In order to be comprehensive, intuitive, and easy to use, there are two ways to define the crop:
Irrespective of how the crop region is defined, the coordinates to define the crop can be in Image (pixel) or World Coordinate System (WCS) standards. All coordinates are read as floating point numbers (not integers, except for the --section option, see below). By setting the mode in Crop, you define the standard that the given coordinates must be interpreted. Here, the different ways to specify the crop region are discussed within each standard. For the full list options, please see Invoking Crop.
When the crop is defined by its center, the respective (integer) central pixel position will be found internally according to the FITS standard. To have this pixel positioned in the center of the cropped region, the final cropped region will have an add number of pixels (even if you give an even number to --width in image mode).
Furthermore, when the crop is defined as by its center, Crop allows you to only keep crops what don’t have any blank pixels in the vicinity of their center (your primary target). This can be very convenient when your input catalog/coordinates originated from another survey/filter which is not fully covered by your input image, to learn more about this feature, please see the description of the --checkcenter option in Invoking Crop.
In image mode (--mode=img), Crop interprets the pixel coordinates and widths in units of the input data-elements (for example pixels in an image, not world coordinates). In image mode, only one image may be input. The output crop(s) can be defined in multiple ways as listed below.
The center of (possibly multiple) crops are read from a text file. In this mode, the columns identified with the --coordcol option are interpreted as the center of a crop with a width of --width pixels along each dimension. The columns can contain any floating point value. The value to --output option is seen as a directory which will host (the possibly multiple) separate crop files, see Crop output for more. For a tutorial using this feature, please see Hubble visually checks and classifies his catalog.
The center of the crop is given on the command-line with the --center option. The crop width is specified by the --width option along each dimension. The given coordinates and width can be any floating point number.
In Image mode there are two options to define the vertices of a region to crop: --section and --polygon. The former is lower-level (doesn’t accept floating point vertices, and only a rectangular region can be defined), it is also only available in Image mode. Please see Crop section syntax for a full description of this method.
The latter option (--polygon) is a higher-level method to define any convex polygon (with any number of vertices) with floating point values. Please see the description of this option in Invoking Crop for its syntax.
In WCS mode (--mode=wcs), the coordinates and widths are interpreted using the World Coordinate System (WCS, that must accompany the dataset), not pixel coordinates. In WCS mode, Crop accepts multiple datasets as input. When the cropped region (defined by its center or vertices) overlaps with multiple of the input images/tiles, the overlapping regions will be taken from the respective input (they will be stitched when necessary for each output crop).
In this mode, the input images do not necessarily have to be the same size, they just need to have the same orientation and pixel resolution. Currently only orientation along the celestial coordinates is accepted, if your input has a different orientation you can use Warp’s --align option to align the image before cropping it (see Warp).
Each individual input image/tile can even be smaller than the final crop. In any case, any part of any of the input images which overlaps with the desired region will be used in the crop. Note that if there is an overlap in the input images/tiles, the pixels from the last input image read are going to be used for the overlap. Crop will not change pixel values, so it assumes your overlapping tiles were cutout from the same original image. There are multiple ways to define your cropped region as listed below.
Similar to catalog inputs in Image mode (above), except that the values along each dimension are assumed to have the same units as the dataset’s WCS information. For example, the central RA and Dec value for each crop will be read from the first and second calls to the --coordcol option. The width of the cropped box (in units of the WCS, or degrees in RA and Dec mode) must be specified with the --width option.
You can specify the center of only one crop box with the --center
option. If it exists in the input images, it will be cropped similar to the
catalog mode, see above also for
The --polygon option is a high-level method to define any convex polygon (with any number of vertices). Please see the description of this option in Invoking Crop for its syntax.
CAUTION: In WCS mode, the image has to be aligned with the celestial coordinates, such that the first FITS axis is parallel (opposite direction) to the Right Ascension (RA) and the second FITS axis is parallel to the declination. If these conditions aren’t met for an image, Crop will warn you and abort. You can use Warp’s --align option to align the input image with these coordinates, see Warp.
As a summary, if you don’t specify a catalog, you have to define the cropped region manually on the command-line. In any case the mode is mandatory for Crop to be able to interpret the values given as coordinates or widths.