def get_resrange(resrange):
'''return resrange as a string
Examples
--------
>>> get_resrange('1-3')
'resrange 1-3'
>>> get_resrange(0)
'resrange 1'
>>> get_resrange(range(3))
'resrange 1,2,3'
>>> get_resrange([2, 5, 7])
'resrange 3,6,8'
>>> get_resrange(None)
''
'''
from pytraj.utils import convert, is_int
if resrange is not None:
if is_int(resrange):
resrange = [
resrange,
]
if isinstance(resrange, string_types):
_resrange = "resrange " + resrange
else:
_resrange = convert.array_to_cpptraj_range(resrange)
_resrange = "resrange " + str(_resrange)
else:
_resrange = ""
return _resrange
def __getitem__(self, idx):
"""return a DataSet instance. Memory view is applied (which mean this new insance
is just alias of self[idx]). Should we use a copy instead?
Examples
--------
>>> import pytraj as pt
>>> traj = pt.datafiles.load_tz2_ortho()
>>> dslist = pt.multidihedral(traj)
>>> d0 = dslist[0]
>>> d1 = dslist['phi:3']
>>> d2 = dslist[:6:2]
>>> d3 = dslist[[0, 3, 8]]
>>> d4 = dslist.__getslice__(0, 3)
>>> d5 = d3.__class__()
>>> d5[0]
Traceback (most recent call last):
...
ValueError: size = 0: can not index
>> # dummy
>>> d6 = dslist[pt.Frame]
Traceback (most recent call last):
...
ValueError: index must be int, string, slice or array-like
"""
if self.size == 0:
raise ValueError("size = 0: can not index")
if is_int(idx):
return super(DatasetList, self).__getitem__(idx)
elif isinstance(idx, string_types):
for d0 in self:
if d0.key.upper() == idx.upper():
d0._base = self
return d0
elif isinstance(idx, slice):
# return new view of `self`
start, stop, step = idx.indices(self.size)
new_dslist = self.__class__()
for _idx in range(start, stop, step):
new_dslist.append(self[_idx], copy=False)
return new_dslist
elif is_array(idx) or isinstance(
idx, list) and not isinstance(idx[0], bool):
new_dslist = self.__class__()
for _idx in idx:
new_dslist.append(self[_idx], copy=False)
return new_dslist
else:
raise ValueError('index must be int, string, slice or array-like')
def __getitem__(self, idx):
"""return a DataSet instance. Memory view is applied (which mean this new insance
is just alias of self[idx]). Should we use a copy instead?
Examples
--------
>>> import pytraj as pt
>>> traj = pt.datafiles.load_tz2_ortho()
>>> dslist = pt.multidihedral(traj)
>>> d0 = dslist[0]
>>> d1 = dslist['phi:3']
>>> d2 = dslist[:6:2]
>>> d3 = dslist[[0, 3, 8]]
>>> d4 = dslist.__getslice__(0, 3)
>>> d5 = d3.__class__()
>>> d5[0]
Traceback (most recent call last):
...
ValueError: size = 0: can not index
>> # dummy
>>> d6 = dslist[pt.Frame]
Traceback (most recent call last):
...
ValueError: index must be int, string, slice or array-like
"""
if self.size == 0:
raise ValueError("size = 0: can not index")
if is_int(idx):
return super(DatasetList, self).__getitem__(idx)
elif isinstance(idx, string_types):
for d0 in self:
if d0.key.upper() == idx.upper():
d0._base = self
return d0
elif isinstance(idx, slice):
# return new view of `self`
start, stop, step = idx.indices(self.size)
new_dslist = self.__class__()
for _idx in range(start, stop, step):
new_dslist.append(self[_idx], copy=False)
return new_dslist
elif is_array(idx) or isinstance(idx, list) and not isinstance(idx[0],
bool):
new_dslist = self.__class__()
for _idx in idx:
new_dslist.append(self[_idx], copy=False)
return new_dslist
else:
raise ValueError('index must be int, string, slice or array-like')
