Skip to main content

PyECsim: fast and general voltammetry simulation

Project description

PyECsim is a fast and general simulator of voltammetry experiments. Using the latest state-of-the-art algorithms, it simulates

  • any number of electrode processes, using Butler-Volmer charge transfer kinetics, coupled to

  • any number of homogeneous reactions (first or second order), using

  • user-defined voltammetry waveforms.

A typical simulation, even with very large reaction rate constants (10e9 /s), takes around 10 ms to run. Because the simulations are fast, you can use them inside the target function of an optimization routine.

In-depth documentation can be found on read the docs.

# Install

Installing PyECsim is easy:

pip install --user pyecsim

# Quick-start

Import PyECsim into your Python code (and matplotlib to plot the voltammogram):

import pyecsim as ecs
import matplotlib.pyplot as plt

Then create a simulator and species, a charge transfer step and a chemical reaction:

sim = ecs.Simulation(True)

red = ecs.Species('reduced species', 1.0, 1.0e-9)
ox = ecs.Species('oxidized species', 0.0, 1.0e-9)
prod = ecs.Species('reaction product', 0.0, 1.0e-9)

sim.sys.addRedox( rdx1 := ecs.Redox(ox, red, 1, 0.0, 10.0, 0.5).enable() ) # Python >= 3.8
sim.sys.addReaction( rxn1 := ecs.Reaction(ox, None, prod, None, 5.0, 0.0).enable() ) # Python >= 3.8

Lastly, we set the electrode type and radius, the voltammograms initial/vertex/final potentials and the scan rate:

sim.el.disk(1.0e-3)
sim.exper.setScanPotentials(-0.5, [0.5], -0.5)
sim.exper.setScanRate(1.0)

And then we can run the simulation and plot the results:

[potential, current] = sim.run()
plt.plot(potential, current)

Which gives:

http://limhes.net/upload/images_ecsim/cv_readme.png

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

pyecsim-0.2.3-cp39-cp39-win_amd64.whl (172.1 kB view details)

Uploaded CPython 3.9Windows x86-64

pyecsim-0.2.3-cp39-cp39-manylinux2014_x86_64.whl (4.5 MB view details)

Uploaded CPython 3.9

pyecsim-0.2.3-cp38-cp38-win_amd64.whl (171.4 kB view details)

Uploaded CPython 3.8Windows x86-64

pyecsim-0.2.3-cp38-cp38-manylinux2014_x86_64.whl (4.6 MB view details)

Uploaded CPython 3.8

pyecsim-0.2.3-cp37-cp37m-win_amd64.whl (170.0 kB view details)

Uploaded CPython 3.7mWindows x86-64

pyecsim-0.2.3-cp37-cp37m-manylinux2014_x86_64.whl (4.6 MB view details)

Uploaded CPython 3.7m

pyecsim-0.2.3-cp36-cp36m-win_amd64.whl (228.2 kB view details)

Uploaded CPython 3.6mWindows x86-64

pyecsim-0.2.3-cp36-cp36m-manylinux2014_x86_64.whl (4.6 MB view details)

Uploaded CPython 3.6m

pyecsim-0.2.3-cp35-cp35m-win_amd64.whl (180.4 kB view details)

Uploaded CPython 3.5mWindows x86-64

pyecsim-0.2.3-cp35-cp35m-manylinux2014_x86_64.whl (4.6 MB view details)

Uploaded CPython 3.5m

File details

Details for the file pyecsim-0.2.3-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: pyecsim-0.2.3-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 172.1 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.8.3

File hashes

Hashes for pyecsim-0.2.3-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 fa68ce4c119342558b541a35229fe6b9cfb70e5c1b7cf3b10f00bcc525b2581c
MD5 f1070b3adc5d513a44db52d4676fb3c0
BLAKE2b-256 63ac0478c7b63b5fbde933223b80ee7b220f8966e2fdc443c20d7bf1b82feb5b

See more details on using hashes here.

File details

Details for the file pyecsim-0.2.3-cp39-cp39-manylinux2014_x86_64.whl.

File metadata

  • Download URL: pyecsim-0.2.3-cp39-cp39-manylinux2014_x86_64.whl
  • Upload date:
  • Size: 4.5 MB
  • Tags: CPython 3.9
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.8.3

File hashes

Hashes for pyecsim-0.2.3-cp39-cp39-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2f01af4e7363a765db0967ef4676b5cd07f3f05e9b700126295efb726cac668c
MD5 1a1d8d02520b5267cb343e87dfbcf5e9
BLAKE2b-256 906da92ee2092a8d5e92aefe922ef17f23a6e14a93dec097b274ce1164087beb

See more details on using hashes here.

File details

Details for the file pyecsim-0.2.3-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: pyecsim-0.2.3-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 171.4 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.8.3

File hashes

Hashes for pyecsim-0.2.3-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 e1fa25acb0c01999844a2b78cf7b0a780b6fcfc79f2fd62e06d03042dc477954
MD5 57fd22b3a9651e849c7a85109d3e4458
BLAKE2b-256 daafc00d1a56f106fe3158f1e68946a2a6e6e42951218f6e8c6f7e0fa9bbf69b

See more details on using hashes here.

File details

Details for the file pyecsim-0.2.3-cp38-cp38-manylinux2014_x86_64.whl.

File metadata

  • Download URL: pyecsim-0.2.3-cp38-cp38-manylinux2014_x86_64.whl
  • Upload date:
  • Size: 4.6 MB
  • Tags: CPython 3.8
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.8.3

File hashes

Hashes for pyecsim-0.2.3-cp38-cp38-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ad2670accae7d9c92e959d922c7e5a98a8d348e38defd3547f8188afb90d34e2
MD5 c33beae5589f6dfac270bd3963c215fe
BLAKE2b-256 971111171258d130e7a78c4a4c85a7496c8a7329f58b1387ead190c50d769e21

See more details on using hashes here.

File details

Details for the file pyecsim-0.2.3-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: pyecsim-0.2.3-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 170.0 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.8.3

File hashes

Hashes for pyecsim-0.2.3-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 43d8ebf55642958852a6e2c7c3bcb8b2580f728f789b0da420ebf41c8c3c4398
MD5 a1649187e852d62507f4caf86c461e46
BLAKE2b-256 7d04c1467d1a6019e511507389ac513353cc561b53ee9b1f8977d638fa2298ca

See more details on using hashes here.

File details

Details for the file pyecsim-0.2.3-cp37-cp37m-manylinux2014_x86_64.whl.

File metadata

  • Download URL: pyecsim-0.2.3-cp37-cp37m-manylinux2014_x86_64.whl
  • Upload date:
  • Size: 4.6 MB
  • Tags: CPython 3.7m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.8.3

File hashes

Hashes for pyecsim-0.2.3-cp37-cp37m-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 fe8f0a21914bae0035ec872597ce06ed90200ea9a0224568b5382c2816635162
MD5 d94f509408c9f16bcf96b0a808500beb
BLAKE2b-256 824bbf1fb0e10ab5b7977504d059222f847b6377cbcafb5cc742f3a6945b5703

See more details on using hashes here.

File details

Details for the file pyecsim-0.2.3-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: pyecsim-0.2.3-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 228.2 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.8.3

File hashes

Hashes for pyecsim-0.2.3-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 baeadaff8aed5a0d9bec61d013d128f43a5c17a0e4eea83b56a0e770fdeaf556
MD5 caaf3339f6d8166aad0e16a6e800eadf
BLAKE2b-256 75d038b54d662fa4afd2aba5d70f2d4edfe7ad5000665d79635bc9129b90a518

See more details on using hashes here.

File details

Details for the file pyecsim-0.2.3-cp36-cp36m-manylinux2014_x86_64.whl.

File metadata

  • Download URL: pyecsim-0.2.3-cp36-cp36m-manylinux2014_x86_64.whl
  • Upload date:
  • Size: 4.6 MB
  • Tags: CPython 3.6m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.8.3

File hashes

Hashes for pyecsim-0.2.3-cp36-cp36m-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 a6e94a495c5f04a288ece6017386658422b6332de50c072052a673f1049955f9
MD5 5b3f9160ac1232529630cd46451cf166
BLAKE2b-256 a5ed428423dbce739077434b58f78433ebb9d777fca73c3b3683a01c39246807

See more details on using hashes here.

File details

Details for the file pyecsim-0.2.3-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: pyecsim-0.2.3-cp35-cp35m-win_amd64.whl
  • Upload date:
  • Size: 180.4 kB
  • Tags: CPython 3.5m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.8.3

File hashes

Hashes for pyecsim-0.2.3-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 d43708e81798ef318e6d053228b432f4210badcd66328e889f7e50fc2c0d25a8
MD5 0845c9898656a560d41e68066b5abf59
BLAKE2b-256 6ed9599118d1ffb7b03ac255eba10d2f46bf3913c5c1f0052f4ae336010ee850

See more details on using hashes here.

File details

Details for the file pyecsim-0.2.3-cp35-cp35m-manylinux2014_x86_64.whl.

File metadata

  • Download URL: pyecsim-0.2.3-cp35-cp35m-manylinux2014_x86_64.whl
  • Upload date:
  • Size: 4.6 MB
  • Tags: CPython 3.5m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.8.3

File hashes

Hashes for pyecsim-0.2.3-cp35-cp35m-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6916b7d00276fa26983f51bd8b1d16a850850f816fbc84a8b33f28bf465ba541
MD5 8ea33639a0f7fbf79a47af627e0e435c
BLAKE2b-256 99c1cbad771bd4c2b87ee05e24489aef813ab21d1b10e5b65ff388845c29c20e

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page