updated submission.md et FAQ"

phase-0-smoothie/bundle/FAQ.md

@@ -1 +1,51 @@
-To complete
+# Problems with creating or submiting your code ? Try the following : 
+
+
+## Submissions fail ?  -> Have a look at the logs on Codabench
+
+If your submission fails on Codabench, don't panic—review the logs! You can access them via the Codabench user interface:
+
+1. Go to the "Submission" tab and scroll to the end of the page to find your submission.
+2. Click on the row corresponding to your submission.
+3. Select the "Logs" tab.
+4. Browse the various types of logs available: `stdout`, `stderr`, `Ingestion stdout`, and `Ingestion stderr`, for both the ingestion and scoring steps.
+
+## Cannot create your submissions ? Try our conda environnement:  (Especially useful for python user !)
+
+A conda evnironnement is provided follow this steps to install and activate it: 
+- retrieve the file environment-r.yml from github : [environment-r.yml](https://github.com/bcm-uga/hadaca3/blob/main/docker/codabench_hadaca3_pyr/environment/environment-r.yml) : 
+- `wget https://raw.githubusercontent.com/bcm-uga/hadaca3/main/docker/codabench_hadaca3_pyr/environment/environment-r.yml`
+- and run: `conda env create -f environment-r.yml && conda activate h3`
+
+
+
+## Running Submissions ingestion and scoring locally with Docker
+
+To speed up the debugging process and avoid the full submission workflow, you can run your submission program locally using **FAKE** data. The fake data serves two purposes: first, it allows testing without relying on the actual scoring program (which requires the ground truth), and second, it speeds up computation.
+
+To test locally, follow these steps:
+
+1. Clone the challenge repository:
+   ```
+   git clone https://github.com/bcm-uga/hadaca3.git
+   cd hadaca3
+   ```
+2. Set up the environment and activate it:
+   ```
+   conda env create -f environment-r.yml && conda activate h3
+   ```
+3. Run the automated Docker test script:
+   ```
+   sh automated_docker_test.sh
+   ```
+
+Please note that this script will use the `submission_script.R` from the `hadaca3/starting_kit/` folder. **Ensure that your script is placed inside the `hadaca3/starting_kit/` folder or modify the existing script at `hadaca3/starting_kit/submission_script.R`**.
+
+
+The script `automated_docker_test.sh` first executes the R submission script locally, then re-executes it within the Docker container (ingestion phase), followed by running the scoring program.
+
+If you wish to test each step independently or run the Python script locally, refer to the `README.md` in the `hadaca3` GitHub repository.
+
+## Include an external file to be used in the submission script
+It is possible to include an external file that is sourced in the submission script and correctly included in the zip file to be submitted on the Codabench platform.
+Beware, when unziped the file 'program.R' has to be on the current directory and not inside a folder. Aditionnal files can in other folder with the correct relative path 

phase-0-smoothie/bundle/submission.md

@@ -1,3 +1,5 @@
+If this page does not answer your questions try the FAQ page :) 
+
 ## How to generate a prediction of the data (R)?
 
 [1] On your local machine, unzip the starting_kit.zip.
@@ -13,7 +15,7 @@ The unziped starting_kit directory contains now:
  - From terminal run `Rscript submission_script.R` 
  - Launch an R console and execute the following command : `source("submission_script.R")`
  - Run the `submission_script.R` in RStudio/ Vscode
- - From docker :`sudo docker run -v .:/hadaca3 -w /hadaca3  hombergn/hadaca3_pyr Rscript submission_script.R`
+ - From docker :`sudo docker run -v .:/hadaca3 -w /hadaca3  hombergn/hadaca3_pyr Rscript submission_script.R`  and regain ownership of the files generated with `sudo chown -R $USER submissions`
 
 
 [3] The code of the  `submission_script.R`  generates the files:
@@ -35,7 +37,7 @@ Edit the code inside the following chunk (i.e. the `program` function):
 
 
 ## How to generate a prediction of the data (Python)?
-Please note that this challenge was primarily designed with R in mind, and as such, R functionality and compatibility have been tested more extensively than those in Python. When using Python, keep in mind that your scripts will need to interact with R data, which requires the rpy2 library. To facilitate this, a Conda environment has been provided. For more details, please refer to the "Conda Environment" chapter under "Troubleshooting".
+Please note that this challenge was primarily designed with R in mind, and as such, R functionality and compatibility have been tested more extensively than those in Python. When using Python, keep in mind that your scripts will need to interact with R data, which requires the rpy2 library. To facilitate this, a Conda environment has been provided. For more details, please refer to the "Conda Environment" chapter under the "FAQ" page.
 
 [1] On your local machine, unzip the starting_kit.zip.
 
@@ -50,7 +52,7 @@ The unzipped starting_kit directory contains now:
  - From terminal run `python submission_script.py` 
  - Launch an interactive python shell by executing : `python -i submission_script.py`
  - Run the `submission_script.py` in Spider/ Vscode
- - From docker : `sudo docker run -v .:/hadaca3 -w /hadaca3  hombergn/hadaca3_pyr python submission_script.py`
+ - From docker : `sudo docker run -v .:/hadaca3 -w /hadaca3  hombergn/hadaca3_pyr python submission_script.py` and regain ownership of the files generated with `sudo chown -R $USER submissions`
 
 
 [3] The code of the  `submission_script.R`  generates the files:
@@ -96,52 +98,3 @@ By clicking on your submission in the submissions summary table, you will access
   - a submission metadata edition menu
 
 [3] Check the leaderboard in the *Results*  menu
-
-## Troubleshooting
-
-### Conda environnement: 
-
-A conda evnironnement is provided follow this steps to install and activate it: 
-- retrieve the file environment-r.yml from github : [environment-r.yml](https://github.com/bcm-uga/hadaca3/blob/main/docker/codabench_hadaca3_pyr/environment/environment-r.yml) : 
-- `wget https://raw.githubusercontent.com/bcm-uga/hadaca3/main/docker/codabench_hadaca3_pyr/environment/environment-r.yml`
-- and run: `conda env create -f environment-r.yml && conda activate h3`
-
-
-### Logs on Codabench
-
-If your submission fails on Codabench, don't panic—review the logs! You can access them via the Codabench user interface:
-
-1. Go to the "Submission" tab and scroll to the end of the page to find your submission.
-2. Click on the row corresponding to your submission.
-3. Select the "Logs" tab.
-4. Browse the various types of logs available: `stdout`, `stderr`, `Ingestion stdout`, and `Ingestion stderr`, for both the ingestion and scoring steps.
-
-### Running Submissions ingestion and scoring locally with Docker
-
-To speed up the debugging process and avoid the full submission workflow, you can run your submission program locally using **FAKE** data. The fake data serves two purposes: first, it allows testing without relying on the actual scoring program (which requires the ground truth), and second, it speeds up computation.
-
-To test locally, follow these steps:
-
-1. Clone the challenge repository:
-   ```
-   git clone https://github.com/bcm-uga/hadaca3.git
-   cd hadaca3
-   ```
-2. Set up the environment and activate it:
-   ```
-   conda env create -f environment-r.yml && conda activate h3
-   ```
-3. Run the automated Docker test script:
-   ```
-   sh automated_docker_test.sh
-   ```
-
-Please note that this script will use the `submission_script.R` from the `hadaca3/starting_kit/` folder. **Ensure that your script is placed inside the `hadaca3/starting_kit/` folder or modify the existing script at `hadaca3/starting_kit/submission_script.R`**.
-
-
-The script `automated_docker_test.sh` first executes the R submission script locally, then re-executes it within the Docker container (ingestion phase), followed by running the scoring program.
-
-If you wish to test each step independently or run the Python script locally, refer to the `README.md` in the `hadaca3` GitHub repository.
-
-### Including an external file to be used in the submission script
-It is possible to include an external file that is sourced in the submission script and correctly included in the zip file to be submitted on the Codabench platform.