quatint
Exact (integer-backed) quaternion arithmetic for the Hurwitz integers.
quatint provides a fast, mypyc-friendly hurwitzint type that behaves like a small, practical numeric object: addition/subtraction/multiplication/power, norms and conjugation, plus left/right Euclidean division, left/right gcd, and deterministic factorization utilities.
Why this exists
Python’s built-in numeric types don’t provide an exact, integer-backed quaternion type—especially not one that can represent the Hurwitz order (a + b i + c j + d k) / 2 without floating point.
quatint keeps everything as integers under the hood while still letting you work with both:
- Lipschitz integers: $a, b, c, d ∈ Z$
- Hurwitz “half” integers: $(a + b i + c j + d k)/2$ with a parity constraint
Key features
- Exact arithmetic (no floats required for quaternion values)
- Hurwitz order representation with parity enforcement
- Non-commutative multiplication
- Reduced norm $N(q) ∈ Z$ and quaternion conjugation
- Euclidean division (norm-Euclidean) via:
divmod(a, b)for left-quotient division (a = q*b + r)a.rdivmod(b)(orquatint.rdivmod(a, b)) for right-quotient division (a = b*q + r)
- Left/right gcd (
gcd_left,gcd_right) built on the corresponding division - Deterministic factorization into
content,unit, and Hurwitz primes (by prime norms)
New helper methods on every Hurwitz integer value:
x.content()— largest positive integernsuch thatx = n*yfor another Hurwitz integery.x.factor_right()— a plain ordered tuple of factors whose product viaprod_right(...)is exactlyx.x.factor_left()— a plain ordered tuple of factors whose product viaprod_left(...)is exactlyx.x.factor_right_detail()— structured right factorization as aNonCommutativeFactorization.x.factor_left_detail()— structured left factorization as aNonCommutativeFactorization.
Installation
python -m pip install quatint
This project is designed to compile cleanly with mypyc for speed (CI/test setups often ensure the compiled artifact is what’s running).
Quick start
from quatint import hurwitzint
a = hurwitzint(1, 1, 1, 1)
b = hurwitzint(2, 3, 4, 5)
print(a) # (1+i+j+k)
print(a * b) # (-10+6i+4j+8k)
print(b * a) # (-10+4i+8j+6k)
Half-integers (Hurwitz elements)
Use half=True to provide numerator components of a /2 element:
from quatint import hurwitzint
h = hurwitzint(1, 3, 5, 7, half=True)
print(h) # (1+3i+5j+7k)/2
Division (left-quotient)
divmod(a, b) defines quotient on the left:
from quatint import hurwitzint
a = hurwitzint(2, 3, 4, 53)
b = hurwitzint(1, 2, 3, 4)
q, r = divmod(a, b)
assert q * b + r == a
Right-division (right-quotient)
Use rdivmod (method or helper) to define quotient on the right:
from quatint import hurwitzint, rdivmod
a = hurwitzint(2, 3, 4, 53)
b = hurwitzint(1, 2, 3, 4)
q, r = rdivmod(a, b)
assert b * q + r == a
GCD (left and right)
Because multiplication is non-commutative, there are two natural gcd notions:
from quatint import hurwitzint
a = hurwitzint(2, 3, 4, 53)
b = hurwitzint(1, 2, 3, 4)
gl = a.gcd_left(b) # common left divisor (a = gl*x, b = gl*y)
gr = a.gcd_right(b) # common right divisor (a = x*gr, b = y*gr)
Factorization
quatint exposes two levels of factorization API:
factor_right()/factor_left()return a simple ordered tuple of factors.factor_right_detail()/factor_left_detail()return a structuredNonCommutativeFactorizationwith metadata.
Use the plain methods when you just want factors that multiply back to the original value. Use the detailed methods when you care about the separated integer content, unit, normalized prime factors, or canonical ordering.
Plain factorization
The flat factorization methods return a tuple of hurwitzint factors. Because multiplication is non-commutative, the order and direction matter.
from quatint import hurwitzint, prod_left, prod_right
n = hurwitzint(2, 3, 4, 53)
right_factors = n.factor_right()
assert prod_right(right_factors) == n
left_factors = n.factor_left()
assert prod_left(left_factors) == n
For factor_right(), multiply the returned factors using prod_right(...), which behaves like ordinary left-to-right multiplication:
assert prod_right((a, b, c)) == a * b * c
For factor_left(), multiply the returned factors using prod_left(...), which multiplies each new factor on the left:
assert prod_left((a, b, c)) == c * b * a
Detailed factorization
The detailed methods return a compact normal form, in a class called NonCommutativeFactorization with these properties:
content: maximal positive integer scalar dividing the element (in the Hurwitz sense)unit: a norm-1 Hurwitz unit (deterministically chosen)primes: Hurwitz primes (each with prime rational norm), normalized via unit migration
NonCommutativeFactorization also exposes some utility methods for convenience, such as:
from quatint import hurwitzint
n = hurwitzint(2, 3, 4, 53)
fr = n.factor_right_detail()
assert fr.prod_right() == n
fl = n.factor_left_detail()
assert fl.prod_left() == n
Representation & guarantees
Internal representation
Values are stored in numerator units:
(A + B i + C j + D k) / 2
This means:
- Lipschitz integers are stored with even numerators.
- True Hurwitz half-integers are stored with odd numerators.
- The constructor enforces the parity constraint.
Scalar coercions
int and float inputs are accepted as scalars and converted via int(...) (i.e., truncation semantics). Quaternion values themselves remain exact.
Public API (high level)
hurwitzint(a=0, b=0, c=0, d=0, *, half=False)hurwitzint.conjugate()abs(h)→ reduced normN(h)(anint)divmod(a, b)→ left-quotient Euclidean divisiona.rdivmod(b)/rdivmod(a, b)→ right-quotient Euclidean divisiona.gcd_left(b)/gcd_left(a, b)a.gcd_right(b)/gcd_right(a, b)a.factor_left_detail()/a.factor_right_detail()→NonCommutativeFactorizationNonCommutativeFactorization.prod_left()/.prod_right()/.prod()
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Release files for quatint 0.0.9
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