# Description¶

This step determines the mean count rate for each pixel by performing a linear fit to the data in the input (jump) file. The fit is done using “ordinary least squares” (the “generalized least squares” is no longer an option). The fit is performed independently for each pixel. There are up to three output files. The primary output file, giving the slope at each pixel, is always produced. If the input exposure contains more than one integration, the resulting slope images from each integration are stored as a data cube in a second output data product. A third, optional output product is also available and is produced only when the step parameter ‘save_opt’ is True (the default is False). The output values will be in units of counts per second. Following a description of the fitting algorithm, these three type of output files are detailed below.

The count rate for each pixel is determined by a linear fit to the cosmic-ray-free ramp intervals for each pixel. CR-free intervals are derived using the 4-D GROUPDQ array of the input data set, under the assumption that the jump step will have already flagged CR’s. Ramp intervals are also terminated where saturation flags are found. Ramp intervals that are noiseless, or have no signal, or contain only 2 reads will initially have fits with variance = 0, preventing their slopes from contributing to the weighted slopes. In these cases, the variance will be recalculated as the poisson noise of the ramp added in quadrature to the pixel-specific read noise, ensuring that all variance values are positive. If the input dataset has only a single group in each integration, the count rate for all unsaturated pixels in that integration will be calculated to be the value of the science data in that group divided by the exposure time. If the input dataset has only two groups per integration, the count rate for all unsaturated pixels in each integration will be calculated from the 2 valid values of the science data. If any input dataset contains ramps saturated in their second read, the count rates for those pixels in that integration will be calculated to be the value of the science data in that group divided by the exposure time. After computing the slopes for all intervals for a given pixel, the final slope is determined as a weighted average from all intervals and is written to a file as the primary output product. In this output product, the 4-D GROUPDQ from all integrations is compressed into 2-D, which is then merged (using a bitwise OR) with the input 2-D PIXELDQ to create the output DQ array. The 3-D VAR_POISSON and VAR_RNOISE arrays from all integrations are averaged into corresponding 2-D output arrays. If the ramp fitting step is run by itself, the output file name will have the suffix ‘_RampFit’ or the suffix ‘_RampFitStep’; if the ramp fitting step is run as part of the calwebb_detector1 pipeline, the final output file name will have the suffix ‘_rate’. In either case, the user can override this name by specifying an output file name.

If the input exposure contains more than one integration, the resulting slope images from each integration are stored as a data cube in a second output data product. Each plane of the 3-D SCI, ERR, DQ, VAR_POISSON, and VAR_RNOISE arrays in this product is the result for a given integration. In this output product, the GROUPDQ data for a given integration is compressed into 2-D, which is then merged with the input 2-D PIXELDQ to create the output DQ array for each integration. The 3-D VAR_POISSON and VAR_RNOISE from an integration are calcuated by averaging over the fit segments in the corresponding 4-D arrays. By default, the name of this output product is based on the name of the input file and will have the suffix ‘_rateints’; the user can override this name by specifying a name using the parameter int_name.

A third, optional output product is also available and is produced only when the step parameter ‘save_opt’ is True (the default is False). This optional product contains 4-D arrays called SLOPE, SIGSLOPE, YINT, SIGYINT, WEIGHTS, VAR_POISSON, and VAR_RNOISE which contain the slopes, uncertainties in the slopes, y-intercept, uncertainty in the y-intercept, fitting weights, the variance of the slope due to poisson noise only, and the variance of the slope due to read noise only for each ramp interval of each pixel. The y-intercept refers to the result of the fit at an exposure time of zero. This product also contains a 3-D array called PEDESTAL, which gives the signal at zero exposure time for each pixel, and the 4-D CRMAG array, which contains the magnitude of each read that was flagged as having a CR hit. By default, the name of this output file is based on the name of the input file and will have the suffix ‘_fitopt’; the user can override this name by specifying a name using the parameter opt_name. In this optional output product, the pedestal array is calculated for each integration by extrapolating the final slope (the weighted average of the slopes of all of ramp segments in the integration) for each pixel from its value at the first sample to an exposure time of zero. Any pixel that is saturated on the first read is given a pedestal value of 0. Before compression, the cosmic ray magnitude array is equivalent to the input SCI array but with the only nonzero values being those whose pixel locations are flagged in the input GROUPDQ as cosmic ray hits. The array is compressed, removing all reads in which all the values are 0 for pixels having at least one read with a non-zero magnitude. The order of the cosmic rays within the ramp is preserved.

The fitting algorithm does an ‘optimal’ linear fit, which is the weighting used by Fixsen et al, PASP,112, 1350. (‘unweighted’ in which pixels are equally weighted, is no longer a weighting option.) Pixels are processed simultaneously in blocks using the array-based functionality of numpy. The size of the block depends on the image size and the number of groups.

Upon successful completion of this step, the status keyword S_RAMP will be set to COMPLETE.

The MIRI last frame correction step flags all pixels in the last group of data in each integration of a MIRI exposure, so that those data do not get used in either the jump detection or ramp fitting steps. As a result, the ramp fitting step does not include any data from the last group of an integration in its calculations; for MIRI exposures that have original values of 2 and 3 groups per integration, ramp fitting processing proceeds using only the first 1 and 2 groups, respectively, using the calculations described above. For MIRI exposures that originally have only 1 group per integration, that group will NOT be flagged by the last frame correction step, so that there will always be at least 1 group of data to work with in subsequent steps. Hence the special ramp fitting processing that’s applied to exposures that have only 1 group will be applied to MIRI exposures that originally have 1 or 2 groups.

# Step Arguments¶

The ramp fitting step has three optional arguments that can be set by the user:

`--save_opt`

: A True/False value that specifies whether to write optional output information.`--opt_name`

: A string that can be used to override the default name for the optional output information.`--int_name`

: A string that can be used to override the default name for the integration-by-integration slopes, for the case that the input file contains more than one integration.