test fixes

Author: jlnav

libensemble/alloc_funcs/persistent_aposmm_alloc.py

@@ -21,6 +21,8 @@ def persistent_aposmm_alloc(W, H, sim_specs, gen_specs, alloc_specs, persis_info
     if libE_info["sim_max_given"] or not libE_info["any_idle_workers"]:
         return {}, persis_info
 
+    if not persis_info:
+        persis_info = {i: {} for i in range(len(W))}
     user = {**gen_specs, **alloc_specs.get("user", {})}
     init_sample_size = user["initial_batch_size"]
     manage_resources = libE_info["use_resource_sets"]
@@ -70,7 +72,7 @@ def persistent_aposmm_alloc(W, H, sim_specs, gen_specs, alloc_specs, persis_info
     if persis_info.get("gen_started") is None:
         for wid in support.avail_worker_ids(persistent=False, gen_workers=True):
             # Finally, call a persistent generator as there is nothing else to do.
-            persis_info.get(wid)["nworkers"] = len(W)
+            persis_info[wid]["nworkers"] = len(W)
             try:
                 Work[wid] = support.gen_work(
                     wid, gen_specs.get("in", []), range(len(H)), persis_info.get(wid), persistent=True

libensemble/tests/functionality_tests/test_runlines_adaptive_workers.py

@@ -63,9 +63,6 @@
 
     alloc_specs = {
         "alloc_f": give_sim_work_first,
-        "user": {
-            "batch_mode": False,
-        },
     }
 
     comms = libE_specs["comms"]
@@ -85,7 +82,7 @@
     exit_criteria = {"sim_max": 40, "wallclock_max": 300}
 
     # Perform the run
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, alloc_specs=libE_specs, libE_specs=libE_specs)
+    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, alloc_specs=alloc_specs, libE_specs=libE_specs)
 
     if is_manager:
         assert flag == 0

libensemble/tests/functionality_tests/test_uniform_sampling_cancel.py

@@ -30,7 +30,7 @@
 from libensemble.libE import libE
 from libensemble.sim_funcs.six_hump_camel import six_hump_camel
 from libensemble.tests.regression_tests.support import six_hump_camel_minima as minima
-from libensemble.tools import parse_args
+from libensemble.tools import get_rng, parse_args
 
 
 def create_H0(persis_info, gen_specs, sim_max):
@@ -42,7 +42,8 @@ def create_H0(persis_info, gen_specs, sim_max):
     b = sim_max
 
     H0 = np.zeros(b, dtype=[("x", float, 2), ("sim_id", int), ("sim_started", bool), ("cancel_requested", bool)])
-    H0["x"] = persis_info[0]["rand_stream"].uniform(lb, ub, (b, n))
+    rng = get_rng(gen_specs, {})
+    H0["x"] = rng.uniform(lb, ub, (b, n))
     H0["sim_id"] = range(b)
     H0["sim_started"] = False
     for i in range(b):
@@ -126,6 +127,7 @@ def create_H0(persis_info, gen_specs, sim_max):
     if is_manager:
         print("Testing cancellations with non-persistent gen functions")
 
+    persis_info = {0: {}}
     for testnum in range(1, 6):
         alloc_specs = allocs[testnum]
         if is_manager:
@@ -142,7 +144,7 @@ def create_H0(persis_info, gen_specs, sim_max):
 
         # Perform the run - do not overwrite persis_info
         H, persis_out, flag = libE(
-            sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs=libE_specs, H0=H0
+            sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs=alloc_specs, libE_specs=libE_specs, H0=H0
         )
 
         if is_manager:

libensemble/tests/regression_tests/support.py

@@ -65,13 +65,16 @@ def remote_write_gen_func(calc_in, persis_info, gen_specs, libE_info):
     return H_o, persis_info
 
 
-def write_uniform_gen_func(H, persis_info, gen_specs, _):
+def write_uniform_gen_func(H, persis_info, gen_specs, libE_info):
+    from libensemble.tools import get_rng
+
     ub = gen_specs["user"]["ub"]
     lb = gen_specs["user"]["lb"]
     n = len(lb)
     b = gen_specs["batch_size"]
     H_o = np.zeros(b, dtype=gen_specs["out"])
-    H_o["x"] = persis_info["rand_stream"].uniform(lb, ub, (b, n))
+    rng = get_rng(gen_specs, libE_info)
+    H_o["x"] = rng.uniform(lb, ub, (b, n))
     with open("test_gen_out.txt", "a") as f:
         f.write(f"gen_f produced: {H_o['x']}\n")
     return H_o, persis_info

libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py

@@ -62,8 +62,6 @@ def six_hump_camel_func(x):
 
         n = 2
 
-        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"},

libensemble/tests/regression_tests/test_ensemble_platform_workdir.py

@@ -50,7 +50,7 @@
         "persis_in": ["f", "x", "sim_id"],
         "out": [("priority", float), ("resource_sets", int), ("x", float, n)],
         "initial_batch_size": ensemble.nworkers - 1,
-        "give_all_with_same_priority": False,
+        "batch_evaluate_same_priority": False,
         "async_return": False,
         "user": {
             "max_resource_sets": ensemble.nworkers - 1,  # Any sim created can req. 1 worker up to all.

libensemble/tests/regression_tests/test_persistent_aposmm_ibcdfo_manifold_sampling.py

@@ -113,12 +113,10 @@ def synthetic_beamline_mapping(H, _, sim_specs):
 
     alloc_specs = {"alloc_f": alloc_f}
 
-    persis_info = {}
-
     exit_criteria = {"sim_max": 500}
 
     # Perform the run
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs)
+    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, alloc_specs=alloc_specs, libE_specs=libE_specs)
 
     if is_manager:
         assert np.min(H["f"]) == 2.0, "The best is 2"

libensemble/tests/regression_tests/test_persistent_aposmm_ibcdfo_pounders.py

@@ -122,12 +122,10 @@ def synthetic_beamline_mapping(H, _, sim_specs):
 
         alloc_specs = {"alloc_f": alloc_f}
 
-        persis_info = {}
-
         exit_criteria = {"sim_max": 500}
 
         # Perform the run
-        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs)
+        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, alloc_specs=alloc_specs, libE_specs=libE_specs)
 
         if is_manager:
             assert persis_info[0].get("run_order"), "Run_order should have been given back"

libensemble/tests/regression_tests/test_persistent_aposmm_ibcdfo_pounders_jax.py

@@ -119,12 +119,10 @@ def synthetic_beamline_mapping(H, _, sim_specs):
 
     alloc_specs = {"alloc_f": alloc_f}
 
-    persis_info = {}
-
     exit_criteria = {"sim_max": 500}
 
     # Perform the run
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs)
+    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, alloc_specs=alloc_specs, libE_specs=libE_specs)
 
     if is_manager:
         print(H[["x", "f", "local_min"]])

libensemble/tests/regression_tests/test_persistent_aposmm_nlopt.py

@@ -81,12 +81,10 @@
 
     alloc_specs = {"alloc_f": alloc_f}
 
-    persis_info = {}
-
     exit_criteria = {"sim_max": 2000}
 
     # Perform the run
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs)
+    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, alloc_specs=alloc_specs, libE_specs=libE_specs)
 
     if is_manager:
         print("[Manager]:", H[np.where(H["local_min"])]["x"])