Changeset 427

Timestamp:

Nov 30, 2011, 10:05:32 AM (13 years ago)

Author:

acolaitis

Message:

PYTHON. Corrected bugs related to contour plots with overlines, and mymath.mean() with no Axis specified. Now working on LES format for pp.py... :)

Location:

trunk/UTIL/PYTHON

Files:

• mcs.py (modified) (2 diffs)
• mymath.py (modified) (1 diff)
• myplot.py (modified) (2 diffs)
• planetoplot.py (modified) (1 diff)

trunk/UTIL/PYTHON/mcs.py

@@ -33 +33 @@
    parser.add_option('-i', '--zrecast', action='store_true', dest='zrecast', default=False, help='Cast zrecast.e on diagfi file with MCS pressure levels. Will pass this operation is recasted file is already present, unless --override is specified. [False]')
    parser.add_option('--override', action='store_true', dest='override', default=False, help='Force zrecast.e to act even if recasted file is already present(will erase previous recasted file) [False]')
-
+   parser.add_option('--ditch', action='store_true', dest='ditch', default=False, help='Ditch recasted file when interpolation is performed. [False]')
    #############################
    ### Get options and variables
@@ -302 +302 @@
                         zvariables=all, \
                         znames=fullnames)
+   if opt.zrecast and opt.ditch:
+      print "removing interpolated file"
+      system("rm -f "+opt.file[0:len(opt.file)-3]+"_P.nc")

trunk/UTIL/PYTHON/mymath.py

@@ -26 +26 @@
               field.set_fill_value(np.NaN)
               zout=np.ma.array(field).mean(axis=axis)
-              zout.set_fill_value(np.NaN)
-              return zout.filled()
+              if axis is not None:
+                 zout.set_fill_value(np.NaN)
+                 return zout.filled()
+              else:return zout
            elif (np.isnan(np.sum(field)) and (type(field).__name__ not in 'MaskedArray')):
               zout=np.ma.masked_invalid(field).mean(axis=axis)
-              zout.set_fill_value([np.NaN])
-              return zout.filled()
+              if axis is not None:
+                 zout.set_fill_value([np.NaN])
+                 return zout.filled()
+              else:return zout
            else: 
               return np.array(field).mean(axis=axis)

trunk/UTIL/PYTHON/myplot.py

@@ -113 +113 @@
              output = mean(input[d4,:,:,:],axis=0)
              output = reduce_zaxis(output[d3,:,:],ax=0,yint=yint,vert=alt,indice=d3)
-             if anomaly: output = 100. * ((output / smooth(output,csmooth)) - 1.) 
+             if anomaly: output = 100. * ((output / smooth(output,csmooth)) - 1.)
              output = mean(output[d2,:],axis=0)
              output = mean(output[d1],axis=0)
@@ -685 +685 @@
              "TEMP_NIGHT":   "%.0f",\
              # Variables from MCS and mcs.py ncdf format
-             "DTEMP":     "%.0f",\
-             "NTEMP":   "%.0f",\
+             "DTEMP":        "%.0f",\
+             "NTEMP":        "%.0f",\
+             "DNUMBINTEMP":  "%.0f",\
+             "NNUMBINTEMP":  "%.0f",\
              # other stuff
              "TPOT":         "%.0f",\

trunk/UTIL/PYTHON/planetoplot.py

@@ -280 +280 @@
               if var2 == 'HGT':  zelevels = np.arange(-10000.,30000.,2000.)
               if mapmode == 0:
-                  x, y = define_axis(lon,lat,vert,time,indexlon,indexlat,indexvert,\
-                        indextime,what_I_plot.shape, len(all_var2[index_f].shape),vertmode)
+                  what_I_plot, x, y = define_axis(lon,lat,vert,time,indexlon,indexlat,indexvert,\
+                        indextime,what_I_plot, len(all_var2[index_f].shape),vertmode)
               ### If we plot a 2-D field
               if len(what_I_plot.shape) is 2:
                   cs = contour(x,y,what_I_plot, zelevels, colors='k', linewidths = 1 ) #0.33 colors='w' )# , alpha=0.5)
-                  #if typefile in ['gcm']: clabel(cs,fmt = '%1.2e')
+#                  clabel(cs,#zelevels[::2],
+#                     inline=3,
+#                     fmt='%1.1e',
+#                     fontsize=7)
               ### If we plot a 1-D field
               elif len(what_I_plot.shape) is 1: