astropy has built in a flexible scheme to verify FITS data conforming to
the FITS standard. The basic verification philosophy in
astropy is to be
tolerant with input and strict with output.
astropy reads a FITS file which does not conform to FITS standard, it
will not raise an error and exit. It will try to make the best educated
interpretation and only gives up when the offending data is accessed and no
unambiguous interpretation can be reached.
On the other hand, when writing to an output FITS file, the content to be written must be strictly compliant to the FITS standard by default. This default behavior can be overwritten by several other options, so the user will not be held up because of a minor standard violation.
Since FITS standard is a “loose” standard, there are many places the violation can occur and to enforce them all will be almost impossible. It is not uncommon for major observatories to generate data products which are not 100% FITS compliant. Some observatories have also developed their own nonstandard dialect and some of these are so prevalent that they have become de facto standards. Examples include the long string value and the use of the CONTINUE card.
The violation of the standard can happen at different levels of the data
astropy’s verification scheme is developed on these hierarchical
levels. Here are the three
astropy verification levels:
The HDU List
Each Card in the HDU Header
These three levels correspond to the three categories of objects:
HDUList, any HDU (e.g.,
Card. They are the only objects having the
Most other classes in
astropy.io.fits do not have a
verify() is called at the HDU List level, it verifies standard
compliance at all three levels, but a call of
verify() at the Card level
will only check the compliance of that Card. Since
astropy is tolerant when
reading a FITS file, no
verify() is called on input. On output,
verify() is called with the most restrictive option as the default.
There are several options accepted by all verify(option) calls in
In addition, they available for the
output_verify argument of the following
flush(). In these cases, they are
passed to a
verify() call within these methods. The available options are:
This option will raise an exception if any FITS standard is violated. This is
the default option for output (i.e., when
flush() is called). If a user wants to overwrite this default on output, the
other options listed below can be used.
This option is the same as the ignore option but will send warning messages. It will not try to fix any FITS standard violations whether fixable or not.
This option will ignore any FITS standard violation. On output, it will write the HDU List content to the output FITS file, whether or not it is conforming to the FITS standard.
The ignore option is useful in the following situations:
An input FITS file with nonstandard formatting is read and the user wants to copy or write out to an output file. The nonstandard formatting will be preserved in the output file.
A user wants to create a nonstandard FITS file on purpose, possibly for testing or consistency.
No warning message will be printed out. This is like a silent warning option (see below).
This option will try to fix any FITS standard violations. It is not always possible to fix such violations. In general, there are two kinds of FITS standard violations: fixable and non-fixable. For example, if a keyword has a floating number with an exponential notation in lower case ‘e’ (e.g., 1.23e11) instead of the upper case ‘E’ as required by the FITS standard, it is a fixable violation. On the other hand, a keyword name like ‘P.I.’ is not fixable, since it will not know what to use to replace the disallowed periods. If a violation is fixable, this option will print out a message noting it is fixed. If it is not fixable, it will throw an exception.
The principle behind fixing is to do no harm. For example, it is plausible to
‘fix’ a Card with a keyword name like ‘P.I.’ by deleting it, but
will not take such action to hurt the integrity of the data.
Not all fixes may be the “correct” fix, but at least
astropy will try to
make the fix in such a way that it will not throw off other FITS readers.
Same as fix, but will not print out informative messages. This may be useful in a large script where the user does not want excessive harmless messages. If the violation is not fixable, it will still throw an exception.
In addition, as of
astropy version 0.4.0 the following combined options
These options combine the semantics of the basic options. For example,
silentfix+exception is actually equivalent to just
silentfix in that
fixable errors will be fixed silently, but any unfixable errors will raise an
exception. On the other hand,
silentfix+warn will issue warnings for
unfixable errors, but will stay silent about any fixed errors.
Verifications at Different Data Object Levels¶
We will examine what
astropy’s verification does at the three different
Verification at HDUList¶
At the HDU List level, the verification is only for two simple cases:
Verify that the first HDU in the HDU list is a primary HDU. This is a fixable case. The fix is to insert a minimal primary HDU into the HDU list.
Verify the second or later HDU in the HDU list is not a primary HDU. Violation will not be fixable.
Verification at Each HDU¶
For each HDU, the mandatory keywords, their locations in the header, and their values will be verified. Each FITS HDU has a fixed set of required keywords in a fixed order. For example, the primary HDU’s header must at least have the following keywords:
SIMPLE = T / BITPIX = 8 / NAXIS = 0
If any of the mandatory keywords are missing or in the wrong order, the fix option will fix them:
>>> hdu.header # has a 'bad' header SIMPLE = T / NAXIS = 0 BITPIX = 8 / >>> hdu.verify('fix') # fix it Output verification result: 'BITPIX' card at the wrong place (card 2). Fixed by moving it to the right place (card 1). >>> hdu.header # voila! SIMPLE = T / conforms to FITS standard BITPIX = 8 / array data type NAXIS = 0
Verification at Each Card¶
The lowest level, the Card, also has the most complicated verification possibilities.
Here is a list of fixable and not fixable Cards:
Floating point numbers with lower case ‘e’ or ‘d’:
>>> from astropy.io import fits >>> c = fits.Card.fromstring('FIX1 = 2.1e23') >>> c.verify('silentfix') >>> print(c) FIX1 = 2.1E23
The equal sign is before column nine in the card image:
>>> c = fits.Card.fromstring('FIX2= 2') >>> c.verify('silentfix') >>> print(c) FIX2 = 2
String value without enclosing quotes:
>>> c = fits.Card.fromstring('FIX3 = string value without quotes') >>> c.verify('silentfix') >>> print(c) FIX3 = 'string value without quotes'
Missing equal sign before column nine in the card image.
Space between numbers and E or D in floating point values:
>>> c = fits.Card.fromstring('FIX5 = 2.4 e 03') >>> c.verify('silentfix') >>> print(c) FIX5 = 2.4E03
Unparsable values will be “fixed” as a string:
>>> c = fits.Card.fromstring('FIX6 = 2 10 ') >>> c.verify('fix+warn') >>> print(c) FIX6 = '2 10 '
Illegal characters in keyword name.
We will summarize the verification with a “life-cycle” example:
>>> h = fits.PrimaryHDU() # create a PrimaryHDU >>> # Try to add an non-standard FITS keyword 'P.I.' (FITS does no allow >>> # '.' in the keyword), if using the update() method - doesn't work! >>> h['P.I.'] = 'Hubble' ValueError: Illegal keyword name 'P.I.' >>> # Have to do it the hard way (so a user will not do this by accident) >>> # First, create a card image and give verbatim card content (including >>> # the proper spacing, but no need to add the trailing blanks) >>> c = fits.Card.fromstring("P.I. = 'Hubble'") >>> h.header.append(c) # then append it to the header >>> # Now if we try to write to a FITS file, the default output >>> # verification will not take it. >>> h.writeto('pi.fits') Output verification result: HDU 0: Card 4: Unfixable error: Illegal keyword name 'P.I.' ...... raise VerifyError VerifyError >>> # Must set the output_verify argument to 'ignore', to force writing a >>> # non-standard FITS file >>> h.writeto('pi.fits', output_verify='ignore') >>> # Now reading a non-standard FITS file >>> # astropy.io.fits is magnanimous in reading non-standard FITS files >>> hdus = fits.open('pi.fits') >>> hdus.header SIMPLE = T / conforms to FITS standard BITPIX = 8 / array data type NAXIS = 0 / number of array dimensions EXTEND = T P.I. = 'Hubble' >>> # even when you try to access the offending keyword, it does NOT >>> # complain >>> hdus.header['p.i.'] 'Hubble' >>> # But if you want to make sure if there is anything wrong/non-standard, >>> # use the verify() method >>> hdus.verify() Output verification result: HDU 0: Card 4: Unfixable error: Illegal keyword name 'P.I.'
Verification Using the FITS Checksum Keyword Convention¶
The North American FITS committee has reviewed the FITS Checksum Keyword Convention for possible adoption as a FITS Standard. This convention provides an integrity check on information contained in FITS HDUs. The convention consists of two header keyword cards: CHECKSUM and DATASUM. The CHECKSUM keyword is defined as an ASCII character string whose value forces the 32-bit 1’s complement checksum accumulated over all the 2880-byte FITS logical records in the HDU to equal negative zero. The DATASUM keyword is defined as a character string containing the unsigned integer value of the 32-bit 1’s complement checksum of the data records in the HDU. Verifying the accumulated checksum is still equal to negative zero provides a fairly reliable way to determine that the HDU has not been modified by subsequent data processing operations or corrupted while copying or storing the file on physical media.
In order to avoid any impact on performance, by default
astropy will not
verify HDU checksums when a file is opened or generate checksum values when a
file is written. In fact, CHECKSUM and DATASUM cards are automatically removed
from HDU headers when a file is opened, and any CHECKSUM or DATASUM cards are
stripped from headers when an HDU is written to a file. In order to verify the
checksum values for HDUs when opening a file, the user must supply the checksum
keyword argument in the call to the open convenience function with a value of
True. When this is done, any checksum verification failure will cause a
warning to be issued (via the warnings module). If checksum verification is
requested in the open, and no CHECKSUM or DATASUM cards exist in the HDU
header, the file will open without comment. Similarly, in order to output the
CHECKSUM and DATASUM cards in an HDU header when writing to a file, the user
must supply the checksum keyword argument with a value of True in the call to
writeto() function. It is possible to write only the DATASUM card to the
header by supplying the checksum keyword argument with a value of ‘datasum’.
To verify the checksum values for HDUs when opening a file:
>>> # Open the file pix.fits verifying the checksum values for all HDUs >>> hdul = fits.open('pix.fits', checksum=True)
>>> # Open the file in.fits where checksum verification fails for the >>> # primary HDU >>> hdul = fits.open('in.fits', checksum=True) Warning: Checksum verification failed for HDU #0.
>>> # Create file out.fits containing an HDU constructed from data and >>> # header containing both CHECKSUM and DATASUM cards. >>> fits.writeto('out.fits', data, header, checksum=True)
>>> # Create file out.fits containing all the HDUs in the HDULIST >>> # hdul with each HDU header containing only the DATASUM card >>> hdul.writeto('out.fits', checksum='datasum')
>>> # Create file out.fits containing the HDU hdu with both CHECKSUM >>> # and DATASUM cards in the header >>> hdu.writeto('out.fits', checksum=True)
>>> # Append a new HDU constructed from array data to the end of >>> # the file existingfile.fits with only the appended HDU >>> # containing both CHECKSUM and DATASUM cards. >>> fits.append('existingfile.fits', data, checksum=True)