From 8bdb4cd437a9d4663e542f95869e8692aa38dadb Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 7 May 2020 08:59:29 +0200 Subject: Static documentation rebuilt by pkgdown --- docs/reference/mkinpredict.html | 205 ++++++++++++++++------------------------ 1 file changed, 84 insertions(+), 121 deletions(-) (limited to 'docs/reference/mkinpredict.html') diff --git a/docs/reference/mkinpredict.html b/docs/reference/mkinpredict.html index fe5bc975..689fb7c7 100644 --- a/docs/reference/mkinpredict.html +++ b/docs/reference/mkinpredict.html @@ -10,23 +10,27 @@ - + - + - + + + + + - - + + - + - - + + @@ -39,7 +43,6 @@ - @@ -57,7 +60,7 @@ kinetic parameters and initial values for the state variables." /> - +
@@ -115,7 +118,12 @@ kinetic parameters and initial values for the state variables." />
@@ -130,7 +138,7 @@ kinetic parameters and initial values for the state variables." />

Produce predictions from a kinetic model using specific parameters

- + Source: R/mkinpredict.R
@@ -258,32 +266,11 @@ solver is used.

Examples


-  SFO <- mkinmod(degradinol = mkinsub("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
+SFO <- mkinmod(degradinol = mkinsub("SFO"))
+# Compare solution types
+mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
+      solution_type = "analytical")
#> Error in (function (t, parent_0, k) {    parent = parent_0 * exp(-k * t)})(t = 0:20, parent.0 = c(degradinol = 100), k = 0.3): unbenutztes Argument (parent.0 = 100)
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
@@ -304,8 +291,8 @@ solver is used.

 #> 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
+#> 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
@@ -326,8 +313,8 @@ solver is used.

 #> 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
+#> 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
@@ -349,92 +336,68 @@ solver is used.

 #> 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
+# Compare integration methods to analytical solution
+mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
+      solution_type = "analytical")[21,]
#> Error in (function (t, parent_0, k) {    parent = parent_0 * exp(-k * t)})(t = 0:20, parent.0 = c(degradinol = 100), k = 0.3): unbenutztes Argument (parent.0 = 100)
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 verstrichen 
-#>       0.003       0.000       0.003 
  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 verstrichen 
-#>       0.002       0.000       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 verstrichen 
-#>       0.021       0.000       0.021 

-  # \dontrun{
-    # Predict from a fitted model
-    f <- mkinfit(SFO_SFO, FOCUS_2006_C)
#> Ordinary least squares optimisation
#> Sum of squared residuals at call 1: 552.5739
-#> Sum of squared residuals at call 3: 552.5739
-#> Sum of squared residuals at call 4: 552.5739
-#> Sum of squared residuals at call 6: 279.9345
-#> Sum of squared residuals at call 7: 279.9344
-#> Sum of squared residuals at call 8: 279.9294
-#> Sum of squared residuals at call 9: 279.9294
-#> Sum of squared residuals at call 12: 200.3629
-#> Sum of squared residuals at call 13: 200.3629
-#> Sum of squared residuals at call 18: 197.904
-#> Sum of squared residuals at call 22: 197.904
-#> Sum of squared residuals at call 25: 196.6753
-#> Sum of squared residuals at call 27: 196.6753
-#> Sum of squared residuals at call 32: 196.5742
-#> Sum of squared residuals at call 33: 196.5742
-#> Sum of squared residuals at call 34: 196.5742
-#> Sum of squared residuals at call 38: 196.5361
-#> Sum of squared residuals at call 40: 196.5361
-#> Sum of squared residuals at call 44: 196.5336
-#> Sum of squared residuals at call 45: 196.5336
-#> Sum of squared residuals at call 50: 196.5334
-#> Sum of squared residuals at call 51: 196.5334
-#> Sum of squared residuals at call 52: 196.5334
-#> Sum of squared residuals at call 56: 196.5334
-#> Sum of squared residuals at call 58: 196.5334
-#> Sum of squared residuals at call 59: 196.5334
-#> Sum of squared residuals at call 65: 196.5334
-#> Negative log-likelihood at call 75: 26.64668
#> Optimisation successfully terminated.
    head(mkinpredict(f))
#>   time   parent       m1
+# 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.
if(require(rbenchmark)) {
+  benchmark(
+    eigen = 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,],
+    deSolve_compiled = 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,],
+    deSolve = 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,],
+    replications = 10)
+}
#> Lade nötiges Paket: rbenchmark
#>               test replications elapsed relative user.self sys.self user.child
+#> 3          deSolve           10   0.229   28.625     0.229        0          0
+#> 2 deSolve_compiled           10   0.008    1.000     0.008        0          0
+#> 1            eigen           10   0.025    3.125     0.026        0          0
+#>   sys.child
+#> 3         0
+#> 2         0
+#> 1         0

+# Since mkin 0.9.49.11 we also have analytical solutions for some models, including SFO-SFO
+#    deSolve = 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 = "analytical", use_compiled = FALSE)[201,],
+
+# \dontrun{
+  # Predict from a fitted model
+  f <- mkinfit(SFO_SFO, FOCUS_2006_C, quiet = TRUE)
+  head(mkinpredict(f))
#>   time   parent       m1
 #> 1  0.0 82.49216 0.000000
 #> 2  0.1 80.00563 1.179963
 #> 3  0.2 77.59404 2.312596
 #> 4  0.3 75.25515 3.399443
 #> 5  0.4 72.98675 4.442000
-#> 6  0.5 70.78673 5.441717
  # }
+#> 6  0.5 70.78673 5.441717
# }
- @@ -445,7 +408,7 @@ solver is used.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 1.5.1.

-- cgit v1.2.1