From 95b019e924279b14b3a01d93d64fa18dd632a822 Mon Sep 17 00:00:00 2001
From: jlnav <jnavarro@anl.gov>
Date: Thu, 12 Feb 2026 16:44:32 -0600
Subject: [PATCH 1/7] some fixes (?), experimenting with calling only suggest
 on LibensembleGenInterfacer's, plus refactoring the aposmm calling script
 into how I'd like it to look eventually.

---
 libensemble/history.py                        |  2 +-
 .../test_asktell_aposmm_nlopt.py              | 31 ++++++++++++-------
 libensemble/utils/runners.py                  |  4 +--
 pixi.lock                                     |  2 +-
 4 files changed, 23 insertions(+), 16 deletions(-)

diff --git a/libensemble/history.py b/libensemble/history.py
index 3d3b5bc6fd..0d036b0415 100644
--- a/libensemble/history.py
+++ b/libensemble/history.py
@@ -107,7 +107,7 @@ def __init__(
         self.last_ended = -1
 
     def _append_new_fields(self, H_f: npt.NDArray) -> None:
-        dtype_new = np.dtype(list(set(self.H.dtype.descr + H_f.dtype.descr)))
+        dtype_new = np.dtype(list(set(self.H.dtype.descr + np.lib.recfunctions.repack_fields(H_f).dtype.descr)))
         H_new = np.zeros(len(self.H), dtype=dtype_new)
         old_fields = self.H.dtype.names
         for field in old_fields:
diff --git a/libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py b/libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py
index 83e3bf6253..765d44c703 100644
--- a/libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py
+++ b/libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py
@@ -15,7 +15,6 @@
 # TESTSUITE_COMMS: local mpi tcp
 # TESTSUITE_NPROCS: 3
 
-import sys
 from math import gamma, pi, sqrt
 
 import numpy as np
@@ -26,7 +25,6 @@
 from libensemble.sim_funcs.executor_hworld import executor_hworld as sim_f_exec
 
 # Import libEnsemble items for this test
-from libensemble.sim_funcs.six_hump_camel import six_hump_camel as sim_f
 
 libensemble.gen_funcs.rc.aposmm_optimizers = "nlopt"
 from time import time
@@ -34,11 +32,25 @@
 from gest_api.vocs import VOCS
 
 from libensemble import Ensemble
-from libensemble.alloc_funcs.persistent_aposmm_alloc import persistent_aposmm_alloc as alloc_f
+from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.gen_classes import APOSMM
 from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, SimSpecs
 from libensemble.tests.regression_tests.support import six_hump_camel_minima as minima
 
+
+def six_hump_camel_func(x):
+    """
+    Definition of the six-hump camel
+    """
+    x1 = x["core"]
+    x2 = x["edge"]
+    term1 = (4 - 2.1 * x1**2 + (x1**4) / 3) * x1**2
+    term2 = x1 * x2
+    term3 = (-4 + 4 * x2**2) * x2**2
+
+    return {"energy": term1 + term2 + term3}
+
+
 # Main block is necessary only when using local comms with spawn start method (default on macOS and Windows).
 if __name__ == "__main__":
 
@@ -49,19 +61,16 @@
         if workflow.is_manager:
             start_time = time()
 
-        if workflow.nworkers < 2:
-            sys.exit("Cannot run with a persistent worker if only one worker -- aborting...")
-
         n = 2
         workflow.alloc_specs = AllocSpecs(alloc_f=alloc_f)
 
+        workflow.libE_specs.gen_on_manager = True
+
         vocs = VOCS(
             variables={"core": [-3, 3], "edge": [-2, 2], "core_on_cube": [-3, 3], "edge_on_cube": [-2, 2]},
             objectives={"energy": "MINIMIZE"},
         )
 
-        workflow.libE_specs.gen_on_manager = True
-
         aposmm = APOSMM(
             vocs,
             max_active_runs=workflow.nworkers,  # should this match nworkers always? practically?
@@ -74,17 +83,15 @@
             ftol_abs=1e-6,
         )
 
-        # SH TODO - dont want this stuff duplicated - pass with vocs instead
         workflow.gen_specs = GenSpecs(
-            persis_in=["x", "x_on_cube", "sim_id", "local_min", "local_pt", "f"],
             generator=aposmm,
+            vocs=vocs,
             batch_size=5,
             initial_batch_size=10,
-            user={"initial_sample_size": 100},
         )
 
         if run == 0:
-            workflow.sim_specs = SimSpecs(sim_f=sim_f, inputs=["x"], outputs=[("f", float)])
+            workflow.sim_specs = SimSpecs(simulator=six_hump_camel_func, vocs=vocs)
             workflow.exit_criteria = ExitCriteria(sim_max=2000)
         elif run == 1:
             workflow.persis_info["num_gens_started"] = 0
diff --git a/libensemble/utils/runners.py b/libensemble/utils/runners.py
index b0c78a7bc6..5fa6c9017a 100644
--- a/libensemble/utils/runners.py
+++ b/libensemble/utils/runners.py
@@ -191,12 +191,12 @@ def _start_generator_loop(self, tag, Work, H_in) -> npt.NDArray:
 class LibensembleGenThreadRunner(StandardGenRunner):
     def _get_initial_suggest(self, libE_info) -> npt.NDArray:
         """Get initial batch from generator based on generator type"""
-        return self.gen.suggest_numpy()  # libE really needs to receive the *entire* initial batch from a threaded gen
+        return self.gen.suggest()  # libE really needs to receive the *entire* initial batch from a threaded gen
 
     def _suggest_and_send(self):
         """Loop over generator's outbox contents, send to manager"""
         while not self.gen._running_gen_f.outbox.empty():  # recv/send any outstanding messages
-            points = self.gen.suggest_numpy()
+            points = self.gen.suggest()
             if callable(getattr(self.gen, "suggest_updates", None)):
                 updates = self.gen.suggest_updates()
             else:
diff --git a/pixi.lock b/pixi.lock
index b0c5eb203a..07f3d567dd 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c10357cee7d3813245c607ea39fde22da46119409451949c0780225515aa5afa
+oid sha256:92f8b98ae9e038ca9165e0c306116ca5144988ac1451e720c4d5c2d1af14cbd9
 size 1216383

From 35fa55ecb02b52bcf492c976fed22ea29501ff63 Mon Sep 17 00:00:00 2001
From: jlnav <jnavarro@anl.gov>
Date: Fri, 13 Feb 2026 16:07:09 -0600
Subject: [PATCH 2/7] various fixes, adjustments, new functions. unmap aposmm's
 output numpy array into the H constructed from VOCS, then do the reverse for
 the numpy array from H back into APOSMM. Also ensure that _id data becomes
 sim_id, and vice-versa

---
 libensemble/gen_classes/aposmm.py | 14 +++++-
 libensemble/utils/misc.py         | 77 ++++++++++++++++++++++++++++---
 libensemble/utils/runners.py      | 17 +++++--
 pixi.lock                         |  2 +-
 4 files changed, 96 insertions(+), 14 deletions(-)

diff --git a/libensemble/gen_classes/aposmm.py b/libensemble/gen_classes/aposmm.py
index 5c92d544d1..71c2fcb437 100644
--- a/libensemble/gen_classes/aposmm.py
+++ b/libensemble/gen_classes/aposmm.py
@@ -293,7 +293,13 @@ def __init__(
 
     def _slot_in_data(self, results):
         """Slot in libE_calc_in and trial data into corresponding array fields. *Initial sample only!!*"""
-        self._ingest_buf[self._n_buffd_results : self._n_buffd_results + len(results)] = results
+        for name in results.dtype.names:
+            if name == "_id":
+                self._ingest_buf["sim_id"][self._n_buffd_results : self._n_buffd_results + len(results)] = results[
+                    "_id"
+                ]
+            else:
+                self._ingest_buf[name][self._n_buffd_results : self._n_buffd_results + len(results)] = results[name]
 
     def _enough_initial_sample(self):
         return (
@@ -361,7 +367,11 @@ def ingest_numpy(self, results: npt.NDArray, tag: int = EVAL_GEN_TAG) -> None:
         # Initial sample buffering here:
 
         if self._n_buffd_results == 0:
-            self._ingest_buf = np.zeros(self.gen_specs["user"]["initial_sample_size"], dtype=results.dtype)
+            # Create a dtype that includes sim_id but excludes _id
+            descr = [d for d in results.dtype.descr if d[0] != "_id"]
+            if "sim_id" not in [d[0] for d in descr]:
+                descr.append(("sim_id", int))
+            self._ingest_buf = np.zeros(self.gen_specs["user"]["initial_sample_size"], dtype=descr)
 
         if not self._enough_initial_sample():
             self._slot_in_data(np.copy(results))
diff --git a/libensemble/utils/misc.py b/libensemble/utils/misc.py
index 19b67f37e3..a6a432f81a 100644
--- a/libensemble/utils/misc.py
+++ b/libensemble/utils/misc.py
@@ -74,9 +74,8 @@ def _get_new_dtype_fields(first: dict, mapping: dict = {}) -> list:
     fields_to_convert = list(  # combining all mapping lists
         chain.from_iterable(list(mapping.values()))
     )  # fields like ["beam_length", "beam_width"] that will become "x"
-    new_dtype_names = [i for i in new_dtype_names if i not in fields_to_convert] + list(
-        mapping.keys()
-    )  # array dtype needs "x". avoid fields from mapping values since we're converting those to "x"
+    new_dtype_names = [i for i in new_dtype_names if i not in fields_to_convert]
+    # array dtype needs "x". avoid fields from mapping values since we're converting those to "x"
     # We need to accommodate "_id" getting mapped to "sim_id", but if it's not present
     # in the input dictionary, then perhaps we're doing an initial sample.
     if "_id" not in first and "sim_id" in mapping:
@@ -139,9 +138,7 @@ def list_dicts_to_np(list_dicts: list, dtype: list = None, mapping: dict = {}) -
     new_dtype_names = _get_new_dtype_fields(first, mapping)
     combinable_names = _get_combinable_multidim_names(first, new_dtype_names)  # [['x0', 'x1'], ['z']]
 
-    if (
-        dtype is None
-    ):  # Default value gets set upon function instantiation (default is mutable).
+    if dtype is None:  # Default value gets set upon function instantiation (default is mutable).
         dtype = []
 
     # build dtype of non-mapped fields. appending onto empty dtype
@@ -219,6 +216,74 @@ def unmap_numpy_array(array: npt.NDArray, mapping: dict = {}) -> npt.NDArray:
     return unmapped_array
 
 
+def map_numpy_array(array: npt.NDArray, mapping: dict = {}) -> npt.NDArray:
+    """Convert numpy array with individual scalar fields to mapped fields.
+    Parameters
+    ----------
+    array : npt.NDArray
+        Input array with unmapped fields like x0, x1, x2
+    mapping : dict
+        Mapping from field names to variable names
+    Returns
+    -------
+    npt.NDArray
+        Array with mapped fields like x = [x0, x1, x2]
+    """
+    if not mapping or array is None:
+        return array
+
+    # Create new dtype with mapped fields
+    new_fields = []
+
+    # Track fields processed by mapping to avoid duplication
+    mapped_source_fields = set()
+    for key, val_list in mapping.items():
+        mapped_source_fields.update(val_list)
+
+    # First add mapped fields from the mapping definition
+    for mapped_name, val_list in mapping.items():
+        if not val_list:
+            continue
+        first_var = val_list[0]
+        # We assume all components have the same type, take from first
+        if first_var in array.dtype.names:
+            base_type = array.dtype[first_var]
+            size = len(val_list)
+            if size > 1:
+                new_fields.append((mapped_name, base_type, (size,)))
+            else:
+                new_fields.append((mapped_name, base_type))
+
+    # Then add any fields from the source array that were NOT part of a mapping
+    for field in array.dtype.names:
+        if field not in mapped_source_fields:
+            new_fields.append((field, array.dtype[field]))
+
+    # remove duplicates from new_fields
+    new_fields = list(dict.fromkeys(new_fields))
+
+    # Create the new array
+    mapped_array = np.zeros(len(array), dtype=new_fields)
+
+    # Fill the new array
+    for field in mapped_array.dtype.names:
+        if field in mapping:
+            # Mapped field: stack the source columns
+            val_list = mapping[field]
+            if len(val_list) == 1:
+                mapped_array[field] = array[val_list[0]]
+            else:
+                # Stack columns horizontally for each row
+                # We need to extract each column, then stack them along axis 1
+                cols = [array[val] for val in val_list]
+                mapped_array[field] = np.stack(cols, axis=1)
+        else:
+            # Direct copy
+            mapped_array[field] = array[field]
+
+    return mapped_array
+
+
 def np_to_list_dicts(array: npt.NDArray, mapping: dict = {}) -> List[dict]:
     """Convert numpy structured array to list of dicts"""
     if array is None:
diff --git a/libensemble/utils/runners.py b/libensemble/utils/runners.py
index 8e940cfa4b..d993866ee5 100644
--- a/libensemble/utils/runners.py
+++ b/libensemble/utils/runners.py
@@ -9,7 +9,7 @@
 from libensemble.generators import LibensembleGenerator, PersistentGenInterfacer
 from libensemble.message_numbers import EVAL_GEN_TAG, FINISHED_PERSISTENT_GEN_TAG, PERSIS_STOP, STOP_TAG
 from libensemble.tools.persistent_support import PersistentSupport
-from libensemble.utils.misc import list_dicts_to_np, np_to_list_dicts
+from libensemble.utils.misc import list_dicts_to_np, map_numpy_array, np_to_list_dicts, unmap_numpy_array
 
 logger = logging.getLogger(__name__)
 
@@ -197,12 +197,17 @@ def _convert_initial_ingest(self, x: npt.NDArray) -> list:
 class LibensembleGenThreadRunner(StandardGenRunner):
     def _get_initial_suggest(self, libE_info) -> npt.NDArray:
         """Get initial batch from generator based on generator type"""
-        return self.gen.suggest()  # libE really needs to receive the *entire* initial batch from a threaded gen
+        return unmap_numpy_array(
+            self.gen.suggest_numpy(), mapping=getattr(self.gen, "variables_mapping", {})
+        )  # libE really needs to receive the *entire* initial batch from a threaded gen
+
+    def _convert_initial_ingest(self, x: npt.NDArray) -> list:
+        self.gen.ingest_numpy(map_numpy_array(x, mapping=getattr(self.gen, "variables_mapping", {})))
 
     def _suggest_and_send(self):
         """Loop over generator's outbox contents, send to manager"""
         while not self.gen._running_gen_f.outbox.empty():  # recv/send any outstanding messages
-            points = self.gen.suggest()
+            points = unmap_numpy_array(self.gen.suggest_numpy(), mapping=getattr(self.gen, "variables_mapping", {}))
             if callable(getattr(self.gen, "suggest_updates", None)):
                 updates = self.gen.suggest_updates()
             else:
@@ -222,6 +227,8 @@ def _loop_over_gen(self, *args):
             while self.ps.comm.mail_flag():  # receive any new messages from Manager, give all to gen
                 tag, _, H_in = self.ps.recv()
                 if tag in [STOP_TAG, PERSIS_STOP]:
-                    self.gen.ingest_numpy(H_in, PERSIS_STOP)
+                    self.gen.ingest_numpy(
+                        map_numpy_array(H_in, mapping=getattr(self.gen, "variables_mapping", {})), PERSIS_STOP
+                    )
                     return self.gen._running_gen_f.result()
-                self.gen.ingest_numpy(H_in)
+                self.gen.ingest_numpy(map_numpy_array(H_in, mapping=getattr(self.gen, "variables_mapping", {})))
diff --git a/pixi.lock b/pixi.lock
index 07f3d567dd..44d37e46ef 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:92f8b98ae9e038ca9165e0c306116ca5144988ac1451e720c4d5c2d1af14cbd9
+oid sha256:432c0bdf87ed393d5f46ace44e8c0e3c37580ab096fbbc72398cd1e98559e0e1
 size 1216383

From dcf2ed9ca0b8c7a5050ce3309f489cb7ffa0e08a Mon Sep 17 00:00:00 2001
From: jlnav <jnavarro@anl.gov>
Date: Wed, 18 Feb 2026 15:46:28 -0600
Subject: [PATCH 3/7] history.py: - Hint towards easy bug where user may have
 intended to set sim_specs.simulator instead of sim_specs.sim_f

the regression test:
- use vocs for second test iteration

misc.py
- more reliably build the dtype out of mapping keys that are present in the input data

runners.py
- some cleanup
---
 libensemble/history.py                                 |  8 +++++++-
 .../regression_tests/test_asktell_aposmm_nlopt.py      |  5 +----
 libensemble/utils/misc.py                              | 10 ++++------
 libensemble/utils/runners.py                           |  6 ++----
 pixi.lock                                              |  4 ++--
 5 files changed, 16 insertions(+), 17 deletions(-)

diff --git a/libensemble/history.py b/libensemble/history.py
index 3f35779cb4..045569edb6 100644
--- a/libensemble/history.py
+++ b/libensemble/history.py
@@ -123,7 +123,13 @@ def update_history_f(self, D: dict, kill_canceled_sims: bool = False) -> None:
 
         new_inds = D["libE_info"]["H_rows"]  # The list of rows (as a numpy array)
         returned_H = D["calc_out"]
-        fields = returned_H.dtype.names if returned_H is not None else []
+        try:
+            fields = returned_H.dtype.names if returned_H is not None else []
+        except AttributeError:
+            raise AttributeError(
+                "Manager received an unexpected datatype from a simulation."
+                + "Perhaps you meant to set `SimSpecs.simulator` instead of `SimSpecs.sim_f`?"
+            )
 
         if returned_H is not None and any([field not in self.H.dtype.names for field in returned_H.dtype.names]):
             self._append_new_fields(returned_H)
diff --git a/libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py b/libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py
index 765d44c703..42cd8bf4eb 100644
--- a/libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py
+++ b/libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py
@@ -22,7 +22,6 @@
 import libensemble.gen_funcs
 from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.sim_funcs import six_hump_camel
-from libensemble.sim_funcs.executor_hworld import executor_hworld as sim_f_exec
 
 # Import libEnsemble items for this test
 
@@ -98,9 +97,7 @@ def six_hump_camel_func(x):
             sim_app2 = six_hump_camel.__file__
             exctr = MPIExecutor()
             exctr.register_app(full_path=sim_app2, app_name="six_hump_camel", calc_type="sim")  # Named app
-            workflow.sim_specs = SimSpecs(
-                sim_f=sim_f_exec, inputs=["x"], outputs=[("f", float), ("cstat", int)], user={"cores": 1}
-            )
+            workflow.sim_specs = SimSpecs(simulator=six_hump_camel_func, vocs=vocs)
             workflow.exit_criteria = ExitCriteria(sim_max=200)
 
         workflow.add_random_streams()
diff --git a/libensemble/utils/misc.py b/libensemble/utils/misc.py
index a6a432f81a..12cd85a86c 100644
--- a/libensemble/utils/misc.py
+++ b/libensemble/utils/misc.py
@@ -75,11 +75,6 @@ def _get_new_dtype_fields(first: dict, mapping: dict = {}) -> list:
         chain.from_iterable(list(mapping.values()))
     )  # fields like ["beam_length", "beam_width"] that will become "x"
     new_dtype_names = [i for i in new_dtype_names if i not in fields_to_convert]
-    # array dtype needs "x". avoid fields from mapping values since we're converting those to "x"
-    # We need to accommodate "_id" getting mapped to "sim_id", but if it's not present
-    # in the input dictionary, then perhaps we're doing an initial sample.
-    if "_id" not in first and "sim_id" in mapping:
-        new_dtype_names.remove("sim_id")
     return new_dtype_names
 
 
@@ -149,9 +144,12 @@ def list_dicts_to_np(list_dicts: list, dtype: list = None, mapping: dict = {}) -
     if len(mapping):
         existing_names = [f[0] for f in dtype]
         for name in mapping:
-            if name not in existing_names:
+            # If the field is already in the dtype, skip it. *And* the field is present in the input data
+            if name not in existing_names and all(src in first for src in mapping[name]):
                 size = len(mapping[name])
                 dtype.append(_decide_dtype(name, 0.0, size))  # default to float
+                new_dtype_names.append(name)
+                combinable_names.append(mapping[name])
 
     out = np.zeros(len(list_dicts), dtype=dtype)
 
diff --git a/libensemble/utils/runners.py b/libensemble/utils/runners.py
index d993866ee5..abff32ac35 100644
--- a/libensemble/utils/runners.py
+++ b/libensemble/utils/runners.py
@@ -195,11 +195,9 @@ def _convert_initial_ingest(self, x: npt.NDArray) -> list:
 
 
 class LibensembleGenThreadRunner(StandardGenRunner):
-    def _get_initial_suggest(self, libE_info) -> npt.NDArray:
+    def _get_initial_suggest(self, _) -> npt.NDArray:
         """Get initial batch from generator based on generator type"""
-        return unmap_numpy_array(
-            self.gen.suggest_numpy(), mapping=getattr(self.gen, "variables_mapping", {})
-        )  # libE really needs to receive the *entire* initial batch from a threaded gen
+        return unmap_numpy_array(self.gen.suggest_numpy(), mapping=getattr(self.gen, "variables_mapping", {}))
 
     def _convert_initial_ingest(self, x: npt.NDArray) -> list:
         self.gen.ingest_numpy(map_numpy_array(x, mapping=getattr(self.gen, "variables_mapping", {})))
diff --git a/pixi.lock b/pixi.lock
index 44d37e46ef..9445b272f8 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:432c0bdf87ed393d5f46ace44e8c0e3c37580ab096fbbc72398cd1e98559e0e1
-size 1216383
+oid sha256:fffa4c0d8ca1c65988df4969fd392f632f6d6505d05cb3935b1fbbc4d23935a1
+size 1216617

From f47c6852b8faa25c70c91ad979d9c46281957e8a Mon Sep 17 00:00:00 2001
From: jlnav <jnavarro@anl.gov>
Date: Thu, 19 Feb 2026 07:49:48 -0600
Subject: [PATCH 4/7] exclude optimas ax tests on macos

---
 libensemble/tests/regression_tests/test_optimas_ax_mf.py   | 7 ++-----
 .../tests/regression_tests/test_optimas_ax_multitask.py    | 4 ++--
 libensemble/tests/regression_tests/test_optimas_ax_sf.py   | 4 ++--
 pixi.lock                                                  | 2 +-
 4 files changed, 7 insertions(+), 10 deletions(-)

diff --git a/libensemble/tests/regression_tests/test_optimas_ax_mf.py b/libensemble/tests/regression_tests/test_optimas_ax_mf.py
index b6f43b3edf..758aa1fc2c 100644
--- a/libensemble/tests/regression_tests/test_optimas_ax_mf.py
+++ b/libensemble/tests/regression_tests/test_optimas_ax_mf.py
@@ -16,9 +16,9 @@
 # TESTSUITE_COMMS: mpi local
 # TESTSUITE_NPROCS: 4
 # TESTSUITE_EXTRA: true
+# TESTSUITE_OS_SKIP: OSX
 
 import numpy as np
-
 from gest_api.vocs import VOCS
 from optimas.generators import AxMultiFidelityGenerator
 
@@ -32,10 +32,7 @@ def eval_func_mf(input_params):
     x0 = input_params["x0"]
     x1 = input_params["x1"]
     resolution = input_params["res"]
-    result = -(
-        (x0 + 10 * np.cos(x0 + 0.1 * resolution))
-        * (x1 + 5 * np.cos(x1 - 0.2 * resolution))
-    )
+    result = -((x0 + 10 * np.cos(x0 + 0.1 * resolution)) * (x1 + 5 * np.cos(x1 - 0.2 * resolution)))
     return {"f": result}
 
 
diff --git a/libensemble/tests/regression_tests/test_optimas_ax_multitask.py b/libensemble/tests/regression_tests/test_optimas_ax_multitask.py
index 04a2b5430f..9e97dcad70 100644
--- a/libensemble/tests/regression_tests/test_optimas_ax_multitask.py
+++ b/libensemble/tests/regression_tests/test_optimas_ax_multitask.py
@@ -23,10 +23,10 @@
 # TESTSUITE_NPROCS: 4
 # TESTSUITE_EXTRA: true
 # TESTSUITE_EXCLUDE: true
+# TESTSUITE_OS_SKIP: OSX
 
 import numpy as np
 from gest_api.vocs import VOCS
-
 from optimas.core import Task
 from optimas.generators import AxMultitaskGenerator
 
@@ -37,7 +37,7 @@
 
 def eval_func_multitask(input_params):
     """Evaluation function for task1 or task2 in multitask test"""
-    print(f'input_params: {input_params}')
+    print(f"input_params: {input_params}")
     x0 = input_params["x0"]
     x1 = input_params["x1"]
     trial_type = input_params["trial_type"]
diff --git a/libensemble/tests/regression_tests/test_optimas_ax_sf.py b/libensemble/tests/regression_tests/test_optimas_ax_sf.py
index ba0b66c297..e4ee9e8a79 100644
--- a/libensemble/tests/regression_tests/test_optimas_ax_sf.py
+++ b/libensemble/tests/regression_tests/test_optimas_ax_sf.py
@@ -16,9 +16,9 @@
 # TESTSUITE_COMMS: mpi local
 # TESTSUITE_NPROCS: 4
 # TESTSUITE_EXTRA: true
+# TESTSUITE_OS_SKIP: OSX
 
 import numpy as np
-
 from gest_api.vocs import VOCS
 from optimas.generators import AxSingleFidelityGenerator
 
@@ -28,7 +28,7 @@
 
 
 def eval_func_sf(input_params):
-    """Evaluation function for single-fidelity test. """
+    """Evaluation function for single-fidelity test."""
     x0 = input_params["x0"]
     x1 = input_params["x1"]
     result = -(x0 + 10 * np.cos(x0)) * (x1 + 5 * np.cos(x1))
diff --git a/pixi.lock b/pixi.lock
index 9445b272f8..79394ef448 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:fffa4c0d8ca1c65988df4969fd392f632f6d6505d05cb3935b1fbbc4d23935a1
+oid sha256:567e81eabdaf24db518cc9f93fa60e37d95dc39bc6a9b69db9eed1e8ec193997
 size 1216617

From 0e7924a69d5d022e4726f410f3913b7e2e313779 Mon Sep 17 00:00:00 2001
From: jlnav <jnavarro@anl.gov>
Date: Thu, 19 Feb 2026 08:39:52 -0600
Subject: [PATCH 5/7] remove optimas-ax tests from newer python extended tests

---
 .github/workflows/extra.yml | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/.github/workflows/extra.yml b/.github/workflows/extra.yml
index 99e1581ac7..de7fd86dcb 100644
--- a/.github/workflows/extra.yml
+++ b/.github/workflows/extra.yml
@@ -84,6 +84,8 @@ jobs:
             rm ./libensemble/tests/regression_tests/test_gpCAM.py # needs gpcam, which doesn't build on 3.13
             rm ./libensemble/tests/regression_tests/test_asktell_gpCAM.py # needs gpcam, which doesn't build on 3.13
             rm ./libensemble/tests/regression_tests/test_persistent_gp_multitask_ax.py # needs ax-platform, which doesn't yet support 3.14
+            rm ./libensemble/tests/regression_tests/test_optimas_ax_mf.py # needs ax-platform, which doesn't yet support 3.14
+            rm ./libensemble/tests/regression_tests/test_optimas_ax_sf.py # needs ax-platform, which doesn't yet support 3.14
 
         - name: Start Redis
           if: matrix.os == 'ubuntu-latest'

From 37bc5d85144b38f7f7a0debb1c2bba50f4d80345 Mon Sep 17 00:00:00 2001
From: jlnav <jnavarro@anl.gov>
Date: Fri, 20 Feb 2026 12:59:28 -0600
Subject: [PATCH 6/7] coverage fixes, plus adjustments for warning/handling
 when both the wrong simulator/sim_f parameter is set in sim_specs, and
 accordingly the wrong data is returned. test for this

---
 libensemble/history.py                        | 10 +----
 libensemble/manager.py                        | 14 ++++++-
 .../test_asktell_aposmm_nlopt.py              | 17 +++++++--
 libensemble/utils/misc.py                     | 37 +++++++------------
 libensemble/utils/runners.py                  | 15 +++++++-
 5 files changed, 56 insertions(+), 37 deletions(-)

diff --git a/libensemble/history.py b/libensemble/history.py
index 045569edb6..aa16a4d771 100644
--- a/libensemble/history.py
+++ b/libensemble/history.py
@@ -121,16 +121,10 @@ def update_history_f(self, D: dict, kill_canceled_sims: bool = False) -> None:
         Updates the history after points have been evaluated
         """
 
-        new_inds = D["libE_info"]["H_rows"]  # The list of rows (as a numpy array)
+        new_inds = D["libE_info"]["H_rows"]
         returned_H = D["calc_out"]
-        try:
-            fields = returned_H.dtype.names if returned_H is not None else []
-        except AttributeError:
-            raise AttributeError(
-                "Manager received an unexpected datatype from a simulation."
-                + "Perhaps you meant to set `SimSpecs.simulator` instead of `SimSpecs.sim_f`?"
-            )
 
+        fields = returned_H.dtype.names if returned_H is not None else []
         if returned_H is not None and any([field not in self.H.dtype.names for field in returned_H.dtype.names]):
             self._append_new_fields(returned_H)
 
diff --git a/libensemble/manager.py b/libensemble/manager.py
index 22ae8b5d3e..5c084d3211 100644
--- a/libensemble/manager.py
+++ b/libensemble/manager.py
@@ -484,7 +484,7 @@ def _update_state_on_worker_msg(self, persis_info: dict, D_recv: dict, w: int) -
         calc_status = D_recv["calc_status"]
 
         keep_state = D_recv["libE_info"].get("keep_state", False)
-        if w not in self.persis_pending and not self.W[w]["active_recv"] and not keep_state:
+        if (w not in self.persis_pending and not self.W[w]["active_recv"] and not keep_state) or self.WorkerExc:
             self.W[w]["active"] = 0
 
         if calc_status in [FINISHED_PERSISTENT_SIM_TAG, FINISHED_PERSISTENT_GEN_TAG]:
@@ -507,7 +507,17 @@ def _update_state_on_worker_msg(self, persis_info: dict, D_recv: dict, w: int) -
             self._freeup_resources(w)
         else:
             if calc_type == EVAL_SIM_TAG:
-                self.hist.update_history_f(D_recv, self.kill_canceled_sims)
+                try:
+                    self.hist.update_history_f(D_recv, self.kill_canceled_sims)
+                except AttributeError as e:
+                    if self.WorkerExc:
+                        logger.debug(f"Manager ignoring secondary data error from worker {w} during shutdown: {e}")
+                    else:
+                        self.WorkerExc = True
+                        self._kill_workers()
+                        raise WorkerException(
+                            f"Error in data from worker {w}", str(e), traceback.format_exc()
+                        ) from None
             if calc_type == EVAL_GEN_TAG:
                 D = D_recv["calc_out"]
                 self._ensure_sim_id_in_persis_in(D)
diff --git a/libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py b/libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py
index 42cd8bf4eb..4b03d7678b 100644
--- a/libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py
+++ b/libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py
@@ -33,6 +33,7 @@
 from libensemble import Ensemble
 from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.gen_classes import APOSMM
+from libensemble.manager import LoggedException
 from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, SimSpecs
 from libensemble.tests.regression_tests.support import six_hump_camel_minima as minima
 
@@ -53,7 +54,7 @@ def six_hump_camel_func(x):
 # Main block is necessary only when using local comms with spawn start method (default on macOS and Windows).
 if __name__ == "__main__":
 
-    for run in range(2):
+    for run in range(3):
 
         workflow = Ensemble(parse_args=True)
 
@@ -99,13 +100,23 @@ def six_hump_camel_func(x):
             exctr.register_app(full_path=sim_app2, app_name="six_hump_camel", calc_type="sim")  # Named app
             workflow.sim_specs = SimSpecs(simulator=six_hump_camel_func, vocs=vocs)
             workflow.exit_criteria = ExitCriteria(sim_max=200)
+        elif run == 2:
+            workflow.persis_info["num_gens_started"] = 0
+            workflow.sim_specs = SimSpecs(
+                sim_f=six_hump_camel_func, vocs=vocs
+            )  # wrong parameter, but check we get error message
+            workflow.exit_criteria = ExitCriteria(sim_max=200)
 
         workflow.add_random_streams()
 
-        H, _, _ = workflow.run()
+        try:
+            H, _, _ = workflow.run()
+        except Exception as e:
+            assert isinstance(e, LoggedException)
+            aposmm.finalize()
+            continue
 
         # Perform the run
-
         if workflow.is_manager and run == 0:
             print("[Manager]:", H[np.where(H["local_min"])]["x"])
             print("[Manager]: Time taken =", time() - start_time, flush=True)
diff --git a/libensemble/utils/misc.py b/libensemble/utils/misc.py
index 12cd85a86c..83f2388800 100644
--- a/libensemble/utils/misc.py
+++ b/libensemble/utils/misc.py
@@ -240,17 +240,14 @@ def map_numpy_array(array: npt.NDArray, mapping: dict = {}) -> npt.NDArray:
 
     # First add mapped fields from the mapping definition
     for mapped_name, val_list in mapping.items():
-        if not val_list:
-            continue
         first_var = val_list[0]
         # We assume all components have the same type, take from first
-        if first_var in array.dtype.names:
-            base_type = array.dtype[first_var]
-            size = len(val_list)
-            if size > 1:
-                new_fields.append((mapped_name, base_type, (size,)))
-            else:
-                new_fields.append((mapped_name, base_type))
+        base_type = array.dtype[first_var]
+        size = len(val_list)
+        if size > 1:
+            new_fields.append((mapped_name, base_type, (size,)))
+        else:
+            new_fields.append((mapped_name, base_type))
 
     # Then add any fields from the source array that were NOT part of a mapping
     for field in array.dtype.names:
@@ -265,27 +262,21 @@ def map_numpy_array(array: npt.NDArray, mapping: dict = {}) -> npt.NDArray:
 
     # Fill the new array
     for field in mapped_array.dtype.names:
-        if field in mapping:
-            # Mapped field: stack the source columns
-            val_list = mapping[field]
-            if len(val_list) == 1:
-                mapped_array[field] = array[val_list[0]]
-            else:
-                # Stack columns horizontally for each row
-                # We need to extract each column, then stack them along axis 1
-                cols = [array[val] for val in val_list]
-                mapped_array[field] = np.stack(cols, axis=1)
+        # Mapped field: stack the source columns
+        val_list = mapping[field]
+        if len(val_list) == 1:
+            mapped_array[field] = array[val_list[0]]
         else:
-            # Direct copy
-            mapped_array[field] = array[field]
+            # Stack columns horizontally for each row
+            # We need to extract each column, then stack them along axis 1
+            cols = [array[val] for val in val_list]
+            mapped_array[field] = np.stack(cols, axis=1)
 
     return mapped_array
 
 
 def np_to_list_dicts(array: npt.NDArray, mapping: dict = {}) -> List[dict]:
     """Convert numpy structured array to list of dicts"""
-    if array is None:
-        return None
     out = []
 
     for row in array:
diff --git a/libensemble/utils/runners.py b/libensemble/utils/runners.py
index abff32ac35..ee0ebd65cf 100644
--- a/libensemble/utils/runners.py
+++ b/libensemble/utils/runners.py
@@ -51,7 +51,20 @@ def shutdown(self) -> None:
     def run(self, calc_in: npt.NDArray, Work: dict) -> (npt.NDArray, dict, int | None):
         if Work["persis_info"] is None:
             Work["persis_info"] = {}
-        return self._result(calc_in, Work["persis_info"], Work["libE_info"])
+        out = self._result(calc_in, Work["persis_info"], Work["libE_info"])
+
+        # Help users who mixed up sim_f and simulator parameters
+        if isinstance(out, (tuple, list)):
+            calc_out = out[0]
+        else:
+            calc_out = out
+
+        if isinstance(calc_out, dict):
+            raise AttributeError(
+                "Manager received a dictionary from a simulation. "
+                "Perhaps you meant to set `SimSpecs.simulator` instead of `SimSpecs.sim_f`?"
+            )
+        return out
 
 
 class GlobusComputeRunner(Runner):

From ebce988dc050d7359903d40464a8be44d4e316b9 Mon Sep 17 00:00:00 2001
From: jlnav <jnavarro@anl.gov>
Date: Fri, 20 Feb 2026 14:04:41 -0600
Subject: [PATCH 7/7] adjusts for MPI case

---
 .../tests/regression_tests/test_asktell_aposmm_nlopt.py     | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py b/libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py
index 4b03d7678b..cbcd4c22e0 100644
--- a/libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py
+++ b/libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py
@@ -106,6 +106,8 @@ def six_hump_camel_func(x):
                 sim_f=six_hump_camel_func, vocs=vocs
             )  # wrong parameter, but check we get error message
             workflow.exit_criteria = ExitCriteria(sim_max=200)
+            return_flag = False
+            workflow.libE_specs.abort_on_exception = False
 
         workflow.add_random_streams()
 
@@ -114,8 +116,12 @@ def six_hump_camel_func(x):
         except Exception as e:
             assert isinstance(e, LoggedException)
             aposmm.finalize()
+            return_flag = False
             continue
 
+        if run == 2 and workflow.is_manager:
+            assert return_flag
+
         # Perform the run
         if workflow.is_manager and run == 0:
             print("[Manager]:", H[np.where(H["local_min"])]["x"])