"""

"""

from neurotrends import validate as val

# Validate boolean values
validation = val.validate()
dprimes = {tag: stats["dprime"] for tag, stats in validation.iteritems()}
val.validate_hist(dprimes, "D-Prime")

# Validate continuous values

_, rp_smooth_kernel, nt_smooth_kernel, = val.validate_continuous(
    val.rp_extract_smooth_kernel, val.nt_extract_smooth_kernel
)
print "Continuous Validation: Smoothing Kernel"
print val.format_continuous_validation(rp_smooth_kernel, nt_smooth_kernel)

_, rp_highpass_cutoff, nt_highpass_cutoff, = val.validate_continuous(
    val.rp_extract_highpass_cutoff, val.nt_extract_highpass_cutoff
)
print "Continuous Validation: High-pass Cutoff"
print val.format_continuous_validation(rp_highpass_cutoff, nt_highpass_cutoff)
Beispiel #2
0
        } for tag, info in tags.iteritems()])
    return pd.DataFrame(data).sort('dprime')


print('{0} articles included in both sets'.format(len(val.pmids)))
print('{0} articles included in both sets, excluding supplements'.format(
    len(val.pmids_no_supplement)))

# Validate categorical values

validation = val.validate()
dprimes, groups = to_hist(validation)
frame = to_frame(validation)
val.validate_hist(dprimes,
                  bins=5,
                  labels=groups,
                  title='Supplements included',
                  xlabel='D-Prime',
                  outname=file_name(['dprime-supplements'], path='validate'))
frame.to_csv(file_name(['dprime-supplements'], path='validate'), ext='.csv')
print('Categorical Validation: Supplements Included')
print(np.mean(sum(dprimes, [])))

validation = val.validate(no_supplement=True)
dprimes, groups = to_hist(validation)
frame = to_frame(validation)
val.validate_hist(dprimes,
                  bins=5,
                  labels=groups,
                  title='Supplements excluded',
                  xlabel='D-Prime',
                  outname=file_name(['dprime-no-supplements'],
            if tag['dprime'] is not None
        ])
    return dprimes, groups

print('{0} articles included in both sets'.format(
    len(val.pmids)
))
print('{0} articles included in both sets, excluding supplements'.format(
    len(val.pmids_no_supplement)
))

# Validate boolean values
validation = val.validate()
dprimes, groups = to_hist(validation)
val.validate_hist(
    dprimes, labels=groups, title='Supplements included', xlabel='D-Prime',
    outname=file_name(['dprime-supplements'], path='validate')
)
print('Categorical Validation: Supplements Included')
print(np.mean(sum(dprimes, [])))

validation = val.validate(no_supplement=True)
dprimes, groups = to_hist(validation)
val.validate_hist(
    dprimes, labels=groups, title='Supplements excluded', xlabel='D-Prime',
    outname=file_name(['dprime-no-supplements'], path='validate')
)
print('Categorical Validation: Supplements Excluded')
print(np.mean(sum(dprimes, [])))

# Validate continuous values