release v4.1.9 and more generic workflow.

.github/workflows/apple.yml

@@ -7,7 +7,7 @@ run-name: ${{ github.actor }}::pytest pcdl library on mac os x; the latest pytho
 
 on:
   push:
-    branches: ["utest", "master"]  # ["v3", "v4"]
+    branches: ["master"]
   pull_request:
     branches: ["development", "master"]
 
@@ -22,7 +22,7 @@ jobs:
 
     env:
       MPLBACKEND: Agg  # https://github.com/orgs/community/discussions/26434
-      PYTHONPATH: /Users/runner/work/physicelldataloader/physicelldataloader
+      PYTHONPATH: ${{ github.workspace }}
 
     steps:
     - uses: actions/checkout@main
@@ -34,8 +34,8 @@ jobs:
       run: |
         brew install ffmpeg imagemagick
         python -m pip install --upgrade pip
-        python -m pip install flake8 pytest anndata bioio bioio-ome-tiff geopandas matplotlib networkx neuroglancer numpy pandas requests scikit-image scipy shapely spatialdata vtk
-        python -m pip install /Users/runner/work/physicelldataloader/physicelldataloader -v
+        python -m pip install flake8 pytest anndata bioio bioio-ome-tiff geopandas matplotlib networkx neuroglancer numpy pandas requests scikit-image scipy shapely simulariumio spatialdata vtk
+        python -m pip install . -v
         #if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
     - name: lint with flake8
       run: |

.github/workflows/linux.yml

@@ -7,7 +7,7 @@ run-name: ${{ github.actor }}::pytest pcdl library on linux os; all python3 vers
 
 on:
   push:
-    branches: ["utest", "master"]  # ["v3","v4"]
+    branches: ["master"]
   pull_request:
     branches: ["development", "master"]
 
@@ -22,7 +22,7 @@ jobs:
 
     env:
       MPLBACKEND: Agg  # https://github.com/orgs/community/discussions/26434
-      PYTHONPATH: /home/runner/work/physicelldataloader/physicelldataloader
+      PYTHONPATH: ${{ github.workspace }}
 
     steps:
     - uses: actions/checkout@main
@@ -35,8 +35,8 @@ jobs:
         sudo apt update
         sudo apt install ffmpeg imagemagick
         python -m pip install --upgrade pip
-        python -m pip install flake8 pytest anndata bioio bioio-ome-tiff geopandas matplotlib networkx neuroglancer numpy pandas requests scikit-image scipy shapely spatialdata vtk
-        python -m pip install /home/runner/work/physicelldataloader/physicelldataloader -v
+        python -m pip install flake8 pytest anndata bioio bioio-ome-tiff geopandas matplotlib networkx neuroglancer numpy pandas requests scikit-image scipy shapely simulariumio spatialdata vtk
+        python -m pip install . -v
         #if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
     - name: lint with flake8
       run: |

.github/workflows/windows.yml

@@ -7,7 +7,7 @@ run-name: ${{ github.actor }}::pytest pcdl library on windows os; the latest pyt
 
 on:
   push:
-    branches: ["utest", "master"]  # ["v3", "v4"]
+    branches: ["master"]
   pull_request:
     branches: ["development", "master"]
 
@@ -22,7 +22,7 @@ jobs:
 
     env:
       MPLBACKEND: Agg  # https://github.com/orgs/community/discussions/26434
-      PYTHONPATH: D:\a\physicelldataloader\physicelldataloader
+      PYTHONPATH: ${{ github.workspace }}
 
     steps:
     - uses: actions/checkout@main
@@ -34,8 +34,8 @@ jobs:
       run: |
         choco install ffmpeg imagemagick
         python -m pip install --upgrade pip
-        python -m pip install flake8 pytest anndata bioio bioio-ome-tiff geopandas matplotlib networkx neuroglancer numpy pandas requests scikit-image scipy shapely spatialdata vtk
-        python -m pip install D:\a\physicelldataloader\physicelldataloader -v
+        python -m pip install flake8 pytest anndata bioio bioio-ome-tiff geopandas matplotlib networkx neuroglancer numpy pandas requests scikit-image scipy shapely simulariumio spatialdata vtk
+        python -m pip install . -v
         #echo 'set PYTHONPATH=D:\a\physicelldataloader\physicelldataloader' >> $GITHUB_ENV
         #if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
     - name: lint with flake8

jakku/biocondarecipes_recipes/pcdl/meta.yaml

@@ -88,4 +88,4 @@ extra:
   recipe-maintainers:
     - elmbeech
   autobump:
-    enable: False  # see https://github.com/bioconda/bioconda-recipes/pull/57971
+    enable: True  # see https://github.com/bioconda/bioconda-recipes/pull/57971

jakku/toolsiuc_tools/pcdl/pcdl_get_anndata.xml

@@ -115,8 +115,8 @@
 Function to transform mcds time steps into one or many anndata objects for downstream analysis.
 
 Scale parameter details: Possible values are None, maxabs, minmax, std.
-None: no scaling. Set scale to None if you would like to have raw data or entirely scale, transform, and normalize the data later. 
-Maxabs: maximum absolute value distance scaler will linearly map all values into a [-1, 1] interval. If the original data has no negative values, the result will be the same as with the minmax scaler (except with attributes with only one value). If the attribute has only zeros, the value will be set to 0. 
+None: no scaling. Set scale to None if you would like to have raw data or entirely scale, transform, and normalize the data later.
+Maxabs: maximum absolute value distance scaler will linearly map all values into a [-1, 1] interval. If the original data has no negative values, the result will be the same as with the minmax scaler (except with attributes with only one value). If the attribute has only zeros, the value will be set to 0.
 Minmax: minimum maximum distance scaler will map all values linearly into a [0, 1] interval. If the attribute has only one value, the value will be set to 0.
 Std: standard deviation scaler will result in sigmas. Each attribute will be mean centered around 0. Ddof delta degree of freedom is set to 1 because it is assumed that the values are samples out of the population and not the entire population. It is incomprehensible to me that the equivalent sklearn method has ddof set to 0. If the attribute has only one value, the value will be set to 0.
 

jakku/toolsiuc_tools/pcdl/pcdl_macros.xml

@@ -229,18 +229,19 @@
         <param argument="--ext" label="file extension" type="select" display="radio" help="Output image format. Possible formats are jpeg, png, and tiff.">
             <option value="jpeg" selected="true">jpeg</option>
             <!--
-        <option value="png">png</option>
-        <option value="tiff">tiff</option>
-        -->
+            <option value="png">png</option>
+            <option value="tiff">tiff</option>
+            <option value="csv">csv</option>
+            -->
         </param>
     </xml>
     <xml name="ext_vtkcell">
-        <param argument="--ext" label="file extension" name="extvtp" type="text" value="_cell.vtp" optional="false" help="File extension for the vtk polydata file.">
+        <param name="extvtp" argument="--ext" label="file extension" type="text" value="_cell.vtp" optional="false" help="File extension for the vtk polydata file.">
             <validator type="regex" message="Characters allowed are alphanumeric, underscore, dash, and dot. The extension has to end with .vtp">^[a-zA-Z0-9_\-.]*\.vtp$</validator>
         </param>
     </xml>
     <xml name="ext_vtkconc">
-        <param argument="--ext" label="file extension" name="extvtr" type="text" value="_conc.vtr" optional="false" help="File extension for the vtk rectilinear grid file.">
+        <param  name="extvtr" argument="--ext" label="file extension" type="text" value="_conc.vtr" optional="false" help="File extension for the vtk rectilinear grid file.">
             <validator type="regex" message="Characters allowed are alphanumeric, underscore, dash, and dot. The extension has to end with .vtr">^[a-zA-Z0-9_\-.]*\.vtr$</validator>
         </param>
     </xml>

man/HOWTO.md

@@ -152,8 +152,10 @@ Now you're rolling!
 
 pyMCDS.py and the pyMCDS class is very lightweight.
 Besides the python3 core library, this code has only matplotlib, numpy, pandas, scipy, and vtk library dependencies.\
-The pyMCDS class evolved into the pcdl.TimeStep class, which has additionally anndata dependency, which makes the library slightly heavier but much more powerful for downstream data analysis.
+The pyMCDS class evolved into the pcdl.TimeStep class, which has additionally dependency (like anndata, muspan, and spatialdata), which makes the library slightly heavier but much more powerful for downstream data analysis.
 Apart from that, pcdl offers the pcdl.TimeSeries class to handle the mcds snapshots from an entire PhysiCell run, and a set of functions that can be run straight from the command line, without even having to fire up a python3 shell.
 Finally, branch version 4 broke with this ancient library structure because it is just out of time to run the code like this.\
+<!--
 Stay assured, if you like pyMCDS.py, it is there to last.
 We will keep on maintaining pyMCDS.py from branch version 3.
+-->