elnjensen/Insulin activity.ipynb

## Insulin activity.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Simple calculation and plotting for formula of insulin-on-board from OpenAPS oref0, https://github.com/openaps/oref0/blob/master/lib/iob/calculate.js"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Import libraries, and make plots inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Create two arrays of time - up to 75 minutes, and from 75 minutes to 180 minutes.\n",
    "# For a duration of insulin activity different from 3 hours, just multiply these\n",
    "# arrays by (duration/3) to stretch or shrink the x-axis appropriately. \n",
    "t = np.linspace(0,75)\n",
    "t2 = np.linspace(75,180)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Calculate the two functions\n",
    "y =  (1 - 0.001852 * (t/5.0 + 1)**2 + 0.001852 * (t/5.0 + 1))\n",
    "y2 =  (0.001323 * ((t2-75)/5.0)**2 - .054233 * ((t2-75)/5.0) + .55556) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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9xb/f+Tej545mQPMBXNvlWprVaBZ1rFIpVWMkl5jZvjGN7mdmjyTSqIhIYWpX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\nBXiHwbpyze4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7f1d87bdd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(t, y)\n",
    "plt.plot(t2, y2)\n",
    "plt.xlabel(\"Minutes after bolus\")\n",
    "plt.ylabel(\"Fraction of bolus still onboard\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.1"
  },
  "widgets": {
   "state": {},
   "version": "1.1.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
	{
	"cells": [
	{
	"cell_type": "markdown",
	"metadata": {},
	"source": [
	"Simple calculation and plotting for formula of insulin-on-board from OpenAPS oref0, https://github.com/openaps/oref0/blob/master/lib/iob/calculate.js"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 28,
	"metadata": {
	"collapsed": false
	},
	"outputs": [],
	"source": [
	"# Import libraries, and make plots inline\n",
	"import numpy as np\n",
	"import matplotlib.pyplot as plt\n",
	"%matplotlib inline"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 29,
	"metadata": {
	"collapsed": true
	},
	"outputs": [],
	"source": [
	"# Create two arrays of time - up to 75 minutes, and from 75 minutes to 180 minutes.\n",
	"# For a duration of insulin activity different from 3 hours, just multiply these\n",
	"# arrays by (duration/3) to stretch or shrink the x-axis appropriately. \n",
	"t = np.linspace(0,75)\n",
	"t2 = np.linspace(75,180)"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 30,
	"metadata": {
	"collapsed": false
	},
	"outputs": [],
	"source": [
	"# Calculate the two functions\n",
	"y = (1 - 0.001852 * (t/5.0 + 1)*2 + 0.001852 (t/5.0 + 1))\n",
	"y2 = (0.001323 * ((t2-75)/5.0)*2 - .054233 ((t2-75)/5.0) + .55556) "
	]
	},
	{
	"cell_type": "code",
	"execution_count": 31,
	"metadata": {
	"collapsed": false
	},
	"outputs": [
	{
	"data": {
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9xb/f+Tej545mQPMBXNvlWprVaBZ1rFIpVWMkl5jZvjGN7mdmjyTSqIhIYWpX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\nBXiHwbpyze4AAAAASUVORK5CYII=\n",
	"text/plain": [
	"<matplotlib.figure.Figure at 0x7f7f1d87bdd8>"
	]
	},
	"metadata": {},
	"output_type": "display_data"
	}
	],
	"source": [
	"plt.plot(t, y)\n",
	"plt.plot(t2, y2)\n",
	"plt.xlabel(\"Minutes after bolus\")\n",
	"plt.ylabel(\"Fraction of bolus still onboard\")\n",
	"plt.show()"
	]
	},
	{
	"cell_type": "code",
	"execution_count": null,
	"metadata": {
	"collapsed": true
	},
	"outputs": [],
	"source": []
	}
	],
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	"kernelspec": {
	"display_name": "Python 3",
	"language": "python",
	"name": "python3"
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	"codemirror_mode": {
	"name": "ipython",
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