The goal of fgeo.tool is to provide functions for general purposes. Many of its functions are used in multiple other fgeo packages.
Install the pre-release version of fgeo.tool:
# install.packages("devtools")
devtools::install_github("forestgeo/fgeo.tool@pre-release")
Or install the development version of fgeo.tool:
# install.packages("devtools")
devtools::install_github("forestgeo/fgeo.tool")
Or install all fgeo packages in one step.
For details on how to install packages from GitHub, see this article.
library(fgeo.tool)
#>
#> Attaching package: 'fgeo.tool'
#> The following object is masked from 'package:stats':
#>
#> filterRead multiple censuses from a directory into a list of dataframes.
dir_multi_rdata <- tool_example("rdata")
dir(dir_multi_rdata)
#> [1] "tree5.RData" "tree6.RData"
census56_list <- rdata_list(dir_multi_rdata)
census56_list
#> $tree5
#> # A tibble: 1,000 x 19
#> treeID stemID tag StemTag sp quadrat gx gy MeasureID CensusID
#> <int> <int> <chr> <chr> <chr> <chr> <dbl> <dbl> <int> <int>
#> 1 104 143 10009 10009 DACE~ 113 10.3 245. 439947 5
#> 2 119 158 1001~ 100104 MYRS~ 1021 183. 410. 466597 5
#> 3 180 225 1001~ 100174 CASA~ 921 165. 410. 466623 5
#> 4 602 736 1006~ 100649 GUAG~ 821 149. 414. 466727 5
#> 5 631 775 10069 10069 PREM~ 213 38.3 245. 439989 5
#> 6 647 793 1007~ 100708 SCHM~ 821 143. 411. 466743 5
#> 7 1086 1339 10122 10122 DRYG~ 413 68.9 253. 440021 5
#> 8 1144 1410 1012~ 101285 SCHM~ 920 161. 395. 466889 5
#> 9 1168 1438 10131 10131 DACE~ 413 70.6 252. 440031 5
#> 10 1380 114352 1015~ 149529 CASA~ 820 142. 386. 466957 5
#> # ... with 990 more rows, and 9 more variables: dbh <dbl>, pom <chr>,
#> # hom <dbl>, ExactDate <date>, DFstatus <chr>, codes <chr>,
#> # nostems <dbl>, status <chr>, date <dbl>
#>
#> $tree6
#> # A tibble: 1,000 x 19
#> treeID stemID tag StemTag sp quadrat gx gy MeasureID CensusID
#> <int> <int> <chr> <chr> <chr> <chr> <dbl> <dbl> <int> <int>
#> 1 104 143 10009 10009 DACE~ 113 10.3 245. 582850 6
#> 2 119 158 1001~ 100104 MYRS~ 1021 183. 410. 578696 6
#> 3 180 225 1001~ 100174 CASA~ 921 165. 410. 617049 6
#> 4 602 736 1006~ 100649 GUAG~ 821 149. 414. 614253 6
#> 5 631 775 10069 10069 PREM~ 213 38.3 245. 598429 6
#> 6 647 793 1007~ 100708 SCHM~ 821 143. 411. 614211 6
#> 7 1086 1339 10122 10122 DRYG~ 413 68.9 253. 603131 6
#> 8 1144 1410 1012~ 101285 SCHM~ 920 161. 395. 616923 6
#> 9 1168 1438 10131 10131 DACE~ 413 70.6 252. 603151 6
#> 10 1380 1702 1015~ 101560 CASA~ 820 142. 386. 614023 6
#> # ... with 990 more rows, and 9 more variables: dbh <dbl>, pom <chr>,
#> # hom <dbl>, ExactDate <date>, DFstatus <chr>, codes <chr>,
#> # nostems <dbl>, status <chr>, date <dbl>Collapse all censuses into a single dataframe.
census56_df <- list_df(census56_list)
census56_df
#> # A tibble: 2,000 x 19
#> treeID stemID tag StemTag sp quadrat gx gy MeasureID CensusID
#> <int> <int> <chr> <chr> <chr> <chr> <dbl> <dbl> <int> <int>
#> 1 104 143 10009 10009 DACE~ 113 10.3 245. 439947 5
#> 2 119 158 1001~ 100104 MYRS~ 1021 183. 410. 466597 5
#> 3 180 225 1001~ 100174 CASA~ 921 165. 410. 466623 5
#> 4 602 736 1006~ 100649 GUAG~ 821 149. 414. 466727 5
#> 5 631 775 10069 10069 PREM~ 213 38.3 245. 439989 5
#> 6 647 793 1007~ 100708 SCHM~ 821 143. 411. 466743 5
#> 7 1086 1339 10122 10122 DRYG~ 413 68.9 253. 440021 5
#> 8 1144 1410 1012~ 101285 SCHM~ 920 161. 395. 466889 5
#> 9 1168 1438 10131 10131 DACE~ 413 70.6 252. 440031 5
#> 10 1380 114352 1015~ 149529 CASA~ 820 142. 386. 466957 5
#> # ... with 1,990 more rows, and 9 more variables: dbh <dbl>, pom <chr>,
#> # hom <dbl>, ExactDate <date>, DFstatus <chr>, codes <chr>,
#> # nostems <dbl>, status <chr>, date <dbl>Summarize by groups.
by_census <- group_by(census56_df, CensusID)
summarize(by_census, n = n_distinct(treeID))
#> Warning in summarise_impl(.data, dots): hybrid evaluation forced for
#> `n_distinct`. Please use dplyr::n_distinct() or library(dplyr) to remove
#> this warning.
#> # A tibble: 3 x 2
#> CensusID n
#> <int> <int>
#> 1 5 957
#> 2 6 1000
#> 3 NA 43
# Same
census56_df %>%
group_by(CensusID) %>%
summarize(n = n_distinct(treeID))
#> Warning in summarise_impl(.data, dots): hybrid evaluation forced for
#> `n_distinct`. Please use dplyr::n_distinct() or library(dplyr) to remove
#> this warning.
#> # A tibble: 3 x 2
#> CensusID n
#> <int> <int>
#> 1 5 957
#> 2 6 1000
#> 3 NA 43Pick rows and reorganize columns.
census56_df %>%
pick_dbh_over(250) %>%
pick_status("A") %>%
add_status_tree() %>%
select(dbh, contains("status"), everything())
#> Warning: No observation has .status = D
#> * Detected values: A
#> # A tibble: 210 x 20
#> dbh DFstatus status status_tree treeID stemID tag StemTag sp
#> <dbl> <chr> <chr> <chr> <int> <int> <chr> <chr> <chr>
#> 1 604 alive A A 1168 1438 10131 10131 DACE~
#> 2 NA broken ~ A A 1380 114352 1015~ 149529 CASA~
#> 3 370 alive A A 1564 1910 10176 10176 HOMR~
#> 4 NA broken ~ A A 1652 2026 1018~ 101867 OCOL~
#> 5 296 alive A A 3645 4426 1041~ 104113 SCHM~
#> 6 359 alive A A 4329 5283 1049 1049 INGL~
#> 7 NA broken ~ A A 6677 8147 1077~ 107760 CECS~
#> 8 319 alive A A 7832 9768 1092~ 109231 TETB~
#> 9 NA stem de~ A A 9689 12178 1115~ 111528 CORB~
#> 10 NA broken ~ A A 9873 116236 1117~ 129228 MICP~
#> # ... with 200 more rows, and 11 more variables: quadrat <chr>, gx <dbl>,
#> # gy <dbl>, MeasureID <int>, CensusID <int>, pom <chr>, hom <dbl>,
#> # ExactDate <date>, codes <chr>, nostems <dbl>, date <dbl>Thanks to all partners of ForestGEO, for sharing their ideas and code.