JumpStep

class jwst.jump.JumpStep(name=None, parent=None, config_file=None, _validate_kwds=True, **kws)[source]

Bases: JwstStep

Perform jump detection using two point difference.

Create a Step instance.

Parameters:
namestr

The name of the Step instance. Used in logging messages and in cache filenames. If not provided, one will be generated based on the class name.

parentStep

The parent step of this step. Used to determine a fully-qualified name for this step, and to determine the mode in which to run this step.

config_filestr or pathlib.Path

The path to the config file that this step was initialized with. Use to determine relative path names of other config files.

_validate_kwdsbool

Validate given kws against specs/config.

**kwsdict

Additional parameters to set. These will be set as member variables on the new Step instance.

Attributes Summary

class_alias

reference_file_types

spec

Methods Summary

process(step_input)

Step method to execute step computations.

Attributes Documentation

class_alias = 'jump'
reference_file_types: ClassVar = ['gain', 'readnoise']
spec
rejection_threshold = float(default=4.0,min=0) # CR sigma rejection threshold
three_group_rejection_threshold = float(default=6.0,min=0) # CR sigma rejection threshold
four_group_rejection_threshold = float(default=5.0,min=0) # CR sigma rejection threshold
maximum_cores = string(default='1') # cores for multiprocessing. Can be an integer, 'half', 'quarter', or 'all'
flag_4_neighbors = boolean(default=True) # flag the four perpendicular neighbors of each CR
max_jump_to_flag_neighbors = float(default=1000) # maximum jump sigma that will trigger neighbor flagging
min_jump_to_flag_neighbors = float(default=10) # minimum jump sigma that will trigger neighbor flagging
after_jump_flag_dn1 = float(default=0) # 1st flag groups after jump above DN threshold
after_jump_flag_time1 = float(default=0) # 1st flag groups after jump groups within specified time
after_jump_flag_dn2 = float(default=0) # 2nd flag groups after jump above DN threshold
after_jump_flag_time2 = float(default=0) # 2nd flag groups after jump groups within specified time
expand_large_events = boolean(default=False) # Turns on Snowball detector for NIR detectors
min_sat_area = float(default=1.0) # minimum required area for the central saturation of snowballs
min_jump_area = float(default=5.0) # minimum area to trigger large events processing
expand_factor = float(default=2.0) # The expansion factor for the enclosing circles or ellipses
use_ellipses = boolean(default=False) # deprecated
sat_required_snowball = boolean(default=True) # Require the center of snowballs to be saturated
min_sat_radius_extend = float(default=2.5) # The min radius of the sat core to trigger the extension of the core
sat_expand = integer(default=2) # Number of pixels to add to the radius of the saturated core of snowballs
edge_size = integer(default=25) # Distance from detector edge where a saturated core is not required for snowball detection
mask_snowball_core_next_int = boolean(default=True) # Flag saturated cores of snowballs in the next integration?
snowball_time_masked_next_int = integer(default=4000) # Time in seconds over which saturated cores are flagged in next integration
find_showers = boolean(default=False) # Apply MIRI shower flagging?
max_shower_amplitude = float(default=4) # Maximum MIRI shower amplitude in DN/s
extend_snr_threshold = float(default=1.2) # The SNR minimum for detection of extended showers in MIRI
extend_min_area = integer(default=90) # Min area of emission after convolution for the detection of showers
extend_inner_radius = float(default=1) # Inner radius of the ring_2D_kernel used for convolution
extend_outer_radius = float(default=2.6) # Outer radius of the ring_2D_Kernel used for convolution
extend_ellipse_expand_ratio = float(default=1.1) # Expand the radius of the ellipse fit to the extended emission
time_masked_after_shower = float(default=15) # Seconds to flag as jump after a detected extended emission
min_diffs_single_pass = integer(default=10) # The minimum number of differences needed to skip the iterative flagging of jumps.
max_extended_radius = integer(default=200) # The maximum radius of an extended snowball or shower
minimum_groups = integer(default=3) # The minimum number of groups to perform jump detection using sigma clipping
minimum_sigclip_groups = integer(default=100) # The minimum number of groups to switch to sigma clipping
only_use_ints = boolean(default=True) # In sigclip only compare the same group across ints, if False compare all groups

Methods Documentation

process(step_input)[source]

Step method to execute step computations.

Parameters:
step_inputRampModel

The ramp model input from the previous step.

Returns:
resultRampModel

The ramp model with jump step as COMPLETE and jumps detected or the jump step is SKIPPED.