The Named Arrays Page

The Named Arrays page will contain a list of arrays saved in the Sitka session, and will look like

_images/sitka_arrayspage.png

Each of the named Array can be highlighted, or multiple arrays can be selected at a time. The Plot Current button will show the highlighted array (as a simple plot or image display).

Note that this list may contain arrays named _imgdat, _ydat, and _tabledat. These arrays are automatically written as the last data used by the Image Display page, the XY Display page and the Table Display page.

You can use Delete Selected Arrays to remove selected named arrays. You can use the Export Selected Arrays to HDF5 to export selected arrays to a simple HDF5 file (and so easily read into later Sitka sessions.

The arrays selected will be written to a new HDF5 file, and all arrays will be put into a Group name “sitka_arrays”. If you read in this file in a later session and select thie “sitka_arrays’ Group, the Import Named Arrays” at the upper right of the main Sitka window will be enables. Hitting that button will import all of these named arrays into the Named Arrays panel. This allows you to extract data from complex datasets and easily retrieve them.

At the bottom, you can also create a new array directly. Here you give a name (which must follow the valid conventions for a Python variable: A letter or underscore followed by any number of letters, numbers, or underscore), and an mathematical expression to evaluate for the array value. This uses an asteval Interpreter, and so uses Python conventions, the built-in math functions from the math module and numpy, and also contains the other named arrays. Example expressions would include

  • ‘0.01 * arange(4096)’, maybe to set an X-axis for XYPlots

  • ‘linspace(-2, 2, 501)’, as another form to set an X-axis for XYPlots

  • ‘image1 - image2’ to take the difference of two images.

  • ‘sin(ydat/10)’ you can use any trig functions from numpy.

  • ‘gradient(ydat)/gradient(xdat)’ to take the derivative ‘dy/dx’.