body_hash
stringlengths 64
64
| body
stringlengths 23
109k
| docstring
stringlengths 1
57k
| path
stringlengths 4
198
| name
stringlengths 1
115
| repository_name
stringlengths 7
111
| repository_stars
float64 0
191k
| lang
stringclasses 1
value | body_without_docstring
stringlengths 14
108k
| unified
stringlengths 45
133k
|
|---|---|---|---|---|---|---|---|---|---|
ae6bd1539ea125c119e9877eb6fe7501e71f9ff23b80ffd39360fa0680dd2e11
|
def perform_raw(self) -> Point:
'\n Perform the scalar-multiplication of the key agreement.\n\n :return: The shared point.\n '
point = self.mult.multiply(int(self.privkey))
return point.to_affine()
|
Perform the scalar-multiplication of the key agreement.
:return: The shared point.
|
pyecsca/ec/key_agreement.py
|
perform_raw
|
Tomko10/pyecsca
| 24 |
python
|
def perform_raw(self) -> Point:
'\n Perform the scalar-multiplication of the key agreement.\n\n :return: The shared point.\n '
point = self.mult.multiply(int(self.privkey))
return point.to_affine()
|
def perform_raw(self) -> Point:
'\n Perform the scalar-multiplication of the key agreement.\n\n :return: The shared point.\n '
point = self.mult.multiply(int(self.privkey))
return point.to_affine()<|docstring|>Perform the scalar-multiplication of the key agreement.
:return: The shared point.<|endoftext|>
|
37487c6050bdaba23891d44b9a420b475ccd49cfb2fa50bcc4d0db450ee4d549
|
def perform(self) -> bytes:
'\n Perform the key agreement operation.\n\n :return: The shared secret.\n '
with ECDHAction(self.params, self.hash_algo, self.privkey, self.pubkey) as action:
affine_point = self.perform_raw()
x = int(affine_point.x)
p = self.params.curve.prime
n = ((p.bit_length() + 7) // 8)
result = x.to_bytes(n, byteorder='big')
if (self.hash_algo is not None):
result = self.hash_algo(result).digest()
return action.exit(result)
|
Perform the key agreement operation.
:return: The shared secret.
|
pyecsca/ec/key_agreement.py
|
perform
|
Tomko10/pyecsca
| 24 |
python
|
def perform(self) -> bytes:
'\n Perform the key agreement operation.\n\n :return: The shared secret.\n '
with ECDHAction(self.params, self.hash_algo, self.privkey, self.pubkey) as action:
affine_point = self.perform_raw()
x = int(affine_point.x)
p = self.params.curve.prime
n = ((p.bit_length() + 7) // 8)
result = x.to_bytes(n, byteorder='big')
if (self.hash_algo is not None):
result = self.hash_algo(result).digest()
return action.exit(result)
|
def perform(self) -> bytes:
'\n Perform the key agreement operation.\n\n :return: The shared secret.\n '
with ECDHAction(self.params, self.hash_algo, self.privkey, self.pubkey) as action:
affine_point = self.perform_raw()
x = int(affine_point.x)
p = self.params.curve.prime
n = ((p.bit_length() + 7) // 8)
result = x.to_bytes(n, byteorder='big')
if (self.hash_algo is not None):
result = self.hash_algo(result).digest()
return action.exit(result)<|docstring|>Perform the key agreement operation.
:return: The shared secret.<|endoftext|>
|
de5baac508483483b330415f45044fd707fbe6e6f070effaceff65685321dd13
|
def path(synset1, synset2):
'Return the Path similarity of *synset1* and *synset2*.'
distance = len(synset1.shortest_path(synset2, simulate_root=True))
return (1 / (distance + 1))
|
Return the Path similarity of *synset1* and *synset2*.
|
wn/similarity.py
|
path
|
fushinari/wn
| 0 |
python
|
def path(synset1, synset2):
distance = len(synset1.shortest_path(synset2, simulate_root=True))
return (1 / (distance + 1))
|
def path(synset1, synset2):
distance = len(synset1.shortest_path(synset2, simulate_root=True))
return (1 / (distance + 1))<|docstring|>Return the Path similarity of *synset1* and *synset2*.<|endoftext|>
|
1c709f5d5818731873096147e201b49f864795372d07e264cc7a8ea669b55e30
|
def wup(synset1: Synset, synset2: Synset) -> float:
'Return the Wu-Palmer similarity of *synset1* and *synset2*.'
lch = synset1.lowest_common_hypernyms(synset2, simulate_root=True)[0]
n = (lch.max_depth() + 1)
n1 = len(synset1.shortest_path(lch, simulate_root=True))
n2 = len(synset2.shortest_path(lch, simulate_root=True))
return ((2 * n) / ((n1 + n2) + (2 * n)))
|
Return the Wu-Palmer similarity of *synset1* and *synset2*.
|
wn/similarity.py
|
wup
|
fushinari/wn
| 0 |
python
|
def wup(synset1: Synset, synset2: Synset) -> float:
lch = synset1.lowest_common_hypernyms(synset2, simulate_root=True)[0]
n = (lch.max_depth() + 1)
n1 = len(synset1.shortest_path(lch, simulate_root=True))
n2 = len(synset2.shortest_path(lch, simulate_root=True))
return ((2 * n) / ((n1 + n2) + (2 * n)))
|
def wup(synset1: Synset, synset2: Synset) -> float:
lch = synset1.lowest_common_hypernyms(synset2, simulate_root=True)[0]
n = (lch.max_depth() + 1)
n1 = len(synset1.shortest_path(lch, simulate_root=True))
n2 = len(synset2.shortest_path(lch, simulate_root=True))
return ((2 * n) / ((n1 + n2) + (2 * n)))<|docstring|>Return the Wu-Palmer similarity of *synset1* and *synset2*.<|endoftext|>
|
89e29cde41cf79e104e5d2f7f677e29cf40f92c1e28a1374807fd6345906f497
|
def lch(synset1: Synset, synset2: Synset, max_depth: int=0) -> float:
'Return the Leacock-Chodorow similarity of *synset1* and *synset2*.'
distance = len(synset1.shortest_path(synset2, simulate_root=True))
if (max_depth <= 0):
raise wn.Error('max_depth must be greater than 0')
return (- math.log(((distance + 1) / (2 * max_depth))))
|
Return the Leacock-Chodorow similarity of *synset1* and *synset2*.
|
wn/similarity.py
|
lch
|
fushinari/wn
| 0 |
python
|
def lch(synset1: Synset, synset2: Synset, max_depth: int=0) -> float:
distance = len(synset1.shortest_path(synset2, simulate_root=True))
if (max_depth <= 0):
raise wn.Error('max_depth must be greater than 0')
return (- math.log(((distance + 1) / (2 * max_depth))))
|
def lch(synset1: Synset, synset2: Synset, max_depth: int=0) -> float:
distance = len(synset1.shortest_path(synset2, simulate_root=True))
if (max_depth <= 0):
raise wn.Error('max_depth must be greater than 0')
return (- math.log(((distance + 1) / (2 * max_depth))))<|docstring|>Return the Leacock-Chodorow similarity of *synset1* and *synset2*.<|endoftext|>
|
5a6ed699d923991602c05de2a606eea776f8434e3458416979ebbf41fa9c1f66
|
def render_get(self, request, components, msg):
'\n Handle a transaction request. There are four types of requests:\n empty path -- return a list of the committed transactions ids\n txnid -- return the contents of the specified transaction\n txnid and field name -- return the contents of the specified\n transaction\n txnid and HEAD request -- return success only if the transaction\n has been committed\n 404 -- transaction does not exist\n 302 -- transaction exists but has not been committed\n 200 -- transaction has been committed\n\n The request may specify additional parameters:\n blockcount -- the number of blocks (newest to oldest) from which to\n pull txns\n\n Transactions are returned from oldest to newest.\n '
if (components and (len(components[0]) == 0)):
components.pop(0)
if (len(components) == 0):
blkcount = 0
if ('blockcount' in msg):
blkcount = int(msg.get('blockcount').pop(0))
txnids = []
blockids = self.Ledger.committed_block_ids(blkcount)
while blockids:
blockid = blockids.pop()
txnids.extend(self.Ledger.BlockStore[blockid].TransactionIDs)
return txnids
txnid = components.pop(0)
if (txnid not in self.Ledger.TransactionStore):
raise Error(http.NOT_FOUND, 'no such transaction {0}'.format(txnid))
txn = self.Ledger.TransactionStore[txnid]
test_only = (request.method == 'HEAD')
if test_only:
if (txn.Status == transaction.Status.committed):
return None
else:
raise Error(http.FOUND, 'transaction not committed {0}'.format(txnid))
tinfo = txn.dump()
tinfo['Identifier'] = txnid
tinfo['Status'] = txn.Status
if (txn.Status == transaction.Status.committed):
tinfo['InBlock'] = txn.InBlock
if (not components):
return tinfo
field = components.pop(0)
if (field not in tinfo):
raise Error(http.BAD_REQUEST, 'unknown transaction field {0}'.format(field))
return tinfo[field]
|
Handle a transaction request. There are four types of requests:
empty path -- return a list of the committed transactions ids
txnid -- return the contents of the specified transaction
txnid and field name -- return the contents of the specified
transaction
txnid and HEAD request -- return success only if the transaction
has been committed
404 -- transaction does not exist
302 -- transaction exists but has not been committed
200 -- transaction has been committed
The request may specify additional parameters:
blockcount -- the number of blocks (newest to oldest) from which to
pull txns
Transactions are returned from oldest to newest.
|
validator/txnserver/web_pages/transaction_page.py
|
render_get
|
NunoEdgarGFlowHub/sawtooth-core
| 4 |
python
|
def render_get(self, request, components, msg):
'\n Handle a transaction request. There are four types of requests:\n empty path -- return a list of the committed transactions ids\n txnid -- return the contents of the specified transaction\n txnid and field name -- return the contents of the specified\n transaction\n txnid and HEAD request -- return success only if the transaction\n has been committed\n 404 -- transaction does not exist\n 302 -- transaction exists but has not been committed\n 200 -- transaction has been committed\n\n The request may specify additional parameters:\n blockcount -- the number of blocks (newest to oldest) from which to\n pull txns\n\n Transactions are returned from oldest to newest.\n '
if (components and (len(components[0]) == 0)):
components.pop(0)
if (len(components) == 0):
blkcount = 0
if ('blockcount' in msg):
blkcount = int(msg.get('blockcount').pop(0))
txnids = []
blockids = self.Ledger.committed_block_ids(blkcount)
while blockids:
blockid = blockids.pop()
txnids.extend(self.Ledger.BlockStore[blockid].TransactionIDs)
return txnids
txnid = components.pop(0)
if (txnid not in self.Ledger.TransactionStore):
raise Error(http.NOT_FOUND, 'no such transaction {0}'.format(txnid))
txn = self.Ledger.TransactionStore[txnid]
test_only = (request.method == 'HEAD')
if test_only:
if (txn.Status == transaction.Status.committed):
return None
else:
raise Error(http.FOUND, 'transaction not committed {0}'.format(txnid))
tinfo = txn.dump()
tinfo['Identifier'] = txnid
tinfo['Status'] = txn.Status
if (txn.Status == transaction.Status.committed):
tinfo['InBlock'] = txn.InBlock
if (not components):
return tinfo
field = components.pop(0)
if (field not in tinfo):
raise Error(http.BAD_REQUEST, 'unknown transaction field {0}'.format(field))
return tinfo[field]
|
def render_get(self, request, components, msg):
'\n Handle a transaction request. There are four types of requests:\n empty path -- return a list of the committed transactions ids\n txnid -- return the contents of the specified transaction\n txnid and field name -- return the contents of the specified\n transaction\n txnid and HEAD request -- return success only if the transaction\n has been committed\n 404 -- transaction does not exist\n 302 -- transaction exists but has not been committed\n 200 -- transaction has been committed\n\n The request may specify additional parameters:\n blockcount -- the number of blocks (newest to oldest) from which to\n pull txns\n\n Transactions are returned from oldest to newest.\n '
if (components and (len(components[0]) == 0)):
components.pop(0)
if (len(components) == 0):
blkcount = 0
if ('blockcount' in msg):
blkcount = int(msg.get('blockcount').pop(0))
txnids = []
blockids = self.Ledger.committed_block_ids(blkcount)
while blockids:
blockid = blockids.pop()
txnids.extend(self.Ledger.BlockStore[blockid].TransactionIDs)
return txnids
txnid = components.pop(0)
if (txnid not in self.Ledger.TransactionStore):
raise Error(http.NOT_FOUND, 'no such transaction {0}'.format(txnid))
txn = self.Ledger.TransactionStore[txnid]
test_only = (request.method == 'HEAD')
if test_only:
if (txn.Status == transaction.Status.committed):
return None
else:
raise Error(http.FOUND, 'transaction not committed {0}'.format(txnid))
tinfo = txn.dump()
tinfo['Identifier'] = txnid
tinfo['Status'] = txn.Status
if (txn.Status == transaction.Status.committed):
tinfo['InBlock'] = txn.InBlock
if (not components):
return tinfo
field = components.pop(0)
if (field not in tinfo):
raise Error(http.BAD_REQUEST, 'unknown transaction field {0}'.format(field))
return tinfo[field]<|docstring|>Handle a transaction request. There are four types of requests:
empty path -- return a list of the committed transactions ids
txnid -- return the contents of the specified transaction
txnid and field name -- return the contents of the specified
transaction
txnid and HEAD request -- return success only if the transaction
has been committed
404 -- transaction does not exist
302 -- transaction exists but has not been committed
200 -- transaction has been committed
The request may specify additional parameters:
blockcount -- the number of blocks (newest to oldest) from which to
pull txns
Transactions are returned from oldest to newest.<|endoftext|>
|
ab9af6e9c914b41a2cfc6add2e0ebbe7a38a36789fddf19f24d410a0be92a487
|
def framesig(sig, frame_len, frame_step, winfunc=(lambda x: numpy.ones((x,)))):
'\n Frame a signal into overlapping frames.\n\n Args:\n sig: the audio signal to frame.\n frame_len: length of each frame measured in samples.\n frame_step: number of samples after the start of the previous frame that\n the next frame should begin.\n winfunc: the analysis window to apply to each frame. By default no\n window is applied.\n\n Returns:\n an array of frames. Size is NUMFRAMES by frame_len.\n '
slen = len(sig)
frame_len = int(round(frame_len))
frame_step = int(round(frame_step))
if (slen <= frame_len):
numframes = 1
else:
numframes = (1 + int(math.ceil((((1.0 * slen) - frame_len) / frame_step))))
padlen = int((((numframes - 1) * frame_step) + frame_len))
zeros = numpy.zeros(((padlen - slen),))
padsignal = numpy.concatenate((sig, zeros))
indices = (numpy.tile(numpy.arange(0, frame_len), (numframes, 1)) + numpy.tile(numpy.arange(0, (numframes * frame_step), frame_step), (frame_len, 1)).T)
indices = numpy.array(indices, dtype=numpy.int32)
frames = padsignal[indices]
win = numpy.tile(winfunc(frame_len), (numframes, 1))
return (frames * win)
|
Frame a signal into overlapping frames.
Args:
sig: the audio signal to frame.
frame_len: length of each frame measured in samples.
frame_step: number of samples after the start of the previous frame that
the next frame should begin.
winfunc: the analysis window to apply to each frame. By default no
window is applied.
Returns:
an array of frames. Size is NUMFRAMES by frame_len.
|
processing/sigproc.py
|
framesig
|
v0lta/tfkaldi
| 200 |
python
|
def framesig(sig, frame_len, frame_step, winfunc=(lambda x: numpy.ones((x,)))):
'\n Frame a signal into overlapping frames.\n\n Args:\n sig: the audio signal to frame.\n frame_len: length of each frame measured in samples.\n frame_step: number of samples after the start of the previous frame that\n the next frame should begin.\n winfunc: the analysis window to apply to each frame. By default no\n window is applied.\n\n Returns:\n an array of frames. Size is NUMFRAMES by frame_len.\n '
slen = len(sig)
frame_len = int(round(frame_len))
frame_step = int(round(frame_step))
if (slen <= frame_len):
numframes = 1
else:
numframes = (1 + int(math.ceil((((1.0 * slen) - frame_len) / frame_step))))
padlen = int((((numframes - 1) * frame_step) + frame_len))
zeros = numpy.zeros(((padlen - slen),))
padsignal = numpy.concatenate((sig, zeros))
indices = (numpy.tile(numpy.arange(0, frame_len), (numframes, 1)) + numpy.tile(numpy.arange(0, (numframes * frame_step), frame_step), (frame_len, 1)).T)
indices = numpy.array(indices, dtype=numpy.int32)
frames = padsignal[indices]
win = numpy.tile(winfunc(frame_len), (numframes, 1))
return (frames * win)
|
def framesig(sig, frame_len, frame_step, winfunc=(lambda x: numpy.ones((x,)))):
'\n Frame a signal into overlapping frames.\n\n Args:\n sig: the audio signal to frame.\n frame_len: length of each frame measured in samples.\n frame_step: number of samples after the start of the previous frame that\n the next frame should begin.\n winfunc: the analysis window to apply to each frame. By default no\n window is applied.\n\n Returns:\n an array of frames. Size is NUMFRAMES by frame_len.\n '
slen = len(sig)
frame_len = int(round(frame_len))
frame_step = int(round(frame_step))
if (slen <= frame_len):
numframes = 1
else:
numframes = (1 + int(math.ceil((((1.0 * slen) - frame_len) / frame_step))))
padlen = int((((numframes - 1) * frame_step) + frame_len))
zeros = numpy.zeros(((padlen - slen),))
padsignal = numpy.concatenate((sig, zeros))
indices = (numpy.tile(numpy.arange(0, frame_len), (numframes, 1)) + numpy.tile(numpy.arange(0, (numframes * frame_step), frame_step), (frame_len, 1)).T)
indices = numpy.array(indices, dtype=numpy.int32)
frames = padsignal[indices]
win = numpy.tile(winfunc(frame_len), (numframes, 1))
return (frames * win)<|docstring|>Frame a signal into overlapping frames.
Args:
sig: the audio signal to frame.
frame_len: length of each frame measured in samples.
frame_step: number of samples after the start of the previous frame that
the next frame should begin.
winfunc: the analysis window to apply to each frame. By default no
window is applied.
Returns:
an array of frames. Size is NUMFRAMES by frame_len.<|endoftext|>
|
1453bd657388c3ab7fce9b7f54e76a0f7674fe8afd0c0f94e62298e955b32dc4
|
def deframesig(frames, siglen, frame_len, frame_step, winfunc=(lambda x: numpy.ones((x,)))):
'\n Does overlap-add procedure to undo the action of framesig.\n\n Args:\n frames the: array of frames.\n siglen the: length of the desired signal, use 0 if unknown. Output will\n be truncated to siglen samples.\n frame_len: length of each frame measured in samples.\n frame_step: number of samples after the start of the previous frame that\n the next frame should begin.\n winfunc: the analysis window to apply to each frame. By default no\n window is applied.\n\n Returns:\n a 1-D signal.\n '
frame_len = round(frame_len)
frame_step = round(frame_step)
numframes = numpy.shape(frames)[0]
assert (numpy.shape(frames)[1] == frame_len), '"frames" matrix is wrong\n size, 2nd dim is not equal to frame_len'
indices = (numpy.tile(numpy.arange(0, frame_len), (numframes, 1)) + numpy.tile(numpy.arange(0, (numframes * frame_step), frame_step), (frame_len, 1)).T)
indices = numpy.array(indices, dtype=numpy.int32)
padlen = (((numframes - 1) * frame_step) + frame_len)
if (siglen <= 0):
siglen = padlen
rec_signal = numpy.zeros((padlen,))
window_correction = numpy.zeros((padlen,))
win = winfunc(frame_len)
for i in range(0, numframes):
window_correction[indices[(i, :)]] = ((window_correction[indices[(i, :)]] + win) + 1e-15)
rec_signal[indices[(i, :)]] = (rec_signal[indices[(i, :)]] + frames[(i, :)])
rec_signal = (rec_signal / window_correction)
return rec_signal[0:siglen]
|
Does overlap-add procedure to undo the action of framesig.
Args:
frames the: array of frames.
siglen the: length of the desired signal, use 0 if unknown. Output will
be truncated to siglen samples.
frame_len: length of each frame measured in samples.
frame_step: number of samples after the start of the previous frame that
the next frame should begin.
winfunc: the analysis window to apply to each frame. By default no
window is applied.
Returns:
a 1-D signal.
|
processing/sigproc.py
|
deframesig
|
v0lta/tfkaldi
| 200 |
python
|
def deframesig(frames, siglen, frame_len, frame_step, winfunc=(lambda x: numpy.ones((x,)))):
'\n Does overlap-add procedure to undo the action of framesig.\n\n Args:\n frames the: array of frames.\n siglen the: length of the desired signal, use 0 if unknown. Output will\n be truncated to siglen samples.\n frame_len: length of each frame measured in samples.\n frame_step: number of samples after the start of the previous frame that\n the next frame should begin.\n winfunc: the analysis window to apply to each frame. By default no\n window is applied.\n\n Returns:\n a 1-D signal.\n '
frame_len = round(frame_len)
frame_step = round(frame_step)
numframes = numpy.shape(frames)[0]
assert (numpy.shape(frames)[1] == frame_len), '"frames" matrix is wrong\n size, 2nd dim is not equal to frame_len'
indices = (numpy.tile(numpy.arange(0, frame_len), (numframes, 1)) + numpy.tile(numpy.arange(0, (numframes * frame_step), frame_step), (frame_len, 1)).T)
indices = numpy.array(indices, dtype=numpy.int32)
padlen = (((numframes - 1) * frame_step) + frame_len)
if (siglen <= 0):
siglen = padlen
rec_signal = numpy.zeros((padlen,))
window_correction = numpy.zeros((padlen,))
win = winfunc(frame_len)
for i in range(0, numframes):
window_correction[indices[(i, :)]] = ((window_correction[indices[(i, :)]] + win) + 1e-15)
rec_signal[indices[(i, :)]] = (rec_signal[indices[(i, :)]] + frames[(i, :)])
rec_signal = (rec_signal / window_correction)
return rec_signal[0:siglen]
|
def deframesig(frames, siglen, frame_len, frame_step, winfunc=(lambda x: numpy.ones((x,)))):
'\n Does overlap-add procedure to undo the action of framesig.\n\n Args:\n frames the: array of frames.\n siglen the: length of the desired signal, use 0 if unknown. Output will\n be truncated to siglen samples.\n frame_len: length of each frame measured in samples.\n frame_step: number of samples after the start of the previous frame that\n the next frame should begin.\n winfunc: the analysis window to apply to each frame. By default no\n window is applied.\n\n Returns:\n a 1-D signal.\n '
frame_len = round(frame_len)
frame_step = round(frame_step)
numframes = numpy.shape(frames)[0]
assert (numpy.shape(frames)[1] == frame_len), '"frames" matrix is wrong\n size, 2nd dim is not equal to frame_len'
indices = (numpy.tile(numpy.arange(0, frame_len), (numframes, 1)) + numpy.tile(numpy.arange(0, (numframes * frame_step), frame_step), (frame_len, 1)).T)
indices = numpy.array(indices, dtype=numpy.int32)
padlen = (((numframes - 1) * frame_step) + frame_len)
if (siglen <= 0):
siglen = padlen
rec_signal = numpy.zeros((padlen,))
window_correction = numpy.zeros((padlen,))
win = winfunc(frame_len)
for i in range(0, numframes):
window_correction[indices[(i, :)]] = ((window_correction[indices[(i, :)]] + win) + 1e-15)
rec_signal[indices[(i, :)]] = (rec_signal[indices[(i, :)]] + frames[(i, :)])
rec_signal = (rec_signal / window_correction)
return rec_signal[0:siglen]<|docstring|>Does overlap-add procedure to undo the action of framesig.
Args:
frames the: array of frames.
siglen the: length of the desired signal, use 0 if unknown. Output will
be truncated to siglen samples.
frame_len: length of each frame measured in samples.
frame_step: number of samples after the start of the previous frame that
the next frame should begin.
winfunc: the analysis window to apply to each frame. By default no
window is applied.
Returns:
a 1-D signal.<|endoftext|>
|
59dd27f65f3e2742e47e9a48194854b931efa3ba29c4647591d4e8ef06b47008
|
def magspec(frames, nfft):
'\n Compute the magnitude spectrum of each frame in frames.\n\n If frames is an NxD matrix, output will be NxNFFT.\n\n Args:\n frames: the array of frames. Each row is a frame.\n nfft: the FFT length to use. If NFFT > frame_len, the frames are\n zero-padded.\n\n Returns:\n If frames is an NxD matrix, output will be NxNFFT. Each row will be the\n magnitude spectrum of the corresponding frame.\n '
complex_spec = numpy.fft.rfft(frames, nfft)
return numpy.absolute(complex_spec)
|
Compute the magnitude spectrum of each frame in frames.
If frames is an NxD matrix, output will be NxNFFT.
Args:
frames: the array of frames. Each row is a frame.
nfft: the FFT length to use. If NFFT > frame_len, the frames are
zero-padded.
Returns:
If frames is an NxD matrix, output will be NxNFFT. Each row will be the
magnitude spectrum of the corresponding frame.
|
processing/sigproc.py
|
magspec
|
v0lta/tfkaldi
| 200 |
python
|
def magspec(frames, nfft):
'\n Compute the magnitude spectrum of each frame in frames.\n\n If frames is an NxD matrix, output will be NxNFFT.\n\n Args:\n frames: the array of frames. Each row is a frame.\n nfft: the FFT length to use. If NFFT > frame_len, the frames are\n zero-padded.\n\n Returns:\n If frames is an NxD matrix, output will be NxNFFT. Each row will be the\n magnitude spectrum of the corresponding frame.\n '
complex_spec = numpy.fft.rfft(frames, nfft)
return numpy.absolute(complex_spec)
|
def magspec(frames, nfft):
'\n Compute the magnitude spectrum of each frame in frames.\n\n If frames is an NxD matrix, output will be NxNFFT.\n\n Args:\n frames: the array of frames. Each row is a frame.\n nfft: the FFT length to use. If NFFT > frame_len, the frames are\n zero-padded.\n\n Returns:\n If frames is an NxD matrix, output will be NxNFFT. Each row will be the\n magnitude spectrum of the corresponding frame.\n '
complex_spec = numpy.fft.rfft(frames, nfft)
return numpy.absolute(complex_spec)<|docstring|>Compute the magnitude spectrum of each frame in frames.
If frames is an NxD matrix, output will be NxNFFT.
Args:
frames: the array of frames. Each row is a frame.
nfft: the FFT length to use. If NFFT > frame_len, the frames are
zero-padded.
Returns:
If frames is an NxD matrix, output will be NxNFFT. Each row will be the
magnitude spectrum of the corresponding frame.<|endoftext|>
|
cc0cb93f78d58260c7b008ff1fd9742ba70801527649b7da38016951ecf4d227
|
def powspec(frames, nfft):
'\n Compute the power spectrum of each frame in frames.\n\n If frames is an NxD matrix, output will be NxNFFT.\n\n Args:\n frames: the array of frames. Each row is a frame.\n nfft: the FFT length to use. If NFFT > frame_len, the frames are\n zero-padded.\n\n Returns:\n If frames is an NxD matrix, output will be NxNFFT. Each row will be the\n power spectrum of the corresponding frame.\n '
return ((1.0 / nfft) * numpy.square(magspec(frames, nfft)))
|
Compute the power spectrum of each frame in frames.
If frames is an NxD matrix, output will be NxNFFT.
Args:
frames: the array of frames. Each row is a frame.
nfft: the FFT length to use. If NFFT > frame_len, the frames are
zero-padded.
Returns:
If frames is an NxD matrix, output will be NxNFFT. Each row will be the
power spectrum of the corresponding frame.
|
processing/sigproc.py
|
powspec
|
v0lta/tfkaldi
| 200 |
python
|
def powspec(frames, nfft):
'\n Compute the power spectrum of each frame in frames.\n\n If frames is an NxD matrix, output will be NxNFFT.\n\n Args:\n frames: the array of frames. Each row is a frame.\n nfft: the FFT length to use. If NFFT > frame_len, the frames are\n zero-padded.\n\n Returns:\n If frames is an NxD matrix, output will be NxNFFT. Each row will be the\n power spectrum of the corresponding frame.\n '
return ((1.0 / nfft) * numpy.square(magspec(frames, nfft)))
|
def powspec(frames, nfft):
'\n Compute the power spectrum of each frame in frames.\n\n If frames is an NxD matrix, output will be NxNFFT.\n\n Args:\n frames: the array of frames. Each row is a frame.\n nfft: the FFT length to use. If NFFT > frame_len, the frames are\n zero-padded.\n\n Returns:\n If frames is an NxD matrix, output will be NxNFFT. Each row will be the\n power spectrum of the corresponding frame.\n '
return ((1.0 / nfft) * numpy.square(magspec(frames, nfft)))<|docstring|>Compute the power spectrum of each frame in frames.
If frames is an NxD matrix, output will be NxNFFT.
Args:
frames: the array of frames. Each row is a frame.
nfft: the FFT length to use. If NFFT > frame_len, the frames are
zero-padded.
Returns:
If frames is an NxD matrix, output will be NxNFFT. Each row will be the
power spectrum of the corresponding frame.<|endoftext|>
|
3ae3c5fbe3c7043bfdde092202b506e0b0e0f0b0c10e8c8273b79032d3453da3
|
def logpowspec(frames, nfft, norm=1):
'\n Compute the log power spectrum of each frame in frames.\n\n If frames is an NxD matrix, output will be NxNFFT.\n\n Args:\n frames: the array of frames. Each row is a frame.\n nfft: the FFT length to use. If NFFT > frame_len, the frames are\n zero-padded.\n norm: If norm=1, the log power spectrum is normalised so that the max\n value (across all frames) is 1.\n\n Returns:\n If frames is an NxD matrix, output will be NxNFFT. Each row will be the\n log power spectrum of the corresponding frame.\n '
ps = powspec(frames, nfft)
ps[(ps <= 1e-30)] = 1e-30
lps = (10 * numpy.log10(ps))
if norm:
return (lps - numpy.max(lps))
else:
return lps
|
Compute the log power spectrum of each frame in frames.
If frames is an NxD matrix, output will be NxNFFT.
Args:
frames: the array of frames. Each row is a frame.
nfft: the FFT length to use. If NFFT > frame_len, the frames are
zero-padded.
norm: If norm=1, the log power spectrum is normalised so that the max
value (across all frames) is 1.
Returns:
If frames is an NxD matrix, output will be NxNFFT. Each row will be the
log power spectrum of the corresponding frame.
|
processing/sigproc.py
|
logpowspec
|
v0lta/tfkaldi
| 200 |
python
|
def logpowspec(frames, nfft, norm=1):
'\n Compute the log power spectrum of each frame in frames.\n\n If frames is an NxD matrix, output will be NxNFFT.\n\n Args:\n frames: the array of frames. Each row is a frame.\n nfft: the FFT length to use. If NFFT > frame_len, the frames are\n zero-padded.\n norm: If norm=1, the log power spectrum is normalised so that the max\n value (across all frames) is 1.\n\n Returns:\n If frames is an NxD matrix, output will be NxNFFT. Each row will be the\n log power spectrum of the corresponding frame.\n '
ps = powspec(frames, nfft)
ps[(ps <= 1e-30)] = 1e-30
lps = (10 * numpy.log10(ps))
if norm:
return (lps - numpy.max(lps))
else:
return lps
|
def logpowspec(frames, nfft, norm=1):
'\n Compute the log power spectrum of each frame in frames.\n\n If frames is an NxD matrix, output will be NxNFFT.\n\n Args:\n frames: the array of frames. Each row is a frame.\n nfft: the FFT length to use. If NFFT > frame_len, the frames are\n zero-padded.\n norm: If norm=1, the log power spectrum is normalised so that the max\n value (across all frames) is 1.\n\n Returns:\n If frames is an NxD matrix, output will be NxNFFT. Each row will be the\n log power spectrum of the corresponding frame.\n '
ps = powspec(frames, nfft)
ps[(ps <= 1e-30)] = 1e-30
lps = (10 * numpy.log10(ps))
if norm:
return (lps - numpy.max(lps))
else:
return lps<|docstring|>Compute the log power spectrum of each frame in frames.
If frames is an NxD matrix, output will be NxNFFT.
Args:
frames: the array of frames. Each row is a frame.
nfft: the FFT length to use. If NFFT > frame_len, the frames are
zero-padded.
norm: If norm=1, the log power spectrum is normalised so that the max
value (across all frames) is 1.
Returns:
If frames is an NxD matrix, output will be NxNFFT. Each row will be the
log power spectrum of the corresponding frame.<|endoftext|>
|
21a19c75c99050c1ee902ef950a21cd39fec70c6270300c2c01e29fcf018ea69
|
def preemphasis(signal, coeff=0.95):
'\n perform preemphasis on the input signal.\n\n Args:\n signal: The signal to filter.\n coeff: The preemphasis coefficient. 0 is no filter, default is 0.95.\n\n Returns:\n the filtered signal.\n '
return numpy.append(signal[0], (signal[1:] - (coeff * signal[:(- 1)])))
|
perform preemphasis on the input signal.
Args:
signal: The signal to filter.
coeff: The preemphasis coefficient. 0 is no filter, default is 0.95.
Returns:
the filtered signal.
|
processing/sigproc.py
|
preemphasis
|
v0lta/tfkaldi
| 200 |
python
|
def preemphasis(signal, coeff=0.95):
'\n perform preemphasis on the input signal.\n\n Args:\n signal: The signal to filter.\n coeff: The preemphasis coefficient. 0 is no filter, default is 0.95.\n\n Returns:\n the filtered signal.\n '
return numpy.append(signal[0], (signal[1:] - (coeff * signal[:(- 1)])))
|
def preemphasis(signal, coeff=0.95):
'\n perform preemphasis on the input signal.\n\n Args:\n signal: The signal to filter.\n coeff: The preemphasis coefficient. 0 is no filter, default is 0.95.\n\n Returns:\n the filtered signal.\n '
return numpy.append(signal[0], (signal[1:] - (coeff * signal[:(- 1)])))<|docstring|>perform preemphasis on the input signal.
Args:
signal: The signal to filter.
coeff: The preemphasis coefficient. 0 is no filter, default is 0.95.
Returns:
the filtered signal.<|endoftext|>
|
d558534fb59ed65e019695628121081cb671d29a3f6272b42266ad52f6944c8f
|
def min_cost(self, costs: List[List[int]]) -> int:
'\n Time: O(n), Space: O(1)\n\n :param costs:\n :return:\n '
if (not costs):
return 0
pre0 = pre1 = pre2 = 0
for i in range(1, (len(costs) + 1)):
cur0 = (min(pre1, pre2) + costs[(i - 1)][0])
cur1 = (min(pre0, pre2) + costs[(i - 1)][1])
cur2 = (min(pre0, pre1) + costs[(i - 1)][2])
(pre0, pre1, pre2) = (cur0, cur1, cur2)
return min(pre0, pre1, pre2)
|
Time: O(n), Space: O(1)
:param costs:
:return:
|
python/src/problem/leetcode/easy/leetcode_256.py
|
min_cost
|
yipwinghong/Algorithm
| 9 |
python
|
def min_cost(self, costs: List[List[int]]) -> int:
'\n Time: O(n), Space: O(1)\n\n :param costs:\n :return:\n '
if (not costs):
return 0
pre0 = pre1 = pre2 = 0
for i in range(1, (len(costs) + 1)):
cur0 = (min(pre1, pre2) + costs[(i - 1)][0])
cur1 = (min(pre0, pre2) + costs[(i - 1)][1])
cur2 = (min(pre0, pre1) + costs[(i - 1)][2])
(pre0, pre1, pre2) = (cur0, cur1, cur2)
return min(pre0, pre1, pre2)
|
def min_cost(self, costs: List[List[int]]) -> int:
'\n Time: O(n), Space: O(1)\n\n :param costs:\n :return:\n '
if (not costs):
return 0
pre0 = pre1 = pre2 = 0
for i in range(1, (len(costs) + 1)):
cur0 = (min(pre1, pre2) + costs[(i - 1)][0])
cur1 = (min(pre0, pre2) + costs[(i - 1)][1])
cur2 = (min(pre0, pre1) + costs[(i - 1)][2])
(pre0, pre1, pre2) = (cur0, cur1, cur2)
return min(pre0, pre1, pre2)<|docstring|>Time: O(n), Space: O(1)
:param costs:
:return:<|endoftext|>
|
ca7ea2756d50937c8a0984e077b8f1887d4c1a87ca9e01cb4fb5ebd002c6d478
|
def require(modulename, package=None):
"\n Load, or reload a module.\n\n When under heavy development, a user's tool might consist of multiple\n modules. If those are imported using the standard 'import' mechanism,\n there is no guarantee that the Python implementation will re-read\n and re-evaluate the module's Python code. In fact, it usually doesn't.\n What should be done instead is 'reload()'-ing that module.\n\n This is a simple helper function that will do just that: In case the\n module doesn't exist, it 'import's it, and if it does exist,\n 'reload()'s it.\n\n The importing module (i.e., the module calling require()) will have\n the loaded module bound to its globals(), under the name 'modulename'.\n (If require() is called from the command line, the importing module\n will be '__main__'.)\n\n For more information, see: <http://www.hexblog.com/?p=749>.\n "
import inspect
(frame_obj, filename, line_number, function_name, lines, index) = inspect.stack()[1]
importer_module = inspect.getmodule(frame_obj)
if (importer_module is None):
importer_module = sys.modules['__main__']
if (modulename in sys.modules.keys()):
reload(sys.modules[modulename])
m = sys.modules[modulename]
else:
import importlib
m = importlib.import_module(modulename, package)
sys.modules[modulename] = m
setattr(importer_module, modulename, m)
|
Load, or reload a module.
When under heavy development, a user's tool might consist of multiple
modules. If those are imported using the standard 'import' mechanism,
there is no guarantee that the Python implementation will re-read
and re-evaluate the module's Python code. In fact, it usually doesn't.
What should be done instead is 'reload()'-ing that module.
This is a simple helper function that will do just that: In case the
module doesn't exist, it 'import's it, and if it does exist,
'reload()'s it.
The importing module (i.e., the module calling require()) will have
the loaded module bound to its globals(), under the name 'modulename'.
(If require() is called from the command line, the importing module
will be '__main__'.)
For more information, see: <http://www.hexblog.com/?p=749>.
|
pywraps/py_idaapi.py
|
require
|
diamondo25/src
| 2 |
python
|
def require(modulename, package=None):
"\n Load, or reload a module.\n\n When under heavy development, a user's tool might consist of multiple\n modules. If those are imported using the standard 'import' mechanism,\n there is no guarantee that the Python implementation will re-read\n and re-evaluate the module's Python code. In fact, it usually doesn't.\n What should be done instead is 'reload()'-ing that module.\n\n This is a simple helper function that will do just that: In case the\n module doesn't exist, it 'import's it, and if it does exist,\n 'reload()'s it.\n\n The importing module (i.e., the module calling require()) will have\n the loaded module bound to its globals(), under the name 'modulename'.\n (If require() is called from the command line, the importing module\n will be '__main__'.)\n\n For more information, see: <http://www.hexblog.com/?p=749>.\n "
import inspect
(frame_obj, filename, line_number, function_name, lines, index) = inspect.stack()[1]
importer_module = inspect.getmodule(frame_obj)
if (importer_module is None):
importer_module = sys.modules['__main__']
if (modulename in sys.modules.keys()):
reload(sys.modules[modulename])
m = sys.modules[modulename]
else:
import importlib
m = importlib.import_module(modulename, package)
sys.modules[modulename] = m
setattr(importer_module, modulename, m)
|
def require(modulename, package=None):
"\n Load, or reload a module.\n\n When under heavy development, a user's tool might consist of multiple\n modules. If those are imported using the standard 'import' mechanism,\n there is no guarantee that the Python implementation will re-read\n and re-evaluate the module's Python code. In fact, it usually doesn't.\n What should be done instead is 'reload()'-ing that module.\n\n This is a simple helper function that will do just that: In case the\n module doesn't exist, it 'import's it, and if it does exist,\n 'reload()'s it.\n\n The importing module (i.e., the module calling require()) will have\n the loaded module bound to its globals(), under the name 'modulename'.\n (If require() is called from the command line, the importing module\n will be '__main__'.)\n\n For more information, see: <http://www.hexblog.com/?p=749>.\n "
import inspect
(frame_obj, filename, line_number, function_name, lines, index) = inspect.stack()[1]
importer_module = inspect.getmodule(frame_obj)
if (importer_module is None):
importer_module = sys.modules['__main__']
if (modulename in sys.modules.keys()):
reload(sys.modules[modulename])
m = sys.modules[modulename]
else:
import importlib
m = importlib.import_module(modulename, package)
sys.modules[modulename] = m
setattr(importer_module, modulename, m)<|docstring|>Load, or reload a module.
When under heavy development, a user's tool might consist of multiple
modules. If those are imported using the standard 'import' mechanism,
there is no guarantee that the Python implementation will re-read
and re-evaluate the module's Python code. In fact, it usually doesn't.
What should be done instead is 'reload()'-ing that module.
This is a simple helper function that will do just that: In case the
module doesn't exist, it 'import's it, and if it does exist,
'reload()'s it.
The importing module (i.e., the module calling require()) will have
the loaded module bound to its globals(), under the name 'modulename'.
(If require() is called from the command line, the importing module
will be '__main__'.)
For more information, see: <http://www.hexblog.com/?p=749>.<|endoftext|>
|
41c5c34f574960874e5db2c0a810ddbe5a46a1dbefedcfd48f5960530989b141
|
def _bounded_getitem_iterator(self):
'Helper function, to be set as __iter__ method for qvector-, or array-based classes.'
for i in range(len(self)):
(yield self[i])
|
Helper function, to be set as __iter__ method for qvector-, or array-based classes.
|
pywraps/py_idaapi.py
|
_bounded_getitem_iterator
|
diamondo25/src
| 2 |
python
|
def _bounded_getitem_iterator(self):
for i in range(len(self)):
(yield self[i])
|
def _bounded_getitem_iterator(self):
for i in range(len(self)):
(yield self[i])<|docstring|>Helper function, to be set as __iter__ method for qvector-, or array-based classes.<|endoftext|>
|
9f1b39c59300acea70943ecbb062e64c0483b495ecdbbb112249393dd7ec61a5
|
def as_cstr(val):
'\n Returns a C str from the passed value. The passed value can be of type refclass (returned by a call to buffer() or byref())\n It scans for the first \x00 and returns the string value up to that point.\n '
if isinstance(val, PyIdc_cvt_refclass__):
val = val.value
n = val.find('\x00')
return (val if (n == (- 1)) else val[:n])
|
Returns a C str from the passed value. The passed value can be of type refclass (returned by a call to buffer() or byref())
It scans for the first and returns the string value up to that point.
|
pywraps/py_idaapi.py
|
as_cstr
|
diamondo25/src
| 2 |
python
|
def as_cstr(val):
'\n Returns a C str from the passed value. The passed value can be of type refclass (returned by a call to buffer() or byref())\n It scans for the first \x00 and returns the string value up to that point.\n '
if isinstance(val, PyIdc_cvt_refclass__):
val = val.value
n = val.find('\x00')
return (val if (n == (- 1)) else val[:n])
|
def as_cstr(val):
'\n Returns a C str from the passed value. The passed value can be of type refclass (returned by a call to buffer() or byref())\n It scans for the first \x00 and returns the string value up to that point.\n '
if isinstance(val, PyIdc_cvt_refclass__):
val = val.value
n = val.find('\x00')
return (val if (n == (- 1)) else val[:n])<|docstring|>Returns a C str from the passed value. The passed value can be of type refclass (returned by a call to buffer() or byref())
It scans for the first and returns the string value up to that point.<|endoftext|>
|
f66883c22932ffe78ebb30f8ea3012fb304593598bb927719d790d36dfa84263
|
def as_unicode(s):
'Convenience function to convert a string into appropriate unicode format'
import _ida_ida
return unicode(s).encode(('UTF-16' + ('BE' if _ida_ida.cvar.inf.is_be() else 'LE')))
|
Convenience function to convert a string into appropriate unicode format
|
pywraps/py_idaapi.py
|
as_unicode
|
diamondo25/src
| 2 |
python
|
def as_unicode(s):
import _ida_ida
return unicode(s).encode(('UTF-16' + ('BE' if _ida_ida.cvar.inf.is_be() else 'LE')))
|
def as_unicode(s):
import _ida_ida
return unicode(s).encode(('UTF-16' + ('BE' if _ida_ida.cvar.inf.is_be() else 'LE')))<|docstring|>Convenience function to convert a string into appropriate unicode format<|endoftext|>
|
74af519fe573f4629db3a4e41ec7490138995b93511835b074e0d81039be68cd
|
def as_uint32(v):
'Returns a number as an unsigned int32 number'
return (v & 4294967295)
|
Returns a number as an unsigned int32 number
|
pywraps/py_idaapi.py
|
as_uint32
|
diamondo25/src
| 2 |
python
|
def as_uint32(v):
return (v & 4294967295)
|
def as_uint32(v):
return (v & 4294967295)<|docstring|>Returns a number as an unsigned int32 number<|endoftext|>
|
6287a575a9c1da335300b80da3efabc6568f6dc6270909d8de2464cb6ca317be
|
def as_int32(v):
'Returns a number as a signed int32 number'
return (- (((~ v) & 4294967295) + 1))
|
Returns a number as a signed int32 number
|
pywraps/py_idaapi.py
|
as_int32
|
diamondo25/src
| 2 |
python
|
def as_int32(v):
return (- (((~ v) & 4294967295) + 1))
|
def as_int32(v):
return (- (((~ v) & 4294967295) + 1))<|docstring|>Returns a number as a signed int32 number<|endoftext|>
|
e3546dba1dae5ecb5a6f252908daa065a1f2ab93153e8d436202b3f8ac0cfa5a
|
def as_signed(v, nbits=32):
'\n Returns a number as signed. The number of bits are specified by the user.\n The MSB holds the sign.\n '
return ((- (((~ v) & ((1 << nbits) - 1)) + 1)) if (v & (1 << (nbits - 1))) else v)
|
Returns a number as signed. The number of bits are specified by the user.
The MSB holds the sign.
|
pywraps/py_idaapi.py
|
as_signed
|
diamondo25/src
| 2 |
python
|
def as_signed(v, nbits=32):
'\n Returns a number as signed. The number of bits are specified by the user.\n The MSB holds the sign.\n '
return ((- (((~ v) & ((1 << nbits) - 1)) + 1)) if (v & (1 << (nbits - 1))) else v)
|
def as_signed(v, nbits=32):
'\n Returns a number as signed. The number of bits are specified by the user.\n The MSB holds the sign.\n '
return ((- (((~ v) & ((1 << nbits) - 1)) + 1)) if (v & (1 << (nbits - 1))) else v)<|docstring|>Returns a number as signed. The number of bits are specified by the user.
The MSB holds the sign.<|endoftext|>
|
71a5306740c2bf1e8907c5f2927b36de87653f7baedee3b1b383ce9e971b044f
|
def copy_bits(v, s, e=(- 1)):
'\n Copy bits from a value\n @param v: the value\n @param s: starting bit (0-based)\n @param e: ending bit\n '
if (e == (- 1)):
e = s
if (s > e):
(e, s) = (s, e)
mask = (~ (((1 << ((e - s) + 1)) - 1) << s))
return ((v & mask) >> s)
|
Copy bits from a value
@param v: the value
@param s: starting bit (0-based)
@param e: ending bit
|
pywraps/py_idaapi.py
|
copy_bits
|
diamondo25/src
| 2 |
python
|
def copy_bits(v, s, e=(- 1)):
'\n Copy bits from a value\n @param v: the value\n @param s: starting bit (0-based)\n @param e: ending bit\n '
if (e == (- 1)):
e = s
if (s > e):
(e, s) = (s, e)
mask = (~ (((1 << ((e - s) + 1)) - 1) << s))
return ((v & mask) >> s)
|
def copy_bits(v, s, e=(- 1)):
'\n Copy bits from a value\n @param v: the value\n @param s: starting bit (0-based)\n @param e: ending bit\n '
if (e == (- 1)):
e = s
if (s > e):
(e, s) = (s, e)
mask = (~ (((1 << ((e - s) + 1)) - 1) << s))
return ((v & mask) >> s)<|docstring|>Copy bits from a value
@param v: the value
@param s: starting bit (0-based)
@param e: ending bit<|endoftext|>
|
55ce6278a184609e1542b877c69b0baa8e94e8b5e09135797928e9769499410f
|
def struct_unpack(buffer, signed=False, offs=0):
"\n Unpack a buffer given its length and offset using struct.unpack_from().\n This function will know how to unpack the given buffer by using the lookup table '__struct_unpack_table'\n If the buffer is of unknown length then None is returned. Otherwise the unpacked value is returned.\n "
n = len(buffer)
if (n not in __struct_unpack_table):
return None
signed = (1 if signed else 0)
return struct.unpack_from(__struct_unpack_table[n][signed], buffer, offs)[0]
|
Unpack a buffer given its length and offset using struct.unpack_from().
This function will know how to unpack the given buffer by using the lookup table '__struct_unpack_table'
If the buffer is of unknown length then None is returned. Otherwise the unpacked value is returned.
|
pywraps/py_idaapi.py
|
struct_unpack
|
diamondo25/src
| 2 |
python
|
def struct_unpack(buffer, signed=False, offs=0):
"\n Unpack a buffer given its length and offset using struct.unpack_from().\n This function will know how to unpack the given buffer by using the lookup table '__struct_unpack_table'\n If the buffer is of unknown length then None is returned. Otherwise the unpacked value is returned.\n "
n = len(buffer)
if (n not in __struct_unpack_table):
return None
signed = (1 if signed else 0)
return struct.unpack_from(__struct_unpack_table[n][signed], buffer, offs)[0]
|
def struct_unpack(buffer, signed=False, offs=0):
"\n Unpack a buffer given its length and offset using struct.unpack_from().\n This function will know how to unpack the given buffer by using the lookup table '__struct_unpack_table'\n If the buffer is of unknown length then None is returned. Otherwise the unpacked value is returned.\n "
n = len(buffer)
if (n not in __struct_unpack_table):
return None
signed = (1 if signed else 0)
return struct.unpack_from(__struct_unpack_table[n][signed], buffer, offs)[0]<|docstring|>Unpack a buffer given its length and offset using struct.unpack_from().
This function will know how to unpack the given buffer by using the lookup table '__struct_unpack_table'
If the buffer is of unknown length then None is returned. Otherwise the unpacked value is returned.<|endoftext|>
|
d674e4b145772084fa59b8f57049bbe83d2e4493bbf624a1199e4df8a17127cb
|
def IDAPython_ExecSystem(cmd):
'\n Executes a command with popen().\n '
try:
cmd = _utf8_native(cmd)
f = os.popen(cmd, 'r')
s = ''.join(f.readlines())
f.close()
return s
except Exception as e:
return ('%s\n%s' % (str(e), traceback.format_exc()))
|
Executes a command with popen().
|
pywraps/py_idaapi.py
|
IDAPython_ExecSystem
|
diamondo25/src
| 2 |
python
|
def IDAPython_ExecSystem(cmd):
'\n \n '
try:
cmd = _utf8_native(cmd)
f = os.popen(cmd, 'r')
s = .join(f.readlines())
f.close()
return s
except Exception as e:
return ('%s\n%s' % (str(e), traceback.format_exc()))
|
def IDAPython_ExecSystem(cmd):
'\n \n '
try:
cmd = _utf8_native(cmd)
f = os.popen(cmd, 'r')
s = .join(f.readlines())
f.close()
return s
except Exception as e:
return ('%s\n%s' % (str(e), traceback.format_exc()))<|docstring|>Executes a command with popen().<|endoftext|>
|
bfe580724ccca85005e16b3a47706895bc3bfed973fc61b691920d3827314244
|
def IDAPython_FormatExc(etype, value, tb, limit=None):
'\n This function is used to format an exception given the\n values returned by a PyErr_Fetch()\n '
try:
return ''.join(traceback.format_exception(etype, value, tb, limit))
except:
return str(value)
|
This function is used to format an exception given the
values returned by a PyErr_Fetch()
|
pywraps/py_idaapi.py
|
IDAPython_FormatExc
|
diamondo25/src
| 2 |
python
|
def IDAPython_FormatExc(etype, value, tb, limit=None):
'\n This function is used to format an exception given the\n values returned by a PyErr_Fetch()\n '
try:
return .join(traceback.format_exception(etype, value, tb, limit))
except:
return str(value)
|
def IDAPython_FormatExc(etype, value, tb, limit=None):
'\n This function is used to format an exception given the\n values returned by a PyErr_Fetch()\n '
try:
return .join(traceback.format_exception(etype, value, tb, limit))
except:
return str(value)<|docstring|>This function is used to format an exception given the
values returned by a PyErr_Fetch()<|endoftext|>
|
8d446adb7ad278dc0c0d03ef7a455028ea3728f55e9939a1556c3bf5f7eaa3c8
|
def IDAPython_ExecScript(script, g, print_error=True):
'\n Run the specified script.\n It also addresses http://code.google.com/p/idapython/issues/detail?id=42\n\n This function is used by the low-level plugin code.\n '
script = _utf8_native(script)
scriptpath = os.path.dirname(script)
if (len(scriptpath) and (scriptpath not in sys.path)):
sys.path.append(scriptpath)
argv = sys.argv
sys.argv = [script]
old__file__ = (g['__file__'] if ('__file__' in g) else '')
g['__file__'] = script
try:
execfile(script, g)
PY_COMPILE_ERR = None
except Exception as e:
PY_COMPILE_ERR = ('%s\n%s' % (str(e), traceback.format_exc()))
if print_error:
print(PY_COMPILE_ERR)
finally:
g['__file__'] = old__file__
sys.argv = argv
return PY_COMPILE_ERR
|
Run the specified script.
It also addresses http://code.google.com/p/idapython/issues/detail?id=42
This function is used by the low-level plugin code.
|
pywraps/py_idaapi.py
|
IDAPython_ExecScript
|
diamondo25/src
| 2 |
python
|
def IDAPython_ExecScript(script, g, print_error=True):
'\n Run the specified script.\n It also addresses http://code.google.com/p/idapython/issues/detail?id=42\n\n This function is used by the low-level plugin code.\n '
script = _utf8_native(script)
scriptpath = os.path.dirname(script)
if (len(scriptpath) and (scriptpath not in sys.path)):
sys.path.append(scriptpath)
argv = sys.argv
sys.argv = [script]
old__file__ = (g['__file__'] if ('__file__' in g) else )
g['__file__'] = script
try:
execfile(script, g)
PY_COMPILE_ERR = None
except Exception as e:
PY_COMPILE_ERR = ('%s\n%s' % (str(e), traceback.format_exc()))
if print_error:
print(PY_COMPILE_ERR)
finally:
g['__file__'] = old__file__
sys.argv = argv
return PY_COMPILE_ERR
|
def IDAPython_ExecScript(script, g, print_error=True):
'\n Run the specified script.\n It also addresses http://code.google.com/p/idapython/issues/detail?id=42\n\n This function is used by the low-level plugin code.\n '
script = _utf8_native(script)
scriptpath = os.path.dirname(script)
if (len(scriptpath) and (scriptpath not in sys.path)):
sys.path.append(scriptpath)
argv = sys.argv
sys.argv = [script]
old__file__ = (g['__file__'] if ('__file__' in g) else )
g['__file__'] = script
try:
execfile(script, g)
PY_COMPILE_ERR = None
except Exception as e:
PY_COMPILE_ERR = ('%s\n%s' % (str(e), traceback.format_exc()))
if print_error:
print(PY_COMPILE_ERR)
finally:
g['__file__'] = old__file__
sys.argv = argv
return PY_COMPILE_ERR<|docstring|>Run the specified script.
It also addresses http://code.google.com/p/idapython/issues/detail?id=42
This function is used by the low-level plugin code.<|endoftext|>
|
3dfe03dbe4f74a8621c9e95d540fe026f4d00d0bfb46ca57bf092f3514ef043e
|
def IDAPython_LoadProcMod(script, g, print_error=True):
'\n Load processor module.\n '
script = _utf8_native(script)
pname = (g['__name__'] if (g and ('__name__' in g)) else '__main__')
parent = sys.modules[pname]
(scriptpath, scriptname) = os.path.split(script)
if (len(scriptpath) and (scriptpath not in sys.path)):
sys.path.append(scriptpath)
procmod_name = os.path.splitext(scriptname)[0]
procobj = None
fp = None
try:
(fp, pathname, description) = imp.find_module(procmod_name)
procmod = imp.load_module(procmod_name, fp, pathname, description)
if parent:
setattr(parent, procmod_name, procmod)
parent_attrs = getattr(parent, '__all__', (attr for attr in dir(parent) if (not attr.startswith('_'))))
for pa in parent_attrs:
setattr(procmod, pa, getattr(parent, pa))
if getattr(procmod, 'PROCESSOR_ENTRY', None):
procobj = procmod.PROCESSOR_ENTRY()
PY_COMPILE_ERR = None
except Exception as e:
PY_COMPILE_ERR = ('%s\n%s' % (str(e), traceback.format_exc()))
if print_error:
print(PY_COMPILE_ERR)
finally:
if fp:
fp.close()
sys.path.remove(scriptpath)
return (PY_COMPILE_ERR, procobj)
|
Load processor module.
|
pywraps/py_idaapi.py
|
IDAPython_LoadProcMod
|
diamondo25/src
| 2 |
python
|
def IDAPython_LoadProcMod(script, g, print_error=True):
'\n \n '
script = _utf8_native(script)
pname = (g['__name__'] if (g and ('__name__' in g)) else '__main__')
parent = sys.modules[pname]
(scriptpath, scriptname) = os.path.split(script)
if (len(scriptpath) and (scriptpath not in sys.path)):
sys.path.append(scriptpath)
procmod_name = os.path.splitext(scriptname)[0]
procobj = None
fp = None
try:
(fp, pathname, description) = imp.find_module(procmod_name)
procmod = imp.load_module(procmod_name, fp, pathname, description)
if parent:
setattr(parent, procmod_name, procmod)
parent_attrs = getattr(parent, '__all__', (attr for attr in dir(parent) if (not attr.startswith('_'))))
for pa in parent_attrs:
setattr(procmod, pa, getattr(parent, pa))
if getattr(procmod, 'PROCESSOR_ENTRY', None):
procobj = procmod.PROCESSOR_ENTRY()
PY_COMPILE_ERR = None
except Exception as e:
PY_COMPILE_ERR = ('%s\n%s' % (str(e), traceback.format_exc()))
if print_error:
print(PY_COMPILE_ERR)
finally:
if fp:
fp.close()
sys.path.remove(scriptpath)
return (PY_COMPILE_ERR, procobj)
|
def IDAPython_LoadProcMod(script, g, print_error=True):
'\n \n '
script = _utf8_native(script)
pname = (g['__name__'] if (g and ('__name__' in g)) else '__main__')
parent = sys.modules[pname]
(scriptpath, scriptname) = os.path.split(script)
if (len(scriptpath) and (scriptpath not in sys.path)):
sys.path.append(scriptpath)
procmod_name = os.path.splitext(scriptname)[0]
procobj = None
fp = None
try:
(fp, pathname, description) = imp.find_module(procmod_name)
procmod = imp.load_module(procmod_name, fp, pathname, description)
if parent:
setattr(parent, procmod_name, procmod)
parent_attrs = getattr(parent, '__all__', (attr for attr in dir(parent) if (not attr.startswith('_'))))
for pa in parent_attrs:
setattr(procmod, pa, getattr(parent, pa))
if getattr(procmod, 'PROCESSOR_ENTRY', None):
procobj = procmod.PROCESSOR_ENTRY()
PY_COMPILE_ERR = None
except Exception as e:
PY_COMPILE_ERR = ('%s\n%s' % (str(e), traceback.format_exc()))
if print_error:
print(PY_COMPILE_ERR)
finally:
if fp:
fp.close()
sys.path.remove(scriptpath)
return (PY_COMPILE_ERR, procobj)<|docstring|>Load processor module.<|endoftext|>
|
28ccbb17fe810e7d5738071234c830af719fb118aa7ae7aeab1412765a6f36b2
|
def IDAPython_UnLoadProcMod(script, g, print_error=True):
'\n Unload processor module.\n '
script = _utf8_native(script)
pname = (g['__name__'] if (g and ('__name__' in g)) else '__main__')
parent = sys.modules[pname]
scriptname = os.path.split(script)[1]
procmod_name = os.path.splitext(scriptname)[0]
if getattr(parent, procmod_name, None):
delattr(parent, procmod_name)
del sys.modules[procmod_name]
PY_COMPILE_ERR = None
return PY_COMPILE_ERR
|
Unload processor module.
|
pywraps/py_idaapi.py
|
IDAPython_UnLoadProcMod
|
diamondo25/src
| 2 |
python
|
def IDAPython_UnLoadProcMod(script, g, print_error=True):
'\n \n '
script = _utf8_native(script)
pname = (g['__name__'] if (g and ('__name__' in g)) else '__main__')
parent = sys.modules[pname]
scriptname = os.path.split(script)[1]
procmod_name = os.path.splitext(scriptname)[0]
if getattr(parent, procmod_name, None):
delattr(parent, procmod_name)
del sys.modules[procmod_name]
PY_COMPILE_ERR = None
return PY_COMPILE_ERR
|
def IDAPython_UnLoadProcMod(script, g, print_error=True):
'\n \n '
script = _utf8_native(script)
pname = (g['__name__'] if (g and ('__name__' in g)) else '__main__')
parent = sys.modules[pname]
scriptname = os.path.split(script)[1]
procmod_name = os.path.splitext(scriptname)[0]
if getattr(parent, procmod_name, None):
delattr(parent, procmod_name)
del sys.modules[procmod_name]
PY_COMPILE_ERR = None
return PY_COMPILE_ERR<|docstring|>Unload processor module.<|endoftext|>
|
c15cc339218c0715001c09d61208a0d946cb92488a3a8051d3fda323c3eec2b9
|
def __del__(self):
'Delete the link upon object destruction (only if not static)'
self._free()
|
Delete the link upon object destruction (only if not static)
|
pywraps/py_idaapi.py
|
__del__
|
diamondo25/src
| 2 |
python
|
def __del__(self):
self._free()
|
def __del__(self):
self._free()<|docstring|>Delete the link upon object destruction (only if not static)<|endoftext|>
|
8c0430d31db4dfe8f2e673c2c5a2d1bdc90443378529cbf157193fc16e1f1897
|
def _free(self):
'Explicitly delete the link (only if not static)'
if ((not self.__static_clink__) and (self.__clink__ is not None)):
self._del_clink(self.__clink__)
self.__clink__ = None
|
Explicitly delete the link (only if not static)
|
pywraps/py_idaapi.py
|
_free
|
diamondo25/src
| 2 |
python
|
def _free(self):
if ((not self.__static_clink__) and (self.__clink__ is not None)):
self._del_clink(self.__clink__)
self.__clink__ = None
|
def _free(self):
if ((not self.__static_clink__) and (self.__clink__ is not None)):
self._del_clink(self.__clink__)
self.__clink__ = None<|docstring|>Explicitly delete the link (only if not static)<|endoftext|>
|
241c6a899853c8498c3e5d66ad856f8546408bb5bd1c0fc07ead6a714be7df68
|
def copy(self):
'Returns a new copy of this class'
inst = self.__class__()
inst.assign(self)
return inst
|
Returns a new copy of this class
|
pywraps/py_idaapi.py
|
copy
|
diamondo25/src
| 2 |
python
|
def copy(self):
inst = self.__class__()
inst.assign(self)
return inst
|
def copy(self):
inst = self.__class__()
inst.assign(self)
return inst<|docstring|>Returns a new copy of this class<|endoftext|>
|
973ed44551e3917065fab51ab5bc04badac1bae973075e50c5af8f0a6208bc77
|
def _create_clink(self):
'\n Overwrite me.\n Creates a new clink\n @return: PyCObject representing the C link\n '
pass
|
Overwrite me.
Creates a new clink
@return: PyCObject representing the C link
|
pywraps/py_idaapi.py
|
_create_clink
|
diamondo25/src
| 2 |
python
|
def _create_clink(self):
'\n Overwrite me.\n Creates a new clink\n @return: PyCObject representing the C link\n '
pass
|
def _create_clink(self):
'\n Overwrite me.\n Creates a new clink\n @return: PyCObject representing the C link\n '
pass<|docstring|>Overwrite me.
Creates a new clink
@return: PyCObject representing the C link<|endoftext|>
|
30ca0c44d7aa729ab1ed7fdd45011500352daffa3e0e942e6d486366cce1e4a6
|
def _del_clink(self, lnk):
'\n Overwrite me.\n This method deletes the link\n '
pass
|
Overwrite me.
This method deletes the link
|
pywraps/py_idaapi.py
|
_del_clink
|
diamondo25/src
| 2 |
python
|
def _del_clink(self, lnk):
'\n Overwrite me.\n This method deletes the link\n '
pass
|
def _del_clink(self, lnk):
'\n Overwrite me.\n This method deletes the link\n '
pass<|docstring|>Overwrite me.
This method deletes the link<|endoftext|>
|
ecff10e13343752c8e15f72ee9f6773144574061442294289e694e169e1adf23
|
def _get_clink_ptr(self):
'\n Overwrite me.\n Returns the C link pointer as a 64bit number\n '
pass
|
Overwrite me.
Returns the C link pointer as a 64bit number
|
pywraps/py_idaapi.py
|
_get_clink_ptr
|
diamondo25/src
| 2 |
python
|
def _get_clink_ptr(self):
'\n Overwrite me.\n Returns the C link pointer as a 64bit number\n '
pass
|
def _get_clink_ptr(self):
'\n Overwrite me.\n Returns the C link pointer as a 64bit number\n '
pass<|docstring|>Overwrite me.
Returns the C link pointer as a 64bit number<|endoftext|>
|
e74863946db3403c1c549e2ae2ec3b0817f3721efa58fd4b69e0c005632a0831
|
def assign(self, other):
'\n Overwrite me.\n This method allows you to assign an instance contents to anothers\n @return: Boolean\n '
pass
|
Overwrite me.
This method allows you to assign an instance contents to anothers
@return: Boolean
|
pywraps/py_idaapi.py
|
assign
|
diamondo25/src
| 2 |
python
|
def assign(self, other):
'\n Overwrite me.\n This method allows you to assign an instance contents to anothers\n @return: Boolean\n '
pass
|
def assign(self, other):
'\n Overwrite me.\n This method allows you to assign an instance contents to anothers\n @return: Boolean\n '
pass<|docstring|>Overwrite me.
This method allows you to assign an instance contents to anothers
@return: Boolean<|endoftext|>
|
7897545e3ad17602fe11830ac1caf40753801fb8e4010801803017c5b6f04cdc
|
def __getitem__(self, idx):
'Allow access to object attributes by index (like dictionaries)'
return getattr(self, idx)
|
Allow access to object attributes by index (like dictionaries)
|
pywraps/py_idaapi.py
|
__getitem__
|
diamondo25/src
| 2 |
python
|
def __getitem__(self, idx):
return getattr(self, idx)
|
def __getitem__(self, idx):
return getattr(self, idx)<|docstring|>Allow access to object attributes by index (like dictionaries)<|endoftext|>
|
3375f14742e298fb62978815cd4950e2384322b1957e0ddc62e2124bc9f81236
|
def cstr(self):
'Returns the string as a C string (up to the zero termination)'
return as_cstr(self.value)
|
Returns the string as a C string (up to the zero termination)
|
pywraps/py_idaapi.py
|
cstr
|
diamondo25/src
| 2 |
python
|
def cstr(self):
return as_cstr(self.value)
|
def cstr(self):
return as_cstr(self.value)<|docstring|>Returns the string as a C string (up to the zero termination)<|endoftext|>
|
a19f766f5e846d3f1a9559ca44e0acd8b8fd26fe1595604e457aefc502b85e4e
|
def accuracy(model, questions, lowercase=True, restrict_vocab=30000):
'\n Compute accuracy of the model. `questions` is a filename where lines are\n 4-tuples of words, split into sections by ": SECTION NAME" lines.\n See https://code.google.com/p/word2vec/source/browse/trunk/questions-words.txt for an example.\n\n The accuracy is reported (=printed to log and returned as a list) for each\n section separately, plus there\'s one aggregate summary at the end.\n\n Use `restrict_vocab` to ignore all questions containing a word whose frequency\n is not in the top-N most frequent words (default top 30,000).\n\n This method corresponds to the `compute-accuracy` script of the original C word2vec.\n\n '
ok_vocab = dict(sorted(model.wv.vocab.items(), key=(lambda item: (- item[1].count)))[:restrict_vocab])
ok_index = set((v.index for v in ok_vocab.values()))
def log_accuracy(section):
(correct, incorrect) = (section['correct'], section['incorrect'])
if ((correct + incorrect) > 0):
print(('%s: %.1f%% (%i/%i)' % (section['section'], ((100.0 * correct) / (correct + incorrect)), correct, (correct + incorrect))))
(sections, section) = ([], None)
for (line_no, line) in enumerate(open(questions)):
if line.startswith(': '):
if section:
sections.append(section)
log_accuracy(section)
section = {'section': line.lstrip(': ').strip(), 'correct': 0, 'incorrect': 0}
else:
if (not section):
raise ValueError(('missing section header before line #%i in %s' % (line_no, questions)))
try:
if lowercase:
(a, b, c, expected) = [word.lower() for word in line.split()]
else:
(a, b, c, expected) = [word for word in line.split()]
except:
print(('skipping invalid line #%i in %s' % (line_no, questions)))
if ((a not in ok_vocab) or (b not in ok_vocab) or (c not in ok_vocab) or (expected not in ok_vocab)):
continue
ignore = set((model.wv.vocab[v].index for v in [a, b, c]))
predicted = None
for index in np.argsort(analogy(model, a, b, c))[::(- 1)]:
if ((index in ok_index) and (index not in ignore)):
predicted = model.wv.index2word[index]
break
section[('correct' if (predicted == expected) else 'incorrect')] += 1
if section:
sections.append(section)
log_accuracy(section)
total = {'section': 'total', 'correct': sum((s['correct'] for s in sections)), 'incorrect': sum((s['incorrect'] for s in sections))}
log_accuracy(total)
sections.append(total)
return sections
|
Compute accuracy of the model. `questions` is a filename where lines are
4-tuples of words, split into sections by ": SECTION NAME" lines.
See https://code.google.com/p/word2vec/source/browse/trunk/questions-words.txt for an example.
The accuracy is reported (=printed to log and returned as a list) for each
section separately, plus there's one aggregate summary at the end.
Use `restrict_vocab` to ignore all questions containing a word whose frequency
is not in the top-N most frequent words (default top 30,000).
This method corresponds to the `compute-accuracy` script of the original C word2vec.
|
examples/test_analogy.py
|
accuracy
|
cod3licious/conec
| 23 |
python
|
def accuracy(model, questions, lowercase=True, restrict_vocab=30000):
'\n Compute accuracy of the model. `questions` is a filename where lines are\n 4-tuples of words, split into sections by ": SECTION NAME" lines.\n See https://code.google.com/p/word2vec/source/browse/trunk/questions-words.txt for an example.\n\n The accuracy is reported (=printed to log and returned as a list) for each\n section separately, plus there\'s one aggregate summary at the end.\n\n Use `restrict_vocab` to ignore all questions containing a word whose frequency\n is not in the top-N most frequent words (default top 30,000).\n\n This method corresponds to the `compute-accuracy` script of the original C word2vec.\n\n '
ok_vocab = dict(sorted(model.wv.vocab.items(), key=(lambda item: (- item[1].count)))[:restrict_vocab])
ok_index = set((v.index for v in ok_vocab.values()))
def log_accuracy(section):
(correct, incorrect) = (section['correct'], section['incorrect'])
if ((correct + incorrect) > 0):
print(('%s: %.1f%% (%i/%i)' % (section['section'], ((100.0 * correct) / (correct + incorrect)), correct, (correct + incorrect))))
(sections, section) = ([], None)
for (line_no, line) in enumerate(open(questions)):
if line.startswith(': '):
if section:
sections.append(section)
log_accuracy(section)
section = {'section': line.lstrip(': ').strip(), 'correct': 0, 'incorrect': 0}
else:
if (not section):
raise ValueError(('missing section header before line #%i in %s' % (line_no, questions)))
try:
if lowercase:
(a, b, c, expected) = [word.lower() for word in line.split()]
else:
(a, b, c, expected) = [word for word in line.split()]
except:
print(('skipping invalid line #%i in %s' % (line_no, questions)))
if ((a not in ok_vocab) or (b not in ok_vocab) or (c not in ok_vocab) or (expected not in ok_vocab)):
continue
ignore = set((model.wv.vocab[v].index for v in [a, b, c]))
predicted = None
for index in np.argsort(analogy(model, a, b, c))[::(- 1)]:
if ((index in ok_index) and (index not in ignore)):
predicted = model.wv.index2word[index]
break
section[('correct' if (predicted == expected) else 'incorrect')] += 1
if section:
sections.append(section)
log_accuracy(section)
total = {'section': 'total', 'correct': sum((s['correct'] for s in sections)), 'incorrect': sum((s['incorrect'] for s in sections))}
log_accuracy(total)
sections.append(total)
return sections
|
def accuracy(model, questions, lowercase=True, restrict_vocab=30000):
'\n Compute accuracy of the model. `questions` is a filename where lines are\n 4-tuples of words, split into sections by ": SECTION NAME" lines.\n See https://code.google.com/p/word2vec/source/browse/trunk/questions-words.txt for an example.\n\n The accuracy is reported (=printed to log and returned as a list) for each\n section separately, plus there\'s one aggregate summary at the end.\n\n Use `restrict_vocab` to ignore all questions containing a word whose frequency\n is not in the top-N most frequent words (default top 30,000).\n\n This method corresponds to the `compute-accuracy` script of the original C word2vec.\n\n '
ok_vocab = dict(sorted(model.wv.vocab.items(), key=(lambda item: (- item[1].count)))[:restrict_vocab])
ok_index = set((v.index for v in ok_vocab.values()))
def log_accuracy(section):
(correct, incorrect) = (section['correct'], section['incorrect'])
if ((correct + incorrect) > 0):
print(('%s: %.1f%% (%i/%i)' % (section['section'], ((100.0 * correct) / (correct + incorrect)), correct, (correct + incorrect))))
(sections, section) = ([], None)
for (line_no, line) in enumerate(open(questions)):
if line.startswith(': '):
if section:
sections.append(section)
log_accuracy(section)
section = {'section': line.lstrip(': ').strip(), 'correct': 0, 'incorrect': 0}
else:
if (not section):
raise ValueError(('missing section header before line #%i in %s' % (line_no, questions)))
try:
if lowercase:
(a, b, c, expected) = [word.lower() for word in line.split()]
else:
(a, b, c, expected) = [word for word in line.split()]
except:
print(('skipping invalid line #%i in %s' % (line_no, questions)))
if ((a not in ok_vocab) or (b not in ok_vocab) or (c not in ok_vocab) or (expected not in ok_vocab)):
continue
ignore = set((model.wv.vocab[v].index for v in [a, b, c]))
predicted = None
for index in np.argsort(analogy(model, a, b, c))[::(- 1)]:
if ((index in ok_index) and (index not in ignore)):
predicted = model.wv.index2word[index]
break
section[('correct' if (predicted == expected) else 'incorrect')] += 1
if section:
sections.append(section)
log_accuracy(section)
total = {'section': 'total', 'correct': sum((s['correct'] for s in sections)), 'incorrect': sum((s['incorrect'] for s in sections))}
log_accuracy(total)
sections.append(total)
return sections<|docstring|>Compute accuracy of the model. `questions` is a filename where lines are
4-tuples of words, split into sections by ": SECTION NAME" lines.
See https://code.google.com/p/word2vec/source/browse/trunk/questions-words.txt for an example.
The accuracy is reported (=printed to log and returned as a list) for each
section separately, plus there's one aggregate summary at the end.
Use `restrict_vocab` to ignore all questions containing a word whose frequency
is not in the top-N most frequent words (default top 30,000).
This method corresponds to the `compute-accuracy` script of the original C word2vec.<|endoftext|>
|
a329f70d10cfdd1fcfdf2c92ca87b03e75d72ee931e50a480ff27c68c15e9c49
|
def init_ui(self, posterize):
'\n Create user interface for :class:`posterize.Posterize`.\n\n The method creates the widget objects in the proper containers\n and assigns the object names to them.\n\n :param posterize: The dialog posterize window\n :type posterize: :class:`posterize.Posterize`\n '
self.operation_ui(self)
posterize.setObjectName('posterize')
icon = QIcon()
icon.addPixmap(QPixmap('icons/posterize.png'), QIcon.Normal, QIcon.Off)
posterize.setWindowIcon(icon)
self.label_bins_num = QLabel(posterize)
self.label_bins_num.setObjectName('label_bins_num')
self.label_bins_num.setAlignment(Qt.AlignCenter)
self.bins_slider = QSlider(posterize)
self.bins_slider.setOrientation(Qt.Horizontal)
self.bins_slider.setPageStep(0)
self.bins_slider.setObjectName('bins_slider')
self.layout.addWidget(self.label_bins_num)
self.layout.addWidget(self.bins_slider)
self.layout.addWidget(self.show_hist_widget)
self.layout.addWidget(self.preview_widget)
self.layout.addWidget(self.button_box)
posterize.setLayout(self.layout)
QMetaObject.connectSlotsByName(posterize)
|
Create user interface for :class:`posterize.Posterize`.
The method creates the widget objects in the proper containers
and assigns the object names to them.
:param posterize: The dialog posterize window
:type posterize: :class:`posterize.Posterize`
|
src/operations/point/posterize_ui.py
|
init_ui
|
vmariiechko/python-image-processing
| 0 |
python
|
def init_ui(self, posterize):
'\n Create user interface for :class:`posterize.Posterize`.\n\n The method creates the widget objects in the proper containers\n and assigns the object names to them.\n\n :param posterize: The dialog posterize window\n :type posterize: :class:`posterize.Posterize`\n '
self.operation_ui(self)
posterize.setObjectName('posterize')
icon = QIcon()
icon.addPixmap(QPixmap('icons/posterize.png'), QIcon.Normal, QIcon.Off)
posterize.setWindowIcon(icon)
self.label_bins_num = QLabel(posterize)
self.label_bins_num.setObjectName('label_bins_num')
self.label_bins_num.setAlignment(Qt.AlignCenter)
self.bins_slider = QSlider(posterize)
self.bins_slider.setOrientation(Qt.Horizontal)
self.bins_slider.setPageStep(0)
self.bins_slider.setObjectName('bins_slider')
self.layout.addWidget(self.label_bins_num)
self.layout.addWidget(self.bins_slider)
self.layout.addWidget(self.show_hist_widget)
self.layout.addWidget(self.preview_widget)
self.layout.addWidget(self.button_box)
posterize.setLayout(self.layout)
QMetaObject.connectSlotsByName(posterize)
|
def init_ui(self, posterize):
'\n Create user interface for :class:`posterize.Posterize`.\n\n The method creates the widget objects in the proper containers\n and assigns the object names to them.\n\n :param posterize: The dialog posterize window\n :type posterize: :class:`posterize.Posterize`\n '
self.operation_ui(self)
posterize.setObjectName('posterize')
icon = QIcon()
icon.addPixmap(QPixmap('icons/posterize.png'), QIcon.Normal, QIcon.Off)
posterize.setWindowIcon(icon)
self.label_bins_num = QLabel(posterize)
self.label_bins_num.setObjectName('label_bins_num')
self.label_bins_num.setAlignment(Qt.AlignCenter)
self.bins_slider = QSlider(posterize)
self.bins_slider.setOrientation(Qt.Horizontal)
self.bins_slider.setPageStep(0)
self.bins_slider.setObjectName('bins_slider')
self.layout.addWidget(self.label_bins_num)
self.layout.addWidget(self.bins_slider)
self.layout.addWidget(self.show_hist_widget)
self.layout.addWidget(self.preview_widget)
self.layout.addWidget(self.button_box)
posterize.setLayout(self.layout)
QMetaObject.connectSlotsByName(posterize)<|docstring|>Create user interface for :class:`posterize.Posterize`.
The method creates the widget objects in the proper containers
and assigns the object names to them.
:param posterize: The dialog posterize window
:type posterize: :class:`posterize.Posterize`<|endoftext|>
|
83f60e670b502b3a98997e9e4455a3c64386da5be9d1af2336b4e08ee9b92eeb
|
def expand(self, action_priors):
'Expand tree by creating new children.\n action_priors: a list of tuples of actions and their prior probability\n according to the policy function.\n '
for (action, prob) in action_priors:
if (action not in self._children):
self._children[action] = TreeNode(self, prob)
|
Expand tree by creating new children.
action_priors: a list of tuples of actions and their prior probability
according to the policy function.
|
mcts_alphaZero.py
|
expand
|
quietsmile/AlphaZero_Gomoku
| 2,876 |
python
|
def expand(self, action_priors):
'Expand tree by creating new children.\n action_priors: a list of tuples of actions and their prior probability\n according to the policy function.\n '
for (action, prob) in action_priors:
if (action not in self._children):
self._children[action] = TreeNode(self, prob)
|
def expand(self, action_priors):
'Expand tree by creating new children.\n action_priors: a list of tuples of actions and their prior probability\n according to the policy function.\n '
for (action, prob) in action_priors:
if (action not in self._children):
self._children[action] = TreeNode(self, prob)<|docstring|>Expand tree by creating new children.
action_priors: a list of tuples of actions and their prior probability
according to the policy function.<|endoftext|>
|
5a30224b39866d70ec2a701ebbd517eb279d972d2d3ff2fcd5e69590a45262a5
|
def select(self, c_puct):
'Select action among children that gives maximum action value Q\n plus bonus u(P).\n Return: A tuple of (action, next_node)\n '
return max(self._children.items(), key=(lambda act_node: act_node[1].get_value(c_puct)))
|
Select action among children that gives maximum action value Q
plus bonus u(P).
Return: A tuple of (action, next_node)
|
mcts_alphaZero.py
|
select
|
quietsmile/AlphaZero_Gomoku
| 2,876 |
python
|
def select(self, c_puct):
'Select action among children that gives maximum action value Q\n plus bonus u(P).\n Return: A tuple of (action, next_node)\n '
return max(self._children.items(), key=(lambda act_node: act_node[1].get_value(c_puct)))
|
def select(self, c_puct):
'Select action among children that gives maximum action value Q\n plus bonus u(P).\n Return: A tuple of (action, next_node)\n '
return max(self._children.items(), key=(lambda act_node: act_node[1].get_value(c_puct)))<|docstring|>Select action among children that gives maximum action value Q
plus bonus u(P).
Return: A tuple of (action, next_node)<|endoftext|>
|
e386850f568b732bc7f512af109f714db75c302989a9259e19c2e49aba09ec3c
|
def update(self, leaf_value):
"Update node values from leaf evaluation.\n leaf_value: the value of subtree evaluation from the current player's\n perspective.\n "
self._n_visits += 1
self._Q += ((1.0 * (leaf_value - self._Q)) / self._n_visits)
|
Update node values from leaf evaluation.
leaf_value: the value of subtree evaluation from the current player's
perspective.
|
mcts_alphaZero.py
|
update
|
quietsmile/AlphaZero_Gomoku
| 2,876 |
python
|
def update(self, leaf_value):
"Update node values from leaf evaluation.\n leaf_value: the value of subtree evaluation from the current player's\n perspective.\n "
self._n_visits += 1
self._Q += ((1.0 * (leaf_value - self._Q)) / self._n_visits)
|
def update(self, leaf_value):
"Update node values from leaf evaluation.\n leaf_value: the value of subtree evaluation from the current player's\n perspective.\n "
self._n_visits += 1
self._Q += ((1.0 * (leaf_value - self._Q)) / self._n_visits)<|docstring|>Update node values from leaf evaluation.
leaf_value: the value of subtree evaluation from the current player's
perspective.<|endoftext|>
|
181b778f31a1d04f414398b63d7f675de04299d2863026f390ab61ddccbbfcfb
|
def update_recursive(self, leaf_value):
'Like a call to update(), but applied recursively for all ancestors.\n '
if self._parent:
self._parent.update_recursive((- leaf_value))
self.update(leaf_value)
|
Like a call to update(), but applied recursively for all ancestors.
|
mcts_alphaZero.py
|
update_recursive
|
quietsmile/AlphaZero_Gomoku
| 2,876 |
python
|
def update_recursive(self, leaf_value):
'\n '
if self._parent:
self._parent.update_recursive((- leaf_value))
self.update(leaf_value)
|
def update_recursive(self, leaf_value):
'\n '
if self._parent:
self._parent.update_recursive((- leaf_value))
self.update(leaf_value)<|docstring|>Like a call to update(), but applied recursively for all ancestors.<|endoftext|>
|
e5086e940ef4161c69b8182e12716aa005d736e05f8b9dd57ac23b3f6aa84bfa
|
def get_value(self, c_puct):
"Calculate and return the value for this node.\n It is a combination of leaf evaluations Q, and this node's prior\n adjusted for its visit count, u.\n c_puct: a number in (0, inf) controlling the relative impact of\n value Q, and prior probability P, on this node's score.\n "
self._u = (((c_puct * self._P) * np.sqrt(self._parent._n_visits)) / (1 + self._n_visits))
return (self._Q + self._u)
|
Calculate and return the value for this node.
It is a combination of leaf evaluations Q, and this node's prior
adjusted for its visit count, u.
c_puct: a number in (0, inf) controlling the relative impact of
value Q, and prior probability P, on this node's score.
|
mcts_alphaZero.py
|
get_value
|
quietsmile/AlphaZero_Gomoku
| 2,876 |
python
|
def get_value(self, c_puct):
"Calculate and return the value for this node.\n It is a combination of leaf evaluations Q, and this node's prior\n adjusted for its visit count, u.\n c_puct: a number in (0, inf) controlling the relative impact of\n value Q, and prior probability P, on this node's score.\n "
self._u = (((c_puct * self._P) * np.sqrt(self._parent._n_visits)) / (1 + self._n_visits))
return (self._Q + self._u)
|
def get_value(self, c_puct):
"Calculate and return the value for this node.\n It is a combination of leaf evaluations Q, and this node's prior\n adjusted for its visit count, u.\n c_puct: a number in (0, inf) controlling the relative impact of\n value Q, and prior probability P, on this node's score.\n "
self._u = (((c_puct * self._P) * np.sqrt(self._parent._n_visits)) / (1 + self._n_visits))
return (self._Q + self._u)<|docstring|>Calculate and return the value for this node.
It is a combination of leaf evaluations Q, and this node's prior
adjusted for its visit count, u.
c_puct: a number in (0, inf) controlling the relative impact of
value Q, and prior probability P, on this node's score.<|endoftext|>
|
d6bb6d8093185401373633d5616a64c748667c5134c695dc543748fbc5b1a23c
|
def is_leaf(self):
'Check if leaf node (i.e. no nodes below this have been expanded).'
return (self._children == {})
|
Check if leaf node (i.e. no nodes below this have been expanded).
|
mcts_alphaZero.py
|
is_leaf
|
quietsmile/AlphaZero_Gomoku
| 2,876 |
python
|
def is_leaf(self):
return (self._children == {})
|
def is_leaf(self):
return (self._children == {})<|docstring|>Check if leaf node (i.e. no nodes below this have been expanded).<|endoftext|>
|
8e89b20e206e7ed90b8b4dbffb1e0ca05a00c3c65c3afea305029ccf062c9ebe
|
def __init__(self, policy_value_fn, c_puct=5, n_playout=10000):
"\n policy_value_fn: a function that takes in a board state and outputs\n a list of (action, probability) tuples and also a score in [-1, 1]\n (i.e. the expected value of the end game score from the current\n player's perspective) for the current player.\n c_puct: a number in (0, inf) that controls how quickly exploration\n converges to the maximum-value policy. A higher value means\n relying on the prior more.\n "
self._root = TreeNode(None, 1.0)
self._policy = policy_value_fn
self._c_puct = c_puct
self._n_playout = n_playout
|
policy_value_fn: a function that takes in a board state and outputs
a list of (action, probability) tuples and also a score in [-1, 1]
(i.e. the expected value of the end game score from the current
player's perspective) for the current player.
c_puct: a number in (0, inf) that controls how quickly exploration
converges to the maximum-value policy. A higher value means
relying on the prior more.
|
mcts_alphaZero.py
|
__init__
|
quietsmile/AlphaZero_Gomoku
| 2,876 |
python
|
def __init__(self, policy_value_fn, c_puct=5, n_playout=10000):
"\n policy_value_fn: a function that takes in a board state and outputs\n a list of (action, probability) tuples and also a score in [-1, 1]\n (i.e. the expected value of the end game score from the current\n player's perspective) for the current player.\n c_puct: a number in (0, inf) that controls how quickly exploration\n converges to the maximum-value policy. A higher value means\n relying on the prior more.\n "
self._root = TreeNode(None, 1.0)
self._policy = policy_value_fn
self._c_puct = c_puct
self._n_playout = n_playout
|
def __init__(self, policy_value_fn, c_puct=5, n_playout=10000):
"\n policy_value_fn: a function that takes in a board state and outputs\n a list of (action, probability) tuples and also a score in [-1, 1]\n (i.e. the expected value of the end game score from the current\n player's perspective) for the current player.\n c_puct: a number in (0, inf) that controls how quickly exploration\n converges to the maximum-value policy. A higher value means\n relying on the prior more.\n "
self._root = TreeNode(None, 1.0)
self._policy = policy_value_fn
self._c_puct = c_puct
self._n_playout = n_playout<|docstring|>policy_value_fn: a function that takes in a board state and outputs
a list of (action, probability) tuples and also a score in [-1, 1]
(i.e. the expected value of the end game score from the current
player's perspective) for the current player.
c_puct: a number in (0, inf) that controls how quickly exploration
converges to the maximum-value policy. A higher value means
relying on the prior more.<|endoftext|>
|
f95faa6191d72d519c9dd3f145030c649b9a3d467989b81bf8f1c3417bc338c8
|
def _playout(self, state):
'Run a single playout from the root to the leaf, getting a value at\n the leaf and propagating it back through its parents.\n State is modified in-place, so a copy must be provided.\n '
node = self._root
while 1:
if node.is_leaf():
break
(action, node) = node.select(self._c_puct)
state.do_move(action)
(action_probs, leaf_value) = self._policy(state)
(end, winner) = state.game_end()
if (not end):
node.expand(action_probs)
elif (winner == (- 1)):
leaf_value = 0.0
else:
leaf_value = (1.0 if (winner == state.get_current_player()) else (- 1.0))
node.update_recursive((- leaf_value))
|
Run a single playout from the root to the leaf, getting a value at
the leaf and propagating it back through its parents.
State is modified in-place, so a copy must be provided.
|
mcts_alphaZero.py
|
_playout
|
quietsmile/AlphaZero_Gomoku
| 2,876 |
python
|
def _playout(self, state):
'Run a single playout from the root to the leaf, getting a value at\n the leaf and propagating it back through its parents.\n State is modified in-place, so a copy must be provided.\n '
node = self._root
while 1:
if node.is_leaf():
break
(action, node) = node.select(self._c_puct)
state.do_move(action)
(action_probs, leaf_value) = self._policy(state)
(end, winner) = state.game_end()
if (not end):
node.expand(action_probs)
elif (winner == (- 1)):
leaf_value = 0.0
else:
leaf_value = (1.0 if (winner == state.get_current_player()) else (- 1.0))
node.update_recursive((- leaf_value))
|
def _playout(self, state):
'Run a single playout from the root to the leaf, getting a value at\n the leaf and propagating it back through its parents.\n State is modified in-place, so a copy must be provided.\n '
node = self._root
while 1:
if node.is_leaf():
break
(action, node) = node.select(self._c_puct)
state.do_move(action)
(action_probs, leaf_value) = self._policy(state)
(end, winner) = state.game_end()
if (not end):
node.expand(action_probs)
elif (winner == (- 1)):
leaf_value = 0.0
else:
leaf_value = (1.0 if (winner == state.get_current_player()) else (- 1.0))
node.update_recursive((- leaf_value))<|docstring|>Run a single playout from the root to the leaf, getting a value at
the leaf and propagating it back through its parents.
State is modified in-place, so a copy must be provided.<|endoftext|>
|
19fc78f59089dddcd8325840db2443fea2cb52c84df5c66b9526399cc575cf0b
|
def get_move_probs(self, state, temp=0.001):
'Run all playouts sequentially and return the available actions and\n their corresponding probabilities.\n state: the current game state\n temp: temperature parameter in (0, 1] controls the level of exploration\n '
for n in range(self._n_playout):
state_copy = copy.deepcopy(state)
self._playout(state_copy)
act_visits = [(act, node._n_visits) for (act, node) in self._root._children.items()]
(acts, visits) = zip(*act_visits)
act_probs = softmax(((1.0 / temp) * np.log((np.array(visits) + 1e-10))))
return (acts, act_probs)
|
Run all playouts sequentially and return the available actions and
their corresponding probabilities.
state: the current game state
temp: temperature parameter in (0, 1] controls the level of exploration
|
mcts_alphaZero.py
|
get_move_probs
|
quietsmile/AlphaZero_Gomoku
| 2,876 |
python
|
def get_move_probs(self, state, temp=0.001):
'Run all playouts sequentially and return the available actions and\n their corresponding probabilities.\n state: the current game state\n temp: temperature parameter in (0, 1] controls the level of exploration\n '
for n in range(self._n_playout):
state_copy = copy.deepcopy(state)
self._playout(state_copy)
act_visits = [(act, node._n_visits) for (act, node) in self._root._children.items()]
(acts, visits) = zip(*act_visits)
act_probs = softmax(((1.0 / temp) * np.log((np.array(visits) + 1e-10))))
return (acts, act_probs)
|
def get_move_probs(self, state, temp=0.001):
'Run all playouts sequentially and return the available actions and\n their corresponding probabilities.\n state: the current game state\n temp: temperature parameter in (0, 1] controls the level of exploration\n '
for n in range(self._n_playout):
state_copy = copy.deepcopy(state)
self._playout(state_copy)
act_visits = [(act, node._n_visits) for (act, node) in self._root._children.items()]
(acts, visits) = zip(*act_visits)
act_probs = softmax(((1.0 / temp) * np.log((np.array(visits) + 1e-10))))
return (acts, act_probs)<|docstring|>Run all playouts sequentially and return the available actions and
their corresponding probabilities.
state: the current game state
temp: temperature parameter in (0, 1] controls the level of exploration<|endoftext|>
|
c4786e0852cb71a204030345a17655f8c27702ec4f4bd7074c07f85b130adef3
|
def update_with_move(self, last_move):
'Step forward in the tree, keeping everything we already know\n about the subtree.\n '
if (last_move in self._root._children):
self._root = self._root._children[last_move]
self._root._parent = None
else:
self._root = TreeNode(None, 1.0)
|
Step forward in the tree, keeping everything we already know
about the subtree.
|
mcts_alphaZero.py
|
update_with_move
|
quietsmile/AlphaZero_Gomoku
| 2,876 |
python
|
def update_with_move(self, last_move):
'Step forward in the tree, keeping everything we already know\n about the subtree.\n '
if (last_move in self._root._children):
self._root = self._root._children[last_move]
self._root._parent = None
else:
self._root = TreeNode(None, 1.0)
|
def update_with_move(self, last_move):
'Step forward in the tree, keeping everything we already know\n about the subtree.\n '
if (last_move in self._root._children):
self._root = self._root._children[last_move]
self._root._parent = None
else:
self._root = TreeNode(None, 1.0)<|docstring|>Step forward in the tree, keeping everything we already know
about the subtree.<|endoftext|>
|
dcb92f2d8cd2467c2f66642315704573a1ab47f0092553a11835cb7ffada6a26
|
def coding_blk():
'Input: node dict\n Output: TensorType([1, hyper.word_dim])\n '
Wcomb1 = param.get('Wcomb1')
Wcomb2 = param.get('Wcomb2')
blk = td.Composition()
with blk.scope():
direct = embedding.direct_embed_blk().reads(blk.input)
composed = embedding.composed_embed_blk().reads(blk.input)
Wcomb1 = td.FromTensor(param.get('Wcomb1'))
Wcomb2 = td.FromTensor(param.get('Wcomb2'))
direct = td.Function(embedding.batch_mul).reads(direct, Wcomb1)
composed = td.Function(embedding.batch_mul).reads(composed, Wcomb2)
added = td.Function(tf.add).reads(direct, composed)
blk.output.reads(added)
return blk
|
Input: node dict
Output: TensorType([1, hyper.word_dim])
|
tbcnn/tbcnn.py
|
coding_blk
|
Aetf/tensorflow-tbcnn
| 34 |
python
|
def coding_blk():
'Input: node dict\n Output: TensorType([1, hyper.word_dim])\n '
Wcomb1 = param.get('Wcomb1')
Wcomb2 = param.get('Wcomb2')
blk = td.Composition()
with blk.scope():
direct = embedding.direct_embed_blk().reads(blk.input)
composed = embedding.composed_embed_blk().reads(blk.input)
Wcomb1 = td.FromTensor(param.get('Wcomb1'))
Wcomb2 = td.FromTensor(param.get('Wcomb2'))
direct = td.Function(embedding.batch_mul).reads(direct, Wcomb1)
composed = td.Function(embedding.batch_mul).reads(composed, Wcomb2)
added = td.Function(tf.add).reads(direct, composed)
blk.output.reads(added)
return blk
|
def coding_blk():
'Input: node dict\n Output: TensorType([1, hyper.word_dim])\n '
Wcomb1 = param.get('Wcomb1')
Wcomb2 = param.get('Wcomb2')
blk = td.Composition()
with blk.scope():
direct = embedding.direct_embed_blk().reads(blk.input)
composed = embedding.composed_embed_blk().reads(blk.input)
Wcomb1 = td.FromTensor(param.get('Wcomb1'))
Wcomb2 = td.FromTensor(param.get('Wcomb2'))
direct = td.Function(embedding.batch_mul).reads(direct, Wcomb1)
composed = td.Function(embedding.batch_mul).reads(composed, Wcomb2)
added = td.Function(tf.add).reads(direct, composed)
blk.output.reads(added)
return blk<|docstring|>Input: node dict
Output: TensorType([1, hyper.word_dim])<|endoftext|>
|
dfe713751ce23202f71501fea8e187986e70a9a037f5fd6fbe63eb9cea0c338e
|
def collect_node_for_conv_patch_blk(max_depth=2):
'Input: node dict\n Output: flattened list of all collected nodes, in the format\n [(node, idx, pclen, depth, max_depth), ...]\n '
def _collect_patch(node):
collected = [(node, 1, 1, 0, max_depth)]
def recurse_helper(node, depth):
if (depth > max_depth):
return
for (idx, c) in enumerate(node['children'], 1):
collected.append((c, idx, node['clen'], (depth + 1), max_depth))
recurse_helper(c, (depth + 1))
recurse_helper(node, 0)
return collected
return td.InputTransform(_collect_patch)
|
Input: node dict
Output: flattened list of all collected nodes, in the format
[(node, idx, pclen, depth, max_depth), ...]
|
tbcnn/tbcnn.py
|
collect_node_for_conv_patch_blk
|
Aetf/tensorflow-tbcnn
| 34 |
python
|
def collect_node_for_conv_patch_blk(max_depth=2):
'Input: node dict\n Output: flattened list of all collected nodes, in the format\n [(node, idx, pclen, depth, max_depth), ...]\n '
def _collect_patch(node):
collected = [(node, 1, 1, 0, max_depth)]
def recurse_helper(node, depth):
if (depth > max_depth):
return
for (idx, c) in enumerate(node['children'], 1):
collected.append((c, idx, node['clen'], (depth + 1), max_depth))
recurse_helper(c, (depth + 1))
recurse_helper(node, 0)
return collected
return td.InputTransform(_collect_patch)
|
def collect_node_for_conv_patch_blk(max_depth=2):
'Input: node dict\n Output: flattened list of all collected nodes, in the format\n [(node, idx, pclen, depth, max_depth), ...]\n '
def _collect_patch(node):
collected = [(node, 1, 1, 0, max_depth)]
def recurse_helper(node, depth):
if (depth > max_depth):
return
for (idx, c) in enumerate(node['children'], 1):
collected.append((c, idx, node['clen'], (depth + 1), max_depth))
recurse_helper(c, (depth + 1))
recurse_helper(node, 0)
return collected
return td.InputTransform(_collect_patch)<|docstring|>Input: node dict
Output: flattened list of all collected nodes, in the format
[(node, idx, pclen, depth, max_depth), ...]<|endoftext|>
|
6a43a82cd37a2784983d22c7306ace83efd7aa70e7c9ea1eaee47b84a4a257d0
|
def tri_combined(idx, pclen, depth, max_depth):
'TF function, input: idx, pclen, depth, max_depth as batch (1D Tensor)\n Output: weight tensor (3D Tensor), first dim is batch\n '
Wconvt = param.get('Wconvt')
Wconvl = param.get('Wconvl')
Wconvr = param.get('Wconvr')
dim = tf.unstack(tf.shape(Wconvt))[0]
batch_shape = tf.shape(idx)
tmp = ((idx - 1) / (pclen - 1))
tmp = tf.where(tf.is_nan(tmp), (tf.ones_like(tmp) * 0.5), tmp)
t = ((max_depth - depth) / max_depth)
r = ((1 - t) * tmp)
l = ((1 - t) * (1 - r))
lb = tf.transpose((tf.transpose(tf.eye(dim, batch_shape=batch_shape)) * l))
rb = tf.transpose((tf.transpose(tf.eye(dim, batch_shape=batch_shape)) * r))
tb = tf.transpose((tf.transpose(tf.eye(dim, batch_shape=batch_shape)) * t))
lb = tf.reshape(lb, [(- 1), dim])
rb = tf.reshape(rb, [(- 1), dim])
tb = tf.reshape(tb, [(- 1), dim])
tmp = ((tf.matmul(lb, Wconvl) + tf.matmul(rb, Wconvr)) + tf.matmul(tb, Wconvt))
tmp = tf.reshape(tmp, [(- 1), hyper.word_dim, hyper.conv_dim])
return tmp
|
TF function, input: idx, pclen, depth, max_depth as batch (1D Tensor)
Output: weight tensor (3D Tensor), first dim is batch
|
tbcnn/tbcnn.py
|
tri_combined
|
Aetf/tensorflow-tbcnn
| 34 |
python
|
def tri_combined(idx, pclen, depth, max_depth):
'TF function, input: idx, pclen, depth, max_depth as batch (1D Tensor)\n Output: weight tensor (3D Tensor), first dim is batch\n '
Wconvt = param.get('Wconvt')
Wconvl = param.get('Wconvl')
Wconvr = param.get('Wconvr')
dim = tf.unstack(tf.shape(Wconvt))[0]
batch_shape = tf.shape(idx)
tmp = ((idx - 1) / (pclen - 1))
tmp = tf.where(tf.is_nan(tmp), (tf.ones_like(tmp) * 0.5), tmp)
t = ((max_depth - depth) / max_depth)
r = ((1 - t) * tmp)
l = ((1 - t) * (1 - r))
lb = tf.transpose((tf.transpose(tf.eye(dim, batch_shape=batch_shape)) * l))
rb = tf.transpose((tf.transpose(tf.eye(dim, batch_shape=batch_shape)) * r))
tb = tf.transpose((tf.transpose(tf.eye(dim, batch_shape=batch_shape)) * t))
lb = tf.reshape(lb, [(- 1), dim])
rb = tf.reshape(rb, [(- 1), dim])
tb = tf.reshape(tb, [(- 1), dim])
tmp = ((tf.matmul(lb, Wconvl) + tf.matmul(rb, Wconvr)) + tf.matmul(tb, Wconvt))
tmp = tf.reshape(tmp, [(- 1), hyper.word_dim, hyper.conv_dim])
return tmp
|
def tri_combined(idx, pclen, depth, max_depth):
'TF function, input: idx, pclen, depth, max_depth as batch (1D Tensor)\n Output: weight tensor (3D Tensor), first dim is batch\n '
Wconvt = param.get('Wconvt')
Wconvl = param.get('Wconvl')
Wconvr = param.get('Wconvr')
dim = tf.unstack(tf.shape(Wconvt))[0]
batch_shape = tf.shape(idx)
tmp = ((idx - 1) / (pclen - 1))
tmp = tf.where(tf.is_nan(tmp), (tf.ones_like(tmp) * 0.5), tmp)
t = ((max_depth - depth) / max_depth)
r = ((1 - t) * tmp)
l = ((1 - t) * (1 - r))
lb = tf.transpose((tf.transpose(tf.eye(dim, batch_shape=batch_shape)) * l))
rb = tf.transpose((tf.transpose(tf.eye(dim, batch_shape=batch_shape)) * r))
tb = tf.transpose((tf.transpose(tf.eye(dim, batch_shape=batch_shape)) * t))
lb = tf.reshape(lb, [(- 1), dim])
rb = tf.reshape(rb, [(- 1), dim])
tb = tf.reshape(tb, [(- 1), dim])
tmp = ((tf.matmul(lb, Wconvl) + tf.matmul(rb, Wconvr)) + tf.matmul(tb, Wconvt))
tmp = tf.reshape(tmp, [(- 1), hyper.word_dim, hyper.conv_dim])
return tmp<|docstring|>TF function, input: idx, pclen, depth, max_depth as batch (1D Tensor)
Output: weight tensor (3D Tensor), first dim is batch<|endoftext|>
|
732265aa411605847109385a891b13d3ce8b096f538cac273f8063a8c63f940d
|
def weighted_feature_blk():
'Input: (feature , idx , pclen, depth, max_depth)\n (TensorType([hyper.word_dim, ]), Scalar, Scalar, Scalar, Scalar)\n Output: weighted_feature\n TensorType([hyper.conv_dim, ])\n '
blk = td.Composition()
with blk.scope():
fea = blk.input[0]
Wi = tri_combined_blk().reads(blk.input[1], blk.input[2], blk.input[3], blk.input[4])
weighted_fea = td.Function(embedding.batch_mul).reads(fea, Wi)
blk.output.reads(weighted_fea)
return blk
|
Input: (feature , idx , pclen, depth, max_depth)
(TensorType([hyper.word_dim, ]), Scalar, Scalar, Scalar, Scalar)
Output: weighted_feature
TensorType([hyper.conv_dim, ])
|
tbcnn/tbcnn.py
|
weighted_feature_blk
|
Aetf/tensorflow-tbcnn
| 34 |
python
|
def weighted_feature_blk():
'Input: (feature , idx , pclen, depth, max_depth)\n (TensorType([hyper.word_dim, ]), Scalar, Scalar, Scalar, Scalar)\n Output: weighted_feature\n TensorType([hyper.conv_dim, ])\n '
blk = td.Composition()
with blk.scope():
fea = blk.input[0]
Wi = tri_combined_blk().reads(blk.input[1], blk.input[2], blk.input[3], blk.input[4])
weighted_fea = td.Function(embedding.batch_mul).reads(fea, Wi)
blk.output.reads(weighted_fea)
return blk
|
def weighted_feature_blk():
'Input: (feature , idx , pclen, depth, max_depth)\n (TensorType([hyper.word_dim, ]), Scalar, Scalar, Scalar, Scalar)\n Output: weighted_feature\n TensorType([hyper.conv_dim, ])\n '
blk = td.Composition()
with blk.scope():
fea = blk.input[0]
Wi = tri_combined_blk().reads(blk.input[1], blk.input[2], blk.input[3], blk.input[4])
weighted_fea = td.Function(embedding.batch_mul).reads(fea, Wi)
blk.output.reads(weighted_fea)
return blk<|docstring|>Input: (feature , idx , pclen, depth, max_depth)
(TensorType([hyper.word_dim, ]), Scalar, Scalar, Scalar, Scalar)
Output: weighted_feature
TensorType([hyper.conv_dim, ])<|endoftext|>
|
52293ed58beeea3775f22e1c848e78af70d5c6deb15683e971120524065c788f
|
def feature_detector_blk(max_depth=2):
'Input: node dict\n Output: TensorType([hyper.conv_dim, ])\n Single patch of the conv. Depth is max_depth\n '
blk = td.Composition()
with blk.scope():
nodes_in_patch = collect_node_for_conv_patch_blk(max_depth=max_depth).reads(blk.input)
mapped = td.Map(td.Record((coding_blk(), td.Scalar(), td.Scalar(), td.Scalar(), td.Scalar()))).reads(nodes_in_patch)
weighted = td.Map(weighted_feature_blk()).reads(mapped)
added = td.Reduce(td.Function(tf.add)).reads(weighted)
biased = td.Function(tf.add).reads(added, td.FromTensor(param.get('Bconv')))
tanh = td.Function(tf.nn.tanh).reads(biased)
blk.output.reads(tanh)
return blk
|
Input: node dict
Output: TensorType([hyper.conv_dim, ])
Single patch of the conv. Depth is max_depth
|
tbcnn/tbcnn.py
|
feature_detector_blk
|
Aetf/tensorflow-tbcnn
| 34 |
python
|
def feature_detector_blk(max_depth=2):
'Input: node dict\n Output: TensorType([hyper.conv_dim, ])\n Single patch of the conv. Depth is max_depth\n '
blk = td.Composition()
with blk.scope():
nodes_in_patch = collect_node_for_conv_patch_blk(max_depth=max_depth).reads(blk.input)
mapped = td.Map(td.Record((coding_blk(), td.Scalar(), td.Scalar(), td.Scalar(), td.Scalar()))).reads(nodes_in_patch)
weighted = td.Map(weighted_feature_blk()).reads(mapped)
added = td.Reduce(td.Function(tf.add)).reads(weighted)
biased = td.Function(tf.add).reads(added, td.FromTensor(param.get('Bconv')))
tanh = td.Function(tf.nn.tanh).reads(biased)
blk.output.reads(tanh)
return blk
|
def feature_detector_blk(max_depth=2):
'Input: node dict\n Output: TensorType([hyper.conv_dim, ])\n Single patch of the conv. Depth is max_depth\n '
blk = td.Composition()
with blk.scope():
nodes_in_patch = collect_node_for_conv_patch_blk(max_depth=max_depth).reads(blk.input)
mapped = td.Map(td.Record((coding_blk(), td.Scalar(), td.Scalar(), td.Scalar(), td.Scalar()))).reads(nodes_in_patch)
weighted = td.Map(weighted_feature_blk()).reads(mapped)
added = td.Reduce(td.Function(tf.add)).reads(weighted)
biased = td.Function(tf.add).reads(added, td.FromTensor(param.get('Bconv')))
tanh = td.Function(tf.nn.tanh).reads(biased)
blk.output.reads(tanh)
return blk<|docstring|>Input: node dict
Output: TensorType([hyper.conv_dim, ])
Single patch of the conv. Depth is max_depth<|endoftext|>
|
64dfef4b9bb6a87ceaad9885f6bcaa29996e329c4e8e81e85c94f5506de37589
|
def dynamic_pooling_blk():
'Input: root node dic\n Output: pooled, TensorType([hyper.conv_dim, ])\n '
leaf_case = feature_detector_blk()
pool_fwd = td.ForwardDeclaration(td.PyObjectType(), td.TensorType([hyper.conv_dim]))
pool = td.Composition()
with pool.scope():
cur_fea = feature_detector_blk().reads(pool.input)
children = td.GetItem('children').reads(pool.input)
mapped = td.Map(pool_fwd()).reads(children)
summed = td.Reduce(td.Function(tf.maximum)).reads(mapped)
summed = td.Function(tf.maximum).reads(summed, cur_fea)
pool.output.reads(summed)
pool = td.OneOf((lambda x: (x['clen'] == 0)), {True: leaf_case, False: pool})
pool_fwd.resolve_to(pool)
return pool
|
Input: root node dic
Output: pooled, TensorType([hyper.conv_dim, ])
|
tbcnn/tbcnn.py
|
dynamic_pooling_blk
|
Aetf/tensorflow-tbcnn
| 34 |
python
|
def dynamic_pooling_blk():
'Input: root node dic\n Output: pooled, TensorType([hyper.conv_dim, ])\n '
leaf_case = feature_detector_blk()
pool_fwd = td.ForwardDeclaration(td.PyObjectType(), td.TensorType([hyper.conv_dim]))
pool = td.Composition()
with pool.scope():
cur_fea = feature_detector_blk().reads(pool.input)
children = td.GetItem('children').reads(pool.input)
mapped = td.Map(pool_fwd()).reads(children)
summed = td.Reduce(td.Function(tf.maximum)).reads(mapped)
summed = td.Function(tf.maximum).reads(summed, cur_fea)
pool.output.reads(summed)
pool = td.OneOf((lambda x: (x['clen'] == 0)), {True: leaf_case, False: pool})
pool_fwd.resolve_to(pool)
return pool
|
def dynamic_pooling_blk():
'Input: root node dic\n Output: pooled, TensorType([hyper.conv_dim, ])\n '
leaf_case = feature_detector_blk()
pool_fwd = td.ForwardDeclaration(td.PyObjectType(), td.TensorType([hyper.conv_dim]))
pool = td.Composition()
with pool.scope():
cur_fea = feature_detector_blk().reads(pool.input)
children = td.GetItem('children').reads(pool.input)
mapped = td.Map(pool_fwd()).reads(children)
summed = td.Reduce(td.Function(tf.maximum)).reads(mapped)
summed = td.Function(tf.maximum).reads(summed, cur_fea)
pool.output.reads(summed)
pool = td.OneOf((lambda x: (x['clen'] == 0)), {True: leaf_case, False: pool})
pool_fwd.resolve_to(pool)
return pool<|docstring|>Input: root node dic
Output: pooled, TensorType([hyper.conv_dim, ])<|endoftext|>
|
7c71d46e0660e4e3e9b82dca084db044c757d1e7786dab74067fe91517748e5d
|
def runMethod(x_i):
"\n I'm going to solve the root of a function using Newton-Raphson Method\n "
iterator = 0
while True:
f = function_ORIGINAL(x_i)
f_d = function_DERIVED(x_i)
x_next = (x_i - (f / f_d))
print('the value N°', iterator, ':', x_next)
ERROR = (math.fabs(((x_next - x_i) / x_next)) * 100)
if (ERROR == 0):
print('the answer:', x_next)
break
x_i = x_next
iterator = (iterator + 1)
|
I'm going to solve the root of a function using Newton-Raphson Method
|
exercises/newton_raphson_method.py
|
runMethod
|
leonel-123/python-fundamentals
| 0 |
python
|
def runMethod(x_i):
"\n \n "
iterator = 0
while True:
f = function_ORIGINAL(x_i)
f_d = function_DERIVED(x_i)
x_next = (x_i - (f / f_d))
print('the value N°', iterator, ':', x_next)
ERROR = (math.fabs(((x_next - x_i) / x_next)) * 100)
if (ERROR == 0):
print('the answer:', x_next)
break
x_i = x_next
iterator = (iterator + 1)
|
def runMethod(x_i):
"\n \n "
iterator = 0
while True:
f = function_ORIGINAL(x_i)
f_d = function_DERIVED(x_i)
x_next = (x_i - (f / f_d))
print('the value N°', iterator, ':', x_next)
ERROR = (math.fabs(((x_next - x_i) / x_next)) * 100)
if (ERROR == 0):
print('the answer:', x_next)
break
x_i = x_next
iterator = (iterator + 1)<|docstring|>I'm going to solve the root of a function using Newton-Raphson Method<|endoftext|>
|
81b6d7abc5c2ee522cc890fe3a8acccb0234670231e61c1d9816656724d81954
|
def plot_cluster_assignments(evl, data, atts=None, inst_no=False, size=10, title=None, outfile=None, wait=True):
'\n Plots the cluster assignments against the specified attributes.\n\n TODO: click events http://matplotlib.org/examples/event_handling/data_browser.html\n\n :param evl: the cluster evaluation to obtain the cluster assignments from\n :type evl: ClusterEvaluation\n :param data: the dataset the clusterer was evaluated against\n :type data: Instances\n :param atts: the list of attribute indices to plot, None for all\n :type atts: list\n :param inst_no: whether to include a fake attribute with the instance number\n :type inst_no: bool\n :param size: the size of the circles in point\n :type size: int\n :param title: an optional title\n :type title: str\n :param outfile: the (optional) file to save the generated plot to. The extension determines the file format.\n :type outfile: str\n :param wait: whether to wait for the user to close the plot\n :type wait: bool\n '
if (not plot.matplotlib_available):
logger.error('Matplotlib is not installed, plotting unavailable!')
return
fig = plt.figure()
if (data.class_index == (- 1)):
c = None
else:
c = []
for i in xrange(data.num_instances):
inst = data.get_instance(i)
c.append(inst.get_value(inst.class_index))
if (atts is None):
atts = []
for i in xrange(data.num_attributes):
atts.append(i)
num_plots = len(atts)
if inst_no:
num_plots += 1
clusters = evl.cluster_assignments
for (index, att) in enumerate(atts):
x = data.values(att)
ax = fig.add_subplot(1, num_plots, (index + 1))
if (c is None):
ax.scatter(clusters, x, s=size, alpha=0.5)
else:
ax.scatter(clusters, x, c=c, s=size, alpha=0.5)
ax.set_xlabel('Clusters')
ax.set_title(data.attribute(att).name)
ax.get_xaxis().set_ticks(list(set(clusters)))
ax.grid(True)
if inst_no:
x = []
for i in xrange(data.num_instances):
x.append((i + 1))
ax = fig.add_subplot(1, num_plots, num_plots)
if (c is None):
ax.scatter(clusters, x, s=size, alpha=0.5)
else:
ax.scatter(clusters, x, c=c, s=size, alpha=0.5)
ax.set_xlabel('Clusters')
ax.set_title('Instance number')
ax.get_xaxis().set_ticks(list(set(clusters)))
ax.grid(True)
if (title is None):
title = data.relationname
fig.canvas.set_window_title(title)
plt.draw()
if (not (outfile is None)):
plt.savefig(outfile)
if wait:
plt.show()
|
Plots the cluster assignments against the specified attributes.
TODO: click events http://matplotlib.org/examples/event_handling/data_browser.html
:param evl: the cluster evaluation to obtain the cluster assignments from
:type evl: ClusterEvaluation
:param data: the dataset the clusterer was evaluated against
:type data: Instances
:param atts: the list of attribute indices to plot, None for all
:type atts: list
:param inst_no: whether to include a fake attribute with the instance number
:type inst_no: bool
:param size: the size of the circles in point
:type size: int
:param title: an optional title
:type title: str
:param outfile: the (optional) file to save the generated plot to. The extension determines the file format.
:type outfile: str
:param wait: whether to wait for the user to close the plot
:type wait: bool
|
flasky2/venv/Lib/site-packages/weka/plot/clusterers.py
|
plot_cluster_assignments
|
akshat0109/kisan_backend
| 0 |
python
|
def plot_cluster_assignments(evl, data, atts=None, inst_no=False, size=10, title=None, outfile=None, wait=True):
'\n Plots the cluster assignments against the specified attributes.\n\n TODO: click events http://matplotlib.org/examples/event_handling/data_browser.html\n\n :param evl: the cluster evaluation to obtain the cluster assignments from\n :type evl: ClusterEvaluation\n :param data: the dataset the clusterer was evaluated against\n :type data: Instances\n :param atts: the list of attribute indices to plot, None for all\n :type atts: list\n :param inst_no: whether to include a fake attribute with the instance number\n :type inst_no: bool\n :param size: the size of the circles in point\n :type size: int\n :param title: an optional title\n :type title: str\n :param outfile: the (optional) file to save the generated plot to. The extension determines the file format.\n :type outfile: str\n :param wait: whether to wait for the user to close the plot\n :type wait: bool\n '
if (not plot.matplotlib_available):
logger.error('Matplotlib is not installed, plotting unavailable!')
return
fig = plt.figure()
if (data.class_index == (- 1)):
c = None
else:
c = []
for i in xrange(data.num_instances):
inst = data.get_instance(i)
c.append(inst.get_value(inst.class_index))
if (atts is None):
atts = []
for i in xrange(data.num_attributes):
atts.append(i)
num_plots = len(atts)
if inst_no:
num_plots += 1
clusters = evl.cluster_assignments
for (index, att) in enumerate(atts):
x = data.values(att)
ax = fig.add_subplot(1, num_plots, (index + 1))
if (c is None):
ax.scatter(clusters, x, s=size, alpha=0.5)
else:
ax.scatter(clusters, x, c=c, s=size, alpha=0.5)
ax.set_xlabel('Clusters')
ax.set_title(data.attribute(att).name)
ax.get_xaxis().set_ticks(list(set(clusters)))
ax.grid(True)
if inst_no:
x = []
for i in xrange(data.num_instances):
x.append((i + 1))
ax = fig.add_subplot(1, num_plots, num_plots)
if (c is None):
ax.scatter(clusters, x, s=size, alpha=0.5)
else:
ax.scatter(clusters, x, c=c, s=size, alpha=0.5)
ax.set_xlabel('Clusters')
ax.set_title('Instance number')
ax.get_xaxis().set_ticks(list(set(clusters)))
ax.grid(True)
if (title is None):
title = data.relationname
fig.canvas.set_window_title(title)
plt.draw()
if (not (outfile is None)):
plt.savefig(outfile)
if wait:
plt.show()
|
def plot_cluster_assignments(evl, data, atts=None, inst_no=False, size=10, title=None, outfile=None, wait=True):
'\n Plots the cluster assignments against the specified attributes.\n\n TODO: click events http://matplotlib.org/examples/event_handling/data_browser.html\n\n :param evl: the cluster evaluation to obtain the cluster assignments from\n :type evl: ClusterEvaluation\n :param data: the dataset the clusterer was evaluated against\n :type data: Instances\n :param atts: the list of attribute indices to plot, None for all\n :type atts: list\n :param inst_no: whether to include a fake attribute with the instance number\n :type inst_no: bool\n :param size: the size of the circles in point\n :type size: int\n :param title: an optional title\n :type title: str\n :param outfile: the (optional) file to save the generated plot to. The extension determines the file format.\n :type outfile: str\n :param wait: whether to wait for the user to close the plot\n :type wait: bool\n '
if (not plot.matplotlib_available):
logger.error('Matplotlib is not installed, plotting unavailable!')
return
fig = plt.figure()
if (data.class_index == (- 1)):
c = None
else:
c = []
for i in xrange(data.num_instances):
inst = data.get_instance(i)
c.append(inst.get_value(inst.class_index))
if (atts is None):
atts = []
for i in xrange(data.num_attributes):
atts.append(i)
num_plots = len(atts)
if inst_no:
num_plots += 1
clusters = evl.cluster_assignments
for (index, att) in enumerate(atts):
x = data.values(att)
ax = fig.add_subplot(1, num_plots, (index + 1))
if (c is None):
ax.scatter(clusters, x, s=size, alpha=0.5)
else:
ax.scatter(clusters, x, c=c, s=size, alpha=0.5)
ax.set_xlabel('Clusters')
ax.set_title(data.attribute(att).name)
ax.get_xaxis().set_ticks(list(set(clusters)))
ax.grid(True)
if inst_no:
x = []
for i in xrange(data.num_instances):
x.append((i + 1))
ax = fig.add_subplot(1, num_plots, num_plots)
if (c is None):
ax.scatter(clusters, x, s=size, alpha=0.5)
else:
ax.scatter(clusters, x, c=c, s=size, alpha=0.5)
ax.set_xlabel('Clusters')
ax.set_title('Instance number')
ax.get_xaxis().set_ticks(list(set(clusters)))
ax.grid(True)
if (title is None):
title = data.relationname
fig.canvas.set_window_title(title)
plt.draw()
if (not (outfile is None)):
plt.savefig(outfile)
if wait:
plt.show()<|docstring|>Plots the cluster assignments against the specified attributes.
TODO: click events http://matplotlib.org/examples/event_handling/data_browser.html
:param evl: the cluster evaluation to obtain the cluster assignments from
:type evl: ClusterEvaluation
:param data: the dataset the clusterer was evaluated against
:type data: Instances
:param atts: the list of attribute indices to plot, None for all
:type atts: list
:param inst_no: whether to include a fake attribute with the instance number
:type inst_no: bool
:param size: the size of the circles in point
:type size: int
:param title: an optional title
:type title: str
:param outfile: the (optional) file to save the generated plot to. The extension determines the file format.
:type outfile: str
:param wait: whether to wait for the user to close the plot
:type wait: bool<|endoftext|>
|
78f50ad48516f44f303939f645bc9d76018604de70b2e33575be5a1e905e5bc1
|
def answer(self, results: List[InlineQueryResult], cache_time: Optional[int]=None, is_personal: Optional[bool]=None, next_offset: Optional[str]=None, switch_pm_text: Optional[str]=None, switch_pm_parameter: Optional[str]=None) -> AnswerInlineQuery:
'\n :param results:\n :param cache_time:\n :param is_personal:\n :param next_offset:\n :param switch_pm_text:\n :param switch_pm_parameter:\n :return:\n '
from ..methods import AnswerInlineQuery
return AnswerInlineQuery(inline_query_id=self.id, results=results, cache_time=cache_time, is_personal=is_personal, next_offset=next_offset, switch_pm_text=switch_pm_text, switch_pm_parameter=switch_pm_parameter)
|
:param results:
:param cache_time:
:param is_personal:
:param next_offset:
:param switch_pm_text:
:param switch_pm_parameter:
:return:
|
tgtypes/models/inline_query.py
|
answer
|
autogram/tgtypes
| 0 |
python
|
def answer(self, results: List[InlineQueryResult], cache_time: Optional[int]=None, is_personal: Optional[bool]=None, next_offset: Optional[str]=None, switch_pm_text: Optional[str]=None, switch_pm_parameter: Optional[str]=None) -> AnswerInlineQuery:
'\n :param results:\n :param cache_time:\n :param is_personal:\n :param next_offset:\n :param switch_pm_text:\n :param switch_pm_parameter:\n :return:\n '
from ..methods import AnswerInlineQuery
return AnswerInlineQuery(inline_query_id=self.id, results=results, cache_time=cache_time, is_personal=is_personal, next_offset=next_offset, switch_pm_text=switch_pm_text, switch_pm_parameter=switch_pm_parameter)
|
def answer(self, results: List[InlineQueryResult], cache_time: Optional[int]=None, is_personal: Optional[bool]=None, next_offset: Optional[str]=None, switch_pm_text: Optional[str]=None, switch_pm_parameter: Optional[str]=None) -> AnswerInlineQuery:
'\n :param results:\n :param cache_time:\n :param is_personal:\n :param next_offset:\n :param switch_pm_text:\n :param switch_pm_parameter:\n :return:\n '
from ..methods import AnswerInlineQuery
return AnswerInlineQuery(inline_query_id=self.id, results=results, cache_time=cache_time, is_personal=is_personal, next_offset=next_offset, switch_pm_text=switch_pm_text, switch_pm_parameter=switch_pm_parameter)<|docstring|>:param results:
:param cache_time:
:param is_personal:
:param next_offset:
:param switch_pm_text:
:param switch_pm_parameter:
:return:<|endoftext|>
|
392783ab59f3231d491b6fd2ed430d5224baa27703f88fe0ede71c58a201a00f
|
def synthesize(evaluator: Callable[([List[Command]], bool)], initial: List[Command], opcodes: List[Opcode], size: int) -> Optional[List[Command]]:
'\n Synthesizes a series of commands of exactly the given size\n using the provided set of opcodes and the initial set of commands.\n\n Either returns a list of commands that passes the given evaluator,\n or returns None otherwise.\n '
def helper(current: List[Command]) -> Tuple[(bool, Optional[List[Command]])]:
if (len(current) == size):
return (evaluator(current), current)
else:
prev_args = list(range(len(current)))
for op in opcodes:
for args in product(prev_args, repeat=op.num_args):
current.append(Command(op, list(args)))
(res, possible) = helper(current)
if res:
return (res, possible)
current.pop()
return (False, None)
copy = list(initial)
(res, out) = helper(copy)
return out
|
Synthesizes a series of commands of exactly the given size
using the provided set of opcodes and the initial set of commands.
Either returns a list of commands that passes the given evaluator,
or returns None otherwise.
|
synthesis.py
|
synthesize
|
Michael0x2a/test_logic
| 0 |
python
|
def synthesize(evaluator: Callable[([List[Command]], bool)], initial: List[Command], opcodes: List[Opcode], size: int) -> Optional[List[Command]]:
'\n Synthesizes a series of commands of exactly the given size\n using the provided set of opcodes and the initial set of commands.\n\n Either returns a list of commands that passes the given evaluator,\n or returns None otherwise.\n '
def helper(current: List[Command]) -> Tuple[(bool, Optional[List[Command]])]:
if (len(current) == size):
return (evaluator(current), current)
else:
prev_args = list(range(len(current)))
for op in opcodes:
for args in product(prev_args, repeat=op.num_args):
current.append(Command(op, list(args)))
(res, possible) = helper(current)
if res:
return (res, possible)
current.pop()
return (False, None)
copy = list(initial)
(res, out) = helper(copy)
return out
|
def synthesize(evaluator: Callable[([List[Command]], bool)], initial: List[Command], opcodes: List[Opcode], size: int) -> Optional[List[Command]]:
'\n Synthesizes a series of commands of exactly the given size\n using the provided set of opcodes and the initial set of commands.\n\n Either returns a list of commands that passes the given evaluator,\n or returns None otherwise.\n '
def helper(current: List[Command]) -> Tuple[(bool, Optional[List[Command]])]:
if (len(current) == size):
return (evaluator(current), current)
else:
prev_args = list(range(len(current)))
for op in opcodes:
for args in product(prev_args, repeat=op.num_args):
current.append(Command(op, list(args)))
(res, possible) = helper(current)
if res:
return (res, possible)
current.pop()
return (False, None)
copy = list(initial)
(res, out) = helper(copy)
return out<|docstring|>Synthesizes a series of commands of exactly the given size
using the provided set of opcodes and the initial set of commands.
Either returns a list of commands that passes the given evaluator,
or returns None otherwise.<|endoftext|>
|
caf5ee7e6237be17ee0a0a392db6aabd5d50ad499f33d2942bf5f38e4926663b
|
def trace(var_assigns: Dict[(str, bool)], commands: List[Command]) -> bool:
'Evaluates the given commands using the provided variable assignments.'
results = []
for cmd in commands:
if isinstance(cmd.op, Variable):
results.append(var_assigns[cmd.op.name])
else:
arg_vals = [results[i] for i in cmd.args]
results.append(cmd.op.eval(arg_vals))
return results[(- 1)]
|
Evaluates the given commands using the provided variable assignments.
|
synthesis.py
|
trace
|
Michael0x2a/test_logic
| 0 |
python
|
def trace(var_assigns: Dict[(str, bool)], commands: List[Command]) -> bool:
results = []
for cmd in commands:
if isinstance(cmd.op, Variable):
results.append(var_assigns[cmd.op.name])
else:
arg_vals = [results[i] for i in cmd.args]
results.append(cmd.op.eval(arg_vals))
return results[(- 1)]
|
def trace(var_assigns: Dict[(str, bool)], commands: List[Command]) -> bool:
results = []
for cmd in commands:
if isinstance(cmd.op, Variable):
results.append(var_assigns[cmd.op.name])
else:
arg_vals = [results[i] for i in cmd.args]
results.append(cmd.op.eval(arg_vals))
return results[(- 1)]<|docstring|>Evaluates the given commands using the provided variable assignments.<|endoftext|>
|
157355497e34ad2b57274a0fa4a427f4cdab6f6f12a150dbfc930f299be816bb
|
def get_vars(commands: List[Command]) -> List[str]:
'Extracts free variables from a command list.'
out = []
for cmd in commands:
if isinstance(cmd.op, Variable):
out.append(cmd.op.name)
return out
|
Extracts free variables from a command list.
|
synthesis.py
|
get_vars
|
Michael0x2a/test_logic
| 0 |
python
|
def get_vars(commands: List[Command]) -> List[str]:
out = []
for cmd in commands:
if isinstance(cmd.op, Variable):
out.append(cmd.op.name)
return out
|
def get_vars(commands: List[Command]) -> List[str]:
out = []
for cmd in commands:
if isinstance(cmd.op, Variable):
out.append(cmd.op.name)
return out<|docstring|>Extracts free variables from a command list.<|endoftext|>
|
480802aaffa22febfdcbdee17d627dd6221412185fd5bfb05a3caa9c538b0cac
|
def truth_table(commands: List[Command]) -> List[Tuple[(Dict[(str, bool)], bool)]]:
'Constructs a truth table of sorts, for debugging.'
out = []
variables = get_vars(commands)
for assignments in product([True, False], repeat=len(variables)):
asgns = {a: b for (a, b) in zip(variables, assignments)}
out.append((asgns, trace(asgns, commands)))
return out
|
Constructs a truth table of sorts, for debugging.
|
synthesis.py
|
truth_table
|
Michael0x2a/test_logic
| 0 |
python
|
def truth_table(commands: List[Command]) -> List[Tuple[(Dict[(str, bool)], bool)]]:
out = []
variables = get_vars(commands)
for assignments in product([True, False], repeat=len(variables)):
asgns = {a: b for (a, b) in zip(variables, assignments)}
out.append((asgns, trace(asgns, commands)))
return out
|
def truth_table(commands: List[Command]) -> List[Tuple[(Dict[(str, bool)], bool)]]:
out = []
variables = get_vars(commands)
for assignments in product([True, False], repeat=len(variables)):
asgns = {a: b for (a, b) in zip(variables, assignments)}
out.append((asgns, trace(asgns, commands)))
return out<|docstring|>Constructs a truth table of sorts, for debugging.<|endoftext|>
|
c021464a757b3008b4d3c18bfc25abf994e6a26a2f35cecac14f8ebf88e36d83
|
def make_evaluator(var_names: List[str], func: Callable[(..., bool)]) -> Callable[([List[Command]], bool)]:
'Takes a list of variable names, a regular function, and constructs\n the corresponding evaluator.'
def eval(commands: List[Command]) -> bool:
for assignments in product([True, False], repeat=len(var_names)):
asgns = {a: b for (a, b) in zip(var_names, assignments)}
given = trace(asgns, commands)
expected = func(*assignments)
if (given != expected):
return False
return True
return eval
|
Takes a list of variable names, a regular function, and constructs
the corresponding evaluator.
|
synthesis.py
|
make_evaluator
|
Michael0x2a/test_logic
| 0 |
python
|
def make_evaluator(var_names: List[str], func: Callable[(..., bool)]) -> Callable[([List[Command]], bool)]:
'Takes a list of variable names, a regular function, and constructs\n the corresponding evaluator.'
def eval(commands: List[Command]) -> bool:
for assignments in product([True, False], repeat=len(var_names)):
asgns = {a: b for (a, b) in zip(var_names, assignments)}
given = trace(asgns, commands)
expected = func(*assignments)
if (given != expected):
return False
return True
return eval
|
def make_evaluator(var_names: List[str], func: Callable[(..., bool)]) -> Callable[([List[Command]], bool)]:
'Takes a list of variable names, a regular function, and constructs\n the corresponding evaluator.'
def eval(commands: List[Command]) -> bool:
for assignments in product([True, False], repeat=len(var_names)):
asgns = {a: b for (a, b) in zip(var_names, assignments)}
given = trace(asgns, commands)
expected = func(*assignments)
if (given != expected):
return False
return True
return eval<|docstring|>Takes a list of variable names, a regular function, and constructs
the corresponding evaluator.<|endoftext|>
|
686e1205fe7f5b2e5cc850e5e42a8076e3b53e2300ba91261563a23889316961
|
def full_synthesize(variables: List[str], func: Callable[(..., bool)], opcodes: List[Opcode], limit: int) -> Optional[List[Command]]:
'Attempts to synthesize a set of commands that match the given function\n using only the provided opcodes. Will give up if the number of commands\n exceeds the provided limit.'
cmds = [Command(Variable(v), []) for v in variables]
evaluator = make_evaluator(variables, func)
for i in range((len(cmds) + 1), limit):
res = synthesize(evaluator, cmds, opcodes, i)
if (res is not None):
return res
return None
|
Attempts to synthesize a set of commands that match the given function
using only the provided opcodes. Will give up if the number of commands
exceeds the provided limit.
|
synthesis.py
|
full_synthesize
|
Michael0x2a/test_logic
| 0 |
python
|
def full_synthesize(variables: List[str], func: Callable[(..., bool)], opcodes: List[Opcode], limit: int) -> Optional[List[Command]]:
'Attempts to synthesize a set of commands that match the given function\n using only the provided opcodes. Will give up if the number of commands\n exceeds the provided limit.'
cmds = [Command(Variable(v), []) for v in variables]
evaluator = make_evaluator(variables, func)
for i in range((len(cmds) + 1), limit):
res = synthesize(evaluator, cmds, opcodes, i)
if (res is not None):
return res
return None
|
def full_synthesize(variables: List[str], func: Callable[(..., bool)], opcodes: List[Opcode], limit: int) -> Optional[List[Command]]:
'Attempts to synthesize a set of commands that match the given function\n using only the provided opcodes. Will give up if the number of commands\n exceeds the provided limit.'
cmds = [Command(Variable(v), []) for v in variables]
evaluator = make_evaluator(variables, func)
for i in range((len(cmds) + 1), limit):
res = synthesize(evaluator, cmds, opcodes, i)
if (res is not None):
return res
return None<|docstring|>Attempts to synthesize a set of commands that match the given function
using only the provided opcodes. Will give up if the number of commands
exceeds the provided limit.<|endoftext|>
|
7059c52c119043bb784922407582e7f40cc66b1ebc898b31f5f00996b9a251ea
|
def display(cmds: Optional[List[Command]]) -> None:
'Nicely displays a command list.'
if (cmds is None):
print('N\\A')
else:
for (idx, cmd) in enumerate(cmds):
print(idx, cmd)
print()
|
Nicely displays a command list.
|
synthesis.py
|
display
|
Michael0x2a/test_logic
| 0 |
python
|
def display(cmds: Optional[List[Command]]) -> None:
if (cmds is None):
print('N\\A')
else:
for (idx, cmd) in enumerate(cmds):
print(idx, cmd)
print()
|
def display(cmds: Optional[List[Command]]) -> None:
if (cmds is None):
print('N\\A')
else:
for (idx, cmd) in enumerate(cmds):
print(idx, cmd)
print()<|docstring|>Nicely displays a command list.<|endoftext|>
|
d8054d0795da4ba3acac56595dd4b070d2bbecc3809b00db1a840a3b352059c0
|
def get_permission_actions(self):
'\n Permisions supported by the plugin.\n '
return ['JANUS_VIEW']
|
Permisions supported by the plugin.
|
tracjanusgateway/web_ui.py
|
get_permission_actions
|
t-kenji/trac-janus-plugin
| 0 |
python
|
def get_permission_actions(self):
'\n \n '
return ['JANUS_VIEW']
|
def get_permission_actions(self):
'\n \n '
return ['JANUS_VIEW']<|docstring|>Permisions supported by the plugin.<|endoftext|>
|
b6a44da36c7334a3b8915c1cb39dab374624eb857d515dba1ed1294cdb4da56b
|
def get_active_navigation_item(self, req):
'\n This method is only called for the `IRequestHandler` processing the\n request.\n '
return 'janus'
|
This method is only called for the `IRequestHandler` processing the
request.
|
tracjanusgateway/web_ui.py
|
get_active_navigation_item
|
t-kenji/trac-janus-plugin
| 0 |
python
|
def get_active_navigation_item(self, req):
'\n This method is only called for the `IRequestHandler` processing the\n request.\n '
return 'janus'
|
def get_active_navigation_item(self, req):
'\n This method is only called for the `IRequestHandler` processing the\n request.\n '
return 'janus'<|docstring|>This method is only called for the `IRequestHandler` processing the
request.<|endoftext|>
|
6263248203c28866789ad2a5bcbc2d7d17b50f06a33b4dd2c8fef862589befad
|
def process_request(self, req):
'\n Processing the request.\n '
req.perm('janus').assert_permission('JANUS_VIEW')
plugins = ('echo', 'videocall', 'videoroom', 'audioroom', 'screensharing')
m = re.match('/janus/(?P<handler>[\\w/-]+)', req.path_info)
if (m is not None):
handler = m.group('handler')
if (handler in plugins):
return self._process_plugin(req, handler)
if handler.startswith('event/'):
return self._process_event(req, handler[6:])
add_stylesheet(req, 'janus/css/janus.css')
return ('janus.html', {}, None)
|
Processing the request.
|
tracjanusgateway/web_ui.py
|
process_request
|
t-kenji/trac-janus-plugin
| 0 |
python
|
def process_request(self, req):
'\n \n '
req.perm('janus').assert_permission('JANUS_VIEW')
plugins = ('echo', 'videocall', 'videoroom', 'audioroom', 'screensharing')
m = re.match('/janus/(?P<handler>[\\w/-]+)', req.path_info)
if (m is not None):
handler = m.group('handler')
if (handler in plugins):
return self._process_plugin(req, handler)
if handler.startswith('event/'):
return self._process_event(req, handler[6:])
add_stylesheet(req, 'janus/css/janus.css')
return ('janus.html', {}, None)
|
def process_request(self, req):
'\n \n '
req.perm('janus').assert_permission('JANUS_VIEW')
plugins = ('echo', 'videocall', 'videoroom', 'audioroom', 'screensharing')
m = re.match('/janus/(?P<handler>[\\w/-]+)', req.path_info)
if (m is not None):
handler = m.group('handler')
if (handler in plugins):
return self._process_plugin(req, handler)
if handler.startswith('event/'):
return self._process_event(req, handler[6:])
add_stylesheet(req, 'janus/css/janus.css')
return ('janus.html', {}, None)<|docstring|>Processing the request.<|endoftext|>
|
65225dbe3fa50ca1d65edfbeecc72f4dcf54e2c6a168c3e7d9fb81d664b712ea
|
def _process_plugin(self, req, plugin):
'\n Processing the plugin.\n '
data = {}
template = 'janus.html'
add_stylesheet(req, 'janus/css/jquery-confirm.min.css')
add_stylesheet(req, 'janus/css/purecss-base-min.css')
add_stylesheet(req, 'janus/css/purecss-forms-min.css')
add_stylesheet(req, 'janus/css/purecss-grids-min.css')
add_stylesheet(req, 'janus/css/purecss-grids-responsive-min.css')
add_stylesheet(req, 'janus/css/purecss-buttons-min.css')
add_stylesheet(req, 'janus/css/purecss-menus-min.css')
add_stylesheet(req, 'janus/css/font-awesome.min.css')
add_script(req, 'janus/js/adapter.min.js')
add_script(req, 'janus/js/jquery.blockUI.min.js')
add_script(req, 'janus/js/jquery-confirm.min.js')
add_script(req, 'janus/js/purecss-menus.js')
add_script(req, 'janus/js/spin.min.js')
add_script(req, 'janus/js/compat.js')
add_script(req, 'janus/js/janus.js')
if (req.locale is not None):
add_script(req, 'janus/js/tracjanusgateway/{}.js'.format(req.locale))
if isinstance(req.remote_user, basestring):
username = req.remote_user
elif isinstance(req.authname, basestring):
username = req.authname
elif ('name' in req.session):
username = req.session.get('name', '')
else:
username = ''
data['username'] = username
data['video_rooms'] = self.video_rooms
data['audio_rooms'] = self.audio_rooms
add_script_data(req, {'debug': req.args.get('debug', 'false'), 'event_uri': req.href.janus('event')})
if plugin.startswith('echo'):
add_ctxtnav(req, _('Echo'))
template = 'echo.html'
add_script(req, 'janus/js/echo.js')
else:
add_ctxtnav(req, _('Echo'), href=req.href.janus('echo'))
if plugin.startswith('videocall'):
add_ctxtnav(req, _('VideoCall'))
template = 'videocall.html'
add_script(req, 'janus/js/videocall.js')
add_script_data(req, {'avatar_url': req.href.avatar('')})
else:
add_ctxtnav(req, _('VideoCall'), href=req.href.janus('videocall'))
if plugin.startswith('videoroom'):
add_ctxtnav(req, _('VideoRoom'))
template = 'videoroom.html'
add_script(req, 'janus/js/videoroom.js')
else:
add_ctxtnav(req, _('VideoRoom'), href=req.href.janus('videoroom'))
if plugin.startswith('audioroom'):
add_ctxtnav(req, _('AudioRoom'))
template = 'audioroom.html'
add_script(req, 'janus/js/audiobridge.js')
else:
add_ctxtnav(req, _('AudioRoom'), href=req.href.janus('audioroom'))
if plugin.startswith('screensharing'):
add_ctxtnav(req, _('ScreenSharing'))
template = 'screensharing.html'
add_script(req, 'janus/js/screensharing.js')
else:
add_ctxtnav(req, _('ScreenSharing'), href=req.href.janus('screensharing'))
add_stylesheet(req, 'janus/css/janus.css')
return (template, data, None)
|
Processing the plugin.
|
tracjanusgateway/web_ui.py
|
_process_plugin
|
t-kenji/trac-janus-plugin
| 0 |
python
|
def _process_plugin(self, req, plugin):
'\n \n '
data = {}
template = 'janus.html'
add_stylesheet(req, 'janus/css/jquery-confirm.min.css')
add_stylesheet(req, 'janus/css/purecss-base-min.css')
add_stylesheet(req, 'janus/css/purecss-forms-min.css')
add_stylesheet(req, 'janus/css/purecss-grids-min.css')
add_stylesheet(req, 'janus/css/purecss-grids-responsive-min.css')
add_stylesheet(req, 'janus/css/purecss-buttons-min.css')
add_stylesheet(req, 'janus/css/purecss-menus-min.css')
add_stylesheet(req, 'janus/css/font-awesome.min.css')
add_script(req, 'janus/js/adapter.min.js')
add_script(req, 'janus/js/jquery.blockUI.min.js')
add_script(req, 'janus/js/jquery-confirm.min.js')
add_script(req, 'janus/js/purecss-menus.js')
add_script(req, 'janus/js/spin.min.js')
add_script(req, 'janus/js/compat.js')
add_script(req, 'janus/js/janus.js')
if (req.locale is not None):
add_script(req, 'janus/js/tracjanusgateway/{}.js'.format(req.locale))
if isinstance(req.remote_user, basestring):
username = req.remote_user
elif isinstance(req.authname, basestring):
username = req.authname
elif ('name' in req.session):
username = req.session.get('name', )
else:
username =
data['username'] = username
data['video_rooms'] = self.video_rooms
data['audio_rooms'] = self.audio_rooms
add_script_data(req, {'debug': req.args.get('debug', 'false'), 'event_uri': req.href.janus('event')})
if plugin.startswith('echo'):
add_ctxtnav(req, _('Echo'))
template = 'echo.html'
add_script(req, 'janus/js/echo.js')
else:
add_ctxtnav(req, _('Echo'), href=req.href.janus('echo'))
if plugin.startswith('videocall'):
add_ctxtnav(req, _('VideoCall'))
template = 'videocall.html'
add_script(req, 'janus/js/videocall.js')
add_script_data(req, {'avatar_url': req.href.avatar()})
else:
add_ctxtnav(req, _('VideoCall'), href=req.href.janus('videocall'))
if plugin.startswith('videoroom'):
add_ctxtnav(req, _('VideoRoom'))
template = 'videoroom.html'
add_script(req, 'janus/js/videoroom.js')
else:
add_ctxtnav(req, _('VideoRoom'), href=req.href.janus('videoroom'))
if plugin.startswith('audioroom'):
add_ctxtnav(req, _('AudioRoom'))
template = 'audioroom.html'
add_script(req, 'janus/js/audiobridge.js')
else:
add_ctxtnav(req, _('AudioRoom'), href=req.href.janus('audioroom'))
if plugin.startswith('screensharing'):
add_ctxtnav(req, _('ScreenSharing'))
template = 'screensharing.html'
add_script(req, 'janus/js/screensharing.js')
else:
add_ctxtnav(req, _('ScreenSharing'), href=req.href.janus('screensharing'))
add_stylesheet(req, 'janus/css/janus.css')
return (template, data, None)
|
def _process_plugin(self, req, plugin):
'\n \n '
data = {}
template = 'janus.html'
add_stylesheet(req, 'janus/css/jquery-confirm.min.css')
add_stylesheet(req, 'janus/css/purecss-base-min.css')
add_stylesheet(req, 'janus/css/purecss-forms-min.css')
add_stylesheet(req, 'janus/css/purecss-grids-min.css')
add_stylesheet(req, 'janus/css/purecss-grids-responsive-min.css')
add_stylesheet(req, 'janus/css/purecss-buttons-min.css')
add_stylesheet(req, 'janus/css/purecss-menus-min.css')
add_stylesheet(req, 'janus/css/font-awesome.min.css')
add_script(req, 'janus/js/adapter.min.js')
add_script(req, 'janus/js/jquery.blockUI.min.js')
add_script(req, 'janus/js/jquery-confirm.min.js')
add_script(req, 'janus/js/purecss-menus.js')
add_script(req, 'janus/js/spin.min.js')
add_script(req, 'janus/js/compat.js')
add_script(req, 'janus/js/janus.js')
if (req.locale is not None):
add_script(req, 'janus/js/tracjanusgateway/{}.js'.format(req.locale))
if isinstance(req.remote_user, basestring):
username = req.remote_user
elif isinstance(req.authname, basestring):
username = req.authname
elif ('name' in req.session):
username = req.session.get('name', )
else:
username =
data['username'] = username
data['video_rooms'] = self.video_rooms
data['audio_rooms'] = self.audio_rooms
add_script_data(req, {'debug': req.args.get('debug', 'false'), 'event_uri': req.href.janus('event')})
if plugin.startswith('echo'):
add_ctxtnav(req, _('Echo'))
template = 'echo.html'
add_script(req, 'janus/js/echo.js')
else:
add_ctxtnav(req, _('Echo'), href=req.href.janus('echo'))
if plugin.startswith('videocall'):
add_ctxtnav(req, _('VideoCall'))
template = 'videocall.html'
add_script(req, 'janus/js/videocall.js')
add_script_data(req, {'avatar_url': req.href.avatar()})
else:
add_ctxtnav(req, _('VideoCall'), href=req.href.janus('videocall'))
if plugin.startswith('videoroom'):
add_ctxtnav(req, _('VideoRoom'))
template = 'videoroom.html'
add_script(req, 'janus/js/videoroom.js')
else:
add_ctxtnav(req, _('VideoRoom'), href=req.href.janus('videoroom'))
if plugin.startswith('audioroom'):
add_ctxtnav(req, _('AudioRoom'))
template = 'audioroom.html'
add_script(req, 'janus/js/audiobridge.js')
else:
add_ctxtnav(req, _('AudioRoom'), href=req.href.janus('audioroom'))
if plugin.startswith('screensharing'):
add_ctxtnav(req, _('ScreenSharing'))
template = 'screensharing.html'
add_script(req, 'janus/js/screensharing.js')
else:
add_ctxtnav(req, _('ScreenSharing'), href=req.href.janus('screensharing'))
add_stylesheet(req, 'janus/css/janus.css')
return (template, data, None)<|docstring|>Processing the plugin.<|endoftext|>
|
f027960704ae5e9ba5fc19489ad6a20392f895162af4438f57726f0f1527b9ca
|
def _ex_connection_class_kwargs(self):
'\n Add the region to the kwargs before the connection is instantiated\n '
kwargs = super(DimensionDataLBDriver, self)._ex_connection_class_kwargs()
kwargs['region'] = self.selected_region
return kwargs
|
Add the region to the kwargs before the connection is instantiated
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
_ex_connection_class_kwargs
|
gig-tech/libcloud
| 1,435 |
python
|
def _ex_connection_class_kwargs(self):
'\n \n '
kwargs = super(DimensionDataLBDriver, self)._ex_connection_class_kwargs()
kwargs['region'] = self.selected_region
return kwargs
|
def _ex_connection_class_kwargs(self):
'\n \n '
kwargs = super(DimensionDataLBDriver, self)._ex_connection_class_kwargs()
kwargs['region'] = self.selected_region
return kwargs<|docstring|>Add the region to the kwargs before the connection is instantiated<|endoftext|>
|
3ad5ed5f24226bb0e247961d6491d8d82114cf4e5834333cd23e7bef410e8ba9
|
def create_balancer(self, name, port=None, protocol=None, algorithm=None, members=None, ex_listener_ip_address=None):
"\n Create a new load balancer instance\n\n :param name: Name of the new load balancer (required)\n :type name: ``str``\n\n :param port: An integer in the range of 1-65535. If not supplied,\n it will be taken to mean 'Any Port'\n :type port: ``int``\n\n :param protocol: Loadbalancer protocol, defaults to http.\n :type protocol: ``str``\n\n :param members: list of Members to attach to balancer (optional)\n :type members: ``list`` of :class:`Member`\n\n :param algorithm: Load balancing algorithm, defaults to ROUND_ROBIN.\n :type algorithm: :class:`.Algorithm`\n\n :param ex_listener_ip_address: Must be a valid IPv4 in dot-decimal\n notation (x.x.x.x).\n :type ex_listener_ip_address: ``str``\n\n :rtype: :class:`LoadBalancer`\n "
network_domain_id = self.network_domain_id
if (protocol is None):
protocol = 'http'
if (algorithm is None):
algorithm = Algorithm.ROUND_ROBIN
pool = self.ex_create_pool(network_domain_id=network_domain_id, name=name, ex_description=None, balancer_method=self._ALGORITHM_TO_VALUE_MAP[algorithm])
if (members is not None):
for member in members:
node = self.ex_create_node(network_domain_id=network_domain_id, name=member.ip, ip=member.ip, ex_description=None)
self.ex_create_pool_member(pool=pool, node=node, port=port)
listener = self.ex_create_virtual_listener(network_domain_id=network_domain_id, name=name, ex_description=name, port=port, pool=pool, listener_ip_address=ex_listener_ip_address)
return LoadBalancer(id=listener.id, name=listener.name, state=State.RUNNING, ip=listener.ip, port=port, driver=self, extra={'pool_id': pool.id, 'network_domain_id': network_domain_id, 'listener_ip_address': ex_listener_ip_address})
|
Create a new load balancer instance
:param name: Name of the new load balancer (required)
:type name: ``str``
:param port: An integer in the range of 1-65535. If not supplied,
it will be taken to mean 'Any Port'
:type port: ``int``
:param protocol: Loadbalancer protocol, defaults to http.
:type protocol: ``str``
:param members: list of Members to attach to balancer (optional)
:type members: ``list`` of :class:`Member`
:param algorithm: Load balancing algorithm, defaults to ROUND_ROBIN.
:type algorithm: :class:`.Algorithm`
:param ex_listener_ip_address: Must be a valid IPv4 in dot-decimal
notation (x.x.x.x).
:type ex_listener_ip_address: ``str``
:rtype: :class:`LoadBalancer`
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
create_balancer
|
gig-tech/libcloud
| 1,435 |
python
|
def create_balancer(self, name, port=None, protocol=None, algorithm=None, members=None, ex_listener_ip_address=None):
"\n Create a new load balancer instance\n\n :param name: Name of the new load balancer (required)\n :type name: ``str``\n\n :param port: An integer in the range of 1-65535. If not supplied,\n it will be taken to mean 'Any Port'\n :type port: ``int``\n\n :param protocol: Loadbalancer protocol, defaults to http.\n :type protocol: ``str``\n\n :param members: list of Members to attach to balancer (optional)\n :type members: ``list`` of :class:`Member`\n\n :param algorithm: Load balancing algorithm, defaults to ROUND_ROBIN.\n :type algorithm: :class:`.Algorithm`\n\n :param ex_listener_ip_address: Must be a valid IPv4 in dot-decimal\n notation (x.x.x.x).\n :type ex_listener_ip_address: ``str``\n\n :rtype: :class:`LoadBalancer`\n "
network_domain_id = self.network_domain_id
if (protocol is None):
protocol = 'http'
if (algorithm is None):
algorithm = Algorithm.ROUND_ROBIN
pool = self.ex_create_pool(network_domain_id=network_domain_id, name=name, ex_description=None, balancer_method=self._ALGORITHM_TO_VALUE_MAP[algorithm])
if (members is not None):
for member in members:
node = self.ex_create_node(network_domain_id=network_domain_id, name=member.ip, ip=member.ip, ex_description=None)
self.ex_create_pool_member(pool=pool, node=node, port=port)
listener = self.ex_create_virtual_listener(network_domain_id=network_domain_id, name=name, ex_description=name, port=port, pool=pool, listener_ip_address=ex_listener_ip_address)
return LoadBalancer(id=listener.id, name=listener.name, state=State.RUNNING, ip=listener.ip, port=port, driver=self, extra={'pool_id': pool.id, 'network_domain_id': network_domain_id, 'listener_ip_address': ex_listener_ip_address})
|
def create_balancer(self, name, port=None, protocol=None, algorithm=None, members=None, ex_listener_ip_address=None):
"\n Create a new load balancer instance\n\n :param name: Name of the new load balancer (required)\n :type name: ``str``\n\n :param port: An integer in the range of 1-65535. If not supplied,\n it will be taken to mean 'Any Port'\n :type port: ``int``\n\n :param protocol: Loadbalancer protocol, defaults to http.\n :type protocol: ``str``\n\n :param members: list of Members to attach to balancer (optional)\n :type members: ``list`` of :class:`Member`\n\n :param algorithm: Load balancing algorithm, defaults to ROUND_ROBIN.\n :type algorithm: :class:`.Algorithm`\n\n :param ex_listener_ip_address: Must be a valid IPv4 in dot-decimal\n notation (x.x.x.x).\n :type ex_listener_ip_address: ``str``\n\n :rtype: :class:`LoadBalancer`\n "
network_domain_id = self.network_domain_id
if (protocol is None):
protocol = 'http'
if (algorithm is None):
algorithm = Algorithm.ROUND_ROBIN
pool = self.ex_create_pool(network_domain_id=network_domain_id, name=name, ex_description=None, balancer_method=self._ALGORITHM_TO_VALUE_MAP[algorithm])
if (members is not None):
for member in members:
node = self.ex_create_node(network_domain_id=network_domain_id, name=member.ip, ip=member.ip, ex_description=None)
self.ex_create_pool_member(pool=pool, node=node, port=port)
listener = self.ex_create_virtual_listener(network_domain_id=network_domain_id, name=name, ex_description=name, port=port, pool=pool, listener_ip_address=ex_listener_ip_address)
return LoadBalancer(id=listener.id, name=listener.name, state=State.RUNNING, ip=listener.ip, port=port, driver=self, extra={'pool_id': pool.id, 'network_domain_id': network_domain_id, 'listener_ip_address': ex_listener_ip_address})<|docstring|>Create a new load balancer instance
:param name: Name of the new load balancer (required)
:type name: ``str``
:param port: An integer in the range of 1-65535. If not supplied,
it will be taken to mean 'Any Port'
:type port: ``int``
:param protocol: Loadbalancer protocol, defaults to http.
:type protocol: ``str``
:param members: list of Members to attach to balancer (optional)
:type members: ``list`` of :class:`Member`
:param algorithm: Load balancing algorithm, defaults to ROUND_ROBIN.
:type algorithm: :class:`.Algorithm`
:param ex_listener_ip_address: Must be a valid IPv4 in dot-decimal
notation (x.x.x.x).
:type ex_listener_ip_address: ``str``
:rtype: :class:`LoadBalancer`<|endoftext|>
|
e44d2244d6c609fb677b2f427a725c2643b9b79b7e3ee1015a53a051230b94c4
|
def list_balancers(self, ex_network_domain_id=None):
'\n List all loadbalancers inside a geography or in given network.\n\n In Dimension Data terminology these are known as virtual listeners\n\n :param ex_network_domain_id: UUID of Network Domain\n if not None returns only balancers in the given network\n if None then returns all pools for the organization\n :type ex_network_domain_id: ``str``\n\n :rtype: ``list`` of :class:`LoadBalancer`\n '
params = None
if (ex_network_domain_id is not None):
params = {'networkDomainId': ex_network_domain_id}
return self._to_balancers(self.connection.request_with_orgId_api_2('networkDomainVip/virtualListener', params=params).object)
|
List all loadbalancers inside a geography or in given network.
In Dimension Data terminology these are known as virtual listeners
:param ex_network_domain_id: UUID of Network Domain
if not None returns only balancers in the given network
if None then returns all pools for the organization
:type ex_network_domain_id: ``str``
:rtype: ``list`` of :class:`LoadBalancer`
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
list_balancers
|
gig-tech/libcloud
| 1,435 |
python
|
def list_balancers(self, ex_network_domain_id=None):
'\n List all loadbalancers inside a geography or in given network.\n\n In Dimension Data terminology these are known as virtual listeners\n\n :param ex_network_domain_id: UUID of Network Domain\n if not None returns only balancers in the given network\n if None then returns all pools for the organization\n :type ex_network_domain_id: ``str``\n\n :rtype: ``list`` of :class:`LoadBalancer`\n '
params = None
if (ex_network_domain_id is not None):
params = {'networkDomainId': ex_network_domain_id}
return self._to_balancers(self.connection.request_with_orgId_api_2('networkDomainVip/virtualListener', params=params).object)
|
def list_balancers(self, ex_network_domain_id=None):
'\n List all loadbalancers inside a geography or in given network.\n\n In Dimension Data terminology these are known as virtual listeners\n\n :param ex_network_domain_id: UUID of Network Domain\n if not None returns only balancers in the given network\n if None then returns all pools for the organization\n :type ex_network_domain_id: ``str``\n\n :rtype: ``list`` of :class:`LoadBalancer`\n '
params = None
if (ex_network_domain_id is not None):
params = {'networkDomainId': ex_network_domain_id}
return self._to_balancers(self.connection.request_with_orgId_api_2('networkDomainVip/virtualListener', params=params).object)<|docstring|>List all loadbalancers inside a geography or in given network.
In Dimension Data terminology these are known as virtual listeners
:param ex_network_domain_id: UUID of Network Domain
if not None returns only balancers in the given network
if None then returns all pools for the organization
:type ex_network_domain_id: ``str``
:rtype: ``list`` of :class:`LoadBalancer`<|endoftext|>
|
dc82a569aa068e2f2ad29ec32900f5d59a6a8a87d756a576cbf4b6764aaa70b4
|
def get_balancer(self, balancer_id):
'\n Return a :class:`LoadBalancer` object.\n\n :param balancer_id: id of a load balancer you want to fetch\n :type balancer_id: ``str``\n\n :rtype: :class:`LoadBalancer`\n '
bal = self.connection.request_with_orgId_api_2(('networkDomainVip/virtualListener/%s' % balancer_id)).object
return self._to_balancer(bal)
|
Return a :class:`LoadBalancer` object.
:param balancer_id: id of a load balancer you want to fetch
:type balancer_id: ``str``
:rtype: :class:`LoadBalancer`
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
get_balancer
|
gig-tech/libcloud
| 1,435 |
python
|
def get_balancer(self, balancer_id):
'\n Return a :class:`LoadBalancer` object.\n\n :param balancer_id: id of a load balancer you want to fetch\n :type balancer_id: ``str``\n\n :rtype: :class:`LoadBalancer`\n '
bal = self.connection.request_with_orgId_api_2(('networkDomainVip/virtualListener/%s' % balancer_id)).object
return self._to_balancer(bal)
|
def get_balancer(self, balancer_id):
'\n Return a :class:`LoadBalancer` object.\n\n :param balancer_id: id of a load balancer you want to fetch\n :type balancer_id: ``str``\n\n :rtype: :class:`LoadBalancer`\n '
bal = self.connection.request_with_orgId_api_2(('networkDomainVip/virtualListener/%s' % balancer_id)).object
return self._to_balancer(bal)<|docstring|>Return a :class:`LoadBalancer` object.
:param balancer_id: id of a load balancer you want to fetch
:type balancer_id: ``str``
:rtype: :class:`LoadBalancer`<|endoftext|>
|
cdf78f52f24e739df3adc63af933389509455e644df1cf88faa90cace88c30d8
|
def list_protocols(self):
'\n Return a list of supported protocols.\n\n Since all protocols are support by Dimension Data, this is a list\n of common protocols.\n\n :rtype: ``list`` of ``str``\n '
return ['http', 'https', 'tcp', 'udp', 'ftp', 'smtp']
|
Return a list of supported protocols.
Since all protocols are support by Dimension Data, this is a list
of common protocols.
:rtype: ``list`` of ``str``
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
list_protocols
|
gig-tech/libcloud
| 1,435 |
python
|
def list_protocols(self):
'\n Return a list of supported protocols.\n\n Since all protocols are support by Dimension Data, this is a list\n of common protocols.\n\n :rtype: ``list`` of ``str``\n '
return ['http', 'https', 'tcp', 'udp', 'ftp', 'smtp']
|
def list_protocols(self):
'\n Return a list of supported protocols.\n\n Since all protocols are support by Dimension Data, this is a list\n of common protocols.\n\n :rtype: ``list`` of ``str``\n '
return ['http', 'https', 'tcp', 'udp', 'ftp', 'smtp']<|docstring|>Return a list of supported protocols.
Since all protocols are support by Dimension Data, this is a list
of common protocols.
:rtype: ``list`` of ``str``<|endoftext|>
|
14b4a3b180fd532a428a3ac3680cd64ce9be0bce30efd7eee8dba19233c69144
|
def balancer_list_members(self, balancer):
'\n Return list of members attached to balancer.\n\n In Dimension Data terminology these are the members of the pools\n within a virtual listener.\n\n :param balancer: LoadBalancer which should be used\n :type balancer: :class:`LoadBalancer`\n\n :rtype: ``list`` of :class:`Member`\n '
pool_members = self.ex_get_pool_members(balancer.extra['pool_id'])
members = []
for pool_member in pool_members:
members.append(Member(id=pool_member.id, ip=pool_member.ip, port=pool_member.port, balancer=balancer, extra=None))
return members
|
Return list of members attached to balancer.
In Dimension Data terminology these are the members of the pools
within a virtual listener.
:param balancer: LoadBalancer which should be used
:type balancer: :class:`LoadBalancer`
:rtype: ``list`` of :class:`Member`
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
balancer_list_members
|
gig-tech/libcloud
| 1,435 |
python
|
def balancer_list_members(self, balancer):
'\n Return list of members attached to balancer.\n\n In Dimension Data terminology these are the members of the pools\n within a virtual listener.\n\n :param balancer: LoadBalancer which should be used\n :type balancer: :class:`LoadBalancer`\n\n :rtype: ``list`` of :class:`Member`\n '
pool_members = self.ex_get_pool_members(balancer.extra['pool_id'])
members = []
for pool_member in pool_members:
members.append(Member(id=pool_member.id, ip=pool_member.ip, port=pool_member.port, balancer=balancer, extra=None))
return members
|
def balancer_list_members(self, balancer):
'\n Return list of members attached to balancer.\n\n In Dimension Data terminology these are the members of the pools\n within a virtual listener.\n\n :param balancer: LoadBalancer which should be used\n :type balancer: :class:`LoadBalancer`\n\n :rtype: ``list`` of :class:`Member`\n '
pool_members = self.ex_get_pool_members(balancer.extra['pool_id'])
members = []
for pool_member in pool_members:
members.append(Member(id=pool_member.id, ip=pool_member.ip, port=pool_member.port, balancer=balancer, extra=None))
return members<|docstring|>Return list of members attached to balancer.
In Dimension Data terminology these are the members of the pools
within a virtual listener.
:param balancer: LoadBalancer which should be used
:type balancer: :class:`LoadBalancer`
:rtype: ``list`` of :class:`Member`<|endoftext|>
|
520298df1364f7ae1cc2bb21c0edbee1bf0fec9148bbc8bfc9c856ed5f5e0e5c
|
def balancer_attach_member(self, balancer, member):
'\n Attach a member to balancer\n\n :param balancer: LoadBalancer which should be used\n :type balancer: :class:`LoadBalancer`\n\n :param member: Member to join to the balancer\n :type member: :class:`Member`\n\n :return: Member after joining the balancer.\n :rtype: :class:`Member`\n '
node = self.ex_create_node(network_domain_id=balancer.extra['network_domain_id'], name=('Member.' + member.ip), ip=member.ip, ex_description='')
if (node is False):
return False
pool = self.ex_get_pool(balancer.extra['pool_id'])
pool_member = self.ex_create_pool_member(pool=pool, node=node, port=member.port)
member.id = pool_member.id
return member
|
Attach a member to balancer
:param balancer: LoadBalancer which should be used
:type balancer: :class:`LoadBalancer`
:param member: Member to join to the balancer
:type member: :class:`Member`
:return: Member after joining the balancer.
:rtype: :class:`Member`
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
balancer_attach_member
|
gig-tech/libcloud
| 1,435 |
python
|
def balancer_attach_member(self, balancer, member):
'\n Attach a member to balancer\n\n :param balancer: LoadBalancer which should be used\n :type balancer: :class:`LoadBalancer`\n\n :param member: Member to join to the balancer\n :type member: :class:`Member`\n\n :return: Member after joining the balancer.\n :rtype: :class:`Member`\n '
node = self.ex_create_node(network_domain_id=balancer.extra['network_domain_id'], name=('Member.' + member.ip), ip=member.ip, ex_description=)
if (node is False):
return False
pool = self.ex_get_pool(balancer.extra['pool_id'])
pool_member = self.ex_create_pool_member(pool=pool, node=node, port=member.port)
member.id = pool_member.id
return member
|
def balancer_attach_member(self, balancer, member):
'\n Attach a member to balancer\n\n :param balancer: LoadBalancer which should be used\n :type balancer: :class:`LoadBalancer`\n\n :param member: Member to join to the balancer\n :type member: :class:`Member`\n\n :return: Member after joining the balancer.\n :rtype: :class:`Member`\n '
node = self.ex_create_node(network_domain_id=balancer.extra['network_domain_id'], name=('Member.' + member.ip), ip=member.ip, ex_description=)
if (node is False):
return False
pool = self.ex_get_pool(balancer.extra['pool_id'])
pool_member = self.ex_create_pool_member(pool=pool, node=node, port=member.port)
member.id = pool_member.id
return member<|docstring|>Attach a member to balancer
:param balancer: LoadBalancer which should be used
:type balancer: :class:`LoadBalancer`
:param member: Member to join to the balancer
:type member: :class:`Member`
:return: Member after joining the balancer.
:rtype: :class:`Member`<|endoftext|>
|
60c419c95ccda9db52003660fb1464e53f23c9ecbf2a7705e9d687262a678889
|
def balancer_detach_member(self, balancer, member):
'\n Detach member from balancer\n\n :param balancer: LoadBalancer which should be used\n :type balancer: :class:`LoadBalancer`\n\n :param member: Member which should be used\n :type member: :class:`Member`\n\n :return: ``True`` if member detach was successful, otherwise ``False``.\n :rtype: ``bool``\n '
create_pool_m = ET.Element('removePoolMember', {'xmlns': TYPES_URN, 'id': member.id})
result = self.connection.request_with_orgId_api_2('networkDomainVip/removePoolMember', method='POST', data=ET.tostring(create_pool_m)).object
response_code = findtext(result, 'responseCode', TYPES_URN)
return (response_code in ['IN_PROGRESS', 'OK'])
|
Detach member from balancer
:param balancer: LoadBalancer which should be used
:type balancer: :class:`LoadBalancer`
:param member: Member which should be used
:type member: :class:`Member`
:return: ``True`` if member detach was successful, otherwise ``False``.
:rtype: ``bool``
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
balancer_detach_member
|
gig-tech/libcloud
| 1,435 |
python
|
def balancer_detach_member(self, balancer, member):
'\n Detach member from balancer\n\n :param balancer: LoadBalancer which should be used\n :type balancer: :class:`LoadBalancer`\n\n :param member: Member which should be used\n :type member: :class:`Member`\n\n :return: ``True`` if member detach was successful, otherwise ``False``.\n :rtype: ``bool``\n '
create_pool_m = ET.Element('removePoolMember', {'xmlns': TYPES_URN, 'id': member.id})
result = self.connection.request_with_orgId_api_2('networkDomainVip/removePoolMember', method='POST', data=ET.tostring(create_pool_m)).object
response_code = findtext(result, 'responseCode', TYPES_URN)
return (response_code in ['IN_PROGRESS', 'OK'])
|
def balancer_detach_member(self, balancer, member):
'\n Detach member from balancer\n\n :param balancer: LoadBalancer which should be used\n :type balancer: :class:`LoadBalancer`\n\n :param member: Member which should be used\n :type member: :class:`Member`\n\n :return: ``True`` if member detach was successful, otherwise ``False``.\n :rtype: ``bool``\n '
create_pool_m = ET.Element('removePoolMember', {'xmlns': TYPES_URN, 'id': member.id})
result = self.connection.request_with_orgId_api_2('networkDomainVip/removePoolMember', method='POST', data=ET.tostring(create_pool_m)).object
response_code = findtext(result, 'responseCode', TYPES_URN)
return (response_code in ['IN_PROGRESS', 'OK'])<|docstring|>Detach member from balancer
:param balancer: LoadBalancer which should be used
:type balancer: :class:`LoadBalancer`
:param member: Member which should be used
:type member: :class:`Member`
:return: ``True`` if member detach was successful, otherwise ``False``.
:rtype: ``bool``<|endoftext|>
|
ac9b4d70ff7bc837e60c1172822f6d24a434b82d344388c18614f0b10c6471c6
|
def destroy_balancer(self, balancer):
'\n Destroy a load balancer (virtual listener)\n\n :param balancer: LoadBalancer which should be used\n :type balancer: :class:`LoadBalancer`\n\n :return: ``True`` if the destroy was successful, otherwise ``False``.\n :rtype: ``bool``\n '
delete_listener = ET.Element('deleteVirtualListener', {'xmlns': TYPES_URN, 'id': balancer.id})
result = self.connection.request_with_orgId_api_2('networkDomainVip/deleteVirtualListener', method='POST', data=ET.tostring(delete_listener)).object
response_code = findtext(result, 'responseCode', TYPES_URN)
return (response_code in ['IN_PROGRESS', 'OK'])
|
Destroy a load balancer (virtual listener)
:param balancer: LoadBalancer which should be used
:type balancer: :class:`LoadBalancer`
:return: ``True`` if the destroy was successful, otherwise ``False``.
:rtype: ``bool``
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
destroy_balancer
|
gig-tech/libcloud
| 1,435 |
python
|
def destroy_balancer(self, balancer):
'\n Destroy a load balancer (virtual listener)\n\n :param balancer: LoadBalancer which should be used\n :type balancer: :class:`LoadBalancer`\n\n :return: ``True`` if the destroy was successful, otherwise ``False``.\n :rtype: ``bool``\n '
delete_listener = ET.Element('deleteVirtualListener', {'xmlns': TYPES_URN, 'id': balancer.id})
result = self.connection.request_with_orgId_api_2('networkDomainVip/deleteVirtualListener', method='POST', data=ET.tostring(delete_listener)).object
response_code = findtext(result, 'responseCode', TYPES_URN)
return (response_code in ['IN_PROGRESS', 'OK'])
|
def destroy_balancer(self, balancer):
'\n Destroy a load balancer (virtual listener)\n\n :param balancer: LoadBalancer which should be used\n :type balancer: :class:`LoadBalancer`\n\n :return: ``True`` if the destroy was successful, otherwise ``False``.\n :rtype: ``bool``\n '
delete_listener = ET.Element('deleteVirtualListener', {'xmlns': TYPES_URN, 'id': balancer.id})
result = self.connection.request_with_orgId_api_2('networkDomainVip/deleteVirtualListener', method='POST', data=ET.tostring(delete_listener)).object
response_code = findtext(result, 'responseCode', TYPES_URN)
return (response_code in ['IN_PROGRESS', 'OK'])<|docstring|>Destroy a load balancer (virtual listener)
:param balancer: LoadBalancer which should be used
:type balancer: :class:`LoadBalancer`
:return: ``True`` if the destroy was successful, otherwise ``False``.
:rtype: ``bool``<|endoftext|>
|
c552f41a067657dd2ba71455461bf6192bee98263f170284709e2b84cfc8f6e3
|
def ex_set_current_network_domain(self, network_domain_id):
'\n Set the network domain (part of the network) of the driver\n\n :param network_domain_id: ID of the pool (required)\n :type network_domain_id: ``str``\n '
self.network_domain_id = network_domain_id
|
Set the network domain (part of the network) of the driver
:param network_domain_id: ID of the pool (required)
:type network_domain_id: ``str``
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_set_current_network_domain
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_set_current_network_domain(self, network_domain_id):
'\n Set the network domain (part of the network) of the driver\n\n :param network_domain_id: ID of the pool (required)\n :type network_domain_id: ``str``\n '
self.network_domain_id = network_domain_id
|
def ex_set_current_network_domain(self, network_domain_id):
'\n Set the network domain (part of the network) of the driver\n\n :param network_domain_id: ID of the pool (required)\n :type network_domain_id: ``str``\n '
self.network_domain_id = network_domain_id<|docstring|>Set the network domain (part of the network) of the driver
:param network_domain_id: ID of the pool (required)
:type network_domain_id: ``str``<|endoftext|>
|
cf40f134f88b6d3fdb071028843e5bdf327498833c00247442f13717181220da
|
def ex_get_current_network_domain(self):
'\n Get the current network domain ID of the driver.\n\n :return: ID of the network domain\n :rtype: ``str``\n '
return self.network_domain_id
|
Get the current network domain ID of the driver.
:return: ID of the network domain
:rtype: ``str``
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_get_current_network_domain
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_get_current_network_domain(self):
'\n Get the current network domain ID of the driver.\n\n :return: ID of the network domain\n :rtype: ``str``\n '
return self.network_domain_id
|
def ex_get_current_network_domain(self):
'\n Get the current network domain ID of the driver.\n\n :return: ID of the network domain\n :rtype: ``str``\n '
return self.network_domain_id<|docstring|>Get the current network domain ID of the driver.
:return: ID of the network domain
:rtype: ``str``<|endoftext|>
|
228537ec9de290a68b3c39f193f014ffe67814a65551020f1869d09c7884eeaa
|
def ex_create_pool_member(self, pool, node, port=None):
'\n Create a new member in an existing pool from an existing node\n\n :param pool: Instance of ``DimensionDataPool`` (required)\n :type pool: ``DimensionDataPool``\n\n :param node: Instance of ``DimensionDataVIPNode`` (required)\n :type node: ``DimensionDataVIPNode``\n\n :param port: Port the the service will listen on\n :type port: ``str``\n\n :return: The node member, instance of ``DimensionDataPoolMember``\n :rtype: ``DimensionDataPoolMember``\n '
create_pool_m = ET.Element('addPoolMember', {'xmlns': TYPES_URN})
ET.SubElement(create_pool_m, 'poolId').text = pool.id
ET.SubElement(create_pool_m, 'nodeId').text = node.id
if (port is not None):
ET.SubElement(create_pool_m, 'port').text = str(port)
ET.SubElement(create_pool_m, 'status').text = 'ENABLED'
response = self.connection.request_with_orgId_api_2('networkDomainVip/addPoolMember', method='POST', data=ET.tostring(create_pool_m)).object
member_id = None
node_name = None
for info in findall(response, 'info', TYPES_URN):
if (info.get('name') == 'poolMemberId'):
member_id = info.get('value')
if (info.get('name') == 'nodeName'):
node_name = info.get('value')
return DimensionDataPoolMember(id=member_id, name=node_name, status=State.RUNNING, ip=node.ip, port=port, node_id=node.id)
|
Create a new member in an existing pool from an existing node
:param pool: Instance of ``DimensionDataPool`` (required)
:type pool: ``DimensionDataPool``
:param node: Instance of ``DimensionDataVIPNode`` (required)
:type node: ``DimensionDataVIPNode``
:param port: Port the the service will listen on
:type port: ``str``
:return: The node member, instance of ``DimensionDataPoolMember``
:rtype: ``DimensionDataPoolMember``
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_create_pool_member
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_create_pool_member(self, pool, node, port=None):
'\n Create a new member in an existing pool from an existing node\n\n :param pool: Instance of ``DimensionDataPool`` (required)\n :type pool: ``DimensionDataPool``\n\n :param node: Instance of ``DimensionDataVIPNode`` (required)\n :type node: ``DimensionDataVIPNode``\n\n :param port: Port the the service will listen on\n :type port: ``str``\n\n :return: The node member, instance of ``DimensionDataPoolMember``\n :rtype: ``DimensionDataPoolMember``\n '
create_pool_m = ET.Element('addPoolMember', {'xmlns': TYPES_URN})
ET.SubElement(create_pool_m, 'poolId').text = pool.id
ET.SubElement(create_pool_m, 'nodeId').text = node.id
if (port is not None):
ET.SubElement(create_pool_m, 'port').text = str(port)
ET.SubElement(create_pool_m, 'status').text = 'ENABLED'
response = self.connection.request_with_orgId_api_2('networkDomainVip/addPoolMember', method='POST', data=ET.tostring(create_pool_m)).object
member_id = None
node_name = None
for info in findall(response, 'info', TYPES_URN):
if (info.get('name') == 'poolMemberId'):
member_id = info.get('value')
if (info.get('name') == 'nodeName'):
node_name = info.get('value')
return DimensionDataPoolMember(id=member_id, name=node_name, status=State.RUNNING, ip=node.ip, port=port, node_id=node.id)
|
def ex_create_pool_member(self, pool, node, port=None):
'\n Create a new member in an existing pool from an existing node\n\n :param pool: Instance of ``DimensionDataPool`` (required)\n :type pool: ``DimensionDataPool``\n\n :param node: Instance of ``DimensionDataVIPNode`` (required)\n :type node: ``DimensionDataVIPNode``\n\n :param port: Port the the service will listen on\n :type port: ``str``\n\n :return: The node member, instance of ``DimensionDataPoolMember``\n :rtype: ``DimensionDataPoolMember``\n '
create_pool_m = ET.Element('addPoolMember', {'xmlns': TYPES_URN})
ET.SubElement(create_pool_m, 'poolId').text = pool.id
ET.SubElement(create_pool_m, 'nodeId').text = node.id
if (port is not None):
ET.SubElement(create_pool_m, 'port').text = str(port)
ET.SubElement(create_pool_m, 'status').text = 'ENABLED'
response = self.connection.request_with_orgId_api_2('networkDomainVip/addPoolMember', method='POST', data=ET.tostring(create_pool_m)).object
member_id = None
node_name = None
for info in findall(response, 'info', TYPES_URN):
if (info.get('name') == 'poolMemberId'):
member_id = info.get('value')
if (info.get('name') == 'nodeName'):
node_name = info.get('value')
return DimensionDataPoolMember(id=member_id, name=node_name, status=State.RUNNING, ip=node.ip, port=port, node_id=node.id)<|docstring|>Create a new member in an existing pool from an existing node
:param pool: Instance of ``DimensionDataPool`` (required)
:type pool: ``DimensionDataPool``
:param node: Instance of ``DimensionDataVIPNode`` (required)
:type node: ``DimensionDataVIPNode``
:param port: Port the the service will listen on
:type port: ``str``
:return: The node member, instance of ``DimensionDataPoolMember``
:rtype: ``DimensionDataPoolMember``<|endoftext|>
|
dbf4d47d40dcef6eaa1fba64f7665af8bbd42bec5067255b81833998eb88ed27
|
def ex_create_node(self, network_domain_id, name, ip, ex_description, connection_limit=25000, connection_rate_limit=2000):
'\n Create a new node\n\n :param network_domain_id: Network Domain ID (required)\n :type name: ``str``\n\n :param name: name of the node (required)\n :type name: ``str``\n\n :param ip: IPv4 address of the node (required)\n :type ip: ``str``\n\n :param ex_description: Description of the node (required)\n :type ex_description: ``str``\n\n :param connection_limit: Maximum number\n of concurrent connections per sec\n :type connection_limit: ``int``\n\n :param connection_rate_limit: Maximum number of concurrent sessions\n :type connection_rate_limit: ``int``\n\n :return: Instance of ``DimensionDataVIPNode``\n :rtype: ``DimensionDataVIPNode``\n '
create_node_elm = ET.Element('createNode', {'xmlns': TYPES_URN})
ET.SubElement(create_node_elm, 'networkDomainId').text = network_domain_id
ET.SubElement(create_node_elm, 'name').text = name
ET.SubElement(create_node_elm, 'description').text = str(ex_description)
ET.SubElement(create_node_elm, 'ipv4Address').text = ip
ET.SubElement(create_node_elm, 'status').text = 'ENABLED'
ET.SubElement(create_node_elm, 'connectionLimit').text = str(connection_limit)
ET.SubElement(create_node_elm, 'connectionRateLimit').text = str(connection_rate_limit)
response = self.connection.request_with_orgId_api_2(action='networkDomainVip/createNode', method='POST', data=ET.tostring(create_node_elm)).object
node_id = None
node_name = None
for info in findall(response, 'info', TYPES_URN):
if (info.get('name') == 'nodeId'):
node_id = info.get('value')
if (info.get('name') == 'name'):
node_name = info.get('value')
return DimensionDataVIPNode(id=node_id, name=node_name, status=State.RUNNING, ip=ip)
|
Create a new node
:param network_domain_id: Network Domain ID (required)
:type name: ``str``
:param name: name of the node (required)
:type name: ``str``
:param ip: IPv4 address of the node (required)
:type ip: ``str``
:param ex_description: Description of the node (required)
:type ex_description: ``str``
:param connection_limit: Maximum number
of concurrent connections per sec
:type connection_limit: ``int``
:param connection_rate_limit: Maximum number of concurrent sessions
:type connection_rate_limit: ``int``
:return: Instance of ``DimensionDataVIPNode``
:rtype: ``DimensionDataVIPNode``
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_create_node
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_create_node(self, network_domain_id, name, ip, ex_description, connection_limit=25000, connection_rate_limit=2000):
'\n Create a new node\n\n :param network_domain_id: Network Domain ID (required)\n :type name: ``str``\n\n :param name: name of the node (required)\n :type name: ``str``\n\n :param ip: IPv4 address of the node (required)\n :type ip: ``str``\n\n :param ex_description: Description of the node (required)\n :type ex_description: ``str``\n\n :param connection_limit: Maximum number\n of concurrent connections per sec\n :type connection_limit: ``int``\n\n :param connection_rate_limit: Maximum number of concurrent sessions\n :type connection_rate_limit: ``int``\n\n :return: Instance of ``DimensionDataVIPNode``\n :rtype: ``DimensionDataVIPNode``\n '
create_node_elm = ET.Element('createNode', {'xmlns': TYPES_URN})
ET.SubElement(create_node_elm, 'networkDomainId').text = network_domain_id
ET.SubElement(create_node_elm, 'name').text = name
ET.SubElement(create_node_elm, 'description').text = str(ex_description)
ET.SubElement(create_node_elm, 'ipv4Address').text = ip
ET.SubElement(create_node_elm, 'status').text = 'ENABLED'
ET.SubElement(create_node_elm, 'connectionLimit').text = str(connection_limit)
ET.SubElement(create_node_elm, 'connectionRateLimit').text = str(connection_rate_limit)
response = self.connection.request_with_orgId_api_2(action='networkDomainVip/createNode', method='POST', data=ET.tostring(create_node_elm)).object
node_id = None
node_name = None
for info in findall(response, 'info', TYPES_URN):
if (info.get('name') == 'nodeId'):
node_id = info.get('value')
if (info.get('name') == 'name'):
node_name = info.get('value')
return DimensionDataVIPNode(id=node_id, name=node_name, status=State.RUNNING, ip=ip)
|
def ex_create_node(self, network_domain_id, name, ip, ex_description, connection_limit=25000, connection_rate_limit=2000):
'\n Create a new node\n\n :param network_domain_id: Network Domain ID (required)\n :type name: ``str``\n\n :param name: name of the node (required)\n :type name: ``str``\n\n :param ip: IPv4 address of the node (required)\n :type ip: ``str``\n\n :param ex_description: Description of the node (required)\n :type ex_description: ``str``\n\n :param connection_limit: Maximum number\n of concurrent connections per sec\n :type connection_limit: ``int``\n\n :param connection_rate_limit: Maximum number of concurrent sessions\n :type connection_rate_limit: ``int``\n\n :return: Instance of ``DimensionDataVIPNode``\n :rtype: ``DimensionDataVIPNode``\n '
create_node_elm = ET.Element('createNode', {'xmlns': TYPES_URN})
ET.SubElement(create_node_elm, 'networkDomainId').text = network_domain_id
ET.SubElement(create_node_elm, 'name').text = name
ET.SubElement(create_node_elm, 'description').text = str(ex_description)
ET.SubElement(create_node_elm, 'ipv4Address').text = ip
ET.SubElement(create_node_elm, 'status').text = 'ENABLED'
ET.SubElement(create_node_elm, 'connectionLimit').text = str(connection_limit)
ET.SubElement(create_node_elm, 'connectionRateLimit').text = str(connection_rate_limit)
response = self.connection.request_with_orgId_api_2(action='networkDomainVip/createNode', method='POST', data=ET.tostring(create_node_elm)).object
node_id = None
node_name = None
for info in findall(response, 'info', TYPES_URN):
if (info.get('name') == 'nodeId'):
node_id = info.get('value')
if (info.get('name') == 'name'):
node_name = info.get('value')
return DimensionDataVIPNode(id=node_id, name=node_name, status=State.RUNNING, ip=ip)<|docstring|>Create a new node
:param network_domain_id: Network Domain ID (required)
:type name: ``str``
:param name: name of the node (required)
:type name: ``str``
:param ip: IPv4 address of the node (required)
:type ip: ``str``
:param ex_description: Description of the node (required)
:type ex_description: ``str``
:param connection_limit: Maximum number
of concurrent connections per sec
:type connection_limit: ``int``
:param connection_rate_limit: Maximum number of concurrent sessions
:type connection_rate_limit: ``int``
:return: Instance of ``DimensionDataVIPNode``
:rtype: ``DimensionDataVIPNode``<|endoftext|>
|
29641b25face12efe1bf553a27e31d69de4093fb9277cb83d551bf6557dbb4a5
|
def ex_update_node(self, node):
'\n Update the properties of a node\n\n :param pool: The instance of ``DimensionDataNode`` to update\n :type pool: ``DimensionDataNode``\n\n :return: The instance of ``DimensionDataNode``\n :rtype: ``DimensionDataNode``\n '
create_node_elm = ET.Element('editNode', {'xmlns': TYPES_URN})
ET.SubElement(create_node_elm, 'connectionLimit').text = str(node.connection_limit)
ET.SubElement(create_node_elm, 'connectionRateLimit').text = str(node.connection_rate_limit)
self.connection.request_with_orgId_api_2(action='networkDomainVip/createNode', method='POST', data=ET.tostring(create_node_elm)).object
return node
|
Update the properties of a node
:param pool: The instance of ``DimensionDataNode`` to update
:type pool: ``DimensionDataNode``
:return: The instance of ``DimensionDataNode``
:rtype: ``DimensionDataNode``
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_update_node
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_update_node(self, node):
'\n Update the properties of a node\n\n :param pool: The instance of ``DimensionDataNode`` to update\n :type pool: ``DimensionDataNode``\n\n :return: The instance of ``DimensionDataNode``\n :rtype: ``DimensionDataNode``\n '
create_node_elm = ET.Element('editNode', {'xmlns': TYPES_URN})
ET.SubElement(create_node_elm, 'connectionLimit').text = str(node.connection_limit)
ET.SubElement(create_node_elm, 'connectionRateLimit').text = str(node.connection_rate_limit)
self.connection.request_with_orgId_api_2(action='networkDomainVip/createNode', method='POST', data=ET.tostring(create_node_elm)).object
return node
|
def ex_update_node(self, node):
'\n Update the properties of a node\n\n :param pool: The instance of ``DimensionDataNode`` to update\n :type pool: ``DimensionDataNode``\n\n :return: The instance of ``DimensionDataNode``\n :rtype: ``DimensionDataNode``\n '
create_node_elm = ET.Element('editNode', {'xmlns': TYPES_URN})
ET.SubElement(create_node_elm, 'connectionLimit').text = str(node.connection_limit)
ET.SubElement(create_node_elm, 'connectionRateLimit').text = str(node.connection_rate_limit)
self.connection.request_with_orgId_api_2(action='networkDomainVip/createNode', method='POST', data=ET.tostring(create_node_elm)).object
return node<|docstring|>Update the properties of a node
:param pool: The instance of ``DimensionDataNode`` to update
:type pool: ``DimensionDataNode``
:return: The instance of ``DimensionDataNode``
:rtype: ``DimensionDataNode``<|endoftext|>
|
3ed7edcc5502022308f675568e252f6e8966240fe43130deb1de6f7c9d703d16
|
def ex_set_node_state(self, node, enabled):
'\n Change the state of a node (enable/disable)\n\n :param pool: The instance of ``DimensionDataNode`` to update\n :type pool: ``DimensionDataNode``\n\n :param enabled: The target state of the node\n :type enabled: ``bool``\n\n :return: The instance of ``DimensionDataNode``\n :rtype: ``DimensionDataNode``\n '
create_node_elm = ET.Element('editNode', {'xmlns': TYPES_URN})
ET.SubElement(create_node_elm, 'status').text = ('ENABLED' if (enabled is True) else 'DISABLED')
self.connection.request_with_orgId_api_2(action='networkDomainVip/editNode', method='POST', data=ET.tostring(create_node_elm)).object
return node
|
Change the state of a node (enable/disable)
:param pool: The instance of ``DimensionDataNode`` to update
:type pool: ``DimensionDataNode``
:param enabled: The target state of the node
:type enabled: ``bool``
:return: The instance of ``DimensionDataNode``
:rtype: ``DimensionDataNode``
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_set_node_state
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_set_node_state(self, node, enabled):
'\n Change the state of a node (enable/disable)\n\n :param pool: The instance of ``DimensionDataNode`` to update\n :type pool: ``DimensionDataNode``\n\n :param enabled: The target state of the node\n :type enabled: ``bool``\n\n :return: The instance of ``DimensionDataNode``\n :rtype: ``DimensionDataNode``\n '
create_node_elm = ET.Element('editNode', {'xmlns': TYPES_URN})
ET.SubElement(create_node_elm, 'status').text = ('ENABLED' if (enabled is True) else 'DISABLED')
self.connection.request_with_orgId_api_2(action='networkDomainVip/editNode', method='POST', data=ET.tostring(create_node_elm)).object
return node
|
def ex_set_node_state(self, node, enabled):
'\n Change the state of a node (enable/disable)\n\n :param pool: The instance of ``DimensionDataNode`` to update\n :type pool: ``DimensionDataNode``\n\n :param enabled: The target state of the node\n :type enabled: ``bool``\n\n :return: The instance of ``DimensionDataNode``\n :rtype: ``DimensionDataNode``\n '
create_node_elm = ET.Element('editNode', {'xmlns': TYPES_URN})
ET.SubElement(create_node_elm, 'status').text = ('ENABLED' if (enabled is True) else 'DISABLED')
self.connection.request_with_orgId_api_2(action='networkDomainVip/editNode', method='POST', data=ET.tostring(create_node_elm)).object
return node<|docstring|>Change the state of a node (enable/disable)
:param pool: The instance of ``DimensionDataNode`` to update
:type pool: ``DimensionDataNode``
:param enabled: The target state of the node
:type enabled: ``bool``
:return: The instance of ``DimensionDataNode``
:rtype: ``DimensionDataNode``<|endoftext|>
|
4a0711f1dff730e693b5fd5156003d03645fe29bd3d7a63d1ac185d79934c471
|
def ex_create_pool(self, network_domain_id, name, balancer_method, ex_description, health_monitors=None, service_down_action='NONE', slow_ramp_time=30):
'\n Create a new pool\n\n :param network_domain_id: Network Domain ID (required)\n :type name: ``str``\n\n :param name: name of the node (required)\n :type name: ``str``\n\n :param balancer_method: The load balancer algorithm (required)\n :type balancer_method: ``str``\n\n :param ex_description: Description of the node (required)\n :type ex_description: ``str``\n\n :param health_monitors: A list of health monitors to use for the pool.\n :type health_monitors: ``list`` of\n :class:`DimensionDataDefaultHealthMonitor`\n\n :param service_down_action: What to do when node\n is unavailable NONE, DROP or RESELECT\n :type service_down_action: ``str``\n\n :param slow_ramp_time: Number of seconds to stagger ramp up of nodes\n :type slow_ramp_time: ``int``\n\n :return: Instance of ``DimensionDataPool``\n :rtype: ``DimensionDataPool``\n '
name.replace(' ', '_')
create_node_elm = ET.Element('createPool', {'xmlns': TYPES_URN})
ET.SubElement(create_node_elm, 'networkDomainId').text = network_domain_id
ET.SubElement(create_node_elm, 'name').text = name
ET.SubElement(create_node_elm, 'description').text = str(ex_description)
ET.SubElement(create_node_elm, 'loadBalanceMethod').text = str(balancer_method)
if (health_monitors is not None):
for monitor in health_monitors:
ET.SubElement(create_node_elm, 'healthMonitorId').text = str(monitor.id)
ET.SubElement(create_node_elm, 'serviceDownAction').text = service_down_action
ET.SubElement(create_node_elm, 'slowRampTime').text = str(slow_ramp_time)
response = self.connection.request_with_orgId_api_2(action='networkDomainVip/createPool', method='POST', data=ET.tostring(create_node_elm)).object
pool_id = None
for info in findall(response, 'info', TYPES_URN):
if (info.get('name') == 'poolId'):
pool_id = info.get('value')
return DimensionDataPool(id=pool_id, name=name, description=ex_description, status=State.RUNNING, load_balance_method=str(balancer_method), health_monitor_id=None, service_down_action=service_down_action, slow_ramp_time=str(slow_ramp_time))
|
Create a new pool
:param network_domain_id: Network Domain ID (required)
:type name: ``str``
:param name: name of the node (required)
:type name: ``str``
:param balancer_method: The load balancer algorithm (required)
:type balancer_method: ``str``
:param ex_description: Description of the node (required)
:type ex_description: ``str``
:param health_monitors: A list of health monitors to use for the pool.
:type health_monitors: ``list`` of
:class:`DimensionDataDefaultHealthMonitor`
:param service_down_action: What to do when node
is unavailable NONE, DROP or RESELECT
:type service_down_action: ``str``
:param slow_ramp_time: Number of seconds to stagger ramp up of nodes
:type slow_ramp_time: ``int``
:return: Instance of ``DimensionDataPool``
:rtype: ``DimensionDataPool``
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_create_pool
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_create_pool(self, network_domain_id, name, balancer_method, ex_description, health_monitors=None, service_down_action='NONE', slow_ramp_time=30):
'\n Create a new pool\n\n :param network_domain_id: Network Domain ID (required)\n :type name: ``str``\n\n :param name: name of the node (required)\n :type name: ``str``\n\n :param balancer_method: The load balancer algorithm (required)\n :type balancer_method: ``str``\n\n :param ex_description: Description of the node (required)\n :type ex_description: ``str``\n\n :param health_monitors: A list of health monitors to use for the pool.\n :type health_monitors: ``list`` of\n :class:`DimensionDataDefaultHealthMonitor`\n\n :param service_down_action: What to do when node\n is unavailable NONE, DROP or RESELECT\n :type service_down_action: ``str``\n\n :param slow_ramp_time: Number of seconds to stagger ramp up of nodes\n :type slow_ramp_time: ``int``\n\n :return: Instance of ``DimensionDataPool``\n :rtype: ``DimensionDataPool``\n '
name.replace(' ', '_')
create_node_elm = ET.Element('createPool', {'xmlns': TYPES_URN})
ET.SubElement(create_node_elm, 'networkDomainId').text = network_domain_id
ET.SubElement(create_node_elm, 'name').text = name
ET.SubElement(create_node_elm, 'description').text = str(ex_description)
ET.SubElement(create_node_elm, 'loadBalanceMethod').text = str(balancer_method)
if (health_monitors is not None):
for monitor in health_monitors:
ET.SubElement(create_node_elm, 'healthMonitorId').text = str(monitor.id)
ET.SubElement(create_node_elm, 'serviceDownAction').text = service_down_action
ET.SubElement(create_node_elm, 'slowRampTime').text = str(slow_ramp_time)
response = self.connection.request_with_orgId_api_2(action='networkDomainVip/createPool', method='POST', data=ET.tostring(create_node_elm)).object
pool_id = None
for info in findall(response, 'info', TYPES_URN):
if (info.get('name') == 'poolId'):
pool_id = info.get('value')
return DimensionDataPool(id=pool_id, name=name, description=ex_description, status=State.RUNNING, load_balance_method=str(balancer_method), health_monitor_id=None, service_down_action=service_down_action, slow_ramp_time=str(slow_ramp_time))
|
def ex_create_pool(self, network_domain_id, name, balancer_method, ex_description, health_monitors=None, service_down_action='NONE', slow_ramp_time=30):
'\n Create a new pool\n\n :param network_domain_id: Network Domain ID (required)\n :type name: ``str``\n\n :param name: name of the node (required)\n :type name: ``str``\n\n :param balancer_method: The load balancer algorithm (required)\n :type balancer_method: ``str``\n\n :param ex_description: Description of the node (required)\n :type ex_description: ``str``\n\n :param health_monitors: A list of health monitors to use for the pool.\n :type health_monitors: ``list`` of\n :class:`DimensionDataDefaultHealthMonitor`\n\n :param service_down_action: What to do when node\n is unavailable NONE, DROP or RESELECT\n :type service_down_action: ``str``\n\n :param slow_ramp_time: Number of seconds to stagger ramp up of nodes\n :type slow_ramp_time: ``int``\n\n :return: Instance of ``DimensionDataPool``\n :rtype: ``DimensionDataPool``\n '
name.replace(' ', '_')
create_node_elm = ET.Element('createPool', {'xmlns': TYPES_URN})
ET.SubElement(create_node_elm, 'networkDomainId').text = network_domain_id
ET.SubElement(create_node_elm, 'name').text = name
ET.SubElement(create_node_elm, 'description').text = str(ex_description)
ET.SubElement(create_node_elm, 'loadBalanceMethod').text = str(balancer_method)
if (health_monitors is not None):
for monitor in health_monitors:
ET.SubElement(create_node_elm, 'healthMonitorId').text = str(monitor.id)
ET.SubElement(create_node_elm, 'serviceDownAction').text = service_down_action
ET.SubElement(create_node_elm, 'slowRampTime').text = str(slow_ramp_time)
response = self.connection.request_with_orgId_api_2(action='networkDomainVip/createPool', method='POST', data=ET.tostring(create_node_elm)).object
pool_id = None
for info in findall(response, 'info', TYPES_URN):
if (info.get('name') == 'poolId'):
pool_id = info.get('value')
return DimensionDataPool(id=pool_id, name=name, description=ex_description, status=State.RUNNING, load_balance_method=str(balancer_method), health_monitor_id=None, service_down_action=service_down_action, slow_ramp_time=str(slow_ramp_time))<|docstring|>Create a new pool
:param network_domain_id: Network Domain ID (required)
:type name: ``str``
:param name: name of the node (required)
:type name: ``str``
:param balancer_method: The load balancer algorithm (required)
:type balancer_method: ``str``
:param ex_description: Description of the node (required)
:type ex_description: ``str``
:param health_monitors: A list of health monitors to use for the pool.
:type health_monitors: ``list`` of
:class:`DimensionDataDefaultHealthMonitor`
:param service_down_action: What to do when node
is unavailable NONE, DROP or RESELECT
:type service_down_action: ``str``
:param slow_ramp_time: Number of seconds to stagger ramp up of nodes
:type slow_ramp_time: ``int``
:return: Instance of ``DimensionDataPool``
:rtype: ``DimensionDataPool``<|endoftext|>
|
694d3207c7ea03fd85d73f76999c4b9ebc2e6d792ce436ae7b33c990dd76eb0e
|
def ex_create_virtual_listener(self, network_domain_id, name, ex_description, port=None, pool=None, listener_ip_address=None, persistence_profile=None, fallback_persistence_profile=None, irule=None, protocol='TCP', connection_limit=25000, connection_rate_limit=2000, source_port_preservation='PRESERVE'):
"\n Create a new virtual listener (load balancer)\n\n :param network_domain_id: Network Domain ID (required)\n :type name: ``str``\n\n :param name: name of the listener (required)\n :type name: ``str``\n\n :param ex_description: Description of the node (required)\n :type ex_description: ``str``\n\n :param port: An integer in the range of 1-65535. If not supplied,\n it will be taken to mean 'Any Port'\n :type port: ``int``\n\n :param pool: The pool to use for the listener\n :type pool: :class:`DimensionDataPool`\n\n :param listener_ip_address: The IPv4 Address of the virtual listener\n :type listener_ip_address: ``str``\n\n :param persistence_profile: Persistence profile\n :type persistence_profile: :class:`DimensionDataPersistenceProfile`\n\n :param fallback_persistence_profile: Fallback persistence profile\n :type fallback_persistence_profile:\n :class:`DimensionDataPersistenceProfile`\n\n :param irule: The iRule to apply\n :type irule: :class:`DimensionDataDefaultiRule`\n\n :param protocol: For STANDARD type, ANY, TCP or UDP\n for PERFORMANCE_LAYER_4 choice of ANY, TCP, UDP, HTTP\n :type protcol: ``str``\n\n :param connection_limit: Maximum number\n of concurrent connections per sec\n :type connection_limit: ``int``\n\n :param connection_rate_limit: Maximum number of concurrent sessions\n :type connection_rate_limit: ``int``\n\n :param source_port_preservation: Choice of PRESERVE,\n PRESERVE_STRICT or CHANGE\n :type source_port_preservation: ``str``\n\n :return: Instance of the listener\n :rtype: ``DimensionDataVirtualListener``\n "
if ((port == 80) or (port == 443)):
listener_type = 'PERFORMANCE_LAYER_4'
else:
listener_type = 'STANDARD'
create_node_elm = ET.Element('createVirtualListener', {'xmlns': TYPES_URN})
ET.SubElement(create_node_elm, 'networkDomainId').text = network_domain_id
ET.SubElement(create_node_elm, 'name').text = name
ET.SubElement(create_node_elm, 'description').text = str(ex_description)
ET.SubElement(create_node_elm, 'type').text = listener_type
ET.SubElement(create_node_elm, 'protocol').text = protocol
if (listener_ip_address is not None):
ET.SubElement(create_node_elm, 'listenerIpAddress').text = str(listener_ip_address)
if (port is not None):
ET.SubElement(create_node_elm, 'port').text = str(port)
ET.SubElement(create_node_elm, 'enabled').text = 'true'
ET.SubElement(create_node_elm, 'connectionLimit').text = str(connection_limit)
ET.SubElement(create_node_elm, 'connectionRateLimit').text = str(connection_rate_limit)
ET.SubElement(create_node_elm, 'sourcePortPreservation').text = source_port_preservation
if (pool is not None):
ET.SubElement(create_node_elm, 'poolId').text = pool.id
if (persistence_profile is not None):
ET.SubElement(create_node_elm, 'persistenceProfileId').text = persistence_profile.id
if (fallback_persistence_profile is not None):
ET.SubElement(create_node_elm, 'fallbackPersistenceProfileId').text = fallback_persistence_profile.id
if (irule is not None):
ET.SubElement(create_node_elm, 'iruleId').text = irule.id
response = self.connection.request_with_orgId_api_2(action='networkDomainVip/createVirtualListener', method='POST', data=ET.tostring(create_node_elm)).object
virtual_listener_id = None
virtual_listener_ip = None
for info in findall(response, 'info', TYPES_URN):
if (info.get('name') == 'virtualListenerId'):
virtual_listener_id = info.get('value')
if (info.get('name') == 'listenerIpAddress'):
virtual_listener_ip = info.get('value')
return DimensionDataVirtualListener(id=virtual_listener_id, name=name, ip=virtual_listener_ip, status=State.RUNNING)
|
Create a new virtual listener (load balancer)
:param network_domain_id: Network Domain ID (required)
:type name: ``str``
:param name: name of the listener (required)
:type name: ``str``
:param ex_description: Description of the node (required)
:type ex_description: ``str``
:param port: An integer in the range of 1-65535. If not supplied,
it will be taken to mean 'Any Port'
:type port: ``int``
:param pool: The pool to use for the listener
:type pool: :class:`DimensionDataPool`
:param listener_ip_address: The IPv4 Address of the virtual listener
:type listener_ip_address: ``str``
:param persistence_profile: Persistence profile
:type persistence_profile: :class:`DimensionDataPersistenceProfile`
:param fallback_persistence_profile: Fallback persistence profile
:type fallback_persistence_profile:
:class:`DimensionDataPersistenceProfile`
:param irule: The iRule to apply
:type irule: :class:`DimensionDataDefaultiRule`
:param protocol: For STANDARD type, ANY, TCP or UDP
for PERFORMANCE_LAYER_4 choice of ANY, TCP, UDP, HTTP
:type protcol: ``str``
:param connection_limit: Maximum number
of concurrent connections per sec
:type connection_limit: ``int``
:param connection_rate_limit: Maximum number of concurrent sessions
:type connection_rate_limit: ``int``
:param source_port_preservation: Choice of PRESERVE,
PRESERVE_STRICT or CHANGE
:type source_port_preservation: ``str``
:return: Instance of the listener
:rtype: ``DimensionDataVirtualListener``
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_create_virtual_listener
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_create_virtual_listener(self, network_domain_id, name, ex_description, port=None, pool=None, listener_ip_address=None, persistence_profile=None, fallback_persistence_profile=None, irule=None, protocol='TCP', connection_limit=25000, connection_rate_limit=2000, source_port_preservation='PRESERVE'):
"\n Create a new virtual listener (load balancer)\n\n :param network_domain_id: Network Domain ID (required)\n :type name: ``str``\n\n :param name: name of the listener (required)\n :type name: ``str``\n\n :param ex_description: Description of the node (required)\n :type ex_description: ``str``\n\n :param port: An integer in the range of 1-65535. If not supplied,\n it will be taken to mean 'Any Port'\n :type port: ``int``\n\n :param pool: The pool to use for the listener\n :type pool: :class:`DimensionDataPool`\n\n :param listener_ip_address: The IPv4 Address of the virtual listener\n :type listener_ip_address: ``str``\n\n :param persistence_profile: Persistence profile\n :type persistence_profile: :class:`DimensionDataPersistenceProfile`\n\n :param fallback_persistence_profile: Fallback persistence profile\n :type fallback_persistence_profile:\n :class:`DimensionDataPersistenceProfile`\n\n :param irule: The iRule to apply\n :type irule: :class:`DimensionDataDefaultiRule`\n\n :param protocol: For STANDARD type, ANY, TCP or UDP\n for PERFORMANCE_LAYER_4 choice of ANY, TCP, UDP, HTTP\n :type protcol: ``str``\n\n :param connection_limit: Maximum number\n of concurrent connections per sec\n :type connection_limit: ``int``\n\n :param connection_rate_limit: Maximum number of concurrent sessions\n :type connection_rate_limit: ``int``\n\n :param source_port_preservation: Choice of PRESERVE,\n PRESERVE_STRICT or CHANGE\n :type source_port_preservation: ``str``\n\n :return: Instance of the listener\n :rtype: ``DimensionDataVirtualListener``\n "
if ((port == 80) or (port == 443)):
listener_type = 'PERFORMANCE_LAYER_4'
else:
listener_type = 'STANDARD'
create_node_elm = ET.Element('createVirtualListener', {'xmlns': TYPES_URN})
ET.SubElement(create_node_elm, 'networkDomainId').text = network_domain_id
ET.SubElement(create_node_elm, 'name').text = name
ET.SubElement(create_node_elm, 'description').text = str(ex_description)
ET.SubElement(create_node_elm, 'type').text = listener_type
ET.SubElement(create_node_elm, 'protocol').text = protocol
if (listener_ip_address is not None):
ET.SubElement(create_node_elm, 'listenerIpAddress').text = str(listener_ip_address)
if (port is not None):
ET.SubElement(create_node_elm, 'port').text = str(port)
ET.SubElement(create_node_elm, 'enabled').text = 'true'
ET.SubElement(create_node_elm, 'connectionLimit').text = str(connection_limit)
ET.SubElement(create_node_elm, 'connectionRateLimit').text = str(connection_rate_limit)
ET.SubElement(create_node_elm, 'sourcePortPreservation').text = source_port_preservation
if (pool is not None):
ET.SubElement(create_node_elm, 'poolId').text = pool.id
if (persistence_profile is not None):
ET.SubElement(create_node_elm, 'persistenceProfileId').text = persistence_profile.id
if (fallback_persistence_profile is not None):
ET.SubElement(create_node_elm, 'fallbackPersistenceProfileId').text = fallback_persistence_profile.id
if (irule is not None):
ET.SubElement(create_node_elm, 'iruleId').text = irule.id
response = self.connection.request_with_orgId_api_2(action='networkDomainVip/createVirtualListener', method='POST', data=ET.tostring(create_node_elm)).object
virtual_listener_id = None
virtual_listener_ip = None
for info in findall(response, 'info', TYPES_URN):
if (info.get('name') == 'virtualListenerId'):
virtual_listener_id = info.get('value')
if (info.get('name') == 'listenerIpAddress'):
virtual_listener_ip = info.get('value')
return DimensionDataVirtualListener(id=virtual_listener_id, name=name, ip=virtual_listener_ip, status=State.RUNNING)
|
def ex_create_virtual_listener(self, network_domain_id, name, ex_description, port=None, pool=None, listener_ip_address=None, persistence_profile=None, fallback_persistence_profile=None, irule=None, protocol='TCP', connection_limit=25000, connection_rate_limit=2000, source_port_preservation='PRESERVE'):
"\n Create a new virtual listener (load balancer)\n\n :param network_domain_id: Network Domain ID (required)\n :type name: ``str``\n\n :param name: name of the listener (required)\n :type name: ``str``\n\n :param ex_description: Description of the node (required)\n :type ex_description: ``str``\n\n :param port: An integer in the range of 1-65535. If not supplied,\n it will be taken to mean 'Any Port'\n :type port: ``int``\n\n :param pool: The pool to use for the listener\n :type pool: :class:`DimensionDataPool`\n\n :param listener_ip_address: The IPv4 Address of the virtual listener\n :type listener_ip_address: ``str``\n\n :param persistence_profile: Persistence profile\n :type persistence_profile: :class:`DimensionDataPersistenceProfile`\n\n :param fallback_persistence_profile: Fallback persistence profile\n :type fallback_persistence_profile:\n :class:`DimensionDataPersistenceProfile`\n\n :param irule: The iRule to apply\n :type irule: :class:`DimensionDataDefaultiRule`\n\n :param protocol: For STANDARD type, ANY, TCP or UDP\n for PERFORMANCE_LAYER_4 choice of ANY, TCP, UDP, HTTP\n :type protcol: ``str``\n\n :param connection_limit: Maximum number\n of concurrent connections per sec\n :type connection_limit: ``int``\n\n :param connection_rate_limit: Maximum number of concurrent sessions\n :type connection_rate_limit: ``int``\n\n :param source_port_preservation: Choice of PRESERVE,\n PRESERVE_STRICT or CHANGE\n :type source_port_preservation: ``str``\n\n :return: Instance of the listener\n :rtype: ``DimensionDataVirtualListener``\n "
if ((port == 80) or (port == 443)):
listener_type = 'PERFORMANCE_LAYER_4'
else:
listener_type = 'STANDARD'
create_node_elm = ET.Element('createVirtualListener', {'xmlns': TYPES_URN})
ET.SubElement(create_node_elm, 'networkDomainId').text = network_domain_id
ET.SubElement(create_node_elm, 'name').text = name
ET.SubElement(create_node_elm, 'description').text = str(ex_description)
ET.SubElement(create_node_elm, 'type').text = listener_type
ET.SubElement(create_node_elm, 'protocol').text = protocol
if (listener_ip_address is not None):
ET.SubElement(create_node_elm, 'listenerIpAddress').text = str(listener_ip_address)
if (port is not None):
ET.SubElement(create_node_elm, 'port').text = str(port)
ET.SubElement(create_node_elm, 'enabled').text = 'true'
ET.SubElement(create_node_elm, 'connectionLimit').text = str(connection_limit)
ET.SubElement(create_node_elm, 'connectionRateLimit').text = str(connection_rate_limit)
ET.SubElement(create_node_elm, 'sourcePortPreservation').text = source_port_preservation
if (pool is not None):
ET.SubElement(create_node_elm, 'poolId').text = pool.id
if (persistence_profile is not None):
ET.SubElement(create_node_elm, 'persistenceProfileId').text = persistence_profile.id
if (fallback_persistence_profile is not None):
ET.SubElement(create_node_elm, 'fallbackPersistenceProfileId').text = fallback_persistence_profile.id
if (irule is not None):
ET.SubElement(create_node_elm, 'iruleId').text = irule.id
response = self.connection.request_with_orgId_api_2(action='networkDomainVip/createVirtualListener', method='POST', data=ET.tostring(create_node_elm)).object
virtual_listener_id = None
virtual_listener_ip = None
for info in findall(response, 'info', TYPES_URN):
if (info.get('name') == 'virtualListenerId'):
virtual_listener_id = info.get('value')
if (info.get('name') == 'listenerIpAddress'):
virtual_listener_ip = info.get('value')
return DimensionDataVirtualListener(id=virtual_listener_id, name=name, ip=virtual_listener_ip, status=State.RUNNING)<|docstring|>Create a new virtual listener (load balancer)
:param network_domain_id: Network Domain ID (required)
:type name: ``str``
:param name: name of the listener (required)
:type name: ``str``
:param ex_description: Description of the node (required)
:type ex_description: ``str``
:param port: An integer in the range of 1-65535. If not supplied,
it will be taken to mean 'Any Port'
:type port: ``int``
:param pool: The pool to use for the listener
:type pool: :class:`DimensionDataPool`
:param listener_ip_address: The IPv4 Address of the virtual listener
:type listener_ip_address: ``str``
:param persistence_profile: Persistence profile
:type persistence_profile: :class:`DimensionDataPersistenceProfile`
:param fallback_persistence_profile: Fallback persistence profile
:type fallback_persistence_profile:
:class:`DimensionDataPersistenceProfile`
:param irule: The iRule to apply
:type irule: :class:`DimensionDataDefaultiRule`
:param protocol: For STANDARD type, ANY, TCP or UDP
for PERFORMANCE_LAYER_4 choice of ANY, TCP, UDP, HTTP
:type protcol: ``str``
:param connection_limit: Maximum number
of concurrent connections per sec
:type connection_limit: ``int``
:param connection_rate_limit: Maximum number of concurrent sessions
:type connection_rate_limit: ``int``
:param source_port_preservation: Choice of PRESERVE,
PRESERVE_STRICT or CHANGE
:type source_port_preservation: ``str``
:return: Instance of the listener
:rtype: ``DimensionDataVirtualListener``<|endoftext|>
|
eb1adcd6851919c7ef18c5f7de97ff447944e319b85eb27a49169bcbc0e1e3ef
|
def ex_get_pools(self, ex_network_domain_id=None):
'\n Get all of the pools inside the current geography or\n in given network.\n\n :param ex_network_domain_id: UUID of Network Domain\n if not None returns only balancers in the given network\n if None then returns all pools for the organization\n :type ex_network_domain_id: ``str``\n\n :return: Returns a ``list`` of type ``DimensionDataPool``\n :rtype: ``list`` of ``DimensionDataPool``\n '
params = None
if (ex_network_domain_id is not None):
params = {'networkDomainId': ex_network_domain_id}
pools = self.connection.request_with_orgId_api_2('networkDomainVip/pool', params=params).object
return self._to_pools(pools)
|
Get all of the pools inside the current geography or
in given network.
:param ex_network_domain_id: UUID of Network Domain
if not None returns only balancers in the given network
if None then returns all pools for the organization
:type ex_network_domain_id: ``str``
:return: Returns a ``list`` of type ``DimensionDataPool``
:rtype: ``list`` of ``DimensionDataPool``
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_get_pools
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_get_pools(self, ex_network_domain_id=None):
'\n Get all of the pools inside the current geography or\n in given network.\n\n :param ex_network_domain_id: UUID of Network Domain\n if not None returns only balancers in the given network\n if None then returns all pools for the organization\n :type ex_network_domain_id: ``str``\n\n :return: Returns a ``list`` of type ``DimensionDataPool``\n :rtype: ``list`` of ``DimensionDataPool``\n '
params = None
if (ex_network_domain_id is not None):
params = {'networkDomainId': ex_network_domain_id}
pools = self.connection.request_with_orgId_api_2('networkDomainVip/pool', params=params).object
return self._to_pools(pools)
|
def ex_get_pools(self, ex_network_domain_id=None):
'\n Get all of the pools inside the current geography or\n in given network.\n\n :param ex_network_domain_id: UUID of Network Domain\n if not None returns only balancers in the given network\n if None then returns all pools for the organization\n :type ex_network_domain_id: ``str``\n\n :return: Returns a ``list`` of type ``DimensionDataPool``\n :rtype: ``list`` of ``DimensionDataPool``\n '
params = None
if (ex_network_domain_id is not None):
params = {'networkDomainId': ex_network_domain_id}
pools = self.connection.request_with_orgId_api_2('networkDomainVip/pool', params=params).object
return self._to_pools(pools)<|docstring|>Get all of the pools inside the current geography or
in given network.
:param ex_network_domain_id: UUID of Network Domain
if not None returns only balancers in the given network
if None then returns all pools for the organization
:type ex_network_domain_id: ``str``
:return: Returns a ``list`` of type ``DimensionDataPool``
:rtype: ``list`` of ``DimensionDataPool``<|endoftext|>
|
3f1d49d5951ef18577b178ddf013863baef6d52a0173f5026078ccfc2a261c85
|
def ex_get_pool(self, pool_id):
'\n Get a specific pool inside the current geography\n\n :param pool_id: The identifier of the pool\n :type pool_id: ``str``\n\n :return: Returns an instance of ``DimensionDataPool``\n :rtype: ``DimensionDataPool``\n '
pool = self.connection.request_with_orgId_api_2(('networkDomainVip/pool/%s' % pool_id)).object
return self._to_pool(pool)
|
Get a specific pool inside the current geography
:param pool_id: The identifier of the pool
:type pool_id: ``str``
:return: Returns an instance of ``DimensionDataPool``
:rtype: ``DimensionDataPool``
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_get_pool
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_get_pool(self, pool_id):
'\n Get a specific pool inside the current geography\n\n :param pool_id: The identifier of the pool\n :type pool_id: ``str``\n\n :return: Returns an instance of ``DimensionDataPool``\n :rtype: ``DimensionDataPool``\n '
pool = self.connection.request_with_orgId_api_2(('networkDomainVip/pool/%s' % pool_id)).object
return self._to_pool(pool)
|
def ex_get_pool(self, pool_id):
'\n Get a specific pool inside the current geography\n\n :param pool_id: The identifier of the pool\n :type pool_id: ``str``\n\n :return: Returns an instance of ``DimensionDataPool``\n :rtype: ``DimensionDataPool``\n '
pool = self.connection.request_with_orgId_api_2(('networkDomainVip/pool/%s' % pool_id)).object
return self._to_pool(pool)<|docstring|>Get a specific pool inside the current geography
:param pool_id: The identifier of the pool
:type pool_id: ``str``
:return: Returns an instance of ``DimensionDataPool``
:rtype: ``DimensionDataPool``<|endoftext|>
|
28cc9667b997d4fd1774a97f7a4d76d978267d7407fb0f447f5c3d01b82397c4
|
def ex_update_pool(self, pool):
'\n Update the properties of an existing pool\n only method, serviceDownAction and slowRampTime are updated\n\n :param pool: The instance of ``DimensionDataPool`` to update\n :type pool: ``DimensionDataPool``\n\n :return: ``True`` for success, ``False`` for failure\n :rtype: ``bool``\n '
create_node_elm = ET.Element('editPool', {'xmlns': TYPES_URN})
ET.SubElement(create_node_elm, 'loadBalanceMethod').text = str(pool.load_balance_method)
ET.SubElement(create_node_elm, 'serviceDownAction').text = pool.service_down_action
ET.SubElement(create_node_elm, 'slowRampTime').text = str(pool.slow_ramp_time)
response = self.connection.request_with_orgId_api_2(action='networkDomainVip/editPool', method='POST', data=ET.tostring(create_node_elm)).object
response_code = findtext(response, 'responseCode', TYPES_URN)
return (response_code in ['IN_PROGRESS', 'OK'])
|
Update the properties of an existing pool
only method, serviceDownAction and slowRampTime are updated
:param pool: The instance of ``DimensionDataPool`` to update
:type pool: ``DimensionDataPool``
:return: ``True`` for success, ``False`` for failure
:rtype: ``bool``
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_update_pool
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_update_pool(self, pool):
'\n Update the properties of an existing pool\n only method, serviceDownAction and slowRampTime are updated\n\n :param pool: The instance of ``DimensionDataPool`` to update\n :type pool: ``DimensionDataPool``\n\n :return: ``True`` for success, ``False`` for failure\n :rtype: ``bool``\n '
create_node_elm = ET.Element('editPool', {'xmlns': TYPES_URN})
ET.SubElement(create_node_elm, 'loadBalanceMethod').text = str(pool.load_balance_method)
ET.SubElement(create_node_elm, 'serviceDownAction').text = pool.service_down_action
ET.SubElement(create_node_elm, 'slowRampTime').text = str(pool.slow_ramp_time)
response = self.connection.request_with_orgId_api_2(action='networkDomainVip/editPool', method='POST', data=ET.tostring(create_node_elm)).object
response_code = findtext(response, 'responseCode', TYPES_URN)
return (response_code in ['IN_PROGRESS', 'OK'])
|
def ex_update_pool(self, pool):
'\n Update the properties of an existing pool\n only method, serviceDownAction and slowRampTime are updated\n\n :param pool: The instance of ``DimensionDataPool`` to update\n :type pool: ``DimensionDataPool``\n\n :return: ``True`` for success, ``False`` for failure\n :rtype: ``bool``\n '
create_node_elm = ET.Element('editPool', {'xmlns': TYPES_URN})
ET.SubElement(create_node_elm, 'loadBalanceMethod').text = str(pool.load_balance_method)
ET.SubElement(create_node_elm, 'serviceDownAction').text = pool.service_down_action
ET.SubElement(create_node_elm, 'slowRampTime').text = str(pool.slow_ramp_time)
response = self.connection.request_with_orgId_api_2(action='networkDomainVip/editPool', method='POST', data=ET.tostring(create_node_elm)).object
response_code = findtext(response, 'responseCode', TYPES_URN)
return (response_code in ['IN_PROGRESS', 'OK'])<|docstring|>Update the properties of an existing pool
only method, serviceDownAction and slowRampTime are updated
:param pool: The instance of ``DimensionDataPool`` to update
:type pool: ``DimensionDataPool``
:return: ``True`` for success, ``False`` for failure
:rtype: ``bool``<|endoftext|>
|
3da36720c64440cb046b01a117bef95024389f85f98d37db39bd76c3047ba26d
|
def ex_destroy_pool(self, pool):
'\n Destroy an existing pool\n\n :param pool: The instance of ``DimensionDataPool`` to destroy\n :type pool: ``DimensionDataPool``\n\n :return: ``True`` for success, ``False`` for failure\n :rtype: ``bool``\n '
destroy_request = ET.Element('deletePool', {'xmlns': TYPES_URN, 'id': pool.id})
result = self.connection.request_with_orgId_api_2(action='networkDomainVip/deletePool', method='POST', data=ET.tostring(destroy_request)).object
response_code = findtext(result, 'responseCode', TYPES_URN)
return (response_code in ['IN_PROGRESS', 'OK'])
|
Destroy an existing pool
:param pool: The instance of ``DimensionDataPool`` to destroy
:type pool: ``DimensionDataPool``
:return: ``True`` for success, ``False`` for failure
:rtype: ``bool``
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_destroy_pool
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_destroy_pool(self, pool):
'\n Destroy an existing pool\n\n :param pool: The instance of ``DimensionDataPool`` to destroy\n :type pool: ``DimensionDataPool``\n\n :return: ``True`` for success, ``False`` for failure\n :rtype: ``bool``\n '
destroy_request = ET.Element('deletePool', {'xmlns': TYPES_URN, 'id': pool.id})
result = self.connection.request_with_orgId_api_2(action='networkDomainVip/deletePool', method='POST', data=ET.tostring(destroy_request)).object
response_code = findtext(result, 'responseCode', TYPES_URN)
return (response_code in ['IN_PROGRESS', 'OK'])
|
def ex_destroy_pool(self, pool):
'\n Destroy an existing pool\n\n :param pool: The instance of ``DimensionDataPool`` to destroy\n :type pool: ``DimensionDataPool``\n\n :return: ``True`` for success, ``False`` for failure\n :rtype: ``bool``\n '
destroy_request = ET.Element('deletePool', {'xmlns': TYPES_URN, 'id': pool.id})
result = self.connection.request_with_orgId_api_2(action='networkDomainVip/deletePool', method='POST', data=ET.tostring(destroy_request)).object
response_code = findtext(result, 'responseCode', TYPES_URN)
return (response_code in ['IN_PROGRESS', 'OK'])<|docstring|>Destroy an existing pool
:param pool: The instance of ``DimensionDataPool`` to destroy
:type pool: ``DimensionDataPool``
:return: ``True`` for success, ``False`` for failure
:rtype: ``bool``<|endoftext|>
|
36c98b9aaf37acb5b6656daf8225609091ae4c68783af3e254a8b7a32fda5aa0
|
def ex_get_pool_members(self, pool_id):
'\n Get the members of a pool\n\n :param pool: The instance of a pool\n :type pool: ``DimensionDataPool``\n\n :return: Returns an ``list`` of ``DimensionDataPoolMember``\n :rtype: ``list`` of ``DimensionDataPoolMember``\n '
members = self.connection.request_with_orgId_api_2(('networkDomainVip/poolMember?poolId=%s' % pool_id)).object
return self._to_members(members)
|
Get the members of a pool
:param pool: The instance of a pool
:type pool: ``DimensionDataPool``
:return: Returns an ``list`` of ``DimensionDataPoolMember``
:rtype: ``list`` of ``DimensionDataPoolMember``
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_get_pool_members
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_get_pool_members(self, pool_id):
'\n Get the members of a pool\n\n :param pool: The instance of a pool\n :type pool: ``DimensionDataPool``\n\n :return: Returns an ``list`` of ``DimensionDataPoolMember``\n :rtype: ``list`` of ``DimensionDataPoolMember``\n '
members = self.connection.request_with_orgId_api_2(('networkDomainVip/poolMember?poolId=%s' % pool_id)).object
return self._to_members(members)
|
def ex_get_pool_members(self, pool_id):
'\n Get the members of a pool\n\n :param pool: The instance of a pool\n :type pool: ``DimensionDataPool``\n\n :return: Returns an ``list`` of ``DimensionDataPoolMember``\n :rtype: ``list`` of ``DimensionDataPoolMember``\n '
members = self.connection.request_with_orgId_api_2(('networkDomainVip/poolMember?poolId=%s' % pool_id)).object
return self._to_members(members)<|docstring|>Get the members of a pool
:param pool: The instance of a pool
:type pool: ``DimensionDataPool``
:return: Returns an ``list`` of ``DimensionDataPoolMember``
:rtype: ``list`` of ``DimensionDataPoolMember``<|endoftext|>
|
559266c9224d537d920fdb190353060d37eb2a7c0a26f126c68c724e5e26b4bb
|
def ex_get_pool_member(self, pool_member_id):
'\n Get a specific member of a pool\n\n :param pool: The id of a pool member\n :type pool: ``str``\n\n :return: Returns an instance of ``DimensionDataPoolMember``\n :rtype: ``DimensionDataPoolMember``\n '
member = self.connection.request_with_orgId_api_2(('networkDomainVip/poolMember/%s' % pool_member_id)).object
return self._to_member(member)
|
Get a specific member of a pool
:param pool: The id of a pool member
:type pool: ``str``
:return: Returns an instance of ``DimensionDataPoolMember``
:rtype: ``DimensionDataPoolMember``
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_get_pool_member
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_get_pool_member(self, pool_member_id):
'\n Get a specific member of a pool\n\n :param pool: The id of a pool member\n :type pool: ``str``\n\n :return: Returns an instance of ``DimensionDataPoolMember``\n :rtype: ``DimensionDataPoolMember``\n '
member = self.connection.request_with_orgId_api_2(('networkDomainVip/poolMember/%s' % pool_member_id)).object
return self._to_member(member)
|
def ex_get_pool_member(self, pool_member_id):
'\n Get a specific member of a pool\n\n :param pool: The id of a pool member\n :type pool: ``str``\n\n :return: Returns an instance of ``DimensionDataPoolMember``\n :rtype: ``DimensionDataPoolMember``\n '
member = self.connection.request_with_orgId_api_2(('networkDomainVip/poolMember/%s' % pool_member_id)).object
return self._to_member(member)<|docstring|>Get a specific member of a pool
:param pool: The id of a pool member
:type pool: ``str``
:return: Returns an instance of ``DimensionDataPoolMember``
:rtype: ``DimensionDataPoolMember``<|endoftext|>
|
82a71a9d78a39e8a1c5ad8aa824603a81342b405c4057124c54181bcb20e622c
|
def ex_destroy_pool_member(self, member, destroy_node=False):
'\n Destroy a specific member of a pool\n\n :param pool: The instance of a pool member\n :type pool: ``DimensionDataPoolMember``\n\n :param destroy_node: Also destroy the associated node\n :type destroy_node: ``bool``\n\n :return: ``True`` for success, ``False`` for failure\n :rtype: ``bool``\n '
destroy_request = ET.Element('removePoolMember', {'xmlns': TYPES_URN, 'id': member.id})
result = self.connection.request_with_orgId_api_2(action='networkDomainVip/removePoolMember', method='POST', data=ET.tostring(destroy_request)).object
if ((member.node_id is not None) and (destroy_node is True)):
return self.ex_destroy_node(member.node_id)
else:
response_code = findtext(result, 'responseCode', TYPES_URN)
return (response_code in ['IN_PROGRESS', 'OK'])
|
Destroy a specific member of a pool
:param pool: The instance of a pool member
:type pool: ``DimensionDataPoolMember``
:param destroy_node: Also destroy the associated node
:type destroy_node: ``bool``
:return: ``True`` for success, ``False`` for failure
:rtype: ``bool``
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_destroy_pool_member
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_destroy_pool_member(self, member, destroy_node=False):
'\n Destroy a specific member of a pool\n\n :param pool: The instance of a pool member\n :type pool: ``DimensionDataPoolMember``\n\n :param destroy_node: Also destroy the associated node\n :type destroy_node: ``bool``\n\n :return: ``True`` for success, ``False`` for failure\n :rtype: ``bool``\n '
destroy_request = ET.Element('removePoolMember', {'xmlns': TYPES_URN, 'id': member.id})
result = self.connection.request_with_orgId_api_2(action='networkDomainVip/removePoolMember', method='POST', data=ET.tostring(destroy_request)).object
if ((member.node_id is not None) and (destroy_node is True)):
return self.ex_destroy_node(member.node_id)
else:
response_code = findtext(result, 'responseCode', TYPES_URN)
return (response_code in ['IN_PROGRESS', 'OK'])
|
def ex_destroy_pool_member(self, member, destroy_node=False):
'\n Destroy a specific member of a pool\n\n :param pool: The instance of a pool member\n :type pool: ``DimensionDataPoolMember``\n\n :param destroy_node: Also destroy the associated node\n :type destroy_node: ``bool``\n\n :return: ``True`` for success, ``False`` for failure\n :rtype: ``bool``\n '
destroy_request = ET.Element('removePoolMember', {'xmlns': TYPES_URN, 'id': member.id})
result = self.connection.request_with_orgId_api_2(action='networkDomainVip/removePoolMember', method='POST', data=ET.tostring(destroy_request)).object
if ((member.node_id is not None) and (destroy_node is True)):
return self.ex_destroy_node(member.node_id)
else:
response_code = findtext(result, 'responseCode', TYPES_URN)
return (response_code in ['IN_PROGRESS', 'OK'])<|docstring|>Destroy a specific member of a pool
:param pool: The instance of a pool member
:type pool: ``DimensionDataPoolMember``
:param destroy_node: Also destroy the associated node
:type destroy_node: ``bool``
:return: ``True`` for success, ``False`` for failure
:rtype: ``bool``<|endoftext|>
|
293a9fd962dafa0a2a4fbf8ef9da3d4b5693867639cdeccf01dc07ad4e7697e8
|
def ex_get_nodes(self, ex_network_domain_id=None):
'\n Get the nodes within this geography or in given network.\n\n :param ex_network_domain_id: UUID of Network Domain\n if not None returns only balancers in the given network\n if None then returns all pools for the organization\n :type ex_network_domain_id: ``str``\n\n :return: Returns an ``list`` of ``DimensionDataVIPNode``\n :rtype: ``list`` of ``DimensionDataVIPNode``\n '
params = None
if (ex_network_domain_id is not None):
params = {'networkDomainId': ex_network_domain_id}
nodes = self.connection.request_with_orgId_api_2('networkDomainVip/node', params=params).object
return self._to_nodes(nodes)
|
Get the nodes within this geography or in given network.
:param ex_network_domain_id: UUID of Network Domain
if not None returns only balancers in the given network
if None then returns all pools for the organization
:type ex_network_domain_id: ``str``
:return: Returns an ``list`` of ``DimensionDataVIPNode``
:rtype: ``list`` of ``DimensionDataVIPNode``
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_get_nodes
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_get_nodes(self, ex_network_domain_id=None):
'\n Get the nodes within this geography or in given network.\n\n :param ex_network_domain_id: UUID of Network Domain\n if not None returns only balancers in the given network\n if None then returns all pools for the organization\n :type ex_network_domain_id: ``str``\n\n :return: Returns an ``list`` of ``DimensionDataVIPNode``\n :rtype: ``list`` of ``DimensionDataVIPNode``\n '
params = None
if (ex_network_domain_id is not None):
params = {'networkDomainId': ex_network_domain_id}
nodes = self.connection.request_with_orgId_api_2('networkDomainVip/node', params=params).object
return self._to_nodes(nodes)
|
def ex_get_nodes(self, ex_network_domain_id=None):
'\n Get the nodes within this geography or in given network.\n\n :param ex_network_domain_id: UUID of Network Domain\n if not None returns only balancers in the given network\n if None then returns all pools for the organization\n :type ex_network_domain_id: ``str``\n\n :return: Returns an ``list`` of ``DimensionDataVIPNode``\n :rtype: ``list`` of ``DimensionDataVIPNode``\n '
params = None
if (ex_network_domain_id is not None):
params = {'networkDomainId': ex_network_domain_id}
nodes = self.connection.request_with_orgId_api_2('networkDomainVip/node', params=params).object
return self._to_nodes(nodes)<|docstring|>Get the nodes within this geography or in given network.
:param ex_network_domain_id: UUID of Network Domain
if not None returns only balancers in the given network
if None then returns all pools for the organization
:type ex_network_domain_id: ``str``
:return: Returns an ``list`` of ``DimensionDataVIPNode``
:rtype: ``list`` of ``DimensionDataVIPNode``<|endoftext|>
|
916a3aa83ca53dbaa1d9c1450f105f6cc90d154ff9a2ff0c3c158f12ded8fc1b
|
def ex_get_node(self, node_id):
'\n Get the node specified by node_id\n\n :return: Returns an instance of ``DimensionDataVIPNode``\n :rtype: Instance of ``DimensionDataVIPNode``\n '
nodes = self.connection.request_with_orgId_api_2(('networkDomainVip/node/%s' % node_id)).object
return self._to_node(nodes)
|
Get the node specified by node_id
:return: Returns an instance of ``DimensionDataVIPNode``
:rtype: Instance of ``DimensionDataVIPNode``
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_get_node
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_get_node(self, node_id):
'\n Get the node specified by node_id\n\n :return: Returns an instance of ``DimensionDataVIPNode``\n :rtype: Instance of ``DimensionDataVIPNode``\n '
nodes = self.connection.request_with_orgId_api_2(('networkDomainVip/node/%s' % node_id)).object
return self._to_node(nodes)
|
def ex_get_node(self, node_id):
'\n Get the node specified by node_id\n\n :return: Returns an instance of ``DimensionDataVIPNode``\n :rtype: Instance of ``DimensionDataVIPNode``\n '
nodes = self.connection.request_with_orgId_api_2(('networkDomainVip/node/%s' % node_id)).object
return self._to_node(nodes)<|docstring|>Get the node specified by node_id
:return: Returns an instance of ``DimensionDataVIPNode``
:rtype: Instance of ``DimensionDataVIPNode``<|endoftext|>
|
52ec8abcb973db68b35116223856890a2b6aa0e3080583f471cf4e670a7e78a6
|
def ex_destroy_node(self, node_id):
'\n Destroy a specific node\n\n :param node_id: The ID of of a ``DimensionDataVIPNode``\n :type node_id: ``str``\n\n :return: ``True`` for success, ``False`` for failure\n :rtype: ``bool``\n '
destroy_request = ET.Element('deleteNode', {'xmlns': TYPES_URN, 'id': node_id})
result = self.connection.request_with_orgId_api_2(action='networkDomainVip/deleteNode', method='POST', data=ET.tostring(destroy_request)).object
response_code = findtext(result, 'responseCode', TYPES_URN)
return (response_code in ['IN_PROGRESS', 'OK'])
|
Destroy a specific node
:param node_id: The ID of of a ``DimensionDataVIPNode``
:type node_id: ``str``
:return: ``True`` for success, ``False`` for failure
:rtype: ``bool``
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_destroy_node
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_destroy_node(self, node_id):
'\n Destroy a specific node\n\n :param node_id: The ID of of a ``DimensionDataVIPNode``\n :type node_id: ``str``\n\n :return: ``True`` for success, ``False`` for failure\n :rtype: ``bool``\n '
destroy_request = ET.Element('deleteNode', {'xmlns': TYPES_URN, 'id': node_id})
result = self.connection.request_with_orgId_api_2(action='networkDomainVip/deleteNode', method='POST', data=ET.tostring(destroy_request)).object
response_code = findtext(result, 'responseCode', TYPES_URN)
return (response_code in ['IN_PROGRESS', 'OK'])
|
def ex_destroy_node(self, node_id):
'\n Destroy a specific node\n\n :param node_id: The ID of of a ``DimensionDataVIPNode``\n :type node_id: ``str``\n\n :return: ``True`` for success, ``False`` for failure\n :rtype: ``bool``\n '
destroy_request = ET.Element('deleteNode', {'xmlns': TYPES_URN, 'id': node_id})
result = self.connection.request_with_orgId_api_2(action='networkDomainVip/deleteNode', method='POST', data=ET.tostring(destroy_request)).object
response_code = findtext(result, 'responseCode', TYPES_URN)
return (response_code in ['IN_PROGRESS', 'OK'])<|docstring|>Destroy a specific node
:param node_id: The ID of of a ``DimensionDataVIPNode``
:type node_id: ``str``
:return: ``True`` for success, ``False`` for failure
:rtype: ``bool``<|endoftext|>
|
134565b9731d96fceab7635ad824ac650077ed783ec68f7a6250a3fe54f1431c
|
def ex_wait_for_state(self, state, func, poll_interval=2, timeout=60, *args, **kwargs):
'\n Wait for the function which returns a instance\n with field status to match\n\n Keep polling func until one of the desired states is matched\n\n :param state: Either the desired state (`str`) or a `list` of states\n :type state: ``str`` or ``list``\n\n :param func: The function to call, e.g. ex_get_vlan\n :type func: ``function``\n\n :param poll_interval: The number of seconds to wait between checks\n :type poll_interval: `int`\n\n :param timeout: The total number of seconds to wait to reach a state\n :type timeout: `int`\n\n :param args: The arguments for func\n :type args: Positional arguments\n\n :param kwargs: The arguments for func\n :type kwargs: Keyword arguments\n '
return self.connection.wait_for_state(state, func, poll_interval, timeout, *args, **kwargs)
|
Wait for the function which returns a instance
with field status to match
Keep polling func until one of the desired states is matched
:param state: Either the desired state (`str`) or a `list` of states
:type state: ``str`` or ``list``
:param func: The function to call, e.g. ex_get_vlan
:type func: ``function``
:param poll_interval: The number of seconds to wait between checks
:type poll_interval: `int`
:param timeout: The total number of seconds to wait to reach a state
:type timeout: `int`
:param args: The arguments for func
:type args: Positional arguments
:param kwargs: The arguments for func
:type kwargs: Keyword arguments
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_wait_for_state
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_wait_for_state(self, state, func, poll_interval=2, timeout=60, *args, **kwargs):
'\n Wait for the function which returns a instance\n with field status to match\n\n Keep polling func until one of the desired states is matched\n\n :param state: Either the desired state (`str`) or a `list` of states\n :type state: ``str`` or ``list``\n\n :param func: The function to call, e.g. ex_get_vlan\n :type func: ``function``\n\n :param poll_interval: The number of seconds to wait between checks\n :type poll_interval: `int`\n\n :param timeout: The total number of seconds to wait to reach a state\n :type timeout: `int`\n\n :param args: The arguments for func\n :type args: Positional arguments\n\n :param kwargs: The arguments for func\n :type kwargs: Keyword arguments\n '
return self.connection.wait_for_state(state, func, poll_interval, timeout, *args, **kwargs)
|
def ex_wait_for_state(self, state, func, poll_interval=2, timeout=60, *args, **kwargs):
'\n Wait for the function which returns a instance\n with field status to match\n\n Keep polling func until one of the desired states is matched\n\n :param state: Either the desired state (`str`) or a `list` of states\n :type state: ``str`` or ``list``\n\n :param func: The function to call, e.g. ex_get_vlan\n :type func: ``function``\n\n :param poll_interval: The number of seconds to wait between checks\n :type poll_interval: `int`\n\n :param timeout: The total number of seconds to wait to reach a state\n :type timeout: `int`\n\n :param args: The arguments for func\n :type args: Positional arguments\n\n :param kwargs: The arguments for func\n :type kwargs: Keyword arguments\n '
return self.connection.wait_for_state(state, func, poll_interval, timeout, *args, **kwargs)<|docstring|>Wait for the function which returns a instance
with field status to match
Keep polling func until one of the desired states is matched
:param state: Either the desired state (`str`) or a `list` of states
:type state: ``str`` or ``list``
:param func: The function to call, e.g. ex_get_vlan
:type func: ``function``
:param poll_interval: The number of seconds to wait between checks
:type poll_interval: `int`
:param timeout: The total number of seconds to wait to reach a state
:type timeout: `int`
:param args: The arguments for func
:type args: Positional arguments
:param kwargs: The arguments for func
:type kwargs: Keyword arguments<|endoftext|>
|
cd67b0b03e1f37fd1d66f03ada01b9df065a40102bbd0c8aa926510c470bf77d
|
def ex_get_default_health_monitors(self, network_domain_id):
'\n Get the default health monitors available for a network domain\n\n :param network_domain_id: The ID of of a ``DimensionDataNetworkDomain``\n :type network_domain_id: ``str``\n\n :rtype: `list` of :class:`DimensionDataDefaultHealthMonitor`\n '
result = self.connection.request_with_orgId_api_2(action='networkDomainVip/defaultHealthMonitor', params={'networkDomainId': network_domain_id}, method='GET').object
return self._to_health_monitors(result)
|
Get the default health monitors available for a network domain
:param network_domain_id: The ID of of a ``DimensionDataNetworkDomain``
:type network_domain_id: ``str``
:rtype: `list` of :class:`DimensionDataDefaultHealthMonitor`
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_get_default_health_monitors
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_get_default_health_monitors(self, network_domain_id):
'\n Get the default health monitors available for a network domain\n\n :param network_domain_id: The ID of of a ``DimensionDataNetworkDomain``\n :type network_domain_id: ``str``\n\n :rtype: `list` of :class:`DimensionDataDefaultHealthMonitor`\n '
result = self.connection.request_with_orgId_api_2(action='networkDomainVip/defaultHealthMonitor', params={'networkDomainId': network_domain_id}, method='GET').object
return self._to_health_monitors(result)
|
def ex_get_default_health_monitors(self, network_domain_id):
'\n Get the default health monitors available for a network domain\n\n :param network_domain_id: The ID of of a ``DimensionDataNetworkDomain``\n :type network_domain_id: ``str``\n\n :rtype: `list` of :class:`DimensionDataDefaultHealthMonitor`\n '
result = self.connection.request_with_orgId_api_2(action='networkDomainVip/defaultHealthMonitor', params={'networkDomainId': network_domain_id}, method='GET').object
return self._to_health_monitors(result)<|docstring|>Get the default health monitors available for a network domain
:param network_domain_id: The ID of of a ``DimensionDataNetworkDomain``
:type network_domain_id: ``str``
:rtype: `list` of :class:`DimensionDataDefaultHealthMonitor`<|endoftext|>
|
a118ed458561280c6a1e4a6bc1ca051b05e85436f98195a4621767028460c811
|
def ex_get_default_persistence_profiles(self, network_domain_id):
'\n Get the default persistence profiles available for a network domain\n\n :param network_domain_id: The ID of of a ``DimensionDataNetworkDomain``\n :type network_domain_id: ``str``\n\n :rtype: `list` of :class:`DimensionDataPersistenceProfile`\n '
result = self.connection.request_with_orgId_api_2(action='networkDomainVip/defaultPersistenceProfile', params={'networkDomainId': network_domain_id}, method='GET').object
return self._to_persistence_profiles(result)
|
Get the default persistence profiles available for a network domain
:param network_domain_id: The ID of of a ``DimensionDataNetworkDomain``
:type network_domain_id: ``str``
:rtype: `list` of :class:`DimensionDataPersistenceProfile`
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_get_default_persistence_profiles
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_get_default_persistence_profiles(self, network_domain_id):
'\n Get the default persistence profiles available for a network domain\n\n :param network_domain_id: The ID of of a ``DimensionDataNetworkDomain``\n :type network_domain_id: ``str``\n\n :rtype: `list` of :class:`DimensionDataPersistenceProfile`\n '
result = self.connection.request_with_orgId_api_2(action='networkDomainVip/defaultPersistenceProfile', params={'networkDomainId': network_domain_id}, method='GET').object
return self._to_persistence_profiles(result)
|
def ex_get_default_persistence_profiles(self, network_domain_id):
'\n Get the default persistence profiles available for a network domain\n\n :param network_domain_id: The ID of of a ``DimensionDataNetworkDomain``\n :type network_domain_id: ``str``\n\n :rtype: `list` of :class:`DimensionDataPersistenceProfile`\n '
result = self.connection.request_with_orgId_api_2(action='networkDomainVip/defaultPersistenceProfile', params={'networkDomainId': network_domain_id}, method='GET').object
return self._to_persistence_profiles(result)<|docstring|>Get the default persistence profiles available for a network domain
:param network_domain_id: The ID of of a ``DimensionDataNetworkDomain``
:type network_domain_id: ``str``
:rtype: `list` of :class:`DimensionDataPersistenceProfile`<|endoftext|>
|
ea3ccdcfa51b8dd175578b7ff7da0975c0fe409b21ca307291cbe84719913e8f
|
def ex_get_default_irules(self, network_domain_id):
'\n Get the default iRules available for a network domain\n\n :param network_domain_id: The ID of of a ``DimensionDataNetworkDomain``\n :type network_domain_id: ``str``\n\n :rtype: `list` of :class:`DimensionDataDefaultiRule`\n '
result = self.connection.request_with_orgId_api_2(action='networkDomainVip/defaultIrule', params={'networkDomainId': network_domain_id}, method='GET').object
return self._to_irules(result)
|
Get the default iRules available for a network domain
:param network_domain_id: The ID of of a ``DimensionDataNetworkDomain``
:type network_domain_id: ``str``
:rtype: `list` of :class:`DimensionDataDefaultiRule`
|
libcloud/loadbalancer/drivers/dimensiondata.py
|
ex_get_default_irules
|
gig-tech/libcloud
| 1,435 |
python
|
def ex_get_default_irules(self, network_domain_id):
'\n Get the default iRules available for a network domain\n\n :param network_domain_id: The ID of of a ``DimensionDataNetworkDomain``\n :type network_domain_id: ``str``\n\n :rtype: `list` of :class:`DimensionDataDefaultiRule`\n '
result = self.connection.request_with_orgId_api_2(action='networkDomainVip/defaultIrule', params={'networkDomainId': network_domain_id}, method='GET').object
return self._to_irules(result)
|
def ex_get_default_irules(self, network_domain_id):
'\n Get the default iRules available for a network domain\n\n :param network_domain_id: The ID of of a ``DimensionDataNetworkDomain``\n :type network_domain_id: ``str``\n\n :rtype: `list` of :class:`DimensionDataDefaultiRule`\n '
result = self.connection.request_with_orgId_api_2(action='networkDomainVip/defaultIrule', params={'networkDomainId': network_domain_id}, method='GET').object
return self._to_irules(result)<|docstring|>Get the default iRules available for a network domain
:param network_domain_id: The ID of of a ``DimensionDataNetworkDomain``
:type network_domain_id: ``str``
:rtype: `list` of :class:`DimensionDataDefaultiRule`<|endoftext|>
|
75d695bb040ef21b3d02f47aedfb9be23cf40e9c0eb0d6370c8f9db3d16e1f0b
|
def read_unsigned(self) -> int:
'Get the stored value as a 256-bit unsigned value'
raise NotImplementedError()
|
Get the stored value as a 256-bit unsigned value
|
hw/ip/otbn/dv/otbnsim/sim/wsr.py
|
read_unsigned
|
sha-ron/opentitan
| 1 |
python
|
def read_unsigned(self) -> int:
raise NotImplementedError()
|
def read_unsigned(self) -> int:
raise NotImplementedError()<|docstring|>Get the stored value as a 256-bit unsigned value<|endoftext|>
|
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