python 化学_chempy-ChemPy是一个Python包，用于解决化学问题。-Bjoern I. Dahlgren About ChemPy Documentation Installati...

作者:Bjoern I. Dahlgren

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ChemPy

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.. contents::

About ChemPy

ChemPy is a Python _ package useful for chemistry (mainly physical/inorganic/analytical chemistry). Currently it includes:

Numerical integration routines for chemical kinetics (ODE solver front-end)

Integrated rate expressions (and convenience fitting routines)

Solver for equilibria (including multiphase systems)

Relations in physical chemistry:

Debye-Hückel expressions

Arrhenius & Eyring equation

Einstein-Smoluchowski equation

Properties (pure python implementations from the literature)

water density as function of temperature

water permittivity as function of temperature and pressure

water diffusivity as function of temperature

water viscosity as function of temperature

sulfuric acid density as function of temperature & weight fraction H₂SO₄

More to come... (and contributions are most welcome!)

Documentation

The easiest way to get started is to have a look at the examples in this README, and also the jupyter notebooks. In addition there is auto-generated API documentation for the latest stable release here (and here are _ the API docs for the development version).

.. _notebooks: http://hera.physchem.kth.se/~chempy/branches/master/examples

Installation

Simplest way to install ChemPy and its (optional) dependencies is to use the conda package manager _::

$ conda install -c bjodah chempy pytest $ pytest -rs -W ignore::chempy.ChemPyDeprecationWarning --pyargs chempy

currently conda packages are only provided for Linux. On Windows and OS X you will need to use pip instead::

$ python3 -m pip install chempy pytest $ python3 -m pytest -rs -W ignore::chempy.ChemPyDeprecationWarning --pyargs chempy

there will a few tests which will be skipped due to some missing optional backends in addition to those in SciPy (used for solving systems of non-linear equations and ordinary differential equations).

If you are still using Python 2 you can use the long-term-support 0.6.x branch of ChemPy which will continue to receive bugfixes::

$ python2 -m pip install "chempy<0.7"

Optional dependencies ~~~~~~~~~~~~~~~~~~~~~ If you used conda to install ChemPy you can skip this section. But if you use pip the default installation is achieved by writing::

$ python3 -m pip install --user --upgrade chempy pytest $ python3 -m pytest -rs --pyargs chempy

you can skip the --user flag if you have got root permissions. You may be interested in using additional backends (in addition to those provided by SciPy) for solving ODE-systems and non-linear optimization problems::

$ python3 -m pip install chempy[all]

Note that this option will install the following libraries (some of which require additional libraries to be present on your system):

pygslodeiv2 : solving initial value problems, requires GSL. (>=1.16).

pyodeint : solving initial value problems, requires boost (>=1.65.0).

pycvodes : solving initial value problems, requires SUNDIALS (>=5.3.0).

pykinsol : solving non-linear root-finding, requires SUNDIALS (>=5.3.0).

pycompilation _: python front-end for calling compilers, requires gcc/clang/icpc.

pycodeexport _: package for code-generation, used when generating C++ code.

.. _GSL: https://www.gnu.org/software/gsl/ .. _boost: http://www.boost.org/ .. _SUNDIALS: https://computation.llnl.gov/projects/sundials

if you want to see what packages need to be installed on a Debian based system you may look at this Dockerfile _.

Using Docker ~~~~~~~~~~~~ If you have Docker _ installed, you may use it to host a jupyter notebook server::

$ ./scripts/host-jupyter-using-docker.sh . 8888

the first time you run the command, some dependencies will be downloaded. When the installation is complete there will be a link visible which you can open in your browser. You can also run the test suite using the same docker-image::

$ ./scripts/host-jupyter-using-docker.sh . 0

there will be a few skipped test (due to some dependencies not being installed by default) and quite a few warnings.

Examples

See demonstration scripts in examples/ , and some rendered jupyter notebooks. You may also browse the documentation for more examples. Below you will find a few code snippets:

Parsing formulae ~~~~~~~~~~~~~~~~ .. code:: python

from chempy import Substance ferricyanide = Substance.fromformula('Fe(CN)6-3') ferricyanide.composition == {0: -3, 26: 1, 6: 6, 7: 6} # 0 for charge True print(ferricyanide.unicodename) Fe(CN)₆³⁻ print(ferricyanide.latexname + ", " + ferricyanide.htmlname) Fe(CN)_{6}^{3-}, Fe(CN)63- print('%.3f' % ferricyanide.mass) 211.955

as you see, in composition, the atomic numbers (and 0 for charge) is used as keys and the count of each kind became respective value.

Balancing stoichiometry of a chemical reaction ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. code:: python

from chempy import balancestoichiometry # Main reaction in NASA's booster rockets: reac, prod = balancestoichiometry({'NH4ClO4', 'Al'}, {'Al2O3', 'HCl', 'H2O', 'N2'}) from pprint import pprint pprint(dict(reac)) {'Al': 10, 'NH4ClO4': 6} pprint(dict(prod)) {'Al2O3': 5, 'H2O': 9, 'HCl': 6, 'N2': 3} from chempy import massfractions for fractions in map(massfractions, [reac, prod]): ... pprint({k: '{0:.3g} wt%'.format(v*100) for k, v in fractions.items()}) ... {'Al': '27.7 wt%', 'NH4ClO4': '72.3 wt%'} {'Al2O3': '52.3 wt%', 'H2O': '16.6 wt%', 'HCl': '22.4 wt%', 'N2': '8.62 wt%'}

ChemPy can also balance reactions where the reacting species are more complex and are better described in other terms than their molecular formula. A silly, yet illustrative example would be how to make pancakes without any partially used packages:

.. code:: python

substances = {s.name: s for s in [ ... Substance('pancake', composition=dict(eggs=1, spoonsofflour=2, cupsofmilk=1)), ... Substance('eggs6pack', composition=dict(eggs=6)), ... Substance('milkcarton', composition=dict(cupsofmilk=4)), ... Substance('flourbag', composition=dict(spoonsofflour=60)) ... ]} pprint([dict() for _ in balancestoichiometry({'eggs6pack', 'milkcarton', 'flourbag'}, ... {'pancake'}, substances=substances)]) [{'eggs6pack': 10, 'flourbag': 2, 'milk_carton': 15}, {'pancake': 60}]

ChemPy can even handle reactions with linear dependencies (underdetermined systems), e.g.:

.. code:: python

pprint([dict() for _ in balancestoichiometry({'C', 'O2'}, {'CO2', 'CO'})]) # doctest: +SKIP [{'C': x1 + 2, 'O2': x1 + 1}, {'CO': 2, 'CO2': x1}]

the x1 object above is an instance of SymPy's Symbol_. If we prefer to get a solution with minimal (non-zero) integer coefficients we can pass underdetermined=None:

.. code:: python

pprint([dict() for _ in balancestoichiometry({'C', 'O2'}, {'CO2', 'CO'}, underdetermined=None)]) [{'C': 3, 'O2': 2}, {'CO': 2, 'CO2': 1}]

note however that even though this solution is in some sense "canonical", it is merely one of an inifite number of solutions (x1 from earlier may be any integer).

.. _Symbol: http://docs.sympy.org/latest/modules/core.html#sympy.core.symbol.Symbol

Balancing reactions ~~~~~~~~~~~~~~~~~~~ .. code:: python

from chempy import Equilibrium from sympy import symbols K1, K2, Kw = symbols('K1 K2 Kw') e1 = Equilibrium({'MnO4-': 1, 'H+': 8, 'e-': 5}, {'Mn+2': 1, 'H2O': 4}, K1) e2 = Equilibrium({'O2': 1, 'H2O': 2, 'e-': 4}, {'OH-': 4}, K2) coeff = Equilibrium.eliminate([e1, e2], 'e-') coeff [4, -5] redox = e1coeff[0] + e2coeff[1] print(redox) 32 H+ + 4 MnO4- + 20 OH- = 26 H2O + 4 Mn+2 + 5 O2; K14/K25 autoprot = Equilibrium({'H2O': 1}, {'H+': 1, 'OH-': 1}, Kw) n = redox.cancel(autoprot) n 20 redox2 = redox + nautoprot print(redox2) 12 H+ + 4 MnO4- = 6 H2O + 4 Mn+2 + 5 O2; K14Kw20/K2**5

Working with units ~~~~~~~~~~~~~~~~~~ Functions and objects useful for working with units are available from the chempy.units module. Here is an example of how ChemPy can check consistency of units:

.. code:: python

from chempy import Reaction r = Reaction.fromstring("H2O -> H+ + OH-; 1e-4/M/s") Traceback (most recent call last): ... ValueError: Unable to convert between units of "1/M" and "dimensionless" r = Reaction.fromstring("H2O -> H+ + OH-; 1e-4/s") from chempy.units import tounitless, defaultunits as u to_unitless(r.param, 1/u.minute) 0.006

right now the .units module wraps the quantities_ package with some minor additions and work-arounds. However, there is no guarantee that the underlying package will not change in a future version of ChemPy (there are many packages for dealing with units in the scientific Python ecosystem).

.. _quantities: http://python-quantities.readthedocs.io/en/latest/

Chemical equilibria ~~~~~~~~~~~~~~~~~~~ If we want to predict pH of a bicarbonate solution we simply just need pKa and pKw values:

.. code:: python

from collections import defaultdict from chempy.equilibria import EqSystem eqsys = EqSystem.from_string("""HCO3- = H+ + CO3-2; 10-10.3 ... H2CO3 = H+ + HCO3-; 10-6.3 ... H2O = H+ + OH-; 10**-14/55.4 ... """) # pKa1(H2CO3) = 6.3 (implicitly incl. CO2(aq)), pKa2=10.3 & pKw=14 arr, info, sane = eqsys.root(defaultdict(float, {'H2O': 55.4, 'HCO3-': 1e-2})) conc = dict(zip(eqsys.substances, arr)) from math import log10 print("pH: %.2f" % -log10(conc['H+'])) pH: 8.30

here is another example for ammonia:

.. code:: python

from chempy import Equilibrium from chempy.chemistry import Species waterautop = Equilibrium({'H2O'}, {'H+', 'OH-'}, 10-14) # unit "molar" assumed ammoniaprot = Equilibrium({'NH4+'}, {'NH3', 'H+'}, 10-9.24) # same here substances = [Species.fromformula(f) for f in 'H2O OH- H+ NH3 NH4+'.split()] eqsys = EqSystem([waterautop, ammoniaprot], substances) print('\n'.join(map(str, eqsys.rxns))) # "rxns" short for "reactions" H2O = H+ + OH-; 1e-14 NH4+ = H+ + NH3; 5.75e-10 initconc = defaultdict(float, {'H2O': 1, 'NH3': 0.1}) x, sol, sane = eqsys.root(init_conc) assert sol['success'] and sane print(', '.join('%.2g' % v for v in x)) 1, 0.0013, 7.6e-12, 0.099, 0.0013

Concepts ~~~~~~~~~ ChemPy collects equations and utility functions for working with concepts such as ionic strength _:

.. code:: python

from chempy.electrolytes import ionicstrength ionicstrength({'Fe+3': 0.050, 'ClO4-': 0.150}) == .3 True

note how ChemPy parsed the charges from the names of the substances. There are also e.g. empirical equations and convenience classes for them available, e.g.:

.. code:: python

from chempy.henry import Henry kHO2 = Henry(1.2e-3, 1800, ref='carpenter1966') print('%.1e' % kH_O2(298.15)) 1.2e-03

to get more information about e.g. this class, you may can look at the API documentation_.

.. _API documentation: https://bjodah.github.io/chempy/latest/chempy.html#module-chempy.henry

Chemical kinetics (system of ordinary differential equations) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ A common task when modelling problems in chemistry is to investigate the time dependence of a system. This branch of study is known as chemical kinetics _, and ChemPy has some classes and functions for working with such problems:

.. code:: python

from chempy import ReactionSystem # The rate constants below are arbitrary rsys = ReactionSystem.fromstring("""2 Fe+2 + H2O2 -> 2 Fe+3 + 2 OH-; 42 ... 2 Fe+3 + H2O2 -> 2 Fe+2 + O2 + 2 H+; 17 ... H+ + OH- -> H2O; 1e10 ... H2O -> H+ + OH-; 1e-4""") # "[H2O]" = 1.0 (actually 55.4 at RT) from chempy.kinetics.ode import getodesys odesys, extra = getodesys(rsys) from collections import defaultdict import numpy as np tout = sorted(np.concatenate((np.linspace(0, 23), np.logspace(-8, 1)))) c0 = defaultdict(float, {'Fe+2': 0.05, 'H2O2': 0.1, 'H2O': 1.0, 'H+': 1e-2, 'OH-': 1e-12}) result = odesys.integrate(tout, c0, atol=1e-12, rtol=1e-14) import matplotlib.pyplot as plt fig, axes = plt.subplots(1, 2, figsize=(12, 5)) for ax in axes: ... _ = result.plot(names=[k for k in rsys.substances if k != 'H2O'], ax=ax) ... _ = ax.legend(loc='best', prop={'size': 9}) ... _ = ax.setxlabel('Time') ... _ = ax.setylabel('Concentration') _ = axes[1].setylim([1e-13, 1e-1]) _ = axes[1].setxscale('log') _ = axes[1].setyscale('log') _ = fig.tight_layout() _ = fig.savefig('examples/kinetics.png', dpi=72)

.. image:: https://raw.githubusercontent.com/bjodah/chempy/master/examples/kinetics.png

Properties ~~~~~~~~~~ One of the fundamental tasks in science is the careful collection of data about the world around us. ChemPy contains a growing collection of parametrizations from the scientific literature with relevance in chemistry. Here is how you use one of these formulations:

.. code:: python

from chempy import Substance from chempy.properties.waterdensitytanaka2001 import waterdensity as rho from chempy.units import tounitless, defaultunits as u water = Substance.fromformula('H2O') for TC in (15, 25, 35): ... concentrationH2O = rho(T=(273.15 + TC)*u.kelvin, units=u)/water.molarmass(units=u) ... print('[H2O] = %.2f M (at %d °C)' % (tounitless(concentrationH2O, u.molar), TC)) ... [H2O] = 55.46 M (at 15 °C) [H2O] = 55.35 M (at 25 °C) [H2O] = 55.18 M (at 35 °C)

Run notebooks using binder ~~~~~~~~~~~~~~~~~~~~~~~~~~ Using only a web-browser (and an internet connection) it is possible to explore the notebooks here: (by the courtesy of the people behind mybinder)

.. image:: http://mybinder.org/badge.svg :target: https://mybinder.org/v2/gh/bjodah/chempy/f5f2546e79e165ba8fb258fc87d83a7fbdcbad64?filepath=index.ipynb :alt: Binder

Citing

If you make use of ChemPy in e.g. academic work you may cite the following peer-reviewed publication:

.. image:: http://joss.theoj.org/papers/10.21105/joss.00565/status.svg :target: https://doi.org/10.21105/joss.00565 :alt: Journal of Open Source Software DOI

Depending on what underlying solver you are using you should also cite the appropriate paper (you can look at the list of references in the JOSS article). If you need to reference, in addition to the paper, a specific point version of ChemPy (for e.g. reproducibility) you can get per-version DOIs from the zendodo archive:

.. image:: https://zenodo.org/badge/8840/bjodah/chempy.svg :target: https://zenodo.org/badge/latestdoi/8840/bjodah/chempy :alt: Zenodo DOI

Licensing

The source code is Open Source and is released under the very permissive "simplified (2-clause) BSD license" . See LICENSE for further details.

See also

SymPy _

pyneqsys _

pyodesys _

thermo _

Contributing

Contributors are welcome to suggest improvements at https://github.com/bjodah/chempy (see further details here _).

Author

Björn I. Dahlgren, contact: - gmail address: bjodah

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