- class jwst.jump.JumpStep(name=None, parent=None, config_file=None, _validate_kwds=True, **kws)¶
JumpStep: Performs CR/jump detection on each ramp integration within an exposure. The 2-point difference method is applied.
name (str, optional) – 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.
parent (Step instance, optional) – 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_file (str path, optional) – The path to the config file that this step was initialized with. Use to determine relative path names of other config files.
**kws (dict) – Additional parameters to set. These will be set as member variables on the new Step instance.
This is where real work happens.
- class_alias = 'jump'¶
- reference_file_types = ['gain', 'readnoise']¶
- spec = "\n rejection_threshold = float(default=4.0,min=0) # CR sigma rejection threshold\n three_group_rejection_threshold = float(default=6.0,min=0) # CR sigma rejection threshold\n four_group_rejection_threshold = float(default=5.0,min=0) # CR sigma rejection threshold\n maximum_cores = option('none', 'quarter', 'half', 'all', default='none') # max number of processes to create\n flag_4_neighbors = boolean(default=True) # flag the four perpendicular neighbors of each CR\n max_jump_to_flag_neighbors = float(default=1000) # maximum jump sigma that will trigger neighbor flagging\n min_jump_to_flag_neighbors = float(default=10) # minimum jump sigma that will trigger neighbor flagging\n after_jump_flag_dn1 = float(default=0) # 1st flag groups after jump above DN threshold\n after_jump_flag_time1 = float(default=0) # 1st flag groups after jump groups within specified time\n after_jump_flag_dn2 = float(default=0) # 2nd flag groups after jump above DN threshold\n after_jump_flag_time2 = float(default=0) # 2nd flag groups after jump groups within specified time\n min_sat_area = float(default=1.0) # minimum required area for the central saturation of snowballs\n min_jump_area = float(default=5.0) # minimum area to trigger large events processing\n expand_factor = float(default=2.0) # The expansion factor for the enclosing circles or ellipses\n use_ellipses = boolean(default=False) # Use an enclosing ellipse rather than a circle for MIRI showers\n sat_required_snowball = boolean(default=True) # Require the center of snowballs to be saturated\n expand_large_events = boolean(default=False) # must be True to trigger snowball and shower flagging\n "¶
This is where real work happens. Every Step subclass has to override this method. The default behaviour is to raise a NotImplementedError exception.