def check_directory_structure(self, dirname):
"""
Assert that directory `dirname` is a properly-formatted
experiment directory.
Should have:
- a folder `typed/`
- a folder `untyped/`
- a folder `base/`
- (optional) a folder `both/`
Constraints:
- the `typed/` and `untyped/` folders should have the same
numbers of files, and matching filenames.
"""
# Ensure directories exist
base_dir = "%s/base" % dirname
un_dir = "%s/base" % dirname
ty_dir = "%s/base" % dirname
req_dirs = [base_dir, un_dir, ty_dir]
for required_dir in req_dirs:
if not os.path.isdir(required_dir):
raise ValueError("Required directory '%s' not found. Please create it." % required_dir)
both_dir = "%s/both"
if os.path.isdir(both_dir):
req_dirs.append(both_dir)
# Ensure no nested directories
for d in req_dirs:
if util.contains_any_directories(d):
raise ValueError("Directory '%s' should not contain any sub-directories, but it does. Please remove." % d)
# Ensure num. typed and num. untyped files are the same
if not(util.count_files(ty_dir) == util.count_files(un_dir)):
raise ValueError("Directories '%s' and '%s' must have the same number of files." % (un_dir, ty_dir))
# Ensure filenames in typed/untyped are the same
if not (sorted((util.get_files(un_dir))) == sorted((util.get_files(ty_dir)))):
raise ValueError("The filenames in '%s' must match the filenames in '%s', but do not. Please fix." % (un_dir, ty_dir))
return
def main():
impath = "/home/john/wsdlims_ripped/ECIR2016TurkData/screenshots" # args["ip"]
compath = "/home/john/wsdlims_ripped/ECIR2016TurkData/composites" # args["cp"]
goodUris = []
with open("gooduris_20160225.txt", "r") as read:
for uri in map(lambda line: line.rstrip("\n"), read):
goodUris.append(uri)
compisits = get_files(compath, lambda f: "allTheSame" not in f and check_if_goodURI(f, goodUris) and
"interval" not in f)
method_composites = defaultdict(dict)
for comp in sorted(compisits):
site = comp[comp.find("_") + 1:comp.rfind("_")]
method_composites[comp[:comp.index("_")]][site] = comp
# composite_only_histogram(method_composites,compath)
files = get_and_process_thumbs(impath, method_composites, goodUris)
print(type(files))
# print(method_composites)
impath += "/"
methods = {'random': MethodCompThums('random', impath, files["random"]),
'temporalInterval': MethodCompThums('temporalInterval', impath, files["temporalInterval"]),
'alSum': MethodCompThums('alSum', impath, files["alSum"])}
# thumbThumbAnalysis(methods['alSum'], methods['random'], methods['temporalInterval'])
temporalPairs(methods['alSum'], methods['random'], methods['temporalInterval'])
def clean(files=None):
"""
Cleans the given files
:param files: List of files or dict to pass to get_files for all files to run against.
"""
logger.debug("Running clean function. Files: " + str(files))
if files is None:
raise Exception("Must run clean with files")
if isinstance(files, dict):
if not os.path.exists(files['path']):
logger.debug("Clean path does not exist. Clean considered successful.")
return
files = get_files(files)
if not getattr(env, 'dry_run', False):
for path in files:
if not os.path.exists(path):
continue
if os.path.isfile(path):
os.remove(path)
else:
shutil.rmtree(path)
logger.info("Successfully cleaned {} files/folders".format(len(files)))
logger.debug("Files/Folders removed: \n" + "\n".join(files))
def get_host(PATHS):
machines = util.get_files(PATHS['MACHINE'], '*')
for n in range(len(machines)):
machines[n] = machines[n].split('/')[-1].replace('.py', '')
try:
machine = __import__(machines[n])
except ImportError:
continue
if machine.matches_host() == True:
break
del machine
try: machine
except NameError: util.warn("HOST " + os.uname()[1] + " UNKNOWN"); sys.exit()
host = machine.get_options()
# overwrite with environment variable if available
for name in HOST_OPTIONS:
env_name = get_env_name(name)
if env_name in os.environ:
util.gentle_warn(
'{} environment variable overriding {} in machine file'.format(env_name,
name)
)
host[name] = os.environ[env_name]
return host
def setup_TAC08(task):
"""
task.topic_file: xml file for TAC
task.doc_path: path containing source documents
task.manual_path: path for manual (human) summaries
"""
## get all document data
all_docs = {}
files = util.get_files(task.doc_path, r'[^_]+_[^_]+_\d+[\.\-]\d+')
sys.stderr.write('Loading [%d] files\n' %len(files))
for file in files:
id = os.path.basename(file)
all_docs[id] = file
## initialize problems
problems = []
# load XML task definition
from xml.etree import ElementTree
root = ElementTree.parse(task.topic_file).getroot()
for topic in root:
if topic.tag != "topic": continue
id = topic.attrib["id"]
title = None
narr = None
docsets = []
docset_ids = []
for node in topic:
if node.tag == "title":
title = node.text.strip()
elif node.tag == "narrative":
narr = node.text.strip()
elif node.tag == "docsetA":
documents = node.findall("doc")
docsets.append([doc.attrib["id"] for doc in documents])
docset_ids.append(node.attrib["id"])
elif node.tag == "docsetB":
documents = node.findall("doc")
docsets.append([doc.attrib["id"] for doc in documents])
docset_ids.append(node.attrib["id"])
old_docs = []
old_problems = []
for docset_index in range(len(docsets)):
## map docids to documents
new_docs = [all_docs[doc] for doc in docsets[docset_index]]
## create a SummaryProblem
problem = SummaryProblem(docset_ids[docset_index], title, narr, new_docs, old_docs, old_problems[:])
old_docs += new_docs
old_problems.append(problem)
## include training data in problem
if task.manual_path: problem._load_training(task.manual_path)
problems.append(problem)
sys.stderr.write('Setting up [%d] problems\n' %len(problems))
task.problems = problems
def add_lm_lattices(model, lattice_dir, output_dir, dict, lm):
sys.stderr.write('adding LM scores to numerator lattices\n')
## Create a config file to use with HLRescore
hlrescore_config = '%s/hlrescore.config' %output_dir
fh = open(hlrescore_config, 'w')
#fh.write('HLANGMODFILTER = "gunzip -c $.gz"\n')
fh.write('HNETFILTER = "gunzip -c < $.gz"\n')
fh.write('HNETOFILTER = "gzip -c > $.gz"\n')
fh.write('RAWMITFORMAT = T\n')
fh.write('HLRESCORE: FIXBADLATS = TRUE\n')
fh.write('HLRESCORE: STARTWORD = <s>\n')
fh.write('HLRESCORE: ENDWORD = </s>\n')
fh.close()
## HLRescore parameters
grammar_scale = 15.0
trans_penalty = 0.0
def hlrescore(input, path):
cmd = 'HLRescore -A -D -T 1 -w -c -q tvaldm -C %s' %hlrescore_config
cmd += ' -S %s' %input
cmd += ' -L %s/%s/' %(lattice_dir, path)
cmd += ' -l %s/%s/' %(output_dir, path)
cmd += ' -s %f' %grammar_scale
cmd += ' -p %f' %trans_penalty
cmd += ' -n %s' %lm
cmd += ' %s' %dict
if model.verbose > 0: cmd += ' >%s/%s.log' %(output_dir, os.path.basename(input))
return cmd
## Split up lattice list
lattice_list = '%s/lattice.list' %output_dir
fh = open(lattice_list, 'w')
remove_gz = lambda x: x.replace('.gz', '')
files = map(remove_gz, util.get_files(lattice_dir, r'.*\.lat'))
fh.write('\n'.join(files))
fh.close()
split_lattice = SplitList(output_dir, lattice_list, by_path=True)
## Create the HLRescore commands
cmds = []
inputs = split_lattice.get_files()
for input in inputs:
key = split_lattice.get_key(input)
new_output = '%s/%s' %(output_dir, key)
if not os.path.isdir(new_output): os.makedirs(new_output)
cmds.append(hlrescore(input, key))
if model.local == 1:
for cmd in cmds:
print cmd
print os.popen(cmd).read()
else:
cmds_file = '%s/hlrescore.commands' %output_dir
fh = open(cmds_file, 'w')
for cmd in cmds: fh.write('%s\n' %cmd)
fh.close()
util.run_parallel(cmds_file, model.jobs, output_dir)
def initializeAuthentication():
#If no file use default but set filename anyway so the dump function will work
for i in range(0,15):
#Gets the highest numbered of all directories that are named after floating point values(i.e. most recent timestamp)
name = util.getHighestNumberedTimeDirectory(directories.usersdir)
possibledir = os.path.join(directories.usersdir,name)
#__COMPLETE__ is a special file we write to the dump directory to show it as valid
if '''__COMPLETE__''' in util.get_files(possibledir):
try:
f = open(os.path.join(possibledir,'users.json'))
temp = json.load(f)
f.close()
except:
temp = {'users':{},'groups':{}}
global Users
Users = temp['users']
global Groups
Groups = temp['groups']
global Tokens
Tokens = {}
for user in Users:
#What an unreadable line! It turs all the dicts in Users into User() instances
Users[user] = User(Users[user])
assignNewToken(user)
generateUserPermissions()
break #We sucessfully found the latest good users.json dump! so we break the loop
else:
#If there was no flag indicating that this was an actual complete dump as opposed
#To an interruption, rename it and try again
shutil.copytree(possibledir,os.path.join(directories.usersdir,name+"INCOMPLETE"))
shutil.rmtree(possibledir)
def wsj(path_wav, path_trans, config, output, wav_list=[]):
## wav files
wav_files = set(util.get_files(path_wav, re.compile('.*\.wv1', re.IGNORECASE)))
print 'found wav files [%d]' %len(wav_files)
## filter using a wav list
keys = set()
if wav_list:
hint = path_wav.split('/')[-2]+'/'
files = os.popen('grep -i %s %s' %(hint, wav_list)).read().splitlines()
if len(files) == 0:
files = [os.path.basename(f).split('.')[0] for f in open(wav_list).read().splitlines()]
for file in files:
key = os.path.basename(file).split('.')[0].upper()
keys.add(key)
print 'found keys [%d]' %len(list(keys))
fh = open(output, 'w')
## transcription files
trans_files = util.get_files(path_trans, re.compile('.*\.dot', re.IGNORECASE))
print 'found transcription files [%d]' %len(trans_files)
unmatched = 0
for file in trans_files:
dirname = os.path.dirname(file)
for line in open(file):
line = line.strip()
ext = re.search('\([^()]*\)$', line).group()
trans = line.replace(ext, '').strip()
trans = fix_wsj_trans(trans)
ext = ext.replace('(','').replace(')','').upper()
wav_file = '%s/%s.WV1' %(dirname, ext)
if wav_file not in wav_files: wav_file = '%s/%s.wv1' %(dirname, ext.lower())
if wav_file not in wav_files:
for w in wav_files:
if ext in w or ext.lower() in w: wav_file = w
if wav_file not in wav_files:
print 'no matching wav file [%s]' %wav_file
unmatched += 1
continue
if ext in keys or len(keys)==0:
fh.write('%s %s %s\n' %(wav_file, config, trans))
fh.close()
print 'unmatched [%d]' %unmatched
def predikate(event, watcher):
if predicate and not predicate(event, watcher):
return False
if not watcher.files:
return True
files = get_files(watcher.files)
found = getattr(event, 'dest_path', None) in files
return found or event.src_path in files
def loadAll():
for i in range(0,15):
#Gets the highest numbered of all directories that are named after floating point values(i.e. most recent timestamp)
name = util.getHighestNumberedTimeDirectory(directories.persistdir)
possibledir = os.path.join(directories.persistdir,name)
#__COMPLETE__ is a special file we write to the dump directory to show it as valid
if '''__COMPLETE__''' in util.get_files(possibledir):
with persistance_dict_connection_lock:
for i in util.get_files(possibledir):
with open(os.path.join(directories.persistdir,i)) as f:
persistancedict[util.unurl(i)] = _PersistanceFile(json.load(f))
break #We sucessfully found the latest good ActiveModules dump! so we break the loop
else:
#If there was no flag indicating that this was an actual complete dump as opposed
#To an interruption, rename it and try again
shutil.copytree(possibledir,os.path.join(directories.persistdir,name+"INCOMPLETE"))
shutil.rmtree(possibledir)
def listlogdumps():
where =os.path.join(directories.logdir,'dumps')
logz = []
r = re.compile(r'^([0-9]*\.[0-9]*)\.json(\.gz|\.bz2)?$')
for i in util.get_files(where):
m = r.match(i)
if not m == None:
#Make time,fn,ext,size tuple
logz.append((float(m.groups('')[0]), os.path.join(where,i),m.groups('Uncompressed')[1],os.path.getsize(os.path.join(where,i))))
return logz
def read_sents(paths):
doc_sets = []
# multiple annotators
for path in paths:
doc_sets.append(sorted(util.get_files(path, r'.*')))
problems = []
for i in range(len(doc_sets[0])):
filenames = [doc_set[i] for doc_set in doc_sets]
read_news_doc(filenames, problems)
print 'Load %d news (BN/WN) problems' % len(problems)
return problems
def jade(files=None, obj=None, out=None, path=None, pretty=False, client=False, no_debug=False, watch=False):
"""
Compiles jade templates
:param files: List of files or dict to pass to get_files for all files to run against
:param obj: javascript options object
:param out: output the compiled html to <dir>
:param path: filename used to resolve includes
:param pretty: compile pretty html output
:param client: compile function for client-side runtime.js
:param no_debug: compile without debugging (smaller functions)
:param watch: watch files for changes and automatically re-render
"""
logger.debug("Running jade function. Files: " + str(files))
if files is None:
raise Exception("Must run jade with files")
if isinstance(files, dict):
# Some sane defaults for jade if not specified
files['only_files'] = True
if 'recursive' not in files:
files['recursive'] = True
if 'match' not in files:
files['match'] = ['*jade', ]
files = get_files(files)
compile_paths = ' '.join(['"{}"'.format(f) for f in files])
if not getattr(env, 'dry_run', False):
opts = []
if obj:
opts.append('-O "{}"'.format(obj))
if out:
opts.append('-o "{}"'.format(out))
if path:
opts.append('-p "{}"'.format(path))
if pretty:
opts.append('-P')
if client:
opts.append('-c')
if no_debug:
opts.append('-D')
if watch:
opts.append('-w')
build_run("jade {} {}".format(' '.join(opts), compile_paths),
async=watch, keep_alive=1 if watch else 0)
logger.info("Successfully compiled {} jade files".format(len(files)))
logger.debug("Files compiled: \n" + "\n".join(files))
def setup_DUC_basic(task, skip_updates=False):
"""
task.topic_file: sgml file for DUC
task.doc_path: path containing source documents
task.manual_path: path for manual (human) summaries
"""
## get all document data
all_docs = {}
files = util.get_files(task.doc_path, '\w{2,3}\d+[\.\-]\d+')
sys.stderr.write('Loading [%d] files\n' % len(files))
for file in files:
id = os.path.basename(file)
all_docs[id] = file
## initialize problems
problems = []
data = open(task.topic_file).read().replace('\n', ' ')
topics = re.findall('<topic>.+?</topic>', data)
sys.stderr.write('Setting up [%d] problems\n' % len(topics))
for topic in topics:
id = util.remove_tags(re.findall('<num>.+?</num>', topic)[0])[:-1]
title = util.remove_tags(re.findall('<title>.+?</title>', topic)[0])
narr = util.remove_tags(re.findall('<narr>.+?</narr>', topic)[0])
docsets = re.findall('<docs.*?>.+?</docs.*?>', topic)
docsets = map(util.remove_tags, docsets)
docsets = [d.split() for d in docsets]
old_docs = []
for docset_index in range(len(docsets)):
## update naming convention different from main
if len(docsets) > 1:
id_ext = '-' + 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'[docset_index]
else:
id_ext = ''
new_docs = [all_docs[doc] for doc in docsets[docset_index]]
## create a SummaryProblem
problem = SummaryProblem(id + id_ext, title, narr, new_docs,
old_docs)
old_docs += new_docs
## include training data in problem
if task.manual_path: problem._load_training(task.manual_path)
problems.append(problem)
## skip updates?
if skip_updates: break
task.problems = problems
def colorAnalysis():
impath = "/home/john/wsdlims_ripped/ECIR2016TurkData/screenshots" # args["ip"]
compath = "/home/john/wsdlims_ripped/ECIR2016TurkData/composites" # args["cp"]
goodUris = []
with open("gooduris_20160225.txt", "r") as read:
for uri in map(lambda line: line.rstrip("\n"), read):
goodUris.append(uri)
compisits = get_files(compath, lambda f: "allTheSame" not in f and check_if_goodURI(f, goodUris) and
"interval" not in f)
method_composites = defaultdict(dict)
for comp in sorted(compisits):
site = comp[comp.find("_") + 1:comp.rfind("_")]
method_composites[comp[:comp.index("_")]][site] = comp
# composite_only_histogram(method_composites,compath)
files = get_and_process_thumbs(impath, method_composites, goodUris)
print(type(files))
# print(method_composites)
impath += "/"
methods = {'random': MethodCompThums('random', impath, files["random"]),
'temporalInterval': MethodCompThums('temporalInterval', impath, files["temporalInterval"]),
'alSum': MethodCompThums('alSum', impath, files["alSum"])} # type: dict[str,MethodCompThums]
alsum = methods['alSum']
out = {} # type: dict[str,dict[str,CompositeColorResulst]]
for mname, method in methods.items():
print(mname,method)
dcm = method.get_composite_dom_colors()
out[mname] = dcm
try:
with open("colorResults2.json","w+") as wout:
wout.write(json.dumps(out,indent=1,default=lambda x:x.to_jdic()))
except TypeError as e:
print("Wow bad thing happened",e)
for k,v in out.items():
print("+++++++++++++++++++++++++++++++++++++++++++++++++")
print(k)
for site,ret in v.items():
print("site: ",site)
for date,color in ret.results.items():
print(date,''.join(color))
def coffee(files=None, bare=False, lint=False, map=False, join=None, output=None, watch=False):
"""
Compiles coffeescript files
:param files: List of files or dict to pass to get_files for all files to run against
:param bare: output bare coffeescript
:param lint: run through jslint
:param map: generate source maps
:param join: join together files to this output location (string path)
:param output: directory to output files
:param watch: True to watch the output and recompile on changes
"""
logger.debug("Running coffee function. Files: " + str(files))
if files is None:
raise Exception("Must run coffee with files")
if isinstance(files, dict):
# Some sane defaults for coffeescript if not specified
files['only_files'] = True
if 'recursive' not in files:
files['recursive'] = True
if 'match' not in files:
files['match'] = ['*coffee', ]
files = get_files(files)
compile_paths = ' '.join(['"{}"'.format(f) for f in files])
if not getattr(env, 'dry_run', False):
opts = []
if bare:
opts.append('-b')
if join:
opts.append('-j "{}"'.format(join))
if lint:
opts.append('-l')
if map:
opts.append('-m')
if watch:
opts.append('-w')
if output:
opts.append('-o "{}"'.format(output))
build_run("coffee {} -c {}".format(' '.join(opts), compile_paths),
async=watch, keep_alive=1 if watch else 0)
logger.info("Successfully compiled {} coffeescript files".format(len(files)))
logger.debug("Files compiled: \n" + "\n".join(files))
def parse_user_verify_files():
files = get_files("E:/取证/05.案件支持/上海/青浦反诈/dibaqu/第八区/实名认证", [])
# 循环打印get_files函数返回的文件名列表
count = 0
user_infos = []
for file in sorted(files):
# if file.find('1414.html') > 0:
print(file)
count = count + 1
print(count)
parse_html(file, user_infos)
# write_to_excel(file, app_infos)
return user_infos
def setup_DUC_basic(task, skip_updates=False):
"""
task.topic_file: sgml file for DUC
task.doc_path: path containing source documents
task.manual_path: path for manual (human) summaries
"""
## get all document data
all_docs = {}
files = util.get_files(task.doc_path, '\w{2,3}\d+[\.\-]\d+')
sys.stderr.write('Loading [%d] files\n' %len(files))
for file in files:
id = os.path.basename(file)
all_docs[id] = file
## initialize problems
problems = []
data = open(task.topic_file).read().replace('\n', ' ')
topics = re.findall('<topic>.+?</topic>', data)
sys.stderr.write('Setting up [%d] problems\n' %len(topics))
for topic in topics:
id = util.remove_tags(re.findall('<num>.+?</num>', topic)[0])[:-1]
title = util.remove_tags(re.findall('<title>.+?</title>', topic)[0])
narr = util.remove_tags(re.findall('<narr>.+?</narr>', topic)[0])
docsets = re.findall('<docs.*?>.+?</docs.*?>', topic)
docsets = map(util.remove_tags, docsets)
docsets = [d.split() for d in docsets]
old_docs = []
for docset_index in range(len(docsets)):
## update naming convention different from main
if len(docsets) > 1: id_ext = '-' + 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'[docset_index]
else: id_ext = ''
new_docs = [all_docs[doc] for doc in docsets[docset_index]]
## create a SummaryProblem
problem = SummaryProblem(id+id_ext, title, narr, new_docs, old_docs)
old_docs += new_docs
## include training data in problem
if task.manual_path: problem._load_training(task.manual_path)
problems.append(problem)
## skip updates?
if skip_updates: break
task.problems = problems
def create_background_dataset(dir, target, ext='jpg', type='otsu'):
from util import get_files
if not os.path.isdir(target):
os.mkdir(target)
for src, fname in get_files(dir, ext=ext):
print src
if type == 'otsu':
bg_file = get_background_otsu(src)
else:
bg_file = get_background_sauvola(src)
f_bg = os.path.join(target, fname)
imsave(f_bg, bg_file)
def align_mappy(dir_in, file_out, file_fasta):
a = mp.Aligner(file_fasta, preset='map-ont') # Load or build index
if not a:
raise Exception("ERROR: failed to load/build index")
reads = get_files(dir_in)
files_fastq = {}
data = []
for read in tqdm(reads):
with h5py.File(read, 'r', libver='latest') as fd:
no_alignment = True
fastq = read_fastq(fd)
files_fastq[fastq.id] = len(fastq.seq)
for hit in a.map(fastq.seq): # Traverse alignments
if hit.is_primary: # Check if the alignment is primary
# Reference
for seq_record in SeqIO.parse(file_fasta, 'fasta'):
ref = seq_record.seq[hit.r_st:hit.r_en]
r_CG_num = len(re.findall(r'(CG)', str(ref)))
# Query
query = fastq.seq[hit.q_st:hit.q_en]
if hit.strand == -1:
query = mp.revcomp(query)
q_CG_num = len(re.findall(r'(CG)', str(query)))
no_alignment = False
data.append([
fastq.id, hit.r_st, hit.r_en, hit.q_st, hit.q_en,
r_CG_num, q_CG_num, hit.cigar_str
])
break
if no_alignment:
data.append([fastq.id, '', '', '', '', 0, 0, ''])
data = pd.DataFrame(data,
columns=[
'read_id', 'r_st', 'r_en', 'q_st', 'q_en',
'r_CG_num', 'q_CG_num', 'cigar_str'
])
data.sort_values('read_id', inplace=True)
data.to_csv(file_out, index=False)
print("Average length of fastq files:",
sum(files_fastq.values()) / len(files_fastq.values()))
def loadAll():
for i in range(0,15):
#Gets the highest numbered of all directories that are named after floating point values(i.e. most recent timestamp)
name = util.getHighestNumberedTimeDirectory(directories.moduledir)
possibledir = os.path.join(directories.moduledir,name)
#__COMPLETE__ is a special file we write to the dump directory to show it as valid
if '''__COMPLETE__''' in util.get_files(possibledir):
loadModules(possibledir)
auth.importPermissionsFromModules()
break #We sucessfully found the latest good ActiveModules dump! so we break the loop
else:
#If there was no flag indicating that this was an actual complete dump as opposed
#To an interruption, rename it and try again
shutil.copytree(possibledir,os.path.join(directories.moduledir,name+"INCOMPLETE"))
shutil.rmtree(possibledir)
def loadModule(moduledir,path_to_module_folder):
with modulesLock:
#Make an empty dict to hold the module resources
module = {}
#Iterate over all resource files and load them
for i in util.get_files(os.path.join(path_to_module_folder,moduledir)):
try:
f = open(os.path.join(path_to_module_folder,moduledir,i))
#Load the resource and add it to the dict. Resouce names are urlencodes in filenames.
module[unurl(i)] = json.load(f)
finally:
f.close()
name = unurl(moduledir)
ActiveModules[name] = module
bookkeeponemodule(name)
def analyse_CG(dir_in, file_out, file_fasta):
a = mp.Aligner(file_fasta, preset='map-ont') # Load or build index
if not a:
raise Exception("ERROR: failed to load/build index")
reads = get_files(dir_in)
data = []
for read in tqdm(reads):
with h5py.File(read, 'r', libver='latest') as fd:
matches = {'M': 0, 'X': 0, 'D': 0, 'I': 0}
CG_cnt = {'M': 0, 'X': 0, 'D': 0, 'I': 0}
fastq = read_fastq(fd)
ref = ''
mapq = 0
for hit in a.map(fastq.seq, cs=True): # Traverse alignments
if hit.is_primary: # Check if the alignment is primary
# Alignment
matches = count_matches(hit.cs)
# Reference
for seq_record in SeqIO.parse(file_fasta, 'fasta'):
ref = seq_record.seq[hit.r_st: hit.r_en]
# Query
query = fastq.seq[hit.q_st: hit.q_en]
if hit.strand == -1:
query = mp.revcomp(query)
# Normalize
ref, query = normalize(ref, query, hit.cigar_str)
# Analyse CG motif
CG_cnt = count_CG(ref, query)
mapq = hit.mapq
break
data.append([fastq.id, len(ref), matches['M'], matches['X'], matches['D'], matches['I'],
CG_cnt['M'], CG_cnt['X'], CG_cnt['D'], CG_cnt['I'], mapq])
data = pd.DataFrame(data, columns=['read_id', 'alignment_len', 'M', 'X', 'D', 'I',
'M_CG', 'X_CG', 'D_CG', 'I_CG', 'mapq'])
data.sort_values('read_id', inplace=True)
data.to_csv(file_out, index=False)
def test_get_files(self):
paths = get_files(dict(path='/tmp/test_fab_build/', recursive=False))
expected = ['/tmp/test_fab_build/test.txt',
'/tmp/test_fab_build/test.py',
'/tmp/test_fab_build/coffee',
'/tmp/test_fab_build/1']
self.assertItemsEqual(paths, expected)
paths = get_files(dict(path='/tmp/test_fab_build/', match=["*.py",], recursive=False))
expected = ['/tmp/test_fab_build/test.py']
self.assertItemsEqual(paths, expected)
paths = get_files(dict(path='/tmp/test_fab_build/', ignore=["*.py",], recursive=False))
expected = ['/tmp/test_fab_build/test.txt',
'/tmp/test_fab_build/coffee',
'/tmp/test_fab_build/1']
self.assertItemsEqual(paths, expected)
paths = get_files(dict(path='/tmp/test_fab_build/', only_files=True, recursive=False))
expected = ['/tmp/test_fab_build/test.txt',
'/tmp/test_fab_build/test.py']
self.assertItemsEqual(paths, expected)
paths = get_files(dict(path='/tmp/test_fab_build/'))
expected = [
'/tmp/test_fab_build/1',
'/tmp/test_fab_build/1/2',
'/tmp/test_fab_build/1/2/3',
'/tmp/test_fab_build/1/test',
'/tmp/test_fab_build/test.txt',
'/tmp/test_fab_build/test.py',
'/tmp/test_fab_build/1/one.py',
'/tmp/test_fab_build/1/2/two.py',
'/tmp/test_fab_build/coffee',
'/tmp/test_fab_build/coffee/test1.coffee',
'/tmp/test_fab_build/coffee/test2.coffee',
'/tmp/test_fab_build/coffee/test3.coffee',
'/tmp/test_fab_build/1/2/3/three.py'
]
self.assertItemsEqual(paths, expected)
paths = get_files(dict(path='/tmp/test_fab_build/', recursive=True, only_files=True))
expected = [
'/tmp/test_fab_build/test.txt',
'/tmp/test_fab_build/test.py',
'/tmp/test_fab_build/1/one.py',
'/tmp/test_fab_build/1/2/two.py',
'/tmp/test_fab_build/1/2/3/three.py',
'/tmp/test_fab_build/coffee/test1.coffee',
'/tmp/test_fab_build/coffee/test2.coffee',
'/tmp/test_fab_build/coffee/test3.coffee'
]
self.assertItemsEqual(paths, expected)
def timit(path_wav, path_trans, output, config, test_speakers=None):
## transcription files
trans_files = [f for f in util.get_files(path_trans, re.compile('\.txt', re.IGNORECASE)) if '/si' in f or '/sx' in f]
if test_speakers != None:
trans_files = [f for f in trans_files if f.split('/')[-2][1:] in test_speakers]
print 'found transcription files [%d]' %len(trans_files)
fh = open(output, 'w')
for trans_file in trans_files:
wav_file = trans_file.replace('.txt', '.wav')
if not os.path.isfile(wav_file): continue
trans = open(trans_file).read().lower()
trans = ' '.join(trans.split()[2:])
trans = re.sub('[^a-z ]', '', trans)
fh.write('%s %s %s\n' %(wav_file, config, trans))
fh.close()
def loadModule(moduledir, path_to_module_folder):
with modulesLock:
#Make an empty dict to hold the module resources
module = {}
#Iterate over all resource files and load them
for i in util.get_files(os.path.join(path_to_module_folder,
moduledir)):
try:
f = open(os.path.join(path_to_module_folder, moduledir, i))
#Load the resource and add it to the dict. Resouce names are urlencodes in filenames.
module[unurl(i)] = json.load(f)
finally:
f.close()
name = unurl(moduledir)
ActiveModules[name] = module
bookkeeponemodule(name)
def loadAll():
for i in range(0, 15):
#Gets the highest numbered of all directories that are named after floating point values(i.e. most recent timestamp)
name = util.getHighestNumberedTimeDirectory(directories.moduledir)
possibledir = os.path.join(directories.moduledir, name)
#__COMPLETE__ is a special file we write to the dump directory to show it as valid
if '''__COMPLETE__''' in util.get_files(possibledir):
loadModules(possibledir)
auth.importPermissionsFromModules()
break #We sucessfully found the latest good ActiveModules dump! so we break the loop
else:
#If there was no flag indicating that this was an actual complete dump as opposed
#To an interruption, rename it and try again
shutil.copytree(
possibledir,
os.path.join(directories.moduledir, name + "INCOMPLETE"))
shutil.rmtree(possibledir)
def start(file_path_in, file_name_need_contain):
"""
得到该文件夹下的所有包含指定字符串的html文件,并解析出每个文件中的链接,而后进行get请求,请求完后再解析
:param file_path_in:
:param file_name_need_contain:
:return:
"""
fs = util.get_files(file_path_in, file_name_need_contain)
for f in fs:
rf = util.open_file_r(f) # 打开文件流
if rf == -1:
continue
html_s = rf.read() # 读取该文件, html文件
rf.close()
urls = list(set(get_navigation_req(html_s))) # 解析出链接
for url in urls:
print(url)
res = req_res(url)
parse_result.parser(res)
def get_rulesets(ruledir, recurse):
"""
List of ruleset objects extracted from the yaml directory
"""
if os.path.isdir(ruledir) and recurse:
yaml_files = []
for root, dirs, files in os.walk(ruledir):
for name in files:
filename, file_extension = os.path.splitext(name)
if file_extension == '.yaml':
yaml_files.append(os.path.join(root, name))
if os.path.isdir(ruledir) and not recurse:
yaml_files = util.get_files(ruledir, 'yaml')
elif os.path.isfile(ruledir):
yaml_files = [ruledir]
extracted_files = util.extract_yaml(yaml_files)
rulesets = []
for extracted_yaml in extracted_files:
rulesets.append(ruleset.Ruleset(extracted_yaml))
return rulesets
def get_mapqs(dir_in, file_fasta):
a = mp.Aligner(file_fasta, preset='map-ont') # Load or build index
if not a:
raise Exception("ERROR: failed to load/build index")
reads = get_files(dir_in)
mapqs = []
for read in tqdm(reads):
with h5py.File(read, 'r', libver='latest') as fd:
fastq = read_fastq(fd)
mapq = 0
for hit in a.map(fastq.seq): # Traverse alignments
if hit.is_primary: # Check if the alignment is primary
mapq = hit.mapq
break
mapqs.append(mapq)
return mapqs
def long():
impath = "/home/john/wsdlims_ripped/ECIR2016TurkData/screenshots" # args["ip"]
compath = "/home/john/wsdlims_ripped/ECIR2016TurkData/composites" # args["cp"]
goodUris = []
origuris = []
with open("gooduris_20160225.txt", "r") as read:
for uri in map(lambda line: line.rstrip("\n"), read):
goodUris.append(uri)
with open("origuris.txt", "r") as read:
for uri in map(lambda line: line.rstrip("\n"), read):
origuris.append(uri)
compisits = get_files(impath, lambda f: filterASI(f) and check_if_goodURI(f, goodUris))
useragent = 'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:44.0) Gecko/20100101 Firefox/44.01'
session = requests.Session()
session.headers.update({'User-Agent': useragent})
got = {}
gotURIs = []
with open("tms2.json", "w+") as out:
out.write("{ tms:[")
for it in sorted(origuris):
# tm = TimeMap("www.%s"%it)
# print(tm.mementos)
request = session.get("http://web.archive.org/web/timemap/json/www.%s" % it)
# got[it] = {"tmuri":"http://web.archive.org/web/timemap/json/www.%s"%it,'uri':it,"tms":json.loads(
# request.text)}
try:
got = json.loads(request.text)
jsn = json.dumps(got)
print(jsn + "\n")
out.write("[" + jsn + "],\n")
gotURIs.append(it)
except ValueError:
print(request.text)
print(request.headers)
print("\n\n")
session.close()
def run(p_method, p_normalise = True, p_reverse_results = True):
all_dirs = current.train + [current.test]
for d in all_dirs:
vectors[d] = {}
util.read_files(util.get_files(dataset.DATA_DIRECTORY + d), d, vectors)
if p_normalise:
util.normalise(vectors)
if p_method == Method.DOT_PRODUCT:
dot.compute_dot_product(current, vectors, results)
elif p_method == Method.DIRICHLET:
bayes.calculate(current, vectors, results)
elif p_method == Method.DIFFERENCE:
dot.compute_difference(current, vectors, results)
elif p_method == Method.PEARSON:
pearson.compute(current, vectors, results)
#bayes.cal(current, vectors, results)
util.print_results(results, p_reverse_results, decimal_numbers)
def run(p_method, p_normalise=True, p_reverse_results=True):
all_dirs = current.train + [current.test]
for d in all_dirs:
vectors[d] = {}
util.read_files(util.get_files(dataset.DATA_DIRECTORY + d), d, vectors)
if p_normalise:
util.normalise(vectors)
if p_method == Method.DOT_PRODUCT:
dot.compute_dot_product(current, vectors, results)
elif p_method == Method.DIRICHLET:
bayes.calculate(current, vectors, results)
elif p_method == Method.DIFFERENCE:
dot.compute_difference(current, vectors, results)
elif p_method == Method.PEARSON:
pearson.compute(current, vectors, results)
#bayes.cal(current, vectors, results)
util.print_results(results, p_reverse_results, decimal_numbers)
def concat(files=None, output=None, banner=None, line_sep=None, clean=True):
"""
Concatenates together files and writes them to output
:param files: List of files or dict to pass to get_files for all files to run against
:param output: the location to output the resulting file
:param banner: A top banner string to add to the file
:param line_sep: The character with which the files will be concatenated
:param clean: If True, removes the output file before running concat.
"""
logger.debug("Running concat function. Files: " + str(files))
if files is None or output is None:
raise Exception("Must run concat with files and output location")
if clean and os.path.exists(output):
os.remove(output)
line_sep = line_sep or "\n"
files = get_files(files)
if not getattr(env, 'dry_run', False):
out_data = banner or ""
for path in files:
if not os.path.exists(path) or not os.path.isfile(path):
continue
with open(path, 'r') as f:
out_data = line_sep.join([out_data, f.read()])
with open(output, 'w') as f:
f.write(out_data)
logger.info("Successfully concatenated {} files/folders to {}".format(len(files), output))
logger.debug("Files/Folders concatenated: \n" + "\n".join(files))
def fisher(path_wav, path_trans, output):
## transcription files
trans_files = util.get_files(path_trans, re.compile('\.txt', re.IGNORECASE))
trans_files = [f for f in trans_files if 'bbn' not in f]
#print 'found transcription files [%d]' %len(trans_files)
fh = open(output, 'w')
file_count = 0
token_count = 0
word_list = set()
for file in trans_files:
file_count += 1
if file_count % 100 == 0: print 'transcription files processed [%d]' %file_count
id = os.path.basename(file).replace('.txt', '')
for line in open(file):
line = line.strip()
if not line: continue
if line.startswith('#'): continue
words = map(str.upper, ' '.join(line.split(':')[1:]).split())
if not words: continue
fh.write(' '.join(words) + '\n')
fh.close()
def setup_TAC08(task):
"""
task.topic_file: xml file for TAC
task.doc_path: path containing source documents
task.manual_path: path for manual (human) summaries
"""
## get all document data
all_docs = {}
files = util.get_files(task.doc_path, r'[^_]+_[^_]+_\d+[\.\-]\d+')
sys.stderr.write('Loading [%d] files\n' % len(files))
for file in files:
id = os.path.basename(file)
all_docs[id] = file
## initialize problems
problems = []
# load XML task definition
from xml.etree import ElementTree
root = ElementTree.parse(task.topic_file).getroot()
for topic in root:
if topic.tag != "topic": continue
id = topic.attrib["id"]
title = None
narr = None
docsets = []
docset_ids = []
for node in topic:
if node.tag == "title":
title = node.text.strip()
elif node.tag == "narrative":
narr = node.text.strip()
elif node.tag == "docsetA":
documents = node.findall("doc")
docsets.append([doc.attrib["id"] for doc in documents])
docset_ids.append(node.attrib["id"])
elif node.tag == "docsetB":
documents = node.findall("doc")
docsets.append([doc.attrib["id"] for doc in documents])
docset_ids.append(node.attrib["id"])
old_docs = []
old_problems = []
for docset_index in range(len(docsets)):
## map docids to documents
new_docs = [all_docs[doc] for doc in docsets[docset_index]]
## create a SummaryProblem
problem = SummaryProblem(docset_ids[docset_index], title, narr,
new_docs, old_docs, old_problems[:])
old_docs += new_docs
old_problems.append(problem)
## include training data in problem
if task.manual_path: problem._load_training(task.manual_path)
problems.append(problem)
sys.stderr.write('Setting up [%d] problems\n' % len(problems))
task.problems = problems
def build(PROBLEM, PATHS):
print("")
print("********************************************************************************")
print("")
print(" BHLIGHT BUILD SCRIPT")
print("")
print(" OPTIONS:")
print(" -help (print this message and exit)")
print(" -debug (use debug compile params)")
print(" -force (do not abort upon compile-time warnings/errors)")
print(" -noclean (do not delete old source files)")
print(" -noparam (do not create new parameter file)")
print(" -dir /path/to/target (create target dir and build there)")
print("")
print("********************************************************************************")
print("")
if is_user_help():
sys.exit()
# PROCESS USER INPUT
DEBUG = is_user_debug()
FORCE = is_user_force()
MOVEEXEC = set_dirs(PATHS)
NOPARAM = is_user_noparam()
NOCLEAN = is_user_noclean()
CLEAN = not NOCLEAN
WRITE_PARAM = not NOPARAM
KEEP_SRC = '-src' in sys.argv
REMOVE_SRC = not KEEP_SRC
# get version
VERSION = get_version()
# PRINT TO TERMINAL AND LOGFILE
LOGFILE = os.path.join(PATHS['BUILD'], 'log_build')
util.log_output(sys, LOGFILE)
# SEARCH FOR MACHINE
host = get_host(PATHS)
if DEBUG and 'DEBUG_FLAGS' not in host.keys():
util.warn("Debug compiler options not set! Using normal compiler flags.")
host['DEBUG_FLAGS'] = host['COMPILER_FLAGS']
C_FLAGS = '-std=c99 '
if 'MEM_MODEL' in host:
C_FLAGS += "-mcmodel=" + host['MEM_MODEL'] + ' '
else:
C_FLAGS += "-mcmodel=medium "
if DEBUG:
C_FLAGS += host['DEBUG_FLAGS']
else:
C_FLAGS += host['COMPILER_FLAGS']
# MATH AND DYNAMIC LINKING
LIB_FLAGS = '-lm -ldl'
LIBRARIES = ''
INCLUDES = ''
# GSL
if 'GSL_DIR' not in host:
host['GSL_DIR'] = ''
host['GSL_DIR'] = util.sanitize_path(host['GSL_DIR'])
LIB_FLAGS += (' -lgsl -lgslcblas'
+ ' -Wl,-rpath='
+ host['GSL_DIR'] + 'lib/')
LIBRARIES += '-L' + host['GSL_DIR'] + 'lib/'
INCLUDES += '-I' + host['GSL_DIR'] + 'include/'
# MPI
if 'MPI_DIR' in host:
host['MPI_DIR'] = util.sanitize_path(host['MPI_DIR'])
LIB_FLAGS += (' -Wl,-rpath='
+ host['MPI_DIR'] + 'lib/')
LIBRARIES += ' -L' + host['MPI_DIR'] + 'lib/'
INCLUDES += ' -I' + host['MPI_DIR'] + 'include/'
# HDF5
if 'HDF5_DIR' in host:
host['HDF5_DIR'] = util.sanitize_path(host['HDF5_DIR'])
LIB_FLAGS += (' -lhdf5_hl -lhdf5'
+' -Wl,-rpath='
+ host['HDF5_DIR'] + 'lib/')
LIBRARIES += ' -L' + host['HDF5_DIR'] + 'lib/'
INCLUDES += ' -I' + host['HDF5_DIR'] + 'include/'
print(" CONFIGURATION\n")
set_cparm("VERSION", '"{}"'.format(VERSION))
print_config("VERSION", VERSION)
print_config("MACHINE", host['NAME'])
print_config("PROBLEM", PROBLEM)
print_config("BUILD DIR", PATHS['BUILD'])
print_config("COMPILER", host['COMPILER'])
print_config("GSL_DIR", host['GSL_DIR'])
if 'MPI_DIR' in host:
print_config("MPI_DIR", host['MPI_DIR'])
if 'HDF5_DIR' in host:
print_config("HDF5_DIR", host['HDF5_DIR'])
if 'EXECUTABLE' in host:
print_config("EXECUTABLE", host['EXECUTABLE'])
if 'MPI_EXECUTABLE' in host:
print_config("MPI_EXECUTABLE", host['MPI_EXECUTABLE'])
print_config("C_FLAGS", C_FLAGS)
print_config("LIB_FLAGS", LIB_FLAGS)
print_config("LIBRARIES", LIBRARIES)
print_config("INCLUDES", INCLUDES)
print_config("OPENMP", CPARMS['OPENMP'])
print("\n COMPILE-TIME PARAMETERS\n")
print_config("N1TOT", CPARMS['N1TOT'])
print_config("N2TOT", CPARMS['N2TOT'])
print_config("N3TOT", CPARMS['N3TOT'])
print_config("N1CPU", CPARMS['N1CPU'])
print_config("N2CPU", CPARMS['N2CPU'])
print_config("N3CPU", CPARMS['N3CPU'])
print_config("METRIC", CPARMS['METRIC'])
print_config("RECONSTRUCTION", CPARMS['RECONSTRUCTION'])
if util.parm_is_active(CPARMS, 'EOS'):
print_config("EOS", CPARMS['EOS'])
else:
set_cparm("EOS", 'EOS_TYPE_GAMMA')
if util.parm_is_active(CPARMS, 'RADIATION'):
print_config("RADIATION", CPARMS['RADIATION'])
if util.parm_is_active(CPARMS, 'NU_BINS'):
print_config('NU_BINS', CPARMS['NU_BINS'])
else:
set_cparm("NU_BINS", 200)
if util.parm_is_active(CPARMS, 'NTH'):
print_config("NTH", CPARMS["NTH"])
else:
set_cparm("NTH", 8)
if util.parm_is_active(CPARMS, 'NPHI'):
print_config("NPHI", CPARMS["NPHI"])
else:
set_cparm("NPHI", 8)
if util.parm_is_active(CPARMS, "NU_BINS_SPEC"):
print_config("NU_BINS_SPEC", CPARMS["NU_BINS_SPEC"])
else:
set_cparm("NU_BINS_SPEC", 200)
if util.parm_is_active(CPARMS, "BURROWS_OPACITIES"):
print_config("BURROWS_OPACITIES", CPARMS["BURROWS_OPACITIES"])
else:
set_cparm("BURROWS_OPACITIES", 0)
if util.parm_is_active(CPARMS, "HDF5_OPACITIES"):
print_config("HDF5_OPACITIES", CPARMS["HDF5_OPACITIES"])
else:
set_cparm("HDF5_OPACITIES", 0)
else:
set_cparm("RADIATION", 0)
if util.parm_is_active(CPARMS, 'ELECTRONS'):
print_config("ELECTRONS", CPARMS['ELECTRONS'])
else:
set_cparm("ELECTRONS", 0)
if util.parm_is_active(CPARMS,'NVAR_PASSIVE'):
print_config("NVAR_PASSIVE", CPARMS["NVAR_PASSIVE"])
else:
set_cparm("NVAR_PASSIVE", 0)
if util.parm_is_active(CPARMS, 'GAMMA_FALLBACK'):
print_config('GAMMA_FALLBACK', CPARMS['GAMMA_FALLBACK'])
else:
set_cparm('GAMMA_FALLBACK', 0)
if util.parm_is_active(CPARMS, 'EXIT_ON_INIT'):
print_config('EXIT_ON_INIT', CPARMS['EXIT_ON_INIT'])
else:
set_cparm('EXIT_ON_INIT', 0)
if util.parm_is_active(CPARMS, 'OUTPUT_EOSVARS'):
print_config("OUTPUT_EOSVARS", CPARMS["OUTPUT_EOSVARS"])
else:
set_cparm("OUTPUT_EOSVARS", 0)
if CPARMS['RADIATION']:
if 'EXPTAU_WEIGHTS' in CPARMS.keys():
print_config('EXPTAU_WEIGHTS', CPARMS['EXPTAU_WEIGHTS'])
else:
set_cparm('EXPTAU_WEIGHTS', 1)
if util.parm_is_active(CPARMS,'ELECTRONS')\
and CPARMS['EOS'] != 'EOS_TYPE_GAMMA':
raise ValueError("ELECTRONS only compatible with Gamma law EOS.\n"
+"Please set EOS = EOS_TYPE_GAMMA.\n")
if CPARMS['EOS'] == 'EOS_TYPE_TABLE' and CPARMS['NVAR_PASSIVE'] < 2:
raise ValueError("Tabulated EOS requires at least two passive scalars\n"
+"for the electron fraction Ye.\n"
+"Please set NVAR_PASSIVE >= 2\n"
+"and ensure your problem generator sets it appropriately.\n")
if CPARMS['EOS'] == 'EOS_TYPE_TABLE' \
and CPARMS['METRIC'] == 'MKS' \
and CPARMS['NVAR_PASSIVE'] < 3:
raise ValueError("Tabulated EOS and MKS metric requires at least three\n"
+"passive scalars, for Ye and atmosphere markers.\n"
+"Please set NVAR_PASSIVE >= 3\n"
+"and ensure your problem generator sets it appropriately.\n")
if util.parm_is_active(CPARMS,'ESTIMATE_THETAE') \
and (CPARMS['RADIATION'] == 'RADTYPE_NEUTRINOS'):
raise ValueError("Neutrinos not compatible "
+"with estimating electron temperature.")
if CPARMS['EOS'] == 'EOS_TYPE_POLYTROPE':
util.gentle_warn("The polytropic EOS is totally untested. "
+"Use at your own risk!\n")
if CPARMS['EOS'] != 'EOS_TYPE_GAMMA' and not CPARMS['OUTPUT_EOSVARS']:
util.gentle_warn("Setting OUTPUT_EOSVARS = True.")
set_cparm("OUTPUT_EOSVARS", 1)
print_config("OUTPUT_EOSVARS", CPARMS["OUTPUT_EOSVARS"])
NEED_UNITS = (util.parm_is_active(CPARMS, 'RADIATION') or
util.parm_is_active(CPARMS, 'COULOMB') or
CPARMS['EOS'] == 'EOS_TYPE_TABLE')
if util.parm_is_active(CPARMS, 'FLATEMISS'):
if not util.parm_is_active(CPARMS, 'EMISSTYPE_FLAT'):
util.gentle_warn("Flatemiss active, but not emission type.\n"
+"Setting EMISSTYPE_FLAT = ANTINU_ELECTRON.\n")
set_cparm("EMISSTYPE_FLAT", "ANTINU_ELECTRON")
if util.parm_is_active(CPARMS, 'RADIATION') \
and 'X1R_RAD_BOUND' in CPARMS.keys():
if CPARMS['X1R_RAD_BOUND'] == 'BC_CAMERA' \
and CPARMS['METRIC'] == 'MINKOWSKI':
util.warn("X1R_RAD_BOUND BC_CAMERA is "
+"not supported for Minkowski metrics.")
print("\n EXTRA PARAMETERS\n")
for k,v in REPVARS.items():
print_config(k,v)
# Set core runtime parameters
set_rparm('tf', 'double')
set_rparm('dt', 'double')
if CPARMS['METRIC'] == 'MINKOWSKI':
set_rparm('x1Min', 'double', default = 0.)
set_rparm('x1Max', 'double', default = 1.)
set_rparm('x2Min', 'double', default = 0.)
set_rparm('x2Max', 'double', default = 1.)
set_rparm('x3Min', 'double', default = 0.)
set_rparm('x3Max', 'double', default = 1.)
if CPARMS['METRIC'] == 'MKS':
set_rparm('a', 'double', default = 0.5)
set_rparm('hslope', 'double', default = 0.3)
set_rparm('poly_xt', 'double', default = 0.82)
set_rparm('poly_alpha', 'double', default = 14.)
set_rparm('mks_smooth', 'double', default = 0.5)
set_rparm('Rout', 'double', default = 40.)
set_rparm('Rout_vis', 'double', default = 40.)
#if util.parm_is_active(CPARMS, 'RADIATION'):
# set_rparm('Rout_rad', 'double')
if NEED_UNITS:
if CPARMS['METRIC'] == 'MINKOWSKI':
set_rparm('L_unit', 'double')
set_rparm('M_unit', 'double')
if CPARMS['METRIC'] == 'MKS':
set_rparm('M_unit', 'double')
set_rparm('mbh', 'double', default = 1.989e34)
if CPARMS['EOS'] == 'EOS_TYPE_GAMMA':
set_rparm('gam', 'double', default = 5./3.)
set_rparm('cour', 'double', default = 0.9)
if util.parm_is_active(CPARMS, 'RADIATION'):
set_rparm('cour_cool', 'double', default = 0.25)
if util.parm_is_active(CPARMS, 'ELECTRONS'):
set_rparm('game', 'double', default = 4./3.)
set_rparm('gamp', 'double', default = 5./3.)
set_rparm('fel0', 'double', default = 0.01)
set_rparm('tptemin', 'double', default = 1.e-3)
set_rparm('tptemax', 'double', default = 1.e3)
if util.parm_is_active(CPARMS, 'RADIATION'):
if not util.parm_is_active(CPARMS, 'ELECTRONS'):
set_rparm('tp_over_te', 'double', default = 1.)
set_rparm('nph_per_proc', 'double', default = 1.e5)
set_rparm('numin', 'double', default = 1.e8)
set_rparm('numax', 'double', default = 1.e20)
set_rparm('tune_emiss', 'double', default = 1.)
set_rparm('tune_scatt', 'double', default = 1.)
set_rparm('t0_tune_emiss', 'double', default = -1.)
set_rparm('t0_tune_scatt', 'double', default = -1.)
set_rparm('thetae_max', 'double', default = 1.e3)
set_rparm('sigma_max', 'double', default = 1.)
set_rparm('kdotk_tol', 'double', default = 1.e-6)
set_rparm('Nph_to_track', 'double', default = 0.);
set_rparm('thbin', 'int', default = 8);
set_rparm('phibin', 'int', default = 8);
if util.parm_is_active(CPARMS, 'FLATEMISS'):
set_rparm('cnu_flat', 'double', default = 1.)
set_rparm('init_from_grmhd', 'string', default = 'No')
set_rparm('DTd', 'double', default = 0.5)
set_rparm('DTl', 'double', default = 0.1)
set_rparm('DTr', 'double', default = 1000.)
set_rparm('DNr', 'integer', default = 1024)
set_rparm('DTp', 'integer', default = 100)
set_rparm('DTf', 'integer', default = 1)
set_rparm('outputdir', 'string', default = './')
# some fixes for fortran compilation
USE_FORTRAN = util.parm_is_active(CPARMS,'BURROWS_OPACITIES')
FORT_USE_MPI = (CPARMS['N1CPU'] > 1
or CPARMS['N2CPU'] > 1
or CPARMS['N3CPU'] > 1)
FORT_USE_MPI_STR = 'TRUE' if FORT_USE_MPI else 'FALSE'
if CPARMS['N1TOT'] > 1 and CPARMS['N2TOT'] > 1 and CPARMS['N2TOT'] > 1:
FORT_NDIM=3
elif ((CPARMS['N1TOT'] > 1 and CPARMS['N2TOT'] > 1)
or (CPARMS['N1TOT'] > 1 and CPARMS['N3TOT'] > 1)
or (CPARMS['N2TOT'] > 1 and CPARMS['N3TOT'] > 1)):
FORT_NDIM=2
else:
FORT_NDIM=1
if USE_FORTRAN:
# -lgfortran for gcc -lifcore -limf for icc
LIB_FLAGS += ' ' + host['FORTLINK']
if len(host['FORTLIB']) > 0:
LIBRARIES += ' -L' + host['FORTLIB']
if DEBUG:
if 'FDEBUG_FLAGS' not in host.keys():
util.warn("Fortran debug options not set! Using normal fortran flags.")
host['FDEBUG_FLAGS'] = host['FCFLAGS']
FCFLAGS = host['FDEBUG_FLAGS']
else:
FCFLAGS = host['FCFLAGS']
FCFLAGS += (' -DUSE_MPI=' + FORT_USE_MPI_STR
+ ' -DNDIM=' + str(FORT_NDIM))
# GET ALL SOURCE FILES
SRC_CORE = util.get_files(PATHS['CORE'], '*.c')
INC_CORE = util.get_files(PATHS['CORE'], '*.h')
if USE_FORTRAN:
F90_CORE = util.get_files(PATHS['CORE'], '*.f90')
else:
F90_CORE = []
SRC_PROB = util.get_files(PATHS['PROB'], '*.c')
INC_PROB = util.get_files(PATHS['PROB'], '*.h')
# Clean if necessary
if CLEAN:
util.make_clean(PATHS['SRC'])
# COPY SOURCE FILES TO BUILD_DIR
for src in SRC_CORE:
call(['cp', src, PATHS['SRC'] + src.rsplit('/',1)[1]])
for inc in INC_CORE:
call(['cp', inc, PATHS['SRC'] + inc.rsplit('/',1)[1]])
if USE_FORTRAN:
for src in F90_CORE:
call(['cp', src, PATHS['SRC'] + src.rsplit('/',1)[1]])
for src in SRC_PROB:
call(['cp', src, PATHS['SRC'] + src.rsplit('/',1)[1]])
for inc in INC_PROB:
call(['cp', inc, PATHS['SRC'] + inc.rsplit('/',1)[1]])
# WRITE PARAMETERS FILE
pf = open(PATHS['SRC'] + 'params.h', 'w')
for KEY in CPARMS:
if isinstance(CPARMS[KEY], str):
pf.write("#define " + KEY + " (" + CPARMS[KEY] + ")\n")
else: # True/False autocast to 1/0.
pf.write("#define " + KEY + " (%g)\n" % CPARMS[KEY])
pf.close()
# GET SINGLE LISTS OF ALL SOURCE, OBJECT, AND HEADER FILES
SRC_ALL = util.get_files(PATHS['SRC'], '*.c')
INC_ALL = util.get_files(PATHS['SRC'], '*.h')
SRC = ''
OBJ = ''
INC = ''
for n in range(len(SRC_ALL)):
SRC += '%s ' % os.path.basename(SRC_ALL[n])
OBJ += '%s.o ' % os.path.basename(SRC_ALL[n])[:-2]
for n in range(len(INC_ALL)):
INC += '%s ' % os.path.basename(INC_ALL[n])
if USE_FORTRAN:
F90 = ''
FOBJ = ''
for src in F90_CORE:
F90 += '%s ' % os.path.basename(src)
FOBJ += '%s.o ' % os.path.basename(src)[:-4]
# WRITE MAKEFILE
os.chdir(PATHS['SRC'])
mf = open('makefile', 'w')
mf.write('CC = ' + host['COMPILER'] + '\n')
if USE_FORTRAN:
mf.write('F90 = ' + host['FORTRAN_COMP'] + '\n')
mf.write('CCFLAGS = ' + C_FLAGS + ' ' + LIBRARIES + ' ' + INCLUDES + '\n')
if USE_FORTRAN:
mf.write('FCFLAGS = ' + FCFLAGS + '\n')
mf.write('LIB_FLAGS = ' + LIB_FLAGS + '\n')
mf.write('CC_COMPILE = $(CC) $(CCFLAGS) -c' + '\n')
mf.write('CC_LOAD = $(CC) $(CCFLAGS)' + '\n')
if USE_FORTRAN:
mf.write('FSRC = ' + F90 + '\n')
mf.write('FOBJ = ' + FOBJ + '\n')
else:
mf.write('FSRC = \n')
mf.write('FOBJ = \n')
mf.write('SRC = ' + SRC + '\n')
mf.write('OBJ = ' + OBJ + '\n')
mf.write('INC = ' + INC + '\n')
mf.write('EXE = bhlight' + '\n')
mf.write('.c.o:' + '\n')
mf.write('\t$(CC_COMPILE) $*.c' + '\n')
if USE_FORTRAN:
mf.write('%.o: %.f90 makefile' + '\n')
mf.write('\t$(F90) $(FCFLAGS) -c $<\n')
mf.write('all: $(EXE)' + '\n')
mf.write('$(OBJ): $(INC) makefile' + '\n')
mf.write('$(EXE): $(OBJ) $(FOBJ) $(INC) makefile' + '\n')
mf.write('\t$(CC_LOAD) $(OBJ) $(FOBJ) $(LIB_FLAGS) -o $(EXE)\n')
mf.write('clean:\n')
mf.write('\t$(RM) $(SRC) $(FSRC) $(OBJ) $(FOBJ) $(EXE) $(INC)\n')
mf.close()
print("\n COMPILING SOURCE\n")
ncomp = 0
first_error = 1
if DEBUG:
popen = subprocess.Popen(['make'], stdout=subprocess.PIPE,
stderr=subprocess.PIPE, universal_newlines=True)
else:
popen = subprocess.Popen(['make','-j','10'], stdout=subprocess.PIPE,
stderr=subprocess.PIPE, universal_newlines=True)
for stdout_line in iter(popen.stdout.readline, ""):
if stdout_line.rstrip()[-2:] == '.c' or stdout_line.rstrip()[-4:] == '.f90':
print(" [" + util.color.BOLD + util.color.BLUE +
"%2d%%" % (100.*float(ncomp)/len(SRC_ALL+F90_CORE)) + util.color.NORMAL +
"] " + util.color.BOLD +
stdout_line.rsplit(' -c ',1)[1].rstrip().lstrip().split('/')[-1] +
util.color.NORMAL)
ncomp += 1
for stderr_line in iter(popen.stderr.readline, ""):
# THIS ALSO FAILS FOR WARNINGS!!!
if first_error == 1:
util.warn("COMPILER ERROR")
first_error = 0
print(stderr_line.rstrip())
if first_error != 1 and not FORCE:
util.warn("COMPILATION FAILED")
sys.exit()
obj_files = util.get_files(PATHS['SRC'], '*.o')
for f in obj_files:
os.remove(f)
os.rename(PATHS['SRC'] + 'bhlight', PATHS['BUILD'] + 'bhlight')
if REMOVE_SRC:
import shutil
shutil.rmtree(PATHS['SRC'])
print("\n BUILD SUCCESSFUL")
# CREATE RUNTIME PARAMETERS FILE
PARAMFILE = PATHS['BUILD'] + PARAM_NAME
if WRITE_PARAM:
with open(PARAMFILE, 'w') as pf:
pf.write("### RUNTIME PARAMETERS ###\n")
pf.write("\n# COORDINATES\n")
write_rparm(pf, 'tf')
write_rparm(pf, 'dt')
if CPARMS['METRIC'] == 'MINKOWSKI':
write_rparm(pf, 'x1Min')
write_rparm(pf, 'x1Max')
write_rparm(pf, 'x2Min')
write_rparm(pf, 'x2Max')
write_rparm(pf, 'x3Min')
write_rparm(pf, 'x3Max')
if CPARMS['METRIC'] == 'MKS':
write_rparm(pf, 'Rout')
if util.parm_is_active(CPARMS, 'RADIATION'):
write_rparm(pf, 'Rout_rad')
if NEED_UNITS:
pf.write("\n# UNITS\n")
if CPARMS['METRIC'] == 'MINKOWSKI':
write_rparm(pf, 'L_unit')
write_rparm(pf, 'M_unit')
if CPARMS['METRIC'] == 'MKS':
write_rparm(pf, 'mbh')
write_rparm(pf, 'M_unit')
pf.write("\n# FLUID\n")
write_rparm(pf, 'cour')
if util.parm_is_active(CPARMS, 'RADIATION'):
write_rparm(pf, 'cour_cool')
if CPARMS['EOS'] == 'EOS_TYPE_GAMMA':
write_rparm(pf, 'gam')
if CPARMS['EOS'] == 'EOS_TYPE_TABLE':
write_rparm(pf, 'eospath')
if util.parm_is_active(CPARMS, 'ELECTRONS'):
pf.write("\n# ELECTRONS\n")
write_rparm(pf, 'game')
write_rparm(pf, 'gamp')
write_rparm(pf, 'fel0')
write_rparm(pf, 'tptemin')
write_rparm(pf, 'tptemax')
if util.parm_is_active(CPARMS, 'RADIATION'):
pf.write("\n# RADIATION\n")
if not util.parm_is_active(CPARMS, 'ELECTRONS'):
write_rparm(pf, 'tp_over_te')
write_rparm(pf, 'nph_per_proc')
write_rparm(pf, 'numin')
write_rparm(pf, 'numax')
write_rparm(pf, 'tune_emiss')
write_rparm(pf, 'tune_scatt')
write_rparm(pf, 't0_tune_emiss')
write_rparm(pf, 't0_tune_scatt')
write_rparm(pf, 'thetae_max')
write_rparm(pf, 'sigma_max')
write_rparm(pf, 'kdotk_tol')
write_rparm(pf, 'Nph_to_track')
write_rparm(pf, 'thbin')
write_rparm(pf, 'phibin')
if util.parm_is_active(CPARMS, 'BURROWS_OPACITIES'):
write_rparm(pf, 'opac_param_file')
write_rparm(pf, 'opac_file')
if util.parm_is_active(CPARMS, 'HDF5_OPACITIES'):
write_rparm(pf, 'opac_file')
write_rparm(pf, 'init_from_grmhd')
pf.write("\n# OUTPUT\n")
write_rparm(pf, 'DTd')
write_rparm(pf, 'DTl')
write_rparm(pf, 'DTr')
write_rparm(pf, 'DNr')
write_rparm(pf, 'DTp')
write_rparm(pf, 'DTf')
write_rparm(pf, 'outputdir')
if len(RPARMS.keys()) > 0:
pf.write("\n# PROBLEM\n")
prob_keys = RPARMS.keys()
for key in list(prob_keys):
write_rparm(pf, key)
print("\n RUNTIME PARAMETER FILE CREATED")
if MOVEEXEC:
os.rename(PATHS['BUILD'] + 'bhlight', PATHS['BUILD'] + '../bhlight')
if WRITE_PARAM:
os.rename(PATHS['BUILD'] + PARAM_NAME, PATHS['BUILD'] + '../' + PARAM_NAME)
print("")
sys.exit()
def initializeAuthentication():
#If no file use default but set filename anyway so the dump function will work
for i in range(0,15):
#Gets the highest numbered of all directories that are named after floating point values(i.e. most recent timestamp)
name = util.getHighestNumberedTimeDirectory(directories.usersdir)
possibledir = os.path.join(directories.usersdir,name)
#__COMPLETE__ is a special file we write to the dump directory to show it as valid
if '''__COMPLETE__''' in util.get_files(possibledir):
try:
f = open(os.path.join(possibledir,'users.json'))
temp = json.load(f)
f.close()
except:
p = "same"
p2 = "different"
while not p == p2:
p = "same"
p2 = "different"
p = input("No users list found. Account 'admin' created. Choose password:"******"Reenter Password:"******"password mismatch")
m = hashlib.sha256()
r = os.urandom(16)
r64 = base64.b64encode(r)
m.update(p)
m.update(r)
pwd = base64.b64encode(m)
temp = {
"groups": {
"Administrators": {
"permissions": [
"/admin/settings.edit",
"/admin/logging.edit",
"/admin/users.edit",
"/users/pagelisting.view",
"/admin/modules.edit",
"/admin/settings.view",
"/admin/mainpage.view",
"/users/logs.view",
"/admin/modules.view"
]
}
},
"users": {
"admin": {
"groups": [
"Administrators"
],
"password": pwd,
"username": "******",
"salt": r64
}
}
}
global Users
Users = temp['users']
global Groups
Groups = temp['groups']
global Tokens
Tokens = {}
for user in Users:
#What an unreadable line! It turs all the dicts in Users into User() instances
Users[user] = User(Users[user])
assignNewToken(user)
generateUserPermissions()
break #We sucessfully found the latest good users.json dump! so we break the loop
else:
#If there was no flag indicating that this was an actual complete dump as opposed
#To an interruption, rename it and try again
shutil.copytree(possibledir,os.path.join(directories.usersdir,name+"INCOMPLETE"))
shutil.rmtree(possibledir)
'grain_cover': 4
}
# extracting features of grains
feat_data = result_dir + 'grain_feature.pkl'
if os.path.isfile(feat_data):
ftrain, y_train, ftest, y_test = pickle.load(open(feat_data, 'rb'))
else:
grain_particles = {
'damaged_grain': data_dir + 'damaged_grain',
'foreign': data_dir + 'foreign_particles',
'grain': data_dir + 'grain',
'broken_grain': data_dir + 'grain_broken',
'grain_cover': data_dir + 'grain_covered'
}
grain_partical_list = {
k: get_files(v)
for k, v in grain_particles.items()
}
# impurity_list = get_files(impure)
# grain_list = get_files(grain)
all_partical = []
for i in grain_partical_list:
all_partical += grain_partical_list[i]
partical_classes = []
for i in grain_partical_list:
a = np.zeros(len(grain_class))
a[grain_class[i]] = 1
partical_classes += [a for j in range(len(grain_partical_list[i]))]
# out = [[1, 0] for i in range(len(grain_list))] + [[0, 1] for i in range(len(impurity_list))]
x_train, y_train, x_test, y_test = make_sets(all_partical,
partical_classes, 0.3)
#coding:utf8
from ConfigParser import ConfigParser
import pymongo
from util import get_files
__author__ = 'cy'
cf = ConfigParser()
cf.read('dev.cfg')
city_num = int(cf.get('calculate', 'city_num'))
predict_hour = int(cf.get('calculate', 'predict_hour'))
file_path = cf.get('file', 'filepath')
start_time = cf.get('file', 'start_time')
end_time = cf.get('file', 'end_time')
gaps = eval(cf.get('calculate', 'gaps'))
all_files = (get_files(start_time, end_time))
day_gaps=eval(cf.get('calculate','day_gaps'))
mongo_host=cf.get('mongodb','host')
mongo_port=int(cf.get('mongodb','port'))
mongo_db_name=cf.get('mongodb','db_name')
client=pymongo.MongoClient(mongo_host,mongo_port)
db=client.get_database(mongo_db_name)
bins = eval(cf.get('calculate', 'bins'))
collection_name=cf.get('mongodb','collection')
def decode_to_lattices(model, output_dir, model_dir, mfc_list, lm, dict,
model_list, gold_mlf):
sys.stderr.write('Decoding to lattices\n')
output_mlf = '%s/train_recog.mlf' % output_dir
results_log = '%s/results.log' % output_dir
## Create a config file to use with HDecode
hdecode_config = '%s/hdecode.config' % output_dir
fh = open(hdecode_config, 'w')
#fh.write('HLANGMODFILTER = "gunzip -c $.gz"\n')
fh.write('HNETFILTER = "gunzip -c < $.gz"\n')
fh.write('HNETOFILTER = "gzip -c > $.gz"\n')
fh.write('RAWMITFORMAT = T\n')
fh.write('HPARM: TARGETKIND = MFCC_0_D_A_Z\n')
fh.write('GCFREQ = 50\n')
fh.write('HLAT:TRACE = 19\n')
fh.write('HLVNET:TRACE = 1\n')
fh.write('HLVREC:TRACE = 1\n')
fh.write('HLVLM:TRACE = 1\n')
fh.write('LATPRUNEBEAM = 500.0\n')
fh.write('MAXLMLA = 3.0\n')
fh.write('BUILDLATSENTEND = T\n')
fh.write('FORCELATOUT = F\n')
fh.write('STARTWORD = <s>\n')
fh.write('ENDWORD = </s>\n')
fh.close()
## HDecode parameters
utts_per_split = 100
block_size = 5
beam = 150.0
word_end_beam = 125.0
max_model = 10000
lm_scale = 15.0
word_insertion_penalty = 0.0
def hdecode(input, output):
cmd = 'HDecode -A -D -V -T 9 -o M -z lat -C %s' % hdecode_config
cmd += ' -H %s/MMF' % model_dir
cmd += ' -k %d' % block_size
cmd += ' -t %f 100.0' % beam
cmd += ' -v %f 115.0' % word_end_beam
cmd += ' -u %d' % max_model
cmd += ' -s %f' % lm_scale
cmd += ' -p %f' % word_insertion_penalty
cmd += ' -w %s' % lm
cmd += ' -S %s' % input
cmd += ' -l %s/' % output
cmd += ' %s %s' % (dict, model_list)
if model.verbose > 0:
cmd += ' >%s/%s.log' % (output_dir, os.path.basename(input))
return cmd
## Split up MFC list
split_mfc = SplitList(output_dir, mfc_list, by_path=True)
## Create the HDecode commands
cmds = []
inputs = split_mfc.get_files()
for input in inputs:
output = '%s/%s' % (output_dir, split_mfc.get_key(input))
if not os.path.isdir(output): os.makedirs(output)
cmds.append(hdecode(input, output))
if model.local == 1:
for cmd in cmds:
print cmd
print os.popen(cmd).read()
else:
cmds_file = '%s/hdecode.commands' % output_dir
fh = open(cmds_file, 'w')
for cmd in cmds:
fh.write('%s\n' % cmd)
fh.close()
util.run_parallel(cmds_file, model.jobs, output_dir)
## Copy old mfc list
old_mfc_list = '%s/mfc_old.list' % output_dir
os.system('cp %s %s' % (mfc_list, old_mfc_list))
## Prune bad lats from the mfc list
lat_ids = [
os.path.basename(f).split('.')[0]
for f in util.get_files(output_dir, r'.*\.lat')
]
bad_count = 0
fh = open(mfc_list, 'w')
for mfc in open(old_mfc_list):
id = os.path.basename(mfc.strip()).split('.')[0]
## Check for missing transcriptions
if id not in lat_ids:
if model.verbose > 1:
util.log_write(model.logfh, 'removed bad lat [%s]' % id)
bad_count += 1
else:
fh.write(mfc)
fh.close()
util.log_write(model.logfh, 'removed bad lats [%d]' % bad_count)
## Create an MLF from the recognition output
outputs = util.get_files(output_dir, r'.*\.rec')
os.popen('rm -f %s' % output_mlf)
fh = open(output_mlf, 'w')
fh.write('#!MLF!#\n')
for output in outputs:
fh.write('"%s"\n' % output)
for line in open(output):
if '<s>' in line or '</s>' in line: continue
fh.write(line)
fh.write('.\n')
fh.close()
## Evaluate
cmd = 'HResults -h -n -A -T 1'
cmd += ' -I %s' % gold_mlf
cmd += ' %s %s > %s' % (model_list, output_mlf, results_log)
os.system(cmd)
print os.popen('cat ' + results_log).read()
def swboard(path_wav, path_trans, config, output, wav_list=[]):
"""
<wav id> <channelId> <speakerId> <begin time segment> <end time segment> <label> text
fsh_60262 1 fsh_60262_A 47.9 49.77 <O,FI,M,STANDARD> I DO IT IS HALLOWEEN
"""
## wav files
#wav_files = set(util.get_files(path_wav, re.compile('.*\.wav', re.IGNORECASE)))
#print 'found wav files [%d]' %len(wav_files)
## load speaker map
speaker_by_conv = {}
convs_by_speaker = {}
for line in open('common/swb_speaker.map'):
[conv, speaker] = line.split()
speaker_by_conv[conv] = speaker
if not speaker in convs_by_speaker: convs_by_speaker[speaker] = []
convs_by_speaker[speaker].append(conv)
sorted_speakers = convs_by_speaker.items()
sorted_speakers.sort(lambda x,y: len(y[1]) - len(x[1]))
## split convs into sets
train1, train2, test = set(), set(), set()
history = [1]
count1, count2 = 0, 0
for speaker, convs in sorted_speakers:
print speaker, convs
if len(convs) == 1: test.add(convs[0])
else:
if history[-2:] == [1,1] or history[-2:] == [1,2]:
train2.update(set(convs))
history.append(2)
count2 += 1
else:
train1.update(set(convs))
history.append(1)
count1 += 1
#print len(train1), len(train2), len(test)
#print count1, count2
#sys.exit()
## transcription files
trans_files = util.get_files(path_trans, re.compile('.*-trans\.text', re.IGNORECASE))
print 'found transcription files [%d]' %len(trans_files)
output1 = output + '_1'
output2 = output + '_2'
output3 = output + '_3'
fh1, fh2, fh3 = open(output1, 'w'), open(output2, 'w'), open(output3, 'w')
stm1, stm2, stm3 = open(output1 + '.stm', 'w'), open(output2 + '.stm', 'w'), open(output3 + '.stm', 'w')
utt_count = 0
file_count = 0
token_count = 0
word_list = set()
for file in trans_files:
file_count += 1
if file_count % 100 == 0: print 'transcription files processed [%d]' %file_count
dirname = os.path.dirname(file)
for line in open(file):
items = line.strip().split()
id = items[0]
[id, ms98, a, utt] = id.split('-')
side = id[-1]
id = id[:-1]
start, end = items[1], items[2]
words = map(str.upper, items[3:])
dir = '%s_%s' %(id, side)
new_id = '%s%s-ms98-a-%s' %(id, side, utt)
wav_file = path_wav + '%s/%s.wav' %(dir, new_id)
if not os.path.isfile(wav_file):
continue
if sum([int(w.startswith('[') or w.endswith(']')) for w in words]) == len(words):
continue
if len(words) == 0: continue
trans = fix_swb_trans(words)
if len(trans) == 0: continue
if trans.isdigit(): continue
conv = (id + '_' + side).replace('sw', '')
if conv in train1:
fh = fh1
stm = stm1
elif conv in train2:
fh = fh2
stm = stm2
elif conv in test:
fh = fh3
stm = stm3
else:
print 'No set exists for conv: %s' %conv
print trans
continue
fh.write('%s %s %s\n' %(wav_file, config, trans))
stm.write('%s %s %s%s %s %s %s\n' %(new_id, side, id, side, start, end, trans))
utt_count += 1
for word in words: word_list.add(word)
token_count += len(words)
fh.close()
stm.close()
print 'Using [%s] wrote [%d] utts to [%s]' %(path_trans, utt_count, output)
print 'Tokens [%d] Types [%d]' %(token_count, len(word_list))
text = text + "{:.40f}".format(y).rstrip('0').rstrip('.') + ','
text = text + '\n'
return text
def addLayer(model):
x = model.output
x = Dense(1024)(x)
x = GlobalMaxPooling2D(name='gmaxpool')(x)
model = Model(model.input, x)
return model
# create models
if __name__ == '__main__':
files = get_files(filesdir)
start = timeit.default_timer()
models = dict()
print('setting up models...')
model = appl.xception.Xception(weights='imagenet', include_top=False)
model = addLayer(model)
models['xception'] = model
model = appl.vgg16.VGG16(weights='imagenet', include_top=False)
model = addLayer(model)
models['vgg16'] = model
model = appl.vgg19.VGG19(weights='imagenet', include_top=False)
model = addLayer(model)
models['vgg19'] = model
model = appl.resnet50.ResNet50(weights='imagenet', include_top=False)
model = addLayer(model)
models['resnet50'] = model
def build(PROBLEM, PATHS):
print("")
print("********************************************************************************")
print("")
print(" BHLIGHT BUILD SCRIPT")
print("")
print(" OPTIONS:")
print(" -help (print this message and exit)")
print(" -debug (use debug compile params)")
print(" -force (do not abort upon compile-time warnings/errors)")
print(" -noclean (do not delete old source files)")
print(" -noparam (do not create new parameter file)")
print(" -dir /path/to/target (create target dir and build there)")
print("")
print("********************************************************************************")
print("")
if is_user_help():
sys.exit()
# PROCESS USER INPUT
DEBUG = is_user_debug()
FORCE = is_user_force()
MOVEEXEC = set_dirs(PATHS)
NOPARAM = is_user_noparam()
NOCLEAN = is_user_noclean()
CLEAN = not NOCLEAN
WRITE_PARAM = not NOPARAM
# get version
VERSION = get_version()
# PRINT TO TERMINAL AND LOGFILE
LOGFILE = os.path.join(PATHS['BUILD'], 'log_build')
util.log_output(sys, LOGFILE)
# SEARCH FOR MACHINE
machines = util.get_files(PATHS['MACHINE'], '*')
for n in range(len(machines)):
machines[n] = machines[n].split('/')[-1].replace('.py', '')
machine = __import__(machines[n])
if machine.matches_host() == True:
break
del machine
try: machine
except NameError: util.warn("HOST " + os.uname()[1] + " UNKNOWN"); sys.exit()
host = machine.get_options()
if DEBUG and 'DEBUG_FLAGS' not in host.keys():
util.warn("Debug compiler options not set! Using normal compiler flags.")
host['DEBUG_FLAGS'] = host['COMPILER_FLAGS']
C_FLAGS = '-std=c99 -mcmodel=medium '
if DEBUG:
C_FLAGS += host['DEBUG_FLAGS']
else:
C_FLAGS += host['COMPILER_FLAGS']
# MATH AND DYNAMIC LINKING
LIB_FLAGS = '-lm -ldl'
LIBRARIES = ''
INCLUDES = ''
# GSL
host['GSL_DIR'] = util.sanitize_path(host['GSL_DIR'])
LIB_FLAGS += (' -lgsl -lgslcblas'
+ ' -Wl,-rpath='
+ host['GSL_DIR'] + 'lib/')
LIBRARIES += '-L' + host['GSL_DIR'] + 'lib/'
INCLUDES += '-I' + host['GSL_DIR'] + 'include/'
# MPI
if 'MPI_DIR' in host:
host['MPI_DIR'] = util.sanitize_path(host['MPI_DIR'])
LIB_FLAGS += (' -Wl,-rpath='
+ host['MPI_DIR'] + 'lib/')
LIBRARIES += ' -L' + host['MPI_DIR'] + 'lib/'
INCLUDES += ' -I' + host['MPI_DIR'] + 'include/'
# HDF5
if 'HDF5_DIR' in host:
host['HDF5_DIR'] = util.sanitize_path(host['HDF5_DIR'])
LIB_FLAGS += (' -lhdf5_hl -lhdf5'
+' -Wl,-rpath='
+ host['HDF5_DIR'] + 'lib/')
LIBRARIES += ' -L' + host['HDF5_DIR'] + 'lib/'
INCLUDES += ' -I' + host['HDF5_DIR'] + 'include/'
print(" CONFIGURATION\n")
def print_config(key, var):
print(" " + util.color.BOLD + "{:<15}".format(key) + util.color.NORMAL +
str(var))
set_cparm("VERSION", '"{}"'.format(VERSION))
set_cparm("PROBLEM_NAME", '"{}"'.format(PROBLEM))
print_config("VERSION", VERSION)
print_config("MACHINE", host['NAME'])
print_config("PROBLEM", PROBLEM)
print_config("BUILD DIR", PATHS['BUILD'])
print_config("COMPILER", host['COMPILER'])
print_config("GSL_DIR", host['GSL_DIR'])
if 'MPI_DIR' in host:
print_config("MPI_DIR", host['MPI_DIR'])
if 'HDF5_DIR' in host:
print_config("HDF5_DIR", host['HDF5_DIR'])
print_config("EXECUTABLE", host['EXECUTABLE'])
print_config("C_FLAGS", C_FLAGS)
print_config("LIB_FLAGS", LIB_FLAGS)
print_config("LIBRARIES", LIBRARIES)
print_config("INCLUDES", INCLUDES)
print_config("OPENMP", CPARMS['OPENMP'])
print("\n COMPILE-TIME PARAMETERS\n")
print_config("N1TOT", CPARMS['N1TOT'])
print_config("N2TOT", CPARMS['N2TOT'])
print_config("N3TOT", CPARMS['N3TOT'])
print_config("N1CPU", CPARMS['N1CPU'])
print_config("N2CPU", CPARMS['N2CPU'])
print_config("N3CPU", CPARMS['N3CPU'])
print_config("METRIC", CPARMS['METRIC'])
print_config("RECONSTRUCTION", CPARMS['RECONSTRUCTION'])
if util.parm_is_active(CPARMS, 'RADIATION'):
print_config("RADIATION", CPARMS['RADIATION'])
if util.parm_is_active(CPARMS, 'NTH'):
print_config("NTH", CPARMS["NTH"])
else:
set_cparm("NTH", 8)
if util.parm_is_active(CPARMS, 'NPHI'):
print_config("NPHI", CPARMS["NPHI"])
else:
set_cparm("NPHI", 8)
if util.parm_is_active(CPARMS, "NU_BINS_EMISS"):
print_config("NU_BINS_EMISS", CPARMS["NU_BINS_EMISS"])
else:
set_cparm("NU_BINS_EMISS", 200)
if util.parm_is_active(CPARMS, "NU_BINS_SPEC"):
print_config("NU_BINS_SPEC", CPARMS["NU_BINS_SPEC"])
else:
set_cparm("NU_BINS_SPEC", 200)
if util.parm_is_active(CPARMS, "SUPPRESS_FLR_RADIATION"):
print_config("SUPPRESS_FLR_RADIATION", CPARMS["SUPPRESS_FLR_RADIATION"])
else:
set_cparm("SUPPRESS_FLR_RADIATION", 0)
else:
set_cparm("RADIATION", 0)
if util.parm_is_active(CPARMS, 'ELECTRONS'):
print_config("ELECTRONS", CPARMS['ELECTRONS'])
else:
set_cparm("ELECTRONS", 0)
if util.parm_is_active(CPARMS, 'FLOORADV'):
print_config("FLOORADV", CPARMS['FLOORADV'])
else:
set_cparm("FLOORADV", 0)
#if util.parm_is_active(CPARMS,'NVAR_PASSIVE'):
# print_config("NVAR_PASSIVE", CPARMS["NVAR_PASSIVE"])
#else:
# set_cparm("NVAR_PASSIVE", 0)
#if util.parm_is_active(CPARMS, 'OUTPUT_EOSVARS'):
# print_config("OUTPUT_EOSVARS", CPARMS["OUTPUT_EOSVARS"])
#else:
# set_cparm("OUTPUT_EOSVARS", 0)
# Set core runtime parameters
set_rparm('tf', 'double')
set_rparm('dt', 'double')
if CPARMS['METRIC'] == 'MINKOWSKI':
set_rparm('x1Min', 'double', default = 0.)
set_rparm('x1Max', 'double', default = 1.)
set_rparm('x2Min', 'double', default = 0.)
set_rparm('x2Max', 'double', default = 1.)
set_rparm('x3Min', 'double', default = 0.)
set_rparm('x3Max', 'double', default = 1.)
if CPARMS['METRIC'] == 'MKS':
set_rparm('a', 'double', default = 0.5)
set_rparm('hslope', 'double', default = 0.3)
set_rparm('Rout', 'double', default = 40.)
set_rparm('Rout_vis', 'double', default = 40.)
if CPARMS['METRIC'] == 'MMKS':
set_rparm('a', 'double', default = 0.5)
set_rparm('hslope', 'double', default = 0.3)
set_rparm('poly_xt', 'double', default = 0.82)
set_rparm('poly_alpha', 'double', default = 14.)
set_rparm('mks_smooth', 'double', default = 0.5)
set_rparm('Rout', 'double', default = 40.)
set_rparm('Rout_vis', 'double', default = 40.)
if util.parm_is_active(CPARMS, 'RADIATION'):
set_rparm('Rout_rad', 'double', default = 40.)
if (util.parm_is_active(CPARMS, 'RADIATION') or
util.parm_is_active(CPARMS, 'COULOMB')):
if CPARMS['METRIC'] == 'MINKOWSKI':
set_rparm('L_unit', 'double')
set_rparm('M_unit', 'double')
if CPARMS['METRIC'] == 'MKS' or CPARMS['METRIC'] == 'MMKS':
set_rparm('M_unit', 'double')
set_rparm('mbh', 'double', default = 1.989e34)
set_rparm('gam', 'double', default = 5./3.)
set_rparm('cour', 'double', default = 0.9)
if util.parm_is_active(CPARMS, 'ELECTRONS'):
set_rparm('game', 'double', default = 4./3.)
set_rparm('gamp', 'double', default = 5./3.)
set_rparm('fel0', 'double', default = 0.01)
set_rparm('tptemin', 'double', default = 1.e-3)
set_rparm('tptemax', 'double', default = 1.e3)
if util.parm_is_active(CPARMS, 'RADIATION'):
if not util.parm_is_active(CPARMS, 'ELECTRONS'):
set_rparm('tp_over_te', 'double', default = 1.)
set_rparm('nph_per_proc', 'double', default = 1.e5)
set_rparm('numin_emiss', 'double', default = 1.e8)
set_rparm('numax_emiss', 'double', default = 1.e20)
set_rparm('numin_spec', 'double', default = 1.e8)
set_rparm('numax_spec', 'double', default = 1.e20)
set_rparm('tune_emiss', 'double', default = 1.)
set_rparm('tune_scatt', 'double', default = 1.)
set_rparm('t0_tune_emiss', 'double', default = -1.)
set_rparm('t0_tune_scatt', 'double', default = -1.)
set_rparm('thetae_max', 'double', default = 1.e3)
set_rparm('sigma_max', 'double', default = 1.)
set_rparm('kdotk_tol', 'double', default = 1.e-6)
set_rparm('Nph_to_track', 'double', default = 0.);
set_rparm('init_from_grmhd', 'string', default = 'No')
set_rparm('DTd', 'double', default = 0.5)
set_rparm('DTl', 'double', default = 0.1)
set_rparm('DTr', 'double', default = 1000.)
set_rparm('DNr', 'integer', default = 1024)
set_rparm('DTp', 'integer', default = 100)
set_rparm('DTf', 'integer', default = 1)
set_rparm('outputdir', 'string', default = './')
# GET ALL SOURCE FILES
SRC_CORE = util.get_files(PATHS['CORE'], '*.c')
INC_CORE = util.get_files(PATHS['CORE'], '*.h')
SRC_PROB = util.get_files(PATHS['PROB'], '*.c')
INC_PROB = util.get_files(PATHS['PROB'], '*.h')
# Clean if necessary
if CLEAN:
util.make_clean(PATHS['SRC'])
# COPY SOURCE FILES TO BUILD_DIR
for src in SRC_CORE:
call(['cp', src, PATHS['SRC'] + src.rsplit('/',1)[1]])
for inc in INC_CORE:
call(['cp', inc, PATHS['SRC'] + inc.rsplit('/',1)[1]])
for src in SRC_PROB:
call(['cp', src, PATHS['SRC'] + src.rsplit('/',1)[1]])
for inc in INC_PROB:
call(['cp', inc, PATHS['SRC'] + inc.rsplit('/',1)[1]])
# WRITE PARAMETERS FILE
pf = open(PATHS['SRC'] + 'params.h', 'w')
for KEY in CPARMS:
if isinstance(CPARMS[KEY], str):
pf.write("#define " + KEY + " (" + CPARMS[KEY] + ")\n")
else:
pf.write("#define " + KEY + " (%g)\n" % CPARMS[KEY])
pf.close()
# GET SINGLE LISTS OF ALL SOURCE, OBJECT, AND HEADER FILES
SRC_ALL = util.get_files(PATHS['SRC'], '*.c')
INC_ALL = util.get_files(PATHS['SRC'], '*.h')
SRC = ''
OBJ = ''
INC = ''
for n in range(len(SRC_ALL)):
SRC += '%s ' % os.path.basename(SRC_ALL[n])
OBJ += '%s.o ' % os.path.basename(SRC_ALL[n])[:-2]
for n in range(len(INC_ALL)):
INC += '%s ' % os.path.basename(INC_ALL[n])
# WRITE MAKEFILE
os.chdir(PATHS['SRC'])
mf = open('makefile', 'w')
mf.write('CC = ' + host['COMPILER'] + '\n')
mf.write('CCFLAGS = ' + C_FLAGS + ' ' + LIBRARIES + ' ' + INCLUDES + '\n')
mf.write('LIB_FLAGS = ' + LIB_FLAGS + '\n')
mf.write('CC_COMPILE = $(CC) $(CCFLAGS) -c' + '\n')
mf.write('CC_LOAD = $(CC) $(CCFLAGS)' + '\n')
mf.write('.c.o:' + '\n')
mf.write('\t$(CC_COMPILE) $*.c' + '\n')
mf.write('EXE = bhlight' + '\n')
mf.write('all: $(EXE)' + '\n')
mf.write('SRC = ' + SRC + '\n')
mf.write('OBJ = ' + OBJ + '\n')
mf.write('INC = ' + INC + '\n')
mf.write('$(OBJ): $(INC) makefile' + '\n')
mf.write('$(EXE): $(OBJ) $(INC) makefile' + '\n')
mf.write('\t$(CC_LOAD) $(OBJ) $(LIB_FLAGS) -o $(EXE)\n')
mf.write('clean:\n')
mf.write('\t$(RM) $(SRC) $(OBJ) $(EXE) $(INC)\n')
mf.close()
print("\n COMPILING SOURCE\n")
ncomp = 0
first_error = 1
if DEBUG:
popen = subprocess.Popen(['make'], stdout=subprocess.PIPE,
stderr=subprocess.PIPE, universal_newlines=True)
else:
popen = subprocess.Popen(['make','-j','10'], stdout=subprocess.PIPE,
stderr=subprocess.PIPE, universal_newlines=True)
for stdout_line in iter(popen.stdout.readline, ""):
if stdout_line.rstrip()[-2:] == '.c':
print(" [" + util.color.BOLD + util.color.BLUE +
"%2d%%" % (100.*float(ncomp)/len(SRC_ALL)) + util.color.NORMAL +
"] " + util.color.BOLD +
stdout_line.rsplit('-c',1)[1].rstrip().lstrip().split('/')[-1] +
util.color.NORMAL)
ncomp += 1
for stderr_line in iter(popen.stderr.readline, ""):
# THIS ALSO FAILS FOR WARNINGS!!!
if first_error == 1:
util.warn("COMPILER ERROR")
first_error = 0
print(stderr_line.rstrip())
if first_error != 1 and not FORCE:
util.warn("COMPILATION FAILED")
sys.exit()
obj_files = util.get_files(PATHS['SRC'], '*.o')
for f in obj_files:
os.remove(f)
os.rename(PATHS['SRC'] + 'bhlight', PATHS['BUILD'] + 'bhlight')
print("\n BUILD SUCCESSFUL")
# CREATE RUNTIME PARAMETERS FILE
PARAMFILE = PATHS['BUILD'] + PARAM_NAME
if WRITE_PARAM:
with open(PARAMFILE, 'w') as pf:
pf.write("### RUNTIME PARAMETERS ###\n")
pf.write("\n# COORDINATES\n")
write_rparm(pf, 'tf')
write_rparm(pf, 'dt')
if CPARMS['METRIC'] == 'MINKOWSKI':
write_rparm(pf, 'x1Min')
write_rparm(pf, 'x1Max')
write_rparm(pf, 'x2Min')
write_rparm(pf, 'x2Max')
write_rparm(pf, 'x3Min')
write_rparm(pf, 'x3Max')
if CPARMS['METRIC'] == 'MKS' or CPARMS['METRIC'] == 'MMKS':
write_rparm(pf, 'Rout')
if util.parm_is_active(CPARMS, 'RADIATION'):
write_rparm(pf, 'Rout_rad')
if (util.parm_is_active(CPARMS, 'RADIATION') or
util.parm_is_active(CPARMS, 'COULOMB')):
pf.write("\n# UNITS\n")
if CPARMS['METRIC'] == 'MINKOWSKI':
write_rparm(pf, 'L_unit')
write_rparm(pf, 'M_unit')
if CPARMS['METRIC'] == 'MKS' or CPARMS['METRIC'] == 'MMKS':
write_rparm(pf, 'mbh')
write_rparm(pf, 'M_unit')
pf.write("\n# FLUID\n")
write_rparm(pf, 'gam')
write_rparm(pf, 'cour')
if util.parm_is_active(CPARMS, 'ELECTRONS'):
pf.write("\n# ELECTRONS\n")
write_rparm(pf, 'game')
write_rparm(pf, 'gamp')
write_rparm(pf, 'fel0')
write_rparm(pf, 'tptemin')
write_rparm(pf, 'tptemax')
if util.parm_is_active(CPARMS, 'RADIATION'):
pf.write("\n# RADIATION\n")
if not util.parm_is_active(CPARMS, 'ELECTRONS'):
write_rparm(pf, 'tp_over_te')
write_rparm(pf, 'nph_per_proc')
write_rparm(pf, 'numin_emiss')
write_rparm(pf, 'numax_emiss')
write_rparm(pf, 'numin_spec')
write_rparm(pf, 'numax_spec')
write_rparm(pf, 'tune_emiss')
write_rparm(pf, 'tune_scatt')
write_rparm(pf, 't0_tune_emiss')
write_rparm(pf, 't0_tune_scatt')
write_rparm(pf, 'thetae_max')
write_rparm(pf, 'sigma_max')
write_rparm(pf, 'kdotk_tol')
write_rparm(pf, 'Nph_to_track')
pf.write("\n# OUTPUT\n")
write_rparm(pf, 'DTd')
write_rparm(pf, 'DTl')
write_rparm(pf, 'DTr')
write_rparm(pf, 'DNr')
write_rparm(pf, 'DTp')
write_rparm(pf, 'DTf')
write_rparm(pf, 'outputdir')
if len(RPARMS.keys()) > 0:
pf.write("\n# PROBLEM\n")
prob_keys = RPARMS.keys()
for key in list(prob_keys):
write_rparm(pf, key)
print("\n RUNTIME PARAMETER FILE CREATED")
if MOVEEXEC:
os.rename(PATHS['BUILD'] + 'bhlight', PATHS['BUILD'] + '../bhlight')
if WRITE_PARAM:
os.rename(PATHS['BUILD'] + PARAM_NAME, PATHS['BUILD'] + '../' + PARAM_NAME)
print("")
sys.exit()
import tensorflow as tf
from preprocess_images.Image import Image
from model.style_transform import StyleTransform, get_style_feature
import params as P
import time
import util
import os
style_name_list = ['la_muse', 'wave_crop', 'mirror', 'starry_night', 'udnie']
style_name = 'wave_crop'
style_p = P.st_style_image_path_dict.get(style_name, 'resource/style/mirror.jpg')
style_image = Image(style_p)
style_image.image_resize(P.width, P.high)
style_image.extend_dim()
trains_files = util.get_files(P.st_train_path)
model_saved_path = P.st_model_saved_dir + style_name + '/'
style_features = get_style_feature(style_image, '/cpu:0', style_name)
with tf.Session() as session:
writer = tf.summary.FileWriter(P.st_logs + style_name + "_{}".format(time.time()))
model = StyleTransform(style_features,
P.st_batch_size,
width=P.width,
height=P.high,
content_weight=P.st_content_weight,
style_weight=P.st_style_weight,
tv_weight=P.st_tv_weight)
model.create_network()
TASK_NAME = 'COVID Lung Ultrasound'
TRAINING_TYPE = 'federated'
# Currently we take the first `NUM_IMAGES` in the folder for each peer. We should make a more complex distribution.
NUM_IMAGES = 10
# paths to folders containing covid positive and coivd negative patients
POSITIVE_CLASS_PATH = r'covid-positive'
NEGATIVE_CLASS_PATH = r'covid-negative'
start_time = time.time()
op = webdriver.ChromeOptions()
op.add_argument('headless')
drivers = [webdriver.Chrome(ChromeDriverManager().install()) for i in range(NUM_PEERS)]
# drivers = [webdriver.Chrome(ChromeDriverManager().install(), opt) for i in range(NUM_PEERS)]
positive_files = get_files(POSITIVE_CLASS_PATH, NUM_IMAGES, '.png')
negative_files = get_files(NEGATIVE_CLASS_PATH, NUM_IMAGES, '.png')
if DATA_SPLIT == 'partition':
pos_partitions = partition(positive_files, NUM_PEERS)
neg_partitions = partition(negative_files, NUM_PEERS)
elif DATA_SPLIT == 'rpartition':
pos_partitions = r_partition(positive_files, NUM_PEERS)
neg_partitions = r_partition(negative_files, NUM_PEERS)
elif DATA_SPLIT == 'spartition':
pos_partitions = s_partition(positive_files, RATIOS)
neg_partitions = s_partition(negative_files, RATIOS)
for index, driver in enumerate(drivers):
# Click 'Start Building' on home page
find_task_page(driver, PLATFORM, TASK_NAME, TRAINING_MODE)
# paths to the file containing the CSV file of Titanic passengers with 12 columns
IMAGE_FILE_PATH = r'CIFAR10'
LABEL_FILE_PATH = 'labels.csv'
NUM_IMAGES = 10
# Download and extract chromedriver from here: https://sites.google.com/a/chromium.org/chromedriver/downloads
op = webdriver.ChromeOptions()
op.add_argument('headless')
# You can add options=op for chrome headless mode
# drivers = [webdriver.Chrome(ChromeDriverManager().install(), options=op) for i in range(NUM_PEERS)]
drivers = [webdriver.Chrome(ChromeDriverManager().install()) for i in range(NUM_PEERS)]
start_time = time.time()
if DATA_SPLIT == 'partition':
partitions = partition(get_files(IMAGE_FILE_PATH, NUM_IMAGES, '.png'), NUM_PEERS)
elif DATA_SPLIT == 'spartition':
partitions = s_partition(get_files(IMAGE_FILE_PATH, NUM_IMAGES, '.png'), RATIOS)
elif DATA_SPLIT == 'rpartition':
partitions = r_partition(get_files(IMAGE_FILE_PATH, NUM_IMAGES, '.png'), NUM_PEERS)
for index, driver in enumerate(drivers):
find_task_page(driver, PLATFORM, TASK_NAME, TRAINING_MODE)
# Upload files on Task Training
time.sleep(6)
if DATA_SPLIT != 'iid':
driver.find_element_by_id('hidden-input_cifar10_Images').send_keys(' \n '.join(partitions[index]))
driver.find_element_by_id('hidden-input_cifar10_Labels').send_keys(os.path.abspath(LABEL_FILE_PATH))
def decode_to_lattices(model, output_dir, model_dir, mfc_list, lm, dict, model_list, gold_mlf):
sys.stderr.write('Decoding to lattices\n')
output_mlf = '%s/train_recog.mlf' %output_dir
results_log = '%s/results.log' %output_dir
## Create a config file to use with HDecode
hdecode_config = '%s/hdecode.config' %output_dir
fh = open(hdecode_config, 'w')
#fh.write('HLANGMODFILTER = "gunzip -c $.gz"\n')
fh.write('HNETFILTER = "gunzip -c < $.gz"\n')
fh.write('HNETOFILTER = "gzip -c > $.gz"\n')
fh.write('RAWMITFORMAT = T\n')
fh.write('HPARM: TARGETKIND = MFCC_0_D_A_Z\n')
fh.write('GCFREQ = 50\n')
fh.write('HLAT:TRACE = 19\n')
fh.write('HLVNET:TRACE = 1\n')
fh.write('HLVREC:TRACE = 1\n')
fh.write('HLVLM:TRACE = 1\n')
fh.write('LATPRUNEBEAM = 500.0\n')
fh.write('MAXLMLA = 3.0\n')
fh.write('BUILDLATSENTEND = T\n')
fh.write('FORCELATOUT = F\n')
fh.write('STARTWORD = <s>\n')
fh.write('ENDWORD = </s>\n')
fh.close()
## HDecode parameters
utts_per_split = 100
block_size = 5
beam = 150.0
word_end_beam = 125.0
max_model = 10000
lm_scale = 15.0
word_insertion_penalty = 0.0
def hdecode(input, output):
cmd = 'HDecode -A -D -V -T 9 -o M -z lat -C %s' %hdecode_config
cmd += ' -H %s/MMF' %model_dir
cmd += ' -k %d' %block_size
cmd += ' -t %f 100.0' %beam
cmd += ' -v %f 115.0' %word_end_beam
cmd += ' -u %d' %max_model
cmd += ' -s %f' %lm_scale
cmd += ' -p %f' %word_insertion_penalty
cmd += ' -w %s' %lm
cmd += ' -S %s' %input
cmd += ' -l %s/' %output
cmd += ' %s %s' %(dict, model_list)
if model.verbose > 0: cmd += ' >%s/%s.log' %(output_dir, os.path.basename(input))
return cmd
## Split up MFC list
split_mfc = SplitList(output_dir, mfc_list, by_path=True)
## Create the HDecode commands
cmds = []
inputs = split_mfc.get_files()
for input in inputs:
output = '%s/%s' %(output_dir, split_mfc.get_key(input))
if not os.path.isdir(output): os.makedirs(output)
cmds.append(hdecode(input, output))
if model.local == 1:
for cmd in cmds:
print cmd
print os.popen(cmd).read()
else:
cmds_file = '%s/hdecode.commands' %output_dir
fh = open(cmds_file, 'w')
for cmd in cmds: fh.write('%s\n' %cmd)
fh.close()
util.run_parallel(cmds_file, model.jobs, output_dir)
## Copy old mfc list
old_mfc_list = '%s/mfc_old.list' %output_dir
os.system('cp %s %s' %(mfc_list, old_mfc_list))
## Prune bad lats from the mfc list
lat_ids = [os.path.basename(f).split('.')[0] for f in util.get_files(output_dir, r'.*\.lat')]
bad_count = 0
fh = open(mfc_list, 'w')
for mfc in open(old_mfc_list):
id = os.path.basename(mfc.strip()).split('.')[0]
## Check for missing transcriptions
if id not in lat_ids:
if model.verbose > 1: util.log_write(model.logfh, 'removed bad lat [%s]' %id)
bad_count += 1
else: fh.write(mfc)
fh.close()
util.log_write(model.logfh, 'removed bad lats [%d]' %bad_count)
## Create an MLF from the recognition output
outputs = util.get_files(output_dir, r'.*\.rec')
os.popen('rm -f %s' %output_mlf)
fh = open(output_mlf, 'w')
fh.write('#!MLF!#\n')
for output in outputs:
fh.write('"%s"\n' %output)
for line in open(output):
if '<s>' in line or '</s>' in line: continue
fh.write(line)
fh.write('.\n')
fh.close()
## Evaluate
cmd = 'HResults -h -n -A -T 1'
cmd += ' -I %s' %gold_mlf
cmd += ' %s %s > %s' %(model_list, output_mlf, results_log)
os.system(cmd)
print os.popen('cat ' + results_log).read()
#coding:utf8
from ConfigParser import ConfigParser
import pymongo
from util import get_files
__author__ = 'cy'
cf = ConfigParser()
cf.read('dev.cfg')
city_num = int(cf.get('calculate', 'city_num'))
predict_hour = int(cf.get('calculate', 'predict_hour'))
file_path = cf.get('file', 'filepath')
start_time = cf.get('file', 'start_time')
end_time = cf.get('file', 'end_time')
gaps = eval(cf.get('calculate', 'gaps'))
all_files = (get_files(start_time, end_time))
day_gaps = eval(cf.get('calculate', 'day_gaps'))
mongo_host = cf.get('mongodb', 'host')
mongo_port = int(cf.get('mongodb', 'port'))
mongo_db_name = cf.get('mongodb', 'db_name')
client = pymongo.MongoClient(mongo_host, mongo_port)
db = client.get_database(mongo_db_name)
bins = eval(cf.get('calculate', 'bins'))
collection_name = cf.get('mongodb', 'collection')
def phonemark_lattices(model, lattice_dir, output_dir, model_dir, mfc_list, lm, dict, model_list):
sys.stderr.write('Phonemarking lattices\n')
## Create a config file to use with HDecode
hdecode_config = '%s/hdecode.config' %output_dir
fh = open(hdecode_config, 'w')
#fh.write('HLANGMODFILTER = "gunzip -c $.gz"\n')
fh.write('HNETFILTER = "gunzip -c < $.gz"\n')
fh.write('HNETOFILTER = "gzip -c > $.gz"\n')
fh.write('RAWMITFORMAT = T\n')
fh.write('HPARM: TARGETKIND = MFCC_0_D_A_Z\n')
fh.write('GCFREQ = 50\n')
fh.write('HLAT:TRACE = 19\n')
fh.write('HLVNET:TRACE = 1\n')
fh.write('HLVREC:TRACE = 1\n')
fh.write('HLVLM:TRACE = 1\n')
fh.write('LATPRUNEBEAM = 500.0\n')
fh.write('MAXLMLA = 3.0\n')
fh.write('BUILDLATSENTEND = T\n')
fh.write('FORCELATOUT = F\n')
fh.write('STARTWORD = <s>\n')
fh.write('ENDWORD = </s>\n')
fh.close()
## HDecode parameters
utts_per_split = 100
block_size = 5
beam = 200.0
lm_scale = 15.0
word_insertion_penalty = 0.0
def hdecode_mod(input, path):
input_dir = '%s/%s/' %(lattice_dir, path)
if not os.path.isdir(input_dir):
input_dir = '%s/%s/' %(lattice_dir, path.replace('_', ''))
cmd = 'HDecode.mod -A -D -V -T 9 -q tvaldm -z lat -X lat -C %s' %hdecode_config
cmd += ' -H %s/MMF' %model_dir
cmd += ' -k %d' %block_size
cmd += ' -t %f' %beam
cmd += ' -s %f' %lm_scale
cmd += ' -p %f' %word_insertion_penalty
cmd += ' -w' # %s' %lm
cmd += ' -S %s' %input
cmd += ' -l %s/%s/' %(output_dir, path)
cmd += ' -L %s' %input_dir
cmd += ' %s %s' %(dict, model_list)
if model.verbose > 0: cmd += ' >%s/%s.log' %(output_dir, os.path.basename(input))
return cmd
## Split up MFC list with unix split
split_mfc = SplitList(output_dir, mfc_list, by_path=True)
## Create the HDecode commands
cmds = []
inputs = split_mfc.get_files()
for input in inputs:
key = split_mfc.get_key(input)
new_output = '%s/%s' %(output_dir, key)
if not os.path.isdir(new_output): os.makedirs(new_output)
cmds.append(hdecode_mod(input, key))
if model.local == 1:
for cmd in cmds:
print cmd
print os.popen(cmd).read()
else:
cmds_file = '%s/hdecode_mod.commands' %output_dir
fh = open(cmds_file, 'w')
for cmd in cmds: fh.write('%s\n' %cmd)
fh.close()
util.run_parallel(cmds_file, model.jobs, output_dir)
## Copy old mfc list
old_mfc_list = '%s/mfc_old.list' %output_dir
os.system('cp %s %s' %(mfc_list, old_mfc_list))
## Prune bad lats from the mfc list
lat_ids = [os.path.basename(f).split('.')[0] for f in util.get_files(output_dir, r'.*\.lat')]
bad_count = 0
fh = open(mfc_list, 'w')
for mfc in open(old_mfc_list):
id = os.path.basename(mfc.strip()).split('.')[0]
## Check for missing transcriptions
if id not in lat_ids:
if model.verbose > 1: util.log_write(model.logfh, 'removed bad lat [%s]' %id)
bad_count += 1
else: fh.write(mfc)
fh.close()
util.log_write(model.logfh, 'removed bad lats [%d]' %bad_count)
def dumpLogFile():
if config['log-format'] == 'normal':
def dump(j,f):
f.write(json.dumps(j,sort_keys=True,indent=1).encode())
elif config['log-format'] == 'tiny':
def dump(j,f):
f.write(json.dumps(j,sort_keys=True,separators=(',',':')).encode())
elif config['log-format'] == 'pretty':
def dump(j,f):
f.write(json.dumps(j,sort_keys=True,indent=4, separators=(',', ': ')).encode())
else:
def dump(j,f):
f.write(json.dumps(j,sort_keys=True,indent=1).encode())
messagebus.postMessage("system/notifications","Invalid config option for 'log-format' so defaulting to normal")
if config['log-compress'] == 'bz2':
openlog= bz2.BZ2File
ext = '.json.bz2'
elif config['log-compress'] == 'gzip':
openlog = gzip.GzipFile
ext = '.json.gz'
elif config['log-compress'] == 'none':
openlog = open
ext = '.json'
else:
openlog = open
messagebus.postMessage("system/notifications","Invalid config option for 'log-compress' so defaulting to no compression")
global log,loglistchanged
global approxtotallogentries
with savelock:
temp = log
log = defaultdict(list)
approxtotallogentries = 0
if loglistchanged:
#Save the list of things to dump
with open(os.path.join(directories.logdir,"whattosave.txt"),'w') as f:
for i in toSave:
f.write(i+'\n')
loglistchanged = False
#Get rid of anything that is not in the list of things to dump to the log
temp2 = {}
saveset = set(toSave)
for i in temp:
#Parsetopic is a function that returns all subscriptions that would match a topic
if not set(messagebus.MessageBus.parseTopic(i)).isdisjoint(saveset):
temp2[i] = temp[i]
temp = temp2
#If there is no log entries to save, don't dump an empty file.
if not temp:
return
where =os.path.join(directories.logdir,'dumps')
#Actually dump the log.
with openlog(os.path.join(where,str(time.time())+ext),'wb') as f:
print()
dump(temp,f)
f.close()
asnumbers = {}
for i in util.get_files(where):
try:
#Remove extensions
if i.endswith(".json"):
asnumbers[float(i[:-5])] = i
elif i.endswith(".json.gz"):
asnumbers[float(i[:-8])] = i
elif i.endswith(".json.bz2"):
asnumbers[float(i[:-9])] = i
except ValueError:
pass
maxsize = unitsofmeasure.strToIntWithSIMultipliers(config['keep-log-files'])
size = 0
#Loop over all the old log dumps and add up the sizes
for i in util.get_files(where):
size = size + os.path.getsize(os.path.join(where,i))
#Get rid of oldest log dumps until the total size is within the limit
for i in sorted(asnumbers.keys()):
if size <= maxsize:
break
size = size - os.path.getsize(os.path.join(where,i))
os.remove(os.path.join(where,asnumbers[i]))
NUM_IMAGES = 20
# Digit folder paths, change to \ for macOS
DIGIT_CLASS_PATHS = [
r'0', r'1', r'2', r'3', r'4', r'5', r'6', r'7', r'8', r'9'
]
start_time = time.time()
op = webdriver.ChromeOptions()
op.add_argument('headless')
drivers = [
webdriver.Chrome(ChromeDriverManager().install()) for i in range(NUM_PEERS)
]
digit_files = [
get_files(DIGIT_CLASS_PATHS[i], NUM_IMAGES, '.jpg')
for i in range(len(DIGIT_CLASS_PATHS))
]
if DATA_SPLIT == 'partition':
digit_partitions = [
partition(digit_files[i], NUM_PEERS) for i in range(len(digit_files))
]
elif DATA_SPLIT == 'rpartition':
digit_partitions = [
r_partition(digit_files[i], NUM_PEERS) for i in range(len(digit_files))
]
elif DATA_SPLIT == 'spartition':
digit_partitions = [
s_partition(digit_files[i], RATIOS) for i in range(len(digit_files))
]
def generate():
impath = "/home/john/wsdlims_ripped/ECIR2016TurkData/screenshots" # args["ip"]
compath = "/home/john/wsdlims_ripped/ECIR2016TurkData/composites" # args["cp"]
with open("tms2.json", "r") as tm:
it = json.load(tm)
goodUris = []
with open("gooduris_20160225.txt", "r") as read:
for uri in map(lambda line: line.rstrip("\n"), read):
goodUris.append(uri)
color = {} # type: dict[str,cs]
with open("temporalPairs.csv","r") as read:
reader = csv.DictReader(read)
for row in reader:
color[row['site']] = cs(row)
with open("compositeToComposite.csv","r") as read:
reader = csv.DictReader(read)
for row in reader:
arsim = row['alsumRandomSim']
atsim = row['alsumTemporalSim']
color[row['site']].ctcRsim = arsim
color[row['site']].ctcTsim = atsim
with open("alSumVSrandom_onetoone.csv","r") as read:
reader = csv.DictReader(read)
for row in reader:
arsim = row['average']
color[row['site']].otoRsim = arsim
with open("alSumVStemporalInterval_onetoone.csv","r") as read:
reader = csv.DictReader(read)
for row in reader:
arsim = row['average']
color[row['site']].otoTsim = arsim
with open("wins.csv","r") as read:
reader = csv.DictReader(read)
for row in reader:
if color.get(row['site'],None) is not None:
color[row['site']].won['r'] = row['awr']
color[row['site']].won['ti'] = row['awt']
tms = it['tms']
timeMaps = {} # type: dict[str,TM]
for s in tms:
it = TM(s)
timeMaps[it.getURIKey()] = it
tmk = list(filter(lambda x: len(x) > 2, timeMaps.keys()))
compisits = get_files(compath, lambda f: "allTheSame" not in f and check_if_goodURI(f, goodUris) and
"interval" not in f)
print(compisits)
uniqueComposite = set()
for c in compisits:
uniqueComposite.add(gsite(c))
compisits = sorted(list(uniqueComposite))
# 640 641
# self.site, self.alSum, self.random, self.aVr, self.temporal, self.aVt,
# self.tmNumMementos, self.tmTimeSpan,
# self.tmNumM2k, self.tmTimeSpan2k, self.tmNumM05k, self.tmTimeSpan05k
# self.won['Random'],
# self.won['TemporalInterval']
with open("allTm2.csv","w+") as out:
out.write("site,ah,mh,mdif,nmemento,timespan,nummtwo,twotimespan,numof,timespanof,aWP,moto,mtcr,method\n")
for c in sorted(compisits):
# print(c)
for tmkey in filter(lambda x: len(x) > 2, tmk):
if tmkey in c:
print(timeMaps[tmkey].timeSpan(), timeMaps[tmkey].numMentos,
timeMaps[tmkey].timeSpanAfter(2000), timeMaps[tmkey].numMementosAfter(2000),
timeMaps[tmkey].timeSpanAfter(2005), timeMaps[tmkey].numMementosAfter(2005))
cc = color[tmkey]
cc.setTMInfo(timeMaps[tmkey].timeSpan(), timeMaps[tmkey].numMentos,
timeMaps[tmkey].timeSpanAfter(2000), timeMaps[tmkey].numMementosAfter(2000),
timeMaps[tmkey].timeSpanAfter(2005), timeMaps[tmkey].numMementosAfter(2005))
out.write(cc.getRString())
out.write(cc.getTString())
print("______________________________")
