python/src/genetic_search.py
def _normalize(netlist: Netlist, r: RangeInfo) -> Tuple[int, ...]:
    """Returns the netlist's fixed point widths, fixed point lengths and fingers in a 1d tuple"""
    widths = (quantize(Decimal(w), r.step_width, r.widths[0]) for w in netlist.device_widths)
    lengths = (quantize(Decimal(l), r.step_length, r.lengths[0]) for l in netlist.device_lengths)
    fingers = (max(f - r.fingers[0], 0) // r.step_fingers for f in netlist.device_fingers)
    return tuple(chain(widths, lengths, fingers))
Returns the netlist's fixed point widths, fixed point lengths and fingers in a 1d tuple
Returns the netlist's fixed point widths, fixed point lengths and fingers in a 1d tuple
Returns the netlist ' s fixed point widths fixed point lengths and fingers in a 1d tuple
def _normalize(netlist: Netlist, r: RangeInfo) -> Tuple[int, ...]:
    widths = (quantize(Decimal(w), r.step_width, r.widths[0]) for w in netlist.device_widths)
    lengths = (quantize(Decimal(l), r.step_length, r.lengths[0]) for l in netlist.device_lengths)
    fingers = (max(f - r.fingers[0], 0) // r.step_fingers for f in netlist.device_fingers)
    return tuple(chain(widths, lengths, fingers))
def _normalize ( netlist : Netlist , r : RangeInfo ) -> Tuple [ int , ... ] : widths = ( quantize ( Decimal ( w ) , r . step_width , r . widths [ 0 ] ) for w in netlist . device_widths ) lengths = ( quantize ( Decimal ( l ) , r . step_length , r . lengths [ 0 ] ) for l in netlist . device_lengths ) fingers = ( max ( f - r . fingers [ 0 ] , 0 ) // r . step_fingers for f in netlist . device_fingers ) return tuple ( chain ( widths , lengths , fingers ) )
Returns the netlist's fixed point widths, fixed point lengths and fingers in a 1d tuple
Returns the netlist ' s fixed point widths fixed point lengths and fingers in a 1d tuple
"""Returns the netlist's fixed point widths, fixed point lengths and fingers in a 1d tuple"""
netlist
Netlist
r
RangeInfo