#!/usr/bin/python

################################################################################
# Description
################################################################################
# This is a sample script for using the tool. I would recommend copying
# this and modifying it to suit your needs for a particular test. Make
# sure you redirect the output to a file (e.g. ./sample_script.py > output).

################################################################################
# Setup
################################################################################

# Import the modules we need. You should not need to know about
# their internals.
import unit_trace
from unit_trace import trace_reader
from unit_trace import sanitizer
from unit_trace import gedf_test
from unit_trace import stats
from unit_trace import stdout_printer
from unit_trace import visualizer

# Specify your trace files
g6 = [
'./sample_traces/st-g6-0.bin',
'./sample_traces/st-g6-1.bin',
'./sample_traces/st-g6-2.bin',
'./sample_traces/st-g6-3.bin',
]

################################################################################
# Pipeline
################################################################################

# Read events from traces
stream = trace_reader.trace_reader(g6)

# Filter out garbage events
stream = sanitizer.sanitizer(stream)

# Produce G-EDF error records
stream = gedf_test.gedf_test(stream)

# Produce a statistics record
stream = stats.stats(stream)

# Filter some records out
# NOTE: Currently, this will break the Visualizer if enabled
def my_filter(record):
    if record.record_type == 'error' and record.type_name == 'inversion_end':
        if record.job.inversion_end - record.job.inversion_start < 4000000:
            return False
    return True
#stream = filter(my_filter, stream)

# Split the stream in two, so we can use both output mechanisms
import itertools
stream1, stream2 = itertools.tee(stream,2)

# Print the records to stdout
stdout_printer.stdout_printer(stream1)

# Visualize the records
visualizer.visualizer(stream2)