easyclimate.plot.mpas¶

Convenience imports for the mpas_plot package.

Submodules¶

Functions¶

`plot_cell_voronoi`(ds, da, *[, ax, transform, lon_min, ...])	Plot MPAS cell-centered scalar field on native polygon cells.
`plot_voronoi_grid`(data[, verticesOnEdge, lonVertex, ...])	Plot MPAS Voronoi mesh edges.
`extract_cell_latlon`(ds, *[, da, lon_min, lon_max, ...])	Extract and wrap MPAS cell and vertex lon/lat.
`plot_cell_contour`(ds, da, *[, ax, lon_min, lon_max, ...])	Draw contour lines for MPAS cell-centered scalar field.
`plot_cell_contourf`(ds, da, *[, ax, lon_min, lon_max, ...])	Draw filled contour for MPAS cell-centered scalar field.
`plot_vertex_voronoi`(ds, da, *[, ax, transform, ...])	Plot MPAS vertex-centered scalar data on dual polygons.
`plot_vertex_contour`(ds, da, *[, ax, lon_min, lon_max, ...])	Draw contour lines for MPAS vertex-centered scalar field.
`plot_vertex_contourf`(ds, da, *[, ax, lon_min, ...])	Draw filled contour for MPAS vertex-centered scalar field.
`plot_cell_quiver`(ds, u_da, v_da, *[, ax, lon_min, ...])	Plot cell-centered vector wind on MPAS mesh.
`plot_cell_curved_quiver`(...)	Plot MPAS cell-centered vector wind as curved quiver trajectories.
`plot_cell_barbs`(ds, u_da, v_da, *[, ax, lon_min, ...])	Plot cell-centered vector wind as wind barbs on an MPAS mesh.
`plot_cell_streamplot`(ds, u_da, v_da, *[, ax, lon_min, ...])	Plot cell-centered vector wind as streamlines on an MPAS mesh.

Package Contents¶

easyclimate.plot.mpas.plot_cell_voronoi(ds, da, *, ax=None, transform=None, lon_min=None, lon_max=None, lat_min=None, lat_max=None, auto_extent=True, extent_margin=0.05, cell_margin=0.05, global_plot=False, input_radians=True, center_lon=None, skip_large_lon_jump=True, max_polygon_lon_span=180.0, cmap=None, vmin=None, vmax=None, symmetric=False, percentile=98, edgecolor='none', linewidth=0.0, add_colorbar=True, cbar_kwargs=None, title=None, xlabel='Longitude', ylabel='Latitude', aspect='auto', lon_name_cell='lonCell', lat_name_cell='latCell', lon_name_vertex='lonVertex', lat_name_vertex='latVertex', vertices_on_cell_name='verticesOnCell', n_edges_on_cell_name='nEdgesOnCell', use_geometry_cache=True)¶

Plot MPAS cell-centered scalar field on native polygon cells.

The scalar field is rendered on each native MPAS cell polygon. The function works with both plain Matplotlib axes and Cartopy GeoAxes.

Parameters¶

dsxarray.Dataset: Dataset containing MPAS mesh geometry.
daxarray.DataArray or numpy.ndarray: Cell-centered scalar field. Must be 1D on nCells after selection.
axmatplotlib.axes.Axes, optional: Axes on which to draw. By default, use the current axes.
projectioncartopy.crs.CRS, optional: Reserved for compatibility with older call sites.
transformcartopy.crs.CRS, optional: Coordinate reference system of the input coordinates for Cartopy axes.
lon_min, lon_max, lat_min, lat_maxfloat, optional: Plot extent. Cross-dateline windows are supported, for example: lon_min=-190, lon_max=-60 describes the continuous longitude window from 170E to 60W.
auto_extentbool, default: True: If True and no explicit extent is supplied, infer the extent from valid cell centers.
extent_marginfloat, default: 0.05: Fractional margin added to the automatically inferred extent.
cell_marginfloat, default: 0.05: Extra fraction of the plot extent used to select cells outside the visible window. This helps avoid missing partial cells along boundaries.
global_plotbool, default: False: If True, draw a global extent centered on center_lon.
input_radiansbool, default: True: If True, MPAS longitude and latitude variables are interpreted as radians and converted to degrees.
center_lonfloat, optional: Longitude wrapping center. If None, inferred from lon_min/lon_max or valid cell centers.
skip_large_lon_jumpbool, default: True: If True, skip polygons with very large wrapped longitude spans.
max_polygon_lon_spanfloat, default: 180.0: Maximum accepted wrapped polygon longitude span in degrees.
cmapstr or matplotlib.colors.Colormap, optional: Colormap used for cell values.
vmin, vmaxfloat, optional: Color limits. If omitted, infer them from selected values.
symmetricbool, default: False: If True, infer symmetric color limits around zero.
percentilefloat, default: 98: Percentile used for automatic color-limit inference.
edgecolor, linewidth: Polygon edge style passed to matplotlib.collections.PolyCollection.
add_colorbarbool, default: True: If True, add a colorbar for the polygon collection.
cbar_kwargsdict, optional: Keyword arguments passed to Figure.colorbar.
titlestr, optional: Axes title. If None, use the data long name.
figsize(float, float), default: (8, 6): Reserved for compatibility with older call sites.
xlabel, ylabelstr: Axis labels used for plain Matplotlib axes.
aspectstr or float, default: “auto”: Aspect setting used for plain Matplotlib axes.
lon_name_cell, lat_name_cell, lon_name_vertex, lat_name_vertexstr: MPAS coordinate variable names.
vertices_on_cell_name, n_edges_on_cell_namestr: MPAS connectivity variable names.
use_geometry_cachebool, default: True: If True, cache native cell polygon geometry for repeated calls.

Returns¶

axmatplotlib.axes.Axes: Axes containing the plot.
pcmatplotlib.collections.PolyCollection: Polygon collection added to the axes.

MPAS Cell-centered Voronoi plots

easyclimate.plot.mpas.plot_voronoi_grid(data, verticesOnEdge='verticesOnEdge', lonVertex='lonVertex', latVertex='latVertex', lon_min=None, lon_max=None, lat_min=None, lat_max=None, ax=None, **linekwags)¶

Plot MPAS Voronoi mesh edges.

Parameters¶

dataxarray.Dataset: MPAS dataset containing verticesOnEdge, lonVertex, and latVertex. Used as the fallback source when these variables are not provided explicitly.
verticesOnEdgestr, optional: Name of the edge-to-vertex connectivity variable using MPAS 1-based vertex indices.
lonVertex, latVertexstr, optional: Names of the vertex longitude and latitude variables in radians.
lon_min, lon_max, lat_min, lat_maxfloat, optional: Optional subset window in degrees. Cross-dateline longitude windows are supported.
axmatplotlib.axes.Axes, optional: Axes on which to draw. By default, use the current axes.
**linekwags: Additional keyword arguments passed to matplotlib.collections.LineCollection.

Returns¶

matplotlib.collections.LineCollection: Line collection containing selected Voronoi mesh edges.

MPAS/Voronoi grid

easyclimate.plot.mpas.extract_cell_latlon(ds, *, da=None, lon_min=None, lon_max=None, lat_min=None, lat_max=None, auto_extent=True, extent_margin=0.05, global_plot=False, center_lon=None, input_radians=True, lon_name_cell='lonCell', lat_name_cell='latCell', lon_name_vertex='lonVertex', lat_name_vertex='latVertex')¶

Extract and wrap MPAS cell and vertex lon/lat.

Parameters¶

dsxarray.Dataset: MPAS dataset containing cell and vertex coordinate variables.
daxarray.DataArray or numpy.ndarray, optional: Cell-centered data. If provided, finite values are used for extent inference and center_lon inference.
lon_min, lon_max, lat_min, lat_maxfloat, optional: User-defined plotting window. Supports cross-dateline windows, e.g. lon_min=90, lon_max=-60 means 90E to 300E.
auto_extentbool, default: True: If True and no explicit extent is supplied, infer the extent from valid cell centers.
extent_marginfloat, default: 0.05: Fractional margin added to the automatically inferred extent.
global_plotbool, default: False: If True, return a global extent centered on center_lon.
center_lonfloat, optional: Longitude wrapping center. If None, inferred automatically.
input_radiansbool, default: True: If True, MPAS longitude and latitude variables are interpreted as radians and converted to degrees.
lon_name_cell, lat_name_cell, lon_name_vertex, lat_name_vertexstr: MPAS coordinate variable names.

Returns¶

dict: Dictionary with wrapped cell and vertex coordinates, the inferred longitude center, and plotting extent values.

easyclimate.plot.mpas.plot_cell_contour(ds, da, *, ax=None, lon_min=None, lon_max=None, lat_min=None, lat_max=None, auto_extent=True, extent_margin=0.05, contour_margin=0.05, global_plot=False, center_lon=None, levels=10, colors=None, linewidths=0.8, linestyles=None, cmap=None, vmin=None, vmax=None, symmetric=False, percentile=98, extend=None, max_triangle_edge=None, input_radians=True, transform=None, title=None, lon_name_cell='lonCell', lat_name_cell='latCell', lon_name_vertex='lonVertex', lat_name_vertex='latVertex', use_triangulation_cache=True)¶

Draw contour lines for MPAS cell-centered scalar field.

Labels are not added automatically. Add them outside this function with ax.clabel(cs, inline=True, fontsize=8, fmt="%g").

Parameters¶

dsxarray.Dataset: MPAS dataset containing cell and vertex coordinate variables.
daxarray.DataArray or numpy.ndarray: Cell-centered scalar values. The data must be one-dimensional on nCells after any time or vertical-level selection.
axmatplotlib.axes.Axes, optional: Axes on which to draw. By default, use the current axes.
lon_min, lon_max, lat_min, lat_maxfloat, optional: Plot extent in degrees. Cross-dateline longitude windows are supported.
auto_extentbool, default: True: If True and no explicit extent is supplied, infer the extent from valid cell centers.
extent_marginfloat, default: 0.05: Fractional margin added to the automatically inferred extent.
contour_marginfloat, default: 0.05: Fractional padding used when selecting source cells for contouring.
global_plotbool, default: False: If True, draw a global extent centered on center_lon.
center_lonfloat, optional: Longitude center used for wrapping. If None, infer it from the extent or valid cell centers.
levelsint or array-like, default: 10: Number of contour levels, or explicit level values.
colorscolor or collections.abc.Sequence of colors, optional: Fixed line colors passed to Axes.tricontour. If omitted, use cmap.
linewidths, linestyles: Contour line style options passed to Axes.tricontour.
cmapstr or matplotlib.colors.Colormap, optional: Colormap used when colors is not supplied.
vmin, vmaxfloat, optional: Data limits used by contour levels and color mapping.
symmetricbool, default: False: If True, infer symmetric limits around zero when vmin or vmax is omitted.
percentilefloat, default: 98: Percentile used for automatic data-limit inference.
extend{“neither”, “both”, “min”, “max”}, optional: Contour extension mode. If None, infer it from data and levels.
max_triangle_edgefloat, optional: Maximum accepted edge length for triangles. Longer triangles are masked.
input_radiansbool, default: True: If True, MPAS longitude and latitude variables are interpreted as radians and converted to degrees.
transformcartopy.crs.CRS, optional: Coordinate reference system of the input coordinates for Cartopy axes.
titlestr, optional: Axes title. If None, use the data long name.
lon_name_cell, lat_name_cell, lon_name_vertex, lat_name_vertexstr: MPAS coordinate variable names.
use_triangulation_cachebool, default: True: If True, cache the triangulation for repeated calls on the same mesh and extent.

Returns¶

matplotlib.contour.QuadContourSet: Contour set returned by Axes.tricontour.

MPAS Cell-centered contour plots

easyclimate.plot.mpas.plot_cell_contourf(ds, da, *, ax=None, lon_min=None, lon_max=None, lat_min=None, lat_max=None, auto_extent=True, extent_margin=0.05, contour_margin=0.05, global_plot=False, center_lon=None, levels=10, cmap=None, vmin=None, vmax=None, symmetric=False, percentile=98, extend=None, max_triangle_edge=None, input_radians=True, transform=None, add_colorbar=True, cbar_kwargs=None, title=None, lon_name_cell='lonCell', lat_name_cell='latCell', lon_name_vertex='lonVertex', lat_name_vertex='latVertex', use_triangulation_cache=True)¶

Draw filled contour for MPAS cell-centered scalar field.

The scalar values are drawn from MPAS cell centers using matplotlib.tri.Triangulation.

Parameters¶

dsxarray.Dataset: MPAS dataset containing cell and vertex coordinate variables.
daxarray.DataArray or numpy.ndarray: Cell-centered scalar values. The data must be one-dimensional on nCells after any time or vertical-level selection.
axmatplotlib.axes.Axes, optional: Axes on which to draw. By default, use the current axes.
lon_min, lon_max, lat_min, lat_maxfloat, optional: Plot extent in degrees. Cross-dateline longitude windows are supported.
auto_extentbool, default: True: If True and no explicit extent is supplied, infer the extent from valid cell centers.
extent_marginfloat, default: 0.05: Fractional margin added to the automatically inferred extent.
contour_marginfloat, default: 0.05: Fractional padding used when selecting source cells for contouring.
global_plotbool, default: False: If True, draw a global extent centered on center_lon.
center_lonfloat, optional: Longitude center used for wrapping. If None, infer it from the extent or valid cell centers.
levelsint or array-like, default: 10: Number of contour levels, or explicit level values.
cmapstr or matplotlib.colors.Colormap, optional: Colormap used for filled contours.
vmin, vmaxfloat, optional: Color/data limits used by contour levels and color mapping. If one side is omitted, infer it from selected finite values.
symmetricbool, default: False: If True, infer symmetric limits around zero when vmin or vmax is omitted.
percentilefloat, default: 98: Percentile used for automatic color-limit inference.
extend{“neither”, “both”, “min”, “max”}, optional: Colorbar extension mode. If None, infer it from data and levels.
max_triangle_edgefloat, optional: Maximum accepted edge length for triangles. Longer triangles are masked.
input_radiansbool, default: True: If True, MPAS longitude and latitude variables are interpreted as radians and converted to degrees.
transformcartopy.crs.CRS, optional: Coordinate reference system of the input coordinates for Cartopy axes.
add_colorbarbool, default: True: If True, add a colorbar for the filled contour set.
cbar_kwargsdict, optional: Keyword arguments passed to Figure.colorbar.
titlestr, optional: Axes title. If None, use the data long name.
lon_name_cell, lat_name_cell, lon_name_vertex, lat_name_vertexstr: MPAS coordinate variable names.
use_triangulation_cachebool, default: True: If True, cache the triangulation for repeated calls on the same mesh and extent.

Returns¶

matplotlib.contour.QuadContourSet: Filled contour set returned by Axes.tricontourf.

MPAS Cell-centered contour plots

easyclimate.plot.mpas.plot_vertex_voronoi(ds, da, *, ax=None, transform=None, lon_min=None, lon_max=None, lat_min=None, lat_max=None, auto_extent=True, extent_margin=0.05, vertex_margin=0.05, global_plot=False, center_lon=None, input_radians=True, skip_large_lon_jump=True, max_polygon_lon_span=180.0, cmap=None, vmin=None, vmax=None, symmetric=None, percentile=98, edgecolor='none', linewidth=0.0, add_colorbar=True, cbar_kwargs=None, title=None, xlabel='Longitude', ylabel='Latitude', aspect='auto', cells_on_vertex_name='cellsOnVertex', lon_name_cell='lonCell', lat_name_cell='latCell', lon_name_vertex='lonVertex', lat_name_vertex='latVertex', use_geometry_cache=True)¶

Plot MPAS vertex-centered scalar data on dual polygons.

Each vertex value is drawn on the dual polygon formed by the surrounding cell centers. If da is cell-centered with length nCells, values are first averaged to vertices using cellsOnVertex.

Parameters¶

dsxarray.Dataset: MPAS dataset containing vertex, cell, and connectivity variables.
daxarray.DataArray or numpy.ndarray: Vertex-centered values on nVertices or cell-centered values on nCells. Cell-centered values are averaged to vertices before plotting.
axmatplotlib.axes.Axes, optional: Axes on which to draw. By default, use the current axes.
transformcartopy.crs.CRS, optional: Coordinate reference system of the input coordinates for Cartopy axes.
lon_min, lon_max, lat_min, lat_maxfloat, optional: Plot extent in degrees. Cross-dateline longitude windows are supported.
auto_extentbool, default: True: If True and no explicit extent is supplied, infer the extent from valid vertices.
extent_marginfloat, default: 0.05: Fractional margin added to the automatically inferred extent.
vertex_marginfloat, default: 0.05: Fractional padding used when selecting dual polygons near the visible extent.
global_plotbool, default: False: If True, draw a global extent centered on center_lon.
center_lonfloat, optional: Longitude center used for wrapping. If None, infer it from the extent or valid vertices.
input_radiansbool, default: True: If True, MPAS longitude and latitude variables are interpreted as radians and converted to degrees.
skip_large_lon_jumpbool, default: True: If True, skip polygons with very large wrapped longitude spans.
max_polygon_lon_spanfloat, default: 180.0: Maximum accepted wrapped polygon longitude span in degrees.
cmapstr or matplotlib.colors.Colormap, optional: Colormap used for polygon values.
vmin, vmaxfloat, optional: Color limits. If omitted, infer them from selected values.
symmetricbool, optional: If True, infer symmetric color limits around zero. If None, default to True for vertex-dual plots.
percentilefloat, default: 98: Percentile used for automatic color-limit inference.
edgecolor, linewidth: Polygon edge style passed to matplotlib.collections.PolyCollection.
add_colorbarbool, default: True: If True, add a colorbar for the polygon collection.
cbar_kwargsdict, optional: Keyword arguments passed to Figure.colorbar.
titlestr, optional: Axes title. If None, use the data long name.
xlabel, ylabelstr: Axis labels used for plain Matplotlib axes.
aspectstr or float, default: “auto”: Aspect setting used for plain Matplotlib axes.
cells_on_vertex_namestr: MPAS variable giving neighboring cells for each vertex.
lon_name_cell, lat_name_cell, lon_name_vertex, lat_name_vertexstr: MPAS coordinate variable names.
use_geometry_cachebool, default: True: If True, cache vertex-dual polygon geometry for repeated calls.

Returns¶

matplotlib.collections.PolyCollection: Polygon collection added to the axes.

MPAS Vertex-centered Voronoi plots

easyclimate.plot.mpas.plot_vertex_contour(ds, da, *, ax=None, lon_min=None, lon_max=None, lat_min=None, lat_max=None, auto_extent=True, extent_margin=0.05, contour_margin=0.05, global_plot=False, center_lon=None, levels=10, colors=None, linewidths=0.8, linestyles=None, cmap=None, vmin=None, vmax=None, symmetric=False, percentile=98, extend=None, max_triangle_edge=None, use_triangulation_cache=True, input_radians=True, transform=None, title=None, xlabel='Longitude', ylabel='Latitude', aspect='auto', lon_name_vertex='lonVertex', lat_name_vertex='latVertex')¶

Draw contour lines for MPAS vertex-centered scalar field.

Parameters¶

dsxarray.Dataset: MPAS dataset containing vertex coordinate variables.
daxarray.DataArray or numpy.ndarray: Vertex-centered scalar values. The data must be one-dimensional on nVertices after any time or vertical-level selection.
axmatplotlib.axes.Axes, optional: Axes on which to draw. By default, use the current axes.
lon_min, lon_max, lat_min, lat_maxfloat, optional: Plot extent in degrees. Cross-dateline longitude windows are supported.
auto_extentbool, default: True: If True and no explicit extent is supplied, infer the extent from valid vertices.
extent_marginfloat, default: 0.05: Fractional margin added to the automatically inferred extent.
contour_marginfloat, default: 0.05: Fractional padding used when selecting source vertices for contouring.
global_plotbool, default: False: If True, draw a global extent centered on center_lon.
center_lonfloat, optional: Longitude center used for wrapping. If None, infer it from the extent or valid vertices.
levelsint or array-like, default: 10: Number of contour levels, or explicit level values.
colorscolor or collections.abc.Sequence of colors, optional: Fixed line colors passed to Axes.tricontour. If omitted, use cmap.
linewidths, linestyles: Contour line style options passed to Axes.tricontour.
cmapstr or matplotlib.colors.Colormap, optional: Colormap used when colors is not supplied.
vmin, vmaxfloat, optional: Data limits used by contour levels and color mapping.
symmetricbool, default: False: If True, infer symmetric limits around zero when vmin or vmax is omitted.
percentilefloat, default: 98: Percentile used for automatic data-limit inference.
extend{“neither”, “both”, “min”, “max”}, optional: Contour extension mode. If None, infer it from data and levels.
max_triangle_edgefloat, optional: Maximum accepted edge length for triangles. Longer triangles are masked.
use_triangulation_cachebool, default: True: If True, cache the triangulation for repeated calls on the same mesh and extent.
input_radiansbool, default: True: If True, MPAS longitude and latitude variables are interpreted as radians and converted to degrees.
transformcartopy.crs.CRS, optional: Coordinate reference system of the input coordinates for Cartopy axes.
titlestr, optional: Axes title. If None, use the data long name.
xlabel, ylabelstr: Axis labels used for plain Matplotlib axes.
aspectstr or float, default: “auto”: Aspect setting used for plain Matplotlib axes.
lon_name_vertex, lat_name_vertexstr: MPAS vertex coordinate variable names.

Returns¶

matplotlib.contour.QuadContourSet: Contour set returned by Axes.tricontour.

MPAS Vertex-centered contour plots

easyclimate.plot.mpas.plot_vertex_contourf(ds, da, *, ax=None, lon_min=None, lon_max=None, lat_min=None, lat_max=None, auto_extent=True, extent_margin=0.05, contour_margin=0.05, global_plot=False, center_lon=None, levels=10, cmap=None, vmin=None, vmax=None, symmetric=False, percentile=98, extend=None, max_triangle_edge=None, use_triangulation_cache=True, input_radians=True, transform=None, add_colorbar=True, cbar_kwargs=None, title=None, xlabel='Longitude', ylabel='Latitude', aspect='auto', lon_name_vertex='lonVertex', lat_name_vertex='latVertex')¶

Draw filled contour for MPAS vertex-centered scalar field.

Parameters¶

dsxarray.Dataset: MPAS dataset containing vertex coordinate variables.
daxarray.DataArray or numpy.ndarray: Vertex-centered scalar values. The data must be one-dimensional on nVertices after any time or vertical-level selection.
axmatplotlib.axes.Axes, optional: Axes on which to draw. By default, use the current axes.
lon_min, lon_max, lat_min, lat_maxfloat, optional: Plot extent in degrees. Cross-dateline longitude windows are supported.
auto_extentbool, default: True: If True and no explicit extent is supplied, infer the extent from valid vertices.
extent_marginfloat, default: 0.05: Fractional margin added to the automatically inferred extent.
contour_marginfloat, default: 0.05: Fractional padding used when selecting source vertices for contouring.
global_plotbool, default: False: If True, draw a global extent centered on center_lon.
center_lonfloat, optional: Longitude center used for wrapping. If None, infer it from the extent or valid vertices.
levelsint or array-like, default: 10: Number of contour levels, or explicit level values.
cmapstr or matplotlib.colors.Colormap, optional: Colormap used for filled contours.
vmin, vmaxfloat, optional: Data limits used by contour levels and color mapping.
symmetricbool, default: False: If True, infer symmetric limits around zero when vmin or vmax is omitted.
percentilefloat, default: 98: Percentile used for automatic data-limit inference.
extend{“neither”, “both”, “min”, “max”}, optional: Colorbar extension mode. If None, infer it from data and levels.
max_triangle_edgefloat, optional: Maximum accepted edge length for triangles. Longer triangles are masked.
use_triangulation_cachebool, default: True: If True, cache the triangulation for repeated calls on the same mesh and extent.
input_radiansbool, default: True: If True, MPAS longitude and latitude variables are interpreted as radians and converted to degrees.
transformcartopy.crs.CRS, optional: Coordinate reference system of the input coordinates for Cartopy axes.
add_colorbarbool, default: True: If True, add a colorbar for the filled contour set.
cbar_kwargsdict, optional: Keyword arguments passed to Figure.colorbar.
titlestr, optional: Axes title. If None, use the data long name.
xlabel, ylabelstr: Axis labels used for plain Matplotlib axes.
aspectstr or float, default: “auto”: Aspect setting used for plain Matplotlib axes.
lon_name_vertex, lat_name_vertexstr: MPAS vertex coordinate variable names.

Returns¶

matplotlib.contour.QuadContourSet: Filled contour set returned by Axes.tricontourf.

MPAS Vertex-centered contour plots

easyclimate.plot.mpas.plot_cell_quiver(ds, u_da, v_da, *, ax=None, lon_min=None, lon_max=None, lat_min=None, lat_max=None, center_lon=None, input_radians=True, lon_name_cell='lonCell', lat_name_cell='latCell', nx_bins=35, ny_bins=20, thin_method='nearest_center', use_thinning_cache=True, add_quiverkey=True, quiverkey_value=None, quiverkey_label=None, quiverkey_x=0.88, quiverkey_y=1.04, transform=None, regrid_shape=None, regrid_global_epsilon=1e-06, title=None, **quiver_kwargs)¶

Plot cell-centered vector wind on MPAS mesh.

Parameters¶

dsxarray.Dataset: MPAS dataset containing cell coordinate variables.
u_da, v_daxarray.DataArray or numpy.ndarray: Cell-centered zonal/eastward and meridional/northward vector components. Each input must be one-dimensional on nCells after selection.
axmatplotlib.axes.Axes, optional: Axes on which to draw. By default, use the current axes.
lon_min, lon_max, lat_min, lat_maxfloat: Plot extent in degrees. These bounds are required so vector thinning is robust on variable-resolution meshes.
center_lonfloat, optional: Longitude center used for wrapping. If None, infer it from the extent or valid cell centers.
input_radiansbool, default: True: If True, MPAS longitude and latitude variables are interpreted as radians and converted to degrees.
lon_name_cell, lat_name_cellstr: MPAS cell coordinate variable names.
nx_bins, ny_binsint, default: 35, 20: Number of longitude and latitude bins used to thin vectors.
thin_method{“nearest_center”, “max_speed”, “mean”}, default: “nearest_center”: Rule used to choose or aggregate one vector per bin.
use_thinning_cachebool, default: True: If True, cache coordinate-only bin metadata for repeated calls.
add_quiverkeybool, default: True: If True, add a reference quiver key.
quiverkey_valuefloat, optional: Reference vector magnitude for the quiver key. If None, use the 75th percentile of thinned vector speeds.
quiverkey_labelstr, optional: Label for the quiver key. If None, build a metres-per-second label from quiverkey_value.
quiverkey_x, quiverkey_yfloat, default: 0.88, 1.04: Quiver-key position in axes coordinates.
transformcartopy.crs.CRS, optional: Coordinate reference system of the input coordinates for Cartopy axes.
regrid_shapeint or (int, int) or None, optional: Regrid vectors onto a regular grid in the target map projection before plotting. This is only supported for Cartopy GeoAxes.
regrid_global_epsilonfloat, default: 1.0e-6: Small longitude shrink applied to full-width global regridding windows.
titlestr, optional: Axes title. If None, use a default wind title.
**quiver_kwargs: Additional keyword arguments passed to Axes.quiver.

Returns¶

matplotlib.quiver.Quiver: Quiver object returned by Axes.quiver.

MPAS Cell-centered quiver plots

easyclimate.plot.mpas.plot_cell_curved_quiver(ds, u_da, v_da, *, ax=None, lon_min=None, lon_max=None, lat_min=None, lat_max=None, center_lon=None, input_radians=True, lon_name_cell='lonCell', lat_name_cell='latCell', nx=160, ny=100, interpolation_padding=None, interpolation_padding_cells=2.0, min_valid_fraction=0.02, use_triangulation_cache=True, use_interp_weight_cache=True, transform=None, project_to_map=True, regrid_shape=None, regrid_global_epsilon=1e-06, density=1, linewidth=None, color=None, cmap=None, norm=None, arrowsize=1, arrowstyle='-|>', zorder=None, start_points=None, integration_direction='both', grains=15, broken_streamlines=True, ref_magnitude: float | None = None, ref_length: float | None = None, min_frac_length: float = 0.0, length_norm: Literal['reference', 'max', 'percentile'] = 'reference', mask_density: int | tuple[int, int] = 10, line_start_stride: int = 1, arrow_stride: int = 1, min_distance: float = 0.0, arrow_head_ratio: float = 1.0, arrow_position: float = 1.0, title=None) → easyclimate.plot.modplot.CurvedQuiverplotSet¶

Plot MPAS cell-centered vector wind as curved quiver trajectories.

The MPAS cell-centered irregular vectors are first interpolated onto a regular grid, then drawn with the same curved-quiver engine used by easyclimate.plot.curved_quiver_plot.curved_quiver().

Parameters¶

dsxarray.Dataset: MPAS dataset containing cell coordinate variables.
u_da, v_daxarray.DataArray or numpy.ndarray: Cell-centered zonal/eastward and meridional/northward vectors, 1D on nCells after selection.
axmatplotlib.axes.Axes, optional: Axes on which to draw. By default, use the current axes.
lon_min, lon_max, lat_min, lat_maxfloat: Plot extent in degrees. These bounds are required to define the regular interpolation grid.
center_lonfloat, optional: Longitude center used for wrapping. If None, infer it from the extent or valid cell centers.
input_radiansbool, default: True: If True, MPAS longitude and latitude variables are interpreted as radians and converted to degrees.
lon_name_cell, lat_name_cellstr: MPAS cell coordinate variable names.
nx, nyint, default: 160, 100: Number of longitude and latitude points in the regular interpolation grid.
interpolation_paddingfloat or (float, float) or None, optional: Extra longitude/latitude degrees used only when selecting source cells for triangular interpolation. If None, padding is inferred from interpolation_padding_cells and the regular grid spacing.
interpolation_padding_cellsfloat, default: 2.0: Number of regular-grid cells used as automatic interpolation padding.
min_valid_fractionfloat, default: 0.02: Minimum fraction of valid interpolated grid points required before plotting.
use_triangulation_cache, use_interp_weight_cachebool, default: True: If True, cache triangulation and interpolation weights for repeated calls on the same mesh and grid.
transformcartopy.crs.CRS, optional: Coordinate reference system of the input coordinates for Cartopy axes.
project_to_mapbool, default: True: For Cartopy GeoAxes, transform the regular lon-lat grid and vector components to the target projection before drawing when the transformed grid remains rectilinear.
regrid_shapeint or (int, int) or None, optional: Regrid vectors directly onto a regular grid in target projection coordinates. This is only supported for Cartopy GeoAxes and takes precedence over project_to_map.
regrid_global_epsilonfloat, default: 1.0e-6: Small longitude shrink applied to full-width global regridding windows.
density, linewidth, color, cmap, norm, arrowsize, arrowstyle: Curved-quiver style options passed to velovect.
zorder, start_points, integration_direction, grains, broken_streamlines: Curved-quiver trajectory options passed to velovect.
ref_magnitude, ref_length, min_frac_length, length_norm: Options controlling how vector magnitude maps to curved-vector length.
mask_density, line_start_stride, arrow_stride, min_distance: Options controlling seed-point density and collision masking.
arrow_head_ratio, arrow_position: Arrow-head size and placement controls.
titlestr, optional: Axes title. If None, use a default curved-quiver title.

Returns¶

easyclimate.plot.modplot.CurvedQuiverplotSet: Container with line and arrow artists returned by velovect.

MPAS Cell-centered curved quiver plots

easyclimate.plot.mpas.plot_cell_barbs(ds, u_da, v_da, *, ax=None, lon_min=None, lon_max=None, lat_min=None, lat_max=None, center_lon=None, input_radians=True, lon_name_cell='lonCell', lat_name_cell='latCell', nx_bins=35, ny_bins=20, thin_method='nearest_center', use_thinning_cache=True, transform=None, regrid_shape=None, regrid_global_epsilon=1e-06, title=None, **barbs_kwargs)¶

Plot cell-centered vector wind as wind barbs on an MPAS mesh.

Parameters¶

dsxarray.Dataset: MPAS dataset containing cell coordinate variables.
u_da, v_daxarray.DataArray or numpy.ndarray: Cell-centered zonal/eastward and meridional/northward vectors, 1D on nCells after selection.
axmatplotlib.axes.Axes, optional: Axes on which to draw. By default, use the current axes.
lon_min, lon_max, lat_min, lat_maxfloat: Plot extent in degrees. These bounds are required so vector thinning is robust on variable-resolution meshes.
center_lonfloat, optional: Longitude center used for wrapping. If None, infer it from the extent or valid cell centers.
input_radiansbool, default: True: If True, MPAS longitude and latitude variables are interpreted as radians and converted to degrees.
lon_name_cell, lat_name_cellstr: MPAS cell coordinate variable names.
nx_bins, ny_binsint, default: 35, 20: Number of longitude and latitude bins used to thin vectors.
thin_method{“nearest_center”, “max_speed”, “mean”}, default: “nearest_center”: Rule used to choose or aggregate one vector per bin.
use_thinning_cachebool, default: True: If True, cache coordinate-only bin metadata for repeated calls.
transformcartopy.crs.CRS, optional: Coordinate reference system of the input coordinates for Cartopy axes.
regrid_shapeint or (int, int) or None, optional: Regrid vectors onto a regular grid in the target map projection before plotting. This is only supported for Cartopy GeoAxes.
regrid_global_epsilonfloat, default: 1.0e-6: Small longitude shrink applied to full-width global regridding windows.
titlestr, optional: Axes title. If None, use a default wind-barb title.
**barbs_kwargs: Additional keyword arguments passed to Axes.barbs.

Returns¶

matplotlib.quiver.Barbs: Barb container returned by Axes.barbs.

MPAS Cell-centered wind barbs

easyclimate.plot.mpas.plot_cell_streamplot(ds, u_da, v_da, *, ax=None, lon_min=None, lon_max=None, lat_min=None, lat_max=None, center_lon=None, input_radians=True, lon_name_cell='lonCell', lat_name_cell='latCell', nx=160, ny=100, interpolation_padding=None, interpolation_padding_cells=2.0, min_valid_fraction=0.02, use_triangulation_cache=True, use_interp_weight_cache=True, transform=None, project_to_map=True, regrid_shape=None, regrid_global_epsilon=1e-06, title=None, **streamplot_kwargs)¶

Plot cell-centered vector wind as streamlines on an MPAS mesh.

The MPAS cell-centered irregular vectors are first interpolated onto a regular lon-lat grid using Matplotlib triangular linear interpolation, then passed to Axes.streamplot / Cartopy GeoAxes streamplot.

Parameters¶

dsxarray.Dataset: MPAS dataset containing cell coordinate variables.
u_da, v_daxarray.DataArray or numpy.ndarray: Cell-centered zonal/eastward and meridional/northward vectors, 1D on nCells after selection.
axmatplotlib.axes.Axes, optional: Axes on which to draw. By default, use the current axes.
lon_min, lon_max, lat_min, lat_maxfloat: Plot extent in degrees. These bounds are required to define the regular interpolation grid.
center_lonfloat, optional: Longitude center used for wrapping. If None, infer it from the extent or valid cell centers.
input_radiansbool, default: True: If True, MPAS longitude and latitude variables are interpreted as radians and converted to degrees.
lon_name_cell, lat_name_cellstr: MPAS cell coordinate variable names.
nx, nyint, default: 160, 100: Number of longitude and latitude points in the regular interpolation grid.
interpolation_paddingfloat or (float, float) or None, optional: Extra longitude/latitude degrees used only when selecting source cells for triangular interpolation. Padding keeps the requested output grid inside the interpolation hull, reducing blank margins near plot edges. If None, padding is inferred from interpolation_padding_cells and the regular grid spacing.
interpolation_padding_cellsfloat, optional: Number of regular-grid cells used as automatic interpolation padding.
project_to_mapbool, optional: For Cartopy GeoAxes, transform the regular lon-lat grid and vector components to the target map projection before calling streamplot. This avoids Cartopy’s internal streamplot regridding from clipping a shifted PlateCarree window near the map edge.
regrid_shapeint or (int, int) or None, optional: Regrid vectors onto a regular grid in the target map projection before plotting. This is only supported for Cartopy GeoAxes. If provided, this projection-grid path takes precedence over project_to_map.
use_triangulation_cachebool, optional: Cache the geometry-only triangulation for repeated calls with the same dataset, extent, padding, and interpolation grid. This avoids rebuilding Qhull triangulation and TriFinder state when plotting multiple levels or time slices on the same MPAS mesh.
use_interp_weight_cachebool, optional: Cache target-grid barycentric interpolation weights. This avoids repeated LinearTriInterpolator setup and plane-coefficient calculations for repeated calls with the same geometry and interpolation grid.
transformcartopy.crs.CRS, optional: Coordinate reference system of the input coordinates for Cartopy axes.
min_valid_fractionfloat, default: 0.02: Minimum fraction of valid interpolated grid points required before plotting.
titlestr, optional: Axes title. If None, use a default streamline title.
**streamplot_kwargs: Additional keyword arguments passed to Axes.streamplot.

Returns¶

matplotlib.streamplot.StreamplotSet: Streamplot set returned by Axes.streamplot.

MPAS Cell-centered streamplots