pydda.vis.plot_horiz_xsection_quiver_map

pydda.vis.plot_horiz_xsection_quiver_map(Grids, ax=None, background_field='reflectivity', level=1, cmap='pyart_LangRainbow12', vmin=None, vmax=None, u_vel_contours=None, v_vel_contours=None, w_vel_contours=None, wind_vel_contours=None, u_field='u', v_field='v', w_field='w', show_lobes=True, title_flag=True, axes_labels_flag=True, colorbar_flag=True, colorbar_contour_flag=False, bg_grid_no=0, contour_alpha=0.7, coastlines=True, quiver_spacing_x_km=10.0, quiver_spacing_y_km=10.0, gridlines=True, quiverkey_len=5.0, quiverkey_loc='best', quiver_width=0.01)[source]

This procedure plots a horizontal cross section of winds from wind fields generated by PyDDA using quivers onto a geographical map. The length of the quivers varies with wind speed.

Parameters
Grids: list

List of Py-ART Grids to visualize

ax: matplotlib axis handle (with cartopy ccrs)

The axis handle to place the plot on. Set to None to create a new map. Note: the axis needs to be in a PlateCarree() projection. Support for other projections is planned in the future.

background_field: str

The name of the background field to plot the quivers on.

level: int

The number of the vertical level to plot the cross section through.

cmap: str or matplotlib colormap

The name of the matplotlib colormap to use for the background field.

vmin: float

The minimum bound to use for plotting the background field. None will automatically detect the background field minimum.

vmax: float

The maximum bound to use for plotting the background field. None will automatically detect the background field maximum.

u_vel_contours: 1-D array

The contours to use for plotting contours of u. Set to None to not display such contours.

v_vel_contours: 1-D array

The contours to use for plotting contours of v. Set to None to not display such contours.

w_vel_contours: 1-D array

The contours to use for plotting contours of w. Set to None to not display such contours.

u_field: str

Name of zonal wind (u) field in Grids.

v_field: str

Name of meridional wind (v) field in Grids.

w_field: str

Name of vertical wind (w) field in Grids.

show_lobes: bool

If True, the dual doppler lobes from each pair of radars will be shown.

title_flag: bool

If True, PyDDA will generate a title for the plot.

axes_labels_flag: bool

If True, PyDDA will generate axes labels for the plot.

colorbar_flag: bool

If True, PyDDA will generate a colorbar for the plot background field.

colorbar_contour_flag: bool

If True, PyDDA will generate a colorbar for the contours.

bg_grid_no: int

Number of grid in Grids to take background field from. Set to -1 to use maximum value from all grids.

contour_alpha: float

Alpha (transparency) of velocity contours. 0 = transparent, 1 = opaque

coastlines: bool

Set to true to display coastlines.

quiver_spacing_x_km: float

Spacing in km between quivers in x axis.

quiver_spacing_y_km: float

Spacing in km between quivers in y axis.

gridlines: bool

Set to true to show grid lines.

quiverkey_len: float

Length to use for the quiver key in m/s.

quiverkey_loc: str

Location of quiverkey. One of:

‘best’

‘top_left’

‘top’

‘top_right’

‘bottom_left’

‘bottom’

‘bottom_right’

‘left’

‘right’

‘top_left_outside’

‘top_right_outside’

‘bottom_left_outside’

‘bottom_right_outside’

‘best’ will put the quiver key in the corner with the fewest amount of

valid data points while keeping the quiver key inside the plot. The rest of the options will put the quiver key in that particular part of the plot.

quiver_width: float

The width of the lines for the quiver given as a fraction relative to the plot width. Use this to specify the thickness of the quiver lines.

Returns
ax: matplotlib axis

Axis handle to output axis