bpo.visualizers module

Functions:

boxplot(series)	Creates a boxplot for each element in the data series.
line_with_ci(series)	Creates a line graph for the data series.
statistics(log[, datetime_format])	Creates statistics for the interarrival time and the processing times of the given log.

bpo.visualizers.boxplot(series)

Creates a boxplot for each element in the data series. The data series is a dictionary. Each key is used as the label of the boxplot. Each value is a list of numerical data that is used to construct the boxplot.

Parameters

series – a dictionary that maps a label to a list of numerical data.

bpo.visualizers.line_with_ci(series)

Creates a line graph for the data series. The data series is a dictionary. Each key is a numerical value that represents an x-coordinate. Each value is a pair of numerical values, where the first element is the y-coordinate and the second element is an interval ci around the y-coordinate. A line graph is creates based on the (x, y) values with a bar around the y-ci, y+ci values. Typically, the ci value represents the confidence interval.

Parameters

series – a dictionary that maps numerical x values to (y, ci) numerical pairs.

bpo.visualizers.statistics(log, datetime_format='%Y/%m/%d %H:%M:%S')

Creates statistics for the interarrival time and the processing times of the given log. Returns the statistics as a dictionary with the labels of the statistics as keys and as values lists with all the observed times. The log must contain the columns case_id, task, resource, start_time, completion_time.

Parameters

• log – a pandas dataframe containing the log.

• datetime_format – optional parameter with the datetime formatting rule that will be used to interpret the start and completion timestamps