Merge pull request #1247 from helmholtz-analytics/features/1246-Conti…

…nuous_Benchmarking_for_Preprocessing_Module

Continuous Benchmarking for the Preprocessing Module

benchmarks/cb/main.py

@@ -9,7 +9,9 @@
 from linalg import run_linalg_benchmarks
 from cluster import run_cluster_benchmarks
 from manipulations import run_manipulation_benchmarks
+from preprocessing import run_preprocessing_benchmarks
 
 run_linalg_benchmarks()
 run_cluster_benchmarks()
 run_manipulation_benchmarks()
+run_preprocessing_benchmarks()

benchmarks/cb/preprocessing.py

@@ -0,0 +1,55 @@
+# flake8: noqa
+import heat as ht
+from mpi4py import MPI
+from perun import monitor
+
+# we benchmark the in-place versions (`copy=False`) of the preprocessing functions
+# for each function, both the forward and the inverse transformation are applied
+
+
+@monitor()
+def apply_inplace_standard_scaler_and_inverse(X):
+    scaler = ht.preprocessing.StandardScaler(copy=False)
+    Y = scaler.fit_transform(X)
+    X = scaler.inverse_transform(Y)
+
+
+@monitor()
+def apply_inplace_min_max_scaler_and_inverse(X):
+    scaler = ht.preprocessing.MinMaxScaler(copy=False)
+    Y = scaler.fit_transform(X)
+    X = scaler.inverse_transform(Y)
+
+
+@monitor()
+def apply_inplace_max_abs_scaler_and_inverse(X):
+    scaler = ht.preprocessing.MaxAbsScaler(copy=False)
+    Y = scaler.fit_transform(X)
+    X = scaler.inverse_transform(Y)
+
+
+@monitor()
+def apply_inplace_robust_scaler_and_inverse(X):
+    scaler = ht.preprocessing.RobustScaler(copy=False)
+    Y = scaler.fit_transform(X)
+    X = scaler.inverse_transform(Y)
+
+
+@monitor()
+def apply_inplace_normalizer(X):
+    scaler = ht.preprocessing.Normalizer(copy=False)
+    scaler.fit_transform(X)
+
+
+def run_preprocessing_benchmarks():
+    n_data_points = 5000
+    n_features = 50
+    X = ht.random.randn(n_data_points, n_features, split=0)
+
+    apply_inplace_standard_scaler_and_inverse(X)
+    apply_inplace_min_max_scaler_and_inverse(X)
+    apply_inplace_max_abs_scaler_and_inverse(X)
+    apply_inplace_robust_scaler_and_inverse(X)
+    apply_inplace_normalizer(X)
+
+    del X