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astronn

Deep Learning for Astronomers with Tensorflow

benford_py

Python implementation of Benford's Law tests.

cashew

The code of the CASHeW framework for analyzing coronal waves

deepem

Demonstrating a Deep Learning Approach for DEM Inversion

demreg

Calculate the Differential Emission Measure (DEM) from solar data using regularised inversion.

eispac

firtez-dz

flca

Fourier local correlation alignment (FLCA) is an efficient method for aligning images based on the [FLCT](http://solarmuri.ssl.berkeley.edu/overview/publicdownloads/software.html). The latter is a method for performing local correlation tracking. FLCA can calculate the local corretion of two images pixel by pixel, and the final shift-X and shift-Y are gained as the median values of those from the middle region (60%). The code has the advantages of being precise, fast, user friendly, and open.

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

image-noise-gate

licplot

Line integral convolution for visualizing vector fields

myspicule

noise2self

A framework for blind denoising with self-supervision.

pydave4vm

This is a working version in python of the dave4vm software that was originally written in IDL

sharmarahul20.github.io

sktime-tutorial-pydata-amsterdam-2020

Introduction to Machine Learning with Time Series at PyData Festival Amsterdam 2020

solar-coronal-inversion

This is the main repository for the CLEDB code distribution. CLEDB is utilized to infer vector coronal magnetic fields in the solar corona.

stic

The Stockholm inversion code

sunkit-sst

YEAH..........THE NAME IS WIERD.................ALSO THERE ARE NO GHOSTS

sunpy

SunPy - Python for solar physics

test2023.github.io

testsitetemplate

Ananke: A theme for Hugo Sites

ucomp-workshop-2023

compPy tutorial for the uCoMP workshop 2023

wisa

WOW demonstration

zdipy

A code for Doppler Imaging and Zeeman Doppler Imaging, for reconstructing stellar surface features from time series observations.