Estefani Gaytan Nunez

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# Based on http://www.sthda.com/english/wiki/ggplot2-line-plot-quick-start-guide-r-software-and-data-visualization
library(ggplot2)
#library(ggpubr)
#library(cowplot)
######### BEST MODELS ##########
# Run1
# Todas las condiciones
dfa <- data.frame(Measure=rep(c("Precision", "Recall", "F1-score"), each=15),
Strategy=rep(c(
"Agit",
"Gversion",
"Substrain",
"Vess",
"OD",
"Anti",
"Supp",
"Air",
"Gtype",
"Med",
"Temp",
"Technique",
"Phase",
"pH",
"Strain"
),3),
Score=c(
0,
0,
0,
0,
1,
1,
0.883,
0.92,
0.905,
0.852,
0.818,
0.88,
1,
1,
1,
0,
0,
0,
0,
0.405,
0.444,
0.669,
0.742,
0.811,
0.912,
1,
1,
0.947,
1,
1,
0,
0,
0,
0,
0.577,
0.615,
0.762,
0.821,
0.856,
0.881,
0.9,
0.936,
0.973,
1,
1
))
# Solo condiciones con F1-score > 0
# Run 1
df <- data.frame(Measure=rep(c("Precision", "Recall", "F1-score"), each=11),
Strategy=rep(c(
"OD",
"Anti",
"Supp",
"Air",
"Gtype",
"Med",
"Temp",
"Technique",
"Phase",
"pH",
"Strain"
),3),
Score=c(
1,
1,
0.883,
0.92,
0.905,
0.852,
0.818,
0.88,
1,
1,
1,
0.405,
0.444,
0.669,
0.742,
0.811,
0.912,
1,
1,
0.947,
1,
1,
0.577,
0.615,
0.762,
0.821,
0.856,
0.881,
0.9,
0.936,
0.973,
1,
1
))
head(df)
pa<-ggplot(df, aes(x=Strategy, y=Score, group=Measure)) +
geom_line(aes(color=Measure))+
geom_point(aes(color=Measure))+
scale_color_manual(values=c("#999999", "#E69F00", "#56B4E9"))+
#scale_color_manual(values=c("#e6194b", "#3cb44b", "#0082c8"))+
#geom_text(aes(label = Score))+
labs(title="Scores by condition (Best model, Run1)",x="Condition", y = "Score")+
theme(
legend.position="top",
# Centrar título: plot.title = element_text(hjust = 0.5),
axis.line = element_line(colour = "gray"),
panel.background = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank()
)
pa
ggsave(".png")
# Solo condiciones con F1-score > 0
# Run 7
df <- data.frame(Measure=rep(c("Precision", "Recall", "F1-score"), each=11),
Strategy=rep(c(
"Anti",
"OD",
"Supp",
"Air",
"Gtype",
"Temp",
"Med",
"Technique",
"Phase",
"pH",
"Strain"
),3),
Score=c(
0.571,
1,
0.886,
0.939,
0.876,
0.818,
0.897,
0.952,
1,
1,
1,
0.444,
0.405,
0.684,
0.742,
0.802,
1,
0.912,
0.909,
0.947,
1,
1,
0.5,
0.577,
0.772,
0.829,
0.837,
0.9,
0.904,
0.93,
0.973,
1,
1
))
head(df)
pa<-ggplot(df, aes(x=Strategy, y=Score, group=Measure)) +
geom_line(aes(color=Measure))+
geom_point(aes(color=Measure))+
scale_color_manual(values=c("#999999", "#E69F00", "#56B4E9"))+
#scale_color_manual(values=c("#e6194b", "#3cb44b", "#0082c8"))+
#geom_text(aes(label = Score))+
labs(title="Scores by condition (Best model, Run7)",x="Condition", y = "Score")+
theme(
legend.position="top",
# Centrar título: plot.title = element_text(hjust = 0.5),
axis.line = element_line(colour = "gray"),
panel.background = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank()
)
pa
ggsave(".png")
# Based on http://www.sthda.com/english/wiki/ggplot2-line-plot-quick-start-guide-r-software-and-data-visualization
library(ggplot2)
#library(ggpubr)
#library(cowplot)
######### BEST MODEL ##########
# Solo condiciones con F1-score > 0
# Run 6 (report_Run6_v11.txt)
df <- data.frame(Measure=rep(c("Precision", "Recall", "F1-score"), each=11),
Strategy=rep(c(
"Air",
"Anti",
"Gtype",
"Med",
"OD",
"pH",
"Phase",
"Supp",
"Technique",
"Temp",
"Vess"
),3),
Score=c(
0.565,
1,
0.889,
1,
1,
1,
0.882,
0.811,
1,
0.923,
1,
0.377,
1,
0.847,
0.943,
0.818,
1,
1,
0.799,
0.913,
0.828,
1,
0.452,
1,
0.867,
0.971,
0.9,
1,
0.938,
0.805,
0.955,
0.873,
1
))
head(df)
pa<-ggplot(df, aes(x=Strategy, y=Score, group=Measure)) +
geom_line(aes(color=Measure))+
geom_point(aes(color=Measure))+
scale_color_manual(values=c("#999999", "#E69F00", "#56B4E9"))+
#scale_color_manual(values=c("#e6194b", "#3cb44b", "#0082c8"))+
#geom_text(aes(label = Score))+
labs(title="Scores by condition (Best model, Run1)",x="Condition", y = "Score")+
theme(
legend.position="top",
# Centrar título: plot.title = element_text(hjust = 0.5),
axis.line = element_line(colour = "gray"),
panel.background = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank()
)
pa
ggsave(".png")
# Based on http://zevross.com/blog/2019/04/02/easy-multi-panel-plots-in-r-using-facet_wrap-and-facet_grid-from-ggplot2/
library(ggplot2)
#library(ggpubr)
#library(cowplot)
organism = 'ECO'
if (organism == 'ECO') {
######### ECO DEVELOPMENT DATASET ##########
# ECO-DEV-WITH-EFFECT-COMBINATION: Combination of strategies with effect in E. coli development dataset
df <- data.frame(Panel=rep(c("Combination of strategies (effect)", "Separated strategies (effect)", "Combination of strategies (no effect)", "Separated strategies (no effect)"), each=12),
Measure=rep(c("Precision", "Recall", "F1-score"), each=4),
Strategy=c(rep(c("D", "D+V", "D+V+At", "D+V+At+Au"),3),rep(c("D", "V", "At", "Au"),3)),
Score=c(
0.78, 0.79, 0.81, 0.81, 0.41, 0.56, 0.63, 0.63, 0.53, 0.65, 0.71, 0.71,
0.78, 0.89, 0.93, 1.00, 0.41, 0.35, 0.13, 0.01, 0.53, 0.50, 0.23, 0.02,
0.82, 0.82, 0.84, 0.84, 0.55, 0.66, 0.72, 0.72, 0.66, 0.73, 0.78, 0.78,
0.82, 0.88, 0.94, 1.00, 0.55, 0.39, 0.20, 0.01, 0.66, 0.54, 0.33, 0.02))
filename = "ECO-dev-multi-panel.png"
title_plot = "E. coli development dataset"
} else if (organism == 'STM')
{
######### STM DEVELOPMENT DATASET ##########
# STM-DEV-WITH-EFFECT-COMBINATION: Combination of strategies with effect in Salmonella evaluation dataset
df <- data.frame(Panel=rep(c("Combination of strategies (effect)", "Separated strategies (effect)", "Combination of strategies (no effect)", "Separated strategies (no effect)"), each=12),
Measure=rep(c("Precision", "Recall", "F1-score"), each=4),
Strategy=c(rep(c("D", "D+V", "D+V+At", "D+V+At+Au"),3),rep(c("D", "V", "At", "Au"),3)),
Score=c(
0.78, 0.77, 0.76, 0.76, 0.33, 0.49, 0.54, 0.54, 0.47, 0.60, 0.63, 0.63,
0.78, 0.81, 0.70, 0.88, 0.33, 0.33, 0.10, 0.01, 0.47, 0.47, 0.18, 0.02,
0.84, 0.82, 0.81, 0.81, 0.47, 0.59, 0.65, 0.65, 0.60, 0.68, 0.72, 0.72,
0.84, 0.84, 0.77, 0.86, 0.47, 0.40, 0.17, 0.01, 0.60, 0.55, 0.27, 0.02))
filename = "STM-dev-multi-panel.png"
title_plot = "Salmonella evaluation dataset"
}
head(df)
pa<-ggplot(df, aes(x=Strategy, y=Score, group=Measure)) +
geom_line(aes(color=Measure))+
geom_point(aes(color=Measure))+
scale_color_manual(values=c("#999999", "#E69F00", "#56B4E9"))+
#scale_color_manual(values=c("#e6194b", "#3cb44b", "#0082c8"))+
geom_text(aes(label = Score))+
labs(title=title_plot,x="Strategies", y = "Score")+
#theme_classic()+
theme(
legend.position="top",
# Centrar título: plot.title = element_text(hjust = 0.5),
axis.line = element_line(colour = "gray"),
panel.background = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
)+
facet_wrap(~Panel, scale="free")
ggsave(filename)
Run1 Run2 Run3 Run4 Run5 Run6 Run7 Run8 Run9
CV 0.9947569260999198 0.8753659172231524 0.871758460762884 0.8832373623657991 0.8736123942774514 0.8826022112505095 0.8772702934120828 0.8742694109779188 0.9916378145389343
f1-score 1.000 0.796 0.762 0.797 0.770 0.802 0.788 0.809 0.995
precision 1.000 0.834 0.795 0.837 0.777 0.815 0.803 0.856 1.000
recall 1.000 0.769 0.749 0.767 0.778 0.800 0.783 0.772 0.991
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