@classmethod<EOL><INDENT>def from_weight_map(cls, pixel_scale, weight_map):<DEDENT>
np.seterr(divide='<STR_LIT:ignore>')<EOL>noise_map = <NUM_LIT:1.0> / np.sqrt(weight_map)<EOL>noise_map[noise_map == np.inf] = <NUM_LIT><EOL>return NoiseMap(array=noise_map, pixel_scale=pixel_scale)<EOL>
Setup the noise-map from a weight map, which is a form of noise-map that comes via HST image-reduction and \
        the software package MultiDrizzle.

        The variance in each pixel is computed as:

        Variance = 1.0 / sqrt(weight_map).

        The weight map may contain zeros, in which cause the variances are converted to large values to omit them from \
        the analysis.

        Parameters
        -----------
        pixel_scale : float
            The size of each pixel in arc seconds.
        weight_map : ndarray
            The weight-value of each pixel which is converted to a variance.