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energy_model: fix np.vectorize on ImportError

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np.vectorize was being unconditionally invoked at top level. On an
ImportError, np as set to None, so this was resuling in an
AttributeError when loading the module if one of the dependent libraries
was not present on the host system. This moves the invocation into the
try block with the imports to avoid an error when energy_model module is
loaded by the extension is not used.
This commit is contained in:
Sergei Trofimov 2015-05-12 10:40:25 +01:00
parent b30d702f22
commit 98b259be33
1 changed files with 2 additions and 3 deletions
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5
wlauto/instrumentation/energy_model/__init__.py
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@ -15,6 +15,7 @@ try:
matplotlib.use('AGG')
import matplotlib.pyplot as plt
import numpy as np
low_filter = np.vectorize(lambda x: x > 0 and x or 0) # pylint: disable=no-member
import_error = None
except ImportError as e:
import_error = e
@ -22,6 +23,7 @@ except ImportError as e:
pd = None
plt = None
np = None
low_filter = None
from wlauto import Instrument, Parameter, File
from wlauto.exceptions import ConfigError, InstrumentError, DeviceError
@ -100,9 +102,6 @@ class PowerPerformanceAnalysis(object):
self.summary['max_power'] = data[data.cpus == 1].power.max()
low_filter = np.vectorize(lambda x: x > 0 and x or 0) # pylint: disable=no-member
def build_energy_model(freq_power_table, cpus_power, idle_power, first_cluster_idle_state):
# pylint: disable=too-many-locals
em = EnergyModel()