cleanup 2

w4k2 · Oct 25, 2023 · 7379adf · 7379adf
1 parent 519498f
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diff --git a/E1P_vis_real.py b/E1P_vis_real.py
@@ -1,11 +1,9 @@
 """
-E1 - scatterplot - rzeczywiste
+E1 - scatterplot - real-world streams
 """
 
 import matplotlib.pyplot as plt
 import numpy as np
-from sklearn.feature_selection import SelectKBest
-from sklearn.neural_network import MLPClassifier
 import utils
 import matplotlib
 from sklearn.decomposition import PCA
@@ -67,7 +65,6 @@
         X = X[perm]
         y = np.array(y)[perm]
 
-        #EH
         X[np.isnan(X)]=1
         X[np.isinf(X)]=1
         names = [n[:6] for n in utils.measure_labels[m_id]]

diff --git a/E1P_vis_semi.py b/E1P_vis_semi.py
@@ -1,5 +1,5 @@
 """
-E1 - scatterplot - semi
+E1 - scatterplot - semi-synthetic streams
 """
 
 import utils
@@ -45,7 +45,6 @@
             for drf_id, drf in enumerate(['nearest', 'cubic']):
                 X, y = res_iter[drf_id,:,:-1], res_iter[drf_id,:,-1]
 
-                #EH
                 X[np.isnan(X)]=1
                 names = [n[:6] for n in utils.measure_labels[m_id]]
 

diff --git a/E1P_vis_synthetic.py b/E1P_vis_synthetic.py
@@ -1,11 +1,10 @@
 """
-E1 - scatterplot - syntetyczne
+E1 - scatterplot - synthetic streams
 """
 
 import matplotlib.pyplot as plt
 import numpy as np
 from sklearn.feature_selection import SelectKBest
-from sklearn.neural_network import MLPClassifier
 import utils
 import matplotlib
 from sklearn.decomposition import PCA
@@ -40,7 +39,6 @@
         for drf_id, drf in enumerate(['sudd', 'inc', 'grad']):
             X, y = res_iter[drf_id,:,:-1], res_iter[drf_id,:,-1]
 
-            #EH
             X[np.isnan(X)]=1
             names = [n[:6] for n in utils.measure_labels[m_id]]
 

diff --git a/E1_extract_real.py b/E1_extract_real.py
@@ -1,5 +1,5 @@
 """
-Experiment 1 -- collect streams and metafetaures -- real-world
+Experiment 1 -- collect streams and metafetaures -- real-world streams
 """
 import numpy as np
 from pymfe.mfe import MFE

diff --git a/E1_extract_semi.py b/E1_extract_semi.py
@@ -1,5 +1,5 @@
 """
-Experiment 1 -- collect streams and metafetaures -- semi-synthetic
+Experiment 1 -- collect streams and metafetaures -- semi-synthetic streams
 """
 
 import numpy as np

diff --git a/E1_extract_synthetic.py b/E1_extract_synthetic.py
@@ -1,5 +1,5 @@
 """
-Experiment 1 -- collect streams and metafetaures -- synthetic
+Experiment 1 -- collect streams and metafetaures -- synthetic streams
 """
 
 import numpy as np

diff --git a/E2P_analyze_real.py b/E2P_analyze_real.py
@@ -1,5 +1,5 @@
 """
-Plot E2 - real
+Plot E2 - Visualize classification results for real-world streams
 """
 import numpy as np
 import matplotlib.pyplot as plt

diff --git a/E2P_analyze_semi.py b/E2P_analyze_semi.py
@@ -1,5 +1,5 @@
 """
-Plot E2 - semi
+Plot E2 - Visualize classification results for semi-synthetic streams
 """
 import numpy as np
 import matplotlib.pyplot as plt

diff --git a/E2P_analyze_synthetic.py b/E2P_analyze_synthetic.py
@@ -1,5 +1,5 @@
 """
-Plot E2 - synthetic
+Plot E2 - Visualize classification results for  synthetic streams
 """
 import numpy as np
 import matplotlib.pyplot as plt

diff --git a/E2_clf_real.py b/E2_clf_real.py
@@ -1,5 +1,5 @@
 """
-E2 - klasyfikacja rzeczywistych
+E2 - classification for real-world streams 
 """
 
 import numpy as np

diff --git a/E2_clf_semi.py b/E2_clf_semi.py
@@ -1,5 +1,5 @@
 """
-E2 - klasyfikacja semi
+E2 - classification for semi-synthetic streams
 """
 
 import numpy as np

diff --git a/E2_clf_synthetic.py b/E2_clf_synthetic.py
@@ -1,5 +1,5 @@
 """
-E2 - klasyfikacja syntetycznych
+E2 - classification for synthetic streams
 """
 
 import numpy as np
@@ -46,11 +46,8 @@
 
 for m_id, m in enumerate(measures):
     res = np.load('results/%s.npy' % m)
-    # print(res.shape) # drfs, reps, chunks, measures + label
 
     for d_id, res_drift in enumerate(res):
-        # print(res_drift.shape) # reps, chunks, measures + label
-
         for r_id, res_rep in enumerate(res_drift):
             #shuffle
             p = np.random.permutation(res_rep.shape[0])

diff --git a/E3P_vis_selection_real.py b/E3P_vis_selection_real.py
@@ -1,7 +1,6 @@
 """
 Plot.
-
-E3, E4 - selekcja k-best + ANOVA - real
+E3, E4 - Visualize -- select k-best + classification + f-test anova --- Real-world streams
 """
 
 import numpy as np
@@ -80,10 +79,8 @@ def sqspace(start, end, num):
 
 labels_measures = np.array(sum(labels_measures, []))
 
-# cols=np.array(['r','g','b','gold','purple'])
 cols=c
 
-
 fig, ax = plt.subplots(1,1,figsize=(9,9/1.618), sharex=True, sharey=True)
 
 start = np.zeros_like(anovas[0])

diff --git a/E3P_vis_selection_semi.py b/E3P_vis_selection_semi.py
@@ -1,7 +1,7 @@
 """
 Plot.
 
-E3, E4 - selekcja k-best + ANOVA - semi
+E3, E4 - Visualize -- select k-best + classification + f-test anova --- Semi-synthetic streams
 """
 
 import numpy as np

diff --git a/E3P_vis_selection_synthetic.py b/E3P_vis_selection_synthetic.py
@@ -1,7 +1,7 @@
 """
 Plot.
 
-E3, E4 - selekcja k-best + ANOVA - sythetic
+E3, E4 - Visualize -- select k-best + classification + f-test anova --- Semi-synthetic streams
 """
 
 import numpy as np

diff --git a/E3_clf_real_selection.py b/E3_clf_real_selection.py
@@ -1,5 +1,5 @@
 """
-E3, E4 - selekcja k-best + klasyfikacja + zapis f-test anova - real
+E3, E4 - select k-best + classification + f-test anova --- Real-world streams
 """
 import numpy as np
 from sklearn import clone

diff --git a/E3_clf_semi_selection.py b/E3_clf_semi_selection.py
@@ -1,5 +1,5 @@
 """
-E3, E4 - selekcja k-best + klasyfikacja + zapis f-test anova - semi
+E3, E4 - select k-best + classification + f-test anova --- semi-synthetic streams
 """
 import numpy as np
 from sklearn import clone

diff --git a/E3_clf_synthetic_selection.py b/E3_clf_synthetic_selection.py
@@ -1,5 +1,5 @@
 """
-E3, E4 - selekcja k-best + klasyfikacja + zapis f-test anova - syntetyczne
+E3, E4 - select k-best + classification + f-test anova --- synthetic streams
 """
 
 import numpy as np

diff --git a/E4P_vis_bar.py b/E4P_vis_bar.py
@@ -1,3 +1,6 @@
+"""
+Visualization for E4
+"""
 from matplotlib.lines import Line2D
 import numpy as np
 import matplotlib.pyplot as plt

diff --git a/E4_clf_real_v2.py b/E4_clf_real_v2.py
@@ -1,5 +1,5 @@
 """
-E4 - klasyfikacja rzeczywistych, ale tylko dla 17 wybranych metryk
+E4 - classification with reduced number of measures -- real-world streams
 """
 import numpy as np
 from sklearn import clone

diff --git a/E4_clf_semi_v2.py b/E4_clf_semi_v2.py
@@ -1,5 +1,5 @@
 """
-E4 - klasyfikacja semi, ale tylko dla 17 wybranych metryk
+E4 - classification with reduced number of measures -- semi-synthetic streams
 """
 import numpy as np
 from sklearn import clone

diff --git a/E4_clf_synthetic_v2.py b/E4_clf_synthetic_v2.py
@@ -1,5 +1,5 @@
 """
-E4 - klasyfikacja syntetycznych, ale tylko dla 17 wybranych metryk
+E4 - classification with reduced number of measures -- synthetic streams
 """
 
 import numpy as np

diff --git a/E5_cov_real.py b/E5_cov_real.py
@@ -1,7 +1,5 @@
 """
-Obliczenia + Plot.
-
-E5 - real
+E5 - experiment and presentation -- real-world streams
 """
 import utils 
 import numpy as np

diff --git a/E5_cov_semi.py b/E5_cov_semi.py
@@ -1,12 +1,9 @@
 """
-Obliczenia + Plot.
-
-E5 - semi
+E5 - experiment and presentation -- semi-synthetic streams
 """
 import utils 
 import numpy as np
 import matplotlib.pyplot as plt
-import time
 
 indexes = utils.selected2_indexes
 labels = utils.selected2_measure_names

diff --git a/E5_cov_syn.py b/E5_cov_syn.py
@@ -1,7 +1,5 @@
 """
-Obliczenia + Plot.
-
-E5 - sythetic
+E5 - experiment and presentation -- synthetic streams
 """
 import utils 
 import numpy as np