tempo.cat<-paste0("\n\n================\n\nERROR IN ",function.name,": REQUIRED fun_param_check() FUNCTION IS MISSING IN THE R ENVIRONMENT\n\n================\n\n")
stop(tempo.cat)
}
# end required function checking
# argument checking
arg.check<-NULL# for function debbuging
checked.arg.names<-NULL# for function debbuging: used by r_debugging_tools
stop()# nothing else because print = TRUE by default in fun_param_check()
}
# end argument checking with fun_param_check()
# source("C:/Users/Gael/Documents/Git_versions_to_use/debugging_tools_for_r_dev-v1.2/r_debugging_tools-v1.2.R") ; eval(parse(text = str_basic_arg_check_dev)) ; eval(parse(text = str_arg_check_with_fun_param_check_dev)) # activate this line and use the function (with no arguments left as NULL) to check arguments status and if they have been checked using fun_param_check()
# end argument checking
# main code
tempo.range<-diff(sort(lim))
tempo.max<-max(lim)
tempo.min<-min(lim)
tempo.inter<-tempo.range/(n+1)# current interval between two ticks, between 0 and Inf
# if tempo.inter = zero -> error
log10.abs.lim<-200
log10.range<-(-log10.abs.lim):log10.abs.lim
log10.vec<-10^log10.range
round.vec<-c(5,2.5,2,1.25,1)
dec.table<-outer(log10.vec,round.vec)# table containing the scale units (row: power of ten from -201 to +199, column: the 5, 2.5, 2, 1.25, 1 notches
# recover the number of leading zeros in tempo.inter
power10.exp<-as.integer(substring(text=tempo.inter,first=(regexpr(pattern="\\+",text=tempo.inter)+1)))# recover the power of 10. Example recover 08 from 1e+08
mantisse<-as.numeric(substr(x=tempo.inter,start=1,stop=(regexpr(pattern="\\+",text=tempo.inter)-2)))# recover the mantisse. Example recover 1.22 from 1.22e+08
power10.exp<-as.integer(substring(text=tempo.inter,first=(regexpr(pattern="\\-",text=tempo.inter)+1)))# recover the power of 10. Example recover 08 from 1e+08
mantisse<-as.numeric(substr(x=tempo.inter,start=1,stop=(regexpr(pattern="\\-",text=tempo.inter)-2)))# recover the mantisse. Example recover 1.22 from 1.22e+08
# if dots from data2 look significant on the graph (outside the frame) but are not (not black on the last figure), this is probably because the frame is flat on the zero coordinate (no volume inside the frame at this position). Thus, no way to conclude that data2 dots here are significant. These dots are refered to as "unknown". The pb.dot argument deals with such dots
# dots that are sometimes inside and outside the frame, depending on the sliding windows, are treated differently: they are removed. Such dots are neither classified as "signif", "non signif" or "unknown", but as "inconsistent"
# unknown dots are treated as finally significant, not significant, or unknown (data2.pb.dot argument) for each x-axis and y-axis separately. Then, the union or intersection of significant dots is performed (argument xy.cross.kind). See the example section
# ARGUMENTS
# data1: a dataframe containing a column of x-axis values and a column of y-axis values
# x1: character string of the data1 column name for x-axis (first column of data1 by default)
