def test_drop(self):
'''Test node columns drop'''
node_obj = {
"id": "abc",
"type": "IndicatorNode",
"conf": self.conf,
"inputs": []
}
task = Task(node_obj)
inN = IndicatorNode(task)
o = inN.process([self._cudf_data])
msg = "bad error: df len %d is not right" % (len(o))
self.assertTrue(len(o) == 162, msg)
newConf = copy.deepcopy(self.conf)
newConf['remove_na'] = False
node_obj = {
"id": "abc",
"type": "IndicatorNode",
"conf": newConf,
"inputs": []
}
task = Task(node_obj)
inN = IndicatorNode(task)
o = inN.process([self._cudf_data])
msg = "bad error: df len %d is not right" % (len(o))
self.assertTrue(len(o) == 200, msg)
def test_indicator(self):
'''Test indicator node'''
conf = {
"indicators": [{
"function": "port_chaikin_oscillator",
"columns": ["high", "low", "close", "volume"],
"args": [10, 20]
}, {
"function": "port_bollinger_bands",
"columns": ["close"],
"args": [10],
"outputs": ["b1", "b2"]
}],
"remove_na":
True
}
node_obj = {
"id": "abc",
"type": "IndicatorNode",
"conf": conf,
"inputs": {}
}
task = Task(node_obj)
inN = IndicatorNode(task)
o = inN.process({'stock_in': self._cudf_data})['stock_out']
err, index_err = error_function_index(o['CH_OS_10_20'], self.gt1)
msg = "bad error %f\n" % (err, )
self.assertTrue(np.isclose(err, 0, atol=1e-6), msg)
msg = "bad error %f\n" % (index_err, )
self.assertTrue(np.isclose(index_err, 0, atol=1e-6), msg)
err, index_err = error_function_index(o['BO_BA_b1_10'], self.gt2)
msg = "bad error %f\n" % (err, )
self.assertTrue(np.isclose(err, 0, atol=1e-6), msg)
msg = "bad error %f\n" % (index_err, )
self.assertTrue(np.isclose(index_err, 0, atol=1e-6), msg)
err, index_err = error_function_index(o['BO_BA_b2_10'], self.gt3)
msg = "bad error %f\n" % (err, )
self.assertTrue(np.isclose(err, 0, atol=1e-6), msg)
msg = "bad error %f\n" % (index_err, )
self.assertTrue(np.isclose(index_err, 0, atol=1e-6), msg)
def test_colums(self):
'''Test node columns requirments'''
node_obj = {
"id": "abc",
"type": "IndicatorNode",
"conf": self.conf,
"inputs": {}
}
task = Task(node_obj)
inN = IndicatorNode(task)
out_cols = inN.columns_setup()
col = "indicator"
msg = "bad error: %s is missing" % (col)
self.assertTrue(col in inN.required['stock_in'], msg)
col = "high"
msg = "bad error: %s is missing" % (col)
self.assertTrue(col in inN.required['stock_in'], msg)
col = "low"
msg = "bad error: %s is missing" % (col)
self.assertTrue(col in inN.required['stock_in'], msg)
col = "close"
msg = "bad error: %s is missing" % (col)
self.assertTrue(col in inN.required['stock_in'], msg)
col = "volume"
msg = "bad error: %s is missing" % (col)
self.assertTrue(col in inN.required['stock_in'], msg)
col = "CH_OS_10_20"
msg = "bad error: %s is missing" % (col)
self.assertTrue(col in out_cols['stock_out'], msg)
col = "BO_BA_b1_10"
msg = "bad error: %s is missing" % (col)
self.assertTrue(col in out_cols['stock_out'], msg)
col = "BO_BA_b2_10"
msg = "bad error: %s is missing" % (col)
self.assertTrue(col in out_cols['stock_out'], msg)
def test_colums(self):
'''Test node columns requirments'''
node_obj = {
"id": "abc",
"type": "IndicatorNode",
"conf": self.conf,
"inputs": []
}
task = Task(node_obj)
inN = IndicatorNode(task)
col = "indicator"
msg = "bad error: %s is missing" % (col)
self.assertTrue(col in inN.required, msg)
col = "high"
msg = "bad error: %s is missing" % (col)
self.assertTrue(col in inN.required, msg)
col = "low"
msg = "bad error: %s is missing" % (col)
self.assertTrue(col in inN.required, msg)
col = "close"
msg = "bad error: %s is missing" % (col)
self.assertTrue(col in inN.required, msg)
col = "volume"
msg = "bad error: %s is missing" % (col)
self.assertTrue(col in inN.required, msg)
col = "CH_OS_10_20"
msg = "bad error: %s is missing" % (col)
self.assertTrue(col in inN.addition, msg)
col = "BO_BA_b1_10"
msg = "bad error: %s is missing" % (col)
self.assertTrue(col in inN.addition, msg)
col = "BO_BA_b2_10"
msg = "bad error: %s is missing" % (col)
self.assertTrue(col in inN.addition, msg)
def test_signal(self):
'''Test signal computation'''
newConf = copy.deepcopy(self.conf)
newConf['remove_na'] = False
node_obj = {
"id": "abc",
"type": "IndicatorNode",
"conf": newConf,
"inputs": []
}
task = Task(node_obj)
inN = IndicatorNode(task)
o = inN.process([self._cudf_data])
# check chaikin oscillator computation
r_cudf = gi.chaikin_oscillator(self._cudf_data[:self.half]['high'],
self._cudf_data[:self.half]['low'],
self._cudf_data[:self.half]['close'],
self._cudf_data[:self.half]['volume'],
10, 20)
computed = o[:self.half]['CH_OS_10_20'].to_array('pandas')
ref = r_cudf.to_array('pandas')
err = np.abs(computed[~np.isnan(computed)] - ref[~np.isnan(ref)]).max()
msg = "bad error %f\n" % (err, )
self.assertTrue(np.isclose(err, 0, atol=1e-6), msg)
r_cudf = gi.chaikin_oscillator(self._cudf_data[self.half:]['high'],
self._cudf_data[self.half:]['low'],
self._cudf_data[self.half:]['close'],
self._cudf_data[self.half:]['volume'],
10, 20)
computed = o[self.half:]['CH_OS_10_20'].to_array('pandas')
ref = r_cudf.to_array('pandas')
err = np.abs(computed[~np.isnan(computed)] - ref[~np.isnan(ref)]).max()
msg = "bad error %f\n" % (err, )
self.assertTrue(np.isclose(err, 0, atol=1e-6), msg)
# check bollinger bands computation
r_cudf = gi.bollinger_bands(self._cudf_data[:self.half]['close'], 10)
computed = o[:self.half]["BO_BA_b1_10"].to_array('pandas')
ref = r_cudf.b1.to_array('pandas')
err = np.abs(computed[~np.isnan(computed)] - ref[~np.isnan(ref)]).max()
msg = "bad error %f\n" % (err, )
self.assertTrue(np.isclose(err, 0, atol=1e-6), msg)
computed = o[:self.half]["BO_BA_b2_10"].to_array('pandas')
ref = r_cudf.b2.to_array('pandas')
err = np.abs(computed[~np.isnan(computed)] - ref[~np.isnan(ref)]).max()
msg = "bad error %f\n" % (err, )
self.assertTrue(np.isclose(err, 0, atol=1e-6), msg)
r_cudf = gi.bollinger_bands(self._cudf_data[self.half:]['close'], 10)
computed = o[self.half:]["BO_BA_b1_10"].to_array('pandas')
ref = r_cudf.b1.to_array('pandas')
err = np.abs(computed[~np.isnan(computed)] - ref[~np.isnan(ref)]).max()
msg = "bad error %f\n" % (err, )
self.assertTrue(np.isclose(err, 0, atol=1e-6), msg)
computed = o[self.half:]["BO_BA_b2_10"].to_array('pandas')
ref = r_cudf.b2.to_array('pandas')
err = np.abs(computed[~np.isnan(computed)] - ref[~np.isnan(ref)]).max()
msg = "bad error %f\n" % (err, )
self.assertTrue(np.isclose(err, 0, atol=1e-6), msg)