import sys from distance import squared_distance from ioutils import read_strings from strutils import words if __name__ == "__main__": x = float(sys.argv[1]) y = float(sys.argv[2]) z = float(sys.argv[3]) array = read_strings() res = [] def closest(x, y, z, v1, v2): if squared_distance([x, y, z], v1) < squared_distance([x, y, z], v2): return v1 return v2 for line in array: [xi, yi, zi] = words(line)[0:3] [xi, yi, zi] = [float(xi), float(yi), float(zi)] if res == []: res = [xi, yi, zi] else: res = closest(x, y, z, res, [xi, yi, xi]) print(res)
parser = argparse.ArgumentParser( description='generate transition matrix given in stdin') parser.add_argument( 'move_to_other_page_prob', type=float, help= 'the probality for moving to another page through link instead of staying on the same page' ) parser.add_argument( '--ignore-multiple-links', help='if multiple links present (from one to anotgher) ignore them', action='store_true') args = parser.parse_args() LOOP_PROBAB = 1 - args.move_to_other_page_prob TRANS_PROB = args.move_to_other_page_prob inp = read_strings() n = int(inp[0]) links = as_tuples(inp[1:]) if args.ignore_multiple_links: links = list(set(links)) #unique lnk_cnts = link_counts(n, links) # print(lnk_cnts) # print(degrees_vec(lnk_cnts)) # print(loop_equi_probab(5,LOOP_PROBAB)) # print(link_probab(lnk_cnts,TRANS_PROB)) trns_matr = transition_matrix(n, links, LOOP_PROBAB) trns_matr = [normalize(row) for row in trns_matr] print(trns_matr)
for line in lines: dig = int(leading_digit(line)) freqs[dig] += 1 count += 1 freqs_array = [freqs[k] for k in range(0, 10)] freqs_array = [f / count for f in freqs_array] return freqs_array def fake_benford(): "Numbers from 1 to 1000" r = random.random() * 3 return str(10**r) if __name__ == "__main__": lines = read_strings() freqs_array = get_benford_dist(lines) print(freqs_array) plt.plot(range(1, 10), freqs_array[1:]) theoritical_freq = [log(1 + 1 / d, 10) for d in range(1, 10)] plt.plot(range(1, 10), theoritical_freq) fake_lines = [fake_benford() for i in range(10000)] freqs_array = get_benford_dist(fake_lines) plt.plot(range(1, 10), freqs_array[1:]) plt.show()
import sys from Interval import Interval from ioutils import read_strings if __name__ == "__main__": x = float(sys.argv[1]) strs = read_strings() for s in strs: flts = [float(x) for x in s.split()] intrvl = Interval(flts[0], flts[1]) if x in intrvl: print(intrvl)