id stringlengths 4 6 | values listlengths 2.05k 2.05k |
|---|---|
gp-0 | [
-2.0421857833862305,
-2.0659384727478027,
-2.0396528244018555,
-2.00286602973938,
-1.9908727407455444,
-2.0044643878936768,
-1.9387058019638062,
-1.9628918170928955,
-1.9268512725830078,
-1.9276092052459717,
-1.889709711074829,
-1.8869171142578125,
-1.8853278160095215,
-1.8361810445785522,... |
gp-1 | [
-0.17863984405994415,
-0.1849057525396347,
-0.19102059304714203,
-0.19670884311199188,
-0.20291520655155182,
-0.2088819444179535,
-0.2147858589887619,
-0.22050151228904724,
-0.22677557170391083,
-0.23242972791194916,
-0.23791030049324036,
-0.24459046125411987,
-0.25052404403686523,
-0.2561... |
gp-2 | [
-10.151269912719727,
-10.165299415588379,
-10.143339157104492,
-10.1659574508667,
-10.106721878051758,
-10.129286766052246,
-10.138358116149902,
-10.104887008666992,
-10.127388000488281,
-10.125205993652344,
-10.088517189025879,
-10.075834274291992,
-10.051020622253418,
-10.065463066101074... |
gp-3 | [
-1.7184216976165771,
-1.7015501260757446,
-1.7057307958602905,
-1.715108036994934,
-1.7140448093414307,
-1.7274680137634277,
-1.7067182064056396,
-1.7291373014450073,
-1.732462763786316,
-1.7214291095733643,
-1.7353907823562622,
-1.733845591545105,
-1.7377575635910034,
-1.7275023460388184,... |
gp-4 | [
4.593202590942383,
4.696541786193848,
4.640899658203125,
4.8155364990234375,
4.566860198974609,
4.650455951690674,
4.6010355949401855,
4.642905235290527,
4.572269439697266,
4.783222198486328,
4.722860813140869,
4.756433486938477,
4.794796943664551,
4.810237884521484,
4.921975135803223,
... |
gp-5 | [0.15466614067554474,0.1603952795267105,0.14881598949432373,0.14312763512134552,0.13453827798366547,(...TRUNCATED) |
gp-6 | [0.054401278495788574,0.05440128594636917,0.05440126731991768,0.05440137907862663,0.0544012375175952(...TRUNCATED) |
gp-7 | [-1.7641507387161255,-1.7631336450576782,-1.7574583292007446,-1.760299801826477,-1.7545568943023682,(...TRUNCATED) |
gp-8 | [-0.07880464941263199,-0.08099263161420822,-0.0795377865433693,-0.08892051875591278,-0.0893061310052(...TRUNCATED) |
gp-9 | [1.1510509252548218,0.6343850493431091,-0.08724723756313324,-0.026637330651283264,-0.280395328998565(...TRUNCATED) |
skycmd synthetic time series (s6-cast generators)
A fixed sample of the four synthetic series generators that pretrain the s6-cast forecaster (Gaussian processes, pulses, trend-seasonality-irregular, SARIMA), and of their training mix. Generated by skycmd's own Rust code: no third-party data.
Part of skycmd, tiny decision models trained from scratch in Rust that run in the
browser. Written by sky-train cast-synth --kind <family> --n 1000 --len 2048 --seed 1, and --n 4000 for the mix at commit 8cc8e276.
Licences of every set: DATA_LICENSES.md.
Each row is one synthetic series: id (<family>-<i>) and values (2,048 floats). The generators
are ours (crates/sky-infer/src/cast/synth.rs), after Reverso (arXiv 2602.17634, appendix B) and
Simulation Alone (arXiv 2601.00970), and deterministic per seed. s6-cast does not train on these
rows: it trains on an endless stream from the same generators (a refreshed pool, other seeds).
This repository is a fixed sample of that stream (sky-train cast-synth --seed 1 --len 2048), to
inspect the generators or to pretrain another forecaster on the same distribution.
Sources and licences
Each config is one source and keeps its source's licence (share-alike sources stay share-alike). Attribution goes to the upstream authors; the conversion is ours.
| config | upstream | licence | how it is used | rows |
|---|---|---|---|---|
gp |
ours: sky_infer::cast::synth, family gp |
apache-2.0 | KernelSynth-style Gaussian-process draws: 1 to 5 kernels (constant, linear, RBF, rational quadratic, Matérn, periodic) combined by sum or product, sampled with random Fourier features | 1,000 |
mixed |
ours: the training mix | apache-2.0 | the four families drawn with weights 0.3 / 0.15 / 0.3 / 0.25, as in s6-cast training | 4,000 |
pulse |
ours: family pulse |
apache-2.0 | trapezoid pulse trains (spikes or dips) over a baseline, with noise | 1,000 |
sarima |
ours: family sarima |
apache-2.0 | seasonal ARIMA with stationary AR parts (sampled through their partial autocorrelations), optional differencing | 1,000 |
tsi |
ours: family tsi |
apache-2.0 | trend (linear, exponential, polynomial, piecewise) + up to 3 seasonal waves + Gaussian, Laplace or Student-t noise + outliers + level shifts | 1,000 |
Files
| file | rows |
|---|---|
data/gp.parquet |
1,000 |
data/mixed.parquet |
4,000 |
data/pulse.parquet |
1,000 |
data/sarima.parquet |
1,000 |
data/tsi.parquet |
1,000 |
from datasets import load_dataset
ds = load_dataset("maxgfr/skycmd-cast-synth", "gp")
skycmd wrote no row with a language model: the targets come from the upstream labels (some upstream sets carry their own teacher soft labels, see their cards), the games' oracles or our generators.
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