Merge branch 'master' of https://github.com/wegamekinglc/alpha-mind

.travis.yml

@@ -37,15 +37,15 @@ install:
   - conda install pandas
   - conda install cython
   - conda install scikit-learn
-  - pip install coveralls
   - pip install cvxopt
   - pip install cvxpy
   - pip install simpleutils
-# command to run tests
+  - pip install coveralls
 script:
-  - python setup.py build_ext --inplace
+  - export NUMBA_DISABLE_JIT=1
+  - python setup.py build_ext --line_trace --inplace
   - coverage run --rcfile=./.coveragerc alphamind/tests/test_suite.py
   - coverage report --rcfile=./.coveragerc -i
   - coverage html --rcfile=./.coveragerc -i
 after_success:
-  - coveralls
\ No newline at end of file
+  - coveralls

README.md

-# Alpha - Mind
\ No newline at end of file
+# Alpha - Mind
+
+<table>
+<tr>
+  <td>Build Status</td>
+  <td>
+    <a href="https://travis-ci.org/wegamekinglc/alpha-mind">
+    <img src="https://travis-ci.org/wegamekinglc/alpha-mind.svg?branch=master" alt="travis build status" />
+    </a>
+  </td>
+</tr>
+<tr>
+  <td>Coverage</td>
+  <td><img src="https://coveralls.io/repos/github/wegamekinglc/alpha-mind/badge.svg?branch=master" alt="coverage" /></td>
+</tr>
+</table>

alphamind/data/standardize.py

@@ -22,13 +22,3 @@ def standardize(x: np.ndarray, groups: np.ndarray=None, ddof=1) -> np.ndarray:
         return (x - mean_values) / std_values
     else:
         return (x - simple_mean(x, axis=0)) / simple_std(x, axis=0)
-
-
-if __name__ == '__main__':
-    import pandas as pd
-
-    df = pd.read_csv('d:/test_data.csv', index_col=0)
-
-    x = df.values
-    groups = df.index.values.astype(int)
-    standardize(x, groups)

alphamind/data/winsorize.py

@@ -63,15 +63,3 @@ def winsorize_normal(x: np.ndarray, num_stds: int = 3, groups: np.ndarray = None
         mean_values = simple_mean(x, axis=0)
         res = mask_values_1d(x, mean_values, std_values, num_stds)
     return res
-
-
-if __name__ == '__main__':
-    x = np.random.randn(3000, 10)
-    groups = np.random.randint(0, 20, size=3000)
-
-    import datetime as dt
-
-    start = dt.datetime.now()
-    for _ in range(3000):
-        winsorize_normal(x, 2, groups)
-    print(dt.datetime.now() - start)

alphamind/portfolio/percentbuilder.py

@@ -46,4 +46,3 @@ def percent_build(er: np.ndarray, percent: float, groups: np.ndarray=None) -> np
             use_rank = int(percent * len(neg_er))
             set_value(weights, ordering[:use_rank], 1.)
         return weights
-

alphamind/portfolio/rankbuilder.py

@@ -42,14 +42,3 @@ def rank_build(er: np.ndarray, use_rank: int, groups: np.ndarray=None) -> np.nda
             ordering = neg_er.argsort(axis=0)
             set_value(weights, ordering[:use_rank], 1.)
         return weights
-
-
-if __name__ == '__main__':
-    n_sample = 6
-    n_groups = 3
-
-    x = np.random.randn(n_sample)
-    groups = np.array([1, 1, 2, 1, 0, 2])
-    print(groups)
-    print(groupby(groups))
-    print(rank_build(x, 1, groups))
\ No newline at end of file

alphamind/settlement/simplesettle.py

@@ -24,11 +24,3 @@ def simple_settle(weights: np.ndarray, ret_series: np.ndarray, groups: np.ndarra
         if ret_mat.ndim == 1:
             ret_mat = ret_mat.reshape((-1, 1))
         return simple_sum(ret_mat, axis=0)
-
-
-if __name__ == '__main__':
-    from alphamind.aggregate import group_mapping_test
-
-    s = np.random.randint(2, 5, size=6)
-    print(s)
-    print(group_mapping_test(s))
\ No newline at end of file