Package to sequentially efficiently read large fits arrays in object by object
Free software: MIT license
Features
Sequentially read in large fits files, within a given fixed memory limit
Quick usage
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'][0]
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'][0]
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.
Installation
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
Details
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.
Metadata
Release files for fitsiochunked 0.2.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| fitsiochunked-0.2.1.tar.gz | 6.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| fitsiochunked-0.2.1-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 12.2 kB
Release files / fitsiochunked-0.2.1.tar.gz
| Download URL | fitsiochunked-0.2.1.tar.gz |
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| Size | 6.3 kB |
| Tags | Source |
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Release files / fitsiochunked-0.2.1-py2.py3-none-any.whl
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| Size | 5.9 kB |
| Tags | Python 2 Python 3 |
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