def execute(self, test_str, imagefilename, imagethreshold, ncfiles, rtol, atol):
print test_str
if imagethreshold is None: # user didn't specify a value
imagethreshold = checkimage.defaultThreshold
# Silence annoying messages about how to set the NetCDF file type. Anything will do.
cdms2.setNetcdfShuffleFlag(0)
cdms2.setNetcdfDeflateFlag(0)
cdms2.setNetcdfDeflateLevelFlag(0)
# nonstandard, suitable for testing:
proc = subprocess.Popen([self.diagstr], shell=True)
proc_status = proc.wait()
if proc_status!=0:
proc = subprocess.Popen([self.diagstr], shell=True)
proc_status = proc.wait()
if proc_status!=0:
raise DiagError("diags run failed")
if self.keep:
print "save ", imagefilename, ncfiles.keys()
print "output directory is = ", self.outpath
else:
# Test of graphics (png) file match:
# This just looks at combined plot, aka summary plot, which is a compound of three plots.
imagefname = os.path.join( self.outpath, imagefilename )
imagebaselinefname = os.path.join( self.baselinepath, imagefilename )
#pdb.set_trace()
print "OK THRESHOLD IS:",imagethreshold
graphics_result = checkimage.check_result_image( imagefname, imagebaselinefname, imagethreshold )
print "Graphics file", imagefname, "match difference:", graphics_result
#initialize to successful graphics check
GR_CLOSE = (graphics_result == 0)
assert(GR_CLOSE), 'graphic images are not close'
# Test of NetCDF data (nc) file match:
NC_CLOSE = True
for ncfilename, ncvars in ncfiles.items():
for var in ncvars:
#print ncfilename, var
try:
#print ">>>>>>>>>>>>>", var, ncfilename
close = self.closeness( var, ncfilename, rtol, atol )
if not close:
print var, ' in ', os.path.join(self.outpath,ncfilename), ' is not close from the one in:',os.path.join(self.baselinepath,ncfilename)
except:
print 'NetCDF comparison failed for ', var, ' in file: ', os.path.join(self.outpath,ncfilename),"vs",os.path.join(self.baselinepath,ncfilename)
close = False
NC_CLOSE = NC_CLOSE and close
assert(NC_CLOSE), 'NetCDF files are not close'
#cleanup the temp files
if GR_CLOSE and NC_CLOSE:
shutil.rmtree(self.outpath)
def checkImage(self,fnm,src=None,threshold=checkimage.defaultThreshold,pngReady=False,pngPathSet=False):
if src is None:
src = os.path.join(self.basedir,os.path.basename(fnm))
if not pngPathSet:
fnm = os.path.join(self.pngsdir,fnm)
print("Test file :",fnm)
print("Source file:",src)
if not pngReady:
self.x.png(fnm,width=self.x.width, height=self.x.height, units="pixels")
ret = checkimage.check_result_image(fnm,src,threshold, update_baseline=self.update)
self.assertEqual(ret,0)
return ret
def check_image(self, compare_against):
"""
Checks the current render window's output against the image specified in the argument,
returns the result of checkimage.check_result_image
"""
generate_png(self.win, self.test_file)
pth = os.path.join(os.path.dirname(__file__), "../..")
sys.path.append(pth)
import checkimage
print "fnm:", self.test_file
print "src:", compare_against
return checkimage.check_result_image(self.test_file, compare_against, checkimage.defaultThreshold)
def check_image(self, compare_against):
"""
Checks the current render window's output against the image specified in the argument,
returns the result of checkimage.check_result_image
"""
generate_png(self.win, self.test_file)
pth = os.path.join(os.path.dirname(__file__), "../..")
sys.path.append(pth)
import checkimage
print "fnm:", self.test_file
print "src:", compare_against
return checkimage.check_result_image(self.test_file, compare_against,
checkimage.defaultThreshold)
def checkImage(self,fnm,src=None,threshold=checkimage.defaultThreshold,pngReady=False,pngPathSet=False):
if src is None:
src = os.path.join(self.basedir,os.path.basename(fnm))
if not pngPathSet:
fnm = os.path.join(self.pngsdir,fnm)
print("Test file :",fnm)
print("Source file:",src)
if not pngReady:
self.x.png(fnm,
width=self.x.width,
height=self.x.height,
units="pixels")
ret = checkimage.check_result_image(fnm,src,threshold)
self.assertEqual(ret,0)
return ret
def test(self):
self.do_test()
if self.test_file is not None:
generate_png(self.win, self.test_file)
if len(sys.argv) >= 2:
src=sys.argv[1]
pth = os.path.join(os.path.dirname(__file__),"../..")
sys.path.append(pth)
import checkimage
print "fnm:", self.test_file
print "src:", src
self.passed = checkimage.check_result_image(self.test_file, src, checkimage.defaultThreshold)
print sys.argv[0], "passed" if self.passed == 0 else "failed"
sys.exit(self.passed)
def test( self, interactive=False ):
self.build()
# test_image = os.path.join( self.test_dir, 'images', '.'.join( [ self.name, 'png' ] ) )
test_image = '.'.join( [ self.name, 'test', 'png' ] )
self.canvas.png( test_image )
ret = checkimage.check_result_image( test_image, self.image_name,\
checkimage.defaultThreshold+3. )
if interactive:
print "Type <Enter> to continue and update ref image ( type 'n' to skip update )."
sys.stdout.flush()
line = sys.stdin.readline()
if line[0] <> 'n':
self.update_image()
sys.exit(ret)
def test( self, interactive=False ):
import checkimage
self.build()
# test_image = os.path.join( self.test_dir, 'images', '.'.join( [ self.name, 'png' ] ) )
test_image = '.'.join( [ self.name, 'test', 'png' ] )
ref_image = '.'.join( [ self.name, 'png' ] )
self.canvas.png( test_image )
print "Copying ref image %s to %s in %s " % ( self.image_name, ref_image, os.path.abspath('.') )
shutil.copy( self.image_name, ref_image )
ret = checkimage.check_result_image( ref_image, test_image, checkimage.defaultThreshold )
if interactive:
print "Type <Enter> to continue and update ref image ( type 'n' to skip update )."
sys.stdout.flush()
line = sys.stdin.readline()
if line[0] <> 'n': self.update_image()
sys.exit(ret)
def test(self, interactive=False):
self.build()
# test_image = os.path.join( self.test_dir, 'images', '.'.join( [ self.name, 'png' ] ) )
test_image = '.'.join([self.name, 'test', 'png'])
self.canvas.png(test_image)
ret = checkimage.check_result_image( test_image, self.image_name,\
checkimage.defaultThreshold+3. )
if interactive:
print "Type <Enter> to continue and update ref image ( type 'n' to skip update )."
sys.stdout.flush()
line = sys.stdin.readline()
if line[0] <> 'n':
self.update_image()
sys.exit(ret)
def test(self):
self.do_test()
if self.test_file is not None:
generate_png(self.win, self.test_file)
if len(sys.argv) >= 2:
src = sys.argv[1]
pth = os.path.join(os.path.dirname(__file__), "../..")
sys.path.append(pth)
import checkimage
print "fnm:", self.test_file
print "src:", src
self.passed = checkimage.check_result_image(
self.test_file, src, checkimage.defaultThreshold)
print sys.argv[0], "passed" if self.passed == 0 else "failed"
sys.exit(self.passed)
def test(self, interactive=False):
import checkimage
self.build()
# test_image = os.path.join( self.test_dir, 'images', '.'.join( [ self.name, 'png' ] ) )
test_image = '.'.join([self.name, 'test', 'png'])
ref_image = '.'.join([self.name, 'png'])
self.canvas.png(test_image)
print "Copying ref image %s to %s in %s " % (
self.image_name, ref_image, os.path.abspath('.'))
shutil.copy(self.image_name, ref_image)
ret = checkimage.check_result_image(ref_image, test_image,
checkimage.defaultThreshold)
if interactive:
print "Type <Enter> to continue and update ref image ( type 'n' to skip update )."
sys.stdout.flush()
line = sys.stdin.readline()
if line[0] <> 'n': self.update_image()
sys.exit(ret)
def execute(self, test_str, imagefilename, imagethreshold, ncfiles, rtol,
atol):
print test_str
# Silence annoying messages about how to set the NetCDF file type. Anything will do.
cdms2.setNetcdfShuffleFlag(0)
cdms2.setNetcdfDeflateFlag(0)
cdms2.setNetcdfDeflateLevelFlag(0)
# nonstandard, suitable for testing:
proc = subprocess.Popen([self.diagstr], shell=True)
proc_status = proc.wait()
if proc_status != 0:
raise DiagError("diags run failed")
if self.keep:
print "save ", imagefilename, ncfiles.keys()
print "output directory is = ", self.outpath
else:
# Test of graphics (png) file match:
# This just looks at combined plot, aka summary plot, which is a compound of three plots.
imagefname = os.path.join(self.outpath, imagefilename)
imagebaselinefname = os.path.join(self.baselinepath, imagefilename)
graphics_result = checkimage.check_result_image(
imagefname, imagebaselinefname, imagethreshold)
print "Graphics file", imagefname, "match difference:", graphics_result
# Test of NetCDF data (nc) file match:
CLOSE = True
for ncfilename, ncvars in ncfiles.items():
for var in ncvars:
#print ncfilename, var
try:
close = self.closeness(var, ncfilename, rtol, atol)
if not close:
print var, ' in ', ncfilename, ' is not close.'
except:
print 'comparison failed for ', var, ' in file: ', ncfilename
close = False
CLOSE = CLOSE and close
#cleanup the temp files
shutil.rmtree(self.outpath)
assert (CLOSE), 'data are not close'
def execute(self, test_str, imagefilename, imagethreshold, ncfiles, rtol, atol):
print test_str
# Silence annoying messages about how to set the NetCDF file type. Anything will do.
cdms2.setNetcdfShuffleFlag(0)
cdms2.setNetcdfDeflateFlag(0)
cdms2.setNetcdfDeflateLevelFlag(0)
# nonstandard, suitable for testing:
proc = subprocess.Popen([self.diagstr], shell=True)
proc_status = proc.wait()
if proc_status!=0:
raise DiagError("diags run failed")
if self.keep:
print "save ", imagefilename, ncfiles.keys()
print "output directory is = ", self.outpath
else:
# Test of graphics (png) file match:
# This just looks at combined plot, aka summary plot, which is a compound of three plots.
imagefname = os.path.join( self.outpath, imagefilename )
imagebaselinefname = os.path.join( self.baselinepath, imagefilename )
graphics_result = checkimage.check_result_image( imagefname, imagebaselinefname, imagethreshold )
print "Graphics file", imagefname, "match difference:", graphics_result
# Test of NetCDF data (nc) file match:
CLOSE = True
for ncfilename, ncvars in ncfiles.items():
for var in ncvars:
#print ncfilename, var
try:
close = self.closeness( var, ncfilename, rtol, atol )
if not close:
print var, ' in ', ncfilename, ' is not close.'
except:
print 'comparison failed for ', var, ' in file: ', ncfilename
close = False
CLOSE = CLOSE and close
#cleanup the temp files
shutil.rmtree(self.outpath)
assert(CLOSE), 'data are not close'
def plot_a_ratio(s,gm,ratio):
ret = 0
x=vcs.init()
x.open()
x.geometry(400,800)
y=vcs.init()
y.open()
y.geometry(800,400)
for X in [x,y]:
X.plot(s,gm,ratio=ratio)
if X.islandscape():
orient = "ldscp"
else:
orient = "port"
fnm = "aspect_ratio_%s_%s.png" % (orient,ratio)
X.png(fnm)
print "fnm:",fnm
src = os.path.join(pth0,fnm)
print "src:",src
ret += checkimage.check_result_image(fnm,src,checkimage.defaultThreshold)
return ret
def plot_a_ratio(s, gm, ratio):
ret = 0
x = vcs.init()
x.open()
x.geometry(400, 800)
y = vcs.init()
y.open()
y.geometry(800, 400)
for X in [x, y]:
X.plot(s, gm, ratio=ratio)
if X.islandscape():
orient = "ldscp"
else:
orient = "port"
fnm = "aspect_ratio_%s_%s.png" % (orient, ratio)
X.png(fnm)
print "fnm:", fnm
src = os.path.join(pth0, fnm)
print "src:", src
ret += checkimage.check_result_image(fnm, src,
checkimage.defaultThreshold)
return ret
#Now plots the amplitude underneath the data
b = x.createboxfill()
b.xticlabels1 = vcs.elements["list"]["Lon30"]
b.yticlabels1 = vcs.elements["list"]["Lat20"]
x.plot(A, b, bg=bg)
u.setAxis(0, lats)
u.setAxis(1, lons)
v.setAxis(0, lats)
v.setAxis(1, lons)
x.plot(u, v, gm, bg=bg)
ret = 0
if args.show:
x.interact()
else:
fnm = "test_vcs_basic_vectors_%i" % args.angle
if args.mask:
fnm += "_masked"
if args.scale != 1.:
fnm += "_%.1g" % args.scale
fnm += nm_xtra
x.png(fnm)
print "fnm:", fnm
print "src:", src
ret = checkimage.check_result_image(fnm + '.png',
src,
checkimage.defaultThreshold,
cleanup=not args.keep)
if args.show:
raw_input("Press Enter")
sys.exit(ret)
import sys,os,cdms2,vcs
import vcs
src1=sys.argv[1]
src2=sys.argv[2]
pth = os.path.join(os.path.dirname(__file__),"..")
sys.path.append(pth)
import checkimage
x=vcs.init()
x.setantialiasing(0)
x.drawlogooff()
x.setbgoutputdimensions(1200,1091,units="pixels")
f=cdms2.open(os.path.join(vcs.sample_data,"clt.nc"))
s=f("clt",time=slice(0,1),latitude=(-7,5),squeeze=1)
x.plot(s,bg=1)
fnm = "test_vcs_issue_960_labels_1.png"
x.png(fnm)
print "fnm:",fnm
print "src:",src1
ret = checkimage.check_result_image(fnm,src1,checkimage.defaultThreshold)
b=x.createboxfill()
b.datawc_y1=-7
b.datawc_y2=5
x.plot(s,b,bg=1)
fnm = "test_vcs_issue_960_labels_2.png"
x.png(fnm)
print "fnm:",fnm
print "src:",src2
ret += checkimage.check_result_image(fnm,src2,checkimage.defaultThreshold)
sys.exit(ret)
def execute(test_str, plotset, obstype, varid, season, imagefilename,
imagethreshold, ncfiles, rtol, atol):
print test_str
# Silence annoying messages about how to set the NetCDF file type. Anything will do.
cdms2.setNetcdfShuffleFlag(0)
cdms2.setNetcdfDeflateFlag(0)
cdms2.setNetcdfDeflateLevelFlag(0)
#get commmand line args
p = argparse.ArgumentParser(description="Basic gm testing code for vcs")
p.add_argument("--datadir",
dest="datadir",
help="root directory for model and obs data")
p.add_argument("--baseline",
dest="baseline",
help="directory with baseline files for comparing results")
p.add_argument("--keep",
dest="keep",
help="Iff True, will keep computed png and nc files")
args = p.parse_args(sys.argv[1:])
datadir = args.datadir
baselinepath = args.baseline
keep = args.keep
#setup paths to data
modelpath = os.path.join(datadir, 'cam_output')
obspath = os.path.join(datadir, 'obs_atmos')
outpath = tempfile.mkdtemp() + "/"
print "outpath=", outpath
#setup string to be executed and run script
#diagstr = "diags --outputdir '%s' --model path=%s,climos=no --obs path=%s,filter=\"f_contains('NCEP')\",climos=yes --package AMWG --set 3 --var T --seasons JJA" % (outpath, modelpath, obspath)
diagstr_parts = [
" --outputdir %s " % (outpath),
" --model path=%s,climos=no " % (modelpath),
" --obs path=%s,filter=\"f_contains('%s')\",climos=yes " %
(obspath, obstype), " --package AMWG ",
" --set %s " % (str(plotset)),
" --var %s" % (varid),
" --seasons %s" % (season)
]
diagstr = "diags "
for part in diagstr_parts:
diagstr += part
print 'executing '
print diagstr
# nonstandard, suitable for testing:
proc = subprocess.Popen([diagstr], shell=True)
proc_status = proc.wait()
if proc_status != 0:
raise DiagError("diags run failed")
if keep:
print "save ", imagefilename, ncfiles.keys()
print "output directory is = ", outpath
else:
# Test of graphics (png) file match:
# This just looks at combined plot, aka summary plot, which is a compound of three plots.
imagefname = os.path.join(outpath, imagefilename)
imagebaselinefname = os.path.join(baselinepath, imagefilename)
graphics_result = checkimage.check_result_image(
imagefname, imagebaselinefname, imagethreshold)
print "Graphics file", imagefname, "match difference:", graphics_result
# Test of NetCDF data (nc) file match:
CLOSE = True
for ncfilename, ncvars in ncfiles.items():
for var in ncvars:
#print ncfilename, var
print baselinepath
try:
close = closeness(var, ncfilename, outpath, baselinepath,
rtol, atol)
if not close:
print var, ' in ', ncfilename, ' is not close.'
except:
print 'comparison failed ', ncfilename, var
close = False
CLOSE = CLOSE and close
#cleanup the temp files
shutil.rmtree(outpath)
assert (CLOSE) #, 'data are not close'
s_esmf_lin.id = "ESMF Linear"
s_esmf_con = s.regrid(grid_dest,regridTool="esmf",regridMethod="conservative")
s_esmf_lin.id = "ESMF Conservative"
x=vcs.init()
x.setantialiasing(0)
x.drawlogooff()
x.setbgoutputdimensions(1200,1091,units="pixels")
t=x.createtemplate()
t.blank()
t.data.priority=1
t.legend.priority=1
t.dataname.priority=1
t.dataname.y=t.dataname.y*.95
M=EzTemplate.Multi(template=t,x=x,rows=2,columns=2)
gm=x.createboxfill()
levels= vcs.mkscale(*vcs.minmax(s))
cols = vcs.getcolors(levels)
gm.boxfill_type = "custom"
gm.fillareacolors = cols
gm.levels = levels
x.plot(s,M.get(),gm,bg=1)
x.plot(s_regrid2,M.get(),gm,bg=1)
x.plot(s_esmf_lin,M.get(),gm,bg=1)
x.plot(s_esmf_con,M.get(),gm,bg=1)
x.png("esmf_issue_1125")
ret = checkimage.check_result_image("esmf_issue_1125.png",png,checkimage.defaultThreshold)
sys.exit(ret)
def test_portrait(self):
try:
import vcs
except:
raise RuntimeError(
"Sorry your python is not build with VCS support cannot geenrate portrait plots")
import json
# CDAT MODULES
import pcmdi_metrics
import pcmdi_metrics.graphics.portraits
import MV2
import numpy
from genutil import statistics
import os
import sys
import glob
# CREATES VCS OBJECT AS A PORTAIT PLOT AND LOADS PLOT SETTINGS FOR
# EXAMPLE
x = vcs.init()
x.portrait()
# Turn off antialiasing for test suite
x.setantialiasing(0)
# PARAMETERS STUFF
P = pcmdi_metrics.graphics.portraits.Portrait()
# Turn off verbosity
P.verbose = False
P.PLOT_SETTINGS.levels = [-1.e20, -.5, -.4, -.3, -.2, -.1,
0., .1, .2, .3, .4, .5, 1.e20]
P.PLOT_SETTINGS.x1 = .1
P.PLOT_SETTINGS.x2 = .85
P.PLOT_SETTINGS.y1 = .12
P.PLOT_SETTINGS.y2 = .95
P.PLOT_SETTINGS.xtic2y1 = P.PLOT_SETTINGS.y1
P.PLOT_SETTINGS.xtic2y2 = P.PLOT_SETTINGS.y2
P.PLOT_SETTINGS.ytic2x1 = P.PLOT_SETTINGS.x1
P.PLOT_SETTINGS.ytic2x2 = P.PLOT_SETTINGS.x2
# P.PLOT_SETTINGS.missing_color = 3
# P.PLOT_SETTINGS.logo = None
P.PLOT_SETTINGS.time_stamp = None
P.PLOT_SETTINGS.draw_mesh = 'n'
# P.PLOT_SETTINGS.tictable.font = 3
x.scriptrun(
os.path.join(
pcmdi_metrics.__path__[0],
"..",
"..",
"..",
"..",
"share",
"graphics",
'vcs',
'portraits.scr'))
P.PLOT_SETTINGS.colormap = 'bl_rd_12'
# cols=vcs.getcolors(P.PLOT_SETTINGS.levels,range(16,40),split=1)
cols = vcs.getcolors(P.PLOT_SETTINGS.levels, range(144, 156), split=1)
P.PLOT_SETTINGS.fillareacolors = cols
P.PLOT_SETTINGS.parametertable.expansion = 100
# LIST OF VARIABLES TO BE USED IN PORTRAIT PLOT
vars = [
'pr',
'rsut',
'rsutcs',
'rlutcs',
'tas',
'tos',
'sos',
'zos',
'ua-850',
'ua-200',
'zg-500']
vars = []
# LOAD METRICS DICTIONARIES FROM JSON FILES FOR EACH VAR AND STORE AS A
# SINGLE DICTIONARY
var_cmip5_dics = {}
mods = set()
json_files = glob.glob(
os.path.join(
pcmdi_metrics.__path__[0],
"..",
"..",
"..",
"..",
"share",
"CMIP_metrics_results",
"CMIP5",
"amip",
"*.json"))
for fnm in json_files:
f = open(fnm)
d = json.load(f)
var = os.path.basename(fnm).split("_")[0]
vars.append(var)
for m in d.keys():
mods.add(m)
if var in var_cmip5_dics:
var_cmip5_dics[var].update(d)
else:
var_cmip5_dics[var] = d
vars.sort()
mods = sorted(list(mods))
print "Models:",mods
for bad in ["GridInfo", "References", "RegionalMasking",
"metrics_git_sha1", "uvcdat_version"]:
if bad in mods:
mods.remove(bad)
else:
print "Not removing column %s (not present)" % bad
# ORGANIZE METRICS INTO A VARIABLES X MODELS MATRIX
out1_rel = MV2.zeros(
(len(vars),
len(mods)),
MV2.float32) # DEFINE ARRAY
vn = -1 # VARIABLE INDEX
for var in vars: # LOOP OVER VARIABLE
vn = vn + 1
vals = []
for mod in mods: # LOOP OVER MODEL
try:
rms = var_cmip5_dics[var][mod]["defaultReference"][
"r1i1p1"]["global"]['rms_xyt_ann_GLB']
if P.verbose:
print var, ' ', mod, ' ', repr(rms), ' WITH global'
except:
rms = 1.e20
if P.verbose:
print var, ' ', mod, ' ', repr(rms), ' missing'
rms = float(rms)
vals.append(rms)
vars_ar = MV2.array(vals)
# COMPUTE MEDIAN RESULT FOR PORTRAIT NORMALIZATION
med_rms = statistics.median(vars_ar)[0]
mn = -1 # MODEL INDEX
for mod in mods:
mn = mn + 1
try:
out1_rel[vn, mn] = (float(var_cmip5_dics[var][mod]["defaultReference"][
"r1i1p1"]["global"]['rms_xyt_ann_GLB']) - med_rms) / med_rms # RELATIVE ERROR
except:
out1_rel[vn, mn] = numpy.ma.masked
# ADD SPACES FOR LABELS TO ALIGN AXIS LABELS WITH PLOT
modsAxis = mods
varsAxis = vars
# LOOP THROUGH LISTS TO ADD SPACES
for i in range(len(modsAxis)):
modsAxis[i] = modsAxis[i] + ' '
for i in range(len(varsAxis)):
varsAxis[i] = varsAxis[i] + ' '
yax = [s.encode('utf-8')
for s in mods] # CHANGE FROM UNICODE TO BYTE STRINGS
xax = vars
# GENERATE PLOT
P.decorate(out1_rel, xax, yax)
# P.plot(out1_rel,x=x,multiple=1.1,bg=0) # FOR PLOTTING TRIANGLES WHEN
# USING TWO OR MORE REFERENCE DATA SETS
P.plot(out1_rel, bg=1, x=x)
# x.backend.renWin.Render()
# END OF PLOTTING
# SAVE PLOT
src = os.path.join(os.path.dirname(__file__), "testPortrait.png")
print src
fnm = os.path.join(os.getcwd(), "testPortrait.png")
x.png(fnm)
ret = checkimage.check_result_image(
fnm,
src,
checkimage.defaultThreshold)
if ret != 0:
sys.exit(ret)
U = U(lon=(-105.0, -15.0),lev=(1000.0, 0.10000000100000001),lat=(7.0, 50.0),squeeze=1,)
canvas = vcs.init()
gm3D_Scalar = vcs.get3d_scalar('default')
args = []
args.append(U)
gm3D_Scalar.VerticalScaling = 1.0
gm3D_Scalar.IsosurfaceValue = 24.463887522462002
gm3D_Scalar.ToggleVolumePlot = vcs.on
gm3D_Scalar.ScaleColormap = [-15.383988656109274, 10.447561660497996, 1]
gm3D_Scalar.ScaleTransferFunction = [6.016036405845739, 12.382244144298838, 1]
gm3D_Scalar.XSlider = -105.0
gm3D_Scalar.ScaleOpacity = [0.0, 0.42135967065922453]
gm3D_Scalar.Animation = 0.0
gm3D_Scalar.ZSlider = 0.0, vcs.on
gm3D_Scalar.YSlider = 7.0, vcs.on
kwargs = { 'cdmsfile': f.id }
args.append( gm3D_Scalar )
canvas.plot( *args, **kwargs )
plotApp = canvas.backend.plotApps[ gm3D_Scalar ]
test_image = 'dv3d_basic_run_test.png'
reference_image = 'dv3d_basic_run_test_ref.png'
canvas.png( test_image )
if image_check:
import checkimage
ret = checkimage.check_result_image( test_image, reference_image, checkimage.defaultThreshold )
print " Image Test returned: %d " % ret
sys.exit(ret)
canvas.interact()
import cdms2
import vcs
x=vcs.init()
import sys,os
src = sys.argv[1]
pth = os.path.join(os.path.dirname(src),"..")
sys.path.append(pth)
import checkimage
f=cdms2.open(sys.prefix+"/sample_data/clt.nc")
s=f("clt",slice(0,15))
x.plot(s,bg=1)
x.animate.create(thread_it=0)
x.animate.save("test_vcs_anim_basic.mp4")
cmd = "ffmpeg -i test_vcs_anim_basic.mp4 test_anim_basic_out_%d.png"
import subprocess
import shlex
p=subprocess.Popen(shlex.split(cmd))
p.wait()
ret = 0
## now check the generated images
for i in range(15):
src_img = src % (i+1)
ret+=checkimage.check_result_image("test_anim_basic_out_%i.png" % (i+1),src_img,0.05)
sys.exit(ret)
# Initialize canvas:
canvas = vcs.init()
canvas.setbgoutputdimensions(1200,1091,units="pixels")
canvas.drawlogooff()
# Create and plot quick boxfill with default settings:
boxfill=canvas.createboxfill()
# Change the type
boxfill.boxfill_type = 'custom'
levels = range(20,81,10)
boxfill.levels=levels
boxfill.ext_1="y"
boxfill.ext_2="y"
boxfill.fillareacolors=vcs.getcolors(boxfill.levels)
canvas.plot(clt, boxfill, bg=1)
# Load the image testing module:
testingDir = os.path.join(os.path.dirname(__file__), "..")
sys.path.append(testingDir)
import checkimage
# Create the test image and compare:
baseline = sys.argv[1]
testFile = "test_boxfill_custom_ext1_ext2.png"
canvas.png(testFile)
ret = checkimage.check_result_image(testFile, baseline,
checkimage.defaultThreshold)
sys.exit(ret)
-6.74967902 -7.09622319 -5.93836983 -4.04592997 -2.65591499
-1.68180032 -0.86935245 -0.40114047 -0.54273785 -1.36178957
-2.67488251 -3.87524401 -4.84708491 -5.49186142 -5.28618944
-4.30557389 -2.89804038 -1.53825408 -1.84771029 -2.74948361
-2.23517037 -1.73306118 -0.71200646 0.76416785 1.51511193
-0.04018418 -1.54564706 -1.88664877 -0.43751604 0.89988184
0.33437949 -1.70341844 -3.79880014 -4.03570169 -4.7740073
-5.04626101 -3.77609961 -3.18667176 -2.21038272 -1.3666902
-0.54267951 -0.16472441 -0.52871418 -0.83520848 -0.90315403
-0.21747426 0.01922666 0.89621996 1.75691927 3.12657503
4.55749531 6.04921304 7.20744489 7.65294958""".split()
data = numpy.array(data,dtype=numpy.float)
data = MV2.array(data)
data=MV2.masked_where(MV2.logical_and(data>-4,data<-2),data)
#yx.datawc_x1 = 0
#yx.datawc_x2 = 80
##yx.datawc_y1 =-12
#yx.datawc_y2 = 12
x.plot(data,yx,bg=1)
fnm = "test_vcs_1d_missing.png"
x.png(fnm)
print "fnm:",fnm
print "src:",src
ret = checkimage.check_result_image(fnm,src,checkimage.defaultThreshold)
sys.exit(ret)
import vcs_legacy
x=vcs_legacy.init()
import sys,os
src = sys.argv[1]
pth = os.path.join(os.path.dirname(src),"..")
sys.path.append(pth)
import checkimage
m=x.createmarker()
m.x=[.5]
m.y=[.5]
m.type=18
m.size = 24
m.color=242
x.plot(m,bg=1)
x.setbgoutputdimensions(1200,1091,units="pixels")
x.png("test_vcs_legacy_hurricane_marker")
ret = checkimage.check_result_image("test_vcs_legacy_hurricane_marker.png",src,0.05)
sys.exit(ret)
import sys
import time
pth = os.path.join(os.path.dirname(__file__),"..")
sys.path.append(pth)
import checkimage
f=cdms2.open(os.path.join(vcs.prefix,"sample_data","clt.nc"))
s=f("clt",slice(0,12)) # read only 12 times steps to speed up things
x=vcs.init()
x.drawlogooff()
x.setbgoutputdimensions(1200,1091,units="pixels")
gm=x.createisofill()
x.plot(s,gm,bg=1)
x.animate.create()
print "Saving now"
prefix= os.path.split(__file__)[1][:-3]
x.animate.save("%s.mp4"%prefix)
pngs = x.animate.close(preserve_pngs = True) # so we can look at them again
src_pth = sys.argv[1]
pth = os.path.join(src_pth,prefix)
ret = 0
for p in pngs:
print "Checking:",p
ret += checkimage.check_result_image(p,os.path.join(pth,os.path.split(p)[1]),checkimage.defaultThreshold)
if ret == 0:
os.removedirs(os.path.split(p)[0])
os.remove("%s.mp4" % prefix)
sys.exit(ret)
vcs._colorMap = "blue_to_grn"
x.setcolormap("blue_to_grey")
else:
## Still setting vcs and canvas to make sure it is not used
vcs._colorMap = "blue_to_grn"
x.setcolormap("blue_to_grey")
gm.colormap = "blue_to_orange"
if args.gm != "meshfill":
f=cdms2.open(os.path.join(vcs.sample_data,"clt.nc"))
if args.gm == "vector":
u = f("u")
v = f("v")
else:
s=f("clt",slice(0,1))
else:
f=cdms2.open(os.path.join(vcs.sample_data,'sampleCurveGrid4.nc'))
s=f("sample")
if args.gm == "vector":
x.plot(u,v,gm,bg=True)
else:
x.plot(s,gm,bg=True)
fnm = "test_vcs_colormaps_source_%s_%s.png" % (args.gm,args.src)
x.png(fnm)
baselineImage = args.baseline
ret = checkimage.check_result_image(fnm, baselineImage,
checkimage.defaultThreshold)
sys.exit(ret)
import vcs_legacy
x = vcs_legacy.init()
import sys, os
src = sys.argv[1]
pth = os.path.join(os.path.dirname(src), "..")
sys.path.append(pth)
import checkimage
m = x.createmarker()
m.x = [.5]
m.y = [.5]
m.type = 18
m.size = 24
m.color = 242
x.plot(m, bg=1)
x.setbgoutputdimensions(1200, 1091, units="pixels")
x.png("test_vcs_legacy_hurricane_marker")
ret = checkimage.check_result_image("test_vcs_legacy_hurricane_marker.png",
src, 0.05)
sys.exit(ret)
text.height = 12
colors.append(100 + 12 * i)
if i%2 == 0:
texts.append(text.name)
else:
texts.append(text)
isoline.text = texts
# First test using isoline.text[...].color
canvas.plot(data, isoline, bg=1)
baselineImage = "%s%s"%baseline
testImage = os.path.abspath("test_isoline_labels.png")
canvas.png(testImage)
ret = checkimage.check_result_image(testImage, baselineImage,
checkimage.defaultThreshold)
# Now set isoline.linecolors and test again.
canvas.clear()
isoline.linecolors = colors
canvas.plot(data, isoline, bg=1)
baselineImage = "%s%d%s"%(baseline[0], 2, baseline[1])
testImage = os.path.abspath("test_isoline_labels2.png")
canvas.png(testImage)
ret += checkimage.check_result_image(testImage, baselineImage,
checkimage.defaultThreshold)
# Now set isoline.textcolors and test again.
canvas.clear()
import sys, os, cdms2, vcs
import vcs
src1 = sys.argv[1]
src2 = sys.argv[2]
pth = os.path.join(os.path.dirname(__file__), "..")
sys.path.append(pth)
import checkimage
x = vcs.init()
x.setantialiasing(0)
x.drawlogooff()
x.setbgoutputdimensions(1200, 1091, units="pixels")
f = cdms2.open(os.path.join(vcs.sample_data, "clt.nc"))
s = f("clt", time=slice(0, 1), latitude=(-7, 5), squeeze=1)
x.plot(s, bg=1)
fnm = "test_vcs_issue_960_labels_1.png"
x.png(fnm)
print "fnm:", fnm
print "src:", src1
ret = checkimage.check_result_image(fnm, src1, checkimage.defaultThreshold)
b = x.createboxfill()
b.datawc_y1 = -7
b.datawc_y2 = 5
x.plot(s, b, bg=1)
fnm = "test_vcs_issue_960_labels_2.png"
x.png(fnm)
print "fnm:", fnm
print "src:", src2
ret += checkimage.check_result_image(fnm, src2, checkimage.defaultThreshold)
sys.exit(ret)
text.height = 12
colors.append(100 + 12 * i)
if i % 2 == 0:
texts.append(text.name)
else:
texts.append(text)
isoline.text = texts
# First test using isoline.text[...].color
canvas.plot(data, isoline, bg=1)
baselineImage = "%s%s" % baseline
testImage = os.path.abspath("test_isoline_labels.png")
canvas.png(testImage)
ret = checkimage.check_result_image(testImage, baselineImage,
checkimage.defaultThreshold)
# Now set isoline.linecolors and test again.
canvas.clear()
isoline.linecolors = colors
canvas.plot(data, isoline, bg=1)
baselineImage = "%s%d%s" % (baseline[0], 2, baseline[1])
testImage = os.path.abspath("test_isoline_labels2.png")
canvas.png(testImage)
ret += checkimage.check_result_image(testImage, baselineImage,
checkimage.defaultThreshold)
# Now set isoline.textcolors and test again.
canvas.clear()
diagstr = "diags --outputdir '%s' --model path=%s,climos=no --obs path=%s,filter=\"f_contains('NCEP')\",climos=yes --varopts 850 --package AMWG --set 5 --var T --seasons ANN" % (pathout,path1,path2)
# nonstandard, suitable for testing:
#diagstr = "diags --outputdir '%s' --model path=%s,climos=yes --obs path=%s,filter=\"f_contains('NCEP')\",climos=yes --varopts 850 --package AMWG --set 5 --var T --seasons ANN" % (pathout,os.path.join(datadir,'cam_output_climo'),path2)
proc = subprocess.Popen([diagstr],shell=True)
proc_status = proc.wait()
if proc_status!=0:
raise DiagError("diags run failed")
# Test of graphics (png) file match:
# This just looks at combined plot, aka summary plot, which is a compound of three plots.
filename = 'set5_Global_ANN_T-combined.png'
fname = os.path.join( pathout, filename )
baselinefname = os.path.join( baselinepath, filename )
threshold = 1.0e6
graphics_result = checkimage.check_result_image( fname, baselinefname, threshold )
print "Graphics file",fname,"match difference:",graphics_result
# Test of NetCDF data (nc) file match:
rtol = 1.0e-3
atol = 1.0e-2 # suitable for temperatures
filename = 'T_ANN_at_850_mbar_(1)_None.nc'
varname = 'dv_T_lp_ANN_ft0_None_None'
close1 = closeness( varname, filename, pathout, baselinepath, rtol, atol )
filename = 'T_ANN_at_850_mbar_(2)_None.nc'
varname = 'dv_T_lp_ANN_ft1_None_None'
close2 = closeness( varname, filename, pathout, baselinepath, rtol, atol )
filename = 'T_ANN_at_850_mbar_(1)-(2)_None,_None.nc'
varname = 'dv_T_lp_ANN_ft0_None_None_dv_T_lp_ANN_ft1_None_None'
close12 = closeness( varname, filename, pathout, baselinepath, rtol, atol )
close = close1 and close2 and close12
-0.14836133615864944 -0.17956528904564023 -0.21109198032585794 -0.23846429237248942 -0.2598536549218765 -0.27795672866320387 -0.2939939095159731 -0.30541031366330024 -0.307643559333884 -0.30078421139811795 -0.2841339526883441 -0.26485737397202497 -0.24287299694779327 -0.22379014890999907 -0.20121548204699846 -0.1746486732156772 -0.14585019344118372 -0.12070675757803526 -0.0997891159111037 -0.08229393660994214 -0.06779720501287469 -0.057213385470859794 -0.04875768191096844 -0.0402377347189964 -0.030169328367807245 -0.017560662894847895 -0.006968922654137132 0.0009773980274431048 0.007054306637034288 0.010472286514133042 0.010702384151997032 0.009231553701801242 0.007544033101056543 0.004639797857203645 -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. """.split() data = numpy.array(data,dtype=numpy.float) data = MV2.masked_less(data,-900) #yx.datawc_x1 = 0 #yx.datawc_x2 = 80 ##yx.datawc_y1 =-12 #yx.datawc_y2 = 12 x.plot(data,yx,bg=1) fnm = "test_vcs_1D_datawc_missing.png" x.png(fnm) print "fnm:",fnm print "src:",src ret = checkimage.check_result_image(fnm,src,0.05) sys.exit(ret)
def test_portrait(self):
try:
import vcs
except:
raise RuntimeError(
"Sorry your python is not build with VCS support cannot geenrate portrait plots")
import json
# CDAT MODULES
import pcmdi_metrics
import pcmdi_metrics.graphics.portraits
import MV2
import numpy
from genutil import statistics
import os
import sys
import glob
print
print
print
print
print "---------------------------------------------------"
print "RUNNING: Portrait test"
print "---------------------------------------------------"
print
print
print
print
# CREATES VCS OBJECT AS A PORTAIT PLOT AND LOADS PLOT SETTINGS FOR
# EXAMPLE
x = vcs.init()
x.portrait()
# Turn off antialiasing for test suite
x.setantialiasing(0)
# PARAMETERS STUFF
P = pcmdi_metrics.graphics.portraits.Portrait()
# Turn off verbosity
P.verbose = False
P.PLOT_SETTINGS.levels = [-1.e20, -.5, -.4, -.3, -.2, -.1,
0., .1, .2, .3, .4, .5, 1.e20]
P.PLOT_SETTINGS.x1 = .1
P.PLOT_SETTINGS.x2 = .85
P.PLOT_SETTINGS.y1 = .12
P.PLOT_SETTINGS.y2 = .95
P.PLOT_SETTINGS.xtic2y1 = P.PLOT_SETTINGS.y1
P.PLOT_SETTINGS.xtic2y2 = P.PLOT_SETTINGS.y2
P.PLOT_SETTINGS.ytic2x1 = P.PLOT_SETTINGS.x1
P.PLOT_SETTINGS.ytic2x2 = P.PLOT_SETTINGS.x2
# P.PLOT_SETTINGS.missing_color = 3
# P.PLOT_SETTINGS.logo = None
P.PLOT_SETTINGS.time_stamp = None
P.PLOT_SETTINGS.draw_mesh = 'n'
# P.PLOT_SETTINGS.tictable.font = 3
x.scriptrun(
os.path.join(
sys.prefix,
"share",
"pmp",
"graphics",
'vcs',
'portraits.scr'))
P.PLOT_SETTINGS.colormap = 'bl_rd_12'
# cols=vcs.getcolors(P.PLOT_SETTINGS.levels,range(16,40),split=1)
cols = vcs.getcolors(P.PLOT_SETTINGS.levels, range(144, 156), split=1)
P.PLOT_SETTINGS.fillareacolors = cols
P.PLOT_SETTINGS.parametertable.expansion = 100
# LIST OF VARIABLES TO BE USED IN PORTRAIT PLOT
vars = [
'pr',
'rsut',
'rsutcs',
'rlutcs',
'tas',
'tos',
'sos',
'zos',
'ua-850',
'ua-200',
'zg-500']
vars = []
# LOAD METRICS DICTIONARIES FROM JSON FILES FOR EACH VAR AND STORE AS A
# SINGLE DICTIONARY
var_cmip5_dics = {}
mods = set()
json_files = glob.glob(
os.path.join(
os.path.dirname(__file__),
"json",
"*.json"))
for fnm in json_files:
f = open(fnm)
d = json.load(f)
var = os.path.basename(fnm).split("_")[0]
vars.append(var)
for m in d.keys():
mods.add(m)
if var in var_cmip5_dics:
var_cmip5_dics[var].update(d)
else:
var_cmip5_dics[var] = d
vars.sort()
mods = sorted(list(mods))
print "Models:", mods
for bad in ["GridInfo", "References", "RegionalMasking",
"metrics_git_sha1", "uvcdat_version"]:
if bad in mods:
mods.remove(bad)
else:
print "Not removing column %s (not present)" % bad
# ORGANIZE METRICS INTO A VARIABLES X MODELS MATRIX
out1_rel = MV2.zeros(
(len(vars),
len(mods)),
MV2.float32) # DEFINE ARRAY
vn = -1 # VARIABLE INDEX
for var in vars: # LOOP OVER VARIABLE
vn = vn + 1
vals = []
for mod in mods: # LOOP OVER MODEL
try:
rms = var_cmip5_dics[var][mod]["defaultReference"][
"r1i1p1"]["global"]['rms_xyt_ann_GLB']
if P.verbose:
print var, ' ', mod, ' ', repr(rms), ' WITH global'
except:
rms = 1.e20
if P.verbose:
print var, ' ', mod, ' ', repr(rms), ' missing'
rms = float(rms)
vals.append(rms)
vars_ar = MV2.array(vals)
# COMPUTE MEDIAN RESULT FOR PORTRAIT NORMALIZATION
med_rms = statistics.median(vars_ar)[0]
mn = -1 # MODEL INDEX
for mod in mods:
mn = mn + 1
try:
out1_rel[vn, mn] = (float(var_cmip5_dics[var][mod]["defaultReference"][
"r1i1p1"]["global"]['rms_xyt_ann_GLB']) - med_rms) / med_rms # RELATIVE ERROR
except:
out1_rel[vn, mn] = numpy.ma.masked
# ADD SPACES FOR LABELS TO ALIGN AXIS LABELS WITH PLOT
modsAxis = mods
varsAxis = vars
# LOOP THROUGH LISTS TO ADD SPACES
for i in range(len(modsAxis)):
modsAxis[i] = modsAxis[i] + ' '
for i in range(len(varsAxis)):
varsAxis[i] = varsAxis[i] + ' '
yax = [s.encode('utf-8')
for s in mods] # CHANGE FROM UNICODE TO BYTE STRINGS
xax = vars
# GENERATE PLOT
P.decorate(out1_rel, xax, yax)
# P.plot(out1_rel,x=x,multiple=1.1,bg=0) # FOR PLOTTING TRIANGLES WHEN
# USING TWO OR MORE REFERENCE DATA SETS
P.plot(out1_rel, bg=1, x=x)
# x.backend.renWin.Render()
# END OF PLOTTING
# SAVE PLOT
src = os.path.join(os.path.dirname(__file__), "testPortrait.png")
print src
fnm = os.path.join(os.getcwd(), "testPortrait.png")
x.png(fnm)
ret = checkimage.check_result_image(
fnm,
src,
checkimage.defaultThreshold)
if ret != 0:
sys.exit(ret)
import vcs
import cdms2
import os,sys
pth = os.path.join(os.path.dirname(__file__),"..")
sys.path.append(pth)
import checkimage
f=cdms2.open(os.path.join(vcs.sample_data,"clt.nc"))
s=f("clt")
x=vcs.init()
x.setantialiasing(0)
x.drawlogooff()
x.setbgoutputdimensions(1200,1091,units="pixels")
iso=x.createisoline()
t=x.createtext()
t.color=243
t.height=25
to=x.createtextorientation()
to.height = 55
tt=x.createtexttable()
tt.color=245
iso.textcolors=[None,None,None,242,244]
iso.text=[t,tt,to]
iso.label="y"
x.plot(s,iso,bg=1)
x.png("test_vcs_isoline_labels_multi_label_input_types.png")
src=sys.argv[1]
ret = checkimage.check_result_image('test_vcs_isoline_labels_multi_label_input_types.png',src,checkimage.defaultThreshold)
sys.exit(ret)
dataonly = vcs.createtemplate()
dataonly.blank()
dataonly.data.priority = 1
multitemplate = EzTemplate.Multi(template=dataonly, rows=4, columns=3)
line_styles = ['long-dash', 'dot', 'dash', 'dash-dot', 'solid']
for i in range(12):
cont_index = i % 6 + 1
cont_line = vcs.createline()
cont_line.width = i % 3 + 1
cont_line.type = line_styles[i % 5]
cont_line.color = i + 200
template = multitemplate.get(i)
canvas.plot(clt, template, boxfill, continents=cont_index, continents_line=cont_line, bg=1)
# Load the image testing module:
testingDir = os.path.join(os.path.dirname(__file__), "..")
sys.path.append(testingDir)
import checkimage
# Create the test image and compare:
baseline = sys.argv[1]
testFile = "test_continents.png"
canvas.png(testFile)
ret = checkimage.check_result_image(testFile, baseline,
25)
sys.exit(ret)
-0.058062458673116 -0.08764922509099882 -0.11697036914487152 -0.14836133615864944 -0.17956528904564023 -0.21109198032585794 -0.23846429237248942 -0.2598536549218765 -0.27795672866320387 -0.2939939095159731 -0.30541031366330024 -0.307643559333884 -0.30078421139811795 -0.2841339526883441 -0.26485737397202497 -0.24287299694779327 -0.22379014890999907 -0.20121548204699846 -0.1746486732156772 -0.14585019344118372 -0.12070675757803526 -0.0997891159111037 -0.08229393660994214 -0.06779720501287469 -0.057213385470859794 -0.04875768191096844 -0.0402377347189964 -0.030169328367807245 -0.017560662894847895 -0.006968922654137132 0.0009773980274431048 0.007054306637034288 0.010472286514133042 0.010702384151997032 0.009231553701801242 0.007544033101056543 0.004639797857203645 -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. """.split() data = numpy.array(data, dtype=numpy.float) data = MV2.masked_less(data, -900) #yx.datawc_x1 = 0 #yx.datawc_x2 = 80 ##yx.datawc_y1 =-12 #yx.datawc_y2 = 12 x.plot(data, yx, bg=1) fnm = "test_vcs_1D_datawc_missing.png" x.png(fnm) print "fnm:", fnm print "src:", src ret = checkimage.check_result_image(fnm, src, 0.05) sys.exit(ret)
sys.path.append(pth)
import checkimage
f = cdms2.open(os.path.join(vcs.sample_data, "clt.nc"))
s = f("clt", slice(0, 12)) # read only 12 times steps to speed up things
x = vcs.init()
x.setantialiasing(0)
x.drawlogooff()
x.setbgoutputdimensions(1200, 1091, units="pixels")
gm = x.createisofill()
x.plot(s, gm, bg=1)
x.animate.create()
print "Saving now"
prefix = os.path.split(__file__)[1][:-3]
x.animate.save("%s.mp4" % prefix)
pngs = x.animate.close(preserve_pngs=True) # so we can look at them again
src_pth = sys.argv[1]
pth = os.path.join(src_pth, prefix)
ret = 0
for p in pngs:
print "Checking:", p
ret += checkimage.check_result_image(
p, os.path.join(pth,
os.path.split(p)[1]), checkimage.defaultThreshold)
if ret == 0:
os.removedirs(os.path.split(p)[0])
os.remove("%s.mp4" % prefix)
sys.exit(ret)
import vcs
import cdms2
import os,sys
pth = os.path.join(os.path.dirname(__file__),"..")
sys.path.append(pth)
import checkimage
f=cdms2.open(os.path.join(sys.prefix,"sample_data","clt.nc"))
s=f("clt")
x=vcs.init()
x.drawlogooff()
x.setbgoutputdimensions(1200,1091,units="pixels")
iso=x.createisoline()
t=x.createtext()
t.color=243
t.height=25
to=x.createtextorientation()
to.height = 55
tt=x.createtexttable()
tt.color=245
iso.textcolors=[None,None,None,242,244]
iso.text=[t,tt,to]
iso.label="y"
x.plot(s,iso,bg=1)
x.png("test_vcs_isoline_labels_multi_label_input_types.png")
src=sys.argv[1]
ret = checkimage.check_result_image('test_vcs_isoline_labels_multi_label_input_types.png',src,checkimage.defaultThreshold)
sys.exit(ret)
x=vcs.init()
x.setantialiasing(0)
x.drawlogooff()
x.setbgoutputdimensions(1200,1091,units="pixels")
m = x.createmarker()
M=7
m.worldcoordinate=[0,M,0,M]
m.type = wmo
m.color=[242,]
m.size=[10.,]
xs = []
ys=[]
for Y in range(7):
for X in range(15):
ys.append([M-M*(Y+1)/8.,])
xs.append([M*(X+1)/16.,])
m.x = xs
m.y = ys
m.list()
x.plot(m,bg=1)
fnm = "wmo_markers.png"
x.png(fnm)
print "fnm:",fnm
print "src:",src
ret = checkimage.check_result_image(fnm,src,checkimage.defaultThreshold)
sys.exit(ret)
diagstr = "diags --outputdir '%s' --model path=%s,climos=no --obs path=%s,filter=\"f_contains('NCEP')\",climos=yes --varopts 850 --package AMWG --set 5 --var T --seasons ANN" % (
pathout, path1, path2)
# nonstandard, suitable for testing:
#diagstr = "diags --outputdir '%s' --model path=%s,climos=yes --obs path=%s,filter=\"f_contains('NCEP')\",climos=yes --varopts 850 --package AMWG --set 5 --var T --seasons ANN" % (pathout,os.path.join(datadir,'cam_output_climo'),path2)
proc = subprocess.Popen([diagstr], shell=True)
proc_status = proc.wait()
if proc_status != 0:
raise DiagError("diags run failed")
# Test of graphics (png) file match:
# This just looks at combined plot, aka summary plot, which is a compound of three plots.
filename = 'set5_Global_ANN_T-combined.png'
fname = os.path.join(pathout, filename)
baselinefname = os.path.join(baselinepath, filename)
threshold = 1.0e6
graphics_result = checkimage.check_result_image(fname, baselinefname,
threshold)
print "Graphics file", fname, "match difference:", graphics_result
# Test of NetCDF data (nc) file match:
rtol = 1.0e-3
atol = 1.0e-2 # suitable for temperatures
filename = 'T_ANN_at_850_mbar_(1)_None.nc'
varname = 'dv_T_lp_ANN_ft0_None_None'
close1 = closeness(varname, filename, pathout, baselinepath, rtol, atol)
filename = 'T_ANN_at_850_mbar_(2)_None.nc'
varname = 'dv_T_lp_ANN_ft1_None_None'
close2 = closeness(varname, filename, pathout, baselinepath, rtol, atol)
filename = 'T_ANN_at_850_mbar_(1)-(2)_None,_None.nc'
varname = 'dv_T_lp_ANN_ft0_None_None_dv_T_lp_ANN_ft1_None_None'
close12 = closeness(varname, filename, pathout, baselinepath, rtol, atol)
close = close1 and close2 and close12
s2-=s2
if args.zero:
s-=s
if args.bigvalues:
gm.levels = [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1.e36]
if gm_type=="vector":
x.plot(u,v,gm,bg=bg)
elif gm_type in ["scatter","xvsy"]:
x.plot(s,s2,gm,bg=bg)
else:
x.plot(s,gm,bg=bg)
fnm = "test_vcs_basic_%s" % gm_type.lower()
if args.mask:
fnm+="_masked"
elif args.bigvalues:
fnm+="_bigvalues"
if args.projtype!="default":
fnm+="_%s_proj" % args.projtype
if args.zero:
fnm+="_zero"
fnm+=nm_xtra
x.png(fnm)
print "fnm:",fnm
print "src:",src
ret = checkimage.check_result_image(fnm+'.png',src,checkimage.defaultThreshold, cleanup=not args.keep)
if args.show:
raw_input("Press Enter")
sys.exit(ret)
isoline = canvas.createisoline()
isoline.label = "y"
texts = []
colors = []
levels = []
for i in range(7):
levels.append(i*10)
text = canvas.createtext()
text.color = 255 - 20 * i
text.height = 12
colors.append(10 + 10 * i)
if i % 2 == 0:
texts.append(text.name)
else:
texts.append(text)
isoline.levels = levels
isoline.text = texts
isoline.linecolors = colors
isoline.linewidths = (1, 2, 3, 4, 1)
isoline.line = ('dot', 'dash', 'solid', 'dash-dot', 'long-dash', 'dot', 'dash')
# Next plot the isolines with labels
canvas.plot(data, isoline, bg=1)
testImage = os.path.abspath("test_isoline_width_stipple.png")
canvas.png(testImage)
ret = checkimage.check_result_image(testImage, baselineImage, 30)
sys.exit(ret)
