diff --git a/MY_RUN/KTEST/012_dust/005_python/plot_012_dust.py b/MY_RUN/KTEST/012_dust/005_python/plot_012_dust.py
index be5585a8942d90a752b1241023742d6f9da5f74f..7448f10d0b38061642aacbb934f40796745cc745 100644
--- a/MY_RUN/KTEST/012_dust/005_python/plot_012_dust.py
+++ b/MY_RUN/KTEST/012_dust/005_python/plot_012_dust.py
@@ -30,7 +30,6 @@ Dvar_input = {
# Read the variables in the files
Dvar = {}
Dvar = read_netcdf(LnameFiles, Dvar_input, path=path, removeHALO=True)
-Dvar['f1']['date'] = convert_date(Dvar['f1']['date'], Dvar['f1']['time'])
################################################################
######### PANEL 1
###############################################################
diff --git a/MY_RUN/KTEST/014_LIMA/004_python/plot_014_LIMA.py b/MY_RUN/KTEST/014_LIMA/004_python/plot_014_LIMA.py
index 12ff241726cb4b00c005051e28ee8e69516e2b35..b64203496df724da0109d0798a84d4b66302de4e 100644
--- a/MY_RUN/KTEST/014_LIMA/004_python/plot_014_LIMA.py
+++ b/MY_RUN/KTEST/014_LIMA/004_python/plot_014_LIMA.py
@@ -20,29 +20,25 @@ os.system('rm -f tempgraph*')
path=""
LnameFiles = ['XPREF.1.SEG01.000.nc' ]
-Dvar_input = {'f1':['RI', 'CICE', 'RS','RG', 'CIFNFREE01','CIFNNUCL01' ]}
+Dvar_input = {'f1':[('RI','AVEF'), ('CICE','AVEF'), ('RS','AVEF'),('RG','AVEF'), ('CIFNFREE01','AVEF'),('CIFNNUCL01','AVEF') ]}
Dvar_input_coord_budget = {'f1':['cart_level', 'cart_ni']}
Dvar_input_coord = {'f1':['ZS','ZTOP']}
-# Add ___AVED to all variables
-for i,var in enumerate(Dvar_input['f1']):
- Dvar_input['f1'][i] = var + '___AVEF'
-#
# Read the variables in the files
Dvar, Dvar_coord_budget, Dvar_coord = {}, {}, {}
Dvar = read_netcdf(LnameFiles, Dvar_input, path=path, removeHALO=False)
Dvar_coord_budget = read_netcdf(LnameFiles, Dvar_input_coord_budget, path=path, removeHALO=False)
Dvar_coord = read_netcdf(LnameFiles, Dvar_input_coord, path=path, removeHALO=True)
-Dvar['f1']['altitude'], Dvar['f1']['ni_2D'] = comp_altitude1DVar(Dvar['f1']['CIFNFREE01'], Dvar_coord['f1']['ZS'],Dvar_coord['f1']['ZTOP'], Dvar_coord_budget['f1']['cart_level'],Dvar_coord_budget['f1']['cart_ni'])
+Dvar['f1']['altitude'], Dvar['f1']['ni_2D'] = comp_altitude1DVar(Dvar['f1'][('CIFNFREE01','AVEF')], Dvar_coord['f1']['ZS'],Dvar_coord['f1']['ZTOP'], Dvar_coord_budget['f1']['cart_level'],Dvar_coord_budget['f1']['cart_ni'])
################################################################
######### PANEL 1
###############################################################
Panel1 = PanelPlot(2,3, [25,14],'014_LIMA', titlepad=25, minmaxpad=1.04, timepad=-0.07, colorbarpad=0.03, labelcolorbarpad = 13, colorbaraspect=40)
-Lplot = [Dvar['f1']['RI'],Dvar['f1']['CICE'], Dvar['f1']['RS'],
- Dvar['f1']['RG'],Dvar['f1']['CIFNFREE01'], Dvar['f1']['CIFNNUCL01']]
+Lplot = [Dvar['f1'][('RI','AVEF')],Dvar['f1'][('CICE','AVEF')], Dvar['f1'][('RS','AVEF')],
+ Dvar['f1'][('RG','AVEF')],Dvar['f1'][('CIFNFREE01','AVEF')], Dvar['f1'][('CIFNNUCL01','AVEF')]]
LaxeX = [Dvar['f1']['ni_2D']]*len(Lplot)
LaxeZ = [Dvar['f1']['altitude']]*len(Lplot)
Ltitle = ['Ice water content', 'Ice concentration', 'Snow water content',
diff --git a/src/LIB/Python/Panel_Plot.py b/src/LIB/Python/Panel_Plot.py
index 7fb3147dd9a0c45724dbcf80627b318c43bf9a73..24134085e04ad816580a545bfb65de987ec3db8b 100644
--- a/src/LIB/Python/Panel_Plot.py
+++ b/src/LIB/Python/Panel_Plot.py
@@ -294,10 +294,11 @@ class PanelPlot():
except:
pass
- # Color label on contour-ligne
+ # Color label on contour-line
if Lpltype[i]=='c': # Contour
- self.ax[iax].clabel(cf, levels=np.arange(Lminval[i],Lmaxval[i],step=Lstep[i]))
-
+ self.ax[iax].clabel(cf)
+ #self.ax[iax].clabel(cf, levels=np.arange(Lminval[i],Lmaxval[i],step=Lstep[i])) #TODO bug, levels not recognized
+
#Filling area under topography
if not orog==[]:
self.ax[iax].fill_between(Lxx[i][0,:], orog, color='black')
@@ -401,7 +402,7 @@ class PanelPlot():
def psectionH(self, lon=[],lat=[], Lvar=[], Lcarte=[], Llevel=[], Lxlab=[], Lylab=[], Ltitle=[], Lminval=[], Lmaxval=[],
Lstep=[], Lstepticks=[], Lcolormap=[], LcolorLine=[], Lcbarlabel=[], Lproj=[], Lfacconv=[], coastLines=True, ax=[],
- Lid_overlap=[], colorbar=True, Ltime=[], LaddWhite_cm=[], Lpltype=[]):
+ Lid_overlap=[], colorbar=True, Ltime=[], LaddWhite_cm=[], Lpltype=[], Lcbformatlabel=[]):
"""
Horizontal cross section plot
Arguments :
@@ -429,6 +430,7 @@ class PanelPlot():
- colorbar : show colorbar or not
- Lpltype : List of types of plot 'cf' or 'c'. cf=contourf, c=contour (lines only)
- LaddWhite_cm : List of boolean to add white color to a colormap at the first (low value) tick colorbar
+ - Lcbformatlabel: List of boolean to reduce the format to exponential 1.1E+02 format colorbar label
"""
self.ax = ax
firstCall = (len(self.ax) == 0)
@@ -447,6 +449,7 @@ class PanelPlot():
if not Lcolormap: LcolorLine=['black']*len(Lvar)
if not Lpltype: Lpltype=['cf']*len(Lvar)
if not LaddWhite_cm: LaddWhite_cm=[False]*len(Lvar)
+ if not Lcbformatlabel: Lcbformatlabel=[False]*len(Lvar)
# Add an extra percentage of the top max value for forcing the colorbar show the true user maximum value (correct a bug)
if Lstep: Lmaxval = list(map(lambda x, y: x + 1E-6*y, Lmaxval, Lstep) ) #The extra value is 1E-6 times the step ticks of the colorbar
@@ -501,22 +504,22 @@ class PanelPlot():
# Add White to colormap
if LaddWhite_cm[i] and Lcolormap: Lcolormap[i]=self.addWhitecm(LaddWhite_cm[i], Lcolormap[i], len(levels_contour))
-
+
# Plot
if Lproj:
if Lpltype[i]=='c': # Contour
if LcolorLine:
- cf = self.ax[iax].contourf(lon[i], lat[i], vartoPlot*Lfacconv[i], levels=levels_contour,transform=Lproj[i],
+ cf = self.ax[iax].contour(lon[i], lat[i], vartoPlot*Lfacconv[i], levels=levels_contour,transform=Lproj[i],
norm=norm, vmin=Lminval[i], vmax=Lmaxval[i], colors=LcolorLine[i])
else:
- cf = self.ax[iax].contourf(lon[i], lat[i], vartoPlot*Lfacconv[i], levels=levels_contour,transform=Lproj[i],
+ cf = self.ax[iax].contour(lon[i], lat[i], vartoPlot*Lfacconv[i], levels=levels_contour,transform=Lproj[i],
norm=norm, vmin=Lminval[i], vmax=Lmaxval[i], cmap=Lcolormap[i])
else:
cf = self.ax[iax].contourf(lon[i], lat[i], vartoPlot*Lfacconv[i], levels=levels_contour,transform=Lproj[i],
norm=norm, vmin=Lminval[i], vmax=Lmaxval[i], cmap=Lcolormap[i])
else: # Cartesian coordinates
if Lpltype[i]=='c': # Contour
- cf = self.ax[iax].contourf(lon[i], lat[i], vartoPlot*Lfacconv[i], levels=levels_contour,
+ cf = self.ax[iax].contour(lon[i], lat[i], vartoPlot*Lfacconv[i], levels=levels_contour,
norm=norm, vmin=Lminval[i], vmax=Lmaxval[i], colors=LcolorLine[i])
else:
cf = self.ax[iax].contourf(lon[i], lat[i], vartoPlot*Lfacconv[i], levels=levels_contour,
@@ -530,18 +533,21 @@ class PanelPlot():
# X/Y Axis
self.set_XYaxislab(self.ax, iax, Lxlab[i], Lylab[i])
- # Color label on contour-ligne
+ # Color label on contour-line
if Lpltype[i]=='c': # Contour
- self.ax[iax].clabel(cf, levels=np.arange(Lminval[i],Lmaxval[i],step=Lstep[i]))
+ if 'GeoAxes' in str(type(self.ax[self.i])): # cartopy does not like the levels arguments in clabel, known issue
+ self.ax[iax].clabel(cf)
+ else:
+ self.ax[iax].clabel(cf, levels=np.arange(Lminval[i],Lmaxval[i],step=Lstep[i]))
# Colorbar
if colorbar:
- cb=plt.colorbar(cf, ax=self.ax[iax], fraction=0.031, pad=self.colorbarpad, ticks=np.arange(Lminval[i],Lmaxval[i],Lstepticks[i]), aspect=self.colorbaraspect)
+ cb=plt.colorbar(cf, ax=self.ax[iax], fraction=0.031, pad=self.colorbarpad, ticks=np.arange(Lminval[i],Lmaxval[i],Lstepticks[i]), aspect=self.colorbaraspect)
cb.ax.set_title(Lcbarlabel[i], pad = self.labelcolorbarpad, loc='left') #This creates a new AxesSubplot only for the colorbar y=0 ==> location at the bottom
+ if Lcbformatlabel[i]: cb.ax.set_yticklabels(["{:.1E}".format(i) for i in cb.get_ticks()])
return self.fig
-
def pvector(self, Lxx=[], Lyy=[], Lvar1=[], Lvar2=[], Lcarte=[], Llevel=[], Lxlab=[], Lylab=[],
Ltitle=[], Lwidth=[], Larrowstep=[], Lcolor=[], Llegendval=[], Lcbarlabel=[],
Lproj=[], Lfacconv=[], ax=[], coastLines=True, Lid_overlap=[], Ltime=[], Lscale=[],
@@ -656,6 +662,107 @@ class PanelPlot():
return self.fig
+ def pstreamline(self, Lxx=[], Lyy=[], Lvar1=[], Lvar2=[], Lcarte=[], Llevel=[], Lxlab=[], Lylab=[], Llinewidth=[], Ldensity=[],
+ Ltitle=[], Lcolor=[], Lproj=[], Lfacconv=[], ax=[], coastLines=True, Lid_overlap=[], Ltime=[],
+ Lylim=[], Lxlim=[]):
+ """
+ Wind stream lines
+ Arguments :
+ - Lxx : List of x or y coordinate variable (lat or ni or nm)
+ - Lyy : List of y coordinates variable (lon or level)
+ - Lvar1 : List of wind-component along x/y or oblic axis (3D for hor. section, 2D for vertical section)
+ - Lvar2 : List of wind-component along y-axis : v-component for horizontal section / w-component for vertical section
+ - Lcarte : Zooming [lonmin, lonmax, latmin, latmax]
+ - Llevel : List of k-level value for the horizontal section plot (ignored if variable is already 2D)
+ - Lxlab : List of x-axis label
+ - Lylab : List of y-axis label
+ - Lxlim : List of x (min, max) value plotted
+ - Lylim : List of y (min, max) value plotted
+ - Ltitle : List of sub-titles
+ - Ltime : List of time (validity)
+ - Llinewidth : List of lines thickness
+ - Ldensity : List of density that control the closeness of streamlines
+ - Lcolor : List of colors for the streamline (default: black)
+ - Lproj : List of ccrs cartopy projection
+ - Lfacconv : List of factors for unit conversion of each variables
+ - coastLines : Boolean to plot coast lines and grid lines
+ - ax : List of fig.axes for ploting multiple different types of plots in a subplot panel
+ - Lid_overlap : List of number index of plot to overlap current variables
+ """
+ self.ax = ax
+ firstCall = (len(self.ax) == 0)
+ # If all plots are not using conversion factor, convert it to List
+ if not Lfacconv: Lfacconv = [1.0]*len(Lvar1)
+ if not Lcolor: Lcolor = ['black']*len(Lvar1)
+ if not Lylab: Lylab = ['']*len(Lvar1)
+ if not Lxlab: Lxlab = ['']*len(Lvar1)
+ if not Llinewidth: Llinewidth = [1.0]*len(Lvar1)
+ if not Ldensity: Ldensity = [1.0]*len(Lvar1)
+
+ # On all variables to plot
+ for i,var1 in enumerate(Lvar1):
+ if firstCall: #1st call
+ iax = i
+ if Lproj:
+ self.ax.append(self.fig.add_subplot(self.nb_l,self.nb_c,i+1, projection = Lproj[i]))
+ else:
+ self.ax.append(self.fig.add_subplot(self.nb_l,self.nb_c,i+1))
+ self.nb_graph+=1
+ elif Lid_overlap != []: #overlapping plot
+ iax = Lid_overlap[i]
+ else: #existing ax with no overlapping (graphd appended to existing panel)
+ if Lproj:
+ self.ax.append(self.fig.add_subplot(self.nb_l,self.nb_c,self.nb_graph+1, projection = Lproj[i]))
+ else:
+ self.ax.append(self.fig.add_subplot(self.nb_l,self.nb_c,self.nb_graph+1))
+ self.nb_graph+=1
+ iax = len(self.ax)-1 # The ax index of the new coming plot is the length of the existant ax -1 for indices matter
+
+ # Zooming
+ if len(Lcarte) == 4: #zoom
+ self.ax[iax].set_xlim(Lcarte[0], Lcarte[1])
+ self.ax[iax].set_ylim(Lcarte[2], Lcarte[3])
+
+ # Variable to plot w.r.t dimensions
+ if var1.ndim==2:
+ vartoPlot1 = var1[:,:]
+ vartoPlot2 = Lvar2[i][:,:]
+ else: # Variable is 3D : only for horizontal section
+ vartoPlot1 = var1[Llevel[i],:,:]
+ vartoPlot2 = Lvar2[i][Llevel[i],:,:]
+
+ # Print min/max val to help choose steps
+ self.set_minmaxText(self.ax, iax, np.sqrt(vartoPlot1**2 + vartoPlot2**2), Ltitle[i], Lid_overlap, Lfacconv[i])
+
+ # Print time validity
+ if Ltime: self.showTimeText(self.ax, iax, str(Ltime[i]))
+
+ # Plot
+ cf = self.ax[iax].streamplot(Lxx[i], Lyy[i], vartoPlot1, vartoPlot2, density=Ldensity[i], linewidth=Llinewidth[i], color=Lcolor[i])
+
+ # Title
+ self.set_Title(self.ax, iax, Ltitle[i], Lid_overlap,Lxlab[i], Lylab[i])
+
+ # X/Y Axis Label
+ self.set_XYaxislab(self.ax, iax, Lxlab[i], Lylab[i])
+
+ # X/Y Axis limits value
+ if Lxlim:
+ try:
+ self.set_xlim(self.ax, iax, Lxlim[i])
+ except:
+ pass
+ if Lylim:
+ try:
+ self.set_ylim(self.ax, iax, Lylim[i])
+ except:
+ pass
+
+ # Coastlines:
+ if Lproj: self.draw_Backmap(coastLines, self.ax[iax], Lproj[i])
+
+ return self.fig
+
def pXY_bar(self, Lbins=[], Lvar=[], Lxlab=[], Lylab=[], Ltitle=[], Lcolor=[], Lwidth=[],
Llinecolor=[], Llinewidth=[], Lfacconv=[], ax=[], id_overlap=None, Lxlim=[],
Lylim=[], Ltime=[], LaxisColor=[]):
diff --git a/src/LIB/Python/read_MNHfile.py b/src/LIB/Python/read_MNHfile.py
index 375d5effe088b07bbf7331c92c53967154f5685c..7ad0bd539810b5413023b7339b11e479f3a7d548 100644
--- a/src/LIB/Python/read_MNHfile.py
+++ b/src/LIB/Python/read_MNHfile.py
@@ -31,8 +31,8 @@ def read_BACKUPfile(nameF, ifile, Dvar_input, Dvar_output, path='.', removeHALO=
Dvar_output[ifile] = {} #initialize dic for each files
# Reading date since beginning of the model run
- Dvar_output[ifile]['date'] = theFile.variables['time'].units
Dvar_output[ifile]['time'] = theFile.variables['time'][0]
+ Dvar_output[ifile]['date'] = nc.num2date(Dvar_output[ifile]['time'],units=theFile.variables['time'].units, calendar = theFile.variables['time'].calendar)
for var in Dvar_input[ifile]: #For each files
# Read variables
@@ -186,11 +186,25 @@ def read_TIMESfiles_55(theFile, ifile, Dvar_input, Dvar_output, removeHALO=False
return Dvar_output
def read_from_group(theFile, Dvar_output, group_name, var):
- suffix, var_name = remove_PROC(var)
- if group_name == 'TSERIES': #always 1D
- Dvar_output[(group_name,var)] = theFile.groups['TSERIES'].variables[var][:]
- elif group_name == 'ZTSERIES': #always 2D
- Dvar_output[(group_name,var)] = theFile.groups['ZTSERIES'].variables[var][:,:].T
+ """
+ Read variables from MNH MASDEV >= 5.5.0
+ Parameters :
+ - var : the variable name
+ - group_name : the group name
+ Return :
+ Dvar_output : dictionnary of :
+ - Dvar_output[ifile]['var_name'] if the group contains only one variable
+ - Dvar_output[ifile][('group_name','var_name'] if the group contains more than one variable
+ """
+ if '___' in var:
+ suffix, var_name = remove_PROC(var)
+ else:
+ suffix = var
+ var_name = var
+ if group_name == 'TSERIES' or group_name =='AVION': #always 1D
+ Dvar_output[(group_name,var)] = theFile.groups[group_name].variables[var][:]
+ elif group_name == 'ZTSERIES' or group_name =='AVIONZ': #always 2D
+ Dvar_output[(group_name,var)] = theFile.groups[group_name].variables[var][:,:].T
elif 'XTSERIES' in group_name: #always 2D
Dvar_output[(group_name,var)] = theFile.groups[group_name].variables[var][:,:].T
elif theFile.groups[group_name].type == 'TLES' : # LES type
@@ -213,7 +227,21 @@ def read_TIMESfiles_55(theFile, ifile, Dvar_input, Dvar_output, removeHALO=False
if shapeVar[2]==1: Ltosqueeze.append(2)
if shapeVar[3]==1: Ltosqueeze.append(3)
Ltosqueeze=tuple(Ltosqueeze)
- Dvar_output[group_name] = np.squeeze(theFile.groups[group_name].variables[suffix][:,:,:,:], axis=Ltosqueeze)
+ if len(theFile.groups[group_name].variables.keys()) > 1: # If more than one variable in the group
+ Dvar_output[(group_name,var)] = np.squeeze(theFile.groups[group_name].variables[suffix][:,:,:,:], axis=Ltosqueeze)
+ else:
+ Dvar_output[group_name] = np.squeeze(theFile.groups[group_name].variables[suffix][:,:,:,:], axis=Ltosqueeze)
+ elif theFile.groups[group_name].type == 'MASK': # Budget MASK type
+ shapeVar = theFile.groups[group_name].variables[suffix].shape
+ Ltosqueeze=[] # Build a tuple with the number of the axis which are 0 dimensions to be removed by np.squeeze
+ if shapeVar[0]==1: Ltosqueeze.append(0)
+ if shapeVar[1]==1: Ltosqueeze.append(1)
+ if shapeVar[2]==1: Ltosqueeze.append(2)
+ Ltosqueeze=tuple(Ltosqueeze)
+ if len(theFile.groups[group_name].variables.keys()) > 1: # If more than one variable in the group
+ Dvar_output[(group_name,var)] = np.squeeze(theFile.groups[group_name].variables[suffix][:,:,:], axis=Ltosqueeze).T
+ else:
+ Dvar_output[group_name] = np.squeeze(theFile.groups[group_name].variables[suffix][:,:,:], axis=Ltosqueeze).T
else:
raise NameError("Type de groups variables not implemented in read_MNHfile.py")
return Dvar_output