size_parameter_info = [
{'name':'Type', 'cols':[
{'name':'rural'},
{'name':'urban'},
{'name':'maritime'}
] },
{'name':'RH', 'units':'%', 'values':[0,50,70,80,90,95,99,99]},
{'name':'Stats', 'cols':[
{'name':'Average radius fine'},
{'name':'Sigma fine'},
{'name':'Average radius coarse'},
{'name':'Sigma coarse'}
]}
]
size_parameter = MetaArray((3,8,4),dtype=float,
info=size_parameter_info)
size_parameter['Type':'rural', 'RH':0] = [0.02700, 0.35, 0.4300, 0.4]
size_parameter['Type':'rural', 'RH':1] = [0.02748, 0.35, 0.4377, 0.4]
size_parameter['Type':'rural', 'RH':2] = [0.02846, 0.35, 0.4571, 0.4]
size_parameter['Type':'rural', 'RH':3] = [0.03274, 0.35, 0.5477, 0.4]
size_parameter['Type':'rural', 'RH':4] = [0.03884, 0.35, 0.6462, 0.4]
size_parameter['Type':'rural', 'RH':5] = [0.04238, 0.35, 0.7078, 0.4]
size_parameter['Type':'rural', 'RH':6] = [0.04751, 0.35, 0.9728, 0.4]
size_parameter['Type':'rural', 'RH':7] = [0.05215, 0.35, 1.1755, 0.4]
size_parameter['Type':'urban', 'RH':0] = [0.02500, 0.35, 0.4000, 0.4]
size_parameter['Type':'urban', 'RH':1] = [0.02563, 0.35, 0.4113, 0.4]
size_parameter['Type':'urban', 'RH':2] = [0.02911, 0.35, 0.4777, 0.4]
size_parameter['Type':'urban', 'RH':3] = [0.03514, 0.35, 0.5805, 0.4]
size_parameter['Type':'urban', 'RH':4] = [0.04187, 0.35, 0.7061, 0.4]
def __new__(cls, *args, **kw):
obj = MetaArray.__new__(cls, *args, **kw)
#print "fma extra"
obj.extrainfo = obj._info[-1]
return obj
def __new__(*args, **kwargs):
subarr = MetaArray.__new__(*args, **kwargs)
subarr.extrainfo = subarr._info[-1]
return subarr
def __new__(*args, **kwargs):
subarr = MetaArray.__new__(*args, **kwargs)
subarr.extrainfo = subarr._info[-1]
return subarr
