No need for that coercion any more, they are already of the right type
@@ -96,11 +96,10 @@ def delta(x, y, x_denominators=1, y_denominators=1, assume_normal=True, alpha=0.
percentiles = [alpha * 100 / 2, 100 - alpha * 100 / 2]
- # Coercing missing values to right format
- _x = np.array(x, dtype=float)
- _y = np.array(y, dtype=float)
- _x_denominators = np.array(x_denominators, dtype=float)
- _y_denominators = np.array(y_denominators, dtype=float)
+ _x = x
+ _y = y
+ _x_denominators = x_denominators
+ _y_denominators = y_denominators
_x_ratio = _x / _x_denominators
_y_ratio = _y / _y_denominators
_x_strange = _x / np.nanmean(_x_denominators)
