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-<title>mkinpredict. mkin 0.9.44.9000</title>
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- Johannes Ranke
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- <li><a href="index.html"><i class="icon-home icon-white"></i> Index</a></li>
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-</div>
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- <div class="container">
- <header>
-
- </header>
-
- <h1>
- Produce predictions from a kinetic model using specific parameters
-</h1>
-
-<div class="row">
- <div class="span8">
- <h2>Usage</h2>
- <pre><div>mkinpredict(mkinmod, odeparms, odeini, outtimes, solution_type&nbsp;=&nbsp;"deSolve",
- use_compiled&nbsp;=&nbsp;"auto", method.ode&nbsp;=&nbsp;"lsoda", atol&nbsp;=&nbsp;1e-08, rtol&nbsp;=&nbsp;1e-10, map_output&nbsp;=&nbsp;TRUE, ...)</div></pre>
-
- <h2>Arguments</h2>
- <dl>
- <dt>mkinmod</dt>
- <dd>
- A kinetic model as produced by <code><a href='mkinmod.html'>mkinmod</a></code>.
- </dd>
- <dt>odeparms</dt>
- <dd>
- A numeric vector specifying the parameters used in the kinetic model, which
- is generally defined as a set of ordinary differential equations.
- </dd>
- <dt>odeini</dt>
- <dd>
- A numeric vectory containing the initial values of the state variables of
- the model. Note that the state variables can differ from the observed
- variables, for example in the case of the SFORB model.
- </dd>
- <dt>outtimes</dt>
- <dd>
- A numeric vector specifying the time points for which model predictions
- should be generated.
- </dd>
- <dt>solution_type</dt>
- <dd>
- The method that should be used for producing the predictions. This should
- generally be "analytical" if there is only one observed variable, and
- usually "deSolve" in the case of several observed variables. The third
- possibility "eigen" is faster but not applicable to some models e.g.
- using FOMC for the parent compound.
- </dd>
- <dt>method.ode</dt>
- <dd>
- The solution method passed via <code><a href='mkinpredict.html'>mkinpredict</a></code> to
- <code><a href='http://www.inside-r.org/packages/cran/deSolve/docs/ode'>ode</a></code> in case the solution type is "deSolve". The default
- "lsoda" is performant, but sometimes fails to converge.
- </dd>
- <dt>use_compiled</dt>
- <dd>
- If set to <code>FALSE</code>, no compiled version of the <code><a href='mkinmod.html'>mkinmod</a></code>
- model is used, even if is present.
- </dd>
- <dt>atol</dt>
- <dd>
- Absolute error tolerance, passed to <code><a href='http://www.inside-r.org/packages/cran/deSolve/docs/ode'>ode</a></code>. Default is 1e-8,
- lower than in <code><a href='http://www.inside-r.org/packages/cran/deSolve/docs/lsoda'>lsoda</a></code>.
- </dd>
- <dt>rtol</dt>
- <dd>
- Absolute error tolerance, passed to <code><a href='http://www.inside-r.org/packages/cran/deSolve/docs/ode'>ode</a></code>. Default is 1e-10,
- much lower than in <code><a href='http://www.inside-r.org/packages/cran/deSolve/docs/lsoda'>lsoda</a></code>.
- </dd>
- <dt>map_output</dt>
- <dd>
- Boolean to specify if the output should list values for the observed
- variables (default) or for all state variables (if set to FALSE).
- </dd>
- <dt>...</dt>
- <dd>
- Further arguments passed to the ode solver in case such a solver is used.
- </dd>
- </dl>
-
- <div class="Description">
- <h2>Description</h2>
-
- <p>This function produces a time series for all the observed variables in a
- kinetic model as specified by <code><a href='mkinmod.html'>mkinmod</a></code>, using a specific set of
- kinetic parameters and initial values for the state variables.</p>
-
- </div>
-
- <div class="Value">
- <h2>Value</h2>
-
- <p><dl>
- A matrix in the same format as the output of <code><a href='http://www.inside-r.org/packages/cran/deSolve/docs/ode'>ode</a></code>.
-</dl></p>
-
- </div>
-
- <h2 id="examples">Examples</h2>
- <pre class="examples"><div class='input'> SFO &lt;- mkinmod(degradinol = list(type = &quot;SFO&quot;))
- # Compare solution types
- mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
- solution_type = &quot;analytical&quot;)
-</div>
-<div class='output'> time degradinol
-1 0 100.0000000
-2 1 74.0818221
-3 2 54.8811636
-4 3 40.6569660
-5 4 30.1194212
-6 5 22.3130160
-7 6 16.5298888
-8 7 12.2456428
-9 8 9.0717953
-10 9 6.7205513
-11 10 4.9787068
-12 11 3.6883167
-13 12 2.7323722
-14 13 2.0241911
-15 14 1.4995577
-16 15 1.1108997
-17 16 0.8229747
-18 17 0.6096747
-19 18 0.4516581
-20 19 0.3345965
-21 20 0.2478752
-</div>
-<div class='input'> mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
- solution_type = &quot;deSolve&quot;)
-</div>
-<div class='output'> time degradinol
-1 0 100.0000000
-2 1 74.0818221
-3 2 54.8811636
-4 3 40.6569660
-5 4 30.1194212
-6 5 22.3130160
-7 6 16.5298888
-8 7 12.2456428
-9 8 9.0717953
-10 9 6.7205513
-11 10 4.9787068
-12 11 3.6883167
-13 12 2.7323722
-14 13 2.0241911
-15 14 1.4995577
-16 15 1.1108996
-17 16 0.8229747
-18 17 0.6096747
-19 18 0.4516581
-20 19 0.3345965
-21 20 0.2478752
-</div>
-<div class='input'> mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
- solution_type = &quot;deSolve&quot;, use_compiled = FALSE)
-</div>
-<div class='output'> time degradinol
-1 0 100.0000000
-2 1 74.0818221
-3 2 54.8811636
-4 3 40.6569660
-5 4 30.1194212
-6 5 22.3130160
-7 6 16.5298888
-8 7 12.2456428
-9 8 9.0717953
-10 9 6.7205513
-11 10 4.9787068
-12 11 3.6883167
-13 12 2.7323722
-14 13 2.0241911
-15 14 1.4995577
-16 15 1.1108996
-17 16 0.8229747
-18 17 0.6096747
-19 18 0.4516581
-20 19 0.3345965
-21 20 0.2478752
-</div>
-<div class='input'> mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
- solution_type = &quot;eigen&quot;)
-</div>
-<div class='output'> time degradinol
-1 0 100.0000000
-2 1 74.0818221
-3 2 54.8811636
-4 3 40.6569660
-5 4 30.1194212
-6 5 22.3130160
-7 6 16.5298888
-8 7 12.2456428
-9 8 9.0717953
-10 9 6.7205513
-11 10 4.9787068
-12 11 3.6883167
-13 12 2.7323722
-14 13 2.0241911
-15 14 1.4995577
-16 15 1.1108997
-17 16 0.8229747
-18 17 0.6096747
-19 18 0.4516581
-20 19 0.3345965
-21 20 0.2478752
-</div>
-<div class='input'>
-
- # Compare integration methods to analytical solution
- mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
- solution_type = &quot;analytical&quot;)[21,]
-</div>
-<div class='output'> time degradinol
-21 20 0.2478752
-</div>
-<div class='input'> mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
- method = &quot;lsoda&quot;)[21,]
-</div>
-<div class='output'> time degradinol
-21 20 0.2478752
-</div>
-<div class='input'> mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
- method = &quot;ode45&quot;)[21,]
-</div>
-<div class='output'> time degradinol
-21 20 0.2478752
-</div>
-<div class='input'> mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
- method = &quot;rk4&quot;)[21,]
-</div>
-<div class='output'> time degradinol
-21 20 0.2480043
-</div>
-<div class='input'> # rk4 is not as precise here
-
- # The number of output times used to make a lot of difference until the
- # default for atol was adjusted
- mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100),
- seq(0, 20, by = 0.1))[201,]
-</div>
-<div class='output'> time degradinol
-201 20 0.2478752
-</div>
-<div class='input'> mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100),
- seq(0, 20, by = 0.01))[2001,]
-</div>
-<div class='output'> time degradinol
-2001 20 0.2478752
-</div>
-<div class='input'>
- # Check compiled model versions - they are faster than the eigenvalue based solutions!
- SFO_SFO = mkinmod(parent = list(type = &quot;SFO&quot;, to = &quot;m1&quot;),
- m1 = list(type = &quot;SFO&quot;))
-</div>
-<strong class='message'>Successfully compiled differential equation model from auto-generated C code.</strong>
-<div class='input'> system.time(
- print(mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01),
- c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
- solution_type = &quot;eigen&quot;)[201,]))
-</div>
-<div class='output'> time parent m1
-201 20 4.978707 27.46227
-</div>
-<div class='output'> user system elapsed
- 0.004 0.028 0.005
-</div>
-<div class='input'> system.time(
- print(mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01),
- c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
- solution_type = &quot;deSolve&quot;)[201,]))
-</div>
-<div class='output'> time parent m1
-201 20 4.978707 27.46227
-</div>
-<div class='output'> user system elapsed
- 0.016 0.004 0.003
-</div>
-<div class='input'> system.time(
- print(mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01),
- c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
- solution_type = &quot;deSolve&quot;, use_compiled = FALSE)[201,]))
-</div>
-<div class='output'> time parent m1
-201 20 4.978707 27.46227
-</div>
-<div class='output'> user system elapsed
- 0.032 0.000 0.035
-</div></pre>
- </div>
- <div class="span4">
- <!-- <ul>
- <li>mkinpredict</li>
- </ul>
- <ul>
- <li> manip </li>
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-
-
- <h2>Author</h2>
-
- Johannes Ranke
-
-
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