Utility functions for handling bit masks and mask arrays.

It is common to use bit fields - e.g., integer variables whose individual bits represent some attributes - to characterize the state of data. For example, HST uses arrays of bit fields to characterize data quality (DQ) of HST images, see, e.g., DQ field values for WFPC2 image data and WFC3 image data. As one can see, the meaning assigned to various bit flags in for the two instruments is generally different.

Bit fields can be thought of as tightly packed collections of bit flags. Using masking we can “inspect” the status of individual bits.

One common operation performed on bit field arrays is their conversion to boolean masks, for example by simply assigning boolean True (in the boolean mask) to those elements that correspond to non-zero-valued bit fields (bit fields with at least one bit set to 1) or, oftentimes, by assigning True to elements whose corresponding bit fields have only specific fields set (to 1). This more sophisticated analysis of bit fields can be accomplished using bit masks and the aforementioned masking operation.

The bitmask module provides two functions that facilitate conversion of bit field arrays (i.e., DQ arrays) to boolean masks: bitfield_to_boolean_mask to convert an input bit fields array to a boolean mask using an input bit mask (or list of individual bit flags) and interpret_bit_flags to create bit mask from input list of individual bit flags.

Creating boolean masks


bitfield_to_boolean_mask by default assumes that all input bit fields that have at least one bit turned “ON” correspond to “bad” data (i.e., pixels) and converts them to boolean True in the output boolean mask (otherwise output boolean mask values are set to False).

Often, for specific algorithms and situations, some bit flags are OK and can be ignored. bitfield_to_boolean_mask accepts lists of bit flags that by default must be ignored in the input bit fields when creating boolean masks.

Fundamentally, by default, bitfield_to_boolean_mask performs the following operation:

(1)    boolean_mask = (bitfield & ~bit_mask) != 0

(here & is bitwise and and ~ is the bitwise not operations). In the previous formula, bit_mask is a bit mask created from individual bit flags that need to be ignored in the bit field.

Table 1: Examples of Boolean Mask Computations (default parameters and 8-bit data type)
Bit Field Bit Mask ~(Bit Mask) Bit Field & ~(Bit Mask) Boolean Mask
11011001 (217) 01010000 (80) 10101111 (175) 10001001 (137) True
11011001 (217) 10101111 (175) 01010000 (80) 01010000 (80) True
00001001 (9) 01001001 (73) 10110110 (182) 00000000 (0) False
00001001 (9) 00000000 (0) 11111111 (255) 00001001 (9) True
00001001 (9) 11111111 (255) 00000000 (0) 00000000 (0) False

Specifying bit flags

bitfield_to_boolean_mask accepts either an integer bit mask or lists of bit flags. Lists of bit flags will be combined into a bit mask and can be provided either as a Python list of integer bit flag values or as a comma-separated (or +-separated) list of integer bit flag values. Consider the bit mask from the first example in Table 1. In this case ignore_flags can be set either to:

  • an integer value bit mask 80, or
  • a Python list indicating individual non-zero bit flag values: [16, 64], or
  • a string of comma-separated bit flag values: '16,64', or
  • a string of +-separated bit flag values: '16+64'

For example,

>>> from astropy.nddata import bitmask
>>> import numpy as np
>>> bitmask.bitfield_to_boolean_mask(217, ignore_flags=80)
>>> bitmask.bitfield_to_boolean_mask(217, ignore_flags='16,64')
>>> bitmask.bitfield_to_boolean_mask(217, ignore_flags=[16, 64])
>>> bitmask.bitfield_to_boolean_mask(9, ignore_flags=[1, 8, 64])
>>> bitmask.bitfield_to_boolean_mask([9, 10, 73, 217], ignore_flags='1,8,64')
array([False,  True, False,  True]...)

It is also possible to specify the type of the output mask:

>>> bitmask.bitfield_to_boolean_mask([9, 10, 73, 217], ignore_flags='1,8,64', dtype=np.uint8)
array([0, 1, 0, 1], dtype=uint8)

Modifying the Formula for Creating Boolean Masks

bitfield_to_boolean_mask provides several parameters that can be used to modify the formula used to create boolean masks.

Inverting Bit Mask

Sometimes it is more convenient to be able to specify those bit flags that must be considered when creating the boolean mask and all other flags should be ignored. In bitfield_to_boolean_mask this can be accomplished by setting parameter flip_bits to True. This effectively modifies equation (1) to:

(2)    boolean_mask = (bitfield & bit_mask) != 0

So, instead of

>>> bitmask.bitfield_to_boolean_mask([9, 10, 73, 217], ignore_flags=[1, 8, 64])
array([False,  True, False,  True]...)

one can obtain the same result as

>>> bitmask.bitfield_to_boolean_mask(
...     [9, 10, 73, 217], ignore_flags=[2, 4, 16, 32, 128], flip_bits=True
... )
array([False,  True, False,  True]...)

Note however, when ignore_flags is a comma-separated list of bit flag values, flip_bits cannot be set to neither True or False. Instead, to flip bits of the bit mask formed from a string list of comma-separated bit flag values, one can prepend a single ~ to the list:

>>> bitmask.bitfield_to_boolean_mask([9, 10, 73, 217], ignore_flags='~2+4+16+32+128')
array([False,  True, False,  True]...)

Inverting Boolean Mask

Other times, it may be more convenient to obtain an inverted mask in which flagged data are converted to False instead of True:

(3)    boolean_mask = (bitfield & ~bit_mask) == 0

This can be accomplished by changing good_mask_value parameter from its default value (False) to True. For example,

>>> bitmask.bitfield_to_boolean_mask([9, 10, 73, 217], ignore_flags=[1, 8, 64],
...                                  good_mask_value=True)
array([ True, False,  True, False]...)