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     "end_time": "2019-02-27T00:53:58.705489Z",
     "start_time": "2019-02-27T00:53:55.960852Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/mnt/cube/tsainbur/conda_envs/tpy3/lib/python3.6/site-packages/tqdm/autonotebook/__init__.py:14: TqdmExperimentalWarning: Using `tqdm.autonotebook.tqdm` in notebook mode. Use `tqdm.tqdm` instead to force console mode (e.g. in jupyter console)\n",
      "  \" (e.g. in jupyter console)\", TqdmExperimentalWarning)\n"
     ]
    }
   ],
   "source": [
    "from birdbrain.atlas import atlas\n",
    "from birdbrain.visualization.plotting_3d import generate_stl\n",
    "from birdbrain.utils import ensure_dir, um_to_vox\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load data, create atlas object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-02-27T00:54:25.594241Z",
     "start_time": "2019-02-27T00:53:58.708300Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "qform_code 32 not valid; setting to 0\n",
      "qform_code 32 not valid; setting to 0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data already download\n",
      "Loading brain labels...\n",
      "Getting voxel data from .img files...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "qform_code 32 not valid; setting to 0\n",
      "qform_code 32 not valid; setting to 0\n"
     ]
    },
    {
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     "metadata": {},
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     "text": [
      "\r"
     ]
    },
    {
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     "text": [
      "\r"
     ]
    },
    {
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     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "Getting location for each nucleus/region from voxel data...\n"
     ]
    },
    {
     "data": {
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       "model_id": "",
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     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "Atlas created\n"
     ]
    }
   ],
   "source": [
    "dset_dir = '../../data/processed/starling/'\n",
    "\n",
    "starling_atlas = atlas(\n",
    "    species = 'starling',\n",
    "    dset_dir = dset_dir,\n",
    "    um_mult = 100,\n",
    "    smoothing = ['Brain', 'Nuclei', 'Tracts'],\n",
    "    updated_y_sinus = [0, 1500, 0]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-02-27T00:54:25.600199Z",
     "start_time": "2019-02-27T00:54:25.596562Z"
    }
   },
   "outputs": [],
   "source": [
    "# ensure the directory\n",
    "ensure_dir('../../data/stl/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-02-27T00:54:28.588897Z",
     "start_time": "2019-02-27T00:54:25.601912Z"
    }
   },
   "outputs": [],
   "source": [
    "# Generate stl of the whole brain\n",
    "zero_point = um_to_vox(np.array([0,0,0]), starling_atlas.voxel_data.loc['Brain' ,'affine'], starling_atlas.um_mult, np.array([0,0,0]))\n",
    "vox = starling_atlas.voxel_data.loc['Brain' ,'voxels']\n",
    "generate_stl(\"../../data/stl/whole_brain.stl\", vox, polygon_simplification=.75, zero_point=zero_point)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-02-27T00:54:28.868467Z",
     "start_time": "2019-02-27T00:54:28.593032Z"
    }
   },
   "outputs": [],
   "source": [
    "vox = starling_atlas.voxel_data.loc['Nuclei' ,'voxels'] == starling_atlas.brain_labels.loc['CMM', 'label']\n",
    "generate_stl(\"../../data/stl/CMM.stl\", vox, polygon_simplification=.5, zero_point = zero_point)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-02-27T00:54:28.874777Z",
     "start_time": "2019-02-27T00:54:28.870655Z"
    }
   },
   "outputs": [],
   "source": [
    "# TODO: generate stl by pulling together half the brain as voxels, and on the other hemisphere grab nuclei of interest (HVC, NCM, CMM, Area X, MAN, Field L)"
   ]
  }
 ],
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