import math
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import argparse

parser = argparse.ArgumentParser()
parser.add_argument("--density", "-d")

args=parser.parse_args()

columns = ["ID", "idx", "Mass", "Radius", "X", "Y", "Z", "vX", "vY", "vZ", "sX", "sY", "sZ", "Colour"]
deviations = []
time = []

for i in range (1,401):
    num = str(i).rjust(5, '0')
    file = "BTs/"+args.density+"/boom."+num+".bt"
    data = pd.read_csv(file, sep=' ', names=columns)
    data["X"] = data["X"]*1.5e8
    data["Y"] = data["Y"]*1.5e8
    data["Z"] = data["Z"]*1.5e8
    data["X2"] = data["X"]**2
    data["Y2"] = data["Y"]**2
    data["Z2"] = data["Z"]**2
    data["distance2"] = data["X2"]+data["Y2"]+data["Z2"]
    data["distance"] = data["distance2"]**0.5
    deviation = data["distance"].std()
    time.append(i)
    deviations.append(deviation)

del time[-1]
del time[-1]
firstDeriv=np.diff(deviations)
secondDeriv=np.diff(firstDeriv)

ax=plt.axes()
# ax.set_yscale("log")
ax.plot(time, secondDeriv)
plt.show()