biogeom (version 1.4.3)

curveovate: Drawing the Ovate Leaf-Shape Curve

Description

curveovate is used to draw the ovate leaf-shape curve.

Usage

curveovate(expr, P, x, fig.opt = FALSE, 
           deform.fun = NULL, Par = NULL,
           xlim = NULL, ylim = NULL, unit = NULL, main = NULL)

Value

x

the \(x\) coordinates of the ovate leaf-shape curve.

y

the \(y\) coordinates of the ovate leaf-shape curve.

Arguments

expr

the simplified version 1 of a performance equation.

P

the three location parameters and the parameters of the simplified version 1 of a performance equation.

x

the given \(x\) values to draw the ovate leaf-shape curve.

fig.opt

an optional argument to draw the ovate leaf-shape curve.

deform.fun

the deformation function used to describe the deviation from a theoretical ovate leaf-shape curve.

Par

the parameter(s) of the deformation function.

xlim

the range of the \(x\)-axis over which to plot the ovate leaf-shape curve.

ylim

the range of the \(y\)-axis over which to plot the ovate leaf-shape curve.

unit

the units of the \(x\)-axis and the \(y\)-axis when showing the ovate leaf-shape curve.

main

the main title of the figure.

Author

Peijian Shi , Johan Gielis , Brady K. Quinn .

Details

P has two types of elements: three location parameters, and model parameters. This means that expr is limited to be the simplified version 1 (where \(x_{\mathrm{min}} = 0\)) in MbetaE, MBriereE, MLRFE, and MPerformanceE. The first three elements of P are location parameters, among which the first two are the planar coordinates of the transferred origin, and the third is the angle between the major axis of the curve and the \(x\)-axis. deform.fun should take the form as: deform.fun <- function(Par, z){...}, where z is a two-dimensional matrix related to the \(x\) and \(y\) values. And the return value of deform.fun should be a list with two variables x and y.

References

Jin, J., Quinn, B.K., Shi, P. (2022) The modified Brière equation and its applications. Plants 11, 1769. tools:::Rd_expr_doi("10.3390/plants11131769")

Huey, R.B., Stevenson, R.D. (1979) Integrating thermal physiology and ecology of ectotherms: a discussion of approaches. American Zoologist 19, 357\(-\)366. tools:::Rd_expr_doi("10.1093/icb/19.1.357")

Li, Y., Zheng, Y., Ratkowsky, D.A., Wei, H., Shi, P. (2022) Application of an ovate leaf shape model to evaluate leaf bilateral asymmetry and calculate lamina centroid location. Frontiers in Plant Science 12, 822907. tools:::Rd_expr_doi("10.3389/fpls.2021.822907")

Lian, M., Shi, P., Zhang, L., Yao, W., Gielis, J., Niklas, K.J. (2023) A generalized performance equation and its application in measuring the Gini index of leaf size inequality. Trees - Structure and Function 37, 1555\(-\)1565. tools:::Rd_expr_doi("10.1007/s00468-023-02448-8")

Shi, P., Fan, M., Ratkowsky, D.A., Huang, J., Wu, H., Chen, L., Fang, S., Zhang, C. (2017) Comparison of two ontogenetic growth equations for animals and plants. Ecological Modelling 349, 1\(-\)10. tools:::Rd_expr_doi("10.1016/j.ecolmodel.2017.01.012")

Shi, P., Ge, F., Sun, Y., Chen, C. (2011) A simple model for describing the effect of temperature on insect developmental rate. Journal of Asia-Pacific Entomology 14, 15\(-\)20. tools:::Rd_expr_doi("10.1016/j.aspen.2010.11.008")

Shi, P., Gielis, J., Quinn, B.K., Niklas, K.J., Ratkowsky, D.A., Schrader, J., Ruan, H., Wang, L., Niinemets, Ü. (2022) 'biogeom': An R package for simulating and fitting natural shapes. Annals of the New York Academy of Sciences 1516, 123\(-\)134. tools:::Rd_expr_doi("10.1111/nyas.14862")

Shi, P., Yu, K., Niklas, K.J., Schrader, J., Song, Y., Zhu, R., Li, Y., Wei, H., Ratkowsky, D.A. (2021) A general model for describing the ovate leaf shape. Symmetry 13, 1524. tools:::Rd_expr_doi("10.3390/sym13081524")

See Also

areaovate, fitovate, MbetaE, MBriereE, MLRFE, MPerformanceE

Examples

P1  <- c(1, 1, pi/4, 2, 3, 10, 4)
RE1 <- curveovate(MLRFE, P=P1, x=seq(0, 10, by=0.1), fig.opt=TRUE)
RE2 <- curveovate(MbetaE, P=P1, x=seq(0, 10, by=0.1), fig.opt=TRUE)

dev.new()
plot(RE1$x, RE1$y, cex.lab=1.5, cex.axis=1.5, type="l", 
  xlab=expression(italic(x)), ylab=expression(italic(y))) 
lines(RE2$x, RE2$y, col=4)

P3  <- c(1, 1, pi/4, 2.4, 0.96, 0.64, 7.75, 1.76, 3.68)
RE3 <- curveovate(MPerformanceE, P=P3, x=seq(0, 7.75, by=0.01), fig.opt=TRUE)

dev.new()
plot(RE3$x, RE3$y, cex.lab=1.5, cex.axis=1.5, type="l", 
  xlab=expression(italic(x)), ylab=expression(italic(y))) 

graphics.off()