def __init__(self, data, dshape=None, metadata=None, layout=None,
params=None):
# Datashape
# ---------
if isinstance(dshape, basestring):
dshape = _dshape(dshape)
if not dshape:
# The user just passed in a raw data source, try
# and infer how it should be layed out or fail
# back on dynamic types.
self._datashape = dshape = CTableSource.infer_datashape(data)
else:
# The user overlayed their custom dshape on this
# data, check if it makes sense
CTableSource.check_datashape(data, given_dshape=dshape)
self._datashape = dshape
# Source
# ------
if isinstance(data, ByteProvider):
self.data = data
if isinstance(data, dict):
ct = self.from_dict(data)
self._axes = data.keys()
dshape = from_numpy(ct.shape, ct.dtype)
self.data = CTableSource(ct, dshape=dshape, params=params)
self._datashape = dshape
elif isinstance(data, (list, tuple)):
self.data = CTableSource(data, dshape=dshape, params=params)
# Pull the labels from the datashape
self._axes = self._datashape[-1].names
else:
raise ValueError
# children graph nodes
self.children = []
self.space = Space(self.data)
# Layout
# ------
if layout:
self._layout = layout
elif not layout:
self._layout = self.data.default_layout()
# Metadata
# --------
self._metadata = NDTable._metaheader + (metadata or [])
# Parameters
# ----------
self.params = params
def __init__(self, obj, dshape=None, metadata=None, layout=None,
params=None):
# Datashape
# ---------
if isinstance(dshape, basestring):
dshape = _dshape(dshape)
if not dshape:
# No explicit dshape provided. Infer it from the source.
# if the source is another blaze array just use its shape,
# otherwile let the provider infer its data_shape
if isinstance(obj, Array):
dshape = obj.datashape
else:
dshape = CArraySource.infer_datashape(obj)
else:
# The user overlayed their custom dshape on this
# data, check if it makes sense
CArraySource.check_datashape(obj, given_dshape=dshape)
self._datashape = dshape
# Values
# ------
# Mimic NumPy behavior in that we have a variety of
# possible arguments to the first argument which result
# in different behavior for the values.
if isinstance(obj, ByteProvider):
self.data = obj
elif isinstance(obj, Array):
self.data = CArraySource(obj.data,
dshape=dshape,
params=params)
else:
self.data = CArraySource(obj, dshape=dshape, params=params)
# children graph nodes
self.children = []
self.space = Space(self.data)
# Layout
# ------
if layout:
self._layout = layout
elif not layout:
self._layout = self.data.default_layout()
# Metadata
# --------
self._metadata = NDArray._metaheader + (metadata or [])
# Parameters
# ----------
self.params = params
def __init__(self, obj, dshape=None, index=None, metadata=None):
self._datashape = dshape
self._metadata = NDTable._metaheader + (metadata or [])
if isinstance(dshape, str):
# run it through the parser
dshape = _dshape(dshape)
# Resolve the values
# ------------------
if isinstance(obj, Space):
self.space = obj
self.children = set(self.space.subspaces)
else:
spaces = injest_iterable(obj)
self.space = Space(*spaces)
self.children = set(self.space.subspaces)
# Resolve the shape
# -----------------
if not dshape:
# The user just passed in a raw data source, try
# and infer how it should be layed out or fail
# back on dynamic types.
self._datashape = CArraySource.infer_datashape(obj)
else:
# The user overlayed their custom dshape on this
# data, check if it makes sense
if CArraySource.check_datashape(obj, given_dshape=dshape):
self._datashape = dshape
else:
raise ValueError("Datashape is inconsistent with source")
self._layout = None
def __init__(self,
obj,
dshape=None,
metadata=None,
layout=None,
params=None):
# Datashape
# ---------
if isinstance(dshape, basestring):
dshape = _dshape(dshape)
if not dshape:
# The user just passed in a raw data source, try
# and infer how it should be layed out or fail
# back on dynamic types.
self._datashape = dshape = CArraySource.infer_datashape(obj)
else:
# The user overlayed their custom dshape on this
# data, check if it makes sense
CArraySource.check_datashape(obj, given_dshape=dshape)
self._datashape = dshape
# Values
# ------
# Mimic NumPy behavior in that we have a variety of
# possible arguments to the first argument which result
# in different behavior for the values.
if isinstance(obj, ByteProvider):
self.data = obj
else:
self.data = CArraySource(obj, params=params)
# children graph nodes
self.children = []
self.space = Space(self.data)
# Layout
# ------
if layout:
self._layout = layout
elif not layout:
self._layout = self.data.default_layout()
# Metadata
# --------
self._metadata = NDArray._metaheader + (metadata or [])
# Parameters
# ----------
self.params = params
def __init__(self,
obj,
dshape=None,
metadata=None,
layout=None,
params=None):
# Datashape
# ---------
if isinstance(dshape, basestring):
dshape = _dshape(dshape)
if not dshape:
# The user just passed in a raw data source, try
# and infer how it should be layed out or fail
# back on dynamic types.
self._datashape = dshape = CTableSource.infer_datashape(obj)
else:
# The user overlayed their custom dshape on this
# data, check if it makes sense
CTableSource.check_datashape(obj, given_dshape=dshape)
self._datashape = dshape
# Source
# ------
if isinstance(obj, ByteProvider):
self.data = obj
else:
self.data = CTableSource(obj, dshape=dshape, params=params)
# children graph nodes
self.children = []
self.space = Space(self.data)
# Layout
# ------
if layout:
self._layout = layout
elif not layout:
self._layout = self.data.default_layout()
# Metadata
# --------
self._metadata = NDTable._metaheader + (metadata or [])
# Parameters
# ----------
self.params = params
def __init__(self, obj, dshape=None, metadata=None, layout=None,
params=None):
# Datashape
# ---------
if isinstance(dshape, basestring):
dshape = _dshape(dshape)
if not dshape:
# The user just passed in a raw data source, try
# and infer how it should be layed out or fail
# back on dynamic types.
self._datashape = dshape = CArraySource.infer_datashape(obj)
else:
# The user overlayed their custom dshape on this
# data, check if it makes sense
CArraySource.check_datashape(obj, given_dshape=dshape)
self._datashape = dshape
# Values
# ------
# Mimic NumPy behavior in that we have a variety of
# possible arguments to the first argument which result
# in different behavior for the values.
if isinstance(obj, CArraySource):
self.data = obj
else:
self.data = CArraySource(obj, params)
# children graph nodes
self.children = []
self.space = Space(self.data)
# Layout
# ------
if layout:
self._layout = layout
elif not layout:
self._layout = ChunkedL(self.data, cdimension=0)
# Metadata
# --------
self._metadata = NDArray._metaheader + (metadata or [])
# Parameters
# ----------
self.params = params
def __init__(self, obj, dshape=None, metadata=None, layout=None,
params=None):
# Datashape
# ---------
if isinstance(dshape, basestring):
dshape = _dshape(dshape)
if not dshape:
# The user just passed in a raw data source, try
# and infer how it should be layed out or fail
# back on dynamic types.
self._datashape = dshape = CTableSource.infer_datashape(obj)
else:
# The user overlayed their custom dshape on this
# data, check if it makes sense
CTableSource.check_datashape(obj, given_dshape=dshape)
self._datashape = dshape
# Source
# ------
if isinstance(obj, ByteProvider):
self.data = obj
else:
self.data = CTableSource(obj, dshape=dshape, params=params)
# children graph nodes
self.children = []
self.space = Space(self.data)
# Layout
# ------
if layout:
self._layout = layout
elif not layout:
self._layout = self.data.default_layout()
# Metadata
# --------
self._metadata = NDTable._metaheader + (metadata or [])
# Parameters
# ----------
self.params = params
