def __eq__(self, other):
"""
Pandas/Numpy-style array/series comparison function.
:param other: Second operand of a Pandas "==" comparison with the series
that wraps this TokenSpanArray.
:return: Returns a boolean mask indicating which rows match `other`.
"""
if isinstance(other, (ABCDataFrame, ABCSeries, ABCIndexClass)):
# Rely on pandas to unbox and dispatch to us.
return NotImplemented
if isinstance(other, TokenSpan) and self.tokens.equals(other.tokens):
mask = np.full(len(self), True, dtype=np.bool)
mask[self.begin_token != other.begin_token] = False
mask[self.end_token != other.end_token] = False
return mask
elif isinstance(other, TokenSpanArray) and self.tokens.equals(
other.tokens):
if len(self) != len(other):
raise ValueError("Can't compare arrays of differing lengths "
"{} and {}".format(len(self), len(other)))
return np.logical_and(self.begin_token == other.begin_token,
self.end_token == other.end_token)
else:
# Different tokens, no tokens, unexpected type ==> fall back on superclass
return SpanArray.__eq__(self, other)
def __eq__(self, other):
"""
Pandas/Numpy-style array/series comparison function.
:param other: Second operand of a Pandas "==" comparison with the series
that wraps this TokenSpanArray.
:return: Returns a boolean mask indicating which rows match `other`.
"""
if isinstance(other, (ABCDataFrame, ABCSeries, ABCIndex)):
# Rely on pandas to unbox and dispatch to us.
return NotImplemented
elif (isinstance(other, TokenSpanArray) and len(self) == len(other)
and self.same_tokens(other)):
return np.logical_and(self.begin_token == other.begin_token,
self.end_token == other.end_token)
else:
# Different tokens, no tokens, unexpected type ==> fall back on superclass
return SpanArray.__eq__(self, other)