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   "source": [
    "#### Part predictions and unfitting data \n",
    "\n",
    "What if we want only part of the predictions, not the end-nodes?\n",
    "\n",
    "See Tutorial 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a (counter:0, decision_name:None, decision_value:None)\n",
      "├── a0 (counter:0, decision_name:m1, decision_value:-1)\n",
      "├── a1 (counter:0, decision_name:m1, decision_value:1)\n",
      "│   └── a1a (counter:0, decision_name:m2, decision_value:test)\n",
      "└── a2 (counter:0, decision_name:m3, decision_value:another)\n"
     ]
    }
   ],
   "source": [
    "from nbnode.nbnode import NBNode\n",
    "import nbnode.nbnode_trees as nbtree\n",
    "simple_tree = nbtree.tree_simple()\n",
    "simple_tree.pretty_print(\"__long__\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following dictionary would usually have raised a ValueError after it does not reach an endnode: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ValueError: Could not find a fitting endnode for the data you gave. You also did not allow for part predictions.\n"
     ]
    }
   ],
   "source": [
    "try: \n",
    "    simple_tree.predict({\"m1\":1, \"m2\":0, \"m3\":0})\n",
    "except ValueError: \n",
    "    print(\"ValueError: Could not find a fitting endnode for the data you gave. You also did not allow for part predictions.\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "However, allowing for partial predictions enables a more flexible approach to the problem. \n",
    "The previous example actually DOES identify a node (``a1``), however it does not find an endnode. \n",
    "We can enable this by setting ``allow_part_predictions`` argument to True:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NBNode('/a/a1', counter=0, decision_name='m1', decision_value=1)"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "simple_tree.predict({\"m1\":1, \"m2\":0, \"m3\":0}, allow_part_predictions=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that this enables more complex results than just a single NBnode. In the following example, the data finds a matching part **and** endnode!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[NBNode('/a/a1', counter=0, decision_name='m1', decision_value=1),\n",
       " NBNode('/a/a2', counter=0, decision_name='m3', decision_value='another')]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "simple_tree.predict({\"m1\":1, \"m2\":0, \"m3\":\"another\"}, allow_part_predictions=True)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following prediction fails because:\n",
    "\n",
    "    1.1 Check if m1=-1 (no)\n",
    "    2.1 Check if m1=1 (yes)\n",
    "    2.2 Check if m2='test' (no), no endnode!\n",
    "      raise exception because in this path no proper endnode was able to be\n",
    "      found with the given values\n",
    "    3.1 Check if m3='another' (yes) -> return this node\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ValueError: Could not find a fitting endnode for the data you gave. You also did not allow for part predictions.\n"
     ]
    }
   ],
   "source": [
    "try: \n",
    "    simple_tree.predict(values={\"m1\": 1, \"m2\": -1, \"m3\": \"another\"})\n",
    "except ValueError:\n",
    "    print(\"ValueError: Could not find a fitting endnode for the data you gave. You also did not allow for part predictions.\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With ``allow_unfitting_data=True``, the previously ValueError is not called and a proper endnode returned! \n",
    "\n",
    "    1.1 Check if m1=-1 (no)\n",
    "    2.1 Check if m1=1 (yes)\n",
    "    2.2 Check if m2='test' (no), no endnode!\n",
    "      raise exception because in this path no proper endnode was able to be\n",
    "      found with the given values\n",
    "    3.1 Check if m3='another' (yes) -> return this node\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NBNode('/a/a2', counter=0, decision_name='m3', decision_value='another')"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "simple_tree.predict(\n",
    "    values={\"m1\": 1, \"m2\": -1, \"m3\": \"another\"}, allow_unfitting_data=True\n",
    ")\n"
   ]
  }
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