melodies_monet.plots.aircraftplots

aircraftplots.py this code is designed for plotting aircraft specific plot types

Functions

add_yax2_altitude(ax, pairdf, altitude_yax2, ...)	Creates secondary y-axis (altitude) for timeseries plot.
calculate_violin(df[, column, label, ...])	Combines data into an acceptable format for violin plots, similar to calculate_boxplot for box plots.
custom_yaxis_formatter(x, pos)
make_scatter_density_plot(df[, mod_var, ...])	Creates a scatter density plot for the specified column (variable) in the paired DataFrame (df).
make_spatial_bias(df[, df_reg, column_o, ...])	Creates surface spatial bias plot.
make_vertprofile(df[, column, label, ax, ...])	Creates altitude profile plot.
make_violin_plot(comb_violin, label_violin)	Creates a violin plot using combined data from multiple model/observation datasets.

melodies_monet.plots.aircraftplots.add_yax2_altitude(ax, pairdf, altitude_yax2, text_kwargs, vmin_y2, vmax_y2)

Creates secondary y-axis (altitude) for timeseries plot.

Parameters

• ax (ax) – Matplotlib ax from previous occurrences so it can overlay obs and model results on the same plot.

• pairdf (pandas.DataFrame) – Model/obs paired data to plot.

• text_kwargs (dictionary) – Dictionary containing information about text.

• altitude_yax2 (dictionary) – Secondary y-axis (altitude) control options, including altitude_variable, altitude_ticks, etc.

• vmin_y2, vmax_y2 (the value[0], value[1] respectively defined in filter_dict in altitude_yax2 in YAML control option)

Returns

ax (ax) – Matplotlib ax such that driver.py can iterate to overlay multiple models on the same plot.

melodies_monet.plots.aircraftplots.calculate_violin(df, column=None, label=None, plot_dict=None, comb_violin=None, label_violin=None)

Combines data into an acceptable format for violin plots, similar to calculate_boxplot for box plots.

Parameters

• df (pandas.DataFrame) – DataFrame containing the model/obs paired data to plot.

• column (str) – Column label of the variable to plot.

• label (str) – Name of the variable to use in the plot legend.

• plot_dict (dict) – Dictionary containing color information for the plot.

• comb_violin (pandas.DataFrame) – DataFrame containing information to create violin plots from previous occurrences, to overlay multiple model results on one plot.

• label_violin (list) – List of dictionaries with string labels and colors to use in the violin plot from previous occurrences, to overlay multiple model results on one plot.

Returns

• comb_violin (pandas.DataFrame) – DataFrame containing information to create violin plots.

• label_violin (list) – List of dictionaries with string labels and colors to use in the violin plot.

melodies_monet.plots.aircraftplots.make_scatter_density_plot(df, mod_var=None, obs_var=None, ax=None, color_map='viridis', xlabel=None, ylabel=None, title=None, fill=False, vmin_x=None, vmax_x=None, vmin_y=None, vmax_y=None, **kwargs)

Creates a scatter density plot for the specified column (variable) in the paired DataFrame (df).

Parameters

• df (dataframe) – Paired DataFrame containing the model and observation data to plot

• obs_var (str) – obs variable name in mapped pairs

• mod_var (str) – model variable name in mapped pairs

• ax (Matplotlib axis from a previous occurrence to overlay obs and model results on the same plot)

• color_map (str) – Colormap for the density (optional)

• xlabel (str) – Label for the x-axis (optional)

• ylabel (str) – Label for the y-axis (optional)

• title (str) – Title for the plot (optional)

• fill (bool) – Fill set to True for seaborn kde plot

• **kwargs (dict) – Additional keyword arguments for customization

Returns

ax (ax) – Matplotlib ax such that driver.py can iterate to overlay multiple models on the same plot.

melodies_monet.plots.aircraftplots.make_spatial_bias(df, df_reg=None, column_o=None, label_o=None, column_m=None, label_m=None, ylabel=None, ptile=None, vdiff=None, outname='plot', domain_type=None, domain_name=None, fig_dict=None, text_dict=None, debug=False)

Creates surface spatial bias plot.

Parameters

• df (pandas.DataFrame) – model/obs paired data to plot

• df_reg (pandas.DataFrame) – model/obs paired regulatory data to plot

• column_o (str) – Column label of observation variable to plot

• label_o (str) – Name of observation variable to use in plot title

• column_m (str) – Column label of model variable to plot

• label_m (str) – Name of model variable to use in plot title

• ylabel (str) – Title of colorbar axis

• ptile (integer) – Percentile calculation

• vdiff (float) – Min and max value to use on colorbar axis

• outname (str) – file location and name of plot (do not include .png)

• domain_type (str) – Domain type specified in input yaml file

• domain_name (str) – Domain name specified in input yaml file

• fig_dict (dictionary) – Dictionary containing information about figure

• text_dict (dictionary) – Dictionary containing information about text

• debug (boolean) – Whether to plot interactively (True) or not (False). Flag for submitting jobs to supercomputer turn off interactive mode.

Returns

plot – surface bias plot

melodies_monet.plots.aircraftplots.make_vertprofile(df, column=None, label=None, ax=None, bins=None, altitude_variable=None, ylabel=None, vmin=None, vmax=None, domain_type=None, domain_name=None, plot_dict=None, fig_dict=None, text_dict=None, debug=False, interquartile_style=None)

Creates altitude profile plot.

Parameters

• df (pandas.DataFrame) – Model/obs paired data to plot.

• column (str) – Column label of variable to plot.

• label (str) – Name of variable to use in plot legend.

• ax (ax) – Matplotlib ax from previous occurrence so it can overlay obs and model results on the same plot.

• bins (int or array-like) – Bins for binning the altitude variable.

• altitude_variable (str) – The Altitude variable in the paired df e.g., ‘MSL_GPS_Altitude_YANG’

• ylabel (str) – Title of y-axis.

• vmin (float) – Min value to use on y-axis.

• vmax (float) – Max value to use on y-axis.

• domain_type (str) – Domain type specified in input yaml file

• domain_name (str) – Domain name specified in input yaml file

• plot_dict (dictionary) – Dictionary containing information about plotting for each pair (e.g., color, linestyle, markerstyle).

• fig_dict (dictionary) – Dictionary containing information about the figure.

• text_dict (dictionary) – Dictionary containing information about text.

• debug (bool) – Whether to plot interactively (True) or not (False). Flag for submitting jobs to supercomputer turn off interactive mode.

• interquartile_style= str – Whether the vertical profile uses shading or box style for interquartile range

Returns

ax (ax) – Matplotlib ax such that driver.py can iterate to overlay multiple models on the same plot.

melodies_monet.plots.aircraftplots.make_violin_plot(comb_violin, label_violin, outname='plot', domain_type=None, domain_name=None, fig_dict=None, text_dict=None, debug=False, ylabel=None, vmin=None, vmax=None)

Creates a violin plot using combined data from multiple model/observation datasets.

Parameters

• comb_violin (pandas.DataFrame) – DataFrame containing combined data for all datasets to be plotted.

• label_violin (list) – List of dictionaries with string labels and colors to use in the violin plot.

• outname (str) – File location and name of plot (do not include .png).

• domain_type (str) – Domain type specified in the input yaml file.

• domain_name (str) – Domain name specified in the input yaml file.

• fig_dict (dict) – Dictionary containing information about figure properties.

• text_dict (dict) – Dictionary containing information about text properties.

• debug (bool) – If True, the plot will be shown interactively. Useful for debugging.

• ylabel (str, optional) – The label for the y-axis.

• vmin (float, optional) – The minimum value for the y-axis.

• vmax (float, optional) – The maximum value for the y-axis.

Returns

None