How to change the inside color (fill) of a subset of points with the same shape based on a second variable in ggplot2?

I had a hard time to find how to change inside color of geom_point in combined regression plot but I couldn't do it using scale_color_manual()

For site F and F1 I want to have same shape and same outside color but the inside of "F" blanck and inside of "F1" grey

Here is my code and plot

mydata<-read.csv(choose.files(),header=T)
ggplot(mydata,aes(y=density,x=Do, color=color, shape=color,group=site))+geom_point(size=3.5)+
  stat_smooth(method="lm",se=FALSE)+
  scale_shape_manual(values=seq(0,8))+
  scale_y_log10()+
  scale_x_log10()+
  labs(x = "Do", y = bquote('density'~(No.m^-3)))+
  theme_classic()+
  theme(aspect.ratio=1)+
  theme(axis.title.x = element_text(color = 'black',face = 'bold',size = 18, hjust = 0.5))+
  theme(axis.text = font)+
  theme(axis.title.y = element_text(color = 'black',face = 'bold',size=25, hjust = 0.5))+theme(legend.title = element_text(size=8, color = "white"),legend.position=c(0.17, 0.20),

enter image description here

mydata

     site     Do      density     color
1     A  15.32500000 14.6254359     A
2     A   3.46153846  2.5634207     A
3     A   1.37692308 54.5375387     A
4     A   0.52115385 44.4123777     A
5     B   9.71431056  5.4299784     B
6     B   7.60803311  2.9582927     B
7     B   6.61874506  1.3994870     B
8     B   5.38889098  2.1169919     B
9     C  18.95522388  0.6911765     C
10    C  12.23880597  1.2352941     C
11    C   7.91044776  1.1029412     C
12    C   4.02985075  1.0441176     C
13    C   3.43283582  0.7500000     C
14    D  19.85892857  5.7023070     D
15    D  15.21785714  3.2076197     D
16    D   8.00357143  2.3692545     D
17    D   7.67142857  3.0929227     D
18    D   5.75357143  3.8173552     D
19    E  96.26288660  5.5576024     E
20    E 118.41752580  4.3844430     E
21    E  88.97938144  4.3557405     E
22    E  33.16752577  6.1140918     E
23    E   8.27164948  4.8505888     E
24    F  23.54920101  2.7593361     F
25    F  20.52144659  2.3236515     F
26    F  15.97981497  3.0497925     F
27    F  56.09756097  5.6639004     F
28    F  37.93103448  6.2448133     F
29    F   2.80908326  5.5186722     F
30    F   5.53406223 11.0373444     F
31    F   4.85281750  5.2282158     F
32    F   9.92430614  1.8879668     F
33    F   0.36809306  5.6639004     F
34    F   2.73338940  1.8879668     F
35    F   3.94449117  6.3900415     F
36    F   1.59798150  3.9211618     F
37    F   4.39865433  2.6141079     F
38    F   1.21951220 33.5477178     F
39    F  40.84051724  4.3388430     F
40    F  36.96120690  2.4586777     F
41    F  35.02155172  3.3264463     F
42    F  44.71982759  0.8677686     F
43    F  52.47844828  0.8677686     F
44    F   4.41379310  2.0247934     F
45    F   1.45358090  7.2314050     F
46    F   0.25615763 17.6446281     F
47    F   5.08222812  1.1570248     F
48    F   0.25615763 30.8057851     F
49    F   3.26790451  5.7851240     F
50    F   3.84084881  4.4834711     F
51    F   2.02652520  8.8223140     F
52    F   5.17771883  2.0247934     F
53    F   0.05941645 12.5826446     F
54   F1  68.20857863  2.7593361     F
55   F1  64.42388562  2.3236515     F
56   F1  72.91645498  3.3402490     F
57   F1  60.63919260  2.1784232     F
58   F1  59.12531539  3.1950207     F
59   F1  56.09756097  4.2116183     F
60   F1  51.55592935  3.7759336     F
61   F1  50.04205214  2.4688797     F
62   F1  49.28511354 11.0373444     F
63   F1  68.96551724  0.8677686     F
64   F1  76.79352531  0.5785124     F
65   F1  79.59555352  2.8925620     F
66   F1  55.38793103  0.8677686     F
67   F1  51.50862069  1.3016529     F
68   F1  53.44827586  5.9297521     F
69   F1  49.56896552  1.1570248     F
70   F1  43.75000000  0.7231405     F
71   F1  44.71982759  7.9545455     F
72    G  31.69856459  2.0000000     G
73    G  61.60287081  4.0000000     G
74    G  53.22966507  8.0000000     G
75    G   8.97129187 12.0000000     G
76    G  10.16746411  6.0000000     G
77    G   9.56937799  5.0000000     G
78    G   8.97129187  5.0000000     G

Any help would be appreciated

Solution

One approach is to pre-calculate the color you want to apply ahead of time with mutate and case_when. This saves us from having to manually define each color. TRUE ~ "white" just makes everything else white.

Then, crucially, you must insure the points you want to fill have a shape that is compatible with a fill, specifically shapes 21, 22, 23, 24, or 25. You can insure this by manually defining them with scale_shape_manual. Finally, use scale_fill_manual to define the colors.

If we want to set up the legend, we can define the labels in scale_shape_manual. Then we can call guides to override the shapes to ones that are compatible with fill.

mydata %>%
  mutate(fill.col = case_when(site == "F" ~ "black",
                              site == "F1" ~ "gray",
                              TRUE ~ "white")) %>%
ggplot(aes(y=density,x=Do, color=color, shape=color, group=site, fill = fill.col)) +
  geom_point(size=3.5)+stat_smooth(method="lm",se=FALSE) +
  scale_shape_manual(values = c(A = 3, B = 4, C = 21, D = 22, E = 23, F = 24, F1 = 25, G = 8)) +
  scale_fill_manual(values = c(black = "black",gray = "gray",white = "white"),
                    labels = c(black = "F", gray = "F1", white = "Other"))+
  scale_y_log10() + scale_x_log10()+
  labs(x = "Do", y = bquote('density'~(No.m^-3))) +
  theme_classic() +
  theme(aspect.ratio=1,
        axis.title.x = element_text(color = 'black',face = 'bold',size = 18, hjust = 0.5),
        axis.title.y = element_text(color = 'black',face = 'bold',size=25, hjust = 0.5),
        legend.title = element_text(size=8, color = "white"),
        legend.position=c(0.17, 0.20),
        legend.text = element_text(color = "black",face = 'bold', size=14)) +
  guides(fill = guide_legend(override.aes = list(shape = c(24,24,21),
                                                 linetype = NA)))