machine rounding during computation. We expect the values to be close
to the input settings (slope 7, offset -33).
machine rounding during computation. We expect the values to be close
to the input settings (slope 7, offset -33).
>>> m = LinearModel(data, rescale=True)
>>> outqueue = Queue()
>>> slope,offset = m.fit(outqueue=outqueue)
>>> m = LinearModel(data, rescale=True)
>>> outqueue = Queue()
>>> slope,offset = m.fit(outqueue=outqueue)
>>> data = 20*numpy.sin(arange(1000)) + 7.*arange(1000)
>>> m = SingleParameterModel(data)
>>> slope, = m.fit(outqueue=outqueue)
>>> data = 20*numpy.sin(arange(1000)) + 7.*arange(1000)
>>> m = SingleParameterModel(data)
>>> slope, = m.fit(outqueue=outqueue)
# def dist(px,py,linex,liney):
# distancesx=scipy.array([(px-x)**2 for x in linex])
# minindex=numpy.argmin(distancesx)
# def dist(px,py,linex,liney):
# distancesx=scipy.array([(px-x)**2 for x in linex])
# minindex=numpy.argmin(distancesx)