samsapti/bachelor-project
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Sam A. 2023-05-14 18:49:20 +02:00
parent 35bd5b5f86
commit 137854380b
Signed by: samsapti
GPG key ID: CBBBE7371E81C4EA
1 changed files with 4 additions and 8 deletions
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12
src/gale_shapley.mpc
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@ -36,8 +36,8 @@ class Matchmaker:
same_as_old = self.int_type(rank_patient) != self.int_type(rank_old_patient)
leaving = paired * matches_exp * same_as_old
print_str('therapist: %s, patient: %s, old patient: %s, ', # worst therapist: %s, ',
*(x.reveal() for x in (therapist, patient, old_patient))) # , worst_therapist)))
print_str('therapist: %s, patient: %s, old patient: %s, ',
*(x.reveal() for x in (therapist, patient, old_patient)))
print_ln('rank patient: %s, rank old patient: %s, paired: %s, leaving: %s',
*(x.reveal() for x in
(rank_patient, rank_old_patient, paired, leaving)))
@ -76,7 +76,7 @@ class Matchmaker:
pref = self.int_type(p_cases[patient][0]) # patient suffers from pref
therapist = types.MemValue(self.int_type(0))
# Get index of next free therapist who has experience with pref
# Get index of first free therapist who has experience with pref
@for_range(self.N)
def _(i):
(_,), free = self.paired_patients.read(i)
@ -101,9 +101,6 @@ class Matchmaker:
@for_range(init_rounds)
def _(i):
print_ln('patient %s : therapist %s', i, self.paired_therapists[i].reveal())
#print_ln('therapist %s : patient %s', i, self.paired_patients[i].reveal())
#types.cint(i).print_reg('ther')
#self.paired_patients[i].reveal().print_reg('pati')
def __init__(self, p_cases, t_exps, N, M=None, reverse=False,
oram_type=OptimalORAM, int_type=types.sint):
@ -125,7 +122,6 @@ p_shares = Matrix(rows=PLAYERS, columns=MATCHING_SIZE, value_type=types.sint)
t_shares = Matrix(rows=PLAYERS, columns=MATCHING_SIZE, value_type=types.sint)
# Fill data from players into the matrices
# The matrix is ordered as m[row:player][col:share]
@for_range(PLAYERS)
def _(i):
@for_range(2 * MATCHING_SIZE)
@ -141,7 +137,7 @@ def _(i):
def _():
t_shares[i][index] = sint.get_input_from(i)
# Add entire column together to reveal secret-shared input
# Add entire columns together to recreate secret-shared input in ORAM
p_cases = OMatrix(N=MATCHING_SIZE, M=1, oram_type=OptimalORAM, int_type=types.sint)
t_exps = OMatrix(N=MATCHING_SIZE, M=1, oram_type=OptimalORAM, int_type=types.sint)