def jitMCQ(self,x,y,jsig, mcp):
from PYME.Analysis.QuadTree import pointQT
Imc = numpy.rand(len(x)) < mcp
qt = pointQT.qtRoot(-250,250, 0, 500)
if type(jsig) == numpy.ndarray:
jsig = jsig[Imc]
for xi, yi in zip(x[Imc] + jsig*numpy.random.normal(size=Imc.sum()), y[Imc] + jsig*numpy.random.normal(size=Imc.sum())):
qt.insert(pointQT.qtRec(xi, yi, None))
self.setQuads(qt, 100, True)
def jitMCQ(self, x, y, jsig, mcp):
from PYME.Analysis.QuadTree import pointQT
Imc = numpy.rand(len(x)) < mcp
qt = pointQT.qtRoot(-250, 250, 0, 500)
if type(jsig) == numpy.ndarray:
jsig = jsig[Imc]
for xi, yi in zip(x[Imc] + jsig * numpy.random.normal(size=Imc.sum()),
y[Imc] + jsig * numpy.random.normal(size=Imc.sum())):
qt.insert(pointQT.qtRec(xi, yi, None))
self.setQuads(qt, 100, True)
def getQuads(self):
from PYME.Analysis.QuadTree import pointQT
di = max(self.imageBounds.x1 - self.imageBounds.x0,
self.imageBounds.y1 - self.imageBounds.y0)
np = di/self.QTGoalPixelSize
di = self.QTGoalPixelSize*2**np.ceil(np.log2(np))
self.Quads = pointQT.qtRoot(self.imageBounds.x0, self.imageBounds.x0+di,
self.imageBounds.y0, self.imageBounds.y0 + di)
for xi, yi in zip(self['x'],self['y']):
self.Quads.insert(pointQT.qtRec(xi,yi, None))
def getQuads(self):
from PYME.Analysis.QuadTree import pointQT
di = max(self.imageBounds.x1 - self.imageBounds.x0,
self.imageBounds.y1 - self.imageBounds.y0)
np = di / self.QTGoalPixelSize
di = self.QTGoalPixelSize * 2**np.ceil(np.log2(np))
self.Quads = pointQT.qtRoot(self.imageBounds.x0,
self.imageBounds.x0 + di,
self.imageBounds.y0,
self.imageBounds.y0 + di)
for xi, yi in zip(self['x'], self['y']):
self.Quads.insert(pointQT.qtRec(xi, yi, None))
