QuantyLF 0.1.22

QuantyLF is a libary to help manage Liegand Field simulations in Quanty.

QuantyLF

This is a libary to run ligand field caclulations using Quanty.

Requirements

Python 3.10 or newer needs to be installed

Installation

Install the package using the following command

$ pip install QuantyLF

Example

Prepare directory

Prepare the experimental XAS without header. The RIXS should all be combined in one file and the first lines needs to include excitation energies with preceeding 0. All values should be sperated by blanks. F.e.:

XAS_Exp.dat

629.843864705601  0.0008603675330224954
630.078187284962  0.0010035145462600522
630.260276168771  0.00034208577301302203
630.513327671302  0.0005305215326067531
...               ...

RIXS_Exp.dat

0 638 639.35
-5.183268710569939230e+01 0.000000e+00 0.000000e+00
-5.173604120400693063e+01 0.000000e+00 0.000000e+00
-5.163939530231446184e+01 0.000000e+00 0.0000000+00
...                       ...          ...

Setup python file

An example for how the python script (QuantyFittingLF.py) could look like, is shown below

# import package
from QuantyLF.QuantyLF import QuantyLF

# create new instance
quantyLF = QuantyLF()
# set custom quanty command
quantyLF.set_quanty_command('../Quanty_macOS', 'Darwin')

# load experimental data including excitation energies
quantyLF.load_exp_xas('XAS_Exp.dat')
quantyLF.load_exp_rixs('RIXS_Exp.dat')

# configure edge jump
# set display to True to see a plot of experimental data along edge jump (display has to be set to false for calculation)
quantyLF.config_edge_jump([[637.7, 0.14, 4], [648.2, 0.006, 8]], [600, 700,], display=False)

# see available cases
print(quantyLF.available_cases())
# load case and print parameters for fitting
quantyLF.load_case('D3h_3d', manual=True)

# Set up ion and oxidation state
quantyLF.add_par('ion', 22, from_file=False)
quantyLF.add_par('oxy', 4, from_file=False)
quantyLF.add_par('Gamma1', 0.4120250470353196, [0.4, 1])

# Crystal field contribution in D4h symmetry
quantyLF.add_par('tenDq', 0.19, [-0.2, 0.2])
quantyLF.add_par('tenDqF', 0.6815489483432551, [0.01, 1.0])

# Destruction parameter
quantyLF.add_par('Ds', 0.999, [0.1, 1])
quantyLF.add_par('Dt', 0.99, [0.1, 1])
quantyLF.add_par('DsF', 0.999, [0.1, 1])
quantyLF.add_par('DtF', 0.999, [0.1, 1])

# Multiplet contribution
# Spin orbit coupling
quantyLF.add_par('zeta_2p', 1.0196625781428472, [0.8, 1.02])
quantyLF.add_par('zeta_3d', 0.8403012992370478, [0.8, 1.02])
quantyLF.add_par('Xzeta_3d', 1.0, [0.8, 1.02])

# Slater integrals (Coulomb repulsion/exchange correlation)
quantyLF.add_par('Fdd', 0.9397729329705585, [0.8, 1.0])
quantyLF.add_par('XFdd', 0.8137253445941214, [0.8, 1.0])
quantyLF.add_par('Fpd', 0.8098173584848158, [0.8, 1.0])
quantyLF.add_par('Gpd', 0.8053014352519605, [0.8, 1.0])


# Ligand field contribution
# on-site energies (usually drops out of the equation in crystal field theory)
quantyLF.add_par('Udd', 6.543685631427877, [2.0, 7.0])
quantyLF.add_par('Upd_Udd', 4.001467895225598, [0.5, 5.0])

# Crystal field contribution of ligand site
quantyLF.add_par('tenDqL', 0.022975132006965073, [0.01, 1.0])

# Charge transfer contribution
quantyLF.add_par('Delta', 4.040660314729548, [1.0, 5.0])

# Hybridization
quantyLF.add_par('VfScale', 0.9775495515653867, [0.8, 1.0])


# # XAS and RIXS broadening
quantyLF.add_broadening('XAS', [[-3.7, 0.5], [3, 0.7], [9, 0.7]], gamma=0.5)
quantyLF.add_broadening('RIXS', [[0, 0.3], [2.7, 0.5], [8, 1]])

# Run calculation in 'RIXS' mode
quantyLF.fit('RIXS')

Running calculation using a SLURM job

Create a job file in this style:

#!/bin/bash
#SBATCH --job-name={name} # Job name
#SBATCH --mail-type=ALL                 # Mail events (NONE, BEGIN, END, FAIL, ALL)
#SBATCH --mail-user={mail}  # Where to send mail
#SBATCH --ntasks=1                      # Run a single task
#SBATCH --cpus-per-task=32              # Number of CPU cores per task
#SBATCH --mem=4G                   # Total memory limit
#SBATCH --time=00:30:00                 # Time limit hrs:min:sec
#SBATCH --output=pyRIXS_03G_%j.out          # Standard output and error log

# Load required modules; for example, if your program was
# compiled with Intel compiler, use the following·
# module load intel
#module load gentoo/2023
module load StdEnv/2023
module load python/3.11.5
module load scipy-stack/2023b

virtualenv --no-download $SLURM_TMPDIR/env
source $SLURM_TMPDIR/env/bin/activate
pip install --no-index --upgrade pip
pip install --no-index joblib
pip install -U lmfit
pip install --no-index h5py
pip install --no-index matplotlib
pip install --no-index scipy
pip install https://github.com/CMM02/QuantyLF/archive/refs/heads/main.zip


#export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK
srun python QuantyFittingLF.py #>> print_1
echo "Program finished with exit code $? at: `date`"
exit 0

Run calculation on computing cluster with SLURM job system

$ sbatch run.job

Documenation

config edge jump

"""
Configure the edge jump for the XAS calculation. The edge jump is modelled as a arctan function.

Parameters
----------
edge_jumps: list of 3-element lists
    List of edge jumps. Each element in the list is a list of 3 elements: [position, jump, slope]
x_range: list of floats
    The range of x values to model the edge jump over
y_offset: float, optional
    The y offset of the edge jump
display: bool, optional
    If True, the edge jump will be displayed along with the experimental XASs
"""
config_edge_jump(edge_jumps, x_range, y_offset=0, display=False)

available_cases

 """
Return the available cases for which the Quanty calculations are available

Returns
-------
List of available cases
"""
available_cases()

load_case

"""
Load a Quanty case

Parameters
----------
case: str
    Name of the case to load (pattern: {point_group}_{orbitals})
manual: bool, optional
    If True, the manual for the case is displayed (list of parameters available for fitting)
"""      
load_case(case, manual=False)

load_custom_case

"""
Load a custom Quanty case from a file

Parameters
----------
case_file: str
    Path to the Quanty case file
"""
load_custom_case(case_file)

add_par

"""
Add a parameter to the model

Parameters
----------
name: str
    Name of the parameter
init_val: float
    Initial value of the parameter
interv: list of 2 floats, optional
    List of two values, lower and upper bounds of the parameter
from_file: bool, optional
    If True (default True), the parameter is read from a file (file value overrides init_val)
"""
add_par(name, init_val, interv = None, from_file = True)

add_broadening

"""
Add broadening to the XAS or RIXS data

Parameters
----------
type: str
    "XAS" or "RIXS"
lorenzians: list of 2-element lists
    List of lorenzian broadening parameters (center, width)
gamma: float, optional
    Guassian broadening parameter
"""
add_broadening(type, lorenzians, gamma=0)

fit

"""
Fit the parameters of the model to the experimental data

Parameters
----------
mode: str
    "XAS" or "RIXS". If "XAS", only the XAS data is fitted. If "RIXS", both XAS and RIXS data is fitted
"""
fit(type)

load_exp_xas

"""
Load the experimental XAS data from a file (no header, two columns: energy, intensity)

Parameters
----------
path: str
    Path to the file containing the experimental XAS data
"""
load_exp_xas(path)

load_exp_rixs

"""
Load the experimental RIXS data from a file (no header, first row: resonance energies, rest of the rows: energy, intensity)

Parameters
----------
path: str   
    Path to the file containing the experimental RIXS data
RIXS_energies: list of floats, optional
    List of resonance energies for which the RIXS data is available (if not provided, the first row of the file is used to extract the resonance energies)
"""
load_exp_rixs(path, RIXS_energies)

set_quanty_command

"""
Set the path to the Quanty executable (default is 'Quanty' added to path)

Parameters
----------
command: str
Path to the Quanty executable
platform: str, optional
Platform for which the path is being set (if not set the current platform is used)
"""
set_quanty_command(command, for_platform=None)

set_par_value

"""
Set custom path to the parameter file (default: ParVals.txt)
!Warning: Should not be changed for default cases!

Parameters
----------
par_file: str
    Path to the parameter file
"""
set_par_file(par_file)

"""
Exports all parameters to a csv file. All scaling factors will be applied.

Parameters
----------
path: str, optional
    Path and filename to be saved to
ignore_pars: list of str, optional
    List of parameters to ignore for export
"""
export_pars(path='ExportedPars.csv', ignore_pars = ['XAS_Gamma', 'XAS_Broad', 'RIXS_Gamma', 'RIXS_Broad', 'RIXS', 'VfScale', 'Gamma1'])

Develop new cases

To develop new cases, the struture of the other .lua-files can be used. Clone the GitHub repository and checkout the dev branch. Copy the file and the utils directory from this directory into the directory of choice. Make the changes wanted. After that add the case file to the same directory. Increment the version number in the setup.cfg and push the dev branch. On GitHub create a pull request from dev to main and merge. Check if the publishing action runs through.