2018-05-22_minimal_working_example_lmfit

2018-05-22_minimal_working_example_lmfit.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 0.9.7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-22T13:41:58.547118Z",
     "start_time": "2018-05-22T13:41:56.314011Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Uninstalling lmfit-0.9.9:\n",
      "  Successfully uninstalled lmfit-0.9.9\n",
      "Collecting lmfit==0.9.7\n",
      "Requirement already satisfied: scipy in /usr/local/lib/python3.6/site-packages (from lmfit==0.9.7) (1.1.0)\n",
      "Requirement already satisfied: six in /usr/local/lib/python3.6/site-packages (from lmfit==0.9.7) (1.11.0)\n",
      "Requirement already satisfied: numpy in /usr/local/lib/python3.6/site-packages (from lmfit==0.9.7) (1.14.3)\n",
      "\u001b[31mtensorboard 1.8.0 has requirement bleach==1.5.0, but you'll have bleach 2.1.3 which is incompatible.\u001b[0m\n",
      "\u001b[31mtensorboard 1.8.0 has requirement html5lib==0.9999999, but you'll have html5lib 1.0.1 which is incompatible.\u001b[0m\n",
      "Installing collected packages: lmfit\n",
      "Successfully installed lmfit-0.9.7\n"
     ]
    }
   ],
   "source": [
    "!pip3 uninstall -y lmfit\n",
    "\n",
    "!pip3 install lmfit==0.9.7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-22T13:41:58.553103Z",
     "start_time": "2018-05-22T13:41:58.548999Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overwriting /tmp/test.py\n"
     ]
    }
   ],
   "source": [
    "%%writefile /tmp/test.py\n",
    "import numpy as np\n",
    "import lmfit\n",
    "print('lmfit version =', lmfit.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-22T13:41:59.580412Z",
     "start_time": "2018-05-22T13:41:58.554754Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lmfit version = 0.9.7\r\n"
     ]
    }
   ],
   "source": [
    "!python3 /tmp/test.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-22T13:41:59.586593Z",
     "start_time": "2018-05-22T13:41:59.582678Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overwriting /tmp/test.py\n"
     ]
    }
   ],
   "source": [
    "%%writefile /tmp/test.py\n",
    "\n",
    "import numpy as np\n",
    "import lmfit\n",
    "print('lmfit version =', lmfit.__version__)\n",
    "from lmfit import Model, Parameters\n",
    "\n",
    "N, n = 500, 50\n",
    "x = np.linspace(-1, 1, N)\n",
    "gamma_true = 1.\n",
    "np.random.seed(7)\n",
    "\n",
    "def ReLU(x, gamma) :\n",
    "    time = np.arange(len(x))\n",
    "    return time * gamma * (time > 0)\n",
    "\n",
    "a = ReLU(x, gamma_true)\n",
    "a += np.random.randn(N)\n",
    "a[N//2-n:N//2+n] *= np.nan\n",
    "\n",
    "model = Model(ReLU)\n",
    "params = Parameters()\n",
    "\n",
    "params.add('gamma', value=gamma_true, min=.1, max=80.)\n",
    "result_deg = model.fit(a, params, x=x, fit_kws={'nan_policy': 'omit'})\n",
    "\n",
    "print(result_deg.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-22T13:42:00.644737Z",
     "start_time": "2018-05-22T13:41:59.587970Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lmfit version = 0.9.7\r\n",
      "{'gamma': 0.9996924995050569}\r\n"
     ]
    }
   ],
   "source": [
    "!python3 /tmp/test.py"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 0.9.9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-22T13:42:02.844429Z",
     "start_time": "2018-05-22T13:42:00.646860Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Uninstalling lmfit-0.9.7:\n",
      "  Successfully uninstalled lmfit-0.9.7\n",
      "Collecting lmfit==0.9.9\n",
      "Requirement already satisfied: six in /usr/local/lib/python3.6/site-packages (from lmfit==0.9.9) (1.11.0)\n",
      "Requirement already satisfied: scipy in /usr/local/lib/python3.6/site-packages (from lmfit==0.9.9) (1.1.0)\n",
      "Requirement already satisfied: asteval in /usr/local/lib/python3.6/site-packages (from lmfit==0.9.9) (0.9.12)\n",
      "Requirement already satisfied: numpy in /usr/local/lib/python3.6/site-packages (from lmfit==0.9.9) (1.14.3)\n",
      "\u001b[31mtensorboard 1.8.0 has requirement bleach==1.5.0, but you'll have bleach 2.1.3 which is incompatible.\u001b[0m\n",
      "\u001b[31mtensorboard 1.8.0 has requirement html5lib==0.9999999, but you'll have html5lib 1.0.1 which is incompatible.\u001b[0m\n",
      "Installing collected packages: lmfit\n",
      "Successfully installed lmfit-0.9.9\n"
     ]
    }
   ],
   "source": [
    "!pip3 uninstall -y lmfit\n",
    "\n",
    "!pip3 install lmfit==0.9.9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-22T13:42:02.850371Z",
     "start_time": "2018-05-22T13:42:02.846509Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overwriting /tmp/test.py\n"
     ]
    }
   ],
   "source": [
    "%%writefile /tmp/test.py\n",
    "import numpy as np\n",
    "import lmfit\n",
    "print('lmfit version =', lmfit.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-22T13:42:03.882082Z",
     "start_time": "2018-05-22T13:42:02.851973Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lmfit version = 0.9.9\r\n"
     ]
    }
   ],
   "source": [
    "!python3 /tmp/test.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-22T13:42:12.634257Z",
     "start_time": "2018-05-22T13:42:12.630203Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overwriting /tmp/test.py\n"
     ]
    }
   ],
   "source": [
    "%%writefile /tmp/test.py\n",
    "\n",
    "import numpy as np\n",
    "import lmfit\n",
    "print('lmfit version =', lmfit.__version__)\n",
    "from lmfit import Model, Parameters\n",
    "\n",
    "N, n = 500, 50\n",
    "x = np.linspace(-1, 1, N)\n",
    "gamma_true = 1.\n",
    "np.random.seed(7)\n",
    "\n",
    "def ReLU(x, gamma) :\n",
    "    time = np.arange(len(x))\n",
    "    return time * gamma * (time > 0)\n",
    "\n",
    "a = ReLU(x, gamma_true)\n",
    "a += np.random.randn(N)\n",
    "a[N//2-n:N//2+n] *= np.nan\n",
    "\n",
    "model = Model(ReLU)\n",
    "params = Parameters()\n",
    "\n",
    "params.add('gamma', value=gamma_true, min=.1, max=80.)\n",
    "result_deg = model.fit(a, params, x=x, nan_policy='omit')\n",
    "\n",
    "print(result_deg.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-22T13:42:14.291280Z",
     "start_time": "2018-05-22T13:42:13.281810Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lmfit version = 0.9.9\r\n",
      "{'gamma': 1.2814511526760501}\r\n"
     ]
    }
   ],
   "source": [
    "!python3 /tmp/test.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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