compareCLASS | R Documentation |
this function takes multiple classifications of the same data and compares the agreement between each, on a timepoint level.
compareCLASS(date, classifications)
date |
datetime in POSIXCT format. See hoopoe$activity$date for example |
classifications |
a dataframe containing the results from different classifications in each column. The classifications must correspond to the same datetimes. |
a dataframe containing date
the raw classifications
each state with the number of times it was used in a classification
whether or not all classes provided the same state
## Import data
#data(hoopoe)
#start = as.POSIXct("2016-07-01","%Y-%m-%d", tz="UTC")
#end = as.POSIXct("2017-06-01","%Y-%m-%d", tz="UTC")
#PAM_data= cutPAM(hoopoe,start,end)
## perform one classification using classifyFLAP
#classification = classifyFLAP(dta = PAM_data$acceleration, period = 12)
## Put the classification in the same resolution as pressure
#class1 = classification2PAM(from = classification$timetable$start,
# to = classification$timetable$end,
# # because the timetable only contains migration periods
# classification = rep_len(1,length(classification$timetable$end)),
# addTO = PAM_data$pressure)
## Convert to categories
#class1 = ifelse(class1 == classification$migration, "Migration", "Other")
## Perform another classification using pressure difference
#class2 = c(0,ifelse(abs(diff(PAM_data$pressure$obs))>2, "Migration", "Other"))
## both classes have been converted to the same time intervals as pressure,
#date = PAM_data$pressure$date
## Combine the classifications into a dataframe
#classifications = data.frame(flap = class1, # flapping classification
# Pdiff = class2) # pressure difference classification
#class_comparison = compareCLASS(date=date,
# classifications=classifications)
#plot(PAM_data$pressure$date,
# PAM_data$pressure$obs,
# type = "l",
# xlab = "Date",
# ylab = "Pressure (hPa)",
# col = "royalblue3")
#points(PAM_data$pressure$date,
# PAM_data$pressure$obs,
# cex = class_comparison$Migration / 2,
# col ="orange",
# pch = 16)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.