Ejemplo n.º 1
0
    def test_ground_stations_invalid(self):

        # Missing column
        with open("ground_stations.temp.txt", "w+") as f_out:
            f_out.write("0,abc,33,11")
        try:
            satgen.read_ground_stations_basic("ground_stations.temp.txt")
            self.fail()
        except ValueError:
            self.assertTrue(True)
        os.remove("ground_stations.temp.txt")

        # Invalid non-ascending gid
        with open("ground_stations.temp.txt", "w+") as f_out:
            f_out.write("0,abc,33,11,5\n")
            f_out.write("0,abc,33,11,5")
        try:
            satgen.read_ground_stations_basic("ground_stations.temp.txt")
            self.fail()
        except ValueError:
            self.assertTrue(True)
        os.remove("ground_stations.temp.txt")

        # Missing column
        with open("ground_stations_extended.temp.txt", "w+") as f_out:
            f_out.write("0,abc,33,11,2,3,3")
        try:
            satgen.read_ground_stations_extended(
                "ground_stations_extended.temp.txt")
            self.fail()
        except ValueError:
            self.assertTrue(True)
        os.remove("ground_stations_extended.temp.txt")

        # Invalid non-ascending gid
        with open("ground_stations_extended.temp.txt", "w+") as f_out:
            f_out.write("0,abc,33,11,5,2,3,3\n")
            f_out.write("0,abc,33,11,5,2,3,3")
        try:
            satgen.read_ground_stations_extended(
                "ground_stations_extended.temp.txt")
            self.fail()
        except ValueError:
            self.assertTrue(True)
        os.remove("ground_stations_extended.temp.txt")
Ejemplo n.º 2
0
    def test_ground_stations_normal(self):

        # Write basic ground stations
        with open("ground_stations.temp.txt", "w+") as f_out:
            f_out.write("0,abc,33,11.0,77")

        # Read basic and compare
        ground_stations = satgen.read_ground_stations_basic(
            "ground_stations.temp.txt")
        self.assertEqual(1, len(ground_stations))
        self.assertEqual(0, ground_stations[0]["gid"])
        self.assertEqual("abc", ground_stations[0]["name"])
        self.assertEqual("33", ground_stations[0]["latitude_degrees_str"])
        self.assertEqual("11.0", ground_stations[0]["longitude_degrees_str"])
        self.assertEqual(77.0, ground_stations[0]["elevation_m_float"])
        self.assertTrue("cartesian_x" not in ground_stations[0])
        self.assertTrue("cartesian_y" not in ground_stations[0])
        self.assertTrue("cartesian_z" not in ground_stations[0])

        # Extend
        satgen.extend_ground_stations("ground_stations.temp.txt",
                                      "ground_stations_extended.temp.txt")
        ground_stations_extended = satgen.read_ground_stations_extended(
            "ground_stations_extended.temp.txt")
        self.assertEqual(1, len(ground_stations_extended))
        self.assertEqual(0, ground_stations_extended[0]["gid"])
        self.assertEqual("abc", ground_stations_extended[0]["name"])
        self.assertEqual("33.000000",
                         ground_stations_extended[0]["latitude_degrees_str"])
        self.assertEqual("11.000000",
                         ground_stations_extended[0]["longitude_degrees_str"])
        self.assertEqual(77.0,
                         ground_stations_extended[0]["elevation_m_float"])
        self.assertTrue("cartesian_x" in ground_stations_extended[0])
        self.assertTrue("cartesian_y" in ground_stations_extended[0])
        self.assertTrue("cartesian_z" in ground_stations_extended[0])
        # TODO: Verify Cartesian coordinates

        # Clean up
        os.remove("ground_stations.temp.txt")
        os.remove("ground_stations_extended.temp.txt")
Ejemplo n.º 3
0
    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]
            duration_s = 200

            # Add base name to setting
            name = "reduced_kuiper_630_" + dynamic_state_algorithm

            # Path trace we base this test on:
            # 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

            # 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
            satgen.extend_ground_stations(
                output_generated_data_dir + "/" + name + "/ground_stations.basic.txt",
                output_generated_data_dir + "/" + name + "/ground_stations.txt"
            )

            # TLEs (taken from Kuiper-610 first shell)
            print("Generating TLEs...")
            with open(output_generated_data_dir + "/" + name + "/tles.txt", "w+") as f_out:
                f_out.write("1 12\n")  # Pretend it's one orbit with 12 satellites
                f_out.write("Kuiper-630 0\n")  # 183
                f_out.write("1 00184U 00000ABC 00001.00000000  .00000000  00000-0  00000+0 0    06\n")
                f_out.write("2 00184  51.9000  52.9412 0000001   0.0000 142.9412 14.80000000    00\n")
                f_out.write("Kuiper-630 1\n")  # 184
                f_out.write("1 00185U 00000ABC 00001.00000000  .00000000  00000-0  00000+0 0    07\n")
                f_out.write("2 00185  51.9000  52.9412 0000001   0.0000 153.5294 14.80000000    07\n")
                f_out.write("Kuiper-630 2\n")  # 216
                f_out.write("1 00217U 00000ABC 00001.00000000  .00000000  00000-0  00000+0 0    03\n")
                f_out.write("2 00217  51.9000  63.5294 0000001   0.0000 127.0588 14.80000000    01\n")
                f_out.write("Kuiper-630 3\n")  # 217
                f_out.write("1 00218U 00000ABC 00001.00000000  .00000000  00000-0  00000+0 0    04\n")
                f_out.write("2 00218  51.9000  63.5294 0000001   0.0000 137.6471 14.80000000    00\n")
                f_out.write("Kuiper-630 4\n")  # 218
                f_out.write("1 00219U 00000ABC 00001.00000000  .00000000  00000-0  00000+0 0    05\n")
                f_out.write("2 00219  51.9000  63.5294 0000001   0.0000 148.2353 14.80000000    08\n")
                f_out.write("Kuiper-630 5\n")  # 250
                f_out.write("1 00251U 00000ABC 00001.00000000  .00000000  00000-0  00000+0 0    01\n")
                f_out.write("2 00251  51.9000  74.1176 0000001   0.0000 132.3529 14.80000000    00\n")
                f_out.write("Kuiper-630 6\n")  # 615
                f_out.write("1 00616U 00000ABC 00001.00000000  .00000000  00000-0  00000+0 0    06\n")
                f_out.write("2 00616  51.9000 190.5882 0000001   0.0000  31.7647 14.80000000    05\n")
                f_out.write("Kuiper-630 7\n")  # 616
                f_out.write("1 00617U 00000ABC 00001.00000000  .00000000  00000-0  00000+0 0    07\n")
                f_out.write("2 00617  51.9000 190.5882 0000001   0.0000  42.3529 14.80000000    03\n")
                f_out.write("Kuiper-630 8\n")  # 647
                f_out.write("1 00648U 00000ABC 00001.00000000  .00000000  00000-0  00000+0 0    01\n")
                f_out.write("2 00648  51.9000 201.1765 0000001   0.0000  15.8824 14.80000000    09\n")
                f_out.write("Kuiper-630 9\n")  # 648
                f_out.write("1 00649U 00000ABC 00001.00000000  .00000000  00000-0  00000+0 0    02\n")
                f_out.write("2 00649  51.9000 201.1765 0000001   0.0000  26.4706 14.80000000    07\n")
                f_out.write("Kuiper-630 10\n")  # 649
                f_out.write("1 00650U 00000ABC 00001.00000000  .00000000  00000-0  00000+0 0    04\n")
                f_out.write("2 00650  51.9000 201.1765 0000001   0.0000  37.0588 14.80000000    05\n")
                f_out.write("Kuiper-630 11\n")  # 650
                f_out.write("1 00651U 00000ABC 00001.00000000  .00000000  00000-0  00000+0 0    05\n")
                f_out.write("2 00651  51.9000 201.1765 0000001   0.0000  47.6471 14.80000000    04\n")

            # Nodes
            #
            # Original ID   Test ID
            # 183           0
            # 184           1
            # 216           2
            # 217           3
            # 218           4
            # 250           5
            # 615           6
            # 616           7
            # 647           8
            # 648           9
            # 649           10
            # 650           11
            #
            # ISLs
            #
            # Original      Test
            # 183-184       0-1
            # 183-217       0-3
            # 216-217       2-3
            # 216-250       2-5
            # 217-218       3-4
            # 615-649       6-10
            # 616-650       7-11
            # 647-648       8-9
            # 648-649       9-10
            # 649-650       10-11
            #
            # Necessary ISLs (above) inferred from trace:
            #
            # 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
            #
            print("Generating ISLs...")
            with open(output_generated_data_dir + "/" + name + "/isls.txt", "w+") as f_out:
                f_out.write("0 1\n")
                f_out.write("0 3\n")
                f_out.write("2 3\n")
                f_out.write("2 5\n")
                f_out.write("3 4\n")
                f_out.write("6 10\n")
                f_out.write("7 11\n")
                f_out.write("8 9\n")
                f_out.write("9 10\n")
                f_out.write("10 11\n")

            # 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",
                12,  # 12 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"
            satgen.post_analysis.print_routes_and_rtt(
                output_analysis_data_dir + "/" + name,
                output_generated_data_dir + "/" + name,
                default_time_step_ms,
                duration_s,
                12,
                13,
                ""
            )

            # Now, we just want to see that the output path matches
            with open(output_analysis_data_dir + "/" + name + "/data/networkx_path_12_to_13.txt", "r") as f_in:
                i = 0
                for line in f_in:
                    line = line.strip()
                    if i == 0:
                        self.assertEqual(line, "0,12-1-0-3-13")
                    elif i == 1:
                        self.assertEqual(line, "18000000000,12-4-3-13")
                    elif i == 2:
                        self.assertEqual(line, "27600000000,12-9-10-11-7-13")
                    elif i == 3:
                        self.assertEqual(line, "74300000000,12-4-3-2-5-13")
                    elif i == 4:
                        self.assertEqual(line, "125900000000,12-8-9-10-11-7-13")
                    elif i == 5:
                        self.assertEqual(line, "128700000000,12-8-9-10-6-13")
                    else:
                        self.fail()
                    i += 1

            # ... and the RTT
            with open(output_analysis_data_dir + "/" + name + "/data/networkx_rtt_12_to_13.txt", "r") as f_in1:
                with open("tests/data_to_match/kuiper_630/networkx_rtt_1173_to_1241.txt", "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])
                        self.assertEqual(a_time, b_time)
                        self.assertAlmostEqual(a_rtt, b_rtt, places=6)

            # 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"
            )
            for i in range(len(columns[0])):

                # Cumulative y-axis check
                if i == 0:
                    self.assertEqual(columns[1][i], 0)
                else:
                    self.assertEqual(columns[1][i], 1.0)

                # Only one pair with 5 path changes
                if i == 0:
                    self.assertEqual(columns[0][i], float("-inf"))
                else:
                    self.assertEqual(columns[0][i], 5)

            # 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"
            )
            for i in range(len(columns[0])):

                # Cumulative y-axis check
                if i == 0:
                    self.assertEqual(columns[1][i], 0)
                else:
                    self.assertEqual(columns[1][i], 1.0)

                # Shortest is 3 hops, longest is 6 hops, max delta is 3
                if i == 0:
                    self.assertEqual(columns[0][i], float("-inf"))
                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"
            )
            for i in range(len(columns[0])):

                # Cumulative y-axis check
                if i == 0:
                    self.assertEqual(columns[1][i], 0)
                else:
                    self.assertEqual(columns[1][i], 1.0)

                # Shortest is 3 hops, longest is 6 hops, max/min division is 2.0
                if i == 0:
                    self.assertEqual(columns[0][i], float("-inf"))
                else:
                    self.assertEqual(columns[0][i], 2.0)

            # For all pairs, the distribution how many times they changed path
            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 only 5 time moments, none of which overlap, so this needs to be 5 times 1
                if i == 0:
                    self.assertEqual(columns[0][i], float("-inf"))
                elif i > 2000 - 6:
                    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"
            )
            for i in range(len(columns[0])):

                # Cumulative y-axis check
                if i == 0:
                    self.assertEqual(columns[1][i], 0)
                else:
                    self.assertEqual(columns[1][i], 1.0)

                # Only one pair with minimum RTT 25ish
                if i == 0:
                    self.assertEqual(columns[0][i], float("-inf"))
                else:
                    self.assertAlmostEqual(columns[0][i], 25229775.250687573, 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"
            )
            for i in range(len(columns[0])):

                # Cumulative y-axis check
                if i == 0:
                    self.assertEqual(columns[1][i], 0)
                else:
                    self.assertEqual(columns[1][i], 1.0)

                # Only one pair with max. RTT 48ish
                if i == 0:
                    self.assertEqual(columns[0][i], float("-inf"))
                else:
                    self.assertAlmostEqual(columns[0][i], 48165140.010532916, 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"
            )
            for i in range(len(columns[0])):

                # Cumulative y-axis check
                if i == 0:
                    self.assertEqual(columns[1][i], 0)
                else:
                    self.assertEqual(columns[1][i], 1.0)

                # Only one pair with minimum RTT of 25ish, max. RTT is 48ish
                if i == 0:
                    self.assertEqual(columns[0][i], float("-inf"))
                else:
                    self.assertAlmostEqual(columns[0][i], 48165140.010532916 - 25229775.250687573, 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"
            )
            for i in range(len(columns[0])):

                # Cumulative y-axis check
                if i == 0:
                    self.assertEqual(columns[1][i], 0)
                else:
                    self.assertEqual(columns[1][i], 1.0)

                # Only one pair with minimum RTT of 25ish, max. RTT is 48ish
                if i == 0:
                    self.assertEqual(columns[0][i], float("-inf"))
                else:
                    self.assertAlmostEqual(columns[0][i], 48165140.010532916 / 25229775.250687573, 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"
            )
            for i in range(len(columns[0])):

                # Cumulative y-axis check
                if i == 0:
                    self.assertEqual(columns[1][i], 0)
                else:
                    self.assertEqual(columns[1][i], 1.0)

                # Distance Manila to Dalian is 2,703 km according to Google Maps, RTT = 2*D / c
                if i == 0:
                    self.assertEqual(columns[0][i], float("-inf"))
                else:
                    self.assertAlmostEqual(columns[0][i], 48165140.010532916 / (2 * 2703000 / 0.299792), 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)
                    else:
                        self.assertEqual(columns[1][i], 1.0)

                    # Only one should have missed for the 10s one
                    if i == 0:
                        self.assertEqual(columns[0][i], float("-inf"))
                    else:
                        if time_step_ms == 10000:
                            self.assertEqual(columns[0][i], 1)
                        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"
            )
            self.assertEqual(len(columns[0]), 5)  # Total 5 path changes, but only 4 of them are not from epoch
            for i in range(len(columns[0])):

                # Cumulative y-axis check
                if i == 0:
                    self.assertEqual(columns[1][i], 0)
                else:
                    if i == 1:
                        self.assertEqual(columns[1][i], 0.25)
                    elif i == 2:
                        self.assertEqual(columns[1][i], 0.5)
                    elif i == 3:
                        self.assertEqual(columns[1][i], 0.75)
                    elif i == 4:
                        self.assertEqual(columns[1][i], 1.0)

                # 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], 9600000000)
                    elif i == 3:
                        self.assertEqual(columns[0][i], 46700000000)
                    elif i == 4:
                        self.assertEqual(columns[0][i], 51650000000)

            # Clean up
            local_shell.remove_force_recursive("temp_gen_data")
            local_shell.remove_force_recursive("temp_analysis_data")
    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")
Ejemplo n.º 6
0
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)
Ejemplo n.º 7
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)

    # 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",
        17,  # 17 satellites