Generate_Input_for_Averaging.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "47bc98a3",
   "metadata": {},
   "outputs": [],
   "source": [
    "from PyQt5.QtWidgets import QFileDialog, QApplication\n",
    "import os\n",
    "import os.path as ospath\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from picasso.picasso import io\n",
    "\n",
    "\n",
    "def gui_fname(dir=None):\n",
    "    \"\"\"\n",
    "    Select a file via a dialog and return the file name.\n",
    "    \"\"\"\n",
    "    if dir is None: \n",
    "        dir =\"./\"\n",
    "\n",
    "    app = QApplication([dir])\n",
    "    fname = QFileDialog.getExistingDirectory(None, \"Select a folder...\", \n",
    "            dir)\n",
    "    if isinstance(fname, tuple):\n",
    "        return fname[0]\n",
    "    else: \n",
    "        return str(fname)\n",
    "    \n",
    "def load_ring_data_df(dirname, filename):\n",
    "    file = ospath.join(dirname, filename)\n",
    "\n",
    "    try: \n",
    "        df = pd.read_pickle(file)\n",
    "    except FileNotFoundError:\n",
    "        print(\"No results of previously analyzed datasets were detected.\")\n",
    "        return None\n",
    "    else: \n",
    "        print(\"Results of previously analyzed datasets were detected.\")\n",
    "        return df\n",
    "\n",
    "def load_files(dirname):\n",
    "    \n",
    "    os.chdir(dirname)\n",
    "    files = glob.glob(\"*.hdf5\")\n",
    "    \n",
    "    if files:\n",
    "        print(\"{} HDF5 files found.\".format(len(files)))\n",
    "    else:\n",
    "        print(\"No HDF5 files found at: {}\".format(dirname))\n",
    "            \n",
    "    return files\n",
    "    \n",
    "def load_data(path):\n",
    "\n",
    "    try:\n",
    "        locs, info = io.load_locs(path)\n",
    "    except io.NoMetadataFileError:\n",
    "        return None, None, None\n",
    "    \n",
    "    try:\n",
    "        pixelsize = info[1][\"Pixelsize\"]\n",
    "    except:  \n",
    "        print(\"No pixelsize found in yaml file. Default 130 nm used.\")\n",
    "\n",
    "        \n",
    "    return locs, info, pixelsize\n",
    "\n",
    "def load_rings_by_radius(df_rings_data, path_rings, bin):\n",
    "    \n",
    "    ring_locs = []\n",
    "    counter = 0\n",
    "    for filename in df_rings_data['ring_filename']:\n",
    "        locs_i, info_i, pixelsize = load_data(os.path.join(path_rings, filename))\n",
    "        df_locs_i = pd.DataFrame.from_records(locs_i)\n",
    "        df_locs_i['pick'] = df_locs_i['group']\n",
    "        df_locs_i['group'] = np.full(len(df_locs_i), counter)\n",
    "        counter +=1\n",
    "        ring_locs.append(df_locs_i)\n",
    "    \n",
    "    df_ring_locs = pd.concat(ring_locs)\n",
    "    \n",
    "    info = info_i + [{'Ring radius interval': bin, 'Merged ring files': list(df_rings_data['ring_filename'])}]\n",
    "    \n",
    "    return df_ring_locs, info\n",
    "    \n",
    "    \n",
    "    \n",
    "    \n",
    "def unfold_groups_square(locs, info, n_square = 100, spacing = 2):\n",
    "    \"\"\"\n",
    "    Shifts grouped locs onto a rectangular grid of chosen length.\n",
    "    Useful for locs that were processed with Picasso: Average.\n",
    "    \"\"\"\n",
    "\n",
    "\n",
    "    if hasattr(locs, \"group\"):\n",
    "\n",
    "        locs.x += (\n",
    "            np.mod(locs.group, n_square) \n",
    "            * spacing\n",
    "        )\n",
    "        locs.y += (\n",
    "            np.floor(locs.group / n_square) \n",
    "            * spacing\n",
    "        )\n",
    "\n",
    "        mean_x = np.mean(locs.x)\n",
    "        mean_y = np.mean(locs.y)\n",
    "\n",
    "        locs.x -= mean_x\n",
    "        locs.y -= mean_y\n",
    "\n",
    "        offset_x = np.absolute(np.min(locs.x))\n",
    "        offset_y = np.absolute(np.min(locs.y))\n",
    "\n",
    "        locs.x += offset_x + spacing\n",
    "        locs.y += offset_y + spacing\n",
    "\n",
    "\n",
    "    # Update width information\n",
    "    info[0][\"Height\"] = int(np.ceil(np.max(locs.y))+spacing)\n",
    "    info[0][\"Width\"] = int(np.ceil(np.max(locs.x))+spacing)\n",
    "    \n",
    "    return locs, info\n",
    "\n",
    "\n",
    "def save_rings_locs(locs, info, path, cell_type, bin, filename = ''):\n",
    "    \n",
    "\n",
    "    ending = \".hdf5\"    \n",
    "    if filename != '':\n",
    "        ending = filename + ending\n",
    "    \n",
    "    locs_name = \"rings_{}_bin_{}_{}{}\".format(cell_type, bin[0], bin[1], ending)\n",
    "    locs_path_name = os.path.join(path, locs_name)\n",
    "    \n",
    "    if not os.path.isdir(path):\n",
    "        os.makedirs(path)\n",
    "    \n",
    "    io.save_locs(locs_path_name, locs, info)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cfdcc8a3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results of previously analyzed datasets were detected.\n",
      "Index(['fov_id', 'cell_type', 'filename', 'group', 'residual', 'radius',\n",
      "       'angle_between_ring_and_coverslip', 'Sigma', 'n_events', 'mean_bright',\n",
      "       'mean_dark', 'fit_bright', 'fit_dark', 'filter_passed'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "#path = gui_fname()\n",
    "path = r'W:\\users\\reinhardt\\z.software\\Git\\spor-PAINT\\dev_sr\\spor-paint\\FtsZ\\FtsZ_picks_all'\n",
    "\n",
    "orientation = 'xy' # 'xy' or 'yz'\n",
    "#filenames = load_files(path)\n",
    "\n",
    "df_ring_data = load_ring_data_df(path, \"ring_data_filter.pkl\")\n",
    "\n",
    "print(df_ring_data.keys())\n",
    "\n",
    "radius_step = 15 # nm\n",
    "sub_step = 5\n",
    "\n",
    "\n",
    "radius_step = 100 # nm\n",
    "sub_step = 25"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "dfa1a7c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\nradius groups: resolution\\nrolling average\\n\\nNeNAs:\\n5.9\\n5.82\\n4.37\\n3.97\\n4.16\\n9.1\\n'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "radius groups: resolution\n",
    "rolling average\n",
    "\n",
    "NeNAs:\n",
    "5.9\n",
    "5.82\n",
    "4.37\n",
    "3.97\n",
    "4.16\n",
    "9.1\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a78cc431",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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[18600, 18700], [18625, 18725], [18650, 18750], [18675, 18775], [18700, 18800], [18725, 18825], [18750, 18850], [18775, 18875], [18800, 18900], [18825, 18925], [18850, 18950], [18875, 18975], [18900, 19000], [18925, 19025], [18950, 19050], [18975, 19075], [19000, 19100], [19025, 19125], [19050, 19150], [19075, 19175], [19100, 19200], [19125, 19225], [19150, 19250], [19175, 19275], [19200, 19300], [19225, 19325], [19250, 19350], [19275, 19375], [19300, 19400], [19325, 19425], [19350, 19450], [19375, 19475], [19400, 19500], [19425, 19525], [19450, 19550], [19475, 19575], [19500, 19600], [19525, 19625], [19550, 19650], [19575, 19675], [19600, 19700], [19625, 19725], [19650, 19750], [19675, 19775], [19700, 19800], [19725, 19825], [19750, 19850], [19775, 19875], [19800, 19900], [19825, 19925], [19850, 19950], [19875, 19975], [19900, 20000], [19925, 20025], [19950, 20050], [19975, 20075], [20000, 20100], [20025, 20125], [20050, 20150], [20075, 20175], [20100, 20200], [20125, 20225], [20150, 20250], [20175, 20275], [20200, 20300], [20225, 20325], [20250, 20350], [20275, 20375], [20300, 20400], [20325, 20425], [20350, 20450], [20375, 20475], [20400, 20500], [20425, 20525], [20450, 20550], [20475, 20575], [20500, 20600], [20525, 20625], [20550, 20650], [20575, 20675], [20600, 20700], [20625, 20725], [20650, 20750], [20675, 20775], [20700, 20800], [20725, 20825], [20750, 20850], [20775, 20875], [20800, 20900], [20825, 20925], [20850, 20950], [20875, 20975], [20900, 21000], [20925, 21025], [20950, 21050], [20975, 21075], [21000, 21100], [21025, 21125], [21050, 21150], [21075, 21175], [21100, 21200], [21125, 21225], [21150, 21250], [21175, 21275], [21200, 21300], [21225, 21325], [21250, 21350], [21275, 21375], [21300, 21400], [21325, 21425], [21350, 21450], [21375, 21475], [21400, 21500], [21425, 21525], [21450, 21550], [21475, 21575], [21500, 21600], [21525, 21625], [21550, 21650], [21575, 21675], [21600, 21700], [21625, 21725], [21650, 21750], [21675, 21775], [21700, 21800], [21725, 21825], [21750, 21850], [21775, 21875], [21800, 21900], [21825, 21925], [21850, 21950], [21875, 21975], [21900, 22000], [21925, 22025], [21950, 22050], [21975, 22075], [22000, 22100], [22025, 22125], [22050, 22150], [22075, 22175], [22100, 22200], [22125, 22225], [22150, 22250], [22175, 22275], [22200, 22300], [22225, 22325], [22250, 22350], [22275, 22375], [22300, 22400], [22325, 22425], [22350, 22450], [22375, 22475], [22400, 22500], [22425, 22525], [22450, 22550], [22475, 22575], [22500, 22600], [22525, 22625], [22550, 22650], [22575, 22675], [22600, 22700], [22625, 22725], [22650, 22750], [22675, 22775], [22700, 22800], [22725, 22825], [22750, 22850], [22775, 22875], [22800, 22900], [22825, 22925], [22850, 22950], [22875, 22975], [22900, 23000], [22925, 23025], [22950, 23050], [22975, 23075], [23000, 23100], [23025, 23125], [23050, 23150], [23075, 23175], [23100, 23200], [23125, 23225], [23150, 23250], [23175, 23275], [23200, 23300], [23225, 23325], [23250, 23350], [23275, 23375], [23300, 23400], [23325, 23425], [23350, 23450], [23375, 23475], [23400, 23500], [23425, 23525], [23450, 23550], [23475, 23575], [23500, 23600], [23525, 23625], [23550, 23650], [23575, 23675], [23600, 23700], [23625, 23725], [23650, 23750], [23675, 23775], [23700, 23800], [23725, 23825], [23750, 23850], [23775, 23875], [23800, 23900], [23825, 23925], [23850, 23950], [23875, 23975], [23900, 24000], [23925, 24025], [23950, 24050], [23975, 24075], [24000, 24100], [24025, 24125], [24050, 24150], [24075, 24175], [24100, 24200], [24125, 24225], [24150, 24250], [24175, 24275], [24200, 24300], [24225, 24325], [24250, 24350], [24275, 24375], [24300, 24400], [24325, 24425], [24350, 24450], [24375, 24475], [24400, 24500], [24425, 24525], [24450, 24550], [24475, 24575], [24500, 24600], [24525, 24625], [24550, 24650], [24575, 24675], [24600, 24700], [24625, 24725], [24650, 24750], [24675, 24775], [24700, 24800], [24725, 24825], [24750, 24850], [24775, 24875], [24800, 24900], [24825, 24925], [24850, 24950], [24875, 24975], [24900, 25000], [24925, 25025], [24950, 25050], [24975, 25075], [25000, 25100], [25025, 25125], [25050, 25150], [25075, 25175], [25100, 25200], [25125, 25225], [25150, 25250], [25175, 25275], [25200, 25300], [25225, 25325], [25250, 25350], [25275, 25375], [25300, 25400], [25325, 25425], [25350, 25450], [25375, 25475], [25400, 25500], [25425, 25525], [25450, 25550], [25475, 25575], [25500, 25600], [25525, 25625], [25550, 25650], [25575, 25675], [25600, 25700], [25625, 25725], [25650, 25750], [25675, 25775], [25700, 25800], [25725, 25825], [25750, 25850], [25775, 25875], [25800, 25900], [25825, 25925], [25850, 25950], [25875, 25975], [25900, 26000], [25925, 26025], [25950, 26050], [25975, 26075], [26000, 26100], [26025, 26125], [26050, 26150], [26075, 26175], [26100, 26200], [26125, 26225], [26150, 26250], [26175, 26275], [26200, 26300], [26225, 26325], [26250, 26350], [26275, 26375], [26300, 26400], [26325, 26425], [26350, 26450], [26375, 26475], [26400, 26500], [26425, 26525], [26450, 26550], [26475, 26575], [26500, 26600], [26525, 26625], [26550, 26650], [26575, 26675], [26600, 26700], [26625, 26725], [26650, 26750], [26675, 26775], [26700, 26800], [26725, 26825], [26750, 26850], [26775, 26875], [26800, 26900], [26825, 26925], [26850, 26950], [26875, 26975], [26900, 27000], [26925, 27025], [26950, 27050], [26975, 27075], [27000, 27100], [27025, 27125], [27050, 27150], [27075, 27175], [27100, 27200], [27125, 27225], [27150, 27250], [27175, 27275], [27200, 27300], [27225, 27325], [27250, 27350], [27275, 27375], [27300, 27400], [27325, 27425], [27350, 27450], [27375, 27475], [27400, 27500], [27425, 27525], [27450, 27550], [27475, 27575], [27500, 27600], [27525, 27625], [27550, 27650], [27575, 27675], [27600, 27700], [27625, 27725], [27650, 27750], [27675, 27775], [27700, 27800], [27725, 27825], [27750, 27850], [27775, 27875], [27800, 27900], [27825, 27925], [27850, 27950], [27875, 27975], [27900, 28000], [27925, 28025], [27950, 28050], [27975, 28075], [28000, 28100], [28025, 28125], [28050, 28150], [28075, 28175], [28100, 28200], [28125, 28225], [28150, 28250], [28175, 28275], [28200, 28300], [28225, 28325], [28250, 28350], [28275, 28375], [28300, 28400], [28325, 28425], [28350, 28450], [28375, 28475], [28400, 28500], [28425, 28525], [28450, 28550], [28475, 28575], [28500, 28600], [28525, 28625], [28550, 28650], [28575, 28675], [28600, 28700], [28625, 28725], [28650, 28750], [28675, 28775], [28700, 28800], [28725, 28825], [28750, 28850], [28775, 28875], [28800, 28900], [28825, 28925], [28850, 28950], [28875, 28975], [28900, 29000], [28925, 29025], [28950, 29050], [28975, 29075], [29000, 29100], [29025, 29125], [29050, 29150], [29075, 29175], [29100, 29200], [29125, 29225], [29150, 29250], [29175, 29275], [29200, 29300], [29225, 29325], [29250, 29350], [29275, 29375], [29300, 29400], [29325, 29425], [29350, 29450], [29375, 29475], [29400, 29500], [29425, 29525], [29450, 29550], [29475, 29575], [29500, 29600], [29525, 29625], [29550, 29650], [29575, 29675], [29600, 29700], [29625, 29725], [29650, 29750], [29675, 29775], [29700, 29800], [29725, 29825], [29750, 29850], [29775, 29875], [29800, 29900], [29825, 29925], [29850, 29950], [29875, 29975], [29900, 30000], [29925, 30025], [29950, 30050], [29975, 30075], [30000, 30100], [30025, 30125], [30050, 30150], [30075, 30175], [30100, 30200], [30125, 30225], [30150, 30250], [30175, 30275], [30200, 30300], [30225, 30325], [30250, 30350], [30275, 30375], [30300, 30400], [30325, 30425], [30350, 30450], [30375, 30475], [30400, 30500], [30425, 30525], [30450, 30550], [30475, 30575], [30500, 30600], [30525, 30625], [30550, 30650], [30575, 30675], [30600, 30700], [30625, 30725], [30650, 30750], [30675, 30775], [30700, 30800], [30725, 30825], [30750, 30850], [30775, 30875], [30800, 30900], [30825, 30925], [30850, 30950], [30875, 30975], [30900, 31000], [30925, 31025], [30950, 31050], [30975, 31075], [31000, 31100], [31025, 31125], [31050, 31150], [31075, 31175], [31100, 31200], [31125, 31225], [31150, 31250], [31175, 31275], [31200, 31300], [31225, 31325], [31250, 31350], [31275, 31375], [31300, 31400], [31325, 31425], [31350, 31450], [31375, 31475], [31400, 31500], [31425, 31525], [31450, 31550], [31475, 31575], [31500, 31600], [31525, 31625], [31550, 31650], [31575, 31675], [31600, 31700], [31625, 31725], [31650, 31750], [31675, 31775], [31700, 31800], [31725, 31825], [31750, 31850], [31775, 31875], [31800, 31900], [31825, 31925], [31850, 31950], [31875, 31975], [31900, 32000], [31925, 32025], [31950, 32050], [31975, 32075], [32000, 32100], [32025, 32125], [32050, 32150], [32075, 32175], [32100, 32200], [32125, 32225], [32150, 32250], [32175, 32275], [32200, 32300], [32225, 32325], [32250, 32350], [32275, 32375], [32300, 32400], [32325, 32425], [32350, 32450], [32375, 32475], [32400, 32500], [32425, 32525], [32450, 32550], [32475, 32575], [32500, 32600], [32525, 32625], [32550, 32650], [32575, 32675], [32600, 32700], [32625, 32725], [32650, 32750], [32675, 32775], [32700, 32800], [32725, 32825], [32750, 32850], [32775, 32875], [32800, 32900], [32825, 32925], [32850, 32950], [32875, 32975], [32900, 33000], [32925, 33025], [32950, 33050], [32975, 33075], [33000, 33100], [33025, 33125], [33050, 33150], [33075, 33175], [33100, 33200], [33125, 33225], [33150, 33250], [33175, 33275], [33200, 33300], [33225, 33325], [33250, 33350], [33275, 33375], [33300, 33400], [33325, 33425], [33350, 33450], [33375, 33475], [33400, 33500], [33425, 33525], [33450, 33550], [33475, 33575], [33500, 33600], [33525, 33625], [33550, 33650], [33575, 33675], [33600, 33700], [33625, 33725], [33650, 33750], [33675, 33775], [33700, 33800], [33725, 33825], [33750, 33850], [33775, 33875], [33800, 33900], [33825, 33925], [33850, 33950], [33875, 33975], [33900, 34000], [33925, 34025], [33950, 34050], [33975, 34075], [34000, 34100], [34025, 34125], [34050, 34150], [34075, 34175], [34100, 34200], [34125, 34225], [34150, 34250], [34175, 34275], [34200, 34300], [34225, 34325], [34250, 34350], [34275, 34375], [34300, 34400], [34325, 34425], [34350, 34450], [34375, 34475], [34400, 34500], [34425, 34525], [34450, 34550], [34475, 34575], [34500, 34600], [34525, 34625], [34550, 34650], [34575, 34675], [34600, 34700], [34625, 34725], [34650, 34750], [34675, 34775], [34700, 34800], [34725, 34825], [34750, 34850], [34775, 34875], [34800, 34900], [34825, 34925], [34850, 34950], [34875, 34975], [34900, 35000], [34925, 35025], [34950, 35050], [34975, 35075], [35000, 35100], [35025, 35125], [35050, 35150], [35075, 35175], [35100, 35200], [35125, 35225], [35150, 35250], [35175, 35275], [35200, 35300], [35225, 35325], [35250, 35350], [35275, 35375], [35300, 35400], [35325, 35425], [35350, 35450], [35375, 35475], [35400, 35500], [35425, 35525], [35450, 35550], [35475, 35575], [35500, 35600], [35525, 35625], [35550, 35650], [35575, 35675], [35600, 35700], [35625, 35725], [35650, 35750], [35675, 35775], [35700, 35800], [35725, 35825], [35750, 35850], [35775, 35875], [35800, 35900], [35825, 35925], [35850, 35950], [35875, 35975], [35900, 36000], [35925, 36025], [35950, 36050], [35975, 36075], [36000, 36100], [36025, 36125], [36050, 36150], [36075, 36175], [36100, 36200], [36125, 36225], [36150, 36250], [36175, 36275], [36200, 36300]]\n"
     ]
    }
   ],
   "source": [
    "min_radius_bin = df_ring_data['radius'].min()\n",
    "print(min_radius_bin)\n",
    "\n",
    "min_radius_bin = int(min_radius_bin / sub_step) * sub_step\n",
    "print(min_radius_bin)\n",
    "\n",
    "max_radius_bin = df_ring_data['radius'].max()\n",
    "print(max_radius_bin)\n",
    "max_radius_bin = (int(max_radius_bin / sub_step)+1) * sub_step\n",
    "print(max_radius_bin)\n",
    "\n",
    "bins = []\n",
    "bins.append([min_radius_bin, min_radius_bin+radius_step])\n",
    "i = 0\n",
    "bin_end = bins[0][1]\n",
    "while bin_end < max_radius_bin:\n",
    "    \n",
    "    bin_start = bins[i][0]+sub_step\n",
    "    bin_end = bins[i][1]+sub_step\n",
    "    bins.append([bin_start, bin_end])\n",
    "    i+=1\n",
    "    \n",
    "print(bins)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1ed35989",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[75, 175] spor\n",
      "69\n",
      "[75, 175] veg\n",
      "17\n",
      "[100, 200] spor\n",
      "95\n",
      "[100, 200] veg\n",
      "23\n",
      "[125, 225] spor\n",
      "116\n",
      "[125, 225] veg\n",
      "27\n",
      "[150, 250] spor\n",
      "120\n",
      "[150, 250] veg\n",
      "32\n",
      "[175, 275] spor\n",
      "119\n",
      "[175, 275] veg\n",
      "37\n",
      "[200, 300] spor\n",
      "119\n",
      "[200, 300] veg\n",
      "40\n",
      "[225, 325] spor\n",
      "115\n",
      "[225, 325] veg\n",
      "41\n",
      "[250, 350] spor\n",
      "113\n",
      "[250, 350] veg\n",
      "42\n",
      "[275, 375] spor\n",
      "95\n",
      "[275, 375] veg\n",
      "32\n",
      "[300, 400] spor\n",
      "66\n",
      "[300, 400] veg\n",
      "24\n",
      "[325, 425] spor\n",
      "40\n",
      "[325, 425] veg\n",
      "16\n",
      "[350, 450] spor\n",
      "14\n",
      "[350, 450] veg\n",
      "5\n",
      "[375, 475] spor\n",
      "[375, 475] veg\n",
      "[400, 500] spor\n",
      "[400, 500] veg\n",
      "[425, 525] spor\n",
      "[425, 525] veg\n",
      "[450, 550] spor\n",
      "[450, 550] veg\n",
      "[475, 575] spor\n",
      "[475, 575] veg\n",
      "[500, 600] spor\n",
      "[500, 600] veg\n",
      "[525, 625] spor\n",
      "[525, 625] veg\n",
      "[550, 650] spor\n",
      "[550, 650] veg\n",
      "[575, 675] spor\n",
      "[575, 675] veg\n",
      "[600, 700] spor\n",
      "[600, 700] veg\n",
      "[625, 725] spor\n",
      "[625, 725] veg\n",
      "[650, 750] spor\n",
      "[650, 750] veg\n",
      "[675, 775] spor\n",
      "[675, 775] veg\n",
      "[700, 800] spor\n",
      "[700, 800] veg\n",
      "[725, 825] spor\n",
      "[725, 825] veg\n",
      "[750, 850] spor\n",
      "[750, 850] veg\n",
      "[775, 875] spor\n",
      "[775, 875] veg\n",
      "[800, 900] spor\n",
      "[800, 900] veg\n",
      "[825, 925] spor\n",
      "[825, 925] veg\n",
      "[850, 950] spor\n",
      "[850, 950] veg\n",
      "[875, 975] spor\n",
      "[875, 975] veg\n",
      "[900, 1000] spor\n",
      "[900, 1000] veg\n",
      "[925, 1025] spor\n",
      "[925, 1025] veg\n",
      "[950, 1050] spor\n",
      "[950, 1050] veg\n",
      "[975, 1075] spor\n",
      "[975, 1075] veg\n",
      "[1000, 1100] spor\n",
      "[1000, 1100] veg\n",
      "[1025, 1125] spor\n",
      "[1025, 1125] veg\n",
      "[1050, 1150] spor\n",
      "[1050, 1150] veg\n",
      "[1075, 1175] spor\n",
      "[1075, 1175] veg\n",
      "[1100, 1200] spor\n",
      "[1100, 1200] veg\n",
      "[1125, 1225] spor\n",
      "[1125, 1225] veg\n",
      "[1150, 1250] spor\n",
      "[1150, 1250] veg\n",
      "[1175, 1275] spor\n",
      "[1175, 1275] veg\n",
      "[1200, 1300] spor\n",
      "[1200, 1300] veg\n",
      "[1225, 1325] spor\n",
      "[1225, 1325] veg\n",
      "[1250, 1350] spor\n",
      "[1250, 1350] veg\n",
      "[1275, 1375] spor\n",
      "[1275, 1375] veg\n",
      "[1300, 1400] spor\n",
      "[1300, 1400] veg\n",
      "[1325, 1425] spor\n",
      "[1325, 1425] veg\n",
      "[1350, 1450] spor\n",
      "[1350, 1450] veg\n",
      "[1375, 1475] spor\n",
      "[1375, 1475] veg\n",
      "[1400, 1500] spor\n",
      "[1400, 1500] veg\n",
      "[1425, 1525] spor\n",
      "[1425, 1525] veg\n",
      "[1450, 1550] spor\n",
      "[1450, 1550] veg\n",
      "[1475, 1575] spor\n",
      "[1475, 1575] veg\n",
      "[1500, 1600] spor\n",
      "[1500, 1600] veg\n",
      "[1525, 1625] spor\n",
      "[1525, 1625] veg\n",
      "[1550, 1650] spor\n",
      "[1550, 1650] veg\n",
      "[1575, 1675] spor\n",
      "[1575, 1675] veg\n",
      "[1600, 1700] spor\n",
      "[1600, 1700] veg\n",
      "[1625, 1725] spor\n",
      "[1625, 1725] veg\n",
      "[1650, 1750] spor\n",
      "[1650, 1750] veg\n",
      "[1675, 1775] spor\n",
      "[1675, 1775] veg\n",
      "[1700, 1800] spor\n",
      "[1700, 1800] veg\n",
      "[1725, 1825] spor\n",
      "[1725, 1825] veg\n",
      "[1750, 1850] spor\n",
      "[1750, 1850] veg\n",
      "[1775, 1875] spor\n",
      "[1775, 1875] veg\n",
      "[1800, 1900] spor\n",
      "[1800, 1900] veg\n",
      "[1825, 1925] spor\n",
      "[1825, 1925] veg\n",
      "[1850, 1950] spor\n",
      "[1850, 1950] veg\n",
      "[1875, 1975] spor\n",
      "[1875, 1975] veg\n",
      "[1900, 2000] spor\n",
      "[1900, 2000] veg\n",
      "[1925, 2025] spor\n",
      "[1925, 2025] veg\n",
      "[1950, 2050] spor\n",
      "[1950, 2050] veg\n",
      "[1975, 2075] spor\n",
      "[1975, 2075] veg\n",
      "[2000, 2100] spor\n",
      "[2000, 2100] veg\n",
      "[2025, 2125] spor\n",
      "[2025, 2125] veg\n",
      "[2050, 2150] spor\n",
      "[2050, 2150] veg\n",
      "[2075, 2175] spor\n",
      "[2075, 2175] veg\n",
      "[2100, 2200] spor\n",
      "[2100, 2200] veg\n",
      "[2125, 2225] spor\n",
      "[2125, 2225] veg\n",
      "[2150, 2250] spor\n",
      "[2150, 2250] veg\n",
      "[2175, 2275] spor\n",
      "[2175, 2275] veg\n",
      "[2200, 2300] spor\n",
      "[2200, 2300] veg\n",
      "[2225, 2325] spor\n",
      "[2225, 2325] veg\n",
      "[2250, 2350] spor\n",
      "[2250, 2350] veg\n",
      "[2275, 2375] spor\n",
      "[2275, 2375] veg\n",
      "[2300, 2400] spor\n",
      "[2300, 2400] veg\n",
      "[2325, 2425] spor\n",
      "[2325, 2425] veg\n",
      "[2350, 2450] spor\n",
      "[2350, 2450] veg\n",
      "[2375, 2475] spor\n",
      "[2375, 2475] veg\n",
      "[2400, 2500] spor\n",
      "[2400, 2500] veg\n",
      "[2425, 2525] spor\n",
      "[2425, 2525] veg\n",
      "[2450, 2550] spor\n",
      "[2450, 2550] veg\n",
      "[2475, 2575] spor\n",
      "[2475, 2575] veg\n",
      "[2500, 2600] spor\n",
      "[2500, 2600] veg\n",
      "[2525, 2625] spor\n",
      "[2525, 2625] veg\n",
      "[2550, 2650] spor\n",
      "[2550, 2650] veg\n",
      "[2575, 2675] spor\n",
      "[2575, 2675] veg\n",
      "[2600, 2700] spor\n",
      "[2600, 2700] veg\n",
      "[2625, 2725] spor\n",
      "[2625, 2725] veg\n",
      "[2650, 2750] spor\n",
      "[2650, 2750] veg\n",
      "[2675, 2775] spor\n",
      "[2675, 2775] veg\n",
      "[2700, 2800] spor\n",
      "[2700, 2800] veg\n",
      "[2725, 2825] spor\n",
      "[2725, 2825] veg\n",
      "[2750, 2850] spor\n",
      "[2750, 2850] veg\n",
      "[2775, 2875] spor\n",
      "[2775, 2875] veg\n",
      "[2800, 2900] spor\n",
      "[2800, 2900] veg\n",
      "[2825, 2925] spor\n",
      "[2825, 2925] veg\n",
      "[2850, 2950] spor\n",
      "[2850, 2950] veg\n",
      "[2875, 2975] spor\n",
      "[2875, 2975] veg\n",
      "[2900, 3000] spor\n",
      "[2900, 3000] veg\n",
      "[2925, 3025] spor\n",
      "[2925, 3025] veg\n",
      "[2950, 3050] spor\n",
      "[2950, 3050] veg\n",
      "[2975, 3075] spor\n",
      "[2975, 3075] veg\n",
      "[3000, 3100] spor\n",
      "[3000, 3100] veg\n",
      "[3025, 3125] spor\n",
      "[3025, 3125] veg\n",
      "[3050, 3150] spor\n",
      "[3050, 3150] veg\n",
      "[3075, 3175] spor\n",
      "[3075, 3175] veg\n",
      "[3100, 3200] spor\n",
      "[3100, 3200] veg\n",
      "[3125, 3225] spor\n",
      "[3125, 3225] veg\n",
      "[3150, 3250] spor\n",
      "[3150, 3250] veg\n",
      "[3175, 3275] spor\n",
      "[3175, 3275] veg\n",
      "[3200, 3300] spor\n",
      "[3200, 3300] veg\n",
      "[3225, 3325] spor\n",
      "[3225, 3325] veg\n",
      "[3250, 3350] spor\n",
      "[3250, 3350] veg\n",
      "[3275, 3375] spor\n",
      "[3275, 3375] veg\n",
      "[3300, 3400] spor\n",
      "[3300, 3400] veg\n",
      "[3325, 3425] spor\n",
      "[3325, 3425] veg\n",
      "[3350, 3450] spor\n",
      "[3350, 3450] veg\n",
      "[3375, 3475] spor\n",
      "[3375, 3475] veg\n",
      "[3400, 3500] spor\n",
      "[3400, 3500] veg\n",
      "[3425, 3525] spor\n",
      "[3425, 3525] veg\n",
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      "[3475, 3575] spor\n",
      "[3475, 3575] veg\n",
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      "[3500, 3600] veg\n",
      "[3525, 3625] spor\n",
      "[3525, 3625] veg\n",
      "[3550, 3650] spor\n",
      "[3550, 3650] veg\n",
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      "[3575, 3675] veg\n",
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      "[3600, 3700] veg\n",
      "[3625, 3725] spor\n",
      "[3625, 3725] veg\n",
      "[3650, 3750] spor\n",
      "[3650, 3750] veg\n",
      "[3675, 3775] spor\n",
      "[3675, 3775] veg\n",
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      "[3700, 3800] veg\n",
      "[3725, 3825] spor\n",
      "[3725, 3825] veg\n",
      "[3750, 3850] spor\n",
      "[3750, 3850] veg\n",
      "[3775, 3875] spor\n",
      "[3775, 3875] veg\n",
      "[3800, 3900] spor\n",
      "[3800, 3900] veg\n",
      "[3825, 3925] spor\n",
      "[3825, 3925] veg\n",
      "[3850, 3950] spor\n",
      "[3850, 3950] veg\n",
      "[3875, 3975] spor\n",
      "[3875, 3975] veg\n",
      "[3900, 4000] spor\n",
      "[3900, 4000] veg\n",
      "[3925, 4025] spor\n",
      "[3925, 4025] veg\n",
      "[3950, 4050] spor\n",
      "[3950, 4050] veg\n",
      "[3975, 4075] spor\n",
      "[3975, 4075] veg\n",
      "[4000, 4100] spor\n",
      "[4000, 4100] veg\n",
      "[4025, 4125] spor\n",
      "[4025, 4125] veg\n",
      "[4050, 4150] spor\n",
      "[4050, 4150] veg\n",
      "[4075, 4175] spor\n",
      "[4075, 4175] veg\n",
      "[4100, 4200] spor\n",
      "[4100, 4200] veg\n",
      "[4125, 4225] spor\n",
      "[4125, 4225] veg\n",
      "[4150, 4250] spor\n",
      "[4150, 4250] veg\n",
      "[4175, 4275] spor\n",
      "[4175, 4275] veg\n",
      "[4200, 4300] spor\n",
      "[4200, 4300] veg\n",
      "[4225, 4325] spor\n",
      "[4225, 4325] veg\n",
      "[4250, 4350] spor\n",
      "[4250, 4350] veg\n",
      "[4275, 4375] spor\n",
      "[4275, 4375] veg\n",
      "[4300, 4400] spor\n",
      "[4300, 4400] veg\n",
      "[4325, 4425] spor\n",
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      "[4350, 4450] spor\n",
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      "[4375, 4475] spor\n",
      "[4375, 4475] veg\n",
      "[4400, 4500] spor\n",
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      "[4875, 4975] spor\n",
      "[4875, 4975] veg\n",
      "[4900, 5000] spor\n",
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      "[4925, 5025] spor\n",
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      "[5000, 5100] spor\n",
      "[5000, 5100] veg\n",
      "[5025, 5125] spor\n",
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      "[6000, 6100] spor\n",
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      "[6475, 6575] spor\n",
      "[6475, 6575] veg\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[6500, 6600] spor\n",
      "[6500, 6600] veg\n",
      "[6525, 6625] spor\n",
      "[6525, 6625] veg\n",
      "[6550, 6650] spor\n",
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      "[7000, 7100] spor\n",
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      "[7100, 7200] spor\n",
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      "[8650, 8750] spor\n",
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      "[9000, 9100] spor\n",
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      "[9100, 9200] spor\n",
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      "[10000, 10100] spor\n",
      "[10000, 10100] veg\n",
      "[10025, 10125] spor\n",
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      "[10125, 10225] spor\n",
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      "[10175, 10275] spor\n",
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      "[10200, 10300] spor\n",
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      "[10225, 10325] spor\n",
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      "[10275, 10375] spor\n",
      "[10275, 10375] veg\n",
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      "[10325, 10425] spor\n",
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      "[10500, 10600] spor\n",
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      "[10525, 10625] spor\n",
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      "[10575, 10675] spor\n",
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      "[10600, 10700] spor\n",
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      "[10625, 10725] spor\n",
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      "[10800, 10900] spor\n",
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      "[10825, 10925] spor\n",
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      "[10925, 11025] spor\n",
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      "[10975, 11075] spor\n",
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      "[11000, 11100] spor\n",
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      "[11025, 11125] spor\n",
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      "[11050, 11150] spor\n",
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      "[11075, 11175] spor\n",
      "[11075, 11175] veg\n",
      "[11100, 11200] spor\n",
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      "[11125, 11225] spor\n",
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      "[11150, 11250] spor\n",
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      "[11175, 11275] spor\n",
      "[11175, 11275] veg\n",
      "[11200, 11300] spor\n",
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      "[11225, 11325] spor\n",
      "[11225, 11325] veg\n",
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      "[11300, 11400] spor\n",
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      "[12100, 12200] spor\n",
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      "[12125, 12225] spor\n",
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      "[12150, 12250] spor\n",
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      "[12175, 12275] spor\n",
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      "[12200, 12300] spor\n",
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      "[12225, 12325] spor\n",
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      "[12700, 12800] spor\n",
      "[12700, 12800] veg\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[12725, 12825] spor\n",
      "[12725, 12825] veg\n",
      "[12750, 12850] spor\n",
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      "[12775, 12875] spor\n",
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      "[15650, 15750] spor\n",
      "[15650, 15750] veg\n",
      "[15675, 15775] spor\n",
      "[15675, 15775] veg\n",
      "[15700, 15800] spor\n",
      "[15700, 15800] veg\n",
      "[15725, 15825] spor\n",
      "[15725, 15825] veg\n",
      "[15750, 15850] spor\n",
      "[15750, 15850] veg\n",
      "[15775, 15875] spor\n",
      "[15775, 15875] veg\n",
      "[15800, 15900] spor\n",
      "[15800, 15900] veg\n",
      "[15825, 15925] spor\n",
      "[15825, 15925] veg\n",
      "[15850, 15950] spor\n",
      "[15850, 15950] veg\n",
      "[15875, 15975] spor\n",
      "[15875, 15975] veg\n",
      "[15900, 16000] spor\n",
      "[15900, 16000] veg\n",
      "[15925, 16025] spor\n",
      "[15925, 16025] veg\n",
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      "[15950, 16050] veg\n",
      "[15975, 16075] spor\n",
      "[15975, 16075] veg\n",
      "[16000, 16100] spor\n",
      "[16000, 16100] veg\n",
      "[16025, 16125] spor\n",
      "[16025, 16125] veg\n",
      "[16050, 16150] spor\n",
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      "[16075, 16175] spor\n",
      "[16075, 16175] veg\n",
      "[16100, 16200] spor\n",
      "[16100, 16200] veg\n",
      "[16125, 16225] spor\n",
      "[16125, 16225] veg\n",
      "[16150, 16250] spor\n",
      "[16150, 16250] veg\n",
      "[16175, 16275] spor\n",
      "[16175, 16275] veg\n",
      "[16200, 16300] spor\n",
      "[16200, 16300] veg\n",
      "[16225, 16325] spor\n",
      "[16225, 16325] veg\n",
      "[16250, 16350] spor\n",
      "[16250, 16350] veg\n",
      "[16275, 16375] spor\n",
      "[16275, 16375] veg\n",
      "[16300, 16400] spor\n",
      "[16300, 16400] veg\n",
      "[16325, 16425] spor\n",
      "[16325, 16425] veg\n",
      "[16350, 16450] spor\n",
      "[16350, 16450] veg\n",
      "[16375, 16475] spor\n",
      "[16375, 16475] veg\n",
      "[16400, 16500] spor\n",
      "[16400, 16500] veg\n",
      "[16425, 16525] spor\n",
      "[16425, 16525] veg\n",
      "[16450, 16550] spor\n",
      "[16450, 16550] veg\n",
      "[16475, 16575] spor\n",
      "[16475, 16575] veg\n",
      "[16500, 16600] spor\n",
      "[16500, 16600] veg\n",
      "[16525, 16625] spor\n",
      "[16525, 16625] veg\n",
      "[16550, 16650] spor\n",
      "[16550, 16650] veg\n",
      "[16575, 16675] spor\n",
      "[16575, 16675] veg\n",
      "[16600, 16700] spor\n",
      "[16600, 16700] veg\n",
      "[16625, 16725] spor\n",
      "[16625, 16725] veg\n",
      "[16650, 16750] spor\n",
      "[16650, 16750] veg\n",
      "[16675, 16775] spor\n",
      "[16675, 16775] veg\n",
      "[16700, 16800] spor\n",
      "[16700, 16800] veg\n",
      "[16725, 16825] spor\n",
      "[16725, 16825] veg\n",
      "[16750, 16850] spor\n",
      "[16750, 16850] veg\n",
      "[16775, 16875] spor\n",
      "[16775, 16875] veg\n",
      "[16800, 16900] spor\n",
      "[16800, 16900] veg\n",
      "[16825, 16925] spor\n",
      "[16825, 16925] veg\n",
      "[16850, 16950] spor\n",
      "[16850, 16950] veg\n",
      "[16875, 16975] spor\n",
      "[16875, 16975] veg\n",
      "[16900, 17000] spor\n",
      "[16900, 17000] veg\n",
      "[16925, 17025] spor\n",
      "[16925, 17025] veg\n",
      "[16950, 17050] spor\n",
      "[16950, 17050] veg\n",
      "[16975, 17075] spor\n",
      "[16975, 17075] veg\n",
      "[17000, 17100] spor\n",
      "[17000, 17100] veg\n",
      "[17025, 17125] spor\n",
      "[17025, 17125] veg\n",
      "[17050, 17150] spor\n",
      "[17050, 17150] veg\n",
      "[17075, 17175] spor\n",
      "[17075, 17175] veg\n",
      "[17100, 17200] spor\n",
      "[17100, 17200] veg\n",
      "[17125, 17225] spor\n",
      "[17125, 17225] veg\n",
      "[17150, 17250] spor\n",
      "[17150, 17250] veg\n",
      "[17175, 17275] spor\n",
      "[17175, 17275] veg\n",
      "[17200, 17300] spor\n",
      "[17200, 17300] veg\n",
      "[17225, 17325] spor\n",
      "[17225, 17325] veg\n",
      "[17250, 17350] spor\n",
      "[17250, 17350] veg\n",
      "[17275, 17375] spor\n",
      "[17275, 17375] veg\n",
      "[17300, 17400] spor\n",
      "[17300, 17400] veg\n",
      "[17325, 17425] spor\n",
      "[17325, 17425] veg\n",
      "[17350, 17450] spor\n",
      "[17350, 17450] veg\n",
      "[17375, 17475] spor\n",
      "[17375, 17475] veg\n",
      "[17400, 17500] spor\n",
      "[17400, 17500] veg\n",
      "[17425, 17525] spor\n",
      "[17425, 17525] veg\n",
      "[17450, 17550] spor\n",
      "[17450, 17550] veg\n",
      "[17475, 17575] spor\n",
      "[17475, 17575] veg\n",
      "[17500, 17600] spor\n",
      "[17500, 17600] veg\n",
      "[17525, 17625] spor\n",
      "[17525, 17625] veg\n",
      "[17550, 17650] spor\n",
      "[17550, 17650] veg\n",
      "[17575, 17675] spor\n",
      "[17575, 17675] veg\n",
      "[17600, 17700] spor\n",
      "[17600, 17700] veg\n",
      "[17625, 17725] spor\n",
      "[17625, 17725] veg\n",
      "[17650, 17750] spor\n",
      "[17650, 17750] veg\n",
      "[17675, 17775] spor\n",
      "[17675, 17775] veg\n",
      "[17700, 17800] spor\n",
      "[17700, 17800] veg\n",
      "[17725, 17825] spor\n",
      "[17725, 17825] veg\n",
      "[17750, 17850] spor\n",
      "[17750, 17850] veg\n",
      "[17775, 17875] spor\n",
      "[17775, 17875] veg\n",
      "[17800, 17900] spor\n",
      "[17800, 17900] veg\n",
      "[17825, 17925] spor\n",
      "[17825, 17925] veg\n",
      "[17850, 17950] spor\n",
      "[17850, 17950] veg\n",
      "[17875, 17975] spor\n",
      "[17875, 17975] veg\n",
      "[17900, 18000] spor\n",
      "[17900, 18000] veg\n",
      "[17925, 18025] spor\n",
      "[17925, 18025] veg\n",
      "[17950, 18050] spor\n",
      "[17950, 18050] veg\n",
      "[17975, 18075] spor\n",
      "[17975, 18075] veg\n",
      "[18000, 18100] spor\n",
      "[18000, 18100] veg\n",
      "[18025, 18125] spor\n",
      "[18025, 18125] veg\n",
      "[18050, 18150] spor\n",
      "[18050, 18150] veg\n",
      "[18075, 18175] spor\n",
      "[18075, 18175] veg\n",
      "[18100, 18200] spor\n",
      "[18100, 18200] veg\n",
      "[18125, 18225] spor\n",
      "[18125, 18225] veg\n",
      "[18150, 18250] spor\n",
      "[18150, 18250] veg\n",
      "[18175, 18275] spor\n",
      "[18175, 18275] veg\n",
      "[18200, 18300] spor\n",
      "[18200, 18300] veg\n",
      "[18225, 18325] spor\n",
      "[18225, 18325] veg\n",
      "[18250, 18350] spor\n",
      "[18250, 18350] veg\n",
      "[18275, 18375] spor\n",
      "[18275, 18375] veg\n",
      "[18300, 18400] spor\n",
      "[18300, 18400] veg\n",
      "[18325, 18425] spor\n",
      "[18325, 18425] veg\n",
      "[18350, 18450] spor\n",
      "[18350, 18450] veg\n",
      "[18375, 18475] spor\n",
      "[18375, 18475] veg\n",
      "[18400, 18500] spor\n",
      "[18400, 18500] veg\n",
      "[18425, 18525] spor\n",
      "[18425, 18525] veg\n",
      "[18450, 18550] spor\n",
      "[18450, 18550] veg\n",
      "[18475, 18575] spor\n",
      "[18475, 18575] veg\n",
      "[18500, 18600] spor\n",
      "[18500, 18600] veg\n",
      "[18525, 18625] spor\n",
      "[18525, 18625] veg\n",
      "[18550, 18650] spor\n",
      "[18550, 18650] veg\n",
      "[18575, 18675] spor\n",
      "[18575, 18675] veg\n",
      "[18600, 18700] spor\n",
      "[18600, 18700] veg\n",
      "[18625, 18725] spor\n",
      "[18625, 18725] veg\n",
      "[18650, 18750] spor\n",
      "[18650, 18750] veg\n",
      "[18675, 18775] spor\n",
      "[18675, 18775] veg\n",
      "[18700, 18800] spor\n",
      "[18700, 18800] veg\n",
      "[18725, 18825] spor\n",
      "[18725, 18825] veg\n",
      "[18750, 18850] spor\n",
      "[18750, 18850] veg\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[18775, 18875] spor\n",
      "[18775, 18875] veg\n",
      "[18800, 18900] spor\n",
      "[18800, 18900] veg\n",
      "[18825, 18925] spor\n",
      "[18825, 18925] veg\n",
      "[18850, 18950] spor\n",
      "[18850, 18950] veg\n",
      "[18875, 18975] spor\n",
      "[18875, 18975] veg\n",
      "[18900, 19000] spor\n",
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      "[18925, 19025] spor\n",
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      "[18975, 19075] spor\n",
      "[18975, 19075] veg\n",
      "[19000, 19100] spor\n",
      "[19000, 19100] veg\n",
      "[19025, 19125] spor\n",
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      "[19050, 19150] spor\n",
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      "[19075, 19175] spor\n",
      "[19075, 19175] veg\n",
      "[19100, 19200] spor\n",
      "[19100, 19200] veg\n",
      "[19125, 19225] spor\n",
      "[19125, 19225] veg\n",
      "[19150, 19250] spor\n",
      "[19150, 19250] veg\n",
      "[19175, 19275] spor\n",
      "[19175, 19275] veg\n",
      "[19200, 19300] spor\n",
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      "[19225, 19325] spor\n",
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      "[19250, 19350] spor\n",
      "[19250, 19350] veg\n",
      "[19275, 19375] spor\n",
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      "[19300, 19400] spor\n",
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      "[19325, 19425] spor\n",
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      "[19375, 19475] spor\n",
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      "[20000, 20100] spor\n",
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      "[20325, 20425] spor\n",
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      "[22650, 22750] spor\n",
      "[22650, 22750] veg\n",
      "[22675, 22775] spor\n",
      "[22675, 22775] veg\n",
      "[22700, 22800] spor\n",
      "[22700, 22800] veg\n",
      "[22725, 22825] spor\n",
      "[22725, 22825] veg\n",
      "[22750, 22850] spor\n",
      "[22750, 22850] veg\n",
      "[22775, 22875] spor\n",
      "[22775, 22875] veg\n",
      "[22800, 22900] spor\n",
      "[22800, 22900] veg\n",
      "[22825, 22925] spor\n",
      "[22825, 22925] veg\n",
      "[22850, 22950] spor\n",
      "[22850, 22950] veg\n",
      "[22875, 22975] spor\n",
      "[22875, 22975] veg\n",
      "[22900, 23000] spor\n",
      "[22900, 23000] veg\n",
      "[22925, 23025] spor\n",
      "[22925, 23025] veg\n",
      "[22950, 23050] spor\n",
      "[22950, 23050] veg\n",
      "[22975, 23075] spor\n",
      "[22975, 23075] veg\n",
      "[23000, 23100] spor\n",
      "[23000, 23100] veg\n",
      "[23025, 23125] spor\n",
      "[23025, 23125] veg\n",
      "[23050, 23150] spor\n",
      "[23050, 23150] veg\n",
      "[23075, 23175] spor\n",
      "[23075, 23175] veg\n",
      "[23100, 23200] spor\n",
      "[23100, 23200] veg\n",
      "[23125, 23225] spor\n",
      "[23125, 23225] veg\n",
      "[23150, 23250] spor\n",
      "[23150, 23250] veg\n",
      "[23175, 23275] spor\n",
      "[23175, 23275] veg\n",
      "[23200, 23300] spor\n",
      "[23200, 23300] veg\n",
      "[23225, 23325] spor\n",
      "[23225, 23325] veg\n",
      "[23250, 23350] spor\n",
      "[23250, 23350] veg\n",
      "[23275, 23375] spor\n",
      "[23275, 23375] veg\n",
      "[23300, 23400] spor\n",
      "[23300, 23400] veg\n",
      "[23325, 23425] spor\n",
      "[23325, 23425] veg\n",
      "[23350, 23450] spor\n",
      "[23350, 23450] veg\n",
      "[23375, 23475] spor\n",
      "[23375, 23475] veg\n",
      "[23400, 23500] spor\n",
      "[23400, 23500] veg\n",
      "[23425, 23525] spor\n",
      "[23425, 23525] veg\n",
      "[23450, 23550] spor\n",
      "[23450, 23550] veg\n",
      "[23475, 23575] spor\n",
      "[23475, 23575] veg\n",
      "[23500, 23600] spor\n",
      "[23500, 23600] veg\n",
      "[23525, 23625] spor\n",
      "[23525, 23625] veg\n",
      "[23550, 23650] spor\n",
      "[23550, 23650] veg\n",
      "[23575, 23675] spor\n",
      "[23575, 23675] veg\n",
      "[23600, 23700] spor\n",
      "[23600, 23700] veg\n",
      "[23625, 23725] spor\n",
      "[23625, 23725] veg\n",
      "[23650, 23750] spor\n",
      "[23650, 23750] veg\n",
      "[23675, 23775] spor\n",
      "[23675, 23775] veg\n",
      "[23700, 23800] spor\n",
      "[23700, 23800] veg\n",
      "[23725, 23825] spor\n",
      "[23725, 23825] veg\n",
      "[23750, 23850] spor\n",
      "[23750, 23850] veg\n",
      "[23775, 23875] spor\n",
      "[23775, 23875] veg\n",
      "[23800, 23900] spor\n",
      "[23800, 23900] veg\n",
      "[23825, 23925] spor\n",
      "[23825, 23925] veg\n",
      "[23850, 23950] spor\n",
      "[23850, 23950] veg\n",
      "[23875, 23975] spor\n",
      "[23875, 23975] veg\n",
      "[23900, 24000] spor\n",
      "[23900, 24000] veg\n",
      "[23925, 24025] spor\n",
      "[23925, 24025] veg\n",
      "[23950, 24050] spor\n",
      "[23950, 24050] veg\n",
      "[23975, 24075] spor\n",
      "[23975, 24075] veg\n",
      "[24000, 24100] spor\n",
      "[24000, 24100] veg\n",
      "[24025, 24125] spor\n",
      "[24025, 24125] veg\n",
      "[24050, 24150] spor\n",
      "[24050, 24150] veg\n",
      "[24075, 24175] spor\n",
      "[24075, 24175] veg\n",
      "[24100, 24200] spor\n",
      "[24100, 24200] veg\n",
      "[24125, 24225] spor\n",
      "[24125, 24225] veg\n",
      "[24150, 24250] spor\n",
      "[24150, 24250] veg\n",
      "[24175, 24275] spor\n",
      "[24175, 24275] veg\n",
      "[24200, 24300] spor\n",
      "[24200, 24300] veg\n",
      "[24225, 24325] spor\n",
      "[24225, 24325] veg\n",
      "[24250, 24350] spor\n",
      "[24250, 24350] veg\n",
      "[24275, 24375] spor\n",
      "[24275, 24375] veg\n",
      "[24300, 24400] spor\n",
      "[24300, 24400] veg\n",
      "[24325, 24425] spor\n",
      "[24325, 24425] veg\n",
      "[24350, 24450] spor\n",
      "[24350, 24450] veg\n",
      "[24375, 24475] spor\n",
      "[24375, 24475] veg\n",
      "[24400, 24500] spor\n",
      "[24400, 24500] veg\n",
      "[24425, 24525] spor\n",
      "[24425, 24525] veg\n",
      "[24450, 24550] spor\n",
      "[24450, 24550] veg\n",
      "[24475, 24575] spor\n",
      "[24475, 24575] veg\n",
      "[24500, 24600] spor\n",
      "[24500, 24600] veg\n",
      "[24525, 24625] spor\n",
      "[24525, 24625] veg\n",
      "[24550, 24650] spor\n",
      "[24550, 24650] veg\n",
      "[24575, 24675] spor\n",
      "[24575, 24675] veg\n",
      "[24600, 24700] spor\n",
      "[24600, 24700] veg\n",
      "[24625, 24725] spor\n",
      "[24625, 24725] veg\n",
      "[24650, 24750] spor\n",
      "[24650, 24750] veg\n",
      "[24675, 24775] spor\n",
      "[24675, 24775] veg\n",
      "[24700, 24800] spor\n",
      "[24700, 24800] veg\n",
      "[24725, 24825] spor\n",
      "[24725, 24825] veg\n",
      "[24750, 24850] spor\n",
      "[24750, 24850] veg\n",
      "[24775, 24875] spor\n",
      "[24775, 24875] veg\n",
      "[24800, 24900] spor\n",
      "[24800, 24900] veg\n",
      "[24825, 24925] spor\n",
      "[24825, 24925] veg\n",
      "[24850, 24950] spor\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[24850, 24950] veg\n",
      "[24875, 24975] spor\n",
      "[24875, 24975] veg\n",
      "[24900, 25000] spor\n",
      "[24900, 25000] veg\n",
      "[24925, 25025] spor\n",
      "[24925, 25025] veg\n",
      "[24950, 25050] spor\n",
      "[24950, 25050] veg\n",
      "[24975, 25075] spor\n",
      "[24975, 25075] veg\n",
      "[25000, 25100] spor\n",
      "[25000, 25100] veg\n",
      "[25025, 25125] spor\n",
      "[25025, 25125] veg\n",
      "[25050, 25150] spor\n",
      "[25050, 25150] veg\n",
      "[25075, 25175] spor\n",
      "[25075, 25175] veg\n",
      "[25100, 25200] spor\n",
      "[25100, 25200] veg\n",
      "[25125, 25225] spor\n",
      "[25125, 25225] veg\n",
      "[25150, 25250] spor\n",
      "[25150, 25250] veg\n",
      "[25175, 25275] spor\n",
      "[25175, 25275] veg\n",
      "[25200, 25300] spor\n",
      "[25200, 25300] veg\n",
      "[25225, 25325] spor\n",
      "[25225, 25325] veg\n",
      "[25250, 25350] spor\n",
      "[25250, 25350] veg\n",
      "[25275, 25375] spor\n",
      "[25275, 25375] veg\n",
      "[25300, 25400] spor\n",
      "[25300, 25400] veg\n",
      "[25325, 25425] spor\n",
      "[25325, 25425] veg\n",
      "[25350, 25450] spor\n",
      "[25350, 25450] veg\n",
      "[25375, 25475] spor\n",
      "[25375, 25475] veg\n",
      "[25400, 25500] spor\n",
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      "[25425, 25525] spor\n",
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      "[25500, 25600] spor\n",
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      "[25525, 25625] spor\n",
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      "[25575, 25675] spor\n",
      "[25575, 25675] veg\n",
      "[25600, 25700] spor\n",
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      "[25700, 25800] spor\n",
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      "[25800, 25900] spor\n",
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      "[26000, 26100] spor\n",
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      "[30375, 30475] spor\n",
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      "[30425, 30525] spor\n",
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      "[30450, 30550] spor\n",
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      "[30475, 30575] spor\n",
      "[30475, 30575] veg\n",
      "[30500, 30600] spor\n",
      "[30500, 30600] veg\n",
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      "[30600, 30700] spor\n",
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      "[30625, 30725] spor\n",
      "[30625, 30725] veg\n",
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      "[30675, 30775] veg\n",
      "[30700, 30800] spor\n",
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      "[30725, 30825] spor\n",
      "[30725, 30825] veg\n",
      "[30750, 30850] spor\n",
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      "[30775, 30875] spor\n",
      "[30775, 30875] veg\n",
      "[30800, 30900] spor\n",
      "[30800, 30900] veg\n",
      "[30825, 30925] spor\n",
      "[30825, 30925] veg\n",
      "[30850, 30950] spor\n",
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      "[30875, 30975] spor\n",
      "[30875, 30975] veg\n",
      "[30900, 31000] spor\n",
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      "[30925, 31025] spor\n",
      "[30925, 31025] veg\n",
      "[30950, 31050] spor\n",
      "[30950, 31050] veg\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[30975, 31075] spor\n",
      "[30975, 31075] veg\n",
      "[31000, 31100] spor\n",
      "[31000, 31100] veg\n",
      "[31025, 31125] spor\n",
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      "[36175, 36275] spor\n",
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      "[36200, 36300] spor\n",
      "[36200, 36300] veg\n"
     ]
    }
   ],
   "source": [
    "\"\"\"\n",
    "grid pattern\n",
    "\n",
    "load rotated locs\n",
    "\n",
    "move to grid positions\n",
    "\n",
    "test version with horizontal ring\n",
    "\n",
    "\"\"\"\n",
    "\n",
    "for bin in bins:\n",
    "    bin_start = bin[0]\n",
    "    bin_end = bin[1]\n",
    "    \n",
    "    for cell_type in ['spor', 'veg']:\n",
    "        print(bin, cell_type)\n",
    "        df_rings = df_ring_data.copy()\n",
    "        df_rings = df_rings[(df_rings['radius']>=bin_start) & (df_rings['radius']<bin_end) & (df_rings['filter_passed']=='Yes')]\n",
    "        \n",
    "        #print(df_rings['cell_type'])\n",
    "        df_rings = df_rings[df_rings['cell_type']==cell_type]\n",
    "        #print(df_rings['cell_type'])\n",
    "\n",
    "\n",
    "        if len(df_rings) < 5:\n",
    "            continue\n",
    "\n",
    "        # Get filename of tilt corrected ring locs\n",
    "        df_rings['ring_filename'] = 'fov_' + df_rings['fov_id'].astype(str) +'_' + df_rings['cell_type'].astype(str) +'_pick_' + df_rings['group'].astype(str) +'_ring_' + '0' +'_rot_' + orientation + '_update.hdf5'\n",
    "\n",
    "\n",
    "        # Load all rings in df_rings, merge to one dataframe and assign group ID to every\n",
    "\n",
    "        # All rings in this intervall will be assigned a new group ID (in the group column).\n",
    "        # In order to trace back, which group ID (pick ID) they had before in the original FOV file, \n",
    "        # we will save the original group ID in a column called pick. \n",
    "        # both in the ring_data file as well as the generated merged hdf5. \n",
    "\n",
    "        df_rings['pick'] = df_rings['group']\n",
    "        df_rings['group'] = np.arange(len(df_rings))\n",
    "        \n",
    "        path_average = os.path.join(path, 'analysis', 'average_' + orientation)\n",
    "        if not os.path.isdir(path_average):\n",
    "            os.makedirs(path_average)\n",
    "            \n",
    "        print(len(df_rings))\n",
    "        \n",
    "        # Save ring data\n",
    "        df_rings.to_csv(os.path.join(path_average, 'rings_data_{}_bin_{}_{}{}'.format(cell_type, bin[0], bin[1], '.csv')))     \n",
    "        df_rings.to_pickle(os.path.join(path_average, 'rings_data_{}_bin_{}_{}{}'.format(cell_type, bin[0], bin[1], '.pkl')))     \n",
    "\n",
    "\n",
    "        path_rings = os.path.join(path, 'analysis', 'ring_locs')\n",
    "        df_locs_merge, info_merge = load_rings_by_radius(df_rings, path_rings, bin)\n",
    "        \n",
    "        locs_merge = pd.DataFrame.to_records(df_locs_merge)\n",
    "        save_rings_locs(locs_merge, info_merge, path_average, cell_type, bin, filename = '_overlay')\n",
    "\n",
    "        # Unfold rings in a grid pattern\n",
    "        locs_unfold, info_unfold = unfold_groups_square(locs_merge, info_merge, n_square = int(np.sqrt(len(df_rings))+1), spacing = 10)\n",
    "    \n",
    "        save_rings_locs(locs_unfold, info_unfold, path_average, cell_type, bin, filename = '_unfold')\n",
    "\n",
    "    \n",
    "        \n",
    "    \n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ca82085d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f1451e51",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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