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__
def test():
import vcs, cdms2 as cdms, time, os, sys, support # import vcs and cu
bg = support.bg
f = cdms.open(
os.path.join(cdms.__path__[0], '..', '..', '..', '..', 'sample_data',
'clt.nc')) # open clt file
u = f.getslab('u', ':', ':', -10., 0., 0, 10) # get slab u
v = f.getslab('v', ':', ':', -10., 0., 0, 10) # get slab v
x = vcs.init() # construct vcs canvas
x.plot(u, v, 'default', 'vector', 'quick', bg=bg) # plot slab the old way
support.check_plot(x)
if bg == 0:
x.geometry(450, 337, 100, 0) # change the geometry and location
x.flush()
support.check_plot(x)
a = x.getvector('quick') # get 'quick' vector
if not vcs.isgraphicsmethod(a): # test object 'a' for graphics method
raise Exception, "Error did not retrieve the gm"
else:
if not vcs.isvector(a): # test object 'a' if vector
raise Exception, "Error gm is not right type"
a.script('test', 'w') # save 'quick' vector as a Python script
a.xticlabels('', '') # remove the x-axis
support.check_plot(x)
a.xticlabels('*') # put the x-axis
support.check_plot(x)
############################################################################
# Change the vector scale #
############################################################################
a.scale = 2.0
support.check_plot(x)
a.scale = 5.0
support.check_plot(x)
a.scale = 1.5
support.check_plot(x)
a.scale = 0.0
support.check_plot(x)
a.scale = -1.5
support.check_plot(x)
a.scale = -2.0
support.check_plot(x)
a.scale = -5.0
support.check_plot(x)
############################################################################
# Change the vector typeiiiiiii #
############################################################################
a.type = 0 # same as a.type = 'arrows'
support.check_plot(x)
a.type = 1 # same as a.type = 'barbs'
support.check_plot(x)
## a.type=2 # same as a.type = 'solidarrows'
## support.check_plot(x)
## raw_input("Done...")
if not '--extended' 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()
############################################################################
# Change the vector reference #
############################################################################
a.reference = 10.
support.check_plot(x)
a.reference = 100.
support.check_plot(x)
a.reference = 4.
support.check_plot(x)
a.reference = 5.
support.check_plot(x)
############################################################################
# Change the vector alignment #
############################################################################
a.alignment = 'head' # same as a.alignment=0
support.check_plot(x)
a.alignment = 'center' # same as a.alignment=1
support.check_plot(x)
a.alignment = 'tail' # same as a.alignment=2
support.check_plot(x)
############################################################################
# Change the vector line #
############################################################################
a.line = 0 # same as 'solid'
support.check_plot(x)
a.line = 1 # same as 'dash'
support.check_plot(x)
a.line = 2 # same as 'dot'
support.check_plot(x)
a.line = 3 # same as 'dash-dot'
support.check_plot(x)
a.line = 4 # same as 'long-dash'
support.check_plot(x)
a.line = None # use default line
support.check_plot(x)
############################################################################
# Change the vector line color #
############################################################################
a.linecolor = (77)
support.check_plot(x)
a.linecolor = 16
support.check_plot(x)
a.linecolor = 44 # same as a.color=(44)
support.check_plot(x)
a.linecolor = None
support.check_plot(x)
x.clear() # clear the VCS Canvas
x.vector(u, v, a, 'default', bg=bg) # plot vector using 'default' template
support.check_plot(x)
objs = x.listelements('template') # get the list of templates
t = x.createtemplate(
'test') # create template 'test' from 'default' template
if not vcs.istemplate(t): # test whether 't' is a template or not
raise Exception, "Error template not created"
else:
a2 = x.listelements('template') # get the list of templates
if objs == a2:
raise Exception, "Error template not created or added to list"
x.clear() # clear the VCS Canvas
x.plot(t, a, u, v,
bg=bg) # plot vector template 't', outline 'a', and arrays 'u':'v'
support.check_plot(x)
x.clear() # clear the VCS Canvas
x.vector(a, u, v, t,
bg=bg) # plot using outline 'a', array 'u':'v', and template 't'
support.check_plot(x)
l = x.getline('red') # get line 'red'
if not vcs.issecondaryobject(
l): # check to see if it is a secondary object
raise Exception, "Error did not get line"
else:
if not vcs.isline(l): # check to see if it is a line
raise Exception, "Error object created is not line"
###########################################################################
# Use the create line object 'm' from above and modify the line object #
###########################################################################
a.line = l # use the line object
support.check_plot(x)
l.color = 44 # change the line color
support.check_plot(x)
l.type = 'dot' # change the line type
support.check_plot(x)
l.width = 4 # change the line size
support.check_plot(x)
a = x.listelements('vector') # show list of gm
r = x.createvector('test2', 'quick') # create xyvsy 'test2'
a2 = x.listelements('vector') # 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('vector') # show list of gm
if a3 != a:
raise "error gm not removed"
#################################################################################
# to see how x.update and x.mode work, see testoutline.py #
#################################################################################
#x.update()
#x.mode=1
#x.mode=0
print '*************************************************************************************'
print '****** ******'
print '****** V E C T O R 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,cdms2 as cdms,time,os,sys,support # import vcs and cu
bg=support.bg
f=cdms.open(os.path.join(cdms.__path__[0],'..','..','..','..','sample_data','clt.nc')) # open clt file
u=f.getslab('u',':',':',-10.,0.,0,10)# get slab u
v=f.getslab('v',':',':',-10.,0.,0,10)# get slab v
x=vcs.init() # construct vcs canvas
x.plot(u, v, 'default','vector','quick',bg=bg) # plot slab the old way
support.check_plot(x)
if bg==0:
x.geometry(450,337,100,0) # change the geometry and location
x.flush()
support.check_plot(x)
a=x.getvector('quick') # get 'quick' vector
if not vcs.isgraphicsmethod(a): # test object 'a' for graphics method
raise Exception, "Error did not retrieve the gm"
else:
if not vcs.isvector(a): # test object 'a' if vector
raise Exception, "Error gm is not right type"
a.script('test','w') # save 'quick' vector as a Python script
a.xticlabels('','') # remove the x-axis
support.check_plot(x)
a.xticlabels('*') # put the x-axis
support.check_plot(x)
############################################################################
# Change the vector scale #
############################################################################
a.scale=2.0
support.check_plot(x)
a.scale=5.0
support.check_plot(x)
a.scale=1.5
support.check_plot(x)
a.scale=0.0
support.check_plot(x)
a.scale=-1.5
support.check_plot(x)
a.scale=-2.0
support.check_plot(x)
a.scale=-5.0
support.check_plot(x)
############################################################################
# Change the vector typeiiiiiii #
############################################################################
a.type=0 # same as a.type = 'arrows'
support.check_plot(x)
a.type=1 # same as a.type = 'barbs'
support.check_plot(x)
## a.type=2 # same as a.type = 'solidarrows'
## support.check_plot(x)
## raw_input("Done...")
if not '--extended' 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()
############################################################################
# Change the vector reference #
############################################################################
a.reference=10.
support.check_plot(x)
a.reference=100.
support.check_plot(x)
a.reference=4.
support.check_plot(x)
a.reference=5.
support.check_plot(x)
############################################################################
# Change the vector alignment #
############################################################################
a.alignment='head' # same as a.alignment=0
support.check_plot(x)
a.alignment='center' # same as a.alignment=1
support.check_plot(x)
a.alignment='tail' # same as a.alignment=2
support.check_plot(x)
############################################################################
# Change the vector line #
############################################################################
a.line=0 # same as 'solid'
support.check_plot(x)
a.line=1 # same as 'dash'
support.check_plot(x)
a.line=2 # same as 'dot'
support.check_plot(x)
a.line=3 # same as 'dash-dot'
support.check_plot(x)
a.line=4 # same as 'long-dash'
support.check_plot(x)
a.line=None # use default line
support.check_plot(x)
############################################################################
# Change the vector line color #
############################################################################
a.linecolor=(77)
support.check_plot(x)
a.linecolor=16
support.check_plot(x)
a.linecolor=44 # same as a.color=(44)
support.check_plot(x)
a.linecolor=None
support.check_plot(x)
x.clear() # clear the VCS Canvas
x.vector(u, v, a,'default',bg=bg) # plot vector using 'default' template
support.check_plot(x)
objs =x.listelements('template') # get the list of templates
t=x.createtemplate('test') # create template 'test' from 'default' template
if not vcs.istemplate(t): # test whether 't' is a template or not
raise Exception,"Error template not created"
else:
a2 =x.listelements('template') # get the list of templates
if objs==a2:
raise Exception,"Error template not created or added to list"
x.clear() # clear the VCS Canvas
x.plot(t,a,u,v,bg=bg) # plot vector template 't', outline 'a', and arrays 'u':'v'
support.check_plot(x)
x.clear() # clear the VCS Canvas
x.vector(a,u,v,t,bg=bg) # plot using outline 'a', array 'u':'v', and template 't'
support.check_plot(x)
l=x.getline('red') # get line 'red'
if not vcs.issecondaryobject(l): # check to see if it is a secondary object
raise Exception,"Error did not get line"
else:
if not vcs.isline(l): # check to see if it is a line
raise Exception, "Error object created is not line"
###########################################################################
# Use the create line object 'm' from above and modify the line object #
###########################################################################
a.line=l # use the line object
support.check_plot(x)
l.color = 44 # change the line color
support.check_plot(x)
l.type ='dot' # change the line type
support.check_plot(x)
l.width=4 # change the line size
support.check_plot(x)
a = x.listelements('vector') # show list of gm
r=x.createvector('test2','quick') # create xyvsy 'test2'
a2 = x.listelements('vector') # 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('vector') # show list of gm
if a3!=a:
raise "error gm not removed"
#################################################################################
# to see how x.update and x.mode work, see testoutline.py #
#################################################################################
#x.update()
#x.mode=1
#x.mode=0
print '*************************************************************************************'
print '****** ******'
print '****** V E C T O R 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 '*************************************************************************************'
