Aiapy

Latest version: v0.9.1

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0.3.0

==================

Features
--------

- Added a function (``aiapy.calibrate.normalize_exposure``) to normalize an image by its exposure time. (`78 <https://gitlab.com/LMSAL_HUB/aia_hub/aiapy/-/merge_requests/78>`__)
- :func:`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 <https://gitlab.com/LMSAL_HUB/aia_hub/aiapy/-/merge_requests/80>`__)
- Citation information for `aiapy` is now available from ``aiapy.__citation__``. (`82 <https://gitlab.com/LMSAL_HUB/aia_hub/aiapy/-/merge_requests/82>`__)
- The pointing table can now be passed in as a keyword argument to :func:`aiapy.calibrate.update_pointing`.
Added a :func:`aiapy.calibrate.util.get_pointing_table` to retrieve the 3-hour pointing table from JSOC over a given time interval. (`84 <https://gitlab.com/LMSAL_HUB/aia_hub/aiapy/-/merge_requests/84>`__)

Bug Fixes
---------

- The ``CROTA2`` keyword update in :func:`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 <https://gitlab.com/LMSAL_HUB/aia_hub/aiapy/-/merge_requests/84>`__)

0.2.0

==================

Features
--------

- 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

0.1.0

===================

Features
--------

- 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)

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