03_enumerate_loops.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Loop closure"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Boilerplate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/mnt/home/pleung/projects/bistable_bundle/r4/hinges\n",
      "dig130\n"
     ]
    }
   ],
   "source": [
    "%load_ext lab_black\n",
    "# python internal\n",
    "import collections\n",
    "import copy\n",
    "import gc\n",
    "from glob import glob\n",
    "import h5py\n",
    "import itertools\n",
    "import os\n",
    "import random\n",
    "import re\n",
    "import socket\n",
    "import shutil\n",
    "import subprocess\n",
    "import sys\n",
    "\n",
    "# conda/pip\n",
    "import dask\n",
    "import graphviz\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import scipy\n",
    "import seaborn as sns\n",
    "from tqdm import tqdm\n",
    "\n",
    "# special packages on the DIGS\n",
    "import py3Dmol\n",
    "import pymol\n",
    "import pyrosetta\n",
    "\n",
    "# notebook magic\n",
    "%matplotlib inline\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "print(os.getcwd())\n",
    "print(socket.gethostname())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Flo's original approach:\n",
    "4. now it gets even worse. I use`/home/flop/switch/5thround/DHRs/loops/score_to_loop.ipynb` to generate cmds for loop closure. have a look, and then we should probably talk about it. it is messy.\n",
    "\t\n",
    "basically I first try to find loops that match the original DHR, for example\n",
    "in: `/home/flop/switch/5thround/DHRs/loops/match_orig_d6_04/`\n",
    "\n",
    "because this doesn't work for all of them, I also re-loop the original DHRs,\n",
    "also sampling truncations and extensions of the helices before and after the\n",
    "new loop\n",
    "\n",
    "i exhaustively did that for all dhrs in my input set: \n",
    "`/home/flop/switch/5thround/DHRs/loops/x_ind_all_te`\n",
    "\n",
    "then I try to find loops in the new states that match the outputs of the state\n",
    "x relooping: `/home/flop/switch/5thround/DHRs/loops/match_ind_d6/`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### I will follow Flo's looping procedure with some changes.\n",
    "I will use the serialization build of PyRosetta to enable recording user defined info about the designs.  \n",
    "This enables downstream inline filtering and data analysis, as well as clustering by lineage.\n",
    "I will try the following hierarchy of closure methods: \n",
    "1. close using identical length loop and no adjustment with connect chains mover (CCM) at 0.8 RMS (total length and SS match)\n",
    "2. constrained remodel with `BluePrintBDR`, forcing SS agreement with parent but allowing any `ABEGO` (total length and SS match)\n",
    "These methods seem to get around 75% closure, which I think will be pretty workable.  \n",
    "\n",
    "\n",
    "Things that aren't at the moment worthwhile:\n",
    "1. close using identical length loop and +/-2 res adjustment on each side with CCM at 0.4 RMS (total length match, potential SS mismatch)  \n",
    "This one has issues with the adjustments resulting in unexpected lengths of the finished design \n",
    "2. less constrained remodel with `BluePrintBDR`, allowing any secondary structure and any `ABEGO` (total length match, potential SS mismatch)  \n",
    "This one doesn't seem like it would get significantly more closures, for approximately 40% more compute\n",
    "3. Dmitri Zorine's brand new enumerative method\n",
    "Would like to try this at some point in the future though"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Make functions for looping and labeling to assist downstream penultimate design step"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyrosetta.distributed.packed_pose.core import PackedPose\n",
    "from pyrosetta.distributed import requires_init\n",
    "from typing import *\n",
    "\n",
    "\n",
    "@requires_init\n",
    "def loop_match(packed_pose_in: PackedPose, **kwargs) -> PackedPose:\n",
    "    \"\"\"\n",
    "    Match loop length, total length and DSSP with parent. Strictest method of closure.\n",
    "    \"\"\"\n",
    "    import bz2\n",
    "    import pyrosetta\n",
    "    import pyrosetta.distributed.io as io\n",
    "    from pyrosetta.distributed.tasks.rosetta_scripts import (\n",
    "        SingleoutputRosettaScriptsTask,\n",
    "    )\n",
    "\n",
    "    if packed_pose_in == None:\n",
    "        file = kwargs[\"-s\"]\n",
    "        with open(file, \"rb\") as f:\n",
    "            packed_pose_in = io.pose_from_pdbstring(bz2.decompress(f.read()).decode())\n",
    "        scores = pyrosetta.distributed.cluster.get_scores_dict(file)[\"scores\"]\n",
    "    else:\n",
    "        raise RuntimeError(\"Need to supply an input\")\n",
    "    # get parent from packed_pose_in, get loop length from parent length - packed_pose_in length\n",
    "    parent_length = int(scores[\"parent_length\"])\n",
    "    length = int(parent_length - len(packed_pose_in.pose.residues))\n",
    "    xml = \"\"\"\n",
    "    <ROSETTASCRIPTS>\n",
    "        <SCOREFXNS>\n",
    "            <ScoreFunction name=\"sfxn\" weights=\"beta_nov16\" /> \n",
    "        </SCOREFXNS>\n",
    "        <RESIDUE_SELECTORS>          \n",
    "        </RESIDUE_SELECTORS>\n",
    "        <TASKOPERATIONS>\n",
    "        </TASKOPERATIONS>\n",
    "        <SIMPLE_METRICS>\n",
    "        </SIMPLE_METRICS>\n",
    "        <MOVERS>\n",
    "            <ConnectChainsMover name=\"closer\" \n",
    "                chain_connections=\"[A+B]\" \n",
    "                loopLengthRange=\"{length},{length}\" \n",
    "                resAdjustmentRangeSide1=\"0,0\" \n",
    "                resAdjustmentRangeSide2=\"0,0\" \n",
    "                RMSthreshold=\"1.0\"/>\n",
    "            <SwitchChainOrder name=\"rechain\" chain_order=\"1\"/>\n",
    "        </MOVERS>\n",
    "        <FILTERS>\n",
    "        </FILTERS>\n",
    "        <PROTOCOLS>\n",
    "            <Add mover_name=\"closer\"/>\n",
    "            <Add mover_name=\"rechain\"/>\n",
    "        </PROTOCOLS>\n",
    "    </ROSETTASCRIPTS>\n",
    "    \"\"\".format(\n",
    "        length=length\n",
    "    )\n",
    "    closer = SingleoutputRosettaScriptsTask(xml)\n",
    "    try:\n",
    "        maybe_closed_ppose = closer(packed_pose_in.pose.clone())\n",
    "        maybe_closed_pose = io.to_pose(maybe_closed_ppose)\n",
    "        closure_type = \"loop_match\"\n",
    "    except RuntimeError:\n",
    "        maybe_closed_pose = io.to_pose(packed_pose_in.pose.clone())\n",
    "        closure_type = \"not_closed\"\n",
    "    pyrosetta.rosetta.core.pose.setPoseExtraScore(\n",
    "        maybe_closed_pose, \"closure_type\", closure_type\n",
    "    )\n",
    "    for key, value in scores.items():\n",
    "        pyrosetta.rosetta.core.pose.setPoseExtraScore(\n",
    "            maybe_closed_pose, key, str(value)\n",
    "        )\n",
    "    final_ppose = io.to_packed(maybe_closed_pose)\n",
    "    return final_ppose\n",
    "\n",
    "\n",
    "def strict_remodel(packed_pose_in: PackedPose, **kwargs) -> PackedPose:\n",
    "    \"\"\"\n",
    "    DSSP and SS agnostic in principle but in practice more or less matches.\n",
    "    \"\"\"\n",
    "    import os\n",
    "    import pyrosetta\n",
    "    import pyrosetta.distributed.io as io\n",
    "    from pyrosetta.distributed.packed_pose.core import PackedPose\n",
    "    from pyrosetta.distributed.tasks.rosetta_scripts import (\n",
    "        SingleoutputRosettaScriptsTask,\n",
    "    )\n",
    "\n",
    "    def strict_remodel_helper(packed_pose_in: PackedPose, loop_length: int) -> str:\n",
    "        import binascii, os\n",
    "        import pyrosetta\n",
    "        from pyrosetta.rosetta.core.pose import Pose\n",
    "\n",
    "        def phi_psi_omega_to_abego(phi: float, psi: float, omega: float) -> str:\n",
    "            \"\"\"\n",
    "            From Buwei\n",
    "            https://wiki.ipd.uw.edu/protocols/dry_lab/rosetta/scaffold_generation_with_piecewise_blueprint_builder\n",
    "            \"\"\"\n",
    "            if psi == None or phi == None:\n",
    "                return \"X\"\n",
    "            if omega == None:\n",
    "                omega = 180\n",
    "\n",
    "            if abs(omega) < 90:\n",
    "                return \"O\"\n",
    "            elif phi > 0:\n",
    "                if -100.0 <= psi < 100:\n",
    "                    return \"G\"\n",
    "                else:\n",
    "                    return \"E\"\n",
    "            else:\n",
    "                if -75.0 <= psi < 50:\n",
    "                    return \"A\"\n",
    "                else:\n",
    "                    return \"B\"\n",
    "            return \"X\"\n",
    "\n",
    "        def abego_string(phi_psi_omega: list) -> str:\n",
    "            \"\"\"\n",
    "            From Buwei\n",
    "            https://wiki.ipd.uw.edu/protocols/dry_lab/rosetta/scaffold_generation_with_piecewise_blueprint_builder\n",
    "            \"\"\"\n",
    "            out = \"\"\n",
    "            for x in phi_psi_omega:\n",
    "                out += phi_psi_omega_to_abego(x[0], x[1], x[2])\n",
    "            return out\n",
    "\n",
    "        def get_torsions(pose: Pose) -> list:\n",
    "            \"\"\"\n",
    "            From Buwei\n",
    "            https://wiki.ipd.uw.edu/protocols/dry_lab/rosetta/scaffold_generation_with_piecewise_blueprint_builder\n",
    "            \"\"\"\n",
    "            torsions = []\n",
    "            for i in range(1, pose.total_residue() + 1):\n",
    "                phi = pose.phi(i)\n",
    "                psi = pose.psi(i)\n",
    "                omega = pose.omega(i)\n",
    "                if i == 1:\n",
    "                    phi = None\n",
    "                if i == pose.total_residue():\n",
    "                    psi = None\n",
    "                    omega = None\n",
    "                torsions.append((phi, psi, omega))\n",
    "            return torsions\n",
    "\n",
    "        pose = packed_pose_in.pose.clone()\n",
    "        tors = get_torsions(pose)\n",
    "        abego_str = abego_string(tors)\n",
    "        dssp = pyrosetta.rosetta.protocols.simple_filters.dssp(pose)\n",
    "        # name blueprint a random 32 long hex string\n",
    "        filename = str(binascii.b2a_hex(os.urandom(16)).decode(\"utf-8\")) + \".bp\"\n",
    "        # write a temporary blueprint file\n",
    "        with open(filename, \"w+\") as f:\n",
    "            end1, begin2 = (\n",
    "                packed_pose_in.pose.chain_end(1),\n",
    "                packed_pose_in.pose.chain_begin(2),\n",
    "            )\n",
    "            end2 = packed_pose_in.pose.chain_end(2)\n",
    "            for i in range(1, end1 + 1):\n",
    "                if i == end1:\n",
    "                    print(\n",
    "                        str(i),\n",
    "                        packed_pose_in.pose.residue(i).name1(),\n",
    "                        dssp[i - 1] + \"X\",\n",
    "                        \"R\",\n",
    "                        file=f,\n",
    "                    )\n",
    "                else:\n",
    "                    print(\n",
    "                        str(i),\n",
    "                        packed_pose_in.pose.residue(i).name1(),\n",
    "                        dssp[i - 1] + abego_str[i - 1],\n",
    "                        \".\",\n",
    "                        file=f,\n",
    "                    )\n",
    "            for i in range(loop_length):\n",
    "                print(\n",
    "                    \"0\", \"V\", \"LX\", \"R\", file=f\n",
    "                )  # TODO DX is bad, causes rare error sometimes\n",
    "            for i in range(begin2, end2 + 1):\n",
    "                if i == begin2:\n",
    "                    print(\n",
    "                        str(i),\n",
    "                        packed_pose_in.pose.residue(i).name1(),\n",
    "                        dssp[i - 1] + \"X\",\n",
    "                        \"R\",\n",
    "                        file=f,\n",
    "                    )\n",
    "                else:\n",
    "                    print(\n",
    "                        str(i),\n",
    "                        packed_pose_in.pose.residue(i).name1(),\n",
    "                        dssp[i - 1] + abego_str[i - 1],\n",
    "                        \".\",\n",
    "                        file=f,\n",
    "                    )\n",
    "        return filename\n",
    "\n",
    "    # ensure pose still needs to be closed\n",
    "    if packed_pose_in.pose.num_chains() == 1:\n",
    "        final_ppose = io.to_packed(packed_pose_in.pose.clone())\n",
    "        return final_ppose\n",
    "    else:\n",
    "        scores = packed_pose_in.pose.scores\n",
    "        # get parent from packed_pose_in, get loop length from parent length - packed_pose_in length\n",
    "        parent_length = int(scores[\"parent_length\"])\n",
    "        length = int(parent_length - len(packed_pose_in.pose.residues))\n",
    "        bp = strict_remodel_helper(packed_pose_in, length)\n",
    "        xml = \"\"\"\n",
    "        <ROSETTASCRIPTS>\n",
    "            <SCOREFXNS>\n",
    "                <ScoreFunction name=\"sfxn1\" weights=\"fldsgn_cen\">\n",
    "                    <Reweight scoretype=\"hbond_sr_bb\" weight=\"1.0\" />\n",
    "                    <Reweight scoretype=\"hbond_lr_bb\" weight=\"1.0\" />\n",
    "                    <Reweight scoretype=\"atom_pair_constraint\" weight=\"1.0\" />\n",
    "                    <Reweight scoretype=\"angle_constraint\" weight=\"1.0\" />\n",
    "                    <Reweight scoretype=\"dihedral_constraint\" weight=\"1.0\" />\n",
    "                </ScoreFunction>\n",
    "            </SCOREFXNS>\n",
    "            <RESIDUE_SELECTORS>          \n",
    "            </RESIDUE_SELECTORS>\n",
    "            <TASKOPERATIONS>\n",
    "            </TASKOPERATIONS>\n",
    "            <SIMPLE_METRICS>\n",
    "            </SIMPLE_METRICS>\n",
    "            <MOVERS>\n",
    "                <BluePrintBDR name=\"bdr\" \n",
    "                blueprint=\"{bp}\" \n",
    "                use_abego_bias=\"0\" \n",
    "                use_sequence_bias=\"0\" \n",
    "                rmdl_attempts=\"20\"\n",
    "                scorefxn=\"sfxn1\"/>\n",
    "            </MOVERS>\n",
    "            <FILTERS>\n",
    "            </FILTERS>\n",
    "            <PROTOCOLS>\n",
    "                <Add mover_name=\"bdr\"/>\n",
    "            </PROTOCOLS>\n",
    "        </ROSETTASCRIPTS>\n",
    "        \"\"\".format(\n",
    "            bp=bp\n",
    "        )\n",
    "        strict_remodel = SingleoutputRosettaScriptsTask(xml)\n",
    "        maybe_closed_ppose = None\n",
    "        for i in range(10):\n",
    "            print(f\"attempt: {i}\")\n",
    "            if maybe_closed_ppose is not None:  # check if it worked\n",
    "                break  # stop retrying if it did\n",
    "            else:  # try again if it didn't. returns None if fail\n",
    "                maybe_closed_ppose = strict_remodel(packed_pose_in.pose.clone())\n",
    "        os.remove(bp)  # cleanup tree\n",
    "        if maybe_closed_ppose is not None:\n",
    "            closure_type = \"strict_remodel\"\n",
    "            maybe_closed_pose = io.to_pose(maybe_closed_ppose)\n",
    "            for key, value in scores.items():\n",
    "                pyrosetta.rosetta.core.pose.setPoseExtraScore(\n",
    "                    maybe_closed_pose, key, str(value)\n",
    "                )\n",
    "            # update closure_type\n",
    "            pyrosetta.rosetta.core.pose.setPoseExtraScore(\n",
    "                maybe_closed_pose, \"closure_type\", closure_type\n",
    "            )\n",
    "            final_ppose = io.to_packed(maybe_closed_pose)\n",
    "        else:  # return the original input if BlueprintBDR still didn't close\n",
    "            final_ppose = io.to_packed(packed_pose_in.pose.clone())\n",
    "        return final_ppose\n",
    "\n",
    "\n",
    "def label(packed_pose_in: PackedPose, **kwargs) -> PackedPose:\n",
    "    \"\"\"\n",
    "    Label poly valine\n",
    "    \"\"\"\n",
    "    import pyrosetta\n",
    "    import pyrosetta.distributed.io as io\n",
    "    from pyrosetta.distributed.tasks.rosetta_scripts import (\n",
    "        SingleoutputRosettaScriptsTask,\n",
    "    )\n",
    "    from pyrosetta.rosetta.core.pose import Pose\n",
    "    from pyrosetta.rosetta.core.select import get_residues_from_subset\n",
    "    from pyrosetta.rosetta.protocols.rosetta_scripts import XmlObjects\n",
    "\n",
    "    def phi_psi_omega_to_abego(phi: float, psi: float, omega: float) -> str:\n",
    "        \"\"\"\n",
    "        From Buwei\n",
    "        https://wiki.ipd.uw.edu/protocols/dry_lab/rosetta/scaffold_generation_with_piecewise_blueprint_builder\n",
    "        \"\"\"\n",
    "        if psi == None or phi == None:\n",
    "            return \"X\"\n",
    "        if omega == None:\n",
    "            omega = 180\n",
    "\n",
    "        if abs(omega) < 90:\n",
    "            return \"O\"\n",
    "        elif phi > 0:\n",
    "            if -100.0 <= psi < 100:\n",
    "                return \"G\"\n",
    "            else:\n",
    "                return \"E\"\n",
    "        else:\n",
    "            if -75.0 <= psi < 50:\n",
    "                return \"A\"\n",
    "            else:\n",
    "                return \"B\"\n",
    "        return \"X\"\n",
    "\n",
    "    def abego_string(phi_psi_omega: list) -> str:\n",
    "        \"\"\"\n",
    "        From Buwei\n",
    "        https://wiki.ipd.uw.edu/protocols/dry_lab/rosetta/scaffold_generation_with_piecewise_blueprint_builder\n",
    "        \"\"\"\n",
    "        out = \"\"\n",
    "        for x in phi_psi_omega:\n",
    "            out += phi_psi_omega_to_abego(x[0], x[1], x[2])\n",
    "        return out\n",
    "\n",
    "    def get_torsions(pose: Pose) -> list:\n",
    "        \"\"\"\n",
    "        From Buwei\n",
    "        https://wiki.ipd.uw.edu/protocols/dry_lab/rosetta/scaffold_generation_with_piecewise_blueprint_builder\n",
    "        \"\"\"\n",
    "        torsions = []\n",
    "        for i in range(1, pose.total_residue() + 1):\n",
    "            phi = pose.phi(i)\n",
    "            psi = pose.psi(i)\n",
    "            omega = pose.omega(i)\n",
    "            if i == 1:\n",
    "                phi = None\n",
    "            if i == pose.total_residue():\n",
    "                psi = None\n",
    "                omega = None\n",
    "            torsions.append((phi, psi, omega))\n",
    "        return torsions\n",
    "\n",
    "    def find_vv(seq):\n",
    "        indices = []\n",
    "        seq_minus_one = seq[:-1]\n",
    "        for i, char in enumerate(seq_minus_one):\n",
    "            if (char == seq[i + 1]) and (char == \"V\"):\n",
    "                indices.append(i + 1)\n",
    "            else:\n",
    "                pass\n",
    "        # rosetta sequence indexes begin at 1\n",
    "        true_indices = [str(x + 1) for x in indices]\n",
    "        return true_indices\n",
    "\n",
    "    scores = packed_pose_in.pose.scores\n",
    "    if (\n",
    "        packed_pose_in.pose.num_chains() != 1\n",
    "    ):  # ensure pose has been closed, if not don't label\n",
    "        new_loop_str = \"0,0\"\n",
    "        labeled_pose = packed_pose_in.pose.clone()\n",
    "    else:\n",
    "        seq = str(packed_pose_in.pose.sequence())\n",
    "        vv_indices = \",\".join(find_vv(seq))\n",
    "        pivot_helix = int(scores[\"pivot_helix\"])\n",
    "        pre_break_helix = int(scores[\"pre_break_helix\"])\n",
    "        # get helix indices for the pre and post break helices\n",
    "        lower = pre_break_helix\n",
    "        upper = pre_break_helix + 1\n",
    "        xml = \"\"\"\n",
    "        <ROSETTASCRIPTS>\n",
    "            <SCOREFXNS>\n",
    "                <ScoreFunction name=\"sfxn\" weights=\"beta_nov16\" /> \n",
    "            </SCOREFXNS>\n",
    "            <RESIDUE_SELECTORS>\n",
    "                <SSElement name=\"middle\" selection=\"{lower},H,E\" to_selection=\"{upper},H,S\" chain=\"A\" reassign_short_terminal_loop=\"2\" />\n",
    "                <Index name=\"polyval_all\" resnums=\"{vv_indices}\" />\n",
    "                <And name=\"polyval\" selectors=\"middle,polyval_all\" />\n",
    "                <PrimarySequenceNeighborhood name=\"entire_val\" selector=\"polyval\" lower=\"5\" upper=\"5\" />\n",
    "                <SecondaryStructure name=\"loop\" overlap=\"0\" minH=\"3\" minE=\"2\" include_terminal_loops=\"true\" use_dssp=\"true\" ss=\"L\"/>\n",
    "                <And name=\"new_loop_center\" selectors=\"entire_val,loop\" />\n",
    "                <PrimarySequenceNeighborhood name=\"entire_new_loop_broad\" selector=\"new_loop_center\" lower=\"5\" upper=\"5\" />\n",
    "                <ResidueName name=\"isval\" residue_name3=\"VAL\" />\n",
    "                <And name=\"entire_new_loop\" selectors=\"entire_new_loop_broad,isval\" />\n",
    "            </RESIDUE_SELECTORS>\n",
    "            <TASKOPERATIONS>\n",
    "            </TASKOPERATIONS>\n",
    "            <SIMPLE_METRICS>\n",
    "            </SIMPLE_METRICS>\n",
    "            <MOVERS>\n",
    "                <AddResidueLabel name=\"add_loop_label\" residue_selector=\"entire_new_loop\" label=\"new_loop\" />  \n",
    "            </MOVERS>\n",
    "            <FILTERS>\n",
    "            </FILTERS>\n",
    "            <PROTOCOLS>\n",
    "                <Add mover=\"add_loop_label\" />\n",
    "            </PROTOCOLS>\n",
    "        </ROSETTASCRIPTS>\n",
    "        \"\"\".format(\n",
    "            lower=lower, upper=upper, vv_indices=vv_indices\n",
    "        )\n",
    "        labeled = SingleoutputRosettaScriptsTask(xml)\n",
    "        xml_obj = XmlObjects.create_from_string(xml)\n",
    "        entire_new_loop_sel = xml_obj.get_residue_selector(\"entire_new_loop\")\n",
    "        labeled_ppose = labeled(packed_pose_in.pose.clone())\n",
    "        labeled_pose = io.to_pose(labeled_ppose)\n",
    "        new_loop_resis = list(\n",
    "            get_residues_from_subset(entire_new_loop_sel.apply(labeled_pose))\n",
    "        )\n",
    "        new_loop_str = \",\".join(str(resi) for resi in new_loop_resis)\n",
    "    pyrosetta.rosetta.core.pose.setPoseExtraScore(\n",
    "        labeled_pose, \"new_loop_resis\", new_loop_str\n",
    "    )\n",
    "    total_length = len(labeled_pose.residues)\n",
    "    pyrosetta.rosetta.core.pose.setPoseExtraScore(\n",
    "        labeled_pose, \"total_length\", total_length\n",
    "    )\n",
    "    dssp = pyrosetta.rosetta.protocols.simple_filters.dssp(labeled_pose)\n",
    "    pyrosetta.rosetta.core.pose.setPoseExtraScore(labeled_pose, \"dssp\", dssp)\n",
    "    tors = get_torsions(labeled_pose)\n",
    "    abego_str = abego_string(tors)\n",
    "    pyrosetta.rosetta.core.pose.setPoseExtraScore(labeled_pose, \"abego_str\", abego_str)\n",
    "    for key, value in scores.items():\n",
    "        pyrosetta.rosetta.core.pose.setPoseExtraScore(labeled_pose, key, str(value))\n",
    "    final_ppose = io.to_packed(labeled_pose)\n",
    "    return final_ppose"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Setup dask, set command line options, make tasks and submit to client\n",
    "At some point I should try using `client.wait_for_workers(n_workers=1, timeout=None)`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "run the following from your local terminal:\n",
      "ssh -L 8000:localhost:8787 pleung@dig112\n",
      "#!/usr/bin/env bash\n",
      "\n",
      "#SBATCH -J dask-worker\n",
      "#SBATCH -e /mnt/home/pleung/logs/slurm_logs/dask-worker-%J.err\n",
      "#SBATCH -o /mnt/home/pleung/logs/slurm_logs/dask-worker-%J.out\n",
      "#SBATCH -p medium\n",
      "#SBATCH -n 1\n",
      "#SBATCH --cpus-per-task=1\n",
      "#SBATCH --mem=6G\n",
      "#SBATCH -t 23:30:00\n",
      "\n",
      "JOB_ID=${SLURM_JOB_ID%;*}\n",
      "\n",
      "/home/pleung/.conda/envs/phil/bin/python -m distributed.cli.dask_worker tcp://172.16.131.216:34281 --nthreads 1 --memory-limit 5.59GiB --name name --nanny --death-timeout 120 --local-directory $TMPDIR/dask --lifetime 23h --lifetime-stagger 4m\n",
      "\n",
      "<Client: 'tcp://172.16.131.216:34281' processes=0 threads=0, memory=0 B>\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:pyrosetta.distributed:maybe_init performing pyrosetta initialization: {'options': '-run:constant_seed 1 -multithreading:total_threads 1', 'extra_options': '-mute all', 'set_logging_handler': 'interactive', 'silent': True}\n",
      "INFO:pyrosetta.rosetta:Found rosetta database at: /home/pleung/.conda/envs/phil/lib/python3.8/site-packages/pyrosetta/database; using it....\n",
      "INFO:pyrosetta.rosetta:PyRosetta-4 2021 [Rosetta PyRosetta4.conda.linux.cxx11thread.serialization.CentOS.python38.Release 2021.12+release.ed6a5560506cfd327d4a6a3e2c9b0c9f6f4a6535 2021-03-26T16:09:25] retrieved from: http://www.pyrosetta.org\n",
      "(C) Copyright Rosetta Commons Member Institutions. Created in JHU by Sergey Lyskov and PyRosetta Team.\n"
     ]
    }
   ],
   "source": [
    "from dask.distributed import Client\n",
    "from dask_jobqueue import SLURMCluster\n",
    "import logging\n",
    "import pwd\n",
    "from pyrosetta.distributed.cluster.core import PyRosettaCluster\n",
    "\n",
    "\n",
    "print(\"run the following from your local terminal:\")\n",
    "print(\n",
    "    f\"ssh -L 8000:localhost:8787 {pwd.getpwuid(os.getuid()).pw_name}@{socket.gethostname()}\"\n",
    ")\n",
    "\n",
    "\n",
    "def create_tasks(selected, options):\n",
    "    with open(selected, \"r\") as f:\n",
    "        for file in f:\n",
    "            tasks = {\"options\": \"-corrections::beta_nov16 true\"}\n",
    "            tasks[\"extra_options\"] = options\n",
    "            tasks[\"-s\"] = file.rstrip()\n",
    "            tasks[\"sfxn\"] = \"beta_nov16\"\n",
    "            yield tasks\n",
    "\n",
    "\n",
    "logging.basicConfig(level=logging.INFO)\n",
    "selected = os.path.join(os.getcwd(), \"02_design_score/not_bad.list\")\n",
    "\n",
    "options = {\n",
    "    \"-out:level\": \"300\",\n",
    "    \"-holes:dalphaball\": \"/home/bcov/ppi/tutorial_build/main/source/external/DAlpahBall/DAlphaBall.gcc\",\n",
    "    \"-indexed_structure_store:fragment_store\": \"/net/databases/VALL_clustered/connect_chains/ss_grouped_vall_helix_shortLoop.h5\",\n",
    "}\n",
    "\n",
    "output_path = os.path.join(os.getcwd(), \"03_enumerate_loops\")\n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    # configure SLURM cluster as a context manager\n",
    "    with SLURMCluster(\n",
    "        cores=1,\n",
    "        processes=1,\n",
    "        job_cpu=1,\n",
    "        memory=\"6GB\",\n",
    "        queue=\"medium\",\n",
    "        walltime=\"23:30:00\",\n",
    "        death_timeout=120,\n",
    "        local_directory=\"$TMPDIR/dask\",\n",
    "        log_directory=\"/mnt/home/pleung/logs/slurm_logs\",\n",
    "        extra=[\"--lifetime\", \"23h\", \"--lifetime-stagger\", \"4m\"],\n",
    "    ) as cluster:\n",
    "        print(cluster.job_script())\n",
    "        # scale between 1-1020 workers,\n",
    "        cluster.adapt(\n",
    "            minimum=1,\n",
    "            maximum=1020,\n",
    "            wait_count=999,  # Number of consecutive times that a worker should be suggested for removal it is removed\n",
    "            interval=\"5s\",  # Time between checks\n",
    "        )\n",
    "        # setup a client to interact with the cluster as a context manager\n",
    "        with Client(cluster) as client:\n",
    "            print(client)\n",
    "            PyRosettaCluster(\n",
    "                tasks=create_tasks(selected, options),\n",
    "                client=client,\n",
    "                scratch_dir=output_path,\n",
    "                output_path=output_path,\n",
    "            ).distribute(protocols=[loop_match, strict_remodel, label])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Look at scores\n",
    "Hacky function to load JSON-like data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>abego_str</th>\n",
       "      <th>bb_clash</th>\n",
       "      <th>closure_type</th>\n",
       "      <th>dssp</th>\n",
       "      <th>interface_buried_sasa</th>\n",
       "      <th>new_loop_resis</th>\n",
       "      <th>parent</th>\n",
       "      <th>parent_length</th>\n",
       "      <th>pivot_helix</th>\n",
       "      <th>pre_break_helix</th>\n",
       "      <th>...</th>\n",
       "      <th>lk_ball</th>\n",
       "      <th>lk_ball_bridge</th>\n",
       "      <th>lk_ball_bridge_uncpl</th>\n",
       "      <th>lk_ball_iso</th>\n",
       "      <th>omega</th>\n",
       "      <th>p_aa_pp</th>\n",
       "      <th>pro_close</th>\n",
       "      <th>rama_prepro</th>\n",
       "      <th>ref</th>\n",
       "      <th>total_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>/mnt/home/pleung/projects/bistable_bundle/r4/hinges/03_enumerate_loops/decoys/0000/2021.05.02.23.34.18.110963_2a6f8cf3bae94e6f94534bc14d0bed0a.pdb.bz2</th>\n",
       "      <td>XAAAAAAAAAAAAAAAAAAAAAAGBBAAAAAAAAAAAAAAAAAAAA...</td>\n",
       "      <td>89.63912963867188</td>\n",
       "      <td>strict_remodel</td>\n",
       "      <td>LHHHHHHHHHHHHHHHHHHHHHHLLLHHHHHHHHHHHHHHHHHHHH...</td>\n",
       "      <td>1652.7481689453125</td>\n",
       "      <td>149,150,151,152</td>\n",
       "      <td>THR11</td>\n",
       "      <td>304</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>/mnt/home/pleung/projects/bistable_bundle/r4/hinges/03_enumerate_loops/decoys/0000/2021.05.02.23.34.18.110963_d0ebbad7002c46bfad8ebf47a42f771c.pdb.bz2</th>\n",
       "      <td>XAAAAAAAAAAAAAAAAAAGBAAAAAAAAAAAAAAAAAAGBBAAAA...</td>\n",
       "      <td>45.20452117919922</td>\n",
       "      <td>loop_match</td>\n",
       "      <td>LHHHHHHHHHHHHHHHHHHLLHHHHHHHHHHHHHHHHHHLLLHHHH...</td>\n",
       "      <td>1786.3101806640625</td>\n",
       "      <td>77,82,83,84</td>\n",
       "      <td>DHR07_nocys</td>\n",
       "      <td>168</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>487.224482</td>\n",
       "      <td>2.694334</td>\n",
       "      <td>17.186658</td>\n",
       "      <td>1190.581348</td>\n",
       "      <td>31.794270</td>\n",
       "      <td>-41.255857</td>\n",
       "      <td>1.113450</td>\n",
       "      <td>25.102051</td>\n",
       "      <td>1.162654</td>\n",
       "      <td>1612.047722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>/mnt/home/pleung/projects/bistable_bundle/r4/hinges/03_enumerate_loops/decoys/0000/2021.05.02.23.34.18.110963_5e3e1aee9f0341778f4a489b7afccd74.pdb.bz2</th>\n",
       "      <td>XAAAAAAAAAAAAAAAAAAAABBAAAAAAAAAAAAAAAAAAAAAAA...</td>\n",
       "      <td>51.77362823486328</td>\n",
       "      <td>loop_match</td>\n",
       "      <td>LHHHHHHHHHHHHHHHHHHHHLLHHHHHHHHHHHHHHHHHHHHHHH...</td>\n",
       "      <td>1681.164794921875</td>\n",
       "      <td>95,99,100,101,102,107</td>\n",
       "      <td>TH_DHR_DN-T6</td>\n",
       "      <td>201</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>551.189029</td>\n",
       "      <td>3.687640</td>\n",
       "      <td>27.051500</td>\n",
       "      <td>1368.291098</td>\n",
       "      <td>145.454600</td>\n",
       "      <td>-65.343508</td>\n",
       "      <td>0.237962</td>\n",
       "      <td>61.566349</td>\n",
       "      <td>0.997786</td>\n",
       "      <td>2658.428334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>/mnt/home/pleung/projects/bistable_bundle/r4/hinges/03_enumerate_loops/decoys/0000/2021.05.02.23.34.18.110963_3f4aa29204234889a6dc9b925287d80b.pdb.bz2</th>\n",
       "      <td>XAAAAAAAAAAAAAAABBGBAAAAAAAAAAAAAAABABAAAAAAAA...</td>\n",
       "      <td>36.63492965698242</td>\n",
       "      <td>strict_remodel</td>\n",
       "      <td>LHHHHHHHHHHHHHHHLLLLHHHHHHHHHHHHHHHLLLHHHHHHHH...</td>\n",
       "      <td>1892.1275634765625</td>\n",
       "      <td>72,74,75,76</td>\n",
       "      <td>DHR21</td>\n",
       "      <td>152</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>XAAAAAAAAAAAAAAAAABBGBAAAAAAAAAAAAAAAAAABBGBAA...</td>\n",
       "      <td>48.391422271728516</td>\n",
       "      <td>loop_match</td>\n",
       "      <td>LHHHHHHHHHHHHHHHHHLLLLHHHHHHHHHHHHHHHHHHLLLLHH...</td>\n",
       "      <td>1861.9246826171875</td>\n",
       "      <td>82,83,85,86,87,88,92</td>\n",
       "      <td>DHR01_nocys</td>\n",
       "      <td>176</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>472.847875</td>\n",
       "      <td>2.807448</td>\n",
       "      <td>17.883739</td>\n",
       "      <td>1161.380661</td>\n",
       "      <td>24.320869</td>\n",
       "      <td>-62.193773</td>\n",
       "      <td>0.328207</td>\n",
       "      <td>94.480159</td>\n",
       "      <td>14.406524</td>\n",
       "      <td>2156.150235</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 45 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                            abego_str  \\\n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  XAAAAAAAAAAAAAAAAAAAAAAGBBAAAAAAAAAAAAAAAAAAAA...   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  XAAAAAAAAAAAAAAAAAAGBAAAAAAAAAAAAAAAAAAGBBAAAA...   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  XAAAAAAAAAAAAAAAAAAAABBAAAAAAAAAAAAAAAAAAAAAAA...   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  XAAAAAAAAAAAAAAABBGBAAAAAAAAAAAAAAABABAAAAAAAA...   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  XAAAAAAAAAAAAAAAAABBGBAAAAAAAAAAAAAAAAAABBGBAA...   \n",
       "\n",
       "                                                              bb_clash  \\\n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...   89.63912963867188   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...   45.20452117919922   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...   51.77362823486328   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...   36.63492965698242   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  48.391422271728516   \n",
       "\n",
       "                                                      closure_type  \\\n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  strict_remodel   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...      loop_match   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...      loop_match   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  strict_remodel   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...      loop_match   \n",
       "\n",
       "                                                                                                 dssp  \\\n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  LHHHHHHHHHHHHHHHHHHHHHHLLLHHHHHHHHHHHHHHHHHHHH...   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  LHHHHHHHHHHHHHHHHHHLLHHHHHHHHHHHHHHHHHHLLLHHHH...   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  LHHHHHHHHHHHHHHHHHHHHLLHHHHHHHHHHHHHHHHHHHHHHH...   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  LHHHHHHHHHHHHHHHLLLLHHHHHHHHHHHHHHHLLLHHHHHHHH...   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  LHHHHHHHHHHHHHHHHHLLLLHHHHHHHHHHHHHHHHHHLLLLHH...   \n",
       "\n",
       "                                                   interface_buried_sasa  \\\n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...    1652.7481689453125   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...    1786.3101806640625   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...     1681.164794921875   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...    1892.1275634765625   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...    1861.9246826171875   \n",
       "\n",
       "                                                           new_loop_resis  \\\n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...        149,150,151,152   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...            77,82,83,84   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  95,99,100,101,102,107   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...            72,74,75,76   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...   82,83,85,86,87,88,92   \n",
       "\n",
       "                                                          parent  \\\n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...         THR11   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...   DHR07_nocys   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  TH_DHR_DN-T6   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...         DHR21   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...   DHR01_nocys   \n",
       "\n",
       "                                                   parent_length pivot_helix  \\\n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...           304           6   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...           168           5   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...           201           5   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...           152           4   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...           176           4   \n",
       "\n",
       "                                                   pre_break_helix  ...  \\\n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...               6  ...   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...               4  ...   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...               4  ...   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...               4  ...   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...               4  ...   \n",
       "\n",
       "                                                       lk_ball lk_ball_bridge  \\\n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...         NaN            NaN   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  487.224482       2.694334   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  551.189029       3.687640   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...         NaN            NaN   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  472.847875       2.807448   \n",
       "\n",
       "                                                   lk_ball_bridge_uncpl  \\\n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...                  NaN   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...            17.186658   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...            27.051500   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...                  NaN   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...            17.883739   \n",
       "\n",
       "                                                    lk_ball_iso       omega  \\\n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...          NaN         NaN   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  1190.581348   31.794270   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  1368.291098  145.454600   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...          NaN         NaN   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  1161.380661   24.320869   \n",
       "\n",
       "                                                      p_aa_pp pro_close  \\\n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...        NaN       NaN   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi... -41.255857  1.113450   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi... -65.343508  0.237962   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...        NaN       NaN   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi... -62.193773  0.328207   \n",
       "\n",
       "                                                    rama_prepro        ref  \\\n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...          NaN        NaN   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...    25.102051   1.162654   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...    61.566349   0.997786   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...          NaN        NaN   \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...    94.480159  14.406524   \n",
       "\n",
       "                                                    total_score  \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...          NaN  \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  1612.047722  \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  2658.428334  \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...          NaN  \n",
       "/mnt/home/pleung/projects/bistable_bundle/r4/hi...  2156.150235  \n",
       "\n",
       "[5 rows x 45 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def read_scorefile(scores):\n",
    "    import pandas as pd\n",
    "\n",
    "    scores = pd.read_json(scores, orient=\"records\", typ=\"frame\", lines=True)\n",
    "    scores = scores.T\n",
    "    mat = scores.values\n",
    "    n = mat.shape[0]\n",
    "    dicts = list(mat[range(n), range(n)])\n",
    "    index = scores.index\n",
    "    tabulated_scores = pd.DataFrame(dicts, index=index)\n",
    "    return tabulated_scores\n",
    "\n",
    "\n",
    "output_path = os.path.join(os.getcwd(), \"03_enumerate_loops\")\n",
    "scores = os.path.join(output_path, \"scores.json\")\n",
    "scores_df = read_scorefile(scores)\n",
    "scores_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3734"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(scores_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(\n",
    "    context=\"talk\",\n",
    "    font_scale=1,  # make the font larger; default is pretty small\n",
    "    style=\"ticks\",  # make the background white with black lines\n",
    "    palette=\"colorblind\",  # a color palette that is colorblind friendly!\n",
    ")\n",
    "(\n",
    "    fig,\n",
    "    ax1,\n",
    ") = plt.subplots(ncols=1, figsize=(20, 10), tight_layout=True)\n",
    "scores_df.groupby(\"closure_type\").size().plot(kind=\"pie\", autopct=\"%1.2f%%\", ax=ax1)\n",
    "ax1.set_ylabel(\"Shifts\", rotation=0)\n",
    "plt.savefig(\"figs/03_closure_types.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What metadata predicts looping failures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['abego_str', 'bb_clash', 'closure_type', 'dssp',\n",
       "       'interface_buried_sasa', 'new_loop_resis', 'parent', 'parent_length',\n",
       "       'pivot_helix', 'pre_break_helix', 'sc', 'sc_int', 'score_A', 'score_B',\n",
       "       'score_per_res', 'sfxn_used', 'shift', 'total_length', 'dslf_fa13',\n",
       "       'fa_atr', 'fa_dun_dev', 'fa_dun_rot', 'fa_dun_semi', 'fa_elec',\n",
       "       'fa_intra_atr_xover4', 'fa_intra_elec', 'fa_intra_rep_xover4',\n",
       "       'fa_intra_sol_xover4', 'fa_rep', 'fa_sol', 'hbond_bb_sc', 'hbond_lr_bb',\n",
       "       'hbond_sc', 'hbond_sr_bb', 'hxl_tors', 'lk_ball', 'lk_ball_bridge',\n",
       "       'lk_ball_bridge_uncpl', 'lk_ball_iso', 'omega', 'p_aa_pp', 'pro_close',\n",
       "       'rama_prepro', 'ref', 'total_score'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scores_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_length</th>\n",
       "      <th>dslf_fa13</th>\n",
       "      <th>fa_atr</th>\n",
       "      <th>fa_dun_dev</th>\n",
       "      <th>fa_dun_rot</th>\n",
       "      <th>fa_dun_semi</th>\n",
       "      <th>fa_elec</th>\n",
       "      <th>fa_intra_atr_xover4</th>\n",
       "      <th>fa_intra_elec</th>\n",
       "      <th>fa_intra_rep_xover4</th>\n",
       "      <th>...</th>\n",
       "      <th>lk_ball</th>\n",
       "      <th>lk_ball_bridge</th>\n",
       "      <th>lk_ball_bridge_uncpl</th>\n",
       "      <th>lk_ball_iso</th>\n",
       "      <th>omega</th>\n",
       "      <th>p_aa_pp</th>\n",
       "      <th>pro_close</th>\n",
       "      <th>rama_prepro</th>\n",
       "      <th>ref</th>\n",
       "      <th>total_score</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>scaffold</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DHR</th>\n",
       "      <td>192.107368</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1229.111229</td>\n",
       "      <td>177.448589</td>\n",
       "      <td>168.422827</td>\n",
       "      <td>223.621586</td>\n",
       "      <td>-424.116100</td>\n",
       "      <td>-70.683324</td>\n",
       "      <td>-40.357464</td>\n",
       "      <td>122.279757</td>\n",
       "      <td>...</td>\n",
       "      <td>594.193020</td>\n",
       "      <td>2.621822</td>\n",
       "      <td>19.540182</td>\n",
       "      <td>1409.177374</td>\n",
       "      <td>63.811452</td>\n",
       "      <td>-64.174055</td>\n",
       "      <td>12.291054</td>\n",
       "      <td>33.088984</td>\n",
       "      <td>-51.431891</td>\n",
       "      <td>1771.884309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KH_DHR</th>\n",
       "      <td>191.260870</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1148.613853</td>\n",
       "      <td>225.297816</td>\n",
       "      <td>148.136980</td>\n",
       "      <td>248.448087</td>\n",
       "      <td>-390.512081</td>\n",
       "      <td>-70.692433</td>\n",
       "      <td>-44.593227</td>\n",
       "      <td>126.351693</td>\n",
       "      <td>...</td>\n",
       "      <td>530.265254</td>\n",
       "      <td>3.845753</td>\n",
       "      <td>27.209187</td>\n",
       "      <td>1315.211464</td>\n",
       "      <td>53.825114</td>\n",
       "      <td>-66.060869</td>\n",
       "      <td>0.391800</td>\n",
       "      <td>31.489193</td>\n",
       "      <td>-36.248622</td>\n",
       "      <td>1900.603329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>THR</th>\n",
       "      <td>341.936118</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-2158.082577</td>\n",
       "      <td>221.692917</td>\n",
       "      <td>283.279515</td>\n",
       "      <td>385.526317</td>\n",
       "      <td>-702.590788</td>\n",
       "      <td>-131.512865</td>\n",
       "      <td>-64.460651</td>\n",
       "      <td>207.302953</td>\n",
       "      <td>...</td>\n",
       "      <td>969.094200</td>\n",
       "      <td>7.228680</td>\n",
       "      <td>53.244981</td>\n",
       "      <td>2358.454761</td>\n",
       "      <td>75.718635</td>\n",
       "      <td>-104.485100</td>\n",
       "      <td>6.398993</td>\n",
       "      <td>101.998793</td>\n",
       "      <td>-78.876142</td>\n",
       "      <td>1607.909376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TH_DHR</th>\n",
       "      <td>229.026398</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1412.243615</td>\n",
       "      <td>189.323544</td>\n",
       "      <td>188.267918</td>\n",
       "      <td>246.614814</td>\n",
       "      <td>-479.669421</td>\n",
       "      <td>-81.033266</td>\n",
       "      <td>-54.808005</td>\n",
       "      <td>149.556717</td>\n",
       "      <td>...</td>\n",
       "      <td>664.210963</td>\n",
       "      <td>4.195498</td>\n",
       "      <td>30.233476</td>\n",
       "      <td>1594.385046</td>\n",
       "      <td>56.865494</td>\n",
       "      <td>-75.185398</td>\n",
       "      <td>13.800293</td>\n",
       "      <td>16.936263</td>\n",
       "      <td>2.771556</td>\n",
       "      <td>1697.387659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hDHR</th>\n",
       "      <td>190.142429</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1166.250881</td>\n",
       "      <td>177.424997</td>\n",
       "      <td>161.068645</td>\n",
       "      <td>216.085621</td>\n",
       "      <td>-395.139214</td>\n",
       "      <td>-69.582459</td>\n",
       "      <td>-46.214676</td>\n",
       "      <td>122.578395</td>\n",
       "      <td>...</td>\n",
       "      <td>553.093407</td>\n",
       "      <td>3.349324</td>\n",
       "      <td>24.919549</td>\n",
       "      <td>1335.549993</td>\n",
       "      <td>54.191555</td>\n",
       "      <td>-59.450994</td>\n",
       "      <td>13.532275</td>\n",
       "      <td>30.651892</td>\n",
       "      <td>-49.939915</td>\n",
       "      <td>1692.199760</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          total_length  dslf_fa13       fa_atr  fa_dun_dev  fa_dun_rot  \\\n",
       "scaffold                                                                 \n",
       "DHR         192.107368        0.0 -1229.111229  177.448589  168.422827   \n",
       "KH_DHR      191.260870        0.0 -1148.613853  225.297816  148.136980   \n",
       "THR         341.936118        0.0 -2158.082577  221.692917  283.279515   \n",
       "TH_DHR      229.026398        0.0 -1412.243615  189.323544  188.267918   \n",
       "hDHR        190.142429        0.0 -1166.250881  177.424997  161.068645   \n",
       "\n",
       "          fa_dun_semi     fa_elec  fa_intra_atr_xover4  fa_intra_elec  \\\n",
       "scaffold                                                                \n",
       "DHR        223.621586 -424.116100           -70.683324     -40.357464   \n",
       "KH_DHR     248.448087 -390.512081           -70.692433     -44.593227   \n",
       "THR        385.526317 -702.590788          -131.512865     -64.460651   \n",
       "TH_DHR     246.614814 -479.669421           -81.033266     -54.808005   \n",
       "hDHR       216.085621 -395.139214           -69.582459     -46.214676   \n",
       "\n",
       "          fa_intra_rep_xover4  ...     lk_ball  lk_ball_bridge  \\\n",
       "scaffold                       ...                               \n",
       "DHR                122.279757  ...  594.193020        2.621822   \n",
       "KH_DHR             126.351693  ...  530.265254        3.845753   \n",
       "THR                207.302953  ...  969.094200        7.228680   \n",
       "TH_DHR             149.556717  ...  664.210963        4.195498   \n",
       "hDHR               122.578395  ...  553.093407        3.349324   \n",
       "\n",
       "          lk_ball_bridge_uncpl  lk_ball_iso      omega     p_aa_pp  pro_close  \\\n",
       "scaffold                                                                        \n",
       "DHR                  19.540182  1409.177374  63.811452  -64.174055  12.291054   \n",
       "KH_DHR               27.209187  1315.211464  53.825114  -66.060869   0.391800   \n",
       "THR                  53.244981  2358.454761  75.718635 -104.485100   6.398993   \n",
       "TH_DHR               30.233476  1594.385046  56.865494  -75.185398  13.800293   \n",
       "hDHR                 24.919549  1335.549993  54.191555  -59.450994  13.532275   \n",
       "\n",
       "          rama_prepro        ref  total_score  \n",
       "scaffold                                       \n",
       "DHR         33.088984 -51.431891  1771.884309  \n",
       "KH_DHR      31.489193 -36.248622  1900.603329  \n",
       "THR        101.998793 -78.876142  1607.909376  \n",
       "TH_DHR      16.936263   2.771556  1697.387659  \n",
       "hDHR        30.651892 -49.939915  1692.199760  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def parent2scaffold(row):\n",
    "    parent = row[\"parent\"]\n",
    "    if \"THR\" in parent:\n",
    "        scaffold = \"THR\"\n",
    "    elif \"TH_DHR\" in parent:\n",
    "        scaffold = \"TH_DHR\"\n",
    "    elif \"KH_\" in parent:\n",
    "        scaffold = \"KH_DHR\"\n",
    "    elif \"hDHR\" in parent:\n",
    "        scaffold = \"hDHR\"\n",
    "    elif \"DHR\" in parent:\n",
    "        scaffold = \"DHR\"\n",
    "    else:\n",
    "        raise RuntimeError\n",
    "    return scaffold\n",
    "\n",
    "\n",
    "scores_df[\"scaffold\"] = scores_df.apply(parent2scaffold, axis=1)\n",
    "scores_df.groupby([\"scaffold\"]).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 2160x2160 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ((ax1, ax2), (ax3, ax4), (ax5, ax6)) = plt.subplots(\n",
    "    ncols=2, nrows=3, figsize=(30, 30), tight_layout=True\n",
    ")\n",
    "scores_df[scores_df[\"scaffold\"] == \"THR\"].groupby(\"closure_type\").size().plot(\n",
    "    kind=\"pie\", autopct=\"%1.2f%%\", ax=ax1\n",
    ")\n",
    "scores_df[scores_df[\"scaffold\"] == \"TH_DHR\"].groupby(\"closure_type\").size().plot(\n",
    "    kind=\"pie\", autopct=\"%1.2f%%\", ax=ax2\n",
    ")\n",
    "scores_df[scores_df[\"scaffold\"] == \"DHR\"].groupby(\"closure_type\").size().plot(\n",
    "    kind=\"pie\", autopct=\"%1.2f%%\", ax=ax3\n",
    ")\n",
    "scores_df[scores_df[\"scaffold\"] == \"hDHR\"].groupby(\"closure_type\").size().plot(\n",
    "    kind=\"pie\", autopct=\"%1.2f%%\", ax=ax4\n",
    ")\n",
    "scores_df[scores_df[\"scaffold\"] == \"KH_DHR\"].groupby(\"closure_type\").size().plot(\n",
    "    kind=\"pie\", autopct=\"%1.2f%%\", ax=ax5\n",
    ")\n",
    "scores_df.groupby(\"closure_type\").size().plot(kind=\"pie\", autopct=\"%1.2f%%\", ax=ax6)\n",
    "ax1.set_ylabel(\"THRs\", rotation=0)\n",
    "ax2.set_ylabel(\"TH_DHRs\", rotation=0)\n",
    "ax3.set_ylabel(\"DHRs\", rotation=0)\n",
    "ax4.set_ylabel(\"hDHRs\", rotation=0)\n",
    "ax5.set_ylabel(\"KH_DHRs\", rotation=0)\n",
    "ax6.set_ylabel(\"All\", rotation=0)\n",
    "plt.savefig(\"figs/03_looping_counts_by_scaffold.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2160x1080 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hue_order = [\"loop_match\", \"not_closed\", \"strict_remodel\"]  # for consistency with above\n",
    "\n",
    "fig, (ax1, ax2) = plt.subplots(ncols=2, figsize=(30, 15), tight_layout=True)\n",
    "\n",
    "temp_df = scores_df.copy()\n",
    "temp_df[\"shift\"] = temp_df[\"shift\"].astype(int)\n",
    "\n",
    "sns.histplot(\n",
    "    x=\"shift\",\n",
    "    data=temp_df.sort_values([\"shift\"]),\n",
    "    ax=ax1,\n",
    "    hue=\"closure_type\",\n",
    "    hue_order=hue_order,\n",
    "    multiple=\"fill\",\n",
    ")\n",
    "\n",
    "sns.histplot(\n",
    "    x=\"pivot_helix\",\n",
    "    data=scores_df.sort_values([\"pivot_helix\"]),\n",
    "    ax=ax2,\n",
    "    hue=\"closure_type\",\n",
    "    hue_order=hue_order,\n",
    "    multiple=\"fill\",\n",
    ")\n",
    "\n",
    "\n",
    "sns.despine()\n",
    "plt.suptitle(\"Shift or Pivot vs. Closure Type\")\n",
    "plt.savefig(\"figs/03_shift_vs_pivot_groupby_closure.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Interpretations:\n",
    "Larger shifts can be harder to loop."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2880x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(ncols=1, figsize=(40, 15), tight_layout=True)\n",
    "\n",
    "sns.histplot(\n",
    "    x=\"parent\",\n",
    "    data=scores_df.sort_values([\"parent\"]),\n",
    "    ax=ax,\n",
    "    hue=\"closure_type\",\n",
    "    hue_order=hue_order,\n",
    "    multiple=\"fill\",\n",
    ")\n",
    "plt.xticks(rotation=90)\n",
    "sns.despine()\n",
    "plt.suptitle(\"Parent vs. Closure Type\")\n",
    "plt.savefig(\"figs/03_parent_groupby_closure.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Some DHRs are very hard to close\n",
    "Remodel improves the success rate by quite a bit\n",
    "THRs and TH_DHRs varied a lot as well. Seems like helical phase matters a lot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2880x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(ncols=1, figsize=(40, 15), tight_layout=True)\n",
    "\n",
    "sns.histplot(\n",
    "    x=\"parent\",\n",
    "    data=scores_df[scores_df[\"scaffold\"] == \"DHR\"].sort_values([\"parent\"]),\n",
    "    ax=ax,\n",
    "    hue=\"closure_type\",\n",
    "    hue_order=hue_order,\n",
    "    multiple=\"fill\",\n",
    ")\n",
    "plt.xticks(rotation=90)\n",
    "sns.despine()\n",
    "plt.suptitle(\"Parent vs. Closure Type\")\n",
    "plt.savefig(\"figs/03_parent_DHRs_only_groupby_closure.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2880x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(ncols=1, figsize=(40, 15), tight_layout=True)\n",
    "\n",
    "sns.histplot(\n",
    "    x=\"parent\",\n",
    "    data=scores_df[scores_df[\"scaffold\"] == \"hDHR\"].sort_values([\"parent\"]),\n",
    "    ax=ax,\n",
    "    hue=\"closure_type\",\n",
    "    hue_order=hue_order,\n",
    "    multiple=\"fill\",\n",
    ")\n",
    "plt.xticks(rotation=90)\n",
    "sns.despine()\n",
    "plt.suptitle(\"Parent vs. Closure Type\")\n",
    "plt.savefig(\"figs/03_parent_hDHRs_only_groupby_closure.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Let's get all the ones that were able to be closed\n",
    "Save a list of the closed designs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2758"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "closed = scores_df[scores_df.closure_type != \"not_closed\"]\n",
    "# the handful of designs that have a helical dssp in the loop need to be taken out too\n",
    "closed = closed[closed.new_loop_resis != \"\"]\n",
    "len(closed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "out_path = os.path.join(os.getcwd(), \"03_enumerate_loops\")\n",
    "with open(os.path.join(out_path, \"closed.list\"), \"w+\") as f:\n",
    "    for decoy in closed.index:\n",
    "        print(decoy, file=f)"
   ]
  }
 ],
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