def test_11(self):
from pm4py.algo.filtering.pandas.timestamp import timestamp_filter
dataframe = self.load_running_example_df()
df_timest_intersecting = timestamp_filter.filter_traces_intersecting(dataframe, "2011-03-09 00:00:00",
"2012-01-18 23:59:59", parameters={
timestamp_filter.Parameters.CASE_ID_KEY: "case:concept:name",
timestamp_filter.Parameters.TIMESTAMP_KEY: "time:timestamp"})
def average_case_duration(
log: EventLog,
t1: Union[datetime, str],
t2: Union[datetime, str],
r: str,
parameters: Optional[Dict[Union[str, Parameters],
Any]] = None) -> float:
"""
The average duration of cases completed during a given time slot in which a given resource was involved.
Metric RBI 4.4 in Pika, Anastasiia, et al.
"Mining resource profiles from event logs." ACM Transactions on Management Information Systems (TMIS) 8.1 (2017): 1-30.
Parameters
-----------------
log
Event log
t1
Left interval
t2
Right interval
r
Resource
Returns
----------------
metric
Value of the metric
"""
if parameters is None:
parameters = {}
resource_key = exec_utils.get_param_value(
Parameters.RESOURCE_KEY, parameters,
xes_constants.DEFAULT_RESOURCE_KEY)
from pm4py.algo.filtering.log.attributes import attributes_filter
parameters_filter = {
attributes_filter.Parameters.ATTRIBUTE_KEY: resource_key
}
log = attributes_filter.apply(log, [r], parameters=parameters_filter)
from pm4py.algo.filtering.log.timestamp import timestamp_filter
log = timestamp_filter.filter_traces_intersecting(log,
t1,
t2,
parameters=parameters)
from pm4py.statistics.traces.generic.log import case_statistics
cd = case_statistics.get_cases_description(log,
parameters=parameters).values()
return mean(x["caseDuration"] for x in cd)
def filter_time_data(self, timestamps, time_weight):
if not isinstance(time_weight, float):
raise TypeError
if time_weight > 1 or time_weight < 0:
raise ValueError
if timestamps is None or len(timestamps) == 0:
return False
event_size = len(timestamps)
used = int(event_size * time_weight)
filtered = event_size - used
if event_size == 0 or used == 0:
return None
begin = int(filtered / 2)
end = begin + used - 1
begin_time = timestamps[begin].strftime("%Y-%m-%d %H:%M:%S")
end_time = timestamps[end].strftime("%Y-%m-%d %H:%M:%S")
df_times_intersecting = timestamp_filter.filter_traces_intersecting(
self.log, begin_time, end_time)
return df_times_intersecting
def apply(log, filter, parameters=None):
"""
Apply a timestamp filter to the log
Parameters
------------
log
log where the filter should be applied
filter
Filter (two timestamps separated by @@@)
parameters
Parameters of the algorithm
"""
if parameters is None:
parameters = {}
dt1 = str(datetime.utcfromtimestamp(int(filter[1].split("@@@")[0])))
dt2 = str(datetime.utcfromtimestamp(int(filter[1].split("@@@")[1])))
return timestamp_filter.filter_traces_intersecting(log,
dt1,
dt2,
parameters=parameters)
def test_10(self):
from pm4py.algo.filtering.log.timestamp import timestamp_filter
log = self.load_running_example_xes()
filtered_log = timestamp_filter.filter_traces_intersecting(log, "2011-03-09 00:00:00", "2012-01-18 23:59:59")
from pm4py.objects.log.importer.xes import importer as xes_importer
from pm4py.objects.log.util import func
log = xes_importer.apply('E:/data/pm/running-example.xes')
log = func.filter_(lambda t: len(t) > 2, log)
log
#filtering event data
#logs type
from pm4py.algo.filtering.log.timestamp import timestamp_filter
filtered_log = timestamp_filter.filter_traces_contained (log, "2011-03-09 00:00:00", "2012-01-18 23:59:59")
filtered_log
from pm4py.algo.filtering.log.timestamp import timestamp_filter
filtered_log = timestamp_filter.filter_traces_intersecting (log, "2011-03-09 00:00:00", "2012-01-18 23:59:59")
filtered_log
from pm4py.algo.filtering.log.cases import case_filter
filtered_log = case_filter.filter_case_performance(log, 86400, 864000)
filtered_log
#on DF
from pm4py.algo.filtering.pandas.timestamp import timestamp_filter
df_timest_intersecting = timestamp_filter.filter_traces_intersecting
(dataframe, "2011-03-09 00:00:00", "2012-01-18 23:59:59", parameters= {timestamp_filter.Parameters.CASE_ID_KEY: "case:concept:name", timestamp_filter.Parameters.TIMESTAMP_KEY: "time:timestamp"})