def compare_accuracy(i, j, k):
mr_errors = []
ss_errors = []
fpt_errors = []
for n in range(i, j):
ans = prime.isPrime_par(n)
if prime.mr(n, k) != ans:
mr_errors.append(n)
if prime.ss(n, k) != ans:
ss_errors.append(n)
if prime.fpt(n, k) != ans:
fpt_errors.append(n)
errors = (len(mr_errors), len(ss_errors), len(fpt_errors))
#print errors
#print mr_errors
#print ss_errors
#print fpt_errors
#_,ax = plot.subplots()
#ax.set_title('Error Histrogram with k=' + str(k))
#ax.set_ylabel('#errors')
#ax.set_ylim([0,50])
#ax.bar(range(0,3), errors, 0.5, color={'r','g','b'})
#ax.set_xticks(numpy.arange(3)+0.5/2)
#ax.set_xticklabels(('MR', 'SS', 'FPT'))
#plot.show()
return errors
def compare_accuracy(i, j, k):
mr_errors = []
ss_errors = []
fpt_errors = []
for n in range(i,j):
ans = prime.isPrime_par(n)
if prime.mr(n,k) != ans:
mr_errors.append(n)
if prime.ss(n,k) != ans:
ss_errors.append(n)
if prime.fpt(n,k) != ans:
fpt_errors.append(n)
errors = (len(mr_errors), len(ss_errors), len(fpt_errors))
#print errors
#print mr_errors
#print ss_errors
#print fpt_errors
#_,ax = plot.subplots()
#ax.set_title('Error Histrogram with k=' + str(k))
#ax.set_ylabel('#errors')
#ax.set_ylim([0,50])
#ax.bar(range(0,3), errors, 0.5, color={'r','g','b'})
#ax.set_xticks(numpy.arange(3)+0.5/2)
#ax.set_xticklabels(('MR', 'SS', 'FPT'))
#plot.show()
return errors
def fpt_accuracy(i, j, k):
fpt_errors = []
for n in range(i, j):
ans = prime.isPrime_par(n)
if prime.fpt(n, k) != ans:
fpt_errors.append(n)
errors = (len(fpt_errors))
return errors
def fpt_accuracy(i, j, k): fpt_errors = [] for n in range(i,j): ans = prime.isPrime_par(n) if prime.fpt(n,k) != ans: fpt_errors.append(n) errors = (len(fpt_errors)) return errors