{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-02-27T02:21:42.494316Z",
     "start_time": "2019-02-27T02:21:42.465698Z"
    }
   },
   "outputs": [],
   "source": [
    "# for automatic reloading\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-02-27T02:21:45.389187Z",
     "start_time": "2019-02-27T02:21:42.496672Z"
    }
   },
   "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.utils import um_to_vox\n",
    "import numpy as np\n",
    "from birdbrain.visualization.plotting_3d import plot_regions_3d, rotate_plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-02-27T02:21:45.424011Z",
     "start_time": "2019-02-27T02:21:45.391471Z"
    }
   },
   "outputs": [],
   "source": [
    "password = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-02-27T02:21:47.022790Z",
     "start_time": "2019-02-27T02:21:45.425984Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data already download\n",
      "Getting voxel data from .img files...\n",
      "Getting location for each nucleus/region from voxel data...\n"
     ]
    },
    {
     "data": {
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      ]
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     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "Atlas created\n"
     ]
    }
   ],
   "source": [
    "# NBVAL_SKIP\n",
    "dset_dir = '../../data/processed/zebra_finch/'\n",
    "\n",
    "zebra_finch_atlas = atlas(\n",
    "    species = 'zebra_finch',\n",
    "    dset_dir = dset_dir,\n",
    "    um_mult = 100,\n",
    "    smoothing = [], #['Brain', 'Brainregions']\n",
    "    password = password\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-02-27T02:21:47.063029Z",
     "start_time": "2019-02-27T02:21:47.025138Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Nuclei']\n",
      "['DLM' 'E' 'HVC' 'L' 'LMAN' 'MLd' 'Olfactory_bulb' 'Ov' 'RA' 'Rt' 'TeO'\n",
      " 'X' 'nXIIts']\n"
     ]
    }
   ],
   "source": [
    "# NBVAL_SKIP\n",
    "# the only delineation for zebra finch is nuclei\n",
    "print(np.unique(list(zebra_finch_atlas.brain_labels.type_)))\n",
    "print(np.unique(list(zebra_finch_atlas.brain_labels.index)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-02-27T02:21:47.166702Z",
     "start_time": "2019-02-27T02:21:47.064968Z"
    }
   },
   "outputs": [],
   "source": [
    "# NBVAL_SKIP\n",
    "nuclei = [[reg, 'Nuclei'] for reg in list(zebra_finch_atlas.brain_labels[zebra_finch_atlas.brain_labels.type_ == 'Nuclei'].region.values)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-02-27T02:21:51.297472Z",
     "start_time": "2019-02-27T02:21:47.168959Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/mnt/cube/tsainbur/conda_envs/tpy3/lib/python3.6/site-packages/traittypes/traittypes.py:101: UserWarning: Given trait value dtype \"uint8\" does not match required type \"float32\". A coerced copy has been created.\n",
      "  np.dtype(self.dtype).name))\n"
     ]
    },
    {
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     "text": [
      "\r"
     ]
    },
    {
     "data": {
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       "model_id": "5b0b9653ba7c4492ac3587c56269f8fe",
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       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
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       "FloatSlider(value=0.0, description='medial-lateral:', max=10200.0, min=-10200.0, step=100.0)"
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     "metadata": {},
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    {
     "data": {
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       "version_minor": 0
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      "text/plain": [
       "FloatSlider(value=0.0, description='posterior-anterior:', max=10200.0, min=-10200.0, step=100.0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2cf5105a64d843c3894fba70ab2f0cc5",
       "version_major": 2,
       "version_minor": 0
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      "text/plain": [
       "FloatSlider(value=0.0, description='ventral-dorsal:', max=10200.0, min=-10200.0, step=100.0)"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7b1bce3e233d4acc95dd2945a1588c8c",
       "version_major": 2,
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      "text/plain": [
       "Dropdown(description='Region:', index=13, options=('L', 'HVC', 'X', 'RA', 'E', 'LMAN', 'MLd', 'DLM', 'Ov', 'Ol…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# NBVAL_SKIP\n",
    "plot, vec  = plot_regions_3d(zebra_finch_atlas, regions_to_plot = nuclei, downsample_pct = 1,\n",
    "                             polygon_simplification = 0,\n",
    "                             verbose=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-02-27T02:21:55.348525Z",
     "start_time": "2019-02-27T02:21:51.300099Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
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       "HBox(children=(IntProgress(value=0, max=120), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r"
     ]
    }
   ],
   "source": [
    "# NBVAL_SKIP\n",
    "rotate_plot(plot, n_frames = 60,  fr=32, nrot = 2, radius = 8000)"
   ]
  }
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