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plot.py
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import os, sys
current_dir = os.path.dirname(os.path.realpath(__file__))
sys.path.append(current_dir + '/sim_common')
import threading
from plot_utils import *
from file_utils import *
from debug_utils import *
from sim_config import *
def plot_client(c):
fontsize = 14
## T over time
t0 = c.req_finished_l[0].epoch_arrived_client
t_l, T_l = [], []
for req in c.req_finished_l:
t_l.append(req.epoch_arrived_client - t0)
T_l.append(1000*(req.epoch_arrived_client - req.epoch_departed_client))
plot.plot(t_l, T_l, color=next(nice_color), marker='_', linestyle='None', mew=3, ms=5)
plot.ylabel('T (msec)', fontsize=fontsize)
plot.xlabel('t', fontsize=fontsize)
plot.legend(fontsize=fontsize)
plot.gcf().set_size_inches(6, 4)
plot_save("plot_{}_T_over_t.png".format(c._id), bbox_inches='tight')
plot.gcf().clear()
## CDF of T
add_cdf(T_l, plot.gca(), '', next(nice_color)) # drawline_x_l=[1000]
plot.xscale('log')
plot.xticks(rotation=70)
plot.ylabel('Pr{T < x}', fontsize=fontsize)
plot.xlabel('x (msec)', fontsize=fontsize)
plot.legend(fontsize=fontsize)
plot.gcf().set_size_inches(6, 4)
plot_save("plot_{}_cdf_T.png".format(c._id), bbox_inches='tight')
plot.gcf().clear()
## CDF of inter result times
add_cdf(c.inter_result_time_l, plot.gca(), '', next(nice_color)) # drawline_x_l=[1000*c.inter_job_gen_time_rv.mean()]
plot.xscale('log')
plot.xticks(rotation=70)
plot.ylabel('Pr{Inter result time < x}', fontsize=fontsize)
plot.xlabel('x (msec)', fontsize=fontsize)
plot.legend(fontsize=fontsize)
plot.gcf().set_size_inches(6, 4)
plot_save("plot_{}_cdf_interResultTime.png".format(c._id), bbox_inches='tight')
log(DEBUG, "done")
def plot_master(m):
log(DEBUG, "", num_dropped_msgs=m.msg_q.num_dropped)
def plot_worker(w):
fontsize = 14
## Q-length over time
t0 = w.epoch__num_req_l[0]
t_l, nreq_l = [], []
for epoch, nreq in w.epoch__num_req_l:
t_l.append(epoch - t0)
nreq_l.append(nreq)
plot.plot(t_l, nreq_l, color=next(nice_color), marker='_', linestyle='None', mew=3, ms=5)
plot.ylabel('Number of requests', fontsize=fontsize)
plot.xlabel('t', fontsize=fontsize)
plot.legend(fontsize=fontsize)
plot.gcf().set_size_inches(6, 4)
plot_save("plot_{}_n_over_t.png".format(w._id), bbox_inches='tight')
plot.gcf().clear()
SUBFOLDER_PODC = 'sim_podc'
SUBFOLDER_TS = 'sim_ts'
SUBFOLDER_RR = 'sim_rr'
SUBFOLDER_UCB = 'sim_ucb'
d, p = 2, 10
w = 0 # 20 # 100
def plot_ET_vs_d_p(ro, hetero_clusters, N_fluctuating_frac, serv_time_rv):
log(INFO, "started", ro=ro, hetero_clusters=hetero_clusters, N_fluctuating_frac=N_fluctuating_frac, serv_time_rv=serv_time_rv)
def plot_(p):
log(INFO, ">> p= {}".format(p))
d_ET_l = read_json_from_file(fname=get_filename('{}/d_ET_l_podc_p_{}'.format(SUBFOLDER_PODC, p), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv), ext='json')
d_l, ET_l = [], []
for (d, ET) in d_ET_l:
d_l.append(d)
ET_l.append(ET)
plot.plot(d_l, ET_l, color=next(light_color), label='p= {}'.format(p), marker='x', linestyle='solid', lw=2, mew=3, ms=5)
# for p in [5, 10, 50, 1000]:
for p in [5, 10, 50]:
plot_(p)
fontsize = 14
plot.legend(fontsize=fontsize)
plot.ylabel(r'$E[T]$', fontsize=fontsize)
plot.xlabel(r'$d$', fontsize=fontsize)
plot.title(get_plot_title(ro, hetero_clusters, N_fluctuating_frac, serv_time_rv='Constant'))
plot.gcf().set_size_inches(6, 4)
plot_save(get_filename('ET_vs_d_p', 'pdf', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv), bbox_inches='tight')
plot.gcf().clear()
log(DEBUG, "done")
def plot_ET_vs_d_p_for_varying_config():
log(INFO, "started")
def plot_(ro, hetero_clusters):
# plot_ET_vs_d_p(ro, hetero_clusters, N_fluctuating_frac=0, serv_time_rv=DiscreteRV(p_l=[1], v_l=[1 / serv_rate]))
# plot_ET_vs_d_p(ro, hetero_clusters, N_fluctuating_frac=0, serv_time_rv=Exp(serv_rate))
plot_ET_vs_d_p(ro, hetero_clusters, N_fluctuating_frac=0.3, serv_time_rv=DiscreteRV(p_l=[1], v_l=[1 / serv_rate]))
# plot_ET_vs_d_p(ro, hetero_clusters, N_fluctuating_frac=0.3, serv_time_rv=Exp(serv_rate))
# plot_(ro=0.3, hetero_clusters=True)
plot_(ro=0.8, hetero_clusters=True)
log(INFO, "done")
def plot_cdf_X(X, ro, hetero_clusters, N_fluctuating_frac, serv_time_rv):
log(INFO, "started", X=X, ro=ro, hetero_clusters=hetero_clusters, N_fluctuating_frac=N_fluctuating_frac, serv_time_rv=serv_time_rv)
X_podc_l = read_json_from_file(fname=get_filename('{}/{}_l_podc_d_{}_p_{}'.format(SUBFOLDER_PODC, X, d, p), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
X_ts_w_0_l = read_json_from_file(fname=get_filename('{}/{}_l_ts_w_0'.format(SUBFOLDER_TS, X), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
X_ts_w_20_l = read_json_from_file(fname=get_filename('{}/{}_l_ts_w_20'.format(SUBFOLDER_TS, X), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
X_ts_w_100_l = read_json_from_file(fname=get_filename('{}/{}_l_ts_w_100'.format(SUBFOLDER_TS, X), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
X_rr_l = read_json_from_file(fname=get_filename('{}/{}_l_rr'.format(SUBFOLDER_RR, X), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
X_ucb_w_100_l = read_json_from_file(fname=get_filename('{}/{}_l_ucb_w_100'.format(SUBFOLDER_UCB, X), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
add_cdf(X_podc_l, ax, 'PodC', next(nice2_color)) # drawline_x_l=[1000]
add_cdf(X_ts_w_0_l, ax, 'TS, w=0', next(nice2_color))
add_cdf(X_ts_w_20_l, ax, 'TS, w=20', next(nice2_color))
add_cdf(X_ts_w_100_l, ax, 'TS, w=100', next(nice2_color))
add_cdf(X_rr_l, ax, 'RR', next(nice2_color))
# add_cdf(X_ucb_w_100_l, ax, 'UCB', next(nice2_color))
fontsize = 14
plot.xscale('log')
# plot.xticks(rotation=70)
plot.ylabel('Pr{' + X + ' < x}', fontsize=fontsize)
plot.xlabel('x', fontsize=fontsize)
plot.legend(fontsize=fontsize, bbox_to_anchor=(1.01, 1))
plot.title(r'$d= {}, p= {}$'.format(d, p) + ', ' + get_plot_title(ro, hetero_clusters, N_fluctuating_frac, serv_time_rv), fontsize=fontsize)
plot_save(get_filename('plot_cdf_{}'.format(X), 'png', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv), bbox_inches='tight')
plot.gcf().clear()
log(INFO, "done")
def plot_cdf_X_for_varying_config(X):
log(INFO, "started", X=X)
def plot_(ro, hetero_clusters):
# plot_cdf_X(X, ro, hetero_clusters, N_fluctuating_frac=0, serv_time_rv=DiscreteRV(p_l=[1], v_l=[1 / serv_rate]))
# plot_cdf_X(X, ro, hetero_clusters, N_fluctuating_frac=0, serv_time_rv=Exp(serv_rate))
plot_cdf_X(X, ro, hetero_clusters, N_fluctuating_frac=0.3, serv_time_rv=DiscreteRV(p_l=[1], v_l=[1 / serv_rate]))
# plot_cdf_X(X, ro, hetero_clusters, N_fluctuating_frac=0.3, serv_time_rv=Exp(serv_rate))
# plot_(ro=0.2, hetero_clusters=False)
# plot_(ro=0.5, hetero_clusters=False)
# plot_(ro=0.8, hetero_clusters=False)
# plot_(ro=0.9, hetero_clusters=False)
# plot_(ro=0.2, hetero_clusters=True)
# plot_(ro=0.5, hetero_clusters=True)
# plot_(ro=0.8, hetero_clusters=True)
# plot_(ro=0.9, hetero_clusters=True)
# plot_(ro=0.3, hetero_clusters=True)
plot_(ro=0.8, hetero_clusters=True)
log(INFO, "done")
def plot_EX_vs_ro(X, hetero_clusters, N_fluctuating_frac, serv_time_rv):
log(INFO, "started", hetero_clusters=hetero_clusters, N_fluctuating_frac=N_fluctuating_frac, serv_time_rv=serv_time_rv)
ro = ''
ro_EX_l_podc = read_json_from_file(fname=get_filename('{}/ro_E{}_l_podc_d_{}_p_{}'.format(SUBFOLDER_PODC, X, d, p), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
ro_std_X_l_podc = read_json_from_file(fname=get_filename('{}/ro_std_{}_l_podc_d_{}_p_{}'.format(SUBFOLDER_PODC, X, d, p), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
ro_EX_l_ts_w_0 = read_json_from_file(fname=get_filename('{}/ro_E{}_l_ts_w_0'.format(SUBFOLDER_TS, X), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
ro_std_X_l_ts_w_0 = read_json_from_file(fname=get_filename('{}/ro_std_{}_l_ts_w_0'.format(SUBFOLDER_TS, X), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
ro_EX_l_ts_w_20 = read_json_from_file(fname=get_filename('{}/ro_E{}_l_ts_w_20'.format(SUBFOLDER_TS, X), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
ro_std_X_l_ts_w_20 = read_json_from_file(fname=get_filename('{}/ro_std_{}_l_ts_w_20'.format(SUBFOLDER_TS, X), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
ro_EX_l_ts_w_100 = read_json_from_file(fname=get_filename('{}/ro_E{}_l_ts_w_100'.format(SUBFOLDER_TS, X), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
ro_std_X_l_ts_w_100 = read_json_from_file(fname=get_filename('{}/ro_std_{}_l_ts_w_100'.format(SUBFOLDER_TS, X), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
ro_EX_l_ts_w_m20 = read_json_from_file(fname=get_filename('{}/ro_E{}_l_ts_w_-20'.format(SUBFOLDER_TS, X), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
ro_std_X_l_ts_w_m20 = read_json_from_file(fname=get_filename('{}/ro_std_{}_l_ts_w_-20'.format(SUBFOLDER_TS, X), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
ro_EX_l_rr = read_json_from_file(fname=get_filename('{}/ro_E{}_l_rr'.format(SUBFOLDER_RR, X), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
ro_std_X_l_rr = read_json_from_file(fname=get_filename('{}/ro_std_{}_l_rr'.format(SUBFOLDER_RR, X), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
ro_EX_l_ucb_w_0 = read_json_from_file(fname=get_filename('{}/ro_E{}_l_ucb_w_0'.format(SUBFOLDER_UCB, X), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
ro_std_X_l_ucb_w_0 = read_json_from_file(fname=get_filename('{}/ro_std_{}_l_ucb_w_0'.format(SUBFOLDER_UCB, X), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
ro_EX_l_ucb_w_100 = read_json_from_file(fname=get_filename('{}/ro_E{}_l_ucb_w_100'.format(SUBFOLDER_UCB, X), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
ro_std_X_l_ucb_w_100 = read_json_from_file(fname=get_filename('{}/ro_std_{}_l_ucb_w_100'.format(SUBFOLDER_UCB, X), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
def plot_(ro_EX_l, ro_std_X_l, label):
if ro_EX_l is None:
return
# check(len(ro_EX_l) == len(ro_std_X_l), "ro_EX_l and ro_std_X_l must have the same size")
ro_l, EX_l, std_X_l = [], [], []
for i in range(len(ro_EX_l)):
ro, EX = ro_EX_l[i]
# ro_, std_X = ro_std_X_l[i]
# check(ro == ro_, "ro's should match for EX and std_X")
ro_l.append(ro)
EX_l.append(EX)
# std_X_l.append(std_X)
# plot.errorbar(ro_l, EX_l, yerr=std_X_l, label=label, color=next(light_color), marker='x', linestyle='solid', lw=2, mew=3, ms=5)
plot.plot(ro_l, EX_l, label=label, color=next(nice2_color), marker='x', linestyle='solid', lw=3, mew=3, ms=7)
# plot_(ro_EX_l_podc, ro_std_X_l_podc, label='PodC')
# plot_(ro_EX_l_ts_w_0, ro_std_X_l_ts_w_0, label='TS-ROR')
# plot_(ro_EX_l_ts_w_20, ro_std_X_l_ts_w_20, label='TS, w=20')
# plot_(ro_EX_l_ts_w_100, ro_std_X_l_ts_w_100, label='TS, w=100')
# plot_(ro_EX_l_rr, ro_std_X_l_rr, label='RR')
# plot_(ro_EX_l_ucb_w_100, ro_std_X_l_ucb_w_100, label='UCB, w=100')
## With ordering legends
def plot_w_ordering_legends():
last_EX__ro_EX_l__label_l = []
def append(ro_EX_l, label):
if ro_EX_l:
last_EX__ro_EX_l__label_l.append((ro_EX_l[-1][1], ro_EX_l, label))
append(ro_EX_l_podc, 'PodC')
append(ro_EX_l_ts_w_0, 'TS-ROR')
append(ro_EX_l_ts_w_20, 'TS, w=20')
append(ro_EX_l_ts_w_100, 'TS, w=100')
# append(ro_EX_l_ts_w_m20, 'TS, w=-20')
append(ro_EX_l_rr, 'RR')
append(ro_EX_l_ucb_w_0, 'UCB-ROR')
append(ro_EX_l_ucb_w_100, 'UCB, w=100')
last_EX__ro_EX_l__label_l.sort()
for _, ro_EX_l, label in reversed(last_EX__ro_EX_l__label_l):
plot_(ro_EX_l, None, label)
plot_w_ordering_legends()
fontsize = 14
plot.legend(fontsize=fontsize, bbox_to_anchor=(1.01, 1))
plot.yscale('log')
plot.ylabel(r'$E[{}]$'.format(X), fontsize=fontsize)
plot.xlabel(r'$\rho$', fontsize=fontsize)
# plot.title(r'$d= {}, p= {}$'.format(d, p) + ', ' + get_plot_title(ro=None, hetero_clusters=hetero_clusters, N_fluctuating_frac=N_fluctuating_frac, serv_time_rv=serv_time_rv))
plot.title(r'$d= {}, p= {}$'.format(d, p) + ', ' + get_plot_title(ro=None, hetero_clusters=hetero_clusters, N_fluctuating_frac=N_fluctuating_frac, serv_time_rv="Constant(1)"))
plot.gcf().set_size_inches(6, 4)
plot_save(get_filename("plot_E{}_vs_ro".format(X), 'png', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv), bbox_inches='tight')
plot.gcf().clear()
log(INFO, "done")
def plot_EX_vs_ro_for_varying_config(X):
log(INFO, "started", X=X)
hetero_clusters = False
plot_EX_vs_ro(X, hetero_clusters, N_fluctuating_frac=0, serv_time_rv=DiscreteRV(p_l=[1], v_l=[1 / serv_rate]))
# plot_EX_vs_ro(X, hetero_clusters, N_fluctuating_frac=0, serv_time_rv=Exp(serv_rate))
plot_EX_vs_ro(X, hetero_clusters, N_fluctuating_frac=0.3, serv_time_rv=DiscreteRV(p_l=[1], v_l=[1 / serv_rate]))
# plot_EX_vs_ro(X, hetero_clusters, N_fluctuating_frac=0.3, serv_time_rv=Exp(serv_rate))
hetero_clusters = True
plot_EX_vs_ro(X, hetero_clusters, N_fluctuating_frac=0, serv_time_rv=DiscreteRV(p_l=[1], v_l=[1 / serv_rate]))
# plot_EX_vs_ro(X, hetero_clusters, N_fluctuating_frac=0, serv_time_rv=Exp(serv_rate))
plot_EX_vs_ro(X, hetero_clusters, N_fluctuating_frac=0.3, serv_time_rv=DiscreteRV(p_l=[1], v_l=[1 / serv_rate]))
# plot_EX_vs_ro(X, hetero_clusters, N_fluctuating_frac=0.3, serv_time_rv=Exp(serv_rate))
log(INFO, "done")
def plot_X_over_time(X, cid, ro, hetero_clusters, N_fluctuating_frac, serv_time_rv, save_to_png=False):
log(INFO, "started", X=X, cid=cid, ro=ro, hetero_clusters=hetero_clusters, N_fluctuating_frac=N_fluctuating_frac, serv_time_rv=serv_time_rv, save_to_png=save_to_png)
cl_id__c_m = {}
def plot_(subfolder, header, label):
nonlocal cl_id__c_m
req_info_m_l = read_json_from_file(fname=get_filename('{}/req_info_m_l_{}_{}'.format(subfolder, cid, header), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
if req_info_m_l is None:
log(WARNING, "Nothing to plot, done.")
return
for i, req_info_m in enumerate(req_info_m_l):
cl_id = req_info_m['cl_id']
if cl_id not in cl_id__c_m:
cl_id__c_m[cl_id] = next(dark_color)
c = cl_id__c_m[cl_id]
if save_to_png and i > 1000:
break
plot.bar([i + 1], height=[req_info_m[X]], color=c) # self.color_map.get_color(info_m_q[_i]['mip'])
plot.xticks([])
fontsize = 14
plot.legend(fontsize=fontsize)
plot.yscale('log')
plot.ylabel(r'${}$'.format(X), fontsize=fontsize)
plot.xlabel('Requests over time', fontsize=fontsize)
plot.title(r'{}, {}, $d= {}, p= {}$'.format(label, cid, d, p) + ', ' + get_plot_title(ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
if save_to_png:
plot.gcf().set_size_inches(16, 4)
plot_save(get_filename("plot_{}_{}_over_time_{}".format(cid, X, header), 'png', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv), bbox_inches='tight')
plot.gcf().clear()
else:
f = zoom_factory(plot.gca(), base_scale=1.5)
plot.show()
plot_(subfolder=SUBFOLDER_PODC, header='podc_d_{}_p_{}'.format(d, p), label='PodC')
plot_(subfolder=SUBFOLDER_TS, header='ts_w_0', label='TS, w=0')
# plot_(subfolder=SUBFOLDER_TS, header='ts_w_20', label='TS, w=20')
# plot_(subfolder=SUBFOLDER_TS, header='ts_w_100', label='TS, w=100')
plot_(subfolder=SUBFOLDER_RR, header='rr', label='RR')
log(DEBUG, "done")
def plot_X_over_time_for_varying_config(X):
ro = 0.3
# ro = 0.8
def plot_(cid):
plot_X_over_time(X, cid, ro, hetero_clusters=True, N_fluctuating_frac=0.0, serv_time_rv=DiscreteRV(p_l=[1], v_l=[1 / serv_rate]), save_to_png=True)
plot_X_over_time(X, cid, ro, hetero_clusters=True, N_fluctuating_frac=0.3, serv_time_rv=DiscreteRV(p_l=[1], v_l=[1 / serv_rate]), save_to_png=True)
# plot_X_over_time(X, cid, ro, hetero_clusters=True, N_fluctuating_frac=0, serv_time_rv=Exp(serv_rate), save_to_png=True)
plot_(cid='c0')
log(DEBUG, "done")
def plot_cl_load_over_time(cl_id, ro, hetero_clusters, N_fluctuating_frac, serv_time_rv, save_to_png=False):
log(INFO, "started", cl_id=cl_id, ro=ro, hetero_clusters=hetero_clusters, N_fluctuating_frac=N_fluctuating_frac, serv_time_rv=serv_time_rv, save_to_png=save_to_png)
def plot_(subfolder, header, label):
epoch_num_req_l = read_json_from_file(fname=get_filename('{}/epoch_num_req_l_{}_{}'.format(subfolder, cl_id, header), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
if epoch_num_req_l is None:
return
epoch_l, num_req_l = [], []
for i, (epoch, num_req) in enumerate(epoch_num_req_l):
epoch_l.append(epoch)
num_req_l.append(num_req)
if save_to_png and i > 3*6500:
break
plot.plot(epoch_l, num_req_l, color=next(nice_color), marker='o', linestyle=':', lw=2, mew=3, ms=5)
fontsize = 14
plot.xticks([])
plot.legend(fontsize=fontsize)
plot.ylabel('Number of requests', fontsize=fontsize)
plot.xlabel('Time', fontsize=fontsize)
plot.title(r'{}, {}, $d= {}, p= {}$'.format(label, cl_id, d, p) + ', ' + get_plot_title(ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
if save_to_png:
plot.gcf().set_size_inches(15, 4)
plot_save(get_filename("plot_{}_loadOverTime_{}".format(cl_id, header), 'png', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv), bbox_inches='tight')
plot.gcf().clear()
else:
f = zoom_factory(plot.gca(), base_scale=1.5)
plot.show()
# plot_(subfolder=SUBFOLDER_PODC, header='podc_d_{}_p_{}'.format(d, p), label='PodC')
plot_(subfolder=SUBFOLDER_TS, header='ts_w_0', label='TS, w=0')
# plot_(subfolder=SUBFOLDER_TS, header='ts_w_20', label='TS, w=20')
# plot_(subfolder=SUBFOLDER_TS, header='ts_w_100', label='TS, w=100')
# plot_(subfolder=SUBFOLDER_RR, header='rr', label='RR')
log(DEBUG, "done")
def plot_cl_load_over_time_for_varying_config():
# ro = 0.3
ro = 0.8
def plot_(cl_id):
plot_cl_load_over_time(cl_id, ro=ro, hetero_clusters=False, N_fluctuating_frac=0.3, serv_time_rv=DiscreteRV(p_l=[1], v_l=[1 / serv_rate]), save_to_png=True)
# plot_cl_load_over_time(cl_id, ro=ro, hetero_clusters=True, N_fluctuating_frac=0, serv_time_rv=DiscreteRV(p_l=[1], v_l=[1 / serv_rate]), save_to_png=True)
# plot_cl_load_over_time(cl_id, ro=ro, hetero_clusters=True, N_fluctuating_frac=0, serv_time_rv=Exp(serv_rate), save_to_png=True)
# plot_cl_load_over_time(cl_id, ro=ro, hetero_clusters=True, N_fluctuating_frac=0.3, serv_time_rv=DiscreteRV(p_l=[1], v_l=[1 / serv_rate]), save_to_png=True)
# plot_cl_load_over_time(cl_id, ro=ro, hetero_clusters=True, N_fluctuating_frac=0.3, serv_time_rv=Exp(serv_rate), save_to_png=True)
plot_(cl_id='cl0')
plot_(cl_id='cl9')
log(DEBUG, "done")
def check_bug():
d, p = 2, 10
ro = 0.9
hetero_clusters = True
N_fluctuating_frac = 0.3
serv_time_rv = DiscreteRV(p_l=[1], v_l=[1 / serv_rate])
T_podc_l = read_json_from_file(fname=get_filename('{}/T_l_podc_d_{}_p_{}'.format(SUBFOLDER_PODC, d, p), 'json', ro, hetero_clusters, N_fluctuating_frac, serv_time_rv))
T_podc_l.sort()
log(INFO, "", len_T_podc_l=len(T_podc_l), T_podc_l_first_20=T_podc_l[:20])
if __name__ == '__main__':
log_to_std()
# plot_ET_vs_d_p_for_varying_config()
# plot_cdf_X_for_varying_config()
# plot_EX_vs_ro_for_varying_config(X='T')
# plot_EX_vs_ro_for_varying_config(X='RW')
# plot_X_over_time_for_varying_config(X='T')
plot_cl_load_over_time_for_varying_config()
# check_bug()