body_hash stringlengths 64 64 | body stringlengths 23 109k | docstring stringlengths 1 57k | path stringlengths 4 198 | name stringlengths 1 115 | repository_name stringlengths 7 111 | repository_stars float64 0 191k | lang stringclasses 1 value | body_without_docstring stringlengths 14 108k | unified stringlengths 45 133k |
|---|---|---|---|---|---|---|---|---|---|
85cca5172a15971100e8036a8282fadd517ab02cda926c1b8dac01fcec671fcb | def load_best_model(self):
'Load best model.'
torch.cuda.empty_cache()
self._model.load_state_dict(torch.load((self._path / 'best.model'))) | Load best model. | sastvd/helpers/ml.py | load_best_model | davidhin/linevd | 13 | python | def load_best_model(self):
torch.cuda.empty_cache()
self._model.load_state_dict(torch.load((self._path / 'best.model'))) | def load_best_model(self):
torch.cuda.empty_cache()
self._model.load_state_dict(torch.load((self._path / 'best.model')))<|docstring|>Load best model.<|endoftext|> |
ec534cff548060a95fd26388847635ad1523b8fab9331ee4a3ccdac7b0ecb55e | def save_logger(self):
'Save class attributes.'
with open((self._path / 'log.pkl'), 'wb') as f:
f.write(pkl.dumps(dict([(i, getattr(self, i)) for i in self.save_attrs])))
with open((self._path / 'current.model'), 'wb') as f:
torch.save(self._model.state_dict(), f) | Save class attributes. | sastvd/helpers/ml.py | save_logger | davidhin/linevd | 13 | python | def save_logger(self):
with open((self._path / 'log.pkl'), 'wb') as f:
f.write(pkl.dumps(dict([(i, getattr(self, i)) for i in self.save_attrs])))
with open((self._path / 'current.model'), 'wb') as f:
torch.save(self._model.state_dict(), f) | def save_logger(self):
with open((self._path / 'log.pkl'), 'wb') as f:
f.write(pkl.dumps(dict([(i, getattr(self, i)) for i in self.save_attrs])))
with open((self._path / 'current.model'), 'wb') as f:
torch.save(self._model.state_dict(), f)<|docstring|>Save class attributes.<|endoftext|> |
ce7e9ecbf41d4f27b82780b8427c708492169cc6846f2614876e2bfb90e76d05 | def load_logger(self):
'Load class attributes.'
with open((self._path / 'log.pkl'), 'rb') as f:
attrs = pkl.load(f)
for (k, v) in attrs.items():
setattr(self, k, v)
torch.cuda.empty_cache()
self._model.load_state_dict(torch.load((self._path / 'current.model'))) | Load class attributes. | sastvd/helpers/ml.py | load_logger | davidhin/linevd | 13 | python | def load_logger(self):
with open((self._path / 'log.pkl'), 'rb') as f:
attrs = pkl.load(f)
for (k, v) in attrs.items():
setattr(self, k, v)
torch.cuda.empty_cache()
self._model.load_state_dict(torch.load((self._path / 'current.model'))) | def load_logger(self):
with open((self._path / 'log.pkl'), 'rb') as f:
attrs = pkl.load(f)
for (k, v) in attrs.items():
setattr(self, k, v)
torch.cuda.empty_cache()
self._model.load_state_dict(torch.load((self._path / 'current.model')))<|docstring|>Load class attributes.<|endoftext|> |
1e7a976fb0d19a3d107fcad9013e74e75f58e74776115ce03c0b0d08d20a2693 | async def _start(self) -> None:
"Start the worker.\n\n Handles initializing a connection & creating a channel,\n then uses aio-pika's RPC.create to create a new worker,\n & finally registers every route created by the user.\n "
self.logger.info(f'Starting {self.worker_name}...')
(host, port, self._connection, self._channel) = (await connect(self._connection_params))
build_route = (await self._pre_start())
(await asyncio.gather(*[build_route(route) for route in self._routes]))
self.logger.info(f'Worker waiting for tasks from {host}:{port}') | Start the worker.
Handles initializing a connection & creating a channel,
then uses aio-pika's RPC.create to create a new worker,
& finally registers every route created by the user. | amqp_worker/worker_base.py | _start | cheese-drawer/lib-python-amqp-worker | 0 | python | async def _start(self) -> None:
"Start the worker.\n\n Handles initializing a connection & creating a channel,\n then uses aio-pika's RPC.create to create a new worker,\n & finally registers every route created by the user.\n "
self.logger.info(f'Starting {self.worker_name}...')
(host, port, self._connection, self._channel) = (await connect(self._connection_params))
build_route = (await self._pre_start())
(await asyncio.gather(*[build_route(route) for route in self._routes]))
self.logger.info(f'Worker waiting for tasks from {host}:{port}') | async def _start(self) -> None:
"Start the worker.\n\n Handles initializing a connection & creating a channel,\n then uses aio-pika's RPC.create to create a new worker,\n & finally registers every route created by the user.\n "
self.logger.info(f'Starting {self.worker_name}...')
(host, port, self._connection, self._channel) = (await connect(self._connection_params))
build_route = (await self._pre_start())
(await asyncio.gather(*[build_route(route) for route in self._routes]))
self.logger.info(f'Worker waiting for tasks from {host}:{port}')<|docstring|>Start the worker.
Handles initializing a connection & creating a channel,
then uses aio-pika's RPC.create to create a new worker,
& finally registers every route created by the user.<|endoftext|> |
ef49861f1bf024c931e306e1bda079a25884707792c26dd78ce35e9b896891dc | async def _stop(self) -> None:
"Defers to aio-pika.Connection's close method."
self.logger.info('Worker stopping...')
(await self._connection.close()) | Defers to aio-pika.Connection's close method. | amqp_worker/worker_base.py | _stop | cheese-drawer/lib-python-amqp-worker | 0 | python | async def _stop(self) -> None:
self.logger.info('Worker stopping...')
(await self._connection.close()) | async def _stop(self) -> None:
self.logger.info('Worker stopping...')
(await self._connection.close())<|docstring|>Defers to aio-pika.Connection's close method.<|endoftext|> |
5971fc6ee85b088cbee74322d0d805ca1387703aa0504eff7e6d76218847fc60 | def route(self, path: str) -> Callable[([RouteHandler], None)]:
"Add new 'route' (consumer queue) to the worker with this Decorator.\n\n Similar to creating a route in Flask, this method listens on a given\n 'path' (queue name) & executes the given handler (callback) when a\n message is received in that queue.\n\n Returns the data returned by the decorated function, wrapped in a\n Response object. Not all Worker types will use this response, but\n any Worker that doesn't will simply ignore the return value.\n "
self.logger.debug(f'Begin processing route decorator with given path: {path}')
def wrap_handler(path: str, handler: RouteHandler) -> RouteHandler:
async def wrapped(data: Any) -> Response:
self.logger.info(f'TASK RECEIVED {path}')
response: Response
try:
result = (await handler(data))
response = OkResponse(result)
except Exception as err:
response = ErrResponse(err)
self.logger.info(f'TASK COMPLETED {path}: {repr(response)}')
return response
return wrapped
def decorate_route(handler: RouteHandler) -> None:
if inspect.iscoroutinefunction(handler):
new_route = Route(path=path, handler=wrap_handler(path, handler))
self.logger.debug(f'Created new route: {new_route}')
self._routes.append(new_route)
self.logger.debug(f'Pushed new route to _routes: {self._routes}')
else:
raise TypeError(f'Handler {handler} must be a coroutine function')
return decorate_route | Add new 'route' (consumer queue) to the worker with this Decorator.
Similar to creating a route in Flask, this method listens on a given
'path' (queue name) & executes the given handler (callback) when a
message is received in that queue.
Returns the data returned by the decorated function, wrapped in a
Response object. Not all Worker types will use this response, but
any Worker that doesn't will simply ignore the return value. | amqp_worker/worker_base.py | route | cheese-drawer/lib-python-amqp-worker | 0 | python | def route(self, path: str) -> Callable[([RouteHandler], None)]:
"Add new 'route' (consumer queue) to the worker with this Decorator.\n\n Similar to creating a route in Flask, this method listens on a given\n 'path' (queue name) & executes the given handler (callback) when a\n message is received in that queue.\n\n Returns the data returned by the decorated function, wrapped in a\n Response object. Not all Worker types will use this response, but\n any Worker that doesn't will simply ignore the return value.\n "
self.logger.debug(f'Begin processing route decorator with given path: {path}')
def wrap_handler(path: str, handler: RouteHandler) -> RouteHandler:
async def wrapped(data: Any) -> Response:
self.logger.info(f'TASK RECEIVED {path}')
response: Response
try:
result = (await handler(data))
response = OkResponse(result)
except Exception as err:
response = ErrResponse(err)
self.logger.info(f'TASK COMPLETED {path}: {repr(response)}')
return response
return wrapped
def decorate_route(handler: RouteHandler) -> None:
if inspect.iscoroutinefunction(handler):
new_route = Route(path=path, handler=wrap_handler(path, handler))
self.logger.debug(f'Created new route: {new_route}')
self._routes.append(new_route)
self.logger.debug(f'Pushed new route to _routes: {self._routes}')
else:
raise TypeError(f'Handler {handler} must be a coroutine function')
return decorate_route | def route(self, path: str) -> Callable[([RouteHandler], None)]:
"Add new 'route' (consumer queue) to the worker with this Decorator.\n\n Similar to creating a route in Flask, this method listens on a given\n 'path' (queue name) & executes the given handler (callback) when a\n message is received in that queue.\n\n Returns the data returned by the decorated function, wrapped in a\n Response object. Not all Worker types will use this response, but\n any Worker that doesn't will simply ignore the return value.\n "
self.logger.debug(f'Begin processing route decorator with given path: {path}')
def wrap_handler(path: str, handler: RouteHandler) -> RouteHandler:
async def wrapped(data: Any) -> Response:
self.logger.info(f'TASK RECEIVED {path}')
response: Response
try:
result = (await handler(data))
response = OkResponse(result)
except Exception as err:
response = ErrResponse(err)
self.logger.info(f'TASK COMPLETED {path}: {repr(response)}')
return response
return wrapped
def decorate_route(handler: RouteHandler) -> None:
if inspect.iscoroutinefunction(handler):
new_route = Route(path=path, handler=wrap_handler(path, handler))
self.logger.debug(f'Created new route: {new_route}')
self._routes.append(new_route)
self.logger.debug(f'Pushed new route to _routes: {self._routes}')
else:
raise TypeError(f'Handler {handler} must be a coroutine function')
return decorate_route<|docstring|>Add new 'route' (consumer queue) to the worker with this Decorator.
Similar to creating a route in Flask, this method listens on a given
'path' (queue name) & executes the given handler (callback) when a
message is received in that queue.
Returns the data returned by the decorated function, wrapped in a
Response object. Not all Worker types will use this response, but
any Worker that doesn't will simply ignore the return value.<|endoftext|> |
aa1d0f77d4b5b516b1db733a5e8b8f9020f2d663a8cb2ba2b2257847a139811c | async def run(self) -> Callable[([], Awaitable[None])]:
'Start the RPC Worker.\n\n Must be called inside an asyncio event loop, such as\n `run_until_complete(run())`.\n '
(await self._start())
return self._stop | Start the RPC Worker.
Must be called inside an asyncio event loop, such as
`run_until_complete(run())`. | amqp_worker/worker_base.py | run | cheese-drawer/lib-python-amqp-worker | 0 | python | async def run(self) -> Callable[([], Awaitable[None])]:
'Start the RPC Worker.\n\n Must be called inside an asyncio event loop, such as\n `run_until_complete(run())`.\n '
(await self._start())
return self._stop | async def run(self) -> Callable[([], Awaitable[None])]:
'Start the RPC Worker.\n\n Must be called inside an asyncio event loop, such as\n `run_until_complete(run())`.\n '
(await self._start())
return self._stop<|docstring|>Start the RPC Worker.
Must be called inside an asyncio event loop, such as
`run_until_complete(run())`.<|endoftext|> |
764af12525c5cc79f20c74bca384d7db07693adc8813617c1f26c10b76407102 | def checkBannedTags(self):
'\n Check for banned hashtags using included dictionary dict.txt\n :return:\n '
with open('dict.txt') as dictFile:
dictionary = dictFile.readlines()
dictionary = [word.rstrip('\n') for word in dictionary]
dictSet = set(dictionary)
for item in self.items:
try:
text = item['caption']['text']
hashtags = {tag.strip('#') for tag in text.split() if tag.startswith('#')}
result = hashtags.intersection(dictSet)
if (len(result) != 0):
print((('===========Post code: ' + item['code']) + '============='))
print(hashtags)
print('Found banned hashtags:')
print(result)
except TypeError:
_
self.countHashtags(hashtags)
print('========All posts successfully checked========') | Check for banned hashtags using included dictionary dict.txt
:return: | main.py | checkBannedTags | tiffany-matsuda/Instagram-API-python | 0 | python | def checkBannedTags(self):
'\n Check for banned hashtags using included dictionary dict.txt\n :return:\n '
with open('dict.txt') as dictFile:
dictionary = dictFile.readlines()
dictionary = [word.rstrip('\n') for word in dictionary]
dictSet = set(dictionary)
for item in self.items:
try:
text = item['caption']['text']
hashtags = {tag.strip('#') for tag in text.split() if tag.startswith('#')}
result = hashtags.intersection(dictSet)
if (len(result) != 0):
print((('===========Post code: ' + item['code']) + '============='))
print(hashtags)
print('Found banned hashtags:')
print(result)
except TypeError:
_
self.countHashtags(hashtags)
print('========All posts successfully checked========') | def checkBannedTags(self):
'\n Check for banned hashtags using included dictionary dict.txt\n :return:\n '
with open('dict.txt') as dictFile:
dictionary = dictFile.readlines()
dictionary = [word.rstrip('\n') for word in dictionary]
dictSet = set(dictionary)
for item in self.items:
try:
text = item['caption']['text']
hashtags = {tag.strip('#') for tag in text.split() if tag.startswith('#')}
result = hashtags.intersection(dictSet)
if (len(result) != 0):
print((('===========Post code: ' + item['code']) + '============='))
print(hashtags)
print('Found banned hashtags:')
print(result)
except TypeError:
_
self.countHashtags(hashtags)
print('========All posts successfully checked========')<|docstring|>Check for banned hashtags using included dictionary dict.txt
:return:<|endoftext|> |
243c0d316bf80a6a38df3e5ab1ce401124b2153363a9d8c785f0a3a0e669ebd9 | def countHashtags(self, hashtags):
'\n Adding/updating hashtags to the hashtag dictionary\n :param hashtags: set of hashtags of a post\n :return:\n '
for hashtag in hashtags:
if (hashtag not in self.hashDict.keys()):
self.hashDict.update({hashtag: 1})
else:
self.hashDict.update({hashtag: (self.hashDict[hashtag] + 1)}) | Adding/updating hashtags to the hashtag dictionary
:param hashtags: set of hashtags of a post
:return: | main.py | countHashtags | tiffany-matsuda/Instagram-API-python | 0 | python | def countHashtags(self, hashtags):
'\n Adding/updating hashtags to the hashtag dictionary\n :param hashtags: set of hashtags of a post\n :return:\n '
for hashtag in hashtags:
if (hashtag not in self.hashDict.keys()):
self.hashDict.update({hashtag: 1})
else:
self.hashDict.update({hashtag: (self.hashDict[hashtag] + 1)}) | def countHashtags(self, hashtags):
'\n Adding/updating hashtags to the hashtag dictionary\n :param hashtags: set of hashtags of a post\n :return:\n '
for hashtag in hashtags:
if (hashtag not in self.hashDict.keys()):
self.hashDict.update({hashtag: 1})
else:
self.hashDict.update({hashtag: (self.hashDict[hashtag] + 1)})<|docstring|>Adding/updating hashtags to the hashtag dictionary
:param hashtags: set of hashtags of a post
:return:<|endoftext|> |
23967e0a75b31fbc12b41668594f6ec142acc5b3b73d140007f376ed96632600 | def getFirstComment(self) -> str:
'\n Get First comment of the post\n :return: First comment text\n '
media_id = self.item['id']
has_more_comments = True
max_id = ''
comments = []
while has_more_comments:
_ = api.getMediaComments(media_id, max_id=max_id)
for c in reversed(api.LastJson['comments']):
comments.append(c)
has_more_comments = api.LastJson.get('has_more_comments', False)
if has_more_comments:
max_id = json.loads(api.LastJson.get('next_max_id', ''))['server_cursor']
if (len(comments) >= self.item['comment_count']):
has_more_comments = False
return '' | Get First comment of the post
:return: First comment text | main.py | getFirstComment | tiffany-matsuda/Instagram-API-python | 0 | python | def getFirstComment(self) -> str:
'\n Get First comment of the post\n :return: First comment text\n '
media_id = self.item['id']
has_more_comments = True
max_id =
comments = []
while has_more_comments:
_ = api.getMediaComments(media_id, max_id=max_id)
for c in reversed(api.LastJson['comments']):
comments.append(c)
has_more_comments = api.LastJson.get('has_more_comments', False)
if has_more_comments:
max_id = json.loads(api.LastJson.get('next_max_id', ))['server_cursor']
if (len(comments) >= self.item['comment_count']):
has_more_comments = False
return | def getFirstComment(self) -> str:
'\n Get First comment of the post\n :return: First comment text\n '
media_id = self.item['id']
has_more_comments = True
max_id =
comments = []
while has_more_comments:
_ = api.getMediaComments(media_id, max_id=max_id)
for c in reversed(api.LastJson['comments']):
comments.append(c)
has_more_comments = api.LastJson.get('has_more_comments', False)
if has_more_comments:
max_id = json.loads(api.LastJson.get('next_max_id', ))['server_cursor']
if (len(comments) >= self.item['comment_count']):
has_more_comments = False
return <|docstring|>Get First comment of the post
:return: First comment text<|endoftext|> |
ddd081aeabd79922143ba458aa8bfac38e49c0ae6ae4174b738d5d6f14c71c2e | def printAll(self):
'\n prints captions of all posts\n :param items:\n :return:\n '
for item in self.items:
try:
print((('=========Post code: ' + item['code']) + '============='))
print(item['caption']['text'])
except TypeError:
print('(Empty caption text)') | prints captions of all posts
:param items:
:return: | main.py | printAll | tiffany-matsuda/Instagram-API-python | 0 | python | def printAll(self):
'\n prints captions of all posts\n :param items:\n :return:\n '
for item in self.items:
try:
print((('=========Post code: ' + item['code']) + '============='))
print(item['caption']['text'])
except TypeError:
print('(Empty caption text)') | def printAll(self):
'\n prints captions of all posts\n :param items:\n :return:\n '
for item in self.items:
try:
print((('=========Post code: ' + item['code']) + '============='))
print(item['caption']['text'])
except TypeError:
print('(Empty caption text)')<|docstring|>prints captions of all posts
:param items:
:return:<|endoftext|> |
b4549659e3d1768d2efed60746dff7cf1be47d53f698e062c504596c47bcb9b6 | def printHashtagsDict(self):
'\n Prints top 10 hashtags of user\n :return:\n '
print('========Top 10 Hashtags=========')
hashtagList = sorted(reader.hashDict, key=reader.hashDict.get, reverse=True)
count = 0
for hashtag in hashtagList:
print(hashtag, self.hashDict[hashtag])
count += 1
if (count >= 10):
return | Prints top 10 hashtags of user
:return: | main.py | printHashtagsDict | tiffany-matsuda/Instagram-API-python | 0 | python | def printHashtagsDict(self):
'\n Prints top 10 hashtags of user\n :return:\n '
print('========Top 10 Hashtags=========')
hashtagList = sorted(reader.hashDict, key=reader.hashDict.get, reverse=True)
count = 0
for hashtag in hashtagList:
print(hashtag, self.hashDict[hashtag])
count += 1
if (count >= 10):
return | def printHashtagsDict(self):
'\n Prints top 10 hashtags of user\n :return:\n '
print('========Top 10 Hashtags=========')
hashtagList = sorted(reader.hashDict, key=reader.hashDict.get, reverse=True)
count = 0
for hashtag in hashtagList:
print(hashtag, self.hashDict[hashtag])
count += 1
if (count >= 10):
return<|docstring|>Prints top 10 hashtags of user
:return:<|endoftext|> |
c75b6789df1faacf55597ec27203c9f5c81c9739f7ea00094807098cfa768737 | def use_cache() -> int:
'\n Only use caching when running the test suite to reduce its duration.\n In production, this won\'t always give us fresh enough data, especially\n when using the "MOST_RECENT" request option. So, let\'s skip it for that\n purpose for now.\n\n https://stackoverflow.com/a/58866220\n\n :return: Cache TTL in seconds.\n '
if (('PYTEST_CURRENT_TEST' in os.environ) and ('CI' not in os.environ)):
return (2 * 60)
else:
return 0 | Only use caching when running the test suite to reduce its duration.
In production, this won't always give us fresh enough data, especially
when using the "MOST_RECENT" request option. So, let's skip it for that
purpose for now.
https://stackoverflow.com/a/58866220
:return: Cache TTL in seconds. | wetterdienst/provider/dwd/radar/index.py | use_cache | bh-chaker/wetterdienst | 155 | python | def use_cache() -> int:
'\n Only use caching when running the test suite to reduce its duration.\n In production, this won\'t always give us fresh enough data, especially\n when using the "MOST_RECENT" request option. So, let\'s skip it for that\n purpose for now.\n\n https://stackoverflow.com/a/58866220\n\n :return: Cache TTL in seconds.\n '
if (('PYTEST_CURRENT_TEST' in os.environ) and ('CI' not in os.environ)):
return (2 * 60)
else:
return 0 | def use_cache() -> int:
'\n Only use caching when running the test suite to reduce its duration.\n In production, this won\'t always give us fresh enough data, especially\n when using the "MOST_RECENT" request option. So, let\'s skip it for that\n purpose for now.\n\n https://stackoverflow.com/a/58866220\n\n :return: Cache TTL in seconds.\n '
if (('PYTEST_CURRENT_TEST' in os.environ) and ('CI' not in os.environ)):
return (2 * 60)
else:
return 0<|docstring|>Only use caching when running the test suite to reduce its duration.
In production, this won't always give us fresh enough data, especially
when using the "MOST_RECENT" request option. So, let's skip it for that
purpose for now.
https://stackoverflow.com/a/58866220
:return: Cache TTL in seconds.<|endoftext|> |
62848d042ad73d0bb8cd73f2d41234a1416fdbc64216ac128bff253b88652d9b | @fileindex_cache_five_minutes.cache_on_arguments(expiration_time=use_cache)
def create_fileindex_radar(parameter: DwdRadarParameter, site: Optional[DwdRadarSite]=None, fmt: Optional[DwdRadarDataFormat]=None, subset: Optional[DwdRadarDataSubset]=None, resolution: Optional[Resolution]=None, period: Optional[Period]=None, parse_datetime: bool=False) -> pd.DataFrame:
'\n Function to create a file index of the DWD radar data, which is shipped as\n bin bufr or odim-hdf5 data. The file index is created for a single parameter.\n\n :param parameter: The radar moment to request\n :param site: Site/station if parameter is one of\n RADAR_PARAMETERS_SITES\n :param fmt: Data format (BINARY, BUFR, HDF5)\n :param subset: The subset (simple or polarimetric) for HDF5 data.\n :param resolution: Time resolution for RadarParameter.RADOLAN_CDC,\n either daily or hourly or 5 minutes.\n :param period: Period type for RadarParameter.RADOLAN_CDC\n :param parse_datetime: Whether to parse datetimes from file names\n\n :return: File index as pandas.DataFrame with FILENAME\n and DATETIME columns\n '
parameter_path = build_path_to_parameter(parameter=parameter, site=site, fmt=fmt, subset=subset, resolution=resolution, period=period)
url = urljoin(DWD_SERVER, parameter_path)
files_server = list_remote_files_fsspec(url, recursive=True)
files_server = pd.DataFrame(files_server, columns=[DwdColumns.FILENAME.value], dtype='str')
if (fmt is not None):
if (fmt == DwdRadarDataFormat.BINARY):
files_server = files_server[files_server[DwdColumns.FILENAME.value].str.contains('--bin')]
elif (fmt == DwdRadarDataFormat.BUFR):
files_server = files_server[files_server[DwdColumns.FILENAME.value].str.contains('--buf')]
if parse_datetime:
files_server[DwdColumns.DATETIME.value] = files_server[DwdColumns.FILENAME.value].apply(get_date_from_filename)
files_server = files_server.dropna()
return files_server | Function to create a file index of the DWD radar data, which is shipped as
bin bufr or odim-hdf5 data. The file index is created for a single parameter.
:param parameter: The radar moment to request
:param site: Site/station if parameter is one of
RADAR_PARAMETERS_SITES
:param fmt: Data format (BINARY, BUFR, HDF5)
:param subset: The subset (simple or polarimetric) for HDF5 data.
:param resolution: Time resolution for RadarParameter.RADOLAN_CDC,
either daily or hourly or 5 minutes.
:param period: Period type for RadarParameter.RADOLAN_CDC
:param parse_datetime: Whether to parse datetimes from file names
:return: File index as pandas.DataFrame with FILENAME
and DATETIME columns | wetterdienst/provider/dwd/radar/index.py | create_fileindex_radar | bh-chaker/wetterdienst | 155 | python | @fileindex_cache_five_minutes.cache_on_arguments(expiration_time=use_cache)
def create_fileindex_radar(parameter: DwdRadarParameter, site: Optional[DwdRadarSite]=None, fmt: Optional[DwdRadarDataFormat]=None, subset: Optional[DwdRadarDataSubset]=None, resolution: Optional[Resolution]=None, period: Optional[Period]=None, parse_datetime: bool=False) -> pd.DataFrame:
'\n Function to create a file index of the DWD radar data, which is shipped as\n bin bufr or odim-hdf5 data. The file index is created for a single parameter.\n\n :param parameter: The radar moment to request\n :param site: Site/station if parameter is one of\n RADAR_PARAMETERS_SITES\n :param fmt: Data format (BINARY, BUFR, HDF5)\n :param subset: The subset (simple or polarimetric) for HDF5 data.\n :param resolution: Time resolution for RadarParameter.RADOLAN_CDC,\n either daily or hourly or 5 minutes.\n :param period: Period type for RadarParameter.RADOLAN_CDC\n :param parse_datetime: Whether to parse datetimes from file names\n\n :return: File index as pandas.DataFrame with FILENAME\n and DATETIME columns\n '
parameter_path = build_path_to_parameter(parameter=parameter, site=site, fmt=fmt, subset=subset, resolution=resolution, period=period)
url = urljoin(DWD_SERVER, parameter_path)
files_server = list_remote_files_fsspec(url, recursive=True)
files_server = pd.DataFrame(files_server, columns=[DwdColumns.FILENAME.value], dtype='str')
if (fmt is not None):
if (fmt == DwdRadarDataFormat.BINARY):
files_server = files_server[files_server[DwdColumns.FILENAME.value].str.contains('--bin')]
elif (fmt == DwdRadarDataFormat.BUFR):
files_server = files_server[files_server[DwdColumns.FILENAME.value].str.contains('--buf')]
if parse_datetime:
files_server[DwdColumns.DATETIME.value] = files_server[DwdColumns.FILENAME.value].apply(get_date_from_filename)
files_server = files_server.dropna()
return files_server | @fileindex_cache_five_minutes.cache_on_arguments(expiration_time=use_cache)
def create_fileindex_radar(parameter: DwdRadarParameter, site: Optional[DwdRadarSite]=None, fmt: Optional[DwdRadarDataFormat]=None, subset: Optional[DwdRadarDataSubset]=None, resolution: Optional[Resolution]=None, period: Optional[Period]=None, parse_datetime: bool=False) -> pd.DataFrame:
'\n Function to create a file index of the DWD radar data, which is shipped as\n bin bufr or odim-hdf5 data. The file index is created for a single parameter.\n\n :param parameter: The radar moment to request\n :param site: Site/station if parameter is one of\n RADAR_PARAMETERS_SITES\n :param fmt: Data format (BINARY, BUFR, HDF5)\n :param subset: The subset (simple or polarimetric) for HDF5 data.\n :param resolution: Time resolution for RadarParameter.RADOLAN_CDC,\n either daily or hourly or 5 minutes.\n :param period: Period type for RadarParameter.RADOLAN_CDC\n :param parse_datetime: Whether to parse datetimes from file names\n\n :return: File index as pandas.DataFrame with FILENAME\n and DATETIME columns\n '
parameter_path = build_path_to_parameter(parameter=parameter, site=site, fmt=fmt, subset=subset, resolution=resolution, period=period)
url = urljoin(DWD_SERVER, parameter_path)
files_server = list_remote_files_fsspec(url, recursive=True)
files_server = pd.DataFrame(files_server, columns=[DwdColumns.FILENAME.value], dtype='str')
if (fmt is not None):
if (fmt == DwdRadarDataFormat.BINARY):
files_server = files_server[files_server[DwdColumns.FILENAME.value].str.contains('--bin')]
elif (fmt == DwdRadarDataFormat.BUFR):
files_server = files_server[files_server[DwdColumns.FILENAME.value].str.contains('--buf')]
if parse_datetime:
files_server[DwdColumns.DATETIME.value] = files_server[DwdColumns.FILENAME.value].apply(get_date_from_filename)
files_server = files_server.dropna()
return files_server<|docstring|>Function to create a file index of the DWD radar data, which is shipped as
bin bufr or odim-hdf5 data. The file index is created for a single parameter.
:param parameter: The radar moment to request
:param site: Site/station if parameter is one of
RADAR_PARAMETERS_SITES
:param fmt: Data format (BINARY, BUFR, HDF5)
:param subset: The subset (simple or polarimetric) for HDF5 data.
:param resolution: Time resolution for RadarParameter.RADOLAN_CDC,
either daily or hourly or 5 minutes.
:param period: Period type for RadarParameter.RADOLAN_CDC
:param parse_datetime: Whether to parse datetimes from file names
:return: File index as pandas.DataFrame with FILENAME
and DATETIME columns<|endoftext|> |
c063d18496d83b5c23c9e87fc3adcaf27a04772cbb91357a47f148bebec97e84 | @fileindex_cache_five_minutes.cache_on_arguments()
def create_fileindex_radolan_cdc(resolution: Resolution, period: Period) -> pd.DataFrame:
'\n Function used to create a file index for the RADOLAN_CDC product. The file index\n will include both recent as well as historical files. A datetime column is created\n from the filenames which contain some datetime formats. This datetime column is\n required for later filtering for the requested file.\n\n :param resolution: Time resolution for RadarParameter.RADOLAN_CDC,\n either daily or hourly or 5 minutes.\n :param period: Period type for RadarParameter.RADOLAN_CDC\n\n :return: File index as DataFrame\n '
file_index = create_fileindex_radar(parameter=DwdRadarParameter.RADOLAN_CDC, resolution=resolution, period=period)
file_index = file_index[(file_index[DwdColumns.FILENAME.value].str.contains('/bin/') & file_index[DwdColumns.FILENAME.value].str.endswith((Extension.GZ.value, Extension.TAR_GZ.value)))].copy()
file_index[DwdColumns.DATETIME.value] = file_index[DwdColumns.FILENAME.value].apply((lambda filename: parse(RADOLAN_DT_PATTERN.findall(filename)[0], date_formats=[DatetimeFormat.YM.value, DatetimeFormat.ymdhm.value])))
return file_index | Function used to create a file index for the RADOLAN_CDC product. The file index
will include both recent as well as historical files. A datetime column is created
from the filenames which contain some datetime formats. This datetime column is
required for later filtering for the requested file.
:param resolution: Time resolution for RadarParameter.RADOLAN_CDC,
either daily or hourly or 5 minutes.
:param period: Period type for RadarParameter.RADOLAN_CDC
:return: File index as DataFrame | wetterdienst/provider/dwd/radar/index.py | create_fileindex_radolan_cdc | bh-chaker/wetterdienst | 155 | python | @fileindex_cache_five_minutes.cache_on_arguments()
def create_fileindex_radolan_cdc(resolution: Resolution, period: Period) -> pd.DataFrame:
'\n Function used to create a file index for the RADOLAN_CDC product. The file index\n will include both recent as well as historical files. A datetime column is created\n from the filenames which contain some datetime formats. This datetime column is\n required for later filtering for the requested file.\n\n :param resolution: Time resolution for RadarParameter.RADOLAN_CDC,\n either daily or hourly or 5 minutes.\n :param period: Period type for RadarParameter.RADOLAN_CDC\n\n :return: File index as DataFrame\n '
file_index = create_fileindex_radar(parameter=DwdRadarParameter.RADOLAN_CDC, resolution=resolution, period=period)
file_index = file_index[(file_index[DwdColumns.FILENAME.value].str.contains('/bin/') & file_index[DwdColumns.FILENAME.value].str.endswith((Extension.GZ.value, Extension.TAR_GZ.value)))].copy()
file_index[DwdColumns.DATETIME.value] = file_index[DwdColumns.FILENAME.value].apply((lambda filename: parse(RADOLAN_DT_PATTERN.findall(filename)[0], date_formats=[DatetimeFormat.YM.value, DatetimeFormat.ymdhm.value])))
return file_index | @fileindex_cache_five_minutes.cache_on_arguments()
def create_fileindex_radolan_cdc(resolution: Resolution, period: Period) -> pd.DataFrame:
'\n Function used to create a file index for the RADOLAN_CDC product. The file index\n will include both recent as well as historical files. A datetime column is created\n from the filenames which contain some datetime formats. This datetime column is\n required for later filtering for the requested file.\n\n :param resolution: Time resolution for RadarParameter.RADOLAN_CDC,\n either daily or hourly or 5 minutes.\n :param period: Period type for RadarParameter.RADOLAN_CDC\n\n :return: File index as DataFrame\n '
file_index = create_fileindex_radar(parameter=DwdRadarParameter.RADOLAN_CDC, resolution=resolution, period=period)
file_index = file_index[(file_index[DwdColumns.FILENAME.value].str.contains('/bin/') & file_index[DwdColumns.FILENAME.value].str.endswith((Extension.GZ.value, Extension.TAR_GZ.value)))].copy()
file_index[DwdColumns.DATETIME.value] = file_index[DwdColumns.FILENAME.value].apply((lambda filename: parse(RADOLAN_DT_PATTERN.findall(filename)[0], date_formats=[DatetimeFormat.YM.value, DatetimeFormat.ymdhm.value])))
return file_index<|docstring|>Function used to create a file index for the RADOLAN_CDC product. The file index
will include both recent as well as historical files. A datetime column is created
from the filenames which contain some datetime formats. This datetime column is
required for later filtering for the requested file.
:param resolution: Time resolution for RadarParameter.RADOLAN_CDC,
either daily or hourly or 5 minutes.
:param period: Period type for RadarParameter.RADOLAN_CDC
:return: File index as DataFrame<|endoftext|> |
56b60430bcbbbbe3bd88c85387f2166acf4d844c48d5ab9f4c319d6f45e7bffe | def build_path_to_parameter(parameter: DwdRadarParameter, site: Optional[DwdRadarSite]=None, fmt: Optional[DwdRadarDataFormat]=None, subset: Optional[DwdRadarDataSubset]=None, resolution: Optional[Resolution]=None, period: Optional[Period]=None) -> str:
'\n Compute URL path to data product.\n\n Supports composite- and site-based radar data as well as RADOLAN_CDC.\n\n Composites\n ----------\n - https://opendata.dwd.de/weather/radar/composit/\n - https://opendata.dwd.de/weather/radar/radolan/\n - https://opendata.dwd.de/climate_environment/CDC/grids_germany/daily/radolan/\n - https://opendata.dwd.de/climate_environment/CDC/grids_germany/hourly/radolan/\n - https://opendata.dwd.de/climate_environment/CDC/grids_germany/5_minutes/radolan/\n\n Sites\n -----\n - https://opendata.dwd.de/weather/radar/sites/\n\n\n :param parameter: The radar moment to request\n :param site: Site/station if parameter is one of\n RADAR_PARAMETERS_SITES\n :param fmt: Data format (BINARY, BUFR, HDF5)\n :param subset: The subset (simple or polarimetric) for HDF5 data.\n :param resolution: Time resolution for RadarParameter.RADOLAN_CDC,\n either daily or hourly or 5 minutes.\n :param period: Period type for RadarParameter.RADOLAN_CDC\n\n :return: URL path to data product\n '
if (parameter == DwdRadarParameter.RADOLAN_CDC):
if (resolution == Resolution.MINUTE_5):
parameter_path = f'{DWD_CDC_PATH}/grids_germany/{resolution.value}/radolan/reproc/2017_002/bin'
else:
parameter_path = f'{DWD_CDC_PATH}/grids_germany/{resolution.value}/radolan/{period.value}/bin'
elif (parameter in RADAR_PARAMETERS_COMPOSITES):
parameter_path = f'weather/radar/composit/{parameter.value}'
elif (parameter in RADAR_PARAMETERS_RADOLAN):
parameter_path = f'weather/radar/radolan/{parameter.value}'
elif (parameter in RADAR_PARAMETERS_RADVOR):
parameter_path = f'weather/radar/radvor/{parameter.value}'
elif (parameter in RADAR_PARAMETERS_SITES):
if (site is None):
raise ValueError("Argument 'site' is missing")
if (fmt is None):
ambiguous_parameters = [DwdRadarParameter.PE_ECHO_TOP, DwdRadarParameter.PL_VOLUME_SCAN, DwdRadarParameter.PR_VELOCITY, DwdRadarParameter.PX_REFLECTIVITY, DwdRadarParameter.PZ_CAPPI]
candidates = None
if (parameter in ambiguous_parameters):
candidates = [DwdRadarDataFormat.BINARY, DwdRadarDataFormat.BUFR]
if (parameter in RADAR_PARAMETERS_SWEEPS):
candidates = [DwdRadarDataFormat.BUFR, DwdRadarDataFormat.HDF5]
if candidates:
raise ValueError(f"Argument 'format' is missing, use one of {candidates}")
parameter_path = f'weather/radar/sites/{parameter.value}/{site.value}'
if (fmt == DwdRadarDataFormat.HDF5):
if (subset is None):
candidates = [DwdRadarDataSubset.SIMPLE, DwdRadarDataSubset.POLARIMETRIC]
raise ValueError(f"Argument 'subset' is missing, use one of {candidates}")
parameter_path = f'{parameter_path}/{fmt.value}/filter_{subset.value}/'
else:
raise NotImplementedError(f'Acquisition for {parameter} not implemented yet')
return parameter_path | Compute URL path to data product.
Supports composite- and site-based radar data as well as RADOLAN_CDC.
Composites
----------
- https://opendata.dwd.de/weather/radar/composit/
- https://opendata.dwd.de/weather/radar/radolan/
- https://opendata.dwd.de/climate_environment/CDC/grids_germany/daily/radolan/
- https://opendata.dwd.de/climate_environment/CDC/grids_germany/hourly/radolan/
- https://opendata.dwd.de/climate_environment/CDC/grids_germany/5_minutes/radolan/
Sites
-----
- https://opendata.dwd.de/weather/radar/sites/
:param parameter: The radar moment to request
:param site: Site/station if parameter is one of
RADAR_PARAMETERS_SITES
:param fmt: Data format (BINARY, BUFR, HDF5)
:param subset: The subset (simple or polarimetric) for HDF5 data.
:param resolution: Time resolution for RadarParameter.RADOLAN_CDC,
either daily or hourly or 5 minutes.
:param period: Period type for RadarParameter.RADOLAN_CDC
:return: URL path to data product | wetterdienst/provider/dwd/radar/index.py | build_path_to_parameter | bh-chaker/wetterdienst | 155 | python | def build_path_to_parameter(parameter: DwdRadarParameter, site: Optional[DwdRadarSite]=None, fmt: Optional[DwdRadarDataFormat]=None, subset: Optional[DwdRadarDataSubset]=None, resolution: Optional[Resolution]=None, period: Optional[Period]=None) -> str:
'\n Compute URL path to data product.\n\n Supports composite- and site-based radar data as well as RADOLAN_CDC.\n\n Composites\n ----------\n - https://opendata.dwd.de/weather/radar/composit/\n - https://opendata.dwd.de/weather/radar/radolan/\n - https://opendata.dwd.de/climate_environment/CDC/grids_germany/daily/radolan/\n - https://opendata.dwd.de/climate_environment/CDC/grids_germany/hourly/radolan/\n - https://opendata.dwd.de/climate_environment/CDC/grids_germany/5_minutes/radolan/\n\n Sites\n -----\n - https://opendata.dwd.de/weather/radar/sites/\n\n\n :param parameter: The radar moment to request\n :param site: Site/station if parameter is one of\n RADAR_PARAMETERS_SITES\n :param fmt: Data format (BINARY, BUFR, HDF5)\n :param subset: The subset (simple or polarimetric) for HDF5 data.\n :param resolution: Time resolution for RadarParameter.RADOLAN_CDC,\n either daily or hourly or 5 minutes.\n :param period: Period type for RadarParameter.RADOLAN_CDC\n\n :return: URL path to data product\n '
if (parameter == DwdRadarParameter.RADOLAN_CDC):
if (resolution == Resolution.MINUTE_5):
parameter_path = f'{DWD_CDC_PATH}/grids_germany/{resolution.value}/radolan/reproc/2017_002/bin'
else:
parameter_path = f'{DWD_CDC_PATH}/grids_germany/{resolution.value}/radolan/{period.value}/bin'
elif (parameter in RADAR_PARAMETERS_COMPOSITES):
parameter_path = f'weather/radar/composit/{parameter.value}'
elif (parameter in RADAR_PARAMETERS_RADOLAN):
parameter_path = f'weather/radar/radolan/{parameter.value}'
elif (parameter in RADAR_PARAMETERS_RADVOR):
parameter_path = f'weather/radar/radvor/{parameter.value}'
elif (parameter in RADAR_PARAMETERS_SITES):
if (site is None):
raise ValueError("Argument 'site' is missing")
if (fmt is None):
ambiguous_parameters = [DwdRadarParameter.PE_ECHO_TOP, DwdRadarParameter.PL_VOLUME_SCAN, DwdRadarParameter.PR_VELOCITY, DwdRadarParameter.PX_REFLECTIVITY, DwdRadarParameter.PZ_CAPPI]
candidates = None
if (parameter in ambiguous_parameters):
candidates = [DwdRadarDataFormat.BINARY, DwdRadarDataFormat.BUFR]
if (parameter in RADAR_PARAMETERS_SWEEPS):
candidates = [DwdRadarDataFormat.BUFR, DwdRadarDataFormat.HDF5]
if candidates:
raise ValueError(f"Argument 'format' is missing, use one of {candidates}")
parameter_path = f'weather/radar/sites/{parameter.value}/{site.value}'
if (fmt == DwdRadarDataFormat.HDF5):
if (subset is None):
candidates = [DwdRadarDataSubset.SIMPLE, DwdRadarDataSubset.POLARIMETRIC]
raise ValueError(f"Argument 'subset' is missing, use one of {candidates}")
parameter_path = f'{parameter_path}/{fmt.value}/filter_{subset.value}/'
else:
raise NotImplementedError(f'Acquisition for {parameter} not implemented yet')
return parameter_path | def build_path_to_parameter(parameter: DwdRadarParameter, site: Optional[DwdRadarSite]=None, fmt: Optional[DwdRadarDataFormat]=None, subset: Optional[DwdRadarDataSubset]=None, resolution: Optional[Resolution]=None, period: Optional[Period]=None) -> str:
'\n Compute URL path to data product.\n\n Supports composite- and site-based radar data as well as RADOLAN_CDC.\n\n Composites\n ----------\n - https://opendata.dwd.de/weather/radar/composit/\n - https://opendata.dwd.de/weather/radar/radolan/\n - https://opendata.dwd.de/climate_environment/CDC/grids_germany/daily/radolan/\n - https://opendata.dwd.de/climate_environment/CDC/grids_germany/hourly/radolan/\n - https://opendata.dwd.de/climate_environment/CDC/grids_germany/5_minutes/radolan/\n\n Sites\n -----\n - https://opendata.dwd.de/weather/radar/sites/\n\n\n :param parameter: The radar moment to request\n :param site: Site/station if parameter is one of\n RADAR_PARAMETERS_SITES\n :param fmt: Data format (BINARY, BUFR, HDF5)\n :param subset: The subset (simple or polarimetric) for HDF5 data.\n :param resolution: Time resolution for RadarParameter.RADOLAN_CDC,\n either daily or hourly or 5 minutes.\n :param period: Period type for RadarParameter.RADOLAN_CDC\n\n :return: URL path to data product\n '
if (parameter == DwdRadarParameter.RADOLAN_CDC):
if (resolution == Resolution.MINUTE_5):
parameter_path = f'{DWD_CDC_PATH}/grids_germany/{resolution.value}/radolan/reproc/2017_002/bin'
else:
parameter_path = f'{DWD_CDC_PATH}/grids_germany/{resolution.value}/radolan/{period.value}/bin'
elif (parameter in RADAR_PARAMETERS_COMPOSITES):
parameter_path = f'weather/radar/composit/{parameter.value}'
elif (parameter in RADAR_PARAMETERS_RADOLAN):
parameter_path = f'weather/radar/radolan/{parameter.value}'
elif (parameter in RADAR_PARAMETERS_RADVOR):
parameter_path = f'weather/radar/radvor/{parameter.value}'
elif (parameter in RADAR_PARAMETERS_SITES):
if (site is None):
raise ValueError("Argument 'site' is missing")
if (fmt is None):
ambiguous_parameters = [DwdRadarParameter.PE_ECHO_TOP, DwdRadarParameter.PL_VOLUME_SCAN, DwdRadarParameter.PR_VELOCITY, DwdRadarParameter.PX_REFLECTIVITY, DwdRadarParameter.PZ_CAPPI]
candidates = None
if (parameter in ambiguous_parameters):
candidates = [DwdRadarDataFormat.BINARY, DwdRadarDataFormat.BUFR]
if (parameter in RADAR_PARAMETERS_SWEEPS):
candidates = [DwdRadarDataFormat.BUFR, DwdRadarDataFormat.HDF5]
if candidates:
raise ValueError(f"Argument 'format' is missing, use one of {candidates}")
parameter_path = f'weather/radar/sites/{parameter.value}/{site.value}'
if (fmt == DwdRadarDataFormat.HDF5):
if (subset is None):
candidates = [DwdRadarDataSubset.SIMPLE, DwdRadarDataSubset.POLARIMETRIC]
raise ValueError(f"Argument 'subset' is missing, use one of {candidates}")
parameter_path = f'{parameter_path}/{fmt.value}/filter_{subset.value}/'
else:
raise NotImplementedError(f'Acquisition for {parameter} not implemented yet')
return parameter_path<|docstring|>Compute URL path to data product.
Supports composite- and site-based radar data as well as RADOLAN_CDC.
Composites
----------
- https://opendata.dwd.de/weather/radar/composit/
- https://opendata.dwd.de/weather/radar/radolan/
- https://opendata.dwd.de/climate_environment/CDC/grids_germany/daily/radolan/
- https://opendata.dwd.de/climate_environment/CDC/grids_germany/hourly/radolan/
- https://opendata.dwd.de/climate_environment/CDC/grids_germany/5_minutes/radolan/
Sites
-----
- https://opendata.dwd.de/weather/radar/sites/
:param parameter: The radar moment to request
:param site: Site/station if parameter is one of
RADAR_PARAMETERS_SITES
:param fmt: Data format (BINARY, BUFR, HDF5)
:param subset: The subset (simple or polarimetric) for HDF5 data.
:param resolution: Time resolution for RadarParameter.RADOLAN_CDC,
either daily or hourly or 5 minutes.
:param period: Period type for RadarParameter.RADOLAN_CDC
:return: URL path to data product<|endoftext|> |
687443bd236b7db072b7a974f23cb4eebf679c3960172064c32f142453768e20 | def print_dumped(source):
'Pretty print the AST'
if isinstance(source, str):
module = extast.parse(source)
if (len(module.body) == 1):
node = module.body[0]
else:
node = module
else:
node = source
print(dump(node)) | Pretty print the AST | transonic/analyses/util.py | print_dumped | fluiddyn/transonic | 88 | python | def print_dumped(source):
if isinstance(source, str):
module = extast.parse(source)
if (len(module.body) == 1):
node = module.body[0]
else:
node = module
else:
node = source
print(dump(node)) | def print_dumped(source):
if isinstance(source, str):
module = extast.parse(source)
if (len(module.body) == 1):
node = module.body[0]
else:
node = module
else:
node = source
print(dump(node))<|docstring|>Pretty print the AST<|endoftext|> |
095175e9aace162de875d5a4ac93f74fa999ae639554e922aa8c21d6e6e0e5df | def print_unparsed(node):
'Print the code corresponding to a tree or a node'
print(extast.unparse(node)) | Print the code corresponding to a tree or a node | transonic/analyses/util.py | print_unparsed | fluiddyn/transonic | 88 | python | def print_unparsed(node):
print(extast.unparse(node)) | def print_unparsed(node):
print(extast.unparse(node))<|docstring|>Print the code corresponding to a tree or a node<|endoftext|> |
03653c32a3925397a364374eb78c48267127b5bbca56db3c10480d8c24bbec02 | def get_annotations(object_def, namespace):
'Create the annotations from a definition node'
ast_annotations = ast.Assign(targets=[extast.Name('annotations', ast.Store())], value=ast.Dict(keys=[], values=[]), type_comment=None)
if isinstance(object_def, ast.FunctionDef):
_fill_ast_annotations_function(object_def, ast_annotations)
elif isinstance(object_def, ast.ClassDef):
_fill_ast_annotations_class(object_def, ast_annotations)
else:
raise NotImplementedError
source = extast.unparse(ast_annotations)
try:
del namespace['__builtins__']
except KeyError:
pass
exec(source, namespace)
return namespace['annotations'] | Create the annotations from a definition node | transonic/analyses/util.py | get_annotations | fluiddyn/transonic | 88 | python | def get_annotations(object_def, namespace):
ast_annotations = ast.Assign(targets=[extast.Name('annotations', ast.Store())], value=ast.Dict(keys=[], values=[]), type_comment=None)
if isinstance(object_def, ast.FunctionDef):
_fill_ast_annotations_function(object_def, ast_annotations)
elif isinstance(object_def, ast.ClassDef):
_fill_ast_annotations_class(object_def, ast_annotations)
else:
raise NotImplementedError
source = extast.unparse(ast_annotations)
try:
del namespace['__builtins__']
except KeyError:
pass
exec(source, namespace)
return namespace['annotations'] | def get_annotations(object_def, namespace):
ast_annotations = ast.Assign(targets=[extast.Name('annotations', ast.Store())], value=ast.Dict(keys=[], values=[]), type_comment=None)
if isinstance(object_def, ast.FunctionDef):
_fill_ast_annotations_function(object_def, ast_annotations)
elif isinstance(object_def, ast.ClassDef):
_fill_ast_annotations_class(object_def, ast_annotations)
else:
raise NotImplementedError
source = extast.unparse(ast_annotations)
try:
del namespace['__builtins__']
except KeyError:
pass
exec(source, namespace)
return namespace['annotations']<|docstring|>Create the annotations from a definition node<|endoftext|> |
b978493d949853417155503b5438a0ddce131df3d2eda49414752393a8247496 | def filter_code_typevars(module, duc, ancestors):
'Create a filtered code with what is needed to create the annotations'
module_filtered = ast.Module()
kept = module_filtered.body = []
module_filtered.type_ignores = []
suppressed = set()
def fill_suppressed(def_):
for user in def_.users():
parent_in_body = ancestors.parents(user.node)[1]
suppressed.add(parent_in_body)
fill_suppressed(user)
for node in module.body:
if (node in suppressed):
continue
if isinstance(node, ast.Import):
if (node.names[0].name in ['transonic', 'numpy']):
kept.append(node)
else:
def_ = duc.chains[node.names[0]]
fill_suppressed(def_)
elif isinstance(node, ast.ImportFrom):
if (node.module in ['transonic', 'numpy']):
kept.append(node)
elif isinstance(node, (ast.Assign, ast.AugAssign)):
kept.append(node)
return extast.unparse(module_filtered) | Create a filtered code with what is needed to create the annotations | transonic/analyses/util.py | filter_code_typevars | fluiddyn/transonic | 88 | python | def filter_code_typevars(module, duc, ancestors):
module_filtered = ast.Module()
kept = module_filtered.body = []
module_filtered.type_ignores = []
suppressed = set()
def fill_suppressed(def_):
for user in def_.users():
parent_in_body = ancestors.parents(user.node)[1]
suppressed.add(parent_in_body)
fill_suppressed(user)
for node in module.body:
if (node in suppressed):
continue
if isinstance(node, ast.Import):
if (node.names[0].name in ['transonic', 'numpy']):
kept.append(node)
else:
def_ = duc.chains[node.names[0]]
fill_suppressed(def_)
elif isinstance(node, ast.ImportFrom):
if (node.module in ['transonic', 'numpy']):
kept.append(node)
elif isinstance(node, (ast.Assign, ast.AugAssign)):
kept.append(node)
return extast.unparse(module_filtered) | def filter_code_typevars(module, duc, ancestors):
module_filtered = ast.Module()
kept = module_filtered.body = []
module_filtered.type_ignores = []
suppressed = set()
def fill_suppressed(def_):
for user in def_.users():
parent_in_body = ancestors.parents(user.node)[1]
suppressed.add(parent_in_body)
fill_suppressed(user)
for node in module.body:
if (node in suppressed):
continue
if isinstance(node, ast.Import):
if (node.names[0].name in ['transonic', 'numpy']):
kept.append(node)
else:
def_ = duc.chains[node.names[0]]
fill_suppressed(def_)
elif isinstance(node, ast.ImportFrom):
if (node.module in ['transonic', 'numpy']):
kept.append(node)
elif isinstance(node, (ast.Assign, ast.AugAssign)):
kept.append(node)
return extast.unparse(module_filtered)<|docstring|>Create a filtered code with what is needed to create the annotations<|endoftext|> |
7c057214f9c8feb62d1b6a6a604b1462da79037bff581f3e229b33aa3f7578a0 | def gather_rawcode_comments(node, code_module):
'Get the comments in a node'
analysis = AnalyseLines(node)
rawcode = dedent(analysis.get_code(code_module))
comments = dedent('\n'.join((line for line in rawcode.split('\n') if line.strip().startswith('#'))))
return (rawcode, comments) | Get the comments in a node | transonic/analyses/util.py | gather_rawcode_comments | fluiddyn/transonic | 88 | python | def gather_rawcode_comments(node, code_module):
analysis = AnalyseLines(node)
rawcode = dedent(analysis.get_code(code_module))
comments = dedent('\n'.join((line for line in rawcode.split('\n') if line.strip().startswith('#'))))
return (rawcode, comments) | def gather_rawcode_comments(node, code_module):
analysis = AnalyseLines(node)
rawcode = dedent(analysis.get_code(code_module))
comments = dedent('\n'.join((line for line in rawcode.split('\n') if line.strip().startswith('#'))))
return (rawcode, comments)<|docstring|>Get the comments in a node<|endoftext|> |
76e6050cf36b99cea2d4370048d25f61608f2585f5deed80b5120fc651fc0137 | def find_path(node: object, pathfile: str):
'Return the path of node (instance of ast.Import or ast.ImportFrom)'
name = str()
path = str()
if isinstance(node, ast.ImportFrom):
name = node.module
if (name in packages_supported_by_pythran):
return (None, None)
else:
parent = Path(pathfile).parent
path = (parent / (str(name.replace('.', '/')) + '.py'))
elif (node.names[0].name in packages_supported_by_pythran):
pass
else:
raise NotImplementedError
return (name, path) | Return the path of node (instance of ast.Import or ast.ImportFrom) | transonic/analyses/util.py | find_path | fluiddyn/transonic | 88 | python | def find_path(node: object, pathfile: str):
name = str()
path = str()
if isinstance(node, ast.ImportFrom):
name = node.module
if (name in packages_supported_by_pythran):
return (None, None)
else:
parent = Path(pathfile).parent
path = (parent / (str(name.replace('.', '/')) + '.py'))
elif (node.names[0].name in packages_supported_by_pythran):
pass
else:
raise NotImplementedError
return (name, path) | def find_path(node: object, pathfile: str):
name = str()
path = str()
if isinstance(node, ast.ImportFrom):
name = node.module
if (name in packages_supported_by_pythran):
return (None, None)
else:
parent = Path(pathfile).parent
path = (parent / (str(name.replace('.', '/')) + '.py'))
elif (node.names[0].name in packages_supported_by_pythran):
pass
else:
raise NotImplementedError
return (name, path)<|docstring|>Return the path of node (instance of ast.Import or ast.ImportFrom)<|endoftext|> |
055f032b1f961ef45c73a5ecb481754dbbb3d6d60fce102153f4cef4a889c9f7 | def change_import_name(code_dep: str, changed_node: object, func_name: str, relative: str=None):
'Change the name of changed_node in code_dep by adding "__" + func + "__"\n at the beginning of the imported module, and return the modified code\n '
mod = extast.parse(code_dep)
for node in mod.body:
if (extast.unparse(node) == extast.unparse(changed_node)):
if isinstance(node, ast.ImportFrom):
node.module = f'__ext__{func_name}__{node.module}'
elif isinstance(node, ast.Import):
node.names[0].name = f'__ext__{func_name}__{node.names[0].name}'
if (not relative):
node.level = 0
return extast.unparse(mod) | Change the name of changed_node in code_dep by adding "__" + func + "__"
at the beginning of the imported module, and return the modified code | transonic/analyses/util.py | change_import_name | fluiddyn/transonic | 88 | python | def change_import_name(code_dep: str, changed_node: object, func_name: str, relative: str=None):
'Change the name of changed_node in code_dep by adding "__" + func + "__"\n at the beginning of the imported module, and return the modified code\n '
mod = extast.parse(code_dep)
for node in mod.body:
if (extast.unparse(node) == extast.unparse(changed_node)):
if isinstance(node, ast.ImportFrom):
node.module = f'__ext__{func_name}__{node.module}'
elif isinstance(node, ast.Import):
node.names[0].name = f'__ext__{func_name}__{node.names[0].name}'
if (not relative):
node.level = 0
return extast.unparse(mod) | def change_import_name(code_dep: str, changed_node: object, func_name: str, relative: str=None):
'Change the name of changed_node in code_dep by adding "__" + func + "__"\n at the beginning of the imported module, and return the modified code\n '
mod = extast.parse(code_dep)
for node in mod.body:
if (extast.unparse(node) == extast.unparse(changed_node)):
if isinstance(node, ast.ImportFrom):
node.module = f'__ext__{func_name}__{node.module}'
elif isinstance(node, ast.Import):
node.names[0].name = f'__ext__{func_name}__{node.names[0].name}'
if (not relative):
node.level = 0
return extast.unparse(mod)<|docstring|>Change the name of changed_node in code_dep by adding "__" + func + "__"
at the beginning of the imported module, and return the modified code<|endoftext|> |
14c28ba862efe9e2eb0a0d7ead67324c6e5cc4eca4c0a992fce96c2b3088b19d | def filter_external_code(module: object, names: list):
'Filter the module to keep only the necessary nodes\n needed by functions or class in the parameter names\n '
code_dependance_annotations = ''
lines_code = []
for node in module.body:
for name in names:
if isinstance(node, ast.FunctionDef):
if (node.name == extast.unparse(name).rstrip('\n\r').strip()):
ancestors = beniget.Ancestors()
ancestors.visit(module)
duc = beniget.DefUseChains()
duc.visit(module)
udc = beniget.UseDefChains(duc)
capturex = CaptureX([node], module, ancestors, defuse_chains=duc, usedef_chains=udc, consider_annotations=None)
lines_code.append(str(extast.unparse(node)))
code_dependance_annotations = capturex.make_code_external()
if isinstance(node, ast.Assign):
if (node.targets[0].id == extast.unparse(name).rstrip('\n\r').strip()):
lines_code.append(str(extast.unparse(node)))
if isinstance(node, ast.ClassDef):
if (node.name == extast.unparse(name).rstrip('\n\r').strip()):
lines_code.append(str(extast.unparse(node)))
return ((code_dependance_annotations + '\n') + '\n'.join(lines_code)) | Filter the module to keep only the necessary nodes
needed by functions or class in the parameter names | transonic/analyses/util.py | filter_external_code | fluiddyn/transonic | 88 | python | def filter_external_code(module: object, names: list):
'Filter the module to keep only the necessary nodes\n needed by functions or class in the parameter names\n '
code_dependance_annotations =
lines_code = []
for node in module.body:
for name in names:
if isinstance(node, ast.FunctionDef):
if (node.name == extast.unparse(name).rstrip('\n\r').strip()):
ancestors = beniget.Ancestors()
ancestors.visit(module)
duc = beniget.DefUseChains()
duc.visit(module)
udc = beniget.UseDefChains(duc)
capturex = CaptureX([node], module, ancestors, defuse_chains=duc, usedef_chains=udc, consider_annotations=None)
lines_code.append(str(extast.unparse(node)))
code_dependance_annotations = capturex.make_code_external()
if isinstance(node, ast.Assign):
if (node.targets[0].id == extast.unparse(name).rstrip('\n\r').strip()):
lines_code.append(str(extast.unparse(node)))
if isinstance(node, ast.ClassDef):
if (node.name == extast.unparse(name).rstrip('\n\r').strip()):
lines_code.append(str(extast.unparse(node)))
return ((code_dependance_annotations + '\n') + '\n'.join(lines_code)) | def filter_external_code(module: object, names: list):
'Filter the module to keep only the necessary nodes\n needed by functions or class in the parameter names\n '
code_dependance_annotations =
lines_code = []
for node in module.body:
for name in names:
if isinstance(node, ast.FunctionDef):
if (node.name == extast.unparse(name).rstrip('\n\r').strip()):
ancestors = beniget.Ancestors()
ancestors.visit(module)
duc = beniget.DefUseChains()
duc.visit(module)
udc = beniget.UseDefChains(duc)
capturex = CaptureX([node], module, ancestors, defuse_chains=duc, usedef_chains=udc, consider_annotations=None)
lines_code.append(str(extast.unparse(node)))
code_dependance_annotations = capturex.make_code_external()
if isinstance(node, ast.Assign):
if (node.targets[0].id == extast.unparse(name).rstrip('\n\r').strip()):
lines_code.append(str(extast.unparse(node)))
if isinstance(node, ast.ClassDef):
if (node.name == extast.unparse(name).rstrip('\n\r').strip()):
lines_code.append(str(extast.unparse(node)))
return ((code_dependance_annotations + '\n') + '\n'.join(lines_code))<|docstring|>Filter the module to keep only the necessary nodes
needed by functions or class in the parameter names<|endoftext|> |
20205589bd86a464b67ff927d82bcec3bd57f568eb73cf5efecb9adb5bde0965 | def adapt_code_dependance(func: str, codes_dependance: str, jitted_dicts: dict):
'\n Adapt code_dependance to the call of a jitted function in a jitted function:\n - Remove the import transonic\n - Remove the jitted function statement (i.e func = jit(func))\n - Add a import statement to the jitted function\n - remove the definition of the jitted function if its on the file, or remove the import statement\n '
special = []
module = extast.parse(codes_dependance)
module_body = module.body.copy()
jitted_functions = []
for node in module_body:
if isinstance(node, ast.ImportFrom):
if (node.module == 'transonic'):
module.body.remove(node)
elif (isinstance(node, ast.Assign) and isinstance(node.value, ast.Call) and (node.value.func.id == 'jit')):
if (node.targets[0].id != node.value.args[0].id):
def_func = extast.unparse(jitted_dicts['functions'][func])
spl = re.split('(\\W+)', def_func)
spl = [(node.value.args[0].id if (x == node.targets[0].id) else x) for x in spl]
st = ''.join((str(e) for e in spl))
jitted_dicts['functions'][func] = extast.parse(st)
special.append(func)
jitted_functions.append(node.value.args[0].id)
else:
jitted_functions.append(node.targets[0].id)
module.body.remove(node)
module.body.insert(0, [extast.parse(((('from ' + node.value.args[0].id) + ' import ') + node.value.args[0].id))])
for node in module_body:
if isinstance(node, ast.FunctionDef):
if (node.name in jitted_functions):
module.body.remove(node)
if isinstance(node, ast.ImportFrom):
for name in node.names:
if (name.name in jitted_functions):
node.names.remove(name)
if (not node.names):
module.body.remove(node)
return (extast.unparse(module), jitted_dicts, special, jitted_functions) | Adapt code_dependance to the call of a jitted function in a jitted function:
- Remove the import transonic
- Remove the jitted function statement (i.e func = jit(func))
- Add a import statement to the jitted function
- remove the definition of the jitted function if its on the file, or remove the import statement | transonic/analyses/util.py | adapt_code_dependance | fluiddyn/transonic | 88 | python | def adapt_code_dependance(func: str, codes_dependance: str, jitted_dicts: dict):
'\n Adapt code_dependance to the call of a jitted function in a jitted function:\n - Remove the import transonic\n - Remove the jitted function statement (i.e func = jit(func))\n - Add a import statement to the jitted function\n - remove the definition of the jitted function if its on the file, or remove the import statement\n '
special = []
module = extast.parse(codes_dependance)
module_body = module.body.copy()
jitted_functions = []
for node in module_body:
if isinstance(node, ast.ImportFrom):
if (node.module == 'transonic'):
module.body.remove(node)
elif (isinstance(node, ast.Assign) and isinstance(node.value, ast.Call) and (node.value.func.id == 'jit')):
if (node.targets[0].id != node.value.args[0].id):
def_func = extast.unparse(jitted_dicts['functions'][func])
spl = re.split('(\\W+)', def_func)
spl = [(node.value.args[0].id if (x == node.targets[0].id) else x) for x in spl]
st = .join((str(e) for e in spl))
jitted_dicts['functions'][func] = extast.parse(st)
special.append(func)
jitted_functions.append(node.value.args[0].id)
else:
jitted_functions.append(node.targets[0].id)
module.body.remove(node)
module.body.insert(0, [extast.parse(((('from ' + node.value.args[0].id) + ' import ') + node.value.args[0].id))])
for node in module_body:
if isinstance(node, ast.FunctionDef):
if (node.name in jitted_functions):
module.body.remove(node)
if isinstance(node, ast.ImportFrom):
for name in node.names:
if (name.name in jitted_functions):
node.names.remove(name)
if (not node.names):
module.body.remove(node)
return (extast.unparse(module), jitted_dicts, special, jitted_functions) | def adapt_code_dependance(func: str, codes_dependance: str, jitted_dicts: dict):
'\n Adapt code_dependance to the call of a jitted function in a jitted function:\n - Remove the import transonic\n - Remove the jitted function statement (i.e func = jit(func))\n - Add a import statement to the jitted function\n - remove the definition of the jitted function if its on the file, or remove the import statement\n '
special = []
module = extast.parse(codes_dependance)
module_body = module.body.copy()
jitted_functions = []
for node in module_body:
if isinstance(node, ast.ImportFrom):
if (node.module == 'transonic'):
module.body.remove(node)
elif (isinstance(node, ast.Assign) and isinstance(node.value, ast.Call) and (node.value.func.id == 'jit')):
if (node.targets[0].id != node.value.args[0].id):
def_func = extast.unparse(jitted_dicts['functions'][func])
spl = re.split('(\\W+)', def_func)
spl = [(node.value.args[0].id if (x == node.targets[0].id) else x) for x in spl]
st = .join((str(e) for e in spl))
jitted_dicts['functions'][func] = extast.parse(st)
special.append(func)
jitted_functions.append(node.value.args[0].id)
else:
jitted_functions.append(node.targets[0].id)
module.body.remove(node)
module.body.insert(0, [extast.parse(((('from ' + node.value.args[0].id) + ' import ') + node.value.args[0].id))])
for node in module_body:
if isinstance(node, ast.FunctionDef):
if (node.name in jitted_functions):
module.body.remove(node)
if isinstance(node, ast.ImportFrom):
for name in node.names:
if (name.name in jitted_functions):
node.names.remove(name)
if (not node.names):
module.body.remove(node)
return (extast.unparse(module), jitted_dicts, special, jitted_functions)<|docstring|>Adapt code_dependance to the call of a jitted function in a jitted function:
- Remove the import transonic
- Remove the jitted function statement (i.e func = jit(func))
- Add a import statement to the jitted function
- remove the definition of the jitted function if its on the file, or remove the import statement<|endoftext|> |
314deba27795d64e5c2b587b150df5c0e94d85b0c3b843dd6d501e1335eeefd3 | def get_exterior_code(codes_dependance: dict, pathfile: str, previous_file_name=None, classes: str=None, relative: bool=None, jitted_dicts: dict=None):
'Get all imported functions needed by boosted functions and methods at multiple levels,\n (i.e get functions needed by functions imported by boosted function) and add them into code_ext\n '
special = []
treated = []
for (func, dep) in codes_dependance.items():
if (not dep):
continue
module_ext = extast.parse(dep)
for node in module_ext.body:
if (not isinstance(node, (ast.ImportFrom, ast.Import))):
continue
(file_name, file_path) = find_path(node, pathfile)
if (file_name == 'transonic'):
(codes_dependance[func], jitted_dicts, spe, treat) = adapt_code_dependance(func, codes_dependance[func], jitted_dicts)
special = (special + spe)
treated = (treated + treat)
for (func, dep) in codes_dependance.items():
if (not dep):
continue
module_ext = extast.parse(dep)
for node in module_ext.body:
if (not isinstance(node, (ast.ImportFrom, ast.Import))):
continue
(file_name, file_path) = find_path(node, pathfile)
if (not (file_name and (file_name not in treated))):
continue
new_file_name = f'__ext__{func}__{file_name}'
try:
with open(str(file_path), 'r') as file:
content = file.read()
except:
raise NotImplementedError((file_name + ' can not be found'))
mod = extast.parse(content)
code_ext[classes][new_file_name] = str(filter_external_code(mod, node.names))
codes_dependance[func] = change_import_name(codes_dependance[func], node, func, relative)
if code_ext[classes][new_file_name]:
get_exterior_code({func: code_ext[classes][new_file_name]}, pathfile, new_file_name, classes)
if previous_file_name:
code_ext[classes][previous_file_name] = change_import_name(code_ext[classes][previous_file_name], node, func, relative)
return (codes_dependance, code_ext, jitted_dicts, special) | Get all imported functions needed by boosted functions and methods at multiple levels,
(i.e get functions needed by functions imported by boosted function) and add them into code_ext | transonic/analyses/util.py | get_exterior_code | fluiddyn/transonic | 88 | python | def get_exterior_code(codes_dependance: dict, pathfile: str, previous_file_name=None, classes: str=None, relative: bool=None, jitted_dicts: dict=None):
'Get all imported functions needed by boosted functions and methods at multiple levels,\n (i.e get functions needed by functions imported by boosted function) and add them into code_ext\n '
special = []
treated = []
for (func, dep) in codes_dependance.items():
if (not dep):
continue
module_ext = extast.parse(dep)
for node in module_ext.body:
if (not isinstance(node, (ast.ImportFrom, ast.Import))):
continue
(file_name, file_path) = find_path(node, pathfile)
if (file_name == 'transonic'):
(codes_dependance[func], jitted_dicts, spe, treat) = adapt_code_dependance(func, codes_dependance[func], jitted_dicts)
special = (special + spe)
treated = (treated + treat)
for (func, dep) in codes_dependance.items():
if (not dep):
continue
module_ext = extast.parse(dep)
for node in module_ext.body:
if (not isinstance(node, (ast.ImportFrom, ast.Import))):
continue
(file_name, file_path) = find_path(node, pathfile)
if (not (file_name and (file_name not in treated))):
continue
new_file_name = f'__ext__{func}__{file_name}'
try:
with open(str(file_path), 'r') as file:
content = file.read()
except:
raise NotImplementedError((file_name + ' can not be found'))
mod = extast.parse(content)
code_ext[classes][new_file_name] = str(filter_external_code(mod, node.names))
codes_dependance[func] = change_import_name(codes_dependance[func], node, func, relative)
if code_ext[classes][new_file_name]:
get_exterior_code({func: code_ext[classes][new_file_name]}, pathfile, new_file_name, classes)
if previous_file_name:
code_ext[classes][previous_file_name] = change_import_name(code_ext[classes][previous_file_name], node, func, relative)
return (codes_dependance, code_ext, jitted_dicts, special) | def get_exterior_code(codes_dependance: dict, pathfile: str, previous_file_name=None, classes: str=None, relative: bool=None, jitted_dicts: dict=None):
'Get all imported functions needed by boosted functions and methods at multiple levels,\n (i.e get functions needed by functions imported by boosted function) and add them into code_ext\n '
special = []
treated = []
for (func, dep) in codes_dependance.items():
if (not dep):
continue
module_ext = extast.parse(dep)
for node in module_ext.body:
if (not isinstance(node, (ast.ImportFrom, ast.Import))):
continue
(file_name, file_path) = find_path(node, pathfile)
if (file_name == 'transonic'):
(codes_dependance[func], jitted_dicts, spe, treat) = adapt_code_dependance(func, codes_dependance[func], jitted_dicts)
special = (special + spe)
treated = (treated + treat)
for (func, dep) in codes_dependance.items():
if (not dep):
continue
module_ext = extast.parse(dep)
for node in module_ext.body:
if (not isinstance(node, (ast.ImportFrom, ast.Import))):
continue
(file_name, file_path) = find_path(node, pathfile)
if (not (file_name and (file_name not in treated))):
continue
new_file_name = f'__ext__{func}__{file_name}'
try:
with open(str(file_path), 'r') as file:
content = file.read()
except:
raise NotImplementedError((file_name + ' can not be found'))
mod = extast.parse(content)
code_ext[classes][new_file_name] = str(filter_external_code(mod, node.names))
codes_dependance[func] = change_import_name(codes_dependance[func], node, func, relative)
if code_ext[classes][new_file_name]:
get_exterior_code({func: code_ext[classes][new_file_name]}, pathfile, new_file_name, classes)
if previous_file_name:
code_ext[classes][previous_file_name] = change_import_name(code_ext[classes][previous_file_name], node, func, relative)
return (codes_dependance, code_ext, jitted_dicts, special)<|docstring|>Get all imported functions needed by boosted functions and methods at multiple levels,
(i.e get functions needed by functions imported by boosted function) and add them into code_ext<|endoftext|> |
3a6e6af5da3a67c71315931b770b82760077d07d384cf91d3bcec28307537523 | def parse_disease(self, url):
'\n 解析疾病页面\n '
headers = {'user-agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/61.0.3163.79 Safari/537.36 Maxthon/5.2.1.6000'}
html = requests.get(url, headers=headers)
html.encoding = 'gbk'
d = pq(html.text)
name = d('div.spreadhead > div.tit.clearfix > a > h1').eq(0).text()
intro = d('dl.intro > dd').eq(0).text()
if intro.endswith('详细>>'):
intro = intro[:(- 4)]
dds = d('div.info > ul > li')
dict1 = dict()
dict1['url'] = url
dict1['疾病名称'] = name
dict1['简介'] = intro
for i in range(len(dds)):
label = dds.eq(i)('i').eq(0).text()
s = dds.eq(i).text()
if s.endswith('[详细]'):
s = s[:(- 4)].strip()
ss = [i.strip() for i in s.split('：')]
content = dds.eq(i)('a')
if (content and (ss[0] in ['典型症状', '临床检查', '并发症', '手术', '常用药品'])):
ll = list()
for ii in range(len(content)):
if content.eq(ii).attr.title:
ll.append(content.eq(ii).attr.title)
dict1[ss[0]] = ll
else:
dict1[ss[0]] = ss[1]
drug = d('.drug > ul >li').eq(0)
if drug:
aa = drug('a')
if aa:
ll = list()
for i in range(len(aa)):
if aa.get(i).attr.title:
ll.append(aa.get(i).attr.title)
dict1[drug('i').text()[:(- 1)]] = ll
return dict1 | 解析疾病页面 | requestProj/39jiankang/health39util.py | parse_disease | mayi140611/crawl | 1 | python | def parse_disease(self, url):
'\n \n '
headers = {'user-agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/61.0.3163.79 Safari/537.36 Maxthon/5.2.1.6000'}
html = requests.get(url, headers=headers)
html.encoding = 'gbk'
d = pq(html.text)
name = d('div.spreadhead > div.tit.clearfix > a > h1').eq(0).text()
intro = d('dl.intro > dd').eq(0).text()
if intro.endswith('详细>>'):
intro = intro[:(- 4)]
dds = d('div.info > ul > li')
dict1 = dict()
dict1['url'] = url
dict1['疾病名称'] = name
dict1['简介'] = intro
for i in range(len(dds)):
label = dds.eq(i)('i').eq(0).text()
s = dds.eq(i).text()
if s.endswith('[详细]'):
s = s[:(- 4)].strip()
ss = [i.strip() for i in s.split('：')]
content = dds.eq(i)('a')
if (content and (ss[0] in ['典型症状', '临床检查', '并发症', '手术', '常用药品'])):
ll = list()
for ii in range(len(content)):
if content.eq(ii).attr.title:
ll.append(content.eq(ii).attr.title)
dict1[ss[0]] = ll
else:
dict1[ss[0]] = ss[1]
drug = d('.drug > ul >li').eq(0)
if drug:
aa = drug('a')
if aa:
ll = list()
for i in range(len(aa)):
if aa.get(i).attr.title:
ll.append(aa.get(i).attr.title)
dict1[drug('i').text()[:(- 1)]] = ll
return dict1 | def parse_disease(self, url):
'\n \n '
headers = {'user-agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/61.0.3163.79 Safari/537.36 Maxthon/5.2.1.6000'}
html = requests.get(url, headers=headers)
html.encoding = 'gbk'
d = pq(html.text)
name = d('div.spreadhead > div.tit.clearfix > a > h1').eq(0).text()
intro = d('dl.intro > dd').eq(0).text()
if intro.endswith('详细>>'):
intro = intro[:(- 4)]
dds = d('div.info > ul > li')
dict1 = dict()
dict1['url'] = url
dict1['疾病名称'] = name
dict1['简介'] = intro
for i in range(len(dds)):
label = dds.eq(i)('i').eq(0).text()
s = dds.eq(i).text()
if s.endswith('[详细]'):
s = s[:(- 4)].strip()
ss = [i.strip() for i in s.split('：')]
content = dds.eq(i)('a')
if (content and (ss[0] in ['典型症状', '临床检查', '并发症', '手术', '常用药品'])):
ll = list()
for ii in range(len(content)):
if content.eq(ii).attr.title:
ll.append(content.eq(ii).attr.title)
dict1[ss[0]] = ll
else:
dict1[ss[0]] = ss[1]
drug = d('.drug > ul >li').eq(0)
if drug:
aa = drug('a')
if aa:
ll = list()
for i in range(len(aa)):
if aa.get(i).attr.title:
ll.append(aa.get(i).attr.title)
dict1[drug('i').text()[:(- 1)]] = ll
return dict1<|docstring|>解析疾病页面<|endoftext|> |
ed1bfe8f3ef738ec370d9b45ef64a125b911757440808681c3a6bfbedb60cf85 | def setUp(self):
'Set up the test case.'
self.regex = SeqparseRegexMixin() | Set up the test case. | seqparse/test/test_regex.py | setUp | hoafaloaf/seqparse | 1 | python | def setUp(self):
self.regex = SeqparseRegexMixin() | def setUp(self):
self.regex = SeqparseRegexMixin()<|docstring|>Set up the test case.<|endoftext|> |
55813b4e469bd84381ebca9b95a1b014ac9df4691b09a6bce9298703c35681bb | def test_bits_match(self):
'SeqparseRegexMixin: Test the bits_match method.'
good_chunks = [('0001', dict(first='0001', last=None, step=None)), ('001-002', dict(first='001', last='002', step=None)), ('1-2', dict(first='1', last='2', step=None)), ('1-10', dict(first='1', last='10', step=None)), ('0001-0010x2', dict(first='0001', last='0010', step='2')), ('001-101x2', dict(first='001', last='101', step='2')), ('1-11x2', dict(first='1', last='11', step='2'))]
bad_chunks = ['-0001', '0001-', '0001x2', 'x2']
print('\n\n GOOD CHUNKS\n -----------')
for (chunk, result) in good_chunks:
bits_dict = self.regex.bits_match(chunk, as_dict=True)
print(' o "{}" --> {}'.format(chunk, bits_dict))
self.assertEqual(bits_dict, result)
result_tuple = tuple((bits_dict[x] for x in ('first', 'last', 'step')))
self.assertEqual(self.regex.bits_match(chunk), result_tuple)
print('\n BAD SEQUENCES\n -------------')
for chunk in bad_chunks:
print(' o "{}"'.format(chunk))
self.assertIsNone(self.regex.bits_match(chunk))
print('') | SeqparseRegexMixin: Test the bits_match method. | seqparse/test/test_regex.py | test_bits_match | hoafaloaf/seqparse | 1 | python | def test_bits_match(self):
good_chunks = [('0001', dict(first='0001', last=None, step=None)), ('001-002', dict(first='001', last='002', step=None)), ('1-2', dict(first='1', last='2', step=None)), ('1-10', dict(first='1', last='10', step=None)), ('0001-0010x2', dict(first='0001', last='0010', step='2')), ('001-101x2', dict(first='001', last='101', step='2')), ('1-11x2', dict(first='1', last='11', step='2'))]
bad_chunks = ['-0001', '0001-', '0001x2', 'x2']
print('\n\n GOOD CHUNKS\n -----------')
for (chunk, result) in good_chunks:
bits_dict = self.regex.bits_match(chunk, as_dict=True)
print(' o "{}" --> {}'.format(chunk, bits_dict))
self.assertEqual(bits_dict, result)
result_tuple = tuple((bits_dict[x] for x in ('first', 'last', 'step')))
self.assertEqual(self.regex.bits_match(chunk), result_tuple)
print('\n BAD SEQUENCES\n -------------')
for chunk in bad_chunks:
print(' o "{}"'.format(chunk))
self.assertIsNone(self.regex.bits_match(chunk))
print() | def test_bits_match(self):
good_chunks = [('0001', dict(first='0001', last=None, step=None)), ('001-002', dict(first='001', last='002', step=None)), ('1-2', dict(first='1', last='2', step=None)), ('1-10', dict(first='1', last='10', step=None)), ('0001-0010x2', dict(first='0001', last='0010', step='2')), ('001-101x2', dict(first='001', last='101', step='2')), ('1-11x2', dict(first='1', last='11', step='2'))]
bad_chunks = ['-0001', '0001-', '0001x2', 'x2']
print('\n\n GOOD CHUNKS\n -----------')
for (chunk, result) in good_chunks:
bits_dict = self.regex.bits_match(chunk, as_dict=True)
print(' o "{}" --> {}'.format(chunk, bits_dict))
self.assertEqual(bits_dict, result)
result_tuple = tuple((bits_dict[x] for x in ('first', 'last', 'step')))
self.assertEqual(self.regex.bits_match(chunk), result_tuple)
print('\n BAD SEQUENCES\n -------------')
for chunk in bad_chunks:
print(' o "{}"'.format(chunk))
self.assertIsNone(self.regex.bits_match(chunk))
print()<|docstring|>SeqparseRegexMixin: Test the bits_match method.<|endoftext|> |
52cb261bcd2dea3bb31c7763fcc941ac483f60fe0139f64bfeffc24304622024 | def test_file_name_match(self):
'SeqparseRegexMixin: Test the file_name_match method.'
good_names = [('0001.exr', dict(name=None, frame='0001', ext='exr')), ('kitty.1.jpg', dict(name='kitty', frame='1', ext='jpg')), ('/i/like/cats/kitty.0001.tif'.replace('/', os.sep), dict(name='/i/like/cats/kitty'.replace('/', os.sep), frame='0001', ext='tif'))]
bad_names = ['kitty.0001', '1', '.111', '111.', '.22.tif']
bad_names.extend(self._singletons)
print('\n\n GOOD NAMES\n ----------')
for (file_name, result) in good_names:
bits_dict = self.regex.file_name_match(file_name, as_dict=True)
print(' o "{}" --> {}'.format(file_name, bits_dict))
self.assertEqual(bits_dict, result)
result_tuple = tuple((bits_dict[x] for x in ('name', 'frame', 'ext')))
self.assertEqual(self.regex.file_name_match(file_name), result_tuple)
print('\n BAD SEQUENCES\n -------------')
for file_name in bad_names:
print(' o "{}"'.format(file_name))
self.assertIsNone(self.regex.file_name_match(file_name))
print('') | SeqparseRegexMixin: Test the file_name_match method. | seqparse/test/test_regex.py | test_file_name_match | hoafaloaf/seqparse | 1 | python | def test_file_name_match(self):
good_names = [('0001.exr', dict(name=None, frame='0001', ext='exr')), ('kitty.1.jpg', dict(name='kitty', frame='1', ext='jpg')), ('/i/like/cats/kitty.0001.tif'.replace('/', os.sep), dict(name='/i/like/cats/kitty'.replace('/', os.sep), frame='0001', ext='tif'))]
bad_names = ['kitty.0001', '1', '.111', '111.', '.22.tif']
bad_names.extend(self._singletons)
print('\n\n GOOD NAMES\n ----------')
for (file_name, result) in good_names:
bits_dict = self.regex.file_name_match(file_name, as_dict=True)
print(' o "{}" --> {}'.format(file_name, bits_dict))
self.assertEqual(bits_dict, result)
result_tuple = tuple((bits_dict[x] for x in ('name', 'frame', 'ext')))
self.assertEqual(self.regex.file_name_match(file_name), result_tuple)
print('\n BAD SEQUENCES\n -------------')
for file_name in bad_names:
print(' o "{}"'.format(file_name))
self.assertIsNone(self.regex.file_name_match(file_name))
print() | def test_file_name_match(self):
good_names = [('0001.exr', dict(name=None, frame='0001', ext='exr')), ('kitty.1.jpg', dict(name='kitty', frame='1', ext='jpg')), ('/i/like/cats/kitty.0001.tif'.replace('/', os.sep), dict(name='/i/like/cats/kitty'.replace('/', os.sep), frame='0001', ext='tif'))]
bad_names = ['kitty.0001', '1', '.111', '111.', '.22.tif']
bad_names.extend(self._singletons)
print('\n\n GOOD NAMES\n ----------')
for (file_name, result) in good_names:
bits_dict = self.regex.file_name_match(file_name, as_dict=True)
print(' o "{}" --> {}'.format(file_name, bits_dict))
self.assertEqual(bits_dict, result)
result_tuple = tuple((bits_dict[x] for x in ('name', 'frame', 'ext')))
self.assertEqual(self.regex.file_name_match(file_name), result_tuple)
print('\n BAD SEQUENCES\n -------------')
for file_name in bad_names:
print(' o "{}"'.format(file_name))
self.assertIsNone(self.regex.file_name_match(file_name))
print()<|docstring|>SeqparseRegexMixin: Test the file_name_match method.<|endoftext|> |
cbd14c1e68371be2e18ef10e16ff540a808e6727959604e7a86d5614ed0246d9 | def test_file_seq_match(self):
'SeqparseRegexMixin: Test the file_seq_match method.'
good_names = [('0001-0011.exr', dict(name=None, frames='0001-0011', ext='exr')), ('kitty.1,3,9.jpg', dict(name='kitty', frames='1,3,9', ext='jpg')), ('/i/like/cats/kitty.11,22-33.tif'.replace('/', os.sep), dict(name='/i/like/cats/kitty'.replace('/', os.sep), frames='11,22-33', ext='tif'))]
bad_names = ['kitty.0001-0011', '1,3,9', '.111', '111.', '.22.tif']
bad_names.extend(self._singletons)
print('\n\n GOOD NAMES\n ----------')
for (frame_seq, result) in good_names:
bits_dict = self.regex.file_seq_match(frame_seq, as_dict=True)
print(' o "{}" --> {}'.format(frame_seq, bits_dict))
self.assertEqual(bits_dict, result)
result_tuple = tuple((bits_dict[x] for x in ('name', 'frames', 'ext')))
self.assertEqual(self.regex.file_seq_match(frame_seq), result_tuple)
print('\n BAD SEQUENCES\n -------------')
for frame_seq in bad_names:
print(' o "{}"'.format(frame_seq))
bits_dict = self.regex.bits_match(frame_seq, as_dict=True)
self.assertIsNone(self.regex.file_seq_match(frame_seq))
print('') | SeqparseRegexMixin: Test the file_seq_match method. | seqparse/test/test_regex.py | test_file_seq_match | hoafaloaf/seqparse | 1 | python | def test_file_seq_match(self):
good_names = [('0001-0011.exr', dict(name=None, frames='0001-0011', ext='exr')), ('kitty.1,3,9.jpg', dict(name='kitty', frames='1,3,9', ext='jpg')), ('/i/like/cats/kitty.11,22-33.tif'.replace('/', os.sep), dict(name='/i/like/cats/kitty'.replace('/', os.sep), frames='11,22-33', ext='tif'))]
bad_names = ['kitty.0001-0011', '1,3,9', '.111', '111.', '.22.tif']
bad_names.extend(self._singletons)
print('\n\n GOOD NAMES\n ----------')
for (frame_seq, result) in good_names:
bits_dict = self.regex.file_seq_match(frame_seq, as_dict=True)
print(' o "{}" --> {}'.format(frame_seq, bits_dict))
self.assertEqual(bits_dict, result)
result_tuple = tuple((bits_dict[x] for x in ('name', 'frames', 'ext')))
self.assertEqual(self.regex.file_seq_match(frame_seq), result_tuple)
print('\n BAD SEQUENCES\n -------------')
for frame_seq in bad_names:
print(' o "{}"'.format(frame_seq))
bits_dict = self.regex.bits_match(frame_seq, as_dict=True)
self.assertIsNone(self.regex.file_seq_match(frame_seq))
print() | def test_file_seq_match(self):
good_names = [('0001-0011.exr', dict(name=None, frames='0001-0011', ext='exr')), ('kitty.1,3,9.jpg', dict(name='kitty', frames='1,3,9', ext='jpg')), ('/i/like/cats/kitty.11,22-33.tif'.replace('/', os.sep), dict(name='/i/like/cats/kitty'.replace('/', os.sep), frames='11,22-33', ext='tif'))]
bad_names = ['kitty.0001-0011', '1,3,9', '.111', '111.', '.22.tif']
bad_names.extend(self._singletons)
print('\n\n GOOD NAMES\n ----------')
for (frame_seq, result) in good_names:
bits_dict = self.regex.file_seq_match(frame_seq, as_dict=True)
print(' o "{}" --> {}'.format(frame_seq, bits_dict))
self.assertEqual(bits_dict, result)
result_tuple = tuple((bits_dict[x] for x in ('name', 'frames', 'ext')))
self.assertEqual(self.regex.file_seq_match(frame_seq), result_tuple)
print('\n BAD SEQUENCES\n -------------')
for frame_seq in bad_names:
print(' o "{}"'.format(frame_seq))
bits_dict = self.regex.bits_match(frame_seq, as_dict=True)
self.assertIsNone(self.regex.file_seq_match(frame_seq))
print()<|docstring|>SeqparseRegexMixin: Test the file_seq_match method.<|endoftext|> |
0bb9d55df05e8f059f1a4af69a3d0a65636da0e907623dd17c3b21b64782f0d6 | def test_is_frame_sequence(self):
'SeqparseRegexMixin: Test the is_file_sequence method.'
good_frame_seqs = ['0001', ',0001', '0001,', '0001-0001', '0001-0001x0', '0001-0003x3', '0001,0003', '0001,,0003', '0001-0010', '0001-0010x0', '0001-0011x2', '0001-0012x2', '0001-0005,0007-0010', '0001-0005x2,0007-0010', '0001-0005,0007-0011x2', '0001-0005,0006,0008-0012x2', '0001,0003-0007,0009-0015x2']
bad_frame_seqs = ['-0001', '0001-', '0001x2', 'x2', '0001,0003x2', '0001-0005x', 'x', ',', ',,', '']
print('\n\n GOOD SEQUENCES\n --------------')
for frame_seq in good_frame_seqs:
print(' o "{}"'.format(frame_seq))
self.assertTrue(self.regex.is_frame_sequence(frame_seq))
print('\n BAD SEQUENCES\n -------------')
for frame_seq in bad_frame_seqs:
print(' o "{}"'.format(frame_seq))
self.assertFalse(self.regex.is_frame_sequence(frame_seq))
print('') | SeqparseRegexMixin: Test the is_file_sequence method. | seqparse/test/test_regex.py | test_is_frame_sequence | hoafaloaf/seqparse | 1 | python | def test_is_frame_sequence(self):
good_frame_seqs = ['0001', ',0001', '0001,', '0001-0001', '0001-0001x0', '0001-0003x3', '0001,0003', '0001,,0003', '0001-0010', '0001-0010x0', '0001-0011x2', '0001-0012x2', '0001-0005,0007-0010', '0001-0005x2,0007-0010', '0001-0005,0007-0011x2', '0001-0005,0006,0008-0012x2', '0001,0003-0007,0009-0015x2']
bad_frame_seqs = ['-0001', '0001-', '0001x2', 'x2', '0001,0003x2', '0001-0005x', 'x', ',', ',,', ]
print('\n\n GOOD SEQUENCES\n --------------')
for frame_seq in good_frame_seqs:
print(' o "{}"'.format(frame_seq))
self.assertTrue(self.regex.is_frame_sequence(frame_seq))
print('\n BAD SEQUENCES\n -------------')
for frame_seq in bad_frame_seqs:
print(' o "{}"'.format(frame_seq))
self.assertFalse(self.regex.is_frame_sequence(frame_seq))
print() | def test_is_frame_sequence(self):
good_frame_seqs = ['0001', ',0001', '0001,', '0001-0001', '0001-0001x0', '0001-0003x3', '0001,0003', '0001,,0003', '0001-0010', '0001-0010x0', '0001-0011x2', '0001-0012x2', '0001-0005,0007-0010', '0001-0005x2,0007-0010', '0001-0005,0007-0011x2', '0001-0005,0006,0008-0012x2', '0001,0003-0007,0009-0015x2']
bad_frame_seqs = ['-0001', '0001-', '0001x2', 'x2', '0001,0003x2', '0001-0005x', 'x', ',', ',,', ]
print('\n\n GOOD SEQUENCES\n --------------')
for frame_seq in good_frame_seqs:
print(' o "{}"'.format(frame_seq))
self.assertTrue(self.regex.is_frame_sequence(frame_seq))
print('\n BAD SEQUENCES\n -------------')
for frame_seq in bad_frame_seqs:
print(' o "{}"'.format(frame_seq))
self.assertFalse(self.regex.is_frame_sequence(frame_seq))
print()<|docstring|>SeqparseRegexMixin: Test the is_file_sequence method.<|endoftext|> |
74869559f9303564fe353192a596564375520e2998d4672008037f8d81cec693 | def kats_Prophet_iskater(y: [[float]], k: int, a: List=None, t: List=None, e=None, deseasonalize=False):
"\n Calls Kats' Prophet forecasting model, but ignores t if supplied.\n "
if a:
assert (len(a) == (len(y) + k))
if np.isscalar(y[0]):
y0s = [yt for yt in y]
else:
y0s = [yt[0] for yt in y]
idx = pd.date_range(end='01/01/2000', periods=len(y0s), freq='H')
df = pd.DataFrame(y0s, index=idx).rename(columns={0: 'y'}).reset_index()
df.columns = ['time', 'value']
train_data = TimeSeriesData(df.head(df.shape[0]))
params = ProphetParams(seasonality_mode='multiplicative')
m = ProphetModel(train_data, params)
m.fit()
fcst = m.predict(steps=k, freq='H')
x = list(fcst.fcst.values)
x_std = ([1] * k)
return (x, x_std) | Calls Kats' Prophet forecasting model, but ignores t if supplied. | timemachines/skaters/kts/ktswrappers.py | kats_Prophet_iskater | iklasky/timemachines | 0 | python | def kats_Prophet_iskater(y: [[float]], k: int, a: List=None, t: List=None, e=None, deseasonalize=False):
"\n \n "
if a:
assert (len(a) == (len(y) + k))
if np.isscalar(y[0]):
y0s = [yt for yt in y]
else:
y0s = [yt[0] for yt in y]
idx = pd.date_range(end='01/01/2000', periods=len(y0s), freq='H')
df = pd.DataFrame(y0s, index=idx).rename(columns={0: 'y'}).reset_index()
df.columns = ['time', 'value']
train_data = TimeSeriesData(df.head(df.shape[0]))
params = ProphetParams(seasonality_mode='multiplicative')
m = ProphetModel(train_data, params)
m.fit()
fcst = m.predict(steps=k, freq='H')
x = list(fcst.fcst.values)
x_std = ([1] * k)
return (x, x_std) | def kats_Prophet_iskater(y: [[float]], k: int, a: List=None, t: List=None, e=None, deseasonalize=False):
"\n \n "
if a:
assert (len(a) == (len(y) + k))
if np.isscalar(y[0]):
y0s = [yt for yt in y]
else:
y0s = [yt[0] for yt in y]
idx = pd.date_range(end='01/01/2000', periods=len(y0s), freq='H')
df = pd.DataFrame(y0s, index=idx).rename(columns={0: 'y'}).reset_index()
df.columns = ['time', 'value']
train_data = TimeSeriesData(df.head(df.shape[0]))
params = ProphetParams(seasonality_mode='multiplicative')
m = ProphetModel(train_data, params)
m.fit()
fcst = m.predict(steps=k, freq='H')
x = list(fcst.fcst.values)
x_std = ([1] * k)
return (x, x_std)<|docstring|>Calls Kats' Prophet forecasting model, but ignores t if supplied.<|endoftext|> |
379ee867ee8eb63234e1af534515d34fd67a9708119c95bfef23b268aa8c3593 | def kats_HoltWinters_iskater(y: [[float]], k: int, a: List=None, t: List=None, e=None, deseasonalize=False):
"\n Calls Kats' Holt-Winters forecasting model, but ignores t if supplied.\n "
if a:
assert (len(a) == (len(y) + k))
if np.isscalar(y[0]):
y0s = [yt for yt in y]
else:
y0s = [yt[0] for yt in y]
idx = pd.date_range(end='01/01/2000', periods=len(y0s), freq='H')
df = pd.DataFrame(y0s, index=idx).rename(columns={0: 'y'}).reset_index()
df.columns = ['time', 'value']
train_data = TimeSeriesData(df.head(df.shape[0]))
params = HoltWintersParams(trend='add')
m = HoltWintersModel(data=train_data, params=params)
m.fit()
fcst = m.predict(steps=k, alpha=0.5)
x = list(fcst.fcst.values)
x_std = ([1] * k)
return (x, x_std) | Calls Kats' Holt-Winters forecasting model, but ignores t if supplied. | timemachines/skaters/kts/ktswrappers.py | kats_HoltWinters_iskater | iklasky/timemachines | 0 | python | def kats_HoltWinters_iskater(y: [[float]], k: int, a: List=None, t: List=None, e=None, deseasonalize=False):
"\n \n "
if a:
assert (len(a) == (len(y) + k))
if np.isscalar(y[0]):
y0s = [yt for yt in y]
else:
y0s = [yt[0] for yt in y]
idx = pd.date_range(end='01/01/2000', periods=len(y0s), freq='H')
df = pd.DataFrame(y0s, index=idx).rename(columns={0: 'y'}).reset_index()
df.columns = ['time', 'value']
train_data = TimeSeriesData(df.head(df.shape[0]))
params = HoltWintersParams(trend='add')
m = HoltWintersModel(data=train_data, params=params)
m.fit()
fcst = m.predict(steps=k, alpha=0.5)
x = list(fcst.fcst.values)
x_std = ([1] * k)
return (x, x_std) | def kats_HoltWinters_iskater(y: [[float]], k: int, a: List=None, t: List=None, e=None, deseasonalize=False):
"\n \n "
if a:
assert (len(a) == (len(y) + k))
if np.isscalar(y[0]):
y0s = [yt for yt in y]
else:
y0s = [yt[0] for yt in y]
idx = pd.date_range(end='01/01/2000', periods=len(y0s), freq='H')
df = pd.DataFrame(y0s, index=idx).rename(columns={0: 'y'}).reset_index()
df.columns = ['time', 'value']
train_data = TimeSeriesData(df.head(df.shape[0]))
params = HoltWintersParams(trend='add')
m = HoltWintersModel(data=train_data, params=params)
m.fit()
fcst = m.predict(steps=k, alpha=0.5)
x = list(fcst.fcst.values)
x_std = ([1] * k)
return (x, x_std)<|docstring|>Calls Kats' Holt-Winters forecasting model, but ignores t if supplied.<|endoftext|> |
d0a6d7ecf8ac658d49e509c860039ff3559ef56ab626de5a97c0e6c812c53f9b | def kats_quadratic_iskater(y: [[float]], k: int, a: List=None, t: List=None, e=None, deseasonalize=False):
"\n Calls Kats' quadratic regressions forecasting model, but ignores t if supplied.\n "
if a:
assert (len(a) == (len(y) + k))
if np.isscalar(y[0]):
y0s = [yt for yt in y]
else:
y0s = [yt[0] for yt in y]
idx = pd.date_range(end='01/01/2000', periods=len(y0s), freq='H')
df = pd.DataFrame(y0s, index=idx).rename(columns={0: 'y'}).reset_index()
df.columns = ['time', 'value']
train_data = TimeSeriesData(df.head(df.shape[0]))
params = QuadraticModelParams()
m = QuadraticModel(train_data, params)
m.fit()
fcst = m.predict(steps=k)
x = list(fcst.fcst.values)
x_std = ([1] * k)
return (x, x_std) | Calls Kats' quadratic regressions forecasting model, but ignores t if supplied. | timemachines/skaters/kts/ktswrappers.py | kats_quadratic_iskater | iklasky/timemachines | 0 | python | def kats_quadratic_iskater(y: [[float]], k: int, a: List=None, t: List=None, e=None, deseasonalize=False):
"\n \n "
if a:
assert (len(a) == (len(y) + k))
if np.isscalar(y[0]):
y0s = [yt for yt in y]
else:
y0s = [yt[0] for yt in y]
idx = pd.date_range(end='01/01/2000', periods=len(y0s), freq='H')
df = pd.DataFrame(y0s, index=idx).rename(columns={0: 'y'}).reset_index()
df.columns = ['time', 'value']
train_data = TimeSeriesData(df.head(df.shape[0]))
params = QuadraticModelParams()
m = QuadraticModel(train_data, params)
m.fit()
fcst = m.predict(steps=k)
x = list(fcst.fcst.values)
x_std = ([1] * k)
return (x, x_std) | def kats_quadratic_iskater(y: [[float]], k: int, a: List=None, t: List=None, e=None, deseasonalize=False):
"\n \n "
if a:
assert (len(a) == (len(y) + k))
if np.isscalar(y[0]):
y0s = [yt for yt in y]
else:
y0s = [yt[0] for yt in y]
idx = pd.date_range(end='01/01/2000', periods=len(y0s), freq='H')
df = pd.DataFrame(y0s, index=idx).rename(columns={0: 'y'}).reset_index()
df.columns = ['time', 'value']
train_data = TimeSeriesData(df.head(df.shape[0]))
params = QuadraticModelParams()
m = QuadraticModel(train_data, params)
m.fit()
fcst = m.predict(steps=k)
x = list(fcst.fcst.values)
x_std = ([1] * k)
return (x, x_std)<|docstring|>Calls Kats' quadratic regressions forecasting model, but ignores t if supplied.<|endoftext|> |
d2ea532b59d2a062dbea15f60509e3ab46a0467a3342671422055d8ba144dafb | def test_post(self):
'Testing for what the user posts to see if it meets the standards'
response = self.client.post('/api/v1/parcels', data=json.dumps(self.data), content_type='application/json')
assert (response.status_code == 201) | Testing for what the user posts to see if it meets the standards | app/Tests/test_sendit.py | test_post | kiruidavid/Sendit254 | 0 | python | def test_post(self):
response = self.client.post('/api/v1/parcels', data=json.dumps(self.data), content_type='application/json')
assert (response.status_code == 201) | def test_post(self):
response = self.client.post('/api/v1/parcels', data=json.dumps(self.data), content_type='application/json')
assert (response.status_code == 201)<|docstring|>Testing for what the user posts to see if it meets the standards<|endoftext|> |
7385098b46229999448f40104a2f75a4dbd7c53a99141b0427370abf4964b2d5 | def test_blank_user_id(self):
'Testing for if the wrong data if the validations work'
response = self.client.post('/api/v1/parcels', data=json.dumps(self.wrong_data), content_type='application/json')
assert (response.status_code == 400) | Testing for if the wrong data if the validations work | app/Tests/test_sendit.py | test_blank_user_id | kiruidavid/Sendit254 | 0 | python | def test_blank_user_id(self):
response = self.client.post('/api/v1/parcels', data=json.dumps(self.wrong_data), content_type='application/json')
assert (response.status_code == 400) | def test_blank_user_id(self):
response = self.client.post('/api/v1/parcels', data=json.dumps(self.wrong_data), content_type='application/json')
assert (response.status_code == 400)<|docstring|>Testing for if the wrong data if the validations work<|endoftext|> |
fa1997d44aa86cf54e25e8d9fb85a3a075d3ad6cb1f458e76ea3d5136e575d35 | def test_get(self):
'Testing for the get methods'
response = self.client.get('/api/v1/parcels')
assert (response.status_code == 200) | Testing for the get methods | app/Tests/test_sendit.py | test_get | kiruidavid/Sendit254 | 0 | python | def test_get(self):
response = self.client.get('/api/v1/parcels')
assert (response.status_code == 200) | def test_get(self):
response = self.client.get('/api/v1/parcels')
assert (response.status_code == 200)<|docstring|>Testing for the get methods<|endoftext|> |
ac2576f0ee00033906fa0be48fbede7951d323afb531e1aab2f5416a322d73b2 | def test_getparcel(self):
'Testing if getting a single delivery url works with the right delivery_id'
response = self.client.get('/api/v1/parcels/1')
assert (response.status_code == 200) | Testing if getting a single delivery url works with the right delivery_id | app/Tests/test_sendit.py | test_getparcel | kiruidavid/Sendit254 | 0 | python | def test_getparcel(self):
response = self.client.get('/api/v1/parcels/1')
assert (response.status_code == 200) | def test_getparcel(self):
response = self.client.get('/api/v1/parcels/1')
assert (response.status_code == 200)<|docstring|>Testing if getting a single delivery url works with the right delivery_id<|endoftext|> |
4523725a0df163d6fff3f8d60dc7911ecbcbb6b18e7093f005e414f87731593e | def test_wrong_url(self):
'Testing if tusing a string instead of an int and if the error response works'
response = self.client.get('/api/v1/parcels/z')
assert (response.status_code == 404) | Testing if tusing a string instead of an int and if the error response works | app/Tests/test_sendit.py | test_wrong_url | kiruidavid/Sendit254 | 0 | python | def test_wrong_url(self):
response = self.client.get('/api/v1/parcels/z')
assert (response.status_code == 404) | def test_wrong_url(self):
response = self.client.get('/api/v1/parcels/z')
assert (response.status_code == 404)<|docstring|>Testing if tusing a string instead of an int and if the error response works<|endoftext|> |
c9bf86bd66de1a693750ec45dd1a04c3b475523697bee33eff893a1454aca2a3 | def test_get_excess(self):
'Testing for getting an excess delivery_id and if the error response works'
response = self.client.get('/api/v1/parcels/3')
assert (response.status_code == 400) | Testing for getting an excess delivery_id and if the error response works | app/Tests/test_sendit.py | test_get_excess | kiruidavid/Sendit254 | 0 | python | def test_get_excess(self):
response = self.client.get('/api/v1/parcels/3')
assert (response.status_code == 400) | def test_get_excess(self):
response = self.client.get('/api/v1/parcels/3')
assert (response.status_code == 400)<|docstring|>Testing for getting an excess delivery_id and if the error response works<|endoftext|> |
ccc5775bd4a1fc3b1479be2d094d8b70f2e42cf24be01208c623e3266e962ca7 | def test_get_user(self):
'Testing if geting parcel using the delivery_id works'
response = self.client.get('/api/v1/users/5/parcels')
assert (response.status_code == 200) | Testing if geting parcel using the delivery_id works | app/Tests/test_sendit.py | test_get_user | kiruidavid/Sendit254 | 0 | python | def test_get_user(self):
response = self.client.get('/api/v1/users/5/parcels')
assert (response.status_code == 200) | def test_get_user(self):
response = self.client.get('/api/v1/users/5/parcels')
assert (response.status_code == 200)<|docstring|>Testing if geting parcel using the delivery_id works<|endoftext|> |
937bcaffb87312e634632019c6a327eea225eafeda6442a3d625fccf394d0101 | def test_url_entry(self):
'Testing if using the wrong url works and it returns the expected error response'
response = self.client.get('/api/v1/users/e/parcels')
assert (response.status_code == 404) | Testing if using the wrong url works and it returns the expected error response | app/Tests/test_sendit.py | test_url_entry | kiruidavid/Sendit254 | 0 | python | def test_url_entry(self):
response = self.client.get('/api/v1/users/e/parcels')
assert (response.status_code == 404) | def test_url_entry(self):
response = self.client.get('/api/v1/users/e/parcels')
assert (response.status_code == 404)<|docstring|>Testing if using the wrong url works and it returns the expected error response<|endoftext|> |
39976fc571213c8d264792dcab94b9bbf86526165917022ee9f365cfa66a8642 | def test_wrong_user(self):
'Testing if using the wrong user_id works and the expected error response'
response = self.client.get('/api/v1/users/3/parcels')
assert (response.status_code == 400) | Testing if using the wrong user_id works and the expected error response | app/Tests/test_sendit.py | test_wrong_user | kiruidavid/Sendit254 | 0 | python | def test_wrong_user(self):
response = self.client.get('/api/v1/users/3/parcels')
assert (response.status_code == 400) | def test_wrong_user(self):
response = self.client.get('/api/v1/users/3/parcels')
assert (response.status_code == 400)<|docstring|>Testing if using the wrong user_id works and the expected error response<|endoftext|> |
ae1e04f47455a2f26ca55eab1c8cf683e76cb01f7da14d782e35fdc21731869e | def test_cancel(self):
'Testing if using the right url to update the status works'
response = self.client.put('/api/v1/parcels/1/cancel/')
assert (response.status_code == 200) | Testing if using the right url to update the status works | app/Tests/test_sendit.py | test_cancel | kiruidavid/Sendit254 | 0 | python | def test_cancel(self):
response = self.client.put('/api/v1/parcels/1/cancel/')
assert (response.status_code == 200) | def test_cancel(self):
response = self.client.put('/api/v1/parcels/1/cancel/')
assert (response.status_code == 200)<|docstring|>Testing if using the right url to update the status works<|endoftext|> |
09704bbf700045a3c69f9125db787bdc5f3578ad2ba6f2e0e68e007efc6cdf91 | @idxDecorator(as_ind=False)
def _indices_equality_match_on_catalog(catalog: _TBL_TYPE, other: _TBL_TYPE, fields: _FIELDS_TYPE) -> _IDX_TYPE:
'Indices of catalog data field(s) to match against a source catalog.\n\n This function is for discrete-valued data, such as tags.\n Note that this only matches `other` against `catalog`, meaning\n `catalog` can still have values which do not appear in `other`\n For coordinates, see `~indices_xmatch_coords`.\n\n This match is done on all the fields simultaneously, so in terms or\n a 2D array, two rows are considered a match only if all the values\n in the columns `fields` match.\n\n Parameters\n ----------\n catalog : recarray\n the source catalog against which the `other` catalog is matched.\n other : recarray\n match this against `catalog`\n fields : list\n List of fields on which to match.\n ex, ["color", "location"] where both `catalog` and `other` have\n those columns, hopefully with some matching values.\n\n Returns\n -------\n idx : ndarray\n indices into `other` such that only has values in `fields` that\n are in `catalog`.\n\n Notes\n -----\n .. todo::\n\n try more axes tricks to avoid loops.\n\n '
uns: T.Tuple[np.array]
uns = (np.unique(np.array(catalog[n])) for n in fields)
idxs = ((other[n] == un[(:, None)]) for (n, un) in zip(fields, uns))
idx: _IDX_TYPE
idx = np.sum(functools.reduce(np.logical_and, idxs), axis=0, dtype=bool)
return idx | Indices of catalog data field(s) to match against a source catalog.
This function is for discrete-valued data, such as tags.
Note that this only matches `other` against `catalog`, meaning
`catalog` can still have values which do not appear in `other`
For coordinates, see `~indices_xmatch_coords`.
This match is done on all the fields simultaneously, so in terms or
a 2D array, two rows are considered a match only if all the values
in the columns `fields` match.
Parameters
----------
catalog : recarray
the source catalog against which the `other` catalog is matched.
other : recarray
match this against `catalog`
fields : list
List of fields on which to match.
ex, ["color", "location"] where both `catalog` and `other` have
those columns, hopefully with some matching values.
Returns
-------
idx : ndarray
indices into `other` such that only has values in `fields` that
are in `catalog`.
Notes
-----
.. todo::
try more axes tricks to avoid loops. | utilipy/data_utils/crossmatch.py | _indices_equality_match_on_catalog | nstarman/utilipy | 2 | python | @idxDecorator(as_ind=False)
def _indices_equality_match_on_catalog(catalog: _TBL_TYPE, other: _TBL_TYPE, fields: _FIELDS_TYPE) -> _IDX_TYPE:
'Indices of catalog data field(s) to match against a source catalog.\n\n This function is for discrete-valued data, such as tags.\n Note that this only matches `other` against `catalog`, meaning\n `catalog` can still have values which do not appear in `other`\n For coordinates, see `~indices_xmatch_coords`.\n\n This match is done on all the fields simultaneously, so in terms or\n a 2D array, two rows are considered a match only if all the values\n in the columns `fields` match.\n\n Parameters\n ----------\n catalog : recarray\n the source catalog against which the `other` catalog is matched.\n other : recarray\n match this against `catalog`\n fields : list\n List of fields on which to match.\n ex, ["color", "location"] where both `catalog` and `other` have\n those columns, hopefully with some matching values.\n\n Returns\n -------\n idx : ndarray\n indices into `other` such that only has values in `fields` that\n are in `catalog`.\n\n Notes\n -----\n .. todo::\n\n try more axes tricks to avoid loops.\n\n '
uns: T.Tuple[np.array]
uns = (np.unique(np.array(catalog[n])) for n in fields)
idxs = ((other[n] == un[(:, None)]) for (n, un) in zip(fields, uns))
idx: _IDX_TYPE
idx = np.sum(functools.reduce(np.logical_and, idxs), axis=0, dtype=bool)
return idx | @idxDecorator(as_ind=False)
def _indices_equality_match_on_catalog(catalog: _TBL_TYPE, other: _TBL_TYPE, fields: _FIELDS_TYPE) -> _IDX_TYPE:
'Indices of catalog data field(s) to match against a source catalog.\n\n This function is for discrete-valued data, such as tags.\n Note that this only matches `other` against `catalog`, meaning\n `catalog` can still have values which do not appear in `other`\n For coordinates, see `~indices_xmatch_coords`.\n\n This match is done on all the fields simultaneously, so in terms or\n a 2D array, two rows are considered a match only if all the values\n in the columns `fields` match.\n\n Parameters\n ----------\n catalog : recarray\n the source catalog against which the `other` catalog is matched.\n other : recarray\n match this against `catalog`\n fields : list\n List of fields on which to match.\n ex, ["color", "location"] where both `catalog` and `other` have\n those columns, hopefully with some matching values.\n\n Returns\n -------\n idx : ndarray\n indices into `other` such that only has values in `fields` that\n are in `catalog`.\n\n Notes\n -----\n .. todo::\n\n try more axes tricks to avoid loops.\n\n '
uns: T.Tuple[np.array]
uns = (np.unique(np.array(catalog[n])) for n in fields)
idxs = ((other[n] == un[(:, None)]) for (n, un) in zip(fields, uns))
idx: _IDX_TYPE
idx = np.sum(functools.reduce(np.logical_and, idxs), axis=0, dtype=bool)
return idx<|docstring|>Indices of catalog data field(s) to match against a source catalog.
This function is for discrete-valued data, such as tags.
Note that this only matches `other` against `catalog`, meaning
`catalog` can still have values which do not appear in `other`
For coordinates, see `~indices_xmatch_coords`.
This match is done on all the fields simultaneously, so in terms or
a 2D array, two rows are considered a match only if all the values
in the columns `fields` match.
Parameters
----------
catalog : recarray
the source catalog against which the `other` catalog is matched.
other : recarray
match this against `catalog`
fields : list
List of fields on which to match.
ex, ["color", "location"] where both `catalog` and `other` have
those columns, hopefully with some matching values.
Returns
-------
idx : ndarray
indices into `other` such that only has values in `fields` that
are in `catalog`.
Notes
-----
.. todo::
try more axes tricks to avoid loops.<|endoftext|> |
0f7dd77547927a9dc3bcd9598abb7a7c5edab1c5f713b9a66c9e600a2d787c67 | def indices_xmatch_fields(catalog: _TBL_TYPE, *others: _TBL_TYPE, fields: _FIELDS_TYPE) -> T.Tuple[(_IDXS_TYPE, _INFO_TYPE)]:
'Indices of xmatch of catalogs\' data field(s) against a source catalog.\n\n This function is for discrete-valued data, such as tags.\n For coordinates, see `~indices_xmatch_coords`.\n\n This match is done on all the fields simultaneously, so in terms or\n a 2D array, two rows are considered a match only if all the values\n in the columns `fields` match.\n\n Parameters\n ----------\n catalog : Table or recarray\n The source catalog against which the `others` catalogs are matched.\n *others : Table or recarray\n match these against `catalog`\n fields : list\n List of fields on which to match.\n ex, ["color", "location"] where both `catalog` and `other` have\n those columns, hopefully with some matching values.\n\n Returns\n -------\n idxs : list of ndarrays\n each element of list is the x-match indices into the ith catalog,\n starting with `catalog`. So the i=0 index list is for `catalog` and\n the i=1 index list is the x-match indices for the first table\n in `others`.\n info : dict\n Useful information. Nothing yet.\n\n Notes\n -----\n .. todo::\n\n try more axes tricks to avoid loops.\n\n '
idxs: _IDXS_TYPE = [_indices_equality_match_on_catalog(catalog, c, fields=fields) for c in others]
catalog_idx: _IDX_TYPE = _indices_equality_match_on_catalog(others[1][idxs[0]], catalog, fields)
idxs.insert(0, catalog_idx)
info: _INFO_TYPE = {}
return (idxs, info) | Indices of xmatch of catalogs' data field(s) against a source catalog.
This function is for discrete-valued data, such as tags.
For coordinates, see `~indices_xmatch_coords`.
This match is done on all the fields simultaneously, so in terms or
a 2D array, two rows are considered a match only if all the values
in the columns `fields` match.
Parameters
----------
catalog : Table or recarray
The source catalog against which the `others` catalogs are matched.
*others : Table or recarray
match these against `catalog`
fields : list
List of fields on which to match.
ex, ["color", "location"] where both `catalog` and `other` have
those columns, hopefully with some matching values.
Returns
-------
idxs : list of ndarrays
each element of list is the x-match indices into the ith catalog,
starting with `catalog`. So the i=0 index list is for `catalog` and
the i=1 index list is the x-match indices for the first table
in `others`.
info : dict
Useful information. Nothing yet.
Notes
-----
.. todo::
try more axes tricks to avoid loops. | utilipy/data_utils/crossmatch.py | indices_xmatch_fields | nstarman/utilipy | 2 | python | def indices_xmatch_fields(catalog: _TBL_TYPE, *others: _TBL_TYPE, fields: _FIELDS_TYPE) -> T.Tuple[(_IDXS_TYPE, _INFO_TYPE)]:
'Indices of xmatch of catalogs\' data field(s) against a source catalog.\n\n This function is for discrete-valued data, such as tags.\n For coordinates, see `~indices_xmatch_coords`.\n\n This match is done on all the fields simultaneously, so in terms or\n a 2D array, two rows are considered a match only if all the values\n in the columns `fields` match.\n\n Parameters\n ----------\n catalog : Table or recarray\n The source catalog against which the `others` catalogs are matched.\n *others : Table or recarray\n match these against `catalog`\n fields : list\n List of fields on which to match.\n ex, ["color", "location"] where both `catalog` and `other` have\n those columns, hopefully with some matching values.\n\n Returns\n -------\n idxs : list of ndarrays\n each element of list is the x-match indices into the ith catalog,\n starting with `catalog`. So the i=0 index list is for `catalog` and\n the i=1 index list is the x-match indices for the first table\n in `others`.\n info : dict\n Useful information. Nothing yet.\n\n Notes\n -----\n .. todo::\n\n try more axes tricks to avoid loops.\n\n '
idxs: _IDXS_TYPE = [_indices_equality_match_on_catalog(catalog, c, fields=fields) for c in others]
catalog_idx: _IDX_TYPE = _indices_equality_match_on_catalog(others[1][idxs[0]], catalog, fields)
idxs.insert(0, catalog_idx)
info: _INFO_TYPE = {}
return (idxs, info) | def indices_xmatch_fields(catalog: _TBL_TYPE, *others: _TBL_TYPE, fields: _FIELDS_TYPE) -> T.Tuple[(_IDXS_TYPE, _INFO_TYPE)]:
'Indices of xmatch of catalogs\' data field(s) against a source catalog.\n\n This function is for discrete-valued data, such as tags.\n For coordinates, see `~indices_xmatch_coords`.\n\n This match is done on all the fields simultaneously, so in terms or\n a 2D array, two rows are considered a match only if all the values\n in the columns `fields` match.\n\n Parameters\n ----------\n catalog : Table or recarray\n The source catalog against which the `others` catalogs are matched.\n *others : Table or recarray\n match these against `catalog`\n fields : list\n List of fields on which to match.\n ex, ["color", "location"] where both `catalog` and `other` have\n those columns, hopefully with some matching values.\n\n Returns\n -------\n idxs : list of ndarrays\n each element of list is the x-match indices into the ith catalog,\n starting with `catalog`. So the i=0 index list is for `catalog` and\n the i=1 index list is the x-match indices for the first table\n in `others`.\n info : dict\n Useful information. Nothing yet.\n\n Notes\n -----\n .. todo::\n\n try more axes tricks to avoid loops.\n\n '
idxs: _IDXS_TYPE = [_indices_equality_match_on_catalog(catalog, c, fields=fields) for c in others]
catalog_idx: _IDX_TYPE = _indices_equality_match_on_catalog(others[1][idxs[0]], catalog, fields)
idxs.insert(0, catalog_idx)
info: _INFO_TYPE = {}
return (idxs, info)<|docstring|>Indices of xmatch of catalogs' data field(s) against a source catalog.
This function is for discrete-valued data, such as tags.
For coordinates, see `~indices_xmatch_coords`.
This match is done on all the fields simultaneously, so in terms or
a 2D array, two rows are considered a match only if all the values
in the columns `fields` match.
Parameters
----------
catalog : Table or recarray
The source catalog against which the `others` catalogs are matched.
*others : Table or recarray
match these against `catalog`
fields : list
List of fields on which to match.
ex, ["color", "location"] where both `catalog` and `other` have
those columns, hopefully with some matching values.
Returns
-------
idxs : list of ndarrays
each element of list is the x-match indices into the ith catalog,
starting with `catalog`. So the i=0 index list is for `catalog` and
the i=1 index list is the x-match indices for the first table
in `others`.
info : dict
Useful information. Nothing yet.
Notes
-----
.. todo::
try more axes tricks to avoid loops.<|endoftext|> |
26778a5a3a4cca82c8af5cd97a67ec5fc00ea1ee6cd3b54ee54cfe15a8867d3a | def xmatch_fields(catalog: _TBL_TYPE, *others: _TBL_TYPE, fields: _FIELDS_TYPE) -> T.Tuple[(T.List[T.Any], _INFO_TYPE)]:
'Cross-match catalogs\' data field(s) against a source catalog.\n\n This function is for discrete-valued data, such as tags.\n For coordinates, see `~indices_xmatch_coords`.\n\n This match is done on all the fields simultaneously, so in terms or\n a 2D array, two rows are considered a match only if all the values\n in the columns `fields` match.\n\n Parameters\n ----------\n catalog : Table or recarray\n The source catalog against which the `others` catalogs are matched.\n fields for which there are no matches are also filtered.\n *others : Table or recarray\n match these against `catalog`\n fields : list\n List of fields on which to match.\n ex, ["color", "location"] where both `catalog` and `other` have\n those columns, hopefully with some matching values.\n\n Returns\n -------\n idxs : list of ndarrays\n each element of list is the x-match indices into the ith catalog,\n starting with `catalog`. So the i=0 index list is for `catalog` and\n the i=1 index list is the x-match indices for the first table\n in `others`,\n\n\n Notes\n -----\n .. todo::\n\n try more axes tricks to avoid loops.\n\n '
if (not isinstance(fields, list)):
raise TypeError('must be a list')
if (len(others) == 0):
raise ValueError('Must have at least one catalog against-which to xmatch.')
for (i, field) in itertools.product(range((len(others) + 1)), fields):
try:
if (i == 0):
catalog[field]
else:
others[i][field]
except Exception as e:
print(f'need to have {field} in catalog {i}')
raise e
idxs: _IDXS_TYPE
info: _INFO_TYPE
(idxs, info) = indices_xmatch_fields(catalog, *others, fields=fields)
cat_matches = ([catalog[idxs[0]]] + [c[idx] for (c, idx) in zip(others, idxs[1:])])
info.update({'idxs': idxs})
return (cat_matches, info) | Cross-match catalogs' data field(s) against a source catalog.
This function is for discrete-valued data, such as tags.
For coordinates, see `~indices_xmatch_coords`.
This match is done on all the fields simultaneously, so in terms or
a 2D array, two rows are considered a match only if all the values
in the columns `fields` match.
Parameters
----------
catalog : Table or recarray
The source catalog against which the `others` catalogs are matched.
fields for which there are no matches are also filtered.
*others : Table or recarray
match these against `catalog`
fields : list
List of fields on which to match.
ex, ["color", "location"] where both `catalog` and `other` have
those columns, hopefully with some matching values.
Returns
-------
idxs : list of ndarrays
each element of list is the x-match indices into the ith catalog,
starting with `catalog`. So the i=0 index list is for `catalog` and
the i=1 index list is the x-match indices for the first table
in `others`,
Notes
-----
.. todo::
try more axes tricks to avoid loops. | utilipy/data_utils/crossmatch.py | xmatch_fields | nstarman/utilipy | 2 | python | def xmatch_fields(catalog: _TBL_TYPE, *others: _TBL_TYPE, fields: _FIELDS_TYPE) -> T.Tuple[(T.List[T.Any], _INFO_TYPE)]:
'Cross-match catalogs\' data field(s) against a source catalog.\n\n This function is for discrete-valued data, such as tags.\n For coordinates, see `~indices_xmatch_coords`.\n\n This match is done on all the fields simultaneously, so in terms or\n a 2D array, two rows are considered a match only if all the values\n in the columns `fields` match.\n\n Parameters\n ----------\n catalog : Table or recarray\n The source catalog against which the `others` catalogs are matched.\n fields for which there are no matches are also filtered.\n *others : Table or recarray\n match these against `catalog`\n fields : list\n List of fields on which to match.\n ex, ["color", "location"] where both `catalog` and `other` have\n those columns, hopefully with some matching values.\n\n Returns\n -------\n idxs : list of ndarrays\n each element of list is the x-match indices into the ith catalog,\n starting with `catalog`. So the i=0 index list is for `catalog` and\n the i=1 index list is the x-match indices for the first table\n in `others`,\n\n\n Notes\n -----\n .. todo::\n\n try more axes tricks to avoid loops.\n\n '
if (not isinstance(fields, list)):
raise TypeError('must be a list')
if (len(others) == 0):
raise ValueError('Must have at least one catalog against-which to xmatch.')
for (i, field) in itertools.product(range((len(others) + 1)), fields):
try:
if (i == 0):
catalog[field]
else:
others[i][field]
except Exception as e:
print(f'need to have {field} in catalog {i}')
raise e
idxs: _IDXS_TYPE
info: _INFO_TYPE
(idxs, info) = indices_xmatch_fields(catalog, *others, fields=fields)
cat_matches = ([catalog[idxs[0]]] + [c[idx] for (c, idx) in zip(others, idxs[1:])])
info.update({'idxs': idxs})
return (cat_matches, info) | def xmatch_fields(catalog: _TBL_TYPE, *others: _TBL_TYPE, fields: _FIELDS_TYPE) -> T.Tuple[(T.List[T.Any], _INFO_TYPE)]:
'Cross-match catalogs\' data field(s) against a source catalog.\n\n This function is for discrete-valued data, such as tags.\n For coordinates, see `~indices_xmatch_coords`.\n\n This match is done on all the fields simultaneously, so in terms or\n a 2D array, two rows are considered a match only if all the values\n in the columns `fields` match.\n\n Parameters\n ----------\n catalog : Table or recarray\n The source catalog against which the `others` catalogs are matched.\n fields for which there are no matches are also filtered.\n *others : Table or recarray\n match these against `catalog`\n fields : list\n List of fields on which to match.\n ex, ["color", "location"] where both `catalog` and `other` have\n those columns, hopefully with some matching values.\n\n Returns\n -------\n idxs : list of ndarrays\n each element of list is the x-match indices into the ith catalog,\n starting with `catalog`. So the i=0 index list is for `catalog` and\n the i=1 index list is the x-match indices for the first table\n in `others`,\n\n\n Notes\n -----\n .. todo::\n\n try more axes tricks to avoid loops.\n\n '
if (not isinstance(fields, list)):
raise TypeError('must be a list')
if (len(others) == 0):
raise ValueError('Must have at least one catalog against-which to xmatch.')
for (i, field) in itertools.product(range((len(others) + 1)), fields):
try:
if (i == 0):
catalog[field]
else:
others[i][field]
except Exception as e:
print(f'need to have {field} in catalog {i}')
raise e
idxs: _IDXS_TYPE
info: _INFO_TYPE
(idxs, info) = indices_xmatch_fields(catalog, *others, fields=fields)
cat_matches = ([catalog[idxs[0]]] + [c[idx] for (c, idx) in zip(others, idxs[1:])])
info.update({'idxs': idxs})
return (cat_matches, info)<|docstring|>Cross-match catalogs' data field(s) against a source catalog.
This function is for discrete-valued data, such as tags.
For coordinates, see `~indices_xmatch_coords`.
This match is done on all the fields simultaneously, so in terms or
a 2D array, two rows are considered a match only if all the values
in the columns `fields` match.
Parameters
----------
catalog : Table or recarray
The source catalog against which the `others` catalogs are matched.
fields for which there are no matches are also filtered.
*others : Table or recarray
match these against `catalog`
fields : list
List of fields on which to match.
ex, ["color", "location"] where both `catalog` and `other` have
those columns, hopefully with some matching values.
Returns
-------
idxs : list of ndarrays
each element of list is the x-match indices into the ith catalog,
starting with `catalog`. So the i=0 index list is for `catalog` and
the i=1 index list is the x-match indices for the first table
in `others`,
Notes
-----
.. todo::
try more axes tricks to avoid loops.<|endoftext|> |
77d709a15a07863031df9fecaeb94ac5b3021ea74b735abd621555b1c491a070 | def xmatch(*catalogs, match_fields: T.Sequence) -> T.Tuple[(T.List[T.Any], _INFO_TYPE)]:
'Cross-match two catalogs.\n\n .. todo::\n\n - find duplicates before matching ?\n - allow more catalogs to be xmatched\n\n Parameters\n ----------\n cat1, cat2: Any\n the two catalogs to crossmatch\n must be convertible to recarray\n match_fields : str, optional\n data tag on which to additionally cross-match, default None.\n this also works for any discrete-valued data column.\n\n References\n ----------\n https://github.com/jobovy/gaia_tools/\n\n '
(cat_matches, info) = xmatch_fields(*catalogs, fields=match_fields)
return (cat_matches, info) | Cross-match two catalogs.
.. todo::
- find duplicates before matching ?
- allow more catalogs to be xmatched
Parameters
----------
cat1, cat2: Any
the two catalogs to crossmatch
must be convertible to recarray
match_fields : str, optional
data tag on which to additionally cross-match, default None.
this also works for any discrete-valued data column.
References
----------
https://github.com/jobovy/gaia_tools/ | utilipy/data_utils/crossmatch.py | xmatch | nstarman/utilipy | 2 | python | def xmatch(*catalogs, match_fields: T.Sequence) -> T.Tuple[(T.List[T.Any], _INFO_TYPE)]:
'Cross-match two catalogs.\n\n .. todo::\n\n - find duplicates before matching ?\n - allow more catalogs to be xmatched\n\n Parameters\n ----------\n cat1, cat2: Any\n the two catalogs to crossmatch\n must be convertible to recarray\n match_fields : str, optional\n data tag on which to additionally cross-match, default None.\n this also works for any discrete-valued data column.\n\n References\n ----------\n https://github.com/jobovy/gaia_tools/\n\n '
(cat_matches, info) = xmatch_fields(*catalogs, fields=match_fields)
return (cat_matches, info) | def xmatch(*catalogs, match_fields: T.Sequence) -> T.Tuple[(T.List[T.Any], _INFO_TYPE)]:
'Cross-match two catalogs.\n\n .. todo::\n\n - find duplicates before matching ?\n - allow more catalogs to be xmatched\n\n Parameters\n ----------\n cat1, cat2: Any\n the two catalogs to crossmatch\n must be convertible to recarray\n match_fields : str, optional\n data tag on which to additionally cross-match, default None.\n this also works for any discrete-valued data column.\n\n References\n ----------\n https://github.com/jobovy/gaia_tools/\n\n '
(cat_matches, info) = xmatch_fields(*catalogs, fields=match_fields)
return (cat_matches, info)<|docstring|>Cross-match two catalogs.
.. todo::
- find duplicates before matching ?
- allow more catalogs to be xmatched
Parameters
----------
cat1, cat2: Any
the two catalogs to crossmatch
must be convertible to recarray
match_fields : str, optional
data tag on which to additionally cross-match, default None.
this also works for any discrete-valued data column.
References
----------
https://github.com/jobovy/gaia_tools/<|endoftext|> |
268b81c1baeaecd52eeeaf6c6f0c4b21d6fdaa9e746bc65c50b863363023bb77 | def non_xmatched(catalog1: T.Sequence, catalog2: T.Sequence, indices1: T.Sequence, indices2: T.Sequence):
'Find non cross-matched catalog components.\n\n Parameters\n ----------\n catalog1, catalog2 : Sequence\n the catalogs\n indices1, indices2 : Sequence\n indices into catalogs for the x-match.\n :func:`~starkman_thesis.utils.data.xmatch.xmatch_indices_coords` output\n or in :func:`~starkman_thesis.utils.data.xmatch.xmatch_coords` info\n\n Returns\n -------\n catalog1_matches, catalog2_matches : catalog input types\n the x-matched catalogs\n info : dict\n Useful information.\n\n - nindices1 : indices into `catalog1` not x-matched.\n - nindices1 : indices into `catalog2` not x-matched.\n\n '
c1idx = np.arange(len(catalog1))
c2idx = np.arange(len(catalog2))
nindices1 = np.where((~ np.in1d(c1idx, indices1)))[0]
nindices2 = np.where((~ np.in1d(c2idx, indices2)))[0]
ninfo = {'nindices1': nindices1, 'nindices2': nindices2}
return ((catalog1[nindices1], catalog2[nindices2]), ninfo) | Find non cross-matched catalog components.
Parameters
----------
catalog1, catalog2 : Sequence
the catalogs
indices1, indices2 : Sequence
indices into catalogs for the x-match.
:func:`~starkman_thesis.utils.data.xmatch.xmatch_indices_coords` output
or in :func:`~starkman_thesis.utils.data.xmatch.xmatch_coords` info
Returns
-------
catalog1_matches, catalog2_matches : catalog input types
the x-matched catalogs
info : dict
Useful information.
- nindices1 : indices into `catalog1` not x-matched.
- nindices1 : indices into `catalog2` not x-matched. | utilipy/data_utils/crossmatch.py | non_xmatched | nstarman/utilipy | 2 | python | def non_xmatched(catalog1: T.Sequence, catalog2: T.Sequence, indices1: T.Sequence, indices2: T.Sequence):
'Find non cross-matched catalog components.\n\n Parameters\n ----------\n catalog1, catalog2 : Sequence\n the catalogs\n indices1, indices2 : Sequence\n indices into catalogs for the x-match.\n :func:`~starkman_thesis.utils.data.xmatch.xmatch_indices_coords` output\n or in :func:`~starkman_thesis.utils.data.xmatch.xmatch_coords` info\n\n Returns\n -------\n catalog1_matches, catalog2_matches : catalog input types\n the x-matched catalogs\n info : dict\n Useful information.\n\n - nindices1 : indices into `catalog1` not x-matched.\n - nindices1 : indices into `catalog2` not x-matched.\n\n '
c1idx = np.arange(len(catalog1))
c2idx = np.arange(len(catalog2))
nindices1 = np.where((~ np.in1d(c1idx, indices1)))[0]
nindices2 = np.where((~ np.in1d(c2idx, indices2)))[0]
ninfo = {'nindices1': nindices1, 'nindices2': nindices2}
return ((catalog1[nindices1], catalog2[nindices2]), ninfo) | def non_xmatched(catalog1: T.Sequence, catalog2: T.Sequence, indices1: T.Sequence, indices2: T.Sequence):
'Find non cross-matched catalog components.\n\n Parameters\n ----------\n catalog1, catalog2 : Sequence\n the catalogs\n indices1, indices2 : Sequence\n indices into catalogs for the x-match.\n :func:`~starkman_thesis.utils.data.xmatch.xmatch_indices_coords` output\n or in :func:`~starkman_thesis.utils.data.xmatch.xmatch_coords` info\n\n Returns\n -------\n catalog1_matches, catalog2_matches : catalog input types\n the x-matched catalogs\n info : dict\n Useful information.\n\n - nindices1 : indices into `catalog1` not x-matched.\n - nindices1 : indices into `catalog2` not x-matched.\n\n '
c1idx = np.arange(len(catalog1))
c2idx = np.arange(len(catalog2))
nindices1 = np.where((~ np.in1d(c1idx, indices1)))[0]
nindices2 = np.where((~ np.in1d(c2idx, indices2)))[0]
ninfo = {'nindices1': nindices1, 'nindices2': nindices2}
return ((catalog1[nindices1], catalog2[nindices2]), ninfo)<|docstring|>Find non cross-matched catalog components.
Parameters
----------
catalog1, catalog2 : Sequence
the catalogs
indices1, indices2 : Sequence
indices into catalogs for the x-match.
:func:`~starkman_thesis.utils.data.xmatch.xmatch_indices_coords` output
or in :func:`~starkman_thesis.utils.data.xmatch.xmatch_coords` info
Returns
-------
catalog1_matches, catalog2_matches : catalog input types
the x-matched catalogs
info : dict
Useful information.
- nindices1 : indices into `catalog1` not x-matched.
- nindices1 : indices into `catalog2` not x-matched.<|endoftext|> |
9fcd250f0a0e6999566a79ba038df81804cb34e46127b0269114933c3d598216 | def air_validate_parser(instance):
'\n @brief Semantic validation of an AIR instance\n @param instance The AIR instance map\n @returns Boolean, True if instance is valid.\n\n The instance is assumed to be a syntactically valid instance.\n This routine checks:\n\n The Parser:\n Each edge connects two declared states\n\n In so doing, the validator generates additional structures\n and binds them to the IR. These inc\n '
pass | @brief Semantic validation of an AIR instance
@param instance The AIR instance map
@returns Boolean, True if instance is valid.
The instance is assumed to be a syntactically valid instance.
This routine checks:
The Parser:
Each edge connects two declared states
In so doing, the validator generates additional structures
and binds them to the IR. These inc | air/air_validate.py | air_validate_parser | dtalayco/air_iri | 0 | python | def air_validate_parser(instance):
'\n @brief Semantic validation of an AIR instance\n @param instance The AIR instance map\n @returns Boolean, True if instance is valid.\n\n The instance is assumed to be a syntactically valid instance.\n This routine checks:\n\n The Parser:\n Each edge connects two declared states\n\n In so doing, the validator generates additional structures\n and binds them to the IR. These inc\n '
pass | def air_validate_parser(instance):
'\n @brief Semantic validation of an AIR instance\n @param instance The AIR instance map\n @returns Boolean, True if instance is valid.\n\n The instance is assumed to be a syntactically valid instance.\n This routine checks:\n\n The Parser:\n Each edge connects two declared states\n\n In so doing, the validator generates additional structures\n and binds them to the IR. These inc\n '
pass<|docstring|>@brief Semantic validation of an AIR instance
@param instance The AIR instance map
@returns Boolean, True if instance is valid.
The instance is assumed to be a syntactically valid instance.
This routine checks:
The Parser:
Each edge connects two declared states
In so doing, the validator generates additional structures
and binds them to the IR. These inc<|endoftext|> |
81b73bb863098e7414ac8d8e5255098129737c6c4478f583bb41e3ac62137110 | def air_validate_instance(instance):
'\n @brief Semantic validation of an AIR instance\n @param instance The AIR instance map\n @returns Boolean, True if instance is valid.\n\n The instance is assumed to be a syntactically valid instance.\n This routine calls the object specific validators:\n parser\n tables\n\n The Parser:\n Each edge connects two declared states\n\n In so doing, the validator generates additional structures\n and binds them to the IR. These inc\n '
pass | @brief Semantic validation of an AIR instance
@param instance The AIR instance map
@returns Boolean, True if instance is valid.
The instance is assumed to be a syntactically valid instance.
This routine calls the object specific validators:
parser
tables
The Parser:
Each edge connects two declared states
In so doing, the validator generates additional structures
and binds them to the IR. These inc | air/air_validate.py | air_validate_instance | dtalayco/air_iri | 0 | python | def air_validate_instance(instance):
'\n @brief Semantic validation of an AIR instance\n @param instance The AIR instance map\n @returns Boolean, True if instance is valid.\n\n The instance is assumed to be a syntactically valid instance.\n This routine calls the object specific validators:\n parser\n tables\n\n The Parser:\n Each edge connects two declared states\n\n In so doing, the validator generates additional structures\n and binds them to the IR. These inc\n '
pass | def air_validate_instance(instance):
'\n @brief Semantic validation of an AIR instance\n @param instance The AIR instance map\n @returns Boolean, True if instance is valid.\n\n The instance is assumed to be a syntactically valid instance.\n This routine calls the object specific validators:\n parser\n tables\n\n The Parser:\n Each edge connects two declared states\n\n In so doing, the validator generates additional structures\n and binds them to the IR. These inc\n '
pass<|docstring|>@brief Semantic validation of an AIR instance
@param instance The AIR instance map
@returns Boolean, True if instance is valid.
The instance is assumed to be a syntactically valid instance.
This routine calls the object specific validators:
parser
tables
The Parser:
Each edge connects two declared states
In so doing, the validator generates additional structures
and binds them to the IR. These inc<|endoftext|> |
5ce26aa6a7cd5b1cdf70588845616d188e46b03b48f4590111795f147bb2ba93 | def air_check_object(air_instance, obj_type_name, name, type, implementation_type=None):
'\n @brief Check basic AIR characteristics for an object reference\n @param air_instance The top level mapping for the IR\n @param obj_type_name The name of the object to report on error\n @param name The name of the top level object\n @param type The expected AIR type for the object\n @param implementation_type If not None, check impl is present and has type\n\n TODO Support a set for implementation type\n '
air_assert((name in air_instance.keys()), ('%s: %s is not in top level for type %s' % (obj_type_name, name, type)))
air_assert(('type' in air_instance[name].keys()), ('%s: %s is not an AIR object' % (obj_type_name, name)))
air_assert((air_instance[name]['type'] == type), ('%s: %s is not the expected type. Got %s, expected %s' % (obj_type_name, name, air_instance[name]['type'], type)))
if (implementation_type is not None):
air_assert(('format' in air_instance[name].keys()), ('%s: Expected format indication for %s' % (obj_type_name, name)))
air_assert((air_instance[name]['format'] == implementation_type), ('%s: implementation format for %s is %s, expected %s' % (obj_type_name, name, air_instance[name]['format'], implementation_type)))
air_assert(('implementation' in air_instance[name].keys()), ('%s: Expected implemenation for %s' % (obj_type_name, name)))
air_assert(('implementation' in air_instance[name].keys()), ('%s: Expected implemenation for %s' % (obj_type_name, name))) | @brief Check basic AIR characteristics for an object reference
@param air_instance The top level mapping for the IR
@param obj_type_name The name of the object to report on error
@param name The name of the top level object
@param type The expected AIR type for the object
@param implementation_type If not None, check impl is present and has type
TODO Support a set for implementation type | air/air_validate.py | air_check_object | dtalayco/air_iri | 0 | python | def air_check_object(air_instance, obj_type_name, name, type, implementation_type=None):
'\n @brief Check basic AIR characteristics for an object reference\n @param air_instance The top level mapping for the IR\n @param obj_type_name The name of the object to report on error\n @param name The name of the top level object\n @param type The expected AIR type for the object\n @param implementation_type If not None, check impl is present and has type\n\n TODO Support a set for implementation type\n '
air_assert((name in air_instance.keys()), ('%s: %s is not in top level for type %s' % (obj_type_name, name, type)))
air_assert(('type' in air_instance[name].keys()), ('%s: %s is not an AIR object' % (obj_type_name, name)))
air_assert((air_instance[name]['type'] == type), ('%s: %s is not the expected type. Got %s, expected %s' % (obj_type_name, name, air_instance[name]['type'], type)))
if (implementation_type is not None):
air_assert(('format' in air_instance[name].keys()), ('%s: Expected format indication for %s' % (obj_type_name, name)))
air_assert((air_instance[name]['format'] == implementation_type), ('%s: implementation format for %s is %s, expected %s' % (obj_type_name, name, air_instance[name]['format'], implementation_type)))
air_assert(('implementation' in air_instance[name].keys()), ('%s: Expected implemenation for %s' % (obj_type_name, name)))
air_assert(('implementation' in air_instance[name].keys()), ('%s: Expected implemenation for %s' % (obj_type_name, name))) | def air_check_object(air_instance, obj_type_name, name, type, implementation_type=None):
'\n @brief Check basic AIR characteristics for an object reference\n @param air_instance The top level mapping for the IR\n @param obj_type_name The name of the object to report on error\n @param name The name of the top level object\n @param type The expected AIR type for the object\n @param implementation_type If not None, check impl is present and has type\n\n TODO Support a set for implementation type\n '
air_assert((name in air_instance.keys()), ('%s: %s is not in top level for type %s' % (obj_type_name, name, type)))
air_assert(('type' in air_instance[name].keys()), ('%s: %s is not an AIR object' % (obj_type_name, name)))
air_assert((air_instance[name]['type'] == type), ('%s: %s is not the expected type. Got %s, expected %s' % (obj_type_name, name, air_instance[name]['type'], type)))
if (implementation_type is not None):
air_assert(('format' in air_instance[name].keys()), ('%s: Expected format indication for %s' % (obj_type_name, name)))
air_assert((air_instance[name]['format'] == implementation_type), ('%s: implementation format for %s is %s, expected %s' % (obj_type_name, name, air_instance[name]['format'], implementation_type)))
air_assert(('implementation' in air_instance[name].keys()), ('%s: Expected implemenation for %s' % (obj_type_name, name)))
air_assert(('implementation' in air_instance[name].keys()), ('%s: Expected implemenation for %s' % (obj_type_name, name)))<|docstring|>@brief Check basic AIR characteristics for an object reference
@param air_instance The top level mapping for the IR
@param obj_type_name The name of the object to report on error
@param name The name of the top level object
@param type The expected AIR type for the object
@param implementation_type If not None, check impl is present and has type
TODO Support a set for implementation type<|endoftext|> |
3fdd1c667f0e75c377f0191829a2308a235dde508b7d002f57904387f8ccc49b | def air_check_header(air_instance, name):
'\n @brief Validate a reference to an AIR header\n @param air_instance The top level AIR instance map\n @param name The name of the header\n @returns Boolean, True if a valid reference\n '
if (name not in air_instance.keys()):
return False
if ('type' not in air_instance[name].keys()):
return False
if (air_instance[name]['type'] != 'header'):
return False
return True | @brief Validate a reference to an AIR header
@param air_instance The top level AIR instance map
@param name The name of the header
@returns Boolean, True if a valid reference | air/air_validate.py | air_check_header | dtalayco/air_iri | 0 | python | def air_check_header(air_instance, name):
'\n @brief Validate a reference to an AIR header\n @param air_instance The top level AIR instance map\n @param name The name of the header\n @returns Boolean, True if a valid reference\n '
if (name not in air_instance.keys()):
return False
if ('type' not in air_instance[name].keys()):
return False
if (air_instance[name]['type'] != 'header'):
return False
return True | def air_check_header(air_instance, name):
'\n @brief Validate a reference to an AIR header\n @param air_instance The top level AIR instance map\n @param name The name of the header\n @returns Boolean, True if a valid reference\n '
if (name not in air_instance.keys()):
return False
if ('type' not in air_instance[name].keys()):
return False
if (air_instance[name]['type'] != 'header'):
return False
return True<|docstring|>@brief Validate a reference to an AIR header
@param air_instance The top level AIR instance map
@param name The name of the header
@returns Boolean, True if a valid reference<|endoftext|> |
8ef0e0857b854c7503b35a207a3431b89429ceb8e70d3cf87086621837cc1472 | def air_validate_data_ref(air_instance, name):
'\n @brief Validate a reference to an AIR field\n @param air_instance The top level AIR instance map\n @param name The reference being checked\n @returns Boolean, True if a valid reference\n\n Currently only supports header and header.fld\n '
parts = name.split('.')
if (len(parts) == 1):
return air_check_header(air_instance, parts[0])
elif (len(parts) == 2):
return (air_find_field(air_instance, parts[0], parts[1]) is not None)
return False | @brief Validate a reference to an AIR field
@param air_instance The top level AIR instance map
@param name The reference being checked
@returns Boolean, True if a valid reference
Currently only supports header and header.fld | air/air_validate.py | air_validate_data_ref | dtalayco/air_iri | 0 | python | def air_validate_data_ref(air_instance, name):
'\n @brief Validate a reference to an AIR field\n @param air_instance The top level AIR instance map\n @param name The reference being checked\n @returns Boolean, True if a valid reference\n\n Currently only supports header and header.fld\n '
parts = name.split('.')
if (len(parts) == 1):
return air_check_header(air_instance, parts[0])
elif (len(parts) == 2):
return (air_find_field(air_instance, parts[0], parts[1]) is not None)
return False | def air_validate_data_ref(air_instance, name):
'\n @brief Validate a reference to an AIR field\n @param air_instance The top level AIR instance map\n @param name The reference being checked\n @returns Boolean, True if a valid reference\n\n Currently only supports header and header.fld\n '
parts = name.split('.')
if (len(parts) == 1):
return air_check_header(air_instance, parts[0])
elif (len(parts) == 2):
return (air_find_field(air_instance, parts[0], parts[1]) is not None)
return False<|docstring|>@brief Validate a reference to an AIR field
@param air_instance The top level AIR instance map
@param name The reference being checked
@returns Boolean, True if a valid reference
Currently only supports header and header.fld<|endoftext|> |
510078a8d239157b597ff13afae39095b40e382f0647604856d3e2ed5e0937c3 | def create_inverse(range_list, diff):
'Creates opposite range for inverse table'
range_list = reversed(range_list)
value = 1
prev_value = 101
for range_obj in range_list:
Range.objects.create(value=value, result=opposites[range_obj.result], difficulty_table=diff)
value += (prev_value - range_obj.value)
prev_value = range_obj.value | Creates opposite range for inverse table | world/stat_checks/migrations/0004_auto_20210906_1457.py | create_inverse | ApostateCD/arxcode | 42 | python | def create_inverse(range_list, diff):
range_list = reversed(range_list)
value = 1
prev_value = 101
for range_obj in range_list:
Range.objects.create(value=value, result=opposites[range_obj.result], difficulty_table=diff)
value += (prev_value - range_obj.value)
prev_value = range_obj.value | def create_inverse(range_list, diff):
range_list = reversed(range_list)
value = 1
prev_value = 101
for range_obj in range_list:
Range.objects.create(value=value, result=opposites[range_obj.result], difficulty_table=diff)
value += (prev_value - range_obj.value)
prev_value = range_obj.value<|docstring|>Creates opposite range for inverse table<|endoftext|> |
f108e3a84ea58ded8834ae29386efae7e96e724e9ad91a074d02b0f688450f80 | @pytest.mark.parametrize('code', default_exceptions)
def test_error_handler_registration(self, code):
'Check custom error handler is registered for all codes'
app = Flask('test')
client = app.test_client()
@app.route('/')
def test():
abort(code)
Api(app)
with NoLoggingContext(app):
response = client.get('/')
assert (response.status_code == code)
if (code != 412):
data = json.loads(response.get_data(as_text=True))
assert (data['status'] == str(default_exceptions[code]())) | Check custom error handler is registered for all codes | tests/test_error_handler.py | test_error_handler_registration | xalioth/flask-rest-api | 2 | python | @pytest.mark.parametrize('code', default_exceptions)
def test_error_handler_registration(self, code):
app = Flask('test')
client = app.test_client()
@app.route('/')
def test():
abort(code)
Api(app)
with NoLoggingContext(app):
response = client.get('/')
assert (response.status_code == code)
if (code != 412):
data = json.loads(response.get_data(as_text=True))
assert (data['status'] == str(default_exceptions[code]())) | @pytest.mark.parametrize('code', default_exceptions)
def test_error_handler_registration(self, code):
app = Flask('test')
client = app.test_client()
@app.route('/')
def test():
abort(code)
Api(app)
with NoLoggingContext(app):
response = client.get('/')
assert (response.status_code == code)
if (code != 412):
data = json.loads(response.get_data(as_text=True))
assert (data['status'] == str(default_exceptions[code]()))<|docstring|>Check custom error handler is registered for all codes<|endoftext|> |
8aff9221d29d1d98e3a7eb4d87f6509af65802e3d7e74646f51877fb347ea7fd | def test_error_handler_uncaught_exception(self):
'Test uncaught exceptions result in 500 status code being returned'
app = Flask('test')
client = app.test_client()
@app.route('/')
def test():
raise Exception('Oops, something really bad happened.')
Api(app)
with NoLoggingContext(app):
response = client.get('/')
assert (response.status_code == 500)
data = json.loads(response.get_data(as_text=True))
assert (data['status'] == str(InternalServerError())) | Test uncaught exceptions result in 500 status code being returned | tests/test_error_handler.py | test_error_handler_uncaught_exception | xalioth/flask-rest-api | 2 | python | def test_error_handler_uncaught_exception(self):
app = Flask('test')
client = app.test_client()
@app.route('/')
def test():
raise Exception('Oops, something really bad happened.')
Api(app)
with NoLoggingContext(app):
response = client.get('/')
assert (response.status_code == 500)
data = json.loads(response.get_data(as_text=True))
assert (data['status'] == str(InternalServerError())) | def test_error_handler_uncaught_exception(self):
app = Flask('test')
client = app.test_client()
@app.route('/')
def test():
raise Exception('Oops, something really bad happened.')
Api(app)
with NoLoggingContext(app):
response = client.get('/')
assert (response.status_code == 500)
data = json.loads(response.get_data(as_text=True))
assert (data['status'] == str(InternalServerError()))<|docstring|>Test uncaught exceptions result in 500 status code being returned<|endoftext|> |
3b1e0d49f9039d76f410dc30eff176df3027b374ca7e8c77242bf2faa55cdd34 | def setup_method(self, method):
' Reset args/kwargs before each test. '
self.args = []
self.kwargs = {} | Reset args/kwargs before each test. | rhcephpkg/tests/test_build.py | setup_method | red-hat-storage/rhcephpkg | 2 | python | def setup_method(self, method):
' '
self.args = []
self.kwargs = {} | def setup_method(self, method):
' '
self.args = []
self.kwargs = {}<|docstring|>Reset args/kwargs before each test.<|endoftext|> |
bad3ebe535651cb1e2aafaace873e5122733752c1a4b17f2e9d71afbaf57c07a | def fake_build_job(self, *args, **kwargs):
' Store args/kwargs, in order to verify later. '
self.args = args
self.kwargs = kwargs
return 123 | Store args/kwargs, in order to verify later. | rhcephpkg/tests/test_build.py | fake_build_job | red-hat-storage/rhcephpkg | 2 | python | def fake_build_job(self, *args, **kwargs):
' '
self.args = args
self.kwargs = kwargs
return 123 | def fake_build_job(self, *args, **kwargs):
' '
self.args = args
self.kwargs = kwargs
return 123<|docstring|>Store args/kwargs, in order to verify later.<|endoftext|> |
040553d4815fd147a69616c25ab2441363da8b5b0283c0e8f03bd40597226406 | def fake_get_queue_item(self, id_):
' Return fake information about a build ID '
return {'executable': {'number': 456}} | Return fake information about a build ID | rhcephpkg/tests/test_build.py | fake_get_queue_item | red-hat-storage/rhcephpkg | 2 | python | def fake_get_queue_item(self, id_):
' '
return {'executable': {'number': 456}} | def fake_get_queue_item(self, id_):
' '
return {'executable': {'number': 456}}<|docstring|>Return fake information about a build ID<|endoftext|> |
e248202fedd45ce4a721b5a41671cb801560a2d9eea087aeb23eb8502d63518d | def fake_get_build_info(self, build_name, id_):
' Return fake information about a queue ID '
return {'building': False, 'duration': 123456, 'result': 'SUCCESS'} | Return fake information about a queue ID | rhcephpkg/tests/test_build.py | fake_get_build_info | red-hat-storage/rhcephpkg | 2 | python | def fake_get_build_info(self, build_name, id_):
' '
return {'building': False, 'duration': 123456, 'result': 'SUCCESS'} | def fake_get_build_info(self, build_name, id_):
' '
return {'building': False, 'duration': 123456, 'result': 'SUCCESS'}<|docstring|>Return fake information about a queue ID<|endoftext|> |
4ce77f90f8ed9897d27fc2ff32d245bfbe389e3a0aba29a46bf2113536680791 | def sam_fetch(sam, chrom, start, end):
'Provide a wrapper for sam-fetch method that could automatically\n handle chrom with or without "chr" prefix.\n @param sam A pysam.AlignmentFile object.\n @param chrom Chromosome name [str]\n @param start 1-based, inclusive [int]\n @param end 1-based, inclusive [int]\n @return Iterator if success, None otherwise. \n '
try:
itr = sam.fetch(chrom, (start - 1), end)
except:
pass
else:
if itr:
return itr
chrom = (chrom[3:] if chrom.startswith('chr') else ('chr' + chrom))
try:
itr = sam.fetch(chrom, (start - 1), end)
except:
return None
else:
return (itr if itr else None) | Provide a wrapper for sam-fetch method that could automatically
handle chrom with or without "chr" prefix.
@param sam A pysam.AlignmentFile object.
@param chrom Chromosome name [str]
@param start 1-based, inclusive [int]
@param end 1-based, inclusive [int]
@return Iterator if success, None otherwise. | xcltk/baf/plp/sam.py | sam_fetch | hxj5/celllib | 0 | python | def sam_fetch(sam, chrom, start, end):
'Provide a wrapper for sam-fetch method that could automatically\n handle chrom with or without "chr" prefix.\n @param sam A pysam.AlignmentFile object.\n @param chrom Chromosome name [str]\n @param start 1-based, inclusive [int]\n @param end 1-based, inclusive [int]\n @return Iterator if success, None otherwise. \n '
try:
itr = sam.fetch(chrom, (start - 1), end)
except:
pass
else:
if itr:
return itr
chrom = (chrom[3:] if chrom.startswith('chr') else ('chr' + chrom))
try:
itr = sam.fetch(chrom, (start - 1), end)
except:
return None
else:
return (itr if itr else None) | def sam_fetch(sam, chrom, start, end):
'Provide a wrapper for sam-fetch method that could automatically\n handle chrom with or without "chr" prefix.\n @param sam A pysam.AlignmentFile object.\n @param chrom Chromosome name [str]\n @param start 1-based, inclusive [int]\n @param end 1-based, inclusive [int]\n @return Iterator if success, None otherwise. \n '
try:
itr = sam.fetch(chrom, (start - 1), end)
except:
pass
else:
if itr:
return itr
chrom = (chrom[3:] if chrom.startswith('chr') else ('chr' + chrom))
try:
itr = sam.fetch(chrom, (start - 1), end)
except:
return None
else:
return (itr if itr else None)<|docstring|>Provide a wrapper for sam-fetch method that could automatically
handle chrom with or without "chr" prefix.
@param sam A pysam.AlignmentFile object.
@param chrom Chromosome name [str]
@param start 1-based, inclusive [int]
@param end 1-based, inclusive [int]
@return Iterator if success, None otherwise.<|endoftext|> |
d08b799d2e5da5340a305932182cc5c87f20e0032bcbf0bb72004d6936f71abe | def chrome(self):
'Chrome with no options\n\n '
opt = SeleniumOptions(self.webdriver)
opt.default() | Chrome with no options | automon/integrations/selenium/config.py | chrome | TheShellLand/automonisaur | 2 | python | def chrome(self):
'\n\n '
opt = SeleniumOptions(self.webdriver)
opt.default() | def chrome(self):
'\n\n '
opt = SeleniumOptions(self.webdriver)
opt.default()<|docstring|>Chrome with no options<|endoftext|> |
b132907f8fa3795410528cee0e59d7afaa26eaf8a920f7a7c713b2dcc6389dd1 | def chrome_maximized(self):
'Chrome with no options\n\n '
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.maximized() | Chrome with no options | automon/integrations/selenium/config.py | chrome_maximized | TheShellLand/automonisaur | 2 | python | def chrome_maximized(self):
'\n\n '
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.maximized() | def chrome_maximized(self):
'\n\n '
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.maximized()<|docstring|>Chrome with no options<|endoftext|> |
8923813e42680675ea9a1e3a6920dd4bf260c83fcd26f999b74604e5acdce4a3 | def chrome_fullscreen(self):
'Chrome with no options\n\n '
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.fullscreen() | Chrome with no options | automon/integrations/selenium/config.py | chrome_fullscreen | TheShellLand/automonisaur | 2 | python | def chrome_fullscreen(self):
'\n\n '
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.fullscreen() | def chrome_fullscreen(self):
'\n\n '
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.fullscreen()<|docstring|>Chrome with no options<|endoftext|> |
7311714ed72d40cc73d1474d5ad66e89e4fc0ac023a4cde1256e8ff7cf6c2bf9 | def chrome_for_docker(self):
'Chrome best used with docker\n\n '
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.nosandbox()
opt.headless()
opt.noinfobars()
opt.noextensions()
opt.nonotifications() | Chrome best used with docker | automon/integrations/selenium/config.py | chrome_for_docker | TheShellLand/automonisaur | 2 | python | def chrome_for_docker(self):
'\n\n '
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.nosandbox()
opt.headless()
opt.noinfobars()
opt.noextensions()
opt.nonotifications() | def chrome_for_docker(self):
'\n\n '
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.nosandbox()
opt.headless()
opt.noinfobars()
opt.noextensions()
opt.nonotifications()<|docstring|>Chrome best used with docker<|endoftext|> |
1f2cc582d016dfe75ae8bf0c40e675119a4c703e212daa30c2a1d5e78c51abe5 | def chrome_sandboxed(self):
'Chrome with sandbox enabled\n\n '
warnings.warn('Docker does not support sandbox option')
warnings.warn('Default shm size is 64m, which will cause chrome driver to crash.', Warning)
opt = SeleniumOptions(self.webdriver)
opt.default() | Chrome with sandbox enabled | automon/integrations/selenium/config.py | chrome_sandboxed | TheShellLand/automonisaur | 2 | python | def chrome_sandboxed(self):
'\n\n '
warnings.warn('Docker does not support sandbox option')
warnings.warn('Default shm size is 64m, which will cause chrome driver to crash.', Warning)
opt = SeleniumOptions(self.webdriver)
opt.default() | def chrome_sandboxed(self):
'\n\n '
warnings.warn('Docker does not support sandbox option')
warnings.warn('Default shm size is 64m, which will cause chrome driver to crash.', Warning)
opt = SeleniumOptions(self.webdriver)
opt.default()<|docstring|>Chrome with sandbox enabled<|endoftext|> |
26948878f8cab4e15ba50ddba12c12dcc59941f3c0deb8c51402a7bb56356523 | def chrome_nosandbox(self):
'Chrome with sandbox disabled\n\n '
warnings.warn('Default shm size is 64m, which will cause chrome driver to crash.', Warning)
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.nosandbox() | Chrome with sandbox disabled | automon/integrations/selenium/config.py | chrome_nosandbox | TheShellLand/automonisaur | 2 | python | def chrome_nosandbox(self):
'\n\n '
warnings.warn('Default shm size is 64m, which will cause chrome driver to crash.', Warning)
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.nosandbox() | def chrome_nosandbox(self):
'\n\n '
warnings.warn('Default shm size is 64m, which will cause chrome driver to crash.', Warning)
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.nosandbox()<|docstring|>Chrome with sandbox disabled<|endoftext|> |
e7cdb24b058a69f53cbc10d14a2eb8e3f6da0c5ffb32b4e9ee015ccc49249ccf | def chrome_headless_sandboxed(self):
'Headless Chrome with sandbox enabled\n\n '
warnings.warn('Docker does not support sandbox option')
warnings.warn('Default shm size is 64m, which will cause chrome driver to crash.', Warning)
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.headless() | Headless Chrome with sandbox enabled | automon/integrations/selenium/config.py | chrome_headless_sandboxed | TheShellLand/automonisaur | 2 | python | def chrome_headless_sandboxed(self):
'\n\n '
warnings.warn('Docker does not support sandbox option')
warnings.warn('Default shm size is 64m, which will cause chrome driver to crash.', Warning)
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.headless() | def chrome_headless_sandboxed(self):
'\n\n '
warnings.warn('Docker does not support sandbox option')
warnings.warn('Default shm size is 64m, which will cause chrome driver to crash.', Warning)
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.headless()<|docstring|>Headless Chrome with sandbox enabled<|endoftext|> |
cdc3ef56d3da4b2a7b08a9593a5b41d71b6923a482bf0ef87f41e8d5d79bddc0 | def chrome_headless_nosandbox(self):
'Headless Chrome with sandbox disabled\n\n '
warnings.warn('Default shm size is 64m, which will cause chrome driver to crash.', Warning)
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.headless()
opt.nosandbox() | Headless Chrome with sandbox disabled | automon/integrations/selenium/config.py | chrome_headless_nosandbox | TheShellLand/automonisaur | 2 | python | def chrome_headless_nosandbox(self):
'\n\n '
warnings.warn('Default shm size is 64m, which will cause chrome driver to crash.', Warning)
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.headless()
opt.nosandbox() | def chrome_headless_nosandbox(self):
'\n\n '
warnings.warn('Default shm size is 64m, which will cause chrome driver to crash.', Warning)
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.headless()
opt.nosandbox()<|docstring|>Headless Chrome with sandbox disabled<|endoftext|> |
5916682252281e941dc50fb537a618656c935d2a3df0e32af2b623f465613fbe | def chrome_headless_nosandbox_unsafe(self):
'Headless Chrome with sandbox disabled with not certificate verification\n\n '
warnings.warn('Default shm size is 64m, which will cause chrome driver to crash.', Warning)
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.headless()
opt.nosandbox()
opt.unsafe() | Headless Chrome with sandbox disabled with not certificate verification | automon/integrations/selenium/config.py | chrome_headless_nosandbox_unsafe | TheShellLand/automonisaur | 2 | python | def chrome_headless_nosandbox_unsafe(self):
'\n\n '
warnings.warn('Default shm size is 64m, which will cause chrome driver to crash.', Warning)
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.headless()
opt.nosandbox()
opt.unsafe() | def chrome_headless_nosandbox_unsafe(self):
'\n\n '
warnings.warn('Default shm size is 64m, which will cause chrome driver to crash.', Warning)
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.headless()
opt.nosandbox()
opt.unsafe()<|docstring|>Headless Chrome with sandbox disabled with not certificate verification<|endoftext|> |
61f652d69eaac4bdab02445d7ab3351c5c1942c83cff864419cfa0b800b4bc52 | def chrome_headless_nosandbox_noshm(self):
'Headless Chrome with sandbox disabled\n\n '
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.headless()
opt.nosandbox()
opt.noshm() | Headless Chrome with sandbox disabled | automon/integrations/selenium/config.py | chrome_headless_nosandbox_noshm | TheShellLand/automonisaur | 2 | python | def chrome_headless_nosandbox_noshm(self):
'\n\n '
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.headless()
opt.nosandbox()
opt.noshm() | def chrome_headless_nosandbox_noshm(self):
'\n\n '
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.headless()
opt.nosandbox()
opt.noshm()<|docstring|>Headless Chrome with sandbox disabled<|endoftext|> |
664cab55dcb013356b8508c64af913459e00f043e76ce321de048378d291a273 | def chrome_headless_nosandbox_bigshm(self):
'Headless Chrome with sandbox disabled\n\n '
warnings.warn('Larger shm option is not implemented', Warning)
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.headless()
opt.nosandbox()
opt.bigshm() | Headless Chrome with sandbox disabled | automon/integrations/selenium/config.py | chrome_headless_nosandbox_bigshm | TheShellLand/automonisaur | 2 | python | def chrome_headless_nosandbox_bigshm(self):
'\n\n '
warnings.warn('Larger shm option is not implemented', Warning)
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.headless()
opt.nosandbox()
opt.bigshm() | def chrome_headless_nosandbox_bigshm(self):
'\n\n '
warnings.warn('Larger shm option is not implemented', Warning)
opt = SeleniumOptions(self.webdriver)
opt.default()
opt.headless()
opt.nosandbox()
opt.bigshm()<|docstring|>Headless Chrome with sandbox disabled<|endoftext|> |
4c0d4bd6aaf55271fa859c4fd316570d3f7235e94c74c3dd5ef52f440abdadc5 | def chrome_remote(self, host: str='127.0.0.1', port: str='4444', executor_path: str='/wd/hub'):
'Remote Selenium\n\n '
log.info(f'Remote WebDriver Hub URL: http://{host}:{port}{executor_path}/static/resource/hub.html')
self.webdriver.Remote(command_executor=f'http://{host}:{port}{executor_path}', desired_capabilities=DesiredCapabilities.CHROME) | Remote Selenium | automon/integrations/selenium/config.py | chrome_remote | TheShellLand/automonisaur | 2 | python | def chrome_remote(self, host: str='127.0.0.1', port: str='4444', executor_path: str='/wd/hub'):
'\n\n '
log.info(f'Remote WebDriver Hub URL: http://{host}:{port}{executor_path}/static/resource/hub.html')
self.webdriver.Remote(command_executor=f'http://{host}:{port}{executor_path}', desired_capabilities=DesiredCapabilities.CHROME) | def chrome_remote(self, host: str='127.0.0.1', port: str='4444', executor_path: str='/wd/hub'):
'\n\n '
log.info(f'Remote WebDriver Hub URL: http://{host}:{port}{executor_path}/static/resource/hub.html')
self.webdriver.Remote(command_executor=f'http://{host}:{port}{executor_path}', desired_capabilities=DesiredCapabilities.CHROME)<|docstring|>Remote Selenium<|endoftext|> |
8a6a130c6835f0e05acd673bb3a465f0c5b0f0acd5793e1d9c35665ff9c06a4b | def __init__(self, symbol_map: Dict, expr):
'Create a new :class:`ParameterExpression`.\n\n Not intended to be called directly, but to be instantiated via operations\n on other :class:`Parameter` or :class:`ParameterExpression` objects.\n\n Args:\n symbol_map (Dict[Parameter, [ParameterExpression, float, or int]]):\n Mapping of :class:`Parameter` instances to the :class:`sympy.Symbol`\n serving as their placeholder in expr.\n expr (sympy.Expr): Expression of :class:`sympy.Symbol` s.\n '
self._parameter_symbols = symbol_map
self._parameters = set(self._parameter_symbols)
self._symbol_expr = expr
self._names = None | Create a new :class:`ParameterExpression`.
Not intended to be called directly, but to be instantiated via operations
on other :class:`Parameter` or :class:`ParameterExpression` objects.
Args:
symbol_map (Dict[Parameter, [ParameterExpression, float, or int]]):
Mapping of :class:`Parameter` instances to the :class:`sympy.Symbol`
serving as their placeholder in expr.
expr (sympy.Expr): Expression of :class:`sympy.Symbol` s. | venv/lib/python3.8/site-packages/qiskit/circuit/parameterexpression.py | __init__ | OscarJHernandez/qc_portfolio_optimization | 15 | python | def __init__(self, symbol_map: Dict, expr):
'Create a new :class:`ParameterExpression`.\n\n Not intended to be called directly, but to be instantiated via operations\n on other :class:`Parameter` or :class:`ParameterExpression` objects.\n\n Args:\n symbol_map (Dict[Parameter, [ParameterExpression, float, or int]]):\n Mapping of :class:`Parameter` instances to the :class:`sympy.Symbol`\n serving as their placeholder in expr.\n expr (sympy.Expr): Expression of :class:`sympy.Symbol` s.\n '
self._parameter_symbols = symbol_map
self._parameters = set(self._parameter_symbols)
self._symbol_expr = expr
self._names = None | def __init__(self, symbol_map: Dict, expr):
'Create a new :class:`ParameterExpression`.\n\n Not intended to be called directly, but to be instantiated via operations\n on other :class:`Parameter` or :class:`ParameterExpression` objects.\n\n Args:\n symbol_map (Dict[Parameter, [ParameterExpression, float, or int]]):\n Mapping of :class:`Parameter` instances to the :class:`sympy.Symbol`\n serving as their placeholder in expr.\n expr (sympy.Expr): Expression of :class:`sympy.Symbol` s.\n '
self._parameter_symbols = symbol_map
self._parameters = set(self._parameter_symbols)
self._symbol_expr = expr
self._names = None<|docstring|>Create a new :class:`ParameterExpression`.
Not intended to be called directly, but to be instantiated via operations
on other :class:`Parameter` or :class:`ParameterExpression` objects.
Args:
symbol_map (Dict[Parameter, [ParameterExpression, float, or int]]):
Mapping of :class:`Parameter` instances to the :class:`sympy.Symbol`
serving as their placeholder in expr.
expr (sympy.Expr): Expression of :class:`sympy.Symbol` s.<|endoftext|> |
08a1f82e3fbcf49346fd6998960c7295dd4baa80ac0d7c04eafdb4714f9a3cfc | @property
def parameters(self) -> Set:
'Returns a set of the unbound Parameters in the expression.'
return self._parameters | Returns a set of the unbound Parameters in the expression. | venv/lib/python3.8/site-packages/qiskit/circuit/parameterexpression.py | parameters | OscarJHernandez/qc_portfolio_optimization | 15 | python | @property
def parameters(self) -> Set:
return self._parameters | @property
def parameters(self) -> Set:
return self._parameters<|docstring|>Returns a set of the unbound Parameters in the expression.<|endoftext|> |
014e50baa7b82f0e406a6f8ec6678863fd90bb1af67c78f1325cc1ce284cd052 | def conjugate(self) -> 'ParameterExpression':
'Return the conjugate, which is the ParameterExpression itself, since it is real.'
return self | Return the conjugate, which is the ParameterExpression itself, since it is real. | venv/lib/python3.8/site-packages/qiskit/circuit/parameterexpression.py | conjugate | OscarJHernandez/qc_portfolio_optimization | 15 | python | def conjugate(self) -> 'ParameterExpression':
return self | def conjugate(self) -> 'ParameterExpression':
return self<|docstring|>Return the conjugate, which is the ParameterExpression itself, since it is real.<|endoftext|> |
61fc77ad6ae45fcdbba748e2098754c417df0de860957ec095682717eada8011 | def assign(self, parameter, value: ParameterValueType) -> 'ParameterExpression':
'\n Assign one parameter to a value, which can either be numeric or another parameter\n expression.\n\n Args:\n parameter (Parameter): A parameter in this expression whose value will be updated.\n value: The new value to bind to.\n\n Returns:\n A new expression parameterized by any parameters which were not bound by assignment.\n '
if isinstance(value, ParameterExpression):
return self.subs({parameter: value})
return self.bind({parameter: value}) | Assign one parameter to a value, which can either be numeric or another parameter
expression.
Args:
parameter (Parameter): A parameter in this expression whose value will be updated.
value: The new value to bind to.
Returns:
A new expression parameterized by any parameters which were not bound by assignment. | venv/lib/python3.8/site-packages/qiskit/circuit/parameterexpression.py | assign | OscarJHernandez/qc_portfolio_optimization | 15 | python | def assign(self, parameter, value: ParameterValueType) -> 'ParameterExpression':
'\n Assign one parameter to a value, which can either be numeric or another parameter\n expression.\n\n Args:\n parameter (Parameter): A parameter in this expression whose value will be updated.\n value: The new value to bind to.\n\n Returns:\n A new expression parameterized by any parameters which were not bound by assignment.\n '
if isinstance(value, ParameterExpression):
return self.subs({parameter: value})
return self.bind({parameter: value}) | def assign(self, parameter, value: ParameterValueType) -> 'ParameterExpression':
'\n Assign one parameter to a value, which can either be numeric or another parameter\n expression.\n\n Args:\n parameter (Parameter): A parameter in this expression whose value will be updated.\n value: The new value to bind to.\n\n Returns:\n A new expression parameterized by any parameters which were not bound by assignment.\n '
if isinstance(value, ParameterExpression):
return self.subs({parameter: value})
return self.bind({parameter: value})<|docstring|>Assign one parameter to a value, which can either be numeric or another parameter
expression.
Args:
parameter (Parameter): A parameter in this expression whose value will be updated.
value: The new value to bind to.
Returns:
A new expression parameterized by any parameters which were not bound by assignment.<|endoftext|> |
5b620c16ab187e45dc8275467d78ce7f9d0c47728a87dfd838e3d917e965ae26 | def bind(self, parameter_values: Dict) -> 'ParameterExpression':
'Binds the provided set of parameters to their corresponding values.\n\n Args:\n parameter_values: Mapping of Parameter instances to the numeric value to which\n they will be bound.\n\n Raises:\n CircuitError:\n - If parameter_values contains Parameters outside those in self.\n - If a non-numeric value is passed in parameter_values.\n ZeroDivisionError:\n - If binding the provided values requires division by zero.\n\n Returns:\n A new expression parameterized by any parameters which were not bound by\n parameter_values.\n '
self._raise_if_passed_unknown_parameters(parameter_values.keys())
self._raise_if_passed_non_real_value(parameter_values)
symbol_values = {self._parameter_symbols[parameter]: value for (parameter, value) in parameter_values.items()}
bound_symbol_expr = self._symbol_expr.subs(symbol_values)
free_parameters = (self.parameters - parameter_values.keys())
free_parameter_symbols = {p: s for (p, s) in self._parameter_symbols.items() if (p in free_parameters)}
if bound_symbol_expr.is_infinite:
raise ZeroDivisionError('Binding provided for expression results in division by zero (Expression: {}, Bindings: {}).'.format(self, parameter_values))
return ParameterExpression(free_parameter_symbols, bound_symbol_expr) | Binds the provided set of parameters to their corresponding values.
Args:
parameter_values: Mapping of Parameter instances to the numeric value to which
they will be bound.
Raises:
CircuitError:
- If parameter_values contains Parameters outside those in self.
- If a non-numeric value is passed in parameter_values.
ZeroDivisionError:
- If binding the provided values requires division by zero.
Returns:
A new expression parameterized by any parameters which were not bound by
parameter_values. | venv/lib/python3.8/site-packages/qiskit/circuit/parameterexpression.py | bind | OscarJHernandez/qc_portfolio_optimization | 15 | python | def bind(self, parameter_values: Dict) -> 'ParameterExpression':
'Binds the provided set of parameters to their corresponding values.\n\n Args:\n parameter_values: Mapping of Parameter instances to the numeric value to which\n they will be bound.\n\n Raises:\n CircuitError:\n - If parameter_values contains Parameters outside those in self.\n - If a non-numeric value is passed in parameter_values.\n ZeroDivisionError:\n - If binding the provided values requires division by zero.\n\n Returns:\n A new expression parameterized by any parameters which were not bound by\n parameter_values.\n '
self._raise_if_passed_unknown_parameters(parameter_values.keys())
self._raise_if_passed_non_real_value(parameter_values)
symbol_values = {self._parameter_symbols[parameter]: value for (parameter, value) in parameter_values.items()}
bound_symbol_expr = self._symbol_expr.subs(symbol_values)
free_parameters = (self.parameters - parameter_values.keys())
free_parameter_symbols = {p: s for (p, s) in self._parameter_symbols.items() if (p in free_parameters)}
if bound_symbol_expr.is_infinite:
raise ZeroDivisionError('Binding provided for expression results in division by zero (Expression: {}, Bindings: {}).'.format(self, parameter_values))
return ParameterExpression(free_parameter_symbols, bound_symbol_expr) | def bind(self, parameter_values: Dict) -> 'ParameterExpression':
'Binds the provided set of parameters to their corresponding values.\n\n Args:\n parameter_values: Mapping of Parameter instances to the numeric value to which\n they will be bound.\n\n Raises:\n CircuitError:\n - If parameter_values contains Parameters outside those in self.\n - If a non-numeric value is passed in parameter_values.\n ZeroDivisionError:\n - If binding the provided values requires division by zero.\n\n Returns:\n A new expression parameterized by any parameters which were not bound by\n parameter_values.\n '
self._raise_if_passed_unknown_parameters(parameter_values.keys())
self._raise_if_passed_non_real_value(parameter_values)
symbol_values = {self._parameter_symbols[parameter]: value for (parameter, value) in parameter_values.items()}
bound_symbol_expr = self._symbol_expr.subs(symbol_values)
free_parameters = (self.parameters - parameter_values.keys())
free_parameter_symbols = {p: s for (p, s) in self._parameter_symbols.items() if (p in free_parameters)}
if bound_symbol_expr.is_infinite:
raise ZeroDivisionError('Binding provided for expression results in division by zero (Expression: {}, Bindings: {}).'.format(self, parameter_values))
return ParameterExpression(free_parameter_symbols, bound_symbol_expr)<|docstring|>Binds the provided set of parameters to their corresponding values.
Args:
parameter_values: Mapping of Parameter instances to the numeric value to which
they will be bound.
Raises:
CircuitError:
- If parameter_values contains Parameters outside those in self.
- If a non-numeric value is passed in parameter_values.
ZeroDivisionError:
- If binding the provided values requires division by zero.
Returns:
A new expression parameterized by any parameters which were not bound by
parameter_values.<|endoftext|> |
d03d7d73fddc84504cbf53acfbbba4671babdbb62abe2caf0bf2c8962ab2716a | def subs(self, parameter_map: Dict) -> 'ParameterExpression':
'Returns a new Expression with replacement Parameters.\n\n Args:\n parameter_map: Mapping from Parameters in self to the ParameterExpression\n instances with which they should be replaced.\n\n Raises:\n CircuitError:\n - If parameter_map contains Parameters outside those in self.\n - If the replacement Parameters in parameter_map would result in\n a name conflict in the generated expression.\n\n Returns:\n A new expression with the specified parameters replaced.\n '
inbound_parameters = {p for replacement_expr in parameter_map.values() for p in replacement_expr.parameters}
self._raise_if_passed_unknown_parameters(parameter_map.keys())
self._raise_if_parameter_names_conflict(inbound_parameters, parameter_map.keys())
from sympy import Symbol
new_parameter_symbols = {p: Symbol(p.name) for p in inbound_parameters}
new_parameter_symbols.update({p: s for (p, s) in self._parameter_symbols.items() if (p not in parameter_map)})
symbol_map = {self._parameter_symbols[old_param]: new_param._symbol_expr for (old_param, new_param) in parameter_map.items()}
substituted_symbol_expr = self._symbol_expr.subs(symbol_map)
return ParameterExpression(new_parameter_symbols, substituted_symbol_expr) | Returns a new Expression with replacement Parameters.
Args:
parameter_map: Mapping from Parameters in self to the ParameterExpression
instances with which they should be replaced.
Raises:
CircuitError:
- If parameter_map contains Parameters outside those in self.
- If the replacement Parameters in parameter_map would result in
a name conflict in the generated expression.
Returns:
A new expression with the specified parameters replaced. | venv/lib/python3.8/site-packages/qiskit/circuit/parameterexpression.py | subs | OscarJHernandez/qc_portfolio_optimization | 15 | python | def subs(self, parameter_map: Dict) -> 'ParameterExpression':
'Returns a new Expression with replacement Parameters.\n\n Args:\n parameter_map: Mapping from Parameters in self to the ParameterExpression\n instances with which they should be replaced.\n\n Raises:\n CircuitError:\n - If parameter_map contains Parameters outside those in self.\n - If the replacement Parameters in parameter_map would result in\n a name conflict in the generated expression.\n\n Returns:\n A new expression with the specified parameters replaced.\n '
inbound_parameters = {p for replacement_expr in parameter_map.values() for p in replacement_expr.parameters}
self._raise_if_passed_unknown_parameters(parameter_map.keys())
self._raise_if_parameter_names_conflict(inbound_parameters, parameter_map.keys())
from sympy import Symbol
new_parameter_symbols = {p: Symbol(p.name) for p in inbound_parameters}
new_parameter_symbols.update({p: s for (p, s) in self._parameter_symbols.items() if (p not in parameter_map)})
symbol_map = {self._parameter_symbols[old_param]: new_param._symbol_expr for (old_param, new_param) in parameter_map.items()}
substituted_symbol_expr = self._symbol_expr.subs(symbol_map)
return ParameterExpression(new_parameter_symbols, substituted_symbol_expr) | def subs(self, parameter_map: Dict) -> 'ParameterExpression':
'Returns a new Expression with replacement Parameters.\n\n Args:\n parameter_map: Mapping from Parameters in self to the ParameterExpression\n instances with which they should be replaced.\n\n Raises:\n CircuitError:\n - If parameter_map contains Parameters outside those in self.\n - If the replacement Parameters in parameter_map would result in\n a name conflict in the generated expression.\n\n Returns:\n A new expression with the specified parameters replaced.\n '
inbound_parameters = {p for replacement_expr in parameter_map.values() for p in replacement_expr.parameters}
self._raise_if_passed_unknown_parameters(parameter_map.keys())
self._raise_if_parameter_names_conflict(inbound_parameters, parameter_map.keys())
from sympy import Symbol
new_parameter_symbols = {p: Symbol(p.name) for p in inbound_parameters}
new_parameter_symbols.update({p: s for (p, s) in self._parameter_symbols.items() if (p not in parameter_map)})
symbol_map = {self._parameter_symbols[old_param]: new_param._symbol_expr for (old_param, new_param) in parameter_map.items()}
substituted_symbol_expr = self._symbol_expr.subs(symbol_map)
return ParameterExpression(new_parameter_symbols, substituted_symbol_expr)<|docstring|>Returns a new Expression with replacement Parameters.
Args:
parameter_map: Mapping from Parameters in self to the ParameterExpression
instances with which they should be replaced.
Raises:
CircuitError:
- If parameter_map contains Parameters outside those in self.
- If the replacement Parameters in parameter_map would result in
a name conflict in the generated expression.
Returns:
A new expression with the specified parameters replaced.<|endoftext|> |
9790711a57090a8dc8d997d5e420356359433e0ce8eab6b495df70005964e464 | def _apply_operation(self, operation: Callable, other: ParameterValueType, reflected: bool=False) -> 'ParameterExpression':
'Base method implementing math operations between Parameters and\n either a constant or a second ParameterExpression.\n\n Args:\n operation: One of operator.{add,sub,mul,truediv}.\n other: The second argument to be used with self in operation.\n reflected: Optional - The default ordering is "self operator other".\n If reflected is True, this is switched to "other operator self".\n For use in e.g. __radd__, ...\n\n Raises:\n CircuitError:\n - If parameter_map contains Parameters outside those in self.\n - If the replacement Parameters in parameter_map would result in\n a name conflict in the generated expression.\n\n Returns:\n A new expression describing the result of the operation.\n '
self_expr = self._symbol_expr
if isinstance(other, ParameterExpression):
self._raise_if_parameter_names_conflict(other._parameter_symbols.keys())
parameter_symbols = {**self._parameter_symbols, **other._parameter_symbols}
other_expr = other._symbol_expr
elif (isinstance(other, numbers.Real) and numpy.isfinite(other)):
parameter_symbols = self._parameter_symbols.copy()
other_expr = other
else:
return NotImplemented
if reflected:
expr = operation(other_expr, self_expr)
else:
expr = operation(self_expr, other_expr)
return ParameterExpression(parameter_symbols, expr) | Base method implementing math operations between Parameters and
either a constant or a second ParameterExpression.
Args:
operation: One of operator.{add,sub,mul,truediv}.
other: The second argument to be used with self in operation.
reflected: Optional - The default ordering is "self operator other".
If reflected is True, this is switched to "other operator self".
For use in e.g. __radd__, ...
Raises:
CircuitError:
- If parameter_map contains Parameters outside those in self.
- If the replacement Parameters in parameter_map would result in
a name conflict in the generated expression.
Returns:
A new expression describing the result of the operation. | venv/lib/python3.8/site-packages/qiskit/circuit/parameterexpression.py | _apply_operation | OscarJHernandez/qc_portfolio_optimization | 15 | python | def _apply_operation(self, operation: Callable, other: ParameterValueType, reflected: bool=False) -> 'ParameterExpression':
'Base method implementing math operations between Parameters and\n either a constant or a second ParameterExpression.\n\n Args:\n operation: One of operator.{add,sub,mul,truediv}.\n other: The second argument to be used with self in operation.\n reflected: Optional - The default ordering is "self operator other".\n If reflected is True, this is switched to "other operator self".\n For use in e.g. __radd__, ...\n\n Raises:\n CircuitError:\n - If parameter_map contains Parameters outside those in self.\n - If the replacement Parameters in parameter_map would result in\n a name conflict in the generated expression.\n\n Returns:\n A new expression describing the result of the operation.\n '
self_expr = self._symbol_expr
if isinstance(other, ParameterExpression):
self._raise_if_parameter_names_conflict(other._parameter_symbols.keys())
parameter_symbols = {**self._parameter_symbols, **other._parameter_symbols}
other_expr = other._symbol_expr
elif (isinstance(other, numbers.Real) and numpy.isfinite(other)):
parameter_symbols = self._parameter_symbols.copy()
other_expr = other
else:
return NotImplemented
if reflected:
expr = operation(other_expr, self_expr)
else:
expr = operation(self_expr, other_expr)
return ParameterExpression(parameter_symbols, expr) | def _apply_operation(self, operation: Callable, other: ParameterValueType, reflected: bool=False) -> 'ParameterExpression':
'Base method implementing math operations between Parameters and\n either a constant or a second ParameterExpression.\n\n Args:\n operation: One of operator.{add,sub,mul,truediv}.\n other: The second argument to be used with self in operation.\n reflected: Optional - The default ordering is "self operator other".\n If reflected is True, this is switched to "other operator self".\n For use in e.g. __radd__, ...\n\n Raises:\n CircuitError:\n - If parameter_map contains Parameters outside those in self.\n - If the replacement Parameters in parameter_map would result in\n a name conflict in the generated expression.\n\n Returns:\n A new expression describing the result of the operation.\n '
self_expr = self._symbol_expr
if isinstance(other, ParameterExpression):
self._raise_if_parameter_names_conflict(other._parameter_symbols.keys())
parameter_symbols = {**self._parameter_symbols, **other._parameter_symbols}
other_expr = other._symbol_expr
elif (isinstance(other, numbers.Real) and numpy.isfinite(other)):
parameter_symbols = self._parameter_symbols.copy()
other_expr = other
else:
return NotImplemented
if reflected:
expr = operation(other_expr, self_expr)
else:
expr = operation(self_expr, other_expr)
return ParameterExpression(parameter_symbols, expr)<|docstring|>Base method implementing math operations between Parameters and
either a constant or a second ParameterExpression.
Args:
operation: One of operator.{add,sub,mul,truediv}.
other: The second argument to be used with self in operation.
reflected: Optional - The default ordering is "self operator other".
If reflected is True, this is switched to "other operator self".
For use in e.g. __radd__, ...
Raises:
CircuitError:
- If parameter_map contains Parameters outside those in self.
- If the replacement Parameters in parameter_map would result in
a name conflict in the generated expression.
Returns:
A new expression describing the result of the operation.<|endoftext|> |
e73cf89fbdfd10dabafc96323e8b6e1e721be8b619e241fdaf0b85cc0b06c692 | def cb_status(self, msg):
'\n :type msg: Status\n '
now = self._node.get_clock().now()
feedback = Feedback()
feedback.set_rumble = True
feedback.rumble_small = abs(msg.axis_left_y)
feedback.rumble_big = abs(msg.axis_right_y)
touch = msg.touch0
if (touch.active and msg.button_circle):
feedback.set_led = True
self._led['r'] = touch.x
if (touch.active and msg.button_triangle):
feedback.set_led = True
self._led['g'] = touch.x
if (touch.active and msg.button_cross):
feedback.set_led = True
self._led['b'] = touch.x
feedback.led_r = float(self._led['r'])
feedback.led_g = float(self._led['g'])
feedback.led_b = float(self._led['b'])
if ((not self._prev.button_ps) and msg.button_ps):
feedback.set_led_flash = True
if self._led['flashing']:
feedback.led_flash_off = 0.0
else:
feedback.led_flash_on = 0.2
feedback.led_flash_off = 0.2
self._led['flashing'] = (not self._led['flashing'])
self._pub_feedback.publish(feedback)
self._prev = msg
self._last_pub_time = now | :type msg: Status | nodes/demo.py | cb_status | Aposhian/ds4_driver | 0 | python | def cb_status(self, msg):
'\n \n '
now = self._node.get_clock().now()
feedback = Feedback()
feedback.set_rumble = True
feedback.rumble_small = abs(msg.axis_left_y)
feedback.rumble_big = abs(msg.axis_right_y)
touch = msg.touch0
if (touch.active and msg.button_circle):
feedback.set_led = True
self._led['r'] = touch.x
if (touch.active and msg.button_triangle):
feedback.set_led = True
self._led['g'] = touch.x
if (touch.active and msg.button_cross):
feedback.set_led = True
self._led['b'] = touch.x
feedback.led_r = float(self._led['r'])
feedback.led_g = float(self._led['g'])
feedback.led_b = float(self._led['b'])
if ((not self._prev.button_ps) and msg.button_ps):
feedback.set_led_flash = True
if self._led['flashing']:
feedback.led_flash_off = 0.0
else:
feedback.led_flash_on = 0.2
feedback.led_flash_off = 0.2
self._led['flashing'] = (not self._led['flashing'])
self._pub_feedback.publish(feedback)
self._prev = msg
self._last_pub_time = now | def cb_status(self, msg):
'\n \n '
now = self._node.get_clock().now()
feedback = Feedback()
feedback.set_rumble = True
feedback.rumble_small = abs(msg.axis_left_y)
feedback.rumble_big = abs(msg.axis_right_y)
touch = msg.touch0
if (touch.active and msg.button_circle):
feedback.set_led = True
self._led['r'] = touch.x
if (touch.active and msg.button_triangle):
feedback.set_led = True
self._led['g'] = touch.x
if (touch.active and msg.button_cross):
feedback.set_led = True
self._led['b'] = touch.x
feedback.led_r = float(self._led['r'])
feedback.led_g = float(self._led['g'])
feedback.led_b = float(self._led['b'])
if ((not self._prev.button_ps) and msg.button_ps):
feedback.set_led_flash = True
if self._led['flashing']:
feedback.led_flash_off = 0.0
else:
feedback.led_flash_on = 0.2
feedback.led_flash_off = 0.2
self._led['flashing'] = (not self._led['flashing'])
self._pub_feedback.publish(feedback)
self._prev = msg
self._last_pub_time = now<|docstring|>:type msg: Status<|endoftext|> |
231652daf4700ba5881e77e18b73bcb296ab7d1ad3a3cef4b596e81ebe0a24be | def find_best_k_value(rows, category):
' 获取最优k值\n\n :param rows:\n :param category:\n :return:\n '
k = 4
if (len(rows) <= 15):
k = 1
elif (15 < len(rows) < 30):
k = 2
return k | 获取最优k值
:param rows:
:param category:
:return: | utils.py | find_best_k_value | guoweikuang/weibo_project | 4 | python | def find_best_k_value(rows, category):
' 获取最优k值\n\n :param rows:\n :param category:\n :return:\n '
k = 4
if (len(rows) <= 15):
k = 1
elif (15 < len(rows) < 30):
k = 2
return k | def find_best_k_value(rows, category):
' 获取最优k值\n\n :param rows:\n :param category:\n :return:\n '
k = 4
if (len(rows) <= 15):
k = 1
elif (15 < len(rows) < 30):
k = 2
return k<|docstring|>获取最优k值
:param rows:
:param category:
:return:<|endoftext|> |
af43d392e018a64093a8b75572c19be2c6005ddc711108412c5c6588c2b2f640 | def run_first_cluster(start_time, end_time, k=1):
' 一次聚类并存入数据库.\n\n :param start_time:\n :param end_time:\n :param k:\n :return:\n '
categories = os.listdir(os.path.join(abs_path, 'classify_text/data'))
for category in categories:
rows = get_text_from_file(category[:(- 4)], cate='category')
rows = [row.decode('utf-8').strip().split('\t') for row in rows]
tf_idf = TFIDF(rows)
tf_idf_dict = tf_idf.tf_idf()
texts = tf_idf.get_filter_text()
vsm = BuildVSM(tf_idf_dict, tf_idf.seg_list, texts, vsm_name=category[:(- 4)])
vsm.build_vsm()
rows = vsm.filter_text()
data_set = numpy.mat(load_data_set(vsm_name=category[:(- 4)]))
k = find_optimal_k_value(data_set)
print(category, k)
k = find_best_k_value(rows, category)
print('k:', k)
if (k == 1):
labels = ([0] * len(data_set))
else:
labels = run_kmeans_by_scikit(k=k, vsm_name=category[:(- 4)])
save_k_cluster_to_redis(labels=labels, texts=rows, category=category[:(- 4)])
classify_k_cluster_from_category(labels=labels, texts=rows, vsm_name=category[:(- 4)], category=category[:(- 4)]) | 一次聚类并存入数据库.
:param start_time:
:param end_time:
:param k:
:return: | utils.py | run_first_cluster | guoweikuang/weibo_project | 4 | python | def run_first_cluster(start_time, end_time, k=1):
' 一次聚类并存入数据库.\n\n :param start_time:\n :param end_time:\n :param k:\n :return:\n '
categories = os.listdir(os.path.join(abs_path, 'classify_text/data'))
for category in categories:
rows = get_text_from_file(category[:(- 4)], cate='category')
rows = [row.decode('utf-8').strip().split('\t') for row in rows]
tf_idf = TFIDF(rows)
tf_idf_dict = tf_idf.tf_idf()
texts = tf_idf.get_filter_text()
vsm = BuildVSM(tf_idf_dict, tf_idf.seg_list, texts, vsm_name=category[:(- 4)])
vsm.build_vsm()
rows = vsm.filter_text()
data_set = numpy.mat(load_data_set(vsm_name=category[:(- 4)]))
k = find_optimal_k_value(data_set)
print(category, k)
k = find_best_k_value(rows, category)
print('k:', k)
if (k == 1):
labels = ([0] * len(data_set))
else:
labels = run_kmeans_by_scikit(k=k, vsm_name=category[:(- 4)])
save_k_cluster_to_redis(labels=labels, texts=rows, category=category[:(- 4)])
classify_k_cluster_from_category(labels=labels, texts=rows, vsm_name=category[:(- 4)], category=category[:(- 4)]) | def run_first_cluster(start_time, end_time, k=1):
' 一次聚类并存入数据库.\n\n :param start_time:\n :param end_time:\n :param k:\n :return:\n '
categories = os.listdir(os.path.join(abs_path, 'classify_text/data'))
for category in categories:
rows = get_text_from_file(category[:(- 4)], cate='category')
rows = [row.decode('utf-8').strip().split('\t') for row in rows]
tf_idf = TFIDF(rows)
tf_idf_dict = tf_idf.tf_idf()
texts = tf_idf.get_filter_text()
vsm = BuildVSM(tf_idf_dict, tf_idf.seg_list, texts, vsm_name=category[:(- 4)])
vsm.build_vsm()
rows = vsm.filter_text()
data_set = numpy.mat(load_data_set(vsm_name=category[:(- 4)]))
k = find_optimal_k_value(data_set)
print(category, k)
k = find_best_k_value(rows, category)
print('k:', k)
if (k == 1):
labels = ([0] * len(data_set))
else:
labels = run_kmeans_by_scikit(k=k, vsm_name=category[:(- 4)])
save_k_cluster_to_redis(labels=labels, texts=rows, category=category[:(- 4)])
classify_k_cluster_from_category(labels=labels, texts=rows, vsm_name=category[:(- 4)], category=category[:(- 4)])<|docstring|>一次聚类并存入数据库.
:param start_time:
:param end_time:
:param k:
:return:<|endoftext|> |
8ed0b0adb745ebe3a92f35f860b9dc25f2a19730b631ac058f88c460af42c3e2 | def get_max_text_from_redis(category):
' 获取一次聚类后的最大数量的类.\n\n :param category:\n :return:\n '
max_num = 0
read_client = redis_client()
max_key = (K_CLUSTER % (category, 1))
for i in range(1, 15):
key_name = (K_CLUSTER % (category, i))
if (read_client.llen(key_name) > max_num):
max_num = read_client.llen(key_name)
max_key = key_name
rows = read_client.lrange(max_key, 0, (- 1))
return rows[::(- 1)] | 获取一次聚类后的最大数量的类.
:param category:
:return: | utils.py | get_max_text_from_redis | guoweikuang/weibo_project | 4 | python | def get_max_text_from_redis(category):
' 获取一次聚类后的最大数量的类.\n\n :param category:\n :return:\n '
max_num = 0
read_client = redis_client()
max_key = (K_CLUSTER % (category, 1))
for i in range(1, 15):
key_name = (K_CLUSTER % (category, i))
if (read_client.llen(key_name) > max_num):
max_num = read_client.llen(key_name)
max_key = key_name
rows = read_client.lrange(max_key, 0, (- 1))
return rows[::(- 1)] | def get_max_text_from_redis(category):
' 获取一次聚类后的最大数量的类.\n\n :param category:\n :return:\n '
max_num = 0
read_client = redis_client()
max_key = (K_CLUSTER % (category, 1))
for i in range(1, 15):
key_name = (K_CLUSTER % (category, i))
if (read_client.llen(key_name) > max_num):
max_num = read_client.llen(key_name)
max_key = key_name
rows = read_client.lrange(max_key, 0, (- 1))
return rows[::(- 1)]<|docstring|>获取一次聚类后的最大数量的类.
:param category:
:return:<|endoftext|> |
1e99de84fc36c27f7d6e87f299f6344f1a7617d98b06babba42b5c08a88306eb | def run_second_cluster():
' 二次聚类\n\n :param key_name:\n :return:\n '
categories = get_categorys()
for category in categories:
results = get_max_text_from_redis(category[:(- 4)])
if (not results):
continue
results = [row.decode('utf-8').split('\t') for row in results]
if (len(results) <= 30):
k = 2
else:
k = 4
vsm_name = (category[:(- 4)] + ':second')
texts = run_build_vsm_by_texts(results, vsm_name=vsm_name)
labels = run_kmeans_by_scikit(k=k, vsm_name=vsm_name)
classify_k_cluster_to_redis(labels=labels, texts=texts, category=category[:(- 4)], db=1) | 二次聚类
:param key_name:
:return: | utils.py | run_second_cluster | guoweikuang/weibo_project | 4 | python | def run_second_cluster():
' 二次聚类\n\n :param key_name:\n :return:\n '
categories = get_categorys()
for category in categories:
results = get_max_text_from_redis(category[:(- 4)])
if (not results):
continue
results = [row.decode('utf-8').split('\t') for row in results]
if (len(results) <= 30):
k = 2
else:
k = 4
vsm_name = (category[:(- 4)] + ':second')
texts = run_build_vsm_by_texts(results, vsm_name=vsm_name)
labels = run_kmeans_by_scikit(k=k, vsm_name=vsm_name)
classify_k_cluster_to_redis(labels=labels, texts=texts, category=category[:(- 4)], db=1) | def run_second_cluster():
' 二次聚类\n\n :param key_name:\n :return:\n '
categories = get_categorys()
for category in categories:
results = get_max_text_from_redis(category[:(- 4)])
if (not results):
continue
results = [row.decode('utf-8').split('\t') for row in results]
if (len(results) <= 30):
k = 2
else:
k = 4
vsm_name = (category[:(- 4)] + ':second')
texts = run_build_vsm_by_texts(results, vsm_name=vsm_name)
labels = run_kmeans_by_scikit(k=k, vsm_name=vsm_name)
classify_k_cluster_to_redis(labels=labels, texts=texts, category=category[:(- 4)], db=1)<|docstring|>二次聚类
:param key_name:
:return:<|endoftext|> |
65dcd3f0cb365827025dee6fdf3df15171d6afbc2acf51744875f72c1023b103 | def run_hot_topic(db=1, hot_db=2, hot_type='first'):
' 获取各分类热点话题热度值.\n\n :return:\n '
categorys = get_categorys()
for category in categorys:
topic = HotTopic(db=db, hot_db=hot_db)
category = category[:(- 4)]
if (hot_type == 'first'):
topic.get_first_cluster_hot(category)
else:
topic.get_second_cluster_hot(category) | 获取各分类热点话题热度值.
:return: | utils.py | run_hot_topic | guoweikuang/weibo_project | 4 | python | def run_hot_topic(db=1, hot_db=2, hot_type='first'):
' 获取各分类热点话题热度值.\n\n :return:\n '
categorys = get_categorys()
for category in categorys:
topic = HotTopic(db=db, hot_db=hot_db)
category = category[:(- 4)]
if (hot_type == 'first'):
topic.get_first_cluster_hot(category)
else:
topic.get_second_cluster_hot(category) | def run_hot_topic(db=1, hot_db=2, hot_type='first'):
' 获取各分类热点话题热度值.\n\n :return:\n '
categorys = get_categorys()
for category in categorys:
topic = HotTopic(db=db, hot_db=hot_db)
category = category[:(- 4)]
if (hot_type == 'first'):
topic.get_first_cluster_hot(category)
else:
topic.get_second_cluster_hot(category)<|docstring|>获取各分类热点话题热度值.
:return:<|endoftext|> |
f4c9c66e1a030021a7041067d829f24cd86f47d97b6b7bde9c189bf1a015f811 | def run_first_cluster_hot_topic():
' 整个聚类过程包括热度计算等.\n\n :return:\n '
run_hot_topic(db=0, hot_db=1) | 整个聚类过程包括热度计算等.
:return: | utils.py | run_first_cluster_hot_topic | guoweikuang/weibo_project | 4 | python | def run_first_cluster_hot_topic():
' 整个聚类过程包括热度计算等.\n\n :return:\n '
run_hot_topic(db=0, hot_db=1) | def run_first_cluster_hot_topic():
' 整个聚类过程包括热度计算等.\n\n :return:\n '
run_hot_topic(db=0, hot_db=1)<|docstring|>整个聚类过程包括热度计算等.
:return:<|endoftext|> |
15923ef0c1c89770450f446b55373ced6095707e9643a4c4626341062c28dbe1 | def run_second_cluster_hot_topic(db=1, hot_db=2):
'\n\n :param db:\n :param hot_db:\n :return:\n '
run_hot_topic(db=db, hot_db=hot_db, hot_type='second') | :param db:
:param hot_db:
:return: | utils.py | run_second_cluster_hot_topic | guoweikuang/weibo_project | 4 | python | def run_second_cluster_hot_topic(db=1, hot_db=2):
'\n\n :param db:\n :param hot_db:\n :return:\n '
run_hot_topic(db=db, hot_db=hot_db, hot_type='second') | def run_second_cluster_hot_topic(db=1, hot_db=2):
'\n\n :param db:\n :param hot_db:\n :return:\n '
run_hot_topic(db=db, hot_db=hot_db, hot_type='second')<|docstring|>:param db:
:param hot_db:
:return:<|endoftext|> |
b029705234d79c410c3c40a55bc3689ca4461c1a9c658fe4628cefbb4f5f5b2f | def run_cluster(start, end, k=7):
' 旧数据库数据全套热点话题流程， test.\n\n :param start:\n :param end:\n :param k:\n :return:\n '
end_time = arrow.get('2016-10-30')
rows = read_text_old_mysql(end_time, days=20, database='weibo')
rows = run_build_vsm_by_texts(texts=rows, vsm_name='total')
data_set = numpy.mat(load_data_set(vsm_name='total'))
k = find_optimal_k_value(data_set)
print(k)
labels = run_kmeans_by_scikit(k=k, vsm_name='total')
classify_k_cluster_to_file(labels=labels, texts=rows)
classify_k_cluster_to_redis(labels=labels, texts=rows)
topic = HotTopic(db=0, hot_db=1)
topic.get_cluster_hot(k)
run_draw_cluster_chart(db=1)
run_keywrod_barh(db=1) | 旧数据库数据全套热点话题流程， test.
:param start:
:param end:
:param k:
:return: | utils.py | run_cluster | guoweikuang/weibo_project | 4 | python | def run_cluster(start, end, k=7):
' 旧数据库数据全套热点话题流程， test.\n\n :param start:\n :param end:\n :param k:\n :return:\n '
end_time = arrow.get('2016-10-30')
rows = read_text_old_mysql(end_time, days=20, database='weibo')
rows = run_build_vsm_by_texts(texts=rows, vsm_name='total')
data_set = numpy.mat(load_data_set(vsm_name='total'))
k = find_optimal_k_value(data_set)
print(k)
labels = run_kmeans_by_scikit(k=k, vsm_name='total')
classify_k_cluster_to_file(labels=labels, texts=rows)
classify_k_cluster_to_redis(labels=labels, texts=rows)
topic = HotTopic(db=0, hot_db=1)
topic.get_cluster_hot(k)
run_draw_cluster_chart(db=1)
run_keywrod_barh(db=1) | def run_cluster(start, end, k=7):
' 旧数据库数据全套热点话题流程， test.\n\n :param start:\n :param end:\n :param k:\n :return:\n '
end_time = arrow.get('2016-10-30')
rows = read_text_old_mysql(end_time, days=20, database='weibo')
rows = run_build_vsm_by_texts(texts=rows, vsm_name='total')
data_set = numpy.mat(load_data_set(vsm_name='total'))
k = find_optimal_k_value(data_set)
print(k)
labels = run_kmeans_by_scikit(k=k, vsm_name='total')
classify_k_cluster_to_file(labels=labels, texts=rows)
classify_k_cluster_to_redis(labels=labels, texts=rows)
topic = HotTopic(db=0, hot_db=1)
topic.get_cluster_hot(k)
run_draw_cluster_chart(db=1)
run_keywrod_barh(db=1)<|docstring|>旧数据库数据全套热点话题流程， test.
:param start:
:param end:
:param k:
:return:<|endoftext|> |
1a45e21fdf59ebd4bd2d19fa638a1473f136455b660b79a2726a4ad806d21fe0 | def run_all_process(start_time, end_time):
'\n\n :param start_time:\n :param end_time:\n :return:\n '
start = arrow.get(start_time, 'YYYY-MM-DD').date()
end = arrow.get(end_time, 'YYYY-MM-DD').date()
rows = get_text_from_mysql('content', start_time=start, end_time=end)
run_classify_text(rows)
run_first_cluster('1', '1') | :param start_time:
:param end_time:
:return: | utils.py | run_all_process | guoweikuang/weibo_project | 4 | python | def run_all_process(start_time, end_time):
'\n\n :param start_time:\n :param end_time:\n :return:\n '
start = arrow.get(start_time, 'YYYY-MM-DD').date()
end = arrow.get(end_time, 'YYYY-MM-DD').date()
rows = get_text_from_mysql('content', start_time=start, end_time=end)
run_classify_text(rows)
run_first_cluster('1', '1') | def run_all_process(start_time, end_time):
'\n\n :param start_time:\n :param end_time:\n :return:\n '
start = arrow.get(start_time, 'YYYY-MM-DD').date()
end = arrow.get(end_time, 'YYYY-MM-DD').date()
rows = get_text_from_mysql('content', start_time=start, end_time=end)
run_classify_text(rows)
run_first_cluster('1', '1')<|docstring|>:param start_time:
:param end_time:
:return:<|endoftext|> |
0d771e78b5cd14fee65a9c87b2b69fc51054869d576fdabce3e271755265c94f | def run_new_all_process(start_time, end_time, k):
' 新数据库热点话题发现流程. （一次聚类）\n\n :param start_time:\n :param end_time:\n :param k:\n :return:\n '
if isinstance(start_time, date):
start = start_time
else:
start = arrow.get(start_time, 'YYYY-MM-DD').date()
if isinstance(end_time, date):
end = end_time
else:
end = arrow.get(end_time, 'YYYY-MM-DD').date()
rows = get_text_from_mysql('content', start_time=start, end_time=end)
run_classify_text(rows)
run_classify(corpus_path, seg_path, bag_path, test_bag_path, test_corpus_path, test_seg_path)
run_first_cluster('1', '1')
run_first_cluster_hot_topic()
run_draw_chart(db=1)
run_draw_top_keyword_barh(db=1) | 新数据库热点话题发现流程. （一次聚类）
:param start_time:
:param end_time:
:param k:
:return: | utils.py | run_new_all_process | guoweikuang/weibo_project | 4 | python | def run_new_all_process(start_time, end_time, k):
' 新数据库热点话题发现流程. （一次聚类）\n\n :param start_time:\n :param end_time:\n :param k:\n :return:\n '
if isinstance(start_time, date):
start = start_time
else:
start = arrow.get(start_time, 'YYYY-MM-DD').date()
if isinstance(end_time, date):
end = end_time
else:
end = arrow.get(end_time, 'YYYY-MM-DD').date()
rows = get_text_from_mysql('content', start_time=start, end_time=end)
run_classify_text(rows)
run_classify(corpus_path, seg_path, bag_path, test_bag_path, test_corpus_path, test_seg_path)
run_first_cluster('1', '1')
run_first_cluster_hot_topic()
run_draw_chart(db=1)
run_draw_top_keyword_barh(db=1) | def run_new_all_process(start_time, end_time, k):
' 新数据库热点话题发现流程. （一次聚类）\n\n :param start_time:\n :param end_time:\n :param k:\n :return:\n '
if isinstance(start_time, date):
start = start_time
else:
start = arrow.get(start_time, 'YYYY-MM-DD').date()
if isinstance(end_time, date):
end = end_time
else:
end = arrow.get(end_time, 'YYYY-MM-DD').date()
rows = get_text_from_mysql('content', start_time=start, end_time=end)
run_classify_text(rows)
run_classify(corpus_path, seg_path, bag_path, test_bag_path, test_corpus_path, test_seg_path)
run_first_cluster('1', '1')
run_first_cluster_hot_topic()
run_draw_chart(db=1)
run_draw_top_keyword_barh(db=1)<|docstring|>新数据库热点话题发现流程. （一次聚类）
:param start_time:
:param end_time:
:param k:
:return:<|endoftext|> |
c04d9fa153f52a6089437533d37fd89de6ee4eb60fd1ac4146bba265152cc269 | def run_old_second_all_process(start_time, end_time):
'\n 所有流程汇总. test 使用\n :param start_time:\n :param end_time:\n :return:\n '
rows = read_text_old_mysql(end_time, days=30, database='weibo')
run_classify_text(rows)
run_classify(corpus_path, seg_path, bag_path, test_bag_path, test_corpus_path, test_seg_path)
run_first_cluster('1', '1')
run_second_cluster()
run_second_cluster_hot_topic(db=1, hot_db=2)
run_draw_chart(db=2)
run_draw_top_keyword_barh(db=2, draw_type='second') | 所有流程汇总. test 使用
:param start_time:
:param end_time:
:return: | utils.py | run_old_second_all_process | guoweikuang/weibo_project | 4 | python | def run_old_second_all_process(start_time, end_time):
'\n 所有流程汇总. test 使用\n :param start_time:\n :param end_time:\n :return:\n '
rows = read_text_old_mysql(end_time, days=30, database='weibo')
run_classify_text(rows)
run_classify(corpus_path, seg_path, bag_path, test_bag_path, test_corpus_path, test_seg_path)
run_first_cluster('1', '1')
run_second_cluster()
run_second_cluster_hot_topic(db=1, hot_db=2)
run_draw_chart(db=2)
run_draw_top_keyword_barh(db=2, draw_type='second') | def run_old_second_all_process(start_time, end_time):
'\n 所有流程汇总. test 使用\n :param start_time:\n :param end_time:\n :return:\n '
rows = read_text_old_mysql(end_time, days=30, database='weibo')
run_classify_text(rows)
run_classify(corpus_path, seg_path, bag_path, test_bag_path, test_corpus_path, test_seg_path)
run_first_cluster('1', '1')
run_second_cluster()
run_second_cluster_hot_topic(db=1, hot_db=2)
run_draw_chart(db=2)
run_draw_top_keyword_barh(db=2, draw_type='second')<|docstring|>所有流程汇总. test 使用
:param start_time:
:param end_time:
:return:<|endoftext|> |
f1bb611f1dfdd12f835fde076ca52e6ed903449011e5b43e12d68a513973c45a | def run_old_all_process(end_time):
'\n\n :param end_time:\n :return:\n '
rows = read_text_old_mysql(end_time, days=30, database='weibo')
save_to_file('old_mysql', rows)
run_classify_text(rows)
run_classify(corpus_path, seg_path, bag_path, test_bag_path, test_corpus_path, test_seg_path)
run_first_cluster('1', '1')
run_hot_topic(db=0, hot_db=1)
run_draw_chart(db=1)
run_draw_top_keyword_barh(db=1) | :param end_time:
:return: | utils.py | run_old_all_process | guoweikuang/weibo_project | 4 | python | def run_old_all_process(end_time):
'\n\n :param end_time:\n :return:\n '
rows = read_text_old_mysql(end_time, days=30, database='weibo')
save_to_file('old_mysql', rows)
run_classify_text(rows)
run_classify(corpus_path, seg_path, bag_path, test_bag_path, test_corpus_path, test_seg_path)
run_first_cluster('1', '1')
run_hot_topic(db=0, hot_db=1)
run_draw_chart(db=1)
run_draw_top_keyword_barh(db=1) | def run_old_all_process(end_time):
'\n\n :param end_time:\n :return:\n '
rows = read_text_old_mysql(end_time, days=30, database='weibo')
save_to_file('old_mysql', rows)
run_classify_text(rows)
run_classify(corpus_path, seg_path, bag_path, test_bag_path, test_corpus_path, test_seg_path)
run_first_cluster('1', '1')
run_hot_topic(db=0, hot_db=1)
run_draw_chart(db=1)
run_draw_top_keyword_barh(db=1)<|docstring|>:param end_time:
:return:<|endoftext|> |
91805efe6c8c1419fec74b31961451070aa4e03b3184ec4ba82376dbf56055e0 | def create_multi_density(data, fields, name):
'\n create plot which compare the density of the input fields\n :param data: pandas dataframe\n :param fields: dataframe fields name to plot thier density\n :param name: plot name and filename for the output\n '
if (type(fields) == type('')):
fields = [fields]
plt.figure(figsize=(8, 4))
for f in range(len(fields)):
clm = list(data[fields[f]])
sns.kdeplot(clm, color=COLORS[(f % len(COLORS))], label=fields[f])
plt.title(name)
plt.xlabel(('values of: ' + ', '.join(fields)))
plt.ylabel('density')
plt.legend(loc='upper left')
plt.savefig((name + '.png'))
plt.show() | create plot which compare the density of the input fields
:param data: pandas dataframe
:param fields: dataframe fields name to plot thier density
:param name: plot name and filename for the output | multi_density.py | create_multi_density | EtzionR/create-multi-smooth-density-plot | 1 | python | def create_multi_density(data, fields, name):
'\n create plot which compare the density of the input fields\n :param data: pandas dataframe\n :param fields: dataframe fields name to plot thier density\n :param name: plot name and filename for the output\n '
if (type(fields) == type()):
fields = [fields]
plt.figure(figsize=(8, 4))
for f in range(len(fields)):
clm = list(data[fields[f]])
sns.kdeplot(clm, color=COLORS[(f % len(COLORS))], label=fields[f])
plt.title(name)
plt.xlabel(('values of: ' + ', '.join(fields)))
plt.ylabel('density')
plt.legend(loc='upper left')
plt.savefig((name + '.png'))
plt.show() | def create_multi_density(data, fields, name):
'\n create plot which compare the density of the input fields\n :param data: pandas dataframe\n :param fields: dataframe fields name to plot thier density\n :param name: plot name and filename for the output\n '
if (type(fields) == type()):
fields = [fields]
plt.figure(figsize=(8, 4))
for f in range(len(fields)):
clm = list(data[fields[f]])
sns.kdeplot(clm, color=COLORS[(f % len(COLORS))], label=fields[f])
plt.title(name)
plt.xlabel(('values of: ' + ', '.join(fields)))
plt.ylabel('density')
plt.legend(loc='upper left')
plt.savefig((name + '.png'))
plt.show()<|docstring|>create plot which compare the density of the input fields
:param data: pandas dataframe
:param fields: dataframe fields name to plot thier density
:param name: plot name and filename for the output<|endoftext|> |
95e075c71f95bed57151108d9f087eea0657508fdb0fd9672e615a1b040b7b57 | def __init__(self, env: Environment, name: str, configuration: Dict[(str, Any)]):
'Initialization'
super().__init__(env, name, configuration, self.execute())
self._efficiency = configuration.get('efficiency', 0.95)
self._refractive_index = configuration.get('refractive_index', 1.47)
self.env.process(self.run()) | Initialization | source/astroNS/nodes/network/fiber_terminal.py | __init__ | pyastroNS/astroNS | 0 | python | def __init__(self, env: Environment, name: str, configuration: Dict[(str, Any)]):
super().__init__(env, name, configuration, self.execute())
self._efficiency = configuration.get('efficiency', 0.95)
self._refractive_index = configuration.get('refractive_index', 1.47)
self.env.process(self.run()) | def __init__(self, env: Environment, name: str, configuration: Dict[(str, Any)]):
super().__init__(env, name, configuration, self.execute())
self._efficiency = configuration.get('efficiency', 0.95)
self._refractive_index = configuration.get('refractive_index', 1.47)
self.env.process(self.run())<|docstring|>Initialization<|endoftext|> |
2871061dc67f02205a5af62ca51d88ac16b8db44ae00433d66012883a5ec6709 | @property
def efficiency(self):
'Efficiency of cabling between two nodes, used to artifically inflate\n the actual distance the fiber optic cable\n :param efficiency: Cabling efficiency, a value of 1 would mean that the\n cable flows directly between the two nodes with no deviations\n\n :return: float\n '
return float(self._efficiency) | Efficiency of cabling between two nodes, used to artifically inflate
the actual distance the fiber optic cable
:param efficiency: Cabling efficiency, a value of 1 would mean that the
cable flows directly between the two nodes with no deviations
:return: float | source/astroNS/nodes/network/fiber_terminal.py | efficiency | pyastroNS/astroNS | 0 | python | @property
def efficiency(self):
'Efficiency of cabling between two nodes, used to artifically inflate\n the actual distance the fiber optic cable\n :param efficiency: Cabling efficiency, a value of 1 would mean that the\n cable flows directly between the two nodes with no deviations\n\n :return: float\n '
return float(self._efficiency) | @property
def efficiency(self):
'Efficiency of cabling between two nodes, used to artifically inflate\n the actual distance the fiber optic cable\n :param efficiency: Cabling efficiency, a value of 1 would mean that the\n cable flows directly between the two nodes with no deviations\n\n :return: float\n '
return float(self._efficiency)<|docstring|>Efficiency of cabling between two nodes, used to artifically inflate
the actual distance the fiber optic cable
:param efficiency: Cabling efficiency, a value of 1 would mean that the
cable flows directly between the two nodes with no deviations
:return: float<|endoftext|> |
e1a981da6fcb75f785be696034a30bf788fa934e82bbe69c9f15ea0254981b7e | @property
def refractive_index(self):
'Refractive index is the slowdown of the speed of light through the\n fiber material compared to free space\n :param refractive_index: Refractive index of fiber material to slow\n down speed of light\n :return: float\n '
return float(self._refractive_index) | Refractive index is the slowdown of the speed of light through the
fiber material compared to free space
:param refractive_index: Refractive index of fiber material to slow
down speed of light
:return: float | source/astroNS/nodes/network/fiber_terminal.py | refractive_index | pyastroNS/astroNS | 0 | python | @property
def refractive_index(self):
'Refractive index is the slowdown of the speed of light through the\n fiber material compared to free space\n :param refractive_index: Refractive index of fiber material to slow\n down speed of light\n :return: float\n '
return float(self._refractive_index) | @property
def refractive_index(self):
'Refractive index is the slowdown of the speed of light through the\n fiber material compared to free space\n :param refractive_index: Refractive index of fiber material to slow\n down speed of light\n :return: float\n '
return float(self._refractive_index)<|docstring|>Refractive index is the slowdown of the speed of light through the
fiber material compared to free space
:param refractive_index: Refractive index of fiber material to slow
down speed of light
:return: float<|endoftext|> |
b968a22ab52a763e141d1223a88bfdc3405e50e205bd1e860743182f49c865f4 | def execute(self):
'Execute function, part of simpy functionality'
delay: float = 0.0
processing_time: float = delay
data_out_list: List[Tuple] = []
while True:
data_in = (yield (delay, processing_time, data_out_list))
if data_in:
msg = data_in.copy()
if ('fiber_transmit_location' in msg):
try:
rcvr_position = self.get_location(self.env.now)[0][:2]
except AttributeError:
raise AttributeError('No Propagator was attached.')
trans_position = msg['fiber_transmit_location'][0][:2]
d = geodesic(rcvr_position, trans_position).km
v = (c.to((u.km / u.s)).value / self._refractive_index)
t = ((d / self._efficiency) / v)
print((self.log_prefix(id) + 'Receiving at fiber location -- Message delay was {}'.format(t)))
msg.pop('fiber_transmit_location')
delay = t
processing_time = t
data_out_list = [msg]
else:
msg['fiber_transmit_location'] = self.get_location(self.env.now)
print((self.log_prefix(id) + 'Transmitting from Fiber Location -- {}'.format(msg['fiber_transmit_location'])))
delay = 0
processing_time = 0
data_out_list = [msg] | Execute function, part of simpy functionality | source/astroNS/nodes/network/fiber_terminal.py | execute | pyastroNS/astroNS | 0 | python | def execute(self):
delay: float = 0.0
processing_time: float = delay
data_out_list: List[Tuple] = []
while True:
data_in = (yield (delay, processing_time, data_out_list))
if data_in:
msg = data_in.copy()
if ('fiber_transmit_location' in msg):
try:
rcvr_position = self.get_location(self.env.now)[0][:2]
except AttributeError:
raise AttributeError('No Propagator was attached.')
trans_position = msg['fiber_transmit_location'][0][:2]
d = geodesic(rcvr_position, trans_position).km
v = (c.to((u.km / u.s)).value / self._refractive_index)
t = ((d / self._efficiency) / v)
print((self.log_prefix(id) + 'Receiving at fiber location -- Message delay was {}'.format(t)))
msg.pop('fiber_transmit_location')
delay = t
processing_time = t
data_out_list = [msg]
else:
msg['fiber_transmit_location'] = self.get_location(self.env.now)
print((self.log_prefix(id) + 'Transmitting from Fiber Location -- {}'.format(msg['fiber_transmit_location'])))
delay = 0
processing_time = 0
data_out_list = [msg] | def execute(self):
delay: float = 0.0
processing_time: float = delay
data_out_list: List[Tuple] = []
while True:
data_in = (yield (delay, processing_time, data_out_list))
if data_in:
msg = data_in.copy()
if ('fiber_transmit_location' in msg):
try:
rcvr_position = self.get_location(self.env.now)[0][:2]
except AttributeError:
raise AttributeError('No Propagator was attached.')
trans_position = msg['fiber_transmit_location'][0][:2]
d = geodesic(rcvr_position, trans_position).km
v = (c.to((u.km / u.s)).value / self._refractive_index)
t = ((d / self._efficiency) / v)
print((self.log_prefix(id) + 'Receiving at fiber location -- Message delay was {}'.format(t)))
msg.pop('fiber_transmit_location')
delay = t
processing_time = t
data_out_list = [msg]
else:
msg['fiber_transmit_location'] = self.get_location(self.env.now)
print((self.log_prefix(id) + 'Transmitting from Fiber Location -- {}'.format(msg['fiber_transmit_location'])))
delay = 0
processing_time = 0
data_out_list = [msg]<|docstring|>Execute function, part of simpy functionality<|endoftext|> |
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