def chapter_one():
#necessary imports
from options import quick_pause
from options import options
#sets player health as "health" using SUD_classes
obj = bat(100, 100)
health = obj.HP
#sets look variables using SUD_classes
look = rooms("\nThis room is number one\n\n",
"\nThis room is number two\n\n",
"\nThis is room number three\n\n")
room1 = look.room_1
room2 = look.room_2
room3 = look.room_3
#sets search variable using SUD_classes
search = rooms("\nYou find one item, cuz it's room one\n\n",
"\nYou find two items, cuz it's room two\n\n",
"\nYou find three items, cuz it's room three\n\n")
room1 = search.room_1
room2 = search.room_2
room3 = search.room_3
print(
"\nYou totter towards the only exit of the room, the door, which is cracked open.\n"
)
quick_pause()
choice1 = input("What do you do now? ")
loop = True
while loop:
if choice1 == "look":
print(look.room_1)
choice1 = input("What do you do now? ")
elif choice1 == "search":
print(search.room_1)
choice1 = input("What do you do now? ")
elif choice1 == "options":
options()
choice1 = input("What do you do now? ")
elif choice1 == "stats":
print("\nYou are at: " + str(health) + " HP\n\n")
choice1 = input("What do you do now? ")
elif choice1 == "test":
break
print("test success!")
def login():
u=os.system("dialog --backtitle 'HADOOP' --title 'USERNAME' --inputbox 'enter your username' 7 30 2>/tmp/username.txt")
p=os.system("dialog --backtitle 'HADOOP' --title 'PASSWORD' --insecure --passwordbox 'enter your password' 7 30 2>/tmp/password.txt")
f=open("/tmp/username.txt")
u=f.read()
f.close()
f1=open("/tmp/password.txt")
p=f1.read()
f1.close()
if u=="":
if p=="":
while True:
os.system("dialog --backtitle 'HADOOP' --title 'MENU' --menu 'select a option' 12 50 4 1 'create single node cluster' 2 'start all services' 3 'stop all services' 4 'Go back to main menu' 2>/tmp/menu.txt")
m=open("/tmp/menu.txt")
ch=m.read()
m.close()
#print type(ch)
if ch=="1":
import single_node
single_node.chooseip()
elif ch=="2":
import single_node
single_node.s_all()
elif ch=="3":
import single_node
single_node.s_all1()
elif ch=="4":
q=os.system("dialog --backtitle 'HADOOP' --title 'WARNING' --yesno 'are you sure Y/N' 5 40")
if q==0:
import options
options.options()
#exit()
else:
continue
elif ch=="":
q=os.system("dialog --backtitle 'HADOOP' --title 'WARNING' --yesno 'are you sure Y/N' 5 40")
if q==0:
import options
options.options()
#exit()
else:
continue
else:
print "wrong choice"
else:
os.system("dialog --msgbox 'password is incorrect' 7 30")
login()
else:
os.system("dialog --msgbox 'username is incorrect' 7 30")
login()
def menu():
while True:
#!son.play()
screen.blit(background, (0, 0))
text('menu', font, (255, 255, 255), screen, 20, 20)
mx, my = pygame.mouse.get_pos()
button_1 = pygame.Rect(490, 300, 300, 75)
button_2 = pygame.Rect(490, 400, 300, 75)
button_3 = pygame.Rect(490, 500, 300, 75)
button_4 = pygame.Rect(490, 600, 300, 75)
if button_1.collidepoint((mx, my)):
if click:
jeu()
if button_2.collidepoint((mx, my)):
if click:
instructions()
if button_3.collidepoint((mx, my)):
if click:
options()
if button_4.collidepoint((mx, my)):
if click:
credits()
pygame.draw.rect(screen, (0, 0, 0), button_1)
pygame.draw.rect(screen, (0, 0, 0), button_2)
pygame.draw.rect(screen, (0, 0, 0), button_3)
pygame.draw.rect(screen, (0, 0, 0), button_4)
text('JOUER', font, (255, 255, 255), screen, 575, 320)
text('INSTRUCTIONS', font, (255, 255, 255), screen, 505, 420)
text('OPTIONS', font, (255, 255, 255), screen, 555, 520)
text('CREDITS', font, (255, 255, 255), screen, 555, 620)
click = False
for event in pygame.event.get():
if event.type == QUIT:
pygame.quit()
sys.exit()
if event.type == KEYDOWN:
if event.key == K_ESCAPE:
pygame.quit()
sys.exit()
if event.type == MOUSEBUTTONDOWN:
if event.button == 1:
click = True
pygame.display.update()
mainClock.tick(60)
def main_menu_enter(window, event, menu):
"""A főmenüben kezeli az enter gomb megyomását."""
if event.key == pygame.K_RETURN:
if menu == 1:
tetris.tetris(window)
if menu == 2:
scoreboard.scoreboard(window)
if menu == 3:
options.options(window)
if menu == 4:
pygame.quit()
def __init__(self, parent, id):
# load options into self.opt
self.opt = options.options()
# variables to store current events like highlight etc.
# for hover and click
self.hittest = {} # to store the hittest paths
self.Highlight = None # hightlight this on move
self.HighlightClick = None # hightlight constantly
# for selection
self.selectionDrawing = []
self.selectionDrawingDirection = "right"
self.selectionDrawingDiff = 0
# initialise the window
DNApyBaseDrawingClass.__init__(self, parent, wx.ID_ANY)
self.parent = parent
genbank.dna_selection = (1,1)
self.Bind(wx.EVT_LEFT_DOWN, self.OnLeftDown)
self.Bind(wx.EVT_LEFT_UP, self.OnLeftUp)
#self.Bind(wx.EVT_RIGHT_UP, self.OnRightUp)
self.Bind(wx.EVT_MOTION, self.OnMotion)
def loadConfluenceBrowser(self, window, confluence):
self.options = options.options()
panel = window.get_side_panel()
image = gtk.Image()
f = urllib.urlopen(self.options.url.replace('/rpc/xmlrpc', '/favicon.ico'))
data = f.read()
pbl = gtk.gdk.PixbufLoader()
pbl.write(data)
pixbuf = pbl.get_pixbuf()
pbl.close()
image.set_from_pixbuf(pixbuf)
self.treestore = gtk.TreeStore(str, str, str)
self.confluence = confluence
# we'll add some data now - 4 rows with 3 child rows each
for parent in self.confluence.getSpaces():
piter = self.treestore.append(None, (parent.name, parent.key, 'isSpace'))
self.browser.set_model(self.treestore)
self.browser.show_all()
self.browser.queue_draw()
#spaces = self.confluence.getSpaces()
panel.add_item(self, "Confluence Browser", image)
# store per window data in the window object
windowdata = {"ConfluenceBrowser": self}
def write(self):
id = database.database.id
self.workbook = xlsxwriter.Workbook(self.filePath.text())
self.worksheet = self.workbook.add_worksheet()
self.data = database.database(
"database", "attendance", 4,
["id", "TEXT", "name", "TEXT", "date", "TEXT", "state", "INTEGER"])
info = np.asarray(self.data.select("attendance", 1, ["id", id]))
print(info)
titels = ["name", "date", "attendance"]
row = 0
col = 0
for i in titels:
self.worksheet.write(row, col, i)
col += 1
dataToWrite = []
for i in range(len(info)):
dataToWrite.append(info[i, 2:])
dataToWrite = np.unique(dataToWrite, axis=0)
print(dataToWrite)
row = 1
for i in range(len(dataToWrite)):
for j in range(3):
self.worksheet.write(row, j, dataToWrite[i][j])
row += 1
self.workbook.close()
self.op = options.options()
self.close()
self.op.show()
def activate(self, window):
self.confluencewidget = ConfluenceBrowser(window)
self.options = options.options(window, self.confluencewidget)
if self.options.loginPassed is True:
self.confluence = confluencerpclib.Confluence(self.options.url, True)
self.confluence.login(self.options.username, self.options.password)
self.confluencewidget.loadConfluenceBrowser(window, self.confluence)
pass
def bridge_chap_one():
#imports
from options import options
choice_options = input('Type "options" for available options: ')
if choice_options == "options":
options()
quick_pause()
chapter_one()
elif choice_options != "options":
quick_pause()
print(
"\nThat wasn't what I told you to do. Try again and don't f**k with me\n"
)
quick_pause()
bridge_chap_one()
def main(argv):
# These are features under development:
# 1) @TODO: Generate the name using the path folder pieces. This is
# working but we need to find a way to detect automatically when using
# pieces or not.
# 3) @TODO: Words to add to the special words list.
# 4) @TODO: Add deep search higher than 1 using pagination links
# get options from parameters
rootpath, debug, force, use_pieces, deep, min_match, number_format = options(
argv)
for extension in VIDEO_EXTENSIONS:
for infile in get_files(rootpath, extension):
# remove path and extension
filename = os.path.basename(infile)[:-len(extension) - 1]
path = os.path.dirname(infile) + os.sep
if debug == 1:
print """
-------------------------------------------------------------------------------
"""
print 'Starting process for "' + path + filename + '"'
# do not search if already have subtitles and is not in force mode
# @TODO: Allow different subtitle types
if force == 0 and os.path.isfile(path + filename + '.' +
SUBTITLE_EXTENSION):
if debug == 1:
print 'Subtitle already exists'
else:
# find season and episode in file name or path (use_pieces),
# search and full search
search, season_episode, full_search = real_name(
filename, path, rootpath, use_pieces, number_format)
if search in BANNED_SEARCH:
if debug == 1:
print 'Not a valid search'
else:
if (season_episode == False):
if debug == 1:
print 'Not valid series name'
else:
if debug == 1:
print 'Valid series name'
subtitle_url = best_subtitle_url(search, full_search,
path + filename,
min_match, force, deep,
debug)
if subtitle_url is False:
if debug == 1:
print "Best subtitle not found"
if debug == 1:
print 'Ending process for "' + path + filename + '"'
print """
def main(): # alap
app = QApplication(sys.argv)
o = options()
w = alapWidget(o)
#w = mouseTracker()
w.show()
#app.installEventFilter(w)
sys.exit(app.exec_())
def getExperiment(config_file):
CONFIG_FILE_NAME = config_file
torch.autograd.set_detect_anomaly(True)
args = options(CONFIG_FILE_NAME)
print("The system will use following resource: {:}".format(
args.argsCommon.device))
print("Experiment Name: " + args.argsCommon.experiment_name)
print("Experiment will be saved to " +
args.argsCommon.experiment_save_path)
device = torch.device("cuda:0" if torch.cuda.is_available()
and args.argsCommon.device == "gpu" else "cpu")
dataloaders = getFlirAdasKaistCombinedDataLoaders(args.argsDataset)
currentModel = model.make_model(args.argsModel)
currentModel.to(device)
possibles = globals().copy()
loss_dict = dict()
loss_dict["types"] = []
loss_dict["functions"] = []
loss_dict["weights"] = []
for loss in args.argsLoss.loss.split('+'):
weight, loss_type = loss.split('*')
loss_dict["functions"].append(
possibles.get('get' + loss_type + 'Loss')(args.argsLoss))
loss_dict["weights"].append(float(weight))
loss_dict["types"].append(loss_type)
loss_dict["types"].append('total')
lr_scheduler, optimizer = possibles.get('get' + args.argsMethod.optimizer +
'Optimizer')(
currentModel.parameters(),
args.argsMethod)
method = getBaseMethod(currentModel, loss_dict, optimizer, args.argsMethod)
benchmark = BenchmarkMetrics(args.argsBenchmark)
logger = LoggerTensorBoard(
args.argsCommon.experiment_save_path,
args.argsCommon.experiment_save_path + '/tensorboard')
experiment = getBaseExperiment(currentModel, dataloaders, loss_dict,
method, optimizer, lr_scheduler, benchmark,
logger, args.argsExperiment)
return experiment
def correct(self):
self.data=database.database("database","User",2,["name","TEXT","password","TEXT"])
# name=self.data.select("User","name",self.lineEdit.text().replace(" ", ""))
# print(name)
database.database.id=self.lineEdit.text().replace(" ", "")
print(database.database.id)
if (self.lineEdit.text() == "" or self.lineEdit_2.text() == ""):
self.ui = null.null()
if self.data.idFound("User",2,["name",self.lineEdit.text().replace(" ", ""),"password",self.lineEdit_2.text().replace(" ", "")]) :
print("enter1")
self.ui = options.options()
self.close()
self.ui.show()
else:
self.ui = incorrect.incorrect()
self.close()
self.ui.show()
def run_reprocess(wd=None):
# by default assume we're in the working directory at this point
if wd is not None:
os.chdir(wd)
update_status(None,'Running')
solsfile = glob.glob('DDS3_full*smoothed.npz')
if len(solsfile) < 1:
die('Cannot find the correct solution file -- exiting')
solsfile = str(solsfile[0])
o = options('reprocess-vlow.cfg',option_list)
cubefiles=['image_full_vlow_QU.cube.dirty.fits','image_full_vlow_QU.cube.dirty.corr.fits']
cthreads=[]
flist=[]
ddf_kw = {}
do_polcubes('DATA','[DDS3_full_smoothed,DDS3_full_slow]',[o['image_uvmin'],1.600000],'image_full_vlow',ddf_kw,beamsize=o['vlow_psf_arcsec'],imsize=o['vlow_imsize'],cellsize=o['vlow_cell'],robust=o['vlow_robust'],options=o,catcher=None)
if o['compress_polcubes']:
for cubefile in cubefiles:
if o['restart'] and os.path.isfile(cubefile+'.fz'):
warn('Compressed cube file '+cubefile+'.fz already exists, not starting compression thread')
else:
report('Starting compression thread for '+cubefile)
thread = threading.Thread(target=compress_fits, args=(cubefile,o['fpack_q']))
thread.start()
cthreads.append(thread)
flist.append(cubefile)
if o['compress_polcubes']:
# cthreads and flist exist
for thread in cthreads:
if thread.isAlive():
warn('Waiting for a compression thread to finish')
thread.join()
if o['delete_compressed']:
for f in flist:
warn('Deleting compressed file %s' % f)
os.remove(f)
update_status(None,'Complete')
def login():
u=os.system("dialog --backtitle 'HADOOP' --title 'USERNAME' --inputbox 'enter your username' 7 30 2>/tmp/username.txt")
p=os.system("dialog --backtitle 'HADOOP' --title 'PASSWORD' --insecure --passwordbox 'enter your password' 7 30 2>/tmp/password.txt")
f=open("/tmp/username.txt")
u=f.read()
f.close()
f1=open("/tmp/password.txt")
p=f1.read()
f1.close()
if u=="":
if p=="":
while True:
os.system("dialog --backtitle 'HADOOP' --title 'MENU' --menu 'select a option' 25 60 17 1 'create namenode and jobtracker' 2 'format, start namenode and jobtracker' 3 'create datanode and tasktracker' 4 'start datanode and tasktracker' 5 'HIVE (use this option when a cluster is ready)' 6 'use PIG (when a cluster is ready)' 7 'set high priority to a job' 8 'make a client' 9 'Decommision nodes' 10 'commision nodes' 11 'hbase' 12 'create hdfs users' 13 'set quota on space' 14 'set qouta on file' 15 'setup fair scheduler' 16 'upload a file' 17 'Go back to main menu' 2>/tmp/menu.txt")
m=open("/tmp/menu.txt")
ch=m.read()
m.close()
#print type(ch)
if ch=="1":
#allip.all_ip()
namenode.chooseip()
#namenode()
elif ch=="2":
namenode.chooseipstart()
elif ch=="3":
datanode.chooseip1()
elif ch=="4":
datanode.chooseipstart1()
elif ch=="5":
datanode.hive()
elif ch=="6":
datanode.pig()
elif ch=="7":
datanode.priority()
elif ch=="8":
datanode.client()
elif ch=="9":
os.system("dialog --infobox 'processing please wait...' 3 34")
ii=commands.getoutput('nmap -sP 192.168.109.0/24 | grep 192 | cut -d: -f 2 | cut -c 22-36 > /root/Desktop/hup.txt')
f=open("/root/Desktop/hup.txt")
ii=f.read()
f.close()
iilist = ii.split('\n')
f20=open("/tmp/snon.txt")
d=f20.read()
f20.close()
i=d
i=int(i)
k = iilist[i]
name=k
allip.all_ip()
os.system("dialog --backtitle 'HADOOP' --inputbox 'enter ips to make that exclude from cluster' 8 60 2>/tmp/decomm.txt")
f20=open("/tmp/decomm.txt")
d=f20.read()
f20.close()
dlist = d.split()
deco=d
datanode.decomm(name,deco)
elif ch=="10":
os.system("dialog --infobox 'processing please wait...' 3 34")
ii=commands.getoutput('nmap -sP 192.168.109.0/24 | grep 192 | cut -d: -f 2 | cut -c 22-36 > /root/Desktop/hup.txt')
f=open("/root/Desktop/hup.txt")
ii=f.read()
f.close()
iilist = ii.split('\n')
f20=open("/tmp/snon.txt")
d=f20.read()
f20.close()
i=d
i=int(i)
k = iilist[i]
name=k
allip.all_ip()
os.system("dialog --backtitle 'HADOOP' --inputbox 'enter ips to make that include from cluster' 8 60 2>/tmp/comm.txt")
f20=open("/tmp/comm.txt")
d=f20.read()
f20.close()
dlist = d.split()
co=d
datanode.comm(name,co)
#datanode.comm()
elif ch=="11":
datanode.hbase()
elif ch=="12":
datanode.users()
elif ch=="13":
datanode.spacequota()
elif ch=="14":
datanode.filequota()
elif ch=="15":
datanode.fairsch()
elif ch=="16":
datanode.uploadfiles()
elif ch=="17":
#os.system("dialog --backtitle 'HADOOP' --title 'WARNING' --inputbox 'are you sure Y/N' 5 40 2>/tmp/decision.txt")
#f2=open("/tmp/decision.txt")
#d=f2.read()
#f2.close()
#if d=="y" or d=="Y" or d=="yes" or d=="YES" or d=="Yes":
q=os.system("dialog --backtitle 'HADOOP' --title 'WARNING' --yesno 'are you sure Y/N' 5 40")
if q==0:
import options
options.options()
#exit()
else:
continue
elif ch=="":
q=os.system("dialog --backtitle 'HADOOP' --title 'WARNING' --yesno 'are you sure Y/N' 5 40")
if q==0:
import options
options.options()
#exit()
else:
continue
else:
print "wrong choice"
else:
os.system("dialog --msgbox 'password is incorrect' 7 30")
login()
else:
os.system("dialog --msgbox 'username is incorrect' 7 30")
login()
import numpy as np
import numpy.random as rand
import matplotlib.pyplot as plt
import options
import gol_utils as utils
import copy
import time
import h5py
print "Welcome to Game of Life"
#Instantiates "options" object from "options" module and assigns it to options
options = options.options()
#Gave the user multiple options to modify attributes for the simulation
options.parseArguments()
#The following attributes are imported from options class in options module
numx = options.numx
numy = options.numy
numsteps = options.numsteps
numsleep = options.numsleep
outputfile = options.outputfile
inputfile = options.inputfile
if inputfile == "": #Checks if an input file has been given,
board = rand.rand(numx, numy) #Seeds a board with random numbers
#between (inclusive) and #1 (noninclusive)
for i in range(numx): #Rounds numbers to 0 or 1
r.add_facet_labels(t)
plot_offsets(t, r.clist, 'red')
if savefig is not None:
plt.savefig(savefig)
if __name__ == '__main__':
# Main loop
if len(sys.argv) < 2:
warn(
'quality_pipeline.py must be called with at least one parameter file\nor a command-line option list.\nE.g "pipeline.py example.cfg second_example.cfg --solutions-robust=0.1"\nSee below for a complete list of possible options with their default values.'
)
print_options(option_list)
sys.exit(1)
o = options(sys.argv[1:], option_list)
if o['pbimage'] is None:
die('pbimage must be specified')
if o['nonpbimage'] is None:
die('nonpbimage must be specified')
if o['list'] is not None:
# fix up the new list-type options
for i, cat in enumerate(o['list']):
try:
o[cat] = o['filenames'][i]
except:
pass
try:
o[cat + '_matchrad'] = o['radii'][i]
except:
pass
def main(msin, config_path):
o = options(config_path, option_list)
if o['pbimage'] is None:
die('pbimage must be specified')
# fix up the new list-type options
for i, cat in enumerate(o['list']):
try:
o[cat] = o['filenames'][i]
except:
pass
try:
o[cat + '_matchrad'] = o['radii'][i]
except:
pass
try:
o[cat + '_fluxfactor'] = o['fluxfactor'][i]
except:
pass
if o['logging'] is not None and not os.path.isdir(o['logging']):
os.mkdir(o['logging'])
# pybdsm source finding
sfind_image(o['catprefix'], o['pbimage'], o['sfind_pixel_fraction'])
# matching with catalogs
for cat in o['list']:
print 'Doing catalogue', cat
crossmatch_image(o['catprefix'] + '.cat.fits', cat)
filter_catalog(o['catprefix'] + '.cat.fits',
o['catprefix'] + '.cat.fits_' + cat + '_match.fits',
o['pbimage'],
o['catprefix'] + '.cat.fits_' + cat +
'_match_filtered.fits',
cat,
options=o)
# Filter catalogs (only keep isolated compact sources within 3deg of pointing centre)
# Astrometric plots
if 'FIRST' in o['list']:
report('Plotting position offsets')
plot_position_offset(
'%s.cat.fits_FIRST_match_filtered.fits' % o['catprefix'],
o['pbimage'],
'%s.cat.fits_FIRST_match_filtered_positions.png' % o['catprefix'],
'FIRST',
options=o)
t = Table.read(o['catprefix'] + '.cat.fits_FIRST_match_filtered.fits')
bsra = np.percentile(bootstrap(t['FIRST_dRA'], np.mean, 10000),
(16, 84))
bsdec = np.percentile(bootstrap(t['FIRST_dDEC'], np.mean, 10000),
(16, 84))
mdra = np.mean(t['FIRST_dRA'])
mddec = np.mean(t['FIRST_dDEC'])
print 'Mean delta RA is %.3f arcsec (1-sigma %.3f -- %.3f arcsec)' % (
mdra, bsra[0], bsra[1])
print 'Mean delta DEC is %.3f arcsec (1-sigma %.3f -- %.3f arcsec)' % (
mddec, bsdec[0], bsdec[1])
report('Plotting flux ratios')
# Flux ratio plots (only compact sources)
plot_flux_ratios(
'%s.cat.fits_FIRST_match_filtered.fits' % o['catprefix'],
o['pbimage'],
'%s.cat.fits_FIRST_match_filtered_fluxerrors.png' % o['catprefix'],
options=o)
report('Plotting flux scale comparison')
# Flux scale comparison plots
if 'TGSS' in o['list']:
plot_flux_errors(
'%s.cat.fits_TGSS_match_filtered.fits' % o['catprefix'],
o['pbimage'],
'%s.cat.fits_TGSS_match_filtered_fluxratio.png' % o['catprefix'],
'TGSS',
options=o)
t = Table.read(o['catprefix'] + '.cat.fits_TGSS_match_filtered.fits')
ratios = t['Total_flux'] / (t['TGSS_Total_flux'] /
o['TGSS_fluxfactor'])
bsratio = np.percentile(bootstrap(ratios, np.median, 10000), (16, 84))
print 'Median LOFAR/TGSS ratio is %.3f (1-sigma %.3f -- %.3f)' % (
np.median(ratios), bsratio[0], bsratio[1])
if 'NVSS' in o['list']:
t = Table.read(o['catprefix'] + '.cat.fits_NVSS_match_filtered.fits')
t = t[t['Total_flux'] > 10e-3]
ratios = t['Total_flux'] / t['NVSS_Total_flux']
bsratio = np.percentile(bootstrap(ratios, np.median, 10000), (16, 84))
print 'Median LOFAR/NVSS ratio is %.3f (1-sigma %.3f -- %.3f)' % (
np.median(ratios), bsratio[0], bsratio[1])
# Noise estimate
hdu = fits.open(o['pbimage'])
imagenoise = get_rms(hdu)
print 'An estimate of the image noise is %.3f muJy/beam' % (imagenoise *
1E6)
return 0
#Local Repo
from options import options
#Web service
from flask import Flask, make_response, jsonify, request, redirect, url_for
from flask.views import MethodView
#GPIO
import RPi.GPIO as GPIO
#Ext REPO
import time
#Adding options
op = options()
#GPIO COMMANDS
def setupGPIO(PIN):
# which naming convention is to be used.
GPIO.setmode(GPIO.BCM)
# Open the pin #DEFAULT = 17
op.printText("+ SETUP FOR GPIO {} STARTED".format(PIN), False)
GPIO.setup(PIN, GPIO.OUT)
# Turning it off
GPIO.output(PIN, GPIO.LOW)
op.printText("+ GPIO {} TURNED OFF".format(PIN), False)
op.printText("+ SETUP FOR GPIO {} ENDED".format(PIN), False)
if isinstance(t,str):
t=Table.read(t)
if 'Facet' not in t.columns:
r.add_facet_labels(t)
plot_offsets(t,r.clist,'red')
if savefig is not None:
plt.savefig(savefig)
if __name__=='__main__':
# Main loop
if len(sys.argv)<2:
warn('quality_pipeline.py must be called with at least one parameter file\nor a command-line option list.\nE.g "pipeline.py example.cfg second_example.cfg --solutions-robust=0.1"\nSee below for a complete list of possible options with their default values.')
print_options(option_list)
sys.exit(1)
o=options(sys.argv[1:],option_list)
if o['pbimage'] is None:
die('pbimage must be specified')
if o['nonpbimage'] is None:
die('nonpbimage must be specified')
if o['list'] is not None:
# fix up the new list-type options
for i,cat in enumerate(o['list']):
try:
o[cat]=o['filenames'][i]
except:
pass
try:
o[cat+'_matchrad']=o['radii'][i]
except:
pass
def napoleon(type_cartes, taille_jeu):
pygame.init()
pygame.display.set_caption("MIASHS")
##Définition des règles
regles = int(taille_jeu / 4)
fenetreX, fenetreY = (200+(regles+1)*80, 750)
fenetre = pygame.display.set_mode((fenetreX, fenetreY))
##Chargement des images
fond = pygame.image.load("images/fond/fond.png")
fond = pygame.transform.scale(fond, (fenetreX, fenetreY))
repertoire_cartes = ("images/" + type_cartes + "/cartes/")
liste_images = fonctions_generales.generation_jeu_aleatoire(repertoire_cartes, regles, 1)
nombre_cartes = len(liste_images)
cartes_dico = images(liste_images, type_cartes)
lignes = 4
colonnes = int(nombre_cartes / lignes)
## creation d'une liste de base, et melange de cartes_dico
liste_cartes = [name for name in cartes_dico] ## prends chaque nom de cartes_dico dans la biblioteque
## rajout de cartes_dico vides a la fin des listes.
cartes_dico = rajoute_carte_vide(cartes_dico)
for i in range(lignes):
liste_cartes.append("V00.png")
shuffle(liste_cartes)
shuffled = [liste_cartes[x:x + colonnes + 1] for x in range(0, len(liste_cartes), colonnes + 1)] ## cree une liste deux dimensions (lignes * colonnes) avec comme valeur les valeurs de liste_cartes
## select transparence
select1 = pygame.image.load("images/select.png").convert_alpha()
select2 = pygame.image.load("images/select2.png").convert_alpha()
mouseX, mouseY = (-1,-1)
select_depart = False ## variable si la carte de depart a été selectionnée
coord_depart = (-1,-1)
select_dest = False ## variable si la carte de destination a été selectionnée
coord_dest = (-1,-1)
myfont = pygame.font.SysFont("monospace", 20)
game_started = False ## devient true quand l'utilisateur commence a jouer! (utilise pour les options)
allow_redo = False ## permet de limiter le nombre de 'redo's de l'utilisateur a une fois
redo = False ## si l'utilisateur veux revenir en arriere d'un mouvement
regles_jeu = [regles, "start", "sup", "same_symbol", "ace on empty", "napoleon"]
all_options = False
while True:
mouseX, mouseY = pygame.mouse.get_pos()
for event in pygame.event.get():
if event.type == QUIT or (event.type == KEYDOWN and event.key == K_ESCAPE):
pygame.quit()
sys.exit()
elif event.type == MOUSEBUTTONDOWN:
## conversion coordonnées brutes en coordonnées tableau
tableauX, tableauY = (mouseX - 30) // 80, (mouseY - 30) // 118
if select_depart == False and 0 <= tableauX < colonnes + 1 and 0 <= tableauY < lignes and shuffled[tableauY][tableauX] != "V00.png": ## pour la carte de depart
coord_depart = tableauX, tableauY
select_depart = True
## si l'utilisateur click sur une carte au lieu du vide en deuxieme choix
elif select_dest == False and 0 <= tableauX < colonnes + 1 and 0 <= tableauY < lignes and shuffled[tableauY][tableauX] != "V00.png":
coord_depart = tableauX, tableauY
select_depart = True
elif select_dest == False and 0 <= tableauX < colonnes + 1 and 0 <= tableauY < lignes and shuffled[tableauY][tableauX] == "V00.png": ## pour la position de destination
coord_dest = tableauX, tableauY
select_dest = True
elif selection == "menu":
principale.main()
elif selection == "options":
type_cartes, restart = options.options(fenetre, type_cartes, taille_jeu, 1, all_options)
if restart:
napoleon(type_cartes, taille_jeu)
repertoire_cartes = "images/" + type_cartes + "/cartes/"
cartes_dico = images(liste_images, type_cartes)
cartes_dico = rajoute_carte_vide(cartes_dico)
elif selection == "retour" and allow_redo:
redo = True
elif event.type == KEYDOWN:
if event.key == K_o:
shuffled = cheat_ordonne(shuffled, lignes, colonnes)
time.sleep(0.2)
## affiche fond
fenetre.blit(fond, (0,0))
## reviens en arriere d'un mouvement
if redo:
shuffled[memory_depart[1]][memory_depart[0]] = shuffled[memory_dest[1]][memory_dest[0]]
shuffled[memory_dest[1]][memory_dest[0]] = "V00.png"
redo = False
allow_redo = False
## affiche cartes_dico
for y in range(lignes):
for x in range(colonnes + 1): # + 1 pour rajouter la carte vide à la fin de chaque ligne
fenetre.blit(cartes_dico[shuffled[y][x]], (x * 80 + 30 , y * 118 + 30))
## affiche contour carte depart
if select_depart:
fenetre.blit(select1, (coord_depart[0] * 80 + 30 , coord_depart[1] * 118 + 30)) ## select transparence
## affiche contour emplacement dest
if select_dest:
fenetre.blit(select2, (coord_dest[0] * 80 + 30 , coord_dest[1] * 118 + 30)) ## select transparence
## affiche les boutons a droite
selection = fonctions_generales.barre_laterale(fenetre, fenetreX, (mouseX,mouseY))
pygame.display.flip()
if select_dest:
carte_depart = shuffled[coord_depart[1]][coord_depart[0]]
carte_compare = shuffled[coord_dest[1]][coord_dest[0]-1]
regles_jeu[4] = coord_dest[0]
if fonctions_generales.check_move(carte_depart, carte_compare, regles_jeu):
memory_card = shuffled[coord_depart[1]][coord_depart[0]]
memory_depart = coord_depart
memory_dest = coord_dest
shuffled[coord_dest[1]][coord_dest[0]] = shuffled[coord_depart[1]][coord_depart[0]]
shuffled[coord_depart[1]][coord_depart[0]] = "V00.png"
game_started = True ## le jeu a commence
allow_redo = True
select_depart,select_dest = False, False
time.sleep(0.2) ## pour qu'il y ait une ptite pause pour qu'on voit bien les couleurs des contours
check_end(shuffled, lignes, colonnes, regles)
def login():
u = os.system(
"dialog --backtitle 'HADOOP' --title 'USERNAME' --inputbox 'enter your username' 7 30 2>/tmp/username.txt"
)
p = os.system(
"dialog --backtitle 'HADOOP' --title 'PASSWORD' --insecure --passwordbox 'enter your password' 7 30 2>/tmp/password.txt"
)
f = open("/tmp/username.txt")
u = f.read()
f.close()
f1 = open("/tmp/password.txt")
p = f1.read()
f1.close()
if u == "":
if p == "":
while True:
os.system(
"dialog --backtitle 'HADOOP' --title 'MENU' --menu 'select a option' 25 60 17 1 'create namenode and jobtracker' 2 'format, start namenode and jobtracker' 3 'create datanode and tasktracker' 4 'start datanode and tasktracker' 5 'HIVE (use this option when a cluster is ready)' 6 'use PIG (when a cluster is ready)' 7 'set high priority to a job' 8 'make a client' 9 'Decommision nodes' 10 'commision nodes' 11 'hbase' 12 'create hdfs users' 13 'set quota on space' 14 'set qouta on file' 15 'setup fair scheduler' 16 'upload a file' 17 'Go back to main menu' 2>/tmp/menu.txt"
)
m = open("/tmp/menu.txt")
ch = m.read()
m.close()
#print type(ch)
if ch == "1":
#allip.all_ip()
namenode.chooseip()
#namenode()
elif ch == "2":
namenode.chooseipstart()
elif ch == "3":
datanode.chooseip1()
elif ch == "4":
datanode.chooseipstart1()
elif ch == "5":
datanode.hive()
elif ch == "6":
datanode.pig()
elif ch == "7":
datanode.priority()
elif ch == "8":
datanode.client()
elif ch == "9":
os.system(
"dialog --infobox 'processing please wait...' 3 34")
ii = commands.getoutput(
'nmap -sP 192.168.109.0/24 | grep 192 | cut -d: -f 2 | cut -c 22-36 > /root/Desktop/hup.txt'
)
f = open("/root/Desktop/hup.txt")
ii = f.read()
f.close()
iilist = ii.split('\n')
f20 = open("/tmp/snon.txt")
d = f20.read()
f20.close()
i = d
i = int(i)
k = iilist[i]
name = k
allip.all_ip()
os.system(
"dialog --backtitle 'HADOOP' --inputbox 'enter ips to make that exclude from cluster' 8 60 2>/tmp/decomm.txt"
)
f20 = open("/tmp/decomm.txt")
d = f20.read()
f20.close()
dlist = d.split()
deco = d
datanode.decomm(name, deco)
elif ch == "10":
os.system(
"dialog --infobox 'processing please wait...' 3 34")
ii = commands.getoutput(
'nmap -sP 192.168.109.0/24 | grep 192 | cut -d: -f 2 | cut -c 22-36 > /root/Desktop/hup.txt'
)
f = open("/root/Desktop/hup.txt")
ii = f.read()
f.close()
iilist = ii.split('\n')
f20 = open("/tmp/snon.txt")
d = f20.read()
f20.close()
i = d
i = int(i)
k = iilist[i]
name = k
allip.all_ip()
os.system(
"dialog --backtitle 'HADOOP' --inputbox 'enter ips to make that include from cluster' 8 60 2>/tmp/comm.txt"
)
f20 = open("/tmp/comm.txt")
d = f20.read()
f20.close()
dlist = d.split()
co = d
datanode.comm(name, co)
#datanode.comm()
elif ch == "11":
datanode.hbase()
elif ch == "12":
datanode.users()
elif ch == "13":
datanode.spacequota()
elif ch == "14":
datanode.filequota()
elif ch == "15":
datanode.fairsch()
elif ch == "16":
datanode.uploadfiles()
elif ch == "17":
#os.system("dialog --backtitle 'HADOOP' --title 'WARNING' --inputbox 'are you sure Y/N' 5 40 2>/tmp/decision.txt")
#f2=open("/tmp/decision.txt")
#d=f2.read()
#f2.close()
#if d=="y" or d=="Y" or d=="yes" or d=="YES" or d=="Yes":
q = os.system(
"dialog --backtitle 'HADOOP' --title 'WARNING' --yesno 'are you sure Y/N' 5 40"
)
if q == 0:
import options
options.options()
#exit()
else:
continue
elif ch == "":
q = os.system(
"dialog --backtitle 'HADOOP' --title 'WARNING' --yesno 'are you sure Y/N' 5 40"
)
if q == 0:
import options
options.options()
#exit()
else:
continue
else:
print "wrong choice"
else:
os.system("dialog --msgbox 'password is incorrect' 7 30")
login()
else:
os.system("dialog --msgbox 'username is incorrect' 7 30")
login()
def main():
# Read config file from command line
config_file = sys.argv[1]
yaml_file = open(config_file)
config = yaml.safe_load(yaml_file)
# Set options structure
opt = options()
opt.palette = config["test_palette"]
opt.test_comp = config["test_composition"]
opt.outer_center = config["outer_center"]
opt.outer_intervals = config["outer_intervals"]
opt.cti_file = config["cti_file"]
opt.mixture = config["mixture_name"]
opt.nx = config["palette_resolution"]
opt.pres = config["pressure"]
opt.temp = config["temperature"]
opt.phi = config["equivalence_ratio"]
opt.t_fin = config["final_time"]
opt.target_mw = config["target_mw"]
opt.target_hc = config["target_hc"]
opt.output_file = config["output_file"]
opt.override_targets = config["override_targets"]
opt.write_output = config["write_output"]
# Close YAML file
yaml_file.close()
# Set gas
gas = ct.Solution(opt.cti_file)
# Check override
check_override(gas, opt)
# Dump options
opt.dump()
# Generate mesh
mesh_data = mesh_generate_box(gas, opt)
print "Mesh generation complete!"
print "Number of points = ", (np.array(mesh_data)).shape[0]
# Estimate number of processes
nProcs = multiprocessing.cpu_count()
print "Number of cores = ", nProcs
# Create gas objects for all processes
pool = multiprocessing.Pool(processes=nProcs,
initializer=init_process,
initargs=(opt.cti_file, ))
try:
os.remove(opt.output_file)
except OSError:
pass
f = open(opt.output_file, 'a')
res = pool.map(
eval_idt,
zip(itertools.repeat(opt.cti_file), itertools.repeat(opt), mesh_data))
# End parallelism
pool.close()
pool.join()
print "Computation finished!"
dump_mat = []
if (opt.write_output):
for idx, mesh_point in enumerate(mesh_data):
dump_point = np.hstack((mesh_point, res[idx]))
dump_mat.append(dump_point)
np.savetxt(f, dump_mat, fmt='%.3e')
f.close()
import gym
import torch
from util import NormalizedActions
from collections import deque
from agent import Agent
import numpy as np
from options import options
options = options()
opts = options.parse()
batch = opts.batch
env = NormalizedActions(gym.make('BipedalWalker-v2'))
from IPython.display import clear_output
import matplotlib.pyplot as plt
policy = Agent(env)
def plot(frame_idx, rewards):
clear_output(True)
plt.figure(figsize=(20,5))
plt.subplot(131)
plt.title('Episode %s. reward: %s' % (frame_idx, rewards[-1]))
plt.plot(rewards)
plt.show()
rewards = []
def __init__(self, confluence):
self.confluence = confluence
self.options = options.options()
def exit(self):
self.op = options.options()
self.close()
self.op.show()
stateDict = {
'net': net.state_dict(),
'acc': acc,
'epoch': epoch,
}
torch.save(stateDict, checkpointPath+dataset+modelName+'Epoch'+str(epoch)+'.pth')
if __name__ == '__main__':
##Parsing options
dataset,checkpointPath,resumeTrainingBool,learningRates,epochs, modelName, sgdMomentum, sgdWeightDecay, trainingBatchSize = options().parseOptions()
##Check whether learning rate array and epoch array has same dimension
if len(learningRates) != len(epochs):
sys.exit('Learning rate array and epoch array must have same dimension')
device = 'cuda' if torch.cuda.is_available() else 'cpu' ##defining device
net = defineModelArchitecture().importModel(dataset,modelName) ##importing the network
net = net.to(device) ##copying network to device
if device == 'cuda':
net = torch.nn.DataParallel(net)
cudnn.benchmark = True
currentEpochNumber = 0 ##current epoch number starts from 0 unless training is resumed from checkpoint
if resumeTrainingBool: # checking whether to resume from checkpoint
def login():
u=os.system("dialog --backtitle 'HADOOP' --title 'USERNAME' --inputbox 'enter your username' 7 30 2>/tmp/username.txt")
p=os.system("dialog --backtitle 'HADOOP' --title 'PASSWORD' --insecure --passwordbox 'enter your password' 7 30 2>/tmp/password.txt")
f=open("/tmp/username.txt")
u=f.read()
f.close()
f1=open("/tmp/password.txt")
p=f1.read()
f1.close()
if u=="":
if p=="":
while True:
os.system("dialog --backtitle 'HADOOP' --title 'MENU' --menu 'select a option' 12 50 2 1 'create automatical cluster' 2 'go back to main menu' 2>/tmp/menu.txt")
m=open("/tmp/menu.txt")
ch=m.read()
m.close()
#print type(ch)
if ch=="1":
#find netid of current computer
os.system("dialog --infobox 'processing please wait...' 3 34")
net=commands.getoutput("ifconfig eth0 | grep 192 | awk '{print$2}'|cut -c 6-20")
net=net+'/24'
netip=commands.getoutput("nmap -sP %s | grep 192 | awk '{print$5}'"%net)
netiplist=netip.split('\n')
#find total ram memory of each active ip in the network
memo=dict() #dictionary containing memory info of all active ips
#print "hi"
for item in netiplist:
if item=='192.168.109.1' or item=='192.168.109.2' or item=='192.168.109.254':
continue
x=commands.getoutput("ssh %s free -m | grep Mem | awk '{print$2}'"%item)
memo[item]=x
sorted_x = sorted(memo.items(), key=operator.itemgetter(1))
nn_ip = sorted_x[0][0]
k=nn_ip
#print k
n_hdfs(k)
n_core(k)
n_mapred(k)
n_start(k)
d_hdfs(k)
d_core(k)
d_mapred(k)
i=0
for df in sorted_x:
i+=1
#print i
j=1
for fd in sorted_x:
if j<i:
#print sorted_x[j][0]
k=sorted_x[j][0]
thread.start_new_thread(copy,(k,))
thread.start_new_thread(d_start,(k,))
j+=1
elif ch=="2":
q=os.system("dialog --backtitle 'HADOOP' --title 'WARNING' --yesno 'are you sure Y/N' 5 40")
if q==0:
import options
options.options()
#exit()
else:
continue
elif ch=="":
q=os.system("dialog --backtitle 'HADOOP' --title 'WARNING' --yesno 'are you sure Y/N' 5 40")
if q==0:
import options
options.options()
#exit()
else:
continue
else:
print "wrong choice"
else:
os.system("dialog --msgbox 'password is incorrect' 7 30")
login()
else:
os.system("dialog --msgbox 'username is incorrect' 7 30")
login()
from gen_tpu_for_vtr import bit_vector
from gen_tpu_for_vtr import process_arrays
from gen_tpu_for_vtr import process_LO
import os
entries = os.listdir("verilog")
data = ""
for entry in entries:
filename = "verilog/" + entry
f = open(filename,'r')
data += f.read()
data += "\n"
f = open("verilog/final.v","w")
uut = options(f)
uut.write()
uut = matmul_defines(f)
uut.write()
f.close()
f = open("verilog/final.v",'a')
f.write(data)
f.close()
f = open("verilog/final.v", 'r')
f2 = open("verilog/final2.v", 'w')
process_arrays(f, f2)
f2.close()
f.close()
from dataloaders.kaistDataset import KaistDataset
from options import options
import torch
CONFIG_FILE_NAME = "../configs/encoderDecoderFusionv2.ini"
args = options(CONFIG_FILE_NAME)
dataset_train = KaistDataset(args.argsDataset, train=True)
dataset_test = KaistDataset(args.argsDataset, train=False)
def checkImageValidity(image):
result1 = torch.isnan(image).any()
result2 = torch.isinf(image).any()
result3 = (image < 0).any()
result = result1.__or__(result2)
result = result.__or__(result3)
return result
bad_indexs_inp = []
bad_indexs_gt = []
f = open('bad_sections.txt', 'a')
print(len(dataset_train))
for index in range(len(dataset_train)):
if index % 1000 == 0:
print(f'{index} file processed')
data = dataset_train.__getitem__(index)
for image in data['inputs']:
if checkImageValidity(image):
bad_indexs_inp.append(dataset_train.imageFiles[0][index])
print(f'Invalid image path in inputs: {dataset_train.imageFiles[0][index]}, {index}')
import sys
sys.path.append('../utils')
sys.path.append('../model')
import options
import importlib
from utils_loadModel import *
from collections import OrderedDict
# get input argument
args = options.options()
args.initialize()
args = args.parser.parse_args()
print args.coarseModel
# load model
coarseModel, fineModel, detailModel = loadModels(args)
print type(coarseModel)
from skimage import io
import os
import numpy as np
import time
import torch.optim as optim
from torch.autograd import Variable
import torchvision.transforms as transforms
import torch
from tensorboardX import SummaryWriter
# set random seed for all possible randomness
import torch.nn as nn
import torch.nn.functional as F
from utils import ReverseLayerF
from options import options
import torchvision.models as models
# options
opt = options().opt
extractor = opt.extractor
classifier = opt.classifier
discriminator = opt.discriminator
class Extractor(nn.Module):
def __init__(self):
super(Extractor, self).__init__()
model = models.__dict__[extractor]()
newmodel = nn.Sequential(*(list(model.children())[:-4]))
self.extractor = newmodel
def forward(self, x):
x = self.extractor(x)
print(x.size())
x = x.view(-1, 128 * 32 * 32)
return x
# class Extractor(nn.Module):
# def __init__(self):
# super(Extractor, self).__init__()
# self.extractor = nn.Sequential(
#option5 = options() #option5.eta = 0.02 #option5.maxepoch = 100 #option5.num_hid =61 #config.append(option1) #config.append(option5) #config.append(option3) # initialize CUDA print 'initializing CUDA' cm.cublas_init() cm.CUDAMatrix.init_random(1) print 'CUDA initialized' config = [] option0 = options() option0.eta = 0.002 option0.maxepoch = 200 option0.num_hid = 2000 option1 = options() option1.eta = 0.02 option1.maxepoch = 100 option1.num_hid = 2000 option2 = options() option2.eta = 0.01 option2.maxepoch = 200 option2.num_hid = 61 config.append(option1)#gaussian layer config.append(option1)#binary layer2 config.append(option1)#binary layer3 config.append(option1)#binary layer4
import copy
import random
import threading
import time
import os
import translate
import kotoha_player
from privval import *
import sys
import options
from idol_db import *
client = Client()
kot_player = None
current_vc = None
option = options.options()
active = True
music_list = []
kot_player = None
flg = False
connected = False
idolJson = GetIdolJson()
async def reload():
update_servers(client)
update_channels(client)
This is called globals.py, but it actually parses all the arguments and performs
the global OpenRAM setup as well.
"""
import os
import debug
import shutil
import optparse
import options
import sys
import re
import importlib
USAGE = "Usage: openram.py [options] <config file>\nUse -h for help.\n"
# Anonymous object that will be the options
OPTS = options.options()
def parse_args():
""" Parse the optional arguments for OpenRAM """
global OPTS
option_list = {
optparse.make_option("-b",
"--backannotated",
action="store_true",
dest="run_pex",
help="Back annotate simulation"),
optparse.make_option("-o",
"--output",
def __init__(self,argvs,rpt): ## {
g_opt = options();
g_opt.set_support('eda','\n\tspecify the eda tool, for now, valid only for vcs tool, \n\tand interfaces will be retained for other eda tools.','edatool');
g_opt.set_support('help','\n\thelp option to display all valid options for fgen tool.');
g_opt.set_support('rtl','\n\tspecify the rtl type to lead the tool to generate the different \n\tcombination of compile.lis. Default rtl_type is \'asic\'.','rtl_type');
g_opt.set_support('path','\n\tspecify the path to generate the filelist, this is an optional param, \n\tif not specified, the default path: <proj_home>/out/sim/<rtl_type>/tests/ will be used.','dest_path');
g_opt.set_support('proj_home','\n\tthe project home specified by caller.','path');
g_opt.set_support('erf','\n\texternal rtl file, this means the file should be added to rtl.lis, this option used to load common rtls, \n\twith different rtl mode, the erf can specify corresponding rtl modules.','file_name');
g_opt.set_support('esf','\n\texternal sim_model file, this means the file should be added to sim_model.lis, this option used to load common sim_models, \n\twith different rtl mode, the esf can specify corresponding sim_model modules.','file_name');
g_opt.set_support('uvc','\n\tspecify the uvc package with path.','uvc_pkg');
g_opt.set_support('y','\n\tto specify the library path, by different eda tools, this option will be \n\ttranslated to the corresponding options recognized by the tool. Besides, \n\tthis option only support the eda tool that can support filelist option insertion.','library');
g_opt.set_support('libext','\n\tthis option work together with -y option, to specify the \n\tsearching file with specified extension. This option can be input \n\twith multiple times for specifying multiple extensions.','extensions');
g_opt.set_support('target','\n\tthe option specify the destined usage for calling this tool. \n\tthe target name for now are valid within: \n <sim>: for simulation, in this target, the compile.lis, rtl.lis, \n\tdpi.lis, fsim.lis and sim_model.lis will be generated nomatter files above exists or not. \n <wav>: for wave vision, in this target, wave.lis, rtl.lis, fsim.lis \n\tand sim_model.lis will be generated nomatter files above exists or not.','target_name');
g_opt.set_support('pt','\n\tthe project type option, valid only within IP, SUBS and SOC.','proj_type');
g_opt.set_support('debug','\n\tthe debug enable switch, use this option to display debug information.');
## -- option process -------------------------------------------------------------------------
if g_opt.load(argvs) == False: ## {
rpt.fatal("program fatal occurred when check option.");
exit(1);
## }
self.g_proj_home = g_opt.get_param('proj_home');
if self.g_proj_home == False: self.g_proj_home = './'; ## if the proj_home is not specified by user, then use default value: './'
## the var that indicates the eda tool user want to use, then we will generate corresponding file list.
## value valid in range of: 'vcs' and 'xcelium'.
self.g_eda = g_opt.get_param('eda');
if self.g_eda == False: self.g_eda = 'vcs'; ## default use vcs tool if no user entered -eda
while g_opt.exists('y'): ## {
## while the 'y' param exists, then to pop the param until all user entered -y are poped from the argv pool
self.g_lpaths.append(g_opt.get_param('y'));
## }
while g_opt.exists('libext'): ## {
## and this option can be specified by user with multiple times
self.g_libext.append(g_opt.get_param('libext'));
## }
self.g_help = g_opt.exists('help');
self.g_debug = g_opt.exists('debug');
self.g_rtl_t = g_opt.get_param('rtl');
if self.g_rtl_t == False: self.g_rtl_t = 'asic'; ## if get the False type, then use the default value: 'asic'
self.g_target = g_opt.get_param('target');
if self.g_target == False: self.g_target = 'sim'; ## if get the False param, then use default: 'sim'.
self.g_pt = g_opt.get_param('pt');
if self.g_pt == False: self.g_pt = 'IP'; ## if get the False param, then use default: 'IP'
self.g_o_path = g_opt.get_param('path');
if self.g_o_path == False: self.g_o_path = self.g_proj_home+'/out/sim/'+self.g_rtl_t+'/tests'; ## if the path not specified by user, then use default output path .
while g_opt.exists('erf'); ## {
SocketServer.ThreadingTCPServer.__init__(self,bind_to,handler)
def verify_request(self,reqsocket,client_address):
hosts = map(gethostbyname,self.options.get('hosts',[]))
if hosts and client_address[0] not in hosts:
print "Hosts allowed:",hosts
print "Rejecting connection from", client_address[0]
return 0
else: return 1
# MAIN ------------------------------------------------------------------------
if __name__ == '__main__':
syntax={'--port':'21','--hosts':[],'--start':0,'--dir':'.',
'--allow':('.txt','.ux','.csv','.doc','.html','.rtf'),
'--allow-also':[],
'--help':0,'--once':0}
opts=options(syntax,sys.argv[1:])
try:
hosts = opts['--hosts']
start = opts['--start']
base = opts['--dir']
allow = list(opts['--allow']) + opts['--allow-also']
port = int(opts['--port'])
once = opts['--once']
help = opts['--help']
except:
port = 21
start = 0
base = '.'
hosts = []
allow = ['.txt']
once = 0
def golf(type_cartes, taille_jeu):
pygame.init()
pygame.display.set_caption("MIASHS")
##Définition des règles
regles = int(taille_jeu / 4)
## determine les lignes et colonnes grace a regles
lignes, colonnes = taille_golf(regles)
fenetreX, fenetreY = 80+(colonnes*75)+((colonnes-1)*45)+80, 750
fenetre = pygame.display.set_mode((fenetreX, fenetreY))
##Chargement des images
fond = pygame.image.load("images/fond/fond.png").convert()
fond = pygame.transform.scale(fond, (fenetreX, fenetreY))
select = pygame.image.load("images/select.png").convert_alpha()
repertoire_cartes = ("images/" + type_cartes + "/cartes/")
liste_images = fonctions_generales.generation_jeu_aleatoire(repertoire_cartes, regles, 1)
cartes_dico = images(liste_images, type_cartes)
## creation d'une liste de base, et melange de cartes_dico
liste_cartes = [name for name in cartes_dico]
shuffle(liste_cartes)
tableau_cartes = [liste_cartes[x:x+lignes] for x in range(0, colonnes * lignes, lignes)]
pioche_cartes = liste_cartes[colonnes * lignes:]
## le dos des cartes_dico (pour la pioche), carte vide
dos = pygame.image.load("images/" + type_cartes + "/dos/dos.png").convert_alpha()
cartes_dico = rajoute_carte_vide(cartes_dico)
carte_pioche = "V00.png"
mouseX, mouseY = (-1,-1)
select_card = False
coord_card = (-1,-1)
pioche = False
myfont = pygame.font.SysFont("monospace", 20)
allow_redo = False ## permet de limiter le nombre de 'redo's de l'utilisateur a une fois
redo = False ## si l'utilisateur veux revenir en arriere d'un mouvement
last_move = '' ## prends les valeurs 'pioche' ou 'tableau' pour indiquer le dernier type de mouvement de l'utilisateur
regles_jeu = [regles, "start", "both+", "any", "hello", "golf"] ## a etre utilise pour la fonction check_move
all_options = False
while True:
mouseX, mouseY = pygame.mouse.get_pos()
for event in pygame.event.get():
if event.type == QUIT or (event.type == KEYDOWN and event.key == K_ESCAPE):
pygame.quit()
sys.exit()
elif event.type == MOUSEBUTTONDOWN:
click_type, ind = check_mouse((mouseX, mouseY), tableau_cartes, len(pioche_cartes), colonnes, (fenetreX, fenetreY))
if click_type == "cartes" and carte_pioche != "V00.png":
coord_card = (mouseX - 80) // 120, len(tableau_cartes[ind]) - 1
select_card = True
game_started = True
last_move = click_type
elif click_type == "pioche":
memory_pioche = carte_pioche
carte_pioche = pioche_cartes.pop()
allow_redo = True
last_move = click_type
elif selection == "menu":
principale.main()
elif selection == "options":
type_cartes, restart = options.options(fenetre, type_cartes, taille_jeu, 1, all_options)
if restart:
golf(type_cartes, taille_jeu)
repertoire_cartes = "images/" + type_cartes + "/cartes/"
cartes_dico = images(liste_images, type_cartes)
cartes_dico = rajoute_carte_vide(cartes_dico)
elif selection == "retour" and allow_redo:
start_time = pygame.time.get_ticks()
redo = True
elif event.type == KEYDOWN:
if event.key == K_p:
print(fonctions_generales.ordre_valeurs(regles, "start"))
## affiche fond
fenetre.blit(fond, (0,0))
## reviens en arriere d'un mouvement
if redo:
if last_move == 'cartes':
tableau_cartes[memory_coord[0]].append(carte_pioche)
carte_pioche = memory_pioche
redo = False
allow_redo = False
elif last_move == 'pioche':
pioche_cartes.append(carte_pioche)
carte_pioche = memory_pioche
redo = False
allow_redo = False
## affiche cartes_dico
for x in range(colonnes):
for y in range(lignes):
try:
fenetre.blit(cartes_dico[tableau_cartes[x][y]], (x * 120 + 80, y * 50 + 30))
except:
break
## affiche pioche
for i in range(len(pioche_cartes)):
fenetre.blit(dos, (80 + i * 5, 400))
## affiche contour carte (+ 1 pour colonnes pour la colonne vide du depart)
if select_card == True:
fenetre.blit(select, (coord_card[0] * 120 + 80 , coord_card[1] * 50 + 30))
## affiche la carte visible
fenetre.blit(cartes_dico[carte_pioche], (300, 400))
## affiche les boutons a droite
selection = fonctions_generales.barre_laterale(fenetre, fenetreX, (mouseX,mouseY))
pygame.display.flip()
## apres le display flip pour que le time.sleep soit precevable
if select_card:
carte_select = tableau_cartes[coord_card[0]][coord_card[1]]
if fonctions_generales.check_move(carte_select, carte_pioche, regles_jeu):
memory_pioche = carte_pioche
memory_coord = coord_card[0], coord_card[1]
carte_pioche = tableau_cartes[coord_card[0]][coord_card[1]]
del(tableau_cartes[coord_card[0]][coord_card[1]])
allow_redo = True
select_card = False
time.sleep(0.2)
check_end(tableau_cartes, carte_pioche, pioche_cartes, regles_jeu)
'''
msg_data = json.loads(msg_json)
msg_id = msg_data['msg_id']
response = {
'status_code': 200,
'status_text': 'OK',
'data': 'what up?',
'msg_id': msg_id,
}
response_json = json.dumps(response)
print 'Sending back to Tornado: %s' % (response_json)
stream.send_multipart(response_json)
'''
if __name__ == '__main__':
opts = options.options()
# print 'opts=', repr(opts)
# print ' logging=', opts.logging
# logging.info('WTF???')
'''
goptions = dict()
if len(sys.argv) > 1:
goptions['immediate_flush'] = False
'''
#EchoRouter = SockJSRouter(ModSock, '/sock', options) # Модуль 1. Постоянное соединение
'''
TestRouter = [('/info/control', ModHTTP), ('/info/clients', Clients), (r'/test(.*)', TestHandler)] # Модуль 2. HTTP управление
settings = {
"template_path": os.path.join(os.path.dirname(__file__), "templates"),
"static_path": os.path.join(os.path.dirname(__file__), "static"),
"cookie_secret": "61oETzKXQAGaYdkL5gEmGeJJFuYh7EQnp2XdTP1o/Vo=",
hat_x = utils.crop_valid(hat_x, k)
x = utils.crop_valid(x, k)
y = utils.crop_valid(y, k)
val_psnr += loss.psnr(hat_x, x)
val_ssim += loss.ssim(hat_x, x)
val_l1 += F.l1_loss(hat_x, x).item()
return val_psnr / len(loader), val_ssim / len(loader), val_l1 / len(loader)
if __name__ == '__main__':
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
parser = options.options()
opts = parser.parse_args()
### data loader
datapath = opts.datapath
savepath = './results'
savepath = os.path.join(savepath,
'uniform_T_%02d_S_%02d' % (opts.n_out, opts.n_in))
if opts.blind:
savepath += '_blind_0.5_to_%2.2f' % (255 / 100 * opts.sigma)
else:
savepath += '_nonblind_%2.2f' % (255 / 100 * opts.sigma)
os.makedirs(savepath, exist_ok=True)
modelpath = os.path.join(savepath, 'weights')
os.makedirs(modelpath, exist_ok=True)
dt_tr = datasets.UniformTrainDataset(opts.datapath,
