def __init__()

in ebm_combine.py [0:0]

• 28 lines of code
• 3 McCabe index (conditional complexity)

    def __init__(self, data, latents, frac=0.0):

        l = latents

        if FLAGS.joint_shape:
            mask_size = (l[:, 3] == 30 * np.pi / 39) & (l[:, 4] == 16/31) & (l[:, 5] == 16/31) & (l[:, 2] == 0.5)
        elif FLAGS.joint_rot:
            mask_size = (l[:, 1] == 1) & (l[:, 4] == 16/31) & (l[:, 5] == 16/31) & (l[:, 2] == 0.5)
        else:
            mask_size = (l[:, 3] == 30 * np.pi / 39) & (l[:, 4] == 16/31) & (l[:, 5] == 16/31) & (l[:, 1] == 1)

        mask_pos = (l[:, 1] == 1) & (l[:, 3] == 30 * np.pi / 39) & (l[:, 2] == 0.5)

        data_pos = data[mask_pos]
        l_pos = l[mask_pos]

        data_size = data[mask_size]
        l_size = l[mask_size]

        n = data_pos.shape[0] // data_size.shape[0]

        data_pos = np.tile(data_pos, (n, 1, 1))
        l_pos = np.tile(l_pos, (n, 1))

        self.data = np.concatenate((data_pos, data_size), axis=0)
        self.label = np.concatenate((l_pos, l_size), axis=0)

        mask_neg = (~(mask_size & mask_pos)) & ((l[:, 1] == 1) & (l[:, 3] == 30 * np.pi / 39))
        data_add = data[mask_neg]
        l_add = l[mask_neg]

        perm_idx = np.random.permutation(data_add.shape[0])
        select_idx = perm_idx[:int(frac*perm_idx.shape[0])]
        data_add = data_add[select_idx]
        l_add = l_add[select_idx]

        self.data = np.concatenate((self.data, data_add), axis=0)
        self.label = np.concatenate((self.label, l_add), axis=0)

        self.identity = np.eye(3)