rm(list=ls())
ts1 <- ts(rnorm(1:100),start=c(1993,4),frequency=4)
ts2 <- ts(rnorm(1:100),start=c(1993,4),frequency=4)
ts3 <- ts(rnorm(1:100),start=c(1993,4),frequency=4)
add_mi(ts1,srcname="chdlu.db",legacy_key="lalal")
add_mi(ts2,srcname="chdlu.db",legacy_key="muooooo")
add_mi(ts3,srcname="chdlu.db",legacy_key="fasdf")
meta$ts2
rm(ts2)
# get all attributes available in the real environment
debug(meta$moooo$add_localized_mi)
meta$ts1$add_localized_mi("en",paste(LETTERS,letters,sep="_"),1:26)
rm(meta)
meta$ts1$ts_localized_mi$en
lookUp <- function(pattern){
objs <- ls(envir=.GlobalEnv)
hits <- lapply(objs,function(x) attr(get(x),"mi_key"))
}
!unlist(lapply(h1,is.null))
meta$moooo$ggplot()
# gotta convert away from
t0 <- ts1
# convert data frame
df <- data.frame(Date = .zoolike.Date.convert(t0),
value = as.numeric(t0))
require(ggplot2)
require(plyr)
g1 <- ggplot(data=df,aes(Date,value))
g1 + geom_point()
str(df)
# next things:
# better show method for mi_ts !
# add show all method
# slot based lookup with xsr
# be able to crawl all mi_keys in attributes of the globals environment.
# maybe rather zoo like date convert based on original series
# in plotting (and database functions)
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