caiman_make-ms_ts_pkl.ipynb

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      "/home/qiushou/.conda/envs/caiman/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:526: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n",
      "/home/qiushou/.conda/envs/caiman/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:527: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n",
      "/home/qiushou/.conda/envs/caiman/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:528: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n",
      "/home/qiushou/.conda/envs/caiman/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:529: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n",
      "/home/qiushou/.conda/envs/caiman/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:530: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n",
      "/home/qiushou/.conda/envs/caiman/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:535: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n"
     ]
    },
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       "      cell.notebook.kernel.execute(cmd, {\n",
       "        iopub: {\n",
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       "      this.keyboard_manager.register_events(toinsert);\n",
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       "      render(props, toinsert[toinsert.length - 1]);\n",
       "      element.append(toinsert);\n",
       "      return toinsert\n",
       "    }\n",
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       "    events.on('delete.Cell', handleClearOutput);\n",
       "\n",
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       "\n",
       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
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       "  }\n",
       "\n",
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       "     \"<div style='background-color: #fdd'>\\n\"+\n",
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       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
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       "    }\n",
       "  }\n",
       "\n",
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       "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
       "        if (callback != null)\n",
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       "    } finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(css_urls, js_urls, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
       "\n",
       "    function on_load() {\n",
       "      root._bokeh_is_loading--;\n",
       "      if (root._bokeh_is_loading === 0) {\n",
       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
       "        run_callbacks()\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function on_error() {\n",
       "      console.error(\"failed to load \" + url);\n",
       "    }\n",
       "\n",
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       "      element.rel = \"stylesheet\";\n",
       "      element.type = \"text/css\";\n",
       "      element.href = url;\n",
       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
       "      document.body.appendChild(element);\n",
       "    }\n",
       "\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
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       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "  };var element = document.getElementById(\"1001\");\n",
       "  if (element == null) {\n",
       "    console.error(\"Bokeh: ERROR: autoload.js configured with elementid '1001' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  function inject_raw_css(css) {\n",
       "    const element = document.createElement(\"style\");\n",
       "    element.appendChild(document.createTextNode(css));\n",
       "    document.body.appendChild(element);\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.3.4.min.js\"];\n",
       "  var css_urls = [];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "    },\n",
       "    function(Bokeh) {} // ensure no trailing comma for IE\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i].call(root, root.Bokeh);\n",
       "      }if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
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       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(css_urls, js_urls, function() {\n",
       "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(\"1001\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };var element = document.getElementById(\"1001\");\n  if (element == null) {\n    console.error(\"Bokeh: ERROR: autoload.js configured with elementid '1001' but no matching script tag was found. \")\n    return false;\n  }\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.3.4.min.js\"];\n  var css_urls = [];\n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    \n    function(Bokeh) {\n      \n    },\n    function(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    \n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "try:                 \n",
    "    get_ipython().magic(u'load_ext autoreload')    \n",
    "    get_ipython().magic(u'autoreload 2')           \n",
    "    get_ipython().magic(u'matplotlib qt')          \n",
    "except:              \n",
    "    pass             \n",
    "import logging       \n",
    "import matplotlib.pyplot as plt                    \n",
    "import numpy as np   \n",
    "                     \n",
    "logging.basicConfig(format= \n",
    "                          \"%(relativeCreated)12d [%(filename)s:%(funcName)20s():%(lineno)s] [%(process)d] %(message)s\",\n",
    "                    # filename=\"/tmp/caiman.log\",  \n",
    "                    level=logging.DEBUG)           \n",
    "                     \n",
    "import caiman as cm  \n",
    "from caiman.source_extraction import cnmf                 \n",
    "from caiman.utils.visualization import inspect_correlation_pnr, nb_inspect_correlation_pnr\n",
    "from caiman.motion_correction import MotionCorrect        \n",
    "from caiman.source_extraction.cnmf import params as params\n",
    "from caiman.utils.visualization import plot_contours, nb_view_patches, nb_plot_contour\n",
    "import cv2           \n",
    "                     \n",
    "try:                 \n",
    "    cv2.setNumThreads(0)\n",
    "except:              \n",
    "    pass             \n",
    "import bokeh.plotting as bpl\n",
    "import holoviews as hv\n",
    "bpl.output_notebook()                                                                                                            \n",
    "                     \n",
    "import glob          \n",
    "import re            \n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['/run/user/1000/gvfs/smb-share:server=10.10.46.135,share=data_archive/qiushou/miniscope/20191110/191172/H15_M27_S28/timestamp.dat', '/run/user/1000/gvfs/smb-share:server=10.10.46.135,share=data_archive/qiushou/miniscope/20191110/191172/H15_M41_S35/timestamp.dat']\n"
     ]
    }
   ],
   "source": [
    "animal_id = '191172' \n",
    "resultDir = '/home/qiushou/Documents/QS_data/miniscope/miniscope_result'\n",
    "tsFileList = glob.glob(os.path.join('/run/user/1000/gvfs/smb-share:server=10.10.46.135,share=data_archive/qiushou/miniscope/20191110'\n",
    "                                    ,animal_id     \n",
    "                                    ,\"H*/timestamp.dat\"))\n",
    "def sort_key(s):     \n",
    "    if s:            \n",
    "        try:         \n",
    "            date = re.findall('\\d{8}', s)[0]\n",
    "        except:      \n",
    "            date = -1            \n",
    "        try:         \n",
    "            H = re.findall('H(\\d+)',s)[0]\n",
    "        except:      \n",
    "            H = -1            \n",
    "        try:         \n",
    "            M = re.findall('M(\\d+)',s)[0]\n",
    "        except:      \n",
    "            M = -1            \n",
    "        try:         \n",
    "            S = re.findall('S(\\d+)',s)[0]\n",
    "        except:      \n",
    "            S = -1            \n",
    "        try:         \n",
    "            ms = re.findall('msCam(\\d+)',s)[0]\n",
    "        except:      \n",
    "            ms = -1  \n",
    "        return [int(date),int(H),int(M),int(S),int(ms)]\n",
    "tsFileList.sort(key=sort_key)\n",
    "print(tsFileList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/qiushou/Documents/QS_data/miniscope/miniscope_result/Results_191172/20191111_093330_20191110/ms_ts.pkl\n"
     ]
    }
   ],
   "source": [
    "import cv2          \n",
    "import pickle       \n",
    "                    \n",
    "newpath_parent=os.path.join(resultDir,'Results'+'_'+animal_id)\n",
    "newpath = os.path.join(newpath_parent,\"20191111_093330_20191110\")\n",
    "\n",
    "#%% concatenate timestamps of tsFileList\n",
    "ms_ts_name = os.path.join(newpath,'ms_ts.pkl')\n",
    "print(ms_ts_name)  \n",
    "temporal_downsampling=3                   \n",
    "import pandas as pd\n",
    "import pickle   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "concatenated timestamp of miniscope_video is located at /home/qiushou/Documents/QS_data/miniscope/miniscope_result/Results_191172/20191111_093330_20191110/ms_ts.pkl\n"
     ]
    }
   ],
   "source": [
    "if not os.path.exists(ms_ts_name):\n",
    "    ts_session=[]  \n",
    "    for tsFile in tsFileList:\n",
    "        datatemp=pd.read_csv(tsFile,sep = \"\\t\", header = 0)\n",
    "        ts_session.append(datatemp['sysClock'].values) \n",
    "#         print(len((datatemp['sysClock'].values)))\n",
    "    ttemp=np.hstack(ts_session)[::temporal_downsampling]\n",
    "    # remporally downsample for each video\n",
    "    # [i[::3] for i in ts_session][0]\n",
    "    session_indend=(np.where(np.diff(ttemp)<0)[0]).tolist()    \n",
    "    session_indend.append(-1)\n",
    "    ts_session_ds=[]\n",
    "    i0=0            \n",
    "    session_indstart=[]\n",
    "    for i in range(len(ts_session)):\n",
    "#         print(i)\n",
    "        session_indstart.append(i0)\n",
    "        ts_session_ds.append(ttemp[i0:session_indend[i]])\n",
    "        i0=session_indend[i]+1\n",
    "    ms_ts=np.array(ts_session_ds)    \n",
    "    with open(ms_ts_name,'wb') as output:\n",
    "        pickle.dump(ms_ts,output,pickle.HIGHEST_PROTOCOL)\n",
    "else:               \n",
    "    with open(ms_ts_name, \"rb\") as f:\n",
    "        ms_ts= pickle.load(f)\n",
    "print(f'concatenated timestamp of miniscope_video is located at {ms_ts_name}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17039\n"
     ]
    }
   ],
   "source": [
    "print(len(ms_ts[0])+len(ms_ts[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "concatenated timestamp of miniscope_video is located at /home/qiushou/Documents/QS_data/miniscope/miniscope_result/Results_191172/20191111_093330_20191110/ms_ts.pkl\n"
     ]
    }
   ],
   "source": [
    "if not os.path.exists(ms_ts_name):\n",
    "    ts_session=[]\n",
    "    for tsFile in tsFileList:\n",
    "        datatemp=pd.read_csv(tsFile,sep = \"\\t\", header = 0)\n",
    "        ts_session.append(datatemp['sysClock'].values)    \n",
    "    ttemp=np.hstack(ts_session)[::temporal_downsampling]\n",
    "    # remporally downsample for each video\n",
    "    # [i[::3] for i in ts_session][0]\n",
    "    session_indend=(np.where(np.diff(ttemp)<0)[0]).tolist()\n",
    "#    session_indend.append(-1)\n",
    "    ts_session_ds=[]\n",
    "    i0=0\n",
    "    session_indstart=[]\n",
    "    if len(session_indend)>0:\n",
    "        for i in range(len(session_indend)):\n",
    "            session_indstart.append(i0)\n",
    "            ts_session_ds.append(ttemp[i0:(session_indend[i]+1)])\n",
    "            i0=session_indend[i]+1\n",
    "        ts_session_ds.append(ttemp[(session_indend[-1]+1):])\n",
    "    else:\n",
    "        ts_session_ds.append(ttemp[i0:])\n",
    "    \n",
    "    \n",
    "    ms_ts=np.array(ts_session_ds)    \n",
    "    with open(ms_ts_name,'wb') as output:\n",
    "        pickle.dump(ms_ts,output,pickle.HIGHEST_PROTOCOL)\n",
    "else:\n",
    "    with open(ms_ts_name, \"rb\") as f:\n",
    "        ms_ts= pickle.load(f)\n",
    "print(f'concatenated timestamp of miniscope_video is located at {ms_ts_name}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "17041"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum([len(i) for i in ms_ts]) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "17041"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import cv2\n",
    "cap = cv2.VideoCapture(os.path.join(newpath_parent,\"20191111_093330_20191110/msCam_concat.avi\"))\n",
    "int(cap.get(7))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum([len(i) for i in ms_ts]) == int(cap.get(7))"
   ]
  }
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