View source: R/A_EVENTS_v1_v2_pipeline.r
| eva | R Documentation | 
Fetches the raw data using a connection to the database based on dbcon, then calculates when an individual was assumably at the nest box. Runs across the databases SNBatWESTERHOLZ and SNBatWESTERHOLZ_v2. Uses parallel computing.
eva(
  df,
  setTZ = "Etc/GMT-2",
  time_threshold_v1 = 2,
  max_distance_v1 = 16 * 60 * 60,
  tr_threshold_v2 = 5,
  cluster_events_threshold_v2 = 2,
  max_distance_v2 = 16 * 60 * 60,
  cluster_fronts_threshold_v2 = 5,
  no_front_v2 = NULL,
  N_cores = 50
)
| df | a data.table that contains three columns about which data should be fetched: the box numbers, and the corresponding from and to (column names: box, from, to). See examples. | 
| time_threshold_v1 | time_threshold argument for function events_v1 | 
| max_distance_v1 | max_distance argument for function events_v1 | 
| tr_threshold_v2 | tr_threshold argument for function events_v2 | 
| cluster_events_threshold_v2 | cluster_events_threshold argument for function events_v2 | 
| max_distance_v2 | max_distance argument for function events_v2 | 
| cluster_fronts_threshold_v2 | arguments for function events_v2 | 
| no_front_v2 | no_front argument for function events_v2 | 
| con | the connection to the database. | 
Note that currently you need to have saved your credentials via save_credentials in order to run the function.
LS
df = data.table(box = 1, from = "2019-05-01 00:00:00", to = "2019-06-30 00:00:00")
hooray = eva(df, 
      time_threshold_v1 = 10, tr_threshold_v2 = 100, N_cores = 2)
hooray
plot(hooray)
plot(subset(hooray, !is.na(transp) & box == 1 & in_ > "2019-05-15" & in_ < "2019-05-25"))
#Note that you can access the colours and counts of individual transponders by using
tr = plot(hooray)
tr
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