Create a very large FITS file from scratch

This example demonstrates how to create a large file (larger than will fit in memory) from scratch using

By: Erik Bray

License: BSD

Normally to create a single image FITS file one would do something like:

import os
import numpy as np
from import fits
data = np.zeros((40000, 40000), dtype=np.float64)
hdu = fits.PrimaryHDU(data=data)

Then use the method to write out the new file to disk


However, a 40000 x 40000 array of doubles is nearly twelve gigabytes! Most systems won’t be able to create that in memory just to write out to disk. In order to create such a large file efficiently requires a little extra work, and a few assumptions.

First, it is helpful to anticipate about how large (as in, how many keywords) the header will have in it. FITS headers must be written in 2880 byte blocks, large enough for 36 keywords per block (including the END keyword in the final block). Typical headers have somewhere between 1 and 4 blocks, though sometimes more.

Since the first thing we write to a FITS file is the header, we want to write enough header blocks so that there is plenty of padding in which to add new keywords without having to resize the whole file. Say you want the header to use 4 blocks by default. Then, excluding the END card which Astropy will add automatically, create the header and pad it out to 36 * 4 cards.

Create a stub array to initialize the HDU; its exact size is irrelevant, as long as it has the desired number of dimensions

data = np.zeros((100, 100), dtype=np.float64)
hdu = fits.PrimaryHDU(data=data)
header = hdu.header
while len(header) < (36 * 4 - 1):
    header.append()  # Adds a blank card to the end

Now adjust the NAXISn keywords to the desired size of the array, and write only the header out to a file. Using the hdu.writeto() method will cause astropy to “helpfully” reset the NAXISn keywords to match the size of the dummy array. That is because it works hard to ensure that only valid FITS files are written. Instead, we can write just the header to a file using the method:

header['NAXIS1'] = 40000
header['NAXIS2'] = 40000

Finally, grow out the end of the file to match the length of the data (plus the length of the header). This can be done very efficiently on most systems by seeking past the end of the file and writing a single byte, like so:

with open('large.fits', 'rb+') as fobj:
    # Seek past the length of the header, plus the length of the
    # Data we want to write.
    # 8 is the number of bytes per value, i.e. abs(header['BITPIX'])/8
    # (this example is assuming a 64-bit float)
    # The -1 is to account for the final byte that we are about to
    # write: + (40000 * 40000 * 8) - 1)

More generally, this can be written:

shape = tuple(header['NAXIS{0}'.format(ii)] for ii in range(1, header['NAXIS']+1))
with open('large.fits', 'rb+') as fobj: + (np.product(shape) * np.abs(header['BITPIX']//8)) - 1)

On modern operating systems this will cause the file (past the header) to be filled with zeros out to the ~12GB needed to hold a 40000 x 40000 image. On filesystems that support sparse file creation (most Linux filesystems, but not the HFS+ filesystem used by most Macs) this is a very fast, efficient operation. On other systems your mileage may vary.

This isn’t the only way to build up a large file, but probably one of the safest. This method can also be used to create large multi-extension FITS files, with a little care.

Finally, we’ll remove the file we created:


Total running time of the script: ( 0 minutes 0.000 seconds)

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