GNU Astronomy Utilities

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10.3.22 Interpolation (interpolate.h)

During data analysis, it often happens that parts of the data cannot be given a value. For example your image was saturated due to a very bright start and you have to mask that star’s footprint. One other common situation in Gnuastro is when we do processing on tiles (for example to estimate the Sky value and its Standard deviation, see Sky value). Some tiles must not be used for the estimation of the Sky value, for example because they cover a large galaxy. So we need to fill them in with blank values. But ultimately, we need a Sky value for every pixel. This job (assigning a value to blank element(s) based on their nearby neighbors with a value) is known as interpolation.

There are many ways to do interpolation, but (mainly due to lack of time), currently Gnuastro only contains the (median of) nearest-neighbor method. The power of this method of interpolation is its non-parametric nature. The produced values are also always within the range of the known values and strong outliers do not get created. We will hopefully implement other methods too (wrappers around the GNU Scientific Library’s very complete set of functions), but currently the developers are too busy. So if you do have the chance to help your contribution would be very welcome and appreciated.

gal_data_t *
gal_interpolate_close_neighbors (gal_data_t *input, struct gal_tile_two_layer_params *tl, size_t numneighbors, size_t numthreads, int onlyblank, int aslinkedlist)

Interpolate the values in the image using the median value of their numneighbors closest neighbors. If onlyblank is non-zero, then only blank elements will be interpolated and pixels that already have a value will be left untouched. This function is multi-threaded and will run on numthreads threads (see gal_threads_number in Multithreaded programming (threads.h)).

tl is Gnuastro’s two later tessellation structure used to define tiles over an image and is fully described in Tile grid. When tl!=NULL, then it is assumed that the input->array contains one value per tile and interpolation will respect certain tessellation properties, for example to not interpolate over channel borders.

If several datasets have the same set of blank values, you don’t need to call this function multiple times. When aslinkedlist is non-zero, then input will be seen as a List of gal_data_t and for all the same neighbor position checking will be done for all the datasets in the list. Of course, the values for each dataset will be different, so a different value will be written in the each dataset, but the neighbor checking that is the most CPU intensive part will only be done once.

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