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Merge pull request #79 from vincelhx/master
updating documentation
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‎README.rst‎

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Documentation and examples
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--------------------------
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https://cyclobs.ifremer.fr/static/sarwing_datarmor/xsarsea
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https://cerweb.ifremer.fr/datarmor/doc_sphinx/xsarsea/

‎docs/examples/create_hh_lut.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Create HH LUT\n",
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"\n",
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"This notebook will show how we create HH LUTs"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"import xarray as xr\n",
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"\n",
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"# optional debug messages\n",
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"import logging\n",
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"logging.basicConfig()\n",
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"logging.getLogger('xsarsea.windspeed').setLevel(logging.DEBUG) #or .setLevel(logging.INFO)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Definition Zhang & Mouche "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"inc_angle = np.arange(17,50,0.5)\n",
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"ar = [1.3794, -3.19e-2, 1.4e-3]\n",
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"br = [-0.1711, 2.6e-3]\n",
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" \n",
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"\n",
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"def get_pol_ratio_zhangA(inc_angle,wind_speed):\n",
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" # do not force the ratio to be greater than 1\n",
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" ars2 = np.polynomial.polynomial.polyval(inc_angle, ar)\n",
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" brs2 = np.polynomial.polynomial.polyval(inc_angle, br)\n",
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"\n",
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" pol_ratio = ars2 * (wind_speed ** brs2)\n",
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" return pol_ratio\n",
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"\n",
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"def get_pol_ratio_zhangB(inc_angle,wind_speed):\n",
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" # do force the ratio to be greater than 1\n",
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" ars2 = np.polynomial.polynomial.polyval(inc_angle, ar)\n",
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" brs2 = np.polynomial.polynomial.polyval(inc_angle, br)\n",
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"\n",
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" pol_ratio = ars2 * (wind_speed ** brs2)\n",
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" # we force the ratio to be greater than 1\n",
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" pol_ratio = np.where(pol_ratio < 1, 1, pol_ratio)\n",
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" return pol_ratio\n",
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"\n",
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"\n",
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"def get_pol_ratio_mouche(inc_angle, wind_dir, wind_speed=None):\n",
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"\n",
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" theta=inc_angle\n",
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" phi=wind_dir\n",
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" # Alexis Mouche, D. Hauser,\n",
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" # V. Kudryavtsev and JF. Daloze,\n",
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" # \"Multi polarization ocean radar\n",
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" # cross-section from ENVISAT ASAR\n",
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" # observations, airborne polarimetric\n",
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" # radar measurements and empirical or\n",
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" # semi-empirical models\", ESA\n",
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" # ERS/ENVISAT Symposium, Salzburg,\n",
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" # September 2004\n",
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" A0 = 0.00650704\n",
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" B0 = 0.128983\n",
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" C0 = 0.992839\n",
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" Api2 = 0.00782194\n",
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" Bpi2 = 0.121405\n",
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" Cpi2 = 0.992839\n",
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" Api = 0.00598416\n",
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" Bpi = 0.140952\n",
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" Cpi = 0.992885\n",
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"\n",
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" P0_theta = A0*np.exp(B0*theta)+C0\n",
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" Ppi2_theta = Api2*np.exp(Bpi2*theta)+Cpi2\n",
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" Ppi_theta = Api*np.exp(Bpi*theta)+Cpi\n",
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"\n",
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" C0_theta = (P0_theta+Ppi_theta+2*Ppi2_theta)/4\n",
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" C1_theta = (P0_theta-Ppi_theta)/2\n",
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" C2_theta = (P0_theta+Ppi_theta-2*Ppi2_theta)/4\n",
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"\n",
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" polrat = C0_theta + C1_theta*np.cos(np.deg2rad(phi)) + C2_theta*np.cos(2*np.deg2rad(phi))\n",
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"\n",
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" return polrat\n",
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"\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Plot"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"plt.figure(figsize=(10,5))\n",
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"\n",
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"for wspd in [3,7,10,15,20]:\n",
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" plt.plot(inc_angle, 10*np.log10(get_pol_ratio_zhangB(inc_angle,wspd)), label=f'Wspd = {wspd} m/s')\n",
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" \n",
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"plt.legend(loc=\"lower right\")\n",
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"plt.title(f'ZhangB Polarization Ratio vs Incidence Angle')\n",
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"plt.xlabel('Incidence Angle [deg]')\n",
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"plt.ylabel('Polarization Ratio [dB]')\n",
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"plt.xlim([17,50])\n",
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"plt.grid()\n",
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"\n",
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"\n",
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"plt.figure(figsize=(10,5))\n",
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"\n",
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"for phi in [30, 60, 90, 120, 150, 180]:\n",
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" plt.plot(inc_angle, 10*np.log10(get_pol_ratio_mouche(inc_angle,phi)), label=f'Phi = {phi} deg')\n",
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" \n",
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"plt.legend(loc=\"upper left\")\n",
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"plt.title(f'Mouche1 Polarization Ratio vs Incidence Angle')\n",
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"plt.xlabel('Incidence Angle [deg]')\n",
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"plt.ylabel('Polarization Ratio [dB]')\n",
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"plt.xlim([17,50])\n",
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"plt.grid()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## create HH LUT "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"def create_gmfHH(fct, vv_name, pr_name, mod, res):\n",
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" pol_ratio_data = xr.apply_ufunc(\n",
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" fct,\n",
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" mod.incidence, mod.wspd,\n",
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" vectorize=True\n",
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" )\n",
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" pol_ratio_data_extended = pol_ratio_data.expand_dims({'phi': mod.phi}).broadcast_like(mod)\n",
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"\n",
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" mod_hh = (mod/pol_ratio_data_extended)\n",
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" mod_hh.name = 'sigma0_model'\n",
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" mod_hh = mod_hh.to_dataset()\n",
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" mod_hh.attrs['units'] = 'linear'\n",
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" mod_hh.attrs['construction'] = f'{vv_name} / {pr_name}'\n",
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" mod_hh.attrs['description'] = f'Backscatter coefficient in HH polarization build from {vv_name.upper()} model and {pr_name[0].upper() + pr_name[1:]} Polarization Ratio model'\n",
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" mod_hh.attrs['resolution'] = f'{res}'\n",
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" mod_hh.attrs['pol'] = 'HH'\n",
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" \n",
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" \n",
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" if vv_name == \"cmod7\":\n",
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" \n",
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" mod_hh.attrs['inc_range'] = np.array([16.,66.])\n",
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" mod_hh.attrs['wspd_range'] = np.array([0.2,50.])\n",
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" mod_hh.attrs['phi_range'] = np.array([0., 180.])\n",
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" \n",
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" elif vv_name == \"cmod5n\":\n",
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" \n",
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" mod_hh.attrs['inc_range'] = np.array([17.,50.])\n",
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" mod_hh.attrs['wspd_range'] = np.array([0.2, 50.])\n",
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" mod_hh.attrs['phi_range'] = np.array([0., 180.])\n",
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" \n",
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" else : \n",
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" raise ValueError(\"vv_name must be cmod7 or cmod5n\")\n",
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" \n",
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" mod_hh.attrs['model'] = f'{vv_name}_R{res}_hh_{pr_name}'\n",
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"\n",
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"\n",
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" mod_hh.attrs['wspd_step'] = np.round(\n",
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" np.unique(np.diff(mod_hh.wspd)), decimals=2)[0]\n",
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" mod_hh.attrs['inc_step'] = np.round(\n",
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" np.unique(np.diff(mod_hh.incidence)), decimals=2)[0]\n",
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" mod_hh.attrs['phi_step'] = np.round(\n",
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" np.unique(np.diff(mod_hh.phi)), decimals=2)[0]\n",
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" fname = f'./nc_lut_gmf_{vv_name}_R{res}_hh_{pr_name}.nc'\n",
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" mod_hh.to_netcdf(fname, mode=\"w\")\n",
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" print(\"model saved at \", fname)\n",
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" mod_hh.close()\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"vv_name = \"cmod5n\"\n",
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"#create_gmfHH(get_pol_ratio_zhangB, vv_name, \"zhangB\", xsarsea.windspeed.get_model(f\"gmf_{vv_name}\").to_lut(**{'resolution':'high'}), 'high')\n"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.12"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

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