本文整理匯總了Python中thunder.ThunderContext.makeExample方法的典型用法代碼示例。如果您正苦於以下問題：Python ThunderContext.makeExample方法的具體用法？Python ThunderContext.makeExample怎麽用？Python ThunderContext.makeExample使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類thunder.ThunderContext的用法示例。
在下文中一共展示了ThunderContext.makeExample方法的4個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: test_sima
# 需要導入模塊: from thunder import ThunderContext [as 別名]
# 或者: from thunder.ThunderContext import makeExample [as 別名]
def test_sima(self):
"""
(BlockMethod) with SIMA strategy
"""
# NOTE: this test was brittle and failed non-deterministically with any
# more than one source
import sima.segment
# construct the SIMA strategy
simaStrategy = sima.segment.STICA(components=1)
simaStrategy.append(sima.segment.SparseROIsFromMasks(min_size=20))
simaStrategy.append(sima.segment.SmoothROIBoundaries())
simaStrategy.append(sima.segment.MergeOverlapping(threshold=0.5))
tsc = ThunderContext(self.sc)
data = tsc.makeExample('sources', dims=(60, 60), centers=[[20, 15]], noise=0.5, seed=42)
# create and fit the thunder extraction strategy
strategy = SourceExtraction('sima', simaStrategy=simaStrategy)
model = strategy.fit(data, size=(30, 30))
assert(model.count == 1)
# check that the one center is recovered
ep = 1.5
assert(model[0].distance([20, 15]) < ep)示例2: test_local_max
# 需要導入模塊: from thunder import ThunderContext [as 別名]
# 或者: from thunder.ThunderContext import makeExample [as 別名]
def test_local_max(self):
"""
(FeatureMethod) localmax with defaults
"""
tsc = ThunderContext(self.sc)
data = tsc.makeExample('sources', dims=[60, 60], centers=[[10, 10], [40, 40]], noise=0.0, seed=42)
model = SourceExtraction('localmax').fit(data)
# order is irrelevant, but one of these must be true
cond1 = (model[0].distance([10, 10]) == 0) and (model[1].distance([40, 40]) == 0)
cond2 = (model[0].distance([40, 40]) == 0) and (model[1].distance([10, 10]) == 0)
assert(cond1 or cond2)示例3: test_nmf
# 需要導入模塊: from thunder import ThunderContext [as 別名]
# 或者: from thunder.ThunderContext import makeExample [as 別名]
def test_nmf(self):
"""
(BlockMethod) nmf with defaults
"""
tsc = ThunderContext(self.sc)
data = tsc.makeExample('sources', dims=(60, 60), centers=[[20, 20], [40, 40]], noise=0.1, seed=42)
model = SourceExtraction('nmf', componentsPerBlock=1).fit(data, size=(30, 30))
# order is irrelevant, but one of these must be true
ep = 0.50
cond1 = (model[0].distance([20, 20]) < ep) and (model[1].distance([40, 40]) < ep)
cond2 = (model[0].distance([40, 40]) < ep) and (model[1].distance([20, 20]) < ep)
assert(cond1 or cond2)示例4: test_sima
# 需要導入模塊: from thunder import ThunderContext [as 別名]
# 或者: from thunder.ThunderContext import makeExample [as 別名]
def test_sima(self):
"""
(BlockMethod) with SIMA strategy
"""
import sima.segment
# construct the SIMA strategy
simaStrategy = sima.segment.STICA(components=2)
simaStrategy.append(sima.segment.SparseROIsFromMasks(min_size=20))
simaStrategy.append(sima.segment.SmoothROIBoundaries())
simaStrategy.append(sima.segment.MergeOverlapping(threshold=0.5))
tsc = ThunderContext(self.sc)
data = tsc.makeExample('sources', dims=(60, 60), centers=[[20, 15], [40, 45]], noise=0.1, seed=42)
# create and fit the thunder extraction strategy
strategy = SourceExtraction('sima', simaStrategy=simaStrategy)
model = strategy.fit(data, size=(30, 30))
# order is irrelevant, but one of these must be true
ep = 1.5
cond1 = (model[0].distance([20, 15]) < ep) and (model[1].distance([40, 45]) < ep)
cond2 = (model[1].distance([20, 15]) < ep) and (model[0].distance([40, 45]) < ep)
assert(cond1 or cond2)