Class NoiseTerm

"
Initialise a NoiseTerm.

Keyword arguments:

    name : str
        description of this NoiseTerm
    channel : str
        data channel from which this noise term is estimated
    frame_type : str
        LDR frame type for files containing data for this NoiseTerm
    

Overrides: object.__init__

Apply a calibration function to the timeseries.

Arguments:

    func : callable
        any callable function that accepts numpy.array as input
    

Apply the transfer function to the spectrum.

Arguments:

    func : [ callable | numpy.array ]
        any callable function that accepts numpy.array as input or
        array by which to multiply spectrum.
    

Read the reference spectrum from a two-column file of frequency and ASD.

Arguments:

    referencefile : str
        path to file with space-delimited columns of frequency and ASD

Keyword arguments:

    epoch : lal.LIGOTimeGPS
        GPS epoch of this reference
    sampleUnits : lal.LALUnit
        amplitude unit for reference spectrum
    fcol : int
        number of column holding frequency array, default 0
    acol : int
        number of column holding amplitude array, default 1
    

Restrict the spectrum for this NoiseTerm to the given semiopen
[fmin, fmax) interval.

Arguments:

    fmin : float
        minimum frequency for this NoiseTerm
    fmax : float
        maximum frequency for this NoiseTerm
    

Plot the spectrum of this NoiseTerm.

Arguments:

outfile : str
    path to output file for this plot

typemap

Value:

{'channel': str, 'frame_type': str, 'name': str, 'sum': bool, 'data': numpy.array, 'deltaT': float, 'spectrum': numpy.array, 'deltaF': float , 'f0': float, 'epoch': seriesutils.lal.LIGOTimeGPS, 'ref_spectrum': n umpy.array, 'ref_deltaF': float, 'ref_f0': float, 'ref_epoch': seriesu tils.lal.LIGOTimeGPS}