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Everything about NumPy
Python library for numerical programming
NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. The predecessor of NumPy, Numeric, was originally created by Jim Hugunin with contributions from several other developers. In 2005, Travis Oliphant created NumPy by incorporating features of the competing Numarray into Numeric, with extensive modifications. NumPy is open-source software and has many contributors. NumPy is fiscally sponsored by NumFOCUS. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: NumPyA 5-minute orientation
- Skim a recent paper: Fast annual daylighting simulation and high dynamic range image processing using NumPyInfluential work since 2022
- Pick up a classic book: Mastering Numerical Computing with NumPyThe most-reprinted book on the subject
- Read the landmark paper: Array programming with NumPyCited 26,085 times
- Go sideways: CuPyA closely related topic
- Go sideways: SciPyA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🏆 Landmark papers (most cited)
Array programming with NumPy
The NumPy Array: A Structure for Efficient Numerical Computation
PROCESSING OCEANOGRAPHIC DATA BY PYTHON LIBRARIES NUMPY, SCIPY AND PANDAS
Windrose: A Python Matplotlib, Numpy library to manage wind and pollution data, draw windrose
PyCPD: Pure NumPy Implementation of the Coherent Point Drift Algorithm
A full-fledged micromagnetic code in fewer than 70 lines of NumPy
Crowdsourcing Scientific Software Documentation: A Case Study of the NumPy Documentation Project
Imagedata: A Python library to handle medical image data in NumPy array subclass Series
🆕 Influential since 2022
Fast annual daylighting simulation and high dynamic range image processing using NumPy
Reservoir computing bootcamp—From Python/NumPy tutorial for the complete beginners to cutting-edge research topics of reservoir computing
IKPLS: Improved Kernel Partial Least Squares and Fast Cross-Validation Algorithms for Python with CPU and GPU Implementations Using NumPy and JAX
2D Simplified Wildfire Spreading Model in Python: From NumPy to CuPy
\Phi_\textrm{ML}: Intuitive Scientific Computing with Dimension Types for Jax, PyTorch, TensorFlow & NumPy
📚 Books worth reading
Mastering Numerical Computing with NumPyUmit Mert Cakmak, Mert Cuhadaroglu · 2018
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
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