{
  "id": 524331,
  "title": "2024 Normalized flux dataset (Host shared notebook) [Dataset ~2.5GB]",
  "url": "/competitions/ariel-data-challenge-2024/discussion/524331",
  "author_name": "SeshuRaju 🧘‍♂️",
  "post_date": "2024-08-05T17:53:18.961000",
  "votes": 8,
  "comment_count": 2,
  "views": 0,
  "content": "<h1><a href=\"https://academic.oup.com/rasti/article/2/1/45/6998590\" target=\"_blank\">Paper - ESA-Ariel Data Challenge NeurIPS 2022: introduction to exo-atmospheric studies and presentation of the Atmospheric Big Challenge (ABC) Database</a></h1>\n<p><img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F761268%2Fe2f62ed6b8e5f391da1273219f2719c4%2FScreenshot%202024-08-05%20at%2011.20.27PM.png?generation=1722880273756783&amp;alt=media\" alt=\"\"></p>\n<hr>\n<h1><a href=\"https://www.kaggle.com/datasets/seshurajup/calibrating-and-time-binning-astronomical-dataset/data\" target=\"_blank\">Dataset ~ 2.5GB</a></h1>\n<blockquote>\n  <p>-&gt; <strong>It took ~ 3 hours to build these normalised flux files</strong><br>\n  -&gt; for <strong>test set will take ~ 3.5 to 4 hours to build these normalised flux fiels</strong> (@gordonyip -&gt; is possible these meta data's available as normalised flux folder in hidden and train dataset -&gt; then most of them focus on model instead building the normalised flux dataset )</p>\n</blockquote>\n<hr>\n<h1><a href=\"https://www.kaggle.com/code/gordonyip/calibrating-and-time-binning-astronomical-data/notebook\" target=\"_blank\">Notebook - Calibrating and Time Binning Astronomical Data</a></h1>\n<p><img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F761268%2F1bbefa93401737d011b6ae820e3e0fa0%2FScreenshot%202024-08-05%20at%2011.21.01PM.png?generation=1722880283195431&amp;alt=media\" alt=\"\"> </p>\n<hr>\n<blockquote>\n  <h1>- is 2022 competition is more similar to 2024 <a href=\"https://www.kaggle.com/gordonyip\" target=\"_blank\">@gordonyip</a> ?   -&gt; <strong>NO - host conformed</strong></h1>\n</blockquote>\n<hr>\n<h1></h1>\n<h1></h1>\n<h1></h1>\n<h1></h1>",
  "messages": [
    {
      "id": 2948154,
      "postDate": "2024-08-05T17:53:18.963Z",
      "content": "<h1><a href=\"https://academic.oup.com/rasti/article/2/1/45/6998590\" target=\"_blank\">Paper - ESA-Ariel Data Challenge NeurIPS 2022: introduction to exo-atmospheric studies and presentation of the Atmospheric Big Challenge (ABC) Database</a></h1>\n<p><img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F761268%2Fe2f62ed6b8e5f391da1273219f2719c4%2FScreenshot%202024-08-05%20at%2011.20.27PM.png?generation=1722880273756783&amp;alt=media\" alt=\"\"></p>\n<hr>\n<h1><a href=\"https://www.kaggle.com/datasets/seshurajup/calibrating-and-time-binning-astronomical-dataset/data\" target=\"_blank\">Dataset ~ 2.5GB</a></h1>\n<blockquote>\n  <p>-&gt; <strong>It took ~ 3 hours to build these normalised flux files</strong><br>\n  -&gt; for <strong>test set will take ~ 3.5 to 4 hours to build these normalised flux fiels</strong> (@gordonyip -&gt; is possible these meta data's available as normalised flux folder in hidden and train dataset -&gt; then most of them focus on model instead building the normalised flux dataset )</p>\n</blockquote>\n<hr>\n<h1><a href=\"https://www.kaggle.com/code/gordonyip/calibrating-and-time-binning-astronomical-data/notebook\" target=\"_blank\">Notebook - Calibrating and Time Binning Astronomical Data</a></h1>\n<p><img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F761268%2F1bbefa93401737d011b6ae820e3e0fa0%2FScreenshot%202024-08-05%20at%2011.21.01PM.png?generation=1722880283195431&amp;alt=media\" alt=\"\"> </p>\n<hr>\n<blockquote>\n  <h1>- is 2022 competition is more similar to 2024 <a href=\"https://www.kaggle.com/gordonyip\" target=\"_blank\">@gordonyip</a> ?   -&gt; <strong>NO - host conformed</strong></h1>\n</blockquote>\n<hr>\n<h1></h1>\n<h1></h1>\n<h1></h1>\n<h1></h1>",
      "rawMarkdown": "# [Paper - ESA-Ariel Data Challenge NeurIPS 2022: introduction to exo-atmospheric studies and presentation of the Atmospheric Big Challenge (ABC) Database](https://academic.oup.com/rasti/article/2/1/45/6998590)\n\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F761268%2Fe2f62ed6b8e5f391da1273219f2719c4%2FScreenshot%202024-08-05%20at%2011.20.27PM.png?generation=1722880273756783&alt=media)\n\n---\n\n# [Dataset ~ 2.5GB](https://www.kaggle.com/datasets/seshurajup/calibrating-and-time-binning-astronomical-dataset/data)\n> -> **It took ~ 3 hours to build these normalised flux files**\n> -> for **test set will take ~ 3.5 to 4 hours to build these normalised flux fiels** (@gordonyip -> is possible these meta data's available as normalised flux folder in hidden and train dataset -> then most of them focus on model instead building the normalised flux dataset )\n\n---\n\n# [Notebook - Calibrating and Time Binning Astronomical Data](https://www.kaggle.com/code/gordonyip/calibrating-and-time-binning-astronomical-data/notebook)\n\n\n\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F761268%2F1bbefa93401737d011b6ae820e3e0fa0%2FScreenshot%202024-08-05%20at%2011.21.01PM.png?generation=1722880283195431&alt=media) \n\n---\n\n\n> # - is 2022 competition is more similar to 2024 @gordonyip ?  ~~[using as external dataset]~~ -> **NO - host conformed**\n\n---\n\n# ~~[2022 competition 2nd place code](https://github.com/EyupBunlu/ArielDataChallenge2022Gators/tree/main)~~\n# ~~@[2023 competition 1st place code](https://github.com/AstroAI-CfA/Ariel_Data_Challenge_2023_solution)~~\n# ~~[2023 competition 2nd place code](https://github.com/EyupBunlu/ArielDataChallenge2023Gators)~~\n# ~~[2023 competition 3rd place code](https://github.com/acsweet/ariel_data_challenge_2023)~~\n\n",
      "votes": 8
    },
    {
      "id": 2948973,
      "postDate": "2024-08-06T09:42:27.083Z",
      "content": "<p>No, ADC 2022 addresses another problem in the pipeline. That competition focuses on interpreting the spectrum, while in this competition we are trying to extract the spectrum.</p>",
      "rawMarkdown": "No, ADC 2022 addresses another problem in the pipeline. That competition focuses on interpreting the spectrum, while in this competition we are trying to extract the spectrum.",
      "votes": 3,
      "replies": [
        {
          "id": 2949002,
          "postDate": "2024-08-06T10:14:30.420Z",
          "content": "<p><a href=\"https://www.kaggle.com/gordonyip\" target=\"_blank\">@gordonyip</a> is it means, we cannot use external datasets except competition dataset or any similar datasets can be used for model pre-training? </p>",
          "rawMarkdown": "@gordonyip is it means, we cannot use external datasets except competition dataset or any similar datasets can be used for model pre-training? "
        }
      ]
    }
  ],
  "comments": [
    {
      "id": 2948973,
      "author_name": "Gordon Yip",
      "author_url": "",
      "post_date": "2024-08-06T09:42:27.083000",
      "content": "<p>No, ADC 2022 addresses another problem in the pipeline. That competition focuses on interpreting the spectrum, while in this competition we are trying to extract the spectrum.</p>",
      "votes": 3,
      "replies": [
        {
          "id": 2949002,
          "author_name": "SeshuRaju 🧘‍♂️",
          "author_url": "",
          "post_date": "2024-08-06T10:14:30.420000",
          "content": "<p><a href=\"https://www.kaggle.com/gordonyip\" target=\"_blank\">@gordonyip</a> is it means, we cannot use external datasets except competition dataset or any similar datasets can be used for model pre-training? </p>",
          "votes": 0,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "2948154": "# [Paper - ESA-Ariel Data Challenge NeurIPS 2022: introduction to exo-atmospheric studies and presentation of the Atmospheric Big Challenge (ABC) Database](https://academic.oup.com/rasti/article/2/1/45/6998590)\n\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F761268%2Fe2f62ed6b8e5f391da1273219f2719c4%2FScreenshot%202024-08-05%20at%2011.20.27PM.png?generation=1722880273756783&alt=media)\n\n---\n\n# [Dataset ~ 2.5GB](https://www.kaggle.com/datasets/seshurajup/calibrating-and-time-binning-astronomical-dataset/data)\n> -> **It took ~ 3 hours to build these normalised flux files**\n> -> for **test set will take ~ 3.5 to 4 hours to build these normalised flux fiels** (@gordonyip -> is possible these meta data's available as normalised flux folder in hidden and train dataset -> then most of them focus on model instead building the normalised flux dataset )\n\n---\n\n# [Notebook - Calibrating and Time Binning Astronomical Data](https://www.kaggle.com/code/gordonyip/calibrating-and-time-binning-astronomical-data/notebook)\n\n\n\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F761268%2F1bbefa93401737d011b6ae820e3e0fa0%2FScreenshot%202024-08-05%20at%2011.21.01PM.png?generation=1722880283195431&alt=media) \n\n---\n\n\n> # - is 2022 competition is more similar to 2024 @gordonyip ?  ~~[using as external dataset]~~ -> **NO - host conformed**\n\n---\n\n# ~~[2022 competition 2nd place code](https://github.com/EyupBunlu/ArielDataChallenge2022Gators/tree/main)~~\n# ~~@[2023 competition 1st place code](https://github.com/AstroAI-CfA/Ariel_Data_Challenge_2023_solution)~~\n# ~~[2023 competition 2nd place code](https://github.com/EyupBunlu/ArielDataChallenge2023Gators)~~\n# ~~[2023 competition 3rd place code](https://github.com/acsweet/ariel_data_challenge_2023)~~\n\n",
    "2948973": "No, ADC 2022 addresses another problem in the pipeline. That competition focuses on interpreting the spectrum, while in this competition we are trying to extract the spectrum."
  }
}