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| Rev | Author | Line No. | Line |
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| 1 | |||
| 791 | werner | 2 | ### |
| 3 | ### load some useful tools/functions |
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| 4 | #source("sql_tools.R") |
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| 5 | library(RSQLite) |
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| 6 | |||
| 7 | # connect to an existing database |
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| 8 | db.conn <<- dbConnect("SQLite", dbname="e:/Daten/iLand/projects/AFJZ_experiment1203/output/bare_soil_afi413.sqlite" ) |
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| 9 | |||
| 10 | ### load data from the iLand output table |
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| 11 | stand <- dbReadTable(db.conn, "stand") |
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| 12 | # alternatively (using sql_tools): stand <- query("select * from stand") |
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| 13 | |||
| 14 | summary(stand) |
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| 15 | |||
| 16 | ## stacked bar chart, e.g. for basal area |
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| 17 | library(ggplot2) |
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| 18 | |||
| 19 | head(stand) |
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| 20 | # aggregate to values for each species and year (i.e. averaging over all the resource units) |
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| 21 | stand.avg <- aggregate(stand, list(year=stand$year, species=stand$species), FUN="mean") |
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| 22 | head(stand.avg) |
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| 23 | |||
| 24 | # now we can plot them: |
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| 25 | ggplot(stand.avg, aes(x=year,y=basal_area_m2,group=species,fill=species)) + geom_area() + labs(xlab="year", ylab="basal area m2", title="average basal area") |
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| 26 | ## stem numbers |
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| 27 | ggplot(stand.avg, aes(x=year,y=count_ha,group=species,fill=species)) + geom_area() |
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| 28 | ggplot(stand.avg, aes(x=year,y=cohortCount_ha,group=species,fill=species)) + geom_area() |
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| 29 | |||
| 30 | ggplot(stand.avg, aes(x=year,y=LAI,group=species,fill=species)) + geom_area() |