64 lines
1.8 KiB
Python
64 lines
1.8 KiB
Python
import math
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import pandas as pd
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import numpy as np
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import matplotlib.pyplot as plt
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columns = ["ID", "idx", "Mass", "Radius", "X", "Y", "Z", "vX", "vY", "vZ", "sX", "sY", "sZ", "Colour"]
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deviations = []
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distances = []
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densities = [300,350,400,450,500,550,600,650,700]
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breakupDistances = []
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theoreticalDensities=np.linspace(300,700,num=100)
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theoreticalDistances=[]
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for i in theoreticalDensities:
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distance=2.44*69911*(1330/i)**(1/3)
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distance=distance/2
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theoreticalDistances.append(distance)
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for density in densities:
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densityDeviations = []
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time = []
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for i in range (25,270):
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num = str(i).rjust(5, '0')
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file = "BTs/High-Res-"+str(density)+"/boom."+num+".bt"
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data = pd.read_csv(file, sep=' ', names=columns)
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data["X"] = data["X"]*1.5e8
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data["Y"] = data["Y"]*1.5e8
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data["Z"] = data["Z"]*1.5e8
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data["X2"] = data["X"]**2
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data["Y2"] = data["Y"]**2
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data["Z2"] = data["Z"]**2
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data["distance2"] = data["X2"]+data["Y2"]+data["Z2"]
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data["distance"] = data["distance2"]**0.5
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deviation = data["distance"].std()
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distance = data["distance"].mean()
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time.append(i)
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densityDeviations.append(deviation)
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distances.append(distance)
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del time[-1]
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del time[-1]
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firstDeriv=np.diff(densityDeviations)
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secondDeriv=np.diff(firstDeriv)
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maxIndex=np.argmax(secondDeriv)
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breakupDistance=distances[maxIndex]
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breakupDistances.append(breakupDistance)
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# oneOverDensities = []
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# for i in densities:
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# oneOver = 1/i
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# oneOverDensities.append(oneOver)
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# breakupDistances3 = []
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# for i in breakupDistances:
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# cubed = i**3
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# breakupDistances3.append(cubed)
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ax=plt.axes()
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# ax.set_yscale("log")
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ax.plot(densities, breakupDistances)
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ax.plot(theoreticalDensities, theoreticalDistances)
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plt.show()
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