# -------- Main Body -----------------------------------------------------------------------
pstep = 0
ret = 'y'
while ret == 'y':
pstep += 1
c = Circuit(N)
qcam.propinit(N, c, initial_a)
for i in range(pstep):
qproc()
master_a = np.array(c.run())
num, vector_a, prob_a = qcam.qvextract(N, R, 1, master_a)
stdev, probability_a = qcam.qcalcd(N, num, vector_a, prob_a)
qcam.qcresultout(N, pstep, num, initial_a, vector_a, prob_a, stdev,
probability_a)
stepdist_a[pstep, 0:N] = probability_a[0:N]
marking_prob_a[pstep] = prob_a[35] * 100 #Decimal number of marked vector
stdev_a[pstep] = stdev
ret = input(' NEXT(Y/N)?')
qcam.qcfinal(N, pstep, initial_a, stepdist_a, stdev_a)
fout(pstep, initial_a, marking_prob_a)
qcam.qcamplot(N, pstep, stepdist_a)
from blueqat import Circuit
import numpy as np
import qcam
# -------- Setting ------------------------------------------------------------------
N = 8 # number of cells :You can change.
R = 1 # number of registries
initial_a = np.array(
[0.9, 0, 0, 1, 0, 0.6, 0, 0],
dtype='float') # initial probability distribution :You can change.
vector_a = np.array([[0] * N] * (2 ^ N), dtype='int')
csum_a = np.array([[0] * N] * (2 ^ N), dtype='float')
final_a = np.array([0] * N, dtype='float')
#---------- Main Body ----------------------------------------------------------------
ret = 'y'
while ret == 'y':
c = Circuit(N)
qcam.propinit(N, c, initial_a)
master_a = np.array(c.run())
num, vector_a, prob_a = qcam.qvextract(N, R, 1, master_a)
stdev, final_a = qcam.qcalcd(N, num, vector_a, prob_a)
qcam.qcresultout(N, 0, num, initial_a, vector_a, prob_a, stdev, final_a)
ret = input(' NEXT(Y/N)?')