def tvbdRun(initialGrid, energyList, Eam, nIterations, gridLength, dimensions,
alloyFraction, temp):
alloyGrid, energyList = srf.runSim(initialGrid, energyList, temp, Eam,
nIterations, gridLength, dimensions)
randomMeasure2, actualList, binList = sref.getOrder(
alloyGrid, alloyFraction, dimensions)
return actualList, binList
def tvRun(initialGrid, eList, j, localEam, nIterationsPerSim, gridLength,
dimensions, alloyFraction, runNum):
gridNew, eList = srf.runSim(initialGrid, eList, j, localEam,
nIterationsPerSim, gridLength, dimensions)
currentOrderValue, actualList, binList = sref.getOrder(
gridNew, alloyFraction, dimensions)
return currentOrderValue
def cvRun(gridLength, alloyFraction, dimensions, eList, T, localEam,
nIterationsPerSim):
grid = srf.initializeGrid(gridLength, alloyFraction, dimensions)
grid, eList = srf.runSim(grid, eList, T, localEam, nIterationsPerSim,
gridLength, dimensions)
currentOrderValue, actualList, binList = sref.getOrder(
grid, alloyFraction, dimensions)
return currentOrderValue
def standardRun(nIterations=3000000,
gridLength=40,
alloyFraction=50,
Eam=0.1,
T=300,
dimensions=2,
showMatrixImages=True):
"""Runs through simulation for one set of parameters"""
alloyGrid = srf.initializeGrid(gridLength, alloyFraction, dimensions)
# Sets up list list to take current system energy as simulation progresses
energyList = [0] * (nIterations + 1)
energyList[0] = sref.getTotalEnergy(alloyGrid, Eam, dimensions)
if showMatrixImages and dimensions == 2:
# Display initial matrix
pyplot.figure(num="Initial config")
img1 = pyplot.imshow(alloyGrid, interpolation='nearest')
pyplot.colorbar(img1)
orderMeasure1, actualList, binList = sref.getOrder(alloyGrid,
alloyFraction,
dimensions)
print("Initial order is: {}".format(str(orderMeasure1)))
alloyGrid, energyList = srf.runSim(alloyGrid, energyList, T, Eam,
nIterations, gridLength, dimensions)
if showMatrixImages and dimensions == 2:
# Display matrix in prettier form, as a coloured graph
pyplot.figure(num="Final config")
img2 = pyplot.imshow(alloyGrid, interpolation='nearest')
pyplot.colorbar(img2)
pyplot.show()
orderMeasure2, actualList, binList = sref.getOrder(alloyGrid,
alloyFraction,
dimensions)
print("Final order is: {}".format(str(orderMeasure2)))
def getOrderTest(dimensions):
gridLength = 20
comp = 40
ranGrid = srf.initializeGrid(gridLength, comp, dimensions)
nForeignAtoms = int(comp * 0.01 * gridLength**dimensions)
orderedGrid = np.zeros([gridLength] * dimensions)
numAdded = 0
try: # try, except statement creates ordered grid (2 blocks)
for i in range(gridLength):
for j in range(gridLength):
if dimensions == 2:
orderedGrid[i, j] = 1
numAdded += 1
elif dimensions == 3:
for k in range(gridLength):
orderedGrid[i, j, k] = 1
numAdded += 1
assert (numAdded < nForeignAtoms)
except (AssertionError
): # exception raised simply means we should stop adding
# atoms, not that there is a problem
pass
if dimensions == 2:
# shows ordered grid to show that we are testing an ordered grid
pyplot.figure(num="orderedGrid")
tempImg = pyplot.imshow(orderedGrid, interpolation='nearest')
pyplot.colorbar(tempImg)
pyplot.show()
ranRan, actualList, binList = sref.getOrder(ranGrid, comp, dimensions)
ranOrd, actualList, binList = sref.getOrder(orderedGrid, comp, dimensions)
# ranRan should be much lower than ranOrd
if ranRan < 0.2 * ranOrd:
print(
"CORRECT: random and ordered grids produces correct orderValues.")
print("The order value for the random grid is: {}".format(str(ranRan)))
print("The order value for the random grid is: {}".format(str(ranOrd)))
def createBarDistribution(gridLength=40,
alloyFraction=50,
nIterations=3000000,
Eam=0.1,
T=300,
dimensions=2):
alloyGrid = srf.initializeGrid(gridLength, alloyFraction, dimensions)
# Sets up list to take current system energy as simulation progresses
energyList = [0] * (nIterations + 1)
energyList[0] = sref.getTotalEnergy(alloyGrid, Eam, dimensions)
alloyGrid, energyList = srf.runSim(alloyGrid, energyList, T, Eam,
nIterations, gridLength, dimensions)
randomMeasure2, actualList, binList = sref.getOrder(
alloyGrid, alloyFraction, dimensions)
trace1 = plotly.graph_objs.Bar(
x=[str(i) for i in range(dimensions * 2 + 1)],
y=actualList,
name='actualDistribution')
trace2 = plotly.graph_objs.Bar(
x=[str(i) for i in range(dimensions * 2 + 1)],
y=binList,
name='binomialDistribution')
data = [trace1, trace2]
layout = plotly.graph_objs.Layout(
barmode='group',
xaxis=dict(title='No. of unlike neighbours',
titlefont=dict(family='Courier New, monospace',
size=18,
color='#7f7f7f')),
yaxis=dict(title='Frequency',
titlefont=dict(family='Courier New, monospace',
size=18,
color='#7f7f7f')))
fig = plotly.graph_objs.Figure(data=data, layout=layout)
plotly.offline.plot(
fig,
filename="""barDistribution [gL={}, n={}, comp={}, Eam={},
T={}, dimensions={}].html""".format(str(gridLength), str(nIterations),
str(alloyFraction / 100.0), str(Eam),
str(T), str(dimensions)).replace(
'\n', '').replace('\t', ''))
def initializeGridTest(dimensions):
"""tests if intial grid is random and displays intial grid"""
gridLength, alloyFraction = 20, 50
grid = srf.initializeGrid(gridLength, alloyFraction, dimensions)
# checks order of inital grid
result, actualList, binList = sref.getOrder(grid, alloyFraction,
dimensions)
if result > gridLength * 0.1:
print("CORRECT: initializeGrid produces random grid")
else:
print(
"""ERROR: initializeGrid most likely does NOT produce a random grid. Run 1
more time to make sure.""")
if dimensions == 2:
# displays intial grid, if 2D
pyplot.figure(num="Initial Grid Test")
img = pyplot.imshow(grid, interpolation='nearest')
pyplot.colorbar(img)
pyplot.show()
def createTempVaryingBarDistribution(gridLength=40,
alloyFraction=50,
nIterations=3000000,
Eam=0.1,
tempList=[300, 1000, 3000, 5000],
dimensions=2,
multiProcess=True):
initialGrid = srf.initializeGrid(gridLength, alloyFraction, dimensions)
# Sets up list to take current system energy as simulation progresses
energyList = [0] * (nIterations + 1)
energyList[0] = sref.getTotalEnergy(initialGrid, Eam, dimensions)
if multiProcess:
p = Pool(processes=10)
mainPartial = partial(tvbdRun, initialGrid, energyList, Eam,
nIterations, gridLength, dimensions,
alloyFraction)
combined_lists = p.map(mainPartial, tempList)
traceList = [i[0] for i in combined_lists]
binList = combined_lists[-1][1]
else:
traceList = [0] * len(tempList)
for i, j in enumerate(tempList):
alloyGrid, energyList = srf.runSim(initialGrid, energyList, j, Eam,
nIterations, gridLength,
dimensions)
randomMeasure2, actualList, binList = sref.getOrder(
alloyGrid, alloyFraction, dimensions)
traceList[i] = actualList
xTraceList = str([str(i) for i in range(dimensions * 2 + 1)])
traceObjs = []
for i, j in enumerate(traceList):
traceObjs.append(
plotly.graph_objs.Bar(x=eval(xTraceList),
y=j,
name=str(tempList[i]) + " K"))
traceObjs.append(
plotly.graph_objs.Bar(x=xTraceList,
y=binList,
name='Binomial Distribution'))
layout = plotly.graph_objs.Layout(
barmode='group',
xaxis=dict(title='No. of unlike neighbours',
titlefont=dict(family='Courier New, monospace',
size=18,
color='#7f7f7f')),
yaxis=dict(title='Frequency',
titlefont=dict(family='Courier New, monospace',
size=18,
color='#7f7f7f')))
fig = plotly.graph_objs.Figure(data=traceObjs, layout=layout)
plotly.offline.plot(
fig,
filename="""tempVaryingBarDistribution [gL={}, n={}, comp={},Eam={},
dimensions={}].html""".format(str(gridLength), str(nIterations),
str(alloyFraction / 100.0), str(Eam),
str(dimensions)).replace('\n',
'').replace('\t', ''))