%matplotlib widget
import matplotlib.pyplot as plt
plt.ioff()
# turn of warnings
import warnings
warnings.filterwarnings('ignore')
import numpy as np
import gstools as gs
# synthetic condtions with a drift
drift_model = gs.Gaussian(dim=1, len_scale=4)
drift = gs.SRF(drift_model, seed=1010)
cond_pos = [0.3, 1.9, 1.1, 3.3, 4.7]
ext_drift = drift(cond_pos)
cond_val = ext_drift * 2 + 1
# resulting grid
gridx = np.linspace(0.0, 15.0, 151)
grid_drift = drift(gridx)
# kriging
model = gs.Gaussian(dim=1, var=2, len_scale=4)
krig = gs.krige.ExtDrift(model, cond_pos, cond_val, ext_drift)
krig(gridx, ext_drift=grid_drift)
ax = krig.plot()
ax.scatter(cond_pos, cond_val, color="k", zorder=10, label="Conditions")
ax.plot(gridx, grid_drift, label="drift")
ax.legend()
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#krig2 = gs.krige.Ordinary(model, cond_pos, cond_val)
#krig2(gridx)
#ax = krig2.plot(ax=ax)