def testMovingRSI(self):
window = 10
rsi = MovingRSI(window=window, dependency='x')
pos_avg = MovingPositiveDifferenceAverage(window=window, dependency='x')
neg_avg = MovingNegativeDifferenceAverage(window=window, dependency='x')
for i, value in enumerate(self.sample):
rsi.push(dict(x=value))
pos_avg.push(dict(x=value))
neg_avg.push(dict(x=value))
calculated = rsi.value
expected = pos_avg.value / (pos_avg.value - neg_avg.value) * 100
if i > 0:
self.assertAlmostEqual(calculated, expected, 8, "at index {0:d}\n"
"negative average expected: {1:f}\n"
"negative average calculated: {2:f}".format(i,
expected,
calculated))
def testMovingRSI(self):
window = 10
rsi = MovingRSI(window=window, dependency='x')
pos_avg = MovingPositiveDifferenceAverage(window=window,
dependency='x')
neg_avg = MovingNegativeDifferenceAverage(window=window,
dependency='x')
for i, value in enumerate(self.sample):
rsi.push(dict(x=value))
pos_avg.push(dict(x=value))
neg_avg.push(dict(x=value))
calculated = rsi.value
expected = pos_avg.value / (pos_avg.value - neg_avg.value) * 100
if i > 0:
self.assertAlmostEqual(
calculated, expected, 8, "at index {0:d}\n"
"negative average expected: {1:f}\n"
"negative average calculated: {2:f}".format(
i, expected, calculated))
def testMovingNegativeDifferenceAverage(self):
window = 10
mv = MovingNegativeDifferenceAverage(window=window, dependency='x')
last = self.sample[0]
diff_list = []
for i, value in enumerate(self.sample):
mv.push(dict(x=value))
diff = value - last
if i > 0:
diff_list.append(diff)
last = value
neg_list = np.minimum(diff_list[-window:], 0.)
expected = 0. if np.isnan(np.mean(neg_list)) else np.mean(neg_list)
calculated = mv.result()
if i > 0:
self.assertAlmostEqual(
calculated, expected, 8, "at index {0:d}\n"
"negative average expected: {1:f}\n"
"negative average calculated: {2:f}".format(
i, expected, calculated))
def testMovingNegativeDifferenceAverage(self):
window = 10
mv = MovingNegativeDifferenceAverage(window=window, dependency='x')
last = self.sample[0]
diff_list = []
for i, value in enumerate(self.sample):
mv.push(dict(x=value))
diff = value - last
if i > 0:
diff_list.append(diff)
last = value
neg_list = np.minimum(diff_list[-window:], 0.)
expected = 0. if np.isnan(np.mean(neg_list)) else np.mean(neg_list)
calculated = mv.result()
if i > 0:
self.assertAlmostEqual(calculated, expected, 8, "at index {0:d}\n"
"negative average expected: {1:f}\n"
"negative average calculated: {2:f}".format(i,
expected,
calculated))
