Commit 0c5d7c1f authored by Jan Janssen's avatar Jan Janssen
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Updated notebooks from Sudarsan

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%% Cell type:markdown id:orange-treaty tags:
%% Cell type:markdown id:expired-green tags:
# [**Workflows for atomistic simulations**](http://potentials.rub.de/)
%% Cell type:markdown id:lasting-stick tags:
%% Cell type:markdown id:brutal-healing tags:
## **Day 1 - Atomistic simulations with [pyiron](https://pyiron.org)**
### **Exercise 2: Creating and working with structure databases**
Before the excercise, you should:
* Finish exercise 1
The aim of this exercise is to make you familiar with:
* Creating structure databases and working with them for potential fitting (day 2)
%% Cell type:markdown id:sharing-maldives tags:
%% Cell type:markdown id:cheap-chick tags:
## **Importing necessary modules and creating a project**
This is done the same way as shown in the first exercise
%% Cell type:code id:serial-slovak tags:
%% Cell type:code id:married-kidney tags:
``` python
import numpy as np
%matplotlib inline
import matplotlib.pylab as plt
```
%% Cell type:code id:departmental-certification tags:
%% Cell type:code id:academic-print tags:
``` python
from pyiron import Project
```
%% Cell type:code id:french-darwin tags:
%% Cell type:code id:comparable-creation tags:
``` python
pr = Project("creating_datasets")
```
%% Cell type:markdown id:electoral-norman tags:
%% Cell type:markdown id:focal-percentage tags:
## Creating a structure "container" from the data
We now go over the jobs generated in the first notebook to store structures, energies, and forces into a structure container which will later be used for potential fitting
**Note**: Usually these datasets are created using highly accurate DFT calculations. But for practical reasons, we only demonstrate how to do this using data from LAMMPS calculations (the workflow remain the same)
%% Cell type:code id:demanding-proxy tags:
%% Cell type:code id:contrary-spider tags:
``` python
# Access the project created in exercise 1
pr_fs = pr["../first_steps"]
```
%% Cell type:code id:alert-undergraduate tags:
%% Cell type:code id:superior-prospect tags:
``` python
# Create a TrainingContainer job (to store structures and databases)
container = pr.create.job.TrainingContainer('dataset_example')
```
%% Cell type:markdown id:comprehensive-sudan tags:
%% Cell type:markdown id:verified-lancaster tags:
## **Add structures from the E-V curves**
For starters, we append structures from the energy volume curves we calculated earlier
%% Cell type:code id:compatible-sight tags:
%% Cell type:code id:false-flexibility tags:
``` python
# Iterate over the jobs in this sub-project and append the final structure, potential energy, and forces
for job in pr_fs["E_V_curve"].iter_jobs(status="finished"):
container.include_job(job, iteration_step=-1)
```
%% Cell type:markdown id:illegal-capture tags:
%% Cell type:markdown id:boolean-reply tags:
We can obtain this data as a `pandas` table
%% Cell type:code id:impressive-basin tags:
%% Cell type:code id:introductory-latitude tags:
``` python
container.to_pandas()
```
%% Output
name atoms energy \
0 job_a_3_4 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) -3.142019
1 job_a_3_5 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) -3.338596
2 job_a_3_6 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) -3.416929
3 job_a_3_7 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) -3.409602
4 job_a_3_8 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) -3.330215
5 job_a_3_9 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) -3.195118
6 job_a_4_0 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) -3.035358
forces \
0 [[1.1869253621046177e-16, -1.7429070520896771e-16, -1.397277865277868e-16]]
1 [[-1.92404082484227e-16, 4.231084758750405e-17, 3.6193775346684653e-17]]
2 [[-2.9113397169423695e-17, 7.54965057835309e-17, -3.624419431643654e-17]]
3 [[3.771496125435321e-17, 3.412312546579927e-17, -2.4310047599025677e-17]]
4 [[-2.0545362501508919e-16, -3.5486130576273854e-17, 3.5486130576273854e-17]]
5 [[1.6101257219667079e-16, -4.2948421129906387e-17, 4.2948421129906387e-17]]
6 [[-5.946777565406637e-17, -1.0605082175909553e-16, -1.2946304704347008e-16]]
number_of_atoms
0 1.0
1 1.0
2 1.0
3 1.0
4 1.0
5 1.0
6 1.0
%% Cell type:markdown id:signed-instrument tags:
%% Cell type:markdown id:indirect-sellers tags:
## **Add structures from the MD**
We also add some structures obtained from the MD simulations
%% Cell type:code id:removed-consent tags:
%% Cell type:code id:applied-spank tags:
``` python
# Reloading the MD job
job_md = pr_fs["lammps_job"]
```
%% Cell type:code id:fewer-average tags:
%% Cell type:code id:operating-academy tags:
``` python
# Iterate over the MD-trajectory to append structures
traj_length = len(job_md["output/generic/positions"])
stride = 10 # append structures every 10 steps
for i in range(0, traj_length, stride):
container.include_job(job_md, iteration_step=i)
```
%% Cell type:markdown id:gentle-manufacturer tags:
%% Cell type:markdown id:consecutive-arbitration tags:
## **Add some defect structures (vacancies, surfaces, etc)**
It's necessary to also include some defect structures, and surfaces to the training dataset
%% Cell type:code id:leading-julian tags:
%% Cell type:code id:certified-eligibility tags:
``` python
# Setup a MD calculation for a structure with a vacancy
job_lammps = pr.create.job.Lammps("lammps_job_vac")
job_lammps.structure = pr.create_ase_bulk('Cu', cubic=True, a=3.61).repeat([3, 3, 3])
del job_lammps.structure[0]
job_lammps.potential = '2012--Mendelev-M-I--Cu--LAMMPS--ipr1'
job_lammps.calc_md(temperature=800, pressure=0, n_ionic_steps=10000)
job_lammps.run()
```
%% Output
The job lammps_job_vac was saved and received the ID: 52
%% Cell type:code id:adjacent-panama tags:
%% Cell type:code id:eleven-intermediate tags:
``` python
# Setup a MD calculation for a surface structure
job_lammps = pr.create.job.Lammps("lammps_job_surf")
job_lammps.structure = pr.create_surface("Cu", surface_type="fcc111", size=(4, 4, 8), vacuum=12, orthogonal=True)
job_lammps.potential = '2012--Mendelev-M-I--Cu--LAMMPS--ipr1'
job_lammps.calc_md(temperature=800, pressure=0, n_ionic_steps=10000)
job_lammps.run()
```
%% Output
The job lammps_job_surf was saved and received the ID: 53
%% Cell type:code id:encouraging-credit tags:
%% Cell type:code id:accepted-silly tags:
``` python
pr
```
%% Output
{'groups': [], 'nodes': ['lammps_job_vac', 'lammps_job_surf']}
%% Cell type:markdown id:humanitarian-effect tags:
%% Cell type:markdown id:diverse-stability tags:
We now add these structures to the dataset
%% Cell type:code id:floating-utility tags:
%% Cell type:code id:single-treasure tags:
``` python
for job_name in ["lammps_job_vac", "lammps_job_surf"]:
job_md = pr.load(job_name)
for job_md in pr.iter_jobs(status="finished"):
pos = job_md["output/generic/positions"]
traj_length = len(pos)
stride = 10
for i in range(0, traj_length, stride):
container.include_job(job_md, iteration_step=i)
if pos is not None:
traj_length = len(pos)
stride = 10
for i in range(0, traj_length, stride):
container.include_job(job_md, iteration_step=i)
```
%% Cell type:code id:excited-digest tags:
%% Cell type:code id:widespread-homework tags:
``` python
# We run the job sto store this dataset in the pyiron database
container.run()
```
%% Output
The job dataset_example was saved and received the ID: 54
/opt/conda/lib/python3.8/site-packages/pandas/core/generic.py:2606: PerformanceWarning:
your performance may suffer as PyTables will pickle object types that it cannot
map directly to c-types [inferred_type->mixed,key->block1_values] [items->Index(['name', 'atoms', 'forces'], dtype='object')]
pytables.to_hdf(
%% Cell type:code id:western-frank tags:
%% Cell type:code id:professional-change tags:
``` python
pr.job_table()
```
%% Output
id status chemicalformula job subjob \
0 52 finished Cu107 lammps_job_vac /lammps_job_vac
1 53 finished Cu128 lammps_job_surf /lammps_job_surf
2 54 finished None dataset_example /dataset_example
projectpath project timestart \
0 /home/pyiron/ day_1/creating_datasets/ 2021-03-09 09:00:43.012322
1 /home/pyiron/ day_1/creating_datasets/ 2021-03-09 09:00:48.219183
2 /home/pyiron/ day_1/creating_datasets/ 2021-03-09 09:01:01.281092
0 /home/pyiron/ day_1/creating_datasets/ 2021-03-09 09:56:52.116789
1 /home/pyiron/ day_1/creating_datasets/ 2021-03-09 09:56:57.326228
2 /home/pyiron/ day_1/creating_datasets/ 2021-03-09 09:57:10.376230
timestop totalcputime computer \
0 2021-03-09 09:00:47.308799 4.0 pyiron@jupyter-janssen#1
1 2021-03-09 09:00:52.902683 4.0 pyiron@jupyter-janssen#1
0 2021-03-09 09:56:56.507766 4.0 pyiron@jupyter-janssen#1
1 2021-03-09 09:57:02.004791 4.0 pyiron@jupyter-janssen#1
2 NaT NaN pyiron@jupyter-janssen#1
hamilton hamversion parentid masterid
0 Lammps 0.1 None None
1 Lammps 0.1 None None
2 TrainingContainer 0.4 None None
%% Cell type:markdown id:valuable-procedure tags:
%% Cell type:markdown id:technological-partner tags:
## **Reloading the dataset**
This dataset can ow be reloaded anywhere to use in the potential fitting procedures
%% Cell type:code id:exempt-sydney tags:
%% Cell type:code id:processed-samuel tags:
``` python
dataset = pr["dataset_example"]
dataset.to_pandas()
```
%% Output
name \
0 job_a_3_4
1 job_a_3_5
2 job_a_3_6
3 job_a_3_7
4 job_a_3_8
5 job_a_3_9
6 job_a_4_0
7 lammps_job
8 lammps_job
9 lammps_job
10 lammps_job
11 lammps_job
12 lammps_job
13 lammps_job
14 lammps_job
15 lammps_job
16 lammps_job
17 lammps_job
18 lammps_job_vac
19 lammps_job_vac
20 lammps_job_vac
21 lammps_job_vac
22 lammps_job_vac
23 lammps_job_vac
24 lammps_job_vac
25 lammps_job_vac
26 lammps_job_vac
27 lammps_job_vac
28 lammps_job_vac
29 lammps_job_surf
30 lammps_job_surf
31 lammps_job_surf
32 lammps_job_surf
33 lammps_job_surf
34 lammps_job_surf
35 lammps_job_surf
36 lammps_job_surf
37 lammps_job_surf
38 lammps_job_surf
39 lammps_job_surf
atoms \
0 (Atom('Cu', [0.0, 0.0, 0.0], index=0))
1 (Atom('Cu', [0.0, 0.0, 0.0], index=0))
2 (Atom('Cu', [0.0, 0.0, 0.0], index=0))
3 (Atom('Cu', [0.0, 0.0, 0.0], index=0))
4 (Atom('Cu', [0.0, 0.0, 0.0], index=0))
5 (Atom('Cu', [0.0, 0.0, 0.0], index=0))
6 (Atom('Cu', [0.0, 0.0, 0.0], index=0))
7 (Atom('Cu', [0.0, 0.0, 0.0], index=0), Atom('Cu', [0.0, 1.804999999999592, 1.804999999999592], index=1), Atom('Cu', [1.804999999999592, 1.1052437362302367e-16, 1.804999999999592], index=2), Atom('...
8 (Atom('Cu', [0.140426153531212, 11.00934611760493, 10.96820769600138], index=0), Atom('Cu', [10.983357200359302, 1.779939365335074, 1.7146804782560903], index=1), Atom('Cu', [2.1228644677344763, 0...
9 (Atom('Cu', [0.1407579358923329, 11.020287239626356, 10.855878337455094], index=0), Atom('Cu', [0.29542104007972325, 1.6514729828183248, 1.7760939949715], index=1), Atom('Cu', [1.9957825818756145,...
10 (Atom('Cu', [0.046752778326835207, 10.951786003502875, 0.20014601215416555], index=0), Atom('Cu', [0.08453269827616121, 1.8072189743037306, 1.7664733621606052], index=1), Atom('Cu', [1.95973571233...
11 (Atom('Cu', [10.99133278089223, 11.027168829788456, 0.17044757336885], index=0), Atom('Cu', [10.869778028731703, 1.9053524080340212, 1.7569642307109046], index=1), Atom('Cu', [1.8902712829055568, ...
12 (Atom('Cu', [10.958070767873476, 0.05270018288526145, 11.015795828313692], index=0), Atom('Cu', [0.045409705041259525, 2.078051985469034, 1.8353871076995325], index=1), Atom('Cu', [1.8285627799498...
13 (Atom('Cu', [10.903697402270652, 10.843249424146602, 0.09574490333936027], index=0), Atom('Cu', [10.59491891666766, 1.7187193807026324, 1.9573011135302476], index=1), Atom('Cu', [1.676074002401891...
14 (Atom('Cu', [0.258411989603464, 0.0706344931649224, 10.912283030397811], index=0), Atom('Cu', [0.1964902001455455, 1.7891621064461172, 1.8031814864809468], index=1), Atom('Cu', [1.7493171890021084...
15 (Atom('Cu', [0.004994793782076363, 10.985055637641707, 10.904222762435255], index=0), Atom('Cu', [10.9417296640056, 1.886861412294462, 1.8147512571859394], index=1), Atom('Cu', [1.8438031255436442...
16 (Atom('Cu', [0.03645923831331586, 10.8560106939291, 10.97057299019823], index=0), Atom('Cu', [10.913522535013476, 1.816191438106623, 1.5447581077438086], index=1), Atom('Cu', [1.7758393302091413, ...
17 (Atom('Cu', [0.00976718182041884, 0.007186523165377699, 11.008902399259645], index=0), Atom('Cu', [10.89374596607187, 1.9969194212527828, 1.5955788370755422], index=1), Atom('Cu', [2.0544219291027...
18 (Atom('Cu', [0.0, 1.804999999999592, 1.804999999999592], index=0), Atom('Cu', [1.804999999999592, 1.1052437362302367e-16, 1.804999999999592], index=1), Atom('Cu', [1.804999999999592, 1.80499999999...
19 (Atom('Cu', [0.10390109091492468, 1.9580560553035562, 1.7791885607676787], index=0), Atom('Cu', [1.3868099266682057, 10.93717630776338, 1.6017909487813904], index=1), Atom('Cu', [1.718398788940990...
20 (Atom('Cu', [0.222323479300276, 1.6999920633404162, 1.7623980235259142], index=0), Atom('Cu', [2.1228826608790445, 0.1862423842302597, 2.0308086839888815], index=1), Atom('Cu', [1.733468948470044,...
21 (Atom('Cu', [10.839434974930233, 1.9008464900018414, 1.6867963294684114], index=0), Atom('Cu', [1.587659858135841, 0.1544755711878935, 1.7152999948177818], index=1), Atom('Cu', [2.148606011735478,...
22 (Atom('Cu', [10.827044041158409, 1.8148855201981695, 2.124190925175089], index=0), Atom('Cu', [1.6679142700199683, 0.11062408070456453, 1.6294014594257846], index=1), Atom('Cu', [1.294186866136013...
23 (Atom('Cu', [0.18579648603934987, 1.6025971043768155, 1.8725196193702205], index=0), Atom('Cu', [2.048083516582408, 0.05523851059960332, 2.2588410942434316], index=1), Atom('Cu', [1.84234468412923...
24 (Atom('Cu', [10.902653792488254, 1.9016481867624628, 1.7123868009764087], index=0), Atom('Cu', [1.684365629566867, 0.20454959543267073, 1.4940727709048371], index=1), Atom('Cu', [1.628967729292809...
25 (Atom('Cu', [0.22025110375749696, 1.5872348575731654, 1.7623998700921586], index=0), Atom('Cu', [1.8386689358494586, 10.988833155464064, 1.8571406735076377], index=1), Atom('Cu', [1.97639089167179...
26 (Atom('Cu', [10.746144724792629, 1.6561216261325158, 1.6676063346541934], index=0), Atom('Cu', [1.8697696007010116, 0.2956610204486699, 1.9071090181785917], index=1), Atom('Cu', [1.820130883905895...
27 (Atom('Cu', [0.17063059334564, 1.853418797177199, 1.7423748774412284], index=0), Atom('Cu', [1.8595651381460672, 10.905723229638589, 1.810598025743776], index=1), Atom('Cu', [1.9346512242265819, 1...
28 (Atom('Cu', [10.866365841890905, 1.8491297824671196, 2.0932441820713352], index=0), Atom('Cu', [1.7536272327257443, 10.898985480280807, 1.8241252899027136], index=1), Atom('Cu', [1.994555229954278...
29 (Atom('Cu', [0.0, 1.47377632857406, 9.024277317236802e-17], index=0), Atom('Cu', [2.5526554800834376, 1.4737763285740602, 2.4654784132287465e-16], index=1), Atom('Cu', [5.105310960166875, 1.473776...
30 (Atom('Cu', [0.4126496185424086, 0.9553642998076769, 0.12158924761653131], index=0), Atom('Cu', [2.831118842513476, 1.070015821634989, 25.91692230427277], index=1), Atom('Cu', [5.314789299948389, ...
31 (Atom('Cu', [10.151562776611796, 1.6587733567107221, 26.430359388947146], index=0), Atom('Cu', [2.521282881985372, 1.9070842851152827, 26.3620394009805], index=1), Atom('Cu', [4.715098279444533, 1...
32 (Atom('Cu', [0.19573901040814495, 1.051460534941852, 26.530022925039262], index=0), Atom('Cu', [2.9957269566314313, 1.1546751485293134, -0.001778040455061588], index=1), Atom('Cu', [5.923947432763...
33 (Atom('Cu', [9.88837962589013, 1.4968159202602165, 26.58551059472219], index=0), Atom('Cu', [2.2075440570158325, 1.2900742458621188, 26.685466830384563], index=1), Atom('Cu', [4.939145903748459, 1...
34 (Atom('Cu', [0.34293262903884986, 1.5170285327525375, 0.1489631508684563], index=0), Atom('Cu', [3.1293458688620657, 1.4951029648602612, 0.016078486508459836], index=1), Atom('Cu', [5.714332108259...
35 (Atom('Cu', [9.95801241508353, 1.4359511579323643, 26.639342243648876], index=0), Atom('Cu', [2.2681416259097977, 1.7861270127584556, 0.004193644623918503], index=1), Atom('Cu', [5.074253116948597...
36 (Atom('Cu', [10.225027496778678, 1.7848555655263902, 26.42388292769736], index=0), Atom('Cu', [2.491486993862084, 1.8611191751030531, 26.648267715418335], index=1), Atom('Cu', [4.968442272628866, ...
37 (Atom('Cu', [10.18811670169521, 1.3482529143794337, 26.353847647583958], index=0), Atom('Cu', [2.4559442807083434, 1.4757747059783504, 26.573792820255626], index=1), Atom('Cu', [5.077086561123885,...
38 (Atom('Cu', [10.165259029717141, 1.7122531597864588, 26.335638965282506], index=0), Atom('Cu', [2.351333086964575, 1.5487334167881261, 26.342581162362286], index=1), Atom('Cu', [4.955731381487939,...
39 (Atom('Cu', [0.3689378411745667, 1.4818319280204475, 26.535047009582307], index=0), Atom('Cu', [2.6965712182140265, 1.4888124298358478, 26.730123523791978], index=1), Atom('Cu', [5.668661293887029...
energy \
0 -3.142019
1 -3.338596
2 -3.416929
3 -3.409602
4 -3.330215
5 -3.195118
6 -3.035358
7 -369.311743
8 -360.190839
9 -356.403521
10 -358.245754
11 -356.564325
12 -357.011799
13 -357.856759
14 -358.316140
15 -356.847816
16 -358.626624
17 -356.796173
18 -364.828772
19 -353.817356
20 -353.115830
21 -352.375089
22 -352.774500
23 -352.466296
24 -353.659518
25 -352.032412
26 -352.885609
27 -352.295316
28 -353.959714
29 -426.377084
30 -412.725659
31 -412.248744
32 -408.987597
33 -410.603331
34 -412.068287
35 -410.426591
36 -413.081270
37 -411.270168
38 -410.951862
39 -411.163952
forces \
0 [[1.1869253621046177e-16, -1.7429070520896771e-16, -1.397277865277868e-16]]
1 [[-1.92404082484227e-16, 4.231084758750405e-17, 3.6193775346684653e-17]]
2 [[-2.9113397169423695e-17, 7.54965057835309e-17, -3.624419431643654e-17]]
3 [[3.771496125435321e-17, 3.412312546579927e-17, -2.4310047599025677e-17]]
4 [[-2.0545362501508919e-16, -3.5486130576273854e-17, 3.5486130576273854e-17]]
5 [[1.6101257219667079e-16, -4.2948421129906387e-17, 4.2948421129906387e-17]]
6 [[-5.946777565406637e-17, -1.0605082175909553e-16, -1.2946304704347008e-16]]
7 [[-1.2656542480726799e-14, -1.46965772884755e-14, -1.61017033040167e-14], [-1.3905543383430098e-14, 4.5310977192514186e-15, 4.8333732849403796e-15], [4.9682480351975795e-15, -1.4072076837123899e-1...
8 [[-0.21910202935187897, -0.37573419410584397, 0.43392575377979187], [0.16208168404695897, -0.00671505675904709, 1.03458554920361], [-1.2001630139266497, -0.40207322348963503, -0.45620473735655703]...
9 [[-0.023031834879864897, 0.04284143869144259, 0.5899774836434099], [-0.5418151518758109, 0.6754733604037649, -0.5582999589285099], [-0.6011411771363389, -0.355590065330048, -0.003590198630652358],...
10 [[-0.32237334386617594, 0.43406651671772695, -0.5886238546573999], [-0.6295919499999019, 0.07530471384292876, -0.12687342568255203], [-0.06506588733974998, 0.8782024477947719, -0.12243680387296693...
11 [[0.45078377546780296, -0.7167806257868728, -0.320969733281809], [0.5707773027839779, -0.5494069530720159, 0.510256621543522], [-0.36439749359319995, 0.17709586752113193, 0.23127352998529296], [0....
12 [[-0.38409855462373593, 0.12077975249587695, 0.02446577119927368], [-0.6560764999470009, -1.05845756801682, -0.658182913092867], [-0.5103420261931418, -0.356562711546522, 0.7090309519858399], [-0....
13 [[0.22044015996419397, -0.26072783887691897, -0.38550323222201893], [0.7754186544628359, -0.04652340102588245, -0.2623216499598349], [0.4314779287479719, -0.9840256256937749, 0.34987911571166197],...
14 [[-0.5020206209738959, 0.007307596546447969, 0.24586848662953095], [-1.1645196400318298, 0.14762851807991492, 0.6168850904682569], [0.7183114431738189, -0.5420093170980669, -0.06687387962120929], ...
15 [[0.04806202890911529, 0.4896972435411299, 1.29371057618316], [0.5538169933312109, -0.7855310261686719, -0.033081946439222513], [0.34832740608971496, 0.9937361742507679, 0.30650548838579206], [-0....
16 [[0.24033044872932896, 1.5305792676779497, -0.6791236163998687], [0.05903491330127059, 0.148151392634253, 0.542468964385662], [0.07921843405774338, 0.145966157230826, 0.7342269239659519], [0.77503...
17 [[-0.13926025200196399, -0.0920021630565197, 0.21001691279918497], [0.6767944835632749, -1.1148612202170798, 1.7165284720013199], [-0.7950973844667609, 0.2356681335380539, 0.13328556065954994], [0...
18 [[-1.3933298959045699e-14, -0.10827842091784899, -0.108278420917849], [-0.10827842091784899, -1.3877479054990188e-14, -0.108278420917849], [-0.10827842091784899, -0.108278420917849, -1.38424758326...
19 [[-0.45079778130212095, 0.19236747741186794, 0.23614131969518395], [1.2984317307785798, 0.047515689332818876, 0.0054434255778954815], [0.48875760189529993, -0.5765163470127389, -0.5531364786691438...
20 [[-0.6920262907037699, 0.3986975029534239, 0.10738641941633598], [-1.2097205794551897, -2.2142354302088, -0.8363385508175151], [-0.36839592956672496, 0.3591989390425319, 0.09738195090699889], [2.1...
21 [[0.5607305368014349, 0.07454461225798582, 0.17092757180355503], [0.7460358156722969, -0.9693709228667519, -0.357775642489466], [-1.4982109077379697, 1.0695224870646098, 0.17016025464195195], [1.1...
22 [[0.7768634672242999, 0.615614277463985, -0.6520778674493769], [0.5196497874591279, -0.7614150189291738, 0.33452284258293197], [1.0185593798557397, 0.11349094339204105, -1.1138567887771997], [0.39...
23 [[-1.2511641504900297, 0.045660252979352216, 0.3942699933548249], [-0.49238478619866294, -0.676187288648693, -1.38021677052805], [-0.12072100498243699, 0.5666924914313989, -0.8825937576412469], [0...
24 [[0.5080309295530009, -0.4875222168854389, 0.46898176419400794], [0.11031309245877298, -0.7243436015235899, 1.2808414835860897], [0.6855285827566528, 0.576817447011234, 0.31599931467165404], [0.50...
25 [[-0.6923371397932379, 0.9615117891395759, 0.396261839405581], [0.18083100479582398, -0.47103552318232994, 0.5072798015385259], [-0.22735248852514198, 0.3701117760834369, -1.1740345739673297], [0....
26 [[0.4694017239681809, 0.557542533620799, 0.861383405389437], [-0.16043498520491098, -1.0997839630796997, -0.013974118048379877], [-0.13554483753545396, 0.6363641150344139, 0.153788969504449], [1.0...
27 [[-1.1653987878668197, -0.07515193358861387, -0.13414295175130306], [0.17707911415253696, 0.37588361844850293, 0.10312993216846503], [0.6003632668071709, 0.386969577632806, 0.03431754138154845], [...
28 [[0.4281914688318719, -1.3404674992878498, -0.840042998895605], [0.4782285361793289, -0.07949121879472046, -0.36737406210665396], [-0.9172013000957939, 0.3239785884620919, -0.013009379648141535], ...
29 [[-8.770761894538741e-15, 1.15657750043852e-09, 0.109956784695642], [-1.0824674490095302e-15, 1.15657515335765e-09, 0.10995678469564], [2.4308896909297503e-15, 1.1565748914144101e-09, 0.1099567846...
30 [[-0.570999988178138, 1.09833300989088, -0.566585257198733], [-0.0492000252908119, 0.59741650677863, 0.966635869516026], [-0.0024866801464869, -0.0674126479000064, 0.2546322145358], [0.22890858859...
31 [[-0.555658749547297, 0.42566314828364293, 0.466167261187242], [-1.39449792316991, -0.5017985009363141, 0.44565311708876987], [1.25410857633047, -0.33111996310053693, -0.24658722383835793], [0.391...
32 [[0.550884754551255, 0.33865983742361505, 0.12042096866994706], [0.189727589275785, -0.524367356684469, -0.17886090450817402], [-1.6758650723095, -0.3103026148332811, 0.6946509585210929], [0.44535...
33 [[0.235449441283078, 0.601163461328045, 0.047374581092271446], [0.337344266120139, 0.664857294034072, 0.37768738132641905], [-0.171831038532397, -0.11286098092806901, -0.07415135874388401], [-0.19...
34 [[1.15453322332514, 0.04603660924936107, -1.21282260886917], [-0.40339091367313, -0.18969536874822704, 0.030526533197075965], [-0.683024325118812, -0.967333273080052, 0.4114320467711059], [-0.8675...
35 [[0.742004122720721, 0.22577315892753805, 0.12298868178080906], [0.771069504023197, -0.90014541932296, -0.660403448735684], [-0.462456173471762, 1.24796716627208, -0.41920103505081097], [0.0821911...
36 [[0.552749731039339, -0.46087407706439093, 0.177277816520108], [0.340079509796374, 0.23574679643604202, 0.26784307872275903], [0.38829857840138, 0.331969932800717, 0.34399524631836903], [-0.598269...
37 [[0.570532228170616, 0.17193739346638104, 0.796311675023456], [0.672970110578221, -0.817732243959863, 0.207420342553793], [0.391385096556072, -0.862073619432422, 0.597813478903035], [-0.2704527267...
38 [[-1.11093024775332, -0.6986058375434832, 0.4467412161766239], [0.0416051560885089, -0.0424634968511256, -0.0874515614131588], [-0.135122617107614, -0.778975629931571, -1.04402814517475], [0.84425...
39 [[-0.645092069842764, 0.049201221165188956, 0.21081031392484997], [1.14893686212593, -0.6114894802487358, -0.40665475714370897], [-0.287092610235497, 0.292443460035198, -0.801010315713759], [-0.18...
number_of_atoms
0 1.0
1 1.0
2 1.0
3 1.0
4 1.0
5 1.0
6 1.0
7 108.0
8 108.0
9 108.0
10 108.0
11 108.0
12 108.0
13 108.0
14 108.0
15 108.0
16 108.0
17 108.0
18 107.0
19 107.0
20 107.0
21 107.0
22 107.0
23 107.0
24 107.0
25 107.0
26 107.0
27 107.0
28 107.0
29 128.0
30 128.0
31 128.0
32 128.0
33 128.0
34 128.0
35 128.0
36 128.0
37 128.0
38 128.0
39 128.0
%% Cell type:markdown id:crazy-clerk tags:
%% Cell type:markdown id:julian-helena tags:
We can now inspect the data in this dataset quite easily
%% Cell type:code id:third-comfort tags:
%% Cell type:code id:starting-dress tags:
``` python
struct = dataset.get_structure(30)
```
%% Cell type:code id:magnetic-spring tags:
%% Cell type:code id:massive-wheat tags:
``` python
structures, energies, forces, num_atoms = dataset.to_list()
```
%% Cell type:markdown id:expired-savage tags:
%% Cell type:markdown id:suited-blank tags:
The datasets used in the potential fitting procedure for day 2 (obtained from accurate DFT calculations) will be accessed in the same way
%% Cell type:code id:regular-branch tags:
%% Cell type:code id:standard-organic tags:
``` python
```
......
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