{ "cells": [ { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import glob" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "scrolled": true }, "outputs": [], "source": [ "tmat_name = 'tmat_Cyc_8/Cycle_8_F163_tmat_012_001.npy'\n", "tmat_loaded = np.load(tmat_name)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[ 9.99986139e-01, -5.26516052e-03, -9.26144773e+00],\n", " [ 5.26516052e-03, 9.99986139e-01, -1.65591080e+01],\n", " [ 0.00000000e+00, 0.00000000e+00, 1.00000000e+00]])" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tmat_loaded" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "import matplotlib.patches as patches\n", "from pathlib import Path\n", "import numpy as np\n", "import os\n", "import sys\n", "import glob\n", "import pandas as pd\n", "import xml.etree.ElementTree as et\n", "import datetime\n", "from skimage.io import imread, imsave\n", "from imageio import volread as imread\n", "\n", "import tifffile\n", "import pystackreg\n", "from pystackreg import StackReg\n", "from skimage.filters import threshold_otsu\n", "\n", "from pystackreg.util import to_uint16 # make sure version 0.2.5 (not anything below)\n", "from ims_to_tiff import convert_to_tif \n", "from tqdm.notebook import tqdm\n", "\n", "import seaborn as sns\n", "import pylab as pl" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "CYCLE_NUMS = 10\n", "NUM_FOVS = 210" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "for i in range(CYCLE_NUMS):\n", " if i == 0:\n", " continue\n", " os.makedirs(f'tmat_Cyc_{i}')\n", " os.makedirs(f'reg_bin_Cyc_{i}')\n", " os.makedirs(f'reg_Cyc_{i}') " ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# jaccard\n", "def jaccard(img1, img2):\n", " assert img1.dtype == 'bool', 'input must be boolean'\n", " assert img2.dtype == 'bool', 'input must be boolean'\n", " AND = np.sum(img1&img2)\n", " OR = np.sum(img1|img2)\n", " J = AND/OR\n", " return J" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "reg_J = pd.DataFrame()\n", "base_J = pd.DataFrame()" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "cycle 1 field 000 \n", "Got threshold\n", "cycle 1 field 001 \n", "Got threshold\n", "cycle 1 field 002 \n", "Got threshold\n", "cycle 1 field 003 \n", "Got threshold\n", "cycle 1 field 004 \n", "Got threshold\n", "cycle 1 field 005 \n", "Got threshold\n", "cycle 1 field 006 \n", "Got threshold\n", "cycle 1 field 007 \n", "Got threshold\n", "cycle 1 field 008 \n", "Got threshold\n", "cycle 1 field 009 \n", "Got threshold\n", "cycle 1 field 010 \n", "Got threshold\n", "cycle 1 field 011 \n", "Got threshold\n", "cycle 1 field 012 \n", "Got threshold\n", "cycle 1 field 013 \n", "Got threshold\n", "cycle 1 field 014 \n", "Got threshold\n", "cycle 1 field 015 \n", "Got threshold\n", "cycle 1 field 016 \n", "Got threshold\n", "cycle 1 field 017 \n", "Got threshold\n", "cycle 1 field 018 \n", "Got threshold\n", "cycle 1 field 019 \n", "Got threshold\n", "cycle 1 field 020 \n", "Got threshold\n", "cycle 1 field 022 \n", "Got threshold\n", "cycle 1 field 024 \n", "Got threshold\n", "cycle 1 field 025 \n", "Got threshold\n", "cycle 1 field 026 \n", "Got threshold\n", "cycle 1 field 027 \n", "Got threshold\n", "cycle 1 field 028 \n", "Got threshold\n", "cycle 1 field 029 \n", "Got threshold\n", "cycle 1 field 030 \n", "Got threshold\n", "cycle 1 field 031 \n", "Got threshold\n", "cycle 1 field 032 \n", "Got threshold\n", "cycle 1 field 033 \n", "Got threshold\n", "cycle 1 field 034 \n", "Got threshold\n", "cycle 1 field 035 \n", "Got threshold\n", "cycle 1 field 036 \n", "Got threshold\n", "cycle 1 field 039 \n", "Got threshold\n", "cycle 1 field 040 \n", "Got threshold\n", "cycle 1 field 041 \n", "Got threshold\n", "cycle 1 field 042 \n", "Got threshold\n", "cycle 1 field 043 \n", "Got threshold\n", "cycle 1 field 044 \n", "Got threshold\n", "cycle 1 field 045 \n", "Got threshold\n", "cycle 1 field 046 \n", "Got threshold\n", "cycle 1 field 047 \n", "Got threshold\n", "cycle 1 field 048 \n", "Got threshold\n", "cycle 1 field 049 \n", "Got threshold\n", "cycle 1 field 050 \n", "Got threshold\n", "cycle 1 field 052 \n", "Got threshold\n", "cycle 1 field 053 \n", "Got threshold\n", "cycle 1 field 054 \n", "Got threshold\n", "cycle 1 field 055 \n", "Got threshold\n", "cycle 1 field 056 \n", "Got threshold\n", "cycle 1 field 057 \n", "Got threshold\n", "cycle 1 field 059 \n", "Got threshold\n", "cycle 1 field 060 \n", "Got threshold\n", "cycle 1 field 061 \n", "Got threshold\n", "cycle 1 field 062 \n", "Got threshold\n", "cycle 1 field 063 \n", "Got threshold\n", "cycle 1 field 064 \n", "Got threshold\n", "cycle 1 field 065 \n", "Got threshold\n", "cycle 1 field 066 \n", "Got threshold\n", "cycle 1 field 067 \n", "Got threshold\n", "cycle 1 field 068 \n", "Got threshold\n", "cycle 1 field 069 \n", "Got threshold\n", "cycle 1 field 070 \n", "Got threshold\n", "cycle 1 field 071 \n", "Got threshold\n", "cycle 1 field 073 \n", "Got threshold\n", "cycle 1 field 074 \n", "Got threshold\n", "cycle 1 field 075 \n", "Got threshold\n", "cycle 1 field 076 \n", "Got threshold\n", "cycle 1 field 077 \n", "Got threshold\n", "cycle 1 field 078 \n", "Got threshold\n", "cycle 1 field 079 \n", "Got threshold\n", "cycle 1 field 080 \n", "Got threshold\n", "cycle 1 field 081 \n", "Got threshold\n", "cycle 1 field 082 \n", "Got threshold\n", "cycle 1 field 084 \n", "Got threshold\n", "cycle 1 field 085 \n", "Got threshold\n", "cycle 1 field 086 \n", "Got threshold\n", "cycle 1 field 087 \n", "Got threshold\n", "cycle 1 field 088 \n", "Got threshold\n", "cycle 1 field 089 \n", "Got threshold\n", "cycle 1 field 090 \n", "Got threshold\n", "cycle 1 field 091 \n", "Got threshold\n", "cycle 1 field 092 \n", "Got threshold\n", "cycle 1 field 093 \n", "Got threshold\n", "cycle 1 field 094 \n", "Got threshold\n", "cycle 1 field 095 \n", "Got threshold\n", "cycle 1 field 096 \n", "Got threshold\n", "cycle 1 field 097 \n", "Got threshold\n", "cycle 1 field 098 \n", "Got threshold\n", "cycle 1 field 099 \n", "Got threshold\n", "cycle 1 field 100 \n", "Got threshold\n", "cycle 1 field 101 \n", "Got threshold\n", "cycle 1 field 102 \n", "Got threshold\n", "cycle 1 field 103 \n", "Got threshold\n", "cycle 1 field 104 \n", "Got threshold\n", "cycle 1 field 105 \n", "Got threshold\n", "cycle 1 field 107 \n", "Got threshold\n", "cycle 1 field 108 \n", "Got threshold\n", "cycle 1 field 109 \n", "Got threshold\n", "cycle 1 field 110 \n", "Got threshold\n", "cycle 1 field 111 \n", "Got threshold\n", "cycle 1 field 112 \n", "Got threshold\n", "cycle 1 field 113 \n", "Got threshold\n", "cycle 1 field 114 \n", "Got threshold\n", "cycle 1 field 115 \n", "Got threshold\n", "cycle 1 field 116 \n", "Got threshold\n", "cycle 1 field 117 \n", "Got threshold\n", "cycle 1 field 118 \n", "Got threshold\n", "cycle 1 field 119 \n", "Got threshold\n", "cycle 1 field 120 \n", "Got threshold\n", "cycle 1 field 121 \n", "Got threshold\n", "cycle 1 field 122 \n", "Got threshold\n", "cycle 1 field 123 \n", "Got threshold\n", "cycle 1 field 124 \n", "Got threshold\n", "cycle 1 field 125 \n", "Got threshold\n", "cycle 1 field 126 \n", "Got threshold\n", "cycle 1 field 127 \n", "Got threshold\n", "cycle 1 field 128 \n", "Got threshold\n", "cycle 1 field 129 \n", "Got threshold\n", "cycle 1 field 130 \n", "Got threshold\n", "cycle 1 field 131 \n", "Got threshold\n", "cycle 1 field 132 \n", "Got threshold\n", "cycle 1 field 133 \n", "Got threshold\n", "cycle 1 field 134 \n", "Got threshold\n", "cycle 1 field 135 \n", "Got threshold\n", "cycle 1 field 137 \n", "Got threshold\n", "cycle 1 field 138 \n", "Got threshold\n", "cycle 1 field 140 \n", "Got threshold\n", "cycle 1 field 141 \n", "Got threshold\n", "cycle 1 field 142 \n", "Got threshold\n", "cycle 1 field 143 \n", "Got threshold\n", "cycle 1 field 144 \n", "Got threshold\n", "cycle 1 field 145 \n", "Got threshold\n", "cycle 1 field 146 \n", "Got threshold\n", "cycle 1 field 147 \n", "Got threshold\n", "cycle 1 field 148 \n", "Got threshold\n", "cycle 1 field 149 \n", "Got threshold\n", "cycle 1 field 150 \n", "Got threshold\n", "cycle 1 field 151 \n", "Got threshold\n", "cycle 1 field 152 \n", "Got threshold\n", "cycle 1 field 153 \n", "Got threshold\n", "cycle 1 field 154 \n", "Got threshold\n", "cycle 1 field 155 \n", "Got threshold\n", "cycle 1 field 156 \n", "Got threshold\n", "cycle 1 field 157 \n", "Got threshold\n", "cycle 1 field 158 \n", "Got threshold\n", "cycle 1 field 159 \n", "Got threshold\n", "cycle 1 field 161 \n", "Got threshold\n", "cycle 1 field 162 \n", "Got threshold\n", "cycle 1 field 163 \n", "Got threshold\n", "cycle 1 field 164 \n", "Got threshold\n", "cycle 1 field 165 \n", "Got threshold\n", "cycle 1 field 166 \n", "Got threshold\n", "cycle 1 field 167 \n", "Got threshold\n", "cycle 1 field 168 \n", "Got threshold\n", "cycle 1 field 169 \n", "Got threshold\n", "cycle 1 field 170 \n", "Got threshold\n", "cycle 1 field 171 \n", "Got threshold\n", "cycle 1 field 172 \n", "Got threshold\n", "cycle 1 field 173 \n", "Got threshold\n", "cycle 1 field 174 \n", "Got threshold\n", "cycle 1 field 175 \n", "Got threshold\n", "cycle 1 field 176 \n", "Got threshold\n", "cycle 1 field 177 \n", "Got threshold\n", "cycle 1 field 178 \n", "Got threshold\n", "cycle 1 field 179 \n", "Got threshold\n", "cycle 1 field 180 \n", "Got threshold\n", "cycle 1 field 181 \n", "Got threshold\n", "cycle 1 field 182 \n", "Got threshold\n", "cycle 1 field 183 \n", "Got threshold\n", "cycle 1 field 184 \n", "Got threshold\n", "cycle 1 field 185 \n", "Got threshold\n", "cycle 1 field 186 \n", "Got threshold\n", "cycle 1 field 188 \n", "Got threshold\n", "cycle 1 field 189 \n", "Got threshold\n", "cycle 1 field 190 \n", "Got threshold\n", "cycle 1 field 191 \n", "Got threshold\n", "cycle 1 field 192 \n", "Got threshold\n", "cycle 1 field 194 \n", "Got threshold\n", "cycle 1 field 195 \n", "Got threshold\n", "cycle 1 field 196 \n", "Got threshold\n", "cycle 1 field 197 \n", "Got threshold\n", "cycle 1 field 198 \n", "Got threshold\n", "cycle 1 field 199 \n", "Got threshold\n", "cycle 1 field 200 \n", "Got threshold\n", "cycle 1 field 201 \n", "Got threshold\n", "cycle 1 field 202 \n", "Got threshold\n", "cycle 1 field 203 \n", "Got threshold\n", "cycle 1 field 204 \n", "Got threshold\n", "cycle 1 field 205 \n", "Got threshold\n", "cycle 1 field 206 \n", "Got threshold\n", "cycle 1 field 207 \n", "Got threshold\n", "cycle 1 field 208 \n", "Got threshold\n", "cycle 1 field 209 \n", "Got threshold\n", "cycle 1 field 211 \n", "Got threshold\n", "cycle 1 field 212 \n", "Got threshold\n", "cycle 1 field 213 \n", "Got threshold\n", "cycle 1 field 214 \n", "Got threshold\n", "cycle 1 field 215 \n", "Got threshold\n", "cycle 1 field 216 \n", "Got threshold\n", "cycle 1 field 217 \n", "Got threshold\n", "cycle 1 field 218 \n", "Got threshold\n", "cycle 1 field 219 \n", "Got threshold\n", "cycle 1 field 220 \n", "Got threshold\n", "cycle 1 field 221 \n", "Got threshold\n", "cycle 1 field 222 \n", "Got threshold\n", "cycle 1 field 223 \n", "Got threshold\n", "cycle 1 field 224 \n", "Got threshold\n", "cycle 2 field 000 \n", "Got threshold\n", "cycle 2 field 001 \n", "Got threshold\n", "cycle 2 field 002 \n", "Got threshold\n", "cycle 2 field 003 \n", "Got threshold\n", "cycle 2 field 004 \n", "Got threshold\n", "cycle 2 field 005 \n", "Got threshold\n", "cycle 2 field 006 \n", "Got threshold\n", "cycle 2 field 007 \n", "Got threshold\n", "cycle 2 field 008 \n", "Got threshold\n", "cycle 2 field 009 \n", "Got threshold\n", "cycle 2 field 010 \n", "Got threshold\n", "cycle 2 field 011 \n", "Got threshold\n", "cycle 2 field 012 \n", "Got threshold\n", "cycle 2 field 013 \n", "Got threshold\n", "cycle 2 field 014 \n", "Got threshold\n", "cycle 2 field 015 \n", "Got threshold\n", "cycle 2 field 016 \n", "Got threshold\n", "cycle 2 field 017 \n", "Got threshold\n", "cycle 2 field 018 \n", "Got threshold\n", "cycle 2 field 019 \n", "Got threshold\n", "cycle 2 field 020 \n", "Got threshold\n", "cycle 2 field 022 \n", "Got threshold\n", "cycle 2 field 024 \n", "Got threshold\n", "cycle 2 field 025 \n", "Got threshold\n", "cycle 2 field 026 \n", "Got threshold\n", "cycle 2 field 027 \n", "Got threshold\n", "cycle 2 field 028 \n", "Got threshold\n", "cycle 2 field 029 \n", "Got threshold\n", "cycle 2 field 030 \n", "Got threshold\n", "cycle 2 field 031 \n", "Got threshold\n", "cycle 2 field 032 \n", "Got threshold\n", "cycle 2 field 033 \n", "Got threshold\n", "cycle 2 field 034 \n", "Got threshold\n", "cycle 2 field 035 \n", "Got threshold\n", "cycle 2 field 036 \n", "Got threshold\n", "cycle 2 field 039 \n", "Got threshold\n", "cycle 2 field 040 \n", "Got threshold\n", "cycle 2 field 041 \n", "Got threshold\n", "cycle 2 field 042 \n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Got threshold\n", "cycle 2 field 043 \n", "Got threshold\n", "cycle 2 field 044 \n", "Got threshold\n", "cycle 2 field 045 \n", "Got threshold\n", "cycle 2 field 046 \n", "Got threshold\n", "cycle 2 field 047 \n", "Got threshold\n", "cycle 2 field 048 \n", "Got threshold\n", "cycle 2 field 049 \n", "Got threshold\n", "cycle 2 field 050 \n", "Got threshold\n", "cycle 2 field 052 \n", "Got threshold\n", "cycle 2 field 053 \n", "Got threshold\n", "cycle 2 field 054 \n", "Got threshold\n", "cycle 2 field 055 \n", "Got threshold\n", "cycle 2 field 056 \n", "Got threshold\n", "cycle 2 field 057 \n", "Got threshold\n", "cycle 2 field 059 \n", "Got threshold\n", "cycle 2 field 060 \n", "Got threshold\n", "cycle 2 field 061 \n", "Got threshold\n", "cycle 2 field 062 \n", "Got threshold\n", "cycle 2 field 063 \n", "Got threshold\n", "cycle 2 field 064 \n", "Got threshold\n", "cycle 2 field 065 \n", "Got threshold\n", "cycle 2 field 066 \n", "Got threshold\n", "cycle 2 field 067 \n", "Got threshold\n", "cycle 2 field 068 \n", "Got threshold\n", "cycle 2 field 069 \n", "Got threshold\n", "cycle 2 field 070 \n", "Got threshold\n", "cycle 2 field 071 \n", "Got threshold\n", "cycle 2 field 073 \n", "Got threshold\n", "cycle 2 field 074 \n", "Got threshold\n", "cycle 2 field 075 \n", "Got threshold\n", "cycle 2 field 076 \n", "Got threshold\n", "cycle 2 field 077 \n", "Got threshold\n", "cycle 2 field 078 \n", "Got threshold\n", "cycle 2 field 079 \n", "Got threshold\n", "cycle 2 field 080 \n", "Got threshold\n", "cycle 2 field 081 \n", "Got threshold\n", "cycle 2 field 082 \n", "Got threshold\n", "cycle 2 field 084 \n", "Got threshold\n", "cycle 2 field 085 \n", "Got threshold\n", "cycle 2 field 086 \n", "Got threshold\n", "cycle 2 field 087 \n", "Got threshold\n", "cycle 2 field 088 \n", "Got threshold\n", "cycle 2 field 089 \n", "Got threshold\n", "cycle 2 field 090 \n", "Got threshold\n", "cycle 2 field 091 \n", "Got threshold\n", "cycle 2 field 092 \n", "Got threshold\n", "cycle 2 field 093 \n", "Got threshold\n", "cycle 2 field 094 \n", "Got threshold\n", "cycle 2 field 095 \n", "Got threshold\n", "cycle 2 field 096 \n", "Got threshold\n", "cycle 2 field 097 \n", "Got threshold\n", "cycle 2 field 098 \n", "Got threshold\n", "cycle 2 field 099 \n", "Got threshold\n", "cycle 2 field 100 \n", "Got threshold\n", "cycle 2 field 101 \n", "Got threshold\n", "cycle 2 field 102 \n", "Got threshold\n", "cycle 2 field 103 \n", "Got threshold\n", "cycle 2 field 104 \n", "Got threshold\n", "cycle 2 field 105 \n", "Got threshold\n", "cycle 2 field 107 \n", "Got threshold\n", "cycle 2 field 108 \n", "Got threshold\n", "cycle 2 field 109 \n", "Got threshold\n", "cycle 2 field 110 \n", "Got threshold\n", "cycle 2 field 111 \n", "Got threshold\n", "cycle 2 field 112 \n", "Got threshold\n", "cycle 2 field 113 \n", "Got threshold\n", "cycle 2 field 114 \n", "Got threshold\n", "cycle 2 field 115 \n", "Got threshold\n", "cycle 2 field 116 \n", "Got threshold\n", "cycle 2 field 117 \n", "Got threshold\n", "cycle 2 field 118 \n", "Got threshold\n", "cycle 2 field 119 \n", "Got threshold\n", "cycle 2 field 120 \n", "Got threshold\n", "cycle 2 field 121 \n", "Got threshold\n", "cycle 2 field 122 \n", "Got threshold\n", "cycle 2 field 123 \n", "Got threshold\n", "cycle 2 field 124 \n", "Got threshold\n", "cycle 2 field 125 \n", "Got threshold\n", "cycle 2 field 126 \n", "Got threshold\n", "cycle 2 field 127 \n", "Got threshold\n", "cycle 2 field 128 \n", "Got threshold\n", "cycle 2 field 129 \n", "Got threshold\n", "cycle 2 field 130 \n", "Got threshold\n", "cycle 2 field 131 \n", "Got threshold\n", "cycle 2 field 132 \n", "Got threshold\n", "cycle 2 field 133 \n", "Got threshold\n", "cycle 2 field 134 \n", "Got threshold\n", "cycle 2 field 135 \n", "Got threshold\n", "cycle 2 field 137 \n", "Got threshold\n", "cycle 2 field 138 \n", "Got threshold\n", "cycle 2 field 140 \n", "Got threshold\n", "cycle 2 field 141 \n", "Got threshold\n", "cycle 2 field 142 \n", "Got threshold\n", "cycle 2 field 143 \n", "Got threshold\n", "cycle 2 field 144 \n", "Got threshold\n", "cycle 2 field 145 \n", "Got threshold\n", "cycle 2 field 146 \n", "Got threshold\n", "cycle 2 field 147 \n", "Got threshold\n", "cycle 2 field 148 \n", "Got threshold\n", "cycle 2 field 149 \n", "Got threshold\n", "cycle 2 field 150 \n", "Got threshold\n", "cycle 2 field 151 \n", "Got threshold\n", "cycle 2 field 152 \n", "Got threshold\n", "cycle 2 field 153 \n", "Got threshold\n", "cycle 2 field 154 \n", "Got 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threshold\n", "cycle 3 field 003 \n", "Got threshold\n", "cycle 3 field 004 \n", "Got threshold\n", "cycle 3 field 005 \n", "Got threshold\n", "cycle 3 field 006 \n", "Got threshold\n", "cycle 3 field 007 \n", "Got threshold\n", "cycle 3 field 008 \n", "Got threshold\n", "cycle 3 field 009 \n", "Got threshold\n", "cycle 3 field 010 \n", "Got threshold\n", "cycle 3 field 011 \n", "Got threshold\n", "cycle 3 field 012 \n", "Got threshold\n", "cycle 3 field 013 \n", "Got threshold\n", "cycle 3 field 014 \n", "Got threshold\n", "cycle 3 field 015 \n", "Got threshold\n", "cycle 3 field 016 \n", "Got threshold\n", "cycle 3 field 017 \n", "Got threshold\n", "cycle 3 field 018 \n", "Got threshold\n", "cycle 3 field 019 \n", "Got threshold\n", "cycle 3 field 020 \n", "Got threshold\n", "cycle 3 field 022 \n", "Got threshold\n", "cycle 3 field 024 \n", "Got threshold\n", "cycle 3 field 025 \n", "Got threshold\n", "cycle 3 field 026 \n", "Got threshold\n", "cycle 3 field 027 \n", "Got threshold\n", "cycle 3 field 028 \n", "Got threshold\n", "cycle 3 field 029 \n", "Got threshold\n", "cycle 3 field 030 \n", "Got threshold\n", "cycle 3 field 031 \n", "Got threshold\n", "cycle 3 field 032 \n", "Got threshold\n", "cycle 3 field 033 \n", "Got threshold\n", "cycle 3 field 034 \n", "Got threshold\n", "cycle 3 field 035 \n", "Got threshold\n", "cycle 3 field 036 \n", "Got threshold\n", "cycle 3 field 039 \n", "Got threshold\n", "cycle 3 field 040 \n", "Got threshold\n", "cycle 3 field 041 \n", "Got threshold\n", "cycle 3 field 042 \n", "Got threshold\n", "cycle 3 field 043 \n", "Got threshold\n", "cycle 3 field 044 \n", "Got threshold\n", "cycle 3 field 045 \n", "Got threshold\n", "cycle 3 field 046 \n", "Got threshold\n", "cycle 3 field 047 \n", "Got threshold\n", "cycle 3 field 048 \n", "Got threshold\n", "cycle 3 field 049 \n", "Got threshold\n", "cycle 3 field 050 \n", "Got threshold\n", "cycle 3 field 052 \n", "Got threshold\n", "cycle 3 field 053 \n", "Got 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threshold\n", "cycle 3 field 079 \n", "Got threshold\n", "cycle 3 field 080 \n", "Got threshold\n", "cycle 3 field 081 \n", "Got threshold\n", "cycle 3 field 082 \n", "Got threshold\n", "cycle 3 field 084 \n", "Got threshold\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "cycle 3 field 085 \n", "Got threshold\n", "cycle 3 field 086 \n", "Got threshold\n", "cycle 3 field 087 \n", "Got threshold\n", "cycle 3 field 088 \n", "Got threshold\n", "cycle 3 field 089 \n", "Got threshold\n", "cycle 3 field 090 \n", "Got threshold\n", "cycle 3 field 091 \n", "Got threshold\n", "cycle 3 field 092 \n", "Got threshold\n", "cycle 3 field 093 \n", "Got threshold\n", "cycle 3 field 094 \n", "Got threshold\n", "cycle 3 field 095 \n", "Got threshold\n", "cycle 3 field 096 \n", "Got threshold\n", "cycle 3 field 097 \n", "Got threshold\n", "cycle 3 field 098 \n", "Got threshold\n", "cycle 3 field 099 \n", "Got threshold\n", "cycle 3 field 100 \n", "Got threshold\n", "cycle 3 field 101 \n", 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threshold\n", "cycle 3 field 126 \n", "Got threshold\n", "cycle 3 field 127 \n", "Got threshold\n", "cycle 3 field 128 \n", "Got threshold\n", "cycle 3 field 129 \n", "Got threshold\n", "cycle 3 field 130 \n", "Got threshold\n", "cycle 3 field 131 \n", "Got threshold\n", "cycle 3 field 132 \n", "Got threshold\n", "cycle 3 field 133 \n", "Got threshold\n", "cycle 3 field 134 \n", "Got threshold\n", "cycle 3 field 135 \n", "Got threshold\n", "cycle 3 field 137 \n", "Got threshold\n", "cycle 3 field 138 \n", "Got threshold\n", "cycle 3 field 140 \n", "Got threshold\n", "cycle 3 field 141 \n", "Got threshold\n", "cycle 3 field 142 \n", "Got threshold\n", "cycle 3 field 143 \n", "Got threshold\n", "cycle 3 field 144 \n", "Got threshold\n", "cycle 3 field 145 \n", "Got threshold\n", "cycle 3 field 146 \n", "Got threshold\n", "cycle 3 field 147 \n", "Got threshold\n", "cycle 3 field 148 \n", "Got threshold\n", "cycle 3 field 149 \n", "Got threshold\n", "cycle 3 field 150 \n", "Got 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threshold\n", "cycle 3 field 224 \n", "Got threshold\n", "cycle 4 field 000 \n", "Got threshold\n", "cycle 4 field 001 \n", "Got threshold\n", "cycle 4 field 002 \n", "Got threshold\n", "cycle 4 field 003 \n", "Got threshold\n", "cycle 4 field 004 \n", "Got threshold\n", "cycle 4 field 005 \n", "Got threshold\n", "cycle 4 field 006 \n", "Got threshold\n", "cycle 4 field 007 \n", "Got threshold\n", "cycle 4 field 008 \n", "Got threshold\n", "cycle 4 field 009 \n", "Got threshold\n", "cycle 4 field 010 \n", "Got threshold\n", "cycle 4 field 011 \n", "Got threshold\n", "cycle 4 field 012 \n", "Got threshold\n", "cycle 4 field 013 \n", "Got threshold\n", "cycle 4 field 014 \n", "Got threshold\n", "cycle 4 field 015 \n", "Got threshold\n", "cycle 4 field 016 \n", "Got threshold\n", "cycle 4 field 017 \n", "Got threshold\n", "cycle 4 field 018 \n", "Got threshold\n", "cycle 4 field 019 \n", "Got threshold\n", "cycle 4 field 020 \n", "Got threshold\n", "cycle 4 field 022 \n", "Got threshold\n", "cycle 4 field 024 \n", "Got threshold\n", "cycle 4 field 025 \n", "Got threshold\n", "cycle 4 field 026 \n", "Got threshold\n", "cycle 4 field 027 \n", "Got threshold\n", "cycle 4 field 028 \n", "Got threshold\n", "cycle 4 field 029 \n", "Got threshold\n", "cycle 4 field 030 \n", "Got threshold\n", "cycle 4 field 031 \n", "Got threshold\n", "cycle 4 field 032 \n", "Got threshold\n", "cycle 4 field 033 \n", "Got threshold\n", "cycle 4 field 034 \n", "Got threshold\n", "cycle 4 field 035 \n", "Got threshold\n", "cycle 4 field 036 \n", "Got threshold\n", "cycle 4 field 039 \n", "Got threshold\n", "cycle 4 field 040 \n", "Got threshold\n", "cycle 4 field 041 \n", "Got threshold\n", "cycle 4 field 042 \n", "Got threshold\n", "cycle 4 field 043 \n", "Got threshold\n", "cycle 4 field 044 \n", "Got threshold\n", "cycle 4 field 045 \n", "Got threshold\n", "cycle 4 field 046 \n", "Got threshold\n", "cycle 4 field 047 \n", "Got threshold\n", "cycle 4 field 048 \n", "Got threshold\n", "cycle 4 field 049 \n", "Got threshold\n", "cycle 4 field 050 \n", "Got threshold\n", "cycle 4 field 052 \n", "Got threshold\n", "cycle 4 field 053 \n", "Got threshold\n", "cycle 4 field 054 \n", "Got threshold\n", "cycle 4 field 055 \n", "Got threshold\n", "cycle 4 field 056 \n", "Got threshold\n", "cycle 4 field 057 \n", "Got threshold\n", "cycle 4 field 059 \n", "Got threshold\n", "cycle 4 field 060 \n", "Got threshold\n", "cycle 4 field 061 \n", "Got threshold\n", "cycle 4 field 062 \n", "Got threshold\n", "cycle 4 field 063 \n", "Got threshold\n", "cycle 4 field 064 \n", "Got threshold\n", "cycle 4 field 065 \n", "Got threshold\n", "cycle 4 field 066 \n", "Got threshold\n", "cycle 4 field 067 \n", "Got threshold\n", "cycle 4 field 068 \n", "Got threshold\n", "cycle 4 field 069 \n", "Got threshold\n", "cycle 4 field 070 \n", "Got threshold\n", "cycle 4 field 071 \n", "Got threshold\n", "cycle 4 field 073 \n", "Got threshold\n", "cycle 4 field 074 \n", "Got threshold\n", "cycle 4 field 075 \n", "Got threshold\n", "cycle 4 field 076 \n", "Got threshold\n", "cycle 4 field 077 \n", "Got threshold\n", "cycle 4 field 078 \n", "Got threshold\n", "cycle 4 field 079 \n", "Got threshold\n", "cycle 4 field 080 \n", "Got threshold\n", "cycle 4 field 081 \n", "Got threshold\n", "cycle 4 field 082 \n", "Got threshold\n", "cycle 4 field 084 \n", "Got threshold\n", "cycle 4 field 085 \n", "Got threshold\n", "cycle 4 field 086 \n", "Got threshold\n", "cycle 4 field 087 \n", "Got threshold\n", "cycle 4 field 088 \n", "Got threshold\n", "cycle 4 field 089 \n", "Got threshold\n", "cycle 4 field 090 \n", "Got threshold\n", "cycle 4 field 091 \n", "Got threshold\n", "cycle 4 field 092 \n", "Got threshold\n", "cycle 4 field 093 \n", "Got threshold\n", "cycle 4 field 094 \n", "Got threshold\n", "cycle 4 field 095 \n", "Got threshold\n", "cycle 4 field 096 \n", "Got threshold\n", "cycle 4 field 097 \n", "Got threshold\n", "cycle 4 field 098 \n", "Got threshold\n", "cycle 4 field 099 \n", "Got threshold\n", "cycle 4 field 100 \n", "Got threshold\n", "cycle 4 field 101 \n", "Got threshold\n", "cycle 4 field 102 \n", "Got threshold\n", "cycle 4 field 103 \n", "Got threshold\n", "cycle 4 field 104 \n", "Got threshold\n", "cycle 4 field 105 \n", "Got threshold\n", "cycle 4 field 107 \n", "Got threshold\n", "cycle 4 field 108 \n", "Got threshold\n", "cycle 4 field 109 \n", "Got threshold\n", "cycle 4 field 110 \n", "Got threshold\n", "cycle 4 field 111 \n", "Got threshold\n", "cycle 4 field 112 \n", "Got threshold\n", "cycle 4 field 113 \n", "Got threshold\n", "cycle 4 field 114 \n", "Got threshold\n", "cycle 4 field 115 \n", "Got threshold\n", "cycle 4 field 116 \n", "Got threshold\n", "cycle 4 field 117 \n", "Got threshold\n", "cycle 4 field 118 \n", "Got threshold\n", "cycle 4 field 119 \n", "Got threshold\n", "cycle 4 field 120 \n", "Got threshold\n", "cycle 4 field 121 \n", "Got threshold\n", "cycle 4 field 122 \n", "Got 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threshold\n", "cycle 4 field 171 \n", "Got threshold\n", "cycle 4 field 172 \n", "Got threshold\n", "cycle 4 field 173 \n", "Got threshold\n", "cycle 4 field 174 \n", "Got threshold\n", "cycle 4 field 175 \n", "Got threshold\n", "cycle 4 field 176 \n", "Got threshold\n", "cycle 4 field 177 \n", "Got threshold\n", "cycle 4 field 178 \n", "Got threshold\n", "cycle 4 field 179 \n", "Got threshold\n", "cycle 4 field 180 \n", "Got threshold\n", "cycle 4 field 181 \n", "Got threshold\n", "cycle 4 field 182 \n", "Got threshold\n", "cycle 4 field 183 \n", "Got threshold\n", "cycle 4 field 184 \n", "Got threshold\n", "cycle 4 field 185 \n", "Got threshold\n", "cycle 4 field 186 \n", "Got threshold\n", "cycle 4 field 188 \n", "Got threshold\n", "cycle 4 field 189 \n", "Got threshold\n", "cycle 4 field 190 \n", "Got threshold\n", "cycle 4 field 191 \n", "Got threshold\n", "cycle 4 field 192 \n", "Got threshold\n", "cycle 4 field 194 \n", "Got threshold\n", "cycle 4 field 195 \n", "Got threshold\n", "cycle 4 field 196 \n", "Got threshold\n", "cycle 4 field 197 \n", "Got threshold\n", "cycle 4 field 198 \n", "Got threshold\n", "cycle 4 field 199 \n", "Got threshold\n", "cycle 4 field 200 \n", "Got threshold\n", "cycle 4 field 201 \n", "Got threshold\n", "cycle 4 field 202 \n", "Got threshold\n", "cycle 4 field 203 \n", "Got threshold\n", "cycle 4 field 204 \n", "Got threshold\n", "cycle 4 field 205 \n", "Got threshold\n", "cycle 4 field 206 \n", "Got threshold\n", "cycle 4 field 207 \n", "Got threshold\n", "cycle 4 field 208 \n", "Got threshold\n", "cycle 4 field 209 \n", "Got threshold\n", "cycle 4 field 211 \n", "Got threshold\n", "cycle 4 field 212 \n", "Got threshold\n", "cycle 4 field 213 \n", "Got threshold\n", "cycle 4 field 214 \n", "Got threshold\n", "cycle 4 field 215 \n", "Got threshold\n", "cycle 4 field 216 \n", "Got threshold\n", "cycle 4 field 217 \n", "Got threshold\n", "cycle 4 field 218 \n", "Got threshold\n", "cycle 4 field 219 \n", "Got threshold\n", "cycle 4 field 220 \n", "Got threshold\n", "cycle 4 field 221 \n", "Got threshold\n", "cycle 4 field 222 \n", "Got threshold\n", "cycle 4 field 223 \n", "Got threshold\n", "cycle 4 field 224 \n", "Got threshold\n", "cycle 5 field 000 \n", "Got threshold\n", "cycle 5 field 001 \n", "Got threshold\n", "cycle 5 field 002 \n", "Got threshold\n", "cycle 5 field 003 \n", "Got threshold\n", "cycle 5 field 004 \n", "Got threshold\n", "cycle 5 field 005 \n", "Got threshold\n", "cycle 5 field 006 \n", "Got threshold\n", "cycle 5 field 007 \n", "Got threshold\n", "cycle 5 field 008 \n", "Got threshold\n", "cycle 5 field 009 \n", "Got threshold\n", "cycle 5 field 010 \n", "Got threshold\n", "cycle 5 field 011 \n", "Got threshold\n", "cycle 5 field 012 \n", "Got threshold\n", "cycle 5 field 013 \n", "Got threshold\n", "cycle 5 field 014 \n", "Got threshold\n", "cycle 5 field 015 \n", "Got threshold\n", "cycle 5 field 016 \n", "Got threshold\n", "cycle 5 field 017 \n", "Got threshold\n", "cycle 5 field 018 \n", "Got threshold\n", "cycle 5 field 019 \n", "Got threshold\n", "cycle 5 field 020 \n", "Got threshold\n", "cycle 5 field 022 \n", "Got threshold\n", "cycle 5 field 024 \n", "Got threshold\n", "cycle 5 field 025 \n", "Got threshold\n", "cycle 5 field 026 \n", "Got threshold\n", "cycle 5 field 027 \n", "Got threshold\n", "cycle 5 field 028 \n", "Got threshold\n", "cycle 5 field 029 \n", "Got threshold\n", "cycle 5 field 030 \n", "Got threshold\n", "cycle 5 field 031 \n", "Got threshold\n", "cycle 5 field 032 \n", "Got threshold\n", "cycle 5 field 033 \n", "Got threshold\n", "cycle 5 field 034 \n", "Got threshold\n", "cycle 5 field 035 \n", "Got threshold\n", "cycle 5 field 036 \n", "Got threshold\n", "cycle 5 field 039 \n", "Got threshold\n", "cycle 5 field 040 \n", "Got threshold\n", "cycle 5 field 041 \n", "Got threshold\n", "cycle 5 field 042 \n", "Got threshold\n", "cycle 5 field 043 \n", "Got threshold\n", "cycle 5 field 044 \n", "Got threshold\n", "cycle 5 field 045 \n", "Got threshold\n", "cycle 5 field 046 \n", "Got threshold\n", "cycle 5 field 047 \n", "Got threshold\n", "cycle 5 field 048 \n", "Got threshold\n", "cycle 5 field 049 \n", "Got threshold\n", "cycle 5 field 050 \n", "Got threshold\n", "cycle 5 field 052 \n", "Got threshold\n", "cycle 5 field 053 \n", "Got threshold\n", "cycle 5 field 054 \n", "Got threshold\n", "cycle 5 field 055 \n", "Got threshold\n", "cycle 5 field 056 \n", "Got threshold\n", "cycle 5 field 057 \n", "Got threshold\n", "cycle 5 field 059 \n", "Got threshold\n", "cycle 5 field 060 \n", "Got threshold\n", "cycle 5 field 061 \n", "Got threshold\n", "cycle 5 field 062 \n", "Got threshold\n", "cycle 5 field 063 \n", "Got threshold\n", "cycle 5 field 064 \n", "Got threshold\n", "cycle 5 field 065 \n", "Got threshold\n", "cycle 5 field 066 \n", "Got threshold\n", "cycle 5 field 067 \n", "Got threshold\n", "cycle 5 field 068 \n", "Got threshold\n", "cycle 5 field 069 \n", "Got 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threshold\n", "cycle 6 field 014 \n", "Got threshold\n", "cycle 6 field 015 \n", "Got threshold\n", "cycle 6 field 016 \n", "Got threshold\n", "cycle 6 field 017 \n", "Got threshold\n", "cycle 6 field 018 \n", "Got threshold\n", "cycle 6 field 019 \n", "Got threshold\n", "cycle 6 field 020 \n", "Got threshold\n", "cycle 6 field 022 \n", "Got threshold\n", "cycle 6 field 024 \n", "Got threshold\n", "cycle 6 field 025 \n", "Got threshold\n", "cycle 6 field 026 \n", "Got threshold\n", "cycle 6 field 027 \n", "Got threshold\n", "cycle 6 field 028 \n", "Got threshold\n", "cycle 6 field 029 \n", "Got threshold\n", "cycle 6 field 030 \n", "Got threshold\n", "cycle 6 field 031 \n", "Got threshold\n", "cycle 6 field 032 \n", "Got threshold\n", "cycle 6 field 033 \n", "Got threshold\n", "cycle 6 field 034 \n", "Got threshold\n", "cycle 6 field 035 \n", "Got threshold\n", "cycle 6 field 036 \n", "Got threshold\n", "cycle 6 field 039 \n", "Got threshold\n", "cycle 6 field 040 \n", "Got threshold\n", "cycle 6 field 041 \n", "Got threshold\n", "cycle 6 field 042 \n", "Got threshold\n", "cycle 6 field 043 \n", "Got threshold\n", "cycle 6 field 044 \n", "Got threshold\n", "cycle 6 field 045 \n", "Got threshold\n", "cycle 6 field 046 \n", "Got threshold\n", "cycle 6 field 047 \n", "Got threshold\n", "cycle 6 field 048 \n", "Got threshold\n", "cycle 6 field 049 \n", "Got threshold\n", "cycle 6 field 050 \n", "Got threshold\n", "cycle 6 field 052 \n", "Got threshold\n", "cycle 6 field 053 \n", "Got threshold\n", "cycle 6 field 054 \n", "Got threshold\n", "cycle 6 field 055 \n", "Got threshold\n", "cycle 6 field 056 \n", "Got threshold\n", "cycle 6 field 057 \n", "Got threshold\n", "cycle 6 field 059 \n", "Got threshold\n", "cycle 6 field 060 \n", "Got threshold\n", "cycle 6 field 061 \n", "Got threshold\n", "cycle 6 field 062 \n", "Got threshold\n", "cycle 6 field 063 \n", "Got threshold\n", "cycle 6 field 064 \n", "Got threshold\n", "cycle 6 field 065 \n", "Got threshold\n", "cycle 6 field 066 \n", "Got threshold\n", "cycle 6 field 067 \n", "Got threshold\n", "cycle 6 field 068 \n", "Got threshold\n", "cycle 6 field 069 \n", "Got threshold\n", "cycle 6 field 070 \n", "Got threshold\n", "cycle 6 field 071 \n", "Got threshold\n", "cycle 6 field 073 \n", "Got threshold\n", "cycle 6 field 074 \n", "Got threshold\n", "cycle 6 field 075 \n", "Got threshold\n", "cycle 6 field 076 \n", "Got threshold\n", "cycle 6 field 077 \n", "Got threshold\n", "cycle 6 field 078 \n", "Got threshold\n", "cycle 6 field 079 \n", "Got threshold\n", "cycle 6 field 080 \n", "Got threshold\n", "cycle 6 field 081 \n", "Got threshold\n", "cycle 6 field 082 \n", "Got threshold\n", "cycle 6 field 084 \n", "Got threshold\n", "cycle 6 field 085 \n", "Got threshold\n", "cycle 6 field 086 \n", "Got threshold\n", "cycle 6 field 087 \n", "Got threshold\n", "cycle 6 field 088 \n", "Got threshold\n", "cycle 6 field 089 \n", "Got threshold\n", "cycle 6 field 090 \n", "Got 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threshold\n", "cycle 7 field 010 \n", "Got threshold\n", "cycle 7 field 011 \n", "Got threshold\n", "cycle 7 field 012 \n", "Got threshold\n", "cycle 7 field 013 \n", "Got threshold\n", "cycle 7 field 014 \n", "Got threshold\n", "cycle 7 field 015 \n", "Got threshold\n", "cycle 7 field 016 \n", "Got threshold\n", "cycle 7 field 017 \n", "Got threshold\n", "cycle 7 field 018 \n", "Got threshold\n", "cycle 7 field 019 \n", "Got threshold\n", "cycle 7 field 020 \n", "Got threshold\n", "cycle 7 field 022 \n", "Got threshold\n", "cycle 7 field 024 \n", "Got threshold\n", "cycle 7 field 025 \n", "Got threshold\n", "cycle 7 field 026 \n", "Got threshold\n", "cycle 7 field 027 \n", "Got threshold\n", "cycle 7 field 028 \n", "Got threshold\n", "cycle 7 field 029 \n", "Got threshold\n", "cycle 7 field 030 \n", "Got threshold\n", "cycle 7 field 031 \n", "Got threshold\n", "cycle 7 field 032 \n", "Got threshold\n", "cycle 7 field 033 \n", "Got threshold\n", "cycle 7 field 034 \n", "Got 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threshold\n", "cycle 8 field 057 \n", "Got threshold\n", "cycle 8 field 059 \n", "Got threshold\n", "cycle 8 field 060 \n", "Got threshold\n", "cycle 8 field 061 \n", "Got threshold\n", "cycle 8 field 062 \n", "Got threshold\n", "cycle 8 field 063 \n", "Got threshold\n", "cycle 8 field 064 \n", "Got threshold\n", "cycle 8 field 065 \n", "Got threshold\n", "cycle 8 field 066 \n", "Got threshold\n", "cycle 8 field 067 \n", "Got threshold\n", "cycle 8 field 068 \n", "Got threshold\n", "cycle 8 field 069 \n", "Got threshold\n", "cycle 8 field 070 \n", "Got threshold\n", "cycle 8 field 071 \n", "Got threshold\n", "cycle 8 field 073 \n", "Got threshold\n", "cycle 8 field 074 \n", "Got threshold\n", "cycle 8 field 075 \n", "Got threshold\n", "cycle 8 field 076 \n", "Got threshold\n", "cycle 8 field 077 \n", "Got threshold\n", "cycle 8 field 078 \n", "Got threshold\n", "cycle 8 field 079 \n", "Got threshold\n", "cycle 8 field 080 \n", "Got threshold\n", "cycle 8 field 081 \n", "Got 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"Got threshold\n", "cycle 9 field 078 \n", "Got threshold\n", "cycle 9 field 079 \n", "Got threshold\n", "cycle 9 field 080 \n", "Got threshold\n", "cycle 9 field 081 \n", "Got threshold\n", "cycle 9 field 082 \n", "Got threshold\n", "cycle 9 field 084 \n", "Got threshold\n", "cycle 9 field 085 \n", "Got threshold\n", "cycle 9 field 086 \n", "Got threshold\n", "cycle 9 field 087 \n", "Got threshold\n", "cycle 9 field 088 \n", "Got threshold\n", "cycle 9 field 089 \n", "Got threshold\n", "cycle 9 field 090 \n", "Got threshold\n", "cycle 9 field 091 \n", "Got threshold\n", "cycle 9 field 092 \n", "Got threshold\n", "cycle 9 field 093 \n", "Got threshold\n", "cycle 9 field 094 \n", "Got threshold\n", "cycle 9 field 095 \n", "Got threshold\n", "cycle 9 field 096 \n", "Got threshold\n", "cycle 9 field 097 \n", "Got threshold\n", "cycle 9 field 098 \n", "Got threshold\n", "cycle 9 field 099 \n", "Got threshold\n", "cycle 9 field 100 \n", "Got threshold\n", "cycle 9 field 101 \n", "Got threshold\n", "cycle 9 field 102 \n", "Got threshold\n", "cycle 9 field 103 \n", "Got threshold\n", "cycle 9 field 104 \n", "Got threshold\n", "cycle 9 field 105 \n", "Got threshold\n", "cycle 9 field 107 \n", "Got threshold\n", "cycle 9 field 108 \n", "Got threshold\n", "cycle 9 field 109 \n", "Got threshold\n", "cycle 9 field 110 \n", "Got threshold\n", "cycle 9 field 111 \n", "Got threshold\n", "cycle 9 field 112 \n", "Got threshold\n", "cycle 9 field 113 \n", "Got threshold\n", "cycle 9 field 114 \n", "Got threshold\n", "cycle 9 field 115 \n", "Got threshold\n", "cycle 9 field 116 \n", "Got threshold\n", "cycle 9 field 117 \n", "Got threshold\n", "cycle 9 field 118 \n", "Got threshold\n", "cycle 9 field 119 \n", "Got threshold\n", "cycle 9 field 120 \n", "Got threshold\n", "cycle 9 field 121 \n", "Got threshold\n", "cycle 9 field 122 \n", "Got threshold\n", "cycle 9 field 123 \n", "Got threshold\n", "cycle 9 field 124 \n", "Got threshold\n", "cycle 9 field 125 \n", "Got threshold\n", "cycle 9 field 126 \n", "Got threshold\n", "cycle 9 field 127 \n", "Got threshold\n", "cycle 9 field 128 \n", "Got threshold\n", "cycle 9 field 129 \n", "Got threshold\n", "cycle 9 field 130 \n", "Got threshold\n", "cycle 9 field 131 \n", "Got threshold\n", "cycle 9 field 132 \n", "Got threshold\n", "cycle 9 field 133 \n", "Got threshold\n", "cycle 9 field 134 \n", "Got threshold\n", "cycle 9 field 135 \n", "Got threshold\n", "cycle 9 field 137 \n", "Got threshold\n", "cycle 9 field 138 \n", "Got threshold\n", "cycle 9 field 140 \n", "Got threshold\n", "cycle 9 field 141 \n", "Got threshold\n", "cycle 9 field 142 \n", "Got threshold\n", "cycle 9 field 143 \n", "Got threshold\n", "cycle 9 field 144 \n", "Got threshold\n", "cycle 9 field 145 \n", "Got threshold\n", "cycle 9 field 146 \n", "Got threshold\n", "cycle 9 field 147 \n", "Got threshold\n", "cycle 9 field 148 \n", "Got threshold\n", "cycle 9 field 149 \n", "Got threshold\n", "cycle 9 field 150 \n", "Got threshold\n", "cycle 9 field 151 \n", "Got threshold\n", "cycle 9 field 152 \n", "Got threshold\n", "cycle 9 field 153 \n", "Got threshold\n", "cycle 9 field 154 \n", "Got threshold\n", "cycle 9 field 155 \n", "Got threshold\n", "cycle 9 field 156 \n", "Got threshold\n", "cycle 9 field 157 \n", "Got threshold\n", "cycle 9 field 158 \n", "Got threshold\n", "cycle 9 field 159 \n", "Got threshold\n", "cycle 9 field 161 \n", "Got threshold\n", "cycle 9 field 162 \n", "Got threshold\n", "cycle 9 field 163 \n", "Got threshold\n", "cycle 9 field 164 \n", "Got threshold\n", "cycle 9 field 165 \n", "Got threshold\n", "cycle 9 field 166 \n", "Got threshold\n", "cycle 9 field 167 \n", "Got threshold\n", "cycle 9 field 168 \n", "Got threshold\n", "cycle 9 field 169 \n", "Got threshold\n", "cycle 9 field 170 \n", "Got threshold\n", "cycle 9 field 171 \n", "Got threshold\n", "cycle 9 field 172 \n", "Got threshold\n", "cycle 9 field 173 \n", "Got threshold\n", "cycle 9 field 174 \n", "Got threshold\n", "cycle 9 field 175 \n", "Got threshold\n", "cycle 9 field 176 \n", "Got threshold\n", "cycle 9 field 177 \n", "Got threshold\n", "cycle 9 field 178 \n", "Got threshold\n", "cycle 9 field 179 \n", "Got threshold\n", "cycle 9 field 180 \n", "Got threshold\n", "cycle 9 field 181 \n", "Got threshold\n", "cycle 9 field 182 \n", "Got threshold\n", "cycle 9 field 183 \n", "Got threshold\n", "cycle 9 field 184 \n", "Got threshold\n", "cycle 9 field 185 \n", "Got threshold\n", "cycle 9 field 186 \n", "Got threshold\n", "cycle 9 field 188 \n", "Got threshold\n", "cycle 9 field 189 \n", "Got threshold\n", "cycle 9 field 190 \n", "Got threshold\n", "cycle 9 field 191 \n", "Got threshold\n", "cycle 9 field 192 \n", "Got threshold\n", "cycle 9 field 194 \n", "Got threshold\n", "cycle 9 field 195 \n", "Got threshold\n", "cycle 9 field 196 \n", "Got threshold\n", "cycle 9 field 197 \n", "Got threshold\n", "cycle 9 field 198 \n", "Got threshold\n", "cycle 9 field 199 \n", "Got threshold\n", "cycle 9 field 200 \n", "Got threshold\n", "cycle 9 field 201 \n", "Got threshold\n", "cycle 9 field 202 \n", "Got threshold\n", "cycle 9 field 203 \n", "Got threshold\n", "cycle 9 field 204 \n", "Got threshold\n", "cycle 9 field 205 \n", "Got threshold\n", "cycle 9 field 206 \n", "Got threshold\n", "cycle 9 field 207 \n", "Got threshold\n", "cycle 9 field 208 \n", "Got threshold\n", "cycle 9 field 209 \n", "Got threshold\n", "cycle 9 field 211 \n", "Got threshold\n", "cycle 9 field 212 \n", "Got threshold\n", "cycle 9 field 213 \n", "Got threshold\n", "cycle 9 field 214 \n", "Got threshold\n", "cycle 9 field 215 \n", "Got threshold\n", "cycle 9 field 216 \n", "Got threshold\n", "cycle 9 field 217 \n", "Got threshold\n", "cycle 9 field 218 \n", "Got threshold\n", "cycle 9 field 219 \n", "Got threshold\n", "cycle 9 field 220 \n", "Got threshold\n", "cycle 9 field 221 \n", "Got threshold\n", "cycle 9 field 222 \n", "Got threshold\n", "cycle 9 field 223 \n", "Got threshold\n", "cycle 9 field 224 \n", "Got threshold\n" ] } ], "source": [ "for c in range(CYCLE_NUMS-1):\n", " refs = iter(sorted(glob.glob('tif/Cycle_0/*'))) # list of cycle 0 .tif \n", " movs = iter(sorted(glob.glob(f'tif/Cycle_{c+1}/*'))) # cycle 1, 2, 3, .tif list --> FOV000, 001, (002 = error) 005 006 \n", " for FOV in range(0, NUM_FOVS): # \n", " #sFOV = str(FOV).zfill(NUM_DIGITS_OF_FOVS)\n", " ref_name = next(refs) \n", " ref = imread(ref_name)\n", " ref = ref.astype(np.uint16)\n", " mov_name = next(movs)\n", " mov = imread(mov_name)\n", " mov = mov.astype(np.uint16)\n", " FOV_num = mov_name.split('_F')[1][0:3]\n", " print(f'cycle {c+1} field {FOV_num} ')\n", "\n", " ref_max = ref.max(0)\n", " ref_binary = ref_max[0] > threshold_otsu(ref_max[0]) # nuclei channel\n", " mov_max = mov.max(0)\n", " mov_binary = mov_max[0] > threshold_otsu(mov_max[0]) # nuclei channel\n", " print(\"Got threshold\")\n", " sr = StackReg(StackReg.RIGID_BODY) \n", " tmat = sr.register(ref_binary, mov_binary) \n", " out = sr.transform(mov_binary) \n", " out = pystackreg.util.to_uint16(out) \n", "\n", " base_J.loc[FOV_num, str(c+1)] = jaccard(ref_binary, mov_binary)\n", " reg_J.loc[FOV_num, str(c+1)] = jaccard(ref_binary, out.astype('bool'))\n", "\n", "# # save binary\n", "# fname_to_save = f'reg_bin_Cyc_{c+1}' + f'/Cycle_{c+1}_F{FOV_num}_bin_reg.tif'\n", "# print('Saving Binary Registered Images...', fname_to_save)\n", "# tifffile.imwrite(fname_to_save, out, imagej=True, photometric = 'minisblack',metadata={'axes':'YX'})\n", "\n", "# # save tmat\n", "# print(\"saving tmat\")\n", "# np.save(f'tmat_Cyc_{c+1}' + f'/Cycle_{c+1}_F{FOV_num}_tmat.npy', tmat)\n", "\n", "\n", "base_J.to_csv('base_J.csv')\n", "reg_J.to_csv('reg_J.csv')" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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0000.7545400.7623920.7620460.7199900.7342330.6894750.6533240.5214520.536774
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210 rows × 9 columns

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0.592380 \n", "221 0.451085 0.619209 \n", "222 0.375059 0.554783 \n", "223 0.440067 0.574752 \n", "224 0.551339 0.615787 \n", "\n", "[210 rows x 9 columns]" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "base_J " ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "dfX_shift = pd.DataFrame()\n", "dfY_shift = pd.DataFrame()\n", "for idx, c in enumerate(range(CYCLE_NUMS-1)):\n", " tmats = iter(sorted(glob.glob(f'tmat_Cyc_{c+1}/*')))\n", " for sFOV in range(0,NUM_FOVS):\n", " tmat_name = next(tmats)\n", " FOV_num = tmat_name.split('_F')[1][0:3]\n", " tmat_loaded = np.load(tmat_name)\n", " moveX = tmat_loaded[0,2]\n", " moveY = tmat_loaded[1,2]\n", "\n", " dfX_shift.loc[FOV_num, str(c+1)] = moveX\n", " dfY_shift.loc[FOV_num, str(c+1)] = moveY\n", "\n", "dfX_shift.to_csv('Cov_9_X_shift.csv')\n", "dfY_shift.to_csv('Cov_9_Y_shift.csv')" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "scrolled": false }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/imaging/mambaforge/envs/all_your_base/lib/python3.7/site-packages/numpy/lib/histograms.py:829: RuntimeWarning: invalid value encountered in greater_equal\n", " keep = (tmp_a >= first_edge)\n", "/home/imaging/mambaforge/envs/all_your_base/lib/python3.7/site-packages/numpy/lib/histograms.py:830: RuntimeWarning: invalid value encountered in less_equal\n", " keep &= (tmp_a <= last_edge)\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# LOOKING AT JACCARD SHIFT\n", "from matplotlib import pyplot\n", "\n", "fig, axs = plt.subplots(CYCLE_NUMS-1, 3, figsize=(15,30))\n", "\n", "for cycle in range(CYCLE_NUMS-1):\n", " axs[cycle][0].hist(reg_J[f'{cycle+1}'], bins = 50, alpha=0.5, label='reg_J', range=[0,1])\n", " axs[cycle][0].hist(base_J[f'{cycle+1}'], bins = 50, alpha=0.5, label='base_J', range=[0,1])\n", " \n", " axs[cycle][1].hist(dfY_shift[f'{cycle+1}'], bins = 50, alpha=0.5, label='dfX_shift', range=[-50,50])\n", " axs[cycle][2].hist(dfX_shift[f'{cycle+1}'], bins = 50, alpha=0.5, label='dfX_shift', range=[-50,50])\n", " \n", " axs[cycle][0].title.set_text(f'Change in Jaccard Index - Cycle {cycle+1}')\n", " axs[cycle][1].title.set_text(f'Y Shift - Cycle {cycle+1}')\n", " axs[cycle][2].title.set_text(f'X Shift - Cycle {cycle+1}')\n", "\n", "# for ax in axs.flat:\n", "# ax.set(xlabel='', ylabel='')" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "scrolled": false }, "outputs": [ { "data": { "image/png": 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\n", 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\n", 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\n", 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\n", 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GcN16LC9Tms/yzxJ9lqfU6MPc2DFiM7NhUafZEGU5EZtZo7hHbGZWsdGxOl1kqxwnYjNrlGEcmhi+Px1mZh2MhUovRSQdLOlXkm6XdNygYi4qg3mMpO0H9eBmZqlFqPTSiaSpwBeBQ8hKPLxN0i6DiLmoR/xPwC8kXSXpvZK2GEQQZmapJKw1MRe4PSLujIhngXOAwwYRc1EivhPYjiwh7wHcIukHko7K609MSNKIpEWSFi1ccVvCcM3MOutmaKI1V+XLSEtT2wL3tvy8LF+XXNHBuoiIMeAy4DJJ08m66W8DPgNM2EOOiPnAfIB/2eHIIRw6N7Nh1c2sidZcNYGJxi4Gks+KEvEagUTESuBi4GJJ6w0iIDOzfiTMlMuA1mNk2wHL0zX/J0WJ+C3tNkTE04ljMTPrW5nZECVdC+wsaUfgt8BbgSNSNd6qqB7xrwfxoGZmg5Kq6E9ErJL0fuBSYCpwekTcnKTxcXxCh5k1SspiURHxPeB7CZuckBOxmTVK1KjiY1kDT8RjyYbOh+/FHTap3qmpidqpUxnMVLGkOpX1pkhTvjLV85qRqJ0UVrkesZlZtdwjNjOrWJ2+SZXlRGxmjeIesZlZxdwjNjOr2Kh7xGZm1RrCKyV1TsSS1iE7rW95RFwh6QhgH2ApMD+vPWFmVhtjDewRn5HfZ6ako4BZwAXAAWS1Oo8abHhmZt0ZxnKPRYn4ZRGxq6RpZEUvtomIUUlnAYvb7ZTX9BwBOGzTuew564XJAjYz62QYD9YVnegzJR+e2ACYCWyUr58BTG+3U0TMj4g5ETHHSdjMJtOYVHqpi6Ie8VeAW8nOWp0HnCfpTmAvssuGmJnVymjVAfSgqAzmqZL+K7+9XNKZwIHAlyNi4WQEaGbWjcbNmoAsAbfc/h1w/kAjMjPrQxNnTZiZDZUmzpowMxsqjRya6NeUGn1NWDAlTQ3XttNFupTqAzMlURcg1TtVp4MldXuN6ybVVK9VidpJYRinr7lHbGaNMlqfvl9pTsRm1ijuEZuZVcyJ2MysYkN4yTonYjNrlkb2iCW9AHgDsD3ZwdHbgLMj4vEBx2Zm1rU6zdopq2PRH0nHAF8C1gX2BNYjS8hXS9p/4NGZmXVpTOWXuiiqvnY0cHBE/DNZjYldImIecDBwarudJI1IWiRp0cIVt6WL1syswFgXS10UJWL40/DFDLJymETEPZQsgzl31s79R2lmVtIwJuKiMeLTgGslXQPsB5wEIGkL4NEBx2Zm1rVhPAmyqAzmZyVdAbwEOCUibs3XP0SWmM3MaqVOY79llSmDeTNw8yTEYmbWt2GcNeF5xGbWKGNDODjhRGxmjVKng3BlDTwRz0z0xynFuM+MGsUC6UorTk3TTLKvdKmG6FK8PFMTvcZPJ3pS6yeK52VakaSdW0bTlIZ9qsz8q0kyfP1h94jNrGHcIzYzq9gqTU6fWNJu/OnM41XAe3u9qHKNvlCYmfUvulj6dDJwYkTsBhyf/9wT94jNrFEmcWgigA3z2xsByzvctyMnYjNrlEmcvvYh4FJJnyEbXdin14aciM2sUbpJw5JGgJGWVfMjYn7L9iuArSfYdR5wAPDhiPiWpDcDXyErjtY1J2Iza5RuhibypDu/w/a2iVXSmcAH8x/PI6vN0xMfrDOzRhklSi99Wg68Kr/9GrKLZvSkqDD8RpL+VdKtkh7Jl6X5uo077PfHesQ/dz1iM5tEk1gG82jg3yQtBj7FmkMcXSnqEZ8LPAbsHxGbRcRmwKvzdee126m1HvE+rkdsZpMouvjX1+NE/DQi9oiI/x4Rr4iI63ptqygRz46IkyLi/pYHvz8iTgKe3+uDmpkNyjAWhi9KxHdLOlbSVqtXSNpK0seBewcbmplZ98aI0ktdFCXitwCbAVdKelTSo8ACYFPg8AHHZmbWtUk8sy6Zoit0PAZ8PF/WIOldwBkDisvMrCerapViy+ln+tqJyaIwM0tksg7WpdSxRyzpxnabgK3abFvDK8fS1E1N4Wqlqb2aqsZtqo9BnQ46QMLnlaAGcKr3KpVU8fySNJ/ltpdi79IkFTwrpW6/D2UUnVm3FfCXZNPVWgn4+UAiMjPrQ516umUVJeLvALMi4obxGyQtGEhEZmZ9aFyPOCLe3WHbEenDMTPrz2g0r0dsZjZU6jQ/uCwnYjNrlCaOEZuZDZXGjRGbmQ2bYRyaGEg94tYymBf8/q5BPISZ2YSG8YSOnhOxpO+329ZaBvON68/u9SHMzLo2GlF6qYuiM+t2b7cJ2C19OGZm/RnGoYmiMeJrgSvJEu94ba/QYWZWlSYerFsK/F1EPOd6R5Jcj9jMaqdOY79lFSXiT9B+HPkDaUMxM+tf44YmIuL8Dps3SRyLmVnfokYH4crqZx7xiZQoDL8wUenJlQlKIgJMqdF7tHekKRGa6jWu29hancqN1uhjk9RA5q9WbHQI362B1yOukzolYZscfsvXPo0bmsD1iM1syDRxaML1iM1sqDSuR+x6xGY2bJo4fc3MbKjU6dTlspyIzaxRGjc0YWY2bJyIzcwqNoyzJjrO55a0oaR/kfR1SUeM2/bvHfb7Yz3in654TpkKM7OBGSNKL3VRdGLNGWRzhr8FvFXStyTNyLft1W6n1nrE+87aOVGoZmbFhrEwfNHQxAsi4m/y2xdJmgf8SNKhA47LzKwno1G3k/WLFSXiGZKmRGTPLCI+KWkZ8BMgTYEDM7OEGjdGDFwCvKZ1RUR8Dfgo8OyggjIz69UwjhEXnVl3bJv1P5D0qcGEZGbWuzqN/ZbVTxW8E5NFYWaWyFhE6aUfkg6XdLOkMUlzxm3bVdLV+fabJK3bqa2Bl8GcnuiP02iCNhKVNE729/aaRHWEU8Xj+siDl+o5rVOzTl+d6hpPYo94CfBG4D9bV0qaBpwF/G1ELJa0GbCyU0Mug2lmjTJZsyYiYimA9Jwu3kHAjRGxOL/fI0VtuQymmTVKN0MOkkaAkZZV8yNifp8hvAgISZcCWwDnRMTJnXZwGUwza5RuhibypNs28Uq6Ath6gk3zIuLbbXabBuwL7Ak8BfxQ0nUR8cN2j+NaE2bWKP0ehGsVEQf2sNsy4MqIeBhA0veA3YG2ibhOY+xmZn2rwSnOlwK7SpqZH7h7FXBLpx2ciM2sUUZjtPTSD0lvyM803hv4bj4mTEQ8BpwCXAvcAFwfEd/t1JaHJsysUSbrFOeIuBC4sM22s8imsJUykB5xaxnMn/zeZTDNbPIM4ynORfWIt5b0H5K+KGkzSZ/IzxI5V9Lz2u3XWgZzv/VdBtPMJk9ElF7qoqhH/FWyQeZ7gR8DTwOvBa4CvjTQyMzMejBZpzinVHhmXUR8HkDSeyPipHz95yW1nWNsZlaVYSz6U5SIW3vMZ47bNjVxLGZmfWtiYfhvS5oVESsi4h9Xr5T0QuBXgw3NzKx7dRr7LavoFOfj26y/XVLHeXFmZlWo09hvWa5HbGaNMoyzJgZej/gPqYoAJzCaKJYpid6/VB+DsUTP6+qaXYawRh+dWsUCsCpRQEr0IazTqGyd5geX5XrEZtYoderpluV6xGbWKI2bNeF6xGY2bIbxYJ2L/phZozRxaMLMbKg08cw6M7Ohslb0iCVtGREPDiIYM7N+DeMYcdFk503HLZsBdwGbAJt22G8EWJQvIyUmVRfep+TkbLczBLG4Hb/nXtZclL9AE5I0Btw9bvV2ZBfHi4jYqbu03/ZxFkXEHLczuHbqFIvbmZx26hRLynaaqOgU52PJivscGhE7RsSOwLL8dpIkbGa2tuuYiCPiM8B7gOMlnSJpA9KdmWtmZpQo+hMRyyLicLIrdFwOzBxAHPPdzsDbqVMsbmdy2qlTLCnbaZyOY8TPubO0HvCCiFgi6V0RccbgQjMzWzt0lYjX2FG6JyKenzgeM7O1TtFVnG9ss9xEyTKYRSQdLOlXkm6XdFyPbZwu6UFJS/qIY3tJP5a0VNLNkj7YYzvrSlooaXHeTl91myVNlfRLSd/po4278qtv3yBpUR/tbCzpfEm35q/T3j208eI8jtXLE5I+1EM7H85f3yWSzpa0brdt5O18MG/j5m7jmOhzJ2lTSZdLui3/f5Me2jg8j2dMUqlZBm3a+XT+Xt0o6UJJG/fYzj/lbdwg6TJJ2/TSTsu2j0kKSZuXeW5rhYJ5fw8AuwE7jFtmA8sTzCucCtwB7ASsAywGdumhnf2A3YElfcTyPGD3/PYGwK97jEVkFesApgO/APbqI66PAN8EvtNHG3cBmyd4v74GvCe/vQ6wcYL3/35ghy732xb4DbBe/vO5wDt7ePyXAkvIjntMA64Adu7ncwecDByX3z4OOKmHNl4CvBhYAMzpI5aDgGn57ZOKYunQzoYtt48BvtRLO/n67YFLyabF9v2ZbMpSdLBudRnMu8ctd+Ufkn7NBW6PiDsj4lngHOCwbhuJiJ8Aj/YTSETcFxHX57efBJaS/cJ3205ExIr8x+n50tP4j6TtgNcCp/Wyf0qSNiT75foKQEQ8GxG/67PZA4A7ImL8XPUypgHrSZpGlkiX99DGS4BrIuKpiFgFXAm8oezObT53h5H9wSL///XdthERSyOiq2tCtmnnsvx5AVxDdg5AL+080fLj+pT4PHf4nTyVbFqsZ1+1KJq+9u6I+GmbbSnKYG4L3Nvy8zJ6SH6pSZoNvJysN9vL/lMl3QA8CFweET21A/w/sg9tvwVWA7hM0nWSRnpsYyfgIeCMfKjkNEnr9xnXW4Gzu90pIn4LfAa4B7gPeDwiLuvh8ZcA+0naTNJM4K/Iemz92Coi7svjvA/Yss/2UvkfwPd73VnSJyXdC7wdmPBaliXaOBT4bUQs7jWOpurnmnUpTHTBl0r/UkqaBXwL+NC4nkBpETEaEbuR9UDmSnppD3G8DngwIq7rJYZxXhkRuwOHAO+TtF8PbUwj+6r5HxHxcuD3ZF+9eyJpHeBQ4Lwe9t2ErOe5I7ANsL6kI7ttJyKWkn1lvxz4AdnQ2KqOOw0hSfPIntc3em0jIuZFxPZ5G+/vIYaZwDx6TOJNV3UiXsaaPZDt6O0rZhKSppMl4W9ExAX9tpd/dV8AHNzD7q8EDpV0F9mQzWskndVjHMvz/x8ELiQbEurWMrKzKlf37s8nS8y9OgS4PiIe6GHfA4HfRMRDEbESuADYp5cgIuIrEbF7ROxH9lX6tl7aafGApOcB5P9XWiBL0lHA64C3R0SKTs43gb/pYb8XkP3hXJx/prcDrpe0dYKYhl7VifhaYGdJO+Y9pLcCF1cRiCSRjX8ujYhT+mhni9VHp5XNuz4QuLXbdiLif0fEdhExm+x1+VFEdN3rk7S+sjMiyYcSDiL7St5tPPcD90p6cb7qAOCWbttp8TZ6GJbI3QPsJWlm/r4dQDam3zVJW+b/Px94Yx8xrXYxcFR++yjg23221zNJBwMfJytR8FQf7ezc8uOh9PZ5vikitoyI2flnehnZwfH7e42rUao+Wkg2LvdrstkT83ps42yyscKVZG/wu3toY1+yYZEbgRvy5a96aGdX4Jd5O0uA4xO8RvvT46wJsrHdxflyc6+vcd7WbmQV9W4ELgI26bGdmcAjwEZ9xHIiWUJYAnwdmNFjO1eR/UFZDBzQ7+eOrELhD8l61j+kQ5XCDm28Ib/9DNnMpUt7jOV2smMwqz/PZWY7TNTOt/LX+UbgEmDbXtoZt/0uPGvij0vPJ3SYmVkaVQ9NmJmt9ZyIzcwq5kRsZlYxJ2Izs4o5EZuZVcyJ2MysYk7EZmYVcyI2M6vY/wcSZWj4GeDNqAAAAABJRU5ErkJggg==\n", 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\n", 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\n", 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\n", 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01PEyKIoS8anAYZJ+AewL/ETSw8B/5tvMzAZKROfLoCiqR/wc8G5JWwB75o9fFhFPjEdwZmbdGqSebqc6mr4WES8AC3sci5lZZcM4fc3ziM2sVkYGaDZEp5yIzaxW3CMeQ6qrlqSoR3xYonq7P5iQpvbq2kTfly0STUxPVUd4cqKDIM8n+NAnJYplSqJ6xKni2WPii0naWRRpPvMnUr2wBGo7RmxmNiwGaTZEp5yIzaxW3CM2M+uzkUaKgczx5URsZrUyjEMTw/erw8ysjUao46WIpKMl/UzSQ5JO71XMRWUwT5O0a6+e3MwstQh1vLQjaSJwAXAMWYmHd0jatxcxF/WIPwXcJukHkt4nabteBGFmlkrCWhOzgYci4uGIWANcDhzXi5iLEvHDwC5kCfkg4H5J35V0cl5/YkyS5khaIGnBrSseTBiumVl73QxNNOeqfJnT1NTOwNKm+8vydckVHayLiGgANwA3SJpM1k1/B3AOMGYPOSLmAfMAPrvbSUM4dG5mw6qbWRPNuWoMY41d9CSfFSXiDQKJiLXAtcC1kqb0IiAzsyoSZsplQPMxsl2A5ema/72iRPyXrTZExKrEsZiZVdbJbIgO3QHsI2kP4JfA24ETUzXerKge8c978aRmZr2SquhPRKyT9H7gemAicFFE3Jek8VF8QoeZ1UrKizNHxLeBbydsckxOxGZWKzHmMbbB1vNEnKpGc8srlfbBSKJ2JidqJ1U5zVQHOdYkiidFOc1Up46mqiOzLlE7C0lTvnJVojdo2wEqtLPO9YjNzPrLPWIzsz5LOUY8XpyIzaxW3CM2M+sz94jNzPpsxD1iM7P+GqAJHB1rm4glbUJ2Wt/yiLhJ0onAIcBiYF5ee8LMbGA0atgjvjh/zFRJJwPTgKuBI8lqdZ7c2/DMzLozjOUeixLxfhGxv6RJZEUvdoqIEUmXAgtb7ZTX9JwD8Nbps3nNtH2SBWxm1s4wHqwrOq9mQj48sQUwFdgqX78pbU4Mi4h5ETErImY5CZvZeGpIHS+DoqhH/AXgAbLKQ3OBKyQ9DBxMdtkQM7OBkqoEwXgqKoN5nqT/ym8vl3QJcBTwnxFx+3gEaGbWjdrNmoAsATfd/g1wZU8jMjOroI6zJszMhkodZ02YmQ2VWg5NVJWipiykGYCfPyFNDddUUp0NMzFRO6m+wKmmD22a4LuzKtFr2jLV9zhR/d9Jid7ktYniSfVznsIwTl9zj9jMaiXVxSjGkxOxmdWKe8RmZn3mRGxm1mdDeMk6J2Izq5da9ogl7QUcD+wKrAMeBC6LiOd6HJuZWdeG8RTntpNXJJ0GfB7YDHg1MIUsIf9E0uE9j87MrEsNdb4MiqJZhO8Fjo6I/0tWY2LfiJgLHA2c12onSXMkLZC04CcrHkwXrZlZgUYXy6DoZDr3+uGLTcnKYRIRj9FhGczXugymmY2jYUzERWPEFwJ3SLoVOBQ4C0DSdsCvexybmVnXBugkv44VlcE8X9JNwCuAcyPigXz9U2SJ2cxsoAzS2G+nOimDeR9w3zjEYmZW2TDOmvA8YjOrlcYQDk44EZtZrQzSQbhO9TwRD9KfCale7LpE7SSqQJjs93+qspzrEo3RrU3QzpREP5VPJPrybJkonv20Ikk7946kKQ27ZoDGZYevP+wesZnVjHvEZmZ9tk7j0yeWdAC/P/N4HfC+shdVTvXXsZnZQIgulorOBs6MiAOAT+T3S3GP2MxqZRyHJgLYMr+9FbC8zWPbciI2s1oZx+lrHwKul3QO2ejCIWUbciI2s1rpJg1LmgPMaVo1LyLmNW2/CdhxjF3nAkcCH46IqyS9DfgCWXG0rjkRm1mtdDM0kSfdeW22t0yski4BPpjfvYKsNk8pPlhnZrUyQnS8VLQcOCy/fQTZRTNKKSoMv5Wkf5L0gKRn8mVxvm7rNvv9rh7xra5HbGbjaBzLYL4X+KykhcBn2HCIoytFPeKvAc8Ch0fEjIiYAbwhX3dFq52a6xEf7HrEZjaOoot/lZ4n4ocRcVBE/FFEvCYi7izbVlEinhkRZ0XE401P/nhEnAXsVvZJzcx6ZRgLwxcl4kclfUzSDutXSNpB0seBpb0Nzcysew2i42VQFCXivwRmAPMl/VrSr4FbgOnACT2Ozcysa+N4Zl0yRVfoeBb4eL5sQNIpwMU9isvMrJR1A5ViO1Nl+tqZyaIwM0tkvA7WpdS2RyzpnlabgB1abNvA4Y00dVNTuHFimtqrL0lUkPjJRKfTpKr5nKqk7KRE3+8UdY1TXb9sSqLXlGri/gONNN/ldTU8k2CQDsJ1qigV7AD8Kdl0tWYCftyTiMzMKhiknm6nihLxdcC0iLh79AZJt/QkIjOzCmrXI46I97TZdmL6cMzMqhmJ+vWIzcyGyiDND+6UE7GZ1Uodx4jNzIZK7caIzcyGzTAOTfRkFmFzGcyrX1zSi6cwMxvTMJ7QUToRS/pOq23NZTDfuvnMsk9hZta1kYiOl0FRdGbdga02AQekD8fMrJphHJooGiO+A5jP2Ge/trxCh5lZv9TxYN1i4G8i4g+udyTJ9YjNbOAM0thvp4oS8SdpPY78gbShmJlVV7uhiYi4ss3mbRLHYmZWWQzQQbhOVZlHfCYdFIa/KVHpyRRlCKcGrE5QFvG5idXbADhiJE2J0B9NSPMeT0z0/V2ZaFJkqtKTKaqWrpiQJphdU9T2TChVydJBMlK3HnGKesSDJEUStuGSqHS0DZHaDU3gesRmNmTqODThesRmNlRq1yN2PWIzGzZ1nL5mZjZUBunU5U45EZtZrdRuaMLMbNg4EZuZ9dkwzppoO/Ve0paS/p+kL0s6cdS2f2uz3+/qEd++4g/KVJiZ9UyD6HgZFEXnQF1MNmf4KuDtkq6StGm+7eBWOzXXI549bZ9EoZqZFRvGwvBFQxN7RcSf57e/Lmku8D1Jx/Y4LjOzUkZi+AphFiXiTSVNiMheWUR8WtIy4PtAmgIHZmYJ1W6MGPgmcETzioj4EvB3wJpeBWVmVtYwjhEXnVn3sRbrvyvpM70JycysvEEa++1UlYKFZyaLwswskUZEx0sVkk6QdJ+khqRZo7btL+kn+fZ7JW3Wrq2el8F8ViOdPKzQtEb1IsCbFj9kXM1PVEc4Vd3e2ZGmPvKtjTSvayRB2dJUE+Unj3nZxu6tSlSKNdV3eXWi2tGpalmnMI494kXAW4H/aF4paRJwKfBXEbFQ0gxgbbuGXAbTzGplvGZNRMRiAOkPfru+EbgnIhbmj3umqC2XwTSzWulmyEHSHGBO06p5ETGvYggvBULS9cB2wOURcXa7HVwG08xqpZuhiTzptky8km4Cdhxj09yI+EaL3SYBrwNeDawEbpZ0Z0Tc3Op5XGvCzGql6kG4ZhFxVIndlgHzI+JpAEnfBg4EWibiREP1ZmaDYQBOcb4e2F/S1PzA3WHA/e12cCI2s1oZiZGOlyokHZ+fafxa4Fv5mDAR8SxwLnAHcDdwV0R8q11bHpows1oZr1OcI+Ia4JoW2y4lm8LWkZ70iJvLYN79wkO9eAozszEN4ynORfWId5T075IukDRD0ifzs0S+JuklrfZrLoN5wBZ7p4/azKyFiOh4GRRFPeIvkg0yLwX+G1gFvAn4AfD5nkZmZlbCeJ3inFLhmXUR8S8Akt4XEWfl6/9FUss5xmZm/TKMRX+KEnFzj/mSUduqF38wM0usjoXhvyFpWkSsiIh/WL9S0t7Az3obmplZ9wZp7LdTRac4f6LF+ocktZ0XZ2bWD4M09tsp1yM2s1oZxlkTPa9HPCPSDCWvTlDHdU2iWrCbJfr81iaKJ1U7g1RHGGBCgve5kSiWVPV2U03cT/UepzJIo7KDND+4U65HbGa1Mkg93U65HrGZ1UrtZk24HrGZDZthPFjnoj9mVit1HJowMxsqdTyzzsxsqGwUPWJJ20fEk70IxsysqmEcIy6a7Dx91DIDWAJsA0xvs98cYEG+zOlgUnXhYzqcnO12hiAWt+PP3MuGi/I3aEySGsCjo1bvQnZxvIiIPbtL+y2fZ0FEzHI7vWtnkGJxO+PTziDFkrKdOio60edjZMV9jo2IPSJiD2BZfjtJEjYz29i1TcQRcQ5wKvAJSedK2gKG8JCkmdkAKzz1PSKWRcQJZFfouBGY2oM45rmdnrczSLG4nfFpZ5BiSdlO7bQdI/6DB0tTgL0iYpGkUyLi4t6FZma2cegqEW+wo/RYROyWOB4zs41O0VWc72mx3EuHZTCLSDpa0s8kPSTp9JJtXCTpSUmLKsSxq6T/lrRY0n2SPliync0k3S5pYd5OpbrNkiZK+qmk6yq0sSS/+vbdkhZUaGdrSVdKeiB/n15boo2X5XGsX56X9KES7Xw4f38XSbpM0mbdtpG388G8jfu6jWOs752k6ZJulPRg/v82Jdo4IY+nIamjWQYt2vnn/LO6R9I1krYu2c6n8jbulnSDpJ3KtNO07aOSQtK2nby2jULBvL8ngAOA3UctM4HlCeYVTgR+AewJbAIsBPYt0c6hwIHAogqxvAQ4ML+9BfDzkrGIrGIdwGTgNuDgCnF9BPgqcF2FNpYA2yb4vL4EnJrf3gTYOsHn/ziwe5f77Qw8AkzJ738NeHeJ538lsIjsuMck4CZgnyrfO+Bs4PT89unAWSXaeAXwMuAWYFaFWN4ITMpvn1UUS5t2tmy6fRrw+TLt5Ot3Ba4nmxZb+TtZl6XoYN36MpiPjlqW5F+SqmYDD0XEwxGxBrgcOK7bRiLi+8CvqwQSEb+KiLvy2y8Ai8l+4LttJyJiRX53cr6UGv+RtAvwJuDCMvunJGlLsh+uLwBExJqI+E3FZo8EfhERo+eqd2ISMEXSJLJEurxEG68Abo2IlRGxDpgPHN/pzi2+d8eR/cIi//8t3bYREYsjoqtrQrZo54b8dQHcSnYOQJl2nm+6uzkdfJ/b/EyeRzYt1rOvmhRNX3tPRPywxbYUZTB3BpY23V9GieSXmqSZwKvIerNl9p8o6W7gSeDGiCjVDvA5si9t1QKrAdwg6U5Jc0q2sSfwFHBxPlRyoaTNK8b1duCybneKiF8C5wCPAb8CnouIG0o8/yLgUEkzJE0F/oysx1bFDhHxqzzOXwHbV2wvlb8GvlN2Z0mflrQUeCcw5rUsO2jjWOCXEbGwbBx1lerKLWWNdcGXvv6mlDQNuAr40KieQMciYiQiDiDrgcyW9MoScbwZeDIi7iwTwyh/HBEHAscA/0vSoSXamET2p+a/R8SrgBfJ/vQuRdImwLHAFSX23Yas57kHsBOwuaSTum0nIhaT/cl+I/BdsqGxdW13GkKS5pK9rq+UbSMi5kbErnkb7y8Rw1RgLiWTeN31OxEvY8MeyC6U+xMzCUmTyZLwVyLi6qrt5X+63wIcXWL3PwaOlbSEbMjmCEmXloxjef7/k8A1ZENC3VpGdlbl+t79lWSJuaxjgLsi4okS+x4FPBIRT0XEWuBq4JAyQUTEFyLiwIg4lOxP6QfLtNPkCUkvAcj/72uBLEknA28G3hkRKTo5XwX+vMR+e5H94lyYf6d3Ae6StGOCmIZevxPxHcA+kvbIe0hvB67tRyCSRDb+uTgizq3Qznbrj04rm3d9FPBAt+1ExP+OiF0iYibZ+/K9iOi61ydpc2VnRJIPJbyR7E/ybuN5HFgq6WX5qiOB+7ttp8k7KDEskXsMOFjS1PxzO5JsTL9rkrbP/98NeGuFmNa7Fjg5v30y8I2K7ZUm6Wjg42QlClZWaGefprvHUu77fG9EbB8RM/Pv9DKyg+OPl42rVvp9tJBsXO7nZLMn5pZs4zKyscK1ZB/we0q08TqyYZF7gLvz5c9KtLM/8NO8nUXAJxK8R4dTctYE2djuwny5r+x7nLd1AFlFvXuArwPblGxnKvAMsFWFWM4kSwiLgC8Dm5Zs5wdkv1AWAkdW/d6RVSi8maxnfTNtqhS2aeP4/PZqsplL15eM5SGyYzDrv8+dzHYYq52r8vf5HuCbwM5l2hm1fQmeNfG7pfQJHWZmlka/hybMzDZ6TsRmZn3mRGxm1mdOxGZmfeZEbGbWZ07EZmZ95kRsZtZnTsRmZn32/wFlzfyaFEbYTgAAAABJRU5ErkJggg==\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, axes = plt.subplots()\n", "for idx, c in enumerate(range(CYCLE_NUMS-1)):\n", " tmats = iter(glob.glob(f'tmat_Cyc_{c+1}/*'))\n", " dfX = pd.DataFrame(0, index=['0','1','2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14'], \n", " columns=['0','1','2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14'])\n", " dfY = pd.DataFrame(0, index=['0','1','2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14'], \n", " columns=['0','1','2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14'])\n", " for sFOV in range(0,NUM_FOVS):\n", " tmat_name = next(tmats)\n", " tmat_loaded = np.load(tmat_name)\n", " moveX = tmat_loaded[0,2]\n", " moveY = tmat_loaded[1,2]\n", "\n", " col = str(int(tmat_name.split('_')[6]))\n", " row = str(int(tmat_name.split('_')[7][0:3]))\n", "\n", " dfX.loc[row, col] = moveX\n", " dfY.loc[row, col] = moveY\n", " fig, axes = plt.subplots()\n", " sns.heatmap(dfX, vmin=-20, vmax=20)\n", " pl.suptitle(f\"Cycle {c+1} X-shift\")" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "scrolled": false }, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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imt96RVE/4ieAD0iaCeyUP35VRDwwHsmZmbWql0a6zWpq+VpErAWWdTgXM7PS+nH5mtcRm1mlDPfQaohmuRCbWaV4RDyKVL17axuLzisWS9Und/q0DUnipJrLevrJyUnizBhM9LoSnQRJ8f1J1Ud4Y6K+vQMT0lxFkKqP8JRJw0niSL1z5quyc8RmZv2il1ZDNMuF2MwqxSNiM7MuG66Vn8Ycby7EZlYp/Tg10X+/OszMxlALNb0VkbS/pFsl3Sbp6E7lXNQG8yhJ23bqyc3MUotQ09tYJA0AXwMOIGvxcKikXTqRc9GI+LPA1ZJ+KenDkrboRBJmZqkk7DWxJ3BbRNwRERuAs4CDOpFzUSG+A1hAVpD3AG6W9DNJh+f9J0YlaZGkpZKWfv/xexKma2Y2tlamJuprVb4tqgu1DVBfwFbl9yVXdLIuIqIGXAJcImkS2TD9UOALwKgj5IhYAiwBuPWlB/Th1LmZ9atWVk3U16pRjDZ30ZF6VlSIn5VIRGwELgIukjStEwmZmZWRsFKuAurPkS0A7ksX/k+KCvF7Gu2IiKcT52JmVlozqyGadC2ws6QdgXuBQ4DDUgWvV9SP+PedeFIzs05J1fQnIoYkfQS4GBgATo2Im5IEH8EXdJhZpaT8cOaI+Anwk4QhR+VCbGaVEqOeY+ttHS/EU6YOFT+oCes2pmn1mEKqpiJrnp6SJM7sRK0eU10aqlT/DhK0UE31kemz561LEueJRwaTxJk8MU37ylRqPdRoZ8j9iM3MussjYjOzLks5RzxeXIjNrFI8IjYz6zKPiM3MumzYI2Izs+7qoQUcTRuzEEuaTHZZ330RcZmkw4DXACuAJXnvCTOznlGr4Ij4tPwxg5IOB2YA5wP7kvXqPLyz6ZmZtaYf2z0WFeJdI+IVkiaSNb3YOiKGJZ0BLGt0UN7TcxHA8QteymHzFiRL2MxsLFU8WTchn56YDgwCs4FHgSnApEYH1ff4XLnbG/vxF5SZ9alasks7x09RIf4mcAtZ56HFwDmS7gD2IvvYEDOzntJbF383p6gN5pckfT+/fZ+k04H9gG9ExDXjkaCZWSsqt2oCsgJcd/tx4NyOZmRmVkIVV02YmfWVfjwp5UJsZpVSyamJsp5ck6bn7gSV/z03OKW3rj+ZPnVDkjjPrE/zY5w4kGbhT4qfVSqpPr9swkCa1zR3/lNJ4tx0x5ZJ4qRa6rXNYJrXlUIVl6+ZmfWVRJ8FMK5ciM2sUjwiNjPrMhdiM7Mu68OPrHMhNrNqqeSIWNILgbcD2wJDwB+AMyPiiQ7nZmbWsn68xHnCWDslHQWcDEwFXgVMIyvIV0nap+PZmZm1qKbmt14xZiEGjgT2j4j/R9ZjYpeIWAzsD3yp0UGSFklaKmnpOWvuTpetmVmBWgtbrygqxPCn6YspwEyAiLibgjaYEbEwIhYePGu78lmamTWpHwtx0RzxKcC1kn4D7A2cACBpC7K+xGZmPaV3rutsXlEbzK9Iugx4GXBSRNyS3/8QWWE2M+spvTT326xm2mDeBNw0DrmYmZXWj6smvI7YzCql1oeTEy7EZlYpvXQSrlkdL8RztlqXJM7aR6aWjhGJflEm+2zCRH9DTZ6YJpAmpPkGRaJJuiT5JGrF9fDqGUnipGo1OnfSM0nipGoNO1xrZgHW+Oi/8bBHxGZWMR4Rm5l12dA4fTCBpN3405XHQ8CH2/1Q5d75e8LMLIFoYSvpROC4iNgNOCb/ui0eEZtZpYzj1EQAs/Lbs4H7xnjsmFyIzaxSxnH52seBiyV9gWx24TXtBnIhNrNKaaUMS1oELKq7a0lELKnbfxkwf5RDFwP7Ap+IiPMkvRv4JllztJa5EJtZpbQyNZEX3SVj7G9YWCWdDnws//Icst48bfHJOjOrlGGi6a2k+4DX57ffQPahGW0pagw/W9LnJd0i6ZF8W5Hft9kYx/2xH/EZD7Q9f21m1rJxbIN5JPBFScuAz/HsKY6WFE1NnA38HNgnIlYDSJoPHE42FH/jaAfVD/fvffUb+vFCFzPrUzFOJ+si4lfAHiliFU1N7BARJ2wqwvmTr46IEwB3fDezntOPjeGLCvFdkj4laatNd0jaStKngXs6m5qZWetqRNNbrygqxO8B5gFXSnpU0qPAFcBc4OAO52Zm1rJxvLIumaJP6HgM+HS+PYukDwKndSgvM7O2DPVUiW1OmeVrxyXLwswskWjhv14x5ohY0g2NdgFbNdj3LPffM6v4QeMkVe9VEvXtTaUWaXruDiR6Y/ZSX+MJiTpxrVk/JUmczaen6c+9bqjhh6i3ZOrkoSRxekkvnYRrVtHyta2AvwYeG3G/gP/qSEZmZiX00ki3WUWF+EfAjIi4fuQOSVd0JCMzsxIqNyKOiA+Nse+w9OmYmZUznOoz0caRm/6YWaX00vrgZrkQm1mlVHGO2Mysr1RujtjMrN/049RER/oR17fBPP+plZ14CjOzUfXjBR1tF2JJP220LyKWRMTCiFj4juk7tPsUZmYtG45oeusVRVfW7d5oF7Bb+nTMzMrpx6mJojnia4EryQrvSA0/ocPMrFuqeLJuBfB3EfGcz2KS5H7EZtZzemnut1lFhfgzNJ5H/mjaVMzMyqvc1EREnDvG7jmJczEzKy166CRcs8qsIz6OJhrDz5yxvsRT/MnGDQOlY9RCydoiprBufZpWhtOnbUgSJ0XbSYDps9P8zNetnZwkzsNrB0vHmDPtmQSZwNBwmhWj281/PEmctU9MTRJn5uw0358Uhqs2Ik7Rj7iX9FIRtvGRoghbf6nc1ATuR2xmfaaKUxPuR2xmfaVyI2L3IzazflPF5WtmZn2lly5dbpYLsZlVSuWmJszM+o0LsZlZl/XjqokxV5dLmiXp/0v6jqTDRuz79zGO+2M/4u8/7pYUZjZ+akTTW68ousznNLI1w+cBh0g6T9KUfN9ejQ6q70f8ns22TZSqmVmxfmwMXzQ18cKIeGd++weSFgM/l3Rgh/MyM2vLcPRfI8yiQjxF0oSI7JVFxPGSVgG/AGZ0PDszsxZVbo4Y+CHwhvo7IuLbwP8E0nSaMTNLqB/niIuurPtUg/t/JulznUnJzKx9vTT326wyPfmOS5aFmVkitYimtzIkHSzpJkk1SQtH7HuFpKvy/TdKGrPfaMfbYE6cmGbifHhj+T6uvdb/d3DKxiRxnlw3pfhBTVCiNqFrV6fJZ9b08j1u5wym6ZNbS9SrOZXVD85MEmd6ovdgqnx2SBBjHEfEy4F3AP9Rf6ekicAZwN9ExDJJ84Axv9Fug2lmlTJeqyYiYgWA9Jxf0m8CboiIZfnjHimK5TaYZlYprUw5SFoELKq7a0lELCmZwouBkHQxsAVwVkScONYBboNpZpXSytREXnQbFl5JlwHzR9m1OCIubHDYROB1wKuAdcDlkn4bEZc3eh73mjCzSil7Eq5eROzXxmGrgCsj4mEAST8BdgcaFuI0n2RoZtYjeuAS54uBV0gazE/cvR64eawDXIjNrFKGY7jprQxJb8+vNH418ON8TpiIeAw4CbgWuB64LiJ+PFYsT02YWaWM1yXOEXEBcEGDfWeQLWFrSkdGxPVtMM96dFUnnsLMbFT9eIlzUT/i+ZK+LulrkuZJ+kx+lcjZkl7Q6Lj6NpiHzF2QPmszswYioumtVxSNiL9FNsl8D/CfwNPAW4BfAid3NDMzszaM1yXOKRVeWRcR/wYg6cMRcUJ+/79JarjG2MysW/qx6U9RIa4fMZ8+Yt9A4lzMzEqrYmP4CyXNiIgnI+KfN90p6UXArZ1Nzcysdb0099usokucj2lw/22SxlwXZ2bWDb0099ss9yM2s0rpx1UTHe9HvO6pya3mNKoU37NUfYRTqUWaHrczp69PEieV2nCa1xU91gM4hed2TGxPqj7CqfRSPr20PrhZ7kdsZpXSSyPdZrkfsZlVSuVWTbgfsZn1m348WeemP2ZWKVWcmjAz6ytVvLLOzKyvPC9GxJK2jIgHO5GMmVlZ/ThHXLTYee6IbR6wEpgDzB3juEXA0nxb1MSi6sLHNLk423H6IBfH8c/c27M35d+gUUmqAXeNuHsB2YfjRUTs1FrZb/g8SyNioeN0Lk4v5eI44xOnl3JJGaeKii5x/hRZc58DI2LHiNgRWJXfTlKEzcye78YsxBHxBeAI4BhJJ0maCX14StLMrIcVNv2JiFURcTDZJ3RcCgx2II8ljtPxOL2Ui+OMT5xeyiVlnMoZc474OQ+WpgEvjIjlkj4YEad1LjUzs+eHlgrxsw6U7o6I7RLnY2b2vFP0Kc43NNhupMk2mEUk7S/pVkm3STq6zRinSnpQ0vISeWwr6T8lrZB0k6SPtRlnqqRrJC3L45Tq2yxpQNLvJP2oRIyV+advXy9paYk4m0k6V9It+ffp1W3EeEmex6ZtjaSPtxHnE/n3d7mkMyVNbTVGHudjeYybWs1jtPedpLmSLpX0h/z/c9qIcXCeT01SU6sMGsT5l/xndYOkCyRt1macz+Yxrpd0iaSt24lTt+8fJYWkzZt5bc8LBev+HgB2A7Yfse0A3JdgXeEAcDuwEzAZWAbs0kacvYHdgeUlcnkBsHt+eybw+zZzEVnHOoBJwNXAXiXy+iTwPeBHJWKsBDZP8PP6NnBEfnsysFmCn/9qYPsWj9sGuBOYln99NvCBNp7/5cBysvMeE4HLgJ3LvO+AE4Gj89tHAye0EeNlwEuAK4CFJXJ5EzAxv31CUS5jxJlVd/so4OR24uT3bwtcTLYstvR7sipb0cm6TW0w7xqxrczfJGXtCdwWEXdExAbgLOCgVoNExC+AR8skEhH3R8R1+e21wAqyf/CtxomIeDL/clK+tTX/I2kB8BbglHaOT0nSLLJ/XN8EiIgNEfF4ybD7ArdHxMi16s2YCEyTNJGskN7XRoyXAb+JiHURMQRcCby92YMbvO8OIvuFRf7/t7UaIyJWRERLnwnZIM4l+esC+A3ZNQDtxFlT9+V0mng/j/Fv8ktky2K9+qpO0fK1D0XErxrsS9EGcxvgnrqvV9FG8UtN0g7AK8lGs+0cPyDpeuBB4NKIaCsO8GWyN23ZBqsBXCLpt5IWtRljJ+Ah4LR8quQUSdNL5nUIcGarB0XEvcAXgLuB+4EnIuKSNp5/ObC3pHmSBoE3k43YytgqIu7P87wf2LJkvFT+FvhpuwdLOl7SPcB7gVE/y7KJGAcC90bEsnbzqKoyn1mXwmgfHNPV35SSZgDnAR8fMRJoWkQMR8RuZCOQPSW9vI083go8GBG/bSeHEV4bEbsDBwD/IGnvNmJMJPtT8+sR8UrgKbI/vdsiaTJwIHBOG8fOIRt57ghsDUyX9L5W40TECrI/2S8FfkY2NTY05kF9SNJistf13XZjRMTiiNg2j/GRNnIYBBbTZhGvum4X4lU8ewSygPb+xExC0iSyIvzdiDi/bLz8T/crgP3bOPy1wIGSVpJN2bxB0hlt5nFf/v8HgQvIpoRatYrsqspNo/tzyQpzuw4ArouIB9o4dj/gzoh4KCI2AucDr2kniYj4ZkTsHhF7k/0p/Yd24tR5QNILAPL/d7VBlqTDgbcC742IFIOc7wHvbOO4F5L94lyWv6cXANdJmp8gp77X7UJ8LbCzpB3zEdIhwEXdSESSyOY/V0TESSXibLHp7LSyddf7Abe0Gici/ndELIiIHci+Lz+PiJZHfZKmK7siknwq4U1kf5K3ms9q4B5JL8nv2he4udU4dQ6ljWmJ3N3AXpIG85/bvmRz+i2TtGX+/+2Ad5TIaZOLgMPz24cDF5aM1zZJ+wOfJmtRsK5EnJ3rvjyQ9t7PN0bElhGxQ/6eXkV2cnx1u3lVSrfPFpLNy/2ebPXE4jZjnEk2V7iR7Af8oTZivI5sWuQG4Pp8e3MbcV4B/C6Psxw4JsH3aB/aXDVBNre7LN9uavd7nMfajayj3g3AD4A5bcYZBB4BZpfI5TiygrAc+A4wpc04vyT7hbIM2Lfs+46sQ+HlZCPryxmjS+EYMd6e315PtnLp4jZzuY3sHMym93Mzqx1Gi3Ne/n2+AfghsE07cUbsX4lXTfxxa/uCDjMzS6PbUxNmZs97LsRmZl3mQmxm1mUuxGZmXeZCbGbWZS7EZmZd5kJsZny2vR8AAAANSURBVNZlLsRmZl3236BBVdnp3GQpAAAAAElFTkSuQmCC\n", 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\n", 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"text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, axes = plt.subplots()\n", "for idx, c in enumerate(range(CYCLE_NUMS-1)):\n", " tmats = iter(glob.glob(f'tmat_Cyc_{c+1}/*'))\n", " dfX = pd.DataFrame(0, index=['0','1','2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14'], \n", " columns=['0','1','2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14'])\n", " dfY = pd.DataFrame(0, index=['0','1','2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14'], \n", " columns=['0','1','2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14'])\n", " for sFOV in range(0,NUM_FOVS):\n", " tmat_name = next(tmats)\n", " tmat_loaded = np.load(tmat_name)\n", " moveX = tmat_loaded[0,2]\n", " moveY = tmat_loaded[1,2]\n", "\n", " col = str(int(tmat_name.split('_')[6]))\n", " row = str(int(tmat_name.split('_')[7][0:3]))\n", "\n", " dfX.loc[row, col] = moveX\n", " dfY.loc[row, col] = moveY\n", " fig, axes = plt.subplots()\n", " sns.heatmap(dfY, vmin=-20, vmax=20)\n", " pl.suptitle(f\"Cycle {c+1} Y-shift\")" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "f0d71354381a4e0094eae8de5dc22326", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(IntProgress(value=0, max=9), HTML(value='')))" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "# We are trying to look for registered binaries that have intensity percentage less than 0.1 percent (< 0.001)\n", "\n", "hist = pd.DataFrame()\n", "\n", "err_lst = []\n", "for c in tqdm(range(CYCLE_NUMS-1)): \n", " binas = iter(glob.glob(f'reg_bin_Cyc_{c+1}/*')) \n", " if c == 7:\n", " for FOV in range(0, NUM_FOVS): # \n", " #sFOV = str(FOV).zfill(NUM_DIGITS_OF_FOVS)\n", " bina_name = next(binas)\n", " bina = imread(bina_name)\n", " bina = bina.astype(np.uint16)\n", " FOV_num = bina_name[-15:-12]\n", "\n", " percentage = (np.sum(bina))/(2048*2048) \n", "\n", " if percentage < 0.001:\n", " err_lst.append(bina_name)\n", "\n", " hist.loc[FOV_num, f'{c+1}'] = percentage # this is the table of percent of signal in images\n", " if c == 8:\n", " for FOV in range(0, NUM_FOVS): # \n", " #sFOV = str(FOV).zfill(NUM_DIGITS_OF_FOVS)\n", " bina_name = next(binas)\n", " bina = imread(bina_name)\n", " bina = bina.astype(np.uint16)\n", " FOV_num = bina_name[-15:-12]\n", "\n", " percentage = (np.sum(bina))/(2048*2048) \n", "\n", " if percentage < 0.001:\n", " err_lst.append(bina_name)\n", "\n", " hist.loc[FOV_num, f'{c+1}'] = percentage # this is the table of percent of signal in images\n", " else:\n", " continue" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "b978bd5099444c85be16345cf7d3f1f3", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(IntProgress(value=0, max=9), HTML(value='')))" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "# We are trying to look for registered binaries that have intensity percentage less than 0.1 percent (< 0.001)\n", "\n", "hist = pd.DataFrame()\n", "err_lst = []\n", "min_lst = []\n", "\n", "for c in tqdm(range(CYCLE_NUMS-1)): \n", " binas = iter(glob.glob(f'reg_bin_Cyc_{c+1}/*')) \n", " for FOV in range(0, NUM_FOVS): # \n", " #sFOV = str(FOV).zfill(NUM_DIGITS_OF_FOVS)\n", " bina_name = next(binas)\n", " bina = imread(bina_name)\n", " bina = bina.astype(np.uint16)\n", " FOV_num = bina_name[-15:-12]\n", " \n", " percentage = (np.sum(bina))/(2048*2048) \n", " \n", " if percentage < 0.001:\n", " err_lst.append(bina_name)\n", " if percentage < 0.01:\n", " min_lst.append(bina_name)\n", " \n", " hist.loc[FOV_num, f'{c+1}'] = percentage # this is the table of percent of signal in images \n", "hist.to_csv('reg_bin_df.csv')" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/html": [ "
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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import pylab as pl\n", "fig, axes = plt.subplots()\n", "for c in range(CYCLE_NUMS-1):\n", " hist.hist(column=f'{c+1}', bins = 80, range=[0, 0.3])\n", " pl.suptitle(f\"Cycle {c+1}\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import pylab as pl\n", "for c in range(CYCLE_NUMS-1):\n", " if c == 7:\n", " hist.hist(column=f'{c+1}', bins = 30, range=[0, 0.3])\n", " pl.suptitle(f\"Cycle {c+1}\")\n", " if c == 8:\n", " hist.hist(column=f'{c+1}', bins = 30, range=[0, 0.3])\n", " pl.suptitle(f\"Cycle {c+1}\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# finding the intensity sums of each image and finding which z stack is the max\n", "df = pd.DataFrame()\n", "\n", "for c in range(CYCLE_NUMS):\n", " if c == 0:\n", " refs = iter(glob.glob('tif/Cycle_0/*'))\n", " for FOV in range(0, NUM_FOVS): \n", " ref_name = next(refs) \n", " ref = imread(ref_name)\n", " ref = ref.astype(np.uint16)\n", " FOV_num = ref_name[-7:-4]\n", " print(f'cycle {c} field {FOV_num} ')\n", "\n", " Z_ch0 = []\n", " Z_ch0_dic = {}\n", "\n", " for Z in range(ref.shape[0]): # Z \n", " for ch in range(0, 1):\n", " arsum = np.sum(ref[Z, ch, ...])\n", " Z_ch0.append(arsum)\n", " Z_ch0_dic[arsum] = Z\n", "\n", " df.loc[FOV_num, 'max_int_C0'] = max(Z_ch0) \n", " df.loc[FOV_num, 'z_idx_C0'] = Z_ch0_dic[max(Z_ch0)] \n", " else:\n", " ims = iter(glob.glob(f'reg_Cyc_{c}/*')) # cycle 1, 2, 3, .tif list --> FOV000, 001, (002 = error) 005 006 \n", " for FOV in range(0, NUM_FOVS): # \n", " #sFOV = str(FOV).zfill(NUM_DIGITS_OF_FOVS)\n", " im_name = next(ims)\n", " im = imread(im_name)\n", " im = im.astype(np.uint16)\n", " FOV_num = im_name[-11:-8]\n", " print(f'cycle {c} field {FOV_num} ')\n", "\n", " Z_ch0 = []\n", " Z_ch0_dic = {}\n", "\n", " for Z in range(im.shape[0]): # Z \n", " for ch in range(0, 1):\n", " arsum = np.sum(im[Z, ch, ...])\n", " Z_ch0.append(arsum)\n", " Z_ch0_dic[arsum] = Z\n", "\n", " df.loc[FOV_num, f'max_int_C{c}'] = max(Z_ch0) \n", " df.loc[FOV_num, f'z_idx_C{c}'] = Z_ch0_dic[max(Z_ch0)] " ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.4" } }, "nbformat": 4, "nbformat_minor": 2 }