def test_filter_simple(self):
res = [
'',
'',
'',
'cow',
'siamese',
'wonderland',
'foo',
'toothpaste',
'',
'',
'',
'milky',
'flight-manual',
'toothpick',
'',
None,
'',
'',
]
generated = []
filter = Filter(options)
for word in words:
generated.append(filter.filter(word))
self.assertEqual(generated, res)
def __init__(self, nelx, nely, volfrac, penal, rmin, ft, gui, bc):
self.n = nelx * nely
self.opt = nlopt.opt(nlopt.LD_MMA, self.n)
self.passive = bc.get_passive_elements()
self.xPhys = np.ones(self.n)
if self.passive is not None:
self.xPhys[self.passive] = 0
# set bounds
ub = np.ones(self.n, dtype=float)
self.opt.set_upper_bounds(ub)
lb = np.zeros(self.n, dtype=float)
self.opt.set_lower_bounds(lb)
# set stopping criteria
self.opt.set_maxeval(2000)
self.opt.set_ftol_rel(0.001)
# set objective and constraint functions
self.opt.set_min_objective(self.compliance_function)
self.opt.add_inequality_constraint(self.volume_function, 0)
# setup filter
self.ft = ft
self.filtering = Filter(nelx, nely, rmin)
# setup problem def
self.init_problem(nelx, nely, penal, bc)
self.volfrac = volfrac
# set GUI callback
self.init_gui(gui)
def text_reply(msg):
print msg
content = msg['Content']
if msg['FromUserName'] == msg['ToUserName']:
print content
WORD_CLEAR = u"自助回复清除成功"
WORD_ADD = u"自助回复增加成功"
WORD_UPDATE = u"自助回复更新成功"
if content == "QC": #清除
AUTO_REPLY.clear()
itchat.send('%s' % (WORD_CLEAR), msg['FromUserName'])
return
sub = content.split("Q")
if len(sub) == 3:
q = sub[1]
a = sub[2]
AUTO_REPLY[q] = a
itchat.send('%s' % (WORD_ADD), msg['FromUserName'])
return
if msg['Type'] == 'Text':
if AUTO_REPLY.has_key(content):
itchat.send('%s' % (AUTO_REPLY[content]), msg['FromUserName'])
return
if msg['Type'] == 'Sharing':
imgFilter = Filter()
img_list = imgFilter.getContents(msg['Url'])
i=0
for img in img_list:
print img_list,img,i
i = i+1
itchat.send('@img@%s' % str(i)+".gif" ,msg['FromUserName'])
def Initialize(credentials=None, opt_url=None):
"""Initialize the EE library.
If this hasn't been called by the time any object constructor is used,
it will be called then. If this is called a second time with a different
URL, this doesn't do an un-initialization of e.g.: the previously loaded
Algorithms, but will overwrite them and let point at alternate servers.
Args:
credentials: OAuth2 credentials.
opt_url: The base url for the EarthEngine REST API to connect to.
"""
data.initialize(credentials, (opt_url + '/api' if opt_url else None), opt_url)
# Initialize the dynamically loaded functions on the objects that want them.
ApiFunction.initialize()
Element.initialize()
Image.initialize()
Feature.initialize()
Collection.initialize()
ImageCollection.initialize()
FeatureCollection.initialize()
Filter.initialize()
Geometry.initialize()
List.initialize()
Number.initialize()
String.initialize()
Date.initialize()
Dictionary.initialize()
_InitializeGeneratedClasses()
_InitializeUnboundMethods()
def delLogPath(self, path):
if not self.containsLogPath(path):
logSys.error(path + " is not monitored")
else:
self.monitor.stop_watch(path)
Filter.delLogPath(self, path)
logSys.info("Removed logfile = %s" % path)
def test_emoji(self):
app = Filter()
app.blocks = ['🚫']
sentences = [
'orospu çocuğu yarak gibi kitap',
'orrrrrooooossssspuuuu evladı',
'am gibi kitap',
'sik gibi kitap',
'Sikimi ye Booooookkkk gibi kitap',
]
results = [
'🚫 çocuğu 🚫 gibi kitap',
'🚫 evladı',
'🚫 gibi kitap',
'🚫 gibi kitap',
'🚫 ye 🚫 gibi kitap',
]
news = []
for sentence in sentences:
news.append(app.replace(sentence))
self.assertEqual(news, results)
def threshold(self):
current_image = self.result_image if self.stack_filters else self.input_image
threshold_args = {}
threshold_args['thresh_value'] = mbox('Threshold cuttof value:',
entry=True)
if threshold_args['thresh_value']:
threshold_args['defaults'] = mbox('Use defaults?', ('yes', 'y'),
('no', 'n'))
if threshold_args['defaults'] == 'n':
threshold_args['max_value'] = mbox('Max value:', entry=True)
threshold_args['thresh_type'] = mbox('Threshold type:',
entry=True)
# mbox(threshold_args, frame=False)
self.undo_stack.append(self.result_image)
if threshold_args['defaults'] == 'n':
self.result_image = Filter.threshold(
current_image, int(threshold_args['thresh_value']),
int(threshold_args['max_value']),
int(threshold_args['thresh_type']))
else:
self.result_image = Filter.threshold(
current_image, int(threshold_args['thresh_value']))
self.show_image()
def highpass(self):
current_image = self.result_image if self.stack_filters else self.input_image
self.undo_stack.append(self.result_image)
highpass_args = {}
highpass_args['defaults'] = mbox('Use defaults?', ('yes', 'y'),
('no', 'n'))
if highpass_args['defaults'] == 'n':
highpass_args['type'] = mbox('High Pass Type', ('Basic', 0),
('Original Factor', 1))
highpass_args['sigma'] = mbox('Sigma:', entry=True)
if highpass_args['type'] == 1:
highpass_args['reinforcement_factor'] = mbox(
'Reinforcement Factor:', entry=True)
# mbox(highpass_args, frame=False)
if highpass_args['defaults'] == 'n' and not highpass_args['sigma']:
return
if highpass_args['defaults'] == 'n':
self.result_image = Filter.highpass(
current_image, highpass_args['type'],
int(highpass_args['sigma']),
float(highpass_args['reinforcement_factor']))
else:
self.result_image = Filter.highpass(current_image)
self.show_image()
def objective(args):
args['ksize'] = int(args['ksize'])
filter = Filter(average_disparity,
frame_down_factor,
mem_down_factor,
fovea_shape,
frame_shape,
values,
verbose=False)
filter.params = dict(args)
costs = []
for i in range(source.n_frames):
frame = [
downsample(source.video[i][0], frame_down_factor),
downsample(source.video[i][1], frame_down_factor)
]
disp, fovea_corner = filter.process_frame(source.positions[i], frame)
true_disp = downsample(source.ground_truth[i], frame_down_factor)
costs.append(cost(disp[:, values:], true_disp, average_disparity))
mean_cost = np.mean(costs)
print(mean_cost, args)
return mean_cost
def Initialize(credentials=None, opt_url=None):
"""Initialize the EE library.
If this hasn't been called by the time any object constructor is used,
it will be called then. If this is called a second time with a different
URL, this doesn't do an un-initialization of e.g.: the previously loaded
Algorithms, but will overwrite them and let point at alternate servers.
Args:
credentials: OAuth2 credentials.
opt_url: The base url for the EarthEngine REST API to connect to.
"""
data.initialize(credentials, (opt_url + '/api' if opt_url else None),
opt_url)
# Initialize the dynamically loaded functions on the objects that want them.
ApiFunction.initialize()
Element.initialize()
Image.initialize()
Feature.initialize()
Collection.initialize()
ImageCollection.initialize()
FeatureCollection.initialize()
Filter.initialize()
Geometry.initialize()
List.initialize()
Number.initialize()
String.initialize()
Date.initialize()
Dictionary.initialize()
_InitializeGeneratedClasses()
_InitializeUnboundMethods()
def _generateArtifactList(options):
# load configuration
logging.info("Loading configuration...")
config = Configuration()
config.load(options)
# build list
logging.info("Building artifact list...")
listBuilder = ArtifactListBuilder(config)
artifactList = listBuilder.buildList()
logging.debug("Generated list contents:")
for gat in artifactList:
priorityList = artifactList[gat]
for priority in priorityList:
versionList = priorityList[priority]
for version in versionList:
logging.debug(" %s:%s", gat, version)
#filter list
logging.info("Filtering artifact list...")
listFilter = Filter(config)
artifactList = listFilter.filter(artifactList)
logging.debug("Filtered list contents:")
for gat in artifactList:
priorityList = artifactList[gat]
for priority in priorityList:
versionList = priorityList[priority]
for version in versionList:
logging.debug(" %s:%s", gat, version)
logging.info("Artifact list generation done")
return artifactList
def run(self):
timer = Timer()
timer.start()
# Create list of search urls
search_urls = []
filter = Filter(self.filter, self.startpage, self.maxpages)
for page in range(self.startpage, self.startpage + self.maxpages):
search_urls.append(filter.create_filter_url((page - 1) * 10))
# Create pool of worker threads
pool = ThreadPool(4)
# Open the urls in their own threads
organisaties = pool.map(unwrap_self_process_search, zip([self] * len(search_urls), search_urls))
pool.close()
pool.join()
results = {}
results["organisaties"] = self.consolidate(organisaties)
timer.stop()
results["stats"] = { "exectime": timer.exectime(), "matches": { "total": str(self.search_results["results"]), "pages": str(self.search_results["pages"]) }, "read": { "page_from": str(self.startpage), "page_to": str(self.maxpages) } }
return results
def config_analysis( alg_list ) :
filt_event = Filter('FilterTauEvent')
filt_event.cut_nTau = '== 1'
filt_event.cut_tauStatus = ' == 3'
alg_list.append(filt_event)
def peakPointers(self, signals, window_size, threshold, reverse=False):
"""
locates & count all peak / bottom pointers
return a tuple (num_of_peaks, array_of_peak_indices)
"""
# first normalize signals
# normalize all peak / lows ranges
#norm_signals = self.guassianNormalize(signals)
# med-filter to give away noises & sharp peaks
med_filterd_signals = Filter.medfilter(signals, window_size)
# caculate residual, only reserve candidate peaks
peak_candidates = signals - med_filterd_signals
# plt.plot(peak_candidates)
# non-max-suppress, reserve one highest pointers for peaks
peaks = Filter.nms(peak_candidates, window_size, reverse)
# plt.plot(peaks)
# threshold check, remove suspecious peaks
idx = np.arange(0, len(signals))
if not reverse:
masks = peaks > threshold
else:
masks = peaks < threshold
peak_idx = idx[masks]
num_of_peaks = masks.sum()
return peak_idx
def addLogPath(self, path):
if self.containsLogPath(path):
logSys.error(path + " already exists")
else:
self.monitor.watch_file(path, self.callback)
Filter.addLogPath(self, path)
logSys.info("Added logfile = %s" % path)
def __init__(self, jail):
Filter.__init__(self, jail)
self.__modified = False
self.__lastModTime = dict()
self.__file404Cnt = dict()
logSys.info("Created FilterPoll")
def test_deletion(self):
app = Filter()
sentences = [
'orospu çocuğu yarak gibi kitap',
'orrrrrooooossssspuuuu evladı',
'am gibi kitap',
'sik gibi kitap',
'Sikimi ye Booooookkkk gibi kitap',
'güzel kitap çok sevdim',
'resmen mükemmel',
]
results = [
'güzel kitap çok sevdim',
'resmen mükemmel',
]
news = []
for sentence in sentences:
result = app.detect(sentence)
if result:
news.append(result)
self.assertEqual(news, results)
def Initialize(credentials="persistent", opt_url=None):
"""Initialize the EE library.
If this hasn't been called by the time any object constructor is used,
it will be called then. If this is called a second time with a different
URL, this doesn't do an un-initialization of e.g.: the previously loaded
Algorithms, but will overwrite them and let point at alternate servers.
Args:
credentials: OAuth2 credentials. 'persistent' (default) means use
credentials already stored in the filesystem, or raise an explanatory
exception guiding the user to create those credentials.
opt_url: The base url for the EarthEngine REST API to connect to.
"""
if credentials == "persistent":
credentials = _GetPersistentCredentials()
data.initialize(credentials, (opt_url + "/api" if opt_url else None), opt_url)
# Initialize the dynamically loaded functions on the objects that want them.
ApiFunction.initialize()
Element.initialize()
Image.initialize()
Feature.initialize()
Collection.initialize()
ImageCollection.initialize()
FeatureCollection.initialize()
Filter.initialize()
Geometry.initialize()
List.initialize()
Number.initialize()
String.initialize()
Date.initialize()
Dictionary.initialize()
Terrain.initialize()
_InitializeGeneratedClasses()
_InitializeUnboundMethods()
def test_filter_finish_same_as_stop(self):
words = [
'cow',
'foo',
'fish',
'flamingo',
'trampoline',
'apollo',
'cow',
'pancakes',
]
options = {'start': 'cow', 'stop': 'Flamingo', 'finish': 'flamingo'}
res = [
'',
'foo',
'fish',
None,
'',
'',
'',
'pancakes',
]
w = Filter(options)
filtered = []
for word in words:
filtered.append(w.filter(word))
self.assertEqual(res, filtered)
def main():
distance = '30'
zip_ = '80223'
min_price = '300'
max_price = '1500'
has_pic = '1' # 0 to disable
bundle = '1' # 0 to disable
main_search = 'https://denver.craigslist.org/search/bia?h\
asPic={}&bundleDuplicates={}&search_distance={}&postal={}&min_price=\
{}&max_price={}'.format(has_pic, bundle, distance, zip_, min_price, max_price)
post_list = Scrape.scrape_search_pg(main_search)
results = []
for post in post_list:
post_Obj = Filter(post[0])
result = Filter.quick_filter(post_Obj)
if result:
result = Filter.size_filter(post_Obj)
if result:
results.append(
Keywords.score(post_Obj, Keywords.find(post_Obj)))
if len(results) > 0:
results = sorted(results, key=lambda x: x[2], reverse=True)
Message.send(Message.format(results))
def __getPlaintext(self):
# extract plaintext from pdf
paper = PdfLib(self.wd + os.sep + self.filename)
textBeginning = self.__guessDocBegining(self.filename)
plaintext = paper.pdf2txt(textBeginning, "max")
# normalize text
f = Filter(asString=plaintext)
plaintext = f.substitutions() \
.oneCharPerLine() \
.normalizeCaracters() \
.lower() \
.uselessCharacters() \
.multipleDots() \
.listEnum() \
.digits() \
.shortTokens() \
.multipleSpaces() \
.getResult()
# experience shows, that less than 6000 characters is mostly waste
if len(plaintext) > 6000:
result = {}
result[self.langKey] = self.__guessLang(plaintext)
result[self.plaintextKey] = plaintext
result[self.filenameKey] = self.filename
return result
else:
raise Exception(u"Document is too short.")
def __getPlaintext(self):
# extract plaintext from pdf
paper = PdfLib(self.wd + os.sep + self.filename)
textBeginning = self.__guessDocBegining(self.filename)
plaintext = paper.pdf2txt(textBeginning, "max")
# normalize text
f = Filter(asString=plaintext)
plaintext = (
f.substitutions()
.oneCharPerLine()
.normalizeCaracters()
.lower()
.uselessCharacters()
.multipleDots()
.listEnum()
.digits()
.shortTokens()
.multipleSpaces()
.getResult()
)
# experience shows, that less than 6000 characters is mostly waste
if len(plaintext) > 6000:
result = {}
result[self.langKey] = self.__guessLang(plaintext)
result[self.plaintextKey] = plaintext
result[self.filenameKey] = self.filename
return result
else:
raise Exception(u"Document is too short.")
def __init__(self, list_of_positive_training_file_paths, list_of_negative_training_file_paths):
unfiltered_training_files = [val for pair in zip(list_of_positive_training_file_paths, list_of_negative_training_file_paths) for val in pair]
filter = Filter()
excellent_training_files = filter.get_excellent_training_files(unfiltered_training_files)
poor_training_files = filter.get_poor_training_files(unfiltered_training_files)
self.hitsCalculator = HitCalculator(excellent_training_files, poor_training_files)
self.phrase_dictionary = {}
def get_entry(self, dn, attributes=None):
if not attributes:
attributes = ['*']
filter = Filter()
filter.add_equal('objectClass', '*')
results = self.search(dn, filter.build(), ldap.SCOPE_BASE, attributes)
return results[0][1]
def addLogPath(self, path):
if self.containsLogPath(path):
logSys.error(path + " already exists")
else:
self.__lastModTime[path] = 0
self.__file404Cnt[path] = 0
Filter.addLogPath(self, path)
logSys.info("Added logfile = %s" % path)
def delLogPath(self, path):
if not self.containsLogPath(path):
logSys.error(path + " is not monitored")
else:
del self.__lastModTime[path]
del self.__file404Cnt[path]
Filter.delLogPath(self, path)
logSys.info("Removed logfile = %s" % path)
def _get_sorted_map_side(self, main, yesterdays_chefs):
filt = Filter()
weights_s = self._get_sorted_map(self.chefs_side)
weights_s = filt.yesterday(yesterdays_chefs, weights_s)
weights_s = filt.same_person(main, weights_s)
weights_s = filt.roommates(main, self.roommates, weights_s)
return weights_s
def __init__(self, **options):
Filter.__init__(self, **options)
self.predicates = self.predicates or self.build_predicate_list()
if len(self.predicates) == 0:
raise NotImplementedError("Must provide at least one predicate")
self.normalize_predicates()
self.normalize_counted_features()
self.setup_counts()
def foveation_sequence():
frame_down_factor = 1
mem_down_factor = 2 # relative to the frame down factor
coarse_down_factor = 2 # for the coarse comparison
fs = 80
fovea_shape = (fs, fs)
full_values = 128
values = full_values / 2**frame_down_factor
index = 15
n_frames = 10
source = KittiMultiViewSource(index, test=False, n_frames=n_frames)
full_shape = source.frame_ten[0].shape
frame_ten = [downsample(source.frame_ten[0], frame_down_factor),
downsample(source.frame_ten[1], frame_down_factor)]
frame_shape = frame_ten[0].shape
average_disp = source.get_average_disparity()
average_disp = cv2.pyrUp(average_disp)[:frame_shape[0],:frame_shape[1]-values]
filter = Filter(average_disp, frame_down_factor, mem_down_factor,
fovea_shape, frame_shape, values, verbose=False, memory_length=0)
plt.figure()
import matplotlib.cm as cm
for i in range(0, 10, 2):
frame = [downsample(source.frame_sequence[i][0], frame_down_factor),
downsample(source.frame_sequence[i][1], frame_down_factor)]
filter_disp, fovea_corner = filter.process_frame(None, frame)
edge = 5
plt.subplot(5,1,i/2+1)
# plt.subplot(5,2,i+1)
plt.imshow(trim(frame[0], values, edge), cmap = cm.Greys_r)
# remove_axes()
# plt.subplot(5,2,i+2)
# plt.imshow(trim(filter_disp, values, edge), vmin=0, vmax=full_values)
fovea_corner = fovea_corner[0]
# plot_edges(fovea_ij, (fs, fs))
fi, fj = fovea_corner
fm = fs
fn = fs
plt.plot([fj, fj+fn, fj+fn, fj, fj], [fi, fi, fi+fm, fi+fm, fi], 'white')
# plt.scatter(fovea_corner[1]-values+fs/2, fovea_corner[0]-edge+fs/2, s=100, c='green', marker='+', linewidths=2)
# plt.scatter(fovea_corner[1]-values, fovea_corner[0]-edge, s=9, c='green', marker='+', linewidths=3)
# plt.scatter(fovea_corner[1]-values+fs, fovea_corner[0]-edge+fs, s=9, c='green', marker='+', linewidths=3)
# plt.scatter(fovea_corner[1]-values, fovea_corner[0]-edge+fs, s=9, c='green', marker='+', linewidths=3)
# plt.scatter(fovea_corner[1]-values+fs, fovea_corner[0]-edge, s=9, c='green', marker='+', linewidths=3)
remove_axes()
plt.tight_layout(-1)
plt.show()
def searching():
results = []
#print(os.getcwd())
search_this = Filter(csv_path, search_fraze)
for item in search_this.filter_file():
results.append(item[0])
results.append('\n')
# return ''.join(str(results))
return results
class JobFilter(object):
def __init__(self, sites):
self._sites = sites
self._jobs = []
self._bad_titled_jobs = []
self._bad_content_jobs = []
self._filter = Filter()
def get_todays_jobs(self):
self._get_todays_links()
self._filter_on_titles()
self._get_postings_content()
self._filter_on_content()
return (self._jobs, self._bad_content_jobs, self._bad_titled_jobs)
def _get_todays_links(self):
for site in self._sites:
list_soup = self._beautiful_soupify_url(site.get_job_listing_url())
links = site.get_todays_links(list_soup)
jobs = []
for link in links:
jobs.append(Job(link.string, link['href'], site))
self._jobs = jobs
def _filter_on_titles(self):
get_posting_jobs = []
for job in self._jobs:
if self._filter.title(job.get_title()):
get_posting_jobs.append(job)
else:
self._bad_titled_jobs.append(job)
self._jobs = get_posting_jobs
def _get_postings_content(self):
for job in self._jobs:
content_soup = self._beautiful_soupify_url(job.get_link())
job.set_content(content_soup)
def _filter_on_content(self):
good_jobs = []
for job in self._jobs:
if self._filter.content(job.get_content()):
good_jobs.append(job)
else:
self._bad_content_jobs.append(job)
self._jobs = good_jobs
def _beautiful_soupify_url(self, url):
html = urllib2.urlopen(url).read()
return BeautifulSoup(html)
def __init__(self, nelx, nely, params, problem_type, bc, gui=None):
"""
Allocate and initialize internal data structures.
"""
n = nelx * nely
self.nelx = nelx
self.nely = nely
self.opt = nlopt.opt(nlopt.LD_MMA, n)
self.problem_type = problem_type
# Alloc arrays
self.x_phys = numpy.ones(n)
self.x_rgb = numpy.ones((nelx, nely, 3))
# Set bounds
lb = numpy.array(params.densityMin * numpy.ones(n, dtype=float))
ub = numpy.array(1.0 * numpy.ones(n, dtype=float))
bc.set_passive_elements(nelx, nely, lb, ub, params.problemOptions)
self.opt.set_upper_bounds(ub)
self.opt.set_lower_bounds(lb)
# Set stopping criteria
self.opt.set_maxeval(params.maxSolverStep)
self.opt.set_ftol_rel(0.0)
# Setup topopt problem
if problem_type.involves_compliance():
self.problem = TopoptProblem(nelx, nely, params, bc)
# Setup filter
self.filtering = Filter(nelx, nely, params, problem_type)
# Setup appearance matcher
if problem_type.involves_appearance():
self.exemplar_rgb = images.load_exemplar(params)
self.appearance_cl = AppearanceCL(params.lambdaOccurrenceMap,
params.exponentSimilarityMetric,
params.appearanceNormWeight)
# Setup user parameters
self.params = params
# Setup functional right-hand sides
self.volume_max = self.params.volumeFracMax * n
self.volume_min = self.params.volumeFracMin * n
self.appearance_max = 0
self.compliance_max = 0
if problem_type.involves_compliance():
if 'complianceMax' in params:
self.compliance_max = params.complianceMax
# Define optimization problem
self.init_problem()
# Set GUI callback
self.gui = gui
def test_filter(self):
filter = Filter(file_path='../../test_data/filter/Test.csv')
date = datetime.datetime.strptime('1/3/2002', "%m/%d/%Y").date()
self.assertTrue(filter.is_white_listed('ABEV3', date),
'filter not working')
self.assertFalse(filter.is_white_listed('NEXISTE4', date),
'filter not working')
"""date = datetime.datetime.strptime("1/1/2000", "%m/%d/%Y").date()
def preprocess(self, prop):
self.__logger.debug('preprocessing...')
# filter images separately
glob = self.__globalCNN.process(Filter(prop))
caus = self.__causticCNN.process(Filter(prop))
assert (glob.shape == caus.shape)
predict = glob + caus
return predict
def filter(self, q):
"""
q is the query.
"""
if not isinstance(q, str):
s = "filter: invalid query argument. You must use a string."
self.logger.error(s)
raise TypeError(s)
f = Filter(self.sites, q)
f.apply()
def add_filter(self, value):
"""Creates filter
:value: can be a Filter or a path to a file
"""
if(isinstance(value, Filter)):
self._filter=value
elif(isinstance(value, str)):
self._filter=Filter(file_path=value)
else:
raise ValueError("Filter type is not supported")
def main():
initialize_log()
config_params = parse_config_params()
logging.info("Starting filter for: {}, operation: {} and parameter {}.".format(
config_params['filter_key'], config_params['filter_operation'], config_params['filter_parameter']
))
filter = Filter(config_params['data_queue'], config_params['sink_exchange'],
config_params['filter_operation'], config_params['filter_key'],
config_params['filter_parameter'], config_params['filter_key_1'],
config_params['filter_key_2'])
filter.start()
def __init__(self):
Filter.__init__(self)
self._name = "Outlier"
self._input = None
self._dimensions = None
self._output = None
# cutoff: we compare the neighborhood average to the current datum; if the
# datum is in the 95th (or higher) percentile, it is considered an outlier.
self.set_parameter_floatrange("cutoff", 0.95, 0.0, 1.0)
# if the averaging out is inclusive of the datum in question
self.set_parameter("inclusive", False, bool)
def __init__(self):
Filter.__init__(self)
self._name = "Outlier"
self._input = None
self._dimensions = None
self._output = None
# cutoff: we compare the neighborhood average to the current datum; if the
# datum is in the 95th (or higher) percentile, it is considered an outlier.
self.set_parameter_floatrange("cutoff", 0.95, 0.0,1.0)
# if the averaging out is inclusive of the datum in question
self.set_parameter("inclusive", False, bool)
def get_audio():
# Stores what user said in var
var = Speech().audio()
# Var goes into find filter function and returns the found filter into choosenfilter
global choosenfilter
choosenfilter = Filter().find_filter(var)
user_filter = Filter().get_name()
global filtervideostream
filtervideostream = FilterCamera(choosenfilter)
curr_string = "You are currently using " + str(user_filter) + "!"
return render_template('filters.html', message=curr_string)
def score_results(self, n_filtered, number_of_medoids,
number_of_iterations):
print("score_results")
# Filtering the trajectory
self.filtered_trajectory, self.filtered_ndx = Filter(
self.trajectory, n_filtered).cabs_filter()
# Clustering the trajectory
self.medoids, self.clusters_dict, self.clusters = Clustering(
self.filtered_trajectory, 'chain ' +
','.join(self.initial_complex.ligand_chains, )).cabs_clustering(
number_of_medoids=number_of_medoids,
number_of_iterations=number_of_iterations)
def filter_ads(url): adblock = Filter(file(ABSPATH+'/ressources/easylist.txt'), is_local=True) if len(adblock.match(self.url)) != 0: self.msg = 'Adblock url' self.status = False return False match_date = re.search(DATE_REGEX, self.url) # if we caught the verified date above, it's an article if match_date is not None: self.date = match_date.group() return True
def __init__(self, aggregatedData):
self.__aData = aggregatedData
self.__currentType = CUSTOMIZATION_TYPE.CAMOUFLAGE
self.__currentSlotIdx = 0
self.__currentDuration = 0
self.__carouselItems = []
self.filter = Filter(self.__aData.availableGroupNames)
self.filter.changed += self.__updateCarouselData
self.slots = Slots(self.__aData)
self.slots.selected += self.__onSlotSelected
self.slots.updated += self.__onSlotUpdated
self.updated = Event()
def test_filter():
mappings = [{'source': 'title'}, {'source': 'description'}, {'source': 'adfasdf'}, {'no source': 'adfasdf'}]
filter = Filter(mappings)
result = {}
result['items'] = [{
'author': 'Fred',
'guid': 1234,
'title': 'Gee golly',
'description': 'This is fun.'
}]
result = filter.filter(result)
print result
assert result['items'] == [{'title': 'Gee golly', 'description': 'This is fun.'}]
def prewitt(self):
current_image = self.result_image if self.stack_filters else self.input_image
if len(self.result_image.shape) == 3:
img_r, img_g, img_b = cv2.split(self.result_image)
img_r = Filter.prewitt(img_r)
img_g = Filter.prewitt(img_g)
img_b = Filter.prewitt(img_b)
self.result_image = cv2.merge((img_r, img_g, img_b))
else:
self.result_image = Filter.prewitt(current_image)
self.show_image()
def test_filter_excluded_GAVs(self):
config = Configuration()
alf = Filter(config)
config.excludedGAVs = ["com.google.guava:guava:1.1.0"]
al = copy.deepcopy(self.artifactList)
self.assertTrue('1.1.0' in al['com.google.guava:guava']['1'])
alf._filterExcludedGAVs(al)
self.assertFalse('1.1.0' in al['com.google.guava:guava']['1'])
config.excludedGAVs = ["com.google.guava:guava:1.0*"]
al = copy.deepcopy(self.artifactList)
self.assertTrue('1.0.0' in al['com.google.guava:guava']['1'])
self.assertTrue('1.0.1' in al['com.google.guava:guava']['1'])
self.assertTrue('1.0.2' in al['com.google.guava:guava']['2'])
self.assertTrue('1.0.0' in al['com.google.guava:guava']['3'])
alf._filterExcludedGAVs(al)
self.assertFalse('1.0.0' in al['com.google.guava:guava']['1'])
self.assertFalse('1.0.1' in al['com.google.guava:guava']['1'])
self.assertFalse('2' in al['com.google.guava:guava'])
self.assertFalse('1.0.0' in al['com.google.guava:guava']['3'])
config.excludedGAVs = ["com.google.guava:*"]
al = copy.deepcopy(self.artifactList)
self.assertTrue('com.google.guava:guava' in al)
alf._filterExcludedGAVs(al)
self.assertFalse('com.google.guava:guava' in al)
def test_filter_duplicates(self):
config = Configuration()
alf = Filter(config)
al = copy.deepcopy(self.artifactList)
self.assertTrue('1.0.0' in al['com.google.guava:guava:pom']['1'])
self.assertTrue('1.0.0' in al['com.google.guava:guava:pom']['3'])
self.assertTrue('1.0.1' in al['org.jboss:jboss-foo:jar']['1'])
self.assertTrue('1.0.1' in al['org.jboss:jboss-foo:jar']['2'])
alf._filterDuplicates(al)
self.assertTrue('1.0.0' in al['com.google.guava:guava:pom']['1'])
self.assertFalse('1.0.0' in al['com.google.guava:guava:pom']['3'])
self.assertTrue('1.0.1' in al['org.jboss:jboss-foo:jar']['1'])
self.assertFalse('1.0.1' in al['org.jboss:jboss-foo:jar']['2'])
def test_filter_duplicates(self):
config = Configuration()
alf = Filter(config)
al = copy.deepcopy(self.artifactList)
self.assertTrue('1.0.0' in al['com.google.guava:guava']['1'])
self.assertTrue('1.0.0' in al['com.google.guava:guava']['3'])
self.assertTrue('1.0.1' in al['org.jboss:jboss-foo']['1'])
self.assertTrue('1.0.1' in al['org.jboss:jboss-foo']['2'])
alf._filterDuplicates(al)
self.assertTrue('1.0.0' in al['com.google.guava:guava']['1'])
self.assertFalse('1.0.0' in al['com.google.guava:guava']['3'])
self.assertTrue('1.0.1' in al['org.jboss:jboss-foo']['1'])
self.assertFalse('1.0.1' in al['org.jboss:jboss-foo']['2'])
def route_dic(terms, temp_original_liwc=None, temp_tags=None):
route_dics = defaultdict(SetMultimap)
f = Filter(term_in_collection=temp_original_liwc,
tag_in_collection=temp_tags)
for term, tags in terms._dict.iteritems():
for tag in tags:
code = f.route(term, tag)
d = route_dics[code]
d[term].add(tag)
for n, dic in route_dics.iteritems():
dump_dic('%s/C%d.txt' % (dic_dir, n), dic=dic)
def __init__(self, filter, startpage, maxpages):
self.filter = filter
self.startpage = startpage
self.maxpages = maxpages
filter = Filter(self.filter, self.startpage, self.maxpages)
self.search_url = filter.create_filter_url(self.startpage)
handler = Handler(self.search_url)
self.search_results = handler.init()
if self.search_results["pages"] < startpage:
raise Exception("Error: startpage exceeds available pages [pages=" + str(self.search_results["pages"]) + "]")
if self.search_results["pages"] < startpage + maxpages:
self.maxpages = self.search_results["pages"]
class MainWin(QtGui.QMainWindow):
lyricEditor = None
def __init__(self, parent=None):
super(MainWin, self).__init__(parent)
self.setupUi()
self.retranslateUi()
pass
def setupUi(self):
'''
main style sheet
'''
style_file = QtCore.QFile("ui/style.css")
style_file.open(QtCore.QFile.ReadOnly)
style_sheet = QtCore.QLatin1String(style_file.readAll())
self.setStyleSheet(style_sheet)
self.setObjectName("MainWindow")
self.resize(900, 680)
self.centralwidget = QtGui.QWidget(self)
self.centralwidget.setObjectName("centralwidget")
self.setCentralWidget(self.centralwidget)
'''
===========菜单=================================================
'''
# 菜单
self.menu_bar = MenuBar(self)
self.setMenuBar(self.menu_bar)
'''
'''
self.statusbar = QtGui.QStatusBar(self)
self.statusbar.setObjectName("statusbar")
self.setStatusBar(self.statusbar)
self.pianoRoll = PianoRoll(self.centralwidget)
# self.pianoRoll.hide()
self.filter = Filter(self.centralwidget)
self.filter.setGeometry(QtCore.QRect(630, 10, 241, 441))
self.lyricEditor = QtGui.QTextEdit(self.centralwidget)
self.lyricEditor.setGeometry(QtCore.QRect(self.filter.x(), 45, 200, 300))
def retranslateUi(self):
self.setWindowTitle(const.WINDOW_TITLE)
def filter_ads(url):
info = {}
info["url"] = url
adblock = Filter(file(ABSPATH+'/ressources/easylist.txt'), is_local=True)
if len(adblock.match(url)) != 0:
info['msg'] = 'Adblock url'
return (False, info)
match_date = re.search(DATE_REGEX, url)
# if we caught the verified date above, it's an article
if match_date is not None:
info["date"] = match_date.group()
info['msg'] = 'verified for date: %s' % info["date"]
return (True, info)
else:
return (True, info)
def parse_filter(self):
last_operator = Filter.__or__
result = None
negated = False
while self.has_tokens():
token = self.get()
if token == '(':
filter = self.parse_filter()
result = self.combine(result, filter, last_operator, negated)
last_operator = Filter.__or__
negated = False
elif token == ')':
return result
elif token == 'and':
last_operator = Filter.__and__
negated = False
elif token == 'or':
last_operator = Filter.__or__
negated = False
elif token == 'not':
negated = True
else:
filter = Filter.matches(re.compile(token))
result = self.combine(result, filter, last_operator, negated)
last_operator = Filter.__or__
negated = False
return result
def __init__(self, pitchnum, stdout, sourcefile, resetPitchSize, resetThresholds, displayBlur, normalizeAtStartup, noDribbling):
self.running = True
self.connected = False
self.stdout = stdout
if sourcefile is None:
self.cap = Camera()
else:
filetype = 'video'
if sourcefile.endswith(('jpg', 'png')):
filetype = 'image'
self.cap = VirtualCamera(sourcefile, filetype)
calibrationPath = os.path.join('calibration', 'pitch{0}'.format(pitchnum))
self.cap.loadCalibration(os.path.join(sys.path[0], calibrationPath))
self.preprocessor = Preprocessor(pitchnum, resetPitchSize)
if self.preprocessor.hasPitchSize:
self.gui = Gui(self.preprocessor.pitch_size)
else:
self.gui = Gui()
self.threshold = Threshold(pitchnum, resetThresholds, displayBlur, normalizeAtStartup)
self.thresholdGui = ThresholdGui(self.threshold, self.gui)
self.features = Features(self.gui, self.threshold)
self.filter = Filter(noDribbling)
eventHandler = self.gui.getEventHandler()
eventHandler.addListener('q', self.quit)
while self.running:
try:
if not self.stdout:
self.connect()
else:
self.connected = True
if self.preprocessor.hasPitchSize:
self.outputPitchSize()
self.gui.setShowMouse(False)
else:
eventHandler.setClickListener(self.setNextPitchCorner)
while self.running:
self.doStuff()
except socket.error:
self.connected = False
# If the rest of the system is not up yet/gets quit,
# just wait for it to come available.
time.sleep(1)
# Strange things seem to happen to X sometimes if the
# display isn't updated for a while
self.doStuff()
if not self.stdout:
self.socket.close()
def __init__(self):
Thread.__init__(self)
logging.basicConfig(filename='trottle.log',level=logging.DEBUG)
logging.basicConfig(format='%(asctime)s %(levelname)s %(message)s',\
datefmt='%m/%d/%Y %I:%M:%S %p')
self.stopped = False
self.active_filters = 0
self.filter_delete_counter = 0
self.tokens = list()
self.devices = dict()
self.max_devices = {
'Number': 0,
'Time' : datetime.now()
}
self.speed = {
'Down' : 0,
'Up' : 0,
'Last_Update' : datetime.now()
}
self.filter = Filter()
self.generate_tokens()
if self.USE_SNMP:
self.SNMPDetector = SNMPDetector()
self.SNMPDetector.start()
class SledFilter: def __init__(self, targets, period): self._dp_filter = Filter(targets, period, self._dp_callback) self._src_filter = Filter(targets, period, self._src_callback) def _dp_callback(self, key): pass def _src_callback(self, key): pass def process(self, sled): self._dp_filter.process( sled.get_dp(), sled.get_dst(), sled.get_timestamp()) self._src_filter.process( sled.get_src(), sled.get_dst(), sled.get_timestamp())
def test_qeinput_filter(self):
input = QEInput(config=fixtures.textMain)
f = Filter("fPlus")
f.setParam("control", "calculation", "'md'")
f.setCard({"name": "occupations", "lines": ("New line",)})
input.applyFilter(f, "plus")
self.assertEqual(input.toString(), fixtures.assertInputFilterPlus)
f = Filter("fMinus")
f.setNamelist({"name":"control"})
f.setCard({"name": "k_points"})
input.applyFilter(f, "minus")
self.assertEqual(input.toString(), fixtures.assertInputFilterMinus)
def route_dic(terms, temp_original_liwc = None, temp_tags = None):
route_dics = defaultdict(SetMultimap)
f = Filter(
term_in_collection = temp_original_liwc,
tag_in_collection = temp_tags
)
for term, tags in terms._dict.iteritems():
for tag in tags:
code = f.route(term, tag)
d = route_dics[code]
d[term].add(tag)
for n,dic in route_dics.iteritems():
dump_dic('%s/C%d.txt' % (dic_dir,n), dic=dic)
def Reset(): """Reset the library. Useful for re-initializing to a different server.""" data.reset() ApiFunction.reset() Image.reset() Feature.reset() Collection.reset() ImageCollection.reset() FeatureCollection.reset() Filter.reset() Geometry.reset() Number.reset() String.reset() _ResetGeneratedClasses() global Algorithms Algorithms = _AlgorithmsContainer()
