Fitting the same degree-11 polynomial in two bases
At its defaults it draws fitting the same degree-11 polynomial in two bases. On the left, the data and two fitted curves that lie on top of each other. On the right, the condition numbers of the two design matrices, ten orders of magnitude apart.
basis-conditioning is one function in lib/figures/lsq.js —
least squares — the projection, the road not to take, and the valley with no bottom. Everything below came out of it during this build, at
arguments taken from the essays rather than invented for this page. A figure here is the
figure a reader meets in an essay, and if the generator changes, this page changes with it.
At its defaults
Drawn even though every essay passes arguments — which on this site is every essay, at 100% of placements since the standard pass. A default nothing exercises is a trap for the next essay to call this with none, and this is the page where a default that has drifted from the figures around it becomes visible.
On the left, the data and two fitted curves that lie on top of each other. On the right, the condition numbers of the two design matrices, ten orders of magnitude apart.
show: "kappa", points: "gap"
The arguments are the ones A basis built from the points passes. A value nobody placed would be a picture no essay asked for and no claim was ever checked against.
Three bases for the polynomials of each degree, on a logarithmic axis. The monomial design matrix reaches 1.5·10¹⁷ by degree 48; Chebyshev polynomials reach 1.55·10⁷; the basis built from the sample points by Arnoldi's process is orthonormal on them and its condition number is 1 to rounding at every degree. The dashed line is 1/u, past which a double cannot hold the matrix's conditioning at all.
deg: 11
The arguments are the ones A basis built from the points passes. A value nobody placed would be a picture no essay asked for and no claim was ever checked against.
On the left, the data and two fitted curves that lie on top of each other. On the right, the condition numbers of the two design matrices, ten orders of magnitude apart.
show: "noise"
The arguments are the ones A basis built from the points passes. A value nobody placed would be a picture no essay asked for and no claim was ever checked against.
The largest distance, at the sample points, between the least-squares curve computed in monomials or in Chebyshev polynomials and the same fit computed in the basis Arnoldi builds from the points, on a logarithmic axis against the degree. With noise of 0.001 the residual is 8.3·10⁻⁴, and each basis's curve is off by about its condition number times the unit roundoff times that residual — the dashed line of the same colour. At degree 48 the monomial curve is off by 0.004 and the Chebyshev curve by 2.4·10⁻¹⁵.
show: "noise", noise: 0.1
The arguments are the ones A basis built from the points passes. A value nobody placed would be a picture no essay asked for and no claim was ever checked against.
The largest distance, at the sample points, between the least-squares curve computed in monomials or in Chebyshev polynomials and the same fit computed in the basis Arnoldi builds from the points, on a logarithmic axis against the degree. With noise of 0.1 the residual is 0.083, and each basis's curve is off by about its condition number times the unit roundoff times that residual — the dashed line of the same colour. At degree 48 the monomial curve is off by 0.4 and the Chebyshev curve by 2.9·10⁻¹⁵.
show: "noise", points: "clustered"
The arguments are the ones A basis built from the points passes. A value nobody placed would be a picture no essay asked for and no claim was ever checked against.
The largest distance, at the sample points, between the least-squares curve computed in monomials or in Chebyshev polynomials and the same fit computed in the basis Arnoldi builds from the points, on a logarithmic axis against the degree. With noise of 0.001 the residual is 8.5·10⁻⁴, and each basis's curve is off by about its condition number times the unit roundoff times that residual — the dashed line of the same colour. At degree 48 the monomial curve is off by 6.6·10⁻⁴ and the Chebyshev curve by 2.9·10⁻¹³.
What it checked while drawing
Every figure above checked its own claims on the way to being drawn, and a claim that failed
would have stopped the picture rather than shipped a wrong one. Those checks used to leave
no trace at all: a passing one returned true and the only evidence the figure had
checked anything was that nothing crashed. The list below is what they actually said, collected
by running this generator with an observer installed — not a description of
what it is believed to check.
39 distinct claims across 6 sets of arguments, grouped below by shape — because most of them are one sentence with a different number in it, and how many separate times that sentence was put to the test is the informative part.
the basis built from the points is orthonormal on them at degree 4 — checked 12 times
the monomial curve's distance from the orthogonal one is κ·u·rms(r) to within the constant at degree 20 — checked 8 times
a new direction to add at this degree
a noise level the dial draws
a noise level the study draws
a point set the sweep defines
a point set this file defines
a reading of the basis this generator draws
a sample the dense least squares is affordable on
a top degree the sweep reaches in steps of four
and the 1/u label has room above its line
and the badly conditioned one still fits the data
and the monomials are not
at enough degrees for the relation to be read
every ratio fits the axis
no noise, or a noise level between 10⁻⁹ and 10⁻¹
the badge sits clear of every line
the legend clears the axis label on their shared line
the monomial basis is far worse conditioned
the well-conditioned fit is excellent
while its coefficients have blown up
Against the rule
It draws a decomposition and prints its residual. It calls
lstsqQR,
and every figure above carries the badge — which residualcheck verifies by looking
for it in the emitted SVG rather than by finding the call that builds one. A badge that is
constructed and then left out of the body is the failure that check exists for.
Across the library: the rule bites on 217
of 397 generators —
199 print a residual and
18 are exempt with a published reason;
180 factorise nothing.
Read from lib/residual-rule.js, which is the same body the gate enforces from,
and the gate's last check fails the build if this page and it disagree about any generator.
Where it is called
Changing this generator changes every figure on this list. That is what makes the list worth publishing rather than keeping in a check script.
A basis built from the points
A polynomial fit computed in monomials and in an orthogonal basis gives the same curve on exact data, and the valley essay drew the two lying on top of each other. Add 0.1% noise and they separate — by 1.7·10⁻⁵ at degree 40 and 0.004 at degree 48 — because the fitted curve moves with the basis by its condition number times the rounding times the residual. Chebyshev polynomials keep that small only on points spread like their weight; on a sample with a hole in it they reach κ = 1.55·10⁷. A basis orthogonalised against the sample points themselves stays at 1 on every set.
Least squares, and the road not to takeThe degree that is safe to overshoot
The rules that choose a Tikhonov parameter miss by factors of millions on one draw in twenty. Transplanted to the degree of a polynomial fit, in a basis orthonormal on the data, the same rules never cost more than 2.7 times the best degree's error in three hundred draws. The reason is the shape of the valley they search: six degrees too few costs from 44 to 16,000 times the best error, forty degrees too many costs about twice it. The one rule with a tail, the discrepancy principle, has its threshold half a standard deviation above the residual it is waiting for.
Least squares, and the road not to takeThe valley with no bottom
A degree-nine fit's coefficients can be moved by a third of their own size before the residual changes in the sixth significant figure. The arithmetic did not lose those digits. The data never contained them.