Python Context.add_node方法代码示例

# 需要导入模块: from context import Context [as 别名]
# 或者: from context.Context import add_node [as 别名]
s = Context()

# add stimulus sizes to root node...would be nicer if they went in stimulus node
s.add_rule('init',
           '$kernel_length = 10',
           '$output_length = 50',
           '$bcm_radius = 4.',
           '$stim_size  = 20',
           '$max_delay  = 3')
           # add all grids here? just name differently...
# NOTE: these are one longer than you think - fix?



# add a container for stimulus and 'focus' on it
s.add_node('$name = "stimulus"')
s.set_focus('$name == "stimulus"')

# add a distribution rule for stimulus points
s.add_rule('init',
           # dx and dy were initially 2 for both of these, changing temporarily
           '$stim_grid = Grid(xl=$stim_size, yl=$stim_size, dx=1, dy=1)',
           # should just reset stim_grid instead of copying?
           '$bph_grid  = Grid(xl=$stim_size, yl=$stim_size, dx=1, dy=1)')
           #'print $stim_grid.positions')

# also maintain a matrix of stimulus values for stimulus points to access
s.add_rule('init',
           #'$stim = SinusoidStim($stim_size, $stim_size)', # why two?
           #'$stim = JigglySinusoidStim($stim_size, 10)',
           #'$stim = InvertingSinusoidStim($stim_size, 20)',

# 需要导入模块: from context import Context [as 别名]
# 或者: from context.Context import add_node [as 别名]
from context import Context






s = Context()

# how to have input layer?...Need input layer? lolz

ps = PretendStimulus(....)

s.add_node('photoreceptor', is_worker=True, ..., focus=True)




# how to assign inputs appropriately? 
# just...add a function to each node that allows it to get the next relevant
# stimulus point...could pass own position to stimulus, then stimulus returns 
# relevant value?'
# and do positioning as before, with just a function that each unit can ask
# for a position from.
# should have a way to reset distribution functions when simulation is reset?

# something like
s.add_step('update', store(access_input, ps)) # have s.store? will passing ps like this work?
# or something
# and access_input basically gets a node to pass its position to ps and then update its output in the right way

# 需要导入模块: from context import Context [as 别名]
# 或者: from context.Context import add_node [as 别名]
           #'$stim = SinusoidStim($stim_size, $stim_size)', # why two?
           #'$stim = JigglySinusoidStim($stim_size, 10)',
           #'$stim = InvertingSinusoidStim($stim_size, 20)',
           #'$stim = SquareWaveStim($stim_size, 8)',
           #'$stim = BarStim($stim_size, 10)',
           '$stim = FullFieldStim($stim_size, 20)',
           '$stim.step()', 
           '$stim_data = $stim.output')
s.add_rule('update',
           '$stim.step()', 
           '$stim_data = $stim.output')



# add photoreceptors (don't specify connections?)
s.add_node('$name = "p_layer"')
s.set_focus('$name == "p_layer"')
s.add_node('$name = "photoreceptor"')
s.set_focus('$name == "photoreceptor"')

# read from associated position in stimulus matrix
s.add_rule('init', 
           '$x, $y = $stim_grid.get_next()',
           '$init_data($output_length)')
s.add_rule('interact',
           '$temp_data = $stim_data[$x][$y]')
s.add_rule('update',
           '$append_data($temp_data)',
           '$clean_data($output_length)')

# ADD APPROPRIATE IRF!!