Example of find intersections failure

intersections_failure.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy.ma as ma\n",
    "import metpy.calc as mpcalc\n",
    "from metpy.units import units\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# No Masked Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "p = ma.masked_array([1000,900,800,700,600,500]) * units.mbar\n",
    "T = ma.masked_array([20,15,10,5,0,-5]) * units.degC\n",
    "profile = ma.masked_array([30,20,8,0,-10, -20]) * units.degC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x1182fd128>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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IhFiLmjVmdpmZ5ZhZlZml1nnuLjPbZGYbzCytZcOURqmsgA+fgKcnwc7PvALV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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117f3e908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(p, T)\n",
    "plt.scatter(p, T)\n",
    "plt.plot(p, profile)\n",
    "plt.scatter(p, profile)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[828.5714285714286] millibar [11.428571428571427] degC\n"
     ]
    }
   ],
   "source": [
    "x, y = mpcalc.find_intersections(p, T, profile, direction='increasing')\n",
    "print(x, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# With masked data\n",
    "\n",
    "Note that it plots masked as a value of 1, but the calculation behaves as below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "p = ma.masked_array([1000,900,800,700,600,500]) * units.mbar\n",
    "T = ma.masked_array([20,15,10,5,0,-5], mask=[True, False, True, False, False, False]) * units.degC\n",
    "profile = ma.masked_array([30,20,8,0,-10, -20]) * units.degC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x11a4219e8>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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hcy69svXUtI1FRYWw4PlSM1A9B71HaAYqEakRBX6s0QxUIhIhCvxYccIMVK/C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\nhAJfRCQkFPgiIiHx/wGFiIuxIkuvlwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10e88d8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(p, T)\n",
    "plt.scatter(p, T)\n",
    "plt.plot(p, profile)\n",
    "plt.scatter(p, profile)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[] millibar [] degC\n"
     ]
    }
   ],
   "source": [
    "x, y = mpcalc.find_intersections(p, T, profile, direction='increasing')\n",
    "print(x, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# With masked data, without units"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "p = ma.masked_array([1000,900,800,700,600,500])\n",
    "T = ma.masked_array([20,15,10,5,0,-5], mask=[True, False, True, False, False, False])\n",
    "profile = ma.masked_array([30,20,8,0,-10, -20])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x11a4fb630>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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3DMzsaP+2F3Ap3msc1de2VlPHNwc4z8w6+H8BnucvS13QH3A080ORvnh/Dr4P\nLAFu95cfBczHe9cwH+joLzfgfuAjYDFQGPQYmjjeU4BioASYhvfJfSTH6o/hMGAL0D5hWZTHewew\nDO9Ny2NAG///+DvASrzDWm38bdv6j1f66/sGXX8Tx/oq3i+094FhUXtt8X6BrQeq8N6pX9Oc8QHf\n9V/jlcDV6apPnbYiIjERykM6IiLSdAp8EZGYUOCLiMSEAl9EJCYU+CIiMaHAFxGJCQW+iEhMKPBF\nRGLi/wO/Atqg1ZlVZAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a457dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(p, T)\n",
    "plt.scatter(p, T)\n",
    "plt.plot(p, profile)\n",
    "plt.scatter(p, profile)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[] []\n"
     ]
    }
   ],
   "source": [
    "x, y = mpcalc.find_intersections(p, T, profile, direction='increasing')\n",
    "print(x, y)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:metpydev35]",
   "language": "python",
   "name": "conda-env-metpydev35-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
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