def __init__()

in data.py [0:0]

• 58 lines of code
• 10 McCabe index (conditional complexity)

    def __init__(
            self,
            cond_size=False,
            cond_shape=False,
            cond_pos=False,
            cond_rot=False):
        dat = np.load(FLAGS.dsprites_path)

        if FLAGS.dshape_only:
            l = dat['latents_values']
            mask = (l[:, 4] == 16 / 31) & (l[:, 5] == 16 /
                                           31) & (l[:, 2] == 0.5) & (l[:, 3] == 30 * np.pi / 39)
            self.data = np.tile(dat['imgs'][mask], (10000, 1, 1))
            self.label = np.tile(dat['latents_values'][mask], (10000, 1))
            self.label = self.label[:, 1:2]
        elif FLAGS.dpos_only:
            l = dat['latents_values']
            # mask = (l[:, 1] == 1) & (l[:, 2] == 0.5) & (l[:, 3] == 30 * np.pi / 39)
            mask = (l[:, 1] == 1) & (
                l[:, 3] == 30 * np.pi / 39) & (l[:, 2] == 0.5)
            self.data = np.tile(dat['imgs'][mask], (100, 1, 1))
            self.label = np.tile(dat['latents_values'][mask], (100, 1))
            self.label = self.label[:, 4:] + 0.5
        elif FLAGS.dsize_only:
            l = dat['latents_values']
            # mask = (l[:, 1] == 1) & (l[:, 2] == 0.5) & (l[:, 3] == 30 * np.pi / 39)
            mask = (l[:, 3] == 30 * np.pi / 39) & (l[:, 4] == 16 /
                                                   31) & (l[:, 5] == 16 / 31) & (l[:, 1] == 1)
            self.data = np.tile(dat['imgs'][mask], (10000, 1, 1))
            self.label = np.tile(dat['latents_values'][mask], (10000, 1))
            self.label = (self.label[:, 2:3])
        elif FLAGS.drot_only:
            l = dat['latents_values']
            mask = (l[:, 2] == 0.5) & (l[:, 4] == 16 /
                                       31) & (l[:, 5] == 16 / 31) & (l[:, 1] == 1)
            self.data = np.tile(dat['imgs'][mask], (100, 1, 1))
            self.label = np.tile(dat['latents_values'][mask], (100, 1))
            self.label = (self.label[:, 3:4])
            self.label = np.concatenate(
                [np.cos(self.label), np.sin(self.label)], axis=1)
        elif FLAGS.dsprites_restrict:
            l = dat['latents_values']
            mask = (l[:, 1] == 1) & (l[:, 3] == 0 * np.pi / 39)

            self.data = dat['imgs'][mask]
            self.label = dat['latents_values'][mask]
        else:
            self.data = dat['imgs']
            self.label = dat['latents_values']

            if cond_size:
                self.label = self.label[:, 2:3]
            elif cond_shape:
                self.label = self.label[:, 1:2]
            elif cond_pos:
                self.label = self.label[:, 4:]
            elif cond_rot:
                self.label = self.label[:, 3:4]
                self.label = np.concatenate(
                    [np.cos(self.label), np.sin(self.label)], axis=1)
            else:
                self.label = self.label[:, 1:2]

        self.identity = np.eye(3)