def _start(self, app_context, **kwargs):
self.length = self.get_stg_config_value("length", 10)
self.bars = [
self.app_context.inst_data_mgr.get_series("Bar.%s.Time.300" % i)
for i in self.app_context.app_config.instrument_ids
]
for bar in self.bars:
bar.start(app_context)
self.opens = MakeVector(self.bars, input_key='Open')
self.volumes = MakeVector(self.bars, input_key="Volume")
self.rank_opens = Rank(self.bars, input_key='open')
self.rank_opens.start(app_context)
self.rank_volumes = Rank(self.bars, input_key='Volume')
self.rank_volumes.start(app_context)
#
self.pair_correlation = PairCorrelation(self.rank_opens,
self.rank_volumes,
length=self.length)
self.pair_correlation.start(app_context)
super(AlphaFormula3, self)._start(app_context, **kwargs)
def test_name(self):
bar = self.app_context.inst_data_mgr.get_series("bar")
bar.start(self.app_context)
sma3 = SMA(inputs=bar, input_keys='close', length=3)
sma20 = SMA(inputs=bar, input_keys='close', length=20)
sma50 = SMA(inputs=bar, input_keys='close', length=50)
sma3.start(self.app_context)
sma20.start(self.app_context)
sma50.start(self.app_context)
rank = Rank(inputs=[sma3, sma20, sma50], input_keys='close')
rank.start(self.app_context)
self.assertEquals(
"Rank(SMA(bar[close],length=3)[close],SMA(bar[close],length=20)[close],SMA(bar[close],length=50)[close],ascending=True)",
rank.name)
bar0 = self.app_context.inst_data_mgr.get_series("bar0")
bar1 = self.app_context.inst_data_mgr.get_series("bar1")
bar2 = self.app_context.inst_data_mgr.get_series("bar2")
bar3 = self.app_context.inst_data_mgr.get_series("bar3")
bar0.start(self.app_context)
bar1.start(self.app_context)
bar2.start(self.app_context)
bar3.start(self.app_context)
barlist = [bar0, bar1, bar2, bar3]
avg = Average(inputs=barlist, input_keys='close')
gssum = GSSum(inputs=barlist, input_keys='close')
basket = MakeVector(inputs=barlist, input_keys='close')
# TODO: the name printed by pipeline now break the "parse" machnism so we have to review it
self.assertEquals(
"Average(bar0[close],bar1[close],bar2[close],bar3[close],length=1)",
avg.name)
self.assertEquals(
"Sum(bar0[close],bar1[close],bar2[close],bar3[close],length=1)",
gssum.name)
self.assertEquals(
"MakeVector(bar0[close],bar1[close],bar2[close],bar3[close],length=1)",
basket.name)
bar4 = self.app_context.inst_data_mgr.get_series("bar4")
bar5 = self.app_context.inst_data_mgr.get_series("bar5")
bar6 = self.app_context.inst_data_mgr.get_series("bar6")
bar7 = self.app_context.inst_data_mgr.get_series("bar7")
basket2 = MakeVector(inputs=[bar4, bar5, bar6, bar7],
input_keys='close')
self.assertEquals(
"MakeVector(bar4[close],bar5[close],bar6[close],bar7[close],length=1)",
basket2.name)
cross_basket_spread = Minus(inputs=[basket2, basket])
self.assertEquals(
"Minus(MakeVector(bar4[close],bar5[close],bar6[close],bar7[close],length=1)[close],MakeVector(bar0[close],bar1[close],bar2[close],bar3[close],length=1)[close],length=1)",
cross_basket_spread.name)
def test_name(self):
bar = self.app_context.inst_data_mgr.get_series("bar")
bar.start(self.app_context)
sma3 = SMA(bar, input_key='close', length=3)
sma20 = SMA(bar, input_key='close', length=20)
sma50 = SMA(bar, input_key='close', length=50)
sma3.start(self.app_context)
sma20.start(self.app_context)
sma50.start(self.app_context)
rank = Rank([sma3, sma20, sma50], input_key='close')
rank.start(self.app_context)
self.assertEquals(
"Rank(SMA('bar',close,3),SMA('bar',close,20),SMA('bar',close,50),close)",
rank.name)
bar0 = self.app_context.inst_data_mgr.get_series("bar0")
bar1 = self.app_context.inst_data_mgr.get_series("bar1")
bar2 = self.app_context.inst_data_mgr.get_series("bar2")
bar3 = self.app_context.inst_data_mgr.get_series("bar3")
bar0.start(self.app_context)
bar1.start(self.app_context)
bar2.start(self.app_context)
bar3.start(self.app_context)
barlist = [bar0, bar1, bar2, bar3]
avg = Average([bar0, bar1, bar2, bar3], input_key='close')
gssum = GSSum([bar0, bar1, bar2, bar3], input_key='close')
basket = MakeVector([bar0, bar1, bar2, bar3], input_key='close')
# TODO: the name printed by pipeline now break the "parse" machnism so we have to review it
self.assertEquals("Average('bar0','bar1','bar2','bar3',close)",
avg.name)
self.assertEquals("Sum('bar0','bar1','bar2','bar3',close)", gssum.name)
self.assertEquals("MakeVector('bar0','bar1','bar2','bar3',close)",
basket.name)
bar4 = self.app_context.inst_data_mgr.get_series("bar4")
bar5 = self.app_context.inst_data_mgr.get_series("bar5")
bar6 = self.app_context.inst_data_mgr.get_series("bar6")
bar7 = self.app_context.inst_data_mgr.get_series("bar7")
basket2 = MakeVector([bar4, bar5, bar6, bar7], input_key='close')
cross_basket_spread = Minus(basket2, basket)
def test_with_pair_corr_with_vec(self):
bar0 = self.app_context.inst_data_mgr.get_series("bar0")
bar1 = self.app_context.inst_data_mgr.get_series("bar1")
bar2 = self.app_context.inst_data_mgr.get_series("bar2")
bar3 = self.app_context.inst_data_mgr.get_series("bar3")
bar0.start(self.app_context)
bar1.start(self.app_context)
bar2.start(self.app_context)
bar3.start(self.app_context)
vec0 = MakeVector([bar0, bar1], input_key='close')
vec1 = MakeVector([bar2, bar3], input_key='close')
vec0.start(self.app_context)
vec1.start(self.app_context)
pcorr = PairCorrelation(vec0, vec1, length=4, input_key=PipeLine.VALUE)
pcorr.start(self.app_context)
now = datetime.datetime.now()
x0 = np.array([80.0, 102.0, 101.0, 99.0])
x1 = np.array([102.0, 101.5, 99.0, 97.0])
x2 = np.array([94.0, 98.5, 91.0, 87.0])
x3 = np.array([104.5, 107.5, 97.0, 91.0])
ts = [now + datetime.timedelta(0, i * 3) for i in range(4)]
for i in range(4):
bar0.add({"timestamp": ts[i], "close": x0[i], "open": 0})
bar1.add({"timestamp": ts[i], "close": x1[i], "open": 0})
bar2.add({"timestamp": ts[i], "close": x2[i], "open": 0})
bar3.add({"timestamp": ts[i], "close": x3[i], "open": 0})
x = np.vstack([x0, x1])
y = np.vstack([x2, x3])
self.__np_assert_almost_equal(pcorr.now('value'), np.corrcoef(x, y))
def test_with_pair_corr_with_vec(self):
bar0 = self.app_context.inst_data_mgr.get_series("bar0")
bar1 = self.app_context.inst_data_mgr.get_series("bar1")
bar2 = self.app_context.inst_data_mgr.get_series("bar2")
bar3 = self.app_context.inst_data_mgr.get_series("bar3")
bar0.start(self.app_context)
bar1.start(self.app_context)
bar2.start(self.app_context)
bar3.start(self.app_context)
vec0 = MakeVector([bar0, bar1], input_key='close')
vec1 = MakeVector([bar2, bar3], input_key='close')
vec0.start(self.app_context)
vec1.start(self.app_context)
pcorr = PairCorrelation(vec0, vec1, length=4, input_key=PipeLine.VALUE)
pcorr.start(self.app_context)
now = datetime.datetime.now()
x0 = np.array([80.0, 102.0, 101.0, 99.0 ])
x1 = np.array([102.0, 101.5, 99.0, 97.0])
x2 = np.array([94.0, 98.5, 91.0, 87.0])
x3 = np.array([104.5, 107.5, 97.0, 91.0])
ts = [now + datetime.timedelta(0, i*3) for i in range(4)]
for i in range(4):
bar0.add({"timestamp": ts[i], "close": x0[i], "open": 0})
bar1.add({"timestamp": ts[i], "close": x1[i], "open": 0})
bar2.add({"timestamp": ts[i], "close": x2[i], "open": 0})
bar3.add({"timestamp": ts[i], "close": x3[i], "open": 0})
x = np.vstack([x0, x1])
y = np.vstack([x2, x3])
self.__np_assert_almost_equal(pcorr.now('value'), np.corrcoef(x, y))
def test_sync(self):
bar0 = self.app_context.inst_data_mgr.get_series("bar0")
bar1 = self.app_context.inst_data_mgr.get_series("bar1")
bar2 = self.app_context.inst_data_mgr.get_series("bar2")
bar3 = self.app_context.inst_data_mgr.get_series("bar3")
bar4 = self.app_context.inst_data_mgr.get_series("bar4")
bar5 = self.app_context.inst_data_mgr.get_series("bar5")
bar6 = self.app_context.inst_data_mgr.get_series("bar6")
bar7 = self.app_context.inst_data_mgr.get_series("bar7")
bar0.start(self.app_context)
bar1.start(self.app_context)
bar2.start(self.app_context)
bar3.start(self.app_context)
bar4.start(self.app_context)
bar5.start(self.app_context)
bar6.start(self.app_context)
bar7.start(self.app_context)
basket = MakeVector(inputs=[bar0, bar1, bar2, bar3],
input_keys='close')
basket2 = MakeVector(inputs=[bar4, bar5, bar6, bar7],
input_keys='close')
basket.start(self.app_context)
basket2.start(self.app_context)
basket_open = MakeVector(inputs=[bar0, bar1, bar2, bar3],
input_keys='open')
basket_open2 = MakeVector(inputs=[bar4, bar5, bar6, bar7],
input_keys='open')
cross_basket_spread = Minus(inputs=[basket2, basket],
input_keys=PipeLine.VALUE)
basket_open.start(self.app_context)
basket_open2.start(self.app_context)
cross_basket_spread.start(self.app_context)
nan_arr = np.empty([1, 4])
nan_arr[:] = np.nan
t1 = 1
bar0.add(data={"timestamp": t1, "close": 80.0, "open": 0})
self.__np_assert_almost_equal(nan_arr, basket.now()["value"])
bar1.add(data={"timestamp": t1, "close": 95.0, "open": 0})
self.__np_assert_almost_equal(nan_arr, basket.now()["value"])
bar2.add(data={"timestamp": t1, "close": 102.0, "open": 0})
self.__np_assert_almost_equal(nan_arr, basket.now()["value"])
sync_vec = np.array([[80.0, 95.0, 102.0, 105.0]])
bar3.add(data={"timestamp": t1, "close": 105.0, "open": 0})
self.__np_assert_almost_equal(sync_vec, basket.now()["value"])
bar4.add(data={"timestamp": t1, "close": 102.0, "open": 0})
bar5.add(data={"timestamp": t1, "close": 95.0, "open": 0})
bar6.add(data={"timestamp": t1, "close": 107.0, "open": 0})
bar7.add(data={"timestamp": t1, "close": 101.0, "open": 0})
sync_vec2 = np.array([[102.0, 95.0, 107.0, 101.0]])
self.__np_assert_almost_equal(sync_vec2, basket2.now()["value"])
target_spread = np.array([[22.0, 0.0, 5.0, -4.0]])
self.__np_assert_almost_equal(target_spread,
cross_basket_spread.now()["value"])
self.__np_assert_almost_equal(sync_vec, basket.now()["value"])
def test_sync(self):
bar0 = self.app_context.inst_data_mgr.get_series("bar0")
bar1 = self.app_context.inst_data_mgr.get_series("bar1")
bar2 = self.app_context.inst_data_mgr.get_series("bar2")
bar3 = self.app_context.inst_data_mgr.get_series("bar3")
bar4 = self.app_context.inst_data_mgr.get_series("bar4")
bar5 = self.app_context.inst_data_mgr.get_series("bar5")
bar6 = self.app_context.inst_data_mgr.get_series("bar6")
bar7 = self.app_context.inst_data_mgr.get_series("bar7")
bar0.start(self.app_context)
bar1.start(self.app_context)
bar2.start(self.app_context)
bar3.start(self.app_context)
bar4.start(self.app_context)
bar5.start(self.app_context)
bar6.start(self.app_context)
bar7.start(self.app_context)
basket = MakeVector([bar0, bar1, bar2, bar3], input_key='close')
basket2 = MakeVector([bar4, bar5, bar6, bar7], input_key='close')
basket.start(self.app_context)
basket2.start(self.app_context)
basket_open = MakeVector([bar0, bar1, bar2, bar3], input_key='open')
basket_open2 = MakeVector([bar4, bar5, bar6, bar7], input_key='open')
cross_basket_spread = Minus(basket2, basket, input_key=PipeLine.VALUE)
basket_open.start(self.app_context)
basket_open2.start(self.app_context)
cross_basket_spread.start(self.app_context)
nan_arr = np.empty([1,4])
nan_arr[:] = np.nan
t1 = datetime.datetime.now()
bar0.add({"timestamp": t1, "close": 80.0, "open": 0})
# self.assertListEqual(nan_arr.tolist(), basket.now()["value"])
self.__np_assert_almost_equal(nan_arr, np.array(basket.now()["value"]))
bar1.add({"timestamp": t1, "close": 95.0, "open": 0})
# self.assertListEqual(nan_arr.tolist(), basket.now()["value"])
self.__np_assert_almost_equal(nan_arr, basket.now()["value"])
bar2.add({"timestamp": t1, "close": 102.0, "open": 0})
# self.assertListEqual(nan_arr.tolist(), basket.now()["value"])
self.__np_assert_almost_equal(nan_arr, np.array(basket.now()["value"]))
# sync_vec = np.array([[80.0, 95.0, 102.0, 105.0]])
sync_vec = [[80.0, 95.0, 102.0, 105.0]]
bar3.add({"timestamp": t1, "close": 105.0, "open": 0})
# self.__np_assert_almost_equal(sync_vec, basket.now()["value"])
self.assertAlmostEqual(sync_vec, basket.now()["value"])
bar4.add({"timestamp": t1, "close": 102.0, "open": 0})
bar5.add({"timestamp": t1, "close": 95.0, "open": 0})
bar6.add({"timestamp": t1, "close": 107.0, "open": 0})
bar7.add({"timestamp": t1, "close": 101.0, "open": 0})
# sync_vec2 = np.array([[102.0, 95.0, 107.0, 101.0]])
sync_vec2 = [[102.0, 95.0, 107.0, 101.0]]
self.assertAlmostEqual(sync_vec2, basket2.now()["value"])
# self.__np_assert_almost_equal(sync_vec2, basket2.now()["value"])
# target_spread = np.array([[22.0, 0.0, 5.0, -4.0]])
target_spread = [[22.0, 0.0, 5.0, -4.0]]
self.assertAlmostEqual(target_spread, cross_basket_spread.now()["value"])
self.assertAlmostEqual(sync_vec, basket.now()["value"])
