FDA_Sample.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FDA Sample Benchmark"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import fda\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fitness Function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# minimize this function\n",
    "def fitness(x):\n",
    "    return np.sum(x**2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FDA Agorithm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "F = fda.FDA(5, -100, 100, fitness, alpha=6, beta=4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FDA Soultions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Initial flow:\n",
      " [88.06176786  8.25948421 35.41815251 25.45834961 75.04164384]\n",
      "[-80.41883032 -70.6429345  -17.13444857 -84.86082914  80.29705715]\n",
      "[-89.25137987  65.5971058  -72.06689668  83.58756154 -10.04851729]\n",
      "[-45.50519575 -97.44679127  68.46639    -69.60192392 -26.73710649]\n",
      "[-19.16773921 -16.57004213 -25.25608939  -5.80720781 -15.77032312]\n",
      "[ 46.70170267   7.74111736   3.43234523 -36.56733447 -22.25173444]\n",
      "\n",
      "\n",
      "Begin 200 Iterations...\n",
      "[ITER 1]\n",
      "best-flow: [-19.16773921 -16.57004213 -25.25608939  -5.80720781 -15.77032312]  cost: 1562.2653282509134\n",
      "[ITER 2]\n",
      "best-flow: [-19.16773921 -16.57004213 -25.25608939  -5.80720781 -15.77032312]  cost: 1562.2653282509134\n",
      "[ITER 3]\n",
      "best-flow: [-19.16773921 -16.57004213 -25.25608939  -5.80720781 -15.77032312]  cost: 1562.2653282509134\n",
      "[ITER 4]\n",
      "best-flow: [-19.16773921 -16.57004213 -25.25608939  -5.80720781 -15.77032312]  cost: 1562.2653282509134\n",
      "[ITER 5]\n",
      "best-flow: [ 17.22120901 -10.19577524 -15.72041855 -16.83911894  -9.26739253]  cost: 1017.0959228160051\n",
      "[ITER 6]\n",
      "best-flow: [ 17.22120901 -10.19577524 -15.72041855 -16.83911894  -9.26739253]  cost: 1017.0959228160051\n",
      "[ITER 7]\n",
      "best-flow: [ -7.99167472  -9.97856449 -19.42871869  -0.86816828 -15.4369271 ]  cost: 779.9661588301396\n",
      "[ITER 8]\n",
      "best-flow: [ 8.57807992 -1.55264615 -7.07728946 -8.19598985 -0.62426344]  cost: 193.64614569113837\n",
      "[ITER 9]\n",
      "best-flow: [ 8.57807992 -1.55264615 -7.07728946 -8.19598985 -0.62426344]  cost: 193.64614569113837\n",
      "[ITER 10]\n",
      "best-flow: [ 8.57807992 -1.55264615 -7.07728946 -8.19598985 -0.62426344]  cost: 193.64614569113837\n",
      "[ITER 11]\n",
      "best-flow: [ 8.57807992 -1.55264615 -7.07728946 -8.19598985 -0.62426344]  cost: 193.64614569113837\n",
      "[ITER 12]\n",
      "best-flow: [ 8.57807992 -1.55264615 -7.07728946 -8.19598985 -0.62426344]  cost: 193.64614569113837\n",
      "[ITER 13]\n",
      "best-flow: [ 8.57807992 -1.55264615 -7.07728946 -8.19598985 -0.62426344]  cost: 193.64614569113837\n",
      "[ITER 14]\n",
      "best-flow: [ 8.57807992 -1.55264615 -7.07728946 -8.19598985 -0.62426344]  cost: 193.64614569113837\n",
      "[ITER 15]\n",
      "best-flow: [ 8.57807992 -1.55264615 -7.07728946 -8.19598985 -0.62426344]  cost: 193.64614569113837\n",
      "[ITER 16]\n",
      "best-flow: [ 8.57807992 -1.55264615 -7.07728946 -8.19598985 -0.62426344]  cost: 193.64614569113837\n",
      "[ITER 17]\n",
      "best-flow: [ 8.57807992 -1.55264615 -7.07728946 -8.19598985 -0.62426344]  cost: 193.64614569113837\n",
      "[ITER 18]\n",
      "best-flow: [ 8.57807992 -1.55264615 -7.07728946 -8.19598985 -0.62426344]  cost: 193.64614569113837\n",
      "[ITER 19]\n",
      "best-flow: [ 8.57807992 -1.55264615 -7.07728946 -8.19598985 -0.62426344]  cost: 193.64614569113837\n",
      "[ITER 20]\n",
      "best-flow: [ 8.57807992 -1.55264615 -7.07728946 -8.19598985 -0.62426344]  cost: 193.64614569113837\n",
      "[ITER 21]\n",
      "best-flow: [ 8.57807992 -1.55264615 -7.07728946 -8.19598985 -0.62426344]  cost: 193.64614569113837\n",
      "[ITER 22]\n",
      "best-flow: [ 8.57807992 -1.55264615 -7.07728946 -8.19598985 -0.62426344]  cost: 193.64614569113837\n",
      "[ITER 23]\n",
      "best-flow: [ 8.57807992 -1.55264615 -7.07728946 -8.19598985 -0.62426344]  cost: 193.64614569113837\n",
      "[ITER 24]\n",
      "best-flow: [ 8.57807992 -1.55264615 -7.07728946 -8.19598985 -0.62426344]  cost: 193.64614569113837\n",
      "[ITER 25]\n",
      "best-flow: [ 8.57807992 -1.55264615 -7.07728946 -8.19598985 -0.62426344]  cost: 193.64614569113837\n",
      "[ITER 26]\n",
      "best-flow: [ 5.1471363  -3.297322   -9.63478402 -6.67868659 -3.69138271]  cost: 188.42556847176132\n",
      "[ITER 27]\n",
      "best-flow: [ 4.08565689 -7.61927192 -1.73879599 -4.38472428 -1.29432649]  cost: 98.67039638731751\n",
      "[ITER 28]\n",
      "best-flow: [ 4.08565689 -7.61927192 -1.73879599 -4.38472428 -1.29432649]  cost: 98.67039638731751\n",
      "[ITER 29]\n",
      "best-flow: [ 4.08565689 -7.61927192 -1.73879599 -4.38472428 -1.29432649]  cost: 98.67039638731751\n",
      "[ITER 30]\n",
      "best-flow: [-2.43003991 -5.8474954  -4.97456442  4.30644524  2.88038094]  cost: 91.68665254452775\n",
      "[ITER 31]\n",
      "best-flow: [ 2.44514417 -6.41736575  0.0442338  -5.69503948 -2.75074784]  cost: 87.16335808536473\n",
      "[ITER 32]\n",
      "best-flow: [ 2.44514417 -6.41736575  0.0442338  -5.69503948 -2.75074784]  cost: 87.16335808536473\n",
      "[ITER 33]\n",
      "best-flow: [ 1.77064052 -3.44715754 -0.77388398  0.10576481  7.08106137]  cost: 65.76957568973872\n",
      "[ITER 34]\n",
      "best-flow: [ 0.97528942 -2.20623255 -2.16104188  2.94975173  1.57954159]  cost: 21.684740422138695\n",
      "[ITER 35]\n",
      "best-flow: [ 1.61334115 -4.03425045 -1.20375004 -0.80288025 -0.30020105]  cost: 21.061797903493957\n",
      "[ITER 36]\n",
      "best-flow: [ 1.61334115 -4.03425045 -1.20375004 -0.80288025 -0.30020105]  cost: 21.061797903493957\n",
      "[ITER 37]\n",
      "best-flow: [ 0.39711981 -2.78440216 -1.58287227  2.37158212  2.1577112 ]  cost: 20.696203518167547\n",
      "[ITER 38]\n",
      "best-flow: [ 0.39711981 -2.78440216 -1.58287227  2.37158212  2.1577112 ]  cost: 20.696203518167547\n",
      "[ITER 39]\n",
      "best-flow: [ 0.39711981 -2.78440216 -1.58287227  2.37158212  2.1577112 ]  cost: 20.696203518167547\n",
      "[ITER 40]\n",
      "best-flow: [ 0.39711981 -2.78440216 -1.58287227  2.37158212  2.1577112 ]  cost: 20.696203518167547\n",
      "[ITER 41]\n",
      "best-flow: [ 0.64442376 -3.03854375 -1.50578233  1.72609344  1.65792436]  cost: 17.643522289571933\n",
      "[ITER 42]\n",
      "best-flow: [ 1.19035148 -3.60378532 -1.33775122  0.2937315   0.51124648]  cost: 16.541434780093017\n",
      "[ITER 43]\n",
      "best-flow: [ 1.19035148 -3.60378532 -1.33775122  0.2937315   0.51124648]  cost: 16.541434780093017\n",
      "[ITER 44]\n",
      "best-flow: [ 0.9688706  -3.37478997 -1.40608415  0.87426978  0.97314778]  cost: 16.01635447070773\n",
      "[ITER 45]\n",
      "best-flow: [ 0.9688706  -3.37478997 -1.40608415  0.87426978  0.97314778]  cost: 16.01635447070773\n",
      "[ITER 46]\n",
      "best-flow: [ 0.93322828 -3.34766743 -1.61454435 -0.06636385  0.16602129]  cost: 14.716512972981542\n",
      "[ITER 47]\n",
      "best-flow: [ 0.93322828 -3.34766743 -1.61454435 -0.06636385  0.16602129]  cost: 14.716512972981542\n",
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      "best-flow: [ 0.64715185 -0.53310138 -0.69743833 -0.00597654  1.96854275]  cost: 5.064619112361937\n",
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      "best-flow: [ 0.64715185 -0.53310138 -0.69743833 -0.00597654  1.96854275]  cost: 5.064619112361937\n",
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      "best-flow: [ 0.70650407 -1.1776659  -0.94818316 -0.19617454  1.40124943]  cost: 4.787080697984307\n",
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      "best-flow: [ 0.70650407 -1.1776659  -0.94818316 -0.19617454  1.40124943]  cost: 4.787080697984307\n",
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      "best-flow: [ 0.32898342 -0.83389564 -1.3187395   0.3710275   1.07126358]  cost: 3.827952960105545\n",
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      "best-flow: [ 0.32898342 -0.83389564 -1.3187395   0.3710275   1.07126358]  cost: 3.827952960105545\n",
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      "best-flow: [ 0.32898342 -0.83389564 -1.3187395   0.3710275   1.07126358]  cost: 3.827952960105545\n",
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      "best-flow: [ 0.32898342 -0.83389564 -1.3187395   0.3710275   1.07126358]  cost: 3.827952960105545\n",
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      "best-flow: [ 0.34100438 -0.82172929 -1.30855391  0.35343634  1.08838299]  cost: 3.81333112090758\n",
      "[ITER 57]\n",
      "best-flow: [ 0.9651092   0.11926281 -0.85419798  0.43533491 -0.00169715]  cost: 1.8648329469438425\n",
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      "best-flow: [ 0.9651092   0.11926281 -0.85419798  0.43533491 -0.00169715]  cost: 1.8648329469438425\n",
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      "best-flow: [ 0.95039201  0.09707301 -0.86491228  0.43340364  0.02400833]  cost: 1.849156503672135\n",
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      "best-flow: [ 0.95039201  0.09707301 -0.86491228  0.43340364  0.02400833]  cost: 1.849156503672135\n",
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      "best-flow: [ 0.93752044  0.07953834 -0.8731001   0.43000503  0.04649779]  cost: 1.8346410694780884\n",
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      "best-flow: [ 0.58593678  0.49037087 -0.50339241  0.2011304  -0.00324369]  cost: 0.8776533715602618\n",
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      "best-flow: [ 0.29330052  0.26285408 -0.43380381 -0.20609438  0.184445  ]  cost: 0.4197980580930401\n",
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      "best-flow: [ 0.30799956  0.26288939 -0.42787678 -0.18141245  0.18010902]  cost: 0.41240283198326194\n",
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      "best-flow: [ 0.03402606  0.05185877  0.02220929 -0.08199939 -0.04592778]  cost: 0.013173618471672404\n",
      "[ITER 115]\n",
      "best-flow: [ 0.02175418  0.00575321 -0.00489307 -0.09056137 -0.04582787]  cost: 0.010831840830999508\n",
      "[ITER 116]\n",
      "best-flow: [ 0.02031064  0.04110274  0.00716348 -0.06800232 -0.03462133]  cost: 0.007976224483950228\n",
      "[ITER 117]\n",
      "best-flow: [ 0.01208951  0.03465549 -0.00185511 -0.05961236 -0.02784415]  cost: 0.005679530737127602\n",
      "[ITER 118]\n",
      "best-flow: [ 0.01208951  0.03465549 -0.00185511 -0.05961236 -0.02784415]  cost: 0.005679530737127602\n",
      "[ITER 119]\n",
      "best-flow: [ 0.01067956  0.03352602 -0.00336032 -0.05819395 -0.02667304]  cost: 0.005347325508683582\n",
      "[ITER 120]\n",
      "best-flow: [ 0.00412111  0.02836485 -0.01052377 -0.05151622 -0.0212599 ]  cost: 0.004038202161713446\n",
      "[ITER 121]\n",
      "best-flow: [ 0.00259176  0.02757612 -0.01277334 -0.04980478 -0.02034061]  cost: 0.003824574329823087\n",
      "[ITER 122]\n",
      "best-flow: [ 0.00259176  0.02757612 -0.01277334 -0.04980478 -0.02034061]  cost: 0.003824574329823087\n",
      "[ITER 123]\n",
      "best-flow: [ 0.00259176  0.02757612 -0.01277334 -0.04980478 -0.02034061]  cost: 0.003824574329823087\n",
      "[ITER 124]\n",
      "best-flow: [-0.00427099  0.02897126 -0.01880438 -0.04329689 -0.01449775]  cost: 0.0032959852073507286\n",
      "[ITER 125]\n",
      "best-flow: [-0.00427099  0.02897126 -0.01880438 -0.04329689 -0.01449775]  cost: 0.0032959852073507286\n",
      "[ITER 126]\n",
      "best-flow: [ 0.01544937  0.01804822  0.00038387 -0.04082703 -0.0109114 ]  cost: 0.002350473761498998\n",
      "[ITER 127]\n",
      "best-flow: [ 0.0100579   0.0131437   0.01396176 -0.03410607  0.01422157]  cost: 0.00183432590109151\n",
      "[ITER 128]\n",
      "best-flow: [-0.00545176  0.00555855 -0.02037119 -0.02601701  0.00359215]  cost: 0.00116539273310867\n",
      "[ITER 129]\n",
      "best-flow: [-0.00545176  0.00555855 -0.02037119 -0.02601701  0.00359215]  cost: 0.00116539273310867\n",
      "[ITER 130]\n",
      "best-flow: [-0.00545176  0.00555855 -0.02037119 -0.02601701  0.00359215]  cost: 0.00116539273310867\n",
      "[ITER 131]\n",
      "best-flow: [-0.00476145 -0.00185855 -0.01854648 -0.00952047  0.0029046 ]  cost: 0.00046917345950479346\n",
      "[ITER 132]\n",
      "best-flow: [-0.00423161 -0.00755149 -0.01714593  0.00314133  0.00237687]  cost: 0.0003844319601422743\n",
      "[ITER 133]\n",
      "best-flow: [-0.00423161 -0.00755149 -0.01714593  0.00314133  0.00237687]  cost: 0.0003844319601422743\n",
      "[ITER 134]\n",
      "best-flow: [-0.00423161 -0.00755149 -0.01714593  0.00314133  0.00237687]  cost: 0.0003844319601422743\n",
      "[ITER 135]\n",
      "best-flow: [-0.00430253 -0.0067895  -0.01733339  0.00144657  0.00244751]  cost: 0.0003731384023172036\n",
      "[ITER 136]\n",
      "best-flow: [-0.00430253 -0.0067895  -0.01733339  0.00144657  0.00244751]  cost: 0.0003731384023172036\n",
      "[ITER 137]\n",
      "best-flow: [-0.00430253 -0.0067895  -0.01733339  0.00144657  0.00244751]  cost: 0.0003731384023172036\n",
      "[ITER 138]\n",
      "best-flow: [-0.00432827 -0.00657693 -0.01739898  0.00097057  0.00246357]  cost: 0.000371725573195661\n",
      "[ITER 139]\n",
      "best-flow: [-0.00432827 -0.00657693 -0.01739898  0.00097057  0.00246357]  cost: 0.000371725573195661\n",
      "[ITER 140]\n",
      "best-flow: [ 0.00672004  0.00423307 -0.00631082  0.01246914 -0.00857506]  cost: 0.0003319154218889219\n",
      "[ITER 141]\n",
      "best-flow: [ 0.00251359 -0.00020361 -0.01045332  0.00989951 -0.00272044]  cost: 0.00022103254596085155\n",
      "[ITER 142]\n",
      "best-flow: [ 0.00251359 -0.00020361 -0.01045332  0.00989951 -0.00272044]  cost: 0.00022103254596085155\n",
      "[ITER 143]\n",
      "best-flow: [ 0.00072634 -0.00100413 -0.01207043  0.00667197 -0.00064016]  cost: 0.0001921561761158335\n",
      "[ITER 144]\n",
      "best-flow: [ 0.00072634 -0.00100413 -0.01207043  0.00667197 -0.00064016]  cost: 0.0001921561761158335\n",
      "[ITER 145]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\qpdb\\alpha\\_pycode\\FDA\\fda.py:108: RuntimeWarning: invalid value encountered in true_divide\n",
      "  s0.append( num/np.abs(flow_i - Neighbour_X[j]) )\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "best-flow: [ 0.00072634 -0.00100413 -0.01207043  0.00667197 -0.00064016]  cost: 0.0001921561761158335\n",
      "[ITER 146]\n",
      "best-flow: [ 0.00072634 -0.00100413 -0.01207043  0.00667197 -0.00064016]  cost: 0.0001921561761158335\n",
      "[ITER 147]\n",
      "best-flow: [ 0.00072634 -0.00100413 -0.01207043  0.00667197 -0.00064016]  cost: 0.0001921561761158335\n",
      "[ITER 148]\n",
      "best-flow: [ 0.00072634 -0.00100413 -0.01207043  0.00667197 -0.00064016]  cost: 0.0001921561761158335\n",
      "[ITER 149]\n",
      "best-flow: [ 0.00049422 -0.00357884 -0.01007332  0.00387001  0.00092072]  cost: 0.00013034871529423684\n",
      "[ITER 150]\n",
      "best-flow: [-0.00016256 -0.00591668 -0.00872527  0.00069855  0.00289683]  cost: 0.00012004349485408002\n",
      "[ITER 151]\n",
      "best-flow: [ 6.05861076e-05 -5.12237968e-03 -9.18328086e-03  1.77608288e-03\n",
      "  2.22542514e-03]  cost: 0.00011868207904070962\n",
      "[ITER 152]\n",
      "best-flow: [ 6.05861076e-05 -5.12237968e-03 -9.18328086e-03  1.77608288e-03\n",
      "  2.22542514e-03]  cost: 0.00011868207904070962\n",
      "[ITER 153]\n",
      "best-flow: [ 0.00026597 -0.00527695 -0.00866566 -0.00095091  0.00270467]  cost: 0.00011123012813894808\n",
      "[ITER 154]\n",
      "best-flow: [ 0.00065281 -0.00483629 -0.00852359 -0.00255929  0.00264673]  cost: 0.00011002265903225396\n",
      "[ITER 155]\n",
      "best-flow: [ 0.00062496 -0.00328109 -0.00928507 -0.00079056  0.00127648]  cost: 9.962300434852297e-05\n",
      "[ITER 156]\n",
      "best-flow: [-0.00103685 -0.00314663 -0.00683393 -0.00424895  0.00433639]  cost: 9.45368780141681e-05\n",
      "[ITER 157]\n",
      "best-flow: [ 0.00051042 -0.00309386 -0.0080559  -0.00335571  0.0024296 ]  cost: 9.189377467152351e-05\n",
      "[ITER 158]\n",
      "best-flow: [-0.00025449 -0.00311995 -0.0074518  -0.0037973   0.00337225]  cost: 9.111975366969337e-05\n",
      "[ITER 159]\n",
      "best-flow: [ 0.00031753 -0.00312611 -0.00819125 -0.0019412   0.00188185]  cost: 8.427959642635927e-05\n",
      "[ITER 160]\n",
      "best-flow: [ 0.00211653 -0.00377787 -0.00636826 -0.00280773  0.00342615]  cost: 7.892854966086061e-05\n",
      "[ITER 161]\n",
      "best-flow: [ 0.00211653 -0.00377787 -0.00636826 -0.00280773  0.00342615]  cost: 7.892854966086061e-05\n",
      "[ITER 162]\n",
      "best-flow: [-0.00241455  0.00078256 -0.00683593 -0.00243576  0.00330912]  cost: 7.005557685766879e-05\n",
      "[ITER 163]\n",
      "best-flow: [-0.00128265 -0.00035668 -0.0067191  -0.00252868  0.00333835]  cost: 6.44575439907411e-05\n",
      "[ITER 164]\n",
      "best-flow: [-0.00128265 -0.00035668 -0.0067191  -0.00252868  0.00333835]  cost: 6.44575439907411e-05\n",
      "[ITER 165]\n",
      "best-flow: [-0.0011416  -0.00049478 -0.00669825 -0.00253745  0.00334595]  cost: 6.404863168840003e-05\n",
      "[ITER 166]\n",
      "best-flow: [-0.00105133 -0.00058533 -0.00668844 -0.00254464  0.00334859]  cost: 6.387132174432195e-05\n",
      "[ITER 167]\n",
      "best-flow: [-0.00294422  0.00130784 -0.00489563 -0.00073483  0.00154333]  cost: 3.7267909957121475e-05\n",
      "[ITER 168]\n",
      "best-flow: [-0.00269899  0.00112329 -0.00497052 -0.00086499  0.00166214]  cost: 3.6763389151867394e-05\n",
      "[ITER 169]\n",
      "best-flow: [-0.00269899  0.00112329 -0.00497052 -0.00086499  0.00166214]  cost: 3.6763389151867394e-05\n",
      "[ITER 170]\n",
      "best-flow: [-0.00269899  0.00112329 -0.00497052 -0.00086499  0.00166214]  cost: 3.6763389151867394e-05\n",
      "[ITER 171]\n",
      "best-flow: [-0.00280189  0.00124121 -0.00493246 -0.00079184  0.00154206]  cost: 3.672528982946798e-05\n",
      "[ITER 172]\n",
      "best-flow: [-0.00280189  0.00124121 -0.00493246 -0.00079184  0.00154206]  cost: 3.672528982946798e-05\n",
      "[ITER 173]\n",
      "best-flow: [-0.00079284  0.00219041 -0.00072157 -0.0039477   0.00082812]  cost: 2.2217248547427476e-05\n",
      "[ITER 174]\n",
      "best-flow: [-0.00079284  0.00219041 -0.00072157 -0.0039477   0.00082812]  cost: 2.2217248547427476e-05\n",
      "[ITER 175]\n",
      "best-flow: [-2.31877037e-03  9.32395108e-06 -1.21378722e-03  2.55625828e-04\n",
      "  1.68221619e-03]  cost: 9.745258237498196e-06\n",
      "[ITER 176]\n",
      "best-flow: [-2.31877037e-03  9.32395108e-06 -1.21378722e-03  2.55625828e-04\n",
      "  1.68221619e-03]  cost: 9.745258237498196e-06\n",
      "[ITER 177]\n",
      "best-flow: [ 8.97214350e-05  1.55121446e-03  7.50235731e-04 -6.02355171e-04\n",
      "  8.80635130e-04]  cost: 4.115519865682458e-06\n",
      "[ITER 178]\n",
      "best-flow: [ 8.97214350e-05  1.55121446e-03  7.50235731e-04 -6.02355171e-04\n",
      "  8.80635130e-04]  cost: 4.115519865682458e-06\n",
      "[ITER 179]\n",
      "best-flow: [ 8.97214350e-05  1.55121446e-03  7.50235731e-04 -6.02355171e-04\n",
      "  8.80635130e-04]  cost: 4.115519865682458e-06\n",
      "[ITER 180]\n",
      "best-flow: [ 8.97214350e-05  1.55121446e-03  7.50235731e-04 -6.02355171e-04\n",
      "  8.80635130e-04]  cost: 4.115519865682458e-06\n",
      "[ITER 181]\n",
      "best-flow: [ 8.97214350e-05  1.55121446e-03  7.50235731e-04 -6.02355171e-04\n",
      "  8.80635130e-04]  cost: 4.115519865682458e-06\n",
      "[ITER 182]\n",
      "best-flow: [-7.58396014e-05  1.44522407e-03  6.15227725e-04 -5.43377090e-04\n",
      "  9.35736248e-04]  cost: 3.6437903866862418e-06\n",
      "[ITER 183]\n",
      "best-flow: [-7.58396014e-05  1.44522407e-03  6.15227725e-04 -5.43377090e-04\n",
      "  9.35736248e-04]  cost: 3.6437903866862418e-06\n",
      "[ITER 184]\n",
      "best-flow: [-7.58396014e-05  1.44522407e-03  6.15227725e-04 -5.43377090e-04\n",
      "  9.35736248e-04]  cost: 3.6437903866862418e-06\n",
      "[ITER 185]\n",
      "best-flow: [-7.58396014e-05  1.44522407e-03  6.15227725e-04 -5.43377090e-04\n",
      "  9.35736248e-04]  cost: 3.6437903866862418e-06\n",
      "[ITER 186]\n",
      "best-flow: [-0.00013072  0.00143615  0.00048569 -0.00055803  0.00095402]  cost: 3.5370493602032956e-06\n",
      "[ITER 187]\n",
      "best-flow: [-0.00016056  0.0014281   0.00042416 -0.00056257  0.00096414]  cost: 3.4912140953017205e-06\n",
      "[ITER 188]\n",
      "best-flow: [-0.00013944  0.0014217   0.00044994 -0.00057449  0.00094949]  cost: 3.4746895587370724e-06\n",
      "[ITER 189]\n",
      "best-flow: [-0.00013335  0.00141986  0.00045736 -0.00057793  0.00094526]  cost: 3.4704878563416876e-06\n",
      "[ITER 190]\n",
      "best-flow: [5.66948789e-04 7.84026724e-04 1.16799090e-03 8.54210362e-05\n",
      " 2.72669212e-04]  cost: 2.3819768342191497e-06\n",
      "[ITER 191]\n",
      "best-flow: [4.84574033e-04 8.58818244e-04 1.08440162e-03 7.39337006e-06\n",
      " 3.51784498e-04]  cost: 2.2721146465792937e-06\n",
      "[ITER 192]\n",
      "best-flow: [4.92013363e-04 8.15349069e-04 1.08839239e-03 5.13834204e-05\n",
      " 2.58704840e-04]  cost: 2.161037701560108e-06\n",
      "[ITER 193]\n",
      "best-flow: [4.92013363e-04 8.15349069e-04 1.08839239e-03 5.13834204e-05\n",
      " 2.58704840e-04]  cost: 2.161037701560108e-06\n",
      "[ITER 194]\n",
      "best-flow: [4.94303260e-04 8.01968840e-04 1.08962079e-03 6.49239796e-05\n",
      " 2.30054029e-04]  cost: 2.1319031746384e-06\n",
      "[ITER 195]\n",
      "best-flow: [4.94303260e-04 8.01968840e-04 1.08962079e-03 6.49239796e-05\n",
      " 2.30054029e-04]  cost: 2.1319031746384e-06\n",
      "[ITER 196]\n",
      "best-flow: [0.00040968 0.0007121  0.00100597 0.00015495 0.00015143]  cost: 1.7338378115670804e-06\n",
      "[ITER 197]\n",
      "best-flow: [ 0.00015574  0.00046341  0.00075106 -0.00027363 -0.0001085 ]  cost: 8.897494557319669e-07\n",
      "[ITER 198]\n",
      "best-flow: [-1.51629632e-05  2.84538303e-04  5.79615059e-04 -4.38824115e-04\n",
      " -2.95137753e-04]  cost: 6.968184755936312e-07\n",
      "[ITER 199]\n",
      "best-flow: [-1.51629632e-05  2.84538303e-04  5.79615059e-04 -4.38824115e-04\n",
      " -2.95137753e-04]  cost: 6.968184755936312e-07\n",
      "--------------------------------------------\n",
      "Final flows: \n",
      "[ 0.00063523  0.00101818  0.00089281 -0.00103691 -0.00040362]\n",
      "[-2.66665969e-05  9.26465414e-04  1.61903979e-04 -2.60179168e-04\n",
      "  8.21890190e-04]\n",
      "[ 0.00012872  0.00043513  0.00072395 -0.00029975 -0.00013801]\n",
      "[-1.51629632e-05  2.84538303e-04  5.79615059e-04 -4.38824115e-04\n",
      " -2.95137753e-04]\n",
      "[-3.88158634e-07  2.99543519e-04  5.94441015e-04 -4.19632246e-04\n",
      " -2.79469118e-04]\n",
      "[ 0.00081327  0.0003598   0.00086493 -0.00022258  0.00010389]\n",
      "\n",
      "Final fitness: [3.47541033e-06 1.62845885e-06 8.38914361e-07 6.96818476e-07\n",
      " 6.97280800e-07 1.59929805e-06]\n",
      "--------------------------------------------\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x864 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x432 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n",
      "Best-Flow [3]:\t [-1.51629632e-05  2.84538303e-04  5.79615059e-04 -4.38824115e-04\n",
      " -2.95137753e-04]\n",
      "Minimum-Cost:\t 6.968184755936312e-07\n",
      "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n",
      "\n",
      "Finished!\n",
      "Elapsed Time: 0:00:00.936436\n",
      "\n"
     ]
    }
   ],
   "source": [
    "best_flow, best_flow_cost, Flow_X, Flow_fitness, W_var_history, C_history, V_history  = F.optimize(200, verbose=2)"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "f2528c8ffdd28c9eaaf2763ca630329d6eb2a1292c57ccaf6996c99d598fde83"
  },
  "kernelspec": {
   "display_name": "Python 3.8.11 64-bit ('base': conda)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.11"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}