3. Input and Output Operations and Extension Manipulation - MEF¶
AstroData is not intended to be Multi-Extension FITS (MEF) centric. The core
is independent of the file format. At Gemini, our data model uses MEF.
Therefore we have implemented a FITS handler that maps a MEF to the
internal AstroData representation. A different handler can be implemented
for a different file format.
In this chapter, we present examples that will help the reader understand how
to access the information stored in a MEF with the AstroData object and
understand that mapping.
Try it yourself
Download the data package (Try it yourself) if you wish to follow along and run the examples. Then
$ cd <path>/ad_usermanual/playground
$ python
3.1. Imports¶
Before doing anything, you need to import AstroData and the Gemini instrument
configuration package gemini_instruments.
>>> import astrodata
>>> import gemini_instruments
3.2. Open and access existing dataset¶
3.2.1. 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.
>>> ad = astrodata.open('../playdata/N20170609S0154.fits')
>>> type(ad)
<class 'gemini_instruments.gmos.adclass.AstroDataGmos'>
From now on, ad knows it is GMOS data. It knows how to access its headers
and when using the Recipe System (recipe_system), it will trigger the
selection of the GMOS primitives and recipes.
The original path and filename are stored in the object. If you were to write
the AstroData object to disk without specifying anything, those path and
filename would be used.
>>> ad.path
'../playdata/N20170609S0154.fits'
>>> ad.filename
'N20170609S0154.fits'
3.2.2. Accessing the content of a MEF file¶
Accessing pixel data, headers, tables will be covered in details in following chapters. Here we just introduce the basic content interface.
For details on the AstroData structure, please refer to the
previous chapter.
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.
3.2.2.1. 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)
<type 'numpy.ndarray'>
>>> data.shape
(2112, 256)
Remember that in a ndarray the y-axis is 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
3.2.2.2. 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, that
table will be packaged within the same AstroData extension as the pixel data.
The AstroData “extension” is the NDAstroData object plus any table or other pixel
array. 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'>
3.2.2.3. Headers¶
Headers are stored in the NDAstroData .meta attribute as astropy.io.fits.Header objects,
which is a form of Python ordered dictionaries. Headers associated with extensions
are stored with the corresponding NDAstroData object. The MEF Primary Header
Unit (PHU) is stored “globally” in the AstroData object. Note that when slicing an AstroData object,
for example copying over just the first extension, the PHU will follow. 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. See the chapters on headers for details.
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]']
3.3. Modify Existing MEF Files¶
Before you start modify the structure of an AstroData object, you should be
familiar with it. Please make sure that you have read the previous chapter
on the structure of the AstroData object.
3.3.1. Appending an extension¶
In this section, we take an extension from one AstroData object and append it
to another. Because we are mapping a FITS file, the EXTVER keyword gets
automatically updated to the next available value to ensure that when the
AstroData object is written back to disk as MEF, it will be coherent.
Here is an example appending a whole AstroData extension, with pixel data, variance, mask and tables.
>>> 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']
5
>>> 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. Also, note
that the EXTVER of the extension in advar was 4, but once appended
to ad, it had to be changed to the next available integer, 5, numbers 1 to
4 being already used by ad’s own extensions.
In this next example, we are appending only the pixel data, leaving behind the other associated data. The header associated with that data does follow however.
>>> ad = astrodata.open('../playdata/N20170609S0154.fits')
>>> advar = astrodata.open('../playdata/N20170609S0154_varAdded.fits')
>>> ad.append(advar[3].data)
>>> 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.
3.3.2. 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
3.4. Writing back to disk¶
The AstroDataFits layer takes care of converting
the AstroData object back to a MEF file on disk. When writing to disk,
one should be aware of the path and filename information associated
with the AstroData object.
>>> ad = astrodata.open('../playdata/N20170609S0154.fits')
>>> ad.path
'../playdata/N20170609S0154.fits'
>>> ad.filename
'N20170609S0154.fits'
3.4.1. 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')
>>> 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()
>>> 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.
3.4.2. 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')
Now let’s open ‘new154.fits’, and write to it
>>> adnew = astrodata.open('new154.fits')
>>> adnew.write(overwrite=True)
3.5. Create New MEF Files¶
A new MEF file can be created from an existing, maybe modified, file or it can be created from scratch. We discuss both cases here.
3.5.1. Create New Copy of MEF Files¶
To create a new copy of a MEF file, modified or not, the user has already been given most of the tools in the sections above. Yet, let’s throw a couple examples for completeness.
3.5.1.1. 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')
3.5.1.2. 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 modify ad too. They point to the same block
of memory.
To create a true independent copy, the deepcopy utility needs to be used.
>>> from copy import deepcopy
>>> ad = astrodata.open('../playdata/N20170609S0154.fits')
>>> adcopy = deepcopy(ad)
Be careful using deepcopy, you memory could balloon really fast. Use it
only when truly needed.
3.5.2. 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 provider 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.
3.5.2.1. 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 blocs:
>>> hdu = fits.ImageHDU(data=pixel_data, name='SCI')
>>> ad = astrodata.create(phu, [hdu])
Then it is just a matter of calling ad.write('somename.fits') on that
new Astrodata object.
3.5.2.2. 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='BOB')
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='BILL')
As before, once the AstroData object is constructed, the ad.write()
method can be used to write it to disk as a MEF file.