cinrad.visualize package

cinrad.visualize.ppi module

class cinrad.visualize.ppi.PPI(data: Dataset, fig: Optional[Any] = None, norm: Optional[Any] = None, cmap: Optional[Any] = None, nlabel: Optional[int] = None, label: Optional[List[str]] = None, dpi: Union[int, float] = 350, highlight: Optional[Union[str, List[str]]] = None, coastline: bool = False, extent: Optional[List[Union[int, float]]] = None, section: Optional[Dataset] = None, style: str = 'black', add_city_names: bool = False, plot_labels: bool = True, **kwargs)

Bases: object

Create a figure plotting plan position indicator

By default, norm, cmap, and colorbar labels will be determined by the data type.

Args:

data (xarray.Dataset): The data to be plotted.

fig (matplotlib.figure.Figure): The figure to plot on. Optional.

norm (matplotlib.colors.Normalize): Customized norm data. Optional.

cmap (matplotlib.colors.Colormap): Customized colormap. Optional.

nlabel (int): Number of labels on the colorbar. Optional.

dpi (int): DPI of the figure. Optional.

highlight (str, list(str)): Areas to be highlighted. Optional.

coastline (bool): Plot coastline on the figure if set to True. Default False.

extent (list(float)): The extent of figure. Optional.

add_city_names (bool): Label city names on the figure if set to True. Default True.

plot_labels (bool): Text scan information on the side of the plot. Default True.

gridlines(draw_labels: bool = True, linewidth: Union[int, float] = 0, **kwargs)

Draw grid lines on cartopy axes

plot_cross_section(data: Dataset, ymax: Optional[int] = None, linecolor: Optional[str] = None, interpolate: bool = True)

Plot cross section data below the PPI plot.

plot_range_rings(_range: Union[int, float, list], color: str = 'white', linewidth: Union[int, float] = 0.5, **kwargs)

Plot range rings on PPI plot.

storm_track_info(filepath: str)

Add storm tracks from Nexrad Level III (PUP) STI product file

cinrad.visualize.rhi module