diff --git a/ERA5_stitching.py b/ERA5_stitching.py
deleted file mode 100644
index daa5084..0000000
--- a/ERA5_stitching.py
+++ /dev/null
@@ -1,100 +0,0 @@
-import numpy as np
-import math
-import xarray as xr
-import matplotlib.pyplot as plt
-from scipy.spatial import cKDTree
-from scipy import interpolate
-import cartopy.crs as ccrs
-from datetime import datetime
-from netCDF4 import Dataset
-begin_time = datetime.now()
-import pandas as pd
-
-name = ["testneu1.nc", "testneu2.nc", "testneu3.nc", "testneu4.nc"]
-
-ds = xr.open_mfdataset(name, combine='by_coords', concat_dim="time")
-#res = Dataset(name)
-
-res1 = Dataset('testneu1.nc')
-# res2 = Dataset('testneu2.nc')
-# res3 = Dataset('testneu3.nc')
-res4 = Dataset('testneu4.nc')
-#print(res1.variables['time'][0])
-#print(res1.variables['time'][-1])
-
-start = int(res1.variables['time'][0])
-end = int(res4.variables['time'][-1])
-
-a = np.linspace(start, end, (end - start) + 1)
-
-ds = ds.assign_coords(time=a)
-
-
-
-
-
-res_comp = Dataset("testfull.nc")
-
-#ERAtime1 = res1.variables['time'][:]
-#ERAtime2 = res2.variables['time'][:]
-#ERAtime3 = res3.variables['time'][:]
-#ERAtime4 = res4.variables['time'][:]
-#ERAtemp1 = res1.variables['t'][:]
-#ERAtemp2 = res2.variables['t'][:]
-#ERAtemp3 = res3.variables['t'][:]
-#ERAtemp4 = res4.variables['t'][:]
-
-ERAtemp = ds.variables['z'][:].values
-ERAtime_sel = ds.variables['time'][:]
-
-ERAtemp_sel = ERAtemp[:, 6, 82, 21]
-
-ERAtime0 = res_comp.variables['time'][:]
-ERAtemp0 = res_comp.variables['z'][:]
-
-#ERAtemp1_sel = ERAtemp1[:, 6, 82, 21]
-#ERAtemp2_sel = ERAtemp2[:, 6, 82, 21]
-#ERAtemp3_sel = ERAtemp3[:, 6, 82, 21]
-#ERAtemp4_sel = ERAtemp4[:, 6, 82, 21]
-
-
-ERAtemp_sel = ERAtemp[:, 6, 82, 21]
-ERAtemp0_sel = ERAtemp0[:, 6, 82, 21]
-
-#print(ERAtime2[0])
-
-
-#ERAtime_sel = ds.variables['time'][:]
-ERAtimecomp_sel = res_comp.variables['time'][:]
-
-
-plt.plot(ERAtime_sel, ERAtemp_sel, 'rx')
-plt.plot(ERAtimecomp_sel, ERAtemp0_sel, 'k-')
-plt.show()
-
-
-
-
-
-
-#print("hier")
-#print(int(ds['time'][0]))
-#print(int(ds['time'][1]))
-#print(type(ds['time'][0]))
-
-#print(type(datetime(1900, 1, 1)))
-
-#print(ds['time'])
-
-
-# print(ds['time'])
-
-ds.to_netcdf('single_new2.nc')
-df = Dataset('single_new2.nc')
-
-
-#print(df.variables['z'][:])
-#print(df.variables['time'][:])
-
-
-