:orphan: 





.. _tut_example1_tut:



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

[Generated automatically as a Tutorial summary]

Model Description
*****************


:Name: tut_example1

:Title: Simple Tut Example

:Author: PoPy for PK/PD

: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


Comparison
**********



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


.. code-block:: pyml

    -44.1427



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


.. code-block:: pyml

    -48.4038



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


Outputs
*******



Fitted f[X] values (after fitting)
==================================


.. code-block:: pyml

    f[KE] = 0.1062
    f[PNOISE] = 0.0450
    f[KE_isv] = 0.0260



Generated data .csv file
========================


:Synthetic Data: :download:`synthetic_data.csv <synthetic_data.csv>`


Gen and Fit Summaries
=====================


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

Inputs
******



True f[X] values (for simulation)
=================================

.. code-block:: pyml

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



Starting f[X] values (before fitting)
=====================================

.. code-block:: pyml

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

