examples/notebooks/quantization/compute_centroids_pairwise_distances.ipynb

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   "cell_type": "code",
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   "source": [
    "from __init__ import *\n",
    "import core.steps as steps\n",
    "from core import data_store as ds\n",
    "from core import transformer as tr\n",
    "from core.common.ds_utils import print_ds_items_info\n",
    "from core.quantization.pq_quantizer import PQQuantizer, restore_from_clusters, build_pq_params_str\n",
    "from core.common.path_helper import DataStoreHelper\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
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    "ds_helper=DataStoreHelper(r'C:\\data\\computation\\brodatz')"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "# SDC search requirement - compute centroids pairwise distances"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
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   "source": [
    "def compute_centroids_pairwise_distances(descriptor_name, pq_params):\n",
    "    centroids_ds = ds_helper.centroids_ds(descriptor_name, pq_params)\n",
    "    centroids = ds.get_as_array(centroids_ds)\n",
    "    centroids_pairwise_distances_ds = ds_helper.centroids_pairwise_distances_ds(descriptor_name, pq_params)\n",
    "    steps.transform_step(centroids_ds, [tr.VectorsToPairwiseDistances()], centroids_pairwise_distances_ds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "K_arr = [2 ** i for i in [4,5,6,7,8]]\n",
    "m_arr = [m for m in [1, 2, 4, 8, 16]]\n",
    "pq_params_arr = [{'n_clusters': K, 'n_quantizers': m} for K in K_arr for m in m_arr]\n",
    "\n",
    "descriptor_names=['histograms', 'glcms','lbphistograms']\n",
    "choosen_bovwproductbincounts_pq_params= [{'n_clusters': K, 'n_quantizers': m} for K,m in [(64,4),(128,1),(16,1)]]\n",
    "descriptor_names+=ds_helper.bovw_descriptors_names('bovwproductbincounts',choosen_bovwproductbincounts_pq_params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for descriptor_name in descriptor_names:\n",
    "    for pq_params in pq_params_arr:\n",
    "        compute_centroids_pairwise_distances(descriptor_name, pq_params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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