Changeset 1996 in lmdz_wrf

Timestamp:

Jul 31, 2018, 9:18:15 PM (7 years ago)

Author:

lfita

Message:

Adding:

• `draw_multiWindRose': Function to plot multiple wind rose (from where the dinw blows)

Location:

trunk/tools

Files:

• drawing.py (modified) (6 diffs)
• drawing_tools.py (modified) (3 diffs)

trunk/tools/drawing.py

@@ -63 +63 @@
 ## e.g. # drawing.py -o draw_2D_shad_contdisc_time -f 'simout_snddiags.nc;ta;time;pres;time|-1,pres|-1@UWyoming_snd_87576.nc;ta;time;pres;time|-1,pres|-1' -S 'ta;y;auto|exct,12,h|%d$^{%H}$|time!($[DD]^{[HH]}$);Vfix,auto,50.,auto;auto;Srange,Srange;auto;obs!&!sim!Ezeiza!airport!sounding;pdf;flip@y;None;yes'
 ## e.g. # drawing.py -o draw_2D_shad_contdisc -f 'simout_sfcdiags.nc;tdas;XLONG;XLAT;Time|0,time|0,west_east|-1,south_north|-1@all_single-stations.nc;tdas;stslon;stslat;time|0,lon|-1,lat|-1' -S 'tdas:west_east,south_north:auto:YlGnBu,auto,auto:286.,298.:auto:obs!&!sim!tdas!on!1995/01/01!00!UTC:png:None:cyl,f:sponge,0.1,0.1:yes'
+## e.g. # drawing.py -o draw_multiWindRose -f '/media/lluis/ExtDiskC_ext3/DATA/estudios/FPS_Alps/additional/IOP/select/out/sounding_uava_10868.nc@pres|-1;time|1@ua,va#/media/lluis/ExtDiskC_ext3/DATA/estudios/FPS_Alps/additional/IOP/select/out/simout_vars_sndpt_10868_38lev.nc@bottom_top|-1;time|0@ua,va#/media/lluis/ExtDiskC_ext3/DATA/estudios/FPS_Alps/additional/IOP/select/out/simout_vars_sndpt_10868_50lev.nc@bottom_top|-1;time|0@ua,va#/media/lluis/ExtDiskC_ext3/DATA/estudios/FPS_Alps/additional/IOP/select/out/simout_vars_sndpt_10868_50lev_assigned.nc@bottom_top|-1;time|0@ua,va#/media/lluis/ExtDiskC_ext3/DATA/estudios/FPS_Alps/additional/IOP/select/out/simout_vars_sndpt_10868_80lev.nc@bottom_top|-1;time|0@ua,va#/media/lluis/ExtDiskC_ext3/DATA/estudios/FPS_Alps/additional/IOP/select/out/simout_vars_sndpt_10868_120lev.nc@bottom_top|-1;time|0@ua,va#/media/lluis/ExtDiskC_ext3/DATA/estudios/FPS_Alps/additional/IOP/select/out/simout_vars_sndpt_10868_NOaerosol.nc@bottom_top|-1;time|0@ua,va' -S 'linepoint;multicol;pres;-;auto;spectral;auto:obs,38lev,50lev,50leva,80lev,120lev:WindRose!obs!sim!comparison!on!2012/10/23!00!UTC:png:auto:True'
 
 #######
@@ -91 +92 @@
 # draw_multi_2D_shad: plotting multiple 2D fields with same projection with shading and sharing colorbar
 # draw_multi_SkewT: creation of a SkewT-logP diagram with multiple lines using matplotlib's API example
+# draw_multiWindRose: Function to plot multiple wind rose (from where the dinw blows)
 # draw_Neighbourghood_evol: Function to draw the temporal evolution of a neighbourghood around a point
 # draw_points: Function to plot a series of points
@@ -124 +126 @@
   'draw_2D_shad_line_time', 'draw_bar', 'draw_bar_line', 'draw_bar_line_time',       \
   'draw_bar_time', 'draw_barbs', 'draw_basins', 'draw_cycle', 'draw_ensembles_time', \
-  'draw_2lines', 'draw_2lines_time', 'draw_multi_2D_shad', 'draw_multi_SkewT',       \
+  'draw_2lines', 'draw_2lines_time',                                                 \
   'draw_lines', 'draw_lines_time',                                                   \
+  'draw_multi_2D_shad', 'draw_multi_SkewT', 'draw_multiWindRose',                    \
   'draw_Neighbourghood_evol',                                                        \
   'draw_points', 'draw_points_lonlat',                                               \
@@ -9894 +9897 @@
 #draw_2D_shad_contdisc_time(contfilen+'@'+discfilen, values, axfig=None, fig=None)
 
+def draw_multiWindRose(ncfiles, values):
+    """ Function to plot multiple wind rose (from where the dinw blows)
+      ncfiles='#' separated list of [filen]@[dimvals]@[uvarn],[vvarn]
+        [filen]: name of the file
+        [dimvals]: ';' list of [dimn]|[dvalue] dimension and slice along dimension to retrieve the winds
+          [dimn]: name of the dimension
+          [dvalue]: value for the slice in the given dimension
+            * [integer]: which value of the dimension
+            * -1: all along the dimension
+            * -9: last value of the dimension
+            * [beg],[end],[freq] slice from [beg] to [end] every [freq]
+            * NOTE, no dim name all the dimension size
+          No value takes all the range of the dimension
+        [uvarn],[vvarn]: name of the x and y wind components
+      values=[kindRose]:[labels]:[imgtit]:[imgkind]:[kindlabelsangle]:[close]
+        [kindRose]: [kind];[value1];[...[valueN]] Kind of rose to plot and values of the kind
+          'linepoint': consecutive (time, height, level, ...) line-point angle and speed values. Three different species
+            'multicol': line-marker color changing according to a third variable [extravarn]
+               values: [extravarn];[lines];[markers];[colbar];[Nang]
+            'multicoltime': line-marker color changing according to a temporal variable [extravarn]
+               values: [extravarn];[lines];[markers];[colbar];[Nang];[timekind];[timefmt];[timelabel]
+            'singlecol': same color for the line-marker
+               values: [lines];[markers];[cols];[Nang]
+          'scatter': a marker for each wind at different values (time, height, level, ...). Three different species
+            'multicol':marker color changing according to a third variable [extravarn]
+               values: [extravarn];[markers];[colbar];[Nang]
+            'multicoltime': marker color changing according to a temporal variable [extravarn]
+               values: [extravarn];[lines];[markers];[colbar];[Nang];[timekind];[timefmt];[timelabel]
+            'singlecol': same color for all the markers
+              values: [markers];[cols];[Nang]
+           meaning (where apply):
+             [extravarn]: name of the extra variable 
+             [lines]: '@' separated list of type of lines (matplotlib ref)
+             [markers]: '@' separated list of type of markers to use (matplotlib ref)
+             [cols] = '@' separated list of colors ('#[RR][GG][BB])
+             [colbar]: name of the colorbar ('auto' for 'spectral_r')
+             [Nang]: number of angles to divide the rose ('auto' for 8)
+             [Nspeed]: number of speeds to divide the wind speed distribution ('auto' for 8)
+             [maxspeed]: maximum wind speed used to compute the frequency of distributions ('auto' for 40.)
+             [timekind]; time computation of ticks
+               'Nval': according to a given number of values as 'Nval',[Nval]
+               'exct': according to an exact time unit as 'exct',[tunit]; 
+                 tunit= [Nunits],[tu]; [tu]= 'c': centuries, 'y': year, 'm': month,
+                  'w': week, 'd': day, 'h': hour, 'i': minute, 's': second, 
+                  'l': milisecond
+             [timefmt]; desired format of time labels (C-like)
+             [timelabel]; label of time colorbar at the graph ('!' for spaces)
+        labels: ',' separated list of labels for the legend ('None' for no label)
+        imgtit: title of the image ('!' for spaces)
+        imgkind: kind of file output of the image (ps, pns, pdf, ...)
+        kindlabelsangle: kind of labels for the angles of the wind Rose
+          'cardianals': Following combinations of 'N', 'E', 'S', 'W' according to Nang
+        close: whether figure should be closed or not
+    """
+    fname = 'draw_WindRose'
+
+    if values == 'h':
+        print fname + '_____________________________________________________________'
+        print draw_multiWindRose.__doc__
+        quit()
+
+    expectargs = '[kindRose]:[labels]:[imgtit]:[imgkind]:[kindlabelsangle]:' + \
+      '[close]'
+    drw.check_arguments(fname,values,expectargs,':')
+
+    dimvariables = values.split(':')[0]
+
+    KindRose = values.split(':')[0]
+    labels = values.split(':')[1].split(',')
+    imgtit = values.split(':')[2].replace('!',' ')
+    imgkind = values.split(':')[3]
+    kindlabelsangle = values.split(':')[4]
+    close = gen.Str_Bool(values.split(':')[5])
+    
+    windrosekinds = ['linepoint', 'scatter']
+
+    if KindRose.find(';') == -1:
+        print errormsg
+        print '  ' + fname + ": all types '" + KindRose + "' require extra values !!"
+        print "    'linepoint';'singlecol';[line];[marker];[col];[Nang]"
+        print "    'linepoint';'multiecoltime';[extravar];[line];[marker];[colbar];"+\
+          "[Nang];[timekind];[timefmt];[timelabel]"
+        print "    'linepoint';'multiecol';[extravar];[line];[marker];[colbar];[Nang]"
+        print "    'scatter';'multiecol';[extravar];[marker];[colbar]"
+        print "    'scatter';'multiecoltime';[extravar];[marker];[colbar];[Nang];" + \
+          "[timekind];[timefmt];[timelabel]"
+        print "    'scatter';'singlecol';[marker];[col];[Nang]"
+        print "  values provided: '" + KindRose + "'" 
+        quit(-1)
+
+    lpvals = KindRose.split(';')
+    lkind = lpvals[1]
+
+    extravarn = None
+
+    if lpvals[0] == 'linepoint':
+        if lkind == 'multicol':
+            if len(lpvals) != 7:
+                print errormsg
+                print '  ' + fname + ": line-point kind '" + lkind + "' requires " + \
+                  "6 values !!"
+                print "    'multiecol';[extravarn];[line];[marker];[colbar];[Nang]"
+                print '    provided:', lpvals
+                quit(-1)     
+            extravarn = lpvals[2]
+        elif lkind == 'multicoltime':
+            if len(lpvals) != 10:
+                print errormsg
+                print '  '+fname + ": scatter kind '"+lkind+ "' requires 9 values !!"
+                print "    'multicol';[extravarn];[line];[marker];[colbar];[Nang];"+ \
+                  "[timekind];[timefmt];[timelabel]"
+                print '    provided:', lpvals
+                quit(-1)     
+            extravarn = lpvals[2]
+            timekind = lpvals[6]
+            timefmt = lpvals[7]
+        elif lkind == 'singlecol':
+            if len(lpvals) != 6:
+                print errormsg
+                print '  '+fname+": line-point kind '"+lkind+ "' requires 5 values !!"
+                print "    'singlecol';[line];[marker];[col];[Nang]"
+                print '    provided:', lpvals
+                quit(-1)     
+        else:
+            print errormsg
+            print '  ' + fname + ": line-point kind '" + lkind + "' not ready !!"
+            print '    ready ones: multicol, multicoltime, singlecol '
+            quit(-1)
+
+    elif lpvals[0] == 'scatter':
+        if lkind == 'multicol':
+            if len(lpvals) != 6:
+                print errormsg
+                print '  '+fname+": scatter kind '"+lkind+"' requires 5 values !!"
+                print "    'multicol';[extravarn];[marker];[colbar];[Nang]"
+                print '    provided:', lpvals
+                quit(-1)     
+            extravarn = lpvals[2]
+        elif lkind == 'multicoltime':
+            if len(lpvals) != 9:
+                print errormsg
+                print '  ' + fname + ": scatter kind '"+lkind+"' requires 8 values !!"
+                print "    'multicol';[extravarn];[marker];[colbar];[Nang];" +       \
+                  "[timekind];[timefmt];[timelabel]"
+                print '    provided:', lpvals
+                quit(-1)     
+            extravarn = lpvals[2]
+            timekind = lpvals[5]
+            timefmt = lpvals[6]
+        elif lkind == 'singlecol':
+            if len(lpvals) != 5:
+                print errormsg
+                print '  '+fname + ": scatter kind '"+lkind+ "' requires 4 values !!"
+                print "    'singlecol';[marker];[col];[Nang]"
+                print '    provided:', lpvals
+                quit(-1)     
+        else:
+            print errormsg
+            print '  ' + fname + ": scatter kind '" + lkind + "' not ready !!"
+            print '    ready ones: multicol, multicoltime, singlecol '
+            quit(-1)
+
+    else:
+        print gen.errormsg
+        print '  ' +  fname + ": kind of WindRose '" + lpvals[0] + "' not ready !!"
+        print '    available ones:', windrosekinds
+        quit(-1)
+
+    angles = []
+    speeds = []
+    extravs = []
+    fvarns = ncfiles.split('#')
+    for fvn in fvarns:
+        ncfile = fvn.split('@')[0]
+        dimvariables = fvn.split('@')[1]
+        uvarn = fvn.split('@')[2].split(',')[0]
+        vvarn = fvn.split('@')[2].split(',')[1]
+
+        if not os.path.isfile(ncfile):
+            print errormsg
+            print '  ' + fname + ": file '" + ncfile + "' does not exist !!"
+            quit(-1)
+
+        onc = NetCDFFile(ncfile,'r')
+        oncvars0 = onc.variables.keys()
+        oncvars = oncvars0 + []
+        oncvars.sort()
+
+        if not gen.searchInlist(oncvars,uvarn):
+            print errormsg
+            print '  ' + fname + ": file '" + ncfile + "' does not have variable " +     \
+              "u_wind '" + uvarn + "' !!"
+            print '    available variables:', oncvars
+            quit(-1)
+        if not gen.searchInlist(oncvars,vvarn):
+            print errormsg
+            print '  ' + fname + ": file '" + ncfile + "' does not have variable " +     \
+              "v_wind '" + vvarn + "' !!"
+            print '    available variables:', oncvars
+            quit(-1)
+        if extravarn is not None:
+            if not gen.searchInlist(oncvars,extravarn):
+                print errormsg
+                print '  ' + fname + ": file '" + ncfile + "' does not have extra " +    \
+                  "variable '" + extravarn + "' !!"
+                print '    available variables:', oncvars
+                quit(-1)
+
+        # Getting the slice
+        dictslice = {}
+        for dnv in dimvariables.split(';'):
+            dimn = dnv.split('|')[0]
+            dimv = dnv.split('|')[1]
+            if dimv.find(',') != -1: 
+                dictslice[dimn] = list(np.array(dimv.split(','), dtype=int))
+            else:
+                dictslice[dimn] = int(dimv)
+
+        # Getting variables
+        ou = onc.variables[uvarn]
+        sliceu, du = ncvar.SliceVarDict(ou, dictslice)
+        uv = ou[tuple(sliceu)]
+        ov = onc.variables[vvarn]
+        slicev, dv = ncvar.SliceVarDict(ov, dictslice)
+        vv = ov[tuple(slicev)]
+        wunit = ov.getncattr('units')
+        if extravarn is not None:
+            oe = onc.variables[extravarn]
+            slicee, de = ncvar.SliceVarDict(oe, dictslice)
+            extrav = oe[tuple(slicee)]
+            dime = extrav.shape[0]
+            extraunit = oe.getncattr('units')
+        else:
+            dime = uv.shape[0]
+            extrav = None
+            extraunit = None
+    
+        onc.close()
+
+        # Wind Rose is with the winds from where they come from!
+        ang = np.arctan2(-vv, -uv)
+        speed = np.sqrt(uv*uv + vv*vv)
+
+        # re-setting to [0, 2pi]
+        ang = np.where(ang <= 0., 2.*np.pi+ang, ang)
+        ang = np.where(np.mod(ang,2.*np.pi) == 0., 0., ang)
+
+        angles.append(ang)
+        speeds.append(speed)
+        if extrav is not None: extravs.append(extrav)
+
+    drw.plot_multiWindRose(angles, speeds, dime, lpvals, kindlabelsangle, wunit,     \
+      labels, imgtit, imgkind, 'multi_WindRose', close, evs=extravs, eunit=extraunit)
+
+    return
+
+#filenames='/media/lluis/ExtDiskC_ext3/DATA/estudios/FPS_Alps/additional/IOP/select/out/sounding_uava_10868.nc@pres|-1;time|1@ua,va#' + \
+#  '/media/lluis/ExtDiskC_ext3/DATA/estudios/FPS_Alps/additional/IOP/select/out/simout_vars_sndpt_10868_38lev.nc@bottom_top|-1;time|12@ua,va#' +  \
+#  '/media/lluis/ExtDiskC_ext3/DATA/estudios/FPS_Alps/additional/IOP/select/out/simout_vars_sndpt_10868_50lev.nc@bottom_top|-1;time|12@ua,va#' +  \
+#  '/media/lluis/ExtDiskC_ext3/DATA/estudios/FPS_Alps/additional/IOP/select/out/simout_vars_sndpt_10868_50lev_assigned.nc@bottom_top|-1;time|12@ua,va#' +  \
+#  '/media/lluis/ExtDiskC_ext3/DATA/estudios/FPS_Alps/additional/IOP/select/out/simout_vars_sndpt_10868_80lev.nc@bottom_top|-1;time|12@ua,va#' +  \
+#  '/media/lluis/ExtDiskC_ext3/DATA/estudios/FPS_Alps/additional/IOP/select/out/simout_vars_sndpt_10868_120lev.nc@bottom_top|-1;time|12@ua,va#' + \
+#  '/media/lluis/ExtDiskC_ext3/DATA/estudios/FPS_Alps/additional/IOP/select/out/simout_vars_sndpt_10868_NOaerosol.nc@bottom_top|-1;time|12@ua,va'
+#wrkind='linepoint;multicol;pres;-;x;spectral;auto'
+#figvalues=wrkind + ':obs,38lev,50lev,50leva,80lev,120lev:WindRose!obs!,!sim!comparison!on!2012/10/23!12!UTC:png:auto:True'
+
+#draw_multiWindRose(filenames, figvalues)
 
 #quit()
@@ -9920 +10190 @@
   'draw_cycle', 'draw_ensembles_time', 'draw_multi_2D_shad', 'draw_multi_SkewT',     \
   'draw_lines',                                                                      \
-  'draw_lines_time', 'draw_points', 'draw_Taylor', 'draw_time_lag',                  \
-  'draw_topo_geogrid_boxes',                                                         \
+  'draw_lines_time', 'draw_multiWindRose', 'draw_points', 'draw_Taylor',             \
+  'draw_time_lag', 'draw_topo_geogrid_boxes',                                        \
   'draw_trajectories', 'draw_vals_trajectories', 'variable_values']
 
@@ -10015 +10285 @@
     elif oper == 'draw_multi_SkewT':
         draw_multi_SkewT(opts.ncfile, opts.values)
+    elif oper == 'draw_multiWindRose':
+        draw_multiWindRose(opts.ncfile, opts.values)
     elif oper == 'draw_points':
         draw_points(opts.ncfile, opts.values)

trunk/tools/drawing_tools.py

@@ -117 +117 @@
 pointkindsauto = ['.', 'x', '+', '*', '|', '_', '1', '2', '3', '4', 'o', '<', '>',   \
   'v', '^', 's', 'D', 'p' ,'h' ,'H']
+
 linekindsauto = ['-', '--', '-.', ':']
 linewidthsauto = [1.]
@@ -184 +185 @@
 # plot_cycle: Function to plot a variale with a circular cycle
 # plot_lines: Function to plot a collection of lines
+# plot_multiWindRose: Function to plot multi wind roses (from where the dinw blows)
 # plot_SkewT: Function to plot a SkewT-logP diagram using matplotlib's API example 
 # plot_Taylor: Function to draw a Taylor diagram (Taylor 2001)
@@ -8838 +8840 @@
     return
 
+def plot_multiWindRose(angs, speeds, dime, lpvals, thetalabs, windu, labs, titimg,   \
+  kfig, figname, close, evs=None, eunit=None):
+    """ Function to plot multi wind roses (from where the dinw blows)
+      angs= list of angles of the winds
+      speeds= list of speed of the winds
+      Nang= number of angles to split the total circumference
+      Nspeed= number of speed sections to split the wind distribution
+      maxspeed= maximum wind speed to be plotted
+      dime= number of winds to plot
+      lpvals= values to configure the kind of Wind Rose to plot
+        lpvals[0]: kind of Wind Rose
+        lpvals[1]: specie of kind of Wind Rose
+        lpvals[>=2]: specific values for the specie Wind Rose
+        'linepoint';[kind];[val1];[...;[valN]]: consecutive (time, height, level, ...) line-point angle and speed values
+          'multicol';[extravarn];[lines];[markers];[colbar]
+          'multicoltime';[extravarn];[lines];[markers];[colbar];[timekind];[timefmt];[timelabel]
+          'singlecol';[lines];[markers];[cols]
+        'scatter';[kind];[val1];[...;[valN]]: a cross for each wind at different values (time, height, level, ...)
+          'multicol';[extravarn];[markers];[colbar]
+          'multicoltime';[extravarn];[lines];[markers];[colbar];[timekind];[timefmt];[timelabel]
+          'singlecol';[markers];[cols]
+      windu= units of the wind speed
+      thetalabs= kind of labels for the angles of the wind-rose
+        'cardianals': Following combinations of 'N', 'E', 'S', 'W' according to Nang
+      titimg= title of the image
+      kfig= kind of figure's file output 
+      labs= list of labels ('None' for no label)
+      figname= name of the figure
+      close= wether figure has to be closed or not
+      evs= extra values (for certain Wind Roses: 'linepoint/scatter' 'multicol' & 'multicoltime')
+      eunits= units of the extravalues (for certain Wind Roses)
+    """
+    fname = 'plot_multiWindRose'
+    
+    Nsnds = len(labs)
+
+    lkind = lpvals[1]
+
+    # Getting time values and ticks
+    if lkind == 'multicoltime':
+        if lpvals[0] == 'linepoint':
+            timekind = lpvals[7]
+            timefmt = lpvals[8]
+        elif lpvals[0] == 'scatter':
+            timekind = lpvals[6]
+            timefmt = lpvals[7]
+        timepos, timelabels = CFtimes_plot(evs[0], eunit, timekind, timefmt)
+    
+    # Plot
+    plt.rc('text', usetex=True)
+    ax = plt.subplot(111, projection='polar')
+
+    # Rosekind
+    if lpvals[0] == 'linepoint':
+        if lkind == 'multicol':
+            colbar = gen.auto_val(lpvals[5],'spectral_r')
+            Nang = gen.auto_val(lpvals[6],8)
+            # Setting up colors for each label
+            #   From: http://stackoverflow.com/questions/15235630/matplotlib-pick-up-one-color-associated-to-one-value-in-a-colorbar
+            vcolmin = 100000.
+            vcolmax = -1.*vcolmin
+            for isnds in range(Nsnds):
+                ev = evs[isnds]
+                nvc = np.min(ev)
+                xvc = np.max(ev)
+                if nvc < vcolmin: vcolmin = nvc
+                if xvc > vcolmax: vcolmax = xvc
+
+            my_cmap = plt.cm.get_cmap(colbar)
+            norm = mpl.colors.Normalize(vcolmin, vcolmax)
+
+            ltyps = gen.auto_val_list(lpvals[3].split('@'), Nsnds, linekindsauto)
+            lmrks = gen.auto_val_list(lpvals[4].split('@'), Nsnds, pointkindsauto)
+
+            for isnds in range(Nsnds):
+                ang = angs[isnds]
+                speed = speeds[isnds]
+                ev = evs[isnds]
+                ltyp = ltyps[isnds]
+                lmrk = lmrks[isnds]
+
+                sndS = labs[isnds]
+                dime = ang.shape[0]
+
+                for ie in range(dime-1):
+                    labcol = my_cmap(norm(ev[ie]))
+                    if ie == 0 and sndS != 'None':
+                        plt.plot([ang[ie], ang[ie+1]], [speed[ie], speed[ie+1]],     \
+                          ltyp, marker=lmrk, color=labcol, label=gen.latex_text(sndS))
+                    else:
+                        plt.plot([ang[ie], ang[ie+1]], [speed[ie], speed[ie+1]],     \
+                          ltyp, marker=lmrk, color=labcol)
+
+                ie = dime-1
+                labcol = my_cmap(norm(ev[ie]))
+                lcolS = gen.coldec_hex(labcol[0:3])
+                plt.plot(ang[ie], speed[ie], ltyp, marker=lmrk, color=lcolS)
+
+            # FROM: http://stackoverflow.com/questions/8342549/matplotlib-add-colorbar-to-a-sequence-of-line-plots
+            # For matplotlib v1.3 or greater the code becomes:
+            sm = plt.cm.ScalarMappable(cmap=colbar, norm=norm)
+            # fake up the array of the scalar mappable. Urgh...
+            sm._A = []
+            cbar = plt.colorbar(sm)
+            cbar.set_label(lpvals[2] + ' (' + units_lunits(eunit) + ')')
+
+        elif lkind == 'multicoltime':
+            colbar = gen.auto_val(lpvals[5],'spectral_r')
+            Nang = gen.auto_val(lpvals[6],8)
+            timekind = lpvals[7]
+            timefmt = lpvals[8]
+            timelabel = lpvals[9].replace('!',' ')
+            # Setting up colors for each label
+            #   From: http://stackoverflow.com/questions/15235630/matplotlib-pick-up-one-color-associated-to-one-value-in-a-colorbar
+            vcolmin = np.min(ev)
+            vcolmax = np.max(ev)
+            my_cmap = plt.cm.get_cmap(colbar)
+            norm = mpl.colors.Normalize(vcolmin, vcolmax)
+
+            for isnds in range(Nsnds):
+                ang = angs[isnds]
+                speed = speeds[isnds]
+                ltyp = gen.auto_val(lpvals[3].split('@')[isnds],'-')
+                lmrk = gen.auto_val(lpvals[4].split('@')[isnds],'x')
+                sndS = labs[isnds]
+
+                for ie in range(dime-1):
+                    labcol = my_cmap(norm(ev[ie]))
+                    lcolS = gen.coldec_hex(labcol[0:3])
+
+                    if ie == 0 and sndS != 'None':
+                        plt.plot([ang[ie], ang[ie+1]], [speed[ie], speed[ie+1]],     \
+                          ltyp, marker=lmrk, color=lcolS, label=sndS)
+                    else:
+                        plt.plot([ang[ie], ang[ie+1]], [speed[ie], speed[ie+1]],     \
+                          ltyp, marker=lmrk, color=lcolS)
+
+                ie = dime-1
+                labcol = my_cmap(norm(ev[ie]))
+                lcolS = gen.coldec_hex(labcol[0:3])
+                plt.plot(ang[ie], speed[ie], ltyp, marker=lmrk, color=lcolS)
+    
+            # FROM: http://stackoverflow.com/questions/8342549/matplotlib-add-colorbar-to-a-sequence-of-line-plots
+            # For matplotlib v1.3 or greater the code becomes:
+            sm = plt.cm.ScalarMappable(cmap=colbar, norm=norm)
+            # fake up the array of the scalar mappable. Urgh...
+            sm._A = []
+            cbar = plt.colorbar(sm, ticks=timepos)
+            cbar.set_label(timelabel)
+            cbar.ax.set_yticklabels(timelabels)
+
+            # An attempt using text...
+            #maxt = np.max(timepos)
+            #for it in range(len(timelabels)):
+            #    daxistT = 0.6
+            #    iaxistT = (1. - daxistT)/2.
+            #    itt = (timepos[it]-timepos[0])*daxistT/(maxt-timepos[0])
+            #    labcol = my_cmap(norm(timepos[it]))
+            #    plt.annotate(timelabels[it], xy=(0.87,iaxistT+itt), color=labcol,        \
+            #      xycoords='figure fraction', multialignment='center')
+            #plt.annotate(timelabel, xy=(0.97,0.5), color='k', rotation=90,               \
+            #  rotation_mode="anchor", xycoords='figure fraction', horizontalalignment='center')
+        elif lkind == 'singlecol':
+            Nang = gen.auto_val(lpvals[5],8)
+            for isnds in range(Nsnds):
+                ang = angs[isnds]
+                speed = speeds[isnds]
+                ltyp = gen.auto_val(lpvals[2].split('@')[isnds],'-')
+                lmrk = gen.auto_val(lpvals[3].split('@')[isnds],'x')
+                lcol = gen.auto_val(lpvals[4].split('@')[isnds],'b')
+                sndS = labs[isnds]
+
+                if sndS != 'None':
+                    plt.plot(ang, speed, ltyp, marker=lmrk, color=lcol, label=sndS)
+                else:
+                    plt.plot(ang, speed, ltyp, marker=lmrk, color=lcol)
+    
+    elif lpvals[0] == 'scatter':
+        if lkind == 'multicol':
+            colbar = gen.auto_val(lpvals[4],'spectral_r')
+            Nang = gen.auto_val(lpvals[5],8)
+
+            for isnds in range(Nsnds):
+                ang = angs[isnds]
+                speed = speeds[isnds]
+                lmrk = gen.auto_val(lpvals[3].split('@')[isnds],'x')
+                sndS = labs[isnds]
+
+                if sndS != 'None':
+                    plt.scatter(ang, speed, c=ev, cmap=colbar, marker=lmrk,label=sndS)
+                else:
+                    plt.scatter(ang, speed, c=ev, cmap=colbar, marker=lmrk)
+
+            cbar = plt.colorbar()
+            cbar.set_label(lpvals[2] + ' (' + units_lunits(eunit) + ')')
+        elif lkind == 'multicoltime':
+            colbar = gen.auto_val(lpvals[4],'spectral_r')
+            Nang = gen.auto_val(lpvals[5],8)
+            timekind = lpvals[6]
+            timefmt = lpvals[7]
+            timelabel = lpvals[8].replace('!',' ')
+            for isnds in range(Nsnds):
+                ang = angs[isnds]
+                speed = speeds[isnds]
+                lmrk = gen.auto_val(lpvals[3].split('@')[isnds],'x')
+                sndS = labs[isnds]
+
+                if sndS != 'None':
+                    plt.scatter(ang, speed, c=ev, cmap=colbar, marker=lmrk,label=sndS)
+                else:
+                    plt.scatter(ang, speed, c=ev, cmap=colbar, marker=lmrk)
+ 
+            cbar = plt.colorbar(ticks=timepos)
+            cbar.set_label(timelabel)
+            cbar.ax.set_yticklabels(timelabels)
+        elif lkind == 'singlecol':
+            Nang = gen.auto_val(lpvals[4],8)
+
+            for isnds in range(Nsnds):
+                ang = angs[isnds]
+                speed = speeds[isnds]
+                lmrk = gen.auto_val(lpvals[2].split('@')[isnds],'x')
+                lcol = gen.auto_val(lpvals[3].split('@')[isnds],'b')
+                sndS = labs[isnds]
+
+                if sndS != 'None':
+                    plt.plot(ang, speed, ',', marker=lmrk, color=lcol, label=sndS)
+                else:
+                    plt.plot(ang, speed, ',', marker=lmrk, color=lcol)
+    
+    if thetalabs == 'cardinals':
+        if Nang == 4:
+            thetalabs = ['N', 'E', 'S', 'W']
+        elif Nang == 8:
+            thetalabs = ['N', 'NE', 'E', 'SE', 'S', 'SW', 'W', 'NW']
+        elif Nang == 16:
+            thetalabs= ['N', 'NNE', 'NE', 'ENE', 'E', 'ESE', 'SE', 'SSE', 'S', 'SSW',\
+              'SW', 'WSW', 'W', 'WNW', 'NW', 'NNW']
+        else:
+            print errormsg
+            print '  ' + fname + ': number of angles:', Nang, "not ready for '" +    \
+              thetalabs + "' !!"
+            print '    available ones: 4, 8, 16'
+            quit(-1)
+
+        dang = 2.*np.pi / (Nang)        
+        angs = np.arange(Nang,dtype=np.float)*dang - dang/2.
+        ax.set_thetagrids((angs+dang/2.)*180./np.pi, thetalabs)
+    
+    ax.set_theta_zero_location('N')
+    ax.set_theta_direction(-1)
+    plt.annotate('wind (' + units_lunits(windu) + ')', xy=(0.75,0.06), color='k',    \
+      xycoords='figure fraction', horizontalalignment='center')
+
+    plt.legend()
+    plt.title(gen.latex_text(titimg))
+
+    output_kind(kfig, figname, close)
+
+    return
+
 def plot_Taylor(stdv, corrv, corrpv, vunits, mtyp, mcol, msize, mlabs, labkind,      \
   tkind, itit, kfig, closefig):