Point d'intersection dans ggplot2

Question

J'ai besoin de trouver les points d'intersection entre deux courbes que j'ai tracées dans ggplot2.

Ceci est mon code:

ggplot(Table1, aes(x=10^H4,y=10^H5, colour = "blabla")) + 
    geom_line(size=1) + coord_cartesian(xlim=c(100,1000000000))+ 
coord_cartesian(ylim=c(0.000000000001,1)) + xlab("blabla")+ 
ylab("blabla") + ggtitle("blabla")+ 
scale_y_log10(breaks=c(0.000000000001, 0.000000001, 0.000001, 0.001) 
, labels = trans_format("log10", math_format(10^.x)))+ 
scale_x_log10(breaks=c(100,1000,10000,100000,1000000,10000000,100000000,1000000000) 
, labels = trans_format("log10", math_format(10^.x))) + 
    geom_line(data=Table1,aes(10^H4,10^H6, colour = "blabla1"))+ 
    scale_color_manual("", values =c("blabla"="blue", "blabla1" = "red") 
, labels=c("blabla","blabla1")) 

J'ai essayé d'utiliser la locator() qui est utile, mais pas précis que je pense:

Desired point

Le point désiré est à 24600.

J'ai également essayé d'utiliser le intercept(x,y):

a <- 10^A5 
b <- 10^A6 
intercept(a,b) 
3.689776e-07 1.963360e-07 6.622165e-07 

Ce qui n'est pas le cas, je présume qu'il pourrait ne pas tenir compte du fait qu'il s'agit d'une échelle log-log.

Mes données:

structure(list(H4 = c(2, 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 
2.9, 3, 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4, 4.1, 
4.2, 4.3, 4.4, 4.5, 4.6, 4.7, 4.8, 4.9, 5, 5.1, 5.2, 5.3, 5.4, 
5.5, 5.6, 5.7, 5.8, 5.9, 6, 6.1, 6.2, 6.3, 6.4, 6.5, 6.6, 6.7, 
6.8, 6.9, 7, 7.1, 7.2, 7.3, 7.4, 7.5, 7.6, 7.7, 7.8, 7.9, 8, 
8.1, 8.2, 8.3, 8.4, 8.5, 8.6, 8.7, 8.8, 8.9, 9), H5 = c(-8.979, 
-8.927, -8.877, -8.829, -8.782, -8.736, -8.691, -8.648, -8.606, 
-8.565, -8.525, -8.485, -8.445, -8.405, -8.364, -8.323, -8.282, 
-8.241, -8.2, -8.159, -8.116, -8.064, -7.982, -7.826, -7.592, 
-7.333, -7.101, -6.91, -6.759, -6.64, -6.543, -6.461, -6.387, 
-6.321, -6.264, -6.218, -6.182, -6.155, -6.132, -6.117, -6.111, 
-6.12, -6.23, -6.433, -6.574, -6.664, -6.712, -6.726, -6.722, 
-6.707, -6.704, -6.748, -6.82, -6.864, -6.872, -6.859, -6.83, 
-6.796, -6.757, -6.717, -6.678, -6.636, -6.594, -6.549, -6.502, 
-6.454, -6.402, -6.349, -6.295, -6.238, -6.179), H6 = c(-5.116, 
-5.31, -5.495, -5.669, -5.823, -5.958, -6.075, -6.179, -6.271, 
-6.355, -6.433, -6.506, -6.575, -6.642, -6.707, -6.769, -6.829, 
-6.886, -6.941, -6.993, -7.044, -7.095, -7.144, -7.192, -7.237, 
-7.28, -7.321, -7.36, -7.398, -7.435, -7.47, -7.504, -7.536, 
-7.569, -7.602, -7.64, -7.684, -7.735, -7.789, -7.848, -7.917, 
-8.003, -8.131, -8.312, -8.494, -8.668, -8.823, -8.963, -9.095, 
-9.225, -9.365, -9.531, -9.711, -9.859, -9.965, -10.041, -10.098, 
-10.141, -10.175, -10.203, -10.236, -10.263, -10.285, -10.301, 
-10.314, -10.323, -10.33, -10.335, -10.339, -10.342, -10.344)), .Names = c("H4", 
"H5", "H6"), row.names = c(NA, -71L), class = "data.frame") 

Answer 1

Nous pourrions utiliser la fonction approxfun(), qui effectue une interpolation linéaire. Nous utilisons la différence entre les deux courbes (ou entre l'ensemble de points de données) et ensuite trouver la valeur approximative dans l'axe des x qui fait la différence ou la valeur de y égale à 0.

#Finding the x value in the log10 scale 

f1 <- approxfun(10^Table1$H5 - 10^Table1$H6,Table1$H4, rule=2) 

f1(0) 
[1] 4.516067 

x11(); ggplot(Table1, aes(x=10^H4,y=10^H5, colour = "blabla")) + 
    geom_line(size=1) + coord_cartesian(xlim=c(100,1000000000))+ 
coord_cartesian(ylim=c(0.000000000001,1)) + xlab("blabla")+ 
ylab("blabla") + ggtitle("blabla")+ 
scale_y_log10(breaks=c(0.000000000001, 0.000000001, 0.000001, 0.001) 
, labels = trans_format("log10", math_format(10^.x)))+ 
scale_x_log10(breaks=c(100,1000,10000,100000,1000000,10000000,100000000,1000000000) 
, labels = trans_format("log10", math_format(10^.x))) + 
    geom_line(data=Table1,aes(10^H4,10^H6, colour = "blabla1"))+ 
    scale_color_manual("", values =c("blabla"="blue", "blabla1" = "red") 
, labels=c("blabla","blabla1"))+ 
geom_vline(xintercept=10^ f1(0)) # adding the verical line 

Données:

structure(list(H4 = c(2, 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 
2.9, 3, 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4, 4.1, 
4.2, 4.3, 4.4, 4.5, 4.6, 4.7, 4.8, 4.9, 5, 5.1, 5.2, 5.3, 5.4, 
5.5, 5.6, 5.7, 5.8, 5.9, 6, 6.1, 6.2, 6.3, 6.4, 6.5, 6.6, 6.7, 
6.8, 6.9, 7, 7.1, 7.2, 7.3, 7.4, 7.5, 7.6, 7.7, 7.8, 7.9, 8, 
8.1, 8.2, 8.3, 8.4, 8.5, 8.6, 8.7, 8.8, 8.9, 9), H5 = c(-8.979, 
-8.927, -8.877, -8.829, -8.782, -8.736, -8.691, -8.648, -8.606, 
-8.565, -8.525, -8.485, -8.445, -8.405, -8.364, -8.323, -8.282, 
-8.241, -8.2, -8.159, -8.116, -8.064, -7.982, -7.826, -7.592, 
-7.333, -7.101, -6.91, -6.759, -6.64, -6.543, -6.461, -6.387, 
-6.321, -6.264, -6.218, -6.182, -6.155, -6.132, -6.117, -6.111, 
-6.12, -6.23, -6.433, -6.574, -6.664, -6.712, -6.726, -6.722, 
-6.707, -6.704, -6.748, -6.82, -6.864, -6.872, -6.859, -6.83, 
-6.796, -6.757, -6.717, -6.678, -6.636, -6.594, -6.549, -6.502, 
-6.454, -6.402, -6.349, -6.295, -6.238, -6.179), H6 = c(-5.116, 
-5.31, -5.495, -5.669, -5.823, -5.958, -6.075, -6.179, -6.271, 
-6.355, -6.433, -6.506, -6.575, -6.642, -6.707, -6.769, -6.829, 
-6.886, -6.941, -6.993, -7.044, -7.095, -7.144, -7.192, -7.237, 
-7.28, -7.321, -7.36, -7.398, -7.435, -7.47, -7.504, -7.536, 
-7.569, -7.602, -7.64, -7.684, -7.735, -7.789, -7.848, -7.917, 
-8.003, -8.131, -8.312, -8.494, -8.668, -8.823, -8.963, -9.095, 
-9.225, -9.365, -9.531, -9.711, -9.859, -9.965, -10.041, -10.098, 
-10.141, -10.175, -10.203, -10.236, -10.263, -10.285, -10.301, 
-10.314, -10.323, -10.33, -10.335, -10.339, -10.342, -10.344)), .Names = c("H4", 
"H5", "H6"), row.names = c(NA, -71L), class = "data.frame")