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disconnectSynapse(syn,
mspec)
Disconnect synapse object syn from ModelSpec object mspec in which it
has been declared, and remove its target cell's synaptic channels. |
source code
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connectWithSynapse(synname,
syntypestr,
source_cell,
dest_cell,
dest_compartment_name='
' ,
threshfun=None,
alpha=None,
beta=None,
threshfun_d=None,
alpha_d=None,
beta_d=None,
adapt_typestr=None,
vrev=None,
g=None,
noauxs=True,
subclass=<class 'PyDSTool.Toolbox.neuralcomp.channel'>)
Make a chemical or electrical synapse between two neurons. |
source code
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makeSynapseChannel(name,
gatevarname=None,
voltage=' V ' ,
typestr=None,
vrev=None,
g=None,
parlist=None,
noauxs=True,
subclass=<class 'PyDSTool.Toolbox.neuralcomp.channel'>,
gamma1=None,
gamma2=None)
Make a chemical or electrical (gap junction) synapse channel in a
soma. |
source code
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makeExtInputCurrentChannel(name,
noauxs=True,
subclass=<class 'PyDSTool.Toolbox.neuralcomp.channel'>,
gamma1=None,
gamma2=None)
External input signal used directly as a current. |
source code
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makeExtInputConductanceChannel(name,
voltage=' V ' ,
g=None,
vrev=None,
parlist=None,
noauxs=True,
subclass=<class 'PyDSTool.Toolbox.neuralcomp.channel'>,
gamma1=None,
gamma2=None)
External input signal used as a conductance. |
source code
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makeFunctionConductanceChannel(name,
parameter_name,
func_def_str,
voltage=' V ' ,
g=None,
vrev=None,
parlist=None,
noauxs=True,
subclass=<class 'PyDSTool.Toolbox.neuralcomp.channel'>,
gamma1=None,
gamma2=None)
Explicit function waveform used as a conductance, e.g. |
source code
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makeBiasChannel(name,
I=None,
noauxs=True,
subclass=<class 'PyDSTool.Toolbox.neuralcomp.channel'>,
gamma1=None,
gamma2=None)
Constant bias / applied current "channel". |
source code
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makeChannel_halfact(name,
voltage=' V ' ,
s=None,
isinstant=False,
sinf=None,
taus=None,
spow=1,
s2=None,
isinstant2=False,
sinf2=None,
taus2=None,
spow2=1,
vrev=None,
g=None,
parlist=None,
noauxs=True,
subclass=<class 'PyDSTool.Toolbox.neuralcomp.channel'>,
gamma1=None,
gamma2=None,
nonlocal_variables=None)
Make an ionic membrane channel using the steady state and rate function formalism. |
source code
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makeChannel_rates(name,
voltage=' V ' ,
s=None,
isinstant=False,
arate=None,
brate=None,
spow=1,
s2=None,
isinstant2=False,
arate2=None,
brate2=None,
spow2=1,
vrev=None,
g=None,
parlist=None,
noauxs=True,
subclass=<class 'PyDSTool.Toolbox.neuralcomp.channel'>,
gamma1=None,
gamma2=None,
nonlocal_variables=None)
Make an ionic membrane channel using the forward and backward rate formalism. |
source code
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makeSoma(name,
voltage=' V ' ,
channelList=None,
C=None,
noauxs=True,
subclass=<class 'PyDSTool.Toolbox.neuralcomp.soma'>,
channelclass=<class 'PyDSTool.Toolbox.neuralcomp.channel'>)
Build a soma type of "compartment" from a list of channels
and a membrane capacitance C, using the local voltage name. |
source code
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makeDendrite(name,
voltage=' V ' ,
channelList=None,
C=None,
noauxs=True,
subclass=<class 'PyDSTool.Toolbox.neuralcomp.dendr_compartment'>,
channelclass=<class 'PyDSTool.Toolbox.neuralcomp.channel'>)
Build a dendrite type of "compartment" from a list of
channels and a membrane capacitance C, using the local voltage name. |
source code
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makeNeurite(name,
voltage=' V ' ,
channelList=None,
C=None,
noauxs=True,
subclass=<class 'PyDSTool.Toolbox.neuralcomp.dendr_compartment'>,
channelclass=<class 'PyDSTool.Toolbox.neuralcomp.channel'>)
Build a neurite type of "compartment" from a list of
channels and a membrane capacitance C, using the local voltage name. |
source code
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makePointNeuron(name,
voltage=' V ' ,
channelList=None,
synapseList=None,
C=None,
noauxs=True)
Factory function for single compartment neurons ("point
neurons"). |
source code
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makePointNeuronNetwork(name,
componentList)
Factory function returning a pnnetwork type object from a list of
compatible components (somas and synapses). |
source code
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makeNeuronNetwork(name,
neuronList)
Factory function returning a network type object from a list of
compatible components (neurons). |
source code
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makeSynapse(name,
gatevar,
precompartment,
typestr,
threshfun=None,
alpha=None,
beta=None,
targetchannel=None,
evalopt=True,
noauxs=True)
Make a chemical synapse channel object. |
source code
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makeAdaptingSynapse(name,
gatevar,
adaptvar,
precompartment,
typestr,
adapt_typestr,
threshfun=None,
alpha=None,
beta=None,
threshfun_d=None,
alpha_d=None,
beta_d=None,
targetchannel=None,
evalopt=True,
noauxs=True)
Make an adapting chemical synapse channel object. |
source code
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compatGens = [ ' Radau_ODEsystem ' , ' ADMC_ODEsystem ' , ' Vode_ODEsy ...
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voltage = ' V '
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V = Var V (ExpFuncSpec)
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ALLOW_THREADS = 1
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Abs = Abs (ModelSpec wrapper)
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Acos = Acos (ModelSpec wrapper)
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Asin = Asin (ModelSpec wrapper)
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Atan = Atan (ModelSpec wrapper)
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Atan2 = Atan2 (ModelSpec wrapper)
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BUFSIZE = 10000
|
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Betavariate = Betavariate (ModelSpec wrapper)
|
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CLIP = 0
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Ceil = Ceil (ModelSpec wrapper)
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Choice = Choice (ModelSpec wrapper)
|
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Cos = Cos (ModelSpec wrapper)
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Cosh = Cosh (ModelSpec wrapper)
|
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Degrees = Degrees (ModelSpec wrapper)
|
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E = QuantSpec e (ExpFuncSpec)
|
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ERR_CALL = 3
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ERR_DEFAULT = 0
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ERR_DEFAULT2 = 2084
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ERR_IGNORE = 0
|
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ERR_LOG = 5
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ERR_PRINT = 4
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ERR_RAISE = 2
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ERR_WARN = 1
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Exp = Exp (ModelSpec wrapper)
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Expovariate = Expovariate (ModelSpec wrapper)
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FLOATING_POINT_SUPPORT = 1
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FPE_DIVIDEBYZERO = 1
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FPE_INVALID = 8
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FPE_OVERFLOW = 2
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FPE_UNDERFLOW = 4
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Fabs = Fabs (ModelSpec wrapper)
|
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False_ = False
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Floor = Floor (ModelSpec wrapper)
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Fmod = Fmod (ModelSpec wrapper)
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Frexp = Frexp (ModelSpec wrapper)
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Gammavariate = Gammavariate (ModelSpec wrapper)
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Gauss = Gauss (ModelSpec wrapper)
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Getrandbits = Getrandbits (ModelSpec wrapper)
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Getstate = Getstate (ModelSpec wrapper)
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Hypot = Hypot (ModelSpec wrapper)
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Infinity = inf
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Jumpahead = Jumpahead (ModelSpec wrapper)
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Ldexp = Ldexp (ModelSpec wrapper)
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Log = Log (ModelSpec wrapper)
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Log10 = Log10 (ModelSpec wrapper)
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Lognormvariate = Lognormvariate (ModelSpec wrapper)
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MAXDIMS = 32
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Max = Max (ModelSpec wrapper)
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Min = Min (ModelSpec wrapper)
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Modf = Modf (ModelSpec wrapper)
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NAN = nan
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NINF = -inf
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NZERO = -0.0
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Normalvariate = Normalvariate (ModelSpec wrapper)
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PINF = inf
|
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PZERO = 0.0
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Paretovariate = Paretovariate (ModelSpec wrapper)
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Pi = QuantSpec pi (ExpFuncSpec)
|
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Pow = Pow (ModelSpec wrapper)
|
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RAISE = 2
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Radians = Radians (ModelSpec wrapper)
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Randint = Randint (ModelSpec wrapper)
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Random = Random (ModelSpec wrapper)
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Randrange = Randrange (ModelSpec wrapper)
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SHIFT_DIVIDEBYZERO = 0
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SHIFT_INVALID = 9
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SHIFT_OVERFLOW = 3
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SHIFT_UNDERFLOW = 6
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Sample = Sample (ModelSpec wrapper)
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ScalarType = ( <type 'int'>, <type 'float'>, <type 'complex'>, ...
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Seed = Seed (ModelSpec wrapper)
|
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Setstate = Setstate (ModelSpec wrapper)
|
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Shuffle = Shuffle (ModelSpec wrapper)
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Sin = Sin (ModelSpec wrapper)
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Sinh = Sinh (ModelSpec wrapper)
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Sqrt = Sqrt (ModelSpec wrapper)
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Sum = Sum (ModelSpec wrapper)
|
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Systemrandom = Systemrandom (ModelSpec wrapper)
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Tan = Tan (ModelSpec wrapper)
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Tanh = Tanh (ModelSpec wrapper)
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True_ = True
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UFUNC_BUFSIZE_DEFAULT = 10000
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UFUNC_PYVALS_NAME = ' UFUNC_PYVALS '
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Uniform = Uniform (ModelSpec wrapper)
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Vonmisesvariate = Vonmisesvariate (ModelSpec wrapper)
|
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WRAP = 1
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Weibullvariate = Weibullvariate (ModelSpec wrapper)
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Wichmannhill = Wichmannhill (ModelSpec wrapper)
|
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absolute = <ufunc 'absolute'>
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add = <ufunc 'add'>
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bitwise_and = <ufunc 'bitwise_and'>
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bitwise_not = <ufunc 'invert'>
|
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bitwise_or = <ufunc 'bitwise_or'>
|
|
bitwise_xor = <ufunc 'bitwise_xor'>
|
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c_ = <numpy.lib.index_tricks.CClass object at 0x115c330>
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cast = {<type 'numpy.int64'>: <function <lambda> at 0x6d0c30>,...
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conj = <ufunc 'conjugate'>
|
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conjugate = <ufunc 'conjugate'>
|
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copysign = <ufunc 'copysign'>
|
|
deg2rad = <ufunc 'deg2rad'>
|
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divide = <ufunc 'divide'>
|
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equal = <ufunc 'equal'>
|
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exp2 = <ufunc 'exp2'>
|
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expm1 = <ufunc 'expm1'>
|
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floor_divide = <ufunc 'floor_divide'>
|
|
fmax = <ufunc 'fmax'>
|
|
fmin = <ufunc 'fmin'>
|
|
greater_equal = <ufunc 'greater_equal'>
|
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index_exp = <numpy.lib.index_tricks.IndexExpression object at ...
|
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inf = inf
|
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infty = inf
|
|
invert = <ufunc 'invert'>
|
|
isinf = <ufunc 'isinf'>
|
|
left_shift = <ufunc 'left_shift'>
|
|
little_endian = True
|
|
log1p = <ufunc 'log1p'>
|
|
logaddexp = <ufunc 'logaddexp'>
|
|
logaddexp2 = <ufunc 'logaddexp2'>
|
|
logical_and = <ufunc 'logical_and'>
|
|
logical_not = <ufunc 'logical_not'>
|
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logical_xor = <ufunc 'logical_xor'>
|
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maximum = <ufunc 'maximum'>
|
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mgrid = <numpy.lib.index_tricks.nd_grid object at 0x1147490>
|
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minimum = <ufunc 'minimum'>
|
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multiply = <ufunc 'multiply'>
|
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n = 9
|
|
nan = nan
|
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nbytes = {<type 'numpy.int64'>: 8, <type 'numpy.int16'>: 2, <t...
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negative = <ufunc 'negative'>
|
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newaxis = None
|
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nextafter = <ufunc 'nextafter'>
|
|
not_equal = <ufunc 'not_equal'>
|
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ogrid = <numpy.lib.index_tricks.nd_grid object at 0x1147bb0>
|
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ones_like = <ufunc 'ones_like'>
|
|
r_ = <numpy.lib.index_tricks.RClass object at 0x115c2f0>
|
|
rad2deg = <ufunc 'rad2deg'>
|
|
reciprocal = <ufunc 'reciprocal'>
|
|
remainder = <ufunc 'remainder'>
|
|
right_shift = <ufunc 'right_shift'>
|
|
rint = <ufunc 'rint'>
|
|
s_ = <numpy.lib.index_tricks.IndexExpression object at 0x115c3f0>
|
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sctypeDict = { 0: <type 'numpy.bool_'>, 1: <type 'numpy.int8'>, ...
|
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sctypeNA = { ' ? ' : ' Bool ' , ' B ' : ' UInt8 ' , ' Bool ' : <type 'numpy.bo...
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sctypes = { ' complex ' : [ <type 'numpy.complex64'>, <type 'numpy....
|
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signbit = <ufunc 'signbit'>
|
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spacing = <ufunc 'spacing'>
|
|
square = <ufunc 'square'>
|
|
subtract = <ufunc 'subtract'>
|
|
t = ' 0 '
|
|
true_divide = <ufunc 'true_divide'>
|
|
trunc = <ufunc 'trunc'>
|
|
typeDict = { 0: <type 'numpy.bool_'>, 1: <type 'numpy.int8'>, 2...
|
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typeNA = { ' ? ' : ' Bool ' , ' B ' : ' UInt8 ' , ' Bool ' : <type 'numpy.bool...
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typecodes = { ' All ' : ' ?bhilqpBHILQPfdgFDGSUVOMm ' , ' AllFloat ' : ' ...
|