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Commit 81fb0153 authored by Stefano Borini's avatar Stefano Borini Committed by GitHub
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Merge pull request #8 from force-h2020/remove-dummy-plugins

Removed dummy plugins that are no longer relevant
parents a6bee42b bce3e7e3
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with 1 addition and 181 deletions
{
"multi_criteria_optimizer": {
"name": "basic",
"name": "dakota",
"model_data": {}
},
"data_sources": [
......
{
"multi_criteria_optimizer": {
"name": "basic",
"model_data": {}
},
"data_sources": [
{
"name": "viscosity",
"model_data": {}
},
{
"name": "price",
"model_data": {}
}
]
}
from traits.api import provides, HasStrictTraits, String
from force_bdss.data_sources.i_data_source_bundle import IDataSourceBundle
from .basic_model import BasicModel
from .basic_data_source import BasicDataSource
@provides(IDataSourceBundle)
class BasicBundle(HasStrictTraits):
name = String("basic")
def create_model(self, model_data):
return BasicModel.from_json(model_data)
def create_ui(self):
pass
def create_data_source(self, application, model):
return BasicDataSource(self, application, model)
from force_bdss.data_sources.base_data_source import BaseDataSource
class BasicDataSource(BaseDataSource):
def run(self):
print("Computing basic key performance indicator")
from traits.has_traits import HasStrictTraits
class BasicModel(HasStrictTraits):
@classmethod
def from_json(cls, model_data):
return cls()
from envisage.plugin import Plugin
from traits.api import List
from force_bdss.data_sources.i_data_source_bundle import IDataSourceBundle
from .basic.basic_bundle import BasicBundle
from .price.price_bundle import PriceBundle
from .viscosity.viscosity_bundle import ViscosityBundle
class DataSourcesPlugin(Plugin):
id = "force_bdss.data_sources_plugin"
data_sources = List(
IDataSourceBundle,
contributes_to='force.bdss.data_sources.bundles'
)
def _data_sources_default(self):
return [BasicBundle(),
ViscosityBundle(),
PriceBundle()]
from traits.api import provides, HasStrictTraits
from traits.trait_types import String
from force_bdss.data_sources.i_data_source_bundle import IDataSourceBundle
from .price_model import PriceModel
from .price_data_source import PriceDataSource
@provides(IDataSourceBundle)
class PriceBundle(HasStrictTraits):
name = String("price")
def create_model(self, model_data):
return PriceModel.from_json(model_data)
def create_ui(self):
pass
def create_data_source(self, application, model):
return PriceDataSource(self, application, model)
from force_bdss.data_sources.base_data_source import BaseDataSource
class PriceDataSource(BaseDataSource):
def run(self):
print("Computing price")
from traits.has_traits import HasStrictTraits
class PriceModel(HasStrictTraits):
@classmethod
def from_json(cls, model_data):
return cls()
from traits.api import provides, HasStrictTraits, String
from force_bdss.data_sources.i_data_source_bundle import IDataSourceBundle
from .viscosity_data_source import ViscosityDataSource
from .viscosity_model import ViscosityModel
@provides(IDataSourceBundle)
class ViscosityBundle(HasStrictTraits):
name = String("viscosity")
def create_model(self, model_data):
return ViscosityModel.from_json(model_data)
def create_ui(self):
pass
def create_data_source(self, application, model):
return ViscosityDataSource(self, application, model)
from force_bdss.data_sources.base_data_source import BaseDataSource
class ViscosityDataSource(BaseDataSource):
def run(self):
print("Computing viscosity")
from traits.api import HasStrictTraits
class ViscosityModel(HasStrictTraits):
@classmethod
def from_json(cls, model_data):
return cls()
from traits.has_traits import HasStrictTraits, provides
from traits.trait_types import String
from force_bdss.mco.i_multi_criteria_optimizer_bundle import (
IMultiCriteriaOptimizerBundle)
from .basic_model import BasicModel
from .basic_optimizer import BasicOptimizer
@provides(IMultiCriteriaOptimizerBundle)
class BasicBundle(HasStrictTraits):
name = String("basic")
def create_model(self, model_data):
return BasicModel.from_json(model_data)
def create_ui(self):
pass
def create_optimizer(self, application, model):
return BasicOptimizer(self, application, model)
from traits.has_traits import HasStrictTraits
class BasicModel(HasStrictTraits):
@classmethod
def from_json(cls, model_data):
return cls()
import subprocess
import sys
from force_bdss.mco.base_multi_criteria_optimizer import (
BaseMultiCriteriaOptimizer
)
class BasicOptimizer(BaseMultiCriteriaOptimizer):
def run(self):
print("Running Basic optimizer")
subprocess.check_call([sys.argv[0], "--evaluate",
self.application.workflow_filepath])
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