Skip to main content

MASSIVEChem is a pip-installable package for analytical chemistry. It simulates molecule mass spectra and graphically displays them. It includes tools like a functional group finder and unsaturation calculator to aid chemical analysis.

Project description

- MASSIVEChem -

  • Python package for applied analytical chemistry focused primarily on mass speectrometry

Project in practical programming in chemistry course -- EPFL CH-200

Package description

MASSIVEChem, which stands for "Mass Analytical Spectrometry System for Investigation and Visual Extrapolation in Chemistry", is a pip-installable package developped at EPFL in 2024 focused on, as its name would suggest, analytical chemistry. The aim of this package is to provide the user functions in order to simulate the mass spectrum of a molecule and to display this spectrum on a graph. The package also provides other features that can facilitate the chemical analysis of a molecule such as a functional group finder and an unsaturation calculator.

Developpers:

What is mass spectrometry ?

  • Mass spectrometry is an analytical technique used to identify and quantify chemical compounds in a sample by measuring the mass and sometimes the charge of molecules. It involves separating pre-charged ions according to their mass-to-charge ratio (m/z), then detecting and analysing them. This method is widely used in chemistry, biochemistry, pharmacology and other fields to characterise substances and understand their composition.

Now, let us go through the steps required to use this package !

Installation

MASSIVEChem can be installed using pip as

pip install MASSIVEChem

The package can also be installed from source by running the following commands

First, clone the repository from github and go in the folder.

git clone https://github.com/ThomasCsson/MASSIVEChem.git
cd MASSIVEChem

Then, install the package using :

pip install -e . 

Requirments

The package runs on python 3.10 but supports python 3.8 through 3.10 The package requires several other packages to function correctly.

matplotlib
bokeh
rdkit
pandas

If everything runs in order during the installation, the preceding packages should install automatically. But check that these packages are correctly installed using

pip show "name of the package"

If not, install them using the following commands, otherwise the package will not work.

pip install matplotlib
pip install bokeh
pip install rdkit
pip install pandas

Usage

'''Show the most important function and use'''

Getting started

To begin to use the package the following jupyter notebook will give you information about all the package's functions:

'''link to jupter notebook'''

Project details


Download files

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

Source Distribution

massivechem-3.3.tar.gz (456.7 kB view details)

Uploaded Source

Built Distribution

massivechem-3.3-py3-none-any.whl (219.9 kB view details)

Uploaded Python 3

File details

Details for the file massivechem-3.3.tar.gz.

File metadata

  • Download URL: massivechem-3.3.tar.gz
  • Upload date:
  • Size: 456.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.10

File hashes

Hashes for massivechem-3.3.tar.gz
Algorithm Hash digest
SHA256 533ba2df77589c02b97e84ec375155f469548d0cb70ed6fd064230b55d64f08b
MD5 d61b81dc7d2052846d3e137de22bce89
BLAKE2b-256 855ad1a6a9d24d1766b2e291b168d72acabf3536c8864660df9719ebf502bfbc

See more details on using hashes here.

File details

Details for the file massivechem-3.3-py3-none-any.whl.

File metadata

  • Download URL: massivechem-3.3-py3-none-any.whl
  • Upload date:
  • Size: 219.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.10

File hashes

Hashes for massivechem-3.3-py3-none-any.whl
Algorithm Hash digest
SHA256 b14c0bddb8c22061445cffcb4ac4a66545d0eebeba6fe3ea111823f955fe61db
MD5 f8ebae6f1625aded3b239234c96166b3
BLAKE2b-256 802491a2dc361b59aa7ccdd8c259c3a9f3dee33aa775e3ee9c9499e550a67db1

See more details on using hashes here.

Supported by

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