Release

.github/workflows/python-package.yml

@@ -18,13 +18,13 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.9", "3.10", "3.11", "3.12"]
+        python-version: ["3.10", "3.11", "3.12", "3.13", "3.14"]
         os: [ubuntu-latest]
 
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v6
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v5
+      uses: actions/setup-python@v6
       with:
         python-version: ${{ matrix.python-version }}
     - name: Install dependencies

README.md

@@ -23,12 +23,11 @@ conda install -c conda-forge chemcat
 
 ### Cite as:
 ```bibtex
-@ARTICLE{CubillosBlecicEtal2024journalRadiativeChemicalEquilibrium,
-       author = {{Cubillos}, Patricio and {Blecic}, Jasmina and {Fossati}, Luca},
-        title = "{Radiative and Chemical Equilibrium Calculations with Application to Exoplanets}",
-      journal = {journal},
-         year = 2024,
-       adsurl = {https://ui.adsabs.harvard.edu/abs/2024journ.000....0C},
-      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
+@ARTICLE{CubillosBlecicEtal2026mnrasPyratbay2,
+       author = {{Cubillos}, Patricio and {Blecic}, Jasmina and {Shulyak}, Denis and {Fossati}, Luca},
+        title = "{Pyrat Bay 2.0: an Upgraded Framework for Exoplanet Atmosphere Modeling in the JWST Era}",
+      journal = {MNRAS},
+         year = 2026,
+       adsurl = {https://ui.adsabs.harvard.edu/abs/2026mnras.000....0C},
 }
 ```

chemcat/__init__.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2022-2025 Blecic and Cubillos
+# Copyright (c) 2022-2026 Blecic and Cubillos
 # chemcat is open-source software under the GPL-2.0 license (see LICENSE)
 
 from .network import *

chemcat/cea/__init__.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2022-2025 Blecic and Cubillos
+# Copyright (c) 2022-2026 Blecic and Cubillos
 # chemcat is open-source software under the GPL-2.0 license (see LICENSE)
 
 from .cea import *

chemcat/cea/cea.py

@@ -1,12 +1,11 @@
-# Copyright (c) 2022-2025 Blecic and Cubillos
+# Copyright (c) 2022-2026 Blecic and Cubillos
 # chemcat is open-source software under the GPL-2.0 license (see LICENSE)
 
 __all__ = [
     'is_in',
     'read_thermo_build',
-    #'write_thermo_build',
-    'heat_func',
-    'gibbs_func',
+    'Heat',
+    'Gibbs',
     'setup_network',
     'find_species',
 ]
@@ -170,53 +169,72 @@ def read_thermo_build(species, thermo_file=None):
     return thermo_data
 
 
-def heat_func(a_coeffs, t_coeffs):
+class Heat():
     """
-    Generate a callable that evaluates the molar heat capacity
+    A class to evaluate the molar heat capacity
     at a given temperature array.
 
     Parameters
     ----------
-    a_coeffs: 2D float ndarray
+    species: string
+        Species name.  If provided, ignore coefficient inputs.
+    a_coeffs: 1D float ndarray
         Polynomial coefficients to reproduce the heat capacity data.
     t_coeffs: 1D float ndarray
         Temperature intervals of validity for each set of coefficients.
 
-    Returns
-    -------
-    heat: Callable
-        A function heat(temperature) that evaluates the molar heat
-        capacity at constant pressure (divided by the universal gas
-        constant), cp(T)/R, for a given temperature input
-        (which can be a single value or a 1D iterable).
-
     Examples
     --------
     >>> import chemcat.cea as cea
 
-    >>> data = cea.read_thermo_build(['H2O'])[0]
-    >>> heat = cea.heat_func(
-    >>>     data['a_coeffs'], data['t_coeffs'])
-
+    >>> heat = cea.Heat('H2O')
     >>> print(heat(300.0))
     [4.04063805]
     >>> print(heat([300.0, 1000.0, 3000.0]))
     [4.04063805 4.96614188 6.8342561 ]
     """
-    def heat(temperature):
+    def __init__(self, species=None, a_coeffs=None, t_coeffs=None):
+        if species is not None:
+            data = read_thermo_build([species])[0]
+            a_coeffs = data['a_coeffs']
+            t_coeffs = data['t_coeffs']
+        self.a_coeffs = a_coeffs
+        self.t_coeffs = t_coeffs
+
+    def __call__(self, temperature):
+        """
+        Parameters
+        ----------
+        temperature: scalar of 1D float
+            Polynomial coefficients to reproduce the heat capacity data.
+
+        Returns
+        -------
+        heat_capacity: 1D array
+            Evaluate the molar heat capacity at constant pressure
+            (divided by the universal gas constant), cp(T)/R
+
+        Examples
+        --------
+        >>> import chemcat.cea as cea
+
+        >>> heat = cea.Heat('H2O')
+        >>> print(heat(300.0))
+        [4.04063805]
+        >>> print(heat([300.0, 1000.0, 3000.0]))
+        [4.04063805 4.96614188 6.8342561 ]
+        """
         if not isinstance(temperature, Iterable):
             temperature = [temperature]
         temperature = np.array(temperature, np.double)
 
-        heat_capacity = u.heat(temperature, a_coeffs, t_coeffs)
+        heat_capacity = u.heat(temperature, self.a_coeffs, self.t_coeffs)
         return heat_capacity
-    return heat
 
 
-def gibbs_func(a_coeffs, b_coeffs, t_coeffs):
+class Gibbs():
     """
-    Generate a callable that evaluates the Gibbs free energy
-    for a given temperature array.
+    A class to evaluate the Gibbs free energy for a given temperature array.
 
     Parameters
     ----------
@@ -227,35 +245,59 @@ def gibbs_func(a_coeffs, b_coeffs, t_coeffs):
     t_coeffs: 1D float ndarray
         Temperature intervals of validity for each set of coefficients.
 
-    Returns
-    -------
-    gibbs: Callable
-        A function gibbs(temperature) that evaluates the Gibbs free
-        energy, G(T)/RT, for a given temperature input (which can be
-        a single value or a 1D iterable).
-
     Examples
     --------
     >>> import chemcat.cea as cea
 
-    >>> data = cea.read_thermo_build(['H2O'])[0]
-    >>> gibbs = cea.gibbs_func(
-    >>>     data['a_coeffs'], data['b_coeffs'], data['t_coeffs'])
-
+    >>> gibbs = cea.Gibbs('H2O')
     >>> print(gibbs(300.0))
     [-119.66025955]
     >>> print(gibbs([300.0, 1000.0, 3000.0]))
     [-119.66025955  -53.94898416  -39.09425268]
     """
-    def gibbs(temperature):
+    def __init__(self, species=None, a_coeffs=None, b_coeffs=None, t_coeffs=None):
+        if species is not None:
+            data = read_thermo_build([species])[0]
+            a_coeffs =  data['a_coeffs']
+            b_coeffs =  data['b_coeffs']
+            t_coeffs =  data['t_coeffs']
+
+        self.a_coeffs = a_coeffs
+        self.b_coeffs = b_coeffs
+        self.t_coeffs = t_coeffs
+
+    def __call__(self, temperature):
+        """
+        Parameters
+        ----------
+        temperature: scalar of 1D float
+            Polynomial coefficients to reproduce the heat capacity data.
+
+        Returns
+        -------
+        gibbs_free_energy: 1D array
+            The Gibbs free energy, G(T)/RT, at temperature input
+
+        Examples
+        --------
+        >>> import chemcat.cea as cea
+
+        >>> data = cea.read_thermo_build(['H2O'])[0]
+        >>> gibbs = cea.gibbs_func(
+        >>>     data['a_coeffs'], data['b_coeffs'], data['t_coeffs'])
+
+        >>> print(gibbs(300.0))
+        [-119.66025955]
+        >>> print(gibbs([300.0, 1000.0, 3000.0]))
+        [-119.66025955  -53.94898416  -39.09425268]
+        """
         if not isinstance(temperature, Iterable):
             temperature = [temperature]
         temperature = np.array(temperature, np.double)
 
-        free_energy = u.gibbs(
-            temperature, a_coeffs, b_coeffs, t_coeffs)
+        free_energy = u.gibbs(temperature, self.a_coeffs, self.b_coeffs, self.t_coeffs)
         return free_energy
-    return gibbs
+
 
 
 def setup_network(input_species):
@@ -325,10 +367,14 @@ def setup_network(input_species):
     gibbs_free_energy = []
     stoich_data = []
     for data in thermo_data:
-        heat_capacity.append(
-            heat_func(data['a_coeffs'], data['t_coeffs']))
-        gibbs_free_energy.append(
-            gibbs_func(data['a_coeffs'], data['b_coeffs'], data['t_coeffs']))
+        a_coeffs = data['a_coeffs']
+        b_coeffs = data['b_coeffs']
+        t_coeffs = data['t_coeffs']
+        heat = Heat(a_coeffs=a_coeffs, t_coeffs=t_coeffs)
+        gibbs = Gibbs(a_coeffs=a_coeffs, b_coeffs=b_coeffs, t_coeffs=t_coeffs)
+
+        heat_capacity.append(heat)
+        gibbs_free_energy.append(gibbs)
         stoich_data.append(data['stoich'])
 
     return (

chemcat/data/thermo_build_cea.dat

@@ -42,6 +42,14 @@ C-                Hotop,1985. Gordon,1999.
    6000.000  20000.0007 -2.0 -1.0  0.0  1.0  2.0  3.0  4.0  0.0         6218.836
  1.223289007D+01-5.196185830D-03 2.500001344D+00-1.743497251D-10 1.206609009D-14
 -4.252419790D-19 5.992333270D-24                 7.001221630D+04 4.879608421D+00
+CaH               Gurvich,1996a pt1 p447 pt2 p353.
+ 2 tpis96 CA  1.00H   1.00    0.00    0.00    0.00 0   41.0859400     229409.105
+    200.000   1000.0007 -2.0 -1.0  0.0  1.0  2.0  3.0  4.0  0.0         8705.105
+-4.513782230D+04 7.629429210D+02-1.280874223D+00 1.318774659D-02-1.481595334D-05
+ 8.536573220D-09-1.989958945D-12 0.000000000D+00 2.300378814D+04 3.053421525D+01
+   1000.000   6000.0007 -2.0 -1.0  0.0  1.0  2.0  3.0  4.0  0.0         8705.105
+-2.696952529D+06 8.607059750D+03-7.027454820D+00 7.467916310D-03-2.318610699D-06
+ 3.423072420D-10-1.892679792D-14 0.000000000D+00-2.773819107D+04 7.845822010D+01
 CH                Gurvich,1979 pt1 p37 pt2 p39.                                 
  3 tpis79 C   1.00H   1.00    0.00    0.00    0.00 0   13.0186400     597370.604
     200.000   1000.0007 -2.0 -1.0  0.0  1.0  2.0  3.0  4.0  0.0         8625.104

chemcat/data/white_pages.txt

@@ -21,4 +21,5 @@ OAlH      HAlO
 OAlOH     HAlO2
 ONO-      NO2-
 SSO       S2O
+COS       COS               OCS
 None      C4H2,butadiyne    C4H2

chemcat/janaf/__init__.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2022-2025 Blecic and Cubillos
+# Copyright (c) 2022-2026 Blecic and Cubillos
 # chemcat is open-source software under the GPL-2.0 license (see LICENSE)
 
 from .janaf import *

chemcat/janaf/janaf.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2022-2025 Blecic and Cubillos
+# Copyright (c) 2022-2026 Blecic and Cubillos
 # chemcat is open-source software under the GPL-2.0 license (see LICENSE)
 
 __all__ = [
@@ -417,4 +417,3 @@ def find_species(elements, charge='neutral', num_atoms=None, state='gas'):
 
     return np.array(species)
 
-

chemcat/network.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2022-2025 Blecic and Cubillos
+# Copyright (c) 2022-2026 Blecic and Cubillos
 # chemcat is open-source software under the GPL-2.0 license (see LICENSE)
 
 __all__ = [

chemcat/utils/__init__.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2022-2025 Blecic and Cubillos
+# Copyright (c) 2022-2026 Blecic and Cubillos
 # chemcat is open-source software under the GPL-2.0 license (see LICENSE)
 
 from .utils import *

chemcat/utils/utils.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2022-2025 Blecic and Cubillos
+# Copyright (c) 2022-2026 Blecic and Cubillos
 # chemcat is open-source software under the GPL-2.0 license (see LICENSE)
 
 __all__ = [

chemcat/version.py

@@ -1,6 +1,6 @@
-# Copyright (c) 2022-2025 Blecic and Cubillos
+# Copyright (c) 2022-2026 Blecic and Cubillos
 # chemcat is open-source software under the GPL-2.0 license (see LICENSE)
 
 # chemcat version:
-__version__ = '0.3.12'
+__version__ = '1.0.0'