guess for CASSCF/GVB/SUHF
  • interface for post-MR

Installation

Pre-requisites

  • tomli
  • PySCF
  • MOKIT (optional, no need to fully compile, only autopair is needed)
  • ExSCF (optional, for SUHF)
  • pyNOF (optional, for GVB)

Install

  • pip install pyAutoMR
  • Or, git clone and add /path/to/pyAutoMR to your PYTHONPATH

Features

  • UHF -> UNO (-> PM LMO -> assoc rot) (-> GVB) -> CASSCF
  • UHF -> SUHF -> CASSCF
  • RHF (-> vir MO projection -> PM LMO -> pairing) (-> GVB ) -> CASSCF
  • CASSCF -> MC-PDFT
  • CASSCF(dry run) -> SA-CASSCF

UHF, RHF can be auto-detected.

Utilities

  • guess for UHF/UKS
    • mix
    • fragment
    • from_fch
    • flipspin (by lmo or by site)
  • internal stability for RHF/RKS, UHF/UKS, ROHF/ROKS
    • optimize wavefunction until stable
  • dump CASCI coefficients
  • dump (active) orbital compositions

Quick Start

from automr import guess, autocas

xyz = 'N 0.0 0.0 0.0; N  0.0 0.0 1.9' 
bas = 'cc-pvdz'

mf = guess.from_frag(xyz, bas, [[0],[1]], [0,0], [3,-3], cycle=50)
mf = guess.check_stab(mf)

mf2 = autocas.cas(mf)

Citation

Please cite pyAutoMR as

Shirong Wang, pyAutoMR, https://github.com/jeanwsr/pyAutoMR (accessed month day, year)

and cite every program called by pyAutoMR, such as PySCF, MOKIT, mrh, etc.

Metadata

Release files for pyAutoMR 0.3.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pyAutoMR 0.3.1
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pyautomr-0.3.1.tar.gz 31.6 kB Details

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Table of built distributions (wheels) for pyAutoMR 0.3.1
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pyautomr-0.3.1-py3-none-any.whl Python 3 none any Details

Total release size: 65.3 kB

Release files / pyautomr-0.3.1.tar.gz

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