wfcommons_parsing.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "DXpM7fF5gN32",
   "metadata": {
    "id": "DXpM7fF5gN32"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "omCm46HZgPKi",
   "metadata": {
    "id": "omCm46HZgPKi"
   },
   "outputs": [],
   "source": [
    "!pip install -q pygraphviz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "UihtvMz3f9UC",
   "metadata": {
    "id": "UihtvMz3f9UC"
   },
   "outputs": [],
   "source": [
    "!pip install -q wfcommons"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "41bc8a0a",
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install -q parse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "62f9a49f",
   "metadata": {
    "id": "62f9a49f",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "from wfcommons.wfchef.recipes import *\n",
    "from wfcommons.wfchef.utils import *\n",
    "from wfcommons import WorkflowGenerator\n",
    "import networkx as nx\n",
    "from networkx.drawing.nx_agraph import graphviz_layout\n",
    "import matplotlib.pyplot as plt\n",
    "import requests\n",
    "from pprint import pprint\n",
    "\n",
    "from typing import List"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ZSbP4M2tgopN",
   "metadata": {
    "id": "ZSbP4M2tgopN"
   },
   "source": [
    "# The first option is to generate a synthetic workflow based on some predefined patterns\n",
    "e.g., BlastRecipe, BwaRecipe, CyclesRecipe, EpigenomicsRecipe, GenomeRecipe, MontageRecipe, SeismologyRecipe, SoykbRecipe, SrasearchRecipe. See [here](https://wfcommons.org/generator) and [here](https://github.com/wfcommons/wfcommons/tree/438983117dc9ccf8b642339d81edef2ae992e34d/wfcommons/wfgen).\n",
    "\n",
    "-- issue: the machines field won't be filled (it provides only jobs)\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "4743c37b",
   "metadata": {
    "id": "4743c37b",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "# TASKS_NUM = 25\n",
    "# generator = WorkflowGenerator(SrasearchRecipe.from_num_tasks(TASKS_NUM))\n",
    "# workflow = generator.build_workflow()\n",
    "# DAG_synthetic = workflow.to_nx_digraph()\n",
    "# workflow.write_json('srasearch-workflow.json')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "jmhzVQ_47bMH",
   "metadata": {
    "id": "jmhzVQ_47bMH",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "HbGxVp0XkWku",
   "metadata": {
    "id": "HbGxVp0XkWku",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "def display_graph(graph):\n",
    "  pos = graphviz_layout(graph, prog='dot')\n",
    "  plt.figure(figsize=(14,10)) \n",
    "  nx.draw(graph, pos=pos, node_size=2000, with_labels=True, arrows=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "XYG4dNQrkZ9g",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 751
    },
    "id": "XYG4dNQrkZ9g",
    "outputId": "17e526b4-0ccf-4e71-e11a-0fa884d6144b",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "# display_graph(DAG_synthetic)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "mqN8LjBchyYF",
   "metadata": {
    "id": "mqN8LjBchyYF"
   },
   "source": [
    "# The second option is to read a workflow from a file\n",
    "There are a few available workflow instances on Github: [pegasus-instances](https://github.com/wfcommons/pegasus-instances) and [makeflow-instances](https://github.com/wfcommons/makeflow-instances). There're json files where jobs are already assigned to machines."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "b4acc22b",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "b4acc22b",
    "outputId": "0b56bcad-70b4-4e4b-b593-b2b65645c703",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'name': '1000genome-20200401T153108Z-0', 'description': 'Trace generated with wrench-pegasus-parser.py from http://wrench-project.org', 'createdAt': '2020-04-01T20:23:49.256573Z', 'schemaVersion': '1.2', 'wms': {'url': 'http://pegasus.isi.edu', 'version': '4.9.3', 'name': 'Pegasus'}, 'author': {'name': 'rafsilva', 'email': 'support@wrench-project.org'}, 'workflow': {'makespan': 2290.0, 'jobs': [{'name': 'individuals_ID0000001', 'type': 'compute', 'runtime': 61.593, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr1.100000.vcf', 'size': 1014258222}, {'link': 'output', 'name': 'chr1n-1-1001.tar.gz', 'size': 27959}], 'avgCPU': 143.3507, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000001', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr1.100000.vcf', '1', '1', '1001', '10000']}}, {'name': 'individuals_ID0000002', 'type': 'compute', 'runtime': 65.301, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr1.100000.vcf', 'size': 1014258222}, {'link': 'output', 'name': 'chr1n-1001-2001.tar.gz', 'size': 28113}], 'avgCPU': 131.5401, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000002', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr1.100000.vcf', '1', '1001', '2001', '10000']}}, {'name': 'individuals_ID0000003', 'type': 'compute', 'runtime': 65.667, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr1.100000.vcf', 'size': 1014258222}, {'link': 'output', 'name': 'chr1n-2001-3001.tar.gz', 'size': 28094}], 'avgCPU': 130.9623, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000003', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr1.100000.vcf', '1', '2001', '3001', '10000']}}, {'name': 'individuals_ID0000004', 'type': 'compute', 'runtime': 69.304, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr1.100000.vcf', 'size': 1014258222}, {'link': 'output', 'name': 'chr1n-3001-4001.tar.gz', 'size': 27874}], 'avgCPU': 125.8672, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000004', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr1.100000.vcf', '1', '3001', '4001', '10000']}}, {'name': 'individuals_ID0000005', 'type': 'compute', 'runtime': 58.227, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr1.100000.vcf', 'size': 1014258222}, {'link': 'output', 'name': 'chr1n-4001-5001.tar.gz', 'size': 27956}], 'avgCPU': 166.7354, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000005', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr1.100000.vcf', '1', '4001', '5001', '10000']}}, {'name': 'individuals_ID0000006', 'type': 'compute', 'runtime': 70.967, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr1.100000.vcf', 'size': 1014258222}, {'link': 'output', 'name': 'chr1n-5001-6001.tar.gz', 'size': 28169}], 'avgCPU': 133.1393, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000006', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr1.100000.vcf', '1', '5001', '6001', '10000']}}, {'name': 'individuals_ID0000007', 'type': 'compute', 'runtime': 66.31, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr1.100000.vcf', 'size': 1014258222}, {'link': 'output', 'name': 'chr1n-6001-7001.tar.gz', 'size': 28098}], 'avgCPU': 143.5485, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000007', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr1.100000.vcf', '1', '6001', '7001', '10000']}}, {'name': 'individuals_ID0000008', 'type': 'compute', 'runtime': 69.365, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr1.100000.vcf', 'size': 1014258222}, {'link': 'output', 'name': 'chr1n-7001-8001.tar.gz', 'size': 27991}], 'avgCPU': 126.1184, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000008', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr1.100000.vcf', '1', '7001', '8001', '10000']}}, {'name': 'individuals_ID0000009', 'type': 'compute', 'runtime': 68.145, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr1.100000.vcf', 'size': 1014258222}, {'link': 'output', 'name': 'chr1n-8001-9001.tar.gz', 'size': 27894}], 'avgCPU': 128.0637, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000009', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr1.100000.vcf', '1', '8001', '9001', '10000']}}, {'name': 'individuals_ID0000010', 'type': 'compute', 'runtime': 69.39, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr1.100000.vcf', 'size': 1014258222}, {'link': 'output', 'name': 'chr1n-9001-10001.tar.gz', 'size': 28081}], 'avgCPU': 126.7459, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000010', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr1.100000.vcf', '1', '9001', '10001', '10000']}}, {'name': 'individuals_merge_ID0000011', 'type': 'compute', 'runtime': 44.705, 'parents': ['individuals_ID0000004', 'individuals_ID0000005', 'individuals_ID0000006', 'individuals_ID0000007', 'individuals_ID0000001', 'individuals_ID0000002', 'individuals_ID0000003', 'individuals_ID0000008', 'individuals_ID0000009', 'individuals_ID0000010'], 'files': [{'link': 'input', 'name': 'chr1n-2001-3001.tar.gz', 'size': 28094}, {'link': 'input', 'name': 'chr1n-5001-6001.tar.gz', 'size': 28169}, {'link': 'input', 'name': 'chr1n-3001-4001.tar.gz', 'size': 27874}, {'link': 'input', 'name': 'chr1n-9001-10001.tar.gz', 'size': 28081}, {'link': 'input', 'name': 'chr1n-7001-8001.tar.gz', 'size': 27991}, {'link': 'input', 'name': 'chr1n-1-1001.tar.gz', 'size': 27959}, {'link': 'input', 'name': 'chr1n-4001-5001.tar.gz', 'size': 27956}, {'link': 'input', 'name': 'chr1n-1001-2001.tar.gz', 'size': 28113}, {'link': 'input', 'name': 'chr1n-6001-7001.tar.gz', 'size': 28098}, {'link': 'input', 'name': 'chr1n-8001-9001.tar.gz', 'size': 27894}, {'link': 'output', 'name': 'chr1n.tar.gz', 'size': 24897}], 'avgCPU': 86.4288, 'machine': 'pegasus-2', 'priority': 30, 'id': 'ID0000011', 'category': 'individuals_merge', 'command': {'program': 'individuals_merge', 'arguments': ['1', 'chr1n-1-1001.tar.gz', 'chr1n-1001-2001.tar.gz', 'chr1n-2001-3001.tar.gz', 'chr1n-3001-4001.tar.gz', 'chr1n-4001-5001.tar.gz', 'chr1n-5001-6001.tar.gz', 'chr1n-6001-7001.tar.gz', 'chr1n-7001-8001.tar.gz', 'chr1n-8001-9001.tar.gz', 'chr1n-9001-10001.tar.gz']}}, {'name': 'sifting_ID0000012', 'type': 'compute', 'runtime': 7.03, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr1.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', 'size': 1580478841}, {'link': 'output', 'name': 'sifted.SIFT.chr1.txt', 'size': 2126612}], 'avgCPU': 30.5405, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000012', 'category': 'sifting', 'command': {'program': 'sifting', 'arguments': ['ALL.chr1.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', '1']}}, {'name': 'individuals_ID0000013', 'type': 'compute', 'runtime': 51.398, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr2.100000.vcf', 'size': 1014229237}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr2n-1-1001.tar.gz', 'size': 27427}], 'avgCPU': 181.6257, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000013', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr2.100000.vcf', '2', '1', '1001', '10000']}}, {'name': 'individuals_ID0000014', 'type': 'compute', 'runtime': 53.474, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr2.100000.vcf', 'size': 1014229237}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr2n-1001-2001.tar.gz', 'size': 27899}], 'avgCPU': 175.072, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000014', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr2.100000.vcf', '2', '1001', '2001', '10000']}}, {'name': 'individuals_ID0000015', 'type': 'compute', 'runtime': 53.394, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr2.100000.vcf', 'size': 1014229237}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr2n-2001-3001.tar.gz', 'size': 27872}], 'avgCPU': 176.8176, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000015', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr2.100000.vcf', '2', '2001', '3001', '10000']}}, {'name': 'individuals_ID0000016', 'type': 'compute', 'runtime': 53.395, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr2.100000.vcf', 'size': 1014229237}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr2n-3001-4001.tar.gz', 'size': 27974}], 'avgCPU': 176.5708, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000016', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr2.100000.vcf', '2', '3001', '4001', '10000']}}, {'name': 'individuals_ID0000017', 'type': 'compute', 'runtime': 55.255, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr2.100000.vcf', 'size': 1014229237}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr2n-4001-5001.tar.gz', 'size': 28074}], 'avgCPU': 169.9448, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000017', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr2.100000.vcf', '2', '4001', '5001', '10000']}}, {'name': 'individuals_ID0000018', 'type': 'compute', 'runtime': 55.118, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr2.100000.vcf', 'size': 1014229237}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr2n-5001-6001.tar.gz', 'size': 28044}], 'avgCPU': 169.8102, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000018', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr2.100000.vcf', '2', '5001', '6001', '10000']}}, {'name': 'individuals_ID0000019', 'type': 'compute', 'runtime': 52.542, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr2.100000.vcf', 'size': 1014229237}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr2n-6001-7001.tar.gz', 'size': 27585}], 'avgCPU': 179.287, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000019', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr2.100000.vcf', '2', '6001', '7001', '10000']}}, {'name': 'individuals_ID0000020', 'type': 'compute', 'runtime': 60.443, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr2.100000.vcf', 'size': 1014229237}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr2n-7001-8001.tar.gz', 'size': 27787}], 'avgCPU': 153.3958, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000020', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr2.100000.vcf', '2', '7001', '8001', '10000']}}, {'name': 'individuals_ID0000021', 'type': 'compute', 'runtime': 61.484, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr2.100000.vcf', 'size': 1014229237}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr2n-8001-9001.tar.gz', 'size': 27626}], 'avgCPU': 149.5674, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000021', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr2.100000.vcf', '2', '8001', '9001', '10000']}}, {'name': 'individuals_ID0000022', 'type': 'compute', 'runtime': 55.467, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr2.100000.vcf', 'size': 1014229237}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr2n-9001-10001.tar.gz', 'size': 28013}], 'avgCPU': 171.3686, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000022', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr2.100000.vcf', '2', '9001', '10001', '10000']}}, {'name': 'individuals_merge_ID0000023', 'type': 'compute', 'runtime': 67.898, 'parents': ['individuals_ID0000015', 'individuals_ID0000016', 'individuals_ID0000017', 'individuals_ID0000018', 'individuals_ID0000013', 'individuals_ID0000014', 'individuals_ID0000019', 'individuals_ID0000022', 'individuals_ID0000020', 'individuals_ID0000021'], 'files': [{'link': 'input', 'name': 'chr2n-7001-8001.tar.gz', 'size': 27787}, {'link': 'input', 'name': 'chr2n-4001-5001.tar.gz', 'size': 28074}, {'link': 'input', 'name': 'chr2n-2001-3001.tar.gz', 'size': 27872}, {'link': 'input', 'name': 'chr2n-1-1001.tar.gz', 'size': 27427}, {'link': 'input', 'name': 'chr2n-3001-4001.tar.gz', 'size': 27974}, {'link': 'input', 'name': 'chr2n-9001-10001.tar.gz', 'size': 28013}, {'link': 'input', 'name': 'chr2n-5001-6001.tar.gz', 'size': 28044}, {'link': 'input', 'name': 'chr2n-6001-7001.tar.gz', 'size': 27585}, {'link': 'input', 'name': 'chr2n-1001-2001.tar.gz', 'size': 27899}, {'link': 'input', 'name': 'chr2n-8001-9001.tar.gz', 'size': 27626}, {'link': 'output', 'name': 'chr2n.tar.gz', 'size': 25272}], 'avgCPU': 54.0031, 'machine': 'pegasus-5', 'priority': 30, 'id': 'ID0000023', 'category': 'individuals_merge', 'command': {'program': 'individuals_merge', 'arguments': ['2', 'chr2n-1-1001.tar.gz', 'chr2n-1001-2001.tar.gz', 'chr2n-2001-3001.tar.gz', 'chr2n-3001-4001.tar.gz', 'chr2n-4001-5001.tar.gz', 'chr2n-5001-6001.tar.gz', 'chr2n-6001-7001.tar.gz', 'chr2n-7001-8001.tar.gz', 'chr2n-8001-9001.tar.gz', 'chr2n-9001-10001.tar.gz']}}, {'name': 'sifting_ID0000024', 'type': 'compute', 'runtime': 7.309, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr2.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', 'size': 1708156254}, {'link': 'output', 'name': 'sifted.SIFT.chr2.txt', 'size': 1365482}], 'avgCPU': 25.0787, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000024', 'category': 'sifting', 'command': {'program': 'sifting', 'arguments': ['ALL.chr2.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', '2']}}, {'name': 'individuals_ID0000025', 'type': 'compute', 'runtime': 56.619, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr3.100000.vcf', 'size': 1014224801}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr3n-1-1001.tar.gz', 'size': 28013}], 'avgCPU': 176.9583, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000025', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr3.100000.vcf', '3', '1', '1001', '10000']}}, {'name': 'individuals_ID0000026', 'type': 'compute', 'runtime': 59.886, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr3.100000.vcf', 'size': 1014224801}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr3n-1001-2001.tar.gz', 'size': 28076}], 'avgCPU': 156.2586, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000026', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr3.100000.vcf', '3', '1001', '2001', '10000']}}, {'name': 'individuals_ID0000027', 'type': 'compute', 'runtime': 60.035, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr3.100000.vcf', 'size': 1014224801}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr3n-2001-3001.tar.gz', 'size': 27988}], 'avgCPU': 157.2932, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000027', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr3.100000.vcf', '3', '2001', '3001', '10000']}}, {'name': 'individuals_ID0000028', 'type': 'compute', 'runtime': 58.735, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr3.100000.vcf', 'size': 1014224801}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr3n-3001-4001.tar.gz', 'size': 27559}], 'avgCPU': 164.9579, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000028', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr3.100000.vcf', '3', '3001', '4001', '10000']}}, {'name': 'individuals_ID0000029', 'type': 'compute', 'runtime': 57.079, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr3.100000.vcf', 'size': 1014224801}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr3n-4001-5001.tar.gz', 'size': 27893}], 'avgCPU': 173.7189, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000029', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr3.100000.vcf', '3', '4001', '5001', '10000']}}, {'name': 'individuals_ID0000030', 'type': 'compute', 'runtime': 57.79, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr3.100000.vcf', 'size': 1014224801}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr3n-5001-6001.tar.gz', 'size': 27995}], 'avgCPU': 177.9685, 'machine': 'pegasus-3', 'priority': 20, 'id': 'ID0000030', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr3.100000.vcf', '3', '5001', '6001', '10000']}}, {'name': 'individuals_ID0000031', 'type': 'compute', 'runtime': 57.233, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr3.100000.vcf', 'size': 1014224801}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr3n-6001-7001.tar.gz', 'size': 27976}], 'avgCPU': 180.0867, 'machine': 'pegasus-3', 'priority': 20, 'id': 'ID0000031', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr3.100000.vcf', '3', '6001', '7001', '10000']}}, {'name': 'individuals_ID0000032', 'type': 'compute', 'runtime': 57.047, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr3.100000.vcf', 'size': 1014224801}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr3n-7001-8001.tar.gz', 'size': 27696}], 'avgCPU': 179.5502, 'machine': 'pegasus-3', 'priority': 20, 'id': 'ID0000032', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr3.100000.vcf', '3', '7001', '8001', '10000']}}, {'name': 'individuals_ID0000033', 'type': 'compute', 'runtime': 57.504, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr3.100000.vcf', 'size': 1014224801}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr3n-8001-9001.tar.gz', 'size': 27903}], 'avgCPU': 174.1722, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000033', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr3.100000.vcf', '3', '8001', '9001', '10000']}}, {'name': 'individuals_ID0000034', 'type': 'compute', 'runtime': 57.406, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr3.100000.vcf', 'size': 1014224801}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr3n-9001-10001.tar.gz', 'size': 27943}], 'avgCPU': 174.0567, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000034', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr3.100000.vcf', '3', '9001', '10001', '10000']}}, {'name': 'individuals_merge_ID0000035', 'type': 'compute', 'runtime': 36.827, 'parents': ['individuals_ID0000026', 'individuals_ID0000027', 'individuals_ID0000028', 'individuals_ID0000029', 'individuals_ID0000025', 'individuals_ID0000033', 'individuals_ID0000034', 'individuals_ID0000030', 'individuals_ID0000031', 'individuals_ID0000032'], 'files': [{'link': 'input', 'name': 'chr3n-1001-2001.tar.gz', 'size': 28076}, {'link': 'input', 'name': 'chr3n-3001-4001.tar.gz', 'size': 27559}, {'link': 'input', 'name': 'chr3n-2001-3001.tar.gz', 'size': 27988}, {'link': 'input', 'name': 'chr3n-4001-5001.tar.gz', 'size': 27893}, {'link': 'input', 'name': 'chr3n-1-1001.tar.gz', 'size': 28013}, {'link': 'input', 'name': 'chr3n-9001-10001.tar.gz', 'size': 27943}, {'link': 'input', 'name': 'chr3n-5001-6001.tar.gz', 'size': 27995}, {'link': 'input', 'name': 'chr3n-7001-8001.tar.gz', 'size': 27696}, {'link': 'input', 'name': 'chr3n-8001-9001.tar.gz', 'size': 27903}, {'link': 'input', 'name': 'chr3n-6001-7001.tar.gz', 'size': 27976}, {'link': 'output', 'name': 'chr3n.tar.gz', 'size': 24372}], 'avgCPU': 107.8095, 'machine': 'pegasus-4', 'priority': 30, 'id': 'ID0000035', 'category': 'individuals_merge', 'command': {'program': 'individuals_merge', 'arguments': ['3', 'chr3n-1-1001.tar.gz', 'chr3n-1001-2001.tar.gz', 'chr3n-2001-3001.tar.gz', 'chr3n-3001-4001.tar.gz', 'chr3n-4001-5001.tar.gz', 'chr3n-5001-6001.tar.gz', 'chr3n-6001-7001.tar.gz', 'chr3n-7001-8001.tar.gz', 'chr3n-8001-9001.tar.gz', 'chr3n-9001-10001.tar.gz']}}, {'name': 'sifting_ID0000036', 'type': 'compute', 'runtime': 1.202, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr3.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', 'size': 1411549292}, {'link': 'output', 'name': 'sifted.SIFT.chr3.txt', 'size': 1132161}], 'avgCPU': 113.1448, 'machine': 'pegasus-3', 'priority': 20, 'id': 'ID0000036', 'category': 'sifting', 'command': {'program': 'sifting', 'arguments': ['ALL.chr3.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', '3']}}, {'name': 'individuals_ID0000037', 'type': 'compute', 'runtime': 52.028, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr4.100000.vcf', 'size': 1014216950}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr4n-1-1001.tar.gz', 'size': 27765}], 'avgCPU': 163.2794, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000037', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr4.100000.vcf', '4', '1', '1001', '10000']}}, {'name': 'individuals_ID0000038', 'type': 'compute', 'runtime': 52.139, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr4.100000.vcf', 'size': 1014216950}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr4n-1001-2001.tar.gz', 'size': 27783}], 'avgCPU': 163.2866, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000038', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr4.100000.vcf', '4', '1001', '2001', '10000']}}, {'name': 'individuals_ID0000039', 'type': 'compute', 'runtime': 52.175, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr4.100000.vcf', 'size': 1014216950}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr4n-2001-3001.tar.gz', 'size': 27800}], 'avgCPU': 163.517, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000039', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr4.100000.vcf', '4', '2001', '3001', '10000']}}, {'name': 'individuals_ID0000040', 'type': 'compute', 'runtime': 54.127, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr4.100000.vcf', 'size': 1014216950}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr4n-3001-4001.tar.gz', 'size': 27733}], 'avgCPU': 157.1027, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000040', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr4.100000.vcf', '4', '3001', '4001', '10000']}}, {'name': 'individuals_ID0000041', 'type': 'compute', 'runtime': 53.828, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr4.100000.vcf', 'size': 1014216950}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr4n-4001-5001.tar.gz', 'size': 27787}], 'avgCPU': 158.3971, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000041', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr4.100000.vcf', '4', '4001', '5001', '10000']}}, {'name': 'individuals_ID0000042', 'type': 'compute', 'runtime': 56.099, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr4.100000.vcf', 'size': 1014216950}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr4n-5001-6001.tar.gz', 'size': 27766}], 'avgCPU': 152.9475, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000042', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr4.100000.vcf', '4', '5001', '6001', '10000']}}, {'name': 'individuals_ID0000043', 'type': 'compute', 'runtime': 53.075, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr4.100000.vcf', 'size': 1014216950}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr4n-6001-7001.tar.gz', 'size': 27637}], 'avgCPU': 176.2657, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000043', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr4.100000.vcf', '4', '6001', '7001', '10000']}}, {'name': 'individuals_ID0000044', 'type': 'compute', 'runtime': 52.632, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr4.100000.vcf', 'size': 1014216950}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr4n-7001-8001.tar.gz', 'size': 27758}], 'avgCPU': 161.8426, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000044', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr4.100000.vcf', '4', '7001', '8001', '10000']}}, {'name': 'individuals_ID0000045', 'type': 'compute', 'runtime': 52.834, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr4.100000.vcf', 'size': 1014216950}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr4n-8001-9001.tar.gz', 'size': 27795}], 'avgCPU': 162.3008, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000045', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr4.100000.vcf', '4', '8001', '9001', '10000']}}, {'name': 'individuals_ID0000046', 'type': 'compute', 'runtime': 51.906, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr4.100000.vcf', 'size': 1014216950}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr4n-9001-10001.tar.gz', 'size': 27722}], 'avgCPU': 163.2278, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000046', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr4.100000.vcf', '4', '9001', '10001', '10000']}}, {'name': 'individuals_merge_ID0000047', 'type': 'compute', 'runtime': 42.246, 'parents': ['individuals_ID0000037', 'individuals_ID0000038', 'individuals_ID0000039', 'individuals_ID0000044', 'individuals_ID0000045', 'individuals_ID0000046', 'individuals_ID0000040', 'individuals_ID0000041', 'individuals_ID0000042', 'individuals_ID0000043'], 'files': [{'link': 'input', 'name': 'chr4n-3001-4001.tar.gz', 'size': 27733}, {'link': 'input', 'name': 'chr4n-1-1001.tar.gz', 'size': 27765}, {'link': 'input', 'name': 'chr4n-5001-6001.tar.gz', 'size': 27766}, {'link': 'input', 'name': 'chr4n-2001-3001.tar.gz', 'size': 27800}, {'link': 'input', 'name': 'chr4n-9001-10001.tar.gz', 'size': 27722}, {'link': 'input', 'name': 'chr4n-1001-2001.tar.gz', 'size': 27783}, {'link': 'input', 'name': 'chr4n-6001-7001.tar.gz', 'size': 27637}, {'link': 'input', 'name': 'chr4n-8001-9001.tar.gz', 'size': 27795}, {'link': 'input', 'name': 'chr4n-7001-8001.tar.gz', 'size': 27758}, {'link': 'input', 'name': 'chr4n-4001-5001.tar.gz', 'size': 27787}, {'link': 'output', 'name': 'chr4n.tar.gz', 'size': 25083}], 'avgCPU': 88.7492, 'machine': 'pegasus-5', 'priority': 30, 'id': 'ID0000047', 'category': 'individuals_merge', 'command': {'program': 'individuals_merge', 'arguments': ['4', 'chr4n-1-1001.tar.gz', 'chr4n-1001-2001.tar.gz', 'chr4n-2001-3001.tar.gz', 'chr4n-3001-4001.tar.gz', 'chr4n-4001-5001.tar.gz', 'chr4n-5001-6001.tar.gz', 'chr4n-6001-7001.tar.gz', 'chr4n-7001-8001.tar.gz', 'chr4n-8001-9001.tar.gz', 'chr4n-9001-10001.tar.gz']}}, {'name': 'sifting_ID0000048', 'type': 'compute', 'runtime': 3.399, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr4.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', 'size': 1343521128}, {'link': 'output', 'name': 'sifted.SIFT.chr4.txt', 'size': 806968}], 'avgCPU': 41.8653, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000048', 'category': 'sifting', 'command': {'program': 'sifting', 'arguments': ['ALL.chr4.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', '4']}}, {'name': 'individuals_ID0000049', 'type': 'compute', 'runtime': 64.37, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr5.100000.vcf', 'size': 1014267665}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr5n-1-1001.tar.gz', 'size': 28451}], 'avgCPU': 131.1636, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000049', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr5.100000.vcf', '5', '1', '1001', '10000']}}, {'name': 'individuals_ID0000050', 'type': 'compute', 'runtime': 53.778, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr5.100000.vcf', 'size': 1014267665}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr5n-1001-2001.tar.gz', 'size': 27988}], 'avgCPU': 175.2966, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000050', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr5.100000.vcf', '5', '1001', '2001', '10000']}}, {'name': 'individuals_ID0000051', 'type': 'compute', 'runtime': 67.731, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr5.100000.vcf', 'size': 1014267665}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr5n-2001-3001.tar.gz', 'size': 28117}], 'avgCPU': 125.7164, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000051', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr5.100000.vcf', '5', '2001', '3001', '10000']}}, {'name': 'individuals_ID0000052', 'type': 'compute', 'runtime': 68.399, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr5.100000.vcf', 'size': 1014267665}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr5n-3001-4001.tar.gz', 'size': 27972}], 'avgCPU': 123.955, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000052', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr5.100000.vcf', '5', '3001', '4001', '10000']}}, {'name': 'individuals_ID0000053', 'type': 'compute', 'runtime': 66.862, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr5.100000.vcf', 'size': 1014267665}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr5n-4001-5001.tar.gz', 'size': 28126}], 'avgCPU': 126.61, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000053', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr5.100000.vcf', '5', '4001', '5001', '10000']}}, {'name': 'individuals_ID0000054', 'type': 'compute', 'runtime': 69.01, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr5.100000.vcf', 'size': 1014267665}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr5n-5001-6001.tar.gz', 'size': 27987}], 'avgCPU': 122.3794, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000054', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr5.100000.vcf', '5', '5001', '6001', '10000']}}, {'name': 'individuals_ID0000055', 'type': 'compute', 'runtime': 65.87, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr5.100000.vcf', 'size': 1014267665}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr5n-6001-7001.tar.gz', 'size': 28263}], 'avgCPU': 128.7005, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000055', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr5.100000.vcf', '5', '6001', '7001', '10000']}}, {'name': 'individuals_ID0000056', 'type': 'compute', 'runtime': 64.935, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr5.100000.vcf', 'size': 1014267665}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr5n-7001-8001.tar.gz', 'size': 28329}], 'avgCPU': 130.0562, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000056', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr5.100000.vcf', '5', '7001', '8001', '10000']}}, {'name': 'individuals_ID0000057', 'type': 'compute', 'runtime': 65.43, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr5.100000.vcf', 'size': 1014267665}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr5n-8001-9001.tar.gz', 'size': 28267}], 'avgCPU': 128.3952, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000057', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr5.100000.vcf', '5', '8001', '9001', '10000']}}, {'name': 'individuals_ID0000058', 'type': 'compute', 'runtime': 65.852, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr5.100000.vcf', 'size': 1014267665}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr5n-9001-10001.tar.gz', 'size': 28270}], 'avgCPU': 128.5716, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000058', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr5.100000.vcf', '5', '9001', '10001', '10000']}}, {'name': 'individuals_merge_ID0000059', 'type': 'compute', 'runtime': 39.738, 'parents': ['individuals_ID0000049', 'individuals_ID0000055', 'individuals_ID0000056', 'individuals_ID0000057', 'individuals_ID0000058', 'individuals_ID0000051', 'individuals_ID0000052', 'individuals_ID0000053', 'individuals_ID0000054', 'individuals_ID0000050'], 'files': [{'link': 'input', 'name': 'chr5n-3001-4001.tar.gz', 'size': 27972}, {'link': 'input', 'name': 'chr5n-4001-5001.tar.gz', 'size': 28126}, {'link': 'input', 'name': 'chr5n-6001-7001.tar.gz', 'size': 28263}, {'link': 'input', 'name': 'chr5n-2001-3001.tar.gz', 'size': 28117}, {'link': 'input', 'name': 'chr5n-7001-8001.tar.gz', 'size': 28329}, {'link': 'input', 'name': 'chr5n-1-1001.tar.gz', 'size': 28451}, {'link': 'input', 'name': 'chr5n-1001-2001.tar.gz', 'size': 27988}, {'link': 'input', 'name': 'chr5n-9001-10001.tar.gz', 'size': 28270}, {'link': 'input', 'name': 'chr5n-8001-9001.tar.gz', 'size': 28267}, {'link': 'input', 'name': 'chr5n-5001-6001.tar.gz', 'size': 27987}, {'link': 'output', 'name': 'chr5n.tar.gz', 'size': 24353}], 'avgCPU': 98.6008, 'machine': 'pegasus-2', 'priority': 30, 'id': 'ID0000059', 'category': 'individuals_merge', 'command': {'program': 'individuals_merge', 'arguments': ['5', 'chr5n-1-1001.tar.gz', 'chr5n-1001-2001.tar.gz', 'chr5n-2001-3001.tar.gz', 'chr5n-3001-4001.tar.gz', 'chr5n-4001-5001.tar.gz', 'chr5n-5001-6001.tar.gz', 'chr5n-6001-7001.tar.gz', 'chr5n-7001-8001.tar.gz', 'chr5n-8001-9001.tar.gz', 'chr5n-9001-10001.tar.gz']}}, {'name': 'sifting_ID0000060', 'type': 'compute', 'runtime': 1.299, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr5.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', 'size': 1248725682}, {'link': 'output', 'name': 'sifted.SIFT.chr5.txt', 'size': 922870}], 'avgCPU': 98.4604, 'machine': 'pegasus-3', 'priority': 20, 'id': 'ID0000060', 'category': 'sifting', 'command': {'program': 'sifting', 'arguments': ['ALL.chr5.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', '5']}}, {'name': 'individuals_ID0000061', 'type': 'compute', 'runtime': 52.273, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr6.100000.vcf', 'size': 1014224690}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6n-1-1001.tar.gz', 'size': 27971}], 'avgCPU': 177.585, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000061', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr6.100000.vcf', '6', '1', '1001', '10000']}}, {'name': 'individuals_ID0000062', 'type': 'compute', 'runtime': 83.174, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr6.100000.vcf', 'size': 1014224690}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6n-1001-2001.tar.gz', 'size': 28786}], 'avgCPU': 105.2456, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000062', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr6.100000.vcf', '6', '1001', '2001', '10000']}}, {'name': 'individuals_ID0000063', 'type': 'compute', 'runtime': 79.449, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr6.100000.vcf', 'size': 1014224690}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6n-2001-3001.tar.gz', 'size': 28738}], 'avgCPU': 110.2217, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000063', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr6.100000.vcf', '6', '2001', '3001', '10000']}}, {'name': 'individuals_ID0000064', 'type': 'compute', 'runtime': 86.233, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr6.100000.vcf', 'size': 1014224690}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6n-3001-4001.tar.gz', 'size': 28808}], 'avgCPU': 101.3939, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000064', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr6.100000.vcf', '6', '3001', '4001', '10000']}}, {'name': 'individuals_ID0000065', 'type': 'compute', 'runtime': 50.291, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr6.100000.vcf', 'size': 1014224690}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6n-4001-5001.tar.gz', 'size': 27790}], 'avgCPU': 179.0996, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000065', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr6.100000.vcf', '6', '4001', '5001', '10000']}}, {'name': 'individuals_ID0000066', 'type': 'compute', 'runtime': 83.541, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr6.100000.vcf', 'size': 1014224690}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6n-5001-6001.tar.gz', 'size': 28781}], 'avgCPU': 104.7151, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000066', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr6.100000.vcf', '6', '5001', '6001', '10000']}}, {'name': 'individuals_ID0000067', 'type': 'compute', 'runtime': 85.69, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr6.100000.vcf', 'size': 1014224690}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6n-6001-7001.tar.gz', 'size': 28767}], 'avgCPU': 102.201, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000067', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr6.100000.vcf', '6', '6001', '7001', '10000']}}, {'name': 'individuals_ID0000068', 'type': 'compute', 'runtime': 83.64, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr6.100000.vcf', 'size': 1014224690}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6n-7001-8001.tar.gz', 'size': 28804}], 'avgCPU': 105.0132, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000068', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr6.100000.vcf', '6', '7001', '8001', '10000']}}, {'name': 'individuals_ID0000069', 'type': 'compute', 'runtime': 85.686, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr6.100000.vcf', 'size': 1014224690}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6n-8001-9001.tar.gz', 'size': 28776}], 'avgCPU': 102.1065, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000069', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr6.100000.vcf', '6', '8001', '9001', '10000']}}, {'name': 'individuals_ID0000070', 'type': 'compute', 'runtime': 79.174, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr6.100000.vcf', 'size': 1014224690}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6n-9001-10001.tar.gz', 'size': 28730}], 'avgCPU': 110.2218, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000070', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr6.100000.vcf', '6', '9001', '10001', '10000']}}, {'name': 'individuals_merge_ID0000071', 'type': 'compute', 'runtime': 41.214, 'parents': ['individuals_ID0000070', 'individuals_ID0000066', 'individuals_ID0000067', 'individuals_ID0000068', 'individuals_ID0000069', 'individuals_ID0000062', 'individuals_ID0000063', 'individuals_ID0000064', 'individuals_ID0000065', 'individuals_ID0000061'], 'files': [{'link': 'input', 'name': 'chr6n-4001-5001.tar.gz', 'size': 27790}, {'link': 'input', 'name': 'chr6n-5001-6001.tar.gz', 'size': 28781}, {'link': 'input', 'name': 'chr6n-9001-10001.tar.gz', 'size': 28730}, {'link': 'input', 'name': 'chr6n-2001-3001.tar.gz', 'size': 28738}, {'link': 'input', 'name': 'chr6n-1-1001.tar.gz', 'size': 27971}, {'link': 'input', 'name': 'chr6n-7001-8001.tar.gz', 'size': 28804}, {'link': 'input', 'name': 'chr6n-6001-7001.tar.gz', 'size': 28767}, {'link': 'input', 'name': 'chr6n-3001-4001.tar.gz', 'size': 28808}, {'link': 'input', 'name': 'chr6n-8001-9001.tar.gz', 'size': 28776}, {'link': 'input', 'name': 'chr6n-1001-2001.tar.gz', 'size': 28786}, {'link': 'output', 'name': 'chr6n.tar.gz', 'size': 24659}], 'avgCPU': 102.4822, 'machine': 'pegasus-5', 'priority': 30, 'id': 'ID0000071', 'category': 'individuals_merge', 'command': {'program': 'individuals_merge', 'arguments': ['6', 'chr6n-1-1001.tar.gz', 'chr6n-1001-2001.tar.gz', 'chr6n-2001-3001.tar.gz', 'chr6n-3001-4001.tar.gz', 'chr6n-4001-5001.tar.gz', 'chr6n-5001-6001.tar.gz', 'chr6n-6001-7001.tar.gz', 'chr6n-7001-8001.tar.gz', 'chr6n-8001-9001.tar.gz', 'chr6n-9001-10001.tar.gz']}}, {'name': 'sifting_ID0000072', 'type': 'compute', 'runtime': 1.147, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr6.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', 'size': 1191539714}, {'link': 'output', 'name': 'sifted.SIFT.chr6.txt', 'size': 1063065}], 'avgCPU': 109.7646, 'machine': 'pegasus-3', 'priority': 20, 'id': 'ID0000072', 'category': 'sifting', 'command': {'program': 'sifting', 'arguments': ['ALL.chr6.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', '6']}}, {'name': 'individuals_ID0000073', 'type': 'compute', 'runtime': 55.14, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr7.100000.vcf', 'size': 1014240904}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr7n-1-1001.tar.gz', 'size': 27947}], 'avgCPU': 169.4922, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000073', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr7.100000.vcf', '7', '1', '1001', '10000']}}, {'name': 'individuals_ID0000074', 'type': 'compute', 'runtime': 54.588, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr7.100000.vcf', 'size': 1014240904}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr7n-1001-2001.tar.gz', 'size': 27920}], 'avgCPU': 170.7024, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000074', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr7.100000.vcf', '7', '1001', '2001', '10000']}}, {'name': 'individuals_ID0000075', 'type': 'compute', 'runtime': 54.517, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr7.100000.vcf', 'size': 1014240904}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr7n-2001-3001.tar.gz', 'size': 27902}], 'avgCPU': 171.1136, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000075', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr7.100000.vcf', '7', '2001', '3001', '10000']}}, {'name': 'individuals_ID0000076', 'type': 'compute', 'runtime': 54.339, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr7.100000.vcf', 'size': 1014240904}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr7n-3001-4001.tar.gz', 'size': 27944}], 'avgCPU': 172.1636, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000076', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr7.100000.vcf', '7', '3001', '4001', '10000']}}, {'name': 'individuals_ID0000077', 'type': 'compute', 'runtime': 53.91, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr7.100000.vcf', 'size': 1014240904}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr7n-4001-5001.tar.gz', 'size': 27944}], 'avgCPU': 175.038, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000077', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr7.100000.vcf', '7', '4001', '5001', '10000']}}, {'name': 'individuals_ID0000078', 'type': 'compute', 'runtime': 55.085, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr7.100000.vcf', 'size': 1014240904}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr7n-5001-6001.tar.gz', 'size': 27569}], 'avgCPU': 171.4514, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000078', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr7.100000.vcf', '7', '5001', '6001', '10000']}}, {'name': 'individuals_ID0000079', 'type': 'compute', 'runtime': 53.129, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr7.100000.vcf', 'size': 1014240904}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr7n-6001-7001.tar.gz', 'size': 28155}], 'avgCPU': 176.3688, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000079', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr7.100000.vcf', '7', '6001', '7001', '10000']}}, {'name': 'individuals_ID0000080', 'type': 'compute', 'runtime': 54.805, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr7.100000.vcf', 'size': 1014240904}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr7n-7001-8001.tar.gz', 'size': 27925}], 'avgCPU': 169.4973, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000080', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr7.100000.vcf', '7', '7001', '8001', '10000']}}, {'name': 'individuals_ID0000081', 'type': 'compute', 'runtime': 54.575, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr7.100000.vcf', 'size': 1014240904}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr7n-8001-9001.tar.gz', 'size': 27521}], 'avgCPU': 171.0912, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000081', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr7.100000.vcf', '7', '8001', '9001', '10000']}}, {'name': 'individuals_ID0000082', 'type': 'compute', 'runtime': 53.809, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr7.100000.vcf', 'size': 1014240904}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr7n-9001-10001.tar.gz', 'size': 27991}], 'avgCPU': 174.7775, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000082', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr7.100000.vcf', '7', '9001', '10001', '10000']}}, {'name': 'individuals_merge_ID0000083', 'type': 'compute', 'runtime': 41.514, 'parents': ['individuals_ID0000077', 'individuals_ID0000078', 'individuals_ID0000079', 'individuals_ID0000073', 'individuals_ID0000074', 'individuals_ID0000075', 'individuals_ID0000076', 'individuals_ID0000080', 'individuals_ID0000081', 'individuals_ID0000082'], 'files': [{'link': 'input', 'name': 'chr7n-1-1001.tar.gz', 'size': 27947}, {'link': 'input', 'name': 'chr7n-6001-7001.tar.gz', 'size': 28155}, {'link': 'input', 'name': 'chr7n-4001-5001.tar.gz', 'size': 27944}, {'link': 'input', 'name': 'chr7n-5001-6001.tar.gz', 'size': 27569}, {'link': 'input', 'name': 'chr7n-7001-8001.tar.gz', 'size': 27925}, {'link': 'input', 'name': 'chr7n-8001-9001.tar.gz', 'size': 27521}, {'link': 'input', 'name': 'chr7n-3001-4001.tar.gz', 'size': 27944}, {'link': 'input', 'name': 'chr7n-1001-2001.tar.gz', 'size': 27920}, {'link': 'input', 'name': 'chr7n-2001-3001.tar.gz', 'size': 27902}, {'link': 'input', 'name': 'chr7n-9001-10001.tar.gz', 'size': 27991}, {'link': 'output', 'name': 'chr7n.tar.gz', 'size': 24453}], 'avgCPU': 94.3369, 'machine': 'pegasus-5', 'priority': 30, 'id': 'ID0000083', 'category': 'individuals_merge', 'command': {'program': 'individuals_merge', 'arguments': ['7', 'chr7n-1-1001.tar.gz', 'chr7n-1001-2001.tar.gz', 'chr7n-2001-3001.tar.gz', 'chr7n-3001-4001.tar.gz', 'chr7n-4001-5001.tar.gz', 'chr7n-5001-6001.tar.gz', 'chr7n-6001-7001.tar.gz', 'chr7n-7001-8001.tar.gz', 'chr7n-8001-9001.tar.gz', 'chr7n-9001-10001.tar.gz']}}, {'name': 'sifting_ID0000084', 'type': 'compute', 'runtime': 1.132, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr7.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', 'size': 1140274616}, {'link': 'output', 'name': 'sifted.SIFT.chr7.txt', 'size': 911594}], 'avgCPU': 98.7633, 'machine': 'pegasus-3', 'priority': 20, 'id': 'ID0000084', 'category': 'sifting', 'command': {'program': 'sifting', 'arguments': ['ALL.chr7.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', '7']}}, {'name': 'individuals_ID0000085', 'type': 'compute', 'runtime': 53.231, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr8.100000.vcf', 'size': 1014222169}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr8n-1-1001.tar.gz', 'size': 27875}], 'avgCPU': 175.3114, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000085', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr8.100000.vcf', '8', '1', '1001', '10000']}}, {'name': 'individuals_ID0000086', 'type': 'compute', 'runtime': 52.159, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr8.100000.vcf', 'size': 1014222169}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr8n-1001-2001.tar.gz', 'size': 27849}], 'avgCPU': 179.3535, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000086', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr8.100000.vcf', '8', '1001', '2001', '10000']}}, {'name': 'individuals_ID0000087', 'type': 'compute', 'runtime': 50.111, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr8.100000.vcf', 'size': 1014222169}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr8n-2001-3001.tar.gz', 'size': 28560}], 'avgCPU': 180.5691, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000087', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr8.100000.vcf', '8', '2001', '3001', '10000']}}, {'name': 'individuals_ID0000088', 'type': 'compute', 'runtime': 50.633, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr8.100000.vcf', 'size': 1014222169}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr8n-3001-4001.tar.gz', 'size': 27971}], 'avgCPU': 178.7905, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000088', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr8.100000.vcf', '8', '3001', '4001', '10000']}}, {'name': 'individuals_ID0000089', 'type': 'compute', 'runtime': 50.439, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr8.100000.vcf', 'size': 1014222169}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr8n-4001-5001.tar.gz', 'size': 27727}], 'avgCPU': 179.266, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000089', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr8.100000.vcf', '8', '4001', '5001', '10000']}}, {'name': 'individuals_ID0000090', 'type': 'compute', 'runtime': 51.867, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr8.100000.vcf', 'size': 1014222169}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr8n-5001-6001.tar.gz', 'size': 27704}], 'avgCPU': 179.2681, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000090', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr8.100000.vcf', '8', '5001', '6001', '10000']}}, {'name': 'individuals_ID0000091', 'type': 'compute', 'runtime': 52.334, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr8.100000.vcf', 'size': 1014222169}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr8n-6001-7001.tar.gz', 'size': 27787}], 'avgCPU': 177.1258, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000091', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr8.100000.vcf', '8', '6001', '7001', '10000']}}, {'name': 'individuals_ID0000092', 'type': 'compute', 'runtime': 52.505, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr8.100000.vcf', 'size': 1014222169}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr8n-7001-8001.tar.gz', 'size': 28009}], 'avgCPU': 176.9412, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000092', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr8.100000.vcf', '8', '7001', '8001', '10000']}}, {'name': 'individuals_ID0000093', 'type': 'compute', 'runtime': 52.873, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr8.100000.vcf', 'size': 1014222169}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr8n-8001-9001.tar.gz', 'size': 27589}], 'avgCPU': 175.078, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000093', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr8.100000.vcf', '8', '8001', '9001', '10000']}}, {'name': 'individuals_ID0000094', 'type': 'compute', 'runtime': 53.729, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr8.100000.vcf', 'size': 1014222169}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr8n-9001-10001.tar.gz', 'size': 27759}], 'avgCPU': 173.8056, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000094', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr8.100000.vcf', '8', '9001', '10001', '10000']}}, {'name': 'individuals_merge_ID0000095', 'type': 'compute', 'runtime': 43.969, 'parents': ['individuals_ID0000088', 'individuals_ID0000089', 'individuals_ID0000085', 'individuals_ID0000086', 'individuals_ID0000087', 'individuals_ID0000090', 'individuals_ID0000091', 'individuals_ID0000092', 'individuals_ID0000093', 'individuals_ID0000094'], 'files': [{'link': 'input', 'name': 'chr8n-8001-9001.tar.gz', 'size': 27589}, {'link': 'input', 'name': 'chr8n-7001-8001.tar.gz', 'size': 28009}, {'link': 'input', 'name': 'chr8n-2001-3001.tar.gz', 'size': 28560}, {'link': 'input', 'name': 'chr8n-1-1001.tar.gz', 'size': 27875}, {'link': 'input', 'name': 'chr8n-5001-6001.tar.gz', 'size': 27704}, {'link': 'input', 'name': 'chr8n-6001-7001.tar.gz', 'size': 27787}, {'link': 'input', 'name': 'chr8n-3001-4001.tar.gz', 'size': 27971}, {'link': 'input', 'name': 'chr8n-9001-10001.tar.gz', 'size': 27759}, {'link': 'input', 'name': 'chr8n-4001-5001.tar.gz', 'size': 27727}, {'link': 'input', 'name': 'chr8n-1001-2001.tar.gz', 'size': 27849}, {'link': 'output', 'name': 'chr8n.tar.gz', 'size': 24288}], 'avgCPU': 85.2987, 'machine': 'pegasus-5', 'priority': 30, 'id': 'ID0000095', 'category': 'individuals_merge', 'command': {'program': 'individuals_merge', 'arguments': ['8', 'chr8n-1-1001.tar.gz', 'chr8n-1001-2001.tar.gz', 'chr8n-2001-3001.tar.gz', 'chr8n-3001-4001.tar.gz', 'chr8n-4001-5001.tar.gz', 'chr8n-5001-6001.tar.gz', 'chr8n-6001-7001.tar.gz', 'chr8n-7001-8001.tar.gz', 'chr8n-8001-9001.tar.gz', 'chr8n-9001-10001.tar.gz']}}, {'name': 'sifting_ID0000096', 'type': 'compute', 'runtime': 6.129, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr8.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', 'size': 1102569865}, {'link': 'output', 'name': 'sifted.SIFT.chr8.txt', 'size': 697067}], 'avgCPU': 22.4343, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000096', 'category': 'sifting', 'command': {'program': 'sifting', 'arguments': ['ALL.chr8.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', '8']}}, {'name': 'individuals_ID0000097', 'type': 'compute', 'runtime': 52.806, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr9.100000.vcf', 'size': 1014213207}, {'link': 'output', 'name': 'chr9n-1-1001.tar.gz', 'size': 27483}], 'avgCPU': 162.9095, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000097', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr9.100000.vcf', '9', '1', '1001', '10000']}}, {'name': 'individuals_ID0000098', 'type': 'compute', 'runtime': 53.058, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr9.100000.vcf', 'size': 1014213207}, {'link': 'output', 'name': 'chr9n-1001-2001.tar.gz', 'size': 27651}], 'avgCPU': 161.821, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000098', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr9.100000.vcf', '9', '1001', '2001', '10000']}}, {'name': 'individuals_ID0000099', 'type': 'compute', 'runtime': 67.077, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr9.100000.vcf', 'size': 1014213207}, {'link': 'output', 'name': 'chr9n-2001-3001.tar.gz', 'size': 27844}], 'avgCPU': 126.8125, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000099', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr9.100000.vcf', '9', '2001', '3001', '10000']}}, {'name': 'individuals_ID0000100', 'type': 'compute', 'runtime': 66.822, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr9.100000.vcf', 'size': 1014213207}, {'link': 'output', 'name': 'chr9n-3001-4001.tar.gz', 'size': 27868}], 'avgCPU': 126.9387, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000100', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr9.100000.vcf', '9', '3001', '4001', '10000']}}, {'name': 'individuals_ID0000101', 'type': 'compute', 'runtime': 70.078, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr9.100000.vcf', 'size': 1014213207}, {'link': 'output', 'name': 'chr9n-4001-5001.tar.gz', 'size': 27982}], 'avgCPU': 123.8677, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000101', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr9.100000.vcf', '9', '4001', '5001', '10000']}}, {'name': 'individuals_ID0000102', 'type': 'compute', 'runtime': 53.093, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr9.100000.vcf', 'size': 1014213207}, {'link': 'output', 'name': 'chr9n-5001-6001.tar.gz', 'size': 27540}], 'avgCPU': 162.5148, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000102', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr9.100000.vcf', '9', '5001', '6001', '10000']}}, {'name': 'individuals_ID0000103', 'type': 'compute', 'runtime': 70.837, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr9.100000.vcf', 'size': 1014213207}, {'link': 'output', 'name': 'chr9n-6001-7001.tar.gz', 'size': 28066}], 'avgCPU': 123.7531, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000103', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr9.100000.vcf', '9', '6001', '7001', '10000']}}, {'name': 'individuals_ID0000104', 'type': 'compute', 'runtime': 65.88, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr9.100000.vcf', 'size': 1014213207}, {'link': 'output', 'name': 'chr9n-7001-8001.tar.gz', 'size': 27873}], 'avgCPU': 128.2165, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000104', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr9.100000.vcf', '9', '7001', '8001', '10000']}}, {'name': 'individuals_ID0000105', 'type': 'compute', 'runtime': 67.387, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr9.100000.vcf', 'size': 1014213207}, {'link': 'output', 'name': 'chr9n-8001-9001.tar.gz', 'size': 27851}], 'avgCPU': 125.315, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000105', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr9.100000.vcf', '9', '8001', '9001', '10000']}}, {'name': 'individuals_ID0000106', 'type': 'compute', 'runtime': 67.234, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr9.100000.vcf', 'size': 1014213207}, {'link': 'output', 'name': 'chr9n-9001-10001.tar.gz', 'size': 27849}], 'avgCPU': 126.6368, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000106', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr9.100000.vcf', '9', '9001', '10001', '10000']}}, {'name': 'individuals_merge_ID0000107', 'type': 'compute', 'runtime': 44.548, 'parents': ['individuals_ID0000103', 'individuals_ID0000104', 'individuals_ID0000105', 'individuals_ID0000106', 'individuals_ID0000100', 'individuals_ID0000101', 'individuals_ID0000102', 'individuals_ID0000099', 'individuals_ID0000097', 'individuals_ID0000098'], 'files': [{'link': 'input', 'name': 'chr9n-1-1001.tar.gz', 'size': 27483}, {'link': 'input', 'name': 'chr9n-7001-8001.tar.gz', 'size': 27873}, {'link': 'input', 'name': 'chr9n-2001-3001.tar.gz', 'size': 27844}, {'link': 'input', 'name': 'chr9n-8001-9001.tar.gz', 'size': 27851}, {'link': 'input', 'name': 'chr9n-6001-7001.tar.gz', 'size': 28066}, {'link': 'input', 'name': 'chr9n-3001-4001.tar.gz', 'size': 27868}, {'link': 'input', 'name': 'chr9n-9001-10001.tar.gz', 'size': 27849}, {'link': 'input', 'name': 'chr9n-5001-6001.tar.gz', 'size': 27540}, {'link': 'input', 'name': 'chr9n-4001-5001.tar.gz', 'size': 27982}, {'link': 'input', 'name': 'chr9n-1001-2001.tar.gz', 'size': 27651}, {'link': 'output', 'name': 'chr9n.tar.gz', 'size': 25101}], 'avgCPU': 91.3262, 'machine': 'pegasus-5', 'priority': 30, 'id': 'ID0000107', 'category': 'individuals_merge', 'command': {'program': 'individuals_merge', 'arguments': ['9', 'chr9n-1-1001.tar.gz', 'chr9n-1001-2001.tar.gz', 'chr9n-2001-3001.tar.gz', 'chr9n-3001-4001.tar.gz', 'chr9n-4001-5001.tar.gz', 'chr9n-5001-6001.tar.gz', 'chr9n-6001-7001.tar.gz', 'chr9n-7001-8001.tar.gz', 'chr9n-8001-9001.tar.gz', 'chr9n-9001-10001.tar.gz']}}, {'name': 'sifting_ID0000108', 'type': 'compute', 'runtime': 1.185, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr9.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', 'size': 848495667}, {'link': 'output', 'name': 'sifted.SIFT.chr9.txt', 'size': 836365}], 'avgCPU': 81.519, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000108', 'category': 'sifting', 'command': {'program': 'sifting', 'arguments': ['ALL.chr9.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', '9']}}, {'name': 'individuals_ID0000109', 'type': 'compute', 'runtime': 51.81, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr10.100000.vcf', 'size': 1014320761}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10n-1-1001.tar.gz', 'size': 27753}], 'avgCPU': 166.1745, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000109', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr10.100000.vcf', '10', '1', '1001', '10000']}}, {'name': 'individuals_ID0000110', 'type': 'compute', 'runtime': 66.654, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr10.100000.vcf', 'size': 1014320761}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10n-1001-2001.tar.gz', 'size': 28139}], 'avgCPU': 126.7336, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000110', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr10.100000.vcf', '10', '1001', '2001', '10000']}}, {'name': 'individuals_ID0000111', 'type': 'compute', 'runtime': 67.154, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr10.100000.vcf', 'size': 1014320761}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10n-2001-3001.tar.gz', 'size': 28199}], 'avgCPU': 126.5092, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000111', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr10.100000.vcf', '10', '2001', '3001', '10000']}}, {'name': 'individuals_ID0000112', 'type': 'compute', 'runtime': 68.342, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr10.100000.vcf', 'size': 1014320761}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10n-3001-4001.tar.gz', 'size': 28328}], 'avgCPU': 126.3074, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000112', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr10.100000.vcf', '10', '3001', '4001', '10000']}}, {'name': 'individuals_ID0000113', 'type': 'compute', 'runtime': 68.365, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr10.100000.vcf', 'size': 1014320761}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10n-4001-5001.tar.gz', 'size': 28303}], 'avgCPU': 127.1908, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000113', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr10.100000.vcf', '10', '4001', '5001', '10000']}}, {'name': 'individuals_ID0000114', 'type': 'compute', 'runtime': 68.394, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr10.100000.vcf', 'size': 1014320761}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10n-5001-6001.tar.gz', 'size': 28372}], 'avgCPU': 127.7539, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000114', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr10.100000.vcf', '10', '5001', '6001', '10000']}}, {'name': 'individuals_ID0000115', 'type': 'compute', 'runtime': 72.034, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr10.100000.vcf', 'size': 1014320761}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10n-6001-7001.tar.gz', 'size': 28470}], 'avgCPU': 121.4982, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000115', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr10.100000.vcf', '10', '6001', '7001', '10000']}}, {'name': 'individuals_ID0000116', 'type': 'compute', 'runtime': 66.473, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr10.100000.vcf', 'size': 1014320761}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10n-7001-8001.tar.gz', 'size': 28308}], 'avgCPU': 128.1949, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000116', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr10.100000.vcf', '10', '7001', '8001', '10000']}}, {'name': 'individuals_ID0000117', 'type': 'compute', 'runtime': 67.945, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr10.100000.vcf', 'size': 1014320761}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10n-8001-9001.tar.gz', 'size': 28154}], 'avgCPU': 124.5537, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000117', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr10.100000.vcf', '10', '8001', '9001', '10000']}}, {'name': 'individuals_ID0000118', 'type': 'compute', 'runtime': 52.862, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr10.100000.vcf', 'size': 1014320761}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10n-9001-10001.tar.gz', 'size': 27693}], 'avgCPU': 163.2118, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000118', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr10.100000.vcf', '10', '9001', '10001', '10000']}}, {'name': 'individuals_merge_ID0000119', 'type': 'compute', 'runtime': 45.692, 'parents': ['individuals_ID0000114', 'individuals_ID0000115', 'individuals_ID0000116', 'individuals_ID0000117', 'individuals_ID0000110', 'individuals_ID0000111', 'individuals_ID0000112', 'individuals_ID0000113', 'individuals_ID0000118', 'individuals_ID0000109'], 'files': [{'link': 'input', 'name': 'chr10n-4001-5001.tar.gz', 'size': 28303}, {'link': 'input', 'name': 'chr10n-9001-10001.tar.gz', 'size': 27693}, {'link': 'input', 'name': 'chr10n-1001-2001.tar.gz', 'size': 28139}, {'link': 'input', 'name': 'chr10n-6001-7001.tar.gz', 'size': 28470}, {'link': 'input', 'name': 'chr10n-7001-8001.tar.gz', 'size': 28308}, {'link': 'input', 'name': 'chr10n-1-1001.tar.gz', 'size': 27753}, {'link': 'input', 'name': 'chr10n-2001-3001.tar.gz', 'size': 28199}, {'link': 'input', 'name': 'chr10n-5001-6001.tar.gz', 'size': 28372}, {'link': 'input', 'name': 'chr10n-8001-9001.tar.gz', 'size': 28154}, {'link': 'input', 'name': 'chr10n-3001-4001.tar.gz', 'size': 28328}, {'link': 'output', 'name': 'chr10n.tar.gz', 'size': 24615}], 'avgCPU': 89.2104, 'machine': 'pegasus-5', 'priority': 30, 'id': 'ID0000119', 'category': 'individuals_merge', 'command': {'program': 'individuals_merge', 'arguments': ['10', 'chr10n-1-1001.tar.gz', 'chr10n-1001-2001.tar.gz', 'chr10n-2001-3001.tar.gz', 'chr10n-3001-4001.tar.gz', 'chr10n-4001-5001.tar.gz', 'chr10n-5001-6001.tar.gz', 'chr10n-6001-7001.tar.gz', 'chr10n-7001-8001.tar.gz', 'chr10n-8001-9001.tar.gz', 'chr10n-9001-10001.tar.gz']}}, {'name': 'sifting_ID0000120', 'type': 'compute', 'runtime': 5.298, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr10.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', 'size': 962745794}, {'link': 'output', 'name': 'sifted.SIFT.chr10.txt', 'size': 797176}], 'avgCPU': 22.1027, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000120', 'category': 'sifting', 'command': {'program': 'sifting', 'arguments': ['ALL.chr10.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', '10']}}, {'name': 'individuals_ID0000121', 'type': 'compute', 'runtime': 66.504, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr19.100000.vcf', 'size': 1014389098}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr19n-1-1001.tar.gz', 'size': 28917}], 'avgCPU': 130.2027, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000121', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr19.100000.vcf', '19', '1', '1001', '10000']}}, {'name': 'individuals_ID0000122', 'type': 'compute', 'runtime': 71.354, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr19.100000.vcf', 'size': 1014389098}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr19n-1001-2001.tar.gz', 'size': 28877}], 'avgCPU': 122.2034, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000122', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr19.100000.vcf', '19', '1001', '2001', '10000']}}, {'name': 'individuals_ID0000123', 'type': 'compute', 'runtime': 83.659, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr19.100000.vcf', 'size': 1014389098}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr19n-2001-3001.tar.gz', 'size': 28881}], 'avgCPU': 105.067, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000123', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr19.100000.vcf', '19', '2001', '3001', '10000']}}, {'name': 'individuals_ID0000124', 'type': 'compute', 'runtime': 71.333, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr19.100000.vcf', 'size': 1014389098}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr19n-3001-4001.tar.gz', 'size': 28899}], 'avgCPU': 122.4566, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000124', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr19.100000.vcf', '19', '3001', '4001', '10000']}}, {'name': 'individuals_ID0000125', 'type': 'compute', 'runtime': 79.244, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr19.100000.vcf', 'size': 1014389098}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr19n-4001-5001.tar.gz', 'size': 28890}], 'avgCPU': 110.3427, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000125', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr19.100000.vcf', '19', '4001', '5001', '10000']}}, {'name': 'individuals_ID0000126', 'type': 'compute', 'runtime': 75.887, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr19.100000.vcf', 'size': 1014389098}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr19n-5001-6001.tar.gz', 'size': 28891}], 'avgCPU': 114.6665, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000126', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr19.100000.vcf', '19', '5001', '6001', '10000']}}, {'name': 'individuals_ID0000127', 'type': 'compute', 'runtime': 64.808, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr19.100000.vcf', 'size': 1014389098}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr19n-6001-7001.tar.gz', 'size': 28966}], 'avgCPU': 133.7458, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000127', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr19.100000.vcf', '19', '6001', '7001', '10000']}}, {'name': 'individuals_ID0000128', 'type': 'compute', 'runtime': 76.309, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr19.100000.vcf', 'size': 1014389098}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr19n-7001-8001.tar.gz', 'size': 28901}], 'avgCPU': 114.1779, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000128', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr19.100000.vcf', '19', '7001', '8001', '10000']}}, {'name': 'individuals_ID0000129', 'type': 'compute', 'runtime': 76.461, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr19.100000.vcf', 'size': 1014389098}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr19n-8001-9001.tar.gz', 'size': 28835}], 'avgCPU': 114.3524, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000129', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr19.100000.vcf', '19', '8001', '9001', '10000']}}, {'name': 'individuals_ID0000130', 'type': 'compute', 'runtime': 81.998, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr19.100000.vcf', 'size': 1014389098}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr19n-9001-10001.tar.gz', 'size': 28868}], 'avgCPU': 106.3611, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000130', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr19.100000.vcf', '19', '9001', '10001', '10000']}}, {'name': 'individuals_merge_ID0000131', 'type': 'compute', 'runtime': 41.962, 'parents': ['individuals_ID0000125', 'individuals_ID0000126', 'individuals_ID0000127', 'individuals_ID0000128', 'individuals_ID0000121', 'individuals_ID0000122', 'individuals_ID0000123', 'individuals_ID0000124', 'individuals_ID0000129', 'individuals_ID0000130'], 'files': [{'link': 'input', 'name': 'chr19n-8001-9001.tar.gz', 'size': 28835}, {'link': 'input', 'name': 'chr19n-2001-3001.tar.gz', 'size': 28881}, {'link': 'input', 'name': 'chr19n-7001-8001.tar.gz', 'size': 28901}, {'link': 'input', 'name': 'chr19n-9001-10001.tar.gz', 'size': 28868}, {'link': 'input', 'name': 'chr19n-3001-4001.tar.gz', 'size': 28899}, {'link': 'input', 'name': 'chr19n-5001-6001.tar.gz', 'size': 28891}, {'link': 'input', 'name': 'chr19n-4001-5001.tar.gz', 'size': 28890}, {'link': 'input', 'name': 'chr19n-1-1001.tar.gz', 'size': 28917}, {'link': 'input', 'name': 'chr19n-1001-2001.tar.gz', 'size': 28877}, {'link': 'input', 'name': 'chr19n-6001-7001.tar.gz', 'size': 28966}, {'link': 'output', 'name': 'chr19n.tar.gz', 'size': 25086}], 'avgCPU': 100.3122, 'machine': 'pegasus-5', 'priority': 30, 'id': 'ID0000131', 'category': 'individuals_merge', 'command': {'program': 'individuals_merge', 'arguments': ['19', 'chr19n-1-1001.tar.gz', 'chr19n-1001-2001.tar.gz', 'chr19n-2001-3001.tar.gz', 'chr19n-3001-4001.tar.gz', 'chr19n-4001-5001.tar.gz', 'chr19n-5001-6001.tar.gz', 'chr19n-6001-7001.tar.gz', 'chr19n-7001-8001.tar.gz', 'chr19n-8001-9001.tar.gz', 'chr19n-9001-10001.tar.gz']}}, {'name': 'sifting_ID0000132', 'type': 'compute', 'runtime': 7.341, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr19.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', 'size': 470301753}, {'link': 'output', 'name': 'sifted.SIFT.chr19.txt', 'size': 1481880}], 'avgCPU': 12.0692, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000132', 'category': 'sifting', 'command': {'program': 'sifting', 'arguments': ['ALL.chr19.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', '19']}}, {'name': 'individuals_ID0000133', 'type': 'compute', 'runtime': 61.609, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr20.100000.vcf', 'size': 1014340420}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20n-1-1001.tar.gz', 'size': 28750}], 'avgCPU': 138.2801, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000133', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr20.100000.vcf', '20', '1', '1001', '10000']}}, {'name': 'individuals_ID0000134', 'type': 'compute', 'runtime': 63.913, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr20.100000.vcf', 'size': 1014340420}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20n-1001-2001.tar.gz', 'size': 28710}], 'avgCPU': 133.7412, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000134', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr20.100000.vcf', '20', '1001', '2001', '10000']}}, {'name': 'individuals_ID0000135', 'type': 'compute', 'runtime': 63.365, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr20.100000.vcf', 'size': 1014340420}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20n-2001-3001.tar.gz', 'size': 28717}], 'avgCPU': 132.8793, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000135', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr20.100000.vcf', '20', '2001', '3001', '10000']}}, {'name': 'individuals_ID0000136', 'type': 'compute', 'runtime': 58.716, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr20.100000.vcf', 'size': 1014340420}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20n-3001-4001.tar.gz', 'size': 28553}], 'avgCPU': 152.8919, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000136', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr20.100000.vcf', '20', '3001', '4001', '10000']}}, {'name': 'individuals_ID0000137', 'type': 'compute', 'runtime': 60.046, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr20.100000.vcf', 'size': 1014340420}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20n-4001-5001.tar.gz', 'size': 28695}], 'avgCPU': 148.8442, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000137', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr20.100000.vcf', '20', '4001', '5001', '10000']}}, {'name': 'individuals_ID0000138', 'type': 'compute', 'runtime': 60.267, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr20.100000.vcf', 'size': 1014340420}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20n-5001-6001.tar.gz', 'size': 28649}], 'avgCPU': 147.2979, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000138', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr20.100000.vcf', '20', '5001', '6001', '10000']}}, {'name': 'individuals_ID0000139', 'type': 'compute', 'runtime': 57.761, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr20.100000.vcf', 'size': 1014340420}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20n-6001-7001.tar.gz', 'size': 28629}], 'avgCPU': 155.508, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000139', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr20.100000.vcf', '20', '6001', '7001', '10000']}}, {'name': 'individuals_ID0000140', 'type': 'compute', 'runtime': 63.909, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr20.100000.vcf', 'size': 1014340420}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20n-7001-8001.tar.gz', 'size': 28702}], 'avgCPU': 133.0501, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000140', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr20.100000.vcf', '20', '7001', '8001', '10000']}}, {'name': 'individuals_ID0000141', 'type': 'compute', 'runtime': 63.479, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr20.100000.vcf', 'size': 1014340420}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20n-8001-9001.tar.gz', 'size': 28775}], 'avgCPU': 132.5761, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000141', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr20.100000.vcf', '20', '8001', '9001', '10000']}}, {'name': 'individuals_ID0000142', 'type': 'compute', 'runtime': 64.599, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr20.100000.vcf', 'size': 1014340420}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20n-9001-10001.tar.gz', 'size': 28669}], 'avgCPU': 131.0345, 'machine': 'pegasus-2', 'priority': 20, 'id': 'ID0000142', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr20.100000.vcf', '20', '9001', '10001', '10000']}}, {'name': 'individuals_merge_ID0000143', 'type': 'compute', 'runtime': 41.834, 'parents': ['individuals_ID0000136', 'individuals_ID0000137', 'individuals_ID0000138', 'individuals_ID0000139', 'individuals_ID0000133', 'individuals_ID0000134', 'individuals_ID0000135', 'individuals_ID0000140', 'individuals_ID0000141', 'individuals_ID0000142'], 'files': [{'link': 'input', 'name': 'chr20n-9001-10001.tar.gz', 'size': 28669}, {'link': 'input', 'name': 'chr20n-1-1001.tar.gz', 'size': 28750}, {'link': 'input', 'name': 'chr20n-4001-5001.tar.gz', 'size': 28695}, {'link': 'input', 'name': 'chr20n-2001-3001.tar.gz', 'size': 28717}, {'link': 'input', 'name': 'chr20n-5001-6001.tar.gz', 'size': 28649}, {'link': 'input', 'name': 'chr20n-3001-4001.tar.gz', 'size': 28553}, {'link': 'input', 'name': 'chr20n-8001-9001.tar.gz', 'size': 28775}, {'link': 'input', 'name': 'chr20n-7001-8001.tar.gz', 'size': 28702}, {'link': 'input', 'name': 'chr20n-1001-2001.tar.gz', 'size': 28710}, {'link': 'input', 'name': 'chr20n-6001-7001.tar.gz', 'size': 28629}, {'link': 'output', 'name': 'chr20n.tar.gz', 'size': 25254}], 'avgCPU': 98.8765, 'machine': 'pegasus-5', 'priority': 30, 'id': 'ID0000143', 'category': 'individuals_merge', 'command': {'program': 'individuals_merge', 'arguments': ['20', 'chr20n-1-1001.tar.gz', 'chr20n-1001-2001.tar.gz', 'chr20n-2001-3001.tar.gz', 'chr20n-3001-4001.tar.gz', 'chr20n-4001-5001.tar.gz', 'chr20n-5001-6001.tar.gz', 'chr20n-6001-7001.tar.gz', 'chr20n-7001-8001.tar.gz', 'chr20n-8001-9001.tar.gz', 'chr20n-9001-10001.tar.gz']}}, {'name': 'sifting_ID0000144', 'type': 'compute', 'runtime': 1.364, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr20.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', 'size': 442329007}, {'link': 'output', 'name': 'sifted.SIFT.chr20.txt', 'size': 523567}], 'avgCPU': 41.4223, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000144', 'category': 'sifting', 'command': {'program': 'sifting', 'arguments': ['ALL.chr20.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', '20']}}, {'name': 'individuals_ID0000145', 'type': 'compute', 'runtime': 57.388, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr21.100000.vcf', 'size': 1014442803}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr21n-1-1001.tar.gz', 'size': 28344}], 'avgCPU': 162.6455, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000145', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr21.100000.vcf', '21', '1', '1001', '10000']}}, {'name': 'individuals_ID0000146', 'type': 'compute', 'runtime': 57.185, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr21.100000.vcf', 'size': 1014442803}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr21n-1001-2001.tar.gz', 'size': 28189}], 'avgCPU': 165.1692, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000146', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr21.100000.vcf', '21', '1001', '2001', '10000']}}, {'name': 'individuals_ID0000147', 'type': 'compute', 'runtime': 54.87, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr21.100000.vcf', 'size': 1014442803}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr21n-2001-3001.tar.gz', 'size': 27875}], 'avgCPU': 172.6918, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000147', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr21.100000.vcf', '21', '2001', '3001', '10000']}}, {'name': 'individuals_ID0000148', 'type': 'compute', 'runtime': 54.913, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr21.100000.vcf', 'size': 1014442803}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr21n-3001-4001.tar.gz', 'size': 28364}], 'avgCPU': 173.1666, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000148', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr21.100000.vcf', '21', '3001', '4001', '10000']}}, {'name': 'individuals_ID0000149', 'type': 'compute', 'runtime': 54.3, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr21.100000.vcf', 'size': 1014442803}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr21n-4001-5001.tar.gz', 'size': 28346}], 'avgCPU': 173.6077, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000149', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr21.100000.vcf', '21', '4001', '5001', '10000']}}, {'name': 'individuals_ID0000150', 'type': 'compute', 'runtime': 61.306, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr21.100000.vcf', 'size': 1014442803}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr21n-5001-6001.tar.gz', 'size': 28201}], 'avgCPU': 153.414, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000150', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr21.100000.vcf', '21', '5001', '6001', '10000']}}, {'name': 'individuals_ID0000151', 'type': 'compute', 'runtime': 61.282, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr21.100000.vcf', 'size': 1014442803}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr21n-6001-7001.tar.gz', 'size': 28313}], 'avgCPU': 152.9764, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000151', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr21.100000.vcf', '21', '6001', '7001', '10000']}}, {'name': 'individuals_ID0000152', 'type': 'compute', 'runtime': 60.354, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr21.100000.vcf', 'size': 1014442803}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr21n-7001-8001.tar.gz', 'size': 28256}], 'avgCPU': 155.0303, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000152', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr21.100000.vcf', '21', '7001', '8001', '10000']}}, {'name': 'individuals_ID0000153', 'type': 'compute', 'runtime': 59.919, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr21.100000.vcf', 'size': 1014442803}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr21n-8001-9001.tar.gz', 'size': 28426}], 'avgCPU': 156.3144, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000153', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr21.100000.vcf', '21', '8001', '9001', '10000']}}, {'name': 'individuals_ID0000154', 'type': 'compute', 'runtime': 55.048, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr21.100000.vcf', 'size': 1014442803}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr21n-9001-10001.tar.gz', 'size': 28170}], 'avgCPU': 169.6683, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000154', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr21.100000.vcf', '21', '9001', '10001', '10000']}}, {'name': 'individuals_merge_ID0000155', 'type': 'compute', 'runtime': 40.726, 'parents': ['individuals_ID0000147', 'individuals_ID0000148', 'individuals_ID0000149', 'individuals_ID0000145', 'individuals_ID0000146', 'individuals_ID0000154', 'individuals_ID0000150', 'individuals_ID0000151', 'individuals_ID0000152', 'individuals_ID0000153'], 'files': [{'link': 'input', 'name': 'chr21n-4001-5001.tar.gz', 'size': 28346}, {'link': 'input', 'name': 'chr21n-9001-10001.tar.gz', 'size': 28170}, {'link': 'input', 'name': 'chr21n-5001-6001.tar.gz', 'size': 28201}, {'link': 'input', 'name': 'chr21n-7001-8001.tar.gz', 'size': 28256}, {'link': 'input', 'name': 'chr21n-6001-7001.tar.gz', 'size': 28313}, {'link': 'input', 'name': 'chr21n-1001-2001.tar.gz', 'size': 28189}, {'link': 'input', 'name': 'chr21n-8001-9001.tar.gz', 'size': 28426}, {'link': 'input', 'name': 'chr21n-1-1001.tar.gz', 'size': 28344}, {'link': 'input', 'name': 'chr21n-3001-4001.tar.gz', 'size': 28364}, {'link': 'input', 'name': 'chr21n-2001-3001.tar.gz', 'size': 27875}, {'link': 'output', 'name': 'chr21n.tar.gz', 'size': 24630}], 'avgCPU': 96.4003, 'machine': 'pegasus-5', 'priority': 30, 'id': 'ID0000155', 'category': 'individuals_merge', 'command': {'program': 'individuals_merge', 'arguments': ['21', 'chr21n-1-1001.tar.gz', 'chr21n-1001-2001.tar.gz', 'chr21n-2001-3001.tar.gz', 'chr21n-3001-4001.tar.gz', 'chr21n-4001-5001.tar.gz', 'chr21n-5001-6001.tar.gz', 'chr21n-6001-7001.tar.gz', 'chr21n-7001-8001.tar.gz', 'chr21n-8001-9001.tar.gz', 'chr21n-9001-10001.tar.gz']}}, {'name': 'sifting_ID0000156', 'type': 'compute', 'runtime': 0.311, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr21.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', 'size': 267806263}, {'link': 'output', 'name': 'sifted.SIFT.chr21.txt', 'size': 231958}], 'avgCPU': 116.3987, 'machine': 'pegasus-3', 'priority': 20, 'id': 'ID0000156', 'category': 'sifting', 'command': {'program': 'sifting', 'arguments': ['ALL.chr21.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', '21']}}, {'name': 'individuals_ID0000157', 'type': 'compute', 'runtime': 74.675, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr22.100000.vcf', 'size': 1014493636}, {'link': 'output', 'name': 'chr22n-1-1001.tar.gz', 'size': 28876}], 'avgCPU': 116.5584, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000157', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr22.100000.vcf', '22', '1', '1001', '10000']}}, {'name': 'individuals_ID0000158', 'type': 'compute', 'runtime': 64.899, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr22.100000.vcf', 'size': 1014493636}, {'link': 'output', 'name': 'chr22n-1001-2001.tar.gz', 'size': 28919}], 'avgCPU': 133.5383, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000158', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr22.100000.vcf', '22', '1001', '2001', '10000']}}, {'name': 'individuals_ID0000159', 'type': 'compute', 'runtime': 74.371, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr22.100000.vcf', 'size': 1014493636}, {'link': 'output', 'name': 'chr22n-2001-3001.tar.gz', 'size': 28878}], 'avgCPU': 117.0376, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000159', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr22.100000.vcf', '22', '2001', '3001', '10000']}}, {'name': 'individuals_ID0000160', 'type': 'compute', 'runtime': 68.025, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr22.100000.vcf', 'size': 1014493636}, {'link': 'output', 'name': 'chr22n-3001-4001.tar.gz', 'size': 28829}], 'avgCPU': 127.8868, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000160', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr22.100000.vcf', '22', '3001', '4001', '10000']}}, {'name': 'individuals_ID0000161', 'type': 'compute', 'runtime': 66.285, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr22.100000.vcf', 'size': 1014493636}, {'link': 'output', 'name': 'chr22n-4001-5001.tar.gz', 'size': 28763}], 'avgCPU': 130.6042, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000161', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr22.100000.vcf', '22', '4001', '5001', '10000']}}, {'name': 'individuals_ID0000162', 'type': 'compute', 'runtime': 66.046, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr22.100000.vcf', 'size': 1014493636}, {'link': 'output', 'name': 'chr22n-5001-6001.tar.gz', 'size': 28836}], 'avgCPU': 131.3918, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000162', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr22.100000.vcf', '22', '5001', '6001', '10000']}}, {'name': 'individuals_ID0000163', 'type': 'compute', 'runtime': 65.887, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr22.100000.vcf', 'size': 1014493636}, {'link': 'output', 'name': 'chr22n-6001-7001.tar.gz', 'size': 28853}], 'avgCPU': 131.4007, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000163', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr22.100000.vcf', '22', '6001', '7001', '10000']}}, {'name': 'individuals_ID0000164', 'type': 'compute', 'runtime': 68.016, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr22.100000.vcf', 'size': 1014493636}, {'link': 'output', 'name': 'chr22n-7001-8001.tar.gz', 'size': 28821}], 'avgCPU': 127.6714, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000164', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr22.100000.vcf', '22', '7001', '8001', '10000']}}, {'name': 'individuals_ID0000165', 'type': 'compute', 'runtime': 65.852, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr22.100000.vcf', 'size': 1014493636}, {'link': 'output', 'name': 'chr22n-8001-9001.tar.gz', 'size': 28937}], 'avgCPU': 132.0583, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000165', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr22.100000.vcf', '22', '8001', '9001', '10000']}}, {'name': 'individuals_ID0000166', 'type': 'compute', 'runtime': 77.189, 'parents': [], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL.chr22.100000.vcf', 'size': 1014493636}, {'link': 'output', 'name': 'chr22n-9001-10001.tar.gz', 'size': 28917}], 'avgCPU': 112.8969, 'machine': 'pegasus-5', 'priority': 20, 'id': 'ID0000166', 'category': 'individuals', 'command': {'program': 'individuals', 'arguments': ['ALL.chr22.100000.vcf', '22', '9001', '10001', '10000']}}, {'name': 'individuals_merge_ID0000167', 'type': 'compute', 'runtime': 40.9, 'parents': ['individuals_ID0000158', 'individuals_ID0000159', 'individuals_ID0000157', 'individuals_ID0000165', 'individuals_ID0000166', 'individuals_ID0000161', 'individuals_ID0000162', 'individuals_ID0000163', 'individuals_ID0000164', 'individuals_ID0000160'], 'files': [{'link': 'input', 'name': 'chr22n-2001-3001.tar.gz', 'size': 28878}, {'link': 'input', 'name': 'chr22n-3001-4001.tar.gz', 'size': 28829}, {'link': 'input', 'name': 'chr22n-1-1001.tar.gz', 'size': 28876}, {'link': 'input', 'name': 'chr22n-4001-5001.tar.gz', 'size': 28763}, {'link': 'input', 'name': 'chr22n-5001-6001.tar.gz', 'size': 28836}, {'link': 'input', 'name': 'chr22n-6001-7001.tar.gz', 'size': 28853}, {'link': 'input', 'name': 'chr22n-8001-9001.tar.gz', 'size': 28937}, {'link': 'input', 'name': 'chr22n-7001-8001.tar.gz', 'size': 28821}, {'link': 'input', 'name': 'chr22n-1001-2001.tar.gz', 'size': 28919}, {'link': 'input', 'name': 'chr22n-9001-10001.tar.gz', 'size': 28917}, {'link': 'output', 'name': 'chr22n.tar.gz', 'size': 25242}], 'avgCPU': 96.1247, 'machine': 'pegasus-2', 'priority': 30, 'id': 'ID0000167', 'category': 'individuals_merge', 'command': {'program': 'individuals_merge', 'arguments': ['22', 'chr22n-1-1001.tar.gz', 'chr22n-1001-2001.tar.gz', 'chr22n-2001-3001.tar.gz', 'chr22n-3001-4001.tar.gz', 'chr22n-4001-5001.tar.gz', 'chr22n-5001-6001.tar.gz', 'chr22n-6001-7001.tar.gz', 'chr22n-7001-8001.tar.gz', 'chr22n-8001-9001.tar.gz', 'chr22n-9001-10001.tar.gz']}}, {'name': 'sifting_ID0000168', 'type': 'compute', 'runtime': 2.111, 'parents': [], 'files': [{'link': 'input', 'name': 'ALL.chr22.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', 'size': 280949919}, {'link': 'output', 'name': 'sifted.SIFT.chr22.txt', 'size': 480587}], 'avgCPU': 23.8276, 'machine': 'pegasus-4', 'priority': 20, 'id': 'ID0000168', 'category': 'sifting', 'command': {'program': 'sifting', 'arguments': ['ALL.chr22.phase3_shapeit2_mvncall_integrated_v5.20130502.sites.annotation.vcf', '22']}}, {'name': 'mutation_overlap_ID0000169', 'type': 'compute', 'runtime': 6.282, 'parents': ['individuals_merge_ID0000011', 'sifting_ID0000012'], 'files': [{'link': 'input', 'name': 'chr1n.tar.gz', 'size': 24897}, {'link': 'input', 'name': 'sifted.SIFT.chr1.txt', 'size': 2126612}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr1-AFR.tar.gz', 'size': 150699}], 'avgCPU': 73.241, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000169', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '1', '-pop', 'AFR']}}, {'name': 'frequency_ID0000170', 'type': 'compute', 'runtime': 118.457, 'parents': ['individuals_merge_ID0000011', 'sifting_ID0000012'], 'files': [{'link': 'input', 'name': 'chr1n.tar.gz', 'size': 24897}, {'link': 'input', 'name': 'sifted.SIFT.chr1.txt', 'size': 2126612}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr1-AFR-freq.tar.gz', 'size': 279625}], 'avgCPU': 77.1183, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000170', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '1', '-pop', 'AFR']}}, {'name': 'mutation_overlap_ID0000171', 'type': 'compute', 'runtime': 4.829, 'parents': ['individuals_merge_ID0000011', 'sifting_ID0000012'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr1n.tar.gz', 'size': 24897}, {'link': 'input', 'name': 'sifted.SIFT.chr1.txt', 'size': 2126612}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'output', 'name': 'chr1-GBR.tar.gz', 'size': 142798}], 'avgCPU': 45.1646, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000171', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '1', '-pop', 'GBR']}}, {'name': 'frequency_ID0000172', 'type': 'compute', 'runtime': 114.386, 'parents': ['individuals_merge_ID0000011', 'sifting_ID0000012'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr1n.tar.gz', 'size': 24897}, {'link': 'input', 'name': 'sifted.SIFT.chr1.txt', 'size': 2126612}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'output', 'name': 'chr1-GBR-freq.tar.gz', 'size': 226983}], 'avgCPU': 77.9877, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000172', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '1', '-pop', 'GBR']}}, {'name': 'mutation_overlap_ID0000173', 'type': 'compute', 'runtime': 21.84, 'parents': ['individuals_merge_ID0000011', 'sifting_ID0000012'], 'files': [{'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'chr1n.tar.gz', 'size': 24897}, {'link': 'input', 'name': 'sifted.SIFT.chr1.txt', 'size': 2126612}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr1-ALL.tar.gz', 'size': 172361}], 'avgCPU': 93.0311, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000173', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '1', '-pop', 'ALL']}}, {'name': 'frequency_ID0000174', 'type': 'compute', 'runtime': 115.032, 'parents': ['individuals_merge_ID0000011', 'sifting_ID0000012'], 'files': [{'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'chr1n.tar.gz', 'size': 24897}, {'link': 'input', 'name': 'sifted.SIFT.chr1.txt', 'size': 2126612}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr1-ALL-freq.tar.gz', 'size': 293802}], 'avgCPU': 79.8326, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000174', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '1', '-pop', 'ALL']}}, {'name': 'mutation_overlap_ID0000175', 'type': 'compute', 'runtime': 4.078, 'parents': ['individuals_merge_ID0000011', 'sifting_ID0000012'], 'files': [{'link': 'input', 'name': 'chr1n.tar.gz', 'size': 24897}, {'link': 'input', 'name': 'sifted.SIFT.chr1.txt', 'size': 2126612}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr1-SAS.tar.gz', 'size': 149379}], 'avgCPU': 90.0196, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000175', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '1', '-pop', 'SAS']}}, {'name': 'frequency_ID0000176', 'type': 'compute', 'runtime': 113.143, 'parents': ['individuals_merge_ID0000011', 'sifting_ID0000012'], 'files': [{'link': 'input', 'name': 'chr1n.tar.gz', 'size': 24897}, {'link': 'input', 'name': 'sifted.SIFT.chr1.txt', 'size': 2126612}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr1-SAS-freq.tar.gz', 'size': 269445}], 'avgCPU': 79.6081, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000176', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '1', '-pop', 'SAS']}}, {'name': 'mutation_overlap_ID0000177', 'type': 'compute', 'runtime': 5.914, 'parents': ['individuals_merge_ID0000011', 'sifting_ID0000012'], 'files': [{'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'chr1n.tar.gz', 'size': 24897}, {'link': 'input', 'name': 'sifted.SIFT.chr1.txt', 'size': 2126612}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr1-EAS.tar.gz', 'size': 148710}], 'avgCPU': 65.8776, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000177', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '1', '-pop', 'EAS']}}, {'name': 'frequency_ID0000178', 'type': 'compute', 'runtime': 77.363, 'parents': ['individuals_merge_ID0000011', 'sifting_ID0000012'], 'files': [{'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'chr1n.tar.gz', 'size': 24897}, {'link': 'input', 'name': 'sifted.SIFT.chr1.txt', 'size': 2126612}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr1-EAS-freq.tar.gz', 'size': 270557}], 'avgCPU': 99.6122, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000178', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '1', '-pop', 'EAS']}}, {'name': 'mutation_overlap_ID0000179', 'type': 'compute', 'runtime': 5.718, 'parents': ['individuals_merge_ID0000011', 'sifting_ID0000012'], 'files': [{'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'chr1n.tar.gz', 'size': 24897}, {'link': 'input', 'name': 'sifted.SIFT.chr1.txt', 'size': 2126612}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr1-AMR.tar.gz', 'size': 148474}], 'avgCPU': 54.1623, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000179', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '1', '-pop', 'AMR']}}, {'name': 'frequency_ID0000180', 'type': 'compute', 'runtime': 116.18, 'parents': ['individuals_merge_ID0000011', 'sifting_ID0000012'], 'files': [{'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'chr1n.tar.gz', 'size': 24897}, {'link': 'input', 'name': 'sifted.SIFT.chr1.txt', 'size': 2126612}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr1-AMR-freq.tar.gz', 'size': 264374}], 'avgCPU': 78.2105, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000180', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '1', '-pop', 'AMR']}}, {'name': 'mutation_overlap_ID0000181', 'type': 'compute', 'runtime': 7.767, 'parents': ['individuals_merge_ID0000011', 'sifting_ID0000012'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'chr1n.tar.gz', 'size': 24897}, {'link': 'input', 'name': 'sifted.SIFT.chr1.txt', 'size': 2126612}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr1-EUR.tar.gz', 'size': 147668}], 'avgCPU': 51.7703, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000181', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '1', '-pop', 'EUR']}}, {'name': 'frequency_ID0000182', 'type': 'compute', 'runtime': 121.158, 'parents': ['individuals_merge_ID0000011', 'sifting_ID0000012'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'chr1n.tar.gz', 'size': 24897}, {'link': 'input', 'name': 'sifted.SIFT.chr1.txt', 'size': 2126612}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr1-EUR-freq.tar.gz', 'size': 273608}], 'avgCPU': 74.9748, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000182', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '1', '-pop', 'EUR']}}, {'name': 'mutation_overlap_ID0000183', 'type': 'compute', 'runtime': 5.341, 'parents': ['individuals_merge_ID0000023', 'sifting_ID0000024'], 'files': [{'link': 'input', 'name': 'chr2n.tar.gz', 'size': 25272}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'sifted.SIFT.chr2.txt', 'size': 1365482}, {'link': 'output', 'name': 'chr2-AFR.tar.gz', 'size': 148773}], 'avgCPU': 79.6106, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000183', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '2', '-pop', 'AFR']}}, {'name': 'frequency_ID0000184', 'type': 'compute', 'runtime': 114.358, 'parents': ['individuals_merge_ID0000023', 'sifting_ID0000024'], 'files': [{'link': 'input', 'name': 'chr2n.tar.gz', 'size': 25272}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'sifted.SIFT.chr2.txt', 'size': 1365482}, {'link': 'output', 'name': 'chr2-AFR-freq.tar.gz', 'size': 276945}], 'avgCPU': 77.3772, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000184', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '2', '-pop', 'AFR']}}, {'name': 'mutation_overlap_ID0000185', 'type': 'compute', 'runtime': 2.906, 'parents': ['individuals_merge_ID0000023', 'sifting_ID0000024'], 'files': [{'link': 'input', 'name': 'chr2n.tar.gz', 'size': 25272}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'input', 'name': 'sifted.SIFT.chr2.txt', 'size': 1365482}, {'link': 'output', 'name': 'chr2-GBR.tar.gz', 'size': 140901}], 'avgCPU': 67.137, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000185', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '2', '-pop', 'GBR']}}, {'name': 'frequency_ID0000186', 'type': 'compute', 'runtime': 105.686, 'parents': ['individuals_merge_ID0000023', 'sifting_ID0000024'], 'files': [{'link': 'input', 'name': 'chr2n.tar.gz', 'size': 25272}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'input', 'name': 'sifted.SIFT.chr2.txt', 'size': 1365482}, {'link': 'output', 'name': 'chr2-GBR-freq.tar.gz', 'size': 224452}], 'avgCPU': 86.2016, 'machine': 'pegasus-4', 'priority': 40, 'id': 'ID0000186', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '2', '-pop', 'GBR']}}, {'name': 'mutation_overlap_ID0000187', 'type': 'compute', 'runtime': 27.429, 'parents': ['individuals_merge_ID0000023', 'sifting_ID0000024'], 'files': [{'link': 'input', 'name': 'chr2n.tar.gz', 'size': 25272}, {'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'sifted.SIFT.chr2.txt', 'size': 1365482}, {'link': 'output', 'name': 'chr2-ALL.tar.gz', 'size': 171953}], 'avgCPU': 73.6994, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000187', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '2', '-pop', 'ALL']}}, {'name': 'frequency_ID0000188', 'type': 'compute', 'runtime': 119.272, 'parents': ['individuals_merge_ID0000023', 'sifting_ID0000024'], 'files': [{'link': 'input', 'name': 'chr2n.tar.gz', 'size': 25272}, {'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'sifted.SIFT.chr2.txt', 'size': 1365482}, {'link': 'output', 'name': 'chr2-ALL-freq.tar.gz', 'size': 291856}], 'avgCPU': 76.3188, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000188', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '2', '-pop', 'ALL']}}, {'name': 'mutation_overlap_ID0000189', 'type': 'compute', 'runtime': 3.674, 'parents': ['individuals_merge_ID0000023', 'sifting_ID0000024'], 'files': [{'link': 'input', 'name': 'chr2n.tar.gz', 'size': 25272}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'sifted.SIFT.chr2.txt', 'size': 1365482}, {'link': 'output', 'name': 'chr2-SAS.tar.gz', 'size': 147412}], 'avgCPU': 91.5623, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000189', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '2', '-pop', 'SAS']}}, {'name': 'frequency_ID0000190', 'type': 'compute', 'runtime': 112.667, 'parents': ['individuals_merge_ID0000023', 'sifting_ID0000024'], 'files': [{'link': 'input', 'name': 'chr2n.tar.gz', 'size': 25272}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'sifted.SIFT.chr2.txt', 'size': 1365482}, {'link': 'output', 'name': 'chr2-SAS-freq.tar.gz', 'size': 268944}], 'avgCPU': 77.745, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000190', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '2', '-pop', 'SAS']}}, {'name': 'mutation_overlap_ID0000191', 'type': 'compute', 'runtime': 3.722, 'parents': ['individuals_merge_ID0000023', 'sifting_ID0000024'], 'files': [{'link': 'input', 'name': 'chr2n.tar.gz', 'size': 25272}, {'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'sifted.SIFT.chr2.txt', 'size': 1365482}, {'link': 'output', 'name': 'chr2-EAS.tar.gz', 'size': 146661}], 'avgCPU': 94.6534, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000191', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '2', '-pop', 'EAS']}}, {'name': 'frequency_ID0000192', 'type': 'compute', 'runtime': 116.578, 'parents': ['individuals_merge_ID0000023', 'sifting_ID0000024'], 'files': [{'link': 'input', 'name': 'chr2n.tar.gz', 'size': 25272}, {'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'sifted.SIFT.chr2.txt', 'size': 1365482}, {'link': 'output', 'name': 'chr2-EAS-freq.tar.gz', 'size': 267986}], 'avgCPU': 76.6568, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000192', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '2', '-pop', 'EAS']}}, {'name': 'mutation_overlap_ID0000193', 'type': 'compute', 'runtime': 2.933, 'parents': ['individuals_merge_ID0000023', 'sifting_ID0000024'], 'files': [{'link': 'input', 'name': 'chr2n.tar.gz', 'size': 25272}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'sifted.SIFT.chr2.txt', 'size': 1365482}, {'link': 'output', 'name': 'chr2-AMR.tar.gz', 'size': 146349}], 'avgCPU': 95.9086, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000193', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '2', '-pop', 'AMR']}}, {'name': 'frequency_ID0000194', 'type': 'compute', 'runtime': 117.273, 'parents': ['individuals_merge_ID0000023', 'sifting_ID0000024'], 'files': [{'link': 'input', 'name': 'chr2n.tar.gz', 'size': 25272}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'sifted.SIFT.chr2.txt', 'size': 1365482}, {'link': 'output', 'name': 'chr2-AMR-freq.tar.gz', 'size': 261746}], 'avgCPU': 76.5052, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000194', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '2', '-pop', 'AMR']}}, {'name': 'mutation_overlap_ID0000195', 'type': 'compute', 'runtime': 4.452, 'parents': ['individuals_merge_ID0000023', 'sifting_ID0000024'], 'files': [{'link': 'input', 'name': 'chr2n.tar.gz', 'size': 25272}, {'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'sifted.SIFT.chr2.txt', 'size': 1365482}, {'link': 'output', 'name': 'chr2-EUR.tar.gz', 'size': 145951}], 'avgCPU': 76.7071, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000195', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '2', '-pop', 'EUR']}}, {'name': 'frequency_ID0000196', 'type': 'compute', 'runtime': 116.099, 'parents': ['individuals_merge_ID0000023', 'sifting_ID0000024'], 'files': [{'link': 'input', 'name': 'chr2n.tar.gz', 'size': 25272}, {'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'sifted.SIFT.chr2.txt', 'size': 1365482}, {'link': 'output', 'name': 'chr2-EUR-freq.tar.gz', 'size': 271613}], 'avgCPU': 75.9541, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000196', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '2', '-pop', 'EUR']}}, {'name': 'mutation_overlap_ID0000197', 'type': 'compute', 'runtime': 6.887, 'parents': ['individuals_merge_ID0000035', 'sifting_ID0000036'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr3n.tar.gz', 'size': 24372}, {'link': 'input', 'name': 'sifted.SIFT.chr3.txt', 'size': 1132161}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'output', 'name': 'chr3-AFR.tar.gz', 'size': 148286}], 'avgCPU': 81.4288, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000197', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '3', '-pop', 'AFR']}}, {'name': 'frequency_ID0000198', 'type': 'compute', 'runtime': 102.392, 'parents': ['individuals_merge_ID0000035', 'sifting_ID0000036'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr3n.tar.gz', 'size': 24372}, {'link': 'input', 'name': 'sifted.SIFT.chr3.txt', 'size': 1132161}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'output', 'name': 'chr3-AFR-freq.tar.gz', 'size': 275040}], 'avgCPU': 88.5313, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000198', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '3', '-pop', 'AFR']}}, {'name': 'mutation_overlap_ID0000199', 'type': 'compute', 'runtime': 6.084, 'parents': ['individuals_merge_ID0000035', 'sifting_ID0000036'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr3n.tar.gz', 'size': 24372}, {'link': 'input', 'name': 'sifted.SIFT.chr3.txt', 'size': 1132161}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'output', 'name': 'chr3-GBR.tar.gz', 'size': 140594}], 'avgCPU': 46.8935, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000199', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '3', '-pop', 'GBR']}}, {'name': 'frequency_ID0000200', 'type': 'compute', 'runtime': 107.189, 'parents': ['individuals_merge_ID0000035', 'sifting_ID0000036'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr3n.tar.gz', 'size': 24372}, {'link': 'input', 'name': 'sifted.SIFT.chr3.txt', 'size': 1132161}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'output', 'name': 'chr3-GBR-freq.tar.gz', 'size': 223609}], 'avgCPU': 85.8148, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000200', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '3', '-pop', 'GBR']}}, {'name': 'mutation_overlap_ID0000201', 'type': 'compute', 'runtime': 27.754, 'parents': ['individuals_merge_ID0000035', 'sifting_ID0000036'], 'files': [{'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'chr3n.tar.gz', 'size': 24372}, {'link': 'input', 'name': 'sifted.SIFT.chr3.txt', 'size': 1132161}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr3-ALL.tar.gz', 'size': 170390}], 'avgCPU': 90.3762, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000201', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '3', '-pop', 'ALL']}}, {'name': 'frequency_ID0000202', 'type': 'compute', 'runtime': 149.628, 'parents': ['individuals_merge_ID0000035', 'sifting_ID0000036'], 'files': [{'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'chr3n.tar.gz', 'size': 24372}, {'link': 'input', 'name': 'sifted.SIFT.chr3.txt', 'size': 1132161}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr3-ALL-freq.tar.gz', 'size': 290745}], 'avgCPU': 60.4359, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000202', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '3', '-pop', 'ALL']}}, {'name': 'mutation_overlap_ID0000203', 'type': 'compute', 'runtime': 7.658, 'parents': ['individuals_merge_ID0000035', 'sifting_ID0000036'], 'files': [{'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'chr3n.tar.gz', 'size': 24372}, {'link': 'input', 'name': 'sifted.SIFT.chr3.txt', 'size': 1132161}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr3-SAS.tar.gz', 'size': 147271}], 'avgCPU': 61.0473, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000203', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '3', '-pop', 'SAS']}}, {'name': 'frequency_ID0000204', 'type': 'compute', 'runtime': 149.612, 'parents': ['individuals_merge_ID0000035', 'sifting_ID0000036'], 'files': [{'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'chr3n.tar.gz', 'size': 24372}, {'link': 'input', 'name': 'sifted.SIFT.chr3.txt', 'size': 1132161}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr3-SAS-freq.tar.gz', 'size': 266837}], 'avgCPU': 58.9445, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000204', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '3', '-pop', 'SAS']}}, {'name': 'mutation_overlap_ID0000205', 'type': 'compute', 'runtime': 10.112, 'parents': ['individuals_merge_ID0000035', 'sifting_ID0000036'], 'files': [{'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'chr3n.tar.gz', 'size': 24372}, {'link': 'input', 'name': 'sifted.SIFT.chr3.txt', 'size': 1132161}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr3-EAS.tar.gz', 'size': 146441}], 'avgCPU': 51.2065, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000205', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '3', '-pop', 'EAS']}}, {'name': 'frequency_ID0000206', 'type': 'compute', 'runtime': 103.47, 'parents': ['individuals_merge_ID0000035', 'sifting_ID0000036'], 'files': [{'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'chr3n.tar.gz', 'size': 24372}, {'link': 'input', 'name': 'sifted.SIFT.chr3.txt', 'size': 1132161}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr3-EAS-freq.tar.gz', 'size': 267659}], 'avgCPU': 86.513, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000206', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '3', '-pop', 'EAS']}}, {'name': 'mutation_overlap_ID0000207', 'type': 'compute', 'runtime': 5.454, 'parents': ['individuals_merge_ID0000035', 'sifting_ID0000036'], 'files': [{'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'chr3n.tar.gz', 'size': 24372}, {'link': 'input', 'name': 'sifted.SIFT.chr3.txt', 'size': 1132161}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr3-AMR.tar.gz', 'size': 146350}], 'avgCPU': 78.5479, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000207', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '3', '-pop', 'AMR']}}, {'name': 'frequency_ID0000208', 'type': 'compute', 'runtime': 103.103, 'parents': ['individuals_merge_ID0000035', 'sifting_ID0000036'], 'files': [{'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'chr3n.tar.gz', 'size': 24372}, {'link': 'input', 'name': 'sifted.SIFT.chr3.txt', 'size': 1132161}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr3-AMR-freq.tar.gz', 'size': 261117}], 'avgCPU': 86.5174, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000208', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '3', '-pop', 'AMR']}}, {'name': 'mutation_overlap_ID0000209', 'type': 'compute', 'runtime': 2.946, 'parents': ['individuals_merge_ID0000035', 'sifting_ID0000036'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'chr3n.tar.gz', 'size': 24372}, {'link': 'input', 'name': 'sifted.SIFT.chr3.txt', 'size': 1132161}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr3-EUR.tar.gz', 'size': 145760}], 'avgCPU': 100.0339, 'machine': 'pegasus-4', 'priority': 40, 'id': 'ID0000209', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '3', '-pop', 'EUR']}}, {'name': 'frequency_ID0000210', 'type': 'compute', 'runtime': 77.404, 'parents': ['individuals_merge_ID0000035', 'sifting_ID0000036'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'chr3n.tar.gz', 'size': 24372}, {'link': 'input', 'name': 'sifted.SIFT.chr3.txt', 'size': 1132161}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr3-EUR-freq.tar.gz', 'size': 268820}], 'avgCPU': 99.9987, 'machine': 'pegasus-4', 'priority': 40, 'id': 'ID0000210', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '3', '-pop', 'EUR']}}, {'name': 'mutation_overlap_ID0000211', 'type': 'compute', 'runtime': 11.836, 'parents': ['individuals_merge_ID0000047', 'sifting_ID0000048'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr4.txt', 'size': 806968}, {'link': 'input', 'name': 'chr4n.tar.gz', 'size': 25083}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr4-AFR.tar.gz', 'size': 146300}], 'avgCPU': 37.369, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000211', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '4', '-pop', 'AFR']}}, {'name': 'frequency_ID0000212', 'type': 'compute', 'runtime': 146.84, 'parents': ['individuals_merge_ID0000047', 'sifting_ID0000048'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr4.txt', 'size': 806968}, {'link': 'input', 'name': 'chr4n.tar.gz', 'size': 25083}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr4-AFR-freq.tar.gz', 'size': 272382}], 'avgCPU': 62.4605, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000212', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '4', '-pop', 'AFR']}}, {'name': 'mutation_overlap_ID0000213', 'type': 'compute', 'runtime': 3.663, 'parents': ['individuals_merge_ID0000047', 'sifting_ID0000048'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr4.txt', 'size': 806968}, {'link': 'input', 'name': 'chr4n.tar.gz', 'size': 25083}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'output', 'name': 'chr4-GBR.tar.gz', 'size': 138236}], 'avgCPU': 59.9509, 'machine': 'pegasus-4', 'priority': 40, 'id': 'ID0000213', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '4', '-pop', 'GBR']}}, {'name': 'frequency_ID0000214', 'type': 'compute', 'runtime': 146.722, 'parents': ['individuals_merge_ID0000047', 'sifting_ID0000048'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr4.txt', 'size': 806968}, {'link': 'input', 'name': 'chr4n.tar.gz', 'size': 25083}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'output', 'name': 'chr4-GBR-freq.tar.gz', 'size': 219540}], 'avgCPU': 62.1147, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000214', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '4', '-pop', 'GBR']}}, {'name': 'mutation_overlap_ID0000215', 'type': 'compute', 'runtime': 22.395, 'parents': ['individuals_merge_ID0000047', 'sifting_ID0000048'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr4.txt', 'size': 806968}, {'link': 'input', 'name': 'chr4n.tar.gz', 'size': 25083}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'output', 'name': 'chr4-ALL.tar.gz', 'size': 168915}], 'avgCPU': 85.0636, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000215', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '4', '-pop', 'ALL']}}, {'name': 'frequency_ID0000216', 'type': 'compute', 'runtime': 100.574, 'parents': ['individuals_merge_ID0000047', 'sifting_ID0000048'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr4.txt', 'size': 806968}, {'link': 'input', 'name': 'chr4n.tar.gz', 'size': 25083}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'output', 'name': 'chr4-ALL-freq.tar.gz', 'size': 290610}], 'avgCPU': 91.5833, 'machine': 'pegasus-4', 'priority': 40, 'id': 'ID0000216', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '4', '-pop', 'ALL']}}, {'name': 'mutation_overlap_ID0000217', 'type': 'compute', 'runtime': 7.414, 'parents': ['individuals_merge_ID0000047', 'sifting_ID0000048'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr4.txt', 'size': 806968}, {'link': 'input', 'name': 'chr4n.tar.gz', 'size': 25083}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr4-SAS.tar.gz', 'size': 144928}], 'avgCPU': 50.9711, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000217', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '4', '-pop', 'SAS']}}, {'name': 'frequency_ID0000218', 'type': 'compute', 'runtime': 139.101, 'parents': ['individuals_merge_ID0000047', 'sifting_ID0000048'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr4.txt', 'size': 806968}, {'link': 'input', 'name': 'chr4n.tar.gz', 'size': 25083}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr4-SAS-freq.tar.gz', 'size': 267056}], 'avgCPU': 73.8967, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000218', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '4', '-pop', 'SAS']}}, {'name': 'mutation_overlap_ID0000219', 'type': 'compute', 'runtime': 4.206, 'parents': ['individuals_merge_ID0000047', 'sifting_ID0000048'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr4.txt', 'size': 806968}, {'link': 'input', 'name': 'chr4n.tar.gz', 'size': 25083}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'output', 'name': 'chr4-EAS.tar.gz', 'size': 144010}], 'avgCPU': 84.9025, 'machine': 'pegasus-4', 'priority': 40, 'id': 'ID0000219', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '4', '-pop', 'EAS']}}, {'name': 'frequency_ID0000220', 'type': 'compute', 'runtime': 141.387, 'parents': ['individuals_merge_ID0000047', 'sifting_ID0000048'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr4.txt', 'size': 806968}, {'link': 'input', 'name': 'chr4n.tar.gz', 'size': 25083}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'output', 'name': 'chr4-EAS-freq.tar.gz', 'size': 269002}], 'avgCPU': 73.11, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000220', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '4', '-pop', 'EAS']}}, {'name': 'mutation_overlap_ID0000221', 'type': 'compute', 'runtime': 3.09, 'parents': ['individuals_merge_ID0000047', 'sifting_ID0000048'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr4.txt', 'size': 806968}, {'link': 'input', 'name': 'chr4n.tar.gz', 'size': 25083}, {'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr4-AMR.tar.gz', 'size': 143786}], 'avgCPU': 98.2524, 'machine': 'pegasus-4', 'priority': 40, 'id': 'ID0000221', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '4', '-pop', 'AMR']}}, {'name': 'frequency_ID0000222', 'type': 'compute', 'runtime': 140.504, 'parents': ['individuals_merge_ID0000047', 'sifting_ID0000048'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr4.txt', 'size': 806968}, {'link': 'input', 'name': 'chr4n.tar.gz', 'size': 25083}, {'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr4-AMR-freq.tar.gz', 'size': 261991}], 'avgCPU': 71.7745, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000222', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '4', '-pop', 'AMR']}}, {'name': 'mutation_overlap_ID0000223', 'type': 'compute', 'runtime': 3.474, 'parents': ['individuals_merge_ID0000047', 'sifting_ID0000048'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'sifted.SIFT.chr4.txt', 'size': 806968}, {'link': 'input', 'name': 'chr4n.tar.gz', 'size': 25083}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr4-EUR.tar.gz', 'size': 143287}], 'avgCPU': 95.1929, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000223', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '4', '-pop', 'EUR']}}, {'name': 'frequency_ID0000224', 'type': 'compute', 'runtime': 102.16, 'parents': ['individuals_merge_ID0000047', 'sifting_ID0000048'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'sifted.SIFT.chr4.txt', 'size': 806968}, {'link': 'input', 'name': 'chr4n.tar.gz', 'size': 25083}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr4-EUR-freq.tar.gz', 'size': 268273}], 'avgCPU': 90.5256, 'machine': 'pegasus-4', 'priority': 40, 'id': 'ID0000224', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '4', '-pop', 'EUR']}}, {'name': 'mutation_overlap_ID0000225', 'type': 'compute', 'runtime': 6.493, 'parents': ['individuals_merge_ID0000059', 'sifting_ID0000060'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr5.txt', 'size': 922870}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'chr5n.tar.gz', 'size': 24353}, {'link': 'output', 'name': 'chr5-AFR.tar.gz', 'size': 147402}], 'avgCPU': 64.0998, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000225', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '5', '-pop', 'AFR']}}, {'name': 'frequency_ID0000226', 'type': 'compute', 'runtime': 137.245, 'parents': ['individuals_merge_ID0000059', 'sifting_ID0000060'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr5.txt', 'size': 922870}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'chr5n.tar.gz', 'size': 24353}, {'link': 'output', 'name': 'chr5-AFR-freq.tar.gz', 'size': 277646}], 'avgCPU': 68.3027, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000226', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '5', '-pop', 'AFR']}}, {'name': 'mutation_overlap_ID0000227', 'type': 'compute', 'runtime': 3.495, 'parents': ['individuals_merge_ID0000059', 'sifting_ID0000060'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr5.txt', 'size': 922870}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'input', 'name': 'chr5n.tar.gz', 'size': 24353}, {'link': 'output', 'name': 'chr5-GBR.tar.gz', 'size': 139775}], 'avgCPU': 55.8226, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000227', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '5', '-pop', 'GBR']}}, {'name': 'frequency_ID0000228', 'type': 'compute', 'runtime': 174.663, 'parents': ['individuals_merge_ID0000059', 'sifting_ID0000060'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr5.txt', 'size': 922870}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'input', 'name': 'chr5n.tar.gz', 'size': 24353}, {'link': 'output', 'name': 'chr5-GBR-freq.tar.gz', 'size': 226677}], 'avgCPU': 52.4593, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000228', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '5', '-pop', 'GBR']}}, {'name': 'mutation_overlap_ID0000229', 'type': 'compute', 'runtime': 43.109, 'parents': ['individuals_merge_ID0000059', 'sifting_ID0000060'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr5.txt', 'size': 922870}, {'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr5n.tar.gz', 'size': 24353}, {'link': 'output', 'name': 'chr5-ALL.tar.gz', 'size': 170063}], 'avgCPU': 45.2295, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000229', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '5', '-pop', 'ALL']}}, {'name': 'frequency_ID0000230', 'type': 'compute', 'runtime': 146.457, 'parents': ['individuals_merge_ID0000059', 'sifting_ID0000060'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr5.txt', 'size': 922870}, {'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr5n.tar.gz', 'size': 24353}, {'link': 'output', 'name': 'chr5-ALL-freq.tar.gz', 'size': 293582}], 'avgCPU': 67.1822, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000230', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '5', '-pop', 'ALL']}}, {'name': 'mutation_overlap_ID0000231', 'type': 'compute', 'runtime': 8.9, 'parents': ['individuals_merge_ID0000059', 'sifting_ID0000060'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr5.txt', 'size': 922870}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'chr5n.tar.gz', 'size': 24353}, {'link': 'output', 'name': 'chr5-SAS.tar.gz', 'size': 145657}], 'avgCPU': 40.1798, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000231', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '5', '-pop', 'SAS']}}, {'name': 'frequency_ID0000232', 'type': 'compute', 'runtime': 133.586, 'parents': ['individuals_merge_ID0000059', 'sifting_ID0000060'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr5.txt', 'size': 922870}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'chr5n.tar.gz', 'size': 24353}, {'link': 'output', 'name': 'chr5-SAS-freq.tar.gz', 'size': 269540}], 'avgCPU': 69.9751, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000232', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '5', '-pop', 'SAS']}}, {'name': 'mutation_overlap_ID0000233', 'type': 'compute', 'runtime': 5.057, 'parents': ['individuals_merge_ID0000059', 'sifting_ID0000060'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr5.txt', 'size': 922870}, {'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr5n.tar.gz', 'size': 24353}, {'link': 'output', 'name': 'chr5-EAS.tar.gz', 'size': 145010}], 'avgCPU': 71.1291, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000233', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '5', '-pop', 'EAS']}}, {'name': 'frequency_ID0000234', 'type': 'compute', 'runtime': 135.427, 'parents': ['individuals_merge_ID0000059', 'sifting_ID0000060'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr5.txt', 'size': 922870}, {'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr5n.tar.gz', 'size': 24353}, {'link': 'output', 'name': 'chr5-EAS-freq.tar.gz', 'size': 271573}], 'avgCPU': 69.3938, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000234', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '5', '-pop', 'EAS']}}, {'name': 'mutation_overlap_ID0000235', 'type': 'compute', 'runtime': 8.26, 'parents': ['individuals_merge_ID0000059', 'sifting_ID0000060'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr5.txt', 'size': 922870}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'chr5n.tar.gz', 'size': 24353}, {'link': 'output', 'name': 'chr5-AMR.tar.gz', 'size': 144773}], 'avgCPU': 33.8499, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000235', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '5', '-pop', 'AMR']}}, {'name': 'frequency_ID0000236', 'type': 'compute', 'runtime': 135.108, 'parents': ['individuals_merge_ID0000059', 'sifting_ID0000060'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr5.txt', 'size': 922870}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'chr5n.tar.gz', 'size': 24353}, {'link': 'output', 'name': 'chr5-AMR-freq.tar.gz', 'size': 264102}], 'avgCPU': 69.4097, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000236', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '5', '-pop', 'AMR']}}, {'name': 'mutation_overlap_ID0000237', 'type': 'compute', 'runtime': 6.006, 'parents': ['individuals_merge_ID0000059', 'sifting_ID0000060'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr5.txt', 'size': 922870}, {'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr5n.tar.gz', 'size': 24353}, {'link': 'output', 'name': 'chr5-EUR.tar.gz', 'size': 144021}], 'avgCPU': 57.9421, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000237', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '5', '-pop', 'EUR']}}, {'name': 'frequency_ID0000238', 'type': 'compute', 'runtime': 131.081, 'parents': ['individuals_merge_ID0000059', 'sifting_ID0000060'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr5.txt', 'size': 922870}, {'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr5n.tar.gz', 'size': 24353}, {'link': 'output', 'name': 'chr5-EUR-freq.tar.gz', 'size': 271930}], 'avgCPU': 70.5037, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000238', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '5', '-pop', 'EUR']}}, {'name': 'mutation_overlap_ID0000239', 'type': 'compute', 'runtime': 11.015, 'parents': ['individuals_merge_ID0000071', 'sifting_ID0000072'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr6.txt', 'size': 1063065}, {'link': 'input', 'name': 'chr6n.tar.gz', 'size': 24659}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6-AFR.tar.gz', 'size': 148019}], 'avgCPU': 38.0663, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000239', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '6', '-pop', 'AFR']}}, {'name': 'frequency_ID0000240', 'type': 'compute', 'runtime': 184.849, 'parents': ['individuals_merge_ID0000071', 'sifting_ID0000072'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr6.txt', 'size': 1063065}, {'link': 'input', 'name': 'chr6n.tar.gz', 'size': 24659}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6-AFR-freq.tar.gz', 'size': 281426}], 'avgCPU': 49.6778, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000240', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '6', '-pop', 'AFR']}}, {'name': 'mutation_overlap_ID0000241', 'type': 'compute', 'runtime': 2.372, 'parents': ['individuals_merge_ID0000071', 'sifting_ID0000072'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'sifted.SIFT.chr6.txt', 'size': 1063065}, {'link': 'input', 'name': 'chr6n.tar.gz', 'size': 24659}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'output', 'name': 'chr6-GBR.tar.gz', 'size': 140571}], 'avgCPU': 83.0944, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000241', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '6', '-pop', 'GBR']}}, {'name': 'frequency_ID0000242', 'type': 'compute', 'runtime': 174.271, 'parents': ['individuals_merge_ID0000071', 'sifting_ID0000072'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'sifted.SIFT.chr6.txt', 'size': 1063065}, {'link': 'input', 'name': 'chr6n.tar.gz', 'size': 24659}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'output', 'name': 'chr6-GBR-freq.tar.gz', 'size': 228868}], 'avgCPU': 51.5835, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000242', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '6', '-pop', 'GBR']}}, {'name': 'mutation_overlap_ID0000243', 'type': 'compute', 'runtime': 88.882, 'parents': ['individuals_merge_ID0000071', 'sifting_ID0000072'], 'files': [{'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'sifted.SIFT.chr6.txt', 'size': 1063065}, {'link': 'input', 'name': 'chr6n.tar.gz', 'size': 24659}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6-ALL.tar.gz', 'size': 171575}], 'avgCPU': 21.7974, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000243', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '6', '-pop', 'ALL']}}, {'name': 'frequency_ID0000244', 'type': 'compute', 'runtime': 132.769, 'parents': ['individuals_merge_ID0000071', 'sifting_ID0000072'], 'files': [{'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'sifted.SIFT.chr6.txt', 'size': 1063065}, {'link': 'input', 'name': 'chr6n.tar.gz', 'size': 24659}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6-ALL-freq.tar.gz', 'size': 294588}], 'avgCPU': 69.9531, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000244', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '6', '-pop', 'ALL']}}, {'name': 'mutation_overlap_ID0000245', 'type': 'compute', 'runtime': 12.429, 'parents': ['individuals_merge_ID0000071', 'sifting_ID0000072'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr6.txt', 'size': 1063065}, {'link': 'input', 'name': 'chr6n.tar.gz', 'size': 24659}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6-SAS.tar.gz', 'size': 147345}], 'avgCPU': 28.7714, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000245', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '6', '-pop', 'SAS']}}, {'name': 'frequency_ID0000246', 'type': 'compute', 'runtime': 177.563, 'parents': ['individuals_merge_ID0000071', 'sifting_ID0000072'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr6.txt', 'size': 1063065}, {'link': 'input', 'name': 'chr6n.tar.gz', 'size': 24659}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6-SAS-freq.tar.gz', 'size': 272078}], 'avgCPU': 51.295, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000246', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '6', '-pop', 'SAS']}}, {'name': 'mutation_overlap_ID0000247', 'type': 'compute', 'runtime': 9.434, 'parents': ['individuals_merge_ID0000071', 'sifting_ID0000072'], 'files': [{'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'sifted.SIFT.chr6.txt', 'size': 1063065}, {'link': 'input', 'name': 'chr6n.tar.gz', 'size': 24659}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6-EAS.tar.gz', 'size': 146496}], 'avgCPU': 40.3222, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000247', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '6', '-pop', 'EAS']}}, {'name': 'frequency_ID0000248', 'type': 'compute', 'runtime': 186.02, 'parents': ['individuals_merge_ID0000071', 'sifting_ID0000072'], 'files': [{'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'sifted.SIFT.chr6.txt', 'size': 1063065}, {'link': 'input', 'name': 'chr6n.tar.gz', 'size': 24659}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6-EAS-freq.tar.gz', 'size': 273431}], 'avgCPU': 49.1442, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000248', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '6', '-pop', 'EAS']}}, {'name': 'mutation_overlap_ID0000249', 'type': 'compute', 'runtime': 4.463, 'parents': ['individuals_merge_ID0000071', 'sifting_ID0000072'], 'files': [{'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'sifted.SIFT.chr6.txt', 'size': 1063065}, {'link': 'input', 'name': 'chr6n.tar.gz', 'size': 24659}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6-AMR.tar.gz', 'size': 145913}], 'avgCPU': 63.8584, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000249', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '6', '-pop', 'AMR']}}, {'name': 'frequency_ID0000250', 'type': 'compute', 'runtime': 129.698, 'parents': ['individuals_merge_ID0000071', 'sifting_ID0000072'], 'files': [{'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'sifted.SIFT.chr6.txt', 'size': 1063065}, {'link': 'input', 'name': 'chr6n.tar.gz', 'size': 24659}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6-AMR-freq.tar.gz', 'size': 264667}], 'avgCPU': 69.4537, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000250', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '6', '-pop', 'AMR']}}, {'name': 'mutation_overlap_ID0000251', 'type': 'compute', 'runtime': 6.718, 'parents': ['individuals_merge_ID0000071', 'sifting_ID0000072'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'sifted.SIFT.chr6.txt', 'size': 1063065}, {'link': 'input', 'name': 'chr6n.tar.gz', 'size': 24659}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6-EUR.tar.gz', 'size': 145728}], 'avgCPU': 51.2504, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000251', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '6', '-pop', 'EUR']}}, {'name': 'frequency_ID0000252', 'type': 'compute', 'runtime': 181.745, 'parents': ['individuals_merge_ID0000071', 'sifting_ID0000072'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'sifted.SIFT.chr6.txt', 'size': 1063065}, {'link': 'input', 'name': 'chr6n.tar.gz', 'size': 24659}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr6-EUR-freq.tar.gz', 'size': 274068}], 'avgCPU': 50.2314, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000252', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '6', '-pop', 'EUR']}}, {'name': 'mutation_overlap_ID0000253', 'type': 'compute', 'runtime': 8.916, 'parents': ['individuals_merge_ID0000083', 'sifting_ID0000084'], 'files': [{'link': 'input', 'name': 'chr7n.tar.gz', 'size': 24453}, {'link': 'input', 'name': 'sifted.SIFT.chr7.txt', 'size': 911594}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr7-AFR.tar.gz', 'size': 146677}], 'avgCPU': 45.8389, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000253', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '7', '-pop', 'AFR']}}, {'name': 'frequency_ID0000254', 'type': 'compute', 'runtime': 134.776, 'parents': ['individuals_merge_ID0000083', 'sifting_ID0000084'], 'files': [{'link': 'input', 'name': 'chr7n.tar.gz', 'size': 24453}, {'link': 'input', 'name': 'sifted.SIFT.chr7.txt', 'size': 911594}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr7-AFR-freq.tar.gz', 'size': 278838}], 'avgCPU': 70.0288, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000254', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '7', '-pop', 'AFR']}}, {'name': 'mutation_overlap_ID0000255', 'type': 'compute', 'runtime': 1.968, 'parents': ['individuals_merge_ID0000083', 'sifting_ID0000084'], 'files': [{'link': 'input', 'name': 'chr7n.tar.gz', 'size': 24453}, {'link': 'input', 'name': 'sifted.SIFT.chr7.txt', 'size': 911594}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'output', 'name': 'chr7-GBR.tar.gz', 'size': 139335}], 'avgCPU': 99.9492, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000255', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '7', '-pop', 'GBR']}}, {'name': 'frequency_ID0000256', 'type': 'compute', 'runtime': 175.698, 'parents': ['individuals_merge_ID0000083', 'sifting_ID0000084'], 'files': [{'link': 'input', 'name': 'chr7n.tar.gz', 'size': 24453}, {'link': 'input', 'name': 'sifted.SIFT.chr7.txt', 'size': 911594}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'output', 'name': 'chr7-GBR-freq.tar.gz', 'size': 226215}], 'avgCPU': 52.2926, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000256', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '7', '-pop', 'GBR']}}, {'name': 'mutation_overlap_ID0000257', 'type': 'compute', 'runtime': 40.916, 'parents': ['individuals_merge_ID0000083', 'sifting_ID0000084'], 'files': [{'link': 'input', 'name': 'chr7n.tar.gz', 'size': 24453}, {'link': 'input', 'name': 'sifted.SIFT.chr7.txt', 'size': 911594}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'output', 'name': 'chr7-ALL.tar.gz', 'size': 169992}], 'avgCPU': 47.947, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000257', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '7', '-pop', 'ALL']}}, {'name': 'frequency_ID0000258', 'type': 'compute', 'runtime': 166.135, 'parents': ['individuals_merge_ID0000083', 'sifting_ID0000084'], 'files': [{'link': 'input', 'name': 'chr7n.tar.gz', 'size': 24453}, {'link': 'input', 'name': 'sifted.SIFT.chr7.txt', 'size': 911594}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'output', 'name': 'chr7-ALL-freq.tar.gz', 'size': 294791}], 'avgCPU': 55.8594, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000258', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '7', '-pop', 'ALL']}}, {'name': 'mutation_overlap_ID0000259', 'type': 'compute', 'runtime': 4.786, 'parents': ['individuals_merge_ID0000083', 'sifting_ID0000084'], 'files': [{'link': 'input', 'name': 'chr7n.tar.gz', 'size': 24453}, {'link': 'input', 'name': 'sifted.SIFT.chr7.txt', 'size': 911594}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr7-SAS.tar.gz', 'size': 145631}], 'avgCPU': 69.4735, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000259', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '7', '-pop', 'SAS']}}, {'name': 'frequency_ID0000260', 'type': 'compute', 'runtime': 174.094, 'parents': ['individuals_merge_ID0000083', 'sifting_ID0000084'], 'files': [{'link': 'input', 'name': 'chr7n.tar.gz', 'size': 24453}, {'link': 'input', 'name': 'sifted.SIFT.chr7.txt', 'size': 911594}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr7-SAS-freq.tar.gz', 'size': 270398}], 'avgCPU': 52.6342, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000260', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '7', '-pop', 'SAS']}}, {'name': 'mutation_overlap_ID0000261', 'type': 'compute', 'runtime': 10.162, 'parents': ['individuals_merge_ID0000083', 'sifting_ID0000084'], 'files': [{'link': 'input', 'name': 'chr7n.tar.gz', 'size': 24453}, {'link': 'input', 'name': 'sifted.SIFT.chr7.txt', 'size': 911594}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'output', 'name': 'chr7-EAS.tar.gz', 'size': 144791}], 'avgCPU': 32.1885, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000261', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '7', '-pop', 'EAS']}}, {'name': 'frequency_ID0000262', 'type': 'compute', 'runtime': 173.211, 'parents': ['individuals_merge_ID0000083', 'sifting_ID0000084'], 'files': [{'link': 'input', 'name': 'chr7n.tar.gz', 'size': 24453}, {'link': 'input', 'name': 'sifted.SIFT.chr7.txt', 'size': 911594}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'output', 'name': 'chr7-EAS-freq.tar.gz', 'size': 271888}], 'avgCPU': 53.41, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000262', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '7', '-pop', 'EAS']}}, {'name': 'mutation_overlap_ID0000263', 'type': 'compute', 'runtime': 5.199, 'parents': ['individuals_merge_ID0000083', 'sifting_ID0000084'], 'files': [{'link': 'input', 'name': 'chr7n.tar.gz', 'size': 24453}, {'link': 'input', 'name': 'sifted.SIFT.chr7.txt', 'size': 911594}, {'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr7-AMR.tar.gz', 'size': 144308}], 'avgCPU': 54.9144, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000263', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '7', '-pop', 'AMR']}}, {'name': 'frequency_ID0000264', 'type': 'compute', 'runtime': 129.165, 'parents': ['individuals_merge_ID0000083', 'sifting_ID0000084'], 'files': [{'link': 'input', 'name': 'chr7n.tar.gz', 'size': 24453}, {'link': 'input', 'name': 'sifted.SIFT.chr7.txt', 'size': 911594}, {'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr7-AMR-freq.tar.gz', 'size': 264503}], 'avgCPU': 71.0084, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000264', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '7', '-pop', 'AMR']}}, {'name': 'mutation_overlap_ID0000265', 'type': 'compute', 'runtime': 6.226, 'parents': ['individuals_merge_ID0000083', 'sifting_ID0000084'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'chr7n.tar.gz', 'size': 24453}, {'link': 'input', 'name': 'sifted.SIFT.chr7.txt', 'size': 911594}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr7-EUR.tar.gz', 'size': 143986}], 'avgCPU': 58.3681, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000265', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '7', '-pop', 'EUR']}}, {'name': 'frequency_ID0000266', 'type': 'compute', 'runtime': 178.462, 'parents': ['individuals_merge_ID0000083', 'sifting_ID0000084'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'chr7n.tar.gz', 'size': 24453}, {'link': 'input', 'name': 'sifted.SIFT.chr7.txt', 'size': 911594}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr7-EUR-freq.tar.gz', 'size': 273116}], 'avgCPU': 51.0422, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000266', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '7', '-pop', 'EUR']}}, {'name': 'mutation_overlap_ID0000267', 'type': 'compute', 'runtime': 5.981, 'parents': ['sifting_ID0000096', 'individuals_merge_ID0000095'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'sifted.SIFT.chr8.txt', 'size': 697067}, {'link': 'input', 'name': 'chr8n.tar.gz', 'size': 24288}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'output', 'name': 'chr8-AFR.tar.gz', 'size': 146485}], 'avgCPU': 64.6213, 'machine': 'pegasus-4', 'priority': 40, 'id': 'ID0000267', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '8', '-pop', 'AFR']}}, {'name': 'frequency_ID0000268', 'type': 'compute', 'runtime': 103.416, 'parents': ['sifting_ID0000096', 'individuals_merge_ID0000095'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'sifted.SIFT.chr8.txt', 'size': 697067}, {'link': 'input', 'name': 'chr8n.tar.gz', 'size': 24288}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'output', 'name': 'chr8-AFR-freq.tar.gz', 'size': 274519}], 'avgCPU': 86.9256, 'machine': 'pegasus-4', 'priority': 40, 'id': 'ID0000268', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '8', '-pop', 'AFR']}}, {'name': 'mutation_overlap_ID0000269', 'type': 'compute', 'runtime': 1.801, 'parents': ['sifting_ID0000096', 'individuals_merge_ID0000095'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'sifted.SIFT.chr8.txt', 'size': 697067}, {'link': 'input', 'name': 'chr8n.tar.gz', 'size': 24288}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'output', 'name': 'chr8-GBR.tar.gz', 'size': 139266}], 'avgCPU': 100.0, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000269', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '8', '-pop', 'GBR']}}, {'name': 'frequency_ID0000270', 'type': 'compute', 'runtime': 116.555, 'parents': ['sifting_ID0000096', 'individuals_merge_ID0000095'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'sifted.SIFT.chr8.txt', 'size': 697067}, {'link': 'input', 'name': 'chr8n.tar.gz', 'size': 24288}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'output', 'name': 'chr8-GBR-freq.tar.gz', 'size': 222496}], 'avgCPU': 74.8393, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000270', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '8', '-pop', 'GBR']}}, {'name': 'mutation_overlap_ID0000271', 'type': 'compute', 'runtime': 18.768, 'parents': ['sifting_ID0000096', 'individuals_merge_ID0000095'], 'files': [{'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'sifted.SIFT.chr8.txt', 'size': 697067}, {'link': 'input', 'name': 'chr8n.tar.gz', 'size': 24288}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr8-ALL.tar.gz', 'size': 168869}], 'avgCPU': 99.4885, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000271', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '8', '-pop', 'ALL']}}, {'name': 'frequency_ID0000272', 'type': 'compute', 'runtime': 103.736, 'parents': ['sifting_ID0000096', 'individuals_merge_ID0000095'], 'files': [{'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'sifted.SIFT.chr8.txt', 'size': 697067}, {'link': 'input', 'name': 'chr8n.tar.gz', 'size': 24288}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr8-ALL-freq.tar.gz', 'size': 291135}], 'avgCPU': 87.3708, 'machine': 'pegasus-4', 'priority': 40, 'id': 'ID0000272', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '8', '-pop', 'ALL']}}, {'name': 'mutation_overlap_ID0000273', 'type': 'compute', 'runtime': 3.106, 'parents': ['sifting_ID0000096', 'individuals_merge_ID0000095'], 'files': [{'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'sifted.SIFT.chr8.txt', 'size': 697067}, {'link': 'input', 'name': 'chr8n.tar.gz', 'size': 24288}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr8-SAS.tar.gz', 'size': 145380}], 'avgCPU': 99.9034, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000273', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '8', '-pop', 'SAS']}}, {'name': 'frequency_ID0000274', 'type': 'compute', 'runtime': 103.667, 'parents': ['sifting_ID0000096', 'individuals_merge_ID0000095'], 'files': [{'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'sifted.SIFT.chr8.txt', 'size': 697067}, {'link': 'input', 'name': 'chr8n.tar.gz', 'size': 24288}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr8-SAS-freq.tar.gz', 'size': 266379}], 'avgCPU': 86.6418, 'machine': 'pegasus-4', 'priority': 40, 'id': 'ID0000274', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '8', '-pop', 'SAS']}}, {'name': 'mutation_overlap_ID0000275', 'type': 'compute', 'runtime': 3.796, 'parents': ['sifting_ID0000096', 'individuals_merge_ID0000095'], 'files': [{'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'sifted.SIFT.chr8.txt', 'size': 697067}, {'link': 'input', 'name': 'chr8n.tar.gz', 'size': 24288}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr8-EAS.tar.gz', 'size': 144634}], 'avgCPU': 81.981, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000275', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '8', '-pop', 'EAS']}}, {'name': 'frequency_ID0000276', 'type': 'compute', 'runtime': 110.844, 'parents': ['sifting_ID0000096', 'individuals_merge_ID0000095'], 'files': [{'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'sifted.SIFT.chr8.txt', 'size': 697067}, {'link': 'input', 'name': 'chr8n.tar.gz', 'size': 24288}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr8-EAS-freq.tar.gz', 'size': 265733}], 'avgCPU': 81.3359, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000276', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '8', '-pop', 'EAS']}}, {'name': 'mutation_overlap_ID0000277', 'type': 'compute', 'runtime': 3.28, 'parents': ['sifting_ID0000096', 'individuals_merge_ID0000095'], 'files': [{'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'sifted.SIFT.chr8.txt', 'size': 697067}, {'link': 'input', 'name': 'chr8n.tar.gz', 'size': 24288}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr8-AMR.tar.gz', 'size': 144153}], 'avgCPU': 83.2317, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000277', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '8', '-pop', 'AMR']}}, {'name': 'frequency_ID0000278', 'type': 'compute', 'runtime': 102.438, 'parents': ['sifting_ID0000096', 'individuals_merge_ID0000095'], 'files': [{'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'sifted.SIFT.chr8.txt', 'size': 697067}, {'link': 'input', 'name': 'chr8n.tar.gz', 'size': 24288}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr8-AMR-freq.tar.gz', 'size': 261279}], 'avgCPU': 87.1308, 'machine': 'pegasus-4', 'priority': 40, 'id': 'ID0000278', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '8', '-pop', 'AMR']}}, {'name': 'mutation_overlap_ID0000279', 'type': 'compute', 'runtime': 3.516, 'parents': ['sifting_ID0000096', 'individuals_merge_ID0000095'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'sifted.SIFT.chr8.txt', 'size': 697067}, {'link': 'input', 'name': 'chr8n.tar.gz', 'size': 24288}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr8-EUR.tar.gz', 'size': 143698}], 'avgCPU': 93.3447, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000279', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '8', '-pop', 'EUR']}}, {'name': 'frequency_ID0000280', 'type': 'compute', 'runtime': 112.081, 'parents': ['sifting_ID0000096', 'individuals_merge_ID0000095'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'sifted.SIFT.chr8.txt', 'size': 697067}, {'link': 'input', 'name': 'chr8n.tar.gz', 'size': 24288}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr8-EUR-freq.tar.gz', 'size': 267510}], 'avgCPU': 79.604, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000280', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '8', '-pop', 'EUR']}}, {'name': 'mutation_overlap_ID0000281', 'type': 'compute', 'runtime': 13.574, 'parents': ['sifting_ID0000108', 'individuals_merge_ID0000107'], 'files': [{'link': 'input', 'name': 'chr9n.tar.gz', 'size': 25101}, {'link': 'input', 'name': 'sifted.SIFT.chr9.txt', 'size': 836365}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr9-AFR.tar.gz', 'size': 147207}], 'avgCPU': 37.255, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000281', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '9', '-pop', 'AFR']}}, {'name': 'frequency_ID0000282', 'type': 'compute', 'runtime': 122.711, 'parents': ['sifting_ID0000108', 'individuals_merge_ID0000107'], 'files': [{'link': 'input', 'name': 'chr9n.tar.gz', 'size': 25101}, {'link': 'input', 'name': 'sifted.SIFT.chr9.txt', 'size': 836365}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr9-AFR-freq.tar.gz', 'size': 274073}], 'avgCPU': 72.4377, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000282', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '9', '-pop', 'AFR']}}, {'name': 'mutation_overlap_ID0000283', 'type': 'compute', 'runtime': 9.977, 'parents': ['sifting_ID0000108', 'individuals_merge_ID0000107'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr9n.tar.gz', 'size': 25101}, {'link': 'input', 'name': 'sifted.SIFT.chr9.txt', 'size': 836365}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'output', 'name': 'chr9-GBR.tar.gz', 'size': 139554}], 'avgCPU': 23.1633, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000283', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '9', '-pop', 'GBR']}}, {'name': 'frequency_ID0000284', 'type': 'compute', 'runtime': 113.194, 'parents': ['sifting_ID0000108', 'individuals_merge_ID0000107'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr9n.tar.gz', 'size': 25101}, {'link': 'input', 'name': 'sifted.SIFT.chr9.txt', 'size': 836365}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'output', 'name': 'chr9-GBR-freq.tar.gz', 'size': 220881}], 'avgCPU': 79.7949, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000284', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '9', '-pop', 'GBR']}}, {'name': 'mutation_overlap_ID0000285', 'type': 'compute', 'runtime': 22.172, 'parents': ['sifting_ID0000108', 'individuals_merge_ID0000107'], 'files': [{'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'chr9n.tar.gz', 'size': 25101}, {'link': 'input', 'name': 'sifted.SIFT.chr9.txt', 'size': 836365}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr9-ALL.tar.gz', 'size': 169087}], 'avgCPU': 85.0216, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000285', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '9', '-pop', 'ALL']}}, {'name': 'frequency_ID0000286', 'type': 'compute', 'runtime': 116.086, 'parents': ['sifting_ID0000108', 'individuals_merge_ID0000107'], 'files': [{'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'chr9n.tar.gz', 'size': 25101}, {'link': 'input', 'name': 'sifted.SIFT.chr9.txt', 'size': 836365}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr9-ALL-freq.tar.gz', 'size': 290796}], 'avgCPU': 77.7553, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000286', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '9', '-pop', 'ALL']}}, {'name': 'mutation_overlap_ID0000287', 'type': 'compute', 'runtime': 14.309, 'parents': ['sifting_ID0000108', 'individuals_merge_ID0000107'], 'files': [{'link': 'input', 'name': 'chr9n.tar.gz', 'size': 25101}, {'link': 'input', 'name': 'sifted.SIFT.chr9.txt', 'size': 836365}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr9-SAS.tar.gz', 'size': 146592}], 'avgCPU': 28.7441, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000287', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '9', '-pop', 'SAS']}}, {'name': 'frequency_ID0000288', 'type': 'compute', 'runtime': 116.029, 'parents': ['sifting_ID0000108', 'individuals_merge_ID0000107'], 'files': [{'link': 'input', 'name': 'chr9n.tar.gz', 'size': 25101}, {'link': 'input', 'name': 'sifted.SIFT.chr9.txt', 'size': 836365}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr9-SAS-freq.tar.gz', 'size': 267498}], 'avgCPU': 77.1195, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000288', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '9', '-pop', 'SAS']}}, {'name': 'mutation_overlap_ID0000289', 'type': 'compute', 'runtime': 11.465, 'parents': ['sifting_ID0000108', 'individuals_merge_ID0000107'], 'files': [{'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'chr9n.tar.gz', 'size': 25101}, {'link': 'input', 'name': 'sifted.SIFT.chr9.txt', 'size': 836365}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr9-EAS.tar.gz', 'size': 145290}], 'avgCPU': 33.3624, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000289', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '9', '-pop', 'EAS']}}, {'name': 'frequency_ID0000290', 'type': 'compute', 'runtime': 124.971, 'parents': ['sifting_ID0000108', 'individuals_merge_ID0000107'], 'files': [{'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'chr9n.tar.gz', 'size': 25101}, {'link': 'input', 'name': 'sifted.SIFT.chr9.txt', 'size': 836365}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr9-EAS-freq.tar.gz', 'size': 267886}], 'avgCPU': 70.794, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000290', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '9', '-pop', 'EAS']}}, {'name': 'mutation_overlap_ID0000291', 'type': 'compute', 'runtime': 11.014, 'parents': ['sifting_ID0000108', 'individuals_merge_ID0000107'], 'files': [{'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'chr9n.tar.gz', 'size': 25101}, {'link': 'input', 'name': 'sifted.SIFT.chr9.txt', 'size': 836365}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr9-AMR.tar.gz', 'size': 144779}], 'avgCPU': 31.4509, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000291', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '9', '-pop', 'AMR']}}, {'name': 'frequency_ID0000292', 'type': 'compute', 'runtime': 122.864, 'parents': ['sifting_ID0000108', 'individuals_merge_ID0000107'], 'files': [{'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'chr9n.tar.gz', 'size': 25101}, {'link': 'input', 'name': 'sifted.SIFT.chr9.txt', 'size': 836365}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr9-AMR-freq.tar.gz', 'size': 260507}], 'avgCPU': 72.3011, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000292', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '9', '-pop', 'AMR']}}, {'name': 'mutation_overlap_ID0000293', 'type': 'compute', 'runtime': 15.477, 'parents': ['sifting_ID0000108', 'individuals_merge_ID0000107'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'chr9n.tar.gz', 'size': 25101}, {'link': 'input', 'name': 'sifted.SIFT.chr9.txt', 'size': 836365}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr9-EUR.tar.gz', 'size': 144384}], 'avgCPU': 28.0028, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000293', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '9', '-pop', 'EUR']}}, {'name': 'frequency_ID0000294', 'type': 'compute', 'runtime': 120.045, 'parents': ['sifting_ID0000108', 'individuals_merge_ID0000107'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'chr9n.tar.gz', 'size': 25101}, {'link': 'input', 'name': 'sifted.SIFT.chr9.txt', 'size': 836365}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr9-EUR-freq.tar.gz', 'size': 267257}], 'avgCPU': 73.7698, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000294', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '9', '-pop', 'EUR']}}, {'name': 'mutation_overlap_ID0000295', 'type': 'compute', 'runtime': 13.156, 'parents': ['individuals_merge_ID0000119', 'sifting_ID0000120'], 'files': [{'link': 'input', 'name': 'chr10n.tar.gz', 'size': 24615}, {'link': 'input', 'name': 'sifted.SIFT.chr10.txt', 'size': 797176}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10-AFR.tar.gz', 'size': 147291}], 'avgCPU': 39.2216, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000295', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '10', '-pop', 'AFR']}}, {'name': 'frequency_ID0000296', 'type': 'compute', 'runtime': 112.891, 'parents': ['individuals_merge_ID0000119', 'sifting_ID0000120'], 'files': [{'link': 'input', 'name': 'chr10n.tar.gz', 'size': 24615}, {'link': 'input', 'name': 'sifted.SIFT.chr10.txt', 'size': 797176}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10-AFR-freq.tar.gz', 'size': 273289}], 'avgCPU': 79.9798, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000296', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '10', '-pop', 'AFR']}}, {'name': 'mutation_overlap_ID0000297', 'type': 'compute', 'runtime': 9.962, 'parents': ['individuals_merge_ID0000119', 'sifting_ID0000120'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr10n.tar.gz', 'size': 24615}, {'link': 'input', 'name': 'sifted.SIFT.chr10.txt', 'size': 797176}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'output', 'name': 'chr10-GBR.tar.gz', 'size': 139834}], 'avgCPU': 26.7918, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000297', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '10', '-pop', 'GBR']}}, {'name': 'frequency_ID0000298', 'type': 'compute', 'runtime': 113.556, 'parents': ['individuals_merge_ID0000119', 'sifting_ID0000120'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr10n.tar.gz', 'size': 24615}, {'link': 'input', 'name': 'sifted.SIFT.chr10.txt', 'size': 797176}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'output', 'name': 'chr10-GBR-freq.tar.gz', 'size': 219856}], 'avgCPU': 79.4463, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000298', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '10', '-pop', 'GBR']}}, {'name': 'mutation_overlap_ID0000299', 'type': 'compute', 'runtime': 33.391, 'parents': ['individuals_merge_ID0000119', 'sifting_ID0000120'], 'files': [{'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'chr10n.tar.gz', 'size': 24615}, {'link': 'input', 'name': 'sifted.SIFT.chr10.txt', 'size': 797176}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10-ALL.tar.gz', 'size': 170175}], 'avgCPU': 58.8272, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000299', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '10', '-pop', 'ALL']}}, {'name': 'frequency_ID0000300', 'type': 'compute', 'runtime': 120.986, 'parents': ['individuals_merge_ID0000119', 'sifting_ID0000120'], 'files': [{'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'chr10n.tar.gz', 'size': 24615}, {'link': 'input', 'name': 'sifted.SIFT.chr10.txt', 'size': 797176}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10-ALL-freq.tar.gz', 'size': 290040}], 'avgCPU': 74.7615, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000300', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '10', '-pop', 'ALL']}}, {'name': 'mutation_overlap_ID0000301', 'type': 'compute', 'runtime': 11.961, 'parents': ['individuals_merge_ID0000119', 'sifting_ID0000120'], 'files': [{'link': 'input', 'name': 'chr10n.tar.gz', 'size': 24615}, {'link': 'input', 'name': 'sifted.SIFT.chr10.txt', 'size': 797176}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10-SAS.tar.gz', 'size': 146541}], 'avgCPU': 36.0756, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000301', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '10', '-pop', 'SAS']}}, {'name': 'frequency_ID0000302', 'type': 'compute', 'runtime': 110.23, 'parents': ['individuals_merge_ID0000119', 'sifting_ID0000120'], 'files': [{'link': 'input', 'name': 'chr10n.tar.gz', 'size': 24615}, {'link': 'input', 'name': 'sifted.SIFT.chr10.txt', 'size': 797176}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10-SAS-freq.tar.gz', 'size': 265442}], 'avgCPU': 80.9045, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000302', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '10', '-pop', 'SAS']}}, {'name': 'mutation_overlap_ID0000303', 'type': 'compute', 'runtime': 13.614, 'parents': ['individuals_merge_ID0000119', 'sifting_ID0000120'], 'files': [{'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'chr10n.tar.gz', 'size': 24615}, {'link': 'input', 'name': 'sifted.SIFT.chr10.txt', 'size': 797176}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10-EAS.tar.gz', 'size': 145475}], 'avgCPU': 35.0081, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000303', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '10', '-pop', 'EAS']}}, {'name': 'frequency_ID0000304', 'type': 'compute', 'runtime': 113.531, 'parents': ['individuals_merge_ID0000119', 'sifting_ID0000120'], 'files': [{'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'chr10n.tar.gz', 'size': 24615}, {'link': 'input', 'name': 'sifted.SIFT.chr10.txt', 'size': 797176}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10-EAS-freq.tar.gz', 'size': 266803}], 'avgCPU': 79.1572, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000304', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '10', '-pop', 'EAS']}}, {'name': 'mutation_overlap_ID0000305', 'type': 'compute', 'runtime': 13.899, 'parents': ['individuals_merge_ID0000119', 'sifting_ID0000120'], 'files': [{'link': 'input', 'name': 'chr10n.tar.gz', 'size': 24615}, {'link': 'input', 'name': 'sifted.SIFT.chr10.txt', 'size': 797176}, {'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10-AMR.tar.gz', 'size': 144877}], 'avgCPU': 26.1602, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000305', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '10', '-pop', 'AMR']}}, {'name': 'frequency_ID0000306', 'type': 'compute', 'runtime': 109.628, 'parents': ['individuals_merge_ID0000119', 'sifting_ID0000120'], 'files': [{'link': 'input', 'name': 'chr10n.tar.gz', 'size': 24615}, {'link': 'input', 'name': 'sifted.SIFT.chr10.txt', 'size': 797176}, {'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10-AMR-freq.tar.gz', 'size': 259224}], 'avgCPU': 81.4327, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000306', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '10', '-pop', 'AMR']}}, {'name': 'mutation_overlap_ID0000307', 'type': 'compute', 'runtime': 13.848, 'parents': ['individuals_merge_ID0000119', 'sifting_ID0000120'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'chr10n.tar.gz', 'size': 24615}, {'link': 'input', 'name': 'sifted.SIFT.chr10.txt', 'size': 797176}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10-EUR.tar.gz', 'size': 144547}], 'avgCPU': 32.7412, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000307', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '10', '-pop', 'EUR']}}, {'name': 'frequency_ID0000308', 'type': 'compute', 'runtime': 119.695, 'parents': ['individuals_merge_ID0000119', 'sifting_ID0000120'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'chr10n.tar.gz', 'size': 24615}, {'link': 'input', 'name': 'sifted.SIFT.chr10.txt', 'size': 797176}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr10-EUR-freq.tar.gz', 'size': 267857}], 'avgCPU': 75.9121, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000308', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '10', '-pop', 'EUR']}}, {'name': 'mutation_overlap_ID0000309', 'type': 'compute', 'runtime': 7.494, 'parents': ['individuals_merge_ID0000131', 'sifting_ID0000132'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr19.txt', 'size': 1481880}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'chr19n.tar.gz', 'size': 25086}, {'link': 'output', 'name': 'chr19-AFR.tar.gz', 'size': 150825}], 'avgCPU': 56.2183, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000309', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '19', '-pop', 'AFR']}}, {'name': 'frequency_ID0000310', 'type': 'compute', 'runtime': 156.891, 'parents': ['individuals_merge_ID0000131', 'sifting_ID0000132'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr19.txt', 'size': 1481880}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'chr19n.tar.gz', 'size': 25086}, {'link': 'output', 'name': 'chr19-AFR-freq.tar.gz', 'size': 280598}], 'avgCPU': 57.3302, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000310', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '19', '-pop', 'AFR']}}, {'name': 'mutation_overlap_ID0000311', 'type': 'compute', 'runtime': 9.438, 'parents': ['individuals_merge_ID0000131', 'sifting_ID0000132'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'sifted.SIFT.chr19.txt', 'size': 1481880}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'input', 'name': 'chr19n.tar.gz', 'size': 25086}, {'link': 'output', 'name': 'chr19-GBR.tar.gz', 'size': 142897}], 'avgCPU': 23.0345, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000311', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '19', '-pop', 'GBR']}}, {'name': 'frequency_ID0000312', 'type': 'compute', 'runtime': 162.36, 'parents': ['individuals_merge_ID0000131', 'sifting_ID0000132'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'sifted.SIFT.chr19.txt', 'size': 1481880}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'input', 'name': 'chr19n.tar.gz', 'size': 25086}, {'link': 'output', 'name': 'chr19-GBR-freq.tar.gz', 'size': 228897}], 'avgCPU': 54.5485, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000312', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '19', '-pop', 'GBR']}}, {'name': 'mutation_overlap_ID0000313', 'type': 'compute', 'runtime': 51.802, 'parents': ['individuals_merge_ID0000131', 'sifting_ID0000132'], 'files': [{'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'sifted.SIFT.chr19.txt', 'size': 1481880}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr19n.tar.gz', 'size': 25086}, {'link': 'output', 'name': 'chr19-ALL.tar.gz', 'size': 172593}], 'avgCPU': 37.79, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000313', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '19', '-pop', 'ALL']}}, {'name': 'frequency_ID0000314', 'type': 'compute', 'runtime': 141.15, 'parents': ['individuals_merge_ID0000131', 'sifting_ID0000132'], 'files': [{'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'sifted.SIFT.chr19.txt', 'size': 1481880}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr19n.tar.gz', 'size': 25086}, {'link': 'output', 'name': 'chr19-ALL-freq.tar.gz', 'size': 294765}], 'avgCPU': 64.5023, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000314', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '19', '-pop', 'ALL']}}, {'name': 'mutation_overlap_ID0000315', 'type': 'compute', 'runtime': 5.151, 'parents': ['individuals_merge_ID0000131', 'sifting_ID0000132'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'sifted.SIFT.chr19.txt', 'size': 1481880}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'chr19n.tar.gz', 'size': 25086}, {'link': 'output', 'name': 'chr19-SAS.tar.gz', 'size': 149799}], 'avgCPU': 65.3465, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000315', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '19', '-pop', 'SAS']}}, {'name': 'frequency_ID0000316', 'type': 'compute', 'runtime': 130.759, 'parents': ['individuals_merge_ID0000131', 'sifting_ID0000132'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'sifted.SIFT.chr19.txt', 'size': 1481880}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'chr19n.tar.gz', 'size': 25086}, {'link': 'output', 'name': 'chr19-SAS-freq.tar.gz', 'size': 271632}], 'avgCPU': 68.7517, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000316', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '19', '-pop', 'SAS']}}, {'name': 'mutation_overlap_ID0000317', 'type': 'compute', 'runtime': 4.836, 'parents': ['individuals_merge_ID0000131', 'sifting_ID0000132'], 'files': [{'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'sifted.SIFT.chr19.txt', 'size': 1481880}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr19n.tar.gz', 'size': 25086}, {'link': 'output', 'name': 'chr19-EAS.tar.gz', 'size': 148907}], 'avgCPU': 72.4566, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000317', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '19', '-pop', 'EAS']}}, {'name': 'frequency_ID0000318', 'type': 'compute', 'runtime': 160.683, 'parents': ['individuals_merge_ID0000131', 'sifting_ID0000132'], 'files': [{'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'sifted.SIFT.chr19.txt', 'size': 1481880}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr19n.tar.gz', 'size': 25086}, {'link': 'output', 'name': 'chr19-EAS-freq.tar.gz', 'size': 273299}], 'avgCPU': 55.6537, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000318', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '19', '-pop', 'EAS']}}, {'name': 'mutation_overlap_ID0000319', 'type': 'compute', 'runtime': 4.261, 'parents': ['individuals_merge_ID0000131', 'sifting_ID0000132'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr19.txt', 'size': 1481880}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'chr19n.tar.gz', 'size': 25086}, {'link': 'output', 'name': 'chr19-AMR.tar.gz', 'size': 148195}], 'avgCPU': 66.4867, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000319', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '19', '-pop', 'AMR']}}, {'name': 'frequency_ID0000320', 'type': 'compute', 'runtime': 163.906, 'parents': ['individuals_merge_ID0000131', 'sifting_ID0000132'], 'files': [{'link': 'input', 'name': 'sifted.SIFT.chr19.txt', 'size': 1481880}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'chr19n.tar.gz', 'size': 25086}, {'link': 'output', 'name': 'chr19-AMR-freq.tar.gz', 'size': 266968}], 'avgCPU': 54.7906, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000320', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '19', '-pop', 'AMR']}}, {'name': 'mutation_overlap_ID0000321', 'type': 'compute', 'runtime': 5.025, 'parents': ['individuals_merge_ID0000131', 'sifting_ID0000132'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'sifted.SIFT.chr19.txt', 'size': 1481880}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr19n.tar.gz', 'size': 25086}, {'link': 'output', 'name': 'chr19-EUR.tar.gz', 'size': 147587}], 'avgCPU': 66.806, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000321', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '19', '-pop', 'EUR']}}, {'name': 'frequency_ID0000322', 'type': 'compute', 'runtime': 167.029, 'parents': ['individuals_merge_ID0000131', 'sifting_ID0000132'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'sifted.SIFT.chr19.txt', 'size': 1481880}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr19n.tar.gz', 'size': 25086}, {'link': 'output', 'name': 'chr19-EUR-freq.tar.gz', 'size': 274544}], 'avgCPU': 54.3121, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000322', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '19', '-pop', 'EUR']}}, {'name': 'mutation_overlap_ID0000323', 'type': 'compute', 'runtime': 4.227, 'parents': ['individuals_merge_ID0000143', 'sifting_ID0000144'], 'files': [{'link': 'input', 'name': 'chr20n.tar.gz', 'size': 25254}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'sifted.SIFT.chr20.txt', 'size': 523567}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20-AFR.tar.gz', 'size': 147566}], 'avgCPU': 90.8209, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000323', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '20', '-pop', 'AFR']}}, {'name': 'frequency_ID0000324', 'type': 'compute', 'runtime': 131.657, 'parents': ['individuals_merge_ID0000143', 'sifting_ID0000144'], 'files': [{'link': 'input', 'name': 'chr20n.tar.gz', 'size': 25254}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'sifted.SIFT.chr20.txt', 'size': 523567}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20-AFR-freq.tar.gz', 'size': 271215}], 'avgCPU': 69.0955, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000324', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '20', '-pop', 'AFR']}}, {'name': 'mutation_overlap_ID0000325', 'type': 'compute', 'runtime': 3.373, 'parents': ['individuals_merge_ID0000143', 'sifting_ID0000144'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr20n.tar.gz', 'size': 25254}, {'link': 'input', 'name': 'sifted.SIFT.chr20.txt', 'size': 523567}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'output', 'name': 'chr20-GBR.tar.gz', 'size': 139175}], 'avgCPU': 55.1141, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000325', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '20', '-pop', 'GBR']}}, {'name': 'frequency_ID0000326', 'type': 'compute', 'runtime': 129.156, 'parents': ['individuals_merge_ID0000143', 'sifting_ID0000144'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr20n.tar.gz', 'size': 25254}, {'link': 'input', 'name': 'sifted.SIFT.chr20.txt', 'size': 523567}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'output', 'name': 'chr20-GBR-freq.tar.gz', 'size': 219025}], 'avgCPU': 69.4075, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000326', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '20', '-pop', 'GBR']}}, {'name': 'mutation_overlap_ID0000327', 'type': 'compute', 'runtime': 25.858, 'parents': ['individuals_merge_ID0000143', 'sifting_ID0000144'], 'files': [{'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'chr20n.tar.gz', 'size': 25254}, {'link': 'input', 'name': 'sifted.SIFT.chr20.txt', 'size': 523567}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20-ALL.tar.gz', 'size': 169035}], 'avgCPU': 75.3577, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000327', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '20', '-pop', 'ALL']}}, {'name': 'frequency_ID0000328', 'type': 'compute', 'runtime': 140.954, 'parents': ['individuals_merge_ID0000143', 'sifting_ID0000144'], 'files': [{'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'chr20n.tar.gz', 'size': 25254}, {'link': 'input', 'name': 'sifted.SIFT.chr20.txt', 'size': 523567}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20-ALL-freq.tar.gz', 'size': 290297}], 'avgCPU': 64.3657, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000328', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '20', '-pop', 'ALL']}}, {'name': 'mutation_overlap_ID0000329', 'type': 'compute', 'runtime': 4.334, 'parents': ['individuals_merge_ID0000143', 'sifting_ID0000144'], 'files': [{'link': 'input', 'name': 'chr20n.tar.gz', 'size': 25254}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'sifted.SIFT.chr20.txt', 'size': 523567}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20-SAS.tar.gz', 'size': 145825}], 'avgCPU': 73.9732, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000329', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '20', '-pop', 'SAS']}}, {'name': 'frequency_ID0000330', 'type': 'compute', 'runtime': 127.784, 'parents': ['individuals_merge_ID0000143', 'sifting_ID0000144'], 'files': [{'link': 'input', 'name': 'chr20n.tar.gz', 'size': 25254}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'sifted.SIFT.chr20.txt', 'size': 523567}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20-SAS-freq.tar.gz', 'size': 263822}], 'avgCPU': 70.724, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000330', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '20', '-pop', 'SAS']}}, {'name': 'mutation_overlap_ID0000331', 'type': 'compute', 'runtime': 4.102, 'parents': ['individuals_merge_ID0000143', 'sifting_ID0000144'], 'files': [{'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'chr20n.tar.gz', 'size': 25254}, {'link': 'input', 'name': 'sifted.SIFT.chr20.txt', 'size': 523567}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20-EAS.tar.gz', 'size': 145235}], 'avgCPU': 76.4505, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000331', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '20', '-pop', 'EAS']}}, {'name': 'frequency_ID0000332', 'type': 'compute', 'runtime': 128.678, 'parents': ['individuals_merge_ID0000143', 'sifting_ID0000144'], 'files': [{'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'chr20n.tar.gz', 'size': 25254}, {'link': 'input', 'name': 'sifted.SIFT.chr20.txt', 'size': 523567}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20-EAS-freq.tar.gz', 'size': 265438}], 'avgCPU': 70.5971, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000332', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '20', '-pop', 'EAS']}}, {'name': 'mutation_overlap_ID0000333', 'type': 'compute', 'runtime': 2.941, 'parents': ['individuals_merge_ID0000143', 'sifting_ID0000144'], 'files': [{'link': 'input', 'name': 'chr20n.tar.gz', 'size': 25254}, {'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'sifted.SIFT.chr20.txt', 'size': 523567}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20-AMR.tar.gz', 'size': 145081}], 'avgCPU': 90.6834, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000333', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '20', '-pop', 'AMR']}}, {'name': 'frequency_ID0000334', 'type': 'compute', 'runtime': 128.605, 'parents': ['individuals_merge_ID0000143', 'sifting_ID0000144'], 'files': [{'link': 'input', 'name': 'chr20n.tar.gz', 'size': 25254}, {'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'sifted.SIFT.chr20.txt', 'size': 523567}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20-AMR-freq.tar.gz', 'size': 260451}], 'avgCPU': 67.9398, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000334', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '20', '-pop', 'AMR']}}, {'name': 'mutation_overlap_ID0000335', 'type': 'compute', 'runtime': 3.256, 'parents': ['individuals_merge_ID0000143', 'sifting_ID0000144'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'chr20n.tar.gz', 'size': 25254}, {'link': 'input', 'name': 'sifted.SIFT.chr20.txt', 'size': 523567}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20-EUR.tar.gz', 'size': 144139}], 'avgCPU': 100.0, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000335', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '20', '-pop', 'EUR']}}, {'name': 'frequency_ID0000336', 'type': 'compute', 'runtime': 108.185, 'parents': ['individuals_merge_ID0000143', 'sifting_ID0000144'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'chr20n.tar.gz', 'size': 25254}, {'link': 'input', 'name': 'sifted.SIFT.chr20.txt', 'size': 523567}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr20-EUR-freq.tar.gz', 'size': 267496}], 'avgCPU': 86.6959, 'machine': 'pegasus-4', 'priority': 40, 'id': 'ID0000336', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '20', '-pop', 'EUR']}}, {'name': 'mutation_overlap_ID0000337', 'type': 'compute', 'runtime': 5.594, 'parents': ['individuals_merge_ID0000155', 'sifting_ID0000156'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'chr21n.tar.gz', 'size': 24630}, {'link': 'input', 'name': 'sifted.SIFT.chr21.txt', 'size': 231958}, {'link': 'output', 'name': 'chr21-AFR.tar.gz', 'size': 144562}], 'avgCPU': 67.3221, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000337', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '21', '-pop', 'AFR']}}, {'name': 'frequency_ID0000338', 'type': 'compute', 'runtime': 115.146, 'parents': ['individuals_merge_ID0000155', 'sifting_ID0000156'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'input', 'name': 'chr21n.tar.gz', 'size': 24630}, {'link': 'input', 'name': 'sifted.SIFT.chr21.txt', 'size': 231958}, {'link': 'output', 'name': 'chr21-AFR-freq.tar.gz', 'size': 272932}], 'avgCPU': 76.7573, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000338', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '21', '-pop', 'AFR']}}, {'name': 'mutation_overlap_ID0000339', 'type': 'compute', 'runtime': 2.509, 'parents': ['individuals_merge_ID0000155', 'sifting_ID0000156'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'input', 'name': 'chr21n.tar.gz', 'size': 24630}, {'link': 'input', 'name': 'sifted.SIFT.chr21.txt', 'size': 231958}, {'link': 'output', 'name': 'chr21-GBR.tar.gz', 'size': 136896}], 'avgCPU': 69.2706, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000339', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '21', '-pop', 'GBR']}}, {'name': 'frequency_ID0000340', 'type': 'compute', 'runtime': 121.762, 'parents': ['individuals_merge_ID0000155', 'sifting_ID0000156'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'input', 'name': 'chr21n.tar.gz', 'size': 24630}, {'link': 'input', 'name': 'sifted.SIFT.chr21.txt', 'size': 231958}, {'link': 'output', 'name': 'chr21-GBR-freq.tar.gz', 'size': 220822}], 'avgCPU': 73.6256, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000340', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '21', '-pop', 'GBR']}}, {'name': 'mutation_overlap_ID0000341', 'type': 'compute', 'runtime': 39.942, 'parents': ['individuals_merge_ID0000155', 'sifting_ID0000156'], 'files': [{'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr21n.tar.gz', 'size': 24630}, {'link': 'input', 'name': 'sifted.SIFT.chr21.txt', 'size': 231958}, {'link': 'output', 'name': 'chr21-ALL.tar.gz', 'size': 166602}], 'avgCPU': 45.2506, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000341', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '21', '-pop', 'ALL']}}, {'name': 'frequency_ID0000342', 'type': 'compute', 'runtime': 136.219, 'parents': ['individuals_merge_ID0000155', 'sifting_ID0000156'], 'files': [{'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr21n.tar.gz', 'size': 24630}, {'link': 'input', 'name': 'sifted.SIFT.chr21.txt', 'size': 231958}, {'link': 'output', 'name': 'chr21-ALL-freq.tar.gz', 'size': 290865}], 'avgCPU': 68.1212, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000342', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '21', '-pop', 'ALL']}}, {'name': 'mutation_overlap_ID0000343', 'type': 'compute', 'runtime': 5.356, 'parents': ['individuals_merge_ID0000155', 'sifting_ID0000156'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'chr21n.tar.gz', 'size': 24630}, {'link': 'input', 'name': 'sifted.SIFT.chr21.txt', 'size': 231958}, {'link': 'output', 'name': 'chr21-SAS.tar.gz', 'size': 143370}], 'avgCPU': 58.5885, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000343', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '21', '-pop', 'SAS']}}, {'name': 'frequency_ID0000344', 'type': 'compute', 'runtime': 110.995, 'parents': ['individuals_merge_ID0000155', 'sifting_ID0000156'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'chr21n.tar.gz', 'size': 24630}, {'link': 'input', 'name': 'sifted.SIFT.chr21.txt', 'size': 231958}, {'link': 'output', 'name': 'chr21-SAS-freq.tar.gz', 'size': 264297}], 'avgCPU': 79.09, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000344', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '21', '-pop', 'SAS']}}, {'name': 'mutation_overlap_ID0000345', 'type': 'compute', 'runtime': 5.768, 'parents': ['individuals_merge_ID0000155', 'sifting_ID0000156'], 'files': [{'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr21n.tar.gz', 'size': 24630}, {'link': 'input', 'name': 'sifted.SIFT.chr21.txt', 'size': 231958}, {'link': 'output', 'name': 'chr21-EAS.tar.gz', 'size': 142606}], 'avgCPU': 75.6241, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000345', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '21', '-pop', 'EAS']}}, {'name': 'frequency_ID0000346', 'type': 'compute', 'runtime': 130.889, 'parents': ['individuals_merge_ID0000155', 'sifting_ID0000156'], 'files': [{'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr21n.tar.gz', 'size': 24630}, {'link': 'input', 'name': 'sifted.SIFT.chr21.txt', 'size': 231958}, {'link': 'output', 'name': 'chr21-EAS-freq.tar.gz', 'size': 267814}], 'avgCPU': 68.9538, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000346', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '21', '-pop', 'EAS']}}, {'name': 'mutation_overlap_ID0000347', 'type': 'compute', 'runtime': 4.537, 'parents': ['individuals_merge_ID0000155', 'sifting_ID0000156'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'chr21n.tar.gz', 'size': 24630}, {'link': 'input', 'name': 'sifted.SIFT.chr21.txt', 'size': 231958}, {'link': 'output', 'name': 'chr21-AMR.tar.gz', 'size': 142088}], 'avgCPU': 58.2103, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000347', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '21', '-pop', 'AMR']}}, {'name': 'frequency_ID0000348', 'type': 'compute', 'runtime': 127.78, 'parents': ['individuals_merge_ID0000155', 'sifting_ID0000156'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'chr21n.tar.gz', 'size': 24630}, {'link': 'input', 'name': 'sifted.SIFT.chr21.txt', 'size': 231958}, {'link': 'output', 'name': 'chr21-AMR-freq.tar.gz', 'size': 260623}], 'avgCPU': 69.9875, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000348', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '21', '-pop', 'AMR']}}, {'name': 'mutation_overlap_ID0000349', 'type': 'compute', 'runtime': 4.152, 'parents': ['individuals_merge_ID0000155', 'sifting_ID0000156'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr21n.tar.gz', 'size': 24630}, {'link': 'input', 'name': 'sifted.SIFT.chr21.txt', 'size': 231958}, {'link': 'output', 'name': 'chr21-EUR.tar.gz', 'size': 141843}], 'avgCPU': 75.3372, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000349', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '21', '-pop', 'EUR']}}, {'name': 'frequency_ID0000350', 'type': 'compute', 'runtime': 128.916, 'parents': ['individuals_merge_ID0000155', 'sifting_ID0000156'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'chr21n.tar.gz', 'size': 24630}, {'link': 'input', 'name': 'sifted.SIFT.chr21.txt', 'size': 231958}, {'link': 'output', 'name': 'chr21-EUR-freq.tar.gz', 'size': 268987}], 'avgCPU': 70.2403, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000350', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '21', '-pop', 'EUR']}}, {'name': 'mutation_overlap_ID0000351', 'type': 'compute', 'runtime': 10.193, 'parents': ['individuals_merge_ID0000167', 'sifting_ID0000168'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'sifted.SIFT.chr22.txt', 'size': 480587}, {'link': 'input', 'name': 'chr22n.tar.gz', 'size': 25242}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'output', 'name': 'chr22-AFR.tar.gz', 'size': 146451}], 'avgCPU': 37.771, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000351', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '22', '-pop', 'AFR']}}, {'name': 'frequency_ID0000352', 'type': 'compute', 'runtime': 174.856, 'parents': ['individuals_merge_ID0000167', 'sifting_ID0000168'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'sifted.SIFT.chr22.txt', 'size': 480587}, {'link': 'input', 'name': 'chr22n.tar.gz', 'size': 25242}, {'link': 'input', 'name': 'AFR', 'size': 8088}, {'link': 'output', 'name': 'chr22-AFR-freq.tar.gz', 'size': 277844}], 'avgCPU': 51.8358, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000352', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '22', '-pop', 'AFR']}}, {'name': 'mutation_overlap_ID0000353', 'type': 'compute', 'runtime': 3.975, 'parents': ['individuals_merge_ID0000167', 'sifting_ID0000168'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'sifted.SIFT.chr22.txt', 'size': 480587}, {'link': 'input', 'name': 'chr22n.tar.gz', 'size': 25242}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'output', 'name': 'chr22-GBR.tar.gz', 'size': 138728}], 'avgCPU': 45.3333, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000353', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '22', '-pop', 'GBR']}}, {'name': 'frequency_ID0000354', 'type': 'compute', 'runtime': 134.996, 'parents': ['individuals_merge_ID0000167', 'sifting_ID0000168'], 'files': [{'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'input', 'name': 'sifted.SIFT.chr22.txt', 'size': 480587}, {'link': 'input', 'name': 'chr22n.tar.gz', 'size': 25242}, {'link': 'input', 'name': 'GBR', 'size': 856}, {'link': 'output', 'name': 'chr22-GBR-freq.tar.gz', 'size': 223185}], 'avgCPU': 67.5339, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000354', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '22', '-pop', 'GBR']}}, {'name': 'mutation_overlap_ID0000355', 'type': 'compute', 'runtime': 54.667, 'parents': ['individuals_merge_ID0000167', 'sifting_ID0000168'], 'files': [{'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'sifted.SIFT.chr22.txt', 'size': 480587}, {'link': 'input', 'name': 'chr22n.tar.gz', 'size': 25242}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr22-ALL.tar.gz', 'size': 169324}], 'avgCPU': 35.5351, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000355', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '22', '-pop', 'ALL']}}, {'name': 'frequency_ID0000356', 'type': 'compute', 'runtime': 181.452, 'parents': ['individuals_merge_ID0000167', 'sifting_ID0000168'], 'files': [{'link': 'input', 'name': 'ALL', 'size': 28000}, {'link': 'input', 'name': 'sifted.SIFT.chr22.txt', 'size': 480587}, {'link': 'input', 'name': 'chr22n.tar.gz', 'size': 25242}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr22-ALL-freq.tar.gz', 'size': 293793}], 'avgCPU': 51.2477, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000356', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '22', '-pop', 'ALL']}}, {'name': 'mutation_overlap_ID0000357', 'type': 'compute', 'runtime': 5.109, 'parents': ['individuals_merge_ID0000167', 'sifting_ID0000168'], 'files': [{'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'sifted.SIFT.chr22.txt', 'size': 480587}, {'link': 'input', 'name': 'chr22n.tar.gz', 'size': 25242}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr22-SAS.tar.gz', 'size': 145893}], 'avgCPU': 66.1186, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000357', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '22', '-pop', 'SAS']}}, {'name': 'frequency_ID0000358', 'type': 'compute', 'runtime': 174.26, 'parents': ['individuals_merge_ID0000167', 'sifting_ID0000168'], 'files': [{'link': 'input', 'name': 'SAS', 'size': 5248}, {'link': 'input', 'name': 'sifted.SIFT.chr22.txt', 'size': 480587}, {'link': 'input', 'name': 'chr22n.tar.gz', 'size': 25242}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr22-SAS-freq.tar.gz', 'size': 268899}], 'avgCPU': 52.5164, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000358', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '22', '-pop', 'SAS']}}, {'name': 'mutation_overlap_ID0000359', 'type': 'compute', 'runtime': 8.058, 'parents': ['individuals_merge_ID0000167', 'sifting_ID0000168'], 'files': [{'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'sifted.SIFT.chr22.txt', 'size': 480587}, {'link': 'input', 'name': 'chr22n.tar.gz', 'size': 25242}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr22-EAS.tar.gz', 'size': 145145}], 'avgCPU': 40.5436, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000359', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '22', '-pop', 'EAS']}}, {'name': 'frequency_ID0000360', 'type': 'compute', 'runtime': 113.968, 'parents': ['individuals_merge_ID0000167', 'sifting_ID0000168'], 'files': [{'link': 'input', 'name': 'EAS', 'size': 4896}, {'link': 'input', 'name': 'sifted.SIFT.chr22.txt', 'size': 480587}, {'link': 'input', 'name': 'chr22n.tar.gz', 'size': 25242}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr22-EAS-freq.tar.gz', 'size': 266060}], 'avgCPU': 84.658, 'machine': 'pegasus-4', 'priority': 40, 'id': 'ID0000360', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '22', '-pop', 'EAS']}}, {'name': 'mutation_overlap_ID0000361', 'type': 'compute', 'runtime': 2.742, 'parents': ['individuals_merge_ID0000167', 'sifting_ID0000168'], 'files': [{'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'sifted.SIFT.chr22.txt', 'size': 480587}, {'link': 'input', 'name': 'chr22n.tar.gz', 'size': 25242}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr22-AMR.tar.gz', 'size': 144354}], 'avgCPU': 96.1342, 'machine': 'pegasus-2', 'priority': 40, 'id': 'ID0000361', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '22', '-pop', 'AMR']}}, {'name': 'frequency_ID0000362', 'type': 'compute', 'runtime': 176.39, 'parents': ['individuals_merge_ID0000167', 'sifting_ID0000168'], 'files': [{'link': 'input', 'name': 'AMR', 'size': 4248}, {'link': 'input', 'name': 'sifted.SIFT.chr22.txt', 'size': 480587}, {'link': 'input', 'name': 'chr22n.tar.gz', 'size': 25242}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr22-AMR-freq.tar.gz', 'size': 263766}], 'avgCPU': 51.7184, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000362', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '22', '-pop', 'AMR']}}, {'name': 'mutation_overlap_ID0000363', 'type': 'compute', 'runtime': 3.605, 'parents': ['individuals_merge_ID0000167', 'sifting_ID0000168'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'sifted.SIFT.chr22.txt', 'size': 480587}, {'link': 'input', 'name': 'chr22n.tar.gz', 'size': 25242}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr22-EUR.tar.gz', 'size': 143820}], 'avgCPU': 92.2885, 'machine': 'pegasus-4', 'priority': 40, 'id': 'ID0000363', 'category': 'mutation_overlap', 'command': {'program': 'mutation_overlap', 'arguments': ['-c', '22', '-pop', 'EUR']}}, {'name': 'frequency_ID0000364', 'type': 'compute', 'runtime': 173.965, 'parents': ['individuals_merge_ID0000167', 'sifting_ID0000168'], 'files': [{'link': 'input', 'name': 'EUR', 'size': 5312}, {'link': 'input', 'name': 'sifted.SIFT.chr22.txt', 'size': 480587}, {'link': 'input', 'name': 'chr22n.tar.gz', 'size': 25242}, {'link': 'input', 'name': 'columns.txt', 'size': 20078}, {'link': 'output', 'name': 'chr22-EUR-freq.tar.gz', 'size': 272227}], 'avgCPU': 52.0944, 'machine': 'pegasus-5', 'priority': 40, 'id': 'ID0000364', 'category': 'frequency', 'command': {'program': 'frequency', 'arguments': ['-c', '22', '-pop', 'EUR']}}], 'machines': [{'nodeName': 'pegasus-2', 'system': 'linux', 'architecture': 'x86_64', 'memory': 131795984, 'release': '4.15.0-88-generic', 'cpu': {'count': 48, 'vendor': 'GenuineIntel', 'speed': 2253}}, {'nodeName': 'pegasus-5', 'system': 'linux', 'architecture': 'x86_64', 'memory': 131795984, 'release': '4.15.0-88-generic', 'cpu': {'count': 48, 'vendor': 'GenuineIntel', 'speed': 1834}}, {'nodeName': 'pegasus-4', 'system': 'linux', 'architecture': 'x86_64', 'memory': 131795984, 'release': '4.15.0-88-generic', 'cpu': {'count': 48, 'vendor': 'GenuineIntel', 'speed': 1494}}, {'nodeName': 'pegasus-3', 'system': 'linux', 'architecture': 'x86_64', 'memory': 131795984, 'release': '4.15.0-88-generic', 'cpu': {'count': 48, 'vendor': 'GenuineIntel', 'speed': 1242}}], 'executedAt': '20200401T153414+0000'}}\n"
     ]
    }
   ],
   "source": [
    "url = 'https://raw.githubusercontent.com/wfcommons/pegasus-instances/master/srasearch/chameleon-cloud/srasearch-chameleon-10a-001.json'\n",
    "url = 'https://raw.githubusercontent.com/wfcommons/pegasus-instances/master/1000genome/chameleon-cloud/1000genome-chameleon-14ch-100k-001.json'\n",
    "resp = requests.get(url)\n",
    "data = json.loads(resp.text)\n",
    "print(data)\n",
    "path = 'pegasus-workflow.json'\n",
    "# workflow.write_json(path)\n",
    "with open(path, 'w') as f:\n",
    "    json.dump(data, f)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "3652576e",
   "metadata": {
    "id": "3652576e",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "DAG_real = create_graph(path)\n",
    "# annotate(DAG) # I thought that this line migth append some data to the DAG, but that's not the case https://github.com/wfcommons/wfcommons/blob/4abe2545998a7b29e65e94f95d7c32d7c9afdc78/wfcommons/wfchef/utils.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "800c0ab5",
   "metadata": {
    "id": "800c0ab5",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "nodes = DAG_real.nodes()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "6a612e2d",
   "metadata": {
    "id": "6a612e2d",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "edges = DAG_real.edges()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "0c394edb",
   "metadata": {
    "id": "0c394edb",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "in_degrees = DAG_real.in_degree(nodes)\n",
    "out_degrees = DAG_real.out_degree(nodes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "b5010194",
   "metadata": {
    "id": "b5010194",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "nodes_connected_to_source = [node for (node, in_degree) in in_degrees if in_degree == 0]\n",
    "nodes_connected_to_sink = [node for (node, out_degree) in out_degrees if out_degree == 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "2f390ada",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "2f390ada",
    "outputId": "9717930e-6f57-4362-ba21-14f44abea641",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "nodes_connected_to_source ['SRC']\n",
      "nodes_connected_to_sink ['DST']\n"
     ]
    }
   ],
   "source": [
    "print('nodes_connected_to_source', nodes_connected_to_source)\n",
    "print('nodes_connected_to_sink', nodes_connected_to_sink)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "a2260590",
   "metadata": {
    "id": "a2260590",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "paths = list(nx.all_simple_paths(DAG_real, source='SRC', target='DST'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "1e117edb",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "1e117edb",
    "outputId": "953d3629-690b-4bad-d7c4-eb9e87389b4f",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Amount of paths: 2156\n"
     ]
    }
   ],
   "source": [
    "paths_amount = len(paths)\n",
    "print(f'Amount of paths: {paths_amount}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "b64c2eb1",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 751
    },
    "id": "b64c2eb1",
    "outputId": "df599e34-af12-4785-aff6-f0cc22dd833b",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1008x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display_graph(DAG_real)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "R2URhNb4YVvl",
   "metadata": {
    "id": "R2URhNb4YVvl"
   },
   "source": [
    "So lets get some data :)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "FD7Z-KBfeEcD",
   "metadata": {
    "id": "FD7Z-KBfeEcD",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "class Machine(object):\n",
    "  def __init__(self, machine):\n",
    "    self.name = machine.get('nodeName')\n",
    "    self.system = machine.get('system')\n",
    "    self.architecture = machine.get('architecture')\n",
    "    self.release = machine.get('release')\n",
    "    self.cpu = machine.get('cpu')\n",
    "    self.memory = machine.get('memory')\n",
    "  def __repr__(self):\n",
    "    return str(vars(self))\n",
    "\n",
    "  def __str__(self):\n",
    "    return str(vars(self))\n",
    "\n",
    "\n",
    "class Job(object):\n",
    "  def __init__(self, id, name, children, parents, machine, inputs, outputs, runtime, used_memeory, normalized_runtime):\n",
    "    self.id = id\n",
    "    self.name = name\n",
    "    self.children = children\n",
    "    self.parents = parents\n",
    "    self.machine = machine\n",
    "    self.inputs = inputs\n",
    "    self.outputs = outputs\n",
    "    self.runtime = runtime\n",
    "    self.used_memeory = used_memeory\n",
    "    self.normalized_runtime = normalized_runtime\n",
    "\n",
    "\n",
    "  def find_and_set_parents(self, jobs):\n",
    "    parent_jobs = []\n",
    "    for j in jobs:\n",
    "      for p in self.parents:\n",
    "        if p == j.name:\n",
    "          parent_jobs.append(j)\n",
    "    self.parents = parent_jobs\n",
    "\n",
    "  def find_and_set_children(self, jobs):\n",
    "    children_jobs = []\n",
    "    for j in jobs:\n",
    "      for c in self.children:\n",
    "        if c == j.name:\n",
    "          children_jobs.append(j)\n",
    "    self.children = children_jobs\n",
    "\n",
    "\n",
    "  def __repr__(self):\n",
    "    return str(f\"['{self.name}']: on machine '{self.machine.name}' parent: '{[p.name for p in self.parents]}' children: '{[c.name for c in self.children]}'\" )\n",
    "\n",
    "  # def __str__(self):\n",
    "  #   return str(vars(self))\n",
    "\n",
    "class JobBuilder(object):\n",
    "  def __init__(self, job, *, machine_name = None):\n",
    "    self.id = job.get('id')\n",
    "    self.name = job.get('name')\n",
    "    self.category =  job.get('category') \n",
    "    self.children_names = job.get('children') or [] \n",
    "    self.parent_names = job.get('parents') or [] \n",
    "    self.commmand = job['command'].get('program') \n",
    "    self.arguments = job['command'].get('arguments')\n",
    "    files = job.get('files')\n",
    "    if files is None:\n",
    "      self.inputs = []\n",
    "      self.outputs = []\n",
    "    else: \n",
    "      self.inputs = [ (file.get('name'), file.get('size')) for file in files if file.get('link') == 'input']\n",
    "      self.outputs = [ (file.get('name'), file.get('size')) for file in files if file.get('link') == 'output']\n",
    "      \n",
    "    self.avg_cpu_usage = job.get('avgCPU')\n",
    "    self.used_memeory = job.get('memory')\n",
    "    self.priotrity = job.get( 'priority')\n",
    "    self.runtime = job.get('runtime')\n",
    "    self.type = job.get('type')\n",
    "    self.normalized_runtime = 1\n",
    "\n",
    "  def __repr__(self):\n",
    "    return str(vars(self))\n",
    "\n",
    "  def __str__(self):\n",
    "    return str(vars(self))\n",
    "\n",
    "  def set_machine(self, machine : Machine):\n",
    "    self.machine = machine\n",
    "\n",
    "  def build(self) -> Job:\n",
    "    return Job(id = self.id, name = self.name, children = self.children_names, parents = self.parent_names, machine = self.machine, inputs = self.inputs, outputs = self.outputs, runtime = self.runtime, used_memeory = self.used_memeory, normalized_runtime = self.normalized_runtime)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "JcyZpxrtj1s2",
   "metadata": {
    "id": "JcyZpxrtj1s2"
   },
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "dF0WHi4SjfE0",
   "metadata": {
    "id": "dF0WHi4SjfE0",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "json_data = data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "L1ciwEkGZw4F",
   "metadata": {
    "cellView": "code",
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "L1ciwEkGZw4F",
    "outputId": "5d976808-532f-4ab2-8993-f70b63ff6928",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'worker-4': {'name': 'worker-4', 'system': 'linux', 'architecture': 'x86_64', 'release': '4.15.0-121-generic', 'cpu': {'count': 48, 'speed': 1274, 'vendor': 'GenuineIntel'}, 'memory': 131795960}}\n"
     ]
    }
   ],
   "source": [
    "#@title Domyślny tekst tytułu\n",
    "machines =  [Machine(machine) for machine in json_data['workflow']['machines']]\n",
    "machines = { machine.name : machine for machine in machines}\n",
    "\n",
    "jobs_b = [ (JobBuilder(job), job['machine']) for job in json_data['workflow']['jobs']]\n",
    "\n",
    "pprint(machines)\n",
    "for job, machine_name in jobs_b:\n",
    "    job.set_machine(machines[machine_name])\n",
    "    job.normalized_runtime = job.runtime / job.machine.cpu['speed'] * job.machine.cpu['count']\n",
    "\n",
    "min_runtime = min(map(lambda x: x[0].normalized_runtime, jobs_b))\n",
    "\n",
    "for j,_ in jobs_b:\n",
    "  j.normalized_runtime /= min_runtime\n",
    "\n",
    "jobs = [job.build() for job, _ in jobs_b]\n",
    "\n",
    "\n",
    "\n",
    "for j in jobs:\n",
    "  j.find_and_set_parents(jobs)\n",
    "  j.find_and_set_children(jobs)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "H2gAe-iPDqGE",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "H2gAe-iPDqGE",
    "outputId": "832f60d1-c015-4264-fa30-32b7732dc7c9",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Jobs: 22\n",
      "Machines: 1\n"
     ]
    }
   ],
   "source": [
    "print(f'Jobs: {len(jobs)}')\n",
    "print(f'Machines: {len(machines)}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "gpErdYl5eJWw",
   "metadata": {
    "id": "gpErdYl5eJWw"
   },
   "source": [
    "# Cyfronet Machines\n",
    "\n",
    "Lets define some machines that are available for AGH."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "iJkglYRJZ0wC",
   "metadata": {
    "id": "iJkglYRJZ0wC",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "base_cpu_hour_price = 0.08\n",
    "base_gpu_hour_price = 5.0\n",
    "gpu_speed_vs_cpu = 100\n",
    "\n",
    "cpus = {'Zeus': 0.25, 'Prometeus': 1 , 'Ares': 1.6}\n",
    "cpus_base_memory = {'Zeus': 2, 'Prometeus': 4 , 'Ares': 8}\n",
    "cpus_more_memory_factor = {'Zeus': 0.2, 'Prometeus': 0.40 , 'Ares': 0.80}\n",
    "\n",
    "\n",
    "gpus = {'Prometeus': 1 , 'Ares': 1.6}\n",
    "gpus_base_memory = {'Prometeus': 4 , 'Ares': 8}\n",
    "gpus_more_memory_factor = {'Prometeus': 0.40 , 'Ares': 0.80}\n",
    "\n",
    "\n",
    "cyfronet_machines = {}\n",
    "for cpu in cpus.keys():\n",
    "  cyfronet_machines[f\"{cpu}Cpu\"] = {\n",
    "      'base_price' :  base_cpu_hour_price,\n",
    "      'base_memory' : cpus_base_memory[cpu],\n",
    "      'memory_cost_multiplayer' : cpus_more_memory_factor[cpu],\n",
    "      'speed': cpus[cpu]\n",
    "  }\n",
    "for gpu in gpus.keys():\n",
    "  cyfronet_machines[f\"{gpu}Gpu\"] = {\n",
    "      'base_price' : base_gpu_hour_price,\n",
    "      'base_memory' : gpus_base_memory[gpu],\n",
    "      'memory_cost_multiplayer' : gpus_more_memory_factor[gpu],\n",
    "      'speed' : gpus[gpu] * gpu_speed_vs_cpu\n",
    "  }\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "EeFL5UAHhj0K",
   "metadata": {
    "id": "EeFL5UAHhj0K",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "import math\n",
    "def calc_cost(machine , job):\n",
    "  if job.used_memeory is not None:\n",
    "    mib_free = 1024 * machine['base_memory']\n",
    "    cost_power = (job.used_memeory - mib_free) // 1024\n",
    "  else:\n",
    "    cost_power = 0\n",
    "  runtime = job.normalized_runtime\n",
    "  return runtime * machine['base_price'] * (1 + machine['memory_cost_multiplayer']* cost_power) / machine['speed']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "9_Sc0EeohkBI",
   "metadata": {
    "id": "9_Sc0EeohkBI",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "costs = {}\n",
    "runtimes = {}\n",
    "for machine in cyfronet_machines:\n",
    "  machine_cost = []\n",
    "  machine_runtime = []\n",
    "  for j in jobs:\n",
    "    machine_cost.append(calc_cost(cyfronet_machines[machine], j))\n",
    "    machine_runtime.append( j.normalized_runtime / cyfronet_machines[machine]['speed'])\n",
    "  costs[machine] = machine_cost\n",
    "  runtimes[f\"{machine}Runtime\"] = machine_runtime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "ZbE8iPJDjJyJ",
   "metadata": {
    "id": "ZbE8iPJDjJyJ",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "WV3Nd7_-oOG2",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 739
    },
    "id": "WV3Nd7_-oOG2",
    "outputId": "019ba39d-fcde-43b0-e064-c287ae2f183d",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ZeusCpu</th>\n",
       "      <th>PrometeusCpu</th>\n",
       "      <th>AresCpu</th>\n",
       "      <th>PrometeusGpu</th>\n",
       "      <th>AresGpu</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>bowtie2-build_ID0000001</th>\n",
       "      <td>335.827478</td>\n",
       "      <td>159.959930</td>\n",
       "      <td>188.350609</td>\n",
       "      <td>99.974957</td>\n",
       "      <td>117.719130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fasterq-dump_ID0000002</th>\n",
       "      <td>159221.188452</td>\n",
       "      <td>78487.560765</td>\n",
       "      <td>96471.693826</td>\n",
       "      <td>49054.725478</td>\n",
       "      <td>60294.808641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowtie2_ID0000003</th>\n",
       "      <td>873.724104</td>\n",
       "      <td>369.073113</td>\n",
       "      <td>362.482522</td>\n",
       "      <td>230.670696</td>\n",
       "      <td>226.551576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fasterq-dump_ID0000004</th>\n",
       "      <td>46585.664000</td>\n",
       "      <td>22726.249600</td>\n",
       "      <td>27581.546000</td>\n",
       "      <td>14203.906000</td>\n",
       "      <td>17238.466250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowtie2_ID0000005</th>\n",
       "      <td>782.037704</td>\n",
       "      <td>330.343513</td>\n",
       "      <td>324.444522</td>\n",
       "      <td>206.464696</td>\n",
       "      <td>202.777826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fasterq-dump_ID0000006</th>\n",
       "      <td>87037.907478</td>\n",
       "      <td>42741.829565</td>\n",
       "      <td>52293.980870</td>\n",
       "      <td>26713.643478</td>\n",
       "      <td>32683.738043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowtie2_ID0000007</th>\n",
       "      <td>860.093217</td>\n",
       "      <td>358.372174</td>\n",
       "      <td>343.440000</td>\n",
       "      <td>223.982609</td>\n",
       "      <td>214.650000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fasterq-dump_ID0000008</th>\n",
       "      <td>39946.646817</td>\n",
       "      <td>19447.709635</td>\n",
       "      <td>23543.116957</td>\n",
       "      <td>12154.818522</td>\n",
       "      <td>14714.448098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowtie2_ID0000009</th>\n",
       "      <td>673.529322</td>\n",
       "      <td>280.637217</td>\n",
       "      <td>268.944000</td>\n",
       "      <td>175.398261</td>\n",
       "      <td>168.090000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fasterq-dump_ID0000010</th>\n",
       "      <td>114676.087096</td>\n",
       "      <td>56526.656139</td>\n",
       "      <td>69475.046870</td>\n",
       "      <td>35329.160087</td>\n",
       "      <td>43421.904293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowtie2_ID0000011</th>\n",
       "      <td>651.335791</td>\n",
       "      <td>271.389913</td>\n",
       "      <td>260.082000</td>\n",
       "      <td>169.618696</td>\n",
       "      <td>162.551250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fasterq-dump_ID0000012</th>\n",
       "      <td>68406.293148</td>\n",
       "      <td>33522.110470</td>\n",
       "      <td>40909.460435</td>\n",
       "      <td>20951.319043</td>\n",
       "      <td>25568.412772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowtie2_ID0000013</th>\n",
       "      <td>714.670748</td>\n",
       "      <td>297.779478</td>\n",
       "      <td>285.372000</td>\n",
       "      <td>186.112174</td>\n",
       "      <td>178.357500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fasterq-dump_ID0000014</th>\n",
       "      <td>35153.921113</td>\n",
       "      <td>17079.499409</td>\n",
       "      <td>20623.910087</td>\n",
       "      <td>10674.687130</td>\n",
       "      <td>12889.943804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowtie2_ID0000015</th>\n",
       "      <td>479.377252</td>\n",
       "      <td>199.740522</td>\n",
       "      <td>191.418000</td>\n",
       "      <td>124.837826</td>\n",
       "      <td>119.636250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fasterq-dump_ID0000016</th>\n",
       "      <td>149033.959513</td>\n",
       "      <td>73465.799791</td>\n",
       "      <td>90299.278957</td>\n",
       "      <td>45916.124870</td>\n",
       "      <td>56437.049348</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowtie2_ID0000017</th>\n",
       "      <td>1016.634991</td>\n",
       "      <td>423.597913</td>\n",
       "      <td>405.948000</td>\n",
       "      <td>264.748696</td>\n",
       "      <td>253.717500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fasterq-dump_ID0000018</th>\n",
       "      <td>117514.342400</td>\n",
       "      <td>57872.865948</td>\n",
       "      <td>71051.470609</td>\n",
       "      <td>36170.541217</td>\n",
       "      <td>44407.169130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowtie2_ID0000019</th>\n",
       "      <td>974.757287</td>\n",
       "      <td>406.148870</td>\n",
       "      <td>389.226000</td>\n",
       "      <td>253.843043</td>\n",
       "      <td>243.266250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fasterq-dump_ID0000020</th>\n",
       "      <td>164060.827826</td>\n",
       "      <td>80876.861217</td>\n",
       "      <td>99413.812174</td>\n",
       "      <td>50548.038261</td>\n",
       "      <td>62133.632609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowtie2_ID0000021</th>\n",
       "      <td>1363.804939</td>\n",
       "      <td>576.090017</td>\n",
       "      <td>565.802696</td>\n",
       "      <td>360.056261</td>\n",
       "      <td>353.626685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>merge_ID0000022</th>\n",
       "      <td>0.384000</td>\n",
       "      <td>0.048000</td>\n",
       "      <td>-0.150000</td>\n",
       "      <td>0.030000</td>\n",
       "      <td>-0.093750</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               ZeusCpu  PrometeusCpu       AresCpu  \\\n",
       "bowtie2-build_ID0000001     335.827478    159.959930    188.350609   \n",
       "fasterq-dump_ID0000002   159221.188452  78487.560765  96471.693826   \n",
       "bowtie2_ID0000003           873.724104    369.073113    362.482522   \n",
       "fasterq-dump_ID0000004    46585.664000  22726.249600  27581.546000   \n",
       "bowtie2_ID0000005           782.037704    330.343513    324.444522   \n",
       "fasterq-dump_ID0000006    87037.907478  42741.829565  52293.980870   \n",
       "bowtie2_ID0000007           860.093217    358.372174    343.440000   \n",
       "fasterq-dump_ID0000008    39946.646817  19447.709635  23543.116957   \n",
       "bowtie2_ID0000009           673.529322    280.637217    268.944000   \n",
       "fasterq-dump_ID0000010   114676.087096  56526.656139  69475.046870   \n",
       "bowtie2_ID0000011           651.335791    271.389913    260.082000   \n",
       "fasterq-dump_ID0000012    68406.293148  33522.110470  40909.460435   \n",
       "bowtie2_ID0000013           714.670748    297.779478    285.372000   \n",
       "fasterq-dump_ID0000014    35153.921113  17079.499409  20623.910087   \n",
       "bowtie2_ID0000015           479.377252    199.740522    191.418000   \n",
       "fasterq-dump_ID0000016   149033.959513  73465.799791  90299.278957   \n",
       "bowtie2_ID0000017          1016.634991    423.597913    405.948000   \n",
       "fasterq-dump_ID0000018   117514.342400  57872.865948  71051.470609   \n",
       "bowtie2_ID0000019           974.757287    406.148870    389.226000   \n",
       "fasterq-dump_ID0000020   164060.827826  80876.861217  99413.812174   \n",
       "bowtie2_ID0000021          1363.804939    576.090017    565.802696   \n",
       "merge_ID0000022               0.384000      0.048000     -0.150000   \n",
       "\n",
       "                         PrometeusGpu       AresGpu  \n",
       "bowtie2-build_ID0000001     99.974957    117.719130  \n",
       "fasterq-dump_ID0000002   49054.725478  60294.808641  \n",
       "bowtie2_ID0000003          230.670696    226.551576  \n",
       "fasterq-dump_ID0000004   14203.906000  17238.466250  \n",
       "bowtie2_ID0000005          206.464696    202.777826  \n",
       "fasterq-dump_ID0000006   26713.643478  32683.738043  \n",
       "bowtie2_ID0000007          223.982609    214.650000  \n",
       "fasterq-dump_ID0000008   12154.818522  14714.448098  \n",
       "bowtie2_ID0000009          175.398261    168.090000  \n",
       "fasterq-dump_ID0000010   35329.160087  43421.904293  \n",
       "bowtie2_ID0000011          169.618696    162.551250  \n",
       "fasterq-dump_ID0000012   20951.319043  25568.412772  \n",
       "bowtie2_ID0000013          186.112174    178.357500  \n",
       "fasterq-dump_ID0000014   10674.687130  12889.943804  \n",
       "bowtie2_ID0000015          124.837826    119.636250  \n",
       "fasterq-dump_ID0000016   45916.124870  56437.049348  \n",
       "bowtie2_ID0000017          264.748696    253.717500  \n",
       "fasterq-dump_ID0000018   36170.541217  44407.169130  \n",
       "bowtie2_ID0000019          253.843043    243.266250  \n",
       "fasterq-dump_ID0000020   50548.038261  62133.632609  \n",
       "bowtie2_ID0000021          360.056261    353.626685  \n",
       "merge_ID0000022              0.030000     -0.093750  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cost_df = pd.DataFrame(data=costs, index = [j.name for j in jobs])\n",
    "cost_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "-h1x8j7TH5Ho",
   "metadata": {
    "id": "-h1x8j7TH5Ho",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "OZaZrqh6pz_t",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 739
    },
    "id": "OZaZrqh6pz_t",
    "outputId": "f027ee49-5cf2-459a-db01-eead99605993",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ZeusCpuRuntime</th>\n",
       "      <th>PrometeusCpuRuntime</th>\n",
       "      <th>AresCpuRuntime</th>\n",
       "      <th>PrometeusGpuRuntime</th>\n",
       "      <th>AresGpuRuntime</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>bowtie2-build_ID0000001</th>\n",
       "      <td>220.939130</td>\n",
       "      <td>55.234783</td>\n",
       "      <td>34.521739</td>\n",
       "      <td>0.552348</td>\n",
       "      <td>0.345217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fasterq-dump_ID0000002</th>\n",
       "      <td>31195.373913</td>\n",
       "      <td>7798.843478</td>\n",
       "      <td>4874.277174</td>\n",
       "      <td>77.988435</td>\n",
       "      <td>48.742772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowtie2_ID0000003</th>\n",
       "      <td>1883.026087</td>\n",
       "      <td>470.756522</td>\n",
       "      <td>294.222826</td>\n",
       "      <td>4.707565</td>\n",
       "      <td>2.942228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fasterq-dump_ID0000004</th>\n",
       "      <td>15738.400000</td>\n",
       "      <td>3934.600000</td>\n",
       "      <td>2459.125000</td>\n",
       "      <td>39.346000</td>\n",
       "      <td>24.591250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowtie2_ID0000005</th>\n",
       "      <td>1685.426087</td>\n",
       "      <td>421.356522</td>\n",
       "      <td>263.347826</td>\n",
       "      <td>4.213565</td>\n",
       "      <td>2.633478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fasterq-dump_ID0000006</th>\n",
       "      <td>21586.782609</td>\n",
       "      <td>5396.695652</td>\n",
       "      <td>3372.934783</td>\n",
       "      <td>53.966957</td>\n",
       "      <td>33.729348</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowtie2_ID0000007</th>\n",
       "      <td>1990.956522</td>\n",
       "      <td>497.739130</td>\n",
       "      <td>311.086957</td>\n",
       "      <td>4.977391</td>\n",
       "      <td>3.110870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fasterq-dump_ID0000008</th>\n",
       "      <td>14600.382609</td>\n",
       "      <td>3650.095652</td>\n",
       "      <td>2281.309783</td>\n",
       "      <td>36.500957</td>\n",
       "      <td>22.813098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowtie2_ID0000009</th>\n",
       "      <td>1559.095652</td>\n",
       "      <td>389.773913</td>\n",
       "      <td>243.608696</td>\n",
       "      <td>3.897739</td>\n",
       "      <td>2.436087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fasterq-dump_ID0000010</th>\n",
       "      <td>22538.539130</td>\n",
       "      <td>5634.634783</td>\n",
       "      <td>3521.646739</td>\n",
       "      <td>56.346348</td>\n",
       "      <td>35.216467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowtie2_ID0000011</th>\n",
       "      <td>1507.721739</td>\n",
       "      <td>376.930435</td>\n",
       "      <td>235.581522</td>\n",
       "      <td>3.769304</td>\n",
       "      <td>2.355815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fasterq-dump_ID0000012</th>\n",
       "      <td>18917.669565</td>\n",
       "      <td>4729.417391</td>\n",
       "      <td>2955.885870</td>\n",
       "      <td>47.294174</td>\n",
       "      <td>29.558859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowtie2_ID0000013</th>\n",
       "      <td>1654.330435</td>\n",
       "      <td>413.582609</td>\n",
       "      <td>258.489130</td>\n",
       "      <td>4.135826</td>\n",
       "      <td>2.584891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fasterq-dump_ID0000014</th>\n",
       "      <td>13818.365217</td>\n",
       "      <td>3454.591304</td>\n",
       "      <td>2159.119565</td>\n",
       "      <td>34.545913</td>\n",
       "      <td>21.591196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowtie2_ID0000015</th>\n",
       "      <td>1109.669565</td>\n",
       "      <td>277.417391</td>\n",
       "      <td>173.385870</td>\n",
       "      <td>2.774174</td>\n",
       "      <td>1.733859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fasterq-dump_ID0000016</th>\n",
       "      <td>29199.443478</td>\n",
       "      <td>7299.860870</td>\n",
       "      <td>4562.413043</td>\n",
       "      <td>72.998609</td>\n",
       "      <td>45.624130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowtie2_ID0000017</th>\n",
       "      <td>2353.321739</td>\n",
       "      <td>588.330435</td>\n",
       "      <td>367.706522</td>\n",
       "      <td>5.883304</td>\n",
       "      <td>3.677065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fasterq-dump_ID0000018</th>\n",
       "      <td>24564.034783</td>\n",
       "      <td>6141.008696</td>\n",
       "      <td>3838.130435</td>\n",
       "      <td>61.410087</td>\n",
       "      <td>38.381304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowtie2_ID0000019</th>\n",
       "      <td>2256.382609</td>\n",
       "      <td>564.095652</td>\n",
       "      <td>352.559783</td>\n",
       "      <td>5.640957</td>\n",
       "      <td>3.525598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fasterq-dump_ID0000020</th>\n",
       "      <td>32043.130435</td>\n",
       "      <td>8010.782609</td>\n",
       "      <td>5006.739130</td>\n",
       "      <td>80.107826</td>\n",
       "      <td>50.067391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bowtie2_ID0000021</th>\n",
       "      <td>2939.234783</td>\n",
       "      <td>734.808696</td>\n",
       "      <td>459.255435</td>\n",
       "      <td>7.348087</td>\n",
       "      <td>4.592554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>merge_ID0000022</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.625000</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>0.006250</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         ZeusCpuRuntime  PrometeusCpuRuntime  AresCpuRuntime  \\\n",
       "bowtie2-build_ID0000001      220.939130            55.234783       34.521739   \n",
       "fasterq-dump_ID0000002     31195.373913          7798.843478     4874.277174   \n",
       "bowtie2_ID0000003           1883.026087           470.756522      294.222826   \n",
       "fasterq-dump_ID0000004     15738.400000          3934.600000     2459.125000   \n",
       "bowtie2_ID0000005           1685.426087           421.356522      263.347826   \n",
       "fasterq-dump_ID0000006     21586.782609          5396.695652     3372.934783   \n",
       "bowtie2_ID0000007           1990.956522           497.739130      311.086957   \n",
       "fasterq-dump_ID0000008     14600.382609          3650.095652     2281.309783   \n",
       "bowtie2_ID0000009           1559.095652           389.773913      243.608696   \n",
       "fasterq-dump_ID0000010     22538.539130          5634.634783     3521.646739   \n",
       "bowtie2_ID0000011           1507.721739           376.930435      235.581522   \n",
       "fasterq-dump_ID0000012     18917.669565          4729.417391     2955.885870   \n",
       "bowtie2_ID0000013           1654.330435           413.582609      258.489130   \n",
       "fasterq-dump_ID0000014     13818.365217          3454.591304     2159.119565   \n",
       "bowtie2_ID0000015           1109.669565           277.417391      173.385870   \n",
       "fasterq-dump_ID0000016     29199.443478          7299.860870     4562.413043   \n",
       "bowtie2_ID0000017           2353.321739           588.330435      367.706522   \n",
       "fasterq-dump_ID0000018     24564.034783          6141.008696     3838.130435   \n",
       "bowtie2_ID0000019           2256.382609           564.095652      352.559783   \n",
       "fasterq-dump_ID0000020     32043.130435          8010.782609     5006.739130   \n",
       "bowtie2_ID0000021           2939.234783           734.808696      459.255435   \n",
       "merge_ID0000022                4.000000             1.000000        0.625000   \n",
       "\n",
       "                         PrometeusGpuRuntime  AresGpuRuntime  \n",
       "bowtie2-build_ID0000001             0.552348        0.345217  \n",
       "fasterq-dump_ID0000002             77.988435       48.742772  \n",
       "bowtie2_ID0000003                   4.707565        2.942228  \n",
       "fasterq-dump_ID0000004             39.346000       24.591250  \n",
       "bowtie2_ID0000005                   4.213565        2.633478  \n",
       "fasterq-dump_ID0000006             53.966957       33.729348  \n",
       "bowtie2_ID0000007                   4.977391        3.110870  \n",
       "fasterq-dump_ID0000008             36.500957       22.813098  \n",
       "bowtie2_ID0000009                   3.897739        2.436087  \n",
       "fasterq-dump_ID0000010             56.346348       35.216467  \n",
       "bowtie2_ID0000011                   3.769304        2.355815  \n",
       "fasterq-dump_ID0000012             47.294174       29.558859  \n",
       "bowtie2_ID0000013                   4.135826        2.584891  \n",
       "fasterq-dump_ID0000014             34.545913       21.591196  \n",
       "bowtie2_ID0000015                   2.774174        1.733859  \n",
       "fasterq-dump_ID0000016             72.998609       45.624130  \n",
       "bowtie2_ID0000017                   5.883304        3.677065  \n",
       "fasterq-dump_ID0000018             61.410087       38.381304  \n",
       "bowtie2_ID0000019                   5.640957        3.525598  \n",
       "fasterq-dump_ID0000020             80.107826       50.067391  \n",
       "bowtie2_ID0000021                   7.348087        4.592554  \n",
       "merge_ID0000022                     0.010000        0.006250  "
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "runtime_df = pd.DataFrame(data=runtimes, index = [j.name for j in jobs])\n",
    "runtime_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "jpUeBNdOw-_v",
   "metadata": {
    "id": "jpUeBNdOw-_v",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "UZJxsI_gxU_V",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "UZJxsI_gxU_V",
    "outputId": "f0baccfc-b285-45d8-8e9c-8c095ffcefc7",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'Shape (110, 20)'\n",
      "array([[2.2093913e+02, 2.2093913e+02, 2.2093913e+02, ..., 0.0000000e+00,\n",
      "        0.0000000e+00, 0.0000000e+00],\n",
      "       [0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ..., 0.0000000e+00,\n",
      "        0.0000000e+00, 0.0000000e+00],\n",
      "       [1.8830261e+03, 0.0000000e+00, 0.0000000e+00, ..., 0.0000000e+00,\n",
      "        0.0000000e+00, 0.0000000e+00],\n",
      "       ...,\n",
      "       [0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ..., 0.0000000e+00,\n",
      "        0.0000000e+00, 5.0067390e+01],\n",
      "       [0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ..., 0.0000000e+00,\n",
      "        0.0000000e+00, 4.5925546e+00],\n",
      "       [6.2500001e-03, 6.2500001e-03, 6.2500001e-03, ..., 6.2500001e-03,\n",
      "        6.2500001e-03, 6.2500001e-03]], dtype=float32)\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# flat_runtimes = [runtime for n, machine_runtimes in runtimes.items() for runtime in machine_runtimes]\n",
    "flat_runtimes = [(runtime, name) for n, machine_runtimes in runtimes.items() for runtime, name in zip(machine_runtimes, [j.name for j in jobs])]\n",
    "\n",
    "R = np.zeros(shape=(len(flat_runtimes),len(paths)), dtype=np.float32)\n",
    "\n",
    "for i, (job, name) in enumerate(flat_runtimes):\n",
    "    for j, path in enumerate(paths):\n",
    "      for node in path:\n",
    "        if name == node:\n",
    "          R[i,j] = job\n",
    "\n",
    "pprint(f'Shape {R.shape}')\n",
    "pprint(R)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "MHMaJtkMyGK3",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "MHMaJtkMyGK3",
    "outputId": "98b03ec8-908f-43ac-9413-dbd488fea97a",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 1., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 1., ..., 0., 0., 0.],\n",
       "       ...,\n",
       "       [0., 0., 0., ..., 1., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 1., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 1.]], dtype=float32)"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_size =  np.array(cost_df).shape[0] * np.array(cost_df).shape[1]\n",
    "USE_ONE_MACHINE  = np.zeros(shape=( y_size, np.array(cost_df).shape[0]), dtype = np.float32)\n",
    "for i in range(len(jobs)):\n",
    "  for j in range(i, y_size, len(jobs)):\n",
    "    USE_ONE_MACHINE[j,i] = 1\n",
    "\n",
    "USE_ONE_MACHINE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "E3uM5d1JT3M_",
   "metadata": {
    "id": "E3uM5d1JT3M_",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "DEADLINE = 40000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "qYZoqaKeT3XP",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "qYZoqaKeT3XP",
    "outputId": "05aeba06-3bf2-423e-a889-c316f7b74ee5",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 220,  220,  220, ...,    0,    0,    0],\n",
       "       [   0,    0,    0, ...,    0,    0,    0],\n",
       "       [1883,    0,    0, ...,    0,    0,    0],\n",
       "       ...,\n",
       "       [   0,    0,    0, ...,    0,    0,   50],\n",
       "       [   0,    0,    0, ...,    0,    0,    4],\n",
       "       [   0,    0,    0, ...,    0,    0,    0]])"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PATHS =  (R).astype(np.int32)\n",
    "PATHS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "gmko9CeiUaoR",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "gmko9CeiUaoR",
    "outputId": "dee17514-e79c-49ae-d5ff-483aeedd7a0c",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[    1,     2,     4, ...,     0,     0,     0],\n",
       "       [    0,     0,     0, ...,     0,     0,     0],\n",
       "       [    0,     0,     0, ...,     0,     0,     0],\n",
       "       ...,\n",
       "       [    0,     0,     0, ...,     0,     0,     0],\n",
       "       [    0,     0,     0, ...,     0,     0,     0],\n",
       "       [    0,     0,     0, ...,  8192, 16384, 32768]])"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "POWERS_2 = [ 2 ** i for i in range(np.ceil(np.log2(DEADLINE)).astype(np.int32))]\n",
    "POWERS_2\n",
    "\n",
    "SLACK = np.zeros(shape=(PATHS.shape[0], PATHS.shape[0] * len(POWERS_2))).astype(np.int32)\n",
    "\n",
    "for i in range(0, SLACK.shape[0]):\n",
    "    SLACK[i, i * len(POWERS_2):(i + 1) * len(POWERS_2)] = POWERS_2\n",
    "SLACK"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "U-CTkNB1Wvyf",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "U-CTkNB1Wvyf",
    "outputId": "326f595f-0eb5-42dc-d56c-2560556d87b4",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PATHS shape (110, 20)\n",
      "SLACK shape (110, 1760)\n",
      "USE_ONE_MACHINE shape (110, 22)\n",
      "Intermediate A shape (110, 1782)\n",
      "U shape (110, 1782)\n",
      "===================================================\n",
      "A shape (220, 1782)\n",
      "b shape (220,)\n"
     ]
    }
   ],
   "source": [
    "A = np.concatenate((PATHS,SLACK), axis=1)\n",
    "\n",
    "\n",
    "U = np.concatenate((USE_ONE_MACHINE, np.zeros(shape = (USE_ONE_MACHINE.shape[0], SLACK.shape[1]))), axis = 1)\n",
    "if U.shape[1] - A.shape[1] > 0:\n",
    "  A = np.pad(A, [(0, 0), (0, U.shape[1] - A.shape[1])], mode='constant', constant_values=0)\n",
    "elif U.shape[1] - A.shape[1] < 0:\n",
    "  U = np.pad(U, [(0, 0), (0, A.shape[1] - U.shape[1])], mode='constant', constant_values=0)\n",
    "\n",
    "b_paths = np.array([DEADLINE for i in range(A.shape[0])] , dtype=np.int32 )\n",
    "b_machines = np.array([1 for i in range(U.shape[0]) ] , dtype=np.int32 )\n",
    "b = np.concatenate((b_paths, b_machines), axis = 0)\n",
    "  \n",
    "A = np.pad(A, [(0, 0), (0, U.shape[1] - A.shape[1])], mode='constant', constant_values=0)\n",
    "S = 10000\n",
    "\n",
    "print(f'PATHS shape {PATHS.shape}')\n",
    "print(f'SLACK shape {SLACK.shape}')\n",
    "print(f'USE_ONE_MACHINE shape {USE_ONE_MACHINE.shape}')\n",
    "\n",
    "print(f'Intermediate A shape {A.shape}')\n",
    "print(f'U shape {U.shape}')\n",
    "\n",
    "A = np.concatenate((A, S * U))\n",
    "\n",
    "print(f'===================================================')\n",
    "print(f'A shape {A.shape}')\n",
    "print(f'b shape {b.shape}')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "VSFmKgZEalSt",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "VSFmKgZEalSt",
    "outputId": "25353b07-b796-487e-d9b8-156357f6ffa3",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C shape (110,)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([ 3.35827478e+02,  1.59959930e+02,  1.88350609e+02,  9.99749565e+01,\n",
       "        1.17719130e+02,  1.59221188e+05,  7.84875608e+04,  9.64716938e+04,\n",
       "        4.90547255e+04,  6.02948086e+04,  8.73724104e+02,  3.69073113e+02,\n",
       "        3.62482522e+02,  2.30670696e+02,  2.26551576e+02,  4.65856640e+04,\n",
       "        2.27262496e+04,  2.75815460e+04,  1.42039060e+04,  1.72384663e+04,\n",
       "        7.82037704e+02,  3.30343513e+02,  3.24444522e+02,  2.06464696e+02,\n",
       "        2.02777826e+02,  8.70379075e+04,  4.27418296e+04,  5.22939809e+04,\n",
       "        2.67136435e+04,  3.26837380e+04,  8.60093217e+02,  3.58372174e+02,\n",
       "        3.43440000e+02,  2.23982609e+02,  2.14650000e+02,  3.99466468e+04,\n",
       "        1.94477096e+04,  2.35431170e+04,  1.21548185e+04,  1.47144481e+04,\n",
       "        6.73529322e+02,  2.80637217e+02,  2.68944000e+02,  1.75398261e+02,\n",
       "        1.68090000e+02,  1.14676087e+05,  5.65266561e+04,  6.94750469e+04,\n",
       "        3.53291601e+04,  4.34219043e+04,  6.51335791e+02,  2.71389913e+02,\n",
       "        2.60082000e+02,  1.69618696e+02,  1.62551250e+02,  6.84062931e+04,\n",
       "        3.35221105e+04,  4.09094604e+04,  2.09513190e+04,  2.55684128e+04,\n",
       "        7.14670748e+02,  2.97779478e+02,  2.85372000e+02,  1.86112174e+02,\n",
       "        1.78357500e+02,  3.51539211e+04,  1.70794994e+04,  2.06239101e+04,\n",
       "        1.06746871e+04,  1.28899438e+04,  4.79377252e+02,  1.99740522e+02,\n",
       "        1.91418000e+02,  1.24837826e+02,  1.19636250e+02,  1.49033960e+05,\n",
       "        7.34657998e+04,  9.02992790e+04,  4.59161249e+04,  5.64370493e+04,\n",
       "        1.01663499e+03,  4.23597913e+02,  4.05948000e+02,  2.64748696e+02,\n",
       "        2.53717500e+02,  1.17514342e+05,  5.78728659e+04,  7.10514706e+04,\n",
       "        3.61705412e+04,  4.44071691e+04,  9.74757287e+02,  4.06148870e+02,\n",
       "        3.89226000e+02,  2.53843043e+02,  2.43266250e+02,  1.64060828e+05,\n",
       "        8.08768612e+04,  9.94138122e+04,  5.05480383e+04,  6.21336326e+04,\n",
       "        1.36380494e+03,  5.76090017e+02,  5.65802696e+02,  3.60056261e+02,\n",
       "        3.53626685e+02,  3.84000000e-01,  4.80000000e-02, -1.50000000e-01,\n",
       "        3.00000000e-02, -9.37500000e-02])"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "C_diag = np.diag(np.array(cost_df).flatten())\n",
    "C = np.array(cost_df).flatten()\n",
    "print(f'C shape {C.shape}')\n",
    "C"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "3hCbRFVFAkZX",
   "metadata": {
    "id": "3hCbRFVFAkZX",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "P = 10000\n",
    "\n",
    "# SOLUTION\n",
    "D = np.diag(2 * A.transpose().dot(b))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "9TdkAY7dwl73",
   "metadata": {
    "id": "9TdkAY7dwl73",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "C = np.pad(C, [(0, D.shape[0] - C.shape[0])], mode='constant')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "Npm2EyNvwj4U",
   "metadata": {
    "id": "Npm2EyNvwj4U",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "QUBO = P * (A.transpose().dot(A) + D) + C"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "383kXyjOxGDI",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "383kXyjOxGDI",
    "outputId": "a7ce21ea-b46d-45f0-8e18-d301c8632c1b",
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[7.41365643e+12, 5.25980160e+08, 5.25980188e+08, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       [5.25980336e+08, 7.18358253e+12, 5.25980188e+08, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       [5.25980336e+08, 5.25980160e+08, 7.53976453e+12, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       ...,\n",
       "       [3.35827478e+02, 1.59959930e+02, 1.88350609e+02, ...,\n",
       "        3.69518182e+13, 0.00000000e+00, 0.00000000e+00],\n",
       "       [3.35827478e+02, 1.59959930e+02, 1.88350609e+02, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       [3.35827478e+02, 1.59959930e+02, 1.88350609e+02, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00]])"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "QUBO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "4531719f",
   "metadata": {
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "import dimod\n",
    "from dimod.generators.constraints import combinations\n",
    "from dimod import BinaryQuadraticModel\n",
    "\n",
    "from hybrid.reference import KerberosSampler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "b33ea595",
   "metadata": {
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "def solve(qubo_matrix):\n",
    "    \"\"\"Solve BQM and return matrix with solution.\"\"\"\n",
    "    bqm = dimod.BinaryQuadraticModel(qubo_matrix, \"BINARY\")\n",
    "    solution = KerberosSampler().sample(bqm,\n",
    "                                        max_iter=10,\n",
    "                                        convergence=3,\n",
    "                                        qpu_params={'label': 'Trial - Workflow Optimization'})\n",
    "    best_solution = solution.first.sample\n",
    "    solution_list = [k for k, v in best_solution.items() if v == 1]\n",
    "\n",
    "    return solution\n",
    "\n",
    "    # result = solve_sudoku(bqm, matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "7c78a0a9",
   "metadata": {
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "solution = solve(QUBO)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "70553e86",
   "metadata": {
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SampleSet(rec.array([([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], -1397., 1)],\n",
       "          dtype=[('sample', 'i1', (1782,)), ('energy', '<f8'), ('num_occurrences', '<i4')]), Variables(range(0, 1782)), {}, 'BINARY')"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "solution"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "44b04368",
   "metadata": {
    "pycharm": {
     "is_executing": true
    }
   },
   "source": [
    "# Trying CQM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "98449079",
   "metadata": {
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['__class__',\n",
      " '__delattr__',\n",
      " '__dict__',\n",
      " '__dir__',\n",
      " '__doc__',\n",
      " '__eq__',\n",
      " '__format__',\n",
      " '__ge__',\n",
      " '__getattribute__',\n",
      " '__gt__',\n",
      " '__hash__',\n",
      " '__init__',\n",
      " '__init_subclass__',\n",
      " '__le__',\n",
      " '__lt__',\n",
      " '__module__',\n",
      " '__ne__',\n",
      " '__new__',\n",
      " '__reduce__',\n",
      " '__reduce_ex__',\n",
      " '__repr__',\n",
      " '__setattr__',\n",
      " '__sizeof__',\n",
      " '__str__',\n",
      " '__subclasshook__',\n",
      " '__weakref__',\n",
      " '_add_variables_from',\n",
      " '_discrete',\n",
      " '_iterable_to_qm',\n",
      " '_objective',\n",
      " '_substitute_self_loops_from_model',\n",
      " 'add_constraint',\n",
      " 'add_constraint_from_comparison',\n",
      " 'add_constraint_from_iterable',\n",
      " 'add_constraint_from_model',\n",
      " 'add_discrete',\n",
      " 'add_variable',\n",
      " 'check_feasible',\n",
      " 'constraints',\n",
      " 'discrete',\n",
      " 'from_bqm',\n",
      " 'from_discrete_quadratic_model',\n",
      " 'from_dqm',\n",
      " 'from_file',\n",
      " 'from_lp_file',\n",
      " 'from_qm',\n",
      " 'from_quadratic_model',\n",
      " 'is_almost_equal',\n",
      " 'is_equal',\n",
      " 'iter_constraint_data',\n",
      " 'iter_violations',\n",
      " 'lower_bound',\n",
      " 'num_biases',\n",
      " 'num_quadratic_variables',\n",
      " 'objective',\n",
      " 'relabel_variables',\n",
      " 'set_objective',\n",
      " 'substitute_self_loops',\n",
      " 'to_file',\n",
      " 'upper_bound',\n",
      " 'variables',\n",
      " 'vartype',\n",
      " 'violations']\n"
     ]
    }
   ],
   "source": [
    "from dimod import Binary, Integer, ConstrainedQuadraticModel\n",
    "from dwave.system import LeapHybridBQMSampler, LeapHybridCQMSampler\n",
    "\n",
    "x = Binary('x')\n",
    "i = Integer('i')\n",
    "j = Integer('j')\n",
    "cqm = ConstrainedQuadraticModel()\n",
    "\n",
    "pprint(dir(cqm))\n",
    "\n",
    "cqm.set_objective(2*i + 0.5*i*j -j*x + 10)\n",
    "cqm.add_constraint(x*j <= 3)                   \n",
    "cqm.add_constraint(i + j >= 1)\n",
    "\n",
    "sampler_cqm = LeapHybridCQMSampler()\n",
    "\n",
    "solution = sampler_cqm.sample_cqm(cqm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "5680273b",
   "metadata": {},
   "outputs": [],
   "source": [
    "best_solution = solution.first.sample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "48510c3d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'i': 0.0, 'j': 3756304736867460.0, 'x': 0.0}"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "best_solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "5b389b8b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['_REQUIRED_FIELDS',\n",
       " '__abstractmethods__',\n",
       " '__class__',\n",
       " '__class_getitem__',\n",
       " '__delattr__',\n",
       " '__dict__',\n",
       " '__dir__',\n",
       " '__doc__',\n",
       " '__eq__',\n",
       " '__format__',\n",
       " '__ge__',\n",
       " '__getattribute__',\n",
       " '__getstate__',\n",
       " '__gt__',\n",
       " '__hash__',\n",
       " '__init__',\n",
       " '__init_subclass__',\n",
       " '__iter__',\n",
       " '__le__',\n",
       " '__len__',\n",
       " '__lt__',\n",
       " '__module__',\n",
       " '__ne__',\n",
       " '__new__',\n",
       " '__reduce__',\n",
       " '__reduce_ex__',\n",
       " '__repr__',\n",
       " '__setattr__',\n",
       " '__sizeof__',\n",
       " '__slots__',\n",
       " '__str__',\n",
       " '__subclasshook__',\n",
       " '__weakref__',\n",
       " '_abc_impl',\n",
       " '_asdict',\n",
       " '_info',\n",
       " '_record',\n",
       " '_variables',\n",
       " '_vartype',\n",
       " 'aggregate',\n",
       " 'append_variables',\n",
       " 'change_vartype',\n",
       " 'copy',\n",
       " 'data',\n",
       " 'data_vectors',\n",
       " 'done',\n",
       " 'filter',\n",
       " 'first',\n",
       " 'from_future',\n",
       " 'from_samples',\n",
       " 'from_samples_bqm',\n",
       " 'from_serializable',\n",
       " 'info',\n",
       " 'is_writeable',\n",
       " 'lowest',\n",
       " 'record',\n",
       " 'relabel_variables',\n",
       " 'resolve',\n",
       " 'samples',\n",
       " 'slice',\n",
       " 'to_pandas_dataframe',\n",
       " 'to_serializable',\n",
       " 'truncate',\n",
       " 'variables',\n",
       " 'vartype',\n",
       " 'wait_id']"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dir(solution)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb5c119e",
   "metadata": {},
   "source": [
    "# Trying worflow problem using CQM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "ef8da95b",
   "metadata": {},
   "outputs": [],
   "source": [
    "cqm = ConstrainedQuadraticModel()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "ad78adb6",
   "metadata": {},
   "outputs": [],
   "source": [
    "job_count = len(cost_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "a880577d",
   "metadata": {},
   "outputs": [],
   "source": [
    "xs = []\n",
    "for machines in range(len(cost_df.columns)):\n",
    "    x = [Binary(f'm{machines}_x{i}') for i in range(job_count)]\n",
    "    xs.extend(x)\n",
    "\n",
    "model = None\n",
    "for variable, cost in zip(np.array(cost_df).flatten(), xs):\n",
    "    if model:\n",
    "        model = model + cost * variable\n",
    "    else:\n",
    "        model = cost * variable\n",
    "cqm.set_objective(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "150ef382",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "QuadraticModel({'m0_x0': 335.8274782608695, 'm0_x1': 159.9599304347826, 'm0_x2': 188.35060869565214, 'm0_x3': 99.97495652173913, 'm0_x4': 117.71913043478261, 'm0_x5': 159221.1884521739, 'm0_x6': 78487.56076521738, 'm0_x7': 96471.69382608694, 'm0_x8': 49054.72547826087, 'm0_x9': 60294.80864130434, 'm0_x10': 873.7241043478261, 'm0_x11': 369.07311304347826, 'm0_x12': 362.48252173913033, 'm0_x13': 230.67069565217392, 'm0_x14': 226.5515760869565, 'm0_x15': 46585.664000000004, 'm0_x16': 22726.249600000003, 'm0_x17': 27581.546000000006, 'm0_x18': 14203.906, 'm0_x19': 17238.466250000005, 'm0_x20': 782.0377043478261, 'm0_x21': 330.34351304347825, 'm1_x0': 324.4445217391304, 'm1_x1': 206.4646956521739, 'm1_x2': 202.7778260869565, 'm1_x3': 87037.90747826088, 'm1_x4': 42741.82956521739, 'm1_x5': 52293.98086956522, 'm1_x6': 26713.64347826087, 'm1_x7': 32683.73804347826, 'm1_x8': 860.0932173913044, 'm1_x9': 358.37217391304347, 'm1_x10': 343.44, 'm1_x11': 223.98260869565217, 'm1_x12': 214.65, 'm1_x13': 39946.6468173913, 'm1_x14': 19447.70963478261, 'm1_x15': 23543.116956521735, 'm1_x16': 12154.818521739131, 'm1_x17': 14714.448097826087, 'm1_x18': 673.5293217391305, 'm1_x19': 280.6372173913044, 'm1_x20': 268.944, 'm1_x21': 175.39826086956523, 'm2_x0': 168.09000000000003, 'm2_x1': 114676.08709565215, 'm2_x2': 56526.65613913043, 'm2_x3': 69475.04686956521, 'm2_x4': 35329.160086956515, 'm2_x5': 43421.904293478256, 'm2_x6': 651.3357913043478, 'm2_x7': 271.38991304347826, 'm2_x8': 260.082, 'm2_x9': 169.61869565217387, 'm2_x10': 162.55124999999998, 'm2_x11': 68406.29314782609, 'm2_x12': 33522.110469565225, 'm2_x13': 40909.46043478261, 'm2_x14': 20951.319043478263, 'm2_x15': 25568.41277173913, 'm2_x16': 714.6707478260869, 'm2_x17': 297.7794782608695, 'm2_x18': 285.37199999999996, 'm2_x19': 186.11217391304345, 'm2_x20': 178.3575, 'm2_x21': 35153.92111304348, 'm3_x0': 17079.49940869565, 'm3_x1': 20623.91008695652, 'm3_x2': 10674.68713043478, 'm3_x3': 12889.943804347826, 'm3_x4': 479.37725217391295, 'm3_x5': 199.74052173913037, 'm3_x6': 191.41799999999995, 'm3_x7': 124.83782608695648, 'm3_x8': 119.63624999999998, 'm3_x9': 149033.9595130435, 'm3_x10': 73465.79979130437, 'm3_x11': 90299.27895652175, 'm3_x12': 45916.12486956522, 'm3_x13': 56437.04934782609, 'm3_x14': 1016.6349913043479, 'm3_x15': 423.59791304347823, 'm3_x16': 405.948, 'm3_x17': 264.7486956521739, 'm3_x18': 253.71750000000003, 'm3_x19': 117514.3424, 'm3_x20': 57872.86594782608, 'm3_x21': 71051.47060869564, 'm4_x0': 36170.5412173913, 'm4_x1': 44407.16913043478, 'm4_x2': 974.7572869565217, 'm4_x3': 406.14886956521735, 'm4_x4': 389.226, 'm4_x5': 253.84304347826085, 'm4_x6': 243.26624999999999, 'm4_x7': 164060.82782608696, 'm4_x8': 80876.8612173913, 'm4_x9': 99413.81217391304, 'm4_x10': 50548.03826086956, 'm4_x11': 62133.632608695654, 'm4_x12': 1363.8049391304348, 'm4_x13': 576.0900173913044, 'm4_x14': 565.8026956521738, 'm4_x15': 360.05626086956516, 'm4_x16': 353.62668478260866, 'm4_x17': 0.384, 'm4_x18': 0.048, 'm4_x19': -0.15, 'm4_x20': 0.03, 'm4_x21': -0.09375}, {}, 0.0, {'m0_x0': 'BINARY', 'm0_x1': 'BINARY', 'm0_x2': 'BINARY', 'm0_x3': 'BINARY', 'm0_x4': 'BINARY', 'm0_x5': 'BINARY', 'm0_x6': 'BINARY', 'm0_x7': 'BINARY', 'm0_x8': 'BINARY', 'm0_x9': 'BINARY', 'm0_x10': 'BINARY', 'm0_x11': 'BINARY', 'm0_x12': 'BINARY', 'm0_x13': 'BINARY', 'm0_x14': 'BINARY', 'm0_x15': 'BINARY', 'm0_x16': 'BINARY', 'm0_x17': 'BINARY', 'm0_x18': 'BINARY', 'm0_x19': 'BINARY', 'm0_x20': 'BINARY', 'm0_x21': 'BINARY', 'm1_x0': 'BINARY', 'm1_x1': 'BINARY', 'm1_x2': 'BINARY', 'm1_x3': 'BINARY', 'm1_x4': 'BINARY', 'm1_x5': 'BINARY', 'm1_x6': 'BINARY', 'm1_x7': 'BINARY', 'm1_x8': 'BINARY', 'm1_x9': 'BINARY', 'm1_x10': 'BINARY', 'm1_x11': 'BINARY', 'm1_x12': 'BINARY', 'm1_x13': 'BINARY', 'm1_x14': 'BINARY', 'm1_x15': 'BINARY', 'm1_x16': 'BINARY', 'm1_x17': 'BINARY', 'm1_x18': 'BINARY', 'm1_x19': 'BINARY', 'm1_x20': 'BINARY', 'm1_x21': 'BINARY', 'm2_x0': 'BINARY', 'm2_x1': 'BINARY', 'm2_x2': 'BINARY', 'm2_x3': 'BINARY', 'm2_x4': 'BINARY', 'm2_x5': 'BINARY', 'm2_x6': 'BINARY', 'm2_x7': 'BINARY', 'm2_x8': 'BINARY', 'm2_x9': 'BINARY', 'm2_x10': 'BINARY', 'm2_x11': 'BINARY', 'm2_x12': 'BINARY', 'm2_x13': 'BINARY', 'm2_x14': 'BINARY', 'm2_x15': 'BINARY', 'm2_x16': 'BINARY', 'm2_x17': 'BINARY', 'm2_x18': 'BINARY', 'm2_x19': 'BINARY', 'm2_x20': 'BINARY', 'm2_x21': 'BINARY', 'm3_x0': 'BINARY', 'm3_x1': 'BINARY', 'm3_x2': 'BINARY', 'm3_x3': 'BINARY', 'm3_x4': 'BINARY', 'm3_x5': 'BINARY', 'm3_x6': 'BINARY', 'm3_x7': 'BINARY', 'm3_x8': 'BINARY', 'm3_x9': 'BINARY', 'm3_x10': 'BINARY', 'm3_x11': 'BINARY', 'm3_x12': 'BINARY', 'm3_x13': 'BINARY', 'm3_x14': 'BINARY', 'm3_x15': 'BINARY', 'm3_x16': 'BINARY', 'm3_x17': 'BINARY', 'm3_x18': 'BINARY', 'm3_x19': 'BINARY', 'm3_x20': 'BINARY', 'm3_x21': 'BINARY', 'm4_x0': 'BINARY', 'm4_x1': 'BINARY', 'm4_x2': 'BINARY', 'm4_x3': 'BINARY', 'm4_x4': 'BINARY', 'm4_x5': 'BINARY', 'm4_x6': 'BINARY', 'm4_x7': 'BINARY', 'm4_x8': 'BINARY', 'm4_x9': 'BINARY', 'm4_x10': 'BINARY', 'm4_x11': 'BINARY', 'm4_x12': 'BINARY', 'm4_x13': 'BINARY', 'm4_x14': 'BINARY', 'm4_x15': 'BINARY', 'm4_x16': 'BINARY', 'm4_x17': 'BINARY', 'm4_x18': 'BINARY', 'm4_x19': 'BINARY', 'm4_x20': 'BINARY', 'm4_x21': 'BINARY'}, dtype='float64')"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cqm.objective"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1da52047",
   "metadata": {},
   "source": [
    "### must use one machine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "f8d4249f",
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(job_count):\n",
    "    one_machine = None\n",
    "    for j in range(i, len(xs), job_count):\n",
    "        if one_machine:\n",
    "            one_machine = one_machine + xs[j]\n",
    "        else:\n",
    "            one_machine = xs[j]\n",
    "    cqm.add_constraint( one_machine == 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b074f305",
   "metadata": {},
   "source": [
    "### All paths must finish before a deadline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "98ecb242",
   "metadata": {},
   "outputs": [],
   "source": [
    "flat_runtimes = [(runtime, name) for n, machine_runtimes in runtimes.items() for runtime, name in zip(machine_runtimes, [j.name for j in jobs])]\n",
    "\n",
    "for path in paths:\n",
    "    path_runtime = None\n",
    "    for var, (runtime, name) in zip(xs, flat_runtimes):\n",
    "        if name not in path:\n",
    "            continue\n",
    "        if path_runtime:\n",
    "            path_runtime = path_runtime + runtime * var\n",
    "        else:\n",
    "            path_runtime = runtime * var\n",
    "    cqm.add_constraint(path_runtime <= DEADLINE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "d8c6ccc6",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'0a35d3': BinaryQuadraticModel({'m0_x0': 1.0, 'm1_x0': 1.0, 'm2_x0': 1.0, 'm3_x0': 1.0, 'm4_x0': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " '36db4e': BinaryQuadraticModel({'m0_x1': 1.0, 'm1_x1': 1.0, 'm2_x1': 1.0, 'm3_x1': 1.0, 'm4_x1': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " '7a0ab0': BinaryQuadraticModel({'m0_x2': 1.0, 'm1_x2': 1.0, 'm2_x2': 1.0, 'm3_x2': 1.0, 'm4_x2': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " 'd95dc1': BinaryQuadraticModel({'m0_x3': 1.0, 'm1_x3': 1.0, 'm2_x3': 1.0, 'm3_x3': 1.0, 'm4_x3': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " '6e464a': BinaryQuadraticModel({'m0_x4': 1.0, 'm1_x4': 1.0, 'm2_x4': 1.0, 'm3_x4': 1.0, 'm4_x4': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " 'a92b35': BinaryQuadraticModel({'m0_x5': 1.0, 'm1_x5': 1.0, 'm2_x5': 1.0, 'm3_x5': 1.0, 'm4_x5': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " 'aec8d4': BinaryQuadraticModel({'m0_x6': 1.0, 'm1_x6': 1.0, 'm2_x6': 1.0, 'm3_x6': 1.0, 'm4_x6': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " 'f69eb4': BinaryQuadraticModel({'m0_x7': 1.0, 'm1_x7': 1.0, 'm2_x7': 1.0, 'm3_x7': 1.0, 'm4_x7': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " '528dac': BinaryQuadraticModel({'m0_x8': 1.0, 'm1_x8': 1.0, 'm2_x8': 1.0, 'm3_x8': 1.0, 'm4_x8': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " 'f277a4': BinaryQuadraticModel({'m0_x9': 1.0, 'm1_x9': 1.0, 'm2_x9': 1.0, 'm3_x9': 1.0, 'm4_x9': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " '491d6b': BinaryQuadraticModel({'m0_x10': 1.0, 'm1_x10': 1.0, 'm2_x10': 1.0, 'm3_x10': 1.0, 'm4_x10': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " 'df1cad': BinaryQuadraticModel({'m0_x11': 1.0, 'm1_x11': 1.0, 'm2_x11': 1.0, 'm3_x11': 1.0, 'm4_x11': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " '45ef8b': BinaryQuadraticModel({'m0_x12': 1.0, 'm1_x12': 1.0, 'm2_x12': 1.0, 'm3_x12': 1.0, 'm4_x12': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " 'e5065b': BinaryQuadraticModel({'m0_x13': 1.0, 'm1_x13': 1.0, 'm2_x13': 1.0, 'm3_x13': 1.0, 'm4_x13': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " '09e8e8': BinaryQuadraticModel({'m0_x14': 1.0, 'm1_x14': 1.0, 'm2_x14': 1.0, 'm3_x14': 1.0, 'm4_x14': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " '74ae77': BinaryQuadraticModel({'m0_x15': 1.0, 'm1_x15': 1.0, 'm2_x15': 1.0, 'm3_x15': 1.0, 'm4_x15': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " '5ed0d8': BinaryQuadraticModel({'m0_x16': 1.0, 'm1_x16': 1.0, 'm2_x16': 1.0, 'm3_x16': 1.0, 'm4_x16': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " '9e8c1d': BinaryQuadraticModel({'m0_x17': 1.0, 'm1_x17': 1.0, 'm2_x17': 1.0, 'm3_x17': 1.0, 'm4_x17': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " '357135': BinaryQuadraticModel({'m0_x18': 1.0, 'm1_x18': 1.0, 'm2_x18': 1.0, 'm3_x18': 1.0, 'm4_x18': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " 'ba79e8': BinaryQuadraticModel({'m0_x19': 1.0, 'm1_x19': 1.0, 'm2_x19': 1.0, 'm3_x19': 1.0, 'm4_x19': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " 'f69ce5': BinaryQuadraticModel({'m0_x20': 1.0, 'm1_x20': 1.0, 'm2_x20': 1.0, 'm3_x20': 1.0, 'm4_x20': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " '3f3993': BinaryQuadraticModel({'m0_x21': 1.0, 'm1_x21': 1.0, 'm2_x21': 1.0, 'm3_x21': 1.0, 'm4_x21': 1.0}, {}, 0.0, 'BINARY') == 1,\n",
       " '43d30a': BinaryQuadraticModel({'m0_x0': 220.93913043478258, 'm0_x2': 1883.0260869565216, 'm0_x21': 4.0, 'm1_x0': 55.234782608695646, 'm1_x2': 470.7565217391304, 'm1_x21': 1.0, 'm2_x0': 34.521739130434774, 'm2_x2': 294.2228260869565, 'm2_x21': 0.625, 'm3_x0': 0.5523478260869564, 'm3_x2': 4.707565217391304, 'm3_x21': 0.01, 'm4_x0': 0.3452173913043478, 'm4_x2': 2.942228260869565, 'm4_x21': 0.00625}, {}, 0.0, 'BINARY') <= 40000,\n",
       " '3868cc': BinaryQuadraticModel({'m0_x0': 220.93913043478258, 'm0_x4': 1685.4260869565217, 'm0_x21': 4.0, 'm1_x0': 55.234782608695646, 'm1_x4': 421.3565217391304, 'm1_x21': 1.0, 'm2_x0': 34.521739130434774, 'm2_x4': 263.3478260869565, 'm2_x21': 0.625, 'm3_x0': 0.5523478260869564, 'm3_x4': 4.213565217391304, 'm3_x21': 0.01, 'm4_x0': 0.3452173913043478, 'm4_x4': 2.6334782608695653, 'm4_x21': 0.00625}, {}, 0.0, 'BINARY') <= 40000,\n",
       " 'b1a399': BinaryQuadraticModel({'m0_x0': 220.93913043478258, 'm0_x6': 1990.9565217391305, 'm0_x21': 4.0, 'm1_x0': 55.234782608695646, 'm1_x6': 497.7391304347826, 'm1_x21': 1.0, 'm2_x0': 34.521739130434774, 'm2_x6': 311.0869565217391, 'm2_x21': 0.625, 'm3_x0': 0.5523478260869564, 'm3_x6': 4.977391304347826, 'm3_x21': 0.01, 'm4_x0': 0.3452173913043478, 'm4_x6': 3.110869565217391, 'm4_x21': 0.00625}, {}, 0.0, 'BINARY') <= 40000,\n",
       " '1c7bde': BinaryQuadraticModel({'m0_x0': 220.93913043478258, 'm0_x8': 1559.095652173913, 'm0_x21': 4.0, 'm1_x0': 55.234782608695646, 'm1_x8': 389.7739130434783, 'm1_x21': 1.0, 'm2_x0': 34.521739130434774, 'm2_x8': 243.6086956521739, 'm2_x21': 0.625, 'm3_x0': 0.5523478260869564, 'm3_x8': 3.8977391304347826, 'm3_x21': 0.01, 'm4_x0': 0.3452173913043478, 'm4_x8': 2.436086956521739, 'm4_x21': 0.00625}, {}, 0.0, 'BINARY') <= 40000,\n",
       " 'd80f6d': BinaryQuadraticModel({'m0_x0': 220.93913043478258, 'm0_x10': 1507.7217391304346, 'm0_x21': 4.0, 'm1_x0': 55.234782608695646, 'm1_x10': 376.93043478260864, 'm1_x21': 1.0, 'm2_x0': 34.521739130434774, 'm2_x10': 235.58152173913038, 'm2_x21': 0.625, 'm3_x0': 0.5523478260869564, 'm3_x10': 3.7693043478260866, 'm3_x21': 0.01, 'm4_x0': 0.3452173913043478, 'm4_x10': 2.355815217391304, 'm4_x21': 0.00625}, {}, 0.0, 'BINARY') <= 40000,\n",
       " 'b5ee9e': BinaryQuadraticModel({'m0_x0': 220.93913043478258, 'm0_x12': 1654.3304347826083, 'm0_x21': 4.0, 'm1_x0': 55.234782608695646, 'm1_x12': 413.5826086956521, 'm1_x21': 1.0, 'm2_x0': 34.521739130434774, 'm2_x12': 258.4891304347825, 'm2_x21': 0.625, 'm3_x0': 0.5523478260869564, 'm3_x12': 4.135826086956521, 'm3_x21': 0.01, 'm4_x0': 0.3452173913043478, 'm4_x12': 2.5848913043478254, 'm4_x21': 0.00625}, {}, 0.0, 'BINARY') <= 40000,\n",
       " 'e0b1fe': BinaryQuadraticModel({'m0_x0': 220.93913043478258, 'm0_x14': 1109.669565217391, 'm0_x21': 4.0, 'm1_x0': 55.234782608695646, 'm1_x14': 277.41739130434775, 'm1_x21': 1.0, 'm2_x0': 34.521739130434774, 'm2_x14': 173.38586956521732, 'm2_x21': 0.625, 'm3_x0': 0.5523478260869564, 'm3_x14': 2.7741739130434775, 'm3_x21': 0.01, 'm4_x0': 0.3452173913043478, 'm4_x14': 1.7338586956521733, 'm4_x21': 0.00625}, {}, 0.0, 'BINARY') <= 40000,\n",
       " '928933': BinaryQuadraticModel({'m0_x0': 220.93913043478258, 'm0_x16': 2353.3217391304347, 'm0_x21': 4.0, 'm1_x0': 55.234782608695646, 'm1_x16': 588.3304347826087, 'm1_x21': 1.0, 'm2_x0': 34.521739130434774, 'm2_x16': 367.7065217391304, 'm2_x21': 0.625, 'm3_x0': 0.5523478260869564, 'm3_x16': 5.883304347826087, 'm3_x21': 0.01, 'm4_x0': 0.3452173913043478, 'm4_x16': 3.6770652173913043, 'm4_x21': 0.00625}, {}, 0.0, 'BINARY') <= 40000,\n",
       " '9ff623': BinaryQuadraticModel({'m0_x0': 220.93913043478258, 'm0_x18': 2256.382608695652, 'm0_x21': 4.0, 'm1_x0': 55.234782608695646, 'm1_x18': 564.095652173913, 'm1_x21': 1.0, 'm2_x0': 34.521739130434774, 'm2_x18': 352.55978260869557, 'm2_x21': 0.625, 'm3_x0': 0.5523478260869564, 'm3_x18': 5.64095652173913, 'm3_x21': 0.01, 'm4_x0': 0.3452173913043478, 'm4_x18': 3.525597826086956, 'm4_x21': 0.00625}, {}, 0.0, 'BINARY') <= 40000,\n",
       " '2aa2dc': BinaryQuadraticModel({'m0_x0': 220.93913043478258, 'm0_x20': 2939.2347826086952, 'm0_x21': 4.0, 'm1_x0': 55.234782608695646, 'm1_x20': 734.8086956521738, 'm1_x21': 1.0, 'm2_x0': 34.521739130434774, 'm2_x20': 459.25543478260863, 'm2_x21': 0.625, 'm3_x0': 0.5523478260869564, 'm3_x20': 7.348086956521738, 'm3_x21': 0.01, 'm4_x0': 0.3452173913043478, 'm4_x20': 4.592554347826086, 'm4_x21': 0.00625}, {}, 0.0, 'BINARY') <= 40000,\n",
       " '371e7b': BinaryQuadraticModel({'m0_x1': 31195.373913043473, 'm0_x2': 1883.0260869565216, 'm0_x21': 4.0, 'm1_x1': 7798.843478260868, 'm1_x2': 470.7565217391304, 'm1_x21': 1.0, 'm2_x1': 4874.277173913042, 'm2_x2': 294.2228260869565, 'm2_x21': 0.625, 'm3_x1': 77.98843478260868, 'm3_x2': 4.707565217391304, 'm3_x21': 0.01, 'm4_x1': 48.742771739130426, 'm4_x2': 2.942228260869565, 'm4_x21': 0.00625}, {}, 0.0, 'BINARY') <= 40000,\n",
       " '6e074a': BinaryQuadraticModel({'m0_x3': 15738.400000000001, 'm0_x4': 1685.4260869565217, 'm0_x21': 4.0, 'm1_x3': 3934.6000000000004, 'm1_x4': 421.3565217391304, 'm1_x21': 1.0, 'm2_x3': 2459.125, 'm2_x4': 263.3478260869565, 'm2_x21': 0.625, 'm3_x3': 39.346000000000004, 'm3_x4': 4.213565217391304, 'm3_x21': 0.01, 'm4_x3': 24.591250000000002, 'm4_x4': 2.6334782608695653, 'm4_x21': 0.00625}, {}, 0.0, 'BINARY') <= 40000,\n",
       " 'b59b65': BinaryQuadraticModel({'m0_x5': 21586.782608695652, 'm0_x6': 1990.9565217391305, 'm0_x21': 4.0, 'm1_x5': 5396.695652173913, 'm1_x6': 497.7391304347826, 'm1_x21': 1.0, 'm2_x5': 3372.9347826086955, 'm2_x6': 311.0869565217391, 'm2_x21': 0.625, 'm3_x5': 53.96695652173913, 'm3_x6': 4.977391304347826, 'm3_x21': 0.01, 'm4_x5': 33.72934782608696, 'm4_x6': 3.110869565217391, 'm4_x21': 0.00625}, {}, 0.0, 'BINARY') <= 40000,\n",
       " '21e758': BinaryQuadraticModel({'m0_x7': 14600.38260869565, 'm0_x8': 1559.095652173913, 'm0_x21': 4.0, 'm1_x7': 3650.0956521739126, 'm1_x8': 389.7739130434783, 'm1_x21': 1.0, 'm2_x7': 2281.309782608695, 'm2_x8': 243.6086956521739, 'm2_x21': 0.625, 'm3_x7': 36.50095652173913, 'm3_x8': 3.8977391304347826, 'm3_x21': 0.01, 'm4_x7': 22.813097826086953, 'm4_x8': 2.436086956521739, 'm4_x21': 0.00625}, {}, 0.0, 'BINARY') <= 40000,\n",
       " '934eff': BinaryQuadraticModel({'m0_x9': 22538.53913043478, 'm0_x10': 1507.7217391304346, 'm0_x21': 4.0, 'm1_x9': 5634.634782608695, 'm1_x10': 376.93043478260864, 'm1_x21': 1.0, 'm2_x9': 3521.646739130434, 'm2_x10': 235.58152173913038, 'm2_x21': 0.625, 'm3_x9': 56.34634782608695, 'm3_x10': 3.7693043478260866, 'm3_x21': 0.01, 'm4_x9': 35.21646739130434, 'm4_x10': 2.355815217391304, 'm4_x21': 0.00625}, {}, 0.0, 'BINARY') <= 40000,\n",
       " 'f0927d': BinaryQuadraticModel({'m0_x11': 18917.66956521739, 'm0_x12': 1654.3304347826083, 'm0_x21': 4.0, 'm1_x11': 4729.417391304348, 'm1_x12': 413.5826086956521, 'm1_x21': 1.0, 'm2_x11': 2955.885869565217, 'm2_x12': 258.4891304347825, 'm2_x21': 0.625, 'm3_x11': 47.29417391304348, 'm3_x12': 4.135826086956521, 'm3_x21': 0.01, 'm4_x11': 29.558858695652173, 'm4_x12': 2.5848913043478254, 'm4_x21': 0.00625}, {}, 0.0, 'BINARY') <= 40000,\n",
       " '56ba37': BinaryQuadraticModel({'m0_x13': 13818.365217391303, 'm0_x14': 1109.669565217391, 'm0_x21': 4.0, 'm1_x13': 3454.591304347826, 'm1_x14': 277.41739130434775, 'm1_x21': 1.0, 'm2_x13': 2159.119565217391, 'm2_x14': 173.38586956521732, 'm2_x21': 0.625, 'm3_x13': 34.54591304347826, 'm3_x14': 2.7741739130434775, 'm3_x21': 0.01, 'm4_x13': 21.591195652173912, 'm4_x14': 1.7338586956521733, 'm4_x21': 0.00625}, {}, 0.0, 'BINARY') <= 40000,\n",
       " '6eb37e': BinaryQuadraticModel({'m0_x15': 29199.44347826087, 'm0_x16': 2353.3217391304347, 'm0_x21': 4.0, 'm1_x15': 7299.860869565217, 'm1_x16': 588.3304347826087, 'm1_x21': 1.0, 'm2_x15': 4562.413043478261, 'm2_x16': 367.7065217391304, 'm2_x21': 0.625, 'm3_x15': 72.99860869565218, 'm3_x16': 5.883304347826087, 'm3_x21': 0.01, 'm4_x15': 45.62413043478261, 'm4_x16': 3.6770652173913043, 'm4_x21': 0.00625}, {}, 0.0, 'BINARY') <= 40000,\n",
       " '2e85c2': BinaryQuadraticModel({'m0_x17': 24564.03478260869, 'm0_x18': 2256.382608695652, 'm0_x21': 4.0, 'm1_x17': 6141.008695652173, 'm1_x18': 564.095652173913, 'm1_x21': 1.0, 'm2_x17': 3838.1304347826076, 'm2_x18': 352.55978260869557, 'm2_x21': 0.625, 'm3_x17': 61.410086956521724, 'm3_x18': 5.64095652173913, 'm3_x21': 0.01, 'm4_x17': 38.38130434782608, 'm4_x18': 3.525597826086956, 'm4_x21': 0.00625}, {}, 0.0, 'BINARY') <= 40000,\n",
       " 'cec10a': BinaryQuadraticModel({'m0_x19': 32043.130434782608, 'm0_x20': 2939.2347826086952, 'm0_x21': 4.0, 'm1_x19': 8010.782608695652, 'm1_x20': 734.8086956521738, 'm1_x21': 1.0, 'm2_x19': 5006.739130434782, 'm2_x20': 459.25543478260863, 'm2_x21': 0.625, 'm3_x19': 80.10782608695652, 'm3_x20': 7.348086956521738, 'm3_x21': 0.01, 'm4_x19': 50.06739130434782, 'm4_x20': 4.592554347826086, 'm4_x21': 0.00625}, {}, 0.0, 'BINARY') <= 40000}"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cqm.constraints"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "cb147ec6",
   "metadata": {},
   "outputs": [],
   "source": [
    "sampler_cqm = LeapHybridCQMSampler()\n",
    "\n",
    "solution = sampler_cqm.sample_cqm(cqm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "47fff72c",
   "metadata": {},
   "outputs": [],
   "source": [
    "best_solution = solution.first.sample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "e4bc625c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'m0_x0': 0.0,\n",
       " 'm0_x1': 0.0,\n",
       " 'm0_x10': 0.0,\n",
       " 'm0_x11': 0.0,\n",
       " 'm0_x12': 0.0,\n",
       " 'm0_x13': 0.0,\n",
       " 'm0_x14': 0.0,\n",
       " 'm0_x15': 0.0,\n",
       " 'm0_x16': 0.0,\n",
       " 'm0_x17': 0.0,\n",
       " 'm0_x18': 0.0,\n",
       " 'm0_x19': 0.0,\n",
       " 'm0_x2': 0.0,\n",
       " 'm0_x20': 0.0,\n",
       " 'm0_x21': 0.0,\n",
       " 'm0_x3': 1.0,\n",
       " 'm0_x4': 0.0,\n",
       " 'm0_x5': 0.0,\n",
       " 'm0_x6': 0.0,\n",
       " 'm0_x7': 0.0,\n",
       " 'm0_x8': 0.0,\n",
       " 'm0_x9': 0.0,\n",
       " 'm1_x0': 0.0,\n",
       " 'm1_x1': 0.0,\n",
       " 'm1_x10': 0.0,\n",
       " 'm1_x11': 1.0,\n",
       " 'm1_x12': 0.0,\n",
       " 'm1_x13': 0.0,\n",
       " 'm1_x14': 0.0,\n",
       " 'm1_x15': 0.0,\n",
       " 'm1_x16': 0.0,\n",
       " 'm1_x17': 0.0,\n",
       " 'm1_x18': 0.0,\n",
       " 'm1_x19': 0.0,\n",
       " 'm1_x2': 0.0,\n",
       " 'm1_x20': 0.0,\n",
       " 'm1_x21': 0.0,\n",
       " 'm1_x3': 0.0,\n",
       " 'm1_x4': 0.0,\n",
       " 'm1_x5': 0.0,\n",
       " 'm1_x6': 0.0,\n",
       " 'm1_x7': 0.0,\n",
       " 'm1_x8': 0.0,\n",
       " 'm1_x9': 0.0,\n",
       " 'm2_x0': 0.0,\n",
       " 'm2_x1': 0.0,\n",
       " 'm2_x10': 0.0,\n",
       " 'm2_x11': 0.0,\n",
       " 'm2_x12': 0.0,\n",
       " 'm2_x13': 0.0,\n",
       " 'm2_x14': 0.0,\n",
       " 'm2_x15': 0.0,\n",
       " 'm2_x16': 0.0,\n",
       " 'm2_x17': 0.0,\n",
       " 'm2_x18': 0.0,\n",
       " 'm2_x19': 0.0,\n",
       " 'm2_x2': 0.0,\n",
       " 'm2_x20': 0.0,\n",
       " 'm2_x21': 0.0,\n",
       " 'm2_x3': 0.0,\n",
       " 'm2_x4': 0.0,\n",
       " 'm2_x5': 0.0,\n",
       " 'm2_x6': 0.0,\n",
       " 'm2_x7': 0.0,\n",
       " 'm2_x8': 0.0,\n",
       " 'm2_x9': 0.0,\n",
       " 'm3_x0': 0.0,\n",
       " 'm3_x1': 0.0,\n",
       " 'm3_x10': 0.0,\n",
       " 'm3_x11': 0.0,\n",
       " 'm3_x12': 0.0,\n",
       " 'm3_x13': 0.0,\n",
       " 'm3_x14': 0.0,\n",
       " 'm3_x15': 0.0,\n",
       " 'm3_x16': 0.0,\n",
       " 'm3_x17': 0.0,\n",
       " 'm3_x18': 0.0,\n",
       " 'm3_x19': 0.0,\n",
       " 'm3_x2': 0.0,\n",
       " 'm3_x20': 0.0,\n",
       " 'm3_x21': 0.0,\n",
       " 'm3_x3': 0.0,\n",
       " 'm3_x4': 0.0,\n",
       " 'm3_x5': 1.0,\n",
       " 'm3_x6': 1.0,\n",
       " 'm3_x7': 0.0,\n",
       " 'm3_x8': 1.0,\n",
       " 'm3_x9': 0.0,\n",
       " 'm4_x0': 0.0,\n",
       " 'm4_x1': 0.0,\n",
       " 'm4_x10': 0.0,\n",
       " 'm4_x11': 0.0,\n",
       " 'm4_x12': 0.0,\n",
       " 'm4_x13': 0.0,\n",
       " 'm4_x14': 0.0,\n",
       " 'm4_x15': 0.0,\n",
       " 'm4_x16': 1.0,\n",
       " 'm4_x17': 1.0,\n",
       " 'm4_x18': 1.0,\n",
       " 'm4_x19': 1.0,\n",
       " 'm4_x2': 0.0,\n",
       " 'm4_x20': 1.0,\n",
       " 'm4_x21': 1.0,\n",
       " 'm4_x3': 0.0,\n",
       " 'm4_x4': 0.0,\n",
       " 'm4_x5': 0.0,\n",
       " 'm4_x6': 0.0,\n",
       " 'm4_x7': 0.0,\n",
       " 'm4_x8': 0.0,\n",
       " 'm4_x9': 0.0}"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "best_solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "b4f2e73a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "provided_solutions: 52\n",
      "correct_solutions: 35\n"
     ]
    }
   ],
   "source": [
    "def is_correct_solution(cqm, sol):\n",
    "    return len(cqm.violations(sol, skip_satisfied = True)) == 0\n",
    "\n",
    "correct_solutions = [ s for s in solution if is_correct_solution(cqm, s)]\n",
    "\n",
    "print( f\"provided_solutions: {len(solution)}\")\n",
    "print( f\"correct_solutions: {len(correct_solutions)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "3eb083dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "from parse import parse\n",
    "\n",
    "def solve_workflow(machines, jobs, solution):\n",
    "    actual_solution = {}\n",
    "\n",
    "    for k, is_used in solution.items():\n",
    "        machine, var = parse('m{}_x{}', k)\n",
    "        if is_used:\n",
    "            actual_solution[int(var)] = machines[int(machine)]\n",
    "    return actual_solution\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "e9745c2d",
   "metadata": {},
   "outputs": [],
   "source": [
    "machine_names = cost_df.columns\n",
    "job_names = cost_df.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "17a61095",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1: 'ZeusCpu',\n",
       " 13: 'ZeusCpu',\n",
       " 14: 'ZeusCpu',\n",
       " 2: 'ZeusCpu',\n",
       " 3: 'ZeusCpu',\n",
       " 4: 'ZeusCpu',\n",
       " 11: 'PrometeusCpu',\n",
       " 12: 'PrometeusCpu',\n",
       " 0: 'AresCpu',\n",
       " 10: 'AresCpu',\n",
       " 9: 'AresCpu',\n",
       " 5: 'PrometeusGpu',\n",
       " 6: 'PrometeusGpu',\n",
       " 7: 'PrometeusGpu',\n",
       " 8: 'PrometeusGpu',\n",
       " 15: 'AresGpu',\n",
       " 16: 'AresGpu',\n",
       " 17: 'AresGpu',\n",
       " 18: 'AresGpu',\n",
       " 19: 'AresGpu',\n",
       " 20: 'AresGpu',\n",
       " 21: 'AresGpu'}"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "solve_workflow(machine_names, job_names, correct_solutions[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "189de590",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SampleSet(rec.array([([0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 1., 1., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0.], 1714.47625   , 1, False, [False,  True,  True,  True,  True,  True, False,  True,  True,  True,  True,  True,  True,  True, False, False,  True, False,  True,  True,  True,  True,  True,  True,  True,  True, False, False,  True,  True,  True, False,  True,  True,  True,  True,  True, False,  True,  True,  True,  True]),\n",
       "           ([0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 2048.90754348, 1, False, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True, False,  True,  True, False,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True, False,  True, False,  True,  True,  True,  True,  True,  True,  True,  True,  True, False,  True,  True,  True,  True]),\n",
       "           ([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 1647.38728261, 1, False, [ True,  True,  True,  True,  True,  True, False,  True,  True,  True,  True,  True,  True,  True, False,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True, False,  True, False,  True,  True,  True, False,  True,  True,  True, False, False, False,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.22124565, 1, False, [ True,  True, False,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True, False,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 1188.59727174, 1, False, [False,  True,  True,  True,  True,  True, False,  True,  True,  True,  True, False,  True,  True, False, False,  True,  True,  True,  True,  True, False,  True,  True,  True, False, False, False,  True,  True,  True, False,  True,  True,  True,  True, False,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 1738.1221913 , 1, False, [ True,  True, False,  True,  True,  True, False,  True,  True, False,  True, False,  True,  True,  True,  True,  True,  True,  True,  True, False, False,  True,  True,  True, False, False,  True,  True,  True,  True,  True,  True,  True,  True, False,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.22124565, 1, False, [ True,  True, False,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True, False,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3069.09628913, 1, False, [False,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True, False,  True,  True,  True,  True,  True]),\n",
       "           ([0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0.], 1897.35793478, 1, False, [ True,  True, False,  True,  True,  True,  True,  True,  True, False,  True, False,  True,  True, False,  True,  True, False,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True, False, False, False,  True,  True,  True,  True]),\n",
       "           ([0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 1513.4811413 , 1, False, [False,  True,  True,  True,  True,  True, False,  True,  True, False,  True, False,  True,  True, False,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True, False,  True, False,  True,  True,  True, False,  True,  True,  True,  True, False,  True]),\n",
       "           ([0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 1., 1., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0.], 1725.68854348, 1, False, [False,  True,  True,  True,  True,  True, False,  True,  True, False,  True,  True,  True,  True, False,  True,  True, False,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True, False, False, False,  True,  True, False,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 1624.5466913 , 1, False, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True, False,  True,  True,  True,  True,  True,  True,  True,  True,  True, False,  True,  True,  True, False,  True, False,  True, False,  True,  True,  True,  True,  True, False, False, False,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 0., 1., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0.], 2443.48037609, 1, False, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True, False,  True, False,  True,  True, False, False,  True,  True,  True,  True,  True,  True,  True, False,  True, False,  True,  True,  True,  True,  True,  True,  True,  True, False,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 2897.26272391, 1, False, [ True,  True,  True,  True,  True,  True, False,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True, False,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 2408.96380435, 1, False, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True, False,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True, False,  True, False,  True,  True,  True,  True,  True,  True,  True,  True,  True, False,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3069.09628913, 1, False, [False,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True, False,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3186.81541957, 1, False, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True, False,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True]),\n",
       "           ([0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 0.], 3311.65324565, 1,  True, [ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True])],\n",
       "          dtype=[('sample', '<f8', (110,)), ('energy', '<f8'), ('num_occurrences', '<i4'), ('is_feasible', '?'), ('is_satisfied', '?', (42,))]), Variables(['m0_x0', 'm0_x1', 'm0_x10', 'm0_x11', 'm0_x12', 'm0_x13', 'm0_x14', 'm0_x15', 'm0_x16', 'm0_x17', 'm0_x18', 'm0_x19', 'm0_x2', 'm0_x20', 'm0_x21', 'm0_x3', 'm0_x4', 'm0_x5', 'm0_x6', 'm0_x7', 'm0_x8', 'm0_x9', 'm1_x0', 'm1_x1', 'm1_x10', 'm1_x11', 'm1_x12', 'm1_x13', 'm1_x14', 'm1_x15', 'm1_x16', 'm1_x17', 'm1_x18', 'm1_x19', 'm1_x2', 'm1_x20', 'm1_x21', 'm1_x3', 'm1_x4', 'm1_x5', 'm1_x6', 'm1_x7', 'm1_x8', 'm1_x9', 'm2_x0', 'm2_x1', 'm2_x10', 'm2_x11', 'm2_x12', 'm2_x13', 'm2_x14', 'm2_x15', 'm2_x16', 'm2_x17', 'm2_x18', 'm2_x19', 'm2_x2', 'm2_x20', 'm2_x21', 'm2_x3', 'm2_x4', 'm2_x5', 'm2_x6', 'm2_x7', 'm2_x8', 'm2_x9', 'm3_x0', 'm3_x1', 'm3_x10', 'm3_x11', 'm3_x12', 'm3_x13', 'm3_x14', 'm3_x15', 'm3_x16', 'm3_x17', 'm3_x18', 'm3_x19', 'm3_x2', 'm3_x20', 'm3_x21', 'm3_x3', 'm3_x4', 'm3_x5', 'm3_x6', 'm3_x7', 'm3_x8', 'm3_x9', 'm4_x0', 'm4_x1', 'm4_x10', 'm4_x11', 'm4_x12', 'm4_x13', 'm4_x14', 'm4_x15', 'm4_x16', 'm4_x17', 'm4_x18', 'm4_x19', 'm4_x2', 'm4_x20', 'm4_x21', 'm4_x3', 'm4_x4', 'm4_x5', 'm4_x6', 'm4_x7', 'm4_x8', 'm4_x9']), {'constraint_labels': ['6e464a', '528dac', '9e8c1d', '43d30a', '1c7bde', '21e758', '45ef8b', 'b59b65', 'e0b1fe', 'df1cad', '56ba37', '74ae77', '371e7b', 'f0927d', '36db4e', 'f277a4', 'cec10a', 'f69ce5', '3f3993', '6e074a', '357135', '0a35d3', '6eb37e', 'd80f6d', 'b1a399', '09e8e8', '7a0ab0', '491d6b', 'b5ee9e', 'd95dc1', '3868cc', 'e5065b', '9ff623', '2e85c2', '2aa2dc', 'aec8d4', 'f69eb4', '5ed0d8', '928933', '934eff', 'a92b35', 'ba79e8'], 'qpu_access_time': 8620, 'charge_time': 4981050, 'run_time': 4981050, 'problem_id': 'eb2110eb-df3d-4d44-b2d8-702fd08cb628'}, 'INTEGER')"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0bc0859b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "name": "Kopia notatnika [WSP] Wfcommons.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}