Commit d4a0d13b authored by Andreas Schmidt's avatar Andreas Schmidt
Browse files

Improve latency code (graphviz, filtering, reformat).

parent 2ffc0736

xlap/analyse/latency.py

+66 −68
Original line number Diff line number Diff line
@@ -4,6 +4,7 @@ from xlap.analyse.util import get_outlier_threshold, extract_durations, box 
from scipy.stats.stats import pearsonr

import numpy as np

import sys

import graphviz





def _get_thread_for_event(config, e):
@@ -14,6 +15,7 @@ def _get_thread_for_event(config, e): 
        print("Cannot find %s".format(name), file=sys.stderr)

        return None





def _happens_before(df, a, b, config):

    """

    check if a happens-before b in the trace
@@ -35,12 +37,14 @@ def _happens_before(df, a, b, config): 
    # If in doubt, a and b are concurrent.

    return not (df[a] >= df[b]).any()





def _fast_happens_before(df, a, b, hb):

    """

    check if a happens-before b, using a pre-computed relation

    """

    return any(r['Start'] == str(a) and r['End'] == str(b) for r in hb)





def _happens_directly_before(df, a, b, hb):

    """

    check if a happens-directly-before b in the trace
@@ -55,6 +59,7 @@ def _happens_directly_before(df, a, b, hb): 
            return False

    return True





def _locally_happens_directly_before(df, a, b, hb, config):

    """

    check if a happens-directly-before b in the trace but, be a little bit more
@@ -101,20 +106,19 @@ def _locally_happens_directly_before(df, a, b, hb, config): 
    else:

        return _happens_directly_before(df, a, b, hb)





def _plot_controlflow_graph(df, hdb):

    """

    print the control flow graph in a format that dot understands

    generate the control flow graph using dot

    """

    print("Digraph G {")

    for event1 in df:

        if not str(event1).endswith("_T"):

            continue

        print("\t_node__"+str(event1) + "[label=\""+str(event1)[:-2]+"\"]")

    t_columns = [x for x in df.columns if x.endswith("_T")]

    d = graphviz.Digraph(filename="graph", format="pdf")

    for event1 in df[t_columns]:

        d.node(str(event1)[:-2])

    for edge in hdb:

        print("\t_node__"+edge['Start'] + " -> _node__"+edge['End'] + ";")

    #for edge in hdb:

    #    print("\t_node__"+edge['Start'] + " -> _node__"+edge['End'] + "[label=\""+str(edge['Correlation'])+"\"];")

    print("}")

        d.edge(edge["Start"][:-2], edge["End"][:-2])

    d.render()  # saves to graph.pdf in local folder

    return d





# Taken from: http://composition.al/blog/2015/11/29/a-better-way-to-add-labels-to-bar-charts-with-matplotlib/
@@ -160,22 +164,17 @@ def _plot_critical_regions(df,hdb): 
        rects = ax.barh(x, correlations, align="center", tick_label="")

        autolabel(rects, ax, ticks)



    # TODO: find a more elegant solution for the label text

        plt.tight_layout()

        plt.savefig("latency-criticality.pdf")

        plt.close()







    def analyse(df, config):

        hb = []

    for event1 in df:

        if not str(event1).endswith("_T"):

            continue

        print(str(event1) + " ...", file=sys.stderr)

        for event2 in df:

            if not str(event2).endswith("_T"):

                continue



        events = [column for column in df.columns if column.endswith("_T")]



        for event1 in df[events]:

            for event2 in df[events]:

                if str(event1) == str(event2):

                    continue

                if _happens_before(df, event1, event2, config):
@@ -183,12 +182,8 @@ def analyse(df, config): 


        hdb = []

        e2e = list(df['EndToEnd_D'])

    for event1 in df:

        if not str(event1).endswith("_T"):

            continue

        for event2 in df:

            if not str(event2).endswith("_T"):

                continue

        for event1 in df[events]:

            for event2 in df[events]:

                if str(event1) == str(event2):

                    continue

                # if _locally_happens_directly_before(df, event1, event2, hb, config):
@@ -202,5 +197,8 @@ def analyse(df, config): 


                    hdb += [{'Start': str(event1), 'End': str(event2), 'Correlation': correlation}]



    _plot_controlflow_graph(df, hdb)

        cfg = _plot_controlflow_graph(df, hdb)

        _plot_critical_regions(df, hdb)

        return {

            "cfg": cfg

        }