def generate_poisson_noise(image, exposure_time_map, seed=-<NUM_LIT:1>):
setup_random_seed(seed)<EOL>image_counts = np.multiply(image, exposure_time_map)<EOL>return image - np.divide(np.random.poisson(image_counts, image.shape), exposure_time_map)<EOL>
Generate a two-dimensional poisson noise_maps-mappers from an image.

Values are computed from a Poisson distribution using the image's input values in units of counts.

Parameters
----------
image : ndarray
    The 2D image, whose values in counts are used to draw Poisson noise_maps values.
exposure_time_map : Union(ndarray, int)
    2D array of the exposure time in each pixel used to convert to / from counts and electrons per second.
seed : int
    The seed of the random number generator, used for the random noise_maps maps.

Returns
-------
poisson_noise_map: ndarray
    An array describing simulated poisson noise_maps