def __init__(self,
materials,
substrates,
elasticity=None,
substrate_settings=None,
query=None,
**kwargs):
"""
Calculates matching substrates for
Args:
materials (Store): Store of materials documents
diffraction (Store): Store of substrate matches
elasticity (Store): Store of elastic tensor documents
substrate_settings (path): Store of xrd settings
query (dict): dictionary to limit materials to be analyzed
"""
self.materials = materials
self.substrates = substrates
self.elasticity = elasticity
self.substrate_settings = substrate_settings
self.query = query if query else {}
self.__settings = load_settings(self.substrate_settings,
default_substrate_settings)
super().__init__(sources=[materials], targets=[substrates], **kwargs)
def __init__(self,
materials,
substrates,
elasticity=None,
substrates_file=None,
query=None,
**kwargs):
"""
Calculates matching substrates
Args:
materials (Store): Store of materials documents
diffraction (Store): Store of substrate matches
elasticity (Store): Store of elastic tensor documents
substrates_file (path): file of substrates to consider
query (dict): dictionary to limit materials to be analyzed
"""
self.materials = materials
self.substrates = substrates
self.elasticity = elasticity
self.substrates_file = substrates_file
self.query = query if query else {}
self.__settings = load_settings(self.substrates_file,
DEFAULT_SUBSTRATES)
super().__init__(sources=[materials, elasticity],
targets=[substrates],
**kwargs)
def __init__(self,
tasks,
materials,
mat_prefix="mp-",
materials_settings=None,
query=None,
ltol=0.2,
stol=0.3,
angle_tol=5,
separate_mag_orderings=False,
require_structure_opt=True,
**kwargs):
"""
Creates a materials collection from tasks and tags
Args:
tasks (Store): Store of task documents
materials (Store): Store of materials documents to generate
mat_prefix (str): prefix for all materials ids
materials_settings (Path): Path to settings files
query (dict): dictionary to limit tasks to be analyzed
ltol (float): StructureMatcher tuning parameter for matching tasks to materials
stol (float): StructureMatcher tuning parameter for matching tasks to materials
angle_tol (float): StructureMatcher tuning parameter for matching tasks to materials
separate_mag_orderings (bool): Separate magnetic orderings into different materials
require_structure_opt (bool): Requires every material have a structure optimization
"""
self.tasks = tasks
self.materials_settings = materials_settings
self.materials = materials
self.mat_prefix = mat_prefix
self.query = query if query else {}
self.ltol = ltol
self.stol = stol
self.angle_tol = angle_tol
self.separate_mag_orderings = separate_mag_orderings
self.require_structure_opt = require_structure_opt
self.__settings = load_settings(self.materials_settings,
default_mat_settings)
self.allowed_tasks = {
t_type
for d in self.__settings for t_type in d['quality_score']
}
super().__init__(sources=[tasks], targets=[materials], **kwargs)
def __init__(
self,
tasks,
materials,
task_types=None,
materials_settings=None,
query=None,
ltol=LTOL,
stol=STOL,
angle_tol=ANGLE_TOL,
separate_mag_orderings=False,
**kwargs
):
"""
Creates a materials collection from tasks and tags
Args:
tasks (Store): Store of task documents
materials (Store): Store of materials documents to generate
materials_settings (Path): Path to settings files
query (dict): dictionary to limit tasks to be analyzed
ltol (float): StructureMatcher tuning parameter for matching tasks to materials
stol (float): StructureMatcher tuning parameter for matching tasks to materials
angle_tol (float): StructureMatcher tuning parameter for matching tasks to materials
separate_mag_orderings (bool): Separate magnetic orderings into different materials
"""
self.tasks = tasks
self.materials_settings = materials_settings
self.materials = materials
self.task_types = task_types
self.query = query if query else {}
self.ltol = ltol
self.stol = stol
self.angle_tol = angle_tol
self.separate_mag_orderings = separate_mag_orderings
self.__settings = load_settings(self.materials_settings, default_mat_settings)
self.allowed_tasks = {
t_type for d in self.__settings for t_type in d["quality_score"]
}
sources = [tasks]
if self.task_types:
sources.append(self.task_types)
super().__init__(sources=sources, targets=[materials], **kwargs)
def __init__(self, materials, diffraction, xrd_settings=None, **kwargs):
"""
Calculates diffraction patterns for materials
Args:
materials (Store): Store of materials documents
diffraction (Store): Store of diffraction data such as formation energy and decomposition pathway
xrd_settings (Store): Store of xrd settings
"""
self.materials = materials
self.diffraction = diffraction
self.xrd_settings = xrd_settings
self.__settings = load_settings(self.xrd_settings, DEFAULT_XRD_SETTINGS)
super().__init__(
source=materials, target=diffraction, ufn=self.calc, projection=["structure"], **kwargs)
def __init__(self,
materials,
diffraction,
xrd_settings=None,
query=None,
**kwargs):
"""
Calculates diffraction patterns for materials
Args:
materials (Store): Store of materials documents
diffraction (Store): Store of diffraction data such as formation energy and decomposition pathway
xrd_settings (Store): Store of xrd settings
query (dict): dictionary to limit materials to be analyzed
"""
self.materials = materials
self.diffraction = diffraction
self.xrd_settings = xrd_settings
self.query = query if query else {}
self.__settings = load_settings(self.xrd_settings,
default_xrd_settings)
super().__init__(sources=[materials], targets=[diffraction], **kwargs)