module: matplots#

matplots.plot_profile(obs_seq, levels, type, bias=True, rmse=True, totalspread=True)#
plot_profile on the levels for prior and posterior if present

  • bias

  • rmse

  • totalspread

Parameters:

  • obs_seq

  • levels

  • type

  • bias=True

  • rmse=True

  • totalspread=True

Example

type = ‘RADIOSONDE_U_WIND_COMPONENT’ hPalevels = [0.0, 100.0, 150.0, 200.0, 250.0, 300.0, 400.0, 500.0, 700, 850, 925, 1000] levels = [i * 100 for i in hPalevels]

plot_profile(obs_seq, levels, type, bias=True, rmse=True, totalspread=True)

matplots.plot_evolution(obs_seq, type, time_bin_width, stat, levels=None, tick_interval=2, time_format='%m-%d', plot_pvu=True)#

Plot the time evolution of the requested statistics and optionally used vs possible observations.

Parameters:

  • obs_seq – The observation sequence object.

  • type (str) – The type of observation to filter by.

  • time_bin_width (str) – The width of each time bin (e.g., ‘3600s’ for 1 hour).

  • stat (str) – The statistic to plot. Default is “prior_rmse”.

  • levels (list, optional) – The levels to bin by. If None, no binning by level.

  • tick_interval (int) – Interval for x-axis ticks (default is 2).

  • time_format (str) – Format string for time labels on the x-axis (default is ‘%m-%d’).

  • plot_pvu (bool) – Whether to plot possible vs used observations (default is True).

Returns:

The matplotlib figure object.

Return type:

fig

matplots.plot_time_evolution(df, df_pvu, stat, type, level, tick_interval, time_format, plot_pvu)#

Plot the time evolution of the requested statistics and optionally used vs possible observations.

Parameters:

  • df (pd.DataFrame) – The aggregated DataFrame for statistics.

  • df_pvu (pd.DataFrame) – The DataFrame for possible vs used observations (if plot_pvu is True).

  • stat (str) – The statistic to plot.

  • type (str) – The type of observation.

  • level (float or None) – The vertical level (if applicable).

  • tick_interval (int) – Interval for x-axis ticks (default is 2).

  • time_format (str) – Format string for time labels on the x-axis.

  • plot_pvu (bool) – Whether to plot possible vs used observations (default is True).

Returns:

The matplotlib figure object.

Return type:

fig