Initial commit

examples/README.txt

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+.. _general_examples:
+
+General examples
+================
+
+Introductory examples.

examples/plot_classifier.py

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+"""
+============================
+Plotting Template Classifier
+============================
+
+An example plot of :class:`bayesclass.template.TemplateClassifier`
+"""
+import numpy as np
+from matplotlib import pyplot as plt
+from bayesclass import TemplateClassifier
+
+X = [[0, 0], [1, 1]]
+y = [0, 1]
+clf = TemplateClassifier()
+clf.fit(X, y)
+
+rng = np.random.RandomState(13)
+X_test = rng.rand(500, 2)
+y_pred = clf.predict(X_test)
+
+X_0 = X_test[y_pred == 0]
+X_1 = X_test[y_pred == 1]
+
+
+p0 = plt.scatter(0, 0, c="red", s=100)
+p1 = plt.scatter(1, 1, c="blue", s=100)
+
+ax0 = plt.scatter(X_0[:, 0], X_0[:, 1], c="crimson", s=50)
+ax1 = plt.scatter(X_1[:, 0], X_1[:, 1], c="deepskyblue", s=50)
+
+leg = plt.legend(
+    [p0, p1, ax0, ax1],
+    ["Point 0", "Point 1", "Class 0", "Class 1"],
+    loc="upper left",
+    fancybox=True,
+    scatterpoints=1,
+)
+leg.get_frame().set_alpha(0.5)
+
+plt.xlabel("Feature 1")
+plt.ylabel("Feature 2")
+plt.xlim([-0.5, 1.5])
+
+plt.show()

examples/plot_template.py

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+"""
+===========================
+Plotting Template Estimator
+===========================
+
+An example plot of :class:`bayesclass.template.TemplateEstimator`
+"""
+import numpy as np
+from matplotlib import pyplot as plt
+from bayesclass import TemplateEstimator
+
+X = np.arange(100).reshape(100, 1)
+y = np.zeros((100,))
+estimator = TemplateEstimator()
+estimator.fit(X, y)
+plt.plot(estimator.predict(X))
+plt.show()

examples/plot_transformer.py

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+"""
+=============================
+Plotting Template Transformer
+=============================
+
+An example plot of :class:`bayesclass.template.TemplateTransformer`
+"""
+import numpy as np
+from matplotlib import pyplot as plt
+from bayesclass import TemplateTransformer
+
+X = np.arange(50, dtype=np.float).reshape(-1, 1)
+X /= 50
+estimator = TemplateTransformer()
+X_transformed = estimator.fit_transform(X)
+
+plt.plot(X.flatten(), label="Original Data")
+plt.plot(X_transformed.flatten(), label="Transformed Data")
+plt.title("Plots of original and transformed data")
+
+plt.legend(loc="best")
+plt.grid(True)
+plt.xlabel("Index")
+plt.ylabel("Value of Data")
+
+plt.show()