{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "c2603451", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import netCDF4 as nc\n", "import datetime as datetime\n", "from matplotlib import dates\n", "import os" ] }, { "cell_type": "code", "execution_count": 2, "id": "c072e72d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "/Users/cbrun/Documents/PROJETS/GC2014/DATA_GC2015\n" ] } ], "source": [ "from pathlib import Path\n", "print(Path.cwd())\n", "Path = Path.cwd()" ] }, { "cell_type": "code", "execution_count": 3, "id": "d9e130fc", "metadata": { "scrolled": true }, "outputs": [], "source": [ "lDIR='DATA_RAW'\n", "file0='TOA5_TOB1_2095.kacosonic_'\n", "file1=\"csat_2015_04_11_0000\"\n", "file1=\"csat_2015_04_12_0000\"\n", "file1=\"csat_2015_04_13_0000\"\n", "file1=\"csat_2015_04_14_0000\"\n", "file1=\"csat_2015_04_15_0000\"\n", "file1=\"csat_2015_04_16_0000\"\n", "file1=\"csat_2015_04_17_0000\"\n", "file1=\"csat_2015_04_18_0000\"\n", "file1=\"csat_2015_04_19_0000\" # il y a des NAN non traités\n", "file1=\"csat_2015_04_20_0000\"\n", "file1=\"csat_2015_04_21_0000\"\n", "file1=\"csat_2015_04_22_0000\"\n", "file1=\"csat_2015_04_10_0000\"\n", "file1=\"csat_2015_04_10_0942\"\n", "file1=\"csat_2015_04_09_0000\"\n", "file1=\"csat_2015_04_08_0000\"\n", "file_path = file0+file1+\".dat\"\n", "Path=Path/lDIR/file_path" ] }, { "cell_type": "code", "execution_count": 4, "id": "6697798e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " TIMESTAMP RECORD Ux_1 Uy_1 Uz_1 \\\n", "2 2015-04-08 00:00:00.05 81783737 0.36525 0.20125 -0.46075 \n", "3 2015-04-08 00:00:00.1 81783738 0.3765 0.196 -0.47575 \n", "4 2015-04-08 00:00:00.15 81783739 0.3355 0.16775 -0.4895 \n", "5 2015-04-08 00:00:00.2 81783740 0.28575 0.16825 -0.51225 \n", "6 2015-04-08 00:00:00.25 81783741 0.34125 0.12825 -0.56475 \n", "... ... ... ... ... ... \n", "1727997 2015-04-08 23:59:59.8 83511732 0.5945 0.26375 -1.30825 \n", "1727998 2015-04-08 23:59:59.85 83511733 0.75425 0.256 -1.18475 \n", "1727999 2015-04-08 23:59:59.9 83511734 0.54025 0.23725 -1.058 \n", "1728000 2015-04-08 23:59:59.95 83511735 0.5295 0.19875 -1.0685 \n", "1728001 2015-04-09 00:00:00 83511736 0.54275 0.37025 -1.0555 \n", "\n", " T_sonic_1 diag_csat_1 Ux_2 Uy_2 Uz_2 T_sonic_2 \\\n", "2 0.1286926 41 0.082 0.26325 -0.36075 -0.3939209 \n", "3 0.1286926 42 0.23825 0.4375 -0.35375 -0.4120178 \n", "4 0.1236877 43 0.1825 0.28875 -0.38025 -0.3889465 \n", "5 0.07754517 44 0.2805 0.3155 -0.37575 -0.374176 \n", "6 0.1204224 45 0.36175 0.3855 -0.342 -0.3494263 \n", "... ... ... ... ... ... ... \n", "1727997 7.542389 36 0.998 0.023 -0.9715 7.214844 \n", "1727998 7.525635 37 1.04 0.03325 -0.9235001 7.169769 \n", "1727999 7.455475 38 0.7655 0.10575 -0.9495 7.072876 \n", "1728000 7.427063 39 0.72325 0.13625 -0.9480001 7.076233 \n", "1728001 7.462158 40 0.8355001 0.2935 -1.0185 7.081238 \n", "\n", " diag_csat_2 Ux_3 Uy_3 Uz_3 T_sonic_3 \\\n", "2 41 0.3145 0.452 -0.43925 -0.2307739 \n", "3 42 0.3105 0.6035 -0.4735 -0.2225342 \n", "4 43 0.31675 0.5732501 -0.4485 -0.2093506 \n", "5 44 0.3825 0.501 -0.3755 -0.2077026 \n", "6 45 0.406 0.4285 -0.36525 -0.2192078 \n", "... ... ... ... ... ... \n", "1727997 36 0.9867501 -0.01675 -0.9137501 7.664429 \n", "1727998 37 1.01175 -0.0385 -0.9365001 7.589172 \n", "1727999 38 0.9845001 0.09325001 -0.8700001 7.64267 \n", "1728000 39 0.8925 0.12725 -0.82025 7.517273 \n", "1728001 40 0.62475 0.32825 -0.9755 7.478882 \n", "\n", " diag_csat_3 Vbatt \n", "2 41 12.58 \n", "3 42 12.58 \n", "4 43 12.58 \n", "5 44 12.58 \n", "6 45 12.58 \n", "... ... ... \n", "1727997 36 12.67 \n", "1727998 37 12.67 \n", "1727999 38 12.67 \n", "1728000 39 12.67 \n", "1728001 40 12.66 \n", "\n", "[1728000 rows x 18 columns]\n", "2 2015-04-08 00:00:00.050\n", "3 2015-04-08 00:00:00.100\n", "4 2015-04-08 00:00:00.150\n", "5 2015-04-08 00:00:00.200\n", "6 2015-04-08 00:00:00.250\n", " ... \n", "1727997 2015-04-08 23:59:59.800\n", "1727998 2015-04-08 23:59:59.850\n", "1727999 2015-04-08 23:59:59.900\n", "1728000 2015-04-08 23:59:59.950\n", "1728001 2015-04-09 00:00:00.000\n", "Name: TIMESTAMP, Length: 1728000, dtype: datetime64[ns]\n" ] } ], "source": [ "data_sonic = pd.read_csv(Path, header=1,low_memory=False)[2::]\n", "print(data_sonic)\n", "csat_u1 = data_sonic['Ux_1'].astype(float) \n", "csat_v1 = data_sonic['Uy_1'].astype(float) \n", "csat_w1 = data_sonic['Uz_1'].astype(float) \n", "csat_t1 = data_sonic['T_sonic_1'].astype(float) \n", "csat_u2 = data_sonic['Ux_2'].astype(float) \n", "csat_v2 = data_sonic['Uy_2'].astype(float) \n", "csat_w2 = data_sonic['Uz_2'].astype(float) \n", "csat_t2 = data_sonic['T_sonic_2'].astype(float) \n", "csat_u3 = data_sonic['Ux_3'].astype(float) \n", "csat_v3 = data_sonic['Uy_3'].astype(float) \n", "csat_w3 = data_sonic['Uz_3'].astype(float) \n", "csat_t3 = data_sonic['T_sonic_3'].astype(float) \n", "# files 11-22 avril\n", "#csat_y = data_sonic['YEAR']\n", "#csat_m = data_sonic['MONTH']\n", "#csat_d = data_sonic['DAY']\n", "#csat_h = data_sonic['HOUR']\n", "#csat_mi = data_sonic['MINUTE']\n", "#csat_s = data_sonic['SECOND']\n", "#time= pd.DataFrame({'year': csat_y, 'month': csat_m , \n", "# 'day': csat_d, 'hour': csat_h, \n", "# 'minute': csat_mi, 'second': csat_s} )\n", "#print(time)\n", "#time_sonic = pd.to_datetime(time, unit='s')\n", "##\n", "# files 10 avril\n", "time_sonic = pd.to_datetime(data_sonic['TIMESTAMP'])\n", "N=len(data_sonic)\n", "print(time_sonic)" ] }, { "cell_type": "code", "execution_count": 5, "id": "fe82628a", "metadata": {}, "outputs": [], "source": [ "#rotation du repere CSAT\n", "file_path = file1+\".nc\"\n", "ds = nc.Dataset(file_path, 'w', format='NETCDF4')\n", "\n", "# taille complete 24h\n", "#ds.createDimension('t', 1728000)\n", "# taill plus courte fin de campagne\n", "#ds.createDimension('t', 671249)\n", "ds.createDimension('t', N)\n", "\n", "\n", "ti = ds.createVariable('time', 'f8', ('t'))\n", "u1 = ds.createVariable('u_csat1', 'f8', ('t'))\n", "v1 = ds.createVariable('v_csat1', 'f8', ('t'))\n", "w1 = ds.createVariable('w_csat1', 'f8', ('t'))\n", "temp1 = ds.createVariable('temp_csat1', 'f8', ('t'))\n", "u2 = ds.createVariable('u_csat2', 'f8', ('t'))\n", "v2 = ds.createVariable('v_csat2', 'f8', ('t'))\n", "w2 = ds.createVariable('w_csat2', 'f8', ('t'))\n", "temp2 = ds.createVariable('temp_csat2', 'f8', ('t'))\n", "u3 = ds.createVariable('u_csat3', 'f8', ('t'))\n", "v3 = ds.createVariable('v_csat3', 'f8', ('t'))\n", "w3 = ds.createVariable('w_csat3', 'f8', ('t'))\n", "temp3 = ds.createVariable('temp_csat3', 'f8', ('t'))\n", "\n", "#rotation du repere CSAT x downslope, z normal to the slope, y direct/xz\n", "ti[:] = time_sonic\n", "u1[:] = csat_u1\n", "v1[:] = csat_w1\n", "w1[:] = -csat_v1\n", "#intercalibration CSAT2 /CSAT1 & CSAT3 => +0.5K A. Philibert M2 2015 p31\n", "temp1[:] = csat_t1\n", "u2[:] = csat_u2\n", "v2[:] = csat_w2\n", "w2[:] = -csat_v2\n", "temp2[:] = csat_t2+0.5\n", "u3[:] = csat_u3\n", "v3[:] = csat_w3\n", "w3[:] = -csat_v3\n", "temp3[:] = csat_t3\n", "ds.close()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.9.7" } }, "nbformat": 4, "nbformat_minor": 5 }