MetPy - FilledContourPlot()

Make color-filled contours plots by defining appropriate traits.

FilledContourPlot()

Attribute	Description
clabels	A boolean (True/False) on whether to plot contour labels.
colorbar	A string (horizontal/vertical) on whether to add a colorbar to the plot.
colorbar_fontsize	An integer, float, or string value to set the font size of labels for the colorbar.
colormap	The string name for a Matplotlib or MetPy colormap.
contours	A list of values to contour or an integer number of contour levels.
data	Xarray dataset that contains the field to be plotted.
field	Name of the field to be plotted.
image_range	A tuple of min and max values that represent the range of values to color the rasterized image.
label_fontsize	An integer, float, or string value to set the font size of labels for contours.
level	The level of the field to be plotted.
plot_units	The desired units to plot the field in.
scale	Scale the field to be plotted by the value given.
smooth_contour	Spline interpolation to smooth contours.
smooth_field	Number of smoothing passes using 9-pt smoother.
time	Set the valid time to be plotted as a datetime object.
mpl_args	Supply a dictionary of valid Matplotlib keyword arguments to modify how the plot variable is drawn.

Attribute Descriptions

data

• This attribute must be set with the variable name that contains the xarray dataset. (Typically this is the variable ds)

field

• This attribute must be set with the name of the variable that you want to contour. For example, to plot the heights of pressure surfaces from the GFS you would use the name ‘Geopotential_height_isobaric’

level

• This attribute sets the level of the data you wish to plot. If it is a pressure level, then it must be set to a unit bearing value (e.g., 500*units.hPa). If the variable does not have any vertical levels (e.g., mean sea-level pressure), then the level attribute must be set to None.

time

• This attribute must be set with a datetime object, just as with the PlotObs() class. To get a forecast hour, you can use the timedelta function from datetime to add the number of hours into the future you wish to plot. For example, if you wanted the six hour forecast from the 00 UTC 2 February 2020 model run, then you would set the attribute with:

  datetime(2020, 2, 2, 0) + timedelta(hours=6)

contours

• This attribute sets the contour values to be plotted with a list. This can be set manually with a list of integers in square brackets (e.g., [5400, 5460, 5520, 5580, 5640, 5700]) or programmatically (e.g., range(0, 10000, 60)). The second method is a way to easily set a contour interval (in this case 60).

colormap

• This attribute is used to set a valid colormap from either Matplotlib or MetPy:

  Matplotlib Colormaps

  MetPy Colormaps

colorbar

• This attribute can be set to ‘vertical’ or ‘horizontal’, which is the location the colorbar will be plotted on the panel.

image_range

• A set of values indicating the minimum and maximum for the data being plotted. This attribute should be set as (min_value, max_value), where min_value and max_value are numeric values.

plot_units

• If you want to change the units for plotting purposes, add the string value of the units desired. For example, if you want to plot temperature in Celsius, then set this attribute to ‘degC’.

smooth_contour

• This attribute is best used to smooth contours when contouring a sparse grid (e.g., when your data has a large grid spacing). This will produce smoothed geopotential heights for all levels available in the DataArray using a spline interpolation.

smooth_field

• This attribute is best used to smooth contours when contouring a higher resolution (smaller grid spacing with lots of grid points) field. This will produce a smoothed field using the nine-point smoother twice.

mpl_args

• This attribute can be set to a dictionary containing keyword arguments (kwarg) valid for the various Matplotlib plotting functions to enhance how a plot is created. For example, you can use this attribute to set the zorder kwarg to alter what aspects of the your plot are on top of one another. NOTE: Setting the mpl_args trait will override any other trait that corresponds to a specific kwarg for the particular plot type (e.g., linecolor, linewidth).