if len(sys.argv) != 2 and len(sys.argv) != 4:
- print("Usage : %s datafile", sys.argv[0])
- print("or : %s datafile p1 p2", sys.argv[0])
+ print("Usage : {} datafile".format(sys.argv[0]))
+ print("or : {} datafile p1 p2".format(sys.argv[0]))
print("where : p1 < p2 belongs to sizes in datafiles")
sys.exit(-1)
##-------------------------------------------------
## cov : covariance
## param X first data vector (..x_i..)
-## param Y second data vector (..x_i..)
+## param Y second data vector (..y_i..)
## = 1/n \Sum_{i=1}^n (x_i - avg(x)) * (y_i - avg(y))
##--------------------------------------------------
def cov(X,Y):
+ assert(len(X)==len(Y))
n=len(X) # n=len(X)=len(Y)
avg_X = avg( X )
avg_Y = avg( Y )
glob_corr = glob_corr + (l/sum_nb_val)*c # weighted product of correlation
print('-- %f * %f' % (c,l/sum_nb_val))
- print("-> glob_corr=%f\n" % glob_corr)
+ print("-> glob_corr={}\n".format(glob_corr))
return (glob_corr,interv);
## ---------------
#count= 8388608 8388608 144916.1 7.6 32 144916.1 143262.0
#("%s %d %d %f %f %d %f %f\n" % (countlbl, count, countn, time, stddev, iter, mini, maxi)
- readdata.append( (int(l[1]),float(l[3]) / 2 ) ); # divide by 2 because of ping-pong measured
+ readdata.append( (int(l[1]),float(l[3])) );
nblines=nblines+1
## These may not be sorted so sort it by message size before processing.
max_glob_corr = glob_cor
max_interv = interv
+ print("#-------------------- result summary ---------------------------------------------------------------------\n");
for (a,b,i,j) in max_interv:
- print("** OPT: [%d .. %d]" % (i,j))
- print("** Product of correl coefs = %f" % (max_glob_corr))
+ print("** OPT: [%d .. %d] correl coef prod=%f slope: %f x + %f" % (i,j,max_glob_corr,a,b))
print("#-------------------- cut here the gnuplot code -----------------------------------------------------------\n");
preamble='set output "regr.eps"\n\