def path_collider(vector, path):
"""adding a path to a vector"""
path_copy = list(path)
if not isinstance( vector, VectorDict):
if len(vector):
vector = tree_from_path( * ( vector + [ "weight" , 1 ] ))
else:
vector = VectorDict( VectorDict, dict() )
current = vector
while len(path) :
current_key = path.pop(0)
if current_key in current.keys():
current = current[current_key]
if current.get("weight", False):
current["weight"]+=1
else:
path = [ current_key ] + path
break
if len(path):
vector.add_path( path_copy + [ "weight" , 1 ] )
return vector
"""
phys = input_dict.get("physical", dict())
rgb_vect = array( [ int(x) for x in bytearray.fromhex(
phys.get( "eye", "000000" ) )[0::1]
] )
prefered_vect = array([ int(x) for x in bytearray.fromhex(prefered_color)[0::1] ] )
max_size = norm( prefered_vect ) * norm( rgb_vect )
return max_size > 0 and (
1.0 * sum( prefered_vect * rgb_vect) / ( max_size )
) or -1
criterion_ponderation = VectorDict(float, dict(
eye = 1 ,
fitness = 5,
bankable = 4,
extra = .5,
not_too_expensive = .1
) )
norm_of_choice = criterion_ponderation.dot(criterion_ponderation)
for candidate,ldot in map (
lambda x : [
VectorDict(VectorDict,x) , criterion_ponderation.dot(
criterion_ponderation * matrix( x )
)
] ,
data
) :
