in phasic_policy_gradient/graph_util.py [0:0]
def ema(data_in, smoothing=0):
data_out = np.zeros_like(data_in)
curr = np.nan
for i in range(len(data_in)):
x = data_in[i]
if np.isnan(curr):
curr = x
else:
curr = (1 - smoothing) * x + smoothing * curr
data_out[i] = curr
return data_out