Merge branch 'main' into fm-v4

.github/workflows/build_docs.yml

@@ -6,6 +6,7 @@ on:
   workflow_dispatch:
   pull_request_review:
     types: [submitted, edited]
+  merge_group:
 
 jobs:
   build:

.github/workflows/lint.yml

@@ -6,6 +6,7 @@ on:
   pull_request:
     branches: [main]
   push:
+  merge_group:
 
 jobs:
   lint:

.github/workflows/test.yml

@@ -7,6 +7,7 @@ on:
     branches: [main]
   push:
     branches: [main]
+  merge_group:
 
 jobs:
   test:

docs/_toc.yml

@@ -43,7 +43,8 @@ parts:
   - file: tutorials/intro
   - file: tutorials/OCP-introduction
   - file: tutorials/adsorbml_walkthrough
-  - file: tutorials/cattsunami_walkthrough
+  - file: tutorials/cattsunami_tutorial
+  - file: tutorials/fairchem_models_for_nebs
   - file: tutorials/NRR/NRR_toc
     sections:
     - file: tutorials/NRR/NRR_example

docs/tutorials/NRR/NRR_example.md

@@ -34,6 +34,11 @@ import os
 from glob import glob
 import pandas as pd
 from fairchem.data.oc.utils import DetectTrajAnomaly
+
+# Set random seed to ensure adsorbate enumeration yields a valid candidate
+# If using a larger number of random samples this wouldn't be necessary
+import numpy as np
+np.random.seed(22)
 ```
 
 ```{code-cell} ipython3

docs/tutorials/fairchem_models_for_nebs.md

@@ -14,6 +14,9 @@ kernelspec:
 # Tutorial for using Fair Chemistry models to relax NEBs
 
 ```{code-cell} ipython3
+---
+tags: ["skip-execution"]
+---
 from ase.optimize import BFGS
 from ase.io import read
 
@@ -24,7 +27,6 @@ from fairchem.core.models.model_registry import model_name_to_local_file
 #Optional
 from x3dase.x3d import X3D
 import matplotlib.pyplot as plt
-from pathlib import Path
 import os
 ```
 
@@ -33,6 +35,9 @@ import os
 Shown here are the values used consistently throughout the paper.
 
 ```{code-cell} ipython3
+---
+tags: ["skip-execution"]
+---
 fmax = 0.05 # [eV / ang]
 delta_fmax_climb = 0.4 # this means that when the fmax is below 0.45 eV/Ang climbing image will be turned on
 k = 1 # you may adjust this value as you see fit
@@ -46,17 +51,24 @@ checkpoint_path = model_name_to_local_file('EquiformerV2-31M-S2EF-OC20-All+MD',
 ## If you have your own set of NEB frames
 
 ```{code-cell} ipython3
+---
+tags: ["skip-execution"]
+---
 """
 Load your frames (change to the appropriate loading method)
 The approach uses ase, so you must provide a list of ase.Atoms objects
 with the appropriate constraints.
 """
-path_ = Path(__file__).parents[2]
+cwd = os.getcwd()
+path_ = os.path.abspath(os.path.join(cwd, os.pardir, os.pardir))
 path_ = os.path.join(path_, "src", "fairchem", "applications", "cattsunami", "tutorial", "sample_traj.traj")
 frame_set = read(path_, ":")[0:10] # Change to the path to your atoms of the frame set
 ```
 
 ```{code-cell} ipython3
+---
+tags: ["skip-execution"]
+---
 neb = OCPNEB(
     frame_set,
     checkpoint_path=checkpoint_path,
@@ -78,7 +90,7 @@ if conv:
 
 You may use the `interpolate` function we implemented which is very similar to idpp but not sensative to periodic boundary crossings. Alternatively you can adopt whatever interpolation scheme you prefer. The `interpolate` function lacks some of the extra protections implemented in the `interpolate_and_correct_frames` which is used in the CatTSunami enumeration workflow. Care should be taken to ensure the results are reasonable.
 
-IMPORTANT NOTES: 
+IMPORTANT NOTES:
 1. Make sure the indices in the initial and final frame map to the same atoms
 2. Ensure you have the proper constraints on subsurface atoms