def __init__(self, categorical_data, categories=None, jitter=None, units=None):
"""
:param categorical_data: The underlying :class:`numpy.ndarray`
:param categories: List of unique values in the data
:jitter: Strategy for jittering the data
"""
# TOOD: deal with custom categories
super(CategoricalComponent, self).__init__(None, units)
self._data = categorical_ndarray(categorical_data, copy=False, categories=categories)
if self._data.ndim != 1:
raise ValueError("Categorical Data must be 1-dimensional")
self.jitter(method=jitter)
def __init__(self,
categorical_data,
categories=None,
jitter=None,
units=None):
# TOOD: deal with custom categories
super(CategoricalComponent, self).__init__(None, units)
self._data = categorical_ndarray(categorical_data,
copy=False,
categories=categories)
if self._data.ndim < 1:
raise ValueError("Categorical Data must be at least 1-dimensional")
self.jitter(method=jitter)
def __init__(self, categorical_data, categories=None, jitter=None, units=None):
"""
:param categorical_data: The underlying :class:`numpy.ndarray`
:param categories: List of unique values in the data
:jitter: Strategy for jittering the data
"""
# TOOD: deal with custom categories
super(CategoricalComponent, self).__init__(None, units)
self._data = categorical_ndarray(categorical_data, copy=False, categories=categories)
if self._data.ndim != 1:
raise ValueError("Categorical Data must be 1-dimensional")
self.jitter(method=jitter)