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2 changes: 1 addition & 1 deletion content/en/_index.md
Original file line number Diff line number Diff line change
Expand Up @@ -32,7 +32,7 @@ MATLAB and Mathematica. Wave 1 is under way, in four organisations:

| Organisation | Package | Status | Pages |
| --- | --- | --- | --- |
| go-approx | [interp](https://github.com/go-approx/interp) | released v0.1.0 | [go-approx]({{< relref "approx" >}}) |
| go-approx | [interp](https://github.com/go-approx/interp) | released v0.2.0 | [go-approx]({{< relref "approx" >}}) |
| go-approx | [poly](https://github.com/go-approx/poly) | released v0.1.0 | [go-approx]({{< relref "approx" >}}) |
| go-dsp | [signal](https://github.com/go-dsp/signal) | released v0.1.0 | [go-dsp]({{< relref "dsp" >}}) |
| go-sparse | [sparse](https://github.com/go-sparse/sparse) | released v0.1.0 | [go-sparse]({{< relref "sparse" >}}) |
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11 changes: 7 additions & 4 deletions content/en/approx.md
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@@ -1,6 +1,6 @@
---
title: "go-approx"
description: "Interpolation, splines and polynomials. interp and poly are released v0.1.0."
description: "Interpolation, splines and polynomials. interp is released v0.2.0 and poly v0.1.0."
---

go-approx is the home of approximation in the parity plan: interpolation,
Expand All @@ -9,15 +9,18 @@ data.

| Package | Status | Repository |
| --- | --- | --- |
| interp | released v0.1.0 | [go-approx/interp](https://github.com/go-approx/interp) |
| interp | released v0.2.0 | [go-approx/interp](https://github.com/go-approx/interp) |
| poly | released v0.1.0 | [go-approx/poly](https://github.com/go-approx/poly) |

## What is verified

From [STATUS.md](https://github.com/go-scikit/roadmap/blob/main/STATUS.md):
`numpy.interp`, `interp1d`, PCHIP, Akima and `poly1d` are bit-identical to
NumPy and SciPy; splines agree within 1e-15 to 1e-10. The remaining `interp`
gaps are in progress. The speed comparison with the Python reference is in
NumPy and SciPy; splines agree within 1e-15 to 1e-10. `interp` v0.2.0 adds `Splrep`
(FITPACK's legacy `splrep`) and is faster than SciPy on every case measured
except two still open: `RegularGridInterpolator` linear evaluation at 10^3 to
10^4 points (0.95 to 0.98x) and shuffled-query cubic evaluation at 10^4 points
(0.94x). The speed comparison with the Python reference is in
[interp's docs/perf.md](https://github.com/go-approx/interp/blob/main/docs/perf.md).

## Where to read more
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