updateConfigFromSubConfig(config)
# Compute predictionSteps based on the predictAheadTime and the aggregation
# period, which may be permuted over.
if config['predictAheadTime'] is not None:
predictionSteps = int(
round(
aggregationDivide(config['predictAheadTime'],
config['aggregationInfo'])))
assert (predictionSteps >= 1)
config['modelParams']['clParams']['steps'] = str(predictionSteps)
# Adjust config by applying ValueGetterBase-derived
# futures. NOTE: this MUST be called after updateConfigFromSubConfig() in order
# to support value-getter-based substitutions from the sub-experiment (if any)
applyValueGettersToContainer(config)
control = {
# The environment that the current model is being run in
"environment":
'nupic',
# Input stream specification per py/nupicengine/cluster/database/StreamDef.json.
#
'dataset': {
u'info':
u'test_NoProviders',
u'streams': [{
u'columns': [u'*'],
u'info': u'test data',
u'source': u'file://swarming/test_data.csv'
updateConfigFromSubConfig(config)
# Compute predictionSteps based on the predictAheadTime and the aggregation
# period, which may be permuted over.
if config['predictAheadTime'] is not None:
predictionSteps = int(round(aggregationDivide(
config['predictAheadTime'], config['aggregationInfo'])))
assert (predictionSteps >= 1)
config['modelParams']['clParams']['steps'] = str(predictionSteps)
# Adjust config by applying ValueGetterBase-derived
# futures. NOTE: this MUST be called after updateConfigFromSubConfig() in order
# to support value-getter-based substitutions from the sub-experiment (if any)
applyValueGettersToContainer(config)
control = {
# The environment that the current model is being run in
"environment": 'nupic',
# Input stream specification per py/nupicengine/cluster/database/StreamDef.json.
#
'dataset' : {u'info': u'test_NoProviders',
u'streams': [ { u'columns': [u'*'],
u'info': "test data",
u'source': "file://swarming/test_data.csv"}],
u'version': 1},
