87 lines
1.8 KiB
Markdown
87 lines
1.8 KiB
Markdown
This is a si
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## Preparations
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Before using this script, make sure, your current working directory looks like
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```{verbatim}
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.
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├── glue.R
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├── kichen_sink.R
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├── make_individual_trees.R
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├── Martonvasar_maize_KSH_Fejer.obs
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├── Martonvasar_maize.obs
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├── README.md
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├── statistics.R
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└── tree_accuracy.R
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```
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### Loading the RBBGCMuso package and the necessary functions
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```{r}
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library(RBBGCMuso)
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source("make_individual_trees.R") # The DT creation and update algorithms
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source("glue.R") # GLUE optimizer algorithms
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```
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The file containing the path to the observation files (Martonvasar_maize.obs), and the parameter intervals (Martonj)
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### Reading the observations
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The mean yield had to be adjust. see in art.
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```{r}
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measureFile <- "Martonvasar_maize.obs"
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measurements <- read.csv2(measureFile, stringsAsFactors=FALSE)
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measurements$mean <- measurements$mean / 10000
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measurements$sd <- measurements$sd / 10000
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```
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### Define conditioning functions
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constraints.json
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```{json}
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{
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"constraints": [
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{
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"Expression": "SELECT(harvest_index, max)|median",
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"Min": 0.45,
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"Max": 0.55
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},
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{
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"Expression": "SELECT(proj_lai, max)|quantile(.,0.5)",
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"Min": 2.7,
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"Max": 5
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},
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{
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"Expression": "SELECT(rootdepth5, max)|quantile(.,0.5)",
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"Min": 1.40,
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"Max": 1.80
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},
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{
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"Expression": "SELECT(flower_date, max)|quantile(.,0.5)",
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"Min": 180,
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"Max": 190
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}
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],
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"treshold": 80
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}
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```
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```{r}
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constraints <- jsonlite::read_json("constraints.json",simplifyVector=TRUE)
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```
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### Cal file:
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```{verbatim}
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Martonvasar_maize.obs
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Martonvasar_maize.set
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site
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Martonvasar_maize;211
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```
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