jasmyace
commented
10 years ago Within function F.get.catch.data, pulled variable includeCatchID from query-derived Access table TempSamplingSummary and joined via function merge to dataframe catch, which has the bulk of the rest of the catch information utilized in this function via variables trapPositionID, EndTime, and ProjID. Ultimately pushed (new and improved) dataframe catch to passage as list tmp.df, from which its dataframe element catch.df is further manipulated.
Eventually, includeCatchID enjoys the ride to function F.est.passage, where it ultimately is included into baseTable.csv output. Most batchDates in baseTable.csv receive either an includeCatchID value of 1 or 2, where 1 presumably means 'yes,' and 2 means 'no.' In some cases however, no value of includeCatchID is found, resulting in an NA for that batchDate. These appear to concur with stretches of multiple days for which counts must be imputed, except for the last in the series.
Finally, within the dataset obtained via use of variable values
river <- 'american'
site <- 57000 # American River site id
taxon <- 161980
run <- 3
min.date <- "2013-01-01"
max.date <- "2013-06-30"
by <- "day"
output.file <- paste0("../outputs/",river,"/",by,"/",river)
by.lifestage <- FALSE
ci <- TRUE
output.type <- "odt"
from <- "Trent McDonald, Ph.D., WEST Incorporated"
to <- "Doug Threloff, USFWS CAMP Coordinator"
return.addr <- "FISH AND WILDLIFE SERVICE!USFWS Caswell State Park Office!1234 Abbey Rd.!Caswell, California 96080!(530) 527-3043, FAX (530) 529-0292",
three batchDates come back with two distinct records, i.e., a 1 and an NA for variable includeCatchID. I haven't investigated this too much, but very preliminarily, it looks like a few records that have a value for includeCatchID in table TempSamplingSummary don't have corresponding records in table TempSumUnmarkedByTrap_Run_Final.
"In the daily production summary CSV file, add the includeCatchID field such that it provides a 'yes' or 'no' notation."