Week 19 notes
9 mai 2016
0.1 Week 19, 2016
Happily it’s not week 19 of the internship, just 2016. However, it’s already week 10 of 34!
thisweek <- 10 yikes <- c(thisweek, 34-thisweek) / 34 barplot(as.matrix(yikes), horiz=TRUE, beside=FALSE)
Last week I got all our current scores loaded into a local postgres database; poked through a shiny tutorial; switched from RPostgres driver to dplyr (for better or worse); and corrected a first CRPS plot to make a little sense.
It’s true, sometimes this geologist struggles to grok the model scores in forecasting!
This week I need to:
- decide if the SOS database format is the way to go forward,
- which makes maintenance easier
- but dplyr less useful
- and I’d learn curl
- load data to AWS instance
- use .Renviron to point at dev / prod databases
- mysteries to solve
- where does dplyr disconnect pooled connections?
- strategies for a multi-user app?
- R fundamentals I still need
- difference btw filter() and subset?
- Some helpful r debugging links:
This week so far I have done:
- modified local db to match v2 specifics
- built interactive dataframe to postgres db,
- built csv upload function which loads SMHI files successfully
- finished main score series viewer
This first-pass structure worked for simple data off all one datatype…
… but in fact we are scoring many variables which need to be tied together more explicitely. Hence, version 2:
We need a structure for the scores to import - currently receiving text files and 3D “cubes” depending on source… tidying takes time; should be automated so users may load / arrange their scores (like EVS).
Working with “reactive” call today: https://gallery.shinyapps.io/003-reactivity/
Something to look into on my time – confidence Intervals discussed in different context: http://learnbayes.org/papers/confidenceIntervalsFallacy/introduction.html …with nifty Shiny app to illustrate Figs 1 - 5 from article: https://richarddmorey.shinyapps.io/confidenceFallacy/ http://learnbayes.org/papers/confidenceIntervalsFallacy/