Welcome to Shift Nth Row N Steps documentation!

Installation & Usage

• Installation
• Usage

Project Info

• Changelog
  • v1.0.0 (2025-06-30)
  • v0.3.0 (2025-06-29)
  • v0.2.11 (2025-05-26)
  • v0.2.10 (2025-05-14)
  • v0.2.9 (2025-04-29)
  • v0.2.8 (2025-02-28)
  • v0.2.7 (2024-12-04)
  • v0.2.6 (2024-12-03)
  • v0.2.5 (2024-11-29)
  • v0.2.4 (2024-11-19)
  • v0.2.3 (2024-11-08)
  • v0.2.2 (2024-11-02)
  • v0.2.1 (2024-11-02)
  • v0.2.0 (2024-10-26)
  • v0.1.3 (2024-10-25)
  • v0.1.2 (2024-10-25)
  • v0.1.1 (2024-10-24)
  • v0.1.0 (2024-10-24)
  • v0.0.0 (2024-10-23)
• Contributing
  • Types of Contributions
  • Get Started!
  • Pull Request Guidelines
  • Tips
  • Making a new release

API Reference

• shift_nth_row_n_steps package
  • create_slice()
  • narrow()
  • select()
  • shift_nth_row_n_steps()
  • take_slice()
  • Submodules
  • shift_nth_row_n_steps.cli module

Shift Nth Row N Steps

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Documentation: https://shift-nth-row-n-steps.readthedocs.io

Source Code: https://github.com/34j/shift-nth-row-n-steps

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Shift Nth row N steps in NumPy / PyTorch / TensorFlow / JAX

Installation

Install this via pip (or your favourite package manager):

pip install shift-nth-row-n-steps

Usage

from shift_nth_row_n_steps import shift_nth_row_n_steps

a = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
shifted = shift_nth_row_n_steps(a)
print(shifted)

[[1 2 3]
 [0 4 5]
 [0 0 7]]

shift_nth_row_n_steps is array API compatible, which means it works with NumPy, PyTorch, JAX, and other libraries that implement the array API standard.

Benchmark

Algorithm

Contributors ✨

Thanks goes to these wonderful people (emoji key):

This project follows the all-contributors specification. Contributions of any kind welcome!

Credits

This package was created with Copier and the browniebroke/pypackage-template project template.