Interpolation with scipy SmoothSphereBivariateSpline

I want to use scipy.interpolate.SmoothSphereBivariateSpline  to interpolate the temperature on the map (I am not familiar with data interpolation, so this may not be a good choice, but I would like to let go of it).

Here is what I did:

• Download the data from the tsv file, which looks like this:

latitude longitude temperature city

30.22 120.14 39 2caves

30.26 120.13 39 3caves

30.23 120.13 39 Anlong

33.48 108.5 30 Anda

37.2 100.74 15 Anan

...

• in pandas

  data = pandas.read_table('temp.tsv')
  

• Get radians from lat, lon:

  theta = numpy.array(data.latitude) / 180 * numpy.pi # the lat, lon domain is safe here so
  phi = numpy.array(data.longitude) / 180 * numpy.pi  # I won't adjust for the output range
  temp = numpy.array(data.temperature)
  

• Submit them to scipy:

  lut = SmoothSphereBivariateSpline(theta, phi, temps)
  

Then the function throws a ValueError value:

ValueError: : nxest nyest . .

s : 1, 2, 3 7000, 8000, . , ?