Update plot_usecase_exampleMuCuBo.py

examples/usecase/plot_usecase_exampleMuCuBo.py

@@ -11,7 +11,7 @@ multi class digit from sklearn, multivue
  - vue 2 gradiant of image in second direction
 
 """
-from __future__ import absolute_import
+
 import numpy as np
 import matplotlib.pyplot as plt
 from sklearn.model_selection import train_test_split
@@ -21,7 +21,29 @@ from multimodal.tests.data.get_dataset_path import get_dataset_path
 from multimodal.datasets.data_sample import MultiModalArray
 
 from multimodal.boosting.cumbo import MuCumboClassifier
-from usecase_function import plot_subplot
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib._color_data as mcd
+
+
+def plot_subplot(X, Y, Y_pred, vue, subplot, title):
+    cn = mcd.CSS4_COLORS
+    classes = np.unique(Y)
+    n_classes = len(np.unique(Y))
+    axs = plt.subplot(subplot[0],subplot[1],subplot[2])
+    axs.set_title(title)
+    #plt.scatter(X._extract_view(vue), X._extract_view(vue), s=40, c='gray',
+    #            edgecolors=(0, 0, 0))
+    for index, k in zip(range(n_classes), cn.keys()):
+         Y_class, = np.where(Y==classes[index])
+         Y_class_pred = np.intersect1d(np.where(Y_pred==classes[index])[0], np.where(Y_pred==Y)[0])
+         plt.scatter(X._extract_view(vue)[Y_class],
+                     X._extract_view(vue)[Y_class],
+                     s=40, c=cn[k], edgecolors='blue', linewidths=2, label="class real class: "+str(index)) #
+         plt.scatter(X._extract_view(vue)[Y_class_pred],
+                     X._extract_view(vue)[Y_class_pred],
+                     s=160, edgecolors='orange', linewidths=2, label="class prediction: "+str(index))
+
 
 
 if __name__ == '__main__':