本文整理汇总了Python中augustus.core.NumpyInterface.NP.max方法的典型用法代码示例。如果您正苦于以下问题：Python NP.max方法的具体用法？Python NP.max怎么用？Python NP.max使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类augustus.core.NumpyInterface.NP的用法示例。
在下文中一共展示了NP.max方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: prepare
# 需要导入模块: from augustus.core.NumpyInterface import NP [as 别名]
# 或者: from augustus.core.NumpyInterface.NP import max [as 别名]
#.........这里部分代码省略.........
xarray[0] = 0.0
xarray = NP("cumsum", xarray)
dxarray, dyarray = None, None
if dxdataColumn is not None:
dxarray = dxdataColumn.data[selection]
if dydataColumn is not None:
dyarray = dydataColumn.data[selection]
xfieldType = self.xfieldType
yfieldType = ydataColumn.fieldType
elif len(nx) == 1 and len(ny) == 1:
performanceTable.pause("PlotCurve prepare")
xdataColumn = nx[0].evaluate(dataTable, functionTable, performanceTable)
ydataColumn = ny[0].evaluate(dataTable, functionTable, performanceTable)
performanceTable.unpause("PlotCurve prepare")
if len(cutExpression) == 1:
performanceTable.pause("PlotCurve prepare")
selection = cutExpression[0].select(dataTable, functionTable, performanceTable)
performanceTable.unpause("PlotCurve prepare")
else:
selection = NP("ones", len(ydataColumn.data), NP.dtype(bool))
if xdataColumn.mask is not None:
selection = NP("logical_and", selection, NP(xdataColumn.mask == defs.VALID), selection)
if ydataColumn.mask is not None:
selection = NP("logical_and", selection, NP(ydataColumn.mask == defs.VALID), selection)
if dxdataColumn is not None and dxdataColumn.mask is not None:
selection = NP("logical_and", selection, NP(dxdataColumn.mask == defs.VALID), selection)
if dydataColumn is not None and dydataColumn.mask is not None:
selection = NP("logical_and", selection, NP(dydataColumn.mask == defs.VALID), selection)
xarray = xdataColumn.data[selection]
yarray = ydataColumn.data[selection]
dxarray, dyarray = None, None
if dxdataColumn is not None:
dxarray = dxdataColumn.data[selection]
if dydataColumn is not None:
dyarray = dydataColumn.data[selection]
xfieldType = xdataColumn.fieldType
yfieldType = ydataColumn.fieldType
else:
raise defs.PmmlValidationError("The only allowed combinations of PlotNumericExpressions are: \"y(x)\" and \"x(t) y(t)\"")
persistentState = {}
stateId = self.get("stateId")
if stateId is not None:
if stateId in dataTable.state:
persistentState = dataTable.state[stateId]
xarray = NP("concatenate", [xarray, persistentState["x"]])
yarray = NP("concatenate", [yarray, persistentState["y"]])
if dxarray is not None:
dxarray = NP("concatenate", [dxarray, persistentState["dx"]])
if dyarray is not None:
dyarray = NP("concatenate", [dyarray, persistentState["dy"]])
else:
dataTable.state[stateId] = persistentState
persistentState["x"] = xarray
persistentState["y"] = yarray
if dxarray is not None:
persistentState["dx"] = dxarray
if dyarray is not None:
persistentState["dy"] = dyarray
smooth = self.get("smooth", defaultFromXsd=True, convertType=True)
if not smooth:
if dyarray is not None and dxarray is None:
dxarray = NP((NP("roll", xarray, -1) - NP("roll", xarray, 1)) / 2.0)
dyarray = dyarray * dxarray
loop = self.get("loop", defaultFromXsd=True, convertType=True)
if dxarray is not None and not loop:
dxarray[0] = 0.0
dxarray[-1] = 0.0
if dyarray is not None and not loop:
dyarray[0] = 0.0
dyarray[-1] = 0.0
state.x = xarray
state.y = yarray
state.dx = dxarray
state.dy = dyarray
else:
smoothingScale = self.get("smoothingScale", defaultFromXsd=True, convertType=True)
loop = self.get("loop", defaultFromXsd=True, convertType=True)
samples = self.generateSamples(xarray.min(), xarray.max())
state.x, state.y, state.dx, state.dy = self.pointsToSmoothCurve(xarray, yarray, samples, smoothingScale, loop)
if plotRange is not None:
plotRange.expand(state.x, state.y, xfieldType, yfieldType)
performanceTable.end("PlotCurve prepare")