Cherry-pick key general improvements from offshore-development for beta

ard/api/interface.py

@@ -1,5 +1,6 @@
 import importlib
 import openmdao.api as om
+from openmdao.drivers.doe_driver import DOEGenerator
 from ard.utils.io import load_yaml, replace_key_value
 from ard.cost.wisdem_wrap import (
     LandBOSSE_setup_latents,
@@ -111,6 +112,7 @@ def set_up_ard_model(input_dict: Union[str, dict], root_data_path: str = None):
 def set_up_system_recursive(
     input_dict: dict,
     system_name: str = "top_level",
+    work_dir: str = "ard_prob_out",
     parent_group=None,
     modeling_options: dict = None,
     analysis_options: dict = None,
@@ -129,7 +131,7 @@ def set_up_system_recursive(
     """
     # Initialize the top-level problem if no parent group is provided
     if parent_group is None:
-        prob = om.Problem()
+        prob = om.Problem(work_dir=work_dir)
         parent_group = prob.model
         # parent_group.name = "ard_model"
     else:
@@ -199,7 +201,30 @@ def set_up_system_recursive(
             # set up driver
             if "driver" in analysis_options:
                 Driver = getattr(om, analysis_options["driver"]["name"])
-                prob.driver = Driver()
+
+                # handle DOE drivers with special treatment
+                if Driver == om.DOEDriver:
+                    generator = None
+                    if "generator" in analysis_options["driver"]:
+                        if type(analysis_options["driver"]["generator"]) == dict:
+                            gen_dict = analysis_options["driver"]["generator"]
+                            generator = getattr(om, gen_dict["name"])(
+                                **gen_dict["args"]
+                            )
+                        elif isinstance(
+                            analysis_options["driver"]["generator"], DOEGenerator
+                        ):
+                            generator = analysis_options["driver"]["generator"]
+                        else:
+                            raise NotImplementedError(
+                                "Only dictionary-specified or OpenMDAO "
+                                "DOEGenerator generators have been implemented."
+                            )
+                    prob.driver = Driver(generator)
+                else:
+                    prob.driver = Driver()
+
+                # handle the options now
                 if "options" in analysis_options["driver"]:
                     for option, value_driver_option in analysis_options["driver"][
                         "options"

ard/cost/orbit_wrap.py

@@ -72,7 +72,15 @@ def generate_orbit_location_from_graph(
     for edge in edges_to_process:
         node_countmap[edge[0]] += 1
         node_countmap[edge[1]] += 1
-    if np.any(np.array(list(node_countmap.values())) > 2):
+    # if this has branching, handle it
+    if np.any(
+        (
+            np.array(list(node_countmap.values())) > 2
+        )  # multiple turbine appearances indicates a branch
+        & (
+            np.array(list(node_countmap.keys())) >= 0
+        )  # but substations do appear so "mask" them
+    ):
         if allow_branching_approximation:
             warnings.warn(
                 "The provided collection system design graph includes branching, "
@@ -369,6 +377,7 @@ def compute(self, inputs, outputs, discrete_inputs, discrete_outputs):
         if self._path_library:
             initialize_library(self._path_library)
 
+        # send it back to the superclass compute
         super().compute(
             inputs,
             outputs,

ard/layout/boundary.py

@@ -73,16 +73,16 @@ def setup(self):
 
         # set up inputs and outputs for mooring system
         self.add_input(
-            "x_turbines", jnp.zeros((self.N_turbines,)), units="km"
-        )  # x location of the mooring platform in km w.r.t. reference coordinates
+            "x_turbines", jnp.zeros((self.N_turbines,)), units="m"
+        )  # x location of the mooring platform in m w.r.t. reference coordinates
         self.add_input(
-            "y_turbines", jnp.zeros((self.N_turbines,)), units="km"
-        )  # y location of the mooring platform in km w.r.t. reference coordinates
+            "y_turbines", jnp.zeros((self.N_turbines,)), units="m"
+        )  # y location of the mooring platform in m w.r.t. reference coordinates
 
         self.add_output(
             "boundary_distances",
             jnp.zeros(self.N_turbines),
-            units="km",
+            units="m",
         )
 
     def setup_partials(self):

ard/layout/fullfarm.py

@@ -19,9 +19,6 @@ class FullFarmLanduse(ard.layout.templates.LanduseTemplate):
     modeling_options : dict
         a modeling options dictionary (inherited from
         `templates.LanduseTemplate`)
-    N_turbines : int
-        the number of turbines that should be in the farm layout (inherited from
-        `templates.LanduseTemplate`)
 
     Inputs
     ------

ard/layout/templates.py

@@ -16,8 +16,6 @@ class LayoutTemplate(om.ExplicitComponent):
     -------
     modeling_options : dict
         a modeling options dictionary
-    N_turbines : int
-        the number of turbines that should be in the farm layout
 
     Inputs
     ------
@@ -104,8 +102,6 @@ class LanduseTemplate(om.ExplicitComponent):
     -------
     modeling_options : dict
         a modeling options dictionary
-    N_turbines : int
-        the number of turbines that should be in the farm layout
 
     Inputs
     ------

ard/viz/layout.py

@@ -94,8 +94,8 @@ def plot_layout(
     windIO_dict = input_dict["modeling_options"]["windIO_plant"]
 
     ax.fill(
-        [x * 1e3 for x in windIO_dict["site"]["boundaries"]["polygons"][0]["x"]],
-        [y * 1e3 for y in windIO_dict["site"]["boundaries"]["polygons"][0]["y"]],
+        windIO_dict["site"]["boundaries"]["polygons"][0]["x"],
+        windIO_dict["site"]["boundaries"]["polygons"][0]["y"],
         linestyle="--",
         alpha=0.5,
         fill=False,

test/system/ard/geometry/test_constraints.py

@@ -39,8 +39,8 @@ def setup_method(self):
                     "boundaries": {
                         "polygons": [
                             {
-                                "x": [-2.0, 2.0, 2.0, -2.0],
-                                "y": [-2.0, -2.0, 2.0, 2.0],
+                                "x": [-2000.0, 2000.0, 2000.0, -2000.0],
+                                "y": [-2000.0, -2000.0, 2000.0, 2000.0],
                             },
                         ],
                     },
@@ -99,7 +99,9 @@ def test_constraint_evaluation(self, subtests):
 
             # load validation data from pyrite file using ard.utils.io
             validation_data = {
-                "boundary_distances": self.prob.get_val("boundary_distances"),
+                "boundary_distances": self.prob.get_val(
+                    "boundary_distances", units="km"
+                ),
             }
             with subtests.test(f"boundary_violations pyrite validation at {spacing}D"):
                 ard.utils.test_utils.pyrite_validator(
@@ -135,9 +137,9 @@ def test_constraint_optimization(self, subtests):
 
         # after 10 iterations, should have near-zero boundary distances
         with subtests.test("boundary distances near zero"):
+            tolerance_spec = 1.0e-3
             assert np.all(
-                np.isclose(self.prob.get_val("boundary_distances"), 0.0)
-                | (self.prob.get_val("boundary_distances") < 0.0)
+                self.prob.get_val("boundary_distances", units="m") < tolerance_spec
             )
 
         # make sure the target spacing matches well

test/unit/ard/cost/test_wisdem_wrap.py

@@ -225,7 +225,7 @@ def test_baseline_farm(self, subtests):
         # Validate each key-value pair using subtests
         for key, value in test_data.items():
             with subtests.test(key=key):
-                assert np.isclose(value, pyrite_data[key], rtol=5e-3), (
+                assert np.allclose(value, pyrite_data[key], rtol=5e-3), (
                     f"Mismatch for {key}: " f"expected {pyrite_data[key]}, got {value}"
                 )
 

test/unit/ard/farm_aero/test_floris.py

@@ -282,7 +282,7 @@ def test_compute_pyrite(self, subtests):
         pyrite_data = ard.utils.test_utils.pyrite_validator(
             test_data,
             Path(__file__).parent / "test_floris_aep_pyrite.npz",
-            # rtol_val=5e-3, # check tol not needed when just loading data
+            # rtol_val=5e-3, # this parameter sets the relative tolerance for validation checks. Uncomment if needed.
             # rewrite=True,  # uncomment to write new pyrite file
             load_only=True,
         )