rcaiman (version 1.2.2)

fit_coneshaped_model: Fit cone-shaped model

Description

Statistical modeling for predicting digital numbers from spherical coordinates.

Usage

fit_coneshaped_model(sky_points, use_azimuth_angle = TRUE)

Value

A list of two objects, one of class function and the other of class lm (see stats::lm()). If the fitting fails, it returns NULL. The function requires two arguments--zenith and azimuth in degrees--to return relative luminance.

Arguments

sky_points

The data.frame returned by extract_rl() or a data.frame with same structure and names.

use_azimuth_angle

Logical vector of length one. If TRUE, the Equation 4 from Diaz2018;textualrcaiman) is used: \(sDN = a + b \cdot \theta + c \cdot \theta^2 + d \cdot sin(\phi) + e \cdot cos(\phi)\), where \(sDN\) is sky digital number, \(a,b,c,d\) and \(e\) are coefficients, \(\theta\) is zenith angle, and \(\phi\) is azimuth angle. If FALSE, the next simplified version based on Wagner2001;textualrcaiman is used: \(sDN = a + b \cdot \theta + c \cdot \theta^2\).

Details

This method was presented in Diaz2018;textualrcaiman, under the heading Estimation of the sky DN as a previous step for our method. If you use this function in your research, please cite that paper in addition to this package (citation("rcaiman").

References

See Also

thr_mblt()

Other Sky Reconstruction Functions: cie_sky_model_raster(), fit_cie_sky_model(), fit_trend_surface(), fix_reconstructed_sky(), interpolate_sky_points(), ootb_sky_reconstruction()

Examples

if (FALSE) {
path <- system.file("external/DSCN4500.JPG", package = "rcaiman")
caim <- read_caim(path, c(1250, 1020) - 745, 745 * 2, 745 * 2)
z <- zenith_image(ncol(caim), lens("Nikon_FCE9"))
a <- azimuth_image(z)
r <- gbc(caim$Blue)

sky_points <- extract_rl(r, z, a, extract_sky_points_simple(r, z, a),
                         NULL,
                         use_window = FALSE)#this is important when
                                            #extract_sky_points_simple()
                                            #is used
model <- fit_coneshaped_model(sky_points$sky_points)
summary(model$model)
sky_cs <- model$fun(z, a)
plot(r/sky_cs)
plot(sky_cs)

z <- zenith_image(50, lens())
a <- azimuth_image(z)
sky_cs <- model$fun(z, a)
persp(sky_cs, theta = 90, phi = 20)
}