def map_pointset_loop_xy(
foldname,
pointset,
optimizer,
parameter_dict,
ctol=1e-2,
ndim=2,
use_minima_database=True,
minima_database_path=None,
coord_arg_0=0,
coord_arg_1=1,
z=0,
):
""" Checks a bunch of points if they match to a minimum by using a for loop
"""
is_same_minimum_list = []
resultlist = []
foldpath = BASE_DIRECTORY + "/" + foldname
sysparams = load_params(foldpath)
(hs_radii, initial_coords, box_length) = load_secondary_params(foldpath)
minimum_coords = np.loadtxt(foldpath + "/coords_of_minimum.txt", delimiter=",")
# Initialize CheckSameMinimum
potential = InversePower(
sysparams.power.value,
sysparams.eps.value,
use_cell_lists=False,
ndim=sysparams.ndim.value,
radii=hs_radii * 1.0,
boxvec=[box_length, box_length],
)
minima_container = CheckSameMinimum(
ctol,
ndim,
boxl=box_length,
minimalist_max_len=200000,
minima_database_location=minima_database_path,
update_database=True,
rattler_check=True,
potential=potential,
hs_radii=hs_radii,
)
if use_minima_database == True:
try:
minima_container.minimalist = [
minima_container.box_reshape_coords(x)
for x in np.load(minima_database_path)
]
except:
print("warning no minima data found. generating")
minima_container.minimalist = [
# minima_container.box_reshape_coords(minimum_coords)
]
nfevlist = []
nstepslist = []
nhevlist = []
for index, point in enumerate(pointset):
res = map_binary_inversepower(
foldname,
point,
optimizer,
parameter_dict,
random_coord_0=coord_arg_0,
random_coord_1=coord_arg_1,
z=z,
)
minima_container.add_minimum(res[0], point, res[2])
# print(index)
# print(minima_container.nrattlermin, 'nrattlermin')
# print(minima_container.nfluidstates, 'nfluidstates')
nfevlist.append(res[3])
nstepslist.append(res[4])
nhevlist.append(res[5])
# print(np.average(nfevlist), 'number of function evaluations')
# print(np.average(nstepslist), 'number of steps')
# print(np.average(nstepslist), 'number of steps')
# print(np.average(nhevlist), "number of hessian evaluations")
# print(minima_container.orderparamlist)
foldpathdata = foldpath + "/" + QUENCH_FOLDER_NAME + "/z_data_30_l6/" + str(z)
os.makedirs(foldpathdata, exist_ok=True)
minima_container.dump_map(foldpathdata)
run_diagnostics = {}
run_diagnostics["nfev"] = float(np.average(nfevlist))
run_diagnostics["nhev"] = float(np.average(nhevlist))
run_diagnostics["nsteps"] = float(np.average(nstepslist))
# print(minima_container.initial_coords_list)
# print(minima_container.orderparamlist)
# print(minima_container.orderparamlist)
return run_diagnostics, is_same_minimum_list, resultlist
def compare_runs_2d(fnames, foldpath, subfoldname, run_a, run_b, ctol):
""" compares runs on points with names fnames between
runs done with 2 minima find routines run_a and run_b
Args:
fnames filenames
run_a run a
run_b run b
Returns:
percentage of minima that are the same
"""
# TODO: replace this
sysparams = load_params(foldpath)
radii = get_hs_radii(foldpath, subfoldname)
box_length = get_box_length(radii, sysparams.ndim.value,
sysparams.phi.value)
subfoldpath = foldpath + "/" + subfoldname
data_path_a = subfoldpath + "/" + run_a
data_path_b = subfoldpath + "/" + run_b
potential = InversePower(
sysparams.power.value,
sysparams.eps.value,
use_cell_lists=False,
ndim=sysparams.ndim.value,
radii=radii * 1.0,
boxvec=[box_length, box_length],
)
minima_checker = CheckSameMinimum(ctol,
dim=2,
boxl=box_length,
hs_radii=radii,
potential=potential)
same_minimum_check_l = []
for fname in fnames:
print(fname)
minimum_a = np.loadtxt(data_path_a + "/" + fname, delimiter=",")
minimum_b = np.loadtxt(data_path_b + "/" + fname, delimiter=",")
boxed_minimum_a = minima_checker.box_reshape_coords(minimum_a)
boxed_minimum_b = minima_checker.box_reshape_coords(minimum_b)
# get first index that is not a rattler
rattlers_exist, rattlers = minima_checker._find_rattlers(minimum_a)
print(rattlers)
# number of non rattlers to ensure we're not in a fluid state
n_non_rattlers = np.count_nonzero(rattlers)
# only do calculations if all particles aren't rattlers
if n_non_rattlers != 0:
first_non_rattler = (np.argwhere(rattlers != 0).T)[0, 0]
# TODO: rewrite the CheckSameMinimum function
# load and make sure the particle being aligned is not a rattler later
# we're choosing -1 because that's always going to be of radius 1.4
# particle
aligned_minimum_b = minima_checker.align_structures(
boxed_minimum_a, boxed_minimum_b, part_ind=first_non_rattler)
same_minimum_check = minima_checker.check_same_structure(
aligned_minimum_b, boxed_minimum_a, rattlers)
same_minimum_check_l.append(same_minimum_check)
fraction_same_minimum = np.mean(same_minimum_check_l)
print(fraction_same_minimum)
return fraction_same_minimum
minima_container = CheckSameMinimum(
ctol,
ndim,
boxl=box_length,
minimalist_max_len=2000,
minima_database_location=minima_database_path,
update_database=True,
rattler_check=True,
potential=potential,
hs_radii=hs_radii,
)
print(box_length, "box_length")
box_length = float(box_length)
minimum_coords = np.loadtxt(foldpath + "/coords_of_minimum.txt", delimiter=",")
m1 = minima_container.box_reshape_coords(th[m1_arg])
m2 = minima_container.box_reshape_coords(th[m2_arg])
m3 = minima_container.box_reshape_coords(th[m3_arg])
m4 = minima_container.box_reshape_coords(th[m4_arg])
print(minima_container.boxl)
# print(th)
# print(m1)
# print(m2)
# print(m3)
# print(m4)
print(m3)
print(m4)
dv = m3 - m4
print(dv)
print(np.where(dv > box_length / 2, box_length - dv, dv))