v0.3.1

aiapy 0.3.1 (2020-11-15)

This release is to coincide with the publication of the aiapy JOSS paper

Features

• aiapy.calibrate.register now raises a
  warning if the level number is missing or is greater than 1.
  (#94)

v0.3.0

aiapy v0.3.0 (2020-10-06)

v0.3.0 of aiapy provides a number of new features and bugfixes.

Features

• Added a function (~aiapy.calibrate.normalize_exposure) to
  normalize an image by its exposure time.
  (#78)
• ~aiapy.calibrate.degradation can now accept ~astropy.time.Time objects with length
  greater than 1. This makes it easier to compute the channel
  degradation over long intervals.
  (#80)
• Citation information for aiapy is now
  available from ~aiapy.__citation__.
  (#82)
• The pointing table can now be passsed in as a keyword argument to
  ~aiapy.calibrate.update_pointing. Added a
  ~aiapy.calibrate.util.get_pointing_table to retrieve the 3-hour
  pointing table from JSOC over a given time interval.
  (#84)

Bug Fixes

• The CROTA2 keyword update in
  ~aiapy.calibrate.update_pointing now includes the value of SAT_ROT from the FITS header. Previously,
  the keyword was only being updated with INSTROT.
  (#84)

v0.2.0

v0.2.0 of aiapy includes the following features and bug fixes

• functionality for respiking level 1 images and fetching spike data from JSOC
• updated calibration data now fetched from JSOC to account for instrument degradation
• compatibility fix with sunpy > 2.0.0 which previously caused level 1.5 maps to expand by several pixels
• functionality for fetching the location of SDO in time

aiapy v0.1.0

This is the first release of the aiapy package, v0.1.0

v0.1.0 includes the following capabilities:

• update pointing keywords in the header using the 3-hour pointing values from the JSOC
• correct Heliographic Stonyhurst observer location
• register images by removing the roll angle, centering the image, and scaling to a common resolution (i.e. "aia_prep")
• calculate wavelength response functions for all channels, including time-dependent effects
• account for channel degradation in image correction
• compute the point spread function and deconvolve an image with the point spread function (with optional GPU acceleration)