Merge pull request #168 from CalebBell/virial_fixes_2

Run CI on new updates

Author: CalebBell

.github/workflows/build.yml

@@ -17,6 +17,8 @@ jobs:
         os: [windows-latest, ubuntu-latest, macos-13, macos-latest]
         architecture: ['x86', 'x64']
         exclude:
+          - os: ubuntu-latest
+            python-version: 3.7
           # Only test pypy on Linux
           - os: windows-latest
             python-version: pypy3.9
@@ -98,7 +100,7 @@ jobs:
       run: |
         # Taken from scipy
         sudo apt-get update
-        sudo apt-get install -y libopenblas-dev libatlas-base-dev liblapack-dev gfortran libgmp-dev libmpfr-dev libsuitesparse-dev ccache libmpc-dev
+        sudo apt-get install -y libopenblas-dev libatlas-base-dev liblapack-dev gfortran libgmp-dev libmpfr-dev libsuitesparse-dev ccache libmpc-dev libjpeg-dev zlib1g-dev libtiff-dev libfreetype6-dev liblcms2-dev libwebp-dev
 
     - name: Install dependencies
       run: |

changelog.md

@@ -11,6 +11,26 @@
 ### Fixed
 
 
+## [0.4.2] - 2025-03-16
+
+### Added
+- Unifac 2.0: Hayer, Nicolas, Thorsten Wendel, Stephan Mandt, Hans Hasse, and Fabian Jirasek. “Advancing Thermodynamic Group-Contribution Methods by Machine Learning: UNIFAC 2.0.” Chemical Engineering Journal 504 (January 15, 2025): 158667. https://doi.org/10.1016/j.cej.2024.158667.
+
+- First pass implementation of Bondi group contribution method for estimating R and Q for UNIQUAC (and regressing new UNIFAC groups). Some definitions are unclear and/or hard to compute programatically. 
+- More UNIFAC groups have SMARTS groups patterns assigned to them
+- Add functions for identifying which functional groups are in a chemical
+- Molecule graph structure functions `count_rings_by_atom_counts`, `identify_functional_group_atoms`, `identify_conjugated_bonds`
+- New Diky Joback implementation which improves predictions of ideal gas heat capacity, from: Elliott, J. Richard, Vladimir Diky, Thomas A. Knotts IV, and W. Vincent Wilding. The Properties of Gases and Liquids, Sixth Edition. 6th edition. New York: McGraw Hill, 2023.
+- Activity coefficient models have `missing_interaction_parameters` function added to return a list of compound interactions that are missing
+
+### Changed
+ - NISTUFSG CH=NOH previously had the group ID 309, but this duplicated another 309 group CH2(O)2, so it was reassigned 1309 in thermo https://github.com/CalebBell/thermo/issues/158
+ - Reorganized the teperature dependent chemical property data additions to TDependentProperty objects so that data is added through generic methods, instead of hardcoding the method and attributes on the classes that the attributes are stored on. This positions thermo for adding new data sets easier in the future.
+ - Renamed arguments `cross_B_model` to `B_mixing_rule` of `VirialGas` to avoid confusion with similar parameter in `VirialCSP`. and the same for `cross_C_model` to `C_mixing_rule`
+ - Fix missing negative sign on `H_dep` of Virial model - this had impact on enthalpy derivatives, `G_dep`, and fugacity related terms as well. This was a serious bug and any `VirialCSP` calculations should be repeated because of it. 
+- Clean up UNIFAC assignment tests
+- Fix inconsistency of using IAPWS name for multiple TDependentProperty methods
+
 ## [0.4.0] - 2024-11-10
 
 ### Changed

docs/conf.py

@@ -58,8 +58,10 @@
     'matplotlib.sphinxext.plot_directive',
     'sphinxcontrib.katex',
     'sphinx_sitemap',
+    'sphinxcontrib.googleanalytics',
 ]
-
+googleanalytics_id = 'G-H82NH09HYY'
+                      
 katex_css_path = \
     'https://cdn.jsdelivr.net/npm/[email protected]/dist/katex.min.css'
 katex_js_path = 'katex.min.js'

docs/modules.rst

@@ -43,3 +43,4 @@ API Reference
    thermo.group_contribution.joback
    thermo.group_contribution.fedors
    thermo.group_contribution.wilson_jasperson
+   thermo.group_contribution.bondi

docs/property_objects.rst

@@ -120,7 +120,7 @@ The low-temperature linearly extrapolated value is actually the same as before,
 To better understand what methods are available, the :obj:`valid_methods <thermo.utils.TDependentProperty.valid_methods>` method checks all available correlations against their temperature limits.
 
 >>> ethanol_psat.valid_methods(100)
-['AMBROSE_WALTON', 'LEE_KESLER_PSAT', 'EDALAT', 'BOILING_CRITICAL', 'SANJARI']
+['AMBROSE_WALTON', 'LEE_KESLER_PSAT', 'EDALAT', 'BOILING_CRITICAL', 'EOS', 'SANJARI']
 
 If the temperature is not provided, all available methods are returned; the returned value favors the methods by the ranking defined in thermo, with the currently selected method as the first item.
 

docs/thermo.group_contribution.bondi.rst

@@ -0,0 +1,4 @@
+Bondi Group Contribution Method (thermo.group_contribution.fedors)
+==================================================================
+
+.. automodule:: thermo.group_contribution.bondi

docs/tutorial_phases_and_flash.rst

@@ -82,8 +82,6 @@ Obtain a heat capacity object, and select a source:
 >>> from thermo.heat_capacity import POLING_POLY
 >>> CpObj = HeatCapacityGas(CASRN='67-56-1')
 >>> CpObj.method = POLING_POLY
->>> CpObj.POLING_coefs # Show the coefficients
-[4.714, -0.006986, 4.211e-05, -4.443e-08, 1.535e-11]
 >>> HeatCapacityGases = [CpObj]
 
 Create a :obj:`ChemicalConstantsPackage <thermo.chemical_package.ChemicalConstantsPackage>` object which holds constant properties of the object, using a minimum of values:
@@ -109,7 +107,7 @@ Do a T-P flash:
 
 >>> res = flasher.flash(T=300, P=1e5)
 >>> res.phase, res.liquid0
-('L', CEOSLiquid(eos_class=PRMIX, eos_kwargs={"Tcs": [512.5], "Pcs": [8084000.0], "omegas": [0.559]}, HeatCapacityGases=[HeatCapacityGas(CASRN="67-56-1", extrapolation="linear", method="POLING_POLY")], T=300.0, P=100000.0, zs=[1.0]))
+('L', CEOSLiquid(eos_class=PRMIX, eos_kwargs={"Tcs": [512.5], "Pcs": [8084000.0], "omegas": [0.559]}, HeatCapacityGases=[HeatCapacityGas(CASRN="67-56-1", extrapolation="linear", method="POLING_POLY", Tmin=50.0, Tmax=1000.0)], T=300.0, P=100000.0, zs=[1.0]))
 
 Do a temperature and vapor-fraction flash:
 

requirements.txt

@@ -3,4 +3,4 @@ scipy>=1.6.0
 pandas
 coolprop
 fluids>=1.1.0
-chemicals>=1.3.2
+chemicals>=1.3.3

requirements_docs.txt

@@ -4,7 +4,7 @@ numpydoc
 pint
 nbsphinx
 fluids>=1.1.0
-chemicals>=1.3.2
+chemicals>=1.3.3
 IPython
 ipython
 numba
@@ -17,5 +17,6 @@ sphinxcontrib-devhelp==1.0.2
 sphinxcontrib-htmlhelp==2.0.1
 sphinxcontrib-qthelp==1.0.3
 sphinxcontrib-serializinghtml==1.1.5
+sphinxcontrib.googleanalytics
 matplotlib
 mpmath

requirements_test_multiarch.txt

@@ -1,6 +1,6 @@
 sympy
 fluids>=1.1.0
-chemicals>=1.3.2
+chemicals>=1.3.3
 pytest
 pint
 IPython