def _trim_state_df(self, state_df):
if state_df.empty:
return state_df
return df_squash(state_df, self.start_time,
state_df.index[-1] + state_df['delta'].iloc[-1],
"delta")
def _trim_state_df(self, state_df):
if state_df.empty:
return state_df
return df_squash(state_df, self.start_time,
state_df.index[-1] + state_df.delta.values[-1],
"delta")
def _max_idle_time(self, start, end, cpus):
"""
:returns: The maximum idle time of 'cpus' in the [start, end] interval
"""
max_time = 0
max_cpu = 0
for cpu in cpus:
busy_df = self._get_active_df(cpu)
busy_df = df_squash(busy_df, start, end)
busy_df = busy_df[busy_df.state == 0]
if busy_df.empty:
continue
local_max = busy_df.delta.max()
if local_max > max_time:
max_time = local_max
max_cpu = cpu
return max_time, max_cpu
def test_squash_df(self):
"""
TestTrace: df_squash() behaves as expected
"""
index = [float(i) for i in range(15, 20)]
data = [(1, i % 2) for i in range(15, 20)]
df = pd.DataFrame(index=index, data=data, columns=['delta', 'state'])
## Test "standard" slice:
# The df here should be:
# Time delta state
# 16.5 .5 0
# 17 .5 1
df1 = df_squash(
df,
16.5,
17.5,
)
head = df1.head(1)
tail = df1.tail(1)
self.assertEqual(len(df1.index), 2)
self.assertEqual(df1.index.tolist(), [16.5, 17])
self.assertAlmostEqual(head['delta'].values[0], 0.5)
self.assertAlmostEqual(tail['delta'].values[0], 0.5)
self.assertEqual(head['state'].values[0], 0)
self.assertEqual(tail['state'].values[0], 1)
## Test slice where no event exists in the interval
# The df here should be:
# Time delta state
# 16.2 .6 0
df2 = df_squash(df, 16.2, 16.8)
self.assertEqual(len(df2.index), 1)
self.assertEqual(df2.index[0], 16.2)
self.assertAlmostEqual(df2['delta'].values[0], 0.6)
self.assertEqual(df2['state'].values[0], 0)
## Test slice that matches an event's index
# The df here should be:
# Time delta state
# 16 1 0
df3 = df_squash(df, 16, 17)
self.assertEqual(len(df3.index), 1)
self.assertEqual(df3.index[0], 16)
self.assertAlmostEqual(df3['delta'].values[0], 1)
self.assertEqual(df3['state'].values[0], 0)
## Test slice past last event
# The df here should be:
# Time delta state
# 19.5 .5 1
df4 = df_squash(df, 19.5, 22)
self.assertEqual(len(df4.index), 1)
self.assertEqual(df4.index[0], 19.5)
self.assertAlmostEqual(df4['delta'].values[0], 0.5)
self.assertEqual(df4['state'].values[0], 1)
## Test slice where there's no past event
df5 = df_squash(df, 10, 30)
self.assertEqual(len(df5.index), 5)
## Test slice where that should contain nothing
df6 = df_squash(df, 8, 9)
self.assertEqual(len(df6.index), 0)
def test_squash_df(self):
"""
TestTrace: df_squash() behaves as expected
"""
index = [float(i) for i in range(15, 20)]
data = [(1, i % 2) for i in range(15, 20)]
df = pd.DataFrame(index=index, data=data, columns=['delta', 'state'])
# Test "standard" slice:
# The df here should be:
# Time delta state
# 16.5 .5 0
# 17 .5 1
df1 = df_squash(
df,
16.5,
17.5,
)
head = df1.head(1)
tail = df1.tail(1)
assert len(df1.index) == 2
assert df1.index.tolist() == [16.5, 17]
assert head['delta'].values[0] == pytest.approx(0.5)
assert tail['delta'].values[0] == pytest.approx(0.5)
assert head['state'].values[0] == 0
assert tail['state'].values[0] == 1
# Test slice where no event exists in the interval
# The df here should be:
# Time delta state
# 16.2 .6 0
df2 = df_squash(df, 16.2, 16.8)
assert len(df2.index) == 1
assert df2.index[0] == 16.2
assert df2['delta'].values[0] == pytest.approx(0.6)
assert df2['state'].values[0] == 0
# Test slice that matches an event's index
# The df here should be:
# Time delta state
# 16 1 0
df3 = df_squash(df, 16, 17)
assert len(df3.index) == 1
assert df3.index[0] == 16
assert df3['delta'].values[0] == pytest.approx(1)
assert df3['state'].values[0] == 0
# Test slice past last event
# The df here should be:
# Time delta state
# 19.5 .5 1
df4 = df_squash(df, 19.5, 22)
assert len(df4.index) == 1
assert df4.index[0] == 19.5
assert df4['delta'].values[0] == pytest.approx(0.5)
assert df4['state'].values[0] == 1
# Test slice where there's no past event
df5 = df_squash(df, 10, 30)
assert len(df5.index) == 5
# Test slice where that should contain nothing
df6 = df_squash(df, 8, 9)
assert len(df6.index) == 0
