#!/usr/bin/env python3 print("Starting plotting") import csv import ternary import matplotlib.pyplot as plt from os import listdir from os.path import isfile, join from plot_data_helpers import parseOpinionLine, clipTuple, tupleInRange from collections import OrderedDict from math import sqrt data_dir = "data" files_to_process = [f for f in listdir(data_dir) if isfile(join(data_dir, f))] attention_files = {} opinion_files = {} contacts_files = {} for filename in files_to_process: rows = [] with open(data_dir + "/" + filename, 'r') as file: csvreader = csv.reader(file) for row in csvreader: rows.append(row) if "attention" in filename: attention_files[filename] = rows if "opinions" in filename: opinion_files[filename] = rows if "contacts" in filename: contacts_files[filename] = rows # sort the dict attention_files = OrderedDict(sorted(attention_files.items())) opinion_files = OrderedDict(sorted(opinion_files.items())) contacts_files = OrderedDict(sorted(contacts_files.items())) ######################################################## # Plot opinions in ternary plot # from https://github.com/marcharper/python-ternary #agent_color = {'abe':'lightsteelblue', 'ben':'moccasin', 'cal':'limegreen', 'deb':'salmon', 'eve':'violet', 'fin':'peru', 'gil':'pink', 'hix':'yellow', 'max':'limegreen', 'ned':'pink', 'oak':'yellow'} #agent_end = {'abe':'tab:blue', 'ben':'tab:orange', 'cal':'tab:green', 'deb':'tab:red', 'eve':'tab:purple', 'fin':'tab:brown', 'gil':'deeppink', 'hix':'tab:olive', 'max':'tab:green', 'ned':'deeppink', 'oak':'tab:olive'} agent_color = {'abe':'tab:blue', 'ben':'tab:orange', 'cal':'tab:green', 'deb':'tab:red', 'eve':'tab:purple', 'fin':'tab:brown', 'gil':'tab:pink', 'hix':'tab:gray', 'ike':'lime', 'jim': 'red', 'kim': 'springgreen', 'lou': 'gold', 'max':'tab:olive', 'ned':'tab:cyan', 'oak':'tab:green'} agent_end = {'abe':'tab:blue', 'ben':'tab:orange', 'cal':'tab:green', 'deb':'tab:red', 'eve':'tab:purple', 'fin':'tab:brown', 'gil':'tab:pink', 'hix':'tab:gray', 'ike':'lime', 'jim': 'red', 'kim': 'springgreen', 'lou': 'gold', 'max':'tab:olive', 'ned':'tab:cyan', 'oak':'tab:green'} fontsize = 12 figure, tax = ternary.figure(scale=9.0) range_lim = [-7.0, 14.0] axis_limits = {'b':range_lim,'l':range_lim,'r':range_lim} tax.set_axis_limits(axis_limits) tax.boundary() tax.gridlines(multiple=1, color="black") saved_opinion_names = ['not_active', 'not_active', 'not_active'] # plot data for each record for filename, data_list in opinion_files.items(): points = [] times = [] for line in data_list: time, v_name, group, opinion_names, opinion_vals_tpl = parseOpinionLine(line) points.append(opinion_vals_tpl) times.append(time) if ( (opinion_names[0] != 'not_active') and (opinion_names[1] != 'not_active') and (opinion_names[2] != 'not_active') ): saved_opinion_names[0] = opinion_names[0] saved_opinion_names[1] = opinion_names[1] saved_opinion_names[2] = opinion_names[2] # clip the data points_clipped = [] for point in points: if (tupleInRange(point, range_lim[0], range_lim[1]) ): points_clipped.append( point ) else: points_clipped.append( clipTuple(point, range_lim[0], range_lim[1]) ) # Plot the data conv_points = tax.convert_coordinates(points_clipped) tax.plot(conv_points, linewidth=1.0, label=v_name, color=agent_color[v_name]) # again plot the end points on top. for filename, data_list in opinion_files.items(): points = [] times = [] for line in data_list: time, v_name, group, opinion_names, opinion_vals_tpl = parseOpinionLine(line) points.append(opinion_vals_tpl) times.append(time) # Plot the data conv_points = tax.convert_coordinates(points) tax.plot([conv_points[-1],conv_points[-1]], marker="o", markersize=10, color=agent_end[v_name]) tax.get_ticks_from_axis_limits(1) tax.set_custom_ticks(offset=0.017) tax.bottom_axis_label(saved_opinion_names[0].capitalize(), fontsize=fontsize) tax.right_axis_label(saved_opinion_names[1].capitalize(), fontsize=fontsize, offset=0.12) tax.left_axis_label(saved_opinion_names[2].capitalize(), fontsize=fontsize, offset=0.12) tax.get_axes().axis('off') tax.clear_matplotlib_ticks() tax.legend() tax.savefig("OpinionTrajectories.pdf", dpi=1200) print("Finished generating plot: " + "OpinionTrajectories.pdf") tax.show() ############################################################### # Plot attention and connection degree from all agents in single plot fig2, (ax1, ax2) = plt.subplots(2, sharex=True) for filename, data_list in attention_files.items(): name = filename[:3] times = [] atten_mag = [] for pair in data_list: times.append(float(pair[0])/60.0) atten_mag.append(float(pair[1])) ax1.plot(times, atten_mag, label=name, color=agent_color[name]) ax1.set_ylabel('Attention (u)', fontsize=20) ax1.tick_params(axis='both', labelsize=18) ax1.grid() ax1.legend(fontsize=16) for filename, data_list in contacts_files.items(): name = filename[:3] times = [] deg_of_vertex = [] for line in data_list: #if (name == 'deb'): # print(line) if (len(deg_of_vertex) > 0): deg_of_vertex.append(deg_of_vertex[-1]) times.append(float(line[0])/60.0) times.append(float(line[0])/60.0) if (len(line) == 2): if (line[1] == ''): deg_of_vertex.append(0.0) else: deg_of_vertex.append(len(line) - 1.0) else: deg_of_vertex.append(len(line) - 1.0) ax2.plot(times, deg_of_vertex, label=name, color=agent_color[name]) #if (name == 'deb'): # print(deg_of_vertex) ax2.set_ylabel('Deg of Vertex/Vehicle', fontsize=20) ax2.set_xlabel('Time Since Mission Start (min)', fontsize=20) ax2.set_xlim(0,130) ax2.tick_params(axis='both', labelsize=18) ax2.grid() fig2.savefig("AttentionTrajectories.pdf", dpi=1200) print("Finished generating plot: " + "AttentionTrajectories.pdf") plt.show() ######################################################################## ## Plot magnitude of opinion for each vehicle fig3, ax3 = plt.subplots() # plot data for each record for filename, data_list in opinion_files.items(): op_mag = [] times = [] for line in data_list: time, v_name, group, opinion_names, opinion_vals_tpl = parseOpinionLine(line) mag = 0.0 for op_val in opinion_vals_tpl: mag = mag + op_val*op_val op_mag.append(sqrt(mag)) times.append(float(time)) #print(type(time)) #print(type(mag)) ax3.plot(times, op_mag, linewidth=1.0, label=v_name, color=agent_color[v_name]) ax3.set_ylabel('Magnitude of Opinions', fontsize=20) ax3.set_xlabel('Time Since Mission Start (min)', fontsize=20) #ax3.set_xlim(0,130) ax3.tick_params(axis='both', labelsize=18) ax3.grid() ax3.legend(fontsize=16) fig3.savefig("OpinionMagnitudes.pdf", dpi=1200) print("Finished generating plot: " + "OpinionMagnitudes.pdf") plt.show()