def get_sample_source(prob_label):
"""Return a SampleSource representing the problem, and sample_sizes to try
in a 2-tuple"""
# map: prob_label -> (sample_source, sample_sizes)
sample_sizes = [i * 2000 for i in range(1, 5 + 1)]
#sample_sizes = [i*1000 for i in range(1, 3+1)]
prob2ss = {
'SSBlobs': (data.SSBlobs(), sample_sizes),
'gmd_d100': (data.SSGaussMeanDiff(d=100, my=1.0), sample_sizes),
'gvd_d50': (data.SSGaussVarDiff(d=50), sample_sizes),
# The null is true
'sg_d50': (data.SSSameGauss(d=50), sample_sizes),
'sg_d5': (data.SSSameGauss(d=5), sample_sizes)
}
if prob_label not in prob2ss:
raise ValueError('Unknown problem label. Need to be one of %s' %
str(list(prob2ss.keys())))
return prob2ss[prob_label]
def get_sample_source_list(prob_label):
"""Return a list of SampleSource's representing the problems, each
corresponding to one dimension in the list.
"""
# map: prob_label -> [sample_source]
# dimensions to try
dimensions = [5] + [100*i for i in range(1, 5+1)]
high_dims = [5] + [300*i for i in range(1, 5+1)]
low_dims = [2*d for d in range(1, 7+1)]
prob2ss = {
'gmd': [data.SSGaussMeanDiff(d=d, my=1.0) for d in high_dims],
'gvd': [data.SSGaussVarDiff(d=d) for d in dimensions],
# The null is true
'sg': [data.SSSameGauss(d=d) for d in high_dims],
'sg_low': [data.SSSameGauss(d=d) for d in low_dims]
}
if prob_label not in prob2ss:
raise ValueError('Unknown problem label. Need to be one of %s'%str(prob2ss.keys()) )
return prob2ss[prob_label]
def get_sample_source(prob_label):
"""Return a SampleSource corresponding to the problem label.
"""
# map: prob_label -> sample_source
prob2ss = {
'SSBlobs': data.SSBlobs(),
'gmd_d100': data.SSGaussMeanDiff(d=100, my=1.0),
'gvd_d50': data.SSGaussVarDiff(d=50),
'gvd_d100': data.SSGaussVarDiff(d=100),
# The null is true
'sg_d50': data.SSSameGauss(d=50)
}
if prob_label not in prob2ss:
raise ValueError('Unknown problem label. Need to be one of %s' %
str(prob2ss.keys()))
return prob2ss[prob_label]
