Merge pull request #230 from fasiondog/feature/tmpstock

开放 stock 属性可写，供使用外部数据源时使用

hikyuu/extend.py

@@ -1,9 +1,9 @@
 #
 # 对 C++ 引出类和函数进行扩展, pybind11 对小函数到导出效率不如 python 直接执行
 #
-
+import numpy as np
+import pandas as pd
 from datetime import *
-from .util.slice import list_getitem
 from .core import *
 
 # ------------------------------------------------------------------
@@ -293,94 +293,87 @@ def new_Query_init(self, start=0, end=None, ktype=Query.DAY, recover_type=Query.
 
 Query.__init__ = new_Query_init
 
+
 # ------------------------------------------------------------------
 # 增加转化为 np.array、pandas.DataFrame 的功能
 # ------------------------------------------------------------------
-
-try:
-    import numpy as np
-    import pandas as pd
-
-    def KData_to_np(kdata):
-        """转化为numpy结构数组"""
-        if kdata.get_query().ktype in ('DAY', 'WEEK', 'MONTH', 'QUARTER', 'HALFYEAR', 'YEAR'):
-            k_type = np.dtype(
-                {
-                    'names': ['datetime', 'open', 'high', 'low', 'close', 'amount', 'volume'],
-                    'formats': ['datetime64[D]', 'd', 'd', 'd', 'd', 'd', 'd']
-                }
-            )
-        else:
-            k_type = np.dtype(
-                {
-                    'names': ['datetime', 'open', 'high', 'low', 'close', 'amount', 'volume'],
-                    'formats': ['datetime64[ms]', 'd', 'd', 'd', 'd', 'd', 'd']
-                }
-            )
-        return np.array(
-            [(k.datetime.datetime(), k.open, k.high, k.low, k.close, k.amount, k.volume) for k in kdata], dtype=k_type
+def KData_to_np(kdata):
+    """转化为numpy结构数组"""
+    if kdata.get_query().ktype in ('DAY', 'WEEK', 'MONTH', 'QUARTER', 'HALFYEAR', 'YEAR'):
+        k_type = np.dtype(
+            {
+                'names': ['datetime', 'open', 'high', 'low', 'close', 'amount', 'volume'],
+                'formats': ['datetime64[D]', 'd', 'd', 'd', 'd', 'd', 'd']
+            }
         )
+    else:
+        k_type = np.dtype(
+            {
+                'names': ['datetime', 'open', 'high', 'low', 'close', 'amount', 'volume'],
+                'formats': ['datetime64[ms]', 'd', 'd', 'd', 'd', 'd', 'd']
+            }
+        )
+    return np.array(
+        [(k.datetime.datetime(), k.open, k.high, k.low, k.close, k.amount, k.volume) for k in kdata], dtype=k_type
+    )
 
-    def KData_to_df(kdata):
-        """转化为pandas的DataFrame"""
-        return pd.DataFrame.from_records(KData_to_np(kdata), index='datetime')
 
-    KData.to_np = KData_to_np
-    KData.to_df = KData_to_df
+def KData_to_df(kdata):
+    """转化为pandas的DataFrame"""
+    return pd.DataFrame.from_records(KData_to_np(kdata), index='datetime')
 
-    def PriceList_to_np(data):
-        """仅在安装了numpy模块时生效，转换为numpy.array"""
-        return np.array(data, dtype='d')
 
-    def PriceList_to_df(data):
-        """仅在安装了pandas模块时生效，转换为pandas.DataFrame"""
-        return pd.DataFrame(data.to_np(), columns=('Value', ))
+KData.to_np = KData_to_np
+KData.to_df = KData_to_df
 
-    PriceList.to_np = PriceList_to_np
-    PriceList.to_df = PriceList_to_df
 
-    def DatetimeList_to_np(data):
-        """仅在安装了numpy模块时生效，转换为numpy.array"""
-        return np.array(data, dtype='datetime64[D]')
+def DatetimeList_to_np(data):
+    """仅在安装了numpy模块时生效，转换为numpy.array"""
+    return np.array(data, dtype='datetime64[D]')
 
-    def DatetimeList_to_df(data):
-        """仅在安装了pandas模块时生效，转换为pandas.DataFrame"""
-        return pd.DataFrame(data.to_np(), columns=('Datetime', ))
 
-    DatetimeList.to_np = DatetimeList_to_np
-    DatetimeList.to_df = DatetimeList_to_df
+def DatetimeList_to_df(data):
+    """仅在安装了pandas模块时生效，转换为pandas.DataFrame"""
+    return pd.DataFrame(data.to_np(), columns=('Datetime', ))
 
-    def TimeLine_to_np(data):
-        """转化为numpy结构数组"""
-        t_type = np.dtype({'names': ['datetime', 'price', 'vol'], 'formats': ['datetime64[ms]', 'd', 'd']})
-        return np.array([(t.date.datetime(), t.price, t.vol) for t in data], dtype=t_type)
 
-    def TimeLine_to_df(kdata):
-        """转化为pandas的DataFrame"""
-        return pd.DataFrame.from_records(TimeLine_to_np(kdata), index='datetime')
+DatetimeList.to_np = DatetimeList_to_np
+DatetimeList.to_df = DatetimeList_to_df
 
-    TimeLineList.to_np = TimeLine_to_np
-    TimeLineList.to_df = TimeLine_to_df
 
-    def TransList_to_np(data):
-        """转化为numpy结构数组"""
-        t_type = np.dtype(
-            {
-                'names': ['datetime', 'price', 'vol', 'direct'],
-                'formats': ['datetime64[ms]', 'd', 'd', 'd']
-            }
-        )
-        return np.array([(t.date.datetime(), t.price, t.vol, t.direct) for t in data], dtype=t_type)
+def TimeLine_to_np(data):
+    """转化为numpy结构数组"""
+    t_type = np.dtype({'names': ['datetime', 'price', 'vol'], 'formats': ['datetime64[ms]', 'd', 'd']})
+    return np.array([(t.date.datetime(), t.price, t.vol) for t in data], dtype=t_type)
+
+
+def TimeLine_to_df(kdata):
+    """转化为pandas的DataFrame"""
+    return pd.DataFrame.from_records(TimeLine_to_np(kdata), index='datetime')
+
+
+TimeLineList.to_np = TimeLine_to_np
+TimeLineList.to_df = TimeLine_to_df
+
+
+def TransList_to_np(data):
+    """转化为numpy结构数组"""
+    t_type = np.dtype(
+        {
+            'names': ['datetime', 'price', 'vol', 'direct'],
+            'formats': ['datetime64[ms]', 'd', 'd', 'd']
+        }
+    )
+    return np.array([(t.date.datetime(), t.price, t.vol, t.direct) for t in data], dtype=t_type)
+
 
-    def TransList_to_df(kdata):
-        """转化为pandas的DataFrame"""
-        return pd.DataFrame.from_records(TransList_to_np(kdata), index='datetime')
+def TransList_to_df(kdata):
+    """转化为pandas的DataFrame"""
+    return pd.DataFrame.from_records(TransList_to_np(kdata), index='datetime')
 
-    TransList.to_np = TransList_to_np
-    TransList.to_df = TransList_to_df
 
-except:
-    pass
+TransList.to_np = TransList_to_np
+TransList.to_df = TransList_to_df
 
 # ------------------------------------------------------------------
 # 增强 Parameter

hikyuu/indicator/indicator.py

@@ -62,30 +62,20 @@ def indicator_getitem(data, i):
 Indicator.__iter__ = indicator_iter
 
 
-try:
-    import numpy as np
-    import pandas as pd
-
-    def indicator_to_df(indicator):
-        """转化为pandas.DataFrame"""
-        if indicator.get_result_num() == 1:
-            return pd.DataFrame(indicator.to_np(), columns=[indicator.name])
-
-        data = {}
-        name = indicator.name
-        columns = []
-        for i in range(indicator.get_result_num()):
-            data[name + str(i)] = indicator.get_result(i)
-            columns.append(name + str(i + 1))
-        return pd.DataFrame(data, columns=columns)
-
-    Indicator.to_df = indicator_to_df
-
-except:
-    print(
-        "warning:can't import numpy or pandas lib, ",
-        "you can't use method Inidicator.to_np() and to_df!"
-    )
+def indicator_to_df(indicator):
+    """转化为pandas.DataFrame"""
+    if indicator.get_result_num() == 1:
+        return pd.DataFrame(indicator.to_np(), columns=[indicator.name])
+    data = {}
+    name = indicator.name
+    columns = []
+    for i in range(indicator.get_result_num()):
+        data[name + str(i)] = indicator.get_result(i)
+        columns.append(name + str(i + 1))
+    return pd.DataFrame(data, columns=columns)
+
+
+Indicator.to_df = indicator_to_df
 
 
 def concat_to_df(dates, ind_list, head_stock_code=True, head_ind_name=False):

hikyuu/test/MoneyManager.py

@@ -2,10 +2,10 @@
 # -*- coding: utf8 -*-
 # gb18030
 
-#===============================================================================
+# ===============================================================================
 # 作者：fasiondog
 # 历史：1）20130316, Added by fasiondog
-#===============================================================================
+# ===============================================================================
 
 import unittest
 
@@ -18,7 +18,7 @@ def __init__(self):
         self.set_param("n", 10)
         self._m_flag = False
 
-    def getBuyNumber(self, datetime, stock, price, risk):
+    def get_buy_num(self, datetime, stock, price, risk):
         if self._m_flag:
             return 10
         else:
@@ -44,14 +44,14 @@ def test_ConditionBase(self):
         self.assertEqual(p.get_param("n"), 10)
         p.set_param("n", 20)
         self.assertEqual(p.get_param("n"), 20)
-        self.assertEqual(p.getBuyNumber(Datetime(200101010000), stock, 10.0, 0.0), 20)
+        self.assertEqual(p.get_buy_num(Datetime(200101010000), stock, 10.0, 0.0), 20)
         p.reset()
-        self.assertEqual(p.getBuyNumber(Datetime(200101010000), stock, 10.0, 0.0), 10)
+        self.assertEqual(p.get_buy_num(Datetime(200101010000), stock, 10.0, 0.0), 10)
 
         p_clone = p.clone()
         self.assertEqual(p_clone.name, "MoneyManagerPython")
         self.assertEqual(p_clone.get_param("n"), 20)
-        self.assertEqual(p_clone.getBuyNumber(Datetime(200101010000), stock, 10, 0.0), 10)
+        self.assertEqual(p_clone.get_buy_num(Datetime(200101010000), stock, 10, 0.0), 10)
 
         p.set_param("n", 1)
         p_clone.set_param("n", 3)
@@ -63,18 +63,18 @@ def testCrtMM(self):
     pass
 
 
-def testgetBuyNumber(self, datetime, stock, price, risk):
+def testget_buy_num(self, datetime, stock, price, risk, part):
     return 10.0 if datetime == Datetime(200101010000) else 0.0
 
 
 class TestCrtMM(unittest.TestCase):
     def test_crt_mm(self):
-        p = crtMM(testCrtMM, params={'n': 10}, name="TestMM")
-        p.getBuyNumber = testgetBuyNumber
+        p = crtMM(testget_buy_num, testCrtMM, params={'n': 10}, name="TestMM")
+        p.tm = crtTM(Datetime(200101010000))
         self.assertEqual(p.name, "TestMM")
         stock = sm['sh000001']
-        self.assertEqual(p.getBuyNumber(p, Datetime(200101010000), stock, 1.0, 1.0), 10.0)
-        self.assertEqual(p.getBuyNumber(p, Datetime(200101020000), stock, 1.0, 1.0), 0.0)
+        self.assertEqual(p.get_buy_num(Datetime(200101010000), stock, 1.0, 1.0, SystemPart.MM), 10.0)
+        self.assertEqual(p.get_buy_num(Datetime(200101020000), stock, 1.0, 1.0, SystemPart.MM), 0.0)
 
         p_clone = p.clone()
         self.assertEqual(p_clone.name, "TestMM")
@@ -85,4 +85,4 @@ def suite():
 
 
 def suiteTestCrtMM():
-    return unittest.TestLoader().loadTestsFromTestCase(TestCrtMM)
+    return unittest.TestLoader().loadTestsFromTestCase(TestCrtMM)

hikyuu/test/Slippage.py

@@ -2,10 +2,10 @@
 # -*- coding: utf8 -*-
 # gb18030
 
-#===============================================================================
+# ===============================================================================
 # 作者：fasiondog
 # 历史：1）20130321, Added by fasiondog
-#===============================================================================
+# ===============================================================================
 
 import unittest
 
@@ -17,12 +17,12 @@ def __init__(self):
         super(SlippagePython, self).__init__("SlippagePython")
         self._x = 0
 
-    def getRealBuyPrice(self, datetime, price):
+    def get_real_buy_price(self, datetime, price):
         if self._x < 10:
             return 0.0
         return 1.0
 
-    def getRealSellPrice(self, datetime, price):
+    def get_real_sell_price(self, datetime, price):
         if self._x < 10:
             return 0.0
         return 1.0
@@ -43,14 +43,14 @@ class SlippageTest(unittest.TestCase):
     def test_SlippageBase(self):
         p = SlippagePython()
         self.assertEqual(p.name, "SlippagePython")
-        self.assertEqual(p.getRealBuyPrice(Datetime(200101010000), 1.0), 0.0)
-        self.assertEqual(p.getRealSellPrice(Datetime(200101010000), 1.0), 0.0)
+        self.assertEqual(p.get_real_buy_price(Datetime(200101010000), 1.0), 0.0)
+        self.assertEqual(p.get_real_sell_price(Datetime(200101010000), 1.0), 0.0)
 
         self.assertEqual(p._x, 0)
         p._x = 10
         self.assertEqual(p._x, 10)
-        self.assertEqual(p.getRealBuyPrice(Datetime(200101010000), 1.0), 1.0)
-        self.assertEqual(p.getRealSellPrice(Datetime(200101010000), 1.0), 1.0)
+        self.assertEqual(p.get_real_buy_price(Datetime(200101010000), 1.0), 1.0)
+        self.assertEqual(p.get_real_sell_price(Datetime(200101010000), 1.0), 1.0)
         p.reset()
         self.assertEqual(p._x, 0)
 
@@ -66,18 +66,16 @@ def test_crtSL_func(self):
     pass
 
 
-def test_getRealBuyPrice_func(self, datetime, price):
+def test_get_real_buy_price_func(self, datetime, price):
     return 10.0 if datetime == Datetime(200101010000) else 0.0
 
 
 class TestCrtSL(unittest.TestCase):
-    def test_crtSL(self):
-        p = crtSL(test_crtSL_func, params={'n': 10}, name="TestSL")
-        p.getRealBuyPrice = test_getRealBuyPrice_func
+    def test_crtSP(self):
+        p = crtSP(test_get_real_buy_price_func, test_crtSL_func, params={'n': 10}, name="TestSL")
         self.assertEqual(p.name, "TestSL")
-        self.assertEqual(p.getRealBuyPrice(p, Datetime(200101010000), 1.0), 10.0)
-        self.assertEqual(p.getRealBuyPrice(p, Datetime(200101020000), 1.0), 0.0)
-
+        self.assertEqual(p.get_real_buy_price(Datetime(200101010000), 1.0), 10.0)
+        self.assertEqual(p.get_real_buy_price(Datetime(200101020000), 1.0), 0.0)
         p_clone = p.clone()
         self.assertEqual(p_clone.name, "TestSL")
 
@@ -87,4 +85,4 @@ def suite():
 
 
 def suiteTestCrtSL():
-    return unittest.TestLoader().loadTestsFromTestCase(TestCrtSL)
+    return unittest.TestLoader().loadTestsFromTestCase(TestCrtSL)