# 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")