Commit 18169ae7 by Sudarsan Surendralal

### Final cleanup

parent 90a83e24
 %% Cell type:markdown id:naval-truck tags: %% Cell type:markdown id:appointed-stylus tags: # [**Workflows for atomistic simulations**](http://potentials.rub.de/) # [**Workflows for atomistic simulations**](http://potentials.rub.de/) %% Cell type:markdown id:pregnant-battery tags: %% Cell type:markdown id:straight-bicycle tags: ## **Day 1 - Atomistic simulations with [pyiron](https://pyiron.org)** ## **Day 1 - Atomistic simulations with [pyiron](https://pyiron.org)** ### **Exercise 2: Creating and working with structure databases** ### **Exercise 2: Creating and working with structure databases** Before the excercise, you should: Before the excercise, you should: * Finish exercise 1 * Finish exercise 1 The aim of this exercise is to make you familiar with: The aim of this exercise is to make you familiar with: * Creating structure databases and working with them for potential fitting (day 2) * Creating structure databases and working with them for potential fitting (day 2) %% Cell type:code id:roman-wilderness tags: %% Cell type:markdown id:durable-leone tags: ## **Importing necessary modules and creating a project** This is done the same way as shown in the first exercise %% Cell type:code id:novel-wisconsin tags: ``` python ``` python import numpy as np import numpy as np %matplotlib inline %matplotlib inline import matplotlib.pylab as plt import matplotlib.pylab as plt ``` ``` %% Cell type:code id:charming-furniture tags: %% Cell type:code id:sitting-religious tags: ``` python ``` python from pyiron import Project from pyiron import Project import pyiron_contrib ``` ``` %% Cell type:code id:bibliographic-honey tags: %% Cell type:code id:technical-newport tags: ``` python ``` python pr = Project("creating_datasets") pr = Project("creating_datasets") ``` ``` %% Cell type:code id:relative-subscriber tags: %% Cell type:markdown id:based-kentucky 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:attached-germany tags: ``` python ``` python # Access the project created in exercise 1 pr_fs = pr["../first_steps"] pr_fs = pr["../first_steps"] ``` ``` %% Cell type:code id:solved-sight tags: %% Cell type:code id:filled-natural tags: ``` python ``` python # Create a TrainingContainer job (to store structures and databases) container = pr.create.job.TrainingContainer('dataset_example') container = pr.create.job.TrainingContainer('dataset_example') ``` ``` %% Cell type:markdown id:falling-spouse tags: %% Cell type:markdown id:married-storm tags: ## **Add structures from the E-V curves** ## **Add structures from the E-V curves** %% Cell type:code id:secure-tract tags: For starters, we append structures from the energy volume curves we calculated earlier ``` python %% Cell type:code id:mediterranean-upset 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"): for job in pr_fs["E_V_curve"].iter_jobs(status="finished"): container.include_job(job, iteration_step=-1) container.include_job(job, iteration_step=-1) ``` ``` %% Cell type:code id:wicked-defeat tags: %% Cell type:markdown id:acquired-missile tags: We can obtain this data as a `pandas` table %% Cell type:code id:greatest-person tags: ``` python ``` python container.to_pandas() container.to_pandas() ``` ``` %%%% Output: execute_result %%%% Output: execute_result name \ name \ 0 None 0 None 1 None 1 None 2 None 2 None 3 None 3 None 4 None 4 None 5 None 5 None 6 None 6 None 7 None 7 None 8 None 8 None 9 None 9 None 10 None 10 None 11 None 11 None 12 None 12 None 13 None 13 None 14 None 14 None 15 None 15 None 16 None 16 None 17 None 17 None 18 None 18 None 19 None 19 None 20 None 20 None 21 None 21 None 22 None 22 None 23 None 23 None 24 None 24 None 25 None 25 None 26 None 26 None 27 None 27 None 28 None 28 None 29 None 29 None 30 None 30 None 31 None 31 None 32 None 32 None 33 None 33 None 34 None 34 None 35 None 35 None 36 None 36 None 37 None 37 None 38 None 38 None 39 None 39 None 40 job_a_3_4 40 job_a_3_4 41 job_a_3_5 41 job_a_3_5 42 job_a_3_6 42 job_a_3_6 43 job_a_3_7 43 job_a_3_7 44 job_a_3_8 44 job_a_3_8 45 job_a_3_9 45 job_a_3_9 46 job_a_4_0 46 job_a_4_0 atoms \ atoms \ 0 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) 0 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) 1 (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)) 2 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) 3 (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)) 4 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) 5 (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)) 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, 1.8049999999995918, 1.804999999999592], index=1), Atom('Cu', [1.8049999999995918, 1.1052437362302365e-16, 1.804999999999592], index=2), Atom... 7 (Atom('Cu', [0.0, 0.0, 0.0], index=0), Atom('Cu', [0.0, 1.8049999999995918, 1.804999999999592], index=1), Atom('Cu', [1.8049999999995918, 1.1052437362302365e-16, 1.804999999999592], index=2), Atom... 8 (Atom('Cu', [0.140426153531212, 11.00934611760493, 10.968207696001379], index=0), Atom('Cu', [10.983357200359302, 1.779939365335074, 1.7146804782560905], index=1), Atom('Cu', [2.1228644677344763, ... 8 (Atom('Cu', [0.140426153531212, 11.00934611760493, 10.968207696001379], index=0), Atom('Cu', [10.983357200359302, 1.779939365335074, 1.7146804782560905], index=1), Atom('Cu', [2.1228644677344763, ... 9 (Atom('Cu', [0.1407579358923329, 11.020287239626356, 10.855878337455094], index=0), Atom('Cu', [0.29542104007972325, 1.6514729828183248, 1.7760939949715002], index=1), 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1.5487334168655387, 26.34258116233103], index=1), Atom('Cu', [4.95573138146394, ... 39 (Atom('Cu', [0.36893784059756035, 1.481831927531004, 26.53504700964859], index=0), Atom('Cu', [2.6965712181950883, 1.488812429574298, 26.730123522873537], index=1), Atom('Cu', [5.668661292604278, ... 39 (Atom('Cu', [0.36893784059756035, 1.481831927531004, 26.53504700964859], index=0), Atom('Cu', [2.6965712181950883, 1.488812429574298, 26.730123522873537], index=1), Atom('Cu', [5.668661292604278, ... 40 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) 40 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) 41 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) 41 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) 42 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) 42 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) 43 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) 43 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) 44 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) 44 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) 45 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) 45 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) 46 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) 46 (Atom('Cu', [0.0, 0.0, 0.0], index=0)) energy \ energy \ 0 -3.142019 0 -3.142019 1 -3.338596 1 -3.338596 2 -3.416929 2 -3.416929 3 -3.409602 3 -3.409602 4 -3.330215 4 -3.330215 5 -3.195118 5 -3.195118 6 -3.035358 6 -3.035358 7 -347.182406 7 -347.182406 8 -348.253665 8 -348.253665 9 -345.424528 9 -345.424528 10 -346.758349 10 -346.758349 11 -344.603627 11 -344.603627 12 -346.849801 12 -346.849801 13 -345.015235 13 -345.015235 14 -346.569097 14 -346.569097 15 -344.892954 15 -344.892954 16 -347.628843 16 -347.628843 17 -345.776979 17 -345.776979 18 -342.906251 18 -342.906251 19 -343.569002 19 -343.569002 20 -343.317892 20 -343.317892 21 -341.057270 21 -341.057270 22 -342.067006 22 -342.067006 23 -342.528496 23 -342.528496 24 -342.900954 24 -342.900954 25 -340.983380 25 -340.983380 26 -342.479965 26 -342.479965 27 -340.174298 27 -340.174298 28 -343.805462 28 -343.805462 29 -400.111422 29 -400.111422 30 -399.591699 30 -399.591699 31 -398.422617 31 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[[3.771496125435321e-17, 3.412312546579927e-17, -2.4310047599025677e-17]] 4 [[-2.0545362501508919e-16, -3.5486130576273854e-17, 3.5486130576273854e-17]] 4 [[-2.0545362501508919e-16, -3.5486130576273854e-17, 3.5486130576273854e-17]] 5 [[1.6101257219667079e-16, -4.2948421129906387e-17, 4.2948421129906387e-17]] 5 [[1.6101257219667079e-16, -4.2948421129906387e-17, 4.2948421129906387e-17]] 6 [[-5.946777565406637e-17, -1.0605082175909553e-16, -1.2946304704347008e-16]] 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... 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, 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[[-5.946777565406637e-17, -1.0605082175909553e-16, -1.2946304704347008e-16]] 46 [[-5.946777565406637e-17, -1.0605082175909553e-16, -1.2946304704347008e-16]] number_of_atoms number_of_atoms 0 1.0 0 1.0 1 1.0 1 1.0 2 1.0 2 1.0 3 1.0 3 1.0 4 1.0 4 1.0 5 1.0 5 1.0 6 1.0 6 1.0 7 108.0 7 108.0 8 108.0 8 108.0 9 108.0 9 108.0 10 108.0 10 108.0 11 108.0 11 108.0 12 108.0 12 108.0 13 108.0 13 108.0 14 108.0 14 108.0 15 108.0 15 108.0 16 108.0 16 108.0 17 108.0 17 108.0 18 107.0 18 107.0 19 107.0 19 107.0 20 107.0 20 107.0 21 107.0 21 107.0 22 107.0 22 107.0 23 107.0 23 107.0 24 107.0 24 107.0 25 107.0 25 107.0 26 107.0 26 107.0 27 107.0 27 107.0 28 107.0 28 107.0 29 128.0 29 128.0 30 128.0 30 128.0 31 128.0 31 128.0 32 128.0 32 128.0 33 128.0 33 128.0 34 128.0 34 128.0 35 128.0 35 128.0 36 128.0 36 128.0 37 128.0 37 128.0 38 128.0 38 128.0 39 128.0 39 128.0 40 1.0 40 1.0 41 1.0 41 1.0 42 1.0 42 1.0 43 1.0 43 1.0 44 1.0 44 1.0 45 1.0 45 1.0 46 1.0 46 1.0 %% Cell type:markdown id:transsexual-journalist tags: %% Cell type:markdown id:imperial-belarus tags: ## **Add structures from the MD** ## **Add structures from the MD** Structures sampled every 10 snapshots (we may need to minimize the structures from the MD) We also add some structures obtained from the MD simulations %% Cell type:code id:earlier-static tags: %% Cell type:code id:healthy-structure tags: