def square_env(self):
    '\n        Generate map where each vertex has a one hot categorical distribution\n        Returns:\n            (N,N,num_categories) matrix with one-hot categorical observations\n        '
    env_size = self.env_size
    env = np.zeros((env_size[0], env_size[1], self.num_categories))
    for i in range(env_size[0]):
        category = np.random.randint(0, self.num_categories, env_size[1])
        env[(i, np.arange(category.size), category)] = 1
    return env
Generate map where each vertex has a one hot categorical distribution
Returns:
    (N,N,num_categories) matrix with one-hot categorical observations
def square_env(self):
    '\n        Generate map where each vertex has a one hot categorical distribution\n        Returns:\n            (N,N,num_categories) matrix with one-hot categorical observations\n        '
    env_size = self.env_size
    env = np.zeros((env_size[0], env_size[1], self.num_categories))
    for i in range(env_size[0]):
        category = np.random.randint(0, self.num_categories, env_size[1])
        env[(i, np.arange(category.size), category)] = 1
    return env