fvs_run | R Documentation |
run fvs after preparing key files 1. prepare parameters 2. prepare prototype key file 3. generate key files for all cns 4. run fvs with run_fvs()
fvs_run(
key_df,
db_merge = "FVSOut.db",
fvs_commands = "FVS_commands.txt",
merge_dbs = T,
cluster = NA,
clear_db = T,
delete_temp_db = T,
append = F,
skip_empty = T
)
key_df |
input dataframe with key file parameters |
db_merge |
merge output parallel databases |
merge_dbs |
T/F should temp dbs be merged into a single databse |
cluster |
optional parallel cluster object |
clear_db |
T/F delete all old inputs |
delete_temp_db |
T/F delete temp db's used for parallel processing |
append |
T/F if the output db already exists, should it be appended or wiped |
run fvs after preparing key files 1. prepare parameters 2. prepare prototype key file 3. generate key files for all cns 4. run fvs with run_fvs()
Revision History
1.0 | 2021 Oct 08 Created |
Jacob Strunk <someone@somewhere.com>
fvs_load
fvs_make_keyfiles
fvs_keyfile_prototype
fvs_param_prototype
clus1 = parallel::makeCluster(4)
#assume a typical inventory dataset and prepare fvs parameters
stand_data = data.frame(stand=1:10, year=2000:2009)#'
df_params = fvs_protype_params()
df_params[1:nrow(stand_data),]=NA
df_params[,"std_id"] = stand_data$stand
df_params[,"invyr"] = stand_data$year
df_params[,"timint"] = 1
df_params[,"numcycle"] = 1
df_params[,"input_db"] = "c:/temp/fordata.db"
df_params[,"fvs_path"] = "C:/FVSbin/FVSca.exe"
df_params[,"tree_table"] = "fvs_treeinit"
df_params[,"stand_table"] = "fvs_standinit"
df_params
#prepare prototype key file
key_proto = fvs_prototype_keyfile(invyr = "InvYear 2001", notriple=NULL)
#convert prototype key file into series of key files associated with each cn
df_keys = fvs_make_keyfiles(df_params, key_proto = key_proto, cluster = clus1, id="std_id")
#lastly, actually run fvs
fvs_run(df_keys, cluster = clus1, db_merge = "FVS_AllRunsB.db")
parallel::stopCluster(clus1)
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