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Minor paper rendering fix
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scls19fr committed Aug 20, 2018
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Expand Up @@ -34,7 +34,8 @@ Windrose is a Python library to manage wind data, draw windroses (also known as

The initial use case of this library was for a technical report concerning pollution exposure and wind distributions analyzes. Data from local pollution measures and meteorologic informations from various sources like Meteo-France were used to generate a pollution source wind rose.

It is also used by some contributors for teaching purpose
It is also used by some contributors for teaching purpose.

![Map overlay](screenshots/overlay.png)

Some others contributors have used it to make figures for a [wind power plant control optimization study](https://www.nrel.gov/docs/fy17osti/68185.pdf).
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# Examples

The bar plot wind rose is the most common plot
- The bar plot wind rose is the most common plot

-![Windrose (bar) example](screenshots/bar.png)
![Windrose (bar) example](screenshots/bar.png)

Contour plots are also possible
- Contour plots are also possible

-![Windrose (contourf-contour) example](screenshots/contourf-contour.png)
![Windrose (contourf-contour) example](screenshots/contourf-contour.png)

Several windroses can be plotted using subplots to provide a plot per year with for example subplots per month
- Several windroses can be plotted using subplots to provide a plot per year with for example subplots per month

-![Windrose subplots](screenshots/subplots.png)
![Windrose subplots](screenshots/subplots.png)

Probability density functions may be plotted. Fitting Weibull distribution is enabled by Scipy.
- Probability density functions may be plotted. Fitting Weibull distribution is enabled by Scipy.
The Weibull distribution is used in weather forecasting and the wind power industry to describe wind speed distributions, as the natural distribution of wind speeds often matches the Weibull shape

-![pdf example](screenshots/pdf.png)
![pdf example](screenshots/pdf.png)

# More advanced usages

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