def _group(self, key):
# adapted from `toolz` package.
# see license in $PYTRAJHOME/licenses/externals/toolz.txt
import collections
# d = collections.defaultdict(lambda: self.__class__().append)
d = collections.defaultdict(lambda: [].append)
for item in self:
d[key(item)](item)
rv = {}
for k, v in iteritems(d):
rv[k] = v.__self__
return rv
def __init__(self, dslist=None, copy=False):
if dslist:
if isinstance(dslist, dict):
# {'x': [1, 3, 5], 'y': [4, 7, 8]}
for key, values in iteritems(dslist):
self.append(DataArray({key: values}), copy=copy)
else:
for d0 in dslist:
# always make a copy
# from DataArray(d0)
# so we set copy=False here
# to avoid copying twice
self.append(DataArray(d0), copy=copy)
def groupby(key, seq):
# lightly adapted from `toolz` package.
# see license in $PYTRAJHOME/licenses/externals/toolz.txt
'''
Examples
--------
>>> names = ['Alice', 'Bob', 'Charlie', 'Dan', 'Edith', 'Frank']
>>> _ = groupby(len, names)
'''
d = defaultdict(lambda: seq.__class__().append)
for item in seq:
d[key(item)](item)
rv = {}
for k, v in iteritems(d):
rv[k] = v.__self__
return rv
def groupby(key, seq):
# lightly adapted from `toolz` package.
# see license in $PYTRAJHOME/licenses/externals/toolz.txt
'''
Examples
--------
>>> names = ['Alice', 'Bob', 'Charlie', 'Dan', 'Edith', 'Frank']
>>> groupby(len, names)
{3: ['Bob', 'Dan'], 5: ['Alice', 'Edith', 'Frank'], 7: ['Charlie']}
'''
d = defaultdict(lambda: seq.__class__().append)
for item in seq:
d[key(item)](item)
rv = {}
for k, v in iteritems(d):
rv[k] = v.__self__
return rv
def concat_dict(iterables):
"""concat dict
Examples
--------
>>> dict_0 = {'x' : [1, 2, 3,]}
>>> dict_1 = {'x' : [4, 5]}
>>> concat_dict((dict_0, dict_1))
OrderedDict([('x', array([1, 2, 3, 4, 5]))])
"""
new_dict = OrderedDict()
for i, d in enumerate(iterables):
if i == 0:
# make a copy of first dict
new_dict.update(d)
else:
for k, v in iteritems(new_dict):
new_dict[k] = np.concatenate((new_dict[k], d[k]))
return new_dict
def dict_to_ndarray(dict_of_array):
"""convert OrderedDict to numpy array
Examples
--------
>>> import pytraj as pt
>>> traj = pt.load_sample_data('tz2')
>>> dslist = pt.multidihedral(traj, dhtypes='phi psi', resrange='2', dtype='dict')
>>> list(dslist.keys())
['phi:2', 'psi:2']
>>> dict_to_ndarray(dslist)
array([[-128.72617304, -109.44321317, -130.93278259, ..., -146.70146067,
-121.58263643, -112.74485175],
[ 150.11249102, 142.52303293, 131.11609265, ..., 123.44883266,
141.18992429, 120.03168126]])
"""
if not isinstance(dict_of_array, OrderedDict):
raise NotImplementedError("support only OrderedDict")
from pytraj.externals.six import iteritems
return np.array([v for _, v in iteritems(dict_of_array)])