Priloha B - Rkod
#Mali

library(tidyverse)
library(lubridate)
library(dplyr)
library(STAT)
library(tibble)
library(reactable)
library(sparkline)
library(ggpubr)
library(ggmap)
library(sf)
library(raster)
library(markdown)
library(pivottabler)
library(ggpubr)
library(plotly)

#převedení názvu stáhnutého souboru na jednodušší
Mali1<-X2015_01_01_2020_06_30_Burkina_Faso_Mali_Niger

#Renaming type of events do ČJ
Mali1<-Mali1%>%
  mutate(event_type = dplyr::recode(event_type, Battles="Boje", `Explosions/Remote violence`="Exploze", `Protests`="Protesty", `Riots`="Výtržnosti", `Strategic developments`="Str. vývoj", `Violence against civilians`="Násilí proti civ."))

#All regions - Mali, BF, Niger

#Geoprecision - Graf 1
Mali1%>%
  ggplot(aes(geo_precision, group=country)) +
  geom_bar(aes(y=..prop..), stat="count",  alpha = 0.8)+
  scale_y_continuous(labels=scales::percent) +
  ylab("Relativní četnost") +
  xlab("Stupeň přesnosti geolokace")+
  facet_grid(country ~ event_type)+
  theme_minimal()+
  labs(caption="Zdroj dat: ACLED,	https://www.acleddata.com")

#počty obětí a počty událostí

#Graf 2 oběti násilných událostí
Mali1%>%
  ggplot(aes(year, fatalities)) +
  geom_col(aes(), alpha = 0.8)+
  facet_grid(country ~ event_type)+
  scale_color_manual(values = c(Battles = "RED", `Explosions/Remote violence` = "PURPLE", Protests = "BLUE", Riots = "GREEN", `Strategic developments` = "BROWN", `Violence against civilians` = "BLACK"))+
  theme_minimal()+
  labs(caption="Zdroj dat: ACLED,	https://www.acleddata.com")+
  ylab("Oběti") +
  xlab("Rok")

Mali1%>%
  ggplot(aes(year)) +
  geom_bar(aes(), alpha = 0.8)+
  facet_grid(country ~ event_type)+
  scale_color_manual(values = c(Battles = "RED", `Explosions/Remote violence` = "PURPLE", Protests = "BLUE", Riots = "GREEN", `Strategic developments` = "BROWN", `Violence against civilians` = "BLACK"))+
  theme_minimal()+
  ggtitle("Počet násilných událostí Mali, Burkina, Niger")

#Graf 3 Regiony s nejv. poctem obeti
Mali1%>%filter(event_type%in%c("Boje", "Exploze", "Násilí proti civ."), admin1%in%c("Diffa", "Tillaberi", "Sahel", "Est", "Nord", "Centre-Nord", "Boucle du Mouhoun", "Gao", "Kidal", "Mopti", "Segou", "Tombouctou"))%>%
  ggplot(aes(year, fatalities, group=event_type)) +
  geom_col(aes(fill=event_type), alpha = 0.8)+
  facet_wrap(country ~ admin1, as.table=T)+
  scale_fill_manual(values = c(Boje = "DARKBLUE", `Exploze` = "GRAY", `Násilí proti civ.` = "BLACK"))+
  theme_minimal()+
  labs(caption="Zdroj dat: ACLED,	https://www.acleddata.com")+
  ylab("Oběti") +
  xlab("Rok")+
  labs(fill = "Typ události")
 

Mali1%>%
  ggplot(aes(event_type, fill=factor(geo_precision)))+
  geom_bar(position="fill")+
  geom_text(aes(label=scales::percent(..count../sum(..count..))),
            stat='count',position=position_fill(vjust=0.5))

Mali1%>%
  ggplot(aes(event_type, fill=factor(time_precision)))+
  geom_bar(position="fill")+
  geom_text(aes(label=scales::percent(..count../sum(..count..))),
            stat='count',position=position_fill(vjust=0.5))

#Mapa1 / nasilne udalosti 2015/2020 vyvoj v case
ggplot(MBFN.map, aes(x=long, y=lat))+
  geom_polygon(aes(group=group, fill=region), col="BLACK", fill="FALSE", alpha =0.5)+
  geom_point(aes(longitude, latitude, size=fatalities, col=event_date), alpha=0.8, data = Mali1)+
  coord_cartesian(xlim = c(-13, 16), ylim = c(9, 25))+
  facet_wrap(.~event_type, ncol = 3)+
  theme_minimal()+
  labs(caption="Zdroj dat: ACLED,	https://www.acleddata.com", size="Oběti", col="Datum")

ggplot(MBFN.map, aes(x=long, y=lat))+
  geom_polygon(aes(group=group, fill=region), col="BLACK", fill="FALSE", alpha =0.5)+
  geom_density2d(aes(longitude, latitude, col=event_type), alpha=1, data = Mali1)+
  coord_cartesian(xlim = c(-13, 16), ylim = c(9, 25))+
  facet_wrap(.~year, ncol = 3)+
  theme_minimal()+
  ggtitle("Násilné události, 2015-2020")

#pokud jste převedli názvy kategorií eventů do čj, zadejte české názvy (boje, exploze atd....)
Mali1BC<-Mali1%>%subset(event_type%in%c("Battles", "Violence against civilians"))

#Akteri bitev, graf 4
Mali1BC%>%filter(event_type%in%"Battles", interaction%in%c("12", "13", "22", "23", "24", "28", "44"))%>%
  ggplot(aes(year, fatalities))+
  geom_col()+
  facet_grid(country~interaction)+
  theme_minimal()+
  labs(caption="Zdroj dat: ACLED,	https://www.acleddata.com")+
  ylab("Oběti") +
  xlab("Rok")
  
#"Aktéři násilí proti civilistům", Graf 5
Mali1BC%>%filter(event_type%in%"Violence against civilians", interaction%in%c("17", "27", "37", "47", "78"))%>%
  ggplot(aes(year, fatalities))+
  geom_col()+
  facet_grid(country~interaction)+
  theme_minimal()+
  labs(caption="Zdroj dat: ACLED,	https://www.acleddata.com")+
  ylab("Oběti") +
  xlab("Rok")



#Mopti
Mopti<-Mali1%>%subset(admin1=="Mopti")
MoptiBV<-Mopti%>%subset(event_type%in%c("Boje", "Násilí proti civ.", "Exploze"))

Mopti20<-MoptiBV%>%subset(event_date > "2019-06-30")

#nasledujici grafy jsou doplnkove, nejsou v clanku
Mopti20%>%group_by(month=floor_date(event_date, "month"))%>%
  ggplot(aes(month, fatalities)) +
  geom_col(aes(), alpha = 0.8)+
  facet_grid(event_type ~ admin2)+
  scale_color_manual(values = c(Battles = "RED", `Explosions/Remote violence` = "PURPLE", Protests = "BLUE", Riots = "GREEN", `Strategic developments` = "BROWN", `Violence against civilians` = "BLACK"))+
  theme_minimal()+
  ggtitle("Oběti násilných událostí Mopti 1.1-30.6 2020")+
  theme(axis.text.x = element_text(angle=45, hjust = 1))

Mopti20%>%group_by(month=floor_date(event_date, "month"))%>%
  ggplot(aes(month)) +
  geom_bar(aes(fill=actor1), alpha = 0.8)+
  facet_grid(event_type ~ admin2)+
  scale_color_manual(values = c(Battles = "RED", `Explosions/Remote violence` = "PURPLE", Protests = "BLUE", Riots = "GREEN", `Strategic developments` = "BROWN", `Violence against civilians` = "BLACK"))+
  theme_minimal()+
  ggtitle("Počet násilných událostí Mali, Burkina, Niger")


#Graf 7 Nepřátelské interakce v bojích, srovnání 2. polovina 2019 a 1. polovina 2020
Mopti20%>%filter(event_type%in%"Battles", fatalities>1)%>%
  ggplot(aes(actor2, actor1))+
  geom_count(aes(shape=as.factor(year)), stroke=1, alpha=0.7)+
  scale_shape_manual(values=c("2019"=0, "2020"=1))+ 
  scale_color_manual(values = c("2019" = "BLACK", "2020" = "BLACK"))+
  scale_size(range =c(2, 11))+
  theme_minimal()+
  theme(axis.text.x = element_text(angle=45, hjust = 1))+
  scale_x_discrete(label = function(x) stringr::str_trunc(x, 30))+
  scale_y_discrete(label = function(y) stringr::str_trunc(y, 30))+
  labs(shape="Rok")+
  xlab("aktér2")+
  ylab("aktér1")


#Spoluprace akteru, neni v clanku

Mopti20%>%filter(event_type%in%"Battles")%>%
  ggplot(aes(assoc_actor_1, actor1))+
  geom_count(aes(shape=as.factor(year)), alpha=0.5)+
  scale_size_area(max_size = 10)+
  theme_minimal()+
  ggtitle("Spolupracující aktéři v bojích - Mopti 2020")+
  theme(axis.text.x = element_text(angle=45, hjust = 1))+
  theme(axis.text.x = element_text(angle=45, hjust = 1))+
  scale_x_discrete(label = function(x) stringr::str_trunc(x, 30))+
  scale_y_discrete(label = function(y) stringr::str_trunc(y, 30))


#mapy Mopti
#na4ten9 shapefilu pro admin jednotky Mali (ke stazeni https://data.humdata.org/dataset/administrative-boundaries-cod-mli)
Mali3all<-st_read("C:/Users/Jan/Downloads/mli_admbndl_admALL_1m_dnct_itos_20190802.shp")

#Mapa 2 - Násilné události v Mopti 19-20
Mali3all%>%filter(admLevel%in%c("0","1"))%>%
  ggplot() + 
  geom_sf(color = "black", size=1) + 
  geom_sf(color = "GRAY", size=0.8, data=Mali3all%>%filter(admLevel%in%"2")) +
  geom_point(aes(longitude, latitude, size=fatalities, col=event_date), alpha=0.6, data = Mopti20)+
  geom_point(aes(-4.2, 14.5), size=2)+
  scale_size(range = c(2, 12))+
  facet_wrap(.~(event_type), ncol = 1)+
  coord_sf(xlim = c(-6, 0), ylim = c(13, 16), expand = T)+
  theme_minimal()+
  labs(caption="Zdroj dat: ACLED,	https://www.acleddata.com", col="Datum", size="Oběti")
  

#vypocet vzdalenosti od mesta Mopti (pomoci package(geosphere))
Mopti20<-Mopti20%>% rowwise() %>% 
  mutate(D_Mopti = (distm(cbind(longitude, latitude), c(-4.2, 14.5), distGeo))/1000)



# Graf 6, Vzdalenost boju od Mopti
Mopti20%>%filter(event_type%in%c("Battles", "Explosions/Remote violence"), interaction%in%c("12", "13", "28"))%>%
  ggplot(aes(D_Mopti, actor1))+
  geom_boxplot()+
  geom_point(aes(size=fatalities, shape=event_type, col=as.factor(geo_precision)), position="jitter", alpha=0.8)+
  scale_color_manual(values = c("1"="BLACK", "2"="GRAY32", "3"="BLUE"))+
  scale_y_discrete(label = function(y) stringr::str_trunc(y, 30))+
  theme_minimal()+
  labs(caption="Zdroj dat: ACLED,	https://www.acleddata.com")+
  ylab("Aktér1") +
  xlab("Vzd Mopti (Km)")+
  labs(col="Přesnost geolokace", shape="Typ události", size="Oběti")



#Pivoty
pt1<-qpvt(Mali1, rows=c("event_type", "country"), columns="year", summariseExpression="n()")
pt1$renderPivot()

#vztvoření reaktivní tabulky největších bojů - příloha C
Mali1B<-Mali1%>%subset(event_type%in%"Battles")
Mali1B<-Mali1B%>%subset(fatalities>19)
Mali1B<-Mali1B%>%subset(interaction%in%"12")
Mali1B<-Mali1B%>%subset(country%in%"Mali")
reactable(Mali1B, groupBy = c("year", "admin1"), columns=list(data_id = colDef(name = "id", show = F), iso = colDef(name = "iso", show = F), event_id_cnty = colDef(name = "id2", show = F), event_id_no_cnty = colDef(name = "id3", show = FALSE), event_date = colDef(name = "Date", filterable = FALSE, width = 60), year = colDef(name = "year", show=T, filterable=T), time_precision = colDef(name = "tp", show = FALSE), event_type = colDef(name = "Event_t", show=F, filterable = F), sub_event_type = colDef(name = "Subevent", show = F), actor1 = colDef(name = "actor1", filterable = T), assoc_actor_1 = colDef(name = "Assoc_a1", show = T), inter1 = colDef(name = "inter1", show = F), actor2 = colDef(name = "actor2", show = T, filterable = T), assoc_actor_2 = colDef(name = "assoc_a2", show = T), inter2 = colDef(name = "inter2", show = F), interaction = colDef(name = "interact", show = F, filterable = T, width = 70), region = colDef(name = "Region", show = F), country = colDef(name = "Country", show = T), admin1 = colDef(name = "Admin1", filterable = T), admin2 = colDef(name= "admin2", filterable = T), admin3 = colDef(name = "admin3", show =  F), location = colDef(name = "location", width = 70), latitude = colDef(name = "lat", show = F), longitude = colDef(name = "long", show = F), geo_precision = colDef(name = "geo_p", show = F), source = colDef(name = "source", show = F), source_scale = colDef(name = "source_sc", show = F), notes = colDef(name = "notes", filterable = F,  show = T, width = 135), fatalities = colDef(name = "Fatal", filterable = F, aggregate = "sum", width = 65), timestamp = colDef(name = "tmst", show = F), iso3 = colDef(name = "iso3", show = F)), resizable = TRUE, filterable = TRUE, bordered = TRUE, showPageSizeOptions = TRUE, highlight = TRUE, striped = TRUE, wrap = T)