def test_isls_plus_grid(self):
for values in [(25, 25, 1), (10, 5, 0), (24, 66, 6), (3, 3, 0)]:
num_orbits = values[0]
num_sat_per_orbit = values[1]
isl_shift = values[2]
satgen.generate_plus_grid_isls("isls.txt.tmp", num_orbits,
num_sat_per_orbit, isl_shift)
isls_list = satgen.read_isls("isls.txt.tmp",
num_orbits * num_sat_per_orbit)
os.remove("isls.txt.tmp")
self.assertEqual(len(isls_list),
num_orbits * num_sat_per_orbit * 2)
self.assertEqual(len(set(isls_list)),
num_orbits * num_sat_per_orbit * 2)
for i in range(num_orbits * num_sat_per_orbit):
orbit_of_i = int(floor(i / float(num_sat_per_orbit)))
# Links in same orbit
neighbor_1 = orbit_of_i * num_sat_per_orbit + (
i + num_sat_per_orbit + 1) % num_sat_per_orbit
neighbor_2 = orbit_of_i * num_sat_per_orbit + (
i + num_sat_per_orbit - 1) % num_sat_per_orbit
# Links to different orbits
neighbor_3 = (
((orbit_of_i + num_orbits - 1) % num_orbits) *
num_sat_per_orbit +
(i + num_sat_per_orbit - isl_shift) % num_sat_per_orbit)
neighbor_4 = (
((orbit_of_i + num_orbits + 1) % num_orbits) *
num_sat_per_orbit +
(i + num_sat_per_orbit + isl_shift) % num_sat_per_orbit)
# All of them must be present
self.assertTrue((min(i, neighbor_1),
max(i, neighbor_1)) in isls_list)
self.assertTrue((min(i, neighbor_2),
max(i, neighbor_2)) in isls_list)
self.assertTrue((min(i, neighbor_3),
max(i, neighbor_3)) in isls_list)
self.assertTrue((min(i, neighbor_4),
max(i, neighbor_4)) in isls_list)
def test_isls_plus_grid_invalid(self):
try:
satgen.generate_plus_grid_isls("isls.txt.tmp", 2, 2, 0)
self.fail()
except ValueError:
self.assertTrue(True)
try:
satgen.generate_plus_grid_isls("isls.txt.tmp", 3, 2, 0)
self.fail()
except ValueError:
self.assertTrue(True)
try:
satgen.generate_plus_grid_isls("isls.txt.tmp", 1, 1, 0)
self.fail()
except ValueError:
self.assertTrue(True)
def calculate(
self,
output_generated_data_dir, # Final directory in which the result will be placed
duration_s,
time_step_ms,
isl_selection, # isls_{none, plus_grid}
gs_selection, # ground_stations_{top_100, paris_moscow_grid}
dynamic_state_algorithm, # algorithm_{free_one_only_{gs_relays,_over_isls}, paired_many_only_over_isls}
num_threads):
# Add base name to setting
name = self.BASE_NAME + "_" + isl_selection + "_" + gs_selection + "_" + dynamic_state_algorithm
# Create output directories
if not os.path.isdir(output_generated_data_dir):
os.makedirs(output_generated_data_dir, exist_ok=True)
if not os.path.isdir(output_generated_data_dir + "/" + name):
os.makedirs(output_generated_data_dir + "/" + name, exist_ok=True)
# Ground stations
print("Generating ground stations...")
if gs_selection == "ground_stations_top_100":
satgen.extend_ground_stations(
"input_data/ground_stations_cities_sorted_by_estimated_2025_pop_top_100.basic.txt",
output_generated_data_dir + "/" + name +
"/ground_stations.txt")
elif gs_selection == "ground_stations_paris_moscow_grid":
satgen.extend_ground_stations(
"input_data/ground_stations_paris_moscow_grid.basic.txt",
output_generated_data_dir + "/" + name +
"/ground_stations.txt")
else:
raise ValueError("Unknown ground station selection: " +
gs_selection)
# TLEs
print("Generating TLEs...")
satgen.generate_tles_from_scratch_manual(
output_generated_data_dir + "/" + name + "/tles.txt",
self.NICE_NAME, self.NUM_ORBS, self.NUM_SATS_PER_ORB,
self.PHASE_DIFF, self.INCLINATION_DEGREE, self.ECCENTRICITY,
self.ARG_OF_PERIGEE_DEGREE, self.MEAN_MOTION_REV_PER_DAY)
# ISLs
print("Generating ISLs...")
if isl_selection == "isls_plus_grid":
satgen.generate_plus_grid_isls(output_generated_data_dir + "/" +
name + "/isls.txt",
self.NUM_ORBS,
self.NUM_SATS_PER_ORB,
isl_shift=0,
idx_offset=0)
elif isl_selection == "isls_none":
satgen.generate_empty_isls(output_generated_data_dir + "/" + name +
"/isls.txt")
else:
raise ValueError("Unknown ISL selection: " + isl_selection)
# Description
print("Generating description...")
satgen.generate_description(
output_generated_data_dir + "/" + name + "/description.txt",
self.MAX_GSL_LENGTH_M, self.MAX_ISL_LENGTH_M)
# GSL interfaces
ground_stations = satgen.read_ground_stations_extended(
output_generated_data_dir + "/" + name + "/ground_stations.txt")
if dynamic_state_algorithm == "algorithm_free_one_only_gs_relays" \
or dynamic_state_algorithm == "algorithm_free_one_only_over_isls":
gsl_interfaces_per_satellite = 1
elif dynamic_state_algorithm == "algorithm_paired_many_only_over_isls":
gsl_interfaces_per_satellite = len(ground_stations)
else:
raise ValueError("Unknown dynamic state algorithm: " +
dynamic_state_algorithm)
print("Generating GSL interfaces info..")
satgen.generate_simple_gsl_interfaces_info(
output_generated_data_dir + "/" + name +
"/gsl_interfaces_info.txt",
self.NUM_ORBS * self.NUM_SATS_PER_ORB,
len(ground_stations),
gsl_interfaces_per_satellite, # GSL interfaces per satellite
1, # (GSL) Interfaces per ground station
1, # Aggregate max. bandwidth satellite (unit unspecified)
1 # Aggregate max. bandwidth ground station (same unspecified unit)
)
# Forwarding state
print("Generating forwarding state...")
satgen.help_dynamic_state(
output_generated_data_dir,
num_threads, # Number of threads
name,
time_step_ms,
duration_s,
self.MAX_GSL_LENGTH_M,
self.MAX_ISL_LENGTH_M,
dynamic_state_algorithm,
True)
def test_end_to_end(self):
local_shell = exputil.LocalShell()
# Clean slate start
local_shell.remove_force_recursive("temp_gen_data")
local_shell.make_full_dir("temp_gen_data")
# Both dynamic state algorithms should yield the same path and RTT
for dynamic_state_algorithm in [
"algorithm_free_one_only_over_isls",
"algorithm_free_gs_one_sat_many_only_over_isls"
]:
# Specific outcomes
output_generated_data_dir = "temp_gen_data"
num_threads = 1
default_time_step_ms = 100
all_time_step_ms = [50, 100, 1000, 10000, 20000]
duration_s = 200
# Add base name to setting
name = "triangle_reduced_kuiper_630_" + dynamic_state_algorithm
# Create output directories
if not os.path.isdir(output_generated_data_dir):
os.makedirs(output_generated_data_dir)
if not os.path.isdir(output_generated_data_dir + "/" + name):
os.makedirs(output_generated_data_dir + "/" + name)
# Ground stations
print("Generating ground stations...")
with open(
output_generated_data_dir + "/" + name +
"/ground_stations.basic.txt", "w+") as f_out:
f_out.write(
"0,Manila,14.6042,120.9822,0\n") # Originally no. 17
f_out.write(
"1,Dalian,38.913811,121.602322,0\n") # Originally no. 85
f_out.write(
"2,Sankt-Peterburg-(Saint-Petersburg),59.929858,30.326228,0\n"
) # Originally no. 73
satgen.extend_ground_stations(
output_generated_data_dir + "/" + name +
"/ground_stations.basic.txt", output_generated_data_dir + "/" +
name + "/ground_stations.txt")
# Path trace we base this test on:
# (1) 1173 -> 1241
# 0,1173-184-183-217-1241
# 18000000000,1173-218-217-1241
# 27600000000,1173-648-649-650-616-1241
# 74300000000,1173-218-217-216-250-1241
# 125900000000,1173-647-648-649-650-616-1241
# 128700000000,1173-647-648-649-615-1241
# (2) 1229 -> 1241
# 0,1229-144-178-212-246-280-281-282-283-1241
# 3300000000,1229-177-178-212-246-280-281-282-283-1241
# 10100000000,1229-177-178-212-246-247-248-249-1241
# 128700000000,1229-177-211-245-246-247-248-249-1241
# 139500000000,1229-144-178-212-246-247-248-249-1241
# 155400000000,Unreachable
# 165200000000,1229-143-177-211-245-279-280-281-282-1241
# 178800000000,1229-176-177-211-245-279-280-281-282-1241
# (3) 1229 -> 1173
# 0,1229-144-178-179-180-181-182-183-184-1173
# 3300000000,1229-177-178-179-180-181-182-183-184-1173
# 139500000000,1229-144-178-179-180-181-182-183-184-1173
# 150100000000,1229-144-178-179-180-181-182-183-1173
# 155400000000,Unreachable
# 165200000000,1229-143-177-178-179-180-181-182-183-1173
# 178800000000,1229-176-177-178-179-180-181-182-183-1173
# Select all satellite IDs
subset_of_satellites = set()
for path_filename in [
"tests/data_to_match/kuiper_630/networkx_path_1173_to_1241.txt",
"tests/data_to_match/kuiper_630/networkx_path_1229_to_1173.txt",
"tests/data_to_match/kuiper_630/networkx_path_1229_to_1241.txt",
]:
columns = exputil.read_csv_direct_in_columns(
path_filename, "pos_int,string")
for path in columns[1]:
if path != "Unreachable":
for sat_id in list(
map(lambda x: int(x),
path.split("-")[1:-1])):
subset_of_satellites.add(sat_id)
list_of_satellites = sorted(list(subset_of_satellites))
original_sat_id_to_new_sat_id = {}
for i in range(len(list_of_satellites)):
original_sat_id_to_new_sat_id[list_of_satellites[i]] = i
# Generate normal TLEs and then only filter out the limited satellite list
print("Generating TLEs...")
satgen.generate_tles_from_scratch_manual(
output_generated_data_dir + "/" + name + "/tles_complete.txt",
NICE_NAME, NUM_ORBS, NUM_SATS_PER_ORB, PHASE_DIFF,
INCLINATION_DEGREE, ECCENTRICITY, ARG_OF_PERIGEE_DEGREE,
MEAN_MOTION_REV_PER_DAY)
with open(
output_generated_data_dir + "/" + name +
"/tles_complete.txt", "r") as f_in:
with open(output_generated_data_dir + "/" + name + "/tles.txt",
"w+") as f_out:
f_out.write(
"1 %d\n" % len(list_of_satellites)
) # Pretend its one orbit with N satellites simply
i = 0
for line in f_in:
line = line.strip()
if int(math.floor(
(i - 1) / 3.0)) in list_of_satellites:
if (i - 1) % 3 == 0:
f_out.write("%s %d\n" %
(line.split(" ")[0],
original_sat_id_to_new_sat_id[int(
line.split(" ")[1])]))
else:
f_out.write("%s\n" % line)
i += 1
# ISLs
print("Generating ISLs...")
complete_list_isls = satgen.generate_plus_grid_isls(
output_generated_data_dir + "/" + name +
"/isls_complete.temp.txt",
NUM_ORBS,
NUM_SATS_PER_ORB,
isl_shift=0,
idx_offset=0)
with open(output_generated_data_dir + "/" + name + "/isls.txt",
"w+") as f_out:
for isl in complete_list_isls:
if isl[0] in list_of_satellites and isl[
1] in list_of_satellites:
f_out.write("%d %d\n" %
(original_sat_id_to_new_sat_id[isl[0]],
original_sat_id_to_new_sat_id[isl[1]]))
# Description
print("Generating description...")
satgen.generate_description(
output_generated_data_dir + "/" + name + "/description.txt",
MAX_GSL_LENGTH_M, MAX_ISL_LENGTH_M)
# Extended ground stations
ground_stations = satgen.read_ground_stations_extended(
output_generated_data_dir + "/" + name +
"/ground_stations.txt")
# GSL interfaces
if dynamic_state_algorithm == "algorithm_free_one_only_over_isls":
gsl_interfaces_per_satellite = 1
gsl_satellite_max_agg_bandwidth = 1.0
elif dynamic_state_algorithm == "algorithm_free_gs_one_sat_many_only_over_isls":
gsl_interfaces_per_satellite = len(ground_stations)
gsl_satellite_max_agg_bandwidth = len(ground_stations)
else:
raise ValueError("Unknown dynamic state algorithm: " +
dynamic_state_algorithm)
print("Generating GSL interfaces info..")
satgen.generate_simple_gsl_interfaces_info(
output_generated_data_dir + "/" + name +
"/gsl_interfaces_info.txt",
len(list_of_satellites), # N satellites
len(ground_stations),
gsl_interfaces_per_satellite, # GSL interfaces per satellite
1, # (GSL) Interfaces per ground station
gsl_satellite_max_agg_bandwidth, # Aggregate max. bandwidth satellite (unit unspecified)
1 # Aggregate max. bandwidth ground station (same unspecified unit)
)
# Forwarding state
for time_step_ms in all_time_step_ms:
print("Generating forwarding state...")
satgen.help_dynamic_state(output_generated_data_dir,
num_threads, name, time_step_ms,
duration_s, MAX_GSL_LENGTH_M,
MAX_ISL_LENGTH_M,
dynamic_state_algorithm, False)
# Clean slate start
local_shell.remove_force_recursive("temp_analysis_data")
local_shell.make_full_dir("temp_analysis_data")
output_analysis_data_dir = "temp_analysis_data"
# Check the path and RTT for each pair
new_gs_id_to_old_node_id = {0: 1173, 1: 1241, 2: 1229}
old_node_id_to_new_node_id = {
1173: len(list_of_satellites) + 0,
1241: len(list_of_satellites) + 1,
1229: len(list_of_satellites) + 2,
}
min_rtts = []
max_rtts = []
for (src, dst) in [(0, 1), (0, 2), (1, 0), (1, 2), (2, 0), (2, 1)]:
# Find node identifiers
src_node_id = len(list_of_satellites) + src
dst_node_id = len(list_of_satellites) + dst
old_src_node_id = new_gs_id_to_old_node_id[src]
old_dst_node_id = new_gs_id_to_old_node_id[dst]
# Print the routes
satgen.post_analysis.print_routes_and_rtt(
output_analysis_data_dir + "/" + name,
output_generated_data_dir + "/" + name,
default_time_step_ms, duration_s, src_node_id, dst_node_id,
"")
# Now, we just want to see that the output path matches
with open(
output_analysis_data_dir + "/" + name +
"/data/networkx_path_%d_to_%d.txt" %
(src_node_id, dst_node_id), "r") as f_in1:
with open(
"tests/data_to_match/kuiper_630/networkx_path_%d_to_%d.txt"
% (old_src_node_id, old_dst_node_id),
"r") as f_in2:
lines1 = []
for line in f_in1:
lines1.append(line.strip())
lines2 = []
for line in f_in2:
lines2.append(line.strip())
self.assertEqual(len(lines1), len(lines2))
for i in range(len(lines1)):
spl1 = lines1[i].split(",")
spl2 = lines2[i].split(",")
# Time must be equal
self.assertEqual(spl1[0], spl2[0])
# Path must be equal
if spl1[1] == "Unreachable" or spl2[
1] == "Unreachable":
self.assertEqual(spl1[1], spl2[1])
else:
node_list1 = list(
map(lambda x: int(x), spl1[1].split("-")))
node_list2 = list(
map(lambda x: int(x), spl2[1].split("-")))
new_node_list2 = []
for j in range(len(node_list2)):
if j == 0 or j == len(node_list2) - 1:
new_node_list2.append(
old_node_id_to_new_node_id[
node_list2[j]])
else:
new_node_list2.append(
original_sat_id_to_new_sat_id[
node_list2[j]])
self.assertEqual(node_list1, new_node_list2)
# ... and the RTT
lowest_rtt_ns = 100000000000
highest_rtt_ns = 0
with open(
output_analysis_data_dir + "/" + name +
"/data/networkx_rtt_%d_to_%d.txt" %
(src_node_id, dst_node_id), "r") as f_in1:
with open(
"tests/data_to_match/kuiper_630/networkx_rtt_%d_to_%d.txt"
% (old_src_node_id, old_dst_node_id),
"r") as f_in2:
lines1 = []
for line in f_in1:
lines1.append(line.strip())
lines2 = []
for line in f_in2:
lines2.append(line.strip())
# Too computationally costly, so the below is equivalent: self.assertEqual(lines1, lines2)
self.assertEqual(len(lines1), len(lines2))
for i in range(len(lines1)):
a_spl = lines1[i].split(",")
b_spl = lines2[i].split(",")
self.assertEqual(len(a_spl), len(b_spl))
self.assertEqual(len(a_spl), 2)
a_time = int(a_spl[0])
b_time = int(b_spl[0])
a_rtt = float(a_spl[1])
b_rtt = float(b_spl[1])
if a_rtt != 0:
lowest_rtt_ns = min(a_rtt, lowest_rtt_ns)
highest_rtt_ns = max(a_rtt, highest_rtt_ns)
self.assertEqual(a_time, b_time)
self.assertAlmostEqual(a_rtt, b_rtt, places=5)
# Save RTTs
if src < dst:
min_rtts.append(lowest_rtt_ns)
max_rtts.append(highest_rtt_ns)
# Now let's run all analyses available
# TODO: Disabled because it requires downloading files from CDNs, which can take too long
# # Print graphically
#
# satgen.post_analysis.print_graphical_routes_and_rtt(
# output_analysis_data_dir + "/" + name,
# output_generated_data_dir + "/" + name,
# default_time_step_ms,
# duration_s,
# 12,
# 13
# )
# Analyze paths
satgen.post_analysis.analyze_path(
output_analysis_data_dir + "/" + name,
output_generated_data_dir + "/" + name, default_time_step_ms,
duration_s, "")
# Number of path changes per pair
columns = exputil.read_csv_direct_in_columns(
output_analysis_data_dir + "/" + name + "/" + name +
"/100ms_for_200s/path/data/ecdf_pairs_num_path_changes.txt",
"float,pos_float")
self.assertEqual(4, len(columns[0]))
for i in range(len(columns[0])):
# Cumulative y-axis check
if i == 0:
self.assertEqual(columns[1][i], 0)
elif i == 1:
self.assertAlmostEqual(columns[1][i],
1.0 / 3.0,
delta=0.0001)
elif i == 2:
self.assertAlmostEqual(columns[1][i],
2.0 / 3.0,
delta=0.0001)
else:
self.assertEqual(columns[1][i], 1.0)
# There are three pairs, with 5, 6 and 7 path changes
if i == 0:
self.assertEqual(columns[0][i], float("-inf"))
elif i == 1:
self.assertEqual(columns[0][i], 5.0)
elif i == 2:
self.assertEqual(columns[0][i], 6.0)
else:
self.assertEqual(columns[0][i], 7.0)
# Max minus min hop count per pair
columns = exputil.read_csv_direct_in_columns(
output_analysis_data_dir + "/" + name + "/" + name +
"/100ms_for_200s/path/data/ecdf_pairs_max_minus_min_hop_count.txt",
"float,pos_float")
self.assertEqual(4, len(columns[0]))
for i in range(len(columns[0])):
# Cumulative y-axis check
if i == 0:
self.assertEqual(columns[1][i], 0)
elif i == 1:
self.assertAlmostEqual(columns[1][i],
1.0 / 3.0,
delta=0.0001)
elif i == 2:
self.assertAlmostEqual(columns[1][i],
2.0 / 3.0,
delta=0.0001)
else:
self.assertEqual(columns[1][i], 1.0)
# One with 3 vs. 6, and two with 8 vs. 9
if i == 0:
self.assertEqual(columns[0][i], float("-inf"))
elif i == 1:
self.assertEqual(columns[0][i], 1)
elif i == 2:
self.assertEqual(columns[0][i], 1)
else:
self.assertEqual(columns[0][i], 3)
# Max divided by min hop count per pair
columns = exputil.read_csv_direct_in_columns(
output_analysis_data_dir + "/" + name + "/" + name +
"/100ms_for_200s/path/data/ecdf_pairs_max_hop_count_to_min_hop_count.txt",
"float,pos_float")
self.assertEqual(4, len(columns[0]))
for i in range(len(columns[0])):
# Cumulative y-axis check
if i == 0:
self.assertEqual(columns[1][i], 0)
elif i == 1:
self.assertAlmostEqual(columns[1][i],
1.0 / 3.0,
delta=0.0001)
elif i == 2:
self.assertAlmostEqual(columns[1][i],
2.0 / 3.0,
delta=0.0001)
else:
self.assertEqual(columns[1][i], 1.0)
# One with 3 vs. 6, and two with 8 vs. 9
if i == 0:
self.assertEqual(columns[0][i], float("-inf"))
elif i == 1:
self.assertAlmostEqual(columns[0][i],
9.0 / 8.0,
delta=0.0001)
elif i == 2:
self.assertAlmostEqual(columns[0][i],
9.0 / 8.0,
delta=0.0001)
else:
self.assertEqual(columns[0][i], 2.0)
# These are the path changes
# 18000000000,1173-218-217-1241
# 27600000000,1173-648-649-650-616-1241
# 3300000000,1229-177-178-179-180-181-182-183-184-1173
# 3300000000,1229-177-178-212-246-280-281-282-283-1241
# 74300000000,1173-218-217-216-250-1241
# 10100000000,1229-177-178-212-246-247-248-249-1241
# 125900000000,1173-647-648-649-650-616-1241
# 128700000000,1229-177-211-245-246-247-248-249-1241
# 128700000000,1173-647-648-649-615-1241
# 139500000000,1229-144-178-179-180-181-182-183-184-1173
# 139500000000,1229-144-178-212-246-247-248-249-1241
# 150100000000,1229-144-178-179-180-181-182-183-1173
# 155400000000,Unreachable
# 155400000000,Unreachable
# 165200000000,1229-143-177-211-245-279-280-281-282-1241
# 165200000000,1229-143-177-178-179-180-181-182-183-1173
# 178800000000,1229-176-177-211-245-279-280-281-282-1241
# 178800000000,1229-176-177-178-179-180-181-182-183-1173
# For all pairs, the distribution how many times they changed path in a time step
columns = exputil.read_csv_direct_in_columns(
output_analysis_data_dir + "/" + name + "/" + name +
"/100ms_for_200s/path/data/ecdf_time_step_num_path_changes.txt",
"float,pos_float")
start_cumulative = 0.0
for i in range(len(columns[0])):
# Cumulative y-axis check
if i == 0:
self.assertEqual(columns[1][i], start_cumulative)
else:
self.assertGreater(columns[1][i], start_cumulative)
if i - 1 == range(len(columns[0])):
self.assertEqual(columns[1][i], 1.0)
# There are 12 time steps, of which 6 have 2 changes, and 6 have 1 change
if i == 0:
self.assertEqual(columns[0][i], float("-inf"))
elif i > 2000 - 7:
self.assertEqual(columns[0][i], 2.0)
elif i > 2000 - 13:
self.assertEqual(columns[0][i], 1.0)
else:
self.assertEqual(columns[0][i], 0)
# Analyze RTTs
satgen.post_analysis.analyze_rtt(
output_analysis_data_dir + "/" + name,
output_generated_data_dir + "/" + name, default_time_step_ms,
duration_s, "")
# Min. RTT
columns = exputil.read_csv_direct_in_columns(
output_analysis_data_dir + "/" + name + "/" + name +
"/100ms_for_200s/rtt/data/ecdf_pairs_min_rtt_ns.txt",
"float,pos_float")
self.assertEqual(4, len(columns[0]))
sorted_min_rtts = sorted(min_rtts)
for i in range(len(columns[0])):
# Cumulative y-axis check
if i == 0:
self.assertEqual(columns[1][i], 0)
elif i == 1:
self.assertAlmostEqual(columns[1][i],
1.0 / 3.0,
delta=0.0001)
elif i == 2:
self.assertAlmostEqual(columns[1][i],
2.0 / 3.0,
delta=0.0001)
else:
self.assertEqual(columns[1][i], 1.0)
# RTT
if i == 0:
self.assertEqual(columns[0][i], float("-inf"))
else:
self.assertAlmostEqual(columns[0][i],
sorted_min_rtts[i - 1],
delta=100)
# Max. RTT
columns = exputil.read_csv_direct_in_columns(
output_analysis_data_dir + "/" + name + "/" + name +
"/100ms_for_200s/rtt/data/ecdf_pairs_max_rtt_ns.txt",
"float,pos_float")
self.assertEqual(4, len(columns[0]))
sorted_max_rtts = sorted(max_rtts)
for i in range(len(columns[0])):
# Cumulative y-axis check
if i == 0:
self.assertEqual(columns[1][i], 0)
elif i == 1:
self.assertAlmostEqual(columns[1][i],
1.0 / 3.0,
delta=0.0001)
elif i == 2:
self.assertAlmostEqual(columns[1][i],
2.0 / 3.0,
delta=0.0001)
else:
self.assertEqual(columns[1][i], 1.0)
# RTT
if i == 0:
self.assertEqual(columns[0][i], float("-inf"))
else:
self.assertAlmostEqual(columns[0][i],
sorted_max_rtts[i - 1],
delta=100)
# Max. - Min. RTT
columns = exputil.read_csv_direct_in_columns(
output_analysis_data_dir + "/" + name + "/" + name +
"/100ms_for_200s/rtt/data/ecdf_pairs_max_minus_min_rtt_ns.txt",
"float,pos_float")
self.assertEqual(4, len(columns[0]))
sorted_max_minus_min_rtts = sorted(
list(map(lambda x: max_rtts[x] - min_rtts[x], list(range(3)))))
for i in range(len(columns[0])):
# Cumulative y-axis check
if i == 0:
self.assertEqual(columns[1][i], 0)
elif i == 1:
self.assertAlmostEqual(columns[1][i],
1.0 / 3.0,
delta=0.0001)
elif i == 2:
self.assertAlmostEqual(columns[1][i],
2.0 / 3.0,
delta=0.0001)
else:
self.assertEqual(columns[1][i], 1.0)
# RTT
if i == 0:
self.assertEqual(columns[0][i], float("-inf"))
else:
self.assertAlmostEqual(columns[0][i],
sorted_max_minus_min_rtts[i - 1],
delta=100)
# Max. / Min. RTT
columns = exputil.read_csv_direct_in_columns(
output_analysis_data_dir + "/" + name + "/" + name +
"/100ms_for_200s/rtt/data/ecdf_pairs_max_rtt_to_min_rtt_slowdown.txt",
"float,pos_float")
self.assertEqual(4, len(columns[0]))
sorted_max_divided_min_rtts = sorted(
list(map(lambda x: max_rtts[x] / min_rtts[x], list(range(3)))))
for i in range(len(columns[0])):
# Cumulative y-axis check
if i == 0:
self.assertEqual(columns[1][i], 0)
elif i == 1:
self.assertAlmostEqual(columns[1][i],
1.0 / 3.0,
delta=0.0001)
elif i == 2:
self.assertAlmostEqual(columns[1][i],
2.0 / 3.0,
delta=0.0001)
else:
self.assertEqual(columns[1][i], 1.0)
# RTT
if i == 0:
self.assertEqual(columns[0][i], float("-inf"))
else:
self.assertAlmostEqual(columns[0][i],
sorted_max_divided_min_rtts[i - 1],
delta=0.01)
# Geodesic slowdown
columns = exputil.read_csv_direct_in_columns(
output_analysis_data_dir + "/" + name + "/" + name +
"/100ms_for_200s/rtt/data/ecdf_pairs_max_rtt_to_geodesic_slowdown.txt",
"float,pos_float")
# From Google search
# Distance Manila to Dalian is 2,703 km according to Google Maps
# Distance St. Petersburg to Manila is 8,635 km according to Google Maps
# Distance St. Petersburg to Dalian is 6,406 km according to Google Maps
self.assertEqual(4, len(columns[0]))
geodesic_expected_distance = [2703, 8635, 6406]
sorted_max_divided_geodesic_rtts = sorted(
list(
map(
lambda x: max_rtts[x] /
(2 * geodesic_expected_distance[x] * 1000.0 / 0.299792
), list(range(3)))))
for i in range(len(columns[0])):
# Cumulative y-axis check
if i == 0:
self.assertEqual(columns[1][i], 0)
elif i == 1:
self.assertAlmostEqual(columns[1][i],
1.0 / 3.0,
delta=0.0001)
elif i == 2:
self.assertAlmostEqual(columns[1][i],
2.0 / 3.0,
delta=0.0001)
else:
self.assertEqual(columns[1][i], 1.0)
# Geodesic RTT = 2*D / c
if i == 0:
self.assertEqual(columns[0][i], float("-inf"))
else:
self.assertAlmostEqual(columns[0][i],
sorted_max_divided_geodesic_rtts[i -
1],
delta=0.01)
# Analyze time step paths
satgen.post_analysis.analyze_time_step_path(
output_analysis_data_dir + "/" + name,
output_generated_data_dir + "/" + name, all_time_step_ms,
duration_s)
# Missed path changes
for time_step_ms in all_time_step_ms:
columns = exputil.read_csv_direct_in_columns(
output_analysis_data_dir + "/" + name + "/" + name +
"/200s/path/data/" + "ecdf_pairs_" + str(time_step_ms) +
"ms_missed_path_changes.txt", "float,pos_float")
for i in range(len(columns[0])):
# Cumulative y-axis check
if i == 0:
self.assertEqual(columns[1][i], 0)
elif i == 1:
self.assertAlmostEqual(columns[1][i],
1.0 / 3.0,
delta=0.0001)
elif i == 2:
self.assertAlmostEqual(columns[1][i],
2.0 / 3.0,
delta=0.0001)
else:
self.assertEqual(columns[1][i], 1.0)
# Only two should have missed one for the 10s one
# 1, 2 and 3 respectively at 20s
if i == 0:
self.assertEqual(columns[0][i], float("-inf"))
else:
if time_step_ms == 10000:
if i == 1:
self.assertEqual(columns[0][i], 0)
if i == 2:
self.assertEqual(columns[0][i], 1)
if i == 3:
self.assertEqual(columns[0][i], 1)
elif time_step_ms == 20000:
if i == 1:
self.assertEqual(columns[0][i], 1)
if i == 2:
self.assertEqual(columns[0][i], 2)
if i == 3:
self.assertEqual(columns[0][i], 3)
else:
self.assertEqual(columns[0][i], 0)
# Time between path changes
columns = exputil.read_csv_direct_in_columns(
output_analysis_data_dir + "/" + name + "/" + name +
"/200s/path/data/" +
"ecdf_overall_time_between_path_change.txt", "float,pos_float")
# Total 18 path changes, but only 15 of them are not from epoch (plus one for (0, -inf))
self.assertEqual(len(columns[0]), 16)
for i in range(len(columns[0])):
# Cumulative y-axis check
if i == 0:
self.assertEqual(columns[1][i], 0)
else:
self.assertAlmostEqual(columns[1][i],
i / float(len(columns[0]) - 1),
delta=0.00001)
# Gap values
if i == 0:
self.assertEqual(columns[0][i], float("-inf"))
else:
if i == 1:
self.assertEqual(columns[0][i], 2750000000)
elif i == 2:
self.assertEqual(columns[0][i], 5350000000)
elif i == 3:
self.assertEqual(columns[0][i], 6800000000)
elif i == 4:
self.assertEqual(columns[0][i], 9600000000)
elif i == 5:
self.assertEqual(columns[0][i], 9750000000)
elif i == 6:
self.assertEqual(columns[0][i], 9750000000)
elif i == 7:
self.assertEqual(columns[0][i], 10550000000)
elif i == 8:
self.assertEqual(columns[0][i], 10800000000)
elif i == 9:
self.assertEqual(columns[0][i], 13600000000)
elif i == 10:
self.assertEqual(columns[0][i], 13600000000)
elif i == 11:
self.assertEqual(columns[0][i], 15900000000)
elif i == 12:
self.assertEqual(columns[0][i], 46700000000)
elif i == 13:
self.assertEqual(columns[0][i], 51650000000)
elif i == 14:
self.assertEqual(columns[0][i], 118650000000)
elif i == 15:
self.assertEqual(columns[0][i], 136250000000)
# Clean up
local_shell.remove_force_recursive("temp_gen_data")
local_shell.remove_force_recursive("temp_analysis_data")
def calculate(duration_s, time_step_ms, dynamic_state_algorithm, num_threads):
# Add base name to setting
name = BASE_NAME + "_" + dynamic_state_algorithm
# Create output directories
if not os.path.isdir("gen_data"):
os.makedirs("gen_data")
if not os.path.isdir("gen_data/" + name):
os.makedirs("gen_data/" + name)
# Ground stations
print("Generating ground stations...")
shutil.copy("input_data/legacy/ground_stations_first_100.txt",
"gen_data/" + name + "/ground_stations.txt")
# TLEs
print("Generating TLEs...")
shutil.copy("input_data/legacy/starlink_tles_25x25.txt",
"gen_data/" + name + "/tles.txt")
# ISLs
print("Generating ISLs...")
satgen.generate_plus_grid_isls("gen_data/" + name + "/isls.txt",
NUM_ORBS,
NUM_SATS_PER_ORB,
isl_shift=1,
idx_offset=0)
# Description
print("Generating description...")
satgen.generate_description("gen_data/" + name + "/description.txt",
MAX_GSL_LENGTH_M, MAX_ISL_LENGTH_M)
# GSL interfaces
ground_stations = satgen.read_ground_stations_extended(
"gen_data/" + name + "/ground_stations.txt")
if dynamic_state_algorithm == "algorithm_free_one_only_over_isls" \
or dynamic_state_algorithm == "algorithm_free_one_only_gs_relays":
gsl_interfaces_per_satellite = 1
elif dynamic_state_algorithm == "algorithm_paired_many_only_over_isls":
gsl_interfaces_per_satellite = len(ground_stations)
else:
raise ValueError("Unknown dynamic state algorithm")
print("Generating GSL interfaces info..")
satgen.generate_simple_gsl_interfaces_info(
"gen_data/" + name + "/gsl_interfaces_info.txt",
NUM_ORBS * NUM_SATS_PER_ORB,
len(ground_stations),
gsl_interfaces_per_satellite, # GSL interfaces per satellite
1, # (GSL) Interfaces per ground station
1, # Aggregate max. bandwidth satellite (unit unspecified)
1 # Aggregate max. bandwidth ground station (same unspecified unit)
)
# Forwarding state
print("Generating forwarding state...")
satgen.help_dynamic_state(
"gen_data",
num_threads, # Number of threads
name,
time_step_ms,
duration_s,
MAX_GSL_LENGTH_M,
MAX_ISL_LENGTH_M,
dynamic_state_algorithm,
True)
f_out.write(
"2 00684 51.9000 211.7647 0000001 0.0000 31.7647 14.80000000 05\n"
)
f_out.write("Kuiper-630 16\n") # 684
f_out.write(
"1 00685U 00000ABC 00001.00000000 .00000000 00000-0 00000+0 0 02\n"
)
f_out.write(
"2 00685 51.9000 211.7647 0000001 0.0000 42.3529 14.80000000 03\n"
)
# ISLs
print("Generating ISLs...")
complete_list_isls = satgen.generate_plus_grid_isls(
output_generated_data_dir + "/" + name + "/isls_complete.temp.txt",
NUM_ORBS,
NUM_SATS_PER_ORB,
isl_shift=0,
idx_offset=0)
with open(output_generated_data_dir + "/" + name + "/isls.txt",
"w+") as f_out:
for isl in complete_list_isls:
if isl[0] in limited_satellite_set and isl[
1] in limited_satellite_set:
f_out.write("%d %d\n" % (limited_satellite_idx_map[isl[0]],
limited_satellite_idx_map[isl[1]]))
# Description
print("Generating description...")
satgen.generate_description(
output_generated_data_dir + "/" + name + "/description.txt",
MAX_GSL_LENGTH_M, MAX_ISL_LENGTH_M)