bluemira.fuel_cycle.timeline_tools
==================================

.. py:module:: bluemira.fuel_cycle.timeline_tools

.. autoapi-nested-parse::

   Distribution and timeline utilities



Classes
-------

.. autoapisummary::

   bluemira.fuel_cycle.timeline_tools.UniformLearningStrategy
   bluemira.fuel_cycle.timeline_tools.UserSpecifiedLearningStrategy
   bluemira.fuel_cycle.timeline_tools.GompertzLearningStrategy
   bluemira.fuel_cycle.timeline_tools.LogNormalAvailabilityStrategy
   bluemira.fuel_cycle.timeline_tools.TruncNormAvailabilityStrategy
   bluemira.fuel_cycle.timeline_tools.ExponentialAvailabilityStrategy


Module Contents
---------------

.. py:class:: UniformLearningStrategy

   Bases: :py:obj:`LearningStrategy`

   .. autoapi-inheritance-diagram:: bluemira.fuel_cycle.timeline_tools.UniformLearningStrategy
      :parts: 1
      :private-bases:


   Uniform learning strategy


   .. py:method:: generate_phase_availabilities(lifetime_op_availability: float, op_durations: collections.abc.Iterable[float]) -> collections.abc.Iterable[float]
      :staticmethod:


      Generate operational availabilities for the specified phase durations.

      :param lifetime_op_availability: Operational availability averaged over the lifetime
      :param op_durations: Durations of the operational phases [fpy]

      :returns: Operational availabilities at each operational phase



.. py:class:: UserSpecifiedLearningStrategy(operational_availabilities: collections.abc.Iterable[float])

   Bases: :py:obj:`LearningStrategy`

   .. autoapi-inheritance-diagram:: bluemira.fuel_cycle.timeline_tools.UserSpecifiedLearningStrategy
      :parts: 1
      :private-bases:


   User-specified learning strategy to hard-code the operational availabilities at
   each operational phase.


   .. py:attribute:: operational_availabilities


   .. py:method:: generate_phase_availabilities(lifetime_op_availability: float, op_durations: collections.abc.Iterable[float]) -> collections.abc.Iterable[float]

      Generate operational availabilities for the specified phase durations.

      :param lifetime_op_availability: Lifetime operational availability
      :param op_durations: Durations of the operational phases [fpy]

      :returns: Operational availabilities at each operational phase

      :raises FuelCycleError: Number of phases should be equal to the number of operational availabilities



.. py:class:: GompertzLearningStrategy(learn_rate: float, min_op_availability: float, max_op_availability: float)

   Bases: :py:obj:`LearningStrategy`

   .. autoapi-inheritance-diagram:: bluemira.fuel_cycle.timeline_tools.GompertzLearningStrategy
      :parts: 1
      :private-bases:


   Gompertz learning strategy.


   .. py:attribute:: learn_rate


   .. py:attribute:: min_op_a


   .. py:attribute:: max_op_a


   .. py:method:: _f_op_availabilities(t, x, arg_dates)


   .. py:method:: generate_phase_availabilities(lifetime_op_availability: float, op_durations: collections.abc.Iterable[float]) -> collections.abc.Iterable[float]

      Generate operational availabilities for the specified phase durations.

      :param lifetime_op_availability: Operational availability averaged over the lifetime
      :param op_durations: Durations of the operational phases [fpy]

      :returns: Operational availabilities at each operational phase

      :raises FuelCycleError: Input lifetimes must be in range



.. py:class:: LogNormalAvailabilityStrategy(sigma: float, rng_seed: int | numpy.random.SeedSequence = RNGSeeds.timeline_tools_lognorm.value)

   Bases: :py:obj:`OperationalAvailabilityStrategy`

   .. autoapi-inheritance-diagram:: bluemira.fuel_cycle.timeline_tools.LogNormalAvailabilityStrategy
      :parts: 1
      :private-bases:


   Log-normal distribution strategy

   :param sigma: Standard deviation of the underlying normal distribution
   :param rng_seed: random number generator seed for the normal distribution


   .. py:attribute:: sigma


   .. py:method:: generate_distribution(n: int, integral: float) -> numpy.ndarray

      Generate a log-normal distribution with a specified number of entries and
      integral.

      :param n: Number of entries in the distribution
      :param integral: Integral of the distribution

      :returns: The distribution of size n and of the correct integral value



.. py:class:: TruncNormAvailabilityStrategy(sigma: float, rng_seed: int | numpy.random.SeedSequence = RNGSeeds.timeline_tools_truncnorm.value)

   Bases: :py:obj:`OperationalAvailabilityStrategy`

   .. autoapi-inheritance-diagram:: bluemira.fuel_cycle.timeline_tools.TruncNormAvailabilityStrategy
      :parts: 1
      :private-bases:


   Truncated normal distribution strategy

   :param sigma: Standard deviation of the underlying normal distribution
   :param rng_seed: random number generator seed for the normal distribution


   .. py:attribute:: sigma


   .. py:method:: generate_distribution(n: int, integral: float) -> numpy.ndarray

      Generate a truncated normal distribution with a specified number of entries and
      integral.

      :param n: Number of entries in the distribution
      :param integral: Integral of the distribution

      :returns: The distribution of size n and of the correct integral value



.. py:class:: ExponentialAvailabilityStrategy(lambdda: float, rng_seed: int | numpy.random.SeedSequence = RNGSeeds.timeline_tools_expo.value)

   Bases: :py:obj:`OperationalAvailabilityStrategy`

   .. autoapi-inheritance-diagram:: bluemira.fuel_cycle.timeline_tools.ExponentialAvailabilityStrategy
      :parts: 1
      :private-bases:


   Exponential distribution strategy

   :param lambdda: Rate of the distribution
   :param rng_seed: random number generator seed for the exponential distribution


   .. py:attribute:: lambdda


   .. py:method:: generate_distribution(n: int, integral: float) -> numpy.ndarray

      Generate an exponential distribution with a specified number of entries and
      integral.

      :param n: Number of entries in the distribution
      :param integral: Integral of the distribution

      :returns: The distribution of size n and of the correct integral value