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

columns = ["ID", "idx", "Mass", "Radius", "X", "Y", "Z", "vX", "vY", "vZ", "sX", "sY", "sZ", "Colour"]
deviations = []
distances = []
densities = ["300","350","400","450","500","550","600","650","700"]
breakUpDistances = []

for density in densities:
    densityDeviations = []
    time = []
    for i in range (25,270):
        num = str(i).rjust(5, '0')
        file = "BTs/High-Res-"+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()
        distance = data["distance"].mean()
        time.append(i)
        densityDeviations.append(deviation)
        distances.append(distance)

    deviations.append(densityDeviations)

ax=plt.axes()
# ax.set_yscale("log")
ax.plot(time, deviations[0],label="300")
ax.plot(time, deviations[1],label="350")
ax.plot(time, deviations[2],label="400")
ax.plot(time, deviations[3],label="450")
ax.plot(time, deviations[4],label="500")
ax.plot(time, deviations[5],label="550")
ax.plot(time, deviations[6],label="600")
ax.plot(time, deviations[7],label="650")
ax.plot(time, deviations[8],label="700")
ax.legend()
plt.show()