03_trim_detail.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Trim and resurface designs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Boilerplate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/mnt/home/pleung/projects/peptide_binders/r0/peptide_binders\n",
      "dig105\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": [
    "### Make function to trim and resurface\n",
    "We want to trim designs that are close to 162 aa to 162. May also want to pad designs with GS at a later step.\n",
    "SAP constraint will prevent grease balls, should probably use fragments too to help folding"
   ]
  },
  {
   "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",
    "\n",
    "\n",
    "@requires_init\n",
    "def detail_design(packed_pose_in: PackedPose, **kwargs) -> PackedPose:\n",
    "    \"\"\"\n",
    "    Truncate designs > 162aa & < 176aa to 162aa.\n",
    "    Resurface with SAP constraint.\n",
    "    Recompute score metrics.\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",
    "    def trim(seq_length: int) -> list:\n",
    "        target = 162\n",
    "        maximum = 175\n",
    "        if seq_length > maximum or seq_length < target:\n",
    "            to_trim = [str(seq_length)]\n",
    "            return to_trim\n",
    "        else:\n",
    "            amount_to_trim = seq_length - target\n",
    "            n_term_trim = int(amount_to_trim / 2)\n",
    "            c_term_trim = amount_to_trim - n_term_trim\n",
    "            all_resis = list(range(1, seq_length + 1))\n",
    "            to_trim = [str(x) for x in all_resis[:n_term_trim]] + [\n",
    "                str(x) for x in all_resis[-c_term_trim:]\n",
    "            ]\n",
    "            return to_trim\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 = dict(pyrosetta.distributed.cluster.get_scores_dict(file)[\"scores\"])\n",
    "    else:\n",
    "        raise RuntimeError(\"Need to supply an input\")\n",
    "\n",
    "    to_trim = trim(int(float(scores[\"chB_start\"]) - 1))\n",
    "    offset = len(to_trim)\n",
    "    new_interface_hydrophobics = \",\".join(\n",
    "        [str(int(x) - offset) for x in scores[\"interface_hydrophobics\"].split(\",\")]\n",
    "    )\n",
    "    scores[\"interface_hydrophobics\"] = new_interface_hydrophobics\n",
    "    xml = \"\"\"\n",
    "    <ROSETTASCRIPTS>\n",
    "        <SCOREFXNS>\n",
    "            <ScoreFunction name=\"sfxn\" weights=\"beta_nov16\" />\n",
    "            <ScoreFunction name=\"sfxn_soft\" weights=\"beta_nov16_soft\" />\n",
    "            <ScoreFunction name=\"sfxn_fa_atr\" weights=\"empty\" >\n",
    "                <Reweight scoretype=\"fa_atr\" weight=\"1\" />\n",
    "            </ScoreFunction>\n",
    "            <ScoreFunction name=\"sfxn_relax\" weights=\"beta_nov16\" >\n",
    "                <Reweight scoretype=\"arg_cation_pi\" weight=\"3\" />\n",
    "                <Reweight scoretype=\"approximate_buried_unsat_penalty\" weight=\"5\" />\n",
    "                <Set approximate_buried_unsat_penalty_burial_atomic_depth=\"3.5\" />\n",
    "                <Set approximate_buried_unsat_penalty_hbond_energy_threshold=\"-0.5\" />\n",
    "            </ScoreFunction>\n",
    "            <ScoreFunction name=\"sfxn_design\" weights=\"beta_nov16\" >\n",
    "                <Reweight scoretype=\"res_type_constraint\" weight=\"1.5\" />\n",
    "                <Reweight scoretype=\"aa_composition\" weight=\"1.0\" />\n",
    "                <Reweight scoretype=\"sap_constraint\" weight=\"1.0\" />\n",
    "                <Reweight scoretype=\"netcharge\" weight=\"1.0\" />\n",
    "                <Reweight scoretype=\"arg_cation_pi\" weight=\"3\" />\n",
    "                <Reweight scoretype=\"approximate_buried_unsat_penalty\" weight=\"5\" />\n",
    "                <Set approximate_buried_unsat_penalty_burial_atomic_depth=\"3.5\" />\n",
    "                <Set approximate_buried_unsat_penalty_hbond_energy_threshold=\"-0.5\" />\n",
    "                <Set approximate_buried_unsat_penalty_hbond_bonus_cross_chain=\"-1\" />\n",
    "            </ScoreFunction>\n",
    "            <ScoreFunction name=\"vdw_sol\" weights=\"empty\" >\n",
    "                <Reweight scoretype=\"fa_atr\" weight=\"1.0\" />\n",
    "                <Reweight scoretype=\"fa_rep\" weight=\"0.55\" />\n",
    "                <Reweight scoretype=\"fa_sol\" weight=\"1.0\" />\n",
    "            </ScoreFunction>\n",
    "        </SCOREFXNS>\n",
    "        <TASKOPERATIONS>\n",
    "            <SelectBySASA name=\"PR_monomer_core_sel\" mode=\"sc\" state=\"monomer\" probe_radius=\"2.2\" core_asa=\"15\" surface_asa=\"15\" core=\"0\" boundary=\"1\" surface=\"1\" verbose=\"0\" />\n",
    "        </TASKOPERATIONS>\n",
    "        <RESIDUE_SELECTORS>\n",
    "            <Chain name=\"chainA\" chains=\"A\"/>\n",
    "            <Chain name=\"chainB\" chains=\"B\"/>\n",
    "            <Neighborhood name=\"interface_chA\" selector=\"chainB\" distance=\"10.0\" />\n",
    "            <Neighborhood name=\"interface_chB\" selector=\"chainA\" distance=\"10.0\" />\n",
    "            <And name=\"AB_interface\" selectors=\"interface_chA,interface_chB\" />\n",
    "            <Not name=\"Not_interface\" selector=\"AB_interface\" />\n",
    "            <And name=\"actual_interface_chA\" selectors=\"AB_interface,chainA\" />\n",
    "            <And name=\"actual_interface_chB\" selectors=\"AB_interface,chainB\" />\n",
    "            <And name=\"chainB_not_interface\" selectors=\"Not_interface,chainB\" />\n",
    "            <Not name=\"not_chB\" selector=\"chainB\" />\n",
    "            <ResidueName name=\"pro_and_gly_positions\" residue_name3=\"PRO,GLY,CYS\" />\n",
    "            <ResidueName name=\"apolar\" residue_name3=\"ALA,CYS,PHE,ILE,LEU,MET,THR,PRO,VAL,TRP,TYR\" />\n",
    "            <Not name=\"polar\" selector=\"apolar\" />\n",
    "            <InterfaceByVector name=\"interface_by_vector\" cb_dist_cut=\"11\" nearby_atom_cut=\"5.5\" vector_angle_cut=\"75\" vector_dist_cut=\"9\" grp1_selector=\"actual_interface_chA\" grp2_selector=\"actual_interface_chB\"/>\n",
    "            <Task name=\"all_cores\" fixed=\"true\" task_operations=\"PR_monomer_core_sel\" packable=\"false\" designable=\"false\"/>\n",
    "            <And name=\"for_hydrophobic\" selectors=\"actual_interface_chA,interface_by_vector\">\n",
    "                <Not selector=\"all_cores\" />\n",
    "            </And>            \n",
    "            <Index name=\"patchdock_res\" resnums=\"{interface_hydrophobics}\" />\n",
    "            <Index name=\"pocket\" resnums=\"{interface_hydrophobics}\" />\n",
    "            <And name=\"target_not_pocket\" selectors=\"chainB\">\n",
    "                <Not selector=\"pocket\" />\n",
    "            </And>\n",
    "            <Layer name=\"surface\" select_core=\"false\" select_boundary=\"false\" select_surface=\"true\" use_sidechain_neighbors=\"true\"/>\n",
    "            <Layer name=\"boundary\" select_core=\"false\" select_boundary=\"true\" select_surface=\"false\" use_sidechain_neighbors=\"true\"/>\n",
    "            <Layer name=\"core\" select_core=\"true\" select_boundary=\"false\" select_surface=\"false\" use_sidechain_neighbors=\"true\"/>\n",
    "            <SecondaryStructure name=\"sheet\" overlap=\"0\" minH=\"3\" minE=\"2\" include_terminal_loops=\"false\" use_dssp=\"true\" ss=\"E\"/>\n",
    "            <SecondaryStructure name=\"entire_loop\" overlap=\"0\" minH=\"3\" minE=\"2\" include_terminal_loops=\"true\" use_dssp=\"true\" ss=\"L\"/>\n",
    "            <SecondaryStructure name=\"entire_helix\" overlap=\"0\" minH=\"3\" minE=\"2\" include_terminal_loops=\"false\" use_dssp=\"true\" ss=\"H\"/>\n",
    "            <And name=\"helix_cap\" selectors=\"entire_loop\">\n",
    "                <PrimarySequenceNeighborhood lower=\"1\" upper=\"0\" selector=\"entire_helix\"/>\n",
    "            </And>\n",
    "            <And name=\"helix_start\" selectors=\"entire_helix\">\n",
    "                <PrimarySequenceNeighborhood lower=\"0\" upper=\"1\" selector=\"helix_cap\"/>\n",
    "            </And>\n",
    "            <And name=\"helix\" selectors=\"entire_helix\">\n",
    "                <Not selector=\"helix_start\"/>\n",
    "            </And>\n",
    "            <And name=\"loop\" selectors=\"entire_loop\">\n",
    "                <Not selector=\"helix_cap\"/>\n",
    "            </And>\n",
    "            <And name=\"surface_not_int\" selectors=\"surface,chainA\">\n",
    "                <Not selector=\"AB_interface\"/>\n",
    "            </And>\n",
    "            <And name=\"boundary_not_int\" selectors=\"boundary,chainA\">\n",
    "                <Not selector=\"AB_interface\"/>\n",
    "            </And>\n",
    "            <Or name=\"resurfaceable\" selectors=\"surface_not_int,boundary_not_int\" />\n",
    "            <Not name=\"not_resurfaceable\" selector=\"resurfaceable\" />\n",
    "            <Index name=\"to_trim\" resnums=\"{indices_to_delete}\" />\n",
    "        </RESIDUE_SELECTORS>\n",
    "        <TASKOPERATIONS>\n",
    "            <DesignRestrictions name=\"layer_design_F_boundary_M\">\n",
    "                <Action selector_logic=\"not_chB AND surface AND helix_start\"  aas=\"DEHKPQR\"/>\n",
    "                <Action selector_logic=\"not_chB AND surface AND helix\"        aas=\"EHKQR\"/>\n",
    "                <Action selector_logic=\"not_chB AND surface AND sheet\"        aas=\"EHKNQRST\"/>\n",
    "                <Action selector_logic=\"not_chB AND surface AND loop\"         aas=\"DEGHKNPQRST\"/>\n",
    "                <Action selector_logic=\"not_chB AND boundary AND helix_start\" aas=\"ADEFHIKLMNPQRSTVWY\"/>\n",
    "                <Action selector_logic=\"not_chB AND boundary AND helix\"       aas=\"ADEFHIKLMNQRSTVWY\"/>\n",
    "                <Action selector_logic=\"not_chB AND boundary AND sheet\"       aas=\"DEFHIKLMNQRSTVWY\"/>\n",
    "                <Action selector_logic=\"not_chB AND boundary AND loop\"        aas=\"ADEFGHIKLNPQRSTVWY\"/>\n",
    "                <Action selector_logic=\"not_chB AND core AND helix_start\"     aas=\"AFILMPVWY\"/>\n",
    "                <Action selector_logic=\"not_chB AND core AND helix\"           aas=\"AFILMVWYDENQSTH\"/>\n",
    "                <Action selector_logic=\"not_chB AND core AND sheet\"           aas=\"FILMVWYDENQSTH\"/>\n",
    "                <Action selector_logic=\"not_chB AND core AND loop\"            aas=\"AFGILPVWYDENQSTH\"/>\n",
    "                <Action selector_logic=\"not_chB AND helix_cap\"                aas=\"DNST\"/>\n",
    "            </DesignRestrictions>\n",
    "        </TASKOPERATIONS>\n",
    "        <TASKOPERATIONS>\n",
    "            <PruneBuriedUnsats name=\"prune_buried_unsats\" allow_even_trades=\"false\" atomic_depth_cutoff=\"3.5\" minimum_hbond_energy=\"-0.5\" />\n",
    "            <IncludeCurrent name=\"current\" />\n",
    "            <LimitAromaChi2 name=\"limitchi2\" chi2max=\"110\" chi2min=\"70\" include_trp=\"True\" />\n",
    "            <ExtraRotamersGeneric name=\"ex1_ex2\" ex1=\"1\" ex2aro=\"1\" />\n",
    "            <OperateOnResidueSubset name=\"restrict_target_not_interface\" selector=\"chainB_not_interface\">\n",
    "                <PreventRepackingRLT/>\n",
    "            </OperateOnResidueSubset>\n",
    "            <OperateOnResidueSubset name=\"restrict_interface\" selector=\"AB_interface\">\n",
    "                <RestrictToRepackingRLT/>\n",
    "            </OperateOnResidueSubset>\n",
    "            <OperateOnResidueSubset name=\"restrict_target2repacking\" selector=\"chainB\">\n",
    "                <RestrictToRepackingRLT/>\n",
    "            </OperateOnResidueSubset>\n",
    "            <OperateOnResidueSubset name=\"resurface_only\" selector=\"not_resurfaceable\">\n",
    "                <RestrictToRepackingRLT/>\n",
    "            </OperateOnResidueSubset>\n",
    "            <OperateOnResidueSubset name=\"lock_core\" selector=\"core\">\n",
    "                <PreventRepackingRLT/>\n",
    "            </OperateOnResidueSubset>\n",
    "            <DisallowIfNonnative name=\"disallow_GLY\" resnum=\"0\" disallow_aas=\"G\" />\n",
    "            <DisallowIfNonnative name=\"disallow_PRO\" resnum=\"0\" disallow_aas=\"P\" />\n",
    "            <OperateOnResidueSubset name=\"restrict_PRO_GLY\" selector=\"pro_and_gly_positions\">\n",
    "                <PreventRepackingRLT/>\n",
    "            </OperateOnResidueSubset>\n",
    "            <SelectBySASA name=\"PR_monomer_core\" mode=\"sc\" state=\"monomer\" probe_radius=\"2.2\" core_asa=\"10\" surface_asa=\"10\" core=\"0\" boundary=\"1\" surface=\"1\" verbose=\"0\" />\n",
    "            <ProteinInterfaceDesign name=\"pack_long\" design_chain1=\"0\" design_chain2=\"0\" jump=\"1\" interface_distance_cutoff=\"15\"/>\n",
    "        </TASKOPERATIONS>\n",
    "        <MOVERS>\n",
    "            <DeleteRegionMover name=\"delete_target_not_pocket\" residue_selector=\"target_not_pocket\" rechain=\"false\" />\n",
    "            <SwitchChainOrder name=\"chain1onlypre\" chain_order=\"1\" />\n",
    "            <ScoreMover name=\"scorepose\" scorefxn=\"sfxn\" verbose=\"false\" />\n",
    "            <ParsedProtocol name=\"chain1only\">\n",
    "                <Add mover=\"chain1onlypre\" />\n",
    "                <Add mover=\"scorepose\" />\n",
    "            </ParsedProtocol>\n",
    "            <TaskAwareMinMover name=\"min\" scorefxn=\"sfxn\" bb=\"0\" chi=\"1\" task_operations=\"pack_long\" />\n",
    "            <DeleteRegionMover name=\"delete_polar\" residue_selector=\"polar\" rechain=\"false\" />\n",
    "            <AddSapConstraintMover name=\"add_sap\" speed=\"lightning\" sap_goal=\"25\" penalty_per_sap=\"1\" />\n",
    "            <AddNetChargeConstraintMover name=\"charged\" filename=\"/mnt/home/bcov/sc/scaffold_comparison/data/net_charges/minus7.charge\" selector=\"chainA\" />\n",
    "            <StructProfileMover name=\"genProfile\" add_csts_to_pose=\"1\" consider_topN_frags=\"100\" eliminate_background=\"0\" ignore_terminal_residue=\"1\" only_loops=\"0\" burialWt=\"0\" RMSthreshold=\"0.6\" residue_selector=\"chainA\" />\n",
    "            <ClearConstraintsMover name=\"clear_constraints\" />\n",
    "            <SavePoseMover name=\"save\" restore_pose=\"0\" reference_name=\"before_relax\" />\n",
    "        </MOVERS>\n",
    "        <FILTERS>\n",
    "            <Rmsd name=\"rmsd\" reference_name=\"before_relax\" confidence=\"0\" />\n",
    "            <Sasa name=\"interface_buried_sasa\" confidence=\"0\" />\n",
    "            <Ddg name=\"ddg\"  threshold=\"-10\" jump=\"1\" repeats=\"5\" repack=\"1\" relax_mover=\"min\" confidence=\"0\" scorefxn=\"sfxn\" extreme_value_removal=\"1\" />\n",
    "            <ShapeComplementarity name=\"interface_sc\" verbose=\"0\" min_sc=\"0.55\" write_int_area=\"1\" write_median_dist=\"1\" jump=\"1\" confidence=\"0\"/>\n",
    "            <ShapeComplementarity name=\"interface_sc_for_fr1\" verbose=\"0\" min_sc=\"0.55\" write_int_area=\"1\" write_median_dist=\"1\" jump=\"1\" confidence=\"0\"/>\n",
    "            <ScoreType name=\"total_score_MBF\" scorefxn=\"sfxn\" score_type=\"total_score\" threshold=\"0\" confidence=\"0\" />\n",
    "            <MoveBeforeFilter name=\"total_score_monomer\" mover=\"chain1only\" filter=\"total_score_MBF\" confidence=\"0\" />\n",
    "            <ResidueCount name=\"res_count_MBF\" max_residue_count=\"9999\" confidence=\"0\"/>\n",
    "            <MoveBeforeFilter name=\"res_count_monomer\" mover=\"chain1only\" filter=\"res_count_MBF\" confidence=\"0\" />\n",
    "            <CalculatorFilter name=\"score_per_res\" equation=\"total_score_monomer / res\" threshold=\"-3.5\" confidence=\"0\">\n",
    "                <Var name=\"total_score_monomer\" filter=\"total_score_monomer\"/>\n",
    "                <Var name=\"res\" filter=\"res_count_monomer\"/>\n",
    "            </CalculatorFilter>\n",
    "            <BuriedUnsatHbonds name=\"buns_heavy_ball_1.1D\" use_reporter_behavior=\"true\" report_all_heavy_atom_unsats=\"true\" scorefxn=\"sfxn\" residue_selector=\"AB_interface\" ignore_surface_res=\"false\" print_out_info_to_pdb=\"true\" confidence=\"0\" use_ddG_style=\"true\" burial_cutoff=\"0.01\" dalphaball_sasa=\"true\" probe_radius=\"1.1\" max_hbond_energy=\"1.5\" burial_cutoff_apo=\"0.2\" />\n",
    "            <BuriedUnsatHbonds name=\"sbuns5.0_heavy_ball_1.1D\" use_reporter_behavior=\"true\" report_all_heavy_atom_unsats=\"true\" scorefxn=\"sfxn\" residue_selector=\"AB_interface\" ignore_surface_res=\"false\" print_out_info_to_pdb=\"true\" confidence=\"0\" use_ddG_style=\"true\" burial_cutoff=\"0.01\" dalphaball_sasa=\"true\" probe_radius=\"1.1\" atomic_depth_selection=\"5.0\" atomic_depth_deeper_than=\"false\" burial_cutoff_apo=\"0.2\" atomic_depth_resolution=\"0.49\" max_hbond_energy=\"1.5\"/>\n",
    "            <BuriedUnsatHbonds name=\"vbuns5.0_heavy_ball_1.1D\" use_reporter_behavior=\"true\" report_all_heavy_atom_unsats=\"true\" scorefxn=\"sfxn\" residue_selector=\"AB_interface\" ignore_surface_res=\"false\" print_out_info_to_pdb=\"true\" confidence=\"0\" use_ddG_style=\"true\" dalphaball_sasa=\"true\" probe_radius=\"1.1\" atomic_depth_selection=\"5.0\" burial_cutoff=\"1000\" burial_cutoff_apo=\"0.2\" atomic_depth_apo_surface=\"5.5\" atomic_depth_resolution=\"0.49\" max_hbond_energy=\"1.5\"/>\n",
    "            <InterfaceHydrophobicResidueContacts name=\"hydrophobic_residue_contacts\" target_selector=\"chainB\" binder_selector=\"chainA\" scorefxn=\"sfxn_soft\" confidence=\"0\"/> \n",
    "            <ContactMolecularSurface name=\"contact_molecular_surface\" distance_weight=\"0.5\" target_selector=\"chainA\" binder_selector=\"chainB\" confidence=\"0\" />\n",
    "            <ContactMolecularSurface name=\"contact_patch\" distance_weight=\"0.5\" target_selector=\"patchdock_res\" binder_selector=\"chainA\" confidence=\"0\" />\n",
    "            <Ddg name=\"ddg_hydrophobic_pre\"  threshold=\"-10\" jump=\"1\" repeats=\"1\" repack=\"0\" confidence=\"0\" scorefxn=\"vdw_sol\" />\n",
    "            <MoveBeforeFilter name=\"ddg_hydrophobic\" mover=\"delete_polar\" filter=\"ddg_hydrophobic_pre\" confidence=\"0\"/>\n",
    "            <Ddg name=\"fa_atr_pocket_pre\"  threshold=\"-15\" jump=\"1\" repeats=\"1\" repack=\"0\" confidence=\"0\" scorefxn=\"sfxn_fa_atr\" />\n",
    "            <MoveBeforeFilter name=\"fa_atr_pocket\" mover=\"delete_target_not_pocket\" filter=\"fa_atr_pocket_pre\" confidence=\"0\"/>\n",
    "            <SSShapeComplementarity name=\"ss_sc_pre\" verbose=\"0\" confidence=\"0\" />\n",
    "            <MoveBeforeFilter name=\"ss_sc\" mover=\"chain1only\" filter=\"ss_sc_pre\" confidence=\"0\"/>\n",
    "            <Time name=\"timed\"/>\n",
    "        </FILTERS>\n",
    "        <MOVERS>\n",
    "            <DeleteRegionMover name=\"trim\" residue_selector=\"to_trim\" rechain=\"false\" />\n",
    "            <SwitchChainOrder name=\"rechain\" chain_order=\"12\"/>\n",
    "            <FastDesign name=\"resurface\" scorefxn=\"sfxn_design\" repeats=\"2\" task_operations=\"current,limitchi2,ex1_ex2,restrict_interface,restrict_target2repacking,resurface_only,lock_core,disallow_GLY,disallow_PRO,PR_monomer_core,restrict_PRO_GLY,prune_buried_unsats,layer_design_F_boundary_M\" batch=\"false\" ramp_down_constraints=\"false\" cartesian=\"false\" bondangle=\"false\" bondlength=\"false\" min_type=\"dfpmin_armijo_nonmonotone\" relaxscript=\"InterfaceDesign2019\" >\n",
    "                <MoveMap name=\"MM\" >\n",
    "                        <Chain number=\"1\" chi=\"true\" bb=\"true\" />\n",
    "                        <Chain number=\"2\" chi=\"true\" bb=\"false\" />\n",
    "                        <Jump number=\"1\" setting=\"true\" />\n",
    "                </MoveMap>\n",
    "            </FastDesign>\n",
    "            <FastRelax name=\"relax\" scorefxn=\"sfxn_relax\" repeats=\"1\" batch=\"false\" ramp_down_constraints=\"false\" cartesian=\"false\" bondangle=\"false\" bondlength=\"false\" min_type=\"dfpmin_armijo_nonmonotone\" task_operations=\"current,ex1_ex2,restrict_target_not_interface,limitchi2,prune_buried_unsats\" >\n",
    "                <MoveMap name=\"MM\" >\n",
    "                    <Chain number=\"1\" chi=\"true\" bb=\"true\" />\n",
    "                    <Chain number=\"2\" chi=\"true\" bb=\"true\" />\n",
    "                    <Jump number=\"1\" setting=\"true\" />\n",
    "                </MoveMap>\n",
    "            </FastRelax>\n",
    "        </MOVERS>\n",
    "        <APPLY_TO_POSE>\n",
    "        </APPLY_TO_POSE>\n",
    "        <PROTOCOLS>\n",
    "            <Add filter=\"timed\" />\n",
    "            <Add mover=\"trim\" />\n",
    "            <Add mover=\"rechain\" />\n",
    "            Add mover=\"genProfile\" />\n",
    "            <Add mover=\"add_sap\" />\n",
    "            <Add mover=\"charged\" />\n",
    "            <Add mover=\"resurface\" />\n",
    "            <Add mover=\"clear_constraints\" />\n",
    "            <Add mover=\"save\" />\n",
    "            <Add mover=\"relax\" />\n",
    "            <Add filter_name=\"rmsd\" />\n",
    "            <Add filter_name=\"interface_buried_sasa\" />   \n",
    "            <Add filter_name=\"ddg\" />                     \n",
    "            <Add filter=\"ddg_hydrophobic\" />              \n",
    "            <Add filter_name=\"interface_sc\" />            \n",
    "            <Add filter_name=\"score_per_res\" />          \n",
    "            <Add filter=\"vbuns5.0_heavy_ball_1.1D\" />    \n",
    "            <Add filter=\"sbuns5.0_heavy_ball_1.1D\" />    \n",
    "            <Add filter=\"buns_heavy_ball_1.1D\" />    \n",
    "            <Add filter=\"hydrophobic_residue_contacts\" />\n",
    "            <Add filter=\"fa_atr_pocket\" />               \n",
    "            <Add filter=\"contact_molecular_surface\" />\n",
    "            <Add filter=\"contact_patch\" />   \n",
    "            <Add filter=\"ss_sc\" />   \n",
    "            <Add filter=\"timed\" />\n",
    "        </PROTOCOLS>\n",
    "        <OUTPUT />\n",
    "    </ROSETTASCRIPTS>\n",
    "    \"\"\".format(\n",
    "        indices_to_delete=\",\".join(to_trim),\n",
    "        interface_hydrophobics=scores[\"interface_hydrophobics\"],\n",
    "    )\n",
    "    detailer = SingleoutputRosettaScriptsTask(xml)\n",
    "    designed_ppose = detailer(packed_pose_in.pose.clone())\n",
    "    new_scores = dict(designed_ppose.pose.scores)\n",
    "    scores.update(new_scores)\n",
    "    scores[\"interface_hydrophobics\"] = new_interface_hydrophobics\n",
    "    score_xml = \"\"\"\n",
    "    <ROSETTASCRIPTS>\n",
    "        <SCOREFXNS>\n",
    "            <ScoreFunction name=\"sfxn\" weights=\"beta_nov16\" />\n",
    "        </SCOREFXNS>\n",
    "        <MOVERS>\n",
    "            <SwitchChainOrder name=\"chain1only\" chain_order=\"1\" />\n",
    "            <RollMover name=\"move_chainA_far_away\" chain=\"1\" min_angle=\"0\" max_angle=\"0\" axis=\"x\" >\n",
    "                <translate x=\"1000\" y=\"1000\" z=\"1000\" /> \n",
    "            </RollMover>\n",
    "        </MOVERS>\n",
    "        <RESIDUE_SELECTORS>\n",
    "            <Chain name=\"chainA\" chains=\"A\"/>\n",
    "            <Chain name=\"chainB\" chains=\"B\"/>\n",
    "            <Neighborhood name=\"interface_chA\" selector=\"chainB\" distance=\"10.0\" />\n",
    "            <Neighborhood name=\"interface_chB\" selector=\"chainA\" distance=\"10.0\" />\n",
    "            <And name=\"AB_interface\" selectors=\"interface_chA,interface_chB\" />\n",
    "            <Not name=\"Not_interface\" selector=\"AB_interface\" />\n",
    "            <And name=\"actual_interface_chA\" selectors=\"AB_interface,chainA\" />\n",
    "            <And name=\"actual_interface_chB\" selectors=\"AB_interface,chainB\" />\n",
    "            <ResidueName name=\"apolar\" residue_name3=\"ALA,CYS,PHE,ILE,LEU,MET,THR,PRO,VAL,TRP,TYR\" />\n",
    "            <And name=\"apolar_A\" selectors=\"apolar,actual_interface_chA\" />\n",
    "            <And name=\"apolar_B\" selectors=\"apolar,actual_interface_chB\" />\n",
    "            <Index name=\"patchdock_res\" resnums=\"{interface_hydrophobics}\" />\n",
    "            <True name=\"true_sel\" />\n",
    "        </RESIDUE_SELECTORS>\n",
    "        <SIMPLE_METRICS>\n",
    "            <SapScoreMetric name=\"sap_score\" score_selector=\"chainA\" />\n",
    "            <SapScoreMetric name=\"sap_score_target\" score_selector=\"chainB\" />\n",
    "            <SapScoreMetric name=\"binder_blocked_sap\" score_selector=\"chainA\" sap_calculate_selector=\"chainA\" sasa_selector=\"true_sel\" />\n",
    "            <SapScoreMetric name=\"target_blocked_sap\" score_selector=\"chainB\" sap_calculate_selector=\"chainB\" sasa_selector=\"true_sel\" />\n",
    "        </SIMPLE_METRICS>\n",
    "        <TASKOPERATIONS>\n",
    "            <ProteinInterfaceDesign name=\"pack_long\" design_chain1=\"0\" design_chain2=\"0\" jump=\"1\" interface_distance_cutoff=\"15\"/>\n",
    "        </TASKOPERATIONS>\n",
    "        <MOVERS>\n",
    "            <TaskAwareMinMover name=\"min\" scorefxn=\"sfxn\" bb=\"0\" chi=\"1\" task_operations=\"pack_long\" />\n",
    "        </MOVERS>\n",
    "        <FILTERS>\n",
    "            <ContactMolecularSurface name=\"contact_patch\" distance_weight=\"0.5\" target_selector=\"patchdock_res\" binder_selector=\"chainA\" confidence=\"0\" />\n",
    "            <Ddg name=\"ddg\"  threshold=\"-10\" jump=\"1\" repeats=\"5\" repack=\"1\" relax_mover=\"min\" confidence=\"0\" scorefxn=\"sfxn\" extreme_value_removal=\"1\" />\n",
    "            <ResidueCount name=\"res_count_all\" max_residue_count=\"9999\" confidence=\"0\"/>\n",
    "            <BuriedSurfaceArea name=\"buried_npsa_FAMILYVW\" select_only_FAMILYVW=\"True\" atom_mode=\"hydrophobic_atoms\" confidence=\"0.0\" />\n",
    "            <BuriedSurfaceArea name=\"buried_npsa\" select_only_FAMILYVW=\"False\" atom_mode=\"hydrophobic_atoms\" confidence=\"0.0\" />\n",
    "            <ExposedHydrophobics name=\"exposed_hydrophobics\"  confidence=\"0\" />\n",
    "            <CalculatorFilter name=\"buried_npsa_per_res\" equation=\"total_score / res\" threshold=\"-3.2\" confidence=\"0\">\n",
    "                <Var name=\"total_score\" filter=\"buried_npsa\"/>\n",
    "                <Var name=\"res\" filter=\"res_count_all\"/>\n",
    "            </CalculatorFilter>\n",
    "            <CalculatorFilter name=\"buried_npsa_FAMILYVW_per_res\" equation=\"total_score / res\" threshold=\"-3.2\" confidence=\"0\">\n",
    "                <Var name=\"total_score\" filter=\"buried_npsa_FAMILYVW\"/>\n",
    "                <Var name=\"res\" filter=\"res_count_all\"/>\n",
    "            </CalculatorFilter>\n",
    "            <MoveBeforeFilter name=\"buried_npsa_FAMILYVW_monomer\" mover=\"chain1only\" filter=\"buried_npsa_FAMILYVW\" confidence=\"0\" />\n",
    "            <MoveBeforeFilter name=\"buried_npsa_monomer\" mover=\"chain1only\" filter=\"buried_npsa\" confidence=\"0\" />\n",
    "            <MoveBeforeFilter name=\"exposed_hydrophobics_monomer\" mover=\"chain1only\" filter=\"exposed_hydrophobics\" confidence=\"0\" />\n",
    "            <MoveBeforeFilter name=\"buried_npsa_per_res_monomer\" mover=\"chain1only\" filter=\"buried_npsa_per_res\" confidence=\"0\" />\n",
    "            <MoveBeforeFilter name=\"buried_npsa_FAMILYVW_per_res_monomer\" mover=\"chain1only\" filter=\"buried_npsa_FAMILYVW_per_res\" confidence=\"0\" />\n",
    "            <MoveBeforeFilter name=\"buried_npsa_FAMILYVW_apo\" mover=\"move_chainA_far_away\" filter=\"buried_npsa_FAMILYVW\" confidence=\"0\" />\n",
    "            <MoveBeforeFilter name=\"buried_npsa_apo\" mover=\"move_chainA_far_away\" filter=\"buried_npsa\" confidence=\"0\" />\n",
    "            <MoveBeforeFilter name=\"exposed_hydrophobics_apo\" mover=\"move_chainA_far_away\" filter=\"exposed_hydrophobics\" confidence=\"0\" />\n",
    "            <CalculatorFilter   name=\"delta_buried_npsa_FAMILYVW\" equation=\"complex - apo\" threshold=\"-3.2\" confidence=\"0\">\n",
    "                <Var name=\"complex\" filter=\"buried_npsa_FAMILYVW\"/>\n",
    "                <Var name=\"apo\"     filter=\"buried_npsa_FAMILYVW_apo\"/>\n",
    "            </CalculatorFilter>\n",
    "            <CalculatorFilter   name=\"delta_buried_npsa\" equation=\"complex - apo\" threshold=\"-3.2\" confidence=\"0\">\n",
    "                <Var name=\"complex\" filter=\"buried_npsa\"/>\n",
    "                <Var name=\"apo\"     filter=\"buried_npsa_apo\"/>\n",
    "            </CalculatorFilter>\n",
    "            <CalculatorFilter   name=\"delta_exposed_hydrophobics\" equation=\"complex - apo\" threshold=\"-3.2\" confidence=\"0\">\n",
    "                <Var name=\"complex\" filter=\"exposed_hydrophobics\"/>\n",
    "                <Var name=\"apo\"     filter=\"exposed_hydrophobics_apo\"/>\n",
    "            </CalculatorFilter>\n",
    "            <ContactMolecularSurface name=\"contact_molecular_surface_ap_target\" distance_weight=\"0.5\" target_selector=\"apolar_B\" binder_selector=\"chainA\" confidence=\"0\" />\n",
    "            <ContactMolecularSurface name=\"contact_molec_sq5_ap_target\" distance_weight=\"0.5\" target_selector=\"apolar_B\" binder_selector=\"chainA\" confidence=\"0\" near_squared_size=\"5\" />\n",
    "            <ContactMolecularSurface name=\"contact_molecular_surface_apap_target\" distance_weight=\"0.5\" target_selector=\"apolar_B\" binder_selector=\"chainA\" confidence=\"0\" apolar_target=\"true\" />\n",
    "            <ContactMolecularSurface name=\"contact_molec_sq5_apap_target\" distance_weight=\"0.5\" target_selector=\"apolar_B\" binder_selector=\"chainA\" confidence=\"0\" near_squared_size=\"5\" apolar_target=\"true\" />\n",
    "            <ContactMolecularSurface name=\"contact_molecular_surface_ap_binder\" distance_weight=\"0.5\" target_selector=\"apolar_A\" binder_selector=\"chainB\" confidence=\"0\" />\n",
    "            <ContactMolecularSurface name=\"contact_molec_sq5_ap_binder\" distance_weight=\"0.5\" target_selector=\"apolar_A\" binder_selector=\"chainB\" confidence=\"0\" near_squared_size=\"5\" />\n",
    "            <ContactMolecularSurface name=\"contact_molecular_surface_apap_binder\" distance_weight=\"0.5\" target_selector=\"apolar_A\" binder_selector=\"chainB\" confidence=\"0\" apolar_target=\"true\" />\n",
    "            <ContactMolecularSurface name=\"contact_molec_sq5_apap_binder\" distance_weight=\"0.5\" target_selector=\"apolar_A\" binder_selector=\"chainB\" confidence=\"0\" near_squared_size=\"5\" apolar_target=\"true\" />\n",
    "            <worst9mer name=\"pre_wnm_all\" rmsd_lookup_threshold=\"0.4\" confidence=\"0\" />\n",
    "            <worst9mer name=\"pre_wnm_hlx\" rmsd_lookup_threshold=\"0.4\" confidence=\"0\" only_helices=\"true\" />\n",
    "            <MoveBeforeFilter name=\"wnm_all\" mover=\"chain1only\" filter=\"pre_wnm_all\" confidence=\"0\" />\n",
    "            <MoveBeforeFilter name=\"wnm_hlx\" mover=\"chain1only\" filter=\"pre_wnm_hlx\" confidence=\"0\" />\n",
    "        </FILTERS>\n",
    "        <PROTOCOLS>\n",
    "            <Add filter=\"contact_molecular_surface_ap_target\" />\n",
    "            <Add filter=\"contact_molec_sq5_ap_target\" />\n",
    "            <Add filter=\"contact_molecular_surface_apap_target\" />\n",
    "            <Add filter=\"contact_molec_sq5_apap_target\" />\n",
    "            <Add filter=\"contact_patch\"/>\n",
    "            <Add filter=\"ddg\"/>\n",
    "            <Add filter=\"wnm_all\"/>\n",
    "            <Add filter=\"wnm_hlx\"/>\n",
    "            <Add metrics=\"sap_score\" />\n",
    "            <Add metrics=\"sap_score_target\" />\n",
    "            <Add metrics=\"binder_blocked_sap\" />\n",
    "            <Add metrics=\"target_blocked_sap\" />\n",
    "        </PROTOCOLS>\n",
    "        <OUTPUT />\n",
    "    </ROSETTASCRIPTS>\n",
    "    \"\"\".format(\n",
    "        interface_hydrophobics=scores[\"interface_hydrophobics\"],\n",
    "    )\n",
    "    scorer = SingleoutputRosettaScriptsTask(score_xml)\n",
    "    scored_ppose = scorer(designed_ppose.pose.clone())\n",
    "    final_scores = dict(scored_ppose.pose.scores)\n",
    "    scores.update(final_scores)\n",
    "    scores[\"interface_hydrophobics\"] = new_interface_hydrophobics\n",
    "    scored_pose = io.to_pose(scored_ppose)\n",
    "    for key, value in scores.items():\n",
    "        pyrosetta.rosetta.core.pose.setPoseExtraScore(scored_pose, key, str(value))\n",
    "    final_ppose = io.to_packed(scored_pose)\n",
    "    return final_ppose"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### We're going to do a huge run here, more than it makes sense to use dask for\n",
    "Will submit everything to `backfill`\n",
    "Make `SLURM` array tasks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "447611it [04:56, 1508.81it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Run the following commands\n",
      "sbatch -a 1-$(cat 03_detail_0.cmds | wc -l) 03_detail_0.sh\n",
      "sbatch -a 1-$(cat 03_detail_1.cmds | wc -l) 03_detail_1.sh\n",
      "sbatch -a 1-$(cat 03_detail_2.cmds | wc -l) 03_detail_2.sh\n",
      "sbatch -a 1-$(cat 03_detail_3.cmds | wc -l) 03_detail_3.sh\n",
      "sbatch -a 1-$(cat 03_detail_4.cmds | wc -l) 03_detail_4.sh\n"
     ]
    }
   ],
   "source": [
    "import os, stat, subprocess\n",
    "\n",
    "\n",
    "def create_tasks(selected):\n",
    "    with open(selected, \"r\") as f:\n",
    "        for file in f:\n",
    "            tasks = {}\n",
    "            path = file.rstrip()\n",
    "            tasks[\"-s\"] = path\n",
    "            yield tasks\n",
    "\n",
    "\n",
    "def file_len(file):\n",
    "    \"\"\"https://stackoverflow.com/questions/845058/how-to-get-line-count-of-a-large-file-cheaply-in-python\"\"\"\n",
    "    with open(file) as f:\n",
    "        for i, l in enumerate(f):\n",
    "            pass\n",
    "    return i + 1\n",
    "\n",
    "\n",
    "# cleanup old cmdslists\n",
    "for cmdslist in glob(os.path.join(os.getcwd(), \"03_detail_*.cmds\")):\n",
    "    os.remove(cmdslist)\n",
    "\n",
    "targets = os.path.join(os.getcwd(), \"02_filter/to_detail.list\")\n",
    "detail = os.path.join(os.getcwd(), \"detail.py\")\n",
    "\n",
    "jid = \"{SLURM_JOB_ID%;*}\"\n",
    "sid = \"{SLURM_ARRAY_TASK_ID}p\"\n",
    "\n",
    "for i, tasks in enumerate(tqdm(create_tasks(targets))):\n",
    "    j = int(i / 100000)\n",
    "    k = int(i / 1000)\n",
    "    tasklist = f\"03_detail_{j}.cmds\"\n",
    "    run_sh = \"\"\"#!/usr/bin/env bash \\n#SBATCH -J detail \\n#SBATCH -e /mnt/home/pleung/logs/slurm_logs/detail-%J.err \\n#SBATCH -o /mnt/home/pleung/logs/slurm_logs/detail-%J.out \\n#SBATCH -p {queue} \\n#SBATCH --mem=4G \\n\\nJOB_ID=${jid} \\nCMD=$(sed -n \"${sid}\" {tasklist}) \\necho \"${c}\" | bash\"\"\".format(\n",
    "        queue=\"backfill\", jid=jid, sid=sid, tasklist=tasklist, c=\"{CMD}\"\n",
    "    )\n",
    "    shell = f\"03_detail_{j}.sh\"\n",
    "    with open(shell, \"w+\") as f:\n",
    "        print(run_sh, file=f)\n",
    "    st = os.stat(shell)\n",
    "    os.chmod(shell, st.st_mode | stat.S_IEXEC)\n",
    "    with open(f\"03_detail_{j}.cmds\", \"a+\") as f:\n",
    "        outpath = os.path.join(os.getcwd(), f\"03_detail_{j}\")\n",
    "        full_outpath = os.path.join(os.getcwd(), outpath, f\"{k}\".zfill(4))\n",
    "        args_ = \" \".join([\" \".join([k, str(v)]) for k, v in tasks.items()])\n",
    "        cmd = f\"mkdir -p {full_outpath}; cd {full_outpath}; {detail} {args_}\"\n",
    "        print(cmd, file=f)\n",
    "\n",
    "# Let's go\n",
    "print(\"Run the following commands\")\n",
    "for i in range(5):\n",
    "    print(f\"sbatch -a 1-$(cat 03_detail_{i}.cmds | wc -l) 03_detail_{i}.sh\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Now need to retrieve the JSONs containing scores for the interface design runs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "reading 100007 runs from 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100007/100007 [00:21<00:00, 4688.77it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "reading 99999 runs from 1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 99999/99999 [00:21<00:00, 4547.84it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "reading 100009 runs from 2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100009/100009 [00:19<00:00, 5179.58it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "reading 99961 runs from 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 99961/99961 [00:19<00:00, 5079.08it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "reading 47620 runs from 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 47620/47620 [00:32<00:00, 1459.46it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 2min 11s, sys: 32.7 s, total: 2min 44s\n",
      "Wall time: 3min 56s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "import json, time\n",
    "\n",
    "\n",
    "output_path = os.path.join(os.getcwd(), \"03_filter\")\n",
    "os.makedirs(output_path, exist_ok=True)\n",
    "targets = range(0,5)\n",
    "for target in targets:\n",
    "    output_paths = glob(os.path.join(os.getcwd(), f\"03_detail_{target}/*/*.json\"))\n",
    "    print(f\"reading {len(output_paths)} runs from {target}\")\n",
    "    time.sleep(0.5)\n",
    "    scores = {}\n",
    "    for path in tqdm(output_paths):\n",
    "        pdb = path.replace(\"json\", \"pdb.bz2\")\n",
    "        key = f\"{pdb}\"\n",
    "        with open(path, \"r\") as f:\n",
    "            try:\n",
    "                values = json.load(f)\n",
    "            except:\n",
    "                print(path)\n",
    "        scores[key] = values\n",
    "    scores_df = pd.DataFrame(scores)\n",
    "    scores_df = scores_df.T\n",
    "    output_file = os.path.join(output_path, f\"{target}_scores.json\")\n",
    "    scores_df.to_json(output_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reread dumped scorefiles\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 5/5 [01:37<00:00, 19.58s/it]\n"
     ]
    }
   ],
   "source": [
    "targets = range(0, 5)\n",
    "rerun_dfs = {}\n",
    "output_path = os.path.join(os.getcwd(), \"03_filter\")\n",
    "for target in tqdm(targets):\n",
    "    scores = os.path.join(output_path, f\"{target}_scores.json\")\n",
    "    rerun_dfs[(str(target))] = pd.read_json(scores)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot metrics by target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def row2state(row):\n",
    "    state = (\n",
    "        row[\"parent\"]\n",
    "        + \"_p_\"\n",
    "        + str(int(row[\"pivot_helix\"]))\n",
    "        + \"_s_\"\n",
    "        + str(int(row[\"shift\"]))\n",
    "        + \"_d_\"\n",
    "        + str(int(row[\"docked_helix\"]))\n",
    "    )\n",
    "    return state\n",
    "\n",
    "\n",
    "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",
    "for _, df in rerun_dfs.items():\n",
    "    df[\"state\"] = df.apply(row2state, axis=1)\n",
    "    df[\"scaffold\"] = df.apply(parent2scaffold, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  0%|          | 0/5 [00:00<?, ?it/s]/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      " 20%|██        | 1/5 [00:45<03:01, 45.49s/it]/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      " 40%|████      | 2/5 [01:32<02:19, 46.43s/it]/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      " 60%|██████    | 3/5 [02:19<01:32, 46.45s/it]/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      " 80%|████████  | 4/5 [03:09<00:47, 47.97s/it]/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/pleung/.conda/envs/phil/lib/python3.8/site-packages/seaborn/distributions.py:306: UserWarning: Dataset has 0 variance; skipping density estimate.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "100%|██████████| 5/5 [03:56<00:00, 47.34s/it]\n"
     ]
    }
   ],
   "source": [
    "sns.set(\n",
    "    context=\"talk\",\n",
    "    font_scale=1.5,  # 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",
    "\n",
    "def rho(x, y, ax=None, **kwargs):\n",
    "    \"\"\"Plot the correlation coefficient in the top left hand corner of a plot.\n",
    "    https://stackoverflow.com/questions/50832204/show-correlation-values-in-pairplot-using-seaborn-in-python/50835066\n",
    "    \"\"\"\n",
    "    import scipy\n",
    "\n",
    "    r, _ = scipy.stats.pearsonr(x, y)\n",
    "    ax = ax or plt.gca()\n",
    "    # Unicode for lowercase rho (ρ)\n",
    "    rho = \"\\u03C1\"\n",
    "    ax.annotate(f\"{rho} = {r:.2f}\", xy=(0.1, 0.9), xycoords=ax.transAxes)\n",
    "\n",
    "\n",
    "def plot_unity(xdata, ydata, **kwargs):\n",
    "    \"\"\"https://stackoverflow.com/questions/48122019/how-can-i-plot-identity-lines-on-a-seaborn-pairplot\"\"\"\n",
    "    xmin, ymin = (xdata.min(), ydata.min())\n",
    "    xmax, ymax = (xdata.max(), ydata.max())\n",
    "    xpoints = np.linspace(xmin, xmax, 100)\n",
    "    ypoints = np.linspace(ymin, ymax, 100)\n",
    "    plt.gca().plot(\n",
    "        xpoints, ypoints, color=\"k\", marker=None, linestyle=\"--\", linewidth=4.0\n",
    "    )\n",
    "\n",
    "\n",
    "for target, df in tqdm(rerun_dfs.items()):\n",
    "    subset = df[df[\"ddg\"] < 0]\n",
    "    subset = subset[subset[\"ddg_hydrophobic\"] < 0]\n",
    "\n",
    "    subset = subset[\n",
    "        [\n",
    "            \"contact_molecular_surface\",\n",
    "            \"contact_patch\",\n",
    "            \"ddg\",\n",
    "            \"ddg_hydrophobic\",\n",
    "            \"dslf_fa13\",\n",
    "            \"fa_atr_pocket\",\n",
    "            \"hydrophobic_residue_contacts\",\n",
    "            \"interface_buried_sasa\",\n",
    "            \"interface_sc\",\n",
    "            \"score_per_res\",\n",
    "            \"ss_sc\",\n",
    "            \"vbuns5.0_heavy_ball_1.1D\",\n",
    "            \"parent\",\n",
    "            \"state\",\n",
    "            \"target_name\",\n",
    "        ]\n",
    "    ]\n",
    "\n",
    "    pack_subset = subset[\n",
    "        [\n",
    "            \"contact_molecular_surface\",\n",
    "            \"contact_patch\",\n",
    "            \"ddg\",\n",
    "            \"ddg_hydrophobic\",\n",
    "            \"fa_atr_pocket\",\n",
    "            \"hydrophobic_residue_contacts\",\n",
    "            \"interface_buried_sasa\",\n",
    "            \"interface_sc\",\n",
    "            \"parent\",\n",
    "            \"state\",\n",
    "            \"target_name\",\n",
    "        ]\n",
    "    ]\n",
    "\n",
    "    ax = sns.pairplot(\n",
    "        data=pack_subset.sample(frac=0.01, random_state=0),\n",
    "        hue=\"parent\",\n",
    "        corner=True,\n",
    "        height=8,\n",
    "    )\n",
    "    plt.suptitle(f\"{target}\\nCorrelation of interface metrics, split by parent\")\n",
    "    sns.despine()\n",
    "    plt.savefig(f\"figs/03_{target}_correlations_int_split_by_parent.png\")\n",
    "    plt.close()\n",
    "    ax = sns.pairplot(\n",
    "        data=pack_subset.sample(frac=0.01, random_state=0), corner=True, height=8\n",
    "    )\n",
    "    ax.map_lower(rho)\n",
    "    ax.map_offdiag(plot_unity)\n",
    "    plt.suptitle(f\"{target}\\nCorrelation of fragment metrics, with pearson R\")\n",
    "    sns.despine()\n",
    "    plt.savefig(f\"figs/03_{target}_correlations_int_pearson.png\")\n",
    "    plt.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get the designs that are short enough to be put on a twist 300nt chip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "42312 total designs\n",
      "mean sap_score_target grouped by target:\n",
      "target_name\n",
      "apoe             20.312746\n",
      "covstem          22.918475\n",
      "gip              28.940673\n",
      "glp              31.467241\n",
      "glucagon         26.893356\n",
      "neuropeptideY    29.016221\n",
      "pth              24.369147\n",
      "Name: sap_score_target, dtype: float64\n",
      "mean target_blocked_sap grouped by target:\n",
      "target_name\n",
      "apoe              3.185100\n",
      "covstem           2.774165\n",
      "gip              10.485092\n",
      "glp              12.032666\n",
      "glucagon          9.987634\n",
      "neuropeptideY     7.892746\n",
      "pth               6.364976\n",
      "Name: target_blocked_sap, dtype: float64\n",
      "mean sap_score_complex grouped by target:\n",
      "target_name\n",
      "apoe             24.309813\n",
      "covstem          15.077300\n",
      "gip              20.715004\n",
      "glp              20.977785\n",
      "glucagon         23.246712\n",
      "neuropeptideY    20.018188\n",
      "pth              24.041388\n",
      "Name: sap_score_complex, dtype: float64\n",
      "mean dSAP grouped by target:\n",
      "target_name\n",
      "apoe            -37.050028\n",
      "covstem         -35.524791\n",
      "gip             -39.530245\n",
      "glp             -41.274761\n",
      "glucagon        -38.121199\n",
      "neuropeptideY   -42.437967\n",
      "pth             -40.310327\n",
      "Name: dSAP, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "tot = 0\n",
    "dfs_to_combine = []\n",
    "for _, df in rerun_dfs.items():\n",
    "    df[\"sap_score_complex\"] = (\n",
    "        df[\"sap_score\"] - df[\"sap_score_target\"] + df[\"target_blocked_sap\"]\n",
    "    )\n",
    "    df[\"dSAP\"] = -(\n",
    "        df[\"sap_score\"]\n",
    "        + df[\"sap_score_target\"]\n",
    "        - df[\"binder_blocked_sap\"]\n",
    "        - df[\"target_blocked_sap\"]\n",
    "    )\n",
    "\n",
    "    df_filt = df[df[\"chB_start\"] < 175]\n",
    "    df_filt = df_filt.query(\n",
    "        \"(scaffold=='DHR') or (scaffold=='hDHR') or (scaffold=='TH_DHR') or (scaffold=='KH_DHR')\"\n",
    "    )\n",
    "    df_filt = df_filt[df_filt[\"rmsd\"] < 0.5]\n",
    "    df_filt = df_filt[df_filt[\"sap_score_complex\"] < 35]\n",
    "    df_filt = df_filt[df_filt[\"dSAP\"] < -15]\n",
    "    df_filt = df_filt[df_filt[\"vbuns5.0_heavy_ball_1.1D\"] < 2]\n",
    "    df_filt = df_filt[df_filt[\"ddg\"] < -40]\n",
    "    tot += len(df_filt)\n",
    "    dfs_to_combine.append(df_filt)\n",
    "\n",
    "print(str(tot), \"total designs\")\n",
    "short_df = pd.concat(dfs_to_combine)\n",
    "print(\"mean sap_score_target grouped by target:\")\n",
    "print(short_df.groupby(\"target_name\")[\"sap_score_target\"].mean())\n",
    "print(\"mean target_blocked_sap grouped by target:\")\n",
    "print(short_df.groupby(\"target_name\")[\"target_blocked_sap\"].mean())\n",
    "print(\"mean sap_score_complex grouped by target:\")\n",
    "print(short_df.groupby(\"target_name\")[\"sap_score_complex\"].mean())\n",
    "print(\"mean dSAP grouped by target:\")\n",
    "print(short_df.groupby(\"target_name\")[\"dSAP\"].mean())\n",
    "\n",
    "output_path = os.path.join(os.getcwd(), \"03_filter\")\n",
    "output_file = os.path.join(output_path, \"short_selected.json\")\n",
    "short_df.to_json(output_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get a subset of really good longer designs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "57439 total designs\n",
      "mean sap_score_target grouped by target:\n",
      "target_name\n",
      "apoe             19.829718\n",
      "covstem          23.333394\n",
      "gip              36.029853\n",
      "glp              39.069768\n",
      "glucagon         33.490593\n",
      "neuropeptideY    34.322069\n",
      "pth              30.794683\n",
      "Name: sap_score_target, dtype: float64\n",
      "mean target_blocked_sap grouped by target:\n",
      "target_name\n",
      "apoe              2.915615\n",
      "covstem           2.637791\n",
      "gip              16.329185\n",
      "glp              17.079782\n",
      "glucagon         15.737939\n",
      "neuropeptideY     9.781020\n",
      "pth              10.707211\n",
      "Name: target_blocked_sap, dtype: float64\n",
      "mean sap_score_complex grouped by target:\n",
      "target_name\n",
      "apoe             25.624150\n",
      "covstem          17.534245\n",
      "gip              22.682063\n",
      "glp              22.035558\n",
      "glucagon         23.830607\n",
      "neuropeptideY    21.997970\n",
      "pth              23.938754\n",
      "Name: sap_score_complex, dtype: float64\n",
      "mean dSAP grouped by target:\n",
      "target_name\n",
      "apoe            -37.074642\n",
      "covstem         -36.123392\n",
      "gip             -42.668322\n",
      "glp             -45.998836\n",
      "glucagon        -40.377674\n",
      "neuropeptideY   -49.093625\n",
      "pth             -44.167149\n",
      "Name: dSAP, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "tot = 0\n",
    "dfs_to_combine = []\n",
    "for _, df in rerun_dfs.items():\n",
    "    df[\"sap_score_complex\"] = (\n",
    "        df[\"sap_score\"] - df[\"sap_score_target\"] + df[\"target_blocked_sap\"]\n",
    "    )\n",
    "    df[\"dSAP\"] = -(\n",
    "        df[\"sap_score\"]\n",
    "        + df[\"sap_score_target\"]\n",
    "        - df[\"binder_blocked_sap\"]\n",
    "        - df[\"target_blocked_sap\"]\n",
    "    )\n",
    "\n",
    "    df_filt = df[df[\"chB_start\"] > 175]\n",
    "    df_filt = df_filt.query(\n",
    "        \"(scaffold=='DHR') or (scaffold=='hDHR') or (scaffold=='TH_DHR') or (scaffold=='KH_DHR')\"\n",
    "    )\n",
    "    df_filt = df_filt[df_filt[\"rmsd\"] < 0.5]\n",
    "    df_filt = df_filt[df_filt[\"sap_score_complex\"] < 30]\n",
    "    df_filt = df_filt[df_filt[\"dSAP\"] < -15]\n",
    "    df_filt = df_filt[df_filt[\"vbuns5.0_heavy_ball_1.1D\"] < 1]\n",
    "    df_filt = df_filt[df_filt[\"ddg\"] < -40]\n",
    "    tot += len(df_filt)\n",
    "    dfs_to_combine.append(df_filt)\n",
    "\n",
    "print(str(tot), \"total designs\")\n",
    "long_df = pd.concat(dfs_to_combine)\n",
    "print(\"mean sap_score_target grouped by target:\")\n",
    "print(long_df.groupby(\"target_name\")[\"sap_score_target\"].mean())\n",
    "print(\"mean target_blocked_sap grouped by target:\")\n",
    "print(long_df.groupby(\"target_name\")[\"target_blocked_sap\"].mean())\n",
    "print(\"mean sap_score_complex grouped by target:\")\n",
    "print(long_df.groupby(\"target_name\")[\"sap_score_complex\"].mean())\n",
    "print(\"mean dSAP grouped by target:\")\n",
    "print(long_df.groupby(\"target_name\")[\"dSAP\"].mean())\n",
    "\n",
    "output_path = os.path.join(os.getcwd(), \"03_filter\")\n",
    "output_file = os.path.join(output_path, \"long_selected.json\")\n",
    "long_df.to_json(output_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Make a combined list of designs to cleanup\n",
    "Need to cleanup disulfides for anything for target APOE or has bad disulfide score, then reset numbering in scores and add sequences for chA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(os.path.join(output_path, \"cleanup_short.list\"), \"w+\") as f:\n",
    "    for decoy in list(short_df.index):\n",
    "        print(decoy, file=f)\n",
    "with open(os.path.join(output_path, \"cleanup_long.list\"), \"w+\") as f:\n",
    "    for decoy in list(long_df.index):\n",
    "        print(decoy, file=f)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cleanup directory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "!mv *.cmds 03_filter; mv *.sh 03_filter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Unused blocks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "%%time\n",
    "import pyrosetta\n",
    "from pyrosetta.distributed import cluster\n",
    "import pyrosetta.distributed.io as io\n",
    "\n",
    "flags = \"\"\"\n",
    "-out:level 300\n",
    "-corrections::beta_nov16 true\n",
    "-holes:dalphaball /home/bcov/ppi/tutorial_build/main/source/external/DAlpahBall/DAlphaBall.gcc\n",
    "-indexed_structure_store:fragment_store /home/bcov/sc/scaffold_comparison/data/ss_grouped_vall_all.h5\n",
    "\"\"\"\n",
    "# pyrosetta.distributed.init(\" \".join(flags.replace(\"\\n\\t\", \" \").split()))\n",
    "pyrosetta.init(\" \".join(flags.replace(\"\\n\\t\", \" \").split()))\n",
    "\n",
    "t = detail_design(\n",
    "    None,\n",
    "    **{\n",
    "        \"-s\": \"/mnt/home/pleung/projects/peptide_binders/r0/peptide_binders/02_filter/decoys/0/0cdba3156384aca724430067c0922d72a63ec833ba196a52.pdb.bz2\",\n",
    "    }\n",
    ")"
   ]
  }
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