Changeset 955 in lmdz_wrf for trunk/tools

Timestamp:

Jun 25, 2016, 7:15:26 PM (8 years ago)

Author:

lfita

Message:

Working version of 'shadow_contour' with 'transform'
'transform' do not flip the locations of the labels of the axis

Location:

trunk/tools

Files:

• drawing.py (modified) (1 diff)
• drawing_tools.py (modified) (4 diffs)

trunk/tools/drawing.py

@@ -611 +611 @@
 
     if mapvalue == 'None': mapvalue = None
+    if revals == 'None': revals = None
 
     drw.plot_2D_shadow_contour(valshad, valcont, vnamesfig, odimxv, odimyv, odimxu,  \

trunk/tools/drawing_tools.py

@@ -1624 +1624 @@
             if flip == 'x':
                 newvals = newvals[...,::-1]
-                if dv:
-                    newdxv = newdxv[...,::-1]
-                if dt:
-                    newdxt = newdxt[::-1]
-                if dl:
+#                if wdvx:
+#                    if len(newdxv.shape) > 1:
+#                        newdxv = newdxv[...,::-1]
+#                    else:
+#                        newdxv = newdxv[::-1]
+#                if wdtx:
+#                    newdxt = newdxt[::-1]
+                if wdlx:
                     newdxl = newdxl[::-1]
             elif flip == 'y':
                 newvals = newvals[...,::-1,:]
-                if dv:
-                    newdyv = newdyv[...,::-1,:]
-                if dt:
-                    newdyt = newdyt[::-1]
-                if dl:
+#                if wdvy:
+#                    Ny=len(newdyt)
+#                    if len(newdyv.shape) > 1:
+#                        newdyv = newdyv[...,::-1]
+#                    else:
+#                        newdyv = newdyv[::-1]
+#                if wdty:
+#                    newdyt = newdyt[::-1]
+                if wdly:
                     newdyl = newdyl[::-1]
             elif flip == 'z':
@@ -4448 +4455 @@
         quit()
 
+    # Usually axis > x must be the lon, thus...
+    dimxv0 = dimxv.copy()
+    dimyv0 = dimyv.copy()
+    dimxt0 = np.array(pretty_int(dimxv.min(),dimxv.max(),10))
+    dimyt0 = np.array(pretty_int(dimyv.min(),dimyv.max(),10))
+    dimxl0 = []
+    for i in range(len(dimxt0)): dimxl0.append('{:.1f}'.format(dimxt0[i]))
+    dimyl0 = []
+    for i in range(len(dimyt0)): dimyl0.append('{:.1f}'.format(dimyt0[i]))
+    dimxT0 = variables_values(dimn[0])[0] + ' (' + units_lunits(dimxu) + ')'
+    dimyT0 = variables_values(dimn[1])[0] + ' (' + units_lunits(dimyu) + ')'
+
+    if reva is not None:
+        varcv, dimxv, dimyv, dimxt, dimyt, dimxl, dimyl, dimxT, dimyT =              \
+          transform(varcv, reva)
+        varsv, dimxv, dimyv, dimxt, dimyt, dimxl, dimyl, dimxT, dimyT =              \
+          transform(varsv, reva, dxv=dimxv0, dyv=dimyv0, dxt=dimxt0, dyt=dimyt0,     \
+          dxl=dimxl0, dyl=dimyl0, dxtit=dimxT0, dytit=dimyT0)
+    else:
+        dimxv = dimxv0
+        dimyv = dimyv0
+        dimxt = dimxt0
+        dimyt = dimyt0
+        dimxl = dimxl0
+        dimyl = dimyl0
+        dimxT = dimxT0
+        dimyT = dimyT0
+
+    if not mapv is None:
+        if len(dimxv[:].shape) == 3:
+            lon0 = dimxv[0,]
+            lat0 = dimyv[0,]
+        elif len(dimxv[:].shape) == 2:
+            lon0 = dimxv[:]
+            lat0 = dimyv[:]
+        elif len(dimxv[:].shape) == 1:
+            lon00 = dimxv[:]
+            lat00 = dimyv[:]
+            lon0 = np.zeros( (len(lat00),len(lon00)), dtype=np.float )
+            lat0 = np.zeros( (len(lat00),len(lon00)), dtype=np.float )
+
+            for iy in range(len(lat00)):
+                lon0[iy,:] = lon00
+            for ix in range(len(lon00)):
+                lat0[:,ix] = lat00
+
+        map_proj=mapv.split(',')[0]
+        map_res=mapv.split(',')[1]
+
+        dx = lon0.shape[1]
+        dy = lon0.shape[0]
+
+        nlon = lon0[0,0]
+        xlon = lon0[dy-1,dx-1]
+        nlat = lat0[0,0]
+        xlat = lat0[dy-1,dx-1]
+
+# Thats too much! :)
+#        if lonlatLims is not None:
+#            print '  ' + fname + ': cutting the domain to plot !!!!'
+#            plt.xlim(lonlatLims[0], lonlatLims[2])
+#            plt.ylim(lonlatLims[1], lonlatLims[3])
+#            print '    limits: W-E', lonlatLims[0], lonlatLims[2]
+#            print '    limits: N-S', lonlatLims[1], lonlatLims[3]
+
+#            if map_proj == 'cyl':
+#                nlon = lonlatLims[0]
+#                nlat = lonlatLims[1]
+#                xlon = lonlatLims[2]
+#                xlat = lonlatLims[3]
+#            elif map_proj == 'lcc':
+#                lon2 = (lonlatLims[0] + lonlatLims[2])/2.
+#                lat2 = (lonlatLims[1] + lonlatLims[3])/2.
+#                nlon =  lonlatLims[0]
+#                xlon =  lonlatLims[2]
+#                nlat =  lonlatLims[1]
+#                xlat =  lonlatLims[3]
+
+        lon2 = lon0[dy/2,dx/2]
+        lat2 = lat0[dy/2,dx/2]
+
+        print 'lon2:', lon2, 'lat2:', lat2, 'SW pt:', nlon, ',', nlat, 'NE pt:',     \
+          xlon, ',', xlat
+
+        if map_proj == 'cyl':
+            m = Basemap(projection=map_proj, llcrnrlon=nlon, llcrnrlat=nlat,         \
+              urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res)
+        elif map_proj == 'lcc':
+            m = Basemap(projection=map_proj, lat_0=lat2, lon_0=lon2, llcrnrlon=nlon, \
+              llcrnrlat=nlat, urcrnrlon=xlon, urcrnrlat= xlat, resolution=map_res)
+
+        if len(dimxv.shape) == 1:
+            lons, lats = np.meshgrid(dimxv, dimyv)
+        else:
+            if len(dimxv.shape) == 3:
+                lons = dimxv[0,:,:]
+                lats = dimyv[0,:,:]
+            else:
+                lons = dimxv[:]
+                lats = dimyv[:]
+ 
+        x,y = m(lons,lats)
+
+    else:
+        x,y = gen.lonlat2D(dimxv,dimyv)
+
+    plt.rc('text', usetex=True)
+
+    plt.pcolormesh(x, y, varsv, cmap=plt.get_cmap(colorbar), vmin=vs[0], vmax=vs[1])
+    cbar = plt.colorbar()
+
+# contour
+##
+    print fname + '; Lluis: shapes x:', x.shape,'y:',y.shape,'varcv:',varcv.shape
+    contkind = ckind.split(',')[0]
+    if contkind == 'cmap':
+        cplot = plt.contour(x, y, varcv, levels=vc)
+    elif  contkind == 'fixc':
+        plt.rcParams['contour.negative_linestyle'] = 'solid'
+        coln = ckind.split(',')[1]
+        cplot = plt.contour(x, y, varcv, levels=vc, colors=coln)
+    elif  contkind == 'fixsigc':
+        coln = ckind.split(',')[1]
+        cplot = plt.contour(x, y, varcv, levels=vc, colors=coln)
+    else:
+        print errormsg
+        print '  ' + fname + ': contour kind "' + contkind + '" not defined !!!!!'
+        quit(-1)
+
+    if clabfmt is not None:
+        plt.clabel(cplot, fmt=clabfmt)
+        mincntS = format(vc[0], clabfmt[1:len(clabfmt)])
+        maxcntS = format(vc[len(vc)-1], clabfmt[1:len(clabfmt)])
+    else:
+        mincntS = '{:g}'.format(vc[0])
+        maxcntS = '{:g}'.format(vc[len(vc)-1])        
+
+    if not mapv is None:
+        m.drawcoastlines()
+
+        meridians = pretty_int(nlon,xlon,5)
+        m.drawmeridians(meridians,labels=[True,False,False,True])
+        parallels = pretty_int(nlat,xlat,5)
+        m.drawparallels(parallels,labels=[False,True,True,False])
+
+        plt.xlabel('W-E')
+        plt.ylabel('S-N')
+    else:
+        plt.xlabel(dimxT)
+        plt.ylabel(dimyT)
+
+        plt.xticks(dimxt, dimxl)
+        plt.yticks(dimyt, dimyl)
+
+# set the limits of the plot to the limits of the data
+    plt.axis([x.min(), x.max(), y.min(), y.max()])
+
+
+# units labels
+    cbar.set_label(vnames[0].replace('_','\_') + ' (' + units_lunits(uts[0]) + ')')
+    plt.annotate(vnames[1].replace('_','\_') +' (' + units_lunits(uts[1]) + ') [' +  \
+      mincntS + ', ' + maxcntS + ']', xy=(0.55,0.04), xycoords='figure fraction',    \
+      color=coln)
+
+    figname = '2Dfields_shadow-contour'
+    graphtit = vtit.replace('_','\_').replace('&','\&')
+
+    plt.title(graphtit)
+    
+    output_kind(kfig, figname, True)
+
+    return
+
+#Nvals=50
+#vals1 = np.zeros((Nvals,Nvals), dtype= np.float)
+#vals2 = np.zeros((Nvals,Nvals), dtype= np.float)
+#for j in range(Nvals):
+#    for i in range(Nvals):
+#      vals1[j,i]=np.sqrt((j-Nvals/2)**2. + (i-Nvals/2)**2.)
+#      vals2[j,i]=np.sqrt((j-Nvals/2)**2. + (i-Nvals/2)**2.) - Nvals/2
+
+#prettylev=pretty_int(-Nvals/2,Nvals/2,10)
+
+#plot_2D_shadow_contour(vals1, vals2, ['var1', 'var2'], np.arange(50)*1.,             \
+#  np.arange(50)*1., ['x-axis','y-axis'], 'rainbow', 'fixc,b', "%.2f", [0, Nvals],    \
+#  prettylev, ['$ms^{-1}$','$kJm^{-1}s^{-1}$'], 'test var1 & var2', 'pdf', False)
+
+def plot_2D_shadow_contour_old(varsv,varcv,vnames,dimxv,dimyv,dimxu,dimyu,dimn,          \
+  colorbar,ckind,clabfmt,vs,vc,uts,vtit,kfig,reva,mapv):
+    """ Adding labels and other staff to the graph
+      varsv= 2D values to plot with shading
+      varcv= 2D values to plot with contours
+      vnames= variable names for the figure
+      dim[x/y]v = values at the axes of x and y
+      dim[x/y]u = units at the axes of x and y
+      dimn= dimension names to plot
+      colorbar= name of the color bar to use
+      ckind= contour kind
+        'cmap': as it gets from colorbar
+        'fixc,[colname]': fixed color [colname], all stright lines
+        'fixsigc,[colname]': fixed color [colname], >0 stright, <0 dashed  line
+      clabfmt= format of the labels in the contour plot (None, no labels)
+      vs= minmum and maximum values to plot in shadow
+      vc= vector with the levels for the contour
+      uts= units of the variable [u-shadow, u-contour]
+      vtit= title of the variable
+      kfig= kind of figure (jpg, pdf, png)
+      reva= 
+        * 'transpose': reverse the axes (x-->y, y-->x)
+        * 'flip'@[x/y]: flip the axis x or y
+      mapv= map characteristics: [proj],[res]
+        see full documentation: http://matplotlib.org/basemap/
+        [proj]: projection
+          * 'cyl', cilindric
+          * 'lcc', lamvbert conformal
+        [res]: resolution:
+          * 'c', crude
+          * 'l', low
+          * 'i', intermediate
+          * 'h', high
+          * 'f', full
+    """
+##    import matplotlib as mpl
+##    mpl.use('Agg')
+##    import matplotlib.pyplot as plt
+    fname = 'plot_2D_shadow_contour'
+
+    if varsv == 'h':
+        print fname + '_____________________________________________________________'
+        print plot_2D_shadow_contour.__doc__
+        quit()
+
     if reva[0:4] == 'flip':
         reva0 = 'flip'
@@ -4582 +4821 @@
 # contour
 ##
+    print fname + '; Lluis: shapes x:', x.shape,'y:',y.shape,'varcv:',varcv.shape
     contkind = ckind.split(',')[0]
     if contkind == 'cmap':
@@ -4652 +4892 @@
 
     return
-
-#Nvals=50
-#vals1 = np.zeros((Nvals,Nvals), dtype= np.float)
-#vals2 = np.zeros((Nvals,Nvals), dtype= np.float)
-#for j in range(Nvals):
-#    for i in range(Nvals):
-#      vals1[j,i]=np.sqrt((j-Nvals/2)**2. + (i-Nvals/2)**2.)
-#      vals2[j,i]=np.sqrt((j-Nvals/2)**2. + (i-Nvals/2)**2.) - Nvals/2
-
-#prettylev=pretty_int(-Nvals/2,Nvals/2,10)
-
-#plot_2D_shadow_contour(vals1, vals2, ['var1', 'var2'], np.arange(50)*1.,             \
-#  np.arange(50)*1., ['x-axis','y-axis'], 'rainbow', 'fixc,b', "%.2f", [0, Nvals],    \
-#  prettylev, ['$ms^{-1}$','$kJm^{-1}s^{-1}$'], 'test var1 & var2', 'pdf', False)
 
 def plot_2D_shadow_contour_time(varsv,varcv,vnames,valv,timv,timpos,timlab,valu,     \