def ema()

in train_procgen/graph_util.py [0:0]

• 11 lines of code
• 3 McCabe index (conditional complexity)

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