datasets/SWiFT/process_TTU_tower.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import os\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.cm import get_cmap\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for data processing\n",
    "from mmctools.dataloaders import read_files\n",
    "from mmctools.helper_functions import calc_wind, theta, covariance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# site-specific correction\n",
    "from TTURawToMMC import reg_coefs, tilts\n",
    "from mmctools.measurements.metmast import tilt_correction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for plotting\n",
    "from mmctools.plotting import plot_timehistory_at_height, plot_profile"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Process and tilt-correct sonic data from TTU tower\n",
    "written by [Eliot Quon](mailto:eliot.quon@nrel.gov)\n",
    "\n",
    "Process data at SWiFT on 2013-11-08 and 09"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# DAP data\n",
    "dataset = 'mmc/tower.z01.00'\n",
    "datapath = 'data' # where the data will get saved locally\n",
    "startdate = pd.to_datetime('2013-11-08')\n",
    "enddate = pd.to_datetime('2013-11-10')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# outputs\n",
    "output_1Hz = 'data/TTU_tilt_corrected_20131108-09.csv'\n",
    "output_10min = 'data/TTU_tilt_corrected_20131108-09_10min.csv'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Data processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "filelist = []\n",
    "overwrite_files = False # force download of files"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1a. try to get data from DAP on the fly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No authentication found. Using guest credentials...\n",
      "username: quon\n",
      "password: ········\n",
      "Success!\n",
      "48 data files selected\n",
      "Could not place order\n",
      "Server Returned Bad Status Code\n",
      "Status Code: 400\n",
      "Reason: order is too large to create (10 GB limit)\n",
      "No files were downloaded; need to manually download and set `filelist`\n"
     ]
    }
   ],
   "source": [
    "try:\n",
    "    import A2e\n",
    "except ImportError:\n",
    "    print('dap-py module not available; need to manually set `filelist`')\n",
    "else:\n",
    "    a2e = A2e.A2e()\n",
    "    a2e.setup_cert_auth()\n",
    "    datafiles = a2e.search({\n",
    "        'Dataset': dataset,\n",
    "        'date_time': {\n",
    "            'between': [startdate.strftime('%Y%m%d%H%M%S'), enddate.strftime('%Y%m%d%H%M%S')]\n",
    "        }\n",
    "    })\n",
    "    print(len(datafiles),'data files selected')\n",
    "    filelist = a2e.download_files(datafiles, path=datapath, force=overwrite_files)\n",
    "    if filelist is None:\n",
    "        print('No files were downloaded; need to manually download and set `filelist`')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['data/mmc.tower.z01.00/tower.z01.00.20131108.000000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.010000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.020000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.030000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.040000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.050000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.060000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.070000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.080000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.090000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.100000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.110000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.120000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.130000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.140000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.150000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.160000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.170000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.180000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.190000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.200000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.210000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.220000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131108.230000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.000000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.010000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.020000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.030000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.040000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.050000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.060000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.070000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.080000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.090000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.100000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.110000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.120000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.130000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.140000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.150000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.160000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.170000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.180000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.190000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.200000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.210000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.220000.ttu200m.dat',\n",
       " 'data/mmc.tower.z01.00/tower.z01.00.20131109.230000.ttu200m.dat']"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# UNCOMMENT THIS to use previously downloaded files\n",
    "import glob\n",
    "filelist = glob.glob('data/mmc.tower.z01.00/*.dat')\n",
    "filelist.sort()\n",
    "filelist"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1b. process downloaded data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "variables = ['unorth','vwest','w','ustream','vcross','wdir','tsonic','t','p','rh']\n",
    "\n",
    "#heights_ft = [3,8,13,33,55,155,245,382,519,656]\n",
    "heights = np.array([0.9, 2.4, 4.0, 10.1, 16.8, 47.3, 74.7, 116.5, 158.2, 200.0])\n",
    "sampling_freq = 50. # Hz\n",
    "resample_interval = '1s'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# *wide* format: variables change the fastest, then heights\n",
    "# e.g., unorth_3ft, vwest_3ft, ..., rh_3ft, unorth_8ft, vwest_8ft, ...\n",
    "columns = pd.MultiIndex.from_product([heights,variables],names=['height',None])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def read_wide_csv(fname,**kwargs):\n",
    "    \"\"\"Convert table in wide format into stacked/long format with multi-index\"\"\"\n",
    "    df = pd.read_csv(fname,\n",
    "                     skiprows=5, header=None,\n",
    "                     index_col=0, parse_dates=True,\n",
    "                     **kwargs)\n",
    "    df.index.name = 'datetime'\n",
    "    df.columns = columns\n",
    "    df = df.resample(resample_interval).first()\n",
    "    return df.stack(level=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 2min 14s, sys: 10.1 s, total: 2min 24s\n",
      "Wall time: 2min 24s\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>p</th>\n",
       "      <th>rh</th>\n",
       "      <th>t</th>\n",
       "      <th>tsonic</th>\n",
       "      <th>unorth</th>\n",
       "      <th>ustream</th>\n",
       "      <th>vcross</th>\n",
       "      <th>vwest</th>\n",
       "      <th>w</th>\n",
       "      <th>wdir</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datetime</th>\n",
       "      <th>height</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2013-11-08</th>\n",
       "      <th>0.9</th>\n",
       "      <td>90.854775</td>\n",
       "      <td>26.186</td>\n",
       "      <td>52.9592</td>\n",
       "      <td>61.26800</td>\n",
       "      <td>-2.638194</td>\n",
       "      <td>2.640161</td>\n",
       "      <td>-0.093404</td>\n",
       "      <td>-0.138231</td>\n",
       "      <td>0.040203</td>\n",
       "      <td>177.000664</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.4</th>\n",
       "      <td>90.872351</td>\n",
       "      <td>25.810</td>\n",
       "      <td>53.2076</td>\n",
       "      <td>64.09399</td>\n",
       "      <td>-2.796803</td>\n",
       "      <td>2.833327</td>\n",
       "      <td>0.393956</td>\n",
       "      <td>-0.600695</td>\n",
       "      <td>0.297950</td>\n",
       "      <td>167.878211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <td>90.821555</td>\n",
       "      <td>25.380</td>\n",
       "      <td>53.6288</td>\n",
       "      <td>57.86600</td>\n",
       "      <td>-4.041865</td>\n",
       "      <td>4.005252</td>\n",
       "      <td>-0.683208</td>\n",
       "      <td>0.414897</td>\n",
       "      <td>0.342024</td>\n",
       "      <td>185.860873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10.1</th>\n",
       "      <td>90.761141</td>\n",
       "      <td>25.264</td>\n",
       "      <td>53.8664</td>\n",
       "      <td>57.38000</td>\n",
       "      <td>-5.229591</td>\n",
       "      <td>5.225090</td>\n",
       "      <td>-0.351743</td>\n",
       "      <td>-0.276876</td>\n",
       "      <td>-0.354408</td>\n",
       "      <td>176.969358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16.8</th>\n",
       "      <td>90.730765</td>\n",
       "      <td>24.934</td>\n",
       "      <td>54.0752</td>\n",
       "      <td>58.02800</td>\n",
       "      <td>-5.908238</td>\n",
       "      <td>5.901349</td>\n",
       "      <td>-0.287311</td>\n",
       "      <td>0.034531</td>\n",
       "      <td>-0.112876</td>\n",
       "      <td>180.334863</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           p      rh        t    tsonic    unorth   ustream  \\\n",
       "datetime   height                                                             \n",
       "2013-11-08 0.9     90.854775  26.186  52.9592  61.26800 -2.638194  2.640161   \n",
       "           2.4     90.872351  25.810  53.2076  64.09399 -2.796803  2.833327   \n",
       "           4.0     90.821555  25.380  53.6288  57.86600 -4.041865  4.005252   \n",
       "           10.1    90.761141  25.264  53.8664  57.38000 -5.229591  5.225090   \n",
       "           16.8    90.730765  24.934  54.0752  58.02800 -5.908238  5.901349   \n",
       "\n",
       "                     vcross     vwest         w        wdir  \n",
       "datetime   height                                            \n",
       "2013-11-08 0.9    -0.093404 -0.138231  0.040203  177.000664  \n",
       "           2.4     0.393956 -0.600695  0.297950  167.878211  \n",
       "           4.0    -0.683208  0.414897  0.342024  185.860873  \n",
       "           10.1   -0.351743 -0.276876 -0.354408  176.969358  \n",
       "           16.8   -0.287311  0.034531 -0.112876  180.334863  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%time rawdata = read_files(filelist, reader=read_wide_csv)\n",
    "rawdata.head()\n",
    "# CPU times: user 2min 16s, sys: 10.3 s, total: 2min 26s\n",
    "# Wall time: 2min 27s"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1c. data standardization\n",
    "<font color='red'>These data conversions are specific to TTU met tower (tower.z01.00)</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "rawdata['u'] = rawdata['vwest']\n",
    "rawdata['v'] = -rawdata['unorth']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# convert from deg F to K\n",
    "rawdata['t'] = 5./9. * (rawdata['t']-32) + 273.15\n",
    "rawdata['tsonic'] = 5./9. * (rawdata['tsonic']-32) + 273.15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# convert kPa to mbar\n",
    "rawdata['p'] *= 10."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# rename vars\n",
    "rawdata = rawdata.rename(columns={\n",
    "    't': 'T',\n",
    "    'tsonic': 'Ts',\n",
    "    'rh': 'RH',\n",
    "})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Calculations\n",
    "### 2a. Perform tilt correction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "corrected = rawdata[['u','v','w','Ts','T','RH','p']].unstack() # make an unstacked copy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "ucorr,vcorr,wcorr = tilt_correction(corrected['u'],corrected['v'],corrected['w'],\n",
    "                                    reg_coefs=reg_coefs,\n",
    "                                    tilts=tilts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "corrected.loc[:,'u'] = ucorr\n",
    "corrected.loc[:,'v'] = vcorr\n",
    "corrected.loc[:,'w'] = wcorr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "corrected = corrected.stack(dropna=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color='green'>At this point, we save the high-frequency data for spectral analysis</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 31.8 s, sys: 1.19 s, total: 33 s\n",
      "Wall time: 33.1 s\n"
     ]
    }
   ],
   "source": [
    "%time corrected.to_csv(output_1Hz)\n",
    "# CPU times: user 32.7 s, sys: 1.33 s, total: 34 s\n",
    "# Wall time: 34.1 s"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2b. Calculate additional quantities of interest\n",
    "Note: per `TTU_tower_heatflux_stability.ipynb`, `theta` (calculated from air temperature) is acceptable for analysis in the mean; for correlations, `thetas` (calculated from sonic temperature) should be used for calculating fluctuations and correlations. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calc_QOIs(df):\n",
    "    df['theta'] = theta(df['T'], df['p'])\n",
    "    df['thetas'] = theta(df['Ts'], df['p'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>p</th>\n",
       "      <th>RH</th>\n",
       "      <th>T</th>\n",
       "      <th>Ts</th>\n",
       "      <th>unorth</th>\n",
       "      <th>ustream</th>\n",
       "      <th>vcross</th>\n",
       "      <th>vwest</th>\n",
       "      <th>w</th>\n",
       "      <th>wdir</th>\n",
       "      <th>u</th>\n",
       "      <th>v</th>\n",
       "      <th>theta</th>\n",
       "      <th>thetas</th>\n",
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       "      <th>datetime</th>\n",
       "      <th>height</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2013-11-08</th>\n",
       "      <th>0.9</th>\n",
       "      <td>908.547754</td>\n",
       "      <td>26.186</td>\n",
       "      <td>284.794</td>\n",
       "      <td>289.410000</td>\n",
       "      <td>-2.638194</td>\n",
       "      <td>2.640161</td>\n",
       "      <td>-0.093404</td>\n",
       "      <td>-0.138231</td>\n",
       "      <td>0.040203</td>\n",
       "      <td>177.000664</td>\n",
       "      <td>-0.138231</td>\n",
       "      <td>2.638194</td>\n",
       "      <td>292.713920</td>\n",
       "      <td>297.458288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.4</th>\n",
       "      <td>908.723508</td>\n",
       "      <td>25.810</td>\n",
       "      <td>284.932</td>\n",
       "      <td>290.979994</td>\n",
       "      <td>-2.796803</td>\n",
       "      <td>2.833327</td>\n",
       "      <td>0.393956</td>\n",
       "      <td>-0.600695</td>\n",
       "      <td>0.297950</td>\n",
       "      <td>167.878211</td>\n",
       "      <td>-0.600695</td>\n",
       "      <td>2.796803</td>\n",
       "      <td>292.839558</td>\n",
       "      <td>299.055399</td>\n",
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       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <td>908.215548</td>\n",
       "      <td>25.380</td>\n",
       "      <td>285.166</td>\n",
       "      <td>287.520000</td>\n",
       "      <td>-4.041865</td>\n",
       "      <td>4.005252</td>\n",
       "      <td>-0.683208</td>\n",
       "      <td>0.414897</td>\n",
       "      <td>0.342024</td>\n",
       "      <td>185.860873</td>\n",
       "      <td>0.414897</td>\n",
       "      <td>4.041865</td>\n",
       "      <td>293.126923</td>\n",
       "      <td>295.546639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10.1</th>\n",
       "      <td>907.611414</td>\n",
       "      <td>25.264</td>\n",
       "      <td>285.298</td>\n",
       "      <td>287.250000</td>\n",
       "      <td>-5.229591</td>\n",
       "      <td>5.225090</td>\n",
       "      <td>-0.351743</td>\n",
       "      <td>-0.276876</td>\n",
       "      <td>-0.354408</td>\n",
       "      <td>176.969358</td>\n",
       "      <td>-0.276876</td>\n",
       "      <td>5.229591</td>\n",
       "      <td>293.318423</td>\n",
       "      <td>295.325299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16.8</th>\n",
       "      <td>907.307654</td>\n",
       "      <td>24.934</td>\n",
       "      <td>285.414</td>\n",
       "      <td>287.610000</td>\n",
       "      <td>-5.908238</td>\n",
       "      <td>5.901349</td>\n",
       "      <td>-0.287311</td>\n",
       "      <td>0.034531</td>\n",
       "      <td>-0.112876</td>\n",
       "      <td>180.334863</td>\n",
       "      <td>0.034531</td>\n",
       "      <td>5.908238</td>\n",
       "      <td>293.465778</td>\n",
       "      <td>295.723729</td>\n",
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      ],
      "text/plain": [
       "                            p      RH        T          Ts    unorth  \\\n",
       "datetime   height                                                      \n",
       "2013-11-08 0.9     908.547754  26.186  284.794  289.410000 -2.638194   \n",
       "           2.4     908.723508  25.810  284.932  290.979994 -2.796803   \n",
       "           4.0     908.215548  25.380  285.166  287.520000 -4.041865   \n",
       "           10.1    907.611414  25.264  285.298  287.250000 -5.229591   \n",
       "           16.8    907.307654  24.934  285.414  287.610000 -5.908238   \n",
       "\n",
       "                    ustream    vcross     vwest         w        wdir  \\\n",
       "datetime   height                                                       \n",
       "2013-11-08 0.9     2.640161 -0.093404 -0.138231  0.040203  177.000664   \n",
       "           2.4     2.833327  0.393956 -0.600695  0.297950  167.878211   \n",
       "           4.0     4.005252 -0.683208  0.414897  0.342024  185.860873   \n",
       "           10.1    5.225090 -0.351743 -0.276876 -0.354408  176.969358   \n",
       "           16.8    5.901349 -0.287311  0.034531 -0.112876  180.334863   \n",
       "\n",
       "                          u         v       theta      thetas  \n",
       "datetime   height                                              \n",
       "2013-11-08 0.9    -0.138231  2.638194  292.713920  297.458288  \n",
       "           2.4    -0.600695  2.796803  292.839558  299.055399  \n",
       "           4.0     0.414897  4.041865  293.126923  295.546639  \n",
       "           10.1   -0.276876  5.229591  293.318423  295.325299  \n",
       "           16.8    0.034531  5.908238  293.465778  295.723729  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "calc_QOIs(rawdata)\n",
    "rawdata.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>v</th>\n",
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       "      <th>Ts</th>\n",
       "      <th>T</th>\n",
       "      <th>RH</th>\n",
       "      <th>p</th>\n",
       "      <th>theta</th>\n",
       "      <th>thetas</th>\n",
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       "      <th>datetime</th>\n",
       "      <th>height</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2013-11-08</th>\n",
       "      <th>0.9</th>\n",
       "      <td>-0.138929</td>\n",
       "      <td>2.637817</td>\n",
       "      <td>0.074016</td>\n",
       "      <td>289.410000</td>\n",
       "      <td>284.794</td>\n",
       "      <td>26.186</td>\n",
       "      <td>908.547754</td>\n",
       "      <td>292.713920</td>\n",
       "      <td>297.458288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.4</th>\n",
       "      <td>-0.601111</td>\n",
       "      <td>2.783204</td>\n",
       "      <td>0.487330</td>\n",
       "      <td>290.979994</td>\n",
       "      <td>284.932</td>\n",
       "      <td>25.810</td>\n",
       "      <td>908.723508</td>\n",
       "      <td>292.839558</td>\n",
       "      <td>299.055399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <td>0.416792</td>\n",
       "      <td>4.043940</td>\n",
       "      <td>0.295800</td>\n",
       "      <td>287.520000</td>\n",
       "      <td>285.166</td>\n",
       "      <td>25.380</td>\n",
       "      <td>908.215548</td>\n",
       "      <td>293.126923</td>\n",
       "      <td>295.546639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10.1</th>\n",
       "      <td>-0.276479</td>\n",
       "      <td>5.227110</td>\n",
       "      <td>-0.418065</td>\n",
       "      <td>287.250000</td>\n",
       "      <td>285.298</td>\n",
       "      <td>25.264</td>\n",
       "      <td>907.611414</td>\n",
       "      <td>293.318423</td>\n",
       "      <td>295.325299</td>\n",
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       "    <tr>\n",
       "      <th>16.8</th>\n",
       "      <td>0.034364</td>\n",
       "      <td>5.908367</td>\n",
       "      <td>-0.173836</td>\n",
       "      <td>287.610000</td>\n",
       "      <td>285.414</td>\n",
       "      <td>24.934</td>\n",
       "      <td>907.307654</td>\n",
       "      <td>293.465778</td>\n",
       "      <td>295.723729</td>\n",
       "    </tr>\n",
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       "</div>"
      ],
      "text/plain": [
       "                          u         v         w          Ts        T      RH  \\\n",
       "datetime   height                                                              \n",
       "2013-11-08 0.9    -0.138929  2.637817  0.074016  289.410000  284.794  26.186   \n",
       "           2.4    -0.601111  2.783204  0.487330  290.979994  284.932  25.810   \n",
       "           4.0     0.416792  4.043940  0.295800  287.520000  285.166  25.380   \n",
       "           10.1   -0.276479  5.227110 -0.418065  287.250000  285.298  25.264   \n",
       "           16.8    0.034364  5.908367 -0.173836  287.610000  285.414  24.934   \n",
       "\n",
       "                            p       theta      thetas  \n",
       "datetime   height                                      \n",
       "2013-11-08 0.9     908.547754  292.713920  297.458288  \n",
       "           2.4     908.723508  292.839558  299.055399  \n",
       "           4.0     908.215548  293.126923  295.546639  \n",
       "           10.1    907.611414  293.318423  295.325299  \n",
       "           16.8    907.307654  293.465778  295.723729  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "calc_QOIs(corrected)\n",
    "corrected.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2c. Calculate rolling statistics\n",
    "See `TTU_tower_heatflux_stability.ipynb` for more details regarding $T_v$ vs $T_s$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calc_rolling_stats(df,offset='10min'):\n",
    "    \"\"\"Calculate quantities of interest, with statistics based on the specified pandas offset string\n",
    "    \n",
    "    Note: we could also have used `resample` instead of `rolling`. To be consistent with previous analyses,\n",
    "    however, I've used rolling statistics for the plots in the next section.\n",
    "    \"\"\"\n",
    "    # calculate statistical quantities on unstacked \n",
    "    unstacked = df.unstack()\n",
    "    stats = unstacked.rolling(offset).mean().stack()\n",
    "    # - recalculate wind based on averaged components\n",
    "    stats['wspd'], stats['wdir'] = calc_wind(stats)\n",
    "#     stats['theta'] = theta(stats['T'], stats['p'])\n",
    "#     stats['thetas'] = theta(stats['Ts'], stats['p'])\n",
    "    # - calculate variances\n",
    "    stats['uu'] = unstacked['u'].rolling(offset).var().stack()\n",
    "    stats['vv'] = unstacked['v'].rolling(offset).var().stack()\n",
    "    stats['ww'] = unstacked['w'].rolling(offset).var().stack()\n",
    "    # - calculate covariances\n",
    "    stats['uv'] = covariance(unstacked['u'], unstacked['v'], offset).stack()\n",
    "    stats['vw'] = covariance(unstacked['v'], unstacked['w'], offset).stack()\n",
    "    stats['uw'] = covariance(unstacked['u'], unstacked['w'], offset).stack()\n",
    "    stats['Tw'] = covariance(unstacked['Ts'], unstacked['w'], offset).stack()\n",
    "    stats['thetaw'] = covariance(unstacked['thetas'], unstacked['w'], offset).stack()\n",
    "    # - calculate derived quantities\n",
    "    #   TODO: implement in helper_functions.py\n",
    "    stats['u*'] = (stats['uw']**2 + stats['vw']**2)**0.25\n",
    "    stats['TKE'] = 0.5*(stats['uu'] + stats['vv'] + stats['ww'])\n",
    "    ang = np.radians(270. - stats['wdir'])\n",
    "    ang[ang<0] += 2*np.pi\n",
    "    stats['TI'] = stats['uu']*np.cos(ang)**2 + 2*stats['uv']*np.sin(ang)*np.cos(ang) + stats['vv']*np.sin(ang)**2\n",
    "    stats['TI'] = np.sqrt(stats['TI']) / stats['wspd']\n",
    "    return stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 23.6 s, sys: 2.14 s, total: 25.7 s\n",
      "Wall time: 24.8 s\n"
     ]
    }
   ],
   "source": [
    "%time uncorrected_10min = calc_rolling_stats(rawdata)\n",
    "# CPU times: user 24.2 s, sys: 2.03 s, total: 26.2 s\n",
    "# Wall time: 24.9 s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 22.6 s, sys: 1.81 s, total: 24.4 s\n",
      "Wall time: 23.6 s\n"
     ]
    }
   ],
   "source": [
    "# rolling 10-min stats\n",
    "%time corrected_10min = calc_rolling_stats(corrected)\n",
    "# CPU times: user 22.3 s, sys: 1.48 s, total: 23.8 s\n",
    "# Wall time: 23 s"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color='green'>We can now save more general (and manageable) validation data for other analyses</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# save resampled 10-min stats (note: we've already calculated the rolling statistics)\n",
    "corrected_10min.unstack().resample('10min').first().stack().to_csv(output_10min)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2013-11-08 00:00:00', '2013-11-08 00:00:01',\n",
       "               '2013-11-08 00:00:02', '2013-11-08 00:00:03',\n",
       "               '2013-11-08 00:00:04', '2013-11-08 00:00:05',\n",
       "               '2013-11-08 00:00:06', '2013-11-08 00:00:07',\n",
       "               '2013-11-08 00:00:08', '2013-11-08 00:00:09',\n",
       "               ...\n",
       "               '2013-11-09 23:59:50', '2013-11-09 23:59:51',\n",
       "               '2013-11-09 23:59:52', '2013-11-09 23:59:53',\n",
       "               '2013-11-09 23:59:54', '2013-11-09 23:59:55',\n",
       "               '2013-11-09 23:59:56', '2013-11-09 23:59:57',\n",
       "               '2013-11-09 23:59:58', '2013-11-09 23:59:59'],\n",
       "              dtype='datetime64[ns]', name='datetime', length=172798, freq=None)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "times = corrected_10min.index.levels[0]\n",
    "times"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x648 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "zhub = 74.7\n",
    "fig,ax = plot_timehistory_at_height(\n",
    "    {'uncorrected':uncorrected_10min, 'tilt corrected':corrected_10min},\n",
    "    fields=['wspd','wdir','w'],\n",
    "    heights=zhub,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, '$\\\\theta$ [K]')"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "selected_times = [\n",
    "    '2013-11-08 12:00:00', # very stable\n",
    "    '2013-11-08 15:00:00', # ~neutral\n",
    "    '2013-11-08 18:00:00', # slightly unstable\n",
    "    '2013-11-08 21:00:00', # ~neutral\n",
    "    '2013-11-09 00:00:00', # ~neutral\n",
    "    '2013-11-09 03:00:00', # slightly stable\n",
    "]\n",
    "fig,ax = plot_profile(corrected_10min, fields=['Ts','theta'], times=selected_times, cmap='viridis')\n",
    "ax[0].set_xlabel(r'$T_s$ [K]')\n",
    "ax[1].set_xlabel(r'$\\theta$ [K]')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, '$time$ $[\\\\mathrm{HH:MM}]$ $Z$')"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Jeremy's plot from `TTU_tiltCorrection.ipynb`\n",
    "w = corrected.xs(zhub, level='height')['w']\n",
    "day1 = (w.index >= '2013-11-08 00:00') & (w.index <= '2013-11-09 00:00')\n",
    "w = w.loc[day1]\n",
    "wmean = w.rolling('10min').mean()\n",
    "fig,ax = plt.subplots(figsize=(18,2))\n",
    "w.plot(style='b.')\n",
    "wmean.plot(style='r-')\n",
    "ax.set_ylabel(r'$w$ $[\\mathrm{ms^{-1}}]$', fontsize=14)\n",
    "ax.set_xlabel(r'$time$ $[\\mathrm{HH:MM}]$ $Z$', fontsize=14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "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": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}