diff --git a/src/LIB/Python/Panel_Plot.py b/src/LIB/Python/Panel_Plot.py
index 2072d1cf9225c27f14b79849e8b11e5e49885ce8..e4588ddde7852b734d0972de097edcbf41bf894f 100644
--- a/src/LIB/Python/Panel_Plot.py
+++ b/src/LIB/Python/Panel_Plot.py
@@ -9,7 +9,7 @@ MNH_LIC for details. version 1.
@author: 07/2021 Quentin Rodier
"""
import matplotlib as mpl
-#mpl.use('Agg')
+# mpl.use('Agg')
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.colors import ListedColormap
@@ -17,9 +17,10 @@ import numpy as np
import cartopy
import cartopy.feature as cfeature
+
class PanelPlot():
-
- def __init__(self, nb_l, nb_c, Lfigsize, bigtitle, titlepad=40, minmaxpad=1.03, timepad=-0.06, lateralminmaxpad=0.86,
+
+ def __init__(self, nb_l, nb_c, Lfigsize, bigtitle, bigtitlepad=0.95, titlepad=40, minmaxpad=1.03, timepad=-0.06, lateralminmaxpad=0.86,
labelcolorbarpad=6.0, colorbaraspect=20, colorbarpad=0.04, tickspad=0.8,
minmaxTextSize=10, bigtitleSize=13, titleSize=12, legendSize=10,
xlabelSize=11, ylabelSize=11, timeSize=11, cbTicksLabelSize=11, cbTitleSize=11, xyTicksLabelSize=10, figBoxLinewidth=1,
@@ -31,6 +32,7 @@ class PanelPlot():
self.nb_c = nb_c # Panel number of rows
self.nb_graph = 0 # New independent graph within the subplot
+ self.bigtitlepad = bigtitlepad # Panel title vertical position
self.titlepad = titlepad # Title pad (vertical shift) from graph
self.tickspad = tickspad # Ticks pad (between ticks and axis label)
self.minmaxpad = minmaxpad # Min/Max print pad (vertical shift)
@@ -56,873 +58,1007 @@ class PanelPlot():
self.xyTicksLength = xyTicksLength # Ticks length
# Initialization of the panel plots
- self.fig = plt.figure(figsize=(self.Lfigsize[0],self.Lfigsize[1]))
+ self.fig = plt.figure(figsize=(self.Lfigsize[0], self.Lfigsize[1]))
self.fig.set_dpi(125)
- self.fig.suptitle(self.bigtitle,fontsize=bigtitleSize)
+ self.fig.suptitle(self.bigtitle, fontsize=self.bigtitleSize, y=self.bigtitlepad)
def save_graph(self, iplt, fig, fig_name='tempgraph'):
- """
- Create a temporary png file of the panel plot which can be converted to PDF
- """
- self.iplt = iplt
- self.fig = fig
- self.fig_name=fig_name # .png figure prefix name
-
- self.fig.savefig(self.fig_name+str(self.iplt))
- self.iplt+=1
- return self.iplt
-
- def draw_Backmap(self,drawCoastLines, ax, projo):
- """
- Handle drawing of the background plot (coastlines, departements, grid lines and labels)
- """
- self.drawCoastLines = drawCoastLines
- self.projo = projo
-
- # Grid lines and labels
- if 'PlateCarree' in str(projo):
+ """
+ Create a temporary png file of the panel plot which can be converted to PDF
+ """
+ self.iplt = iplt
+ self.fig = fig
+ self.fig_name = fig_name # .png figure prefix name
+
+ self.fig.savefig(self.fig_name + str(self.iplt))
+ self.iplt += 1
+ return self.iplt
+
+ def draw_Backmap(self, drawCoastLines, ax, projo):
+ """
+ Handle drawing of the background plot (coastlines, departements, grid lines and labels)
+ """
+ self.drawCoastLines = drawCoastLines
+ self.projo = projo
+
+ # Grid lines and labels
gl = ax.gridlines(crs=self.projo, draw_labels=True, linewidth=1, color='gray')
if float(cartopy.__version__[:4]) >= 0.18:
- gl.top_labels = False
- gl.right_labels = False
+ from cartopy.mpl.ticker import (LatitudeLocator, LongitudeLocator,LongitudeFormatter, LatitudeFormatter)
+ gl.top_labels = False
+ gl.right_labels = False
+ gl.xlines = True
+ gl.ylines = True
+ gl.xlocator = LongitudeLocator()
+ gl.ylocator = LatitudeLocator()
+ gl.xformatter = LongitudeFormatter()
+ gl.yformatter = LatitudeFormatter()
else:
- gl.xlabels_top = False
- gl.ylabels_right = False
-
- # Coastlines
- if self.drawCoastLines and 'GeoAxes' in str(type(ax)):
- ax.coastlines(resolution='10m')
-
- # Countries border
- ax.add_feature(cfeature.BORDERS)
- ax.add_feature(cfeature.LAKES, alpha=0.7)
-
- def addWhitecm(self, colormap_in, nb_level,whiteTop=False):
+ gl.xlabels_top = False
+ gl.ylabels_right = False
+ gl.xlabel_style = {'size': self.xyTicksLabelSize, 'color': 'black'}
+ gl.ylabel_style = {'size': self.xyTicksLabelSize, 'color': 'black'}
+
+ # Coastlines
+ if self.drawCoastLines and 'GeoAxes' in str(type(ax)):
+ ax.coastlines(resolution='10m', color='black', linewidth=1)
+
+ # Countries border
+ ax.add_feature(cfeature.BORDERS)
+ ax.add_feature(cfeature.LAKES, alpha=0.7)
+
+ def addWhitecm(self, colormap_in, nb_level, whiteTop=False):
"""
Add a white color at the top (whiteTop=True) or bottom of the colormap w.r.t. the number of independent colors used
"""
color_map = cm.get_cmap(colormap_in, 256)
newcolor_map = color_map(np.linspace(0, 1, 256))
- whites = np.array([1, 1, 1, 1]) #RBG code + opacity
+ whites = np.array([1, 1, 1, 1]) # RBG code + opacity
if whiteTop:
- for i in range(int(256/nb_level)): newcolor_map[-i, :] = whites
+ for i in range(int(256 / nb_level)):
+ newcolor_map[-i, :] = whites
else:
- for i in range(int(256/nb_level)): newcolor_map[:i, :] = whites
+ for i in range(int(256 / nb_level)):
+ newcolor_map[:i, :] = whites
newcmp = ListedColormap(newcolor_map)
return newcmp
-
def set_Title(self, ax, i, title, Lid_overlap, xlab, ylab):
- """
- Handle top title of each graph
- Parameters :
- - titlepad : global attribute for vertical shift placement w.r.t the graph
- """
- self.ax = ax
- self.title = title
- self.Lid_overlap = Lid_overlap
- self.i = i
- #self.ax[self.i].set_xlabel("test", fontweight='bold')
- if not Lid_overlap:
- self.ax[self.i].set_title(title, pad=self.titlepad, fontsize=self.titleSize)
- else: # If graph overlap, title is concatenated
- new_title = self.ax[self.i].get_title() + ' and ' + title
- self.ax[self.i].set_title(new_title, pad=self.titlepad, fontsize=self.titleSize)
+ """
+ Handle top title of each graph
+ Parameters :
+ - titlepad : global attribute for vertical shift placement w.r.t the graph
+ """
+ self.ax = ax
+ self.title = title
+ self.Lid_overlap = Lid_overlap
+ self.i = i
+ #self.ax[self.i].set_xlabel("test", fontweight='bold')
+ if not Lid_overlap:
+ self.ax[self.i].set_title(title, pad=self.titlepad, fontsize=self.titleSize)
+ else: # If graph overlap, title is concatenated
+ new_title = self.ax[self.i].get_title() + ' and ' + title
+ self.ax[self.i].set_title(new_title, pad=self.titlepad, fontsize=self.titleSize)
def set_xlim(self, ax, i, xlim):
- """
- Handle x limits plotted if necessary
- """
- self.ax = ax
- self.xlim = xlim
- self.i = i
-
- self.ax[self.i].set_xlim(xlim[0],xlim[1])#, fontsize=self.xlabelSize)
-
+ """
+ Handle x limits plotted if necessary
+ """
+ self.ax = ax
+ self.xlim = xlim
+ self.i = i
+
+ self.ax[self.i].set_xlim(xlim[0], xlim[1]) # , fontsize=self.xlabelSize)
+
def set_ylim(self, ax, i, ylim):
- """
- Handle x limits plotted if necessary
- """
- self.ax = ax
- self.ylim = ylim
- self.i = i
-
- self.ax[self.i].set_ylim(ylim[0],ylim[1])#, fontsize=self.ylabelSize)
+ """
+ Handle x limits plotted if necessary
+ """
+ self.ax = ax
+ self.ylim = ylim
+ self.i = i
+
+ self.ax[self.i].set_ylim(ylim[0], ylim[1]) # , fontsize=self.ylabelSize)
def set_XYaxislab(self, ax, i, xlab, ylab):
- """
- Handle x and y axis labels
- """
- self.ax = ax
- self.xlab = xlab
- self.ylab = ylab
- self.i = i
-
- # This handing label is a known issue with GeoAxes of cartopy
- # https://stackoverflow.com/questions/35479508/cartopy-set-xlabel-set-ylabel-not-ticklabels
- # https://github.com/SciTools/cartopy/issues/1332
- if 'GeoAxes' in str(type(self.ax[self.i])):
- self.ax[self.i].text(-0.11, 0.45, ylab, verticalalignment='top', horizontalalignment='left',
- rotation='vertical', rotation_mode='anchor', transform=self.ax[self.i].transAxes, color='black', fontsize=self.ylabelSize)
- self.ax[self.i].text(0.45, -0.06, xlab, verticalalignment='top', horizontalalignment='left',
- rotation='horizontal', rotation_mode='anchor', transform=self.ax[self.i].transAxes, color='black', fontsize=self.xlabelSize)
- else:
- self.ax[self.i].set_xlabel(xlab, fontsize=self.xlabelSize, labelpad=0.1)
- self.ax[self.i].set_ylabel(ylab, fontsize=self.ylabelSize, labelpad=0.1)
-
+ """
+ Handle x and y axis labels
+ """
+ self.ax = ax
+ self.xlab = xlab
+ self.ylab = ylab
+ self.i = i
+
+ # This handing label is a known issue with GeoAxes of cartopy
+ # https://stackoverflow.com/questions/35479508/cartopy-set-xlabel-set-ylabel-not-ticklabels
+ # https://github.com/SciTools/cartopy/issues/1332
+ if 'GeoAxes' in str(type(self.ax[self.i])):
+ self.ax[self.i].text(-0.11, 0.45, ylab, verticalalignment='top', horizontalalignment='left',
+ rotation='vertical', rotation_mode='anchor', transform=self.ax[self.i].transAxes, color='black', fontsize=self.ylabelSize)
+ self.ax[self.i].text(0.45, -0.06, xlab, verticalalignment='top', horizontalalignment='left',
+ rotation='horizontal', rotation_mode='anchor', transform=self.ax[self.i].transAxes, color='black', fontsize=self.xlabelSize)
+ else:
+ self.ax[self.i].set_xlabel(xlab, fontsize=self.xlabelSize, labelpad=0.1)
+ self.ax[self.i].set_ylabel(ylab, fontsize=self.ylabelSize, labelpad=0.1)
+
def addLine(self, ax, beg_coord, end_coord, color='black', linewidth=0.2):
- self.ax = ax
- self.beg_coord = beg_coord
- self.end_coord = end_coord
- self.color = color
- self.linewidth = linewidth
-
- x1, y1 = [self.beg_coord[0],self.end_coord[0]], [self.beg_coord[1], self.end_coord[1]]
- ax.plot(x1, y1,color=self.color,linewidth=self.linewidth)
+ self.ax = ax
+ self.beg_coord = beg_coord
+ self.end_coord = end_coord
+ self.color = color
+ self.linewidth = linewidth
+
+ x1, y1 = [self.beg_coord[0], self.end_coord[0]], [self.beg_coord[1], self.end_coord[1]]
+ ax.plot(x1, y1, color=self.color, linewidth=self.linewidth)
def print_minmax(self, var, title):
print(str(title) + " min = " + str(np.nanmin(var)) + " max = " + str(np.nanmax(var)))
def set_minmaxText(self, ax, i, var, title, Lid_overlap, facconv):
- """
- Show min and max value Text in the plot
- If overlap variable, text is align to the right
- TODO : handle more than 2 overlap variables
- """
- self.ax = ax
- self.var = var
- self.i = i
- self.title = title
- self.facconv = facconv
-
- strtext = " min = " + "{:.3e}".format(np.nanmin(var*facconv)) + " max = " + "{:.3e}".format(np.nanmax(var*facconv))
- if not Lid_overlap:
- self.ax[self.i].text(0.01, self.minmaxpad, strtext, verticalalignment='top', horizontalalignment='left',
- transform=self.ax[self.i].transAxes, color='black', fontsize=self.minmaxTextSize)
- else:
- self.ax[self.i].text(self.lateralminmaxpad, self.minmaxpad, strtext, verticalalignment='top', horizontalalignment='right',
- transform=self.ax[self.i].transAxes, color='black', fontsize=self.minmaxTextSize)
- # Print to help choose min/max value for ticks
- self.print_minmax(var*facconv, title)
-
+ """
+ Show min and max value Text in the plot
+ If overlap variable, text is align to the right
+ TODO : handle more than 2 overlap variables
+ """
+ self.ax = ax
+ self.var = var
+ self.i = i
+ self.title = title
+ self.facconv = facconv
+
+ strtext = " min = " + "{:.3e}".format(np.nanmin(var * facconv)) + " max = " + "{:.3e}".format(np.nanmax(var * facconv))
+ if not Lid_overlap:
+ self.ax[self.i].text(0.01, self.minmaxpad, strtext, verticalalignment='top', horizontalalignment='left',
+ transform=self.ax[self.i].transAxes, color='black', fontsize=self.minmaxTextSize)
+ else:
+ self.ax[self.i].text(self.lateralminmaxpad, self.minmaxpad, strtext, verticalalignment='top', horizontalalignment='right',
+ transform=self.ax[self.i].transAxes, color='black', fontsize=self.minmaxTextSize)
+ # Print to help choose min/max value for ticks
+ self.print_minmax(var * facconv, title)
+
def showTimeText(self, ax, i, timetxt):
- """
- Show time validity
- """
- self.ax = ax
- self.i = i
- self.timetxt = timetxt
-
- strtext = "Time = " + timetxt
- self.ax[self.i].text(0.0, self.timepad, strtext, verticalalignment='top', horizontalalignment='left',
- transform=self.ax[self.i].transAxes, color='black', fontsize=self.timeSize)
-
-
- def psectionV(self, Lxx=[], Lzz=[], Lvar=[], Lxlab=[], Lylab=[], Ltitle=[], Lminval=[], Lmaxval=[],
- Lstep=[], Lstepticks=[], Lcolormap=[], Lcbarlabel=[], LcolorLine=[],
- Lfacconv=[], ax=[], Lid_overlap=[], colorbar=True, orog=[], Lxlim=[], Lylim=[], Ltime=[], Lpltype=[], LaddWhite_cm=[], LwhiteTop=[]):
- """
- Vertical cross section plot
- Parameters :
- - Lxx : List of x or y coordinate variable or time axis
- - Lzz : List of z coordinates variable
- - Lvar : List of variables to plot
- - 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
- - Ltime : List of time (validity)
- - Ltitle : List of sub-title
- - Lminval: List of minimum value for each colorbar
- - Lmaxval: List of maximum value for each colorbar
- - Lstep : List of color-steps for each colorbar
- - Lstepticks : List of value of labels for each colorbar
- - Lcolormap : List of colormap
- - LcolorLine : List of colors for colors arg of contour (color line only)
- - Lcbarlabel : List of colorbar label legend (units)
- - Lfacconv : List of factors for unit conversion of each variables
- - 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
- - Lpltype : List of types of plot 'cf' or 'c'. cf=contourf, c=contour (lines only)
- - colorbar : show colorbar or not
- - LaddWhite_cm : List of boolean to add white color to a colormap at the last bottom (low value) tick colorbar
- - LwhiteTop : List of boolean to add the white color at the first top (high value). If false, the white is added at the bottom if Laddwhite_cm=T
- - orog : Orography variable
- """
- self.ax = ax
- firstCall = (len(self.ax) == 0)
-
- # Initialize default value w.r.t to the number of plots
-# D={'Lxlab':Lxlab, 'Lylab':Lylab, 'Ltitle':Ltitle,'Lminval':Lminval, 'Lmaxval':Lmaxval,
+ """
+ Show time validity
+ """
+ self.ax = ax
+ self.i = i
+ self.timetxt = timetxt
+
+ strtext = "Time = " + timetxt
+ self.ax[self.i].text(0.0, self.timepad, strtext, verticalalignment='top', horizontalalignment='left',
+ transform=self.ax[self.i].transAxes, color='black', fontsize=self.timeSize)
+
+ def psectionV(self, Lxx=[], Lzz=[], Lvar=[], Lxlab=[], Lylab=[], Ltitle=[], Lminval=[], Lmaxval=[],
+ Lstep=[], Lstepticks=[], Lcolormap=[], Lcbarlabel=[], LcolorLine=[], Lcbformatlabel=[], Llinewidth=[],
+ Lfacconv=[], ax=[], Lid_overlap=[], colorbar=True, orog=[], Lxlim=[], Lylim=[], Ltime=[], Lpltype=[], LaddWhite_cm=[], LwhiteTop=[]):
+ """
+ Vertical cross section plot
+ Parameters :
+ - Lxx : List of x or y coordinate variable or time axis
+ - Lzz : List of z coordinates variable
+ - Lvar : List of variables to plot
+ - 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
+ - Ltime : List of time (validity)
+ - Ltitle : List of sub-title
+ - Lminval: List of minimum value for each colorbar
+ - Lmaxval: List of maximum value for each colorbar
+ - Lstep : List of color-steps for each colorbar
+ - Lstepticks : List of value of labels for each colorbar
+ - Lcolormap : List of colormap
+ - Llinewidth : List of lines thickness of contour
+ - LcolorLine : List of colors for colors arg of contour (color line only)
+ - Lcbarlabel : List of colorbar label legend (units)
+ - Lfacconv : List of factors for unit conversion of each variables
+ - 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
+ - Lpltype : List of types of plot 'cf' or 'c'. cf=contourf, c=contour (lines only)
+ - colorbar : show colorbar or not
+ - LaddWhite_cm : List of boolean to add white color to a colormap at the last bottom (low value) tick colorbar
+ - LwhiteTop : List of boolean to add the white color at the first top (high value). If false, the white is added at the bottom if Laddwhite_cm=T
+ - Lcbformatlabel: List of boolean to reduce the format to exponential 1.1E+02 format colorbar label
+ - orog : Orography variable
+ """
+ self.ax = ax
+ firstCall = (len(self.ax) == 0)
+
+ # Initialize default value w.r.t to the number of plots
+# D={'Lxlab':Lxlab, 'Lylab':Lylab, 'Ltitle':Ltitle,'Lminval':Lminval, 'Lmaxval':Lmaxval,
# 'Lstep':Lstep, 'Lstepticks':Lstepticks, 'Lcolormap':Lcolormap, 'Lcbarlabel':Lcbarlabel, 'Lfacconv':Lfacconv, 'Ltime':Ltime,
# 'LaddWhite_cm':LaddWhite_cm, 'Lpltype':Lpltype}
# D = initialize_default_val(Lvar, D)
- # Default values
- if not Lfacconv: Lfacconv = [1.0]*len(Lvar)
- if not Lcolormap and not LcolorLine: Lcolormap=['gist_rainbow_r']*len(Lvar) # If no color given, a cmap is given
- 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 LwhiteTop: LwhiteTop=[False]*len(Lvar)
- if not Lylab: Lylab = ['']*len(Lvar)
- if not Lxlab: Lxlab = ['']*len(Lvar)
- # Add an extra percentage of the top max value for forcing the colorbar show the true user maximum value (correct a bug)
- 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
-
- # On all variables to plot
- for i,var in enumerate(Lvar):
- if firstCall: #1st call
- iax = i
- 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)
- 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
-
- # Colors normalization
- norm = mpl.colors.Normalize(vmax=Lmaxval[i], vmin=Lminval[i])
-
- # Print min/max (stout and on plot)
- self.set_minmaxText(self.ax, iax, var, Ltitle[i], Lid_overlap, Lfacconv[i])
-
- # Print time validity
- if Ltime: self.showTimeText(self.ax, iax, str(Ltime[i]))
-
- # Number of contours level
- if not Lstep[i]: # Default value of number of steps is 20
- Lstep[i] = (Lmaxval[i] - Lminval[i])/20
- Lstepticks[i] = Lstep[i]
-
- levels_contour = np.arange(Lminval[i],Lmaxval[i],step=Lstep[i])
-
- # Add White to colormap
- if LaddWhite_cm[i] and Lcolormap: Lcolormap[i]=self.addWhitecm(Lcolormap[i], len(levels_contour), LwhiteTop[i])
-
- # Plot
- if Lpltype[i]=='c': # Contour
- if LcolorLine:
- cf = self.ax[iax].contour(Lxx[i], Lzz[i], var*Lfacconv[i], levels=levels_contour,
- norm=norm, vmin=Lminval[i], vmax=Lmaxval[i], colors=LcolorLine[i], linewidths=0.1)
- else:
- cf = self.ax[iax].contour(Lxx[i], Lzz[i], var*Lfacconv[i], levels=levels_contour,
- norm=norm, vmin=Lminval[i], vmax=Lmaxval[i], cmap=Lcolormap[i], linewidths=0.1)
- else: # Contourf
- cf = self.ax[iax].contourf(Lxx[i], Lzz[i], var*Lfacconv[i], levels=levels_contour,
- norm=norm, vmin=Lminval[i], vmax=Lmaxval[i], cmap=Lcolormap[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])
-
- # Ticks label
- self.ax[iax].tick_params(axis='both', labelsize=self.xyTicksLabelSize, width=self.xyTicksWidth, length=self.xyTicksLength, pad=self.tickspad)
-
- # Bounding box of the plot line width
- for axis in ['top','bottom','left','right']:
- self.ax[iax].spines[axis].set_linewidth(self.figBoxLinewidth)
-
- # 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
-
- # Color label on contour-line
- if Lpltype[i]=='c': # Contour
- self.ax[iax].clabel(cf, fontsize=self.cbTicksLabelSize)
- #self.ax[iax].clabel(cf, levels=np.arange(Lminval[i],Lmaxval[i],step=Lstep[i]), fontsize=self.cbTicksLabelSize) #TODO bug, levels not recognized
-
- #Filling area under topography
- if not orog==[]:
- self.ax[iax].fill_between(Lxx[i][0,:], orog, color='black', linewidth=0.2)
-
- # 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.ax.set_title(Lcbarlabel[i], pad=self.labelcolorbarpad, loc='left', fontsize=self.cbTitleSize) # This creates a new AxesSubplot only for the colorbar y=0 ==> location at the bottom
-
- return self.fig
+ # Default values
+ if not Lfacconv:
+ Lfacconv = [1.0] * len(Lvar)
+ if not Lcolormap and not LcolorLine:
+ Lcolormap = ['gist_rainbow_r'] * len(Lvar) # If no color given, a cmap is given
+ 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 LwhiteTop:
+ LwhiteTop = [False] * len(Lvar)
+ if not Lylab:
+ Lylab = [''] * len(Lvar)
+ if not Lxlab:
+ Lxlab = [''] * len(Lvar)
+ if not Lcbformatlabel:
+ Lcbformatlabel = [False] * len(Lvar)
+ if not Llinewidth:
+ Llinewidth = [1.0] * len(Lvar)
+
+ # Add an extra percentage of the top max value for forcing the colorbar show the true user maximum value (correct a bug)
+ 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
+
+ # On all variables to plot
+ for i, var in enumerate(Lvar):
+ if firstCall: # 1st call
+ iax = i
+ 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)
+ 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
+
+ # Colors normalization
+ norm = mpl.colors.Normalize(vmax=Lmaxval[i], vmin=Lminval[i])
+
+ # Print min/max (stout and on plot)
+ self.set_minmaxText(self.ax, iax, var, Ltitle[i], Lid_overlap, Lfacconv[i])
+
+ # Print time validity
+ if Ltime:
+ self.showTimeText(self.ax, iax, str(Ltime[i]))
+
+ # Number of contours level
+ if not Lstep[i]: # Default value of number of steps is 20
+ Lstep[i] = (Lmaxval[i] - Lminval[i]) / 20
+ Lstepticks[i] = Lstep[i]
+
+ levels_contour = np.arange(Lminval[i], Lmaxval[i], step=Lstep[i])
+
+ # Add White to colormap
+ if LaddWhite_cm[i] and Lcolormap:
+ Lcolormap[i] = self.addWhitecm(Lcolormap[i], len(levels_contour), LwhiteTop[i])
+
+ # Plot
+ if Lpltype[i] == 'c': # Contour
+ if LcolorLine:
+ cf = self.ax[iax].contour(Lxx[i], Lzz[i], var * Lfacconv[i], levels=levels_contour,
+ norm=norm, vmin=Lminval[i], vmax=Lmaxval[i], colors=LcolorLine[i], linewidths=Llinewidth[i])
+ else:
+ cf = self.ax[iax].contour(Lxx[i], Lzz[i], var * Lfacconv[i], levels=levels_contour,
+ norm=norm, vmin=Lminval[i], vmax=Lmaxval[i], cmap=Lcolormap[i], linewidths=Llinewidth[i])
+ else: # Contourf
+ cf = self.ax[iax].contourf(Lxx[i], Lzz[i], var * Lfacconv[i], levels=levels_contour,
+ norm=norm, vmin=Lminval[i], vmax=Lmaxval[i], cmap=Lcolormap[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])
+
+ # Ticks label
+ self.ax[iax].tick_params(
+ axis='both',
+ labelsize=self.xyTicksLabelSize,
+ width=self.xyTicksWidth,
+ length=self.xyTicksLength,
+ pad=self.tickspad)
+
+ # Bounding box of the plot line width
+ for axis in ['top', 'bottom', 'left', 'right']:
+ self.ax[iax].spines[axis].set_linewidth(self.figBoxLinewidth)
+
+ # X/Y Axis limits value
+ if Lxlim:
+ try:
+ self.set_xlim(self.ax, iax, Lxlim[i])
+ except BaseException:
+ pass
+ if Lylim:
+ try:
+ self.set_ylim(self.ax, iax, Lylim[i])
+ except BaseException:
+ pass
+
+ # Color label on contour-line
+ if Lpltype[i] == 'c': # Contour
+ self.ax[iax].clabel(cf, fontsize=self.cbTicksLabelSize)
+ # self.ax[iax].clabel(cf,
+ # levels=np.arange(Lminval[i],Lmaxval[i],step=Lstep[i]),
+ # fontsize=self.cbTicksLabelSize) #TODO bug, levels not recognized
+
+ # Filling area under topography
+ if not orog == []:
+ if Lxx[i].ndim == 1:
+ self.ax[iax].fill_between(Lxx[i], orog, color='black', linewidth=0.2)
+ else:
+ self.ax[iax].fill_between(Lxx[i][0, :], orog, color='black', linewidth=0.2)
+
+ # 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.ax.tick_params(labelsize=self.cbTicksLabelSize)
+ # This creates a new AxesSubplot only for the colorbar y=0 ==> location at the bottom
+ cb.ax.set_title(Lcbarlabel[i], pad=self.labelcolorbarpad, loc='left', fontsize=self.cbTitleSize)
+ if Lcbformatlabel[i]:
+ cb.ax.set_yticklabels(["{:.1E}".format(i) for i in cb.get_ticks()])
+
+ return self.fig
def pXY_lines(self, Lxx=[], Lyy=[], Lxlab=[], Lylab=[], Ltitle=[], Llinetype=[], Llinewidth=[],
- Llinecolor=[], Llinelabel=[], LfacconvX=[], LfacconvY=[], ax=[], id_overlap=None, Lxlim=[],
- Lylim=[], Ltime=[], LaxisColor=[]):
- """
- XY (multiple)-lines plot
- Parameters :
- - Lxx : List of variables to plot or coordinates along the X axis
- - Lyy : List of variables to plot or coordinates along the Y axis
- - 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
- - Ltime : List of time (validity)
- - Ltitle : List of sub-title
- - Llinewidth : List of lines thickness
- - Llinetype : List of line types
- - Lcolorlines: List of color lines
- - Llinelabel : List of legend label lines
- - LfacconvX/Y: List of factors for unit conversion of the variables/coordinates to plot on X and Y axis
- - 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
- - LaxisColor : List of colors for multiple x-axis overlap
- """
- self.ax = ax
- firstCall = (len(self.ax) == 0)
- # Defaults value convert to x number of variables list
- if not LfacconvX: LfacconvX = [1.0]*len(Lxx)
- if not LfacconvY: LfacconvY = [1.0]*len(Lxx)
- if not Llinewidth: Llinewidth = [1.0]*len(Lxx)
- if not Llinecolor: Llinecolor = ['blue']*len(Lxx)
- if not Llinetype: Llinetype = ['-']*len(Lxx)
- if not Llinelabel: Llinelabel = ['']*len(Lxx)
- if not LaxisColor: LaxisColor = ['black']*len(Lxx)
- if not Lylab: Lylab = ['']*len(Lxx)
- if not Lxlab: Lxlab = ['']*len(Lxx)
-
- if firstCall: # 1st call
- iax = 0
- self.ax.append(self.fig.add_subplot(self.nb_l,self.nb_c,1, label='graph axe x down'))
- self.nb_graph+=1
- elif id_overlap: # overlapping plot with a different x-axis
- self.ax.append(self.fig.add_subplot(self.nb_l,self.nb_c,self.nb_graph, label='graph axe x top',frame_on=False))
- iax = len(self.ax)-1
- else: # existing ax with no overlapping (graph appended to existing panel)
- 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
-
- # On all variables to plot
- for i,var in enumerate(Lxx):
- # Print time validity
- if Ltime: self.showTimeText(self.ax, iax, str(Ltime[i]))
-
- # Plot
- cf = self.ax[iax].plot(Lxx[i]*LfacconvX[i], Lyy[i]*LfacconvY[i], color=Llinecolor[i], ls=Llinetype[i],
- label=Llinelabel[i], linewidth=Llinewidth[i])
- # Legend
- #TODO : Handling legend with overlap two axis lines in the same box. For now, placement is by hand
- if not id_overlap:
- self.ax[iax].legend(loc='upper right', bbox_to_anchor=(1, 0.95),fontsize=self.legendSize)
- else:
- self.ax[iax].legend(loc='upper right', bbox_to_anchor=(1, 0.90),fontsize=self.legendSize)
+ Llinecolor=[], Llinelabel=[], LfacconvX=[], LfacconvY=[], ax=[], id_overlap=None, Lxlim=[],
+ Lylim=[], Ltime=[], LaxisColor=[], LlocLegend=[]):
+ """
+ XY (multiple)-lines plot
+ Parameters :
+ - Lxx : List of variables to plot or coordinates along the X axis
+ - Lyy : List of variables to plot or coordinates along the Y axis
+ - 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
+ - Ltime : List of time (validity)
+ - Ltitle : List of sub-title
+ - Llinewidth : List of lines thickness
+ - Llinetype : List of line types
+ - Lcolorlines: List of color lines
+ - Llinelabel : List of legend label lines
+ - LfacconvX/Y: List of factors for unit conversion of the variables/coordinates to plot on X and Y axis
+ - 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
+ - LaxisColor : List of colors for multiple x-axis overlap
+ - LlocLegend : List of localisation of the legend : 'best', 'upper left', 'upper right', 'lower left', 'lower right',
+ 'upper center', 'lower center', 'center left', 'center right', 'center'
+ """
+ self.ax = ax
+ firstCall = (len(self.ax) == 0)
+ # Defaults value convert to x number of variables list
+ if not LfacconvX:
+ LfacconvX = [1.0] * len(Lxx)
+ if not LfacconvY:
+ LfacconvY = [1.0] * len(Lxx)
+ if not Llinewidth:
+ Llinewidth = [1.0] * len(Lxx)
+ if not Llinecolor:
+ Llinecolor = ['blue'] * len(Lxx)
+ if not Llinetype:
+ Llinetype = ['-'] * len(Lxx)
+ if not Llinelabel:
+ Llinelabel = [''] * len(Lxx)
+ if not LaxisColor:
+ LaxisColor = ['black'] * len(Lxx)
+ if not Lylab:
+ Lylab = [''] * len(Lxx)
+ if not Lxlab:
+ Lxlab = [''] * len(Lxx)
+ if not LlocLegend:
+ LlocLegend = ['upper right'] * len(Lxx)
- # Title
- if Ltitle: self.set_Title(self.ax, iax, Ltitle[i], id_overlap,Lxlab[i], Lylab[i])
-
- # Ticks label
- self.ax[iax].tick_params(axis='both', labelsize=self.xyTicksLabelSize, width=self.xyTicksWidth, length=self.xyTicksLength, pad=self.tickspad)
-
- # X/Y Axis label
- if id_overlap:
- self.ax[iax].xaxis.tick_top()
- self.ax[iax].xaxis.set_label_position('top')
- self.ax[iax].set_xlabel(Lxlab[i])
- self.ax[iax].set_ylabel(Lylab[i])
- else:
- self.set_XYaxislab(self.ax, iax, Lxlab[i], Lylab[i])
-
- self.ax[iax].tick_params(axis='x', colors=LaxisColor[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
- return self.fig
-
- 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=[], LwhiteTop=[], Lpltype=[], Lcbformatlabel=[]):
- """
- Horizontal cross section plot
- Parameters :
- - lon : longitude 2D array
- - lat : latitude 2D array
- - Lvar : List of variables to plot
- - Lcarte : Zooming [lonmin, lonmax, latmin, latmax]
- - Llevel : List of k-level value for the section plot (ignored if variable is already 2D)
- - Lxlab : List of x-axis label
- - Lylab : List of y-axis label
- - Ltitle : List of sub-title
- - Ltime : List of time (validity)
- - Lminval: List of minimum value for each colorbar
- - Lmaxval: List of maximum value for each colorbar
- - Lstep : List of color-steps for each colorbar
- - Lstepticks : List of value of labels for each colorbar
- - Lcolormap : List of colormap
- - LcolorLine : List of colors for colors arg of contour (color line only)
- - Lcbarlabel : List of colorbar label legend (units)
- - Lproj : List of ccrs cartopy projection ([] for cartesian coordinates)
- - 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
- - 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
- - LwhiteTop : List of boolean to add the white color at the first top (high value). If false, the white is added at the bottom if Laddwhite_cm=T
- - Lcbformatlabel: List of boolean to reduce the format to exponential 1.1E+02 format colorbar label
- """
- self.ax = ax
- firstCall = (len(self.ax) == 0)
-
- # Initialize default value w.r.t to the number of plots
-# D={'lon':lon, 'lat':lat, 'Lcarte':Lcarte, 'Llevel':Llevel, 'Lxlab':Lxlab, 'Lylab':Lylab, 'Ltitle':Ltitle,'Lminval':Lminval, 'Lmaxval':Lmaxval,
+ if firstCall: # 1st call
+ iax = 0
+ self.ax.append(self.fig.add_subplot(self.nb_l, self.nb_c, 1, label='graph axe x down'))
+ self.nb_graph += 1
+ elif id_overlap: # overlapping plot with a different x-axis
+ self.ax.append(self.fig.add_subplot(self.nb_l, self.nb_c, self.nb_graph, label='graph axe x top', frame_on=False))
+ iax = len(self.ax) - 1
+ else: # existing ax with no overlapping (graph appended to existing panel)
+ 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
+
+ # On all variables to plot
+ for i, var in enumerate(Lxx):
+ # Print time validity
+ if Ltime:
+ self.showTimeText(self.ax, iax, str(Ltime[i]))
+
+ # Plot
+ cf = self.ax[iax].plot(Lxx[i] * LfacconvX[i], Lyy[i] * LfacconvY[i], color=Llinecolor[i], ls=Llinetype[i],
+ label=Llinelabel[i], linewidth=Llinewidth[i])
+ # Legend
+ # TODO : Handling legend with overlap two axis lines in the same box. For now, placement is by hand
+ if not id_overlap:
+ self.ax[iax].legend(loc=LlocLegend[i], bbox_to_anchor=(1, 0.95), fontsize=self.legendSize)
+ else:
+ self.ax[iax].legend(loc=LlocLegend[i], bbox_to_anchor=(1, 0.90), fontsize=self.legendSize)
+
+ # Title
+ if Ltitle:
+ self.set_Title(self.ax, iax, Ltitle[i], id_overlap, Lxlab[i], Lylab[i])
+
+ # Ticks label
+ self.ax[iax].tick_params(
+ axis='both',
+ labelsize=self.xyTicksLabelSize,
+ width=self.xyTicksWidth,
+ length=self.xyTicksLength,
+ pad=self.tickspad)
+
+ # X/Y Axis label
+ if id_overlap:
+ self.ax[iax].xaxis.tick_top()
+ self.ax[iax].xaxis.set_label_position('top')
+ self.ax[iax].set_xlabel(Lxlab[i])
+ self.ax[iax].set_ylabel(Lylab[i])
+ else:
+ self.set_XYaxislab(self.ax, iax, Lxlab[i], Lylab[i])
+
+ self.ax[iax].tick_params(axis='x', colors=LaxisColor[i])
+
+ # X/Y Axis limits value
+ if Lxlim:
+ try:
+ self.set_xlim(self.ax, iax, Lxlim[i])
+ except BaseException:
+ pass
+ if Lylim:
+ try:
+ self.set_ylim(self.ax, iax, Lylim[i])
+ except BaseException:
+ pass
+ return self.fig
+
+ 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=[], LwhiteTop=[], Lpltype=[], Lcbformatlabel=[], Llinewidth=[]):
+ """
+ Horizontal cross section plot
+ Parameters :
+ - lon : longitude 2D array
+ - lat : latitude 2D array
+ - Lvar : List of variables to plot
+ - Lcarte : Zooming [lonmin, lonmax, latmin, latmax]
+ - Llevel : List of k-level value for the section plot (ignored if variable is already 2D)
+ - Lxlab : List of x-axis label
+ - Lylab : List of y-axis label
+ - Ltitle : List of sub-title
+ - Ltime : List of time (validity)
+ - Lminval: List of minimum value for each colorbar
+ - Lmaxval: List of maximum value for each colorbar
+ - Lstep : List of color-steps for each colorbar
+ - Lstepticks : List of value of labels for each colorbar
+ - Llinewidth : List of lines thickness of contour
+ - Lcolormap : List of colormap
+ - LcolorLine : List of colors for colors arg of contour (color line only)
+ - Lcbarlabel : List of colorbar label legend (units)
+ - Lproj : List of ccrs cartopy projection ([] for cartesian coordinates)
+ - 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
+ - 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
+ - LwhiteTop : List of boolean to add the white color at the first top (high value). If false, the white is added at the bottom if Laddwhite_cm=T
+ - Lcbformatlabel: List of boolean to reduce the format to exponential 1.1E+02 format colorbar label
+ """
+ self.ax = ax
+ firstCall = (len(self.ax) == 0)
+
+ # Initialize default value w.r.t to the number of plots
+# D={'lon':lon, 'lat':lat, 'Lcarte':Lcarte, 'Llevel':Llevel, 'Lxlab':Lxlab, 'Lylab':Lylab, 'Ltitle':Ltitle,'Lminval':Lminval, 'Lmaxval':Lmaxval,
# 'Lstep':Lstep, 'Lstepticks':Lstepticks, 'Lcolormap':Lcolormap, 'Lcbarlabel':Lcbarlabel, 'Lproj':Lproj, 'Lfacconv':Lfacconv, 'Ltime':Ltime,
# 'LaddWhite_cm':LaddWhite_cm, 'Lpltype':Lpltype}
# D = initialize_default_val(Lvar, D)
-
- # If all plots are not using conversion factor, convert it to List
- if not Lfacconv: Lfacconv = [1.0]*len(Lvar)
- if not Lylab: Lylab = ['']*len(Lvar)
- if not Lxlab: Lxlab = ['']*len(Lvar)
- if not Lcolormap and not LcolorLine: Lcolormap=['gist_rainbow_r']*len(Lvar) # If no color given, a cmap is given
- 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 LwhiteTop: LwhiteTop=[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
-
- # This following must be after the extra percentage top value addition
- if not Lstep: Lstep=[None]*len(Lvar)
- if not Lstepticks: Lstepticks=[None]*len(Lvar)
-
- # On all variables to plot
- for i,var in enumerate(Lvar):
- 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: # Cartesian coordinates
- 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: # Cartesian coordinates
- 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
-
- #Colors normalization
- norm = mpl.colors.Normalize(vmax=Lmaxval[i], vmin=Lminval[i])
-
- # 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 var.ndim==2:
- vartoPlot = var[:,:]
- else:
- vartoPlot = var[Llevel[i],:,:]
-
- # Print min/max (stout and on plot)
- self.set_minmaxText(self.ax, iax, vartoPlot, Ltitle[i], Lid_overlap, Lfacconv[i])
-
- # Print time validity
- if Ltime: self.showTimeText(self.ax, iax, str(Ltime[i]))
-
- # Number of contours level
- if not Lstep[i]: # Default value of number of steps is 20
- Lstep[i] = (Lmaxval[i] - Lminval[i])/20
- Lstepticks[i] = Lstep[i]
-
- levels_contour = np.arange(Lminval[i],Lmaxval[i],step=Lstep[i])
-
- # Add White to colormap
- if LaddWhite_cm[i] and Lcolormap: Lcolormap[i]=self.addWhitecm(Lcolormap[i], len(levels_contour), LwhiteTop[i])
-
- # Plot
- if Lproj:
- if Lpltype[i]=='c': # Contour
- if LcolorLine:
- 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].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].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,
- norm=norm, vmin=Lminval[i], vmax=Lmaxval[i], cmap=Lcolormap[i])
- # Title
- self.set_Title(self.ax, iax, Ltitle[i], Lid_overlap,Lxlab[i], Lylab[i])
-
- # Coastlines / Grid lines and labels
- if Lproj: self.draw_Backmap(coastLines, self.ax[iax], Lproj[i])
-
- # X/Y Axis
- self.set_XYaxislab(self.ax, iax, Lxlab[i], Lylab[i])
- # Ticks label
- self.ax[iax].tick_params(axis='both', labelsize=self.xyTicksLabelSize, width=self.xyTicksWidth, length=self.xyTicksLength, pad=self.tickspad)
-
- # Color label on contour-line
- if Lpltype[i]=='c': # Contour
- 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, fontsize=self.cbTicksLabelSize)
- else:
- self.ax[iax].clabel(cf, levels=np.arange(Lminval[i],Lmaxval[i],step=Lstep[i]), fontsize=self.cbTicksLabelSize)
-
- # 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.ax.set_title(Lcbarlabel[i], pad = self.labelcolorbarpad, loc='left', fontsize=self.cbTitleSize) #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=[], Llegendlabel=[],
+
+ # If all plots are not using conversion factor, convert it to List
+ if not Lfacconv:
+ Lfacconv = [1.0] * len(Lvar)
+ if not Lylab:
+ Lylab = [''] * len(Lvar)
+ if not Lxlab:
+ Lxlab = [''] * len(Lvar)
+ if not Lcolormap and not LcolorLine:
+ Lcolormap = ['gist_rainbow_r'] * len(Lvar) # If no color given, a cmap is given
+ 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 LwhiteTop:
+ LwhiteTop = [False] * len(Lvar)
+ if not Lcbformatlabel:
+ Lcbformatlabel = [False] * len(Lvar)
+ if not Llinewidth:
+ Llinewidth = [1.0] * 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
+
+ # This following must be after the extra percentage top value addition
+ if not Lstep:
+ Lstep = [None] * len(Lvar)
+ if not Lstepticks:
+ Lstepticks = [None] * len(Lvar)
+
+ # On all variables to plot
+ for i, var in enumerate(Lvar):
+ 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: # Cartesian coordinates
+ 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: # Cartesian coordinates
+ 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
+
+ # Colors normalization
+ norm = mpl.colors.Normalize(vmax=Lmaxval[i], vmin=Lminval[i])
+
+ # 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 var.ndim == 2:
+ vartoPlot = var[:, :]
+ else:
+ vartoPlot = var[Llevel[i], :, :]
+
+ # Print min/max (stout and on plot)
+ self.set_minmaxText(self.ax, iax, vartoPlot, Ltitle[i], Lid_overlap, Lfacconv[i])
+
+ # Print time validity
+ if Ltime:
+ self.showTimeText(self.ax, iax, str(Ltime[i]))
+
+ # Number of contours level
+ if not Lstep[i]: # Default value of number of steps is 20
+ Lstep[i] = (Lmaxval[i] - Lminval[i]) / 20
+ Lstepticks[i] = Lstep[i]
+
+ levels_contour = np.arange(Lminval[i], Lmaxval[i], step=Lstep[i])
+
+ # Add White to colormap
+ if LaddWhite_cm[i] and Lcolormap:
+ Lcolormap[i] = self.addWhitecm(Lcolormap[i], len(levels_contour), LwhiteTop[i])
+
+ # Plot
+ if Lproj:
+ if Lpltype[i] == 'c': # Contour
+ if LcolorLine:
+ 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],linewidths=Llinewidth[i])
+ else:
+ 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],linewidths=Llinewidth[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].contour(lon[i], lat[i], vartoPlot * Lfacconv[i], levels=levels_contour,
+ norm=norm, vmin=Lminval[i], vmax=Lmaxval[i], colors=LcolorLine[i],linewidths=Llinewidth[i])
+ else:
+ cf = self.ax[iax].contourf(lon[i], lat[i], vartoPlot * Lfacconv[i], levels=levels_contour,
+ norm=norm, vmin=Lminval[i], vmax=Lmaxval[i], cmap=Lcolormap[i])
+ # Title
+ self.set_Title(self.ax, iax, Ltitle[i], Lid_overlap, Lxlab[i], Lylab[i])
+
+ # Coastlines / Grid lines and labels
+ if Lproj:
+ self.draw_Backmap(coastLines, self.ax[iax], Lproj[i])
+
+ # X/Y Axis
+ self.set_XYaxislab(self.ax, iax, Lxlab[i], Lylab[i])
+ # Ticks label
+ self.ax[iax].tick_params(
+ axis='both',
+ labelsize=self.xyTicksLabelSize,
+ width=self.xyTicksWidth,
+ length=self.xyTicksLength,
+ pad=self.tickspad)
+
+ # Color label on contour-line
+ if Lpltype[i] == 'c': # Contour
+ 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, fontsize=self.cbTicksLabelSize)
+ else:
+ self.ax[iax].clabel(cf, levels=np.arange(Lminval[i], Lmaxval[i], step=Lstep[i]), fontsize=self.cbTicksLabelSize)
+
+ # 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.ax.tick_params(labelsize=self.cbTicksLabelSize)
+ # This creates a new AxesSubplot only for the colorbar y=0 ==> location at the bottom
+ cb.ax.set_title(Lcbarlabel[i], pad=self.labelcolorbarpad, loc='left', fontsize=self.cbTitleSize)
+ 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=[], Llegendlabel=[],
Lproj=[], Lfacconv=[], ax=[], coastLines=True, Lid_overlap=[], Ltime=[], Lscale=[],
Lylim=[], Lxlim=[]):
- """
- Vectors
- Parameters :
- - 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)
- - Lwidth : List of thickness of the arrows
- - Lscale : List of scale for the length of the arrows (high value <=> small length)
- - Larrowstep : List of sub-sample (frequency) if too much arrows
- - Lcolor : List of colors for the arrows (default: black)
- - Llegendval : List of value for the legend of the default arrow
- - Llegendlabel : List of labels for the legend of the default arrow
- - 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 Lscale : Lscale = [None]*len(Lvar1)
- if not Lylab: Lylab = ['']*len(Lvar1)
- if not Lxlab: Lxlab = ['']*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 colorbar 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
- axeX = Lxx[i]
- axeY = Lyy[i]
- if Lxx[i].ndim == 2:
- cf = self.ax[iax].quiver(axeX[::Larrowstep[i],::Larrowstep[i]], axeY[::Larrowstep[i],::Larrowstep[i]],
- vartoPlot1[::Larrowstep[i],::Larrowstep[i]], vartoPlot2[::Larrowstep[i],::Larrowstep[i]],
- width=Lwidth[i] ,angles='uv', color=Lcolor[i],scale=Lscale[i])
- else:
- cf = self.ax[iax].quiver(axeX[::Larrowstep[i]], axeY[::Larrowstep[i]],
- vartoPlot1[::Larrowstep[i],::Larrowstep[i]], vartoPlot2[::Larrowstep[i],::Larrowstep[i]],
- width=Lwidth[i] ,angles='uv', color=Lcolor[i], scale=Lscale[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])
-
- # Arrow legend key
- qk = self.ax[iax].quiverkey(cf, 1.0, -0.05, Llegendval[i], str(Llegendval[i]) + Llegendlabel[i], labelpos='E', color='black')
-
- return self.fig
+ """
+ Vectors
+ Parameters :
+ - 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)
+ - Lwidth : List of thickness of the arrows
+ - Lscale : List of scale for the length of the arrows (high value <=> small length)
+ - Larrowstep : List of sub-sample (frequency) if too much arrows
+ - Lcolor : List of colors for the arrows (default: black)
+ - Llegendval : List of value for the legend of the default arrow
+ - Llegendlabel : List of labels for the legend of the default arrow
+ - 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 Lscale:
+ Lscale = [None] * len(Lvar1)
+ if not Lylab:
+ Lylab = [''] * len(Lvar1)
+ if not Lxlab:
+ Lxlab = [''] * 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 colorbar 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
+ axeX = Lxx[i]
+ axeY = Lyy[i]
+ if Lxx[i].ndim == 2:
+ cf = self.ax[iax].quiver(axeX[::Larrowstep[i], ::Larrowstep[i]], axeY[::Larrowstep[i], ::Larrowstep[i]],
+ vartoPlot1[::Larrowstep[i], ::Larrowstep[i]], vartoPlot2[::Larrowstep[i], ::Larrowstep[i]],
+ width=Lwidth[i], angles='uv', color=Lcolor[i], scale=Lscale[i])
+ else:
+ cf = self.ax[iax].quiver(axeX[::Larrowstep[i]], axeY[::Larrowstep[i]],
+ vartoPlot1[::Larrowstep[i], ::Larrowstep[i]], vartoPlot2[::Larrowstep[i], ::Larrowstep[i]],
+ width=Lwidth[i], angles='uv', color=Lcolor[i], scale=Lscale[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 BaseException:
+ pass
+ if Lylim:
+ try:
+ self.set_ylim(self.ax, iax, Lylim[i])
+ except BaseException:
+ pass
+
+ # Coastlines:
+ if Lproj:
+ self.draw_Backmap(coastLines, self.ax[iax], Lproj[i])
+
+ # Arrow legend key
+ qk = self.ax[iax].quiverkey(cf, 1.0, -0.05, Llegendval[i], str(Llegendval[i]) + Llegendlabel[i],
+ labelpos='E', color='black', fontproperties={'size': self.legendSize})
+
+ 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
- Parameters :
- - 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]))
+ Ltitle=[], Lcolor=[], Lproj=[], Lfacconv=[], ax=[], coastLines=True, Lid_overlap=[], Ltime=[],
+ Lylim=[], Lxlim=[]):
+ """
+ Wind stream lines
+ Parameters :
+ - 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)
- # 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])
+ # 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 BaseException:
+ pass
+ if Lylim:
+ try:
+ self.set_ylim(self.ax, iax, Lylim[i])
+ except BaseException:
+ pass
+
+ # Coastlines:
+ if Lproj:
+ self.draw_Backmap(coastLines, self.ax[iax], Lproj[i])
+
+ return self.fig
- # 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=[]):
- """
- XY Histogram
- Parameters :
- - Lbins : List of bins
- - Lvar : List of the value for each bin
- - Lxlab : List of x-axis label
- - Lylab : List of y-axis label
- - Ltitle : List of sub-title
- - Lcolor : List of color (or sequence of colors for each value) of the bars
- - Lwidth : List of width of the bars
- - Llinecolor : List of line color of the bar edges
- - Llinewidth : List of lines thickness of the bar edges
- - Lfacconv : List of factors for unit conversion of each variables
- - Lxlim : List of x (min, max) value plotted
- - Lylim : List of y (min, max) value plotted
- - Ltime : List of time (validity)
- - 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
- - LaxisColor : List of colors for multiple x-axis overlap
- """
- self.ax = ax
- firstCall = (len(self.ax) == 0)
- # Defaults value convert to x number of variables list
- if not Lfacconv: Lfacconv = [1.0]*len(Lvar)
- if not LaxisColor: LaxisColor = ['black']*len(Lvar)
- if not Lylab: Lylab = ['']*len(Lvar)
- if not Lxlab: Lxlab = ['']*len(Lvar)
- if not Lcolor: Lcolor = ['black']*len(Lvar)
- if not Lwidth: Lwidth = [1]*len(Lvar)
- if not Llinecolor: Llinecolor = ['black']*len(Lvar)
- if not Llinewidth: Llinewidth = [0]*len(Lvar)
-
- # On all variables to plot
- for i,var in enumerate(Lvar):
- if firstCall: # 1st call
- iax = i
- self.ax.append(self.fig.add_subplot(self.nb_l,self.nb_c,i+1, label='graph axe x down'))
- self.nb_graph+=1
- elif id_overlap: # overlapping plot with a different x-axis
- self.ax.append(self.fig.add_subplot(self.nb_l,self.nb_c,self.nb_graph, label='graph axe x top',frame_on=False))
- iax = len(self.ax)-1
- else: # existing ax with no overlapping (graph appended to existing panel)
- self.ax.append(self.fig.add_subplot(self.nb_l,self.nb_c,self.nb_graph+1))
- self.nb_graph+=1
- print(len(self.ax))
- iax = len(self.ax)-1 # The ax index of the new coming plot is the length of the existant ax -1 for indices matter
-
- # Print time validity
- if Ltime: self.showTimeText(self.ax, iax, str(Ltime[i]))
-
- # Bins by labels
- labels = np.array([str(L) for L in Lbins[i]])
-
- # Plot
- cf = self.ax[iax].bar(labels, var*Lfacconv[i], width=Lwidth[i], color=Lcolor[i], linewidth=Llinewidth[i], edgecolor=Llinecolor[i])
-
- # Legend
- #TODO : Handling legend with overlap two axis lines in the same box. For now, placement is by hand
- if not id_overlap:
- self.ax[iax].legend(loc='upper right', bbox_to_anchor=(1, 0.95))
- else:
- self.ax[iax].legend(loc='upper right', bbox_to_anchor=(1, 0.90))
-
- # Title
- if Ltitle: self.set_Title(self.ax, iax, Ltitle[i], id_overlap,Lxlab[i], Lylab[i])
-
- # X/Y Axis label
- if id_overlap:
- self.ax[iax].xaxis.tick_top()
- self.ax[iax].xaxis.set_label_position('top')
- self.ax[iax].set_xlabel(Lxlab[i])
- self.ax[iax].set_ylabel(Lylab[i])
- else:
- self.set_XYaxislab(self.ax, iax, Lxlab[i], Lylab[i])
-
- self.ax[iax].tick_params(axis='x', colors=LaxisColor[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
-
- return self.fig
-#def initialize_default_val(Lvar, Dparam):
+ Llinecolor=[], Llinewidth=[], Lfacconv=[], ax=[], id_overlap=None, Lxlim=[],
+ Lylim=[], Ltime=[], LaxisColor=[], LlocLegend=[]):
+ """
+ XY Histogram
+ Parameters :
+ - Lbins : List of bins
+ - Lvar : List of the value for each bin
+ - Lxlab : List of x-axis label
+ - Lylab : List of y-axis label
+ - Ltitle : List of sub-title
+ - Lcolor : List of color (or sequence of colors for each value) of the bars
+ - Lwidth : List of width of the bars
+ - Llinecolor : List of line color of the bar edges
+ - Llinewidth : List of lines thickness of the bar edges
+ - Lfacconv : List of factors for unit conversion of each variables
+ - Lxlim : List of x (min, max) value plotted
+ - Lylim : List of y (min, max) value plotted
+ - Ltime : List of time (validity)
+ - 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
+ - LaxisColor : List of colors for multiple x-axis overlap
+ - LlocLegend : List of localisation of the legend : 'best', 'upper left', 'upper right', 'lower left', 'lower right',
+ 'upper center', 'lower center', 'center left', 'center right', 'center'
+ """
+ self.ax = ax
+ firstCall = (len(self.ax) == 0)
+ # Defaults value convert to x number of variables list
+ if not Lfacconv:
+ Lfacconv = [1.0] * len(Lvar)
+ if not LaxisColor:
+ LaxisColor = ['black'] * len(Lvar)
+ if not Lylab:
+ Lylab = [''] * len(Lvar)
+ if not Lxlab:
+ Lxlab = [''] * len(Lvar)
+ if not Lcolor:
+ Lcolor = ['black'] * len(Lvar)
+ if not Lwidth:
+ Lwidth = [1] * len(Lvar)
+ if not Llinecolor:
+ Llinecolor = ['black'] * len(Lvar)
+ if not Llinewidth:
+ Llinewidth = [0] * len(Lvar)
+ if not LlocLegend:
+ LlocLegend = ['upper right'] * len(Lvar)
+
+ # On all variables to plot
+ for i, var in enumerate(Lvar):
+ if firstCall: # 1st call
+ iax = i
+ self.ax.append(self.fig.add_subplot(self.nb_l, self.nb_c, i + 1, label='graph axe x down'))
+ self.nb_graph += 1
+ elif id_overlap: # overlapping plot with a different x-axis
+ self.ax.append(self.fig.add_subplot(self.nb_l, self.nb_c, self.nb_graph, label='graph axe x top', frame_on=False))
+ iax = len(self.ax) - 1
+ else: # existing ax with no overlapping (graph appended to existing panel)
+ self.ax.append(self.fig.add_subplot(self.nb_l, self.nb_c, self.nb_graph + 1))
+ self.nb_graph += 1
+ print(len(self.ax))
+ iax = len(self.ax) - 1 # The ax index of the new coming plot is the length of the existant ax -1 for indices matter
+
+ # Print time validity
+ if Ltime:
+ self.showTimeText(self.ax, iax, str(Ltime[i]))
+
+ # Bins by labels
+ labels = np.array([str(L) for L in Lbins[i]])
+
+ # Plot
+ cf = self.ax[iax].bar(labels, var * Lfacconv[i], width=Lwidth[i], color=Lcolor[i], linewidth=Llinewidth[i], edgecolor=Llinecolor[i])
+
+ # Legend
+ # TODO : Handling legend with overlap two axis lines in the same box. For now, placement is by hand
+ if not id_overlap:
+ self.ax[iax].legend(loc=LlocLegend[i], bbox_to_anchor=(1, 0.95))
+ else:
+ self.ax[iax].legend(loc=LlocLegend[i], bbox_to_anchor=(1, 0.90))
+
+ # Title
+ if Ltitle:
+ self.set_Title(self.ax, iax, Ltitle[i], id_overlap, Lxlab[i], Lylab[i])
+
+ # X/Y Axis label
+ if id_overlap:
+ self.ax[iax].xaxis.tick_top()
+ self.ax[iax].xaxis.set_label_position('top')
+ self.ax[iax].set_xlabel(Lxlab[i])
+ self.ax[iax].set_ylabel(Lylab[i])
+ else:
+ self.set_XYaxislab(self.ax, iax, Lxlab[i], Lylab[i])
+
+ self.ax[iax].tick_params(axis='x', colors=LaxisColor[i])
+
+ # X/Y Axis limits value
+ if Lxlim:
+ try:
+ self.set_xlim(self.ax, iax, Lxlim[i])
+ except BaseException:
+ pass
+ if Lylim:
+ try:
+ self.set_ylim(self.ax, iax, Lylim[i])
+ except BaseException:
+ pass
+
+ return self.fig
+# def initialize_default_val(Lvar, Dparam):
# #TODO : initialize default value for all parameter of all type of graphs
# #Returns All the parameters given in Dparam where :
# "- If no value is found (empty list []) : return the default value (if exist) * number of graph
# #- If ONE value only is found : return the value copied x times the number of graph
# #- If the list is complete, nothing is done
# #CURRENT PROBLEM
-# #The returned value do not change the true referenced variable given as argument
+# #The returned value do not change the true referenced variable given as argument
# # Number of graphs
# l = 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 Dparam['Lstep'] and Dparam['Lmaxval']: Dparam['Lmaxval'] = list(map(lambda x, y: x + 1E-6*y, Dparam['Lmaxval'], Dparam['Lstep']) ) #The extra value is 1E-6 times the step ticks of the colorbar
# print(Dparam.items())
-#
+#
# # Read on which parameters initialize the default values
# for args_t in list(Dparam.items()): # Test on all arguments present, if they are empty list, default values apply for each graph
# args = list(args_t)
@@ -936,16 +1072,16 @@ class PanelPlot():
# elif args[0] == 'Lstepticks' and not args[1]: args[1] = [None]*l
# Dparam[args[0]] = args[1]
# print(args)
-#
+#
# # Check if there is no value for a parameter
-## for args_t in list(Dparam.items()):
+# for args_t in list(Dparam.items()):
## args = list(args_t)
-## if args[1]
+# if args[1]
# # Number of contours level
-## for i in range(l):
-## if 'Lstepticks' in arguments.args and 'Lmaxval' in arguments.args and 'Lminval' in arguments.args:
-## Lstep[i] = (Lmaxval[i] - Lminval[i])/20 # Default value of number of steps is 20
-## Lstepticks[i] = Lstep[i] # Default value is stepticks are the same as steps values
+# for i in range(l):
+# if 'Lstepticks' in arguments.args and 'Lmaxval' in arguments.args and 'Lminval' in arguments.args:
+# Lstep[i] = (Lmaxval[i] - Lminval[i])/20 # Default value of number of steps is 20
+# Lstepticks[i] = Lstep[i] # Default value is stepticks are the same as steps values
+#
#
-#
# return Dparam
diff --git a/src/LIB/Python/misc_functions.py b/src/LIB/Python/misc_functions.py
index efc0916e04a60a7ee3cd2a276d1bb1eba3de0182..53577de6ee71fbc12524c19af6daff7657bd5fe9 100644
--- a/src/LIB/Python/misc_functions.py
+++ b/src/LIB/Python/misc_functions.py
@@ -13,207 +13,214 @@ from scipy.interpolate import RectBivariateSpline
import numpy as np
import math
+
def convert_date(datesince, time_in_sec):
- return str(time_in_sec) + datesince[:33]
+ return str(time_in_sec) + datesince[:33]
+
class mean_operator():
- def MYM(self,var):
+ def MYM(self, var):
ny = var.shape[1]
out = copy.deepcopy(var)
- for j in range(ny-1):
- out[:,j,:] = (var[:,j,:] + var[:,j+1,:])*0.5
+ for j in range(ny - 1):
+ out[:, j, :] = (var[:, j, :] + var[:, j + 1, :]) * 0.5
return out
-
- def MXM(self,var):
+
+ def MXM(self, var):
nx = var.shape[2]
out = copy.deepcopy(var)
- for i in range(nx-1):
- out[:,:,i] = (var[:,:,i] + var[:,:,i+1])*0.5
+ for i in range(nx - 1):
+ out[:, :, i] = (var[:, :, i] + var[:, :, i + 1]) * 0.5
return out
-
- def MZM(self,var):
+
+ def MZM(self, var):
nz = var.shape[0]
out = copy.deepcopy(var)
- for k in range(nz-1):
- out[k,:,:] = (var[k,:,:] + var[k+1,:,:])*0.5
+ for k in range(nz - 1):
+ out[k, :, :] = (var[k, :, :] + var[k + 1, :, :]) * 0.5
return out
+
def windvec_verti_proj(u, v, level, angle):
"""Compute the projected horizontal wind vector on an axis with a given angle w.r.t. the x/ni axes (West-East)
-
+
Parameters
----------
u : array 3D
U-wind component
-
+
v : array 3D
V-wind component
level : array 1D
level dimension array
-
+
angle : float
angle (radian) of the new axe w.r.t the x/ni axes (West-East). angle = 0 for (z,x) sections, angle=pi/2 for (z,y) sections
-
+
Returns
-------
-
+
projected_wind : array 3D
a 3D wind component projected on the axe to be used with Panel_Plot.pvector as Lvar1
- """
+ """
projected_wind = copy.deepcopy(u)
for k in range(len(level)):
- projected_wind[k,:,:] = u[k,:,:]*math.cos(angle) + v[k,:,:]*math.sin(angle)
+ projected_wind[k, :, :] = u[k, :, :] * math.cos(angle) + v[k, :, :] * math.sin(angle)
return projected_wind
+
def oblique_proj(var, ni, nj, lvl, i_beg, j_beg, i_end, j_end):
"""Compute an oblique projection of a variable w.r.t. its axes
-
+
Parameters
----------
var : array 3D or 2D
the variable to project (e.g. THT, ZS)
-
+
ni : array 1D
1D x-axis of the 3D dimension
-
+
nj : array 1D
1D y-axis of the 3D dimension
-
+
level : array 1D
1D z-axe of the 3D dimension
-
+
i_beg, j_beg : int
coordinate of the begin point of the new axe
-
+
i_end, j_end : int
- coordinate of the end point of the new axe
-
+ coordinate of the end point of the new axe
+
Returns
-------
angle_proj : float
the angle (radian) of the new axe w.r.t the x/ni axes (West-East)
-
+
out_var : array 2D or 1D
a 2D (z,m) or 1D (m) variable projected on the oblique axe
-
+
axe_m : array 1D
a 1D m new axe (distance from the beggining point)
-
+
"""
- dist_seg=np.sqrt((i_end-i_beg)**2.0 + (j_end-j_beg)**2.0) # Distance de la section oblique m
- if var.ndim ==3:
- out_var = np.zeros((len(lvl),int(dist_seg)+1)) # Initialisation du nouveau champs projeté dans la coupe (z,m)
+ dist_seg = np.sqrt((i_end - i_beg)**2.0 + (j_end - j_beg)**2.0) # Distance de la section oblique m
+ if var.ndim == 3:
+ out_var = np.zeros((len(lvl), int(dist_seg) + 1)) # Initialisation du nouveau champs projeté dans la coupe (z,m)
else: # 2D
- out_var = np.zeros(int(dist_seg)+1) # Initialisation du nouveau champs projeté dans la coupe (m)
+ out_var = np.zeros(int(dist_seg) + 1) # Initialisation du nouveau champs projeté dans la coupe (m)
- axe_m = np.zeros(int(dist_seg)+1) # Axe des abscisses qui sera tracé selon la coupe
- axe_m_coord = [] # Coordonnées x,y des points qui composent l'axe
- axe_m_coord.append( (ni[i_beg],nj[j_beg]) ) # Le premier point est celui donné par l'utilisateur
+ axe_m = np.zeros(int(dist_seg) + 1) # Axe des abscisses qui sera tracé selon la coupe
+ axe_m_coord = [] # Coordonnées x,y des points qui composent l'axe
+ axe_m_coord.append((ni[i_beg], nj[j_beg])) # Le premier point est celui donné par l'utilisateur
- for m in range(int(dist_seg)): # Discrétisation selon distance de la coupe / int(distance_de_la_coupe)
- axe_m_coord.append( (axe_m_coord[0][0] + (ni[i_end]-ni[i_beg])/(int(dist_seg))*(m+1),
- axe_m_coord[0][1] + (nj[j_end]-nj[j_beg])/(int(dist_seg))*(m+1) ))
- axe_m[m+1] = np.sqrt((ni[i_beg]-axe_m_coord[m+1][0])**2 + (nj[j_beg]-axe_m_coord[m+1][1])**2)
+ for m in range(int(dist_seg)): # Discrétisation selon distance de la coupe / int(distance_de_la_coupe)
+ axe_m_coord.append((axe_m_coord[0][0] + (ni[i_end] - ni[i_beg]) / (int(dist_seg)) * (m + 1),
+ axe_m_coord[0][1] + (nj[j_end] - nj[j_beg]) / (int(dist_seg)) * (m + 1)))
+ axe_m[m + 1] = np.sqrt((ni[i_beg] - axe_m_coord[m + 1][0])**2 + (nj[j_beg] - axe_m_coord[m + 1][1])**2)
- if var.ndim ==3: # 3D variables to project
+ if var.ndim == 3: # 3D variables to project
for k in range(len(lvl)):
- a=RectBivariateSpline(ni, nj,var[k,:,:],kx=1,ky=1) # Interpolation par niveau à l'ordre 1 pour éviter des valeurs négatives de champs strictement > 0
- for m in range(int(dist_seg)+1):
- out_var[k,m] = a.ev(axe_m_coord[m][0],axe_m_coord[m][1]) # La fonction ev de RectBivariate retourne la valeur la plus proche du point considéré
+ a = RectBivariateSpline(nj, ni, var[k, :, :], kx=1, ky=1)
+ for m in range(int(dist_seg) + 1):
+ # La fonction ev de RectBivariate retourne la valeur la plus proche du point considéré
+ out_var[k, m] = a.ev(axe_m_coord[m][1], axe_m_coord[m][0])
else: # 2D variables to project
- a=RectBivariateSpline(ni, nj,var[:,:],kx=1,ky=1)
- for m in range(int(dist_seg)+1):
- out_var[m] = a.ev(axe_m_coord[m][0],axe_m_coord[m][1])
-
- angle_proj = math.acos((ni[i_end]-ni[i_beg])/axe_m[-1])
+ a = RectBivariateSpline(nj, ni, var[:, :], kx=1, ky=1)
+ for m in range(int(dist_seg) + 1):
+ out_var[m] = a.ev(axe_m_coord[m][1], axe_m_coord[m][0])
+
+ angle_proj = math.acos((ni[i_end] - ni[i_beg]) / axe_m[-1])
return angle_proj, out_var, axe_m
+
def comp_altitude1DVar(oneVar2D, orography, ztop, level, n_xory):
"""Compute and returns an altitude and x or y grid mesh variable in 2D following the topography in 1D
To be used with 2D simulations
-
+
Parameters
----------
oneVar2D : array 2D
a 2D array (e.g. UT, THT)
-
+
orography : array 1D
1D orography (ZS)
-
+
ztop : real
scalar of the top height of the model (ZTOP)
-
+
level : array 1D
1D level variable (level or level_w)
-
- n_xory : array 1D
+
+ n_xory : array 1D
1D directionnal grid variable (ni_u, nj_u, ni_v or nj_v)
-
+
Returns
-------
altitude
a 2D altitude variable with topography taken into account
-
+
n_xory_2D
a 2D directionnal variable duplicated from n_xory
"""
n_xory_2D = copy.deepcopy(oneVar2D)
- altitude = copy.deepcopy(oneVar2D)
-
+ altitude = copy.deepcopy(oneVar2D)
+
for k in range(len(level)):
- n_xory_2D[k,:] = n_xory
+ n_xory_2D[k, :] = n_xory
for j in range(len(n_xory)):
for k in range(len(level)):
- altitude[k,j] = orography[j] + level[k]*((ztop-orography[j])/ztop)
+ altitude[k, j] = orography[j] + level[k] * ((ztop - orography[j]) / ztop)
return altitude, n_xory_2D
+
def comp_altitude2DVar(oneVar3D, orography, ztop, level, n_y, n_x):
"""Compute and returns an altitude and x or y grid mesh variable in 3D following the topography in 2D
To be used with 3D simulations
-
+
Parameters
----------
oneVar3D : array 3D
a 3D array (e.g. UT, THT)
-
+
orography : array 2D
2D orography (ZS)
-
+
ztop : real
scalar of the top height of the model (ZTOP)
-
+
level : array 1D
1D level variable (level or level_w)
-
- n_x : array 1D
+
+ n_x : array 1D
1D directionnal grid variable along i (ni_u, or ni_v)
-
- n_y : array 1D
+
+ n_y : array 1D
1D directionnal grid variable along j (nj_u, or nj_v)
-
+
Returns
-------
altitude
a 3D altitude variable with topography taken into account
-
+
n_x3D
a 3D directionnal variable duplicated from n_x
-
+
n_y3D
a 3D directionnal variable duplicated from n_y
"""
n_x3D = copy.deepcopy(oneVar3D)
n_y3D = copy.deepcopy(oneVar3D)
- altitude = copy.deepcopy(oneVar3D)
+ altitude = copy.deepcopy(oneVar3D)
for i in range(len(level)):
- n_y3D[i,:] = n_y
- n_x3D[i,:] = n_x
+ n_y3D[i, :] = n_y
+ n_x3D[i, :] = n_x
for i in range(oneVar3D.shape[2]):
for j in range(oneVar3D.shape[1]):
- if ztop==0:
- altitude[:,i,j] = level[:]
+ if ztop == 0:
+ altitude[:, i, j] = level[:]
else:
for k in range(len(level)):
- altitude[k,j,i] = orography[j,i] + level[k]*((ztop-orography[j,i])/ztop)
+ altitude[k, j, i] = orography[j, i] + level[k] * ((ztop - orography[j, i]) / ztop)
return altitude, n_x3D, n_y3D
diff --git a/src/LIB/Python/read_MNHfile.py b/src/LIB/Python/read_MNHfile.py
index 38072becffe3b1d8c066c6f370683b4988cf7ccf..7e240f65c91f1abbb80576f99655cdad016f080d 100644
--- a/src/LIB/Python/read_MNHfile.py
+++ b/src/LIB/Python/read_MNHfile.py
@@ -11,33 +11,67 @@ MNH_LIC for details. version 1.
import netCDF4 as nc
import numpy as np
-def read_withEPY(LnameFiles,Dvar_input, Dvar_output={}, path='.'):
+
+def read_withEPY(LnameFiles, Dvar_input, Dvar_output={}, path='.'):
+ """Read a netCDF4 Meso-NH file, LFI, FA or GRIB 1/2 file with the Epygram Meteo-France library
+ Parameters
+ ----------
+ LnameFiles : list of str
+ list of Meso-NH netCDF4 file (diachronic or synchronous)
+
+ Dvar_input : Dict{'keyFile' : [field_identifier]}
+ where
+ 'keyFile' is a str corresponding to a key for the file number in LnameFiles (by order)
+ [field_identifier] is
+ - GRIB1 [indicatorOfParameter, paramId, indicatorOfTypeOfLevel, level, casual name] for GRIB1
+ - GRIB2 [discipline, parameterCategory, typeOfFirstFixedSurface, parameterNumber, level, casual name] for GRIB2
+ - MNH netcdf ('variable string', level) for netcdf MNH; set level=0 for 2D variables
+ - LFI ('variable string', level) for LFI; set level=0 for 2D variables
+ - FA 'variable string'
+
+ path : str or list
+ path(s) of the files to read
+
+ Returns
+ -------
+ Dvar : Dict
+ Dvar[ifile]['var_name'] an epygram list of resources
+
+ """
import epygram
epygram.init_env()
- for i,keyFiles in enumerate(Dvar_input.keys()):
+ for i, keyFiles in enumerate(Dvar_input.keys()):
+ if isinstance(path, list):
+ ipath = path[i]
+ else:
+ ipath = path
print('Reading file ' + keyFiles)
- theFile = epygram.formats.resource(LnameFiles[i],'r')
- Dvar_output[keyFiles] = {} #initialize dic for each files
- for var in Dvar_input[keyFiles]: #For each files
+ theFile = epygram.formats.resource(ipath + LnameFiles[i], 'r')
+ Dvar_output[keyFiles] = {} # initialize dic for each files
+ for var in Dvar_input[keyFiles]: # For each files
# Read variables
if(theFile.format == 'FA'):
Dvar_output[keyFiles][var] = theFile.readfield(var)
elif(theFile.format == 'LFI'):
- if(var[1]==None or var[1]==0): # 2D Field
+ if(var[1] is None or var[1] == 0): # 2D Field
Dvar_output[keyFiles][var[0]] = theFile.readfield(var)
- else: # 3D Field
- Dvar_output[keyFiles][var[0]+str(var[1])] = theFile.readfield(var).getlevel(k=var[1])
+ else: # 3D Field
+ Dvar_output[keyFiles][var[0] + str(var[1])] = theFile.readfield(var).getlevel(k=var[1])
elif(theFile.format == 'netCDFMNH'):
- if(var[1]==None or var[1]==0): # 2D Field
+ if(var[1] is None or var[1] == 0): # 2D Field
Dvar_output[keyFiles][var[0]] = theFile.readfield(var[0])
else:
- Dvar_output[keyFiles][var[0]+str(var[1])] = theFile.readfield(var[0]).getlevel(k=var[1])
- elif(theFile.format == 'GRIB'):
- if len(var)==6: # GRIB2
- Dvar_output[keyFiles][var[5]] = theFile.readfield({'discipline': var[0], 'parameterCategory': var[1], 'typeOfFirstFixedSurface': var[2],'parameterNumber': var[3], 'level': var[4]})
- elif len(var)==5: # GRIB1
- Dvar_output[keyFiles][var[4]] = theFile.readfield({'indicatorOfParameter': var[0], 'paramId': var[1], 'indicatorOfTypeOfLevel': var[2], 'level': var[3]})
- else: epygramError("GRIB format error. GRIB1 expects 4 values : [indicatorOfParameter, paramId, indicatorOfTypeOfLevel, level, 'casual name'], GRIB2 expects 5 values [discipline, parameterCategory, typeOfFirstFixedSurface, parameterNumber, level, casual name]")
+ Dvar_output[keyFiles][var[0] + str(var[1])] = theFile.readfield(var[0]).getlevel(k=var[1])
+ elif(theFile.format == 'GRIB'):
+ if len(var) == 6: # GRIB2
+ Dvar_output[keyFiles][var[5]] = theFile.readfield(
+ {'discipline': var[0], 'parameterCategory': var[1], 'typeOfFirstFixedSurface': var[2], 'parameterNumber': var[3], 'level': var[4]})
+ elif len(var) == 5: # GRIB1
+ Dvar_output[keyFiles][var[4]] = theFile.readfield(
+ {'indicatorOfParameter': var[0], 'paramId': var[1], 'indicatorOfTypeOfLevel': var[2], 'level': var[3]})
+ else:
+ epygramError(
+ "GRIB format error. GRIB1 expects 4 values : [indicatorOfParameter, paramId, indicatorOfTypeOfLevel, level, 'casual name'], GRIB2 expects 5 values [discipline, parameterCategory, typeOfFirstFixedSurface, parameterNumber, level, casual name]")
else:
raise epygramError("Unknown format file, please use FA, LFI, GRIB or MNH NetCDF")
theFile.close()
@@ -45,22 +79,23 @@ def read_withEPY(LnameFiles,Dvar_input, Dvar_output={}, path='.'):
# Transform spectral data to physics space (for AROME and ARPEGE)
for f in Dvar_output:
for var in Dvar_output[f]:
- try:
+ try:
if(Dvar_output[f][var].spectral):
Dvar_output[f][var].sp2gp()
- except:
+ except BaseException:
break
return Dvar_output
+
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{'keyFile' : 'var_name',('group_name','var_name')}
where
'keyFile' is a str corresponding to a key for the file number in LnameFiles (by order)
@@ -69,211 +104,225 @@ def read_netcdf(LnameFiles, Dvar_input, path='.', get_data_only=True, del_empty_
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
-
+
+ path : str or list
+ path(s) of the files to read
+
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
+ 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 : 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
"""
Dvar = {}
- for i,keyFiles in enumerate(Dvar_input.keys()):
+ for i, keyFiles in enumerate(Dvar_input.keys()):
+ if isinstance(path, list):
+ ipath = path[i]
+ else:
+ ipath = path
print('Reading file ' + keyFiles)
- print(path + LnameFiles[i])
- theFile = nc.Dataset(path + LnameFiles[i],'r')
+ print(ipath + LnameFiles[i])
+ theFile = nc.Dataset(ipath + LnameFiles[i], 'r')
Dvar[keyFiles] = {}
- if '000' in LnameFiles[i][-6:-3]:
+ if '000' in LnameFiles[i][-6:-3]:
if theFile['MASDEV'][0] <= 54:
raise TypeError('The python lib is available for MNH >= 5.5')
else:
Dvar[keyFiles] = read_TIMESfiles_55(theFile, Dvar_input[keyFiles], Dvar[keyFiles], get_data_only, del_empty_dim, removeHALO)
else:
- Dvar[keyFiles]= read_BACKUPfile(theFile, Dvar_input[keyFiles], Dvar[keyFiles], get_data_only, del_empty_dim, removeHALO)
- #theFile.close()
+ Dvar[keyFiles] = read_BACKUPfile(theFile, Dvar_input[keyFiles], Dvar[keyFiles], get_data_only, del_empty_dim, removeHALO)
+ # theFile.close()
return Dvar
+
def read_var(theFile, Dvar, var_name, get_data_only, del_empty_dim=True, removeHALO=True):
"""Read a netCDF4 variable
-
+
Parameters
----------
theFile : netCDF4._netCDF4.Dataset
a Meso-NH diachronic netCDF4 file
-
+
var_name : str
a Meso-NH netCDF4 variable name
-
+
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
+ 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 : Dict
Dvar['var_name'] if the group contains only one variable
Dvar[('group_name','var_name')] if the group contains more than one variable
"""
try:
var_dim = theFile.variables[var_name].ndim
var_dim_name = theFile.variables[var_name].dimensions
- except:
- raise KeyError("Group and variable name not found in the file, check the group/variable name with ncdump -h YourMNHFile.000.nc. You asked for variable : " + var_name)
+ except BaseException:
+ raise KeyError(
+ "Group and variable name not found in the file, check the group/variable name with ncdump -h YourMNHFile.000.nc. You asked for variable : " +
+ var_name)
if not get_data_only:
Dvar[var_name] = theFile.variables[var_name]
- else:
+ else:
if var_dim == 0:
Dvar[var_name] = theFile.variables[var_name][0].data
elif var_dim == 1:
Dvar[var_name] = theFile.variables[var_name][:]
elif var_dim == 2:
- Dvar[var_name] = theFile.variables[var_name][:,:]
+ Dvar[var_name] = theFile.variables[var_name][:, :]
elif var_dim == 3:
- Dvar[var_name] = theFile.variables[var_name][:,:,:]
+ Dvar[var_name] = theFile.variables[var_name][:, :, :]
elif var_dim == 4:
- Dvar[var_name] = theFile.variables[var_name][:,:,:,:]
+ Dvar[var_name] = theFile.variables[var_name][:, :, :, :]
elif var_dim == 5:
- Dvar[var_name] = theFile.variables[var_name][:,:,:,:,:]
+ Dvar[var_name] = theFile.variables[var_name][:, :, :, :, :]
elif var_dim == 6:
- Dvar[var_name] = theFile.variables[var_name][:,:,:,:,:,:]
+ Dvar[var_name] = theFile.variables[var_name][:, :, :, :, :, :]
elif var_dim == 7:
- Dvar[var_name] = theFile.variables[var_name][:,:,:,:,:,:,:]
+ Dvar[var_name] = theFile.variables[var_name][:, :, :, :, :, :, :]
if removeHALO:
for i in range(8):
try:
- if var_dim_name[i]=='level' or var_dim_name[i]=='level_w' or \
- var_dim_name[i]=='ni' or var_dim_name[i]=='ni_u' or var_dim_name[i]=='ni_v' or \
- var_dim_name[i]=='nj' or var_dim_name[i]=='nj_u' or var_dim_name[i]=='nj_v':
+ if var_dim_name[i] == 'level' or var_dim_name[i] == 'level_w' or \
+ var_dim_name[i] == 'ni' or var_dim_name[i] == 'ni_u' or var_dim_name[i] == 'ni_v' or \
+ var_dim_name[i] == 'nj' or var_dim_name[i] == 'nj_u' or var_dim_name[i] == 'nj_v':
if var_dim != 0:
- Dvar[var_name] = removetheHALO(i+1, Dvar[var_name])
- except:
+ Dvar[var_name] = removetheHALO(i + 1, Dvar[var_name])
+ except BaseException:
break
if del_empty_dim:
- Ldimtosqueeze=[]
+ Ldimtosqueeze = []
var_shape = theFile.variables[var_name].shape
for i in range(8):
try:
- if var_shape[i]==1: Ldimtosqueeze.append(i)
+ if var_shape[i] == 1:
+ Ldimtosqueeze.append(i)
except IndexError:
break
- Ldimtosqueeze=tuple(Ldimtosqueeze)
+ Ldimtosqueeze = tuple(Ldimtosqueeze)
Dvar[var_name] = np.squeeze(Dvar[var_name], axis=Ldimtosqueeze)
return Dvar
-def read_from_group(theFile, Dvar, group_name, var_name, get_data_only, del_empty_dim=True,removeHALO=True):
- """Read a variable from a netCDF4 group
-
+
+def read_from_group(theFile, Dvar, group_name, var_name, get_data_only, del_empty_dim=True, removeHALO=True):
+ """Read a variable from a netCDF4 group
+
Parameters
----------
theFile : netCDF4._netCDF4.Dataset
a Meso-NH diachronic netCDF4 file
-
+
group_name : str
a Meso-NH netCDF4 group name
-
+
var_name : str
a Meso-NH netCDF4 variable name
-
+
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
+ 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 : Dict
Dvar['var_name'] if the group contains only one variable
Dvar[('group_name','var_name')] if the group contains more than one variable
"""
try:
var_dim = theFile[group_name].variables[var_name].ndim
var_dim_name = theFile[group_name].variables[var_name].dimensions
- except:
- raise KeyError("Group and variable name not found in the file, check the group/variable name with ncdump -h YourMNHFile.000.nc. You asked for group/variable : " + group_name + var_name)
-
+ except BaseException:
+ raise KeyError(
+ "Group and variable name not found in the file, check the group/variable name with ncdump -h YourMNHFile.000.nc. You asked for group/variable : " +
+ group_name +
+ var_name)
+
if not get_data_only:
- Dvar[(group_name,var_name)] = theFile[group_name].variables[var_name]
+ Dvar[(group_name, var_name)] = theFile[group_name].variables[var_name]
else:
if var_dim == 0:
- Dvar[(group_name,var_name)] = theFile[group_name].variables[var_name][0].data
+ Dvar[(group_name, var_name)] = theFile[group_name].variables[var_name][0].data
if var_dim == 1:
- Dvar[(group_name,var_name)] = theFile[group_name].variables[var_name][:]
+ Dvar[(group_name, var_name)] = theFile[group_name].variables[var_name][:]
elif var_dim == 2:
- Dvar[(group_name,var_name)] = theFile[group_name].variables[var_name][:,:]
+ Dvar[(group_name, var_name)] = theFile[group_name].variables[var_name][:, :]
elif var_dim == 3:
- Dvar[(group_name,var_name)] = theFile[group_name].variables[var_name][:,:,:]
+ Dvar[(group_name, var_name)] = theFile[group_name].variables[var_name][:, :, :]
elif var_dim == 4:
- Dvar[(group_name,var_name)] = theFile[group_name].variables[var_name][:,:,:,:]
+ Dvar[(group_name, var_name)] = theFile[group_name].variables[var_name][:, :, :, :]
elif var_dim == 5:
- Dvar[(group_name,var_name)] = theFile[group_name].variables[var_name][:,:,:,:,:]
+ Dvar[(group_name, var_name)] = theFile[group_name].variables[var_name][:, :, :, :, :]
elif var_dim == 6:
- Dvar[(group_name,var_name)] = theFile[group_name].variables[var_name][:,:,:,:,:,:]
+ Dvar[(group_name, var_name)] = theFile[group_name].variables[var_name][:, :, :, :, :, :]
elif var_dim == 7:
- Dvar[(group_name,var_name)] = theFile[group_name].variables[var_name][:,:,:,:,:,:,:]
+ Dvar[(group_name, var_name)] = theFile[group_name].variables[var_name][:, :, :, :, :, :, :]
if removeHALO:
for i in range(8):
try:
- if var_dim_name[i]=='level' or var_dim_name[i]=='level_w' or \
- var_dim_name[i]=='ni' or var_dim_name[i]=='ni_u' or var_dim_name[i]=='ni_v' or \
- var_dim_name[i]=='nj' or var_dim_name[i]=='nj_u' or var_dim_name[i]=='nj_v':
+ if var_dim_name[i] == 'level' or var_dim_name[i] == 'level_w' or \
+ var_dim_name[i] == 'ni' or var_dim_name[i] == 'ni_u' or var_dim_name[i] == 'ni_v' or \
+ var_dim_name[i] == 'nj' or var_dim_name[i] == 'nj_u' or var_dim_name[i] == 'nj_v':
if var_dim != 0:
- Dvar[(group_name,var_name)] = removetheHALO(i+1, Dvar[(group_name,var_name)])
- except:
+ Dvar[(group_name, var_name)] = removetheHALO(i + 1, Dvar[(group_name, var_name)])
+ except BaseException:
break
if del_empty_dim:
- Ldimtosqueeze=[]
- var_shape = Dvar[(group_name,var_name)].shape
+ Ldimtosqueeze = []
+ var_shape = Dvar[(group_name, var_name)].shape
for i in range(8):
try:
- if var_shape[i]==1: Ldimtosqueeze.append(i)
+ if var_shape[i] == 1:
+ Ldimtosqueeze.append(i)
except IndexError:
break
- Ldimtosqueeze=tuple(Ldimtosqueeze)
- Dvar[(group_name,var_name)] = np.squeeze(Dvar[(group_name,var_name)], axis=Ldimtosqueeze)
-
+ Ldimtosqueeze = tuple(Ldimtosqueeze)
+ Dvar[(group_name, var_name)] = np.squeeze(Dvar[(group_name, var_name)], axis=Ldimtosqueeze)
+
# LES budget, ZTSERIES needs to be transposed to use psection functions without specifying .T each time
if 'LES_budget' in group_name or 'ZTSERIES' in group_name or 'XTSERIES' in group_name:
- Dvar[(group_name,var_name)] = Dvar[(group_name,var_name)].T
+ Dvar[(group_name, var_name)] = Dvar[(group_name, var_name)].T
return Dvar
+
def read_BACKUPfile(theFile, Dvar_input, Dvar, get_data_only, del_empty_dim=True, removeHALO=True):
"""Read variables from Meso-NH MASDEV >= 5.5.0 synchronous file
For all variables in Dvar_input of one file, call functions to read the variable of the group+variable
-
+
Parameters
----------
theFile : netCDF4._netCDF4.Dataset
a Meso-NH diachronic netCDF4 file
-
+
Dvar_input : Dict{'var_name',('group_name','var_name')}
with
'var_name' is the exact str of the netCDF4 variable name
@@ -281,35 +330,40 @@ def read_BACKUPfile(theFile, Dvar_input, Dvar, get_data_only, del_empty_dim=True
e.g. : {'f1':['ZS', 'WT','ni', 'level'],
'f2':[('/LES_budgets/Cartesian/Not_time_averaged/Not_normalized/cart/',MEAN_TH'),('/Budgets/RI','AVEF')]
}
-
+
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 masked_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)
-
+
Returns
-------
- Dvar : Dict
+ Dvar : Dict
Dvar['var_name'] if the group contains only one variable
Dvar[('group_name','var_name')] if the group contains more than one variable
- """
- # Reading date since beginning of the model run
- Dvar['time'] = theFile.variables['time'][0]
- Dvar['date'] = nc.num2date(Dvar['time'],units=theFile.variables['time'].units, calendar = theFile.variables['time'].calendar)
+ """
+ # Reading date since beginning of the model run if theFile is a Meso-NH netCDF file
+ if 'MNH_cleanly_closed' in theFile.ncattrs():
+ try:
+ Dvar['time'] = theFile.variables['time'][0]
+ Dvar['date'] = nc.num2date(Dvar['time'], units=theFile.variables['time'].units, calendar=theFile.variables['time'].calendar)
+ except BaseException:
+ pass
for var in Dvar_input:
- if type(var) == tuple:
+ if isinstance(var, tuple):
Dvar = read_from_group(theFile, Dvar, var[0], var[1], get_data_only, del_empty_dim, removeHALO)
else:
Dvar = read_var(theFile, Dvar, var, get_data_only, del_empty_dim, removeHALO)
# For all variables except scalars, change Fill_Value to NaN
if get_data_only:
- Dvar[var]= np.where(Dvar[var] != -99999.0, Dvar[var], np.nan)
- Dvar[var]= np.where(Dvar[var] != 999.0, Dvar[var], np.nan)
+ Dvar[var] = np.where(Dvar[var] != -99999.0, Dvar[var], np.nan)
+ Dvar[var] = np.where(Dvar[var] != 999.0, Dvar[var], np.nan)
return Dvar
+
def read_TIMESfiles_55(theFile, Dvar_input, Dvar, get_data_only, del_empty_dim=True, removeHALO=True):
"""Read variables from Meso-NH MASDEV >= 5.5.0 diachronic file
For all variables in Dvar_input of one file, call functions to read the variable of the group+variable
@@ -318,7 +372,7 @@ def read_TIMESfiles_55(theFile, Dvar_input, Dvar, get_data_only, del_empty_dim=T
----------
theFile : netCDF4._netCDF4.Dataset
a Meso-NH diachronic netCDF4 file
-
+
Dvar_input : Dict{'var_name',('group_name','var_name')}
with
'var_name' is the exact str of the netCDF4 variable name
@@ -326,57 +380,58 @@ def read_TIMESfiles_55(theFile, Dvar_input, Dvar, get_data_only, del_empty_dim=T
e.g. : {'f1':['ZS', 'WT','ni', 'level'],
'f2':[('/LES_budgets/Cartesian/Not_time_averaged/Not_normalized/cart/',MEAN_TH'),('/Budgets/RI','AVEF')]
}
-
+
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 masked_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)
-
+
Returns
-------
- Dvar : Dict
+ 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
- """
+ """
for var in Dvar_input:
- if type(var) == tuple:
+ if isinstance(var, tuple):
Dvar = read_from_group(theFile, Dvar, var[0], var[1], get_data_only, del_empty_dim, removeHALO)
else:
Dvar = read_var(theFile, Dvar, var, get_data_only, del_empty_dim, removeHALO)
return Dvar
+
def removetheHALO(idim, var):
"""Remove a NHALO=1 point [1:-1] at a given dimension idim of a variable var
TODO: with NHALO=3 with WENO5
TODO: with the use of get_data_only=False (NetCDF4 output)
-
+
Parameters
----------
idim: int
the dimension over which remove the first and last point
-
+
var: array
a Meso-NH netCDF4 variable name
-
+
Returns
-------
- var : array
- """
+ var : array
+ """
if idim == 1:
var = var[1:-1]
elif idim == 2:
- var = var[:,1:-1]
+ var = var[:, 1:-1]
elif idim == 3:
- var = var[:,:,1:-1]
+ var = var[:, :, 1:-1]
elif idim == 4:
- var = var[:,:,:,1:-1]
+ var = var[:, :, :, 1:-1]
elif idim == 5:
- var = var[:,:,:,:,1:-1]
+ var = var[:, :, :, :, 1:-1]
elif idim == 6:
- var = var[:,:,:,:,:,1:-1]
+ var = var[:, :, :, :, :, 1:-1]
elif idim == 7:
- var = var[:,:,:,:,:,:,1:-1]
+ var = var[:, :, :, :, :, :, 1:-1]
return var