def main_action(self):
inDir = self.inputPicker.directory.get()
outDir = self.outputPicker.directory.get()
args = self.argumentsView.arguments.get()
cmd = self.executablePicker.fileName.get()
subprocess32.call(BenchCommandBuilder().buildCommand(
inDir, outDir, cmd, args))
array = CSVReader().read("res.csv")
self.plotCanvas.plot(array[0], array[1])
def enter_screen(self):
self.player_list.clear_widgets()
self.selection_list.clear_widgets()
self.description_list.clear_widgets()
self.color_list.clear_widgets()
all_players = []
for resultFile in self.manager.i_file_results:
reader = CSVReader(resultFile.id)
newLine = reader.getNext()
while newLine != None:
all_players.append(reader.getItem("Name", newLine))
newLine = reader.getNext()
all_players = sorted(all_players, key=str.lower)
self.playerIdentList = []
index = 0
for p in all_players:
player = PlayerIdentification()
player.name = p
self.playerIdentList.append(player)
self.moveUp()
import CSVReader as csv
import CSVWriter
import MetaReader as meta
import DecisionTree as DT
########################################################################
####################### LOAD NECESSARY DATA ############################
########################################################################
# Load training set
training_set = csv.CSVReader(
raw_input("Please enter the full filepath of the TRAINING DATA below: \n"))
# training_set = csv.CSVReader("./data/btrain.csv")
training_header, training_data = training_set.readFile()
# Load meta data
meta_reader = meta.MetaReader(
raw_input("\nPlease enter the full filepath of the META DATA below: \n"))
# meta_reader = meta.MetaReader("./data/bmeta.csv")
meta_data = meta_reader.parseMetaData()
# Load validation set
validation_set = csv.CSVReader(
raw_input(
"\nPlease enter the full filepath of the VALIDATION DATA below: \n"))
# validation_set = csv.CSVReader("./data/bvalidate.csv")
validate_header, validate_data = validation_set.readFile()
# Load test set
test_set = csv.CSVReader(
raw_input("\nPlease enter the full filepath of the TEST DATA below: \n"))
def printTeamStandings(myCanvas, startTop, filepath, num_trophy_winners,
trophy_highlight):
myCanvas.setFont("Helvetica", 11 * POINT)
y = startTop
x = MARGIN_LEFT
teamResult = CSVReader(filepath)
columns = [
x, x + INCH * .5, x + INCH * 6.25, x + INCH * 7.00, x + INCH * 7.75,
x + INCH * 8.50, x + INCH * 9.25
]
ignore = 0
playerCount = 0
for i in range(0, len(teamResult.headers)):
if (teamResult.headers[i] not in IGNORE_TEAM):
myCanvas.drawString(columns[i - ignore], y, teamResult.headers[i])
else:
ignore += 1
y -= LINE
ignore = 0
num_trophies = 0
line = teamResult.getNext()
while (line != None):
if (y < MARGIN_BOTTOM):
y = MARGIN_TOP
myCanvas.showPage()
if (line[0] == ""):
playerCount += 1
else:
playerCount = 0
if (playerCount > 4):
line = teamResult.getNext()
continue
if (num_trophies < int(num_trophy_winners)) and (playerCount == 0):
num_trophies += 1
myCanvas.setStrokeColorRGB(trophy_highlight[0],
trophy_highlight[1],
trophy_highlight[2])
myCanvas.setFillColorRGB(trophy_highlight[0], trophy_highlight[1],
trophy_highlight[2])
myCanvas.rect(columns[0] - 3, y - 3, columns[3] - columns[0] - 2,
LINE + 1, 1, 1)
myCanvas.setStrokeColorRGB(0, 0, 0)
myCanvas.setFillColorRGB(0, 0, 0)
ignore = 0
for i in range(0, len(line)):
if (teamResult.headers[i] in IGNORE_TEAM):
ignore += 1
else:
myCanvas.drawString(columns[i - ignore], y, line[i])
y -= LINE
line = teamResult.getNext()
highlights = [trophy_highlight]
descriptions = ["Trophy Winners"]
if len(highlights) > 0:
draw_highlight_key(myCanvas, highlights, descriptions)
def printIndividual(myCanvas, left, top, filepath, num_trophy_winners,
trophy_highlight, player_identification):
player_ident = copy.copy(player_identification)
base_left = .20 * INCH
base_right = 10.30 * INCH
space = base_right - base_left
lengths = []
total_characters = 0
result = CSVReader(filepath)
buff = 3
for head in result.headers:
if head.lower() == "name".lower():
buff = 8
else:
buff = 3
length = result.getLongest(head) + buff
lengths.append(length)
total_characters += length
increment = math.floor(space / total_characters)
columns = [base_left]
for i in range(0, len(lengths) - 1):
columns.append(columns[i] + increment * lengths[i])
myCanvas.setFont("Helvetica", 12 * POINT)
y = top
for i in range(0, len(result.headers)):
myCanvas.drawString(columns[i], y, result.headers[i])
y -= LINE
highlights = []
descriptions = []
if int(num_trophy_winners) > 0:
highlights.append(trophy_highlight)
descriptions.append("Trophy Winners")
num_trophies = 0
next = result.getNext()
new_page = False
highlight_width = columns[6] - columns[0]
while (next != None):
if (y < (.5 * INCH)):
new_page = True
if (num_trophies < int(num_trophy_winners)) == True:
num_trophies += 1
highlight(myCanvas, columns[0], y, highlight_width,
trophy_highlight)
status = result.getItem("St", next)
name = result.getItem("Name", next)
if (status != "Out"):
if new_page == True:
draw_highlight_key(myCanvas, highlights, descriptions)
highlights = []
descriptions = []
y = top
myCanvas.showPage()
new_page = False
for player in player_ident:
if player.name == name:
if player.description in descriptions:
player.col = highlights[descriptions.index(
player.description)]
else:
highlights.append(player.col)
descriptions.append(player.description)
highlight(myCanvas, columns[0], y, highlight_width,
player.col)
player_ident.remove(player)
for i in range(0, len(next)):
myCanvas.drawString(columns[i], y, next[i])
y -= LINE
next = result.getNext()
if len(highlights) > 0:
draw_highlight_key(myCanvas, highlights, descriptions)
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
from sklearn.cluster import KMeans
from pandas import DataFrame
from algorithms import kmean as km
import CSVReader as cr
import DataNormalisation as dt
MAX_ITERATIONS = 100
filePathRusia = 'C:\\Users\\dprefac\\PycharmProjects\\netscan-master\\csv\\pythonScript_1000_telekom_VPNRusia.csv'
filePathLocal = 'C:\\Users\\dprefac\\PycharmProjects\\netscan-master\\csv\\bruteForceWithValidPassword100Attempts200Status.csv'
features = [9, 10, 13, 14]
csvReader = cr.CSVReader()
dataFromRusia = csvReader.load_csv_and_extract_feature(filePathRusia, features,
"RUSIA")
dataFromLocal = csvReader.load_csv_and_extract_feature(filePathLocal, features,
"LOCAL")
dataFromRusia = np.array(dataFromRusia)
dataFromLocal = np.array(dataFromLocal)
dataFromRusia = dt.DataNormalisation.eliminate_outlier_column(dataFromRusia, 0)
dataFromLocal = dt.DataNormalisation.eliminate_outlier_column(dataFromLocal, 0)
#
dataFromRusia = dt.DataNormalisation.eliminate_outlier_column(dataFromRusia, 1)
dataFromLocal = dt.DataNormalisation.eliminate_outlier_column(dataFromLocal, 1)
def __init__(self, filename):
metaCSV = csv.CSVReader(filename)
self.attributes, self.types = metaCSV.readFile()
