Patch attribute parsing errors

examples/nmr_chemical_shifts.py

@@ -1,28 +1,68 @@
 import isicle
 
 # Load example structure
-geom = isicle.load('CCCC(=O)O')
+geom = isicle.load("CCCC(=O)O")
 
 # Initial optimization
 geom = geom.initial_optimize(embed=True, forcefield="UFF", ff_iter=200)
 
 # Molecular dynamics
-md_result = geom.md(program='xtb',
-                    task='conformer',
-                    forcefield='gff',
-                    ewin=1,
-                    optlevel='Normal')
+md = isicle.md.md(
+    geom,
+    backend="xtb",
+    forcefield="gff",
+    optlevel="Normal",
+    ewin=3,
+    task="conformer",
+    solvation="water",
+    processes=4,
+)
+# Recommend saving, joblib or pkl
+isicle.save("nmr_conformers.joblib", md)
+
+# Parse molecular dynamics
+# Now separate from isicle.md.md()
+md_parsed = md.parse()
+
+# Using all conformers from CREST
+conformers = md_parsed["geometry"]["conformers"]
 
 # Density functional theory
-dft_result = md_result.get_structures().apply(func=isicle.qm.dft,
-                                              tasks=['energy', 'shielding'],
-                                              functional='b3lyp',
-                                              basis_set='3-21g*',
-                                              ao_basis='cartesian',
-                                              charge=0,
-                                              atoms=['C', 'H'],
-                                              temp=298.15,
-                                              processes=8)
-
-# Combine shielding result across conformers
-shielding = dft_result.get_structures().reduce('shielding', func='boltzmann')
+dft = conformers.apply(
+    func=isicle.qm.dft,
+    backend="nwchem",
+    tasks=["energy", "shielding"],
+    functional="b3lyp",
+    basis_set="6-31g*",
+    ao_basis="cartesian",
+    solvent="h2o",
+    gas=False,
+    atoms=["C", "H"],
+    temp=298.15,
+    scratch_dir="/tmp",
+    processes=8,
+)
+
+# Recommended saving, joblib or pkl
+isicle.save("nmr_dft_conformers.joblib", dft)
+
+# Parse density functional theory results
+dft_parsed = [x.parse() for x in dft]
+
+# Create conformational ensemble, which enable func mapping
+# Combine shielding result across conformers with Boltzmann weighting
+shielding = isicle.conformers.ConformationalEnsemble(
+    [x["geometry"] for x in dft_parsed]
+).reduce("_shielding")
+
+# Apply scaling factor to translate tensors to shifts
+shifts = isicle.conformers.transform(
+    shielding["mean"],
+    m={"H": -0.9921, "C": -0.9816},
+    b={"H": 32.2773, "C": 180.4295},
+    atom=shielding["atom"],
+    index=shielding["index"],
+)
+
+# Save results
+isicle.save("shifts.csv", shifts)