Is there a numpy builtin to reject outliers from a list

Question

Is there a numpy builtin to do something like the following? That is, take a list d and return a list filtered_d with any outlying elements removed

Answer 1

For a set of images (each image has 3 dimensions), where I wanted to reject outliers for each pixel I used:

mean = np.mean(imgs, axis=0)
std = np.std(imgs, axis=0)
mask = np.greater(0.5 * std + 1, np.abs(imgs - mean))
masked = np.multiply(imgs, mask)

Then it is possible to compute the mean:

masked_mean = np.divide(np.sum(masked, axis=0), np.sum(mask, axis=0))

(I use it for Background Subtraction)