Adds exact_values example

Author: nannau

examples/exact_values_example_1D.py

@@ -0,0 +1,50 @@
+from pykrige.ok import OrdinaryKriging
+import matplotlib.pyplot as plt
+import numpy as np
+
+plt.style.use("ggplot")
+
+np.random.seed(42)
+
+x = np.linspace(0, 12.5, 50)
+xpred = np.linspace(0, 12.5, 393)
+y = np.sin(x) * np.exp(-0.25 * x) + np.random.normal(-0.25, 0.25, 50)
+
+# compare OrdinaryKriging as an exact and non exact interpolator
+uk = OrdinaryKriging(
+    x, np.zeros(x.shape), y, variogram_model="linear", exact_values=False
+)
+uk_exact = OrdinaryKriging(x, np.zeros(x.shape), y, variogram_model="linear")
+
+y_pred, y_std = uk.execute("grid", xpred, np.array([0.0]), backend="loop")
+y_pred_exact, y_std_exact = uk_exact.execute(
+    "grid", xpred, np.array([0.0]), backend="loop"
+)
+
+
+y_pred = np.squeeze(y_pred)
+y_std = np.squeeze(y_std)
+
+y_pred_exact = np.squeeze(y_pred_exact)
+y_std_exact = np.squeeze(y_std_exact)
+
+
+fig, ax = plt.subplots(1, 1, figsize=(10, 4))
+
+ax.scatter(x, y, label="Input Data")
+ax.plot(xpred, y_pred_exact, label="Exact Prediction")
+ax.plot(xpred, y_pred, label="Non Exact Prediction")
+
+ax.fill_between(
+    xpred,
+    y_pred - 3 * y_std,
+    y_pred + 3 * y_std,
+    alpha=0.3,
+    label="Confidence interval",
+)
+ax.legend(loc=9)
+ax.set_ylim(-1.8, 1.3)
+ax.legend(loc=9)
+plt.xlabel("X")
+plt.ylabel("Field")
+plt.show()