How to Python in computational neuroscience, data mining, and more

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All the tutorials are tested with Python 3.11.x. Older version might have a problem with the new versions of type anotations.

Flow chart

• Basic Structure of a Computer
• Representation of Numbers in the Computer
• Systematic Programming
• Flow chart symbols
• Examples
• Flow chart for baking bread

Workflow

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Python: The Basics of the basics

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Python: Special topics

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Numpy: The Basics of the basics

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Numpy: Special topics

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Numpy: Matlab topics

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Matplotlib.pyplot

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Pandas

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Sci-kit Learn

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SciPy

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Python: Questions of spectral nature

• PyWavelets: Wavelet Transforms in Python
• Instantanious Spectral Coherence
• Linearize the spectral coherence

Python: Daily little helper

• TQDM: Make your progress visible
• Argh: Organize your command line arguments
• psutil vs os.cpu_count: How many "CPUs" do I have?
• ZeroMQ: Microservices as well as connecting computers via message queue
• Austin: Time and memory profiling

OpenCV2 and Python

• OpenCV2: Play, write, read a video
• How to read a webcam with CV2

PyTorch

• Get CUDA ready!
• Converting the original MNIST files into numpy
• Interfacing Data
• Data augmentation
• Layers
• Creating networks
• Train the network
• Fisher Exact Test: Test if your performance difference is significant
• Write your own layer
  • Replace the automatic autograd with your own torch.autograd.Function
• How to take advantage of an optimizer for your non-Pytorch project
• How to take advantage of a learning rate scheduler for your non-Pytorch project
• Unfold: How to manually calculate the indices for a sliding 2d window

PyBind11

• Expanding Python with C++ modules
• The fast and furious way (CPU and GPU CUDA)
• PyBind11 Stub-Generation

Tensorflow / Keras

• A fast non-introduction

Sympy

• Symbolic Computation

Numerical Integration, Differentiation, and Differential Equations

• Integration and Differentiation
• Differential Equations

Arduino

• Basics with Python / Matlab

Matlab: Basics

{: .topic-optional} This pages are in a rough state. e.g. equations are broken. Don't know why...

• Basic Commands and Variables
• Graphics
• Vectorization and Vector Calculus in Matlab
• Data Analysis

Other topics

• Open Source Tools
• Machine Learning Resources
• Datasets

S1: Advanced Programming (last update 16.02.2024)

• S1 Advanced programming and data analysis
• Preperations
• Task 1 -- Classycal neurons: Simulation and Mathematical Anaylsis
• Task 2 -- Collective coherent cortices: Data analysis
• Neuron Models Equations
  • For detailed descriptions, please see: 'Neuronal Dynamics' textbook 'Theoretical Neuroscience' textbook
• Neuron Models Equations -- Rate-based neurons
  • DivInE-model for MT neurons
• Neuron Models Equations -- Spiking neurons without explicit spike generation mechanism
  • Leaky Integrate-and-Fire
  • Exponential Integrate-and-Fire
  • Quadratic Integrate-and-Fire
  • Connor Stevens
• References
• Task 1 -- Pictures for comparision
  • Mandatory Tasks
• Task 2 -- Pictures for comparision
  • Mandatory Tasks
  • Voluntary Tasks: Preprocessing
  • Voluntary Tasks: More Information!

Advanced Studies

• Material from ages past
  • 2022: Preparation -- Python class with and without classes
  • 2022: Deep Networks and Pytorch
  • 2022: Divisive inhibition: a dynamical circuit for change detection
  • 2022: Synchronization and dynamic oscillations in the visual system
  • 2020: Deep Networks and Tensor Flow
  • 2020: Divisive Normalization -- a Universal Concept for Adaptive Dynamics and Function of Cortical Circuits
  • 2020: Recurrent networks: Temporal dynamics and synchronization
  • 2017: Oscillations and information routing: CTC model
  • 2017: Change detection: The DivInE-Model
  • 2017: Contour Integration
  • 2017: Computation Spike by Spike
  • 2017: Natural scenes and sparse coding in visual cortex

Non Python tutorials:

• Computer admin tutorials