def _jinput(arg): # strip for java input
if type(arg) is _types.DictType:
d = dict()
for k,v in arg.items():
d[_jinput(k)] = _jinput(v)
return d
elif type(arg) is _types.ListType:
return [ _jinput(a) for a in arg ]
elif type(arg) is _types.TupleType:
return tuple([ _jinput(a) for a in arg ])
elif isinstance(arg, _jlist):
return [ _jinput(a) for a in arg ]
elif type(arg) is _arraytype:
return [ _jinput(a) for a in arg if a is not None]
elif isinstance(arg, ndarray):
return arg._jdataset()
elif isinstance(arg, complex):
return _jcomplex(arg.real, arg.imag)
return arg
def asDataset(data, dtype=None, force=False):
'''
Used for arithmetic ops to coerce a sequence to a dataset otherwise leave as single item
'''
if isinstance(data, ndarray):
if dtype is None or dtype == data.dtype:
return data
return ndarray(buffer=data, dtype=dtype, copy=False)
if isinstance(data, _ds):
return ndarray(buffer=data, dtype=dtype, copy=False)
try:
iter(data)
except:
if not force:
if isinstance(data, complex):
return _jcomplex(data.real, data.imag)
return data
return ndarray(buffer=data, dtype=dtype, copy=False)
def asDataset(data, dtype=None, force=False):
"""
Used for arithmetic ops to coerce a sequence to a dataset otherwise leave as single item
"""
# if isinstance(data, _dataset):
# return Sciwrap(_dataset.convertToDoubleDataset())
if isinstance(data, ndarray):
return data
if isinstance(data, _abstractds):
return ndarray(buffer=data, dtype=dtype, copy=False)
try:
iter(data)
except:
if not force:
if isinstance(data, complex):
return _jcomplex(data.real, data.imag)
return data
return ndarray(buffer=data, dtype=dtype, copy=False)
def asDataset(data, dtype=None, force=False):
'''
Used for arithmetic ops to coerce a sequence to a dataset otherwise leave as single item
'''
if isinstance(data, ndarray):
if dtype is None or dtype == data.dtype:
return data
return ndarray(buffer=data, dtype=dtype, copy=False)
if isinstance(data, _ds):
return ndarray(buffer=data, dtype=dtype, copy=False)
try:
iter(data)
except:
if not force:
if isinstance(data, complex):
return _jcomplex(data.real, data.imag)
return data
return ndarray(buffer=data, dtype=dtype, copy=False)
def __cvt_jobj(obj, dtype=None, copy=True, force=False):
'''Convert object to java object'''
if isinstance(obj, ndarray):
obj = obj._jdataset()
if isinstance(obj, _ds):
if copy:
if dtype is None or _translatenativetype(dtype).value == obj.dtype:
return obj.clone()
else:
return obj.cast(_translatenativetype(dtype).value)
else:
if dtype is None:
return obj
return obj.cast(_translatenativetype(dtype).value)
if not isinstance(obj, list):
if isinstance(obj, _matrix): # cope with JAMA matrices
if dtype is None:
dtype = float64
obj = obj.getArray()
elif len(obj) == 0 and dtype is None:
dtype = float64
obj = _cvt2j(obj)
try:
iter(obj)
except:
if not force:
if isinstance(obj, complex):
return _jcomplex(obj.real, obj.imag)
return obj
if dtype is None:
dtype = _getdtypefromobj(obj)
else:
dtype = _translatenativetype(dtype)
return _df.createFromObject(obj, dtype.value)
def __cvt_jobj(obj, dtype=None, copy=True, force=False):
'''Convert object to java object'''
if isinstance(obj, ndarray):
obj = obj._jdataset()
dtype = _translatenativetype(dtype)
if isinstance(obj, _ds):
if copy:
if dtype is None or dtype.value == obj.getDType():
return obj.clone()
else:
return obj.cast(dtype.value)
else:
if dtype is None:
return obj
return obj.cast(dtype.value)
if not isinstance(obj, list):
if isinstance(obj, _matrix): # cope with JAMA matrices
if dtype is None:
dtype = float64
obj = obj.getArray()
elif len(obj) == 0 and dtype is None:
dtype = float64
obj = _cvt2j(obj)
try:
iter(obj)
except:
if not force:
if isinstance(obj, complex):
return _jcomplex(obj.real, obj.imag)
return obj
if dtype is None:
dtype = _getdtypefromobj(obj)
return _create(dtype.value, obj)
