fitplot function

Plot the fitted results for a tidal object

Plot a tidal object to view response variable observations, predictions, and normalized results.

fitplot(dat_in, ...)

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

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

Arguments

• dat_in: input tidal or tidalmean object
• ...: arguments passed to other methods
• tau: numeric vector of quantiles to plot, defaults to all in object if not supplied
• predicted: logical indicating if standard predicted values are plotted, default TRUE, otherwise normalized predictions are plotted
• 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.
• grids: logical indicating if grid lines are present
• 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
• lwd: numeric value indicating width of lines
• size: numeric value indicating size of points
• alpha: numeric value indicating transparency of points or lines

Returns

A ggplot object that can be further modified

Examples

## load a fitted tidal object
data(tidfit)

# plot using defaults
fitplot(tidfit)

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

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

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

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

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

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

fitplot(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.

fitplot(tidfit, pretty = FALSE, linetype = 'dashed') + 
 theme_classic() + 
 scale_y_continuous(
   'Chlorophyll', 
   limits = c(0, 50)
   ) +
 scale_colour_manual( 
   'Predictions', 
   labels = c('lo', 'md', 'hi'), 
   values = c('red', 'green', 'blue'), 
   guide = guide_legend(reverse = TRUE)
   ) 
 
# plot a tidalmean object
data(tidfitmean)

fitplot(tidfitmean)

See Also

fitmoplot, prdnrmplot, sliceplot