#+NAME: R_plot
#+BEGIN_SRC R :exports both :results output graphics :file r_comparison.png
# graph in R
library("ggplot2")
performance <- read.csv("comparison.csv", header=FALSE)$V1
df <- data.frame(resource = c("1node1core", "1node8core", "2node8core"), performance = performance)
p <- ggplot(data = df, aes(x=resource, y=performance)) +
     geom_bar(stat="identity", fill="steelblue") +
     theme_minimal() +
     ggtitle("Computation time (min) vs. Resource (type)")
p
#+END_SRC

#+NAME: python_plot
#+BEGIN_SRC python :exports both :results output graphics :file py_comparison.png
import matplotlib.pyplot as plt; plt.rcdefaults()
import matplotlib.pyplot as plt
import csv

objects = ['1node1core', '1node8core', '2node8core']
y_pos = list(range(0, len(objects)))

performance = []
with open('comparison.csv', newline='') as csvfile:
  reader = csv.reader(csvfile)
  for row in reader:
    f_row = float(row[0])
    performance.append(f_row)

plt.bar(y_pos, performance, align='center', alpha=0.5)
plt.xticks(y_pos, objects)
plt.ylabel('Time')
plt.title('Resource vs. Time')

plt.show()
#+END_SRC