index int64 0 731k | package stringlengths 2 98 ⌀ | name stringlengths 1 76 | docstring stringlengths 0 281k ⌀ | code stringlengths 4 8.19k | signature stringlengths 2 42.8k ⌀ | embed_func_code listlengths 768 768 |
|---|---|---|---|---|---|---|
722,367 | paramz.parameterized | copy | null | def copy(self, memo=None):
if memo is None:
memo = {}
memo[id(self.optimizer_array)] = None # and param_array
memo[id(self.param_array)] = None # and param_array
copy = super(Parameterized, self).copy(memo)
copy._connect_parameters()
copy._connect_fixes()
copy._notify_parent_change()... | (self, memo=None) | [
-0.006168125197291374,
-0.039837151765823364,
0.047281280159950256,
0.022406093776226044,
-0.12139090895652771,
0.015210716053843498,
-0.03206135332584381,
0.028984198346734047,
0.043669771403074265,
0.007190771400928497,
-0.012124350294470787,
0.025851767510175705,
-0.03788398951292038,
0... |
722,368 | paramz.core.parameter_core | disable_caching | null | def disable_caching(self):
def visit(self):
self.cache.disable_caching()
self.traverse(visit)
| (self) | [
0.031239710748195648,
-0.00030667666578665376,
-0.03358227014541626,
0.03145723417401314,
-0.024345891550183296,
0.010215234942734241,
-0.06505624204874039,
0.016314256936311722,
0.013168534263968468,
-0.013109969906508923,
0.007918689399957657,
0.016289157792925835,
-0.012959376908838749,
... |
722,369 | paramz.core.parameter_core | enable_caching | null | def enable_caching(self):
def visit(self):
self.cache.enable_caching()
self.traverse(visit)
| (self) | [
0.022566696628928185,
-0.022732142359018326,
-0.04453779011964798,
0.04496794939041138,
0.020134655758738518,
0.034180935472249985,
-0.04099727049469948,
0.01281371433287859,
-0.0003934488631784916,
-0.014120729640126228,
0.028605438768863678,
-0.006506124045699835,
0.017404813319444656,
0... |
722,371 | paramz.parameterized | get_property_string | null | def get_property_string(self, propname):
props = []
for p in self.parameters:
props.extend(p.get_property_string(propname))
return props
| (self, propname) | [
0.007221184205263853,
-0.03161707893013954,
0.029044419527053833,
-0.02876054123044014,
0.019144123420119286,
-0.001370605663396418,
0.002510559279471636,
-0.05237576365470886,
0.10517735034227371,
0.012535053305327892,
0.015356105752289295,
0.02098933979868889,
-0.029204102233052254,
0.00... |
722,372 | paramz.parameterized | grep_param_names |
create a list of parameters, matching regular expression regexp
| def grep_param_names(self, regexp):
"""
create a list of parameters, matching regular expression regexp
"""
if not isinstance(regexp, _pattern_type): regexp = compile(regexp)
found_params = []
def visit(innerself, regexp):
if (innerself is not self) and regexp.match(innerself.hierarchy_n... | (self, regexp) | [
0.03582914546132088,
-0.03892243653535843,
0.051012784242630005,
0.019797060638666153,
-0.02653159573674202,
-0.013433719985187054,
0.057234715670347214,
-0.05960329249501228,
-0.0017819564091041684,
0.006244028452783823,
0.0002079685655189678,
0.00909427460283041,
0.008418169803917408,
-0... |
722,373 | paramz.core.parentable | has_parent |
Return whether this parentable object currently has a parent.
| def has_parent(self):
"""
Return whether this parentable object currently has a parent.
"""
return self._parent_ is not None
| (self) | [
0.020805176347494125,
0.019000645726919174,
-0.00912880152463913,
0.04897000640630722,
-0.0032463858369737864,
0.023335058242082596,
0.04153958708047867,
0.07536569237709045,
0.04387486353516579,
0.0038810677360743284,
0.007041207514703274,
-0.0723935216665268,
0.03559524938464165,
-0.0006... |
722,374 | paramz.core.nameable | hierarchy_name |
return the name for this object with the parents names attached by dots.
:param bool adjust_for_printing: whether to call :func:`~adjust_for_printing()`
on the names, recursively
| def hierarchy_name(self, adjust_for_printing=True):
"""
return the name for this object with the parents names attached by dots.
:param bool adjust_for_printing: whether to call :func:`~adjust_for_printing()`
on the names, recursively
... | (self, adjust_for_printing=True) | [
-0.008669245056807995,
0.011320754885673523,
0.042071208357810974,
0.04934190213680267,
-0.0338122621178627,
-0.021247372031211853,
0.010808982886373997,
-0.024070942774415016,
0.07588347047567368,
-0.029541611671447754,
0.007111869286745787,
-0.06310681253671646,
0.018723804503679276,
-0.... |
722,375 | paramz.core.parameter_core | initialize_parameter |
Call this function to initialize the model, if you built it without initialization.
This HAS to be called manually before optmizing or it will be causing
unexpected behaviour, if not errors!
| def initialize_parameter(self):
"""
Call this function to initialize the model, if you built it without initialization.
This HAS to be called manually before optmizing or it will be causing
unexpected behaviour, if not errors!
"""
#logger.debug("connecting parameters")
self._highest_parent_.... | (self) | [
0.013582386076450348,
0.012266537174582481,
0.028789712116122246,
0.04934874549508095,
-0.04168326407670975,
-0.024356450885534286,
-0.01843954622745514,
0.028878025710582733,
0.02875438891351223,
-0.020382409915328026,
-0.04090612009167671,
-0.004389106761664152,
0.0049763815477490425,
0.... |
722,376 | paramz.parameterized | link_parameter |
:param parameters: the parameters to add
:type parameters: list of or one :py:class:`paramz.param.Param`
:param [index]: index of where to put parameters
Add all parameters to this param class, you can insert parameters
at any given index using the :func:`list.insert` sy... | def link_parameter(self, param, index=None):
"""
:param parameters: the parameters to add
:type parameters: list of or one :py:class:`paramz.param.Param`
:param [index]: index of where to put parameters
Add all parameters to this param class, you can insert parameters
at any given index u... | (self, param, index=None) | [
0.00606866180896759,
0.007127036340534687,
-0.02759541943669319,
0.05651137977838516,
-0.034062184393405914,
0.01648733951151371,
-0.060706038028001785,
-0.0018290946027264,
0.021750083193182945,
-0.013302506878972054,
-0.01668153703212738,
-0.03668384626507759,
0.0008490057662129402,
-0.0... |
722,377 | paramz.parameterized | link_parameters |
convenience method for adding several
parameters without gradient specification
| def link_parameters(self, *parameters):
"""
convenience method for adding several
parameters without gradient specification
"""
[self.link_parameter(p) for p in parameters]
| (self, *parameters) | [
-0.02483977936208248,
-0.0019909145776182413,
0.010783090256154537,
0.01155652292072773,
-0.06989672780036926,
0.016745716333389282,
-0.08856703341007233,
-0.014758174307644367,
0.061658769845962524,
0.05151421204209328,
-0.03007393889129162,
-0.029030704870820045,
0.006268401630222797,
0.... |
722,378 | paramz.core.observable | notify_observers |
Notifies all observers. Which is the element, which kicked off this
notification loop. The first argument will be self, the second `which`.
.. note::
notifies only observers with priority p > min_priority!
:param min_priority: only notify observers wi... | def notify_observers(self, which=None, min_priority=None):
"""
Notifies all observers. Which is the element, which kicked off this
notification loop. The first argument will be self, the second `which`.
.. note::
notifies only observers with priority p > min_priority!
:param m... | (self, which=None, min_priority=None) | [
0.03817036375403404,
0.024871185421943665,
-0.01910245232284069,
-0.03348974138498306,
0.0008274203282780945,
-0.06608135998249054,
-0.004216443281620741,
0.017133483663201332,
0.0048749251291155815,
0.04190104082226753,
-0.011451108381152153,
-0.030380845069885254,
0.04355911910533905,
-0... |
722,379 | paramz.model | objective_function |
The objective function for the given algorithm.
This function is the true objective, which wants to be minimized.
Note that all parameters are already set and in place, so you just need
to return the objective function here.
For probabilistic models this is the negative log_li... | def objective_function(self):
"""
The objective function for the given algorithm.
This function is the true objective, which wants to be minimized.
Note that all parameters are already set and in place, so you just need
to return the objective function here.
For probabilistic models this is the ... | (self) | [
0.03691192343831062,
-0.01894022896885872,
-0.005048934370279312,
0.03108278289437294,
-0.013039343990385532,
-0.0665060356259346,
-0.054309673607349396,
-0.05172691494226456,
0.03404219448566437,
-0.02195344865322113,
-0.04702772945165634,
-0.02803369238972664,
0.013129022903740406,
0.036... |
722,380 | paramz.model | objective_function_gradients |
The gradients for the objective function for the given algorithm.
The gradients are w.r.t. the *negative* objective function, as
this framework works with *negative* log-likelihoods as a default.
You can find the gradient for the parameters in self.gradient at all times.
This i... | def objective_function_gradients(self):
"""
The gradients for the objective function for the given algorithm.
The gradients are w.r.t. the *negative* objective function, as
this framework works with *negative* log-likelihoods as a default.
You can find the gradient for the parameters in self.gradien... | (self) | [
0.02462603710591793,
-0.019650166854262352,
0.002795534674078226,
0.031085623428225517,
-0.025657400488853455,
-0.04603132978081703,
-0.057575348764657974,
-0.0644872859120369,
0.0246079433709383,
-0.0024969824589788914,
-0.03716523200273514,
-0.016592267900705338,
0.024517472833395004,
0.... |
722,381 | paramz.model | optimize |
Optimize the model using self.log_likelihood and self.log_likelihood_gradient, as well as self.priors.
kwargs are passed to the optimizer. They can be:
:param max_iters: maximum number of function evaluations
:type max_iters: int
:messages: True: Display messages during optimi... | def optimize(self, optimizer=None, start=None, messages=False, max_iters=1000, ipython_notebook=True, clear_after_finish=False, **kwargs):
"""
Optimize the model using self.log_likelihood and self.log_likelihood_gradient, as well as self.priors.
kwargs are passed to the optimizer. They can be:
:param ma... | (self, optimizer=None, start=None, messages=False, max_iters=1000, ipython_notebook=True, clear_after_finish=False, **kwargs) | [
-0.004613934550434351,
-0.03393232822418213,
0.016497744247317314,
0.013574805110692978,
-0.038860104978084564,
-0.02600666508078575,
-0.07479726523160934,
-0.07543431967496872,
-0.019523736089468002,
-0.03458811342716217,
-0.020104575902223587,
-0.017340900376439095,
-0.007110612001270056,
... |
722,382 | paramz.model | optimize_restarts |
Perform random restarts of the model, and set the model to the best
seen solution.
If the robust flag is set, exceptions raised during optimizations will
be handled silently. If _all_ runs fail, the model is reset to the
existing parameter values.
\*\*kwargs are passe... | def optimize_restarts(self, num_restarts=10, robust=False, verbose=True, parallel=False, num_processes=None, **kwargs):
"""
Perform random restarts of the model, and set the model to the best
seen solution.
If the robust flag is set, exceptions raised during optimizations will
be handled silently. ... | (self, num_restarts=10, robust=False, verbose=True, parallel=False, num_processes=None, **kwargs) | [
0.05332554131746292,
0.006919534411281347,
-0.02051416225731373,
0.05949295312166214,
-0.016960380598902702,
-0.020100494846701622,
-0.0899539440870285,
-0.054416120052337646,
0.060583531856536865,
-0.02015690505504608,
-0.0011898825177922845,
0.01702619157731533,
0.03141995146870613,
0.01... |
722,383 | paramz.core.parameter_core | parameter_names |
Get the names of all parameters of this model or parameter. It starts
from the parameterized object you are calling this method on.
Note: This does not unravel multidimensional parameters,
use parameter_names_flat to unravel parameters!
:param bool add_self: whether to a... | def parameter_names(self, add_self=False, adjust_for_printing=False, recursive=True, intermediate=False):
"""
Get the names of all parameters of this model or parameter. It starts
from the parameterized object you are calling this method on.
Note: This does not unravel multidimensional parameters,
... | (self, add_self=False, adjust_for_printing=False, recursive=True, intermediate=False) | [
-0.011619329452514648,
-0.023946711793541908,
0.02982899732887745,
0.026615526527166367,
-0.04143017157912254,
-0.016530310735106468,
-0.01059356052428484,
-0.06107410043478012,
0.07345594465732574,
-0.006649342831224203,
0.00370139186270535,
-0.03249781206250191,
0.013198832049965858,
-0.... |
722,384 | paramz.core.parameter_core | parameter_names_flat |
Return the flattened parameter names for all subsequent parameters
of this parameter. We do not include the name for self here!
If you want the names for fixed parameters as well in this list,
set include_fixed to True.
if not hasattr(obj, 'cache'):
obj.cach... | def parameter_names_flat(self, include_fixed=False):
"""
Return the flattened parameter names for all subsequent parameters
of this parameter. We do not include the name for self here!
If you want the names for fixed parameters as well in this list,
set include_fixed to True.
if not hasattr(... | (self, include_fixed=False) | [
-0.009617718867957592,
-0.022739289328455925,
0.03843512013554573,
0.015847783535718918,
-0.024294571951031685,
-0.04311884194612503,
0.010225529782474041,
-0.051985736936330795,
0.05194998160004616,
0.008808793500065804,
-0.022292369976639748,
-0.050841622054576874,
-0.018788516521453857,
... |
722,385 | paramz.core.parameter_core | parameters_changed |
This method gets called when parameters have changed.
Another way of listening to param changes is to
add self as a listener to the param, such that
updates get passed through. See :py:function:``paramz.param.Observable.add_observer``
| def parameters_changed(self):
"""
This method gets called when parameters have changed.
Another way of listening to param changes is to
add self as a listener to the param, such that
updates get passed through. See :py:function:``paramz.param.Observable.add_observer``
"""
pass
| (self) | [
0.02402462251484394,
0.0058966344222426414,
0.011276327073574066,
0.03217301890254021,
0.0036426829174160957,
0.0029132701456546783,
-0.06101658195257187,
0.029211558401584625,
0.016340598464012146,
0.02008185163140297,
-0.00501170102506876,
-0.03704453259706497,
0.04983663558959961,
0.026... |
722,386 | paramz.core.pickleable | pickle |
:param f: either filename or open file object to write to.
if it is an open buffer, you have to make sure to close
it properly.
:param protocol: pickling protocol to use, python-pickle for details.
| def pickle(self, f, protocol=-1):
"""
:param f: either filename or open file object to write to.
if it is an open buffer, you have to make sure to close
it properly.
:param protocol: pickling protocol to use, python-pickle for details.
"""
try: #Py2
import cPickle... | (self, f, protocol=-1) | [
0.043797023594379425,
-0.02451431378722191,
-0.04998304322361946,
0.05005374178290367,
-0.02709476836025715,
-0.051997918635606766,
-0.08646288514137268,
0.05631045997142792,
-0.010648791678249836,
-0.03359892591834068,
-0.0016735394019633532,
-0.010321816429495811,
-0.06613739579916,
0.01... |
722,387 | paramz.core.parameter_core | randomize |
Randomize the model.
Make this draw from the rand_gen if one exists, else draw random normal(0,1)
:param rand_gen: np random number generator which takes args and kwargs
:param flaot loc: loc parameter for random number generator
:param float scale: scale parameter for random n... | def randomize(self, rand_gen=None, *args, **kwargs):
"""
Randomize the model.
Make this draw from the rand_gen if one exists, else draw random normal(0,1)
:param rand_gen: np random number generator which takes args and kwargs
:param flaot loc: loc parameter for random number generator
:param fl... | (self, rand_gen=None, *args, **kwargs) | [
0.00046789253246970475,
-0.045028865337371826,
0.0029996081721037626,
0.014472240582108498,
-0.00522093940526247,
0.0072778137400746346,
-0.05388639494776726,
-0.03872853145003319,
0.028981542214751244,
-0.010812487453222275,
-0.03202052786946297,
0.053960517048835754,
-0.0037802010774612427... |
722,388 | paramz.core.indexable | remove_index_operation | null | def remove_index_operation(self, name):
if name in self._index_operations:
delitem(self._index_operations, name)
#delattr(self, name)
else:
raise AttributeError("No index operation with the name {}".format(name))
| (self, name) | [
0.021173547953367233,
-0.02152208238840103,
0.028318529948592186,
0.00538923405110836,
-0.018977772444486618,
-0.01061291340738535,
-0.04774940013885498,
-0.002531240927055478,
0.013070090673863888,
-0.02244570292532444,
0.024990012869238853,
0.01577124372124672,
0.05524291843175888,
-0.07... |
722,389 | paramz.core.observable | remove_observer |
Either (if callble is None) remove all callables,
which were added alongside observer,
or remove callable `callble` which was added alongside
the observer `observer`.
| def remove_observer(self, observer, callble=None):
"""
Either (if callble is None) remove all callables,
which were added alongside observer,
or remove callable `callble` which was added alongside
the observer `observer`.
"""
to_remove = []
for poc in self.observers:
_, obs, clbl... | (self, observer, callble=None) | [
-0.02270221896469593,
0.017552178353071213,
-0.02408607304096222,
0.007913369685411453,
-0.08015845715999603,
-0.04512416571378708,
-0.023122631013393402,
0.053182050585746765,
0.02958645671606064,
0.042041145265102386,
-0.001954256324097514,
-0.004009236581623554,
0.009135191328823566,
-0... |
722,390 | paramz.core.parameter_core | save |
Save all the model parameters into a file (HDF5 by default).
This is not supported yet. We are working on having a consistent,
human readable way of saving and loading GPy models. This only
saves the parameter array to a hdf5 file. In order
to load the model again, use the same... | def save(self, filename, ftype='HDF5'): # pragma: no coverage
"""
Save all the model parameters into a file (HDF5 by default).
This is not supported yet. We are working on having a consistent,
human readable way of saving and loading GPy models. This only
saves the parameter array to a hdf5 file. In... | (self, filename, ftype='HDF5') | [
0.02926906943321228,
-0.020168447867035866,
-0.055633291602134705,
0.03849838674068451,
0.0035414285957813263,
-0.031309813261032104,
-0.08685117959976196,
-0.022319503128528595,
-0.027081243693828583,
-0.042653415352106094,
-0.015526211820542812,
-0.028772670775651932,
-0.029342608526349068... |
722,391 | paramz.core.observable | set_updates | null | def set_updates(self, on=True):
self._update_on = on
| (self, on=True) | [
0.02885134331882,
0.02670932561159134,
-0.01983838900923729,
0.025539454072713852,
0.02226051688194275,
-0.00080016755964607,
-0.03364617004990578,
0.026017287746071815,
0.007414679974317551,
0.040961988270282745,
-0.06887413561344147,
-0.06511736661195755,
0.06702870875597,
0.039874501526... |
722,392 | paramz.core.updateable | toggle_update | null | def toggle_update(self):
print("deprecated: toggle_update was renamed to update_toggle for easier access")
self.update_toggle()
| (self) | [
0.04985593631863594,
-0.033888090401887894,
0.02956491895020008,
-0.011993316002190113,
-0.015392584726214409,
-0.03887368366122246,
-0.004846136551350355,
0.06415029615163803,
-0.00536474259570241,
0.009361062198877335,
-0.06871751695871353,
-0.08918285369873047,
0.059025246649980545,
0.0... |
722,393 | paramz.core.parameter_core | traverse |
Traverse the hierarchy performing `visit(self, *args, **kwargs)`
at every node passed by downwards. This function includes self!
See *visitor pattern* in literature. This is implemented in pre-order fashion.
Example::
#Collect all children:
children = []
... | def traverse(self, visit, *args, **kwargs):
"""
Traverse the hierarchy performing `visit(self, *args, **kwargs)`
at every node passed by downwards. This function includes self!
See *visitor pattern* in literature. This is implemented in pre-order fashion.
Example::
#Collect all children:
... | (self, visit, *args, **kwargs) | [
-0.054509446024894714,
-0.04716109111905098,
-0.05641051381826401,
0.03215362876653671,
-0.05162128806114197,
0.03341491147875786,
-0.01078490074723959,
-0.0010944845853373408,
0.024384843185544014,
0.014916066080331802,
0.00685023982077837,
-0.023763339966535568,
0.0699373409152031,
0.016... |
722,394 | paramz.core.parameter_core | traverse_parents |
Traverse the hierarchy upwards, visiting all parents and their children except self.
See "visitor pattern" in literature. This is implemented in pre-order fashion.
Example:
parents = []
self.traverse_parents(parents.append)
print parents
| def traverse_parents(self, visit, *args, **kwargs):
"""
Traverse the hierarchy upwards, visiting all parents and their children except self.
See "visitor pattern" in literature. This is implemented in pre-order fashion.
Example:
parents = []
self.traverse_parents(parents.append)
print parent... | (self, visit, *args, **kwargs) | [
-0.05224006995558739,
-0.03590364009141922,
-0.041069239377975464,
0.041799359023571014,
-0.07235486805438995,
0.0462895929813385,
0.015989623963832855,
0.01629992388188839,
0.06567427515983582,
0.021264739334583282,
0.02168455719947815,
-0.06753607839345932,
0.05983331426978111,
0.0237471... |
722,395 | paramz.core.updateable | trigger_update |
Update the model from the current state.
Make sure that updates are on, otherwise this
method will do nothing
:param bool trigger_parent: Whether to trigger the parent, after self has updated
| def trigger_update(self, trigger_parent=True):
"""
Update the model from the current state.
Make sure that updates are on, otherwise this
method will do nothing
:param bool trigger_parent: Whether to trigger the parent, after self has updated
"""
if not self.update_model() or (hasattr(self, ... | (self, trigger_parent=True) | [
0.06881824135780334,
-0.02197187766432762,
0.008549505844712257,
0.05812256783246994,
-0.035165559500455856,
-0.05970580875873566,
0.00042659571045078337,
0.04112910479307175,
0.05822811648249626,
0.020933974534273148,
-0.06434998661279678,
-0.05784109979867935,
0.04067172482609749,
0.0343... |
722,396 | paramz.core.constrainable | unconstrain |
:param transforms: The transformations to unconstrain from.
remove all :py:class:`paramz.transformations.Transformation`
transformats of this parameter object.
| def unconstrain(self, *transforms):
"""
:param transforms: The transformations to unconstrain from.
remove all :py:class:`paramz.transformations.Transformation`
transformats of this parameter object.
"""
return self._remove_from_index_operations(self.constraints, transforms)
| (self, *transforms) | [
0.029548421502113342,
0.010629802010953426,
0.035652320832014084,
-0.004495556466281414,
-0.10439055413007736,
-0.024831771850585938,
-0.029617784544825554,
-0.05677320063114166,
0.027692975476384163,
0.022594831883907318,
-0.04844970256090164,
0.02651381306350231,
-0.010204956866800785,
-... |
722,397 | paramz.core.constrainable | unconstrain_bounded |
:param lower, upper: the limits to unbound this parameter from
Remove (lower, upper) bounded constrain from this parameter/
| def unconstrain_bounded(self, lower, upper):
"""
:param lower, upper: the limits to unbound this parameter from
Remove (lower, upper) bounded constrain from this parameter/
"""
self.unconstrain(Logistic(lower, upper))
| (self, lower, upper) | [
-0.023779820650815964,
0.04499977454543114,
0.017599089071154594,
0.03287408873438835,
-0.06318830698728561,
-0.056653909385204315,
-0.03671388700604439,
-0.07490980625152588,
0.004989215172827244,
-0.018441149964928627,
-0.027737511321902275,
0.015216054394841194,
-0.01731278747320175,
-0... |
722,398 | paramz.core.constrainable | unconstrain_fixed |
This parameter will no longer be fixed.
If there was a constraint on this parameter when fixing it,
it will be constraint with that previous constraint.
| def unconstrain_fixed(self):
"""
This parameter will no longer be fixed.
If there was a constraint on this parameter when fixing it,
it will be constraint with that previous constraint.
"""
unconstrained = self.unconstrain(__fixed__)
self._highest_parent_._set_unfixed(self, unconstrained)
... | (self) | [
0.056954722851514816,
0.05751928687095642,
0.029689516872167587,
0.03410641476511955,
-0.07797649502754211,
-0.03530196473002434,
-0.011166778393089771,
-0.03530196473002434,
0.06459296494722366,
-0.04905080050230026,
-0.025006942451000214,
-0.02668403461575508,
-0.0244755856692791,
-0.051... |
722,399 | paramz.core.constrainable | unconstrain_negative |
Remove negative constraint of this parameter.
| def unconstrain_negative(self):
"""
Remove negative constraint of this parameter.
"""
self.unconstrain(NegativeLogexp())
| (self) | [
0.024126533418893814,
0.017461290583014488,
0.06207727640867233,
0.058259159326553345,
-0.05144580081105232,
-0.04413871839642525,
-0.02761550061404705,
-0.0542764738202095,
0.04440203681588173,
-0.05365109071135521,
-0.031548816710710526,
-0.0030281597282737494,
0.012227840721607208,
-0.0... |
722,400 | paramz.core.constrainable | unconstrain_positive |
Remove positive constraint of this parameter.
| def unconstrain_positive(self):
"""
Remove positive constraint of this parameter.
"""
self.unconstrain(Logexp())
| (self) | [
0.009255959652364254,
0.023798702284693718,
0.059676799923181534,
0.06671492755413055,
-0.03911891207098961,
-0.035648949444293976,
-0.019248468801379204,
-0.05790908262133598,
0.04648439586162567,
-0.0474664606153965,
-0.032359033823013306,
-0.008863134309649467,
0.015655748546123505,
-0.... |
722,402 | paramz.parameterized | unlink_parameter |
:param param: param object to remove from being a parameter of this parameterized object.
| def unlink_parameter(self, param):
"""
:param param: param object to remove from being a parameter of this parameterized object.
"""
if not param in self.parameters:
try:
raise HierarchyError("{} does not belong to this object {}, remove parameters directly from their respective pare... | (self, param) | [
0.024013563990592957,
0.03386710211634636,
-0.005586919840425253,
0.032998714596033096,
-0.05327289551496506,
-0.03379621356725693,
-0.055328670889139175,
0.012538447976112366,
0.022542623803019524,
0.016490496695041656,
-0.008099040016531944,
-0.026069339364767075,
0.0044792830012738705,
... |
722,403 | paramz.core.updateable | update_model |
Get or set, whether automatic updates are performed. When updates are
off, the model might be in a non-working state. To make the model work
turn updates on again.
:param bool|None updates:
bool: whether to do updates
None: get the current update state
| def update_model(self, updates=None):
"""
Get or set, whether automatic updates are performed. When updates are
off, the model might be in a non-working state. To make the model work
turn updates on again.
:param bool|None updates:
bool: whether to do updates
None: get the current up... | (self, updates=None) | [
0.053432855755090714,
-0.0010627887677401304,
-0.017828870564699173,
0.02589217759668827,
0.015508429147303104,
-0.04751976206898689,
-0.018599364906549454,
0.037951305508613586,
0.026393895968794823,
0.02275644801557064,
-0.05547555908560753,
-0.06902191787958145,
0.07382406294345856,
0.0... |
722,404 | paramz.core.updateable | update_toggle | null | def update_toggle(self):
self.update_model(not self.update_model())
| (self) | [
0.040589239448308945,
-0.004392371512949467,
0.02589721977710724,
0.03021342307329178,
-0.025169389322400093,
-0.0465472936630249,
-0.01096823439002037,
0.055992159992456436,
0.010443519800901413,
0.01773875020444393,
-0.0522683784365654,
-0.06712965667247772,
0.03872734680771828,
0.067908... |
722,405 | paramz.core.observable_array | ObsAr |
An ndarray which reports changes to its observers.
.. warning::
ObsAr tries to not ever give back an observable array itself. Thus,
if you want to preserve an ObsAr you need to work in memory. Let
`a` be an ObsAr and you want to add a random number `r` to it. You need to
make sure... | class ObsAr(np.ndarray, Pickleable, Observable):
"""
An ndarray which reports changes to its observers.
.. warning::
ObsAr tries to not ever give back an observable array itself. Thus,
if you want to preserve an ObsAr you need to work in memory. Let
`a` be an ObsAr and you want to add... | (input_array, *a, **kw) | [
-0.008930717594921589,
-0.04495418816804886,
-0.017328113317489624,
0.02193407528102398,
0.007112574763596058,
-0.031126605346798897,
-0.08401274681091309,
0.01638752780854702,
0.00041180936386808753,
-0.01523361261934042,
-0.03601377457380295,
-0.017657803371548653,
0.03603316843509674,
0... |
722,406 | paramz.core.observable_array | __array_finalize__ | null | def __array_finalize__(self, obj):
# see InfoArray.__array_finalize__ for comments
if obj is None: return
self.observers = getattr(obj, 'observers', None)
self._update_on = getattr(obj, '_update_on', None)
| (self, obj) | [
0.0011575882090255618,
0.011786352843046188,
-0.02011561393737793,
-0.0010898569598793983,
-0.05491938814520836,
-0.05201758071780205,
-0.05843021720647812,
0.05201758071780205,
-0.005620012525469065,
-0.006264858413487673,
-0.01824376918375492,
-0.01603158935904503,
0.026170002296566963,
... |
722,407 | paramz.core.observable_array | __array_wrap__ | null | def __array_wrap__(self, out_arr, context=None):
#np.ndarray.__array_wrap__(self, out_arr, context)
#return out_arr
return out_arr.view(np.ndarray)
| (self, out_arr, context=None) | [
-0.030554896220564842,
-0.07077288627624512,
-0.007306239567697048,
0.031059935688972473,
-0.00871193315833807,
0.025504499673843384,
-0.05515032634139061,
0.02695227973163128,
0.04010014608502388,
-0.04932553693652153,
0.030201368033885956,
-0.06780998408794403,
-0.015504715964198112,
-0.... |
722,408 | paramz.core.observable_array | __deepcopy__ | null | def __deepcopy__(self, memo):
s = self.__new__(self.__class__, input_array=self.view(np.ndarray).copy())
memo[id(self)] = s
import copy
Pickleable.__setstate__(s, copy.deepcopy(self.__getstate__(), memo))
return s
| (self, memo) | [
-0.008332889527082443,
-0.058901697397232056,
0.06255204230546951,
0.026101745665073395,
-0.09320785850286484,
0.0035528852604329586,
-0.044654715806245804,
0.02588910423219204,
0.0064634159207344055,
-0.019811101257801056,
-0.029007846489548683,
0.04164229705929756,
-0.049687232822179794,
... |
722,409 | paramz.core.observable_array | __getslice__ | null | def __getslice__(self, start, stop): #pragma: no cover
return self.__getitem__(slice(start, stop))
| (self, start, stop) | [
-0.002232555765658617,
-0.02063104324042797,
-0.07605944573879242,
-0.0015739209484308958,
-0.029223186895251274,
-0.0004079104110132903,
0.02094438299536705,
0.009062156081199646,
0.06405353546142578,
-0.06718694418668747,
0.018553094938397408,
-0.000021500332877621986,
0.008534424006938934... |
722,411 | paramz.core.observable_array | __iadd__ | null | def __iadd__(self, *args, **kwargs): #pragma: no cover
r = np.ndarray.__iadd__(self, *args, **kwargs)
self.notify_observers()
return r
| (self, *args, **kwargs) | [
-0.06248942390084267,
-0.07366258651018143,
0.03196394070982933,
0.06784183531999588,
-0.011348788626492023,
-0.011114620603621006,
-0.05442735180258751,
0.009893600828945637,
0.0058667464181780815,
-0.011900756508111954,
0.01633322238922119,
-0.027447843924164772,
0.03065929189324379,
0.0... |
722,412 | paramz.core.observable_array | __iand__ | null | def __iand__(self, *args, **kwargs): #pragma: no cover
r = np.ndarray.__iand__(self, *args, **kwargs)
self.notify_observers()
return r
| (self, *args, **kwargs) | [
-0.005315050482749939,
-0.0894988626241684,
0.02912934683263302,
0.034195318818092346,
-0.03328344598412514,
-0.0156623013317585,
-0.03284439444541931,
0.0008828514255583286,
0.018524575978517532,
-0.00339631293900311,
0.03880535811185837,
-0.01138155348598957,
0.04032514989376068,
0.03914... |
722,413 | paramz.core.observable_array | __idiv__ | null | def __idiv__(self, *args, **kwargs): #pragma: no cover
r = np.ndarray.__idiv__(self, *args, **kwargs)
self.notify_observers()
return r
| (self, *args, **kwargs) | [
-0.0028393499087542295,
-0.09133172035217285,
0.029178224503993988,
0.036316677927970886,
-0.0035586801823228598,
-0.011374276131391525,
-0.03530413284897804,
-0.019322767853736877,
0.0060752807185053825,
0.00992295891046524,
0.012648397125303745,
-0.04519334062933922,
0.017837699502706528,
... |
722,414 | paramz.core.observable_array | __ifloordiv__ | null | def __ifloordiv__(self, *args, **kwargs): #pragma: no cover
r = np.ndarray.__ifloordiv__(self, *args, **kwargs)
self.notify_observers()
return r
| (self, *args, **kwargs) | [
-0.04464462399482727,
-0.0430864654481411,
-0.0008785811369307339,
0.06127627193927765,
-0.0027648843824863434,
-0.011736997403204441,
-0.0007176843355409801,
-0.05314674973487854,
-0.05995522439479828,
0.03217935934662819,
0.0400717668235302,
-0.04295097291469574,
0.05731312930583954,
-0.... |
722,415 | paramz.core.observable_array | __ilshift__ | null | def __ilshift__(self, *args, **kwargs): #pragma: no cover
r = np.ndarray.__ilshift__(self, *args, **kwargs)
self.notify_observers()
return r
| (self, *args, **kwargs) | [
-0.06683988124132156,
-0.03162839263677597,
0.007668503560125828,
0.029468486085534096,
-0.024378474801778793,
-0.039347127079963684,
-0.02585189789533615,
0.01952287182211876,
0.018384316936135292,
-0.01641695946455002,
0.00894937850534916,
-0.05508597567677498,
0.05769795551896095,
0.020... |
722,416 | paramz.core.observable_array | __imod__ | null | def __imod__(self, *args, **kwargs): #pragma: no cover
r = np.ndarray.__imod__(self, *args, **kwargs)
self.notify_observers()
return r
| (self, *args, **kwargs) | [
0.005169818177819252,
-0.06568709760904312,
0.013177967630326748,
0.03564809262752533,
-0.04227086529135704,
-0.011936197988688946,
-0.07136376202106476,
0.050785861909389496,
0.018263312056660652,
0.011040771380066872,
0.02221670188009739,
-0.02502124384045601,
0.002853114390745759,
0.012... |
722,417 | paramz.core.observable_array | __imul__ | null | def __imul__(self, *args, **kwargs): #pragma: no cover
r = np.ndarray.__imul__(self, *args, **kwargs)
self.notify_observers()
return r
| (self, *args, **kwargs) | [
-0.020725766196846962,
-0.08164695650339127,
0.029105322435498238,
0.08336584270000458,
-0.0250890851020813,
-0.025816304609179497,
-0.026841023936867714,
-0.03546849638223648,
-0.01713925041258335,
0.024378392845392227,
0.01841188408434391,
-0.025733666494488716,
0.04412902146577835,
0.02... |
722,418 | paramz.core.pickleable | __init__ | null | def __init__(self, *a, **kw):
super(Pickleable, self).__init__()
| (self, *a, **kw) | [
-0.036233264952898026,
-0.00512476172298193,
-0.022744344547390938,
0.027971943840384483,
-0.03585619106888771,
-0.003877850715070963,
-0.0387013778090477,
0.05457271263003349,
-0.018082354217767715,
-0.02226443402469158,
-0.010258093476295471,
0.068181611597538,
-0.06585061550140381,
0.03... |
722,419 | paramz.core.observable_array | __ior__ | null | def __ior__(self, *args, **kwargs): #pragma: no cover
r = np.ndarray.__ior__(self, *args, **kwargs)
self.notify_observers()
return r
| (self, *args, **kwargs) | [
-0.025687258690595627,
-0.07260666787624359,
0.0047822026535868645,
0.03454779088497162,
-0.03984754532575607,
-0.04024503007531166,
-0.03477965295314789,
0.02318643592298031,
0.025041351094841957,
0.004591742530465126,
0.03842323645949364,
-0.014731667935848236,
0.021381206810474396,
0.03... |
722,420 | paramz.core.observable_array | __ipow__ | null | def __ipow__(self, *args, **kwargs): #pragma: no cover
r = np.ndarray.__ipow__(self, *args, **kwargs)
self.notify_observers()
return r
| (self, *args, **kwargs) | [
-0.026321809738874435,
-0.08141756057739258,
-0.0033888258039951324,
0.018948273733258247,
-0.032254934310913086,
-0.02352672442793846,
-0.0177136342972517,
0.01903401128947735,
0.049762796610593796,
0.0023213778622448444,
0.024881398305296898,
-0.040057163685560226,
0.039954278618097305,
... |
722,421 | paramz.core.observable_array | __irshift__ | null | def __irshift__(self, *args, **kwargs): #pragma: no cover
r = np.ndarray.__irshift__(self, *args, **kwargs)
self.notify_observers()
return r
| (self, *args, **kwargs) | [
-0.04776468127965927,
-0.051474884152412415,
0.006931561045348644,
0.019286368042230606,
-0.016645774245262146,
-0.03543076291680336,
-0.027926795184612274,
0.03593214228749275,
0.03619954362511635,
-0.0034407114144414663,
0.01898554153740406,
-0.042984869331121445,
0.0525779165327549,
0.0... |
722,422 | paramz.core.observable_array | __isub__ | null | def __isub__(self, *args, **kwargs): #pragma: no cover
r = np.ndarray.__isub__(self, *args, **kwargs)
self.notify_observers()
return r
| (self, *args, **kwargs) | [
-0.011854873038828373,
-0.06287078559398651,
-0.028854627162218094,
0.035864319652318954,
-0.07705667614936829,
-0.00036864366848021746,
-0.0327007994055748,
0.03789563104510307,
0.022061385214328766,
0.001705594826489687,
0.0016847822116687894,
-0.015717696398496628,
-0.0019220461836084723,... |
722,423 | paramz.core.observable_array | __itruediv__ | null | def __itruediv__(self, *args, **kwargs): #pragma: no cover
r = np.ndarray.__itruediv__(self, *args, **kwargs)
self.notify_observers()
return r
| (self, *args, **kwargs) | [
0.00020999570551794022,
-0.09426497668027878,
0.008015410974621773,
0.049613144248723984,
-0.008499649353325367,
-0.0158014465123415,
-0.06402134150266647,
-0.0030286104883998632,
0.013813522644340992,
0.01255620364099741,
0.03168784826993942,
0.0017224426846951246,
0.010568278841674328,
0... |
722,424 | paramz.core.observable_array | __ixor__ | null | def __ixor__(self, *args, **kwargs): #pragma: no cover
r = np.ndarray.__ixor__(self, *args, **kwargs)
self.notify_observers()
return r
| (self, *args, **kwargs) | [
-0.019287094473838806,
-0.092658631503582,
0.037902750074863434,
0.0377013199031353,
-0.00973587017506361,
-0.0370970256626606,
-0.044650718569755554,
0.017793143168091774,
0.045288585126399994,
-0.004326587542891502,
0.054823022335767746,
-0.006559123285114765,
0.025531481951475143,
-0.00... |
722,425 | paramz.core.observable_array | __new__ | null | def __new__(cls, input_array, *a, **kw):
# allways make a copy of input paramters, as we need it to be in C order:
if not isinstance(input_array, ObsAr):
try:
# try to cast ints to floats
obj = np.atleast_1d(np.require(input_array, dtype=np.float_, requirements=['W', 'C'])).view(... | (cls, input_array, *a, **kw) | [
0.0028019226156175137,
-0.05819237232208252,
0.015816716477274895,
-0.03411591798067093,
-0.002194991335272789,
-0.03033742867410183,
-0.045268844813108444,
0.015853222459554672,
-0.022908227518200874,
-0.008624810725450516,
-0.020955095067620277,
-0.011271577328443527,
-0.007246666122227907... |
722,426 | paramz.core.observable_array | __reduce__ | null | def __reduce__(self):
func, args, state = super(ObsAr, self).__reduce__()
return func, args, (state, Pickleable.__getstate__(self))
| (self) | [
-0.003977487329393625,
-0.04569190740585327,
-0.03935941308736801,
0.02639704756438732,
0.011020636186003685,
-0.019469790160655975,
-0.0490155927836895,
-0.024962615221738815,
0.03465377911925316,
-0.04156354069709778,
-0.014781646430492401,
0.042158305644989014,
0.011204313486814499,
0.0... |
722,427 | paramz.core.observable_array | __setitem__ | null | def __setitem__(self, s, val):
super(ObsAr, self).__setitem__(s, val)
self.notify_observers()
| (self, s, val) | [
0.02310645952820778,
-0.0020774633157998323,
-0.0429903082549572,
0.005091394297778606,
-0.014127996750175953,
-0.013239286839962006,
-0.06275787204504013,
0.04980098083615303,
0.03584740310907364,
-0.002906995126977563,
-0.06392066925764084,
-0.007109679747372866,
0.03993380814790726,
0.0... |
722,428 | paramz.core.observable_array | __setslice__ | null | def __setslice__(self, start, stop, val): #pragma: no cover
return self.__setitem__(slice(start, stop), val)
| (self, start, stop, val) | [
0.018184136599302292,
0.0048734149895608425,
-0.07247132807970047,
-0.01497663464397192,
-0.03825796768069267,
0.029837235808372498,
-0.02494724467396736,
0.022908367216587067,
0.0321744866669178,
-0.05562986806035042,
-0.03036767616868019,
-0.022162435576319695,
0.023289620876312256,
0.01... |
722,429 | paramz.core.observable_array | __setstate__ | null | def __setstate__(self, state):
np.ndarray.__setstate__(self, state[0])
Pickleable.__setstate__(self, state[1])
| (self, state) | [
-0.022009065374732018,
-0.014725489541888237,
0.011989750899374485,
0.048909034579992294,
-0.04894421994686127,
-0.011391582898795605,
-0.08128047734498978,
0.025844378396868706,
0.009333181194961071,
-0.03026026487350464,
-0.03916241228580475,
0.022818351164460182,
-0.013370814733207226,
... |
722,430 | paramz.core.observable_array | _setup_observers | null | def _setup_observers(self):
# do not setup anything, as observable arrays do not have default observers
pass
| (self) | [
-0.02245447412133217,
0.03535953536629677,
0.0038064089603722095,
-0.01995025761425495,
-0.015643004328012466,
0.01869814842939377,
-0.05479225516319275,
0.050885677337646484,
0.004595237318426371,
0.050184495747089386,
0.0023518765810877085,
0.006803121417760849,
0.057530198246240616,
0.0... |
722,433 | paramz.core.observable_array | copy |
Make a copy. This means, we delete all observers and return a copy of this
array. It will still be an ObsAr!
| def copy(self):
"""
Make a copy. This means, we delete all observers and return a copy of this
array. It will still be an ObsAr!
"""
from .lists_and_dicts import ObserverList
memo = {}
memo[id(self)] = self
memo[id(self.observers)] = ObserverList()
return self.__deepcopy__(memo)
| (self) | [
-0.01777256466448307,
-0.016589531674981117,
-0.044323038309812546,
-0.04396180808544159,
-0.07621973752975464,
-0.030939431861042976,
-0.05953086540102959,
0.031770262867212296,
0.04862168803811073,
0.016047686338424683,
-0.052884213626384735,
-0.054618123918771744,
-0.02266724407672882,
... |
722,438 | paramz.param | Param |
Parameter object for GPy models.
:param str name: name of the parameter to be printed
:param input_array: array which this parameter handles
:type input_array: np.ndarray
:param default_constraint: The default constraint for this parameter
:type default_constraint:
... | class Param(Parameterizable, ObsAr):
"""
Parameter object for GPy models.
:param str name: name of the parameter to be printed
:param input_array: array which this parameter handles
:type input_array: np.ndarray
:param default_constraint: The default constraint for this... | (name, input_array, default_constraint=None) | [
0.052980951964855194,
-0.045336730778217316,
-0.035008903592824936,
0.0405997559428215,
-0.011527321301400661,
-0.022282090038061142,
-0.06489454954862595,
-0.05058196932077408,
0.0005435197963379323,
-0.05208641663193703,
-0.013489202596247196,
-0.034033045172691345,
0.006337993778288364,
... |
722,439 | paramz.param | __array_finalize__ | null | def __array_finalize__(self, obj):
# see InfoArray.__array_finalize__ for comments
if obj is None: return
super(Param, self).__array_finalize__(obj)
self._parent_ = getattr(obj, '_parent_', None)
self._parent_index_ = getattr(obj, '_parent_index_', None)
self._default_constraint_ = getattr(obj, ... | (self, obj) | [
0.02870084159076214,
-0.019589178264141083,
-0.007426814176142216,
0.015895988792181015,
-0.05887536332011223,
-0.0332476869225502,
-0.0341462716460228,
-0.014422307722270489,
-0.014772756025195122,
-0.03355320543050766,
-0.00827597826719284,
-0.03881892189383507,
0.027334989979863167,
-0.... |
722,441 | paramz.param | __deepcopy__ | null | def __deepcopy__(self, memo):
s = self.__new__(self.__class__, name=self.name, input_array=self.view(np.ndarray).copy())
memo[id(self)] = s
import copy
Pickleable.__setstate__(s, copy.deepcopy(self.__getstate__(), memo))
return s
| (self, memo) | [
-0.008205674588680267,
-0.060814350843429565,
0.06092091649770737,
0.021988365799188614,
-0.09385018795728683,
0.0030194041319191456,
-0.04539762809872627,
0.023498067632317543,
0.005923360586166382,
-0.017530305311083794,
-0.025700457394123077,
0.03804449364542961,
-0.05093912407755852,
0... |
722,442 | paramz.param | __getitem__ | null | def __getitem__(self, s, *args, **kwargs):
if not isinstance(s, tuple):
s = (s,)
#if not reduce(lambda a, b: a or np.any(b is Ellipsis), s, False) and len(s) <= self.ndim:
# s += (Ellipsis,)
new_arr = super(Param, self).__getitem__(s, *args, **kwargs)
try:
new_arr._current_slice_ ... | (self, s, *args, **kwargs) | [
-0.007665671408176422,
-0.05357326194643974,
-0.01885254681110382,
0.011655460111796856,
-0.041271794587373734,
0.004076226614415646,
-0.0290067195892334,
-0.014840012416243553,
0.05695798620581627,
-0.018343020230531693,
0.005850476678460836,
-0.0007984126568771899,
0.01325683481991291,
-... |
722,452 | paramz.param | __init__ | null | def __init__(self, name, input_array, default_constraint=None, *a, **kw):
self._in_init_ = True
super(Param, self).__init__(name=name, default_constraint=default_constraint, *a, **kw)
self._in_init_ = False
| (self, name, input_array, default_constraint=None, *a, **kw) | [
0.013494282960891724,
0.0006197454058565199,
0.027385203167796135,
-0.008657035417854786,
-0.04173311963677406,
-0.01329596433788538,
-0.03392109274864197,
-0.027609389275312424,
0.02095278538763523,
-0.03314506262540817,
-0.005078678950667381,
-0.015417110174894333,
0.0004683119768742472,
... |
722,459 | paramz.param | __new__ | null | def __new__(cls, name, input_array, default_constraint=None):
obj = super(Param, cls).__new__(cls, input_array=input_array)
obj._current_slice_ = (slice(obj.shape[0]),)
obj._realshape_ = obj.shape
obj._realsize_ = obj.size
obj._realndim_ = obj.ndim
obj._original_ = obj
return obj
| (cls, name, input_array, default_constraint=None) | [
0.052082572132349014,
-0.03790046274662018,
-0.0036590539384633303,
-0.020068032667040825,
-0.04195249453186989,
-0.006239603739231825,
-0.032852888107299805,
-0.04715725779533386,
0.030233042314648628,
-0.021674873307347298,
0.02361355908215046,
-0.009125802665948868,
-0.009937955066561699,... |
722,461 | paramz.param | __repr__ | null | def __repr__(self, *args, **kwargs):
name = "\033[1m{x:s}\033[0;0m:\n".format(
x=self.hierarchy_name())
return name + super(Param, self).__repr__(*args, **kwargs)
| (self, *args, **kwargs) | [
0.018413826823234558,
-0.035287465900182724,
0.07372376322746277,
0.020262055099010468,
0.01112359482795,
-0.026799306273460388,
-0.0006914811674505472,
-0.04216698184609413,
0.038641657680273056,
-0.010969575494527817,
0.0046334052458405495,
-0.014357993379235268,
0.013083058409392834,
0.... |
722,464 | paramz.core.parameter_core | __setstate__ | null | def __setstate__(self, state):
super(Parameterizable, self).__setstate__(state)
self.logger = logging.getLogger(self.__class__.__name__)
return self
| (self, state) | [
-0.03876565396785736,
-0.02236619032919407,
0.03565572202205658,
0.03811473771929741,
-0.0005760492058470845,
0.002454495057463646,
-0.04437076300382614,
-0.01661643385887146,
0.024282775819301605,
-0.01699613593518734,
-0.027754327282309532,
0.037789277732372284,
-0.016390422359108925,
0.... |
722,465 | paramz.param | __str__ | null | def __str__(self, indices=None, iops=None, lx=None, li=None, lls=None, only_name=False, VT100=True):
filter_ = self._current_slice_
vals = self.flat
if indices is None: indices = self._indices(filter_)
if iops is None:
ravi = self._raveled_index(filter_)
iops = OrderedDict([name, iop.pro... | (self, indices=None, iops=None, lx=None, li=None, lls=None, only_name=False, VT100=True) | [
0.00007056921458570287,
-0.05846690014004707,
0.04540867730975151,
-0.026079557836055756,
0.016894536092877388,
-0.035227689892053604,
-0.017918167635798454,
-0.07296374440193176,
0.03579945117235184,
-0.033235758543014526,
-0.010282428003847599,
0.005574643611907959,
0.023958519101142883,
... |
722,469 | paramz.core.gradcheckable | _checkgrad |
Perform the checkgrad on the model.
TODO: this can be done more efficiently, when doing it inside here
| def _checkgrad(self, param, verbose=0, step=1e-6, tolerance=1e-3, df_tolerance=1e-12):
"""
Perform the checkgrad on the model.
TODO: this can be done more efficiently, when doing it inside here
"""
raise HierarchyError("This parameter is not in a model with a likelihood, and, therefore, cannot be gr... | (self, param, verbose=0, step=1e-06, tolerance=0.001, df_tolerance=1e-12) | [
0.03088936023414135,
0.030706088989973068,
0.018093766644597054,
0.08150525391101837,
-0.029789738357067108,
0.013745265081524849,
-0.031589116901159286,
-0.03605424612760544,
-0.01032144483178854,
-0.00923848431557417,
0.005348157603293657,
-0.022992080077528954,
0.07264164090156555,
-0.0... |
722,471 | paramz.core.parameter_core | _connect_parameters | null | def _connect_parameters(self):
pass
| (self) | [
-0.03759539872407913,
-0.06935643404722214,
0.02138691395521164,
0.007461254019290209,
-0.009036359377205372,
0.02729032374918461,
-0.024580279365181923,
0.06618033349514008,
0.05278545990586281,
-0.0046303789131343365,
-0.031761035323143005,
0.02007504552602768,
0.017537614330649376,
0.05... |
722,473 | paramz.param | _ensure_fixes | null | def _ensure_fixes(self):
if (not hasattr(self, "_fixes_")) or (self._fixes_ is None) or (self._fixes_.size != self._realsize_): self._fixes_ = np.ones(self._realsize_, dtype=bool)
| (self) | [
-0.0011122984578832984,
0.02402394637465477,
0.023887833580374718,
0.011442000046372414,
-0.0018173212883993983,
-0.000007024142178124748,
-0.0420929491519928,
0.06509604305028915,
0.01881762407720089,
-0.018188100308179855,
0.007001312915235758,
0.017609620466828346,
0.023037126287817955,
... |
722,474 | paramz.param | _format_spec | null | def _format_spec(self, indices, iops, lx=None, li=None, lls=None, VT100=True):
if li is None: li = self._max_len_index(indices)
if lx is None: lx = self._max_len_values()
if lls is None: lls = [self._max_len_names(iop, name) for name, iop in iops.items()]
if VT100:
format_spec = [" \033[1m{{ind... | (self, indices, iops, lx=None, li=None, lls=None, VT100=True) | [
0.03039134293794632,
-0.027195041999220848,
0.015301626175642014,
-0.05212971568107605,
0.0237515140324831,
0.0013310560025274754,
-0.03191002830862999,
-0.029243499040603638,
-0.02104966901242733,
0.017111685127019882,
0.014030169695615768,
-0.00151537312194705,
-0.015178011730313301,
-0.... |
722,475 | paramz.param | _get_original | null | def _get_original(self, param):
return self._original_
| (self, param) | [
0.05366632714867592,
-0.015582672320306301,
0.016241559758782387,
0.0691831111907959,
-0.03917082026600838,
-0.04819756746292114,
0.015244993381202221,
0.03574460744857788,
0.1296689212322235,
-0.013202443718910217,
-0.005258739925920963,
-0.05478643625974655,
-0.04490313306450844,
0.00625... |
722,477 | paramz.param | _indices | null | def _indices(self, slice_index=None):
# get a int-array containing all indices in the first axis.
if slice_index is None:
slice_index = self._current_slice_
#try:
indices = np.indices(self._realshape_, dtype=int)
indices = indices[(slice(None),)+slice_index]
indices = np.rollaxis(indices... | (self, slice_index=None) | [
-0.05670264735817909,
-0.05456086993217468,
-0.009007262997329235,
0.04022185131907463,
0.010926694609224796,
-0.024630438536405563,
-0.01412121020257473,
0.042617738246917725,
-0.02582838200032711,
-0.008893821388483047,
-0.010917618870735168,
-0.022343456745147705,
0.006761119235306978,
... |
722,478 | paramz.param | _max_len_index | null | def _max_len_index(self, ind):
return reduce(lambda a, b: max(a, len(str(b))), ind, len(__index_name__))
| (self, ind) | [
0.013926810584962368,
-0.000996735179796815,
0.02577347867190838,
0.04211021214723587,
-0.006354582961648703,
0.013994458131492138,
-0.0003791927301790565,
0.024775687605142593,
0.05452342331409454,
-0.08286748081445694,
-0.00003005795952049084,
0.013690046966075897,
-0.01498379372060299,
... |
722,479 | paramz.param | _max_len_names | null | def _max_len_names(self, gen, header):
return reduce(lambda a, b: max(a, len(" ".join(map(str, b)))), gen, len(header))
| (self, gen, header) | [
0.0004445631057024002,
0.02068476565182209,
0.018839409574866295,
-0.0026673786342144012,
-0.021305477246642113,
0.005716410465538502,
0.0015329038724303246,
0.00027470645727589726,
0.0542534738779068,
-0.05089827999472618,
0.018839409574866295,
0.03791368380188942,
0.003938158042728901,
-... |
722,480 | paramz.param | _max_len_values | null | def _max_len_values(self):
return reduce(lambda a, b: max(a, len("{x:=.{0}g}".format(__precision__, x=b))), self.flat, len(self.hierarchy_name()))
| (self) | [
0.005833727307617664,
0.007182937581092119,
0.025870569050312042,
0.054893575608730316,
-0.0006419455748982728,
0.015787899494171143,
0.00659613823518157,
-0.0458131805062294,
0.037795014679431915,
-0.022375471889972687,
0.010493856854736805,
0.028286296874284744,
0.002077355282381177,
-0.... |
722,488 | paramz.param | _raveled_index | null | def _raveled_index(self, slice_index=None):
# return an index array on the raveled array, which is formed by the current_slice
# of this object
extended_realshape = np.cumprod((1,) + self._realshape_[:0:-1])[::-1]
ind = self._indices(slice_index)
if ind.ndim < 2: ind = ind[:, None]
return np.asa... | (self, slice_index=None) | [
-0.034796856343746185,
-0.045568596571683884,
-0.032045476138591766,
0.08732482045888901,
0.023773355409502983,
-0.03952635079622269,
-0.013873784802854061,
0.02988753281533718,
0.008105779066681862,
-0.01133820042014122,
-0.006338961888104677,
-0.01116736326366663,
-0.0059118689969182014,
... |
722,489 | paramz.param | _raveled_index_for | null | def _raveled_index_for(self, obj):
return self._raveled_index()
| (self, obj) | [
0.01698678359389305,
-0.026551751419901848,
-0.05363720655441284,
0.04619871452450752,
0.020997898653149605,
-0.028369680047035217,
0.01133286114782095,
0.03333979472517967,
-0.007104928605258465,
-0.03227238729596138,
-0.03822651877999306,
-0.011774834245443344,
-0.010165384970605373,
-0.... |
722,493 | paramz.param | _repr_html_ | Representation of the parameter in html for notebook display. | def _repr_html_(self, indices=None, iops=None, lx=None, li=None, lls=None):
"""Representation of the parameter in html for notebook display."""
filter_ = self._current_slice_
vals = self.flat
if indices is None: indices = self._indices(filter_)
if iops is None:
ravi = self._raveled_index(fil... | (self, indices=None, iops=None, lx=None, li=None, lls=None) | [
0.0006218152120709419,
-0.05440300703048706,
-0.008686781860888004,
-0.014364629983901978,
0.009716153144836426,
-0.005090966355055571,
-0.0464288666844368,
-0.04445396363735199,
-0.022171087563037872,
-0.002394104842096567,
0.012995238415896893,
0.016842573881149292,
0.02541291154921055,
... |
722,496 | paramz.param | _setup_observers |
Setup the default observers
1: pass through to parent, if present
| def _setup_observers(self):
"""
Setup the default observers
1: pass through to parent, if present
"""
if self.has_parent():
self.add_observer(self._parent_, self._parent_._pass_through_notify_observers, -np.inf)
| (self) | [
-0.01617036759853363,
0.04101330414414406,
0.008676888421177864,
0.03282446414232254,
-0.0477164052426815,
0.007290486246347427,
-0.0003239256329834461,
0.06312663108110428,
0.03914749249815941,
0.059014931321144104,
0.008612102828919888,
-0.020282063633203506,
0.051309820264577866,
0.0066... |
722,503 | paramz.param | build_pydot |
Build a pydot representation of this model. This needs pydot installed.
Example Usage:
np.random.seed(1000)
X = np.random.normal(0,1,(20,2))
beta = np.random.uniform(0,1,(2,1))
Y = X.dot(beta)
m = RidgeRegression(X, Y)
G = m.build_pydot()
G.writ... | def build_pydot(self,G): # pragma: no cover
"""
Build a pydot representation of this model. This needs pydot installed.
Example Usage:
np.random.seed(1000)
X = np.random.normal(0,1,(20,2))
beta = np.random.uniform(0,1,(2,1))
Y = X.dot(beta)
m = RidgeRegression(X, Y)
G = m.build_pydot... | (self, G) | [
0.05118698626756668,
-0.08412983268499374,
0.07659582048654556,
0.03543572500348091,
-0.039775166660547256,
-0.037060707807540894,
-0.06865555793046951,
-0.007363207172602415,
0.061934035271406174,
-0.011919624172151089,
0.00491188233718276,
-0.027476996183395386,
0.0013110663276165724,
0.... |
722,511 | paramz.param | copy | null | def copy(self):
return Parameterizable.copy(self, which=self)
| (self) | [
0.01612955890595913,
-0.0337752103805542,
0.014605041593313217,
-0.03153476119041443,
-0.0718291774392128,
-0.00038007640978321433,
0.01068846508860588,
-0.01451239176094532,
0.07263775914907455,
0.002931115683168173,
-0.013375320471823215,
-0.03244441747665405,
-0.05788110941648483,
0.064... |
722,515 | paramz.param | get_property_string | null | def get_property_string(self, propname):
prop = self._index_operations[propname]
return [' '.join(map(lambda c: str(c[0]) if c[1].size == self._realsize_ else "{" + str(c[0]) + "}", prop.items()))]
| (self, propname) | [
0.038798317313194275,
-0.05990098789334297,
0.031601857393980026,
-0.02616105228662491,
0.04655103012919426,
-0.016435399651527405,
-0.011698597110807896,
-0.061395905911922455,
0.050618596374988556,
-0.04196198284626007,
0.02440539374947548,
0.03938933461904526,
-0.007956958375871181,
-0.... |
722,520 | paramz.param | parameter_names | null | def parameter_names(self, add_self=False, adjust_for_printing=False, recursive=True, **kw):
# this is just overwrighting the parameterized calls to
# parameter names, in order to maintain OOP
if adjust_for_printing:
return [adjust_name_for_printing(self.name)]
return [self.name]
| (self, add_self=False, adjust_for_printing=False, recursive=True, **kw) | [
-0.00501333037391305,
-0.016897102817893028,
0.023383915424346924,
0.01542361918836832,
-0.04837209731340408,
-0.014054762199521065,
0.00850086472928524,
-0.03668886050581932,
0.06322899460792542,
-0.011055483482778072,
-0.005667243152856827,
-0.03225969150662422,
0.038188498467206955,
0.0... |
722,541 | paramz.parameterized | Parameterized |
Say m is a handle to a parameterized class.
Printing parameters::
- print m: prints a nice summary over all parameters
- print m.name: prints details for param with name 'name'
- print m[regexp]: prints details for all the parameters
which m... | class Parameterized(with_metaclass(ParametersChangedMeta, Parameterizable)):
"""
Say m is a handle to a parameterized class.
Printing parameters::
- print m: prints a nice summary over all parameters
- print m.name: prints details for param with name 'name'
- print m... | (*args, **kw) | [
0.049715202301740646,
-0.01406856719404459,
-0.023834053426980972,
0.04791877046227455,
-0.022330064326524734,
-0.012669021263718605,
-0.0677630752325058,
-0.002317344769835472,
0.009013491682708263,
-0.030246896669268608,
-0.020940963178873062,
-0.014987671747803688,
-0.0022794839460402727,... |
722,545 | paramz.parameterized | __init__ | null | def __init__(self, name=None, parameters=[]):
super(Parameterized, self).__init__(name=name)
self.size = sum(p.size for p in self.parameters)
self.add_observer(self, self._parameters_changed_notification, -100)
self._fixes_ = None
self._param_slices_ = []
#self._connect_parameters()
self.lin... | (self, name=None, parameters=[]) | [
0.031211670488119125,
-0.017545340582728386,
-0.015103000216186047,
-0.0042449128814041615,
-0.03580901399254799,
0.013702246360480785,
-0.07679004222154617,
0.00024313967151101679,
0.005454858765006065,
0.026686158031225204,
-0.023884648457169533,
0.0382513552904129,
-0.038790106773376465,
... |
722,549 | paramz.parameterized | __str__ | null | def __str__(self, header=True, VT100=True):
name = adjust_name_for_printing(self.name) + "."
names = self.parameter_names(adjust_for_printing=True)
desc = self._description_str
iops = OrderedDict()
for opname in self._index_operations:
iops[opname] = self.get_property_string(opname)
form... | (self, header=True, VT100=True) | [
0.02090860716998577,
-0.03470580652356148,
0.0294564850628376,
-0.06359479576349258,
0.047031063586473465,
-0.07391609251499176,
-0.005284787621349096,
-0.0771791860461235,
0.021919455379247665,
-0.0345284640789032,
-0.02119235321879387,
0.00288845575414598,
0.008698618970811367,
0.0145509... |
722,573 | paramz.parameterized | _repr_html_ | Representation of the parameters in html for notebook display. | def _repr_html_(self, header=True):
"""Representation of the parameters in html for notebook display."""
name = adjust_name_for_printing(self.name) + "."
names = self.parameter_names()
desc = self._description_str
iops = OrderedDict()
for opname in self._index_operations:
iop = []
... | (self, header=True) | [
0.016852186992764473,
-0.0570770762860775,
-0.005274210590869188,
-0.03021833673119545,
0.014657609164714813,
-0.0059425183571875095,
-0.03771422058343887,
-0.03408368304371834,
-0.011171572841703892,
-0.01166828814893961,
0.0073694451712071896,
0.0053419447503983974,
0.00429884297773242,
... |
722,626 | paramz | _unpickle | null | def _unpickle(file_or_path, pickle, strcl, p3kw):
if isinstance(file_or_path, strcl):
with open(file_or_path, 'rb') as f:
m = pickle.load(f, **p3kw)
else:
m = pickle.load(file_or_path, **p3kw)
return m
| (file_or_path, pickle, strcl, p3kw) | [
0.03422261402010918,
-0.010872992686927319,
-0.010696769692003727,
0.06456831097602844,
-0.05219741538167,
-0.03760610520839691,
0.0014119911938905716,
0.05875293165445328,
0.031825970858335495,
-0.011445719748735428,
0.017869068309664726,
0.031878840178251266,
-0.08853471279144287,
0.0145... |
722,632 | paramz | load |
Load a previously pickled model, using `m.pickle('path/to/file.pickle)'`
:param file_name: path/to/file.pickle
| def load(file_or_path):
"""
Load a previously pickled model, using `m.pickle('path/to/file.pickle)'`
:param file_name: path/to/file.pickle
"""
from pickle import UnpicklingError
_python3 = True
try:
import cPickle as pickle
_python3 = False
except ImportError: #python3
... | (file_or_path) | [
0.03922893479466438,
-0.013710477389395237,
-0.0209006629884243,
0.08288809657096863,
-0.01516637858003378,
-0.04022930935025215,
-0.03740682825446129,
0.015193173661828041,
0.021150756627321243,
-0.02383032813668251,
0.005390406120568514,
0.029314519837498665,
-0.0771716758608818,
0.01191... |
722,671 | stackprinter.tracing | TracePrinter |
Print a trace of all calls & returns in a piece of code as they are executed
Example:
```
with Traceprinter(style='color', depth_limit=5):
dosomething()
dosomethingelse()
```
Params
---
Accepts all keyword wargs accepted by stackprinter.format, and:
depth_limit: i... | class TracePrinter():
"""
Print a trace of all calls & returns in a piece of code as they are executed
Example:
```
with Traceprinter(style='color', depth_limit=5):
dosomething()
dosomethingelse()
```
Params
---
Accepts all keyword wargs accepted by stackprinter.for... | (suppressed_paths=[], depth_limit=20, print_function=<built-in function print>, stop_on_exception=True, **formatter_kwargs) | [
0.02295651100575924,
-0.01983124203979969,
0.008390869945287704,
0.040533773601055145,
-0.024301322177052498,
-0.01739732176065445,
-0.0383366160094738,
0.019433481618762016,
0.0023119875695556402,
-0.07193797826766968,
-0.015578985214233398,
-0.02916916273534298,
0.025494607165455818,
-0.... |
722,672 | stackprinter.tracing | __enter__ | null | def __enter__(self):
depth = count_stack(sys._getframe(1))
self.enable(current_depth=depth)
return self
| (self) | [
0.01719403825700283,
-0.023936133831739426,
0.011586918495595455,
0.04804166778922081,
-0.017871635034680367,
0.041299570351839066,
-0.010333362966775894,
-0.03243998438119888,
0.001252496731467545,
-0.03150828555226326,
-0.000028238746381248347,
-0.05339468643069267,
-0.005513950251042843,
... |
722,673 | stackprinter.tracing | __exit__ | null | def __exit__(self, etype, evalue, tb):
self.disable()
if etype is None:
return True
| (self, etype, evalue, tb) | [
0.06537878513336182,
0.01919250376522541,
0.03374221920967102,
-0.015852801501750946,
-0.02778770960867405,
-0.042699869722127914,
-0.006735499016940594,
-0.005531652830541134,
-0.01020033285021782,
-0.04597916454076767,
-0.0033957960549741983,
-0.009829254820942879,
-0.009846514090895653,
... |
722,674 | stackprinter.tracing | __init__ | null | def __init__(self,
suppressed_paths=[],
depth_limit=20,
print_function=print,
stop_on_exception=True,
**formatter_kwargs):
self.fmt = get_formatter(**formatter_kwargs)
self.fmt_style = formatter_kwargs.get('style', 'plaintext')
assert isinstan... | (self, suppressed_paths=[], depth_limit=20, print_function=<built-in function print>, stop_on_exception=True, **formatter_kwargs) | [
-0.01953206956386566,
0.004442189354449511,
0.027055533602833748,
-0.004625302739441395,
-0.029894918203353882,
0.016801197081804276,
-0.02065335586667061,
-0.011104343459010124,
-0.030491730198264122,
-0.011176683939993382,
0.0005784453824162483,
0.04760037735104561,
0.002861990826204419,
... |
722,675 | stackprinter.tracing | disable | null | def disable(self):
sys.settrace(self.trace_before)
try:
del self.previous_frame
except AttributeError:
pass
| (self) | [
-0.012783597223460674,
0.0405823215842247,
-0.0009669617284089327,
0.05309216305613518,
-0.07924005389213562,
-0.028188619762659073,
-0.04555971175432205,
0.06746022403240204,
-0.007300172001123428,
-0.04356875643134117,
-0.04688701406121254,
-0.03265167772769928,
-0.016823578625917435,
-0... |
722,676 | stackprinter.tracing | enable | null | def enable(self, force=False, current_depth=None):
if current_depth is None:
current_depth = count_stack(sys._getframe(1))
self.starting_depth = current_depth
self.previous_frame = None
self.trace_before = sys.gettrace()
if (self.trace_before is not None) and not force:
raise Excepti... | (self, force=False, current_depth=None) | [
0.034130681306123734,
0.016977375373244286,
0.01443516742438078,
0.051442328840494156,
-0.02561560459434986,
0.015464366413652897,
-0.052568286657333374,
0.01968671940267086,
0.021533997729420662,
-0.03029537945985794,
0.01710052788257599,
-0.09683261811733246,
-0.015912991017103195,
-0.03... |
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