diff --git a/src/LIB/Python/Panel_Plot.py b/src/LIB/Python/Panel_Plot.py
index b2f04b53ca69eae68a40eca69199cd4987049ce6..f063e48c7f6c0a96f4762e4378ab6567525c1113 100644
--- a/src/LIB/Python/Panel_Plot.py
+++ b/src/LIB/Python/Panel_Plot.py
@@ -315,7 +315,7 @@ class PanelPlot():
"""
XY (multiple)-lines plot
Arguments :
- - Lzz : List of z coordinates variable [1D]
+ - Lzz : List of z coordinates variable [1D] #TODO : Renommer argument Lvar en Lxx et Lzz en Lyy et ajouter Lfacconv pour les deux axes. Impact tous les cas test avec lignes X/Y
- Lvar : List of variables to plot [1D]
- Lxlab : List of x-axis label
- Lylab : List of y-axis label
diff --git a/src/LIB/Python/read_MNHfile.py b/src/LIB/Python/read_MNHfile.py
index 4279599fb48fb9c67ffc640c157c3088462d163f..5158f4b67218b64a16fb1e4335f993aed85ed249 100644
--- a/src/LIB/Python/read_MNHfile.py
+++ b/src/LIB/Python/read_MNHfile.py
@@ -143,47 +143,87 @@ def read_TIMESfiles_54(theFile, ifile, Dvar_input, Dvar_output):
return Dvar_output #Return the dic of [files][variables]
def read_TIMESfiles_55(theFile, ifile, Dvar_input, Dvar_output, removeHALO=False):
+ """
+ Read variables from MNH MASDEV >= 5.5.0
+ Parameters :
+ - Dvar_input : dictionnary of {file : var}. var can be either
+ - a string = the variable name
+ - or a tuple of ('group_name','var_name')
+ If the variable desired is in a group_name and the group_name is not specified, it is assumed group_name = variable_name
+ except for specific variable as (cart, neb, clear, cs1, cs2, cs3) type
+ Return :
+ Dvar_output : dictionnary of Dvar_output[ifile][variables or tuple (group,variables) if the user specified a tuple]
+ """
Dvar_output[ifile] = {} #initialize dic for each files
-
- for var in Dvar_input[ifile]: #For each var
+ def read_var(theFile, Dvar_output, var):
suffix, var_name = remove_PROC(var)
-
try: # NetCDF4 Variables
n_dim = theFile.variables[var_name].ndim
# First, test if the variable is a dimension/coordinate variable
if (n_dim ==0): # Scalaires variable
- Dvar_output[ifile][var_name] = theFile.variables[var_name][0].data
+ Dvar_output[var_name] = theFile.variables[var_name][0].data
else:
if(removeHALO):
if n_dim == 1:
- Dvar_output[ifile][var_name] = theFile.variables[var_name][1:-1]
+ Dvar_output[var_name] = theFile.variables[var_name][1:-1]
elif n_dim == 2:
- Dvar_output[ifile][var_name] = theFile.variables[var_name][1:-1,1:-1]
+ Dvar_output[var_name] = theFile.variables[var_name][1:-1,1:-1]
else:
raise NameError("Lecture des variables de dimension sup a 2 pas encore implementees pour fichiers .000")
else:
if n_dim == 1:
- Dvar_output[ifile][var_name] = theFile.variables[var_name][:]
+ Dvar_output[var_name] = theFile.variables[var_name][:]
elif n_dim == 2:
- Dvar_output[ifile][var_name] = theFile.variables[var_name][:,:]
+ Dvar_output[var_name] = theFile.variables[var_name][:,:]
else:
raise NameError("Lecture des variables de dimension sup a 2 pas encore implementees pour fichiers .000")
- except KeyError: # NetCDF4 Group
- if theFile.groups[var_name].type == 'TLES' : #LES type
- # Build the true name of the groups.variables :
- whites = ' '*(17 - len('(cart)') - len(var_name)) # TODO : a adapter selon le type de la variable cart ou autres
- Dvar_output[ifile][var] = theFile.groups[var].variables[var + whites + '(cart)'][:,:].T
- elif theFile.groups[var_name].type == 'CART': # Budget CART type
- shapeVar = theFile.groups[var_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)
- if shapeVar[3]==1: Ltosqueeze.append(3)
- Ltosqueeze=tuple(Ltosqueeze)
- Dvar_output[ifile][var_name] = np.squeeze(theFile.groups[var_name].variables[suffix][:,:,:,:], axis=Ltosqueeze)
+ except KeyError: # NetCDF4 Group not specified by the user
+ if '(cart)' in var_name or '(neb)' in var_name or '(clear)' in var_name or '(cs1)' in var_name or '(cs2)' in var_name or '(cs3)' in var_name:
+ # If users specify the complete variable name with averaging type
+ group_name = get_group_from_varname(var_name)
else:
- raise NameError("Type de groups variables not implemented in read_MNHfile.py")
+ group_name = var_name
+ read_from_group(theFile, Dvar_output, var, var)
+ 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
+ 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
+ try: #By default, most variables read are 2D cart and user does not specify it in the variable name
+ whites = ' '*(17 - len('(cart)') - len(var_name))
+ Dvar_output[var] = theFile.groups[var].variables[var + whites + '(cart)'][:,:].T
+ except:
+ try: #Variable 3D sv,time_les, level_les
+ Dvar_output[var] = theFile.groups[group_name].variables[var][:,:,:]
+ except:
+ try: #Variable 2D with type of variable specified (cart, neb, clear, cs1, cs2, cs3)
+ Dvar_output[var] = theFile.groups[group_name].variables[var][:,:].T
+ except ValueError: # Variable 1D
+ Dvar_output[var] = theFile.groups[group_name].variables[var][:]
+ elif theFile.groups[group_name].type == 'CART': # Budget CART 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)
+ if shapeVar[3]==1: Ltosqueeze.append(3)
+ Ltosqueeze=tuple(Ltosqueeze)
+ Dvar_output[group_name] = np.squeeze(theFile.groups[group_name].variables[suffix][:,:,:,:], axis=Ltosqueeze)
+ else:
+ raise NameError("Type de groups variables not implemented in read_MNHfile.py")
+ return Dvar_output
+ for var in Dvar_input[ifile]: #For each var
+ if type(var) == tuple:
+ Dvar_output[ifile] = read_from_group(theFile, Dvar_output, var[0], var[1])
+ else:
+ Dvar_output[ifile] = read_var(theFile, Dvar_output, var)
+
return Dvar_output #Return the dic of [files][variables]
def list_size1(n_dim, named_dim):
@@ -198,7 +238,7 @@ def list_size1(n_dim, named_dim):
def remove_PROC(var):
if '___PROC' in var:
var_name = var[:-8]
- suffix = "" # No need of suffix for MNHVERSION < 550 (suffix is for NetCDF4 group
+ suffix = "" # No need of suffix for MNHVERSION < 550 (suffix is for NetCDF4 group)
elif '___ENDF' in var or '___INIF' in var or '___AVEF' in var:
var_name = var[:-7]
suffix = var[-4:]
@@ -206,3 +246,12 @@ def remove_PROC(var):
var_name = var
suffix = ''
return suffix, var_name
+
+def get_group_from_varname(var):
+ group_name=''
+ for i in range(len(var)):
+ if var[i] is not ' ':
+ group_name+=var[i]
+ else: # As soon as the caracter is a blank, the group variable is set
+ break
+ return group_name