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,
