added simple settle benchmark

alphamind/benchmarks/benchmarks.py

@@ -12,28 +12,36 @@ from alphamind.benchmarks.data.winsorize import benchmark_winsorize_normal
 from alphamind.benchmarks.data.winsorize import benchmark_winsorize_normal_with_group
 from alphamind.benchmarks.portfolio.rankbuild import benchmark_build_rank
 from alphamind.benchmarks.portfolio.rankbuild import benchmark_build_rank_with_group
+from alphamind.benchmarks.settlement.simplesettle import benchmark_simple_settle
+from alphamind.benchmarks.settlement.simplesettle import benchmark_simple_settle_with_group
 
 
 if __name__ == '__main__':
 
-    # benchmark_neutralize(3000, 10, 1000)
-    # benchmark_neutralize(30, 10, 50000)
-    # benchmark_neutralize(50000, 50, 20)
-    # benchmark_standardize(3000, 10, 1000)
-    # benchmark_standardize_with_group(3000, 10, 1000, 30)
-    # benchmark_standardize(30, 10, 50000)
-    # benchmark_standardize_with_group(30, 10, 5000, 5)
-    # benchmark_standardize(50000, 50, 20)
-    # benchmark_standardize_with_group(50000, 50, 20, 50)
-    # benchmark_winsorize_normal(3000, 10, 1000)
-    # benchmark_winsorize_normal_with_group(3000, 10, 1000, 30)
-    # benchmark_winsorize_normal(30, 10, 50000)
-    # benchmark_winsorize_normal_with_group(30, 10, 5000, 5)
-    # benchmark_winsorize_normal(50000, 50, 20)
-    # benchmark_winsorize_normal_with_group(50000, 50, 20, 50)
+    benchmark_neutralize(3000, 10, 1000)
+    benchmark_neutralize(30, 10, 50000)
+    benchmark_neutralize(50000, 50, 20)
+    benchmark_standardize(3000, 10, 1000)
+    benchmark_standardize_with_group(3000, 10, 1000, 30)
+    benchmark_standardize(30, 10, 50000)
+    benchmark_standardize_with_group(30, 10, 5000, 5)
+    benchmark_standardize(50000, 50, 20)
+    benchmark_standardize_with_group(50000, 50, 20, 50)
+    benchmark_winsorize_normal(3000, 10, 1000)
+    benchmark_winsorize_normal_with_group(3000, 10, 1000, 30)
+    benchmark_winsorize_normal(30, 10, 50000)
+    benchmark_winsorize_normal_with_group(30, 10, 5000, 5)
+    benchmark_winsorize_normal(50000, 50, 20)
+    benchmark_winsorize_normal_with_group(50000, 50, 20, 50)
     benchmark_build_rank(3000, 1000, 300)
     benchmark_build_rank_with_group(3000, 1000, 10, 30)
     benchmark_build_rank(30, 50000, 3)
     benchmark_build_rank_with_group(30, 50000, 1, 3)
     benchmark_build_rank(50000, 20, 3000)
     benchmark_build_rank_with_group(50000, 20, 10, 300)
+    benchmark_simple_settle(3000, 10, 1000)
+    benchmark_simple_settle_with_group(3000, 10, 1000, 30)
+    benchmark_simple_settle(30, 10, 50000)
+    benchmark_simple_settle_with_group(30, 10, 5000, 5)
+    benchmark_simple_settle(50000, 50, 20)
+    benchmark_simple_settle_with_group(50000, 50, 20, 50)

alphamind/benchmarks/settlement/__init__.py

+# -*- coding: utf-8 -*-
+"""
+Created on 2017-4-28
+
+@author: cheng.li
+"""
\ No newline at end of file

alphamind/benchmarks/settlement/simplesettle.py

+# -*- coding: utf-8 -*-
+"""
+Created on 2017-4-28
+
+@author: cheng.li
+"""
+
+import datetime as dt
+import numpy as np
+import pandas as pd
+from alphamind.settlement.simplesettle import simple_settle
+
+
+def benchmark_simple_settle(n_samples: int, n_portfolios: int, n_loops: int) -> None:
+    print("-" * 60)
+    print("Starting simple settle benchmarking")
+    print("Parameters(n_samples: {0}, n_portfolios: {1}, n_loops: {2})".format(n_samples, n_portfolios, n_loops))
+
+    weights = np.random.randn(n_samples, n_portfolios)
+    ret_series = np.random.randn(n_samples)
+
+    start = dt.datetime.now()
+    for _ in range(n_loops):
+        calc_ret = simple_settle(weights, ret_series)
+    impl_model_time = dt.datetime.now() - start
+
+    print('{0:20s}: {1}'.format('Implemented model', impl_model_time))
+
+    start = dt.datetime.now()
+    ret_series.shape = -1, 1
+    for _ in range(n_loops):
+        exp_ret = (weights * ret_series).sum(axis=0)
+    benchmark_model_time = dt.datetime.now() - start
+
+    np.testing.assert_array_almost_equal(calc_ret, exp_ret)
+
+    print('{0:20s}: {1}'.format('Benchmark model', benchmark_model_time))
+
+
+def benchmark_simple_settle_with_group(n_samples: int, n_portfolios: int, n_loops: int, n_groups: int) -> None:
+    print("-" * 60)
+    print("Starting simple settle with group-by values benchmarking")
+    print("Parameters(n_samples: {0}, n_portfolios: {1}, n_loops: {2}, n_groups: {3})".format(n_samples, n_portfolios, n_loops, n_groups))
+
+    weights = np.random.randn(n_samples, n_portfolios)
+    ret_series = np.random.randn(n_samples)
+    groups = np.random.randint(n_groups, size=n_samples)
+
+    start = dt.datetime.now()
+    for _ in range(n_loops):
+        calc_ret = simple_settle(weights, ret_series, groups=groups)
+    impl_model_time = dt.datetime.now() - start
+
+    print('{0:20s}: {1}'.format('Implemented model', impl_model_time))
+
+    start = dt.datetime.now()
+    ret_series.shape = -1, 1
+    for _ in range(n_loops):
+        ret_mat = weights * ret_series
+        exp_ret = pd.DataFrame(ret_mat).groupby(groups).sum().values
+    benchmark_model_time = dt.datetime.now() - start
+
+    np.testing.assert_array_almost_equal(calc_ret, exp_ret)
+
+    print('{0:20s}: {1}'.format('Benchmark model', benchmark_model_time))
+
+
+if __name__ == '__main__':
+    benchmark_simple_settle(3000, 3, 1000)
+    benchmark_simple_settle_with_group(3000, 3, 1000, 30)