Use ffcAPIClient to Follow CEFF Steps • ffcAPIClient

Step One

library(ffcAPIClient)

ffc <- FFCProcessor$new()  # make a new object we can use to run the commands

# configure the object and run CEFF step 1 plus outputs

ffc$step_one_functional_flow_results(gage_id=11336000,
     token=token,
     output_folder = "C:/Users/myusername/Downloads/test")

That command will output DOH data + image, observed annual data, observed percentiles, and observed plots to the specified folder. It will output the percentiles to the console as well.

It also makes that data available for further analysis on the object ffc, so you can now access the FFC results by year as ffc$ffc_results, the processed percentiles as ffc$ffc_percentiles, and the underlying DOH data as ffc$doh_data if you want to view them again in R or feed them into other code and visualizations.

It is highly recommended that you provide the output_folder parameter, as the package will also output its log file there, in addition to plots and CSV results. The log will help track the history of the results in case of future changes.

Step Two

For step 2, we now run simply ffc$step_two_explore_ecological_flow_criteria() and it continues where we left off. In fact, everything is run in step 1, and we just control what is output with these functions. This outputs the predicted metric percentile data as a CSV and to the console, and plots the predicted values on their own.

Now we can access ffc$predicted_percentiles if we want to feed that into other processing or visualizations too.

Step Three

For step 3, same thing. Run ffc$step_three_assess_alteration() and get the alteration data frame saved as a CSV and printed to the console. Full comparison plots of predicted vs. observed percentiles are output now to the screen and to the folder specified in step 1 (where everything is saved).

And now we get one more thing we can access - ffc$alteration contains the alteration assessment results. In fact everything is accessible after step 1, but conceptually, this is the data frame that corresponds with this step.

There’s also more that’s available as part of the ffc object, but we’ll document that elsewhere.