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)