def create_det_eff(obj, **kwargs):
"""
This function creates detector efficiency spectra based on the wavelength
spectra from the given object. The efficiency spectra are created based on
the following formalism: Ci*exp(-di*lambda) where i represents the
constants for a given detector pixel.
@param obj: Object containing spectra that will create the detector
efficiency spectra.
@type obj: C{SOM.SOM} or C{SOM.SO}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword inst_name: The short name of an instrument.
@type inst_name: C{string}
@keyword eff_scale_const: Use this provided efficiency scaling constant.
@type eff_scale_const: L{hlr_utils.DrParameter}
@keyword eff_atten_const: Use this provided efficiency attenuation
constant.
@type eff_atten_const: L{hlr_utils.DrParameter}
@return: Object containing the detector efficiency spectra
@rtype: C{SOM.SOM} or C{SOM.SO}
@raise TypeError: Incoming object is not a C{SOM} or a C{SO}
@raise RuntimeError: The C{SOM} x-axis units are not I{Angstroms}
"""
# Check keywords
inst_name = kwargs.get("inst_name")
eff_scale_const = kwargs.get("eff_scale_const")
eff_atten_const = kwargs.get("eff_atten_const")
# set up for working through data
(result, res_descr) = hlr_utils.empty_result(obj)
o_descr = hlr_utils.get_descr(obj)
if o_descr != "SOM" and o_descr != "SO":
raise TypeError("Only SOM or SO objects permitted to create "\
+"efficiency spectra!")
# Check units on SOM, SO is assumed to be correct
if o_descr == "SOM":
if not obj.hasAxisUnits("Angstroms"):
raise RuntimeError("Incoming object must has a wavelength axis "\
+"with units of Angstroms!")
result = hlr_utils.copy_som_attr(result, res_descr, obj, o_descr)
# iterate through the values
import dr_lib
import phys_corr
import utils
# Get object length
len_obj = hlr_utils.get_length(obj)
for i in xrange(len_obj):
map_so = hlr_utils.get_map_so(obj, None, i)
axis = hlr_utils.get_value(obj, i, o_descr, "x", 0)
if inst_name is None:
axis_bc = utils.calc_bin_centers(axis)
(eff,
eff_err2) = phys_corr.exp_detector_eff(axis_bc[0], 1.0, 0.0, 1.0)
else:
if inst_name == "SANS":
(eff, eff_err2) = dr_lib.subexp_eff(eff_atten_const, axis,
eff_scale_const)
else:
raise RuntimeError("Do not know how to handle %s instrument" \
% inst_name)
hlr_utils.result_insert(result, res_descr, (eff, eff_err2), map_so)
return result
def create_det_eff(obj, **kwargs):
"""
This function creates detector efficiency spectra based on the wavelength
spectra from the given object. The efficiency spectra are created based on
the following formalism: Ci*exp(-di*lambda) where i represents the
constants for a given detector pixel.
@param obj: Object containing spectra that will create the detector
efficiency spectra.
@type obj: C{SOM.SOM} or C{SOM.SO}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword inst_name: The short name of an instrument.
@type inst_name: C{string}
@keyword eff_scale_const: Use this provided efficiency scaling constant.
@type eff_scale_const: L{hlr_utils.DrParameter}
@keyword eff_atten_const: Use this provided efficiency attenuation
constant.
@type eff_atten_const: L{hlr_utils.DrParameter}
@return: Object containing the detector efficiency spectra
@rtype: C{SOM.SOM} or C{SOM.SO}
@raise TypeError: Incoming object is not a C{SOM} or a C{SO}
@raise RuntimeError: The C{SOM} x-axis units are not I{Angstroms}
"""
# Check keywords
inst_name = kwargs.get("inst_name")
eff_scale_const = kwargs.get("eff_scale_const")
eff_atten_const = kwargs.get("eff_atten_const")
# set up for working through data
(result, res_descr) = hlr_utils.empty_result(obj)
o_descr = hlr_utils.get_descr(obj)
if o_descr != "SOM" and o_descr != "SO":
raise TypeError("Only SOM or SO objects permitted to create "\
+"efficiency spectra!")
# Check units on SOM, SO is assumed to be correct
if o_descr == "SOM":
if not obj.hasAxisUnits("Angstroms"):
raise RuntimeError("Incoming object must has a wavelength axis "\
+"with units of Angstroms!")
result = hlr_utils.copy_som_attr(result, res_descr, obj, o_descr)
# iterate through the values
import dr_lib
import phys_corr
import utils
# Get object length
len_obj = hlr_utils.get_length(obj)
for i in xrange(len_obj):
map_so = hlr_utils.get_map_so(obj, None, i)
axis = hlr_utils.get_value(obj, i, o_descr, "x", 0)
if inst_name is None:
axis_bc = utils.calc_bin_centers(axis)
(eff, eff_err2) = phys_corr.exp_detector_eff(axis_bc[0], 1.0,
0.0, 1.0)
else:
if inst_name == "SANS":
(eff, eff_err2) = dr_lib.subexp_eff(eff_atten_const, axis,
eff_scale_const)
else:
raise RuntimeError("Do not know how to handle %s instrument" \
% inst_name)
hlr_utils.result_insert(result, res_descr, (eff, eff_err2), map_so)
return result
def feff_correct_mon(obj, **kwargs):
"""
This function takes in a monitor spectra, calculates efficiencies based on
the montior's wavelength axis and divides the monitor counts by the
calculated efficiencies. The function is a M{constant * wavelength}.
@param obj: Object containing monitor spectra
@type obj: C{SOM.SOM} or C{SOM.SO}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword units: The expected units for this function. The default for this
function is I{Angstroms}.
@type units: C{string}
@keyword eff_const: Use this provided effieciency constant. The default is
(0.00000085 / 1.8) Angstroms^-1.
@type eff_const: L{hlr_utils.DrParameter}
@keyword inst_name: The short name of an instrument.
@type inst_name: C{string}
@return: Efficiency corrected monitor spectra
@rtype: C{SOM.SOM} or C{SOM.SO}
"""
# import the helper functions
import hlr_utils
if obj is None:
return obj
# set up for working through data
(result, res_descr) = hlr_utils.empty_result(obj)
o_descr = hlr_utils.get_descr(obj)
# Setup keyword arguments
try:
units = kwargs["units"]
except KeyError:
units = "Angstroms"
try:
eff_const = kwargs["eff_const"]
except KeyError:
# This is for SNS (specifically BASIS) monitors
eff_const = hlr_utils.DrParameter((0.00000085 / 1.8), 0.0,
"Angstroms^-1") # A^-1
inst_name = kwargs.get("inst_name")
# Primary axis for transformation. If a SO is passed, the function, will
# assume the axis for transformation is at the 0 position
if o_descr == "SOM":
axis = hlr_utils.one_d_units(obj, units)
else:
axis = 0
result = hlr_utils.copy_som_attr(result, res_descr, obj, o_descr)
# iterate through the values
import array_manip
import nessi_list
import dr_lib
for i in xrange(hlr_utils.get_length(obj)):
val = hlr_utils.get_value(obj, i, o_descr, "x", axis)
map_so = hlr_utils.get_map_so(obj, None, i)
if inst_name is None:
eff = nessi_list.NessiList()
for j in xrange(len(val) - 1):
bin_center = (val[j + 1] + val[j]) / 2.0
eff.append(eff_const.getValue() * bin_center)
eff_err2 = nessi_list.NessiList(len(eff))
else:
if inst_name == "SANS":
(eff, eff_err2) = dr_lib.subexp_eff(eff_const, val)
else:
raise RuntimeError("Do not know how to handle %s instrument" \
% inst_name)
y_val = hlr_utils.get_value(obj, i, o_descr, "y")
y_err2 = hlr_utils.get_err2(obj, i, o_descr, "y")
value = array_manip.div_ncerr(y_val, y_err2, eff, eff_err2)
hlr_utils.result_insert(result, res_descr, value, map_so, "y")
return result
def feff_correct_mon(obj, **kwargs):
"""
This function takes in a monitor spectra, calculates efficiencies based on
the montior's wavelength axis and divides the monitor counts by the
calculated efficiencies. The function is a M{constant * wavelength}.
@param obj: Object containing monitor spectra
@type obj: C{SOM.SOM} or C{SOM.SO}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword units: The expected units for this function. The default for this
function is I{Angstroms}.
@type units: C{string}
@keyword eff_const: Use this provided effieciency constant. The default is
(0.00000085 / 1.8) Angstroms^-1.
@type eff_const: L{hlr_utils.DrParameter}
@keyword inst_name: The short name of an instrument.
@type inst_name: C{string}
@return: Efficiency corrected monitor spectra
@rtype: C{SOM.SOM} or C{SOM.SO}
"""
# import the helper functions
import hlr_utils
if obj is None:
return obj
# set up for working through data
(result, res_descr) = hlr_utils.empty_result(obj)
o_descr = hlr_utils.get_descr(obj)
# Setup keyword arguments
try:
units = kwargs["units"]
except KeyError:
units = "Angstroms"
try:
eff_const = kwargs["eff_const"]
except KeyError:
# This is for SNS (specifically BASIS) monitors
eff_const = hlr_utils.DrParameter((0.00000085 / 1.8), 0.0,
"Angstroms^-1") # A^-1
inst_name = kwargs.get("inst_name")
# Primary axis for transformation. If a SO is passed, the function, will
# assume the axis for transformation is at the 0 position
if o_descr == "SOM":
axis = hlr_utils.one_d_units(obj, units)
else:
axis = 0
result = hlr_utils.copy_som_attr(result, res_descr, obj, o_descr)
# iterate through the values
import array_manip
import nessi_list
import dr_lib
for i in xrange(hlr_utils.get_length(obj)):
val = hlr_utils.get_value(obj, i, o_descr, "x", axis)
map_so = hlr_utils.get_map_so(obj, None, i)
if inst_name is None:
eff = nessi_list.NessiList()
for j in xrange(len(val)-1):
bin_center = (val[j+1] + val[j]) / 2.0
eff.append(eff_const.getValue() * bin_center)
eff_err2 = nessi_list.NessiList(len(eff))
else:
if inst_name == "SANS":
(eff, eff_err2) = dr_lib.subexp_eff(eff_const, val)
else:
raise RuntimeError("Do not know how to handle %s instrument" \
% inst_name)
y_val = hlr_utils.get_value(obj, i, o_descr, "y")
y_err2 = hlr_utils.get_err2(obj, i, o_descr, "y")
value = array_manip.div_ncerr(y_val, y_err2, eff, eff_err2)
hlr_utils.result_insert(result, res_descr, value, map_so, "y")
return result
