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Data preprocessor for DAS systems

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About

This project is a data preprocessor for DAS systems. It is designed to receive packets from DAS system, concatenate them in chunks of defined size and save them as separate files and.

Getting Started

To run the project you need to have Python 3.9 or higher installed on your machine.

Configuration

Before running the project you have to configure parameters in the config.ini file:

System parameters

NAME - name of the DAS system (e.g. Mekorot or Prisma)

PATHs

LOCALPATH is absolute PATH to the LOCAL directory, DAS client will write packets to LOCALPATH/YYYYMMDD.

NASPATH_final is absolute PATHs to the NAS directory which will contain concatenated hdf5 files.

Data characteristics

CHUNK_SIZE is the size of the chunk in seconds. By default 300. SPS is expected time frequency after data downsamling (in Hz). By default 100. DX is expected spatial spacing after data downsampling (in m). By default 9.6

Save format

File naming

  • Files are named according to the following convention:
    • YYYY/YYYYMMDD/.h5
      • YYYY - year of the recording in UTC
      • YYYYMMDD - date of the recording in UTC
      • - timestamp of the beginning of the chunk

Data

  • Data is stored in .h5 format
    • Data is located in data_down dataset
      • Each point stored as float32

Metadata

  • Metadata saved in attributes. Contents of the metadata can vary depending on the system and date of recording.
    • Always present:
      • DX_down - spatial sampling rate after downsampling
      • PRR_down - temporal sampling rate after downsampling
      • down_factor_space, down_factor_time - downsampling factors
    • May be present:
      • Gauge_m - (Prisma specific) gauge length of the system
      • Index, Origin, Spacing - (Mekorot specific) packet-wise original data descriptors

About

Concatenation, down-sampling and unification of DAS data for further processing and long-term storage

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