seims.parameters_sensitivity.figure Namespace Reference

Functions
def	cal_row_col_num (tot)
def	sample_histograms (input_sample, names, levels, outpath, outname, param_dict, plot_cfg=None # type:PlotConfig)
def	empirical_cdf (out_values, subsections, input_sample, names, levels, outpath, outname, param_dict, plot_cfg=None)

Detailed Description

Plot figures based on matplotlib for parameters sensitivity analysis.

    @author   : Liangjun Zhu

    @changelog:
    - 18-01-15  - lj - initial implementation.
    - 18-02-09  - lj - compatible with Python3.
    - 19-01-07  - lj - incorporated with PlotConfig

Function Documentation

cal_row_col_num()

def seims.parameters_sensitivity.figure.cal_row_col_num

(

tot

)

determine the appropriate row and col number.
Cols number decreases from 8 to 5 to figure out the most uniform row and col num.

empirical_cdf()

def seims.parameters_sensitivity.figure.empirical_cdf	(		out_values,
			subsections,
			input_sample,
			names,
			levels,
			outpath,
			outname,
			param_dict,
			plot_cfg = None
	)

Visualize the empirical cumulative distribution function(CDF)
of the given variable (x) and subsections of y.

sample_histograms()

def seims.parameters_sensitivity.figure.sample_histograms	(		input_sample,
			names,
			levels,
			outpath,
			outname,
			param_dict,
			plot_cfg = None  # type: PlotConfig
	)

Plot histograms as subplot.

Args:
    input_sample:
    names:
    levels:
    outpath:
    outname:
    param_dict:
    plot_cfg:

Returns:
    subplot list.