fftFilter

fftFilter( QDataSet ds, int len, org.das2.qds.ops.Ops.FFTFilterType filt ) → QDataSet

Apply windows to the data to prepare for FFT. The data is reformed into a rank 2 dataset [N,len]. The filter is applied to the data to remove noise caused by the discontinuity. This is deprecated, and windowFunction should be used so that the filter is applied to records just before each fft is performed to save space.

Parameters

ds - rank 1, 2, or 3 data
len - size of the window.
filt - FFTFilterType.Hanning or FFTFilterType.TenPercentEdgeCosine

Returns:

data[N,len] with the window applied.

search for examples view on GitHub view source

fftPowerMultiThread

fftPowerMultiThread( QDataSet ds, int len, ProgressMonitor mon ) → QDataSet

Experiment with multi-threaded FFTPower function. This breaks up the task into four independent tasks that can be run in parallel.

Parameters

ds - rank 2 dataset ds(N,M) with M>len
len - the number of elements to have in each fft.
mon - a ProgressMonitor for the process

Returns:

rank 2 FFT spectrum

search for examples view on GitHub view source

fftWindow

fftWindow( QDataSet ds, int len ) → QDataSet

perform ffts on the rank 1 dataset to make a rank2 spectrogram.

Parameters

ds - rank 1 dataset
len - the window length

Returns:

rank 2 dataset.

search for examples view on GitHub view source

finite

finite( QDataSet ds ) → QDataSet

returns 1 where the data is not NaN, Inf, etc I needed this when I was working with the RBSP polar scatter script. Note valid should be used to check for valid data, which also checks for NaN.

Parameters

ds - qdataset of any rank.

Returns:

1 where the data is not Nan or Inf, 0 otherwise.

search for examples view on GitHub view source

flatten

flatten( QDataSet ds ) → QDataSet

flatten a rank N dataset, though currently rank 4 is not supported. The result for rank 2 is an n,3 dataset of [x,y,z], or if there are no tags, just [z]. The last index will be the dependent variable, and the first indeces will be the independent variables sorted by dimension.

Parameters

ds - the rank N dataset (note only Rank 2 is supported for now).

Returns:

rank 2 dataset bundle

See Also:

Ops_r.mdorg.das2.qds.DataSetOps#flattenRank2(QDataSet)
Ops_g.md#grid(QDataSet)
flattenWaveform(QDataSet)


search for examples view on GitHub view source

flattenWaveform

flattenWaveform( QDataSet ds ) → QDataSet

flatten a rank 2 dataset where the y depend variable is just an offset from the xtag. Note the new DEPEND_0 may have different units from ds.property(DEPEND_0).

Parameters

ds - rank 2 waveform with tags for DEPEND_0 and offsets for DEPEND_1

Returns:

rank 1 waveform

See Also:

flatten(QDataSet)
Ops_a.mdDataSetOps#flattenWaveform(QDataSet)


search for examples view on GitHub view source

floor

floor( QDataSet ds1 ) → QDataSet

element-wise floor function.

Parameters

ds1 -

Returns:

org.das2.qds.QDataSet

search for examples view on GitHub view source

fltarr

fltarr( int len0 ) → QDataSet

create a dataset filled with zeros, stored in 4-byte floats.

Parameters

len0 - the zeroth dimension length

Returns:

rank 1 dataset filled with zeros.

See Also:

Ops_z.md#zeros(int)
Ops_d.md#dblarr(int)


search for examples view on GitHub view source