Distortion Distribution Analysis enabled by Fragmentation (D2AF)
Description
Distortion Distribution Analysis enabled by Fragmentation
Distortion energy visualization of one/multiple conformers relative to the reference structure(eg: global minima). Subsystem extracted based on ONIOM methods(link atoms and scale factors). The subsystem can be defined using three methods:
* 1. atomic/fragments resolution based on fragmentations
* 2. bond and angle resolution based on internal coordinates (bond & angle)
* 3. combination of 1 & 2
Installation
conda env create -f environment.yml
pip install D2AF-x.x.x-py3-none-any.whl
requirements
D2AF:
- python=3.9
- numpy
- pandas
- openbabel
- openpyxl
[Gaussian](https://gaussian.com/):
- Gaussian03/09/16
[xTB](https://xtb-python.readthedocs.io/en/latest/#):
- xtb-python
[ANI](https://aiqm.github.io/torchani/index.html):
- torchvision
- torch
- torchani
[MLatom](http://mlatom.com/):
- matplotlib
- tensorboard
- torchvision
- torch
- torchani
- MLatom (3.0.0))
- scipy
- pyh5md
- statsmodels
quantum chemical calculation packages:
Gaussian: Gaussian03,09,16
xTB: xTB-python
ANI: torchani
Mlatom: AIQM1
Usage
D2AF -inp input.inp
D2AF -h
The -inp input.inp are recommended
example of inp file showed in example directory
calculator available:
['g03', 'g09', 'g16','gfn1-xtb', 'gfn2-xtb','ani-1x', 'ani-2x', 'ani-1ccx', 'aiqm1']
inp file example:
ref = ref.gjf
conf = conf.gjf
method = int
cpu = int
pal = int
calculator = g16
scale = e/10.0 (optional)
fraglist (optional: only method = 1/3 required)
1-2,4-6
3
coordination (optional: only method = 3 available)
3-5
include (optional: only method = 2/3 and extra bond/angles (no connection ) are needed)
1 2
1 2 3
exclude (optional: only method = 2/3 and extra bond/angles are not need)
4 7
4 7 9
charge (optional: only if atomic charge not zero required)
5 1
spin (optional: only if atomic charge not zero required)
3 1
preparations
**ref**: ref.gjf-reference stucture in Gaussian file, containing **method lines**, **cartesian coordinates** and **connectivity**
* the connectivity (bond order) values should be **1.0, 2.0, 3.0**!
* **1.5 is forbidden**, it should be modified before computations!
**conf**: conf.gjf/.xyz conformer structure, and multiple structure in one xyz file is acceptable
**method**: 1 for framentation method, 2 for bond/angle method, 3 1+2
**cpu**: number of cpu for subsystem computation
**pal**: number of paralle subsystem computations (available for Gaussian, xTB)
**calculator**: calculator (Gaussian, xTB, ANI, AIQM1) for subsystem computation
**scale**: log scale factor for pymol visualization
**fraglist**: method =1/3, define the fragmentation list
**coordination**: method =3, define the coordination center (similar to fraglist)
**include**: method =2/3, additional bond/angle for non-connected atoms
**exclude**: method =2/3, exclude the bond/angle
**charge**: define the atomic charge if not 0
**spin**: define the atomic spin if not 0 (using integer: spin * 2)
Including in D2AF tools:
**autofragment.py** `autofragment`
auto fragmentation!
input: xyz file/ or Gaussian gjf file with/without connectivity
ouput: gjf file with connectivity， fraglist for M1, pymol script for visualization
**atompair.py** `atompair`
pair atom between two gjfs with same connectivity info but different label order
input: gjf1 gjf2 Gaussian files with connectivity
ouput: new gjf2 with same atom label to gjf1
the symmetric atoms can not be separated (warning information)
**pml_str.py** `pml_str`
add addtional command to the pml files such as `bond id x, id x` and `unbond id x, id x` (using `;` to separate lines) in a `""` **not** `''`
**write_run_pml.py** `write_run_pml`
write Pymol run pml to generate strain png files for multi-conformer case (IRC/MD).
inputs: `method number` eg.: `M2 125`
**multi_mov.py** `multi_mov`
after Run Pymol pml to generate strain png files for multi-conformer case (IRC/MD). Generate electronic energy (MEP) and strain energy figure for each conformer, then combine them with stran visualization png to generate a movie
inputs: `energy_xlsx type(IRC/MD)` where xlsx file including ` pos, Energy, Strain M1/M2/M3 columns`
**Combine_multi_conf.py** `Combine_multi`
Similar to Combine_fig_MS.py, but for multiple conformers.
inputs: `conf_id1 conf_id2 ... conf_idn` combine selected confs
**Combine_fig_MS.py/Combine_fig_ppt.py** `Combine_fig_MS/Combine_fig_ppt`
combine multiple pngs (M1, M2, M3) into one png for publication (label a/b/c/d) or ppt (file names)
Citation