GitPlanet

Cheap and reliable Node.js hosting starts at $3/month, and $1/month static HTML hosting

Created with love in Canada, visit hostnodejs.com today

Feel like to post an Ad? Learn Details
All Projects → weisscharlesj → SciCompforChemists

weisscharlesj / SciCompforChemists

Licence: other
Scientific Computing for Chemists text for teaching basic computing skills to chemistry students using Python, Jupyter notebooks, and the SciPy stack. This text makes use of a variety of packages including NumPy, SciPy, matplotlib, pandas, seaborn, NMRglue, SymPy, scikit-image, and scikit-learn.

Programming Languages

Jupyter Notebook
11667 projects

Labels

sciencechemistrybooknumpychemicalbiochemistryscientific-computingscipyjupyterlabscientificsimulationstextbookjupyter-notebookscomputingjupyter-labnmrgluechemists

Projects that are alternatives of or similar to SciCompforChemists

Stdlib
✨ Standard library for JavaScript and Node.js. ✨
Stars: ✭ 2,749 (+4129.23%)
Mutual labels:  science, scientific-computing, scientific
Python-Matematica
Explorando aspectos fundamentais da matemática com Python e Jupyter
Stars: ✭ 41 (-36.92%)
Mutual labels:  numpy, scientific-computing, scipy
adorad
Fast, Expressive, & High-Performance Programming Language for those who dare
Stars: ✭ 54 (-16.92%)
Mutual labels:  science, scientific-computing, computing
Scipy-Bordeaux-2017
Course taught at the University of Bordeaux in the academic year 2017 for PhD students.
Stars: ✭ 16 (-75.38%)
Mutual labels:  science, numpy, scipy
PyRates
Open-source, graph-based Python code generator and analysis toolbox for dynamical systems (pre-implemented and custom models). Most pre-implemented models belong to the family of neural population models.
Stars: ✭ 33 (-49.23%)
Mutual labels:  numpy, scientific-computing, simulations
OOMMFTools
OOMMFTools is a set of utilities designed to assist OOMMF postprocessing
Stars: ✭ 15 (-76.92%)
Mutual labels:  science, scientific-computing
OpenSkyStacker
Multi-platform stacker for deep-sky astrophotography.
Stars: ✭ 80 (+23.08%)
Mutual labels:  science, scientific-computing
object-detection-with-deep-learning
demonstrating use of convolution neural networks to detect objects in a video
Stars: ✭ 17 (-73.85%)
Mutual labels:  numpy, scipy
PVMismatch
An explicit Python PV system IV & PV curve trace calculator which can also calculate mismatch.
Stars: ✭ 51 (-21.54%)
Mutual labels:  numpy, scipy
steep
⤴️ Steep Workflow Management System – Run scientific workflows in the Cloud
Stars: ✭ 30 (-53.85%)
Mutual labels:  scientific-computing, scientific
Geoweaver
a web system to allow users to automatically record history and manage complicated scientific workflows in web browsers involving the online spatial data facilities, high-performance computation platforms, and open-source libraries.
Stars: ✭ 32 (-50.77%)
Mutual labels:  scientific-computing, jupyter-lab
introduction to ml with python
도서 "[개정판] 파이썬 라이브러리를 활용한 머신 러닝"의 주피터 노트북과 코드입니다.
Stars: ✭ 211 (+224.62%)
Mutual labels:  numpy, scipy
pem-dataset1
Proton Exchange Membrane (PEM) Fuel Cell Dataset
Stars: ✭ 48 (-26.15%)
Mutual labels:  science, chemistry
PyCORN
A script to extract data from ÄKTA/UNICORN result-files (.res)
Stars: ✭ 30 (-53.85%)
Mutual labels:  science, scientific-computing
skinner
Skin export / import tools for Autodesk Maya
Stars: ✭ 68 (+4.62%)
Mutual labels:  numpy, scipy
notebook-free-notebook
A professional, lock-in-free Jupyter dev env for coders, teams and non-trivial, large Jupyter projects
Stars: ✭ 38 (-41.54%)
Mutual labels:  jupyterlab, jupyter-notebooks
CATmistry
Chemistry, Gamified
Stars: ✭ 15 (-76.92%)
Mutual labels:  science, chemistry
ELLIPTIc
ELLIPTIc: The Extensible LIbrary for Physical simulaTIons
Stars: ✭ 14 (-78.46%)
Mutual labels:  scientific-computing, scientific
audiophile
Audio fingerprinting and recognition
Stars: ✭ 17 (-73.85%)
Mutual labels:  numpy, scipy
mdct
A fast MDCT implementation using SciPy and FFTs
Stars: ✭ 42 (-35.38%)
Mutual labels:  scientific-computing, scipy
View All Similar Projects ➔

Scientific Computing for Chemists with Python

The following is the textbook used for the Scientific Computing Chemists course intended to teach chemists and chemistry students basic computer programming in Python and Jupyter Notebooks and advanced tools for processing, visualization, and analysis of digital data. A chapter outline is provided below. The book starts with a streamlined introduction to Python for chemists followed by introducing powerful computing tools and numerous applications to chemistry. This book assumes that the student or reader has no prior programming experience and has at least one year of undergraduate chemistry background and some very basic spectroscopy/spectrometry (i.e., NMR, IR, UV-vis, and GC/MS) background. All software used (e.g., Python, NumPy, SciPy, etc...) is free and open source software and runs on macOS, Windows, and Linux.

This book is periodically updated to fix typos, account for new software versions, and add new content. The most recent version can be viewed using the link below or downloaded or forked above along with Jupyter notebooks containing all code in the book. Reports of errors and information on how people are using this book are always welcome.

Answer keys to exercises are available to instructors upon request. Please email me using your institutional email address to request a copy.

View Scientific Computing for Chemists with Python (Jupyter Book)

The book and all files/materials included with it are copyright © 2021-2022 Charles J. Weiss and are released under under the CC BY-NC-SA 4.0 license.

  • Chapter 0: Python & Jupyter Notebooks
  • Chapter 1: Basic Python
  • Chapter 2: Intermediate Python
  • Chapter 3: Plotting with Matplotlib
  • Chapter 4: NumPy
  • Chapter 5: Pandas
  • Chapter 6: Signal & Noise
  • Chapter 7: Image Processing & Analysis
  • Chapter 8: Mathematics
  • Chapter 9: Simulations
  • Chapter 10: Plotting with Seaborn
  • Chapter 11: Nuclear Magnetic Resonance with NMRglue
  • Chapter 12: Machine Learning using Scikit-Learn
  • Chapter 13: Command Line & Spyder

Articles on Course and Textbook

Scientific Computing for Chemists: An Undergraduate Course in Simulations, Data Processing, and Visualization J. Chem. Educ. 2017, 94, 592-597 DOI: 10.1021/acs.jchemed.7b00078

Introduction to Stochastic Simulations for Chemical and Physical Processes: Principles and Applications J. Chem. Educ. 2017, 94, 1904-1910 DOI: 10.1021/acs.jchemed.7b00395

A Creative Commons Textbook for Teaching Scientific Computing to Chemistry Students with Python and Jupyter Notebooks J. Chem. Educ. 2021, 98, 489-494 DOI: 10.1021/acs.jchemed.0c01071

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].