environmentaltools.graphics.nonstationary_cdf

environmentaltools.graphics.nonstationary_cdf(data: DataFrame, variable: str, param: dict = None, daysWindowsLength: int = 14, equal_windows: bool = False, ax=None, log: bool = False, file_name: str = None, label: str = None, lst='-', legend: bool = True, legend_loc: str = 'right', title: str = None, date_axis: bool = False, pemp: list = None, emp: bool = True)[source]

Plots the time variation of given percentiles of data and theoretical function if provided

Parameters:

  • data (*) – time series

  • variable (*) – name of the variable to be adjusted

  • param (*) – the parameters of the the theoretical model if they are also plotted.

  • daysWindowsLength (*) – period of windows length for making the non-stationary empirical distribution function. Defaults to 14 days.

  • equal_windows (*) – use the windows for the ecdf of total data and timestep

  • ax (*) – matplotlib.ax

  • log (*) – logarhitmic scale

  • file_name (*) – name of the file to save the plot or None to see plots on the screen. Defaults to None.

  • label (*) – string with the label

  • lst (*) – linestyle for theoretical distribution.

  • legend (*) – plot the legend

  • legend_loc (*) – locate the legend

  • title (*) – draw the title

  • date_axis (*) – create a secondary axis with time

  • pemp (*) – list with percentiles to be plotted

  • emp (*) – if True plot the empirical nonst distribution

Returns:

axis for the plot or None

Return type:

  • ax (matplotlib.axis)