def test_unsignednumpyint_to_rint():
values = (1, 2, 3)
a8 = numpy.array(values, dtype='uint8')
v = rpyn.unsignednumpyint_to_rint(a8)
assert values == tuple(v)
a64 = numpy.array(values, dtype='uint64')
with pytest.raises(ValueError):
rpyn.unsignednumpyint_to_rint(a64)
def test_unsignednumpyint_to_rint(dtype):
values = (1, 2, 3)
a = numpy.array(values, dtype=dtype)
v = rpyn.unsignednumpyint_to_rint(a)
assert values == tuple(v)
def test_unsignednumpyint_to_rint_error(dtype):
values = (1, 2, 3)
a = numpy.array(values, dtype=dtype)
with pytest.raises(ValueError):
rpyn.unsignednumpyint_to_rint(a)
def py2rpy_pandasseries(obj):
if obj.dtype.name == 'O':
warnings.warn('Element "%s" is of dtype "O" and converted '
'to R vector of strings.' % obj.name)
res = StrVector(obj)
elif obj.dtype.name == 'category':
res = py2rpy_categoryseries(obj)
res = FactorVector(res)
elif is_datetime64_any_dtype(obj.dtype):
# time series
tzname = obj.dt.tz.zone if obj.dt.tz else ''
d = [
IntVector([x.year for x in obj]),
IntVector([x.month for x in obj]),
IntVector([x.day for x in obj]),
IntVector([x.hour for x in obj]),
IntVector([x.minute for x in obj]),
FloatSexpVector([x.second + x.microsecond * 1e-6 for x in obj])
]
res = ISOdatetime(*d, tz=StrSexpVector([tzname]))
# TODO: can the POSIXct be created from the POSIXct constructor ?
# (is '<M8[ns]' mapping to Python datetime.datetime ?)
res = POSIXct(res)
elif (obj.dtype == dt_O_type):
homogeneous_type = None
for x in obj.values:
if x is None:
continue
if homogeneous_type is None:
homogeneous_type = type(x)
continue
if type(x) is not homogeneous_type:
raise ValueError('Series can only be of one type, or None.')
# TODO: Could this be merged with obj.type.name == 'O' case above ?
res = {
int: IntVector,
bool: BoolVector,
None: BoolVector,
str: StrVector,
bytes: numpy2ri.converter.py2rpy.registry[numpy.ndarray]
}[homogeneous_type](obj)
elif obj.dtype.name in integer_array_types:
if not obj.dtype.numpy_dtype.isnative:
raise (ValueError('Cannot pass numpy arrays with non-native byte'
' orders at the moment.'))
if obj.dtype.kind == 'i':
res = numpy2ri._numpyarray_to_r(obj, IntVector)
elif obj.dtype.kind == 'u':
res = numpy2ri.unsignednumpyint_to_rint(obj)
else:
raise (ValueError('Unknown pandas dtype "%s".' % str(obj.dtype)))
if len(obj.shape) == 1:
if obj.dtype != dt_O_type:
# force into an R vector
res = as_vector(res)
else:
# converted as a numpy array
func = numpy2ri.converter.py2rpy.registry[numpy.ndarray]
# current conversion as performed by numpy
res = func(obj)
if len(obj.shape) == 1:
if (obj.dtype != dt_O_type):
# force into an R vector
res = as_vector(res)
# "index" is equivalent to "names" in R
if obj.ndim == 1:
res.do_slot_assign('names',
StrVector(tuple(str(x) for x in obj.index)))
else:
res.do_slot_assign('dimnames',
SexpVector(conversion.py2rpy(obj.index)))
return res