def test_update_history_f():
hist, sim_specs, _, _, _ = setup.hist_setup2()
exp_vals = [0.0] * 10
# First update a single point
size = 1
sim_ids = 0 # First row to be filled
sim_ids = np.atleast_1d(sim_ids)
calc_out = np.zeros(size, dtype=sim_specs['out'])
a = np.arange(9) - 4
calc_out['g'] = sim_specs['sim_f'](a) #np.linalg.norm
exp_vals[0] = calc_out['g'][0]
D_recv = {
'calc_out': calc_out,
'persis_info': {},
'libE_info': {
'H_rows': sim_ids
},
'calc_status': WORKER_DONE,
'calc_type': 2
}
hist.update_history_f(D_recv)
assert isclose(exp_vals[0], hist.H['g'][0])
assert np.all(hist.H['returned'][0:1])
assert np.all(hist.H['returned'][1:10] == False) #Check the rest
assert hist.sim_count == 1
assert hist.given_count == 0 # In real case this would be ahead.....
assert hist.index == 0 # In real case this would be ahead....
# Update two further consecutive points
size = 2
sim_ids = [1, 2] # First row to be filled
sim_ids = np.atleast_1d(sim_ids)
calc_out = np.zeros(size, dtype=sim_specs['out'])
a = np.arange(9) - 3
calc_out['g'][0] = sim_specs['sim_f'](a) #np.linalg.norm
exp_vals[1] = calc_out['g'][0]
a = np.arange(9) - 2
calc_out['g'][1] = sim_specs['sim_f'](a) #np.linalg.norm
exp_vals[2] = calc_out['g'][1]
D_recv = {
'calc_out': calc_out,
'persis_info': {},
'libE_info': {
'H_rows': sim_ids
},
'calc_status': WORKER_DONE,
'calc_type': 2
}
hist.update_history_f(D_recv)
assert np.allclose(exp_vals, hist.H['g'])
assert np.all(hist.H['returned'][0:3])
assert np.all(hist.H['returned'][3:10] == False) #Check the rest
assert hist.sim_count == 3
assert hist.given_count == 0 # In real case this would be ahead.....
assert hist.index == 0 # In real case this would be ahead....
def test_update_history_x_in_Oempty():
hist, sim_specs, gen_specs, _, _ = setup.hist_setup2()
O = np.zeros(0, dtype=gen_specs['out'])
gen_worker = 1
hist.update_history_x_in(gen_worker, O)
assert np.array_equal(hist.H, wrs2), "H Array does not match expected"
assert hist.given_count == 0
assert hist.index == 0
assert hist.sim_count == 0
def test_update_history_x_in():
hist, _, gen_specs, _, _ = setup.hist_setup2(7)
#import pdb; pdb.set_trace()
#calc_in = hist.H[gen_specs['in']][0]
np.random.seed(1)
single_rand = gen_specs['gen_f']() # np.random.uniform()
# Check seeded correctly going in
assert isclose(
single_rand,
0.417022004702574), "Random numbers not correct before function"
size = 1
gen_worker = 2
O = np.zeros(size, dtype=gen_specs['out'])
O['x'] = single_rand
hist.update_history_x_in(gen_worker, O)
assert isclose(single_rand, hist.H['x'][0])
assert hist.given_count == 0
assert hist.index == 1
assert hist.sim_count == 0
size = 6
gen_worker = 3
O = np.zeros(size, dtype=gen_specs['out'])
O['x'] = gen_specs['gen_f'](size=size)
hist.update_history_x_in(gen_worker, O)
# Compare by column
exp_x = exp_x_in_setup2[:size + 1]
for field in exp_x.dtype.names:
np.allclose(hist.H[field], exp_x[field])
assert hist.given_count == 0
assert hist.index == 7
assert hist.sim_count == 0
# Force H to grow when add points
size = 3
gen_worker = 3
O = np.zeros(size, dtype=gen_specs['out'])
O['x'] = gen_specs['gen_f'](size=size)
hist.update_history_x_in(gen_worker, O)
# Compare by column
exp_x = exp_x_in_setup2
for field in exp_x.dtype.names:
np.allclose(hist.H[field], exp_x[field])
assert hist.given_count == 0
assert hist.index == 10
assert hist.sim_count == 0
def test_term_test_3():
# Test 3.
# Terminate because enough time has passed
H0 = np.zeros(3,
dtype=[('g', float)] + [('x', float), ('priority', float)])
hist, sim_specs, gen_specs, exit_criteria, al = setup.hist_setup2(H0_in=H0)
mgr = man.Manager(hist, libE_specs, al, sim_specs, gen_specs,
exit_criteria)
hist.index = 4
hist.H['given_time'][0] = time.time()
time.sleep(0.5)
hist.given_count = 4
assert mgr.term_test()
def test_term_test_2():
# Test 2 - these could also be sep - with a setup or fixture....
# Shouldn't terminate
hist, sim_specs, gen_specs, exit_criteria, al = setup.hist_setup2()
mgr = man.Manager(hist, libE_specs, al, sim_specs, gen_specs,
exit_criteria)
assert not mgr.term_test()
#
# Terminate because we've found a good 'g' value
hist.H['g'][0] = -1
hist.H['returned'][0] = True
hist.index = 1
hist.given_count = 1
assert mgr.term_test()
#
# Terminate because everything has been given.
hist.H['given'] = np.ones
hist.given_count = len(hist.H)
assert mgr.term_test()
def test_hist_init_2():
hist, _, _, _, _ = setup.hist_setup2()
assert np.array_equal(hist.H, wrs2), "Array does not match expected"
assert hist.given_count == 0
assert hist.index == 0
assert hist.sim_count == 0