PRISMdownload.R

######################################################################################
# PROGRAM: download.prism 
# USE: BATCH DOWNLOAD AND UNCOMPRESSION OF PRISM DAILY OR MONTHLY GRIDDED DATA
#        PRISM URL: http://prism.nacse.org/
# REQUIRES: >= R 3.0, RCurl
#
# ARGUMENTS:
#     data.type             TYPE OF CLIMATE DATA ("ppt","tmin","tmax","tmean")
#     date.range            A VECTOR WITH START AND END DATA IN y/m/d FORMAT 
#     time.step             DEFINES TIMESTEP OF PRODUCT ("daily"/"monthly") 

anarosner

#purling is in the knitr package
library(knitr)


setwd("C:/ALR/Models/boo") #example using local windows directory, can easily switch

#it can be really simple
purl( "script1.Rmd", "script1.R" )
#just specify the rmd filename, then r filename, with extensions

djhocking

# fetch temperature data
tbl_values <- left_join(tbl_series,
                        select(tbl_variables, variable_id, variable_name),
                        by=c('variable_id'='variable_id')) %>%
  select(-file_id) %>%
  filter(location_id %in% df_locations$location_id,
         variable_name=="TEMP") %>%
  left_join(tbl_values,
            by=c('series_id'='series_id')) %>%
  left_join(select(tbl_locations, location_id, location_name, latitude, longitude, featureid=catchment_id),

tmalsburg

Predict vs simulate in lme4

For this investigation we are going to use the sleepdata data set from the lme4 package. Here is the head of the data frame:

djhocking

# ggplot boxplot groups of continuous x

### Daniel J. Hocking

I am trying to make a boxplot with ggplot2 in R where the x-axis in continous but their are paired boxplots for each value of on the x-axis based on another factor with two possible values. I want to make a plot where boxplots are arranged by number of survey years on the x-axis but paired by spatialTF (2 boxplots for every value of n_years) but n_years are not evenly spaced.

This plot gets the paired boxplots correct by year but the years on the x-axis are evenly spaced and don't reflect the actual (continuous) time between years.

```
ggplot(df_converged, aes(factor(n_years), mean_N_est)) +