diff --git a/Modified Sequent Peak Algorithm (mSPA)/SPA.R b/Modified Sequent Peak Algorithm (mSPA)/SPA.R
index 675c43048576e1777c0218371568c557651ff435..2b820bb938a7bffcd037320e93addbbc694b213c 100644
--- a/Modified Sequent Peak Algorithm (mSPA)/SPA.R	
+++ b/Modified Sequent Peak Algorithm (mSPA)/SPA.R	
@@ -1,27 +1,10 @@
-library("pacman")
-library(hydroTSM)
-library(reshape2)
-pacman::p_load(
-  pacman,
-  dplyr,
-  GGally,
-  ggplot2,
-  ggthemes,
-  ggvis,
-  httr,
-  lubridate,
-  plotly,
-  rio,
-  rmarkdown,
-  shiny,
-  stringr,
-  tidyr
-)
+library(ggplot2)
+library(readr)
 
 
 data <- readr::read_delim(
   file = "https://raw.githubusercontent.com/infohquan/link/master/inputdata_b.txt", 
-  delim = "\t"
+  delim = "\t", col_names = c("inflow", "release", "precip", "evapo", "downstreamFlow")
 )
 
 time <-
@@ -43,11 +26,11 @@ year <-
     "%Y"
   ))
 n <- NROW(na.omit(data))
-Inflow <- data[, 1]
-dem <- data[, 2]
-prec <- data[, 3]
-eva  <- data[, 4]
-netev <- (data[, 4] - data[, 3]) / 1000
+Inflow <- data$inflow
+dem <- data$release
+prec <- data$precip
+eva  <- data$evapo
+netev <- (data$evapo - data$precip) / 1000
 rule_curve <- c(34, 50, 63, 73, 77, 79, 80, 63, 46, 29, 12, 21)
 DS <- rep(8.5, 12)
 capacity <-  rep(82.5, 12)
@@ -155,7 +138,8 @@ result$Month = factor(
 result.gather <-
   gather(result, key = "Rule Curve", value = IndexValue, -Month)
 
-ggplot(result.gather,
+print(
+  ggplot2::ggplot(result.gather,
        aes(Month, IndexValue, group = `Rule Curve`, color = `Rule Curve`)) +
   ylim(0, 85) +
   geom_line(aes(y = IndexValue), lwd = 1.2) +
@@ -164,3 +148,4 @@ ggplot(result.gather,
        x = "") + theme_few(base_size = 20) +
   scale_color_brewer(palette = "Set2") +
   theme(plot.title = element_text(hjust = 0.5))
+)
\ No newline at end of file