These Python modules provide a broad range of fundamental infrastructure for analyzing astronomical data. They are easy to use and implement, and support various operations, such as data processing, visualization, and manipulation, making them essential for astronomers using Python.
As a comprehensive library of Python routines and C extensions, stsci_python provides an excellent infrastructure for analyzing astronomical data. It includes a range of powerful tools that can help users work more efficiently with their data, such as PyRAF, MultiDrizzle, PyFITS, and Numdisplay.
PyRAF is particularly noteworthy, as it enables users to run IRAF tasks without having to use the IRAF CL. Meanwhile, MultiDrizzle is a task designed specifically for combining dithered STScI images, which can be a challenging process without the right tools.
PyFITS is another useful module, which allows users to read FITS images and tables into numpy or numarray objects, as well as manipulate FITS headers. This can be a huge timesaver for users who need to work with large volumes of data.
Finally, Numdisplay is an incredibly powerful tool for visualizing numpy array objects using popular image display tools like ds9 and ximtool. This makes it easy to explore complex data sets and identify patterns or outliers that might be missed using other visualization methods.
Overall, stsci_python is an excellent tool for anyone who needs to analyze astronomical data. Detailed installation instructions can be found on the library's website, making it easy to get started and take full advantage of all its features.
PyRAF is particularly noteworthy, as it enables users to run IRAF tasks without having to use the IRAF CL. Meanwhile, MultiDrizzle is a task designed specifically for combining dithered STScI images, which can be a challenging process without the right tools.
PyFITS is another useful module, which allows users to read FITS images and tables into numpy or numarray objects, as well as manipulate FITS headers. This can be a huge timesaver for users who need to work with large volumes of data.
Finally, Numdisplay is an incredibly powerful tool for visualizing numpy array objects using popular image display tools like ds9 and ximtool. This makes it easy to explore complex data sets and identify patterns or outliers that might be missed using other visualization methods.
Overall, stsci_python is an excellent tool for anyone who needs to analyze astronomical data. Detailed installation instructions can be found on the library's website, making it easy to get started and take full advantage of all its features.
What's New
Version 2.7: N/A