From d0f19b8bc7ab11449cea028106504cacecd94f66 Mon Sep 17 00:00:00 2001 From: hanemile Date: Mon, 19 Mar 2018 20:47:13 +0100 Subject: cleaned up --- src/a.out | Bin 13200 -> 0 bytes src/c/lookup.c | 74 + src/coord.py | 138 -- src/data/pizzablech_11360.csv | 3 - src/data/pizzablech_19005.csv | 3 - src/data/pizzablech_21823.csv | 1 - src/data/pizzablech_27529.csv | 1 - src/data/pizzablech_32000.csv | 2 - src/data/pizzablech_32315.csv | 2 - src/data/pizzablech_7274.csv | 1 - src/data/pizzablech_8705.csv | 1 - src/data/pizzablech_924.csv | 1 - src/go/coords.go | 18 + src/go/data/100.csv | 5 + src/go/go | Bin 0 -> 2025101 bytes src/go/lookup | Bin 0 -> 2025566 bytes src/go/lookup.go | 54 + src/lookup.c | 74 - src/lookup.py | 86 -- src/python/average_force.py | 109 -- src/python/cells.py | 62 - src/python/coord.py | 21 +- src/python/coord_clean.py | 117 -- src/python/draw.py | 20 - src/python/draw/draw.py | 20 + src/python/draw/plot_lookuptable.py | 21 + src/python/experiments/nn.py | 60 + src/python/experiments/view.py | 48 + src/python/lookup.py | 42 +- src/python/nn.py | 60 - src/python/plot_lookuptable.py | 21 - src/python/spiral/average_force.py | 109 ++ src/python/spiral/cells.py | 62 + src/python/stars/test.csv | 2656 +++++++++++++++++++++++++++++++++++ src/python/stars/test2.csv | 50 + src/python/stars/test3.csv | 377 +++++ src/python/view.py | 30 - src/testFile.csv | 1000 ------------- src/view.py | 48 - 39 files changed, 3587 insertions(+), 1810 deletions(-) delete mode 100755 src/a.out create mode 100644 src/c/lookup.c delete mode 100755 src/coord.py delete mode 100644 src/data/pizzablech_11360.csv delete mode 100644 src/data/pizzablech_19005.csv delete mode 100644 src/data/pizzablech_21823.csv delete mode 100644 src/data/pizzablech_27529.csv delete mode 100644 src/data/pizzablech_32000.csv delete mode 100644 src/data/pizzablech_32315.csv delete mode 100644 src/data/pizzablech_7274.csv delete mode 100644 src/data/pizzablech_8705.csv delete mode 100644 src/data/pizzablech_924.csv create mode 100644 src/go/coords.go create mode 100644 src/go/data/100.csv create mode 100755 src/go/go create mode 100755 src/go/lookup create mode 100644 src/go/lookup.go delete mode 100644 src/lookup.c delete mode 100755 src/lookup.py delete mode 100755 src/python/average_force.py delete mode 100755 src/python/cells.py delete mode 100644 src/python/coord_clean.py delete mode 100644 src/python/draw.py create mode 100644 src/python/draw/draw.py create mode 100755 src/python/draw/plot_lookuptable.py create mode 100755 src/python/experiments/nn.py create mode 100644 src/python/experiments/view.py delete mode 100755 src/python/nn.py delete mode 100755 src/python/plot_lookuptable.py create mode 100755 src/python/spiral/average_force.py create mode 100755 src/python/spiral/cells.py create mode 100644 src/python/stars/test.csv create mode 100644 src/python/stars/test2.csv create mode 100644 src/python/stars/test3.csv delete mode 100644 src/python/view.py delete mode 100644 src/testFile.csv delete mode 100644 src/view.py (limited to 'src') diff --git a/src/a.out b/src/a.out deleted file mode 100755 index 6a6368d..0000000 Binary files a/src/a.out and /dev/null differ diff --git a/src/c/lookup.c b/src/c/lookup.c new file mode 100644 index 0000000..01b5508 --- /dev/null +++ b/src/c/lookup.c @@ -0,0 +1,74 @@ +#include +#include +#include + +// Define some variables +int sigma = 200; +float f_0 = 0.1; +float R_s = 1e4; + +// Define some constants +float pi = M_PI; +float e = M_E; +float G = 4.302e-3; + +// Define the directory where the data shall be stored + +// Prototype +float rho(float r); +float phi(float x); + +int main(int argc, char *argv[] ){ + if( argc == 2 ) { + printf("Generating %s Values...\n", argv[1]); + + FILE * fp = fopen("testFile.csv", "w+"); + if(fp == NULL){ + printf("Error opening the file!\n"); + exit(1); + } + + int x = atoi(argv[1]); + + for(int i = 0; i < x; i++){ + fprintf(fp, "%d, %f\n", i, phi(i)); + } + + // for(int i = 0; i < 1e7; i = i + 1e4){ + // printf("%s, %f\n", i, phi(i)); + // } + + fclose(fp); + + } + else if( argc > 2 ) { + printf("Too many arguments supplied.\n"); + return 0; + } + else { + printf("One argument expected.\n"); + return 0; + } + + return 0; +} + +// Define rho function +float rho(float r){ + float a = (1) / ( sqrt(2 * pi) * sigma); + float b = exp( - (phi(r) / pow(sigma, 2) )); + return a; +} + +// Define phi function +float phi(float x){ + if(x == 0) { + float a = -4 * pi * f_0 * G * pow(R_s, 2); + return(a); + } + else { + float a = - (4 * pi * G * f_0 * pow(R_s, 3) / x); + float b = log(1 + (x / R_s) ); + return(a * b); + } +} diff --git a/src/coord.py b/src/coord.py deleted file mode 100755 index 0a7a9d4..0000000 --- a/src/coord.py +++ /dev/null @@ -1,138 +0,0 @@ -#!/usr/bin/env python - -# import libraries -import time -import numpy as np -import sys -from subprocess import call - -# define the number of stars that should be generated -nos = int(sys.argv[1]) - -# define some arrays for storing the values -arr_stars = np.zeros((int(nos), 3)) -arr_saved_stars = np.zeros((int(nos), 3)) - -# define various paths -path = "data/2e7.csv" -save_path = "stars/" + sys.argv[2] + ".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(): - - # define the variables for storing the amount of stars kept or kicked away - stars_kept = 0 - stars_kicked = 0 - i = 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): - while(stars_kept < nos): - - # generate the random star-coordinates - x = np.random.uniform(range_min, range_max, size=1) - y = np.random.uniform(range_min, range_max, size=1) - z = np.random.uniform(range_min, range_max, size=1) - - # 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] - 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), 0)].split(", ")[1].strip("\n")) - - # print("{:<5}{:<20}{:<20}{:<20}{:<20}{:<20}{:<20}".format(str(stars_kept), str(x), str(y), str(z), str(a), str(b), str(r))) - - # 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] = x - arr_saved_stars[stars_kept][1] = y - arr_saved_stars[stars_kept][2] = z - - # increment the star_kept counter - stars_kept += 1 - print(stars_kept) - - else: - # increment the star_kicked counter - stars_kicked += 1 - - # increment i - i = i + 1 - - print("") - end = time.time() - whole_time = end - start - out = ">> Finished generating stars in " + str(whole_time) + " seconds\n" - print(out) - - # write the star coordinates to a file - start_write_file = time.time() - 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 - out = ">> Finished writing star-data to " + save_path + " in " + str(round(time_write_file, 4)) + " seconds\n" - print(out) - - time_all = whole_time + time_write_file - - time_min = round(time_all / 60, 1) - - # 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 ) + "%")) - - hour = int( time_all // 3600 ) - time_all = time_all % 3600 - minutes = int( time_all // 60 ) - time_all = time_all % 60 - seconds = int( time_all ) - - a = path - - 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 ) + "%") - - f = a + "\n" + b + "\n" + c + "\n" + d + "\n" + e - - call(["telegram-send", "--pre", str(f) ]) - -if __name__ == "__main__": - main() diff --git a/src/data/pizzablech_11360.csv b/src/data/pizzablech_11360.csv deleted file mode 100644 index 227282f..0000000 --- a/src/data/pizzablech_11360.csv +++ /dev/null @@ -1,3 +0,0 @@ - 1774.72102827, 1178.10406515 --734.67958771,-1207.38476906 --913.24944432,-5918.62094729 diff --git a/src/data/pizzablech_19005.csv b/src/data/pizzablech_19005.csv deleted file mode 100644 index 0d1e896..0000000 --- a/src/data/pizzablech_19005.csv +++ /dev/null @@ -1,3 +0,0 @@ - 17265.79511097,-3162.68726106 --2369.0947882, 320.72212317 - 49080.10883372, 62913.02531819 diff --git a/src/data/pizzablech_21823.csv b/src/data/pizzablech_21823.csv deleted file mode 100644 index 20baaa5..0000000 --- a/src/data/pizzablech_21823.csv +++ /dev/null @@ -1 +0,0 @@ - 20678.62453795,-120221.31056653 diff --git a/src/data/pizzablech_27529.csv b/src/data/pizzablech_27529.csv deleted file mode 100644 index 8a84290..0000000 --- a/src/data/pizzablech_27529.csv +++ /dev/null @@ -1 +0,0 @@ --84.27519625, 2799.48771798 diff --git a/src/data/pizzablech_32000.csv b/src/data/pizzablech_32000.csv deleted file mode 100644 index 8afae9d..0000000 --- a/src/data/pizzablech_32000.csv +++ /dev/null @@ -1,2 +0,0 @@ - 14077.72819654, 15732.23314295 - 4779.21771898,-32486.50451903 diff --git a/src/data/pizzablech_32315.csv b/src/data/pizzablech_32315.csv deleted file mode 100644 index 0aa0951..0000000 --- a/src/data/pizzablech_32315.csv +++ /dev/null @@ -1,2 +0,0 @@ - 3914.51482843,-47.19622038 - 104001.67675349, 87348.92176592 diff --git a/src/data/pizzablech_7274.csv b/src/data/pizzablech_7274.csv deleted file mode 100644 index 2101fa4..0000000 --- a/src/data/pizzablech_7274.csv +++ /dev/null @@ -1 +0,0 @@ - 1384.895152, 883.74479782 diff --git a/src/data/pizzablech_8705.csv b/src/data/pizzablech_8705.csv deleted file mode 100644 index 2869ef9..0000000 --- a/src/data/pizzablech_8705.csv +++ /dev/null @@ -1 +0,0 @@ --1332.03040452,-1942.03814714 diff --git a/src/data/pizzablech_924.csv b/src/data/pizzablech_924.csv deleted file mode 100644 index 8dbeac9..0000000 --- a/src/data/pizzablech_924.csv +++ /dev/null @@ -1 +0,0 @@ --787.29212918, 3181.78632621 diff --git a/src/go/coords.go b/src/go/coords.go new file mode 100644 index 0000000..819f36f --- /dev/null +++ b/src/go/coords.go @@ -0,0 +1,18 @@ +// Generate Star coordinates using a custom function + +// arg1 = number of stars +// arg2 = save path + +package main + +import ( + "fmt" + "os" +) + +func main(){ + + arguments := os.Args[1:] + + fmt.Println(arguments) +} diff --git a/src/go/data/100.csv b/src/go/data/100.csv new file mode 100644 index 0000000..eea675d --- /dev/null +++ b/src/go/data/100.csv @@ -0,0 +1,5 @@ +This is test content +If this is displayed, the software is working! +\o/ + | +/ \ diff --git a/src/go/go b/src/go/go new file mode 100755 index 0000000..43dbd99 Binary files /dev/null and b/src/go/go differ diff --git a/src/go/lookup b/src/go/lookup new file mode 100755 index 0000000..03c8927 Binary files /dev/null and b/src/go/lookup differ diff --git a/src/go/lookup.go b/src/go/lookup.go new file mode 100644 index 0000000..c222de5 --- /dev/null +++ b/src/go/lookup.go @@ -0,0 +1,54 @@ +// ./lookup.py + +package main + +import ( + "fmt" // printing + // "os" // system arguments + "math" +) + +const sigma = 200 +const f_0 = 0.1 +const R_s = 1e4 +const pi = 3.141592 +// e = math.e +const G = 4.302e-3 + +func rho(r int) float64 { + var a float64 = (1000) / (math.Sqrt( 2 * pi ) * sigma ) + var b float64 = r / sigma * sigma + var c float64 = math.Exp(float64(b)) + var d float64 = float64(a) * float64(c) + return d +} + +// # rho function +// def rho(r): +// a = (1) / (math.sqrt( 2 * pi ) * sigma ) +// b = math.exp( - (phi(r) / sigma ** 2 ) ) +// return a * b + +// func phi(x int) float64 { +// // if x == 0{ +// // return -4 * pi * f_0 * G * (R_s * R_s) +// // } else { +// // a := - ( 4 * pi * G * f_0 * (R_s * R_s * R_s) ) / x +// // b := 1 + (x / R_s) +// // c := math.Log(b) +// // d := a * b +// // return d +// // } +// } + +func main(){ + // nos := os.Args[1] + // save := "/data/" + string(os.Args[2]) + ".csv" + + fmt.Println(float64(rho(1e6))) + fmt.Println(float64(rho(3e6))) + fmt.Println(float64(rho(5e6))) + fmt.Println(float64(rho(7e6))) + fmt.Println(float64(rho(9e6))) + +} diff --git a/src/lookup.c b/src/lookup.c deleted file mode 100644 index 01b5508..0000000 --- a/src/lookup.c +++ /dev/null @@ -1,74 +0,0 @@ -#include -#include -#include - -// Define some variables -int sigma = 200; -float f_0 = 0.1; -float R_s = 1e4; - -// Define some constants -float pi = M_PI; -float e = M_E; -float G = 4.302e-3; - -// Define the directory where the data shall be stored - -// Prototype -float rho(float r); -float phi(float x); - -int main(int argc, char *argv[] ){ - if( argc == 2 ) { - printf("Generating %s Values...\n", argv[1]); - - FILE * fp = fopen("testFile.csv", "w+"); - if(fp == NULL){ - printf("Error opening the file!\n"); - exit(1); - } - - int x = atoi(argv[1]); - - for(int i = 0; i < x; i++){ - fprintf(fp, "%d, %f\n", i, phi(i)); - } - - // for(int i = 0; i < 1e7; i = i + 1e4){ - // printf("%s, %f\n", i, phi(i)); - // } - - fclose(fp); - - } - else if( argc > 2 ) { - printf("Too many arguments supplied.\n"); - return 0; - } - else { - printf("One argument expected.\n"); - return 0; - } - - return 0; -} - -// Define rho function -float rho(float r){ - float a = (1) / ( sqrt(2 * pi) * sigma); - float b = exp( - (phi(r) / pow(sigma, 2) )); - return a; -} - -// Define phi function -float phi(float x){ - if(x == 0) { - float a = -4 * pi * f_0 * G * pow(R_s, 2); - return(a); - } - else { - float a = - (4 * pi * G * f_0 * pow(R_s, 3) / x); - float b = log(1 + (x / R_s) ); - return(a * b); - } -} diff --git a/src/lookup.py b/src/lookup.py deleted file mode 100755 index 52e1966..0000000 --- a/src/lookup.py +++ /dev/null @@ -1,86 +0,0 @@ -#!/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/python/average_force.py b/src/python/average_force.py deleted file mode 100755 index a3a3146..0000000 --- a/src/python/average_force.py +++ /dev/null @@ -1,109 +0,0 @@ -#!/usr/bin/env python - -# import stuff -import sys -import matplotlib.pyplot as plt -import numpy as np -import time -from subprocess import call - -# define from where to get the star data -path = "stars/" + sys.argv[1] + ".csv" - -# define a list to store the coordinates -listx = [] -listy = [] -listz = [] -list_force = [] - -# define constants -G = 6.674e-11 - -def glaw(m1, m2, a1, b1): - a = m1 * m2 - b = np.power(a1 - b1, 2) - c = np.sqrt(b) - d = a / c - e = G * d - return e - -# start the timer -start = time.time() - -# open the data file -with open(path) as f: - - # read the individial lines from the data file - data = f.readlines() - - # for each line - for i in range(0, len(data)): - - # parse the first value in each line - v_i_x = data[i].split(", ")[0] - v_i_y = data[i].split(", ")[1] - v_i_z = data[i].split(", ")[2] - - print("{:20}{:20}{:20}".format("v_i_x", "v_j_x", "v_f_x")) - # print it - # print("{:20}{:20}{:20}".format(v_i_x, v_i_y, v_i_z)) - - # append it to lista for further usage - listx.append(v_i_x) - listy.append(v_i_y) - listy.append(v_i_z) - - for j in range(0, len(data)): - v_j_x = data[j].split(", ")[0].strip("\n") - v_j_y = data[j].split(", ")[1].strip("\n") - v_j_z = data[j].split(", ")[2].strip("\n") - - if(v_j_x != v_i_x): - pv_f_x = glaw(int(1), int(2), float(v_i_x), float(v_j_x)) - print("{:20}{:20}{:20}".format(v_i_x.strip("\n"), v_j_x, v_f_x)) - - if(v_j_y != v_i_y): - v_f_y = glaw(int(1), int(2), float(v_i_y), float(v_j_y)) - print("{:20}{:20}{:20}".format(v_i_y.strip("\n"), v_j_y, v_f_y)) - - if(v_j_z != v_i_z): - v_f_z = glaw(int(1), int(2), float(v_i_z), float(v_j_z)) - print("{:20}{:20}{:20}".format(v_i_z.strip("\n"), v_j_z, v_f_z)) - - - print("---\n") - -print("") -end = time.time() -whole_time = end - start -out = ">> Finished calculating the forces in " + str(whole_time) + " seconds\n" -print(out) - -try: - call(["telegram-send", "--pre", str(out) ]) -except Exception: - print("Failed to send telegram message D:") - - -# # initialize some variables -# sum_a = 0 -# avarage_a = 0 -# -# # calculate the average value -# for i in range(0, 40): -# sum_a += float(lista[i]) -# -# # calculate the average -# avarage_a = sum_a / 40 -# -# # print the average -# print("avarage_a: " + str(avarage_a)) - -# sort lista and store the result in listb -# listb = sorted(lista) - -# plot listb using a normal line, red color and round markers -# plt.plot(lista, "-ro") - -# dispaly the plot -# plt.show() diff --git a/src/python/cells.py b/src/python/cells.py deleted file mode 100755 index 3304296..0000000 --- a/src/python/cells.py +++ /dev/null @@ -1,62 +0,0 @@ -#!/usr/bin/env python - -import numpy as np -from numpy import genfromtxt -import json -import bpy -import time -import sys - -num = 100 # number of stars that should be generated -range_max = 10 # define the range in which the coordinates should be generated -axes = 3 # define the number of axes -data = "galaxy" # define the name of the galaxy -path = "cell_stars/1.csv" # define the path where the galaxy should be saved - -# generate random coordinates -# rand_a = (np.random.rand(num, axes) * 2 * rand_range) - rand_range - - -for i in range(0, num, 1): - - # generate the random star-coordinates - x = np.random.uniform(-range_max, range_max, size=1) - y = np.random.uniform(-range_max, range_max, size=1) - z = np.random.uniform(-range_max, range_max, size=1) - - with open(path, "a") as star_data: - x_a = str(float(x)) + ", " - y_a = str(float(y)) + ", " - z_a = str(float(z)) - - star_data.write(x_a + y_a + z_a + "\n") - -for data in path: - verts = genfromtxt(path, delimiter=', ', skip_header=0, usecols = (0, 1, 2)) - - # 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') - -# parsed_json = json.loads(stars) -# print(parsed_json["s1"]) -# -# -# # The Vector array contains vectors describing forces acting inside the cells. -# cell_num = 3 # number of cells -# -# vector_arr = np.zeros((cell_num, cell_num, cell_num)) -# -# vector_arr[0][1][2] = Vector(1, 2, 3) -# -# print(vector_arr[0]) diff --git a/src/python/coord.py b/src/python/coord.py index 6cadf16..00fe056 100755 --- a/src/python/coord.py +++ b/src/python/coord.py @@ -18,7 +18,7 @@ parser = argparse.ArgumentParser( # 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("path", help="Name of 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") @@ -34,7 +34,7 @@ save_path = "stars/" + str(args.path) + ".csv" # define the path to the lookuptable # (The default args.lookup value is 1e7) -path = "data/" + str(args.lookup) + ".csv" +path = "data/" + str(args.lookup) + ".big.csv" # define a varible storing how many cores should be user to compute cores = int(args.cores) @@ -103,20 +103,25 @@ def main(): # 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 + local_nos = int(nos / cores) - print(f"Generating {local_nos} Stars using the {path} lookuptable.") + print(f"Generating {local_nos} Stars using the {path} lookuptable utilizing {cores} cores") # 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)] # start the threads in the lsit - for thread in threads: - thread.start() + # for thread in threads: + for i in range(0, len(threads)): + threads[i].start() + print(f"Thread {i} Started!") + # thread.start() # join the threads - for thread in threads: - thread.join() + # for thread in threads: + for i in range(0, len(threads)): + threads[i].join() + # thread.join() # time stuff end = time.time() diff --git a/src/python/coord_clean.py b/src/python/coord_clean.py deleted file mode 100644 index 85f578d..0000000 --- a/src/python/coord_clean.py +++ /dev/null @@ -1,117 +0,0 @@ -#!/usr/bin/env python - -# import libraries -import time -import numpy as np -import sys - -# define the number of stars that should be generated -nos = int(sys.argv[1]) - -# define some arrays for storing the values -arr_stars = np.zeros((int(nos), 3)) -arr_saved_stars = np.zeros((int(nos), 3)) - -# define various paths -path = "data/2e7.csv" -save_path = "stars/" + sys.argv[2] + ".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(): - - # define the variables for storing the amount of stars kept or kicked away - stars_kept = 0 - stars_kicked = 0 - i = 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): - while(stars_kept < nos): - - # generate the random star-coordinates - x = np.random.uniform(range_min, range_max, size=1) - y = np.random.uniform(range_min, range_max, size=1) - z = np.random.uniform(range_min, range_max, size=1) - - # 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] - a = np.random.uniform(rand_min, rand_max, size=1) - # print(a) - # read out the corresponding rho value from the lookuptable (rho-file) - 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): - # add the coordinate to arr_saved_stars - arr_saved_stars[stars_kept][0] = x - arr_saved_stars[stars_kept][1] = y - arr_saved_stars[stars_kept][2] = z - - # increment the star_kept counter - stars_kept += 1 - print(stars_kept) - - else: - # increment the star_kicked counter - stars_kicked += 1 - - # increment i - i = i + 1 - - print("") - end = time.time() - whole_time = end - start - out = ">> Finished generating stars in " + str(whole_time) + " seconds\n" - print(out) - - # write the star coordinates to a file - start_write_file = time.time() - 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 - out = ">> Finished writing star-data to " + save_path + " in " + str(round(time_write_file, 4)) + " seconds\n" - print(out) - - time_all = whole_time + time_write_file - - time_min = round(time_all / 60, 1) - - # 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 ) + "%")) - -if __name__ == "__main__": - main() diff --git a/src/python/draw.py b/src/python/draw.py deleted file mode 100644 index e672a76..0000000 --- a/src/python/draw.py +++ /dev/null @@ -1,20 +0,0 @@ -import matplotlib.pyplot as plt - -listx = [] -listy = [] - -with open("testFile.csv") as f: - data = f.readlines() - - print(data[1:1000]) - - for i in range(0, 1000): - listx.append(data[i].split(", ")[0]) - - - -# for value in listx: -# print(value, end="\n") - -plt.plot(listx) -plt.show() diff --git a/src/python/draw/draw.py b/src/python/draw/draw.py new file mode 100644 index 0000000..e672a76 --- /dev/null +++ b/src/python/draw/draw.py @@ -0,0 +1,20 @@ +import matplotlib.pyplot as plt + +listx = [] +listy = [] + +with open("testFile.csv") as f: + data = f.readlines() + + print(data[1:1000]) + + for i in range(0, 1000): + listx.append(data[i].split(", ")[0]) + + + +# for value in listx: +# print(value, end="\n") + +plt.plot(listx) +plt.show() diff --git a/src/python/draw/plot_lookuptable.py b/src/python/draw/plot_lookuptable.py new file mode 100755 index 0000000..9d5c6f2 --- /dev/null +++ b/src/python/draw/plot_lookuptable.py @@ -0,0 +1,21 @@ +#!/usr/bin/env python3 + +import matplotlib.pyplot as plt + +lookup_arr_a = [] +lookup_arr_b = [] + +path = "data/2e7.csv" + +print("opening data...") + +with open(path) as data: + print("opened " + path) + + lookup = data.readlines() + for i in range(0, len(lookup)): + lookup_arr_a.append(lookup[i].split(", ")[0]) + lookup_arr_b.append(lookup[i].split(", ")[1]) + +plt.plot(lookup_arr_a, lookup_arr_b) +plt.show() diff --git a/src/python/experiments/nn.py b/src/python/experiments/nn.py new file mode 100755 index 0000000..b36b103 --- /dev/null +++ b/src/python/experiments/nn.py @@ -0,0 +1,60 @@ +#!/usr/bin/env python + +# Import numpy for using matrix operations +import numpy as np + +# define an actovation function +def sigmoid(x,deriv=False): + if(deriv==True): + return x*(1-x) + return 1/(1+np.exp(-x)) + +# 0 0 1 0 +# 0 1 1 0 +# 1 0 1 1 +# 1 1 1 1 + +# define an input matrix +X = np.array([ [0,0,1], [0,1,1], [1,0,1], [1,1,1] ]) + +# define an output matrix +y = np.array([[0,0,1,1]]).T + +# seed numpy +np.random.seed(1) + +# generate some weights +syn0 = 2*np.random.random((3,4)) - 1 + +# define how often the calculations should be run + +n = 100000 + +# loop +for i in range(n): + # define the first layer + l0 = X + + # define the second layer using the first layer and the weights + l1 = sigmoid(np.dot(l0,syn0)) + + # calculate an error + l1_error = y - l1 + + # calculate how fatal the error is + l1_delta = l1_error * sigmoid(l1,True) + + # adjust the weights + syn0 += np.dot(l0.T,l1_delta) + + # print some information + if (i % (n / 10000) == 0): + print("l1: " + str(l1)) + +print("") +print("Output After Training:") +print(l1) + +l0 = np.array([0, 1, 0]) +l1 = sigmoid(np.dot(l0, syn0)) +print(l1) diff --git a/src/python/experiments/view.py b/src/python/experiments/view.py new file mode 100644 index 0000000..a30ec48 --- /dev/null +++ b/src/python/experiments/view.py @@ -0,0 +1,48 @@ +import bpy +from numpy import genfromtxt +import os +import sys + +directory = "stars/" +# # print(directory) +# +files = [sys.argv[3]] + +# 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) diff --git a/src/python/lookup.py b/src/python/lookup.py index 52e1966..4c81295 100755 --- a/src/python/lookup.py +++ b/src/python/lookup.py @@ -7,6 +7,21 @@ import matplotlib.pyplot as plt import time import os import sys +import argparse + +parser = argparse.ArgumentParser( + description="Lookuptable generator", + usage='./%(prog)s [-h]', +) +parser.add_argument("radius", help="Number of Values to be calculated") +parser.add_argument("path", help="Path to the location where the lookuptable should be saved", type=str) +args = parser.parse_args() + +# define the radius until where the values should be generated +radius = int(float(args.radius)) + +# Define the path to where the data should be stored +path = 'data/' + str(args.path) + '.big.csv' # Defining some variables sigma = 200 @@ -33,33 +48,22 @@ def phi(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): + for i in range(0, radius): # 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)) + if ((i % 1000) == 0): + print(str(i) + ", " + str(rho_i)) # write the data into the file data.write(str(i) + ", " + str(rho_i) + "\n") @@ -74,13 +78,7 @@ runtime = end - start print("\n Runtime: ", end="") print(str(runtime) + " seconds") -print(" Stars: " + str(stars)) +print(" Radius: " + str(radius)) print(" Rho-values per second: ", end="") -print(str(stars / runtime)) - -# plt.plot(list_rho) -# plt.xscale('log') -# plt.yscale('log') -# plt.grid() -# plt.show() +print(str(radius / runtime)) diff --git a/src/python/nn.py b/src/python/nn.py deleted file mode 100755 index b36b103..0000000 --- a/src/python/nn.py +++ /dev/null @@ -1,60 +0,0 @@ -#!/usr/bin/env python - -# Import numpy for using matrix operations -import numpy as np - -# define an actovation function -def sigmoid(x,deriv=False): - if(deriv==True): - return x*(1-x) - return 1/(1+np.exp(-x)) - -# 0 0 1 0 -# 0 1 1 0 -# 1 0 1 1 -# 1 1 1 1 - -# define an input matrix -X = np.array([ [0,0,1], [0,1,1], [1,0,1], [1,1,1] ]) - -# define an output matrix -y = np.array([[0,0,1,1]]).T - -# seed numpy -np.random.seed(1) - -# generate some weights -syn0 = 2*np.random.random((3,4)) - 1 - -# define how often the calculations should be run - -n = 100000 - -# loop -for i in range(n): - # define the first layer - l0 = X - - # define the second layer using the first layer and the weights - l1 = sigmoid(np.dot(l0,syn0)) - - # calculate an error - l1_error = y - l1 - - # calculate how fatal the error is - l1_delta = l1_error * sigmoid(l1,True) - - # adjust the weights - syn0 += np.dot(l0.T,l1_delta) - - # print some information - if (i % (n / 10000) == 0): - print("l1: " + str(l1)) - -print("") -print("Output After Training:") -print(l1) - -l0 = np.array([0, 1, 0]) -l1 = sigmoid(np.dot(l0, syn0)) -print(l1) diff --git a/src/python/plot_lookuptable.py b/src/python/plot_lookuptable.py deleted file mode 100755 index 9d5c6f2..0000000 --- a/src/python/plot_lookuptable.py +++ /dev/null @@ -1,21 +0,0 @@ -#!/usr/bin/env python3 - -import matplotlib.pyplot as plt - -lookup_arr_a = [] -lookup_arr_b = [] - -path = "data/2e7.csv" - -print("opening data...") - -with open(path) as data: - print("opened " + path) - - lookup = data.readlines() - for i in range(0, len(lookup)): - lookup_arr_a.append(lookup[i].split(", ")[0]) - lookup_arr_b.append(lookup[i].split(", ")[1]) - -plt.plot(lookup_arr_a, lookup_arr_b) -plt.show() diff --git a/src/python/spiral/average_force.py b/src/python/spiral/average_force.py new file mode 100755 index 0000000..a3a3146 --- /dev/null +++ b/src/python/spiral/average_force.py @@ -0,0 +1,109 @@ +#!/usr/bin/env python + +# import stuff +import sys +import matplotlib.pyplot as plt +import numpy as np +import time +from subprocess import call + +# define from where to get the star data +path = "stars/" + sys.argv[1] + ".csv" + +# define a list to store the coordinates +listx = [] +listy = [] +listz = [] +list_force = [] + +# define constants +G = 6.674e-11 + +def glaw(m1, m2, a1, b1): + a = m1 * m2 + b = np.power(a1 - b1, 2) + c = np.sqrt(b) + d = a / c + e = G * d + return e + +# start the timer +start = time.time() + +# open the data file +with open(path) as f: + + # read the individial lines from the data file + data = f.readlines() + + # for each line + for i in range(0, len(data)): + + # parse the first value in each line + v_i_x = data[i].split(", ")[0] + v_i_y = data[i].split(", ")[1] + v_i_z = data[i].split(", ")[2] + + print("{:20}{:20}{:20}".format("v_i_x", "v_j_x", "v_f_x")) + # print it + # print("{:20}{:20}{:20}".format(v_i_x, v_i_y, v_i_z)) + + # append it to lista for further usage + listx.append(v_i_x) + listy.append(v_i_y) + listy.append(v_i_z) + + for j in range(0, len(data)): + v_j_x = data[j].split(", ")[0].strip("\n") + v_j_y = data[j].split(", ")[1].strip("\n") + v_j_z = data[j].split(", ")[2].strip("\n") + + if(v_j_x != v_i_x): + pv_f_x = glaw(int(1), int(2), float(v_i_x), float(v_j_x)) + print("{:20}{:20}{:20}".format(v_i_x.strip("\n"), v_j_x, v_f_x)) + + if(v_j_y != v_i_y): + v_f_y = glaw(int(1), int(2), float(v_i_y), float(v_j_y)) + print("{:20}{:20}{:20}".format(v_i_y.strip("\n"), v_j_y, v_f_y)) + + if(v_j_z != v_i_z): + v_f_z = glaw(int(1), int(2), float(v_i_z), float(v_j_z)) + print("{:20}{:20}{:20}".format(v_i_z.strip("\n"), v_j_z, v_f_z)) + + + print("---\n") + +print("") +end = time.time() +whole_time = end - start +out = ">> Finished calculating the forces in " + str(whole_time) + " seconds\n" +print(out) + +try: + call(["telegram-send", "--pre", str(out) ]) +except Exception: + print("Failed to send telegram message D:") + + +# # initialize some variables +# sum_a = 0 +# avarage_a = 0 +# +# # calculate the average value +# for i in range(0, 40): +# sum_a += float(lista[i]) +# +# # calculate the average +# avarage_a = sum_a / 40 +# +# # print the average +# print("avarage_a: " + str(avarage_a)) + +# sort lista and store the result in listb +# listb = sorted(lista) + +# plot listb using a normal line, red color and round markers +# plt.plot(lista, "-ro") + +# dispaly the plot +# plt.show() diff --git a/src/python/spiral/cells.py b/src/python/spiral/cells.py new file mode 100755 index 0000000..3304296 --- /dev/null +++ b/src/python/spiral/cells.py @@ -0,0 +1,62 @@ +#!/usr/bin/env python + +import numpy as np +from numpy import genfromtxt +import json +import bpy +import time +import sys + +num = 100 # number of stars that should be generated +range_max = 10 # define the range in which the coordinates should be generated +axes = 3 # define the number of axes +data = "galaxy" # define the name of the galaxy +path = "cell_stars/1.csv" # define the path where the galaxy should be saved + +# generate random coordinates +# rand_a = (np.random.rand(num, axes) * 2 * rand_range) - rand_range + + +for i in range(0, num, 1): + + # generate the random star-coordinates + x = np.random.uniform(-range_max, range_max, size=1) + y = np.random.uniform(-range_max, range_max, size=1) + z = np.random.uniform(-range_max, range_max, size=1) + + with open(path, "a") as star_data: + x_a = str(float(x)) + ", " + y_a = str(float(y)) + ", " + z_a = str(float(z)) + + star_data.write(x_a + y_a + z_a + "\n") + +for data in path: + verts = genfromtxt(path, delimiter=', ', skip_header=0, usecols = (0, 1, 2)) + + # 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') + +# parsed_json = json.loads(stars) +# print(parsed_json["s1"]) +# +# +# # The Vector array contains vectors describing forces acting inside the cells. +# cell_num = 3 # number of cells +# +# vector_arr = np.zeros((cell_num, cell_num, cell_num)) +# +# vector_arr[0][1][2] = Vector(1, 2, 3) +# +# print(vector_arr[0]) diff --git a/src/python/stars/test.csv b/src/python/stars/test.csv new file mode 100644 index 0000000..76829c5 --- /dev/null +++ b/src/python/stars/test.csv @@ -0,0 +1,2656 @@ +-225313.49522130808, 59705.87029883778, 113772.11279696762 +83540.9539508142, 242210.64319142513, 40103.852860355866 +-70980.7662655781, -170132.46343507804, 2156.7295612652088 +-313622.5117297316, -74247.44479375333, 121384.48953946773 +709065.6002544295, -861197.5649344983, -178630.8364081754 +-6308.193418741925, 183519.04485822213, -458685.5789406153 +58791.81321212812, -56038.32424577698, -59979.48388399533 +-96182.26402844, -150443.72826359305, 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+[-9829.6413012], [-69533.08017861], [12995.51846012] +[25259.3609388], [-60381.1130031], [-33607.93205954] diff --git a/src/python/view.py b/src/python/view.py deleted file mode 100644 index 8b802b6..0000000 --- a/src/python/view.py +++ /dev/null @@ -1,30 +0,0 @@ -import bpy -from numpy import genfromtxt -import os -import sys - -directory = "other_stars/" - -files = [sys.argv[4] + ".csv"] - -for data in files: - path = str(directory) + str(data) - print(path) - - verts = genfromtxt(path, delimiter=' ', skip_header=0, usecols = (0, 1, 2)) - - #print(verts) - - # 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') diff --git a/src/testFile.csv b/src/testFile.csv deleted file 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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) -- cgit 1.4.1