Published June 6, 2026 | Version v0.11
Software Open

phasorpy/phasorpy: v0.11

  • 1. Institut Pasteur de Montevideo
  • 2. University of California, Irvine

Description

PhasorPy is an open-source Python library for the analysis of luminescence lifetime and hyperspectral images using the phasor approach.

This is the second beta release of the PhasorPy library. It contains several new functions, improvements, and bug fixes.

The new io.signal_from_ometiff function reads hyperspectral and RGB images from OME-TIFF files using the tifffile library.

The filter.phasor_filter_gaussian function was fixed to apply intensity weighting by default.

The new nadh_fraction application tutorial demonstrates how to estimate the bound NADH fraction using phasor component analysis.

Several documentation inconsistencies have been fixed.

This release supports Python 3.12 through 3.14.

What's Changed

  • Bump version by @cgohlke in https://github.com/phasorpy/phasorpy/pull/339
  • Add nadh_fraction tutorial and improve documentation by @cgohlke in https://github.com/phasorpy/phasorpy/pull/341
  • Add signal_from_ometiff function by @cgohlke in https://github.com/phasorpy/phasorpy/pull/342
  • Update phasor approach software list by @cgohlke in https://github.com/phasorpy/phasorpy/pull/343
  • Update GitHub workflows by @cgohlke in https://github.com/phasorpy/phasorpy/pull/344
  • Fix documentation inconsistencies by @cgohlke in https://github.com/phasorpy/phasorpy/pull/345
  • Fix phasor_filter_gaussian to apply intensity weighting by default by @cgohlke in https://github.com/phasorpy/phasorpy/pull/346
  • Revise phasor software table by @cgohlke in https://github.com/phasorpy/phasorpy/pull/347
  • Fix Mypy errors with numpy 2.5.0rc1 by @cgohlke in https://github.com/phasorpy/phasorpy/pull/348
  • Release v0.11 by @cgohlke in https://github.com/phasorpy/phasorpy/pull/349

Full Changelog: https://github.com/phasorpy/phasorpy/compare/v0.10...v0.11

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Additional details

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Software: https://github.com/phasorpy/phasorpy/tree/v0.11 (URL)

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