Fix geometry -> InChI generation

src/autochem/rate/data.py

@@ -648,7 +648,10 @@ def fit(
         if not validate or bad_fit == "fill":
             try:
                 with np.errstate(all="raise"):
-                    obj(T=T)
+                    vals = obj(T=T)
+                    if not np.all(np.isfinite(vals)):
+                        msg = "Fitted rate gives non-finite values over the input temperature range."
+                        raise FloatingPointError(msg)
             except FloatingPointError as e:
                 if A_fill is not None:
                     return cls(order=order, A=A_fill, b=0, E=0)
@@ -917,22 +920,25 @@ def fit(  # noqa: PLR0913
             (Options: "fill", replace with the fill value, or numpy.seterr options)
         :return: Rate fit
         """
-        bad_fits = [
-            "fill" if np.any(np.isclose(p, bad_fit_fill_pressures)) else bad_fit
-            for p in Ps
-        ]
-        k_data_fits = [
-            ArrheniusRateFit.fit(
+        k_fits = []
+        for k_data, P in zip(np.transpose(k_data), Ps, strict=True):
+            if validate:
+                print(f"Fitting Arrhenius rate for {P = }")
+
+            bad_fit = (
+                "fill" if np.any(np.isclose(P, bad_fit_fill_pressures)) else bad_fit
+            )
+            k_fit = ArrheniusRateFit.fit(
                 Ts=Ts,
-                ks=ks,
+                ks=k_data,
                 A_fill=A_fill,
-                bad_fit=f,  # pyright: ignore[reportArgumentType]
+                bad_fit=bad_fit,
                 validate=validate,
                 order=order,
                 units=units,
             )
-            for ks, f in zip(np.transpose(k_data), bad_fits, strict=True)
-        ]
+            k_fits.append(k_fit)
+
         k_high_fit = None
         if k_high is not None:
             k_high_fit = ArrheniusRateFit.fit(
@@ -943,9 +949,9 @@ def fit(  # noqa: PLR0913
 
         return cls(
             order=order,
-            As=[f.A for f in k_data_fits],
-            bs=[f.b for f in k_data_fits],
-            Es=[f.E for f in k_data_fits],
+            As=[f.A for f in k_fits],
+            bs=[f.b for f in k_fits],
+            Es=[f.E for f in k_fits],
             Ps=Ps,  # pyright: ignore[reportArgumentType]
         )
 

src/autochem/therm/_species.py

@@ -1,8 +1,9 @@
 """Thermodynamic data."""
 
 import datetime
+import re
 from collections.abc import Sequence
-from typing import ClassVar, Literal
+from typing import ClassVar, Literal, Self
 
 import altair as alt
 import numpy as np
@@ -23,6 +24,17 @@ class Species(Scalable):
     name: str
     therm: Therm_
 
+    def racemize(
+        self, enant_suffixes: tuple[str, str] = ("0", "1"), rac_suffix: str = "R"
+    ) -> Self:
+        """Racemize the thermodynamic functions for a chiral species."""
+        suffix0, suffix1 = enant_suffixes
+        pattern = re.compile(rf"(?:{re.escape(suffix0)}|{re.escape(suffix1)})$")
+        if pattern.search(self.name):
+            self.name = pattern.sub(rac_suffix, self.name)
+            self.therm = self.therm.racemize()
+        return self
+
     # Private attributes
     _scalers: ClassVar[Scalers] = {"therm": (lambda c, x: c * x)}
 

src/autochem/therm/data.py

@@ -45,6 +45,11 @@ class BaseTherm(ThermCalculator, UnitManager, Frozen, Scalable, SubclassTyped, a
     formula: Formula_
     charge: int = 0
 
+    @abc.abstractmethod
+    def racemize(self) -> Self:
+        """Racemize the thermodynamic functions for a chiral species."""
+        return self
+
     def display(  # noqa: PLR0913
         self,
         props: Sequence[Literal["Cv", "Cp", "S", "H", "dH"]] = ("Cp", "S", "H"),
@@ -227,6 +232,11 @@ def sort_by_temperature(self) -> Self:
         self.model_config["frozen"] = frozen
         return self
 
+    def racemize(self) -> Self:
+        """Racemize the thermodynamic functions for a chiral species."""
+        self.Z0 = np.add(self.Z0, np.log(2)).tolist()
+        return self
+
     # Replace this with a model validator (before or after), allowing extra arguments
     def __init__(
         self,
@@ -530,6 +540,12 @@ def piecewise_conditions(
             calc_high.in_bounds(T, include_max=True),
         ]
 
+    def racemize(self) -> Self:
+        """Racemize the thermodynamic functions for a chiral species."""
+        self.coeffs_low[-1] += np.log(2).item()
+        self.coeffs_high[-1] += np.log(2).item()
+        return self
+
     def heat_capacity(
         self,
         T: ArrayLike,  # noqa: N803

src/autochem/util/plot.py

@@ -166,7 +166,7 @@ def regular_scale(val_range: tuple[float, float]) -> alt.Scale:
     :param val_range: Range
     :return: Scale
     """
-    return alt.Scale(domain=val_range)
+    return alt.Scale(domain=val_range, domainMax=val_range[-1], nice=True)
 
 
 def regular_scale_axis(val_range: tuple[float, float]) -> alt.Axis:

src/automol/geom/_1conv.py

@@ -9,6 +9,7 @@
 import pyparsing as pp
 from numpy.typing import ArrayLike
 from pyparsing import pyparsing_common as ppc
+from rdkit.Chem.inchi import MolBlockToInchiAndAuxInfo
 from phydat import phycon
 
 from .. import vmat
@@ -340,38 +341,10 @@ def inchi_with_numbers(geo, stereo=True, gra=None):
         gra = graph_base.set_stereo_from_geometry(gra, geo)
 
     mlf, key_map_inv = molfile_with_atom_mapping(gra, geo=geo)
-    rdm = rdkit_.from_molfile(mlf)
-    ich, aux_info = rdkit_.to_inchi(rdm, with_aux_info=True)
+    ich, aux_info = MolBlockToInchiAndAuxInfo(mlf)
 
     nums_lst = _parse_sort_order_from_aux_info(aux_info)
     nums_lst = tuple(tuple(map(key_map_inv.__getitem__, nums)) for nums in nums_lst)
-
-    # Assuming the MolFile InChI works, the above code is all we need. What
-    # follows is to correct cases where it fails.
-    # This only appears to work sometimes, so when it doesn't, we fall back on
-    # the original inchi output.
-    if geo is not None:
-        gra = graph_base.set_stereo_from_geometry(gra, geo)
-        gra = graph_base.implicit(gra)
-        sub_ichs = inchi_base.split(ich)
-
-        failed = False
-
-        new_sub_ichs = []
-        for sub_ich, nums in zip(sub_ichs, nums_lst):
-            sub_gra = graph_base.subgraph(gra, nums, stereo=True)
-            sub_ich = _connected_inchi_with_graph_stereo(sub_ich, sub_gra, nums)
-            if sub_ich is None:
-                failed = True
-                break
-
-            new_sub_ichs.append(sub_ich)
-
-        # If it worked, replace the InChI with our forced-stereo InChI.
-        if not failed:
-            ich = inchi_base.join(new_sub_ichs)
-            ich = inchi_base.standard_form(ich)
-
     return ich, nums_lst