def dict_subset(dict_, keys, default=util_const.NoParam):
"""
Get a subset of a dictionary
Args:
dict_ (Mapping): superset dictionary
keys (Iterable): keys to take from ``dict_``
default (object, optional): if specified uses default if keys are missing
Returns:
OrderedDict: subset dictionary
SeeAlso:
:func:`dict_isect` - similar functionality, but will only take existing
keys
Example:
>>> import ubelt as ub
>>> dict_ = {'K': 3, 'dcvs_clip_max': 0.2, 'p': 0.1}
>>> keys = ['K', 'dcvs_clip_max']
>>> subdict_ = ub.dict_subset(dict_, keys)
>>> print(ub.repr2(subdict_, nl=0))
{'K': 3, 'dcvs_clip_max': 0.2}
"""
keys = list(keys)
items = util_list.take(dict_, keys, default)
subdict_ = OrderedDict(list(zip(keys, items)))
return subdict_
def dict_subset(dict_, keys, default=util_const.NoParam, cls=OrderedDict):
"""
Get a subset of a dictionary
Args:
dict_ (Dict[KT, VT]): superset dictionary
keys (Iterable[KT]): keys to take from ``dict_``
default (Optional[object] | util_const._NoParamType):
if specified uses default if keys are missing.
cls (Type[Dict], default=OrderedDict): type of the returned dictionary.
Returns:
Dict[KT, VT]: subset dictionary
SeeAlso:
:func:`dict_isect` - similar functionality, but ignores missing keys
Example:
>>> import ubelt as ub
>>> dict_ = {'K': 3, 'dcvs_clip_max': 0.2, 'p': 0.1}
>>> keys = ['K', 'dcvs_clip_max']
>>> subdict_ = ub.dict_subset(dict_, keys)
>>> print(ub.repr2(subdict_, nl=0))
{'K': 3, 'dcvs_clip_max': 0.2}
"""
keys = list(keys)
items = util_list.take(dict_, keys, default)
subdict_ = cls(list(zip(keys, items)))
return subdict_
def main():
import ubelt as ub
from ubelt import util_list
from ubelt.util_list import take
import random
from math import e
# # Data
N = 100
array = [random.random() for _ in range(N)]
indices = [random.randint(0, N - 1) for _ in range(int(N // e))]
ti = ub.Timerit(2 ** 11, bestof=2 ** 8, verbose=1)
for timer in ti.reset('take'):
with timer:
list(take(array, indices))
for timer in ti.reset('util_list.take'):
with timer:
list(util_list.take(array, indices))
for timer in ti.reset('ub.take'):
with timer:
list(ub.take(array, indices))
print('---')
# import pandas as pd
# df = pd.DataFrame(rankings)
# print('df =\n{}'.format(df))
print('rankings = {}'.format(ub.repr2(ti.rankings, precision=9, nl=2)))
print('consistency = {}'.format(ub.repr2(ti.consistency, precision=9, nl=2)))
positions = ub.ddict(list)
for m1, v1 in ti.rankings.items():
for pos, label in enumerate(ub.argsort(v1), start=0):
positions[label].append(pos)
average_position = ub.map_vals(lambda x: sum(x) / len(x), positions)
print('average_position = {}'.format(ub.repr2(average_position)))