Simulation Functions

Below are example simulation functions available in libEnsemble. Most of these demonstrate an inexpensive algorithm and do not launch tasks (user applications). To see an example of a simulation function launching tasks, see the Electrostatic Forces tutorial.

Important

See the API for simulation functions here.

six_hump_camel

This module contains various versions that evaluate the six-hump camel function.

Six-hump camel function is documented here:

https://www.sfu.ca/~ssurjano/camel6.html

six_hump_camel.six_hump_camel(H, persis_info, sim_specs, libE_info)

Evaluates the six hump camel function for a collection of points given in H["x"]. Additionally evaluates the gradient if "grad" is a field in sim_specs["out"] and pauses for sim_specs["user"]["pause_time"]] if defined.

six_hump_camel.six_hump_camel_simple(x, _, sim_specs)

Evaluates the six hump camel function for a single point x.

See also

test_fast_alloc.py # noqa

six_hump_camel.persistent_six_hump_camel(H, persis_info, sim_specs, libE_info)

Similar to six_hump_camel, but runs in persistent mode.

six_hump_camel.py
  1"""
  2This module contains various versions that evaluate the six-hump camel function.
  3
  4Six-hump camel function is documented here:
  5  https://www.sfu.ca/~ssurjano/camel6.html
  6
  7"""
  8__all__ = [
  9    "six_hump_camel",
 10    "six_hump_camel_simple",
 11    "persistent_six_hump_camel",
 12]
 13
 14import sys
 15import time
 16import numpy as np
 17
 18from libensemble.message_numbers import (
 19    EVAL_SIM_TAG,
 20    FINISHED_PERSISTENT_SIM_TAG,
 21    PERSIS_STOP,
 22    STOP_TAG,
 23)
 24from libensemble.tools.persistent_support import PersistentSupport
 25
 26
 27def six_hump_camel(H, persis_info, sim_specs, libE_info):
 28    """
 29    Evaluates the six hump camel function for a collection of points given in ``H["x"]``.
 30    Additionally evaluates the gradient if ``"grad"`` is a field in
 31    ``sim_specs["out"]`` and pauses for ``sim_specs["user"]["pause_time"]]`` if
 32    defined.
 33
 34    .. seealso::
 35        `test_old_aposmm_with_gradients.py  <https://github.com/Libensemble/libensemble/blob/develop/libensemble/tests/regression_tests/test_old_aposmm_with_gradients.py>`_ # noqa
 36    """
 37
 38    batch = len(H["x"])
 39    H_o = np.zeros(batch, dtype=sim_specs["out"])
 40
 41    for i, x in enumerate(H["x"]):
 42        H_o["f"][i] = six_hump_camel_func(x)
 43
 44        if "grad" in H_o.dtype.names:
 45            H_o["grad"][i] = six_hump_camel_grad(x)
 46
 47        if "user" in sim_specs and "pause_time" in sim_specs["user"]:
 48            time.sleep(sim_specs["user"]["pause_time"])
 49
 50    return H_o, persis_info
 51
 52
 53def six_hump_camel_simple(x, _, sim_specs):
 54    """
 55    Evaluates the six hump camel function for a single point ``x``.
 56
 57    .. seealso::
 58        `test_fast_alloc.py <https://github.com/Libensemble/libensemble/blob/develop/libensemble/tests/regression_tests/test_fast_alloc.py>`_ # noqa
 59    """
 60
 61    H_o = np.zeros(1, dtype=sim_specs["out"])
 62
 63    H_o["f"] = six_hump_camel_func(x[0][0])
 64
 65    if "pause_time" in sim_specs["user"]:
 66        time.sleep(sim_specs["user"]["pause_time"])
 67
 68    return H_o
 69
 70
 71def persistent_six_hump_camel(H, persis_info, sim_specs, libE_info):
 72    """
 73    Similar to ``six_hump_camel``, but runs in persistent mode.
 74    """
 75
 76    ps = PersistentSupport(libE_info, EVAL_SIM_TAG)
 77
 78    # Either start with a work item to process - or just start and wait for data
 79    if H.size > 0:
 80        tag = None
 81        Work = None
 82        calc_in = H
 83    else:
 84        tag, Work, calc_in = ps.recv()
 85
 86    while tag not in [STOP_TAG, PERSIS_STOP]:
 87        # calc_in: This should either be a function (unpack_work ?) or included/unpacked in ps.recv/ps.send_recv.
 88        if Work is not None:
 89            persis_info = Work.get("persis_info", persis_info)
 90            libE_info = Work.get("libE_info", libE_info)
 91
 92        # Call standard six_hump_camel sim
 93        H_o, persis_info = six_hump_camel(calc_in, persis_info, sim_specs, libE_info)
 94
 95        tag, Work, calc_in = ps.send_recv(H_o)
 96
 97    final_return = None
 98
 99    # Overwrite final point - for testing only
100    if sim_specs["user"].get("replace_final_fields", 0):
101        calc_in = np.ones(1, dtype=[("x", float, (2,))])
102        H_o, persis_info = six_hump_camel(calc_in, persis_info, sim_specs, libE_info)
103        final_return = H_o
104
105    return final_return, persis_info, FINISHED_PERSISTENT_SIM_TAG
106
107
108def six_hump_camel_func(x):
109    """
110    Definition of the six-hump camel
111    """
112    x1 = x[0]
113    x2 = x[1]
114    term1 = (4 - 2.1 * x1**2 + (x1**4) / 3) * x1**2
115    term2 = x1 * x2
116    term3 = (-4 + 4 * x2**2) * x2**2
117
118    return term1 + term2 + term3
119
120
121def six_hump_camel_grad(x):
122    """
123    Definition of the six-hump camel gradient
124    """
125
126    x1 = x[0]
127    x2 = x[1]
128    grad = np.zeros(2)
129
130    grad[0] = 2.0 * (x1**5 - 4.2 * x1**3 + 4.0 * x1 + 0.5 * x2)
131    grad[1] = x1 + 16 * x2**3 - 8 * x2
132
133    return grad
134
135
136if __name__ == "__main__":
137    x = (float(sys.argv[1]), float(sys.argv[2]))
138    result = six_hump_camel_func(x)
139    print(result)

chwirut

chwirut1.chwirut_eval(H, _, sim_specs)

Evaluates the chwirut objective function at a given set of points in H["x"]. If "obj_component" is a field in sim_specs["out"], only that component of the objective will be evaluated. Otherwise, all 214 components are evaluated and returned in the "fvec" field.

See also

test_old_aposmm_pounders.py for an example where the entire fvec is computed each call.

See also

test_old_aposmm_one_residual_at_a_time.py for an example where one component of fvec is computed per call

noisy_vector_mapping

This module contains a test noisy function

noisy_vector_mapping.func_wrapper(H, persis_info, sim_specs, libE_info)

Wraps an objective function

noisy_vector_mapping.noisy_function(x)
noisy_vector_mapping.py
 1"""
 2This module contains a test noisy function
 3"""
 4
 5import numpy as np
 6from numpy import cos, sin
 7from numpy.linalg import norm
 8
 9
10def func_wrapper(H, persis_info, sim_specs, libE_info):
11    """
12    Wraps an objective function
13
14    .. seealso::
15        `test_persistent_fd_param_finder.py` <https://github.com/Libensemble/libensemble/blob/develop/libensemble/tests/regression_tests/test_persistent_fd_param_finder.py>`_ # noqa
16    """
17
18    batch = len(H["x"])
19    H0 = np.zeros(batch, dtype=sim_specs["out"])
20
21    for i, x in enumerate(H["x"]):
22        H0["f_val"][i] = noisy_function(x)[H["f_ind"][i]]
23
24    return H0, persis_info
25
26
27def noisy_function(x):
28    """ """
29    x1 = x[0]
30    x2 = x[1]
31    term1 = (4 - 2.1 * x1**2 + (x1**4) / 3) * x1**2
32    term2 = x1 * x2
33    term3 = (-4 + 4 * x2**2) * x2**2
34
35    phi1 = 0.9 * sin(100 * norm(x, 1)) * cos(100 * norm(x, np.inf)) + 0.1 * cos(norm(x, 2))
36    phi1 = phi1 * (4 * phi1**2 - 3)
37
38    phi2 = 0.8 * sin(100 * norm(x, 1)) * cos(100 * norm(x, np.inf)) + 0.2 * cos(norm(x, 2))
39    phi2 = phi2 * (4 * phi2**2 - 3)
40
41    phi3 = 0.7 * sin(100 * norm(x, 1)) * cos(100 * norm(x, np.inf)) + 0.3 * cos(norm(x, 2))
42    phi3 = phi3 * (4 * phi3**2 - 3)
43
44    F = np.zeros(3)
45    F[0] = (1 + 1e-1 * phi1) * term1
46    F[1] = (1 + 1e-2 * phi2) * term2
47    F[2] = (1 + 1e-3 * phi3) * term3
48
49    return F

periodic_func

This module contains a periodic test function

periodic_func.func_wrapper(H, persis_info, sim_specs, libE_info)

Wraps an objective function

periodic_func.periodic_func(x)

This function is periodic

borehole

borehole.borehole(H, persis_info, sim_specs, _)

Wraps the borehole function

borehole.borehole_func(x)

This evaluates the Borehole function for n-by-8 input matrix x, and returns the flow rate through the Borehole. (Harper and Gupta, 1983) input:

Parameters:

x (matrix of dimension (n, 8), where n is the number of input configurations:) –

x[:,0]: Tu, transmissivity of upper aquifer (m^2/year)
x[:,1]: Tl, transmissivity of lower aquifer (m^2/year)
x[:,2]: Hu, potentiometric head of upper aquifer (m)
x[:,3]: Hl, potentiometric head of lower aquifer (m)
x[:,4]: r, radius of influence (m)
x[:,5]: rw, radius of borehole (m)
x[:,6]: Kw, hydraulic conductivity of borehole (m/year)
x[:,7]: L, length of borehole (m)

Returns:

flow rate through the Borehole (m^3/year)

Return type:

vector of dimension (n, 1)

borehole.gen_borehole_input(n)

Generates and returns n inputs for the Borehole function, according to distributions outlined in Harper and Gupta (1983).

input:

n: number of input to generate

output:

matrix of (n, 8), input to borehole_func(x) function

executor_hworld

executor_hworld.executor_hworld(H, _, sim_specs)

Tests launching and polling task and exiting on task finish

executor_hworld.py
  1import numpy as np
  2
  3from libensemble.executors.mpi_executor import MPIExecutor
  4from libensemble.message_numbers import (
  5    MAN_SIGNAL_FINISH,
  6    TASK_FAILED,
  7    UNSET_TAG,
  8    WORKER_DONE,
  9    WORKER_KILL_ON_ERR,
 10    WORKER_KILL_ON_TIMEOUT,
 11)
 12
 13__all__ = ["executor_hworld"]
 14
 15# Alt send values through X
 16sim_ended_count = 0
 17
 18
 19def custom_polling_loop(exctr, task, timeout_sec=5.0, delay=0.3):
 20    import time
 21
 22    calc_status = UNSET_TAG  # Sim func determines status of libensemble calc - returned to worker
 23
 24    while task.runtime < timeout_sec:
 25        time.sleep(delay)
 26
 27        if exctr.manager_kill_received():
 28            exctr.kill(task)
 29            calc_status = MAN_SIGNAL_FINISH  # Worker will pick this up and close down
 30            print(f"Task {task.id} killed by manager on worker {exctr.workerID}")
 31            break
 32
 33        task.poll()
 34        if task.finished:
 35            break
 36        elif task.state == "RUNNING":
 37            print(f"Task {task.id} still running on worker {exctr.workerID} ....")
 38
 39        if task.stdout_exists():
 40            if "Error" in task.read_stdout():
 41                print(
 42                    "Found (deliberate) Error in output file - cancelling " f"task {task.id} on worker {exctr.workerID}"
 43                )
 44                exctr.kill(task)
 45                calc_status = WORKER_KILL_ON_ERR
 46                break
 47
 48    # After exiting loop
 49    if task.finished:
 50        print(f"Task {task.id} done on worker {exctr.workerID}")
 51        # Fill in calc_status if not already
 52        if calc_status == UNSET_TAG:
 53            if task.state == "FINISHED":  # Means finished successfully
 54                calc_status = WORKER_DONE
 55            elif task.state == "FAILED":
 56                calc_status = TASK_FAILED
 57
 58    else:
 59        # assert task.state == 'RUNNING', "task.state expected to be RUNNING. Returned: " + str(task.state)
 60        print(f"Task {task.id} timed out - killing on worker {exctr.workerID}")
 61        exctr.kill(task)
 62        if task.finished:
 63            print(f"Task {task.id} done on worker {exctr.workerID}")
 64        calc_status = WORKER_KILL_ON_TIMEOUT
 65
 66    return task, calc_status
 67
 68
 69def executor_hworld(H, _, sim_specs):
 70    """Tests launching and polling task and exiting on task finish"""
 71    exctr = MPIExecutor.executor
 72    cores = sim_specs["user"]["cores"]
 73    ELAPSED_TIMEOUT = "elapsed_timeout" in sim_specs["user"]
 74
 75    wait = False
 76    args_for_sim = "sleep 1"
 77    calc_status = UNSET_TAG
 78
 79    batch = len(H["x"])
 80    H_o = np.zeros(batch, dtype=sim_specs["out"])
 81
 82    if "six_hump_camel" not in exctr.default_app("sim").full_path:
 83        global sim_ended_count
 84        sim_ended_count += 1
 85        print("sim_ended_count", sim_ended_count, flush=True)
 86
 87        if ELAPSED_TIMEOUT:
 88            args_for_sim = "sleep 60"  # Manager kill - if signal received else completes
 89            timeout = 65.0
 90
 91        else:
 92            timeout = 6.0
 93            launch_shc = False
 94
 95            if sim_ended_count == 1:
 96                args_for_sim = "sleep 1"  # Should finish
 97            elif sim_ended_count == 2:
 98                args_for_sim = "sleep 1 Error"  # Worker kill on error
 99            elif sim_ended_count == 3:
100                wait = True
101                args_for_sim = "sleep 1"  # Should finish
102                launch_shc = True
103            elif sim_ended_count == 4:
104                args_for_sim = "sleep 8"  # Worker kill on timeout
105                timeout = 1.0
106            elif sim_ended_count == 5:
107                args_for_sim = "sleep 2 Fail"  # Manager kill - if signal received else completes
108
109        task = exctr.submit(calc_type="sim", num_procs=cores, app_args=args_for_sim, hyperthreads=True)
110
111        if wait:
112            task.wait()
113            if not task.finished:
114                calc_status = UNSET_TAG
115            if task.state == "FINISHED":
116                calc_status = WORKER_DONE
117            elif task.state == "FAILED":
118                calc_status = TASK_FAILED
119
120        else:
121            if sim_ended_count >= 2:
122                calc_status = exctr.polling_loop(task, timeout=timeout, delay=0.3, poll_manager=True)
123                if sim_ended_count == 2 and task.stdout_exists() and "Error" in task.read_stdout():
124                    calc_status = WORKER_KILL_ON_ERR
125            else:
126                task, calc_status = custom_polling_loop(exctr, task, timeout)
127
128    else:
129        launch_shc = True
130        calc_status = UNSET_TAG
131
132        # Comparing six_hump_camel output, directly called vs. submitted as app
133        for i, x in enumerate(H["x"]):
134            H_o["f"][i] = six_hump_camel_func(x)
135            if launch_shc:
136                # Test launching a named app.
137                app_args = " ".join(str(val) for val in list(x[:]))
138                task = exctr.submit(app_name="six_hump_camel", num_procs=1, app_args=app_args)
139                task.wait()
140                output = np.float64(task.read_stdout())
141                assert np.isclose(H_o["f"][i], output)
142                calc_status = WORKER_DONE
143
144    # This is just for testing at calling script level - status of each task
145    H_o["cstat"] = calc_status
146
147    return H_o, calc_status
148
149
150def six_hump_camel_func(x):
151    """
152    Definition of the six-hump camel
153    """
154    x1 = x[0]
155    x2 = x[1]
156    term1 = (4 - 2.1 * x1**2 + (x1**4) / 3) * x1**2
157    term2 = x1 * x2
158    term3 = (-4 + 4 * x2**2) * x2**2
159
160    return term1 + term2 + term3