calibrate_reconstructions | R Documentation |
Calculate and displays reconstructed shapes using a range of harmonic number. Compare them visually with the maximal fit. This explicitely demonstrates how robust efourier is compared to tfourier and rfourier.
calibrate_reconstructions_efourier(x, id, range = 1:9)
calibrate_reconstructions_rfourier(x, id, range = 1:9)
calibrate_reconstructions_tfourier(x, id, range = 1:9)
calibrate_reconstructions_sfourier(x, id, range = 1:9)
calibrate_reconstructions_npoly(
x,
id,
range = 2:10,
baseline1 = c(-1, 0),
baseline2 = c(1, 0)
)
calibrate_reconstructions_opoly(
x,
id,
range = 2:10,
baseline1 = c(-1, 0),
baseline2 = c(1, 0)
)
calibrate_reconstructions_dfourier(
x,
id,
range = 2:10,
baseline1 = c(-1, 0),
baseline2 = c(1, 0)
)
x |
the |
id |
the shape on which to perform calibrate_reconstructions |
range |
vector of harmonics on which to perform calibrate_reconstructions |
baseline1 |
|
baseline2 |
|
a ggplot object and the full list of intermediate results. See examples.
Other calibration:
calibrate_deviations()
,
calibrate_harmonicpower()
,
calibrate_r2()
### On Out
shapes %>%
calibrate_reconstructions_efourier(id=1, range=1:6)
# you may prefer efourier...
shapes %>%
calibrate_reconstructions_tfourier(id=1, range=1:6)
#' you may prefer efourier...
shapes %>%
calibrate_reconstructions_rfourier(id=1, range=1:6)
#' you may prefer efourier... # todo
#shapes %>%
# calibrate_reconstructions_sfourier(id=5, range=1:6)
### On Opn
olea %>%
calibrate_reconstructions_opoly(id=1)
olea %>%
calibrate_reconstructions_npoly(id=1)
olea %>%
calibrate_reconstructions_dfourier(id=1)
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