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)
