def eval_algorithm(closes):
""" Evaluates the SMA algorithm
Args:
closes: List of price closes.
Returns:
Float average of closes.
"""
return stats.avg(closes)
def eval_rs(gains, losses):
""" Evaluates the RS variable in RSI algorithm
Args:
gains: List of price gains.
losses: List of prices losses.
Returns:
Float of average gains over average losses.
"""
# Number of days that the data was collected through
count = len(gains) + len(losses)
avg_gains = stats.avg(gains, count=count) if gains else 1
avg_losses = stats.avg(losses,count=count) if losses else 1
if avg_losses == 0:
return avg_gains
else:
return avg_gains / avg_losses
def eval_rs(gains, losses):
""" Evaluates the RS variable in RSI algorithm
Args:
gains: List of price gains.
losses: List of prices losses.
Returns:
Float of average gains over average losses.
"""
# Number of days that the data was collected through
count = len(gains) + len(losses)
avg_gains = stats.avg(gains, count=count)
avg_losses = stats.avg(losses,count=count)
try:
return avg_gains / avg_losses
except ZeroDivisionError: # No losses
return avg_gains
def test_avg(self):
nums = [0.24, 0.62, 0.15, 0.83, 0.12345]
self.assertEqual(stats.avg(nums), 0.39269)
nums = [0.24, 0.62, 0.15, 0.83, 0.12345]
self.assertEqual(stats.avg(nums, count=8), 0.24543125)