dacapo.plot
===========

.. py:module:: dacapo.plot


Attributes
----------

.. autoapisummary::

   dacapo.plot.RunInfo


Functions
---------

.. autoapisummary::

   dacapo.plot.smooth_values
   dacapo.plot.get_runs_info
   dacapo.plot.bokeh_plot_runs
   dacapo.plot.plot_runs


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

.. py:data:: RunInfo

.. py:function:: smooth_values(a, n, stride=1)

   Smooth values with a moving average.

   :param a: values to smooth
   :param n: number of values to average
   :param stride: stride of the smoothing

   :returns: smoothed values
             s: standard deviation of the smoothed values
   :rtype: m

   :raises ValueError: If run_name is not found in config store

   .. rubric:: Examples

   >>> smooth_values([1,2,3,4,5], 3)


.. py:function:: get_runs_info(run_config_names: List[str], validation_score_names: List[str], plot_losses: List[bool]) -> List[RunInfo]

.. py:function:: bokeh_plot_runs(run_config_base_names, smooth=100, validation_scores=None, higher_is_betters=None, plot_losses=None, return_json=False)

   Plot runs.
   :param run_config_base_names: Names of run configs to plot
   :param smooth: Smoothing factor
   :param validation_scores: Validation scores to plot
   :param higher_is_betters: Whether higher is better
   :param plot_losses: Whether to plot losses
   :param return_json: Whether to return JSON

   :returns: JSON or HTML plot

   :raises ValueError: If run_name is not found in config store

   .. rubric:: Examples

   >>> plot_runs(["run_name"], 100, None, None, [True])


.. py:function:: plot_runs(run_config_base_names, smooth=100, validation_scores=None, higher_is_betters=None, plot_losses=None)

   Plot runs.
   :param run_config_base_names: Names of run configs to plot
   :param smooth: Smoothing factor
   :param validation_scores: Validation scores to plot
   :param higher_is_betters: Whether higher is better
   :param plot_losses: Whether to plot losses

   :returns: None