Input and Output Operations and Extension Manipulation - MEF
AstroData is not intended to exclusively support Multi-Extension FITS (MEF)
files. However, given FITS’ unflagging popularity as an astronomical data format,
the base AstroData object supports FITS and MEF files without any additional
effort by a user or programmer.
Note
For more information about FITS support and extending AstroData to
support other file formats, see AstroData and Derivatives.
Open and access existing dataset
Read in the dataset
The file on disk is loaded into the AstroData class associated with the
instrument the data is from. This association is done automatically based on
header content.
>>> import astrodata
>>> ad = astrodata.open(EXAMPLE_FILE)
>>> type(ad)
<class 'gemini_instruments.gmos.adclass.AstroDataGmos'>
ad has loaded in the file’s header and parsed the keys present. Header access is done
through the .hdr attribute.
>>> ad.hdr['CCDSEC']
['[1:512,1:4224]', '[513:1024,1:4224]', '[1025:1536,1:4224]', '[1537:2048,1:4224]']
With descriptors:
>>> ad.array_section(pretty=True)
['[1:512,1:4224]', '[513:1024,1:4224]', '[1025:1536,1:4224]', '[1537:2048,1:4224]']
The original path and filename are also stored. If you were to write
the AstroData object to disk without specifying anything, path and
file name would be set to None.
>>> ad.path
'../playdata/N20170609S0154.fits'
>>> ad.filename
'N20170609S0154.fits'
Accessing the content of a MEF file
AstroData uses NDData as the core of its structure. Each FITS extension
becomes a NDAstroData object, subclassed from NDData, and is added to
a list representing all extensions in the file.
Note
For details on the AstroData object, please refer to
The AstroData Object.
Pixel data
To access pixel data, the list index and the .data attribute are used. That
returns a numpy.ndarray. The list of NDAstroData is zero-indexed.
Extension number 1 in a MEF is index 0 in an |AstroData| object.
>>> ad = astrodata.open('../playdata/N20170609S0154_varAdded.fits')
>>> data = ad[0].data
>>> type(data)
<class 'numpy.ndarray'>
>>> data.shape
(2112, 256)
Note
This implementation ignores the fact that the first extension in a MEF
file is the Primary Header Unit (PHU). The PHU is accessibly through the
.phu attribute of the AstroData object, and indexing with [i]
notation will only access the extensions.
Note
Remember that in a ndarray the ‘y-axis’ of the image is
accessed through the first number.
The variance and data quality planes, the VAR and DQ planes in Gemini
MEF files, are represented by the .variance and .mask attributes,
respectively. They are not their own “extension”, they don’t have their own
index in the list, unlike in a MEF. They are attached to the pixel data,
packaged together by the NDAstroData object. They are represented as
numpy.ndarray just like the pixel data
>>> var = ad[0].variance
>>> dq = ad[0].mask
Tables
Tables in the MEF file will also be loaded into the AstroData object. If a table
is associated with a specific science extension through the EXTVER header keyword, that
table will be packaged within the same AstroData extension as the pixel data
and accessible like an attribute. The AstroData “extension” is the
NDAstroData object plus any table or other pixel array associated with the
image data. If the table is not associated with a specific extension and
applies globally, it will be added to the AstroData object as a global
addition. No indexing will be required to access it. In the example below, one
OBJCAT is associated with each extension, while the REFCAT has a global
scope
>>> ad.info()
Filename: ../playdata/N20170609S0154_varAdded.fits
Tags: ACQUISITION GEMINI GMOS IMAGE NORTH OVERSCAN_SUBTRACTED OVERSCAN_TRIMMED
PREPARED SIDEREAL
Pixels Extensions
Index Content Type Dimensions Format
[ 0] science NDAstroData (2112, 256) float32
.variance ndarray (2112, 256) float32
.mask ndarray (2112, 256) uint16
.OBJCAT Table (6, 43) n/a
.OBJMASK ndarray (2112, 256) uint8
[ 1] science NDAstroData (2112, 256) float32
.variance ndarray (2112, 256) float32
.mask ndarray (2112, 256) uint16
.OBJCAT Table (8, 43) n/a
.OBJMASK ndarray (2112, 256) uint8
[ 2] science NDAstroData (2112, 256) float32
.variance ndarray (2112, 256) float32
.mask ndarray (2112, 256) uint16
.OBJCAT Table (7, 43) n/a
.OBJMASK ndarray (2112, 256) uint8
[ 3] science NDAstroData (2112, 256) float32
.variance ndarray (2112, 256) float32
.mask ndarray (2112, 256) uint16
.OBJCAT Table (5, 43) n/a
.OBJMASK ndarray (2112, 256) uint8
Other Extensions
Type Dimensions
.REFCAT Table (245, 16)
The tables are stored internally as astropy.table.Table objects.
>>> ad[0].OBJCAT
<Table length=6>
NUMBER X_IMAGE Y_IMAGE ... REF_MAG_ERR PROFILE_FWHM PROFILE_EE50
int32 float32 float32 ... float32 float32 float32
------ ------- ------- ... ----------- ------------ ------------
1 283.461 55.4393 ... 0.16895 -999.0 -999.0
...
>>> type(ad[0].OBJCAT)
<class 'astropy.table.table.Table'>
>>> refcat = ad.REFCAT
>>> type(refcat)
<class 'astropy.table.table.Table'>
Note
Tables are accessed through attribute notation. However, if a conflicting
attribute exists for a given AstroData or NDData object, a
AttributeError will be raised to avoid confusion.
Headers
Headers are stored in the NDAstroData .meta attribute as
astropy.io.fits.Header objects, which implements a dict-like
object. Headers associated with extensions are stored with the corresponding
NDAstroData object. The MEF Primary Header Unit (PHU) is stored as an
attribute in the AstroData object. When slicing an AstroData object or
accessing an index, the PHU will be included in the new sliced object. The
slice of an AstroData object is an AstroData object. Headers can be
accessed directly, or for some predefined concepts, the use of Descriptors is
preferred. More detailed information on Headers is covered in the section
Metadata and Headers.
Using Descriptors
>>> ad = astrodata.open('../playdata/N20170609S0154.fits')
>>> ad.filter_name()
'open1-6&g_G0301'
>>> ad.filter_name(pretty=True)
'g'
Using direct header access
>>> ad.phu['FILTER1']
'open1-6'
>>> ad.phu['FILTER2']
'g_G0301'
Accessing the extension headers
>>> ad.hdr['CCDSEC']
['[1:512,1:4224]', '[513:1024,1:4224]', '[1025:1536,1:4224]', '[1537:2048,1:4224]']
>>> ad[0].hdr['CCDSEC']
'[1:512,1:4224]'
With descriptors:
>>> ad.array_section(pretty=True)
['[1:512,1:4224]', '[513:1024,1:4224]', '[1025:1536,1:4224]', '[1537:2048,1:4224]']
Modify Existing MEF Files
Appending an extension
Extensions can be appended to an AstroData objects using the
append() method.
Here is an example appending a whole AstroData extension, with pixel data,
variance, mask and tables. While these are treated as separate extensions in
the MEF file, they are all packaged together in the AstroData object.
>>> ad = astrodata.open('../playdata/N20170609S0154.fits')
>>> advar = astrodata.open('../playdata/N20170609S0154_varAdded.fits')
>>> ad.info()
Filename: ../playdata/N20170609S0154.fits
Tags: ACQUISITION GEMINI GMOS IMAGE NORTH RAW SIDEREAL UNPREPARED
Pixels Extensions
Index Content Type Dimensions Format
[ 0] science NDAstroData (2112, 288) uint16
[ 1] science NDAstroData (2112, 288) uint16
[ 2] science NDAstroData (2112, 288) uint16
[ 3] science NDAstroData (2112, 288) uint16
>>> ad.append(advar[3])
>>> ad.info()
Filename: ../playdata/N20170609S0154.fits
Tags: ACQUISITION GEMINI GMOS IMAGE NORTH RAW SIDEREAL UNPREPARED
Pixels Extensions
Index Content Type Dimensions Format
[ 0] science NDAstroData (2112, 288) uint16
[ 1] science NDAstroData (2112, 288) uint16
[ 2] science NDAstroData (2112, 288) uint16
[ 3] science NDAstroData (2112, 288) uint16
[ 4] science NDAstroData (2112, 256) float32
.variance ndarray (2112, 256) float32
.mask ndarray (2112, 256) int16
.OBJCAT Table (5, 43) n/a
.OBJMASK ndarray (2112, 256) uint8
>>> ad[4].hdr['EXTVER']
4
>>> advar[3].hdr['EXTVER']
4
As you can see above, the fourth extension of advar, along with everything
it contains was appended at the end of the first AstroData object. However,
note that, because the EXTVER of the extension in advar was 4, there are
now two extensions in ad with this EXTVER. This is not a problem because
EXTVER is not used by AstroData (it uses the index instead) and it is handled
only when the file is written to disk.
In this next example, we are appending only the pixel data, leaving behind the other associated data. One can attach the headers too, like we do here.
>>> ad = astrodata.open('../playdata/N20170609S0154.fits')
>>> advar = astrodata.open('../playdata/N20170609S0154_varAdded.fits')
>>> ad.append(advar[3].data, header=advar[3].hdr)
>>> ad.info()
Filename: ../playdata/N20170609S0154.fits
Tags: ACQUISITION GEMINI GMOS IMAGE NORTH RAW SIDEREAL UNPREPARED
Pixels Extensions
Index Content Type Dimensions Format
[ 0] science NDAstroData (2112, 288) uint16
[ 1] science NDAstroData (2112, 288) uint16
[ 2] science NDAstroData (2112, 288) uint16
[ 3] science NDAstroData (2112, 288) uint16
[ 4] science NDAstroData (2112, 256) float32
Notice how a new extension was created but variance, mask, the OBJCAT
table and OBJMASK image were not copied over. Only the science pixel data was
copied over.
Please note, there is no implementation for the “insertion” of an extension.
Removing an extension or part of one
Removing an extension or a part of an extension is straightforward. The
Python command del() is used on the item to remove. Below are a few
examples, but first let us load a file
>>> ad = astrodata.open('../playdata/N20170609S0154_varAdded.fits')
>>> ad.info()
As you go through these examples, check the new structure with ad.info()
after every removal to see how the structure has changed.
Deleting a whole AstroData extension, the fourth one
>>> del ad[3]
Deleting only the variance array from the second extension
>>> ad[1].variance = None
Deleting a table associated with the first extension
>>> del ad[0].OBJCAT
Deleting a global table, not attached to a specific extension
>>> del ad.REFCAT
Writing back to a file
The AstroData class implements methods for writing its data back to a
MEF file on disk.
Writing to a new file
There are various ways to define the destination for the new FITS file. The most common and natural way is
>>> ad.write('new154.fits')
# If the file already exists, an error will be raised unless overwrite=True
# is specified.
>>> ad.write('new154.fits', overwrite=True)
This will write a FITS file named ‘new154.fits’ in the current directory. With
overwrite=True, it will overwrite the file if it already exists. A path
can be prepended to the filename if the current directory is not the
destination.
Note that ad.filename and ad.path have not changed, we have just
written to the new file, the AstroData object is in no way associated with
that new file.
>>> ad.path
'../playdata/N20170609S0154.fits'
>>> ad.filename
'N20170609S0154.fits'
If you want to create that association, the ad.filename and ad.path
needs to be modified first. For example
>>> ad.filename = 'new154.fits'
>>> ad.write(overwrite=True)
>>> ad.path
'../playdata/new154.fits'
>>> ad.filename
'new154.fits'
Changing ad.filename also changes the filename in the ad.path. The
sequence above will write ‘new154.fits’ not in the current directory but
rather to the directory that is specified in ad.path.
Warning
ad.write() has an argument named filename. Setting filename
in the call to ad.write(), as in ad.write(filename='new154.fits')
will NOT modify ad.filename or ad.path. The two “filenames”, one a
method argument the other a class attribute have no association to each
other.
Updating an existing file on disk
Updating an existing file on disk requires explicitly allowing overwrite.
If you have not written ‘new154.fits’ to disk yet (from previous section)
>>> ad = astrodata.open('../playdata/N20170609S0154.fits')
>>> ad.write('new154.fits', overwrite=True)
Now let’s open ‘new154.fits’, and write to it
>>> adnew = astrodata.open('new154.fits')
>>> adnew.write(overwrite=True)
A note on FITS header keywords
When writing an AstroData object as a FITS file, it is necessary to add or
update header keywords to represent some of the internally-stored information.
Any extensions that did not originally belong to a given AstroData instance
will be assigned new EXTVER keywords to avoid conflicts with existing
extensions, and the internal WCS is converted to the appropriate FITS keywords.
Note that in some cases it may not be possible for standard FITS keywords to
accurately represent the true WCS. In such cases, the FITS keywords are written
as an approximation to the true WCS, together with an additional keyword
to indicate this. The accurate WCS is written as an additional FITS extension with
EXTNAME='WCS' that AstroData will recognize when the file is read back in. The
WCS extension will not be written to disk if there is an accurate FITS
representation of the WCS (e.g., for a simple image).
Create New MEF Files
A new MEF file can be created from an existing, maybe modified, file or created from scratch (e.g., using computer-generated data/images).
Create New Copy of MEF Files
Basic example
As seen above, a MEF file can be opened with astrodata, the AstroData
object can be modified (or not), and then written back to disk under a
new name.
>>> ad = astrodata.open('../playdata/N20170609S0154.fits')
... optional modifications here ...
>>> ad.write('newcopy.fits')
Needing true copies in memory
Sometimes it is a true copy in memory that is needed. This is not specific
to MEF. In Python, doing something like adnew = ad does not create a
new copy of the AstrodData object; it just gives it a new name. If you
modify adnew you will be modifying ad too. They point to the same
block of memory.
To create a true independent copy, the deepcopy utility needs to be used.
.. code-block:: python
>>> from copy import deepcopy
>>> ad = astrodata.open('../playdata/N20170609S0154.fits')
>>> adcopy = deepcopy(ad)
Warning
deepcopy can cause memory problems, depending on the size of the data
being copied as well as the size of objects it references. If you notice
your memory becoming large/full, consider breaking down the copy into
smaller pieces and f.
Create New MEF Files from Scratch
Before one creates a new MEF file on disk, one has to create the AstroData
object that will be eventually written to disk. The AstroData object
created also needs to know that it will have to be written using the MEF
format. This is fortunately handled fairly transparently by astrodata.
The key to associating the FITS data to the AstroData object is simply to
create the AstroData object from astropy.io.fits header objects. Those
will be recognized by astrodata as FITS and the constructor for FITS will be
used. The user does not need to do anything else special. Here is how it is
done.
Create a MEF with basic header and data array set to zeros
>>> import numpy as np
>>> from astropy.io import fits
>>> phu = fits.PrimaryHDU()
>>> pixel_data = np.zeros((100,100))
>>> hdu = fits.ImageHDU()
>>> hdu.data = pixel_data
>>> ad = astrodata.create(phu)
>>> ad.append(hdu, name='SCI')
# Or another way to do the last two blocks:
>>> hdu = fits.ImageHDU(data=pixel_data, name='SCI')
>>> ad = astrodata.create(phu, [hdu])
# Finally write to a file.
>>> ad.write('new_MEF.fits')
Associate a pixel array with a science pixel array
Only main science (labed as SCI) pixel arrays are added an
AstroData object. It not uncommon to have pixel information associated with
those main science pixels, such as pixel masks, variance arrays, or other
information.
These pixel arrays are added to specific slice of the astrodata object they are associated with.
Building on the AstroData object we created in the previously, we can add a
new pixel array directly to the slice(s) of the AstroData object it should be
associated with by assigning it as an attribute of the object.
>>> extra_data = np.ones((100, 100))
>>> ad[0].EXTRADATA = extra_data
When the file is written to disk as a MEF, an extension will be created with
EXTNAME = EXTRADATA and an EXTVER that matches the slice’s EXTVER,
in this case is would be 1.
Represent a table as a FITS binary table in an AstroData object
One first needs to create a table, either an astropy.table.Table
or a BinTableHDU. See the Astropy documentation
on tables and this manual’s section dedicated to tables for
more information.
In the first example, we assume that my_astropy_table is
a Table ready to be attached to an AstroData
object. (Warning: we have not created my_astropy_table therefore the
example below will not run, though this is how it would be done.)
>>> phu = fits.PrimaryHDU()
>>> ad = astrodata.create(phu)
>>> astrodata.add_header_to_table(my_astropy_table)
>>> ad.append(my_astropy_table, name='SMAUG')
In the second example, we start with a FITS BinTableHDU
and attach it to a new AstroData object. (Again, we have not created
my_fits_table so the example will not run.)
>>> phu = fits.PrimaryHDU()
>>> ad = astrodata.create(phu)
>>> ad.append(my_fits_table, name='DROGON')
As before, once the AstroData object is constructed, the ad.write()
method can be used to write it to disk as a MEF file.