def testAvgGainLoss(self):
# We divide by 2 because N samples yield N-1 averages.
# Gain only
avgGain, avgLoss = rsi.avg_gain_loss([1, 2, 3], 0, 3)
self.assertTrue(avgGain == 2 / float(2))
self.assertTrue(avgLoss == 0)
# Loss only
avgGain, avgLoss = rsi.avg_gain_loss([3, 2, 1], 0, 3)
self.assertTrue(avgGain == 0)
self.assertTrue(avgLoss == 2 / float(2))
# Gain and Loss equal
avgGain, avgLoss = rsi.avg_gain_loss([1, 0, 1], 0, 3)
self.assertTrue(avgGain == 1 / float(2))
self.assertTrue(avgLoss == 1 / float(2))
# Gain and Loss different
avgGain, avgLoss = rsi.avg_gain_loss([1, 3, 2], 0, 3)
self.assertTrue(avgGain == 2 / float(2))
self.assertTrue(avgLoss == 1 / float(2))
# Error
self.assertEqual(rsi.avg_gain_loss([1, 1.5, 2], 0, 1), None)
self.assertEqual(rsi.avg_gain_loss([1, 1.5, 2], 1, 2), None)
with self.assertRaises(IndexError):
rsi.avg_gain_loss([1, 1.5, 2], 2, 4)
def testAvgGainLoss(self):
# We divide by 2 because N samples yield N-1 averages.
# Gain only
avgGain, avgLoss = rsi.avg_gain_loss([1, 2, 3], 0, 3)
self.assertTrue(avgGain == 2 / float(2))
self.assertTrue(avgLoss == 0)
# Loss only
avgGain, avgLoss = rsi.avg_gain_loss([3, 2, 1], 0, 3)
self.assertTrue(avgGain == 0)
self.assertTrue(avgLoss == 2 / float(2))
# Gain and Loss equal
avgGain, avgLoss = rsi.avg_gain_loss([1, 0, 1], 0, 3)
self.assertTrue(avgGain == 1 / float(2))
self.assertTrue(avgLoss == 1 / float(2))
# Gain and Loss different
avgGain, avgLoss = rsi.avg_gain_loss([1, 3, 2], 0, 3)
self.assertTrue(avgGain == 2 / float(2))
self.assertTrue(avgLoss == 1 / float(2))
# Error
self.assertEqual(rsi.avg_gain_loss([1, 1.5, 2], 0, 1), None)
self.assertEqual(rsi.avg_gain_loss([1, 1.5, 2], 1, 2), None)
with self.assertRaises(IndexError):
rsi.avg_gain_loss([1, 1.5, 2], 2, 4)
def testAvgGainLoss(self): # We divide by 2 because N samples yield N-1 averages. # Gain only avgGain, avgLoss = rsi.avg_gain_loss([1, 2, 3]) self.assertTrue(avgGain == 2 / float(2)) self.assertTrue(avgLoss == 0) # Loss only avgGain, avgLoss = rsi.avg_gain_loss([3, 2, 1]) self.assertTrue(avgGain == 0) self.assertTrue(avgLoss == 2 / float(2)) # Gain and Loss equal avgGain, avgLoss = rsi.avg_gain_loss([1, 0, 1]) self.assertTrue(avgGain == 1 / float(2)) self.assertTrue(avgLoss == 1 / float(2)) # Gain and Loss different avgGain, avgLoss = rsi.avg_gain_loss([1, 3, 2]) self.assertTrue(avgGain == 2 / float(2)) self.assertTrue(avgLoss == 1 / float(2))
def testAvgGainLoss(self):
# We divide by 2 because N samples yield N-1 averages.
# Gain only
avgGain, avgLoss = rsi.avg_gain_loss([1, 2, 3])
self.assertTrue(avgGain == 2 / float(2))
self.assertTrue(avgLoss == 0)
# Loss only
avgGain, avgLoss = rsi.avg_gain_loss([3, 2, 1])
self.assertTrue(avgGain == 0)
self.assertTrue(avgLoss == 2 / float(2))
# Gain and Loss equal
avgGain, avgLoss = rsi.avg_gain_loss([1, 0, 1])
self.assertTrue(avgGain == 1 / float(2))
self.assertTrue(avgLoss == 1 / float(2))
# Gain and Loss different
avgGain, avgLoss = rsi.avg_gain_loss([1, 3, 2])
self.assertTrue(avgGain == 2 / float(2))
self.assertTrue(avgLoss == 1 / float(2))
