class CounterPage(object): def __init__(self, selenium): super(CounterPage, self).__init__() self.selenium = selenium def open(self): self.selenium.get('http://localhost:3000/counter') counter=selector(".App-intro .counter") button=selector(".App-intro") def plus_one(self): self.button.click() @property def number(self): return self.counter.text location=selector(".App-pathname i")
def test_operators(): assert len( selector('name /b/').match(tree2) ) == 4 assert len( selector('name>/b/').match(tree2) ) == 4 assert len( selector('branch>branch>name').match(tree1) ) == 4 assert len( selector('branch>branch>branch>name').match(tree1) ) == 3 assert len( selector('branch branch branch name').match(tree1) ) == 3 assert len( selector('branch branch branch').match(tree1) ) == 3 assert len( selector('branch+branch').match(tree1) ) == 2 assert len( selector('branch~branch~branch').match(tree1) ) == 1 assert len( selector('branch~branch~branch~branch').match(tree1) ) == 0 assert len( selector('branch:is-parent + branch branch > name > /a/:is-leaf').match(tree2) ) == 1 # test all at once; only innermost 'a' matches
def test_operators(): assert len(selector("name /b/").match(tree2)) == 4 assert len(selector("name>/b/").match(tree2)) == 4 assert len(selector("branch>branch>name").match(tree1)) == 4 assert len(selector("branch>branch>branch>name").match(tree1)) == 3 assert len(selector("branch branch branch name").match(tree1)) == 3 assert len(selector("branch branch branch").match(tree1)) == 3 assert len(selector("branch~branch").match(tree1)) == 2 assert len(selector("branch+branch+branch").match(tree1)) == 1 assert len(selector("branch+branch+branch+branch").match(tree1)) == 0 assert ( len(selector("branch:is-parent ~ branch branch > name > /a/:is-leaf").match(tree2)) == 1 ) # test all at once; only innermost 'a' matches
class ContactPage(object): def __init__(self, selenium): super(ContactPage, self).__init__() self.selenium = selenium def open(self): self.selenium.get('http://localhost:3000/contacts') name = selector("input[name=name]") email = selector("input[name=email]") button = selector('button#add') location = selector(".App-pathname i") contact_name = selector(".Contact-name", many=True) contact_email = selector(".Contact-email", many=True) contacts = selector(".Contact", many=True) @property def names(self): return map(lambda contact: contact.text, self.contact_name) @property def emails(self): return map(lambda contact: contact.text, self.contact_email) def add(self, name, email): self.name.send_keys(name) self.email.send_keys(email) self.button.click()
def get_owned(self, find_kind): """ Returns a list of apiobjects which are declare an object of this kind/name as their owner. :param find_kind: The kind to check for ownerReferences :return: A (potentially empty) list of APIObjects owned by this object """ owned = [] def check_owned_by_me(apiobj): if self.do_i_own(apiobj): owned.append(apiobj) selector(find_kind, static_context=self.context).for_each(check_owned_by_me) return owned
def related(self, find_kind): """ Returns a dynamic selector which all of a the specified kind of object which is related to this object. For example: - if this object is a node, and find_kind=='pod', it will find all pods associated with the node. - if this object is a template and find_kind=='buildconfig', it will select buildconfigs created by this template. - if this object is a buildconfig and find_kind='builds', builds created by this buildconfig will be selected. :return: A selector which selects objects of kind find_kind which are related to this object. """ labels = {} this_kind = self.kind() name = self.name() # TODO: add rc, rs, ds, project, ... ? if kind_matches(this_kind, 'node') and kind_matches(find_kind, 'pod'): return selector('pod', all_namespaces=True, field_selectors={'spec.nodeName': self.name()}) if this_kind.startswith("template"): labels["template"] = name elif this_kind.startswith("deploymentconfig"): labels["deploymentconfig"] = name elif this_kind.startswith("deployment"): labels["deployment"] = name elif this_kind.startswith("buildconfig"): labels["openshift.io/build-config.name"] = name elif this_kind.startswith("statefulset"): labels["statefulset.kubernetes.io/pod-name"] = name elif this_kind.startswith("job"): labels["job-name"] = name else: raise OpenShiftPythonException( "Unknown how to find {} resources to related to kind: {}". format(find_kind, this_kind)) return selector(find_kind, labels=labels, static_context=self.context)
def __init__(self): self.onlyLayerHint = 0 self.mouseTool = 0 print "Init modules" self.data = ocad_data.ocad_data() self.gui = ocad_gui.ocad_gui(self.data) self.selector = selector.selector() self.miner = ocad_semantic.ocad_semantic(self.data) self.ontology = ocad_ontology(self.data) #self.gui.viewer.selector = self.selector print "Connect signals" sigs = { "open_file": self.open_file, "open_file_dialog": self.gui.open_dialog, "on_layer_box_cursor_changed": self.clickLayer, "on_viewport_box_changed": self.switchViewport, "on_cellrenderertext1_toggled": self.edit_layer_visible, "on_showall_clicked": self.gui.view.showAll, #reset view "on_save_clicked": self.saveProject, "on_open_clicked": self.gui.open_dialog, "on_exit_clicked": self.close, "on_individuals_clicked": self.showIndivs, "on_zones_clicked": self.showZones, "on_treeview1_cursor_changed": self.displayIndivParams, "on_class_box_changed": self.gui.updateClassDataProps, "on_button4_clicked": self.searchForTemplate, "on_button5_clicked": self.stopPatternMatching, "on_invert_clicked": self.invert_visible, "on_hide_all_clicked": self.hide_all, "on_button3_clicked": self.addOntEntity, "on_new_clicked": self.new, "on_file_new_activate": self.new, "on_file_quit_activate": self.close, "on_button7_clicked": self.cancelNew, "on_button6_clicked": self.newProject, "on_button10_clicked": self.deleteAllIndivs, "on_button11_clicked": self.deleteIndiv, "on_button8_clicked": self.gui.open_dialog, "on_button9_clicked": self.gui.open_dialog, "on_button12_clicked": self.gui.open_dialog, "on_button1_clicked": self.gui.close_dialog, "on_treeview3_row_activated": self.openProject, "on_toolbutton2_clicked": self.userHelp, "on_lasso_clicked": self.setLassoMode, "on_pin_clicked": self.setPinMode } self.data.builder.connect_signals(sigs) self.gui.connectViewerMouseHandler(self.viewPress)
def get_events(self): """ Returns a list of apiobjects events which indicate this object as their involvedObject. This can be an expensive if there are a large number of events to search. :return: A (potentially empty) list of event APIObjects """ # If this is a project, just return all events in the namespace. if kind_matches(self.kind(), ['project', 'namespace']): return selector('events').objects() involved = [] def check_if_involved(apiobj): if self.am_i_involved(apiobj): involved.append(apiobj) selector('events', static_context=self.context).for_each(check_if_involved) return involved
def test_elem_head(): assert len( selector('name').match(tree1) ) == 5 assert len( selector('branch').match(tree1) ) == 5 assert len( selector('name').match(tree2) ) == 9 assert len( selector('branch').match(tree2) ) == 9
def test_elem_regexp(): assert len( selector('/[a-c]$/').match(tree1) ) == 3 assert len( selector('/[b-z]$/').match(tree2) ) == len('bcbbbc')
import selector as slctr # Select general parameters for all optimizers (population size, number of iterations) PopulationSize = 30 Iterations = 5 x = slctr.selector(PopulationSize, Iterations)
def test_yield(): assert list( selector('=name /a/').match(tree1) )[0].head == 'name' assert len( selector('=branch /c/').match(tree1) ) == 3 assert set( selector('(=name /a/,name /b$/)').match(tree1) ) == set([STree('name', ['a']), 'b']) assert set( selector('=branch branch branch').match(tree1) ) == set([tree1.tail[0]]) assert set( selector('=(name,=branch branch branch) /c/').match(tree1) ) == set([STree('name', ['c']), tree1.tail[0]])
tic = time.time() data = pd.read_csv('C:\Users\Adam\Documents\FireLoss\cdips\\train.csv') toc = time.time() seconds_elapsed = toc - tic print "Reading .csv took", seconds_elapsed, "seconds" tic = time.time() samples_imp = preprocess.preprocess(data) toc = time.time() seconds_elapsed = toc - tic print "preprocessing took", seconds_elapsed, "seconds" score=[] RFscore=[] for i in range(repeat): use_train, use_validate = selector.selector(data, fires_in_train, nofires_in_train, validation_size) samples = samples_imp[use_train,:] labels = data.ix[use_train,'target'] labels = labels !=0 weights = np.asarray(data.ix[use_train,'var11']) forest = RandomForestClassifier(n_estimators = ntrees,n_jobs=-1) tic = time.time() forest = forest.fit(samples,labels,weights) toc = time.time() seconds_elapsed = toc - tic print "RF fit took", seconds_elapsed, "seconds"
home = os.environ["HOME"] cfg = {} cfg["cmd"] = cmd cfg["files"] = map(os.path.basename, args) cfg["env"] = {} cfg["env"]["ASAN_OPTIONS"] = "coverage=1:symbolize=1" cfg["env"]["MALLOC_CHECK_"] = "0" cfg["env"]["PATH"] = "%s/asan-builds/bin/:%s/asan-builds/sbin/" % (home,home) cfg["env"]["LD_LIBRARY_PATH"] = "%s/asan-builds/lib/" % home save_json("%s/cfg.json" % workdir, cfg) elif what == "select-testcases": cfg = load_json("%s/cfg.json" % workdir) seeddirs = map(os.path.abspath, args) s = selector(cfg, workdir) s.select_testcases(seeddirs) elif what == "fuzz": cfg = load_json("%s/cfg.json" % workdir) f = master(cfg, workdir, port) while True: seeds = glob.glob("seeds/*") shuffle(seeds) for seed in seeds: try: f.fuzz(seed) except: import traceback; traceback.print_exc() os.kill(os.getpid(), 9)
def test_modifiers(): assert len(selector("*:is-leaf").match(tree1)) == 5 assert len(selector("/[a-c]/:is-leaf").match(tree1)) == 3 assert len(selector("/[b]/:is-parent").match(tree1)) == 5 assert len(selector("/[b]/:is-parent").match(tree2)) == 9
def test_elem_any(): assert len(selector("*").match(tree1)) == 16 assert len(selector("*").match(tree2)) == 28
def test_elem_regexp(): assert len(selector("/[a-c]$/").match(tree1)) == 3 assert len(selector("/[b-z]$/").match(tree2)) == len("bcbbbc")
def test_elem_head(): assert len(selector("name").match(tree1)) == 5 assert len(selector("branch").match(tree1)) == 5 assert len(selector("name").match(tree2)) == 9 assert len(selector("branch").match(tree2)) == 9
pid = os.fork() except OSError, e: raise Exception, "%s [%d]" % (e.strerror, e.errno) if (pid != 0): open("/var/run/console-%s.pid" % self.vmName, "w").write(str(pid)) os._exit(0) else: return # We are now running inside a detached child process # find a free telnet port if not self.getTelnet(): return None sel = selector.selector() telneti = telnet(self.telnet, self.logFile, None, self.vmName) inOuti = inOut(None, telneti) sel.addHandler(telneti) sel.addHandler(inOuti) while True: # wait for the vm to be in the proper state state = self.session.xenapi.VM.get_power_state(self.vmRef) self.log("%s's power state is '%s'" % (self.vmName, state)) if state != 'Running': self.log( "Waiting for the vm to be running. Current state is '%s'..." % state)
############################################################################### #Author: Priyank Jain (@priyankjain) #Email: [email protected] ############################################################################### from selector import selector import os import string class preprocessor(object): def __init__(self): pass def process(self, data): self.data = data for dct in self.data: dct['text'] = dct['text'].lower() dct['text'] = dct['text'].translate(str.maketrans('','',string.punctuation)) dct['text'] = dct['text'].split() return self.data if __name__ == "__main__": Selector = selector(os.getcwd() + '/../data/yelp_data.csv') train_data, test_data = Selector.read(10) TestPreProcessor = preprocessor(data) train_data = TestPreProcessor.process(train_data) test_data = TestPreProcessor.process(test_data) print(train_data, test_data) print(len(train_data), len(test_data))
for l in range(0,Iterations): CnvgHeader.append("Iter"+str(l+1)) trainDataset="breastTrain.csv" testDataset="breastTest.csv" for j in range (0, len(datasets)): # specfiy the number of the datasets for i in range (0, len(optimizer)): if((optimizer[i]==True)): # start experiment if an optimizer and an objective function is selected for k in range (0,NumOfRuns): func_details=["costNN",-1,1] trainDataset=datasets[j]+"Train.csv" testDataset=datasets[j]+"Test.csv" x=slctr.selector(i,func_details,PopulationSize,Iterations,trainDataset,testDataset) if(Export==True): with open(ExportToFile, 'a',newline='\n') as out: writer = csv.writer(out,delimiter=',') if (Flag==False): # just one time to write the header of the CSV file header= numpy.concatenate([["Optimizer","Dataset","objfname","Experiment","startTime","EndTime","ExecutionTime","trainAcc", "trainTP","trainFN","trainFP","trainTN", "testAcc", "testTP","testFN","testFP","testTN"],CnvgHeader]) writer.writerow(header) a=numpy.concatenate([[x.optimizer,datasets[j],x.objfname,k+1,x.startTime,x.endTime,x.executionTime,x.trainAcc, x.trainTP,x.trainFN,x.trainFP,x.trainTN, x.testAcc, x.testTP,x.testFN,x.testFP,x.testTN],x.convergence]) writer.writerow(a) out.close() Flag=True # at least one experiment if (Flag==False): # Faild to run at least one experiment print("No Optomizer or Cost function is selected. Check lists of available optimizers and cost functions")
def test_lists(): assert set( selector('(/a/)').match(tree1) ) == set('a') assert set( selector('(/a/,/b$/)').match(tree1) ) == set('ab') assert set( selector('(/e/, (/a/,/b$/), /c/)').match(tree1) ) == set('abce')
#import json import time import psycopg2 import psycopg2.extras from connector import connect_DB as connect from builder import build_JSON as build from selector import report_selector as selector from constructor import report_construction from file_check import check_file from report_list import report_list_maker connection = connect() #connects to the DB selector = selector() #holds lists of reports to be generated for each MSA cur = connection.connect() #creates cursor object connected to HMDAPub2013 sql database, locally hosted postgres selector.get_report_lists('MSAinputs2013.csv') #fills the dictionary of lists of reports to be generated build_msa = build() #instantiate the build object for file path, jekyll files #build_msa.msas_in_state(cur, selector, 'aggregate') #creates a list of all MSAs in each state and places the file in the state's aggregate folder #List of Alabama MSAs for test state case #AL_MSAs = ['45180', '45980', '11500', '10760', '42460', '13820', '19460', '23460', '46740', '17980', '12220', '20020', '18980', '33860', '46260', '33660', '19300', '22840', '21460','10700','21640','42820','26620','22520','46220'] AL_MSAs = ['33660'] #report lists for testing #selector.reports_to_run = ['A 3-1', 'D 3-1'] #selector.reports_to_run = ['A 11-1'] #selector.reports_to_run = ['D 4-1', 'D 4-2', 'D 4-3', 'D 4-4', 'D 4-6', 'D 4-7'] #selector.reports_to_run = ['A 5-1', 'A 5-2', 'A 5-3', 'A 5-4', 'A 5-5', 'A 5-7'] #selector.reports_to_run = ['A 7-1', 'A 7-2', 'A 7-3', 'A 7-4', 'A 7-5', 'A 7-6', 'A 7-7'] #selector.reports_to_run = ['A 8-1', 'A 8-2', 'A 8-3', 'A 8-4', 'A 8-5', 'A 8-6', 'A 8-7'] #selector.reports_to_run = ['A 11-1', 'A 11-2', 'A 11-3', 'A 11-4', 'A 11-5', 'A 11-6', 'A 11-7', 'A 11-8', 'A 11-9', 'A 11-10']
def test_lists(): assert set(selector("(/a/)").match(tree1)) == set("a") assert set(selector("(/a/,/b$/)").match(tree1)) == set("ab") assert set(selector("(/e/, (/a/,/b$/), /c/)").match(tree1)) == set("abce")
k = k + 1 trainDataset, testDataset = data[train], data[test] for i in range(0, len(optimizer)): if ( (optimizer[i] == True) ): # start experiment if an optimizer and an objective function is selected for ai in range(0, len(actv_func)): if (actv_func[ai] == True): for b in range(0, len(loss_func)): func_details = ["costNN" + loss_func[b], -1, 1] #if(i > 7 and b < 2): # continue for p in population_sizes: x = slctr.selector(i, func_details, p, Iterations, trainDataset, testDataset, ai) elapsedRuns += 1 timeEnd = time.time() timeElapsed = timeEnd - timeStart timeRemaining = totalTime - timeElapsed print( str( numpy.round((elapsedRuns / totalRuns * 100), 2)) + "%/100%" + "\tTime Elapsed:" + str(cvtHours(timeElapsed)) + "\tTime Remaining:" + str(cvtHours(timeRemaining))) if (Export == True): with open(ExportToFile, 'a',
def test_yield(): assert list(selector("=name /a/").match(tree1))[0].head == "name" assert len(selector("=branch /c/").match(tree1)) == 3 assert set(selector("(=name /a/,name /b$/)").match(tree1)) == set([STree("name", ["a"]), "b"]) assert set(selector("=branch branch branch").match(tree1)) == set([tree1.tail[0]]) assert set(selector("=(name,=branch branch branch) /c/").match(tree1)) == set([STree("name", ["c"]), tree1.tail[0]])
#import json import time import psycopg2 import psycopg2.extras from connector import connect_DB as connect from builder import build_JSON as build from selector import report_selector as selector from constructor import report_construction from file_check import check_file from report_list import report_list_maker connection = connect() #connects to the DB selector = selector() #holds lists of reports to be generated for each MSA cur = connection.connect() #creates cursor object connected to HMDAPub2013 sql database, locally hosted postgres selector.get_report_lists('MSAinputs2013.csv') #fills the dictionary of lists of reports to be generated build_msa = build() #instantiate the build object for file path, jekyll files #build_msa.msas_in_state(cur, selector, 'aggregate') #creates a list of all MSAs in each state and places the file in the state's aggregate folder #List of Alabama MSAs for test state case #AL_MSAs = ['45180', '45980', '11500', '10760', '42460', '13820', '19460', '23460', '46740', '17980', '12220', '20020', '18980', '33860', '46260', '33660', '19300', '22840', '21460','10700','21640','42820','26620','22520','46220'] AL_MSAs = ['33340'] #report lists for testing #selector.reports_to_run = ['A B'] #selector.reports_to_run = ['A 11-2'] #selector.reports_to_run = ['D 4-1', 'D 4-2', 'D 4-3', 'D 4-4', 'D 4-6', 'D 4-7'] #selector.reports_to_run = ['A 7-1', 'A 7-2', 'A 7-3', 'A 7-4', 'A 7-5', 'A 7-6', 'A 7-7']
def select(self, s): from selector import selector # import loop, don't use internally return selector(s).match(self)
'> *«Скажите, что произойдет в будущем, и мы будем знать, что вы боги» \n(Ис 41:23)*' ) st.markdown( '**Cервис для автоматизированного прогноза временных рядов. Файлы с данными \nзагружаются в форматах' ' *.csv .txt .xls .xlsx *. Необходимые настройки указываются в боковом меню слева.**' ) st.sidebar.title('Конфигурация данных') uploaded_file = st.sidebar.file_uploader( "Загрузите файл в подходящем формате ", type="csv") if uploaded_file is not None: df = pd.read_csv(uploaded_file) filename = uploaded_file else: filename, df = selector() st.header('Предварительный просмотр данных') st.dataframe(df.head(10)) ds_column, y, data_frequency, test_set_size, exog_variables = sidebarmenu( 'feature_target', df=df) exog_variables_names = exog_variables exog_variables = df[exog_variables] if len(exog_variables) > 0 else None plot_menu_title = st.sidebar.markdown('### Графики') plot_menu_text = st.sidebar.text('Выберите, какие нужно отобразить') show_absolute_plot = sidebarmenu('Временной ряд') show_seasonal_decompose = sidebarmenu('Сезонная декомпозиция')
def self_selector(self): """ :return: Returns a selector that selects this exact receiver """ return selector(self.qname(), static_context=self.context)
from tkinter import * from event import event from event2 import event2 from selector import selector from graphics import graphics Queue = queue.Queue() master = Tk() def stop(): thread1.stop() thread2.stop() thread3.stop() master.destroy() p = graphics(master, Queue, stop) thread3 = selector(p.status_callback3) thread1 = event(p.status_callback, thread3) thread2 = event2(p.status_callback2, thread3) try: thread1.start() thread2.start() thread3.start() master.mainloop() except KeyboardInterrupt: stop()
for l in range(0, Iterations): CnvgHeader2.append("Iter" + str(l + 1)) for j in range(0, len(datasets)): # specfiy the number of the datasets for i in range(0, len(optimizer)): if ( (optimizer[i] == True) ): # start experiment if an optimizer and an objective function is selected for k in range(0, NumOfRuns): #func_details=["costNN",-1,1] func_details = fitnessFUNs.getFunctionDetails(0) completeData = datasets[j] + ".csv" x = slctr.selector(i, func_details, PopulationSize, Iterations, completeData) if (Export == True): with open(ExportToFile, 'a', newline='\n') as out: writer = csv.writer(out, delimiter=',') if ( Flag == False ): # just one time to write the header of the CSV file header = numpy.concatenate([[ "Optimizer", "Dataset", "objfname", "Experiment", "startTime", "EndTime", "ExecutionTime", "trainAcc", "testAcc" ], CnvgHeader1, CnvgHeader1]) writer.writerow(header) a = numpy.concatenate([[ x.optimizer, datasets[j], x.objfname, k + 1,