:orphan: 





.. _circ_cos_tut:



Cosine circadian model
######################

[Generated automatically as a Tutorial summary]

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


:Name: circ_cos

:Title: Cosine circadian model

:Author: PoPy for PK/PD

:Abstract: 

| A PD Model based on the concentration of drug in the body.
| The PD model uses a cosine function which simulates a circadian rhythm for the generation of a biomarker.
| The amount in the central compartment is determined by CL and V, PK parameters, which have been estimated for each individual.
| The concentration in the central compartment influences the rate of removal of a biomarker (KOUT).

:Keywords: PD; Pharmacodynamics; cosine function; Circadian rhythm

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

:Diagram: 


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


Comparison
**********



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


.. code-block:: pyml

    815.0562



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


.. code-block:: pyml

    813.7698



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]
=====================


No Variance f[X] values to compare.

Outputs
*******



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


.. code-block:: pyml

    f[AMP] = 2.0077
    f[INT] = 20.0368
    f[KOUT] = 0.0502
    f[ANOISE] = 3.0888



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


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


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


* Gen: :ref:`circ_cos_gen` (gen)
* Fit: :ref:`circ_cos_fit` (fit)

Inputs
******



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

.. code-block:: pyml

    f[AMP] = 2.0000
    f[INT] = 8.0000
    f[KOUT] = 0.0500
    f[ANOISE] = 3.0000



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

.. code-block:: pyml

    f[AMP] = 3.0000
    f[INT] = 16.0000
    f[KOUT] = 0.1000
    f[ANOISE] = 5.0000

