def rebin(self,
new_shape=None,
scale=None,
crop=False,
out=None,
rechunk=True):
factors = self._validate_rebin_args_and_get_factors(
new_shape=new_shape, scale=scale)
if _requires_linear_rebin(arr=self.data, scale=factors):
if new_shape:
raise NotImplementedError(
"Lazy rebin requires that the new shape is a divisor "
"of the original signal shape e.g. if original shape "
"(10| 6), new_shape=(5| 3) is valid, (3 | 4) is not.")
else:
raise NotImplementedError(
"Lazy rebin requires scale to be integer and divisor of the "
"original signal shape")
axis = {ax.index_in_array: ax
for ax in self.axes_manager._axes}[factors.argmax()]
self._make_lazy(axis=axis, rechunk=rechunk)
return super().rebin(new_shape=new_shape,
scale=scale,
crop=crop,
out=out)
def rebin(self, new_shape=None, scale=None,
crop=False, out=None, rechunk=True):
factors = self._validate_rebin_args_and_get_factors(
new_shape=new_shape,
scale=scale)
if _requires_linear_rebin(arr=self.data, scale=factors):
if new_shape:
raise NotImplementedError(
"Lazy rebin requires that the new shape is a divisor "
"of the original signal shape e.g. if original shape "
"(10| 6), new_shape=(5| 3) is valid, (3 | 4) is not.")
else:
raise NotImplementedError(
"Lazy rebin requires scale to be integer and divisor of the "
"original signal shape")
axis = {ax.index_in_array: ax
for ax in self.axes_manager._axes}[factors.argmax()]
self._make_lazy(axis=axis, rechunk=rechunk)
return super().rebin(new_shape=new_shape,
scale=scale, crop=crop, out=out)