query stringlengths 9 3.4k | document stringlengths 9 87.4k | metadata dict | negatives listlengths 4 101 | negative_scores listlengths 4 101 | document_score stringlengths 3 10 | document_rank stringclasses 102
values |
|---|---|---|---|---|---|---|
Sentiment module forward function | def forward(self, vec, training = False):
if self.dropout:
out = self.logsoftmax(self.l1(F.dropout(vec, training = training)))
else:
out = self.logsoftmax(self.l1(vec))
return out | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def process_sentiment(self):\r\n\r\n\r\n print(\"Beginning sentiment analysis\")\r\n # textblob time\r\n #tweet_sentiment = [TextBlob(tweet['filtered_text']).sentiment for index, tweet in self.tweet_dataframe.iterrows()]\r\n #self.tweet_dataframe['polarity'] = [i.polarity for i in tweet... | [
"0.6426259",
"0.6316986",
"0.631381",
"0.6263776",
"0.6206533",
"0.61623794",
"0.61538345",
"0.61538345",
"0.6142153",
"0.6090091",
"0.6080952",
"0.6045462",
"0.6017502",
"0.6017271",
"0.6006004",
"0.5997427",
"0.59766227",
"0.5972965",
"0.5962752",
"0.59570754",
"0.59559005"... | 0.0 | -1 |
the first ID from 1999 should always exist | def test_get_cve_id(reg_user_headers):
res = requests.get(
f'{env.AWG_BASE_URL}{CVE_ID_URL}/{cve_id}',
headers=reg_user_headers
)
ok_response_contains(res, cve_id) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_first_id(self):\r\n ids = \\\r\n \"R27DLI_4812 R27DLI_600 R27DLI_727 U1PLI_403 U1PLI_8969\".split(\r\n )\r\n self.assertEqual(first_id(ids, {}), 'R27DLI_4812')",
"def test_get_first_id(self):\r\n lines = \"\"\">S74_1 E86FECS01CEVAV orig_bc=ACATGTCACGTG new_... | [
"0.7088285",
"0.64710146",
"0.6314301",
"0.60994",
"0.6067378",
"0.5958204",
"0.5878371",
"0.5851126",
"0.5837657",
"0.58209383",
"0.5790208",
"0.5774725",
"0.5746272",
"0.57414085",
"0.5736358",
"0.57287204",
"0.57021135",
"0.57021135",
"0.5698367",
"0.5693931",
"0.5688653",... | 0.0 | -1 |
unauthenticated users can't get full information about IDs | def test_get_cve_id_bad_org_header(reg_user_headers):
uid = str(uuid.uuid4())
tmp = copy.deepcopy(reg_user_headers)
tmp['CVE-API-ORG'] = uid
tmp['CVE-API-USER'] = uid
res = requests.get(
f'{env.AWG_BASE_URL}{CVE_ID_URL}/{cve_id}',
headers=tmp
)
assert res.status_code == 200
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_user_id_identities_get(self):\n pass",
"def test_user_id_get(self):\n pass",
"def getIDs():",
"def getUserIds(self):\n raise BorkedGetUserIds",
"def get_id(self): \n\t\treturn (self.user_id)",
"def get_id_users(self):\n return self.execute(TABELLE['id_users']['select'... | [
"0.7316585",
"0.67288077",
"0.659847",
"0.6421961",
"0.64209867",
"0.6371666",
"0.62216234",
"0.62147516",
"0.6213287",
"0.6206303",
"0.618542",
"0.61826223",
"0.6156035",
"0.61465263",
"0.6134009",
"0.6125052",
"0.61215866",
"0.6115197",
"0.6093895",
"0.6083895",
"0.6075531"... | 0.0 | -1 |
the id parameter must be a string | def test_get_cve_id_id(reg_user_headers):
res = requests.get(
f'{env.AWG_BASE_URL}{CVE_ID_URL}/{cve_id}',
headers=reg_user_headers
)
assert isinstance (cve_id, str) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def id(self, *args, **kwargs) -> Any:\n pass",
"def get(self, _id):",
"def __init__(self, id: str):\n self.id = id",
"def getId(*args):",
"def getId(*args):",
"def getId(*args):",
"def getId(*args):",
"def getId(*args):",
"def getId(*args):",
"def getId(*args):",
"def getId(*args)... | [
"0.76560944",
"0.7627602",
"0.75842464",
"0.7416983",
"0.7416983",
"0.7416983",
"0.7416983",
"0.7416983",
"0.7416983",
"0.7416983",
"0.7416983",
"0.7416983",
"0.7416983",
"0.7416983",
"0.7416983",
"0.73131484",
"0.7311683",
"0.7311683",
"0.7311683",
"0.7311683",
"0.72077703",... | 0.0 | -1 |
org users can update own information | def test_post_cve_id_update_parameters(reg_user_headers):
res = requests.post(
f'{env.AWG_BASE_URL}{CVE_ID_URL}',
headers=reg_user_headers,
params={
'amount': '10',
'batch_type': 'sequential',
'cve_year': f'{utils.CURRENT_YEAR}',
'short_name': ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def update_user():",
"def update_user():\n #TODO user update \n pass",
"def update(self, user: U) -> None:\n ...",
"def home_edituser():\n\tpass",
"def update_user(id):\n pass",
"def testUpdateAccessAllowed(self):\n for user in (self.contributor, self.delegate, self.owner, self.roo... | [
"0.76065016",
"0.7539096",
"0.7087189",
"0.66907394",
"0.66773206",
"0.66604584",
"0.6412654",
"0.6342757",
"0.6323371",
"0.6305936",
"0.62408584",
"0.62351125",
"0.6233493",
"0.62263346",
"0.62000376",
"0.6190823",
"0.61851096",
"0.61774594",
"0.61385065",
"0.61379594",
"0.6... | 0.0 | -1 |
batch type is the only optional parameter for reserving ids | def test_post_cve_id_no_params(reg_user_headers):
res = requests.post(
f'{env.AWG_BASE_URL}{CVE_ID_URL}',
headers=reg_user_headers
)
assert res.status_code == 400
response_contains(res, 'amount')
response_contains(res, 'cve_year')
response_contains(res, 'short_name') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def instantiate_batch(self, inputs):\n return inputs",
"def is_batch():\n\n pass",
"def instantiate_batch(self, inputs):\n _ = inputs\n raise NotImplementedError(\n 'LoomOp needs a definition for instantiate_batch.')",
"def batch(data, batch_type=\"static\", batch_size=16, max_frames_in_ba... | [
"0.620192",
"0.6078552",
"0.5926326",
"0.575632",
"0.57218003",
"0.5705383",
"0.57025623",
"0.56738985",
"0.5569064",
"0.55206966",
"0.5487136",
"0.54771787",
"0.54666287",
"0.5466322",
"0.5463773",
"0.5463626",
"0.5457613",
"0.54541177",
"0.54437494",
"0.5442572",
"0.5442572... | 0.0 | -1 |
cve services doesn't accept id reservation with blank parameters | def test_post_cve_id_empty_params(reg_user_headers):
res = requests.post(
f'{env.AWG_BASE_URL}{CVE_ID_URL}',
headers=reg_user_headers,
params={
'amount': '',
'batch_type': '',
'cve_year': '',
'short_name': ''
}
)
# NOTE: there i... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_get_cve_id_empty_parameters(reg_user_headers):\n res = requests.get(\n f'{env.AWG_BASE_URL}{CVE_ID_URL}',\n headers=reg_user_headers,\n params={\n 'page': ' ',\n 'state': ' ',\n 'cve_id_year': ' ',\n 'time_reserved.lt': ' ',\n ... | [
"0.61553484",
"0.58308715",
"0.573636",
"0.566231",
"0.5647734",
"0.56073105",
"0.55616593",
"0.5545219",
"0.54743046",
"0.54703945",
"0.54675317",
"0.5464173",
"0.5453533",
"0.5425584",
"0.53871393",
"0.53465134",
"0.53299",
"0.5293856",
"0.52780175",
"0.52433264",
"0.521291... | 0.583669 | 1 |
reg_user_headers cannot post for 'mitre' org | def test_post_cve_id_wrong_header(reg_user_headers):
res = requests.post(
f'{env.AWG_BASE_URL}{CVE_ID_URL}',
headers=reg_user_headers,
params={
'amount': '10',
'batch_type': 'sequential',
'cve_year': f'{utils.CURRENT_YEAR}',
'short_name': 'mitr... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add_headers():\n # the actual access token -\n g.x_tapis_token = request.headers.get('X-Tapis-Token')\n\n # the tenant associated with the subject of the request; used, for instance, when the subject is different\n # from the subject in the actual access_token (for example, when the access_token re... | [
"0.6172347",
"0.5913672",
"0.58570987",
"0.5665602",
"0.56624866",
"0.56378",
"0.5583079",
"0.55241895",
"0.5515951",
"0.54737747",
"0.5450771",
"0.5438605",
"0.5401117",
"0.54006624",
"0.5383342",
"0.53809106",
"0.53769517",
"0.5355783",
"0.5343951",
"0.53330714",
"0.5323301... | 0.51243687 | 33 |
cve services rejects empty year | def test_post_cve_id_empty_year(reg_user_headers):
res = requests.post(
f'{env.AWG_BASE_URL}{CVE_ID_URL}',
headers=reg_user_headers,
params={
'amount': '10',
'batch_type': 'sequential',
'cve_year': '',
'short_name': 'mitre'
}
)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_post_cve_id_bad_year(reg_user_headers):\n res = requests.post(\n f'{env.AWG_BASE_URL}{CVE_ID_URL}',\n headers=reg_user_headers,\n params={\n 'amount': '10',\n 'batch_type': 'sequential',\n 'cve_year': '20111',\n 'short_name': 'mitre'\n ... | [
"0.6313151",
"0.6143077",
"0.6127024",
"0.60904646",
"0.60735536",
"0.58609223",
"0.58071655",
"0.5775344",
"0.57210094",
"0.5700775",
"0.5646941",
"0.5644524",
"0.5628136",
"0.5607409",
"0.5587389",
"0.5573917",
"0.5566914",
"0.55656594",
"0.55643725",
"0.555612",
"0.5514439... | 0.6794595 | 0 |
bulk download user should not be a CNA so can't reserve ids | def test_get_cve_id_bulk_download_user(bulk_download_user_headers):
res = requests.post(
f'{env.AWG_BASE_URL}{CVE_ID_URL}',
headers=bulk_download_user_headers,
params={
'amount': '1',
'cve_year': f'{utils.CURRENT_YEAR}',
'short_name': bulk_download_user_he... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def NSK129_user_ids():\n return [\n707057500045751944,\n707057500045752170,\n707057500045752255,\n707057500045752231,\n707057500045752217,\n707057500045752194,\n707057500045752156,\n707057500045752132,\n707057500045752118,\n707057500045752088,\n707057500045752064,\n707057500045752057,\n707057500045752033,\n7070... | [
"0.58862513",
"0.5735354",
"0.5705536",
"0.56432605",
"0.5610844",
"0.5497258",
"0.5476385",
"0.5470781",
"0.54458916",
"0.5398383",
"0.53948796",
"0.53903925",
"0.53885984",
"0.53872275",
"0.5369535",
"0.5365663",
"0.53542453",
"0.5341866",
"0.53160834",
"0.5290616",
"0.5284... | 0.68713385 | 0 |
cve services rejects year that isn't a 4 digit number | def test_post_cve_id_bad_year(reg_user_headers):
res = requests.post(
f'{env.AWG_BASE_URL}{CVE_ID_URL}',
headers=reg_user_headers,
params={
'amount': '10',
'batch_type': 'sequential',
'cve_year': '20111',
'short_name': 'mitre'
}
)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_get_cve_id_year_format_with_digits(reg_user_headers):\n res = requests.get(\n f'{env.AWG_BASE_URL}{CVE_ID_URL}',\n headers=reg_user_headers,\n params={\n 'cve_id_year': '20111',\n }\n )\n assert res.status_code == 400\n response_contains_json(res, 'error'... | [
"0.7325939",
"0.71417135",
"0.6948594",
"0.6882464",
"0.68685347",
"0.6862119",
"0.6835641",
"0.6804949",
"0.6762876",
"0.67234796",
"0.6682335",
"0.66758084",
"0.6662942",
"0.6632925",
"0.66314346",
"0.6624864",
"0.6588926",
"0.65760773",
"0.65724236",
"0.6571841",
"0.656731... | 0.6614464 | 16 |
cve services rejects empty amount | def test_post_cve_id_empty_amount(reg_user_headers):
res = requests.post(
f'{env.AWG_BASE_URL}{CVE_ID_URL}',
headers=reg_user_headers,
params={
'amount': '',
'batch_type': 'sequential',
'cve_year': f'{utils.CURRENT_YEAR}',
'short_name': 'mitre'... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_post_cve_id_bad_amount(reg_user_headers):\n res = get_reserve_cve_ids('a', utils.CURRENT_YEAR, reg_user_headers['CVE-API-USER'])\n assert res.status_code == 400\n assert res.reason == 'Bad Request'\n response_contains_json(res, 'error', 'BAD_INPUT')\n assert_contains(res, 'amount')",
"def... | [
"0.653086",
"0.62721187",
"0.5955064",
"0.59161574",
"0.59132206",
"0.57916385",
"0.5741534",
"0.5699919",
"0.569672",
"0.5678238",
"0.5673891",
"0.5644661",
"0.5555724",
"0.55537736",
"0.5542234",
"0.55271494",
"0.54556924",
"0.5434752",
"0.5424136",
"0.5397019",
"0.5380233"... | 0.6919644 | 0 |
cve services rejects amount less than or equal to 0 | def test_post_cve_id_invalid_amount(reg_user_headers):
res = requests.post(
f'{env.AWG_BASE_URL}{CVE_ID_URL}',
headers=reg_user_headers,
params={
'amount': '-1',
'batch_type': 'sequential',
'cve_year': f'{utils.CURRENT_YEAR}',
'short_name': reg... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_post_cve_id_bad_amount(reg_user_headers):\n res = get_reserve_cve_ids('a', utils.CURRENT_YEAR, reg_user_headers['CVE-API-USER'])\n assert res.status_code == 400\n assert res.reason == 'Bad Request'\n response_contains_json(res, 'error', 'BAD_INPUT')\n assert_contains(res, 'amount')",
"def... | [
"0.6360491",
"0.611909",
"0.6005989",
"0.58923316",
"0.58782834",
"0.57782614",
"0.57418144",
"0.5704172",
"0.5667392",
"0.55872136",
"0.5577535",
"0.5539598",
"0.55343425",
"0.54992557",
"0.54754955",
"0.5465203",
"0.54476887",
"0.5438703",
"0.54337156",
"0.5433273",
"0.5429... | 0.5951793 | 3 |
cve services rejects not having a batch type | def test_post_cve_id_no_batch_type(reg_user_headers):
res = requests.post(
f'{env.AWG_BASE_URL}{CVE_ID_URL}',
headers=reg_user_headers,
params={
'amount': '10',
'batch_type': '',
'cve_year': f'{utils.CURRENT_YEAR}',
'short_name': reg_user_heade... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_post_cve_id_invalid_batch_type(reg_user_headers):\n res = requests.post(\n f'{env.AWG_BASE_URL}{CVE_ID_URL}',\n headers=reg_user_headers,\n params={\n 'amount': '10',\n 'batch_type': '---',\n 'cve_year': f'{utils.CURRENT_YEAR}',\n 'short_... | [
"0.59317034",
"0.54606634",
"0.5347346",
"0.5305016",
"0.5238327",
"0.5208267",
"0.51238453",
"0.51060337",
"0.50457895",
"0.50359416",
"0.49542272",
"0.49313167",
"0.4925144",
"0.49151918",
"0.48936203",
"0.48852006",
"0.48664358",
"0.48178315",
"0.48169056",
"0.48044324",
"... | 0.59035945 | 1 |
cve services rejects batch types that aren't 'sequential' or 'nonsequential' | def test_post_cve_id_invalid_batch_type(reg_user_headers):
res = requests.post(
f'{env.AWG_BASE_URL}{CVE_ID_URL}',
headers=reg_user_headers,
params={
'amount': '10',
'batch_type': '---',
'cve_year': f'{utils.CURRENT_YEAR}',
'short_name': reg_u... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_post_cve_id_no_batch_type(reg_user_headers):\n res = requests.post(\n f'{env.AWG_BASE_URL}{CVE_ID_URL}',\n headers=reg_user_headers,\n params={\n 'amount': '10',\n 'batch_type': '',\n 'cve_year': f'{utils.CURRENT_YEAR}',\n 'short_name': r... | [
"0.58494323",
"0.5699419",
"0.56590396",
"0.5447683",
"0.5235617",
"0.51089853",
"0.5033172",
"0.49491057",
"0.49415886",
"0.49031293",
"0.4901575",
"0.49012297",
"0.4887945",
"0.48630536",
"0.4860203",
"0.4859041",
"0.4856981",
"0.4837587",
"0.4836359",
"0.48355365",
"0.4825... | 0.625506 | 0 |
api rejects nonnumeric amount when requesting IDs | def test_post_cve_id_bad_amount(reg_user_headers):
res = get_reserve_cve_ids('a', utils.CURRENT_YEAR, reg_user_headers['CVE-API-USER'])
assert res.status_code == 400
assert res.reason == 'Bad Request'
response_contains_json(res, 'error', 'BAD_INPUT')
assert_contains(res, 'amount') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_details_nonnum_id(self):\n self.check_response(\n '/attributes/xyz',\n ('Please enter an integer value for Attribute ID',))",
"def test_post_cve_id_invalid_amount(reg_user_headers):\n res = requests.post(\n f'{env.AWG_BASE_URL}{CVE_ID_URL}',\n headers=reg_us... | [
"0.5972634",
"0.58182454",
"0.57866687",
"0.57143825",
"0.56861025",
"0.5576269",
"0.55707586",
"0.5519899",
"0.54803365",
"0.54670215",
"0.54645705",
"0.54422504",
"0.5417482",
"0.54086465",
"0.53886473",
"0.53857684",
"0.53546566",
"0.5326676",
"0.53108746",
"0.5281189",
"0... | 0.6417517 | 0 |
priority ids can be reserved on behalf of the general user org | def test_post_cve_id_reserve_priority(reg_user_headers):
res = requests.post(
f'{env.AWG_BASE_URL}{CVE_ID_URL}',
headers=reg_user_headers,
params={
'amount': '1',
'cve_year': f'{utils.CURRENT_YEAR}',
'short_name': reg_user_headers['CVE-API-ORG']
}
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_priority(self):\n self.assertEqual(UserIdHook.priority, priority.AUTH)",
"def getPriority(self):",
"def getPriorityList(self):",
"def set_normal_priority(self, cr, uid, ids, context=None):\n return self.set_priority(cr, uid, ids, '3')",
"def priority(self):\n pass # pragma: n... | [
"0.60231215",
"0.57526404",
"0.5749479",
"0.5691362",
"0.5494412",
"0.5494412",
"0.5437413",
"0.5436863",
"0.54265106",
"0.5387683",
"0.5371276",
"0.5330336",
"0.5297356",
"0.5265151",
"0.5230199",
"0.5230199",
"0.5230199",
"0.5230199",
"0.5209371",
"0.51991934",
"0.51988536"... | 0.54266983 | 8 |
sequential ids can be reserved on behalf of the mitre org | def test_post_cve_id_reservation(batch_type, amount, reg_user_headers):
res = get_reserve_cve_ids(amount, utils.CURRENT_YEAR, reg_user_headers['CVE-API-ORG'], batch_type)
ok_response_contains(res, f'CVE-{utils.CURRENT_YEAR}-')
assert json.loads(res.content.decode())['cve_ids']
assert len(json.loads(res.... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def next_identity(self) -> OrganisationId:\n ...",
"def next_identity(self) -> PublicationId:\n ...",
"def new_id(self):\n self.next += 1\n return self.next",
"def getID():",
"def getIDs():",
"def test_post_cve_id_reserve_nonsequential_over_limit(reg_user_headers):\n res = get_rese... | [
"0.66211927",
"0.63096344",
"0.6253805",
"0.6164127",
"0.61354417",
"0.6101703",
"0.6076065",
"0.60546607",
"0.6034217",
"0.59827703",
"0.5974946",
"0.59362704",
"0.5935875",
"0.5897026",
"0.58955956",
"0.5877061",
"0.58733565",
"0.58589154",
"0.5828302",
"0.5784769",
"0.5774... | 0.0 | -1 |
the services api enforces a max quota of 100,000 | def test_post_cve_id_reserve_sequential_over_quota(reg_user_headers):
res = get_reserve_cve_ids(100001, utils.CURRENT_YEAR, reg_user_headers['CVE-API-ORG'])
assert res.status_code == 403
response_contains_json(res, 'error', 'EXCEEDED_ID_QUOTA') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def api_quota():\n # Create the required data dictionary for Quota/Status\n api_data = {} # type: Dict[str, str]\n response = http_request(endpoint=API_QUOTA, data=api_data)\n\n if response.get('errorNo') != 0:\n return_error('API Returned, {}:{}'.format(response.get('errorNo'), response.get('... | [
"0.72457856",
"0.6541689",
"0.6496974",
"0.6474122",
"0.64361095",
"0.6393663",
"0.6295374",
"0.62406343",
"0.62023115",
"0.61947495",
"0.6192351",
"0.61151093",
"0.6046293",
"0.60001254",
"0.5982207",
"0.5900475",
"0.58583516",
"0.5853473",
"0.5826973",
"0.5823149",
"0.58192... | 0.0 | -1 |
the services api enforces a max nonsequential limit of 10 | def test_post_cve_id_reserve_nonsequential_over_limit(reg_user_headers):
res = get_reserve_cve_ids(11, utils.CURRENT_YEAR, reg_user_headers['CVE-API-ORG'], 'nonsequential')
assert res.status_code == 403
response_contains_json(res, 'error', 'OVER_NONSEQUENTIAL_MAX_AMOUNT') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_exceed_limit_request(self):\n actions.login(ADMIN_EMAIL)\n ids_list = list(range(SkillAggregateRestHandler.MAX_REQUEST_SIZE))\n get_url = '%s?%s' % (self.URL, urllib.urlencode({\n 'ids': ids_list}, True))\n\n response = transforms.loads(self.get(get_url).body)\n ... | [
"0.65852773",
"0.6520471",
"0.63269025",
"0.6082659",
"0.59556395",
"0.5954305",
"0.5910449",
"0.5846189",
"0.58163947",
"0.580862",
"0.5794993",
"0.5748793",
"0.5740031",
"0.57182795",
"0.57025313",
"0.5619837",
"0.56094044",
"0.5550615",
"0.5540406",
"0.5538336",
"0.5536613... | 0.5607715 | 17 |
we can get ids immediately after reserving them using the time they're reserved (noting that this may not work against a shared integration environment, we check that at least this many have been reserved) | def test_get_cve_id_by_time_reserved(reg_user_headers):
n_ids = 10
time.sleep(1)
t_before = get_now_timestamp()
time.sleep(1)
res_ids = get_reserve_cve_ids(n_ids, utils.CURRENT_YEAR, reg_user_headers['CVE-API-ORG'])
time.sleep(1)
t_after = get_now_timestamp()
res_get_ids = requests.get(... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def ReserveIds(self, request, global_params=None):\n config = self.GetMethodConfig('ReserveIds')\n return self._RunMethod(\n config, request, global_params=global_params)",
"def AllocateIds(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)",
"def getIDs():"... | [
"0.6781136",
"0.66229504",
"0.66153526",
"0.6419672",
"0.6226388",
"0.6134424",
"0.61175394",
"0.605653",
"0.6043901",
"0.60392207",
"0.60173976",
"0.59599423",
"0.59259146",
"0.5866394",
"0.58563846",
"0.580518",
"0.5782845",
"0.5740038",
"0.571097",
"0.56960756",
"0.5666711... | 0.63052136 | 4 |
we can get ids immediately after reserving them using the time they're reserved (noting that this may not work against a shared integration environment, we check that at least this many have been reserved) | def test_get_cve_id_by_time_modified(reg_user_headers):
n_ids = 10
time.sleep(1)
t_before = get_now_timestamp()
time.sleep(1)
res_ids = get_reserve_cve_ids(n_ids, utils.CURRENT_YEAR, reg_user_headers['CVE-API-ORG'])
time.sleep(1)
t_after = get_now_timestamp()
res_get_ids = requests.get(... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def ReserveIds(self, request, global_params=None):\n config = self.GetMethodConfig('ReserveIds')\n return self._RunMethod(\n config, request, global_params=global_params)",
"def AllocateIds(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)",
"def getIDs():"... | [
"0.6780814",
"0.66223234",
"0.66155624",
"0.64196247",
"0.63053685",
"0.62260455",
"0.613415",
"0.61171174",
"0.6056178",
"0.60432154",
"0.603923",
"0.6016525",
"0.5960478",
"0.5926661",
"0.5866722",
"0.58551824",
"0.58061886",
"0.5783054",
"0.5740248",
"0.5710705",
"0.569540... | 0.0 | -1 |
org user can retrieve ids | def test_get_cve_id_with_params(reg_user_headers):
res = requests.get(
f'{env.AWG_BASE_URL}{CVE_ID_URL}',
headers=reg_user_headers,
params={
'page': 1,
'state': 'PUBLISHED',
'cve_id_year': 2011
}
)
assert res.status_code == 200 | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_user_id_identities_get(self):\n pass",
"def user_ids(self):\r\n raise NotImplementedError",
"def getUserIds(self):\n raise BorkedGetUserIds",
"def getInterestedUsers():",
"def get_id_users(self):\n return self.execute(TABELLE['id_users']['select']['all'])",
"def getID... | [
"0.72742236",
"0.7113426",
"0.69859695",
"0.68559736",
"0.6748318",
"0.6734738",
"0.66231877",
"0.6608751",
"0.6369346",
"0.636064",
"0.63404447",
"0.62787783",
"0.62327987",
"0.61808455",
"0.6162478",
"0.6126701",
"0.6066175",
"0.6033917",
"0.60191303",
"0.6018655",
"0.60166... | 0.0 | -1 |
cannot get id with empty parameters | def test_get_cve_id_empty_parameters(reg_user_headers):
res = requests.get(
f'{env.AWG_BASE_URL}{CVE_ID_URL}',
headers=reg_user_headers,
params={
'page': ' ',
'state': ' ',
'cve_id_year': ' ',
'time_reserved.lt': ' ',
'time_reserved... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getId(*args):",
"def getId(*args):",
"def getId(*args):",
"def getId(*args):",
"def getId(*args):",
"def getId(*args):",
"def getId(*args):",
"def getId(*args):",
"def getId(*args):",
"def getId(*args):",
"def getId(*args):",
"def getId(*args):",
"def _get_id(key):\n id = reques... | [
"0.7320569",
"0.7320569",
"0.7320569",
"0.7320569",
"0.7320569",
"0.7320569",
"0.7320569",
"0.7320569",
"0.7320569",
"0.7320569",
"0.7320569",
"0.7320569",
"0.6974481",
"0.69206655",
"0.6858404",
"0.6776071",
"0.6651017",
"0.6584284",
"0.65360487",
"0.6476524",
"0.645016",
... | 0.0 | -1 |
page must be an integer' | def test_get_cve_id_page_format_number(reg_user_headers):
res = requests.get(
f'{env.AWG_BASE_URL}{CVE_ID_URL}',
headers=reg_user_headers,
params={
'page': 'test',
}
)
assert res.status_code == 400
response_contains_json(res, 'error', 'BAD_INPUT') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_page(self, num):\n return num + 10",
"def get_page_arg() -> int:\n page = request.args.get('page', '1')\n try:\n page = int(page)\n except ValueError:\n page = 1\n return page",
"def access_page(self, page_number):\n pass",
"def get_page(data):\n try:\n ... | [
"0.72942066",
"0.7255621",
"0.70951617",
"0.7084217",
"0.69198793",
"0.6883078",
"0.68631285",
"0.66765064",
"0.6582172",
"0.65000105",
"0.6479773",
"0.64404786",
"0.6272016",
"0.6267252",
"0.6241071",
"0.61810404",
"0.6149198",
"0.6130814",
"0.6092832",
"0.60616213",
"0.5963... | 0.5665793 | 49 |
page must be greater than or equal to 1' | def test_get_cve_id_page_limit(reg_user_headers):
res = requests.get(
f'{env.AWG_BASE_URL}{CVE_ID_URL}',
headers=reg_user_headers,
params={
'page': '-1',
}
)
assert res.status_code == 400
response_contains_json(res, 'error', 'BAD_INPUT') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def validate_page_number(self, page_number):\n try:\n page_number = int(page_number)\n except ValueError:\n raise PageNotAnInteger('That page number is not an integer')\n if page_number < 1:\n raise EmptyPage('That page number is less than 1')\n if page_... | [
"0.68724334",
"0.67795455",
"0.6575791",
"0.6404563",
"0.6392881",
"0.6365751",
"0.6325652",
"0.6285816",
"0.6275277",
"0.6239366",
"0.6166517",
"0.6119553",
"0.6100605",
"0.6086404",
"0.6025112",
"0.59399664",
"0.5886595",
"0.58713305",
"0.5866949",
"0.58475083",
"0.58428866... | 0.5324134 | 82 |
state parameter can only be 'REJECTED', 'PUBLISHED' or 'RESERVED' | def test_get_cve_id_state_in_choices(reg_user_headers):
res = requests.get(
f'{env.AWG_BASE_URL}{CVE_ID_URL}',
headers=reg_user_headers,
params={
'state': 'TEST',
}
)
assert res.status_code == 400
response_contains_json(res, 'error', 'BAD_INPUT') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def state(self, state):\n allowed_values = [\"New\", \"StartSent\", \"StartSentFailure\", \"StartSuccess\", \"StartFailure\", \"UpdateSentFailure\", \"UpdateSent\", \"DeleteSentFailure\", \"DeleteInProgress\", \"DeleteFailure\", \"DeleteSuccess\"]\n if state not in allowed_values:\n raise ... | [
"0.6176275",
"0.6131376",
"0.6055712",
"0.5957187",
"0.59544176",
"0.59054977",
"0.58795524",
"0.57650197",
"0.56667703",
"0.5662892",
"0.56489974",
"0.5598072",
"0.55912334",
"0.5574002",
"0.5551734",
"0.5543479",
"0.5529127",
"0.5524667",
"0.55142933",
"0.5511482",
"0.54829... | 0.0 | -1 |
cve_id_year format cannot have letters | def test_get_cve_id_year_format_with_letters(reg_user_headers):
res = requests.get(
f'{env.AWG_BASE_URL}{CVE_ID_URL}',
headers=reg_user_headers,
params={
'cve_id_year': 'test',
}
)
assert res.status_code == 400
response_contains_json(res, 'error', 'BAD_INPUT') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_get_cve_id_year_format_with_digits(reg_user_headers):\n res = requests.get(\n f'{env.AWG_BASE_URL}{CVE_ID_URL}',\n headers=reg_user_headers,\n params={\n 'cve_id_year': '20111',\n }\n )\n assert res.status_code == 400\n response_contains_json(res, 'error'... | [
"0.7290299",
"0.68064517",
"0.6639915",
"0.6629726",
"0.65061045",
"0.6400136",
"0.6279429",
"0.62579036",
"0.6201554",
"0.6189587",
"0.6148076",
"0.61450696",
"0.6132923",
"0.6132025",
"0.61171603",
"0.6104892",
"0.6042868",
"0.60263044",
"0.6016714",
"0.601461",
"0.60107243... | 0.72332454 | 1 |
cve_id_year format must be 4 digits only | def test_get_cve_id_year_format_with_digits(reg_user_headers):
res = requests.get(
f'{env.AWG_BASE_URL}{CVE_ID_URL}',
headers=reg_user_headers,
params={
'cve_id_year': '20111',
}
)
assert res.status_code == 400
response_contains_json(res, 'error', 'BAD_INPUT') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_get_cve_id_year_format_with_letters(reg_user_headers):\n res = requests.get(\n f'{env.AWG_BASE_URL}{CVE_ID_URL}',\n headers=reg_user_headers,\n params={\n 'cve_id_year': 'test',\n }\n )\n assert res.status_code == 400\n response_contains_json(res, 'error'... | [
"0.6879809",
"0.6652131",
"0.6589121",
"0.65639925",
"0.65207195",
"0.640766",
"0.64061123",
"0.63677484",
"0.6340106",
"0.6324387",
"0.631996",
"0.6299573",
"0.6240616",
"0.6234675",
"0.6224217",
"0.61875993",
"0.61271626",
"0.60666287",
"0.6056316",
"0.60426563",
"0.6026599... | 0.7553173 | 0 |
CVE ID filter endpoint does not return any IDs with state 'AVAILABLE' | def test_get_cve_id_available_state(reg_user_headers):
res = requests.get(
f'{env.AWG_BASE_URL}{CVE_ID_URL}',
headers=reg_user_headers,
params={
'page': 1,
'state': 'PUBLISHED',
'cve_id_year': 2011
}
)
assert res.status_code == 200
asse... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_get_cve_id_empty_parameters(reg_user_headers):\n res = requests.get(\n f'{env.AWG_BASE_URL}{CVE_ID_URL}',\n headers=reg_user_headers,\n params={\n 'page': ' ',\n 'state': ' ',\n 'cve_id_year': ' ',\n 'time_reserved.lt': ' ',\n ... | [
"0.60389936",
"0.5929574",
"0.58426833",
"0.5815951",
"0.570661",
"0.5682153",
"0.5544171",
"0.54931444",
"0.5453357",
"0.5426285",
"0.5375902",
"0.5353277",
"0.53115815",
"0.5262179",
"0.52360713",
"0.5179641",
"0.51218987",
"0.51197237",
"0.51189655",
"0.50833505",
"0.50806... | 0.6503651 | 0 |
Returns how many items are currently held in the stack | def __len__(self):
return self._size | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def size(self):\n return self.N # Number of items in the stack",
"def size(self): #returns the size or number of items in the stack\n if self.is_empty():\n return 0\n else:\n return self.num_items",
"def size(self):\n return len(self._stack_items... | [
"0.8463215",
"0.8247272",
"0.8208759",
"0.7955895",
"0.7887319",
"0.7887319",
"0.78505945",
"0.78081095",
"0.7623325",
"0.74243367",
"0.74243367",
"0.73424596",
"0.73139846",
"0.7303499",
"0.7220582",
"0.7211484",
"0.71613765",
"0.71384513",
"0.7075491",
"0.7070831",
"0.70675... | 0.0 | -1 |
Returns the capacity of the stack | def capacity(self):
return self._capacity | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def capacity(self):\n return self._cap",
"def capacity(self):\n return self._capacity",
"def size(self) -> int:\n return len(self.stack)",
"def size(self):\n return len(self.stack)",
"def size(self):\n return len(self.__stack)",
"def size(self):\n return len(... | [
"0.7462714",
"0.74571216",
"0.74546",
"0.7357611",
"0.7292455",
"0.7292455",
"0.7283221",
"0.72271335",
"0.7219159",
"0.72018915",
"0.7150927",
"0.70750976",
"0.69642293",
"0.69642293",
"0.69642293",
"0.69642293",
"0.6958376",
"0.6918588",
"0.6907446",
"0.6886556",
"0.6886556... | 0.74791604 | 0 |
Push a new value at the top of the stack | def push(self, value):
if len(self)>= self.capacity():
raise ValueError("Stack capacity has been reached")
self._head_pos +=1
self._data[self._head_pos] = value
self._size += 1 | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def push(value):\n _get_stack().append(value)\n return value",
"def stack_push(self, value):\n self.stack.append(value)",
"def push(self, val):\n self._stack.push(val)",
"def push(self, val):\n self._stack.push(val)",
"def push(stack,number):\n stack.append(number)",
"def pu... | [
"0.87266916",
"0.8457053",
"0.8216962",
"0.8216962",
"0.7929966",
"0.7875772",
"0.7875772",
"0.7808286",
"0.7808286",
"0.7808286",
"0.780612",
"0.77987015",
"0.7753277",
"0.77151126",
"0.7651747",
"0.762848",
"0.7595179",
"0.7592026",
"0.7587173",
"0.75634444",
"0.7550379",
... | 0.72400415 | 43 |
Pop the top of the stack | def pop(self):
if self.empty():
raise ValueError("Empty Stack")
data = self._data[self._head_pos]
self._data[self._head_pos] = None
self._head_pos -= 1
self._size -= 1
return data | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def pop():\n stack = _get_stack()\n return _pop(stack)",
"def pop(self):\n if not self.isEmpty():\n self.top -= 1\n return self.stack.pop()\n else:\n raise Exception(\"Stack Underflow\")",
"def pop(stack):\n item = top(stack)\n stack.top = stack.top.ne... | [
"0.8520551",
"0.83142734",
"0.82947034",
"0.8183635",
"0.81185114",
"0.80919856",
"0.8073228",
"0.8025369",
"0.8021493",
"0.80164456",
"0.8005645",
"0.8002933",
"0.79993117",
"0.79921395",
"0.7989008",
"0.7974085",
"0.79444706",
"0.79217684",
"0.7914295",
"0.7904163",
"0.7896... | 0.7206383 | 73 |
Select the weight function | def window_func(method='hamming'):
assert type(method) == str, 'method must be a string'
if method == 'hamming':
return _weight_hamming
elif method == 'hann':
return _weight_hann
elif method == 'blackman':
return _weight_blackman
elif method == 'triangular':
retur... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def weight(self):",
"def _create_weight_func(G, weight):\n\n def weight_func(u, v):\n edge = G[u][v]\n\n if G.is_multigraph():\n return min(att.get(weight, 1) for att in edge.values())\n\n return edge.get(weight, 1)\n\n return weight_func",
"def select(weights):\n r = r... | [
"0.7193525",
"0.663707",
"0.66011775",
"0.657812",
"0.657812",
"0.6494727",
"0.64417845",
"0.638619",
"0.638619",
"0.638619",
"0.638619",
"0.638619",
"0.638619",
"0.638619",
"0.638619",
"0.63677955",
"0.6302994",
"0.6295462",
"0.62838084",
"0.6233081",
"0.62268186",
"0.6223... | 0.6393914 | 7 |
Hamming weight w = 0.54 0.46cos(2pin/(N1)) where n is the element index of a total N elements. or w = 0.54 + 0.46cos(2pir/l), where r is the distance to the center of the window, and l is the total width of the filter window. | def _weight_hamming(r, l):
w = 0.54 + 0.46*np.cos(2*pi*r/l)
w[np.absolute(r)>l/2.]=0
return w | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def windowing(input):\n N, M = np.shape(input)\n\n window = signal.hamming(M, sym=0)\n\n window_axis = lambda sample: sample * window\n\n output = np.apply_along_axis(window_axis, 1, input)\n\n # myplot(output, 'Hamming Window')\n\n return output",
"def make_hamming(N):\n return map(lambda x... | [
"0.6837442",
"0.65596735",
"0.6552758",
"0.6512625",
"0.6077814",
"0.605841",
"0.5993005",
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"0.5748788",
"0.5671822",
"0.566978",
"0.56511",
"0.56271595",
"0.5613923",
"0.5583017",
"0.55617875",
"0.55501837",
"0.5534077",
"0.5513793",
"0.54881024",
"0.54877645",
... | 0.71120054 | 0 |
using values from wikipedia 'exact blackman' | def _weight_blackman(r,l):
w = 0.42 + 0.5*np.cos(2*pi*r/l) + 0.08*np.cos(4*pi*r/l) # fase lag-> sign change
w[np.absolute(r)>l/2.]=0
return w | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def substantiate():",
"def med_in_english(word):\r\n\treturn int(med(TextBlob(word).correct(), word))",
"def med_in_hindi(word):\r\n\treturn int(med(correction(word),word))",
"def abw(og, fg):\n\n oe = sg2plato(og)\n re = real_extract(og, fg)\n return (oe - re) / (2.0665 - 0.010665 * oe)",
"def te... | [
"0.5924522",
"0.58038145",
"0.5717298",
"0.5541843",
"0.55333203",
"0.55237454",
"0.5522544",
"0.5512436",
"0.55012935",
"0.5500108",
"0.54784954",
"0.54728377",
"0.54658407",
"0.54618037",
"0.53966427",
"0.5384012",
"0.53421545",
"0.52895534",
"0.5272849",
"0.52247196",
"0.5... | 0.0 | -1 |
Returns a 4 digit block nearest the right of the string title. OR Returns None. EG. Starwars (1977) year is 1997 2001 A space odyssey 1968 year is 1968 2010 NO year 1985. NO year 75 NO year | def find_year(title):
# find all patterns that match the year pattern
matches = year_pattern.findall(title)
# if any matches
if matches:
# record for convienence
year = matches[-1]
too_short = len(title) < 8
# If the year is the title then return None
if year == t... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_year(string): \n return int(string[11:15])",
"def findYear(str):\n return int(re.search(\"(?<=yr=)\\d*\", str)[0])",
"def get_year_from_movielist_title(title):\n match = re.match(r'.*\\s+\\((\\d+)\\)', title)\n year = int(match.groups()[0])\n return year",
"def search_ye... | [
"0.58915716",
"0.58567333",
"0.56649774",
"0.56625235",
"0.5659744",
"0.56596863",
"0.56417406",
"0.5590322",
"0.55717194",
"0.5556086",
"0.55372804",
"0.55324984",
"0.5495838",
"0.5452335",
"0.5448456",
"0.5435247",
"0.5400344",
"0.5391075",
"0.53525335",
"0.530363",
"0.5269... | 0.72216535 | 0 |
Returns a dictionary of decades > number of movies released. | def rank_decades(movies):
results = {}
for movie in movies:
year = find_year(movie)
# If we found a release year then count it
if year:
# A way to map year to decade
decade = "{0}0s".format(year[:3])
else:
decade = "None"
results[decad... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def mostMoviesPerDecades (movies):\n movieDecades = {}\n for (title,year) in movies:\n key = year[:3]\n movieDecades[key] = movieDecades.get(key, 0) + 1\n return sorted([ (count, decade+'0s') for (decade,count) in movieDecades.items() ], reverse=True)\n # OR:\n # decades = [ k[1][:3]+'... | [
"0.7007399",
"0.6177839",
"0.58240515",
"0.58192813",
"0.5802243",
"0.5785403",
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"0.5368315",
"0.53631794",
"0.5360716",
"0.529787",
"0.5292788",
... | 0.7228442 | 0 |
Pipeline(memory=None, steps=[('tfidfvectorizer', TfidfVectorizer(analyzer='word', binary=False, decode_error='strict', dtype=, encoding='utf8', input='content', lowercase=True, max_df=0.8, max_features=None, min_df=2, ngram_range=(1, 4), norm='l2', preprocessor=None, smooth...penalty='l2', random_state=None, solver='wa... | def do_gridsearch():
df = read_df()
X = df['review']
y = df['sentiment']
X_train, X_holdout, y_train, y_holdout = train_test_split(X, y, test_size=0.3, shuffle=True, stratify=y, random_state=222 )
tfidf = TfidfVectorizer(stop_words='english', max_df=0.8)
stem_pipeline = make_pipeline(TextNormal... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def build_own_pipeline() -> Pipeline:\n clf = svm.LinearSVC(C=2, loss='hinge')\n vect = TfidfVectorizer(ngram_range=(1, 2))\n\n pipeline = None\n ##### Write code here #######\n pipeline = Pipeline([\n ('vect', vect),\n ('tfidf', TfidfTransformer()),\n ('clf', clf)\n ])\n ... | [
"0.6975826",
"0.6789501",
"0.6725526",
"0.62977254",
"0.6239499",
"0.6235239",
"0.61340624",
"0.61331767",
"0.60290724",
"0.60272926",
"0.6016024",
"0.59683824",
"0.58748174",
"0.5874547",
"0.58424956",
"0.5838253",
"0.58332974",
"0.5811651",
"0.5795148",
"0.57756644",
"0.576... | 0.0 | -1 |
MultinomialNB = 0.878 LogisticRegression(C=100) = 0.9029 SVC(kernel='linear', C=1) = DNF LogisticRegression(C=100) w/ Stemming = 0.89 LogisticRegression(C=100) w/o TextNormalizer 0.90 | def do_crossval():
df = read_df()
# X = df['review'].apply(remove_html_lower)
X = df['review']
y = df['sentiment']
X_train, X_holdout, y_train, y_holdout = train_test_split(X, y, test_size=0.3, shuffle=True, stratify=y, random_state=222 )
tfidf = TfidfVectorizer(stop_words='english', min_df=2,... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self, reg_penalty='l2', reg_inv=1.0, k_fold=5, random_state=0):\n print(\"Initialize model Logistic Regression\")\n self.reg_penalty = reg_penalty\n self.reg_inv = reg_inv\n self.k_fold = k_fold\n self.random_state = random_state\n self.model = sklearn.linear_... | [
"0.62698585",
"0.61725384",
"0.61637604",
"0.6154692",
"0.6104252",
"0.6065043",
"0.6043689",
"0.6036467",
"0.6005035",
"0.59768355",
"0.5962559",
"0.5954204",
"0.5923508",
"0.5914702",
"0.5897691",
"0.5893453",
"0.58933365",
"0.5870308",
"0.586354",
"0.58188796",
"0.58144957... | 0.0 | -1 |
Tests if the input configuration can be used to successfully connect to the integration | def check_config(self, logger: AirbyteLogger, config_path: str, config: json) -> AirbyteConnectionStatus:
url = "https://api.kustomerapp.com/v1/customers"
headers = {"Authorization": f"Bearer {config['api_token']}"}
try:
session = requests.get(url, headers=headers)
sessi... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_check_connection(self):\n self.assertIsNotNone(app.check_connection())",
"def _check_config(self):",
"def check_config(config):\n pass",
"def test_verify_connection_to_a_device():",
"def check_configuration(self, configuration):\n super(Hipchap, self).check_configuration(confi... | [
"0.6990856",
"0.68949676",
"0.684888",
"0.6785907",
"0.677721",
"0.676802",
"0.661468",
"0.65629077",
"0.64611405",
"0.64611405",
"0.63934875",
"0.6344222",
"0.6334913",
"0.6320825",
"0.63101155",
"0.63068146",
"0.62989163",
"0.62725794",
"0.62673503",
"0.6253545",
"0.624385"... | 0.5818214 | 84 |
Return the string commands to invoke the tap with the discover flag and the right configuration options | def discover_cmd(self, logger: AirbyteLogger, config_path: str) -> str:
return f"{self.TAP_CMD} -c {config_path} --discover" | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def cmd_path():\n\n return {\n \"tariff:Tariff management\": {\n \"list:Show list of tariffs\": [],\n \"show:Show tariff info\": [\"tariff\"],\n \"add:Add tariff to system\": [\"tariff\", \"cpu\", \"disk\", \"ram\", \"io\"],\n \"disable:... | [
"0.58859074",
"0.58670986",
"0.5826348",
"0.58100325",
"0.5771427",
"0.5704115",
"0.5698732",
"0.56129",
"0.5583267",
"0.5536959",
"0.5536959",
"0.5536959",
"0.5536959",
"0.55263853",
"0.5525248",
"0.5517902",
"0.54636204",
"0.54554516",
"0.5440602",
"0.54287976",
"0.542587",... | 0.7558065 | 0 |
Return the string commands to invoke the tap with the right configuration options to read data from the source | def read_cmd(self, logger: AirbyteLogger, config_path: str, catalog_path: str, state_path: str = None) -> str:
config_option = f"--config {config_path}"
properties_option = f"--catalog {catalog_path}"
state_option = f"--state {state_path}" if state_path else ""
return f"{self.TAP_CMD} {c... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getCommands(self):",
"def discover_cmd(self, logger: AirbyteLogger, config_path: str) -> str:\n return f\"{self.TAP_CMD} -c {config_path} --discover\"",
"def read_cmd(self):\n\n parser = ArgumentParser(formatter_class=ArgumentDefaultsHelpFormatter)\n req_opts = parser.add_argument_grou... | [
"0.57491606",
"0.5746505",
"0.5679547",
"0.5584499",
"0.5541998",
"0.5482936",
"0.5449338",
"0.5402556",
"0.537918",
"0.53708476",
"0.5344244",
"0.5337871",
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"0.52798516",
"0.5266515",
"0.52500254",
"0.5231561",
"0.5224792",
"0.52229244",
"0.52014023... | 0.6807015 | 0 |
Helper to extract the necessary information from the source and destination arguments. | def _extract_service_info(self, source, destination):
self._validate_args(source, destination)
src_tags = []
dest_tags = []
src_ranges = []
dest_ranges = []
if isinstance(source, Service):
src_tags.append("%s-%s" % (source.network.name, source.name))
i... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def extract_info_from_arguments(self):\r\n\r\n for sample_name in self.arguments['--sample_name']:\r\n self.list_of_samples_to_be_combined.append(sample_name)\r\n\r\n for file_path in self.arguments['--input_file']:\r\n file_object = Input_file(file_path, self.list_of_samples_to... | [
"0.6327258",
"0.611357",
"0.6070593",
"0.6032475",
"0.5898038",
"0.5862193",
"0.57831115",
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"0.5718328",
"0.57162285",
"0.57139033",
"0.5698845",
"0.56835914",
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"0.561419",
"0.56104034",
"0.555884",
"0.5511409",
"0.54986507",
"0.54595613",
"0.5454608",... | 0.66374743 | 0 |
Add path between two services on a given port. | def add(self, source, destination, port):
logger.info('Adding path from %s to %s on port %s', source, destination, port)
rules = [{"IPProtocol": "tcp", "ports": [int(port)]}]
src_tags, dest_tags, src_ranges, _ = self._extract_service_info(
source, destination)
firewall_name =... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def paths_allow_service(ctx, network, destination, source, port):\n source_service = get_service_for_cli(ctx, network, source)\n destination_service = get_service_for_cli(ctx, network, destination)\n ctx.obj['CLIENT'].paths.add(source_service, destination_service, port)\n click.echo('Ad... | [
"0.72288865",
"0.62011",
"0.59549165",
"0.5698274",
"0.569521",
"0.56599027",
"0.5586385",
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"0.5568475",
"0.54433686",
"0.53352237",
"0.53007907",
"0.5271029",
"0.5248992",
"0.5241183",
"0.5220928",
"0.52087563",
"0.5194345",
"0.5165232",
"0.5164921",
"0.5087458"... | 0.685008 | 1 |
Remove path between two services on a given port. | def remove(self, source, destination, port):
logger.info('Removing path from %s to %s on port %s',
source, destination, port)
firewall_name = "bu-%s-%s-%s" % (destination.network.name, destination.name, port)
def remove_from_ranges(to_remove, address_ranges):
lo... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def paths_revoke_service(ctx, network, destination, source, port):\n source_service = get_service_for_cli(ctx, network, source)\n destination_service = get_service_for_cli(ctx, network, destination)\n ctx.obj['CLIENT'].paths.remove(source_service, destination_service, port)\n click.echo... | [
"0.73585504",
"0.63231486",
"0.6160031",
"0.6030933",
"0.59920424",
"0.5941496",
"0.57573885",
"0.5690381",
"0.56471235",
"0.5642937",
"0.5599214",
"0.55907756",
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"0.5519539",
"0.5490159",
"0.5467465",
"0.5436124",
"0.5414947",
"0.54074705",
"0.5395... | 0.65104246 | 1 |
List all paths in a dictionary structure. | def list(self):
firewalls = self.driver.ex_list_firewalls()
tag_to_service = {}
for service in self.service.list():
service_tag = "%s-%s" % (service.network.name, service.name)
if service_tag in tag_to_service:
raise BadEnvironmentStateException(
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def list_paths():\n paths = db.session.query(Path).all()\n data = []\n for path in paths:\n data.append({\"id\" : path.id,\n \"title\":path.title,\"rating\":path.rating,\n \"description\":path.description,\"date\":path.date,\n \"start_coordinate\":path.start_coordin... | [
"0.67503875",
"0.6593327",
"0.6496042",
"0.64637524",
"0.6462023",
"0.6399366",
"0.6267905",
"0.6239227",
"0.61681885",
"0.6145046",
"0.6088481",
"0.6067918",
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"0.59594834",
"0.5934607",
"0.5927588",
"0.59196013",
"0.58615535",
"0.5857183",
"0.5844941... | 0.0 | -1 |
Return true if the given network is internet accessible. | def internet_accessible(self, service, port):
paths = self.list()
for public_block in get_public_blocks():
source = CidrBlock(public_block)
self._validate_args(source, service)
if self._has_access(paths, source, service, port):
return True
retu... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def internet_on():\n try:\n urllib.request.urlopen('http://216.58.192.142', timeout=1)\n return True\n except urllib.error.URLError: \n return False",
"def has_internet() -> bool:\n if public_address():\n return True\n else:\n return False",
"def is_internet_on() ... | [
"0.80673635",
"0.78484184",
"0.7726492",
"0.77061474",
"0.7639725",
"0.7414",
"0.73989576",
"0.73573595",
"0.7167946",
"0.69066286",
"0.6890679",
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"0.67271066",
"0.66752124",
"0.6611635",
"0.6597703",
"0.6585244",
"0.65795463",
"0.6493639",
"0.64728... | 0.65210694 | 19 |
Return true if there's a path between the services. | def has_access(self, source, destination, port):
logger.info('Looking for path from %s to %s on port %s', source, destination, 80)
self._validate_args(source, destination)
paths = self.list()
logger.info('Found paths %s', paths)
return self._has_access(paths, source, destination,... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def exists_path(self, start, end):\n return end in self.paths(start)",
"def paths_service_has_access(ctx, network, destination, source, port):\n source_service = get_service_for_cli(ctx, network, source)\n destination_service = get_service_for_cli(ctx, network, destination)\n if ctx.o... | [
"0.6967411",
"0.65646327",
"0.652668",
"0.64812905",
"0.6433106",
"0.63819546",
"0.61939585",
"0.6148311",
"0.61272573",
"0.60953724",
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"0.5914023",
"0.5902984",
"0.58886826",
"0.588194",
"0.5872661",
"0.5815296",
"0.58065... | 0.5584994 | 43 |
updates the learning rate using inverse time decay | def learning_rate(epoch):
return alpha / (1 + decay_rate * epoch) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def update_learning_rate(self) -> None:\n self.epsilon = self.initial_epsilon / (1. + self.rate_decay * self.n_it)\n return",
"def update_learning_rate(self) -> None:\n self.epsilon = self.initial_epsilon / (1. + self.rate_decay * self.n_it)\n return",
"def update_learning_rate(self... | [
"0.7914394",
"0.7914394",
"0.7600384",
"0.7560176",
"0.7499523",
"0.74376434",
"0.7421272",
"0.74188656",
"0.73709327",
"0.7334627",
"0.73209643",
"0.7318579",
"0.7294742",
"0.7198275",
"0.7148807",
"0.71447504",
"0.7119928",
"0.70642436",
"0.69671065",
"0.68856674",
"0.68773... | 0.679231 | 28 |
Returns the ManagementForm instance for this FormSet. | def management_form(self):
if self.is_bound:
form = AttachmentManagementForm(self.data, auto_id=self.auto_id, prefix=self.prefix)
if not form.is_valid():
raise ValidationError('ManagementForm data is missing or has been tampered with')
else:
form = Att... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _management_form(self):\n if self.is_bound:\n form = ConcurrentManagementForm(self.data, auto_id=self.auto_id,\n prefix=self.prefix)\n if not form.is_valid():\n raise ValidationError('ManagementForm data is missing or has be... | [
"0.7361065",
"0.6664403",
"0.6664403",
"0.6357645",
"0.622903",
"0.619828",
"0.6129273",
"0.6124485",
"0.61211973",
"0.6112333",
"0.6099777",
"0.60755575",
"0.5937113",
"0.58789",
"0.5841554",
"0.575287",
"0.5716436",
"0.56436545",
"0.5578003",
"0.555524",
"0.55537564",
"0.... | 0.7139378 | 1 |
Saves and returns an existing model instance for the given form. | def save_existing(self, form, instance, commit=True):
t = None
if type(instance.content_object) == Temporary:
t = instance.content_object
setattr(instance, self.ct_field.get_attname(), ContentType.objects.get_for_model(self.instance).pk)
setattr(instance, self.ct_fk_field.ge... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def submit_form(self, form, **kwargs):\n if form.is_valid():\n # check for save arg\n if kwargs.get('save_arg'):\n obj = form.save(kwargs.get('save_arg'))\n else:\n obj = form.save()\n if kwargs.get('data'):\n for k, v... | [
"0.6576403",
"0.64161557",
"0.6384659",
"0.63773",
"0.63773",
"0.632624",
"0.6257641",
"0.625082",
"0.62410504",
"0.61304533",
"0.60362434",
"0.60285646",
"0.60066885",
"0.598247",
"0.59468055",
"0.59448826",
"0.58961785",
"0.5891683",
"0.5856457",
"0.5836138",
"0.5831977",
... | 0.0 | -1 |
Get all the roidbs(dict for each image) in this dataset. | def get_roidb(self):
# get all the images_ids in this dataset
img_ids = self._COCO.getImgIds()
# sort the ids, make each time the same order
img_ids.sort()
# load the 'image' of the COCO dataset
roidb = copy.deepcopy(self._COCO.loadImgs(img_ids))
for entry in roid... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getimgs():",
"def _get_images(self):\n raw_outputs = self.interface.get_data(self.target_charge,\n self.charge_deviation,\n n_samples=self.n_samples)\n\n # apply roi to images\n roi_images = []\n ... | [
"0.63079953",
"0.6234191",
"0.6219616",
"0.6211326",
"0.61850816",
"0.61710894",
"0.6158927",
"0.61159897",
"0.6075292",
"0.606353",
"0.6056601",
"0.5999819",
"0.597429",
"0.5974166",
"0.5902935",
"0.5876047",
"0.5860083",
"0.5860083",
"0.58325046",
"0.5830358",
"0.581679",
... | 0.6564253 | 0 |
Adds empty metadata fields to an roidb entry | def _prep_roidb_entry(self, entry):
im_path = os.path.join(self.root, 'images', self.img_dir_name, entry['file_name'])
assert os.path.exists(im_path), 'Image \'{}\' not found'.format(im_path)
entry['image'] = im_path
entry['flipped'] = False
# empty placeholders
entry['bb... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_add_none_field(self):\n user_id = get_rand_string()\n data = get_rand_string()\n id = get_rand_string()\n\n doc = {}\n doc[\"user_id\"] = user_id\n doc[\"data\"] = data\n doc[\"id\"] = id\n doc[\"num\"] = None\n\n self.conn.add(**doc)",
"def... | [
"0.6160103",
"0.6061121",
"0.59801316",
"0.58670473",
"0.5864214",
"0.5544845",
"0.554237",
"0.55322087",
"0.5514025",
"0.5416703",
"0.541656",
"0.5356941",
"0.53148735",
"0.5307623",
"0.5273423",
"0.52616686",
"0.5258249",
"0.5258102",
"0.52420217",
"0.52291954",
"0.5199936"... | 0.5816735 | 5 |
Read gt annotation metadata from cached file | def _read_roidb_from_cachefile(self, roidb, cache_file):
with open(cache_file, 'rb') as f:
cached_roidb = pickle.load(f)
assert len(roidb) == len(cached_roidb)
for entry, cached_entry in zip(roidb, cached_roidb):
values = [cached_entry[key] for key in self.valid_cached_... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _read_annotations(self) -> Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray, np.ndarray, np.ndarray]:\n print('Loading annotations...')\n \n if self.caching:\n # Get last modified timestamp of the cache path\n cache_path = pathlib.Path(self.cache_path)\n ... | [
"0.62027264",
"0.5997888",
"0.5976737",
"0.59695655",
"0.59675443",
"0.5937609",
"0.5937239",
"0.59047294",
"0.5897617",
"0.5891092",
"0.58580345",
"0.5820216",
"0.57935876",
"0.57935876",
"0.576893",
"0.5730197",
"0.5653852",
"0.565109",
"0.5638312",
"0.56168824",
"0.5604916... | 0.0 | -1 |
Add gt annotation metadata to an roidb entry | def _add_roidb_from_annotations(self, entry):
ann_ids = self._COCO.getAnnIds(imgIds=entry['id'], iscrowd=None)
objs = self._COCO.loadAnns(ann_ids)
width = entry['width']
height = entry['height']
# valid objs
# change the annotation boxes from 'xywh' to 'xyxy'
vali... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def annotate(self, annotation):\n self._data = self._data.annotate(**annotation)",
"def add_annotation_metadata(self, value):\n\n if self._properties is None:\n self._properties = LabelProperties()\n self._properties.parameters.insert_new_element(value)",
"def add_annotations(an... | [
"0.60331297",
"0.5977848",
"0.5928702",
"0.5885852",
"0.56935644",
"0.5640169",
"0.5632724",
"0.55520755",
"0.55051976",
"0.54648685",
"0.5353418",
"0.5333789",
"0.5326382",
"0.53186566",
"0.5228458",
"0.5219965",
"0.51834035",
"0.51765555",
"0.51679146",
"0.5166681",
"0.5164... | 0.5174346 | 18 |
Get a time at a proportion of a range of two formatted times. start and end should be strings specifying times formated in the given format (strftimestyle), giving an interval [start, end]. prop specifies how a proportion of the interval to be taken after start. The returned time will be in the specified format. | def strTimeProp(start, end, format, prop):
stime = time.mktime(time.strptime(start, format))
etime = time.mktime(time.strptime(end, format))
ptime = stime + prop * (etime - stime)
return time.strftime(format, time.localtime(ptime)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def string_time_proportion(start, end, format, prop):\n\n stime = time.mktime(time.strptime(start, format))\n etime = time.mktime(time.strptime(end, format))\n\n ptime = stime + prop * (etime - stime)\n\n return time.strftime(format, time.localtime(ptime))",
"def str_time_prop(start, end, format, pro... | [
"0.85178894",
"0.79471684",
"0.7846328",
"0.7843137",
"0.77967566",
"0.7789479",
"0.7489254",
"0.6821654",
"0.5855493",
"0.56891155",
"0.5462127",
"0.5439004",
"0.5263487",
"0.5042992",
"0.50261956",
"0.5021218",
"0.500701",
"0.49870068",
"0.49614337",
"0.49568093",
"0.487238... | 0.7883204 | 6 |
Assert linter output messages with expected messages. | def validate(self, lint_task_report, expected_messages, failed_count):
for stdout in lint_task_report:
if stdout.failed:
for message in expected_messages:
self.assert_same_list_elements(
[message], stdout.trimmed_messages)
s... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_common_case(self):\n loglevel_from_command_line = \"WARNING\"\n assert output(self.msg, \"INFO\", loglevel_from_command_line)",
"def test_conformance_tests_test_output(self):\n style = pycodestyle.StyleGuide(quiet=True)\n result = style.check_files(['tests/test_output.py'])\n... | [
"0.66211826",
"0.65319955",
"0.6322452",
"0.62098235",
"0.6205033",
"0.6191707",
"0.614406",
"0.61428285",
"0.6142819",
"0.6119627",
"0.60981184",
"0.60862803",
"0.608246",
"0.6077644",
"0.6076441",
"0.60103965",
"0.60043216",
"0.60003436",
"0.59985435",
"0.59970367",
"0.5990... | 0.58783114 | 35 |
A reference implementation of a fitting function | def fit(self, X, y):
n_samples = X.shape[0]
self.U = 0.1 * self.rng.randn(self.num_user, self.D) # user vectors
self.V = 0.1 * self.rng.randn(self.num_item, self.D) # item vectors
mask_u = np.zeros((self.num_user, self.D))
mask_v = np.zeros((self.num_item, self.D))
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def fit():\n pass",
"def _fit_function(self,x,a,b):\n return b + a*x",
"def fit(self, x):\n pass",
"def fit(self):\n raise NotImplementedError",
"def fit(self, x):\n raise NotImplementedError()",
"def fit(self, X):",
"def fit(self):\n raise NotImplementedError ... | [
"0.79639536",
"0.78046715",
"0.766744",
"0.7549818",
"0.75253206",
"0.74864894",
"0.7471354",
"0.73796034",
"0.7347994",
"0.7347994",
"0.7347994",
"0.7347994",
"0.7347994",
"0.7347994",
"0.7347994",
"0.7347994",
"0.7347994",
"0.7347994",
"0.724212",
"0.724212",
"0.724212",
... | 0.0 | -1 |
A reference implementation of a predicting function. | def predict(self, X):
n_samples = X.shape[0]
y_pred = self.mean_rating_*np.ones(n_samples)
for i in np.arange(n_samples):
if X[i,0] < self.num_user and X[i,1] < self.num_item:
y_pred[i] += np.dot(self.U[X[i,0],:],self.V[X[i,1],:])
y_pred[i] = ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def predict(self):\n raise NotImplementedError",
"def predict(self, src): # real signature unknown; restored from __doc__\n pass",
"def predict(self, **kwargs):\n raise NotImplementedError",
"def _predict(self, x):\n pass",
"def predictIpdFuncModel(self, refId):\n\n # Mat... | [
"0.7543543",
"0.7530832",
"0.7339275",
"0.7310924",
"0.7306891",
"0.72665805",
"0.72665805",
"0.7234079",
"0.7234079",
"0.7234079",
"0.7225656",
"0.71698153",
"0.71546125",
"0.71517646",
"0.7147604",
"0.7123053",
"0.71057063",
"0.7061365",
"0.7060866",
"0.7042472",
"0.7041859... | 0.0 | -1 |
Check all registered stateless apps and create ORM entries that are missing | def add_stateless_apps(request, **kwargs):
check_stateless_loaded()
return redirect('admin:django_plotly_dash_statelessapp_changelist') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_db_is_created(test_teardown):\n try:\n applications = Application.query.first()\n inhouse_postings = Inhouse.query.first()\n external_postings = External.query.first()\n except Exception:\n assert False\n assert True",
"def test_app() -> Generator[FastAPI, Any, None]... | [
"0.6631696",
"0.6563358",
"0.63753223",
"0.61903685",
"0.6188892",
"0.6129401",
"0.6111491",
"0.61106694",
"0.6104654",
"0.6092305",
"0.60732937",
"0.6062053",
"0.6016797",
"0.5972828",
"0.5951301",
"0.59272087",
"0.59242654",
"0.5873568",
"0.58552974",
"0.5852981",
"0.584797... | 0.55525464 | 61 |
Initiate all elements necessary to create a visualization | def __init__(self, area, algorithm, showDecrease=False):
self._running = True
self._display_surf = None
self.size = self.width, self.height = 1040, 770
self.area = area
self.algorithm = algorithm
self.lastPrice = 0
self.scores = []
self.allTimeHigh = 0
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def initialize_visualization(self) -> None:\n pass",
"def _plot_init(self):\n pass",
"def _plot_init(self):\n pass",
"def initialize(self) -> None:\n # Only do matplotlib import when necessary\n super().initialize()\n from matplotlib import pyplot as plt\n sel... | [
"0.7872412",
"0.7087144",
"0.7087144",
"0.69636714",
"0.6836767",
"0.6821109",
"0.675592",
"0.67427933",
"0.6721345",
"0.6704872",
"0.67046523",
"0.6684778",
"0.66836005",
"0.66741896",
"0.66685414",
"0.66287583",
"0.66133267",
"0.6607237",
"0.6592763",
"0.65526634",
"0.65430... | 0.0 | -1 |
Executes given algorithm and draws visualization | def on_render(self):
# set text font for in visualization
pygame.font.init()
font = pygame.font.SysFont('Arial', 24)
# continue running algorithm until done
if self.algorithm.isDone is False:
self.algorithm.execute()
# draw background
for i in range... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def main(self):\n if self.mode==0: #drawing\n self.draw()\n self.graph_drawing=self.cleanGraph(self.graph_drawing)\n #if len(self.graph_drawing)>1:\n # self.function_interpolation=self.polynomialInterpolation2D(self.graph_drawing,1)\n # self.graph... | [
"0.6958115",
"0.6749951",
"0.667682",
"0.6547552",
"0.6451062",
"0.6338296",
"0.6285082",
"0.6275436",
"0.62320006",
"0.6227646",
"0.6182338",
"0.6178661",
"0.6141961",
"0.6119228",
"0.60796785",
"0.6072379",
"0.6065661",
"0.6045414",
"0.6041594",
"0.6021481",
"0.6011331",
... | 0.0 | -1 |
Closes the pygame window | def on_cleanup(self):
pygame.quit() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def close(self):\n self._screen = None\n pygame.display.quit()",
"def end_pygame(self):\n pygame.quit()",
"def end_game():\n pygame.quit()\n exit()",
"def close_window() -> bool:\n global WINDOW\n global IMPL\n global ACTIVE_CALLBACK\n try:\n cast(PygletRenderer,... | [
"0.82715863",
"0.78452134",
"0.77165353",
"0.74987227",
"0.73441",
"0.72341275",
"0.719603",
"0.71945214",
"0.7189006",
"0.7164061",
"0.713809",
"0.70922494",
"0.70883983",
"0.7088168",
"0.70871246",
"0.70871246",
"0.7066076",
"0.70659834",
"0.70413816",
"0.70319366",
"0.7005... | 0.6695328 | 40 |
Starts and executes the visualisation | def on_execute(self):
# cannot run without visualization
if self.on_init() is False:
self._running = False
# while running listen for events and render these
while(self._running):
for event in pygame.event.get():
self.on_event(event)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def visualize(self):\n app = QtGui.QApplication([''])\n SceneGUI(self)\n app.exec_()",
"def main():\n configuration = ConfigParser()\n configuration.read_file(open('src/default.ini'))\n configuration.read(['config.ini'])\n push_exception_handler(reraise_exceptions=True)\n # Cr... | [
"0.7402717",
"0.7213778",
"0.71236545",
"0.71204275",
"0.70529693",
"0.70103776",
"0.6953393",
"0.68962806",
"0.6810111",
"0.6803159",
"0.67920536",
"0.6783941",
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"0.6744664",
"0.67096233",
"0.6675253",
"0.66208965",
"0.66193354",
"0.6582743",
"0.6575067",
"0.6571... | 0.0 | -1 |
Define command line flags for MNIST model. | def define_mnist_flags():
flags_core.define_base(
clean=True,
num_gpu=True,
train_epochs=True,
epochs_between_evals=True,
distribution_strategy=True)
flags_core.define_device()
flags_core.define_distribution()
# flags.DEFINE_string('data_dir', r'D:\tf2_official_... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def load_args():\n parser = argparse.ArgumentParser(description=\"Classify and predict digits using the mnist dataset\")\n parser.add_argument('mode', help='the mode to run in: fit, model or predict')\n parser.add_argument('--algo', help='which algorithm to use: RandomForest, KNN')\n return parser.pars... | [
"0.63784486",
"0.63677526",
"0.6337081",
"0.6322367",
"0.62878275",
"0.6251837",
"0.62503946",
"0.61637074",
"0.6119836",
"0.611938",
"0.6100962",
"0.6022951",
"0.6016902",
"0.59860235",
"0.5975369",
"0.5955694",
"0.5928708",
"0.5927573",
"0.5901932",
"0.58923614",
"0.5875625... | 0.7942187 | 0 |
Returns whether the scene contains an image pixmap. | def hasImage(self):
return self._image is not None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def hasImage(self):\n if self.getImage():\n return True\n return False",
"def has_image(self):\n return hasattr(self, \"_image\") and self._image is not None",
"def hasPng(self):\n\t\tif self.isPng:\n\t\t\treturn True\n\t\treturn textureFile( self.path.replace( self.extension, '... | [
"0.7148394",
"0.69063604",
"0.6811348",
"0.6708111",
"0.6708111",
"0.66627085",
"0.63021797",
"0.6208606",
"0.61569035",
"0.613535",
"0.6075283",
"0.6071318",
"0.59205896",
"0.59165484",
"0.5906985",
"0.58777034",
"0.5860418",
"0.581497",
"0.5773688",
"0.5759203",
"0.57401556... | 0.7086305 | 1 |
Removes the current image pixmap from the scene if it exists. | def clearImage(self):
if self.hasImage():
self.scene.removeItem(self._image)
self._image = None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def clearImage(self):\n if self.hasImage():\n self.scene.removeItem(self._pixmapHandle)\n self._pixmapHandle = None\n self.zoom=-1\n self.scene.clear()",
"def removeScene(self):\n del self.scene, self.imgPixmapItem",
"def clean_all(self):\n self.... | [
"0.79136795",
"0.7713988",
"0.67695427",
"0.6741188",
"0.6572793",
"0.65437007",
"0.64187896",
"0.63136613",
"0.61855835",
"0.61837137",
"0.61759114",
"0.61759114",
"0.61453015",
"0.61429083",
"0.6075483",
"0.6035884",
"0.6033798",
"0.5917658",
"0.59154296",
"0.5910521",
"0.5... | 0.7800114 | 1 |
Returns the scene's current image pixmap as a QPixmap, or else None if no image exists. | def pixmap(self):
if self.hasImage():
return self._image.pixmap()
return None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def pixmap(self):\n if self.hasImage():\n return self._pixmapHandle.pixmap()\n return None",
"def image(self):\n if self.hasImage():\n return self._pixmapHandle.pixmap().toImage()\n return None",
"def image(self):\n if self.hasImage():\n retur... | [
"0.7835423",
"0.75290245",
"0.74141395",
"0.67934173",
"0.6428947",
"0.61595285",
"0.6098856",
"0.58280176",
"0.5742987",
"0.5732158",
"0.5682366",
"0.56738436",
"0.5643078",
"0.56390196",
"0.5633685",
"0.5633685",
"0.5633685",
"0.56182927",
"0.5591214",
"0.5585604",
"0.55093... | 0.79953897 | 0 |
Returns the scene's current image pixmap as a QImage, or else None if no image exists. | def image(self):
if self.hasImage():
return self._image.pixmap().toImage()
return None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def pixmap(self):\n if self.hasImage():\n return self._image.pixmap()\n return None",
"def image(self):\n if self.hasImage():\n return self._pixmapHandle.pixmap().toImage()\n return None",
"def pixmap(self):\n if self.hasImage():\n return self... | [
"0.75357985",
"0.7390828",
"0.7325522",
"0.63724256",
"0.63046825",
"0.60485345",
"0.5909091",
"0.58557355",
"0.58035487",
"0.5761733",
"0.57425255",
"0.5711291",
"0.5696588",
"0.5677836",
"0.5676707",
"0.5676707",
"0.5676707",
"0.5646885",
"0.5624013",
"0.5589218",
"0.557353... | 0.7408162 | 1 |
Set the scene's current image pixmap to the input QImage or QPixmap. Raises a RuntimeError if the input image has type other than QImage or QPixmap. | def setImage(self, image):
if type(image) is QPixmap:
pixmap = image
elif type(image) is QImage:
pixmap = QPixmap.fromImage(image)
elif (np is not None) and (type(image) is np.ndarray):
if qimage2ndarray is not None:
qimage = qimage2ndarray.arr... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def setImage(self, image):\n if type(image) is QPixmap:\n pixmap = image\n elif type(image) is QImage:\n pixmap = QPixmap.fromImage(image)\n else:\n raise RuntimeError(\"ImageViewer.setImage: Argument must be a QImage or QPixmap.\")\n if self.hasImage():... | [
"0.7422291",
"0.6897182",
"0.6531623",
"0.63586396",
"0.62505937",
"0.6145541",
"0.6143544",
"0.61127263",
"0.6110928",
"0.6067547",
"0.5999988",
"0.59984446",
"0.59641266",
"0.5930717",
"0.59233356",
"0.58951384",
"0.58449477",
"0.580186",
"0.57875705",
"0.5784541",
"0.57468... | 0.76077926 | 0 |
Load an image from file. Without any arguments, loadImageFromFile() will pop up a file dialog to choose the image file. With a fileName argument, loadImageFromFile(fileName) will attempt to load the specified image file directly. | def open(self, filepath=None):
if filepath is None:
filepath, dummy = QFileDialog.getOpenFileName(self, "Open image file.")
if len(filepath) and os.path.isfile(filepath):
image = QImage(filepath)
self.setImage(image) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def load_image(path_to_image, image_name):\n print(\"Loading: \", path_to_image + image_name, \" ...\")\n return Image.open(path_to_image + image_name)",
"def load_image_file(filename, mode='RGB'):\n return imread(filename, mode=mode)",
"def load_image(file_path):\r\n return Image.open(file_path)",... | [
"0.69220436",
"0.68596613",
"0.67387414",
"0.66391367",
"0.6533708",
"0.6456546",
"0.643648",
"0.6392238",
"0.63555753",
"0.63424206",
"0.62883973",
"0.6251465",
"0.61765534",
"0.61312544",
"0.6113461",
"0.60655653",
"0.60602564",
"0.6048459",
"0.59921944",
"0.5976241",
"0.59... | 0.5638605 | 51 |
Show current zoom (if showing entire image, apply current aspect ratio mode). | def updateViewer(self):
if not self.hasImage():
return
if len(self.zoomStack):
self.fitInView(self.zoomStack[-1], self.aspectRatioMode) # Show zoomed rect.
else:
self.fitInView(self.sceneRect(), self.aspectRatioMode) # Show entire image. | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def updateViewer(self):\n if not self.hasImage():\n return\n if self.zoom<0:\n self.fitInView(self.sceneRect(), self.aspectRatioMode)\n self.zoom=self.size().width()/self.scene.width()\n else:\n self.setTransform(QTransform().scale(self.zoom, self.zo... | [
"0.7110633",
"0.6878876",
"0.67799777",
"0.66970503",
"0.6600747",
"0.6560286",
"0.648813",
"0.64450556",
"0.6328534",
"0.63201594",
"0.63057935",
"0.62695974",
"0.6250653",
"0.6239383",
"0.62117034",
"0.618607",
"0.6161364",
"0.61387765",
"0.611919",
"0.6115448",
"0.6115113"... | 0.7233747 | 0 |
Maintain current zoom on resize. | def resizeEvent(self, event):
self.updateViewer() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __zoomIn(self):\n if QApplication.focusWidget() == e5App().getObject(\"Shell\"):\n e5App().getObject(\"Shell\").zoomIn()\n else:\n aw = self.activeWindow()\n if aw:\n aw.zoomIn()\n self.sbZoom.setValue(aw.getZoom())",
"def __zoomRes... | [
"0.7117528",
"0.7017072",
"0.69751215",
"0.6882993",
"0.6858646",
"0.6840816",
"0.67645746",
"0.6685849",
"0.6667905",
"0.6667615",
"0.6667457",
"0.66327095",
"0.66290236",
"0.6545775",
"0.64846504",
"0.64807826",
"0.6464954",
"0.6435762",
"0.64198947",
"0.6410689",
"0.640780... | 0.6529663 | 14 |
Start mouse pan or zoom mode. | def mousePressEvent(self, event):
# Ignore dummy events. e.g., Faking pan with left button ScrollHandDrag.
dummyModifiers = Qt.KeyboardModifier(Qt.KeyboardModifier.ShiftModifier | Qt.KeyboardModifier.ControlModifier
| Qt.KeyboardModifier.AltModifier | Qt.Keyb... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_panning_mouse(self):\n # Panning: left button mouse\n self.set('LeftClickMove', 'Pan',\n param_getter=lambda p: (p[\"mouse_position_diff\"][0],\n p[\"mouse_position_diff\"][1]))",
"def enableZoomIn(self):\n self.zoomInID =... | [
"0.6292223",
"0.6211446",
"0.6109515",
"0.60822356",
"0.5996879",
"0.59794855",
"0.5846898",
"0.57985544",
"0.5691063",
"0.5691012",
"0.5656027",
"0.5603103",
"0.5591536",
"0.55351645",
"0.55156785",
"0.5500062",
"0.54949075",
"0.54825634",
"0.54653955",
"0.54614025",
"0.5441... | 0.52884054 | 28 |
Stop mouse pan or zoom mode (apply zoom if valid). | def mouseReleaseEvent(self, event):
# Ignore dummy events. e.g., Faking pan with left button ScrollHandDrag.
dummyModifiers = Qt.KeyboardModifier(Qt.KeyboardModifier.ShiftModifier | Qt.KeyboardModifier.ControlModifier
| Qt.KeyboardModifier.AltModifier | Qt.Ke... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def action_zoom_out(self):\n if self.cur_zoom > 0:\n self.cur_zoom -= 1\n self.zoom_widget.setValue(self.cur_zoom)\n self.apply_zoom()",
"def disableZoomOut(self):\n self.canvas.mpl_disconnect(self.zoomOutID)\n self.master.config(cursor = \"arrow\")",
"def ... | [
"0.68419695",
"0.6739481",
"0.65681237",
"0.6543827",
"0.6457997",
"0.6321618",
"0.6290279",
"0.6144844",
"0.6118293",
"0.6052398",
"0.6047929",
"0.59668887",
"0.5871435",
"0.5862427",
"0.5862376",
"0.5830977",
"0.57818764",
"0.5772399",
"0.5762828",
"0.5702071",
"0.5701795",... | 0.0 | -1 |
Factory function for creating a trainer for supervised models | def create_setops_trainer(
base_model,
classifier,
setops_model,
optimizer,
criterion1,
criterion2,
params_object,
metrics={},
device=None):
if device:
base_model.to(device)
classifier.to(device)
setops_mode... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self, trainer):\n self.trainer = trainer",
"def trainer_factory(\n algorithm: Algorithm, config_overrides: dict, env: Optional[str] = None\n) -> Trainer:\n ensure_moab_envs_register()\n trainer_cls = algorithm.get_trainer_cls()\n default_config = algorithm.get_default_config()\n ... | [
"0.71435684",
"0.7107374",
"0.69590217",
"0.6899696",
"0.68078077",
"0.67690617",
"0.6763507",
"0.66558087",
"0.66419077",
"0.6584648",
"0.65843713",
"0.6530679",
"0.6478796",
"0.64768434",
"0.6475404",
"0.64570993",
"0.6412537",
"0.6393217",
"0.63930285",
"0.6369134",
"0.636... | 0.5883267 | 60 |
Factory function for creating an evaluator for supervised models | def create_setops_evaluator(
base_model,
classifier,
setops_model,
metrics={},
device=None):
if device:
base_model.to(device)
classifier.to(device)
setops_model.to(device)
def _inference(engine, batch):
base_model.eval()
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def build_evaluator(cls, cfg, dataset_name, output_folder=None):\n if output_folder is None:\n output_folder = os.path.join(cfg.OUTPUT_DIR, \"inference\")\n evaluator_list = []\n evaluator_type = MetadataCatalog.get(dataset_name).evaluator_type\n if evaluator_type in [\"sem_s... | [
"0.70951146",
"0.70931005",
"0.6880831",
"0.67547524",
"0.6727796",
"0.6719201",
"0.6615242",
"0.65753007",
"0.6541401",
"0.6517219",
"0.63667166",
"0.62752193",
"0.6263758",
"0.6261502",
"0.62416553",
"0.6239041",
"0.6132677",
"0.61306274",
"0.6113522",
"0.610134",
"0.607877... | 0.5975046 | 26 |
Save checkpoints of the models. | def setup_checkpoint(self, base_model, classifier, setops_model, evaluator):
checkpoint_handler_acc = ModelCheckpoint(
self.results_path,
CKPT_PREFIX,
score_function=lambda eng: round(
(eng.state.metrics["fake class acc"] + eng.state.metrics["S class ac... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def save(self, checkpoint) -> None:\r\n self.model.save(checkpoint)",
"def checkpoint(self):\n save()",
"def save_checkpoint(self, model):\n # print(f\"save model {self.save_model_path}\")\n torch.save(model.state_dict(), self.save_model_path)",
"def save_checkpoint(self, model, o... | [
"0.7800809",
"0.7565651",
"0.7409244",
"0.7344545",
"0.73144007",
"0.72660166",
"0.7262461",
"0.7247549",
"0.72064286",
"0.7176319",
"0.7068394",
"0.7047076",
"0.70424587",
"0.7033007",
"0.70235634",
"0.702158",
"0.70195657",
"0.6974094",
"0.6958324",
"0.69301397",
"0.6920729... | 0.0 | -1 |
Create or resume the models. | def setup_model(self):
logging.info("Setup the models.")
logging.info("{} model".format(self.base_network_name))
if self.base_network_name.lower().startswith("resnet"):
base_model, classifier = getattr(setops_models, self.base_network_name)(
num_classes=80,
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_models( self ):",
"def create_model(self):\n self.create_model_file()\n self.create_model_unit_test()\n self.add_model_to_list()\n self.readme_reminder()",
"def create_model(self):\n pass",
"def create_model(self):\n pass",
"def _execute(self):\n ... | [
"0.70078397",
"0.63238263",
"0.61417264",
"0.61417264",
"0.61415637",
"0.59057415",
"0.5848274",
"0.5814495",
"0.57502663",
"0.5723252",
"0.5714471",
"0.56826335",
"0.56672585",
"0.5664253",
"0.5658536",
"0.56254953",
"0.56254256",
"0.56186324",
"0.558689",
"0.5583091",
"0.55... | 0.57413155 | 9 |
Load the training datasets. | def setup_datasets(self):
train_transform = transforms.Compose(
[
transforms.Resize(self.crop_size),
transforms.RandomRotation(degrees=self.random_angle, resample=Image.BILINEAR),
transforms.RandomResizedCrop(
size=self.crop... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def load_dataset(self):\n # Get all the files in the directory\n file_list = self.get_file_list()\n\n # Concatenate the data corresponding to a list of files\n data = self.concatenate_file_data(file_list)\n\n # Shuffle the data and create the training and the validation datasets\... | [
"0.8218399",
"0.8125178",
"0.80490196",
"0.7737084",
"0.7685521",
"0.76708466",
"0.761472",
"0.7569029",
"0.7523898",
"0.75187165",
"0.7513626",
"0.74819964",
"0.7391458",
"0.73578954",
"0.728657",
"0.71922135",
"0.71755755",
"0.71751636",
"0.71503323",
"0.7139459",
"0.713235... | 0.0 | -1 |
Fill in created_at timestamp with something correct enough. | def forwards(apps, schema_editor):
Event = apps.get_model("kompomaatti", "Event")
for event in Event.objects.filter(tag__isnull=True):
if event.name.startswith("Instanssi"):
event.tag = str(event.date.year)
event.save(update_fields=["tag"]) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def created_at(self, created_at: \"datetime\"):\n self._attrs[\"createdAt\"] = created_at",
"def created_at(self, created_at: \"datetime\"):\n self._attrs[\"createdAt\"] = created_at",
"def created_at(self, created_at: \"datetime\"):\n self._attrs[\"createdAt\"] = created_at",
"def creat... | [
"0.7633237",
"0.7633237",
"0.7633237",
"0.7492085",
"0.74196297",
"0.7287477",
"0.7287477",
"0.7287477",
"0.7287477",
"0.7287477",
"0.7287477",
"0.7287477",
"0.7287477",
"0.7287477",
"0.7287477",
"0.7287477",
"0.7287477",
"0.7287477",
"0.7287477",
"0.7287477",
"0.7287477",
... | 0.0 | -1 |
Verifies if a given expression is a DOI link. | def is_doi(
expr: str
) -> bool:
return "/" in expr | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_valid_doi(doi):\n\n try:\n req = requests.get('http://dx.doi.org/%s' % doi, timeout=2.5)\n except (Timeout, RequestException) as e:\n logger.error('Can not validate doi: ' + str(e))\n raise\n else:\n return req.status_code == 200",
"def test_external_link_no_optional()... | [
"0.5902243",
"0.5859285",
"0.58372796",
"0.5793471",
"0.5750182",
"0.57325715",
"0.5698225",
"0.56601554",
"0.5649386",
"0.5642453",
"0.5627013",
"0.5585181",
"0.5577459",
"0.55432963",
"0.55078125",
"0.55066365",
"0.54943603",
"0.5493496",
"0.5486709",
"0.5483652",
"0.546083... | 0.6097317 | 0 |
Verifies if a given expression is a PMCID. | def is_pmc(
expr: str
) -> bool:
return expr.startswith("PMC") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_pmcid(val):\n return pmcid_regexp.match(val)",
"def is_pmid(val):\n return pmid_regexp.match(val)",
"def isValid(t_id):\n\tstr_id=str(t_id).strip()\n\treturn str_id.isdigit()",
"def validate_crx_id(crx_id):\n try:\n assert isinstance(crx_id, str)\n assert crx_id.isalnum()\n ... | [
"0.7058424",
"0.5879918",
"0.52431554",
"0.5222485",
"0.5149193",
"0.51324445",
"0.51155275",
"0.509177",
"0.49949974",
"0.49601135",
"0.4931984",
"0.49043941",
"0.4885397",
"0.4833352",
"0.48165584",
"0.48036438",
"0.48029396",
"0.4801181",
"0.4782276",
"0.478221",
"0.478114... | 0.6777141 | 1 |
Verifies if a given expression is not found when trying to find a PMID from a DOI or when trying to find a PMCID from a PMID. | def not_found(
expr: str
) -> bool:
return expr.startswith("N") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_pmc(\n expr: str\n ) -> bool:\n return expr.startswith(\"PMC\")",
"def test_raises_useful_exception(self):\n exp = Expression(r'inalid (\\d]', {}, [], lambda x: x)\n with self.assertRaises(exp.InvalidPattern):\n assert not exp.pattern",
"def test_fetch_nonexist_... | [
"0.5836214",
"0.5558532",
"0.54999846",
"0.5269607",
"0.52547735",
"0.51899976",
"0.5160352",
"0.51542646",
"0.50802845",
"0.5080079",
"0.50719815",
"0.50708777",
"0.5060157",
"0.50567174",
"0.5032003",
"0.501759",
"0.5013457",
"0.50105387",
"0.5006492",
"0.5003135",
"0.49980... | 0.5569078 | 1 |
This function transforms a list of articles IDs into another type. | def find_ids(
ids_file: str,
id_type: str
) -> str:
if id_type == "PMID":
finder = get_pmid_for_otherid
elif id_type == "DOI":
finder = get_doi_for_otherid
elif id_type == "PMCID":
finder = get_pmcid_for_otherid
else:
ra... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def convert_ids(docs: List) -> List:\r\n try:\r\n for doc in docs:\r\n doc[\"_id\"] = str(doc[\"_id\"])\r\n except TypeError:\r\n pass\r\n return docs",
"def map_to_per_etype(self, ids): # -> None:\n ...",
"def map_to_per_ntype(self, ids): # -> None:\n ...",
"d... | [
"0.6685242",
"0.62097913",
"0.61651856",
"0.61146766",
"0.58948886",
"0.584178",
"0.5735238",
"0.5686752",
"0.5686752",
"0.56518906",
"0.5582395",
"0.5522685",
"0.5522685",
"0.5428211",
"0.5428211",
"0.5423706",
"0.53926516",
"0.53802526",
"0.5362936",
"0.5321825",
"0.5321825... | 0.0 | -1 |
this includes bots apparently | def player_activate(game_event):
print("Player Connect")
userid = game_event.get_int('userid')
print("userid: %s" % userid)
playerinfo = playerinfo_from_userid(userid)
print("playerinfo: %s" % playerinfo)
print("playerinfo userid: %s" % playerinfo.get_userid())
steam64 = convertSteamIDT... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_bot(self) -> bool:",
"def bots():\n return get_bots(\"botsunlimited.settings\")",
"def getBottoms(self):\n\t\treturn self.bottoms",
"async def otherdiscords(self, ctx: commands.Context, team: HockeyTeams) -> None:\n if team is None:\n return await ctx.send(_(\"You must provide a v... | [
"0.67719287",
"0.67631114",
"0.6262418",
"0.59412503",
"0.5838326",
"0.58037865",
"0.5743516",
"0.57257545",
"0.56945395",
"0.5681595",
"0.5681595",
"0.5680498",
"0.5637873",
"0.5630661",
"0.5527503",
"0.55264086",
"0.54999554",
"0.5485988",
"0.54819053",
"0.54798585",
"0.547... | 0.0 | -1 |
this includes bots apparently | def player_disconnect(game_event):
print("Player Disconnect")
userid = game_event.get_int('userid')
print("userid: %s" % userid)
playerinfo = playerinfo_from_userid(userid)
print("playerinfo: %s" % playerinfo)
steamid = playerinfo.get_networkid_string()
print("player steamid: %s" % steamid)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_bot(self) -> bool:",
"def bots():\n return get_bots(\"botsunlimited.settings\")",
"def getBottoms(self):\n\t\treturn self.bottoms",
"async def otherdiscords(self, ctx: commands.Context, team: HockeyTeams) -> None:\n if team is None:\n return await ctx.send(_(\"You must provide a v... | [
"0.67719287",
"0.67631114",
"0.6262418",
"0.59412503",
"0.5838326",
"0.58037865",
"0.5743516",
"0.57257545",
"0.56945395",
"0.5681595",
"0.5681595",
"0.5680498",
"0.5637873",
"0.5630661",
"0.5527503",
"0.55264086",
"0.54999554",
"0.5485988",
"0.54819053",
"0.54798585",
"0.547... | 0.0 | -1 |
this includes bots apparently | def player_death(game_event):
print("Player Death")
# Get the userid from the event
victim = game_event.get_int('userid')
attacker = game_event.get_int('attacker')
print("victim: %s" % victim)
print("attacker: %s" % attacker)
#victim_edict = edict_from_userid(victim)
#attacker_edict... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_bot(self) -> bool:",
"def bots():\n return get_bots(\"botsunlimited.settings\")",
"def getBottoms(self):\n\t\treturn self.bottoms",
"async def otherdiscords(self, ctx: commands.Context, team: HockeyTeams) -> None:\n if team is None:\n return await ctx.send(_(\"You must provide a v... | [
"0.67719287",
"0.67631114",
"0.6262418",
"0.59412503",
"0.5838326",
"0.58037865",
"0.5743516",
"0.57257545",
"0.56945395",
"0.5681595",
"0.5681595",
"0.5680498",
"0.5637873",
"0.5630661",
"0.5527503",
"0.55264086",
"0.54999554",
"0.5485988",
"0.54819053",
"0.54798585",
"0.547... | 0.0 | -1 |
tell all players the message | def tell_all_players(message):
print("tell_all_players - disabled")
#player_obj_list = leetcoin_client.getPlayerObjList()
#for player_obj in player_obj_list:
# #print("player_obj key: %s" player_obj.get_key())
# print(player_obj.get_userid())
#
# playerinfo = playerinfo_from_use... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def message_all(self, message):\n # We copy the _clients into a list to avoid dictionary changing\n # size during iteration.\n for character in self.players.values():\n character.message(message)",
"def send_msg_to_players(players, msg=\"\"):\n for player in players:\n p... | [
"0.70819765",
"0.69221133",
"0.67780375",
"0.644569",
"0.64424276",
"0.63831353",
"0.63645077",
"0.6316337",
"0.629872",
"0.6286281",
"0.62688696",
"0.6267403",
"0.62594795",
"0.62567353",
"0.6223139",
"0.6213465",
"0.6205974",
"0.6203498",
"0.61870635",
"0.61756897",
"0.6165... | 0.7917727 | 0 |
Fired when a nonplayer entity is dying. | def other_death(game_event):
# Make sure the entity was a chicken...
if game_event.get_string('othertype') != 'chicken':
return
print("CHICKEN DIED")
# Get the attacker's userid...
userid = game_event.get_int('attacker')
# Make sure the attacker was a player...
if not userid:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def die(self):\n events.trigger_event(\"on_entity_death\", self)",
"def die(self, dt):\r\n self.dead = True",
"def on_death(self, state):",
"def on_death(self):\n self.bark('I was killed.')\n self.where = self.category.spawn\n self.life = self.life_max\n for this in ... | [
"0.7837138",
"0.6934105",
"0.6703524",
"0.6597946",
"0.6566147",
"0.65286016",
"0.6384168",
"0.6287133",
"0.62799877",
"0.62252057",
"0.6216475",
"0.620601",
"0.6187029",
"0.61190146",
"0.6063468",
"0.6046929",
"0.60035783",
"0.5991906",
"0.59220314",
"0.5872454",
"0.58209693... | 0.57358956 | 25 |
Fired every time a player is typing something. | def player_say(game_event):
# Make sure the typed text was "/chicken"...
if game_event.get_string('text') != '/chicken':
return
# Create a chicken entity...
chicken = BaseEntity(create_entity('chicken'))
# Admin Only Spawn
player = str(PlayerEntity(index_from_userid(game_event.get_int('... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def on_typing(self, user: \"steam.User\", when: \"datetime.datetime\") -> None:",
"def on_text(self, char: str, game: type):",
"def ev_keyup(self, event: KeyUp) -> None:",
"def on_typing(self, author_id, metadata=None):\n pass",
"def ev_textinput(self, event: TextInput) -> None:",
"def on_ty... | [
"0.68697137",
"0.669045",
"0.64575166",
"0.6253871",
"0.61605495",
"0.6110913",
"0.604485",
"0.6038742",
"0.6024695",
"0.60245764",
"0.59954387",
"0.59585464",
"0.5911463",
"0.5904285",
"0.584641",
"0.57990056",
"0.57855916",
"0.5767433",
"0.57247984",
"0.5722716",
"0.5712976... | 0.0 | -1 |
Clears the LSystem, leaving it in an empty state. | def clear(self):
self.globalDefines = {}
self.axiom = self.setAxiomFromString("")
self.clearProductions()
self.niterations = 1
self.resultPString = None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def clear(self):\n self._ll_tree.clear()",
"def clear(self):\n self.state = [[None, None, None],\n [None, None, None],\n [None, None, None]]",
"def clear(self):\n self.call('clear')",
"def clear(self):\n self.initialize()\n self.device_disconnect()",
... | [
"0.70731115",
"0.68451196",
"0.6841078",
"0.67400897",
"0.6628969",
"0.66263187",
"0.66138744",
"0.6606035",
"0.6603668",
"0.65833545",
"0.6568264",
"0.6566893",
"0.6512311",
"0.65085864",
"0.65085864",
"0.65085864",
"0.6487675",
"0.6486742",
"0.64708894",
"0.6469002",
"0.646... | 0.6351805 | 44 |
Defines the number of iterations for this LSystem. | def setIterations(self,niterations):
self.niterations = niterations | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def number_of_iterations(self) -> int:\n pass",
"def setNumberOfIterations(self, value):\n return self._set(numberOfIterations=value)",
"def setNumberOfIterations(self, value):\n return self._set(numberOfIterations=value)",
"def number_of_iterations(self) -> int:\n return self._so... | [
"0.77225906",
"0.73913205",
"0.73913205",
"0.73364985",
"0.7133316",
"0.71064",
"0.705243",
"0.70468533",
"0.698997",
"0.6880098",
"0.68696505",
"0.68569124",
"0.674406",
"0.674406",
"0.674406",
"0.674406",
"0.65591484",
"0.6519867",
"0.6519867",
"0.6314424",
"0.631092",
"0... | 0.6959807 | 9 |
Defines a new global parameter. Global defines are part of a LSystem definition. | def addGlobalDefine(self,name,value):
self.globalDefines[name] = value
self.refreshGlobals()
return name,value | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def setGlobal(name, value):",
"def _register_global_params(self, params):\n\n for name,obj in self.params().items():\n global_params.add(**{name:obj})\n\n for name,val in params.items():\n global_params.params(name).default=val\n\n params.update(global_params.get_param_... | [
"0.7220049",
"0.6664844",
"0.63944066",
"0.6321146",
"0.6292508",
"0.6287569",
"0.6168385",
"0.6102255",
"0.6082242",
"0.607618",
"0.5988118",
"0.59781164",
"0.59773254",
"0.59147763",
"0.5875671",
"0.58619636",
"0.5822638",
"0.57786924",
"0.5713862",
"0.5713862",
"0.5651559"... | 0.67719114 | 1 |
Overrides an existing global parameter. | def overrideGlobalDefine(self,name,value):
if name in self.globalDefines:
self.globalDefines[name] = value
self.refreshGlobals()
else:
raise Exception("Trying to override inexistent define!") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def resetParam(key, value):\n \n if globalParams == {}:\n warning(\"WARNING: runtime parameters not yet initialized\")\n LoadParams(\"_defaults\")\n \n if key in globalParams.keys():\n globalParams[key] = value\n else:\n raise ValueError()",
"def change_general_para... | [
"0.70273",
"0.6755417",
"0.67453146",
"0.66492784",
"0.66449267",
"0.6542654",
"0.6311179",
"0.62206256",
"0.6200415",
"0.61735564",
"0.61186",
"0.6057449",
"0.5984768",
"0.5965548",
"0.59429675",
"0.5929845",
"0.5915069",
"0.5876854",
"0.58686477",
"0.5866304",
"0.5859666",
... | 0.65476304 | 5 |
Adds a new empty production. | def addNewProduction(self):
newProduction = ParametricProduction()
newProduction.setGlobals(self.globalDefines)
self.productions.append(newProduction)
return newProduction | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add_production(g, prod):\n prods = list(g.productions())\n prods.append(prod)\n\n return CFG(prods)",
"def __add__(self, other):\n return Production(self, other)",
"def add_empty ( self ):\n self.add_item( 0 )\n self.delete_item()",
"def eliminate_unit_productions(self) -> \... | [
"0.6510565",
"0.54904515",
"0.5418957",
"0.5269639",
"0.5244652",
"0.52325046",
"0.51680905",
"0.5140562",
"0.51313096",
"0.51223606",
"0.503379",
"0.49855718",
"0.49611712",
"0.49484378",
"0.4942469",
"0.4886154",
"0.48101586",
"0.47989944",
"0.4791486",
"0.47834474",
"0.476... | 0.6333782 | 1 |
Perform a set of iterations of the LSystem | def iterate(self,N = None):
result = self.iterate_loop(N)
#self.writeToFile()
#TODO: We need a timeout for really long executions, but it won't work because it opens another blender instance! Fix this!
"""
queue = multiprocessing.Queue(1) # Maximum size is 1
proc = multi... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def run(self):\n import time\n\n\n for msr in self.msrs:\n # find state transition matrix\n phi_p, state_prop = self._compute_stm(msr.time)\n\n # use stm to propagate perturbation and covariance\n pert_m = np.matmul(phi_p, self.pert_vec[-1])\n co... | [
"0.66005445",
"0.6599382",
"0.6535561",
"0.6529551",
"0.62713087",
"0.62709314",
"0.62124425",
"0.6200158",
"0.61928564",
"0.6149193",
"0.6080613",
"0.60784876",
"0.6033699",
"0.5954994",
"0.5933657",
"0.5933471",
"0.59150016",
"0.58930504",
"0.5889543",
"0.5878386",
"0.58312... | 0.0 | -1 |
Defines compactly a complete lsystem | def toGenomeRepresentation(self):
s = ""
s += str(self.axiom)
s += "||"+str(self.niterations) # The iterations must be shown as well
for prod in self.productions:
s += "||"
s += prod.toGenomeRepresentation()
return s | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def createLsystemFromFile( filename ):\n\tfp = open(filename, \"r\")\n\tlines = fp.readlines()\n\tfp.close()\n\tlsys = init()\n\tfor line in lines:\n\t\twords = line.split()\n\t\tif words[0] == 'base':\n\t\t\tsetBase(lsys, words[1])\n\t\telif words[0] == 'rule':\n\t\t\taddRule(lsys, words[1:])\n\treturn lsys",
"... | [
"0.60046726",
"0.57798505",
"0.5777421",
"0.57441545",
"0.5731508",
"0.55573076",
"0.5503251",
"0.5494484",
"0.5390676",
"0.538684",
"0.5380898",
"0.53788805",
"0.53682077",
"0.53663224",
"0.5363068",
"0.5362513",
"0.5357351",
"0.535137",
"0.5327021",
"0.5323201",
"0.5297664"... | 0.0 | -1 |
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