Computational Chemistry Input Generator
Project description
Computational Chemistry Input Generator
ccinput
is an application to generate input files for computational chemistry software.
Example usage:
$ ccinput gaussian opt M062X -bs def2tzvp -f ethanol.xyz -n 8 --mem 32G
%chk=calc.chk
%nproc=8
%mem=32000MB
#p opt M062X/Def2TZVP
File created by ccinput
0 1
C -1.31970000 -0.64380000 0.00000000
H -0.96310000 -1.65260000 0.00000000
H -0.96310000 -0.13940000 -0.87370000
H -2.38970000 -0.64380000 0.00000000
C -0.80640000 0.08220000 1.25740000
H -1.16150000 1.09160000 1.25640000
H -1.16470000 -0.42110000 2.13110000
O 0.62360000 0.07990000 1.25870000
H 0.94410000 0.53240000 2.04240000
$ ccinput orca sp DLPNO-CCSDT -bs cc-pVTZ -f *.xyz -o .inp -n 32 --mem 250GB --parse_name
*** No C auxiliary basis set specified, using cc-pVTZ ***
*** No C auxiliary basis set specified, using cc-pVTZ ***
*** No C auxiliary basis set specified, using cc-pVTZ ***
*** No C auxiliary basis set specified, using cc-pVTZ ***
Input file written to carbo_cation.inp
Input file written to CH4.inp
Input file written to ethanol.inp
Input file written to H2.inp
$ cat H2.inp
!SP DLPNO-CCSD(T) cc-pVTZ cc-pVTZ/C
*xyz 0 1
H -1.43860000 -0.26820000 0.00000000
H -2.03860000 -0.26820000 0.00000000
*
%MaxCore 7812
%pal
nprocs 32
end
$ cat carbo_cation.inp
!SP DLPNO-CCSD(T) cc-pVTZ cc-pVTZ/C
*xyz 1 1
C -2.90770000 1.66310000 0.00000000
H -2.55100000 2.16750000 0.87370000
H -3.97770000 1.66310000 0.00000000
H -2.55100000 2.16750000 -0.87370000
*
%MaxCore 7812
%pal
nprocs 32
end
ccinput
can also be used as python library:
>>> from ccinput.wrapper import gen_input
>>> inp = gen_input(software="orca", type="ts", method="PBEh-3c", file="ethanol.xyz", nproc=16, solvent="ethanol", solvation_model="SMD")
*** No solvation radii specified; using default radii ***
>>> print(inp)
!OPTTS PBEh-3c
*xyz 0 1
C -1.31970000 -0.64380000 0.00000000
H -0.96310000 -1.65260000 0.00000000
H -0.96310000 -0.13940000 -0.87370000
H -2.38970000 -0.64380000 0.00000000
C -0.80640000 0.08220000 1.25740000
H -1.16150000 1.09160000 1.25640000
H -1.16470000 -0.42110000 2.13110000
O 0.62360000 0.07990000 1.25870000
H 0.94410000 0.53240000 2.04240000
*
%pal
nprocs 16
end
%cpcm
smd true
SMDsolvent "ethanol"
end
>>>
Installation
From PyPI
pip install ccinput
From Github
You can install the bleeding-edge version of ccinput
from Github:
pip install git+https://github.com/cyllab/ccinput
Usage
ccinput
supports a wide range of options, including different solvation radii, density fitting and multiple basis sets. As of now, Gaussian 16, ORCA 5 and xtb are supported, and more packages will be added in the future.
From the command line
Simply use the ccinput
command with the desired parameters:
usage: ccinput [-h] [--basis_set BASIS_SET] [--solvent SOLVENT] [--solvation_model SOLVATION_MODEL]
[--solvation_radii SOLVATION_RADII] [--custom_solvation_radii CUSTOM_SOLVATION_RADII]
[--specifications SPECIFICATIONS] [--density_fitting DENSITY_FITTING] [--custom_basis_sets CUSTOM_BASIS_SETS]
[--xyz XYZ] [--file FILE [FILE ...]] [--output OUTPUT] [--constraints CONSTRAINTS] [--freeze ATOM [ATOM ...]]
[--scan ATOM [ATOM ...]] [--from FROM] [--to TO] [--nsteps NSTEPS] [--step STEP] [--nproc NPROC] [--mem MEM]
[--charge CHARGE] [--mult MULT] [--parse_name] [--trust_me] [--d3 | --d3bj] [--name NAME]
[--aux_name AUX_NAME] [--header HEADER] [--save SAVE] [--preset [PRESET]] [--driver {none,ORCA,pysis}]
[--version] [--fragments FRAGMENTS]
[software] [type] [method]
More detailed information about each option can be obtained with the ccinput -h
command.
As Python library
The function gen_input
returns input files as a single strings with the correct whitespace.
>>> from ccinput.wrapper import gen_input
>>> inp = gen_input(...)
The input can also be directly written to a file using write_input
.
>>> from ccinput.wrapper import write_input
>>> write_input(filename, ...)
See the documentation for all options.
Contributing
We welcome all contributions to the project. This includes:
- Support for new packages (even if rudimentary)
- Support for new features of supported packages
- Correction or improvement of static data (like DFT functionals or basis sets)
Planned tasks are listed in the roadmap. This can be a good place to start when looking to contribute, although do not limit yourself to what is listed there. The contribution guidelines are detailed in CONTRIBUTING.md.
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