'operator': 'lte',
'bound': 35
}]
# Blocks
import_csv = wf.Import(type_='csv')
instantiate_pareto = wf.InstanciateModel(model_class=ParetoSettings,
name='Pareto Settings')
instantiate_catalog = wf.InstanciateModel(model_class=Catalog,
name='Cars Instantiation')
filter_method = wf.ModelMethod(model_class=Catalog,
method_name='filter_',
name='Filters')
filtered_catalog = wf.InstanciateModel(model_class=Catalog,
name='Filtered Catalog')
display = wf.Display(order=0, name="Display")
# display = wf.MultiPlot(choice_args, 1, name='Display')
filtered = wf.Display(order=1, name="Filtered")
# filtered = wf.MultiPlot(choice_args, 1, name='Filtered')
# objectives_method = wf.ModelMethod(model_class=Catalog,
# method_name='find_best_objective',
# name="Find best objectives")
# objectives_attributes = wf.ModelAttribute(attribute_name='objectives',
# name='Objectives')
blocks = [
import_csv, instantiate_pareto, instantiate_catalog, filter_method,
filtered_catalog, display, filtered
]
# , objectives_method, objectives_attributes]
# from dessia_api_client import Client
import numpy as np
from dessia_common.typings import MethodType
block_generator = wf.InstanciateModel(objects.GearBoxGenerator,
name='Gearbox Generator')
block_generate = wf.ModelMethod(MethodType(class_=objects.GearBoxGenerator,
name='generate'),
name='Generate')
block_efficiencymap = wf.InstanciateModel(objects.EfficiencyMap,
name='Efficiency Map')
block_engine = wf.InstanciateModel(objects.Engine, name='Engine')
block_gearbox = wf.InstanciateModel(objects.GearBox, name='Gearbox')
block_cluster = wf.InstanciateModel(objects.Clustering, name='Clustering')
display = wf.Display(name='Display')
block_workflow = [
block_generator, block_generate, block_gearbox, block_engine,
block_efficiencymap, block_cluster, display
]
pipe_workflow = [
wf.Pipe(block_generator.outputs[0], block_generate.inputs[0]),
wf.Pipe(block_gearbox.outputs[0], block_generator.inputs[0]),
wf.Pipe(block_engine.outputs[0], block_gearbox.inputs[0]),
wf.Pipe(block_efficiencymap.outputs[0], block_engine.inputs[0]),
wf.Pipe(block_generate.outputs[0], block_cluster.inputs[0]),
wf.Pipe(block_cluster.outputs[0], display.inputs[0])
]
workflow = wf.Workflow(block_workflow, pipe_workflow,
filtered_catalog1 = wf.InstanciateModel(model_class=Catalog,
name='Filtered Catalog 1')
filter_max = [{'attribute': 'MPG', 'operator': 'gte', 'bound': 30}]
catalog2 = wf.InstanciateModel(model_class=Catalog, name='Car 2')
filter2 = wf.ModelMethod(model_class=Catalog,
method_name='filter_',
name='Filter 2')
filtered_catalog2 = wf.InstanciateModel(model_class=Catalog,
name='Filtered Catalog 2')
catalogs = wf.Sequence(number_arguments=2, name='Catalogs')
concatenate = wf.ClassMethod(class_=Catalog,
method_name='concatenate',
name='Concatenate')
display = wf.Display(order=0)
array_attribute = wf.ModelAttribute(attribute_name='array', name='Array')
blocks = [
import_csv, instantiate_pareto, catalog1, filter1, filtered_catalog1,
catalog2, filter2, filtered_catalog2, catalogs, concatenate, display,
array_attribute
]
# Pipes
pipes = [
wf.Pipe(import_csv.outputs[0], catalog1.inputs[0]),
wf.Pipe(import_csv.outputs[1], catalog1.inputs[1]),
wf.Pipe(instantiate_pareto.outputs[0], catalog1.inputs[2]),
wf.Pipe(import_csv.outputs[0], catalog2.inputs[0]),