def get_histogram(monitor):
from mcstas2.utils.carray import bpptr2npyarr
core = monitor.core()
nx = core.nx
ny = core.ny
n = nx * ny
shape = nx, ny
# xmin = core.x_min; xmax = core.x_max
# ymin = core.y_min; ymax = core.y_max
xmin = attr(core, "xmin", "x_min")
xmax = attr(core, "xmax", "x_max")
ymin = attr(core, "ymin", "y_min")
ymax = attr(core, "ymax", "y_max")
dx = (xmax - xmin) / nx
dy = (ymax - ymin) / ny
Iarr = bpptr2npyarr(core.getPSD_p_00(), 'double', n).copy()
E2arr = bpptr2npyarr(core.getPSD_p2_00(), 'double', n).copy()
Iarr.shape = E2arr.shape = shape
from histogram import histogram, axis, arange
xaxis = axis('x', arange(xmin, xmax, dx))
yaxis = axis('y', arange(ymin, ymax, dy))
h = histogram('I(x,y)', [xaxis, yaxis], data=Iarr, errors=E2arr)
return h
def get_histogram( monitor ):
from mcstas2.utils.carray import bpptr2npyarr
core = monitor.core()
nx = core.nxchan; ny =core.nychan; nb = core.nbchan
n = nx * ny * nb
shape = nx, ny, nb
xmin = -core.xwidth/2; xmax = core.xwidth/2
ymin = -core.yheight/2; ymax = core.yheight/2
dx = (xmax - xmin)/nx
dy = (ymax - ymin)/ny
if core.bmax!=0:
bmax=core.bmax
bmin=core.bmin
db=(bmax-bmin)/nb
else :
db = core.deltab
bmin=0;
bmax=nb*db+bmin
Iarr = bpptr2npyarr( core.getTOF_p_00( ), 'double', n ).copy()
E2arr = bpptr2npyarr( core.getTOF_p2_00( ), 'double', n ).copy()
Iarr.shape = E2arr.shape = shape
from histogram import histogram, axis, arange
xaxis = axis( 'x', boundaries=arange( xmin, xmax+dx/10, dx ) )
yaxis = axis( 'y', boundaries=arange( ymin, ymax+dy/10, dy ) )
baxis = axis( 'b', boundaries=arange( bmin, bmax+db/10, db ) )
h = histogram(
'I(x,y,b)', [xaxis,yaxis,baxis],
data = Iarr, errors = E2arr )
return h
def get_histogram(monitor):
from mcstas2.utils.carray import bpptr2npyarr
core = monitor.core()
nx = core.nx
ny = core.ny
assert nx == int(nx)
nx = int(nx)
assert ny == int(ny)
ny = int(ny)
n = nx * ny
shape = nx, ny
Iarr = bpptr2npyarr(core.getPSD_p_00(), 'double', n).copy()
E2arr = bpptr2npyarr(core.getPSD_p2_00(), 'double', n).copy()
Iarr.shape = E2arr.shape = shape
from histogram import histogram, axis, arange
dx = 360. / nx
xaxis = axis('x', arange(0, 360, dx), unit='deg')
dy = 180. / ny
yaxis = axis('y', arange(-90, 90, dy), unit='deg')
h = histogram('I(x,y)', [xaxis, yaxis], data=Iarr, errors=E2arr)
return h
def get_histogram( monitor ):
from mcstas2.utils.carray import bpptr2npyarr
core = monitor.core()
nx = core.nx; ny =core.ny
n = nx * ny
shape = nx, ny
# xmin = core.x_min; xmax = core.x_max
# ymin = core.y_min; ymax = core.y_max
xmin = attr(core, "xmin", "x_min");
xmax = attr(core, "xmax", "x_max");
ymin = attr(core, "ymin", "y_min");
ymax = attr(core, "ymax", "y_max");
dx = (xmax - xmin)/nx
dy = (ymax - ymin)/ny
Iarr = bpptr2npyarr( core.getPSD_p_00( ), 'double', n ).copy()
E2arr = bpptr2npyarr( core.getPSD_p2_00( ), 'double', n ).copy()
Iarr.shape = E2arr.shape = shape
from histogram import histogram, axis, arange
xaxis = axis( 'x', arange( xmin, xmax, dx ) )
yaxis = axis( 'y', arange( ymin, ymax, dy ) )
h = histogram( 'I(x,y)', [xaxis,yaxis], data = Iarr, errors = E2arr )
return h
def get_histogram(monitor):
from mcstas2.utils.carray import bpptr2npyarr
core = monitor.core()
n = core.nchan
Iarr = bpptr2npyarr( core.getL_p( ), 'double', n ).copy()
E2arr = bpptr2npyarr( core.getL_p2( ), 'double', n ).copy()
from histogram import histogram, axis, arange
dL = (core.Lmax-core.Lmin)/core.nchan
Laxis = axis( 'wavelength', arange( core.Lmin+dL/2, core.Lmax+dL/2, dL ), unit = 'angstrom' )
h = histogram( 'I(L)', [Laxis], data = Iarr, errors = E2arr )
return h
def get_histogram( monitor ):
from mcstas2.utils.carray import bpptr2npyarr
core = monitor.core()
n = core.nchan
Iarr = bpptr2npyarr( core.getTOF_p( ), 'double', n ).copy()
E2arr = bpptr2npyarr( core.getTOF_p2( ), 'double', n ).copy()
from histogram import histogram, axis, arange
dt = (core.tmax-core.tmin)/core.nchan
taxis = axis( 'tof', arange( core.tmin+dt/2., core.tmax+dt/2-0.1*dt, dt ), unit = 's' )
h = histogram( 'I(tof)', [taxis], data = Iarr, errors = E2arr )
return h
def get_histogram(monitor):
from mcstas2.utils.carray import bpptr2npyarr
core = monitor.core()
n = core.nchan
Iarr = bpptr2npyarr( core.getE_p( ), 'double', n ).copy()
E2arr = bpptr2npyarr( core.getE_p2( ), 'double', n ).copy()
from histogram import histogram, axis, arange
dE = (core.Emax-core.Emin)/core.nchan
Eaxis = axis( 'energy', arange( core.Emin+dE/2, core.Emax, dE ), unit = 'meV' )
h = histogram( 'I(E)', [Eaxis], data = Iarr, errors = E2arr )
return h
def get_histogram(monitor):
from mcstas2.utils.carray import bpptr2npyarr
core = monitor.core()
n = core.nchan
Iarr = bpptr2npyarr(core.getE_p(), 'double', n).copy()
E2arr = bpptr2npyarr(core.getE_p2(), 'double', n).copy()
from histogram import histogram, axis, arange
dE = (core.Emax - core.Emin) / core.nchan
Eaxis = axis('energy',
arange(core.Emin + dE / 2, core.Emax, dE),
unit='meV')
h = histogram('I(E)', [Eaxis], data=Iarr, errors=E2arr)
return h
def get_histogram(monitor):
from mcstas2.utils.carray import bpptr2npyarr
core = monitor.core()
n = core.nchan
Iarr = bpptr2npyarr(core.getL_p(), 'double', n).copy()
E2arr = bpptr2npyarr(core.getL_p2(), 'double', n).copy()
from histogram import histogram, axis, arange
dL = (core.Lmax - core.Lmin) / core.nchan
Laxis = axis('wavelength',
arange(core.Lmin + dL / 2, core.Lmax + dL / 2, dL),
unit='angstrom')
h = histogram('I(L)', [Laxis], data=Iarr, errors=E2arr)
return h
def get_histogram(monitor):
from mcstas2.utils.carray import bpptr2npyarr
core = monitor.core()
n = core.nchan
Iarr = bpptr2npyarr(core.getTOF_p(), 'double', n).copy()
E2arr = bpptr2npyarr(core.getTOF_p2(), 'double', n).copy()
from histogram import histogram, axis, arange
dt = (core.tmax - core.tmin) / core.nchan
taxis = axis('tof',
arange(core.tmin + dt / 2., core.tmax + dt / 2 - 0.1 * dt,
dt),
unit='s')
h = histogram('I(tof)', [taxis], data=Iarr, errors=E2arr)
return h
def get_histogram( monitor ):
from mcstas2.utils.carray import bpptr2npyarr
core = monitor.core()
nQ = core.nQ; nE =core.nE
n = nQ * nE
shape = nQ, nE
Iarr = bpptr2npyarr( core.getIQE_p( ), 'double', n ).copy()
E2arr = bpptr2npyarr( core.getIQE_p2( ), 'double', n ).copy()
Iarr.shape = E2arr.shape = shape
from histogram import histogram, axis, arange
dE = (core.Emax-core.Emin)/nE
Eaxis = axis( 'energy', arange( core.Emin, core.Emax, dE ), unit = 'meV' )
dQ = (core.Qmax-core.Qmin)/nQ
Qaxis = axis( 'Q', arange( core.Qmin, core.Qmax, dQ ), unit = 'angstrom**-1' )
h = histogram( 'I(Q,E)', [Qaxis,Eaxis], data = Iarr, errors = E2arr )
return h
def get_histogram(monitor):
from mcstas2.utils.carray import bpptr2npyarr
core = monitor.core()
nQ = core.nQ
nE = core.nE
n = nQ * nE
shape = nQ, nE
Iarr = bpptr2npyarr(core.getIQE_p(), 'double', n).copy()
E2arr = bpptr2npyarr(core.getIQE_p2(), 'double', n).copy()
Iarr.shape = E2arr.shape = shape
from histogram import histogram, axis, arange
dE = (core.Emax - core.Emin) / nE
Eaxis = axis('energy', arange(core.Emin, core.Emax, dE), unit='meV')
dQ = (core.Qmax - core.Qmin) / nQ
Qaxis = axis('Q', arange(core.Qmin, core.Qmax, dQ), unit='angstrom**-1')
h = histogram('I(Q,E)', [Qaxis, Eaxis], data=Iarr, errors=E2arr)
return h
def get_histogram( monitor ):
from mcstas2.utils.carray import bpptr2npyarr
core = monitor.core()
nx = core.nx; ny =core.ny
assert nx == int(nx); nx = int(nx)
assert ny == int(ny); ny = int(ny)
n = nx * ny
shape = nx, ny
Iarr = bpptr2npyarr( core.getPSD_p_00( ), 'double', n ).copy()
E2arr = bpptr2npyarr( core.getPSD_p2_00( ), 'double', n ).copy()
Iarr.shape = E2arr.shape = shape
from histogram import histogram, axis, arange
dx = 360./nx
xaxis = axis( 'x', arange( 0, 360, dx ), unit = 'deg' )
dy = 180./ny
yaxis = axis( 'y', arange( -90, 90, dy ), unit = 'deg' )
h = histogram( 'I(x,y)', [xaxis,yaxis], data = Iarr, errors = E2arr )
return h
def get_histogram(monitor):
from mcstas2.utils.carray import bpptr2npyarr
core = monitor.core()
nx = core.nxchan
ny = core.nychan
nb = core.nbchan
n = nx * ny * nb
shape = nx, ny, nb
xmin = -core.xwidth / 2
xmax = core.xwidth / 2
ymin = -core.yheight / 2
ymax = core.yheight / 2
dx = (xmax - xmin) / nx
dy = (ymax - ymin) / ny
if core.bmax != 0:
bmax = core.bmax
bmin = core.bmin
db = (bmax - bmin) / nb
else:
db = core.deltab
bmin = 0
bmax = nb * db + bmin
Iarr = bpptr2npyarr(core.getTOF_p_00(), 'double', n).copy()
E2arr = bpptr2npyarr(core.getTOF_p2_00(), 'double', n).copy()
Iarr.shape = E2arr.shape = shape
from histogram import histogram, axis, arange
xaxis = axis('x', boundaries=arange(xmin, xmax + dx / 10, dx))
yaxis = axis('y', boundaries=arange(ymin, ymax + dy / 10, dy))
baxis = axis('b', boundaries=arange(bmin, bmax + db / 10, db))
h = histogram('I(x,y,b)', [xaxis, yaxis, baxis], data=Iarr, errors=E2arr)
return h
