QuentinRodier · JorisPianezze · Dec 3, 2025 · Dec 3, 2025 · Dec 3, 2025 · Dec 3, 2025
diff --git a/_config.yml b/_config.yml
@@ -0,0 +1,3 @@
+theme: jekyll-theme-cayman
+title: [MNHPy]
+description: [Gallery from MNHPy library.]
diff --git a/_layouts/default.html b/_layouts/default.html
@@ -0,0 +1,42 @@
+<!DOCTYPE html>
+<html lang="{{ site.lang | default: "en-US" }}">
+  <head>
+    <meta charset="UTF-8">
+
+{% seo %}
+    <link rel="preconnect" href="https://fonts.gstatic.com">
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+
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diff --git a/gallery/figures/3D_mayavi.png b/gallery/figures/3D_mayavi.png
diff --git a/gallery/figures/XY_budget_terms.png b/gallery/figures/XY_budget_terms.png
diff --git a/gallery/figures/XY_lines_001_2Drelief.png b/gallery/figures/XY_lines_001_2Drelief.png
diff --git a/gallery/figures/XY_lines_tseries_aircraft_AZF2M.png b/gallery/figures/XY_lines_tseries_aircraft_AZF2M.png
diff --git a/gallery/figures/XY_multisimple_GABLS1.png b/gallery/figures/XY_multisimple_GABLS1.png
diff --git a/gallery/figures/histogramm_009ICARTT_full.png b/gallery/figures/histogramm_009ICARTT_full.png
diff --git a/gallery/figures/horizontal_oasis_coupling.png b/gallery/figures/horizontal_oasis_coupling.png
diff --git a/gallery/figures/sectionH_004_Reunion.png b/gallery/figures/sectionH_004_Reunion.png
diff --git a/gallery/figures/sectionH_2dom_front_AZF_full.png b/gallery/figures/sectionH_2dom_front_AZF_full.png
diff --git a/gallery/figures/sectionH_OCEAN.png b/gallery/figures/sectionH_OCEAN.png
diff --git a/gallery/figures/sectionH_vectors_007janvier_full.png b/gallery/figures/sectionH_vectors_007janvier_full.png
diff --git a/gallery/figures/sectionV_KW78_full.png b/gallery/figures/sectionV_KW78_full.png
diff --git a/gallery/figures/sectionV_Reunion_full.png b/gallery/figures/sectionV_Reunion_full.png
diff --git a/gallery/figures/timeseries_FIRE_full.png b/gallery/figures/timeseries_FIRE_full.png
diff --git a/gallery/view/3D_mayavi.md b/gallery/view/3D_mayavi.md
@@ -0,0 +1,84 @@
+## Plot 2
+
+![3D_mayavi.png](../figures/3D_mayavi.png)
+
+````python
+# --------------------------------------------------------
+#
+#                 G. Feger  (    06/02/2024   )
+#
+#                    ~~~~~~~~~~~~~~~
+#       Script used to visualize aerosol cloud interaction
+#     in the case of a dusty Saharan Air Layer at Cape Verde
+#                    ~~~~~~~~~~~~~~~
+#
+# --------------------------------------------------------
+
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+import matplotlib as mpl                ; import matplotlib.pyplot as plt
+from matplotlib import cm               ; from matplotlib.colors import ListedColormap
+import numpy as np                      ; import pandas as pd
+import cartopy                          ; import cartopy.feature as cfeature
+import xarray as xr                     ; import math ; import numpy.ma as ma
+import datetime                         ; from netCDF4 import Dataset
+import cftime                           ; import os
+import datetime                         ; import cartopy.crs as ccrs
+import scipy                            ; from scipy.stats import gmean
+import fct                              ; from scipy.interpolate import interpn
+import PyQt5                            ; import mayavi   ; from mayavi import mlab
+import metpy                            ; import metpy.calc as mpcalc
+from metpy.cbook import get_test_data
+from metpy.interpolate import cross_section
+from mpl_toolkits.basemap import Basemap, shiftgrid
+import pandas as pd
+from IPython.display import display, HTML
+display(HTML("<style>.container { width:80% !important; }</style>"))
+
+# MAYAVI 3D plot
+%gui qt 
+# lecture fichier méso-nh
+def process_data(directory, pattern, endwith):
+    nc_files = [os.path.join(directory, filename) for filename in os.listdir(directory) if filename.endswith(endwith) and filename.startswith(pattern)]
+    datasets = [xr.open_mfdataset(file,combine='by_coords') for file in nc_files]
+    ho = xr.concat(datasets, dim='time', join='override')
+    ho = ho.sortby('time')
+    ho = ho.assign_coords(nj=('nj', ho.latitude[:,0].values), ni=('ni', ho.longitude[0,:].values), nj_u=('nj_u', ho.latitude[:,0].values), ni_u=('ni_u', ho.longitude[0,:].values)).rename({'ni': 'lon', 'nj': 'lat', 'ni_u': 'lon_u', 'nj_u': 'lat_u'})
+    return ho
+m1  = process_data('.' , 'CMS01.1.SEG01.OUT.012', '.nc')
+pgd = process_data('.' , 'AFCAV', '.nc')
+
+# prepare le domaine 3d
+step    = 0
+lon     = m1.lon.values
+lat     = m1.lat.values
+alt     = m1.level_w.values/1000                          # en km
+topo    = pgd.CLAY[0,:,:].values/1000
+Z_plot  = 10                                              # Z_plot = alt[-1] si on veut visu tout le domaine sans zoomer
+alt_reg = np.linspace(0,Z_plot,101)                       # altitude dz fixe pour interpolation et plot
+x, y, z = np.meshgrid(lon, lat, alt_reg, indexing='ij')   # grille 3D : dx dy dz constant
+# selection des variables
+var1 = m1.WT[step, :, :,:].values      
+var2 = m1.NIF01[step, :, :,:].values       
+var1 = np.transpose(var1, (2, 1, 0))                       # Z en 3e position
+var2 = np.transpose(var2, (2, 1, 0))                       # Z en 3e position 
+var1 = interpn((lon, lat, alt), var1, (x, y, z), method='linear', bounds_error=False, fill_value=0)  # interp variables sur domaine régulier
+var2 = interpn((lon, lat, alt), var2, (x, y, z), method='linear', bounds_error=False, fill_value=0)
+
+# --  Figure  --
+fig       = mlab.figure(bgcolor=(1,1,1), fgcolor=(0.,0.,0.))
+ratio=2
+pltextent = (lon[0], lon[-1], lat[0], lat[-1], alt[0]/ratio, Z_plot/ratio)   # rapport d'aspect de la fig pour lisibilité
+contour1 = mlab.contour3d(x,y,z/ratio,var1, vmin=2, vmax=10 , contours=[2,5,10],   transparent=True,opacity=0.7)
+contour2 = mlab.contour3d(x,y,z/ratio,var2, vmin=20,vmax=40,  contours=[20,30,40], transparent=False,opacity=0.99,colormap='Reds')
+mlab.imshow(topo.T, colormap='gist_gray',figure=fig, extent=[lon[0], lon[-1], lat[0], lat[-1], alt[0]/ratio, alt[1]/ratio], opacity=0.5)
+#mlab.surf(lon, lat, topo.T/ratio, colormap='gist_gray',figure=fig,opacity=0.7, vmin=alt[0]/ratio)
+# setup figure
+mlab.outline(contour1, color=(.1, .7, .7), extent=pltextent)
+mlab.axes(xlabel='Lon', ylabel='Lat', zlabel='Alt (km)')
+mlab.axes(nb_labels=5,ranges=(lon[0], lon[-1], lat[0], lat[-1], alt[0], Z_plot)) # valeurs reelles des coordonnees
+mlab.gcf().scene.parallel_projection = True
+mlab.orientation_axes()
+mlab.colorbar(object=contour2, nb_colors=3, nb_labels=3, orientation='vertical', title='IFN FREE (#/cm3)')
+mlab.title('Simulation Méso-NH', line_width=2.0, size=4, figure=fig)
+mlab.text3d(lon[-104],lat[-44],alt[26]/ratio, 'Saharan air layer', scale=0.4, color=(0.6,0,0.3))
+````
diff --git a/gallery/view/XY_budget_terms.md b/gallery/view/XY_budget_terms.md
@@ -0,0 +1,49 @@
+## Plot 2
+
+![XY_budget_terms.png](../figures/XY_budget_terms.png)
+
+````python
+Panel = PanelPlot(2,2, [20,20],'COPT81 avec Mask', titlepad=11, minmaxpad=1.04, timepad=-0.07, colorbarpad=0.03, labelcolorbarpad = 13, colorbaraspect=40)
+
+# Budget of potential temperature
+nmask=0 #Convective mask, criteria in set_mask.f90
+ntime=7 # 8th hour
+
+Lplot = [Dvar['f1'][('/Budgets/TH','SFR')][nmask,ntime,:], Dvar['f1'][('/Budgets/TH','DEPS')][nmask,ntime,:], Dvar['f1'][('/Budgets/TH','DEPG')][nmask,ntime,:],
+         Dvar['f1'][('/Budgets/TH','REVA')][nmask,ntime,:],
+         Dvar['f1'][('/Budgets/TH','DEPI')][nmask,ntime,:], Dvar['f1'][('/Budgets/TH','IMLT')][nmask,ntime,:], Dvar['f1'][('/Budgets/TH','GMLT')][nmask,ntime,:],
+         Dvar['f1'][('/Budgets/TH','DRYG')][nmask,ntime,:], Dvar['f1'][('/Budgets/TH','ACC')][nmask,ntime,:], Dvar['f1'][('/Budgets/TH','RIM')][nmask,ntime,:],
+         Dvar['f1'][('/Budgets/TH','BERFI')][nmask,ntime,:], Dvar['f1'][('/Budgets/TH','CFRZ')][nmask,ntime,:], Dvar['f1'][('/Budgets/TH','WETG')][nmask,ntime,:]
+         ]
+LaxeZ = [Dvar['f1']['mask_level']]*len(Lplot)
+Ltitle = ['Bilan température potentielle : partie convective - MASK1']*len(Lplot)
+Llinelabel = ['SFR','DEPS','DEPG','REVA','DEPI','IMLT','GMLT','DRYG','ACC','RIM','BERFI','CFRZ','WETG']
+Lxlim = [(-0.7E-2, 0.7E-2)]*len(Lplot)
+Lxlab = ['Terme du bilan (K)']*len(Lplot)
+Lylab = ['altitude (m)']*len(Lplot)
+Lylim = [(0,12000.0)]*len(Lplot)
+LaxisColor = ['black']*len(Lplot)
+Llinewidth = [3]*len(Lplot)
+LfacconvX=[1]*len(Lplot)
+Llinecolor = ['red','green','blue','cyan','indigo','bisque','brown','orange','yellow',
+              'magenta','gray','lightblue','black']
+
+fig = Panel.pXY_lines(Lxx=Lplot, Lyy=LaxeZ, Lxlab=Lxlab, Lylab=Lylab, Ltitle=Ltitle, Llinewidth=Llinewidth, LfacconvX=LfacconvX,
+                        Lylim=Lylim, Lxlim=Lxlim, Llinelabel=Llinelabel, Llinecolor=Llinecolor,LaxisColor=LaxisColor,
+                        ax=fig.axes)
+
+nmask=1 #Convective mask, criteria in set_mask.f90
+Lplot = [Dvar['f1'][('/Budgets/TH','SFR')][nmask,ntime,:], Dvar['f1'][('/Budgets/TH','DEPS')][nmask,ntime,:], Dvar['f1'][('/Budgets/TH','DEPG')][nmask,ntime,:],
+         Dvar['f1'][('/Budgets/TH','REVA')][nmask,ntime,:],
+         Dvar['f1'][('/Budgets/TH','DEPI')][nmask,ntime,:], Dvar['f1'][('/Budgets/TH','IMLT')][nmask,ntime,:], Dvar['f1'][('/Budgets/TH','GMLT')][nmask,ntime,:],
+         Dvar['f1'][('/Budgets/TH','DRYG')][nmask,ntime,:], Dvar['f1'][('/Budgets/TH','ACC')][nmask,ntime,:], Dvar['f1'][('/Budgets/TH','RIM')][nmask,ntime,:],
+         Dvar['f1'][('/Budgets/TH','BERFI')][nmask,ntime,:], Dvar['f1'][('/Budgets/TH','CFRZ')][nmask,ntime,:], Dvar['f1'][('/Budgets/TH','WETG')][nmask,ntime,:]
+         ]
+Lxlim = [(-0.7E-3, 0.7E-3)]*len(Lplot)
+Ltitle = ['Bilan température potentielle : partie stratiforme - MASK2']*len(Lplot)
+
+fig = Panel.pXY_lines(Lxx=Lplot, Lyy=LaxeZ, Lxlab=Lxlab, Lylab=Lylab, Ltitle=Ltitle, Llinewidth=Llinewidth, LfacconvX=LfacconvX,
+                        Lylim=Lylim, Lxlim=Lxlim, Llinelabel=Llinelabel, Llinecolor=Llinecolor,LaxisColor=LaxisColor,
+                        ax=fig.axes)
+Panel.save_graph(1,fig)
+````
diff --git a/gallery/view/XY_lines_001_2Drelief.md b/gallery/view/XY_lines_001_2Drelief.md
@@ -0,0 +1,35 @@
+## Plot 2
+
+![XY_lines_001_2Drelief.png](../figures/XY_lines_001_2Drelief.png)
+
+````python
+Panel6 = PanelPlot(2,2, [20,20],'Profiles at the center (top of the topography)')
+
+Lplot = [ Dvar['f1']['WT'][:,127]]
+LaxeZ = [Dvar['f1']['altitude'][:,127]]*len(Lplot)
+Ltitle = ['WT and THT-LSTHM']*len(Lplot)
+Llinelabel = ['WT']
+Lxlab = ['velocity (m/s)']*len(Lplot)
+Lylab = ['altitude (m)']*len(Lplot)
+Lylim = [(0,15000.1)]*len(Lplot)
+Lxlim = [(-0.3,0.3)]
+Llinecolor = ['r']
+LaxisColor = Llinecolor
+Llvl = [0]*len(Lplot)
+Ltime = [Dvar['f1']['time']]
+fig6 = Panel6.pXY_lines(Lyy=LaxeZ, Lxx=Lplot, Lxlab=Lxlab, Lylab=Lylab, Ltitle=Ltitle, Lylim=Lylim, Lxlim=Lxlim, Llinelabel=Llinelabel,
+                                Llinecolor=Llinecolor, LaxisColor=LaxisColor, Ltime=Ltime)
+
+Lplot = [ Dvar['f1']['THT-LSTHM'][:,127]]
+Ltitle = []
+Llinelabel = ['THT - LSTHM ']
+Lxlab = ['theta perturb (K)']*len(Lplot)
+Lylab = ['altitude (m)']*len(Lplot)
+Lylim = [(0,15000.1)]*len(Lplot)
+Lxlim = [(-0.8,0.1)]
+Llinecolor = ['g']
+LaxisColor = Llinecolor
+Llvl = [0]*len(Lplot)
+fig7 = Panel6.pXY_lines(Lyy=LaxeZ, Lxx=Lplot, Lxlab=Lxlab, Lylab=Lylab, Ltitle=Ltitle,ax=fig6.axes, id_overlap=1,
+                        Lylim=Lylim, Lxlim=Lxlim, Llinelabel=Llinelabel, Llinecolor=Llinecolor,LaxisColor=LaxisColor, Ltime=Ltime)
+````
diff --git a/gallery/view/XY_lines_tseries_aircraft_AZF2M.md b/gallery/view/XY_lines_tseries_aircraft_AZF2M.md
@@ -0,0 +1,61 @@
+## Plot 2
+
+![XY_lines_tseries_aircraft_AZF2M.png](../figures/XY_lines_tseries_aircraft_AZF2M.png)
+
+````python
+Panel = PanelPlot(8,2, [14,20],'Time series from Aircraft', titlepad=25, minmaxpad=1.04, timepad=-0.07, colorbarpad=0.03, labelcolorbarpad = 13, colorbaraspect=18)
+
+Lplot = [ Dvar['f13'][(LG_AVIONT,'ZS')]]
+Ltime = [Dvar['f13'][(LG_AVION,'time_flyer')]/3600.0]
+Ltitle = ['Orography']
+Lxlab = ['Time (h)']
+Lylab = ['ZS (m)']
+Lylim = [(0, 350)]
+Lxlim = [(9.0, 9.2)]
+fig = Panel.pXY_lines(Lyy=Lplot, Lxx=Ltime, Lxlab=Lxlab, Lylab=Lylab, Ltitle=Ltitle, Lylim=Lylim, Lxlim=Lxlim)
+
+Lplot = [ Dvar['f13'][(LG_AVIONT,'P')]]
+Ltitle = ['Pressure']
+Lylab = ['P (Pa)']
+Lylim = [(0, 95000)]
+fig = Panel.pXY_lines(Lyy=Lplot, Lxx=Ltime, Lxlab=Lxlab, Lylab=Lylab, Ltitle=Ltitle, Lylim=Lylim, Lxlim=Lxlim, ax=fig.axes) 
+
+Lplot = [ Dvar['f13'][(LG_AVIONT,'LON')]]
+Ltitle = ['Longitude']
+Lylab = ['Longitude']
+Lylim = [(0, 2.5)]
+fig = Panel.pXY_lines(Lyy=Lplot, Lxx=Ltime, Lxlab=Lxlab, Lylab=Lylab, Ltitle=Ltitle, Lylim=Lylim, Lxlim=Lxlim, ax=fig.axes)
+
+Lplot = [ Dvar['f13'][(LG_AVIONT,'ZON_WIND')]]
+Ltitle = ['Zonal wind']
+Lylab = ['u (m/s)']
+Lylim = [(-1, 11)]
+fig = Panel.pXY_lines(Lyy=Lplot, Lxx=Ltime, Lxlab=Lxlab, Lylab=Lylab, Ltitle=Ltitle, Lylim=Lylim, Lxlim=Lxlim, ax=fig.axes)
+
+Lplot = [ Dvar['f13'][(LG_AVIONT,'MER_WIND')]]
+Ltitle = ['Meridional wind']
+Lylab = ['v (m/s)']
+Lylim = [(-3, 3)]
+fig = Panel.pXY_lines(Lyy=Lplot, Lxx=Ltime, Lxlab=Lxlab, Lylab=Lylab, Ltitle=Ltitle, Lylim=Lylim, Lxlim=Lxlim, ax=fig.axes)
+
+Lplot = [ Dvar['f13'][(LG_AVIONT,'W')]]
+Ltitle = ['Vertical velocity']
+Lylab = ['w (m/s)']
+Lylim = [(-0.1, 0.1)]
+fig = Panel.pXY_lines(Lyy=Lplot, Lxx=Ltime, Lxlab=Lxlab, Lylab=Lylab, Ltitle=Ltitle, Lylim=Lylim, Lxlim=Lxlim, ax=fig.axes)
+
+Lplot = [ Dvar['f13'][(LG_AVIONT,'Th')]]
+Ltitle = ['Potential Temperature']
+Lylab = [r'$\theta$ (K)']
+Lylim = [(290, 305)]
+fig = Panel.pXY_lines(Lyy=Lplot, Lxx=Ltime, Lxlab=Lxlab, Lylab=Lylab, Ltitle=Ltitle, Lylim=Lylim, Lxlim=Lxlim, ax=fig.axes)
+
+Lplot = [ Dvar['f13'][(LG_AVIONT,'Rv')]]
+Ltitle = ['Water vapor mixing ratio']
+Lylab = ['Rv (kg/kg))']
+Lylim = [(0, 0.01)]
+fig = Panel.pXY_lines(Lyy=Lplot, Lxx=Ltime, Lxlab=Lxlab, Lylab=Lylab, Ltitle=Ltitle, Lylim=Lylim, Lxlim=Lxlim, ax=fig.axes)
+
+fig.tight_layout()
+Panel.save_graph(1,fig)
+````
diff --git a/gallery/view/XY_multisimple_GABLS1.md b/gallery/view/XY_multisimple_GABLS1.md
@@ -0,0 +1,40 @@
+## Plot 2
+
+![XY_multisimple_GABLS1.png](../figures/XY_multisimple_GABLS1.png)
+
+````python
+Panel = PanelPlot(3,3, [25,25],'8-9h time averaged vertical profiles', titlepad=11, minmaxpad=1.04, timepad=-0.07, colorbarpad=0.03, labelcolorbarpad = 13, colorbaraspect=40)
+
+Lplot = [np.mean(Dvar['f1'][(LG_MEAN,'MEAN_TH')][:,t_beg:t_end],axis=1), np.mean(Dvar['f2'][(LG_MEAN,'MEAN_TH')][:,t_beg:t_end],axis=1),
+         np.mean(Dvar['f3'][(LG_MEAN,'MEAN_TH')][:,t_beg:t_end],axis=1)]
+LaxeZ = [Dvar['f1']['level_les'], Dvar['f2']['level_les'], Dvar['f3']['level_les']]
+Ltitle = ['MEAN_TH']*len(Lplot)
+Llinelabel = ['1D BL89','1D RM17', 'LES']
+Lxlab = ['theta (K)']*len(Lplot)
+Lylab = ['altitude (m)']*len(Lplot)
+Lylim = [(0,400.1)]*len(Lplot)
+Lxlim = [(262, 268)]*len(Lplot)
+Llinecolor = ['red','blue', 'black']
+LaxisColor = ['black']*len(Lplot)
+Llinewidth = [3]*len(Lplot)
+fig = Panel.pXY_lines(Lxx=Lplot, Lyy=LaxeZ, Lxlab=Lxlab, Lylab=Lylab, Ltitle=Ltitle, Llinewidth=Llinewidth,
+                        Lylim=Lylim, Lxlim=Lxlim, Llinelabel=Llinelabel, Llinecolor=Llinecolor,LaxisColor=LaxisColor)
+
+Lplot = [np.mean(Dvar['f1']['WIND'][:,t_beg:t_end],axis=1), np.mean(Dvar['f2']['WIND'][:,t_beg:t_end],axis=1), np.mean(Dvar['f3']['WIND'][:,t_beg:t_end],axis=1)]
+Ltitle = ['Wind speed']*len(Lplot)
+Lxlab = ['Wind speed (m/s)']*len(Lplot)
+Lxlim = [(0, 11)]*len(Lplot)
+fig = Panel.pXY_lines(Lxx=Lplot, Lyy=LaxeZ, Lxlab=Lxlab, Lylab=Lylab, Ltitle=Ltitle, ax=fig.axes, Llinewidth=Llinewidth,
+                        Lylim=Lylim, Lxlim=Lxlim, Llinelabel=Llinelabel, Llinecolor=Llinecolor,LaxisColor=LaxisColor)
+
+Lplot = [Dvar['f1']['SBL_H'][:], Dvar['f2']['SBL_H'][:], Dvar['f3']['SBL_H'][:]]
+
+Ltitle = ['Boundary layer height']*len(Lplot)
+LaxeTime = [Dvar['f1']['time_les']/3600.0, Dvar['f2']['time_les']/3600.0, Dvar['f3']['time_les']/3600.0]
+Lxlab = ['Time (h)']*len(Lplot)
+Lxlim = [(0, 9)]*len(Lplot)
+Lylim = [(0, 300.1)]*len(Lplot)
+fig = Panel.pXY_lines(Lyy=Lplot, Lxx=LaxeTime, Lxlab=Lxlab, Lylab=Lylab, Ltitle=Ltitle, ax=fig.axes,Llinewidth=Llinewidth,
+                        Lylim=Lylim, Lxlim=Lxlim, Llinelabel=Llinelabel, Llinecolor=Llinecolor,LaxisColor=LaxisColor)
+Panel.save_graph(1,fig)
+````
diff --git a/gallery/view/diachronic_file.md b/gallery/view/diachronic_file.md
@@ -0,0 +1,22 @@
+## Read diachronic file
+
+````python
+LnameFiles = ['RBL89.1.ECH01.000.nc','GABL1.1.ECH01.000.nc']
+LG_MEAN = '/LES_budgets/Mean/Cartesian/Not_time_averaged/Not_normalized/cart/'
+LG_SBG = '/LES_budgets/Subgrid/Cartesian/Not_time_averaged/Not_normalized/cart/'
+LG_RES = '/LES_budgets/Resolved/Cartesian/Not_time_averaged/Not_normalized/cart/'
+
+Dvar_input = {
+'f1':[(LG_SBG,'SBG_TKE'),(LG_SBG,'SBG_WU'),(LG_SBG,'SBG_WV'),(LG_SBG,'SBG_KM'),(LG_SBG,'SBG_KH'),(LG_SBG,'SBG_WTHL'),(LG_SBG,'SBG_THL2'),
+      (LG_MEAN,'MEAN_U'),(LG_MEAN,'MEAN_V'),(LG_MEAN,'MEAN_TH'),
+      'time_les','level_les'],
+'f2':[(LG_SBG,'SBG_TKE'),(LG_SBG,'SBG_WU'),(LG_SBG,'SBG_WV'),(LG_SBG,'SBG_KM'),(LG_SBG,'SBG_KH'),(LG_SBG,'SBG_WTHL'),(LG_SBG,'SBG_THL2'),
+      (LG_RES,'RES_KE'),(LG_RES,'RES_WU'),(LG_RES,'RES_WV'),(LG_RES,'RES_WTH'),(LG_RES,'RES_TH2'),
+      (LG_MEAN,'MEAN_U'),(LG_MEAN,'MEAN_V'),(LG_MEAN,'MEAN_TH'),
+      'time_les','level_les']
+}
+
+#  Read the variables in the files
+Dvar = {}
+Dvar = read_netcdf(LnameFiles, Dvar_input, path=path, removeHALO=False)
+````
diff --git a/gallery/view/full_doc.md b/gallery/view/full_doc.md
@@ -0,0 +1,43 @@
+## Full documentation
+
+````python
+def read_netcdf(LnameFiles, Dvar_input, path='.', get_data_only=True, del_empty_dim=True, removeHALO=True):
+    """Read a netCDF4 Meso-NH file
+    For each file, call functions to read diachronic or synchronous file
+
+    Parameters
+    ----------
+    LnameFiles : list of str
+        list of Meso-NH netCDF4 file (diachronic or synchronous)
+
+    Dvar_input : Dict{'fileNumber' : 'var_name',('group_name','var_name')}
+        where
+        'fileNumber' is a str corresponding to 'f' + the file number in LnameFiles (by order)
+        'var_name' is the exact str of the netCDF4 variable name
+        ('group_name','var_name') is the exact tuple of the (sub-)groups name and the netCDF4 variable name
+        e.g. : {'f1':['ZS', 'WT','ni', 'level'],
+                'f2':[('/LES_budgets/Cartesian/Not_time_averaged/Not_normalized/cart/',MEAN_TH'),('/Budgets/RI','AVEF')]
+                }
+
+    path : str
+        unique path of the files
+
+    get_data_only : bool, default: True
+        if True,  the function returns Dvar as masked_array (only data)
+        if False, the function returns Dvar as netCDF4._netCDF4.Variable
+
+    del_empty_dim : bool, default: True
+        if get_data_only=True and del_empty_dim=True, returns Dvar as an array without dimensions with size 1 and 0
+        e.g. : an array of dimensions (time_budget, cart_level, cart_nj, cart_ni) with shape (180,1,50,1) is returned (180,50)
+
+    removeHALO : bool, default: True
+        if True, remove first and last (NHALO=1) point [1:-1] if get_data_only=True on each
+        level, level_w, ni, ni_u, ni_v, nj, nj_u, nj_v dimensions
+
+    Returns
+    -------
+    Dvar : Dict
+        Dvar[ifile]['var_name']                if the group contains only one variable
+        Dvar[ifile][('group_name','var_name')] if the group contains more than one variable
+    """
+````