Merge pull request #58 from zoccoler/ncp_0_8_0_compatible

Make plugin compatible with ncp 0_8_0

.github/workflows/test_and_deploy.yml

@@ -23,7 +23,7 @@ jobs:
     strategy:
       matrix:
         platform: [ubuntu-latest, windows-latest, macos-latest]
-        python-version: ['3.8', '3.9', '3.10']
+        python-version: ['3.9', '3.10']
 
     steps:
       - uses: actions/checkout@v3

MANIFEST.in

@@ -4,4 +4,3 @@ include README.md
 recursive-exclude * __pycache__
 recursive-exclude * *.py[co]
 include src/napari_flim_phasor_plotter/data/*
-include src/napari_flim_phasor_plotter/data/hazelnut_FLIM_z_stack/*

setup.cfg

@@ -18,7 +18,6 @@ classifiers =
     Programming Language :: Python
     Programming Language :: Python :: 3
     Programming Language :: Python :: 3 :: Only
-    Programming Language :: Python :: 3.8
     Programming Language :: Python :: 3.9
     Programming Language :: Python :: 3.10
     Topic :: Scientific/Engineering :: Image Processing
@@ -34,7 +33,8 @@ install_requires =
     numpy
     magicgui
     qtpy
-    napari-clusters-plotter
+    napari-clusters-plotter>=0.8.0
+    ptufile
     sdtfile
     natsort
     rocket-fft
@@ -43,7 +43,7 @@ install_requires =
     napari-segment-blobs-and-things-with-membranes
     napari-skimage-regionprops
 
-python_requires = >=3.8
+python_requires = >=3.9
 include_package_data = True
 package_dir =
     =src

src/napari_flim_phasor_plotter/__init__.py

@@ -2,14 +2,14 @@
 
 from ._reader import napari_get_reader
 from ._sample_data import load_seminal_receptacle_image, load_hazelnut_image, load_hazelnut_z_stack, load_lifetime_cat_synthtetic_single_image
-from ._io.readPTU_FLIM import PTUreader
+from ._io import convert_to_zarr
 from . import phasor, filters, _plotting, _widget
 
 
 __all__ = (
     "napari_get_reader",
     "_sample_data",
-    "PTUreader",
+    "convert_to_zarr",
     "phasor",
     "filters",
     "_plotting",

src/napari_flim_phasor_plotter/_io/convert_to_zarr.py

@@ -33,6 +33,7 @@ def convert_folder_to_zarr(folder_path: pathlib.Path, cancel_button: bool = Fals
         Path to the folder containing the FLIM images.
     """
     import zarr
+    from numcodecs import Blosc
     import dask.array as da
     import numpy as np
     from pathlib import Path
@@ -76,9 +77,11 @@ def convert_folder_to_zarr(folder_path: pathlib.Path, cancel_button: bool = Fals
     # zarr file will be saved in the same folder as the input folder
     output_path = folder_path / (folder_path.stem + '.zarr')
     # Using zarr to automatically guess chunk sizes
+    # Use Blosc compressor for better compression and speed
+    compressor = Blosc(cname='zstd', clevel=3, shuffle=Blosc.BITSHUFFLE)
     # Create an empty zarr array of a specified shape and dtype filled with zeros
     zarr_array = zarr.open(output_path, mode='w',
-                           shape=stack_shape, dtype=image_dtype)
+                           shape=stack_shape, dtype=image_dtype, compressor=compressor)
     # Using dask to rechunk micro-time axis in single chunk (for fft calculation afterwards)
     dask_array = da.from_zarr(output_path)
     # Rechunk axis 1 (micro-time axis) to a single chunk