nemora module
.. py:module:: nemora
Top-level package exports for Nemora.
.. py:class:: FitResult(distribution, parameters, covariance=None, gof=
Bases: :py:class:object
Container for a single distribution fit.
.. py:attribute:: FitResult.covariance :module: nemora :type: ~numpy.ndarray | None
.. py:attribute:: FitResult.diagnostics :module: nemora :type: dict[str, ~typing.Any]
.. py:attribute:: FitResult.distribution :module: nemora :type: str
.. py:attribute:: FitResult.gof :module: nemora :type: dict[str, float]
.. py:attribute:: FitResult.parameters :module: nemora :type: dict[str, float]
.. py:class:: FitSummary(inventory, results, best=None, notes=None) :module: nemora :canonical: nemora.core.FitSummary
Bases: :py:class:object
Aggregate fit outputs over candidate distributions.
.. py:attribute:: FitSummary.best :module: nemora :type: ~nemora.core.FitResult | None
.. py:attribute:: FitSummary.inventory :module: nemora :type: ~nemora.core.InventorySpec
.. py:attribute:: FitSummary.notes :module: nemora :type: str | None
.. py:attribute:: FitSummary.results :module: nemora :type: list[~nemora.core.FitResult]
.. py:method:: FitSummary.to_frame() :module: nemora
Return a tidy data frame summarising candidate results.
:rtype: :sphinx_autodoc_typehints_type:`\:py\:class\:\`\~pandas.DataFrame\``
.. py:class:: InventorySpec(name, sampling, bins, tallies, metadata=
Bases: :py:class:object
Describe a single inventory tally source.
.. py:attribute:: InventorySpec.bins :module: nemora :type: ~numpy.ndarray | ~collections.abc.Sequence[float]
.. py:attribute:: InventorySpec.metadata :module: nemora :type: dict[str, ~typing.Any]
.. py:attribute:: InventorySpec.name :module: nemora :type: str
.. py:attribute:: InventorySpec.sampling :module: nemora :type: str
.. py:attribute:: InventorySpec.tallies :module: nemora :type: ~numpy.ndarray | ~collections.abc.Sequence[float]
.. py:function:: fit_censored_inventory(dbh_cm, density, *, support, distributions=None, configs=None) :module: nemora
Fit complete-form PDFs to censored tallies with a two-stage scaler.
:rtype: :sphinx_autodoc_typehints_type:\:py\:class\:\list`\ \[:py:class:`~nemora.core.FitResult`]`
.. py:function:: fit_hps_inventory(dbh_cm, tally, *, baf, distributions=None, configs=None, grouped_weibull_mode=’auto’) :module: nemora
Fit HPS tallies using weighted stand-table expansion.
:rtype: :sphinx_autodoc_typehints_type:\:py\:class\:\list`\ \[:py:class:`~nemora.core.FitResult`]`