Merge pull request #162 from QuantumChemist/docs

Docs fixes

docs/user/fitting/fitting.md

@@ -213,6 +213,61 @@ complete_flow = CompleteDFTvsMLBenchmarkWorkflow(
 )
 ```
 
+## Example script for `autoplex` workflow using GAP to fit and benchmark a Si database
+
+The following code snippet will demonstrate, how you can submit an `autoplex` workflow for an automated SOAP-only GAP fit 
+and DFT benchmark for a Si allotrope database. The GAP fit parameters are taken from [J. Chem. Phys. 153, 044104 (2020)](https://pubs.aip.org/aip/jcp/article/153/4/044104/1056348/Combining-phonon-accuracy-with-high).
+In this example we will also use `hyper_para_loop=True` to loop through a set of given GAP fit convergence parameter 
+and hyperparameters set as provided by the lists `atomwise_regularization_list`, `soap_delta_list` and `n_sparse_list`.
+In this example script, we are using `jobflow_remote` to submit the jobs to a remote cluster.
+
+```python
+from jobflow_remote import submit_flow
+from autoplex.auto.phonons.flows import CompleteDFTvsMLBenchmarkWorkflow
+from mp_api.client import MPRester
+
+mpr = MPRester(api_key='YOUR_MP_API_KEY')
+struc_list = []
+benchmark_structure_list = []
+mpids = ["mp-149"]  # add all the Si structure mpids you are interested in
+mpbenchmark = ["mp-149"]  # add all the Si structure mpids you are interested in
+for mpid in mpids:
+    struc = mpr.get_structure_by_material_id(mpid)
+    struc_list.append(struc)
+for mpbm in mpbenchmark:
+    bm_struc = mpr.get_structure_by_material_id(mpbm)
+    benchmark_structure_list.append(bm_struc)
+
+autoplex_flow = CompleteDFTvsMLBenchmarkWorkflow(
+    n_structures=50, symprec=0.1,
+    volume_scale_factor_range=[0.95, 1.05], rattle_type=0, distort_type=0,
+    hyper_para_loop=True, atomwise_regularization_list=[0.1, 0.01],
+    soap_delta_list=[0.5], n_sparse_list=[7000, 8000, 9000]).make(
+    structure_list=struc_list, mp_ids=mpids, benchmark_structures=benchmark_structure_list,
+    benchmark_mp_ids=mpbenchmark, preprocessing_data=True,
+    **{
+        "split_ratio": 0.33,
+        "regularization": False,
+        "separated": True,
+        "num_processes_fit": 48,
+        "GAP": {"soap": {"delta": 1.0, "l_max": 12, "n_max": 10,
+                         "atom_sigma": 0.5, "zeta": 4, "cutoff": 5.0,
+                         "cutoff_transition_width": 1.0,
+                         "central_weight": 1.0, "n_sparse": 9000, "f0": 0.0,
+                         "covariance_type": "dot_product",
+                         "sparse_method": "cur_points"},
+                "general": {"two_body": False, "three_body": False, "soap": True,
+                            "default_sigma": "{0.001 0.05 0.05 0.0}", "sparse_jitter": 1.0e-8, }}},
+)
+
+autoplex_flow.name = "autoplex_wf"
+
+resources = {...}
+
+print(submit_flow(autoplex_flow, worker="autoplex_worker", resources=resources, project="autoplex"))
+```
+
+
 ## Running a MLIP fit only
 
 The following script shows an example of how you can run a sole GAP fit with `autoplex` using `run_locally` from 

docs/user/flows/flows.md

@@ -12,7 +12,7 @@ This tutorial will demonstrate how to use `autoplex` with its default setup and
 
 The complete workflow of `autoplex` involves the data generation 
 (including the execution of VASP calculations), 
-the fitting of the  machine-learned interatomic potential (MLIP) and the benchmark to the DFT results.
+the fitting of the machine-learned interatomic potential (MLIP) and the benchmark to the DFT results.
 
 ### Before running the workflow
 
@@ -42,9 +42,11 @@ check_supercells(structure_list, mpids, min_length=18, max_length=25, fallback_m
 `check_supercells` will list all structures that should likely be excluded. 
 However, please carefully check yourself as your local memory requirements might be different.
 Remove all structures which you cannot treat computationally 
-(e.g., structures with lattice parameters larger than 25 Angstrom or more than 500 atoms).
+(e.g., structures with lattice parameters larger than 25 Å or more than 500 atoms).
+
 Using the `MPRester` is a convenient way to draw structures from the Materials Project database using their MP-ID.
 
+
 ### Test DFT run times and memory requirements
 
 To get a rough estimate of DFT requirements for the supercells that you have chosen, you can use the `DFTSupercellSettingsMaker` 

docs/user/generation/data.md

@@ -100,25 +100,60 @@ that can be used to construct customized randomized structures workflows.
 
 ## VASP settings
 
-For the single-atom displaced as well as the randomized structures the [TightDFTStaticMaker](#autoplex.data.phonons.flows.TightDFTStaticMaker) is used to set up the 
-VASP calculation input and settings. PBEsol is the default GGA functional.
+This part will show you how you can adjust the different Makers for the VASP calculations in the workflow.
 
-The `TightDFTStaticMaker` settings can be overridden by
+For the single-atom displaced as well as the rattled structures the `autoplex` [TightDFTStaticMaker](#autoplex.data.phonons.flows.TightDFTStaticMaker) is 
+used to set up the VASP calculation input and settings. PBEsol is the default GGA functional. For the VASP calculation 
+of the isolated atoms' energies, `autoplex` also provides its own [IsoAtomStaticMaker](#autoplex.data.phonons.flows.IsoAtomStaticMaker), 
+which settings you can further adjust. 
+For the VASP geometry relaxation and static calculations of the unit cells as prerequisite calculations for generating 
+the single-atom displaced as well as the rattled supercells, 
+we rely on the [atomate2](https://materialsproject.github.io/atomate2/user/codes/vasp.html#list-of-vasp-workflows) 
+Makers `StaticMaker`, `TightRelaxMaker` in combination with the `StaticSetGenerator` VASP input set generator for this example.
 
 ```python
 from autoplex.auto.phonons.flows import CompleteDFTvsMLBenchmarkWorkflow
-from autoplex.data.phonons.flows import TightDFTStaticMaker
+from autoplex.data.phonons.flows import IsoAtomStaticMaker, TightDFTStaticMaker
+from atomate2.vasp.jobs.core import StaticMaker, TightRelaxMaker
 from atomate2.vasp.sets.core import StaticSetGenerator
 
-complete_flow = CompleteDFTvsMLBenchmarkWorkflow(
-    displacement_maker=TightDFTStaticMaker(
-    input_set_generator=StaticSetGenerator(user_incar_settings={
+example_input_set = StaticSetGenerator(  # you can also define multiple input sets
+    user_kpoints_settings={"grid_density": 1},
+    user_incar_settings={
         "ALGO": "Normal",
         "IBRION": -1,
         "ISPIN": 1,
         "ISMEAR": 0,
          ...,         # set all INCAR tags you need
         "SIGMA": 0.05,
         "GGA": "PE",  # switches to PBE
-         ...}))).make(...)
+         ...},
+)
+static_isolated_atom_maker = IsoAtomStaticMaker(
+    name="isolated_atom_maker",
+    input_set_generator=example_input_set,
+)
+displacement_maker = TightDFTStaticMaker(
+    name="displacement_maker",
+    input_set_generator=example_input_set,
+)
+rattled_bulk_relax_maker = TightRelaxMaker(
+    name="bulk_rattled_maker",
+    input_set_generator=example_input_set,
+)
+phonon_bulk_relax_maker = TightRelaxMaker(
+    name="bulk_phonon_maker",
+    input_set_generator=example_input_set,
+)
+phonon_static_energy_maker = StaticMaker(
+    name="phonon_static_energy_maker",
+    input_set_generator=example_input_set,
+)
+
+complete_flow = CompleteDFTvsMLBenchmarkWorkflow(
+    displacement_maker=displacement_maker,  # one displacement maker for rattled and single-atom displaced supercells to keep VASP settings consistent
+    phonon_bulk_relax_maker=phonon_bulk_relax_maker,
+    phonon_static_energy_maker=phonon_static_energy_maker,
+    rattled_bulk_relax_maker=rattled_bulk_relax_maker,
+    isolated_atom_maker=static_isolated_atom_maker,).make(...)
 ```