def test_frequency_sane_fmap(self):
"""
Test that the hint is respected for MPI regions within a
user marked region with the compute hint.
"""
report = geopmpy.io.RawReport(self._fmap_report_path)
host_name = report.host_names()[0]
region = report.raw_region(host_name, 'compute_region')
assigned_freq = report.get_field(region, 'frequency-map')
achieved_freq = report.get_field(region, 'frequency', 'Hz')
# Fmap agent should assign policy default frequency for regions not
# in the map.
self.assertEqual(
self._freq_default,
assigned_freq,
msg=
'Expected assigned frequency to be max from policy since this region has the COMPUTE hint. ({} != {})'
.format(self._freq_default, assigned_freq))
util.assertNear(
self,
self._freq_default,
achieved_freq,
msg=
'Expected achieved frequency to be near default from policy. ({} !~= {})'
.format(self._freq_default, achieved_freq))
def testBmiNotNan(self):
#tombomist is too old for most calculations, but BMI should be calculated
visit_stats = VisitStatistics.get_stats(
datetime.date(1995,03,21),
datetime.date(2007,03,25),
Sex.MALE,
30, 49.5, 140,
Measured.STANDING, None)
util.assertNear(self, 15.3, visit_stats.body_mass_index, 0.1)
def test_uniform_performance(self):
"""Test that the reports generated show uniform performance with
respect to CPU frequency.
"""
report = geopmpy.io.RawReport(self._report_path)
host_names = report.host_names()
for host in host_names:
for rn in report.region_names(host):
if rn.startswith('timed_scaling_region'):
region = report.raw_region(host, rn)
util.assertNear(self, 1.0, report.get_field(region, 'runtime', 'sec'))
def testZeroDayStats(self):
# Age is 0 days, whcih is still valid.
# Equivalent to AA2 in the anthrotest.csv
visit_stats = VisitStatistics.get_stats(
datetime.date(2009,11,27),
datetime.date(2009,11,27),
Sex.FEMALE,
4, 35, 49,
Measured.RECUMBENT, None)
# Length-or-height for age
zandp = visit_stats.get_zandp('length_or_height_for_age')
util.assertNear(self, -0.08, zandp.zscore, 0.01)
util.assertNear(self, 46.8, zandp.percentile, 0.1)
def testLengthOrHeightForAgeNotNan(self):
# Age is right on the border, but still valid.
# Equivalent to AA2 in the anthrotest.csv.
visit_stats = VisitStatistics.get_stats(
datetime.date(2002,03,15),
datetime.date(2007,04,14),
Sex.MALE,
10, 50, 65.6,
Measured.RECUMBENT, None)
# Length-or-height for age
zandp = visit_stats.get_zandp('length_or_height_for_age')
util.assertNear(self, -9.76, zandp.zscore, 0.01)
self.assertTrue(util.isNaN(zandp.percentile))
def test_achieved_frequency(self):
"""Test that the reports show achieved frequencies near target
frequency.
"""
report = geopmpy.io.RawReport(self._report_path)
host_names = report.host_names()
for host in host_names:
for rn in ['timed_scaling_region_{}'.format(idx)
for idx in range(len(self._region_freq))]:
region = report.raw_region(host, rn)
request_freq = report.get_field(region, 'frequency-map')
actual_freq = report.get_field(region, 'frequency', 'Hz')
util.assertNear(self, request_freq, actual_freq)
def test2(self):
visit_stats = VisitStatistics.get_stats(
datetime.date(2005,03,21),
datetime.date(2007,03,25),
Sex.FEMALE,
8.2, 45, 74,
Measured.RECUMBENT, None)
# BMI
util.assertNear(self, 15.3, visit_stats.body_mass_index, 0.1)
# Weight-for-length-or-height
zandp = visit_stats.get_zandp('weight_for_length_or_height')
util.assertNear(self, -1.00, zandp.zscore, 0.01)
util.assertNear(self, 15.9, zandp.percentile, 0.1)
# Weight-for-age
zandp = visit_stats.get_zandp('weight_for_age')
util.assertNear(self, -2.87, zandp.zscore, 0.01)
util.assertNear(self, 0.2, zandp.percentile, 0.1)
# Length-or-height for age
zandp = visit_stats.get_zandp('length_or_height_for_age')
util.assertNear(self, -3.87, zandp.zscore, 0.01)
self.assertTrue(util.isNaN(zandp.percentile))
# BMI-for-age
zandp = visit_stats.get_zandp('body_mass_index_for_age')
util.assertNear(self, -0.33, zandp.zscore, 0.01)
util.assertNear(self, 37.2, zandp.percentile, 0.1)
# HC-for-age
zandp = visit_stats.get_zandp('head_circumference_for_age')
util.assertNear(self, -1.58, zandp.zscore, 0.01)
util.assertNear(self, 5.8, zandp.percentile, 0.1)
def test1(self):
# Bernadette
sex = Sex.FEMALE
dateOfBirth = datetime.date(2005,03,21)
dateOfVisit = datetime.date(2007,03,25)
ageInDays = (dateOfVisit - dateOfBirth).days
weight = 8.2 # kg
length = 74.0 # cm
headCircumference = 45.0 # cm
measured = Measured.RECUMBENT
loh = growthcalc.growthcalc.NormalizedLengthOrHeight(
ageInDays, length, measured)
bmi = growthcalc.growthcalc.heightAndWeightToBmi(loh.lengthOrHeight, weight)
util.assertNear(self, 15.3, bmi, 0.1)
anthro = growthcalc.growthcalc.Anthro()
# Weight-for-length-or-height
zscore = anthro.getWeightZscoreConfigForLengthOrHeight(
Sex.map[sex], loh, weight, ageInDays)
percentile = growthcalc.growthcalc.zscoreToPercentile(zscore)
util.assertNear(self, -1.00, zscore, 0.01)
util.assertNear(self, 15.9, percentile, 0.1)
# Weight-for-age
zscore = anthro.getWeightZscoreConfigForAge(Sex.map[sex], ageInDays, weight)
percentile = growthcalc.growthcalc.zscoreToPercentile(zscore)
util.assertNear(self, -2.87, zscore, 0.01)
util.assertNear(self, 0.2, percentile, 0.1)
# Length-or-height for age
zscore = anthro.getLengthOrHeightZscoreConfigForAge(
Sex.map[sex], ageInDays, loh.lengthOrHeight, measured)
percentile = growthcalc.growthcalc.zscoreToPercentile(zscore)
util.assertNear(self, -3.87, zscore, 0.01)
self.assertTrue(util.isNaN(percentile))
# BMI-for-age
zscore = anthro.getBodyMassIndexZscoreConfigForAge(
Sex.map[sex], ageInDays, bmi, weight, loh.lengthOrHeight)
percentile = growthcalc.growthcalc.zscoreToPercentile(zscore)
util.assertNear(self, -0.33, zscore, 0.01)
util.assertNear(self, 37.2, percentile, 0.1)
# HC-for-age
zscore = anthro.getHeadCircumferenceZscoreConfigForAge(
Sex.map[sex], ageInDays, headCircumference)
percentile = growthcalc.growthcalc.zscoreToPercentile(zscore)
util.assertNear(self, -1.58, zscore, 0.01)
util.assertNear(self, 5.8, percentile, 0.1)
