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diff --git a/src/README.md b/src/README.md
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+# README
+
+### workflow:
+
+---
+
+#### Generate the lookuptable
+
+
+    $ ./lookup.py <number of values> <filename>
+
+- the __number of values__ can be given using the scientific notaion e.g. 1e7.
+- the __filename__ should not overlap with any existing filename
+
+---
+
+#### Generate the coordinates
+
+
+    $ ./coord.py <number of stars>
+
+
+#### Display the stars using Blender
+
+    $ blender --python view.py
diff --git a/src/coord.py b/src/coord.py
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+++ b/src/coord.py
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+#!/usr/bin/env python
+
+# import libraries
+import time
+import numpy as np
+import sys
+
+# define the number of stars that should be generated
+# (this is not the final value -> the final value is about 1000 times smaller)
+nos = int(sys.argv[1])
+
+# define some arrays for storing the values
+arr_stars = np.zeros((int(nos), 3))
+arr_r = np.zeros((int(nos), 1))
+arr_saved_stars = np.zeros((int(nos), 3))
+
+# define various paths
+path = "data/rho6.csv"
+save_path = "stars/star18.csv"
+# star13 -> 586 stars
+
+# define the random-value range [rho_min; rho_max]
+rand_min = 0
+rand_max = 1477.1586582000994
+
+# define the range (size) of the galaxy
+range_min = -1e7
+range_max = 1e7
+
+# main function
+def main():
+
+    time_start_gen_array = time.time()
+
+    # generate n=nos stars
+    for i in range(0, nos):
+
+        # generate the random values
+        arr_stars[i][0] = np.random.uniform(range_min, range_max, size=1)
+        arr_stars[i][1] = np.random.uniform(range_min, range_max, size=1)
+        arr_stars[i][2] = np.random.uniform(range_min, range_max, size=1)
+
+        # calculate the distance of the star to the center of the galaxy
+        arr_r[i][0] = np.sqrt(pow(arr_stars[i][0], 2) + pow(arr_stars[i][1], 2) + pow(arr_stars[i][2], 2))
+
+    # print the randomly generated arrays
+    print(arr_stars)
+    print(arr_r)
+
+    time_end_gen_array = time.time()
+    time_all_gen_array = time_end_gen_array - time_start_gen_array
+    # define the variables for storing the amount of stars kept or kicked away
+    stars_kept = 0
+    stars_kicked = 0
+
+    # start the timer
+    start = time.time()
+
+    # open the rho file
+    with open(path) as data:
+
+        # read out the lines from the rho file
+        rho_file = data.readlines()
+
+        # for every star...
+        for i in range(0, nos):
+            # print(i)
+
+            # random value
+            a = np.random.uniform(rand_min, rand_max, size=1)
+
+            # corresponding rho value
+            b = float(rho_file[int(round(arr_r[i][0], 0))].split(", ")[1].strip("\n"))
+
+            # if the random value is smaller than the corresponding rho value
+            if( a < b):
+                # add the coordinate to arr_saved_stars
+                arr_saved_stars[stars_kept][0] = arr_stars[i][0]
+                arr_saved_stars[stars_kept][1] = arr_stars[i][1]
+                arr_saved_stars[stars_kept][2] = arr_stars[i][2]
+
+                # increment the star_kept counter
+                stars_kept += 1
+
+            else:
+                # increment the star_kicked counter
+                stars_kicked += 1
+
+            if(i % (nos/(nos/10)) == 0):
+                if(i != 0):
+                    a = str(round(i / nos * 100, 1)) + "%"
+                    time_temp = time.time()
+                    time_past = round(time_temp - start, 2)
+                    print("{:<10}{:<20}".format(a, time_past))
+
+    print("")
+    end = time.time()
+    whole_time = end - start
+    print(">> Finished generating stars in " + str(whole_time) + " seconds\n")
+
+    start_delete_rows = time.time()
+
+    # delete all unused rows
+    print(">> Deleting unused rows in the arr_saved_stars array")
+    # for i in range(nos - stars_kicked, nos):
+    #     np.delete(arr_saved_stars, (i), axis=0)
+    end_delete_rows = time.time()
+    time_delete_rows = end_delete_rows - start_delete_rows
+    print(">> Finished deleting stars in " + str(round(time_delete_rows, 4)) + " seconds \n")
+
+    start_write_file = time.time()
+
+    # write the star coordinates to a file
+    print(">> Writing the star-data to " + save_path)
+    with open(save_path, "a") as stars_data:
+        for i in range(0, nos):
+            x = arr_saved_stars[i][0]
+            y = arr_saved_stars[i][1]
+            z = arr_saved_stars[i][2]
+
+            stars_data.write(str(x) + ", " + str(y) + ", " + str(z) + "\n")
+
+    end_write_file = time.time()
+    time_write_file = end_write_file - start_write_file
+    print(">> Finished writing star-data to " + save_path + " in " + str(round(time_write_file, 4)) + " seconds\n")
+
+
+    stars_percent = stars_kept / nos * 100
+
+    time_all = whole_time + time_write_file + time_delete_rows
+
+    # print some stats
+    print("")
+    print("{:<30}{:<30}".format("Time (complete)", str(round(time_all, 4)) + " seconds"))
+    print("{:<30}{:<30}".format("Time (gen arrays)", str(round(time_all_gen_array, 4)) + " seconds"))
+    print("{:<30}{:<30}".format("Time (calculate stars)", str(round(whole_time, 4)) + " seconds"))
+    print("{:<30}{:<30}".format("Time (delete rows)", str(round(time_delete_rows, 4)) + " seconds"))
+    print("{:<30}{:<30}".format("Time (write to file)", str(round(time_write_file, 4)) + " seconds"))
+    print("{:-<40}".format(""))
+    print("{:<20}{:<20}".format("Number of Stars", str(nos)))
+    print("{:<20}{:<20}".format("Stars Kept:", str(stars_kept)))
+    print("{:<20}{:<20}".format("Stars Kicked:", str(stars_kicked)))
+    print("{:<20}{:<20}".format("Stars Percent", str(round(stars_percent, 4)) + "%"))
+
+if __name__ == "__main__":
+    main()
diff --git a/src/lookup.py b/src/lookup.py
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+++ b/src/lookup.py
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+#!/usr/bin/env python
+
+# Import some libraries
+import math
+import numpy as np
+import matplotlib.pyplot as plt
+import time
+import os
+import sys
+
+# Defining some variables
+sigma = 200
+f_0 = 0.1
+R_s = 1e4
+
+# Defining some constants
+pi = math.pi
+e = math.e
+G = 4.302e-3
+
+# rho function
+def rho(r):
+    a = (1) / (math.sqrt( 2 * pi ) * sigma )
+    b = math.exp( - (phi(r) / sigma ** 2 ) )
+    return a * b
+
+# phi function
+def phi(x):
+    if x == 0:
+        return -4 * pi * f_0 * G * R_s**2
+    else:
+        a = - ( 4 * pi * G * f_0 * R_s ** 3 ) / x
+        b = np.log(1. + (x / R_s) )
+        return a * b
+
+# Defining a list to store the rho-values for plotting
+list_rho = []
+
+# Define the path to where the data should be stored
+path = 'data/' + str(sys.argv[2]) + '.csv'
+
+# get the start time
+start = time.time()
+
+# define the number of stars using system arguments
+stars = int(float(sys.argv[1]))
+
+# open the file where the information should be written to
+with open(path, "a") as data:
+
+    # for every star
+    for i in range(0, stars):
+
+        # calculate the rho value
+        rho_i = rho(i/10)
+
+        # append the rho value to list_rho for plotting
+        # list_rho.append(rho_i)
+
+        # print the distance to the center of the universe and the rho value to
+        # the user
+        print(str(i) + ", " + str(rho_i))
+
+        # write the data into the file
+        data.write(str(i) + ", " + str(rho_i) + "\n")
+
+# get the end time
+end = time.time()
+
+# calculate the runtime
+runtime = end - start
+
+# print some information to the user
+print("\n Runtime: ", end="")
+print(str(runtime) + " seconds")
+
+print(" Stars: " + str(stars))
+
+print(" Rho-values per second: ", end="")
+print(str(stars / runtime))
+
+# plt.plot(list_rho)
+# plt.xscale('log')
+# plt.yscale('log')
+# plt.grid()
+# plt.show()
diff --git a/src/view.py b/src/view.py
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+++ b/src/view.py
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+import bpy
+from numpy import genfromtxt
+import os
+import sys
+
+directory = "stars/"
+# # print(directory)
+#
+files = ["final_star15.csv"]
+
+# print("### \n\n")
+#
+# for data_file in os.listdir(directory):
+#     files.append(data_file)
+#     print(data_file)
+#
+# print("### \n\n")
+
+for data in files:
+    path = str(directory) + str(data)
+    print(path)
+
+    verts = genfromtxt(path, delimiter=', ', skip_header=0)
+
+    print(verts)
+
+# verts = [(-1.0, 1.0, 0.0), (-1.0, -1.0, 0.0), (1.0, -1.0, 0.0), (1.0, 1.0, 0.0)]
+
+    # create mesh and object
+    mesh = bpy.data.meshes.new(data)
+    object = bpy.data.objects.new(data,mesh)
+
+    # set mesh location
+    object.location = bpy.context.scene.cursor_location
+    bpy.context.scene.objects.link(object)
+
+    # create mesh from python data
+    mesh.from_pydata(verts,[],[])
+    mesh.update(calc_edges=True)
+
+    bpy.ops.object.select_all(action='SELECT')
+
+for area in bpy.context.screen.areas:
+    if area.type == 'VIEW_3D':
+        for region in area.regions:
+            if region.type == 'WINDOW':
+                override = {'area': area, 'region': region, 'edit_object': bpy.context.edit_object}
+bpy.ops.view3d.view_all(override)