def _plotVirtualTime(accessList, archName, fgname, rd_bin_width = 250):
"""
Plot data access based on virtual time
"""
print "converting to num arrary for _plotVirtualTime"
stt = time.time()
x, y, id, ad, yd = _raListToVTimeNA(accessList)
print ("Converting to num array takes %d seconds" % (time.time() - stt))
fig = pl.figure()
ax = fig.add_subplot(211)
ax.set_xlabel('Access sequence number (%s to %s)' % (id.split('T')[0], ad.split('T')[0]), fontsize = 9)
ax.set_ylabel('Observation sequence number', fontsize = 9)
ax.set_title('%s archive activity ' % (archName), fontsize=10)
ax.tick_params(axis='both', which='major', labelsize=8)
ax.tick_params(axis='both', which='minor', labelsize=6)
ax.plot(x, y, color = 'b', marker = 'x', linestyle = '',
label = 'access', markersize = 3)
#legend = ax.legend(loc = 'upper left', shadow=True, prop={'size':7})
ax1 = fig.add_subplot(212)
ax1.set_xlabel('Access sequence number (%s to %s)' % (id.split('T')[0], ad.split('T')[0]), fontsize = 9)
ax1.set_ylabel('Reuse distance (in-between accesses)', fontsize = 9)
ax1.tick_params(axis='both', which='major', labelsize=8)
ax1.tick_params(axis='both', which='minor', labelsize=6)
ax1.plot(x, yd, color = 'k', marker = '+', linestyle = '',
label = 'reuse distance', markersize = 3)
pl.tight_layout()
fig.savefig(fgname)
pl.close(fig)
y1d = yd[~np.isnan(yd)]
num_bin = (max(y1d) - min(y1d)) / rd_bin_width
hist, bins = np.histogram(y1d, bins = num_bin)
width = 0.7 * (bins[1] - bins[0])
center = (bins[:-1] + bins[1:]) / 2
fig1 = pl.figure()
#fig1.suptitle('Histogram of data transfer rate from Pawsey to MIT', fontsize=14)
ax2 = fig1.add_subplot(111)
ax2.set_title('Reuse distance Histogram for %s' % archName, fontsize = 10)
ax2.set_ylabel('Frequency', fontsize = 9)
ax2.set_xlabel('Reuse distance (# of observation)', fontsize = 9)
ax2.tick_params(axis='both', which='major', labelsize=8)
ax2.tick_params(axis='both', which='minor', labelsize=6)
pl.bar(center, hist, align='center', width=width)
fileName, fileExtension = os.path.splitext(fgname)
fig1.savefig('%s_rud_hist%s' % (fileName, fileExtension))
pl.close(fig1)
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