def rebin_monitor(obj1, obj2, **kwargs):
"""
This function takes objects (1st is the monitor, 2nd is the detector data)
and rebins the data for obj1 onto the axis provided by obj2. The pixel ID
can be transferred as the pixel ID of the rebinned monitor histogram. A
prefix is placed on the bank ID to dilineate that this is a rebinned
monitor spectrum for that pixel.
@param obj1: Monitor object that will be rebinned
@type obj1: C{SOM.SOM} or C{SOM.SO}
@param obj2: Detector data object that will provide the axis for rebinning
@type obj2: C{SOM.SOM} or C{SOM.SO}
@param kwargs: A list of keyword arguments that the function accepts
@keyword use_pix_id: A flag that specifies if the pixel ID is to be used
in the rebinned monitor spectrum. The default is I{False}.
@type use_pix_id: C{boolean}
@keyword prefix: Allows one to specify a prefix for the bank ID. The
default is I{m}.
@type prefix: C{string}
@keyword rtype: A short string that defines the rebinning function to use.
The default is I{None} which uses
L{common_lib.rebin_axis_1D()}. The other possibilities are
I{linint} which uses L{common_lib.rebin_axis_1D_linint()}
and I{frac} which uses L{common_lib.rebin_axis_1D_frac()}.
@type rtype: C{boolean}
@return: Object that has been rebinned
@rtype: C{SOM.SOM} or C{SOM.SO}
@raise TypeError: The C{SOM}-C{SO} operation is attempted
@raise TypeError: The C{SO}-C{SOM} operation is attempted
@raise TypeError: obj1 not a C{SOM} or C{SO}
@raise TypeError: obj2 not a C{SOM} or C{SO}
"""
# import the helper functions
import hlr_utils
# Kickout if monitor object is None
if obj1 is None:
return obj1
# set up for working through data
(result, res_descr) = hlr_utils.empty_result(obj1, obj2)
(o1_descr, o2_descr) = hlr_utils.get_descr(obj1, obj2)
# error checking for types
if o1_descr == "SOM" and o2_descr == "SO":
raise TypeError, "SOM-SO operation not supported"
elif o1_descr == "SO" and o2_descr == "SOM":
raise TypeError("SO-SOM operation not supported")
# Have the right object combination, go on
else:
pass
# Check for keywords
try:
prefix = kwargs["prefix"]
except KeyError:
prefix = "m"
try:
use_pix_id = kwargs["use_pix_id"]
except KeyError:
use_pix_id = False
try:
rtype = kwargs["rtype"]
except KeyError:
rtype = None
# Set the name of the rebinning function
rebin_function_name = "rebin_axis_1D"
if rtype is not None:
rebin_function_name += "_" + str(rtype)
# Get function pointer
import common_lib
rebin_function = common_lib.__getattribute__(rebin_function_name)
result = hlr_utils.copy_som_attr(result, res_descr, obj1, o1_descr)
# iterate through the values
val1 = hlr_utils.get_value(obj1, 0, o1_descr, "all")
# Cache length
len_obj2 = hlr_utils.get_length(obj2)
for i in xrange(len_obj2):
val2 = hlr_utils.get_value(obj2, i, o2_descr, "x")
value = rebin_function(val1, val2)
if use_pix_id:
# Set the pixel ID to the spectrum with modified bank ID
try:
value.id = (prefix+obj2[i].id[0],
(obj2[i].id[1][0], obj2[i].id[1][1]))
except TypeError:
value.id = prefix+str(obj2[i].id)
hlr_utils.result_insert(result, res_descr, value, None, "all")
return result
def convert_single_to_list(funcname, number, som, **kwargs):
"""
This function retrieves a function object from the L{common_lib} set of
functions that provide axis transformations and converts the provided
number based on that function. Instrument geometry information needs to be
provided via the C{SOM}. The following is the list of functions supported
by this one.
- d_spacing_to_tof_focused_det
- energy_to_wavelength
- frequency_to_energy
- initial_wavelength_igs_lin_time_zero_to_tof
- init_scatt_wavevector_to_scalar_Q
- tof_to_initial_wavelength_igs_lin_time_zero
- tof_to_initial_wavelength_igs
- tof_to_scalar_Q
- tof_to_wavelength_lin_time_zero
- tof_to_wavelength
- wavelength_to_d_spacing
- wavelength_to_energy
- wavelength_to_scalar_k
- wavelength_to_scalar_Q
@param funcname: The name of the axis conversion function to use
@type funcname: C{string}
@param number: The value and error^2 to convert
@type number: C{tuple}
@param som: The object containing geometry and other special information
@type som: C{SOM.SOM}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword inst_param: The type of parameter requested from an associated
instrument. For this function the acceptable
parameters are I{primary}, I{secondary} and I{total}.
Default is I{primary}.
@type inst_param: C{string}
@keyword pixel_id: The pixel ID from which the geometry information will
be retrieved from the instrument
@type pixel_id: C{tuple}=(\"bankN\", (x, y))
@return: A converted number for every unique spectrum
@rtype: C{list} of C{tuple}s
@raise AttributeError: The requested function is not in the approved
list
"""
# Setup supported function list and check to see if funcname is available
function_list = []
function_list.append("d_spacing_to_tof_focused_det")
function_list.append("energy_to_wavelength")
function_list.append("frequency_to_energy")
function_list.append("initial_wavelength_igs_lin_time_zero_to_tof")
function_list.append("init_scatt_wavevector_to_scalar_Q")
function_list.append("tof_to_initial_wavelength_igs_lin_time_zero")
function_list.append("tof_to_initial_wavelength_igs")
function_list.append("tof_to_scalar_Q")
function_list.append("tof_to_wavelength_lin_time_zero")
function_list.append("tof_to_wavelength")
function_list.append("wavelength_to_d_spacing")
function_list.append("wavelength_to_energy")
function_list.append("wavelength_to_scalar_k")
function_list.append("wavelength_to_scalar_Q")
if funcname not in function_list:
raise AttributeError("Function %s is not supported by "\
+"convert_single_to_list" % funcname)
import common_lib
# Get the common_lib function object
func = common_lib.__getattribute__(funcname)
# Setup inclusive dictionary containing the requested keywords for all
# common_lib axis conversion functions
fkwds = {}
fkwds["pathlength"] = ()
fkwds["polar"] = ()
fkwds["lambda_f"] = ()
try:
lambda_final = som.attr_list["Wavelength_final"]
except KeyError:
lambda_final = None
try:
fkwds["time_zero_slope"] = som.attr_list["Time_zero_slope"]
except KeyError:
pass
try:
fkwds["time_zero_offset"] = som.attr_list["Time_zero_offset"]
except KeyError:
pass
try:
fkwds["time_zero"] = som.attr_list["Time_zero"]
except KeyError:
pass
fkwds["dist_source_sample"] = ()
fkwds["dist_sample_detector"] = ()
try:
fkwds["inst_param"] = kwargs["inst_param"]
except KeyError:
fkwds["inst_param"] = "primary"
try:
fkwds["pixel_id"] = kwargs["pixel_id"]
except KeyError:
fkwds["pixel_id"] = None
fkwds["run_filter"] = False
# Set up for working through data
# This time highest object in the hierarchy is NOT what we need
result = []
res_descr = "list"
inst = som.attr_list.instrument
import hlr_utils
# iterate through the values
for i in xrange(hlr_utils.get_length(som)):
map_so = hlr_utils.get_map_so(som, None, i)
fkwds["pathlength"] = hlr_utils.get_parameter(fkwds["inst_param"],
map_so, inst)
fkwds["dist_source_sample"] = hlr_utils.get_parameter("primary",
map_so, inst)
fkwds["dist_sample_detector"] = hlr_utils.get_parameter("secondary",
map_so, inst)
fkwds["polar"] = hlr_utils.get_parameter("polar", map_so, inst)
fkwds["lambda_f"] = hlr_utils.get_special(lambda_final, map_so)
value = tuple(func(number, **fkwds))
hlr_utils.result_insert(result, res_descr, value, None, "all")
return result
def rebin_monitor(obj1, obj2, **kwargs):
"""
This function takes objects (1st is the monitor, 2nd is the detector data)
and rebins the data for obj1 onto the axis provided by obj2. The pixel ID
can be transferred as the pixel ID of the rebinned monitor histogram. A
prefix is placed on the bank ID to dilineate that this is a rebinned
monitor spectrum for that pixel.
@param obj1: Monitor object that will be rebinned
@type obj1: C{SOM.SOM} or C{SOM.SO}
@param obj2: Detector data object that will provide the axis for rebinning
@type obj2: C{SOM.SOM} or C{SOM.SO}
@param kwargs: A list of keyword arguments that the function accepts
@keyword use_pix_id: A flag that specifies if the pixel ID is to be used
in the rebinned monitor spectrum. The default is I{False}.
@type use_pix_id: C{boolean}
@keyword prefix: Allows one to specify a prefix for the bank ID. The
default is I{m}.
@type prefix: C{string}
@keyword rtype: A short string that defines the rebinning function to use.
The default is I{None} which uses
L{common_lib.rebin_axis_1D()}. The other possibilities are
I{linint} which uses L{common_lib.rebin_axis_1D_linint()}
and I{frac} which uses L{common_lib.rebin_axis_1D_frac()}.
@type rtype: C{boolean}
@return: Object that has been rebinned
@rtype: C{SOM.SOM} or C{SOM.SO}
@raise TypeError: The C{SOM}-C{SO} operation is attempted
@raise TypeError: The C{SO}-C{SOM} operation is attempted
@raise TypeError: obj1 not a C{SOM} or C{SO}
@raise TypeError: obj2 not a C{SOM} or C{SO}
"""
# import the helper functions
import hlr_utils
# Kickout if monitor object is None
if obj1 is None:
return obj1
# set up for working through data
(result, res_descr) = hlr_utils.empty_result(obj1, obj2)
(o1_descr, o2_descr) = hlr_utils.get_descr(obj1, obj2)
# error checking for types
if o1_descr == "SOM" and o2_descr == "SO":
raise TypeError, "SOM-SO operation not supported"
elif o1_descr == "SO" and o2_descr == "SOM":
raise TypeError("SO-SOM operation not supported")
# Have the right object combination, go on
else:
pass
# Check for keywords
try:
prefix = kwargs["prefix"]
except KeyError:
prefix = "m"
try:
use_pix_id = kwargs["use_pix_id"]
except KeyError:
use_pix_id = False
try:
rtype = kwargs["rtype"]
except KeyError:
rtype = None
# Set the name of the rebinning function
rebin_function_name = "rebin_axis_1D"
if rtype is not None:
rebin_function_name += "_" + str(rtype)
# Get function pointer
import common_lib
rebin_function = common_lib.__getattribute__(rebin_function_name)
result = hlr_utils.copy_som_attr(result, res_descr, obj1, o1_descr)
# iterate through the values
val1 = hlr_utils.get_value(obj1, 0, o1_descr, "all")
# Cache length
len_obj2 = hlr_utils.get_length(obj2)
for i in xrange(len_obj2):
val2 = hlr_utils.get_value(obj2, i, o2_descr, "x")
value = rebin_function(val1, val2)
if use_pix_id:
# Set the pixel ID to the spectrum with modified bank ID
try:
value.id = (prefix + obj2[i].id[0], (obj2[i].id[1][0],
obj2[i].id[1][1]))
except TypeError:
value.id = prefix + str(obj2[i].id)
hlr_utils.result_insert(result, res_descr, value, None, "all")
return result
def run(config, tim):
"""
This method is where the data reduction process gets done.
@param config: Object containing the data reduction configuration
information.
@type config: L{hlr_utils.Configure}
@param tim: Object that will allow the method to perform timing
evaluations.
@type tim: C{sns_time.DiffTime}
"""
import common_lib
import dr_lib
if tim is not None:
tim.getTime(False)
old_time = tim.getOldTime()
if config.data1 is None or config.data2 is None:
raise RuntimeError("Need to pass a data filename(s) to the driver "\
+"script.")
dst_type1 = hlr_utils.file_peeker(config.data1[0])
if config.verbose:
print "Initial file type (data set 1):", dst_type1
d_som1 = dr_lib.add_files(config.data1,
dst_type=dst_type1,
Verbose=config.verbose,
Timer=tim)
dst_type2 = hlr_utils.file_peeker(config.data2[0])
if config.verbose:
print "Initial file type (data set 2):", dst_type2
d_som2 = dr_lib.add_files(config.data2,
dst_type=dst_type2,
Verbose=config.verbose,
Timer=tim)
# Get requested simple math operation
func = common_lib.__getattribute__(config.operation)
d_som3 = func(d_som1, d_som2)
del d_som1, d_som2
# Rescale data if necessary
if config.rescale is not None:
d_som4 = common_lib.mult_ncerr(d_som3, (config.rescale, 0.0))
else:
d_som4 = d_som3
del d_som3
# Write out file after simple math operation
hlr_utils.write_file(config.output,
dst_type1,
d_som4,
verbose=config.verbose,
replace_ext=False,
path_replacement=config.path_replacement,
axis_ok=True,
message="operated file")
if tim is not None:
tim.setOldTime(old_time)
tim.getTime(msg="Total Running Time")
def run(config, tim):
"""
This method is where the data reduction process gets done.
@param config: Object containing the data reduction configuration
information.
@type config: L{hlr_utils.Configure}
@param tim: Object that will allow the method to perform timing
evaluations.
@type tim: C{sns_time.DiffTime}
"""
import common_lib
import dr_lib
if tim is not None:
tim.getTime(False)
old_time = tim.getOldTime()
if config.data1 is None or config.data2 is None:
raise RuntimeError("Need to pass a data filename(s) to the driver "\
+"script.")
dst_type1 = hlr_utils.file_peeker(config.data1[0])
if config.verbose:
print "Initial file type (data set 1):", dst_type1
d_som1 = dr_lib.add_files(config.data1, dst_type=dst_type1,
Verbose=config.verbose,
Timer=tim)
dst_type2 = hlr_utils.file_peeker(config.data2[0])
if config.verbose:
print "Initial file type (data set 2):", dst_type2
d_som2 = dr_lib.add_files(config.data2, dst_type=dst_type2,
Verbose=config.verbose,
Timer=tim)
# Get requested simple math operation
func = common_lib.__getattribute__(config.operation)
d_som3 = func(d_som1, d_som2)
del d_som1, d_som2
# Rescale data if necessary
if config.rescale is not None:
d_som4 = common_lib.mult_ncerr(d_som3, (config.rescale, 0.0))
else:
d_som4 = d_som3
del d_som3
# Write out file after simple math operation
hlr_utils.write_file(config.output, dst_type1, d_som4,
verbose=config.verbose,
replace_ext=False,
path_replacement=config.path_replacement,
axis_ok=True,
message="operated file")
if tim is not None:
tim.setOldTime(old_time)
tim.getTime(msg="Total Running Time")
def convert_single_to_list(funcname, number, som, **kwargs):
"""
This function retrieves a function object from the L{common_lib} set of
functions that provide axis transformations and converts the provided
number based on that function. Instrument geometry information needs to be
provided via the C{SOM}. The following is the list of functions supported
by this one.
- d_spacing_to_tof_focused_det
- energy_to_wavelength
- frequency_to_energy
- initial_wavelength_igs_lin_time_zero_to_tof
- init_scatt_wavevector_to_scalar_Q
- tof_to_initial_wavelength_igs_lin_time_zero
- tof_to_initial_wavelength_igs
- tof_to_scalar_Q
- tof_to_wavelength_lin_time_zero
- tof_to_wavelength
- wavelength_to_d_spacing
- wavelength_to_energy
- wavelength_to_scalar_k
- wavelength_to_scalar_Q
@param funcname: The name of the axis conversion function to use
@type funcname: C{string}
@param number: The value and error^2 to convert
@type number: C{tuple}
@param som: The object containing geometry and other special information
@type som: C{SOM.SOM}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword inst_param: The type of parameter requested from an associated
instrument. For this function the acceptable
parameters are I{primary}, I{secondary} and I{total}.
Default is I{primary}.
@type inst_param: C{string}
@keyword pixel_id: The pixel ID from which the geometry information will
be retrieved from the instrument
@type pixel_id: C{tuple}=(\"bankN\", (x, y))
@return: A converted number for every unique spectrum
@rtype: C{list} of C{tuple}s
@raise AttributeError: The requested function is not in the approved
list
"""
# Setup supported function list and check to see if funcname is available
function_list = []
function_list.append("d_spacing_to_tof_focused_det")
function_list.append("energy_to_wavelength")
function_list.append("frequency_to_energy")
function_list.append("initial_wavelength_igs_lin_time_zero_to_tof")
function_list.append("init_scatt_wavevector_to_scalar_Q")
function_list.append("tof_to_initial_wavelength_igs_lin_time_zero")
function_list.append("tof_to_initial_wavelength_igs")
function_list.append("tof_to_scalar_Q")
function_list.append("tof_to_wavelength_lin_time_zero")
function_list.append("tof_to_wavelength")
function_list.append("wavelength_to_d_spacing")
function_list.append("wavelength_to_energy")
function_list.append("wavelength_to_scalar_k")
function_list.append("wavelength_to_scalar_Q")
if funcname not in function_list:
raise AttributeError("Function %s is not supported by "\
+"convert_single_to_list" % funcname)
import common_lib
# Get the common_lib function object
func = common_lib.__getattribute__(funcname)
# Setup inclusive dictionary containing the requested keywords for all
# common_lib axis conversion functions
fkwds = {}
fkwds["pathlength"] = ()
fkwds["polar"] = ()
fkwds["lambda_f"] = ()
try:
lambda_final = som.attr_list["Wavelength_final"]
except KeyError:
lambda_final = None
try:
fkwds["time_zero_slope"] = som.attr_list["Time_zero_slope"]
except KeyError:
pass
try:
fkwds["time_zero_offset"] = som.attr_list["Time_zero_offset"]
except KeyError:
pass
try:
fkwds["time_zero"] = som.attr_list["Time_zero"]
except KeyError:
pass
fkwds["dist_source_sample"] = ()
fkwds["dist_sample_detector"] = ()
try:
fkwds["inst_param"] = kwargs["inst_param"]
except KeyError:
fkwds["inst_param"] = "primary"
try:
fkwds["pixel_id"] = kwargs["pixel_id"]
except KeyError:
fkwds["pixel_id"] = None
fkwds["run_filter"] = False
# Set up for working through data
# This time highest object in the hierarchy is NOT what we need
result = []
res_descr = "list"
inst = som.attr_list.instrument
import hlr_utils
# iterate through the values
for i in xrange(hlr_utils.get_length(som)):
map_so = hlr_utils.get_map_so(som, None, i)
fkwds["pathlength"] = hlr_utils.get_parameter(fkwds["inst_param"],
map_so, inst)
fkwds["dist_source_sample"] = hlr_utils.get_parameter(
"primary", map_so, inst)
fkwds["dist_sample_detector"] = hlr_utils.get_parameter(
"secondary", map_so, inst)
fkwds["polar"] = hlr_utils.get_parameter("polar", map_so, inst)
fkwds["lambda_f"] = hlr_utils.get_special(lambda_final, map_so)
value = tuple(func(number, **fkwds))
hlr_utils.result_insert(result, res_descr, value, None, "all")
return result