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‎MANIFEST.in

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exclude .readthedocs.yml
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exclude requirements-dev.txt
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exclude *.png
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exclude binder.ipynb
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exclude reminder.md
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recursive-exclude dist *

‎README.md

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ugropy is in an early development stage, leaving issues of examples of
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molecules that ugropy fails solving the UNIFAC's groups is very helpful.
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## Try ugropy now
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You can try ugropy from it's
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[Binder](https://mybinder.org/v2/gh/ipqa-research/ugropy/main). Open the
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binder.ipynb file to explore the basic features.
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## Models supported v1.0.0
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- Classic liquid-vapor UNIFAC
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- Predictive Soave-Redlich-Kwong (PSRK)
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- Joback
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## Example of use
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You can check the full tutorial [here](https://ugropy.readthedocs.io/en/latest/tutorial/tutorial.html).
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You can check the full tutorial
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[here](https://ugropy.readthedocs.io/en/latest/tutorial/tutorial.html).
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Get UNIFAC groups from the molecule's name:
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657.4486692170663 K
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1.0254019428522743 bar
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Write down the [Clapeyron.jl](https://github.com/ClapeyronThermo/Clapeyron.jl)
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.csv input files.
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```python
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from ugropy import writers
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names = ["limonene", "adrenaline", "Trinitrotoluene"]
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grps = [Groups(n) for n in names]
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# Write the csv files into a database directory
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writers.to_clapeyron(
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molecules_names=names,
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unifac_groups=[g.unifac_groups for g in grps],
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psrk_groups=[g.psrk_groups for g in grps],
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joback_objects=[g.joback for g in grps],
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path="./database"
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)
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```
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## Installation
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At the moment ugropy is not uploaded in PyPI (will be soon).
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‎binder.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Welcome to the ugropy's Binder\n",
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"\n",
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"You can use this notebook to try the basics features of ugropy. You can \n",
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"check the full tutorial here: https://ugropy.readthedocs.io/en/latest/index.html\n",
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"\n",
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"Let's use the Groups class to obtain information of the desired molecules:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 35,
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"metadata": {},
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"outputs": [],
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"source": [
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"from ugropy import Groups\n",
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"\n",
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"# Write the molecule's name as it appears on pubchem\n",
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"molecule_name = \"ethanol\"\n",
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"\n",
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"mol = Groups(molecule_name)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Get groups information and properties from the Joback model"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 36,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{'CH3': 1, 'CH2': 1, 'OH': 1}\n",
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"{'CH3': 1, 'CH2': 1, 'OH': 1}\n",
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"{'-CH3': 1, '-CH2-': 1, '-OH (alcohol)': 1}\n"
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]
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}
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],
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"source": [
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"print(mol.unifac_groups)\n",
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"print(mol.psrk_groups)\n",
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"print(mol.joback.groups)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 37,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"57.56641437226128\n",
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"499.40737356625846\n",
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"1.702089531406276\n"
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]
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}
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],
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"source": [
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"# Experimental value of ethanol's critical pressure is 61.37 bar\n",
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"print(mol.joback.critical_pressure)\n",
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"\n",
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"# Experimental value of ethanol's critical temperature is 514.0 K\n",
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"print(mol.joback.critical_temperature)\n",
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"\n",
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"# Vapor pressure at the normal boiling temperature of ethanol\n",
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"print(mol.joback.vapor_pressure(78.37 + 273.15))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"You can provide the normal boiling point of the molecules to improve some \n",
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"Joback's predictions."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 38,
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"metadata": {},
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"outputs": [],
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"source": [
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"mol = Groups(molecule_name, normal_boiling_temperature=78.37+273.15)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 39,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"520.0914853232541\n",
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"1.0132499999999998\n"
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]
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}
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],
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"source": [
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"print(mol.joback.critical_temperature)\n",
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"\n",
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"print(mol.joback.vapor_pressure(78.37+273.15))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"You can also create a Groups object from the molecule's SMILES."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 40,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"520.0914853232541\n",
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"1.0132499999999998\n"
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]
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}
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],
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"source": [
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"# Ethanol again\n",
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"mol = Groups(\n",
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" \"CCO\", \n",
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" identifier_type=\"smiles\", \n",
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" normal_boiling_temperature=78.37+273.15\n",
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")\n",
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"\n",
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"print(mol.joback.critical_temperature)\n",
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"\n",
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"print(mol.joback.vapor_pressure(78.37+273.15))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Check the tutorial to explore more features."
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "ugropy",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.12"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎docs/source/README.rst

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657.4486692170663 K
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1.0254019428522743 bar
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Write down the Clapeyron.jl .csv input files.
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.. code:: python
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from ugropy import writers
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names = ["limonene", "adrenaline", "Trinitrotoluene"]
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grps = [Groups(n) for n in names]
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# Write the csv files into a database directory
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writers.to_clapeyron(
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molecules_names=names,
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unifac_groups=[g.unifac_groups for g in grps],
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psrk_groups=[g.psrk_groups for g in grps],
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joback_objects=[g.joback for g in grps],
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path="./database"
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)
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Installation
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============
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‎docs/source/tutorial/database/PSRK/PSRK_groups.csv

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Clapeyron Database File,
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PSRK Groups [csvtype = groups,grouptype = PSRK]
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species,groups
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limonene,"[""CH3"" => 2, ""CH2"" => 3, ""CH"" => 1, ""CH2=C"" => 1, ""CH=C"" => 1]"
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adrenaline,"[""CH2"" => 1, ""ACH"" => 3, ""ACCH"" => 1, ""OH"" => 1, ""ACOH"" => 2, ""CH3NH"" => 1]"
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Trinitrotoluene,"[""ACH"" => 2, ""ACCH3"" => 1, ""ACNO2"" => 3]"

‎docs/source/tutorial/database/critical.csv

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Clapeyron Database File,,,,,
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Critical Single Parameters,,,,,
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species,CAS,Tc,Pc,Vc,acentricfactor
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limonene,,657.4486692170663,2755561.066677689,0.0004965,0.3219127551737521
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adrenaline,,953.7486693594541,5569169.079973267,0.0004115,1.6071531017924205
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Trinitrotoluene,,1146.7095578060987,4067315.701790919,0.0005654999999999999,1.0796561474496789

‎docs/source/tutorial/database/molarmass.csv

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Clapeyron Database File,,
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Molar Mases Single Params,,
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species,CAS,Mw
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limonene,,136.23760000000001
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adrenaline,,183.20680000000002
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Trinitrotoluene,,227.132

‎docs/source/tutorial/database/ogUNIFAC/ogUNIFAC_groups.csv

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Clapeyron Database File,
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original UNIFAC Groups,[csvtype = groups,grouptype = originalUNIFAC]
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species,groups
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limonene,"[""CH3"" => 2, ""CH2"" => 3, ""CH"" => 1, ""CH2=C"" => 1, ""CH=C"" => 1]"
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adrenaline,"[""CH2"" => 1, ""ACH"" => 3, ""ACCH"" => 1, ""OH"" => 1, ""ACOH"" => 2, ""CH3NH"" => 1]"
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Trinitrotoluene,"[""ACH"" => 2, ""ACCH3"" => 1, ""ACNO2"" => 3]"

‎docs/source/tutorial/easy_way.ipynb

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"metadata": {},
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"source": [
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"Well, that was easy... `ugropy` uses\n",
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"[`PubChemPy`](https://github.com/mcs07/PubChemPy) to access to pubchem and\n",
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"`PubChemPy` (https://github.com/mcs07/PubChemPy) to access to pubchem and\n",
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"obtain the SMILES representation of the molecule. ugropy uses the SMILES\n",
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"representation and the [`rdkit`](https://github.com/rdkit/rdkit) library to\n",
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"representation and the `rdkit` (https://github.com/rdkit/rdkit) library to\n",
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"obtain the functional groups of the molecules.\n",
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"\n",
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"The complete signature of the `Groups` class is the following:"
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.12"
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"version": "3.10.6"
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}
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},
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"nbformat": 4,

‎docs/source/tutorial/hard_way.ipynb

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"#### Joback\n",
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"\n",
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"For context, check the [Joback's article](https://doi.org/10.1080/00986448708960487).\n",
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"For context, check the Joback's article: https://doi.org/10.1080/00986448708960487\n",
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"\n",
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"The Joback object is instantiated by the Group object as we saw in the previous \n",
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"tutorial but, a Joback object can be instantiated individually:"
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.12"
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"version": "3.10.6"
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}
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},
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"nbformat": 4,

‎docs/source/tutorial/installation.ipynb

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"At the moment ugropy is not uploaded in PyPI (will be soon).\n",
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"\n",
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"```\n",
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"pip install git+https://github.com/SalvadorBrandolin/ugropy.git\n",
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"pip install git+https://github.com/ipqa-research/ugropy.git\n",
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"```"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "ugropy",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"name": "python"
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"name": "python",
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"version": "3.10.12"
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}
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"nbformat": 4,

‎docs/source/tutorial/tutorial.rst

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installation.ipynb
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easy_way.ipynb
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hard_way.ipynb
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ugropy_failing.ipynb
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ugropy_failing.ipynb
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writers.ipynb

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