def install(**kwargs):
"""setup entry point"""
if USE_SETUPTOOLS:
if '--force-manifest' in sys.argv:
sys.argv.remove('--force-manifest')
# install-layout option was introduced in 2.5.3-1~exp1
elif sys.version_info < (2, 5, 4) and '--install-layout=deb' in sys.argv:
sys.argv.remove('--install-layout=deb')
if subpackage_of:
package = subpackage_of + '.' + modname
kwargs['package_dir'] = {package : '.'}
packages = [package] + get_packages(os.getcwd(), package)
if USE_SETUPTOOLS:
kwargs['namespace_packages'] = [subpackage_of]
else:
kwargs['package_dir'] = {modname : '.'}
packages = [modname] + get_packages(os.getcwd(), modname)
if USE_SETUPTOOLS and install_requires:
kwargs['install_requires'] = install_requires
kwargs['dependency_links'] = dependency_links
kwargs['packages'] = packages
return setup(name = distname,
version = version,
license = license,
description = description,
long_description = long_description,
author = author,
author_email = author_email,
url = web,
scripts = ensure_scripts(scripts),
data_files = data_files,
ext_modules = ext_modules,
cmdclass = {'install_lib': MyInstallLib},
**kwargs
)
def create_filetree(path=None, depth=0, max_depth=0):
tree = None
if max_depth == 0 or depth < max_depth:
if path is None:
path = os.getcwd()
tree = dict(name=os.path.basename(path), children=[])
try:
lst = os.listdir(path)
except OSError:
pass # ignore errors
else:
for name in lst:
fn = os.path.join(path, name)
if (os.path.isdir(fn) and
re.match('^.*(Compiled)$', fn) is None):
child = create_filetree(fn, depth + 1, max_depth)
if child is not None:
tree['children'].append(child)
elif re.match('^.*\.(m|def|txt|csv)$', fn) is not None:
tree['children'].append(dict(name=fn.replace(
os.getcwd() + os.path.sep, "")))
return tree
def SanityCheckDirectory():
if os.getcwd().endswith(SAFE_DIR_SUFFIX):
return
logging.error('httpd.py should only be run from the %s', SAFE_DIR_SUFFIX)
logging.error('directory for testing purposes.')
logging.error('We are currently in %s', os.getcwd())
sys.exit(1)
def get_file_list_recursive(extension="*", file_list=[], dir_path=None, recurs_iter=0, recurs_max=8):
"""
Returns a list of files with a specific extension by analysing directories recursively
"""
cwd = os.getcwd()
if dir_path is not None:
os.chdir(dir_path)
dir_path_add = os.getcwd()
for _, dirs, files in os.walk("./"):
if len(dirs) > 0:
for dir_recur in dirs:
file_list_dir = get_file_list_recursive(extension=extension, file_list=file_list,
dir_path=dir_recur, recurs_iter=recurs_iter+1, recurs_max=recurs_max)
else:
file_list_dir = glob.glob("*.%s" % (extension))
# adding directory to the path
for i in range(len(file_list_dir)):
file_list_dir[i] = os.path.join(dir_path_add, file_list_dir[i])
# joining two lists, python makes it so easy :)
file_list += file_list_dir
os.chdir(cwd)
return file_list
def download_mango(url, path):
"""
Function: download_mango(url, path)
Usage: download_mango('http://www.mangareader.net/poyopoyo-kansatsu-nikki/1', os.getcwd())
Added in version: 0.1 Beta
"""
if path != os.getcwd():
pathchange(os.getcwd(), path)
urlContent = urllib2.urlopen(url).read()
imgUrls = re.findall('img .*?src="(.*?.jpg)"', urlContent)
for imgUrl in imgUrls:
try:
imgData = urllib2.urlopen(imgUrl).read()
fileName = basename(urlsplit(imgUrl)[2])
output = open(fileName, 'wb')
output.write(imgData)
output.close()
except IOError:
print "File not found or full disk. Try again."
sys.exit(1)
except KeyboardInterrupt:
print "Operation aborted manually."
sys.exit(1)
except:
print "Unknown error. If this persists, contact the author or create a ticket in the bugtracker."
sys.exit(1)
def filter_files(kernel, is_relative, exclude, write_files):
extra=''
for i in exclude:
extra += ' -not -path "*' + i + '/*" '
if kernel:
cmd="""find {0} \
-path "$PWD/arch/*" ! -path "$PWD/arch/x86*" -prune -o \
-path "$PWD/include/asm-*" ! -path "$PWD/include/asm-i386*" -prune -o \
-path "$PWD/sound*" -prune -o \
-path "$PWD/firmware*" -prune -o \
{1} \
-iname "*.[chxsS]" -print > {2}
""".format('.' if is_relative else os.getcwd(), extra, write_files)
else:
cmd="""find {0} \( \
-name '*.py' \
-o -name '*.php' \
-o -name '*.java' \
-o -iname '*.[ch]' \
-o -name '*.cpp' \
-o -name '*.cc' \
-o -name '*.hpp' \) \
{1} \
> {2}
""".format('.' if is_relative else os.getcwd(), extra, write_files)
print cmd
process = subprocess.Popen(cmd, stdout=subprocess.PIPE,shell=True)
out, err = process.communicate()
print out
def test_run_multiproc_nondaemon_with_flag(nondaemon_flag):
'''
Start a pipe with two nodes using the multiproc plugin and passing the nondaemon_flag.
'''
cur_dir = os.getcwd()
temp_dir = mkdtemp(prefix='test_engine_')
os.chdir(temp_dir)
pipe = pe.Workflow(name='pipe')
f1 = pe.Node(interface=Function(function=TestInterface.testFunction, input_names=['sum'], output_names=['sum_out']), name='f1')
f2 = pe.Node(interface=Function(function=TestInterface.testFunction, input_names=['sum'], output_names=['sum_out']), name='f2')
pipe.connect([(f1,f2,[('sum_out','sum')])])
pipe.base_dir = os.getcwd()
f1.inputs.sum = 0
# execute the pipe using the MultiProc plugin with 2 processes and the non_daemon flag
# to enable child processes which start other multiprocessing jobs
execgraph = pipe.run(plugin="MultiProc", plugin_args={'n_procs':2, 'non_daemon':nondaemon_flag})
names = ['.'.join((node._hierarchy,node.name)) for node in execgraph.nodes()]
node = execgraph.nodes()[names.index('pipe.f2')]
result = node.get_output('sum_out')
yield assert_equal, result, 180 # n_procs (2) * numberOfThreads (2) * 45 == 180
os.chdir(cur_dir)
rmtree(temp_dir)
def paipai(self):
self.parent.cam.saveSnapshot(os.getcwd() + '/image/s2.png', timestamp=self.timestamp, boldfont=self.boldfont, quality=self.quality)
self.autoCam()
img = ImageProcess()
img.thumbnails(os.getcwd() + '/image/s2.png', os.getcwd() + '/image/s3.png', 170, 170)
self.parent.showimage()
self.close()
def create_backup():
cwd = os.getcwd()
os.chdir(BASE_DIR)
current_date = datetime.utcnow().strftime(FILE_TIME_FORMAT)
filename = os.path.join(MEDIA_ROOT, current_date + SQL_FORMAT)
backup_name = "Ignite_" + current_date + TAR_FORMAT
tar_name = os.path.join(MEDIA_ROOT, BACKUP, backup_name)
db_dump(filename)
file_obj = tarfile.open(tar_name, "w:gz")
logger.debug("cwd = " + os.getcwd())
for name in FILE_LIST:
file_obj.add(MEDIA + "/" + name)
file_obj.add(MEDIA + "/" + current_date + SQL_FORMAT)
file_obj.close()
try:
os.remove(filename)
except:
delete_backup([current_date + TAR_FORMAT])
raise IgniteException(ERR_FAILED_TO_REMOVE + filename)
resp = {}
resp["status"] = "success"
resp["filename"] = backup_name
os.chdir(cwd)
return resp
def download_dir(dsvc,dir_file,depth=0):
cwd = os.getcwd()
out_root = os.path.join(cwd,dir_file['title'])
disp_path = out_root.replace(PROG_ROOT,"")
print("ChangeDir to %s" % disp_path)
if(not os.path.exists(out_root)):
os.makedirs(out_root)
os.chdir(out_root)
file_list = get_file_meta(dsvc,"'%s' in parents" % dir_file['id'])
counter = 1
total = len(file_list)
for file in file_list:
if(file['mimeType'] == "application/vnd.google-apps.folder"):
print("[%s%d/%d] %s (Directory)" % ((depth * "-"),counter,total,file['title']))
download_dir(dsvc,file,depth+1)
else:
#We have a file.
fsmb = float(float(file['fileSize']) / (1024*1024))
print("[%s%d/%d] %s (%.2fMB)" % ((depth * "-"),counter,total,file['title'],fsmb))
download_file(dsvc,file)
counter +=1
os.chdir("..")
cwd = os.getcwd()
disp_path = cwd.replace(PROG_ROOT,"")
if(disp_path != ""):
print("ChangeDir to %s" % disp_path)
def run(self, args):
namespace = self.parser.parse_args(args)
# Get absolute paths
namespace.pecan_config = os.path.join(os.getcwd(),
namespace.pecan_config)
namespace.api_paste_config = os.path.join(os.getcwd(),
namespace.api_paste_config)
namespace.config_file = os.path.join(os.getcwd(),
namespace.config_file)
# Check conf files exist
if not os.path.isfile(namespace.pecan_config):
print("Bad config file: %s" % namespace.pecan_config,
file=sys.stderr)
sys.exit(1)
if not os.path.isfile(namespace.api_paste_config):
print("Bad config file: %s" % namespace.api_paste_config,
file=sys.stderr)
sys.exit(2)
if not os.path.isfile(namespace.config_file):
print("Bad config file: %s" % namespace.config_file,
file=sys.stderr)
sys.exit(1)
app.SurveilCommand().run(namespace)
def unzip_input(file):
print "* Unzipping" + file
zfile = zipfile.ZipFile(os.getcwd() + "/input/" + file + ".zip")
for name in zfile.namelist():
(dirname, filename) = os.path.split(name)
zfile.extract(name, os.getcwd() + "/input/")
zfile.close()
def prompt_for_solution_stack(module_name=None):
solution_stacks = elasticbeanstalk.get_available_solution_stacks()
# get list of platforms
platforms = []
for stack in solution_stacks:
if stack.platform not in platforms:
platforms.append(stack.platform)
cwd = os.getcwd()
# First check to see if we know what language the project is in
try:
fileoperations._traverse_to_project_root()
platform = heuristics.find_language_type()
if platform == 'Docker':
# Check to see if dockerrun is version one or two
dockerrun_file = dockerrun.get_dockerrun(
os.path.join(os.getcwd(), 'Dockerrun.aws.json'))
if dockerrun_file:
if dockerrun_file.get('AWSEBDockerrunVersion') in (1, '1'):
platform = 'Docker'
else:
platform = 'Multi-container Docker'
finally:
os.chdir(cwd)
if platform is not None:
io.echo()
io.echo(prompts['platform.validate'].replace('{platform}', platform))
correct = io.get_boolean_response()
if not platform or not correct:
# ask for platform
io.echo()
io.echo(prompts['platform.prompt']
if not module_name
else prompts['platform.prompt.withmodule'].replace('{module_name}',
module_name))
platform = utils.prompt_for_item_in_list(platforms)
# filter
solution_stacks = [x for x in solution_stacks if x.platform == platform]
#get Versions
versions = []
for stack in solution_stacks:
if stack.version not in versions:
versions.append(stack.version)
#now choose a version (if applicable)
if len(versions) > 1:
io.echo()
io.echo(prompts['sstack.version'])
version = utils.prompt_for_item_in_list(versions)
else:
version = versions[0]
return get_latest_solution_stack(version, stack_list=solution_stacks)
def get_extensions():
from distutils.extension import Extension
common_extension_args = {
'include_dirs': get_include_dirs(),
'library_dirs': get_library_dirs(),
'libraries': get_libraries()}
try:
from Cython.Build import cythonize
sources = [os.path.join(os.getcwd(), 'pyfftw', 'pyfftw.pyx')]
have_cython = True
except ImportError as e:
# no cython
sources = [os.path.join(os.getcwd(), 'pyfftw', 'pyfftw.c')]
if not os.path.exists(sources[0]):
raise ImportError(
str(e) + '. ' +
'Cython is required to build the initial .c file.')
have_cython = False
ext_modules = [
Extension('pyfftw.pyfftw', sources=sources,
**common_extension_args)]
if have_cython:
return cythonize(ext_modules)
else:
return ext_modules
def __upload_file(self,ip="",port=36000,username="",password="",file_name=""):
"""function:upload script file"""
try:
result=True
code =0
msg = "OK"
t = paramiko.Transport((ip,port))
t.connect(username=username,password=password)
sftp =paramiko.SFTPClient.from_transport(t)
#
try:
sftp.put(os.getcwd()+"/tools/"+file_name,"/tmp/"+file_name)
#print "Upload Local File:",
except Exception,e:
print "Exception:",str(e)
print "Try again"
time.sleep(5)
try:
sftp.put(os.getcwd()+"/tools/"+file_name,"/tmp/"+file_name)
except Exception,e:
msg+=(str(e))
result=False
code = 1
msg=str(e)
def verifyArguments(args):
# Verify supplied arguments
if args.application is None or os.path.exists(args.application) is False:
# Before we error, lets verfiy if current parent directory matches
# the application they were supplying:
if os.path.basename(os.getcwd()) != args.application:
print 'You must specify a path to the application you wish to build an SQA documentation for.'
sys.exit(1)
else:
args.application = os.getcwd()
else:
if os.path.exists(os.path.join(args.application, 'doc/sqa', args.requirements)) is False:
print 'I could not find ', os.path.join(os.path.abspath(args.application), 'doc/sqa', args.requirements), 'file.' \
'\nPlease see the directory:', os.path.join(os.path.abspath(os.path.dirname(sys.argv[0])), '..', 'framework/doc/sqa'), 'for a working example'
sys.exit(1)
args.application_path = os.path.abspath(args.application)
args.requirements_path = os.path.join(args.application_path, 'doc/sqa', args.requirements)
args.application_name = os.path.split(args.application_path)[1]
# Set the current working directory to this script location
# We to do this _after_ discovering application path in case
# the user supplied a relative path instead of an absolute
# path
args.cwd = os.getcwd()
os.chdir(os.path.abspath(os.path.dirname(sys.argv[0])))
# Set MOOSE_DIR to parent directory (were sitting
# in moose/scripts at the moment)
args.moose_dir = os.path.abspath('..')
return args
def copy_rails_config_file(directory, filename, flag=0):
"""
Description:
Vars:
1. f_dst: source file name
2. f_src: dst file name
3. flag
1 => copy ".project"
2 => copy "do_heroku.bat"
4. content: content of ".project"
5. fin: file object
6. fout: file object
7. directory: full directory path
"""
f_dst = os.path.join(os.getcwd(), filename)
f_src = os.path.join(os.path.dirname(inspect.currentframe().f_code.co_filename), directory, filename)
if flag == 1:
fin = open(f_src, "r")
# content = f.read()
content = fin.read()
content = content.replace("@project_name@", os.path.basename(os.getcwd()))
# os.path.basename(f_dst))
fout = open(f_dst, "w")
fout.write(content)
fin.close()
fout.close()
else:
shutil.copyfile(f_src, f_dst)
print "File copied"
print "\t", "From: %s" % f_src
print "\t", "To: %s" % f_dst
def create(username, site_name):
import re
newsite = "bench new-site " + site_name
installapp = "bench --site "+ site_name + " install-app erpnext"
# NOTETHIS: check if site_name already exists
print "Creating new site.."
os.system(newsite)
print "Installing erpnext to site.."
os.system(installapp)
# get database name from site_config.json of new site
old_dir = os.getcwd()
path = '/home/testuser/frappe-bench/sites/'+ site_name
os.chdir(path)
print os.getcwd()
with open('site_config.json') as f:
content = f.readlines()
tmp = content[1].strip()
tmp = tmp.split(":")[1]
db_name = re.sub('\W+','',tmp)
os.chdir(old_dir)
# add site to database, mapped to owner
newsite = User_Sites()
newsite.username = username
newsite.db_name = db_name
newsite.site_name = site_name
newsite.save()
print "Done!"
def __init__(self, defaults=None, confFile=None, *args, **kwds):
"""Initialize the parser.
*defaults* -- defaults values.
*confFile* -- the file (or list of files) to parse."""
ConfigParser.ConfigParser.__init__(self, defaults=defaults)
if confFile is None:
dotFileName = '.' + confFileName
# Current and home directory.
confFile = [os.path.join(os.getcwd(), confFileName),
os.path.join(os.getcwd(), dotFileName),
os.path.join(os.path.expanduser('~'), confFileName),
os.path.join(os.path.expanduser('~'), dotFileName)]
if os.name == 'posix':
sep = getattr(os.path, 'sep', '/')
# /etc/ and /etc/conf.d/
confFile.append(os.path.join(sep, 'etc', confFileName))
confFile.append(os.path.join(sep, 'etc', 'conf.d',
confFileName))
else:
# etc subdirectory of sys.prefix, for non-unix systems.
confFile.append(os.path.join(sys.prefix, 'etc', confFileName))
for fname in confFile:
try:
self.read(fname)
except (ConfigParser.MissingSectionHeaderError,
ConfigParser.ParsingError), e:
_aux_logger.warn('Troubles reading config file: %s' % e)
# Stop at the first valid file.
if self.has_section('imdbpy'):
break
def main():
description = ("Output an LZW compressed binary file and JSON dict"
"containing the keycodes for decompression, or decompress a"
"previously LZW compressed file.")
parser = argparse.ArgumentParser(description=description)
subparsers = parser.add_subparsers()
parser_comp = subparsers.add_parser("compress")
parser_comp.add_argument("--infile", nargs="?",
type=argparse.FileType("r"), default=sys.stdin)
parser_comp.add_argument("--outfile", nargs="?",
type=argparse.FileType("wb"),
default=os.path.join(os.getcwd(), "output.bin"))
parser_comp.add_argument("--keycode-file", nargs="?",
type=argparse.FileType("w"),
default=os.path.join(os.getcwd(), "keycodes.json"))
parser_comp.set_defaults(func=parse_for_compress)
parser_decomp = subparsers.add_parser("decompress")
parser_decomp.add_argument("--infile", nargs="?",
type=argparse.FileType("rb"),
default=os.path.join(os.getcwd(), "output.bin"))
parser_decomp.add_argument("--keycode-file", nargs="?",
type=argparse.FileType("r"),
default=os.path.join(os.getcwd(), "keycodes.json"))
parser_decomp.add_argument("--outfile", nargs="?",
type=argparse.FileType("w"), default=sys.stdout)
parser_decomp.set_defaults(func=parse_for_decompress)
args = parser.parse_args()
args.func(args)
args.infile.close()
args.outfile.close()
args.keycode_file.close()
def load_XRF_data(self):
file = '%s/XRF_Training_Set.xlsx'%os.getcwd()
wb = xlrd.open_workbook(filename = 'XRF_Training_Set.xlsx')
sh = wb.sheet_by_index(0)
row_index = 1
while True:
try:
XRF_data_list = []
column_index = 1
while True:
try:
XRF_data_list.append(sh.cell_value(row_index, column_index))
column_index += 1
except:
break
with open('%s/controlData_AVG_Files/%s Ref Data/XRF_%s.json'%(os.getcwd(), sh.cell_value(row_index, 0), sh.cell_value(row_index, 0)), 'w') as j:
j.write(json.dumps(XRF_data_list, sort_keys=True, indent=4, separators=(',', ': ')))
with open('%s/controlData_AVG_Files/%s Ref Data/XRF_%s.csv'%(os.getcwd(), sh.cell_value(row_index, 0), sh.cell_value(row_index, 0)), 'w') as c:
writer = csv.writer(c)
writer.writerow(XRF_data_list)
row_index += 1
self.XRF_listLength = len(XRF_data_list)
except:
break
def display_path(path):
"""Gives the display value for a given path, making it relative to cwd
if possible."""
path = os.path.normcase(os.path.abspath(path))
if path.startswith(os.getcwd() + os.path.sep):
path = '.' + path[len(os.getcwd()):]
return path
def _quick_savefile(self, PTYPE=IMAGE_EXT):
'''Save the current display via PyArt interface.'''
imagename = self.display.generate_filename(
self.Vfield.value, self.Vtilt.value, ext=IMAGE_EXT)
self.canvas.print_figure(os.path.join(os.getcwd(), imagename), dpi=DPI)
self.statusbar.showMessage(
'Saved to %s' % os.path.join(os.getcwd(), imagename))
def OnButton_textUserButton(self, evt):
'''txt 用户数据库处理'''
wildcard = "txt (*.txt)|*.txt"
try:
Dir=unicode(os.getcwd(), self.textencoding)
except:
Dir=os.getcwd()
#这里的style不能选 wx.CHANGE_DIR，更改后，会引起脚本执行目录的变化
dlg = wx.FileDialog(
self,
message="Choose a txt file",
defaultDir=Dir,
defaultFile="",
wildcard=wildcard,
style=wx.OPEN
)
if dlg.ShowModal() == wx.ID_OK:
path = dlg.GetPath()
self.mainStatusBar.SetLabel(path)
self.userControlPanelString=path
dlg.Destroy()
self.users=txtUserControl(self.userControlPanelString)
if self.users.userDataInit()== userControlErrValue["OK"]:
self.Config.setContrlMedia("txt")
self.Config.setControlMediaPath(self.userControlPanelString)
self.Config.saveServerConfig()
else:
uiDebug("serverManager userDataInit error")
uiDebug("OnButton_textUserButton()")
def OnButton_xmlUserButton(self, evt):
'''xml 用户数据库处理'''
wildcard = "xml (*.xml)|*.xml"
try:
Dir=unicode(os.getcwd(), self.textencoding)
except:
Dir=os.getcwd()
dlg = wx.FileDialog(
self, message="Choose a xml file",
defaultDir=Dir,
defaultFile="",
wildcard=wildcard,
style=wx.OPEN
)
if dlg.ShowModal() == wx.ID_OK:
path = dlg.GetPath()
self.mainStatusBar.SetLabel(path)
self.userControlPanelString=path
dlg.Destroy()
self.users=xmlUserControl(self.userControlPanelString)
if self.users.userDataInit()== userControlErrValue["OK"]:
self.Config.setContrlMedia("xml")
self.Config.setControlMediaPath(self.userControlPanelString)
self.Config.saveServerConfig()
else:
uiDebug("serverManager userDataInit error")
uiDebug("serverManager OnButton_xmlUserButton()")
def _call_avrdude(args):
if utils.is_windows():
avr_exe_path = os.path.join(pm.RES_PATH, 'avrdude.exe')
avr_config_path = os.path.join(pm.RES_PATH, 'avrdude.conf')
elif utils.is_mac():
avr_exe_path = os.path.join(pm.RES_PATH, 'avrdude')
avr_config_path = os.path.join(pm.RES_PATH, 'avrdude.conf')
elif utils.is_linux():
avr_exe_path = os.path.join(pm.RES_PATH, 'avrdude64' if utils.is64bits() else "avrdude")
avr_config_path = os.path.join(pm.RES_PATH, 'avrdude.conf' if utils.is64bits() else "avrdude32.conf")
else:
raise Exception("Platform not supported")
os.chmod(avr_exe_path, int("755", 8)) # force to have executable rights in avrdude
avr_exe_path = os.path.normpath(os.path.relpath(avr_exe_path, os.getcwd()))
avr_config_path = os.path.normpath(os.path.relpath(avr_config_path, os.getcwd()))
cmd = [avr_exe_path] + ["-C"] + [avr_config_path] + args.split(" ")
log.debug("Command executed: {}".format(cmd))
p = subprocess.Popen(cmd, shell=utils.is_windows(), stdin=subprocess.PIPE, stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
close_fds=(not utils.is_windows()))
output = p.stdout.read()
err = p.stderr.read()
log.debug(output)
log.debug(err)
return output, err
def plot_graphs(self,path,count):
'''Save graphs'''
Gs=nx.to_agraph(self.gS)
Gm=nx.to_agraph(self.gM)
Gs_w=nx.to_agraph(self.gS_w)
#add color to main nodes
for node in self.gM.nodes():
n=Gs.get_node(node)
n.attr['shape']='box'
n.attr['style']='filled'
n.attr['fillcolor']='turquoise'
#add weight to edges
for edge in self.gS_w.edges(data=True):
ed=Gs_w.get_edge(edge[0],edge[1])
ed.attr['label']=edge[2]['weight']
loc= os.getcwd()+path+'/spanning/gS' + str(count)+'.png'
loc1= os.getcwd()+path+'/projection/gM' + str(count)+'.png'
loc2= os.getcwd()+path+'/spanning_w/gS_w' + str(count)+'.png'
Gs.layout(prog='dot') # use dot
Gm.layout(prog='dot') # use dot
Gs_w.layout(prog='dot')
Gs.draw(loc)
Gm.draw(loc1)
Gs_w.draw(loc2)
return
def test_absolute_paths(self):
from certbot.configuration import NamespaceConfig
config_base = "foo"
work_base = "bar"
logs_base = "baz"
server = "mock.server"
mock_namespace = mock.MagicMock(spec=['config_dir', 'work_dir',
'logs_dir', 'http01_port',
'tls_sni_01_port',
'domains', 'server'])
mock_namespace.config_dir = config_base
mock_namespace.work_dir = work_base
mock_namespace.logs_dir = logs_base
mock_namespace.server = server
config = NamespaceConfig(mock_namespace)
self.assertTrue(os.path.isabs(config.config_dir))
self.assertEqual(config.config_dir,
os.path.join(os.getcwd(), config_base))
self.assertTrue(os.path.isabs(config.work_dir))
self.assertEqual(config.work_dir,
os.path.join(os.getcwd(), work_base))
self.assertTrue(os.path.isabs(config.logs_dir))
self.assertEqual(config.logs_dir,
os.path.join(os.getcwd(), logs_base))
self.assertTrue(os.path.isabs(config.accounts_dir))
self.assertTrue(os.path.isabs(config.backup_dir))
self.assertTrue(os.path.isabs(config.csr_dir))
self.assertTrue(os.path.isabs(config.in_progress_dir))
self.assertTrue(os.path.isabs(config.key_dir))
self.assertTrue(os.path.isabs(config.temp_checkpoint_dir))
def parse_args():
parser = argparse.ArgumentParser(description='Train a Region Proposal Network')
parser.add_argument('--image_set', dest='image_set', help='can be trainval or train',
default='trainval', type=str)
parser.add_argument('--year', dest='year', help='can be 2007, 2010, 2012',
default='2007', type=str)
parser.add_argument('--root_path', dest='root_path', help='output data folder',
default=os.path.join(os.getcwd(), 'data'), type=str)
parser.add_argument('--devkit_path', dest='devkit_path', help='VOCdevkit path',
default=os.path.join(os.getcwd(), 'data', 'VOCdevkit'), type=str)
parser.add_argument('--pretrained', dest='pretrained', help='pretrained model prefix',
default=os.path.join(os.getcwd(), 'model', 'vgg16'), type=str)
parser.add_argument('--epoch', dest='epoch', help='epoch of pretrained model',
default=1, type=int)
parser.add_argument('--prefix', dest='prefix', help='new model prefix',
default=os.path.join(os.getcwd(), 'model', 'rpn'), type=str)
parser.add_argument('--gpus', dest='gpu_ids', help='GPU device to train with',
default='0', type=str)
parser.add_argument('--begin_epoch', dest='begin_epoch', help='begin epoch of training',
default=0, type=int)
parser.add_argument('--end_epoch', dest='end_epoch', help='end epoch of training',
default=8, type=int)
parser.add_argument('--frequent', dest='frequent', help='frequency of logging',
default=20, type=int)
parser.add_argument('--kv_store', dest='kv_store', help='the kv-store type',
default='device', type=str)
parser.add_argument('--work_load_list', dest='work_load_list', help='work load for different devices',
default=None, type=list)
parser.add_argument('--finetune', dest='finetune', help='second round finetune', action='store_true')
parser.add_argument('--resume', dest='resume', help='continue training', action='store_true')
args = parser.parse_args()
return args
def render_all(template_path=None, output_path=None, static_path=None):
if not template_path:
template_path = 'lae_site/templates/'
if not output_path:
output_path = 'lae_rendered/'
if not static_path:
static_path = 'content/static/'
env = Environment(loader=MyLoader(template_path))
# find all the files inside all the subdirectories of the template path
all_the_things = os.walk(template_path)
for root, dirs, files in all_the_things:
for f in files:
# check that it's a template file
if f[-5:] == '.html' and f[:1] != '_':
full_path = root + '/' + f
# path relative to template_path
relative_path = full_path[len(template_path) + 1:]
print "Rendering " + relative_path
# render the template
template = env.get_template(relative_path)
# calculate directory output should go in
dirname = os.path.dirname(output_path + '/' + relative_path)
# and if it doesn't exist yet, create it
if not os.path.exists(dirname):
os.makedirs(dirname)
# make rendered html file
with codecs.open(output_path + '/' + relative_path, 'w', 'utf-8') as render_file:
for line in template.render():
render_file.write(line)
if not os.path.isdir(output_path + 'static'):
subprocess.check_call(['ln', '-s', '../' + static_path, 'static'], cwd=os.getcwd() + '/' + output_path)
print "Made symlink to static files."
subprocess.check_call(['python', '-m', 'SimpleHTTPServer', '8002'], cwd=os.getcwd() + '/' + output_path)
'''
Everything the code does operates through an instance of the Flask class. We followed this format for our own packages,
which perfrom all their operations on their respective objects and are linked to the database file, rather than having all
functions live in the same app file. app.py just talks to fucntions in other objects and links the results
together with the HTML and CSS.
'''
# This stores the page names and links for our navigation bar.
page_link_dict = {
"Home": "/home/",
"About": "/about/",
"Weather": "/weather/",
"Polls": "/polls/",
}
my_path = os.getcwd().replace('\\', '/') + "/static/audio"
songs = [i.replace(my_path + "\\", "") for i in glob.glob(my_path + "/*.mp3")]
'''
Flask uses decorators, a special Python tool for linking functions together, in order to redirect requests to our custom
server code. "Endpoints" (app.route) are the paths that tell the server what the client wants and thus, what function to
run. A client will specify where on the site they want to go, and if that endpoint is assigned to a function, that
function will tell Flask what information to render back to the client.
'''
def log_user_entrance(user):
with open("User-Logs.txt", "a+") as file:
file.write(f"User: {user}\tTime: {datetime.now()}\n")
@app.route("/")
"../../../../../../..", "../../../../../../../..", "../../../../../../../../.." ]
head = os.path.dirname(sys.argv[0])
if len(head) > 0:
path = [os.path.join(head, p) for p in path]
path = [os.path.abspath(p) for p in path if os.path.exists(os.path.join(p, "scripts", "TestUtil.py")) ]
if len(path) == 0:
raise RuntimeError("can't find toplevel directory!")
sys.path.append(os.path.join(path[0], "scripts"))
import TestUtil
router = os.path.join(TestUtil.getCppBinDir(), "glacier2router")
#
# Generate the crypt passwords file
#
TestUtil.hashPasswords(os.path.join(os.getcwd(), "passwords"), {"userid": "abc123"})
args = ' --Ice.Warn.Dispatch=0' + \
' --Ice.Warn.Connections=0' + \
' --Glacier2.Filter.Category.Accept="c1 c2"' + \
' --Glacier2.Filter.Category.AcceptUser="******"' + \
' --Glacier2.SessionTimeout="30"' + \
' --Glacier2.Client.Endpoints="default -p 12347"' + \
' --Glacier2.Server.Endpoints="tcp -h 127.0.0.1"' \
' --Ice.Admin.Endpoints="tcp -h 127.0.0.1 -p 12348"' + \
' --Ice.Admin.InstanceName=Glacier2' + \
' --Glacier2.CryptPasswords="' + os.path.join(os.getcwd(), "passwords") + '"'
sys.stdout.write("starting router... ")
sys.stdout.flush()
routerConfig = TestUtil.DriverConfig("server")
num_classes = 2
################################################################################
# HYPERPARAMETERS AND DESIGN CHOICES
num_neurons = 128
batch_size = 64
ACTIV_FN = "relu"
activation_fn = cnn.get_activ_fn(ACTIV_FN)
num_epochs = 50
learn_rate = 0.001
drop_prob = 0.1
optim = "Adam"
# callbacks for Save weights, Tensorboard
# creating a new directory for each run using timestamp
folder = os.path.join(os.getcwd(),
datetime.now().strftime("%d-%m-%Y_%H-%M-%S"),
str(ACTIV_FN))
tb_callback = TensorBoard(log_dir=folder)
# Build, train, and test model
model = cnn.build_model(input_shape, activation_fn, learn_rate, drop_prob,
num_neurons, num_classes)
train_accuracy, train_loss, valid_accuracy, valid_loss = cnn.train_model(
model, train_images, train_labels, batch_size, num_epochs, valid_images,
valid_labels, tb_callback)
test_accuracy, test_loss, predictions = cnn.test_model(model, test_images,
test_labels)
#
# # save test set results to csv
# predictions = np.round(predictions)
# -------------
#%% User Edits
# -------------
# Indicate machine to set path
machine='pdwang'
# Set directory and load data depending on machine
if machine == 'local-glenn':
os.chdir('/Users/gliu/Downloads/2020_Fall/6.862/Project/predict_amv/')
outpath = '/Users/gliu/Downloads/2020_Fall/6.862/Project'
sst_normed = np.load('../CESM_data/CESM_SST_normalized_lat_weighted.npy').astype(np.float32)
sss_normed = np.load('../CESM_data/CESM_SSS_normalized_lat_weighted.npy').astype(np.float32)
psl_normed = np.load('../CESM_data/CESM_PSL_normalized_lat_weighted.npy').astype(np.float32)
else:
outpath = os.getcwd()
sst_normed = np.load('../../CESM_data/CESM_sst_normalized_lat_weighted_2deg_NAT_Ann.npy').astype(np.float32)
sss_normed = np.load('../../CESM_data/CESM_sss_normalized_lat_weighted_2deg_NAT_Ann.npy').astype(np.float32)
psl_normed = np.load('../../CESM_data/CESM_psl_normalized_lat_weighted_2deg_NAT_Ann.npy').astype(np.float32)
# Data preparation settings
#tunits = 'year' # Indicate units of time ('month' or 'year)
leads = np.arange(0,25,1) # Time ahead (in tunits) to forecast AMV
tstep = 1032 # Total number of time units
percent_train = 0.8 # Percentage of data to use for training (remaining for testing)
ens = 40 # Ensemble members to use
# Select variable
Forked from cluster.py to cluster_mem.py
to load dev data in memory and try other
methods (DBSCAN). Do I need to load the
entire dataset into memory?
"""
import argparse
import matplotlib.pyplot as plt
import numpy as np
import os
import pandas as pd
import sys
import wandb
PROJECT_DIR = os.path.abspath(os.path.join(os.getcwd(), '../'))
print(PROJECT_DIR)
sys.path.append(PROJECT_DIR)
from project_core.models import model_factory, LinearModel
from project_core.utils import load_image, build_files_dataframe, prune_file_list
from sklearn.cluster import MiniBatchKMeans, DBSCAN
from sklearn.metrics import (adjusted_rand_score, balanced_accuracy_score,
normalized_mutual_info_score)
from sklearn.preprocessing import LabelEncoder, MinMaxScaler, StandardScaler
from tensorflow.keras import Model
from tensorflow.keras.optimizers import Adam
from tensorflow.keras.preprocessing.image import ImageDataGenerator
def main(args):
def select_class_file(self):
options = QFileDialog.Options()
options |= QFileDialog.DontUseNativeDialog
fileName, _ = QFileDialog.getOpenFileName(self,"QFileDialog.getOpenFileName()", os.getcwd(),
"Text Files (*.txt);;All Files (*)",
options=options)
self.system["class_file"] = fileName;
self.tb5.setText(fileName);
self.system["model"] = self.cb1.currentText();
self.system["use_gpu"] = self.cb3.currentText();
self.system["conf_thresh"] = self.e4.text();
self.system["img_short_side"] = self.e6.text();
self.system["img_long_side"] = self.e7.text();
self.system["mean"] = self.e8.text();
self.system["std"] = self.e9.text();
with open('obj_3_mxrcnn_infer.json', 'w') as outfile:
json.dump(self.system, outfile)
import os
from requests import get # to make GET request
import urllib, tarfile
def download(url, file_name):
# open in binary mode
with open(file_name, "wb") as file:
# get request
response = get(url)
# write to file
file.write(response.content)
path_cwd = os.getcwd()
path = path_cwd+"/extra_data/body_module"
try:
os.makedirs(path)
except OSError:
print ("Creation of the directory %s failed" % path)
os.chdir(path)
else:
print ("Successfully created the directory %s " % path)
os.chdir(path)
url = "http://visiondata.cis.upenn.edu/spin/data.tar.gz"
filename = 'data.tar.gz'
print ('Downloading: '+filename)
download(url,filename)
tf = tarfile.open(filename)
tf.extractall()
def write_2chan_franalyzeFile(xytab,frTrials_dico,ratio,shuffled,nbTrials,filename,simuTime,seed,pathToFile=os.getcwd(), model=None,rezero=False,reversedChans=False) :
print "------------- Saving data -----------"
# retrieving the string for the xytab values
xytext = ";".join(map(str,xytab))
# first writting the model and the antag
textToWrite = "#%d\nratio=%.3f\nseed=%d\nSimuDuration=%s\nshuffled=%s\nNbTrials=%d\nReZero=%s\nReversedChannels=%s\n\n%s\n\n" % (model,ratio,seed,simuTime,shuffled,nbTrials,rezero,reversedChans,xytext)
directory = os.path.join(pathToFile,"data/files/")
# writing every trails for each (x.y) tuple
for keys,values in frTrials_dico.items() :
keyTxt = str(keys[0]) + ";" + str(keys[1]) + ";"
valTxt = ";".join(map(lambda x: str(x[0])+","+str(x[1])+","+str(x[2])+","+x[3],values)) # values is a list of (3 int and a str) tuples
textToWrite += keyTxt + valTxt + "\n"
try :
with open(os.path.join(directory,filename),"w") as outFile :
outFile.write(textToWrite)
except IOError as e:
os.system("mkdir -p %s" % directory)
with open(os.path.join(directory,filename),"w") as outFile :
outFile.write(textToWrite)
print "\tData saved in %s file in %s directory" % (filename,directory)
def main():
"""Run when running this module as the primary one."""
EVALUATION_SCALES = [1.0] # must be all floats!
parser = argparse.ArgumentParser()
parser.add_argument('-m', '--model', type=str, default='pspnet50_ade20k',
help='Model/Weights to use',
choices=['pspnet50_ade20k',
'pspnet101_cityscapes',
'pspnet101_voc2012'])
parser.add_argument('-i', '--input_path', type=str, default='../example_images',
help='Path to the input images')
parser.add_argument('-o', '--output_path', type=str, default='../example_results',
help='Path to output')
parser.add_argument('-g', '--groundtruth_path', type=str, default='../example_groundtruth',
help='Path to groundtruth')
parser.add_argument('--id', default="0")
parser.add_argument('-s', '--sliding', action='store_true',
help="Whether the network should be slided over the original image for prediction.")
parser.add_argument('-f', '--flip', action='store_true',
help="Whether the network should predict on both image and flipped image.")
parser.add_argument('-ms', '--multi_scale', action='store_true',
help="Whether the network should predict on multiple scales.")
parser.add_argument('-hm', '--heat_maps', action='store_true',
help="Whether the network should diplay heatmaps.")
parser.add_argument('-v', '--vis', action='store_false',
help="Whether an interactive plot should be diplayed.")
parser.add_argument('-cci', '--complete_coarse_image', action='store_true',
help="Whether a coarse imae should be completed with predictions.")
parser.add_argument('-e', '--evaluate', action='store_true',
help="Whether an evaluation against groundtruth should be attempted.")
args = parser.parse_args()
environ["CUDA_VISIBLE_DEVICES"] = args.id
sess = tf.Session()
K.set_session(sess)
with sess.as_default():
print(args)
import os
cwd = os.getcwd()
print("Running in %s" % cwd)
image_paths = []
if isfile(args.input_path):
image_paths.append(args.input_path)
elif isdir(args.input_path):
file_types = ('png', 'jpg')
for file_type in file_types:
image_paths.extend(glob.glob(join(args.input_path + '/**/*.' + file_type), recursive=True))
image_paths = sorted(image_paths)
# print(image_paths)
if "pspnet50" in args.model:
pspnet = PSPNet50(nb_classes=150, input_shape=(473, 473),
weights=args.model)
if "ade20k" in args.model:
from ade20k_labels import id2label, name2label
elif "pspnet101" in args.model:
if "cityscapes" in args.model:
pspnet = PSPNet101(nb_classes=19, input_shape=(713, 713),
weights=args.model)
from cityscapes_labels import id2label, name2label
if "voc2012" in args.model:
pspnet = PSPNet101(nb_classes=21, input_shape=(473, 473),
weights=args.model)
from pascal_voc_labels import id2label, name2label
else:
print("Network architecture not implemented.")
if args.multi_scale:
EVALUATION_SCALES = [0.5, 0.75, 1.0, 1.25, 1.5, 1.75] # original implementation, must be all floats!
for image_path in image_paths:
image_name, ext = splitext(os.path.basename(image_path))
image_name = image_name.replace('_leftImg8bit', '') # strip leftImg8bit tag for gt matching and producting groundtruth
print("Predicting image name: %s" % (image_name + ext))
img = misc.imread(image_path)
class_scores = predict_multi_scale(img, pspnet, EVALUATION_SCALES, args.sliding, args.flip)
if args.heat_maps:
# show_class_heatmap(class_scores, 'person')
show_class_heatmaps(class_scores)
# visualize_prediction(img, class_scores, id2label)
class_image = np.argmax(class_scores, axis=2)
output_path, _ = splitext(args.output_path)
if not os.path.exists(output_path):
os.makedirs(output_path)
output_path = join(output_path, image_name)
print("Writing results to %s" % (output_path + ext))
confidence_map = np.max(class_scores, axis=2) # probability of the most likely class, a vage measure of the networks confidence
colored_class_image = color_class_image(class_image, id2label)
# colored_class_image is [0.0-1.0] img is [0-255]
alpha_blended = 0.5 * colored_class_image + 0.5 * img
if "cityscapes" in args.model:
class_image = trainid_to_class_image(class_image)
misc.imsave(output_path + "_gtFine_labelIds" + ext, class_image)
misc.imsave(output_path + "_seg" + ext, colored_class_image)
misc.imsave(output_path + "_probs" + ext, confidence_map)
misc.imsave(output_path + "_seg_blended" + ext, alpha_blended)
gt_path = find_matching_gt(args.groundtruth_path, image_name, args.model, verbose=True)
if gt_path is not None:
if args.complete_coarse_image: # only for cityscapes
try:
coarse_image = misc.imread(gt_path)
class_image = complete_coarse_image(coarse_image, class_image)
misc.imsave(output_path + "_gtFine_labelIds" + ext, class_image)
except AttributeError as err:
print("Warning: Could not read groundtruth: %s" % err)
if args.evaluate:
if "cityscapes" in args.model:
evaluate_iou([class_image], [misc.imread(gt_path)], classes=35)
else:
# gt_image to class image
gt_image = misc.imread(gt_path)
gt_class_image = gt_image_to_class_image(gt_image, id2label)
evaluate_iou([class_image], [gt_class_image], classes=pspnet.nb_classes)
else:
print("Could not find groundtruth for %s" % image_name)
import os
import random
import unittest
from MyFunction import Search_Website, Login_Admin
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.support.ui import Select
from selenium.webdriver.common.by import By
from selenium.webdriver.support.wait import WebDriverWait
from selenium.webdriver.common.action_chains import ActionChains
import pytest
import allure
current_url = os.getcwd()
screenshot_folder = current_url+'/images'
if not os.path.exists(screenshot_folder):
os.mkdir(screenshot_folder)
admin_images = current_url+'/images/Admin'
if not os.path.exists(admin_images):
os.mkdir(admin_images)
class TestAdmin(unittest.TestCase):
def setUp(self):
self.driver = webdriver.Chrome(current_url+'/chromedriver.exe')
self.start_url = "https://admin.myreales.tk/login"
self.driver.maximize_window()
#!/usr/bin/env python3
from __future__ import unicode_literals, absolute_import, print_function, division
import sys, re, time, traceback
import socket, asyncore, asynchat, ssl, select
import os, codecs
import errno
import tools
IRC_CODES = ('001', '354', '002', '003', '004', '005', '253', '251', '252',
'254', '255', '265', '266', '250', '315', '328', '333', '352',
'353', '354', '366', '372', '375', '376', 'QUIT', 'NICK', 'JOIN')
cwd = os.getcwd()
class Origin(object):
source = re.compile(r'([^!]*)!?([^@]*)@?(.*)')
def __init__(self, bot, source, args):
match = Origin.source.match(source or '')
self.nick, self.user, self.host = match.groups()
target = mode = mode_target = names = other = other2 = other4 = rest = other5 = other6 = None
arg_len = len(args)
if arg_len > 1:
target = args[1]
if arg_len > 2:
mode = args[2]
if arg_len > 3:
mode_target = args[3]
if arg_len > 4:
def write_2chan_chanChoicefile(xytab,trials_dico,ratio,shuffled,filename,simuTime,pathToFile=os.getcwd(),model=0) :
print "------------- Saving data -----------"
# retrieving the string for the xytab values
xytext = ";".join(map(str,xytab))
# first writting the model and the antag
textToWrite = "#%d\nratio=%.3f\nSimuDuration=%s\nshuffled=%s\n%s\n\n" % (model,ratio,simuTime,shuffled,xytext)
directory = os.path.join(pathToFile,"data/files/")
# writing every trails for each (x.y) tuple
for keys,values in trials_dico.items() :
keyTxt = str(keys[0]) + ";" + str(keys[1]) + ";"
valTxt = ";".join(values) # values is already a list of string ["1","2","0","3"...]
textToWrite += keyTxt + valTxt + "\n"
try :
with open(os.path.join(directory,filename),"w") as outFile :
outFile.write(textToWrite)
except IOError as e:
os.system("mkdir -p %s" % directory)
with open(os.path.join(directory,filename),"w") as outFile :
outFile.write(textToWrite)
print "\tData saved in %s file in %s directory" % (filename,directory)
import json
import os
f = open('city.list.json', 'r')
saveFileName = 'sorted_CN_city.txt'
dic = {}
for line in f:
if '"CN"' in line:
j = json.loads(line)
key = j["name"]
dic[key] = line
dict = sorted(dic.iteritems(), key=lambda d: d[0])
for fileName in os.listdir(os.getcwd()):
if fileName == saveFileName:
os.remove(fileName)
g = open(saveFileName, 'w')
for item in dict:
g.write(item[1])
g.close()
f.close()
import os import sys sys.path.extend([os.path.dirname(os.getcwd())]) from torch.utils.data import DataLoader from torchvision import transforms from Jizong_code import medicalDataLoader from Jizong_code.network import UNet, SegNet from Jizong_code.enet import Enet import numpy as np, matplotlib.pyplot as plt from Jizong_code.criterion import CrossEntropyLoss2d, partialCrossEntropyLoss2d, logBarrierLoss, dice_loss import pandas as pd, torch, torch.nn as nn, torch.nn.functional as F from tqdm import tqdm from torchnet.meter import AverageValueMeter from Jizong_code.utils import pred2segmentation, dice_loss, Colorize from Jizong_code.visualize import Dashboard board_train_image = Dashboard(server='http://turing.livia.etsmtl.ca', env="train_image") board_val_image = Dashboard(server='http://turing.livia.etsmtl.ca', env="vali_image") board_loss = Dashboard(server='http://turing.livia.etsmtl.ca', env="loss") cuda_device = "0" batch_size = 1 batch_size_val = 1 num_workers = 0 lr = 0.0002 max_epoch = 100 root_dir = '../ACDC-2D-All' model_dir = 'model' os.environ["CUDA_VISIBLE_DEVICES"] = cuda_device
-------------------------------- ''' # Import the required python modules import arcpy import os import sys import re ############################ VARIABLES #################################### # Data base connection to ArcGIS Server containing floor maps for buildings database_conn = "ehsprod2.ehs.unr.edu.sde" # The current building to process buildings = ["sde.BUILDING.ansari_business_building"] ############################ CONSTANTS #################################### # Output location to create the intermediate files and output protobuffer files current_working_dir = os.getcwd() outputPath = current_working_dir + os.sep + "\Output" # The output projected co-ordinate system outSpatialReference = "NAD 1983 UTM Zone 11N" # Features from building dataset to process features = ["rooms", "doors"] # The maximum distance that will be used to combine adjecent features for navigable space aggregationDist = "4 Feet" # Query used to find open spaces rooms_query = "(UPPER([ROOM_TYPE]) LIKE '%CORRIDOR%' OR UPPER([ROOM_TYPE]) LIKE '%VESTIBULE%' OR UPPER([ROOM_TYPE]) LIKE '%LOBBY%')" # Query used to find the elevators and stairs on a floor stairs_query = "(UPPER([ROOM_TYPE]) LIKE '%ELEVATOR%' OR UPPER([ROOM_TYPE]) LIKE '%STAIRS%')" # set arcpy environment variable for overwriting database outputs arcpy.env.overwriteOutput = True #############################################################################
# visualize
import matplotlib.pyplot as plt
import matplotlib.style as style
import seaborn as sns
from matplotlib import pyplot
from matplotlib.ticker import ScalarFormatter
sns.set_context("talk")
style.use('seaborn-colorblind')
# custom
from lgb_param_models import lgb_model
from xgb_param_models import xgb_model
from catb_param_models import catb_model
from lin_param_models import lin_model
from nn_param_models import nn_model
mypath = os.getcwd()
sys.path.append(mypath + '/code/')
from train_helper import get_oof_ypred
from cv_methods import GroupKFold, StratifiedGroupKFold
class RunModel(object):
"""
Model Fitting and Prediction Class:
:INPUTS:
:train_df: train pandas dataframe
:test_df: test pandas dataframe
:target: target column name (str)
:features: list of feature names
:categoricals: list of categorical feature names. Note that categoricals need to be in 'features'
import os
import glob
from tqdm import tqdm
import pandas as pd
from joblib import Parallel, delayed
num_loc = 3
PWD = os.getcwd()
csvs = glob.glob('./csv/*/*')
def raster(category):
df = pd.read_csv(category, index_col=0)
csv_num = int(len(df)/num_loc)
bar = tqdm(desc = str(category), total = csv_num, leave = False)
for i in range(csv_num):
for j in range(num_loc-1): ##bubble sort
for k in range(num_loc-1, j, -1):
if df.loc[num_loc*i+k-1, 'y']>df.loc[num_loc*i+k, 'y']:
temp_x = df.loc[num_loc*i+k-1, 'x']
temp_y = df.loc[num_loc*i+k-1, 'y']
df.loc[num_loc*i+k-1, 'x'] = df.loc[num_loc*i+k, 'x']
df.loc[num_loc*i+k-1, 'y'] = df.loc[num_loc*i+k, 'y']
df.loc[num_loc*i+k, 'x'] = temp_x
df.loc[num_loc*i+k, 'y'] = temp_y
elif df.loc[num_loc*i+k-1, 'y']==df.loc[num_loc*i+k, 'y']:
t.cell(0, 2).paragraphs[0].clear() # 清楚原‘姓名’字符串，
t.cell(0, 2).paragraphs[0].add_run(c) # 替换为‘编号’
# 定义自动创建文件夹的函数
def make_folder(p):
if os.path.exists(p): # 判断文件夹是否存在
shutil.rmtree(p) # 如果存在删除原有目录的文件夹以及其中所有文件
os.mkdir(p)
if __name__ == '__main__':
# 定义全局变量c,a分别存放‘序号’字符串和
c = '序号'
a = 1
file_path = os.getcwd() # 获取当前py文件的路径
local_path = file_path + '/tihuanmingzi'
make_folder(local_path)
# 遍历当前路径的所有.doc文件
for file_name in glob.glob(os.path.join(file_path, '*.docx')):
file = docx.Document(file_name)
tables = file.tables # 读取所有表格
name = {} # 定义字典储存姓名编号
# 遍历所有表，迭代得出每一张表
for i in range(len(tables)):
t = tables[i] # 将每一张表传递给参数t
if t.cell(0, 0).text == '编号': # 查找目标表
if t.cell(0, 3).text + t.cell(
0, 1).text not in name: # 判断是否已经收录了个人信息
p = Process(target=replace_name_and_count(
t)) # Process 对象只是一个子任务，运行该任务时系统会自动创建一个子进程
# оформленные в виде соответствующих функций,
# и импортированные в данный файл из easy.py
import os, shutil
import easy
while True:
print('1. Перейти в папку')
print('2. Просмотреть содержимое текущей папки')
print('3. Удалить папку')
print('4. Создать папку')
print('5. Выход')
command = input('>>> ')
if command == '5':
break
if command == '2':
print('Текущая папка: ', os.getcwd())
list = easy.view_dir()
if command == '1':
new_dir = input('Введите имя директории: ')
if new_dir == '/':
a = os.getcwd().split('\\')[:-1]
new_dir = '\\'.join(i for i in os.getcwd().split('\\')[:-1])
try:
os.chdir(new_dir)
print('переход осуществлен')
print('Текущая папка: ', os.getcwd())
except FileNotFoundError:
print('переход невозможен - неверный адрес')
def main(argv):
parser = ArgumentParser(usage=__doc__.lstrip())
parser.add_argument("--verbose",
"-v",
action="count",
default=1,
help="more verbosity")
parser.add_argument(
"--no-build",
"-n",
action="store_true",
default=False,
help="do not build the project (use system installed version)")
parser.add_argument("--build-only",
"-b",
action="store_true",
default=False,
help="just build, do not run any tests")
parser.add_argument("--doctests",
action="store_true",
default=False,
help="Run doctests in module")
parser.add_argument(
"--coverage",
action="store_true",
default=False,
help=("report coverage of project code. HTML output goes "
"under build/coverage"))
parser.add_argument(
"--gcov",
action="store_true",
default=False,
help=("enable C code coverage via gcov (requires GCC). "
"gcov output goes to build/**/*.gc*"))
parser.add_argument("--lcov-html",
action="store_true",
default=False,
help=("produce HTML for C code coverage information "
"from a previous run with --gcov. "
"HTML output goes to build/lcov/"))
parser.add_argument("--mode",
"-m",
default="fast",
help="'fast', 'full', or something that could be "
"passed to nosetests -A [default: fast]")
parser.add_argument(
"--submodule",
"-s",
default=None,
help="Submodule whose tests to run (cluster, constants, ...)")
parser.add_argument("--pythonpath",
"-p",
default=None,
help="Paths to prepend to PYTHONPATH")
parser.add_argument("--tests",
"-t",
action='append',
help="Specify tests to run")
parser.add_argument("--python",
action="store_true",
help="Start a Python shell with PYTHONPATH set")
parser.add_argument("--ipython",
"-i",
action="store_true",
help="Start IPython shell with PYTHONPATH set")
parser.add_argument("--shell",
action="store_true",
help="Start Unix shell with PYTHONPATH set")
parser.add_argument("--debug",
"-g",
action="store_true",
help="Debug build")
parser.add_argument("--show-build-log",
action="store_true",
help="Show build output rather than using a log file")
parser.add_argument("--bench",
action="store_true",
help="Run benchmark suite instead of test suite")
parser.add_argument("args",
metavar="ARGS",
default=[],
nargs=REMAINDER,
help="Arguments to pass to Nose, Python or shell")
args = parser.parse_args(argv)
if args.lcov_html:
# generate C code coverage output
lcov_generate()
sys.exit(0)
if args.pythonpath:
for p in reversed(args.pythonpath.split(os.pathsep)):
sys.path.insert(0, p)
if args.gcov:
gcov_reset_counters()
if not args.no_build:
site_dir = build_project(args)
sys.path.insert(0, site_dir)
os.environ['PYTHONPATH'] = site_dir
extra_argv = args.args[:]
if extra_argv and extra_argv[0] == '--':
extra_argv = extra_argv[1:]
if args.python:
if extra_argv:
# Don't use subprocess, since we don't want to include the
# current path in PYTHONPATH.
sys.argv = extra_argv
with open(extra_argv[0], 'r') as f:
script = f.read()
sys.modules['__main__'] = imp.new_module('__main__')
ns = dict(__name__='__main__', __file__=extra_argv[0])
exec_(script, ns)
sys.exit(0)
else:
import code
code.interact()
sys.exit(0)
if args.ipython:
import IPython
IPython.embed(user_ns={})
sys.exit(0)
if args.shell:
shell = os.environ.get('SHELL', 'sh')
print("Spawning a Unix shell...")
os.execv(shell, [shell] + extra_argv)
sys.exit(1)
if args.coverage:
dst_dir = os.path.join(ROOT_DIR, 'build', 'coverage')
fn = os.path.join(dst_dir, 'coverage_html.js')
if os.path.isdir(dst_dir) and os.path.isfile(fn):
shutil.rmtree(dst_dir)
extra_argv += ['--cover-html', '--cover-html-dir=' + dst_dir]
test_dir = os.path.join(ROOT_DIR, 'build', 'test')
if args.build_only:
sys.exit(0)
elif args.submodule:
modname = PROJECT_MODULE + '.' + args.submodule
try:
__import__(modname)
if args.bench:
test = sys.modules[modname].bench
else:
test = sys.modules[modname].test
except (ImportError, KeyError, AttributeError) as e:
print("Cannot run tests for %s (%s)" % (modname, e))
sys.exit(2)
elif args.tests:
def fix_test_path(x):
# fix up test path
p = x.split(':')
p[0] = os.path.relpath(os.path.abspath(p[0]), test_dir)
return ':'.join(p)
tests = [fix_test_path(x) for x in args.tests]
def test(*a, **kw):
extra_argv = kw.pop('extra_argv', ())
extra_argv = extra_argv + tests[1:]
kw['extra_argv'] = extra_argv
from numpy.testing import Tester
if args.bench:
return Tester(tests[0]).bench(*a, **kw)
else:
return Tester(tests[0]).test(*a, **kw)
else:
__import__(PROJECT_MODULE)
if args.bench:
test = sys.modules[PROJECT_MODULE].bench
else:
test = sys.modules[PROJECT_MODULE].test
# Run the tests under build/test
try:
shutil.rmtree(test_dir)
except OSError:
pass
try:
os.makedirs(test_dir)
except OSError:
pass
shutil.copyfile(os.path.join(ROOT_DIR, '.coveragerc'),
os.path.join(test_dir, '.coveragerc'))
cwd = os.getcwd()
try:
os.chdir(test_dir)
if args.bench:
result = test(args.mode,
verbose=args.verbose,
extra_argv=extra_argv)
else:
result = test(args.mode,
verbose=args.verbose,
extra_argv=extra_argv,
doctests=args.doctests,
coverage=args.coverage)
finally:
os.chdir(cwd)
if isinstance(result, bool):
sys.exit(0 if result else 1)
elif result.wasSuccessful():
sys.exit(0)
else:
sys.exit(1)
## License: GPL v.2
##
## Purpose: Post processing script
################################################################################
import fileinput
import os
import sys
import shutil
cmake_src_path = os.path.join(sys.argv[1], 'CMakeLists.txt')
if not os.path.exists(cmake_src_path):
exit('Parse path not exists')
utilfile = os.path.join(os.getcwd(), os.pardir, 'cmake', 'util.cmake')
# Get values
ft_major = "0"
ft_minor = "0"
ft_patch = "0"
major_get = False
minor_get = False
patch_get = False
def extract_value(text):
val_text = text.split("\"")
return val_text[1]
from transformers.configuration_bert import BertConfig
from tokenization_numerical import BertNumericalTokenizer
from transformers.optimization import get_linear_schedule_with_warmup
import wandb
from metrics import log_wandb, summarize_metrics, anomaly_evaluation
from metrics import exponent_metrics, loss_metrics, mantissa_metrics, regression_metrics, numeracy_metrics, flow_metrics, log_metrics
from metrics import anomaly_sample
from metrics import save_metrics, save_results, save_args
PREGENERATED_DATA = {
"fin-all": 'news',
"fin-dol": 'news_dollar',
"sci-doc": 'scidocs'
}
CHECKPOINT_PATH = os.getcwd()+'/checkpoints/'
log_format = '%(asctime)-10s: %(message)s'
logging.basicConfig(level=logging.INFO, format=log_format)
def get_model(args):
if args.model_name == 'GMMBert':
NumberBertModel = GMMBert
args.do_gmm = True
elif args.model_name == 'LogBert':
NumberBertModel = LogBert
args.do_log = True
elif args.model_name == 'ExpBert':
NumberBertModel = ExponentBert
args.do_exp = True
"""
Created on Thu Sep 23 2019
@author: fkaragul
"""
import osmnx as ox
import networkx as nx
import numpy as np
import pandas as pd
import matplotlib.cm as cm
import os
# os.chdir('C:\\giraffe\\viasat_data\\gv_net')
os.chdir('C:\\python\\projects\\giraffe\\viasat_data\\reti_VALENTI\\gv_net')
os.getcwd()
#load Graph
Bracciano = ox.load_graphml('network_Bracciano_6km_epgs4326.graphml')
# way class: mean, max, min (make a DICTIONARY) these are the "keys"
# these numbers are the speeds on different type of road
way_dict={
"residential" : [ 30 , 50 , 10 ],
"secondary" : [ 40 , 90 , 30 ],
"primary" : [ 50 , 70 , 20 ],
"tertiary" : [ 35 , 70 , 10 ],
"unclassified" :[ 40 , 60 , 10 ],
"secondary_link": [ 40 , 55 , 30 ],
"trunk" : [ 70 , 90 , 40 ],
"tertiary_link": [ 35 , 50 , 30 ],
def url_for_version(self, version):
return "file://{0}/maker-{1}.tgz".format(os.getcwd(), version)
def load(filename):
input_data = {}
if os.path.isfile(os.path.join(os.getcwd(), 'input', filename)):
if filename.split(".")[-1] == 'xls':
workbook = xlrd.open_workbook(
os.path.join(os.getcwd(), 'input', filename))
elif filename.split(".")[-1] == 'xlsx':
workbook = openpyxl.open_workbook(
os.path.join(os.getcwd(), 'input', filename))
else:
print('Extension of file not allowed')
pass
else:
print('File does not exist')
pass
worksheet = workbook.sheet_by_index(0)
# Refrigerant
input_data["refrigerant"] = worksheet.cell_value(22, 3)
# Evaporator
input_data["ev_temperature"] = worksheet.cell_value(
5, 3) + k # [C] Evaporator temperature
input_data["ev_super_heat"] = worksheet.cell_value(
6, 3) # [K] Evaporator outlet super heating
input_data["ev_pressure_drop"] = worksheet.cell_value(
7, 3) * 1e3 # [Pa] Evaporator pressure drop
# Suction line
input_data["sl_temperature_change"] = worksheet.cell_value(
8, 3) # [K] Superheat (Suction line)
input_data["sl_pressure_drop"] = worksheet.cell_value(
9, 3) * 1e3 # [Pa] Suction Line
# Compressor
input_data["capacity_volumetric"] = worksheet.cell_value(
10, 3) # [-] Isentropic Efficiency
input_data["efficiency_isentropic"] = worksheet.cell_value(
11, 3) # [-] Isentropic Efficiency
input_data["efficiency_volymetric"] = worksheet.cell_value(
12, 3) # [-] Volymetric Efficiency
# Discharge line
input_data["dl_temperature_change"] = worksheet.cell_value(
13, 3) # [K] Superheat (Suction line)
input_data["dl_pressure_drop"] = worksheet.cell_value(
14, 3) * 1e3 # [K] Superheat (Suction line)
# Condenser
input_data["co_temperature"] = worksheet.cell_value(
15, 3) + k # [C] Temperature
input_data["co_sub_cooling"] = worksheet.cell_value(
16, 3) # [K] Outlet sub cooling
input_data["co_pressure_drop"] = worksheet.cell_value(
17, 3) * 1e3 # [Pa] Pressure drop
# Liquid line
input_data["ll_temperature_change"] = worksheet.cell_value(
18, 3) # [K] Superheat (Suction line)
input_data["ll_pressure_drop"] = worksheet.cell_value(
19, 3) * 1e3 # [K] Superheat (Suction line)
return input_data
import sys, os
sys.path.append(os.path.dirname(os.getcwd()))
from bs4 import BeautifulSoup
from beautifultable import BeautifulTable
from _tools import *
from _helpers import *
STARTING_URL = "https://www.tripadvisor.fr/Restaurants-g187147-Paris_Ile_de_France.html"
restaurants = {}
raw_html = simple_get(STARTING_URL)
if raw_html : print('Connection successful...')
html = BeautifulSoup(raw_html, 'html.parser')
restaurant_nodes = html.select('[id^="eatery_"]')
for r in restaurant_nodes :
key = get_key(r)
restaurants[key] = {
'name': get_name(r),
'rating': get_rating(r),
'reviews': get_reviews(r),
'rank': get_rank(r),
}
def writeFrame( w2if, lwr, n ):
w2if.Modified()
current_dir = os.getcwd()
filename = current_dir + "/frames/vd_lin50"+ ('%05d' % n)+".png"
lwr.SetFileName( filename )
lwr.Write()
def reference(filename):
reference_data = numpy.zeros((10, 6), dtype=numpy.float) # Temperature
# Differenft functions depending of version of Excel
if filename.split(".")[-1] == 'xls':
workbook = xlrd.open_workbook(
os.path.join(os.getcwd(), 'input', filename))
elif filename.split(".")[-1] == 'xlsx':
workbook = openpyxl.open_workbook(
os.path.join(os.getcwd(), 'input', filename))
else:
print('Extension of file not allowed')
pass
# Set working sheet
worksheet = workbook.sheet_by_index(0)
# After suction line/ Before compressor
reference_data[0, 0] = worksheet.cell_value(108, 3) + k # Temperature
reference_data[0, 1] = worksheet.cell_value(109, 3) * 1e3 # Pressure
reference_data[0, 2] = worksheet.cell_value(110, 3) * 1e3 # Enthalpy
reference_data[0, 3] = worksheet.cell_value(111, 3) * 1e3 # Entropy
reference_data[0, 4] = worksheet.cell_value(112, 3) # Density
# After compressor / Before discharge line
reference_data[1, 0] = worksheet.cell_value(108, 4) + k # Temperature
reference_data[1, 1] = worksheet.cell_value(109, 4) * 1e3 # Pressure
reference_data[1, 2] = worksheet.cell_value(110, 4) * 1e3 # Enthalpy
reference_data[1, 3] = worksheet.cell_value(111, 4) * 1e3 # Entropy
reference_data[1, 4] = worksheet.cell_value(112, 4) # Density
# After discharge line / Condenser inlet
reference_data[2, 0] = worksheet.cell_value(124, 3) + k # Temperature
reference_data[2, 1] = worksheet.cell_value(125, 3) * 1e3 # Pressure
reference_data[2, 2] = worksheet.cell_value(126, 3) * 1e3 # Enthalpy
reference_data[2, 3] = worksheet.cell_value(127, 3) * 1e3 # Entropy
reference_data[2, 4] = worksheet.cell_value(128, 3) # Density
# Condenser dew point
reference_data[3, 0] = worksheet.cell_value(130, 3) + k # Temperature
# Condenser bubble point
reference_data[4, 0] = worksheet.cell_value(130, 4) + k # Temperature
# Condenser outlet / Before liquid line
reference_data[5, 0] = worksheet.cell_value(124, 4) + k # Temperature
reference_data[5, 1] = worksheet.cell_value(125, 4) * 1e3 # Pressure
reference_data[5, 2] = worksheet.cell_value(126, 4) * 1e3 # Enthalpy
reference_data[5, 3] = worksheet.cell_value(127, 4) * 1e3 # Entropy
reference_data[5, 4] = worksheet.cell_value(128, 4) # Density
# After liquid line / Before expansion valve
reference_data[6, 0] = worksheet.cell_value(141, 3) + k # Temperature
reference_data[6, 1] = worksheet.cell_value(142, 3) * 1e3 # Pressure
reference_data[6, 2] = worksheet.cell_value(143, 3) * 1e3 # Enthalpy
reference_data[6, 3] = worksheet.cell_value(144, 3) * 1e3 # Entropy
reference_data[6, 4] = worksheet.cell_value(145, 3) # Density
# After expansion valve / Evaporator inlet
reference_data[7, 0] = worksheet.cell_value(47, 3) + k # Temperature
reference_data[7, 1] = worksheet.cell_value(48, 3) * 1e3 # Pressure
reference_data[7, 2] = worksheet.cell_value(49, 3) * 1e3 # Enthalpy
reference_data[7, 3] = worksheet.cell_value(50, 3) * 1e3 # Entropy
reference_data[7, 4] = worksheet.cell_value(51, 3) # Density
reference_data[7, 5] = worksheet.cell_value(52, 3) # Vapor mass quality
# Evaporator dew point
reference_data[8, 0] = worksheet.cell_value(53, 4) + k # Temperature
# Evaporator outlet / Before suction line
reference_data[9, 0] = worksheet.cell_value(47, 4) + k # Temperature
reference_data[9, 1] = worksheet.cell_value(48, 4) * 1e3 # Pressure
reference_data[9, 2] = worksheet.cell_value(49, 4) * 1e3 # Enthalpy
reference_data[9, 3] = worksheet.cell_value(50, 4) * 1e3 # Entropy
reference_data[9, 4] = worksheet.cell_value(51, 4) # Density
return reference_data
import os
import argparse
import cv2
from imageai.Detection import ObjectDetection
execution_path = os.getcwd()
from tqdm import tqdm
parser = argparse.ArgumentParser(description="YOLO car cropped.")
parser.add_argument("--data_dir", type=str,
help="The location of the dataset")
parser.add_argument("--output_dir", type=str,
help="The location of the dataset")
args = parser.parse_args()
if __name__=='__main__':
failed_filenames = []
detector = ObjectDetection()
detector.setModelTypeAsRetinaNet()
detector.setModelPath( os.path.join(execution_path , "object-detection-models/resnet50_coco_best_v2.0.1.h5"))
detector.loadModel(detection_speed="fastest")
custom_objects = detector.CustomObjects(car=True, truck=True)
categories = os.listdir(args.data_dir)
categories.sort()
if not os.path.exists(args.output_dir):
os.mkdir(args.output_dir)
filler = np.zeros(difference)
self.num_steps = max_steps
self.xcom = np.concatenate((self.xcom, filler))
self.xfbk = np.concatenate((self.xfbk, filler))
self.ycom = np.concatenate((self.ycom, filler))
self.yfbk = np.concatenate((self.yfbk, filler))
self.errors = np.zeros((2, self.num_steps))
actions = [
2, 1.9, 1.8, 1.7, 1.6, 1.5, 1.4, 1.3, 1.2, 1.1, 1, .9, .8, .7, .6, .5, .4,
.3, .2, .1, 0, -.1, -.2, -.3, -.4, -.5, -.6, -.7, -.8, -.9, -1, -1.1, -1.2,
-1.3 - 1.4, -1.5, -1.6, -1.7, -1.8, -1.9, -2
]
action_size = len(actions)
dirname = os.getcwd()
dirname += '/data/'
data_parser = parser()
files = []
for file in os.listdir(dirname):
if file.endswith(".DAT"):
files.append(file)
chosen_test_set = 0
file_data_train = []
file_data_test = []
for i in range(len(files)):
data_parser.parse_data(dirname + files[i])
temp = data_parser.get_all_com_fbk().values
if i == chosen_test_set:
file_data_test.append(temp)
