expose trjcat.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# How does `trjcat` reacts in different scenarios?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-27T06:13:07.419139Z",
     "start_time": "2018-05-27T06:13:07.041727Z"
    }
   },
   "outputs": [],
   "source": [
    "import subprocess\n",
    "import numpy as np\n",
    "import MDAnalysis as mda\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-27T06:13:07.428620Z",
     "start_time": "2018-05-27T06:13:07.420471Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0.18.1-dev'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mda.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-27T06:13:07.485535Z",
     "start_time": "2018-05-27T06:13:07.430012Z"
    }
   },
   "outputs": [],
   "source": [
    "def build_trajectories(*sequences):\n",
    "    \"\"\"\n",
    "    Expose trjcat behavior for a given scenario.\n",
    "    \n",
    "    A scenario is given as a series of time sequences. The result is\n",
    "    returned as a list of time and origin of the frame. Each element of that\n",
    "    result list correspond to a frame of the conatenated trajectory, The\n",
    "    first element of each tuple is the time it corresponds to, the second\n",
    "    element is the index of the input the frame comes from.\n",
    "    \"\"\"\n",
    "    template = 'trjcat_test{}.xtc'\n",
    "    final_name = 'trjcat_test_cat.xtc'\n",
    "    \n",
    "    # Use an empty universe to have a topology\n",
    "    utop = mda.Universe.empty(1, trajectory=True)\n",
    "    \n",
    "    # Create synthetic trajectories. The times come from the user input,\n",
    "    # the coordinates indicate the index of the input.\n",
    "    for index, subseq in enumerate(sequences):\n",
    "        coords = np.zeros((len(subseq), 1, 3), dtype=np.float32) + index\n",
    "        u = mda.Universe(utop._topology, coords)\n",
    "        out_traj = mda.coordinates.XTC.XTCWriter(template.format(index),\n",
    "                                                 n_atoms=len(u.atoms))\n",
    "        with out_traj:\n",
    "            for ts, time in zip(u.trajectory, subseq):\n",
    "                # The time step needs a box to avoid a warning\n",
    "                ts.dimensions = [10, 10, 10, 90, 90, 90]\n",
    "                # The time is set from the user input\n",
    "                ts.time = time\n",
    "                out_traj.write(ts)\n",
    "    \n",
    "    subprocess.call(['gmx', 'trjcat', '-o', final_name, '-f']\n",
    "                    + [template.format(index)\n",
    "                       for index, _ in enumerate(sequences)])\n",
    "    u = mda.Universe(utop._topology, final_name)\n",
    "    final_seq = [(ts.time, int(ts.positions[0, 0])) for ts in u.trajectory]\n",
    "    \n",
    "    # Clean the files\n",
    "    del u  # Maybe we can try to close the file before deleting it?\n",
    "    for index, _ in enumerate(sequences):\n",
    "        os.remove(template.format(index))\n",
    "    os.remove(final_name)\n",
    "    # Clean the offset to avoid a warning\n",
    "    os.remove('.{}_offsets.npz'.format(final_name))\n",
    "    \n",
    "    return final_seq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-27T06:13:07.522604Z",
     "start_time": "2018-05-27T06:13:07.487276Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.0, 0), (1.0, 0), (2.0, 0), (3.0, 0), (5.0, 1), (6.0, 1), (7.0, 1)]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "build_trajectories([0, 1, 2, 3], [5, 6, 7])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-27T06:13:07.577814Z",
     "start_time": "2018-05-27T06:13:07.527599Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.0, 0),\n",
       " (1.0, 0),\n",
       " (2.0, 1),\n",
       " (3.0, 1),\n",
       " (4.0, 2),\n",
       " (5.0, 2),\n",
       " (6.0, 2),\n",
       " (7.0, 2)]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "build_trajectories([0, 1, 2, 3], [2, 3, 4, 5], [4, 5, 6, 7])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-27T06:13:07.631861Z",
     "start_time": "2018-05-27T06:13:07.580580Z"
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.0, 1), (1.0, 1), (2.0, 1), (4.0, 1)]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "build_trajectories([0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-27T06:13:07.739296Z",
     "start_time": "2018-05-27T06:13:07.637023Z"
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   },
   "outputs": [
    {
     "data": {
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       "[(0.0, 1),\n",
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       " (3.0, 1),\n",
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       " (6.0, 1),\n",
       " (7.0, 1),\n",
       " (8.0, 1),\n",
       " (9.0, 1)]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "build_trajectories([0, 1, 2, 4], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-27T06:13:07.799234Z",
     "start_time": "2018-05-27T06:13:07.745348Z"
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.0, 0),\n",
       " (1.0, 0),\n",
       " (2.0, 3),\n",
       " (3.0, 2),\n",
       " (5.0, 4),\n",
       " (6.0, 4),\n",
       " (7.0, 4),\n",
       " (8.0, 4),\n",
       " (9.0, 4)]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "build_trajectories([0, 1, 2, 3], [2], [3], [2, 3, 4, 5, 6], [5, 6, 7, 8, 9])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-27T06:13:07.863896Z",
     "start_time": "2018-05-27T06:13:07.803406Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.0, 0),\n",
       " (1.0, 0),\n",
       " (2.0, 3),\n",
       " (3.0, 1),\n",
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       " (6.0, 4),\n",
       " (7.0, 4),\n",
       " (8.0, 4),\n",
       " (9.0, 4)]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "build_trajectories([0, 1, 2, 3], [3], [2], [2, 3, 4, 5, 6], [5, 6, 7, 8, 9])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-27T06:13:07.912673Z",
     "start_time": "2018-05-27T06:13:07.867085Z"
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
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       " (1.0, 0),\n",
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       " (7.0, 2),\n",
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     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "build_trajectories([0, 1, 2, 3], [2, 3, 4, 5, 6], [5, 6, 7, 8, 9])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-27T06:13:07.969307Z",
     "start_time": "2018-05-27T06:13:07.915906Z"
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.0, 2),\n",
       " (1.0, 2),\n",
       " (2.0, 1),\n",
       " (3.0, 1),\n",
       " (4.0, 1),\n",
       " (5.0, 0),\n",
       " (6.0, 0),\n",
       " (7.0, 0),\n",
       " (8.0, 0),\n",
       " (9.0, 0)]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "build_trajectories([5, 6, 7, 8, 9], [2, 3, 4, 5, 6], [0, 1, 2, 3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-27T06:13:08.030434Z",
     "start_time": "2018-05-27T06:13:07.975922Z"
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.0, 0),\n",
       " (1.0, 0),\n",
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       " (3.0, 0),\n",
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       " (6.0, 1),\n",
       " (7.0, 1),\n",
       " (8.0, 1),\n",
       " (9.0, 1)]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "build_trajectories([0, 1, 2, 3], [5, 6, 7, 8, 9])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-27T06:13:08.064889Z",
     "start_time": "2018-05-27T06:13:08.033557Z"
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.0, 0),\n",
       " (1.0, 0),\n",
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       " (3.0, 0),\n",
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       " (5.0, 2),\n",
       " (6.0, 2),\n",
       " (7.0, 2),\n",
       " (8.0, 2),\n",
       " (9.0, 2)]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "build_trajectories([0, 1, 2, 3], [4], [5, 6, 7, 8, 9])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-27T06:13:08.132904Z",
     "start_time": "2018-05-27T06:13:08.067214Z"
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.0, 8), (1.0, 8), (2.0, 8), (3.0, 8)]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "build_trajectories([0], [0, 1, 2, 3], [0], [0], [0, 1, 2, 3], [0], [0], [0], [0, 1, 2, 3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-27T06:13:08.183070Z",
     "start_time": "2018-05-27T06:13:08.135039Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.0, 0), (1.0, 1)]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "build_trajectories([0, 1, 2, 3], [1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-27T06:13:08.219324Z",
     "start_time": "2018-05-27T06:13:08.185573Z"
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.0, 0), (1.0, 0), (2.0, 0), (3.0, 1)]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "build_trajectories([0, 1, 2, 3], [3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-27T06:13:08.281314Z",
     "start_time": "2018-05-27T06:13:08.232134Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.0, 0),\n",
       " (1.0, 0),\n",
       " (2.0, 1),\n",
       " (3.0, 1),\n",
       " (4.0, 3),\n",
       " (5.0, 2),\n",
       " (6.0, 2),\n",
       " (7.0, 2),\n",
       " (8.0, 4)]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "build_trajectories([0, 1, 2, 3], [2, 3, 4, 5, 6], [5, 6, 7, 8, 9], [4], [8])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-27T06:13:08.336350Z",
     "start_time": "2018-05-27T06:13:08.284910Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.0, 4), (1.0, 4), (2.0, 4), (3.0, 4)]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "build_trajectories(*([[0, 1, 2, 3]] * 5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-27T06:13:08.390264Z",
     "start_time": "2018-05-27T06:13:08.338545Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.0, 1), (1.0, 1), (2.0, 1), (3.0, 1), (5.0, 2), (6.0, 2), (7.0, 2)]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "build_trajectories([0, 1, 2, 3, 4], [0, 1, 2, 3], [5, 6, 7])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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