"""
Fit Variogram with automatic binning
------------------------------------
"""

import numpy as np

import gstools as gs

###############################################################################
# Generate a synthetic field with an exponential model.

x = np.random.RandomState(19970221).rand(1000) * 100.0
y = np.random.RandomState(20011012).rand(1000) * 100.0
model = gs.Exponential(dim=2, var=2, len_scale=8)
srf = gs.SRF(model, mean=0, seed=19970221)
field = srf((x, y))
print(field.var())
###############################################################################
# Estimate the variogram of the field with automatic binning.

bin_center, gamma = gs.vario_estimate((x, y), field)
print("estimated bin number:", len(bin_center))
print("maximal bin distance:", max(bin_center))

###############################################################################
# Fit the variogram with a stable model (no nugget fitted).

fit_model = gs.Stable(dim=2)
fit_model.fit_variogram(bin_center, gamma, nugget=False)
print(fit_model)

###############################################################################
# Plot the fitting result.

ax = fit_model.plot(x_max=max(bin_center))
ax.scatter(bin_center, gamma)