Query Sampler (Implementation)

Query Sampler (Implementation)#

alts.modules.query.query_sampler

Core Module

class AllDataPoolQuerySampler(num_queries)[source]#

Bases: DataPoolQuerySampler

Description

Samples all of the Data Pool’s data (asbtract).

Parameters:: num_queries (int) – Number of queries to sample by default (ignored in this class)

num_queries: int = None#

sample(self, num_queries) → queries[source]#

Description

Returns all queries in the data pool.

Parameters:: num_queries (Any) – Unused
Returns:: Sampled queries
Return type:: NDArray

class AllProcessPoolQuerySampler(num_queries)[source]#

Bases: AllDataPoolQuerySampler

Description

Samples the entire ProcessDataPools.

Parameters:: num_queries (int) – Number of queries to sample by default (ignored in this class)

property data_pools: ProcessDataPools#

Description

Returns the sampler’s DataPools.

Returns:: QuerySampler’s DataPools
Return type:: ProcessDataPools

pool(self) → QueriedDataPool[source]#

Description

Returns the sampler’s data pools as a queryable.

Returns:: Sampler’s queryable data pool
Return type:: QueriedDataPool

post_init(self) → None[source]#

Description

Raises TypeError if DataPools is not ProcessDataPools

Raises:: TypeError – If DataPools is not ProcessDataPools

class AllResultPoolQuerySampler(num_queries)[source]#

Bases: AllDataPoolQuerySampler

Description

Samples the entire ResultDataPools.

Parameters:: num_queries (int) – Number of queries to sample by default (ignored in this class)

property data_pools: ResultDataPools#

Description

Returns the sampler’s DataPools.

Returns:: QuerySampler’s DataPools
Return type:: ResultDataPools

pool(self) → QueriedDataPool[source]#

Description

Returns the sampler’s data pools as a queryable.

Returns:: Sampler’s queryable data pool
Return type:: QueriedDataPool

post_init(self) → None[source]#

Description

Raises TypeError if DataPools is not ResultDataPools

Raises:: TypeError – If DataPools is not ResultDataPools

class AllStreamPoolQuerySampler(num_queries)[source]#

Bases: AllDataPoolQuerySampler

Description

Samples the entire StreamDataPools.

Parameters:: num_queries (int) – Number of queries to sample by default (ignored in this class)

property data_pools: StreamDataPools#

Description

Returns the sampler’s DataPools.

Returns:: QuerySampler’s DataPools
Return type:: StreamDataPools

pool(self) → QueriedDataPool[source]#

Description

Returns the sampler’s data pools as a queryable.

Returns:: Sampler’s queryable data pool
Return type:: QueriedDataPool

post_init(self) → None[source]#

Description

Raises TypeError if DataPools is not StreamDataPools

Raises:: TypeError – If DataPools is not StreamDataPools

class DataPoolQuerySampler(num_queries)[source]#

Bases: QuerySampler

Description

Samples from Queried Data Pools in some way (this class is abstract).

Parameters:: num_queries (int) – Number of queries to sample by default (ignored in this class)

num_queries: int = None#

pool(self) → QueriedDataPool[source]#

Description

Returns the sampler’s data pool (abstract).

Returns:: This Query Sampler’s data pool
Return type:: QueriedDataPool
Raises:: NotImplementedError – This class is abstract

class FixedQuerySampler(num_queries, fixed_query)[source]#

Bases: QuerySampler

Description

Always samples the same fixed query.

Parameters:

num_queries (int) – Default number of queries to sample
fixed_query – The fixed query that is always sampled

fixed_query: NDArray[Shape['... query_dims'], Number] = NOTSET#

post_init(self) → None[source]#

Description

Checks if all queries optimal_queries meet its oracle’s query constraints.

Raises:: ValueError – If any query in optimal_queries does not meet the query constraints.

sample(self, num_queries) → queries[source]#

Description

Returns num_queries copies of fixed_query

Parameters:

num_queries (int) – Number of queries to sample (default= self.num_query)

Returns:

Sampled queries

Return type:

NDArray

class LastDataPoolQuerySampler(num_queries)[source]#

Bases: DataPoolQuerySampler

Description

Samples the DataPool’s last added queries

Parameters:: num_queries (int) – Number of queries to sample by default (ignored in this class)

num_queries: int = None#

sample(self, num_queries) → queries[source]#

Description

Returns the DataPool’s last added queries.

Parameters:

num_queries (Any) – Unused

Returns:

Sampled queries

Return type:

NDArray

class LastProcessPoolQuerySampler(*args: Any, **kwargs: Any)[source]#

Bases: LastDataPoolQuerySampler

LastStreamPoolQuerySampler(num_queries) | Description | Samples the ProcessDataPool’s last added queries

Parameters:: num_queries (int) – Number of queries to sample by default (ignored in this class)

property data_pools: ProcessDataPools#

Description

Returns the sampler’s DataPools.

Returns:: QuerySampler’s DataPools
Return type:: ProcessDataPools

pool(self) → QueriedDataPool[source]#

Description

Returns the sampler’s data pools as a queryable.

Returns:: Sampler’s queryable data pool
Return type:: QueriedDataPool

post_init(self) → None[source]#

Description

Raises TypeError if DataPools is not ProcessDataPools

Raises:: TypeError – If DataPools is not ProcessDataPools

class LastProcessQuerySampler(num_queries)[source]#

Bases: ProcessQuerySampler

Description

Samples the queries last added to the Process Oracle.

Parameters:: num_queries (int) – Number of queries to sample by default (ignored in this class)

num_queries: int = None#

sample(self, num_queries) → queries[source]#

Description

Returns the queries last added to the Procass Oracle.

Parameters:

num_queries (Any) – Unused

Returns:

Sampled queries

Return type:

NDArray

class LastResultPoolQuerySampler(num_queries)[source]#

Bases: LastDataPoolQuerySampler

Description

Samples the ResultDataPool’s last added queries

Parameters:: num_queries (int) – Number of queries to sample by default (ignored in this class)

property data_pools: ResultDataPools#

Description

Returns the sampler’s DataPools.

Returns:: QuerySampler’s DataPools
Return type:: ResultDataPools

pool(self) → QueriedDataPool[source]#

Description

Returns the sampler’s data pools as a queryable.

Returns:: Sampler’s queryable data pool
Return type:: QueriedDataPool

post_init(self) → None[source]#

Description

Raises TypeError if DataPools is not ResultDataPools

Raises:: TypeError – If DataPools is not ResultDataPools

class LastStreamPoolQuerySampler(num_queries)[source]#

Bases: LastDataPoolQuerySampler

Description

Samples the StreamDataPool’s last added queries

Parameters:: num_queries (int) – Number of queries to sample by default (ignored in this class)

property data_pools: StreamDataPools#

Description

Returns the sampler’s DataPools.

Returns:: QuerySampler’s DataPools
Return type:: StreamDataPools

pool(self) → QueriedDataPool[source]#

Description

Returns the sampler’s data pools as a queryable.

Returns:: Sampler’s queryable data pool
Return type:: QueriedDataPool

post_init(self) → None[source]#

Description

Raises TypeError if DataPools is not StreamDataPools

Raises:: TypeError – If DataPools is not StreamDataPools

class LatinHypercubeQuerySampler(num_queries)[source]#

Bases: QuerySampler

Description

Does Latin Hypercube sampling of queries.

Parameters:: num_queries (int) – Number of queries to sample by default

post_init(self) → None[source]#: Description

Initializes the appropiate dimesnional quasi monte-carlo Latin Hypercube Sampler.

sample(self, num_queries) → queries[source]#

Description

Returns queries with latin-hypercube random values within the query constraints.

Parameters:

num_queries (int) – Number of queries to sample (default= self.num_queries)

Returns:

Sampled queries

Return type:

NDArray

Raises:

ValueError – If queries are constraint to discrete values

class OptimalQuerySampler(num_queries)[source]#

Bases: QuerySampler

Description

Samples randomly from a given list of “optimal” queries.

Parameters:

num_queries (int) – Number of queries to sample by default
optimal_queries (Tuple[NDArray[Shape["query_nr, ... query_dims"], Number], ...]) – What queries to sample from

optimal_queries: Tuple[NDArray[Shape['query_nr, ... query_dims'], Number], ...] = NOTSET#

post_init(self) → None[source]#

Description

Checks if all queries optimal_queries meet its oracle’s query constraints.

Raises:: ValueError – If any query in optimal_queries does not meet the query constraints.

sample(self, num_queries) → queries[source]#

Description

Returns approximately `num_queries` queries randomly chosen among the `optimal_queries`

Parameters:

num_queries (int) – Number of queries to sample (default= self.num_queries)

Returns:

Sampled queries

Return type:

NDArray

class ProcessQuerySampler(num_queries)[source]#

Bases: QuerySampler

Description

Samples queries from a Process Oracle in some way.

This class is abstract.

Parameters:: num_queries (int) – Number of queries to sample by default

property oracles: POracles#

Description

Returns the sampler’s oracle.

Returns:: QuerySampler’s oracle
Return type:: POracles

post_init(self) → None[source]#

Description

Raises TypeError if Oracles is not PORacles

Raises:: TypeError – If Oracles is not PORacles

class ProcessQueueQuerySampler(num_queries)[source]#

Bases: ProcessQuerySampler

Description

Samples all queries in the Process Oracle’s query queue.

Parameters:: num_queries (int) – Number of queries to sample by default (ignored in this class)

num_queries: int = None#

sample(self, num_queries) → queries[source]#

Description

Returns all queries in the query queue of the Procass Oracle.

Parameters:

num_queries (Any) – Unused

Returns:

Sampled queries

Return type:

NDArray

class RandomChoiceQuerySampler(num_queries)[source]#

Bases: QuerySampler

Description

Samples queries from discrete constraint pools.

Parameters:: num_queries (int) – Number of queries to sample by default

sample(self, num_queries) → queries[source]#

Description

Returns randomly chosen queries from the constraint-permitted pool of queires.

Parameters:

num_queries (int) – Number of queries to sample (default= self.num_queries)

Returns:

Sampled queries

Return type:

NDArray

Raises:

ValueError – If queries are constraint to continuous values

class UniformQuerySampler(num_queries)[source]#

Bases: QuerySampler

Description

Samples queries with random values.

Parameters:: num_queries (int) – Number of queries to sample by default

sample(self, num_queries) → queries[source]#

Description

Returns queries with uniformly random values within the query constraints.

Parameters:

num_queries (int) – Number of queries to sample (default= self.num_queries)

Returns:

Sampled queries

Return type:

NDArray

Raises:

ValueError – If queries are constraint to discrete values

Query Sampler (Implementation)

Contents

Query Sampler (Implementation)#