RET_OUTPUT_AVI = 'retina_output.avi' LAM_OUTPUT_AVI = 'lamina_output.avi' RET_OUTPUT_MPEG = 'retina_output.mp4' LAM_OUTPUT_MPEG = 'lamina_output.mp4' eyemodel = EyeGeomImpl(args.num_layers, retina_only=args.retina_only) #current implementation of output manipulation depends on input if args.output: args.input = True if args.input: print('Generating input of model from image file') _dummy = eyemodel.get_intensities(IMAGE_FILE, {'type': args.video_type, 'steps': args.steps, 'dt': dt, 'output_file': INPUT_FILE, 'factors': [1, 5, 10, 20, 50, 100]}) if args.gexf: print('Writing retina lpu') eyemodel.write_retina(RET_GEXF_FILE) if not args.retina_only: print('Writing lamina lpu') eyemodel.write_lamina(LAM_GEXF_FILE) if args.port_data is None and args.port_ctrl is None: port_data = get_random_port() port_ctrl = get_random_port() else: port_data = args.port_data port_ctrl = args.port_ctrl
LAM_OUTPUT_AVI = 'lamina_output.avi' RET_OUTPUT_MPEG = 'retina_output.mp4' LAM_OUTPUT_MPEG = 'lamina_output.mp4' eyemodel = EyeGeomImpl(args.num_layers, retina_only=args.retina_only) #current implementation of output manipulation depends on input if args.output: args.input = True if args.input: print('Generating input of model from image file') _dummy = eyemodel.get_intensities( IMAGE_FILE, { 'type': args.video_type, 'steps': args.steps, 'dt': dt, 'output_file': INPUT_FILE, 'factors': [1, 5, 10, 20, 50, 100] }) if args.gexf: print('Writing retina lpu') eyemodel.write_retina(RET_GEXF_FILE) if not args.retina_only: print('Writing lamina lpu') eyemodel.write_lamina(LAM_GEXF_FILE) if args.port_data is None and args.port_ctrl is None: port_data = get_random_port() port_ctrl = get_random_port() else: port_data = args.port_data
print('Instantiating eye geometry') eyemodel = EyeGeomImpl(args.num_layers, model=args.model) if args.input: print('Generating input of model') config = {'type': args.type, 'steps': args.steps, 'dt': dt, 'output_file': RET_INPUT} ''' replace with above for bar generation config = {'type': 'bar', 'steps': args.steps, 'dt': dt, 'shape': (100,100), 'width': 20, 'speed': 100, 'dir':0} ''' _dummy = eyemodel.get_intensities(file=None, config=config) if args.gexf: print('Writing retina lpu') eyemodel.write_retina(RET_GEXF_FILE) print('Writing lamina lpu') eyemodel.write_lamina(LAM_GEXF_FILE) print('Writing medulla lpu') eyemodel.write_medulla(MED_GEXF_FILE) if not args.suppress: man = core.Manager() if 'r' in args.model: print('Parsing retina LPU data') n_dict_ret, s_dict_ret = LPU.lpu_parser(RET_GEXF_FILE)
if args.input: print('Generating input of model') config = { 'type': args.type, 'steps': args.steps, 'dt': dt, 'output_file': RET_INPUT } ''' replace with above for bar generation config = {'type': 'bar', 'steps': args.steps, 'dt': dt, 'shape': (100,100), 'width': 20, 'speed': 100, 'dir':0} ''' _dummy = eyemodel.get_intensities(file=None, config=config) if args.gexf: print('Writing retina lpu') eyemodel.write_retina(RET_GEXF_FILE) print('Writing lamina lpu') eyemodel.write_lamina(LAM_GEXF_FILE) print('Writing medulla lpu') eyemodel.write_medulla(MED_GEXF_FILE) if not args.suppress: man = core.Manager() if 'r' in args.model: print('Parsing retina LPU data') n_dict_ret, s_dict_ret = LPU.lpu_parser(RET_GEXF_FILE)