calwp2 performs similar functions for observations taken with the WF/PC-2 instrument. These corrections include the A/D fixup, removing the global bias level, subtracting bias, preflash, dark, and superpurge frames (after appropriate scaling), and applying the flat field frame. The input data quality file (DQF) is updated with pixels observed to be saturated, and with the DQF of known bad pixels (static mask), and with the DQFs of any images used in the processing sequence. Histograms of the input data, the data following A/D correction, and the output data are generated. The steps performed by this task are specified by setting keywords in the input image header.
Several other tasks are available in the wfpc package to aid in the analysis of calibrated data. Most of these tasks are used for both WF/PC and WF/PC-2 data. Most of these tasks can exclude any or all classes of bad pixels (as identified in the DQF associated with each image) from the calculations, and all tasks either perform operations on all groups by default, or provide a means to switch between groups without exiting the task, as appropriate. These tasks include:
- checkwfpc: Check the correctness of the image header of a WF/PC reference file and its associated data quality mask.
- combine: Combine images using various algorithms and pixel rejection schemes. This task is similar to images.imcombine, but will ignore DQF-flagged pixels and loop through all image groups.
- crrej: Reduce the cosmic rays registered in images of multiple exposures of the same field and combine the images by rejecting very high counts in each pixel stack. This task has more sophisticated options for propagating cosmic ray events to neighboring pixels and doing iterative rejections with several threshold levels.
- dqfpar: A pset for specifying which DQF error flags to use in masking bad pixels. The user may exclude any or all pathologies when using the combine, noisemodel, and wstatistics tasks.
- engextr: Extract information from WF/PC engineering data (i.e., the .x0h and .x0d) files and write it to an STSDAS table.
- metric: Calculate the RA and Dec of points in a WF/PC image while correcting geometric distortions and offset and rotations between the chips.
- noisemodel: Determine noise model parameters from CCD frames. The gain, read noise, and scale noise are used in other tasks as a basis for modelling the noise characteristics of WF/PC data.
- noisepar: Set parameters describing noise model (pset).
- pixcoord: Compute pixel coordinates of stars in WF/PC frames based upon an input list of stellar RA and Dec, and world coordinate system (WCS) information in the image header. This task also fine-tunes the WCS information with an interactive fit of the mapped stellar positions.
- qwmosaic: Produce a quick (i.e., no geometric correction) mosaic of the four groups that comprise the full WF/PC field of view. A more sophisticated mosaic task is available (wmosaic) to correct for the geometric distortion and inter-chip rotations, offsets, and scale differences.
- seam: After the four groups of a WF/PC image are mosaicked (using the task wmosaic) into one image, brightness discontinuities may still show up near the boundaries between the four frames creating a seam effect. This task will essentially airbrush the seams from the image, making it look smoother.
- wfixup: This task will take an input image and its data quality file, check for pixels flagged as bad in the data quality file, and do a simple linear one-dimensional interpolation over the bad pixels. The result looks better when displayed, but may not be improved from a scientific perspective.
- wmosaic: Mosaic the four individual WFPC frames into one image. This task does geometric correction and corrects for rotation, offsets, and scale differences among the chips. The qwmosaic is quicker than wmosaic, but does no corrections.
- wstatistics: Compute and print WF/PC image pixel statistics. This task is similar to images.imstatistics, but it will loop through all image groups and optionally exclude DQF-flagged pixels from the calculation. This task is somewhat outdated and will be replaced by the imgtools.gstatistics task.
There are two 
