The operators in this section take a single dataset as input, and will return the desired statistic as a single value.
minvalue
Minimum value in the first popped operand, so “a.fits minvalue
” will push the minimum pixel value in this image onto the stack.
When this operator acts on a single image, the output (operand that is put back on the stack) will no longer be an image, but a number.
The output of this operand is in the same type as the input.
This operator is mainly intended for multi-element datasets (for example, images or data cubes), if the popped operand is a number, it will just return it without any change.
Note that when the final remaining/output operand is a single number, it is printed onto the standard output. For example, with the command below the minimum pixel value in image.fits will be printed in the terminal:
$ astarithmetic image.fits minvalue
However, the output above also includes a lot of extra information that are not relevant in this context. If you just want the final number, run Arithmetic in quiet mode:
$ astarithmetic image.fits minvalue -q
Also see the description of sqrt for other example usages of this operator.
maxvalue
Maximum value of first operand in the same type, similar to minvalue
, see the description there for more.
For example
$ astarithmetic image.fits maxvalue -q
numbervalue
Number of non-blank elements in first operand in the uint64
type (since it is always a positive integer, see Numeric data types).
Its usage is similar to minvalue
, for example
$ astarithmetic image.fits numbervalue -q
sumvalue
Sum of non-blank elements in first operand in the float32
type.
Its usage is similar to minvalue
, for example
$ astarithmetic image.fits sumvalue -q
meanvalue
Mean value of non-blank elements in first operand in the float32
type.
Its usage is similar to minvalue
, for example
$ astarithmetic image.fits meanvalue -q
stdvalue
Standard deviation of non-blank elements in first operand in the float32
type.
Its usage is similar to minvalue
, for example
$ astarithmetic image.fits stdvalue -q
medianvalue
Median of non-blank elements in first operand with the same type.
Its usage is similar to minvalue
, for example
$ astarithmetic image.fits medianvalue -q
unique
Remove all duplicate (and blank) elements from the first popped operand. The unique elements of the dataset will be stored in a single-dimensional dataset.
Recall that by default, single-dimensional datasets are stored as a table column in the output. But you can use --onedasimage or --onedonstdout to respectively store them as a single-dimensional FITS array/image, or to print them on the standard output.
Although you can use this operator on the floating point dataset, due to floating-point errors it may give non-reasonable values: because the tenth digit of the decimal point is also considered although it may be statistically meaningless, see Numeric data types. It is therefore better/recommended to use it on the integer dataset like the labeled images of Segment output where each pixel has the integer label of the object/clump it is associated with. For example, let’s assume you have cropped a region of a larger labeled image and want to find the labels/objects that are within the crop. With this operator, this job is trivial:
$ astarithmetic seg-crop.fits unique
noblank
Remove all blank elements from the first popped operand. Since the blank pixels are being removed, the output dataset will always be single-dimensional, independent of the dimensionality of the input.
Recall that by default, single-dimensional datasets are stored as a table column in the output. But you can use --onedasimage or --onedonstdout to respectively store them as a single-dimensional FITS array/image, or to print them on the standard output.
For example, with the command below, the non-blank pixel values of cropped.fits are printed on the command-line (the --quiet option is used to remove the extra information that Arithmetic prints as it reads the inputs, its version and its running time).
$ astarithmetic cropped.fits noblank --onedonstdout --quiet
GNU Astronomy Utilities 0.20 manual, April 2023.