def testErrors(self):
crpss_dict = self.crpssDict()
crpss_dict['variable'] = 'pr'
crpss = Crpss(**crpss_dict)
self.assertRaises(NoFilesFoundError, crpss.prepareInput)
crpss_dict['variable'] = 'tas'
crpss_dict['observation'] = 'merra'
crpss = Crpss(**crpss_dict)
self.assertRaises(NotEnoughYearsInFile, crpss.prepareInput)
crpss_dict['observation'] = 'HadCrut'
crpss_dict['project'] = 'cmip5'
crpss_dict['experiment'] = 'hist*'
crpss_dict['product1'] = 'output1'
crpss = Crpss(**crpss_dict)
self.assertRaises(NoFilesFoundError, crpss.prepareInput)
crpss_dict = self.crpssDict()
crpss_dict['ensemblemembers'] = 'r1i1p1'
crpss.deleteCache()
crpss = Crpss(**crpss_dict)
#crpss.prepareInput()
self.assertRaises(NotEnoughEnsemblemembersFound, crpss.prepareInput)#crpss.analyze)
def main(argv=None): # IGNORE:C0111
'''Command line options.'''
if argv is None:
argv = sys.argv[1:]
args, lastargs = getopt.getopt(argv, _short_args, _args)
for flag,arg in args:
if flag=='-h' or flag=='--help':
return printHelp()
murcss_dict = getMurcssDict()
for arg in lastargs:
if '=' not in arg:
raise CommandError("Invalid format for query: %s" % arg)
items = arg.split('=')
key, value = items[0], ''.join(items[1:])
murcss_dict[key] = value
murcss_dict['decadals'] = map(int,murcss_dict['decadals'].split(','))
murcss_dict['bootstrap_number'] = int(murcss_dict['bootstrap_number'])
analysis_type = murcss_dict.pop('analysis_type')
if analysis_type == 'map':
murcss_dict['fieldmean'] = False
murcss_dict['zonalmean'] = False
elif analysis_type == 'fieldmean':
murcss_dict['fieldmean'] = True
murcss_dict['zonalmean'] = False
elif analysis_type == 'zonalmean':
murcss_dict['fieldmean'] = False
murcss_dict['zonalmean'] = True
output_type = murcss_dict.pop('output_type')
if output_type == 'basic':
murcss_dict['basic_output'] = True
else:
murcss_dict['basic_output'] = False
#Check for right metics value
metrics = murcss_dict.pop('metrics')
if metrics not in ['all','accuracy','ensemble_spread']:
raise Exception, '%s is not a valid option. Only valid options for metric are: "all", "ensemble_spread", and "accuracy".' % (metrics)
if metrics in ['all','accuracy']:
print '#######################'
print 'Calculating the MSSS'
print '#######################'
#Calculation of MSESS
if(not murcss_dict['significance']):
msss_dict = murcss_dict.copy()
msss_dict.pop('bootstrap_number')
msss_dict.pop('significance')
msss = Msss(**msss_dict)
msss.prepareInput()
msss.analyze()
msss.deleteCache()
else:
from metrics.msssBootstrap import main
msss = main(murcss_dict.copy(),'..')
if metrics in ['all','ensemble_spread']:
print '#######################'
print 'Calculating the CRPSS for Model1'
print '#######################'
crpss1 = Crpss(output=murcss_dict['output'],
output_plots=murcss_dict['output_plots'],
basic_output=murcss_dict['basic_output'],
decadals=murcss_dict['decadals'],
variable=murcss_dict['variable'],
project = murcss_dict['project1'],
product1=murcss_dict['product1'],
institute1=murcss_dict['institute1'],
model=murcss_dict['model1'],
experiment=murcss_dict['experiment1'],
ensemblemembers=murcss_dict['ensemblemembers1'],
observation = murcss_dict['observation'],
leadtimes=murcss_dict['leadtimes'],
result_grid=murcss_dict['result_grid'],
maskMissingValues=murcss_dict['maskMissingValues'],
bootstrapSwitch=murcss_dict['significance'],
bootstrap_number=murcss_dict['bootstrap_number'],
level=murcss_dict['level'],
lonlatbox=murcss_dict['lonlatbox'],
fieldmean=murcss_dict['fieldmean'],
zonalmean=murcss_dict['zonalmean'],
cache=murcss_dict['cache'],
baseDir = murcss_dict['baseDir'])
if metrics != 'ensemble_spread':
crpss1.outputDir = msss.outputDir
crpss1.outputPlots = msss.outputPlots
crpss1.prepareInput()
crpss1.analyze()
crpss1.deleteCache()
print '#######################'
print 'Calculating the CRPSS for Model2'
print '#######################'
crpss2 = Crpss(output=murcss_dict['output'],
output_plots=murcss_dict['output_plots'],
basic_output=murcss_dict['basic_output'],
decadals=murcss_dict['decadals'],
variable=murcss_dict['variable'],
project = murcss_dict['project2'],
product1=murcss_dict['product2'],
institute1=murcss_dict['institute2'],
model=murcss_dict['model2'],
experiment=murcss_dict['experiment2'],
ensemblemembers=murcss_dict['ensemblemembers2'],
observation = murcss_dict['observation'],
leadtimes=murcss_dict['leadtimes'],
result_grid=murcss_dict['result_grid'],
maskMissingValues=murcss_dict['maskMissingValues'],
bootstrapSwitch=murcss_dict['significance'],
bootstrap_number=murcss_dict['bootstrap_number'],
level=murcss_dict['level'],
lonlatbox=murcss_dict['lonlatbox'],
fieldmean=murcss_dict['fieldmean'],
zonalmean=murcss_dict['zonalmean'],
cache=murcss_dict['cache'],
input_part='input2',
baseDir = murcss_dict['baseDir'])
if metrics != 'ensemble_spread':
crpss2.outputDir = msss.outputDir
crpss2.outputPlots = msss.outputPlots
crpss2.prepareInput()
crpss2.analyze()
crpss2.deleteCache()
import metrics.msss, metrics.metricAbstract, metrics.filehandler, metrics.taylorplot, metrics.crpss, metrics.msssBootstrap
del metrics.msss.cdo, metrics.metricAbstract.cdo, metrics.filehandler.cdo, metrics.taylorplot.cdo, metrics.crpss.cdo, metrics.msssBootstrap.cdo
print 'Calculation finished.'
print 'Plots produced in %s' %(msss.outputPlots,)