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| public:user_software:documentation:ndppp [2019-05-06 08:40] – [DDECal] André Offringa | public:user_software:documentation:ndppp [2019-05-16 13:31] – [DDECal] Francesco De Gasperin |
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| | <step>.nchan | int | 1 | Number of channels in each channel block, for which the solution is assumed to be constant. The default is 1, meaning one solution per channel (or in the case of constraints, fitting the constraint over all channels individually). 0 means one solution for the whole channel range. If the total number of channels is not divisable by nchan, some channelblocks will become slightly larger. | | | <step>.nchan | int | 1 | Number of channels in each channel block, for which the solution is assumed to be constant. The default is 1, meaning one solution per channel (or in the case of constraints, fitting the constraint over all channels individually). 0 means one solution for the whole channel range. If the total number of channels is not divisable by nchan, some channelblocks will become slightly larger. | |
| | <step>.coreconstraint | double | 0 | Distance in meters. When unequal to 0, all stations within the given distance from the reference station (0) will be constraint to have the same solution. | | | <step>.coreconstraint | double | 0 | Distance in meters. When unequal to 0, all stations within the given distance from the reference station (0) will be constraint to have the same solution. | |
| | <step>.antennaconstraint | list | [] | A list of lists specifying groups of antennas that are to be constrained to have the same solution. Example: "[[CS002HBA0,CS002HBA1],[CS003HBA0,CS003HBA1]]" will keep the solutions of CS002HBA0 and 1 the same, and the same for CS003. | | | <step>.antennaconstraint | list | [] | A list of lists specifying groups of antennas that are to be constrained to have the same solution. Example: "[ [CS002HBA0,CS002HBA1],[CS003HBA0,CS003HBA1] ]" will keep the solutions of CS002HBA0 and 1 the same, and the same for CS003. | |
| | <step>.smoothnessconstraint | double | 0 | Kernel size in Hz. When unequal to 0, will constrain the solutions to be smooth over frequency by convolving the solutions with a kernel of the given size (bandwidth). The default kernel is a Gaussian kernel, and the kernel size parameter is the 3 sigma point where the kernel is cut off. | | | <step>.smoothnessconstraint | double | 0 | Kernel size in Hz. When unequal to 0, will constrain the solutions to be smooth over frequency by convolving the solutions with a kernel of the given size (bandwidth). The default kernel is a Gaussian kernel, and the kernel size parameter is the 3 sigma point where the kernel is cut off. | |
| | <step>.statfilename | string | "" | File to write the step-sizes to. Form of the file is: "<iterationnr> <normalized-stepsize> <unnormalized-stepsize>", and all solution intervals are concatenated. File is not written when this parameter is empty. | | | <step>.statfilename | string | "" | File to write the step-sizes to. Form of the file is: "<iterationnr> <normalized-stepsize> <unnormalized-stepsize>", and all solution intervals are concatenated. File is not written when this parameter is empty. | |
| | <step>.savefacets | bool | false | Write out each facet as a fits file (named facet<N>.fits). Only useful when useidg=true. | | | <step>.savefacets | bool | false | Write out each facet as a fits file (named facet<N>.fits). Only useful when useidg=true. | |
| | <step>.onlypredict | bool | false | Instead of solving, output the predicted visibilities instead. This is useful for testing, although when doing faceted prediction with IDG, it might be fast for certain cases. | | | <step>.onlypredict | bool | false | Instead of solving, output the predicted visibilities instead. This is useful for testing, although when doing faceted prediction with IDG, it might be fast for certain cases. | |
| | | <step>.applycal.*| | | ApplyCal sub-step, same as in Predict step. One can pass an h5parm with as many directions as set in "directions" and each direction model is corrupted accordingly. | |
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| ==== Predict ==== | ==== Predict ==== |