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reports.py
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REPORT_FILE_SUFFIX = "MsgStatsAndAbortRep.txt"
FIELDS = ['latency_avg', 'delivery_prob', 'overhead_ratio', 'delivered']
LAYER_FILE_SUFFIX = "DeliveredMessagesReport.txt"
LAYERS = ['L0', 'L1', 'L2', 'L3', 'L4', 'L5', 'L6', 'L7', 'L8', 'L9']
COLOURS = ["#FFA500", "#0000FF", "#00FF00"]
"""Gives the best delivered layer in a given burst"""
BEST_LAYER = 0
"""Gives all layers in a given burst"""
ALL_LAYERS = 1
"""
Run pip3 install -r requirements.txt before running this script.
"""
import os
import sys
import copy
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
def generate_layer_report(dir_path="./rep2", dest_path="./", report_name="report.txt", run_count=None):
"""
Goes through all LAYER_FILE_SUFFIX file endings and generate each iteration's layer stats.
"""
report_set = list()
summary = dict()
rep_name = report_name.replace(".txt", "_layer_.txt")
for reports in os.listdir(dir_path):
if str(reports).endswith(LAYER_FILE_SUFFIX) and not str(reports).startswith('._'):
report_set.append( str(dir_path) + '/' + str(reports))
for report in report_set:
# try:
current_iteration = str(report).strip(dir_path).strip('/').split("_")[4]
_, report_summary = extract_layer_data(report)
report_summary = [round(float(i)/5, 3) for i in report_summary]
sub_report_name = str(report).strip(dir_path).strip("/" + "\t").replace("_" + current_iteration, "")
if summary.keys().__contains__(sub_report_name):
for i in range(len(summary[sub_report_name])):
summary[sub_report_name][i] += report_summary[i]
else:
summary[sub_report_name] = report_summary
# except Exception as e:
# print(e)
file_summary = "Summary_Filename\taI\tmD\t0,1,2,3,4,5,6,7,8,9\n"
for report in summary.keys():
file_summary += report + "\t" + report.split("_")[6].strip("aI") + "\t" + report.split("_")[7].strip("mD") + "\t"
for layer in summary[report]:
file_summary += str(layer) + ","
file_summary += "\n"
print(file_summary)
with open(dest_path + rep_name.replace(".txt", "_summary.txt"), 'w') as f:
f.write(file_summary)
def generate_report(dir_path="./rep2", dest_path="./", report_name="report.txt"):
"""
Extracts all fields from the files that end with suffix MsgStatsAndAbortRep.txt.
"""
report_set = list()
report_data = dict()
seg_list = dict()
run_count = 0
for reports in os.listdir(dir_path):
if str(reports).endswith(REPORT_FILE_SUFFIX) and not str(reports).startswith('._'):
report_set.append(str(dir_path) + '/' + str(reports))
try:
if int(str(reports).split("_")[4]) - 1000 > run_count:
run_count = int(str(reports).split("_")[4]) - 1000
except:
pass
for iteration in report_set:
filename, stat = extract_data(iteration, run_count)
filename = filename.replace(dir_path + "/", "")
if report_data.keys().__contains__(str(filename).replace("_" + filename.split("_")[4], "")):
for k in report_data[str(filename).replace("_" + filename.split("_")[4], "")].keys():
report_data[str(filename).replace("_" + filename.split("_")[4], "")][k] += stat[k]
else:
report_data[str(filename).replace("_" + filename.split("_")[4], "")] = stat
report = "StatsFilename" + "\t"
for field in report_data[list(report_data.keys())[0]].keys():
report += str(field) + "\t"
report += '\n'
for files in report_data.keys():
filedata = str(files).strip(dir_path).strip(dest_path) + "\t"
for field in report_data[files].keys():
filedata += str(report_data[files][field]).strip("\n") + "\t"
filedata += ("\n")
report += filedata
if dest_path.endswith("/"):
dest_path += "/"
with open(dest_path+report_name, 'w') as f:
f.write(report)
print(report)
generate_layer_report(dir_path, dest_path, report_name, run_count)
plot_report_data(dest_path+report_name)
def extract_data(filename=None, run_count=None):
"""
Searches for all lines that contain a field and it's corresponding value and returns a dictonary containing those fields.
"""
stat = dict()
with open(filename, 'r', encoding='ISO-8859-1') as f:
data = f.readlines()
for line in data:
if len(str(line).split(": ")) == 2:
try:
if FIELDS.__contains__(str(line).split(": ")[0]):
stat[str(line).split(": ")[0]] = float(str(line).split(": ")[1]) / run_count
except Exception as e:
pass
return filename, stat
def extract_layer_data(filename=None, run_count=None):
"""
Extracts layer data for each burst in each iteration.
"""
layers_delivered_burst_id = dict()
with open(filename, 'r', encoding='ISO-8859-1') as f:
data = f.readlines()
for line in data[1:]:
burst_id, current_layer = line.split(" ")[1].split("_L")
if layers_delivered_burst_id.keys().__contains__(burst_id):
layers_delivered_burst_id[burst_id].append(int(current_layer))
layers_delivered_burst_id[burst_id] = sorted(layers_delivered_burst_id[burst_id])
else:
layers_delivered_burst_id[burst_id] = [int(current_layer)]
remove_id = []
for id in layers_delivered_burst_id.keys():
if layers_delivered_burst_id[id][0] == 0:
test = str()
test += str(layers_delivered_burst_id[id])
delivered_list = layers_delivered_burst_id[id]
i = 0
while i < len(delivered_list) - 1:
if delivered_list[i+1] == delivered_list[i] + 1:
i += 1
else:
break
delivered_list.clear()
delivered_list = list(range(0, i+1))
print(test,delivered_list, sep=' ')
layers_delivered_burst_id[id] = delivered_list
else:
remove_id.append(id)
for i in remove_id:
try:
layers_delivered_burst_id.pop(i)
except:
pass
summary = [0,0,0,0,0,0,0,0,0,0]
for id in layers_delivered_burst_id.keys():
for layers in layers_delivered_burst_id[id]:
summary[layers] += 1
layers_delivered_burst_id[id] = summary
return str(filename), summary
def plot_report_data(report_path=None, all=True):
"""
Plots relevant additive, multiplicative data against existing fields
"""
if not all:
with open(report_path, 'r') as f:
report = f.readlines()
seg_data = dict()
for line in report[1:]:
data = line.split("\t")
ack = data[0][1]
if not ack == 'o':
addIncr = data[0].split("_")[6]
multDecr = data[0].split("_")[7]
delivery_prob, latency_avg = data[1], data[2]
addIncr = float(addIncr.strip("aI"))
multDecr = float(multDecr.strip("mD"))
if seg_data.keys().__contains__(ack):
seg_data[ack][0].append(addIncr)
seg_data[ack][1].append(multDecr)
seg_data[ack][2].append(delivery_prob)
seg_data[ack][3].append(latency_avg)
else:
seg_data[ack] = [[addIncr], [multDecr], [delivery_prob], [latency_avg]]
const_add = 0.004
const_mult = 0.08
const_add_mult_data = list()
const_mult_add_data = list()
const_add_delivery_data = list()
const_mult_delivery_data = list()
const_add_latency_data = list()
const_mult_latency_data = list()
for ackNum in seg_data.keys():
ack_add_delivery_data = list()
ack_add_latency_data = list()
for a in range(len(seg_data[ackNum][0])):
if seg_data[ackNum][0][a] == const_add:
"Add equal"
if ackNum == '1':
const_add_mult_data.append(seg_data[ackNum][1][a])
ack_add_delivery_data.append(round(float(seg_data[ackNum][2][a]), 6))
ack_add_latency_data.append(round(float(seg_data[ackNum][3][a]), 6))
const_add_delivery_data.append(ack_add_delivery_data)
const_add_latency_data.append(ack_add_latency_data)
ack_mult_delivery_data = list()
ack_mult_latency_data = list()
for m in range(len(seg_data[ackNum][1])):
if seg_data[ackNum][1][m] == const_mult:
if ackNum == '1':
const_mult_add_data.append(seg_data[ackNum][0][m])
ack_mult_delivery_data.append(round(float(seg_data[ackNum][2][m]), 6))
ack_mult_latency_data.append(round(float(seg_data[ackNum][3][m]), 6))
const_mult_delivery_data.append(ack_mult_delivery_data)
const_mult_latency_data.append(ack_mult_latency_data)
print(const_mult_add_data)
print(const_add_mult_data)
print(const_add_latency_data)
print(const_add_delivery_data)
print(const_mult_delivery_data)
print(const_mult_latency_data)
plot_data("Additive Increase vs Latency", "Additive Increase", "Latency", const_mult_add_data, const_mult_latency_data, seg_data.keys())
plot_data("Additive Increase vs Delivery payloads", "Additive Increase", "Delivery payloads", const_mult_add_data, const_mult_delivery_data, seg_data.keys())
plot_data("Multiplicative Decrease vs Latency", "Multiplicative decrease", "Latency", const_add_mult_data, const_add_latency_data, seg_data.keys())
plot_data("Multiplicative Decrease vs Delivery Payload", "Multiplicative decrease", "Delivery payload", const_add_mult_data, const_add_delivery_data, seg_data.keys())
else:
with open(report_path, 'r') as f:
report = f.readlines()
addData = list()
multData = list()
delivery_prob_data = list()
latency_avg_data = list()
for line in report[1:]:
data = line.split("\t")
ack = data[0][1]
if not ack == 'o':
addIncr = data[0].split("_")[6]
multDecr = data[0].split("_")[7]
delivery_prob_data.append(data[1])
latency_avg_data.append(data[2])
addData.append(float(addIncr.strip("aI")))
multData.append(float(multDecr.strip("mD")))
plot_data("Delivery probability vs AddIncr vs MultDecr", "AddIncr", "MultDecr", addData, multData, None, z_data=delivery_prob_data, z_label="Delivery probability")
plot_data("Latency vs AddIncr vs MultDecr", "AddIncr", "MultDecr", addData, multData, None, z_data=latency_avg_data, z_label="Latency")
with open(report_path.replace(".txt", "_summary.txt"), 'r') as f:
report = f.readlines()
addData = list()
multData = list()
# TODO Add delivered 3D plot code
def plot_data(graph_title=None, x_label=None, y_label=None, x_data=None, y_data=None, y_data_labels=None, all=True, z_data=None, z_label=None):
"""
General method to plot given arguments. Only for multiple y-data
"""
if not all:
y_data_labels = list(y_data_labels)
# if str(graph_title).__contains__("Latency"):
# plt.gca().set_ylim([0.1, 1000]) # Set's the Y limits. gca - get current axes
# else:
# plt.gca().set_ylim([0.40, 0.55])
for Y in y_data:
x, y = zip(*sorted(zip(x_data, Y), key=lambda x: x[0]))
plt.plot(x, y, color=COLOURS[y_data.index(Y)], label="Ack" + str(y_data_labels[y_data.index(Y)]), marker=".")
#if graph_title.__contains__("Latency"):
plt.xscale('log', basex=10)
#plt.gca().set_xlim([0, 0.03]) # Set's the Y limits. gca - get current axes
plt.title(graph_title, fontsize=16, fontweight='bold')
plt.legend(loc="best")
plt.xlabel(x_label)
plt.ylabel(y_label)
y_data_labels = list(y_data_labels)
plt.savefig(graph_title + ".png")
plt.clf()
else:
x_data = [float(i) for i in x_data]
y_data = [float(i) for i in y_data]
z_data = [float(i) for i in z_data]
x, y, z = zip(*sorted(zip(x_data, y_data, z_data), key=lambda x: x[1]))
plt.title(graph_title, fontsize=16, fontweight='bold')
plt.legend(loc="best")
fig = plt.figure()
ax = plt.axes(projection='3d')
ax.plot3D(x, y, z, COLOURS[0])
ax.set_xlabel = x_label
ax.set_ylabel = y_label
ax.set_zlabel = z_label
plt.savefig(graph_title + ".png")
plt.clf()
if __name__ == "__main__":
"""
Arguments:
1. Existing reports directory path
2. Generated report destination path
3. Report's name
"""
if len(sys.argv) > 1:
dir_path = sys.argv[1]
dest_path = sys.argv[2]
report_name = sys.argv[3]
generate_report(dir_path, dest_path, report_name)
else:
generate_report()