From 759f772976caa660418e6ae621a97651f257090a Mon Sep 17 00:00:00 2001
From: Gao <gao@physi.uni-heidelberg.de>
Date: Fri, 19 May 2023 17:17:57 +0200
Subject: [PATCH] implentment FFT function

---
 Analyser/FFTAnalyser.py | 55 +++++++++++++++++++++++++++++++++++++++++
 1 file changed, 55 insertions(+)
 create mode 100644 Analyser/FFTAnalyser.py

diff --git a/Analyser/FFTAnalyser.py b/Analyser/FFTAnalyser.py
new file mode 100644
index 0000000..55c3217
--- /dev/null
+++ b/Analyser/FFTAnalyser.py
@@ -0,0 +1,55 @@
+import xarray as xr
+import pandas as pd
+import numpy as np
+
+from datetime import datetime
+
+import xrft
+import finufft
+
+
+class FFTAnalyser():
+    
+    def __init__(self) -> None:
+        pass
+    
+    def fft(self, dataArray, **kwargs):
+        return xrft.fft(dataArray, **kwargs)
+    
+    def ifft(self, dataArray, **kwargs):
+        return xrft.ifft(dataArray, **kwargs)
+    
+    def fft_nutou(self, dataArray, modeNum):
+        
+        data = dataArray.to_numpy()
+        data = data.astype('complex128')
+        
+        time = dataArray[dataArray.dims[0]].to_numpy()
+        
+        if isinstance(time[0], type(np.datetime64(500,'s'))):
+            time = time.astype(float)
+            time = time - time[0]
+            freqUpLim = 1 / np.min(np.abs(time - np.roll(time, 1))) * 1e9
+        else:
+            time = time.astype(float)
+            time = time - time[0]
+            freqUpLim = 1 / np.min(np.abs(time - np.roll(time, 1)))
+            
+        print(freqUpLim)
+        
+        time = time / time.max() * 2 * np.pi
+
+        # calculate the transform
+        res = xr.DataArray(
+            data=finufft.nufft1d1(time, data, modeNum),
+            dims=['freq'],
+            coords={
+                "freq":np.linspace(-freqUpLim/2, freqUpLim/2, modeNum)
+            }
+        )
+
+        return res
+    
+    def ifft_nutou(self, dataArray, modeNum):
+        pass
+        
\ No newline at end of file