Package to efficiently read large fits arrays in object by object
Package to sequentially efficiently read large fits arrays in object by object
The following example shows an example of reading in a large fits hdu within a memory limit of 2048MB, assuming light curves are stored in rows:
import numpy as np import fitsio import fitsiochunked as fc with fitsio.FITS(filename) as infile: hdu = infile['flux'] napertures = hdu.get_info()['ndim'] mean_flux = np.zeros(napertures) for chunk in fc.chunks(hdu, memory_limit_mb=2048): # `chunk` is a namedtuple with `.data` and `.slice` properties chunk_data = chunk.data print('Data shape:', chunk_data.shape) print('Data dtype:', chunk_data.dtype) chunk_slice = chunk.slice print('Chunk starting from aperture:', chunk_slice.start) print('Chunk up to:', chunk_slice.stop) chunk_mean = np.average(chunk_data, axis=1) mean_flux[chunk_slice] = chunk_mean
The library copes with an aribtrary number of hdus:
import numpy as np import fitsio import fitsiochunked as fc with fitsio.FITS(filename) as infile: hjd_hdu = infile['hjd'] flux_hdu = infile['flux'] fluxerr_hdu = infile['fluxerr'] napertures = flux_hdu.get_info()['ndim'] mean_flux = np.zeros(napertures) for chunks in fc.chunks(hjd_hdu, flux_hdu, fluxerr_hdu, memory_limit_mb=2048): # chunks is a tuple of chunks hjd_chunk, flux_chunk, fluxerr_chunk = chunks # `chunk` is a namedtuple with `.data` and `.slice` properties flux_chunk_data = flux_chunk.data print('Data shape:', flux_chunk_data.shape) print('Data dtype:', flux_chunk_data.dtype) # and so on
Note: if multiple hdus are supplied, then the memory_limit_mb and chunksize arguments to chunks apply to each HDU i.e. three HDUs and a memory limit of 2048MB will lead to 3x2048 = 6144MB of memory used.
Install with pip:
pip install fitsiochunked # or get the latest development version from github pip install git+https://github.com/mindriot101/fitsiochunked
or download and run the setup file:
git clone https://github.com/mindriot101/fitsiochunked cd fitsiochunked python setup.py install
The high level interface is the chunks function, which builds a ChunkedAdapter object wrapping a fitsio.ImageHDU object.
The ChunkedAdapter wraps a fitsio HDU object. When constructed, it becomes a callable which yields the image data in that hdu in chunks.
The chunksize can be set either with with the parameter chunksize which simply yields chunksize rows each time, or with memory_limit_mb which tries (no promises!) to automatically calculate the number of lightcurves that will fit into memory_limit_mb megabytes of memory.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|File Name & Checksum SHA256 Checksum Help||Version||File Type||Upload Date|
|fitsiochunked-0.2.1-py2.py3-none-any.whl (5.9 kB) Copy SHA256 Checksum SHA256||py2.py3||Wheel||Jan 27, 2017|
|fitsiochunked-0.2.1.tar.gz (6.3 kB) Copy SHA256 Checksum SHA256||–||Source||Jan 27, 2017|