Prepare v1.0.0 release as acsm-fairifier

CHANGELOG.md

@@ -0,0 +1,20 @@
+# Changelog
+
+All notable changes to this project will be documented in this file, which is a **cumulative record**.
+
+Each version entry follows a consistent structure with the following optional sections:
+
+- **Added** – New features
+- **Changed** – Modifications to existing functionality
+- **Deprecated** – Features marked for future removal
+- **Removed** – Features removed in this version
+- **Fixed** – Bug fixes
+- **Security** – Vulnerability fixes
+
+Format based on [Keep a Changelog](https://keepachangelog.com) and [Semantic Versioning](https://semver.org).
+
+
+## [v1.0.0] - 2025-07-04
+### Added
+- Initial release of the ACSM FAIRifier
+

README.md

@@ -113,16 +113,16 @@ Open **Git Bash** and run:
 
 ```bash
 cd Gitea
-git clone --recurse-submodules https://gitea.psi.ch/apog/acsmnode.git
+git clone --recurse-submodules https://gitea.psi.ch/apog/acsm-fairifier.git
-cd acsmnode
+cd acsm-fairifier
 ```
 
 ## Run the ACSM FAIRifier Toolkit
 
 This toolkit includes a containerized JupyterLab environment for executing the data processing pipeline, plus an optional dashboard for manual flagging.
 
-1. Open **PowerShell as Administrator** and navigate to the `acsmnode` repository.  
+1. Open **PowerShell as Administrator** and navigate to the `acsm-fairifier` repository.  
-2. Create a `.env` file in the root of `acsmnode/`.  
+2. Create a `.env` file in the root of `acsm-fairifier/`.  
 3. **Securely store your network drive access credentials** in the `.env` file by adding the following lines: 
    ```plaintext
    CIFS_USER=<your-username>
@@ -175,13 +175,9 @@ We recommend using Miniforge to manage your conda environments. Miniforge ensure
 2. Create the Environment from `environment.yml`
 After installing Miniforge, open **Miniforge Prompt** or a terminal with access to conda and run:
    ```bash
-   cd path/to/Gitea/acsmnode
+   cd path/to/Gitea/acsm-fairifier
    conda env create --file environment.yml
    ```
-3. Activate the Environment
-   ```bash
-   conda activate acsmnode_env
-   ```
 
 ### Working with Jupyter Notebooks
 We now make the previously installed Python environment `acsmnode_env` selectable as a kernel in Jupyter's interface.

notebooks/demo_acsm_pipeline.ipynb

@@ -20,9 +20,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "c:\\Users\\juanf\\OneDrive\\Documents\\Gitea\\acsmnode\\dima\n",
+      "c:\\Users\\juanf\\OneDrive\\Documents\\Gitea\\acsmnode\n",
+      "c:\\Users\\juanf\\OneDrive\\Documents\\Gitea\\acsmnode\\dima\n",
+      "c:\\Users\\juanf\\OneDrive\\Documents\\Gitea\\acsmnode\n",
+      "c:\\Users\\juanf\\OneDrive\\Documents\\Gitea\\acsmnode\\dima\n",
+      "c:\\Users\\juanf\\envs\\acsmnode_env\\python311.zip\n",
+      "c:\\Users\\juanf\\envs\\acsmnode_env\\DLLs\n",
+      "c:\\Users\\juanf\\envs\\acsmnode_env\\Lib\n",
+      "c:\\Users\\juanf\\envs\\acsmnode_env\n",
+      "\n",
+      "c:\\Users\\juanf\\envs\\acsmnode_env\\Lib\\site-packages\n",
+      "c:\\Users\\juanf\\envs\\acsmnode_env\\Lib\\site-packages\\win32\n",
+      "c:\\Users\\juanf\\envs\\acsmnode_env\\Lib\\site-packages\\win32\\lib\n",
+      "c:\\Users\\juanf\\envs\\acsmnode_env\\Lib\\site-packages\\Pythonwin\n",
+      "c:\\Users\\juanf\\OneDrive\\Documents\\Gitea\\acsmnode\n",
+      "c:\\Users\\juanf\\OneDrive\\Documents\\Gitea\\acsmnode\\third_party\\acsmProcessingSoftware\\src\n",
+      "c:\\Users\\juanf\\OneDrive\\Documents\\Gitea\\acsmnode\\third_party\\acsmProcessingSoftware\\src\\db\n",
+      "c:\\Users\\juanf\\OneDrive\\Documents\\Gitea\\acsmnode\\third_party\\acsmProcessingSoftware\\src\\iointerface\n",
+      "c:\\Users\\juanf\\OneDrive\\Documents\\Gitea\\acsmnode\\third_party\\acsmProcessingSoftware\n",
+      "workflow_acsm_data_JFJ_2024\n"
+     ]
+    }
+   ],
    "source": [
     "import sys\n",
     "import os\n",
@@ -81,9 +108,58 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Manually loaded .env from: C:\\Users\\juanf\\OneDrive\\Documents\\Gitea\\acsmnode\\.env\n",
+      "Success : True\n",
+      "[Notice] All files already exist at ../data/collection_1_JFJ_2024_2025-07-04/, skipping copy.\n",
+      "\n",
+      "[Start] Data integration :\n",
+      "Source: ..\\data\\collection_1_JFJ_2024_2025-07-04\n",
+      "Destination: ..\\data\\collection_1_JFJ_2024_2025-07-04.h5\n",
+      "\n",
+      "Starting data transfer from instFolder: /ACSM_TOFWARE/2024\n",
+      "Completed transfer for //ACSM_TOFWARE/2024/calibration_params.yaml\n",
+      "Completed transfer for //ACSM_TOFWARE/2024/limits_of_detection.yaml\n",
+      "Completed transfer for //ACSM_TOFWARE/2024/validity_thresholds.yaml\n",
+      "[==================================================--------------------------------------------------] 50.0% ...\n",
+      "Completed data transfer for instFolder: /ACSM_TOFWARE/2024\n",
+      "Completed transfer for //ACSM_TOFWARE/2024/ACSM_JFJ_2024_meta.txt\n",
+      "Completed transfer for //ACSM_TOFWARE/2024/ACSM_JFJ_2024_timeseries.txt\n",
+      "Startdate                     20240101000000\n",
+      "\n",
+      "Completed transfer for //ACSM_TOFWARE/2024/CH0001G.20240101000000.20250430141458.cpc.particle_number_concentration.aerosol.1y.1mn.CH02L_TSI_3772_JFJ.CH02L_CPC.lev1.nas\n",
+      "Completed transfer for //ACSM_TOFWARE/2024/Org_data_valid.csv\n",
+      "Completed transfer for //ACSM_TOFWARE/2024/Org_err_valid.csv\n",
+      "Completed transfer for //ACSM_TOFWARE/2024/Org_mz_valid.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\Users\\juanf\\OneDrive\\Documents\\Gitea\\acsmnode\\dima\\instruments\\readers\\acsm_tofware_reader.py:112: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n",
+      "  df = pd.read_csv(tmp_filename,\n",
+      "c:\\Users\\juanf\\OneDrive\\Documents\\Gitea\\acsmnode\\dima\\instruments\\readers\\acsm_tofware_reader.py:112: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n",
+      "  df = pd.read_csv(tmp_filename,\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Completed transfer for //ACSM_TOFWARE/2024/Org_time_valid.csv\n",
+      "[====================================================================================================] 100.0% ...\n",
+      "Completed data transfer for instFolder: /ACSM_TOFWARE/2024\n",
+      "[End] Data integration\n"
+     ]
+    }
+   ],
    "source": [
     "path_to_config_file = '../campaignDescriptor.yaml'\n",
     "paths_to_hdf5_files = get_campaign_data(path_to_config_file)\n",
@@ -353,7 +429,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "acsmnode_env",
    "language": "python",
    "name": "python3"
   },
@@ -367,7 +443,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.10"
+   "version": "3.11.13"
   }
  },
  "nbformat": 4,