def box_plot_for_degree(log_directory, output_directory, channel_name):
cutoff = 0
for channel_name_iter in channel_name:
out_degree_fit_parameters = np.zeros((12, 4))
in_degree_fit_parameters = np.zeros((12, 4))
total_degree_fit_parameters = np.zeros((12, 4))
for month in range(1, 13):
log_data = reader.linux_input(log_directory, channel_name_iter,
"2013-" + str(month) + "-1",
"2013-" + str(month) + "-31")
nicks, nick_same_list = nickTracker.nick_tracker(log_data)
message_number_graph = network.message_number_graph(
log_data, nicks, nick_same_list, False)
degree_anal_message_number = network.degree_analysis_on_graph(
message_number_graph)
out_degree_fit_parameters[month - 1] = vis.generate_log_plots(
degree_anal_message_number["out_degree"]["raw_for_vis"],
output_directory, channel_name_iter[0])
in_degree_fit_parameters[month - 1] = vis.generate_log_plots(
degree_anal_message_number["in_degree"]["raw_for_vis"],
output_directory, channel_name_iter[0])
total_degree_fit_parameters[month - 1] = vis.generate_log_plots(
degree_anal_message_number["total_degree"]["raw_for_vis"],
output_directory, channel_name_iter[0])
parameters = ['slope', 'intercept', 'r_square']
for para_ind in range(len(parameters)):
vis.box_plot(
out_degree_fit_parameters[:, para_ind], output_directory,
"out_degree_" + str(parameters[para_ind]) + "_2013_" +
channel_name_iter[0] + "_cut_" + str(cutoff))
vis.box_plot(
in_degree_fit_parameters[:, para_ind], output_directory,
"in_degree_" + str(parameters[para_ind]) + "_2013_" +
channel_name_iter[0] + "_cut_" + str(cutoff))
vis.box_plot(
total_degree_fit_parameters[:, para_ind], output_directory,
"total_degree_" + str(parameters[para_ind]) + "_2013_" +
channel_name_iter[0] + "_cut_" + str(cutoff))
saver.save_csv([out_degree_fit_parameters[:, para_ind].tolist()],
output_directory, "out_degree_" +
str(parameters[para_ind]) + "_2013_" +
channel_name_iter[0] + "_cut_" + str(cutoff))
saver.save_csv([in_degree_fit_parameters[:, para_ind].tolist()],
output_directory, "in_degree_" +
str(parameters[para_ind]) + "_2013_" +
channel_name_iter[0] + "_cut_" + str(cutoff))
saver.save_csv([total_degree_fit_parameters[:, para_ind].tolist()],
output_directory, "total_degree_" +
str(parameters[para_ind]) + "_2013_" +
channel_name_iter[0] + "_cut_" + str(cutoff))
def test_degree_distribution_multi_channel(self):
log_data = reader.linux_input(self.log_data_dir, ["ALL"],
self.start_date, self.end_date)
expected_result_CC_degree_curve_fit = util.load_from_disk(
self.current_directory + '/data/output/CC_degree_curve_fit')
expected_result_CU_degree_curve_fit = util.load_from_disk(
self.current_directory + '/data/output/CU_degree_curve_fit')
expected_result_UU_degree_curve_fit = util.load_from_disk(
self.current_directory + '/data/output/UU_degree_curve_fit')
nicks, nick_same_list, channels_for_user, nick_channel_dict, nicks_hash, channels_hash = nickTracker.nick_tracker(
log_data, True)
dict_out, graph = network.channel_user_presence_graph_and_csv(
nicks, nick_same_list, channels_for_user, nick_channel_dict,
nicks_hash, channels_hash)
degree_anal_message_number_CC = network.degree_analysis_on_graph(
dict_out["CC"]["graph"], directed=False)
degree_anal_message_number_UU = network.degree_analysis_on_graph(
dict_out["UU"]["graph"], directed=False)
degree_anal_message_number_CU = network.degree_analysis_on_graph(
dict_out["CU"]["graph"], directed=False)
Y = degree_anal_message_number_CU["degree"]["raw_for_vis"][1:]
data = [(i, Y[i]) for i in range(len(Y))]
CU_truncated, cutoff = channel.truncate_table(data, 0.5)
CU_T = [data[1] for data in list(CU_truncated)]
expected_output_CC_degree_curve_fit = vis.generate_log_plots(
degree_anal_message_number_CC["degree"]["raw_for_vis"],
self.current_directory, "CC_degree_curve_fit")
expected_output_CU_degree_curve_fit = vis.generate_log_plots(
CU_T, self.current_directory, "CU_degree_curve_fit")
expected_output_UU_degree_curve_fit = vis.generate_log_plots(
degree_anal_message_number_UU["degree"]["raw_for_vis"],
self.current_directory, "UU_degree_curve_fit")
os.remove(self.current_directory + "/CC_degree_curve_fit" + ".png")
os.remove(self.current_directory + "/CU_degree_curve_fit" + ".png")
os.remove(self.current_directory + "/UU_degree_curve_fit" + ".png")
self.assertEqual(expected_result_CC_degree_curve_fit,
expected_output_CC_degree_curve_fit)
self.assertEqual(expected_result_CU_degree_curve_fit,
expected_output_CU_degree_curve_fit)
self.assertEqual(expected_result_UU_degree_curve_fit,
expected_output_UU_degree_curve_fit)
def test_generate_log_plots(self, data, expected_result):
output = vis.generate_log_plots(data, current_dir, "log_plot_test")
#delete the plot created
os.remove(current_dir + '/log_plot_test.png')
assert np.allclose(output, expected_result)
def test_generate_log_plots(self, mock_calc_plot):
data = util.load_from_disk(self.test_data_dir +
"/vis/degree_msg_number")
expected_result = util.load_from_disk(self.test_data_dir +
"/vis/out_degree_analysis")
mock_calc_plot.return_value = util.load_from_disk(self.test_data_dir +
"vis/calc_plot_data")
expected_output = vis.generate_log_plots(data, self.test_data_dir,
"log_plot_test")
self.assertTrue(np.allclose(expected_output, expected_result))
def test_degree_distribution_message_exchange_network(self):
degree_type = ["out_degree", "in_degree", "total_degree"]
log_data = reader.linux_input(self.log_data_dir, ["#kubuntu-devel"],
self.start_date, self.end_date)
expected_result = util.load_from_disk(
self.current_directory +
'/data/output/message_exchange_network_curve_fit')
nicks, nick_same_list = nickTracker.nick_tracker(log_data)
message_number_graph = network.message_number_graph(
log_data, nicks, nick_same_list, False)
degree_anal_message_number = network.degree_analysis_on_graph(
message_number_graph)
expected_output = {}
for dtype in degree_type:
expected_output[dtype] = vis.generate_log_plots(
degree_anal_message_number[dtype]["raw_for_vis"],
self.current_directory, "#kubuntu-devel" + dtype)
os.remove(self.current_directory + "/#kubuntu-devel" + dtype +
".png")
self.assertEqual(expected_result, expected_output)
saver.save_csv([["response_time_cutoff"], [rt_cutoff_time]], output_directory, "rt_cutoff")
saver.save_csv([["month", "users", "directed_messages"], ["Jan-2013", len(message_number_graph), int(message_number_graph.size('weight'))]], output_directory, "users_messages")
for dtype in degree_type:
saver.save_csv(degree_anal_message_number[dtype]["formatted_for_csv"], output_directory, dtype)
saver.save_csv(bin_matrix, output_directory, "MessageNumber_binsize_"+str(config.BIN_LENGTH_MINS))
# =============== VIZ ===================
message_graph, message_comm = community.infomap_igraph(ig_graph=None, net_file_location= output_directory + 'message_number_graph.net')
vis.plot_infomap_igraph(message_graph, message_comm.membership, output_directory, "message")
vis.plot_data (data, output_directory, "bins")
for dtype in degree_type:
slope,intercept,r_square,mse = vis.generate_log_plots(degree_anal_message_number[dtype]["raw_for_vis"], output_directory, channel_name[0] +dtype)
saver.save_csv( [["Y","K","R^2", "MSE"], [slope,intercept,r_square,mse]], output_directory, dtype+"-curve-fit")
# ============== PRESENCE ACROSS MULTIPLE CHANNELS ==============
# Change analysis to all channels in config
log_data = reader.linux_input(log_directory, ["ALL"], starting_date, ending_date)
nicks, nick_same_list, channels_for_user, nick_channel_dict, nicks_hash, channels_hash = nickTracker.nick_tracker(log_data, True)
dict_out, graph = network.channel_user_presence_graph_and_csv(nicks, nick_same_list, channels_for_user, nick_channel_dict, nicks_hash, channels_hash)
saver.save_js_arc(dict_out["CC"]["reducedGraph"], channels_hash, config.OUTPUT_DIRECTORY + "protovis/", "cc.js")
for ptype in presence_type:
saver.save_csv(dict_out[ptype]["reducedMatrix"],output_directory, "r"+ptype)
saver.save_net_nx_graph(dict_out[ptype]["graph"], output_directory, "adj"+ptype)
saver.save_net_nx_graph(dict_out[ptype]["reducedGraph"], output_directory, "radj"+ptype)
radj_graph, radj_comm = community.infomap_igraph(ig_graph=None, net_file_location= output_directory + 'radj'+ptype+'.net')
def box_plot_for_degree(log_directory, output_directory, channel_name,
start_date, end_date):
"""
Correlational : statistical distribution of curve fit parameters generated for degree distribution. The function
takes the given time duration and selects one month at a time for generation of a degree distribution sample. Each
degree distribution sample shall have 3 curve fit parameters namely slope, intercept & r_square. The function collects these parameters
for all the months of the given time duration. The function produces box plot separately for each parameter.
Args:
log_directory(str): path to the location of Logs
output_directory(str): path to the location where the results are to be stored
channel_name(list): channels for which the analysis is to be done.
start_date(datetime): starting date for the logs to be analysed. This has to be the beginning of the month.
end_date(datetime): ending date for which the logs are to be analysed. This has to be the end of the month.
Returns:
null
"""
start_date = start_date.strptime('%Y-%m-%d')
end_date = end_date.strptime('%Y-%m-%d')
cutoff = 0
for channel_name_iter in channel_name:
out_degree_fit_parameters = np.zeros((12, 4))
in_degree_fit_parameters = np.zeros((12, 4))
total_degree_fit_parameters = np.zeros((12, 4))
for dt in rrule(MONTHLY, dtstart=start_date, until=end_date):
last_day_of_the_month = dt + relativedelta(
months=1) - datetime.timedelta(days=1)
# for month in range(1, 13):
log_data = reader.linux_input(
log_directory, channel_name_iter, dt.strftime("%Y-%m-%d"),
last_day_of_the_month.strftime("%Y-%m-%d"))
nicks, nick_same_list = nickTracker.nick_tracker(log_data)
message_number_graph = network.message_number_graph(
log_data, nicks, nick_same_list, False)
degree_anal_message_number = network.degree_analysis_on_graph(
message_number_graph)
out_degree_fit_parameters[dt.month - 1] = vis.generate_log_plots(
degree_anal_message_number["out_degree"]["raw_for_vis"],
output_directory, channel_name_iter[0])
in_degree_fit_parameters[dt.month - 1] = vis.generate_log_plots(
degree_anal_message_number["in_degree"]["raw_for_vis"],
output_directory, channel_name_iter[0])
total_degree_fit_parameters[dt.month - 1] = vis.generate_log_plots(
degree_anal_message_number["total_degree"]["raw_for_vis"],
output_directory, channel_name_iter[0])
parameters = ['slope', 'intercept', 'r_square']
for para_ind in range(len(parameters)):
vis.box_plot(
out_degree_fit_parameters[:, para_ind], output_directory,
"out_degree_" + str(parameters[para_ind]) + "_2013_" +
channel_name_iter[0] + "_cut_" + str(cutoff))
vis.box_plot(
in_degree_fit_parameters[:, para_ind], output_directory,
"in_degree_" + str(parameters[para_ind]) + "_2013_" +
channel_name_iter[0] + "_cut_" + str(cutoff))
vis.box_plot(
total_degree_fit_parameters[:, para_ind], output_directory,
"total_degree_" + str(parameters[para_ind]) + "_2013_" +
channel_name_iter[0] + "_cut_" + str(cutoff))
saver.save_csv([out_degree_fit_parameters[:, para_ind].tolist()],
output_directory, "out_degree_" +
str(parameters[para_ind]) + "_2013_" +
channel_name_iter[0] + "_cut_" + str(cutoff))
saver.save_csv([in_degree_fit_parameters[:, para_ind].tolist()],
output_directory, "in_degree_" +
str(parameters[para_ind]) + "_2013_" +
channel_name_iter[0] + "_cut_" + str(cutoff))
saver.save_csv([total_degree_fit_parameters[:, para_ind].tolist()],
output_directory, "total_degree_" +
str(parameters[para_ind]) + "_2013_" +
channel_name_iter[0] + "_cut_" + str(cutoff))
len(message_number_graph),
int(message_number_graph.size('weight'))
]], output_directory, "users_messages")
degree_anal_message_number = network.degree_analysis_on_graph(
message_number_graph)
print("msg exchange graph node degree analysis completed at: ",
datetime.datetime.now(),
file=exec_times_file)
exec_times_file.flush()
for dtype in degree_type:
saver.save_csv(degree_anal_message_number[dtype]["formatted_for_csv"],
output_directory, dtype)
slope, intercept, r_square, mse = vis.generate_log_plots(
degree_anal_message_number[dtype]["raw_for_vis"], output_directory,
"slackware-" + dtype)
saver.save_csv(
[["Y", "K", "R^2", "MSE"], [slope, intercept, r_square, mse]],
output_directory, dtype + "-curve-fit")
print("msg exchange graph node degree analysis saved at: ",
datetime.datetime.now(),
file=exec_times_file)
exec_times_file.flush()
del message_number_graph, degree_anal_message_number
del slope, intercept, r_square, mse
gc.collect()
print("msg exchange with cutoff=0 gc completed at: ",
datetime.datetime.now(),
