Algorithm

This routine detects jumps by looking for outliers in the up-the-ramp signal for each pixel. On output, the GROUPDQ array is updated with the DQ flag “JUMP_DET” to indicate the location of each jump that was found. In addition, any pixels that have non-positive or NaN values in the gain reference file will have DQ flags “NO_GAIN_VALUE” and “DO_NOT_USE” set in the output PIXELDQ array. The SCI array of the input data is not modified.

Jumps can be detected in two different ways. The primary way is the two-point difference method described below. The other way is by selecting only_use_ints as True and if there are enough integrations, then sigma_clip from the astropy.stats package will be used to detect jumps. The sigma_clip method will also be used if the total number of usable groups (number of groups per integration multiplied by the number of integrations) is above a minimum threshold.

The current implementation uses the two-point difference method described in Anderson & Gordon (2011).

Two-Point Difference Method

The two-point difference method is applied to each integration as follows:

  1. Compute the first differences for each pixel (the difference between adjacent groups)

  2. Compute the clipped median (dropping the largest difference) of the first differences for each pixel. If there are only three first difference values (four groups), no clipping is performed when computing the median.

  3. Use the median to estimate the Poisson noise for each group and combine it with the read noise to arrive at an estimate of the total expected noise for each difference.

  4. Compute the “difference ratio” as the difference between the first differences of each group and the median, divided by the expected noise.

  5. If the largest “difference ratio” is greater than the rejection threshold, flag the group corresponding to that ratio as having a jump.

  6. If a jump is found in a given pixel, iterate the above steps with the jump-impacted group excluded, looking for additional lower-level jumps that still exceed the rejection threshold.

  7. Stop iterating on a given pixel when no new jumps are found or only one difference remains.

  8. If there are only two differences (three groups), the smallest one is compared to the larger one and if the larger one is above a threshold, it is flagged as a jump.

  9. If flagging of the 4 neighbors is requested, then the 4 adjacent pixels will have ramp jumps flagged in the same group as the central pixel as long as it has a jump between the min and max requested levels for this option.

  10. If flagging of groups after a ramp jump is requested, then the groups in the requested time since a detected ramp jump will be flagged as ramp jumps if the ramp jump is above the requested threshold. Two thresholds and times are possible for this option.

Note that any ramp groups flagged as SATURATED in the input GROUPDQ array are not used in any of the above calculations and hence will never be marked as containing a jump.