def autotyped(cls, data, units=None):
"""
Automatically choose between Component and CategoricalComponent,
based on the input data type.
:param data: The data to pack into a Component (array-like)
:param units: Optional units
:type units: str
:returns: A Component (or subclass)
"""
data = np.asarray(data)
if np.issubdtype(data.dtype, np.object_):
return CategoricalComponent(data, units=units)
if data.dtype.kind == 'M':
return DateTimeComponent(data)
n = coerce_numeric(data)
thresh = 0.5
try:
use_categorical = np.issubdtype(data.dtype, np.character) and \
np.isfinite(n).mean() <= thresh
except TypeError: # isfinite not supported. non-numeric dtype
use_categorical = True
if use_categorical:
return CategoricalComponent(data, units=units)
else:
return Component(n, units=units)
def __init__(self, data, units=None):
# The physical units of the data
self.units = units
# The actual data
# subclasses may pass non-arrays here as placeholders.
if isinstance(data, np.ndarray):
if data.dtype.kind == 'M':
raise TypeError(
'DateTimeComponent should be used instead of Component for np.datetime64 arrays'
)
data = coerce_numeric(data)
data.setflags(write=False) # data is read-only
self._data = data
def __init__(self, data, units=None):
"""
:param data: The data to store
:type data: :class:`numpy.ndarray`
:param units: Optional unit label
:type units: str
"""
# The physical units of the data
self.units = units
# The actual data
# subclasses may pass non-arrays here as placeholders.
if isinstance(data, np.ndarray):
data = coerce_numeric(data)
data.setflags(write=False) # data is read-only
self._data = data
def autotyped(cls, data, units=None):
"""
Automatically choose between Component and CategoricalComponent,
based on the input data type.
Parameters
----------
data : array-like
The data to pack into a Component.
units : `str`, optional
Unit description.
Returns
-------
:class:`Component` (or subclass)
"""
if DASK_INSTALLED and isinstance(data, da.Array):
return DaskComponent(data, units=units)
data = np.asarray(data)
if np.issubdtype(data.dtype, np.object_):
return CategoricalComponent(data, units=units)
if data.dtype.kind == 'M':
return DateTimeComponent(data)
n = coerce_numeric(data.ravel()).reshape(data.shape)
thresh = 0.5
try:
use_categorical = np.issubdtype(data.dtype, np.character) and \
np.isfinite(n).mean() <= thresh
except TypeError: # isfinite not supported. non-numeric dtype
use_categorical = True
if use_categorical:
return CategoricalComponent(data, units=units)
else:
return Component(n, units=units)
def __init__(self, data, units=None):
"""
:param data: The data to store
:type data: :class:`numpy.ndarray`
:param units: Optional unit label
:type units: str
"""
# The physical units of the data
self.units = units
# The actual data
# subclasses may pass non-arrays here as placeholders.
if isinstance(data, np.ndarray):
if data.dtype.kind == 'M':
raise TypeError('DateTimeComponent should be used instead of Component for np.datetime64 arrays')
data = coerce_numeric(data)
data.setflags(write=False) # data is read-only
self._data = data
