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Merge pull request #29 from PhysiCell-Tools/master
pcdl release v3.3.4
2 parents ae2a745 + ccad4ee commit 5db9bf4

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.github/workflows/apple.yml

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@@ -8,17 +8,17 @@ run-name: ${{ github.actor }}::pytest pcdl library on mac os x; the latest pytho
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on:
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push:
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branches: ["master", "v3", "v4"]
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pull_request:
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branches: ["master", "v3", "v4"]
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#pull_request:
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# branches: ["master", "v3", "v4"]
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jobs:
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build-macosx:
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runs-on: macos-latest
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strategy:
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fail-fast: false
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matrix:
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#python-version: ["3.12"]
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python-version: ["3.9", "3.10", "3.11", "3.12"]
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python-version: ["3.13"]
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#python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"]
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env:
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PYTHONPATH: /Users/runner/work/physicelldataloader/physicelldataloader
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run: |
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brew install ffmpeg imagemagick
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python -m pip install --upgrade pip
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python -m pip install flake8 pytest aicsimageio anndata matplotlib numpy pandas requests scipy vtk
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python -m pip install flake8 pytest anndata bioio matplotlib numpy pandas requests scipy vtk
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python -m pip install /Users/runner/work/physicelldataloader/physicelldataloader -v
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#if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
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- name: lint with flake8
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- name: test with pytest
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run: |
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pytest
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.github/workflows/linux.yml

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push:
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branches: ["master", "v3", "v4"]
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pull_request:
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branches: ["master", "v3", "v4"]
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#pull_request:
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# branches: ["master", "v3", "v4"]
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jobs:
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build-linux:
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runs-on: ubuntu-latest
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strategy:
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fail-fast: false
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matrix:
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#python-version: ["3.12"]
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python-version: ["3.9", "3.10", "3.11", "3.12"]
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python-version: ["3.13"]
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#python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"]
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env:
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PYTHONPATH: /home/runner/work/physicelldataloader/physicelldataloader
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run: |
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sudo apt install ffmpeg imagemagick
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python -m pip install --upgrade pip
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python -m pip install flake8 pytest aicsimageio anndata matplotlib numpy pandas requests scipy vtk
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python -m pip install flake8 pytest anndata bioio matplotlib numpy pandas requests scipy vtk
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python -m pip install /home/runner/work/physicelldataloader/physicelldataloader -v
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#if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
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- name: lint with flake8

.github/workflows/windows.yml

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push:
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branches: ["master", "v3", "v4"]
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pull_request:
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branches: ["master", "v3", "v4"]
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#pull_request:
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# branches: ["master", "v3", "v4"]
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jobs:
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build-windows:
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runs-on: windows-latest
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strategy:
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fail-fast: false
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matrix:
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#python-version: ["3.12"]
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python-version: ["3.9", "3.10", "3.11", "3.12"]
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python-version: ["3.13"]
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#python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"]
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env:
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PYTHONPATH: D:\a\physicelldataloader\physicelldataloader
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run: |
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choco install ffmpeg imagemagick
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python -m pip install --upgrade pip
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python -m pip install flake8 pytest aicsimageio anndata matplotlib numpy pandas requests scipy vtk
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python -m pip install flake8 pytest anndata bioio matplotlib numpy pandas requests scipy vtk
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python -m pip install D:\a\physicelldataloader\physicelldataloader -v
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#echo 'set PYTHONPATH=D:\a\physicelldataloader\physicelldataloader' >> $GITHUB_ENV
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#if [ -f requirements.txt ]; then pip install -r requirements.txt; fi

README.md

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![physicellcdataloader logo & title](man/img/physicelldataloader_title_v3.0.0.png)
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## Abstract:
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physicelldataloader (pcdl) provides a platform independent, python3 based, [pip](https://en.wikipedia.org/wiki/Pip_(package_manager)) installable interface
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## Header:
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+ Language: python [>= 3.9](https://devguide.python.org/versions/)
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+ Library dependencies: aicsimageio, anndata, matplotlib, numpy, pandas, (requests), scipy, vtk
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+ Library dependencies: anndata, bioio, matplotlib, numpy, pandas, (requests), scipy, vtk
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+ Date of origin original PhysiCell-Tools python-loader: 2019-09-02
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+ Date of origin pcdl fork: 2022-08-30
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+ Doi: https://doi.org/10.5281/ZENODO.8176399
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+ evt generate lineage tree graph output files.
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+ evt add neuroglancer ome.tiff support.
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+ switch from aicsimageio to bioio library, when the library is ripe (napari has switched to bioio).
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+ evt add DataDiVR support.
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## Release Notes:
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+ version 3.3.4 (2025-03-07): elmbeech/physicelldataloader
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+ replace the **aicsimageio** library dependency with its successor **bioio**. special thanks to Joel Eliason!
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+ **make_ome_tiff** can handle automatically generated file names with > 255 characters. special thank to Genevieve Stein-O'Brien and DanielBergman!
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+ **get_mesh_spacing** handels now an edge case correctly that would have resulted in a division by zero. special thanks to Randy Heiland!
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+ version 3.3.3 (2025-01-10): elmbeech/physicelldataloader
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+ bug fix **plot_contour** plot orientation. special thanks to Marco Ruscone!
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+ add test data for new improved **unittest physicell model**. special thanks to Nick Oldfather!

man/TUTORIAL_blender.md

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## ✨ Handle ome tiff files
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The blender bioxel nodes plugin allows us load ome tiff files into blender.
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The blender bioxel nodes plugin allows us load single time step ome tiff files into blender.
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### Generate vtk files from the command line
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### Generate ome tiff files from the command line
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```bash
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pcdl_make_conc_vtk output
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```
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```bash
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pcdl_make_cell_vtk output
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pcdl_make_ome_tiff output --collapse false
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```
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### Generate vtk files from within python
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### Generate ome tiff files from within python
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```python
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mcdsts = pcdl.TimeSeries('output/')
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mcdsts.make_conc_vtk()
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mcdsts.make_cell_vtk()
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mcdsts.make_ome_tiff(collapse=False)
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```
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### The blender bioxel nodes plugin

man/TUTORIAL_python3_napari.md

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## Install napari
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And install the [aicsimageio](https://github.com/AllenCellModeling/aicsimageio) library,
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which installs the "ome-types" napari plugin,
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that napari can read ome.tiff images inclusive ome metadata.
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```bash
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pip3 install napari[all]
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pip3 install aicsimageio
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```
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man/TUTORIAL_python3_ometiff.md

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Additionally ome.tiff, tiff, png, and jpeg files can as well be loaded back in to python as [numpy](https://numpy.org/) array, for example with the [sci-kit image](https://scikit-image.org/) library (image data only).
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Besides that, ome.tiff files can be loaded with Allen Institute for Cell Science's [aicsimageio](https://github.com/AllenCellModeling/aicsimageio) library and possibly with its successor library [bioio](https://github.com/bioio-devs/bioio) (image and metadata).
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Besides that, ome.tiff files can be loaded with the [bioio](https://github.com/bioio-devs/bioio) library (image and metadata).
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### Save pcdl data constructs from the command line into tiff and ome.tiff files
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### Load ome.tiff files as AICSImage object into python
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### Load ome.tiff files as BioImage object into python
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from aicsimageio import AICSImage
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from bioio import BioImage
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img = AICSImage('output/timeseries_ID.ome.tiff')
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img = BioImage('output/timeseries_ID.ome.tiff')
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img.shape # (25, 2, 1, 200, 300)
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```
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```python

pcdl/VERSION.py

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__version__ = '3.3.3'
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__version__ = '3.3.4'

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