fixed some alignementS and added tutorial to mkdocs

Author: ReboreExplore

README.md

@@ -3,8 +3,12 @@
   LSLAutoBIDS
 </h1>
 <p align="center"> Tools to convert LSL + friends automatically to BIDS, and upload it to a Dataverse </p>
-
-
+<p align="center">
+  <a href="https://s-ccs.github.io/LSLAutoBIDS/" target="_blank">
+    <img src="https://img.shields.io/badge/View%20Full%20Documentation-%230072C6?style=for-the-badge&logo=readthedocs&logoColor=white" alt="View Full Documentation">
+  </a>
+</p>
+ss
 ## 🚀 Getting Started
 
 Get started with LSLAutoBIDS by installing the package and its dependencies.

docs/README.md

@@ -1,4 +1,4 @@
-### 4. BIDS Conversion and Upload Pipeline ⚙️ (`convert_to_bids_and_upload.py`)
+## BIDS Conversion and Upload Pipeline ⚙️ (`convert_to_bids_and_upload.py`)
 
 The pipeline is designed to ensure:
 
@@ -12,7 +12,7 @@ The pipeline is designed to ensure:
 
 5. The dataset is registered in Dataverse and optionally pushed/uploaded automatically.
 
-#### 1. Entry Point (`bids_process_and_upload()`)
+#### Entry Point (`bids_process_and_upload()`)
 
 - Reads project configuration (<project_name>_config.toml) to check if a other computer (non eeg files) was used. (otherFilesUsed: true)
 
@@ -42,7 +42,7 @@ The pipeline is designed to ensure:
 
     - Pushes data to Dataverse automatically (--yes) or via user confirmation.
 
-#### 2. Convert to BIDS (`convert_to_bids()`)
+#### Convert to BIDS (`convert_to_bids()`)
 This function handles the core conversion of a XDF files to BIDS format and constructs the dataset structure. It performs the following steps:
 
 1. Copy raw/behavioral/experiment files via `copy_source_files_to_bids()` (See section).
@@ -77,7 +77,7 @@ This function handles the core conversion of a XDF files to BIDS format and cons
 
     - 0: BIDS Conversion done but validation failure
 
-#### 3. Copy Source Files (`copy_source_files_to_bids()`)
+#### Copy Source Files (`copy_source_files_to_bids()`)
 This function ensures that the original source files (EEG and other/behavioral files) are also a part our dataset. These files can't be directly converted to BIDS format but we give the user the option to include them in the BIDS directory structure in a pseudo-BIDS format for completeness.
 
 - Copies the .xdf into the following structure: 
@@ -104,7 +104,7 @@ If otherFilesUsed=True in project config file:
 
 There is a flag in the `lslautobids run` command called `--redo_other_pc` which when specified, forces overwriting of existing other and experiment files in the BIDS dataset. This is useful if there are updates or corrections to the other/behavioral data that need to be reflected in the BIDS dataset.
 
-#### 4. Create Raw XDF (`create_raw_xdf()`)
+#### Create Raw XDF (`create_raw_xdf()`)
 This function reads the XDF file and creates an MNE Raw object. It performs the following steps:
 - Select EEG stream using match_streaminfos(type="EEG").
 
@@ -118,20 +118,20 @@ This function reads the XDF file and creates an MNE Raw object. It performs the
 
 This produces a clean, memory-efficient Raw object ready for BIDS conversion.
 
-#### 5. BIDS Validation (`validate_bids()`)
+#### BIDS Validation (`validate_bids()`)
 This function validates the generated BIDS files using the `bids-validator` package. It performs the following steps:
 - Walks through the BIDS directory.
 - Skips irrelevant files: (`.xdf`, `.tar.gz`, behavioral files, hidden/system files.)
 - Uses `BIDSValidator` to validate relative paths. 
 - If any file fails validation, logs an error and returns 0 ; Otherwise, logs success and returns 1.
 
-#### 6. Populate dataset_description.json (`populate_dataset_description_json()`)
+#### Populate dataset_description.json (`populate_dataset_description_json()`)
 This function generates the `dataset_description.json` file required by the BIDS standard. It performs the following steps:
 - Gathers metadata from the project configuration file (title, authors, license, etc.) from the project TOML config file.
 - Calls make_dataset_description() from mne_bids.
 - Overwrites existing file with updated values.
 
-#### 7. Datalad and Dataverse Integration
+#### Datalad and Dataverse Integration
 This part of the pipeline manages version control and data sharing using DataLad and Dataverse. After conversion, the following steps occur:
 
 - `generate_json_file()` → Generates supplementary metadata JSONs.

docs/bids_convert_and_upload.md

@@ -1,4 +1,4 @@
-### 1. CLI Module (`cli.py`)
+## CLI Module (`cli.py`)
 
 The `lslautobids` command-line interface provides the main entry point for the application:
 

docs/cli.md

@@ -1,8 +1,8 @@
-### 2. Configuration System
+## Configuration System
 
 The configuration system manages dataversse and project-specific settings using YAML and TOML files.
 
-#### 1. Dataverse and Project Root Configuration (`gen_dv_config.py`)
+#### Dataverse and Project Root Configuration (`gen_dv_config.py`)
 
 This module generates a global configuration file for Dataverse and project root directories. This is a one-time setup per system.  This file is stored in `~/.config/lslautobids/autobids_config.yaml` and contains:
 - Paths for BIDS, projects, and project_other directories : This allows users to specify where their eeg data, behavioral data, and converted BIDS data are stored on their system. This paths should be relative to the home/users directory of your system and string format.
@@ -19,7 +19,7 @@ _Currently, the package doesn't allow you to have multiple dataverse configurati
 
 However for testing purposes, we create a separate test configuration file `~/.config/lslautobids/test-autobids_config.yaml` which is used when running the tests.
 
-#### 2. Project Configuration (`gen_project_config.py`)
+#### Project Configuration (`gen_project_config.py`)
 This module generates a project-specific configuration file in TOML format. This file is stored in the `projects/<PROJECT_NAME>/<PROJECT_NAME>_config.toml` file and contains:
 - Project metadata: Title, description, license, and authors, etc.
 

docs/configuration.md

@@ -1,3 +1,5 @@
+## Contribution Guidelines
+
 First of all, thanks for the interest!
 
 We welcome all kinds of contribution, including, but not limited to code, documentation, examples, configuration, issue creating, etc.

docs/contributions.md

@@ -1,4 +1,4 @@
-### 4. DataLad Integration (`datalad_create.py`)
+## DataLad Integration (`datalad_create.py`)
 
 The DataLad integration module manages the creation and updating of DataLad datasets for version control of the BIDS dataset. This function initializes a DataLad dataset at a given project path.
 The function performs the following steps:

docs/datalad_integration.md

@@ -1,4 +1,4 @@
-### 5. Dataverse Integration
+### Dataverse Integration
 
 #### 1. Dataverse Dataset Creation (`dataverse_dataset_create.py`)
 This module handles the creation of a new dataset in Dataverse using the `pyDataverse` library. The function performs the following steps:

docs/dataverse_integration.md

@@ -1,3 +1,4 @@
+# Frequently Asked Questions (FAQ)
 
 These are some frequently asked questions regarding the LSLAutoBIDS tool and workflow.
 

docs/faq.md

@@ -1,4 +1,4 @@
-### 3. File Processing Pipeline (`processing_new_files.py`)
+### File Processing Pipeline (`processing_new_files.py`)
 
 The file processing part of the pipeline handles finding and processing new XDF files in the specified project directory: