Merge cp4-windows to master branch

.gitignore

@@ -0,0 +1,10 @@
+venv/
+.idea/
+__pycache__/
+RunOnCluster.egg-info/
+CellProfiler-plugins/
+*/__pycache__/
+__init__.py
+setup.py
+loadimagesfromomero.py
+*.pyc

README.md

@@ -1,43 +1,44 @@
-# CellProfiler-RunOnCluster 
+# CellProfiler-RunOnCluster
+
 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3275888.svg)](https://doi.org/10.5281/zenodo.3275888)
 
 A CellProfiler module for submitting batch jobs to a cluster running slurm.
 
 ## Installation
-### Windows
-
-A precompiled executable with default settings for the Sunbird cluster in Swansea is provided in [releases](https://github.com/sa2c/CellProfiler-RunOnCluster/releases/download/v1.0/CellProfiler.exe). These executables require that a Java Runtime Environment is installed. You can get one for example form the [Java downloads page](https://www.java.com/en/download/). 
 
-### Source Installation
+Note as our plugin requires additional libraries which aren’t packaged with CellProfiler 4, you’ll need to build CellProfiler from source rather than using a pre-packaged version. ([Reference](https://cellprofiler-manual.s3.amazonaws.com/CellProfiler-4.0.6/help/other_plugins.html?highlight=plugins)). The most straightforward method is to copy the plugin sources to your Cellprofiler plugins directory. Using the default `CellProfiler\plugins` folder as your plugin directory is recommended, but you can still have the plugins in other locations. Follow the instructions for installing CellProfiler on the [Wiki](https://github.com/CellProfiler/CellProfiler/wiki). Choose your operating system on the right-side panel. Once you have installed CellProfiler, set the plugin's directory in Cellprofiler preferences, then save and restart CellProfiler.
 
-When running on Linux or developing your own plugins, the most straight forward method is to copy the plugin sources to your Cellprofiler plugins directory.
+Please download the [plugins](https://codeload.github.com/sa2c/CellProfiler-RunOnCluster/zip/refs/heads/master) to your plugins directory. In the plugins directory, install the requirements for the plugins:
 
-Follow the instructions for installing CellProfiler on the [wiki](https://github.com/CellProfiler/CellProfiler/wiki). Choose you operating system on the right side panel. Once you have installed CellProfiler, set the plugins directory in Cellprofiler preferences. Download [the plugins](https://github.com/sa2c/CellProfiler-RunOnCluster/archive/master.zip) and copy move the files to your plugins directory.
-
-In the plugins directory, install the additional requirements for the plugins:
 ```
-python2 -m pip install -r requirements.txt
+python -m pip install -r requirements.txt
 ```
 
 ## Usage
 
-### Submitting to Cluster
+### Submitting jobs to the cluster
 
 Once you have tested your pipeline on your local machine, add all images to be processed into the Images plugin in the usual way. Add the `RunOnCluster` module in the `Other` category to the end of the pipeline.
 
 The module has four settings:
- * Run Name: An identifier that allows you to recognize the pipeline and image batch.
- * Number of images per measurement: If several image files are required for a single measurement, adjust this to the number of images required.
- * Image type first: Select `Yes` if the image type appears before the measurement number in the image file name. Select `No` if the measurement number appears before the image type.
- * Maximum Runtime (hours): The amount of time to reserve a node for on the cluster. The actual runtime can be lower, but not larger than this. If the run takes longer than the time given, it will be terminated before completion. Must be less than 72.
-
- Submit the pipeline by pressing `Analyze Images`. The plugin will copy the image files and the pipeline to the cluster and add the process to the queue.
 
- ### Checking run status
+- Run Name: An identifier that allows you to recognise the pipeline and image batch.
+- Number of images per measurement: If several image files are required for a single measurement, adjust this to the number of images required.
+- Image type first: Select `Yes` if the image type appears before the measurement number in the image file name. Select `No` if the measurement number appears before the image type.
+- Maximum Runtime (hours): The amount of time to reserve a node on the cluster. The actual runtime can be lower, but not larger than this. If the run takes longer than the time given, it will be terminated before completion. Must be less than 72.
+- Project Code: Specify your Supercomputing Wales project code, for example, scw0123.
+- Partition: Select the partition you wish to run your job on. (Defaults to `compute` partition)
+- Local script directory: Choose where local copies of remote scripts and batch data are saved.
 
- Open the ClusterView module in the Data Tools menu. You will see a list of all runs submitted to the cluster. Under the run name the module will display `PENDING` for runs in queue or currently running and `COMPLETED` for runs that have stopped running. Click `Update` in the upper left corner to refresh the status of the runs. Use the `Download Results` button to download and inspect the results.
- If you have already downloaded the results, the button label will change to `Download Again`.
+Submit the pipeline by pressing `Analyze Images`. The plugin will copy the image files and the pipeline to the cluster and add the process to the queue.
 
+### Checking job status
 
+Please add the `ClusterView` plugin from the `Data Tools` category in the Module list into the pipeline, then you will be able to select a list of all runs submitted to the cluster. Under the run name, the module will display `PENDING` for runs in the queue or currently running and `COMPLETED` for runs that have stopped running. Click the `Update` button to refresh the status of the runs. Use the `Download Results` button to download and inspect the results. If you have already downloaded the results, the button label will change to `Download Again`.
 
+## TODO
 
+- [ ] Light refactoring of ClusterView functions to separate directory management from Rynner functions for easier testing.
+- [ ] Include testing for directory and file management functions in ClusterView.
+- [ ] (Optional) Consider folding the ClusterView window into RunOnCluster as a single module.
+- [ ] MacOS version