findSMP.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5c8761f8-3dbd-4900-b6e8-8f210aadaeca",
   "metadata": {},
   "outputs": [],
   "source": [
    "from snowexsql.api import LayerMeasurements\n",
    "data_type = 'depth'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d4101397-65f2-4e13-b168-0ce1408ed931",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Available types = sample_signal, force, density, grain_size, reflectance, permittivity, lwc_vol, manual_wetness, equivalent_diameter, specific_surface_area, grain_type, temperature, hand_hardness\n"
     ]
    }
   ],
   "source": [
    "measurements = LayerMeasurements()\n",
    "results = measurements.all_types\n",
    "print('Available types = {}'.format(', '.join([str(r) for r in results])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b601342d-7de2-454d-b6ce-52d4fb7958ce",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Available types = IS3-SP-15-01US, IRIS, None, snowmicropen, IS3-SP-11-01F\n"
     ]
    }
   ],
   "source": [
    "results = measurements.all_instruments\n",
    "print('Available types = {}'.format(', '.join([str(r) for r in results])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f356f89b-80ee-470f-b530-2a5ef1dba245",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Available types = Fairbanks, Fraser Experimental Forest, Boise River Basin, Little Cottonwood Canyon, North Slope, East River, Jemez River, Grand Mesa, Cameron Pass, Sagehen Creek, Mammoth Lakes, Niwot Ridge, American River Basin, Senator Beck, Central Ag Research Center\n"
     ]
    }
   ],
   "source": [
    "results = measurements.all_site_names\n",
    "print('Available types = {}'.format(', '.join([str(r) for r in results])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5a5298dd-ca0a-4bfe-ad3f-d82d0590bba9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Available Dates = 2021-03-09, 2020-03-12, 2020-02-21, 2020-01-09, 2020-12-17, 2023-03-07, 2021-03-19, 2020-01-04, 2021-02-11, 2021-01-28, 2020-04-17, 2023-03-16, 2019-12-18, 2020-02-19, 2021-02-19, 2020-02-26, 2019-12-30, 2020-02-03, 2021-04-14, 2023-03-09, 2020-01-30, 2023-03-08, 2020-01-24, 2020-12-18, 2020-04-22, 2020-03-31, 2020-01-08, 2020-02-06, 2020-03-05, 2021-02-18, 2021-05-27, 2020-04-01, 2021-03-18, 2019-10-29, 2020-01-31, 2020-04-18, 2021-02-04, 2020-04-29, 2021-03-03, 2020-01-22, 2021-01-15, 2021-01-21, 2020-02-20, 2023-03-13, 2020-11-23, 2020-02-12, 2020-05-06, 2021-05-07, 2019-12-03, 2021-01-26, 2020-02-08, 2020-04-28, 2021-04-21, 2021-03-21, 2021-02-16, 2023-03-15, 2020-05-20, 2020-11-25, 2023-03-10, 2021-01-27, 2020-02-05, 2020-01-28, 2020-04-21, 2021-01-22, 2019-12-19, 2021-03-05, 2020-03-28, 2020-02-10, 2021-04-28, 2019-11-24, 2020-04-09, 2021-03-10, 2021-03-04, 2021-03-24, 2021-03-16, 2020-03-16, 2020-03-21, 2021-04-23, 2020-02-02, 2020-02-25, 2020-04-08, 2019-12-16, 2020-01-29, 2021-03-22, 2020-02-04, 2021-02-10, 2020-03-07, 2020-04-06, 2020-05-03, 2019-12-10, 2021-02-03, 2020-02-27, 2020-02-14, 2020-02-13, 2021-02-09, 2020-01-19, 2020-12-08, 2020-01-17, 2021-03-02, 2021-02-17, 2020-12-16, 2021-01-07, 2021-03-31, 2020-03-13, 2021-05-20, 2021-01-13, 2019-10-24, 2020-03-11, 2020-02-01, 2021-03-23, 2020-02-09, 2020-05-12, 2020-04-19, 2020-01-23, 2021-02-23, 2020-11-20, 2020-02-07, 2021-05-05, 2021-04-06, 2020-03-18, 2020-05-13, 2019-12-20, 2021-01-20, 2019-12-23, 2020-02-28, 2021-05-17, 2021-04-07, 2021-01-14, 2020-12-09, 2020-01-16, 2023-03-11, 2023-03-14, 2021-02-02, 2020-02-11, 2023-03-12, 2020-01-27, 2020-11-16, 2020-03-06, 2021-03-17, 2020-03-04, 2021-02-24, 2020-04-27, 2020-03-25, 2021-02-25, 2020-12-01\n"
     ]
    }
   ],
   "source": [
    "results = measurements.all_dates\n",
    "print('\\nAvailable Dates = {}'.format(', '.join([str(r) for r in results])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6893c117-451a-4695-ad3c-02f1c52f36a3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[datetime.date(2020, 2, 4),\n",
       " datetime.date(2020, 2, 3),\n",
       " datetime.date(2020, 1, 30),\n",
       " datetime.date(2020, 2, 1),\n",
       " datetime.date(2020, 2, 6),\n",
       " datetime.date(2020, 1, 31),\n",
       " datetime.date(2020, 2, 12),\n",
       " datetime.date(2020, 2, 8),\n",
       " datetime.date(2020, 2, 5),\n",
       " datetime.date(2020, 1, 28),\n",
       " datetime.date(2020, 2, 11),\n",
       " datetime.date(2020, 2, 10),\n",
       " datetime.date(2020, 1, 29)]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LayerMeasurements.from_unique_entries(['date'], instrument='snowmicropen', site_name='Grand Mesa')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4bff5fef-0ed7-46cb-88af-34b57a37d090",
   "metadata": {},
   "outputs": [
    {
     "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>depth</th>\n",
       "      <th>site_id</th>\n",
       "      <th>pit_id</th>\n",
       "      <th>bottom_depth</th>\n",
       "      <th>comments</th>\n",
       "      <th>sample_a</th>\n",
       "      <th>sample_b</th>\n",
       "      <th>sample_c</th>\n",
       "      <th>value</th>\n",
       "      <th>flags</th>\n",
       "      <th>...</th>\n",
       "      <th>date</th>\n",
       "      <th>time_created</th>\n",
       "      <th>time_updated</th>\n",
       "      <th>id</th>\n",
       "      <th>doi</th>\n",
       "      <th>date_accessed</th>\n",
       "      <th>instrument</th>\n",
       "      <th>type</th>\n",
       "      <th>units</th>\n",
       "      <th>observers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-3.55</td>\n",
       "      <td>COGM3S38_20200204</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>fname = SNEX20_SMP_S19M1095_3S38_20200204.CSV,...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.052</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>2020-02-04</td>\n",
       "      <td>2022-07-06 16:33:38.300848+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>56036</td>\n",
       "      <td>https://doi.org/10.5067/ZYW6IHFRYDSE</td>\n",
       "      <td>2022-07-06</td>\n",
       "      <td>snowmicropen</td>\n",
       "      <td>force</td>\n",
       "      <td>Newtons</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-3.59</td>\n",
       "      <td>COGM3S38_20200204</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>fname = SNEX20_SMP_S19M1095_3S38_20200204.CSV,...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.05</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>2020-02-04</td>\n",
       "      <td>2022-07-06 16:33:38.300848+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>56037</td>\n",
       "      <td>https://doi.org/10.5067/ZYW6IHFRYDSE</td>\n",
       "      <td>2022-07-06</td>\n",
       "      <td>snowmicropen</td>\n",
       "      <td>force</td>\n",
       "      <td>Newtons</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-3.64</td>\n",
       "      <td>COGM3S38_20200204</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>fname = SNEX20_SMP_S19M1095_3S38_20200204.CSV,...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.047</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>2020-02-04</td>\n",
       "      <td>2022-07-06 16:33:38.300848+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>56038</td>\n",
       "      <td>https://doi.org/10.5067/ZYW6IHFRYDSE</td>\n",
       "      <td>2022-07-06</td>\n",
       "      <td>snowmicropen</td>\n",
       "      <td>force</td>\n",
       "      <td>Newtons</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-3.68</td>\n",
       "      <td>COGM3S38_20200204</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>fname = SNEX20_SMP_S19M1095_3S38_20200204.CSV,...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.05</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>2020-02-04</td>\n",
       "      <td>2022-07-06 16:33:38.300848+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>56039</td>\n",
       "      <td>https://doi.org/10.5067/ZYW6IHFRYDSE</td>\n",
       "      <td>2022-07-06</td>\n",
       "      <td>snowmicropen</td>\n",
       "      <td>force</td>\n",
       "      <td>Newtons</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-3.72</td>\n",
       "      <td>COGM3S38_20200204</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>fname = SNEX20_SMP_S19M1095_3S38_20200204.CSV,...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.055</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>2020-02-04</td>\n",
       "      <td>2022-07-06 16:33:38.300848+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>56040</td>\n",
       "      <td>https://doi.org/10.5067/ZYW6IHFRYDSE</td>\n",
       "      <td>2022-07-06</td>\n",
       "      <td>snowmicropen</td>\n",
       "      <td>force</td>\n",
       "      <td>Newtons</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>-7.48</td>\n",
       "      <td>COGM3S38_20200204</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>fname = SNEX20_SMP_S19M1095_3S38_20200204.CSV,...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.053</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>2020-02-04</td>\n",
       "      <td>2022-07-06 16:33:38.300848+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>56131</td>\n",
       "      <td>https://doi.org/10.5067/ZYW6IHFRYDSE</td>\n",
       "      <td>2022-07-06</td>\n",
       "      <td>snowmicropen</td>\n",
       "      <td>force</td>\n",
       "      <td>Newtons</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>-7.52</td>\n",
       "      <td>COGM3S38_20200204</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>fname = SNEX20_SMP_S19M1095_3S38_20200204.CSV,...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.06</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>2020-02-04</td>\n",
       "      <td>2022-07-06 16:33:38.300848+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>56132</td>\n",
       "      <td>https://doi.org/10.5067/ZYW6IHFRYDSE</td>\n",
       "      <td>2022-07-06</td>\n",
       "      <td>snowmicropen</td>\n",
       "      <td>force</td>\n",
       "      <td>Newtons</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>-7.56</td>\n",
       "      <td>COGM3S38_20200204</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>fname = SNEX20_SMP_S19M1095_3S38_20200204.CSV,...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.051</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>2020-02-04</td>\n",
       "      <td>2022-07-06 16:33:38.300848+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>56133</td>\n",
       "      <td>https://doi.org/10.5067/ZYW6IHFRYDSE</td>\n",
       "      <td>2022-07-06</td>\n",
       "      <td>snowmicropen</td>\n",
       "      <td>force</td>\n",
       "      <td>Newtons</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>-7.60</td>\n",
       "      <td>COGM3S38_20200204</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>fname = SNEX20_SMP_S19M1095_3S38_20200204.CSV,...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.052</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>2020-02-04</td>\n",
       "      <td>2022-07-06 16:33:38.300848+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>56134</td>\n",
       "      <td>https://doi.org/10.5067/ZYW6IHFRYDSE</td>\n",
       "      <td>2022-07-06</td>\n",
       "      <td>snowmicropen</td>\n",
       "      <td>force</td>\n",
       "      <td>Newtons</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>-7.64</td>\n",
       "      <td>COGM3S38_20200204</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>fname = SNEX20_SMP_S19M1095_3S38_20200204.CSV,...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.057</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>2020-02-04</td>\n",
       "      <td>2022-07-06 16:33:38.300848+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>56135</td>\n",
       "      <td>https://doi.org/10.5067/ZYW6IHFRYDSE</td>\n",
       "      <td>2022-07-06</td>\n",
       "      <td>snowmicropen</td>\n",
       "      <td>force</td>\n",
       "      <td>Newtons</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    depth            site_id pit_id bottom_depth  \\\n",
       "0   -3.55  COGM3S38_20200204   None         None   \n",
       "1   -3.59  COGM3S38_20200204   None         None   \n",
       "2   -3.64  COGM3S38_20200204   None         None   \n",
       "3   -3.68  COGM3S38_20200204   None         None   \n",
       "4   -3.72  COGM3S38_20200204   None         None   \n",
       "..    ...                ...    ...          ...   \n",
       "95  -7.48  COGM3S38_20200204   None         None   \n",
       "96  -7.52  COGM3S38_20200204   None         None   \n",
       "97  -7.56  COGM3S38_20200204   None         None   \n",
       "98  -7.60  COGM3S38_20200204   None         None   \n",
       "99  -7.64  COGM3S38_20200204   None         None   \n",
       "\n",
       "                                             comments sample_a sample_b  \\\n",
       "0   fname = SNEX20_SMP_S19M1095_3S38_20200204.CSV,...     None     None   \n",
       "1   fname = SNEX20_SMP_S19M1095_3S38_20200204.CSV,...     None     None   \n",
       "2   fname = SNEX20_SMP_S19M1095_3S38_20200204.CSV,...     None     None   \n",
       "3   fname = SNEX20_SMP_S19M1095_3S38_20200204.CSV,...     None     None   \n",
       "4   fname = SNEX20_SMP_S19M1095_3S38_20200204.CSV,...     None     None   \n",
       "..                                                ...      ...      ...   \n",
       "95  fname = SNEX20_SMP_S19M1095_3S38_20200204.CSV,...     None     None   \n",
       "96  fname = SNEX20_SMP_S19M1095_3S38_20200204.CSV,...     None     None   \n",
       "97  fname = SNEX20_SMP_S19M1095_3S38_20200204.CSV,...     None     None   \n",
       "98  fname = SNEX20_SMP_S19M1095_3S38_20200204.CSV,...     None     None   \n",
       "99  fname = SNEX20_SMP_S19M1095_3S38_20200204.CSV,...     None     None   \n",
       "\n",
       "   sample_c  value flags  ...        date                     time_created  \\\n",
       "0      None  0.052  None  ...  2020-02-04 2022-07-06 16:33:38.300848+00:00   \n",
       "1      None   0.05  None  ...  2020-02-04 2022-07-06 16:33:38.300848+00:00   \n",
       "2      None  0.047  None  ...  2020-02-04 2022-07-06 16:33:38.300848+00:00   \n",
       "3      None   0.05  None  ...  2020-02-04 2022-07-06 16:33:38.300848+00:00   \n",
       "4      None  0.055  None  ...  2020-02-04 2022-07-06 16:33:38.300848+00:00   \n",
       "..      ...    ...   ...  ...         ...                              ...   \n",
       "95     None  0.053  None  ...  2020-02-04 2022-07-06 16:33:38.300848+00:00   \n",
       "96     None   0.06  None  ...  2020-02-04 2022-07-06 16:33:38.300848+00:00   \n",
       "97     None  0.051  None  ...  2020-02-04 2022-07-06 16:33:38.300848+00:00   \n",
       "98     None  0.052  None  ...  2020-02-04 2022-07-06 16:33:38.300848+00:00   \n",
       "99     None  0.057  None  ...  2020-02-04 2022-07-06 16:33:38.300848+00:00   \n",
       "\n",
       "    time_updated     id                                   doi  date_accessed  \\\n",
       "0           None  56036  https://doi.org/10.5067/ZYW6IHFRYDSE     2022-07-06   \n",
       "1           None  56037  https://doi.org/10.5067/ZYW6IHFRYDSE     2022-07-06   \n",
       "2           None  56038  https://doi.org/10.5067/ZYW6IHFRYDSE     2022-07-06   \n",
       "3           None  56039  https://doi.org/10.5067/ZYW6IHFRYDSE     2022-07-06   \n",
       "4           None  56040  https://doi.org/10.5067/ZYW6IHFRYDSE     2022-07-06   \n",
       "..           ...    ...                                   ...            ...   \n",
       "95          None  56131  https://doi.org/10.5067/ZYW6IHFRYDSE     2022-07-06   \n",
       "96          None  56132  https://doi.org/10.5067/ZYW6IHFRYDSE     2022-07-06   \n",
       "97          None  56133  https://doi.org/10.5067/ZYW6IHFRYDSE     2022-07-06   \n",
       "98          None  56134  https://doi.org/10.5067/ZYW6IHFRYDSE     2022-07-06   \n",
       "99          None  56135  https://doi.org/10.5067/ZYW6IHFRYDSE     2022-07-06   \n",
       "\n",
       "      instrument   type    units observers  \n",
       "0   snowmicropen  force  Newtons      None  \n",
       "1   snowmicropen  force  Newtons      None  \n",
       "2   snowmicropen  force  Newtons      None  \n",
       "3   snowmicropen  force  Newtons      None  \n",
       "4   snowmicropen  force  Newtons      None  \n",
       "..           ...    ...      ...       ...  \n",
       "95  snowmicropen  force  Newtons      None  \n",
       "96  snowmicropen  force  Newtons      None  \n",
       "97  snowmicropen  force  Newtons      None  \n",
       "98  snowmicropen  force  Newtons      None  \n",
       "99  snowmicropen  force  Newtons      None  \n",
       "\n",
       "[100 rows x 29 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Find some density pit measurements at the Boise site in december 2019.\n",
    "from snowexsql.api import LayerMeasurements\n",
    "from datetime import datetime \n",
    "dt = datetime(2020, 2, 4)\n",
    "df = LayerMeasurements.from_filter(\n",
    "    instrument='snowmicropen',\n",
    "    site_name=\"Grand Mesa\",\n",
    "    date=dt,\n",
    "    limit=100\n",
    ")\n",
    "\n",
    "# Plot Example!\n",
    "df.plot()\n",
    "\n",
    "# Show off the dataframe\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "cf54f5a2-fe15-4619-8aa4-b8ef66a9f02c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['fname = SNEX20_SMP_S19M1093_5S29_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1065_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1094_5S29_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1047_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1085_5S29_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1074_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1025_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1067_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1039_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1051_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1036_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1072_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1064_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1070_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1068_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1066_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1071_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1078_5S29_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1081_5S29_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1030_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1073_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1083_5S29_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1046_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1033_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1060_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1089_5S29_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1024_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1045_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1061_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1037_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1032_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1052_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1048_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1062_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1056_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1043_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1097_3S38_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1034_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1027_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1059_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1087_5S29_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1096_3S38_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1042_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1095_3S38_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1028_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1040_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1050_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1026_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1080_5S29_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1063_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1088_5S29_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1041_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1055_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1091_5S29_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1075_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1031_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1069_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1049_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1057_3S33_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1082_5S29_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1077_5S29_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1029_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1079_5S29_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1092_5S29_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1035_6S34_20200204.CSV, serial no. = 19',\n",
       " 'fname = SNEX20_SMP_S19M1058_3S33_20200204.CSV, serial no. = 19']"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LayerMeasurements.from_unique_entries(['comments'],date=dt, instrument='snowmicropen', site_name='Grand Mesa')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d1efdb4a-103d-400e-8d39-f8f5b1cad132",
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1ac30288-6359-4d3a-aed9-8f5a2f1af626",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/jovyan/microsnowex2024\n"
     ]
    }
   ],
   "source": [
    "!pwd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "50e90c6c-35e5-4b46-b818-3aa25bfda4cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = gpd.read_file(\"swesarr-roi.shp\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "3d0f6f9f-9499-42be-bffc-7714bba487d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=[12,8])\n",
    "ax = fig.add_axes([0, 0, 1, 1])\n",
    "df2.plot(ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "73c4fe8d-c663-4875-9439-0983763f9b56",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"300\" height=\"300\" viewBox=\"740869.8010793859 4322270.919254883 2011.5748953677248 926.3530404604971\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,8645468.191550227)\"><path fill-rule=\"evenodd\" fill=\"#66cc99\" stroke=\"#555555\" stroke-width=\"13.410499302451498\" opacity=\"0.6\" d=\"M 741035.6077682596,4323122.769521441 L 742806.8732008511,4322981.931958243 L 742744.2646405416,4322345.422028786 L 740944.3038532884,4322517.562325507 L 741035.6077682596,4323122.769521441 z\" /></g></svg>"
      ],
      "text/plain": [
       "<POLYGON ((741035.608 4323122.77, 742806.873 4322981.932, 742744.265 4322345...>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.crs\n",
    "gdf = df2.to_crs(26912)\n",
    "gdf.geometry[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c99a7c40-e8bf-4461-8966-de5c8a3ae75d",
   "metadata": {},
   "outputs": [],
   "source": [
    "site_df = LayerMeasurements.from_filter(site_id='2s7', limit=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "1f6675f4-7e6c-47d3-b4a6-25f5f0445613",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "82d4445e-aa74-4b7c-a72c-0cb1c6b1d36c",
   "metadata": {},
   "outputs": [],
   "source": [
    "s=LayerMeasurements.from_area(shp=gdf.geometry[0], instrument='snowmicropen', site_name='Grand Mesa', limit=276255)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "6828417e-3eac-469a-9553-4eb634de26c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['COGM1S1_20200129', 'COGM1S2_20200208', 'COGM1S8_20200201',\n",
       "       'COGM2S3_20200129', 'COGM2S7_20200208', 'COGM3S5_20200129'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.unique(s['site_id'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "327982f6-275f-4142-b74c-cf112a947c7b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['fname = SNEX20_SMP_S19M0798_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0799_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0800_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0801_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0802_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0803_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0804_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0805_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0806_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0807_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0808_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0809_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0810_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0811_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0812_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0813_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0814_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0815_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0816_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0817_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0818_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0819_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0820_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0821_1S1_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0822_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0823_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0824_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0825_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0826_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0827_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0828_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0829_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0830_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0831_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0832_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0833_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0834_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0835_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0836_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0837_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0838_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0839_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0840_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0841_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0842_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0843_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0844_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0845_2S3_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0846_3S5_20200129.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0903_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0904_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0905_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0906_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0907_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0908_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0909_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0910_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0911_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0912_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0913_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0914_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0915_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0916_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0917_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0918_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0919_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0920_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0921_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0922_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0923_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0924_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0925_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0926_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0927_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0928_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0929_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0930_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0931_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0932_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0933_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0934_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0935_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0936_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0937_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0938_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0939_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0940_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0941_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M0944_1S8_20200201.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1214_1S2_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1215_1S2_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1216_1S2_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1217_1S2_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1218_1S2_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1220_1S2_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1221_1S2_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1222_1S2_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1224_1S2_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1225_1S2_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1226_1S2_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1228_1S2_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1230_1S2_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1233_1S2_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1234_1S2_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1235_1S2_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1236_2S7_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1237_2S7_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1239_2S7_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1240_2S7_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1241_2S7_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1242_2S7_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1243_2S7_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1244_2S7_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1245_2S7_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1246_2S7_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1247_2S7_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1249_2S7_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1250_2S7_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1251_2S7_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1254_2S7_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1255_2S7_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1256_2S7_20200208.CSV, serial no. = 19',\n",
       "       'fname = SNEX20_SMP_S19M1257_2S7_20200208.CSV, serial no. = 19'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.unique(s['comments'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "a7d0486d-c136-46a7-9582-7e2d05e70d5a",
   "metadata": {},
   "outputs": [],
   "source": [
    "s=LayerMeasurements.from_area(shp=gdf.geometry[0], instrument='IRIS', site_name='Grand Mesa')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "66266642-0a27-4df5-8b83-d093711645d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['1S1', '1S8', '2S3', '2S4', '2S6', '3S5'], dtype=object)"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.unique(s['site_id'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "7fa0ca84-f328-4331-bdd6-c4e4a640812b",
   "metadata": {},
   "outputs": [
    {
     "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>depth</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>73.0</td>\n",
       "      <td>631.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>83.0</td>\n",
       "      <td>46.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>80.0</td>\n",
       "      <td>44.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>78.0</td>\n",
       "      <td>44.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>73.0</td>\n",
       "      <td>40.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>38.0</td>\n",
       "      <td>15.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>33.0</td>\n",
       "      <td>14.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>28.0</td>\n",
       "      <td>11.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>23.0</td>\n",
       "      <td>10.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>18.0</td>\n",
       "      <td>11.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>68 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    depth  value\n",
       "0    73.0  631.0\n",
       "1    83.0  46.91\n",
       "2    80.0  44.34\n",
       "3    78.0  44.63\n",
       "4    73.0  40.13\n",
       "..    ...    ...\n",
       "63   38.0  15.49\n",
       "64   33.0  14.96\n",
       "65   28.0  11.98\n",
       "66   23.0  10.32\n",
       "67   18.0   11.2\n",
       "\n",
       "[68 rows x 2 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s[['depth','value']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "d2376d88-f961-463e-8cf8-e725e1c8333a",
   "metadata": {},
   "outputs": [],
   "source": [
    "s2=LayerMeasurements.from_area(shp=gdf.geometry[0], instrument='IS3-SP-11-01F', site_name='Grand Mesa')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "df0b72f6-ac86-4c90-8336-bc53a1ee7e07",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['1S2', '2S7'], dtype=object)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.unique(s2['site_id'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d5efa1be-d2df-42a7-a597-ad256c54fe92",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "7428c040-61f8-4ca5-b61e-c99c2f5b76ac",
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'GeoDataFrame' object has no attribute 'from_filter'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_427/2546819169.py\u001b[0m in \u001b[0;36m?\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ms2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfrom_filter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msite_id\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'2s7'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/srv/conda/envs/notebook/lib/python3.11/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m?\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m   6295\u001b[0m             \u001b[0;32mand\u001b[0m \u001b[0mname\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_accessors\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   6296\u001b[0m             \u001b[0;32mand\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_info_axis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_can_hold_identifiers_and_holds_name\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   6297\u001b[0m         ):\n\u001b[1;32m   6298\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 6299\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mobject\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__getattribute__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m: 'GeoDataFrame' object has no attribute 'from_filter'"
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "6238cb66-71e7-4b80-a366-82abebe2e21d",
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "positional argument follows keyword argument (553227028.py, line 4)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;36m  Cell \u001b[0;32mIn[53], line 4\u001b[0;36m\u001b[0m\n\u001b[0;31m    ds = RasterMeasurements.from_filter(instrument='lidar','2020-02-02')\u001b[0m\n\u001b[0m                                                                       ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m positional argument follows keyword argument\n"
     ]
    }
   ],
   "source": [
    "from snowexsql.api import RasterMeasurements\n",
    "from datetime import datetime \n",
    "from rasterio.plot import show\n",
    "dt = datetime(2020, 2, 4)\n",
    "ds = RasterMeasurements.from_filter(instrument='lidar',date=dt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fcba4fd3-8c50-4d81-a402-e26b09c32874",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.9"
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