roboschool/gym_mujoco_xml_env.py [75:105]:
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        s = self.calc_state()    # optimization: calc_state() can calculate something in self.* for calc_potential() to use
        self.potential = self.calc_potential()
        self.camera = self.scene.cpp_world.new_camera_free_float(self.VIDEO_W, self.VIDEO_H, "video_camera")
        return s

    def render(self, mode='human'):
        if mode=="human":
            self.scene.human_render_detected = True
            return self.scene.cpp_world.test_window()
        elif mode=="rgb_array":
            self.camera_adjust()
            rgb, _, _, _, _ = self.camera.render(False, False, False) # render_depth, render_labeling, print_timing)
            rendered_rgb = np.fromstring(rgb, dtype=np.uint8).reshape( (self.VIDEO_H,self.VIDEO_W,3) )
            return rendered_rgb
        else:
            assert(0)

    def calc_potential(self):
        return 0

    def HUD(self, s, a, done):
        active = self.scene.actor_is_active(self)
        if active and self.done<=2:
            self.scene.cpp_world.test_window_history_advance()
            self.scene.cpp_world.test_window_observations(s.tolist())
            self.scene.cpp_world.test_window_actions(a.tolist())
            self.scene.cpp_world.test_window_rewards(self.rewards)
        if self.done<=1: # Only post score on first time done flag is seen, keep this score if user continues to use env
            s = "%04i %07.1f %s" % (self.frame, self.reward, "DONE" if self.done else "")
            if active:
                self.scene.cpp_world.test_window_score(s)
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roboschool/gym_urdf_robot_env.py [82:112]:
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        s = self.calc_state()    # optimization: calc_state() can calculate something in self.* for calc_potential() to use
        self.potential = self.calc_potential()
        self.camera = self.scene.cpp_world.new_camera_free_float(self.VIDEO_W, self.VIDEO_H, "video_camera")
        return s

    def render(self, mode='human'):
        if mode=="human":
            self.scene.human_render_detected = True
            return self.scene.cpp_world.test_window()
        elif mode=="rgb_array":
            self.camera_adjust()
            rgb, _, _, _, _ = self.camera.render(False, False, False) # render_depth, render_labeling, print_timing)
            rendered_rgb = np.fromstring(rgb, dtype=np.uint8).reshape( (self.VIDEO_H,self.VIDEO_W,3) )
            return rendered_rgb
        else:
            assert(0)

    def calc_potential(self):
        return 0

    def HUD(self, s, a, done):
        active = self.scene.actor_is_active(self)
        if active and self.done<=2:
            self.scene.cpp_world.test_window_history_advance()
            self.scene.cpp_world.test_window_observations(s.tolist())
            self.scene.cpp_world.test_window_actions(a.tolist())
            self.scene.cpp_world.test_window_rewards(self.rewards)
        if self.done<=1: # Only post score on first time done flag is seen, keep this score if user continues to use env
            s = "%04i %07.1f %s" % (self.frame, self.reward, "DONE" if self.done else "")
            if active:
                self.scene.cpp_world.test_window_score(s)
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