spynnaker.pyNN.utilities.random_stats package¶
Module contents¶
- class spynnaker.pyNN.utilities.random_stats.AbstractRandomStats[source]¶
Bases:
object
Statistics about PyNN ~spynnaker.pyNN.RandomDistribution objects.
- abstract high(distribution)[source]¶
Return the high cut-off value of the distribution, or None if the distribution is unbounded.
- class spynnaker.pyNN.utilities.random_stats.RandomStatsBinomialImpl[source]¶
Bases:
AbstractRandomStats
An implementation of AbstractRandomStats for binomial distributions.
- high(distribution)[source]¶
Return the high cut-off value of the distribution, or None if the distribution is unbounded.
- class spynnaker.pyNN.utilities.random_stats.RandomStatsExponentialImpl[source]¶
Bases:
AbstractRandomStats
An implementation of AbstractRandomStats for exponential distributions.
- high(distribution)[source]¶
Return the high cut-off value of the distribution, or None if the distribution is unbounded.
- class spynnaker.pyNN.utilities.random_stats.RandomStatsGammaImpl[source]¶
Bases:
AbstractRandomStats
An implementation of AbstractRandomStats for gamma distributions.
- high(distribution)[source]¶
Return the high cut-off value of the distribution, or None if the distribution is unbounded.
- class spynnaker.pyNN.utilities.random_stats.RandomStatsLogNormalImpl[source]¶
Bases:
AbstractRandomStats
An implementation of AbstractRandomStats for log normal distributions.
- high(distribution)[source]¶
Return the high cut-off value of the distribution, or None if the distribution is unbounded.
- class spynnaker.pyNN.utilities.random_stats.RandomStatsNormalClippedImpl[source]¶
Bases:
AbstractRandomStats
An implementation of AbstractRandomStats for normal distributions that are clipped to a boundary (redrawn).
- high(distribution)[source]¶
Return the high cut-off value of the distribution, or None if the distribution is unbounded.
- class spynnaker.pyNN.utilities.random_stats.RandomStatsNormalImpl[source]¶
Bases:
AbstractRandomStats
An implementation of AbstractRandomStats for normal distributions.
- high(distribution)[source]¶
Return the high cut-off value of the distribution, or None if the distribution is unbounded.
- class spynnaker.pyNN.utilities.random_stats.RandomStatsPoissonImpl[source]¶
Bases:
AbstractRandomStats
An implementation of AbstractRandomStats for Poisson distributions.
- high(distribution)[source]¶
Return the high cut-off value of the distribution, or None if the distribution is unbounded.
- class spynnaker.pyNN.utilities.random_stats.RandomStatsRandIntImpl[source]¶
Bases:
AbstractRandomStats
An implementation of AbstractRandomStats for uniform distributions.
- high(distribution)[source]¶
Return the high cut-off value of the distribution, or None if the distribution is unbounded.
- class spynnaker.pyNN.utilities.random_stats.RandomStatsScipyImpl(distribution_type)[source]¶
Bases:
AbstractRandomStats
A Random Statistics object that uses scipy directly.
- high(distribution)[source]¶
Return the high cut-off value of the distribution, or None if the distribution is unbounded.
- class spynnaker.pyNN.utilities.random_stats.RandomStatsUniformImpl[source]¶
Bases:
AbstractRandomStats
An implementation of AbstractRandomStats for uniform distributions.
- high(distribution)[source]¶
Return the high cut-off value of the distribution, or None if the distribution is unbounded.
- class spynnaker.pyNN.utilities.random_stats.RandomStatsVonmisesImpl[source]¶
Bases:
AbstractRandomStats
An implementation of AbstractRandomStats for von Mises distributions.
- high(distribution)[source]¶
Return the high cut-off value of the distribution, or None if the distribution is unbounded.