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stringlengths 64
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stringlengths 23
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| docstring
stringlengths 1
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| path
stringlengths 4
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| name
stringlengths 1
115
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stringlengths 7
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value | body_without_docstring
stringlengths 14
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stringlengths 45
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|
|---|---|---|---|---|---|---|---|---|---|
3e10350d0beb1b02fe413faff599ae8968edd34fd0881da228b00db0f088db8e
|
def set_cookie(key, value, days=7):
'Set cookie'
_init_cookie_client()
run_js('setCookie(key, value, days)', key=key, value=value, days=days)
|
Set cookie
|
pywebio_battery/web.py
|
set_cookie
|
pywebio/pywebio-battery
| 2
|
python
|
def set_cookie(key, value, days=7):
_init_cookie_client()
run_js('setCookie(key, value, days)', key=key, value=value, days=days)
|
def set_cookie(key, value, days=7):
_init_cookie_client()
run_js('setCookie(key, value, days)', key=key, value=value, days=days)<|docstring|>Set cookie<|endoftext|>
|
99056e696ef815400390f8c60fb6b7956c2990daf582e3c64224737da7e7c7dd
|
def get_cookie(key):
'Get cookie'
_init_cookie_client()
return eval_js('getCookie(key)', key=key)
|
Get cookie
|
pywebio_battery/web.py
|
get_cookie
|
pywebio/pywebio-battery
| 2
|
python
|
def get_cookie(key):
_init_cookie_client()
return eval_js('getCookie(key)', key=key)
|
def get_cookie(key):
_init_cookie_client()
return eval_js('getCookie(key)', key=key)<|docstring|>Get cookie<|endoftext|>
|
2552a1eb855e91b6d89a081d5dad2272565e8293cb4f1e4a1247495a311a594b
|
@router.post('/uploadfile', status_code=status.HTTP_201_CREATED)
async def create_upload_file(request: Request, file: UploadFile=File(...)):
'\n File upload route\n '
(await authenticate(request))
if (not upload_file(file, os.path.join(settings.MEDIA_UPLOAD_LOCATION, 'file'), settings.ALLOWED_IMAGE_TYPES, settings.FILE_SERVICE)):
raise HTTPException(detail='file could not be uploaded', status_code=status.HTTP_500_INTERNAL_SERVER_ERROR)
return JSONResponse(content=(('The file ' + file.filename) + ' was uploaded successfully'), status_code=status.HTTP_201_CREATED)
|
File upload route
|
routers/media_routes.py
|
create_upload_file
|
olubiyiontheweb/malliva
| 0
|
python
|
@router.post('/uploadfile', status_code=status.HTTP_201_CREATED)
async def create_upload_file(request: Request, file: UploadFile=File(...)):
'\n \n '
(await authenticate(request))
if (not upload_file(file, os.path.join(settings.MEDIA_UPLOAD_LOCATION, 'file'), settings.ALLOWED_IMAGE_TYPES, settings.FILE_SERVICE)):
raise HTTPException(detail='file could not be uploaded', status_code=status.HTTP_500_INTERNAL_SERVER_ERROR)
return JSONResponse(content=(('The file ' + file.filename) + ' was uploaded successfully'), status_code=status.HTTP_201_CREATED)
|
@router.post('/uploadfile', status_code=status.HTTP_201_CREATED)
async def create_upload_file(request: Request, file: UploadFile=File(...)):
'\n \n '
(await authenticate(request))
if (not upload_file(file, os.path.join(settings.MEDIA_UPLOAD_LOCATION, 'file'), settings.ALLOWED_IMAGE_TYPES, settings.FILE_SERVICE)):
raise HTTPException(detail='file could not be uploaded', status_code=status.HTTP_500_INTERNAL_SERVER_ERROR)
return JSONResponse(content=(('The file ' + file.filename) + ' was uploaded successfully'), status_code=status.HTTP_201_CREATED)<|docstring|>File upload route<|endoftext|>
|
b45b7257cb347a749c99d49f54805573b2157375d3995c5931451007403639ce
|
@router.get('/{file_path:path}')
async def read_files(request: Request, file_path: str):
'read files '
logging.info('TODO: we may need to allow only authenticated user to access files for security and cost reasons')
(await get_db_name(request))
try:
with open(os.path.join(settings.MEDIA_UPLOAD_LOCATION, file_path), 'r') as file:
return FileResponse(path=os.path.join(settings.MEDIA_UPLOAD_LOCATION, file_path))
except:
return JSONResponse(content='File does not exist', status_code=status.HTTP_404_NOT_FOUND)
|
read files
|
routers/media_routes.py
|
read_files
|
olubiyiontheweb/malliva
| 0
|
python
|
@router.get('/{file_path:path}')
async def read_files(request: Request, file_path: str):
' '
logging.info('TODO: we may need to allow only authenticated user to access files for security and cost reasons')
(await get_db_name(request))
try:
with open(os.path.join(settings.MEDIA_UPLOAD_LOCATION, file_path), 'r') as file:
return FileResponse(path=os.path.join(settings.MEDIA_UPLOAD_LOCATION, file_path))
except:
return JSONResponse(content='File does not exist', status_code=status.HTTP_404_NOT_FOUND)
|
@router.get('/{file_path:path}')
async def read_files(request: Request, file_path: str):
' '
logging.info('TODO: we may need to allow only authenticated user to access files for security and cost reasons')
(await get_db_name(request))
try:
with open(os.path.join(settings.MEDIA_UPLOAD_LOCATION, file_path), 'r') as file:
return FileResponse(path=os.path.join(settings.MEDIA_UPLOAD_LOCATION, file_path))
except:
return JSONResponse(content='File does not exist', status_code=status.HTTP_404_NOT_FOUND)<|docstring|>read files<|endoftext|>
|
e64d152b6330a9d8a6696130ab4ef4b848f3cd0edd17e1d9c7db40e3a670c67b
|
def minimum_part_size(size_in_bytes, default_part_size=DEFAULT_PART_SIZE):
'Calculate the minimum part size needed for a multipart upload.\n\n Glacier allows a maximum of 10,000 parts per upload. It also\n states that the maximum archive size is 10,000 * 4 GB, which means\n the part size can range from 1MB to 4GB (provided it is one 1MB\n multiplied by a power of 2).\n\n This function will compute what the minimum part size must be in\n order to upload a file of size ``size_in_bytes``.\n\n It will first check if ``default_part_size`` is sufficient for\n a part size given the ``size_in_bytes``. If this is not the case,\n then the smallest part size than can accomodate a file of size\n ``size_in_bytes`` will be returned.\n\n If the file size is greater than the maximum allowed archive\n size of 10,000 * 4GB, a ``ValueError`` will be raised.\n\n '
part_size = _MEGABYTE
if ((default_part_size * MAXIMUM_NUMBER_OF_PARTS) < size_in_bytes):
if (size_in_bytes > ((4096 * _MEGABYTE) * 10000)):
raise ValueError(('File size too large: %s' % size_in_bytes))
min_part_size = (size_in_bytes / 10000)
power = 3
while (part_size < min_part_size):
part_size = math.ldexp(_MEGABYTE, power)
power += 1
part_size = int(part_size)
else:
part_size = default_part_size
return part_size
|
Calculate the minimum part size needed for a multipart upload.
Glacier allows a maximum of 10,000 parts per upload. It also
states that the maximum archive size is 10,000 * 4 GB, which means
the part size can range from 1MB to 4GB (provided it is one 1MB
multiplied by a power of 2).
This function will compute what the minimum part size must be in
order to upload a file of size ``size_in_bytes``.
It will first check if ``default_part_size`` is sufficient for
a part size given the ``size_in_bytes``. If this is not the case,
then the smallest part size than can accomodate a file of size
``size_in_bytes`` will be returned.
If the file size is greater than the maximum allowed archive
size of 10,000 * 4GB, a ``ValueError`` will be raised.
|
boto/glacier/utils.py
|
minimum_part_size
|
khagler/boto
| 5,079
|
python
|
def minimum_part_size(size_in_bytes, default_part_size=DEFAULT_PART_SIZE):
'Calculate the minimum part size needed for a multipart upload.\n\n Glacier allows a maximum of 10,000 parts per upload. It also\n states that the maximum archive size is 10,000 * 4 GB, which means\n the part size can range from 1MB to 4GB (provided it is one 1MB\n multiplied by a power of 2).\n\n This function will compute what the minimum part size must be in\n order to upload a file of size ``size_in_bytes``.\n\n It will first check if ``default_part_size`` is sufficient for\n a part size given the ``size_in_bytes``. If this is not the case,\n then the smallest part size than can accomodate a file of size\n ``size_in_bytes`` will be returned.\n\n If the file size is greater than the maximum allowed archive\n size of 10,000 * 4GB, a ``ValueError`` will be raised.\n\n '
part_size = _MEGABYTE
if ((default_part_size * MAXIMUM_NUMBER_OF_PARTS) < size_in_bytes):
if (size_in_bytes > ((4096 * _MEGABYTE) * 10000)):
raise ValueError(('File size too large: %s' % size_in_bytes))
min_part_size = (size_in_bytes / 10000)
power = 3
while (part_size < min_part_size):
part_size = math.ldexp(_MEGABYTE, power)
power += 1
part_size = int(part_size)
else:
part_size = default_part_size
return part_size
|
def minimum_part_size(size_in_bytes, default_part_size=DEFAULT_PART_SIZE):
'Calculate the minimum part size needed for a multipart upload.\n\n Glacier allows a maximum of 10,000 parts per upload. It also\n states that the maximum archive size is 10,000 * 4 GB, which means\n the part size can range from 1MB to 4GB (provided it is one 1MB\n multiplied by a power of 2).\n\n This function will compute what the minimum part size must be in\n order to upload a file of size ``size_in_bytes``.\n\n It will first check if ``default_part_size`` is sufficient for\n a part size given the ``size_in_bytes``. If this is not the case,\n then the smallest part size than can accomodate a file of size\n ``size_in_bytes`` will be returned.\n\n If the file size is greater than the maximum allowed archive\n size of 10,000 * 4GB, a ``ValueError`` will be raised.\n\n '
part_size = _MEGABYTE
if ((default_part_size * MAXIMUM_NUMBER_OF_PARTS) < size_in_bytes):
if (size_in_bytes > ((4096 * _MEGABYTE) * 10000)):
raise ValueError(('File size too large: %s' % size_in_bytes))
min_part_size = (size_in_bytes / 10000)
power = 3
while (part_size < min_part_size):
part_size = math.ldexp(_MEGABYTE, power)
power += 1
part_size = int(part_size)
else:
part_size = default_part_size
return part_size<|docstring|>Calculate the minimum part size needed for a multipart upload.
Glacier allows a maximum of 10,000 parts per upload. It also
states that the maximum archive size is 10,000 * 4 GB, which means
the part size can range from 1MB to 4GB (provided it is one 1MB
multiplied by a power of 2).
This function will compute what the minimum part size must be in
order to upload a file of size ``size_in_bytes``.
It will first check if ``default_part_size`` is sufficient for
a part size given the ``size_in_bytes``. If this is not the case,
then the smallest part size than can accomodate a file of size
``size_in_bytes`` will be returned.
If the file size is greater than the maximum allowed archive
size of 10,000 * 4GB, a ``ValueError`` will be raised.<|endoftext|>
|
b97bb20544e2ad9774129a247398394794d753702558d4ca4de9148ea83d5a10
|
def tree_hash(fo):
'\n Given a hash of each 1MB chunk (from chunk_hashes) this will hash\n together adjacent hashes until it ends up with one big one. So a\n tree of hashes.\n '
hashes = []
hashes.extend(fo)
while (len(hashes) > 1):
new_hashes = []
while True:
if (len(hashes) > 1):
first = hashes.pop(0)
second = hashes.pop(0)
new_hashes.append(hashlib.sha256((first + second)).digest())
elif (len(hashes) == 1):
only = hashes.pop(0)
new_hashes.append(only)
else:
break
hashes.extend(new_hashes)
return hashes[0]
|
Given a hash of each 1MB chunk (from chunk_hashes) this will hash
together adjacent hashes until it ends up with one big one. So a
tree of hashes.
|
boto/glacier/utils.py
|
tree_hash
|
khagler/boto
| 5,079
|
python
|
def tree_hash(fo):
'\n Given a hash of each 1MB chunk (from chunk_hashes) this will hash\n together adjacent hashes until it ends up with one big one. So a\n tree of hashes.\n '
hashes = []
hashes.extend(fo)
while (len(hashes) > 1):
new_hashes = []
while True:
if (len(hashes) > 1):
first = hashes.pop(0)
second = hashes.pop(0)
new_hashes.append(hashlib.sha256((first + second)).digest())
elif (len(hashes) == 1):
only = hashes.pop(0)
new_hashes.append(only)
else:
break
hashes.extend(new_hashes)
return hashes[0]
|
def tree_hash(fo):
'\n Given a hash of each 1MB chunk (from chunk_hashes) this will hash\n together adjacent hashes until it ends up with one big one. So a\n tree of hashes.\n '
hashes = []
hashes.extend(fo)
while (len(hashes) > 1):
new_hashes = []
while True:
if (len(hashes) > 1):
first = hashes.pop(0)
second = hashes.pop(0)
new_hashes.append(hashlib.sha256((first + second)).digest())
elif (len(hashes) == 1):
only = hashes.pop(0)
new_hashes.append(only)
else:
break
hashes.extend(new_hashes)
return hashes[0]<|docstring|>Given a hash of each 1MB chunk (from chunk_hashes) this will hash
together adjacent hashes until it ends up with one big one. So a
tree of hashes.<|endoftext|>
|
2f4e999547b21e4f9477b4a174c7d428b14b42c744c72a95e26bb7c0c48b828d
|
def compute_hashes_from_fileobj(fileobj, chunk_size=(1024 * 1024)):
'Compute the linear and tree hash from a fileobj.\n\n This function will compute the linear/tree hash of a fileobj\n in a single pass through the fileobj.\n\n :param fileobj: A file like object.\n\n :param chunk_size: The size of the chunks to use for the tree\n hash. This is also the buffer size used to read from\n `fileobj`.\n\n :rtype: tuple\n :return: A tuple of (linear_hash, tree_hash). Both hashes\n are returned in hex.\n\n '
if (six.PY3 and hasattr(fileobj, 'mode') and ('b' not in fileobj.mode)):
raise ValueError('File-like object must be opened in binary mode!')
linear_hash = hashlib.sha256()
chunks = []
chunk = fileobj.read(chunk_size)
while chunk:
if (not isinstance(chunk, bytes)):
chunk = chunk.encode((getattr(fileobj, 'encoding', '') or 'utf-8'))
linear_hash.update(chunk)
chunks.append(hashlib.sha256(chunk).digest())
chunk = fileobj.read(chunk_size)
if (not chunks):
chunks = [hashlib.sha256(b'').digest()]
return (linear_hash.hexdigest(), bytes_to_hex(tree_hash(chunks)))
|
Compute the linear and tree hash from a fileobj.
This function will compute the linear/tree hash of a fileobj
in a single pass through the fileobj.
:param fileobj: A file like object.
:param chunk_size: The size of the chunks to use for the tree
hash. This is also the buffer size used to read from
`fileobj`.
:rtype: tuple
:return: A tuple of (linear_hash, tree_hash). Both hashes
are returned in hex.
|
boto/glacier/utils.py
|
compute_hashes_from_fileobj
|
khagler/boto
| 5,079
|
python
|
def compute_hashes_from_fileobj(fileobj, chunk_size=(1024 * 1024)):
'Compute the linear and tree hash from a fileobj.\n\n This function will compute the linear/tree hash of a fileobj\n in a single pass through the fileobj.\n\n :param fileobj: A file like object.\n\n :param chunk_size: The size of the chunks to use for the tree\n hash. This is also the buffer size used to read from\n `fileobj`.\n\n :rtype: tuple\n :return: A tuple of (linear_hash, tree_hash). Both hashes\n are returned in hex.\n\n '
if (six.PY3 and hasattr(fileobj, 'mode') and ('b' not in fileobj.mode)):
raise ValueError('File-like object must be opened in binary mode!')
linear_hash = hashlib.sha256()
chunks = []
chunk = fileobj.read(chunk_size)
while chunk:
if (not isinstance(chunk, bytes)):
chunk = chunk.encode((getattr(fileobj, 'encoding', ) or 'utf-8'))
linear_hash.update(chunk)
chunks.append(hashlib.sha256(chunk).digest())
chunk = fileobj.read(chunk_size)
if (not chunks):
chunks = [hashlib.sha256(b).digest()]
return (linear_hash.hexdigest(), bytes_to_hex(tree_hash(chunks)))
|
def compute_hashes_from_fileobj(fileobj, chunk_size=(1024 * 1024)):
'Compute the linear and tree hash from a fileobj.\n\n This function will compute the linear/tree hash of a fileobj\n in a single pass through the fileobj.\n\n :param fileobj: A file like object.\n\n :param chunk_size: The size of the chunks to use for the tree\n hash. This is also the buffer size used to read from\n `fileobj`.\n\n :rtype: tuple\n :return: A tuple of (linear_hash, tree_hash). Both hashes\n are returned in hex.\n\n '
if (six.PY3 and hasattr(fileobj, 'mode') and ('b' not in fileobj.mode)):
raise ValueError('File-like object must be opened in binary mode!')
linear_hash = hashlib.sha256()
chunks = []
chunk = fileobj.read(chunk_size)
while chunk:
if (not isinstance(chunk, bytes)):
chunk = chunk.encode((getattr(fileobj, 'encoding', ) or 'utf-8'))
linear_hash.update(chunk)
chunks.append(hashlib.sha256(chunk).digest())
chunk = fileobj.read(chunk_size)
if (not chunks):
chunks = [hashlib.sha256(b).digest()]
return (linear_hash.hexdigest(), bytes_to_hex(tree_hash(chunks)))<|docstring|>Compute the linear and tree hash from a fileobj.
This function will compute the linear/tree hash of a fileobj
in a single pass through the fileobj.
:param fileobj: A file like object.
:param chunk_size: The size of the chunks to use for the tree
hash. This is also the buffer size used to read from
`fileobj`.
:rtype: tuple
:return: A tuple of (linear_hash, tree_hash). Both hashes
are returned in hex.<|endoftext|>
|
5337782b7e965160e9e0ab57e9efc212684954d2b63d329da25c7e495a66295a
|
def tree_hash_from_str(str_as_bytes):
'\n\n :type str_as_bytes: str\n :param str_as_bytes: The string for which to compute the tree hash.\n\n :rtype: str\n :return: The computed tree hash, returned as hex.\n\n '
return bytes_to_hex(tree_hash(chunk_hashes(str_as_bytes)))
|
:type str_as_bytes: str
:param str_as_bytes: The string for which to compute the tree hash.
:rtype: str
:return: The computed tree hash, returned as hex.
|
boto/glacier/utils.py
|
tree_hash_from_str
|
khagler/boto
| 5,079
|
python
|
def tree_hash_from_str(str_as_bytes):
'\n\n :type str_as_bytes: str\n :param str_as_bytes: The string for which to compute the tree hash.\n\n :rtype: str\n :return: The computed tree hash, returned as hex.\n\n '
return bytes_to_hex(tree_hash(chunk_hashes(str_as_bytes)))
|
def tree_hash_from_str(str_as_bytes):
'\n\n :type str_as_bytes: str\n :param str_as_bytes: The string for which to compute the tree hash.\n\n :rtype: str\n :return: The computed tree hash, returned as hex.\n\n '
return bytes_to_hex(tree_hash(chunk_hashes(str_as_bytes)))<|docstring|>:type str_as_bytes: str
:param str_as_bytes: The string for which to compute the tree hash.
:rtype: str
:return: The computed tree hash, returned as hex.<|endoftext|>
|
9aa49ee0797190c286045c37c3837761d99c90e7b3dfcd1e5b1cfd8cc0f544e7
|
@pytest.mark.tryfirst
def pytest_pyfunc_call(pyfuncitem):
'\n Run asyncio marked test functions in an event loop instead of a normal\n function call.\n '
if ('run_loop' in pyfuncitem.keywords):
funcargs = pyfuncitem.funcargs
loop = funcargs['loop']
testargs = {arg: funcargs[arg] for arg in pyfuncitem._fixtureinfo.argnames}
loop.run_until_complete(pyfuncitem.obj(**testargs))
return True
|
Run asyncio marked test functions in an event loop instead of a normal
function call.
|
tests/conftest.py
|
pytest_pyfunc_call
|
norbeq/aiomysql
| 0
|
python
|
@pytest.mark.tryfirst
def pytest_pyfunc_call(pyfuncitem):
'\n Run asyncio marked test functions in an event loop instead of a normal\n function call.\n '
if ('run_loop' in pyfuncitem.keywords):
funcargs = pyfuncitem.funcargs
loop = funcargs['loop']
testargs = {arg: funcargs[arg] for arg in pyfuncitem._fixtureinfo.argnames}
loop.run_until_complete(pyfuncitem.obj(**testargs))
return True
|
@pytest.mark.tryfirst
def pytest_pyfunc_call(pyfuncitem):
'\n Run asyncio marked test functions in an event loop instead of a normal\n function call.\n '
if ('run_loop' in pyfuncitem.keywords):
funcargs = pyfuncitem.funcargs
loop = funcargs['loop']
testargs = {arg: funcargs[arg] for arg in pyfuncitem._fixtureinfo.argnames}
loop.run_until_complete(pyfuncitem.obj(**testargs))
return True<|docstring|>Run asyncio marked test functions in an event loop instead of a normal
function call.<|endoftext|>
|
c728dc5006ec18a173c80e7c93cbf5f540a524672e0b7c2fe713852223d6854d
|
@pytest.fixture(scope='session')
def session_id():
'Unique session identifier, random string.'
return str(uuid.uuid4())
|
Unique session identifier, random string.
|
tests/conftest.py
|
session_id
|
norbeq/aiomysql
| 0
|
python
|
@pytest.fixture(scope='session')
def session_id():
return str(uuid.uuid4())
|
@pytest.fixture(scope='session')
def session_id():
return str(uuid.uuid4())<|docstring|>Unique session identifier, random string.<|endoftext|>
|
93ac368de973532cc9e04359c1aed7583219f4e9da093402b3c42188641b2888
|
def is_admin(user):
' Checks the is_superuser fields in user model.\n :param user: User object\n :return: boolean\n '
return user.is_superuser
|
Checks the is_superuser fields in user model.
:param user: User object
:return: boolean
|
accounts/helpers.py
|
is_admin
|
tony-joseph/livre
| 1
|
python
|
def is_admin(user):
' Checks the is_superuser fields in user model.\n :param user: User object\n :return: boolean\n '
return user.is_superuser
|
def is_admin(user):
' Checks the is_superuser fields in user model.\n :param user: User object\n :return: boolean\n '
return user.is_superuser<|docstring|>Checks the is_superuser fields in user model.
:param user: User object
:return: boolean<|endoftext|>
|
ac6edda7e7301112431659635ad5650a37af8bd046a4461e278c71455f2e839e
|
def is_staff(user):
' Checks the is_staff fields in user model.\n :param user: User object\n :return: boolean\n '
return user.is_staff
|
Checks the is_staff fields in user model.
:param user: User object
:return: boolean
|
accounts/helpers.py
|
is_staff
|
tony-joseph/livre
| 1
|
python
|
def is_staff(user):
' Checks the is_staff fields in user model.\n :param user: User object\n :return: boolean\n '
return user.is_staff
|
def is_staff(user):
' Checks the is_staff fields in user model.\n :param user: User object\n :return: boolean\n '
return user.is_staff<|docstring|>Checks the is_staff fields in user model.
:param user: User object
:return: boolean<|endoftext|>
|
a6775384825002cabe80961e3a99fd5e59f303f0d3abc7df4308775d3fe672cf
|
def setUp(self):
' Prepares the test fixture before each test method is called. '
listener.obj = None
listener.trait_name = None
listener.old = None
listener.new = None
|
Prepares the test fixture before each test method is called.
|
Latest/venv/Lib/site-packages/envisage/tests/test_extension_point_changed.py
|
setUp
|
adamcvj/SatelliteTracker
| 1
|
python
|
def setUp(self):
' '
listener.obj = None
listener.trait_name = None
listener.old = None
listener.new = None
|
def setUp(self):
' '
listener.obj = None
listener.trait_name = None
listener.old = None
listener.new = None<|docstring|>Prepares the test fixture before each test method is called.<|endoftext|>
|
0eb682cdfd252e50164085adad1ad26c08114302bad817966aaeee27227020cb
|
def test_set_extension_point(self):
' set extension point '
a = PluginA()
application = TestApplication(plugins=[a])
application.start()
with self.assertRaises(SystemError):
setattr(a, 'x', [1, 2, 3])
|
set extension point
|
Latest/venv/Lib/site-packages/envisage/tests/test_extension_point_changed.py
|
test_set_extension_point
|
adamcvj/SatelliteTracker
| 1
|
python
|
def test_set_extension_point(self):
' '
a = PluginA()
application = TestApplication(plugins=[a])
application.start()
with self.assertRaises(SystemError):
setattr(a, 'x', [1, 2, 3])
|
def test_set_extension_point(self):
' '
a = PluginA()
application = TestApplication(plugins=[a])
application.start()
with self.assertRaises(SystemError):
setattr(a, 'x', [1, 2, 3])<|docstring|>set extension point<|endoftext|>
|
433007e5ac36e7e978ff604e676ad894cf7502132f46d2cdb24fb0c7f0639ec3
|
def test_append(self):
' append '
a = PluginA()
a.on_trait_change(listener, 'x_items')
b = PluginB()
c = PluginC()
application = TestApplication(plugins=[a, b, c])
application.start()
self.assertEqual([1, 2, 3, 98, 99, 100], a.x)
b.x.append(4)
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(7, len(extensions))
self.assertEqual([1, 2, 3, 4, 98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(7, len(extensions))
self.assertEqual([1, 2, 3, 4, 98, 99, 100], extensions)
self.assertEqual(a, listener.obj)
self.assertEqual('x_items', listener.trait_name)
self.assertEqual([4], listener.new.added)
self.assertEqual([], listener.new.removed)
self.assertEqual(3, listener.new.index)
|
append
|
Latest/venv/Lib/site-packages/envisage/tests/test_extension_point_changed.py
|
test_append
|
adamcvj/SatelliteTracker
| 1
|
python
|
def test_(self):
' '
a = PluginA()
a.on_trait_change(listener, 'x_items')
b = PluginB()
c = PluginC()
application = TestApplication(plugins=[a, b, c])
application.start()
self.assertEqual([1, 2, 3, 98, 99, 100], a.x)
b.x.(4)
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(7, len(extensions))
self.assertEqual([1, 2, 3, 4, 98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(7, len(extensions))
self.assertEqual([1, 2, 3, 4, 98, 99, 100], extensions)
self.assertEqual(a, listener.obj)
self.assertEqual('x_items', listener.trait_name)
self.assertEqual([4], listener.new.added)
self.assertEqual([], listener.new.removed)
self.assertEqual(3, listener.new.index)
|
def test_(self):
' '
a = PluginA()
a.on_trait_change(listener, 'x_items')
b = PluginB()
c = PluginC()
application = TestApplication(plugins=[a, b, c])
application.start()
self.assertEqual([1, 2, 3, 98, 99, 100], a.x)
b.x.(4)
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(7, len(extensions))
self.assertEqual([1, 2, 3, 4, 98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(7, len(extensions))
self.assertEqual([1, 2, 3, 4, 98, 99, 100], extensions)
self.assertEqual(a, listener.obj)
self.assertEqual('x_items', listener.trait_name)
self.assertEqual([4], listener.new.added)
self.assertEqual([], listener.new.removed)
self.assertEqual(3, listener.new.index)<|docstring|>append<|endoftext|>
|
06d2411eec50304d4cd26502f4890e1bdedeeb2195a22abb874e3ab7dddaab23
|
def test_remove(self):
' remove '
a = PluginA()
a.on_trait_change(listener, 'x_items')
b = PluginB()
c = PluginC()
application = TestApplication(plugins=[a, b, c])
application.start()
self.assertEqual([1, 2, 3, 98, 99, 100], a.x)
b.x.remove(3)
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(5, len(extensions))
self.assertEqual([1, 2, 98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(5, len(extensions))
self.assertEqual([1, 2, 98, 99, 100], extensions)
self.assertEqual(a, listener.obj)
self.assertEqual('x_items', listener.trait_name)
self.assertEqual([], listener.new.added)
self.assertEqual([3], listener.new.removed)
self.assertEqual(2, listener.new.index)
|
remove
|
Latest/venv/Lib/site-packages/envisage/tests/test_extension_point_changed.py
|
test_remove
|
adamcvj/SatelliteTracker
| 1
|
python
|
def test_(self):
' '
a = PluginA()
a.on_trait_change(listener, 'x_items')
b = PluginB()
c = PluginC()
application = TestApplication(plugins=[a, b, c])
application.start()
self.assertEqual([1, 2, 3, 98, 99, 100], a.x)
b.x.(3)
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(5, len(extensions))
self.assertEqual([1, 2, 98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(5, len(extensions))
self.assertEqual([1, 2, 98, 99, 100], extensions)
self.assertEqual(a, listener.obj)
self.assertEqual('x_items', listener.trait_name)
self.assertEqual([], listener.new.added)
self.assertEqual([3], listener.new.d)
self.assertEqual(2, listener.new.index)
|
def test_(self):
' '
a = PluginA()
a.on_trait_change(listener, 'x_items')
b = PluginB()
c = PluginC()
application = TestApplication(plugins=[a, b, c])
application.start()
self.assertEqual([1, 2, 3, 98, 99, 100], a.x)
b.x.(3)
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(5, len(extensions))
self.assertEqual([1, 2, 98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(5, len(extensions))
self.assertEqual([1, 2, 98, 99, 100], extensions)
self.assertEqual(a, listener.obj)
self.assertEqual('x_items', listener.trait_name)
self.assertEqual([], listener.new.added)
self.assertEqual([3], listener.new.d)
self.assertEqual(2, listener.new.index)<|docstring|>remove<|endoftext|>
|
78131b4d0e9edde76c71643a3a72f56aa7b4c9d4524ad4c39336b45d6a29b791
|
def test_assign_empty_list(self):
' assign empty list '
a = PluginA()
a.on_trait_change(listener, 'x_items')
b = PluginB()
c = PluginC()
application = TestApplication(plugins=[a, b, c])
application.start()
self.assertEqual([1, 2, 3, 98, 99, 100], a.x)
b.x = []
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([98, 99, 100], extensions)
self.assertEqual(a, listener.obj)
self.assertEqual('x_items', listener.trait_name)
self.assertEqual([], listener.new.added)
self.assertEqual([1, 2, 3], listener.new.removed)
self.assertEqual(0, listener.new.index.start)
self.assertEqual(3, listener.new.index.stop)
|
assign empty list
|
Latest/venv/Lib/site-packages/envisage/tests/test_extension_point_changed.py
|
test_assign_empty_list
|
adamcvj/SatelliteTracker
| 1
|
python
|
def test_assign_empty_list(self):
' '
a = PluginA()
a.on_trait_change(listener, 'x_items')
b = PluginB()
c = PluginC()
application = TestApplication(plugins=[a, b, c])
application.start()
self.assertEqual([1, 2, 3, 98, 99, 100], a.x)
b.x = []
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([98, 99, 100], extensions)
self.assertEqual(a, listener.obj)
self.assertEqual('x_items', listener.trait_name)
self.assertEqual([], listener.new.added)
self.assertEqual([1, 2, 3], listener.new.removed)
self.assertEqual(0, listener.new.index.start)
self.assertEqual(3, listener.new.index.stop)
|
def test_assign_empty_list(self):
' '
a = PluginA()
a.on_trait_change(listener, 'x_items')
b = PluginB()
c = PluginC()
application = TestApplication(plugins=[a, b, c])
application.start()
self.assertEqual([1, 2, 3, 98, 99, 100], a.x)
b.x = []
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([98, 99, 100], extensions)
self.assertEqual(a, listener.obj)
self.assertEqual('x_items', listener.trait_name)
self.assertEqual([], listener.new.added)
self.assertEqual([1, 2, 3], listener.new.removed)
self.assertEqual(0, listener.new.index.start)
self.assertEqual(3, listener.new.index.stop)<|docstring|>assign empty list<|endoftext|>
|
0e78faac694a86823298b86d74b863942c36e616a595c285961c1eba7922dbad
|
def test_assign_empty_list_no_event(self):
' assign empty list no event '
a = PluginA()
a.on_trait_change(listener, 'x_items')
b = PluginB()
c = PluginC()
application = TestApplication(plugins=[a, b, c])
application.start()
b.x = []
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([98, 99, 100], extensions)
self.assertEqual(None, listener.obj)
|
assign empty list no event
|
Latest/venv/Lib/site-packages/envisage/tests/test_extension_point_changed.py
|
test_assign_empty_list_no_event
|
adamcvj/SatelliteTracker
| 1
|
python
|
def test_assign_empty_list_no_event(self):
' '
a = PluginA()
a.on_trait_change(listener, 'x_items')
b = PluginB()
c = PluginC()
application = TestApplication(plugins=[a, b, c])
application.start()
b.x = []
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([98, 99, 100], extensions)
self.assertEqual(None, listener.obj)
|
def test_assign_empty_list_no_event(self):
' '
a = PluginA()
a.on_trait_change(listener, 'x_items')
b = PluginB()
c = PluginC()
application = TestApplication(plugins=[a, b, c])
application.start()
b.x = []
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([98, 99, 100], extensions)
self.assertEqual(None, listener.obj)<|docstring|>assign empty list no event<|endoftext|>
|
f775b394ee3438220c87c16bf163b66944eda0dd2869b71e11ee76630b33425e
|
def test_assign_non_empty_list(self):
' assign non-empty list '
a = PluginA()
a.on_trait_change(listener, 'x_items')
b = PluginB()
c = PluginC()
application = TestApplication(plugins=[a, b, c])
application.start()
self.assertEqual([1, 2, 3, 98, 99, 100], a.x)
b.x = [2, 4, 6, 8]
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(7, len(extensions))
self.assertEqual([2, 4, 6, 8, 98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(7, len(extensions))
self.assertEqual([2, 4, 6, 8, 98, 99, 100], extensions)
self.assertEqual(a, listener.obj)
self.assertEqual('x_items', listener.trait_name)
self.assertEqual([2, 4, 6, 8], listener.new.added)
self.assertEqual([1, 2, 3], listener.new.removed)
self.assertEqual(0, listener.new.index.start)
self.assertEqual(4, listener.new.index.stop)
|
assign non-empty list
|
Latest/venv/Lib/site-packages/envisage/tests/test_extension_point_changed.py
|
test_assign_non_empty_list
|
adamcvj/SatelliteTracker
| 1
|
python
|
def test_assign_non_empty_list(self):
' '
a = PluginA()
a.on_trait_change(listener, 'x_items')
b = PluginB()
c = PluginC()
application = TestApplication(plugins=[a, b, c])
application.start()
self.assertEqual([1, 2, 3, 98, 99, 100], a.x)
b.x = [2, 4, 6, 8]
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(7, len(extensions))
self.assertEqual([2, 4, 6, 8, 98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(7, len(extensions))
self.assertEqual([2, 4, 6, 8, 98, 99, 100], extensions)
self.assertEqual(a, listener.obj)
self.assertEqual('x_items', listener.trait_name)
self.assertEqual([2, 4, 6, 8], listener.new.added)
self.assertEqual([1, 2, 3], listener.new.removed)
self.assertEqual(0, listener.new.index.start)
self.assertEqual(4, listener.new.index.stop)
|
def test_assign_non_empty_list(self):
' '
a = PluginA()
a.on_trait_change(listener, 'x_items')
b = PluginB()
c = PluginC()
application = TestApplication(plugins=[a, b, c])
application.start()
self.assertEqual([1, 2, 3, 98, 99, 100], a.x)
b.x = [2, 4, 6, 8]
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(7, len(extensions))
self.assertEqual([2, 4, 6, 8, 98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(7, len(extensions))
self.assertEqual([2, 4, 6, 8, 98, 99, 100], extensions)
self.assertEqual(a, listener.obj)
self.assertEqual('x_items', listener.trait_name)
self.assertEqual([2, 4, 6, 8], listener.new.added)
self.assertEqual([1, 2, 3], listener.new.removed)
self.assertEqual(0, listener.new.index.start)
self.assertEqual(4, listener.new.index.stop)<|docstring|>assign non-empty list<|endoftext|>
|
8ad4a1cccf132ce78dd05be944e6d1fabffe758e43bd27cae8bf92fe95291130
|
def test_add_plugin(self):
' add plugin '
a = PluginA()
a.on_trait_change(listener, 'x_items')
b = PluginB()
c = PluginC()
application = TestApplication(plugins=[a, b])
application.start()
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([1, 2, 3], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([1, 2, 3], extensions)
application.add_plugin(c)
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(6, len(extensions))
self.assertEqual([1, 2, 3, 98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(6, len(extensions))
self.assertEqual([1, 2, 3, 98, 99, 100], extensions)
self.assertEqual(a, listener.obj)
self.assertEqual('x_items', listener.trait_name)
self.assertEqual([98, 99, 100], listener.new.added)
self.assertEqual([], listener.new.removed)
self.assertEqual(3, listener.new.index)
|
add plugin
|
Latest/venv/Lib/site-packages/envisage/tests/test_extension_point_changed.py
|
test_add_plugin
|
adamcvj/SatelliteTracker
| 1
|
python
|
def test_add_plugin(self):
' '
a = PluginA()
a.on_trait_change(listener, 'x_items')
b = PluginB()
c = PluginC()
application = TestApplication(plugins=[a, b])
application.start()
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([1, 2, 3], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([1, 2, 3], extensions)
application.add_plugin(c)
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(6, len(extensions))
self.assertEqual([1, 2, 3, 98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(6, len(extensions))
self.assertEqual([1, 2, 3, 98, 99, 100], extensions)
self.assertEqual(a, listener.obj)
self.assertEqual('x_items', listener.trait_name)
self.assertEqual([98, 99, 100], listener.new.added)
self.assertEqual([], listener.new.removed)
self.assertEqual(3, listener.new.index)
|
def test_add_plugin(self):
' '
a = PluginA()
a.on_trait_change(listener, 'x_items')
b = PluginB()
c = PluginC()
application = TestApplication(plugins=[a, b])
application.start()
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([1, 2, 3], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([1, 2, 3], extensions)
application.add_plugin(c)
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(6, len(extensions))
self.assertEqual([1, 2, 3, 98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(6, len(extensions))
self.assertEqual([1, 2, 3, 98, 99, 100], extensions)
self.assertEqual(a, listener.obj)
self.assertEqual('x_items', listener.trait_name)
self.assertEqual([98, 99, 100], listener.new.added)
self.assertEqual([], listener.new.removed)
self.assertEqual(3, listener.new.index)<|docstring|>add plugin<|endoftext|>
|
a42703ede643c40a8a5bda94fbe0f032cc114cb82c9c8739ec69796664123564
|
def test_remove_plugin(self):
' remove plugin '
a = PluginA()
a.on_trait_change(listener, 'x_items')
b = PluginB()
c = PluginC()
application = TestApplication(plugins=[a, b, c])
application.start()
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(6, len(extensions))
self.assertEqual([1, 2, 3, 98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(6, len(extensions))
self.assertEqual([1, 2, 3, 98, 99, 100], extensions)
application.remove_plugin(b)
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([98, 99, 100], extensions)
self.assertEqual(a, listener.obj)
self.assertEqual('x_items', listener.trait_name)
self.assertEqual([], listener.new.added)
self.assertEqual([1, 2, 3], listener.new.removed)
self.assertEqual(0, listener.new.index)
|
remove plugin
|
Latest/venv/Lib/site-packages/envisage/tests/test_extension_point_changed.py
|
test_remove_plugin
|
adamcvj/SatelliteTracker
| 1
|
python
|
def test_remove_plugin(self):
' '
a = PluginA()
a.on_trait_change(listener, 'x_items')
b = PluginB()
c = PluginC()
application = TestApplication(plugins=[a, b, c])
application.start()
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(6, len(extensions))
self.assertEqual([1, 2, 3, 98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(6, len(extensions))
self.assertEqual([1, 2, 3, 98, 99, 100], extensions)
application.remove_plugin(b)
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([98, 99, 100], extensions)
self.assertEqual(a, listener.obj)
self.assertEqual('x_items', listener.trait_name)
self.assertEqual([], listener.new.added)
self.assertEqual([1, 2, 3], listener.new.removed)
self.assertEqual(0, listener.new.index)
|
def test_remove_plugin(self):
' '
a = PluginA()
a.on_trait_change(listener, 'x_items')
b = PluginB()
c = PluginC()
application = TestApplication(plugins=[a, b, c])
application.start()
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(6, len(extensions))
self.assertEqual([1, 2, 3, 98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(6, len(extensions))
self.assertEqual([1, 2, 3, 98, 99, 100], extensions)
application.remove_plugin(b)
extensions = application.get_extensions('a.x')
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([98, 99, 100], extensions)
extensions = a.x[:]
extensions.sort()
self.assertEqual(3, len(extensions))
self.assertEqual([98, 99, 100], extensions)
self.assertEqual(a, listener.obj)
self.assertEqual('x_items', listener.trait_name)
self.assertEqual([], listener.new.added)
self.assertEqual([1, 2, 3], listener.new.removed)
self.assertEqual(0, listener.new.index)<|docstring|>remove plugin<|endoftext|>
|
5d8616a2b05fb15fdf9be8ba358839be3284332021544653cc62fd913d0c02b5
|
def step(self, indx_block, closure=None):
'Performs a single optimization step.\n\n Arguments:\n closure (callable, optional): A closure that reevaluates the model\n and returns the loss.\n '
loss = None
if (closure is not None):
loss = closure()
if (indx_block >= len(self.param_groups)):
raise ValueError('Block index exceeds the total number of blocks')
group = self.param_groups[indx_block]
weight_decay = group['weight_decay']
momentum = group['momentum']
dampening = group['dampening']
nesterov = group['nesterov']
for p in group['params']:
if (p.grad is None):
continue
d_p = p.grad.data
if (weight_decay != 0):
d_p.add_(weight_decay, p.data)
if (momentum != 0):
param_state = self.state[p]
if ('momentum_buffer' not in param_state):
buf = param_state['momentum_buffer'] = torch.clone(d_p).detach()
else:
buf = param_state['momentum_buffer']
buf.mul_(momentum).add_((1 - dampening), d_p)
if nesterov:
d_p = d_p.add(momentum, buf)
else:
d_p = buf
p.data.add_((- group['lr']), d_p)
return loss
|
Performs a single optimization step.
Arguments:
closure (callable, optional): A closure that reevaluates the model
and returns the loss.
|
trim/convolutional_sparse_coding/matfac.py
|
step
|
csinva/transformation-importance
| 6
|
python
|
def step(self, indx_block, closure=None):
'Performs a single optimization step.\n\n Arguments:\n closure (callable, optional): A closure that reevaluates the model\n and returns the loss.\n '
loss = None
if (closure is not None):
loss = closure()
if (indx_block >= len(self.param_groups)):
raise ValueError('Block index exceeds the total number of blocks')
group = self.param_groups[indx_block]
weight_decay = group['weight_decay']
momentum = group['momentum']
dampening = group['dampening']
nesterov = group['nesterov']
for p in group['params']:
if (p.grad is None):
continue
d_p = p.grad.data
if (weight_decay != 0):
d_p.add_(weight_decay, p.data)
if (momentum != 0):
param_state = self.state[p]
if ('momentum_buffer' not in param_state):
buf = param_state['momentum_buffer'] = torch.clone(d_p).detach()
else:
buf = param_state['momentum_buffer']
buf.mul_(momentum).add_((1 - dampening), d_p)
if nesterov:
d_p = d_p.add(momentum, buf)
else:
d_p = buf
p.data.add_((- group['lr']), d_p)
return loss
|
def step(self, indx_block, closure=None):
'Performs a single optimization step.\n\n Arguments:\n closure (callable, optional): A closure that reevaluates the model\n and returns the loss.\n '
loss = None
if (closure is not None):
loss = closure()
if (indx_block >= len(self.param_groups)):
raise ValueError('Block index exceeds the total number of blocks')
group = self.param_groups[indx_block]
weight_decay = group['weight_decay']
momentum = group['momentum']
dampening = group['dampening']
nesterov = group['nesterov']
for p in group['params']:
if (p.grad is None):
continue
d_p = p.grad.data
if (weight_decay != 0):
d_p.add_(weight_decay, p.data)
if (momentum != 0):
param_state = self.state[p]
if ('momentum_buffer' not in param_state):
buf = param_state['momentum_buffer'] = torch.clone(d_p).detach()
else:
buf = param_state['momentum_buffer']
buf.mul_(momentum).add_((1 - dampening), d_p)
if nesterov:
d_p = d_p.add(momentum, buf)
else:
d_p = buf
p.data.add_((- group['lr']), d_p)
return loss<|docstring|>Performs a single optimization step.
Arguments:
closure (callable, optional): A closure that reevaluates the model
and returns the loss.<|endoftext|>
|
d457cbded2c36440d185072286ea615ecb9046ae6bc754f8375caf1690bc70d4
|
def test_basic():
' Tests that basic example works '
big_field = (1, 1, 4, 4)
inner_field = (2, 2, 3, 3)
assert (overlap_area(big_field, inner_field) == 1)
|
Tests that basic example works
|
test_overlap.py
|
test_basic
|
samcornish/git_lesson
| 0
|
python
|
def test_basic():
' '
big_field = (1, 1, 4, 4)
inner_field = (2, 2, 3, 3)
assert (overlap_area(big_field, inner_field) == 1)
|
def test_basic():
' '
big_field = (1, 1, 4, 4)
inner_field = (2, 2, 3, 3)
assert (overlap_area(big_field, inner_field) == 1)<|docstring|>Tests that basic example works<|endoftext|>
|
36c7a5ead925fae2725422cca441e8aff2e93f4007d6b9815e8632df7e7987a0
|
def test_partial_overlap():
" Tests when there's a partial overlap"
base_field = (1, 1, 4, 3)
over_field = (2, 2, 3, 4)
assert (overlap_area(base_field, over_field) == 1)
|
Tests when there's a partial overlap
|
test_overlap.py
|
test_partial_overlap
|
samcornish/git_lesson
| 0
|
python
|
def test_partial_overlap():
" "
base_field = (1, 1, 4, 3)
over_field = (2, 2, 3, 4)
assert (overlap_area(base_field, over_field) == 1)
|
def test_partial_overlap():
" "
base_field = (1, 1, 4, 3)
over_field = (2, 2, 3, 4)
assert (overlap_area(base_field, over_field) == 1)<|docstring|>Tests when there's a partial overlap<|endoftext|>
|
c5574108e0cb27ff4eb4a98fa95e656610678b2e029352eb3e6abfa442b81564
|
def test_corner_overlap():
" Tests when there's a partial overlap"
base_field = (1, 0, 3, 5)
over_field = (2, 4, 4, 6)
assert (overlap_area(base_field, over_field) == 1)
|
Tests when there's a partial overlap
|
test_overlap.py
|
test_corner_overlap
|
samcornish/git_lesson
| 0
|
python
|
def test_corner_overlap():
" "
base_field = (1, 0, 3, 5)
over_field = (2, 4, 4, 6)
assert (overlap_area(base_field, over_field) == 1)
|
def test_corner_overlap():
" "
base_field = (1, 0, 3, 5)
over_field = (2, 4, 4, 6)
assert (overlap_area(base_field, over_field) == 1)<|docstring|>Tests when there's a partial overlap<|endoftext|>
|
2c40120a07591768472f9048ff35ff25e48f86170972d1bc5e0fef37bb4d4693
|
def test_edge_touching():
' Test when there is an edge '
base_field = (1, 1, 4, 4)
over_field = (2, 2, 3, 4)
assert (overlap_area(base_field, over_field) == 2)
|
Test when there is an edge
|
test_overlap.py
|
test_edge_touching
|
samcornish/git_lesson
| 0
|
python
|
def test_edge_touching():
' '
base_field = (1, 1, 4, 4)
over_field = (2, 2, 3, 4)
assert (overlap_area(base_field, over_field) == 2)
|
def test_edge_touching():
' '
base_field = (1, 1, 4, 4)
over_field = (2, 2, 3, 4)
assert (overlap_area(base_field, over_field) == 2)<|docstring|>Test when there is an edge<|endoftext|>
|
14abf13e789db15bed99296649a1b612d39db139fd6b0baadefbacd0950b29ca
|
def test_edge_touching():
' Test when there is an edge '
base_field = (1, 1, 4, 4)
over_field = (2, 1, 3, 4)
assert (overlap_area(base_field, over_field) == 3)
|
Test when there is an edge
|
test_overlap.py
|
test_edge_touching
|
samcornish/git_lesson
| 0
|
python
|
def test_edge_touching():
' '
base_field = (1, 1, 4, 4)
over_field = (2, 1, 3, 4)
assert (overlap_area(base_field, over_field) == 3)
|
def test_edge_touching():
' '
base_field = (1, 1, 4, 4)
over_field = (2, 1, 3, 4)
assert (overlap_area(base_field, over_field) == 3)<|docstring|>Test when there is an edge<|endoftext|>
|
000e65452a13fc14c9ee0adcac05239b8c8469c37d38c522dda61a60cff561a5
|
def test_outside_edge_touching():
' Test when they are touching on the outside '
base_field = (1, 1, 4, 4)
over_field = (2, 4, 3, 5)
assert (overlap_area(base_field, over_field) == 0)
|
Test when they are touching on the outside
|
test_overlap.py
|
test_outside_edge_touching
|
samcornish/git_lesson
| 0
|
python
|
def test_outside_edge_touching():
' '
base_field = (1, 1, 4, 4)
over_field = (2, 4, 3, 5)
assert (overlap_area(base_field, over_field) == 0)
|
def test_outside_edge_touching():
' '
base_field = (1, 1, 4, 4)
over_field = (2, 4, 3, 5)
assert (overlap_area(base_field, over_field) == 0)<|docstring|>Test when they are touching on the outside<|endoftext|>
|
850fd77c0ab281dfdd94ff4d49b677f9b0efa5d8a3f120190be70a3bec00a077
|
def test_no_overlap():
' Test when they are not touching each other '
base_field = (0, 0, 3, 3)
over_field = (4, 4, 5, 5)
assert (overlap_area(base_field, over_field) == 0)
|
Test when they are not touching each other
|
test_overlap.py
|
test_no_overlap
|
samcornish/git_lesson
| 0
|
python
|
def test_no_overlap():
' '
base_field = (0, 0, 3, 3)
over_field = (4, 4, 5, 5)
assert (overlap_area(base_field, over_field) == 0)
|
def test_no_overlap():
' '
base_field = (0, 0, 3, 3)
over_field = (4, 4, 5, 5)
assert (overlap_area(base_field, over_field) == 0)<|docstring|>Test when they are not touching each other<|endoftext|>
|
d94e4191e679ed44c29d31f0f649566fe494193340b64eb556f3194cafab2bf8
|
def test_floats():
' Test that still works when using floats '
base_field = (1, 1.0, 3.5, 3.5)
over_field = (3, 3, 5, 5)
assert (overlap_area(base_field, over_field) == (0.5 * 0.5))
|
Test that still works when using floats
|
test_overlap.py
|
test_floats
|
samcornish/git_lesson
| 0
|
python
|
def test_floats():
' '
base_field = (1, 1.0, 3.5, 3.5)
over_field = (3, 3, 5, 5)
assert (overlap_area(base_field, over_field) == (0.5 * 0.5))
|
def test_floats():
' '
base_field = (1, 1.0, 3.5, 3.5)
over_field = (3, 3, 5, 5)
assert (overlap_area(base_field, over_field) == (0.5 * 0.5))<|docstring|>Test that still works when using floats<|endoftext|>
|
806018e156a0347adb5fcfb11780fb5f9c1d5d9aeb9603e955154fca96e65acc
|
def test_floats():
' Test that still works when using floats '
base_field = (1, 1.0, 3.3, 3.1)
over_field = (3, 3, 5, 5)
assert (overlap_area(base_field, over_field) == approx((0.3 * 0.1), rel=0.001))
|
Test that still works when using floats
|
test_overlap.py
|
test_floats
|
samcornish/git_lesson
| 0
|
python
|
def test_floats():
' '
base_field = (1, 1.0, 3.3, 3.1)
over_field = (3, 3, 5, 5)
assert (overlap_area(base_field, over_field) == approx((0.3 * 0.1), rel=0.001))
|
def test_floats():
' '
base_field = (1, 1.0, 3.3, 3.1)
over_field = (3, 3, 5, 5)
assert (overlap_area(base_field, over_field) == approx((0.3 * 0.1), rel=0.001))<|docstring|>Test that still works when using floats<|endoftext|>
|
86c9c46ed5d5befe58bd61d98621bea50b25d6e8a42a3ff01e89bc627afb36c7
|
@property
def dataset_paths(self) -> List[str]:
'path that the data should be loaded from in the child class'
return self._data_paths
|
path that the data should be loaded from in the child class
|
disent/data/groundtruth/base.py
|
dataset_paths
|
neonkitchen/disent
| 0
|
python
|
@property
def dataset_paths(self) -> List[str]:
return self._data_paths
|
@property
def dataset_paths(self) -> List[str]:
return self._data_paths<|docstring|>path that the data should be loaded from in the child class<|endoftext|>
|
39ce1f3a24213c4b4b1e6d1c5f776a2431e590118bb10bd5300ee354f5fa78dd
|
@property
def dataset_path(self):
'path that the dataset should be loaded from in the child class'
return self._proc_path
|
path that the dataset should be loaded from in the child class
|
disent/data/groundtruth/base.py
|
dataset_path
|
neonkitchen/disent
| 0
|
python
|
@property
def dataset_path(self):
return self._proc_path
|
@property
def dataset_path(self):
return self._proc_path<|docstring|>path that the dataset should be loaded from in the child class<|endoftext|>
|
26fb7f03d3b03bcd03d3d3f8a6f2c6e822f8a71b7f7b6413a1bfabfc888f39d1
|
def get_version():
'Reads the version from the package'
with open(VERSION_FILE) as handle:
lines = handle.read()
result = VERSION_REGEX.search(lines)
if result:
return result.groupdict()['version']
else:
raise ValueError('Unable to determine __version__')
|
Reads the version from the package
|
setup.py
|
get_version
|
jordan-wright/rapportive
| 42
|
python
|
def get_version():
with open(VERSION_FILE) as handle:
lines = handle.read()
result = VERSION_REGEX.search(lines)
if result:
return result.groupdict()['version']
else:
raise ValueError('Unable to determine __version__')
|
def get_version():
with open(VERSION_FILE) as handle:
lines = handle.read()
result = VERSION_REGEX.search(lines)
if result:
return result.groupdict()['version']
else:
raise ValueError('Unable to determine __version__')<|docstring|>Reads the version from the package<|endoftext|>
|
15cd208ebe9374712a526c2485e0ea97ce5d137d6686df24038cc9255b720b14
|
def get_requirements():
'Reads the installation requirements from requirements.pip'
with open('requirements.pip') as f:
return [line.rstrip() for line in f if (not line.startswith('#'))]
|
Reads the installation requirements from requirements.pip
|
setup.py
|
get_requirements
|
jordan-wright/rapportive
| 42
|
python
|
def get_requirements():
with open('requirements.pip') as f:
return [line.rstrip() for line in f if (not line.startswith('#'))]
|
def get_requirements():
with open('requirements.pip') as f:
return [line.rstrip() for line in f if (not line.startswith('#'))]<|docstring|>Reads the installation requirements from requirements.pip<|endoftext|>
|
351162ecfff45f6bbdee443dca8a014aeffaebca31cb76c0dfc9ab577b73f2f8
|
def getdata(cube, ecube, w=None):
'\n Input\n -----\n cube: astropy.io.fits object\n data cube\n ecube: astropy.io.fits object\n variance cube\n w: astropy.wcs.WCS object\n wcs object\n Output\n ------\n images: ndarray\n data array\n weights: ndarray\n weights array\n ifu_wl: array\n wl array\n w: stropy.wcs.WCS object\n wcs object\n '
chdu = fits.open(cube)
ehdu = fits.open(ecube)
if (w == None):
w = wcs.WCS(chdu[0].header, chdu)
else:
chdu[0].header.update(w.to_header())
w = wcs.WCS(chdu[0].header, chdu)
assert (w.axis_type_names == ['RA', 'DEC', 'pixel'])
wlstart = chdu[0].header['CRVAL3']
wldelta = chdu[0].header['CDELT3']
wlend = (wlstart + (wldelta * chdu[0].header['NAXIS3']))
ifu_wl = np.arange(wlstart, wlend, wldelta)
images = chdu[0].data
weights = (1 / ehdu[0].data)
weights[np.isnan(weights)] = 0.0
weights[np.isinf(weights)] = 0.0
weights[np.isinf(images)] = 0.0
wmask = ((weights != 0).sum((1, 2)) != 0)
images = images[wmask]
weights = weights[wmask]
ifu_wl = ifu_wl[wmask]
return (images, weights, ifu_wl, w)
|
Input
-----
cube: astropy.io.fits object
data cube
ecube: astropy.io.fits object
variance cube
w: astropy.wcs.WCS object
wcs object
Output
------
images: ndarray
data array
weights: ndarray
weights array
ifu_wl: array
wl array
w: stropy.wcs.WCS object
wcs object
|
junk/spaxlet.py
|
getdata
|
Majoburo/spaxlet
| 0
|
python
|
def getdata(cube, ecube, w=None):
'\n Input\n -----\n cube: astropy.io.fits object\n data cube\n ecube: astropy.io.fits object\n variance cube\n w: astropy.wcs.WCS object\n wcs object\n Output\n ------\n images: ndarray\n data array\n weights: ndarray\n weights array\n ifu_wl: array\n wl array\n w: stropy.wcs.WCS object\n wcs object\n '
chdu = fits.open(cube)
ehdu = fits.open(ecube)
if (w == None):
w = wcs.WCS(chdu[0].header, chdu)
else:
chdu[0].header.update(w.to_header())
w = wcs.WCS(chdu[0].header, chdu)
assert (w.axis_type_names == ['RA', 'DEC', 'pixel'])
wlstart = chdu[0].header['CRVAL3']
wldelta = chdu[0].header['CDELT3']
wlend = (wlstart + (wldelta * chdu[0].header['NAXIS3']))
ifu_wl = np.arange(wlstart, wlend, wldelta)
images = chdu[0].data
weights = (1 / ehdu[0].data)
weights[np.isnan(weights)] = 0.0
weights[np.isinf(weights)] = 0.0
weights[np.isinf(images)] = 0.0
wmask = ((weights != 0).sum((1, 2)) != 0)
images = images[wmask]
weights = weights[wmask]
ifu_wl = ifu_wl[wmask]
return (images, weights, ifu_wl, w)
|
def getdata(cube, ecube, w=None):
'\n Input\n -----\n cube: astropy.io.fits object\n data cube\n ecube: astropy.io.fits object\n variance cube\n w: astropy.wcs.WCS object\n wcs object\n Output\n ------\n images: ndarray\n data array\n weights: ndarray\n weights array\n ifu_wl: array\n wl array\n w: stropy.wcs.WCS object\n wcs object\n '
chdu = fits.open(cube)
ehdu = fits.open(ecube)
if (w == None):
w = wcs.WCS(chdu[0].header, chdu)
else:
chdu[0].header.update(w.to_header())
w = wcs.WCS(chdu[0].header, chdu)
assert (w.axis_type_names == ['RA', 'DEC', 'pixel'])
wlstart = chdu[0].header['CRVAL3']
wldelta = chdu[0].header['CDELT3']
wlend = (wlstart + (wldelta * chdu[0].header['NAXIS3']))
ifu_wl = np.arange(wlstart, wlend, wldelta)
images = chdu[0].data
weights = (1 / ehdu[0].data)
weights[np.isnan(weights)] = 0.0
weights[np.isinf(weights)] = 0.0
weights[np.isinf(images)] = 0.0
wmask = ((weights != 0).sum((1, 2)) != 0)
images = images[wmask]
weights = weights[wmask]
ifu_wl = ifu_wl[wmask]
return (images, weights, ifu_wl, w)<|docstring|>Input
-----
cube: astropy.io.fits object
data cube
ecube: astropy.io.fits object
variance cube
w: astropy.wcs.WCS object
wcs object
Output
------
images: ndarray
data array
weights: ndarray
weights array
ifu_wl: array
wl array
w: stropy.wcs.WCS object
wcs object<|endoftext|>
|
4f1b6a16b915d5001511ee790bcae48c598ead71355df6b44b04fdbbf2131996
|
def query_ps_from_wcs(w):
'Query PanStarrs for a wcs.\n '
(nra, ndec) = w.array_shape[1:]
(dra, ddec) = w.wcs.cdelt[:2]
c = wcs.utils.pixel_to_skycoord((nra / 2.0), (ndec / 2.0), w)
ddeg = np.linalg.norm([((dra * nra) / 2), ((ddec * ndec) / 2)])
pd_table = query(c.ra.value, c.dec.value, ddeg)
scat = wcs.utils.skycoord_to_pixel(SkyCoord(pd_table['raMean'], pd_table['decMean'], unit='deg'), w, origin=0, mode='all')
mask = ((((scat[0] < nra) * (scat[1] < ndec)) * (scat[0] > 0)) * (scat[1] > 0))
pd_table = pd_table[mask]
pd_table['x'] = scat[0][mask]
pd_table['y'] = scat[1][mask]
return pd_table
|
Query PanStarrs for a wcs.
|
junk/spaxlet.py
|
query_ps_from_wcs
|
Majoburo/spaxlet
| 0
|
python
|
def query_ps_from_wcs(w):
'\n '
(nra, ndec) = w.array_shape[1:]
(dra, ddec) = w.wcs.cdelt[:2]
c = wcs.utils.pixel_to_skycoord((nra / 2.0), (ndec / 2.0), w)
ddeg = np.linalg.norm([((dra * nra) / 2), ((ddec * ndec) / 2)])
pd_table = query(c.ra.value, c.dec.value, ddeg)
scat = wcs.utils.skycoord_to_pixel(SkyCoord(pd_table['raMean'], pd_table['decMean'], unit='deg'), w, origin=0, mode='all')
mask = ((((scat[0] < nra) * (scat[1] < ndec)) * (scat[0] > 0)) * (scat[1] > 0))
pd_table = pd_table[mask]
pd_table['x'] = scat[0][mask]
pd_table['y'] = scat[1][mask]
return pd_table
|
def query_ps_from_wcs(w):
'\n '
(nra, ndec) = w.array_shape[1:]
(dra, ddec) = w.wcs.cdelt[:2]
c = wcs.utils.pixel_to_skycoord((nra / 2.0), (ndec / 2.0), w)
ddeg = np.linalg.norm([((dra * nra) / 2), ((ddec * ndec) / 2)])
pd_table = query(c.ra.value, c.dec.value, ddeg)
scat = wcs.utils.skycoord_to_pixel(SkyCoord(pd_table['raMean'], pd_table['decMean'], unit='deg'), w, origin=0, mode='all')
mask = ((((scat[0] < nra) * (scat[1] < ndec)) * (scat[0] > 0)) * (scat[1] > 0))
pd_table = pd_table[mask]
pd_table['x'] = scat[0][mask]
pd_table['y'] = scat[1][mask]
return pd_table<|docstring|>Query PanStarrs for a wcs.<|endoftext|>
|
012ed5469d3e422fcdb5c655e53570d73ef16b1e838cb8e7536605dbe31b4c28
|
def define_model(images, weights, psf='startpsf.npy'):
' Create model psf and obsevation\n '
start_psf = np.load(psf)
out = np.outer(np.ones(len(images)), start_psf)
out.shape = (len(images), start_psf.shape[0], start_psf.shape[1])
psfs = scarlet.PSF(out)
model_psf = scarlet.PSF(partial(scarlet.psf.gaussian, sigma=0.8), shape=(None, 8, 8))
model_frame = scarlet.Frame(images.shape, psfs=model_psf)
observation = scarlet.Observation(images, weights=weights, psfs=psfs).match(model_frame)
return (model_frame, observation)
|
Create model psf and obsevation
|
junk/spaxlet.py
|
define_model
|
Majoburo/spaxlet
| 0
|
python
|
def define_model(images, weights, psf='startpsf.npy'):
' \n '
start_psf = np.load(psf)
out = np.outer(np.ones(len(images)), start_psf)
out.shape = (len(images), start_psf.shape[0], start_psf.shape[1])
psfs = scarlet.PSF(out)
model_psf = scarlet.PSF(partial(scarlet.psf.gaussian, sigma=0.8), shape=(None, 8, 8))
model_frame = scarlet.Frame(images.shape, psfs=model_psf)
observation = scarlet.Observation(images, weights=weights, psfs=psfs).match(model_frame)
return (model_frame, observation)
|
def define_model(images, weights, psf='startpsf.npy'):
' \n '
start_psf = np.load(psf)
out = np.outer(np.ones(len(images)), start_psf)
out.shape = (len(images), start_psf.shape[0], start_psf.shape[1])
psfs = scarlet.PSF(out)
model_psf = scarlet.PSF(partial(scarlet.psf.gaussian, sigma=0.8), shape=(None, 8, 8))
model_frame = scarlet.Frame(images.shape, psfs=model_psf)
observation = scarlet.Observation(images, weights=weights, psfs=psfs).match(model_frame)
return (model_frame, observation)<|docstring|>Create model psf and obsevation<|endoftext|>
|
8b7fcbfb4c089506ed25f05d0eb05a8bcb5c206ac97c11bab4d566c96a65171a
|
def new_handle(self, context=None):
'\n The new_handle function returns a Handle object with a url and a\n node id. The new_handle function invokes the localize_handle\n method first to set the url and then invokes the initialize_handle\n function to get an ID.\n :returns: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n '
return self._client.call_method('AbstractHandle.new_handle', [], self._service_ver, context)
|
The new_handle function returns a Handle object with a url and a
node id. The new_handle function invokes the localize_handle
method first to set the url and then invokes the initialize_handle
function to get an ID.
:returns: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String
|
lib/installed_clients/AbstractHandleClient.py
|
new_handle
|
ialarmedalien/kb_blast
| 1
|
python
|
def new_handle(self, context=None):
'\n The new_handle function returns a Handle object with a url and a\n node id. The new_handle function invokes the localize_handle\n method first to set the url and then invokes the initialize_handle\n function to get an ID.\n :returns: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n '
return self._client.call_method('AbstractHandle.new_handle', [], self._service_ver, context)
|
def new_handle(self, context=None):
'\n The new_handle function returns a Handle object with a url and a\n node id. The new_handle function invokes the localize_handle\n method first to set the url and then invokes the initialize_handle\n function to get an ID.\n :returns: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n '
return self._client.call_method('AbstractHandle.new_handle', [], self._service_ver, context)<|docstring|>The new_handle function returns a Handle object with a url and a
node id. The new_handle function invokes the localize_handle
method first to set the url and then invokes the initialize_handle
function to get an ID.
:returns: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String<|endoftext|>
|
96cfd83257d7248566fd12fd4c709075fde5047723f01e31ece1b10961ab9bc4
|
def localize_handle(self, h1, service_name, context=None):
'\n The localize_handle function attempts to locate a shock server near\n the service. The localize_handle function must be called before the\n Handle is initialized becuase when the handle is initialized, it is\n given a node id that maps to the shock server where the node was\n created. This function should not be called directly.\n :param h1: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n :param service_name: instance of String\n :returns: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n '
return self._client.call_method('AbstractHandle.localize_handle', [h1, service_name], self._service_ver, context)
|
The localize_handle function attempts to locate a shock server near
the service. The localize_handle function must be called before the
Handle is initialized becuase when the handle is initialized, it is
given a node id that maps to the shock server where the node was
created. This function should not be called directly.
:param h1: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String
:param service_name: instance of String
:returns: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String
|
lib/installed_clients/AbstractHandleClient.py
|
localize_handle
|
ialarmedalien/kb_blast
| 1
|
python
|
def localize_handle(self, h1, service_name, context=None):
'\n The localize_handle function attempts to locate a shock server near\n the service. The localize_handle function must be called before the\n Handle is initialized becuase when the handle is initialized, it is\n given a node id that maps to the shock server where the node was\n created. This function should not be called directly.\n :param h1: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n :param service_name: instance of String\n :returns: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n '
return self._client.call_method('AbstractHandle.localize_handle', [h1, service_name], self._service_ver, context)
|
def localize_handle(self, h1, service_name, context=None):
'\n The localize_handle function attempts to locate a shock server near\n the service. The localize_handle function must be called before the\n Handle is initialized becuase when the handle is initialized, it is\n given a node id that maps to the shock server where the node was\n created. This function should not be called directly.\n :param h1: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n :param service_name: instance of String\n :returns: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n '
return self._client.call_method('AbstractHandle.localize_handle', [h1, service_name], self._service_ver, context)<|docstring|>The localize_handle function attempts to locate a shock server near
the service. The localize_handle function must be called before the
Handle is initialized becuase when the handle is initialized, it is
given a node id that maps to the shock server where the node was
created. This function should not be called directly.
:param h1: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String
:param service_name: instance of String
:returns: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String<|endoftext|>
|
2403f66b876c293b4eba38c5ff956d8362ddbdecc08e9e41579b1a69d9223ee3
|
def initialize_handle(self, h1, context=None):
'\n The initialize_handle returns a Handle object with an ID. This\n function should not be called directly\n :param h1: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n :returns: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n '
return self._client.call_method('AbstractHandle.initialize_handle', [h1], self._service_ver, context)
|
The initialize_handle returns a Handle object with an ID. This
function should not be called directly
:param h1: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String
:returns: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String
|
lib/installed_clients/AbstractHandleClient.py
|
initialize_handle
|
ialarmedalien/kb_blast
| 1
|
python
|
def initialize_handle(self, h1, context=None):
'\n The initialize_handle returns a Handle object with an ID. This\n function should not be called directly\n :param h1: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n :returns: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n '
return self._client.call_method('AbstractHandle.initialize_handle', [h1], self._service_ver, context)
|
def initialize_handle(self, h1, context=None):
'\n The initialize_handle returns a Handle object with an ID. This\n function should not be called directly\n :param h1: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n :returns: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n '
return self._client.call_method('AbstractHandle.initialize_handle', [h1], self._service_ver, context)<|docstring|>The initialize_handle returns a Handle object with an ID. This
function should not be called directly
:param h1: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String
:returns: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String<|endoftext|>
|
6958a66414a86e2d6c9a056c65540eaabb1a80b3001ea890e5ec07ac57c5e5e8
|
def persist_handle(self, h, context=None):
'\n The persist_handle writes the handle to a persistent store\n that can be later retrieved using the list_handles\n function.\n :param h: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n :returns: instance of String\n '
return self._client.call_method('AbstractHandle.persist_handle', [h], self._service_ver, context)
|
The persist_handle writes the handle to a persistent store
that can be later retrieved using the list_handles
function.
:param h: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String
:returns: instance of String
|
lib/installed_clients/AbstractHandleClient.py
|
persist_handle
|
ialarmedalien/kb_blast
| 1
|
python
|
def persist_handle(self, h, context=None):
'\n The persist_handle writes the handle to a persistent store\n that can be later retrieved using the list_handles\n function.\n :param h: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n :returns: instance of String\n '
return self._client.call_method('AbstractHandle.persist_handle', [h], self._service_ver, context)
|
def persist_handle(self, h, context=None):
'\n The persist_handle writes the handle to a persistent store\n that can be later retrieved using the list_handles\n function.\n :param h: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n :returns: instance of String\n '
return self._client.call_method('AbstractHandle.persist_handle', [h], self._service_ver, context)<|docstring|>The persist_handle writes the handle to a persistent store
that can be later retrieved using the list_handles
function.
:param h: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String
:returns: instance of String<|endoftext|>
|
ff8ef4bcef93245b5860c996b8900f23c8388d0c394bcaebc1f0792b77bc4087
|
def upload(self, infile, context=None):
'\n The upload and download functions provide an empty\n implementation that must be provided in a client. If a concrete\n implementation is not provided an error is thrown. These are\n the equivelant of abstract methods, with runtime rather than\n compile time inforcement.\n \n [client_implemented]\n :param infile: instance of String\n :returns: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n '
return self._client.call_method('AbstractHandle.upload', [infile], self._service_ver, context)
|
The upload and download functions provide an empty
implementation that must be provided in a client. If a concrete
implementation is not provided an error is thrown. These are
the equivelant of abstract methods, with runtime rather than
compile time inforcement.
[client_implemented]
:param infile: instance of String
:returns: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String
|
lib/installed_clients/AbstractHandleClient.py
|
upload
|
ialarmedalien/kb_blast
| 1
|
python
|
def upload(self, infile, context=None):
'\n The upload and download functions provide an empty\n implementation that must be provided in a client. If a concrete\n implementation is not provided an error is thrown. These are\n the equivelant of abstract methods, with runtime rather than\n compile time inforcement.\n \n [client_implemented]\n :param infile: instance of String\n :returns: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n '
return self._client.call_method('AbstractHandle.upload', [infile], self._service_ver, context)
|
def upload(self, infile, context=None):
'\n The upload and download functions provide an empty\n implementation that must be provided in a client. If a concrete\n implementation is not provided an error is thrown. These are\n the equivelant of abstract methods, with runtime rather than\n compile time inforcement.\n \n [client_implemented]\n :param infile: instance of String\n :returns: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n '
return self._client.call_method('AbstractHandle.upload', [infile], self._service_ver, context)<|docstring|>The upload and download functions provide an empty
implementation that must be provided in a client. If a concrete
implementation is not provided an error is thrown. These are
the equivelant of abstract methods, with runtime rather than
compile time inforcement.
[client_implemented]
:param infile: instance of String
:returns: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String<|endoftext|>
|
fd29ffd2c8d1caad2fe143800655081aac9878d8c3897aeb50349089088c7bd7
|
def download(self, h, outfile, context=None):
'\n The upload and download functions provide an empty\n implementation that must be provided in a client. If a concrete\n implementation is not provided an error is thrown. These are\n the equivelant of abstract methods, with runtime rather than\n compile time inforcement.\n [client_implemented]\n :param h: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n :param outfile: instance of String\n '
return self._client.call_method('AbstractHandle.download', [h, outfile], self._service_ver, context)
|
The upload and download functions provide an empty
implementation that must be provided in a client. If a concrete
implementation is not provided an error is thrown. These are
the equivelant of abstract methods, with runtime rather than
compile time inforcement.
[client_implemented]
:param h: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String
:param outfile: instance of String
|
lib/installed_clients/AbstractHandleClient.py
|
download
|
ialarmedalien/kb_blast
| 1
|
python
|
def download(self, h, outfile, context=None):
'\n The upload and download functions provide an empty\n implementation that must be provided in a client. If a concrete\n implementation is not provided an error is thrown. These are\n the equivelant of abstract methods, with runtime rather than\n compile time inforcement.\n [client_implemented]\n :param h: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n :param outfile: instance of String\n '
return self._client.call_method('AbstractHandle.download', [h, outfile], self._service_ver, context)
|
def download(self, h, outfile, context=None):
'\n The upload and download functions provide an empty\n implementation that must be provided in a client. If a concrete\n implementation is not provided an error is thrown. These are\n the equivelant of abstract methods, with runtime rather than\n compile time inforcement.\n [client_implemented]\n :param h: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n :param outfile: instance of String\n '
return self._client.call_method('AbstractHandle.download', [h, outfile], self._service_ver, context)<|docstring|>The upload and download functions provide an empty
implementation that must be provided in a client. If a concrete
implementation is not provided an error is thrown. These are
the equivelant of abstract methods, with runtime rather than
compile time inforcement.
[client_implemented]
:param h: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String
:param outfile: instance of String<|endoftext|>
|
8dbb7c9832f05c3a18ce31c1b2446ebcdd10a15af8fbe2d669d1a7b49884c31a
|
def upload_metadata(self, h, infile, context=None):
'\n The upload_metadata function uploads metadata to an existing\n handle. This means that the data that the handle represents\n has already been uploaded. Uploading meta data before the data\n has been uploaded is not currently supported.\n [client_implemented]\n :param h: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n :param infile: instance of String\n '
return self._client.call_method('AbstractHandle.upload_metadata', [h, infile], self._service_ver, context)
|
The upload_metadata function uploads metadata to an existing
handle. This means that the data that the handle represents
has already been uploaded. Uploading meta data before the data
has been uploaded is not currently supported.
[client_implemented]
:param h: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String
:param infile: instance of String
|
lib/installed_clients/AbstractHandleClient.py
|
upload_metadata
|
ialarmedalien/kb_blast
| 1
|
python
|
def upload_metadata(self, h, infile, context=None):
'\n The upload_metadata function uploads metadata to an existing\n handle. This means that the data that the handle represents\n has already been uploaded. Uploading meta data before the data\n has been uploaded is not currently supported.\n [client_implemented]\n :param h: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n :param infile: instance of String\n '
return self._client.call_method('AbstractHandle.upload_metadata', [h, infile], self._service_ver, context)
|
def upload_metadata(self, h, infile, context=None):
'\n The upload_metadata function uploads metadata to an existing\n handle. This means that the data that the handle represents\n has already been uploaded. Uploading meta data before the data\n has been uploaded is not currently supported.\n [client_implemented]\n :param h: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n :param infile: instance of String\n '
return self._client.call_method('AbstractHandle.upload_metadata', [h, infile], self._service_ver, context)<|docstring|>The upload_metadata function uploads metadata to an existing
handle. This means that the data that the handle represents
has already been uploaded. Uploading meta data before the data
has been uploaded is not currently supported.
[client_implemented]
:param h: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String
:param infile: instance of String<|endoftext|>
|
144d1096533e5d4df07082f9d77ffb0e34c2b9103a350ed0743181bf0a264862
|
def download_metadata(self, h, outfile, context=None):
'\n The download_metadata function downloads metadata associated\n with the data handle and writes it to a file.\n [client_implemented]\n :param h: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n :param outfile: instance of String\n '
return self._client.call_method('AbstractHandle.download_metadata', [h, outfile], self._service_ver, context)
|
The download_metadata function downloads metadata associated
with the data handle and writes it to a file.
[client_implemented]
:param h: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String
:param outfile: instance of String
|
lib/installed_clients/AbstractHandleClient.py
|
download_metadata
|
ialarmedalien/kb_blast
| 1
|
python
|
def download_metadata(self, h, outfile, context=None):
'\n The download_metadata function downloads metadata associated\n with the data handle and writes it to a file.\n [client_implemented]\n :param h: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n :param outfile: instance of String\n '
return self._client.call_method('AbstractHandle.download_metadata', [h, outfile], self._service_ver, context)
|
def download_metadata(self, h, outfile, context=None):
'\n The download_metadata function downloads metadata associated\n with the data handle and writes it to a file.\n [client_implemented]\n :param h: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n :param outfile: instance of String\n '
return self._client.call_method('AbstractHandle.download_metadata', [h, outfile], self._service_ver, context)<|docstring|>The download_metadata function downloads metadata associated
with the data handle and writes it to a file.
[client_implemented]
:param h: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String
:param outfile: instance of String<|endoftext|>
|
499f596cdbdaac1d90362f6c0b7feba97b96028859726cae691c2c5925612146
|
def hids_to_handles(self, hids, context=None):
'\n Given a list of handle ids, this function returns\n a list of handles.\n :param hids: instance of list of type "HandleId" (Handle provides a\n unique reference that enables access to the data files through\n functions provided as part of the HandleService. In the case of\n using shock, the id is the node id. In the case of using shock the\n value of type is shock. In the future these values should\n enumerated. The value of url is the http address of the shock\n server, including the protocol (http or https) and if necessary\n the port. The values of remote_md5 and remote_sha1 are those\n computed on the file in the remote data store. These can be used\n to verify uploads and downloads.)\n :returns: instance of list of type "Handle" -> structure: parameter\n "hid" of type "HandleId" (Handle provides a unique reference that\n enables access to the data files through functions provided as\n part of the HandleService. In the case of using shock, the id is\n the node id. In the case of using shock the value of type is\n shock. In the future these values should enumerated. The value of\n url is the http address of the shock server, including the\n protocol (http or https) and if necessary the port. The values of\n remote_md5 and remote_sha1 are those computed on the file in the\n remote data store. These can be used to verify uploads and\n downloads.), parameter "file_name" of String, parameter "id" of\n type "NodeId", parameter "type" of String, parameter "url" of\n String, parameter "remote_md5" of String, parameter "remote_sha1"\n of String\n '
return self._client.call_method('AbstractHandle.hids_to_handles', [hids], self._service_ver, context)
|
Given a list of handle ids, this function returns
a list of handles.
:param hids: instance of list of type "HandleId" (Handle provides a
unique reference that enables access to the data files through
functions provided as part of the HandleService. In the case of
using shock, the id is the node id. In the case of using shock the
value of type is shock. In the future these values should
enumerated. The value of url is the http address of the shock
server, including the protocol (http or https) and if necessary
the port. The values of remote_md5 and remote_sha1 are those
computed on the file in the remote data store. These can be used
to verify uploads and downloads.)
:returns: instance of list of type "Handle" -> structure: parameter
"hid" of type "HandleId" (Handle provides a unique reference that
enables access to the data files through functions provided as
part of the HandleService. In the case of using shock, the id is
the node id. In the case of using shock the value of type is
shock. In the future these values should enumerated. The value of
url is the http address of the shock server, including the
protocol (http or https) and if necessary the port. The values of
remote_md5 and remote_sha1 are those computed on the file in the
remote data store. These can be used to verify uploads and
downloads.), parameter "file_name" of String, parameter "id" of
type "NodeId", parameter "type" of String, parameter "url" of
String, parameter "remote_md5" of String, parameter "remote_sha1"
of String
|
lib/installed_clients/AbstractHandleClient.py
|
hids_to_handles
|
ialarmedalien/kb_blast
| 1
|
python
|
def hids_to_handles(self, hids, context=None):
'\n Given a list of handle ids, this function returns\n a list of handles.\n :param hids: instance of list of type "HandleId" (Handle provides a\n unique reference that enables access to the data files through\n functions provided as part of the HandleService. In the case of\n using shock, the id is the node id. In the case of using shock the\n value of type is shock. In the future these values should\n enumerated. The value of url is the http address of the shock\n server, including the protocol (http or https) and if necessary\n the port. The values of remote_md5 and remote_sha1 are those\n computed on the file in the remote data store. These can be used\n to verify uploads and downloads.)\n :returns: instance of list of type "Handle" -> structure: parameter\n "hid" of type "HandleId" (Handle provides a unique reference that\n enables access to the data files through functions provided as\n part of the HandleService. In the case of using shock, the id is\n the node id. In the case of using shock the value of type is\n shock. In the future these values should enumerated. The value of\n url is the http address of the shock server, including the\n protocol (http or https) and if necessary the port. The values of\n remote_md5 and remote_sha1 are those computed on the file in the\n remote data store. These can be used to verify uploads and\n downloads.), parameter "file_name" of String, parameter "id" of\n type "NodeId", parameter "type" of String, parameter "url" of\n String, parameter "remote_md5" of String, parameter "remote_sha1"\n of String\n '
return self._client.call_method('AbstractHandle.hids_to_handles', [hids], self._service_ver, context)
|
def hids_to_handles(self, hids, context=None):
'\n Given a list of handle ids, this function returns\n a list of handles.\n :param hids: instance of list of type "HandleId" (Handle provides a\n unique reference that enables access to the data files through\n functions provided as part of the HandleService. In the case of\n using shock, the id is the node id. In the case of using shock the\n value of type is shock. In the future these values should\n enumerated. The value of url is the http address of the shock\n server, including the protocol (http or https) and if necessary\n the port. The values of remote_md5 and remote_sha1 are those\n computed on the file in the remote data store. These can be used\n to verify uploads and downloads.)\n :returns: instance of list of type "Handle" -> structure: parameter\n "hid" of type "HandleId" (Handle provides a unique reference that\n enables access to the data files through functions provided as\n part of the HandleService. In the case of using shock, the id is\n the node id. In the case of using shock the value of type is\n shock. In the future these values should enumerated. The value of\n url is the http address of the shock server, including the\n protocol (http or https) and if necessary the port. The values of\n remote_md5 and remote_sha1 are those computed on the file in the\n remote data store. These can be used to verify uploads and\n downloads.), parameter "file_name" of String, parameter "id" of\n type "NodeId", parameter "type" of String, parameter "url" of\n String, parameter "remote_md5" of String, parameter "remote_sha1"\n of String\n '
return self._client.call_method('AbstractHandle.hids_to_handles', [hids], self._service_ver, context)<|docstring|>Given a list of handle ids, this function returns
a list of handles.
:param hids: instance of list of type "HandleId" (Handle provides a
unique reference that enables access to the data files through
functions provided as part of the HandleService. In the case of
using shock, the id is the node id. In the case of using shock the
value of type is shock. In the future these values should
enumerated. The value of url is the http address of the shock
server, including the protocol (http or https) and if necessary
the port. The values of remote_md5 and remote_sha1 are those
computed on the file in the remote data store. These can be used
to verify uploads and downloads.)
:returns: instance of list of type "Handle" -> structure: parameter
"hid" of type "HandleId" (Handle provides a unique reference that
enables access to the data files through functions provided as
part of the HandleService. In the case of using shock, the id is
the node id. In the case of using shock the value of type is
shock. In the future these values should enumerated. The value of
url is the http address of the shock server, including the
protocol (http or https) and if necessary the port. The values of
remote_md5 and remote_sha1 are those computed on the file in the
remote data store. These can be used to verify uploads and
downloads.), parameter "file_name" of String, parameter "id" of
type "NodeId", parameter "type" of String, parameter "url" of
String, parameter "remote_md5" of String, parameter "remote_sha1"
of String<|endoftext|>
|
1f98e1d0ff4012b56d4fcf7a51d2e3813e84bc4fe3853b39f4d581121833b618
|
def are_readable(self, arg_1, context=None):
'\n Given a list of handle ids, this function determines if\n the underlying data is readable by the caller. If any\n one of the handle ids reference unreadable data this\n function returns false.\n :param arg_1: instance of list of type "HandleId" (Handle provides a\n unique reference that enables access to the data files through\n functions provided as part of the HandleService. In the case of\n using shock, the id is the node id. In the case of using shock the\n value of type is shock. In the future these values should\n enumerated. The value of url is the http address of the shock\n server, including the protocol (http or https) and if necessary\n the port. The values of remote_md5 and remote_sha1 are those\n computed on the file in the remote data store. These can be used\n to verify uploads and downloads.)\n :returns: instance of Long\n '
return self._client.call_method('AbstractHandle.are_readable', [arg_1], self._service_ver, context)
|
Given a list of handle ids, this function determines if
the underlying data is readable by the caller. If any
one of the handle ids reference unreadable data this
function returns false.
:param arg_1: instance of list of type "HandleId" (Handle provides a
unique reference that enables access to the data files through
functions provided as part of the HandleService. In the case of
using shock, the id is the node id. In the case of using shock the
value of type is shock. In the future these values should
enumerated. The value of url is the http address of the shock
server, including the protocol (http or https) and if necessary
the port. The values of remote_md5 and remote_sha1 are those
computed on the file in the remote data store. These can be used
to verify uploads and downloads.)
:returns: instance of Long
|
lib/installed_clients/AbstractHandleClient.py
|
are_readable
|
ialarmedalien/kb_blast
| 1
|
python
|
def are_readable(self, arg_1, context=None):
'\n Given a list of handle ids, this function determines if\n the underlying data is readable by the caller. If any\n one of the handle ids reference unreadable data this\n function returns false.\n :param arg_1: instance of list of type "HandleId" (Handle provides a\n unique reference that enables access to the data files through\n functions provided as part of the HandleService. In the case of\n using shock, the id is the node id. In the case of using shock the\n value of type is shock. In the future these values should\n enumerated. The value of url is the http address of the shock\n server, including the protocol (http or https) and if necessary\n the port. The values of remote_md5 and remote_sha1 are those\n computed on the file in the remote data store. These can be used\n to verify uploads and downloads.)\n :returns: instance of Long\n '
return self._client.call_method('AbstractHandle.are_readable', [arg_1], self._service_ver, context)
|
def are_readable(self, arg_1, context=None):
'\n Given a list of handle ids, this function determines if\n the underlying data is readable by the caller. If any\n one of the handle ids reference unreadable data this\n function returns false.\n :param arg_1: instance of list of type "HandleId" (Handle provides a\n unique reference that enables access to the data files through\n functions provided as part of the HandleService. In the case of\n using shock, the id is the node id. In the case of using shock the\n value of type is shock. In the future these values should\n enumerated. The value of url is the http address of the shock\n server, including the protocol (http or https) and if necessary\n the port. The values of remote_md5 and remote_sha1 are those\n computed on the file in the remote data store. These can be used\n to verify uploads and downloads.)\n :returns: instance of Long\n '
return self._client.call_method('AbstractHandle.are_readable', [arg_1], self._service_ver, context)<|docstring|>Given a list of handle ids, this function determines if
the underlying data is readable by the caller. If any
one of the handle ids reference unreadable data this
function returns false.
:param arg_1: instance of list of type "HandleId" (Handle provides a
unique reference that enables access to the data files through
functions provided as part of the HandleService. In the case of
using shock, the id is the node id. In the case of using shock the
value of type is shock. In the future these values should
enumerated. The value of url is the http address of the shock
server, including the protocol (http or https) and if necessary
the port. The values of remote_md5 and remote_sha1 are those
computed on the file in the remote data store. These can be used
to verify uploads and downloads.)
:returns: instance of Long<|endoftext|>
|
4c3f0c54bbc3138a6733c1b37c55219c317b8949362ee13566bb505ff0649193
|
def is_owner(self, arg_1, context=None):
'\n Given a list of handle ids, this function determines if the underlying\n data is owned by the caller. If any one of the handle ids reference\n unreadable data this function returns false.\n :param arg_1: instance of list of type "HandleId" (Handle provides a\n unique reference that enables access to the data files through\n functions provided as part of the HandleService. In the case of\n using shock, the id is the node id. In the case of using shock the\n value of type is shock. In the future these values should\n enumerated. The value of url is the http address of the shock\n server, including the protocol (http or https) and if necessary\n the port. The values of remote_md5 and remote_sha1 are those\n computed on the file in the remote data store. These can be used\n to verify uploads and downloads.)\n :returns: instance of Long\n '
return self._client.call_method('AbstractHandle.is_owner', [arg_1], self._service_ver, context)
|
Given a list of handle ids, this function determines if the underlying
data is owned by the caller. If any one of the handle ids reference
unreadable data this function returns false.
:param arg_1: instance of list of type "HandleId" (Handle provides a
unique reference that enables access to the data files through
functions provided as part of the HandleService. In the case of
using shock, the id is the node id. In the case of using shock the
value of type is shock. In the future these values should
enumerated. The value of url is the http address of the shock
server, including the protocol (http or https) and if necessary
the port. The values of remote_md5 and remote_sha1 are those
computed on the file in the remote data store. These can be used
to verify uploads and downloads.)
:returns: instance of Long
|
lib/installed_clients/AbstractHandleClient.py
|
is_owner
|
ialarmedalien/kb_blast
| 1
|
python
|
def is_owner(self, arg_1, context=None):
'\n Given a list of handle ids, this function determines if the underlying\n data is owned by the caller. If any one of the handle ids reference\n unreadable data this function returns false.\n :param arg_1: instance of list of type "HandleId" (Handle provides a\n unique reference that enables access to the data files through\n functions provided as part of the HandleService. In the case of\n using shock, the id is the node id. In the case of using shock the\n value of type is shock. In the future these values should\n enumerated. The value of url is the http address of the shock\n server, including the protocol (http or https) and if necessary\n the port. The values of remote_md5 and remote_sha1 are those\n computed on the file in the remote data store. These can be used\n to verify uploads and downloads.)\n :returns: instance of Long\n '
return self._client.call_method('AbstractHandle.is_owner', [arg_1], self._service_ver, context)
|
def is_owner(self, arg_1, context=None):
'\n Given a list of handle ids, this function determines if the underlying\n data is owned by the caller. If any one of the handle ids reference\n unreadable data this function returns false.\n :param arg_1: instance of list of type "HandleId" (Handle provides a\n unique reference that enables access to the data files through\n functions provided as part of the HandleService. In the case of\n using shock, the id is the node id. In the case of using shock the\n value of type is shock. In the future these values should\n enumerated. The value of url is the http address of the shock\n server, including the protocol (http or https) and if necessary\n the port. The values of remote_md5 and remote_sha1 are those\n computed on the file in the remote data store. These can be used\n to verify uploads and downloads.)\n :returns: instance of Long\n '
return self._client.call_method('AbstractHandle.is_owner', [arg_1], self._service_ver, context)<|docstring|>Given a list of handle ids, this function determines if the underlying
data is owned by the caller. If any one of the handle ids reference
unreadable data this function returns false.
:param arg_1: instance of list of type "HandleId" (Handle provides a
unique reference that enables access to the data files through
functions provided as part of the HandleService. In the case of
using shock, the id is the node id. In the case of using shock the
value of type is shock. In the future these values should
enumerated. The value of url is the http address of the shock
server, including the protocol (http or https) and if necessary
the port. The values of remote_md5 and remote_sha1 are those
computed on the file in the remote data store. These can be used
to verify uploads and downloads.)
:returns: instance of Long<|endoftext|>
|
95c645e8a900164f78a68a8e5fb295b6753e85277bd5f5fd563cd70440ce21fd
|
def is_readable(self, id, context=None):
'\n Given a handle id, this function queries the underlying\n data store to see if the data being referred to is\n readable to by the caller.\n :param id: instance of String\n :returns: instance of Long\n '
return self._client.call_method('AbstractHandle.is_readable', [id], self._service_ver, context)
|
Given a handle id, this function queries the underlying
data store to see if the data being referred to is
readable to by the caller.
:param id: instance of String
:returns: instance of Long
|
lib/installed_clients/AbstractHandleClient.py
|
is_readable
|
ialarmedalien/kb_blast
| 1
|
python
|
def is_readable(self, id, context=None):
'\n Given a handle id, this function queries the underlying\n data store to see if the data being referred to is\n readable to by the caller.\n :param id: instance of String\n :returns: instance of Long\n '
return self._client.call_method('AbstractHandle.is_readable', [id], self._service_ver, context)
|
def is_readable(self, id, context=None):
'\n Given a handle id, this function queries the underlying\n data store to see if the data being referred to is\n readable to by the caller.\n :param id: instance of String\n :returns: instance of Long\n '
return self._client.call_method('AbstractHandle.is_readable', [id], self._service_ver, context)<|docstring|>Given a handle id, this function queries the underlying
data store to see if the data being referred to is
readable to by the caller.
:param id: instance of String
:returns: instance of Long<|endoftext|>
|
0cc64fa6f8a42dfddfb2080c00c3d341e1a2fd1276c05e47ae72430325c2c360
|
def list_handles(self, context=None):
'\n The list function returns the set of handles that were\n created by the user.\n :returns: instance of list of type "Handle" -> structure: parameter\n "hid" of type "HandleId" (Handle provides a unique reference that\n enables access to the data files through functions provided as\n part of the HandleService. In the case of using shock, the id is\n the node id. In the case of using shock the value of type is\n shock. In the future these values should enumerated. The value of\n url is the http address of the shock server, including the\n protocol (http or https) and if necessary the port. The values of\n remote_md5 and remote_sha1 are those computed on the file in the\n remote data store. These can be used to verify uploads and\n downloads.), parameter "file_name" of String, parameter "id" of\n type "NodeId", parameter "type" of String, parameter "url" of\n String, parameter "remote_md5" of String, parameter "remote_sha1"\n of String\n '
return self._client.call_method('AbstractHandle.list_handles', [], self._service_ver, context)
|
The list function returns the set of handles that were
created by the user.
:returns: instance of list of type "Handle" -> structure: parameter
"hid" of type "HandleId" (Handle provides a unique reference that
enables access to the data files through functions provided as
part of the HandleService. In the case of using shock, the id is
the node id. In the case of using shock the value of type is
shock. In the future these values should enumerated. The value of
url is the http address of the shock server, including the
protocol (http or https) and if necessary the port. The values of
remote_md5 and remote_sha1 are those computed on the file in the
remote data store. These can be used to verify uploads and
downloads.), parameter "file_name" of String, parameter "id" of
type "NodeId", parameter "type" of String, parameter "url" of
String, parameter "remote_md5" of String, parameter "remote_sha1"
of String
|
lib/installed_clients/AbstractHandleClient.py
|
list_handles
|
ialarmedalien/kb_blast
| 1
|
python
|
def list_handles(self, context=None):
'\n The list function returns the set of handles that were\n created by the user.\n :returns: instance of list of type "Handle" -> structure: parameter\n "hid" of type "HandleId" (Handle provides a unique reference that\n enables access to the data files through functions provided as\n part of the HandleService. In the case of using shock, the id is\n the node id. In the case of using shock the value of type is\n shock. In the future these values should enumerated. The value of\n url is the http address of the shock server, including the\n protocol (http or https) and if necessary the port. The values of\n remote_md5 and remote_sha1 are those computed on the file in the\n remote data store. These can be used to verify uploads and\n downloads.), parameter "file_name" of String, parameter "id" of\n type "NodeId", parameter "type" of String, parameter "url" of\n String, parameter "remote_md5" of String, parameter "remote_sha1"\n of String\n '
return self._client.call_method('AbstractHandle.list_handles', [], self._service_ver, context)
|
def list_handles(self, context=None):
'\n The list function returns the set of handles that were\n created by the user.\n :returns: instance of list of type "Handle" -> structure: parameter\n "hid" of type "HandleId" (Handle provides a unique reference that\n enables access to the data files through functions provided as\n part of the HandleService. In the case of using shock, the id is\n the node id. In the case of using shock the value of type is\n shock. In the future these values should enumerated. The value of\n url is the http address of the shock server, including the\n protocol (http or https) and if necessary the port. The values of\n remote_md5 and remote_sha1 are those computed on the file in the\n remote data store. These can be used to verify uploads and\n downloads.), parameter "file_name" of String, parameter "id" of\n type "NodeId", parameter "type" of String, parameter "url" of\n String, parameter "remote_md5" of String, parameter "remote_sha1"\n of String\n '
return self._client.call_method('AbstractHandle.list_handles', [], self._service_ver, context)<|docstring|>The list function returns the set of handles that were
created by the user.
:returns: instance of list of type "Handle" -> structure: parameter
"hid" of type "HandleId" (Handle provides a unique reference that
enables access to the data files through functions provided as
part of the HandleService. In the case of using shock, the id is
the node id. In the case of using shock the value of type is
shock. In the future these values should enumerated. The value of
url is the http address of the shock server, including the
protocol (http or https) and if necessary the port. The values of
remote_md5 and remote_sha1 are those computed on the file in the
remote data store. These can be used to verify uploads and
downloads.), parameter "file_name" of String, parameter "id" of
type "NodeId", parameter "type" of String, parameter "url" of
String, parameter "remote_md5" of String, parameter "remote_sha1"
of String<|endoftext|>
|
56adfb5b196eaa69f589cdd59b8b0a37976ae7cc7f153f7c5b3cf266f7570616
|
def delete_handles(self, l, context=None):
'\n The delete_handles function takes a list of handles\n and deletes them on the handle service server.\n :param l: instance of list of type "Handle" -> structure: parameter\n "hid" of type "HandleId" (Handle provides a unique reference that\n enables access to the data files through functions provided as\n part of the HandleService. In the case of using shock, the id is\n the node id. In the case of using shock the value of type is\n shock. In the future these values should enumerated. The value of\n url is the http address of the shock server, including the\n protocol (http or https) and if necessary the port. The values of\n remote_md5 and remote_sha1 are those computed on the file in the\n remote data store. These can be used to verify uploads and\n downloads.), parameter "file_name" of String, parameter "id" of\n type "NodeId", parameter "type" of String, parameter "url" of\n String, parameter "remote_md5" of String, parameter "remote_sha1"\n of String\n '
return self._client.call_method('AbstractHandle.delete_handles', [l], self._service_ver, context)
|
The delete_handles function takes a list of handles
and deletes them on the handle service server.
:param l: instance of list of type "Handle" -> structure: parameter
"hid" of type "HandleId" (Handle provides a unique reference that
enables access to the data files through functions provided as
part of the HandleService. In the case of using shock, the id is
the node id. In the case of using shock the value of type is
shock. In the future these values should enumerated. The value of
url is the http address of the shock server, including the
protocol (http or https) and if necessary the port. The values of
remote_md5 and remote_sha1 are those computed on the file in the
remote data store. These can be used to verify uploads and
downloads.), parameter "file_name" of String, parameter "id" of
type "NodeId", parameter "type" of String, parameter "url" of
String, parameter "remote_md5" of String, parameter "remote_sha1"
of String
|
lib/installed_clients/AbstractHandleClient.py
|
delete_handles
|
ialarmedalien/kb_blast
| 1
|
python
|
def delete_handles(self, l, context=None):
'\n The delete_handles function takes a list of handles\n and deletes them on the handle service server.\n :param l: instance of list of type "Handle" -> structure: parameter\n "hid" of type "HandleId" (Handle provides a unique reference that\n enables access to the data files through functions provided as\n part of the HandleService. In the case of using shock, the id is\n the node id. In the case of using shock the value of type is\n shock. In the future these values should enumerated. The value of\n url is the http address of the shock server, including the\n protocol (http or https) and if necessary the port. The values of\n remote_md5 and remote_sha1 are those computed on the file in the\n remote data store. These can be used to verify uploads and\n downloads.), parameter "file_name" of String, parameter "id" of\n type "NodeId", parameter "type" of String, parameter "url" of\n String, parameter "remote_md5" of String, parameter "remote_sha1"\n of String\n '
return self._client.call_method('AbstractHandle.delete_handles', [l], self._service_ver, context)
|
def delete_handles(self, l, context=None):
'\n The delete_handles function takes a list of handles\n and deletes them on the handle service server.\n :param l: instance of list of type "Handle" -> structure: parameter\n "hid" of type "HandleId" (Handle provides a unique reference that\n enables access to the data files through functions provided as\n part of the HandleService. In the case of using shock, the id is\n the node id. In the case of using shock the value of type is\n shock. In the future these values should enumerated. The value of\n url is the http address of the shock server, including the\n protocol (http or https) and if necessary the port. The values of\n remote_md5 and remote_sha1 are those computed on the file in the\n remote data store. These can be used to verify uploads and\n downloads.), parameter "file_name" of String, parameter "id" of\n type "NodeId", parameter "type" of String, parameter "url" of\n String, parameter "remote_md5" of String, parameter "remote_sha1"\n of String\n '
return self._client.call_method('AbstractHandle.delete_handles', [l], self._service_ver, context)<|docstring|>The delete_handles function takes a list of handles
and deletes them on the handle service server.
:param l: instance of list of type "Handle" -> structure: parameter
"hid" of type "HandleId" (Handle provides a unique reference that
enables access to the data files through functions provided as
part of the HandleService. In the case of using shock, the id is
the node id. In the case of using shock the value of type is
shock. In the future these values should enumerated. The value of
url is the http address of the shock server, including the
protocol (http or https) and if necessary the port. The values of
remote_md5 and remote_sha1 are those computed on the file in the
remote data store. These can be used to verify uploads and
downloads.), parameter "file_name" of String, parameter "id" of
type "NodeId", parameter "type" of String, parameter "url" of
String, parameter "remote_md5" of String, parameter "remote_sha1"
of String<|endoftext|>
|
0b3d1d83568d6dd306509904350d736c887826844bf77c4b0e666dc493b76a37
|
def give(self, user, perm, h, context=None):
'\n :param user: instance of String\n :param perm: instance of String\n :param h: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n '
return self._client.call_method('AbstractHandle.give', [user, perm, h], self._service_ver, context)
|
:param user: instance of String
:param perm: instance of String
:param h: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String
|
lib/installed_clients/AbstractHandleClient.py
|
give
|
ialarmedalien/kb_blast
| 1
|
python
|
def give(self, user, perm, h, context=None):
'\n :param user: instance of String\n :param perm: instance of String\n :param h: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n '
return self._client.call_method('AbstractHandle.give', [user, perm, h], self._service_ver, context)
|
def give(self, user, perm, h, context=None):
'\n :param user: instance of String\n :param perm: instance of String\n :param h: instance of type "Handle" -> structure: parameter "hid" of\n type "HandleId" (Handle provides a unique reference that enables\n access to the data files through functions provided as part of the\n HandleService. In the case of using shock, the id is the node id.\n In the case of using shock the value of type is shock. In the\n future these values should enumerated. The value of url is the\n http address of the shock server, including the protocol (http or\n https) and if necessary the port. The values of remote_md5 and\n remote_sha1 are those computed on the file in the remote data\n store. These can be used to verify uploads and downloads.),\n parameter "file_name" of String, parameter "id" of type "NodeId",\n parameter "type" of String, parameter "url" of String, parameter\n "remote_md5" of String, parameter "remote_sha1" of String\n '
return self._client.call_method('AbstractHandle.give', [user, perm, h], self._service_ver, context)<|docstring|>:param user: instance of String
:param perm: instance of String
:param h: instance of type "Handle" -> structure: parameter "hid" of
type "HandleId" (Handle provides a unique reference that enables
access to the data files through functions provided as part of the
HandleService. In the case of using shock, the id is the node id.
In the case of using shock the value of type is shock. In the
future these values should enumerated. The value of url is the
http address of the shock server, including the protocol (http or
https) and if necessary the port. The values of remote_md5 and
remote_sha1 are those computed on the file in the remote data
store. These can be used to verify uploads and downloads.),
parameter "file_name" of String, parameter "id" of type "NodeId",
parameter "type" of String, parameter "url" of String, parameter
"remote_md5" of String, parameter "remote_sha1" of String<|endoftext|>
|
e44747f2a37946c602725858bdcc5eef6c0904b02ced80f20c779e16adfcf238
|
def ids_to_handles(self, ids, context=None):
'\n Given a list of ids, this function returns\n a list of handles. In case of Shock, the list of ids\n are shock node ids and this function the handles, which\n contains Shock url and related information.\n :param ids: instance of list of type "NodeId"\n :returns: instance of list of type "Handle" -> structure: parameter\n "hid" of type "HandleId" (Handle provides a unique reference that\n enables access to the data files through functions provided as\n part of the HandleService. In the case of using shock, the id is\n the node id. In the case of using shock the value of type is\n shock. In the future these values should enumerated. The value of\n url is the http address of the shock server, including the\n protocol (http or https) and if necessary the port. The values of\n remote_md5 and remote_sha1 are those computed on the file in the\n remote data store. These can be used to verify uploads and\n downloads.), parameter "file_name" of String, parameter "id" of\n type "NodeId", parameter "type" of String, parameter "url" of\n String, parameter "remote_md5" of String, parameter "remote_sha1"\n of String\n '
return self._client.call_method('AbstractHandle.ids_to_handles', [ids], self._service_ver, context)
|
Given a list of ids, this function returns
a list of handles. In case of Shock, the list of ids
are shock node ids and this function the handles, which
contains Shock url and related information.
:param ids: instance of list of type "NodeId"
:returns: instance of list of type "Handle" -> structure: parameter
"hid" of type "HandleId" (Handle provides a unique reference that
enables access to the data files through functions provided as
part of the HandleService. In the case of using shock, the id is
the node id. In the case of using shock the value of type is
shock. In the future these values should enumerated. The value of
url is the http address of the shock server, including the
protocol (http or https) and if necessary the port. The values of
remote_md5 and remote_sha1 are those computed on the file in the
remote data store. These can be used to verify uploads and
downloads.), parameter "file_name" of String, parameter "id" of
type "NodeId", parameter "type" of String, parameter "url" of
String, parameter "remote_md5" of String, parameter "remote_sha1"
of String
|
lib/installed_clients/AbstractHandleClient.py
|
ids_to_handles
|
ialarmedalien/kb_blast
| 1
|
python
|
def ids_to_handles(self, ids, context=None):
'\n Given a list of ids, this function returns\n a list of handles. In case of Shock, the list of ids\n are shock node ids and this function the handles, which\n contains Shock url and related information.\n :param ids: instance of list of type "NodeId"\n :returns: instance of list of type "Handle" -> structure: parameter\n "hid" of type "HandleId" (Handle provides a unique reference that\n enables access to the data files through functions provided as\n part of the HandleService. In the case of using shock, the id is\n the node id. In the case of using shock the value of type is\n shock. In the future these values should enumerated. The value of\n url is the http address of the shock server, including the\n protocol (http or https) and if necessary the port. The values of\n remote_md5 and remote_sha1 are those computed on the file in the\n remote data store. These can be used to verify uploads and\n downloads.), parameter "file_name" of String, parameter "id" of\n type "NodeId", parameter "type" of String, parameter "url" of\n String, parameter "remote_md5" of String, parameter "remote_sha1"\n of String\n '
return self._client.call_method('AbstractHandle.ids_to_handles', [ids], self._service_ver, context)
|
def ids_to_handles(self, ids, context=None):
'\n Given a list of ids, this function returns\n a list of handles. In case of Shock, the list of ids\n are shock node ids and this function the handles, which\n contains Shock url and related information.\n :param ids: instance of list of type "NodeId"\n :returns: instance of list of type "Handle" -> structure: parameter\n "hid" of type "HandleId" (Handle provides a unique reference that\n enables access to the data files through functions provided as\n part of the HandleService. In the case of using shock, the id is\n the node id. In the case of using shock the value of type is\n shock. In the future these values should enumerated. The value of\n url is the http address of the shock server, including the\n protocol (http or https) and if necessary the port. The values of\n remote_md5 and remote_sha1 are those computed on the file in the\n remote data store. These can be used to verify uploads and\n downloads.), parameter "file_name" of String, parameter "id" of\n type "NodeId", parameter "type" of String, parameter "url" of\n String, parameter "remote_md5" of String, parameter "remote_sha1"\n of String\n '
return self._client.call_method('AbstractHandle.ids_to_handles', [ids], self._service_ver, context)<|docstring|>Given a list of ids, this function returns
a list of handles. In case of Shock, the list of ids
are shock node ids and this function the handles, which
contains Shock url and related information.
:param ids: instance of list of type "NodeId"
:returns: instance of list of type "Handle" -> structure: parameter
"hid" of type "HandleId" (Handle provides a unique reference that
enables access to the data files through functions provided as
part of the HandleService. In the case of using shock, the id is
the node id. In the case of using shock the value of type is
shock. In the future these values should enumerated. The value of
url is the http address of the shock server, including the
protocol (http or https) and if necessary the port. The values of
remote_md5 and remote_sha1 are those computed on the file in the
remote data store. These can be used to verify uploads and
downloads.), parameter "file_name" of String, parameter "id" of
type "NodeId", parameter "type" of String, parameter "url" of
String, parameter "remote_md5" of String, parameter "remote_sha1"
of String<|endoftext|>
|
a1a2d3d83c391f5ae30600cc8c3b3dcb64719db6108db1d144c77978349bf51d
|
def setUp(self):
'\n \n TEST_ASSETS_DIR contains external required content for test. \n \n Test func naming: test_<name of url>_url_is_resolved\n for ex if url is:path("<str:username>/",UserProfileView.as_view(),name="profile"),,\n then: test_profile_url_is_resolved\n \n '
self.TEST_ASSETS_DIR = os.path.join(settings.BASE_DIR, 'test_assets')
self.user_dummy_username = 'testuser'
self.user_dummy_password = dummy_password()
self.client = Client()
self.user = User.objects.create_user(username=self.user_dummy_username, password=self.user_dummy_password)
self.client.login(username=self.user_dummy_username, password=self.user_dummy_password)
|
TEST_ASSETS_DIR contains external required content for test.
Test func naming: test_<name of url>_url_is_resolved
for ex if url is:path("<str:username>/",UserProfileView.as_view(),name="profile"),,
then: test_profile_url_is_resolved
|
users/tests/test_urls.py
|
setUp
|
alexdeathway/Gecom
| 7
|
python
|
def setUp(self):
'\n \n TEST_ASSETS_DIR contains external required content for test. \n \n Test func naming: test_<name of url>_url_is_resolved\n for ex if url is:path("<str:username>/",UserProfileView.as_view(),name="profile"),,\n then: test_profile_url_is_resolved\n \n '
self.TEST_ASSETS_DIR = os.path.join(settings.BASE_DIR, 'test_assets')
self.user_dummy_username = 'testuser'
self.user_dummy_password = dummy_password()
self.client = Client()
self.user = User.objects.create_user(username=self.user_dummy_username, password=self.user_dummy_password)
self.client.login(username=self.user_dummy_username, password=self.user_dummy_password)
|
def setUp(self):
'\n \n TEST_ASSETS_DIR contains external required content for test. \n \n Test func naming: test_<name of url>_url_is_resolved\n for ex if url is:path("<str:username>/",UserProfileView.as_view(),name="profile"),,\n then: test_profile_url_is_resolved\n \n '
self.TEST_ASSETS_DIR = os.path.join(settings.BASE_DIR, 'test_assets')
self.user_dummy_username = 'testuser'
self.user_dummy_password = dummy_password()
self.client = Client()
self.user = User.objects.create_user(username=self.user_dummy_username, password=self.user_dummy_password)
self.client.login(username=self.user_dummy_username, password=self.user_dummy_password)<|docstring|>TEST_ASSETS_DIR contains external required content for test.
Test func naming: test_<name of url>_url_is_resolved
for ex if url is:path("<str:username>/",UserProfileView.as_view(),name="profile"),,
then: test_profile_url_is_resolved<|endoftext|>
|
e2fa460302e49825479fc9705d13cfb89b4e35102564756e0e68a2d41474417d
|
def get_spar_components(self, document='Client:Foo', **kwargs) -> ComponentSummaryRoot:
'Get SPAR components # noqa: E501\n\n This endpoint returns the list of SPAR components in a given SPAR document. # noqa: E501\n This method makes a synchronous HTTP request. Returns the http data only\n\n Args:\n document (str): Document Name. defaults to "Client:Foo", must be one of ["Client:Foo"]\n\n Keyword Args:\n _preload_content (bool): if False, the urllib3.HTTPResponse object\n will be returned without reading/decoding response data.\n Default is True.\n _request_timeout (int/float/tuple): timeout setting for this request. If\n one number provided, it will be total request timeout. It can also\n be a pair (tuple) of (connection, read) timeouts.\n Default is None.\n _check_input_type (bool): specifies if type checking\n should be done one the data sent to the server.\n Default is True.\n _check_return_type (bool): specifies if type checking\n should be done one the data received from the server.\n Default is True.\n _spec_property_naming (bool): True if the variable names in the input data\n are serialized names, as specified in the OpenAPI document.\n False if the variable names in the input data\n are pythonic names, e.g. snake case (default)\n _content_type (str/None): force body content-type.\n Default is None and content-type will be predicted by allowed\n content-types and body.\n _host_index (int/None): specifies the index of the server\n that we want to use.\n Default is read from the configuration.\n Returns:\n ComponentSummaryRoot\n Response Object\n '
self.apply_kwargs_defaults(kwargs=kwargs, return_http_data_only=True, async_req=False)
kwargs['document'] = document
return self.get_spar_components_endpoint.call_with_http_info(**kwargs)
|
Get SPAR components # noqa: E501
This endpoint returns the list of SPAR components in a given SPAR document. # noqa: E501
This method makes a synchronous HTTP request. Returns the http data only
Args:
document (str): Document Name. defaults to "Client:Foo", must be one of ["Client:Foo"]
Keyword Args:
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (int/float/tuple): timeout setting for this request. If
one number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_content_type (str/None): force body content-type.
Default is None and content-type will be predicted by allowed
content-types and body.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
Returns:
ComponentSummaryRoot
Response Object
|
code/python/SPAREngine/v3/fds/sdk/SPAREngine/api/components_api.py
|
get_spar_components
|
factset/enterprise-sdk
| 6
|
python
|
def get_spar_components(self, document='Client:Foo', **kwargs) -> ComponentSummaryRoot:
'Get SPAR components # noqa: E501\n\n This endpoint returns the list of SPAR components in a given SPAR document. # noqa: E501\n This method makes a synchronous HTTP request. Returns the http data only\n\n Args:\n document (str): Document Name. defaults to "Client:Foo", must be one of ["Client:Foo"]\n\n Keyword Args:\n _preload_content (bool): if False, the urllib3.HTTPResponse object\n will be returned without reading/decoding response data.\n Default is True.\n _request_timeout (int/float/tuple): timeout setting for this request. If\n one number provided, it will be total request timeout. It can also\n be a pair (tuple) of (connection, read) timeouts.\n Default is None.\n _check_input_type (bool): specifies if type checking\n should be done one the data sent to the server.\n Default is True.\n _check_return_type (bool): specifies if type checking\n should be done one the data received from the server.\n Default is True.\n _spec_property_naming (bool): True if the variable names in the input data\n are serialized names, as specified in the OpenAPI document.\n False if the variable names in the input data\n are pythonic names, e.g. snake case (default)\n _content_type (str/None): force body content-type.\n Default is None and content-type will be predicted by allowed\n content-types and body.\n _host_index (int/None): specifies the index of the server\n that we want to use.\n Default is read from the configuration.\n Returns:\n ComponentSummaryRoot\n Response Object\n '
self.apply_kwargs_defaults(kwargs=kwargs, return_http_data_only=True, async_req=False)
kwargs['document'] = document
return self.get_spar_components_endpoint.call_with_http_info(**kwargs)
|
def get_spar_components(self, document='Client:Foo', **kwargs) -> ComponentSummaryRoot:
'Get SPAR components # noqa: E501\n\n This endpoint returns the list of SPAR components in a given SPAR document. # noqa: E501\n This method makes a synchronous HTTP request. Returns the http data only\n\n Args:\n document (str): Document Name. defaults to "Client:Foo", must be one of ["Client:Foo"]\n\n Keyword Args:\n _preload_content (bool): if False, the urllib3.HTTPResponse object\n will be returned without reading/decoding response data.\n Default is True.\n _request_timeout (int/float/tuple): timeout setting for this request. If\n one number provided, it will be total request timeout. It can also\n be a pair (tuple) of (connection, read) timeouts.\n Default is None.\n _check_input_type (bool): specifies if type checking\n should be done one the data sent to the server.\n Default is True.\n _check_return_type (bool): specifies if type checking\n should be done one the data received from the server.\n Default is True.\n _spec_property_naming (bool): True if the variable names in the input data\n are serialized names, as specified in the OpenAPI document.\n False if the variable names in the input data\n are pythonic names, e.g. snake case (default)\n _content_type (str/None): force body content-type.\n Default is None and content-type will be predicted by allowed\n content-types and body.\n _host_index (int/None): specifies the index of the server\n that we want to use.\n Default is read from the configuration.\n Returns:\n ComponentSummaryRoot\n Response Object\n '
self.apply_kwargs_defaults(kwargs=kwargs, return_http_data_only=True, async_req=False)
kwargs['document'] = document
return self.get_spar_components_endpoint.call_with_http_info(**kwargs)<|docstring|>Get SPAR components # noqa: E501
This endpoint returns the list of SPAR components in a given SPAR document. # noqa: E501
This method makes a synchronous HTTP request. Returns the http data only
Args:
document (str): Document Name. defaults to "Client:Foo", must be one of ["Client:Foo"]
Keyword Args:
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (int/float/tuple): timeout setting for this request. If
one number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_content_type (str/None): force body content-type.
Default is None and content-type will be predicted by allowed
content-types and body.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
Returns:
ComponentSummaryRoot
Response Object<|endoftext|>
|
39399eeb1b4484c1a4b367fd700ef904a23fbe7c7776df6954d5b94112377748
|
def get_spar_components_with_http_info(self, document='Client:Foo', **kwargs) -> typing.Tuple[(ComponentSummaryRoot, int, typing.MutableMapping)]:
'Get SPAR components # noqa: E501\n\n This endpoint returns the list of SPAR components in a given SPAR document. # noqa: E501\n This method makes a synchronous HTTP request. Returns http data, http status and headers\n\n Args:\n document (str): Document Name. defaults to "Client:Foo", must be one of ["Client:Foo"]\n\n Keyword Args:\n _preload_content (bool): if False, the urllib3.HTTPResponse object\n will be returned without reading/decoding response data.\n Default is True.\n _request_timeout (int/float/tuple): timeout setting for this request. If\n one number provided, it will be total request timeout. It can also\n be a pair (tuple) of (connection, read) timeouts.\n Default is None.\n _check_input_type (bool): specifies if type checking\n should be done one the data sent to the server.\n Default is True.\n _check_return_type (bool): specifies if type checking\n should be done one the data received from the server.\n Default is True.\n _spec_property_naming (bool): True if the variable names in the input data\n are serialized names, as specified in the OpenAPI document.\n False if the variable names in the input data\n are pythonic names, e.g. snake case (default)\n _content_type (str/None): force body content-type.\n Default is None and content-type will be predicted by allowed\n content-types and body.\n _host_index (int/None): specifies the index of the server\n that we want to use.\n Default is read from the configuration.\n Returns:\n ComponentSummaryRoot\n Response Object\n int\n Http Status Code\n dict\n Dictionary of the response headers\n '
self.apply_kwargs_defaults(kwargs=kwargs, return_http_data_only=False, async_req=False)
kwargs['document'] = document
return self.get_spar_components_endpoint.call_with_http_info(**kwargs)
|
Get SPAR components # noqa: E501
This endpoint returns the list of SPAR components in a given SPAR document. # noqa: E501
This method makes a synchronous HTTP request. Returns http data, http status and headers
Args:
document (str): Document Name. defaults to "Client:Foo", must be one of ["Client:Foo"]
Keyword Args:
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (int/float/tuple): timeout setting for this request. If
one number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_content_type (str/None): force body content-type.
Default is None and content-type will be predicted by allowed
content-types and body.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
Returns:
ComponentSummaryRoot
Response Object
int
Http Status Code
dict
Dictionary of the response headers
|
code/python/SPAREngine/v3/fds/sdk/SPAREngine/api/components_api.py
|
get_spar_components_with_http_info
|
factset/enterprise-sdk
| 6
|
python
|
def get_spar_components_with_http_info(self, document='Client:Foo', **kwargs) -> typing.Tuple[(ComponentSummaryRoot, int, typing.MutableMapping)]:
'Get SPAR components # noqa: E501\n\n This endpoint returns the list of SPAR components in a given SPAR document. # noqa: E501\n This method makes a synchronous HTTP request. Returns http data, http status and headers\n\n Args:\n document (str): Document Name. defaults to "Client:Foo", must be one of ["Client:Foo"]\n\n Keyword Args:\n _preload_content (bool): if False, the urllib3.HTTPResponse object\n will be returned without reading/decoding response data.\n Default is True.\n _request_timeout (int/float/tuple): timeout setting for this request. If\n one number provided, it will be total request timeout. It can also\n be a pair (tuple) of (connection, read) timeouts.\n Default is None.\n _check_input_type (bool): specifies if type checking\n should be done one the data sent to the server.\n Default is True.\n _check_return_type (bool): specifies if type checking\n should be done one the data received from the server.\n Default is True.\n _spec_property_naming (bool): True if the variable names in the input data\n are serialized names, as specified in the OpenAPI document.\n False if the variable names in the input data\n are pythonic names, e.g. snake case (default)\n _content_type (str/None): force body content-type.\n Default is None and content-type will be predicted by allowed\n content-types and body.\n _host_index (int/None): specifies the index of the server\n that we want to use.\n Default is read from the configuration.\n Returns:\n ComponentSummaryRoot\n Response Object\n int\n Http Status Code\n dict\n Dictionary of the response headers\n '
self.apply_kwargs_defaults(kwargs=kwargs, return_http_data_only=False, async_req=False)
kwargs['document'] = document
return self.get_spar_components_endpoint.call_with_http_info(**kwargs)
|
def get_spar_components_with_http_info(self, document='Client:Foo', **kwargs) -> typing.Tuple[(ComponentSummaryRoot, int, typing.MutableMapping)]:
'Get SPAR components # noqa: E501\n\n This endpoint returns the list of SPAR components in a given SPAR document. # noqa: E501\n This method makes a synchronous HTTP request. Returns http data, http status and headers\n\n Args:\n document (str): Document Name. defaults to "Client:Foo", must be one of ["Client:Foo"]\n\n Keyword Args:\n _preload_content (bool): if False, the urllib3.HTTPResponse object\n will be returned without reading/decoding response data.\n Default is True.\n _request_timeout (int/float/tuple): timeout setting for this request. If\n one number provided, it will be total request timeout. It can also\n be a pair (tuple) of (connection, read) timeouts.\n Default is None.\n _check_input_type (bool): specifies if type checking\n should be done one the data sent to the server.\n Default is True.\n _check_return_type (bool): specifies if type checking\n should be done one the data received from the server.\n Default is True.\n _spec_property_naming (bool): True if the variable names in the input data\n are serialized names, as specified in the OpenAPI document.\n False if the variable names in the input data\n are pythonic names, e.g. snake case (default)\n _content_type (str/None): force body content-type.\n Default is None and content-type will be predicted by allowed\n content-types and body.\n _host_index (int/None): specifies the index of the server\n that we want to use.\n Default is read from the configuration.\n Returns:\n ComponentSummaryRoot\n Response Object\n int\n Http Status Code\n dict\n Dictionary of the response headers\n '
self.apply_kwargs_defaults(kwargs=kwargs, return_http_data_only=False, async_req=False)
kwargs['document'] = document
return self.get_spar_components_endpoint.call_with_http_info(**kwargs)<|docstring|>Get SPAR components # noqa: E501
This endpoint returns the list of SPAR components in a given SPAR document. # noqa: E501
This method makes a synchronous HTTP request. Returns http data, http status and headers
Args:
document (str): Document Name. defaults to "Client:Foo", must be one of ["Client:Foo"]
Keyword Args:
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (int/float/tuple): timeout setting for this request. If
one number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_content_type (str/None): force body content-type.
Default is None and content-type will be predicted by allowed
content-types and body.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
Returns:
ComponentSummaryRoot
Response Object
int
Http Status Code
dict
Dictionary of the response headers<|endoftext|>
|
5aa11e1ee17d4574e9609763c1ed6876fa21c459cb8d824df3fb18548d81fdc4
|
def get_spar_components_async(self, document='Client:Foo', **kwargs) -> 'ApplyResult[ComponentSummaryRoot]':
'Get SPAR components # noqa: E501\n\n This endpoint returns the list of SPAR components in a given SPAR document. # noqa: E501\n This method makes a asynchronous HTTP request. Returns the http data, wrapped in ApplyResult\n\n Args:\n document (str): Document Name. defaults to "Client:Foo", must be one of ["Client:Foo"]\n\n Keyword Args:\n _preload_content (bool): if False, the urllib3.HTTPResponse object\n will be returned without reading/decoding response data.\n Default is True.\n _request_timeout (int/float/tuple): timeout setting for this request. If\n one number provided, it will be total request timeout. It can also\n be a pair (tuple) of (connection, read) timeouts.\n Default is None.\n _check_input_type (bool): specifies if type checking\n should be done one the data sent to the server.\n Default is True.\n _check_return_type (bool): specifies if type checking\n should be done one the data received from the server.\n Default is True.\n _spec_property_naming (bool): True if the variable names in the input data\n are serialized names, as specified in the OpenAPI document.\n False if the variable names in the input data\n are pythonic names, e.g. snake case (default)\n _content_type (str/None): force body content-type.\n Default is None and content-type will be predicted by allowed\n content-types and body.\n _host_index (int/None): specifies the index of the server\n that we want to use.\n Default is read from the configuration.\n Returns:\n ApplyResult[ComponentSummaryRoot]\n '
self.apply_kwargs_defaults(kwargs=kwargs, return_http_data_only=True, async_req=True)
kwargs['document'] = document
return self.get_spar_components_endpoint.call_with_http_info(**kwargs)
|
Get SPAR components # noqa: E501
This endpoint returns the list of SPAR components in a given SPAR document. # noqa: E501
This method makes a asynchronous HTTP request. Returns the http data, wrapped in ApplyResult
Args:
document (str): Document Name. defaults to "Client:Foo", must be one of ["Client:Foo"]
Keyword Args:
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (int/float/tuple): timeout setting for this request. If
one number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_content_type (str/None): force body content-type.
Default is None and content-type will be predicted by allowed
content-types and body.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
Returns:
ApplyResult[ComponentSummaryRoot]
|
code/python/SPAREngine/v3/fds/sdk/SPAREngine/api/components_api.py
|
get_spar_components_async
|
factset/enterprise-sdk
| 6
|
python
|
def get_spar_components_async(self, document='Client:Foo', **kwargs) -> 'ApplyResult[ComponentSummaryRoot]':
'Get SPAR components # noqa: E501\n\n This endpoint returns the list of SPAR components in a given SPAR document. # noqa: E501\n This method makes a asynchronous HTTP request. Returns the http data, wrapped in ApplyResult\n\n Args:\n document (str): Document Name. defaults to "Client:Foo", must be one of ["Client:Foo"]\n\n Keyword Args:\n _preload_content (bool): if False, the urllib3.HTTPResponse object\n will be returned without reading/decoding response data.\n Default is True.\n _request_timeout (int/float/tuple): timeout setting for this request. If\n one number provided, it will be total request timeout. It can also\n be a pair (tuple) of (connection, read) timeouts.\n Default is None.\n _check_input_type (bool): specifies if type checking\n should be done one the data sent to the server.\n Default is True.\n _check_return_type (bool): specifies if type checking\n should be done one the data received from the server.\n Default is True.\n _spec_property_naming (bool): True if the variable names in the input data\n are serialized names, as specified in the OpenAPI document.\n False if the variable names in the input data\n are pythonic names, e.g. snake case (default)\n _content_type (str/None): force body content-type.\n Default is None and content-type will be predicted by allowed\n content-types and body.\n _host_index (int/None): specifies the index of the server\n that we want to use.\n Default is read from the configuration.\n Returns:\n ApplyResult[ComponentSummaryRoot]\n '
self.apply_kwargs_defaults(kwargs=kwargs, return_http_data_only=True, async_req=True)
kwargs['document'] = document
return self.get_spar_components_endpoint.call_with_http_info(**kwargs)
|
def get_spar_components_async(self, document='Client:Foo', **kwargs) -> 'ApplyResult[ComponentSummaryRoot]':
'Get SPAR components # noqa: E501\n\n This endpoint returns the list of SPAR components in a given SPAR document. # noqa: E501\n This method makes a asynchronous HTTP request. Returns the http data, wrapped in ApplyResult\n\n Args:\n document (str): Document Name. defaults to "Client:Foo", must be one of ["Client:Foo"]\n\n Keyword Args:\n _preload_content (bool): if False, the urllib3.HTTPResponse object\n will be returned without reading/decoding response data.\n Default is True.\n _request_timeout (int/float/tuple): timeout setting for this request. If\n one number provided, it will be total request timeout. It can also\n be a pair (tuple) of (connection, read) timeouts.\n Default is None.\n _check_input_type (bool): specifies if type checking\n should be done one the data sent to the server.\n Default is True.\n _check_return_type (bool): specifies if type checking\n should be done one the data received from the server.\n Default is True.\n _spec_property_naming (bool): True if the variable names in the input data\n are serialized names, as specified in the OpenAPI document.\n False if the variable names in the input data\n are pythonic names, e.g. snake case (default)\n _content_type (str/None): force body content-type.\n Default is None and content-type will be predicted by allowed\n content-types and body.\n _host_index (int/None): specifies the index of the server\n that we want to use.\n Default is read from the configuration.\n Returns:\n ApplyResult[ComponentSummaryRoot]\n '
self.apply_kwargs_defaults(kwargs=kwargs, return_http_data_only=True, async_req=True)
kwargs['document'] = document
return self.get_spar_components_endpoint.call_with_http_info(**kwargs)<|docstring|>Get SPAR components # noqa: E501
This endpoint returns the list of SPAR components in a given SPAR document. # noqa: E501
This method makes a asynchronous HTTP request. Returns the http data, wrapped in ApplyResult
Args:
document (str): Document Name. defaults to "Client:Foo", must be one of ["Client:Foo"]
Keyword Args:
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (int/float/tuple): timeout setting for this request. If
one number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_content_type (str/None): force body content-type.
Default is None and content-type will be predicted by allowed
content-types and body.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
Returns:
ApplyResult[ComponentSummaryRoot]<|endoftext|>
|
8ad6fb8adeef973b2f56940256309ed251c520736cf79d9a44922d7c5f83b500
|
def get_spar_components_with_http_info_async(self, document='Client:Foo', **kwargs) -> 'ApplyResult[typing.Tuple[ComponentSummaryRoot, int, typing.MutableMapping]]':
'Get SPAR components # noqa: E501\n\n This endpoint returns the list of SPAR components in a given SPAR document. # noqa: E501\n This method makes a asynchronous HTTP request. Returns http data, http status and headers, wrapped in ApplyResult\n\n Args:\n document (str): Document Name. defaults to "Client:Foo", must be one of ["Client:Foo"]\n\n Keyword Args:\n _preload_content (bool): if False, the urllib3.HTTPResponse object\n will be returned without reading/decoding response data.\n Default is True.\n _request_timeout (int/float/tuple): timeout setting for this request. If\n one number provided, it will be total request timeout. It can also\n be a pair (tuple) of (connection, read) timeouts.\n Default is None.\n _check_input_type (bool): specifies if type checking\n should be done one the data sent to the server.\n Default is True.\n _check_return_type (bool): specifies if type checking\n should be done one the data received from the server.\n Default is True.\n _spec_property_naming (bool): True if the variable names in the input data\n are serialized names, as specified in the OpenAPI document.\n False if the variable names in the input data\n are pythonic names, e.g. snake case (default)\n _content_type (str/None): force body content-type.\n Default is None and content-type will be predicted by allowed\n content-types and body.\n _host_index (int/None): specifies the index of the server\n that we want to use.\n Default is read from the configuration.\n Returns:\n ApplyResult[(ComponentSummaryRoot, int, typing.Dict)]\n '
self.apply_kwargs_defaults(kwargs=kwargs, return_http_data_only=False, async_req=True)
kwargs['document'] = document
return self.get_spar_components_endpoint.call_with_http_info(**kwargs)
|
Get SPAR components # noqa: E501
This endpoint returns the list of SPAR components in a given SPAR document. # noqa: E501
This method makes a asynchronous HTTP request. Returns http data, http status and headers, wrapped in ApplyResult
Args:
document (str): Document Name. defaults to "Client:Foo", must be one of ["Client:Foo"]
Keyword Args:
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (int/float/tuple): timeout setting for this request. If
one number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_content_type (str/None): force body content-type.
Default is None and content-type will be predicted by allowed
content-types and body.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
Returns:
ApplyResult[(ComponentSummaryRoot, int, typing.Dict)]
|
code/python/SPAREngine/v3/fds/sdk/SPAREngine/api/components_api.py
|
get_spar_components_with_http_info_async
|
factset/enterprise-sdk
| 6
|
python
|
def get_spar_components_with_http_info_async(self, document='Client:Foo', **kwargs) -> 'ApplyResult[typing.Tuple[ComponentSummaryRoot, int, typing.MutableMapping]]':
'Get SPAR components # noqa: E501\n\n This endpoint returns the list of SPAR components in a given SPAR document. # noqa: E501\n This method makes a asynchronous HTTP request. Returns http data, http status and headers, wrapped in ApplyResult\n\n Args:\n document (str): Document Name. defaults to "Client:Foo", must be one of ["Client:Foo"]\n\n Keyword Args:\n _preload_content (bool): if False, the urllib3.HTTPResponse object\n will be returned without reading/decoding response data.\n Default is True.\n _request_timeout (int/float/tuple): timeout setting for this request. If\n one number provided, it will be total request timeout. It can also\n be a pair (tuple) of (connection, read) timeouts.\n Default is None.\n _check_input_type (bool): specifies if type checking\n should be done one the data sent to the server.\n Default is True.\n _check_return_type (bool): specifies if type checking\n should be done one the data received from the server.\n Default is True.\n _spec_property_naming (bool): True if the variable names in the input data\n are serialized names, as specified in the OpenAPI document.\n False if the variable names in the input data\n are pythonic names, e.g. snake case (default)\n _content_type (str/None): force body content-type.\n Default is None and content-type will be predicted by allowed\n content-types and body.\n _host_index (int/None): specifies the index of the server\n that we want to use.\n Default is read from the configuration.\n Returns:\n ApplyResult[(ComponentSummaryRoot, int, typing.Dict)]\n '
self.apply_kwargs_defaults(kwargs=kwargs, return_http_data_only=False, async_req=True)
kwargs['document'] = document
return self.get_spar_components_endpoint.call_with_http_info(**kwargs)
|
def get_spar_components_with_http_info_async(self, document='Client:Foo', **kwargs) -> 'ApplyResult[typing.Tuple[ComponentSummaryRoot, int, typing.MutableMapping]]':
'Get SPAR components # noqa: E501\n\n This endpoint returns the list of SPAR components in a given SPAR document. # noqa: E501\n This method makes a asynchronous HTTP request. Returns http data, http status and headers, wrapped in ApplyResult\n\n Args:\n document (str): Document Name. defaults to "Client:Foo", must be one of ["Client:Foo"]\n\n Keyword Args:\n _preload_content (bool): if False, the urllib3.HTTPResponse object\n will be returned without reading/decoding response data.\n Default is True.\n _request_timeout (int/float/tuple): timeout setting for this request. If\n one number provided, it will be total request timeout. It can also\n be a pair (tuple) of (connection, read) timeouts.\n Default is None.\n _check_input_type (bool): specifies if type checking\n should be done one the data sent to the server.\n Default is True.\n _check_return_type (bool): specifies if type checking\n should be done one the data received from the server.\n Default is True.\n _spec_property_naming (bool): True if the variable names in the input data\n are serialized names, as specified in the OpenAPI document.\n False if the variable names in the input data\n are pythonic names, e.g. snake case (default)\n _content_type (str/None): force body content-type.\n Default is None and content-type will be predicted by allowed\n content-types and body.\n _host_index (int/None): specifies the index of the server\n that we want to use.\n Default is read from the configuration.\n Returns:\n ApplyResult[(ComponentSummaryRoot, int, typing.Dict)]\n '
self.apply_kwargs_defaults(kwargs=kwargs, return_http_data_only=False, async_req=True)
kwargs['document'] = document
return self.get_spar_components_endpoint.call_with_http_info(**kwargs)<|docstring|>Get SPAR components # noqa: E501
This endpoint returns the list of SPAR components in a given SPAR document. # noqa: E501
This method makes a asynchronous HTTP request. Returns http data, http status and headers, wrapped in ApplyResult
Args:
document (str): Document Name. defaults to "Client:Foo", must be one of ["Client:Foo"]
Keyword Args:
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (int/float/tuple): timeout setting for this request. If
one number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_content_type (str/None): force body content-type.
Default is None and content-type will be predicted by allowed
content-types and body.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
Returns:
ApplyResult[(ComponentSummaryRoot, int, typing.Dict)]<|endoftext|>
|
9c2a23dc224f0aad43417a7b88ae90f4c1e9b6c032e8b764d4cad1f986fc41b2
|
@contextmanager
def key(mesg=None):
"\n Wrapper for curses module to simplify getting a single keypress from the terminal (default), a buttonbox, or a\n figure. Set slab.psychoacoustics.input_method = 'buttonbox' to use a custom USB buttonbox or to 'figure' to open\n a figure called 'stairs' (if not already opened by the `slab.Staricase.plot` method). Optianally takes a string\n argument which is printed in the terminal for conveying instructions to the participant.\n\n Example::\n\n with slab.key('Waiting for buttons 1 (yes) or 2 (no).') as key:\n response = key.getch()\n "
if (input_method == 'keyboard'):
if (curses is None):
raise ImportError('You need curses to use the keypress class (pip install curses (or windows-curses))')
curses.filter()
stdscr = curses.initscr()
curses.noecho()
curses.cbreak()
stdscr.clear()
stdscr.refresh()
if (mesg is not None):
stdscr.addstr(str(mesg))
(yield stdscr)
curses.nocbreak()
curses.echo()
curses.endwin()
elif (input_method == 'buttonbox'):
if (mesg is not None):
print(mesg)
(yield _Buttonbox)
elif (input_method == 'figure'):
if (mesg is not None):
print(mesg)
(yield _FigChar)
else:
raise ValueError('Unknown input method!')
|
Wrapper for curses module to simplify getting a single keypress from the terminal (default), a buttonbox, or a
figure. Set slab.psychoacoustics.input_method = 'buttonbox' to use a custom USB buttonbox or to 'figure' to open
a figure called 'stairs' (if not already opened by the `slab.Staricase.plot` method). Optianally takes a string
argument which is printed in the terminal for conveying instructions to the participant.
Example::
with slab.key('Waiting for buttons 1 (yes) or 2 (no).') as key:
response = key.getch()
|
slab/psychoacoustics.py
|
key
|
jakab13/slab
| 7
|
python
|
@contextmanager
def key(mesg=None):
"\n Wrapper for curses module to simplify getting a single keypress from the terminal (default), a buttonbox, or a\n figure. Set slab.psychoacoustics.input_method = 'buttonbox' to use a custom USB buttonbox or to 'figure' to open\n a figure called 'stairs' (if not already opened by the `slab.Staricase.plot` method). Optianally takes a string\n argument which is printed in the terminal for conveying instructions to the participant.\n\n Example::\n\n with slab.key('Waiting for buttons 1 (yes) or 2 (no).') as key:\n response = key.getch()\n "
if (input_method == 'keyboard'):
if (curses is None):
raise ImportError('You need curses to use the keypress class (pip install curses (or windows-curses))')
curses.filter()
stdscr = curses.initscr()
curses.noecho()
curses.cbreak()
stdscr.clear()
stdscr.refresh()
if (mesg is not None):
stdscr.addstr(str(mesg))
(yield stdscr)
curses.nocbreak()
curses.echo()
curses.endwin()
elif (input_method == 'buttonbox'):
if (mesg is not None):
print(mesg)
(yield _Buttonbox)
elif (input_method == 'figure'):
if (mesg is not None):
print(mesg)
(yield _FigChar)
else:
raise ValueError('Unknown input method!')
|
@contextmanager
def key(mesg=None):
"\n Wrapper for curses module to simplify getting a single keypress from the terminal (default), a buttonbox, or a\n figure. Set slab.psychoacoustics.input_method = 'buttonbox' to use a custom USB buttonbox or to 'figure' to open\n a figure called 'stairs' (if not already opened by the `slab.Staricase.plot` method). Optianally takes a string\n argument which is printed in the terminal for conveying instructions to the participant.\n\n Example::\n\n with slab.key('Waiting for buttons 1 (yes) or 2 (no).') as key:\n response = key.getch()\n "
if (input_method == 'keyboard'):
if (curses is None):
raise ImportError('You need curses to use the keypress class (pip install curses (or windows-curses))')
curses.filter()
stdscr = curses.initscr()
curses.noecho()
curses.cbreak()
stdscr.clear()
stdscr.refresh()
if (mesg is not None):
stdscr.addstr(str(mesg))
(yield stdscr)
curses.nocbreak()
curses.echo()
curses.endwin()
elif (input_method == 'buttonbox'):
if (mesg is not None):
print(mesg)
(yield _Buttonbox)
elif (input_method == 'figure'):
if (mesg is not None):
print(mesg)
(yield _FigChar)
else:
raise ValueError('Unknown input method!')<|docstring|>Wrapper for curses module to simplify getting a single keypress from the terminal (default), a buttonbox, or a
figure. Set slab.psychoacoustics.input_method = 'buttonbox' to use a custom USB buttonbox or to 'figure' to open
a figure called 'stairs' (if not already opened by the `slab.Staricase.plot` method). Optianally takes a string
argument which is printed in the terminal for conveying instructions to the participant.
Example::
with slab.key('Waiting for buttons 1 (yes) or 2 (no).') as key:
response = key.getch()<|endoftext|>
|
5ea076528259b07d8b63a3e9011272eb64c48457365023304ef21289484d4dc6
|
def load_config(filename):
"\n Reads a text file with variable assignments. This is a simple convenience method that allows easy writing and\n loading of configuration text files. Experiments sometimes use configuration files when experimenters (who might\n not by Python programmers) need to set parameters without changing the code. The format is a plain text file with a\n variable assignment on each line, because it is meant to be written and changed by humans. These variables and their\n values are then accessible as a namedtuple.\n\n Arguments:\n filename (str | pathlib.Path): path to the file to be read.\n Returns:\n (collections.namedtuple): a tuple containing the variables and values defined in the text file.\n Example::\n\n # assuming there is a file named 'example.txt' with the following content:\n samplerate = 32000\n pause_duration = 30\n speeds = [60,120,180]\n # call load_config to parse the file into a named tuple:\n conf = load_config('example.txt')\n conf.speeds\n # Out: [60, 120, 180]\n "
from collections import namedtuple
with open(filename, 'r') as f:
lines = f.readlines()
if lines:
var_names = []
values = []
for line in lines:
(var, val) = line.strip().split('=')
var_names.append(var.strip())
values.append(eval(val.strip()))
config_tuple = namedtuple('config', var_names)
return config_tuple(*values)
|
Reads a text file with variable assignments. This is a simple convenience method that allows easy writing and
loading of configuration text files. Experiments sometimes use configuration files when experimenters (who might
not by Python programmers) need to set parameters without changing the code. The format is a plain text file with a
variable assignment on each line, because it is meant to be written and changed by humans. These variables and their
values are then accessible as a namedtuple.
Arguments:
filename (str | pathlib.Path): path to the file to be read.
Returns:
(collections.namedtuple): a tuple containing the variables and values defined in the text file.
Example::
# assuming there is a file named 'example.txt' with the following content:
samplerate = 32000
pause_duration = 30
speeds = [60,120,180]
# call load_config to parse the file into a named tuple:
conf = load_config('example.txt')
conf.speeds
# Out: [60, 120, 180]
|
slab/psychoacoustics.py
|
load_config
|
jakab13/slab
| 7
|
python
|
def load_config(filename):
"\n Reads a text file with variable assignments. This is a simple convenience method that allows easy writing and\n loading of configuration text files. Experiments sometimes use configuration files when experimenters (who might\n not by Python programmers) need to set parameters without changing the code. The format is a plain text file with a\n variable assignment on each line, because it is meant to be written and changed by humans. These variables and their\n values are then accessible as a namedtuple.\n\n Arguments:\n filename (str | pathlib.Path): path to the file to be read.\n Returns:\n (collections.namedtuple): a tuple containing the variables and values defined in the text file.\n Example::\n\n # assuming there is a file named 'example.txt' with the following content:\n samplerate = 32000\n pause_duration = 30\n speeds = [60,120,180]\n # call load_config to parse the file into a named tuple:\n conf = load_config('example.txt')\n conf.speeds\n # Out: [60, 120, 180]\n "
from collections import namedtuple
with open(filename, 'r') as f:
lines = f.readlines()
if lines:
var_names = []
values = []
for line in lines:
(var, val) = line.strip().split('=')
var_names.append(var.strip())
values.append(eval(val.strip()))
config_tuple = namedtuple('config', var_names)
return config_tuple(*values)
|
def load_config(filename):
"\n Reads a text file with variable assignments. This is a simple convenience method that allows easy writing and\n loading of configuration text files. Experiments sometimes use configuration files when experimenters (who might\n not by Python programmers) need to set parameters without changing the code. The format is a plain text file with a\n variable assignment on each line, because it is meant to be written and changed by humans. These variables and their\n values are then accessible as a namedtuple.\n\n Arguments:\n filename (str | pathlib.Path): path to the file to be read.\n Returns:\n (collections.namedtuple): a tuple containing the variables and values defined in the text file.\n Example::\n\n # assuming there is a file named 'example.txt' with the following content:\n samplerate = 32000\n pause_duration = 30\n speeds = [60,120,180]\n # call load_config to parse the file into a named tuple:\n conf = load_config('example.txt')\n conf.speeds\n # Out: [60, 120, 180]\n "
from collections import namedtuple
with open(filename, 'r') as f:
lines = f.readlines()
if lines:
var_names = []
values = []
for line in lines:
(var, val) = line.strip().split('=')
var_names.append(var.strip())
values.append(eval(val.strip()))
config_tuple = namedtuple('config', var_names)
return config_tuple(*values)<|docstring|>Reads a text file with variable assignments. This is a simple convenience method that allows easy writing and
loading of configuration text files. Experiments sometimes use configuration files when experimenters (who might
not by Python programmers) need to set parameters without changing the code. The format is a plain text file with a
variable assignment on each line, because it is meant to be written and changed by humans. These variables and their
values are then accessible as a namedtuple.
Arguments:
filename (str | pathlib.Path): path to the file to be read.
Returns:
(collections.namedtuple): a tuple containing the variables and values defined in the text file.
Example::
# assuming there is a file named 'example.txt' with the following content:
samplerate = 32000
pause_duration = 30
speeds = [60,120,180]
# call load_config to parse the file into a named tuple:
conf = load_config('example.txt')
conf.speeds
# Out: [60, 120, 180]<|endoftext|>
|
3d8951f0bb8911f112b568d5bddb961aa997a6bdd236168a88e231a6a205320a
|
def save_pickle(self, file_name, clobber=False):
'\n Save the object as pickle file.\n\n Arguments:\n file_name (str | pathlib.Path): name of the file to create.\n clobber (bool): overwrite existing file with the same name, defaults to False.\n Returns:\n (bool): True if writing was successful.\n '
if isinstance(file_name, pathlib.Path):
file_name = str(file_name)
if (pathlib.Path(file_name).exists() and (not clobber)):
raise FileExistsError('Select clobber=True to overwrite.')
with open(file_name, 'wb') as fp:
pickle.dump(self.__dict__, fp, protocol=pickle.HIGHEST_PROTOCOL)
return True
|
Save the object as pickle file.
Arguments:
file_name (str | pathlib.Path): name of the file to create.
clobber (bool): overwrite existing file with the same name, defaults to False.
Returns:
(bool): True if writing was successful.
|
slab/psychoacoustics.py
|
save_pickle
|
jakab13/slab
| 7
|
python
|
def save_pickle(self, file_name, clobber=False):
'\n Save the object as pickle file.\n\n Arguments:\n file_name (str | pathlib.Path): name of the file to create.\n clobber (bool): overwrite existing file with the same name, defaults to False.\n Returns:\n (bool): True if writing was successful.\n '
if isinstance(file_name, pathlib.Path):
file_name = str(file_name)
if (pathlib.Path(file_name).exists() and (not clobber)):
raise FileExistsError('Select clobber=True to overwrite.')
with open(file_name, 'wb') as fp:
pickle.dump(self.__dict__, fp, protocol=pickle.HIGHEST_PROTOCOL)
return True
|
def save_pickle(self, file_name, clobber=False):
'\n Save the object as pickle file.\n\n Arguments:\n file_name (str | pathlib.Path): name of the file to create.\n clobber (bool): overwrite existing file with the same name, defaults to False.\n Returns:\n (bool): True if writing was successful.\n '
if isinstance(file_name, pathlib.Path):
file_name = str(file_name)
if (pathlib.Path(file_name).exists() and (not clobber)):
raise FileExistsError('Select clobber=True to overwrite.')
with open(file_name, 'wb') as fp:
pickle.dump(self.__dict__, fp, protocol=pickle.HIGHEST_PROTOCOL)
return True<|docstring|>Save the object as pickle file.
Arguments:
file_name (str | pathlib.Path): name of the file to create.
clobber (bool): overwrite existing file with the same name, defaults to False.
Returns:
(bool): True if writing was successful.<|endoftext|>
|
b8fc90fd7a9be32104fcf8b918a6f925d618a9b4697dab1c203c8503a3b75061
|
def load_pickle(self, file_name):
'\n Read pickle file and deserialize the object into `self.__dict__`.\n\n Attributes:\n file_name (str | pathlib.Path): name of the file to read.\n '
if isinstance(file_name, pathlib.Path):
file_name = str(file_name)
with open(file_name, 'rb') as fp:
self.__dict__ = pickle.load(fp)
|
Read pickle file and deserialize the object into `self.__dict__`.
Attributes:
file_name (str | pathlib.Path): name of the file to read.
|
slab/psychoacoustics.py
|
load_pickle
|
jakab13/slab
| 7
|
python
|
def load_pickle(self, file_name):
'\n Read pickle file and deserialize the object into `self.__dict__`.\n\n Attributes:\n file_name (str | pathlib.Path): name of the file to read.\n '
if isinstance(file_name, pathlib.Path):
file_name = str(file_name)
with open(file_name, 'rb') as fp:
self.__dict__ = pickle.load(fp)
|
def load_pickle(self, file_name):
'\n Read pickle file and deserialize the object into `self.__dict__`.\n\n Attributes:\n file_name (str | pathlib.Path): name of the file to read.\n '
if isinstance(file_name, pathlib.Path):
file_name = str(file_name)
with open(file_name, 'rb') as fp:
self.__dict__ = pickle.load(fp)<|docstring|>Read pickle file and deserialize the object into `self.__dict__`.
Attributes:
file_name (str | pathlib.Path): name of the file to read.<|endoftext|>
|
e3b836ac8a781a7c2039aaf049b1499ea7eb7fa90d9cae134715d48b66ee9b2e
|
def save_json(self, file_name=None, clobber=False):
"\n Save the object as JSON file. The object's __dict__ is serialized and saved in standard JSON format, so that it\n can be easily reconstituted (see load_json method). Raises FileExistsError if the file exists, unless `clobber`\n is True. When `file_name` in None (default), the method returns the JSON string, in case you want to inspect it.\n Note that Numpy arrays are not serializable and are converted to Python int. This works because the\n Trialsequence and Staircase classes use arrays of indices. If your instances of these classes contain arrays of\n float, use `save_pickle` instead.\n\n Arguments:\n file_name (str | pathlib.Path): name of the file to create. If None or 'stdout', return a JSON object.\n clobber (bool): overwrite existing file with the same name, defaults to False.\n Returns:\n (bool): True if writing was successful.\n "
def default(i):
return (int(i) if isinstance(i, numpy.int64) else i)
if isinstance(file_name, pathlib.Path):
file_name = str(file_name)
if ((file_name is None) or (file_name == 'stdout')):
return json.dumps(self.__dict__, indent=2, default=default)
if (pathlib.Path(file_name).exists() and (not clobber)):
raise FileExistsError('Select clobber=True to overwrite.')
try:
with open(file_name, 'w') as f:
json.dump(self.__dict__, f, indent=2, default=default)
return True
except (TypeError, ValueError):
print('Your sequence contains data which is not JSON serializable, use the save_pickle method instead.')
|
Save the object as JSON file. The object's __dict__ is serialized and saved in standard JSON format, so that it
can be easily reconstituted (see load_json method). Raises FileExistsError if the file exists, unless `clobber`
is True. When `file_name` in None (default), the method returns the JSON string, in case you want to inspect it.
Note that Numpy arrays are not serializable and are converted to Python int. This works because the
Trialsequence and Staircase classes use arrays of indices. If your instances of these classes contain arrays of
float, use `save_pickle` instead.
Arguments:
file_name (str | pathlib.Path): name of the file to create. If None or 'stdout', return a JSON object.
clobber (bool): overwrite existing file with the same name, defaults to False.
Returns:
(bool): True if writing was successful.
|
slab/psychoacoustics.py
|
save_json
|
jakab13/slab
| 7
|
python
|
def save_json(self, file_name=None, clobber=False):
"\n Save the object as JSON file. The object's __dict__ is serialized and saved in standard JSON format, so that it\n can be easily reconstituted (see load_json method). Raises FileExistsError if the file exists, unless `clobber`\n is True. When `file_name` in None (default), the method returns the JSON string, in case you want to inspect it.\n Note that Numpy arrays are not serializable and are converted to Python int. This works because the\n Trialsequence and Staircase classes use arrays of indices. If your instances of these classes contain arrays of\n float, use `save_pickle` instead.\n\n Arguments:\n file_name (str | pathlib.Path): name of the file to create. If None or 'stdout', return a JSON object.\n clobber (bool): overwrite existing file with the same name, defaults to False.\n Returns:\n (bool): True if writing was successful.\n "
def default(i):
return (int(i) if isinstance(i, numpy.int64) else i)
if isinstance(file_name, pathlib.Path):
file_name = str(file_name)
if ((file_name is None) or (file_name == 'stdout')):
return json.dumps(self.__dict__, indent=2, default=default)
if (pathlib.Path(file_name).exists() and (not clobber)):
raise FileExistsError('Select clobber=True to overwrite.')
try:
with open(file_name, 'w') as f:
json.dump(self.__dict__, f, indent=2, default=default)
return True
except (TypeError, ValueError):
print('Your sequence contains data which is not JSON serializable, use the save_pickle method instead.')
|
def save_json(self, file_name=None, clobber=False):
"\n Save the object as JSON file. The object's __dict__ is serialized and saved in standard JSON format, so that it\n can be easily reconstituted (see load_json method). Raises FileExistsError if the file exists, unless `clobber`\n is True. When `file_name` in None (default), the method returns the JSON string, in case you want to inspect it.\n Note that Numpy arrays are not serializable and are converted to Python int. This works because the\n Trialsequence and Staircase classes use arrays of indices. If your instances of these classes contain arrays of\n float, use `save_pickle` instead.\n\n Arguments:\n file_name (str | pathlib.Path): name of the file to create. If None or 'stdout', return a JSON object.\n clobber (bool): overwrite existing file with the same name, defaults to False.\n Returns:\n (bool): True if writing was successful.\n "
def default(i):
return (int(i) if isinstance(i, numpy.int64) else i)
if isinstance(file_name, pathlib.Path):
file_name = str(file_name)
if ((file_name is None) or (file_name == 'stdout')):
return json.dumps(self.__dict__, indent=2, default=default)
if (pathlib.Path(file_name).exists() and (not clobber)):
raise FileExistsError('Select clobber=True to overwrite.')
try:
with open(file_name, 'w') as f:
json.dump(self.__dict__, f, indent=2, default=default)
return True
except (TypeError, ValueError):
print('Your sequence contains data which is not JSON serializable, use the save_pickle method instead.')<|docstring|>Save the object as JSON file. The object's __dict__ is serialized and saved in standard JSON format, so that it
can be easily reconstituted (see load_json method). Raises FileExistsError if the file exists, unless `clobber`
is True. When `file_name` in None (default), the method returns the JSON string, in case you want to inspect it.
Note that Numpy arrays are not serializable and are converted to Python int. This works because the
Trialsequence and Staircase classes use arrays of indices. If your instances of these classes contain arrays of
float, use `save_pickle` instead.
Arguments:
file_name (str | pathlib.Path): name of the file to create. If None or 'stdout', return a JSON object.
clobber (bool): overwrite existing file with the same name, defaults to False.
Returns:
(bool): True if writing was successful.<|endoftext|>
|
ac91fab17882aee6f88a837b98ef31cdaccf58b62605d5910bfbec762292ec61
|
def load_json(self, file_name):
'\n Read JSON file and deserialize the object into `self.__dict__`.\n\n Attributes:\n file_name (str | pathlib.Path): name of the file to read.\n '
if isinstance(file_name, pathlib.Path):
file_name = str(file_name)
with open(file_name, 'r') as f:
self.__dict__ = json.load(f)
|
Read JSON file and deserialize the object into `self.__dict__`.
Attributes:
file_name (str | pathlib.Path): name of the file to read.
|
slab/psychoacoustics.py
|
load_json
|
jakab13/slab
| 7
|
python
|
def load_json(self, file_name):
'\n Read JSON file and deserialize the object into `self.__dict__`.\n\n Attributes:\n file_name (str | pathlib.Path): name of the file to read.\n '
if isinstance(file_name, pathlib.Path):
file_name = str(file_name)
with open(file_name, 'r') as f:
self.__dict__ = json.load(f)
|
def load_json(self, file_name):
'\n Read JSON file and deserialize the object into `self.__dict__`.\n\n Attributes:\n file_name (str | pathlib.Path): name of the file to read.\n '
if isinstance(file_name, pathlib.Path):
file_name = str(file_name)
with open(file_name, 'r') as f:
self.__dict__ = json.load(f)<|docstring|>Read JSON file and deserialize the object into `self.__dict__`.
Attributes:
file_name (str | pathlib.Path): name of the file to read.<|endoftext|>
|
834a74cb9ffe78e5f316f03b088fcc8ed4649eeef76c4ba1dd26b0213ded198a
|
def present_afc_trial(self, target, distractors, key_codes=range(49, 58), isi=0.25, print_info=True):
'\n Present the reference and distractor sounds in random order and acquire a response keypress.\n The subject has to identify at which position the reference was played. The result (True if response was correct\n or False if response was wrong) is stored in the sequence via the `add_response` method.\n\n Arguments:\n target (instance of slab.Sound): sound that ought to be identified in the trial\n distractors (instance or list of slab.Sound): distractor sound(s)\n key_codes (list of int): ascii codes for the response keys (get code for button \'1\': ord(\'1\') --> 49)\n pressing the second button in the list is equivalent to the response "the reference was the second sound\n played in this trial". Defaults to the key codes for buttons \'1\' to \'9\'\n isi (int or float): inter stimulus interval which is the pause between the end of one sound and the start\n of the next one.\n print_info (bool): If true, call the `print_trial_info` method afterwards\n '
if isinstance(distractors, list):
stims = ([target] + distractors)
else:
stims = [target, distractors]
order = numpy.random.permutation(len(stims))
for idx in order:
stim = stims[idx]
stim.play()
plt.pause(isi)
with key() as k:
response = k.getch()
interval = numpy.where((order == 0))[0][0]
interval_key = key_codes[interval]
response = (response == interval_key)
self.add_response(response)
if print_info:
self.print_trial_info()
|
Present the reference and distractor sounds in random order and acquire a response keypress.
The subject has to identify at which position the reference was played. The result (True if response was correct
or False if response was wrong) is stored in the sequence via the `add_response` method.
Arguments:
target (instance of slab.Sound): sound that ought to be identified in the trial
distractors (instance or list of slab.Sound): distractor sound(s)
key_codes (list of int): ascii codes for the response keys (get code for button '1': ord('1') --> 49)
pressing the second button in the list is equivalent to the response "the reference was the second sound
played in this trial". Defaults to the key codes for buttons '1' to '9'
isi (int or float): inter stimulus interval which is the pause between the end of one sound and the start
of the next one.
print_info (bool): If true, call the `print_trial_info` method afterwards
|
slab/psychoacoustics.py
|
present_afc_trial
|
jakab13/slab
| 7
|
python
|
def present_afc_trial(self, target, distractors, key_codes=range(49, 58), isi=0.25, print_info=True):
'\n Present the reference and distractor sounds in random order and acquire a response keypress.\n The subject has to identify at which position the reference was played. The result (True if response was correct\n or False if response was wrong) is stored in the sequence via the `add_response` method.\n\n Arguments:\n target (instance of slab.Sound): sound that ought to be identified in the trial\n distractors (instance or list of slab.Sound): distractor sound(s)\n key_codes (list of int): ascii codes for the response keys (get code for button \'1\': ord(\'1\') --> 49)\n pressing the second button in the list is equivalent to the response "the reference was the second sound\n played in this trial". Defaults to the key codes for buttons \'1\' to \'9\'\n isi (int or float): inter stimulus interval which is the pause between the end of one sound and the start\n of the next one.\n print_info (bool): If true, call the `print_trial_info` method afterwards\n '
if isinstance(distractors, list):
stims = ([target] + distractors)
else:
stims = [target, distractors]
order = numpy.random.permutation(len(stims))
for idx in order:
stim = stims[idx]
stim.play()
plt.pause(isi)
with key() as k:
response = k.getch()
interval = numpy.where((order == 0))[0][0]
interval_key = key_codes[interval]
response = (response == interval_key)
self.add_response(response)
if print_info:
self.print_trial_info()
|
def present_afc_trial(self, target, distractors, key_codes=range(49, 58), isi=0.25, print_info=True):
'\n Present the reference and distractor sounds in random order and acquire a response keypress.\n The subject has to identify at which position the reference was played. The result (True if response was correct\n or False if response was wrong) is stored in the sequence via the `add_response` method.\n\n Arguments:\n target (instance of slab.Sound): sound that ought to be identified in the trial\n distractors (instance or list of slab.Sound): distractor sound(s)\n key_codes (list of int): ascii codes for the response keys (get code for button \'1\': ord(\'1\') --> 49)\n pressing the second button in the list is equivalent to the response "the reference was the second sound\n played in this trial". Defaults to the key codes for buttons \'1\' to \'9\'\n isi (int or float): inter stimulus interval which is the pause between the end of one sound and the start\n of the next one.\n print_info (bool): If true, call the `print_trial_info` method afterwards\n '
if isinstance(distractors, list):
stims = ([target] + distractors)
else:
stims = [target, distractors]
order = numpy.random.permutation(len(stims))
for idx in order:
stim = stims[idx]
stim.play()
plt.pause(isi)
with key() as k:
response = k.getch()
interval = numpy.where((order == 0))[0][0]
interval_key = key_codes[interval]
response = (response == interval_key)
self.add_response(response)
if print_info:
self.print_trial_info()<|docstring|>Present the reference and distractor sounds in random order and acquire a response keypress.
The subject has to identify at which position the reference was played. The result (True if response was correct
or False if response was wrong) is stored in the sequence via the `add_response` method.
Arguments:
target (instance of slab.Sound): sound that ought to be identified in the trial
distractors (instance or list of slab.Sound): distractor sound(s)
key_codes (list of int): ascii codes for the response keys (get code for button '1': ord('1') --> 49)
pressing the second button in the list is equivalent to the response "the reference was the second sound
played in this trial". Defaults to the key codes for buttons '1' to '9'
isi (int or float): inter stimulus interval which is the pause between the end of one sound and the start
of the next one.
print_info (bool): If true, call the `print_trial_info` method afterwards<|endoftext|>
|
476c25d1ba409a1ccedafe92f58880f27e07ea0dd7274561172af831a3f44c5a
|
def present_tone_trial(self, stimulus, correct_key_idx=0, key_codes=range(49, 58), print_info=True):
"\n Present the reference and distractor sounds in random order and acquire a response keypress.\n The result (True if response was correct or False if response was wrong) is stored in the sequence via the\n `add_response` method.\n\n Arguments:\n stimulus (slab.Sound): sound played in the trial.\n correct_key_idx (int | list of int): index of the key in `key_codes` that represents a correct response.\n Response is correct if `response == key_codes[correct_key_idx]`. Can be a list of ints if several keys\n are counted as correct response.\n key_codes (list of int): ascii codes for the response keys (get code for button '1': ord('1') --> 49).\n print_info (bool): If true, call the `print_trial_info` method afterwards.\n "
stimulus.play()
with slab.key() as k:
response = k.getch()
response = (response in [key_codes[i] for i in correct_key_idx])
self.add_response(response)
if print_info:
self.print_trial_info()
|
Present the reference and distractor sounds in random order and acquire a response keypress.
The result (True if response was correct or False if response was wrong) is stored in the sequence via the
`add_response` method.
Arguments:
stimulus (slab.Sound): sound played in the trial.
correct_key_idx (int | list of int): index of the key in `key_codes` that represents a correct response.
Response is correct if `response == key_codes[correct_key_idx]`. Can be a list of ints if several keys
are counted as correct response.
key_codes (list of int): ascii codes for the response keys (get code for button '1': ord('1') --> 49).
print_info (bool): If true, call the `print_trial_info` method afterwards.
|
slab/psychoacoustics.py
|
present_tone_trial
|
jakab13/slab
| 7
|
python
|
def present_tone_trial(self, stimulus, correct_key_idx=0, key_codes=range(49, 58), print_info=True):
"\n Present the reference and distractor sounds in random order and acquire a response keypress.\n The result (True if response was correct or False if response was wrong) is stored in the sequence via the\n `add_response` method.\n\n Arguments:\n stimulus (slab.Sound): sound played in the trial.\n correct_key_idx (int | list of int): index of the key in `key_codes` that represents a correct response.\n Response is correct if `response == key_codes[correct_key_idx]`. Can be a list of ints if several keys\n are counted as correct response.\n key_codes (list of int): ascii codes for the response keys (get code for button '1': ord('1') --> 49).\n print_info (bool): If true, call the `print_trial_info` method afterwards.\n "
stimulus.play()
with slab.key() as k:
response = k.getch()
response = (response in [key_codes[i] for i in correct_key_idx])
self.add_response(response)
if print_info:
self.print_trial_info()
|
def present_tone_trial(self, stimulus, correct_key_idx=0, key_codes=range(49, 58), print_info=True):
"\n Present the reference and distractor sounds in random order and acquire a response keypress.\n The result (True if response was correct or False if response was wrong) is stored in the sequence via the\n `add_response` method.\n\n Arguments:\n stimulus (slab.Sound): sound played in the trial.\n correct_key_idx (int | list of int): index of the key in `key_codes` that represents a correct response.\n Response is correct if `response == key_codes[correct_key_idx]`. Can be a list of ints if several keys\n are counted as correct response.\n key_codes (list of int): ascii codes for the response keys (get code for button '1': ord('1') --> 49).\n print_info (bool): If true, call the `print_trial_info` method afterwards.\n "
stimulus.play()
with slab.key() as k:
response = k.getch()
response = (response in [key_codes[i] for i in correct_key_idx])
self.add_response(response)
if print_info:
self.print_trial_info()<|docstring|>Present the reference and distractor sounds in random order and acquire a response keypress.
The result (True if response was correct or False if response was wrong) is stored in the sequence via the
`add_response` method.
Arguments:
stimulus (slab.Sound): sound played in the trial.
correct_key_idx (int | list of int): index of the key in `key_codes` that represents a correct response.
Response is correct if `response == key_codes[correct_key_idx]`. Can be a list of ints if several keys
are counted as correct response.
key_codes (list of int): ascii codes for the response keys (get code for button '1': ord('1') --> 49).
print_info (bool): If true, call the `print_trial_info` method afterwards.<|endoftext|>
|
7abec54fd80fa595ef9ca680a60f4575d6dd97685058f9c9bac722fb19939dcc
|
def simulate_response(self, threshold=None, transition_width=2, intervals=1, hitrates=None):
'\n Return a simulated response to the current condition index value by calculating the hitrate from a\n psychometric (logistic) function. This is only sensible if trials is numeric and an interval scale representing\n a continuous stimulus value.\n\n Arguments:\n threshold(None | int | float): Midpoint of the psychometric function for adaptive testing. When the\n intensity of the current trial is equal to the `threshold` the hitrate is 50 percent.\n transition_width (int | float): range of stimulus intensities over which the hitrate increases\n from 0.25 to 0.75.\n intervals (int): use 1 (default) to indicate a yes/no trial, 2 or more to indicate an alternative forced\n choice trial. The number of choices determines the probability for a correct response by chance.\n hitrates (None | list | numpy.ndarray): list or numpy array of hitrates for the different conditions,\n to allow custom rates instead of simulation. If given, `threshold` and `transition_width` are not used.\n If a single value is given, this value is used.\n '
slope = (0.5 / transition_width)
if isinstance(self, slab.psychoacoustics.Trialsequence):
current_condition = self.trials[self.this_n]
elif isinstance(self, slab.psychoacoustics.Staircase):
current_condition = self._next_intensity
else:
return None
if (hitrates is None):
if (threshold is None):
raise ValueError("threshold can't be None if hitrates is None!")
hitrate = (1 / (1 + numpy.exp(((4 * slope) * (threshold - current_condition)))))
elif isinstance(hitrates, (list, numpy.ndarray)):
hitrate = hitrates[current_condition]
else:
hitrate = hitrates
hit = (numpy.random.rand() < hitrate)
if (hit or (intervals == 1)):
return hit
return (numpy.random.rand() < (1 / intervals))
|
Return a simulated response to the current condition index value by calculating the hitrate from a
psychometric (logistic) function. This is only sensible if trials is numeric and an interval scale representing
a continuous stimulus value.
Arguments:
threshold(None | int | float): Midpoint of the psychometric function for adaptive testing. When the
intensity of the current trial is equal to the `threshold` the hitrate is 50 percent.
transition_width (int | float): range of stimulus intensities over which the hitrate increases
from 0.25 to 0.75.
intervals (int): use 1 (default) to indicate a yes/no trial, 2 or more to indicate an alternative forced
choice trial. The number of choices determines the probability for a correct response by chance.
hitrates (None | list | numpy.ndarray): list or numpy array of hitrates for the different conditions,
to allow custom rates instead of simulation. If given, `threshold` and `transition_width` are not used.
If a single value is given, this value is used.
|
slab/psychoacoustics.py
|
simulate_response
|
jakab13/slab
| 7
|
python
|
def simulate_response(self, threshold=None, transition_width=2, intervals=1, hitrates=None):
'\n Return a simulated response to the current condition index value by calculating the hitrate from a\n psychometric (logistic) function. This is only sensible if trials is numeric and an interval scale representing\n a continuous stimulus value.\n\n Arguments:\n threshold(None | int | float): Midpoint of the psychometric function for adaptive testing. When the\n intensity of the current trial is equal to the `threshold` the hitrate is 50 percent.\n transition_width (int | float): range of stimulus intensities over which the hitrate increases\n from 0.25 to 0.75.\n intervals (int): use 1 (default) to indicate a yes/no trial, 2 or more to indicate an alternative forced\n choice trial. The number of choices determines the probability for a correct response by chance.\n hitrates (None | list | numpy.ndarray): list or numpy array of hitrates for the different conditions,\n to allow custom rates instead of simulation. If given, `threshold` and `transition_width` are not used.\n If a single value is given, this value is used.\n '
slope = (0.5 / transition_width)
if isinstance(self, slab.psychoacoustics.Trialsequence):
current_condition = self.trials[self.this_n]
elif isinstance(self, slab.psychoacoustics.Staircase):
current_condition = self._next_intensity
else:
return None
if (hitrates is None):
if (threshold is None):
raise ValueError("threshold can't be None if hitrates is None!")
hitrate = (1 / (1 + numpy.exp(((4 * slope) * (threshold - current_condition)))))
elif isinstance(hitrates, (list, numpy.ndarray)):
hitrate = hitrates[current_condition]
else:
hitrate = hitrates
hit = (numpy.random.rand() < hitrate)
if (hit or (intervals == 1)):
return hit
return (numpy.random.rand() < (1 / intervals))
|
def simulate_response(self, threshold=None, transition_width=2, intervals=1, hitrates=None):
'\n Return a simulated response to the current condition index value by calculating the hitrate from a\n psychometric (logistic) function. This is only sensible if trials is numeric and an interval scale representing\n a continuous stimulus value.\n\n Arguments:\n threshold(None | int | float): Midpoint of the psychometric function for adaptive testing. When the\n intensity of the current trial is equal to the `threshold` the hitrate is 50 percent.\n transition_width (int | float): range of stimulus intensities over which the hitrate increases\n from 0.25 to 0.75.\n intervals (int): use 1 (default) to indicate a yes/no trial, 2 or more to indicate an alternative forced\n choice trial. The number of choices determines the probability for a correct response by chance.\n hitrates (None | list | numpy.ndarray): list or numpy array of hitrates for the different conditions,\n to allow custom rates instead of simulation. If given, `threshold` and `transition_width` are not used.\n If a single value is given, this value is used.\n '
slope = (0.5 / transition_width)
if isinstance(self, slab.psychoacoustics.Trialsequence):
current_condition = self.trials[self.this_n]
elif isinstance(self, slab.psychoacoustics.Staircase):
current_condition = self._next_intensity
else:
return None
if (hitrates is None):
if (threshold is None):
raise ValueError("threshold can't be None if hitrates is None!")
hitrate = (1 / (1 + numpy.exp(((4 * slope) * (threshold - current_condition)))))
elif isinstance(hitrates, (list, numpy.ndarray)):
hitrate = hitrates[current_condition]
else:
hitrate = hitrates
hit = (numpy.random.rand() < hitrate)
if (hit or (intervals == 1)):
return hit
return (numpy.random.rand() < (1 / intervals))<|docstring|>Return a simulated response to the current condition index value by calculating the hitrate from a
psychometric (logistic) function. This is only sensible if trials is numeric and an interval scale representing
a continuous stimulus value.
Arguments:
threshold(None | int | float): Midpoint of the psychometric function for adaptive testing. When the
intensity of the current trial is equal to the `threshold` the hitrate is 50 percent.
transition_width (int | float): range of stimulus intensities over which the hitrate increases
from 0.25 to 0.75.
intervals (int): use 1 (default) to indicate a yes/no trial, 2 or more to indicate an alternative forced
choice trial. The number of choices determines the probability for a correct response by chance.
hitrates (None | list | numpy.ndarray): list or numpy array of hitrates for the different conditions,
to allow custom rates instead of simulation. If given, `threshold` and `transition_width` are not used.
If a single value is given, this value is used.<|endoftext|>
|
c187e80dcfa73f9a71b79fc904a2fb9f99be45664f93cef7fcdfe2c7caaad128
|
def __next__(self):
'\n Is called when iterating trough a sequenceAdvances to next trial and returns it. Updates attributes\n `this_trial` and `this_n`. If the trials have ended this method will raise a StopIteration.\n Returns:\n (int): current element of the list in `trials`\n '
self.this_n += 1
self.n_remaining -= 1
if (self.n_remaining < 0):
if (self.kind == 'infinite'):
self.trials = self._create_simple_sequence(len(self.conditions), self.n_reps, dont_start_with=self.trials[(- 1)])
self.this_n = 0
self.n_remaining = (self.n_trials - 1)
else:
self.this_trial = []
self.finished = True
if self.finished:
raise StopIteration
if (self.trials[self.this_n] == 0):
self.this_trial = 0
else:
self.this_trial = self.conditions[(self.trials[self.this_n] - 1)]
return self.this_trial
|
Is called when iterating trough a sequenceAdvances to next trial and returns it. Updates attributes
`this_trial` and `this_n`. If the trials have ended this method will raise a StopIteration.
Returns:
(int): current element of the list in `trials`
|
slab/psychoacoustics.py
|
__next__
|
jakab13/slab
| 7
|
python
|
def __next__(self):
'\n Is called when iterating trough a sequenceAdvances to next trial and returns it. Updates attributes\n `this_trial` and `this_n`. If the trials have ended this method will raise a StopIteration.\n Returns:\n (int): current element of the list in `trials`\n '
self.this_n += 1
self.n_remaining -= 1
if (self.n_remaining < 0):
if (self.kind == 'infinite'):
self.trials = self._create_simple_sequence(len(self.conditions), self.n_reps, dont_start_with=self.trials[(- 1)])
self.this_n = 0
self.n_remaining = (self.n_trials - 1)
else:
self.this_trial = []
self.finished = True
if self.finished:
raise StopIteration
if (self.trials[self.this_n] == 0):
self.this_trial = 0
else:
self.this_trial = self.conditions[(self.trials[self.this_n] - 1)]
return self.this_trial
|
def __next__(self):
'\n Is called when iterating trough a sequenceAdvances to next trial and returns it. Updates attributes\n `this_trial` and `this_n`. If the trials have ended this method will raise a StopIteration.\n Returns:\n (int): current element of the list in `trials`\n '
self.this_n += 1
self.n_remaining -= 1
if (self.n_remaining < 0):
if (self.kind == 'infinite'):
self.trials = self._create_simple_sequence(len(self.conditions), self.n_reps, dont_start_with=self.trials[(- 1)])
self.this_n = 0
self.n_remaining = (self.n_trials - 1)
else:
self.this_trial = []
self.finished = True
if self.finished:
raise StopIteration
if (self.trials[self.this_n] == 0):
self.this_trial = 0
else:
self.this_trial = self.conditions[(self.trials[self.this_n] - 1)]
return self.this_trial<|docstring|>Is called when iterating trough a sequenceAdvances to next trial and returns it. Updates attributes
`this_trial` and `this_n`. If the trials have ended this method will raise a StopIteration.
Returns:
(int): current element of the list in `trials`<|endoftext|>
|
faad33f44aac5bbb8fa7693e6630e5334595436eb1a2ad79de814637960c9cef
|
def add_response(self, response):
"\n Append response to the list in the `data` attribute belonging to the current trial (see Trialsequence doc).\n\n Attributes:\n response (any): data to append to the list. Can be anything but save_json method won't be available if\n the content of `response` is not JSON serializable (if it's an object for example).\n "
if (self.this_n < 0):
print("Can't add response because trial hasn't started yet!")
else:
self.data[self.this_n].append(response)
|
Append response to the list in the `data` attribute belonging to the current trial (see Trialsequence doc).
Attributes:
response (any): data to append to the list. Can be anything but save_json method won't be available if
the content of `response` is not JSON serializable (if it's an object for example).
|
slab/psychoacoustics.py
|
add_response
|
jakab13/slab
| 7
|
python
|
def add_response(self, response):
"\n Append response to the list in the `data` attribute belonging to the current trial (see Trialsequence doc).\n\n Attributes:\n response (any): data to append to the list. Can be anything but save_json method won't be available if\n the content of `response` is not JSON serializable (if it's an object for example).\n "
if (self.this_n < 0):
print("Can't add response because trial hasn't started yet!")
else:
self.data[self.this_n].append(response)
|
def add_response(self, response):
"\n Append response to the list in the `data` attribute belonging to the current trial (see Trialsequence doc).\n\n Attributes:\n response (any): data to append to the list. Can be anything but save_json method won't be available if\n the content of `response` is not JSON serializable (if it's an object for example).\n "
if (self.this_n < 0):
print("Can't add response because trial hasn't started yet!")
else:
self.data[self.this_n].append(response)<|docstring|>Append response to the list in the `data` attribute belonging to the current trial (see Trialsequence doc).
Attributes:
response (any): data to append to the list. Can be anything but save_json method won't be available if
the content of `response` is not JSON serializable (if it's an object for example).<|endoftext|>
|
e23b4e023ca79b2e16608b62b4f2a5a3a6597715536d09403e77db30cb232f56
|
def print_trial_info(self):
' Convenience method for printing current trial information. '
print(f"{self.label} | trial # {self.this_n} of {('inf' if (self.kind == 'infinite') else self.n_trials)} ({('inf' if (self.kind == 'infinite') else self.n_remaining)} remaining): condition {self.this_trial}, last response: {self.data[(self.this_n - 1)]}")
|
Convenience method for printing current trial information.
|
slab/psychoacoustics.py
|
print_trial_info
|
jakab13/slab
| 7
|
python
|
def print_trial_info(self):
' '
print(f"{self.label} | trial # {self.this_n} of {('inf' if (self.kind == 'infinite') else self.n_trials)} ({('inf' if (self.kind == 'infinite') else self.n_remaining)} remaining): condition {self.this_trial}, last response: {self.data[(self.this_n - 1)]}")
|
def print_trial_info(self):
' '
print(f"{self.label} | trial # {self.this_n} of {('inf' if (self.kind == 'infinite') else self.n_trials)} ({('inf' if (self.kind == 'infinite') else self.n_remaining)} remaining): condition {self.this_trial}, last response: {self.data[(self.this_n - 1)]}")<|docstring|>Convenience method for printing current trial information.<|endoftext|>
|
eacbb060c1b19f334854dfb0bf2c349cd3582146bb3a52ce3a63cf44632fae33
|
@staticmethod
def _create_simple_sequence(n_conditions, n_reps, dont_start_with=None):
'\n Create a randomized sequence of integers without direct repetitions of any element.\n\n Arguments:\n n_conditions (int): the number of conditions in the list. The array returned contains integers from 1\n to the value of `n_conditions`.\n n_reps (int): number that each element is repeated. Length of the returned array is `n_conditions * n_reps`\n dont_start_with (int): if not None, dont start the sequence with this integer. Can be useful if several\n sequences are used and the final trial of the last sequence should not be the same as the first\n element of the next sequence.\n Returns:\n (numpy.ndarray): randomized sequence of length n_conditions * n_reps without direct repetitions of any\n element.\n '
permute = list(range(1, (n_conditions + 1)))
if (dont_start_with is not None):
trials = [dont_start_with]
else:
trials = []
for _ in range(n_reps):
numpy.random.shuffle(permute)
if (len(trials) > 0):
while (trials[(- 1)] == permute[0]):
numpy.random.shuffle(permute)
trials += permute
if (dont_start_with is not None):
trials = trials[1:]
return numpy.array(trials)
|
Create a randomized sequence of integers without direct repetitions of any element.
Arguments:
n_conditions (int): the number of conditions in the list. The array returned contains integers from 1
to the value of `n_conditions`.
n_reps (int): number that each element is repeated. Length of the returned array is `n_conditions * n_reps`
dont_start_with (int): if not None, dont start the sequence with this integer. Can be useful if several
sequences are used and the final trial of the last sequence should not be the same as the first
element of the next sequence.
Returns:
(numpy.ndarray): randomized sequence of length n_conditions * n_reps without direct repetitions of any
element.
|
slab/psychoacoustics.py
|
_create_simple_sequence
|
jakab13/slab
| 7
|
python
|
@staticmethod
def _create_simple_sequence(n_conditions, n_reps, dont_start_with=None):
'\n Create a randomized sequence of integers without direct repetitions of any element.\n\n Arguments:\n n_conditions (int): the number of conditions in the list. The array returned contains integers from 1\n to the value of `n_conditions`.\n n_reps (int): number that each element is repeated. Length of the returned array is `n_conditions * n_reps`\n dont_start_with (int): if not None, dont start the sequence with this integer. Can be useful if several\n sequences are used and the final trial of the last sequence should not be the same as the first\n element of the next sequence.\n Returns:\n (numpy.ndarray): randomized sequence of length n_conditions * n_reps without direct repetitions of any\n element.\n '
permute = list(range(1, (n_conditions + 1)))
if (dont_start_with is not None):
trials = [dont_start_with]
else:
trials = []
for _ in range(n_reps):
numpy.random.shuffle(permute)
if (len(trials) > 0):
while (trials[(- 1)] == permute[0]):
numpy.random.shuffle(permute)
trials += permute
if (dont_start_with is not None):
trials = trials[1:]
return numpy.array(trials)
|
@staticmethod
def _create_simple_sequence(n_conditions, n_reps, dont_start_with=None):
'\n Create a randomized sequence of integers without direct repetitions of any element.\n\n Arguments:\n n_conditions (int): the number of conditions in the list. The array returned contains integers from 1\n to the value of `n_conditions`.\n n_reps (int): number that each element is repeated. Length of the returned array is `n_conditions * n_reps`\n dont_start_with (int): if not None, dont start the sequence with this integer. Can be useful if several\n sequences are used and the final trial of the last sequence should not be the same as the first\n element of the next sequence.\n Returns:\n (numpy.ndarray): randomized sequence of length n_conditions * n_reps without direct repetitions of any\n element.\n '
permute = list(range(1, (n_conditions + 1)))
if (dont_start_with is not None):
trials = [dont_start_with]
else:
trials = []
for _ in range(n_reps):
numpy.random.shuffle(permute)
if (len(trials) > 0):
while (trials[(- 1)] == permute[0]):
numpy.random.shuffle(permute)
trials += permute
if (dont_start_with is not None):
trials = trials[1:]
return numpy.array(trials)<|docstring|>Create a randomized sequence of integers without direct repetitions of any element.
Arguments:
n_conditions (int): the number of conditions in the list. The array returned contains integers from 1
to the value of `n_conditions`.
n_reps (int): number that each element is repeated. Length of the returned array is `n_conditions * n_reps`
dont_start_with (int): if not None, dont start the sequence with this integer. Can be useful if several
sequences are used and the final trial of the last sequence should not be the same as the first
element of the next sequence.
Returns:
(numpy.ndarray): randomized sequence of length n_conditions * n_reps without direct repetitions of any
element.<|endoftext|>
|
e5c7eb77c5eb7f6559abc306e0c7e29d960d25f6c3e1588c1f2e608d4335e3f7
|
@staticmethod
def _deviant_indices(n_standard, deviant_freq=0.1):
'\n Create sequence for an oddball experiment which contains two conditions: standards (1) and deviants (0).\n\n Arguments:\n n_standard (int): number of standard trials, encoded as 1, in the sequence.\n deviant_freq (float): frequency of deviants, encoded as 0, in the sequence. Also determines the minimum\n number of standards between two deviants which is 3 if deviant_freq <= .1, 2 if deviant_freq <= .2 and\n 1 if deviant_freq <= .3. A deviant frequency > .3 is not supported.\n Returns:\n (numpy.ndarray): sequence of length n_standard+(n_standard*deviant_freq) with deviants.\n '
if (deviant_freq <= 0.1):
min_dist = 3
elif (deviant_freq <= 0.2):
min_dist = 2
elif (deviant_freq <= 0.3):
min_dist = 1
else:
raise ValueError("Deviant frequency can't be greater than 0.3!")
n_deviants = int((n_standard * deviant_freq))
indices = range(n_standard)
deviant_indices = numpy.random.choice(indices, n_deviants, replace=False)
deviant_indices.sort()
dist = numpy.diff(deviant_indices)
while (numpy.min(dist) < min_dist):
deviant_indices = numpy.random.choice(indices, n_deviants, replace=False)
deviant_indices.sort()
dist = numpy.diff(deviant_indices)
return deviant_indices
|
Create sequence for an oddball experiment which contains two conditions: standards (1) and deviants (0).
Arguments:
n_standard (int): number of standard trials, encoded as 1, in the sequence.
deviant_freq (float): frequency of deviants, encoded as 0, in the sequence. Also determines the minimum
number of standards between two deviants which is 3 if deviant_freq <= .1, 2 if deviant_freq <= .2 and
1 if deviant_freq <= .3. A deviant frequency > .3 is not supported.
Returns:
(numpy.ndarray): sequence of length n_standard+(n_standard*deviant_freq) with deviants.
|
slab/psychoacoustics.py
|
_deviant_indices
|
jakab13/slab
| 7
|
python
|
@staticmethod
def _deviant_indices(n_standard, deviant_freq=0.1):
'\n Create sequence for an oddball experiment which contains two conditions: standards (1) and deviants (0).\n\n Arguments:\n n_standard (int): number of standard trials, encoded as 1, in the sequence.\n deviant_freq (float): frequency of deviants, encoded as 0, in the sequence. Also determines the minimum\n number of standards between two deviants which is 3 if deviant_freq <= .1, 2 if deviant_freq <= .2 and\n 1 if deviant_freq <= .3. A deviant frequency > .3 is not supported.\n Returns:\n (numpy.ndarray): sequence of length n_standard+(n_standard*deviant_freq) with deviants.\n '
if (deviant_freq <= 0.1):
min_dist = 3
elif (deviant_freq <= 0.2):
min_dist = 2
elif (deviant_freq <= 0.3):
min_dist = 1
else:
raise ValueError("Deviant frequency can't be greater than 0.3!")
n_deviants = int((n_standard * deviant_freq))
indices = range(n_standard)
deviant_indices = numpy.random.choice(indices, n_deviants, replace=False)
deviant_indices.sort()
dist = numpy.diff(deviant_indices)
while (numpy.min(dist) < min_dist):
deviant_indices = numpy.random.choice(indices, n_deviants, replace=False)
deviant_indices.sort()
dist = numpy.diff(deviant_indices)
return deviant_indices
|
@staticmethod
def _deviant_indices(n_standard, deviant_freq=0.1):
'\n Create sequence for an oddball experiment which contains two conditions: standards (1) and deviants (0).\n\n Arguments:\n n_standard (int): number of standard trials, encoded as 1, in the sequence.\n deviant_freq (float): frequency of deviants, encoded as 0, in the sequence. Also determines the minimum\n number of standards between two deviants which is 3 if deviant_freq <= .1, 2 if deviant_freq <= .2 and\n 1 if deviant_freq <= .3. A deviant frequency > .3 is not supported.\n Returns:\n (numpy.ndarray): sequence of length n_standard+(n_standard*deviant_freq) with deviants.\n '
if (deviant_freq <= 0.1):
min_dist = 3
elif (deviant_freq <= 0.2):
min_dist = 2
elif (deviant_freq <= 0.3):
min_dist = 1
else:
raise ValueError("Deviant frequency can't be greater than 0.3!")
n_deviants = int((n_standard * deviant_freq))
indices = range(n_standard)
deviant_indices = numpy.random.choice(indices, n_deviants, replace=False)
deviant_indices.sort()
dist = numpy.diff(deviant_indices)
while (numpy.min(dist) < min_dist):
deviant_indices = numpy.random.choice(indices, n_deviants, replace=False)
deviant_indices.sort()
dist = numpy.diff(deviant_indices)
return deviant_indices<|docstring|>Create sequence for an oddball experiment which contains two conditions: standards (1) and deviants (0).
Arguments:
n_standard (int): number of standard trials, encoded as 1, in the sequence.
deviant_freq (float): frequency of deviants, encoded as 0, in the sequence. Also determines the minimum
number of standards between two deviants which is 3 if deviant_freq <= .1, 2 if deviant_freq <= .2 and
1 if deviant_freq <= .3. A deviant frequency > .3 is not supported.
Returns:
(numpy.ndarray): sequence of length n_standard+(n_standard*deviant_freq) with deviants.<|endoftext|>
|
6213ab943d17296c4614764e76919a25549d35ea0a262434f63a0bc548fc5bb7
|
@staticmethod
def _create_random_permutation(n_conditions, n_reps):
'\n Create a completely random sequence of integers.\n\n Arguments:\n n_conditions (int): the number of conditions in the list. The array returned contains integers from 1\n to the value of `n_conditions`.\n n_reps (int): number that each element is repeated. Length of the returned array is n_conditions * n_reps.\n Returns:\n (numpy.ndarray): randomized sequence.\n '
return numpy.random.permutation(numpy.tile(list(range(1, (n_conditions + 1))), n_reps))
|
Create a completely random sequence of integers.
Arguments:
n_conditions (int): the number of conditions in the list. The array returned contains integers from 1
to the value of `n_conditions`.
n_reps (int): number that each element is repeated. Length of the returned array is n_conditions * n_reps.
Returns:
(numpy.ndarray): randomized sequence.
|
slab/psychoacoustics.py
|
_create_random_permutation
|
jakab13/slab
| 7
|
python
|
@staticmethod
def _create_random_permutation(n_conditions, n_reps):
'\n Create a completely random sequence of integers.\n\n Arguments:\n n_conditions (int): the number of conditions in the list. The array returned contains integers from 1\n to the value of `n_conditions`.\n n_reps (int): number that each element is repeated. Length of the returned array is n_conditions * n_reps.\n Returns:\n (numpy.ndarray): randomized sequence.\n '
return numpy.random.permutation(numpy.tile(list(range(1, (n_conditions + 1))), n_reps))
|
@staticmethod
def _create_random_permutation(n_conditions, n_reps):
'\n Create a completely random sequence of integers.\n\n Arguments:\n n_conditions (int): the number of conditions in the list. The array returned contains integers from 1\n to the value of `n_conditions`.\n n_reps (int): number that each element is repeated. Length of the returned array is n_conditions * n_reps.\n Returns:\n (numpy.ndarray): randomized sequence.\n '
return numpy.random.permutation(numpy.tile(list(range(1, (n_conditions + 1))), n_reps))<|docstring|>Create a completely random sequence of integers.
Arguments:
n_conditions (int): the number of conditions in the list. The array returned contains integers from 1
to the value of `n_conditions`.
n_reps (int): number that each element is repeated. Length of the returned array is n_conditions * n_reps.
Returns:
(numpy.ndarray): randomized sequence.<|endoftext|>
|
12cc35da06d73cd06e11ab63a323562201d539f74af65f9c3e4d5a634ad482a4
|
def get_future_trial(self, n=1):
'\n Returns the condition of a trial n iterations into the future or past, without advancing the trials.\n\n Arguments:\n n (int): number of iterations into the future or past (negative numbers).\n Returns:\n (any): element of the list stored in the `conditions` attribute belonging to the trial n\n iterations into the past/future. Returns None if attempting to go beyond the first/last trial\n '
if ((n > self.n_remaining) or ((self.this_n + n) < 0)):
return None
return self.conditions[(self.trials[(self.this_n + n)] - 1)]
|
Returns the condition of a trial n iterations into the future or past, without advancing the trials.
Arguments:
n (int): number of iterations into the future or past (negative numbers).
Returns:
(any): element of the list stored in the `conditions` attribute belonging to the trial n
iterations into the past/future. Returns None if attempting to go beyond the first/last trial
|
slab/psychoacoustics.py
|
get_future_trial
|
jakab13/slab
| 7
|
python
|
def get_future_trial(self, n=1):
'\n Returns the condition of a trial n iterations into the future or past, without advancing the trials.\n\n Arguments:\n n (int): number of iterations into the future or past (negative numbers).\n Returns:\n (any): element of the list stored in the `conditions` attribute belonging to the trial n\n iterations into the past/future. Returns None if attempting to go beyond the first/last trial\n '
if ((n > self.n_remaining) or ((self.this_n + n) < 0)):
return None
return self.conditions[(self.trials[(self.this_n + n)] - 1)]
|
def get_future_trial(self, n=1):
'\n Returns the condition of a trial n iterations into the future or past, without advancing the trials.\n\n Arguments:\n n (int): number of iterations into the future or past (negative numbers).\n Returns:\n (any): element of the list stored in the `conditions` attribute belonging to the trial n\n iterations into the past/future. Returns None if attempting to go beyond the first/last trial\n '
if ((n > self.n_remaining) or ((self.this_n + n) < 0)):
return None
return self.conditions[(self.trials[(self.this_n + n)] - 1)]<|docstring|>Returns the condition of a trial n iterations into the future or past, without advancing the trials.
Arguments:
n (int): number of iterations into the future or past (negative numbers).
Returns:
(any): element of the list stored in the `conditions` attribute belonging to the trial n
iterations into the past/future. Returns None if attempting to go beyond the first/last trial<|endoftext|>
|
72d1d8066b07f1efa0e88de0212c6d69b5d68ea00b2193330cd9897ee8bf50f0
|
def transitions(self):
'\n Count the number of transitions between conditions.\n\n Returns:\n (numpy.ndarray): table of shape `n_conditions` x `n_conditions` where the rows represent the condition\n transitioning from and the columns represent the condition transitioning to. For example [0, 2] shows the\n number of transitions from condition 1 to condition 3. If the `kind` of the sequence is "non_repeating",\n the diagonal is 0 because no condition transitions into itself.\n '
transitions = numpy.zeros((self.n_conditions, self.n_conditions))
for (i, j) in zip(self.trials, self.trials[1:]):
transitions[((i - 1), (j - 1))] += 1
return transitions
|
Count the number of transitions between conditions.
Returns:
(numpy.ndarray): table of shape `n_conditions` x `n_conditions` where the rows represent the condition
transitioning from and the columns represent the condition transitioning to. For example [0, 2] shows the
number of transitions from condition 1 to condition 3. If the `kind` of the sequence is "non_repeating",
the diagonal is 0 because no condition transitions into itself.
|
slab/psychoacoustics.py
|
transitions
|
jakab13/slab
| 7
|
python
|
def transitions(self):
'\n Count the number of transitions between conditions.\n\n Returns:\n (numpy.ndarray): table of shape `n_conditions` x `n_conditions` where the rows represent the condition\n transitioning from and the columns represent the condition transitioning to. For example [0, 2] shows the\n number of transitions from condition 1 to condition 3. If the `kind` of the sequence is "non_repeating",\n the diagonal is 0 because no condition transitions into itself.\n '
transitions = numpy.zeros((self.n_conditions, self.n_conditions))
for (i, j) in zip(self.trials, self.trials[1:]):
transitions[((i - 1), (j - 1))] += 1
return transitions
|
def transitions(self):
'\n Count the number of transitions between conditions.\n\n Returns:\n (numpy.ndarray): table of shape `n_conditions` x `n_conditions` where the rows represent the condition\n transitioning from and the columns represent the condition transitioning to. For example [0, 2] shows the\n number of transitions from condition 1 to condition 3. If the `kind` of the sequence is "non_repeating",\n the diagonal is 0 because no condition transitions into itself.\n '
transitions = numpy.zeros((self.n_conditions, self.n_conditions))
for (i, j) in zip(self.trials, self.trials[1:]):
transitions[((i - 1), (j - 1))] += 1
return transitions<|docstring|>Count the number of transitions between conditions.
Returns:
(numpy.ndarray): table of shape `n_conditions` x `n_conditions` where the rows represent the condition
transitioning from and the columns represent the condition transitioning to. For example [0, 2] shows the
number of transitions from condition 1 to condition 3. If the `kind` of the sequence is "non_repeating",
the diagonal is 0 because no condition transitions into itself.<|endoftext|>
|
2ed2d265378da4e994911f8dfaa0b6a65cb38260e2e57d7126f0f02d3f2c4c9b
|
def condition_probabilities(self):
'\n Return the frequency with which each condition appears in the sequence.\n\n Returns:\n (list): list of floats floats, where every element represents the frequency of one condition.\n The fist element is the frequency of the first condition and so on.\n '
probabilities = []
for i in range(self.n_conditions):
num = self.trials.count(i)
num /= self.n_trials
probabilities.append(num)
return probabilities
|
Return the frequency with which each condition appears in the sequence.
Returns:
(list): list of floats floats, where every element represents the frequency of one condition.
The fist element is the frequency of the first condition and so on.
|
slab/psychoacoustics.py
|
condition_probabilities
|
jakab13/slab
| 7
|
python
|
def condition_probabilities(self):
'\n Return the frequency with which each condition appears in the sequence.\n\n Returns:\n (list): list of floats floats, where every element represents the frequency of one condition.\n The fist element is the frequency of the first condition and so on.\n '
probabilities = []
for i in range(self.n_conditions):
num = self.trials.count(i)
num /= self.n_trials
probabilities.append(num)
return probabilities
|
def condition_probabilities(self):
'\n Return the frequency with which each condition appears in the sequence.\n\n Returns:\n (list): list of floats floats, where every element represents the frequency of one condition.\n The fist element is the frequency of the first condition and so on.\n '
probabilities = []
for i in range(self.n_conditions):
num = self.trials.count(i)
num /= self.n_trials
probabilities.append(num)
return probabilities<|docstring|>Return the frequency with which each condition appears in the sequence.
Returns:
(list): list of floats floats, where every element represents the frequency of one condition.
The fist element is the frequency of the first condition and so on.<|endoftext|>
|
b62f21276619ed5d1b495cb8d44dca24a70f6e56e8b5a91c62c9aedc6dc2d726
|
def response_summary(self):
'\n Generate a summary of the responses for each condition. The function counts how often a specific response\n was given to a condition for all conditions and each possible response (including None).\n\n Returns:\n (list of lists | None): indices of the outer list represent the conditions in the sequence. Each inner\n list contains the number of responses per response key, with the response keys sorted in ascending order,\n the last element always represents None. If the sequence is not finished yet, None is returned.\n Examples::\n\n import slab\n import random\n sequence = slab.Trialsequence(conditions=3, n_reps=10) # a sequence with three conditions\n # iterate trough the list and generate a random response. The response can be either yes (1), no (0) or\n # there can be no response at all (None)\n for trial in sequence:\n response = random.choice([0, 1, None])\n sequence.add_response(response)\n sequence.response_summary()\n # Out: [[1, 1, 7], [2, 5, 3], [4, 4, 2]]\n # The first sublist shows that the subject responded to the first condition once with no (0),\n # once with yes (1) and did not give a response seven times, the second and third list show\n # prevalence of the same response keys for conditions two and three.\n '
if self.finished:
response_keys = [item for sublist in self.data for item in sublist]
response_keys = list(set((response_keys + [None])))
response_keys = sorted(response_keys, key=(lambda x: ((x is None), x)))
responses = []
for condition in self.conditions:
idx = [i for (i, cond) in enumerate(self.trials) if (cond == condition)]
condition_data = [self.data[i] for i in idx]
count = collections.Counter([item for sublist in condition_data for item in sublist])
resp_1cond = []
for r in response_keys:
resp_1cond.append(count[r])
responses.append(resp_1cond)
return responses
else:
return None
|
Generate a summary of the responses for each condition. The function counts how often a specific response
was given to a condition for all conditions and each possible response (including None).
Returns:
(list of lists | None): indices of the outer list represent the conditions in the sequence. Each inner
list contains the number of responses per response key, with the response keys sorted in ascending order,
the last element always represents None. If the sequence is not finished yet, None is returned.
Examples::
import slab
import random
sequence = slab.Trialsequence(conditions=3, n_reps=10) # a sequence with three conditions
# iterate trough the list and generate a random response. The response can be either yes (1), no (0) or
# there can be no response at all (None)
for trial in sequence:
response = random.choice([0, 1, None])
sequence.add_response(response)
sequence.response_summary()
# Out: [[1, 1, 7], [2, 5, 3], [4, 4, 2]]
# The first sublist shows that the subject responded to the first condition once with no (0),
# once with yes (1) and did not give a response seven times, the second and third list show
# prevalence of the same response keys for conditions two and three.
|
slab/psychoacoustics.py
|
response_summary
|
jakab13/slab
| 7
|
python
|
def response_summary(self):
'\n Generate a summary of the responses for each condition. The function counts how often a specific response\n was given to a condition for all conditions and each possible response (including None).\n\n Returns:\n (list of lists | None): indices of the outer list represent the conditions in the sequence. Each inner\n list contains the number of responses per response key, with the response keys sorted in ascending order,\n the last element always represents None. If the sequence is not finished yet, None is returned.\n Examples::\n\n import slab\n import random\n sequence = slab.Trialsequence(conditions=3, n_reps=10) # a sequence with three conditions\n # iterate trough the list and generate a random response. The response can be either yes (1), no (0) or\n # there can be no response at all (None)\n for trial in sequence:\n response = random.choice([0, 1, None])\n sequence.add_response(response)\n sequence.response_summary()\n # Out: [[1, 1, 7], [2, 5, 3], [4, 4, 2]]\n # The first sublist shows that the subject responded to the first condition once with no (0),\n # once with yes (1) and did not give a response seven times, the second and third list show\n # prevalence of the same response keys for conditions two and three.\n '
if self.finished:
response_keys = [item for sublist in self.data for item in sublist]
response_keys = list(set((response_keys + [None])))
response_keys = sorted(response_keys, key=(lambda x: ((x is None), x)))
responses = []
for condition in self.conditions:
idx = [i for (i, cond) in enumerate(self.trials) if (cond == condition)]
condition_data = [self.data[i] for i in idx]
count = collections.Counter([item for sublist in condition_data for item in sublist])
resp_1cond = []
for r in response_keys:
resp_1cond.append(count[r])
responses.append(resp_1cond)
return responses
else:
return None
|
def response_summary(self):
'\n Generate a summary of the responses for each condition. The function counts how often a specific response\n was given to a condition for all conditions and each possible response (including None).\n\n Returns:\n (list of lists | None): indices of the outer list represent the conditions in the sequence. Each inner\n list contains the number of responses per response key, with the response keys sorted in ascending order,\n the last element always represents None. If the sequence is not finished yet, None is returned.\n Examples::\n\n import slab\n import random\n sequence = slab.Trialsequence(conditions=3, n_reps=10) # a sequence with three conditions\n # iterate trough the list and generate a random response. The response can be either yes (1), no (0) or\n # there can be no response at all (None)\n for trial in sequence:\n response = random.choice([0, 1, None])\n sequence.add_response(response)\n sequence.response_summary()\n # Out: [[1, 1, 7], [2, 5, 3], [4, 4, 2]]\n # The first sublist shows that the subject responded to the first condition once with no (0),\n # once with yes (1) and did not give a response seven times, the second and third list show\n # prevalence of the same response keys for conditions two and three.\n '
if self.finished:
response_keys = [item for sublist in self.data for item in sublist]
response_keys = list(set((response_keys + [None])))
response_keys = sorted(response_keys, key=(lambda x: ((x is None), x)))
responses = []
for condition in self.conditions:
idx = [i for (i, cond) in enumerate(self.trials) if (cond == condition)]
condition_data = [self.data[i] for i in idx]
count = collections.Counter([item for sublist in condition_data for item in sublist])
resp_1cond = []
for r in response_keys:
resp_1cond.append(count[r])
responses.append(resp_1cond)
return responses
else:
return None<|docstring|>Generate a summary of the responses for each condition. The function counts how often a specific response
was given to a condition for all conditions and each possible response (including None).
Returns:
(list of lists | None): indices of the outer list represent the conditions in the sequence. Each inner
list contains the number of responses per response key, with the response keys sorted in ascending order,
the last element always represents None. If the sequence is not finished yet, None is returned.
Examples::
import slab
import random
sequence = slab.Trialsequence(conditions=3, n_reps=10) # a sequence with three conditions
# iterate trough the list and generate a random response. The response can be either yes (1), no (0) or
# there can be no response at all (None)
for trial in sequence:
response = random.choice([0, 1, None])
sequence.add_response(response)
sequence.response_summary()
# Out: [[1, 1, 7], [2, 5, 3], [4, 4, 2]]
# The first sublist shows that the subject responded to the first condition once with no (0),
# once with yes (1) and did not give a response seven times, the second and third list show
# prevalence of the same response keys for conditions two and three.<|endoftext|>
|
49825a038d936f19f3b384dc62547f4e30459949d93f04c8ecd428b667ce0580
|
def plot(self, axis=None, show=True):
'\n Plot the trial sequence as scatter plot.\n\n Arguments:\n axis (matplotlib.pyplot.Axes): plot axis to draw on, if none a new plot is generated\n show (bool): show the plot immediately, defaults to True\n '
if (plt is None):
raise ImportError('Plotting requires matplotlib!')
if (axis is None):
axis = plt.subplot()
axis.scatter(range(self.n_trials), self.trials)
axis.set(title='Trial sequence', xlabel='Trials', ylabel='Condition index')
if show:
plt.show()
|
Plot the trial sequence as scatter plot.
Arguments:
axis (matplotlib.pyplot.Axes): plot axis to draw on, if none a new plot is generated
show (bool): show the plot immediately, defaults to True
|
slab/psychoacoustics.py
|
plot
|
jakab13/slab
| 7
|
python
|
def plot(self, axis=None, show=True):
'\n Plot the trial sequence as scatter plot.\n\n Arguments:\n axis (matplotlib.pyplot.Axes): plot axis to draw on, if none a new plot is generated\n show (bool): show the plot immediately, defaults to True\n '
if (plt is None):
raise ImportError('Plotting requires matplotlib!')
if (axis is None):
axis = plt.subplot()
axis.scatter(range(self.n_trials), self.trials)
axis.set(title='Trial sequence', xlabel='Trials', ylabel='Condition index')
if show:
plt.show()
|
def plot(self, axis=None, show=True):
'\n Plot the trial sequence as scatter plot.\n\n Arguments:\n axis (matplotlib.pyplot.Axes): plot axis to draw on, if none a new plot is generated\n show (bool): show the plot immediately, defaults to True\n '
if (plt is None):
raise ImportError('Plotting requires matplotlib!')
if (axis is None):
axis = plt.subplot()
axis.scatter(range(self.n_trials), self.trials)
axis.set(title='Trial sequence', xlabel='Trials', ylabel='Condition index')
if show:
plt.show()<|docstring|>Plot the trial sequence as scatter plot.
Arguments:
axis (matplotlib.pyplot.Axes): plot axis to draw on, if none a new plot is generated
show (bool): show the plot immediately, defaults to True<|endoftext|>
|
d441562c60a4634b07021cdfaf57f1c6b357399a1f2d8f3dc6f97220ac3cd69c
|
def __next__(self):
'\n Is called when iterating trough a sequenceAdvances to next trial and returns it. Updates attributes\n this_trial, this_n, and this_index. If the trials have ended this method will raise a StopIteration.\n\n Returns:\n (int | float | StopIteration): the intensity for the next trial which is calculated by the\n `_next_intensity` method. If the sequence is finished a StopIteration is returned instead.\n '
if (not self.finished):
self.this_trial_n += 1
self.intensities.append(self._next_intensity)
return self._next_intensity
else:
self._psychometric_function()
raise StopIteration
|
Is called when iterating trough a sequenceAdvances to next trial and returns it. Updates attributes
this_trial, this_n, and this_index. If the trials have ended this method will raise a StopIteration.
Returns:
(int | float | StopIteration): the intensity for the next trial which is calculated by the
`_next_intensity` method. If the sequence is finished a StopIteration is returned instead.
|
slab/psychoacoustics.py
|
__next__
|
jakab13/slab
| 7
|
python
|
def __next__(self):
'\n Is called when iterating trough a sequenceAdvances to next trial and returns it. Updates attributes\n this_trial, this_n, and this_index. If the trials have ended this method will raise a StopIteration.\n\n Returns:\n (int | float | StopIteration): the intensity for the next trial which is calculated by the\n `_next_intensity` method. If the sequence is finished a StopIteration is returned instead.\n '
if (not self.finished):
self.this_trial_n += 1
self.intensities.append(self._next_intensity)
return self._next_intensity
else:
self._psychometric_function()
raise StopIteration
|
def __next__(self):
'\n Is called when iterating trough a sequenceAdvances to next trial and returns it. Updates attributes\n this_trial, this_n, and this_index. If the trials have ended this method will raise a StopIteration.\n\n Returns:\n (int | float | StopIteration): the intensity for the next trial which is calculated by the\n `_next_intensity` method. If the sequence is finished a StopIteration is returned instead.\n '
if (not self.finished):
self.this_trial_n += 1
self.intensities.append(self._next_intensity)
return self._next_intensity
else:
self._psychometric_function()
raise StopIteration<|docstring|>Is called when iterating trough a sequenceAdvances to next trial and returns it. Updates attributes
this_trial, this_n, and this_index. If the trials have ended this method will raise a StopIteration.
Returns:
(int | float | StopIteration): the intensity for the next trial which is calculated by the
`_next_intensity` method. If the sequence is finished a StopIteration is returned instead.<|endoftext|>
|
bf08868ab56455efa3800e30fa6d3de2b216bab1a3f4b6b927510eb668ee506d
|
def add_response(self, result, intensity=None):
'\n Add a True or 1 to indicate a correct/detected trial\n or False or 0 to indicate an incorrect/missed trial.\n This is essential to advance the staircase to a new intensity level.\n Supplying an `intensity` value indicates that you did not use\n the recommended intensity in your last trial and the staircase will\n replace its recorded value with the one supplied.\n '
if (self._next_intensity <= self.min_val):
result = False
else:
result = bool(result)
self.data.append(result)
if (intensity is not None):
self.intensities.pop()
self.intensities.append(intensity)
if (self.this_trial_n > 0):
if result:
if ((len(self.data) > 1) and (self.data[(- 2)] == result)):
self.correct_counter += 1
else:
self.correct_counter = 1
elif ((len(self.data) > 1) and (self.data[(- 2)] == result)):
self.correct_counter -= 1
else:
self.correct_counter = (- 1)
self.calculate_next_intensity()
|
Add a True or 1 to indicate a correct/detected trial
or False or 0 to indicate an incorrect/missed trial.
This is essential to advance the staircase to a new intensity level.
Supplying an `intensity` value indicates that you did not use
the recommended intensity in your last trial and the staircase will
replace its recorded value with the one supplied.
|
slab/psychoacoustics.py
|
add_response
|
jakab13/slab
| 7
|
python
|
def add_response(self, result, intensity=None):
'\n Add a True or 1 to indicate a correct/detected trial\n or False or 0 to indicate an incorrect/missed trial.\n This is essential to advance the staircase to a new intensity level.\n Supplying an `intensity` value indicates that you did not use\n the recommended intensity in your last trial and the staircase will\n replace its recorded value with the one supplied.\n '
if (self._next_intensity <= self.min_val):
result = False
else:
result = bool(result)
self.data.append(result)
if (intensity is not None):
self.intensities.pop()
self.intensities.append(intensity)
if (self.this_trial_n > 0):
if result:
if ((len(self.data) > 1) and (self.data[(- 2)] == result)):
self.correct_counter += 1
else:
self.correct_counter = 1
elif ((len(self.data) > 1) and (self.data[(- 2)] == result)):
self.correct_counter -= 1
else:
self.correct_counter = (- 1)
self.calculate_next_intensity()
|
def add_response(self, result, intensity=None):
'\n Add a True or 1 to indicate a correct/detected trial\n or False or 0 to indicate an incorrect/missed trial.\n This is essential to advance the staircase to a new intensity level.\n Supplying an `intensity` value indicates that you did not use\n the recommended intensity in your last trial and the staircase will\n replace its recorded value with the one supplied.\n '
if (self._next_intensity <= self.min_val):
result = False
else:
result = bool(result)
self.data.append(result)
if (intensity is not None):
self.intensities.pop()
self.intensities.append(intensity)
if (self.this_trial_n > 0):
if result:
if ((len(self.data) > 1) and (self.data[(- 2)] == result)):
self.correct_counter += 1
else:
self.correct_counter = 1
elif ((len(self.data) > 1) and (self.data[(- 2)] == result)):
self.correct_counter -= 1
else:
self.correct_counter = (- 1)
self.calculate_next_intensity()<|docstring|>Add a True or 1 to indicate a correct/detected trial
or False or 0 to indicate an incorrect/missed trial.
This is essential to advance the staircase to a new intensity level.
Supplying an `intensity` value indicates that you did not use
the recommended intensity in your last trial and the staircase will
replace its recorded value with the one supplied.<|endoftext|>
|
619292b15f4a4fa34a281706f30b92c4f6f7607831163252adde975d6251ef35
|
def calculate_next_intensity(self):
' Based on current intensity, counter of correct responses, and current direction. '
if (not self.reversal_intensities):
if (self.data[(- 1)] is True):
reversal = bool((self.current_direction == 'up'))
self.current_direction = 'down'
else:
reversal = bool((self.current_direction == 'down'))
self.current_direction = 'up'
elif (self.correct_counter >= self.n_down):
reversal = bool((self.current_direction != 'down'))
self.current_direction = 'down'
elif (self.correct_counter <= (- self.n_up)):
reversal = bool((self.current_direction != 'up'))
self.current_direction = 'up'
else:
reversal = False
if reversal:
self.reversal_points.append(self.this_trial_n)
self.reversal_intensities.append(self.intensities[(- 1)])
if (len(self.reversal_intensities) >= self.n_reversals):
self.finished = True
if (len(self.reversal_intensities) >= len(self.step_sizes)):
self.step_size_current = self.step_sizes[(- 1)]
else:
_sz = len(self.reversal_intensities)
self.step_size_current = self.step_sizes[_sz]
if (self.current_direction == 'up'):
self.step_size_current *= self.step_up_factor
if (not self.reversal_intensities):
if (self.data[(- 1)] == 1):
self._intensity_dec()
else:
self._intensity_inc()
elif (self.correct_counter >= self.n_down):
self._intensity_dec()
elif (self.correct_counter <= (- self.n_up)):
self._intensity_inc()
|
Based on current intensity, counter of correct responses, and current direction.
|
slab/psychoacoustics.py
|
calculate_next_intensity
|
jakab13/slab
| 7
|
python
|
def calculate_next_intensity(self):
' '
if (not self.reversal_intensities):
if (self.data[(- 1)] is True):
reversal = bool((self.current_direction == 'up'))
self.current_direction = 'down'
else:
reversal = bool((self.current_direction == 'down'))
self.current_direction = 'up'
elif (self.correct_counter >= self.n_down):
reversal = bool((self.current_direction != 'down'))
self.current_direction = 'down'
elif (self.correct_counter <= (- self.n_up)):
reversal = bool((self.current_direction != 'up'))
self.current_direction = 'up'
else:
reversal = False
if reversal:
self.reversal_points.append(self.this_trial_n)
self.reversal_intensities.append(self.intensities[(- 1)])
if (len(self.reversal_intensities) >= self.n_reversals):
self.finished = True
if (len(self.reversal_intensities) >= len(self.step_sizes)):
self.step_size_current = self.step_sizes[(- 1)]
else:
_sz = len(self.reversal_intensities)
self.step_size_current = self.step_sizes[_sz]
if (self.current_direction == 'up'):
self.step_size_current *= self.step_up_factor
if (not self.reversal_intensities):
if (self.data[(- 1)] == 1):
self._intensity_dec()
else:
self._intensity_inc()
elif (self.correct_counter >= self.n_down):
self._intensity_dec()
elif (self.correct_counter <= (- self.n_up)):
self._intensity_inc()
|
def calculate_next_intensity(self):
' '
if (not self.reversal_intensities):
if (self.data[(- 1)] is True):
reversal = bool((self.current_direction == 'up'))
self.current_direction = 'down'
else:
reversal = bool((self.current_direction == 'down'))
self.current_direction = 'up'
elif (self.correct_counter >= self.n_down):
reversal = bool((self.current_direction != 'down'))
self.current_direction = 'down'
elif (self.correct_counter <= (- self.n_up)):
reversal = bool((self.current_direction != 'up'))
self.current_direction = 'up'
else:
reversal = False
if reversal:
self.reversal_points.append(self.this_trial_n)
self.reversal_intensities.append(self.intensities[(- 1)])
if (len(self.reversal_intensities) >= self.n_reversals):
self.finished = True
if (len(self.reversal_intensities) >= len(self.step_sizes)):
self.step_size_current = self.step_sizes[(- 1)]
else:
_sz = len(self.reversal_intensities)
self.step_size_current = self.step_sizes[_sz]
if (self.current_direction == 'up'):
self.step_size_current *= self.step_up_factor
if (not self.reversal_intensities):
if (self.data[(- 1)] == 1):
self._intensity_dec()
else:
self._intensity_inc()
elif (self.correct_counter >= self.n_down):
self._intensity_dec()
elif (self.correct_counter <= (- self.n_up)):
self._intensity_inc()<|docstring|>Based on current intensity, counter of correct responses, and current direction.<|endoftext|>
|
2eb18c3ff34cde4a368e498f59001a48d68873fdc7dc310b4ebc9061ed4ba0d2
|
def _intensity_inc(self):
' increment the current intensity and reset counter. '
if (self.step_type == 'db'):
self._next_intensity *= (10.0 ** (self.step_size_current / 20.0))
elif (self.step_type == 'log'):
self._next_intensity *= (10.0 ** self.step_size_current)
elif (self.step_type == 'lin'):
self._next_intensity += self.step_size_current
if ((self.max_val is not None) and (self._next_intensity > self.max_val)):
self._next_intensity = self.max_val
self.correct_counter = 0
|
increment the current intensity and reset counter.
|
slab/psychoacoustics.py
|
_intensity_inc
|
jakab13/slab
| 7
|
python
|
def _intensity_inc(self):
' '
if (self.step_type == 'db'):
self._next_intensity *= (10.0 ** (self.step_size_current / 20.0))
elif (self.step_type == 'log'):
self._next_intensity *= (10.0 ** self.step_size_current)
elif (self.step_type == 'lin'):
self._next_intensity += self.step_size_current
if ((self.max_val is not None) and (self._next_intensity > self.max_val)):
self._next_intensity = self.max_val
self.correct_counter = 0
|
def _intensity_inc(self):
' '
if (self.step_type == 'db'):
self._next_intensity *= (10.0 ** (self.step_size_current / 20.0))
elif (self.step_type == 'log'):
self._next_intensity *= (10.0 ** self.step_size_current)
elif (self.step_type == 'lin'):
self._next_intensity += self.step_size_current
if ((self.max_val is not None) and (self._next_intensity > self.max_val)):
self._next_intensity = self.max_val
self.correct_counter = 0<|docstring|>increment the current intensity and reset counter.<|endoftext|>
|
322bcee652197f6b2808900d74dd5c84335bd593e680038a638eb8179b467d06
|
def _intensity_dec(self):
' decrement the current intensity and reset counter. '
if (self.step_type == 'db'):
self._next_intensity /= (10.0 ** (self.step_size_current / 20.0))
if (self.step_type == 'log'):
self._next_intensity /= (10.0 ** self.step_size_current)
elif (self.step_type == 'lin'):
self._next_intensity -= self.step_size_current
self.correct_counter = 0
if ((self.min_val is not None) and (self._next_intensity < self.min_val)):
self._next_intensity = self.min_val
|
decrement the current intensity and reset counter.
|
slab/psychoacoustics.py
|
_intensity_dec
|
jakab13/slab
| 7
|
python
|
def _intensity_dec(self):
' '
if (self.step_type == 'db'):
self._next_intensity /= (10.0 ** (self.step_size_current / 20.0))
if (self.step_type == 'log'):
self._next_intensity /= (10.0 ** self.step_size_current)
elif (self.step_type == 'lin'):
self._next_intensity -= self.step_size_current
self.correct_counter = 0
if ((self.min_val is not None) and (self._next_intensity < self.min_val)):
self._next_intensity = self.min_val
|
def _intensity_dec(self):
' '
if (self.step_type == 'db'):
self._next_intensity /= (10.0 ** (self.step_size_current / 20.0))
if (self.step_type == 'log'):
self._next_intensity /= (10.0 ** self.step_size_current)
elif (self.step_type == 'lin'):
self._next_intensity -= self.step_size_current
self.correct_counter = 0
if ((self.min_val is not None) and (self._next_intensity < self.min_val)):
self._next_intensity = self.min_val<|docstring|>decrement the current intensity and reset counter.<|endoftext|>
|
24a22da12d87f5a2ce20389c92160c2400d1728ba1ee52057b1d0582d934144a
|
def threshold(self, n=0):
"\n Returns the average of the last n reversals.\n\n Arguments:\n n (int): number of reversals to average over, if 0 use `n_reversals` - 1.\n Returns:\n the arithmetic (if `step_type`==='lin') or geometric mean of the `reversal_intensities`.\n "
if self.finished:
if ((n == 0) or (n > self.n_reversals)):
n = (int(self.n_reversals) - 1)
if (self.step_type == 'lin'):
return numpy.mean(self.reversal_intensities[(- n):])
return numpy.exp(numpy.mean(numpy.log(self.reversal_intensities[(- n):])))
return None
|
Returns the average of the last n reversals.
Arguments:
n (int): number of reversals to average over, if 0 use `n_reversals` - 1.
Returns:
the arithmetic (if `step_type`==='lin') or geometric mean of the `reversal_intensities`.
|
slab/psychoacoustics.py
|
threshold
|
jakab13/slab
| 7
|
python
|
def threshold(self, n=0):
"\n Returns the average of the last n reversals.\n\n Arguments:\n n (int): number of reversals to average over, if 0 use `n_reversals` - 1.\n Returns:\n the arithmetic (if `step_type`==='lin') or geometric mean of the `reversal_intensities`.\n "
if self.finished:
if ((n == 0) or (n > self.n_reversals)):
n = (int(self.n_reversals) - 1)
if (self.step_type == 'lin'):
return numpy.mean(self.reversal_intensities[(- n):])
return numpy.exp(numpy.mean(numpy.log(self.reversal_intensities[(- n):])))
return None
|
def threshold(self, n=0):
"\n Returns the average of the last n reversals.\n\n Arguments:\n n (int): number of reversals to average over, if 0 use `n_reversals` - 1.\n Returns:\n the arithmetic (if `step_type`==='lin') or geometric mean of the `reversal_intensities`.\n "
if self.finished:
if ((n == 0) or (n > self.n_reversals)):
n = (int(self.n_reversals) - 1)
if (self.step_type == 'lin'):
return numpy.mean(self.reversal_intensities[(- n):])
return numpy.exp(numpy.mean(numpy.log(self.reversal_intensities[(- n):])))
return None<|docstring|>Returns the average of the last n reversals.
Arguments:
n (int): number of reversals to average over, if 0 use `n_reversals` - 1.
Returns:
the arithmetic (if `step_type`==='lin') or geometric mean of the `reversal_intensities`.<|endoftext|>
|
7a66828dbafb7827fc73113ab3bc3efb84c1c83f1be76e078b63fd85a7fa103d
|
def print_trial_info(self):
' Convenience method for printing current trial information. '
print(f'{self.label} | trial # {self.this_trial_n}: reversals: {len(self.reversal_points)}/{self.n_reversals}, intensity {(round(self.intensities[(- 1)], 2) if self.intensities else round(self._next_intensity, 2))}, going {self.current_direction}, response {(self.data[(- 1)] if self.data else None)}')
|
Convenience method for printing current trial information.
|
slab/psychoacoustics.py
|
print_trial_info
|
jakab13/slab
| 7
|
python
|
def print_trial_info(self):
' '
print(f'{self.label} | trial # {self.this_trial_n}: reversals: {len(self.reversal_points)}/{self.n_reversals}, intensity {(round(self.intensities[(- 1)], 2) if self.intensities else round(self._next_intensity, 2))}, going {self.current_direction}, response {(self.data[(- 1)] if self.data else None)}')
|
def print_trial_info(self):
' '
print(f'{self.label} | trial # {self.this_trial_n}: reversals: {len(self.reversal_points)}/{self.n_reversals}, intensity {(round(self.intensities[(- 1)], 2) if self.intensities else round(self._next_intensity, 2))}, going {self.current_direction}, response {(self.data[(- 1)] if self.data else None)}')<|docstring|>Convenience method for printing current trial information.<|endoftext|>
|
fa90fcde3513eca73a56e4486c9be50e4f15fe7d6b38d1455f100acc765b7bd7
|
def save_csv(self, filename):
'\n Write a csv text file with the stimulus values in the 1st line and the corresponding responses in the 2nd.\n\n Arguments:\n filename (str): the name under which the csv file is saved.\n Returns:\n (bool): True if saving was successful, False if there are no trials to save.\n '
if (self.this_trial_n < 1):
return False
with open(filename, 'w') as f:
raw_intensities = str(self.intensities)
raw_intensities = raw_intensities.replace('[', '').replace(']', '')
f.write(raw_intensities)
f.write('\n')
responses = str(numpy.multiply(self.data, 1))
responses = responses.replace('[', '').replace(']', '')
responses = responses.replace(' ', ', ')
f.write(responses)
return True
|
Write a csv text file with the stimulus values in the 1st line and the corresponding responses in the 2nd.
Arguments:
filename (str): the name under which the csv file is saved.
Returns:
(bool): True if saving was successful, False if there are no trials to save.
|
slab/psychoacoustics.py
|
save_csv
|
jakab13/slab
| 7
|
python
|
def save_csv(self, filename):
'\n Write a csv text file with the stimulus values in the 1st line and the corresponding responses in the 2nd.\n\n Arguments:\n filename (str): the name under which the csv file is saved.\n Returns:\n (bool): True if saving was successful, False if there are no trials to save.\n '
if (self.this_trial_n < 1):
return False
with open(filename, 'w') as f:
raw_intensities = str(self.intensities)
raw_intensities = raw_intensities.replace('[', ).replace(']', )
f.write(raw_intensities)
f.write('\n')
responses = str(numpy.multiply(self.data, 1))
responses = responses.replace('[', ).replace(']', )
responses = responses.replace(' ', ', ')
f.write(responses)
return True
|
def save_csv(self, filename):
'\n Write a csv text file with the stimulus values in the 1st line and the corresponding responses in the 2nd.\n\n Arguments:\n filename (str): the name under which the csv file is saved.\n Returns:\n (bool): True if saving was successful, False if there are no trials to save.\n '
if (self.this_trial_n < 1):
return False
with open(filename, 'w') as f:
raw_intensities = str(self.intensities)
raw_intensities = raw_intensities.replace('[', ).replace(']', )
f.write(raw_intensities)
f.write('\n')
responses = str(numpy.multiply(self.data, 1))
responses = responses.replace('[', ).replace(']', )
responses = responses.replace(' ', ', ')
f.write(responses)
return True<|docstring|>Write a csv text file with the stimulus values in the 1st line and the corresponding responses in the 2nd.
Arguments:
filename (str): the name under which the csv file is saved.
Returns:
(bool): True if saving was successful, False if there are no trials to save.<|endoftext|>
|
fbb8725e8f03a568a40d7826875e2c868e4c7803a4b2fdd8326938480339126b
|
def plot(self, axis=None, show=True):
'\n Plot the staircase. If called after each trial, one plot is created and updated.\n\n Arguments:\n axis (matplotlib.pyplot.Axes): plot axis to draw on, if none a new plot is generated\n show (bool): whether to show the plot right after drawing.\n '
if (plt is None):
raise ImportError('Plotting requires matplotlib!')
if self.intensities:
x = numpy.arange((- self.n_pretrials), (len(self.intensities) - self.n_pretrials))
y = numpy.array(self.intensities)
responses = numpy.array(self.data)
if (axis is None):
fig = plt.figure('stairs')
axis = fig.gca()
axis.clear()
axis.plot(x, y)
axis.set_xlim((- self.n_pretrials), max(20, (((self.this_trial_n + 15) // 10) * 10)))
axis.set_ylim((min(0, min(y)) if (self.min_val == (- numpy.Inf)) else self.min_val), (max(y) if (self.max_val == numpy.Inf) else self.max_val))
axis.scatter(x[responses], y[responses], color='green')
axis.scatter(x[(~ responses)], y[(~ responses)], color='red')
axis.scatter(((len(self.intensities) - self.n_pretrials) + 1), self._next_intensity, color='grey')
axis.set_ylabel('Dependent variable')
axis.set_xlabel('Trial')
axis.set_title('Staircase')
if self.finished:
axis.hlines(self.threshold(), min(x), max(x), 'r')
plt.draw()
if show:
plt.pause(0.01)
|
Plot the staircase. If called after each trial, one plot is created and updated.
Arguments:
axis (matplotlib.pyplot.Axes): plot axis to draw on, if none a new plot is generated
show (bool): whether to show the plot right after drawing.
|
slab/psychoacoustics.py
|
plot
|
jakab13/slab
| 7
|
python
|
def plot(self, axis=None, show=True):
'\n Plot the staircase. If called after each trial, one plot is created and updated.\n\n Arguments:\n axis (matplotlib.pyplot.Axes): plot axis to draw on, if none a new plot is generated\n show (bool): whether to show the plot right after drawing.\n '
if (plt is None):
raise ImportError('Plotting requires matplotlib!')
if self.intensities:
x = numpy.arange((- self.n_pretrials), (len(self.intensities) - self.n_pretrials))
y = numpy.array(self.intensities)
responses = numpy.array(self.data)
if (axis is None):
fig = plt.figure('stairs')
axis = fig.gca()
axis.clear()
axis.plot(x, y)
axis.set_xlim((- self.n_pretrials), max(20, (((self.this_trial_n + 15) // 10) * 10)))
axis.set_ylim((min(0, min(y)) if (self.min_val == (- numpy.Inf)) else self.min_val), (max(y) if (self.max_val == numpy.Inf) else self.max_val))
axis.scatter(x[responses], y[responses], color='green')
axis.scatter(x[(~ responses)], y[(~ responses)], color='red')
axis.scatter(((len(self.intensities) - self.n_pretrials) + 1), self._next_intensity, color='grey')
axis.set_ylabel('Dependent variable')
axis.set_xlabel('Trial')
axis.set_title('Staircase')
if self.finished:
axis.hlines(self.threshold(), min(x), max(x), 'r')
plt.draw()
if show:
plt.pause(0.01)
|
def plot(self, axis=None, show=True):
'\n Plot the staircase. If called after each trial, one plot is created and updated.\n\n Arguments:\n axis (matplotlib.pyplot.Axes): plot axis to draw on, if none a new plot is generated\n show (bool): whether to show the plot right after drawing.\n '
if (plt is None):
raise ImportError('Plotting requires matplotlib!')
if self.intensities:
x = numpy.arange((- self.n_pretrials), (len(self.intensities) - self.n_pretrials))
y = numpy.array(self.intensities)
responses = numpy.array(self.data)
if (axis is None):
fig = plt.figure('stairs')
axis = fig.gca()
axis.clear()
axis.plot(x, y)
axis.set_xlim((- self.n_pretrials), max(20, (((self.this_trial_n + 15) // 10) * 10)))
axis.set_ylim((min(0, min(y)) if (self.min_val == (- numpy.Inf)) else self.min_val), (max(y) if (self.max_val == numpy.Inf) else self.max_val))
axis.scatter(x[responses], y[responses], color='green')
axis.scatter(x[(~ responses)], y[(~ responses)], color='red')
axis.scatter(((len(self.intensities) - self.n_pretrials) + 1), self._next_intensity, color='grey')
axis.set_ylabel('Dependent variable')
axis.set_xlabel('Trial')
axis.set_title('Staircase')
if self.finished:
axis.hlines(self.threshold(), min(x), max(x), 'r')
plt.draw()
if show:
plt.pause(0.01)<|docstring|>Plot the staircase. If called after each trial, one plot is created and updated.
Arguments:
axis (matplotlib.pyplot.Axes): plot axis to draw on, if none a new plot is generated
show (bool): whether to show the plot right after drawing.<|endoftext|>
|
7aeca0c9dd1aecf2e340cb01bab147331d6d64113da4141e89397cbfd4f12fa3
|
@staticmethod
def close_plot():
' Closes a staircase plot (if not drawn into a specified axis) - used for plotting after each trial. '
plt.close('stairs')
|
Closes a staircase plot (if not drawn into a specified axis) - used for plotting after each trial.
|
slab/psychoacoustics.py
|
close_plot
|
jakab13/slab
| 7
|
python
|
@staticmethod
def close_plot():
' '
plt.close('stairs')
|
@staticmethod
def close_plot():
' '
plt.close('stairs')<|docstring|>Closes a staircase plot (if not drawn into a specified axis) - used for plotting after each trial.<|endoftext|>
|
217c7b0050b15d57e85176d6f22d664cc67c25cbaed5ae139708f623064a64e4
|
def _psychometric_function(self):
'\n Create a psychometric function by binning data from a staircase procedure.\n Called automatically when staircase is finished. Sets attributes `pf_intensites` (array of intensity values\n where each is the center of an intensity bin), `pf_percent_correct` (array of mean percent correct in each bin),\n `pf_responses_per_intensity` (array of number of responses contributing to each mean).\n '
intensities = numpy.array(self.intensities)
responses = numpy.array(self.data)
binned_resp = []
binned_intensities = []
n_points = []
intensities = numpy.round(intensities, decimals=8)
unique_intensities = numpy.unique(intensities)
for this_intensity in unique_intensities:
these_responses = responses[(intensities == this_intensity)]
binned_intensities.append(this_intensity)
binned_resp.append(numpy.mean(these_responses))
n_points.append(len(these_responses))
self.pf_intensities = binned_intensities
self.pf_percent_correct = binned_resp
self.pf_responses_per_intensity = n_points
|
Create a psychometric function by binning data from a staircase procedure.
Called automatically when staircase is finished. Sets attributes `pf_intensites` (array of intensity values
where each is the center of an intensity bin), `pf_percent_correct` (array of mean percent correct in each bin),
`pf_responses_per_intensity` (array of number of responses contributing to each mean).
|
slab/psychoacoustics.py
|
_psychometric_function
|
jakab13/slab
| 7
|
python
|
def _psychometric_function(self):
'\n Create a psychometric function by binning data from a staircase procedure.\n Called automatically when staircase is finished. Sets attributes `pf_intensites` (array of intensity values\n where each is the center of an intensity bin), `pf_percent_correct` (array of mean percent correct in each bin),\n `pf_responses_per_intensity` (array of number of responses contributing to each mean).\n '
intensities = numpy.array(self.intensities)
responses = numpy.array(self.data)
binned_resp = []
binned_intensities = []
n_points = []
intensities = numpy.round(intensities, decimals=8)
unique_intensities = numpy.unique(intensities)
for this_intensity in unique_intensities:
these_responses = responses[(intensities == this_intensity)]
binned_intensities.append(this_intensity)
binned_resp.append(numpy.mean(these_responses))
n_points.append(len(these_responses))
self.pf_intensities = binned_intensities
self.pf_percent_correct = binned_resp
self.pf_responses_per_intensity = n_points
|
def _psychometric_function(self):
'\n Create a psychometric function by binning data from a staircase procedure.\n Called automatically when staircase is finished. Sets attributes `pf_intensites` (array of intensity values\n where each is the center of an intensity bin), `pf_percent_correct` (array of mean percent correct in each bin),\n `pf_responses_per_intensity` (array of number of responses contributing to each mean).\n '
intensities = numpy.array(self.intensities)
responses = numpy.array(self.data)
binned_resp = []
binned_intensities = []
n_points = []
intensities = numpy.round(intensities, decimals=8)
unique_intensities = numpy.unique(intensities)
for this_intensity in unique_intensities:
these_responses = responses[(intensities == this_intensity)]
binned_intensities.append(this_intensity)
binned_resp.append(numpy.mean(these_responses))
n_points.append(len(these_responses))
self.pf_intensities = binned_intensities
self.pf_percent_correct = binned_resp
self.pf_responses_per_intensity = n_points<|docstring|>Create a psychometric function by binning data from a staircase procedure.
Called automatically when staircase is finished. Sets attributes `pf_intensites` (array of intensity values
where each is the center of an intensity bin), `pf_percent_correct` (array of mean percent correct in each bin),
`pf_responses_per_intensity` (array of number of responses contributing to each mean).<|endoftext|>
|
e56af3b1f5878be291c7e0674e997efbcd96a14184f4fc5ba93c4170da25f211
|
def write(self, data, tag=None):
'\n Safely write data to the file which is opened just before writing and closed immediately after to avoid\n data loss. Call this method at the end of each trial to save the response and trial state.\n\n Arguments:\n data (any): data to save must be JSON serializable [string, list, dict, ...]). If data is an object,\n the __dict__ is extracted and saved.\n tag (str): The tag is prepended as a key. If None is provided, the current time is used.\n '
if hasattr(data, '__dict__'):
data = data.__dict__
try:
data = json.loads(data)
except (json.JSONDecodeError, TypeError):
pass
if ((tag is None) or (tag == 'time')):
tag = datetime.datetime.now().strftime('%Y-%m-%d-%H-%M-%S')
with open(self.path, 'a') as file:
file.write(json.dumps({tag: data}))
file.write('\n')
|
Safely write data to the file which is opened just before writing and closed immediately after to avoid
data loss. Call this method at the end of each trial to save the response and trial state.
Arguments:
data (any): data to save must be JSON serializable [string, list, dict, ...]). If data is an object,
the __dict__ is extracted and saved.
tag (str): The tag is prepended as a key. If None is provided, the current time is used.
|
slab/psychoacoustics.py
|
write
|
jakab13/slab
| 7
|
python
|
def write(self, data, tag=None):
'\n Safely write data to the file which is opened just before writing and closed immediately after to avoid\n data loss. Call this method at the end of each trial to save the response and trial state.\n\n Arguments:\n data (any): data to save must be JSON serializable [string, list, dict, ...]). If data is an object,\n the __dict__ is extracted and saved.\n tag (str): The tag is prepended as a key. If None is provided, the current time is used.\n '
if hasattr(data, '__dict__'):
data = data.__dict__
try:
data = json.loads(data)
except (json.JSONDecodeError, TypeError):
pass
if ((tag is None) or (tag == 'time')):
tag = datetime.datetime.now().strftime('%Y-%m-%d-%H-%M-%S')
with open(self.path, 'a') as file:
file.write(json.dumps({tag: data}))
file.write('\n')
|
def write(self, data, tag=None):
'\n Safely write data to the file which is opened just before writing and closed immediately after to avoid\n data loss. Call this method at the end of each trial to save the response and trial state.\n\n Arguments:\n data (any): data to save must be JSON serializable [string, list, dict, ...]). If data is an object,\n the __dict__ is extracted and saved.\n tag (str): The tag is prepended as a key. If None is provided, the current time is used.\n '
if hasattr(data, '__dict__'):
data = data.__dict__
try:
data = json.loads(data)
except (json.JSONDecodeError, TypeError):
pass
if ((tag is None) or (tag == 'time')):
tag = datetime.datetime.now().strftime('%Y-%m-%d-%H-%M-%S')
with open(self.path, 'a') as file:
file.write(json.dumps({tag: data}))
file.write('\n')<|docstring|>Safely write data to the file which is opened just before writing and closed immediately after to avoid
data loss. Call this method at the end of each trial to save the response and trial state.
Arguments:
data (any): data to save must be JSON serializable [string, list, dict, ...]). If data is an object,
the __dict__ is extracted and saved.
tag (str): The tag is prepended as a key. If None is provided, the current time is used.<|endoftext|>
|
cbda71c049b4fb5779f651af78d0f189f5d2c71d06323e87639275f8a0a673ad
|
@staticmethod
def read_file(filename, tag=None):
'\n Read a results file and return the content.\n\n Arguments:\n filename (str | pathlib.Path):\n tag (None | str):\n Returns:\n (list | dict): The content of the file. If tag is None, the whole file is returned, else only the\n dictionaries with that tag as a key are returned. The content will be a list of dictionaries or a\n dictionary if there is only a single element.\n '
content = []
with open(filename) as file:
if (tag is None):
for line in file:
content.append(json.loads(line))
else:
for line in file:
jwd = json.loads(line)
if (tag in jwd):
content.append(jwd[tag])
if (len(content) == 1):
content = content[0]
return content
|
Read a results file and return the content.
Arguments:
filename (str | pathlib.Path):
tag (None | str):
Returns:
(list | dict): The content of the file. If tag is None, the whole file is returned, else only the
dictionaries with that tag as a key are returned. The content will be a list of dictionaries or a
dictionary if there is only a single element.
|
slab/psychoacoustics.py
|
read_file
|
jakab13/slab
| 7
|
python
|
@staticmethod
def read_file(filename, tag=None):
'\n Read a results file and return the content.\n\n Arguments:\n filename (str | pathlib.Path):\n tag (None | str):\n Returns:\n (list | dict): The content of the file. If tag is None, the whole file is returned, else only the\n dictionaries with that tag as a key are returned. The content will be a list of dictionaries or a\n dictionary if there is only a single element.\n '
content = []
with open(filename) as file:
if (tag is None):
for line in file:
content.append(json.loads(line))
else:
for line in file:
jwd = json.loads(line)
if (tag in jwd):
content.append(jwd[tag])
if (len(content) == 1):
content = content[0]
return content
|
@staticmethod
def read_file(filename, tag=None):
'\n Read a results file and return the content.\n\n Arguments:\n filename (str | pathlib.Path):\n tag (None | str):\n Returns:\n (list | dict): The content of the file. If tag is None, the whole file is returned, else only the\n dictionaries with that tag as a key are returned. The content will be a list of dictionaries or a\n dictionary if there is only a single element.\n '
content = []
with open(filename) as file:
if (tag is None):
for line in file:
content.append(json.loads(line))
else:
for line in file:
jwd = json.loads(line)
if (tag in jwd):
content.append(jwd[tag])
if (len(content) == 1):
content = content[0]
return content<|docstring|>Read a results file and return the content.
Arguments:
filename (str | pathlib.Path):
tag (None | str):
Returns:
(list | dict): The content of the file. If tag is None, the whole file is returned, else only the
dictionaries with that tag as a key are returned. The content will be a list of dictionaries or a
dictionary if there is only a single element.<|endoftext|>
|
a051ef2bb82185cbb53f3a49fdef5281a0077fd1f3b9646edd7d0f4e6c96d02d
|
def read(self, tag=None):
' Wrapper for the read_file method. '
return ResultsFile.read_file(self.path, tag)
|
Wrapper for the read_file method.
|
slab/psychoacoustics.py
|
read
|
jakab13/slab
| 7
|
python
|
def read(self, tag=None):
' '
return ResultsFile.read_file(self.path, tag)
|
def read(self, tag=None):
' '
return ResultsFile.read_file(self.path, tag)<|docstring|>Wrapper for the read_file method.<|endoftext|>
|
8969d64c1a29a0f11bcaa43fc9711ab0bb71927637d87fbc488f52505c3b3b3d
|
@staticmethod
def previous_file(subject=None):
'\n Returns the name of the most recently used results file for a given subject.\n Intended for extracting information from a previous file when running partial experiments.\n\n Arguments:\n subject (str): the subject name name under which the file is stored.\n Returns:\n (pathlib.Path): full path to the most recent results file.\n '
path = (pathlib.Path(results_folder) / pathlib.Path(subject))
files = [f for f in path.glob((subject + '*')) if f.is_file()]
files.sort()
return files[(- 1)]
|
Returns the name of the most recently used results file for a given subject.
Intended for extracting information from a previous file when running partial experiments.
Arguments:
subject (str): the subject name name under which the file is stored.
Returns:
(pathlib.Path): full path to the most recent results file.
|
slab/psychoacoustics.py
|
previous_file
|
jakab13/slab
| 7
|
python
|
@staticmethod
def previous_file(subject=None):
'\n Returns the name of the most recently used results file for a given subject.\n Intended for extracting information from a previous file when running partial experiments.\n\n Arguments:\n subject (str): the subject name name under which the file is stored.\n Returns:\n (pathlib.Path): full path to the most recent results file.\n '
path = (pathlib.Path(results_folder) / pathlib.Path(subject))
files = [f for f in path.glob((subject + '*')) if f.is_file()]
files.sort()
return files[(- 1)]
|
@staticmethod
def previous_file(subject=None):
'\n Returns the name of the most recently used results file for a given subject.\n Intended for extracting information from a previous file when running partial experiments.\n\n Arguments:\n subject (str): the subject name name under which the file is stored.\n Returns:\n (pathlib.Path): full path to the most recent results file.\n '
path = (pathlib.Path(results_folder) / pathlib.Path(subject))
files = [f for f in path.glob((subject + '*')) if f.is_file()]
files.sort()
return files[(- 1)]<|docstring|>Returns the name of the most recently used results file for a given subject.
Intended for extracting information from a previous file when running partial experiments.
Arguments:
subject (str): the subject name name under which the file is stored.
Returns:
(pathlib.Path): full path to the most recent results file.<|endoftext|>
|
231e209878d15a81d28dbc7762733302f61f2f410f8e6af50803d8b37c0c4039
|
def clear(self):
' Clears the file by erasing all content. '
with open(self.path, 'w') as file:
file.write('')
|
Clears the file by erasing all content.
|
slab/psychoacoustics.py
|
clear
|
jakab13/slab
| 7
|
python
|
def clear(self):
' '
with open(self.path, 'w') as file:
file.write()
|
def clear(self):
' '
with open(self.path, 'w') as file:
file.write()<|docstring|>Clears the file by erasing all content.<|endoftext|>
|
edeab087a02c2953273f7a8cee25074961bf00d33ee8b84b54754992831ca1d2
|
def play(self):
' Play a random, but never the previous, stimulus from the list. '
if self.sequence:
previous = self.sequence[(- 1)]
else:
previous = None
idx = previous
while (idx == previous):
idx = numpy.random.randint(len(self))
self.sequence.append(idx)
self[idx].play()
|
Play a random, but never the previous, stimulus from the list.
|
slab/psychoacoustics.py
|
play
|
jakab13/slab
| 7
|
python
|
def play(self):
' '
if self.sequence:
previous = self.sequence[(- 1)]
else:
previous = None
idx = previous
while (idx == previous):
idx = numpy.random.randint(len(self))
self.sequence.append(idx)
self[idx].play()
|
def play(self):
' '
if self.sequence:
previous = self.sequence[(- 1)]
else:
previous = None
idx = previous
while (idx == previous):
idx = numpy.random.randint(len(self))
self.sequence.append(idx)
self[idx].play()<|docstring|>Play a random, but never the previous, stimulus from the list.<|endoftext|>
|
b265408b06f6e11dec9603a6720398d5c45be51f83611135d723d36a5e232583
|
def random_choice(self, n=1):
'\n Pick (without replacement) random elements from the list.\n\n Arguments:\n n (int): number of elements to pick.\n Returns:\n (list): list of n random elements.\n '
idxs = numpy.random.randint(0, len(self), size=n)
return [self[i] for i in idxs]
|
Pick (without replacement) random elements from the list.
Arguments:
n (int): number of elements to pick.
Returns:
(list): list of n random elements.
|
slab/psychoacoustics.py
|
random_choice
|
jakab13/slab
| 7
|
python
|
def random_choice(self, n=1):
'\n Pick (without replacement) random elements from the list.\n\n Arguments:\n n (int): number of elements to pick.\n Returns:\n (list): list of n random elements.\n '
idxs = numpy.random.randint(0, len(self), size=n)
return [self[i] for i in idxs]
|
def random_choice(self, n=1):
'\n Pick (without replacement) random elements from the list.\n\n Arguments:\n n (int): number of elements to pick.\n Returns:\n (list): list of n random elements.\n '
idxs = numpy.random.randint(0, len(self), size=n)
return [self[i] for i in idxs]<|docstring|>Pick (without replacement) random elements from the list.
Arguments:
n (int): number of elements to pick.
Returns:
(list): list of n random elements.<|endoftext|>
|
eb5bc8c8563aec0dae2e016ec94aa82bc37fdc3867c1c931415bf98a33e26d4e
|
def write(self, filename):
'\n Save the Precomputed object as a zip file containing all sounds as wav files.\n\n Arguments:\n filename (str | pathlib.Path): full path to under which the file is saved.\n '
with zipfile.ZipFile(filename, mode='a') as zip_file:
for (idx, sound) in enumerate(self):
f = io.BytesIO()
sound.write(f)
f.seek(0)
zip_file.writestr(f's_{idx}.wav', f.read())
f.close()
|
Save the Precomputed object as a zip file containing all sounds as wav files.
Arguments:
filename (str | pathlib.Path): full path to under which the file is saved.
|
slab/psychoacoustics.py
|
write
|
jakab13/slab
| 7
|
python
|
def write(self, filename):
'\n Save the Precomputed object as a zip file containing all sounds as wav files.\n\n Arguments:\n filename (str | pathlib.Path): full path to under which the file is saved.\n '
with zipfile.ZipFile(filename, mode='a') as zip_file:
for (idx, sound) in enumerate(self):
f = io.BytesIO()
sound.write(f)
f.seek(0)
zip_file.writestr(f's_{idx}.wav', f.read())
f.close()
|
def write(self, filename):
'\n Save the Precomputed object as a zip file containing all sounds as wav files.\n\n Arguments:\n filename (str | pathlib.Path): full path to under which the file is saved.\n '
with zipfile.ZipFile(filename, mode='a') as zip_file:
for (idx, sound) in enumerate(self):
f = io.BytesIO()
sound.write(f)
f.seek(0)
zip_file.writestr(f's_{idx}.wav', f.read())
f.close()<|docstring|>Save the Precomputed object as a zip file containing all sounds as wav files.
Arguments:
filename (str | pathlib.Path): full path to under which the file is saved.<|endoftext|>
|
799570b77c2d18ec63b9e30917b1a3efd79663e92ba4b8754a11bd1087e18051
|
@staticmethod
def read(filename):
'\n Read a zip file containing wav files.\n\n Arguments:\n filename (str | pathlib.Path): full path to the file to be read.\n Returns:\n (slab.Precomputed): the file content.\n '
stims = Precomputed([])
with zipfile.ZipFile(filename, 'r') as zipped:
files = zipped.namelist()
for file in files:
wav_bytes = zipped.read(file)
stims.append(slab.Sound.read(io.BytesIO(wav_bytes)))
return stims
|
Read a zip file containing wav files.
Arguments:
filename (str | pathlib.Path): full path to the file to be read.
Returns:
(slab.Precomputed): the file content.
|
slab/psychoacoustics.py
|
read
|
jakab13/slab
| 7
|
python
|
@staticmethod
def read(filename):
'\n Read a zip file containing wav files.\n\n Arguments:\n filename (str | pathlib.Path): full path to the file to be read.\n Returns:\n (slab.Precomputed): the file content.\n '
stims = Precomputed([])
with zipfile.ZipFile(filename, 'r') as zipped:
files = zipped.namelist()
for file in files:
wav_bytes = zipped.read(file)
stims.append(slab.Sound.read(io.BytesIO(wav_bytes)))
return stims
|
@staticmethod
def read(filename):
'\n Read a zip file containing wav files.\n\n Arguments:\n filename (str | pathlib.Path): full path to the file to be read.\n Returns:\n (slab.Precomputed): the file content.\n '
stims = Precomputed([])
with zipfile.ZipFile(filename, 'r') as zipped:
files = zipped.namelist()
for file in files:
wav_bytes = zipped.read(file)
stims.append(slab.Sound.read(io.BytesIO(wav_bytes)))
return stims<|docstring|>Read a zip file containing wav files.
Arguments:
filename (str | pathlib.Path): full path to the file to be read.
Returns:
(slab.Precomputed): the file content.<|endoftext|>
|
105c3528ed18eb0840d2f59d49c672bb6efe6a4ef6e47d69462f8e3282228587
|
def t_unk() -> TestShaped:
'\n Creates an object with an unknown shape, for testing.\n '
return TestShaped(None)
|
Creates an object with an unknown shape, for testing.
|
tests/gpflow/experimental/check_shapes/utils.py
|
t_unk
|
joelberkeley/GPflow
| 0
|
python
|
def t_unk() -> TestShaped:
'\n \n '
return TestShaped(None)
|
def t_unk() -> TestShaped:
'\n \n '
return TestShaped(None)<|docstring|>Creates an object with an unknown shape, for testing.<|endoftext|>
|
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