How SciPy and Python helped catch ripples in space and paint a black hole
SciPy began as a small toolkit and grew into a library used by millions, it's part of the backbone for people who do science with code.
Built for Python, it gives simple tools for math, images, sound and data, so researchers and hobby coders both win.
You might not notice it but SciPy powers almost half of machine learning projects on GitHub, and yes it was used in big moments like the LIGO discoveries and the first picture of a black hole image.
The package includes many helpers for solving problems, from sorting data to cleaning images to fitting curves.
Developers from around the world contribute, so the code keeps getting better, sometimes messy but very useful.
If you like tinkering or you're curious about how science meets code, SciPy makes complex tasks feel smaller.
Try a simple example and you'll see how a few lines can turn data into discovery, and maybe spark your own project, or even help explain the universe a little bit more.
Read article comprehensive review in Paperium.net:
SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python
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