View source: R/dm.na.interpolation.R
| plot.dm_na_interpolation | R Documentation |
S3 plot method for objects returned by dm.na.interpolation.
## S3 method for class 'dm_na_interpolation'
plot(
x,
type = NULL,
series = NULL,
metric = "MdAPE",
original = NULL,
start = NULL,
end = NULL,
free_y = TRUE,
ncol = 1,
facet = TRUE,
empty_gaps = c("plot", "error"),
...
)
x |
Object returned by |
type |
Character. Plot type:
|
series |
Optional character vector of series names to plot. |
metric |
Character assessment metric used when |
original |
Optional original input data frame used before interpolation. |
start |
Optional start datetime for subsetting. |
end |
Optional end datetime for subsetting. |
free_y |
Logical. If |
ncol |
Integer. Number of facet columns. |
facet |
Logical. If |
empty_gaps |
Character. Behavior when |
... |
Further arguments. |
A ggplot2 object.
library(dendRoAnalyst)
data(nepa17)
## No gaps: defaults to time-series plot
#res0 <- dm.na.interpolation(nepa17[1:1000, ], resolution = 60)
#plot(res0)
#plot(res0, type = "gaps")
#plot(res0, type = "gaps", empty_gaps = "error")
## Filled data
#res1 <- dm.na.interpolation(
# nepa17[1:1000, ],
# resolution = 60,
# fill = TRUE,
# method = "spline"
#)
#plot(res1)
#plot(res1, type = "gaps")
#plot(res1, type = "interpolation", original = nepa17[1:1000, ])
## Assessed data
#res2 <- dm.na.interpolation(
# nepa17[1:1000, ],
# resolution = 60,
# fill = TRUE,
# method = "seasonal",
# assess = TRUE
#)
#plot(res2)
#plot(res2, type = "assessment", metric = "MdAPE")
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