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Merge pull request #414 from bastonero/new/flare-interface
New active learning with AiiDA and FLARE
2 parents b36d5db + 2be60bd commit 35216ec

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‎.github/workflows/python-testsuite.yml‎

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cd CellConstructor
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pip install --no-build-isolation .
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cd ..
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git clone --depth 1 https://github.com/mir-group/flare.git flare
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cd flare
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pip install .
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cd ..
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pip install --no-build-isolation .
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‎.gitignore‎

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timer.json
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minim.dat
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otf_run*
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nohup.out
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disp_*
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_data_tmp_
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‎Examples/sscha_and_aiida/README.md‎

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# Instructions
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We provide here the script `run_aiida_sscha.py`, which performs a thermal expansion calculation using SSCHA and aiida-quantumespresso.
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We provide here some scripts to run SSCHA using AiiDA, FLARE machine-learning potential, and a combination of the two as on-the-fly active learning.
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It is preferable to execute the example that you already have some experience with both the SSCHA and AiiDA-QuantumEspresso codes. Nevertheless, you can try following the instructions and to run the example.
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* `run_aiida_sscha.py`, which performs a thermal expansion calculation using SSCHA and aiida-quantumespresso.
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* `run_flare_sscha.py`, which performs a thermal expansion calculation using SSCHA and FLARE machine-learning interatomic potential.
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* `run_aiida_flare_sscha.py`, which performs an on-the-fly active learning SSCHA calculation using aiida-quantumespresso for DFT and FLARE as the ML potential.
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It is preferable to execute the example that you already have some experience with both the SSCHA and AiiDA-QuantumESPRESSO codes. Nevertheless, you can try following the instructions and to run the example.
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## Installation
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We recommend to install all the packages via `mamba` (which is based on top of `conda`). After having installed `mamba`, you can simply run the following:
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We recommend to install all the packages via `mamba` (which is based on `conda`). After having installed `mamba`, you can simply run the following:
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```console
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> mamba create -n aiida-sscha -c conda-forge python gfortran libblas lapack openmpi julia openmpi-mpicc pip numpy scipy spglib aiida-core
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> pip install ase quippy-ase cellconstructor python-sscha aiida-quantumespresso aiida-pseudo
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> mamba activate aiida-sscha
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> mamba create -n sscha-aiida -c conda-forge python gfortran "blas=*=openblas" openblas lapack julia pip numpy scipy spglib pkg-config aiida-core
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> pip install ase cellconstructor python-sscha aiida-quantumespresso aiida-pseudo
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> mamba activate sscha-aiida
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```
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Then, you should configure an AiiDA profile and the pw.x code in order to use the example script (see also Prerequisites section).
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Then, you should configure an AiiDA profile in order to use the example script (see also Prerequisites section).
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For on-the-fly active learning you also need the FLARE package:
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```console
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> git clone --depth 1 https://github.com/mir-group/flare.git
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> cd flare
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> pip install .
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```
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## Prerequisites
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- `cellconstructor`
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- `aiida-core`
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- `aiida-quantumespresso`
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- (optional, for active learning) `mir-flare`
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For the AiiDA part, it is essential the dameon is running and you have:
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1. Configured a computer where to run the code (e.g. on your own laptop; see `aiida-core` docs for further details)
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## How-to run
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### SSCHA with the aiida-quantumespresso interface
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Open the `run_aiida_sscha.py` and change the data according to your needs and local installation. Then simply
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```console
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> nohup python run_aiida_sscha.py > run_aiida_sscha.log &
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```
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or a submit script at glance.
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### On-the-fly active learning SSCHA with aiida-quantumespresso and FLARE interface
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Open the `run_aiida_flare_sscha.py` and change the data according to your needs and local installation. Then simply
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```console
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> python run_aiida_flare_sscha.py > run_aiida_sscha.log
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```
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Usually an actual production run would take a while. We suggest to use instead
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```console
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> nohup python run_aiida_sscha.py > run_aiida_sscha.log &
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```
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or a submit script at glance.

‎Examples/sscha_and_aiida/Si-dynamical-matrix1‎

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Dynamical matrix file
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File generated with the CellConstructor by Lorenzo Monacelli
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1 2 0 1.8897259890000000 0.0000000000000000 0.0000000000000000 0.0000000000000000 0.0000000000000000 0.0000000000000000
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Basis vectors
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2.7154799999999999 2.7154799999999999 0.0000000000000000
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2.7154799999999999 0.0000000000000000 2.7154799999999999
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0.0000000000000000 2.7154799999999999 2.7154799999999999
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1 'Si ' 25597.9124185021937592
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1 1 -0.0000000000000004 0.0000000000000004 0.0000000000000004
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2 1 1.3577400000000002 1.3577400000000006 1.3577400000000004
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Dynamical Matrix in cartesian axes
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q = ( 0.000000000000 0.000000000000 0.000000000000 )
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1 1
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0.2590944141379855 0.0000000000000000 0.0000000000000001 0.0000000000000000 -0.0000000000000000 0.0000000000000000
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0.0000000000000001 0.0000000000000000 0.0000000000000002 0.0000000000000000 -0.2590944141379855 0.0000000000000000
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0.2590944141379858 0.0000000000000000 0.0000000000000001 0.0000000000000000 -0.0000000000000001 0.0000000000000000
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0.0000000000000001 0.0000000000000000 0.2590944141379858 0.0000000000000000 -0.0000000000000001 0.0000000000000000
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-0.0000000000000001 0.0000000000000000 -0.0000000000000001 0.0000000000000000 0.2590944141379858 0.0000000000000000
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Diagonalizing the dynamical matrix
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q = ( 0.000000000000 0.000000000000 0.000000000000 )
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***************************************************************************
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freq ( 1) = -0.00000009 [THz] = -0.00000305 [cm-1]
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( 0.699099 0.000000 -0.097697 0.000000 0.041428 0.000000 )
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( 0.699099 0.000000 -0.097697 0.000000 0.041428 0.000000 )
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freq ( 2) = 0.00000020 [THz] = 0.00000677 [cm-1]
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( 0.002505 0.000000 0.291167 0.000000 0.644372 0.000000 )
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( 0.002505 0.000000 0.291167 0.000000 0.644372 0.000000 )
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freq ( 3) = 0.00000026 [THz] = 0.00000855 [cm-1]
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( -0.106088 0.000000 -0.636928 0.000000 0.288216 0.000000 )
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( -0.106088 0.000000 -0.636928 0.000000 0.288216 0.000000 )
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freq ( 4) = 14.80188490 [THz] = 493.73766382 [cm-1]
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( -0.042416 0.000000 -0.451763 0.000000 -0.542320 0.000000 )
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( 0.042416 0.000000 0.451763 0.000000 0.542320 0.000000 )
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freq ( 5) = 14.80188490 [THz] = 493.73766382 [cm-1]
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( -0.515182 0.000000 0.391193 0.000000 -0.285579 0.000000 )
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( 0.515182 0.000000 -0.391193 0.000000 0.285579 0.000000 )
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freq ( 6) = 14.80188490 [THz] = 493.73766382 [cm-1]
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( -0.482481 0.000000 -0.377992 0.000000 0.352610 0.000000 )
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( 0.482481 0.000000 0.377992 0.000000 -0.352610 0.000000 )
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***************************************************************************

‎Examples/sscha_and_aiida/Si-dynamical-matrix2‎

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Dynamical matrix file
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File generated with the CellConstructor by Lorenzo Monacelli
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1 2 0 1.8897259890000000 0.0000000000000000 0.0000000000000000 0.0000000000000000 0.0000000000000000 0.0000000000000000
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Basis vectors
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2.7154799999999999 2.7154799999999999 0.0000000000000000
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2.7154799999999999 0.0000000000000000 2.7154799999999999
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0.0000000000000000 2.7154799999999999 2.7154799999999999
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1 'Si ' 25597.9124185021937592
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1 1 -0.0000000000000004 0.0000000000000004 0.0000000000000004
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2 1 1.3577400000000002 1.3577400000000006 1.3577400000000004
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Dynamical Matrix in cartesian axes
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q = ( -0.184129509332 0.000000000000 0.000000000000 )
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1 1
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0.3548752551952572 0.0000000000000000 0.0000000000000000 0.0000000000000000 -0.0000000000000000 -0.0000000000000000
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0.0000000000000000 -0.0000000000000000 0.2477607075541515 0.0000000000000000 0.0000000000000001 -0.0000000000000000
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0.0000000000000000 0.0000000000000000 -0.0000000000000000 0.0000000000000000 0.0000000000000000 -0.0000000000000000
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0.0000000000000000 0.0000000000000000 -0.2008555582082014 0.0000000087796757 -0.0000000000000002 0.0000000000000000
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0.3548752551952572 0.0000000000000000 0.0000000000000000 0.0000000000000000 -0.0000000000000000 -0.0000000000000000
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0.0000000000000000 -0.0000000000000000 0.2477607075541515 0.0000000000000000 -0.0000000000000001 -0.0000000000000000
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-0.0000000000000000 0.0000000000000000 -0.0000000000000001 0.0000000000000000 0.2477607075541518 0.0000000000000000
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Dynamical Matrix in cartesian axes
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q = ( 0.000000000000 0.000000000000 -0.184129509332 )
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1 1
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0.2477607075541515 0.0000000000000000 0.0000000000000000 -0.0000000000000000 -0.0000000000000000 0.0000000000000000
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0.0000000000000000 0.0000000000000000 0.2477607075541516 -0.0000000000000000 0.0000000000000001 -0.0000000000000000
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-0.0000000000000000 -0.0000000000000000 0.0000000000000001 0.0000000000000000 0.3548752551952568 0.0000000000000000
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1 2
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-0.0000000000000000 -0.0000000000000000 -0.2008555582082013 -0.0000000087796755 0.0000000000000000 0.0000000000000000
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-0.2008555582082013 -0.0000000087796755 -0.0000000000000002 -0.0000000000000000 0.0000000000000000 -0.0000000000000000
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-0.0000000000000001 -0.0000000000000000 0.0000000000000000 0.0000000000000000 0.0000000000000001 0.0000000000000000
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-0.0000000000000000 0.0000000000000000 -0.2008555582082013 0.0000000087796755 -0.0000000000000001 0.0000000000000000
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0.0000000000000000 -0.0000000000000000 0.0000000000000000 0.0000000000000000 0.0000000000000001 -0.0000000000000000
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0.0000000000000001 -0.0000000000000000 0.2477607075541518 0.0000000000000000 0.0000000000000000 -0.0000000000000000
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-0.0000000000000000 -0.0000000000000000 0.0000000000000000 0.0000000000000000 0.3548752551952572 0.0000000000000000
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Dynamical Matrix in cartesian axes
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q = ( 0.000000000000 -0.184129509332 0.000000000000 )
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1 1
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0.2477607075541516 -0.0000000000000000 0.0000000000000000 -0.0000000000000000 0.0000000000000000 -0.0000000000000000
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0.0000000000000000 0.0000000000000000 0.3548752551952573 -0.0000000000000000 0.0000000000000001 0.0000000000000000
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0.0000000000000000 0.0000000000000000 0.0000000000000001 -0.0000000000000000 0.2477607075541516 -0.0000000000000000
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1 2
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0.0000000000000000 -0.0000000000000000 0.0000000000000000 0.0000000000000000 -0.2008555582082014 -0.0000000087796755
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-0.0000000000000000 -0.0000000000000000 -0.0000000000000000 -0.0000000000000000 -0.0000000000000000 -0.0000000000000000
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-0.2008555582082015 -0.0000000087796755 0.0000000000000001 -0.0000000000000000 -0.0000000000000000 -0.0000000000000000
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2 1
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0.0000000000000000 0.0000000000000000 -0.0000000000000000 0.0000000000000000 -0.2008555582082015 0.0000000087796755
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0.0000000000000000 -0.0000000000000000 -0.0000000000000000 0.0000000000000000 0.0000000000000001 0.0000000000000000
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-0.2008555582082014 0.0000000087796755 -0.0000000000000000 0.0000000000000000 -0.0000000000000000 0.0000000000000000
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2 2
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0.2477607075541516 0.0000000000000000 -0.0000000000000000 0.0000000000000000 -0.0000000000000000 0.0000000000000000
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-0.0000000000000000 -0.0000000000000000 0.3548752551952571 -0.0000000000000000 0.0000000000000000 -0.0000000000000000
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-0.0000000000000000 -0.0000000000000000 0.0000000000000000 0.0000000000000000 0.2477607075541518 0.0000000000000000
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Diagonalizing the dynamical matrix
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q = ( -0.184129509332 0.000000000000 0.000000000000 )
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***************************************************************************
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freq ( 1) = 4.45331342 [THz] = 148.54652494 [cm-1]
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( -0.000000 0.000000 0.703431 0.000000 0.072005 0.000000 )
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( 0.000000 -0.000000 0.072005 -0.000000 0.703431 -0.000000 )
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freq ( 2) = 4.45331342 [THz] = 148.54652494 [cm-1]
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( 0.000000 -0.000000 -0.072005 -0.000000 0.703431 0.000000 )
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( -0.000000 0.000000 0.703431 -0.000000 -0.072005 0.000000 )
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freq ( 3) = 12.24928837 [THz] = 408.59222083 [cm-1]
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( -0.145074 0.000000 0.000000 -0.000000 -0.000000 0.000000 )
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( -0.989421 0.000000 0.000000 -0.000000 -0.000000 0.000000 )
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freq ( 4) = 12.24928837 [THz] = 408.59222083 [cm-1]
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( 0.989421 0.000000 -0.000000 -0.000000 -0.000000 0.000000 )
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( -0.145074 0.000000 -0.000000 -0.000000 0.000000 0.000000 )
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freq ( 5) = 13.77242792 [THz] = 459.39867995 [cm-1]
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( 0.000000 -0.000000 0.411585 -0.000000 -0.574977 0.000000 )
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( 0.000000 -0.000000 0.574977 -0.000000 -0.411585 0.000000 )
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freq ( 6) = 13.77242792 [THz] = 459.39867995 [cm-1]
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( 0.000000 -0.000000 0.574977 -0.000000 0.411585 -0.000000 )
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( 0.000000 0.000000 -0.411585 0.000000 -0.574977 0.000000 )
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***************************************************************************

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