Simpy Monitor Example

gistfile1.txt

import pandas as pd

class Monitor(object):
    """ Monitors hold data collected during the simulation """

    def __init__(self, name):
        """ Initialize the monitor """

        self.name = name
        self._data = {}

    def _key(self, index, group=None):
        """ Keys are stored in tuples for the dictionary """

        if group:
            metric_name = self.name + "_" + group
            key = (metric_name, index)
        else:
            key = (self.name, index)

        return key

    def observe(self, index, group, value=None):
        """ Observe a quantity """

        if value is None:
            # No group is specified, swap the arguments. This makes it easy
            # to call monitor.observe(1, 10) if there are no sub-groupings
            group, value = None, group

        key = self._key(index, group)

        if key not in self._data:
            # Only save if we have no observed value for this key
            self._data[key] = value
        else:
            # Otherwise raise an exception
            msg = "Attempted to ovewrite {} at {} with {}".format(
                (self.name, key, value))
            raise Exception(msg)

    def increment(self, index, group=None, by=1):
        """ Increment the key by one (or another amount)

        Supported calls:
            (1) m.increment(1) => increment key 1 on self by 1
            (2) m.increment(1, "step") => increment step monitor key 1 by 1
            (3) m.increment(1, by=10) => increment key 1 on self by 10
            (4) m.increment(1, "step", by=10) => increment step key 1 by 10
        """

        key = self._key(index, group)

        if key not in self._data:
            self._data[key] = by
        else:
            self._data[key] += by

    def get_value(self, index, group=None):
        """ Return the value for a key """

        key = self._key(index, group)

        return self._data[key]

    def data(self):
        """ Return a dictionary with the data """

        return self._data

    def df(self):
        """ Return the data as a pandas dataframe """

        values = self._data.values()
        keys = self._data.keys()
        index = pd.MultiIndex.from_tuples(keys, names=["metric", "idx"])
        df = pd.DataFrame(values, index=index)
        df.columns = ["value"]

        df = df.unstack(0)
        df.columns = df.columns.droplevel(0)

        return(df)
        

m = Monitor("My_Monitor")

m.increment(1, "Step1") # Step 1 happens at time 1
m.increment(1, "Step1") # Step 1 happens at time 1
m.increment(2, "Step1") # Step 1 happens at time 2

m.observe(1, "Queue1", 50) # 50 items in queue1 at time 1
m.observe(2, "Queue1", 48) # 48 items in queue1 at time 2
m.observe(3, "Queue1", 48) # 48 items in queue1 at time 3

m.df() # Obtain the data as a pandas dataframe