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]