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Docs: r2 is NSE, not cc虏; wind_rose example labels #735

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Docs: r2 is NSE, not cc虏; wind_rose example labels #735

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c4b4836
Clarify that r2 is the coefficient of determination, not cc squared
ecomodeller Oct 22, 2026
07ef7de
Pass measured columns first in the wind_rose example
ecomodeller Oct 22, 2026
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4 changes: 2 additions & 2 deletions docs/user-guide/plotting.qmd
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Expand Up @@ -135,12 +135,12 @@ The radial distance from the point to the observation point is the standard devi

## Directional data (e.g. wind or currents)

Directional data can be plotted using the [`wind_rose`](`modelskill.plotting.wind_rose`). The function takes an array-like structure with speed and direction as columns (from one or two sources) and plots a wind rose:
Directional data can be plotted using the [`wind_rose`](`modelskill.plotting.wind_rose`). The function takes an array-like structure with speed and direction as columns (from one or two sources) and plots a wind rose. With two sources, the first pair is labelled "Measurement" and the second "Model" (see `labels`):

```{python}
import mikeio
ds = mikeio.read("../data/wave_dir.dfs0")
df = ds[[0,2,1,3]].to_dataframe()
df = ds[[1,3,0,2]].to_dataframe() # measured speed, direction, then model
df.round(2).head()
```

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11 changes: 7 additions & 4 deletions src/modelskill/metrics.py
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Expand Up @@ -311,7 +311,9 @@ def kge(obs: ArrayLike, model: ArrayLike) -> Any:
def r2(obs: ArrayLike, model: ArrayLike) -> Any:
r"""Coefficient of determination (R2)

Pronounced 'R-squared'; the proportion of the variation in the dependent variable that is predictable from the independent variable(s), i.e. the proportion of explained variance.
Same value as Nash-Sutcliffe efficiency and scikit-learn's `r2_score`.
Not squared Pearson correlation (`cc**2`): r2 penalises bias and amplitude
errors, and is negative when the model is worse than the observed mean.

$$
R^2 = 1 - \frac{\sum_{i=1}^n (model_i - obs_i)^2}
Expand All @@ -320,9 +322,10 @@ def r2(obs: ArrayLike, model: ArrayLike) -> Any:

Range: $(-\infty, 1]$; Best: 1

Notes
-----
r2 = nash_sutcliffe_efficiency(nse)
See Also
--------
nash_sutcliffe_efficiency
cc

Examples
--------
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