diff --git a/examples/test_csv.json b/examples/test_csv.json
index 721ceee308bde6478d91c6b8e59419a7dbc667ab..0fe50484a4c12813bcb882f6ea2d865aa9aac6bb 100644
--- a/examples/test_csv.json
+++ b/examples/test_csv.json
@@ -1,7 +1,9 @@
{
"multi_criteria_optimizer": {
"name": "dakota",
- "model_data": {}
+ "model_data": {
+ "value_types": ["DUMMY"]
+ }
},
"data_sources": [
{
diff --git a/force_bdss/core_mco_driver.py b/force_bdss/core_mco_driver.py
index 54932bea10456e089627b8b339215ab492b352f2..b9e001e3a7e9f17bdc3328dfba785fb103b57bdb 100644
--- a/force_bdss/core_mco_driver.py
+++ b/force_bdss/core_mco_driver.py
@@ -41,68 +41,63 @@ class CoreMCODriver(Plugin):
@on_trait_change("application:started")
def application_started(self):
workflow = self.application.workflow
- if self.application.evaluate:
- ds_results = []
- for requested_ds in workflow.data_sources:
- ds_bundle = self._find_data_source_bundle_by_name(
- requested_ds.name)
- if ds_bundle:
- ds_model = ds_bundle.create_model(requested_ds.model_data)
- data_source = ds_bundle.create_data_source(
- self.application, ds_model)
- ds_results.append(data_source.run())
- else:
- raise Exception("Requested data source {} but don't know "
- "to find it.".format(requested_ds.name))
-
- kpi_results = []
- for requested_kpic in workflow.kpi_calculators:
- kpic_bundle = self._find_kpi_calculator_bundle_by_name(
- requested_kpic.name)
- if kpic_bundle:
- ds_model = kpic_bundle.create_model(
- requested_kpic.model_data)
- kpi_calculator = kpic_bundle.create_data_source(
- self.application, ds_model)
- kpi_results.append(kpi_calculator.run(ds_results))
- else:
- raise Exception(
- "Requested kpi calculator {} but don't know "
- "to find it.".format(requested_kpic.name))
-
- print(
- kpi_results[0].value_types,
- kpi_results[0].values
- )
-
- else:
- mco_data = workflow.multi_criteria_optimizer
- mco_bundle = self._find_mco_bundle_by_name(mco_data.name)
- if mco_bundle:
- mco_model = mco_bundle.create_model(mco_data.model_data)
- mco = mco_bundle.create_optimizer(self.application, mco_model)
- mco.run()
- else:
- raise Exception("Requested MCO {} but it's not available"
- "to compute it.".format(mco_data.name))
-
- def _find_data_source_bundle_by_name(self, name):
+
+ mco_data = workflow.multi_criteria_optimizer
+ mco_bundle = self._mco_bundle_by_name(mco_data.name)
+ mco_model = mco_bundle.create_model(mco_data.model_data)
+ mco = mco_bundle.create_optimizer(self.application, mco_model)
+ mco_communicator = mco_bundle.create_communicator(
+ self.application,
+ mco_model)
+
+ if not self.application.evaluate:
+ mco.run()
+ return
+
+ parameters = mco_communicator.receive_from_mco()
+
+ ds_results = []
+ for requested_ds in workflow.data_sources:
+ ds_bundle = self._data_source_bundle_by_name(
+ requested_ds.name)
+ ds_model = ds_bundle.create_model(requested_ds.model_data)
+ data_source = ds_bundle.create_data_source(
+ self.application, ds_model)
+ ds_results.append(data_source.run(parameters))
+
+ kpi_results = []
+ for requested_kpic in workflow.kpi_calculators:
+ kpic_bundle = self._kpi_calculator_bundle_by_name(
+ requested_kpic.name)
+ ds_model = kpic_bundle.create_model(
+ requested_kpic.model_data)
+ kpi_calculator = kpic_bundle.create_data_source(
+ self.application, ds_model)
+ kpi_results.append(kpi_calculator.run(ds_results))
+
+ mco_communicator.send_to_mco(kpi_results)
+
+ def _data_source_bundle_by_name(self, name):
for ds in self.data_source_bundles:
if ds.name == name:
return ds
- return None
+ raise Exception("Requested data source {} but don't know "
+ "to find it.".format(name))
- def _find_kpi_calculator_bundle_by_name(self, name):
+ def _kpi_calculator_bundle_by_name(self, name):
for kpic in self.kpi_calculator_bundles:
if kpic.name == name:
return kpic
- return None
+ raise Exception(
+ "Requested kpi calculator {} but don't know "
+ "to find it.".format(name))
- def _find_mco_bundle_by_name(self, name):
+ def _mco_bundle_by_name(self, name):
for mco in self.mco_bundles:
if mco.name == name:
return mco
- return None
+ raise Exception("Requested MCO {} but it's not available"
+ "to compute it.".format(mco_data.name))
diff --git a/force_bdss/core_plugins/csv_extractor/csv_extractor/csv_extractor_data_source.py b/force_bdss/core_plugins/csv_extractor/csv_extractor/csv_extractor_data_source.py
index 8cfb74e216012d83c3cb1a5bf819617f0ae4ae6b..7208153c407f679ab45978fa594415ce3cb7d67b 100644
--- a/force_bdss/core_plugins/csv_extractor/csv_extractor/csv_extractor_data_source.py
+++ b/force_bdss/core_plugins/csv_extractor/csv_extractor/csv_extractor_data_source.py
@@ -5,7 +5,7 @@ from force_bdss.data_sources.data_source_result import DataSourceResult
class CSVExtractorDataSource(BaseDataSource):
- def run(self):
+ def run(self, parameters):
with open(self.model.filename) as csvfile:
reader = csv.reader(csvfile)
for rowindex, row in enumerate(reader):
@@ -17,7 +17,8 @@ class CSVExtractorDataSource(BaseDataSource):
originator=self,
value_types = [self.model.cuba_type],
values=numpy.array(
- float(row[self.model.column])).reshape(1,1)
+ parameters.values[0]+float(
+ row[self.model.column])).reshape(1,1)
)
return None
diff --git a/force_bdss/core_plugins/test_mco/dakota/dakota_bundle.py b/force_bdss/core_plugins/test_mco/dakota/dakota_bundle.py
index 12c34ab2e3502eb1edbbf0ef9952551da93b0db8..effed5735912edbfbd331e04a69aaf1dfce4b59e 100644
--- a/force_bdss/core_plugins/test_mco/dakota/dakota_bundle.py
+++ b/force_bdss/core_plugins/test_mco/dakota/dakota_bundle.py
@@ -1,6 +1,8 @@
from traits.has_traits import HasStrictTraits, provides
from traits.trait_types import String
+from force_bdss.core_plugins.test_mco.dakota.dakota_communicator import \
+ DakotaCommunicator
from force_bdss.mco.i_multi_criteria_optimizer_bundle import (
IMultiCriteriaOptimizerBundle)
@@ -17,3 +19,6 @@ class DakotaBundle(HasStrictTraits):
def create_optimizer(self, application, model):
return DakotaOptimizer(self, application, model)
+
+ def create_communicator(self, application, model):
+ return DakotaCommunicator(self, application, model)
diff --git a/force_bdss/core_plugins/test_mco/dakota/dakota_communicator.py b/force_bdss/core_plugins/test_mco/dakota/dakota_communicator.py
new file mode 100644
index 0000000000000000000000000000000000000000..ae9677fdf72b409ef79956c3852163da4ba9d35c
--- /dev/null
+++ b/force_bdss/core_plugins/test_mco/dakota/dakota_communicator.py
@@ -0,0 +1,27 @@
+import sys
+import numpy
+
+from force_bdss.data_sources.data_source_parameters import DataSourceParameters
+from force_bdss.mco.base_mco_communicator import BaseMCOCommunicator
+
+
+class DakotaCommunicator(BaseMCOCommunicator):
+ def receive_from_mco(self):
+ data = sys.stdin.read()
+ values = list(map(float, data.split()))
+ value_types = self.model.value_types
+ if len(values) != len(value_types):
+ raise ValueError("Length of provided data differs from the number "
+ "of expected types. {} {}".format(values,
+ value_types))
+
+ return DataSourceParameters(
+ value_types=value_types,
+ values=numpy.array(values)
+ )
+
+ def send_to_mco(self, kpi_results):
+ data = " ".join(
+ [" ".join(list(map(str, r.values.tolist()))) for r in kpi_results]
+ )
+ sys.stdout.write(data)
diff --git a/force_bdss/core_plugins/test_mco/dakota/dakota_model.py b/force_bdss/core_plugins/test_mco/dakota/dakota_model.py
index ed6ff342dfdd8c2ee8742ba32f86808cb8f82582..fe7edcdc6cb3411945de29cdec4806e5cecce88f 100644
--- a/force_bdss/core_plugins/test_mco/dakota/dakota_model.py
+++ b/force_bdss/core_plugins/test_mco/dakota/dakota_model.py
@@ -1,7 +1,9 @@
-from traits.api import HasStrictTraits
+from traits.api import HasStrictTraits, List, String
class DakotaModel(HasStrictTraits):
+ value_types = List(String)
+
@classmethod
def from_json(cls, model_data):
- return cls()
+ return cls(value_types=model_data["value_types"])
diff --git a/force_bdss/core_plugins/test_mco/dakota/dakota_optimizer.py b/force_bdss/core_plugins/test_mco/dakota/dakota_optimizer.py
index 0f8f064cc985e2afdb6fc99765f42596ae49cece..edd177d6e863c41a4e6b378926ceff92a5b3c15a 100644
--- a/force_bdss/core_plugins/test_mco/dakota/dakota_optimizer.py
+++ b/force_bdss/core_plugins/test_mco/dakota/dakota_optimizer.py
@@ -10,5 +10,13 @@ from force_bdss.mco.base_multi_criteria_optimizer import (
class DakotaOptimizer(BaseMultiCriteriaOptimizer):
def run(self):
print("Running dakota optimizer")
- subprocess.check_call([sys.argv[0], "--evaluate",
- self.application.workflow_filepath])
+ for initial_value in range(10):
+ ps = subprocess.Popen(
+ [sys.argv[0],
+ "--evaluate",
+ self.application.workflow_filepath],
+ stdout=subprocess.PIPE,
+ stdin=subprocess.PIPE)
+
+ out = ps.communicate("{}".format(initial_value).encode("utf-8"))
+ print("{}: {}".format(initial_value, out[0].decode("utf-8")))
diff --git a/force_bdss/data_sources/base_data_source.py b/force_bdss/data_sources/base_data_source.py
index 469ed8b902cc9d237139bf6b53ef6e2a952a20e8..e8eec36d78660d9aab8eb24f2e140392d807a05e 100644
--- a/force_bdss/data_sources/base_data_source.py
+++ b/force_bdss/data_sources/base_data_source.py
@@ -13,7 +13,7 @@ class BaseDataSource(six.with_metaclass(abc.ABCMeta)):
return self.bundle.name
@abc.abstractmethod
- def run(self):
+ def run(self, parameters):
"""Executes the data source evaluation/fetching and returns
the list of results as a DataSourceResult instance."""
pass
diff --git a/force_bdss/data_sources/data_source_parameters.py b/force_bdss/data_sources/data_source_parameters.py
new file mode 100644
index 0000000000000000000000000000000000000000..c45915dd1f056873e96e9e957753a90409c3d215
--- /dev/null
+++ b/force_bdss/data_sources/data_source_parameters.py
@@ -0,0 +1,6 @@
+from traits.api import HasStrictTraits, Array, List, String
+
+
+class DataSourceParameters(HasStrictTraits):
+ value_types = List(String)
+ values = Array(shape=(None,))
diff --git a/force_bdss/mco/base_mco_communicator.py b/force_bdss/mco/base_mco_communicator.py
new file mode 100644
index 0000000000000000000000000000000000000000..308903166cdebdbf8dcee705ff4089fb626e3639
--- /dev/null
+++ b/force_bdss/mco/base_mco_communicator.py
@@ -0,0 +1,17 @@
+import abc
+import six
+
+
+class BaseMCOCommunicator(six.with_metaclass(abc.ABCMeta)):
+ def __init__(self, bundle, application, model):
+ self.bundle = bundle
+ self.application = application
+ self.model = model
+
+ @abc.abstractmethod
+ def receive_from_mco(self):
+ pass
+
+ @abc.abstractmethod
+ def send_to_mco(self):
+ pass
diff --git a/force_bdss/mco/i_multi_criteria_optimizer_bundle.py b/force_bdss/mco/i_multi_criteria_optimizer_bundle.py
index 33c9a37c78a932045132609ef4f3a455b706ba22..f84cca5379b0bacb7ca11365ac84777307015cdb 100644
--- a/force_bdss/mco/i_multi_criteria_optimizer_bundle.py
+++ b/force_bdss/mco/i_multi_criteria_optimizer_bundle.py
@@ -9,3 +9,6 @@ class IMultiCriteriaOptimizerBundle(Interface):
def create_model(self, model_data):
pass
+
+ def create_communicator(self, model_data):
+ pass