Everything should be functional now.

Author: keevindoherty

examples/g2o_experiment.py

@@ -3,14 +3,12 @@
 import numpy as np
 import networkx as nx
 from timeit import default_timer as timer
-from pose_graph_utils import read_g2o_file, plot_poses, rpm_to_mac, RelativePoseMeasurement, poses_ate_tran, poses_rpe_rot
+from pose_graph_utils import split_edges, read_g2o_file, plot_poses, rpm_to_mac, RelativePoseMeasurement, poses_ate_tran, poses_rpe_rot
 
 # MAC requirements
-from mac import MAC
-from mac.baseline import NaiveGreedy
-from mac.greedy_eig import GreedyEig
-from mac.greedy_esp import GreedyESP
-from mac.utils import split_edges, Edge, round_madow
+from mac.solvers import MAC, NaiveGreedy, GreedyESP
+from mac.utils.graphs import Edge
+from mac.utils.rounding import round_madow
 
 import matplotlib.pyplot as plt
 plt.rcParams['text.usetex'] = True
@@ -267,14 +265,13 @@ def to_sesync_format(measurements):
     #     pass
 
     # Make a MAC Solver
-    mac = MAC(odom_edges, lc_edges, num_poses, use_cache=True, fiedler_method="tracemin_cholesky")
+    mac = MAC(odom_edges, lc_edges, num_poses, fiedler_method="tracemin_cholesky")
 
     # Make a Naive Solver
     naive = NaiveGreedy(lc_edges)
 
     # Make a GreedyEig Solver
     if run_greedy:
-        # greedy_eig = GreedyEig(rpm_to_mac(odom_measurements), rpm_to_mac(lc_measurements), num_poses)
         greedy_esp = GreedyESP(odom_edges, lc_edges, num_poses, lazy=True)
 
     #############################
@@ -318,7 +315,7 @@ def to_sesync_format(measurements):
 
         # Solve the relaxed maximum algebraic connectivity augmentation problem.
         start = timer()
-        result, unrounded, upper, rtime = mac.fw_subset(w_init, num_lc, max_iters=20, rounding="nearest", return_rounding_time=True)
+        result, unrounded, upper, rtime = mac.solve(num_lc, w_init, max_iters=20, rounding="nearest", return_rounding_time=True, use_cache=True)
         end = timer()
         solve_time = end - start
         times.append(solve_time)

examples/g2o_mac_cache.py

@@ -4,7 +4,7 @@
 from scipy.sparse import csr_matrix, coo_matrix
 from typing import List, Tuple, Union
 import networkx as nx
-from mac.utils import Edge
+from mac.utils.graphs import Edge
 
 from evo.core.trajectory import PoseTrajectory3D
 from evo.core import sync

examples/greedy_esp_example.py

@@ -1,12 +1,12 @@
 import numpy as np
 import networkx as nx
 import matplotlib.pyplot as plt
-from mac.utils import select_edges, split_edges, Edge, nx_to_mac, mac_to_nx
-from mac.baseline import NaiveGreedy
-from mac.mac import MAC
+from mac.utils.graphs import select_edges, Edge
+from mac.utils.conversions import nx_to_mac, mac_to_nx
+from mac.solvers import MAC
 
 n = 20
-p = 0.99
+p = 0.6
 G = nx.erdos_renyi_graph(n, p)
 
 # Add a chain
@@ -16,39 +16,41 @@
     if not G.has_edge(i, i+1):
         G.add_edge(i, i+1)
 
-print(G)
+# Split the graph into a tree part and a "loop" part
+spanning_tree = nx.minimum_spanning_tree(G)
+loop_graph = nx.difference(G, spanning_tree)
+
 nx.draw(G)
 plt.title("Original Graph")
 plt.show()
 
 # Ensure G is connected before proceeding
 assert(nx.is_connected(G))
 
-edges = nx_to_mac(G)
-
-# Split chain and non-chain parts
-fixed_edges, candidate_edges = split_edges(edges)
+fixed_edges = nx_to_mac(spanning_tree)
+candidate_edges = nx_to_mac(loop_graph)
 
-pct_candidates = 0.1
+pct_candidates = 0.2
 num_candidates = int(pct_candidates * len(candidate_edges))
 mac = MAC(fixed_edges, candidate_edges, n)
 
 w_init = np.zeros(len(candidate_edges))
 w_init[:num_candidates] = 1.0
+np.random.shuffle(w_init)
 
-result, rounded, upper = mac.fw_subset(w_init, num_candidates, max_iters=50)
+result, rounded, upper = mac.solve(num_candidates, w_init, max_iters=100, rounding="madow", use_cache=True)
 init_selected = select_edges(candidate_edges, w_init)
 selected = select_edges(candidate_edges, result)
 
 init_selected_G = mac_to_nx(fixed_edges + init_selected)
 selected_G = mac_to_nx(fixed_edges + selected)
 
-print(f"lambda2 Random: {mac.evaluate_objective(w_init)}")
+print(f"lambda2 Initial: {mac.evaluate_objective(w_init)}")
 print(f"lambda2 Ours: {mac.evaluate_objective(result)}")
 
 plt.subplot(121)
 nx.draw(init_selected_G)
-plt.title(f"Random Selection\n$\lambda_2$ = {mac.evaluate_objective(w_init):.2f}")
+plt.title(f"Initial Selection\n$\lambda_2$ = {mac.evaluate_objective(w_init):.2f}")
 plt.subplot(122)
 nx.draw(selected_G)
 plt.title(f"Ours\n$\lambda_2$ = {mac.evaluate_objective(result):.2f}")

examples/pose_graph_utils.py

@@ -0,0 +1,3 @@
+from .mac import MAC
+from .baseline import NaiveGreedy
+from .greedy_esp import GreedyESP

examples/random_graph_sparsification.py

@@ -36,7 +36,7 @@ def find_fiedler_pair(L, X=None, method='tracemin_lu', tol=1e-8, seed=None):
     assert X.shape[1] == q
 
     if method == 'tracemin_cholesky':
-        from mac.cholesky_utils import tracemin_fiedler_cholesky
+        from mac.utils.cholesky import tracemin_fiedler_cholesky
         sigma, X = tracemin_fiedler_cholesky(L=L, X=X, normalized=False, tol=tol)
     else:
         sigma, X = la.algebraicconnectivity._tracemin_fiedler(L=L, X=X, normalized=False, tol=tol, method=method)