Reuse network topologies between sub-experiments

Fixes the issue #50 .

Signed-off-by: Andres Correa Casablanca <andres@thirdhash.com>

experiments/notebooks/real_nodes_forking_01.ipynb

@@ -146,7 +146,8 @@
     "from itertools import product as cartesian_product \n",
     "from pathlib import Path\n",
     "\n",
-    "from experiments.forking_simulation import ForkingSimulation"
+    "from experiments.forking_simulation import ForkingSimulation\n",
+    "from experiments.graph import create_network_graph"
    ]
   },
   {
@@ -178,6 +179,30 @@
     "target_spacings = [4, 8, 12, 16]         # Expected averate time between blocks\n",
     "time_steps = [1, 2, 4, 6, 8]             # Time granularity used to generate block hashes\n",
     "latencies = [0, 0.1, 0.5, 1.0]           # Block propagation delays\n",
+    "num_network_topologies = 3               # How many networks will be used to experiment with other parameters\n",
+    "\n",
+    "# We create a list of network topologies for each graph size, and not for each settings combination.\n",
+    "network_topologies = {\n",
+    "    graph_size: [\n",
+    "        create_network_graph(\n",
+    "            num_nodes=graph_size,\n",
+    "            num_outbound_connections=8,\n",
+    "            max_inbound_connections=125,\n",
+    "            graph_model='preferential_attachment'\n",
+    "        ) for _ in range(num_network_topologies)\n",
+    "    ]\n",
+    "    for graph_size in {\n",
+    "        num_proposer_nodes + num_validator_nodes + num_relay_nodes for (\n",
+    "            num_proposer_nodes,\n",
+    "            num_validator_nodes,\n",
+    "            num_relay_nodes\n",
+    "        ) in cartesian_product(\n",
+    "            num_proposer_nodes_values,\n",
+    "            num_validator_nodes_values,\n",
+    "            num_relay_nodes_values,\n",
+    "        )\n",
+    "    }\n",
+    "}\n",
     "\n",
     "settings_tuples = list(cartesian_product(\n",
     "    num_proposer_nodes_values,\n",
@@ -190,22 +215,32 @@
     "\n",
     "settings_tuples = sorted([\n",
     "    (\n",
-    "        num_proposer_nodes_values,\n",
-    "        num_validator_nodes_values,\n",
-    "        num_relay_nodes_values,\n",
+    "        num_proposer_nodes,\n",
+    "        num_validator_nodes,\n",
+    "        num_relay_nodes,\n",
     "        target_spacings,\n",
     "        time_steps,\n",
-    "        latencies\n",
+    "        latencies,\n",
+    "        graph_id,   # Just used to create directory names\n",
+    "        graph_edges # Besides filtering, we also add this\n",
     "    )\n",
     "    for (\n",
-    "        num_proposer_nodes_values,\n",
-    "        num_validator_nodes_values,\n",
-    "        num_relay_nodes_values,\n",
+    "        num_proposer_nodes,\n",
+    "        num_validator_nodes,\n",
+    "        num_relay_nodes,\n",
     "        target_spacings,\n",
     "        time_steps,\n",
     "        latencies\n",
     "    ) in settings_tuples\n",
     "    \n",
+    "    # That's like a nested loop, but \"unrolled\" in the list comprehension\n",
+    "    # We keep the graph id to construct directory names\n",
+    "    for graph_id, graph_edges in enumerate(network_topologies[\n",
+    "        num_proposer_nodes +\n",
+    "        num_validator_nodes +\n",
+    "        num_relay_nodes\n",
+    "    ])\n",
+    "    \n",
     "    if (\n",
     "        time_steps < target_spacings and\n",
     "        target_spacings % time_steps == 0\n",
@@ -248,11 +283,21 @@
     "\n",
     "# We generate a dataset per settings tuple\n",
     "for c, settings in enumerate(settings_tuples):\n",
-    "    num_proposer_nodes, num_validator_nodes, num_relay_nodes, target_spacing, time_step, latency = settings\n",
+    "    (\n",
+    "        num_proposer_nodes,\n",
+    "        num_validator_nodes,\n",
+    "        num_relay_nodes,\n",
+    "        target_spacing,\n",
+    "        time_step,\n",
+    "        latency,\n",
+    "        graph_id,\n",
+    "        graph_edges\n",
+    "    ) = settings\n",
     "\n",
     "    # Each simulation stores results in a different path\n",
     "    result_directory = results_path.joinpath(\n",
-    "        '_'.join(str(v) for v in settings)\n",
+    "        # We discard `graph_edges` to construct the directory name\n",
+    "        '_'.join(str(v) for v in settings[:-1])\n",
     "    ).resolve()\n",
     "\n",
     "    # Previous data will be overwritten\n",
@@ -275,7 +320,7 @@
     "        num_relay_nodes=num_relay_nodes,\n",
     "        simulation_time=simulation_time,\n",
     "        sample_time=sample_time,\n",
-    "        graph_model=graph_model,\n",
+    "        graph_edges=graph_edges,\n",
     "        block_time_seconds=target_spacing,\n",
     "        block_stake_timestamp_interval_seconds=time_step,\n",
     "        network_stats_file_name=network_stats_filename,\n",