PyNGL Home > Functions > Graphics routines

Ngl.streamline_scalar_map

Creates and draws streamlines, colored by a scalar field, over a map.

Available in version 1.3.0 or later.

Prototype

stmap = Ngl.streamline_scalar_map(wks, u, v, data, res=None)

Arguments

wks

The identifier returned from calling Ngl.open_wks.

u, v

The U and V components of the streamlines. u and v should be two-dimensional NumPy arrays or NumPy masked arrays (dimensioned ny x nx).

data

The scalar data field for coloring the streamlines (dimensioned ny x nx).

res=None

An (optional) instance of the Resources class having PyNGL resources as attributes.

Description

This function creates and draws streamlines, colored by a scalar field, over a map on the given workstation and advances the frame. Plot options can be set via the res variable.

In order to overlay streamlines on a map plot, you must tell the streamline plot (and the scalar field) where on the map it is being overlaid (in latitude/longitude degrees). You can do this via the array resources vfXArray (sfXArray) and vfYArray (sfYArray), or the vfXCStartV (sfXCStartV), vfXCEndV (sfXCEndV), vfYCStartV (sfYCStartV), vfYCEndV (sfYCEndV) resources.

As of version 1.3.0, if u, v, and/or data are masked arrays, then any values equal to the corresponding fill values will not be plotted. If u, v, and/or data are not masked arrays and they contain missing values, then set the resources vfMissingUValueV, vfMissingVValueV, and/or sfMissingValueV to these values.

Note that PyNGL internally sets some resources for you, depending on how other resources are set. See the list of default settings for more information.

See Also

Ngl.vector_scalar, Ngl.vector, Ngl.vector_map, Ngl.streamline, Ngl.streamline_scalar, Ngl.streamline_map,

MapPlot resources
StreamlinePlot resources
ContourPlot resources
VectorField resources
ScalarField resources
LabelBar resources
Title resources
TickMark resources
Transformation resources
View resources
Transform resources
PlotManager resources
Special "ngl" resources

Examples

See stream_scalar.py (output) in the gallery.