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The Astro-wise pipeline

Python Data processing - the low-level interfaces Data administration - persistent objects. The Astro-wise pipeline. Python. Object Oriented scripting language clean, easy-to-understand syntax extensive library powerful built-in data types (str, dict, list, file)

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The Astro-wise pipeline

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  1. Python Data processing - the low-level interfaces Data administration - persistent objects The Astro-wise pipeline

  2. Python • Object Oriented scripting language • clean, easy-to-understand syntax • extensive library • powerful built-in data types (str, dict, list, file) • byte-code interpreted, dynamically typed Rapid development and easy maintenance

  3. Python, a 1-slide course wordcount = {} for line in file('my_thesis.txt'): for word in line.split(): if word not in wordcount: wordcount[word] = 1 else: wordcount[word] += 1 print wordcount

  4. Image processing • eclipse libraray in C (ESO, N. Devillard) • wrapped with SWIG • fits images and headers as built-in data types >>> from eclipse import image, header >>> img = image('science.fits') >>> hdr = header('science.fits') >>> flat = image('flat.fits') >>> img = img / flat >>> hdr['FLATFLD'] = 'flat.fits' >>> img.save('flatfielded.fits', hdr) • Co-addition with SWARP (IAP, E. Bertin)

  5. Catalog Processing • Sextractor (IAP, E. Bertin) • LDAC (OmegaCAM, E. Deul) • Astrometry • Photometry • Common interfaces, but no Python types • Persistent Sourcelists (see KGB)

  6. Astro-wise Pipelines • Pipelines are about data-administration, not about data-processing • Persistent objects • Object's state persists across program boundaries • Python classes representing SQL tables • Should also work without back-end • Distinguish meta-data and bulk (FITS) data • meta data in persistent objects • bulk (FITS) data through file-server

  7. The make metaphor • 'Making' objects • think unix Makefile • targets and dependencies (recursive) >>> bias = BiasFrame() >>> bias.raw_frames = [RawBiasFrame('bias1.fits'), RawBiasFrame('bias2.fits'), ... RawBiasFrane('biasN.fits')] >>> bias.make()

  8. An example with Queries • Queries are Python expressions (see Danny) • Dependencies can be filled through queries >>> bias = BiasFrame() >>> query = ((RawBiasFrames.chip.name == 'ccd50') & (RawBiasFrames.DATE_OBS > a_date-1) & (RawBiasFrames.DATE_OBS < a_date+1)) >>> bias.raw_frames = list(query) >>> bias.make() >>> bias.store() # the bulk FITS data >>> bias.commit() # the meta data

  9. Image Pipeline

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