From 7c62da1269e8910a210ba1917d4dc62d186d5606 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 6 Oct 2016 09:40:35 +0200 Subject: Static documentation rebuilt by pkgdown::build_site() --- docs/mkinpredict.html | 345 -------------------------------------------------- 1 file changed, 345 deletions(-) delete mode 100644 docs/mkinpredict.html (limited to 'docs/mkinpredict.html') diff --git a/docs/mkinpredict.html b/docs/mkinpredict.html deleted file mode 100644 index 438b37c0..00000000 --- a/docs/mkinpredict.html +++ /dev/null @@ -1,345 +0,0 @@ - - - - -mkinpredict. mkin 0.9.44.9000 - - - - - - - - - - - - - - - -
-
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- mkin 0.9.44.9000 -
- -
-
-
-
- - -
-
- -
- -

- Produce predictions from a kinetic model using specific parameters -

- -
-
-

Usage

- 
mkinpredict(mkinmod, odeparms, odeini, outtimes, solution_type = "deSolve",
-              use_compiled = "auto", method.ode = "lsoda", atol = 1e-08, rtol = 1e-10,
-        map_output = TRUE, ...)
- -

Arguments

-
-
mkinmod
-
- A kinetic model as produced by mkinmod. -
-
odeparms
-
- A numeric vector specifying the parameters used in the kinetic model, which - is generally defined as a set of ordinary differential equations. -
-
odeini
-
- 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. -
-
outtimes
-
- A numeric vector specifying the time points for which model predictions - should be generated. -
-
solution_type
-
- 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. -
-
method.ode
-
- The solution method passed via mkinpredict to - ode in case the solution type is "deSolve". The default - "lsoda" is performant, but sometimes fails to converge. -
-
use_compiled
-
- If set to FALSE, no compiled version of the mkinmod - model is used, even if is present. -
-
atol
-
- Absolute error tolerance, passed to ode. Default is 1e-8, - lower than in lsoda. -
-
rtol
-
- Absolute error tolerance, passed to ode. Default is 1e-10, - much lower than in lsoda. -
-
map_output
-
- Boolean to specify if the output should list values for the observed - variables (default) or for all state variables (if set to FALSE). -
-
...
-
- Further arguments passed to the ode solver in case such a solver is used. -
-
- -
-

Description

- -

This function produces a time series for all the observed variables in a - kinetic model as specified by mkinmod, using a specific set of - kinetic parameters and initial values for the state variables.

- -
- -
-

Value

- -

- A matrix in the same format as the output of ode. -

- -
- -

Examples

- 
  SFO <- mkinmod(degradinol = list(type = "SFO"))
-  # Compare solution types
-  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-              solution_type = "analytical")

-
   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
-

-
  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-              solution_type = "deSolve")

-
   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
-

-
  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-              solution_type = "deSolve", use_compiled = FALSE)

-
   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
-

-
  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-              solution_type = "eigen")

-
   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
-

-

-
-  # Compare integration methods to analytical solution
-  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-              solution_type = "analytical")[21,]

-
   time degradinol
-21   20  0.2478752
-

-
  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-              method = "lsoda")[21,]

-
   time degradinol
-21   20  0.2478752
-

-
  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-              method = "ode45")[21,]

-
   time degradinol
-21   20  0.2478752
-

-
  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-              method = "rk4")[21,]

-
   time degradinol
-21   20  0.2480043
-

-
 # 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,]

-
    time degradinol
-201   20  0.2478752
-

-
  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100),
-              seq(0, 20, by = 0.01))[2001,]

-
     time degradinol
-2001   20  0.2478752
-

-

-  # Check compiled model versions - they are faster than the eigenvalue based solutions!
-  SFO_SFO = mkinmod(parent = list(type = "SFO", to = "m1"),
-                    m1 = list(type = "SFO"))

-Successfully compiled differential equation model from auto-generated C code.
-
  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 = "eigen")[201,]))

-
    time   parent       m1
-201   20 4.978707 27.46227
-

-
   user  system elapsed 
-  0.008   0.020   0.005 
-

-
  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 = "deSolve")[201,]))

-
    time   parent       m1
-201   20 4.978707 27.46227
-

-
   user  system elapsed 
-  0.012   0.004   0.002 
-

-
  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 = "deSolve", use_compiled = FALSE)[201,]))

-
    time   parent       m1
-201   20 4.978707 27.46227
-

-
   user  system elapsed 
-  0.036   0.000   0.036 
-
-
-
- - - - -

Author

- - Johannes Ranke - - -
-
- - -
- - \ No newline at end of file -- cgit v1.2.1