Meteorographica.pressure

This module is designed to make plots of mean-sea-level-pressure (mslp), but they are basically just contour plots, so the functions can be used for any (continuous) scalar variable (with appropriate specification of levels).

It takes a cartopy.mpl.geoaxes.GeoAxes to draw into, and an iris.cube.Cube (with ‘latitude’ and ‘longitude’ dimensions) of data to plot. Then it’s just:

Meteorographica.pressure.plot(geoaxes,cube,**options)

Three different types of plot are supported:

  • ‘contour’ - straight contour plot of a single pressure field.
  • ‘spaghetti’ - spaghetti-contour plot of multiple pressure fields.
  • ‘spread’ - mean-contour plot with error bars derived from an ensemble of pressure fields.

See examples of use.


Meteorographica.pressure.make_label_hints(ax, CS)[source]

Make hints for the contour label placement algorithm - these stabilise the positions of the contour labels between frames in videos. They don’t eliminate the problem of jittery and flickering contour labels, but they do help.

Parameters:
Returns:

iterable of (x,y) tuples - each a position hint for a label.

Meteorographica.pressure.plot(ax, pe, **kwargs)[source]

Plot pressure.

Generic function for plotting pressure. Use the ‘type’ argument to choose the plot style.

Parameters:
Keyword Arguments:
 

type (str) – Style to plot. Options are:’contour’ (default), which delegates plotting to plot_contour(), ‘spaghetti’, which delegates plotting to plot_spaghetti_contour(), ‘spread’, which delegates plotting to plot_mean_spread().

Other keyword arguments are passed to the style-specific plotting function.

Returns:See matplotlib.axes.Axes.contour() - Also adds the lines to the plot.

Meteorographica.pressure.plot_contour(ax, pe, **kwargs)[source]

Plots a variable as a contour plot.

This is the same as matplotlib.axes.Axes.contour(), except that it takes an iris.cube.Cube instead of an array of values, and its defaults are chosen for plots of mean-sea-level pressure.

Parameters:
Keyword Arguments:
 
  • label (bool) – Label contour lines? Defaults to False. If it’s ‘video’ use stablised label locations.
  • resolution (float) – What lat:lon resolution (in degrees) to interpolate pe.data to before plotting. Defaults to None - use original resolution.
  • scale (float) – This function is tuned for data in hPa. For data in Pa, set this to 0.01. Defaults to 1.
  • colors (see matplotlib.colors) –
  • linewidths (float) – Line width for contour lines. Defaults to 0.5.
  • alpha (float) – Colour alpha blend. Defaults to 1 (opaque).
  • fontsize (int) – Font size for contour labels. Defaults to 12.
  • zorder (float) – Standard matplotlib parameter determining which things are plotted on top (high zorder), and which underneath (low zorder), Defaults to 30.
Returns:

See matplotlib.axes.Axes.contour() - also adds the lines to the plot.

Meteorographica.pressure.plot_mean_spread(ax, pe, **kwargs)[source]

Plots a variable as a contour plot.

Plots contours of the mean of an ensemble, mark uncertainty by fading out the contours where the ensemble spread is large.

Parameters:
Keyword Arguments:
 
  • ensemble_dimension (float) – name of the ensemble dimension. Defaults to ‘member’.
  • resolution (float) – What lat:lon resolution (in degrees) to interpolate pe.data to before plotting. Defaults to None - use original resolution.
  • colors (see matplotlib.colors) –
  • linewidths (float) – Line width for contour lines. Defaults to 0.2.
  • label (bool) – Label contour lines? Defaults to False.
  • cmap (matplotlib.colors.LinearSegmentedColormap) – Mapping of pe.data to plot colour. Defaults to blackblack semi-transparent.
  • threshold (float) – Ranges shown are regions where the probability that a contour line passes through the region is greater than this. Defaults to 0.05 (5%).
  • vmax (float) – Show as ‘most likely’, regions where the prob of a contour is greater than this Defaults to 0.4 (40%).
  • line_threshold (float) – Only draw contours where the local standard deviation is less than this. Defaults to None - draw contours everywhere.
  • alpha (float) – Colour alpha blend. Defaults to 1 (opaque).
  • fontsize (int) – Font size for contour labels. Defaults to 12.
  • zorder (float) – Standard matplotlib parameter determining which things are plotted on top (high zorder), and which underneath (low zorder), Defaults to 40.
  • label – Label contour lines? Defaults to True.
Returns:

See matplotlib.axes.Axes.contour() - also adds the lines to the plot.

Meteorographica.pressure.plot_spaghetti_contour(ax, pe, **kwargs)[source]

Plots a multi-contour (spaghetti) plot.

Calls plot_pressure_contour() multiple times with sensible defaults colurs and styles

Parameters:
Keyword Arguments:
 
  • ensemble_dimension (float) – name of the ensemble dimension. Defaults to ‘member’.
  • colors (see matplotlib.colors) –
  • linewidths (float) – Line width for contour lines. Defaults to 0.2.
  • label (bool) – Label contour lines? Defaults to False.

:keyword Other keyword arguments are passed to plot_pressure_contour():

Returns:See matplotlib.axes.Axes.contour() - except it’s an array, one for each member. Also adds the lines to the plot.