.Rapp.history

dim(legodata_ranks)
class(legodata_ranks)
legodata_ranks[1:10]
range(legodata_ranks)
range(scale(legodata_ranks))
get_rank <- function(x,type="lb")#
{#
	if(type=="lb") return(rank(x))#
	if(type=="lg") return(rank(-1*x))#
}#
range01 <- function(x){(x-min(x))/(max(x)-min(x))}#
legodata_spl <- as.list(legodata)[2:11]#
legodata_ranks <- range01(apply(mapply(get_rank,legodata_spl,type=c("lb","lg","lb","lb","lb","lg","lb","lg","lg","lg")),1,sum))
range(legodata_ranks)
hist(legodata_ranks)
library(readr)#
#
## Read in Handles#
legodata <- data.frame(Handle=read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/gr15_contributions/20220923-001354_handles.csv")[,1,drop=TRUE])#
#
## Lev Data#
lev_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Levenshtein_scores.csv")#
legodata$LevDistance <- lev_df$Distance_Min[match(legodata$Handle,lev_df$Handle)]#
legodata$LevMatchCount <- lev_df$Distance_Min_is1_Count[match(legodata$Handle,lev_df$Handle)]#
#
## Intersectionality#
inter_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Intersectionality.csv")#
legodata$IntersectionalityScore <- inter_df$Score[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOAPActive <- inter_df$poap[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOAPCount <- inter_df$poap_count[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensActive <- inter_df$lens[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensFollowers <- inter_df$lens_followers[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensFollowing <- inter_df$lens_following[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOHActive <- inter_df$poh[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityNFTActive <- inter_df$nft[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityNFTCount <- inter_df$nft_count[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalitySnapshotActive <- inter_df$snapshot[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalitySnapshotVotes <- inter_df$snapshot_votes[match(legodata$Handle,inter_df$Handle)]#
#
## DDNA#
ddna_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Jaccard_handles_scores.csv")#
legodata$DDNADistance <- round(ddna_df$Distance_Min[match(legodata$Handle,ddna_df$Handle)],2)#
#
## APU#
apu_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/APU.csv")#
legodata$APUScore <- round(apu_df$Score[match(legodata$Handle,apu_df$Handle)],2)#
#
## SAD#
sad_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/SAD.csv")#
legodata$SADScore <- round(sad_df$Score[match(legodata$Handle,sad_df$Handle)],2)#
#
## GrantOwner#
owner_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/grants_owners.csv")#
legodata$GrantOwner <- ifelse(legodata$Handle %in% owner_df$handle,1,0)#
#
## IPs Shared#
ip_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/IPShared_scores.csv")#
ip_df$Score <- ip_df$IPCount_ProfShared_gt1/ip_df$IPCount#
legodata$IPsSharedRatio <- round(ip_df$Score[match(legodata$Handle,ip_df$Handle)],2)#
legodata$IPsUsedCount <- round(ip_df$IPCount[match(legodata$Handle,ip_df$Handle)],2)#
legodata$IPsSharedCount <- ip_df$IPCount_ProfShared_gt1[match(legodata$Handle,ip_df$Handle)]#
#
## Meta Rank#
get_rank <- function(x,type="lb")#
{#
	if(type=="lb") return(rank(x))#
	if(type=="lg") return(rank(-1*x))#
}#
range01 <- function(x){(x-min(x))/(max(x)-min(x))}#
legodata_spl <- as.list(legodata)[2:11]#
legodata$MetaRank <- range01(apply(mapply(get_rank,legodata_spl,type=c("lb","lg","lb","lb","lb","lg","lb","lg","lg","lg")),1,sum))#
#
## Write Out Data#
write_csv(legodata,"~/Desktop/Gitcoin Sybil LEGOs/data_app/LegoDataFull.csv")
x <- 1:10
ranl(x)
rank(x)
rank(-x)
library(readr)#
#
## Read in Handles#
legodata <- data.frame(Handle=read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/gr15_contributions/20220923-001354_handles.csv")[,1,drop=TRUE])#
#
## Lev Data#
lev_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Levenshtein_scores.csv")#
legodata$LevDistance <- lev_df$Distance_Min[match(legodata$Handle,lev_df$Handle)]#
legodata$LevMatchCount <- lev_df$Distance_Min_is1_Count[match(legodata$Handle,lev_df$Handle)]#
#
## Intersectionality#
inter_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Intersectionality.csv")#
legodata$IntersectionalityScore <- inter_df$Score[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOAPActive <- inter_df$poap[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOAPCount <- inter_df$poap_count[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensActive <- inter_df$lens[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensFollowers <- inter_df$lens_followers[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensFollowing <- inter_df$lens_following[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOHActive <- inter_df$poh[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityNFTActive <- inter_df$nft[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityNFTCount <- inter_df$nft_count[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalitySnapshotActive <- inter_df$snapshot[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalitySnapshotVotes <- inter_df$snapshot_votes[match(legodata$Handle,inter_df$Handle)]#
#
## DDNA#
ddna_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Jaccard_handles_scores.csv")#
legodata$DDNADistance <- round(ddna_df$Distance_Min[match(legodata$Handle,ddna_df$Handle)],2)#
#
## APU#
apu_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/APU.csv")#
legodata$APUScore <- round(apu_df$Score[match(legodata$Handle,apu_df$Handle)],2)#
#
## SAD#
sad_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/SAD.csv")#
legodata$SADScore <- round(sad_df$Score[match(legodata$Handle,sad_df$Handle)],2)#
#
## GrantOwner#
owner_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/grants_owners.csv")#
legodata$GrantOwner <- ifelse(legodata$Handle %in% owner_df$handle,1,0)#
#
## IPs Shared#
ip_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/IPShared_scores.csv")#
ip_df$Score <- ip_df$IPCount_ProfShared_gt1/ip_df$IPCount#
legodata$IPsSharedRatio <- round(ip_df$Score[match(legodata$Handle,ip_df$Handle)],2)#
legodata$IPsUsedCount <- round(ip_df$IPCount[match(legodata$Handle,ip_df$Handle)],2)#
legodata$IPsSharedCount <- ip_df$IPCount_ProfShared_gt1[match(legodata$Handle,ip_df$Handle)]#
#
## Meta Rank#
get_rank <- function(x,type="lb",wt=1)#
{#
	if(type=="lb") return(wt*rank(x,na.last=TRUE))#
	if(type=="lg") return(wt*rank(-1*x,na.last=TRUE))#
}#
get_rank_NAsWorst <- function(x,type="lb",wt=1)#
{#
	if(type=="lb") return(wt*rank(x,na.last=FALSE))#
	if(type=="lg") return(wt*rank(-1*x,na.last=FALSE))#
}#
range01 <- function(x){(x-min(x))/(max(x)-min(x))}#
legodata_spl <- as.list(legodata)[2:11]#
legodata$MetaRank <- range01(apply(mapply(get_rank,legodata_spl,type=c("lb","lg","lb","lb","lb","lg","lb","lg","lg","lg"),wt=rep(1,10)),1,sum))#
legodata$MetaRank_NAsWorst <- range01(apply(mapply(get_rank_NAsWorst,legodata_spl,type=c("lb","lg","lb","lb","lb","lg","lb","lg","lg","lg"),wt=rep(1,10)),1,sum))#
#
# data.frame(Var=names(legodata_spl),RankType=c("lb","lg","lb","lb","lb","lg","lb","lg","lg","lg"))#
#
## Write Out Data#
write_csv(legodata,"~/Desktop/Gitcoin Sybil LEGOs/data_app/LegoDataFull.csv")
library(readr)#
#
## Read in Handles#
legodata <- data.frame(Handle=read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/gr15_contributions/20220923-001354_handles.csv")[,1,drop=TRUE])#
#
## Lev Data#
lev_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Levenshtein_scores.csv")#
legodata$LevDistance <- lev_df$Distance_Min[match(legodata$Handle,lev_df$Handle)]#
legodata$LevMatchCount <- lev_df$Distance_Min_is1_Count[match(legodata$Handle,lev_df$Handle)]#
#
## Intersectionality#
inter_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Intersectionality.csv")#
legodata$IntersectionalityScore <- inter_df$Score[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOAPActive <- inter_df$poap[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOAPCount <- inter_df$poap_count[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensActive <- inter_df$lens[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensFollowers <- inter_df$lens_followers[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensFollowing <- inter_df$lens_following[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOHActive <- inter_df$poh[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityNFTActive <- inter_df$nft[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityNFTCount <- inter_df$nft_count[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalitySnapshotActive <- inter_df$snapshot[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalitySnapshotVotes <- inter_df$snapshot_votes[match(legodata$Handle,inter_df$Handle)]#
#
## DDNA#
ddna_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Jaccard_handles_scores.csv")#
legodata$DDNADistance <- round(ddna_df$Distance_Min[match(legodata$Handle,ddna_df$Handle)],2)#
#
## APU#
apu_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/APU.csv")#
legodata$APUScore <- round(apu_df$Score[match(legodata$Handle,apu_df$Handle)],2)#
#
## SAD#
sad_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/SAD.csv")#
legodata$SADScore <- round(sad_df$Score[match(legodata$Handle,sad_df$Handle)],2)#
#
## GrantOwner#
owner_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/grants_owners.csv")#
legodata$GrantOwner <- ifelse(legodata$Handle %in% owner_df$handle,1,0)#
#
## IPs Shared#
ip_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/IPShared_scores.csv")#
ip_df$Score <- ip_df$IPCount_ProfShared_gt1/ip_df$IPCount#
legodata$IPsSharedRatio <- round(ip_df$Score[match(legodata$Handle,ip_df$Handle)],2)#
legodata$IPsUsedCount <- round(ip_df$IPCount[match(legodata$Handle,ip_df$Handle)],2)#
legodata$IPsSharedCount <- ip_df$IPCount_ProfShared_gt1[match(legodata$Handle,ip_df$Handle)]#
#
## Meta Rank#
get_rank_Loki <- function(x,type="lb",wt=1)#
{#
	if(type=="lb") return(wt*rank(x,na.last=TRUE))#
	if(type=="lg") return(wt*rank(-1*x,na.last=TRUE))#
}#
get_rank_Thor <- function(x,type="lb",wt=1)#
{#
	if(type=="lb") return(wt*rank(x,na.last=FALSE))#
	if(type=="lg") return(wt*rank(-1*x,na.last=FALSE))#
}#
range01 <- function(x){(x-min(x))/(max(x)-min(x))}#
legodata_spl <- as.list(legodata)[2:11]#
legodata$MetaRank_Loki <- range01(apply(mapply(get_rank_Loki,legodata_spl,type=c("lb","lg","lb","lb","lb","lg","lb","lg","lg","lg"),wt=rep(1,10)),1,sum))#
legodata$MetaRank_Thor <- range01(apply(mapply(get_rank_Thor,legodata_spl,type=c("lb","lg","lb","lb","lb","lg","lb","lg","lg","lg"),wt=rep(1,10)),1,sum))#
#
# data.frame(Var=names(legodata_spl),RankType=c("lb","lg","lb","lb","lb","lg","lb","lg","lg","lg"))#
#
## Write Out Data#
write_csv(legodata,"~/Desktop/Gitcoin Sybil LEGOs/data_app/LegoDataFull.csv")
library(RSelenium)#
library(stringr)#
#
## Start Server#
rD <- rsDriver(browser = "chrome",chromever="105.0.5195.52")#
remDr <- rD[["client"]]#
remDr$getStatus()#
#
#############################################################
## Login#
#############################################################
## Go to feast login#
remDr$navigate("https://feast.punjab.gov.in/login.aspx")#
Sys.sleep(5)#
#
## Select Login type#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_ddllogintype"]/option[3]')#
webElem$clickElement()#
Sys.sleep(5)#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_ddlRegion"]/option[2]')#
webElem$clickElement()#
Sys.sleep(5)#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_ddlDist"]/option[21]')#
webElem$clickElement()#
Sys.sleep(5)#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_ddlDepot"]/option[111]')#
webElem$clickElement()#
Sys.sleep(5)#
#
## Fill Password#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_Password"]')#
webElem$clickElement()#
webElem$sendKeysToElement(list("depot@123"))#
Sys.sleep(2)#
## Solve capthca#
# webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_CaptchaImage1"]')#
# webElem$getElementAttribute("src")#
# chars <- tesseract(options = list(tessedit_char_whitelist = toupper(letters)))#
# ocr_data(aa, engine = chars)#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_txtcaptcha"]')#
webElem$clickElement()
library(ggplot2)
update.packages()
library(readr)#
#
## Read in Handles#
legodata <- data.frame(Handle=read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/gr15_contributions/20220923-001354_handles.csv")[,1,drop=TRUE])#
#
## Lev Data#
lev_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Levenshtein_scores.csv")#
legodata$LevDistance <- lev_df$Distance_Min[match(legodata$Handle,lev_df$Handle)]#
legodata$LevMatchCount <- lev_df$Distance_Min_is1_Count[match(legodata$Handle,lev_df$Handle)]#
#
## Intersectionality#
inter_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Intersectionality.csv")#
legodata$IntersectionalityScore <- inter_df$Score[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOAPActive <- inter_df$poap[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOAPCount <- inter_df$poap_count[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensActive <- inter_df$lens[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensFollowers <- inter_df$lens_followers[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensFollowing <- inter_df$lens_following[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOHActive <- inter_df$poh[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityNFTActive <- inter_df$nft[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityNFTCount <- inter_df$nft_count[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalitySnapshotActive <- inter_df$snapshot[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalitySnapshotVotes <- inter_df$snapshot_votes[match(legodata$Handle,inter_df$Handle)]#
#
## DDNA#
ddna_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Jaccard_handles_scores.csv")#
data_mat_amt <- readRDS("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Jaccard_binmat_handles.RDS")
dim(data_mat_amt)
names(data_mat_amt)
class(data_mat_amt)
colnames(data_mat_amt)
data_mat_handles <- data_mat_amt[,!grepl("Amt",colnames(data_mat_amt))]
dim(data_mat_handles)
dim(data_mat_amt)
library(Rfast)
aa <- rowsums(data_mat_handles)
rownames(data_mat_handles)[1:1-]
rownames(data_mat_handles)[1:10]
which(rownames(data_mat_handles)=="yogesh-bansal")
aa[38657]
library(readr)#
library(Rfast)#
#
## Read in Handles#
legodata <- data.frame(Handle=read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/gr15_contributions/20220923-001354_handles.csv")[,1,drop=TRUE])#
#
## Lev Data#
lev_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Levenshtein_scores.csv")#
legodata$LevDistance <- lev_df$Distance_Min[match(legodata$Handle,lev_df$Handle)]#
legodata$LevMatchCount <- lev_df$Distance_Min_is1_Count[match(legodata$Handle,lev_df$Handle)]#
#
## Intersectionality#
inter_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Intersectionality.csv")#
legodata$IntersectionalityScore <- inter_df$Score[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOAPActive <- inter_df$poap[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOAPCount <- inter_df$poap_count[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensActive <- inter_df$lens[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensFollowers <- inter_df$lens_followers[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensFollowing <- inter_df$lens_following[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOHActive <- inter_df$poh[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityNFTActive <- inter_df$nft[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityNFTCount <- inter_df$nft_count[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalitySnapshotActive <- inter_df$snapshot[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalitySnapshotVotes <- inter_df$snapshot_votes[match(legodata$Handle,inter_df$Handle)]#
#
## DDNA#
ddna_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Jaccard_handles_scores.csv")#
data_mat_amt <- readRDS("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Jaccard_binmat_handles.RDS")#
data_mat_handles <- data_mat_amt[,!grepl("Amt",colnames(data_mat_amt))]#
legodata$DDNADistance <- round(ddna_df$Distance_Min[match(legodata$Handle,ddna_df$Handle)],2)#
legodata$DDNAGrantsDonated <- rowsums(data_mat_handles)#
#
## APU#
apu_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/APU.csv")#
legodata$APUScore <- round(apu_df$Score[match(legodata$Handle,apu_df$Handle)],2)#
#
## SAD#
sad_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/SAD.csv")#
legodata$SADScore <- round(sad_df$Score[match(legodata$Handle,sad_df$Handle)],2)#
#
## GrantOwner#
owner_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/grants_owners.csv")#
legodata$GrantOwner <- ifelse(legodata$Handle %in% owner_df$handle,1,0)#
#
## IPs Shared#
ip_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/IPShared_scores.csv")#
ip_df$Score <- ip_df$IPCount_ProfShared_gt1/ip_df$IPCount#
legodata$IPsSharedRatio <- round(ip_df$Score[match(legodata$Handle,ip_df$Handle)],2)#
legodata$IPsUsedCount <- round(ip_df$IPCount[match(legodata$Handle,ip_df$Handle)],2)#
legodata$IPsSharedCount <- ip_df$IPCount_ProfShared_gt1[match(legodata$Handle,ip_df$Handle)]
head(legodata)
dim(data_mat_handles)
aa[1:10]
names(aa)
library(readr)#
library(Rfast)#
#
## Read in Handles#
legodata <- data.frame(Handle=read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/gr15_contributions/20220923-001354_handles.csv")[,1,drop=TRUE])#
#
## Lev Data#
lev_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Levenshtein_scores.csv")#
legodata$LevDistance <- lev_df$Distance_Min[match(legodata$Handle,lev_df$Handle)]#
legodata$LevMatchCount <- lev_df$Distance_Min_is1_Count[match(legodata$Handle,lev_df$Handle)]#
#
## Intersectionality#
inter_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Intersectionality.csv")#
legodata$IntersectionalityScore <- inter_df$Score[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOAPActive <- inter_df$poap[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOAPCount <- inter_df$poap_count[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensActive <- inter_df$lens[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensFollowers <- inter_df$lens_followers[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensFollowing <- inter_df$lens_following[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOHActive <- inter_df$poh[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityNFTActive <- inter_df$nft[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityNFTCount <- inter_df$nft_count[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalitySnapshotActive <- inter_df$snapshot[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalitySnapshotVotes <- inter_df$snapshot_votes[match(legodata$Handle,inter_df$Handle)]#
#
## DDNA#
ddna_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Jaccard_handles_scores.csv")#
data_mat_handles <- readRDS("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Jaccard_binmat_handles.RDS")#
data_mat_handles <- data_mat_handles[,!grepl("Amt",colnames(data_mat_handles))]#
data_sum_handles <- data.frame(Handle = rownames(data_mat_handles),DDNAGrantsDonated=rowsums(data_mat_handles))
head(data_sum_handles)
library(readr)#
library(Rfast)#
#
## Read in Handles#
legodata <- data.frame(Handle=read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/gr15_contributions/20220923-001354_handles.csv")[,1,drop=TRUE])#
#
## Lev Data#
lev_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Levenshtein_scores.csv")#
legodata$LevDistance <- lev_df$Distance_Min[match(legodata$Handle,lev_df$Handle)]#
legodata$LevMatchCount <- lev_df$Distance_Min_is1_Count[match(legodata$Handle,lev_df$Handle)]#
#
## Intersectionality#
inter_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Intersectionality.csv")#
legodata$IntersectionalityScore <- inter_df$Score[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOAPActive <- inter_df$poap[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOAPCount <- inter_df$poap_count[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensActive <- inter_df$lens[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensFollowers <- inter_df$lens_followers[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensFollowing <- inter_df$lens_following[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOHActive <- inter_df$poh[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityNFTActive <- inter_df$nft[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityNFTCount <- inter_df$nft_count[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalitySnapshotActive <- inter_df$snapshot[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalitySnapshotVotes <- inter_df$snapshot_votes[match(legodata$Handle,inter_df$Handle)]#
#
## DDNA#
ddna_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Jaccard_handles_scores.csv")#
data_mat_handles <- readRDS("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Jaccard_binmat_handles.RDS")#
data_mat_handles <- data_mat_handles[,!grepl("Amt",colnames(data_mat_handles))]#
data_sum_handles <- data.frame(Handle = rownames(data_mat_handles),DDNAGrantsDonated=rowsums(data_mat_handles))#
legodata$DDNADistance <- round(ddna_df$Distance_Min[match(legodata$Handle,ddna_df$Handle)],2)#
legodata$DDNAGrantsDonated <- data_sum_handles$DDNAGrantsDonated[match(legodata$Handle,data_sum_handles$Handle)]#
#
## APU#
apu_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/APU.csv")#
legodata$APUScore <- round(apu_df$Score[match(legodata$Handle,apu_df$Handle)],2)#
#
## SAD#
sad_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/SAD.csv")#
legodata$SADScore <- round(sad_df$Score[match(legodata$Handle,sad_df$Handle)],2)#
#
## GrantOwner#
owner_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/grants_owners.csv")#
legodata$GrantOwner <- ifelse(legodata$Handle %in% owner_df$handle,1,0)#
#
## IPs Shared#
ip_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/IPShared_scores.csv")#
ip_df$Score <- ip_df$IPCount_ProfShared_gt1/ip_df$IPCount#
legodata$IPsSharedRatio <- round(ip_df$Score[match(legodata$Handle,ip_df$Handle)],2)#
legodata$IPsUsedCount <- round(ip_df$IPCount[match(legodata$Handle,ip_df$Handle)],2)#
legodata$IPsSharedCount <- ip_df$IPCount_ProfShared_gt1[match(legodata$Handle,ip_df$Handle)]
head(legodata)
library(readr)#
library(Rfast)#
#
## Read in Handles#
legodata <- data.frame(Handle=read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/gr15_contributions/20220923-001354_handles.csv")[,1,drop=TRUE])#
#
## Lev Data#
lev_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Levenshtein_scores.csv")#
legodata$LevDistance <- lev_df$Distance_Min[match(legodata$Handle,lev_df$Handle)]#
legodata$LevMatchCount <- lev_df$Distance_Min_is1_Count[match(legodata$Handle,lev_df$Handle)]#
#
## Intersectionality#
inter_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Intersectionality.csv")#
legodata$IntersectionalityScore <- inter_df$Score[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOAPActive <- inter_df$poap[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOAPCount <- inter_df$poap_count[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensActive <- inter_df$lens[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensFollowers <- inter_df$lens_followers[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensFollowing <- inter_df$lens_following[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOHActive <- inter_df$poh[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityNFTActive <- inter_df$nft[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityNFTCount <- inter_df$nft_count[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalitySnapshotActive <- inter_df$snapshot[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalitySnapshotVotes <- inter_df$snapshot_votes[match(legodata$Handle,inter_df$Handle)]#
#
## DDNA#
ddna_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Jaccard_handles_scores.csv")#
data_mat_handles <- readRDS("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Jaccard_binmat_handles.RDS")#
data_mat_handles <- data_mat_handles[,!grepl("Amt",colnames(data_mat_handles))]#
data_sum_handles <- data.frame(Handle = rownames(data_mat_handles),DDNAGrantsDonated=rowsums(data_mat_handles))#
legodata$DDNADistance <- round(ddna_df$Distance_Min[match(legodata$Handle,ddna_df$Handle)],2)#
legodata$DDNAGrantsDonated <- data_sum_handles$DDNAGrantsDonated[match(legodata$Handle,data_sum_handles$Handle)]#
#
## APU#
apu_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/APU.csv")#
legodata$APUScore <- round(apu_df$Score[match(legodata$Handle,apu_df$Handle)],2)#
#
## SAD#
sad_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/SAD.csv")#
legodata$SADScore <- round(sad_df$Score[match(legodata$Handle,sad_df$Handle)],2)#
#
## GrantOwner#
owner_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/grants_owners.csv")#
legodata$GrantOwner <- ifelse(legodata$Handle %in% owner_df$handle,1,0)#
#
## IPs Shared#
ip_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/IPShared_scores.csv")#
ip_df$Score <- ip_df$IPCount_ProfShared_gt1/ip_df$IPCount#
legodata$IPsSharedRatio <- round(ip_df$Score[match(legodata$Handle,ip_df$Handle)],2)#
legodata$IPsUsedCount <- round(ip_df$IPCount[match(legodata$Handle,ip_df$Handle)],2)#
legodata$IPsSharedCount <- ip_df$IPCount_ProfShared_gt1[match(legodata$Handle,ip_df$Handle)]#
#
## Meta Rank#
get_rank_Loki <- function(x,type="lb",wt=1)#
{#
	if(type=="lb") return(wt*rank(x,na.last=TRUE))#
	if(type=="lg") return(wt*rank(-1*x,na.last=TRUE))#
}#
get_rank_Thor <- function(x,type="lb",wt=1)#
{#
	if(type=="lb") return(wt*rank(x,na.last=FALSE))#
	if(type=="lg") return(wt*rank(-1*x,na.last=FALSE))#
}#
range01 <- function(x){(x-min(x))/(max(x)-min(x))}#
legodata_spl <- as.list(legodata)[2:12]#
legodata$MetaRank_Loki <- range01(apply(mapply(get_rank_Loki,legodata_spl,type=c("lb","lg","lb","lb","lb","lb","lg","lb","lg","lg","lg"),wt=rep(1,11)),1,sum))#
legodata$MetaRank_Thor <- range01(apply(mapply(get_rank_Thor,legodata_spl,type=c("lb","lg","lb","lb","lb","lb","lg","lb","lg","lg","lg"),wt=rep(1,11)),1,sum))#
#
# data.frame(Var=names(legodata_spl),RankType=c("lb","lg","lb","lb","lb","lg","lb","lg","lg","lg"))#
#
## Write Out Data#
write_csv(legodata,"~/Desktop/Gitcoin Sybil LEGOs/data_app/LegoDataFull.csv")
as.dist(matrix(rep(0,100),10,10))
as.dist(matrix(rep(0,100),10,10))+as.dist(matrix(rep(0,100),10,10))
as.dist(matrix(sample(0:1,100,replace=TRUE),10,10))+as.dist(matrix(sample(0:1,100,replace=TRUE),10,10))
as.dist(matrix(sample(0:1,100,replace=TRUE),10,10))->aa
aa
aa<=0
aa>=0
aa==1
as.dist(aa==1)
library(RSelenium)#
library(stringr)#
#
## Start Server#
rD <- rsDriver(browser = "chrome",chromever="105.0.5195.52")#
remDr <- rD[["client"]]#
remDr$getStatus()#
#
#############################################################
## Login#
#############################################################
## Go to feast login#
remDr$navigate("https://feast.punjab.gov.in/login.aspx")#
Sys.sleep(5)#
#
## Select Login type#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_ddllogintype"]/option[3]')#
webElem$clickElement()#
Sys.sleep(5)#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_ddlRegion"]/option[2]')#
webElem$clickElement()#
Sys.sleep(5)#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_ddlDist"]/option[21]')#
webElem$clickElement()#
Sys.sleep(5)#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_ddlDepot"]/option[111]')#
webElem$clickElement()#
Sys.sleep(5)#
#
## Fill Password#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_Password"]')#
webElem$clickElement()#
webElem$sendKeysToElement(list("depot@123"))#
Sys.sleep(2)#
## Solve capthca#
# webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_CaptchaImage1"]')#
# webElem$getElementAttribute("src")#
# chars <- tesseract(options = list(tessedit_char_whitelist = toupper(letters)))#
# ocr_data(aa, engine = chars)#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_txtcaptcha"]')#
webElem$clickElement()
remDr$navigate("https://feast.punjab.gov.in/login.aspx")#
Sys.sleep(5)#
#
## Select Login type#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_ddllogintype"]/option[3]')#
webElem$clickElement()#
Sys.sleep(5)#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_ddlRegion"]/option[2]')#
webElem$clickElement()#
Sys.sleep(5)#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_ddlDist"]/option[21]')#
webElem$clickElement()#
Sys.sleep(5)#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_ddlDepot"]/option[111]')#
webElem$clickElement()#
Sys.sleep(5)#
#
## Fill Password#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_Password"]')#
webElem$clickElement()#
webElem$sendKeysToElement(list("depot@123"))#
Sys.sleep(2)#
## Solve capthca#
# webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_CaptchaImage1"]')#
# webElem$getElementAttribute("src")#
# chars <- tesseract(options = list(tessedit_char_whitelist = toupper(letters)))#
# ocr_data(aa, engine = chars)#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_txtcaptcha"]')#
webElem$clickElement()
remDr$navigate("https://feast.punjab.gov.in/login.aspx")#
Sys.sleep(5)#
#
## Select Login type#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_ddllogintype"]/option[3]')#
webElem$clickElement()#
Sys.sleep(5)#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_ddlRegion"]/option[2]')#
webElem$clickElement()#
Sys.sleep(5)#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_ddlDist"]/option[21]')#
webElem$clickElement()#
Sys.sleep(5)#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_ddlDepot"]/option[110]')#
webElem$clickElement()#
Sys.sleep(5)#
#
## Fill Password#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_Password"]')#
webElem$clickElement()#
webElem$sendKeysToElement(list("depot@123"))#
Sys.sleep(2)#
## Solve capthca#
# webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_CaptchaImage1"]')#
# webElem$getElementAttribute("src")#
# chars <- tesseract(options = list(tessedit_char_whitelist = toupper(letters)))#
# ocr_data(aa, engine = chars)#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_txtcaptcha"]')#
webElem$clickElement()
#############################################################
## Issue Parameters#
#############################################################
## Issue Parameters#
issued <- data.frame()#
trucks <- c("pb13f7185","pcis9482","pb13ab1643","pb08g8617","pb550761","pb13y2294","pb138683","pb04g8188","pas 4005","pb07al5025","pb13a6028","pb139030","pb131401","pb13a1649","pb248816","pb135827","pb635009","pb13s3484")#
wcmnum <- 155#
depot_code <- 0#
max_bags <- 30000#
idx=0#
## Weight Code#
options(digits=8)#
cbp50 <- function(weight)#
{#
	n_bags <- round(weight/.5)#
	return(list(Bags=n_bags,Weight = (weight+n_bags*.00135)))#
}#
cbj50 <- function(weight)#
{#
	n_bags <- round(weight/.5)#
	return(list(Bags=n_bags,Weight = (weight+n_bags*.00580)))#
}#
cbp30 <- function(weight)#
{#
	n_bags <- round(weight/.3)#
	return(list(Bags=n_bags,Weight = (weight+n_bags*.00088)))#
}#
#############################################################
#############################################################
#############################################################
## Loop Challan Issue#
#############################################################
while(TRUE)#
{#
	start_time <- Sys.time()#
	## Go to truck challan page#
	webElem <- remDr$findElement(using = "xpath", value = '//*[@id="tvHierarchyViewt3"]')#
	webElem$clickElement()#
	Sys.sleep(5)#
#
	## Select Allocation#
	webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_txtAllocationOrder"]')#
	webElem$clickElement()#
	Sys.sleep(3)#
	webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_ddlAllocationOrder_3"]')#
	webElem$clickElement()#
	Sys.sleep(12)#
	webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_deliverytr"]/td[1]')#
	webElem$clickElement()#
	Sys.sleep(12)#
	## Select Depot#
	while(TRUE)#
	{#
		## Select Depot#
		depot_idx <- paste0("//*[@id='ContentPlaceHolder1_lstDeliveryOrder_",idx,"']")#
		webElem <- remDr$findElement(using = "xpath", value = depot_idx)#
		webElem$clickElement()#
		Sys.sleep(15)#
		depot_idx <- paste0("//*[@id='ContentPlaceHolder1_lstDeliveryOrder']/tbody/tr[",idx+1,"]/td/label")#
		webElem <- remDr$findElement(using = "xpath", value = depot_idx)#
		depot_code <- as.numeric(gsub("105300500","",str_extract(webElem$getElementText()[[1]], "(?<=\\().+?(?=\\))")[[1]]))#
		## Submit and get allocation#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_btnsubmittdetails"]')#
		webElem$clickElement()#
		Sys.sleep(8)#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_Grdcomqtytotal_lblgrdissueqty_0"]')#
		wheat_issue <- as.numeric(webElem$getElementText()[[1]])#
		if(wheat_issue < 2)#
		{#
			depot_idx <- paste0("//*[@id='ContentPlaceHolder1_lstDeliveryOrder_",idx,"']")#
			webElem <- remDr$findElement(using = "xpath", value = depot_idx)#
			webElem$clickElement()#
			Sys.sleep(10)#
			idx <- idx+1#
			next()#
		}#
#
		## Fill Book Number#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_txtWCMBookNo"]')#
		webElem$clickElement()#
		webElem$sendKeysToElement(list("1"))#
		Sys.sleep(2)#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_txtWCMSerialNo"]')#
		webElem$clickElement()#
		webElem$sendKeysToElement(list(as.character(wcmnum)))#
#
		## Fill gatepass Details#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_ddlcommodity"]/option[2]')#
		webElem$clickElement()#
		Sys.sleep(5)#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_ddlWeighmentType"]/option[2]')#
		webElem$clickElement()#
		Sys.sleep(5)#
		## Bag Weight#
		bag_issue <- cbp30(wheat_issue)#
		message(paste0("Bags ",(sum(issued$Bags)+bag_issue[[1]])))#
		if((sum(issued$Bags)+bag_issue[[1]])>max_bags) stop("Max Bag Limit Reached")#
		# webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_ddlBagType"]/option[6]') # Jute50 580#
		# webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_ddlBagType"]/option[4]') # PP50 135#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_ddlBagType"]/option[7]') # PP30 88#
		webElem$clickElement()#
		Sys.sleep(5)#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_txtNoOfBag"]')#
		webElem$clickElement()#
		webElem$sendKeysToElement(list(selKeys$right_arrow))#
		webElem$sendKeysToElement(list(selKeys$backspace))#
		webElem$sendKeysToElement(list(as.character(bag_issue[[1]])))#
		Sys.sleep(3)#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_deliverytr"]/td[1]')#
		webElem$clickElement()#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_txtGrossQty"]')#
		webElem$clickElement()#
		Sys.sleep(3)#
		webElem$sendKeysToElement(list(as.character(bag_issue[[2]])))#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_deliverytr"]/td[1]')#
		webElem$clickElement()#
		Sys.sleep(5)#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_btnAddBagDetails"]')#
		webElem$clickElement()#
		Sys.sleep(5)#
#
		## Transport#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_ddltransportername"]/option[689]')#
		webElem$clickElement()#
		Sys.sleep(3)#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_txttruckno"]')#
		webElem$clickElement()#
		Sys.sleep(3)#
		webElem$sendKeysToElement(list(trucks[ifelse(wcmnum%%length(trucks)==0,length(trucks),wcmnum%%length(trucks))]))#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_deliverytr"]/td[1]')#
		webElem$clickElement()#
		Sys.sleep(5)#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_txtDriverMobileNo"]')#
		webElem$clickElement()#
		Sys.sleep(3)#
		webElem$sendKeysToElement(list("9999988888"))#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_deliverytr"]/td[1]')#
		webElem$clickElement()#
		Sys.sleep(5)#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_btngentruckchallan"]')#
		webElem$clickElement()#
		Sys.sleep(5)#
		webElem$acceptAlert()#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_btnPrint"]')#
		webElem$clickElement()#
		Sys.sleep(8)#
#
		## On success#
		issued <- rbind(issued,data.frame(#
											Date = as.Date(Sys.time()),#
											GPNum = wcmnum,#
											Depot = depot_code,#
											Bags = bag_issue[[1]],#
											Weight = bag_issue[[2]]#
				))#
		wcmnum <- wcmnum+1#
		break()#
	}#
	end_time <- Sys.time()#
	message(paste0("Took ",round(as.numeric(difftime(end_time,start_time,units="mins")),2)," Minutes."))#
}
## Go to feast login#
remDr$navigate("https://feast.punjab.gov.in/login.aspx")#
Sys.sleep(5)#
#
## Select Login type#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_ddllogintype"]/option[3]')#
webElem$clickElement()#
Sys.sleep(5)#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_ddlRegion"]/option[2]')#
webElem$clickElement()#
Sys.sleep(5)#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_ddlDist"]/option[21]')#
webElem$clickElement()#
Sys.sleep(5)#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_ddlDepot"]/option[111]')#
webElem$clickElement()#
Sys.sleep(5)#
#
## Fill Password#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_Password"]')#
webElem$clickElement()#
webElem$sendKeysToElement(list("depot@123"))#
Sys.sleep(2)#
## Solve capthca#
# webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_CaptchaImage1"]')#
# webElem$getElementAttribute("src")#
# chars <- tesseract(options = list(tessedit_char_whitelist = toupper(letters)))#
# ocr_data(aa, engine = chars)#
webElem <- remDr$findElement(using = "xpath", value = '//*[@id="UXLogin_txtcaptcha"]')#
webElem$clickElement()
## Issue Parameters#
issued <- data.frame()#
trucks <- c("pb13f7185","pcis9482","pb13ab1643","pb08g8617","pb550761","pb13y2294","pb138683","pb04g8188","pas 4005","pb07al5025","pb13a6028","pb139030","pb131401","pb13a1649","pb248816","pb135827","pb635009","pb13s3484")#
wcmnum <- 156#
depot_code <- 0#
max_bags <- 30000#
idx=0#
## Weight Code#
options(digits=8)#
cbp50 <- function(weight)#
{#
	n_bags <- round(weight/.5)#
	return(list(Bags=n_bags,Weight = (weight+n_bags*.00135)))#
}#
cbj50 <- function(weight)#
{#
	n_bags <- round(weight/.5)#
	return(list(Bags=n_bags,Weight = (weight+n_bags*.00580)))#
}#
cbp30 <- function(weight)#
{#
	n_bags <- round(weight/.3)#
	return(list(Bags=n_bags,Weight = (weight+n_bags*.00088)))#
}#
#############################################################
#############################################################
#############################################################
## Loop Challan Issue#
#############################################################
while(TRUE)#
{#
	start_time <- Sys.time()#
	## Go to truck challan page#
	webElem <- remDr$findElement(using = "xpath", value = '//*[@id="tvHierarchyViewt3"]')#
	webElem$clickElement()#
	Sys.sleep(5)#
#
	## Select Allocation#
	webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_txtAllocationOrder"]')#
	webElem$clickElement()#
	Sys.sleep(3)#
	webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_ddlAllocationOrder_3"]')#
	webElem$clickElement()#
	Sys.sleep(12)#
	webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_deliverytr"]/td[1]')#
	webElem$clickElement()#
	Sys.sleep(12)#
	## Select Depot#
	while(TRUE)#
	{#
		## Select Depot#
		depot_idx <- paste0("//*[@id='ContentPlaceHolder1_lstDeliveryOrder_",idx,"']")#
		webElem <- remDr$findElement(using = "xpath", value = depot_idx)#
		webElem$clickElement()#
		Sys.sleep(15)#
		depot_idx <- paste0("//*[@id='ContentPlaceHolder1_lstDeliveryOrder']/tbody/tr[",idx+1,"]/td/label")#
		webElem <- remDr$findElement(using = "xpath", value = depot_idx)#
		depot_code <- as.numeric(gsub("105300500","",str_extract(webElem$getElementText()[[1]], "(?<=\\().+?(?=\\))")[[1]]))#
		## Submit and get allocation#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_btnsubmittdetails"]')#
		webElem$clickElement()#
		Sys.sleep(8)#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_Grdcomqtytotal_lblgrdissueqty_0"]')#
		wheat_issue <- as.numeric(webElem$getElementText()[[1]])#
		if(wheat_issue < 2)#
		{#
			depot_idx <- paste0("//*[@id='ContentPlaceHolder1_lstDeliveryOrder_",idx,"']")#
			webElem <- remDr$findElement(using = "xpath", value = depot_idx)#
			webElem$clickElement()#
			Sys.sleep(10)#
			idx <- idx+1#
			next()#
		}#
#
		## Fill Book Number#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_txtWCMBookNo"]')#
		webElem$clickElement()#
		webElem$sendKeysToElement(list("1"))#
		Sys.sleep(2)#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_txtWCMSerialNo"]')#
		webElem$clickElement()#
		webElem$sendKeysToElement(list(as.character(wcmnum)))#
#
		## Fill gatepass Details#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_ddlcommodity"]/option[2]')#
		webElem$clickElement()#
		Sys.sleep(5)#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_ddlWeighmentType"]/option[2]')#
		webElem$clickElement()#
		Sys.sleep(5)#
		## Bag Weight#
		bag_issue <- cbp30(wheat_issue)#
		message(paste0("Bags ",(sum(issued$Bags)+bag_issue[[1]])))#
		if((sum(issued$Bags)+bag_issue[[1]])>max_bags) stop("Max Bag Limit Reached")#
		# webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_ddlBagType"]/option[6]') # Jute50 580#
		# webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_ddlBagType"]/option[4]') # PP50 135#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_ddlBagType"]/option[7]') # PP30 88#
		webElem$clickElement()#
		Sys.sleep(5)#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_txtNoOfBag"]')#
		webElem$clickElement()#
		webElem$sendKeysToElement(list(selKeys$right_arrow))#
		webElem$sendKeysToElement(list(selKeys$backspace))#
		webElem$sendKeysToElement(list(as.character(bag_issue[[1]])))#
		Sys.sleep(3)#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_deliverytr"]/td[1]')#
		webElem$clickElement()#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_txtGrossQty"]')#
		webElem$clickElement()#
		Sys.sleep(3)#
		webElem$sendKeysToElement(list(as.character(bag_issue[[2]])))#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_deliverytr"]/td[1]')#
		webElem$clickElement()#
		Sys.sleep(5)#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_btnAddBagDetails"]')#
		webElem$clickElement()#
		Sys.sleep(5)#
#
		## Transport#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_ddltransportername"]/option[689]')#
		webElem$clickElement()#
		Sys.sleep(3)#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_txttruckno"]')#
		webElem$clickElement()#
		Sys.sleep(3)#
		webElem$sendKeysToElement(list(trucks[ifelse(wcmnum%%length(trucks)==0,length(trucks),wcmnum%%length(trucks))]))#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_deliverytr"]/td[1]')#
		webElem$clickElement()#
		Sys.sleep(5)#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_txtDriverMobileNo"]')#
		webElem$clickElement()#
		Sys.sleep(3)#
		webElem$sendKeysToElement(list("9999988888"))#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_deliverytr"]/td[1]')#
		webElem$clickElement()#
		Sys.sleep(5)#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_btngentruckchallan"]')#
		webElem$clickElement()#
		Sys.sleep(5)#
		webElem$acceptAlert()#
		webElem <- remDr$findElement(using = "xpath", value = '//*[@id="ContentPlaceHolder1_btnPrint"]')#
		webElem$clickElement()#
		Sys.sleep(8)#
#
		## On success#
		issued <- rbind(issued,data.frame(#
											Date = as.Date(Sys.time()),#
											GPNum = wcmnum,#
											Depot = depot_code,#
											Bags = bag_issue[[1]],#
											Weight = bag_issue[[2]]#
				))#
		wcmnum <- wcmnum+1#
		break()#
	}#
	end_time <- Sys.time()#
	message(paste0("Took ",round(as.numeric(difftime(end_time,start_time,units="mins")),2)," Minutes."))#
}
issued
readr::write_csv(issued,"~/Downloads/Issued.csv")
## Read in file#
library(readxl)#
#
## List all sheets#
sheets <- excel_sheets("~/Downloads/GR15 Squelch Prep.xlsx")#
all_handles <- list()#
#
## Sybil Scoring Legos#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Sybil Scoring Legos")
head(data)
sheets
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Sybil Donation")
head(data)
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Sybil Donation",skip=1)
head(data)
## Read in file#
library(readxl)#
#
## List all sheets#
sheets <- excel_sheets("~/Downloads/GR15 Squelch Prep.xlsx")#
all_handles <- list()#
#
## Sybil Scoring Legos#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Sybil Scoring Legos")#
all_handles <- c(all_handles,"Sybil Scoring Legos" = list(data$Handle))#
#
## Sybil Donation#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Sybil Donation",skip=1)#
all_handles <- c(all_handles,"Sybil Donation" = list(data$handle))
all_handles[[2]]
## Read in file#
library(readxl)#
#
## List all sheets#
sheets <- excel_sheets("~/Downloads/GR15 Squelch Prep.xlsx")#
all_handles <- list()#
#
## Sybil Scoring Legos#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Sybil Scoring Legos")#
all_handles <- c(all_handles,"Sybil Scoring Legos" = unique(list(data$Handle)))#
#
## Sybil Donation#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Sybil Donation",skip=1)#
all_handles <- c(all_handles,"Sybil Donation" = unique(list(data$handle)))
sheets
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="NaiveFlagging",skip=0)
head(daya)
head(data)
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="NaiveFlagging",skip=0)#
all_handles <- c(all_handles,"NaiveFlagging" = unique(list(data$handle)))
all_handles[[3]]
sheets
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Burners",skip=0)
head(data)
dim(data)
table(data$Flag)
all_handles <- c(all_handles,"Burners" = unique(list(data$handle[data$Flag])))
all_handles[[4]]
sheets
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="SyncSwapVoters",skip=0)
head(data)
dim(data)
unique(list(data$handle[data$Review]))
data$handle[data$Review?]
data$handle[data$`Review?`]
apudf <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/stamps_and_scores.csv")
library(jsonlite)#
library(readr)#
#
## Read in APU data#
apudf <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/stamps_and_scores.csv")
head(apudf)
min(apudf$last_apu_score)
which(apudf$last_apu_score==0)
apudf [7,]
which(apudf$handle=="omnianalytics")
head(apudf)
apudf$stamps[1]
lapply(apudf$stamps,fromJSON)[[1]]
apudfs <- lapply(apudf$stamps,fromJSON)
all_stamps <- unique(unlist(apudfs))
all_stamps
apudfs <- lapply(apudf$stamps,fromJSON)#
all_stamps <- unique(unlist(apudfs))#
lapply(apudfs,function(x,all_stamps) all_stamps %in% x)[[1]]
lapply(apudfs,function(x,all_stamps) all_stamps %in% x,all_stamps=all_stamps)[[1]]
head(apudf)
stamps_wide <- cbind(Handle = apudf$handle, do.call(rbind,lapply(apudfs,function(x,all_stamps) all_stamps %in% x,all_stamps=all_stamps))
stamps_wide <- cbind(Handle = apudf$handle, do.call(rbind,lapply(apudfs,function(x,all_stamps) all_stamps %in% x,all_stamps=all_stamps)))
head(stamps_wide)
stamps_wide <- cbind(Handle = apudf$handle, as.data.frame(do.call(rbind,lapply(apudfs,function(x,all_stamps) all_stamps %in% x,all_stamps=all_stamps))))
head(stamps_wide)
names(stamps_wide)[-1] <- all_stamps
head(stamps_wide)
write_csv(stamps_wide,"~/Downloads/stamps_wide.csv")
sapply(apudfs,length)
hist(sapply(apudfs,length))
quantile(sapply(apudfs,length))
quantile(sapply(apudfs,length),1:100/100)
mean(sapply(apudfs,length))
aa <- unlist(apudfs)
table(aa)
barplot(table(aa))
sort(table(aa))
sort(table(aa),decreasing=TRUE)
hist(sapply(apudfs,length))
hist(sapply(apudfs,length),20)
hist(sapply(apudfs,length),100)
hist(sapply(apudfs,length),50)
## Read in file#
library(readxl)#
#
## List all sheets#
sheets <- excel_sheets("~/Downloads/GR15 Squelch Prep.xlsx")#
all_handles <- list()#
#
## Sybil Scoring Legos#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Sybil Scoring Legos")#
all_handles <- c(all_handles,"Sybil Scoring Legos" = unique(list(data$Handle)))#
#
## Sybil Donation#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Sybil Donation",skip=1)#
all_handles <- c(all_handles,"Sybil Donation" = unique(list(data$handle)))#
#
## NaiveFlagging#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="NaiveFlagging",skip=0)#
all_handles <- c(all_handles,"NaiveFlagging" = unique(list(data$handle)))#
#
## Burners#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Burners",skip=0)#
all_handles <- c(all_handles,"Burners" = unique(list(data$handle[data$Flag])))
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="SyncSwapVoters",skip=0)
unique(list(data$handle[data$Review?]))
unique(list(data$handle[data$`Review?`]))
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="SyncSwapVoters",skip=0)#
all_handles <- c(all_handles,"Burners" = unique(list(data$handle[data$Review?])))
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="SyncSwapVoters",skip=0)#
all_handles <- c(all_handles,"Burners" = unique(list(data$handle[data$`Review?`])))
sheets
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="LOKI set",skip=0)
head(data)
dim(data)
unique(list(data$handle))
## Read in file#
library(readxl)#
#
## List all sheets#
sheets <- excel_sheets("~/Downloads/GR15 Squelch Prep.xlsx")#
all_handles <- list()#
#
## Sybil Scoring Legos#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Sybil Scoring Legos")#
all_handles <- c(all_handles,"Sybil Scoring Legos" = unique(list(data$Handle)))#
#
## Sybil Donation#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Sybil Donation",skip=1)#
all_handles <- c(all_handles,"Sybil Donation" = unique(list(data$handle)))#
#
## NaiveFlagging#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="NaiveFlagging",skip=0)#
all_handles <- c(all_handles,"NaiveFlagging" = unique(list(data$handle)))#
#
## Burners#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Burners",skip=0)#
all_handles <- c(all_handles,"Burners" = unique(list(data$handle[data$Flag])))#
#
## SyncSwapVoters#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="SyncSwapVoters",skip=0)#
all_handles <- c(all_handles,"SyncSwapVoters" = unique(list(data$handle[data$`Review?`])))#
#
## LOKI set#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="LOKI set",skip=0)#
all_handles <- c(all_handles,"LOKI set" = unique(list(data$handle)))
sheets
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Jigger GR14",skip=0)
head(data)
dim(data)
wall_handles <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/gr15_contributions/20220923-001354_wallets.csv")
library(readr)
wall_handles <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/gr15_contributions/20220923-001354_wallets.csv")
head(wall_handles)
table(data$address %in% wall_handles$address)
length(data$address[data$burner])
table(data$address[data$burner] %in% wall_handles$address)
## Read in file#
library(readxl)#
library(readr)#
#
## List all sheets#
sheets <- excel_sheets("~/Downloads/GR15 Squelch Prep.xlsx")#
all_handles <- list()#
#
## Sybil Scoring Legos#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Sybil Scoring Legos")#
all_handles <- c(all_handles,"Sybil Scoring Legos" = unique(list(data$Handle)))#
#
## Sybil Donation#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Sybil Donation",skip=1)#
all_handles <- c(all_handles,"Sybil Donation" = unique(list(data$handle)))#
#
## NaiveFlagging#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="NaiveFlagging",skip=0)#
all_handles <- c(all_handles,"NaiveFlagging" = unique(list(data$handle)))#
#
## Burners#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Burners",skip=0)#
all_handles <- c(all_handles,"Burners" = unique(list(data$handle[data$Flag])))#
#
## SyncSwapVoters#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="SyncSwapVoters",skip=0)#
all_handles <- c(all_handles,"SyncSwapVoters" = unique(list(data$handle[data$`Review?`])))#
#
## LOKI set#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="LOKI set",skip=0)#
all_handles <- c(all_handles,"LOKI set" = unique(list(data$handle)))
all_handles_u <- unique(unlist(all_handles))
length(all_handles_u)
SybilBinary <- lapply(all_handles,function(x,all_handles_u) all_handles_u %in% x)
SybilBinary <- lapply(all_handles,function(x,all_handles_u) all_handles_u %in% x,all_handles_u=all_handles_u)
SybilBinary[[1]]
head(do.call(cbind,lapply(all_handles,function(x,all_handles_u) as.numeric(all_handles_u %in% x,all_handles_u=all_handles_u))))
all_handles_u <- unique(unlist(all_handles))
SybilBinary <- do.call(cbind,lapply(all_handles,function(x,all_handles_u) as.numeric(all_handles_u %in% x,all_handles_u=all_handles_u)))
SybilBinary <- do.call(cbind,lapply(all_handles,function(x,all_handles_u) as.numeric(all_handles_u %in% x),all_handles_u=all_handles_u))
head(SybilBinary)
SybilBinary <- cbind(Handle=all_handles_u,as.data.frame(do.call(cbind,lapply(all_handles,function(x,all_handles_u) as.numeric(all_handles_u %in% x),all_handles_u=all_handles_u))))
head(SybilBinary)
apply(SybilBinary,1,sum)
apply(SybilBinary[,-1],1,sum)
order(apply(SybilBinary[,-1],1,sum),decreasing=TRUE)
head(SybilBinary[order(apply(SybilBinary[,-1],1,sum),decreasing=TRUE),])
## Read in file#
library(readxl)#
library(readr)#
#
## List all sheets#
sheets <- excel_sheets("~/Downloads/GR15 Squelch Prep.xlsx")#
all_handles <- list()#
#
## Sybil Scoring Legos#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Sybil Scoring Legos")#
all_handles <- c(all_handles,"Sybil Scoring Legos" = unique(list(data$Handle)))#
#
## Sybil Donation#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Sybil Donation",skip=1)#
all_handles <- c(all_handles,"Sybil Donation" = unique(list(data$handle)))#
#
## NaiveFlagging#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="NaiveFlagging",skip=0)#
all_handles <- c(all_handles,"NaiveFlagging" = unique(list(data$handle)))#
#
## Burners#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Burners",skip=0)#
all_handles <- c(all_handles,"Burners" = unique(list(data$handle[data$Flag])))#
#
## SyncSwapVoters#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="SyncSwapVoters",skip=0)#
all_handles <- c(all_handles,"SyncSwapVoters" = unique(list(data$handle[data$`Review?`])))#
#
## LOKI set#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="LOKI set",skip=0)#
all_handles <- c(all_handles,"LOKI set" = unique(list(data$handle)))#
#
## Jigger GR14#
# data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Jigger GR14",skip=0)#
# wall_handles <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/gr15_contributions/20220923-001354_wallets.csv")#
#
## Make Binary Matrix#
all_handles_u <- unique(unlist(all_handles))#
SybilBinary <- cbind(Handle=all_handles_u,as.data.frame(do.call(cbind,lapply(all_handles,function(x,all_handles_u) as.numeric(all_handles_u %in% x),all_handles_u=all_handles_u))))#
SybilBinary <- SybilBinary[order(apply(SybilBinary[,-1],1,sum),decreasing=TRUE),]#
write_csv(SybilBinary,"~/Downloads/SybilBinary.csv")
head(SybilBinary,20)
rle(SybilBinary$Sybil Scoring Lego)
rle(SybilBinary$`Sybil Scoring Lego`)
legodata <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_app/LegoData.csv")
table(SybilBinary$Handle %in% legodata$Handle)
451*30
library(readr)#
#
## Read in Handles#
legodata <- data.frame(Handle=read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/gr15_contributions/20220923-001354_handles.csv")[,1,drop=TRUE])#
#
## Lev Data#
lev_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Levenshtein_scores.csv")#
legodata$LevDistance <- lev_df$Distance_Min[match(legodata$Handle,lev_df$Handle)]#
#
## Intersectionality#
inter_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Intersectionality.csv")#
legodata$IntersectionalityScore <- inter_df$Score[match(legodata$Handle,inter_df$Handle)]#
#
## DDNA#
ddna_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Jaccard_handles_scores.csv")#
legodata$DDNADistance <- round(ddna_df$Distance_Min[match(legodata$Handle,ddna_df$Handle)],2)#
#
## APU#
apu_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/APU.csv")
sum(is.na(match(legodata$Handle,apu_df$Handle)))
legodata$APUScore <- round(apu_df$Score[match(legodata$Handle,apu_df$Handle)],2)
legodata$APUScore <- ifelse(is.na(legodata$APUScore),0,legodata$APUScore)
sum(is.na())
sum(is.na(legodata$APUScore))
library(readr)#
#
## Read in Handles#
legodata <- data.frame(Handle=read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/gr15_contributions/20220923-001354_handles.csv")[,1,drop=TRUE])#
#
## Lev Data#
lev_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Levenshtein_scores.csv")#
legodata$LevDistance <- lev_df$Distance_Min[match(legodata$Handle,lev_df$Handle)]#
#
## Intersectionality#
inter_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Intersectionality.csv")#
legodata$IntersectionalityScore <- inter_df$Score[match(legodata$Handle,inter_df$Handle)]#
#
## DDNA#
ddna_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Jaccard_handles_scores.csv")#
legodata$DDNADistance <- round(ddna_df$Distance_Min[match(legodata$Handle,ddna_df$Handle)],2)#
#
## APU#
apu_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/APU.csv")#
legodata$APUScore <- round(apu_df$Score[match(legodata$Handle,apu_df$Handle)],2)#
legodata$APUScore <- ifelse(is.na(legodata$APUScore),0,legodata$APUScore)#
#
## SAD#
sad_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/SAD.csv")#
legodata$SADScore <- round(sad_df$Score[match(legodata$Handle,sad_df$Handle)],2)#
#
## GrantOwner#
owner_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/grants_owners.csv")#
legodata$GrantOwner <- ifelse(legodata$Handle %in% owner_df$handle,1,0)#
#
## IPs Shared#
ip_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/IPShared_scores.csv")#
ip_df$Score <- ip_df$IPCount_ProfShared_gt1/ip_df$IPCount#
legodata$IPsShared <- round(ip_df$Score[match(legodata$Handle,ip_df$Handle)],2)#
#
## Write Out Data#
write_csv(legodata,"~/Desktop/Gitcoin Sybil LEGOs/data_app/LegoData.csv")
library(readr)#
library(Rfast)#
#
## Read in Handles#
legodata <- data.frame(Handle=read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/gr15_contributions/20220923-001354_handles.csv")[,1,drop=TRUE])#
#
## Lev Data#
lev_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Levenshtein_scores.csv")#
legodata$LevDistance <- lev_df$Distance_Min[match(legodata$Handle,lev_df$Handle)]#
legodata$LevMatchCount <- lev_df$Distance_Min_is1_Count[match(legodata$Handle,lev_df$Handle)]#
#
## Intersectionality#
inter_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Intersectionality.csv")#
legodata$IntersectionalityScore <- inter_df$Score[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOAPActive <- inter_df$poap[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOAPCount <- inter_df$poap_count[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensActive <- inter_df$lens[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensFollowers <- inter_df$lens_followers[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityLensFollowing <- inter_df$lens_following[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityPOHActive <- inter_df$poh[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityNFTActive <- inter_df$nft[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalityNFTCount <- inter_df$nft_count[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalitySnapshotActive <- inter_df$snapshot[match(legodata$Handle,inter_df$Handle)]#
# legodata$IntersectionalitySnapshotVotes <- inter_df$snapshot_votes[match(legodata$Handle,inter_df$Handle)]#
#
## DDNA#
ddna_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Jaccard_handles_scores.csv")#
data_mat_handles <- readRDS("~/Desktop/Gitcoin Sybil LEGOs/data_processed/Jaccard_binmat_handles.RDS")#
data_mat_handles <- data_mat_handles[,!grepl("Amt",colnames(data_mat_handles))]#
data_sum_handles <- data.frame(Handle = rownames(data_mat_handles),DDNAGrantsDonated=rowsums(data_mat_handles))#
legodata$DDNADistance <- round(ddna_df$Distance_Min[match(legodata$Handle,ddna_df$Handle)],2)#
legodata$DDNAGrantsDonated <- data_sum_handles$DDNAGrantsDonated[match(legodata$Handle,data_sum_handles$Handle)]#
#
## APU#
apu_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/APU.csv")#
legodata$APUScore <- round(apu_df$Score[match(legodata$Handle,apu_df$Handle)],2)#
legodata$APUScore <- ifelse(is.na(legodata$APUScore),0,legodata$APUScore)#
#
## SAD#
sad_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/SAD.csv")#
legodata$SADScore <- round(sad_df$Score[match(legodata$Handle,sad_df$Handle)],2)#
#
## GrantOwner#
owner_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/grants_owners.csv")#
legodata$GrantOwner <- ifelse(legodata$Handle %in% owner_df$handle,1,0)#
#
## IPs Shared#
ip_df <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_processed/IPShared_scores.csv")#
ip_df$Score <- ip_df$IPCount_ProfShared_gt1/ip_df$IPCount#
legodata$IPsSharedRatio <- round(ip_df$Score[match(legodata$Handle,ip_df$Handle)],2)#
legodata$IPsUsedCount <- round(ip_df$IPCount[match(legodata$Handle,ip_df$Handle)],2)#
legodata$IPsSharedCount <- ip_df$IPCount_ProfShared_gt1[match(legodata$Handle,ip_df$Handle)]#
#
## Meta Rank#
get_rank_Loki <- function(x,type="lb",wt=1)#
{#
	if(type=="lb") return(wt*rank(x,na.last=TRUE))#
	if(type=="lg") return(wt*rank(-1*x,na.last=TRUE))#
}#
get_rank_Thor <- function(x,type="lb",wt=1)#
{#
	if(type=="lb") return(wt*rank(x,na.last=FALSE))#
	if(type=="lg") return(wt*rank(-1*x,na.last=FALSE))#
}#
range01 <- function(x){(x-min(x))/(max(x)-min(x))}#
legodata_spl <- as.list(legodata)[2:12]#
legodata$MetaRank_Loki <- range01(apply(mapply(get_rank_Loki,legodata_spl,type=c("lb","lg","lb","lb","lb","lb","lg","lb","lg","lg","lg"),wt=rep(1,11)),1,sum))#
legodata$MetaRank_Thor <- range01(apply(mapply(get_rank_Thor,legodata_spl,type=c("lb","lg","lb","lb","lb","lb","lg","lb","lg","lg","lg"),wt=rep(1,11)),1,sum))#
#
# data.frame(Var=names(legodata_spl),RankType=c("lb","lg","lb","lb","lb","lg","lb","lg","lg","lg"))#
#
## Write Out Data#
write_csv(legodata,"~/Desktop/Gitcoin Sybil LEGOs/data_app/LegoDataFull.csv")
## Loading Libraries#
library(readr)#
library(dplyr)#
library(ggplot2)#
library(ggthemes)#
library(omnitheme)#
options(scipen=999)#
#
## Load whole data#
legodata <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_app/LegoData.csv")#
#
## Lev Plot#
y_lim1 <- c(0,15000)#
p1 <-   legodata %>%#
		group_by(LevDistance) %>%#
		summarise(count = n()) %>%#
		ggplot(aes(x = LevDistance, y = count)) +#
		annotate("rect", xmin = -Inf, xmax = 1.5, ymin = -Inf, ymax = Inf, alpha = 0.25, fill = "red") +#
		annotate("rect", xmin = 1.5, xmax = Inf, ymin = -Inf, ymax = Inf, alpha = 0.25, fill = "green") +#
		geom_bar(stat = "identity", fill = "#6F3FF5", width=.35) +#
		scale_y_continuous(breaks = scales::pretty_breaks(n = 10),limits=y_lim1) + #
		scale_x_continuous(breaks = (1:5),limits=c(0,6)) + #
		theme_fivethirtyeight() +#
		theme(#
				axis.title = element_text(),#
				rect=element_blank(),#
				panel.grid = element_blank(),#
				panel.background= element_blank(),#
				plot.background = element_blank()#
		) +#
		watermark_img(filename = "~/Desktop/Gitcoin Sybil LEGOs/www/gc.png", location = "tr", width = 40, alpha = 0.5) +#
		labs(#
				# title = "Distribution of the Minimum Levenshtein Distances across Gitcoin Account Names.",#
				x = "Minimum Levenshtein Distance",#
				y = "Number of Accounts"#
		)#
saveRDS(p1,"~/Desktop/Gitcoin Sybil LEGOs/data_app/Plot_Lev.RDS")#
# ggsave("~/Plot_Lev.jpg",plot=p1,width = 12,height=6)#
#
## Intersectionality#
y_lim2 <- c(0,12000)#
p2 <-   legodata %>%#
		group_by(IntersectionalityScore) %>%#
		summarise(count = n()) %>%#
		ggplot(aes(x = IntersectionalityScore, y = count)) +#
		annotate("rect", xmin = -Inf, xmax = .5, ymin = -Inf, ymax = Inf, alpha = 0.25, fill = "red") +#
		annotate("rect", xmin = .5, xmax = Inf, ymin = -Inf, ymax = Inf, alpha = 0.25, fill = "green") +#
		geom_bar(stat = "identity", fill = "#6F3FF5",width=.5) +#
		scale_y_continuous(breaks = scales::pretty_breaks(n = 10),limits=y_lim2) + #
		scale_x_continuous(breaks = scales::pretty_breaks(n = 5)) + #
		theme_fivethirtyeight() +#
		theme(#
				axis.title = element_text(),#
				rect=element_blank(),#
				panel.grid = element_blank(),#
				panel.background= element_blank(),#
				plot.background = element_blank()#
		) +#
		watermark_img(filename = "~/Desktop/Gitcoin Sybil LEGOs/www/gc.png", location = "tr", width = 40, alpha = 0.5) +#
		labs(#
				# title = "Distribution of the On-Chain Intersectionality Scores",#
				x = "On-chain Intersectionality Score",#
				y = "Number of Accounts"#
		)#
saveRDS(p2,"~/Desktop/Gitcoin Sybil LEGOs/data_app/Plot_Intersectionality.RDS")#
# ggsave("~/Plot_Intersectionality.jpg",plot=p2,width = 12,height=6)#
#
## DDNA#
y_lim3 <- c(0,22000)#
p3 <-   legodata %>%#
		group_by(DDNADistance) %>%#
		summarise(count = n()) %>%#
		ggplot(aes(x = DDNADistance, y = count)) +#
		annotate("rect", xmin = -Inf, xmax = .1, ymin = -Inf, ymax = Inf, alpha = 0.25, fill = "red") +#
		annotate("rect", xmin = .5, xmax = Inf, ymin = -Inf, ymax = Inf, alpha = 0.25, fill = "green") +#
		geom_bar(stat = "identity", fill = "#6F3FF5") +#
		scale_y_continuous(breaks = scales::pretty_breaks(n = 10),limits=y_lim3) + #
		scale_x_continuous(breaks = scales::pretty_breaks(n = 10)) + #
		theme_fivethirtyeight() +#
		theme(#
				axis.title = element_text(),#
				rect=element_blank(),#
				panel.grid = element_blank(),#
				panel.background= element_blank(),#
				plot.background = element_blank()#
		) +#
		watermark_img(filename = "~/Desktop/Gitcoin Sybil LEGOs/www/gc.png", location = "tr", width = 40, alpha = 0.5) +#
		labs(#
				# title = "Distribution of the Minimum Jaccard Distances across Gitcoin Donor DNA Profiles.",#
				# subtitle = "DonorDNA profiles have been derived from both the collection of sets and the total amount donated per user.",#
				x = "Jaccard Minumum Distance between Donors",#
				y = "Number of Accounts"#
		)#
saveRDS(p3,"~/Desktop/Gitcoin Sybil LEGOs/data_app/Plot_DDNA.RDS")#
# ggsave("~/Plot_DDNA.jpg",plot=p3,width = 12,height=6)#
#
## APU#
y_lim4 <- c(0,4000)#
p4 <-   legodata %>%#
		group_by(APUScore) %>%#
		summarise(count = n()) %>%#
		ggplot(aes(x = APUScore, y = count)) +#
		annotate("rect", xmin = -Inf, xmax = .1, ymin = -Inf, ymax = Inf, alpha = 0.25, fill = "red") +#
		annotate("rect", xmin = .2, xmax = Inf, ymin = -Inf, ymax = Inf, alpha = 0.25, fill = "green") +#
		geom_bar(stat = "identity", fill = "#6F3FF5") +#
		scale_y_continuous(breaks = scales::pretty_breaks(n = 10),limits=y_lim4) + #
		scale_x_continuous(breaks = (1:10)/10,limits=c(0,1)) +#
		theme_fivethirtyeight() +#
		theme(#
				axis.title = element_text(),#
				rect=element_blank(),#
				panel.grid = element_blank(),#
				panel.background= element_blank(),#
				plot.background = element_blank()#
		) +#
		watermark_img(filename = "~/Desktop/Gitcoin Sybil LEGOs/www/gc.png", location = "tr", width = 40, alpha = 0.5) +#
		labs(#
				# title = "Distribution of APU Scores for Passport Users.",#
				x = "APU Score",#
				y = "Number of Accounts"#
		)#
saveRDS(p4,"~/Desktop/Gitcoin Sybil LEGOs/data_app/Plot_APU.RDS")#
# ggsave("~/Plot_APU.jpg",plot=p4,width = 12,height=6)#
#
## SAD#
y_lim5 <- c(0,30000)#
p5 <-   legodata %>%#
		group_by(SADScore) %>%#
		summarise(count = n()) %>%#
		ggplot(aes(x = SADScore, y = count)) +#
		annotate("rect", xmin = -Inf, xmax = .4, ymin = -Inf, ymax = Inf, alpha = 0.25, fill = "green") +#
		annotate("rect", xmin = .7, xmax = Inf, ymin = -Inf, ymax = Inf, alpha = 0.25, fill = "red") +#
		geom_bar(stat = "identity", fill = "#6F3FF5") +#
		scale_y_continuous(breaks = scales::pretty_breaks(n = 10),limits=y_lim5) + #
		scale_x_continuous(breaks = scales::pretty_breaks(n = 10)) + #
		theme_fivethirtyeight() +#
		theme(#
				axis.title = element_text(),#
				rect=element_blank(),#
				panel.grid = element_blank(),#
				panel.background= element_blank(),#
				plot.background = element_blank()#
		) +#
		watermark_img(filename = "~/Desktop/Gitcoin Sybil LEGOs/www/gc.png", location = "tr", width = 40, alpha = 0.5) +#
		labs(#
				# title = "Distribution of SAD Prediction Scores for Gitcoin Accounts.",#
				x = "SAD Prediction Score",#
				y = "Number of Accounts"#
		)#
saveRDS(p5,"~/Desktop/Gitcoin Sybil LEGOs/data_app/Plot_SAD.RDS")#
# ggsave("~/Plot_SAD.jpg",plot=p5,width = 12,height=6)#
#
## IPs#
y_lim6 <- c(0,18000)#
p6 <-   legodata %>%#
		group_by(IPsShared) %>%#
		summarise(count = n()) %>%#
		ggplot(aes(x = IPsShared, y = count)) +#
		annotate("rect", xmin = -Inf, xmax = .4, ymin = -Inf, ymax = Inf, alpha = 0.25, fill = "green") +#
		annotate("rect", xmin = .7, xmax = Inf, ymin = -Inf, ymax = Inf, alpha = 0.25, fill = "red") +#
		geom_bar(stat = "identity", fill = "#6F3FF5") +#
		scale_y_continuous(breaks = scales::pretty_breaks(n = 10),limits=y_lim6) + #
		scale_x_continuous(breaks = scales::pretty_breaks(n = 10)) + #
		theme_fivethirtyeight() +#
		theme(#
				axis.title = element_text(),#
				rect=element_blank(),#
				panel.grid = element_blank(),#
				panel.background= element_blank(),#
				plot.background = element_blank()#
		) +#
		watermark_img(filename = "~/Desktop/Gitcoin Sybil LEGOs/www/gc.png", location = "tr", width = 40, alpha = 0.5) +#
		labs(#
				# title = "Distribution of ip_ratio_gt5 for Gitcoin Accounts.",#
				x = "Ratio Shared IPs",#
				y = "Number of Accounts"#
		)#
saveRDS(p6,"~/Desktop/Gitcoin Sybil LEGOs/data_app/Plot_IPs.RDS")#
# ggsave("~/Plot_IPs.jpg",plot=p6,width = 12,height=6)
## Read in file#
library(readxl)#
library(readr)#
#
## List all sheets#
sheets <- excel_sheets("~/Downloads/GR15 Squelch Prep.xlsx")#
all_handles <- list()#
#
## Sybil Scoring Legos#
# data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Sybil Scoring Legos")#
# all_handles <- c(all_handles,"Sybil Scoring Legos" = unique(list(data$Handle)))#
data <- read_csv("~/Downloads/FilterHandles_1664365741.csv")#
all_handles <- c(all_handles,"Sybil Scoring Legos" = unique(list(data$Handle)))
## Sybil Donation#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Sybil Donation",skip=1)#
all_handles <- c(all_handles,"Sybil Donation" = unique(list(data$handle)))#
#
## NaiveFlagging#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="NaiveFlagging",skip=0)#
all_handles <- c(all_handles,"NaiveFlagging" = unique(list(data$handle)))#
#
## Burners#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Burners",skip=0)#
all_handles <- c(all_handles,"Burners" = unique(list(data$handle[data$Flag])))#
#
## SyncSwapVoters#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="SyncSwapVoters",skip=0)#
all_handles <- c(all_handles,"SyncSwapVoters" = unique(list(data$handle[data$`Review?`])))#
#
## LOKI set#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="LOKI set",skip=0)#
all_handles <- c(all_handles,"LOKI set" = unique(list(data$handle)))#
#
## Jigger GR14#
# data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Jigger GR14",skip=0)#
# wall_handles <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/gr15_contributions/20220923-001354_wallets.csv")#
#
## Make Binary Matrix#
all_handles_u <- unique(unlist(all_handles))#
SybilBinary <- cbind(Handle=all_handles_u,as.data.frame(do.call(cbind,lapply(all_handles,function(x,all_handles_u) as.numeric(all_handles_u %in% x),all_handles_u=all_handles_u))))#
SybilBinary <- SybilBinary[order(apply(SybilBinary[,-1],1,sum),decreasing=TRUE),]
head(SybilBinary)
rle(SybilBinary$`Sybil Scoring Legos`)
legodata <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_app/LegoData.csv",show_col_types = FALSE)#
SybilBinary <- SybilBinary[SybilBinary$Handle %in% legodata$Handle,]
legodata <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_app/LegoData.csv",show_col_types = FALSE)#
SybilBinary <- SybilBinary[SybilBinary$Handle %in% legodata$Handle,]#
SybilBinary <- SybilBinary[order(apply(SybilBinary[,-1],1,sum),decreasing=TRUE),]#
rle(SybilBinary$`Sybil Scoring Legos`)
105+79+207
SybilBinary [391:400,]
## Read in file#
library(readxl)#
library(readr)#
#
## List all sheets#
sheets <- excel_sheets("~/Downloads/GR15 Squelch Prep.xlsx")#
all_handles <- list()#
#
## Sybil Scoring Legos#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Sybil Scoring Legos")#
all_handles <- c(all_handles,"Sybil Scoring Legos" = unique(list(data$Handle)))#
# data <- read_csv("~/Downloads/FilterHandles_1664365741.csv")#
# all_handles <- c(all_handles,"Sybil Scoring Legos" = unique(list(data$Handle)))#
## Sybil Donation#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Sybil Donation",skip=1)#
all_handles <- c(all_handles,"Sybil Donation" = unique(list(data$handle)))#
#
## NaiveFlagging#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="NaiveFlagging",skip=0)#
all_handles <- c(all_handles,"NaiveFlagging" = unique(list(data$handle)))#
#
## Burners#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Burners",skip=0)#
all_handles <- c(all_handles,"Burners" = unique(list(data$handle[data$Flag])))#
#
## SyncSwapVoters#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="SyncSwapVoters",skip=0)#
all_handles <- c(all_handles,"SyncSwapVoters" = unique(list(data$handle[data$`Review?`])))#
#
## LOKI set#
data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="LOKI set",skip=0)#
all_handles <- c(all_handles,"LOKI set" = unique(list(data$handle)))#
#
## Jigger GR14#
# data <-  read_excel("~/Downloads/GR15 Squelch Prep.xlsx",sheet="Jigger GR14",skip=0)#
# wall_handles <- read_csv("~/Desktop/Gitcoin Sybil LEGOs/data_input/gr15_contributions/20220923-001354_wallets.csv")#
#
## Make Binary Matrix#
all_handles_u <- unique(unlist(all_handles))#
SybilBinary <- cbind(Handle=all_handles_u,as.data.frame(do.call(cbind,lapply(all_handles,function(x,all_handles_u) as.numeric(all_handles_u %in% x),all_handles_u=all_handles_u))))#
SybilBinary <- SybilBinary[order(apply(SybilBinary[,-1],1,sum),decreasing=TRUE),]#
write_csv(SybilBinary,"~/Downloads/SybilBinary.csv")
rle(SybilBinary$`Sybil Scoring Legos`)
283+71+177
head(SybilBinary)
table(SybilBinary$`Sybil Donation` == SybilBinary$`LOKI set`)
SybilBinary[531:540,]
library(readr)#
library(ggplot2)#
library(hrbrthemes)#
#
data <- read_csv("~/Downloads/FilterHandles_1664376617.csv")
head(data)
plot(data$MetaRank_Loki, data$MetaRank_Thor)
cor(data$MetaRank_Loki, data$MetaRank_Thor)
length(NA)
library(readr)#
library(networkD3)#
library(fst)#
library(jsonlite)#
library(tidyr)#
library(ggplot2)#
library(ggthemes)#
library(omnitheme)#
library(RColorBrewer)#
library(igraph)#
library(parallel)#
## Load Helper Functions#
setwd("~/Desktop/Gitcoin Sybil LEGOs")#
source("app_helpers.R")#
#
## Load Lego Data#
legodata <- read_csv("data_app/LegoData.csv",show_col_types = FALSE)#
# Plot_Lev <- readRDS("data_app/Plot_Lev.RDS")#
# Plot_Intersectionality <- readRDS("data_app/Plot_Intersectionality.RDS")#
# Plot_DDNA <- readRDS("data_app/Plot_DDNA.RDS")#
# Plot_APU <- readRDS("data_app/Plot_APU.RDS")#
# Plot_SAD <- readRDS("data_app/Plot_SAD.RDS")#
# Plot_IPs <- readRDS("data_app/Plot_IPs.RDS")#
#
## Read Data for Lev Panel#
data_lev_scores <- read_csv("data_processed/Levenshtein_scores.csv",show_col_types = FALSE)#
data_lev_matches <- "data_processed/Levenshtein_matches.fst"#
#
## Read Data for DDNA Panel#
data_ddna_scores <- read_csv("data_processed/Jaccard_handles_scores.csv",show_col_types = FALSE)#
data_ddna_matches <- "data_processed/Jaccard_handles_matches.fst"#
data_ddna_matches_loaded <- read_fst(data_ddna_matches)#
data_ddna_binmat <- "data_processed/Jaccard_binmat_handles.fst"#
#
## Read Data for GDNA Panel#
owner_df <- read_csv("data_processed/grants_owners.csv",show_col_types = FALSE)#
data_gdna_scores <- read_csv("data_processed/Jaccard_grants_scores.csv",show_col_types = FALSE)#
data_gdna_matches <- "data_processed/Jaccard_grants_matches.fst"#
data_gdna_binmat <- "data_processed/Jaccard_binmat_grants.fst"#
#
## Read Data for IPs Panel#
data_ips_scores <- read_csv("data_processed/IPShared_scores.csv",show_col_types = FALSE)#
data_ips_matches <- "data_processed/IPShared_matches.fst"#
#
## Read Data for Filtering and Export#
legodatafull <- read_csv("data_app/LegoDataFull.csv",show_col_types = FALSE)#
#
input <- list()#
input$handle_sel <- "004hf"#
input$ips_network_handle <- "004hf"#
input$grant_ddna_network_cutoff <- 0#
input$grant_sel <- c("5719","7213","7219","6492")#
                                                dt_grant <- 562#input$grant_sel[1]
which(grepl("Whiteblock",owner_df$title))
owner_df [282,]
dt_grant <- 3557#input$grant_sel[1]#
                                                dt_grant2 <- owner_df$title[match(dt_grant,owner_df$grant_id)]#
                                                han_idx <- lapply(match(dt_grant,data_gdna_scores$GrantId),function(x) names(which(unlist(read_fst(data_gdna_binmat, from=x,to=x))>0)))#
                                                han_idx_fil <- data.frame(Handle=unique(unlist(han_idx)))#
                                                han_idx_fil$Group = paste0("Donated To ",sapply(apply(sapply(han_idx,function(x,y) y%in% x,y=han_idx_fil$Handle),1,function(x,y) y[x],y=dt_grant),paste0,collapse=", "))#
                                                han_idx_fil$GroupSize = apply(sapply(han_idx,function(x,y) y%in% x,y=han_idx_fil$Handle),1,sum)
dt_grant2
dt_grant <- 15#input$grant_sel[1]#
                                                dt_grant2 <- owner_df$title[match(dt_grant,owner_df$grant_id)]
dt_grant2
han_idx <- lapply(match(dt_grant,data_gdna_scores$GrantId),function(x) names(which(unlist(read_fst(data_gdna_binmat, from=x,to=x))>0)))
han_idx
han_idx_fil <- data.frame(Handle=unique(unlist(han_idx)))#
                                                han_idx_fil$Group = paste0("Donated To ",sapply(apply(sapply(han_idx,function(x,y) y%in% x,y=han_idx_fil$Handle),1,function(x,y) y[x],y=dt_grant),paste0,collapse=", "))#
                                                han_idx_fil$GroupSize = apply(sapply(han_idx,function(x,y) y%in% x,y=han_idx_fil$Handle),1,sum)#
                                                han_idx_fil <- han_idx_fil[data_ddna_scores$Distance_Min[match(han_idx_fil$Handle,data_ddna_scores$Handle)]<=input$grant_ddna_network_cutoff,]#
                                                if(nrow(han_idx_fil)==0) stop("No Sybil Clusters Found")
dt_grant <- 15#input$grant_sel[1]#
                                                dt_grant2 <- owner_df$title[match(dt_grant,owner_df$grant_id)]#
                                                han_idx <- lapply(match(dt_grant,data_gdna_scores$GrantId),function(x) names(which(unlist(read_fst(data_gdna_binmat, from=x,to=x))>0)))
han_idx_fil <- data.frame(Handle=unique(unlist(han_idx)))
han_idx_fil$Group = paste0("Donated To ",sapply(apply(sapply(han_idx,function(x,y) y%in% x,y=han_idx_fil$Handle),1,function(x,y) y[x],y=dt_grant),paste0,collapse=", "))#
                                                han_idx_fil$GroupSize = apply(sapply(han_idx,function(x,y) y%in% x,y=han_idx_fil$Handle),1,sum)
sapply(han_idx,function(x,y) y%in% x,y=han_idx_fil$Handle)
dt_grant <- 15#input$grant_sel[1]#
                                                dt_grant2 <- owner_df$title[match(dt_grant,owner_df$grant_id)]#
                                                han_idx <- lapply(match(dt_grant,data_gdna_scores$GrantId),function(x) names(which(unlist(read_fst(data_gdna_binmat, from=x,to=x))>0)))#
                                                han_idx_fil <- data.frame(Handle=unique(unlist(han_idx)))#
                                                # han_idx_fil$Group = paste0("Donated To ",sapply(apply(sapply(han_idx,function(x,y) y%in% x,y=han_idx_fil$Handle),1,function(x,y) y[x],y=dt_grant),paste0,collapse=", "))#
                                                # han_idx_fil$GroupSize = apply(sapply(han_idx,function(x,y) y%in% x,y=han_idx_fil$Handle),1,sum)#
                                                han_idx_fil <- han_idx_fil[data_ddna_scores$Distance_Min[match(han_idx_fil$Handle,data_ddna_scores$Handle)]<=input$grant_ddna_network_cutoff,]
han_idx_fil
if(nrow(han_idx_fil)==0)
nrow(han_idx_fil)==0
dt_grant <- 15#input$grant_sel[1]#
                                                dt_grant2 <- owner_df$title[match(dt_grant,owner_df$grant_id)]#
                                                han_idx <- lapply(match(dt_grant,data_gdna_scores$GrantId),function(x) names(which(unlist(read_fst(data_gdna_binmat, from=x,to=x))>0)))#
                                                han_idx_fil <- data.frame(Handle=unique(unlist(han_idx)))
han_idx_fil
han_idx_fil <- han_idx_fil[data_ddna_scores$Distance_Min[match(han_idx_fil$Handle,data_ddna_scores$Handle)]<=input$grant_ddna_network_cutoff,,drop=FALSE]
han_idx_fil
class(han_idx_fil)
dt_grant <- 15#input$grant_sel[1]#
                                                dt_grant2 <- owner_df$title[match(dt_grant,owner_df$grant_id)]#
                                                han_idx <- lapply(match(dt_grant,data_gdna_scores$GrantId),function(x) names(which(unlist(read_fst(data_gdna_binmat, from=x,to=x))>0)))
han_idx_fil <- data.frame(Handle=unique(unlist(han_idx)))
han_idx_fil
paste0("Donated To ",sapply(apply(sapply(han_idx,function(x,y) y%in% x,y=han_idx_fil$Handle),1,function(x,y) y[x],y=dt_grant),paste0,collapse=", "))
if(TRUE)#
{#
    message("Here1")#
    if(FALSE) break#
    message("Here2")#
}
if(TRUE)#
{#
    message("Here1")#
    if(FALSE) next#
    message("Here2")#
}
dt_grant <- input$grant_sel#
                                        dt_grant2 <- owner_df$title[match(dt_grant,owner_df$grant_id)]#
                                        han_idx <- lapply(match(dt_grant,data_gdna_scores$GrantId),function(x) names(which(unlist(read_fst(data_gdna_binmat, from=x,to=x))>0)))#
                                        han_idx_fil <- data.frame(Handle=unique(unlist(han_idx)))
han_idx_fil
dt_grant <- 15#input$grant_sel[1]#
                                                dt_grant2 <- owner_df$title[match(dt_grant,owner_df$grant_id)]#
                                                han_idx <- lapply(match(dt_grant,data_gdna_scores$GrantId),function(x) names(which(unlist(read_fst(data_gdna_binmat, from=x,to=x))>0)))#
                                                han_idx_fil <- data.frame(Handle=unique(unlist(han_idx)))
han_idx_fil
dt_grant <- 15#input$grant_sel[1]
dt_grant2 <- owner_df$title[match(dt_grant,owner_df$grant_id)]#
                                        han_idx <- lapply(match(dt_grant,data_gdna_scores$GrantId),function(x) names(which(unlist(read_fst(data_gdna_binmat, from=x,to=x))>0)))#
                                        han_idx_fil <- data.frame(Handle=unique(unlist(han_idx)))#
                                        if(nrow(han_idx_fil)>1) #
                                        {   #
                                            han_idx_fil$Group = paste0("Donated To ",sapply(apply(sapply(han_idx,function(x,y) y%in% x,y=han_idx_fil$Handle),1,function(x,y) y[x],y=dt_grant),paste0,collapse=", "))#
                                            han_idx_fil$GroupSize = apply(sapply(han_idx,function(x,y) y%in% x,y=han_idx_fil$Handle),1,sum)#
                                        }#
                                        han_idx_fil <- han_idx_fil[data_ddna_scores$Distance_Min[match(han_idx_fil$Handle,data_ddna_scores$Handle)]<=input$grant_ddna_network_cutoff,]
han_idx_fil
dt_grant <- input$grant_sel#
                                        dt_grant2 <- owner_df$title[match(dt_grant,owner_df$grant_id)]#
                                        han_idx <- lapply(match(dt_grant,data_gdna_scores$GrantId),function(x) names(which(unlist(read_fst(data_gdna_binmat, from=x,to=x))>0)))#
                                        han_idx_fil <- data.frame(Handle=unique(unlist(han_idx)))#
                                        if(nrow(han_idx_fil)>1) #
                                        {   #
                                            han_idx_fil$Group = paste0("Donated To ",sapply(apply(sapply(han_idx,function(x,y) y%in% x,y=han_idx_fil$Handle),1,function(x,y) y[x],y=dt_grant),paste0,collapse=", "))#
                                            han_idx_fil$GroupSize = apply(sapply(han_idx,function(x,y) y%in% x,y=han_idx_fil$Handle),1,sum)#
                                        }#
                                        han_idx_fil <- han_idx_fil[data_ddna_scores$Distance_Min[match(han_idx_fil$Handle,data_ddna_scores$Handle)]<=input$grant_ddna_network_cutoff,]#
                                        if(nrow(han_idx_fil)==0) gddna$nocluster <- TRUE
dt_grant <- 15
dt_grant2 <- owner_df$title[match(dt_grant,owner_df$grant_id)]#
                                        han_idx <- lapply(match(dt_grant,data_gdna_scores$GrantId),function(x) names(which(unlist(read_fst(data_gdna_binmat, from=x,to=x))>0)))#
                                        han_idx_fil <- data.frame(Handle=unique(unlist(han_idx)))#
                                        if(nrow(han_idx_fil)>1) #
                                        {   #
                                            han_idx_fil$Group = paste0("Donated To ",sapply(apply(sapply(han_idx,function(x,y) y%in% x,y=han_idx_fil$Handle),1,function(x,y) y[x],y=dt_grant),paste0,collapse=", "))#
                                            han_idx_fil$GroupSize = apply(sapply(han_idx,function(x,y) y%in% x,y=han_idx_fil$Handle),1,sum)#
                                        }#
                                        han_idx_fil <- han_idx_fil[data_ddna_scores$Distance_Min[match(han_idx_fil$Handle,data_ddna_scores$Handle)]<=input$grant_ddna_network_cutoff,]#
                                        if(nrow(han_idx_fil)==0) gddna$nocluster <- TRUE
dt_grant <- 15#
                                        dt_grant2 <- owner_df$title[match(dt_grant,owner_df$grant_id)]#
                                        han_idx <- lapply(match(dt_grant,data_gdna_scores$GrantId),function(x) names(which(unlist(read_fst(data_gdna_binmat, from=x,to=x))>0)))#
                                        han_idx_fil <- data.frame(Handle=unique(unlist(han_idx)))#
                                        if(nrow(han_idx_fil)>1) #
                                        {   #
                                            han_idx_fil$Group = paste0("Donated To ",sapply(apply(sapply(han_idx,function(x,y) y%in% x,y=han_idx_fil$Handle),1,function(x,y) y[x],y=dt_grant),paste0,collapse=", "))#
                                            han_idx_fil$GroupSize = apply(sapply(han_idx,function(x,y) y%in% x,y=han_idx_fil$Handle),1,sum)#
                                        }#
                                        han_idx_fil <- han_idx_fil[data_ddna_scores$Distance_Min[match(han_idx_fil$Handle,data_ddna_scores$Handle)]<=input$grant_ddna_network_cutoff,]#
                                        if(nrow(han_idx_fil)==0) gddna$nocluster <- TRUE
dt_grant <- 15#
                                        dt_grant2 <- owner_df$title[match(dt_grant,owner_df$grant_id)]#
                                        han_idx <- lapply(match(dt_grant,data_gdna_scores$GrantId),function(x) names(which(unlist(read_fst(data_gdna_binmat, from=x,to=x))>0)))#
                                        han_idx_fil <- data.frame(Handle=unique(unlist(han_idx)))#
                                        if(nrow(han_idx_fil)>1) #
                                        {   #
                                            han_idx_fil$Group = paste0("Donated To ",sapply(apply(sapply(han_idx,function(x,y) y%in% x,y=han_idx_fil$Handle),1,function(x,y) y[x],y=dt_grant),paste0,collapse=", "))#
                                            han_idx_fil$GroupSize = apply(sapply(han_idx,function(x,y) y%in% x,y=han_idx_fil$Handle),1,sum)#
                                        }#
                                        han_idx_fil <- han_idx_fil[data_ddna_scores$Distance_Min[match(han_idx_fil$Handle,data_ddna_scores$Handle)]<=input$grant_ddna_network_cutoff,]
han_idx_fil
input$grant_sel <- c("5719","7213","7219","6492")
dt_grant <- input$grant_sel#
                                        dt_grant2 <- owner_df$title[match(dt_grant,owner_df$grant_id)]
dt_grant2
selectizeInput
?selectizeInput
??selectizeInput