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?i 6 R t ^RIHt RsR t ! R R]4 tR# )a Read FITS files.
Backend Library: `Astropy `_
.. note::
To use this plugin you have to install its backend::
pip install imageio[fits]
Flexible Image Transport System (FITS) is an open standard defining a
digital file format useful for storage, transmission and processing of
scientific and other images. FITS is the most commonly used digital
file format in astronomy.
Parameters
----------
cache : bool
If the file name is a URL, `~astropy.utils.data.download_file` is used
to open the file. This specifies whether or not to save the file
locally in Astropy's download cache (default: `True`).
uint : bool
Interpret signed integer data where ``BZERO`` is the
central value and ``BSCALE == 1`` as unsigned integer
data. For example, ``int16`` data with ``BZERO = 32768``
and ``BSCALE = 1`` would be treated as ``uint16`` data.
Note, for backward compatibility, the kwarg **uint16** may
be used instead. The kwarg was renamed when support was
added for integers of any size.
ignore_missing_end : bool
Do not issue an exception when opening a file that is
missing an ``END`` card in the last header.
checksum : bool or str
If `True`, verifies that both ``DATASUM`` and
``CHECKSUM`` card values (when present in the HDU header)
match the header and data of all HDU's in the file. Updates to a
file that already has a checksum will preserve and update the
existing checksums unless this argument is given a value of
'remove', in which case the CHECKSUM and DATASUM values are not
checked, and are removed when saving changes to the file.
disable_image_compression : bool, optional
If `True`, treats compressed image HDU's like normal
binary table HDU's.
do_not_scale_image_data : bool
If `True`, image data is not scaled using BSCALE/BZERO values
when read.
ignore_blank : bool
If `True`, the BLANK keyword is ignored if present.
scale_back : bool
If `True`, when saving changes to a file that contained scaled
image data, restore the data to the original type and reapply the
original BSCALE/BZERO values. This could lead to loss of accuracy
if scaling back to integer values after performing floating point
operations on the data.
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