:orphan: 





.. _tut_example1_tut:



Simple Tut Example
##################

[Generated automatically as a Tutorial summary]

Inputs
******



Description
===========

:Name: tut_example1

:Title: Simple Tut Example

:Author: J.R. Hartley

:Abstract: 

| One compartment model with elimination rate constant KE.

:Keywords: one compartment model; iv_one_cmp_k

:Input Script: :download:`tut_example1.pyml <tut_example1.pyml>`

:Diagram: 


.. thumbnail:: ./compartment_diagram.svg
    :width: 200px


True f[X] values
================

.. code-block:: pyml

    f[KE] = 0.1000
    f[PNOISE] = 0.0500
    f[KE_isv] = 0.0300



Starting f[X] values
====================

.. code-block:: pyml

    f[KE] = 0.0500
    f[PNOISE] = 0.1000
    f[KE_isv] = 0.1000



Outputs
*******



Generating and Fitting Summaries
================================

* Gen: :ref:`tut_example1_gen` (gen)
* Fit: :ref:`tut_example1_fit` (fit)

Fitted f[X] values
==================

.. code-block:: pyml

    f[KE] = 0.1062
    f[PNOISE] = 0.0449
    f[KE_isv] = 0.0274



Plots
*****



Dense comp plots
================



.. thumbnail:: images/comp_dense/000001.svg
    :width: 200px


.. thumbnail:: images/comp_dense/000002.svg
    :width: 200px


.. thumbnail:: images/comp_dense/000003.svg
    :width: 200px


Alternatively see :ref:`tut_example1_dense_comp_plots`

Comparison
**********



True objective value
====================


.. code-block:: pyml

    -44.8609



Final fitted objective value
============================


.. code-block:: pyml

    -49.0965



Compare Main f[X]
=================



.. csv-table:: 
    :file: fx_comp_main.csv
    :header-rows: 1


Compare Noise f[X]
==================



.. csv-table:: 
    :file: fx_comp_noise.csv
    :header-rows: 1


Compare Variance f[X]
=====================



.. csv-table:: 
    :file: fx_comp_variance.csv
    :header-rows: 1
