diff --git a/force_bdss/core_plugins/dummy_mco/dakota/dakota_communicator.py b/force_bdss/core_plugins/dummy_mco/dakota/dakota_communicator.py
index ee349e806571d776d49a0dfc533bd53224931322..1b816841c7a719d2e1c566cc3afacaa7a0d245b3 100644
--- a/force_bdss/core_plugins/dummy_mco/dakota/dakota_communicator.py
+++ b/force_bdss/core_plugins/dummy_mco/dakota/dakota_communicator.py
@@ -8,13 +8,20 @@ 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))
+ parameters = self.model.parameters
+
+ if len(values) != len(parameters):
+ raise ValueError(
+ "The passed information length is {}, but the model "
+ "specifies {} values.".format(
+ len(values), len(parameters)
+ ))
+
+ value_types = [p.type for p in parameters]
+ value_names = [p.name for p in parameters]
return DataSourceParameters(
+ value_names=value_names,
value_types=value_types,
values=numpy.array(values)
)
diff --git a/force_bdss/core_plugins/dummy_mco/dakota/dakota_model.py b/force_bdss/core_plugins/dummy_mco/dakota/dakota_model.py
index b4c081a6b38bd5478f4287624411c5ce185cd01d..3c0d14a4dffbc438c267eb32121010b8fd1437f4 100644
--- a/force_bdss/core_plugins/dummy_mco/dakota/dakota_model.py
+++ b/force_bdss/core_plugins/dummy_mco/dakota/dakota_model.py
@@ -1,7 +1,5 @@
-from traits.api import List, String
-
from force_bdss.api import BaseMCOModel
class DakotaModel(BaseMCOModel):
- value_types = List(String)
+ pass
diff --git a/force_bdss/core_plugins/dummy_mco/dakota/dakota_optimizer.py b/force_bdss/core_plugins/dummy_mco/dakota/dakota_optimizer.py
index 6b607cfce35432d286642465e36e90387f5a6c34..485a3d6531432c6fa89c34e47c6dc065903717d1 100644
--- a/force_bdss/core_plugins/dummy_mco/dakota/dakota_optimizer.py
+++ b/force_bdss/core_plugins/dummy_mco/dakota/dakota_optimizer.py
@@ -1,14 +1,34 @@
import subprocess
-
import sys
+import itertools
+import collections
from force_bdss.api import BaseMultiCriteriaOptimizer
+def rotated_range(start, stop, starting_value):
+ r = list(range(start, stop))
+ start_idx = r.index(starting_value)
+ d = collections.deque(r)
+ d.rotate(-start_idx)
+ return list(d)
+
+
class DakotaOptimizer(BaseMultiCriteriaOptimizer):
def run(self):
- print("Running dakota optimizer")
- for initial_value in range(10):
+ parameters = self.model.parameters
+
+ values = []
+ for p in parameters:
+ values.append(
+ rotated_range(p.lower_bound,
+ p.upper_bound,
+ p.initial_value)
+ )
+
+ value_iterator = itertools.product(*values)
+
+ for value in value_iterator:
ps = subprocess.Popen(
[sys.argv[0],
"--evaluate",
@@ -16,5 +36,7 @@ class DakotaOptimizer(BaseMultiCriteriaOptimizer):
stdout=subprocess.PIPE,
stdin=subprocess.PIPE)
- out = ps.communicate("{}".format(initial_value).encode("utf-8"))
- print("{}: {}".format(initial_value, out[0].decode("utf-8")))
+ out = ps.communicate(
+ " ".join([str(v) for v in value]).encode("utf-8"))
+ print("{}: {}".format(" ".join([str(v) for v in value]),
+ out[0].decode("utf-8")))
diff --git a/force_bdss/data_sources/data_source_parameters.py b/force_bdss/data_sources/data_source_parameters.py
index c45915dd1f056873e96e9e957753a90409c3d215..6e33d16c1ef6760b55a913903cc5b19444471862 100644
--- a/force_bdss/data_sources/data_source_parameters.py
+++ b/force_bdss/data_sources/data_source_parameters.py
@@ -2,5 +2,6 @@ from traits.api import HasStrictTraits, Array, List, String
class DataSourceParameters(HasStrictTraits):
+ value_names = List(String)
value_types = List(String)
values = Array(shape=(None,))
diff --git a/force_bdss/mco/base_mco_model.py b/force_bdss/mco/base_mco_model.py
index e7466353e63a32edc862d744b643752f6c2f88cb..acdebfbb0ce74b0315c2056889153cad21278bd5 100644
--- a/force_bdss/mco/base_mco_model.py
+++ b/force_bdss/mco/base_mco_model.py
@@ -1,5 +1,6 @@
-from traits.api import ABCHasStrictTraits, Instance
+from traits.api import ABCHasStrictTraits, Instance, List
+from ..workspecs.mco_parameters import MCOParameter
from .i_multi_criteria_optimizer_bundle import IMultiCriteriaOptimizerBundle
@@ -17,6 +18,8 @@ class BaseMCOModel(ABCHasStrictTraits):
visible=False,
transient=True)
+ parameters = List(MCOParameter)
+
def __init__(self, bundle, *args, **kwargs):
self.bundle = bundle
super(BaseMCOModel, self).__init__(*args, **kwargs)
diff --git a/force_bdss/tests/fixtures/test_csv.json b/force_bdss/tests/fixtures/test_csv.json
index 1c15b0f07f2bdeee497b41ea655e31fb64b19dff..f061c1092201a1cb409595a1d002ea3a85d57166 100644
--- a/force_bdss/tests/fixtures/test_csv.json
+++ b/force_bdss/tests/fixtures/test_csv.json
@@ -4,7 +4,6 @@
"multi_criteria_optimizer": {
"id": "force.bdss.bundles.enthought.dakota",
"model_data": {
- "value_types": ["DUMMY"]
}
},
"data_sources": [
diff --git a/force_bdss/workspecs/mco_parameters.py b/force_bdss/workspecs/mco_parameters.py
new file mode 100644
index 0000000000000000000000000000000000000000..5020117e19a8bc7d8d45d70fe2b60aa9ef77cdee
--- /dev/null
+++ b/force_bdss/workspecs/mco_parameters.py
@@ -0,0 +1,13 @@
+from traits.api import HasStrictTraits, String, Float
+
+
+class MCOParameter(HasStrictTraits):
+ pass
+
+
+class RangedMCOParameter(MCOParameter):
+ name = String()
+ value_type = String()
+ initial_value = Float()
+ upper_bound = Float()
+ lower_bound = Float()