529be500d5e81487081a84da8bfc90ddbc40072d,skimage/util/dtype.py,,convert,#Any#Any#Any#Any#,63

Before Change

        // floating point -> integer
        prec_loss()
        // use float type that can represent output integer type
        image = image.astype(_dtype_itemsize(itemsize_out, dtype_in,
                                             np.float32, np.float64))
        if not uniform:
            if kind_out == "u":
                image *= imax_out
            else:
                image *= imax_out - imin_out
                image -= 1.0
                image /= 2.0
            np.rint(image, out=image)
            np.clip(image, imin_out, imax_out, out=image)
        elif kind_out == "u":

After Change

                np.multiply(image, imax_out,
                            out=image_out, dtype=computation_type)
            else:
                np.multiply(image, (imax_out - imin_out)/2,
                            out=image_out, dtype=computation_type)
                image_out -= 1.0 / 2.
            np.rint(image_out, out=image_out)
            np.clip(image_out, imin_out, imax_out, out=image_out)
        elif kind_out == "u":

Instances