DISCONTINUED!!!!

** THIS PROJECT IS DISCONTINUED ** For the global DAS month of February 2023, native interrogator format is encouraged! More information about global DAS month 2023 can be found at https://www.norsar.no/in-focus/global-das-monitoring-month-february-2023

A more comprehensive IRIS data format is under development here: https://github.com/DAS-RCN/DAS_metadata

miniDAS data format (discontinued)

The miniDAS data format is a minimalistic approach to store data from Distributed Acoustic Sensing (DAS) recordings in an HDF5 file.

Filename convention

Files are stored in day-folders, each folder containing all files from this particular day. The file has the name syntax

./2022-01-01/ProjName_YYYY-MM-DD_HH.MM.SS.FFF.miniDAS

where ProjName is a description of the project, or installation name Note that files have the extension .miniDAS, even though technically they are .hdf5 files.

Trace-Data

The signal is stored in as a dataset under root with the name traces Units of the traces mus be given as a string in data_unit field. And additional scale_factor may be given that is to be multiplied with the trace data. This is accompanied by a string units_after_scaling Note that data need to be geo-calibrated, such that excess fibre lengths (such as loops) are corrected for.

traces          Traces of signal (nsmpl, nchnl)

Header

Basic header information are stored as attributes under root. These are the very minimal data necessary to process the data.

format                 Format name (must be 'miniDAS'), type=string
version                Version of DAS file format, type=string
data_units             Units of the data-traces (e.g. radians, m/(m*s), m/m) type=string
scale_factor           A scaling factor to be multiplied with the data; type=float32
units_after_scaling    Units of traces *after* scaling is multiplied with traces; type=string
start_time             UNIX time stamp of first sample in file (in nano-seconds) type=uint64
sampling_rate          Temporal sampling rate in Hz type=float32
gauge_length           Gauge length [in meters] type=float32
latitudes              numpy array of latitudes (or y-values), type=float32
longitudes             numpy array of longitudes (or x-values), type=float32
elevations             numpy array of elevations above sea-level (in meters), type=float32
meta                   Dictionary of addtional user-defined meta-data

Additional Meta Data

Additional information can be stored under the name meta as dataset. This is free-format, but should be kept to a minimum.

Example File Information

>>> fname = './Reference_2022-09-28_09.00.00.000.miniDAS'
>>> infoDAS(fname, meta=True)

./Reference_2022-09-28_09.00.00.000.miniDAS
              traces == (10000, 300) numpy array
          data_units == 'rad'
          elevations == (300,) numpy array, (     0 <= elevations <=     0)
              format == 'miniDAS'
        gauge_length == 10.2
           latitudes == (300,) numpy array, (48.858 <= latitudes <=48.868)
          longitudes == (300,) numpy array, (2.2945 <= longitudes <=2.2945)
       sampling_rate == 1000.0
        scale_factor == 567890.1234
          start_time == 28 Sep 2022 09:00:00.000000
 units_after_scaling == 'µε/s'
             version == '0.1.0'

     /meta/dict/val1 == 1.23
     /meta/dict/val2 == dummy
        /meta/scalar == 3.14159265358979
        /meta/string == This is a test
        /meta/vector == (10,) numpy array, (10 <= /meta/vector <=19)
>>>

Documentation

TBD

Installation

Using pip

Download miniDAS from pipy repositories using pip.

pip install miniDAS

From source and for development

This method is recommended for development

git clone ...miniDAS
cd miniDAS
pip install -e .

License

MIT