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Revisions to get test notebooks working.
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@bjmorgan
bjmorgan committed Jul 5, 2021
1 parent ca27ba6 commit a1df2dd
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Showing 7 changed files with 360 additions and 187 deletions.
2 changes: 1 addition & 1 deletion pyscses/grid.py
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Original file line number Diff line number Diff line change
Expand Up @@ -149,7 +149,7 @@ def __init__(self,
for site in set_of_sites:
i = index_of_grid_at_x(self.x, site.x)
self.points[i].sites.append(site)
# site.grid_point = self.points[i]
site.grid_point = self.points[i]
for defect_species in site.defect_species:
if defect_species not in self.defect_species:
self.defect_species.append(defect_species)
Expand Down
77 changes: 37 additions & 40 deletions pyscses/grid_point.py
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Original file line number Diff line number Diff line change
Expand Up @@ -21,44 +21,41 @@ def __init__(self,
self.volume = volume
self.sites: List[Site] = []

# def average_site_energy(self,
# method: str = 'mean') -> Optional[np.ndarray]:
# """
#
# Returns the average segregation energy for all sites based on a specified method
#
# Args:
# method (str): The method in which the average segregation energies will be calculated.
# 'mean' - Returns the sum of all values at that site divided by the number of values at that site.
# 'min' - Returns the minimum segregation energy value for that site (appropriate for low temperature calculations).
#
# Returns:
# np.ndarray: Average segregation energies on a 1D grid.
#
# """
#
# if self.sites:
# return avg(np.array([s.energies() for s in self.sites]), method)
# else:
# return None
def average_site_energy(self,
method: str = 'mean') -> Optional[np.ndarray]:
"""Returns the average segregation energy for all sites based on a specified method
# def avg(energies,
# method: str = 'mean') -> np.ndarray:
# """Returns the average segregation energy for a site based on a specified method
#
# Args:
# energies (np.array): Segregation energies on 1D grid.
# method (str): The method in which the average segregation energies will be calculated.
# 'mean' - Returns the sum of all values at that site divided by the number of values at that site.
# 'min' - Returns the minimum segregation energy value for that site (appropriate for low temperature calculations).
#
# Returns:
# np.array: Average segregation energies on a 1D grid.
#
# """
# if method == 'mean':
# return np.array([np.mean(row) for row in energies.T])
# elif method == 'min':
# return np.array([np.min(row) for row in energies.T])
# else:
# raise ValueError("method: {}".format(method))
Args:
method (str): The method in which the average segregation energies will be calculated.
'mean' - Returns the sum of all values at that site divided by the number of values at that site.
'min' - Returns the minimum segregation energy value for that site (appropriate for low temperature calculations).
Returns:
np.ndarray: Average segregation energies on a 1D grid.
"""
if self.sites:
return avg(np.array([s.energies() for s in self.sites]), method)
else:
return None

def avg(energies,
method: str = 'mean') -> np.ndarray:
"""Returns the average segregation energy for a site based on a specified method
Args:
energies (np.array): Segregation energies on 1D grid.
method (str): The method in which the average segregation energies will be calculated.
'mean' - Returns the sum of all values at that site divided by the number of values at that site.
'min' - Returns the minimum segregation energy value for that site (appropriate for low temperature calculations).
Returns:
np.array: Average segregation energies on a 1D grid.
"""
if method == 'mean':
return np.array([np.mean(row) for row in energies.T])
elif method == 'min':
return np.array([np.min(row) for row in energies.T])
else:
raise ValueError("method: {}".format(method))
130 changes: 70 additions & 60 deletions pyscses/set_of_sites.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,10 +8,8 @@
from pyscses.defect_species import DefectSpecies
from bisect import bisect_left
from typing import List, Iterator, Tuple, Optional
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from pyscses.site import Site
from pyscses.grid import Grid
from pyscses.site import Site
from pyscses.grid import Grid

class SetOfSites:
"""The SetOfSites object groups together all of the Site objects into one object and
Expand Down Expand Up @@ -43,6 +41,10 @@ def __iter__(self) -> Iterator[Site]:
"""Iterator over self.sites"""
return iter(self.sites)

def __len__(self) -> int:
"""Number of sites"""
return len(self.sites)

def subset(self,
label: str) -> SetOfSites:
"""Returns a subset of all the sites which contain a particular defect """
Expand Down Expand Up @@ -156,48 +158,55 @@ def subgrid_calculate_defect_density(self,
defect_density[ i ] += np.asarray( site.probabilities( phi_at_x( phi, full_grid.x, site.x ), temp ) ) / sub_grid.volumes[ i ]
return defect_density

# BEN: Does not appear to be called?
# def form_continuum_sites(all_sites,
# x_min,
# x_max,
# n_points,
# b,
# c,
# defect_species,
# limits_for_laplacian,
# site_labels,
# defect_labels):
# """
# Creates a SetOfSites object for sites interpolated onto a regular grid, this is equivalent to assuming a continuum approximation.
#
# Args:
# all_sites (SetOfSites): Orginal SetOfSites object from full data.
# x_min (float): Minimum x coordinate value defining the calculation region.
# x_max (float): Maximum x coordinate value defining the calculation region.
# n_points (int): Number of points that the data should be interpolated on to.
# b (float): b dimension for every grid point.
# c (float): c dimension for every grid point.
# defect_species (object): Class object containing information about the defect species present in the system.
# limits for laplacian (list): distance between the endmost sites and the midpoint of the next site outside of the calculation region for the first and last sites respectively.
# site_labels( list ): List of strings for the different site species.
# defect_labels (list): List of strings for the different defect species.
#
# Returns:
# :obj:`SetOfSites`: Sites interpolated onto a regular grid.
#
# """
#
# grid = np.linspace( x_min, x_max, n_points )
# limits = [grid[1] - grid[0], grid[1] - grid[0]]
# sites = []
# for label, d_label in zip(site_labels, defect_labels):
# scaling = len( all_sites.subset( label ) ) / len( grid )
# continuum_grid = Grid(grid, b, c, limits, limits_for_laplacian, all_sites.subset(label))
# average_energies = np.array( [ site.average_local_energy( method = 'mean' )[0] for site in all_sites.subset( label ) ] )
# new_energies = griddata( ( [ site.x for site in all_sites.subset( label ) ] ), average_energies, grid, method = 'nearest' )
# for x, e in zip( grid, new_energies):
# sites.append( Site( label, x, [ defect_species[ d_label ] ], [e], scaling = np.array( scaling ) ) )
# return SetOfSites( sites ), limits

def form_continuum_sites(all_sites,
x_min,
x_max,
n_points,
b,
c,
defect_species,
limits_for_laplacian,
site_labels,
defect_labels):
"""
Creates a SetOfSites object for sites interpolated onto a regular grid, this is equivalent to assuming a continuum approximation.
Args:
all_sites (SetOfSites): Original SetOfSites object from full data.
x_min (float): Minimum x coordinate value defining the calculation region.
x_max (float): Maximum x coordinate value defining the calculation region.
n_points (int): Number of points that the data should be interpolated on to.
b (float): b dimension for every grid point.
c (float): c dimension for every grid point.
defect_species (object): Class object containing information about the defect species present in the system.
limits for laplacian (list): distance between the endmost sites and the midpoint of the next site outside of the calculation region for the first and last sites respectively.
site_labels( list ): List of strings for the different site species.
defect_labels (list): List of strings for the different defect species.
Returns:
:obj:`SetOfSites`: Sites interpolated onto a regular grid.
"""

grid = np.linspace(x_min, x_max, n_points)
limits = (grid[1] - grid[0], grid[1] - grid[0])
sites = []
for label, d_label in zip(site_labels, defect_labels):
scaling = len( all_sites.subset(label)) / len(grid)
continuum_grid = Grid(grid, b, c, limits, limits_for_laplacian, all_sites.subset(label))
average_energies = np.array([site.average_local_energy(method='mean')[0] for site in all_sites.subset(label)])
new_energies = griddata(([site.x for site in all_sites.subset(label)]),
average_energies,
grid,
method='nearest')
for x, e in zip(grid, new_energies):
sites.append(Site(label,
x,
[defect_species[d_label]],
[e],
scaling=np.array([scaling])))
return SetOfSites(sites), limits

@ classmethod
def set_of_sites_from_input_data(cls: object,
Expand All @@ -210,14 +219,14 @@ def set_of_sites_from_input_data(cls: object,
offset: float = 0.0) -> SetOfSites:
"""
Takes the data from the input file and creates a SetOfSites object for those sites.
The input data file is a .txt file where each line in the file corresponds to a site. The values in each line are formatted and separated into the corresponding properties before creating a Site object for each site.
The input data file is a .txt file where each line in the file corresponds to a site. The values in each line are formatted and separated into the corresponding properties before creating a Site object for each site.
Args:
filename (str): Name of the input file to be parsed.
limits (list): Minimum and maximum x coordinated defining the calculation region.
defect_species (object): Class object containing information about the defect species present in the system.
site_charge (bool): The site charge refers to the contribution to the overall charge of a site given by the original, non-defective species present at that site. True if the site charge contribution is to be included in the calculation, False if it is not to be included.
core (str): Core definition. 'single' = Single segregation energy used to define the core. 'multi-site' = Layered segregation energies used to define the core while the energies fall in the region of positive and negative kT. 'all' = All sites between a minimum and maximum x coordinate used in calculation.
defect_species (object): Class object containing information about the defect species present in the system.
site_charge (bool): The site charge refers to the contribution to the overall charge of a site given by the original, non-defective species present at that site. True if the site charge contribution is to be included in the calculation, False if it is not to be included.
core (str): Core definition. 'single' = Single segregation energy used to define the core. 'multi-site' = Layered segregation energies used to define the core while the energies fall in the region of positive and negative kT. 'all' = All sites between a minimum and maximum x coordinate used in calculation.
temperature (float): Temperature that the calculation is being run at.
Returns:
Expand All @@ -238,22 +247,23 @@ def set_of_sites_from_input_data(cls: object,
return SetOfSites([site_from_input_file(line, defect_species, site_charge, core, temperature) for line in site_data])

@ classmethod
def core_width_analysis( cls, input_data, limits, defect_species, site_charge, core, temperature ):
def core_width_analysis(cls,
input_data, limits, defect_species, site_charge, core, temperature ):
"""
Calculated the width of the 'core' region. This is given as the region where the segregation energies in the system are within a region of positive to negative kT.
Calculated the width of the 'core' region. This is given as the region where the segregation energies in the system are within a region of positive to negative kT.
Args:
input_data (file): A .txt file where each line includes information about a site.
limits (list): Minimum and maximum x coordinates defining the calculation region.
defect_species (object): Class object containing information about the defect species present in the system.
input_data (file): A .txt file where each line includes information about a site.
limits (list): Minimum and maximum x coordinates defining the calculation region.
defect_species (object): Class object containing information about the defect species present in the system.
site_charge (bool): The site charge refers to the contribution to the overall charge of a site given by the original, non-defective species present at that site. True if the site charge contribution is to be included in the calculation, False if it is not to be included.
core (str): Core definition. Allowed keywords: 'single' = Single segregation energy used to define the core. 'multi-site' = Layered segregation energies used to define the core while the energies fall in the region of positive and negative kT. 'all' = All sites between a minimum and maximum x coordinate used in calculation.
temperature (float): Temperature that the calculation is being run at.
core (str): Core definition. Allowed keywords: 'single' = Single segregation energy used to define the core. 'multi-site' = Layered segregation energies used to define the core while the energies fall in the region of positive and negative kT. 'all' = All sites between a minimum and maximum x coordinate used in calculation.
temperature (float): Temperature that the calculation is being run at.
Returns:
float: Distance between the minimum and maximum x coordinates where the segregation energy is in the range of positive to negative kT.
Returns:
float: Distance between the minimum and maximum x coordinates where the segregation energy is in the range of positive to negative kT.
"""
"""
site_data = load_site_data( input_data, limits[0], limits[1], site_charge )
energies = [ line[4] for line in site_data ]
min_energy = min(energies)
Expand Down
41 changes: 20 additions & 21 deletions pyscses/site.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,7 @@
import numpy as np
import math
from pyscses.constants import fundamental_charge, boltzmann_eV
# from pyscses.grid_point import GridPoint
from pyscses.grid_point import GridPoint
from pyscses.defect_species import DefectSpecies
from typing import List, Optional
from pyscses.defect_at_site import DefectAtSite
Expand Down Expand Up @@ -69,7 +69,7 @@ def __init__(self,
self.scaling = scaling
else:
self.scaling = np.ones_like(defect_energies, dtype=float)
# self.grid_point: Optional[GridPoint] = None
self.grid_point: Optional[GridPoint] = None
self.valence = valence

def defect_with_label(self,
Expand All @@ -92,25 +92,24 @@ def energies(self) -> List[float]:
"""Returns a list of the segregation energies for each defect from self.defects """
return [d.energy for d in self.defects]

# BEN: Does not appear to be used?
# def average_local_energy(self,
# method: str = 'mean') -> Optional[np.ndarray]:
# """
# Returns the average local segregation energy for each site based on a specified method
#
# Args:
# method (str): The method in which the average segregation energies will be calculated.
# 'mean' - Returns the sum of all values at that site divided by the number of values at that site.
# 'min' - Returns the minimum segregation energy value for that site (appropriate for low temperature calculations).
#
# Returns:
# numpy.array: Average segregation energies on the site coordinates grid.
#
# """
# if self.grid_point is not None:
# return self.grid_point.average_site_energy(method)
# else:
# raise ValueError("TODO")
def average_local_energy(self,
method: str = 'mean') -> Optional[np.ndarray]:
"""
Returns the average local segregation energy for each site based on a specified method.
Args:
method (str): The method in which the average segregation energies will be calculated.
'mean' - Returns the sum of all values at that site divided by the number of values at that site.
'min' - Returns the minimum segregation energy value for that site (appropriate for low temperature calculations).
Returns:
numpy.array: Average segregation energies on the site coordinates grid.
"""
if self.grid_point is not None:
return self.grid_point.average_site_energy(method)
else:
raise ValueError("TODO")

def sum_of_boltzmann_three(self,
phi: float,
Expand Down
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