dafDiscovery_Case IV - option-3.ipynb

{
 "cells": [
  {
   "attachments": {
    "dafDISCOVERY_icon_small-01-01.png": {
     "image/png": 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Q3gMhfTRHId1lW0c9bkctryUvrp2ynD4qKuKQHrp21ITvCXlHjo6ora2t1E90MQRL3yvj+CrFCbX/09g+H2UnvrZXJwiarqhkGy7HxidSD8nbv5dpjt6H/u75PI5Nt6NcHjLaj4T03gjpgzkK6S6lJn0qjjr+qiKkE9JTrh3NoqzE1+Xi0Ot3h6qj9VmX7qstQ4WbtAO6j9Is145xt/c1GRF1ufpis7TqzqA3OTWtjhwdsSo5svmcsV5p8Xkcb966bXRs2rw3IZ2QHlV7OIxgL0Q0ol9ThPSeD+lp146m+IPvPVSGXM7QNeCkcQUgrYBuu1pEWtvnM5C5XjnpdsXBdETUttTIZW7Ctevr93TKy+Uhq7K4EJOXswrpPn+TTVfrsXlvQjohPZr2cKwFn1Tx1MZnWvJCSM8+pIdalSOWMOxzNMrnBME0A7pt6MpiG13aOuuAbhNUfLRpt3kbNse/aamRbUej0dhqe8XE5IpS6wpGmsdn7B03l6totu/NxFFCekwh3aXU5YCKa2JhVRHSezKkz8xWVKOxFd1JzWcY9jUa1WhsBRtF1w0Xrp0Nl5rpNAOQzSh6ViUuLp0h05IOmxIb29WZTMq6bEPdtevrbY9J04mfrRAc42CDUuZlez6/a6YlWC7v7ak8kZCeg6Ceh5Buuz75WqDtmcxjyQshPbuQnuYawqYnT19h2OdnDHWbb92gNjNbcf48tifRtEcoTds6poCuG9J9rUDSqa1c6rN1yyNcRl13C482t7uPZclF1ysrPjputt95l++5xwn1hHRCuvP2DaQZ0DS36UAeS14I6dmE9DSWpbu5salOzs0b17v7CsM+J5Dd3NgMcpdR3fKMVjmD62eyCelpB3Sbtg4xn6J67rx1iE5jomi3UdJSqd9pZFlnH4QYpTc9xlulMlnfWXS3/WNy9cr30pEmy9e6dnI8TvInpBPSnbfvlMP2DQTcrrW8lbwQ0tMP6aFPZteur99zcjCZAObr1tKlUr/avHU7s8vVIQJ6FiE9ixpf0230fbOt5ZVVVS4POV21SOvmT51CmEu76JSb2R4bnbbZdILr9lrrGEtdTCdr+lz61qRk0HUuh89J/oR0QnqWpS43VLydh5oipBc+pIcM6Msrq20Dlsl7+hpF9zmyGmLJRZuAvm2Z2egvfafV1j5LHOr1xt1R2VKp32muRhrlDJ2Cket7dAuXtu3eKaCblixdu75+T4c+NqY3YfNZmmcSml0DeoC5OoR0QnpmZSWnIi7DyaTkhZCeXkgPFdB3C+dZjaL7DG4hylx0L2nvtka4C91L71kE9J2hK83SgEuXr9zz3i6BqduqKD5q5+v1Rsdg5DIi26222HY5x04dMNOA3q6MJCam6/v7LM0z+R75WA0pwFwdQjohPbMJmsMq3lH+TEpeCOnphPQQAf3mxmbX0SKTsOBjRRefZS6NxpbTaiguYaRTW7gEsFgDumntrq+rJfV6475j2DX8dxrF9DVa2ikEunZSuwVMm05GpzbxEdB9hvRara6WV1ZV9dx5NTNbUWPjE0F/x3x2NtMO6L7vCE1IJ6RnWfddS6ntqnkqeSGkh/+N8FX/2q4swOf7+rhk6vOSsenl6jQCuktI11l94cjREa9Lcp4+c1arVti0dtfH1ZJr19fbHnOux9BuI4u2I9DtRv07tY1LbXaI5Ry7TW71EdBtP/fyyqq6cHFRnT5zVo2NT7TdTpPPbDPQ4Ks0z6Sj6+t+Ar4HMQjphPQsS12qKbXdcJ5KXgjpYX8jfN8iu3ruvNZIje0tvV0epncozGNAd5kQ2O21fY7o3dzYvFsC5butXVct6VZ64doGu5V++Qhj3W7t7noVpFPpgm2d+27tYRoUd+tU2XaudL5rJp1Bm98wX6V5JgHd170xQi1JS0iPP6APRBzSRx22azQnnZyqIqQXIqT7DF2tFS9CjdL4GJHxtTJCzAHdZaQ3xF0pdTpynQK1TVu7jnR3ek8fpT4hO8vdvichR9Ftjo/djmnToLhzzoDrqLTOZEeTKx82ZR++fp9NA7qvspqA50dCeuQhfTDikL7gsF19KbbhQl5KXgjp4X4jfI3cmZQi2AR0H8t3+QhB9XojyFKLOvvBZBTONqR2Cjk+yoTq9UbbY6XdyP9ufxsy2OiEGdfvzG7Hso8OZLcOjeuobIjOy84gbHrPBKXMJ2GePnO26zGiMwqsu8+6Xd0IuXRoFgE9YJkLIZ2Q7rRdfQ7btJByG47mpeSFkB7mN8JHaD195qzRyce2ztHHyLVruLKZuOhrwq7pZXKbQN3pPXwsCdhppLNU6lfVc+fVzY1NVavV1YWLi9bzD2w7Ezr7t1Tqd26HdoHSx3dRZ2lKl+9At5FRmxH6ncfcybl54/IW2+9kp++dztwMk+PMZht9lOZt3rqt/d4+7yUQsMyFkN4jIX0gwuA7mXIb9uWl5MUxpFdUweZj+PqNcBm5szk5jo1PWAX0bpfY0zjh5Smg2wbVUMv1NRpbxiOdLg/bY0xn//qoD27Xzq4dSJ1jxLWD0ekKkm27tNp8bHzCuFTGJQh2295uV8tMOq222+l6ZcVkFRefK3sFLnMhpOckjDhNfAy4XS6rphzIoB3X8lDyQkj3/xvhMnJnc+Mel8uoPiaMuqxek7eAbjMq1ul9XI4Vl5FOm4ftcaZbwuRa8tOu1MW1A6l7jLh0MLp95206GTc3NtXk1LRxGF1eWXU6prrVkeuEat0OhW1gdb1ypRvQTVfOiaDMhZCekzBSiTSk1yy3aS2jdpzMQ8kLId3/b4TtyEkWk/hs6pJ9jVSGCOilUr9W+7vcxdQ0+HQaRbc9Vi5cXPR+k6cQ+9lkpNN1dLPd98fl+2HSibMtZ+h2JctHCZBu6YZr2Vu3UKoTqkOXubiObOtOoD1ydMR5BSTb71Kp1O86t4eQTkhPdXS/klE7HshDyQsh3f9vhE1JQLe1l0NdRvUR9Gq1ehSjQronRtcwYrJ/u51Ys5pDkEapi+ndYm2Po05h1zYomV5lse1gdAtToW9sVa83jOe+2Pwe6ZTVmVz1cLkCaDvxWfc9Z2Yr3lb1srlq8NrrP3X9fSWkRx5GXMpK1iLcprw+aoT0/IV02/IFk4l8pVK/l9UqfKzqYltO4DtoTk5Na50YXct7TC6Vdzux2hwrWQX0NLbV9yij7bFpc4yEKHMpl4e8l0u0NBpb3sK5TsmbTmA0Wb7Rdrttf5915334nCBqM6Cx/f0dRtMJ6apAE+R2PJYCbdONHgzpqZS8ENL9fi9s6rNNQoHPOkcfqwTYnPRcSk18tLnL6KHu1Yt6vdG142VaipHmBFEfZSOm7evC151LbdrYpiSlW12z7UTwNEfOdevxdTprJr8jtr9btp0ene0P2aHS+bztBm4I6cUN6S6BeCHA9gz0aEBPpeSFkO73N8ImGOjWhfu6lbTPenSbTomvgKBbf94psJi0gcnIbLcTpO7Iv0s5VJZtbDOpz2ftuM2Ipm1AX//kl15HRn2smZ9GONe5qqd7NcXkyqDN8qG2nR6d753pd9n39+jI0ZG2HQRCenFDuooptInIqR4O6TVCerFDer3eCHqSCVkTblMv66PExvfIle8g0e31fC/hGOrhMvktrZKRnbXOuwWWEN8H24C+WwfZZdt3c3NjU83MVoJMMu72HdQd8TYZRU9ryVSd77LNjaF8H5OdzguE9AKGdA+j1pOKUpdclbwQ0rMN6TonnVCTx7JYjs9HiY3vkatGY6vryVB3ZLbbSd1mLkFKayN7Hc21qZ13qes+cnTE+aqKaUC1Deg7r+KMjU94XUu7NQIc4u69uoMGJiVtJt8J0ytfrp2e3To3IUfPdduw22+wQ8eMkB5xEBl2/PIOet6eAz0e0IOXvBDSsw3pvkddN2/dDh7SXSZHuYb0UBOzOq1EorsPOu3LsfEJo30T4uqDbrDxMSnZ5ipNqJpe323su+wsixrmkCVuJh0008m9Jtvouo/albqUy0PBR8+7/R7pzI356B//F0swFjSku94i/oDn7ZkkpIcteSGkZxvSfa6hXa83tEe4bUdnXUf8bGurQ5QCdBu5MqnH7hRMQtykJ1T48hE+TUelQ9yZMVSwjT2ghwzpOt8H0++3Sadb53tw5OiIl07mzu90qdSvTp85m9q+3+0qiM4+2NraUv/xPx0lpBc0pC/EtEa64107KXkhpEe/uouvyXqtGwPp1neaBj9fyz6ajrK2To5paZ0cJ6emtUa+6/XGridUXx2L0OUuvkbPXTsVodcEtwlFeQvouiV0ITrJOmuhu6xj36nzVy4Pee/ktW4YlmY477T/dFf28lDmREiPOIi41H+vKUpdclfyQkjPbp30dmHGdonF1g+zbqC9ubGZ2Si27p1GZ2Yr1iUitjZv3dYOrNeur7f9HCE6FqHuLhqiA2Q7kptlSO82MTeLbbP9zvm+8nJybl41GltevtOu69hfunzl7vuUSv1qcmo60yswvu3W0dE9L3i6jwIhPdIQEtUdMkVklHAevuSFkO73N8LkxLNzZMh2NY3tP8wmoSurVWW2jxhtH/VpnXSr584bv+fyyqrX0WDdUbY07jYYooRhcmra6FgzOa5MlzIslfqDzDUwuYNp2h2Zbh3FI0dHnN7XR6fO5AqLzXKuaXd8WstQZkH3u+ay6o/HG50R0lUxJ41OqohKbyh5IaRnEdJNL+GePnNWlctDqnrufNfRKp0fZpOg2m3kK6sTms2IYxrLoSl1ZyWYnW3eGjk32e8XLi52vQnMzoDhYxnGsfEJ485M6/Pqhl6TlT1CrJLRWjnF5HOGWIffRvXc+bsB2+T48B3YTEo8bN8rzd+X1ki/zY2n0uoYtLsColti5flGZ4T0SEPIqbR2rMa29BHK0yl5IaT7/41I68Te7uRoEkx2G501KW9JewS702V2mxsrmXYGWu81Nj6hTs7NW3UMWjWnR46OWHVGbMO5zXG5/RjT/aw6pQ82nQXd47HVmTEJgTs7QK4lXvV6Q52cm9fuuC2vrN5XS2x7C/tOZRM6o9smnU2XzkBavxvrn/zynuMxrVWEWt8Dnc/ZaGy1PQZ1AnqAOQiEdFW8enRFqUs+S14I6f5/I9K4jLvbyIntKKlNkGuFxlDLIuqc2LaffE1DbxZ27jfTUeTNW7eNJobNzFasw9DOAGZyXNfrDVU9d16NjU/cDYulUr/T9nQrJ9i5vSYj0RcuLqpyecjLfIKdnZSZ2Yq6dPnKPVcibm5squWVVXX6zNldOzSux/O16+taV19KpX6jDoWvcJhGSG/XsQ3dmd/+vrrfmZ0DJhkGdEK6KmY9uu9Jo1VCedvHKCE9/pAe+pJqpx/mLEawXS7L+76SYHuHzCzKZExGp9uNvM7MVu4LeNtH+F3KSNpta9qlAjpXcDqF3Cy212YCpe8bPLUrt9i+TaVSv9OVIF/hMHRI3+3Kk82EVdO2KZX6VanUr/Ud3DmJX7cEzHY5W0J6PgOI63rkpzxvT41A3vaxQEiPP6S7hC/Xk2Nadp70YwjoWa8QYhPc0hjV8xkys1pJwzb4pnmDJN8BPc2SkLQDeuhjqVtpWKh23T4fQ/fzbb8yZnKfi1ArPhHSC7g+us9JjR4msBb90UdIjz+khxhd1jk5ZhWQ05i02S2gx3DnStOTaehRPd8hM4uSIpe657Q6QSECesg77GYd0ENOHNUJsCE68ztLB3VsHw2PJKAT0gtY6uI1ODqWupxSBa/9913yQkgP9xvhs/RC9+RY9BFsncB25OiI1Uo5IUfVYh8tNQmZMXXIsi49CxnQY5tnYbJqT1Zzd0w6Eb5+n9vd0ExnoGD7ZFHdtvC1yhMhvbdKXZYiCrGDOWjvUzGVvBDSw/1G+DoJmZwcszxJh74rn0lgy7LspbUEYB62tTUyZ3LiT2v039e6zyHLKnauHBLiEcM8C49rcAc7jkw7ET6+d6017W2u3rQmi5oE9NDHGiE9zvCxFsv66CIyEOMNfzy392BkVy4I6QF/I1xPsKYnxywvc3J3ebUAAAnzSURBVIe6fG17csoi/G5fAjAPQcz20nnoNa59hsJQnYoUyg4yv1/BbhOefT18lKa5bKPL967d/tedLLp567bR6i9KKaNVnQjpBQnpngLjgUhGmRdy1O61WEpeCOlhfyPSviFJiLCnewlZ9wQVcpQ3q5rkRmPL6YYiWXQoYl1CL0Qo9F3bnVZAD/W9imXk1vW4v7mx6bSNtr/Pu43a6161mZmtGH32kB0lQnrcwcN1qUPfSy/ekEhqtSNv9wVFSM9FSLep4XUZGfIdnEyDnM8Js62lzGKsffUxep7lhNfdbmRlGh59bnO72t4Yg+6ly1dSC+hZrQKUZifE9hjytR9Mfp/r9cauv826k0VbS4em+V0lpPfuhNHJiLbnQI7afjiWkhdCevjfiFKpX23eup3K6JXPEUPbkWHXGmDTmm7dCXi+rzLc3Nj0up1pTBL03ba+grrrFRPdu65mffUhD8sx+p4gqnPcm3SgQhzDOr/P3Trjut8Dk9+hjI43QnokoWMhlqCo3CewruWw/aO4sREhPZXfCK0TkY/RK1+jxq6XV22Duq/R891Oxj46Me3ubpmHEdNQQdilXRuNrVRHCm2/H6Frs7O4ctGuTjrFumfjTnTrxkwhfh86/T7X642uAxYhvrfLK6tZHWuE9ILUolc9b9NaL4VFD52kBUJ6fkJ6txOBr6DiuuSczzrUk3Pz2iNkrduyp3ESKpeH1IWLi8blD627fIbevhCrkaQRhMfGJ4xGe9Pc5y5B/dr19bRW1dD6DQkR1EOFX9PfrpNz8/d8vlqtri5dvqJOzs0H375SqV9duLioarX63f2u876h5uJkuD8I6RmHjT4Pa3V7/dweSl0Gchj6RmO4kkFITy+kbw+IrRPBpctXvAcA25C3vLLq/cTQWsHg0uUrdz9z6+S7vLKqTs7NZxLUWts2OTWtqufOtw2X166vqwsXF9XMbCX1bfQV1LMImEeOjrRt05sbm+rS5StqZraSeSCcnJruWuLQGrmN7YZ2pVK/t9KXrDpKRXr47lSntBY6IT3isHHKw068EVFgreU09PXFUPJCSE83pKc1Umxa45n1pXwefpfeY5/qj6rv7EC2Oo9ZdyR0tt1mnoXuCDGPdOY57BTBVRtCes5Hb0Pc9dKl9KPaw8FvgZBOSLetgQ9Z48kjmxKSVr08+7S3jpHWlYvtnY3tV6yyuiJU9IfvybyRdKwJ6RmFjAERqXvYgTcjG1EezXHwm/SwP/oI6YT0TjWe20/e20s4CHL5CmIXLi7eV498c2Pz7pJusdRN8+DRK1dh8jZvhJAed0CvRTqKPpplSM14vxzIen8Q0osb0nnw4MGDR5gBEN1ldWNf2tMl0/6OwFmSJKMi8o8istfDy20opaqeN3HQ4blXlVKf5XXfKKVuiMhVx5cZ5igHACAdz0xNy74HP+/lta6vfyLf++5zuWwHQrpbOO9LkuSUiPxURPZ4etnvB9jUxx2eWy3ArlpyfP7hJEn6OOIBAAirXB6S0Se/4eW1Go0tOfzYY/LrX/+KkN5jAX1U7qw7/ozHl73qexQ9SZJhcRvhXyrA7vLRpoymAwAQ2MTx4/K5z/0r59fZ2vqtjI0fy21AJ6SbB96+JElGkyS5IXdGz/d7fovJAJvtEi4/VUqt5X2/NT/Dp4R0AADiNTY+IX85/JiX15r70bz8/d/9ba7b4wEOia7BfEDu1HQPisjhgG/1plJqKcDrDjo8d6lAu3JB3K56HE6SpC/P9fkAAMTs2LFjXl7nx6+8Kj/8QSX37UFIvxPEB3eE2j65s1rLgIj8bgqbUJcAo+jNDobLaP9CgXbzkriXJg1LMWr0AQCIytj4hBw6+LDz67z/wYfynW8fL0Sb5CWkf5gkSZGPzcOBRmhHPQTbQlBKLSRJUhe3+nxCOgAAATz/vPu6GdfXP5FvHX+6MG1CTXr2/iZQmUsrVNr6qIClHRddO1Os8gIAgF8zsxX54hf2Ob1Go7Elz049m+uJooT0uFxVSoWYLCpJkhwQSl1CfCYmkAIA4NHExLjza0w9Oy3vvffzQrULIT07G+I2qTN0mCxiSF8ipAMAEA8fo+g/fuVVeeP11wrXNoT0bNRF5LHA5SSjDs/9tHmnzkJptvei48tQ8gIAgCfHj084Pb9IE0UJ6XEE9EdCrj/eLHV5yOElFgrc/pS8AAAQgZnZiux78PPWzy/aRFFCesEDetOg4/OXCrwPfHw2QjoAAI5catG3tn4rlcqJQk0UJaRn56qIPJTSHTydQqRSqrAj6c0ynquOL0PJCwAADlxr0YtwR1FCehwWRWQwjTrvZng87LitRVfNuiMEAEAvcxlF/4eFdwpxR1FCerbqIvJXSqnhFNccdw2PSz2wX6hLBwAgI5NT09aj6NfXP5Hvffe5nmgnQno4b4rIfqVUNeX3HYwgwEateUXjU8eXoeQFAAALA1/9I6vnFfGGRYT0dH0kIl9VSo1mdMfOxx2ee7WISy8G7Iwwmg4AgKEv/eEfWD3v+89XCnfDIkJ6eHW5M3L++0qpwZQmh94nSZJhEdnr8BJLPbTPqoR0AADy4c2fvS2nXn6ppz7zA+x2J4tyZ0R2IaNRc9+hcaFXdpxSai1Jkk9FZL/DyxxOkqQvkn0PAEAhrfziYxl98us997kJ6WY+kjujzUtKqaUIt2/Q4bn1SD9TSEsi8pSHjlGVrwYAAP41Glvyja8/0ZOfnZB+fwjfHuBa/7wRe612kiQD4jYq/GEP7u8FQjoAAOla/fh/y6GDD2v97dSz0z0zUTSzkK6UGuSwDNq+ayKS0BJGbbaQRpsppSoiUqHFAQAQWfvnf9L6uzd/9ra88fprPdtOiVJK/4+TZOcfP9qDJRIAQvwYJcmSiDxCSwBA8dXrDdmz53O7/vfr65/Iv/3Kl4v40bWzM6u7AAAAIFX/sPDOrv+t0diSSuVEz7cRIR0AAACp+u/n39r1v/3oxZfk7//ubwnpHCYAAABI03vv/Vx+/Mqr9/37uR+9JD/8QYUGElZ3AQAAQAa+8+3jIiLy5DeekPVPfikvvcQI+nZMHAUQx48RE0cBAMXHxFEAAAAgrwjpAAAAACEdAAAAACEdAAAAIKQDAAAAIKQDAAAAhHQAAAAAhHQAAACAkA4AAACAkA4AAAAQ0gEAAAAQ0gEAAAAQ0gEAAABCOgAAAABCOgAAAEBIBwAAAEBIBwAAAAjpAAAAAAjpAAAAACEdAAAAACEdAAAAACEdAAAAyIUHHJ9/KkmSz2hGAB48RBMAAOAnpHNSBQAAADyj3AUAAAAgpAMAAADoxLTc5QRNBgAAAFi5ofuHiVKK5gIAAAAiQrkLAAAAQEgHAAAAQEgHAAAACOkAAAAACOkAAAAAIR0AAAAAIR0AAAAgpAMAAABI2/8Hu2n5TjkY0/IAAAAASUVORK5CYII="
    }
   },
   "cell_type": "markdown",
   "id": "64b9795f",
   "metadata": {},
   "source": [
    "![dafDISCOVERY_icon_small-01-01.png](attachment:dafDISCOVERY_icon_small-01-01.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58bfdc43",
   "metadata": {},
   "source": [
    "# Data Fusion Discovery Pipeline (DAF*discovery*)\n",
    "\n",
    "\n",
    "This is the Jupyter Notebook related to [Paper on: LAABio](https://laabioippn.wordpress.com/) for more information\n",
    "\n",
    "This is a pipeline to merge __previously processed__ data from different (spectral) techniques. \n",
    "\n",
    "- Projects might be orgaized into different folders\n",
    "- Data must be accompanied to a __Metdata__ with a common ID header to index different data from the same sample.\n",
    "\n",
    "Example: \n",
    "\n",
    "Metadata with at least: (1) sample name; (2) NMR code per sample; __Optional:__ (3) MS code per sample; (4) Grouping information; (5) Sample Comment \n",
    "\n",
    "processed NMR data (e.g. MNova, TopSpin) and peak intensities/areas exported to a .CSV file \n",
    "\n",
    "processed MS data (feature list; e.g. MZmine, MSDial) and peak intensities/areas exported to a .CSV file \n",
    "\n",
    "> There are some possibilities to explore: (1) NMR only; (2) NMR + MS; (3) NMR + Bioactivity/Phenotipic data; (4) MS + Bioactivity/Phenotipic data; (5) NMR + MS + Bioactivity/Phenotipic data\n",
    "\n",
    "> 1. When there is only NMR data, the STOCSY calculation should be done as it is.\n",
    "\n",
    "\n",
    "> 2. When there are NMR and MS data, and the \"STOCSY driver\" is chosen from the MS data (a specific feature number), the correlation in the direction of NMR results in a highligthed NMR spectra.\n",
    "\n",
    "> 3. When there are NMR and MS data, and the \"STOCSY driver\" is chosen from the NMR data (a specific chemical shift/peak), the correlation in the direction of MS results in a .CSV table with MS feature number + indexed correlation results.\n",
    "\n",
    "> 4. When there are Bioactivity/Phenotipic data, the \"STOCSY driver\" should always be chosen from this Bioactivity/Phenotipic data and the correlation in the direction of NMR results in a highligthed NMR spectra and/or the correlation in the direction of MS results in a .CSV table with MS feature number + indexed correlation results.\n",
    "\n",
    "\n",
    "Note that the output from (1) NMR data is a color coded spectra modulated by Covariance and Correlations, and (2) MS data is a matrix (2 x X samples) indexed by MS feature list and the correlation results so we can add it into Cytoscape to color code MSMS base Molecular Networks.\n",
    "#### Option 1: NMR + MS + Bioact\n",
    "#### Option 2: NMR + MS\n",
    "#### Option 3: NMR + Bioact\n",
    "#### Option 4: MS + Bioact\n",
    "#### Option 5: NMR only\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5f6823b0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dependencies to install and import\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import warnings\n",
    "import matplotlib as plt\n",
    "import matplotlib.pyplot as pltpy\n",
    "plt.rcParams['pdf.fonttype'] = 42 #set up for Acrobat Illustratorv\n",
    "plt.rcParams['ps.fonttype'] = 42  #set up for Acrobat Illustrator manipulation\n",
    "import os\n",
    "import os.path"
   ]
  },
  {
   "attachments": {
    "pipeline2-01.png": {
     "image/png": 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CqzZtIIpGLNj1H4YG1UOrwNqPtZxTxvTEkQtX8FH4aqyd826xrQg+DP9qnjhz9XbB/13bBGDpvNNYtuZfjHitfblajwxWRERl4wB/A0xVAcv6coZxbRERPVmiKMLKytSk+Li7qv4FNvDGXzujMXJJ0V1ETPx1rN58GDKZgK2HTmLD+QQoBAF7fSqhrr8fEhNNYSXy0Blczc3DsF7tHns5lQo5ZoX2Q4/PFmPmgj8x7Z3ejz1NCUDhm72CW/rhg+NN8fG6XTh2/jLeG/Qiant7lIv1yKqARERERESlSBDuf0juYGdzTze5ICAlPRtJaVlQmK8cWcnlsLFWFZlm7LnLqGFnA79alZ7IstarXQlTuwfjx/3HsPvgmcee3snLN1HDo2i1w0mje+Cnkb1w8loi2kz+AUOnLELUiYQyvx55xYqIiIiIqDSD1QP6t2teF6083XDwdnJBN98q7hgz6AUAppb8uu6KRi1vryItBAJAcloWqtjb3nf6RqME0UJL4XJBgEx279KN7BeMAyfjMGnZn9hSzxsujjaP9Lk3747FocQUTBjQ5Z5+PTsFomenQOw+eBqLNuxBz5kRmNK1Dd4Z3JnBioiIiIiILAQbyXjf/jKZgG8/GIBhX0TAVmuqMqjVGbDvyHm0bVYHMpmAnp2LPsZPKjTNBwW3N6cvxV8XL9/T/e1WAZjxXh+L43w5vh9e+uh7TJ67CgunD3/oz7zt3xOYsPwvDGroi/Yt/IodrkOreujQqh4W/L4Ln23+Fyq5HKMGdGSwIiIiIiKie4lGI+Sy4qsELlsXiUn9OmH97xcAAAO6t8Gc37fB2kqF67dTEVDPp6Alv+vXrsPBwfQkDFdne1w7l3DfeTfz84a9uQphvsi4a/cdx93FDjOH98DgH1ehzbq9GPpq8fdwrdx2CLsOnTIFQoMBpy/fQuT12+jrXxOzStiM+piBL0Cj1WHmln3o/WLze57vxWBFRERERPScq1evPnZt3You3bpZ7B93JQnxt1PxeccmWP+7qZudjRrDurbG1n2x6P9ya+w+cBK1vb3QtlkdbP5zI9q0bQsACKjjja92Hsa5+FuoW9PL4vTHDup0T7c+H/7wwOXu3LY+xhwLwGcbItGisW+x0z8cfx1WCjkAQCWToYa7C5aPfhVdQwIeqpzeHtwFC/ZE4e/dxzCsT7sytx4ZrKjEBEEIgak5aCIiIiofEiRJimAxlG2vDxyI6Z9MLTZYzf15C9597d7qb7eS0zF1bC8AQK3q7ljw+y60bVYH0dHRGDV2LACgQyt/VI2wxs8b9+L/3u/7xJd96pheOHrhCj6atwrr5rxrcZhvx/ZB88a1HnteKqUc/s6OuJaUVibXI4MVlTRU+QAIAxDM0iAiIio3LguCkCBJUiSLouxydHKCp6cX9uzaheAXXijovuD3Xfh2+0E4KpWY06jmPeMp5TKkZebB2cEaOr0Io9GIn5ctRZs2rSEIpjur5HIZRndois//3odeMUFo3rjmE112lVKOWe/2RY/Pl2Dmor8eeTqiaMSgKQsxpncIQlr5FztchlYHG7WSwYrKNR9zqLoMIILFQVShtu1h3LaJKqQQ8747BKYHelMZ9sFHHyF07Fg0CAiAq5ubKVjt+g+pWh1StTrs/e8sXmhTv8g4g19ph0Urd0GlUCJHo0FLP3es+HUdwn+cX2S40QNewJ7jFzDm+1X4ddIw1Ktd6Ykue/06VTC5WztM/ysStopHixdyuQypORps2R9bbLCKPX0FJ9MzEVavBoMVVQgJkiSFsRiIKgZzFd9h3LaJKuT2HQbWNCk31Go1Jk2ZgskffYQvZ82Cq5sb2vhUxqrTcahsY40GdavfO45KgdChLwIALp6/gFkzv8SsOd/cM5xMJuDHqcMx7NPFeO3zJfi0zwvo36OVxeWQJAnL1+5FTFIK2jcsefW9Uf074OCpeIutC5bUyBdb4oOVW9FqexR6dynaymFyWg4mzV+L4Moe921FkMGKiIiIiOg5V7N2bXw0aTImf/QRBg0ehPCpQzHo2EXUqVkZbs7FP4tq3epV2LVzJ76cNQtOzk4Wh3F2sMaKL97Cp+FrMH7FVizeegCdG9WBX43KsLVRIzM7D6fjrmPHiQu4lJ2D8R2a473hLz3U8s8c3w8xH//wyJ+/f49WOJtwE2Mj/kRk1Bl0bFYP9rZWOHnhKpbvjYG1XIZFk4eV2fXHYEVERERUDJ3eIJXxRZyhUirCuKYqjtp1fBE+fz6+mfUVNqxbj27dX4ZLk3uvHImiiA1r1mDHzh2o718P3y9YWHBfVXFsbdSY8/EgDDyRgBV/H8DG6DP4Zs9RSJIEhSDAz9Eewf41sLRXe9T28SgYz97GGlUcHty8uYerPb4Y+jJiziQAAFQKOeo62kOlKvk9UWGhr6JBrSpYtvUgVizdCKMkwcvaCj0b+mLCG93h7GBdZtedIEnP/vdCEAQJACRJErj5lA/m6kK7AeyRJCmEJULEbZuIwapsBytzVcDpAGawqm+Zdd/vV1pqKlat+B1nzpwxr1MZTp09jx07t2PMqNFo3aoFXus/ANbWjx42tDoDsnI0cLS3htLcJPrjunQ1GTWquT32dDQ6A/I0+geFqQ4oI/cQ8ooVERER0UMcBet1OphOTD9+5pIkQKvTQi6Xw8bGBjJBxkKmAs4uLnjrnaJNmL/x5mgAwLA33kTLFs0eex5qlQJq1ZN92O6TCFUAYKVSwEpVfuIKg1U5kPjvn9VuRW7rlX72fCtjnq4GADmA2+qqXseqd35pc5WeI/5jKRERET19osEAg8EAe3v7JzZNQRBw9eoVAAKqV68OlUrFgiYqhxisyrDUvX9WOzk/PCz9QMJQi+vq2I0eSX9Ffxr7+bf76749JKzW8Ik7WWpERERPj9EoQhTFJzpNlVoNd3cPXLx4ATdvKlG5ciUolQxXz4mHvi1m6ZLFkQCCW7Vs3oHPJytbeL25jDr68Yh39g358Hz6gYSRDwrAhsS8NqfCFu2IfCV4Zfa5KHuWHhERUfkhlwmwslLDxcUFebk5SExMhE6nY8EQlTO8YlXG3FizoNGZJcu/yjmT/NLDjpt57Mbr//YZ0tLrtZDPGrwz5ReVe1U9S5SIiOjpSk5KQmZmpsV+Nra28PLywtWrV6EvJiy5urlBqVQiNTkZBoMBzi6uSEpKhLu7B6sFEjFY0cNK+nejz/Fv5nyeE3NzIB7hsnA+Q7be+1rEjiWJf++bWPW1LtP93/l0jdzWwcgSJiIiejquXrmCazeuW+zn4eYOLy8vXDh/Hjm5ORaHqefvDw9PL1y4eBGSJKFBQABycnKQlJQINzd3qNVqFjJROcCqgKXMkJ0m3/tmr2kHh044lxNzc9DjhKrCdIl5fvE/bvxjV5f2e5O2/l6TJU1ERPTkCIVeJRpWuP8QMpkACAI0eXmwsbGFvZ09VGorJCcnsVogEYMV3Y+Ykyk7/+OM3js6Bh9N23n6MwBP5Vq/5npO64Njpp84MKr33KS9m6qx5ImIiJ5wyHrMU6JCwXQE6A16KOVyWFlbw87WFkqVCklJvOeKqDxgVcBScPrHGZ2vRKydpUvMa/yMZmmTvOPUuOQd74/27LrshzpvvjPbOahjItcEERHR46tT1w/VfXws9lOb75EKDGoKUTRYHMbW1g6CALRo3hw3b9wEACjlcgjmh75mZWchKSkRrq5usLKyYoETMVhRWtQ/VY5OmLg471Jm11JaBOvbW45PuL3lrber9G/7QdDMZQu5VoiIiB5PXl4uMjOziglNNrCzs0ei4TZ0BstXnSqJlWCjsEWSlIw0IR1b929GblY2RJ0IBztHVKvsDWdndyQlJcHd3Z3hikpKetyRhYpfRk/0IzJYPSOnZk98MWH55ggxW+9VBhbH5vrKfQtSolt0arto2Zs2PvUyuIaIiIgezdUrV3D1evGNV3h6euG/61FI1Vje3YZUb40aTjWw7/ph5GXkICMlExmJ6cjJzIE2TwujKKJ5tSDUrFoD9Rs0QG1fXz7nip6q1OvxyLpyBoJMDgkqVGvaHjI5Y8OD8B6rZ+D4rAkvxv2wYXMZCVUFNOdTXzvw1ojfuIaIyoelOy+/FzT7UGK9mQeyP111br7OIClZKkRlgQBBKO5VgrEFQBBkEGQyKFQK2NhZw8nTGe5V3eHl7QUvn8qoVr0a5AoFYmJiEH8x7ok/pJjIxIjkG5eQErMTVSo7o0olD7i52+C/NUsgSRKLh8GqdGWeOeJy7ee/lwGQl8Xlyz2X+vKJL98fwTVFVLZtj058eenxWx99373uq2sGNWp2KT2v3tzNcZ+zZIgqSDQTBMjlMiit1bB2sIGDqwOcvVzgVtUN7tXdUdu3Nvz9/dGgQQNkZmUiOyebhUaPRtQDkuX7/SRJwK3j+1GzXg3IjAZIkg4qpRL2tkokXDzDsnsAXtN7ys4u/HayIVtfqSwv45Xftn1Re2jcSusqtfK4xohKhyF2fwsp5XYVRfOO2wU7p3uOmJYfuT55Ulvvca38nfcBwBev+g3qtvTYiRGZ3rPdHZTJLEGi0lPL1xdVqla12E9lfgZVxxrB0It6i8O42rrCSmGFXn7dYDQaIRpEiKIIo9FoukogSfCw94JSpoAEwKA3QJOngaODIwufSr6f0eXhyo4FUEnXIJOrIHNtDM9mfSEIAkRNFtIvHwUyk+BlnQVBcgOgh0wSYDQCDvZq3L55GzV867EgGaxKhz49SUjccGRImT9xka33urD46z6Nwub/yrVG9OxpIuZ8olmz60OZu8NNLPt9lt03c9vI3Kvezu+fcDvP+1K2rmbXpp4b8rtVc7O61qWK499bom71G9qh2o8sRaLS42BvDwd7+3u6p2an4XLSVWRo0uHt6f3A6dRwNT12UpKMMBolSJLRcusDEpCckvy8NC5AT8j532bCLe8I3Fq0gKBQQC9eRNqBH6BQADIxC7ZKFbKSUpCZmg1Hdyco1E6AEZAJEpKuJCC3ihcLkcGq9NzYvibQCHiWh2VNjT3dHQCDFdGzPrFx6VQdzZpdExx+mNNU5u1/MXf2pJ/yvp/1o+2MeX3yh9lzKqnnC1WdNsllQpGbKl70d1uxMvrmeAYromdLEAQIMgGpWWm4dPMSYs+ewLXkW8jS5yJDl4MUfQ6uarKQKYqQyWSYENAZnr4eyNRabjmwaeVAeDt5Y+3p9fm56R7dfF+Ek7UT8m9zESAAkhEQeFcHPVhOdjYQfwiCJg45Ki1sm7SDUqGGSp+A9FvZyIUHrufJcOCMHka5E/orY+DTuCk06am4GZeAkzflaNTAlQXJYFV6si7HNy8vy5p57EaghR2HjyRJCffZsThJkpTONU306LQbV45Td2m+XObtfxEArMd8/EHm0KEXDcf3t1A0anMYAPYnpHft1dDzp7vHbd/QbcdHu+J+Ts3SO7vYK9Me4qDwvtuuIAhOAMDtm8hk6/6/ceTsUaRkZyApJwOJuRlI0ecg0yhClMshyGWATA65XA65TA6ZXA6ZuTEKU1KSkKZJL7ZVQI0hD6JkRFJeavEnYSTRvH0+9vZ93307VdBglZMLKzsVrOVGyJISoD0ng9qvLbKNrvhurwhRyoC7uzV6DxgOtZU1bh5ZB/dbCTh3W4m9cSqo7JzQuEljFiSDValyK0fLauk0xHjzAVaYhR/mMAAh5hcRFUMjwvq785ple7KMndvay/55r7Z6lJ1SSAcAKTfLRrczaqD9N//XrmDbsnfOVPfp9I1mxa+f2jVq83KORrQ9kJTTZlY91wF3T9tKKdMGezns3Bmb2Ltf2yrLHmKxQgRBGA9gvIVte7h5m+celMhsZ9RurDp9GJDJIMgFyORyCDIBMlmZvFo0VzClr/EWTpiMN2/bvblWny9p6RlIca0Pz6QzENQikHoR+ivWuGEIwrQZM+DgeOd+PdEowTnZHtqcXOw8l4XWrdqhQ6dOLMQS4PVjymep5sFcAMMAxAAYnh8WBUFIADAdQASLjej+Fsdp52WKcP22rlU3SR8WEsEAACAASURBVILs09Oav3VGqAFAv2PtIEVNz1PyOk1OFh5H/cqI78Vz14MM/+3ssDM2qXsrd9sDTrYKi6e6u/i5rfzzVNJDtewpSdIGAD4AjgGYZO5sJwhCJIBlACJ5tYroyXJQ2cPFytHiSyVXQxCEYvu7WDlCLpS4ceH8fXcCgJbmbn7mffl0ABu4Np4/dev64miGGxK8X0W60h3p6irIzs5CXdtYqHLPFjkM1Ockw0aehUupBowaPYah6iHwitXTpSmuh5WbHQSlAtrbmTAajQXdVY7WkFuroL2VgfyuShs1FE7WEHO00GUUbbhP7WQDmY0KuuRsiDpT05kyQYDay/HOHa2iEdqUHBgN933mhdbCwVeCIAgbAfQy/0gDQH3zewZ/nInu72iy+NLODLHn8gDrBk4qIekje6v+n57SbAs/r13yvo84SrN60yTrUUPH3T2eYOuQbT2iz5Tc7xcu2tDq4+RXg6rOKW4enZt4/DV7X8Lcg2fT2rTyc97/EIsXYT7IetH8f9BdB2ZE9AT19O/xwGEGBwx87PlIkhQjCMIeAMGFtu/X8/fdkiRFcG08X/KS4yCd/BM9vdOxZF86tEIrQBDQsK43utnvgO35+dCrbaB0qQ9AgC7pBFRSLvQ2vvDwvLfyVcKlBIiiAbVq12bhMlg92++ypY4O9T0RsnkfAOD6hmWIGv+FKSS52qLLoSMQlEpEfTgU19ceBAC0+WMpHBo2h1GTh12d2yDvqunmV3t/D4Rs3A1BpULyns04MMx01b926Ovw++B/RX9o9Xpc2xCBkzPmQp+ts7RY+vscfPWy0H0Dz2gTFe9yttF/xiXtL5O81WOcVEISAChl0E/2U/eZcFKzN2LH4RN9qnvGKYN7brI0vqrHsKV7z2YO0KbebtG1gf+W4uajUgj6sU2rhn21K/6HFTWbtLRWyTQPGazuFitJUgzXINGTtenc38jUZlrs17RyIHycfLDm9Lpix+/m+xKcrJ0e5sRJcDHd6TmSeTkGOUvehL0qDR7WEj72t4a8y/dQewdj/7692HZRju5WW6C+8AP0dcZC1GZAnhkDnd4AlUsNFG538vt58/DNd9/h2vUbAIBKXh74cNx4vPf++8XOP+FSAn5ZvhwdO72ANm3bVvjyZlXAUghWclvrgr+r9B4Bt46mZwLIbJQQlErTMDa2BcPY1mpo6m9lDa8uBbdiwOf1PhBUKnPIalrQXengXPC3NjkRRq0WglKJan1Hofa7g4pbVotpy1xl6LKFXjyjTWRpmwGEyFuGQe+c1uwd6qGc08ZDvrZwf3sxN+/zg3P/uylZeU/tO9vjWIr4gqXpHDyT1nYimga+n3vwYt6EMZHiueiGxc2zX7sqyyrZqK6+/9upNRm5BocSLafp5vWN3LaJHp5aJkN9J3cEuVWF+X4m1LZ2wJC6LdC9en2L46RrMpCiSbf40hq0ECVjsf1TNOkQJRGC+TBXePD2HQFTzRJu38/5HunWtuWw0qdBLpMgk0tQSLkQz/wGQELbdu3hXtkX/6R0h14bB5xdAvWN3bARtFCrlajplIr8KoJ/bdyADz/+GHmaPIx5YyRCx4yBKBrx8dSpOHzwULFLcPb0KXw280vs2b37Qd9Z0zPbYARgen6bVNDPCEAs1M38KAJJBCDe2fsWjHtneNOw+e+ieRzpqZU4r1g9XfqSDFR/3CTs/WeoxX5KlRJymztBrHLHbri05G8orJSo3nfUnR95dw/IBAFGqeiXJbJzFxj1BrRdHQF7/6bwbN0BZ2DxHvf71ROMQNEz23t4RpvKor27I4MAwN3TM8Wvnn/Cg4ZPuJRQ6WpCQmUAaNqy+YljR6PqiQaxRDcy1K5b57JKpTbExcV7a42wT9dL1a7mSk2jssVeKQapam8n2ZfeorD5vxtoKDPoVUhPqiLFnW4tHjw6RAKkjoP9+u6+anxt2llsr6SUXQywk22pYoVoQaPPPnIpo/v2KxmDB/g6z5ZadF5/csNv/xPGTToma1Bjh6xBwN+oXOMU7BxTjYKsYLvtX9P4f+F7ri15febpcy/Wdl5Uv6rdXkdrRVKToCanVCql4T7bduEr0qziS1SyExOY+8YM+Pv4Y8Cs0dibfAVj2r2C/h37YcrP/3fP8IIgmJvzsxyJBOS39ld8ZHqE51VFAChc1XgjWwN8vhgMBugyEiET7nzJBEGCMmUPtNt7QuFUDSE+1bHl5nUYrKvBRncOkJoDogxKpQo2GVHQ57SC0tYFi3/6CZIELFm4GN26vwwAaNasKaZMm4aNGzfgk2lT0aRxE8z6+mskJyWjf/9+aNe2HbZs3QoAWLFqFRo2CkD7kBCEvjMWB/87AkBCi6ZNEf7DfDjZyZC7ewYMicchU1hD2WgI1P6vQX/7GDT7v4aUfR0yp2pQt5sMmX015O2bBeO1wwBEyKu1hU37T6A9+QcMmnTg2mEYs65B7tkYVh0+hUzlCM2Z9dAfWwJJr4WiWgtYtZsKmdKOwaq8facfNICYmwPHgFaoPvwl3N51b+JXeNgUGtgI15adYV3dAfZ+PpDb2gOiEZDLAEGA0tkG2tSce9Ndtha5VxJMV7Vk8kf5HHcHqwiuWiqLJn0y7RAAhY21ddJvv/1a18PTo9gmyEVRlE344IMtNxOTAgBg0YL5taaFzfhHo9E6l2RewwYOGG3v6Jj607IIS8+QylgBvL0CeLvYCcz9caH5r+R4wCkeGADTCwDgAKRt/Q9vbgXeNHdKwbH4QByLD3zQsm3ajzGbgDEA8NPiRQE1ata4VczB4QZBEC4DyH9yKav4EpWATpIwe3U4lk78Eb2CXkDmwc3oG9IHJxNOYX3cMYspyE5pA9Fo+RymUq6CDAIcVMUf6Mke/nlVc+8KVtx3P2fy8jRIkjmjGgAJEgTzufdcRVUYtIDy9n9Qp29BN18N5KIe0MshSZ4QrHwgCAKsrRXIuHECzr7BiL+UgCqVvQpCFQD0HzQI/QeZakI1adIEq9etw6yvv8aGdWuxZ/8B9H+9P3x9ayMqNhbVqlaBp6cH3n17DP5Yux49ur4IQSbDqnUboDcYsOyTXhA0abAfsB6GlIvI3PA2VLU7QrtjAuSNh8Da/zXkxP4Mze7PIa/9IoSUONj2/Q2SQQ/t2v7Q3+gGIfMypAubYfXyfMgcPKHZNhXaQ/OgajAA+oPfQN1jPhQO1ZC3azJ00Yth1eJ9BqtyRnzQANfX/4rqg95CgylzkH3p9Xt/bF3vBKvkfdvgFtwV1V/tBptKVU1HWvt3wLW96d5UpaftPcGq7ocjobRzgOeLrwEAbkVufZQzcwmCICyHqQEL3vhKZV5uXp77t19/Pf3L2bPGFzfMkgULR+aHqkciCNKAwYPWDhg8aG05L665AL41/x3Gbw9Ryey8cgY7juxAr3a9YGtlC7lMjq83LobWKEImv/ck5iv+PR84zeGNBz2x5TPvu/MbsbhsrtpPzxF7eztcUtdEZfvaqCJdBGBEjlAZe3Wv4tiJm5DLGsHN2QoN/d3Q0nE1lNqzMOYchFzmCqgcAFFCrkYDZwB6gwHWVtbFzqtjcAjCFyzA3j178M/uf2BvZ4vXBwxE1SpVsHLNWrRt3QbNWrTA9lf+QVDjRli73vR1bNO6FXbv+RfGsIEQ0i9Cd2IF5JWawWX4XzCkJQCSEdYNBkMQlLAJGAmtTSUoqrWEVL01jOlXIWZeg0wQIelzIUkyKGp3h9KjIQA5lM1GQbdjMnQOlSF3rQtBkwOD5gwEj/rQJ+yHVYsnX+YMVqXs5t5/4BzUHPZ+TVCz74B7g5X9ndslrm/bCLfgrqjaoz+UDi4AgGtbN94JVvb3fuF9Br9X8Hd6zD7ELVxV7MmwByxqhDlYMVRRubD/8OG3o49GLQhsGnT27n7pael2azdu/OzuqPT6q69O0hv06ruHNxhExcZNm6drdTpHAHB1drrwat++qytIUUWYg9UeVhMiKjkjgAXbfkPnZp3Ro013bDm8DbsT4yEvpmbIgauHkKPLtdivrpsvKtl5ITJhb7Hza1WtOexUD111aa45WHHf/VwS4OPXCCv+uY3uQS/BWi1h1+kcVPL2wP++CIVWp8P5M+dw9uQRSLZqGHUA9HkwJEVD4dkWGZnJuGGrQhUADna2iE+4DJ1OD5XK1B7A7Vu3sXzpEjRv2RKDhw5F+IIF2LxpE47FHkebFi1gb1/0+2oURaSlZaBSy0oF3Sp5VcKR6GMwVg2BSmaAdH4LNId/hOTqB2WTIZCrHQriikxhBSu/3tDGbYN2z2eQO9eA3MUXRrkaMgmAAMitXQGYtkHJ1h2SIQsyTTrEjDjoj/1kqnMryaBw9XsqJc5gVdokCafmfoGWC1bDo/O9Z7OUzneCVerxk8iJPwXbWqYbYzOO7Ufa6VN3hnVyxt3tTFz9YwHc270Eq8o+gChCzNY/0ndBkqRIc5Uh3vhK5YIoGpXz5n43N+LXn1+6u99333wzJTsnt9Lde6DR77y9yNK0pk2eOis/VKlUyqxp06b1dnN3y6gYP0FSuvmKdCS/NUQPJ0ObC9EoQi6TIzM3+77DxqUlIE1j+WfDy9Yd7rbuOJNyodjxAysFPHSwKlTdl8HqOdWxUyd4enlh7Zo1MIpGdO78Atq0NzUYqVbJ4O/rjDpJf8OYnIBsq8aw0p4D9Fcgyc7gTF5z6JXm71/jJog9eRqTJk7EnO/mApKEqZM/xs8r/sCcr2YidNw4BDSohy3btyHuUgI+GDcuP9sVkCsUqOTliYtx8RBFU6WuuPh4eHl6QnH9H8it3KDsuRSSPgO5K1+BQZsFKes2rAw5gNIOhuwbyN39GRSGLCibvQXrhkMhQETOSvPxswSImVfu7NQTT0NmWxUyOy8YnXxh0/MnAAJ01w9DTIljsCqHSlQhOmlbDK78sRDVX3/r3mDleOdH1JCah8trf0G9iTMBAOeX/gAxU1NoWJt7xj89cwHcjhxC0NcRcAoKhlfv5rix/tCjfhd684w2lScXLl16cfWKP3r2HfD6n/ndTp04WfOfPf+WuGL1L8si+u/eu3cCAAiCII0eOXJEsxbNTwPA0kWLh/+5adMEABgxfPj4zZs3vx2XkBAMSZL5VK++b8zYsZPq1K1zec6s2dOijsX0zc7N9XS0t78a3LbNkvETJ8yRy+XGMW+OWnMrMdHPzsY2af7CBS8NGTIkCgBat2z5s1wmk/YeODA8PTPTx8bKOjmwccDqiZMnT3d0dCio87v97y3tVq1ePTHh6tWWBoNo7ebsdKFtmza/jA1993u1Wq0v4cecywZpiB6OIACTe72F1Kw0nLtyDv1CXsXfx//F3uQrxY/zoGk+nUXlvvs5V79BA9Rv0KBw5Ebe2Q0wRn0NmTwLBkmBk7ZjsOu/NATW6YjqlaxQ9dqvcHcLgm+HEADAjM8/x76DB/D9woVYvX4dJElCYlISmgUGYszYsQCAri++hC/nzIGToyOGDDM9/tTD0wsCBPz8+29o0LAhRgwZgi9mf43AJk0gCAJOnzuPD94LhUyQQbPvM4iZcYA2CwZRB1ufYGjidiJ36/tQVm8B/YXtUFRqAmhSIcX9A4NMCc3NGMjy0mC4vh9yALrLuyAcnA3B2gn6479CHjQWQo0XoI/5GZo90yE4eEN3eiWUzd9lsCqHlCU7owScnvk9KnXqDaWrZ5F+agfXQsFKg8vL/0Lu1RswarVI3BZdJEyp7C0/3+LmxkPIGWu60uX/9kTc+rMvjKLx7sGsSnDmiwdeVC7I5XINAEEURfXPv/76dffePbdaW1vrACD8u3lfGUTRSpAJoq21dWKhK1f3HNMc2Lu38U8Ry5dIkiQAQMf27b8aMGRwwT1VWVlZrkkpqfUBYM7c7/4SRbFgOzp74WL3SVOmtnZxdIi/cTux4HkIKWlpddf9tWlWRmaW62dffD4pJTW1ZlJKan2NRntDNBpl+dPbvG3bdINBLNjAM/RZ1Xfv3ffh9euh9Zf9srwrAMwPDx/z2x+rf5AkqeAkzs3EpCar129oEn3s2MuLly7pWpJwxW2b6OG96huEF5q+gPB1P+LIpVNo27ANJr0yFgd+mmqxMWeZgIKm2YtLVMX2fwzcvuluoihCE7MWVlnXIRPkOOU6ClHxckyYPAkrfl2JqINXMbJhCDxu/gNN2jBYOVeFl5cXdu+ORNin03D6zBnI5QoMGTgQn4aFQWl+9M+QocPw5Zw5aNOyBaysTbenBAYFYdqkj3H+4gU4ODoi7H//g4uLC/7eugUSgGFDh+L9Dz+EURIhyFSQrh+AqLKDVc8lUNh4wrbrXOTGREBKjoPg3wdW/r0h6fOgjV4KQ/JZqOv0gNSgLwzXj0DKTYPS73UYVHZQpCVA0XoK1LU6ARBg03sZDMd/gZAWD2XbKVBXb89gVQ6pLHU0ZOUAogjIZNBnmB4WqEvT4OTX09Dki4WAIECfYaouIImmhgXzEs5D1OhgBHDjz4MF09JnaaBLugmVe6WCsKRNNjUAZshIhVGjh1EvIvZ/U9By4R+w9W0El1a+SN537u7FsubqogpzRkOpzG7TovmyXXv+nZianu77w3fzxk+Y9PGs7X9vaXfy7Nk+ANAiMHDZ7cQkv+ycKxaD1e1bt12++PKrtQaDwQYAatfw2Tnts7BPipun0WhUNQ9ssrRSpUpx+w4cHJaSllZHo9G43NBoXNxcnM+1btnyl9u3b9f8L/rYCEmShD3797+XkZH5v+KmZzCINi5OThdat2zxa25OruO/Bw+ONRgM1ufj41/a88/uZvYOjlm/r1ozT5IkmZe7e+zIkcM/cHf3SPxz48bhu/fu+yAu4fILP3w3b9wHH038mt8IoifLXqHAB31DYZQkbIz9F2fz0nH47BG08GuGnt4NsPHqqXvGeb3+a8WfDBJkEAQZxgSNLP6ATcZDNnoykpJSoRHcoNYokau0htLND+++1hsAMOLNkTAYRGxauQTtk7Yhc+9SaOq9BLvKdeHh4Y4fFyy0OM0Tx09g4YL5ECCgV4+it7ZMCwsr8v97779/z0OFZYIc6jovA3VeLnrOQWEL26bvFJ2ZWg3rVh8U2WmrKzWHZt/ngFwBu8DR+acVCnbtSvtqULaZ8tTLlltpKQSrrDNJ2FTH9FDgwleOrq7Yjeur/CAAEM3d4xdtwOUlf8EoGmG0fDCH7S2CIZMJMBhMQ1xcsB4JizfCKEkwGk3nzZIjT+Nv/0YQBKFg2nex4uqiimT8hx9+fvjI0SHZublem7dtn9qnb99fF/3001xJkgSVSpkVOn78tE+mTF1tOdQY5B9PmLgiLSOjJgA4OThcmvX17P5KhaLYlj7bt24974tZM98HgE5Ho9aFjht/BgAUCkXu9z98H1ytevXbADB21GiH46fPvGYwGKxjo6P9i5uelVqd9tOSxa08vbxSAGDOzK9urftr0ywAOHXiRLNbt2/7GI1GpSAIxs//7/NX/OvXuwQAzVu1nDBi6LB65+Piu/67b99wBiuiJ89OocLnv82G3ijiTHYqBLkMszYuQvCZo7BRWd6dnkw8BY1eY7Gft5M33G3dcPR6VLHzbOTVCDZKngOlx+fm5oQ5cW7o0egd3MhTIPWmFkGFw4FCDoW9J7Lt/CHb8SvSN/6OBMEOXm+EwatVd4vT3LVzBxYtXYbmQU0KqgE+TZau7YoqR0hKB5ialpHhqVWuZbAqNcVWBTRaDjf3dJckwGC4f6vtRuOdAFVwYGhh+qZhJH4X6Lng4uqS2fe1PpOX/fzLMp1O5/Dee+N2p6an1wGAbp07f+FTw+dW4Q0iLy+voDrd/6bP+N+FS5e6mINR3uRJH72WH3CK06JF8+35fwc2DTorl8tzRVG0qezpEZsfqgCgdm3fo8dPn3kNAHJzc22Lm14N7+r7Cs/Tv379I/hrE8zj2V+9eq0RYLrva8qUKZsKj5udk+sBAMmpaX4Gg0GmUCiM/EYQPTk3Nbm4lXAKMpkMUJhaIDucdgNHj96GXCa32Nz6qaSzxTZeYauyhZO1E47eii12nr6utRms6Mkc/CtU6NGzN1atWgV3N3e8HdrvnmFa1/FA5s4T0OTIoNUIMORl4+L8GVDVbgoXd697hn/73XfR7/XXUblKlVL7XLYF900JpVe2/Ho9VeXpQZsZXF1U0Ywc9ebynTt3jr5642ar/FDl4uR48Z3x4/Kf2yTdOYlh+vO3n3/pu2vPno/zQ8vwIYNHtQ0Ojn7QvNRWVkXaURYEwQAAcrkir+gOTW4oybKrVaoiTYzJZLIiZ1gkmO77kiRJZqVWZxXekViprbIAxAGQBEGQ+E0gIqLC6jVogLAiDVoUlRS7D8YMI/QaAXodIBkFKNKzcfHIfjTv1uee4VUqVamGqtIOVAxWz4B9laoXys3ZC2f1Ga4xqmhkMpk0duyYcVM/DTuU38DD4IEDP7KxsdFaGv7Q/gONFi9dtix/2PatW88d8eYbv5XFz1a9WrXYC/GXukiSJAwZMnhytx49duf3y8nOtrKysdHJZTJeqSIiooeWmmeEOhsQDeZzc5IAg1yOtIwsFg6DVenwCO4eJeD7TAlwKIXZS6oqtoddmtWLSo8566tJyOqE+zT/7tq+wTauMaqIgjt2PNJ0/frlR6JjRtSoXi3y9UED11saTpOXZz1r9ter9Hp9QfW8U6dPv/xKr94vWhq+rq/vzkqVKl0prc/1ap8+SyL37RsnikbVnG+/W3fq5Kmv/Pz8Ym7fulV5y7bt4+rUrh355dezxvEbQFQ2vFS7M0TRciOd9laOsJKr0c+/V7HjO1k5shDpmbkEZ1RycIRdSjoAAaIAXHH1AvSMDgxWpcS6Si2tc+saq1MPXHrjWc7XqoptdK1Rgz6q3PnVA7f3bmngO2pcfN7lC15n5n3/Zc7ZlB53Dy8Dsn2HjJ7PNUYV1eSpUyf+s3PXlqCmTf+7q1fBFZ2srCyH1PT02oV7Jqel1Slumu6urudKM1g1Dgo8N2TAgLE//75ioUarddqwafOX2LS5oH9iSor/kcP/Lcx/5hYRPbog38ZIzcnEjcwUXM/LRDYe/mJwck4StKLOYj+5TAGVlRK3chKLHd/RyglytgxIz4hHlZrY69oM/jbxUGRnINXKGfvzHDC7W1cWDoNV6ak5eOic1AMzhgOQP4PZ5XiP6PJhwPQfFp6cNaHPjjYvXQHgBiC7Up8WnwVH/P7qucXf9I5bsm0egPwmpuHcud4il6YdE7m2qNzvCNxcWwEQ1Cp1kfuYPL28UgYMHnRPC4Buri5jc3Jz7AHA1sbmrIeba/OSzsvFxSXN1tY2x8XJcS8AWKnVZwv3d3Z06CiKotzJ0SGzcHdbW9vfC4/j6OAwVKPV2tja2OgFmUzr4uTYAgAc7B1Si5wwUatj8vvZ2tleA4BRY8csrevnt3rlihXVL8RfcszNy1NaqdWGmt7VMwYOGnilWYvmmfxWED2+AV0HYUDXQdBqtbhyJQHxV+KRnJWKlOw0ZGizcD0tESnabGRLOiRDjxwLwSvqZgzStJY3yeBqrWCjssXeq4eKXYYqDlWgVqi5MuiZ6NSlEzIzUrF1uxYa0Rm2gh3en/AWXN1cWTj3IeTfsP1MZ2q+mTr/oZsV3cGRPb5M+ufspKc5D5u6LtsCPpk2OvfG5SoX5i2enns9pwvuuotP5WF9osaI1z6q3nPQntjPP/o8ccvxDxR2yrMhm9a0tPGpx8YriIiI7qLTG4ocKOl0Wuh0OtjZ2SMzMwOpKSmIjY1FclIS5AoFlColRMEIDXTIEXUQlRI6N22DC2I80jTFB6tarrWxNOaXYpejf/0+cLV2Kfj/+o2bcHNzhSDIZqiUijCuqefo4F0QIgEEA+ggSVLkfQYNYWk9UOSTnBivWD0Dzeb9PPXfgT09s4/fGvE0pq9wUF1t/8emHifnTh92LWLHQhRzL5UuMa/hua9+2XJ9y45lreZHvLH3bL+qDSa+P4WhioiI6CEObCFApVTAzdUVbq6uyM7Kglwuh06ngyiaGvC0l9uiskoFL08vNPNvhgsn41lwVK5DAzFYlY1CtnM2dvxz78iYsLejrkTs+AJPuDELx6Y1d+feSJBdi9gxOz9Ueb4UAOcGDXH+uxVwbFwV1V/tg9Ozf4Q+VYPs47dGJO7b+nOX3VGvc+0QERE9nrp+fqju7VPwv9Eowmg0AhCgtjI9MLhTjRDoRMtPW3C2doKVXIVedboVv69XO7CgiRisKF/jsB9/qDUg6tcz8+e8f2vDkQ8A2D+J6Wa7urm/9u4kzXuFutXsPwzuIT2gz8pGtR594dCgOW7s3IGkXScAAD/sid09u3+ZrIn5F4ChkiSl8xtDzytBEJzGjH3npS1/b552+XJCvQrwkbYB6M/tmioqW1tb2Nra3ncYD1tPAEBGRibOnD2H8Hnz8Pvvvz6J2U83v7h9E5UyGYvg2bKvG5TRfO7vYe3WLvS3r+mwAoUeUPqoTt1M7pqTV+QZpLCuVA0AUH/ybDg0MN2Pb+V5p252adxbV0I9AEQKguDEbws9xxovmP/DCqVSWa+CfJ4XuV0TmZw5ew6tWjbHf/8dBrdvIgYregKcgzpe7/BP1MBGM8e1tvKxP/C402vRvMWdlSoA1tXrQpd4HZAk5F46g2NT3kLSnqiCYca0qDNckiShrLwAdDAvmgFAAH+kiYD2wSGQJOnuV4YkSXskSZohSVIHSZKcy9K2bGHbzsftmioI4a6moZ7o9l3i140bt6DR6aHV6Wdw+yYqG1gVsJT59H/3kE//d9vERcx+6eKPv3ymTcxr9rDTECVAJrvz+2ZV2Qlya2tcXbUGyceOIu/mLaQdTigyjp2PbzCAWAAxZaxIYgHULvQjHcLqBURFOMLUGlQw7lT/yd+WY2C6WTmmDC53BrdrqgjkcjnSM3KRmJgIo/jwz7O6ffvhnm6i0+mRl5cLjUaDnJxcaLVaqNQqODo6QeD2TcRgHAtOrwAAIABJREFURfeqNXziVu/X3tx+cvaU0VeW7/wSQInP+ihVKmi0OsiUMhj1Rog6PfQpiUj87xBubT5qcRzbqjVGAMhvpXBPoYOxGAAJpVgU2TA1DxrJH2miEgswv4YV6rbnrqCVUMrLyO2aKkywcnF2gaOD4yNVq7+dmPxQw6tUSqhUjnB0dCzolt/yIABID3G8wO2b6OliVcCylHLtnI2NZ8xf0G7twvqOTSr/gRLef+WSdBNanQ6+7w8AAGiTcrAtqE2xocqxlQ/sajUq3Cn/zPd6AJfMB2AbAIxHKTwDQZKkGPN8C58BY/UCoocTDGBcoe063bxdh3G7JnrM/bVCAbVaDSsrq4d+KZXKJxLu8l8KuXwct28iBisqhnNQxxvB6/f095s89AWFgyruQcM7nk6Gj6s96r4dhqD5YZDZKmGpcoKkEBDTMRBdN+7H4qXLC7ovXhIBQRAKXm+Neds7PSOjV3pGxrd16/rtrlvXT0pOST0BYC6A4c7OzlcFQZAEQejEH2mi0rNy1Vp069a9YNtdvCSioN/fW7cX6TdgwCDH4ydO9UrPyJh+13Ydwe2aiNs3t2+iJ7MhPPMXTFdipNKYd3l7aRKvWh+bPvbdLa0D/t3oXVuz0bu2VOh1889Rr2zp06uXNPKNUVI+UaeVLiz5UvrLt65pOB9faUH/LlLvHj2k/LIHIG3esk1a8ceaIt3yXxMmfixJkiRNmPixBEBa8ccaSZIkKfb4SQmA9OKLXUVJkiIlSfp/9u48vKliYQP4O4iASmlxQ3BpWcuiUCgCrqQIIqDQyiKiQqG2Bb1KAQXcLsEVUKCAqC1bQVkEsQUEVNAGvSoISPFehJatVRS3D1KKiGzz/ZFJmyYnaZaTNknf3/PkgeRsk5NMet4zc+YYpZQGKWWEj98Jg9q2ye71GHUmTsLSnSmC3ws+Qv1hrQ+29dre+o2faNbd9Rs/kYcLizSn9erVx2W9VtOt9Tre13rt7Pee9ZqPYHr8c+as1PPxn6+2ygCp31Gs30H7N8Kk9q+B+yOwHmyxCnC1r7ru7xjjW2/e81Xend1Na+rdsTqj+R2rM9rcsTqjQd/C/Q37zsueunrNmvLNkBfXQrMRE9H7f7vRbfMH2PHgAIxc8Sl697sfUkosf/8DAMCanByUlJQAAJ56ekK5L8br06YAAOK6dQMA5H7+GQBg27fbAQD9Bw6qgbIuhLkAjsPShTALOnYh5BkwIm1rcnIAAJnzFznU6yM//wIAaNEiuly93rDhI5f1OqH/AKB812Brvc5hvaZqbIuej7/++mt3gNTvw6zfRGyx4sPDM9stWkRLAPJwYZHDtMOFRaXTAciU1FFy+szZ5ebp1auPbNEiWh43m2WvXn2crssJk5QyvaKzY85arHgGjA/Wa8/rtZRSDh48pNyZ7OkzZ5eb18d6nafqdWJFZ71d/d6zXvPB+h3w9TuG9ZstVnywxaraeOel59oPuj8BdWrXxvGdnwMAzhb/iV8+XoY/v94ISIk+htvQq+c9EELg9y1rAQBnjv2K47u+QFTkDcjP34fpM2dj8ouvIDPjbYwb8yR69763dBvd7+6JgoJ8LFy0BBs3rsfgwUMQFXmDu0Ws6AL6CDdPAPAMGJEHli9fisz5izB95mwcPHgA48Y8icZRkfj+v3v0qNftVL1eZFOvTazXRCFXv3exfhO5j8EqyEWW/Not/s/DuLzuJdg16QWcOfYrNnU1oHbElfj92y/x3fPJaHV1BHo2uhRfbFiLoo3ZWLFyNbJShmBzyihcOPMPAGBs2hP49wvPQkqJFi2isXHj+tIf6E6dLLfWynh7LgCgW/cevhQ5HEA/lO9CmLd23YaJANC4cZO6/JEmqpghztLd58NsS1fgFStXQwhR7qRIclIixqY9gfz8fUhJHQWgrFuQH+q1s67BPPgiYv1m/SYGKwoO/9S5GE0OfwcAOL77G1zS+1ZceUtPLP/zYvz28TY0u6MHrtu+Bz99+QlWHQNefflF1Dl5Epf0NODD+XPLjQgohEBBQT569eqDtje1AQDcfmsX9OrVBwUF+WjRIhoDByTo/RbaXXXVlT0BIK7bXbFQXQJhOTsWDyCKP9JU3W34+FMIIfD0+IkAgH7x8QCAcWOetIwK9sAAAJbrKKzz2j4yM94GAHRWB1yVUK8jUf6+WtZ6nc56TcT6zU+dQhFvEBwC9lwXjS5Fe4E6tRHeOhYnxz6PfyU+jFbnf8dVd3VAx7vvwdpmV6Plnv14ET+hb+e2uKJxQ8Q9PAIF77yOzPmLkPLo8NL1paSOwjPPTCy3jYT+A7Bx43r07RePCJubFOrtxIkT2LptO2A5O9bV+vrZs2d/++uvUwfMxcUHXn1tWt6zz4x/Sv2AtwPwtRDiVt6MkKqT3vfcjeXvf4AlWYuwceN6AJYL3ZOTEgHAYdrgwUPwyLBhpSdMKrNeA7Cv16MB4Pz583+VlJzMs9br1R+s+vfOndtfVfV6mxCiM+s1sX6zfhMFC+HNXcN93qgQUp3FEPwIfPPBa89OXbWzYHzr6OYY2voaNH5oNE7s3Y7C1e+iVng4WqQ+jxq1auPkwe/xxzYTGg95EkdWZ+DKO+9Fnauuxb43J6HlvyZXfTj8YS+Mxsn4YNX73iz+F4Dr+ANNIfPDLIQBQO6IpGQsmJ8Z1O9l4KDBXtXrGjVqnL1w4cLVrNfE+h169RvABQBNpZSF/EZ49R0yqRAbJ6U0cY8EDrZYBbmBz762EcD4EUnJaPzKawCAeq1uRtvnby43X92mbVG3aVsAwHX9U0tfD4RQBQBtWreC0TgJ9erV82i5hQvmAcBlPPgiCkze1usLFy5czHpNFJr1G0ANhipisCLyc7jy9Oyd+oEmItZrImL9JqpSHLyCiIiIiChACSGihBCJLqYbhBDx3FMMVkRERERE5ITqNmkUQuSpa/SsrhFC5MAyDH4e91TVY1dAIiIiIqLAlg5gpgpRf6rX5gO4DMAaXrMWGNhiRUREREQU2LJguRcYAFyp/r3MZhoFALZYhajV2Wtx9OhRr5bte18f3HD9daXPf/zpCNauW+/Vuho2bIj+CX39Vjai6mTrtu3YsfM73erOm29l6Fav9S4bEes36zeVkVKaVbe/YXaTiqSUOdxDDFbkRxvWf+T1yDsdY78t9yP4yy9H8cTjI71a14ikZIcfaD3LRlSd7Nj5ndd1Uavu6Fmv9S4bEes36zc5SNcIVlncLYGDXQGJiIiIiAKclDIPwG4GKwYrIiIiIiLyTbrN/xdz0AoGKyIiIiIi8lwOygaxyOLuYLAiIiIiIiIPSSnNKlAVSSlN3COBhYNXEBEREREFj3QAhdwNgUdIKSt/o0JIlboFPwKf96UBQO6IpGQsmJ9ZHd8/+F0i1mvWayLWb9ZvoqrGroBEREREREQMVkRERERERAxWREREREREQY2DV4SoKdOmY39BvlfLjh07Bm1atyp9vueHvZgxY6ZX62reIhoTx4/zW9mIqpPV2WuxYf1HutWdpEdTdKvXepeNiPWb9TvQiWxzFAAjgCibl7NkQkQWv9EMVhRC9hfkY+GCeV4tm5ycXO55SclJr9c1IinZr2Ujqk6OHj2qa93Rs17rXTYi1m/W7wAPVYkAFmlM6iqyzWkADDIhwsxvdvXCroBERERERO6HKoOTUGXVDoCJe4rBioiIiIiInEt3Y552Itscz13FYEVERERERHZEtjkClhYpdzBYMVgREREREZGGGA/mjeLuql44eEWI6t3nXrTvEOvVso0aNXR4PmfuO16tq2HDhn4tG1F10jG2g9d1Uavu6Fmv9S4bEes363eAyvNg3kJ+s6sXIaWs/I0KIQFASin4Efi8Lw0AckckJWPB/Mzq+P7B7xKxXrNeE7F+s35X2nvINhcCiHRj1uEcer16YVdAIiIiIiL3pbkxTxFDFYMVERERERE5IRMicgDMcjFLMThwRbXEa6xC1J4f9qKk5KRXy7ZqGY3w8Hplvw7FJ7B3X75X6woLq+twx3U9y0ZUnfz40xH88stR3erO1m3bdavXepeNiPWb9TvAw1WayDbnwNJ61Q8AcPI34Pzp1QiPfDQkbg5cIgxlXwxpYi1154shZaU/AEjLpiX48HlfGgDIEUnJ0taIpGRp3c+ePr7Z+m25dX2z9Vuv12VfLr3Lxu8SH9WpXs+Z+45udce2/uhRr/UsG+s1H6zfrN9B+LlmqfdmDOr3cgIGeQI58gSkxiNLnkAM67HzB1usiIiIiIh8kwdgGDwbjj3QWqiy1HtwZhiAYSgRkxEmjb5ubkmDZomwdJk0AAi3mVQEwAQga+hvByq1pUzdp8xarq52k3ercqXLhIhCreUZrIiIiIiIfA9WCNpgVXGosjUJJQLehqslDZoZYGnhczayYqQ1xC1p0GwLgLShvx3I8/cuENlmIyxdO8OdzNJOPUaLbPNiAGn2XT45eAURERERkQ+kLL0GKVIIERFkoSrNg1BlG64MXoQqI4BcuDdcPWBpNTKp1i1/BaoIkW02AZjkIlTZGwYgT2SbYxisiIiIiIj0tVv9G2ytVsbKWE6FqklebCccwCLV0qV7qIKle19XLxaPBGAS2eYoBisiIiIiIv1Yu6sZgqbEJSIe7rfS2OuKEhHlZqgyeBmqbOUsadBM79ZAIyzd+7wVDiCnNKipkUwqlRDCMjRgEN91O1DwDu7Bfwd3ItZr1mti/Wb9Don3lgZgJoDFUsrEIAlWRh8DTwLCZI4bwaoQ7nf/c2Xx0N8O6LJvRbbZAEu3RD0MlwkRWWyxIiIiIiLyXXAPYOGFfft6xFd0TdmSBs3idQpVgGVAC71arfQMv0aAXQGJiIiIiHxmM4BFu+ryntdtvnoYgONCCCmEMKmHUQiRJoQwCCFiYBm6XE96rW+YjmWKFNnmGA63TkRERESkj90A2gkhDDZBK5CZfVn4xyP/HATQVD3tavcvAOBY5KW4vOiUnmX2uUVQdQPUm4HBKkRNmTYd+wvyvVp27NgxaNO6VenzPT/sxYwZM71aV/MW0Zg4fpzfykZUnazOXosN6z/Sre4kPZqiW73Wu2xErN+s30GqEJYWqxhYRpsLdDmwXBfmjeI5c1c1mzMXUN0BYwBE2T8uLzoVqWeB/y/qsmGqJcxdDp/D3aNfjPq06xN678sIBqsQtb8gHwsXzPNq2eTk5HLPS0pOer2uEUnJfi0bUXVy9OhRXeuOnvVa77IRsX6zfgepPAD9ECzXWYXJQpSILfBuuPF063+klGZnQXJJg2a6jpR3puZFER6W12HeC7Vq+2V3MlgREREREenDBMsoe8E0gEWiCoSeDLu+2zZYVaAY3g/p7qD+H6d2A0hzc/YIrc+ixpl/oqDvNVYMVkREREREOrKODBg8A1hYWq0MKhS6E4CKASQiTJo92Cdd9SpuneJzOR5ev+YwHLzINsf4IViZOSogEREREZEOVJe4IqD0nmXBEq7yYLmx8ZYK5lwDIErN73Ww8ZHJ588pISJPBURdy8VgRURERESkn+C8n1WYzEOYNABoD2CyClnWx2QAjREm4z1oqfJHsCoa+tsBk07r0rVcMiEij10BQ1TvPveifYdYr5Zt1Kihw/M5c9/xal0NGzb0a9mIqpOOsR28rotadUfPeq132YhYv1m/gzxYBc8AFloBqywc+mzobwcKlzRothj6dL0z6vhOjdCvO6ARAISUstI/LyGEBAAppeBPqc/70gAgd0RSMhbMz6yO7x/8LhHrNes1Ees363egfcYAtkgpDfzWA0saNItQYc2Xode3DP3tgK77U2SbjbAMNuKLLTIhwgAA7ApIRERERKQfa2tPV+4Ki6G/HTADiIf31zXtVsvrSiZEGAEs9mEV5crFYEVEREREpNfBevkBLGK4R0rDVR4Ag7xI/M+T5U5defFXAAwqnOn/eSVEJHoZrnYDMMiEiNJy8RqrELXnh70oKTnp1bKtWkYjPLxe6fPi4hPYuy/fq3WFhdV1uOO6nmUjqk5+/OkIfvnlqG51Z+u27brVa73LRsT6zfod5Kzd3mKg4/VKoRCuhBCrR3e/7ca2Bb+fq3n6gtMscjq85knT9VfVXf75f+qqsOq/MJwQkSiyzTmw3Jurou6KxQDSVWtXOQxWIWrGjJle3yX9m63fokvnm0uf792Xj1u6dPJqXVp9yPUsG1F1snbdejzx+Ejd6o6e9VrvshGxfrN+h0CwCt4BLPxECBEBIG3W5q8AoMfiq5sClmHeo9QjD0AhAFPq/vxC7M8vBNBOCJEopczyc7jKAZAj5m1NaWI+knEorAHQ4Cbr5N2qXDkAcmxbqRisiIiIiIj8G6zAYOUgHZabEG+xucmvSWvGoZYglg7L4BJGIUSOv1uuAAApt/x+yPI/jwcf4TVWRERERET+CVYcwEIRQkShbHhzozvLSCmNsFyvFgkgrZKKGmP3GTJYERERERFVBSllIdQIeBzAopQ1TNm2VrnDGqjSVDjzN4P61+TpggxWRERERET6Y3dAxZvWKpuQmgNgCyxdCI2VUNyudp8fgxURERERURUyMViVsgYiT1urrKytVsPUDZj9FQCtn1WxanX0bHkpZVWkVqkSqOD3zOd9aQDv4M7vErFes14TsX6zfgfae40HkA0vBkEIsf0QBeCwehrnZbCCECILllYvv+1PIUQigEUA1kgpPb4hcY1K2qExQog0V2+C/U+JiIiIKIRwAAsLo/p3sbehymY9xQC6qgDkDwa7zy7wgpWUMg+WYRLzbJvvhBAGIUQegHQ1DxERERFR0OMAFqUttF5dW+Vkf6brsS4XrJ+TVwGwMq+xSgfQDkCuzWu56rUsVj8iIiIiCjHWhoOoavr+rQFosTfXLDnJE0UAIoUQ/ghX7ew+N49U5g2Cs2C5wZeznUQ6mjJtOvYX5Hu17NixY9CmdavS53t+2IsZM2Z6ta7mLaIxcfw4v5WNqDpZnb0WG9Z/pFvdSXo0Rbd6rXfZiFi/Wb9DhAmWroAxAHKq0xtXrVVd7QKWT6SUZhWoFsEy/Hq6XjcNtulVt9vbdVZasJJSFgoh1gDoZzdpi04JlmzsL8jHwgXzvFo2OTm53POSkpNer2tEUrJfy0ZUnRw9elTXuqNnvda7bESs36zfIcLa8mEItTd2YkibKFha4mIARKgQaa63bE+eXZharOexvpQyS11j1RWWxplEnVZtsPvMAjdYKVkawSqLP6dEREREFMLBKiSusToxpE0ELEOfJwKItJs8Sc1T/POlYVsH9rqr66qNn9kGLD0ZYbmkaJhqtdJjrIYYX4NVpd7HSt3gq8jmpSIpJYMVEREREYUcm5aacDXseDCHqjQAhSpARbqYNfzaUyU950ccxabUuw4WP9ja7If9agKwWD3V65Iig/rXFBTBSsly8n8iIiIiolCzRf0blK1WJ4a0iTgxpE0WgJkAwj1ZttOJo00B5J0Y0sYf792o/u2q7hnmNRV6w1VoC44WK41UyWBFRERERKEs2LsD5qBsyHRvRAIw6R2uVGvgZI184Y0YuxDslcq+xso6msdiABEctMJ/eve5F+07xHq1bKNGDR2ez5n7jlfratiwoV/LRlSddIzt4HVd1Ko7etZrvctGxPrN+h2CwcoQbAU/MaRNOvS5wXE4gJwTQ9rE1Fu2R8+ugemwXPMVKYQwSimNXq7H+tmYfCmMkFJW+odkHc7Qx7svU9m+zB2RlIwF8zOr4/u3BnbBbwOxXrNeE7F+s34H4HuOAbALQLGUMiKIQpUB5e8/q4dZ9ZbtSdN5/ybCMvx6MYAob4ZKF0KYVIBMUGNCeKUqugJCSmliqCIiIiKiUGdzzU6wDWBh9MM6R6th2vXcv1kAdsPSKuZtma2tcj6NLlglLVaka0r3x9mEYPzR4pltYr1mvSZi/Wb9DjiN4+YZ2kb8mHXqXHjkr6cvKzx5rqZtsChWB/N5sHRDMx3OTTZXdZlV+Dnsp9VPrrdsj9GP9aqxJ5cb2bQoFkkpfQp9NUFERERERHqGqXL3e/refIN1kv2BezgsrSVdAYxWyy4GkHU4N9lUhW8h3s/r1jVYSSlNQog1sNwvNwueXc9mndfne2GxxYqIiIiISL9QZVShKtzHVa0BkHY4N7mwst/DiSFtclRI8Yt6y/bo3mKpullaW9ni3L3sSAiRBcuoh5N9GPwCQBVdY0VEREREFGKBKqZx3Lw8WG6gG67DKvsByGscNy+xCt6OXwfZ8Md9reyGX8/yYFFrWUy+loHBioiIiIjIt1BlUAfm7XRedTiARY3j5qWH2C7zV3BLh+W6tUghRIWjDwohIqyfmR4D6zFYERERERF5H6riYRk4IdyPmxndOG5eFve2a2qodaN6alTByRVra9VuPbYvpJTWkTQMIbA/d0gpP+LXioiIiIgqIVTFwNJSFV5JmxxzODfZr61XQoiYvUmdP2h0qqSpv7bhj2us7N5DIYBIVHDdlBDCCEvXzcVSykRft1tTCGEc9MCDj658f/m1wf7lrlGjxikhxEYp5QBWdSIiIiLyY6iKAJBTiaEKAGY2jpuXp+eIgWrQh3hYGlkMAMI/xdVIRIm/3kNRJeynRFhaEScJIbJcDL9uUP/qsj9rApi08v3lmDP3HQDAqVOnfvvr5Mlff//9t8Jffv7517Vrc34Nku/3YxcuXLgKQH+1AxNZ5YmIiIjIT4ywtIpUtiw4DtvuaZAy2Dzs30Px98fO7kIdv/VmM/l7B6nh17fAMox9OpwPH2/tCpinx3YFAKkK4Gq+LWonWG9eZg60b7YQwoSyuyYDOjXpERERERHZahw3Lwr+u4GuOyYfzk026hWk1PG9CYBJSpkHACeGtCn0U3BsX2/Znjx/76CKhl+3na7XDavdvUFwV7vQUmQTsvIqI3l6YCqACQCGCSHAcEVEREREOjNW8fbTnJVBDdhgG6S0RircYhOkTC7e4yKdy72lMkKVCkuFQohZsNx4OR1lrVNWBpt9oU+Yg3stVu7YbRe0Civz22XTYhUHS/Oo9YvAlisiIiIi0oW6tup4ABRl+OHc5Cwdg5SDE0PaWI+v9VAMIKbesj2VlhHUvimE5Tq44VLKLJtp6Sp0+XxjYCu3hls3Fxfj6fETIYSAEAKpIx9DYdGPAIDCoh+ROvIxCCHaCSFGR0e3XLRi5erDAMz9+iWcEELIp8c/Y4Qar14IkSGEkEKICX5MqFkAhqunw9QdlYmIiIiIfBUfCIWIvOzkC0KIPBXyslVIsIaq3QBmAUiQUgoppUFKafTiXk3x0G+wibTKDFUqE5hhaa0CgHS74dd1vb7K7WA1auRjeOP1qaXPMzPexjMTnwEAPDbqMWRmvF06raAgHw8+MADf/3dP+L19+4UBQFhY2CT1oRe2b9/hQQBYtTrnRz/vyGoVroQQ9VVglUKIFLtpx9Tr9e3mk0KI7jbzTbB5faV6bYfd/NbHQfvtVFC+gWq5HW7OHyuE2CSEqM/fbyKH+jHFpi5uclLfpRAi1ub3YaVdHc7wcptT3Jw/xfo7QlTN62usk7+j5eqTTR2b4MU2Nmn9Xffg+GGlEGKgB8tYjw0Gujn/BHd/O4KEIRAKUfRX3SZaQQpAfSlljJQyTUqZ48s26i3bY9YpXA2vt2xPlRyLq9aoIgDh3QcOM4psc6LINhvvfP7NrncPSQZ0vKSpwmD1n6+3YsWKZejVqw+Om82QUmLw4CFYsWIZ/vP1Vhw8eMDyaX7/P0gpSx9tb2qDgQMS0KJFNJa+t8S6rshdu74LS0kdhQH391sGSzdEE8pG64hiuNLFBA8CSazN/z35MW4CIMN64OYHmzwsD1F1FWtz8NIdQH0n9cn+ACjFPpTpeSAJIEP9ThCR67/XE9Qxy0TVsjDVw/rWxO7v5UAPy5DhxTKelG8CgCkh9rkZAqUg/eKfHGsfpFQrjW7UNVExANZ4k/8AxFVVqCr9wO4b8Fz7l7Kw+cH00bBcLjTpiw4P4dMB04APj+eJbLMun2mFwWrv3n0AgC633IqIcMsw/cuXL4WUErff2gUPPTwUANCu7Y0QQmBG+hxs+PhTAEBEeDj69otHQUE+Nnz8KT7/7HMAQFy3u2w30RWWpstsWEbmMMNyTwCj+uJG+PIGq2m4auLGj9hxjTAVC+d9hgepH3yhRk7Z7CqMCSGa2JzROmg/n5pue4btmLUFTAhxzObg8Jj1j47GGfcpIKrejgOob3OGOtaufltDjvX1Hqr+plrrrzoo06rDA21avzbZhyQ1/aBNfdyhzszHArC2TFvP1Me6qvNE1cROu7+jE23rrVaLlWrpsW2F1mrNsoaizc6ClWpBPmi/HtWqbJ1/pbNWZq0eLW7+HtiGqgnq77vT+YPos4wMlILsNt94WO8g5SRcmest2xMPy1gGFQ72cPTSuvi2XsM1sFxTZarq/WQaPu/pXW36ufo8c0W22ecunjV9XcG/X3gWHW/uiH378rF921aMG/MkACBz/iIkJyUirls3vPH6VOzYvgNbv/kaLVpE456eLhsiwgH0U49J1u8Nyo9C6FFfSClllhACKqGG+miB1gOqFCFEppRyp4t5D9n8oKeoMLMT5Vux3N2ePdsDsSYAUlxMh9p2hhBis5Mfda0zahOEEIeklJn8e03VlLUOx6qDqhRVJw9phSz1u1Bf1Rmn9UYd4NgePDmcGLGbbj04XAlgkBu/CeXqvJTyED9Kqub1WDPMwPEk6RQhRBMpZaptvVb/TlX1KlYIkWL926i662VorMeteqdRjoEe/B5kaqzP1fxNA/3DUsOsB5IYWBokKoUKSYYTQ9pEwdIAEqXKEKGO083/lo1bzlqwPlUdg1f5LZpEttkI7QE97GWJbHOUTIjwuswVtli1atUSALD1m69LB6x48MGHIITAipWrAQC977kbY9OewPLlS5E53zIYX0H+vtJp1u6AGzeuR99+8aUtXx5oB2CYCka7UNYSaz1+AAAgAElEQVSF0Ag3uxBWs5YrazeCiq6h2Iyys92xdme87JVrLVIHWocArNI6M6YOoA4BaGrXwmX9PJranbmzHvw1kVJebvP8cinlVCllqpMWM16DRdVZacuxOlhpok6O2Na1QzYHNwNt6vJKZ61VNgdqm1V9u9z24E9KeciuPvaw1kd1Mqejem49Q7/TVZ3nx0jVRKzd39Epqg476/pnbZ2aqOrMIJsTJE3U39vu1r+3UsrNNn+TB2rU54l2LdYpUspBNssMUs+d/R5Mtavv7vweTEVZy9xUKeXlruYPks8xil9loN6yPYX1lu3Jqrdsj7Hesj3x9ZbtMaj/p89asd4axPupe0VVtTQ35wsHkOjLhhyClbm4GEIIREdbAtXtt3bB4MFDsHHjejSOirQEKnXN1T09uyM6umXpaIFCCKQ8askuLdTyAPDQw0NRUJAPAIjr1k2vndQVlhatbACHHxma2BkAFr+7bACc9H2tLuFK/ZDtVD/iri6C3Wlzpqi7OtDZ6cYmjqs/BB2llFotVvVtDqqsB2NaZ60mqK4PO9z5QVVdB6aobkm8/oqofOtUd2cnR9TZ7Ykof2Z8IIAdTsJVfdt1qXqudRJliuqS69YgFZ7WeaJqoDs0uu6rVuP6KjBNVfVwlU39jrULUKts/tYeR/luvrG280gpM1Wo6eFmGevbLb9Z61jBi98Dj+anoDoOLURZd8EqHUFRXTvlSYuOT+V1a1TAt995C089XXZ8npI6ClOmTkVEeDhWfbAaKamjSqe1aBFd2g3QqttdljDVq1cf9L7nbr/suIsvvrgOALRo3uxxALmwtGrlwTIwRiLUkIrVqOXKeobIVbCy7Y/dBM5bqwB1jZWapz6AWCehyr0vuuXAylq2Hig7e33cyfwZ6se3vnpvq/jTRVRaj+vDppXJ2QkXKWVTWFqfpqq6Vh9eXLSurpc6ZnNCpofedZ4oBNlfY9VRff99GTjCuuwE1Qpme43ywMp4U57+Hnjz+xFIDucmm/hVdov1+DqtOr1ph2usIsLDHW4WHBEejtenTcHr0xzHCmh7UxtkvPMWMt55y+lGbr+1ix43IHbL9OnTUa9ePevTdrDpU3nhwoVzf586dbJPn/uK//e///5cVFR4rQpXhXrdGCyAzhZsFkJkwvHaJtt5Dqk+1hV1A7Rdpoc6QOouhMiw6+cNuwOl7qov+CHbcqj+3rGwnImb6GIkM+v8tgeNmSh//QhRtT9YU/9a69ROdU2ptf5Yr484BMvgFYeEEFPVQY2zenTc5sBsqjrzbd+1qPRsekXDQ3ta54mqCWs9q28/kq+qx8cBNBFCTFD1bCDKWqZ32lwb7UyKOomyUy2XAmCiWi5D1cembpbT+nc41aY+e/V74MX85FqgBr0cWBo3IoUQMVLKvOrwYdQMlTfSu8+9+OnHH/HBqvcrer8RcBxp8LMQ/XwnqoMhVz+8mSjrhrDZzcAyEZYL0VPUheer7P4gZKofyiYADtoe5Nn9MWmizrDZsi/rMbU96w/7DhCRfX2bouqH1smRVbC0FGnVR80ufup3IQXqmhBXwcvJdCvr8hM9qPNEocpZfVolpTyu8bdyqvr7PMVuFNxMdYLEerJjou0Q7SqkHVT1rbuqz91hM7S7TT23tVIIsUrjOivrcUKKk5E83f09mKCWn+rm/IFsN9wbDKEyFAbo3yazECIHljES0uDjtUtelyMhwiSyzcVwvzugTwOB1AiVX6v+CX0xM30mvtn6rduPAQMfsC5+UYgecB2H84tiraxnuw+5OzKX6l9tXe8UJ/fM6mG7btsfcLX8RLsf7XLDzmqUO9Xmx3szyi7i5bVWRGV1badGfT2k6qN96NoM1YKlscxOVcds69wqm+lT7daXCpvBcNTyq+y2VVGdJ6qONqNsMAn7emgd+MG2u+xEKWWq3b2rNmv87bf+FgxUJz9TUf4aS9swNhUuuuTaDUBhPVmz093fA1XfrfMfd2P+YGAKkHIUHc5NLgzg/ZSl/o2v4nKkuzlfsU2ZvSJguRap0rrqBZKkR1OwcME8AIiTUppARERERORC47h58bAMnlalatW4sDz/s9QhgbyvhBCFsNwnarga56Dyy5Bttg4FX1Er43CZEOFTGWuwehARERERuedwbnIOgKKqLkfTOl/2FUIYhRARAby7rEGlylqt1H2pDADWOJmlGECCr6GKwYqIiIiIyPvAUCWuveTUmY0bll4Gy62HCgM4YFn3U5Xe00omRJhlQkQ8gMYAxgCYrB4JMiEiQiZE6HKT5ZqsF0REREREHkmHZVCG8KrY+M9/X9oTlpsVG2HpajcJwCQhxGIARnUvqSonpSwUQmyB5f6z8XD/eid/BaxCf5aBLVZERERERB44nJtsRtXdo2nL4dxkk5QyS0oZBSAOZTfkHQbgsBAiqypbiOxkqX9D/p5Wmi1We37YixkzZnq1wuYtojFx/Lhyr02ZNh37C/K9Wt/YsWPQpnUrv5WNiIiIiMiLcJWlBrLoV4mbLYbd9UpqADaDEMIASwtWVxWwhqkWrPQqvo9UtbmnlWawKik5aR0tz2MjkpIdXttfkO/1+pKTk/1aNnKP6rcbA8BcXW7yRlSN6rfB5o8zEYVO3Y6CpbtYYaB0DQtBiXBvxDm9GFRrmQO7gJWmAp81YG2BpYtgpf/OB8o9rSoDuwKSu2IA5KKK+8YSkV/kqgcRhd5Bf24oH8hWNRVyDLDcNNjfhh/OTa7w5LaU0iSltA7UsFi93BVArhDCZD2ZVsmy1L/xofx9YLAiIiIiIgrccFUMIO5wbnKWJwtJKQullIkuAlalBW7VUlYEILwyt8tgRUREREQUZOHqcG5yDIBZOq96C4CYw7nJJh9CjW3AmqWCWlcAi4QQhZUYdKzBMGRbrRisiIiIiIj0CVhpANqjbJQ+bxXB0vXPcDg3uVCPsqmAlQbLdXeTVcCKrMSAZQ1W/QJoxEJdaQ5e0ahRQ8yZ+45XK2zYsKHDa7373Iv2HWK9Wl+jRg39WjYiIiIiIh3DVR4AQ+O4eQZYrm+Lh/v3u1oDIMfTbn8eBiwzAKMQwnovrjSbgGWE5Xr6LDWfntsNqHta+YMAINWbrXZf/KRHU6wjDMZxNKwKviiWCx1zAWyRUhq4R4hCqn5b/w4I7g2ikKrbRlhuHDtZSmnkHqk6jePmxcByHZZ1lOUINSkPgBmWkQXznI345+fvSYQKOkYVsABLa1Y6LEO1m3XcViKARQB2SyljQu1zrsmvOhERERGR/6hWrIC8XY0KTlkAslTwsQasSQDSVMuWXgHLek+rdqF4TyteY0VERERERJBSZkkpowAMhxrFTwWsQiFElq/XRqlwlqOeJoba/tNssSouPoG9+/K9WmFYWF20ad2q3Gt7ftiLkpKTXq2vVctohIfX81vZiIiIiIiofMCCpQXLAEsLVleU3Wx4MSw3Gy70cvVZal2JsFzfFdrBau++fNzSpZNXKxyRlIwF8zPLvTZjxkzrtUwe+2brt+jS+Wa/lY2IiIiIiDQDlgmAQc+AJaU0CSGKAEQKIeLlCZhgue4MAAoR5nVgq3LsCkhERERERC7DkBq8LA6WkQuhAtZhdbNhgyfre+Th+3LeXfAQjhc2XQrgOCwDpOUCOIwSYUaJyEKJZ+sMBBy8goiIiIiI3ApYAEzqWiujClddAeSqodSNFY60XSLSl7yF0erZpRpzhKv1DkOJWAMgEWHSHAz7hy1WRERERETkScAqlFImAmgMYLF62RqwTEKIeI1AFYESkQeUhip39AOQhxIRFEOzM1gREREREZEeAatYBaxsIUShGr7dKgdAOy82EwkgByUigsGKiIiIiIiqQ8CKAjBZBaxIAIuEEIVbNyfkqMDlrUhYRhMMaJrXWHXpfDOklLptZMH8TN1G49O7bEREREREpEvAMgMwqpsKpwFIa9aseeRNbbZF6rD6figRBoRVcA1XFWKLFRERERER6RqwpJRGAFEzX4vNuazuUb1WnRjI75ujAhIRERERkV8CFkqE0HGV8YH8ftliRURERERE/qLniH7hgTyIhWaL1Z4f9mLGjJlerbB5i2hMHD+u3GtTpk3H/oJ8r9Y3duwYtGndym9lIyIiIiIiv4nUeX0xAExBE6xKSk5i4YJ5Xq1wRFKyw2v7C/K9Xl9ycrJfy0ZEREREROQrdgUkIiIiIiJ/KdJ1bRwVkIiIiIiIqiE9g1BRIL9RBisiIiIiIgqGYJXDYFXNCSFihBBR3BNEREREVK2EySzo19KUHshvVXPwikaNGmLO3He8WmHDhg0dXuvd51607xDr1foaNWro17L5OVAlwnLXaUgpY1iziIiIiKgaSgOQ7eM6JiNMFgZdsLrh+uvwr8dSddtI/4S+uq1L77L5IUxFqS9PIoBw9XIc6xMRERERVUthMgclYhaA0V6uYQvCpDHQ32ZNftK6BapEFaa62k1aI2Xgjl5CRERERFQJ4SoNJQJehKs16hg74DFY+RamotQHnYay1il7K4QQhhB4u9aujBEh8n6IyPE3jXWbKLREcRdQAIYrEyzXSlV04+BiAEaEyfRgeXuawaq4+AT27sv3bn+F1UWb1q3Kvbbnh70oKTnp1fpatYxGeHg9v5XNy4OPGABGAP3cmH15iFWJdgBy+ctAFJJYt4mIyN/hKgdADkpEPIB4WE7et1NTiwDkwTL6Xw7CpDmY3ppmsNq7Lx+3dOnk1QpHJCVjwfzMcq/NmDETCxfM82p932z9Fl063+y3snlDSpknhMgBEAHHrn+2zAB2swYRERFRFcmSUmZxN1DABqwQwq6A3oerLABZqjugUSVu++6AEQDSpZQ53GNERERERKGL97HyPWAVSikTYenHPByOLVTp3EtERERERAxW5F7AMksps9T9qtoDWAzLRXeRQggj9xAREREREYMVeRay8mxascYAiBdCRHDPEBERERExWJHnAcsspUyXUsZIGVyjmhAREZHvZtWqwxOrRNWE5uAVrVpG45ut33q1wrCwug6vjR07BsnJyV6tr1XLaL+WjYiIiMiPYgCYuBuIqmmwCg+vV26Ic1/pce8of5WNiIiIiIjIV+wKSEREROQ/Bu4CIgYrIiIiImKwIiI3aHYF3PPDXsyYMdOrFTZvEY2J48eVe23KtOnYX5Dv1frGjh1Triuh3mUjIiIiIgpVQoh4KWUO90QVBauSkpNYuGCeVysckeQ4SMX+gnyv12c/6IXeZSMiIiIiCtFQFQUgWwhRnyNU+x+7AhIRERERhaY09W8idwWDFREREREReSfRLmARgxURERFRcJlVq04UgK7cE1QVhBCJAMLV00ghRDz3CoMVERERUTCK4i6gKpRYwXPSmebgFWFhdb0e6KF5i2jN17xdX1hYXb+WjYiIiIgolKhBK+xbS/sJIaKklIXcQ5UYrNq0boUF8zN124ieQ5zrXTYiIiIiohBjdPJ6ootp5CN2BSQiIiIiChFCiAgA8S6CFTFYEREREQWfWbXqRHAvUCWKh2XQii0AZqnXMtTzSDWoBTFYEREREXkcbGKqaNMxdv96UmYDPznyIVglSCkNAKw3Bf5VPU/w5vtIPgSrrdu2Qwjh1SPp0RSH9SU9muL1+rZu2+7XslGVk3zwwQcffLj9MPLPhk8Bp7L50lLFYEXeHVhJGS+lzHEyLUdKyXtaVWawIiIiIgohUdwF7mNrGRGDFREREVGohIWqvC6LwYrICzW5CyiQmD7/HDt37eKOIKJqr0GDq/Hww49wR1TPEBgBXgdDxGBF5IsVK1ZgwZIl3BFEVO11urkjg5V+ooJs+1UdqjiKIRGDFYWKoYMHo1at2twR1cS7y5fhn7NnuSOIKNSClSFAgp2n4gFwgAMiPYJVq5bR+Gbrt16tMCysrsNrY8eOQXJyslfra9Uy2q9lo8BkfPkVXH/dtdwR1cQH2R8yWBFRZYQcUxCVtypbjSL5dSHSKViFh9dDl84367aRNq1b6bYuvctGREREFIChqh13A1GQBiv7+0VVBydOnOA3gIiIKPRFBVl5q3zgilm16kSNPnO6kF8dIi+C1S1dOnFvEBERUShi1zb3A1WMTRhlsCLyMFht4W6AmbuAiIgopBmqYJvW66S8aoGaVatOxOgzp81VVGYi8jRYSSkN3A1EREREumvnZViJsglkJu5GouBQg7uAiIiIQtWsWnWigrDYVVlmawg08NtDxGBFREREFAghJRjFcBcQMVgREREROdM1CMvM652IGKyIiIiIyEtR6t+qbD1iqCNisCIiIiJyCCmVyu7aLk9byyIDYH+xSyARgxURERFR1QYrBO+1XVH8yhAxWBERERE5NatWHUOQlYnd8YgYrIiIiIjIDfF2QSvK5mlVdseL4kdD5Jma3AUULMaOHo3jZu9vQF/zootwUc3yX/nWrVrhwYcfwRVXXIEaNUSVvr8//vgT458a53T6osWL/bLdKa++ivz8/Ep/v926dcMjw4bxi01E1T0gxMyqVSdm9JnTee6Wd1atOmmjz5xO91d51L+R/OoQMVhRiFq3cQMKf/xJ9/WOe+YZCAjcHNsBN7Vpg9SRI9G+Q4dKf39vTJ2C995/3+n0jh064PHRo3Xf7memXJi++LLS32/t2rUZrIio2gSrWbXqRIw+c9rspHwRHqwnys/vKZxfGSLvlHYFFEJMEUJI9dhkO5MQ4pjNtFh3ViyEmCCEmOJtwWzKM6UytkfVm4TEtzt3YsGSJeh06614a/bsSi/DH3/+4XL6rt15/KCIiHxjqMRtxVTw3CrSRbkinAQxjthHFMjByk6sTWDpDqC+h6FoAoBKCzmVvT0KfaPHj8f4ceMqdZvrP/7U5fSvv/2WHwwRUfCosBVqVq06MRrzRtn8v52TcFgpwcqmfETkZbA6DqC+ClS2Ieu4XZgZKIQ4qFqVjgkhUjRCzgQhxDGN+aUQYodt65eafsymxayJi+2VLu9ie02EEJts5i8tI5E7Zs6diwbXXIPlS5f6fVtz35yLY+bjLufZf+Agvs/bzQ/GTz+E015+GcsWL8b9/fpxhxCFlqggCF8xHpQ3BkD4rFp1dB8xUGOEQo5KSORjsDpkF6hSVKg6ZBNyugNYaRN+6gPIEEIM1NqIEKKJ3fzW9a9U063/t7aMdQcw0N3lndik1gO7Mjbhx07uOmY2I2XkKL9vZ+IzE92ab9GCBfxQ/CBpWCLGPPUUBj7wAN5//33Ede3KnUIUOiIDOCgYNIKVu0GRrUlEQRCsNlvDjQohTQDstJvHGnomSikFgB7WECalnArAepQ4VUp5uZTykJRSWB8289e3CW8AsFlNv9w2yLlaXmt7apmmdstYmwMYrMgjp8+eQUK/vn5b/949e3D67Fm35v3p6M/8QHTWt3dvTE8vP7hW4xtu4I4hCk2BFkasIcnpgBEaLVPtGKyIApPWqIDW1qlYlLX4bLYJU0BZa9YUuwEjXA5sYTOvfZe8+rahTkp5XAixCsAEN5d3tr0Jat0eXydGwSVp6NAK5/n79N84c/Ysjh07jr35+fjt199wAdKt9X/0yad4+805GPWvJ3Qve3q6+yPmrvloPU6dOoVLL700YPart+IMhir/3tx1551Y/eGHWr8drFRE5K8QpfnarFp1DKPPnDZpzBcDwKTm8aTLoDfsQ5zBum0i8i5YWQNOik2AsQ9WztQXQtTXOEhpAmCHCmyrYGlx2uFuIb1ZXgixA5bWqUw1/0EVro7zYw8972RmerXc1q1bMXJkKvbsq/g+TuOffc4vwerob796NP/sOXMwccKEgN6vwWJG+izN10+fPs1KReQlIYQJQA6ALCmluSrLYnez3cpmcCNYxWiEmig3w5k/WqzYCkbkA2ejAlq7/sUCOCSl3Olk+kTb7nbqoRVcUlSoOaS67nW3m25dZqBNkBrowfL2P+oDVdmPSyknqv+zxYocdOnSBXl5u/HJuo8Qc+ONLuc9feYMHhg0UPcyfJ5r0nz92kYNNV83Gifzg9NB59gOaN26lea0r7Zt4w4i8l46gJkAjgshsoQQVXmwbh9SAu0aq3APQ00MQxBRkAUrKWWmTdjZrDHLKvWv7b2vpBDCfjAJ6yh9pcFJCCHhODS69bR4rJp+EOWvhapoeWfba6Lmt70vFwMWOejWozu279iBp598EgLOu4F9uHYd3pqj3z2uFi9ciH+cXF81+YUXNF8/Ly9g+rRp/NB8NH+e9kAg8QnxKCwqcmsd7dvFIPGhh3Brp07coURlxxA5ALaop8MA7BJC5AkhEoUQVR1s2gXKftIYgS/KyawRTsKUX0YGDPAgShTQarqYthOWlqGdGj+am4UQqbBcA2UNQKuklINsgpJtq9FUNZKgtaUpVU3vLoTortY3CECGCj6bVTgaqLbncnmN7W0WQky0CWCZsHQjnKLm2cyPnrS8Om0aOsR2xIPDnF9b9Pa8+XjsiSd12d6WL7Zovl4/PBzDho9AyqjHNa8D+88332AcPy6vpY4YgZYarVVzZ8/B+o0fV7h87YsvxvtLl6JP37JBTfYX7EffhHgcOHiQO5gqhRDCgMq94a0n8gB0tQs0iwCkCyFyABillIXV/COMcBKs7ANWDCxdK51NM+lYJq31E5G7v8tSSu4FqkrlvoAjU1KwYMkSHDpwENdfd225GZu3aI7CH3/SXMlZna+JGThoIHLWrnM6/UjRj2jQ4Gqft9OydSscPHTY4fVePXpg7bp16HF3D5i++NKx4gI4o9N7drYNf+xXZ6666iqYS0oq7UtXfOyY5gAgHTt1wu7vv69w+TGPPY5pM6Y7vP5oUhIWV8J9z6h66HRzR3z15X/sX54MwKiClRHApCB9e8UAElXrVqm27WcF83si7235ftdoA3eDHw70y34nJkspjdwj/lWTu4DI0bCHHnYZrKa99qrDEN2eOnnypGaoAoAGV10FAIi67nqnaXTHtm3o2LkzPywPzU2fpRmqVixb7laoaty4MV587VXNabUvvpg7mCqTKYDLFgVLN0B7u2G5BitHa2CL73eNNlqDY6UefKausw90s2TGfWkidZ392ec49d4W2YYCmXFfwIYCkbrOhPKth5Nlxn3GYNtGNQtDBujXGm1dj0GFrIr8DmADW5QZrIh0c2+/fugRF4dNubma07/46iuftzHj9dedTrv11tsAAN179EDWsmWa8yxatIjBykM977oLKSNTNae9MuU1t9YxsF8/1KldW3PaiZMl3MlUaaSUpkANV0KIPJunxbB0ZUuXUuYFcEi1DVauylkYRAEXAMwhso3qEqoSe/bsNfuTTzaG6bzqrnbh15kLAN4QQtwawPWVwYoo2LRv29ZpsMr77399Xv9PR444nTb80SQAwAMPPoiHhw/XnOd/+/bxQ/LQuLHaV6bNmj4D+woK3FrHfX2d3yx6dfYa7mTigaEQabBcU1UES+tUlQ+77oY8J8+LAESWhtmM+0wAIFLXwc0QFijvrZ+fQ5D9NgpZE7wW9cknG8NGJCWjfQfL7WFPnTr1218nT/5qNpt/LTx8qHDt2hxP7tNiUIFqixsnAboDuA3AJQBMQggDwxWDFZEuJr/yCqbNmuV0+uxZs/HkaO8HsTD95z+ar3e++eZyzwfEx+ODnByH+b7euhXFxcUIDw/nh+WGli2iEXdXN81py95f4fZ6zpw95/DauXPnkXB/PM6eP+fWOvr26YMmN0QiMvIG7P7vf5HF67IoxA4MAcSpFrWgIDPuM4vUdbtVICyWGffl2QSESI1FrPMGY4iojANlBisfte8Qi389VtrDooF62I5quUV9lib1b6GTEx1GFaxMFV1jJYSACla/qe0xXHmoBncBkZOzDjVr4tUXX3Q6/aWXX/J63R9v2Oh0SO8PVn1Q7vm7773ndD0J99/PD8pNj6WmOLx24YLEvffeh+/cuLaq9HN/0fHv0u233YKPP93k3vKTJmH16tV4feYM/CstDfMWLEBEWBg/IAoZUso0X0OVEOKYEGKl+neHECJW/X+T+jfF5rWDQogpapoUQkzxMXC4cxBZaBPKeNDJroB+t2LlagghIITAipWr8f1/93SNjm45WgiR/fT4iYcBFF533XVnnnt+0qbvdu2+T9UFb2++maVOHoSrcMXRIRmsiHw37qmnnf8VKSmBt2NqjlBd/exFRUbimmsaOAS8O267TXP+L3W41qu6GPX44w6vvTV7Nj7ZvMmj9Zi++hrJjz4KACgoOIAut9yCnbvdC2YCwPgJEx1eP63j6Iu1L65Vzf6ICYSH1atwvs6dOuH4n8fw0OAHWBmCQ31YbuNyOSz3zlypXssE0BGW27PEqtd6wHL7l0wAl8NyT8tYH4KVyUlg2K0x75Yg2JemSthGnrPgSfqY9MJzyJy/CJnzF2HSC89h27fb0bRpM6zf+AneeH0qvv/vnsixT024+NDBA90L9h9Y26JFNKSUz23f8V388y8YMWbsU9d4sLnTsHQhZLhisCLSsYLUEIhw0dVuy+efebzOH4t+xB/HjmlO63q7doCKbtrU6fpee+UVflA24u68EwMSEtAhJqb0wHvrV19rzrt46XtebSPrvfdwcZ06aNP2Ruzctcvt5e7p0QM1ajjegPrSyy7z+v126dwFTz05Gn+f/AtnT5/GyZITWJSZiYuE5z/v/ePjMTIpCa8ajfhXcgpGjhiBmBtvDKjP95oGDZD40EN4b9EinP7rL/xz+m/8+cfvOHv6NN6cORM17G7w3TgyEk+OHIn/fPEF6ta9FLd27qJ7mRL69sXRn39B4aHDeICtyJVOSnlI/fe4lPK4TTDzNoDkOQkMZo15gy5AWK8T8/M2GKx0VlCQj7CwMCQnJSI/fx86d7oZ4eHh6NOrJ3r16oN69cLQqdPNWLFiGXI//wx9+8UDQLuOse3bvfTiJMyY/nqq+g6bYBl5Mx4ubgCtrotkuPJQlVxjJYRIh+Wmc2nst+9DpiwAACAASURBVEmBrk/Pu7F05SrNaStWvA9Dt7s8Wt80F6PPdTPEaR/w9u+P+UuWaE77ZtvWav35CAD9ExLQMaY9xjz9dLngsuy9pdi0aRNiYzs4LPf61GluD0LSMSYGd9x2G66+8krUueQSfPrZZ9i4aZPHZe3Xt5/m6xs+Wo8uTkK1Mze1bo2XjMZyNym2enjoUPx85Aied9GV1aptmzaYOH4CBj4wyOk8wxMT8d4K969Du7R2HZz6x3UrXM0aNRDfrx/+/vtvrP/4Y7fWO+ZfT2DKtGma4RQAUkeNwq+//oqXp04FADRq2BDZqz9EmxvblM5z8q9TeHDgANSpVRthYWFo2rQpbrn9DjRr1gxhYXVx4YJEUuIwvLdyZYXluUjUwDtz30TiiBGlr723bBmO9boHm3KdH7uOevRRJCTcj+zsD/H2/Pn8kXVughBiJYCdAAYB2AFgigpNqep1a5A67uT/noSBPDUohTvBo1AjeFVn7AroZy1aRKOkpAQrVq7GpBeew0MPD7UGIAghsHXbdgwe1B8tWkQjM+NtrN/4idZqwuE4OmCR+h6bBg8eErVixbJy4UoN/W6C5fouXnPlxpmeSn+oD0gCMFTF9vkIqEc5qcnJsmbt2vLHn47YT5LNmjeTNWvX1nz4k7VMWo/U5GSP1zdg4ACv3oezZXx9/917dK+S/WrryiuvdPn+nD3CwurJ//33f15t87obbnBrGw888IDm8rVr1/GorEveW+qyPLU8WF+z5s3luXPnXK7v0KHCCtfTNS7O7f3lTrk+3rCxdP7zFy7I7t17OJ33C9OW0nkHD37A5Xp73H232+X85quvSpd74Zlnvfpu/PPPGXlxBe/1iiuvcrp81oIFTpd78MEHy817401tnc576+23aa3eWB3+NqhjhO4Vvab7dlPWZtk9NyJlrVQP+2lmpKwN+OMYpKyNsHkP0o/bsW6jkMc2Pn33jQDknLnvyC+/+kZaDtVl6f8ByOXvfyAPFxbJXr36SABy8OAh8rjZLKWUcvrM2bJFi+jS556YM/cdCUC++tq0QillupQyUUoZpVq28tT2zQBi+FlpP9gVkKiiZt2LLnI67fz58x6vb8sXX2q+3io62uVyXW7u6HTaf77YUq0+k+uvuw4jHnkEBw4eKNca4a6FCxbi199+cznPFfXrY8Qjj2CFk5aahtc2cnt7T4wahUceGuJynq533uFG65zA4AEDsHnTZlzk4nsJABcuOP9u1r30Uox45BFs+uQTt8r//PP/rrDVcGFGBnr2uqf0tRpCYOPGDZrzv/7qq7ij652lz1u3bO28FfeOO/Dxxo/d3td11M2fY268ES++6l032Vq1Lkbrli2dTr+kdm3MneX8BuHNmjfXfP26a6/FzJnll7utC+9F54RWq5NXLVEesv9gTRqtVLBprQr4M/cy4z5n14n5SyG/vvq4/dYu1rBV+n8pJQYP6o+oyBuwYcNHkFJi+fKlpZctjE17Avn5+1xexlCRZ58ZHymEGC2EWCSEOKzqXTubVq83+Ok4OWbkLiByLeqGG5xO8/SGsB+tycFxs3aPidsquNlvzE1tsXX7Ds1p7723FLff2VX39/6y0ajr+trceBMSBvT3aR197r4bK1atcnqT3opcuCAx7Y3XXc5zkaiB5e++i7ju3TWnn/7nH/z88y9uba9vn96YMXNmhfM1joxErovpl9SujfkZGRg0eLBb21327ruar0fecAOWLFyIW2+/3f3vwcsv4orLIzD+2Wcdpt3YqhW2b9+OmjUd/5zYh78brr8eS5e8iy63dHEIHPZaNG+OJ0eNQupjjzlMMxefwCtGI2Lat8dDQx8pN+1z1UXz7bfe9ul71vnmm7FH415xNWvUwIKMTAx0MQjGco2beteAwOuvvooGDa7mj6o7YcAyaEWFr/khhHgSlLLsQksw8Gd5i9VBNwUp6/DuTzw+sqJZr+TeYrAi8kp4fafXduLsmbMerWujizPvnTt3crnswIGD8M7ChZrT/HWz4MlTpui6vl49e/oUrO7r3RsffvihT2W47bbbcPDwYZfzjExKchqqAOCVyZMh3RgTsn69cKxe7V55L61zicvpk5591u1QBQBbt2/XfH3qK694FKqsnhydphms5syarRmqAOC7nTvLPe9/X1+HUAUA277d5njEumAhbu50s8Pr/5w5gw6xHfDTkSN4LDnZIVgVFBQgM2MeOmos6wl1PxeHcPT7738irO6lLoN7xqJFDq//+NNPaHAVj0WCnNkuhGUFUdnL3ejYT/JguXankF+V4A5XNvfPKv93Zdt23NKlk78DelBjV0Ciig6O6zs/SXr6zD+e/WU78pP2QRyAxKRHXS57Z5zBYcSzsgPTb3H6n39C9jO4SNTA8Icfxvvvv+/TetatWYMdu75zOU//hHhMd9HNCwA+/azi0SDDLrsM895+q/xBf36+0/l733uf02kPDhiIcRMmuP0+9/7wAzZ9trnca5dH1MeijEz0H+j6tibWbicOn8FFNVDLLkB1vfVW3O6iC+Nbc98s/X+bli0xdcZ07RMUZ8ufoHj1xRc1Q9UP/9uDWzp3wU9HjqDBVVfD+FL5e8mdO3cOW3fuxPBhj/j8ndtuFwoB4LVXXnYZqgDgheefc3htxtSpTkPVrt28BjzAORshMNgU2v1bGdsiYrAiovKubtDA6bTiEyfcXs/pf/7BJ5u1D8hfnjzZrXX06d3L6bQZ06aF6I+UwNLFi5E5fz4uvvjiCudf+u67SE1OxpSXHa+vmfa66y6A995zD1YsX+Hy+qU3Z8/Gd7tdX6YQ264t/vzjT/Trb2mdO/LTEdzdsyfGPvWU02WimjR2eK3hNdcgfdobWPLeux7ts5SUZIf2tJlvvI6Hhw11udzU117DYo3WltITADZDuEdFRuKjjRudzltQsB/vLX+/9MTBzDemOzktAKy3udYrefgIPD1+vMM8b0yZirju3fHfvT+gXZs2OPLTj6gfUb41edjQoYht19bn75zx3//G93v2lHuth8GAsePGOQ+kAFKTkzFtxoxyrz83fjyeGD1ac5l3Fy/Gd7u/BwWuIOzqV5Whh60YVO2xKyBRJXl7zhzN1y+CwHg3WyOimzXDOifTQnXY9RXvvedW98H5mZl48623sGffPtx0401In11+f69a8T627tjhdPlrGzXC8gpaxD7Z+AkmVTCEeYe2N+E/X31dOiT4z78cRe8+vbG3oAAXOY0WwK4dO+0CJbBkwUIY7urmdJkL5y+gxkU17ELBJGy1W9fQBx/EkIcfdrqe16dOxXOTJqFNq1bY5eS+XOfPn8c/Z8+UPp/8wgsur3MbkTgMF1S8G9S/P+K6a9+WYEnWYvyfuq/bY48mY9abjvXk5ZdewmR1v7abWrfGli++KDf9t19/w5Ojn8SHa9Ygaajr8HjmzFns+u47bPr4YzxvnFRu2t9/n0ZqyqNYvuqD8vWuefMKh4S/y2DAl1vL6mCzpk0x9eVX0DchXnP+kydP4qXXXuMPI1WWygg9eQD6gS1WupoybTr2F+S7nKd3n3vRP6Gv2/M3bxGNieMtJ4pWZ6/FhvUfuT0/MVgRBYT8ggLN1wd5cM3RS6++ijdmz9ac9vHmz0Junw0b8mCFoerggYPo3KULitVAIheJGvh221aH0Rw3bFzvcj197r7bZVDYs+cH3JvQr8Iyf7Th43LXHD02aiT2qs/e1VVZn+eW//xSk5Jchqo//vgTL076N+a8Vdbd8Icf9uGVaVMd5p3p5DsDAC8bJ2OyurfarS4GUCkqKuvG2r5tjMugtubDbGz7rqzL5cuvvOo8rG6ytFbd06OHZqg6d/48XlLL14CAacsXuMzuhsopKcnY8OmnlqPHE8Wa21m/7iOMmzAeBw9Z7iX78AOOg0+M/tfjDqEKAHr3uNtFJAZen/JauVAFWK4R6+xixL+OHTvicCGPP4NEEYDIyrixbiWEnsoIWPxi62h/QT4WLpjncp72HWI9mn9EUnLp/48ePerR/OQauwISVeDMmTNOp9WuVcvt9Xz59dear1995VXunwmpWRNNNbqMWb05e07I7Pd6l9XFM88+7/xzOXcOLzz7HNrcdFNpqAKAhZmZmkPku7phKwA8P2mS02k/Fv2IIRUMlw4Ab85Mx1VXXlH6fOqUKdhg083tgotodfKvk6X/79Gtm0OXsnIhcd063Gnoip9/PVoWnqZPR7sOMQ7z9oiLQ72wMM31LFqwEC/a3LB6uM2Nbu0tWWQZOCXyhhvw7bfOW0dPnfobxpfKWvXu79cPUVHa18z//sef+Gi9pTvhgPvv15zH+Py/cQESPbvfhQ9WLEe9sLpl+/PCBQwaNKg0VAFAds5apD3xBE6dOlX6mgTwb+Ok0lDV4Kor8eLLLzuEwUVLlzpsv0vnznhVI6xafZGbi6nTy4/6OO2VV1yGqlkzZ+IgQ1UwCaUPK4/7ich/2GJFVIFffv7Z6bRLL7nErXXs3LEDBQcOaE5LGTXSo/Isf28pOt16q+a0MeOfxsjHRjkdpS1YCAjs3bsXV1/tGDrPnD2HR0cMx/JVq8q9fnlEfbw9Zzbu1xicISEhAb/9/rvT7T0woD8aNmyoOe3wocO4r19f5O/f73T51i2jsXzZCrRu3QoAcOTIz3hy9JNYt3693fvSZi4+gew1awFYhi/fsEH7/k+7d+Vh+vQ3sPwDS6vKgYMHcXGdOi735bixYx1eO3fuHEalpCDLZljw66+7Dh07OR+ZcmeepYvggwOcD37x4apVeOCRobC2zV1Rv77TAUfy9+XjxhjLbVFubN0aw4YPd5hHAsjP34ePPvwQPXv3LgtU5y/gReMkZK9bhx/sRsS8AInFS5di5GOPo2Wrljh16m/06tOn9JqpNi1bIi8vzy7g/YGxExyv62oVHY0vtzi/R9zEp57CmxmZpV0ka9aogbffnIvEEcOdLrNv7z489cwz/GGlUA6gDFjEYEVE2kqKi51Oq13LvXsppaSmaL5eAwItKrgxsL32HTqgBoTT1o+Zr0/D0888q8t7P3v6dJXs89739NQMVQAw+IFBWKcRPF57+SXNUPX36dMuB1kAgMbXOx+FeMyYMS5DFQCkT59ZGqoA4F//elzzmhzhJFo1btwYZ86dA2C5f5KW8+fP4864OJw6/bdH+/KuHj0cXnt+4jPlQhUATJz4nMv1fKzuD/X0xIma0yWAYUlJsO3w2NlFUJv+etlgK507dnQSsIFVH64uH5wuSNzTuxdynQSeGhA4rq7ZAoAJT43D19+UtRbfZYhzWOba66/XXNftXbo4/148MRpvzssofX5FRH38atOC6PR9V3APNQpIZlTOjXX9yQRgUmVsSGbcx2Clo7FjxyA52XVXvEaNGno0f5hNy3/f+/qgY+y3bs9PDFZEPvnlqPODpUvcaLEqLi7G93t+0JzWpEljjExJ8bhMLVu2wA/7tC9OLdh/IOj3+TVXa99EdfXKlQ6hqt2NNyJrURZuvOlGzWU+37S5wu11jTM4vHb6n3/w0JAhWP+J60ELxo0ejTiba6G+27kTn9h0TbN1x22OLY2zZ6bj5Km/Sp/3vLundhnvuMPjUDXxqfGar282Od6K+BEXXR1HDE9Un0sD1Kvn2K3w3Pnz6Nb1Tpy26zZ79RVXaH9HCwqwZNnyss+wrXsj+S2YNw9z5s7VvHFvaXCx6ba3b+8+LMhaXPr8huuvx/T08t323nAxmua99/V1Uo75mGsTqm5s1QpLFi+psPwHDxzEkqXLyoXAN6ZOwY6dO7Bs5Sr+2AauPAARofBG/HydGAOVH7SxOWnnj/lvuP463HD9ddzRDFZEleP/jh93Ou2ySy+tcPlJzzu/TujAoUM4oK770MtndiOmBWWwanCN5usf2N0c+I4uXfCZyeRyYIF169Y6nda2TRusXfcRrm3k2A3wsZGpWLve+YAXN7VujbfmvuVww9v/b+/O42pK/ziAf46tGDHIoBnLb8gWZmEw9DMLYSxZkiQmoiIxWQZDTPZlbCGSMjJZWjU1zNKYYTCUaYx9hqlQahARP6Xt/P7ouO7tnnPvjUo1n/frdV7VeZ6z3Ofc7dtznu/zdufOuHEjFR7T3LUSIYz72FHj74NR0ZitdlvYrE8+kU3WMd7xY41kEIYYMXQolizVzmCYlZWNM+fPa62vWk0+xXzIvmB8tXcf3rCwQIB/gFb5rdu3ZXt8WrVsCc/PvWT3uWLZMuSLBWjSqDHmfvopJrtPUX6NXL6CZcuWIsiAOcwWfPYZ3KdNKzyvW7cxYqQtcgvyVeXuk7Rvu90uk16+dq1a2Lh+AwYMGqhVduJELCZNdVf9bW9ri11fGZYO39FxrKqn2aJ9e8ydNQujRo/GRB1j24gqUNB2VXCNvsaWKFkXLl7CgwcPddYxM2uiCo4MqW9iUlsVgF1PTkFqaprB9YmBFVGpEQThuQKz0pCckoL79++jbt26la69Dx95GjTaDrfFnj1fPff+TGq/JFuWfueu4na1a9ZC3KlTskkyAKB+vZex66sg3L5zBz/+VNg7tHf3XoywGaZRb/qc2ciXvmi7jnfCilXySRLO//lXsR7XaDs7BAYGypadipO/5SPz4QOY1quntf7c2TPw2eQDF+cJ8oH89/K9c76bfdC8eTPZsnXeGzFg0GDY2o7Q+TgcxjgiJEx/QFUFAu5n3oexWjKZKVPctG7hnOrhofF3QkIiEpOSNF/TAKKjomFp2VP2WNbWhRM5G9eogdvp6RrH1GVfSAhi4wuD416Wljj049Oe1JzcHL6Zln9XK/j5/8F2qpjWrVuvN2vfJh9fuLu5GlzfaYIzAvz9AABR0Qcwdcokg+uTvs8jIsMCiDcFQRj6b3zs11NSFMsMSV5x+OjRMj/n9WvWVOg2vyWTaCI/Px/pGYXBjufcubJBlf2oUVrrcnIea60zql4DewN3KQZVAFCrlvy1fatTJ/x67KhiUKXOxWkCXq5TFz4bNmgEVXn5+ejz4YdITErCGxYW8N24CZu2blHcjyiKBred09iP8eWXOxXLQ4P3ya63txslu37J8uWKQRUA/PbbKa11KxYvlr298ol6L9fVG1QBMCioatG8GSLDwlQBztWkqxg8eDAiozVnfOvaubPWNTuvNtFzVaEKXJ2ccO/ePcWgKvPBQxSIImyGDEFiQqLBQdXB6GiMlebX6tiuHfaqjW87d/YcQsIi+CFTzv+nU9EDBmmi47IYJ8bAiv7V2GNFxXmzPCwIwj0AOwHsFEXxX/EGGvPTT4plrpMn69z2+NFf8M/Nm2V+zrGn4ip0m+fK/Ac/I+M+LCwsMNtjOkaP1Z5DacH8+Ui7qR2Q1SiSYGTwgAGY6eGBnr16Pf3CnJmJOnXqaNTz3rARRtVrIDY+HqIoolvnzpg02Q09ioyTysvLU8zCOGzECAy1sdHo2Vy3Zg3menrCzKwJvObPx/wFC54Ggbl5uH/vHho2NNXYj0WbNjhz9qzyPz4AjLW3h5+/P6qqBQ/hoaGwKZLQIyc3V2v7Lm++iVkz9E/+mJxyA01fe1Vj3f/U0pq/3akTfj58RDEolRO8dx9s7exUEyqrs+rdGzGHlOdnG9S/P/YGh8DYqDDAyX78GDYjbFQZANV1tLDQWjdk+DBEhIQgLycPg4daa1zH9PQ7uJeRgVbmrVTr6pjUxp302zofT05OLmrUqP70Cy0Az4ULAQBvduiAE7GxqgAvJeUGRtqPQr5YwE8YKgtlMYfVYTYzMbAi0kMUxXuCIHgBWI/CzEKfC4IQKAVYlfaNVFdvFQC0adtWZ3lIcMgLOe8fDx+p0O1+WmYMkKlpffwRHy9bPyIyCivXroWtzFxI/fr1Q8CuwsQCC2bPwcLFizTKvRYvRaN6L2Oy2rgZAGjUuBEC9YydycvPx/y5c7FKRw+helD12ezZ2Oq3HYGBX8HeTjuDoctEJ/Tr2w/2Dg4a69du8Mae0FDFoCroy50Yaa/Z47Rty1a4z5iO3CKBlWl9zYQSA/v1R+TXkfq/Lf18BMtXLscPavNyqWvYoAFiFW4zLCgQEbI3GKMcRmm0Xf9+/XHk2FEMGmItO14xOvob1KxVUyv/ZeNXXkHy9eta9T9xd5cNqgCgXRv51+pga/kEFR4e0/CySR1s3rrV4Oft3Xv3ER0RAUe1dOt+W7bi3KVLqFGtGk7GxmoEvp/NnYO/ExL4AcOgpKxcZWBV8Zi3bqN3gl716UIMqW/euo3GtsWpT+U7sHrTkDEqVG78ASABQEvpb0cAjoIgXAOwQQqy7lWmB7xs8WLFstdbtNC7fdqtmy/s3GO++w5W/ftXyHY/e/YcbqffRUPT+nrrbli3Hp/OK0wAYfKS9q19w2xskPBOV1SrVhVmZmYaZVt9tmDZ8qVwd3Et9jmGBQfDwXEcbIYbfofsitWrsUIhC93SJUuwOzgExkbGWoGVaYP62LxuPbx9NiP5+nVUrVYN3bt1Q/++/TDNw0Ort+fYkV+waNkyAMDJEyfQ/d13nz6nV62EZa9euHjhPFq2MsfQ4cO0ziUz8z7u3MnAg8xMRISH4++EvxER+TWMjLRvfZv2yXS0bmWOiZOU27DPhx/g6MmTWLj4c5iYmCAnNxdXLl9R9dTcSE5B6zattbarWkVAYEAAgkNDkZWdjQb166FjewtM//RTrcBtkquLzkD4lcaNDb5OGzdsQHBYOOxkEokoWbdmDY4eO4aI/fs11gd8uQOW3boh5tAhVVCVl5eHiU5OCA4L46dKxfnsqwxKPehhqvWSN3f2zFKtbzPMGjbDrNnQlSSwWs9LUCk0l67lekEQAkVRHFcZHtSjR4+wY5dyCuXNGzfq3D4vPx/7o6Jly8xbtkSvnj2f+xxvpd9G9EH5OZrCwsMrbGAlQsRHA/rjtzjdtzR6r38aVAHKyUSaNdPOWrcnKAifzCz8AIo/XbyMeweiojDBdRIKICI0Yj/cjx5Dj/9aPtNjjQgLx/RZM5H6zz8AgDPnzsnWc3WbDFe3yXr3Fx4SAhc3N2Q+LMwK5b3RWyOwAoCPBg7ARwMHyG5/8+YtfND7Q1yRmdA691Eevj1wUGPb9hbt0N6inWI72TmMUU2gm3RNPmHYrp07sXTFctkyewcHrUCz6OusV88eOPWH7uEjFy+c19t2ycnJmDNnNkIjCoOj0LAIeG/MQIP69XQ8V4GxDg5ISkrC8V9/1SgbbG2NunXqaNzOKAJ4v9d/Efv7aX5yVJT3o22D7wmu0ZUhYDjMq0lUCQMrURTfFwRhA4A3eQkqnBZSIFXUfRSOvdpQWR7oImlchBKrvn11lm/YoNwU8+fNg4OOL4vFUd3YWHZ9ZHQ0tlXg9j9z9iz8tvrCZbJ8tqIjR49hllqq8uJynDhR9fuJU6eKte3ESZM15pRasXoVop8hsLp2PRl2YzSfB7+dPo3sxzmqcUPFNUpKkqAKsPdHIig/X+MWNF2mT/eQDapUz6vI/YpBWdGAw260Ax7n5eqt+3fSs085MHWym96gCgBup6frreM0YSIO//L0NtoCiOjevRuuXL6suM0U10kIDg+Hz3rN/xN+sWI5Ll68iIQibfn5vPklElQJgvA+P47KluCHFnwMVEbfs1RWrl6LK5d1Z4YdMHCQqtfJkPrmrduoerbC90fh4IFvDK5P+oMcLlwMWqQXu1hkOQxg3HPsV4Ors7NYzchIvJ6cUrRIbGXeSqxmZCS7lAaH0faKx+tr1Ufv9o2bNJHdtrqRkVhQguf5xhtvKJ5nYmKS3u37WPUp03aVY2pqKnv893r1kq2/wNNTtr6dnZ3eY+XnF4i9LC21tl2/dq3ebR9lZYvdu3WVPbbNiBFisszzVsmXAQFi0+bNZffV8Y03xcc5ucVqQ98tW8QaRsay+3OwtzdoH4sXLVJ8LjxZmjZvJj5+nKO3jS179NC7rydLnbp1xUePsov9vFn7xRdidYXHXHTp1rWr4n4e5+SK1oMHKW4buGOH1jbXr18XHceOEasbGYkdO3bUKl+zarXWur8u/Sk2UnhfkFt6WPaUO10v6f1Y5MKFS+VdNvn4iqIoik4TnA2ua2h9pwnOqvqbfHwNrn/iZJzqux+/F8svTF5BxbFTrXcqEoBXZc0MmJSYhOBw5RTI3bt217n9Dn9/pN+VnwdpqPVglOTIwvcsLXHhzz9ly4aPGI7T8b9X2OtwPDYWn82Zo5rf6XFODoYMGohDv8insP86Kkrn/gK2+2PKtGmyWdi8Fi+BlZUVLDp21Cp7nJMDZ6cJ2BsWqrjvr6OjERsXhyULP8e4CfITvubk5GLFsmXYtTtIZ2KUS39eguPYMdi7b5/eNsrJy8MER0fsCw9XrBMcEYHqjo7w37FDtufK3287lq1cgZTUVL3HS/vnJkzq1EFkeBg+Gqg9ge75s+fgOH6cYhIJOY+ys/FRfyuNecp0CQoMhOeiRbhhwPk+EX/mDL5YvRqfzp79tO1y8zB75gxs9duumrhXzsIlS/B2l3fQoWMHiAB8Nm7EAi8vPJQyIs6RGfM1c7bmurS0NIwYaYs7d++W1MujYmeoISJdPVbN2QwVEwMrMoh028nLAMYDiKxsSSqKcnNTniyvqlAFXkuX6Nz+l1+Uv/O0a922RM91wsSJ2OLvL1t2/sJFHIyOwoDBFXdg6hpvb8TFxcHc3Bzf/RiDGzpmiM8rKMC2rb5wLXL7YMqNNMzwmIb90dGK2/4vOwvde1pitN1IvP3WW2jTti1u3byFo8eOIjQiwqCJnv+5eRPOU9yw1nsDenTrpjHmK+2ff/D9DzGqCYH1CYuMhLmnJxYvXSpbnpWVjWnuU7Bz927DgpHgYAQFB6N/nz54VS2Jx8m4OMXAXEkBRNjYjoTXggWYOn06ahobIfbkSSzw9MTPx449YxAdBxOTOli1Yjnc3N1l6+wPD4e3tzeOxz3bdALzFi5EaGgo3n7rLWRlZSE0IgK5v0vG/AAACO1JREFU+fl6t7uRmorO77yDmjWNkZWVrRGEvW/ZEw5jx2rUL5pMJHRfMBzGOUIswdeFKIrv85OJqFJ+3/JCYfZlqojXrzgTTxKVAo0n4CQXFwTs2oXEvxO05ssxb22Oq9eTZXeSm51dYid0+vff0bVHD8Xy4UOHIHif7olL27Vvj78T5ceN/HnhAlq2bFmijag0zgoAnB3HYcs2X8Vyq75WOKzQA1SS7apLw4YNce/BgxLb3/7wCAyUxgHZjxqF8MjICv0iybhzF7VfepqO/OHDh2hi9iqyZSY/rgxaNG+OA9HfoHmL5khPvwsnp3H46fDhcnmuh77/Ab3e6/XMr09dur7TBcePagWqiwB48aODqHIHVpt8fOHu5ooLFy/hwYOHOrcxM2uCZk1fAwCD6puY1IZF+8KkQ9eTU5Cq4x+W6vVPxp7Cu927AsAR/nNHHnusiNSkpqbCxcVFZx2r3n10lmdlZSsGVVUhlHhQBQAD+vXDQYX5hS7/feVfdx2H2QyvVI/H1NQUHTpYoEqVKrh9Ox0pqTcq9fW7eu0aLDp1LPfnaTt8uN6gatZMDvgmomf3JAAqrfrNmr6mCsqIgRVRiXj06BFcnZ11jlMBADsbG0x01j2R3vIlynNfDR82tFTO36JtW8XA6sjx40hPvwNT0wa80BVUvligmIadXozuXbpgz549iuV5eXkY5+iIYD3vKUREupSnHitiYEWk1++/n8a7PXroHLwOAFUgIMiA8Sw3bij3JjSoV69UHsOcefPwhbe3YnlggD9mzpnDi01UQnp2f1dn+fRp0xhUEdFzW7duPXYEbNdZ58ltg4bWd5rgjAB/PwBAVPQBTJ0yyeD6xMCK/gUm6bl9r6iCgnzcSEvDseO/4pGB44hWL19mUL3jcbGKZTY2NqXy+OvWrQvTBg2QfueObPnlK1f4JCEqIa+amWHlmi8Uy8/9cQZBesZhEhERAyuicilg165S3f8Hlj3xyYwZeuud/eMPJCZdlQ9+TOrg/d69S+0c+/b+EHtC5NOB7wkOwTaFzIFEVDxTJ7spluXk5OLj8ePw8NH/2FBERAysiKiob7793qB6u4OCFMv+a9mjVM/xpZovKZZl5+bghx9+QN++fXkxiZ7TdB0JKWZ6fILzly6xkYioRJi3bgOnCbrHdjdp0qRY9c1bt9HYtjj1iYEV0XPZ4euLGtUNe6mkpikPAH3FtGGpnueipUuwPXCnzi+DF5gAgei57PIP0Jqn6onf4+MRun8/G4mISszc2TNLtb7NMGvYDLNmQ5eQKmwCInkD+1rhYWYmxo4bZ1B9EUBIeIRi+dSp00r1fBs2bIjBAz5SLL985QpC9+3jhSV6Rv1694b9GAfZsqBdu9CtZ0+DJpImIqLKiT1WRDKcxowp9pik8LAwxcyCVQB0KIN5eYJ270Xdei8rlv/888+wHTWKF5joGfyneXPFMo+Zs9hARFTiVq5eiyuX/9JZZ8DAQapeJ0Pqm7duo+rZCt8fhYMHvjG4PjGwIjJI40aN0K9PH/T+4APYjxlT7O09FyxQLJvpMb1MHkOtmsZo+Z//ICEpSbb8kp43WyLS8YFZVf4jc92aNbj/IJMNREQl7srlv/SmT3/r7c7Fqq8+piotLa1Y9YmBFVUSRjWMUFV4/rtXa9SoDosOHdC2VUsYGRnjVbMmGDbcBh06dXrmfX4T9TWuXr2meH7LV64os3bq/d57uHr1mmzZiZNxuHP3LhrUr6/xZbEk2pWossvNy9VaF/P995jr6cnGISIiBlZUcZw/f77cntsg6yHIznpULs7Fx9cXPr6+Btf/9ttv+eQiMsD9TO1eqY2bN+uZWpyIiBhYERERkcqhI0eQn5+PqlWrAgBcnZ3xXUwMG4aISs2MGdPh7Kz7VjwzsybFqm9iUlv1u/XggejSOc7g+sTAioiI6LndTk9H48aNMdLGBhcvXcKx2Fg2ChGVKov27Uq1frOmr6FZ09fY0AysiIiIyta9Bw/gt3MnG4KIysSFi5fw4MFDnXXMzJqogiND6puY1FYFYNeTU5CammZwfWJgRURERERU4axbt15v1r5NPr5wd3M1uL7TBGcE+PsBAKKiD2DqlEkG1yfdmAqMiIiIiIiIgRUREREREREDKyIiIiIiogqNY6yIiIiIiMqhAH+/Yo1vKm59dzdX1fgsen7ssSIiIiIiKkemTpkEQRDK1fJu9668MAysiIiIiIiIShdvBSQiIiIiKgdEUfQC4MWWqJjYY0VERERERPSc2GNF5ZLT+HEwNjZmQ/xLZOqZJZ6IiIiIgRXRMzh89CgbgYiIiIgYWBE9C6fx49GtK7POEBG90qgRG4GIqAIRRFFkK9CLxCcgEZHhFoED24mIyiUmryAiIiIi+pcRBCFGEITX2RIMrIiIiIiIKkOA00cQhARBEETpZ+cS2u8cQRBilI4JoI++elQ8HGNFL9oiNgERkcEOswmIKp1tAEJFUZwrCEKI9HcXQRDmAFgp1XEVRdFPEIQEAK8DyAAQCsBFKu8i/e4CIBGAVZFAaiWAOWp1n/weA8BPrV6MFHBlSPvIAJAg7fN1AH6iKLoKgrBN/diiKMbzMnKMFRERERHRi/kiXtg79VvR4ERt/UgpoFkJoL60Ll4UxZFScGMrimJ9tfotpcAsXgqK+kj7uCttHyMFZPHS7y0B2Er1fpQCri7S8V6Xtk0AMBdAPQAu0vFEaV1nABBFcSSvJm8FJCIiIiIqb+pJP+OlQAhPghhpHYr8/qQsQQqSVLcTiqKYAWCVFEh1lgImJRmiKCZKQVbnIsdJVDuvVVLwZVvkfBhYERERERFR2ZJ6qTKkAAWCIIRIt/tlqAVMtjIBVVGJ0s+WUj313i9bFPZEuarVUwzopIQWfZSOJwhCPWl/I1HYa+XCK8nAioiIiIjoRRsJwFa6va4zgJFSwDUXQAgKe4ZcpZ4npQDtRxSOlUpAYa+Sn1rxk+DtN+lnPbV1MWr7WCWtf9Lr5apwrIwi57aKl1AKOjnGioiIiIiI6Pmwx4qIiIiIiIiBFRERERER0Yv1fzWFdESoLhzmAAAAAElFTkSuQmCC"
    }
   },
   "cell_type": "markdown",
   "id": "d9746e9a",
   "metadata": {},
   "source": [
    "# Import\n",
    "\n",
    "![pipeline2-01.png](attachment:pipeline2-01.png)\n",
    "\n",
    "\n",
    "Import each data already processes. __DAF*discovery*__ does not preprocess data; we assume this part is covered (add REF)\n",
    "\n",
    "__Metadata__ (as .csv) should have 'Samples', 'NMR_filename', 'MS_filename' and/or 'BioAct_filename' as headers\n",
    "\n",
    "This section will get filenames from the __Metadata__ to reorder the actual data exported from the previous processing steps\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "144a90dd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set Project and Project path inside your main folder\n",
    "Project = 'CaseIV';\n",
    "\n",
    "os.chdir(Project) # navigate to the Project folder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "74a9c0e3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "You are about to merge data from: NMR + BioAct. Go for Option 3\n",
      "Data in Use: ['NMR', 'BioAct']\n"
     ]
    }
   ],
   "source": [
    "Metadata = pd.read_csv('Metadata.csv', sep=',',header=0) # Rename the Metadata filename accordingly to your specific case\n",
    "\n",
    "# Set order from Metadata\n",
    "if ('NMR_filename') in Metadata.columns and ('MS_filename') in Metadata.columns and ('BioAct_filename') in Metadata.columns:\n",
    "    Ordered_Samples = Metadata['Samples'].values.tolist() \n",
    "    Ordered_MS_filename = Metadata['MS_filename'].values.tolist()\n",
    "    Ordered_NMR_filename = Metadata['NMR_filename'].values.tolist()\n",
    "    Ordered_BioAct_filename = Metadata['BioAct_filename'].values.tolist()\n",
    "    print('You are about to merge data from: NMR + MS + BioAct. Go for Option 1')\n",
    "    data_inuse = ['NMR', 'MS', 'BioAct']\n",
    "    \n",
    "elif ('NMR_filename') in Metadata.columns and ('MS_filename') in Metadata.columns:\n",
    "    Ordered_Samples = Metadata['Samples'].values.tolist()\n",
    "    Ordered_MS_filename = Metadata['MS_filename'].values.tolist()\n",
    "    Ordered_NMR_filename = Metadata['NMR_filename'].values.tolist()  \n",
    "    print('You are about to merge data from: NMR + MS. Go for Option 2')\n",
    "    data_inuse = ['NMR', 'MS']\n",
    "    \n",
    "elif ('NMR_filename') in Metadata.columns and ('BioAct_filename') in Metadata.columns:\n",
    "    Ordered_Samples = Metadata['Samples'].values.tolist()\n",
    "    Ordered_NMR_filename = Metadata['NMR_filename'].values.tolist()\n",
    "    Ordered_BioAct_filename = Metadata['BioAct_filename'].values.tolist()\n",
    "    print('You are about to merge data from: NMR + BioAct. Go for Option 3')\n",
    "    data_inuse = ['NMR', 'BioAct']\n",
    "\n",
    "elif ('MS_filename') in Metadata.columns and ('BioAct_filename') in Metadata.columns:\n",
    "    Ordered_Samples = Metadata['Samples'].values.tolist()\n",
    "    Ordered_MS_filename = Metadata['MS_filename'].values.tolist()\n",
    "    Ordered_BioAct_filename = Metadata['BioAct_filename'].values.tolist()\n",
    "    print('You are about to merge data from: MS + BioAct. Go for Option 4')\n",
    "    data_inuse = ['MS', 'BioAct'] \n",
    "    \n",
    "elif ('NMR_filename') in Metadata.columns:\n",
    "    Ordered_Samples = Metadata['Samples'].values.tolist()\n",
    "    Ordered_NMR_filename = Metadata['NMR_filename'].values.tolist()    \n",
    "    print('You are about to work with NMR data alone. Have a look in what more you could do with additional data. . Go for Option 5')\n",
    "    data_inuse = ['NMR']\n",
    "\n",
    "    \n",
    "else: print('Error (sorry!), please check your Metadata')\n",
    "\n",
    "print(f'Data in Use: {data_inuse}')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4c0407c6",
   "metadata": {},
   "source": [
    "___\n",
    "___\n",
    "## Option 3: NMR + BioActivity\n",
    "\n",
    "\n",
    "\n",
    "__Use this cell to work with 'NMR' + 'BioAct'__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "525dd296",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data from both NMR and MS and BioActivity are now MERGED and reordered according to the Matadata. We save it as a .CSV file for you\n"
     ]
    }
   ],
   "source": [
    "if data_inuse == ['NMR', 'BioAct']:\n",
    "    # NMR\n",
    "    NMR = pd.read_csv('NMRAl.csv', sep=',',header=0)   # assuming the NMR data was exported and saved as NMR.csv\n",
    "    ppm = NMR[\"Unnamed: 0\"]\n",
    "    \n",
    "    # Bioact\n",
    "    BioAct = pd.read_csv('Bioact.csv', sep=',',header=0)  # assuming the BioActivity data was recorded and saved as Bioact.csv\n",
    "    BioActdata = BioAct.iloc[:,1:]\n",
    "else: print('This is not the cell/option for you. Please, try the next one')\n",
    "    \n",
    "# REORDERING data according to the Metadata (Ordered_Samples)\n",
    "NMR = NMR[Ordered_NMR_filename] # reorder columns according to the sampleIDs\n",
    "NMR.rename(columns={i:j for i,j in zip(Ordered_NMR_filename,Ordered_Samples)}, inplace=True) # rename column headers as sampleIDs\n",
    "\n",
    "BioActdata = BioActdata[Ordered_BioAct_filename] # reorder columns according to the sampleIDs\n",
    "BioActdata.rename(columns={i:j for i,j in zip(Ordered_BioAct_filename,Ordered_Samples)}, inplace=True) # rename column headers as sampleIDs\n",
    "\n",
    "# MERGE - Data from different sources has to be merged to creat a single data vector for ...\n",
    "#each sample. This is the data fusion side of it.\n",
    "MergeDF = pd.concat([NMR,BioActdata/20000],ignore_index=True)\n",
    "\n",
    "# Save outside (CSV)\n",
    "MergeDF = pd.DataFrame(MergeDF)\n",
    "\n",
    "if not os.path.exists('data'):     # Rename the folder name to your specific case. Keep it organized.\n",
    "    os.mkdir('data')\n",
    "MergeDF.to_csv(\"data/MergeDF_NMR_MS_BioAct.csv\", sep=',',index=False)\n",
    "\n",
    "# expand the axis to cover both NMR and MS\n",
    "gap = ppm.values[-1] - ppm.values[-2]\n",
    "start = ppm.values[-1] + gap\n",
    "end = start + (gap)    # considering 1 column for BioActivity\n",
    "axis2 = pd.DataFrame([np.arange(start, end, gap)])\n",
    "new_axis = pd.concat([ppm,axis2.T], ignore_index=True)\n",
    "#new_axis = new_axis[0]\n",
    "\n",
    "print('Data from both NMR and MS and BioActivity are now MERGED and reordered according to the Matadata. We save it as a .CSV file for you')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79ffdd97",
   "metadata": {},
   "source": [
    "### STOCSY calculations\n",
    "\n",
    "Use this cell to apply STOCSY on a given driver peak.\n",
    "\n",
    "The driver peak should be infromed by the user __in line 5__."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0b548ec7",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
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       "\n",
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       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
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       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
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       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
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       "        fig.send_message('refresh', {});\n",
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       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
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       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
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       "        'style',\n",
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       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
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       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
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       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
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       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
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       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
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       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
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       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "<img 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\" width=\"1600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Chose driver from the Bioactivity values\n",
    "from STOCSY import *\n",
    "%matplotlib notebook\n",
    "\n",
    "# DRIVER FROM THE BIOACTIVITY DATA\n",
    "driverBioAct = new_axis.values[-1] # in this case (where bioactivity is intend to be used as driver) the driver selection was design to be the BioActivity derived signal\n",
    "\n",
    "corr, covar = STOCSY(float(driverBioAct),MergeDF,new_axis[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "70a09378",
   "metadata": {},
   "source": [
    "## Miscellaneous\n",
    "\n",
    " Other Multivariate analysis stuff ... PCA, PLS-DA, O-PLS-DA, HCA, HeatMap, etc..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "94fcba80",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(58907, 49)\n",
      "(58908, 49)\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "import seaborn as sns\n",
    "\n",
    "features = Ordered_Samples         # Separating out the features\n",
    "y = features  # Separating out the target\n",
    "#x = MSdata   # get data from the MS data DataFrame\n",
    "#x = NMR      # get data from the NMR data DataFrame\n",
    "x = MergeDF   # get data from the merged DataFrame\n",
    "\n",
    "x_norm = (x-x.mean())/x.std()\n",
    "\n",
    "print(NMR.shape)\n",
    "print(MergeDF.shape)\n",
    "\n",
    "x = StandardScaler().fit_transform(x_norm.T)\n",
    "\n",
    "# Set classification for hue\n",
    "hue_v = [0,0,0,0,0,0,1,1,1,1,1,1,0,0,1,0,0,1,0,0,1,1,0,0,0,0,1,0,0,0,1,1,1,0,1,1,1,1,1,1,0,1,0,0,0,0,1,0,1]\n",
    "\n",
    "pca = PCA(n_components=5).fit(x)\n",
    "\n",
    "transformed = pca.transform(x)\n",
    "\n",
    "fig = plt.figure(figsize=(5,5))\n",
    "ax=sns.scatterplot(x=transformed[:,0], y=transformed[:,1], hue=hue_v);\n",
    "ax.set_xlabel('Principal Component 1', fontsize = 10)\n",
    "ax.set_ylabel('Principal Component 2', fontsize = 10)\n",
    "ax.set_title('2 components PCA', fontsize = 12)\n",
    "\n",
    "if not os.path.exists(\"images\"):     # Rename the folder name to your specific case. Keep it organized.\n",
    "    os.mkdir(\"images\")\n",
    "fig.savefig(\"images/pca.pdf\")"
   ]
  },
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   "id": "3df24eae",
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   "source": [
    "### REFERENCES\n",
    "\n",
    "Cloarec O et. al. Statistical total correlation spectroscopy: an exploratory approach for latent biomarker identification from metabolic 1H NMR data sets. Analytical Chemistry. 2005. [link](https://pubmed.ncbi.nlm.nih.gov/15732908/)\n",
    "\n",
    "Crockford DJ et. al. Statistical Heterospectroscopy, an Approach to the Integrated Analysis of NMR and UPLC-MS Data Sets:  Application in Metabonomic Toxicology Studies. 2006. [link](https://pubs.acs.org/doi/10.1021/ac051444m)\n",
    "\n",
    "Borges RM et al. Exploring correlations between MS and NMR for compound identification using essential oils: A pilot study. Phytochemical Analysis. 2022. [link](https://pubmed.ncbi.nlm.nih.gov/35098600/)\n",
    "\n",
    "Kuhn S. An integrated approach for mixture analysis using MS and NMR techniques. 2019. [link](https://pubs.rsc.org/en/content/articlelanding/2019/fd/c8fd00227d)"
   ]
  }
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