draw_2D_shad_contdisc_time(ncfiles, values)
   ncfiles= [contfilen];[contvarn];[dimtvarn];[dimvvarn];[dimvals]@[discfilen];
      [discvarn];[dimtvarn];[dimvvarn];[dimvals] files and variables to use
    [contfilen]: name of the file with the continuous varible
    [contvarn]: name of the continuos variable
    [dimtvarn]: name of the variable with values for the time-dimension
    [dimvvarn]: name of the variable with values for the variable-dimension
    [dimvals]: ',' list of [dimname]|[value] values to slice the variable:
      * [integer]: which value of the dimension
      * -1: all along the dimension
      * -9: last value of the dimension
      * [beg]@[end]@[inc] slice from [beg] to [end] every [inc]
      * NOTE, no dim name all the dimension size
    [discfilen]: name of the file with the discrete varible
    [discvarn]: name of the discrete variable
    * NOTE: limits of the graph will be computed from the continuous variable
   values=[vnamefs];[varaxis];[timevals];[dimvfmt];[colorbarvals];[sminv],[smaxv];
     [discvals];[figt];[kindfig];[reverse];[mapv];[close]
    [vnamefs]: Name in the figure of the variable to be shaded
    [varaxis]: axis in the figure for the variable-axis ('x' or 'y')
    [timevals]: [units]|[kind]|[tfmt]|[label] time labels characteristics
      [units]: units string according to CF conventions ([tunits] since
        [YYYY]-[MM]-[DD] [[HH]:[MI]:[SS]], '!' for spaces),
        'auto' for minutes!since!1949-12-01!00:00:00
      [kind]: kind of output
        '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
      [tfmt]: desired format (combination of 'C'-style values and LaTeX)
      [label]: label at the graph ('!' for spaces, combination of 'C'-style
        values and LaTeX)
    [dimvfmt]=[[dvs],[dvf],[Ndv],[ordv]: format of the values at variable-axis
        (or 'auto')
      [dvs]: style of variable-axis ('auto' for 'pretty')
        'Nfix', values computed at even 'Ndx'
        'Vfix', values computed at even 'Ndx' increments
        'pretty', values computed following aprox. 'Ndx' at 'pretty' intervals (2.,2.5,4,5,10)
      [dvf]: format of the labels at the var-axis ('auto' for '%5g')
      [Ndv]: Number of ticks at the var-axis ('auto' for 5)
      [ordv]: angle of orientation of ticks at the var-axis ('auto' for horizontal)
    [colorbarvals]=[colbarn],[fmtcolorbar],[orientation]
      [colorbarn]: name of the color bar
      [fmtcolorbar]: format of the numbers in the color bar 'C'-like ('auto' for %6g)
      [orientation]: orientation of the colorbar ('vertical' ['auto'], 'horizontal')
      * NOTE: single 'auto' for 'rainbow,%6g,vertical'
    [smin/axv]: minimum and maximum values for the shading or string for each for:
      'Srange': for full range
      'Saroundmean@val': for mean-xtrm,mean+xtrm where
        xtrm = np.min(mean-min@val,max@val-mean)
      'Saroundminmax@val': for min*val,max*val
      'Saroundpercentile@val': for median-xtrm,median+xtrm where
        xtrm = np.min(median-percentile_(val),percentile_(100-val)-median)
      'Smean@val': for -xtrm,xtrm where xtrm = np.min(mean-min*@val,max*@val-mean)
      'Smedian@val': for -xtrm,xtrm where
         xtrm = np.min(median-min@val,max@val-median)
      'Spercentile@val': for -xtrm,xtrm where
         xtrm = np.min(median-percentile_(val),percentile_(100-val)-median)
    [discvals]= [type],[size],[lwidth],[lcol] characteristics of the points for the discrete field
      [type]: type of point. Any marker from matoplib must be filled !
      [size]: size of point
      [lwidth]: width of the line around the point
      [lcol]: color of the line around the point
      * 'auto': for [type]='o', [size]=5, [lwdith]=0.25, [lcol]='#000000'
    [figt]: title of the figure ('!' for spaces)
    [kindfig]: kind of figure output (ps, png, pdf)
    [reverse]: Transformation of the values to plot
      * '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', lambert conformal
      [res]: resolution of the coastaline data:
        * 'c', crude
        * 'l', low
        * 'i', intermediate
        * 'h', high
        * 'f', full
    [close]: Whether figure should be finished or not