Package qubx :: Module model

Module model

Hidden Markov model and math.

QUB Express is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

QUB Express is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License, named LICENSE.txt, in the QUB Express program directory. If not, see <http://www.gnu.org/licenses/>.

Version: 1.11.0

Classes

[hide private]

ConstraintsKinTable

QubModel
Hidden Markov model, e.g.

QubModels
Table-like collection of open model files.

RandomNormalsSmallN
Generates batches of gaussian data; mean 0, std 1.

Functions

[hide private]

GenerateEvents(model)
Yields (state, duration) of a Markov process, starting from fixed probabilities (model.states:Pr).

source code

GenerateEventsX(q, start_state)
Yields (state, duration) of a Markov process, starting from a particular state.

source code

GenerateSampleBunches(model, sampling, events)
Yields (sample_array, state_index), one event at a time, from a hidden Markov process.

source code

GenerateSampleBunchesX(events, sampling, amps, stds)
Yields (sample_array, state_index), one event at a time from a hidden Markov process.

source code

GenerateSamples(model, sampling, events)
Yields one sample at a time from a hidden Markov process.

source code

GetNewState(q, state)
Returns the next state, given the state it's coming from.

source code

K012ToModel(K0, K1, K2, model)
Copies rate constants from matrices K0 and K1 into model.rates.

source code

K01ToModel(K0, K1, model)
Copies rate constants from matrices K0 and K1 into model.rates.

source code

MeanFirstPassage(A, Peq, dt)
Returns the matrix M of mean first passage times M[i,j] between states i and j.

source code

ModelToClazz(model)
Returns the array([class of state s, for s in (0..nstate-1)]).

source code

ModelToFast(model, signal_names=[], on_status=<bound method _DevNull.write of <epydoc.docintrospecter._DevNu...)
Returns a new qubx.fast.model.Model. source code

ModelToP0(model)
Returns the array[nstate] of fixed starting probabilities.

source code

ModelToQ(model, stimulus=None)
Returns the matrix Q of combined rate constants.

source code

ModelToRateMatrices(model, signal_names=[]) source code

ModelToRateMatricesP(model, signal_names=[])
Returns the (nstate x nstate) matrices (K0, K1, K2, Ligand, Voltage, Pressure). source code

NewQubModel()
Returns a new QubModel with two states.

source code

OpenQubModel(path)
Reads a QMF file from disk and returns a QubModel.

source code

QtoA(Q, dt)
Returns the matrix A = exp( dt * Q ).

source code

QtoPe(Q)
Returns the array[nstate] of equilibrium probabilities.

source code

QtoQe(Q, clazz, td)
Returns the apparent rate constant matrix, given that events with duration <= td are not recorded.

source code

RandomLT(high)
Returns a uniform random number between 0 and high.

source code

RandomWeighted(weights)
Returns a random index into weights (number between 0 and len(weights)-1), with likelihood proportional to weights[i].

source code

append_clone_if(parent, node)
if node: parent.appendClone(node)

source code

dec_if_gt(n)
if x > n: return x-1; else: return x.

source code

fieldinfo_k_f(s)

source code

fieldname_k0_f(sa, sb)

source code

fieldname_k1_f(sa, sb)

source code

fieldname_k2_f(sa, sb)

source code

fieldname_k_f(ki, sa, sb)

source code

Variables

[hide private]

ALLOW_THREADS = 1

BUFSIZE = 8192

CLIP = 0

COLOR = defaultdict(<function <lambda> at 0x7fd137b1e1b8>, {0:...

ERR_CALL = 3

ERR_DEFAULT = 521

ERR_IGNORE = 0

ERR_LOG = 5

ERR_PRINT = 4

ERR_RAISE = 2

ERR_WARN = 1

FLOATING_POINT_SUPPORT = 1

FPE_DIVIDEBYZERO = 1

FPE_INVALID = 8

FPE_OVERFLOW = 2

FPE_UNDERFLOW = 4

False_ = False

Inf = inf

Infinity = inf

MAXDIMS = 32

MAX_SAFENAME_LEN = 32

MAY_SHARE_BOUNDS = 0

MAY_SHARE_EXACT = -1

MIN_TOTAL_RATE = 1e-09

NAN = nan

NINF = -inf

NZERO = -0.0

NaN = nan

PINF = inf

PZERO = 0.0

RAISE = 2

SHIFT_DIVIDEBYZERO = 0

SHIFT_INVALID = 9

SHIFT_OVERFLOW = 3

SHIFT_UNDERFLOW = 6

ScalarType = (<type 'int'>, <type 'float'>, <type 'complex'>, ...

ShowDropped = False

True_ = True

UFUNC_BUFSIZE_DEFAULT = 8192

UFUNC_PYVALS_NAME = 'UFUNC_PYVALS'

UNSET_VALUE = 86738.82583

WRAP = 1

__package__ = 'qubx'

absolute = <ufunc 'absolute'>

add = <ufunc 'add'>

arccos = <ufunc 'arccos'>

arccosh = <ufunc 'arccosh'>

arcsin = <ufunc 'arcsin'>

arcsinh = <ufunc 'arcsinh'>

arctan = <ufunc 'arctan'>

arctan2 = <ufunc 'arctan2'>

arctanh = <ufunc 'arctanh'>

bitwise_and = <ufunc 'bitwise_and'>

bitwise_not = <ufunc 'invert'>

bitwise_or = <ufunc 'bitwise_or'>

bitwise_xor = <ufunc 'bitwise_xor'>

c_ = <numpy.lib.index_tricks.CClass object>

cast = {<type 'numpy.bool_'>: <function <lambda> at 0x7fd1396e...

cbrt = <ufunc 'cbrt'>

ceil = <ufunc 'ceil'>

conj = <ufunc 'conjugate'>

conjugate = <ufunc 'conjugate'>

copysign = <ufunc 'copysign'>

cos = <ufunc 'cos'>

cosh = <ufunc 'cosh'>

deg2rad = <ufunc 'deg2rad'>

degrees = <ufunc 'degrees'>

divide = <ufunc 'divide'>

e = 2.71828182846

equal = <ufunc 'equal'>

euler_gamma = 0.577215664902

exp = <ufunc 'exp'>

exp2 = <ufunc 'exp2'>

expm1 = <ufunc 'expm1'>

fabs = <ufunc 'fabs'>

false = False

floor = <ufunc 'floor'>

floor_divide = <ufunc 'floor_divide'>

fmax = <ufunc 'fmax'>

fmin = <ufunc 'fmin'>

fmod = <ufunc 'fmod'>

frexp = <ufunc 'frexp'>

greater = <ufunc 'greater'>

greater_equal = <ufunc 'greater_equal'>

hypot = <ufunc 'hypot'>

index_exp = <numpy.lib.index_tricks.IndexExpression object>

inf = inf

infty = inf

invert = <ufunc 'invert'>

isfinite = <ufunc 'isfinite'>

isinf = <ufunc 'isinf'>

isnan = <ufunc 'isnan'>

ldexp = <ufunc 'ldexp'>

left_shift = <ufunc 'left_shift'>

less = <ufunc 'less'>

less_equal = <ufunc 'less_equal'>

little_endian = True

log = <ufunc 'log'>

log10 = <ufunc 'log10'>

log1p = <ufunc 'log1p'>

log2 = <ufunc 'log2'>

logaddexp = <ufunc 'logaddexp'>

logaddexp2 = <ufunc 'logaddexp2'>

logical_and = <ufunc 'logical_and'>

logical_not = <ufunc 'logical_not'>

logical_or = <ufunc 'logical_or'>

logical_xor = <ufunc 'logical_xor'>

maximum = <ufunc 'maximum'>

mgrid = <numpy.lib.index_tricks.nd_grid object>

minimum = <ufunc 'minimum'>

mod = <ufunc 'remainder'>

modf = <ufunc 'modf'>

multiply = <ufunc 'multiply'>

name_float = 'a number'

name_int = 'an integer'

nan = nan

nbytes = {<type 'numpy.bool_'>: 1, <type 'numpy.timedelta64'>:...

negative = <ufunc 'negative'>

newaxis = None
hash(x)

nextafter = <ufunc 'nextafter'>

not_equal = <ufunc 'not_equal'>

ogrid = <numpy.lib.index_tricks.nd_grid object>

pi = 3.14159265359

power = <ufunc 'power'>

r_ = <numpy.lib.index_tricks.RClass object>

rad2deg = <ufunc 'rad2deg'>

radians = <ufunc 'radians'>

rdbk = 'Expired.'

rdbreak = 'supporting'

rdname = 'qubfast.txt'

reciprocal = <ufunc 'reciprocal'>

remainder = <ufunc 'remainder'>

right_shift = <ufunc 'right_shift'>

rint = <ufunc 'rint'>

s_ = <numpy.lib.index_tricks.IndexExpression object>

sctypeDict = {0: <type 'numpy.bool_'>, 1: <type 'numpy.int8'>,...

sctypeNA = {'?': 'Bool', 'B': 'UInt8', 'Bool': <type 'numpy.bo...

sctypes = {'complex': [<type 'numpy.complex64'>, <type 'numpy....

sign = <ufunc 'sign'>

signbit = <ufunc 'signbit'>

sin = <ufunc 'sin'>

sinh = <ufunc 'sinh'>

spacing = <ufunc 'spacing'>

sqrt = <ufunc 'sqrt'>

square = <ufunc 'square'>

subtract = <ufunc 'subtract'>

tan = <ufunc 'tan'>

tanh = <ufunc 'tanh'>

true = True

true_divide = <ufunc 'true_divide'>

trunc = <ufunc 'trunc'>

typeDict = {0: <type 'numpy.bool_'>, 1: <type 'numpy.int8'>, 2...

typeNA = {'?': 'Bool', 'B': 'UInt8', 'Bool': <type 'numpy.bool...

typecodes = {'All': '?bhilqpBHILQPefdgFDGSUVOMm', 'AllFloat': ...

valid_identifier = re.compile(r'^[A-Za-z_][A-Za-z_0-9]*$')

Function Details

[hide private]

GenerateSampleBunchesX(events, sampling, amps, stds)

source code

Yields (sample_array, state_index), one event at a time from a hidden Markov process.

Parameters:

amps - mean current of each state
stds - standard deviation of current in each state

MeanFirstPassage(A, Peq, dt)

source code

Returns the matrix M of mean first passage times M[i,j] between states i and j.

>>> from  http://www.scopenvironment.org/downloadpubs/scope34/contents.html

Z = inv(I - A + col(1)*row(pEq)) FL[i][j] = (Z[j][j] - Z[i][j]) / pEq[j]

Parameters:

A - sampled transition probability matrix A = expm(dt * Q)
Peq - equilibrium probability vector
dt - sampling interval in seconds

Variables Details

[hide private]

COLOR

Value:

defaultdict(<function <lambda> at 0x7fd137b1e1b8>, {0: (0, 0, 0), 1: (
1, 0, 0), 2: (0, 0, 1), 3: (0, 1, 0), 4: (0, 1, 1), 5: (1, 1, 0), 6: (
1, 0, 1), 7: (0.5, 0.0, 0.0), 8: (0.525, 0.32025, 0.013125000000000012
), 9: (0.44550000000000006, 0.55, 0.027500000000000028), 10: (0.149499
99999999994, 0.575, 0.04312499999999997), 11: (0.059999999999999984, 0
.6, 0.2759999999999999), 12: (0.078125, 0.625, 0.625), 13: (0.09750000
000000002, 0.3185, 0.65), 14: (0.22949999999999962, 0.1181250000000000
4, 0.675), 15: (0.5879999999999999, 0.13999999999999996, 0.7), 16: (0.
...

ScalarType

Value:

(<type 'int'>,
 <type 'float'>,
 <type 'complex'>,
 <type 'long'>,
 <type 'bool'>,
 <type 'str'>,
 <type 'unicode'>,
 <type 'buffer'>,
...

cast

Value:

{<type 'numpy.bool_'>: <function <lambda> at 0x7fd1396ed758>, <type 'n
umpy.timedelta64'>: <function <lambda> at 0x7fd1396ed7d0>, <type 'nump
y.float16'>: <function <lambda> at 0x7fd1396ed848>, <type 'numpy.uint8
'>: <function <lambda> at 0x7fd1396ed8c0>, <type 'numpy.int8'>: <funct
ion <lambda> at 0x7fd1396ed938>, <type 'numpy.object_'>: <function <la
mbda> at 0x7fd1396ed9b0>, <type 'numpy.datetime64'>: <function <lambda
> at 0x7fd1396eda28>, <type 'numpy.uint64'>: <function <lambda> at 0x7
fd1396edaa0>, <type 'numpy.int64'>: <function <lambda> at 0x7fd1396edb
...

nbytes

Value:

{<type 'numpy.bool_'>: 1, <type 'numpy.timedelta64'>: 8, <type 'numpy.
float16'>: 2, <type 'numpy.uint8'>: 1, <type 'numpy.int8'>: 1, <type '
numpy.object_'>: 8, <type 'numpy.datetime64'>: 8, <type 'numpy.uint64'
>: 8, <type 'numpy.int64'>: 8, <type 'numpy.void'>: 0, <type 'numpy.co
mplex256'>: 32, <type 'numpy.float128'>: 16, <type 'numpy.uint64'>: 8,
 <type 'numpy.int64'>: 8, <type 'numpy.unicode_'>: 0, <type 'numpy.com
plex128'>: 16, <type 'numpy.float64'>: 8, <type 'numpy.uint32'>: 4, <t
ype 'numpy.int32'>: 4, <type 'numpy.string_'>: 0, <type 'numpy.complex
...

sctypeDict

Value:

{0: <type 'numpy.bool_'>,
 1: <type 'numpy.int8'>,
 2: <type 'numpy.uint8'>,
 3: <type 'numpy.int16'>,
 4: <type 'numpy.uint16'>,
 5: <type 'numpy.int32'>,
 6: <type 'numpy.uint32'>,
 7: <type 'numpy.int64'>,
...

sctypeNA

Value:

{'?': 'Bool',
 'B': 'UInt8',
 'Bool': <type 'numpy.bool_'>,
 'Complex128': <type 'numpy.complex256'>,
 'Complex32': <type 'numpy.complex64'>,
 'Complex64': <type 'numpy.complex128'>,
 'D': 'Complex64',
 'Datetime64': <type 'numpy.datetime64'>,
...

sctypes

Value:

{'complex': [<type 'numpy.complex64'>,
             <type 'numpy.complex128'>,
             <type 'numpy.complex256'>],
 'float': [<type 'numpy.float16'>,
           <type 'numpy.float32'>,
           <type 'numpy.float64'>,
           <type 'numpy.float128'>],
 'int': [<type 'numpy.int8'>, <type 'numpy.int16'>, <type 'numpy.int32
...

typeDict

Value:

{0: <type 'numpy.bool_'>,
 1: <type 'numpy.int8'>,
 2: <type 'numpy.uint8'>,
 3: <type 'numpy.int16'>,
 4: <type 'numpy.uint16'>,
 5: <type 'numpy.int32'>,
 6: <type 'numpy.uint32'>,
 7: <type 'numpy.int64'>,
...

typeNA

Value:

{'?': 'Bool',
 'B': 'UInt8',
 'Bool': <type 'numpy.bool_'>,
 'Complex128': <type 'numpy.complex256'>,
 'Complex32': <type 'numpy.complex64'>,
 'Complex64': <type 'numpy.complex128'>,
 'D': 'Complex64',
 'Datetime64': <type 'numpy.datetime64'>,
...

typecodes

Value:

{'All': '?bhilqpBHILQPefdgFDGSUVOMm',
 'AllFloat': 'efdgFDG',
 'AllInteger': 'bBhHiIlLqQpP',
 'Character': 'c',
 'Complex': 'FDG',
 'Datetime': 'Mm',
 'Float': 'efdg',
 'Integer': 'bhilqp',
...