mask_databounds¶
- astroimtools.utils.mask_databounds(data, mask=None, lower_bound=None, upper_bound=None, value=None, mask_invalid=True)[source]¶
Create or update a mask by masking data values that are below a lower bound, above an upper bound, equal to particular value, or are invalid (e.g. np.nan or np.inf).
- Parameters:
- data
ndarray
The data array.
- maskbool
ndarray
, optional A boolean mask array with the same shape as
data
.- lower_boundfloat, optional
The value of the lower bound. Data values lower than
lower_bound
will be masked.- upper_boundfloat, optional
The value of the upper bound. Data values greater than
upper_bound
will be masked.- valuefloat, optional
A data value (e.g.,
0.0
) to mask.- mask_invalidbool, optional
If
True
(the default), then any unmasked invalid values (e.g. NaN, inf) will be masked.
- data
- Returns:
- maskbool
ndarray
The resulting boolean mask array with the same shape as
data
.
- maskbool
Examples
>>> from astroimtools import mask_databounds >>> data = np.arange(7) >>> print(data) [0 1 2 3 4 5 6] >>> mask_databounds(data, lower_bound=2, upper_bound=5, value=3) array([ True, True, False, True, False, False, True]...)