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pyiron
Potentials Workshop 2021
Commits
56d057e8
Commit
56d057e8
authored
Mar 09, 2021
by
Jan Janssen
Browse files
Clean up day3
parent
8c04e90a
Changes
8
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day_3/Cu_training_archive.tar.gz
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File deleted
day_3/RuNNerMD.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"id": "suffering-touch",
"metadata": {},
"outputs": [],
"source": [
"from pyiron import Project"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "geological-bankruptcy",
"metadata": {},
"outputs": [],
"source": [
"pr = Project('md_run')"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "prompt-evaluation",
"metadata": {},
"outputs": [],
"source": [
"j = pr.create.job.Lammps(\"md\", delete_existing_job=True)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "governing-consortium",
"metadata": {},
"outputs": [],
"source": [
"j.potential = Project('../day_2/02-runner/runner_fit').load('fit').lammps_potential"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "authentic-moscow",
"metadata": {},
"outputs": [],
"source": [
"j.structure = pr.create.structure.ase_bulk('Cu', cubic=True).repeat(3)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "tamil-witch",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "af0fa5be14e94b06ba4ea70a958f5368",
"version_major": 2,
"version_minor": 0
},
"text/plain": []
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "543d34f0039747ddb1f27d54f817c71e",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"NGLWidget()"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"j.structure.plot3d()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "fatty-asbestos",
"metadata": {},
"outputs": [],
"source": [
"j.calc_md(n_ionic_steps=1000, temperature=500)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "under-shirt",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The job md was saved and received the ID: 13792062\n",
"CPU times: user 370 ms, sys: 58 ms, total: 428 ms\n",
"Wall time: 53 s\n"
]
}
],
"source": [
"%%time \n",
"j.run()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "liked-thomson",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "50d669a6ac55448699b1518b9be8d9dd",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"NGLWidget(max_frame=10)"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"j.animate_structure()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.9"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
%% Cell type:code id:suffering-touch tags:
```
python
from
pyiron
import
Project
```
%% Cell type:code id:geological-bankruptcy tags:
```
python
pr
=
Project
(
'md_run'
)
```
%% Cell type:code id:prompt-evaluation tags:
```
python
j
=
pr
.
create
.
job
.
Lammps
(
"md"
,
delete_existing_job
=
True
)
```
%% Cell type:code id:governing-consortium tags:
```
python
j
.
potential
=
Project
(
'../day_2/02-runner/runner_fit'
).
load
(
'fit'
).
lammps_potential
```
%% Cell type:code id:authentic-moscow tags:
```
python
j
.
structure
=
pr
.
create
.
structure
.
ase_bulk
(
'Cu'
,
cubic
=
True
).
repeat
(
3
)
```
%% Cell type:code id:tamil-witch tags:
```
python
j
.
structure
.
plot3d
()
```
%% Output
%% Cell type:code id:fatty-asbestos tags:
```
python
j
.
calc_md
(
n_ionic_steps
=
1000
,
temperature
=
500
)
```
%% Cell type:code id:under-shirt tags:
```
python
%%
time
j
.
run
()
```
%% Output
The job md was saved and received the ID: 13792062
CPU times: user 370 ms, sys: 58 ms, total: 428 ms
Wall time: 53 s
%% Cell type:code id:liked-thomson tags:
```
python
j
.
animate_structure
()
```
%% Output
day_3/export.csv
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,id,status,chemicalformula,job,subjob,project,timestart,timestop,totalcputime,computer,hamilton,hamversion,parentid,masterid
0,0,finished,,df1_A1_A2_A3_EV_elast_phon,/df1_A1_A2_A3_EV_elast_phon,Cu_training_archive/Cu_database,2021-02-08 10:33:52.341472,,,zora@cmti001#1,GenericJob,0.4,,
1,1,finished,,df3_10k,/df3_10k,Cu_training_archive/Cu_database,2021-02-08 10:33:53.993230,,,zora@cmti001#1,GenericJob,0.4,,
2,2,finished,,df2_1k,/df2_1k,Cu_training_archive/Cu_database,2021-02-08 10:33:54.435308,,,zora@cmti001#1,GenericJob,0.4,,
day_3/fit/input.nn
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### ####################################################################################################################
### This is the input file for the RuNNer tutorial (POTENTIALS WORKSHOP 2021-03-10)
### This input file is intended for release version 1.2
### RuNNer is hosted at www.gitlab.com. The most recent version can only be found in this repository.
### For access please contact Prof. Jörg Behler, joerg.behler@uni-goettingen.de
###
### ####################################################################################################################
### General remarks:
### - commands can be switched off by using the # character at the BEGINNING of the line
### - the input file can be structured by blank lines and comment lines
### - the order of the keywords is arbitrary
### - if keywords are missing, default values will be used and written to runner.out
### - if mandatory keywords or keyword options are missing, RuNNer will stop with an error message
###
########################################################################################################################
########################################################################################################################
### The following keywords just represent a subset of the keywords offered by RuNNer
########################################################################################################################
########################################################################################################################
########################################################################################################################
### general keywords
########################################################################################################################
nn_type_short 1 # 1=Behler-Parrinello
runner_mode 3 # 1=calculate symmetry functions, 2=fitting mode, 3=predicition mode
number_of_elements 1 # number of elements
elements Cu # specification of elements
random_seed 10 # integer seed for random number generator
random_number_type 6 # 6 recommended
########################################################################################################################
### NN structure of the short-range NN
########################################################################################################################
use_short_nn # use NN for short range interactions
global_hidden_layers_short 2 # number of hidden layers
global_nodes_short 15 15 # number of nodes in hidden layers
global_activation_short t t l # activation functions (t = hyperbolic tangent, l = linear)
########################################################################################################################
### symmetry function generation ( mode 1):
########################################################################################################################
test_fraction 0.10000 # threshold for splitting between fitting and test set
########################################################################################################################
### symmetry function definitions (all modes):
########################################################################################################################
cutoff_type 1
symfunction_short Cu 2 Cu 0.000000 0.000000 12.000000
symfunction_short Cu 2 Cu 0.006000 0.000000 12.000000
symfunction_short Cu 2 Cu 0.016000 0.000000 12.000000
symfunction_short Cu 2 Cu 0.040000 0.000000 12.000000
symfunction_short Cu 2 Cu 0.109000 0.000000 12.000000
symfunction_short Cu 3 Cu Cu 0.00000 1.000000 1.000000 12.000000
symfunction_short Cu 3 Cu Cu 0.00000 1.000000 2.000000 12.000000
symfunction_short Cu 3 Cu Cu 0.00000 1.000000 4.000000 12.000000
symfunction_short Cu 3 Cu Cu 0.00000 1.000000 16.000000 12.000000
symfunction_short Cu 3 Cu Cu 0.00000 -1.000000 1.000000 12.000000
symfunction_short Cu 3 Cu Cu 0.00000 -1.000000 2.000000 12.000000
symfunction_short Cu 3 Cu Cu 0.00000 -1.000000 4.000000 12.000000
symfunction_short Cu 3 Cu Cu 0.00000 -1.000000 16.000000 12.000000
########################################################################################################################
### fitting (mode 2):general inputs for short range AND electrostatic part:
########################################################################################################################
epochs 20 # number of epochs
fitting_unit eV # unit for error output in mode 2 (eV or Ha)
precondition_weights # optional precondition initial weights
########################################################################################################################
### fitting options ( mode 2): short range part only:
########################################################################################################################
short_energy_error_threshold 0.10000 # threshold of adaptive Kalman filter short E
short_force_error_threshold 1.00000 # threshold of adaptive Kalman filter short F
kalman_lambda_short 0.98000 # Kalman parameter short E/F, do not change
kalman_nue_short 0.99870 # Kalman parameter short E/F, do not change
use_short_forces # use forces for fitting
repeated_energy_update # optional: repeat energy update for each force update
mix_all_points # do not change
scale_symmetry_functions # optional
center_symmetry_functions # optional
short_force_fraction 0.01 #
force_update_scaling -1.0 #
########################################################################################################################
### output options for mode 2 (fitting):
########################################################################################################################
write_trainpoints # write trainpoints.out and testpoints.out files
write_trainforces # write trainforces.out and testforces.out files
########################################################################################################################
### output options for mode 3 (prediction):
########################################################################################################################
calculate_forces # calculate forces
calculate_stress # calculate stress tensor
day_3/fit/scaling.data
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1 1 14.256833324 19.604083786 16.584187995
1 2 10.772870436 14.917517522 12.575789477
1 3 7.067719199 9.940850811 8.325756144
1 4 3.063546892 4.514143322 3.699677080
1 5 0.443438674 0.840539370 0.611310762
1 6 11.372207256 23.338043099 16.099109800
1 7 30.908289966 62.610854904 43.470717798
1 8 4.747847116 10.201151151 6.890568480
1 9 24.299123692 49.473962957 34.262176478
1 10 1.690730707 3.912715044 2.559298728
1 11 16.549052901 34.322241783 23.555567314
1 12 0.252821214 0.820637834 0.460356083
1 13 4.065311900 9.687837138 6.245172716
-0.1359667057 -0.1284178204
day_3/fit/weights.029.data
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