In USGS-R/mda.streams: Data Preparation, Access, and Analysis Functions for the Powell Center Continental Stream Metabolism Project

Fitting models in batch mode with config files is nice, but sometimes you just want to look at some data and/or run a model manually. In this case you can still leverage config files to specify the data based on what's available on ScienceBase.

library(mda.streams)
library(dplyr)
library(streamMetabolizer)

First make a config file.

sites <- c("nwis_01649190", "nwis_06478522")
config <- stage_metab_config(
  tag='0.0.13', strategy='initial K600 estimate', date=Sys.time(), 
  model="metab_mle", model_args="list(specs=specs('mle'))", site=sites, 
  start_date="2015-03-15", end_date="2015-04-15", filename=NULL)

Then use config_to_metab with prep_only=TRUE to get a list of the input data and arguments rather than a full metabolism model. Set the names of the list in a way that distinguishes meaningfully among the rows in config - that part is up to you to determine.

prep_list <- config_to_metab(config, rows=1:nrow(config), prep_only=TRUE) %>%
  setNames(sites)

The result is a list as long as nrow(config), where each list element is itself a list containing data, data_daily, and other arguments for that config row.

names(prep_list[[1]])

You can now inspect the data.

lapply(prep_list, function(prep) range(prep$data$solar.time))

You can still run the model if you like.

mm <- do.call(metab, prep_list[[1]])

The resulting model can now be explored.

plot_DO_preds(predict_DO(mm, "2015-04-10", "2015-04-15"))

USGS-R/mda.streams documentation built on June 3, 2023, 8:43 a.m.