np.searchsorted not working properly on netCDF4 array

np.searchsorted is not finding the right indexes but i think it is related to the type of data.

To me it looks like this function can't tell floats and strs apart but I can't convert the array to float.

 coord=Dataset(r"C:\\Users\\Admin\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\coordenadas.nc",'r')
 lat=coord.variables\['latitude'\]
 lon=coord.variables\['longitude'\]
 lat=np.array(lat,dtype=float)
 lon=np.array(lon,dtype=float)

this gives me back the error:

Traceback (most recent call last):

File "c:\\Users\\Admin\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\extract.py", line 41, in \<module\>

lat=np.array(lat,dtype=float)

^^^^^^^^^^^^^^^^^^^^^^^^^

TypeError: Variable.__array__() takes no arguments (1 given)

and when I try to make element I'm searching for into a float:

 coord=Dataset(r"C:\\Users\\Admin\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\coordenadas.nc",'r')
 lat=coord.variables\['latitude'\]
 lon=coord.variables\['longitude'\]
 x0=np.searchsorted(lat,float(x))
 y0=np.searchsorted(lon,float(y))

this doesn't give me an error back but gives me the last possible index which is incorrect what I've noticed is that for negative elements this last method works just fine.

If you get the error TypeError: Variable.array() takes no arguments (1 given),it is probably because you did not put [:] after the variable object.

Regarding the second part of your code snippet, it looks like you're trying to use the np.searchsorted function to find the index of a value in the lat and lon arrays that's closest to a given value x and y, respectively. However, the np.searchsorted function expects the input array to be sorted in ascending order, so you should make sure that lat and lon are sorted before calling np.searchsorted. Alternatively, you could use the np.argmin function to find the index of the element in lat and lon that's closest to x and y, respectively:

coord = Dataset(r"C:\\Users\\Admin\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\coordenadas.nc", 'r')
lat = coord.variables['latitude'][:]
lon = coord.variables['longitude'][:]
x0 = np.argmin(np.abs(lat - float(x)))
y0 = np.argmin(np.abs(lon - float(y)))

Note that I added [:] to the end of lat and lon to extract their values as NumPy arrays, instead of as netCDF4 variables.