20 lines
1.3 KiB
Python
20 lines
1.3 KiB
Python
"""
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The aim of this project is to extend pyerrors to be able to collect measurements from different projects and make them easily accessable to
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the research group. The idea is to build a database, in which the researcher can easily search for measurements on a correlator basis,
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which may be reusable.
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As a standard to store the measurements, we will use the .json.gz format from pyerrors.
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This allows us to organize a library by files and exported dictionaries.
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Also, this is compressable, but is also human readable in uncompressed form.
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The project creates a database with a table to store the measurements, and a folder to store the .json.gz files and tracks the changes to the folder automatically using datalad.
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This way, we can harness the power of datalad as a backand, to reproducibly build our database.
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Projects, that are also datalad datasets can be linked to the backlog of correlators as subdatasets, such that, using datalad rerun function,
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it can be easily seen wehere the respective measurement came from and ho it may be reproduced.
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For now, we are interested in collecting primary IObservables only, as these are the most computationally expensive and time consuming to calculate.
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"""
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from .main import *
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from .input import *
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from .initialization import *
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from .io import *
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