trace_list, ss = gen_leaves(trace, sizes)
st_tree, lvl = generate_tree(trace_list)
root = st_tree[lvl][0]
root.is_root = True
curr = st_tree[0][0]
## Initialize
c_trace = []
tries = 0
i = 0
j = 0
k = 0
no_desc = 0
fail = 0
fd_sample = joint_dst("results/" + w_dir + "/popularity_desc_all.txt",
False, 2)
sampled_fds = []
sampled_sds_pop = defaultdict(list)
result_fds = []
land_pos = []
land_obj_sz = []
sz_added = 0
sz_removed = 0
evicted_ = 0
req_count = [0] * (25 * total_objects)
#req_count.extend([0] * (25*total_objects))
while curr != None and i <= t_len:
pl = np.cumsum(sz_dst.pr)
plt.plot(sz_dst.p_keys, pl, label="orig")
i = 0
total_sz = 0
sizes = []
for p in popularities:
sz = pop_sz.sample(p)
sizes.append(sz)
plot_list(sizes, label="sampled")
plt.xlabel("sizes")
plt.legend()
plt.ylabel("cdf")
plt.xscale("log")
plt.grid()
plt.savefig("results/v/size_sanity.png")
plt.clf()
pp = 2
fd_sample = joint_dst("results/" + w_dir + "/pop_sd_0.txt", False, 2)
fds = []
for i in range(MIL):
fds.append(fd_sample.sample(pp))
plot_list(fds, label="sampled")
keys = fd_sample.pop_sz_vals[pp]
vals = fd_sample.pop_sz_prs[pp]
vals = np.cumsum(vals)
plt.plot(keys, vals, label="orig")
plt.savefig("results/v/2.png")
trace_list, ss = gen_leaves(trace, sizes)
st_tree, lvl = generate_tree(trace_list)
root = st_tree[lvl][0]
root.is_root = True
curr = st_tree[0][0]
## Initialize
c_trace = []
tries = 0
i = 0
j = 0
k = 0
no_desc = 0
fail = 0
fd_sample = joint_dst("results/" + w_dir + "/size_sd_0.txt")
sampled_fds = []
sampled_sds_pop = defaultdict(list)
result_fds = []
land_pos = []
land_obj_sz = []
sz_added = 0
sz_removed = 0
evicted_ = 0
while curr != None and i <= t_len:
## Sample based on size of the object
sz = sizes[curr.obj_id]