In [3]:
def primeFactors(n: int) -> list[int]:
    assert n > 0, "Only positive numbers have factors"
    if n == 1:
        return []
    for f in range(2, n+1):
        if n % f == 0:
            r = primeFactors(n // f)
            r.append(f)
            return r
    return []

print(primeFactors(44100))

[7, 7, 5, 5, 3, 3, 2, 2]
In [6]:
import typing

def sortedSearch(lst: list, needle: typing.Any) -> bool:
    print(f"Searching for {needle} in {lst}")
    if len(lst) == 0:
        print("Base case, False")
        return False
    midpoint = len(lst) // 2
    if lst[midpoint] == needle:
        print(f"Early return case, found {needle} at {midpoint}")
        return True
    elif lst[midpoint] < needle:
        print("Recursing right starting")
        r = sortedSearch(lst[midpoint+1:], needle)
        print("Recursing right ending")
        return r
    else: # lst[midpoint] > needle
        print("Recursing left starting")
        r = sortedSearch(lst[:midpoint], needle)
        print("Recursing left ending")
        return r
    
lst = [
    "Aardvark", "Cui", "Dostoyevsky", "Mendelsson", "Richards", "Shakespeare", "Sun Tzu", "Xavier"
]

print(sortedSearch(lst, "Shakespeare"))
print(sortedSearch(lst, "Strauss"))

Searching for Shakespeare in ['Aardvark', 'Cui', 'Dostoyevsky', 'Mendelsson', 'Richards', 'Shakespeare', 'Sun Tzu', 'Xavier']
Recursing right starting
Searching for Shakespeare in ['Shakespeare', 'Sun Tzu', 'Xavier']
Recursing left starting
Searching for Shakespeare in ['Shakespeare']
Early return case, found Shakespeare at 0
Recursing left ending
Recursing right ending
True
Searching for Strauss in ['Aardvark', 'Cui', 'Dostoyevsky', 'Mendelsson', 'Richards', 'Shakespeare', 'Sun Tzu', 'Xavier']
Recursing right starting
Searching for Strauss in ['Shakespeare', 'Sun Tzu', 'Xavier']
Recursing left starting
Searching for Strauss in ['Shakespeare']
Recursing right starting
Searching for Strauss in []
Base case, False
Recursing right ending
Recursing left ending
Recursing right ending
False
In [19]:
import random

def longestExcursion(lst: list[float], threshold: float) -> int:
    print(f"Looking for excursion in length {len(lst)}")
    if len(lst) == 0:
        return 0
    s = sum(lst)
    if s > threshold or s < -threshold:
        return len(lst)
    l = longestExcursion(lst[:-1], threshold)
    r = longestExcursion(lst[1:], threshold)
    if l > r:
        return l
    else:
        return r
    
lst = []
for _ in range(64):
    lst.append(random.random() - 0.5)
print(lst)
print(longestExcursion(lst, 1.1))

[-0.2982722642433727, -0.2884297276579818, 0.3488152683237594, 0.49417105686176555, 0.3904051924093147, 0.37989070025947647, -0.4223381531774162, -0.46305886870483015, 0.38762732261603927, 0.17522008476264117, 0.4777089122128906, -0.21163148457328984, 0.00329002398421685, 0.38959479347062487, 0.15002627092783927, 0.4913742572246298, -0.2021941085709218, -0.2765938521352741, -0.2681258673381408, 0.4658647428392586, 0.008679915601038979, 0.1629353758577068, -0.2699294057939625, 0.12165569784611763, -0.33180692752180974, -0.06452549951914399, -0.2324510210634697, -0.37972948274186924, 0.0215745442132248, -0.2566189981424103, -0.40920303802120717, -0.2572370632586982, 0.2561691465851361, 0.37115331058451084, -0.049059209921746505, -0.47249499346487245, 0.315529136822048, -0.31945712513505575, -0.3647584122208073, -0.32955810015650866, -0.23741294638913246, 0.09132994407352713, 0.19234246133034938, 0.2531206868977278, 0.45896466470321295, 0.1752787079183057, -0.05638114960096485, -0.27928729911032757, 0.03028003010269109, -0.05964761981491973, 0.41226920397789124, 0.24999337269621735, -0.35594037044136306, 0.39250227359965517, -0.07210260518471068, 0.1449632864562581, 0.11183391327323688, -0.42888888326048036, -0.10919794589890053, -0.2956642475547381, -0.12063260028714606, -0.43565520891325216, -0.21190813057723024, 0.04816567435129804]
Looking for excursion in length 64
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---------------------------------------------------------------------------
KeyboardInterrupt                         Traceback (most recent call last)
Input In [19], in <cell line: 21>()
     19     lst.append(random.random() - 0.5)
     20 print(lst)
---> 21 print(longestExcursion(lst, 1.1))

Input In [19], in longestExcursion(lst, threshold)
      8 if s > threshold or s < -threshold:
      9     return len(lst)
---> 10 l = longestExcursion(lst[:-1], threshold)
     11 r = longestExcursion(lst[1:], threshold)
     12 if l > r:

Input In [19], in longestExcursion(lst, threshold)
      8 if s > threshold or s < -threshold:
      9     return len(lst)
---> 10 l = longestExcursion(lst[:-1], threshold)
     11 r = longestExcursion(lst[1:], threshold)
     12 if l > r:

    [... skipping similar frames: longestExcursion at line 10 (32 times)]

Input In [19], in longestExcursion(lst, threshold)
      9     return len(lst)
     10 l = longestExcursion(lst[:-1], threshold)
---> 11 r = longestExcursion(lst[1:], threshold)
     12 if l > r:
     13     return l

Input In [19], in longestExcursion(lst, threshold)
      9     return len(lst)
     10 l = longestExcursion(lst[:-1], threshold)
---> 11 r = longestExcursion(lst[1:], threshold)
     12 if l > r:
     13     return l

    [... skipping similar frames: longestExcursion at line 10 (6 times), longestExcursion at line 11 (3 times)]

Input In [19], in longestExcursion(lst, threshold)
      9     return len(lst)
     10 l = longestExcursion(lst[:-1], threshold)
---> 11 r = longestExcursion(lst[1:], threshold)
     12 if l > r:
     13     return l

    [... skipping similar frames: longestExcursion at line 10 (6 times)]

Input In [19], in longestExcursion(lst, threshold)
      8 if s > threshold or s < -threshold:
      9     return len(lst)
---> 10 l = longestExcursion(lst[:-1], threshold)
     11 r = longestExcursion(lst[1:], threshold)
     12 if l > r:

Input In [19], in longestExcursion(lst, threshold)
      3 def longestExcursion(lst: list[float], threshold: float) -> int:
----> 4     print(f"Looking for excursion in length {len(lst)}")
      5     if len(lst) == 0:
      6         return 0

File /mnt/zfs/jupyter-p03/home/gkrichar/.ipython/profile_default/startup/cs114-setup.py:5, in print(*args, **kwargs)
----> 5 def print(*args, **kwargs): builtins.print(*args, **kwargs); sys.stdout.flush(); time.sleep(0.04)

KeyboardInterrupt:
In [29]:
import random

def longestExcursionPrime(lst: list[float], threshold: float, right: bool) -> int:
    #print(f"Looking for excursion in length {len(lst)}")
    if len(lst) == 0:
        return 0
    s = sum(lst)
    if s > threshold or s < -threshold:
        return len(lst)
    r = longestExcursionPrime(lst[1:], threshold, True)
    if not right:
        l = longestExcursionPrime(lst[:-1], threshold, False)
        if l > r:
            return l
        else:
            return r
    else:
        return r
    
def longestExcursion(lst: list[float], threshold: float) -> int:
    return longestExcursionPrime(lst, threshold, False)
    
lst = []
for _ in range(64):
    lst.append(random.random() - 0.5)
print(lst)
print(longestExcursion(lst, 1.1))

[0.03783920596326085, -0.4275923952633002, -0.049627049649719535, -0.03890624390203201, -0.44443594903118, 0.4819529789200606, -0.1980182121067805, -0.326500377261588, -0.3198843181102149, -0.06045552220131378, 0.3453264053368277, -0.38629255858393874, 0.44639496592355365, 0.43972558357672153, 0.13522249720705293, 0.42570227239250036, -0.14778286237377158, -0.18861190401484274, 0.27026749932109273, -0.20884902180417753, -0.16795078303841138, -0.07078540567798519, 0.2995888017556003, -0.043577961728356485, 0.3534121763356902, -0.49351920090801926, 0.21758125230752423, 0.05208324912637763, -0.4170242903331689, 0.2690372989692329, 0.449846902603085, 0.006461900369552187, 0.006260350988763541, -0.13722324770222594, -0.25240565292224393, 0.42418275805310823, -0.2623518667224719, -0.2369488912317267, 0.38418937638366046, 0.2639662763509788, -0.19610216542993375, -0.15255635722443306, 0.10565508414396385, -0.1509870755365813, 0.12619558146264576, 0.28280042198587974, -0.3949111940504547, 0.4368337766611472, 0.10632687685477171, 0.322744029869934, 0.1784546800074558, 0.41084736255150844, 0.07822723163042966, -0.20987502510083056, 0.08418214669911539, 0.22483481658898163, 0.1836744730055504, -0.04296587431775534, -0.07425647844220817, -0.4862736681781932, -0.41759372711444176, -0.24843640462270278, -0.2835091683391554, -0.49700434059729304]
60
In [33]:
def insertSortedPrime(lst: list, val: typing.Any, lb: int, ub: int) -> int:
    if ub == lb:
        lst.insert(lb, val)
        return lb
    midpoint = (ub - lb) // 2 + lb
    mid = lst[midpoint]
    if val < mid:
        return insertSortedPrime(lst, val, lb, midpoint)
    else:
        return insertSortedPrime(lst, val, midpoint+1, ub)

def insertSorted(lst: list, val: typing.Any) -> int:
    return insertSortedPrime(lst, val, 0, len(lst))

lst: list[float] = []
for _ in range(64):
    print(insertSorted(lst, random.random()))
    print(lst)
print(lst)

0
[0.23071034621591868]
1
[0.23071034621591868, 0.366560077951821]
2
[0.23071034621591868, 0.366560077951821, 0.45487465582824993]
3
[0.23071034621591868, 0.366560077951821, 0.45487465582824993, 0.6948355827009094]
3
[0.23071034621591868, 0.366560077951821, 0.45487465582824993, 0.5237084244009244, 0.6948355827009094]
5
[0.23071034621591868, 0.366560077951821, 0.45487465582824993, 0.5237084244009244, 0.6948355827009094, 0.7731895518801317]
6
[0.23071034621591868, 0.366560077951821, 0.45487465582824993, 0.5237084244009244, 0.6948355827009094, 0.7731895518801317, 0.9453702765127643]
7
[0.23071034621591868, 0.366560077951821, 0.45487465582824993, 0.5237084244009244, 0.6948355827009094, 0.7731895518801317, 0.9453702765127643, 0.963578964883363]
0
[0.056200849232629024, 0.23071034621591868, 0.366560077951821, 0.45487465582824993, 0.5237084244009244, 0.6948355827009094, 0.7731895518801317, 0.9453702765127643, 0.963578964883363]
5
[0.056200849232629024, 0.23071034621591868, 0.366560077951821, 0.45487465582824993, 0.5237084244009244, 0.5575979720227956, 0.6948355827009094, 0.7731895518801317, 0.9453702765127643, 0.963578964883363]
8
[0.056200849232629024, 0.23071034621591868, 0.366560077951821, 0.45487465582824993, 0.5237084244009244, 0.5575979720227956, 0.6948355827009094, 0.7731895518801317, 0.8669056355289189, 0.9453702765127643, 0.963578964883363]
4
[0.056200849232629024, 0.23071034621591868, 0.366560077951821, 0.45487465582824993, 0.4556710143099284, 0.5237084244009244, 0.5575979720227956, 0.6948355827009094, 0.7731895518801317, 0.8669056355289189, 0.9453702765127643, 0.963578964883363]
5
[0.056200849232629024, 0.23071034621591868, 0.366560077951821, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.6948355827009094, 0.7731895518801317, 0.8669056355289189, 0.9453702765127643, 0.963578964883363]
0
[0.05252813094597775, 0.056200849232629024, 0.23071034621591868, 0.366560077951821, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.6948355827009094, 0.7731895518801317, 0.8669056355289189, 0.9453702765127643, 0.963578964883363]
4
[0.05252813094597775, 0.056200849232629024, 0.23071034621591868, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.6948355827009094, 0.7731895518801317, 0.8669056355289189, 0.9453702765127643, 0.963578964883363]
2
[0.05252813094597775, 0.056200849232629024, 0.1841726576229168, 0.23071034621591868, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.6948355827009094, 0.7731895518801317, 0.8669056355289189, 0.9453702765127643, 0.963578964883363]
4
[0.05252813094597775, 0.056200849232629024, 0.1841726576229168, 0.23071034621591868, 0.314499174038942, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.6948355827009094, 0.7731895518801317, 0.8669056355289189, 0.9453702765127643, 0.963578964883363]
12
[0.05252813094597775, 0.056200849232629024, 0.1841726576229168, 0.23071034621591868, 0.314499174038942, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.6448558427210742, 0.6948355827009094, 0.7731895518801317, 0.8669056355289189, 0.9453702765127643, 0.963578964883363]
2
[0.05252813094597775, 0.056200849232629024, 0.14470023631144813, 0.1841726576229168, 0.23071034621591868, 0.314499174038942, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.6448558427210742, 0.6948355827009094, 0.7731895518801317, 0.8669056355289189, 0.9453702765127643, 0.963578964883363]
16
[0.05252813094597775, 0.056200849232629024, 0.14470023631144813, 0.1841726576229168, 0.23071034621591868, 0.314499174038942, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.6448558427210742, 0.6948355827009094, 0.7731895518801317, 0.8462132753889359, 0.8669056355289189, 0.9453702765127643, 0.963578964883363]
16
[0.05252813094597775, 0.056200849232629024, 0.14470023631144813, 0.1841726576229168, 0.23071034621591868, 0.314499174038942, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.6448558427210742, 0.6948355827009094, 0.7731895518801317, 0.8216592490507226, 0.8462132753889359, 0.8669056355289189, 0.9453702765127643, 0.963578964883363]
14
[0.05252813094597775, 0.056200849232629024, 0.14470023631144813, 0.1841726576229168, 0.23071034621591868, 0.314499174038942, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.6448558427210742, 0.6830776593172871, 0.6948355827009094, 0.7731895518801317, 0.8216592490507226, 0.8462132753889359, 0.8669056355289189, 0.9453702765127643, 0.963578964883363]
2
[0.05252813094597775, 0.056200849232629024, 0.08250159574485039, 0.14470023631144813, 0.1841726576229168, 0.23071034621591868, 0.314499174038942, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.6448558427210742, 0.6830776593172871, 0.6948355827009094, 0.7731895518801317, 0.8216592490507226, 0.8462132753889359, 0.8669056355289189, 0.9453702765127643, 0.963578964883363]
18
[0.05252813094597775, 0.056200849232629024, 0.08250159574485039, 0.14470023631144813, 0.1841726576229168, 0.23071034621591868, 0.314499174038942, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.6448558427210742, 0.6830776593172871, 0.6948355827009094, 0.7731895518801317, 0.8081997665853873, 0.8216592490507226, 0.8462132753889359, 0.8669056355289189, 0.9453702765127643, 0.963578964883363]
15
[0.05252813094597775, 0.056200849232629024, 0.08250159574485039, 0.14470023631144813, 0.1841726576229168, 0.23071034621591868, 0.314499174038942, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.6448558427210742, 0.6458462563361999, 0.6830776593172871, 0.6948355827009094, 0.7731895518801317, 0.8081997665853873, 0.8216592490507226, 0.8462132753889359, 0.8669056355289189, 0.9453702765127643, 0.963578964883363]
0
[0.0072314934152583055, 0.05252813094597775, 0.056200849232629024, 0.08250159574485039, 0.14470023631144813, 0.1841726576229168, 0.23071034621591868, 0.314499174038942, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.6448558427210742, 0.6458462563361999, 0.6830776593172871, 0.6948355827009094, 0.7731895518801317, 0.8081997665853873, 0.8216592490507226, 0.8462132753889359, 0.8669056355289189, 0.9453702765127643, 0.963578964883363]
15
[0.0072314934152583055, 0.05252813094597775, 0.056200849232629024, 0.08250159574485039, 0.14470023631144813, 0.1841726576229168, 0.23071034621591868, 0.314499174038942, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.5848232631871598, 0.6448558427210742, 0.6458462563361999, 0.6830776593172871, 0.6948355827009094, 0.7731895518801317, 0.8081997665853873, 0.8216592490507226, 0.8462132753889359, 0.8669056355289189, 0.9453702765127643, 0.963578964883363]
8
[0.0072314934152583055, 0.05252813094597775, 0.056200849232629024, 0.08250159574485039, 0.14470023631144813, 0.1841726576229168, 0.23071034621591868, 0.314499174038942, 0.32918508733693586, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.5848232631871598, 0.6448558427210742, 0.6458462563361999, 0.6830776593172871, 0.6948355827009094, 0.7731895518801317, 0.8081997665853873, 0.8216592490507226, 0.8462132753889359, 0.8669056355289189, 0.9453702765127643, 0.963578964883363]
16
[0.0072314934152583055, 0.05252813094597775, 0.056200849232629024, 0.08250159574485039, 0.14470023631144813, 0.1841726576229168, 0.23071034621591868, 0.314499174038942, 0.32918508733693586, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.5795206067564788, 0.5848232631871598, 0.6448558427210742, 0.6458462563361999, 0.6830776593172871, 0.6948355827009094, 0.7731895518801317, 0.8081997665853873, 0.8216592490507226, 0.8462132753889359, 0.8669056355289189, 0.9453702765127643, 0.963578964883363]
23
[0.0072314934152583055, 0.05252813094597775, 0.056200849232629024, 0.08250159574485039, 0.14470023631144813, 0.1841726576229168, 0.23071034621591868, 0.314499174038942, 0.32918508733693586, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.5795206067564788, 0.5848232631871598, 0.6448558427210742, 0.6458462563361999, 0.6830776593172871, 0.6948355827009094, 0.7731895518801317, 0.8078420432507271, 0.8081997665853873, 0.8216592490507226, 0.8462132753889359, 0.8669056355289189, 0.9453702765127643, 0.963578964883363]
3
[0.0072314934152583055, 0.05252813094597775, 0.056200849232629024, 0.0753660931573541, 0.08250159574485039, 0.14470023631144813, 0.1841726576229168, 0.23071034621591868, 0.314499174038942, 0.32918508733693586, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.5795206067564788, 0.5848232631871598, 0.6448558427210742, 0.6458462563361999, 0.6830776593172871, 0.6948355827009094, 0.7731895518801317, 0.8078420432507271, 0.8081997665853873, 0.8216592490507226, 0.8462132753889359, 0.8669056355289189, 0.9453702765127643, 0.963578964883363]
29
[0.0072314934152583055, 0.05252813094597775, 0.056200849232629024, 0.0753660931573541, 0.08250159574485039, 0.14470023631144813, 0.1841726576229168, 0.23071034621591868, 0.314499174038942, 0.32918508733693586, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.5795206067564788, 0.5848232631871598, 0.6448558427210742, 0.6458462563361999, 0.6830776593172871, 0.6948355827009094, 0.7731895518801317, 0.8078420432507271, 0.8081997665853873, 0.8216592490507226, 0.8462132753889359, 0.8669056355289189, 0.8697729195886702, 0.9453702765127643, 0.963578964883363]
5
[0.0072314934152583055, 0.05252813094597775, 0.056200849232629024, 0.0753660931573541, 0.08250159574485039, 0.14307757158532153, 0.14470023631144813, 0.1841726576229168, 0.23071034621591868, 0.314499174038942, 0.32918508733693586, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.5795206067564788, 0.5848232631871598, 0.6448558427210742, 0.6458462563361999, 0.6830776593172871, 0.6948355827009094, 0.7731895518801317, 0.8078420432507271, 0.8081997665853873, 0.8216592490507226, 0.8462132753889359, 0.8669056355289189, 0.8697729195886702, 0.9453702765127643, 0.963578964883363]
28
[0.0072314934152583055, 0.05252813094597775, 0.056200849232629024, 0.0753660931573541, 0.08250159574485039, 0.14307757158532153, 0.14470023631144813, 0.1841726576229168, 0.23071034621591868, 0.314499174038942, 0.32918508733693586, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.5795206067564788, 0.5848232631871598, 0.6448558427210742, 0.6458462563361999, 0.6830776593172871, 0.6948355827009094, 0.7731895518801317, 0.8078420432507271, 0.8081997665853873, 0.8216592490507226, 0.836245378245413, 0.8462132753889359, 0.8669056355289189, 0.8697729195886702, 0.9453702765127643, 0.963578964883363]
8
[0.0072314934152583055, 0.05252813094597775, 0.056200849232629024, 0.0753660931573541, 0.08250159574485039, 0.14307757158532153, 0.14470023631144813, 0.1841726576229168, 0.20507459215634272, 0.23071034621591868, 0.314499174038942, 0.32918508733693586, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.5237084244009244, 0.5575979720227956, 0.5795206067564788, 0.5848232631871598, 0.6448558427210742, 0.6458462563361999, 0.6830776593172871, 0.6948355827009094, 0.7731895518801317, 0.8078420432507271, 0.8081997665853873, 0.8216592490507226, 0.836245378245413, 0.8462132753889359, 0.8669056355289189, 0.8697729195886702, 0.9453702765127643, 0.963578964883363]
17
[0.0072314934152583055, 0.05252813094597775, 0.056200849232629024, 0.0753660931573541, 0.08250159574485039, 0.14307757158532153, 0.14470023631144813, 0.1841726576229168, 0.20507459215634272, 0.23071034621591868, 0.314499174038942, 0.32918508733693586, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.46848339613523493, 0.5237084244009244, 0.5575979720227956, 0.5795206067564788, 0.5848232631871598, 0.6448558427210742, 0.6458462563361999, 0.6830776593172871, 0.6948355827009094, 0.7731895518801317, 0.8078420432507271, 0.8081997665853873, 0.8216592490507226, 0.836245378245413, 0.8462132753889359, 0.8669056355289189, 0.8697729195886702, 0.9453702765127643, 0.963578964883363]
19
[0.0072314934152583055, 0.05252813094597775, 0.056200849232629024, 0.0753660931573541, 0.08250159574485039, 0.14307757158532153, 0.14470023631144813, 0.1841726576229168, 0.20507459215634272, 0.23071034621591868, 0.314499174038942, 0.32918508733693586, 0.366560077951821, 0.3991502334347915, 0.45487465582824993, 0.4556710143099284, 0.4570876289902964, 0.46848339613523493, 0.5237084244009244, 0.546538631771329, 0.5575979720227956, 0.5795206067564788, 0.5848232631871598, 0.6448558427210742, 0.6458462563361999, 0.6830776593172871, 0.6948355827009094, 0.7731895518801317, 0.8078420432507271, 0.8081997665853873, 0.8216592490507226, 0.836245378245413, 0.8462132753889359, 0.8669056355289189, 0.8697729195886702, 0.9453702765127643, 0.963578964883363]
17
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34
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37
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10
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5
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22
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26
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32
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37
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28
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12
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22
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9
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3
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19
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