[CI] Implemented md_link_check CI (#91)

* Implemented workflow to check markdown links

* Added `md_link_check_config.json`

* Updated broken and dead links

* Increased `timeout` to 60s

* Updated dead link

* Updated the `run_mriqc.py` link

* Updated trigger events for `md_link_check` workflow

* Updated `md_link_check.yml` to use `main` branch

.github/workflows/md_link_check.yaml

@@ -0,0 +1,18 @@
+name: Check markdown links
+
+on:
+  push:
+    branches: [main]
+  pull_request:
+  workflow_dispatch:
+
+jobs:
+  markdown-link-check:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@main
+    - uses: gaurav-nelson/github-action-markdown-link-check@v1
+      with:
+        use-quiet-mode: 'yes'
+        use-verbose-mode: 'yes'
+        config-file: 'md_link_check_config.json'

docs/nipoppy/configs.md

@@ -9,7 +9,7 @@ Nipoppy requires two global files for specifying local data/container paths and
 ### Global configs: `global_configs.json`
    - This is a dataset-specific file and needs to be modified based on local configs and paths
    - This file is used as an input to all workflow runscripts to read, process and track available data
-   - Copy, rename, and populate [sample_global_configs.json](https://github.com/neurodatascience/nipoppy/blob/main/sample_global_configs.json) 
+   - Copy, rename, and populate [sample_global_configs.json](https://github.com/neurodatascience/nipoppy/blob/main/nipoppy/sample_global_configs.json) 
    - This file contains:
       - Name of the Nipoppy dataset (`DATASET_NAME`, e.g., `PPMI`)
       - Path to the Nipoppy dataset (`DATASET_ROOT`)

docs/nipoppy/workflow/bids_conv.md

@@ -17,7 +17,7 @@ Convert DICOMs to BIDS using [Heudiconv](https://heudiconv.readthedocs.io/en/lat
 ### Procedure
 
 1. Ensure you have the appropriate HeuDiConv container listed in your `global_configs.json`
-2. Use [run_bids_conv.py](https://github.com/neurodatascience/nipoppy/blob/main/workflow/bids_conv/run_bids_conv.py) to run HeuDiConv `stage_1` and `stage_2`.  
+2. Use [run_bids_conv.py](https://github.com/neurodatascience/nipoppy/blob/main/nipoppy/workflow/bids_conv/run_bids_conv.py) to run HeuDiConv `stage_1` and `stage_2`.  
    - Run `stage_1` to generate a list of available protocols from the DICOM header. These protocols are listed in `<DATASET_ROOT>/bids/.heudiconv/<participant_id>/info/dicominfo_ses-<session_id>.tsv`
 
 > Sample cmd:
@@ -32,7 +32,7 @@ python run_bids_conv.py \
 
     If participants have multiple sessions (or visits), these need to be converted separately and combined post-hoc to avoid Heudiconv errors. 
 
-3. Copy+Rename [sample_heuristic.py](https://github.com/neurodatascience/nipoppy/blob/main/workflow/bids_conv/sample_heuristic.py) to `heuristic.py` in the code repo itself. Then edit `./heuristic.py` to create a name-mapping (i.e. dictionary) for BIDS organization based on the list of available protocols. 
+3. Copy+Rename [sample_heuristic.py](https://github.com/neurodatascience/nipoppy/blob/main/nipoppy/workflow/bids_conv/sample_heuristic.py) to `heuristic.py` in the code repo itself. Then edit `./heuristic.py` to create a name-mapping (i.e. dictionary) for BIDS organization based on the list of available protocols. 
 
 !!! note
 

docs/nipoppy/workflow/dicom_org.md

@@ -15,7 +15,7 @@ This is a dataset specific process and needs to be customized based on local sca
 
 ### Procedure
 
-1. Run [`workflow/dicom_org/check_dicom_status.py`](https://github.com/neurodatascience/nipoppy/blob/main/workflow/dicom_org/check_dicom_status.py) to update `doughnut.csv` based on the manifest. It will add new rows for any subject-session pair not already in the file.
+1. Run [`workflow/dicom_org/check_dicom_status.py`](https://github.com/neurodatascience/nipoppy/blob/main/nipoppy/workflow/dicom_org/check_dicom_status.py) to update `doughnut.csv` based on the manifest. It will add new rows for any subject-session pair not already in the file.
     - To create the `doughnut.csv` for the first time, use the `--empty` argument. If processing has been done without updating `doughnut.csv`, use `--regenerate` to update it based on new files in the dataset.
 
 !!! note
@@ -45,7 +45,7 @@ This is a dataset specific process and needs to be customized based on local sca
     It is **okay** for the participant directory to have messy internal subdir tree with DICOMs from multiple modalities. (See [data org schematic](data_org.md) for details). The run script will search and validate all available DICOM files automatically. 
 
 
-4. Run [`run_dicom_org.py`](https://github.com/neurodatascience/nipoppy/blob/main/workflow/dicom_org/run_dicom_org.py) to:
+4. Run [`run_dicom_org.py`](https://github.com/neurodatascience/nipoppy/blob/main/nipoppy/workflow/dicom_org/run_dicom_org.py) to:
     - Search: Find all the DICOMs inside the participant directory. 
     - Validate: Excludes certain individual dicom files that are invalid or contain scanner-derived data not compatible with BIDS conversion.
     - Symlink (default) or copy: Creates symlinks from `raw_dicoms/` to the `<DATASET_ROOT>/dicom`, where all participant specific dicoms are in a flat list. The symlinks are relative so that they are preserved in containers.

docs/nipoppy/workflow/proc_pipe/fmriprep.md

@@ -16,9 +16,9 @@ Run [fMRIPrep](https://fmriprep.org/en/stable/) pipeline on BIDS formatted datas
 ### Procedure
 
 - Ensure you have the appropriate fMRIPrep container listed in your `global_configs.json` 
-- Use [run_fmriprep.py](https://github.com/neurodatascience/nipoppy/blob/main/workflow/proc_pipe/fmriprep/run_fmriprep.py) script to run fmriprep pipeline. 
+- Use [run_fmriprep.py](https://github.com/neurodatascience/nipoppy/blob/main/nipoppy/workflow/proc_pipe/fmriprep/run_fmriprep.py) script to run fmriprep pipeline. 
 - You can run "anatomical only" workflow by adding `--anat_only` flag
-- (Optional) Copy+Rename [sample_bids_filter.json](https://github.com/neurodatascience/nipoppy/blob/main/workflow/proc_pipe/fmriprep/sample_bids_filter.json) to `bids_filter.json` in the code repo itself. Then edit `bids_filter.json` to filter certain modalities / acquisitions. This is common when you have multiple T1w acquisitions (e.g. Neuromelanin, SPIR etc.) for a given modality. 
+- (Optional) Copy+Rename [sample_bids_filter.json](https://github.com/neurodatascience/nipoppy/blob/main/nipoppy/workflow/proc_pipe/fmriprep/sample_bids_filter.json) to `bids_filter.json` in the code repo itself. Then edit `bids_filter.json` to filter certain modalities / acquisitions. This is common when you have multiple T1w acquisitions (e.g. Neuromelanin, SPIR etc.) for a given modality. 
 
 !!! note
 

docs/nipoppy/workflow/proc_pipe/mriqc.md

@@ -8,7 +8,7 @@ MRIQC processes the participants and produces image quality metrics from T1w, T2
 
 
 ### [MRIQC](https://mriqc.readthedocs.io/en/latest/)
-- Use [run_mriqc.py](https://github.com/neurodatascience/nipoppy/tree/main/workflow/proc_pipe/mriqc) to run MRIQC pipeline directly or wrap the script in an SGE/Slurm script to run on cluster
+- Use [run_mriqc.py](https://github.com/neurodatascience/nipoppy/blob/main/nipoppy/workflow/proc_pipe/mriqc/run_mriqc.py) to run MRIQC pipeline directly or wrap the script in an SGE/Slurm script to run on cluster
 
 ```bash
 python run_mriqc.py --global_config CONFIG.JSON --subject_id 001 --output_dir OUTPUT_DIR_PATH
@@ -20,7 +20,7 @@ python run_mriqc.py --global_config CONFIG.JSON --subject_id 001 --output_dir OU
 - Mandatory: Pass in the absolute path to the output directory to `output_dir`
 
 !!! note
-	An example config is located [here](https://github.com/neurodatascience/nipoppy/blob/main/sample_global_configs.json)
+	An example config is located [here](https://github.com/neurodatascience/nipoppy/blob/main/nipoppy/sample_global_configs.json)
 
 > Sample cmd:
 ```bash
@@ -35,7 +35,7 @@ python run_mriqc.py \
 	A run for a participant is considered successful when the participant's log file reads `Participant level finished successfully`
 
 ### Evaluate MRIQC Results
-- Use [mriqc_tracker.py](https://github.com/neurodatascience/nipoppy/blob/main/trackers/mriqc_tracker.py) to determine how many subjects successfully passed through the MRIQC pipeline
+- Use [mriqc_tracker.py](https://github.com/neurodatascience/nipoppy/blob/main/nipoppy/trackers/mriqc_tracker.py) to determine how many subjects successfully passed through the MRIQC pipeline
 	- Mandatory: Pass in the subject directory as an argument
 - After a successful run of the script, a dictionary called tracker_configs is returned contained whether the subject passed through the pipeline successfully
 

md_link_check_config.json

@@ -0,0 +1,11 @@
+{
+    "ignorePatterns": [
+        {"pattern": "http://neurobagel.org/vocab/*"},
+        {"pattern": "http://neurobagel.org/graph/"},
+        {"pattern": "https://www.cognitiveatlas.org/task/id/"},
+        {"pattern": "^../"},
+        {"pattern": "localhost*"},
+        {"pattern": "https://api.neurobagel.org/*"}
+    ],
+    "timeout": "60s"
+}