def test():
"""Run the unit tests."""
# Run the tests in each of the virtual environments defined in Project.test_python_versions
# or if not defined, then in Project.wheel_python_versions. If neither are defined, then
# run the test in the current environment.
venvs = VirtualenvInfo('test_python_versions', 'wheel_python_versions')
coverage = '--cov-report term-missing --cov={package}'.format(package=Project.package)
reports = '--junitxml={quality}/tests.xml'.format(quality=Project.quality_dir)
mkdir_p(Project.tests_dir)
if not venvs.in_virtualenv and venvs.defined:
for venv_info in venvs.infos():
info('Running unit tests using the {venv} virtual environment.'.format(venv=venv_info.venv))
venv_info.run('py.test {coverage} {reports} {tests_dir}'.format(coverage=coverage,
reports=reports,
tests_dir=Project.tests_dir),
verbose=True)
else:
with LocalShell() as local:
info('Running unit tests using the current python environment')
local.run("py.test {coverage} {reports} {tests_dir}".format(coverage=coverage,
reports=reports,
tests_dir=Project.tests_dir),
verbose=True)
def feagen_run_with_configs(global_config, bundle_config, dag_output_path=None,
no_bundle=False):
"""Generate feature with configurations.
global_config (collections.Mapping): global configuration
generator_class: string
data_bundles_dir: string
generator_kwargs: collections.Mapping
bundle_config (collections.Mapping): bundle configuration
name: string
structure: collections.Mapping
"""
if not isinstance(global_config, collections.Mapping):
raise ValueError("global_config should be a "
"collections.Mapping object.")
if not isinstance(bundle_config, collections.Mapping):
raise ValueError("bundle_config should be a "
"collections.Mapping object.")
data_generator = get_data_generator_from_config(global_config)
data_keys = get_data_keys_from_structure(bundle_config['structure'])
data_generator.generate(data_keys, dag_output_path)
if not no_bundle:
mkdir_p(global_config['data_bundles_dir'])
bundle_path = join(global_config['data_bundles_dir'],
bundle_config['name'] + '.h5')
data_generator.bundle(
bundle_config['structure'], data_bundle_hdf_path=bundle_path,
structure_config=bundle_config['structure_config'])
def make_exec_file(self, config):
outputPath = config.exec_file_path
cmd_str = config.cmd_str
mkdir_p(os.path.dirname(outputPath))
outputFile = open(outputPath, "w")
outputFile.write(cmd_str)
outputFile.close()
def __init__(self, suite_dir=None, new_mode=False):
if suite_dir is None:
suite_dir = os.getcwd()
self.db_file_name = os.path.join(suite_dir, self.DB_FILE_BASE_NAME)
# create the host directory if necessary
try:
mkdir_p( suite_dir )
except Exception, x:
raise Exception( "ERROR: " + str(x) )
def setup_experiments(auto_var):
exp_name = 'experiment01'
mkdir_p(f"./results/{exp_name}")
auto_var.register_experiment(f'{exp_name}', run_experiment01,
{'file_format': 'pickle', 'result_file_dir': f'./results/{exp_name}'})
exp_name = 'restrictedImgnet'
mkdir_p(f"./results/{exp_name}")
auto_var.register_experiment(f'{exp_name}', run_restrictedImgnet,
{'file_format': 'pickle', 'result_file_dir': f'./results/{exp_name}'})
def __init__(self, suite_dir=None, new_mode=False):
if suite_dir is None:
suite_dir = os.getcwd()
self.db_file_name = os.path.join(suite_dir, self.DB_FILE_BASE_NAME)
# create the host directory if necessary
try:
mkdir_p( suite_dir )
except Exception, x:
raise Exception( "ERROR: " + str(x) )
def init_config():
mkdir_p(".dagianrc")
default_global_config = """\
generator_class: feature_generator.FeatureGenerator
data_bundles_dir: data_bundles
# The additional arguments that will be given when initiating the data generator
# object.
generator_kwargs:
h5py_hdf_dir:
h5py
pandas_hdf_dir:
pandas.h5
"""
default_bundle_config = """\
# The name of this bundle. This will be the file name of the data bundle.
# Another suggested usage is to comment out this line, so the name will be
# obtained from the file name of this config, that is, the name will be the same
# as the config file name without the extension.
name: default
# The structure of the data bundle. All the involved data will be generated and
# put into the global data file first (if data not exist), and then be bundled
# according to this structure, and then write to the data bundle file.
structure:
id: id
label: label
features:
- feature_1
- feature_2
# Special configuration for the structure. Here we set concat=True for
# 'features'. It means that the data list in 'features' will be concatenated
# into a dataset.
structure_config:
features:
concat: True
"""
default_global_config_path = join(".dagianrc", "config.yml")
if exists(default_global_config_path):
print("Warning: %s exists so it's not generated." %
default_global_config_path)
else:
with open(default_global_config_path, "w") as fp:
fp.write(default_global_config)
default_bundle_config_path = join(".dagianrc", "bundle_config.yml")
if exists(default_bundle_config_path):
print("Warning: %s exists so it's not generated." %
default_bundle_config_path)
else:
with open(default_bundle_config_path, "w") as fp:
fp.write(default_bundle_config)
def __init__( self, suite, run_mode='live', clock=None, start_tag=None, stop_tag=None ):
self.run_mode = run_mode
self.clock = clock
self.start_tag = start_tag
self.stop_tag = stop_tag
globals = gcfg
self.dir = os.path.join( globals.cfg['task hosts']['local']['run directory'], suite, 'state' )
self.path = os.path.join( self.dir, 'state' )
try:
mkdir_p( self.dir )
except Exception, x:
# To Do: handle error
raise
def daemonize( suite, port ):
"""
ATTRIBUTION: base on a public domain code recipe by Jurgen Hermann:
http://code.activestate.com/recipes/66012-fork-a-daemon-process-on-unix/
"""
# Do the UNIX double-fork magic, see Stevens' "Advanced
# Programming in the UNIX Environment" for details (ISBN 0201563177)
sout = suite_output( suite )
try:
mkdir_p( sout.get_dir() )
except Exception, x:
sys.exit( str(x) )
def make_condor_file(self,condorConfig):
outputPath = condorConfig.condor_file_path
mkdir_p(os.path.dirname(outputPath))
condor_file_content = condor_file_template.format(
exec_file_path = condorConfig.exec_file_path,
arguments = condorConfig.arguments,
input = condorConfig.input,
output = condorConfig.output,
error = condorConfig.error,
log = condorConfig.log,
njob = condorConfig.njob,
)
outputFile = open(outputPath,"w")
outputFile.write(condor_file_content)
outputFile.close()
def __init__(self, suite_dir=None, new_mode=False, primary_db=True):
if suite_dir is None:
suite_dir = os.getcwd()
if primary_db:
prefix = os.path.join(suite_dir, 'state')
else:
prefix = suite_dir
self.db_file_name = os.path.join(prefix, self.DB_FILE_BASE_NAME)
self.db_dump_name = os.path.join(prefix, self.DB_DUMP_BASE_NAME)
# create the host directory if necessary
try:
mkdir_p( suite_dir )
except Exception, x:
raise Exception( "ERROR: " + str(x) )
def __init__(self, suite, config, initial_oldest_ctime, start_tag):
self.config = config
self.initial_oldest_ctime = initial_oldest_ctime
self.start_tag = start_tag
title = 'suite ' + suite + ' run-time dependency graph'
# create output directory if necessary
odir = config['visualization']['runtime graph']['directory']
# raises OSError:
mkdir_p(odir)
self.file = os.path.join(odir, 'runtime-graph.dot')
self.graph = CGraph(title, config['visualization'])
self.finalized = False
self.cutoff = config['visualization']['runtime graph']['cutoff']
def convert_dir(oldDir, newDir):
dat = open('{}.dat'.format(newDir), 'w')
mkdir_p(newDir)
for svgFile in os.listdir(oldDir):
try:
dat.write('{}: '.format(svgFile))
convert_svg(os.path.join(oldDir, svgFile),
os.path.join(newDir, svgFile),
dataWriter=dat)
dat.write('\n')
except Exception:
print 'Could not convert {}'.format(svgFile)
dat.close()
def __init__(self, suite, config, initial_oldest_ctime, start_tag ):
self.config = config
self.initial_oldest_ctime = initial_oldest_ctime
self.start_tag = start_tag
title = 'suite ' + suite + ' run-time dependency graph'
# create output directory if necessary
odir = config['visualization']['runtime graph']['directory']
# raises OSError:
mkdir_p( odir )
self.file = os.path.join( odir, 'runtime-graph.dot' )
self.graph = CGraph( title, config['visualization'] )
self.finalized = False
self.cutoff = config['visualization']['runtime graph']['cutoff']
def __init__(self,
before_experiment_hooks=None,
after_experiment_hooks=None,
settings: Dict = None,
logging_level: int = logging.WARNING) -> None:
"""
settings : {
'server_url': 'http://127.0.0.1:8080/nn_attack/',
'result_file_dir': './results/'
'file_format': 'json' or 'pickle'
}
"""
logger.setLevel(logging_level)
self.experiments: Dict[str, Any] = {}
self.variables: Dict[str, dict] = {}
self.var_shown_name: Dict[str, Dict[str, str]] = {}
self.var_description: Dict[str, str] = {}
self.var_class: Dict[str, Any] = {}
self.var_value: Dict[str, Any] = {}
self.inter_var: Dict[str, Any] = {}
self.result_fields: List[str] = []
self.settings: Dict
self.settings = {'file_format': 'json'}
if isinstance(settings, dict):
self.settings.update(settings)
if ('result_file_dir'
in self.settings) and self.settings['result_file_dir']:
mkdir_p(self.settings['result_file_dir'])
try:
self.repo = git.Repo(search_parent_directories=True)
self.var_value['git_hash'] = self.repo.head.object.hexsha
except git.exc.InvalidGitRepositoryError:
logger.warning("Git repository not found.")
try:
self.var_value['hostname'] = socket.gethostname()
except:
logger.warning("Unable to get hostname.")
self.after_experiment_hooks = after_experiment_hooks
self.before_experiment_hooks = before_experiment_hooks
self._read_only: bool = False
self._no_hooks: bool = False
def generate( self, dir ):
pfile = os.path.join(dir, 'passphrase')
if os.path.isfile( pfile ):
try:
self.get( pfile )
return
except SecurityError:
pass
# Note: Perhaps a UUID might be better here?
char_set = string.ascii_uppercase + string.ascii_lowercase + string.digits
self.passphrase = ''.join(random.sample(char_set, 20))
mkdir_p(dir)
f = open(pfile, 'w')
f.write(self.passphrase)
f.close()
# set passphrase file permissions to owner-only
os.chmod( pfile, 0600 )
if flags.verbose:
print 'Generated suite passphrase file on', user + '@' + get_hostname() + ':', pfile
def generate(self, dir):
pfile = os.path.join(dir, 'passphrase')
if os.path.isfile(pfile):
try:
self.get(pfile)
return
except SecurityError:
pass
# Note: Perhaps a UUID might be better here?
char_set = string.ascii_uppercase + string.ascii_lowercase + string.digits
self.passphrase = ''.join(random.sample(char_set, 20))
mkdir_p(dir)
f = open(pfile, 'w')
f.write(self.passphrase)
f.close()
# set passphrase file permissions to owner-only
os.chmod(pfile, 0600)
if self.verbose:
print 'Generated suite passphrase file on', user + '@' + get_hostname(
) + ':', pfile
def main():
input_fn = sys.argv[1]
#input_fn = 'clip009.mp4'
#input_fn = 'clip010.mp4'
output_fn = os.path.splitext(input_fn)[0] + '_output.mp4'
output_tracking_result_fn = os.path.splitext(input_fn)[0] + '_tracking_result.csv'
output_background_fn = os.path.splitext(input_fn)[0] + '_background.bmp'
tmp_dir = '__tmp/'
tmp_dir_cluster = os.path.join(tmp_dir, 'cluster/')
tmp_dir_extraction = os.path.join(tmp_dir, 'extraction/')
output_temp_file_zip = input_fn + '.__tmp'
mkdir_p(tmp_dir)
make_clean_dir(tmp_dir_cluster) # dangerous
make_clean_dir(tmp_dir_extraction) # dangerous
print('auto_background starts...')
#dangerous: race condition(ignore it)
if os.path.basename(output_background_fn) in os.listdir('.'):
print('use cached background file: ' + output_background_fn)
else:
auto_background(input_fn, output_background_fn)
print('auto_background finished')
print('ball_extraction starts...')
ball_extraction(input_fn, output_background_fn, tmp_dir_extraction)
print('ball_extraction finished')
print('ball_clustering starts...')
ball_clustering(tmp_dir_extraction, tmp_dir_cluster, 'bmp')
print('ball_clustering finished')
print('tracking_from_auto_template starts...')
if os.path.basename(output_tracking_result_fn) in os.listdir('.'):
print('use cached tracking result csv file: ' + output_tracking_result_fn)
else:
tracking_from_auto_template(input_fn, output_background_fn, tmp_dir_cluster, output_tracking_result_fn)
print('tracking_from_auto_template finished')
print('creating output video...')
create_tracking_video_from_detection_result_csv(input_fn, output_tracking_result_fn, output_fn)
print('output video %s created' % output_fn)
print('creating temp file archive...')
shutil.make_archive(output_temp_file_zip, 'zip', tmp_dir)
print('temp file archive %s.zip created' % output_temp_file_zip)
return
def test_json_file(self):
settings = {'file_format': 'json', 'result_file_dir': 'test'}
mkdir_p(settings['result_file_dir'])
auto_var = AutoVar(
settings=settings,
after_experiment_hooks=[
partial(save_result_to_file, get_name_fn=default_get_file_name)
],
)
auto_var.add_variable_class(OrdVarClass())
auto_var.set_variable_value_by_dict({'ord': '1'})
def experiment(auto_var):
return {'test': auto_var.get_var('ord')}
_ = auto_var.run_single_experiment(experiment, with_hook=True)
with open("test/1.json", 'r') as f:
ret = json.load(f)
self.assertEqual(ret['test'], auto_var.get_var('ord'))
shutil.rmtree(settings['result_file_dir'])
def make_crab_file(self, crabConfig):
outputPath = crabConfig.crab_file_path
mkdir_p(os.path.dirname(outputPath))
crab_file_content = crab_file_template.format(
taskName=crabConfig.taskName,
JobType_plugName=crabConfig.JobType_plugName,
JobType_psetName=crabConfig.JobType_psetName,
JobType_scriptExe=crabConfig.JobType_scriptExe,
JobType_inputFiles=crabConfig.JobType_inputFiles,
JobType_outputFiles=crabConfig.JobType_outputFiles,
JobType_maxMemoryMB=crabConfig.JobType_maxMemoryMB,
Data_outputPrimaryDataset=crabConfig.Data_outputPrimaryDataset,
Data_unitsPerJob=crabConfig.Data_unitsPerJob,
Data_totalUnits=crabConfig.Data_totalUnits,
Data_publication=crabConfig.Data_publication,
Data_outputDatasetTag=crabConfig.Data_outputDatasetTag,
Data_outLFNDirBase=crabConfig.Data_outLFNDirBase,
Site_storageSite=crabConfig.Site_storageSite,
)
outputFile = open(outputPath, "w")
outputFile.write(crab_file_content)
outputFile.close()
def draw_dag(nx_dag, path):
if dirname(path) != '':
mkdir_p(dirname(path))
agraph = nx.nx_agraph.to_agraph(nx_dag)
for edge in agraph.edges_iter():
if edge.attr['nonskipped_data'] is None:
edge.attr['label'] = edge.attr['data_definitions']
else:
edge.attr['label'] = ""
if edge.attr['nonskipped_data'] not in ["set()", "set([])"]:
edge.attr['label'] += edge.attr['nonskipped_data']
if (edge.attr['skipped_data'] not in ["set()", "set([])"]
and edge.attr['skipped_data'] is not None):
edge.attr['label'] += "(%s skipped)" % edge.attr['skipped_data']
for node in agraph.nodes_iter():
if node.attr['skipped'] == "True":
node.attr['label'] = node.attr['func_name'] + " (skipped)"
node.attr['fontcolor'] = 'grey'
else:
node.attr['label'] = node.attr['func_name']
agraph.layout('dot')
agraph.draw(path)
def __init__(self, hdf_path):
hdf_dir = os.path.dirname(hdf_path)
if hdf_dir != '':
mkdir_p(hdf_dir)
self.h5f = h5py.File(hdf_path, 'a')
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
# Load Training Data
X_train, y_train, X_val, y_val = load_training_data(args.track)
print(X_train.shape[0], 'training samples.')
print(X_val.shape[0], 'validation samples.')
# Training loop variables
epochs = 100
batch_size = 50
model = create_model()
mkdir_p("weights")
weights_file = "weights/{}.hdf5".format(args.track)
if os.path.isfile(weights_file):
model.load_weights(weights_file)
model.compile(loss=customized_loss, optimizer=optimizers.adam(lr=0.0001))
checkpointer = ModelCheckpoint(monitor='val_loss',
filepath=weights_file,
verbose=1,
save_best_only=True,
mode='min')
earlystopping = EarlyStopping(monitor='val_loss', patience=20)
model.fit(X_train,
y_train,
batch_size=batch_size,
epochs=epochs,
def get_var_with_argument(self, var_name: str, argument: str, *args,
**kwargs):
if self.variables[var_name]["type"] == "val":
return argument
else:
cache_dir = None
if argument in self.variables[var_name]["argument_fn"]:
func = self.variables[var_name]["argument_fn"][argument]
cache_dir = self.variables[var_name]['cache_dirs'][argument]
required_vars = self.variables[var_name]['required_vars'][
argument]
else:
m = None
for arg_template, func in self.variables[var_name][
"argument_fn"].items():
m = re.fullmatch(arg_template, argument)
if m is not None:
kwargs.update(m.groupdict())
cache_dir = self.variables[var_name]['cache_dirs'][
arg_template]
required_vars = self.variables[var_name][
'required_vars'][arg_template]
break
if m is None:
raise ValueError('Argument "%s" not matched in Variable '
'"%s".' % (argument, var_name))
kwargs['auto_var'] = self
named_args = inspect.getfullargspec(func)[0]
if 'var_value' in named_args:
kwargs['var_value'] = self.var_value
if 'inter_var' in named_args:
kwargs['inter_var'] = self.inter_var
if cache_dir is not None:
mkdir_p(cache_dir)
#var_used = {var_name: self.var_value[var_name]}
var_used = {var_name: argument}
if required_vars is not None:
for var in required_vars:
if var not in self.var_value:
raise ValueError(
'Variable "%s" required by Variable '
'"%s" is not set.' % (var, argument))
var_used[var] = self.var_value[var]
required_variables = [
str(v) for k, v in sorted(var_used.items())
]
cache_filename = os.path.join(
cache_dir, '-'.join(required_variables) + '.pkl')
if os.path.exists(cache_filename):
try:
func_outputs = joblib.load(cache_filename)
logger.info(
f"using result from cache file {cache_filename} ..."
)
except:
os.unlink(cache_filename)
func_outputs = func(*args, **kwargs)
logger.info(
f"dumping cache file to {cache_filename} ...")
joblib.dump(func_outputs, cache_filename)
else:
func_outputs = func(*args, **kwargs)
logger.info(f"dumping cache file to {cache_filename} ...")
joblib.dump(func_outputs, cache_filename)
else:
func_outputs = func(*args, **kwargs)
return func_outputs
def create_directory( self, d, name ):
try:
mkdir_p( d )
except Exception, x:
print >> sys.stderr, str(x)
raise GlobalConfigError( 'Failed to create directory "' + name + '"' )
def main(date_range=1):
session = requests.Session()
adapters = requests.adapters.HTTPAdapter(max_retries=3)
session.mount("http://", adapters)
session.mount("https://", adapters)
pdf_root_dir = OUTPUT_DIR + '/pdf'
xbrl_root_dir = OUTPUT_DIR + '/xbrl'
mkdir_p(OUTPUT_DIR)
mkdir_p(pdf_root_dir)
mkdir_p(xbrl_root_dir)
dbname = '%s/sqlite3.db' % (OUTPUT_DIR)
with closing(sqlite3.connect(dbname)) as conn:
cur = conn.cursor()
query = '''
CREATE TABLE IF NOT EXISTS td_net (
id INTEGER PRIMARY KEY AUTOINCREMENT,
date DATETIME,
item_id text,
stock_code text,
stock_code_long text,
company_name text,
title text,
content text,
xbrl text,
pdf text,
security text,
refresh_info text
);
'''
cur.execute(query)
now = datetime.datetime.now()
start_date = datetime.datetime(now.year, now.month, now.day)
current_date = start_date
for i in range(date_range):
current_date -= datetime.timedelta(days=1)
logging.info('Collecting data on %s' % (current_date))
datestring = current_date.strftime('%Y%m%d')
result = session.get(
'https://www.release.tdnet.info/inbs/I_list_001_%s.html' %
(datestring))
time.sleep(0.5)
soup = BeautifulSoup(result.content, 'lxml')
if soup.find(id='pager-box-top'):
page_size = len(
soup.find(id='pager-box-top').find_all('div')) - 3
pdf_dir = pdf_root_dir + '/%s' % (datestring)
xbrl_dir = xbrl_root_dir + '/%s' % (datestring)
mkdir_p(pdf_dir)
mkdir_p(xbrl_dir)
record_data(session, cur, conn, current_date, pdf_dir,
xbrl_dir, soup)
for a in range(page_size - 1):
result = session.get(
'https://www.release.tdnet.info/inbs/I_list_0%02d_%s.html'
% (a + 2, datestring))
time.sleep(0.5)
soup = BeautifulSoup(result.content, 'lxml')
record_data(session, cur, conn, current_date, pdf_dir,
xbrl_dir, soup)
BaseObject("phi3",xmin=-np.pi,xmax=np.pi,binwidth=np.pi/20,xlabel="#phi_{3}"+" [radians]",ylabel=str("%.5f" % (np.pi/20))+" [radians]",xminrange=-3.5,xmaxrange=3.5,ymaxrange=0.04),
BaseObject("phi4",xmin=-np.pi,xmax=np.pi,binwidth=np.pi/20,xlabel="#phi_{4}"+" [radians]",ylabel=str("%.5f" % (np.pi/20))+" [radians]",xminrange=-3.5,xmaxrange=3.5,ymaxrange=0.04),
BaseObject("phi5",xmin=-np.pi,xmax=np.pi,binwidth=np.pi/20,xlabel="#phi_{5}"+" [radians]",ylabel=str("%.5f" % (np.pi/20))+" [radians]",xminrange=-3.5,xmaxrange=3.5,ymaxrange=0.04),
BaseObject("phi6",xmin=-np.pi,xmax=np.pi,binwidth=np.pi/20,xlabel="#phi_{6}"+" [radians]",ylabel=str("%.5f" % (np.pi/20))+" [radians]",xminrange=-3.5,xmaxrange=3.5,ymaxrange=0.04),
BaseObject("pto1",xmin=0.0,xmax=120.0,binwidth=1.0,xlabel="p_{T,1} [GeV]",ylabel=str("%.5f" % 1.0)+" [GeV]",xminrange=0.0,xmaxrange=120.0,ymaxrange=0.1),
BaseObject("pto2",xmin=0.0,xmax=120.0,binwidth=1.0,xlabel="p_{T,2} [GeV]",ylabel=str("%.5f" % 1.0)+" [GeV]",xminrange=0.0,xmaxrange=120.0,ymaxrange=0.1),
BaseObject("pto3",xmin=0.0,xmax=120.0,binwidth=1.0,xlabel="p_{T,3} [GeV]",ylabel=str("%.5f" % 1.0)+" [GeV]",xminrange=0.0,xmaxrange=120.0,ymaxrange=0.1),
BaseObject("pto4",xmin=0.0,xmax=120.0,binwidth=1.0,xlabel="p_{T,4} [GeV]",ylabel=str("%.5f" % 1.0)+" [GeV]",xminrange=0.0,xmaxrange=120.0,ymaxrange=0.1),
BaseObject("costheta1",xmin=-1.0,xmax=1.0,binwidth=0.05,xlabel="cos(#theta_{1})",ylabel=str("%.5f" % 0.05),xminrange=-1.2,xmaxrange=1.2,ymaxrange=0.05),
BaseObject("costheta2",xmin=-1.0,xmax=1.0,binwidth=0.05,xlabel="cos(#theta_{2})",ylabel=str("%.5f" % 0.05),xminrange=-1.2,xmaxrange=1.2,ymaxrange=0.05),
BaseObject("costhetastar",xmin=-1.0,xmax=1.0,binwidth=0.05,xlabel="cos(#theta_{*})",ylabel=str("%.5f" % 0.05),xminrange=-1.2,xmaxrange=1.2,ymaxrange=0.05),
BaseObject("phi",xmin=-np.pi,xmax=np.pi,binwidth=np.pi/20,xlabel="#phi"+" [radians]",ylabel=str("%.5f" % (np.pi/20))+" [radians]",xminrange=-3.5,xmaxrange=3.5,ymaxrange=0.04),
BaseObject("phi1",xmin=-np.pi,xmax=np.pi,binwidth=np.pi/20,xlabel="#phi_{1}"+" [radians]",ylabel=str("%.5f" % (np.pi/20))+" [radians]",xminrange=-3.5,xmaxrange=3.5,ymaxrange=0.04),
]
mkdir_p(outPlotDir)
if extratitle != "":
extratitle = ", " + extratitle
f1 = TFile(inputFilePath1,"READ")
f2 = TFile(inputFilePath2,"READ")
t1 = f1.Get("lheEvents_tchan")
t2 = f2.Get("lheEvents_tchan")
for p in plotlist:
kinem = p.name
xmin = p.xmin
xmax = p.xmax
binwidth = p.binwidth
xlabel = p.xlabel
ylabel = p.ylabel
xminrange = p.xmin
def __init__(self, pickle_dir):
mkdir_p(pickle_dir)
self.pickle_dir = pickle_dir
def download_data(url, output_path):
mkdir_p(dirname(output_path))
os.system("wget {} -O {}".format(url, output_path))
TARGET_DIR_TST = "/tmp2/RestrictedImageNet/val/"
ds = ImageNet("/tmp2/ImageNet")
meta = torch.load("/tmp2/ImageNet/meta.bin")
inv_map = {v: k for k, v in meta[0].items()}
class_dict = {
"dog": (151, 269),
"cat": (281, 286),
"frog": (30, 33),
"turtle": (33, 38),
"bird": (80, 101),
"primate": (365, 383),
"fish": (389, 398),
"crab": (118, 122),
"insect": (300, 320),
}
for class_name, idx in class_dict.items():
mkdir_p(join(TARGET_DIR_TRN, class_name))
mkdir_p(join(TARGET_DIR_TST, class_name))
for k in ds.classes[idx[0]:idx[1]]:
fn = inv_map[k]
os.system(
f"cp -rf {join(IMGNET_DIR_TRN, fn)}/* {join(TARGET_DIR_TRN, class_name)}"
)
os.system(
f"cp -rf {join(IMGNET_DIR_TST, fn)}/* {join(TARGET_DIR_TST, class_name)}"
)
def __init__(self, hdf_path):
hdf_dir = os.path.dirname(hdf_path)
if hdf_dir != '':
mkdir_p(hdf_dir)
self.hdf_store = pd.HDFStore(hdf_path)
RESULT_DIR = "shake_results"
TOKENIZER_FILE = RESULT_DIR + "/tokenizer.pickle"
WEIGHTS_FILE = RESULT_DIR + "/shake-weights.hdf5"
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('data', help='Data file of (line, author, work) tuples. Use generate_data.py in data/shakespeare to generate new datasets.')
parser.add_argument('--train', help='Run training.', action='store_true')
parser.add_argument('--evaluate_test', help='Run evaluations on the test split.', action='store_true')
parser.add_argument('--evaluate_val', help='Run evaluations on the val split.', action='store_true')
parser.add_argument('--evaluate_disputed', help='Run model on disputed W.S. works.', action='store_true')
args = parser.parse_args()
mkdir_p(RESULT_DIR)
if os.path.isfile(TOKENIZER_FILE):
print("======= Loading Tokenizer =======")
with open(TOKENIZER_FILE, 'rb') as handle:
tokenizer, data_tuples, author_id_map, works_id_map, lines_by_author_and_work = pickle.load(handle)
else:
print("======= Loading Plays =======")
print()
with open(args.data, 'r') as data_handle:
all_lines = [l.strip() for l in data_handle.readlines()]
# strip "// Metadata", extract json metadata object, strip "\n // (<fields>)"
metadata = json.loads(all_lines[1])
def save(self, sha256sum, message, file):
engine = create_engine('sqlite:///telescam.db')
Base.metadata.bind = engine
DBSession = sessionmaker(bind=engine)
session = DBSession()
data = self.koodous_link_existing_analysis_json(sha256sum)
koodous_url = self.koodous_link_existing_analysis(sha256sum)
if data == None:
logger.debug(
'Received empty json response at save from koodous_link_existing_analysis_json'
)
return False
try:
new_certificate = None
try:
new_certificate = session.query(Certificate).filter(
Certificate.sha1 == data['androguard']['certificate']
['sha1']).first()
logger.debug(
"Checking if current certificate exists in the database")
except KeyError, e:
logger.debug(
"Koodous couldn't exctract the certificate, Corrupted APK, using default certificate"
)
new_certificate = session.query(Certificate).filter(
Certificate.sha1 == '-').first()
if new_certificate == None:
logger.debug("Certificate didn't exist")
new_certificate = Certificate(
sha1=data['androguard']['certificate']['sha1'],
not_before=data['androguard']['certificate']['not_before'],
not_after=data['androguard']['certificate']['not_after'],
subjectdn=data['androguard']['certificate']['subjectDN'],
issuerdn=data['androguard']['certificate']['issuerDN'],
serial=data['androguard']['certificate']['serial'])
session.add(new_certificate)
new_apk = session.query(APK).filter(
APK.sha256 == data['sha256']).first()
logger.debug("Checking if current apk exists in the database")
if new_apk == None:
logger.debug("apk didn't exist")
# Save apk
local_filename = self.FILES_DIR + message.document.file_id + '.apk'
try:
logger.debug("Saving to disk")
mkdir_p(os.path.dirname(local_filename))
with open(local_filename, 'wb') as new_file:
new_file.write(file)
except Exception as e:
logger.error('Failed to save apk to disk: %s' %
local_filename,
exc_info=True)
raise
new_apk = APK(
app_name=data['androguard']['app_name'],
package_name=data['androguard']['package_name'],
version_code=data['androguard']['version_code'],
displayed_version=data['androguard']['displayed_version'],
local_package=local_filename,
koodous_url=koodous_url,
sha256=data['sha256'],
certificate=new_certificate)
session.add(new_apk)
new_submission = Submission(
submitted_to_username=message.chat.username,
submitted_to_title=message.chat.title,
submitted_to_id=message.chat.id,
forwarded_from_username=message.forward_from.username
if message.forward_from != None else None,
forwarded_from_firstname=message.forward_from.first_name
if message.forward_from != None else None,
forwarded_from_lastname=message.forward_from.last_name
if message.forward_from != None else None,
forwarded_from_id=message.forward_from.id
if message.forward_from != None else None,
submitted_by_username=message.from_user.username,
submitted_by_firstname=message.from_user.first_name,
submitted_by_lastname=message.from_user.last_name,
submitted_by_id=message.from_user.id,
message_text=message.text,
filename=message.document.file_name,
apk=new_apk)
session.add(new_submission)
logger.debug("Adding submission details to database")
try:
session.commit()
logger.debug("Saved changes to database")
return True
except Exception as e:
logger.error('Failed to save changes to the database',
exc_info=True)
raise
def _register_experiment(auto_var, exp_name):
mkdir_p(f"./results/{exp_name}")
auto_var.register_experiment(f'{exp_name}', getattr(experiments, f'run_{exp_name}'),
{'file_format': 'pickle', 'result_file_dir': f'./results/{exp_name}'})
def createFolders_callback(data):
params = dict(data);
root = params.pop('moldb_root');
prototype = params.pop('moldb_prototype');
printOnly = params.pop('moldb_printOnly');
project_name = params.pop('moldb_projectName');
visited={}
m = buildImplementation(params,prototype,visited);
meth = [];
for pid in sorted(visited.keys()):
meth.append(visited[pid]);
folder = root + '/' + m.getRef();
relroot = '$MOLDB_PROJECTS/'+project_name+'/Methods';
relfolder = relroot + '/' + m.getRef();
print folder;
if printOnly: return
# mkdir
mkdir_p(folder);
#chain.implementation
chain = Chain();
chain.fromMethods(meth,m.getHash(),project_name,False);
f=open(folder + '/chain.imp','w');
f.write( chain.toString() );
f.close();
#PARAMETERS
paramStr = 'PROJECT='+project_name+'\n';
paramStr += 'FOLDER='+relfolder+'\n'
paramStr += 'PROTOTYPES=$MOLDB_PROJECTS/'+project_name+'/Prototypes\n';
paramStr += paramsString(params);
f=open(folder+'/PARAMETERS','w');
f.write(paramStr);
f.close();
os.system('chmod +x '+folder+ '/PARAMETERS');
#DEPENDENCIES
depStr = dependenciesString(m.dependencies,relroot);
f=open(folder+'/DEPENDENCIES','w');
f.write(depStr);
f.close();
os.system('chmod +x '+ folder +'/DEPENDENCIES');
#Scripts
strPrm = '#!/bin/bash\n'
strPrm += '# METHOD '+m.name+'\n';
strPrm += '# ID' + str(m.getHash())+'\n';
strPrm += '# --- Dependencies --- \n'
strPrm += '. ./DEPENDENCIES\n'
# strPrm += dependenciesString(m.dependencies,root);
strPrm += '# --- Method Parameters ---\n'
strPrm += '. ./PARAMETERS\n'
# strPrm += 'PROJECT='+root+'\n'
# strPrm += 'FOLDER=' + folder +'\n'
strPrm += paramsString(params);
strPrm += '\n # ---- Script ----\n'
for script in m.scripts:
f=open(folder+'/'+script.name,'w');
f.write(strPrm+script.text);
f.close();
os.system('chmod +x '+folder+'/'+script.name);
def make_clean_dir(path): mkdir_p(path) shutil.rmtree(path) # dangerous mkdir_p(path) return
mass = m,
)
for m in [4,5,7,15,20,25,30,] ],
color = ROOT.kBlue,
),
]
treeName = "lheEvents_tchan"
histName = "acc"
n_tot_evts = 10000.
outputPath = "/home/lucien/public_html/Higgs/ALP/AcceptanceStudy/2019-11-26_hToZX/plot.pdf"
y_range = [0.,1.]
selection = "(massZ2 > %s) && (massZ2 < %s)"
width = 0.02
# ________________________________________________________________________________________________________________________ ||
mkdir_p(os.path.dirname(outputPath))
c = ROOT.TCanvas()
leg = ROOT.TLegend(0.70,0.65,0.89,0.87)
for i,hist_cfg in enumerate(hist_cfgs):
hist_cfg.hist = ROOT.TH1D(hist_cfg.name,"",len(hist_cfg.cfgs),-0.5,len(hist_cfg.cfgs)-0.5)
leg.AddEntry(hist_cfg.hist,hist_cfg.name,"l")
for ibin,cfg in enumerate(hist_cfg.cfgs):
f = ROOT.TFile(cfg.inputPath,"READ")
t = f.Get(treeName)
#acc = float(t.GetEntries())/float(n_tot_evts)
selectionStr = selection%(str(cfg.mass*(1.-width)),str(cfg.mass*(1.+width)))
acc = float(t.GetEntries(selectionStr)/float(n_tot_evts))
hist_cfg.hist.SetBinContent(ibin+1,acc)
hist_cfg.hist.SetBinError(ibin+1,math.sqrt(1./float(t.GetEntries())+1./float(n_tot_evts))*acc)
hist_cfg.hist.GetXaxis().SetBinLabel(ibin+1,cfg.x_label)
f.Close()
def mkdir( self ):
try:
mkdir_p( self.dir )
except Exception, x:
# To Do: handle error
raise
# Copyright: (c) Tiffany 2019
#-------------------------------------------------------------------------------
print("importing libraries ...")
import pandas as pd
import numpy as np
import csv
import sys
from mkdir_p import mkdir_p # library for command mkdir -p (create folder if not existed)
iupac_code = {
"A", "C", "G", "T", "W", "S", "M", "K", "R", "Y", "B", "D", "H", "V", "N"
}
length = sys.argv[1]
OUTPUT = "./IUPAC_input/"
mkdir_p(OUTPUT)
#read csv
def readcsv(infile):
print("reading csv...")
df = pd.read_csv(infile, index_col=0)
return df
def gen_iupac_nt_input():
for code1 in iupac_code:
for code2 in iupac_code:
for code3 in iupac_code:
output_df = pd.DataFrame()
iucode = code1 + code2 + code3