def get_samples(desired_data):
"""
Return the data values from desired_data, transformed to interaction products.
Parameters
----------
desired_data : list
List of matched desired data, e.g. for a single property
Returns
-------
list
List of sample values that are properly transformed.
Notes
-----
Transforms data to interaction products, e.g. YS*{}^{xs}G=YS*XS*DXS^{n} {}^{n}L
"""
# TODO: binary and ternaries only, possibly non-working ternary cross interactions
# TODO does not ravel pressure conditions
# TODO: could possibly combine with ravel_conditions if we do the math outside.
all_samples = []
for data in desired_data:
temperatures = np.atleast_1d(data['conditions']['T'])
num_configs = np.array(data['solver'].get('sublattice_configurations'), dtype=np.object).shape[0]
site_fractions = data['solver'].get('sublattice_occupancies', [[1]] * num_configs)
site_fraction_product = calc_site_fraction_product(site_fractions)
# TODO: Subtle sorting bug here, if the interactions aren't already in sorted order...
interaction_product = calc_interaction_product(site_fractions)
comp_features = zip(site_fraction_product, interaction_product)
all_samples.extend(list(itertools.product(temperatures, comp_features)))
return all_samples
def _get_sample_condition_dicts(calculate_dict, sublattice_dof) -> List[Dict[Symbol, float]]:
sample_condition_dicts = []
for sample_idx in range(calculate_dict["values"].size):
cond_dict = {}
points = calculate_dict["points"][sample_idx, :]
# T and P
cond_dict[v.T] = calculate_dict["T"][sample_idx]
cond_dict[v.P] = calculate_dict["P"][sample_idx]
# YS site fraction product
site_fraction_product = np.prod(points)
cond_dict[Symbol("YS")] = site_fraction_product
# Reconstruct site fractions in sublattice form from points
# Required so we can identify which sublattices have interactions
points_idxs = [0] + np.cumsum(sublattice_dof).tolist()
site_fractions = []
for i in range(len(points_idxs)-1):
site_fractions.append(points[points_idxs[i]:points_idxs[i+1]].tolist())
# Z (binary) or V_I, V_J, V_K (ternary) interaction products
interaction_product = calc_interaction_product(site_fractions)
if hasattr(interaction_product, "__len__"):
# Ternary interaction
assert len(interaction_product) == 3
cond_dict[Symbol("V_I")] = interaction_product[0]
cond_dict[Symbol("V_J")] = interaction_product[1]
cond_dict[Symbol("V_K")] = interaction_product[2]
else:
cond_dict[Symbol("Z")] = interaction_product
sample_condition_dicts.append(cond_dict)
return sample_condition_dicts