def test():
import vcs
import cdms2 as cdms
import os
import support # import vcs and cdms
bg = support.bg
f = cdms.open(os.path.join(vcs.sample_data, 'clt.nc'))
s = f('clt') # get slab clt
x = vcs.init() # construct vcs canvas
x.plot(s, 'default', 'isofill', 'quick', bg=bg) # plot slab the old way
support.check_plot(x)
# Check the legend
g = x.createisofill('vcsmoduletest')
x.clear() # clear the VCS Canvas
x.plot(s, g, bg=bg) # plot slab the new way
support.check_plot(x)
g.legend = (10, 30, 70, 120)
support.check_plot(x)
g.legend = {0: 'test string1', 50: 'test string2', 100: 'test string3'}
support.check_plot(x)
g.legend = None
support.check_plot(x)
if bg == 0:
x.geometry(450, 337, 100, 0) # change the geometry and location
x.flush()
support.check_plot(x)
# open and plot a missing data with isofill
f = cdms.open(os.path.join(vcs.sample_data, 'tas_cru_1979.nc'))
s = f('tas', longitude=(-180, 180), latitude=(-90, 90)) + 273.15
x.clear() # clear the VCS Canvas
x.plot(s, 'default', 'isofill', 'quick',
bg=bg) # plot missing value slabe the old way
support.check_plot(x)
a = x.getisofill('quick') # get 'quick' isofill graphics method
# test object 'a' for graphics method
if not vcs.isgraphicsmethod(a):
raise Exception("Error did not retrieve the gm")
else:
if not vcs.isisofill(a): # check for isofill
raise Exception("Error gm is not right type")
a.script('test', 'w') # save 'quick' isofill as a Python script
x.setcolormap("AMIP") # change the colormap from default to AMIP
a.missing = 241 # change the missing background color to black
support.check_plot(x)
if '--extended' not in sys.argv:
print '\n************* PARTIAL TEST *****************'
print 'FOR COMPLETE TEST OF THIS MODULE USE '
print ' -F (--full) or -E (--extended) option'
print '************* PARTIAL TEST *****************\n'
sys.exit()
a.xticlabels('lon30', 'lon30') # change the x-axis
support.check_plot(x)
a.xticlabels('', '') # remove the x-axis
support.check_plot(x)
a.xticlabels('*') # put the x-axis
support.check_plot(x)
a.datawc(-45.0, 45.0, -90.0, 90.0) # change the region
support.check_plot(x)
a.datawc(1e20, 1e20, 1e20, 1e20) # put the region back
support.check_plot(x)
a.levels = ([0, 220], [230, 240], [250, 260]) # change the isofill levels
support.check_plot(x)
# change the isofill levels
a.levels = ([0, 220, 225, 230, 235, 240], [230, 240], [250, 260])
support.check_plot(x)
a.levels = ([0, 220, 225, 230, 235, 240], ) # change the isofill levels
support.check_plot(x)
# change the isofill levels
a.levels = ([0, 220, 225, 230, 235, 240, 245, 250])
support.check_plot(x)
a.levels = [0, 220, 225, 230, 235, 240] # change the isofill levels
support.check_plot(x)
a.levels = (0.0, 220.0, 225.0, 230.0, 235.0, 240.0, 250.0
) # change the isofill levels
support.check_plot(x)
a.levels = ([1e20], ) # change back to default settings
support.check_plot(x)
a.levels = (0, 220, 225, 230, 235, 240, 250, 260, 270
) # change the isofill levels
support.check_plot(x)
##########################################################################
# Below will produce an error. Later, if needed, I will add this functionality. #
# a.levels=('0','20','25','30') # this will produce an error #
##########################################################################
a.ext_1 = 'y' # add the extended legend arrow to the left
support.check_plot(x)
a.ext_1 = 'n' # remove the extended legend arrow to the left
support.check_plot(x)
a.ext_2 = 'y' # add the extended legend arrow to the right
support.check_plot(x)
a.ext_2 = 'n' # remove the extended legend arrow to the right
support.check_plot(x)
a.exts('y', 'y') # add the extended legend arrow to left and right
support.check_plot(x)
a.exts('n', 'n') # remove the extended legend arrow to left and right
support.check_plot(x)
a.fillareastyle = 'pattern' # change the fill style to pattern
support.check_plot(x)
a.fillareastyle = 'hatch' # change the fill style to hatch
support.check_plot(x)
a.fillareaindices = ([1, 3, 5, 6, 9, 18]) # set the hatch index patterns
support.check_plot(x)
# set the fill area color indices
a.fillareacolors = ([22, 33, 44, 55, 66, 77])
support.check_plot(x)
a.fillareacolors = None # use default color indices
support.check_plot(x)
a.fillareastyle = 'solid' # change the fill style back to solid
support.check_plot(x)
x.clear() # clear the VCS Canvas
x.plot(s, a, 'default', bg=bg) # plot isofill using 'default' template
support.check_plot(x)
# get the list of templates
objs = x.listelements('template')
# create template 'test' from 'default' template
t = x.createtemplate('test')
# test whether 't' is a template or not
if not vcs.istemplate(t):
raise Exception("Error template not created")
else:
# get the list of templates
a2 = x.listelements('template')
if objs == a2:
raise Exception("Error template not created or added to list")
# show the list of fillarea secondary objects
objs = x.listelements('fillarea')
f = x.getfillarea('AuTo_1') # get fillarea 'red'
# check to see if it is a secondary object
if not vcs.issecondaryobject(f):
raise Exception("Error did not get fillarea")
else:
# check to see if it is a fillarea
if not vcs.isfillarea(f):
raise Exception("Error object created is not fillarea")
a.levels = (220, 225, 230, 235, 240, 250, 260, 270, 280, 290, 300, 310
) # change the isofill levels
x.clear() # clear the VCS Canvas
x.plot(a, t, s, bg=bg) # plot array using isofill 'a' and template 't'
support.check_plot(x)
a.fillareaindices = (3, 4, 7, 9, 11) # set the indices
support.check_plot(x)
a.fillareaindices = (f, f, f, f, f, f
) # set the indices using the fillarea object
support.check_plot(x)
a.fillareaindices = (f, 2, 4, 7
) # reset the indices using the fillarea object
support.check_plot(x)
a.fillareaindices = (7, f, f, f, 8
) # resett the indices using the fillare object
support.check_plot(x)
f.color = 44 # change the fillarea object's color
support.check_plot(x)
f.style = 'hatch' # change the fillarea object's fill style
support.check_plot(x)
x.scriptobject(a, 'test') # save 'quick' isofill as a Python script
x.scriptobject(f, 'test') # save 'def37' fill area as a Python script
a = x.listelements('isofill') # show list of gm
r = x.createisofill('test2', 'quick') # create xyvsy 'test2'
a2 = x.listelements('isofill') # show list of gm
if a2 == a:
raise "error gm not created or not added to list"
x.removeobject(r) # remove xyvsy 'test2'
a3 = x.listelements('isofill') # show list of gm
if a3 != a:
raise "error gm not removed"
##########################################################################
# to see how x.update and x.mode work, see testisofill.py #
##########################################################################
# x.update()
# x.mode=1
# x.mode=0
print '*************************************************************************************'
print '****** ******'
print '****** I S O F I L L T E S T C O M P L E T E D S U C E S S F U L L Y ******'
print '****** ******'
print '*************************************************************************************'
def test():
import vcs
import cdms2 as cdms
import os
import support # import vcs and cdms
bg = support.bg
f = cdms.open(os.path.join(vcs.sample_data, 'clt.nc'))
s = f('clt') # get slab clt
x = vcs.init() # construct vcs canvas
x.plot(s, 'default', 'isofill', 'quick', bg=bg) # plot slab the old way
support.check_plot(x)
# Check the legend
g = x.createisofill('vcsmoduletest')
x.clear() # clear the VCS Canvas
x.plot(s, g, bg=bg) # plot slab the new way
support.check_plot(x)
g.legend = (10, 30, 70, 120)
support.check_plot(x)
g.legend = {0: 'test string1', 50: 'test string2', 100: 'test string3'}
support.check_plot(x)
g.legend = None
support.check_plot(x)
if bg == 0:
x.geometry(450, 337, 100, 0) # change the geometry and location
x.flush()
support.check_plot(x)
# open and plot a missing data with isofill
f = cdms.open(os.path.join(vcs.sample_data, 'tas_cru_1979.nc'))
s = f('tas', longitude=(-180, 180), latitude=(-90, 90)) + 273.15
x.clear() # clear the VCS Canvas
x.plot(
s,
'default',
'isofill',
'quick',
bg=bg) # plot missing value slabe the old way
support.check_plot(x)
a = x.getisofill('quick') # get 'quick' isofill graphics method
# test object 'a' for graphics method
if not vcs.isgraphicsmethod(a):
raise Exception("Error did not retrieve the gm")
else:
if not vcs.isisofill(a): # check for isofill
raise Exception("Error gm is not right type")
a.script('test', 'w') # save 'quick' isofill as a Python script
x.setcolormap("AMIP") # change the colormap from default to AMIP
a.missing = 241 # change the missing background color to black
support.check_plot(x)
if '--extended' not in sys.argv:
print '\n************* PARTIAL TEST *****************'
print 'FOR COMPLETE TEST OF THIS MODULE USE '
print ' -F (--full) or -E (--extended) option'
print '************* PARTIAL TEST *****************\n'
sys.exit()
a.xticlabels('lon30', 'lon30') # change the x-axis
support.check_plot(x)
a.xticlabels('', '') # remove the x-axis
support.check_plot(x)
a.xticlabels('*') # put the x-axis
support.check_plot(x)
a.datawc(-45.0, 45.0, -90.0, 90.0) # change the region
support.check_plot(x)
a.datawc(1e20, 1e20, 1e20, 1e20) # put the region back
support.check_plot(x)
a.levels = ([0, 220], [230, 240], [250, 260]) # change the isofill levels
support.check_plot(x)
# change the isofill levels
a.levels = ([0, 220, 225, 230, 235, 240], [230, 240], [250, 260])
support.check_plot(x)
a.levels = ([0, 220, 225, 230, 235, 240],) # change the isofill levels
support.check_plot(x)
# change the isofill levels
a.levels = ([0, 220, 225, 230, 235, 240, 245, 250])
support.check_plot(x)
a.levels = [0, 220, 225, 230, 235, 240] # change the isofill levels
support.check_plot(x)
a.levels = (
0.0,
220.0,
225.0,
230.0,
235.0,
240.0,
250.0) # change the isofill levels
support.check_plot(x)
a.levels = ([1e20],) # change back to default settings
support.check_plot(x)
a.levels = (
0,
220,
225,
230,
235,
240,
250,
260,
270) # change the isofill levels
support.check_plot(x)
##########################################################################
# Below will produce an error. Later, if needed, I will add this functionality. #
# a.levels=('0','20','25','30') # this will produce an error #
##########################################################################
a.ext_1 = 'y' # add the extended legend arrow to the left
support.check_plot(x)
a.ext_1 = 'n' # remove the extended legend arrow to the left
support.check_plot(x)
a.ext_2 = 'y' # add the extended legend arrow to the right
support.check_plot(x)
a.ext_2 = 'n' # remove the extended legend arrow to the right
support.check_plot(x)
a.exts('y', 'y') # add the extended legend arrow to left and right
support.check_plot(x)
a.exts('n', 'n') # remove the extended legend arrow to left and right
support.check_plot(x)
a.fillareastyle = 'pattern' # change the fill style to pattern
support.check_plot(x)
a.fillareastyle = 'hatch' # change the fill style to hatch
support.check_plot(x)
a.fillareaindices = ([1, 3, 5, 6, 9, 18]) # set the hatch index patterns
support.check_plot(x)
# set the fill area color indices
a.fillareacolors = ([22, 33, 44, 55, 66, 77])
support.check_plot(x)
a.fillareacolors = None # use default color indices
support.check_plot(x)
a.fillareastyle = 'solid' # change the fill style back to solid
support.check_plot(x)
x.clear() # clear the VCS Canvas
x.plot(s, a, 'default', bg=bg) # plot isofill using 'default' template
support.check_plot(x)
# get the list of templates
objs = x.listelements('template')
# create template 'test' from 'default' template
t = x.createtemplate('test')
# test whether 't' is a template or not
if not vcs.istemplate(t):
raise Exception("Error template not created")
else:
# get the list of templates
a2 = x.listelements('template')
if objs == a2:
raise Exception("Error template not created or added to list")
# show the list of fillarea secondary objects
objs = x.listelements('fillarea')
f = x.getfillarea('AuTo_1') # get fillarea 'red'
# check to see if it is a secondary object
if not vcs.issecondaryobject(f):
raise Exception("Error did not get fillarea")
else:
# check to see if it is a fillarea
if not vcs.isfillarea(f):
raise Exception("Error object created is not fillarea")
a.levels = (
220,
225,
230,
235,
240,
250,
260,
270,
280,
290,
300,
310) # change the isofill levels
x.clear() # clear the VCS Canvas
x.plot(a, t, s, bg=bg) # plot array using isofill 'a' and template 't'
support.check_plot(x)
a.fillareaindices = (3, 4, 7, 9, 11) # set the indices
support.check_plot(x)
a.fillareaindices = (
f,
f,
f,
f,
f,
f) # set the indices using the fillarea object
support.check_plot(x)
a.fillareaindices = (
f,
2,
4,
7) # reset the indices using the fillarea object
support.check_plot(x)
a.fillareaindices = (
7,
f,
f,
f,
8) # resett the indices using the fillare object
support.check_plot(x)
f.color = 44 # change the fillarea object's color
support.check_plot(x)
f.style = 'hatch' # change the fillarea object's fill style
support.check_plot(x)
x.scriptobject(a, 'test') # save 'quick' isofill as a Python script
x.scriptobject(f, 'test') # save 'def37' fill area as a Python script
a = x.listelements('isofill') # show list of gm
r = x.createisofill('test2', 'quick') # create xyvsy 'test2'
a2 = x.listelements('isofill') # show list of gm
if a2 == a:
raise "error gm not created or not added to list"
x.removeobject(r) # remove xyvsy 'test2'
a3 = x.listelements('isofill') # show list of gm
if a3 != a:
raise "error gm not removed"
##########################################################################
# to see how x.update and x.mode work, see testisofill.py #
##########################################################################
# x.update()
# x.mode=1
# x.mode=0
print '*************************************************************************************'
print '****** ******'
print '****** I S O F I L L T E S T C O M P L E T E D S U C E S S F U L L Y ******'
print '****** ******'
print '*************************************************************************************'
def finalize( self, flip_x=False, flip_y=False ):
"""By the time this is called, all synchronize operations should have been done. But even
so, each variable has a min and max and a min and max for each of its axes. We need to
simplify further for the plot package.
The options flip_x and flip_y may be set to True to flip the axis. That is, in x right
to left and left to right, and in y top to bottom and bottom to top."""
# old test:
#if self.presentation.__class__.__name__=="GYx" or\
# self.presentation.__class__.__name__=="Gfi":
# interim test here and below. Once all the is* functions work, I should
# drop the tests on self.presentation.__class__.__name__ :
if vcs.isscatter(self.presentation):
ylabel, xlabel = string.split(self.title, ' vs ')
#pdb.set_trace()
#in the case of scatter plots there are 2 variables packed together
var = self.vars[0]
[xMIN, xMAX], [yMIN, yMAX] = self.make_ranges(var)
#print xMIN, xMAX, yMIN, yMAX
#print vcs.mkscale(xMIN, xMAX)
#print vcs.mkscale(yMIN, yMAX)
self.presentation.xticlabels1 = vcs.mklabels(vcs.mkscale(xMIN, xMAX))
self.presentation.datawc_x1 = xMIN
self.presentation.datawc_x2 = xMAX
self.presentation.xticlabels2 = {(xMIN+xMAX)/2.: xlabel}
if flip_y:
self.presentation.datawc_y2 = yMIN
self.presentation.datawc_y1 = yMAX
self.presentation.flip = True
else:
self.presentation.datawc_y1 = yMIN
self.presentation.datawc_y2 = yMAX
self.presentation.yticlabels1 = vcs.mklabels(vcs.mkscale(yMIN, yMAX))
self.presentation.yticlabels2 = {(yMIN+yMAX)/2.: ylabel}
self.presentation.linewidth = 0
self.presentation.markercolor = 1
self.presentation.markersize = 5
#add overplotline is a total kludge
self.presentation.overplotline = self.overplotline
if flip_y:
self.presentation.flip = True
#self.presentation.list()
elif vcs.isyxvsx(self.presentation) or\
vcs.isisofill(self.presentation) or\
vcs.isboxfill(self.presentation) or\
self.presentation.__class__.__name__=="GYx" or\
self.presentation.__class__.__name__=="G1d" or\
self.presentation.__class__.__name__=="Gv":
#pdb.set_trace()
if flip_y:
self.presentation.flip = True
var = self.vars[0]
axmax = self.axmax[seqgetattr(var,'id','')]
axmin = self.axmin[seqgetattr(var,'id','')]
varmax = self.varmax[seqgetattr(var,'id','')]
varmin = self.varmin[seqgetattr(var,'id','')]
for v in self.vars[1:]:
for ax in axmax.keys():
axmax[ax] = max(axmax[ax],self.axmax[seqgetattr(v,'id','')][ax])
axmin[ax] = min(axmin[ax],self.axmin[seqgetattr(v,'id','')][ax])
varmax = max(varmax,self.varmax[v.id])
varmin = min(varmin,self.varmin[v.id])
if vcs.isyxvsx(self.presentation) or\
self.presentation.__class__.__name__=="GYx" or\
self.presentation.__class__.__name__=="G1d":
if len(axmax.keys())<=0:
return None
# VCS Yxvsx
ax = axmax.keys()[0]
if flip_x:
self.presentation.datawc_x2 = axmin[ax]
self.presentation.datawc_x1 = axmax[ax]
else:
self.presentation.datawc_x1 = axmin[ax]
self.presentation.datawc_x2 = axmax[ax]
if flip_y:
self.presentation.datawc_y2 = varmin
self.presentation.datawc_y1 = varmax
else:
self.presentation.datawc_y1 = varmin
self.presentation.datawc_y2 = varmax
#print "DEBUG, in finalize for line plot, datawc_{x1,x2,y1,y2}=",\
# self.presentation.datawc_x1, self.presentation.datawc_x2,\
# self.presentation.datawc_y1, self.presentation.datawc_y2
if vcs.isisofill(self.presentation) or self.presentation.__class__.__name__=="Gfi"\
or vcs.isboxfill(self.presentation):
# VCS Isofill or Boxfill
# First we have to identify which axes will be plotted as X and Y.
# If the axes each had an 'axis' attribute, axaxi will look something like
# {'X':'axis1id', 'Y':'axis2id'}. If one misses the attribute, 'axis0id':'axis0id'.
axaxi = {ax:id for id,ax in self.axax[seqgetattr(var,'id','')].items()}
if 'X' in axaxi.keys() and 'Y' in axaxi.keys():
axx = axaxi['X']
axy = axaxi['Y']
elif 'Y' in axaxi.keys() and 'Z' in axaxi.keys():
axx = axaxi['Y']
axy = axaxi['Z']
#added case of time vs variable
elif 'T' in axaxi.keys() and 'Y' in axaxi.keys():
axx = axaxi['T']
axy = axaxi['Y']
if axx == 'time':
t=var.getTime()
if 'units' in dir(t) and t.units == "months since 1800":
time_lables = {}
months_names = get_month_strings(length=3)
tc=t.asComponentTime()
for i, v in enumerate(t):
time_lables[v] = months_names[tc[i].month-1]
self.presentation.xticlabels1 = time_lables
self.presentation.datawc_timeunits = t.units
#self.presentation.list()
elif len(axaxi.keys())==2:
# It's not clear what should be the X variable and what the Y variable,
# but it's worth trying to do something
axx = None
axy = None
for axetc in var.getDomain()[:]:
ax = axetc[0]
if getattr(ax,'units',None)=='mbar':
# probably pressure levels, a vertical axis
axy = ax.id
else:
axx = ax.id
if axx is None or axy is None:
# last resort
axy = axaxi[axaxi.keys()[0]]
axx = axaxi[axaxi.keys()[1]]
else:
return None
# Now send the plotted min,max for the X,Y axes to the graphics:
# and if it is not a polar projection
if vcs.getprojection(self.presentation.projection)._type!=-3:
if flip_x:
self.presentation.datawc_x2 = axmin[axx]
self.presentation.datawc_x1 = axmax[axx]
else:
self.presentation.datawc_x1 = axmin[axx]
self.presentation.datawc_x2 = axmax[axx]
if flip_y:
self.presentation.datawc_y2 = axmin[axy]
self.presentation.datawc_y1 = axmax[axy]
else:
self.presentation.datawc_y1 = axmin[axy]
self.presentation.datawc_y2 = axmax[axy]
# The variable min and max, varmin and varmax, should be passed on to the graphics
# for setting the contours. But apparently you can't tell VCS just the min and max;
# you have to give it all the contour levels. So...
if vcs.isboxfill(self.presentation):
self.presentation.boxfill_type = 'custom' # without this, can't set levels
nlevels = 16
try:
levels = [float(v) for v in vcs.mkscale( varmin, varmax, nlevels )]
# Exceptions occur because mkscale doesn't always work. E.g. vcs.mkscale(0,1.e35,16)
except RuntimeWarning:
levels = []
if levels==[]:
## Here's how to do it with percentiles (clip out large values first).
#pc05 = numpy.percentile(self.vars[0],0.05)
#pc95 = numpy.percentile(self.vars[0],0.95)
#levels = [float(v) for v in vcs.mkscale( pc05, pc95, nlevels-2 )]
#levels = [varmin]+levels+[varmax]
# Evenly distributed levels, after clipping out large values:
# This cannot be expected to work always, but it's better than doing nothing.
amed = numpy.median(self.vars[0]._data)
vclip = amed * 1.0e6
print "WARNING graphics problems, clipping some data at",vclip
self.vars[0]._data[ self.vars[0]._data > vclip ] = vclip
a = numpy.sort(self.vars[0]._data.flatten())
asp = numpy.array_split(a,nlevels)
afirsts = [c[0] for c in asp]+[asp[-1][-1]]
alasts = [asp[0][0]]+[c[-1] for c in asp]
levels = [0.5*(afirsts[i]+alasts[i]) for i in range(len(afirsts))]
levf = levels[0]
levl = levels[-1]
levels = [ round(lv,2) for lv in levels ]
levels[0] = round(1.1*levels[0]-0.1*levels[1],2)
levels[-1] = round(1.1*levels[-1]-0.1*levels[-2],2)
# ... mkscale returns numpy.float64, which behaves unexpectedly in _setlevels when
# passed a tuple value
if levels is not None and len(levels)>0:
self.presentation.levels = levels
#nlevels = max(1, len(levels) - 1)
#nlrange = range(nlevels+1)
#nlrange.reverse()
#self.presentation.legend = vcs.mklabels( self.presentation.levels )
## Once you set the levels, the VCS default color choice looks bad. So you really
## have to set contour fill colors (integers from 0 through 255) too:
#cmin = 32./nlevels
#cmax = 255./nlevels
## A more flexible way to do what's going on here, thanks to Charles Doutriaux:
## r=10
## g=16
## b=20
## X.setcolorcell(16,r,g,b)
## colors = [16,17,18,...] etc.
## vcs.getcolors is useful, more complicated - see its doc string
#colors = [int(round(a*cmin+(nlevels-a)*cmax)) for a in nlrange]
#self.presentation.fillareacolors = colors
##self.presentation.fillareacolors=[32,48,64,80,96,112,128,144,160,176,240]
elif vcs.isvector(self.presentation) or self.presentation.__class__.__name__=="Gv":
# axis min,max copied from isofill
axaxi = {ax:id for id,ax in self.axax[seqgetattr(var,'id','')].items()}
if 'X' in axaxi.keys() and 'Y' in axaxi.keys():
axx = axaxi['X']
axy = axaxi['Y']
elif 'Y' in axaxi.keys() and 'Z' in axaxi.keys():
axx = axaxi['Y']
axy = axaxi['Z']
self.presentation.datawc_x1 = axmin[axx]
self.presentation.datawc_x2 = axmax[axx]
self.presentation.datawc_y1 = axmin[axy]
self.presentation.datawc_y2 = axmax[axy]
vec = self.presentation
vec.scale = min(vcsx.bgX,vcsx.bgY)/ 10.
if hasattr(self.vars[0],'__getitem__') and not hasattr( self.vars[0], '__cdms_internals__'):
# generally a tuple of variables - we need 2 variables to describe a vector
v = self.vars[0][0]
w = self.vars[0][1]
else: # We shouldn't get here, but may as well try to make it work if possible:
print "WARNING trying to make a vector plot without tuples! Variables involved are:"
v = self.vars[0]
print "variable",v.id
v = self.vars[1]
print "variable",v.id
nlats = latAxis(v).shape[0]
nlons = lonAxis(w).shape[0]
nlatvs = vcsx.bgY/16 # how many vectors we want in lat direction
nlonvs = vcsx.bgX/16
#self.strideX = int( 0.9* vcsx.bgX/nlons )
#self.strideY = int( 0.6* vcsx.bgY/nlats )
self.strideX = max(1, int( nlons/nlonvs )) # stride values must be at least 1
self.strideY = max(1, int( nlats/nlatvs ))
else:
print "ERROR cannot identify graphics method",self.presentation.__class__.__name__