dflist,d = read_in_datafiles('file20.txt')
dname = sorted(d.values())
dflist = stars_outside_2HMR(dflist,dname)
#%% print the count the number of stars outside 2xHMR in a snapshot....
print (dname[5])
print (dflist[5].loc[10]['escaped'].value_counts())
#%%
dflist = velocity_elements(dflist,dname)
for n in range(20):
dflist[n]['3D-vel'] = (np.sqrt(dflist[n]['velx']**2.+dflist[n]['vely']**2.+dflist[n]['velz']**2.))
dflist[n]['3D-veldist'] = (np.sqrt(dflist[n]['xvel']**2.+dflist[n]['yvel']**2.+dflist[n]['zvel']**2.))
dflist[n]['PM-vel'] = (np.sqrt(dflist[n]['velx']**2.+dflist[n]['vely']**2.))
dflist[n]['PM-veldist'] = (np.sqrt(dflist[n]['xvel']**2.+dflist[n]['yvel']**2.))
dflist[n].ESC = (dflist[n].loc[dflist[n]['escaped'] == True])
ESClist = [dflist[0].ESC, dflist[1].ESC, dflist[2].ESC, dflist[3].ESC, dflist[4].ESC,dflist[5].ESC,dflist[6].ESC,dflist[7].ESC,dflist[8].ESC,dflist[9].ESC,dflist[10].ESC, \
dflist[11].ESC, dflist[12].ESC, dflist[13].ESC, dflist[14].ESC, dflist[15].ESC, dflist[16].ESC, dflist[17].ESC, dflist[18].ESC,dflist[19].ESC]
ESC = pd.concat(ESClist)
#%% plots umulative velocity distribution for unbound stars at 5 Myr as PM-velocity and 3D-velocity
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri May 18 13:48:50 2018
@author: php17cs
"""
import numpy as np
from function_file import read_in_any_datafiles, velocity_elements, plots_legend
#reads in the .dat files from an inputfile list
dflist, dname, nlines = read_in_any_datafiles('file.txt')
#calculates the velocity (distance travelled/snapshot length
dflist = velocity_elements(dflist, dname, nlines)
#creates the legend for for plots of single simulations
legend = plots_legend(dname)
j = 50
velocity = 'PM-velxy'
dflist_mean = np.empty(1000)
for line in range(1000):
dflist_sumlist = []
for n in range(nlines):
dflist_sumlist.append(
(dflist[n].loc[j].sort_values(velocity)[velocity]).iloc[line])
dflist_mean[line] = (np.mean(dflist_sumlist))
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import AutoMinorLocator
#import F_COD_Radius_Nstars as CODRN #turn this on, if COD-correcion is required.
from function_file import read_in_any_datafiles, velocity_elements, energy_stars, stars_in_outside_2HMR
dflist, dname, nlines = read_in_any_datafiles(
'file.txt') #this reads in the .dat files from an inputfile list
dflist = energy_stars(
dflist, dname, nlines
) #this calculates the energy of each star in each snapshot an simulation and adds this in a column
dflist = velocity_elements(
dflist, dname, nlines
) #this calculates the velocity by using the distance travelled between each snapshot and divides it by snapshot length - this is an alternative to the provided velocities from the simulation
dflist = stars_in_outside_2HMR(
dflist, dname, nlines
) # this calculates the half-mass radius based on centre of density corrected locations and then adds a column identifying if the stars are inside or outside 2*HMR
# different velocity distributions are calculated, e.g. 3D and PM for the original velocity data velx - velz and the velocities calculated by using the distance travelled between each snapshot.
#both are expressed in km/s
#%% this cell produces dataframes for each simulation containing the unbound/escaped stars,
# this cell also creates dataframes for each simulation containing the high-mass and low-mass unbound and escaped stars.
dflistUB = []
dflistESC = []
dflistHMUB = []
dflistHMESC = []
dflistHMall = []