From e52df0674a0e674874d8a8fe9f339d91655c032e Mon Sep 17 00:00:00 2001
From: Christian Fournier <Christian.Fournier@inra.fr>
Date: Fri, 22 Nov 2024 20:26:26 +0100
Subject: [PATCH] Fix sky map bug (add area of disv=cretized arc of sphere) Add
 tutorials

---
 example/notebooks/Sky irradiance.ipynb       | 906 +++++++++++++++++++
 example/notebooks/Sky luminance.ipynb        | 490 ++++++++++
 example/notebooks/Sky_models.ipynb           | 753 ---------------
 src/alinea/astk/meteorology/sky_luminance.py |  22 +-
 src/alinea/astk/sky_map.py                   |  21 +-
 5 files changed, 1421 insertions(+), 771 deletions(-)
 create mode 100644 example/notebooks/Sky irradiance.ipynb
 create mode 100644 example/notebooks/Sky luminance.ipynb
 delete mode 100644 example/notebooks/Sky_models.ipynb

diff --git a/example/notebooks/Sky irradiance.ipynb b/example/notebooks/Sky irradiance.ipynb
new file mode 100644
index 0000000..c6472ba
--- /dev/null
+++ b/example/notebooks/Sky irradiance.ipynb	
@@ -0,0 +1,906 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Modelling sun and sky irradiance"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "- This notebook explain how to use astk functions to simulate the natural lighting of a scenesky irradiance for diiferent conditions.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Conventions"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    " - Radiation fluxes are expressed in terms of irradiance of a horizontal unit placed at earth surface(total energetic flux passing through a square meter of ground). \n",
+    " - The standard measurement of radiation at earth surface is the global horizontal irradiance (ghi, W.m-2 i.e. J.m-2.s-1), that captures radiations coming from the sun and from the sky in the shortwave domain (visible light)\n",
+    " - The sun contribution is called direct normal irradiance (dni), whereas sky contribution is called diffuse horizontal irradiance (dhi)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Imports and setup location"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "from alinea.astk.data_access import montpellier_spring_2013\n",
+    "from alinea.astk.meteorology.sky_irradiance import sky_irradiance"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Specify a location on earth:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Montpellier ={\n",
+    "'longitude': 3.87,\n",
+    "'latitude': 43.61,\n",
+    "'altitude': 56,\n",
+    "'timezone': 'Europe/Paris'}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Simulating clear sky conditions"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "      <th>ghi</th>\n",
+       "      <th>dni</th>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
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+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                           sun_azimuth  sun_zenith  sun_elevation         ghi   \n",
+       "2000-06-21 07:00:00+02:00    65.222522   81.781574       8.218426   69.608228  \\\n",
+       "2000-06-21 08:00:00+02:00    74.723897   71.647009      18.352991  241.741681   \n",
+       "2000-06-21 09:00:00+02:00    84.230207   61.003100      28.996900  428.277428   \n",
+       "2000-06-21 10:00:00+02:00    94.525066   50.169169      39.830831  603.268306   \n",
+       "2000-06-21 11:00:00+02:00   106.936113   39.517644      50.482356  751.612236   \n",
+       "2000-06-21 12:00:00+02:00   124.101947   29.712676      60.287324  862.071318   \n",
+       "2000-06-21 13:00:00+02:00   150.974668   22.305842      67.694158  926.637555   \n",
+       "2000-06-21 14:00:00+02:00   189.036867   20.362593      69.637407  940.709766   \n",
+       "2000-06-21 15:00:00+02:00   222.847350   25.217800      64.782200  903.290967   \n",
+       "2000-06-21 16:00:00+02:00   244.565120   34.007293      55.992707  817.036014   \n",
+       "2000-06-21 17:00:00+02:00   259.103202   44.316289      45.683711  688.127892   \n",
+       "2000-06-21 18:00:00+02:00   270.327385   55.107908      34.892092  526.051805   \n",
+       "2000-06-21 19:00:00+02:00   280.142111   65.894619      24.105381  343.602529   \n",
+       "2000-06-21 20:00:00+02:00   289.566812   76.349471      13.650529  158.912224   \n",
+       "2000-06-21 21:00:00+02:00   299.258754   86.099097       3.900903   15.621544   \n",
+       "\n",
+       "                                  dni         dhi         ppfd  \n",
+       "2000-06-21 07:00:00+02:00  133.668645   50.500666   167.643135  \n",
+       "2000-06-21 08:00:00+02:00  432.873390  105.442654   528.836249  \n",
+       "2000-06-21 09:00:00+02:00  708.490643   84.827871   897.324728  \n",
+       "2000-06-21 10:00:00+02:00  781.227518  102.874099  1233.792552  \n",
+       "2000-06-21 11:00:00+02:00  811.181337  125.843702  1515.360865  \n",
+       "2000-06-21 12:00:00+02:00  805.824816  162.194835  1723.771894  \n",
+       "2000-06-21 13:00:00+02:00  815.663749  172.009087  1845.290578  \n",
+       "2000-06-21 14:00:00+02:00  813.385068  178.153651  1871.754717  \n",
+       "2000-06-21 15:00:00+02:00  801.009537  178.621855  1801.370007  \n",
+       "2000-06-21 16:00:00+02:00  809.396716  146.073338  1638.894191  \n",
+       "2000-06-21 17:00:00+02:00  792.097153  121.387018  1395.154930  \n",
+       "2000-06-21 18:00:00+02:00  757.091487   92.970738  1086.065369  \n",
+       "2000-06-21 19:00:00+02:00  611.132818   94.005988   731.774188  \n",
+       "2000-06-21 20:00:00+02:00  318.904517   83.651016   359.130268  \n",
+       "2000-06-21 21:00:00+02:00    0.000000   15.621544    41.965131  "
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    " sky_irr = sky_irradiance(daydate='2000-06-21', **Montpellier)\n",
+    " sky_irr"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Simulating cloudy conditions"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "      <th>ghi</th>\n",
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+       "      <th>2000-06-21 17:00:00+02:00</th>\n",
+       "      <td>259.103202</td>\n",
+       "      <td>44.316289</td>\n",
+       "      <td>45.683711</td>\n",
+       "      <td>137.625578</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>137.625578</td>\n",
+       "      <td>321.337452</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2000-06-21 18:00:00+02:00</th>\n",
+       "      <td>270.327385</td>\n",
+       "      <td>55.107908</td>\n",
+       "      <td>34.892092</td>\n",
+       "      <td>105.210361</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>105.210361</td>\n",
+       "      <td>249.555017</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2000-06-21 19:00:00+02:00</th>\n",
+       "      <td>280.142111</td>\n",
+       "      <td>65.894619</td>\n",
+       "      <td>24.105381</td>\n",
+       "      <td>68.720506</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>68.720506</td>\n",
+       "      <td>167.479703</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2000-06-21 20:00:00+02:00</th>\n",
+       "      <td>289.566812</td>\n",
+       "      <td>76.349471</td>\n",
+       "      <td>13.650529</td>\n",
+       "      <td>31.782445</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>31.782445</td>\n",
+       "      <td>81.596061</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2000-06-21 21:00:00+02:00</th>\n",
+       "      <td>299.258754</td>\n",
+       "      <td>86.099097</td>\n",
+       "      <td>3.900903</td>\n",
+       "      <td>3.124309</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>3.124309</td>\n",
+       "      <td>9.353447</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                           sun_azimuth  sun_zenith  sun_elevation         ghi   \n",
+       "2000-06-21 07:00:00+02:00    65.222522   81.781574       8.218426   13.921646  \\\n",
+       "2000-06-21 08:00:00+02:00    74.723897   71.647009      18.352991   48.348336   \n",
+       "2000-06-21 09:00:00+02:00    84.230207   61.003100      28.996900   85.655486   \n",
+       "2000-06-21 10:00:00+02:00    94.525066   50.169169      39.830831  120.653661   \n",
+       "2000-06-21 11:00:00+02:00   106.936113   39.517644      50.482356  150.322447   \n",
+       "2000-06-21 12:00:00+02:00   124.101947   29.712676      60.287324  172.414264   \n",
+       "2000-06-21 13:00:00+02:00   150.974668   22.305842      67.694158  185.327511   \n",
+       "2000-06-21 14:00:00+02:00   189.036867   20.362593      69.637407  188.141953   \n",
+       "2000-06-21 15:00:00+02:00   222.847350   25.217800      64.782200  180.658193   \n",
+       "2000-06-21 16:00:00+02:00   244.565120   34.007293      55.992707  163.407203   \n",
+       "2000-06-21 17:00:00+02:00   259.103202   44.316289      45.683711  137.625578   \n",
+       "2000-06-21 18:00:00+02:00   270.327385   55.107908      34.892092  105.210361   \n",
+       "2000-06-21 19:00:00+02:00   280.142111   65.894619      24.105381   68.720506   \n",
+       "2000-06-21 20:00:00+02:00   289.566812   76.349471      13.650529   31.782445   \n",
+       "2000-06-21 21:00:00+02:00   299.258754   86.099097       3.900903    3.124309   \n",
+       "\n",
+       "                                dni         dhi        ppfd  \n",
+       "2000-06-21 07:00:00+02:00  0.000000   13.921646   37.808178  \n",
+       "2000-06-21 08:00:00+02:00  0.000000   48.348336  120.629656  \n",
+       "2000-06-21 09:00:00+02:00  0.000000   85.655486  205.795668  \n",
+       "2000-06-21 10:00:00+02:00  0.000000  120.653661  283.847764  \n",
+       "2000-06-21 11:00:00+02:00  0.105614  150.240974  349.281690  \n",
+       "2000-06-21 12:00:00+02:00  0.618064  171.877462  397.754979  \n",
+       "2000-06-21 13:00:00+02:00  2.164173  183.325281  426.028282  \n",
+       "2000-06-21 14:00:00+02:00  2.292383  185.992823  432.186277  \n",
+       "2000-06-21 15:00:00+02:00  0.783678  179.949204  415.808807  \n",
+       "2000-06-21 16:00:00+02:00  0.422203  163.057211  378.010644  \n",
+       "2000-06-21 17:00:00+02:00  0.000000  137.625578  321.337452  \n",
+       "2000-06-21 18:00:00+02:00  0.000000  105.210361  249.555017  \n",
+       "2000-06-21 19:00:00+02:00  0.000000   68.720506  167.479703  \n",
+       "2000-06-21 20:00:00+02:00  0.000000   31.782445   81.596061  \n",
+       "2000-06-21 21:00:00+02:00  0.000000    3.124309    9.353447  "
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    " sky_irr = sky_irradiance(daydate='2000-06-21', attenuation=0.2,**Montpellier)\n",
+    " sky_irr"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Simulating actual irradiances"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In general, meteorological conditions are between overcast and clear sky conditions. The cursor between theses two extremes is a function of the ratio between actual irradiance (measured) and clear sky irradiance. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "get some meteorological data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "meteo_db = montpellier_spring_2013()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2013-05-26 00:00:00+02:00      0.000000\n",
+       "2013-05-26 01:00:00+02:00      0.000000\n",
+       "2013-05-26 02:00:00+02:00      0.000000\n",
+       "2013-05-26 03:00:00+02:00      0.000000\n",
+       "2013-05-26 04:00:00+02:00      0.000000\n",
+       "2013-05-26 05:00:00+02:00      0.000000\n",
+       "2013-05-26 06:00:00+02:00     31.615385\n",
+       "2013-05-26 07:00:00+02:00    166.370370\n",
+       "2013-05-26 08:00:00+02:00    335.425926\n",
+       "2013-05-26 09:00:00+02:00    505.481481\n",
+       "2013-05-26 10:00:00+02:00    660.689655\n",
+       "2013-05-26 11:00:00+02:00    783.516667\n",
+       "2013-05-26 12:00:00+02:00    865.300000\n",
+       "2013-05-26 13:00:00+02:00    887.883333\n",
+       "2013-05-26 14:00:00+02:00    843.233333\n",
+       "2013-05-26 15:00:00+02:00    861.366667\n",
+       "2013-05-26 16:00:00+02:00    700.766667\n",
+       "2013-05-26 17:00:00+02:00    576.966667\n",
+       "2013-05-26 18:00:00+02:00    415.766667\n",
+       "2013-05-26 19:00:00+02:00    241.550000\n",
+       "2013-05-26 20:00:00+02:00     68.566667\n",
+       "2013-05-26 21:00:00+02:00      1.433333\n",
+       "2013-05-26 22:00:00+02:00      0.000000\n",
+       "2013-05-26 23:00:00+02:00      0.000000\n",
+       "2013-05-27 00:00:00+02:00      0.000000\n",
+       "Name: ghi, dtype: float64"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas\n",
+    "when = pandas.date_range(start='2013-05-26', freq='H', periods=25,\n",
+    "                             tz='Europe/Paris')\n",
+    "observed = meteo_db.loc[when,'ghi']\n",
+    "observed"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "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>sun_azimuth</th>\n",
+       "      <th>sun_zenith</th>\n",
+       "      <th>sun_elevation</th>\n",
+       "      <th>ghi</th>\n",
+       "      <th>dni</th>\n",
+       "      <th>dhi</th>\n",
+       "      <th>ppfd</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2013-05-26 07:00:00+02:00</th>\n",
+       "      <td>67.394678</td>\n",
+       "      <td>82.902288</td>\n",
+       "      <td>7.097712</td>\n",
+       "      <td>166.370370</td>\n",
+       "      <td>382.539320</td>\n",
+       "      <td>119.103104</td>\n",
+       "      <td>372.883646</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2013-05-26 08:00:00+02:00</th>\n",
+       "      <td>76.998278</td>\n",
+       "      <td>72.595513</td>\n",
+       "      <td>17.404487</td>\n",
+       "      <td>335.425926</td>\n",
+       "      <td>708.145583</td>\n",
+       "      <td>123.608595</td>\n",
+       "      <td>712.692855</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2013-05-26 09:00:00+02:00</th>\n",
+       "      <td>86.670875</td>\n",
+       "      <td>61.831377</td>\n",
+       "      <td>28.168623</td>\n",
+       "      <td>505.481481</td>\n",
+       "      <td>756.869728</td>\n",
+       "      <td>148.187460</td>\n",
+       "      <td>1043.076789</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2013-05-26 10:00:00+02:00</th>\n",
+       "      <td>97.240796</td>\n",
+       "      <td>50.953097</td>\n",
+       "      <td>39.046903</td>\n",
+       "      <td>660.689655</td>\n",
+       "      <td>850.791955</td>\n",
+       "      <td>124.727856</td>\n",
+       "      <td>1339.890179</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2013-05-26 11:00:00+02:00</th>\n",
+       "      <td>110.082221</td>\n",
+       "      <td>40.367996</td>\n",
+       "      <td>49.632004</td>\n",
+       "      <td>783.516667</td>\n",
+       "      <td>882.613527</td>\n",
+       "      <td>111.053233</td>\n",
+       "      <td>1573.703322</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2013-05-26 12:00:00+02:00</th>\n",
+       "      <td>127.790259</td>\n",
+       "      <td>30.809505</td>\n",
+       "      <td>59.190495</td>\n",
+       "      <td>865.300000</td>\n",
+       "      <td>820.208961</td>\n",
+       "      <td>160.843080</td>\n",
+       "      <td>1729.864628</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2013-05-26 13:00:00+02:00</th>\n",
+       "      <td>154.619856</td>\n",
+       "      <td>23.898554</td>\n",
+       "      <td>66.101446</td>\n",
+       "      <td>887.883333</td>\n",
+       "      <td>676.893420</td>\n",
+       "      <td>269.023929</td>\n",
+       "      <td>1775.511620</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2013-05-26 14:00:00+02:00</th>\n",
+       "      <td>190.458560</td>\n",
+       "      <td>22.437564</td>\n",
+       "      <td>67.562436</td>\n",
+       "      <td>843.233333</td>\n",
+       "      <td>578.462848</td>\n",
+       "      <td>308.562438</td>\n",
+       "      <td>1695.371933</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2013-05-26 15:00:00+02:00</th>\n",
+       "      <td>222.025552</td>\n",
+       "      <td>27.340165</td>\n",
+       "      <td>62.659835</td>\n",
+       "      <td>861.366667</td>\n",
+       "      <td>669.045851</td>\n",
+       "      <td>267.056253</td>\n",
+       "      <td>1725.259707</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2013-05-26 16:00:00+02:00</th>\n",
+       "      <td>243.129279</td>\n",
+       "      <td>36.027976</td>\n",
+       "      <td>53.972024</td>\n",
+       "      <td>700.766667</td>\n",
+       "      <td>530.630224</td>\n",
+       "      <td>271.630139</td>\n",
+       "      <td>1425.687318</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2013-05-26 17:00:00+02:00</th>\n",
+       "      <td>257.658296</td>\n",
+       "      <td>46.287318</td>\n",
+       "      <td>43.712682</td>\n",
+       "      <td>576.966667</td>\n",
+       "      <td>510.687303</td>\n",
+       "      <td>224.060075</td>\n",
+       "      <td>1188.519867</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2013-05-26 18:00:00+02:00</th>\n",
+       "      <td>268.996379</td>\n",
+       "      <td>57.092156</td>\n",
+       "      <td>32.907844</td>\n",
+       "      <td>415.766667</td>\n",
+       "      <td>402.926728</td>\n",
+       "      <td>196.860848</td>\n",
+       "      <td>876.394984</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2013-05-26 19:00:00+02:00</th>\n",
+       "      <td>278.938942</td>\n",
+       "      <td>67.937211</td>\n",
+       "      <td>22.062789</td>\n",
+       "      <td>241.550000</td>\n",
+       "      <td>248.774528</td>\n",
+       "      <td>148.104704</td>\n",
+       "      <td>530.208075</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2013-05-26 20:00:00+02:00</th>\n",
+       "      <td>288.494733</td>\n",
+       "      <td>78.476514</td>\n",
+       "      <td>11.523486</td>\n",
+       "      <td>68.566667</td>\n",
+       "      <td>6.658009</td>\n",
+       "      <td>67.236599</td>\n",
+       "      <td>165.803474</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2013-05-26 21:00:00+02:00</th>\n",
+       "      <td>298.338059</td>\n",
+       "      <td>88.229752</td>\n",
+       "      <td>1.770248</td>\n",
+       "      <td>1.433333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.433333</td>\n",
+       "      <td>4.500906</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                           sun_azimuth  sun_zenith  sun_elevation         ghi   \n",
+       "2013-05-26 07:00:00+02:00    67.394678   82.902288       7.097712  166.370370  \\\n",
+       "2013-05-26 08:00:00+02:00    76.998278   72.595513      17.404487  335.425926   \n",
+       "2013-05-26 09:00:00+02:00    86.670875   61.831377      28.168623  505.481481   \n",
+       "2013-05-26 10:00:00+02:00    97.240796   50.953097      39.046903  660.689655   \n",
+       "2013-05-26 11:00:00+02:00   110.082221   40.367996      49.632004  783.516667   \n",
+       "2013-05-26 12:00:00+02:00   127.790259   30.809505      59.190495  865.300000   \n",
+       "2013-05-26 13:00:00+02:00   154.619856   23.898554      66.101446  887.883333   \n",
+       "2013-05-26 14:00:00+02:00   190.458560   22.437564      67.562436  843.233333   \n",
+       "2013-05-26 15:00:00+02:00   222.025552   27.340165      62.659835  861.366667   \n",
+       "2013-05-26 16:00:00+02:00   243.129279   36.027976      53.972024  700.766667   \n",
+       "2013-05-26 17:00:00+02:00   257.658296   46.287318      43.712682  576.966667   \n",
+       "2013-05-26 18:00:00+02:00   268.996379   57.092156      32.907844  415.766667   \n",
+       "2013-05-26 19:00:00+02:00   278.938942   67.937211      22.062789  241.550000   \n",
+       "2013-05-26 20:00:00+02:00   288.494733   78.476514      11.523486   68.566667   \n",
+       "2013-05-26 21:00:00+02:00   298.338059   88.229752       1.770248    1.433333   \n",
+       "\n",
+       "                                  dni         dhi         ppfd  \n",
+       "2013-05-26 07:00:00+02:00  382.539320  119.103104   372.883646  \n",
+       "2013-05-26 08:00:00+02:00  708.145583  123.608595   712.692855  \n",
+       "2013-05-26 09:00:00+02:00  756.869728  148.187460  1043.076789  \n",
+       "2013-05-26 10:00:00+02:00  850.791955  124.727856  1339.890179  \n",
+       "2013-05-26 11:00:00+02:00  882.613527  111.053233  1573.703322  \n",
+       "2013-05-26 12:00:00+02:00  820.208961  160.843080  1729.864628  \n",
+       "2013-05-26 13:00:00+02:00  676.893420  269.023929  1775.511620  \n",
+       "2013-05-26 14:00:00+02:00  578.462848  308.562438  1695.371933  \n",
+       "2013-05-26 15:00:00+02:00  669.045851  267.056253  1725.259707  \n",
+       "2013-05-26 16:00:00+02:00  530.630224  271.630139  1425.687318  \n",
+       "2013-05-26 17:00:00+02:00  510.687303  224.060075  1188.519867  \n",
+       "2013-05-26 18:00:00+02:00  402.926728  196.860848   876.394984  \n",
+       "2013-05-26 19:00:00+02:00  248.774528  148.104704   530.208075  \n",
+       "2013-05-26 20:00:00+02:00    6.658009   67.236599   165.803474  \n",
+       "2013-05-26 21:00:00+02:00    0.000000    1.433333     4.500906  "
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sky_irr = sky_irradiance(dates=observed.index, ghi=observed)\n",
+    "sky_irr"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "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": "3.8.15"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/example/notebooks/Sky luminance.ipynb b/example/notebooks/Sky luminance.ipynb
new file mode 100644
index 0000000..7892bd3
--- /dev/null
+++ b/example/notebooks/Sky luminance.ipynb	
@@ -0,0 +1,490 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "37969f3a",
+   "metadata": {},
+   "source": [
+    "# Modelling sky luminance"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bc1597b3",
+   "metadata": {},
+   "source": [
+    "In this tutorial, we will show how astk can be used to model sky luminance, that is how to input natural light conditions for simulating light interception"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "7f668bd7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from alinea.astk.sky_map import sky_grid, show_sky, sky_turtle, sky_map, sky_dirs\n",
+    "from alinea.astk.meteorology.sky_luminance import sky_luminance\n",
+    "from alinea.astk.meteorology.sky_irradiance import sky_irradiance"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "34b9cff9",
+   "metadata": {},
+   "source": [
+    "## Estimate sky irradiance"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c4d08f01",
+   "metadata": {},
+   "source": [
+    "By default , astk simulate one day long clear sky irradiance at Montpellier, the 21 of June 2000.\n",
+    "For computing sky irradiance at your location or for longer/shorter perido of time, see 'Modeling sky irradiance' companion tutorial"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "9a425195",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>sun_azimuth</th>\n",
+       "      <th>sun_zenith</th>\n",
+       "      <th>sun_elevation</th>\n",
+       "      <th>ghi</th>\n",
+       "      <th>dni</th>\n",
+       "      <th>dhi</th>\n",
+       "      <th>ppfd</th>\n",
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+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2000-06-21 07:00:00+02:00</th>\n",
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+       "      <th>2000-06-21 09:00:00+02:00</th>\n",
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+       "    </tr>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2000-06-21 13:00:00+02:00</th>\n",
+       "      <td>149.893038</td>\n",
+       "      <td>22.213724</td>\n",
+       "      <td>67.786276</td>\n",
+       "      <td>918.828032</td>\n",
+       "      <td>787.889552</td>\n",
+       "      <td>189.415600</td>\n",
+       "      <td>1831.279539</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2000-06-21 14:00:00+02:00</th>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2000-06-21 15:00:00+02:00</th>\n",
+       "      <td>222.570039</td>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2000-06-21 16:00:00+02:00</th>\n",
+       "      <td>244.497975</td>\n",
+       "      <td>33.670653</td>\n",
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+       "      <td>1630.727935</td>\n",
+       "    </tr>\n",
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+       "      <th>2000-06-21 17:00:00+02:00</th>\n",
+       "      <td>259.065446</td>\n",
+       "      <td>44.019757</td>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2000-06-21 18:00:00+02:00</th>\n",
+       "      <td>270.262468</td>\n",
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+       "      <td>110.736258</td>\n",
+       "      <td>1079.269004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2000-06-21 19:00:00+02:00</th>\n",
+       "      <td>280.031698</td>\n",
+       "      <td>65.688728</td>\n",
+       "      <td>24.311272</td>\n",
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+       "      <td>103.127220</td>\n",
+       "      <td>725.138994</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2000-06-21 20:00:00+02:00</th>\n",
+       "      <td>289.403843</td>\n",
+       "      <td>76.194198</td>\n",
+       "      <td>13.805802</td>\n",
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+       "      <td>353.173644</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2000-06-21 21:00:00+02:00</th>\n",
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+       "      <td>3.997439</td>\n",
+       "      <td>14.846194</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>14.846194</td>\n",
+       "      <td>40.029084</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                           sun_azimuth  sun_zenith  sun_elevation         ghi   \n",
+       "2000-06-21 07:00:00+02:00    64.964943   82.113168       7.886832   60.946465  \\\n",
+       "2000-06-21 08:00:00+02:00    74.426178   71.957421      18.042579  229.864545   \n",
+       "2000-06-21 09:00:00+02:00    83.866975   61.281260      28.718740  416.105120   \n",
+       "2000-06-21 10:00:00+02:00    94.061489   50.403526      39.596474  591.750512   \n",
+       "2000-06-21 11:00:00+02:00   106.318067   39.689358      50.310642  741.184658   \n",
+       "2000-06-21 12:00:00+02:00   123.250892   29.785355      60.214645  852.932174   \n",
+       "2000-06-21 13:00:00+02:00   149.893038   22.213724      67.786276  918.828032   \n",
+       "2000-06-21 14:00:00+02:00   188.216321   20.077412      69.922588  934.150316   \n",
+       "2000-06-21 15:00:00+02:00   222.570039   24.861968      65.138032  897.808460   \n",
+       "2000-06-21 16:00:00+02:00   244.497975   33.670653      56.329347  812.392859   \n",
+       "2000-06-21 17:00:00+02:00   259.065446   44.019757      45.980243  684.060062   \n",
+       "2000-06-21 18:00:00+02:00   270.262468   54.855468      35.144532  522.326049   \n",
+       "2000-06-21 19:00:00+02:00   280.031698   65.688728      24.311272  340.124868   \n",
+       "2000-06-21 20:00:00+02:00   289.403843   76.194198      13.805802  156.015935   \n",
+       "2000-06-21 21:00:00+02:00   299.040349   86.002561       3.997439   14.846194   \n",
+       "\n",
+       "                                  dni         dhi         ppfd  \n",
+       "2000-06-21 07:00:00+02:00   92.041199   48.316857   148.294639  \n",
+       "2000-06-21 08:00:00+02:00  453.118711   89.522953   504.948469  \n",
+       "2000-06-21 09:00:00+02:00  671.771159   93.312118   873.937767  \n",
+       "2000-06-21 10:00:00+02:00  751.066148  113.038550  1212.231017  \n",
+       "2000-06-21 11:00:00+02:00  782.891568  138.735360  1496.174934  \n",
+       "2000-06-21 12:00:00+02:00  778.469936  177.303988  1707.180678  \n",
+       "2000-06-21 13:00:00+02:00  787.889552  189.415600  1831.279539  \n",
+       "2000-06-21 14:00:00+02:00  785.467446  196.415993  1860.110781  \n",
+       "2000-06-21 15:00:00+02:00  790.895864  180.210219  1791.714236  \n",
+       "2000-06-21 16:00:00+02:00  781.474663  162.019789  1630.727935  \n",
+       "2000-06-21 17:00:00+02:00  764.123266  134.578851  1387.926414  \n",
+       "2000-06-21 18:00:00+02:00  715.011297  110.736258  1079.269004  \n",
+       "2000-06-21 19:00:00+02:00  575.665050  103.127220   725.138994  \n",
+       "2000-06-21 20:00:00+02:00  290.498008   86.693873   353.173644  \n",
+       "2000-06-21 21:00:00+02:00    0.000000   14.846194    40.029084  "
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sky_irr = sky_irradiance()\n",
+    "sky_irr"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "49de7ca9",
+   "metadata": {},
+   "source": [
+    "## Estimate sky luminance"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3679a767",
+   "metadata": {},
+   "source": [
+    "* Sky luminance is estimated from sky irradiances, using Perez all weather sky model (R. Perez, R. Seals, J. Michalsky, \"All-weather model for sky luminance distribution—Preliminary configuration and validation\", Solar Energy, Volume 50, Issue 3, 1993, Pages 235-245)\n",
+    "* Luminance is computed every steradian of the sky hemisphere\n",
+    "* For other strategies, see 'sky_luminance modeling strategies' companion tutorial"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "3de60ff5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "grid=sky_grid()\n",
+    "lum=sky_luminance(grid, 'all_weather', sky_irr)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "cd773db5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "show_sky(grid, lum)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "56e4e68f",
+   "metadata": {},
+   "source": [
+    "## Define sky discretisation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d7b9eba6",
+   "metadata": {},
+   "source": [
+    "Sky discretisation allow to split the sky in a limited number of direction for efficiency of light modelling.\n",
+    "You can use football like dicretisation (sky_turtle) or a latitude/longitude regular grid (sky_dirs)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "b4107571",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sectors = sky_turtle(16)\n",
+    "# sectors=sky_dirs(30,30)\n",
+    "skylights, skymap = sky_map(grid, lum, sectors)\n",
+    "show_sky(grid,skymap)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "53f412cd",
+   "metadata": {},
+   "source": [
+    "## Estimate normalised ligth sources and light energy"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a74c987b",
+   "metadata": {},
+   "source": [
+    "light sources are given as elevation, azimuth, irradiance tuples, normalised by global horizontal irradiance over the considered period"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "d06710fc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[(90.0, 0.0, 0.055656409336818494),\n",
+       " (89.0, 1.0, 0.0492460598900486),\n",
+       " (88.0, 2.0, 0.09029268282616403),\n",
+       " (87.0, 3.0, 0.07103702590687165),\n",
+       " (86.0, 4.0, 0.07109031672143143),\n",
+       " (85.0, 5.0, 0.08932458026884416),\n",
+       " (84.0, 6.0, 0.036699781202782965),\n",
+       " (83.0, 7.0, 0.07666293096915303),\n",
+       " (82.0, 8.0, 0.06638709997775812),\n",
+       " (81.0, 9.0, 0.07671032976934453),\n",
+       " (80.0, 10.0, 0.036779034802281174),\n",
+       " (79.0, 11.0, 0.047864811098967695),\n",
+       " (78.0, 12.0, 0.06805303708057643),\n",
+       " (77.0, 13.0, 0.04896869574239473),\n",
+       " (76.0, 14.0, 0.06771838256788859),\n",
+       " (75.0, 15.0, 0.04750882183867402)]"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "azimuth, zenith,_,_,_=grid\n",
+    "sky_sources = 90 - zenith, azimuth, skylights\n",
+    "list(zip(*sky_sources))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "486601e8",
+   "metadata": {},
+   "source": [
+    "* Ligth energy can be computed to unscale the values by averaging over sky irradiances for irradiance estimates, or by summing I*dt for total energy estimate\n",
+    "* The following line compute mean pppfd (micromolPAR.m-2.s-1), and total energy over that day (MJ.m-2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "89abef2b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1109.4758088961805, 294.2401049406819)"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sky_irr.ppfd.mean(), sky_irr.ghi.sum() * 3600 / 1e5"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "40d9d31d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "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": "3.8.15"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/example/notebooks/Sky_models.ipynb b/example/notebooks/Sky_models.ipynb
deleted file mode 100644
index 181c04c..0000000
--- a/example/notebooks/Sky_models.ipynb
+++ /dev/null
@@ -1,753 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Modelling sun and sky light sources"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "- This notebook explain how to use astk functions to simulate the natural lighting of a scene.\n",
-    "- This consist of defining a finite set of direction (i.ie. a set of elevation, azimuth) + a set irradiances representing the sky and the sun for a given period.\n",
-    "- It is generally easier to compute the relative irradiance of sources (so that their sum equal 1), and to multiply by mean irradiance or total amount of light depending on the application. This approach is the one demonstrated here."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Conventions"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    " - Radiation fluxes are expressed in terms of irradiance of a horizontal unit placed at earth surface(total energetic flux passing through a square meter of ground). \n",
-    " - The standard measurement of radiation at earth surface is the global horizontal irradiance (ghi, W.m-2 i.e. J.m-2.s-1), that captures radiations coming from the sun and from the sky in the shortwave domain (visible light)\n",
-    " - The sun contribution is called direct normal irradiance (dni), whereas sky contribution is called diffuse horizontal irradiance (dhi)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Imports and setup location"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [],
-   "source": [
-    "%gui qt\n",
-    "import alinea.astk\n",
-    "from alinea.astk.data_access import montpellier_spring_2013\n",
-    "from alinea.astk.meteorology.sky_irradiance import sky_irradiances\n",
-    "from alinea.astk.sun_and_sky import sky_sources, sun_sky_sources"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Specify a location on earth:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "Montpellier ={\n",
-    "'longitude': 3.87,\n",
-    "'latitude': 43.61,\n",
-    "'altitude': 56,\n",
-    "'timezone': 'Europe/Paris'}"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "{'longitude': 3.87,\n",
-       " 'latitude': 43.61,\n",
-       " 'altitude': 56,\n",
-       " 'timezone': 'Europe/Paris'}"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "Montpellier"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Simulating difuse light conditions"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "   - When the sky is very cloudy, direct light equals zero, and diffuse light is almost uniform among sky sources as long as cloudy condition last. The absolute value of global horizontal irradiance is varying with time or between two days, but the relative contributions of the different sky sources to ghi does not vary.\n",
-    "   - The positioning and the relative contribution of sky sources to global horizontal irradiance for cloudy conditions can be obtained by the following function that used the 'standard overcast condition' sky luminance model, and make the integration of luminance so that one source capture the portion of sky arround it:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([0.15986923, 0.04397197, 0.04397197, 0.04397197, 0.04397197,\n",
-       "       0.04397197, 0.11305245, 0.11305245, 0.11305245, 0.11305245,\n",
-       "       0.11305245, 0.01100174, 0.01100174, 0.01100174, 0.01100174,\n",
-       "       0.01100174])"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "sky = sky_sources(turtle_sectors=16)\n",
-    "#skys.show_sources(sky)\n",
-    "elevation, azimuth, irradiance = sky\n",
-    "irradiance"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "  - turtle sector indicate the number of sources sampling the sky hemisphere (possible values are 6, 16 and 46)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1.0000000000000002"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "sum(irradiance)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "- Lighting the scene with such light is done like before, yielding the distribution of irradiance within the plant"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#cscene, raw, agg = ltfs.illuminate(lscene, light=sky, scene_unit='cm')\n",
-    "#scene, _ = cscene.plot(raw, maxval=1.01)\n",
-    "#skys.show_sources(sky,scene=scene, distance=15, radius=0.3)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "* Muliplying the results by ghi (instantaneous or averaged over time) yields absolute irradiance values on organs"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(137.94282490295114, 137.18468003683014)"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    " sky_irr = sky_irradiances(daydate='2000-06-21', attenuation=0.25, **Montpellier)\n",
-    "sky_irr.ghi.mean(),sky_irr.dhi.mean()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
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-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
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-       "      <th></th>\n",
-       "      <th>azimuth</th>\n",
-       "      <th>zenith</th>\n",
-       "      <th>elevation</th>\n",
-       "      <th>clearness</th>\n",
-       "      <th>brightness</th>\n",
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-       "      <th>2000-06-21 07:00:00+02:00</th>\n",
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-       "      <th>2000-06-21 08:00:00+02:00</th>\n",
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-       "    <tr>\n",
-       "      <th>2000-06-21 09:00:00+02:00</th>\n",
-       "      <td>84.230207</td>\n",
-       "      <td>61.003100</td>\n",
-       "      <td>28.996900</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.165523</td>\n",
-       "      <td>107.069357</td>\n",
-       "      <td>0.000000</td>\n",
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-       "      <th>2000-06-21 10:00:00+02:00</th>\n",
-       "      <td>94.525066</td>\n",
-       "      <td>50.169169</td>\n",
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-       "      <td>1.000000</td>\n",
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-       "      <td>150.817077</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>150.817077</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2000-06-21 11:00:00+02:00</th>\n",
-       "      <td>106.936113</td>\n",
-       "      <td>39.517644</td>\n",
-       "      <td>50.482356</td>\n",
-       "      <td>1.002645</td>\n",
-       "      <td>0.182443</td>\n",
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-       "    <tr>\n",
-       "      <th>2000-06-21 12:00:00+02:00</th>\n",
-       "      <td>124.101947</td>\n",
-       "      <td>29.712676</td>\n",
-       "      <td>60.287324</td>\n",
-       "      <td>1.004560</td>\n",
-       "      <td>0.185581</td>\n",
-       "      <td>215.517829</td>\n",
-       "      <td>1.120370</td>\n",
-       "      <td>214.544764</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2000-06-21 13:00:00+02:00</th>\n",
-       "      <td>150.974668</td>\n",
-       "      <td>22.305842</td>\n",
-       "      <td>67.694158</td>\n",
-       "      <td>1.013752</td>\n",
-       "      <td>0.185633</td>\n",
-       "      <td>231.659389</td>\n",
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-       "    <tr>\n",
-       "      <th>2000-06-21 14:00:00+02:00</th>\n",
-       "      <td>189.036867</td>\n",
-       "      <td>20.362593</td>\n",
-       "      <td>69.637407</td>\n",
-       "      <td>1.014207</td>\n",
-       "      <td>0.185897</td>\n",
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-       "      <td>3.449277</td>\n",
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-       "    <tr>\n",
-       "      <th>2000-06-21 15:00:00+02:00</th>\n",
-       "      <td>222.847350</td>\n",
-       "      <td>25.217800</td>\n",
-       "      <td>64.782200</td>\n",
-       "      <td>1.005178</td>\n",
-       "      <td>0.186591</td>\n",
-       "      <td>225.822742</td>\n",
-       "      <td>1.266676</td>\n",
-       "      <td>224.676786</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2000-06-21 16:00:00+02:00</th>\n",
-       "      <td>244.565120</td>\n",
-       "      <td>34.007293</td>\n",
-       "      <td>55.992707</td>\n",
-       "      <td>1.003821</td>\n",
-       "      <td>0.184385</td>\n",
-       "      <td>204.259004</td>\n",
-       "      <td>0.946751</td>\n",
-       "      <td>203.474179</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2000-06-21 17:00:00+02:00</th>\n",
-       "      <td>259.103202</td>\n",
-       "      <td>44.316289</td>\n",
-       "      <td>45.683711</td>\n",
-       "      <td>1.009050</td>\n",
-       "      <td>0.178828</td>\n",
-       "      <td>172.031973</td>\n",
-       "      <td>2.285008</td>\n",
-       "      <td>170.397063</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2000-06-21 18:00:00+02:00</th>\n",
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-       "      <td>55.107908</td>\n",
-       "      <td>34.892092</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.172476</td>\n",
-       "      <td>131.512951</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>131.512951</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2000-06-21 19:00:00+02:00</th>\n",
-       "      <td>280.142111</td>\n",
-       "      <td>65.894619</td>\n",
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-       "      <td>0.000000</td>\n",
-       "      <td>85.900632</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2000-06-21 20:00:00+02:00</th>\n",
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-       "      <td>76.349471</td>\n",
-       "      <td>13.650529</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.124519</td>\n",
-       "      <td>39.728056</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>39.728056</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2000-06-21 21:00:00+02:00</th>\n",
-       "      <td>299.258754</td>\n",
-       "      <td>86.099097</td>\n",
-       "      <td>3.900903</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.036813</td>\n",
-       "      <td>3.905386</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>3.905386</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                              azimuth     zenith  elevation  clearness   \n",
-       "2000-06-21 07:00:00+02:00   65.222522  81.781574   8.218426   1.000000  \\\n",
-       "2000-06-21 08:00:00+02:00   74.723897  71.647009  18.352991   1.000000   \n",
-       "2000-06-21 09:00:00+02:00   84.230207  61.003100  28.996900   1.000000   \n",
-       "2000-06-21 10:00:00+02:00   94.525066  50.169169  39.830831   1.000000   \n",
-       "2000-06-21 11:00:00+02:00  106.936113  39.517644  50.482356   1.002645   \n",
-       "2000-06-21 12:00:00+02:00  124.101947  29.712676  60.287324   1.004560   \n",
-       "2000-06-21 13:00:00+02:00  150.974668  22.305842  67.694158   1.013752   \n",
-       "2000-06-21 14:00:00+02:00  189.036867  20.362593  69.637407   1.014207   \n",
-       "2000-06-21 15:00:00+02:00  222.847350  25.217800  64.782200   1.005178   \n",
-       "2000-06-21 16:00:00+02:00  244.565120  34.007293  55.992707   1.003821   \n",
-       "2000-06-21 17:00:00+02:00  259.103202  44.316289  45.683711   1.009050   \n",
-       "2000-06-21 18:00:00+02:00  270.327385  55.107908  34.892092   1.000000   \n",
-       "2000-06-21 19:00:00+02:00  280.142111  65.894619  24.105381   1.000000   \n",
-       "2000-06-21 20:00:00+02:00  289.566812  76.349471  13.650529   1.000000   \n",
-       "2000-06-21 21:00:00+02:00  299.258754  86.099097   3.900903   1.000000   \n",
-       "\n",
-       "                           brightness         ghi       dni         dhi  \n",
-       "2000-06-21 07:00:00+02:00    0.087529   17.402057  0.000000   17.402057  \n",
-       "2000-06-21 08:00:00+02:00    0.143055   60.435420  0.000000   60.435420  \n",
-       "2000-06-21 09:00:00+02:00    0.165523  107.069357  0.000000  107.069357  \n",
-       "2000-06-21 10:00:00+02:00    0.176735  150.817077  0.000000  150.817077  \n",
-       "2000-06-21 11:00:00+02:00    0.182443  187.903059  0.664856  187.390170  \n",
-       "2000-06-21 12:00:00+02:00    0.185581  215.517829  1.120370  214.544764  \n",
-       "2000-06-21 13:00:00+02:00    0.185633  231.659389  3.336463  228.572590  \n",
-       "2000-06-21 14:00:00+02:00    0.185897  235.177442  3.449277  231.943712  \n",
-       "2000-06-21 15:00:00+02:00    0.186591  225.822742  1.266676  224.676786  \n",
-       "2000-06-21 16:00:00+02:00    0.184385  204.259004  0.946751  203.474179  \n",
-       "2000-06-21 17:00:00+02:00    0.178828  172.031973  2.285008  170.397063  \n",
-       "2000-06-21 18:00:00+02:00    0.172476  131.512951  0.000000  131.512951  \n",
-       "2000-06-21 19:00:00+02:00    0.157370   85.900632  0.000000   85.900632  \n",
-       "2000-06-21 20:00:00+02:00    0.124519   39.728056  0.000000   39.728056  \n",
-       "2000-06-21 21:00:00+02:00    0.036813    3.905386  0.000000    3.905386  "
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "sky_irr"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Simulating clear sky conditions"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "* On clear days, 80% of the radiation is coming from the sun, that is from the south-oriented hemisphere. Moreover, sun irradiance is also varying as a function of time of the day.\n",
-    "* In such case, it is recomended to add sun sources in addition to sky sources. Generaly one position per hour is added "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "sky_irr, sun, sky = sun_sky_sources(daydate='2000-06-21', **Montpellier) \n",
-    "#sources = skys.add_sources(sun, sky)\n",
-    "\n",
-    "#\n",
-    "#cscene, raw, agg = ltfs.illuminate(lscene, light=sources, scene_unit='cm', north=180)\n",
-    "#scene, _ = cscene.plot(raw)\n",
-    "#skys.show_sources(sources,scene=scene, distance=15, radius=0.3, north=180)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "- north is the angle (deg, positive clockwise) from X+ to North. It should be pass both to illuminate AND show_source function"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Simulating actual irradiances"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In general, meteorological conditions are between overcast and clear sky conditions. The cursor between theses two extremes is a function of the ratio between actual irradiance (measured) and clear sky irradiance. "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "get some meteorological data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [],
-   "source": [
-    "meteo_data = montpellier_spring_2013()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
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-       "\n",
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-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>ghi</th>\n",
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-       "      <th>Unnamed: 0</th>\n",
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-       "      <th>2013-05-21 00:00:00+02:00</th>\n",
-       "      <td>0.000000</td>\n",
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-       "      <th>2013-05-21 01:00:00+02:00</th>\n",
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-       "      <th>2013-05-21 02:00:00+02:00</th>\n",
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-       "      <th>2013-05-21 03:00:00+02:00</th>\n",
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-       "      <th>2013-05-21 04:00:00+02:00</th>\n",
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-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
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-       "    <tr>\n",
-       "      <th>2013-07-04 19:00:00+02:00</th>\n",
-       "      <td>270.550000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2013-07-04 20:00:00+02:00</th>\n",
-       "      <td>103.850000</td>\n",
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-       "    <tr>\n",
-       "      <th>2013-07-04 21:00:00+02:00</th>\n",
-       "      <td>6.016667</td>\n",
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-       "    <tr>\n",
-       "      <th>2013-07-04 22:00:00+02:00</th>\n",
-       "      <td>0.000000</td>\n",
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-       "    <tr>\n",
-       "      <th>2013-07-04 23:00:00+02:00</th>\n",
-       "      <td>0.000000</td>\n",
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-       "  </tbody>\n",
-       "</table>\n",
-       "<p>1080 rows × 1 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                                  ghi\n",
-       "Unnamed: 0                           \n",
-       "2013-05-21 00:00:00+02:00    0.000000\n",
-       "2013-05-21 01:00:00+02:00    0.000000\n",
-       "2013-05-21 02:00:00+02:00    0.000000\n",
-       "2013-05-21 03:00:00+02:00    0.000000\n",
-       "2013-05-21 04:00:00+02:00    0.000000\n",
-       "...                               ...\n",
-       "2013-07-04 19:00:00+02:00  270.550000\n",
-       "2013-07-04 20:00:00+02:00  103.850000\n",
-       "2013-07-04 21:00:00+02:00    6.016667\n",
-       "2013-07-04 22:00:00+02:00    0.000000\n",
-       "2013-07-04 23:00:00+02:00    0.000000\n",
-       "\n",
-       "[1080 rows x 1 columns]"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "meteo_data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "2013-05-26 00:00:00+02:00      0.000000\n",
-       "2013-05-26 01:00:00+02:00      0.000000\n",
-       "2013-05-26 02:00:00+02:00      0.000000\n",
-       "2013-05-26 03:00:00+02:00      0.000000\n",
-       "2013-05-26 04:00:00+02:00      0.000000\n",
-       "2013-05-26 05:00:00+02:00      0.000000\n",
-       "2013-05-26 06:00:00+02:00     31.615385\n",
-       "2013-05-26 07:00:00+02:00    166.370370\n",
-       "2013-05-26 08:00:00+02:00    335.425926\n",
-       "2013-05-26 09:00:00+02:00    505.481481\n",
-       "2013-05-26 10:00:00+02:00    660.689655\n",
-       "2013-05-26 11:00:00+02:00    783.516667\n",
-       "2013-05-26 12:00:00+02:00    865.300000\n",
-       "2013-05-26 13:00:00+02:00    887.883333\n",
-       "2013-05-26 14:00:00+02:00    843.233333\n",
-       "2013-05-26 15:00:00+02:00    861.366667\n",
-       "2013-05-26 16:00:00+02:00    700.766667\n",
-       "2013-05-26 17:00:00+02:00    576.966667\n",
-       "2013-05-26 18:00:00+02:00    415.766667\n",
-       "2013-05-26 19:00:00+02:00    241.550000\n",
-       "2013-05-26 20:00:00+02:00     68.566667\n",
-       "2013-05-26 21:00:00+02:00      1.433333\n",
-       "2013-05-26 22:00:00+02:00      0.000000\n",
-       "2013-05-26 23:00:00+02:00      0.000000\n",
-       "2013-05-27 00:00:00+02:00      0.000000\n",
-       "Freq: H, Name: ghi, dtype: float64"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "observed = skys.actual_irradiance('2013-05-26', meteo_data)\n",
-    "observed"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<openalea.plantgl.scenegraph._pglsg.Scene at 0x24dd30e90b0>"
-      ]
-     },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "sun, sky = skys.sun_sky_sources(ghi=observed, dates=observed.index, normalisation=1, **Montpellier) \n",
-    "sources = skys.add_sources(sun, sky)\n",
-    "#\n",
-    "cscene, raw, agg = ltfs.illuminate(lscene, light=sources, scene_unit='cm', north=180)\n",
-    "scene, _ = cscene.plot(raw)\n",
-    "skys.show_sources(sources,scene=scene, distance=15, radius=0.3, north=180)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "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": "3.8.15"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 1
-}
diff --git a/src/alinea/astk/meteorology/sky_luminance.py b/src/alinea/astk/meteorology/sky_luminance.py
index acc6300..dbd0e33 100644
--- a/src/alinea/astk/meteorology/sky_luminance.py
+++ b/src/alinea/astk/meteorology/sky_luminance.py
@@ -19,7 +19,7 @@
 
 
 def sky_hi(grid, luminance):
-    _, _, _, sky_zenith = grid
+    _, _, _, sky_zenith, _ = grid
     return horizontal_irradiance(luminance, 90 - sky_zenith).sum()
 
 
@@ -75,7 +75,7 @@ def cie_relative_luminance(sky_zenith=None, grid=None, sun_zenith=None,
         raise ValueError('Either sky_zenith or grid should be passed')
     sky_azimuth = None
     if grid is not None:
-        _, _, _, sky_zenith = grid
+        _, _, _, sky_zenith, _ = grid
     else:
         sky_zenith = numpy.array(sky_zenith)
 
@@ -181,7 +181,7 @@ def _acute(v1, v2):
         angle = numpy.arccos(numpy.clip(x, -1, 1))
         return numpy.degrees(angle)
 
-    _, _, sky_azimuth, sky_zenith = grid
+    _, _, sky_azimuth, sky_zenith, _ = grid
     v_sky = numpy.stack(_cartesian(sky_zenith, sky_azimuth), axis=2)
     v_sun = _cartesian(sun_zenith, sun_azimuth)
 
@@ -205,7 +205,7 @@ def all_weather_relative_luminance(grid, sun_zenith, sun_azimuth, clearness, bri
 
     """
     a, b, c, d, e = all_weather_abcde(sun_zenith, clearness, brightness)
-    _, _, _, sky_zenith = grid
+    _, _, _, sky_zenith, _ = grid
     gradation = cie_luminance_gradation(sky_zenith, a=a, b=b)
     ksi_sun = sun_zenith
     ksi = ksi_grid(grid, sun_zenith, sun_azimuth)
@@ -223,19 +223,19 @@ def sky_luminance(grid, sky_type='soc', sky_irradiance=None):
         astk.sky_irradiance.sky_irradiance. Needed for all sky_types except 'uoc' and 'soc'
     """
 
-    azimuth, zenith, az_c, z_c = grid
+    azimuth, zenith, az_c, z_c, w_c = grid
     lum = numpy.zeros_like(az_c)
     if sky_irradiance is not None:
         irrad = sky_irradiance.copy()
         irrad['dates'] = irrad.index
 
     if sky_type in ('soc', 'uoc'):
-        lum = cie_relative_luminance(grid=grid, type=sky_type)
+        lum = w_c * cie_relative_luminance(grid=grid, type=sky_type)
         lum /= lum.sum()
         return lum
     elif sky_type == 'clear_sky':
         for row in irrad.itertuples():
-            _lum = cie_relative_luminance(grid=grid,
+            _lum = w_c * cie_relative_luminance(grid=grid,
                                           sun_zenith=row.sun_zenith,
                                           sun_azimuth=row.sun_azimuth,
                                           type='clear_sky')
@@ -248,7 +248,7 @@ def sky_luminance(grid, sky_type='soc', sky_irradiance=None):
         for row in irrad.itertuples():
             brightness = all_weather_sky_brightness(row.dates, row.dhi, row.sun_zenith)
             clearness = all_weather_sky_clearness(row.dni, row.dhi, row.sun_zenith)
-            _lum = all_weather_relative_luminance(grid,
+            _lum = w_c * all_weather_relative_luminance(grid,
                                                   sun_zenith=row.sun_zenith,
                                                   sun_azimuth=row.sun_azimuth,
                                                   brightness=brightness,
@@ -259,7 +259,7 @@ def sky_luminance(grid, sky_type='soc', sky_irradiance=None):
         lum /= lum.sum()
         return lum
     elif sky_type == 'sun_soc':
-        lum = cie_relative_luminance(grid=grid, type='soc')
+        lum = w_c * cie_relative_luminance(grid=grid, type='soc')
         # scale to total luminance of sky
         lum /= lum.sum()
         hi = sky_hi(grid, lum)
@@ -271,9 +271,9 @@ def sky_luminance(grid, sky_type='soc', sky_irradiance=None):
         lum /= lum.sum()
         return lum
     elif sky_type == 'blended':
-        soc = cie_relative_luminance(grid=grid, type='soc')
+        soc = w_c * cie_relative_luminance(grid=grid, type='soc')
         for row in irrad.itertuples():
-            cs = cie_relative_luminance(grid=grid,
+            cs = w_c * cie_relative_luminance(grid=grid,
                                           sun_zenith=row.sun_zenith,
                                           sun_azimuth=row.sun_azimuth,
                                           type='clear_sky')
diff --git a/src/alinea/astk/sky_map.py b/src/alinea/astk/sky_map.py
index 623845f..04a0002 100644
--- a/src/alinea/astk/sky_map.py
+++ b/src/alinea/astk/sky_map.py
@@ -33,12 +33,16 @@ def _c(x):
 
     # grid cell centers positioned in a 2D grid matrix
     az_c, z_c = numpy.meshgrid(_c(azimuth), _c(zenith))
-    return azimuth, zenith , az_c, z_c
+    # grid cell relative area on sky hemisphere
+    w_c = numpy.radians(d_az) * (numpy.cos(numpy.radians(z_c - d_z / 2)) - numpy.cos(numpy.radians(z_c + d_z / 2)))
+    return azimuth, zenith , az_c, z_c, w_c
+
 
 def sky_dirs(d_az=10, d_z=10, n_az=None, n_z=None):
-    _,_,az, z = sky_grid(d_az=d_az, d_z=d_z, n_az=n_az, n_z=n_z)
+    _,_,az, z, _ = sky_grid(d_az=d_az, d_z=d_z, n_az=n_az, n_z=n_z)
     return [*zip(90 - z.flatten(), az.flatten())]
 
+
 def sun_path(sky_irradiance):
     irr = sky_irradiance
     return [*zip(irr.sun_elevation, irr.sun_azimuth)]
@@ -56,12 +60,14 @@ def sky_turtle(sectors=46):
     nb_sect = [1, 6, 16, 46][numpy.searchsorted([1, 6, 16, 46], min(46, sectors))]
     return [*zip(elevations_h[:nb_sect], azimuths_h[:nb_sect])]
 
+
 def closest_point(point_grid, point_list):
     dists = [numpy.sum((point_grid - p)**2, axis=2) for p in point_list]
     return numpy.argmin(numpy.stack(dists, axis=2), axis=2)
 
+
 def sky_map(luminance_grid, luminance_map, directions):
-    _, _, az, z = luminance_grid
+    _, _, az, z, _ = luminance_grid
 
     def _polar(az, z):
         theta = numpy.radians(az)
@@ -70,11 +76,12 @@ def _polar(az, z):
     grid_points = numpy.stack(_polar(az, z), axis=2)
     target_points = numpy.array([_polar(a,90- el) for el,a in directions])
     targets = closest_point(grid_points, target_points)
-    lums = numpy.bincount(targets.flatten(), weights=luminance_map.flatten())
+    slum = numpy.bincount(targets.flatten(), weights=luminance_map.flatten())
     smap = numpy.zeros_like(luminance_map)
-    for i, w in enumerate(lums):
+    for i, w in enumerate(slum):
         smap[targets==i] = w
-    return lums, smap
+    return slum, smap
+
 
 def show_sky(grid, sky, cmap='jet', shading='flat'):
     """Display sky luminance polar image
@@ -83,7 +90,7 @@ def show_sky(grid, sky, cmap='jet', shading='flat'):
         grid: a (azimuth, zenith, az_c, z_c) tuple, such as returned by sky_grid
         sky: a 2-D array of values to be plotted on the grid
     """
-    az, z, _, _ = grid
+    az, z, _, _ , _= grid
     theta = numpy.radians(az)
     r = z
     fig, ax = plt.subplots(subplot_kw={'projection': 'polar'})