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Release v2024.10.10
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cgohlke committed Oct 11, 2024
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21 changes: 14 additions & 7 deletions README.rst
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Expand Up @@ -11,7 +11,7 @@ measurement data and instrumentation parameters.

:Author: `Christoph Gohlke <https://www.cgohlke.com>`_
:License: BSD 3-Clause
:Version: 2024.9.14
:Version: 2024.10.10
:DOI: `10.5281/zenodo.10120021 <https://doi.org/10.5281/zenodo.10120021>`_

Quickstart
Expand All @@ -33,17 +33,22 @@ Requirements
This revision was tested with the following requirements and dependencies
(other versions may work):

- `CPython <https://www.python.org>`_ 3.10.11, 3.11.9, 3.12.5, 3.13.0rc2 64-bit
- `NumPy <https://pypi.org/project/numpy>`_ 2.1.1
- `CPython <https://www.python.org>`_ 3.10.11, 3.11.9, 3.12.7, 3.13.0 64-bit
- `NumPy <https://pypi.org/project/numpy>`_ 2.1.2
- `Xarray <https://pypi.org/project/xarray>`_ 2024.9.0 (recommended)
- `Matplotlib <https://pypi.org/project/matplotlib/>`_ 3.9.2 (optional)
- `Tifffile <https://pypi.org/project/tifffile/>`_ 2024.8.30 (optional)
- `Numcodecs <https://pypi.org/project/numcodecs/>`_ 0.13.0 (optional)
- `Tifffile <https://pypi.org/project/tifffile/>`_ 2024.9.20 (optional)
- `Numcodecs <https://pypi.org/project/numcodecs/>`_ 0.13.1 (optional)
- `Cython <https://pypi.org/project/cython/>`_ 3.0.11 (build)

Revisions
---------

2024.10.10

- Also trim leading channels without photons (breaking).
- Add property to identify channels with photons.

2024.9.14

- Improve typing.
Expand Down Expand Up @@ -117,7 +122,7 @@ The PicoQuant unified file formats are documented at the

The following features are currently not implemented: PT2 and PT3 files,
decoding images from T2 formats, bidirectional scanning, and deprecated
image reconstruction.
image reconstruction. Line-scanning is not tested.

Other Python or C/C++ modules for reading PicoQuant files are:

Expand Down Expand Up @@ -198,6 +203,8 @@ Get information about the FLIM image histogram in the PTU file:
{'T': ..., 'Y': ..., 'X': ..., 'H': ...}
>>> ptu.dtype
dtype('uint16')
>>> ptu.active_channels
(0, 1)
Decode parts of the image histogram to ``numpy.ndarray`` using slice notation.
Slice step sizes define binning, -1 being used to integrate along axis:
Expand All @@ -223,8 +230,8 @@ to a ``xarray.DataArray``, keeping reduced axes:
* T (T) float64... 0.05625
* Y (Y) float64... -0.0001304 ... 0.0001294
* X (X) float64... -0.0001304 ... 0.0001294
* C (C) uint8... 0
* H (H) float64... 0.0
Dimensions without coordinates: C
Attributes...
frequency: 19999200.0
...
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