本文整理匯總了Python中zeobuilder.actions.composed.Parameters.interval_b方法的典型用法代碼示例。如果您正苦於以下問題：Python Parameters.interval_b方法的具體用法？Python Parameters.interval_b怎麽用？Python Parameters.interval_b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zeobuilder.actions.composed.Parameters的用法示例。
在下文中一共展示了Parameters.interval_b方法的2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: fn
# 需要導入模塊: from zeobuilder.actions.composed import Parameters [as 別名]
# 或者: from zeobuilder.actions.composed.Parameters import interval_b [as 別名]
def fn():
context.application.model.file_open("test/input/silica_layer.zml")
parameters = Parameters()
parameters.interval_a = numpy.array([0.0, 3.0], float)
parameters.interval_b = numpy.array([0.0, 3.0], float)
UnitCellToCluster = context.application.plugins.get_action("UnitCellToCluster")
assert UnitCellToCluster.analyze_selection(parameters)
UnitCellToCluster(parameters)
crd_cluster = [node.transformation.t for node in context.application.model.universe.children]
context.application.model.file_open("test/input/silica_layer.zml")
parameters = Parameters()
parameters.repetitions_a = 3
parameters.repetitions_b = 3
SuperCell = context.application.plugins.get_action("SuperCell")
assert SuperCell.analyze_selection(parameters)
SuperCell(parameters)
crd_super = [node.transformation.t for node in context.application.model.universe.children]
# check that the number of atoms is the same
assert len(crd_super) == len(crd_cluster)
# check if the coordinates match
for c_super in crd_super:
for i in xrange(len(crd_cluster)):
c_cluster = crd_cluster[i]
delta = c_cluster - c_super
delta = context.application.model.universe.shortest_vector(delta)
if numpy.linalg.norm(delta) < 1e-3:
del crd_cluster[i]
break
assert len(crd_cluster) == 0示例2: default_parameters
# 需要導入模塊: from zeobuilder.actions.composed import Parameters [as 別名]
# 或者: from zeobuilder.actions.composed.Parameters import interval_b [as 別名]
def default_parameters(cls):
result = Parameters()
universe = context.application.model.universe
if universe.cell.active[0]:
result.interval_a = numpy.array([0.0, universe.repetitions[0]], float)
if universe.cell.active[1]:
result.interval_b = numpy.array([0.0, universe.repetitions[1]], float)
if universe.cell.active[2]:
result.interval_c = numpy.array([0.0, universe.repetitions[2]], float)
return result