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52 lines
1.1 KiB
52 lines
1.1 KiB
import xarray as xr
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import numpy as np
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from datetime import datetime
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import xrft
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import finufft
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def fft(dataArray, **kwargs):
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return xrft.fft(dataArray, **kwargs)
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def ifft(dataArray, **kwargs):
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return xrft.ifft(dataArray, **kwargs)
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def fft_nutou(dataArray, modeNum, **kwargs):
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data = dataArray.to_numpy()
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data = data.astype('complex128')
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time = dataArray[dataArray.dims[0]].to_numpy()
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if isinstance(time[0], type(np.datetime64(500,'s'))):
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time = time.astype(float)
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time = time - time[0]
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freqUpLim = 1 / np.min(np.abs(time - np.roll(time, 1))) * 1e9
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else:
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time = time.astype(float)
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time = time - time[0]
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freqUpLim = 1 / np.min(np.abs(time - np.roll(time, 1)))
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print(freqUpLim)
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time = time / time.max() * 2 * np.pi
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# calculate the transform
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res = xr.DataArray(
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data=finufft.nufft1d1(time, data, modeNum, **kwargs),
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dims=['freq'],
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coords={
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"freq":np.linspace(-freqUpLim/2, freqUpLim/2, modeNum)
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}
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)
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return res
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def ifft_nutou(dataArray, modeNum):
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pass
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