- raise ValueError("For dimension %i, the variable definition %s is incorrect, it should be [min,max,step]."%(i,dim))
+ raise ValueError("For dimension %i, the variable definition \"%s\" is incorrect, it should be [min,max,step]."%(i,dim))
+ else:
+ coordinatesList.append(numpy.linspace(dim[0],dim[1],1+int((float(dim[1])-float(dim[0]))/float(dim[2]))))
+ sampleList = itertools.product(*coordinatesList)
+ elif len(self._parameters["SampleAsIndependantRandomVariables"]) > 0:
+ coordinatesList = []
+ for i,dim in enumerate(self._parameters["SampleAsIndependantRandomVariables"]):
+ if len(dim) != 3:
+ raise ValueError("For dimension %i, the variable definition \"%s\" is incorrect, it should be ('distribution',(parameters),length) with distribution in ['normal'(mean,std),'lognormal'(mean,sigma),'uniform'(low,high),'weibull'(shape)]."%(i,dim))
+ elif not( str(dim[0]) in ['normal','lognormal','uniform','weibull'] and hasattr(numpy.random,dim[0]) ):
+ raise ValueError("For dimension %i, the distribution name \"%s\" is not allowed, please choose in ['normal'(mean,std),'lognormal'(mean,sigma),'uniform'(low,high),'weibull'(shape)]"%(i,dim[0]))