def na_op(x, y):
try:
result = expressions.evaluate(op, str_rep, x, y,
raise_on_error=True, **eval_kwargs)
except TypeError:
xrav = x.ravel()
if isinstance(y, (np.ndarray, ABCSeries)):
dtype = np.find_common_type([x.dtype, y.dtype], [])
result = np.empty(x.size, dtype=dtype)
yrav = y.ravel()
mask = notnull(xrav) & notnull(yrav)
xrav = xrav[mask]
yrav = yrav[mask]
if np.prod(xrav.shape) and np.prod(yrav.shape):
result[mask] = op(xrav, yrav)
elif hasattr(x, 'size'):
result = np.empty(x.size, dtype=x.dtype)
mask = notnull(xrav)
xrav = xrav[mask]
if np.prod(xrav.shape):
result[mask] = op(xrav, y)
else:
raise TypeError("cannot perform operation {op} between "
"objects of type {x} and {y}".format(
op=name, x=type(x), y=type(y)))
result, changed = _maybe_upcast_putmask(result, ~mask, np.nan)
result = result.reshape(x.shape)
result = missing.fill_zeros(result, x, y, name, fill_zeros)
return result
def na_op(x, y):
try:
result = expressions.evaluate(op, str_rep, x, y,
raise_on_error=True, **eval_kwargs)
except TypeError:
# TODO: might need to find_common_type here?
result = np.empty(len(x), dtype=x.dtype)
mask = notnull(x)
result[mask] = op(x[mask], y)
result, changed = _maybe_upcast_putmask(result, ~mask, np.nan)
result = missing.fill_zeros(result, x, y, name, fill_zeros)
return result
def _get_values(values,
skipna,
fill_value=None,
fill_value_typ=None,
isfinite=False,
copy=True):
""" utility to get the values view, mask, dtype
if necessary copy and mask using the specified fill_value
copy = True will force the copy
"""
values = _values_from_object(values)
if isfinite:
mask = _isfinite(values)
else:
mask = isnull(values)
dtype = values.dtype
dtype_ok = _na_ok_dtype(dtype)
# get our fill value (in case we need to provide an alternative
# dtype for it)
fill_value = _get_fill_value(dtype,
fill_value=fill_value,
fill_value_typ=fill_value_typ)
if skipna:
if copy:
values = values.copy()
if dtype_ok:
np.putmask(values, mask, fill_value)
# promote if needed
else:
values, changed = _maybe_upcast_putmask(values, mask, fill_value)
elif copy:
values = values.copy()
values = _view_if_needed(values)
# return a platform independent precision dtype
dtype_max = dtype
if is_integer_dtype(dtype) or is_bool_dtype(dtype):
dtype_max = np.int64
elif is_float_dtype(dtype):
dtype_max = np.float64
return values, mask, dtype, dtype_max
def _get_values(values, skipna, fill_value=None, fill_value_typ=None,
isfinite=False, copy=True):
""" utility to get the values view, mask, dtype
if necessary copy and mask using the specified fill_value
copy = True will force the copy
"""
values = _values_from_object(values)
if isfinite:
mask = _isfinite(values)
else:
mask = isnull(values)
dtype = values.dtype
dtype_ok = _na_ok_dtype(dtype)
# get our fill value (in case we need to provide an alternative
# dtype for it)
fill_value = _get_fill_value(dtype, fill_value=fill_value,
fill_value_typ=fill_value_typ)
if skipna:
if copy:
values = values.copy()
if dtype_ok:
np.putmask(values, mask, fill_value)
# promote if needed
else:
values, changed = _maybe_upcast_putmask(values, mask, fill_value)
elif copy:
values = values.copy()
values = _view_if_needed(values)
# return a platform independent precision dtype
dtype_max = dtype
if is_integer_dtype(dtype) or is_bool_dtype(dtype):
dtype_max = np.int64
elif is_float_dtype(dtype):
dtype_max = np.float64
return values, mask, dtype, dtype_max
def na_op(x, y):
try:
result = expressions.evaluate(op, str_rep, x, y,
raise_on_error=True, **eval_kwargs)
except TypeError:
if isinstance(y, (np.ndarray, ABCSeries, pd.Index)):
dtype = np.find_common_type([x.dtype, y.dtype], [])
result = np.empty(x.size, dtype=dtype)
mask = notnull(x) & notnull(y)
result[mask] = op(x[mask], _values_from_object(y[mask]))
elif isinstance(x, np.ndarray):
result = np.empty(len(x), dtype=x.dtype)
mask = notnull(x)
result[mask] = op(x[mask], y)
else:
raise TypeError("{typ} cannot perform the operation "
"{op}".format(typ=type(x).__name__,
op=str_rep))
result, changed = _maybe_upcast_putmask(result, ~mask, np.nan)
result = missing.fill_zeros(result, x, y, name, fill_zeros)
return result
