RecipePythonBeginner Background subtraction: one threshold for every cell in a microscope image yx = np.reshape(ndi.center_of_mass(true_labels > 0, true_labels, np.setdiff1d(ids, found(lab))), (-1, 2)) * px
ConceptPythonBeginner Overfitting: why the model that fits its data best predicts worst keep = np.setdiff1d(np.arange(N), fold)splits = [(np.setdiff1d(np.arange(N), fold), fold) for fold in folds]