fixed error

alphamind/analysis/factoranalysis.py

@@ -7,11 +7,13 @@ Created on 2017-5-25
 
 from typing import Optional
 from typing import Tuple
+from typing import Union
 import numpy as np
 import pandas as pd
 from alphamind.data.standardize import standardize
 from alphamind.data.winsorize import winsorize_normal
 from alphamind.portfolio.constraints import Constraints
+from alphamind.portfolio.constraints import LinearConstraints
 from alphamind.portfolio.longshortbulder import long_short_build
 from alphamind.portfolio.rankbuilder import rank_build
 from alphamind.portfolio.linearbuilder import linear_build
@@ -60,7 +62,7 @@ def factor_analysis(factors: pd.DataFrame,
 def er_portfolio_analysis(er: np.ndarray,
                           industry: np.ndarray,
                           dx_return: np.ndarray,
-                          constraints: Optional[Constraints]=None,
+                          constraints: Optional[Union[LinearConstraints, Constraints]]=None,
                           detail_analysis=True,
                           benchmark: Optional[np.ndarray] = None,
                           is_tradable: Optional[np.ndarray] = None,

alphamind/api.py

@@ -14,6 +14,10 @@ from alphamind.data.engines.universe import Universe
 from alphamind.data.processing import factor_processing
 
 from alphamind.portfolio.constraints import Constraints
+from alphamind.portfolio.constraints import LinearConstraints
+from alphamind.portfolio.constraints import BoundaryType
+from alphamind.portfolio.constraints import BoundaryDirection
+from alphamind.portfolio.constraints import create_box_bounds
 from alphamind.portfolio.evolver import evolve_positions
 
 from alphamind.data.engines.sqlengine import risk_styles
@@ -58,6 +62,10 @@ __all__ = [
     'Universe',
     'factor_processing',
     'Constraints',
+    'LinearConstraints',
+    'BoundaryType',
+    'BoundaryDirection',
+    'create_box_bounds',
     'evolve_positions',
     'risk_styles',
     'industry_styles',

alphamind/portfolio/constraints.py

@@ -53,7 +53,7 @@ class BoundaryImpl(object):
         if self.b_type == BoundaryType.ABSOLUTE:
             return self.val + center
         else:
-            pyFinAssert(center > 0., ValueError, "relative bounds only support positive back bone value")
+            pyFinAssert(center >= 0., ValueError, "relative bounds only support positive back bone value")
             return self.val * center
 
 
@@ -72,7 +72,7 @@ class BoxBoundary(object):
 
 
 def create_box_bounds(names: List[str],
-                      b_type: BoundaryType,
+                      b_type: Union[Iterable[BoundaryType], BoundaryType],
                       l_val: Union[Iterable[float], float],
                       u_val: Union[Iterable[float], float]) -> Dict[str, BoxBoundary]:
     """
@@ -80,6 +80,9 @@ def create_box_bounds(names: List[str],
     """
     bounds = dict()
 
+    if not hasattr(b_type, '__iter__'):
+        b_type = np.array([b_type] * len(names))
+
     if not hasattr(l_val, '__iter__'):
         l_val = np.array([l_val] * len(names))
 
@@ -88,10 +91,10 @@ def create_box_bounds(names: List[str],
 
     for i, name in enumerate(names):
         lower = BoundaryImpl(BoundaryDirection.LOWER,
-                             b_type,
+                             b_type[i],
                              l_val[i])
         upper = BoundaryImpl(BoundaryDirection.UPPER,
-                             b_type,
+                             b_type[i],
                              u_val[i])
         bounds[name] = BoxBoundary(lower, upper)
     return bounds
@@ -122,6 +125,7 @@ class LinearConstraints(object):
             upper_bounds.append(u)
         return np.array(lower_bounds), np.array(upper_bounds)
 
+    @property
     def risk_exp(self) -> np.ndarray:
         return self.cons_mat[self.names].values