prdnrmplot function

Plot combined predicted and normalized results from a tidal object

Plot combined predicted and normalized results from a tidal object to evaluate the influence of salinity or flow changes on the response variable. The plot is similar to that produced by fitplot except predicted values are shown as points and observed values are removed.

prdnrmplot(dat_in, ...)

## S3 method for class 'tidal'
prdnrmplot(
  dat_in,
  tau = NULL,
  annuals = TRUE,
  logspace = TRUE,
  dt_rng = NULL,
  col_vec = NULL,
  lwd = 1,
  size = 2,
  alpha = 1,
  min_mo = 9,
  mo_strt = 10,
  pretty = TRUE,
  plot = TRUE,
  ...
)

## S3 method for class 'tidalmean'
prdnrmplot(
  dat_in,
  annuals = TRUE,
  logspace = TRUE,
  dt_rng = NULL,
  col_vec = NULL,
  lwd = 1,
  size = 2,
  alpha = 1,
  min_mo = 9,
  mo_strt = 10,
  pretty = TRUE,
  plot = TRUE,
  ...
)

Arguments

• dat_in: input tidal or tidalmean object
• ...: arguments passed to geom_line
• tau: numeric vector of quantiles to plot, defaults to all in object if not supplied
• annuals: logical indicating if plots are annual aggregations of results
• logspace: logical indicating if plots are in log space
• dt_rng: Optional chr string indicating the date range of the plot. Must be two values in the format 'YYYY-mm-dd' which is passed to as.Date.
• col_vec: chr string of plot colors to use, passed to gradcols. Any color palette from RColorBrewer can be used as a named input. Palettes from grDevices must be supplied as the returned string of colors for each palette.
• lwd: numeric value indicating width of lines
• size: numeric value indicating size of points
• alpha: numeric value indicating transparency of points or lines
• min_mo: numeric value from one to twelve indicating the minimum number of months with observations for averaging by years, applies only if annuals = TRUE. See annual_agg.
• mo_strt: numeric indicating month to start aggregation years, defaults to October for USGS water year from October to September, applies only if annuals = TRUE. See annual_agg.
• pretty: logical indicating if my subjective idea of plot aesthetics is applied, otherwise the ggplot default themes are used
• plot: logical if plot is returned, otherwise data used in the plot

Returns

A ggplot object that can be further modified

Examples

## load a fitted tidal object
data(tidfit)

## plot using defaults
prdnrmplot(tidfit)

## get the same plot but use default ggplot settings
prdnrmplot(tidfit, pretty = FALSE)

## plot in log space
prdnrmplot(tidfit, logspace = TRUE)

## plot specific quantiles
prdnrmplot(tidfit, tau = c(0.1, 0.9))

## plot the normalized predictions
prdnrmplot(tidfit, predicted = FALSE)

## plot as monthly values
prdnrmplot(tidfit, annuals = FALSE) 

## format the x-axis is using annual aggregations
library(ggplot2)

prdnrmplot(tidfit, annual = TRUE) + 
 scale_x_date(limits = as.Date(c('2000-01-01', '2012-01-01')))

## modify the plot as needed using ggplot scales, etc.
prdnrmplot(tidfit, pretty = FALSE, linetype = 'dashed') + 
 theme_classic() + 
 scale_y_continuous(
   'Chlorophyll', 
   limits = c(0, 50)
   ) +
 scale_colour_manual( 
   '', 
   labels = c('lo', 'md', 'hi'), 
   values = c('red', 'green', 'blue'), 
   guide = guide_legend(reverse = TRUE)
   ) 
 
 ## plot a tidalmean object
 data(tidfitmean)
 
 prdnrmplot(tidfitmean)

See Also

fitplot, sliceplot