about summary refs log tree commit diff
path: root/src/python
diff options
context:
space:
mode:
Diffstat (limited to 'src/python')
-rwxr-xr-xsrc/python/coord.py132
1 files changed, 75 insertions, 57 deletions
diff --git a/src/python/coord.py b/src/python/coord.py
index b033f9d..6cadf16 100755
--- a/src/python/coord.py
+++ b/src/python/coord.py
@@ -1,43 +1,68 @@
 #!/usr/bin/env python
 
 # import libraries
-import time
-import numpy as np
-import sys
-from subprocess import call
+import time                             # time how long operations take
+import numpy as np                      # advanced math
+import argparse                         # fancy parsing
+from multiprocessing import Process     # multiprocessing!
+import multiprocessing                  # mor multiprocessing (corecount)
+
+# get the amount of cores in the system
+cpu_count = multiprocessing.cpu_count()
+
+# generate a parser
+parser = argparse.ArgumentParser(
+    description="Star Coordinate Generator",
+    usage='./%(prog)s <number of stars> <path> [-l LOOKUP] [-r RANGE] [-m CORES] [-h]',
+)
+
+# add some arguments to the parser
+parser.add_argument("nos", help="Number of stars that should be generated")
+parser.add_argument("path", help="Path to the file where the coordinates of the stars should be saved")
+parser.add_argument("-l", dest="lookup", help="Define a custom lookuptable filepath", default="1e7")
+parser.add_argument("-r", dest="range", help="Define a custom range in where the stars should be generated", default="1e7")
+parser.add_argument("-m", dest="cores", help=f"Enable Multithreading with up to {cpu_count} cores", default="2")
+
+# extract the arguments for further use
+args = parser.parse_args()
 
 # define the number of stars that should be generated
-nos = int(sys.argv[1])
+nos = int(args.nos)
 
-# define various paths
-path = "data/2e7.csv"
-save_path = "stars/" + sys.argv[2] + ".csv"
+# define the file where the stars should be saved
+save_path = "stars/" + str(args.path) + ".csv"
 
-# define the random-value range [rho_min; rho_max]
-rand_min = 0
-rand_max = 1477.1586582000994
+# define the path to the lookuptable
+# (The default args.lookup value is 1e7)
+path = "data/" + str(args.lookup) + ".csv"
 
-# define the range (size) of the galaxy
-range_min = -1e8
-range_max = -range_min
+# define a varible storing how many cores should be user to compute
+cores = int(args.cores)
 
-# main function
-def main():
+def gen_stars(nos, threads):
+    # define the range (size) of the galaxy
+    range_max = int(float(args.range))
+    range_min = - range_max
+
+    # define the random-value range [rho_min; rho_max]
+    rand_min = 0
+    rand_max = 1477.1586582000994
 
-    # 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()
+    local_nos = int(nos / threads)
+
+    np.random.seed()
 
     # open the rho file
     with open(path) as data:
+
         # read out the lines from the rho file
         rho_file = data.readlines()
 
-        # for every star...
-        while(stars_kept < nos):
+        # the anticipated amount of stars is not reached...
+        while(stars_kept < local_nos):
 
             # generate the random star-coordinates
             x = np.random.uniform(range_min, range_max, size=1)
@@ -46,65 +71,58 @@ def main():
 
             # calculate the distance of the star to the center of the galaxy
             r = np.sqrt(pow(x, 2) + pow(y, 2) + pow(z, 2))
+            # print(round(int(r), 0))
 
-            # generate a random value in the range [rand_min; rand_max]
+            # generate a random value in the range [rand_n; rand_max]
             a = np.random.uniform(rand_min, rand_max, size=1)
 
             # read out the corresponding rho value from the lookuptable (rho-file)
-            b = float(rho_file[round(int(r / 10), 0)].split(", ")[1].strip("\n"))
+            # print(round(int(r), 0))
+            b = float(rho_file[round(int(r), 0)].split(", ")[1].strip("\n"))
 
             # if the random value is smaller than the corresponding rho value
             if(a < b):
 
+                # open the stars_data file and save the coordinates
                 with open(save_path, "a") as stars_data:
-                    stars_data.write(str(float(x)) + ", " + str(float(y)) + ", " + str(float(z)) + "\n")
+                    stars_data.write(str(x) + ", " + str(y) + ", " + str(z) + "\n")
 
-                # increment the stars_kept counter
+                # increment the star_kept counter
                 stars_kept += 1
-                print(stars_kept)
+                print(f"Stars Kept: {stars_kept}")
 
             else:
                 # increment the star_kicked counter
                 stars_kicked += 1
 
-    print("")
-    end = time.time()
-    whole_time = end - start
-    out = ">> Finished generating stars in " + str(whole_time) + " seconds\n"
-    print(out)
-
-    # time_all = whole_time + time_write_file
-    time_all = whole_time
-
-    time_min = round(time_all / 60, 1)
+# main function
+def main():
 
-    # print some stats
-    print("")
-    print("{:<20}{:<20}".format("Time (complete)", str(round(time_all, 4)) + " seconds"))
-    print("{:-<40}".format(""))
-    print("{:<20}{:<20}".format("Number of Stars", str(nos)))
-    print("{:<20}{:<20}".format("Stars Kicked:", str(stars_kicked)))
-    print("{:<20}{:<20}".format("Percent: ", str( nos / stars_kicked * 100 ) + "%"))
+    # start the timer
+    start = time.time()
 
-    hour = int( time_all // 3600 )
-    time_all = time_all % 3600
-    minutes = int( time_all // 60 )
-    time_all = time_all % 60
-    seconds = int( time_all )
+    # calculate how many stars each core should generate
+    # BUG: local_nos might be wrong because of int rounding down
+    local_nos = int(nos / cores) * cores
 
-    a = "stars/" + str(sys.argv[2]) + ".csv"
+    print(f"Generating {local_nos} Stars using the {path} lookuptable.")
 
-    time_a = str(hour) + ":" + str(minutes) + ":" + str(seconds)
-    b = "{:<20}{:<20}".format("Time (h:m:s)", time_a )
-    c = "{:<20}{:<20}".format("Number of Stars", str(nos))
-    d = "{:<20}{:<20}".format("Stars Kicked:", str(stars_kicked))
-    e = "{:<20}{:<20}".format("Percent: ", str( nos / stars_kicked * 100 ) + "%")
+    # define a base threads and stor it n times in a list
+    threads = [Process(target=gen_stars, args=(nos, cores, )) for i in range(0, cores)]
 
-    f = a + "\n" + b + "\n" + c + "\n" + d + "\n" + e
+    # start the threads in the lsit
+    for thread in threads:
+        thread.start()
 
-    call(["telegram-send", "--pre", str(f) ])
-    call(["telegram-send", "-f", str(a) ])
+    # join the threads
+    for thread in threads:
+        thread.join()
 
+    # time stuff
+    end = time.time()
+    time_all = end - start
+    out = ">> Finished generating stars in " + str(time_all) + " seconds\n"
+    print(out)
 
 if __name__ == "__main__":
     main()