def dshape_extract(data, columns=None):
if data is None:
return None
if hasattr(data, 'dshape'):
return data.dshape
if isinstance(data, np.ndarray):
dshape = dshape_from_dtype(data.dtype)
if columns is None:
columns = gen_columns(len(data))
dshapes = [ "%s: %s"%(column, dshape) for column in columns ]
return "{" + ", ".join(dshapes)+"}"
if isinstance(data, pd.DataFrame):
return dshape_from_dataframe(data)
if isinstance(data, dict):
return dshape_from_dict(data)
return None
def dshape_extract(data: Any,
columns: Optional[List[str]] = None) -> Optional[DataShape]:
if data is None:
return None
if hasattr(data, "dshape"):
return data.dshape # type: ignore
if isinstance(data, np.ndarray):
dshape = dshape_from_dtype(data.dtype)
if columns is None:
columns = gen_columns(len(data))
dshapes = ["%s: %s" % (column, dshape) for column in columns]
return ds.dshape("{" + ", ".join(dshapes) + "}")
if isinstance(data, pd.DataFrame):
return dshape_from_dataframe(data)
if isinstance(data, dict):
return dshape_from_dict(data)
return None
def from_array(
array: np.ndarray[Any, Any],
name: Optional[str] = None,
columns: Optional[List[str]] = None,
offsets: Optional[Union[List[int], List[Tuple[int, int]]]] = None,
dshape: Optional[Union[str, DataShape]] = None,
**kwds: Any,
) -> Table:
"""offsets is a list of indices or pairs."""
if offsets is None:
offsets = [(i, i + 1) for i in range(array.shape[1])]
elif offsets is not None:
if all_int(offsets):
ioffsets = cast(List[int], offsets)
offsets = [(ioffsets[i], ioffsets[i + 1])
for i in range(len(ioffsets) - 1)]
elif not all([isinstance(elt, tuple) for elt in offsets]):
raise ValueError("Badly formed offset list %s", offsets)
toffsets = cast(List[Tuple[int, int]], offsets)
if columns is None:
if dshape is None:
columns = gen_columns(len(toffsets))
else:
dshape = dshape_create(dshape)
columns = [
fieldname for (fieldname, _) in dshape_fields(dshape)
]
if dshape is None:
dshape_type = dshape_from_dtype(array.dtype)
dims = [
"" if (off[0] + 1 == off[1]) else "%d *" % (off[1] - off[0])
for off in toffsets
]
dshapes = [
"%s: %s %s" % (column, dim, dshape_type)
for column, dim in zip(columns, dims)
]
dshape = "{" + ", ".join(dshapes) + "}"
data = OrderedDict()
for nam, off in zip(columns, toffsets):
if off[0] + 1 == off[1]:
data[nam] = array[:, off[0]]
else:
data[nam] = array[:, off[0]:off[1]]
return Table(name, data=data, dshape=str(dshape), **kwds)
def from_array(array,
name=None,
columns=None,
offsets=None,
dshape=None,
**kwds):
"""offsets is a list of indices or pairs. """
if offsets is None:
offsets = [(i, i + 1) for i in range(array.shape[1])]
if offsets is not None:
if all_int(offsets):
offsets = [(offsets[i], offsets[i + 1])
for i in range(len(offsets) - 1)]
elif not all([isinstance(elt, tuple) for elt in offsets]):
raise ValueError('Badly formed offset list %s', offsets)
if columns is None:
if dshape is None:
columns = gen_columns(len(offsets))
else:
dshape = dshape_create(dshape)
columns = [
fieldname for (fieldname, _) in dshape_fields(dshape)
]
if dshape is None:
dshape_type = dshape_from_dtype(array.dtype)
dims = [
"" if (off[0] + 1 == off[1]) else "%d *" % (off[1] - off[0])
for off in offsets
]
dshapes = [
"%s: %s %s" % (column, dim, dshape_type)
for column, dim in zip(columns, dims)
]
dshape = "{" + ", ".join(dshapes) + "}"
data = OrderedDict()
for nam, off in zip(columns, offsets):
if off[0] + 1 == off[1]:
data[nam] = array[:, off[0]]
else:
data[nam] = array[:, off[0]:off[1]]
return Table(name, data=data, dshape=dshape, **kwds)