# Copyright 2015-2017 ARM Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from test_thermal import BaseTestThermal
import trappy
from trappy.stats.grammar import Parser
from pandas.util.testing import assert_series_equal
import numpy as np
import pandas
from distutils.version import LooseVersion as V
import unittest
class TestStatsGrammar(BaseTestThermal):
def __init__(self, *args, **kwargs):
super(TestStatsGrammar, self).__init__(*args, **kwargs)
def test_sum_operator(self):
"""Test Addition And Subtraction: Numeric"""
parser = Parser(trappy.BareTrace())
# Simple equation
eqn = "10 + 2 - 3"
self.assertEquals(parser.solve(eqn), 9)
# Equation with bracket and unary ops
eqn = "(10 + 2) - (-3 + 2)"
self.assertEquals(parser.solve(eqn), 13)
@unittest.skipIf(V(pandas.__version__) < V('0.16.1'),
"check_names is not supported in pandas < 0.16.1")
def test_accessors_sum(self):
"""Test Addition And Subtraction: Data"""
thermal_zone_id = 0
parser = Parser(trappy.FTrace())
# Equation with dataframe accessors
eqn = "trappy.thermal.Thermal:temp + \
trappy.thermal.Thermal:temp"
assert_series_equal(
parser.solve(eqn)[thermal_zone_id],
2 *
parser.data.thermal.data_frame["temp"], check_names=False)
def test_funcparams_sum(self):
"""Test Addition And Subtraction: Functions"""
thermal_zone_id = 0
parser = Parser(trappy.FTrace())
# Equation with functions as parameters (Mixed)
eqn = "numpy.mean(trappy.thermal.Thermal:temp) + 1000"
self.assertEquals(
parser.solve(eqn)[thermal_zone_id],
np.mean(
parser.data.thermal.data_frame["temp"]) +
1000)
# Multiple func params
eqn = "numpy.mean(trappy.thermal.Thermal:temp) + numpy.mean(trappy.thermal.Thermal:temp)"
self.assertEquals(
parser.solve(eqn)[thermal_zone_id],
np.mean(
parser.data.thermal.data_frame["temp"]) *
2)
def test_parser_with_name(self):
"""Test equation using event name"""
thermal_zone_id = 0
parser = Parser(trappy.FTrace())
# Equation with functions as parameters (Mixed)
eqn = "numpy.mean(thermal:temp) + 1000"
self.assertEquals(
parser.solve(eqn)[thermal_zone_id],
np.mean(
parser.data.thermal.data_frame["temp"]) + 1000)
def test_bool_ops_vector(self):
"""Test Logical Operations: Vector"""
thermal_zone_id = 0
# The equation returns a vector mask
parser = Parser(trappy.FTrace())
eqn = "(trappy.thermal.ThermalGovernor:current_temperature > 77000)\
& (trappy.pid_controller.PIDController:output > 2500)"
mask = parser.solve(eqn)
self.assertEquals(len(parser.ref(mask.dropna()[0])), 0)
def test_bool_ops_scalar(self):
"""Test Logical Operations: Vector"""
thermal_zone_id=0
parser = Parser(trappy.FTrace())
# The equation returns a boolean scalar
eqn = "(numpy.mean(trappy.thermal.Thermal:temp) > 65000) && (numpy.mean(trappy.cpu_power.CpuOutPower) > 500)"
self.assertTrue(parser.solve(eqn)[thermal_zone_id])
eqn = "(numpy.mean(trappy.thermal.Thermal:temp) > 65000) || (numpy.mean(trappy.cpu_power.CpuOutPower) < 500)"
self.assertTrue(parser.solve(eqn)[thermal_zone_id])
def test_super_indexing(self):
"Test if super-indexing works correctly"""
trace = trappy.FTrace()
parser = Parser(trace)
# The first event has less index values
sol1 = parser.solve("trappy.thermal.Thermal:temp")
# The second index has more index values
sol2 = parser.solve("trappy.pid_controller.PIDController:output")
# Super Indexing should result in len(sol2) > len(sol1)
self.assertGreater(len(sol2), len(sol1))
def test_single_func_call(self):
"""Test Single Function Call"""
thermal_zone_id = 0
parser = Parser(trappy.FTrace())
eqn = "numpy.mean(trappy.thermal.Thermal:temp)"
self.assertEquals(
parser.solve(eqn)[thermal_zone_id],
np.mean(
parser.data.thermal.data_frame["temp"]))
def test_mul_ops(self):
"""Test Mult and Division: Numeric"""
parser = Parser(trappy.BareTrace())
eqn = "(10 * 2 / 10)"
self.assertEquals(parser.solve(eqn), 2)
eqn = "-2 * 2 + 2 * 10 / 10"
self.assertEquals(parser.solve(eqn), -2)
eqn = "3.5 // 2"
self.assertEquals(parser.solve(eqn), 1)
eqn = "5 % 2"
self.assertEquals(parser.solve(eqn), 1)
def test_exp_ops(self):
"""Test exponentiation: Numeric"""
parser = Parser(trappy.BareTrace())
eqn = "3**3 * 2**4"
self.assertEquals(parser.solve(eqn), 432)
eqn = "3**(4/2)"
self.assertEquals(parser.solve(eqn), 9)
@unittest.skipIf(V(pandas.__version__) < V('0.16.1'),
"check_names is not supported in pandas < 0.16.1")
def test_funcparams_mul(self):
"""Test Mult and Division: Data"""
thermal_zone_id = 0
parser = Parser(trappy.FTrace())
eqn = "trappy.thermal.Thermal:temp * 10.0"
series = parser.data.thermal.data_frame["temp"]
assert_series_equal(parser.solve(eqn)[thermal_zone_id], series * 10.0, check_names=False)
eqn = "trappy.thermal.Thermal:temp / trappy.thermal.Thermal:temp * 10"
assert_series_equal(parser.solve(eqn)[thermal_zone_id], series / series * 10, check_names=False)
def test_var_forward(self):
"""Test Forwarding: Variable"""
thermal_zone_id = 0
pvars = {}
pvars["control_temp"] = 78000
parser = Parser(trappy.FTrace(), pvars=pvars)
eqn = "numpy.mean(trappy.thermal.Thermal:temp) < control_temp"
self.assertTrue(parser.solve(eqn)[thermal_zone_id])
def test_func_forward(self):
"""Test Forwarding: Mixed"""
thermal_zone_id = 0
pvars = {}
pvars["mean"] = np.mean
pvars["control_temp"] = 78000
parser = Parser(trappy.FTrace(), pvars=pvars)
eqn = "mean(trappy.thermal.Thermal:temp) < control_temp"
self.assertTrue(parser.solve(eqn)[thermal_zone_id])
def test_cls_forward(self):
"""Test Forwarding: Classes"""
cls = trappy.thermal.Thermal
pvars = {}
pvars["mean"] = np.mean
pvars["control_temp"] = 78000
pvars["therm"] = cls
thermal_zone_id = 0
parser = Parser(trappy.FTrace(), pvars=pvars)
eqn = "mean(therm:temp) < control_temp"
self.assertTrue(parser.solve(eqn)[thermal_zone_id])
def test_for_parsed_event(self):
"""Test if an added parsed event can be accessed"""
trace = trappy.FTrace(scope="custom")
dfr = pandas.DataFrame({"l1_misses": [24, 535, 41],
"l2_misses": [155, 11, 200],
"cpu": [ 0, 1, 0]},
index=pandas.Series([1.020, 1.342, 1.451], name="Time"))
trace.add_parsed_event("pmu_counters", dfr)
p = Parser(trace)
self.assertTrue(len(p.solve("pmu_counters:cpu")), 3)
def test_windowed_parse(self):
"""Test that the parser can operate on a window of the trace"""
trace = trappy.FTrace()
prs = Parser(trace, window=(2, 3))
dfr_res = prs.solve("thermal:temp")
self.assertGreater(dfr_res.index[0], 2)
self.assertLess(dfr_res.index[-1], 3)
prs = Parser(trace, window=(4, None))
dfr_res = prs.solve("thermal:temp")
self.assertGreater(dfr_res.index[0], 4)
self.assertEquals(dfr_res.index[-1], trace.thermal.data_frame.index[-1])
prs = Parser(trace, window=(0, 1))
dfr_res = prs.solve("thermal:temp")
self.assertEquals(dfr_res.index[0], trace.thermal.data_frame.index[0])
self.assertLess(dfr_res.index[-1], 1)
def test_filtered_parse(self):
"""The Parser can filter a trace"""
trace = trappy.FTrace()
prs = Parser(trace, filters={"cdev_state": 3})
dfr_res = prs.solve("devfreq_out_power:freq")
self.assertEquals(len(dfr_res), 1)
def test_no_events(self):
"""Test trying to parse absent data"""
trace = trappy.FTrace()
prs = Parser(trace)
# cpu_frequency is an event we know how to parse, but it isn't present
# in the test trace.
self.assertRaisesRegexp(ValueError, "No events found for cpu_frequency",
prs.solve, "cpu_frequency:frequency")