Github repository in Python.
#ML
#python
@scientific_programming

The Information Dynamics Toolkit xl (IDTxl) is a comprehensive software package for efficient inference of networks and their node dynamics from multivariate time series data using information theory. IDTxl provides functionality to estimate the following measures:

For network inference:
🌱multivariate transfer entropy (TE)/Granger causality (GC)
🌱 multivariate mutual information (MI)
🌱 bivariate TE/GC
🌱 bivariate MI

For analysis of node dynamics:
🌱 active information storage (AIS)
🌱partial information decomposition (PID)

https://github.com/pwollstadt/IDTxl

#information_theory
#network_inference
#transfer_entropy
#python

🔆 STAN
☘️ Stan is a state-of-the-art platform for statistical modeling and high-performance statistical computation.
☘️ Stan interfaces with the most popular data analysis languages (R, #python, shell, MATLAB, Julia, Stata) and runs on all major platforms (Linux, Mac, Windows).

🌱 Stan User’s Guide
🌱 PyStan Guide
To install simply use:
$ pip3 install pystan

#Kuramoto model various implementation using #Python and #jitcode:
GitHub

Quantitative #Economics with
#Python

Link

Here is where I start to learn #Machine_Learning:

The course is available here:
Machine Learning, Andrew Ng
The whole course can be downloaded from here at once.

GitHub for Exercises in #Python.
You can check the solution in "solution" branch in case.

NetPyNE
#NetPyNE (Networks using #Python and #NEURON) is a Python package to facilitate the development, simulation, parallelization, analysis, and optimization of biological neuronal networks using the NEURON simulator.

Although NEURON already enables multiscale simulations ranging from the molecular to the network level, using NEURON for network simulations requires substantial programming, and often requires parallel simulations. NetPyNE greatly facilitates the development and parallel simulation of biological neuronal networks in NEURON for students and experimentalists. NetPyNE is also intended for experienced modelers, providing powerful features to incorporate complex anatomical and physiological data into models.
#simulator

Programming for Computations – Python
Hans Petter Langtangen
A Gentle Introduction to Numerical
Simulations with Python

Open access book
#book
#python
#basic

We have this awesome function called sublots_mosaic where you can pass us a layout id'ed on name
axd = plt.subplot_mosaic(
"""
ABD
CCD
""")

Link

#matplotlib
#python

Always use close!
I spent hours on a large code to find out I had not closed the pool in #multiprocessing in #Python
It gives you "too many files open", misleading nasty error 😤.

A Student's Guide to Python for Physical Modeling: Second Edition
#python
#book
#beginner

#python Decorators, quick simple start.
Video

The map() function in #Python takes a function and a series of arguments, and makes an iterable of results. It can also work on functions with multiple arguments.
(But most Python people prefer list comprehensions.)

Credit: nedbat

Have you tried out the sh package for #Python yet? This package makes calling Linux and Mac terminal commands really easy! 🐍🔥

pypi.org/project/sh/

Credit: driscollis

A Collection of 25 Awesome Python Scripts (mini projects)
#Python

Mastering #Python
Credit: Mousa