""" non-generated points """ #from simulator.points_dataset_... import points #from outlierfilter import outlierfilterlib #points = outlierfilterlib.filter_outliers(points) """ pre-filtered points """ #from simulator.points_dataset_fish_robot_room import points """ detect room """ #L = detect_room(points, do_preprocessing=False, numwalls=[4, 6, 8, 10], numcalculations=4, fancy_output=True) #L = detect_room(points, do_preprocessing=False, numwalls=[4, 6], numcalculations=2, fancy_output=True) L = detect_room(points, do_preprocessing=False, numwalls=[4], numcalculations=12, fancy_output=True) #L = detect_room(points, do_preprocessing=False, numwalls=[4], numcalculations=1, fancy_output=True) """ evaluate """ evaluator.evaluate_lines(L, 'line', points) """ plot """ ioff() plot_lines() plot_points(points) plot_walls(L) show() """ print """ #print encode_tuplearray_to_string([ l.E() for l in L ])
from simulator.evaluator import Evaluator """ setup evaluator """ evaluator = Evaluator("wmm") """ generate points """ points = generate_points(evaluator.sigma) """ non-generated points """ #from simulator.points_dataset_... import points #from outlierfilter import outlierfilterlib #points = outlierfilterlib.filter_outliers(points) """ pre-filtered points """ #from simulator.points_dataset_fish_robot_room import points """ detect room """ #L = detect_room(points, do_preprocessing=False, numwalls=[4, 6, 8, 10], numcalculations=4, fancy_output=True) #L = detect_room(points, do_preprocessing=False, numwalls=[4, 6], numcalculations=2, fancy_output=True) L = detect_room(points, do_preprocessing=False, numwalls=[4], numcalculations=12, fancy_output=True) #L = detect_room(points, do_preprocessing=False, numwalls=[4], numcalculations=1, fancy_output=True) """ evaluate """ evaluator.evaluate_lines(L, 'line', points) """ plot """ ioff() plot_lines() plot_points(points) plot_walls(L) show() """ print """ #print encode_tuplearray_to_string([ l.E() for l in L ])
for i, (rho_i, theta_i) in enumerate(peaks): peaks[i] = theta_i - 1, rho_i - 1 """ convert peaks to lines """ lines = [] peaks_theta_rho = [] for p in peaks: theta = thetas[p[0]] rho = rhos[p[1]] a = cos(theta) b = sin(theta) c = -rho peaks_theta_rho.append([theta, rho]) lines.append([a, b, c]) """ evaluate """ evaluator.evaluate_lines(lines, "abc", points) """ hough plot """ ## plot 1: points space plot_lines() plot_points(points) for l in lines: plot_abc_line(l, points) show() ## plot 2: parameter space # plot_hough(thetas, rhos, hgrid, peaks=peaks) # plot_hough(thetas, rhos, hgrid) # show()
peaks = loadmat(MATLAB_PEAKS_FILE)['P'] evaluator.toc() """ convert from matlab to python """ for i, (rho_i, theta_i) in enumerate(peaks): peaks[i] = theta_i - 1, rho_i - 1 """ convert peaks to lines """ lines = [] peaks_theta_rho = [] for p in peaks: theta = thetas[p[0]] rho = rhos[p[1]] a = cos(theta) b = sin(theta) c = -rho peaks_theta_rho.append([theta, rho]) lines.append([a, b, c]) """ evaluate """ evaluator.evaluate_lines(lines, 'abc', points) """ hough plot """ ## plot 1: points space plot_lines() plot_points(points) for l in lines: plot_abc_line(l, points) show() ## plot 2: parameter space #plot_hough(thetas, rhos, hgrid, peaks=peaks) #plot_hough(thetas, rhos, hgrid) #show()