{
  "id": 19172,
  "title": "bug in Fourier Based Tutorial",
  "url": "/competitions/second-annual-data-science-bowl/discussion/19172",
  "author_name": "",
  "post_date": "2016-02-25T01:11:18.477Z",
  "votes": null,
  "comment_count": 1,
  "views": 368,
  "content": "<p>At the start of the function <code>get_weighted_distances</code> the vector <code>n</code> should be normalized. For example:</p>\n\n<pre><code>n = np.array([1, ys, xs])/np.sqrt(1.*1. + ys*ys + xs*xs)\n</code></pre>",
  "messages": [
    {
      "id": "109308",
      "postDate": "02/25/2016 01:11:18",
      "content": "<p>At the start of the function <code>get_weighted_distances</code> the vector <code>n</code> should be normalized. For example:</p>\n\n<pre><code>n = np.array([1, ys, xs])/np.sqrt(1.*1. + ys*ys + xs*xs)\n</code></pre>",
      "rawMarkdown": "At the start of the function `get_weighted_distances` the vector `n` should be normalized. For example:\r\n\r\n    n = np.array([1, ys, xs])/np.sqrt(1.*1. + ys*ys + xs*xs)",
      "votes": null
    },
    {
      "id": "109311",
      "postDate": "02/25/2016 01:36:52",
      "content": "<p>Yes, the example is a good a proof of concept. :D And have many problems.</p>",
      "rawMarkdown": "Yes, the example is a good a proof of concept. :D And have many problems.",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 109311,
      "author_name": "alvaroosvaldo",
      "author_url": "",
      "post_date": "02/25/2016 01:36:52",
      "content": "<p>Yes, the example is a good a proof of concept. :D And have many problems.</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "109308": "At the start of the function `get_weighted_distances` the vector `n` should be normalized. For example:\r\n\r\n    n = np.array([1, ys, xs])/np.sqrt(1.*1. + ys*ys + xs*xs)",
    "109311": "Yes, the example is a good a proof of concept. :D And have many problems."
  },
  "source": "meta"
}