def test(self):
a = numpy.arange(12, dtype = numpy.double)
a.shape = 3,4
ptr = numpyext.getdataptr( a )
wp = bpext.wrap_native_ptr( ptr )
shape = mccomponentsbp.vector_uint( 0 )
for i in a.shape: shape.append( i )
a1 = mccomponentsbp.new_NdArray_dblarr_2( wp, shape )
a1.origin = a
indexes = mccomponentsbp.vector_uint( 0 )
indexes.append( 2 ); indexes.append( 1 )
self.assertEqual( a1[ indexes ], 9 )
return
def eventmodemca( self, outfilename, detectorDims ):
'''eventmodemca( outfilename, detectorDims ): new event-mode mca
outfilename: output file name
detectorDims: detector dimensions.
For example, if a detectory system has 15 packs, 8 tubes per pack, 128 pixels per tube, then
detectorDims = 15,8,128
'''
dims = b.vector_uint( 0 )
for dim in detectorDims: dims.append(dim)
return b.EventModeMCA( outfilename, dims )
def eventmodemca(self, outfilename, detectorDims):
'''eventmodemca( outfilename, detectorDims ): new event-mode mca
outfilename: output file name
detectorDims: detector dimensions.
For example, if a detectory system has 15 packs, 8 tubes per pack, 128 pixels per tube, then
detectorDims = 15,8,128
'''
dims = b.vector_uint(0)
for dim in detectorDims:
dims.append(dim)
return b.EventModeMCA(outfilename, dims)
def test(self):
import numpyext
import numpy
a = numpy.arange(12, dtype=numpy.double)
a.shape = 3, 4
ptr = numpyext.getdataptr(a)
import bpext
wp = bpext.wrap_native_ptr(ptr)
shape = mccomponentsbp.vector_uint(0)
for i in a.shape:
shape.append(i)
a1 = mccomponentsbp.new_NdArray_dblarr_2(wp, shape)
a1.origin = a
indexes = mccomponentsbp.vector_uint(0)
indexes.append(2)
indexes.append(1)
self.assertEqual(a1[indexes], 9)
return
def ndarray( self, npyarr ):
'''create boost python instance of NdArray object
arguments:
npyarr: numpy array. it must be a contiguous array.
'''
assert npyarr.dtype == numpy.double, "only work for double array for this time"
ptr = numpyext.getdataptr( npyarr )
wp = bpext.wrap_native_ptr( ptr )
shape = b.vector_uint( 0 )
for i in npyarr.shape: shape.append( i )
factory = 'new_NdArray_dblarr_%d' % len(shape)
a1 = getattr(b,factory)( wp, shape )
a1.origin = npyarr # keep a reference to avoid seg fault
return a1
def test(self):
npixels = 100
detlength = 1. # meter
tofmin = 1000.
tofmax = 3000.
tofstep = 1.
detID = 23
atm = 1.013e5
pressure = 10 * atm
prob = 3.3
tof = 2000
t2c = mccomponentsbp.Tof2Channel(tofmin, tofmax, tofstep)
z_direction = mccompositebp.Vector(0, 0, 1)
pixel0 = mccompositebp.Vector(0, 0, -0.5)
z2c = mccomponentsbp.Z2Channel(detlength, npixels, z_direction, pixel0)
datafile = "test.out"
dims = mccomponentsbp.vector_uint(0)
dims.append(
detID + 1
) # The first dimension is for detectors. must be larger than the largest number of detector IDs.
dims.append(npixels)
mca = mccomponentsbp.EventModeMCA(datafile, dims)
tube_channels = mccomponentsbp.vector_int(0)
tube_channels.append(detID)
tube = mccomponentsbp.He3TubeKernel(pressure, tube_channels, z2c, t2c,
mca)
event = mcni.neutron(r=(0, 0, 0.001), prob=prob, time=tof)
tube.absorb(event)
del tube, mca
s = open(datafile).read()
import struct
pixelID, tofChannelNo, prob1 = struct.unpack('IId', s)
self.assertEqual(pixelID, detID * npixels + npixels / 2)
self.assertEqual(tofChannelNo, (tof - tofmin) / tofstep)
self.assertEqual(prob, prob1)
return
def ndarray( self, npyarr ):
'''create boost python instance of NdArray object
arguments:
npyarr: numpy array. it must be a contiguous array.
'''
assert npyarr.dtype == numpy.double, "only work for double array for this time"
import numpyext
ptr = numpyext.getdataptr( npyarr )
import bpext
wp = bpext.wrap_native_ptr( ptr )
shape = b.vector_uint( 0 )
for i in npyarr.shape: shape.append( i )
factory = 'new_NdArray_dblarr_%d' % len(shape)
a1 = getattr(b,factory)( wp, shape )
a1.origin = npyarr # keep a reference to avoid seg fault
return a1
def test(self):
npixels = 100
detlength = 1. # meter
tofmin = 1000. ; tofmax = 3000.; tofstep = 1.
detID = 23
atm = 1.013e5
pressure = 10 * atm
prob = 3.3
tof = 2000
t2c = mccomponentsbp.Tof2Channel(tofmin, tofmax, tofstep)
z_direction = mccompositebp.Vector(0,0,1)
pixel0 = mccompositebp.Vector(0,0,-0.5)
z2c = mccomponentsbp.Z2Channel(detlength, npixels, z_direction, pixel0)
datafile = "test.out"
dims = mccomponentsbp.vector_uint(0)
dims.append( detID+1 ) # The first dimension is for detectors. must be larger than the largest number of detector IDs.
dims.append( npixels )
mca = mccomponentsbp.EventModeMCA( datafile, dims )
tube_channels = mccomponentsbp.vector_int(0)
tube_channels.append( detID )
tube = mccomponentsbp.He3TubeKernel( pressure, tube_channels, z2c, t2c, mca);
event = mcni.neutron( r = (0,0,0.001), prob = prob, time = tof )
tube.absorb( event );
del tube, mca
s = open( datafile ).read()
import struct
pixelID, tofChannelNo, prob1 = struct.unpack( 'IId', s )
self.assertEqual( pixelID, detID * npixels + npixels/2 )
self.assertEqual( tofChannelNo, (tof-tofmin)/tofstep)
self.assertEqual( prob, prob1 )
return
def bp_ndarray_getitem(self, indexes):
import mccomponents.mccomponentsbp as binding
cindexes = binding.vector_uint( 0 )
for ind in indexes: cindexes.append( ind )
return self._getitem_bp( cindexes )
def bp_ndarray_getitem(self, indexes):
cindexes = b.vector_uint( 0 )
for ind in indexes: cindexes.append( ind )
return self._getitem_bp( cindexes )
def bp_eventmodemca( self, outfilename, detectorDims ):
import mccomponents.mccomponentsbp as b
dims = b.vector_uint( 0 )
for dim in detectorDims: dims.append(dim)
return b.EventModeMCA( outfilename, dims )
def test(self):
dims = mccomponentsbp.vector_uint( 0 )
dims.append( 100 )
mca = mccomponentsbp.EventModeMCA( "test.out", dims )
return
def bp_ndarray_getitem(self, indexes):
import mccomponents.mccomponentsbp as binding
cindexes = binding.vector_uint(0)
for ind in indexes:
cindexes.append(ind)
return self._getitem_bp(cindexes)
def test(self):
dims = mccomponentsbp.vector_uint(0)
dims.append(100)
mca = mccomponentsbp.EventModeMCA("test.out", dims)
return
