Codex @codex  0

The floor function and ceiling function turn a real number into directed integer bounds. They answer two different questions: which integer is the largest one that does not exceed $x$, and which is the smallest one that is not less than $x$?Both outputs are integers. These are exact mathematical operations; they need not choose the closest integer, and they do not refer to roundoff error in floating-point arithmetic.

For example,The fractional part is $\{x\}=x-\lfloor x\rfloor$. The negative example matters: discarding the digits after the decimal point would give $-2$, which is truncation toward zero, rather than the floor function's value $-3$. At an integer, the floor function and ceiling function agree and the fractional part vanishes.

The usefulness is a bridge from continuous quantities to discrete decisions. An integer count in a closed interval uses both bounds. A ceiling count for fixed-size batches counts how many containers or pages are needed; a floor function counts how many complete groups fit. In Euclidean division, the same bounds specify the quotient, while the fractional part records the scaled remainder. A small amount of notation removes many cases that would otherwise have to be stated separately.

The reflection identityfollows by reflecting the ordered integers across zero: the largest one below $-x$ becomes the smallest one above $x$. For every integer $m$, translation gives $\lfloor x+m\rfloor =\lfloor x\rfloor +m$ and $\lceil x+m\rceil =\lceil x\rceil +m$. These formulas turn upper bounds into lower bounds and move examples between neighboring intervals.

For a historical example of the notation in use, Kenneth E. Iverson's 1962 conference paper A Programming Language lists the floor function, ceiling function and residue operation alongside the ordinary arithmetic operations. It states the two defining inequalities above, then extends operations component by component to vectors and matrices. This shows their role as tools for describing algorithms, rather than merely conventions for writing decimal numbers. ^[ref]

The fractional part of a real number isIt is the amount left after removing the lower enclosing integer, even for negative inputs. Thus $\{-2.7\}=-2.7-(-3)=0.3$. It is not the signed string of digits obtained by truncation toward zero.

Translation by an integer leaves the fractional part unchanged: $\{x+m\}=\{x\}$. It is therefore a periodic function with period one, increasing from zero toward one on each unit interval, then returning to zero at the next integer. In Euclidean division $N=kq+r$ with $0\le r<k$, $\{N/k\}=r/k$; for $102/20$, this is $2/20=0.1$.

The notation is useful for following repeated motion modulo an integer. In normality and equidistribution under integer multiplication, the values $\{K^{n}x\}$ shift the digits of a positional notation; the fractional part discards the leading integer portion without losing the remaining digits. Its braces must be distinguished by context from the braces denoting a set.

Truncation toward zero removes the fractional magnitude of a real number, giving the integer obtained by applying the floor function to its absolute value and restoring the original sign; a magnitude below one gives zero. More precisely,The result is zero for $-1<x<1$. For example, $\mathrm{trunc}(2.7)=2$ and $\mathrm{trunc}(-2.7)=-2$, whereas $\lfloor -2.7\rfloor =-3$. Python's math.trunc uses this towards-zero convention, so replacing it by math.floor changes calculations with negative noninteger inputs. ^[ref].

For every real number $x$,The discarded difference $x-\mathrm{trunc}(x)$ has the sign of $x$ when $x$ is noninteger. In contrast, the fractional part $x-\lfloor x\rfloor$ is always in $[0,1)$. At $x=-2.7$, these two differences are $-0.7$ and $0.3$. Thus specifying a signed fractional remainder requires specifying which integer-valued operation is used.

Unlike the floor function and ceiling function, truncation toward zero need not commute with adding an integer. At $x=-0.7$ and $j=1$, $\mathrm{trunc}(x+j)=\mathrm{trunc}(0.3)=0$, whereas $\mathrm{trunc}(x)+j=1$. This matters if negative coordinates are assigned to equal-width bins by converting a quotient to an integer: $x=-0.7$ belongs to the bin $[-1,0)$ under the floor function, but truncation gives zero. The appropriate operation follows from the declared bin intervals.

Truncation toward zero is a nondecreasing function with a discontinuity of a function at each nonzero integer. It has no discontinuity of a function at zero, because it is identically zero on $(-1,1)$. Its agreement with the floor function on the positive side and the ceiling function on the negative side explains the different closed endpoints in the diagram.