xbitinfo.graphics.plot_distribution
xbitinfo.graphics.plot_distribution#
- xbitinfo.graphics.plot_distribution(ds, nbins=1000, cmap='viridis', offset=0.01, close_zero=0.01)[source]#
Plot statistical distributions of all variables as in Klöwer et al. 2021 Figure SI 1. For large data subsetting, i.e. ds = ds.isel(x=slice(None, None, 100)) is recommended.
Klöwer, M., Razinger, M., Dominguez, J. J., Düben, P. D., & Palmer, T. N. (2021). Compressing atmospheric data into its real information content. Nature Computational Science, 1(11), 713–724. doi: 10/gnm4jj
- Parameters
bitinfo (
xarray.Dataset
) – Raw input values for distributionsnbints (int) – Number of bins for histograms across all variable range. Defaults to
1000
.cmap (str) – Which matplotlib colormap to use. Defaults to
"viridis"
.offset (float) – Offset on the yaxis between variables 0 lines. Defaults to
0.01
.close_zero (float) – Threshold where to stop close to 0, when distributions ranges from negative to positive. Increase this value when seeing an unexpected dip around 0 in the distribution. Defaults to
0.01
.
- Returns
fig (matplotlib figure)
Example
>>> ds = xr.tutorial.load_dataset("eraint_uvz") >>> xb.plot_distribution(ds) <AxesSubplot:title={'center':'Statistical distributions'}, xlabel='value', ylabel='Probability density'>