How to draw three differents non-linear regression with ggplot2

Question

I am trying to draw three differents non-linear regression with ggplot2 (like I did with graphpad below (dotted line) (because graphpad can't compare non-linear regression between groups):

So far, I drew this graph:

With the following code:

gp <- ggplot(datapoidsmono, aes(x = time, y = weight)) +
  stat_summary(aes(color = group), fun.data="mean_sdl", fun.args = list(mult=1), geom="errorbar", position = "identity", size=0.5, width=0.2) +
  stat_summary(fun.y = "mean", geom = "point", size=3, aes(shape=group,color=group)) + 
  scale_x_discrete(name = "Days after injection") +
  scale_y_continuous(name = "Weight (g)", limits=c(0, 4000), breaks = seq(0, 4000,500)) +
  scale_color_manual(values=c("green", "blue", "red"), name="Treatment", labels=c("A","B","C")) +
  scale_shape_manual(values=c(15,16,17), name  ="Treatment", labels=c("A", "B", "C")) +
  ggtitle("Weight variation over time") + theme(plot.title = element_text(hjust = 0.5)) +
  theme(legend.position = "right") + 
  theme(legend.background = element_rect(size=0.5, linetype="solid", color ="black", fill="white")) +
  theme(axis.line.x = element_line(size = 0.5, color = "black"),axis.text.x = element_text(color="black", size = 12),axis.line.y = element_line(size = 0.5, color = "black"),axis.text.y = element_text(color="black", size = 12),axis.title = element_text(size =15, face="bold"),plot.title = element_text(size =20, face = "bold"),panel.grid.major = element_line(color = "#F1F1F1"),panel.grid.minor = element_blank(), panel.background = element_blank())

I can't figure out how to draw a non-linear regression for each groups.

The following code did not return any drawn line (no error either):

ggplot(datapoidsmono, aes(time, weight, color = group)) +
  geom_point() +
  stat_smooth(method = "lm", se=FALSE)

Nor did this one (found here):

ggplot(datapoidsmono, aes(x = time, y = weight, colour=group)) +
  stat_smooth(method = 'nls', formula = 'y~a*exp(b*x)') +
  stat_smooth(color = 1, method = 'nls', formula = 'y~a*exp(b*x)') +
  geom_point(aes(fill=group))

Any idea or clue would be useful to continue! Thanks

---

Update

As suggested by @PoGibas, I added "group=group" in aes inside first line which worked pefectly to draw the lines!

I tried mulltiple solution to get the perfect fit:

gp + ggplot(aes(group=group))
  stat_smooth(method = "lm", formula = y ~ x, size = 1, se = FALSE,colour = "black") + 
  stat_smooth(method = "lm", formula = y ~ x + I(x^2),size = 1, se = FALSE, colour = "blue") + 
  stat_smooth(method = "loess", formula = y ~ x, size = 1, se = FALSE, colour = "red") + 
  stat_smooth(method = "gam", formula = y ~ s(x), size = 1, se = FALSE, colour = "green") + 
  stat_smooth(method = "gam", formula = y ~ s(x, k = 3), size = 1, se = FALSE, colour = "violet") +
  stat_smooth(method = "auto", se=F, colour = "yellow")

But I figured that simply gp + stat_smooth() did perfectly the job (the LOESS method is used).

Now I am trying to change aspect (to a dotted line) and color of the fit...

I tryed gp + stat_smooth(se=F, aes(fill = group)) but now I have another legend box and my lines are always with the same color...

I also tryed to add linetype=group in the aes, but when I use scale_linetype_manual(values=c("dotted", "dotted", "dotted")), every line is dotted (included errorbar)

The complete code is:

ggplot(datapoidsmono, aes(x = time, y = weight, group=group, linetype=group)) +
  stat_summary(aes(color = group), fun.data="mean_sdl", fun.args = list(mult=1), geom="errorbar", position = "identity", size=0.5, width=0.2) +
  stat_summary(fun.y = "mean", geom = "point", size=3, aes(shape=group,color=group)) + 
  scale_x_discrete(name = "Days after injection") +
  scale_y_continuous(name = "Weight (g)", limits=c(0, 4000), breaks = seq(0, 4000,500)) +
  scale_color_manual(values=c("green", "blue", "red"), name="Treatment", labels=c("A","B","C")) +
  scale_shape_manual(values=c(15,16,17), name  ="Treatment", labels=c("A", "B", "C")) +
  ggtitle("Weight variation over time") + theme(plot.title = element_text(hjust = 0.5)) +
  theme(legend.position = "right") + 
  theme(legend.background = element_rect(size=0.5, linetype="solid", color ="black", fill="white")) +
  theme(axis.line.x = element_line(size = 0.5, color = "black"),axis.text.x = element_text(color="black", size = 12),axis.line.y = element_line(size = 0.5, color = "black"),axis.text.y = element_text(color="black", size = 12),axis.title = element_text(size =15, face="bold"),plot.title = element_text(size =20, face = "bold"),panel.grid.major = element_line(color = "#F1F1F1"),panel.grid.minor = element_blank(), panel.background = element_blank()) +
  stat_smooth(se=F, aes(fill = group)) +
  scale_linetype_manual(values=c("dotted", "dotted", "dotted"))

Answer 1

Thanks to @PoGibas and this post, I added group=group, color=group in the aes of ggplot and it gave me a good result.

ggplot(datapoidsmono, aes(x = time, y = weight, group=group, color=group)) +
  stat_summary(aes(color = group), fun.data="mean_sdl", fun.args = list(mult=1), geom="errorbar", position = "identity", size=0.5, width=0.2) +
  stat_summary(fun.y = "mean", geom = "point", size=3, aes(shape=group,color=group)) + 
  scale_x_discrete(name = "Days after injection") +
  scale_y_continuous(name = "Weight (g)", limits=c(0, 4000), breaks = seq(0, 4000,500)) +
  scale_color_manual(values=c("green", "blue", "red"), name="Treatment", labels=c("A","B","C")) +
  scale_shape_manual(values=c(15,16,17), name  ="Treatment", labels=c("A", "B", "C")) +
  ggtitle("Weight variation over time") + theme(plot.title = element_text(hjust = 0.5)) +
  theme(legend.position = "right") + 
  theme(legend.background = element_rect(size=0.5, linetype="solid", color ="black", fill="white")) +
  theme(axis.line.x = element_line(size = 0.5, color = "black"),axis.text.x = element_text(color="black", size = 12),axis.line.y = element_line(size = 0.5, color = "black"),axis.text.y = element_text(color="black", size = 12),axis.title = element_text(size =15, face="bold"),plot.title = element_text(size =20, face = "bold"),panel.grid.major = element_line(color = "#F1F1F1"),panel.grid.minor = element_blank(), panel.background = element_blank()) +
  stat_smooth(se=F, linetype="dotted")

Here is the final graph:

NB: the fit proposed by graphpad (see first graph) is more stat_smooth(method = "lm", formula = y ~ x + I(x^2),size = 1, se = FALSE) than the one I finally chose (LOESS)