return [
{'label': label}
for label in set(labels)
]
def get_version_labels(summary, label):
return [
{
'label': label,
'version': version,
}
for version in get_versions(summary, label)
]
summary_field_strength = summarize_custom(
cursor, 'field_strength', summarize_field_strength
)
fields = get_values(summary_field_strength)
def formatter(field):
def _formatter(key):
if isinstance(key, Key):
return '{0}'.format(getattr(key, field))
return key
return _formatter
def sort_value(value):
return value.value
groups_by_year(
"""
"""
from neurotrends.config import mongo
from neurotrends.model.utils import verified_mongo
from neurotrends.analysis.groupby.naive import summarize_custom
from neurotrends.analysis.groupby.naive import summarize_smooth_kernel, summarize_highpass_cutoff
from neurotrends.analysis.plot.histplot import hist
from neurotrends.analysis.plot.utils import file_name
import numpy as np
cursor = mongo['article'].find(verified_mongo, {'tags': 1, 'date': 1})
summary_smooth_kernel = summarize_custom(cursor, 'smooth_kernel',
summarize_smooth_kernel)
summary_highpass_cutoff = summarize_custom(cursor, 'highpass_cutoff',
summarize_highpass_cutoff)
hist(summary_smooth_kernel,
bins=np.arange(0.5, 19.5, 1),
xlabel='Smoothing Kernel',
outname=file_name(['smooth-kernel'], path='hist'))
hist(summary_highpass_cutoff,
xlog=True,
xlabel='High-pass Filter Cutoff',
outname=file_name(['highpass-cutoff'], path='hist'))
"""
"""
from neurotrends.config import mongo
from neurotrends.model.utils import verified_mongo
from neurotrends.analysis.groupby.naive import summarize_custom
from neurotrends.analysis.groupby.naive import summarize_smooth_kernel, summarize_highpass_cutoff
from neurotrends.analysis.plot.histplot import hist
from neurotrends.analysis.plot.utils import file_name
import numpy as np
cursor = mongo["article"].find(verified_mongo, {"tags": 1, "date": 1})
summary_smooth_kernel = summarize_custom(cursor, "smooth_kernel", summarize_smooth_kernel)
summary_highpass_cutoff = summarize_custom(cursor, "highpass_cutoff", summarize_highpass_cutoff)
hist(
summary_smooth_kernel,
bins=np.arange(0.5, 19.5, 1),
xlabel="Smoothing Kernel",
outname=file_name(["smooth-kernel"], path="hist"),
)
hist(
summary_highpass_cutoff,
xlog=True,
xlabel="High-pass Filter Cutoff",
outname=file_name(["highpass-cutoff"], path="hist"),
)
#
def get_labels(labels):
return [{'label': label} for label in set(labels)]
def get_version_labels(summary, label):
return [{
'label': label,
'version': version,
} for version in get_versions(summary, label)]
summary_field_strength = summarize_custom(cursor, 'field_strength',
summarize_field_strength)
fields = get_values(summary_field_strength)
def formatter(field):
def _formatter(key):
if isinstance(key, Key):
return '{0}'.format(getattr(key, field))
return key
return _formatter
def sort_value(value):
return value.value
