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#!/usr/bin/env python
# Demo application of the spigot Python module.
#
# This program expects two integer arguments a,b, and will use a
# technique based on continued fractions to efficiently search for the
# smallest n such that a^n begins with the digits of b. (More exactly,
# such that frac(log2(a^n)) is between frac(log2(b)) and
# frac(log2(b+1)).)
import sys, os, string, getopt, traceback, signal, itertools
from spigot import Spigot
def debug(dbgclass, *args):
if dbgclass in dbgclasses_enabled:
sys.stdout.write("[%s] %s\n" % (dbgclass, " ".join(map(str,args))))
def format_in_base(n, base):
assert base <= 36
digits = string.digits + string.ascii_uppercase
ret = ""
while True:
ret = digits[n % base] + ret
n /= base
if n == 0:
return ret
def make_f(x):
def f(n):
if n == 0:
return Spigot(0)
return Spigot("frac(x*n)", {"x":x, "n":Spigot(n)})
return f
def floor_within_limits(spig, lo, hi):
"""Return floor(spig), clamped to the range [lo,hi]."""
# The purpose of this function is to avoid an exactness hazard if
# spig happens to non-obviously evaluate to an exact integer
# _outside_ the target range. If it evaluates to one inside the
# range then there's nothing we can do, but if it's out of range
# then we can at least detect that without wasting time on
# figuring out exactly _what_ out-of-range thing it might be.
if lo is not None and lo == hi:
return lo
if lo is not None and spig < lo+1:
return lo
if hi is not None and spig >= hi:
return hi
return int(Spigot("floor(x)", {"x":spig}))
def ceil_within_limits(spig, lo, hi):
"""Return ceil(spig), clamped to the range [lo,hi]."""
return -floor_within_limits(-spig, -hi, -lo)
class Firstupto(object):
"""Given some real k, return the smallest m such that frac(xm) < k.
We expect our caller to give us k values in decreasing sequence, and
we make use of that assumption to increase efficiency.
If our caller knows that frac(xM) is exactly equal to k for some M,
then passing that M as an extra parameter to our __call__ function
will cause us to notice that and not suffer an exactness hazard when
we reach it."""
def __init__(self, x):
self.xconv = x.convergents()
self.b_low = self.xconv.next()[1]
try:
self.b_step = self.xconv.next()[1]
self.b_high = self.xconv.next()[1]
except StopIteration:
debug("firstupto", "continued fraction terminated extremely early")
self.b_step = 1
self.b_high = self.b_low
self.f = make_f(x)
def __call__(self, k, M=None):
debug("firstupto", "called with k =", float(k), "and M =", M)
while True:
debug("firstupto", "b = {", self.b_low,
self.b_step, self.b_high, "}")
fl = self.f(self.b_low)
fs = self.f(self.b_step)
debug("firstupto", "fl =", float(fl))
debug("firstupto", "fs =", float(fs))
if self.b_low != M:
debug("firstupto", "normal expression: (k-fl)/(fs-1)")
i_sp = Spigot("(k-fl)/(fs-1)",
{"fl":fl, "fs":fs, "k":k})
else:
# A roundabout alternative way to compute the same
# thing, which avoids running into an exactness hazard
# when the numerator (k-fl) of the above version would
# have turned out to be exactly zero.
fl1 = self.f(self.b_low+self.b_step)
debug("firstupto", "fl1 =", float(fl1))
debug("firstupto", "b_low = M: (k-fl1)/(fs-1) + 1")
i_sp = Spigot("(k-fl1)/(fs-1) + 1",
{"fl1":fl1, "fs":fs, "k":k})
#debug("firstupto", "i_sp =", float(i_sp))
upper_bound = (self.b_high - self.b_low) / self.b_step + 1
if (M is not None and
self.b_low <= M <= self.b_high and
(M - self.b_low) % self.b_step == 0):
# Special case: one of the values taken by the
# arithmetic progression from b_low to b_high in steps
# of b_step yields *exactly* k when given to f. That
# means we can't return that value, so try each side
# of it.
i_avoid = (M - self.b_low) / self.b_step
debug("firstupto", "have to avoid", i_avoid)
debug("firstupto", "try [", 0, ",", i_avoid, "]")
i = ceil_within_limits(i_sp, 0, i_avoid)
if i == i_avoid:
debug("firstupto", "try (", i_avoid, ",", upper_bound, "]")
i = ceil_within_limits(i_sp, i_avoid+1, upper_bound)
else:
debug("firstupto", "try [", 0, ",", upper_bound, "]")
i = ceil_within_limits(i_sp, 0, upper_bound)
debug("firstupto", "i =", i)
if self.b_low + i*self.b_step <= self.b_high:
m = self.b_low + i*self.b_step
debug("firstupto", "ok, m =", m, float(self.f(m)))
return m
else:
debug("firstupto", "get more convergents")
try:
self.b_low = self.b_high
self.b_step = self.xconv.next()[1]
self.b_high = self.xconv.next()[1]
except StopIteration:
debug("firstupto", "continued fraction terminated")
return None
def writeaspowers(n, u, v):
"""Find unique integers ui,vi such that n = u^ui * v^vi.
One of ui,vi might be negative. If no such ui,vi exist, return
(None,None). We also return that if ui,vi are not unique, which can
only happen if log(u,v) is rational."""
# Helper routine: straight Euclid's algorithm.
def gcd(a,b):
"""Return the greatest common divisor of a and b."""
while b != 0:
a, b = b, a % b
return a
# The main strategy of writeaspowers() is to try to find two
# 'atomic' factors of u,v. By 'atomic' I don't necessarily mean
# prime: a prime would do if we happen to find out, but finding
# prime factors is hard in general, and we don't need anything
# that specific for this purpose. What we want is some number
# which you can divide off u a certain number of times and then it
# becomes immediately _coprime_ to u - i.e. no smaller factor of
# it will come off. And you can do the same to v. Then anything
# expressible as a product of powers of u,v has that same
# property, and we've acquired a linear relation saying what the
# powers ui,vi have to be - namely, if our atom g has multiplicity
# gu in u, gv in v and gn in n, then we know ui*gu + vi*gv = gn.
#
# The technique for finding such an 'atom' is to start with
# gcd(u,v), and keep trying to prove it _is_ an atom, by dividing
# it off u as many times as possible and then seeing if any
# fraction of it still survives (i.e. if the gcd of our candidate
# atom and whatever is left of u is non-trivial). If one does, we
# replace our atom candidate with that smaller fraction, and try
# again. So we reduce the size of our candidate in every
# iteration, and hence the algorithm must terminate.
#
# Once we've divided off this atom, we'll then look for a second
# atom between the remains of u,v, and since this search technique
# will find as large an atom as possible, it follows that the
# second atom will have _different_ ui and vi - i.e. the second
# atom gives us a second independent linear relation, and between
# those two relations, we'll have enough information to nail down
# a single pair of values that ui and vi will have to have if they
# exist at all.
def find_common_atom(u,v):
"""Find a number 'atomically' dividing u and v.
The returned value g should have the property that u/g^i and v/g^j,
for some i,j, are both integers coprime to g."""
g = gcd(u,v)
if g == 1:
return None
prev = max(u,v)
while g < prev:
prev = g
# Try to 'split' our atom using each of u and v. If we
# succeed in either attempt, g will reduce and the while
# loop will go round again. If we fail, we'll terminate
# the loop and return g.
for w in u,v:
# Divide off g as many times as we can.
while w % g == 0:
w /= g
# Is there a nontrivial common factor between g and
# what's left of w?
gg = gcd(g, w)
if gg > 1:
# Yes, so let that be our new g.
g = gg
return g
def find_multiplicity(u, g):
"""Return i such that u/g^i is an integer coprime to g.
Returns None if no such i exists."""
ret = 0
# Divide off g as many times as we can, and count them.
while u % g == 0:
u /= g
ret += 1
# Now we want the remains of u to be coprime to g. If not,
# fail.
if gcd(u, g) != 1:
return None
return ret
def find_atom_and_multiplicities(u, v):
"""Find an atom between u and v, and its multiplicities.
Returns a tuple (g,gu,gv) such that u/g^gu and v/g^gv are integers
coprime to g."""
if u == 1 and v == 1:
# Trivial case: nothing at all to find here.
return None, None, None
g = find_common_atom(u, v)
if g == None:
# We can make do with using u or v itself as an atom at a
# pinch; it will have multiplicity 1 in one of u,v and 0
# in the other, which is good enough for a linear
# relation.
g = u if u != 1 else v
return g, find_multiplicity(u, g), find_multiplicity(v, g)
debug("writeaspowers", "try to write", n, "as powers of", u, "and", v)
# Look for our first atom, g0.
g0, g0u, g0v = find_atom_and_multiplicities(u, v)
debug("writeaspowers", "found atom", g0)
assert g0 is not None
# Divide off g0 from both u and v, and look for a second atom in
# the remainders.
u0 = u / g0 ** g0u
v0 = v / g0 ** g0v
g1, g1u, g1v = find_atom_and_multiplicities(u0, v0)
if g1 is None:
# This can only happen if u and v are both exact powers of g0.
# In that case, any power of g0**gcd(g0u,g0v) is representable
# in infinitely many ways, and anything that is not such a
# power is not representable at all. We don't distinguish
# nonexistence from nonuniqueness in this function's API, so
# we can just fail immediately in both cases.
debug("writeaspowers", "one-atom failure case")
return None, None
debug("writeaspowers", "found another atom", g1)
# Our atoms should be coprime.
assert gcd(g0, g1) == 1
# Find the multiplicity of each atom in our target number n. If it
# doesn't divide 'atomically' into n, there's no point going any
# further - we'll have already proved that n is not any ratio of
# powers of u,v.
g0n = find_multiplicity(n, g0)
if g0n is None:
debug("writeaspowers", "no answer:", g0, "does not go evenly into", n)
return None, None
g1n = find_multiplicity(n, g1)
if g1n is None:
debug("writeaspowers", "no answer:", g1, "does not go evenly into", n)
return None, None
debug("writeaspowers", "multiplicities of", g0, g1, "in", n, ":", g0n, g1n)
debug("writeaspowers", "multiplicities of", g0, g1, "in", u, ":", g0u, g1u)
debug("writeaspowers", "multiplicities of", g0, g1, "in", v, ":", g0v, g1v)
# Now we have our two linear relations in ui,vi, namely
#
# g0u * ui + g0v * vi = g0n
# g1u * ui + g1v * vi = g1n
#
# I.e. we need to solve the matrix equation
#
# (g0u g0v) (ui) = (g0n)
# (g1u g1v) (vi) (g1n)
#
# which has solution
#
# (ui) = 1/(g0u g1v - g0v g1u) ( g1v -g0v) (g0n)
# (vi) (-g1u g0u) (g1n)
det = g0u * g1v - g0v * g1u
# We expect our two linear relations to be independent, i.e. the
# determinant of the matrix is nonzero so the linear system has a
# unique solution. I admit my proof of that was a _bit_ handwavy;
# if I turn out to be wrong about it, the fix will be to go back
# to the code that finds g1, check _there_ whether the two linear
# relations are scalings of each other, and if so, amalgamate g0
# and g1 into a larger atom and try again to find a new g1.
assert det != 0
# Numerators of the fractions giving ui and vi, with common
# denominator det.
ui_num = +g1v * g0n -g0v * g1n
vi_num = -g1u * g0n +g0u * g1n
debug("writeaspowers", "raw matrix solution is",
ui_num, "/", det, "and", vi_num, "/", det)
# Those fractions should have integer values, or else the solution
# isn't valid.
if ui_num % det or vi_num % det:
return None, None
ui = ui_num / det
vi = vi_num / det
debug("writeaspowers", "integer solution is", ui, "and", vi)
# Now we know that ui,vi cannot be anything _other_ than the
# values we've found. But we don't know that they _are_ the values
# we've found - the remains of u,v other than our two atoms g0,g1
# might still come out wrong. So we now check by actually
# computing the product u^ui v^vi, and seeing if it is equal to n.
#
# (Of course, the product could fail to be an integer, if one or
# both of our putative ui,vi is negative, so we must check that
# too.)
num = u**max(ui,0) * v**max(vi,0)
denom = u**max(-ui,0) * v**max(-vi,0)
if num % denom != 0 or num / denom != n:
debug("writeaspowers", "failure:", num, "/", denom, "!=", n)
return None, None
debug("writeaspowers", "success! Returning", ui, vi)
return ui, vi
def powbegin(a, b, base, minpower):
debug("modmax", "a =", a, "b =", b, "base =", base, "minpower =", minpower)
if minpower is None:
# Default to choosing a minimum power which guarantees that
# a^result >= b. It's pedantic and annoying to ask 'what power
# of 2 begins with 100' and be told that 2^0 begins 1.00! I'd
# much rather be told that 2^196 = 100433...06336. So the
# default choice of minpower arranges that all the digits of b
# will appear _before_ the decimal point.
#
# If a user really does want digits below the decimal point,
# they can explicitly reset to the more straightforward
# semantics by saying -m0.
#
# To calculate the right minimum power, spigot itself is the
# easiest way - and using the dyadic log function guarantees
# that this expression cannot hang.
minpower = int(Spigot("ceil(log(b,a))",
{"a":Spigot(a), "b":Spigot(b)}))
debug("modmax", "auto minpower =", minpower)
# If some power of a is equal to b times a power of the base, then
# that's the absolute optimum answer, and we'll have to be aware
# when we're coming up on it to avoid running into an exactness
# hazard.
exact_answer, _ = writeaspowers(b, a, base)
debug("modmax", "exact_answer =", exact_answer)
if exact_answer is not None:
exact_answer -= minpower
debug("modmax", " adjusted to", exact_answer)
if exact_answer < 0: exact_answer = None
# If a power of a is similarly equal to b+1 times a power of the
# base, then that's a value that is definitely _not_ the answer
# (it's on the precise upper bound of our legal interval, but the
# interval is open at the top end), and we'll want to tell
# firstmodbelow to make sure to avoid trying to return it.
exact_non_answer, _ = writeaspowers(b+1, a, base)
debug("modmax", "exact_non_answer =", exact_non_answer)
if exact_non_answer is not None:
exact_non_answer -= minpower
debug("modmax", " adjusted to", exact_non_answer)
if exact_non_answer < 0: exact_non_answer = None
scope = {"a":Spigot(a), "b":Spigot(b),
"base":Spigot(base), "m":Spigot(minpower)}
x = Spigot("log(a,base)", scope)
if exact_answer == 0:
lowerbound = Spigot("0")
else:
lowerbound = Spigot("frac(log(b,base)-m log(a,base))", scope)
if exact_non_answer == 0:
y = Spigot("1")
else:
y = Spigot("frac(log(b+1,base)-m log(a,base))", scope)
debug("modmax", "x =", float(x))
debug("modmax", "target interval [", float(lowerbound), ",", float(y), "]")
if lowerbound > y:
# Special case: minpower was already in the interval!
return minpower
f = make_f(x)
firstupto = Firstupto(x)
n = 0
while True:
# Find m = firstupto(y - f(n)).
k = y - f(n)
debug("modmax", "n =", n)
debug("modmax", "need k =", float(k))
if exact_non_answer is not None:
debug("modmax", "exact_non_answer =", exact_non_answer)
M = exact_non_answer - n
else:
M = None
m = firstupto(k, M)
debug("modmax", "got m =", m)
if m is None or not f(m):
# If firstupto returned None, or f(m) is actually zero,
# that means the convergents of x ran out, so the value n
# we already have is still the best we can do. So return
# it, if it's good enough.
if f(n) < lowerbound:
debug("modmax", "convergents finished, no solution")
return None
debug("modmax", "convergents finished, returning", n)
return n + minpower
debug("modmax", "fm =", float(f(m)))
i_sp = Spigot("(y-fn) / fm", {"fn":f(n), "fm":f(m), "y":y})
if (exact_non_answer is not None and
exact_non_answer >= n and
(exact_non_answer - n) % m == 0):
i_avoid = (exact_non_answer - n) / m
debug("modmax", "avoiding", i_avoid)
i = floor_within_limits(i_sp, i_avoid, None)
if i == i_avoid:
i = floor_within_limits(i_sp, None, i_avoid - 1)
else:
i = floor_within_limits(i_sp, None, None)
debug("modmax", "i =", i)
# Our possible answers are n, n+m, ..., n+im. Pick the first of
# those which is at least lower_bound, if any is.
j_sp = Spigot("(lowerbound-fn) / fm",
{"fn":f(n), "fm":f(m), "lowerbound":lowerbound})
j_limit = i+1
if (exact_answer is not None and
exact_answer <= n + i*m and
(exact_answer - n) % m == 0):
j_limit = min(i, (exact_answer - n) / m)
j = ceil_within_limits(j_sp, 0, j_limit)
debug("modmax", "j =", j)
if j <= i:
debug("modmax", "done!")
return n + j*m + minpower
n = n + i*m
base = 10
a = None
b = None
minpower = None
testmode = soaktestmode = False
dbgclasses_enabled = set()
opts, args = getopt.gnu_getopt(sys.argv[1:], "b:d:m:tT")
for opt, val in opts:
if opt == "-b":
base = long(val)
elif opt == "-d":
dbgclasses_enabled.add(val)
elif opt == "-m":
minpower = long(val)
elif opt == "-t":
testmode = True
elif opt == "-T":
soaktestmode = True
for arg in args:
if a == None:
a = string.atol(arg, base)
elif b == None:
b = string.atol(arg, base)
else:
sys.stderr.write("powbegin.py: unexpected extra argument '%s'\n" % arg)
sys.exit(1)
if (a == None or b == None) and not (testmode or soaktestmode):
sys.stderr.write("usage: powbegin.py <a> <b>\n")
sys.exit(1)
directed_test_cases = [
((2, 13, 10, 0), 17), # nice easy basic case
((7, 10, 10, 0), 0), # b is a power of base (trivial answer!)
((7, 9, 10, 0), 13), # b+1 is a power of base
((7, 49, 10, 0), 2), # b is a power of a
((7, 48, 10, 0), 228), # b+1 is a power of a
((2, 3, 5, 0), 4), # same here, but exercises a different code path
((9, 3, 27, 0), 2), # log_{base}(a) is rational, answer exists
((9, 4, 27, 0), None), # log_{base}(a) is rational, answer does not exist
((14645, 42487246, 36, 0), 34473395), # a larger case to prove it goes fast
((49, 2022, 10, 0), 183), # regression test for a past bug
((7, 49, 10, 3), 73), # test minpower > 0
((7, 49, 10, None), 2), # test auto-discovery of minpower
((2, 7, 10, 46), 46), # test minpower == exactly where we were aiming
((7, 49, 10, 2), 2), # same again but a different code path
]
if testmode or soaktestmode:
passes = 0
fails = 0
class TimeoutException(Exception): pass
def sigalrm(signum, frame):
raise TimeoutException
def runtests(test_cases):
global passes
global fails
for (a, b, base, minpower), expected in test_cases:
desc = (
("power of %d%s starting '%s' in base %d "+
"should be %s") % (
a,
"" if minpower is None else " at least %d" % minpower,
format_in_base(b, base), base,
"None" if expected is None else "%d" % expected))
desc += " [-b%d %s %s%s]" % (
base, format_in_base(a, base), format_in_base(b, base),
"" if minpower is None else " -m%d" % minpower)
debug("test", "test case:", desc)
try:
signal.alarm(10)
got = powbegin(a, b, base, minpower)
if got != expected:
print "test FAILED:", desc, "but got", got
fails += 1
else:
debug("test", "passed")
passes += 1
except Exception as e:
print "test FAILED:", desc, "but threw", repr(e)
debug("test",
"exception traceback:\n" + traceback.format_exc())
fails += 1
finally:
signal.alarm(0)
signal.signal(signal.SIGALRM, sigalrm)
if testmode:
debug("test", "running", len(directed_test_cases), "directed tests")
runtests(directed_test_cases)
if soaktestmode:
debug("testgen", "generating soak tests")
soak_test_dict = {}
max_digits = 6
for base in 4,5,6,8,12: # numbers of the form: p, p^2, p^3, qp, qp^2
max_value = base**max_digits
for a in range(2, 2*base+1):
power_limit = next(power for power in itertools.count()
if a**power >= max_value)
debug("testgen", "doing powers of", a, "in base", base,
"up to", power_limit)
for power in range(power_limit-1, -1, -1):
# Compute the actual value of a^power.
b = a**power
debug("testgen", a, "^", power, "in base", base,
"=", format_in_base(b, base))
# Add zeroes on the end until it has the maximum
# number of digits we handle. (This is because,
# for example, if a larger power of a starts with
# '10' and this one is simply '1', we'll expect
# this smaller power to be returned even for the
# prefix '10', because it will be treated as 1.0.)
while b * base < max_value:
b *= base
# Insert each prefix of it into our list of
# outputs. Since we process powers in descending
# order, we can safely overwrite any value we find
# in our dictionary already.
while b > 0:
debug("testgen", "inserting (",
a, format_in_base(b, base), base, ") ->", power)
soak_test_dict[(a, b, base, 0)] = power
b /= base
soak_test_cases = sorted(soak_test_dict.items())
debug("test", "running", len(soak_test_cases), "soak tests")
runtests(soak_test_cases)
print "passed", passes, "failed", fails
sys.exit(1 if fails > 0 else 0)
else:
print powbegin(a, b, base, minpower)
sys.exit(0)
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