## ----include=FALSE------------------------------------------------------------ library("incR") data("incR_rawdata") # loading the data head(incR_rawdata) ## ----eval = TRUE-------------------------------------------------------------- incR_rawdata_prep <- incRprep(data = incR_rawdata, date.name = "DATE", date.format= "%d/%m/%Y %H:%M", timezone="GMT", temperature.name="temperature") head(incR_rawdata_prep, 3) ## ----eval = TRUE-------------------------------------------------------------- data(incR_envdata) # environmental data head (incR_envdata) # then use incRenv to merge environmental data incR_data <- incRenv (data.nest = incR_rawdata_prep, # data set prepared by incRprep data.env = incR_envdata, env.temperature.name = "env_temperature", env.date.name = "DATE", env.date.format = "%d/%m/%Y %H:%M", env.timezone = "GMT") head (incR_data, 3) ## ----------------------------------------------------------------------------- incubation.analysis <- incRscan (data=incR_data, temp.name="temperature", lower.time=22, upper.time=3, sensitivity=0.15, temp.diff.threshold =5, maxNightVariation=2, env.temp="env_temp") ## ----------------------------------------------------------------------------- names(incubation.analysis) # incRscan output head(incubation.analysis$incRscan_data) head(incubation.analysis$incRscan_threshold) ## ----------------------------------------------------------------------------- my_plot <- incRplot(data = incubation.analysis$incRscan_data, time.var = "dec_time", day.var = "date", inc.temperature.var = "temperature", env.temperature.var = "env_temp", vector.incubation = "incR_score") # a ggplot plot is created that can be modified by the user my_plot + ggplot2::labs(x = "Time", y = "Temperature") ## ----------------------------------------------------------------------------- incRatt(data = incubation.analysis[[1]], vector.incubation = "incR_score") ## ----------------------------------------------------------------------------- incRact(data = incubation.analysis[[1]], time_column = "time", vector.incubation = "incR_score") ## ----eval = TRUE-------------------------------------------------------------- incRt(data = incubation.analysis[[1]], temp.name = "temperature", limits = c(5,21), # time window coor = NULL, activity.times = FALSE, civil.twilight = FALSE, time.zone = NULL) ## ----eval = TRUE-------------------------------------------------------------- incRt(data = incubation.analysis[[1]], temp.name = "temperature", limits = NULL, coor = NULL, activity.times = TRUE, # incRact is called to define time window civil.twilight = FALSE, time.zone = "GMT", time_column= "time", vector.incubation="incR_score") ## ----eval = TRUE-------------------------------------------------------------- incRt(data = incubation.analysis[[1]], temp.name = "temperature", limits = NULL, coor = c(39.5, 40.5), # choose your coordinates activity.times = FALSE, civil.twilight = TRUE, time.zone = "GMT") ## ----eval = TRUE-------------------------------------------------------------- bouts <- incRbouts(data = incubation.analysis[[1]], vector.incubation = "incR_score", sampling.rate = incubation.analysis[[1]]$dec_time[56] - incubation.analysis[[1]]$dec_time[55], # sampling interval dec_time = "dec_time", temp = "temperature") # the results are in two tables names(bouts) # bouts per day head(bouts$day_bouts) # bout specific data head(bouts$total_bouts)