def __trig_param_array(som, param, trig_func):
"""
This private function applies a trigonometric function to a given
parameter obtained from the supplied object.
@param som: The object containing the requested information.
@type som: C{SOM.SOM}
@param param: The name of the parameter to seek.
@type param: C{string}
@param trig_func: The name of the trigonometric function to apply.
@type trig_func: C{string}
@return: An array of trigonometry applied values from parameters from the
incoming object.
@rtype: C{list}
"""
import math
len_som = hlr_utils.get_length(som)
plist = []
inst = som.attr_list.instrument
tfunc = math.__getattribute__(trig_func)
for i in xrange(len_som):
plist.append(tfunc(hlr_utils.get_parameter(param, som[i], inst)[0]))
return plist
def __trig_param_array(som, param, trig_func):
"""
This private function applies a trigonometric function to a given
parameter obtained from the supplied object.
@param som: The object containing the requested information.
@type som: C{SOM.SOM}
@param param: The name of the parameter to seek.
@type param: C{string}
@param trig_func: The name of the trigonometric function to apply.
@type trig_func: C{string}
@return: An array of trigonometry applied values from parameters from the
incoming object.
@rtype: C{list}
"""
import math
len_som = hlr_utils.get_length(som)
plist = []
inst = som.attr_list.instrument
tfunc = math.__getattribute__(trig_func)
for i in xrange(len_som):
plist.append(tfunc(hlr_utils.get_parameter(param, som[i], inst)[0]))
return plist
def calc_BSS_solid_angle(map_so, inst):
"""
This function calculates the solid angle for a given BSS detector pixel
@param map_so: The object containing the pixel ID
@type map_so: C{SOM.SO}
@param inst: The object containing the instrument geometry
@type inst: C{SOM.Instrument} or C{SOM.CompositeInstrument}
@return: The solid angle for the given pixel
@rtype: C{float}
"""
# Get polar angle from instrument information
angle_tuple = hlr_utils.get_parameter("polar", map_so, inst)
angle = angle_tuple[0]
# Get the detector pixel height
dh_tuple = hlr_utils.get_parameter("dh", map_so, inst)
dh = dh_tuple[0]
# Get the detector pixel angular width
dtd_tuple = hlr_utils.get_parameter("dtd", map_so, inst)
dtd = dtd_tuple[0]
# Get partial derivatives
dazi_dh_tuple = hlr_utils.get_parameter("dazi_dh", map_so, inst)
dazi_dh = dazi_dh_tuple[0]
dpol_dh_tuple = hlr_utils.get_parameter("dpol_dh", map_so, inst)
dpol_dh = dpol_dh_tuple[0]
dpol_dtd_tuple = hlr_utils.get_parameter("dpol_dtd", map_so, inst)
dpol_dtd = dpol_dtd_tuple[0]
dazi_dtd_tuple = hlr_utils.get_parameter("dazi_dtd", map_so, inst)
dazi_dtd = dazi_dtd_tuple[0]
import math
sin_pol = math.sin(angle)
return math.fabs(sin_pol * dtd * dh *
(dpol_dtd * dazi_dh - dpol_dh * dazi_dtd))
def calc_BSS_solid_angle(map_so, inst):
"""
This function calculates the solid angle for a given BSS detector pixel
@param map_so: The object containing the pixel ID
@type map_so: C{SOM.SO}
@param inst: The object containing the instrument geometry
@type inst: C{SOM.Instrument} or C{SOM.CompositeInstrument}
@return: The solid angle for the given pixel
@rtype: C{float}
"""
# Get polar angle from instrument information
angle_tuple = hlr_utils.get_parameter("polar", map_so, inst)
angle = angle_tuple[0]
# Get the detector pixel height
dh_tuple = hlr_utils.get_parameter("dh", map_so, inst)
dh = dh_tuple[0]
# Get the detector pixel angular width
dtd_tuple = hlr_utils.get_parameter("dtd", map_so, inst)
dtd = dtd_tuple[0]
# Get partial derivatives
dazi_dh_tuple = hlr_utils.get_parameter("dazi_dh", map_so, inst)
dazi_dh = dazi_dh_tuple[0]
dpol_dh_tuple = hlr_utils.get_parameter("dpol_dh", map_so, inst)
dpol_dh = dpol_dh_tuple[0]
dpol_dtd_tuple = hlr_utils.get_parameter("dpol_dtd", map_so, inst)
dpol_dtd = dpol_dtd_tuple[0]
dazi_dtd_tuple = hlr_utils.get_parameter("dazi_dtd", map_so, inst)
dazi_dtd = dazi_dtd_tuple[0]
import math
sin_pol = math.sin(angle)
return math.fabs(sin_pol * dtd * dh * (dpol_dtd * dazi_dh - dpol_dh * dazi_dtd))
def param_array(som, param):
"""
This function takes a parameter and interrogates the object for that
information.
@param som: The object containing the requested information.
@type som: C{SOM.SOM}
@param param: The name of the parameter to seek.
@type param: C{string}
@return: An array of the parameters from the incoming object.
@rtype: C{list}
"""
len_som = hlr_utils.get_length(som)
plist = []
inst = som.attr_list.instrument
for i in xrange(len_som):
plist.append(hlr_utils.get_parameter(param, som[i], inst)[0])
return plist
def param_array(som, param):
"""
This function takes a parameter and interrogates the object for that
information.
@param som: The object containing the requested information.
@type som: C{SOM.SOM}
@param param: The name of the parameter to seek.
@type param: C{string}
@return: An array of the parameters from the incoming object.
@rtype: C{list}
"""
len_som = hlr_utils.get_length(som)
plist = []
inst = som.attr_list.instrument
for i in xrange(len_som):
plist.append(hlr_utils.get_parameter(param, som[i], inst)[0])
return plist
def calc_solid_angle(inst, pix, **kwargs):
"""
This function calculates the solid angle of a given pixel by taking the
area of the pixel and the cosine of the polar angle and dividing it by the
square of the pathlength.
@param inst: The object containing the geometry information.
@type inst: C{Instrument} or C{CompositeInstrument}
@param pix: The pixel to calculate the solid angle for.
@type pix: C{SOM.SO}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword pathtype: The pathlength type from which to calculate the solid
angle. The possible values are I{total}, I{primary} and
I{secondary}. The default is I{secondary}.
@type pathtype: C{string}
"""
import hlr_utils
# Check for keywords
try:
pathtype = kwargs["pathtype"]
except KeyError:
pathtype = "secondary"
# Get pixel pathlength and square it (this is in meters)
pl = hlr_utils.get_parameter(pathtype, pix, inst)
pl2 = pl[0] * pl[0]
# Make object for neighboring pixel
import SOM
npix = SOM.SO()
import math
# Get x pixel size
x1 = hlr_utils.get_parameter("x-offset", pix, inst)
# Make the neighboring pixel ID in the x direction
try:
npix.id = (pix.id[0], (pix.id[1][0]+1, pix.id[1][1]))
x2 = hlr_utils.get_parameter("x-offset", npix, inst)
except IndexError:
npix.id = (pix.id[0], (pix.id[1][0]-1, pix.id[1][1]))
x2 = hlr_utils.get_parameter("x-offset", npix, inst)
# Pixel offsets are in meters
xdiff = math.fabs(x2 - x1)
# Get y pixel size
y1 = hlr_utils.get_parameter("y-offset", pix, inst)
# Make the neighboring pixel ID in the y direction
try:
npix.id = (pix.id[0], (pix.id[1][0], pix.id[1][1]+1))
y2 = hlr_utils.get_parameter("y-offset", npix, inst)
except IndexError:
npix.id = (pix.id[0], (pix.id[1][0], pix.id[1][1]-1))
y2 = hlr_utils.get_parameter("y-offset", npix, inst)
# Pixel offsets are in meters
ydiff = math.fabs(y2 - y1)
# Make pixel area
pix_area = xdiff * ydiff
# Get the polar angle
polar = hlr_utils.get_parameter("polar", pix, inst)
solid_angle = (pix_area * math.cos(polar[0])) / pl2
return solid_angle
def tof_to_wavelength_lin_time_zero(obj, **kwargs):
"""
This function converts a primary axis of a C{SOM} or C{SO} from
time-of-flight to wavelength incorporating a linear time zero which is a
described as a linear function of the wavelength. The time-of-flight axis
for a C{SOM} must be in units of I{microseconds}. The primary axis of a
C{SO} is assumed to be in units of I{microseconds}. A C{tuple} of C{(tof,
tof_err2)} (assumed to be in units of I{microseconds}) can be converted to
C{(wavelength, wavelength_err2)}.
@param obj: Object to be converted
@type obj: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword pathlength: The pathlength and its associated error^2
@type pathlength: C{tuple} or C{list} of C{tuple}s
@keyword time_zero_slope: The time zero slope and its associated error^2
@type time_zero_slope: C{tuple}
@keyword time_zero_offset: The time zero offset and its associated error^2
@type time_zero_offset: C{tuple}
@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 lojac: A flag that allows one to turn off the calculation of the
linear-order Jacobian. The default action is I{True} for
histogram data.
@type lojac: C{boolean}
@keyword units: The expected units for this function. The default for this
function is I{microseconds}.
@type units: C{string}
@keyword cut_val: Specify a wavelength to cut the spectra at.
@type cut_val: C{float}
@keyword cut_less: A flag that specifies cutting the spectra less than
C{cut_val}. The default is C{True}.
@type cut_less: C{boolean}
@return: Object with a primary axis in time-of-flight converted to
wavelength
@rtype: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@raise TypeError: The incoming object is not a type the function recognizes
@raise RuntimeError: The C{SOM} x-axis units are not I{microseconds}
@raise RuntimeError: A C{SOM} does not contain an instrument and no
pathlength was provided
@raise RuntimeError: No C{SOM} is provided and no pathlength given
"""
# import the helper functions
import hlr_utils
# 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:
inst_param = kwargs["inst_param"]
except KeyError:
inst_param = "primary"
try:
pathlength = kwargs["pathlength"]
except KeyError:
pathlength = None
try:
time_zero_slope = kwargs["time_zero_slope"]
except KeyError:
time_zero_slope = None
# Current constants for Time Zero Slope
TIME_ZERO_SLOPE = (float(0.0), float(0.0))
try:
time_zero_offset = kwargs["time_zero_offset"]
except KeyError:
time_zero_offset = None
# Current constants for Time Zero Offset
TIME_ZERO_OFFSET = (float(0.0), float(0.0))
try:
lojac = kwargs["lojac"]
except KeyError:
lojac = hlr_utils.check_lojac(obj)
try:
units = kwargs["units"]
except KeyError:
units = "microseconds"
try:
cut_val = kwargs["cut_val"]
except KeyError:
cut_val = None
try:
cut_less = kwargs["cut_less"]
except KeyError:
cut_less = True
# 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)
if res_descr == "SOM":
result = hlr_utils.force_units(result, "Angstroms", axis)
result.setAxisLabel(axis, "wavelength")
result.setYUnits("Counts/A")
result.setYLabel("Intensity")
else:
pass
if pathlength is not None:
p_descr = hlr_utils.get_descr(pathlength)
else:
if o_descr == "SOM":
try:
obj.attr_list.instrument.get_primary()
inst = obj.attr_list.instrument
except RuntimeError:
raise RuntimeError("A detector was not provided")
else:
raise RuntimeError("If no SOM is provided, then pathlength "\
+"information must be provided")
if time_zero_slope is not None:
t_0_slope_descr = hlr_utils.get_descr(time_zero_slope)
else:
if o_descr == "SOM":
try:
t_0_slope = obj.attr_list["Time_zero_slope"][0]
t_0_slope_err2 = obj.attr_list["Time_zero_slope"][1]
except KeyError:
t_0_slope = TIME_ZERO_SLOPE[0]
t_0_slope_err2 = TIME_ZERO_SLOPE[1]
else:
t_0_slope = TIME_ZERO_SLOPE[0]
t_0_slope_err2 = TIME_ZERO_SLOPE[1]
if time_zero_offset is not None:
t_0_offset_descr = hlr_utils.get_descr(time_zero_offset)
else:
if o_descr == "SOM":
try:
t_0_offset = obj.attr_list["Time_zero_offset"][0]
t_0_offset_err2 = obj.attr_list["Time_zero_offset"][1]
except KeyError:
t_0_offset = TIME_ZERO_OFFSET[0]
t_0_offset_err2 = TIME_ZERO_OFFSET[1]
else:
t_0_offset = TIME_ZERO_OFFSET[0]
t_0_offset_err2 = TIME_ZERO_OFFSET[1]
# iterate through the values
import axis_manip
if lojac or cut_val is not None:
import utils
for i in xrange(hlr_utils.get_length(obj)):
val = hlr_utils.get_value(obj, i, o_descr, "x", axis)
err2 = hlr_utils.get_err2(obj, i, o_descr, "x", axis)
map_so = hlr_utils.get_map_so(obj, None, i)
if pathlength is None:
(pl, pl_err2) = hlr_utils.get_parameter(inst_param, map_so, inst)
else:
pl = hlr_utils.get_value(pathlength, i, p_descr)
pl_err2 = hlr_utils.get_err2(pathlength, i, p_descr)
if time_zero_slope is not None:
t_0_slope = hlr_utils.get_value(time_zero_slope, i,
t_0_slope_descr)
t_0_slope_err2 = hlr_utils.get_err2(time_zero_slope, i,
t_0_slope_descr)
else:
pass
if time_zero_offset is not None:
t_0_offset = hlr_utils.get_value(time_zero_offset, i,
t_0_offset_descr)
t_0_offset_err2 = hlr_utils.get_err2(time_zero_offset, i,
t_0_offset_descr)
else:
pass
value = axis_manip.tof_to_wavelength_lin_time_zero(
val, err2, pl, pl_err2, t_0_slope, t_0_slope_err2, t_0_offset,
t_0_offset_err2)
if cut_val is not None:
index = utils.bisect_helper(value[0], cut_val)
if cut_less:
# Need to cut at this index, so increment by one
index += 1
value[0].__delslice__(0, index)
value[1].__delslice__(0, index)
map_so.y.__delslice__(0, index)
map_so.var_y.__delslice__(0, index)
if lojac:
val.__delslice__(0, index)
err2.__delslice__(0, index)
else:
len_data = len(value[0])
# All axis arrays need starting index adjusted by one since
# they always carry one more bin than the data
value[0].__delslice__(index + 1, len_data)
value[1].__delslice__(index + 1, len_data)
map_so.y.__delslice__(index, len_data)
map_so.var_y.__delslice__(index, len_data)
if lojac:
val.__delslice__(index + 1, len_data)
err2.__delslice__(index + 1, len_data)
if lojac:
counts = utils.linear_order_jacobian(val, value[0], map_so.y,
map_so.var_y)
hlr_utils.result_insert(result, res_descr, counts, map_so, "all",
axis, [value[0]])
else:
hlr_utils.result_insert(result, res_descr, value, map_so, "x",
axis)
return result
def calc_BSS_coeffs(map_so, inst, *args):
"""
This function calculates the x_i coefficients for the BSS instrument
@param map_so: The spectrum object to calculate the coefficients for
@type map_so: C{SOM.SO}
@param inst: The instrument object associated with the data
@type inst: C{SOM.Instrument} or C{SOM.CompositeInstrument}
@param args: A list of parameters (C{tuple}s with value and err^2) used to
calculate the x_i coefficients
The following is a list of the arguments needed in there expected order
1. Initial Energy
2. Momentum Transfer
3. Initial Wavevector
4. Initial Time-of-Flight
5. Detector Pixel Height
6. Polar Angle
7. Final Energy
8. Final Wavevector
9. Final Wavelength
10. Source to Sample Distance
11. Sample to Detector Distance
12. Time-zero Slope
13. Vector of Zeros
@type args: C{list}
@return: The calculated coefficients (x_1, x_2, x_3, x_4)
@rtype: C{tuple} of 4 C{nessi_list.NessiList}s
"""
import math
# Settle out the arguments to sensible names
E_i = args[0][0]
E_i_err2 = args[0][1]
Q = args[1][0]
Q_err2 = args[1][1]
k_i = args[2][0]
k_i_err2 = args[2][1]
T_i = args[3][0]
T_i_err2 = args[3][1]
dh = args[4]
polar_angle = args[5]
E_f = args[6]
k_f = args[7]
l_f = args[8]
L_s = args[9]
L_d = args[10]
T_0_s = args[11]
zero_vec = args[12]
# Constant h/m_n (meters / microsecond)
H_OVER_MNEUT = 0.003956034e-10
# Get the differential geometry parameters
dlf_dh_tuple = hlr_utils.get_parameter("dlf_dh", map_so, inst)
dlf_dh = dlf_dh_tuple[0]
# dlf_dh should be unitless (Angstrom/Angstrom)
dlf_dh *= 1e-10
dpol_dh_tuple = hlr_utils.get_parameter("dpol_dh", map_so, inst)
dpol_dh = dpol_dh_tuple[0]
# Convert to radian/Angstrom
dpol_dh *= 1e-10
dpol_dtd_tuple = hlr_utils.get_parameter("dpol_dtd", map_so, inst)
dpol_dtd = dpol_dtd_tuple[0]
# Get the detector pixel angular width
dtd_tuple = hlr_utils.get_parameter("dtd", map_so, inst)
dtd = dtd_tuple[0]
# Calculate bin centric values
E_i_bc_tuple = utils.calc_bin_centers(E_i, E_i_err2)
E_i_bc = E_i_bc_tuple[0]
k_i_bc_tuple = utils.calc_bin_centers(k_i, k_i_err2)
k_i_bc = k_i_bc_tuple[0]
Q_bc_tuple = utils.calc_bin_centers(Q, Q_err2)
Q_bc = Q_bc_tuple[0]
T_i_bc_tuple = utils.calc_bin_centers(T_i, T_i_err2)
T_i_bc = T_i_bc_tuple[0]
# Get numeric values
sin_polar = math.sin(polar_angle)
cos_polar = math.cos(polar_angle)
length_ratio = L_d / L_s
lambda_const = ((2.0 * math.pi) / (l_f * l_f)) * dlf_dh
kf_cos_pol = k_f * cos_polar
kf_sin_pol = k_f * sin_polar
t0_slope_corr = (1.0 / (1.0 + H_OVER_MNEUT * (T_0_s / L_s)))
dtd_over_dh = dtd / dh
# Calculate coefficients
x_1_tuple = __calc_x1(k_i_bc, Q_bc, length_ratio, k_f, kf_cos_pol,
kf_sin_pol, lambda_const, dpol_dh, dpol_dtd,
dtd_over_dh, cos_polar, t0_slope_corr, zero_vec)
x_1 = x_1_tuple[0]
x_2_tuple = __calc_x2(k_i_bc, Q_bc, T_i_bc, kf_cos_pol, t0_slope_corr,
zero_vec)
x_2 = x_2_tuple[0]
x_3_tuple = __calc_x3(k_i_bc, E_i_bc, length_ratio, E_f, k_f, lambda_const,
t0_slope_corr, zero_vec)
x_3 = x_3_tuple[0]
x_4_tuple = __calc_x4(E_i_bc, T_i_bc, t0_slope_corr, zero_vec)
x_4 = x_4_tuple[0]
return (x_1, x_2, x_3, x_4)
def initial_wavelength_igs_lin_time_zero_to_tof(obj, **kwargs):
"""
This function converts a primary axis of a C{SOM} or C{SO} from
initial_wavelength_igs_lin_time_zero to time-of-flight. The
initial_wavelength_igs_lin_time_zero axis for a C{SOM} must be in units of
I{Angstroms}. The primary axis of a C{SO} is assumed to be in units of
I{Angstroms}. A C{tuple} of C{(initial_wavelength_igs_lin_time_zero,
initial_wavelength_igs_lin_time_zero_err2)} (assumed to be in units of
I{Angstroms}) can be converted to C{(tof, tof_err2)}.
@param obj: Object to be converted
@type obj: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword lambda_f:The final wavelength and its associated error^2
@type lambda_f: C{tuple}
@keyword time_zero_slope: The time zero slope and its associated error^2
@type time_zero_slope: C{tuple}
@keyword time_zero_offset: The time zero offset and its associated error^2
@type time_zero_offset: C{tuple}
@keyword dist_source_sample: The source to sample distance information and
its associated error^2
@type dist_source_sample: C{tuple} or C{list} of C{tuple}s
@keyword dist_sample_detector: The sample to detector distance information
and its associated error^2
@type dist_sample_detector: C{tuple} or C{list} of C{tuple}s
@keyword lojac: A flag that allows one to turn off the calculation of the
linear-order Jacobian. The default action is True for
histogram data.
@type lojac: C{boolean}
@keyword units: The expected units for this function. The default for this
function is I{Angstroms}
@type units: C{string}
@return: Object with a primary axis in initial_wavelength_igs converted to
time-of-flight
@rtype: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@raise TypeError: The incoming object is not a type the function recognizes
@raise RuntimeError: The C{SOM} x-axis units are not I{Angstroms}
"""
# import the helper functions
import hlr_utils
# 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:
lambda_f = kwargs["lambda_f"]
except KeyError:
lambda_f = None
try:
time_zero_slope = kwargs["time_zero_slope"]
except KeyError:
time_zero_slope = None
# Current constants for Time Zero Slope
TIME_ZERO_SLOPE = (float(0.0), float(0.0))
try:
time_zero_offset = kwargs["time_zero_offset"]
except KeyError:
time_zero_offset = None
# Current constants for Time Zero Offset
TIME_ZERO_OFFSET = (float(0.0), float(0.0))
try:
dist_source_sample = kwargs["dist_source_sample"]
except KeyError:
dist_source_sample = None
try:
dist_sample_detector = kwargs["dist_sample_detector"]
except KeyError:
dist_sample_detector = None
try:
lojac = kwargs["lojac"]
except KeyError:
lojac = hlr_utils.check_lojac(obj)
try:
units = kwargs["units"]
except KeyError:
units = "Angstroms"
# 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)
if res_descr == "SOM":
result = hlr_utils.force_units(result, "Microseconds", axis)
result.setAxisLabel(axis, "time-of-flight")
result.setYUnits("Counts/uS")
result.setYLabel("Intensity")
else:
pass
# Where to get instrument information
if dist_source_sample is None or dist_sample_detector is None:
if o_descr == "SOM":
try:
obj.attr_list.instrument.get_primary()
inst = obj.attr_list.instrument
except RuntimeError:
raise RuntimeError("A detector was not provided!")
else:
if dist_source_sample is None and dist_sample_detector is None:
raise RuntimeError("If a SOM is not passed, the "\
+"source-sample and sample-detector "\
+"distances must be provided.")
elif dist_source_sample is None:
raise RuntimeError("If a SOM is not passed, the "\
+"source-sample distance must be provided.")
elif dist_sample_detector is None:
raise RuntimeError("If a SOM is not passed, the "\
+"sample-detector distance must be "\
+"provided.")
else:
raise RuntimeError("If you get here, see Steve Miller for "\
+"your mug.")
else:
pass
if lambda_f is not None:
l_descr = hlr_utils.get_descr(lambda_f)
else:
if o_descr == "SOM":
try:
som_l_f = obj.attr_list["Wavelength_final"]
except KeyError:
raise RuntimeError("Please provide a final wavelength "\
+"parameter either via the function call "\
+"or the SOM")
else:
raise RuntimeError("You need to provide a final wavelength")
if time_zero_slope is not None:
t_0_slope_descr = hlr_utils.get_descr(time_zero_slope)
else:
if o_descr == "SOM":
try:
t_0_slope = obj.attr_list["Time_zero_slope"][0]
t_0_slope_err2 = obj.attr_list["Time_zero_slope"][1]
except KeyError:
t_0_slope = TIME_ZERO_SLOPE[0]
t_0_slope_err2 = TIME_ZERO_SLOPE[1]
else:
t_0_slope = TIME_ZERO_SLOPE[0]
t_0_slope_err2 = TIME_ZERO_SLOPE[1]
if time_zero_offset is not None:
t_0_offset_descr = hlr_utils.get_descr(time_zero_offset)
else:
if o_descr == "SOM":
try:
t_0_offset = obj.attr_list["Time_zero_offset"][0]
t_0_offset_err2 = obj.attr_list["Time_zero_offset"][1]
except KeyError:
t_0_offset = TIME_ZERO_OFFSET[0]
t_0_offset_err2 = TIME_ZERO_OFFSET[1]
else:
t_0_offset = TIME_ZERO_OFFSET[0]
t_0_offset_err2 = TIME_ZERO_OFFSET[1]
if dist_source_sample is not None:
ls_descr = hlr_utils.get_descr(dist_source_sample)
# Do nothing, go on
else:
pass
if dist_sample_detector is not None:
ld_descr = hlr_utils.get_descr(dist_sample_detector)
# Do nothing, go on
else:
pass
# iterate through the values
len_obj = hlr_utils.get_length(obj)
MNEUT_OVER_H = 1.0 / 0.003956034
MNEUT_OVER_H2 = MNEUT_OVER_H * MNEUT_OVER_H
for i in xrange(len_obj):
val = hlr_utils.get_value(obj, i, o_descr, "x", axis)
err2 = hlr_utils.get_err2(obj, i, o_descr, "x", axis)
map_so = hlr_utils.get_map_so(obj, None, i)
if dist_source_sample is None:
(L_s, L_s_err2) = hlr_utils.get_parameter("primary", map_so, inst)
else:
L_s = hlr_utils.get_value(dist_source_sample, i, ls_descr)
L_s_err2 = hlr_utils.get_err2(dist_source_sample, i, ls_descr)
if dist_sample_detector is None:
(L_d, L_d_err2) = hlr_utils.get_parameter("secondary", map_so,
inst)
else:
L_d = hlr_utils.get_value(dist_sample_detector, i, ld_descr)
L_d_err2 = hlr_utils.get_err2(dist_sample_detector, i, ld_descr)
if lambda_f is not None:
l_f = hlr_utils.get_value(lambda_f, i, l_descr)
l_f_err2 = hlr_utils.get_err2(lambda_f, i, l_descr)
else:
l_f_tuple = hlr_utils.get_special(som_l_f, map_so)
l_f = l_f_tuple[0]
l_f_err2 = l_f_tuple[1]
if time_zero_slope is not None:
t_0_slope = hlr_utils.get_value(time_zero_slope, i,
t_0_slope_descr)
t_0_slope_err2 = hlr_utils.get_err2(time_zero_slope, i,
t_0_slope_descr)
else:
pass
if time_zero_offset is not None:
t_0_offset = hlr_utils.get_value(time_zero_offset, i,
t_0_offset_descr)
t_0_offset_err2 = hlr_utils.get_err2(time_zero_offset, i,
t_0_offset_descr)
else:
pass
# Going to violate rules since the current usage is with a single
# number. When an SCL equivalent function arises, this code can be
# fixed.
front_const = MNEUT_OVER_H * L_s + t_0_slope
term2 = MNEUT_OVER_H * l_f * L_d
tof = (front_const * val) + term2 + t_0_offset
front_const2 = front_const * front_const
eterm1 = l_f * l_f * L_d_err2
eterm2 = L_d * L_d * l_f_err2
eterm3 = MNEUT_OVER_H2 * L_s_err2
tof_err2 = (front_const2 * err2) + (val * val) * \
(eterm3 + t_0_slope_err2) + (MNEUT_OVER_H2 * \
(eterm1 + eterm2)) + \
t_0_offset_err2
hlr_utils.result_insert(result, res_descr, (tof, tof_err2), None,
"all")
return result
def d_spacing_to_tof_focused_det(obj, **kwargs):
"""
This function converts a primary axis of a C{SOM} or C{SO} from d-spacing
to a focused time-of-flight. The focusing is done using the geometry
information from a single detector pixel. The d-spacing axis for a C{SOM}
must be in units of I{Angstroms}. The primary axis of a C{SO} is assumed
to be in units of I{Angstroms}.
@param obj: Object to be converted
@type obj: C{SOM.SOM} or C{SOM.SO}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword polar: The polar angle and its associated error^2
@type polar: C{tuple} or C{list} of C{tuple}s
@keyword pathlength: The total pathlength and its associated error^2
@type pathlength: C{tuple} or C{list} of C{tuple}s
@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))
@keyword verbose: This determines if the pixel geometry information is
printed. The default is False
@type verbose: C{boolean}
@keyword units: The expected units for this function. The default for
this function is I{microseconds}.
@type units: C{string}
@return: Object with a primary axis in d-spacing converted to
time-of-flight
@rtype: C{SOM.SOM} or C{SOM.SO}
@raise RuntimeError: A C{SOM} or C{SO} is not provided to the function
@raise RuntimeError: No C{SOM.Instrument} is provided in a C{SOM}
@raise RuntimeError: No C{SOM} is given and both the pathlength and polar
angle are not provided
@raise RuntimeError: No C{SOM} is given and the pathlength is not provided
@raise RuntimeError: No C{SOM} is given and the polar angle is not provided
"""
# import the helper functions
import hlr_utils
# set up for working through data
(result, res_descr) = hlr_utils.empty_result(obj)
o_descr = hlr_utils.get_descr(obj)
if o_descr == "number" or o_descr == "list":
raise RuntimeError("Must provide a SOM of a SO to the function.")
# Go on
else:
pass
# Setup keyword arguments
try:
polar = kwargs["polar"]
except KeyError:
polar = None
try:
pathlength = kwargs["pathlength"]
except KeyError:
pathlength = None
try:
pixel_id = kwargs["pixel_id"]
except KeyError:
pixel_id = None
try:
verbose = kwargs["verbose"]
except KeyError:
verbose = False
try:
units = kwargs["units"]
except KeyError:
units = "Angstroms"
# 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)
if res_descr == "SOM":
result = hlr_utils.force_units(result, "microseconds", axis)
result.setAxisLabel(axis, "time-of-flight")
result.setYUnits("Counts/usec")
result.setYLabel("Intensity")
else:
pass
if pathlength is None or polar is None:
if o_descr == "SOM":
try:
obj.attr_list.instrument.get_primary()
inst = obj.attr_list.instrument
except RuntimeError:
raise RuntimeError("An instrument was not provided")
else:
if pathlength is None and polar is None:
raise RuntimeError("If no SOM is provided, then pathlength "\
+"and polar angle information must be provided")
elif pathlength is None:
raise RuntimeError("If no SOM is provided, then pathlength "\
+"information must be provided")
elif polar is None:
raise RuntimeError("If no SOM is provided, then polar angle "\
+"information must be provided")
else:
raise RuntimeError("If you get here, see Steve Miller for "\
+"your mug.")
else:
pass
if pathlength is not None:
p_descr = hlr_utils.get_descr(pathlength)
if polar is not None:
a_descr = hlr_utils.get_descr(polar)
# iterate through the values
if pixel_id is not None:
tmp_so = SOM.SO()
tmp_so.id = pixel_id
(pl, pl_err2) = hlr_utils.get_parameter("total", tmp_so, inst)
(angle, angle_err2) = hlr_utils.get_parameter("polar", tmp_so, inst)
if verbose:
format_str = "Pixel ID %s has polar angle: (%f,%f) and "
format_str += "pathlength: (%f,%f)"
print format_str % (str(pixel_id), angle, angle_err2, pl, pl_err2)
else:
pass
else:
pl = hlr_utils.get_value(pathlength, 0, p_descr)
pl_err2 = hlr_utils.get_err2(pathlength, 0, p_descr)
angle = hlr_utils.get_value(polar, 0, a_descr)
angle_err2 = hlr_utils.get_err2(polar, 0, a_descr)
# iterate through the values
import axis_manip
for i in xrange(hlr_utils.get_length(obj)):
val = hlr_utils.get_value(obj, i, o_descr, "x", axis)
err2 = hlr_utils.get_err2(obj, i, o_descr, "x", axis)
map_so = hlr_utils.get_map_so(obj, None, i)
value = axis_manip.d_spacing_to_tof_focused_det(val, err2, pl, pl_err2,
angle, angle_err2)
hlr_utils.result_insert(result, res_descr, value, map_so, "x", axis)
return result
def calc_substrate_trans(obj, subtrans_coeff, substrate_diam, **kwargs):
"""
This function calculates substrate transmission via the following formula:
T = exp[-(A + B * wavelength) * d] where A is a constant with units of
cm^-1, B is a constant with units of cm^-2 and d is the substrate
diameter in units of cm.
@param obj: The data object that contains the TOF axes to calculate the
transmission from.
@type obj: C{SOM.SOM} or C{SOM.SO}
@param subtrans_coeff: The two coefficients for substrate transmission
calculation.
@type subtrans_coeff: C{tuple} of two C{float}s
@param substrate_diam: The diameter of the substrate.
@type substrate_diam: C{float}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword pathlength: The pathlength and its associated error^2
@type pathlength: C{tuple} or C{list} of C{tuple}s
@keyword units: The expected units for this function. The default for this
function is I{microsecond}.
@type units: C{string}
@return: The calculate transmission for the given substrate parameters
@rtype: C{SOM.SOM} or C{SOM.SO}
@raise TypeError: The object used for calculation is not a C{SOM} or a
C{SO}
@raise RuntimeError: The C{SOM} x-axis units are not I{microsecond}
@raise RuntimeError: A C{SOM} does not contain an instrument and no
pathlength was provided
@raise RuntimeError: No C{SOM} is provided and no pathlength given
"""
# import the helper functions
import hlr_utils
# set up for working through data
(result, res_descr) = hlr_utils.empty_result(obj)
o_descr = hlr_utils.get_descr(obj)
if o_descr == "number" or o_descr == "list":
raise TypeError("Do not know how to handle given type: %s" % o_descr)
else:
pass
# Setup keyword arguments
try:
pathlength = kwargs["pathlength"]
except KeyError:
pathlength = None
try:
units = kwargs["units"]
except KeyError:
units = "microsecond"
# 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
if pathlength is not None:
p_descr = hlr_utils.get_descr(pathlength)
else:
if o_descr == "SOM":
try:
obj.attr_list.instrument.get_primary()
inst = obj.attr_list.instrument
except RuntimeError:
raise RuntimeError("A detector was not provided")
else:
raise RuntimeError("If no SOM is provided, then pathlength "\
+"information must be provided")
result = hlr_utils.copy_som_attr(result, res_descr, obj, o_descr)
if res_descr == "SOM":
result.setYLabel("Transmission")
# iterate through the values
import array_manip
import axis_manip
import nessi_list
import utils
import math
len_obj = hlr_utils.get_length(obj)
for i in xrange(len_obj):
val = hlr_utils.get_value(obj, i, o_descr, "x", axis)
err2 = hlr_utils.get_err2(obj, i, o_descr, "x", axis)
map_so = hlr_utils.get_map_so(obj, None, i)
if pathlength is None:
(pl, pl_err2) = hlr_utils.get_parameter("total", map_so, inst)
else:
pl = hlr_utils.get_value(pathlength, i, p_descr)
pl_err2 = hlr_utils.get_err2(pathlength, i, p_descr)
value = axis_manip.tof_to_wavelength(val, err2, pl, pl_err2)
value1 = utils.calc_bin_centers(value[0])
del value
# Convert Angstroms to centimeters
value2 = array_manip.mult_ncerr(value1[0], value1[1],
subtrans_coeff[1] * 1.0e-8, 0.0)
del value1
# Calculate the exponential
value3 = array_manip.add_ncerr(value2[0], value2[1], subtrans_coeff[0],
0.0)
del value2
value4 = array_manip.mult_ncerr(value3[0], value3[1],
-1.0 * substrate_diam, 0.0)
del value3
# Calculate transmission
trans = nessi_list.NessiList()
len_trans = len(value4[0])
for j in xrange(len_trans):
trans.append(math.exp(value4[0][j]))
trans_err2 = nessi_list.NessiList(len(trans))
hlr_utils.result_insert(result, res_descr, (trans, trans_err2), map_so)
return result
def tof_to_initial_wavelength_igs_lin_time_zero(obj, **kwargs):
"""
This function converts a primary axis of a C{SOM} or C{SO} from
time-of-flight to initial_wavelength_igs_lin_time_zero. The time-of-flight
axis for a C{SOM} must be in units of I{microseconds}. The primary axis of
a C{SO} is assumed to be in units of I{microseconds}. A C{tuple} of
C{(tof, tof_err2)} (assumed to be in units of I{microseconds}) can be
converted to C{(initial_wavelength_igs, initial_wavelength_igs_err2)}.
@param obj: Object to be converted
@type obj: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword lambda_f:The final wavelength and its associated error^2
@type lambda_f: C{tuple}
@keyword time_zero_slope: The time zero slope and its associated error^2
@type time_zero_slope: C{tuple}
@keyword time_zero_offset: The time zero offset and its associated error^2
@type time_zero_offset: C{tuple}
@keyword dist_source_sample: The source to sample distance information and
its associated error^2
@type dist_source_sample: C{tuple} or C{list} of C{tuple}s
@keyword dist_sample_detector: The sample to detector distance information
and its associated error^2
@type dist_sample_detector: C{tuple} or C{list} of C{tuple}s
@keyword run_filter: This determines if the filter on the negative
wavelengths is run. The default setting is True.
@type run_filter: C{boolean}
@keyword lojac: A flag that allows one to turn off the calculation of the
linear-order Jacobian. The default action is True for
histogram data.
@type lojac: C{boolean}
@keyword units: The expected units for this function. The default for this
function is I{microseconds}
@type units: C{string}
@return: Object with a primary axis in time-of-flight converted to
initial_wavelength_igs
@rtype: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@raise TypeError: The incoming object is not a type the function recognizes
@raise RuntimeError: The C{SOM} x-axis units are not I{microseconds}
"""
# import the helper functions
import hlr_utils
# 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:
lambda_f = kwargs["lambda_f"]
except KeyError:
lambda_f = None
try:
time_zero_slope = kwargs["time_zero_slope"]
except KeyError:
time_zero_slope = None
# Current constants for Time Zero Slope
TIME_ZERO_SLOPE = (float(0.0), float(0.0))
try:
time_zero_offset = kwargs["time_zero_offset"]
except KeyError:
time_zero_offset = None
# Current constants for Time Zero Offset
TIME_ZERO_OFFSET = (float(0.0), float(0.0))
try:
dist_source_sample = kwargs["dist_source_sample"]
except KeyError:
dist_source_sample = None
try:
dist_sample_detector = kwargs["dist_sample_detector"]
except KeyError:
dist_sample_detector = None
try:
lojac = kwargs["lojac"]
except KeyError:
lojac = hlr_utils.check_lojac(obj)
try:
units = kwargs["units"]
except KeyError:
units = "microseconds"
try:
run_filter = kwargs["run_filter"]
except KeyError:
run_filter = True
try:
iobj = kwargs["iobj"]
except KeyError:
iobj = None
# 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)
if res_descr == "SOM":
result = hlr_utils.force_units(result, "Angstroms", axis)
result.setAxisLabel(axis, "wavelength")
result.setYUnits("Counts/A")
result.setYLabel("Intensity")
else:
pass
# Where to get instrument information
if dist_source_sample is None or dist_sample_detector is None:
if o_descr == "SOM":
try:
obj.attr_list.instrument.get_primary()
inst = obj.attr_list.instrument
mobj = obj
except RuntimeError:
raise RuntimeError("A detector was not provided!")
else:
if iobj is None:
if dist_source_sample is None and dist_sample_detector is None:
raise RuntimeError("If a SOM is not passed, the "\
+"source-sample and sample-detector "\
+"distances must be provided.")
elif dist_source_sample is None:
raise RuntimeError("If a SOM is not passed, the "\
+"source-sample distance must be "\
+"provided.")
elif dist_sample_detector is None:
raise RuntimeError("If a SOM is not passed, the "\
+"sample-detector distance must be "\
+"provided.")
else:
raise RuntimeError("If you get here, see Steve Miller "\
+"for your mug.")
else:
inst = iobj.attr_list.instrument
mobj = iobj
else:
mobj = obj
if lambda_f is not None:
l_descr = hlr_utils.get_descr(lambda_f)
else:
if o_descr == "SOM":
try:
som_l_f = obj.attr_list["Wavelength_final"]
except KeyError:
raise RuntimeError("Please provide a final wavelength "\
+"parameter either via the function call "\
+"or the SOM")
else:
if iobj is None:
raise RuntimeError("You need to provide a final wavelength")
else:
som_l_f = iobj.attr_list["Wavelength_final"]
if time_zero_slope is not None:
t_0_slope_descr = hlr_utils.get_descr(time_zero_slope)
else:
if o_descr == "SOM":
try:
t_0_slope = obj.attr_list["Time_zero_slope"][0]
t_0_slope_err2 = obj.attr_list["Time_zero_slope"][1]
except KeyError:
t_0_slope = TIME_ZERO_SLOPE[0]
t_0_slope_err2 = TIME_ZERO_SLOPE[1]
else:
t_0_slope = TIME_ZERO_SLOPE[0]
t_0_slope_err2 = TIME_ZERO_SLOPE[1]
if time_zero_offset is not None:
t_0_offset_descr = hlr_utils.get_descr(time_zero_offset)
else:
if o_descr == "SOM":
try:
t_0_offset = obj.attr_list["Time_zero_offset"][0]
t_0_offset_err2 = obj.attr_list["Time_zero_offset"][1]
except KeyError:
t_0_offset = TIME_ZERO_OFFSET[0]
t_0_offset_err2 = TIME_ZERO_OFFSET[1]
else:
t_0_offset = TIME_ZERO_OFFSET[0]
t_0_offset_err2 = TIME_ZERO_OFFSET[1]
if dist_source_sample is not None:
ls_descr = hlr_utils.get_descr(dist_source_sample)
# Do nothing, go on
else:
pass
if dist_sample_detector is not None:
ld_descr = hlr_utils.get_descr(dist_sample_detector)
# Do nothing, go on
else:
pass
# iterate through the values
import axis_manip
if lojac:
import utils
for i in xrange(hlr_utils.get_length(obj)):
val = hlr_utils.get_value(obj, i, o_descr, "x", axis)
err2 = hlr_utils.get_err2(obj, i, o_descr, "x", axis)
map_so = hlr_utils.get_map_so(mobj, None, i)
if dist_source_sample is None:
(L_s, L_s_err2) = hlr_utils.get_parameter("primary", map_so, inst)
else:
L_s = hlr_utils.get_value(dist_source_sample, i, ls_descr)
L_s_err2 = hlr_utils.get_err2(dist_source_sample, i, ls_descr)
if dist_sample_detector is None:
(L_d, L_d_err2) = hlr_utils.get_parameter("secondary", map_so,
inst)
else:
L_d = hlr_utils.get_value(dist_sample_detector, i, ld_descr)
L_d_err2 = hlr_utils.get_err2(dist_sample_detector, i, ld_descr)
if lambda_f is not None:
l_f = hlr_utils.get_value(lambda_f, i, l_descr)
l_f_err2 = hlr_utils.get_err2(lambda_f, i, l_descr)
else:
l_f_tuple = hlr_utils.get_special(som_l_f, map_so)
l_f = l_f_tuple[0]
l_f_err2 = l_f_tuple[1]
if time_zero_slope is not None:
t_0_slope = hlr_utils.get_value(time_zero_slope, i,
t_0_slope_descr)
t_0_slope_err2 = hlr_utils.get_err2(time_zero_slope, i,
t_0_slope_descr)
else:
pass
if time_zero_offset is not None:
t_0_offset = hlr_utils.get_value(time_zero_offset, i,
t_0_offset_descr)
t_0_offset_err2 = hlr_utils.get_err2(time_zero_offset, i,
t_0_offset_descr)
else:
pass
value = axis_manip.tof_to_initial_wavelength_igs_lin_time_zero(
val, err2,
l_f, l_f_err2,
t_0_slope, t_0_slope_err2,
t_0_offset, t_0_offset_err2,
L_s, L_s_err2,
L_d, L_d_err2)
# Remove all wavelengths < 0
if run_filter:
index = 0
for valx in value[0]:
if valx >= 0:
break
index += 1
value[0].__delslice__(0, index)
value[1].__delslice__(0, index)
map_so.y.__delslice__(0, index)
map_so.var_y.__delslice__(0, index)
if lojac:
val.__delslice__(0, index)
err2.__delslice__(0, index)
else:
pass
if lojac:
try:
counts = utils.linear_order_jacobian(val, value[0],
map_so.y, map_so.var_y)
except Exception, e:
# Lets us know offending pixel ID
raise Exception(str(map_so.id) + " " + str(e))
hlr_utils.result_insert(result, res_descr, counts, map_so,
"all", axis, [value[0]])
else:
hlr_utils.result_insert(result, res_descr, value, map_so,
"x", axis)
def wavelength_to_d_spacing(obj, **kwargs):
"""
This function converts a primary axis of a C{SOM} or C{SO} from wavelength
to d-spacing. The wavelength axis for a C{SOM} must be in units of
I{Angstroms}. The primary axis of a C{SO} is assumed to be in units of
I{Angstroms}. A C{tuple} of C{(wavelength, wavelength_err2)} (assumed to
be in units of I{Angstroms}) can be converted to C{(d_spacing,
d_spacing_err2)}.
@param obj: Object to be converted
@type obj: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword polar:The polar angle and its associated error^2
@type polar: C{tuple}
@keyword units: The expected units for this function. The default for this
function is I{Angstroms}
@type units: C{string}
@return: Object with a primary axis in wavelength converted to d-spacing
@rtype: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@raise TypeError: The incoming object is not a type the function recognizes
@raise RuntimeError: A C{SOM} is not passed and no polar angle is provided
@raise RuntimeError: The C{SOM} x-axis units are not I{Angstroms}
"""
# import the helper functions
import hlr_utils
# set up for working through data
(result, res_descr) = hlr_utils.empty_result(obj)
o_descr = hlr_utils.get_descr(obj)
if o_descr == "list":
raise TypeError("Do not know how to handle given type: %s" % \
o_descr)
else:
pass
# Setup keyword arguments
try:
polar = kwargs["polar"]
except KeyError:
polar = None
try:
units = kwargs["units"]
except KeyError:
units = "Angstroms"
# 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)
if res_descr == "SOM":
result = hlr_utils.force_units(result, "Angstroms", axis)
result.setAxisLabel(axis, "d-spacing")
result.setYUnits("Counts/A")
result.setYLabel("Intensity")
else:
pass
if polar is None:
if o_descr == "SOM":
try:
obj.attr_list.instrument.get_primary()
inst = obj.attr_list.instrument
except RuntimeError:
raise RuntimeError("A detector was not provided!")
else:
raise RuntimeError("If no SOM is provided, then polar "\
+"information must be given.")
else:
p_descr = hlr_utils.get_descr(polar)
# iterate through the values
import axis_manip
for i in xrange(hlr_utils.get_length(obj)):
val = hlr_utils.get_value(obj, i, o_descr, "x", axis)
err2 = hlr_utils.get_err2(obj, i, o_descr, "x", axis)
map_so = hlr_utils.get_map_so(obj, None, i)
if polar is None:
(angle, angle_err2) = hlr_utils.get_parameter("polar", map_so,
inst)
else:
angle = hlr_utils.get_value(polar, i, p_descr)
angle_err2 = hlr_utils.get_err2(polar, i, p_descr)
value = axis_manip.wavelength_to_d_spacing(val, err2, angle,
angle_err2)
hlr_utils.result_insert(result, res_descr, value, map_so, "x",
axis)
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 tof_to_final_velocity_dgs(obj, velocity_i, time_zero_offset, **kwargs):
"""
This function converts a primary axis of a C{SOM} or C{SO} from
time-of-flight to final_velocity_dgs. The time-of-flight axis for a
C{SOM} must be in units of I{microseconds}. The primary axis of a C{SO} is
assumed to be in units of I{microseconds}. A C{tuple} of C{(tof, tof_err2)}
(assumed to be in units of I{microseconds}) can be converted to
C{(final_velocity_dgs, final_velocity_dgs_err2)}.
@param obj: Object to be converted
@type obj: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@param velocity_i: The initial velocity and its associated error^2
@type velocity_i: C{tuple}
@param time_zero_offset: The time zero offset and its associated error^2
@type time_zero_offset: C{tuple}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword dist_source_sample: The source to sample distance information and
its associated error^2
@type dist_source_sample: C{tuple} or C{list} of C{tuple}s
@keyword dist_sample_detector: The sample to detector distance information
and its associated error^2
@type dist_sample_detector: C{tuple} or C{list} of C{tuple}s
@keyword run_filter: This determines if the filter on the negative
velocities is run. The default setting is True.
@type run_filter: C{boolean}
@keyword lojac: A flag that allows one to turn off the calculation of the
linear-order Jacobian. The default action is True for
histogram data.
@type lojac: C{boolean}
@keyword units: The expected units for this function. The default for this
function is I{microseconds}
@type units: C{string}
@return: Object with a primary axis in time-of-flight converted to
final_velocity_dgs
@rtype: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@raise TypeError: The incoming object is not a type the function recognizes
@raise RuntimeError: The C{SOM} x-axis units are not I{microseconds}
"""
import hlr_utils
# 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:
dist_source_sample = kwargs["dist_source_sample"]
except KeyError:
dist_source_sample = None
try:
dist_sample_detector = kwargs["dist_sample_detector"]
except KeyError:
dist_sample_detector = None
try:
units = kwargs["units"]
except KeyError:
units = "microseconds"
try:
run_filter = kwargs["run_filter"]
except KeyError:
run_filter = True
try:
lojac = kwargs["lojac"]
except KeyError:
lojac = hlr_utils.check_lojac(obj)
# 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)
if res_descr == "SOM":
result = hlr_utils.force_units(result, "meters/microseconds", axis)
result.setAxisLabel(axis, "velocity")
result.setYUnits("Counts/meters/microseconds")
result.setYLabel("Intensity")
else:
pass
# Where to get instrument information
if dist_source_sample is None or dist_sample_detector is None:
if o_descr == "SOM":
try:
obj.attr_list.instrument.get_primary()
inst = obj.attr_list.instrument
except RuntimeError:
raise RuntimeError("A detector was not provided!")
else:
if dist_source_sample is None and dist_sample_detector is None:
raise RuntimeError("If a SOM is not passed, the "\
+"source-sample and sample-detector "\
+"distances must be provided.")
elif dist_source_sample is None:
raise RuntimeError("If a SOM is not passed, the "\
+"source-sample distance must be provided.")
elif dist_sample_detector is None:
raise RuntimeError("If a SOM is not passed, the "\
+"sample-detector distance must be "\
+"provided.")
else:
raise RuntimeError("If you get here, see Steve Miller for "\
+"your mug.")
else:
pass
if dist_source_sample is not None:
ls_descr = hlr_utils.get_descr(dist_source_sample)
# Do nothing, go on
else:
pass
if dist_sample_detector is not None:
ld_descr = hlr_utils.get_descr(dist_sample_detector)
# Do nothing, go on
else:
pass
# iterate through the values
import axis_manip
if lojac:
import utils
len_obj = hlr_utils.get_length(obj)
for i in xrange(len_obj):
val = hlr_utils.get_value(obj, i, o_descr, "x", axis)
err2 = hlr_utils.get_err2(obj, i, o_descr, "x", axis)
map_so = hlr_utils.get_map_so(obj, None, i)
if dist_source_sample is None:
(L_s, L_s_err2) = hlr_utils.get_parameter("primary", map_so, inst)
else:
L_s = hlr_utils.get_value(dist_source_sample, i, ls_descr)
L_s_err2 = hlr_utils.get_err2(dist_source_sample, i, ls_descr)
if dist_sample_detector is None:
(L_d, L_d_err2) = hlr_utils.get_parameter("secondary", map_so,
inst)
else:
L_d = hlr_utils.get_value(dist_sample_detector, i, ld_descr)
L_d_err2 = hlr_utils.get_err2(dist_sample_detector, i, ld_descr)
value = axis_manip.tof_to_final_velocity_dgs(val, err2, velocity_i[0],
velocity_i[1],
time_zero_offset[0],
time_zero_offset[1], L_s,
L_s_err2, L_d, L_d_err2)
# Remove all velocities < 0
if run_filter:
index = 0
for valx in value[0]:
if valx >= 0:
break
index += 1
value[0].__delslice__(0, index)
value[1].__delslice__(0, index)
map_so.y.__delslice__(0, index)
map_so.var_y.__delslice__(0, index)
if lojac:
val.__delslice__(0, index)
err2.__delslice__(0, index)
else:
pass
if lojac:
(map_so.y, map_so.var_y) = utils.linear_order_jacobian(
val, value[0], map_so.y, map_so.var_y)
# Need to reverse arrays due to conversion
if o_descr != "number":
valx = axis_manip.reverse_array_cp(value[0])
valxe = axis_manip.reverse_array_cp(value[1])
rev_value = (valx, valxe)
else:
rev_value = value
if map_so is not None:
map_so.y = axis_manip.reverse_array_cp(map_so.y)
map_so.var_y = axis_manip.reverse_array_cp(map_so.var_y)
hlr_utils.result_insert(result, res_descr, rev_value, map_so, "x",
axis)
return result
def tof_to_final_velocity_dgs(obj, velocity_i, time_zero_offset, **kwargs):
"""
This function converts a primary axis of a C{SOM} or C{SO} from
time-of-flight to final_velocity_dgs. The time-of-flight axis for a
C{SOM} must be in units of I{microseconds}. The primary axis of a C{SO} is
assumed to be in units of I{microseconds}. A C{tuple} of C{(tof, tof_err2)}
(assumed to be in units of I{microseconds}) can be converted to
C{(final_velocity_dgs, final_velocity_dgs_err2)}.
@param obj: Object to be converted
@type obj: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@param velocity_i: The initial velocity and its associated error^2
@type velocity_i: C{tuple}
@param time_zero_offset: The time zero offset and its associated error^2
@type time_zero_offset: C{tuple}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword dist_source_sample: The source to sample distance information and
its associated error^2
@type dist_source_sample: C{tuple} or C{list} of C{tuple}s
@keyword dist_sample_detector: The sample to detector distance information
and its associated error^2
@type dist_sample_detector: C{tuple} or C{list} of C{tuple}s
@keyword run_filter: This determines if the filter on the negative
velocities is run. The default setting is True.
@type run_filter: C{boolean}
@keyword lojac: A flag that allows one to turn off the calculation of the
linear-order Jacobian. The default action is True for
histogram data.
@type lojac: C{boolean}
@keyword units: The expected units for this function. The default for this
function is I{microseconds}
@type units: C{string}
@return: Object with a primary axis in time-of-flight converted to
final_velocity_dgs
@rtype: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@raise TypeError: The incoming object is not a type the function recognizes
@raise RuntimeError: The C{SOM} x-axis units are not I{microseconds}
"""
import hlr_utils
# 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:
dist_source_sample = kwargs["dist_source_sample"]
except KeyError:
dist_source_sample = None
try:
dist_sample_detector = kwargs["dist_sample_detector"]
except KeyError:
dist_sample_detector = None
try:
units = kwargs["units"]
except KeyError:
units = "microseconds"
try:
run_filter = kwargs["run_filter"]
except KeyError:
run_filter = True
try:
lojac = kwargs["lojac"]
except KeyError:
lojac = hlr_utils.check_lojac(obj)
# 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)
if res_descr == "SOM":
result = hlr_utils.force_units(result, "meters/microseconds", axis)
result.setAxisLabel(axis, "velocity")
result.setYUnits("Counts/meters/microseconds")
result.setYLabel("Intensity")
else:
pass
# Where to get instrument information
if dist_source_sample is None or dist_sample_detector is None:
if o_descr == "SOM":
try:
obj.attr_list.instrument.get_primary()
inst = obj.attr_list.instrument
except RuntimeError:
raise RuntimeError("A detector was not provided!")
else:
if dist_source_sample is None and dist_sample_detector is None:
raise RuntimeError("If a SOM is not passed, the "\
+"source-sample and sample-detector "\
+"distances must be provided.")
elif dist_source_sample is None:
raise RuntimeError("If a SOM is not passed, the "\
+"source-sample distance must be provided.")
elif dist_sample_detector is None:
raise RuntimeError("If a SOM is not passed, the "\
+"sample-detector distance must be "\
+"provided.")
else:
raise RuntimeError("If you get here, see Steve Miller for "\
+"your mug.")
else:
pass
if dist_source_sample is not None:
ls_descr = hlr_utils.get_descr(dist_source_sample)
# Do nothing, go on
else:
pass
if dist_sample_detector is not None:
ld_descr = hlr_utils.get_descr(dist_sample_detector)
# Do nothing, go on
else:
pass
# iterate through the values
import axis_manip
if lojac:
import utils
len_obj = hlr_utils.get_length(obj)
for i in xrange(len_obj):
val = hlr_utils.get_value(obj, i, o_descr, "x", axis)
err2 = hlr_utils.get_err2(obj, i, o_descr, "x", axis)
map_so = hlr_utils.get_map_so(obj, None, i)
if dist_source_sample is None:
(L_s, L_s_err2) = hlr_utils.get_parameter("primary", map_so, inst)
else:
L_s = hlr_utils.get_value(dist_source_sample, i, ls_descr)
L_s_err2 = hlr_utils.get_err2(dist_source_sample, i, ls_descr)
if dist_sample_detector is None:
(L_d, L_d_err2) = hlr_utils.get_parameter("secondary", map_so,
inst)
else:
L_d = hlr_utils.get_value(dist_sample_detector, i, ld_descr)
L_d_err2 = hlr_utils.get_err2(dist_sample_detector, i, ld_descr)
value = axis_manip.tof_to_final_velocity_dgs(val, err2,
velocity_i[0],
velocity_i[1],
time_zero_offset[0],
time_zero_offset[1],
L_s, L_s_err2,
L_d, L_d_err2)
# Remove all velocities < 0
if run_filter:
index = 0
for valx in value[0]:
if valx >= 0:
break
index += 1
value[0].__delslice__(0, index)
value[1].__delslice__(0, index)
map_so.y.__delslice__(0, index)
map_so.var_y.__delslice__(0, index)
if lojac:
val.__delslice__(0, index)
err2.__delslice__(0, index)
else:
pass
if lojac:
(map_so.y,
map_so.var_y) = utils.linear_order_jacobian(val,
value[0],
map_so.y,
map_so.var_y)
# Need to reverse arrays due to conversion
if o_descr != "number":
valx = axis_manip.reverse_array_cp(value[0])
valxe = axis_manip.reverse_array_cp(value[1])
rev_value = (valx, valxe)
else:
rev_value = value
if map_so is not None:
map_so.y = axis_manip.reverse_array_cp(map_so.y)
map_so.var_y = axis_manip.reverse_array_cp(map_so.var_y)
hlr_utils.result_insert(result, res_descr, rev_value, map_so,
"x", axis)
return result
def initial_wavelength_igs_lin_time_zero_to_tof(obj, **kwargs):
"""
This function converts a primary axis of a C{SOM} or C{SO} from
initial_wavelength_igs_lin_time_zero to time-of-flight. The
initial_wavelength_igs_lin_time_zero axis for a C{SOM} must be in units of
I{Angstroms}. The primary axis of a C{SO} is assumed to be in units of
I{Angstroms}. A C{tuple} of C{(initial_wavelength_igs_lin_time_zero,
initial_wavelength_igs_lin_time_zero_err2)} (assumed to be in units of
I{Angstroms}) can be converted to C{(tof, tof_err2)}.
@param obj: Object to be converted
@type obj: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword lambda_f:The final wavelength and its associated error^2
@type lambda_f: C{tuple}
@keyword time_zero_slope: The time zero slope and its associated error^2
@type time_zero_slope: C{tuple}
@keyword time_zero_offset: The time zero offset and its associated error^2
@type time_zero_offset: C{tuple}
@keyword dist_source_sample: The source to sample distance information and
its associated error^2
@type dist_source_sample: C{tuple} or C{list} of C{tuple}s
@keyword dist_sample_detector: The sample to detector distance information
and its associated error^2
@type dist_sample_detector: C{tuple} or C{list} of C{tuple}s
@keyword lojac: A flag that allows one to turn off the calculation of the
linear-order Jacobian. The default action is True for
histogram data.
@type lojac: C{boolean}
@keyword units: The expected units for this function. The default for this
function is I{Angstroms}
@type units: C{string}
@return: Object with a primary axis in initial_wavelength_igs converted to
time-of-flight
@rtype: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@raise TypeError: The incoming object is not a type the function recognizes
@raise RuntimeError: The C{SOM} x-axis units are not I{Angstroms}
"""
# import the helper functions
import hlr_utils
# 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:
lambda_f = kwargs["lambda_f"]
except KeyError:
lambda_f = None
try:
time_zero_slope = kwargs["time_zero_slope"]
except KeyError:
time_zero_slope = None
# Current constants for Time Zero Slope
TIME_ZERO_SLOPE = (float(0.0), float(0.0))
try:
time_zero_offset = kwargs["time_zero_offset"]
except KeyError:
time_zero_offset = None
# Current constants for Time Zero Offset
TIME_ZERO_OFFSET = (float(0.0), float(0.0))
try:
dist_source_sample = kwargs["dist_source_sample"]
except KeyError:
dist_source_sample = None
try:
dist_sample_detector = kwargs["dist_sample_detector"]
except KeyError:
dist_sample_detector = None
try:
lojac = kwargs["lojac"]
except KeyError:
lojac = hlr_utils.check_lojac(obj)
try:
units = kwargs["units"]
except KeyError:
units = "Angstroms"
# 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)
if res_descr == "SOM":
result = hlr_utils.force_units(result, "Microseconds", axis)
result.setAxisLabel(axis, "time-of-flight")
result.setYUnits("Counts/uS")
result.setYLabel("Intensity")
else:
pass
# Where to get instrument information
if dist_source_sample is None or dist_sample_detector is None:
if o_descr == "SOM":
try:
obj.attr_list.instrument.get_primary()
inst = obj.attr_list.instrument
except RuntimeError:
raise RuntimeError("A detector was not provided!")
else:
if dist_source_sample is None and dist_sample_detector is None:
raise RuntimeError("If a SOM is not passed, the "\
+"source-sample and sample-detector "\
+"distances must be provided.")
elif dist_source_sample is None:
raise RuntimeError("If a SOM is not passed, the "\
+"source-sample distance must be provided.")
elif dist_sample_detector is None:
raise RuntimeError("If a SOM is not passed, the "\
+"sample-detector distance must be "\
+"provided.")
else:
raise RuntimeError("If you get here, see Steve Miller for "\
+"your mug.")
else:
pass
if lambda_f is not None:
l_descr = hlr_utils.get_descr(lambda_f)
else:
if o_descr == "SOM":
try:
som_l_f = obj.attr_list["Wavelength_final"]
except KeyError:
raise RuntimeError("Please provide a final wavelength "\
+"parameter either via the function call "\
+"or the SOM")
else:
raise RuntimeError("You need to provide a final wavelength")
if time_zero_slope is not None:
t_0_slope_descr = hlr_utils.get_descr(time_zero_slope)
else:
if o_descr == "SOM":
try:
t_0_slope = obj.attr_list["Time_zero_slope"][0]
t_0_slope_err2 = obj.attr_list["Time_zero_slope"][1]
except KeyError:
t_0_slope = TIME_ZERO_SLOPE[0]
t_0_slope_err2 = TIME_ZERO_SLOPE[1]
else:
t_0_slope = TIME_ZERO_SLOPE[0]
t_0_slope_err2 = TIME_ZERO_SLOPE[1]
if time_zero_offset is not None:
t_0_offset_descr = hlr_utils.get_descr(time_zero_offset)
else:
if o_descr == "SOM":
try:
t_0_offset = obj.attr_list["Time_zero_offset"][0]
t_0_offset_err2 = obj.attr_list["Time_zero_offset"][1]
except KeyError:
t_0_offset = TIME_ZERO_OFFSET[0]
t_0_offset_err2 = TIME_ZERO_OFFSET[1]
else:
t_0_offset = TIME_ZERO_OFFSET[0]
t_0_offset_err2 = TIME_ZERO_OFFSET[1]
if dist_source_sample is not None:
ls_descr = hlr_utils.get_descr(dist_source_sample)
# Do nothing, go on
else:
pass
if dist_sample_detector is not None:
ld_descr = hlr_utils.get_descr(dist_sample_detector)
# Do nothing, go on
else:
pass
# iterate through the values
len_obj = hlr_utils.get_length(obj)
MNEUT_OVER_H = 1.0 / 0.003956034
MNEUT_OVER_H2 = MNEUT_OVER_H * MNEUT_OVER_H
for i in xrange(len_obj):
val = hlr_utils.get_value(obj, i, o_descr, "x", axis)
err2 = hlr_utils.get_err2(obj, i, o_descr, "x", axis)
map_so = hlr_utils.get_map_so(obj, None, i)
if dist_source_sample is None:
(L_s, L_s_err2) = hlr_utils.get_parameter("primary", map_so, inst)
else:
L_s = hlr_utils.get_value(dist_source_sample, i, ls_descr)
L_s_err2 = hlr_utils.get_err2(dist_source_sample, i, ls_descr)
if dist_sample_detector is None:
(L_d, L_d_err2) = hlr_utils.get_parameter("secondary", map_so,
inst)
else:
L_d = hlr_utils.get_value(dist_sample_detector, i, ld_descr)
L_d_err2 = hlr_utils.get_err2(dist_sample_detector, i, ld_descr)
if lambda_f is not None:
l_f = hlr_utils.get_value(lambda_f, i, l_descr)
l_f_err2 = hlr_utils.get_err2(lambda_f, i, l_descr)
else:
l_f_tuple = hlr_utils.get_special(som_l_f, map_so)
l_f = l_f_tuple[0]
l_f_err2 = l_f_tuple[1]
if time_zero_slope is not None:
t_0_slope = hlr_utils.get_value(time_zero_slope, i,
t_0_slope_descr)
t_0_slope_err2 = hlr_utils.get_err2(time_zero_slope, i,
t_0_slope_descr)
else:
pass
if time_zero_offset is not None:
t_0_offset = hlr_utils.get_value(time_zero_offset, i,
t_0_offset_descr)
t_0_offset_err2 = hlr_utils.get_err2(time_zero_offset, i,
t_0_offset_descr)
else:
pass
# Going to violate rules since the current usage is with a single
# number. When an SCL equivalent function arises, this code can be
# fixed.
front_const = MNEUT_OVER_H * L_s + t_0_slope
term2 = MNEUT_OVER_H * l_f * L_d
tof = (front_const * val) + term2 + t_0_offset
front_const2 = front_const * front_const
eterm1 = l_f * l_f * L_d_err2
eterm2 = L_d * L_d * l_f_err2
eterm3 = MNEUT_OVER_H2 * L_s_err2
tof_err2 = (front_const2 * err2) + (val * val) * \
(eterm3 + t_0_slope_err2) + (MNEUT_OVER_H2 * \
(eterm1 + eterm2)) + \
t_0_offset_err2
hlr_utils.result_insert(result, res_descr, (tof, tof_err2), None,
"all")
return result
def tof_to_initial_wavelength_igs_lin_time_zero(obj, **kwargs):
"""
This function converts a primary axis of a C{SOM} or C{SO} from
time-of-flight to initial_wavelength_igs_lin_time_zero. The time-of-flight
axis for a C{SOM} must be in units of I{microseconds}. The primary axis of
a C{SO} is assumed to be in units of I{microseconds}. A C{tuple} of
C{(tof, tof_err2)} (assumed to be in units of I{microseconds}) can be
converted to C{(initial_wavelength_igs, initial_wavelength_igs_err2)}.
@param obj: Object to be converted
@type obj: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword lambda_f:The final wavelength and its associated error^2
@type lambda_f: C{tuple}
@keyword time_zero_slope: The time zero slope and its associated error^2
@type time_zero_slope: C{tuple}
@keyword time_zero_offset: The time zero offset and its associated error^2
@type time_zero_offset: C{tuple}
@keyword dist_source_sample: The source to sample distance information and
its associated error^2
@type dist_source_sample: C{tuple} or C{list} of C{tuple}s
@keyword dist_sample_detector: The sample to detector distance information
and its associated error^2
@type dist_sample_detector: C{tuple} or C{list} of C{tuple}s
@keyword run_filter: This determines if the filter on the negative
wavelengths is run. The default setting is True.
@type run_filter: C{boolean}
@keyword lojac: A flag that allows one to turn off the calculation of the
linear-order Jacobian. The default action is True for
histogram data.
@type lojac: C{boolean}
@keyword units: The expected units for this function. The default for this
function is I{microseconds}
@type units: C{string}
@return: Object with a primary axis in time-of-flight converted to
initial_wavelength_igs
@rtype: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@raise TypeError: The incoming object is not a type the function recognizes
@raise RuntimeError: The C{SOM} x-axis units are not I{microseconds}
"""
# import the helper functions
import hlr_utils
# 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:
lambda_f = kwargs["lambda_f"]
except KeyError:
lambda_f = None
try:
time_zero_slope = kwargs["time_zero_slope"]
except KeyError:
time_zero_slope = None
# Current constants for Time Zero Slope
TIME_ZERO_SLOPE = (float(0.0), float(0.0))
try:
time_zero_offset = kwargs["time_zero_offset"]
except KeyError:
time_zero_offset = None
# Current constants for Time Zero Offset
TIME_ZERO_OFFSET = (float(0.0), float(0.0))
try:
dist_source_sample = kwargs["dist_source_sample"]
except KeyError:
dist_source_sample = None
try:
dist_sample_detector = kwargs["dist_sample_detector"]
except KeyError:
dist_sample_detector = None
try:
lojac = kwargs["lojac"]
except KeyError:
lojac = hlr_utils.check_lojac(obj)
try:
units = kwargs["units"]
except KeyError:
units = "microseconds"
try:
run_filter = kwargs["run_filter"]
except KeyError:
run_filter = True
try:
iobj = kwargs["iobj"]
except KeyError:
iobj = None
# 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)
if res_descr == "SOM":
result = hlr_utils.force_units(result, "Angstroms", axis)
result.setAxisLabel(axis, "wavelength")
result.setYUnits("Counts/A")
result.setYLabel("Intensity")
else:
pass
# Where to get instrument information
if dist_source_sample is None or dist_sample_detector is None:
if o_descr == "SOM":
try:
obj.attr_list.instrument.get_primary()
inst = obj.attr_list.instrument
mobj = obj
except RuntimeError:
raise RuntimeError("A detector was not provided!")
else:
if iobj is None:
if dist_source_sample is None and dist_sample_detector is None:
raise RuntimeError("If a SOM is not passed, the "\
+"source-sample and sample-detector "\
+"distances must be provided.")
elif dist_source_sample is None:
raise RuntimeError("If a SOM is not passed, the "\
+"source-sample distance must be "\
+"provided.")
elif dist_sample_detector is None:
raise RuntimeError("If a SOM is not passed, the "\
+"sample-detector distance must be "\
+"provided.")
else:
raise RuntimeError("If you get here, see Steve Miller "\
+"for your mug.")
else:
inst = iobj.attr_list.instrument
mobj = iobj
else:
mobj = obj
if lambda_f is not None:
l_descr = hlr_utils.get_descr(lambda_f)
else:
if o_descr == "SOM":
try:
som_l_f = obj.attr_list["Wavelength_final"]
except KeyError:
raise RuntimeError("Please provide a final wavelength "\
+"parameter either via the function call "\
+"or the SOM")
else:
if iobj is None:
raise RuntimeError("You need to provide a final wavelength")
else:
som_l_f = iobj.attr_list["Wavelength_final"]
if time_zero_slope is not None:
t_0_slope_descr = hlr_utils.get_descr(time_zero_slope)
else:
if o_descr == "SOM":
try:
t_0_slope = obj.attr_list["Time_zero_slope"][0]
t_0_slope_err2 = obj.attr_list["Time_zero_slope"][1]
except KeyError:
t_0_slope = TIME_ZERO_SLOPE[0]
t_0_slope_err2 = TIME_ZERO_SLOPE[1]
else:
t_0_slope = TIME_ZERO_SLOPE[0]
t_0_slope_err2 = TIME_ZERO_SLOPE[1]
if time_zero_offset is not None:
t_0_offset_descr = hlr_utils.get_descr(time_zero_offset)
else:
if o_descr == "SOM":
try:
t_0_offset = obj.attr_list["Time_zero_offset"][0]
t_0_offset_err2 = obj.attr_list["Time_zero_offset"][1]
except KeyError:
t_0_offset = TIME_ZERO_OFFSET[0]
t_0_offset_err2 = TIME_ZERO_OFFSET[1]
else:
t_0_offset = TIME_ZERO_OFFSET[0]
t_0_offset_err2 = TIME_ZERO_OFFSET[1]
if dist_source_sample is not None:
ls_descr = hlr_utils.get_descr(dist_source_sample)
# Do nothing, go on
else:
pass
if dist_sample_detector is not None:
ld_descr = hlr_utils.get_descr(dist_sample_detector)
# Do nothing, go on
else:
pass
# iterate through the values
import axis_manip
if lojac:
import utils
for i in xrange(hlr_utils.get_length(obj)):
val = hlr_utils.get_value(obj, i, o_descr, "x", axis)
err2 = hlr_utils.get_err2(obj, i, o_descr, "x", axis)
map_so = hlr_utils.get_map_so(mobj, None, i)
if dist_source_sample is None:
(L_s, L_s_err2) = hlr_utils.get_parameter("primary", map_so, inst)
else:
L_s = hlr_utils.get_value(dist_source_sample, i, ls_descr)
L_s_err2 = hlr_utils.get_err2(dist_source_sample, i, ls_descr)
if dist_sample_detector is None:
(L_d, L_d_err2) = hlr_utils.get_parameter("secondary", map_so,
inst)
else:
L_d = hlr_utils.get_value(dist_sample_detector, i, ld_descr)
L_d_err2 = hlr_utils.get_err2(dist_sample_detector, i, ld_descr)
if lambda_f is not None:
l_f = hlr_utils.get_value(lambda_f, i, l_descr)
l_f_err2 = hlr_utils.get_err2(lambda_f, i, l_descr)
else:
l_f_tuple = hlr_utils.get_special(som_l_f, map_so)
l_f = l_f_tuple[0]
l_f_err2 = l_f_tuple[1]
if time_zero_slope is not None:
t_0_slope = hlr_utils.get_value(time_zero_slope, i,
t_0_slope_descr)
t_0_slope_err2 = hlr_utils.get_err2(time_zero_slope, i,
t_0_slope_descr)
else:
pass
if time_zero_offset is not None:
t_0_offset = hlr_utils.get_value(time_zero_offset, i,
t_0_offset_descr)
t_0_offset_err2 = hlr_utils.get_err2(time_zero_offset, i,
t_0_offset_descr)
else:
pass
value = axis_manip.tof_to_initial_wavelength_igs_lin_time_zero(
val, err2, l_f, l_f_err2, t_0_slope, t_0_slope_err2, t_0_offset,
t_0_offset_err2, L_s, L_s_err2, L_d, L_d_err2)
# Remove all wavelengths < 0
if run_filter:
index = 0
for valx in value[0]:
if valx >= 0:
break
index += 1
value[0].__delslice__(0, index)
value[1].__delslice__(0, index)
map_so.y.__delslice__(0, index)
map_so.var_y.__delslice__(0, index)
if lojac:
val.__delslice__(0, index)
err2.__delslice__(0, index)
else:
pass
if lojac:
try:
counts = utils.linear_order_jacobian(val, value[0], map_so.y,
map_so.var_y)
except Exception, e:
# Lets us know offending pixel ID
raise Exception(str(map_so.id) + " " + str(e))
hlr_utils.result_insert(result, res_descr, counts, map_so, "all",
axis, [value[0]])
else:
hlr_utils.result_insert(result, res_descr, value, map_so, "x",
axis)
def tof_to_initial_wavelength_igs(obj, **kwargs):
"""
This function converts a primary axis of a C{SOM} or C{SO} from
time-of-flight to initial_wavelength_igs. The time-of-flight axis for a
C{SOM} must be in units of I{microseconds}. The primary axis of a C{SO} is
assumed to be in units of I{microseconds}. A C{tuple} of C{(tof, tof_err2)}
(assumed to be in units of I{microseconds}) can be converted to
C{(initial_wavelength_igs, initial_wavelength_igs_err2)}.
@param obj: Object to be converted
@type obj: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword lambda_f:The final wavelength and its associated error^2
@type lambda_f: C{tuple}
@keyword time_zero: The time zero offset and its associated error^2
@type time_zero: C{tuple}
@keyword dist_source_sample: The source to sample distance information and
its associated error^2
@type dist_source_sample: C{tuple} or C{list} of C{tuple}s
@keyword dist_sample_detector: The sample to detector distance information
and its associated error^2
@type dist_sample_detector: C{tuple} or C{list} of C{tuple}s
@keyword run_filter: This determines if the filter on the negative
wavelengths is run. The default setting is True.
@type run_filter: C{boolean}
@keyword units: The expected units for this function. The default for this
function is I{microseconds}
@type units: C{string}
@return: Object with a primary axis in time-of-flight converted to
initial_wavelength_igs
@rtype: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@raise TypeError: The incoming object is not a type the function recognizes
@raise RuntimeError: The C{SOM} x-axis units are not I{microseconds}
"""
# import the helper functions
import hlr_utils
# 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:
lambda_f = kwargs["lambda_f"]
except KeyError:
lambda_f = None
try:
time_zero = kwargs["time_zero"]
except KeyError:
time_zero = None
try:
dist_source_sample = kwargs["dist_source_sample"]
except KeyError:
dist_source_sample = None
try:
dist_sample_detector = kwargs["dist_sample_detector"]
except KeyError:
dist_sample_detector = None
try:
units = kwargs["units"]
except KeyError:
units = "microseconds"
try:
run_filter = kwargs["run_filter"]
except KeyError:
run_filter = True
# 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)
if res_descr == "SOM":
result = hlr_utils.force_units(result, "Angstroms", axis)
result.setAxisLabel(axis, "wavelength")
result.setYUnits("Counts/A")
result.setYLabel("Intensity")
else:
pass
# Where to get instrument information
if dist_source_sample is None or dist_sample_detector is None:
if o_descr == "SOM":
try:
obj.attr_list.instrument.get_primary()
inst = obj.attr_list.instrument
except RuntimeError:
raise RuntimeError("A detector was not provided!")
else:
if dist_source_sample is None and dist_sample_detector is None:
raise RuntimeError("If a SOM is not passed, the "\
+"source-sample and sample-detector "\
+"distances must be provided.")
elif dist_source_sample is None:
raise RuntimeError("If a SOM is not passed, the "\
+"source-sample distance must be provided.")
elif dist_sample_detector is None:
raise RuntimeError("If a SOM is not passed, the "\
+"sample-detector distance must be "\
+"provided.")
else:
raise RuntimeError("If you get here, see Steve Miller for "\
+"your mug.")
else:
pass
if lambda_f is not None:
l_descr = hlr_utils.get_descr(lambda_f)
else:
if o_descr == "SOM":
try:
som_l_f = obj.attr_list["Wavelength_final"]
except KeyError:
raise RuntimeError("Please provide a final wavelength "\
+"parameter either via the function call "\
+"or the SOM")
else:
raise RuntimeError("You need to provide a final wavelength")
if time_zero is not None:
t_descr = hlr_utils.get_descr(time_zero)
else:
if o_descr == "SOM":
try:
t_0 = obj.attr_list["Time_zero"][0]
t_0_err2 = obj.attr_list["Time_zero"][1]
except KeyError:
raise RuntimeError("Please provide a time-zero "\
+"parameter either via the function call "\
+"or the SOM")
else:
t_0 = 0.0
t_0_err2 = 0.0
if dist_source_sample is not None:
ls_descr = hlr_utils.get_descr(dist_source_sample)
# Do nothing, go on
else:
pass
if dist_sample_detector is not None:
ld_descr = hlr_utils.get_descr(dist_sample_detector)
# Do nothing, go on
else:
pass
# iterate through the values
import axis_manip
for i in xrange(hlr_utils.get_length(obj)):
val = hlr_utils.get_value(obj, i, o_descr, "x", axis)
err2 = hlr_utils.get_err2(obj, i, o_descr, "x", axis)
map_so = hlr_utils.get_map_so(obj, None, i)
if dist_source_sample is None:
(L_s, L_s_err2) = hlr_utils.get_parameter("primary", map_so, inst)
else:
L_s = hlr_utils.get_value(dist_source_sample, i, ls_descr)
L_s_err2 = hlr_utils.get_err2(dist_source_sample, i, ls_descr)
if dist_sample_detector is None:
(L_d, L_d_err2) = hlr_utils.get_parameter("secondary", map_so,
inst)
else:
L_d = hlr_utils.get_value(dist_sample_detector, i, ld_descr)
L_d_err2 = hlr_utils.get_err2(dist_sample_detector, i, ld_descr)
if lambda_f is not None:
l_f = hlr_utils.get_value(lambda_f, i, l_descr)
l_f_err2 = hlr_utils.get_err2(lambda_f, i, l_descr)
else:
l_f_tuple = hlr_utils.get_special(som_l_f, map_so)
l_f = l_f_tuple[0]
l_f_err2 = l_f_tuple[1]
if time_zero is not None:
t_0 = hlr_utils.get_value(time_zero, i, t_descr)
t_0_err2 = hlr_utils.get_err2(time_zero, i, t_descr)
else:
pass
value = axis_manip.tof_to_initial_wavelength_igs(
val, err2, l_f, l_f_err2, t_0, t_0_err2, L_s, L_s_err2, L_d,
L_d_err2)
# Remove all wavelengths < 0
if run_filter:
index = 0
for val in value[0]:
if val >= 0:
break
index += 1
value[0].__delslice__(0, index)
value[1].__delslice__(0, index)
map_so.y.__delslice__(0, index)
map_so.var_y.__delslice__(0, index)
else:
pass
hlr_utils.result_insert(result, res_descr, value, map_so, "x", axis)
return result
def create_E_vs_Q_igs(som, *args, **kwargs):
"""
This function starts with the initial IGS wavelength axis and turns this
into a 2D spectra with E and Q axes.
@param som: The input object with initial IGS wavelength axis
@type som: C{SOM.SOM}
@param args: A mandatory list of axes for rebinning. There is a particular
order to them. They should be present in the following order:
Without errors
1. Energy transfer
2. Momentum transfer
With errors
1. Energy transfer
2. Energy transfer error^2
3. Momentum transfer
4. Momentum transfer error ^2
@type args: C{nessi_list.NessiList}s
@param kwargs: A list of keyword arguments that the function accepts:
@keyword withXVar: Flag for whether the function should be expecting the
associated axes to have errors. The default value will
be I{False}.
@type withXVar: C{boolean}
@keyword data_type: Name of the data type which can be either I{histogram},
I{density} or I{coordinate}. The default value will be
I{histogram}
@type data_type: C{string}
@keyword Q_filter: Flag to turn on or off Q filtering. The default behavior
is I{True}.
@type Q_filter: C{boolean}
@keyword so_id: The identifier represents a number, string, tuple or other
object that describes the resulting C{SO}
@type so_id: C{int}, C{string}, C{tuple}, C{pixel ID}
@keyword y_label: The y axis label
@type y_label: C{string}
@keyword y_units: The y axis units
@type y_units: C{string}
@keyword x_labels: This is a list of names that sets the individual x axis
labels
@type x_labels: C{list} of C{string}s
@keyword x_units: This is a list of names that sets the individual x axis
units
@type x_units: C{list} of C{string}s
@keyword split: This flag causes the counts and the fractional area to
be written out into separate files.
@type split: C{boolean}
@keyword configure: This is the object containing the driver configuration.
@type configure: C{Configure}
@return: Object containing a 2D C{SO} with E and Q axes
@rtype: C{SOM.SOM}
@raise RuntimeError: Anything other than a C{SOM} is passed to the function
@raise RuntimeError: An instrument is not contained in the C{SOM}
"""
import nessi_list
# Setup some variables
dim = 2
N_y = []
N_tot = 1
N_args = len(args)
# Get T0 slope in order to calculate dT = dT_i + dT_0
try:
t_0_slope = som.attr_list["Time_zero_slope"][0]
t_0_slope_err2 = som.attr_list["Time_zero_slope"][1]
except KeyError:
t_0_slope = float(0.0)
t_0_slope_err2 = float(0.0)
# Check withXVar keyword argument and also check number of given args.
# Set xvar to the appropriate value
try:
value = kwargs["withXVar"]
if value.lower() == "true":
if N_args != 4:
raise RuntimeError("Since you have requested x errors, 4 x "\
+"axes must be provided.")
else:
xvar = True
elif value.lower() == "false":
if N_args != 2:
raise RuntimeError("Since you did not requested x errors, 2 "\
+"x axes must be provided.")
else:
xvar = False
else:
raise RuntimeError("Do not understand given parameter %s" % \
value)
except KeyError:
if N_args != 2:
raise RuntimeError("Since you did not requested x errors, 2 "\
+"x axes must be provided.")
else:
xvar = False
# Check dataType keyword argument. An offset will be set to 1 for the
# histogram type and 0 for either density or coordinate
try:
data_type = kwargs["data_type"]
if data_type.lower() == "histogram":
offset = 1
elif data_type.lower() == "density" or \
data_type.lower() == "coordinate":
offset = 0
else:
raise RuntimeError("Do not understand data type given: %s" % \
data_type)
# Default is offset for histogram
except KeyError:
offset = 1
try:
Q_filter = kwargs["Q_filter"]
except KeyError:
Q_filter = True
# Check for split keyword
try:
split = kwargs["split"]
except KeyError:
split = False
# Check for configure keyword
try:
configure = kwargs["configure"]
except KeyError:
configure = None
so_dim = SOM.SO(dim)
for i in range(dim):
# Set the x-axis arguments from the *args list into the new SO
if not xvar:
# Axis positions are 1 (Q) and 0 (E)
position = dim - i - 1
so_dim.axis[i].val = args[position]
else:
# Axis positions are 2 (Q), 3 (eQ), 0 (E), 1 (eE)
position = dim - 2 * i
so_dim.axis[i].val = args[position]
so_dim.axis[i].var = args[position + 1]
# Set individual value axis sizes (not x-axis size)
N_y.append(len(args[position]) - offset)
# Calculate total 2D array size
N_tot = N_tot * N_y[-1]
# Create y and var_y lists from total 2D size
so_dim.y = nessi_list.NessiList(N_tot)
so_dim.var_y = nessi_list.NessiList(N_tot)
# Create area sum and errors for the area sum lists from total 2D size
area_sum = nessi_list.NessiList(N_tot)
area_sum_err2 = nessi_list.NessiList(N_tot)
# Create area sum and errors for the area sum lists from total 2D size
bin_count = nessi_list.NessiList(N_tot)
bin_count_err2 = nessi_list.NessiList(N_tot)
inst = som.attr_list.instrument
lambda_final = som.attr_list["Wavelength_final"]
inst_name = inst.get_name()
import bisect
import math
import dr_lib
import utils
arr_len = 0
#: Vector of zeros for function calculations
zero_vec = None
for j in xrange(hlr_utils.get_length(som)):
# Get counts
counts = hlr_utils.get_value(som, j, "SOM", "y")
counts_err2 = hlr_utils.get_err2(som, j, "SOM", "y")
arr_len = len(counts)
zero_vec = nessi_list.NessiList(arr_len)
# Get mapping SO
map_so = hlr_utils.get_map_so(som, None, j)
# Get lambda_i
l_i = hlr_utils.get_value(som, j, "SOM", "x")
l_i_err2 = hlr_utils.get_err2(som, j, "SOM", "x")
# Get lambda_f from instrument information
l_f_tuple = hlr_utils.get_special(lambda_final, map_so)
l_f = l_f_tuple[0]
l_f_err2 = l_f_tuple[1]
# Get source to sample distance
(L_s, L_s_err2) = hlr_utils.get_parameter("primary", map_so, inst)
# Get sample to detector distance
L_d_tuple = hlr_utils.get_parameter("secondary", map_so, inst)
L_d = L_d_tuple[0]
# Get polar angle from instrument information
(angle, angle_err2) = hlr_utils.get_parameter("polar", map_so, inst)
# Get the detector pixel height
dh_tuple = hlr_utils.get_parameter("dh", map_so, inst)
dh = dh_tuple[0]
# Need dh in units of Angstrom
dh *= 1e10
# Calculate T_i
(T_i, T_i_err2) = axis_manip.wavelength_to_tof(l_i, l_i_err2,
L_s, L_s_err2)
# Scale counts by lambda_f / lambda_i
(l_i_bc, l_i_bc_err2) = utils.calc_bin_centers(l_i, l_i_err2)
(ratio, ratio_err2) = array_manip.div_ncerr(l_f, l_f_err2,
l_i_bc, l_i_bc_err2)
(counts, counts_err2) = array_manip.mult_ncerr(counts, counts_err2,
ratio, ratio_err2)
# Calculate E_i
(E_i, E_i_err2) = axis_manip.wavelength_to_energy(l_i, l_i_err2)
# Calculate E_f
(E_f, E_f_err2) = axis_manip.wavelength_to_energy(l_f, l_f_err2)
# Calculate E_t
(E_t, E_t_err2) = array_manip.sub_ncerr(E_i, E_i_err2, E_f, E_f_err2)
if inst_name == "BSS":
# Convert E_t from meV to ueV
(E_t, E_t_err2) = array_manip.mult_ncerr(E_t, E_t_err2,
1000.0, 0.0)
(counts, counts_err2) = array_manip.mult_ncerr(counts, counts_err2,
1.0/1000.0, 0.0)
# Convert lambda_i to k_i
(k_i, k_i_err2) = axis_manip.wavelength_to_scalar_k(l_i, l_i_err2)
# Convert lambda_f to k_f
(k_f, k_f_err2) = axis_manip.wavelength_to_scalar_k(l_f, l_f_err2)
# Convert k_i and k_f to Q
(Q, Q_err2) = axis_manip.init_scatt_wavevector_to_scalar_Q(k_i,
k_i_err2,
k_f,
k_f_err2,
angle,
angle_err2)
# Calculate dT = dT_0 + dT_i
dT_i = utils.calc_bin_widths(T_i, T_i_err2)
(l_i_bw, l_i_bw_err2) = utils.calc_bin_widths(l_i, l_i_err2)
dT_0 = array_manip.mult_ncerr(l_i_bw, l_i_bw_err2,
t_0_slope, t_0_slope_err2)
dT_tuple = array_manip.add_ncerr(dT_i[0], dT_i[1], dT_0[0], dT_0[1])
dT = dT_tuple[0]
# Calculate Jacobian
if inst_name == "BSS":
(x_1, x_2,
x_3, x_4) = dr_lib.calc_BSS_coeffs(map_so, inst, (E_i, E_i_err2),
(Q, Q_err2), (k_i, k_i_err2),
(T_i, T_i_err2), dh, angle,
E_f, k_f, l_f, L_s, L_d,
t_0_slope, zero_vec)
else:
raise RuntimeError("Do not know how to calculate x_i "\
+"coefficients for instrument %s" % inst_name)
(A, A_err2) = dr_lib.calc_EQ_Jacobian(x_1, x_2, x_3, x_4, dT, dh,
zero_vec)
# Apply Jacobian: C/dlam * dlam / A(EQ) = C/EQ
(jac_ratio, jac_ratio_err2) = array_manip.div_ncerr(l_i_bw,
l_i_bw_err2,
A, A_err2)
(counts, counts_err2) = array_manip.mult_ncerr(counts, counts_err2,
jac_ratio,
jac_ratio_err2)
# Reverse counts, E_t, k_i and Q
E_t = axis_manip.reverse_array_cp(E_t)
E_t_err2 = axis_manip.reverse_array_cp(E_t_err2)
Q = axis_manip.reverse_array_cp(Q)
Q_err2 = axis_manip.reverse_array_cp(Q_err2)
counts = axis_manip.reverse_array_cp(counts)
counts_err2 = axis_manip.reverse_array_cp(counts_err2)
k_i = axis_manip.reverse_array_cp(k_i)
x_1 = axis_manip.reverse_array_cp(x_1)
x_2 = axis_manip.reverse_array_cp(x_2)
x_3 = axis_manip.reverse_array_cp(x_3)
x_4 = axis_manip.reverse_array_cp(x_4)
dT = axis_manip.reverse_array_cp(dT)
# Filter for duplicate Q values
if Q_filter:
k_i_cutoff = k_f * math.cos(angle)
k_i_cutbin = bisect.bisect(k_i, k_i_cutoff)
counts.__delslice__(0, k_i_cutbin)
counts_err2.__delslice__(0, k_i_cutbin)
Q.__delslice__(0, k_i_cutbin)
Q_err2.__delslice__(0, k_i_cutbin)
E_t.__delslice__(0, k_i_cutbin)
E_t_err2.__delslice__(0, k_i_cutbin)
x_1.__delslice__(0, k_i_cutbin)
x_2.__delslice__(0, k_i_cutbin)
x_3.__delslice__(0, k_i_cutbin)
x_4.__delslice__(0, k_i_cutbin)
dT.__delslice__(0, k_i_cutbin)
zero_vec.__delslice__(0, k_i_cutbin)
try:
if inst_name == "BSS":
((Q_1, E_t_1),
(Q_2, E_t_2),
(Q_3, E_t_3),
(Q_4, E_t_4)) = dr_lib.calc_BSS_EQ_verticies((E_t, E_t_err2),
(Q, Q_err2), x_1,
x_2, x_3, x_4,
dT, dh, zero_vec)
else:
raise RuntimeError("Do not know how to calculate (Q_i, "\
+"E_t_i) verticies for instrument %s" \
% inst_name)
except IndexError:
# All the data got Q filtered, move on
continue
try:
(y_2d, y_2d_err2,
area_new,
bin_count_new) = axis_manip.rebin_2D_quad_to_rectlin(Q_1, E_t_1,
Q_2, E_t_2,
Q_3, E_t_3,
Q_4, E_t_4,
counts,
counts_err2,
so_dim.axis[0].val,
so_dim.axis[1].val)
except IndexError, e:
# Get the offending index from the error message
index = int(str(e).split()[1].split('index')[-1].strip('[]'))
print "Id:", map_so.id
print "Index:", index
print "Verticies: %f, %f, %f, %f, %f, %f, %f, %f" % (Q_1[index],
E_t_1[index],
Q_2[index],
E_t_2[index],
Q_3[index],
E_t_3[index],
Q_4[index],
E_t_4[index])
raise IndexError(str(e))
# Add in together with previous results
(so_dim.y, so_dim.var_y) = array_manip.add_ncerr(so_dim.y,
so_dim.var_y,
y_2d, y_2d_err2)
(area_sum, area_sum_err2) = array_manip.add_ncerr(area_sum,
area_sum_err2,
area_new,
area_sum_err2)
if configure.dump_pix_contrib or configure.scale_sqe:
if inst_name == "BSS":
dOmega = dr_lib.calc_BSS_solid_angle(map_so, inst)
(bin_count_new,
bin_count_err2) = array_manip.mult_ncerr(bin_count_new,
bin_count_err2,
dOmega, 0.0)
(bin_count,
bin_count_err2) = array_manip.add_ncerr(bin_count,
bin_count_err2,
bin_count_new,
bin_count_err2)
else:
del bin_count_new
def tof_to_initial_wavelength_igs(obj, **kwargs):
"""
This function converts a primary axis of a C{SOM} or C{SO} from
time-of-flight to initial_wavelength_igs. The time-of-flight axis for a
C{SOM} must be in units of I{microseconds}. The primary axis of a C{SO} is
assumed to be in units of I{microseconds}. A C{tuple} of C{(tof, tof_err2)}
(assumed to be in units of I{microseconds}) can be converted to
C{(initial_wavelength_igs, initial_wavelength_igs_err2)}.
@param obj: Object to be converted
@type obj: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword lambda_f:The final wavelength and its associated error^2
@type lambda_f: C{tuple}
@keyword time_zero: The time zero offset and its associated error^2
@type time_zero: C{tuple}
@keyword dist_source_sample: The source to sample distance information and
its associated error^2
@type dist_source_sample: C{tuple} or C{list} of C{tuple}s
@keyword dist_sample_detector: The sample to detector distance information
and its associated error^2
@type dist_sample_detector: C{tuple} or C{list} of C{tuple}s
@keyword run_filter: This determines if the filter on the negative
wavelengths is run. The default setting is True.
@type run_filter: C{boolean}
@keyword units: The expected units for this function. The default for this
function is I{microseconds}
@type units: C{string}
@return: Object with a primary axis in time-of-flight converted to
initial_wavelength_igs
@rtype: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@raise TypeError: The incoming object is not a type the function recognizes
@raise RuntimeError: The C{SOM} x-axis units are not I{microseconds}
"""
# import the helper functions
import hlr_utils
# 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:
lambda_f = kwargs["lambda_f"]
except KeyError:
lambda_f = None
try:
time_zero = kwargs["time_zero"]
except KeyError:
time_zero = None
try:
dist_source_sample = kwargs["dist_source_sample"]
except KeyError:
dist_source_sample = None
try:
dist_sample_detector = kwargs["dist_sample_detector"]
except KeyError:
dist_sample_detector = None
try:
units = kwargs["units"]
except KeyError:
units = "microseconds"
try:
run_filter = kwargs["run_filter"]
except KeyError:
run_filter = True
# 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)
if res_descr == "SOM":
result = hlr_utils.force_units(result, "Angstroms", axis)
result.setAxisLabel(axis, "wavelength")
result.setYUnits("Counts/A")
result.setYLabel("Intensity")
else:
pass
# Where to get instrument information
if dist_source_sample is None or dist_sample_detector is None:
if o_descr == "SOM":
try:
obj.attr_list.instrument.get_primary()
inst = obj.attr_list.instrument
except RuntimeError:
raise RuntimeError("A detector was not provided!")
else:
if dist_source_sample is None and dist_sample_detector is None:
raise RuntimeError("If a SOM is not passed, the "\
+"source-sample and sample-detector "\
+"distances must be provided.")
elif dist_source_sample is None:
raise RuntimeError("If a SOM is not passed, the "\
+"source-sample distance must be provided.")
elif dist_sample_detector is None:
raise RuntimeError("If a SOM is not passed, the "\
+"sample-detector distance must be "\
+"provided.")
else:
raise RuntimeError("If you get here, see Steve Miller for "\
+"your mug.")
else:
pass
if lambda_f is not None:
l_descr = hlr_utils.get_descr(lambda_f)
else:
if o_descr == "SOM":
try:
som_l_f = obj.attr_list["Wavelength_final"]
except KeyError:
raise RuntimeError("Please provide a final wavelength "\
+"parameter either via the function call "\
+"or the SOM")
else:
raise RuntimeError("You need to provide a final wavelength")
if time_zero is not None:
t_descr = hlr_utils.get_descr(time_zero)
else:
if o_descr == "SOM":
try:
t_0 = obj.attr_list["Time_zero"][0]
t_0_err2 = obj.attr_list["Time_zero"][1]
except KeyError:
raise RuntimeError("Please provide a time-zero "\
+"parameter either via the function call "\
+"or the SOM")
else:
t_0 = 0.0
t_0_err2 = 0.0
if dist_source_sample is not None:
ls_descr = hlr_utils.get_descr(dist_source_sample)
# Do nothing, go on
else:
pass
if dist_sample_detector is not None:
ld_descr = hlr_utils.get_descr(dist_sample_detector)
# Do nothing, go on
else:
pass
# iterate through the values
import axis_manip
for i in xrange(hlr_utils.get_length(obj)):
val = hlr_utils.get_value(obj, i, o_descr, "x", axis)
err2 = hlr_utils.get_err2(obj, i, o_descr, "x", axis)
map_so = hlr_utils.get_map_so(obj, None, i)
if dist_source_sample is None:
(L_s, L_s_err2) = hlr_utils.get_parameter("primary", map_so, inst)
else:
L_s = hlr_utils.get_value(dist_source_sample, i, ls_descr)
L_s_err2 = hlr_utils.get_err2(dist_source_sample, i, ls_descr)
if dist_sample_detector is None:
(L_d, L_d_err2) = hlr_utils.get_parameter("secondary", map_so,
inst)
else:
L_d = hlr_utils.get_value(dist_sample_detector, i, ld_descr)
L_d_err2 = hlr_utils.get_err2(dist_sample_detector, i, ld_descr)
if lambda_f is not None:
l_f = hlr_utils.get_value(lambda_f, i, l_descr)
l_f_err2 = hlr_utils.get_err2(lambda_f, i, l_descr)
else:
l_f_tuple = hlr_utils.get_special(som_l_f, map_so)
l_f = l_f_tuple[0]
l_f_err2 = l_f_tuple[1]
if time_zero is not None:
t_0 = hlr_utils.get_value(time_zero, i, t_descr)
t_0_err2 = hlr_utils.get_err2(time_zero, i, t_descr)
else:
pass
value = axis_manip.tof_to_initial_wavelength_igs(val, err2,
l_f, l_f_err2,
t_0, t_0_err2,
L_s, L_s_err2,
L_d, L_d_err2)
# Remove all wavelengths < 0
if run_filter:
index = 0
for val in value[0]:
if val >= 0:
break
index += 1
value[0].__delslice__(0, index)
value[1].__delslice__(0, index)
map_so.y.__delslice__(0, index)
map_so.var_y.__delslice__(0, index)
else:
pass
hlr_utils.result_insert(result, res_descr, value, map_so, "x", axis)
return result
def tof_to_wavelength_lin_time_zero(obj, **kwargs):
"""
This function converts a primary axis of a C{SOM} or C{SO} from
time-of-flight to wavelength incorporating a linear time zero which is a
described as a linear function of the wavelength. The time-of-flight axis
for a C{SOM} must be in units of I{microseconds}. The primary axis of a
C{SO} is assumed to be in units of I{microseconds}. A C{tuple} of C{(tof,
tof_err2)} (assumed to be in units of I{microseconds}) can be converted to
C{(wavelength, wavelength_err2)}.
@param obj: Object to be converted
@type obj: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword pathlength: The pathlength and its associated error^2
@type pathlength: C{tuple} or C{list} of C{tuple}s
@keyword time_zero_slope: The time zero slope and its associated error^2
@type time_zero_slope: C{tuple}
@keyword time_zero_offset: The time zero offset and its associated error^2
@type time_zero_offset: C{tuple}
@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 lojac: A flag that allows one to turn off the calculation of the
linear-order Jacobian. The default action is I{True} for
histogram data.
@type lojac: C{boolean}
@keyword units: The expected units for this function. The default for this
function is I{microseconds}.
@type units: C{string}
@keyword cut_val: Specify a wavelength to cut the spectra at.
@type cut_val: C{float}
@keyword cut_less: A flag that specifies cutting the spectra less than
C{cut_val}. The default is C{True}.
@type cut_less: C{boolean}
@return: Object with a primary axis in time-of-flight converted to
wavelength
@rtype: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@raise TypeError: The incoming object is not a type the function recognizes
@raise RuntimeError: The C{SOM} x-axis units are not I{microseconds}
@raise RuntimeError: A C{SOM} does not contain an instrument and no
pathlength was provided
@raise RuntimeError: No C{SOM} is provided and no pathlength given
"""
# import the helper functions
import hlr_utils
# 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:
inst_param = kwargs["inst_param"]
except KeyError:
inst_param = "primary"
try:
pathlength = kwargs["pathlength"]
except KeyError:
pathlength = None
try:
time_zero_slope = kwargs["time_zero_slope"]
except KeyError:
time_zero_slope = None
# Current constants for Time Zero Slope
TIME_ZERO_SLOPE = (float(0.0), float(0.0))
try:
time_zero_offset = kwargs["time_zero_offset"]
except KeyError:
time_zero_offset = None
# Current constants for Time Zero Offset
TIME_ZERO_OFFSET = (float(0.0), float(0.0))
try:
lojac = kwargs["lojac"]
except KeyError:
lojac = hlr_utils.check_lojac(obj)
try:
units = kwargs["units"]
except KeyError:
units = "microseconds"
try:
cut_val = kwargs["cut_val"]
except KeyError:
cut_val = None
try:
cut_less = kwargs["cut_less"]
except KeyError:
cut_less = True
# 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)
if res_descr == "SOM":
result = hlr_utils.force_units(result, "Angstroms", axis)
result.setAxisLabel(axis, "wavelength")
result.setYUnits("Counts/A")
result.setYLabel("Intensity")
else:
pass
if pathlength is not None:
p_descr = hlr_utils.get_descr(pathlength)
else:
if o_descr == "SOM":
try:
obj.attr_list.instrument.get_primary()
inst = obj.attr_list.instrument
except RuntimeError:
raise RuntimeError("A detector was not provided")
else:
raise RuntimeError("If no SOM is provided, then pathlength "\
+"information must be provided")
if time_zero_slope is not None:
t_0_slope_descr = hlr_utils.get_descr(time_zero_slope)
else:
if o_descr == "SOM":
try:
t_0_slope = obj.attr_list["Time_zero_slope"][0]
t_0_slope_err2 = obj.attr_list["Time_zero_slope"][1]
except KeyError:
t_0_slope = TIME_ZERO_SLOPE[0]
t_0_slope_err2 = TIME_ZERO_SLOPE[1]
else:
t_0_slope = TIME_ZERO_SLOPE[0]
t_0_slope_err2 = TIME_ZERO_SLOPE[1]
if time_zero_offset is not None:
t_0_offset_descr = hlr_utils.get_descr(time_zero_offset)
else:
if o_descr == "SOM":
try:
t_0_offset = obj.attr_list["Time_zero_offset"][0]
t_0_offset_err2 = obj.attr_list["Time_zero_offset"][1]
except KeyError:
t_0_offset = TIME_ZERO_OFFSET[0]
t_0_offset_err2 = TIME_ZERO_OFFSET[1]
else:
t_0_offset = TIME_ZERO_OFFSET[0]
t_0_offset_err2 = TIME_ZERO_OFFSET[1]
# iterate through the values
import axis_manip
if lojac or cut_val is not None:
import utils
for i in xrange(hlr_utils.get_length(obj)):
val = hlr_utils.get_value(obj, i, o_descr, "x", axis)
err2 = hlr_utils.get_err2(obj, i, o_descr, "x", axis)
map_so = hlr_utils.get_map_so(obj, None, i)
if pathlength is None:
(pl, pl_err2) = hlr_utils.get_parameter(inst_param, map_so, inst)
else:
pl = hlr_utils.get_value(pathlength, i, p_descr)
pl_err2 = hlr_utils.get_err2(pathlength, i, p_descr)
if time_zero_slope is not None:
t_0_slope = hlr_utils.get_value(time_zero_slope, i,
t_0_slope_descr)
t_0_slope_err2 = hlr_utils.get_err2(time_zero_slope, i,
t_0_slope_descr)
else:
pass
if time_zero_offset is not None:
t_0_offset = hlr_utils.get_value(time_zero_offset, i,
t_0_offset_descr)
t_0_offset_err2 = hlr_utils.get_err2(time_zero_offset, i,
t_0_offset_descr)
else:
pass
value = axis_manip.tof_to_wavelength_lin_time_zero(val, err2,
pl, pl_err2,
t_0_slope,
t_0_slope_err2,
t_0_offset,
t_0_offset_err2)
if cut_val is not None:
index = utils.bisect_helper(value[0], cut_val)
if cut_less:
# Need to cut at this index, so increment by one
index += 1
value[0].__delslice__(0, index)
value[1].__delslice__(0, index)
map_so.y.__delslice__(0, index)
map_so.var_y.__delslice__(0, index)
if lojac:
val.__delslice__(0, index)
err2.__delslice__(0, index)
else:
len_data = len(value[0])
# All axis arrays need starting index adjusted by one since
# they always carry one more bin than the data
value[0].__delslice__(index + 1, len_data)
value[1].__delslice__(index + 1, len_data)
map_so.y.__delslice__(index, len_data)
map_so.var_y.__delslice__(index, len_data)
if lojac:
val.__delslice__(index + 1, len_data)
err2.__delslice__(index + 1, len_data)
if lojac:
counts = utils.linear_order_jacobian(val, value[0],
map_so.y, map_so.var_y)
hlr_utils.result_insert(result, res_descr, counts, map_so,
"all", axis, [value[0]])
else:
hlr_utils.result_insert(result, res_descr, value, map_so,
"x", axis)
return result
def calc_BSS_coeffs(map_so, inst, *args):
"""
This function calculates the x_i coefficients for the BSS instrument
@param map_so: The spectrum object to calculate the coefficients for
@type map_so: C{SOM.SO}
@param inst: The instrument object associated with the data
@type inst: C{SOM.Instrument} or C{SOM.CompositeInstrument}
@param args: A list of parameters (C{tuple}s with value and err^2) used to
calculate the x_i coefficients
The following is a list of the arguments needed in there expected order
1. Initial Energy
2. Momentum Transfer
3. Initial Wavevector
4. Initial Time-of-Flight
5. Detector Pixel Height
6. Polar Angle
7. Final Energy
8. Final Wavevector
9. Final Wavelength
10. Source to Sample Distance
11. Sample to Detector Distance
12. Time-zero Slope
13. Vector of Zeros
@type args: C{list}
@return: The calculated coefficients (x_1, x_2, x_3, x_4)
@rtype: C{tuple} of 4 C{nessi_list.NessiList}s
"""
import math
# Settle out the arguments to sensible names
E_i = args[0][0]
E_i_err2 = args[0][1]
Q = args[1][0]
Q_err2 = args[1][1]
k_i = args[2][0]
k_i_err2 = args[2][1]
T_i = args[3][0]
T_i_err2 = args[3][1]
dh = args[4]
polar_angle = args[5]
E_f = args[6]
k_f = args[7]
l_f = args[8]
L_s = args[9]
L_d = args[10]
T_0_s = args[11]
zero_vec = args[12]
# Constant h/m_n (meters / microsecond)
H_OVER_MNEUT = 0.003956034e-10
# Get the differential geometry parameters
dlf_dh_tuple = hlr_utils.get_parameter("dlf_dh", map_so, inst)
dlf_dh = dlf_dh_tuple[0]
# dlf_dh should be unitless (Angstrom/Angstrom)
dlf_dh *= 1e-10
dpol_dh_tuple = hlr_utils.get_parameter("dpol_dh", map_so, inst)
dpol_dh = dpol_dh_tuple[0]
# Convert to radian/Angstrom
dpol_dh *= 1e-10
dpol_dtd_tuple = hlr_utils.get_parameter("dpol_dtd", map_so, inst)
dpol_dtd = dpol_dtd_tuple[0]
# Get the detector pixel angular width
dtd_tuple = hlr_utils.get_parameter("dtd", map_so, inst)
dtd = dtd_tuple[0]
# Calculate bin centric values
E_i_bc_tuple = utils.calc_bin_centers(E_i, E_i_err2)
E_i_bc = E_i_bc_tuple[0]
k_i_bc_tuple = utils.calc_bin_centers(k_i, k_i_err2)
k_i_bc = k_i_bc_tuple[0]
Q_bc_tuple = utils.calc_bin_centers(Q, Q_err2)
Q_bc = Q_bc_tuple[0]
T_i_bc_tuple = utils.calc_bin_centers(T_i, T_i_err2)
T_i_bc = T_i_bc_tuple[0]
# Get numeric values
sin_polar = math.sin(polar_angle)
cos_polar = math.cos(polar_angle)
length_ratio = L_d / L_s
lambda_const = ((2.0 * math.pi) / (l_f * l_f)) * dlf_dh
kf_cos_pol = k_f * cos_polar
kf_sin_pol = k_f * sin_polar
t0_slope_corr = 1.0 / (1.0 + H_OVER_MNEUT * (T_0_s / L_s))
dtd_over_dh = dtd / dh
# Calculate coefficients
x_1_tuple = __calc_x1(
k_i_bc,
Q_bc,
length_ratio,
k_f,
kf_cos_pol,
kf_sin_pol,
lambda_const,
dpol_dh,
dpol_dtd,
dtd_over_dh,
cos_polar,
t0_slope_corr,
zero_vec,
)
x_1 = x_1_tuple[0]
x_2_tuple = __calc_x2(k_i_bc, Q_bc, T_i_bc, kf_cos_pol, t0_slope_corr, zero_vec)
x_2 = x_2_tuple[0]
x_3_tuple = __calc_x3(k_i_bc, E_i_bc, length_ratio, E_f, k_f, lambda_const, t0_slope_corr, zero_vec)
x_3 = x_3_tuple[0]
x_4_tuple = __calc_x4(E_i_bc, T_i_bc, t0_slope_corr, zero_vec)
x_4 = x_4_tuple[0]
return (x_1, x_2, x_3, x_4)
def tof_to_wavelength(obj, **kwargs):
"""
This function converts a primary axis of a C{SOM} or C{SO} from
time-of-flight to wavelength. The wavelength axis for a C{SOM} must be in
units of I{microseconds}. The primary axis of a C{SO} is assumed to be in
units of I{microseconds}. A C{tuple} of C{(tof, tof_err2)} (assumed to be
in units of I{microseconds}) can be converted to C{(wavelength,
wavelength_err2)}.
@param obj: Object to be converted
@type obj: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword pathlength: The pathlength and its associated error^2
@type pathlength: C{tuple} or C{list} of C{tuple}s
@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 lojac: A flag that allows one to turn off the calculation of the
linear-order Jacobian. The default action is I{True} for
histogram data.
@type lojac: C{boolean}
@keyword units: The expected units for this function. The default for this
function is I{microseconds}.
@type units: C{string}
@return: Object with a primary axis in time-of-flight converted to
wavelength
@rtype: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@raise TypeError: The incoming object is not a type the function recognizes
@raise RuntimeError: The C{SOM} x-axis units are not I{microseconds}
@raise RuntimeError: A C{SOM} does not contain an instrument and no
pathlength was provided
@raise RuntimeError: No C{SOM} is provided and no pathlength given
"""
# import the helper functions
import hlr_utils
# 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:
inst_param = kwargs["inst_param"]
except KeyError:
inst_param = "primary"
try:
pathlength = kwargs["pathlength"]
except KeyError:
pathlength = None
try:
units = kwargs["units"]
except KeyError:
units = "microseconds"
try:
lojac = kwargs["lojac"]
except KeyError:
lojac = hlr_utils.check_lojac(obj)
# 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)
if res_descr == "SOM":
result = hlr_utils.force_units(result, "Angstroms", axis)
result.setAxisLabel(axis, "wavelength")
result.setYUnits("Counts/A")
result.setYLabel("Intensity")
else:
pass
if pathlength is not None:
p_descr = hlr_utils.get_descr(pathlength)
else:
if o_descr == "SOM":
try:
obj.attr_list.instrument.get_primary()
inst = obj.attr_list.instrument
except RuntimeError:
raise RuntimeError("A detector was not provided")
else:
raise RuntimeError("If no SOM is provided, then pathlength "\
+"information must be provided")
# iterate through the values
import axis_manip
if lojac:
import utils
for i in xrange(hlr_utils.get_length(obj)):
val = hlr_utils.get_value(obj, i, o_descr, "x", axis)
err2 = hlr_utils.get_err2(obj, i, o_descr, "x", axis)
map_so = hlr_utils.get_map_so(obj, None, i)
if pathlength is None:
(pl, pl_err2) = hlr_utils.get_parameter(inst_param, map_so, inst)
else:
pl = hlr_utils.get_value(pathlength, i, p_descr)
pl_err2 = hlr_utils.get_err2(pathlength, i, p_descr)
value = axis_manip.tof_to_wavelength(val, err2, pl, pl_err2)
if lojac:
y_val = hlr_utils.get_value(obj, i, o_descr, "y")
y_err2 = hlr_utils.get_err2(obj, i, o_descr, "y")
counts = utils.linear_order_jacobian(val, value[0],
y_val, y_err2)
hlr_utils.result_insert(result, res_descr, counts, map_so,
"all", axis, [value[0]])
else:
hlr_utils.result_insert(result, res_descr, value, map_so,
"x", axis)
return result
def wavelength_to_scalar_Q(obj, **kwargs):
"""
This function converts a primary axis of a C{SOM} or C{SO} from wavelength
to scalar Q. The wavelength axis for a C{SOM} must be in units of
I{Angstroms}. The primary axis of a C{SO} is assumed to be in units of
I{Angstroms}. A C{tuple} of C{(wavelength, wavelength_err2)} (assumed to
be in units of I{Angstroms}) can be converted to C{(scalar_Q,
scalar_Q_err2)}.
@param obj: Object to be converted
@type obj: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword polar: The polar angle and its associated error^2
@type polar: C{tuple} or C{list} of C{tuple}s
@keyword pathlength: The pathlength and its associated error^2
@type pathlength: C{tuple} or C{list} of C{tuple}s
@keyword units: The expected units for this function. The default for this
function is I{Angstroms}.
@type units: C{string}
@return: Object with a primary axis in wavelength converted to scalar Q
@rtype: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@raise TypeError: The incoming object is not a type the function recognizes
@raise RuntimeError: A C{SOM} is not passed and no polar angle is provided
@raise RuntimeError: The C{SOM} x-axis units are not I{Angstroms}
"""
# import the helper functions
import hlr_utils
# set up for working through data
(result, res_descr) = hlr_utils.empty_result(obj)
o_descr = hlr_utils.get_descr(obj)
if o_descr == "list":
raise TypeError("Do not know how to handle given type: %s" % \
o_descr)
else:
pass
# Setup keyword arguments
try:
polar = kwargs["polar"]
except KeyError:
polar = None
try:
units = kwargs["units"]
except KeyError:
units = "Angstroms"
try:
lojac = kwargs["lojac"]
except KeyError:
lojac = hlr_utils.check_lojac(obj)
# 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)
if res_descr == "SOM":
result = hlr_utils.force_units(result, "1/Angstroms", axis)
result.setAxisLabel(axis, "scalar wavevector transfer")
result.setYUnits("Counts/A-1")
result.setYLabel("Intensity")
else:
pass
if polar is None:
if o_descr == "SOM":
try:
obj.attr_list.instrument.get_primary()
inst = obj.attr_list.instrument
except RuntimeError:
raise RuntimeError("A detector was not provided!")
else:
raise RuntimeError("If no SOM is provided, then polar "\
+"information must be given.")
else:
p_descr = hlr_utils.get_descr(polar)
# iterate through the values
import axis_manip
if lojac:
import utils
for i in xrange(hlr_utils.get_length(obj)):
val = hlr_utils.get_value(obj, i, o_descr, "x", axis)
err2 = hlr_utils.get_err2(obj, i, o_descr, "x", axis)
map_so = hlr_utils.get_map_so(obj, None, i)
if polar is None:
(angle, angle_err2) = hlr_utils.get_parameter("polar", map_so,
inst)
else:
angle = hlr_utils.get_value(polar, i, p_descr)
angle_err2 = hlr_utils.get_err2(polar, i, p_descr)
value = axis_manip.wavelength_to_scalar_Q(val, err2, angle, angle_err2)
if lojac:
y_val = hlr_utils.get_value(obj, i, o_descr, "y")
y_err2 = hlr_utils.get_err2(obj, i, o_descr, "y")
counts = utils.linear_order_jacobian(val, value[0],
y_val, y_err2)
else:
pass
if o_descr != "number":
value1 = axis_manip.reverse_array_cp(value[0])
value2 = axis_manip.reverse_array_cp(value[1])
rev_value = (value1, value2)
else:
rev_value = value
if map_so is not None:
if not lojac:
map_so.y = axis_manip.reverse_array_cp(map_so.y)
map_so.var_y = axis_manip.reverse_array_cp(map_so.var_y)
else:
map_so.y = axis_manip.reverse_array_cp(counts[0])
map_so.var_y = axis_manip.reverse_array_cp(counts[1])
else:
pass
hlr_utils.result_insert(result, res_descr, rev_value, map_so, "x",
axis)
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 apply_sas_correct(obj):
"""
This function applies the following corrections to SAS TOF data:
- Multiply counts by the following formula:
(sin(polar) * cos(polar)) / (1 + tan^2(polar))
@param obj: The data to apply the corrections to
@type obj: C{SOM.SOM} or C{SOM.SO}
@return: The data after corrections have been applied
@rtype: C{SOM.SOM} or C{SOM.SO}
@raise TypeError: The object being rebinned is not a C{SOM} or a C{SO}
"""
# import the helper functions
import hlr_utils
# set up for working through data
o_descr = hlr_utils.get_descr(obj)
if o_descr == "number" or o_descr == "list":
raise TypeError("Do not know how to handle given type: %s" % \
o_descr)
else:
pass
if o_descr == "SOM":
inst = obj.attr_list.instrument
else:
inst = None
(result, res_descr) = hlr_utils.empty_result(obj)
result = hlr_utils.copy_som_attr(result, res_descr, obj, o_descr)
# iterate through the values
import array_manip
import math
len_obj = hlr_utils.get_length(obj)
for i in xrange(len_obj):
val = hlr_utils.get_value(obj, i, o_descr, "y")
err2 = hlr_utils.get_err2(obj, i, o_descr, "y")
map_so = hlr_utils.get_map_so(obj, None, i)
polar = hlr_utils.get_parameter("polar", map_so, inst)
sin_pol = math.sin(polar[0])
cos_pol = math.cos(polar[0])
tan_pol = math.tan(polar[0])
scale = (sin_pol * cos_pol) / (1.0 + (tan_pol * tan_pol))
value = array_manip.mult_ncerr(val, err2, scale, 0.0)
hlr_utils.result_insert(result, res_descr, value, map_so, "y")
return result
def create_E_vs_Q_igs(som, *args, **kwargs):
"""
This function starts with the initial IGS wavelength axis and turns this
into a 2D spectra with E and Q axes.
@param som: The input object with initial IGS wavelength axis
@type som: C{SOM.SOM}
@param args: A mandatory list of axes for rebinning. There is a particular
order to them. They should be present in the following order:
Without errors
1. Energy transfer
2. Momentum transfer
With errors
1. Energy transfer
2. Energy transfer error^2
3. Momentum transfer
4. Momentum transfer error ^2
@type args: C{nessi_list.NessiList}s
@param kwargs: A list of keyword arguments that the function accepts:
@keyword withXVar: Flag for whether the function should be expecting the
associated axes to have errors. The default value will
be I{False}.
@type withXVar: C{boolean}
@keyword data_type: Name of the data type which can be either I{histogram},
I{density} or I{coordinate}. The default value will be
I{histogram}
@type data_type: C{string}
@keyword Q_filter: Flag to turn on or off Q filtering. The default behavior
is I{True}.
@type Q_filter: C{boolean}
@keyword so_id: The identifier represents a number, string, tuple or other
object that describes the resulting C{SO}
@type so_id: C{int}, C{string}, C{tuple}, C{pixel ID}
@keyword y_label: The y axis label
@type y_label: C{string}
@keyword y_units: The y axis units
@type y_units: C{string}
@keyword x_labels: This is a list of names that sets the individual x axis
labels
@type x_labels: C{list} of C{string}s
@keyword x_units: This is a list of names that sets the individual x axis
units
@type x_units: C{list} of C{string}s
@keyword split: This flag causes the counts and the fractional area to
be written out into separate files.
@type split: C{boolean}
@keyword configure: This is the object containing the driver configuration.
@type configure: C{Configure}
@return: Object containing a 2D C{SO} with E and Q axes
@rtype: C{SOM.SOM}
@raise RuntimeError: Anything other than a C{SOM} is passed to the function
@raise RuntimeError: An instrument is not contained in the C{SOM}
"""
import nessi_list
# Setup some variables
dim = 2
N_y = []
N_tot = 1
N_args = len(args)
# Get T0 slope in order to calculate dT = dT_i + dT_0
try:
t_0_slope = som.attr_list["Time_zero_slope"][0]
t_0_slope_err2 = som.attr_list["Time_zero_slope"][1]
except KeyError:
t_0_slope = float(0.0)
t_0_slope_err2 = float(0.0)
# Check withXVar keyword argument and also check number of given args.
# Set xvar to the appropriate value
try:
value = kwargs["withXVar"]
if value.lower() == "true":
if N_args != 4:
raise RuntimeError("Since you have requested x errors, 4 x "\
+"axes must be provided.")
else:
xvar = True
elif value.lower() == "false":
if N_args != 2:
raise RuntimeError("Since you did not requested x errors, 2 "\
+"x axes must be provided.")
else:
xvar = False
else:
raise RuntimeError("Do not understand given parameter %s" % \
value)
except KeyError:
if N_args != 2:
raise RuntimeError("Since you did not requested x errors, 2 "\
+"x axes must be provided.")
else:
xvar = False
# Check dataType keyword argument. An offset will be set to 1 for the
# histogram type and 0 for either density or coordinate
try:
data_type = kwargs["data_type"]
if data_type.lower() == "histogram":
offset = 1
elif data_type.lower() == "density" or \
data_type.lower() == "coordinate":
offset = 0
else:
raise RuntimeError("Do not understand data type given: %s" % \
data_type)
# Default is offset for histogram
except KeyError:
offset = 1
try:
Q_filter = kwargs["Q_filter"]
except KeyError:
Q_filter = True
# Check for split keyword
try:
split = kwargs["split"]
except KeyError:
split = False
# Check for configure keyword
try:
configure = kwargs["configure"]
except KeyError:
configure = None
so_dim = SOM.SO(dim)
for i in range(dim):
# Set the x-axis arguments from the *args list into the new SO
if not xvar:
# Axis positions are 1 (Q) and 0 (E)
position = dim - i - 1
so_dim.axis[i].val = args[position]
else:
# Axis positions are 2 (Q), 3 (eQ), 0 (E), 1 (eE)
position = dim - 2 * i
so_dim.axis[i].val = args[position]
so_dim.axis[i].var = args[position + 1]
# Set individual value axis sizes (not x-axis size)
N_y.append(len(args[position]) - offset)
# Calculate total 2D array size
N_tot = N_tot * N_y[-1]
# Create y and var_y lists from total 2D size
so_dim.y = nessi_list.NessiList(N_tot)
so_dim.var_y = nessi_list.NessiList(N_tot)
# Create area sum and errors for the area sum lists from total 2D size
area_sum = nessi_list.NessiList(N_tot)
area_sum_err2 = nessi_list.NessiList(N_tot)
# Create area sum and errors for the area sum lists from total 2D size
bin_count = nessi_list.NessiList(N_tot)
bin_count_err2 = nessi_list.NessiList(N_tot)
inst = som.attr_list.instrument
lambda_final = som.attr_list["Wavelength_final"]
inst_name = inst.get_name()
import bisect
import math
import dr_lib
import utils
arr_len = 0
#: Vector of zeros for function calculations
zero_vec = None
for j in xrange(hlr_utils.get_length(som)):
# Get counts
counts = hlr_utils.get_value(som, j, "SOM", "y")
counts_err2 = hlr_utils.get_err2(som, j, "SOM", "y")
arr_len = len(counts)
zero_vec = nessi_list.NessiList(arr_len)
# Get mapping SO
map_so = hlr_utils.get_map_so(som, None, j)
# Get lambda_i
l_i = hlr_utils.get_value(som, j, "SOM", "x")
l_i_err2 = hlr_utils.get_err2(som, j, "SOM", "x")
# Get lambda_f from instrument information
l_f_tuple = hlr_utils.get_special(lambda_final, map_so)
l_f = l_f_tuple[0]
l_f_err2 = l_f_tuple[1]
# Get source to sample distance
(L_s, L_s_err2) = hlr_utils.get_parameter("primary", map_so, inst)
# Get sample to detector distance
L_d_tuple = hlr_utils.get_parameter("secondary", map_so, inst)
L_d = L_d_tuple[0]
# Get polar angle from instrument information
(angle, angle_err2) = hlr_utils.get_parameter("polar", map_so, inst)
# Get the detector pixel height
dh_tuple = hlr_utils.get_parameter("dh", map_so, inst)
dh = dh_tuple[0]
# Need dh in units of Angstrom
dh *= 1e10
# Calculate T_i
(T_i, T_i_err2) = axis_manip.wavelength_to_tof(l_i, l_i_err2, L_s,
L_s_err2)
# Scale counts by lambda_f / lambda_i
(l_i_bc, l_i_bc_err2) = utils.calc_bin_centers(l_i, l_i_err2)
(ratio, ratio_err2) = array_manip.div_ncerr(l_f, l_f_err2, l_i_bc,
l_i_bc_err2)
(counts, counts_err2) = array_manip.mult_ncerr(counts, counts_err2,
ratio, ratio_err2)
# Calculate E_i
(E_i, E_i_err2) = axis_manip.wavelength_to_energy(l_i, l_i_err2)
# Calculate E_f
(E_f, E_f_err2) = axis_manip.wavelength_to_energy(l_f, l_f_err2)
# Calculate E_t
(E_t, E_t_err2) = array_manip.sub_ncerr(E_i, E_i_err2, E_f, E_f_err2)
if inst_name == "BSS":
# Convert E_t from meV to ueV
(E_t, E_t_err2) = array_manip.mult_ncerr(E_t, E_t_err2, 1000.0,
0.0)
(counts,
counts_err2) = array_manip.mult_ncerr(counts, counts_err2,
1.0 / 1000.0, 0.0)
# Convert lambda_i to k_i
(k_i, k_i_err2) = axis_manip.wavelength_to_scalar_k(l_i, l_i_err2)
# Convert lambda_f to k_f
(k_f, k_f_err2) = axis_manip.wavelength_to_scalar_k(l_f, l_f_err2)
# Convert k_i and k_f to Q
(Q, Q_err2) = axis_manip.init_scatt_wavevector_to_scalar_Q(
k_i, k_i_err2, k_f, k_f_err2, angle, angle_err2)
# Calculate dT = dT_0 + dT_i
dT_i = utils.calc_bin_widths(T_i, T_i_err2)
(l_i_bw, l_i_bw_err2) = utils.calc_bin_widths(l_i, l_i_err2)
dT_0 = array_manip.mult_ncerr(l_i_bw, l_i_bw_err2, t_0_slope,
t_0_slope_err2)
dT_tuple = array_manip.add_ncerr(dT_i[0], dT_i[1], dT_0[0], dT_0[1])
dT = dT_tuple[0]
# Calculate Jacobian
if inst_name == "BSS":
(x_1, x_2, x_3, x_4) = dr_lib.calc_BSS_coeffs(
map_so, inst, (E_i, E_i_err2), (Q, Q_err2), (k_i, k_i_err2),
(T_i, T_i_err2), dh, angle, E_f, k_f, l_f, L_s, L_d, t_0_slope,
zero_vec)
else:
raise RuntimeError("Do not know how to calculate x_i "\
+"coefficients for instrument %s" % inst_name)
(A, A_err2) = dr_lib.calc_EQ_Jacobian(x_1, x_2, x_3, x_4, dT, dh,
zero_vec)
# Apply Jacobian: C/dlam * dlam / A(EQ) = C/EQ
(jac_ratio,
jac_ratio_err2) = array_manip.div_ncerr(l_i_bw, l_i_bw_err2, A,
A_err2)
(counts, counts_err2) = array_manip.mult_ncerr(counts, counts_err2,
jac_ratio,
jac_ratio_err2)
# Reverse counts, E_t, k_i and Q
E_t = axis_manip.reverse_array_cp(E_t)
E_t_err2 = axis_manip.reverse_array_cp(E_t_err2)
Q = axis_manip.reverse_array_cp(Q)
Q_err2 = axis_manip.reverse_array_cp(Q_err2)
counts = axis_manip.reverse_array_cp(counts)
counts_err2 = axis_manip.reverse_array_cp(counts_err2)
k_i = axis_manip.reverse_array_cp(k_i)
x_1 = axis_manip.reverse_array_cp(x_1)
x_2 = axis_manip.reverse_array_cp(x_2)
x_3 = axis_manip.reverse_array_cp(x_3)
x_4 = axis_manip.reverse_array_cp(x_4)
dT = axis_manip.reverse_array_cp(dT)
# Filter for duplicate Q values
if Q_filter:
k_i_cutoff = k_f * math.cos(angle)
k_i_cutbin = bisect.bisect(k_i, k_i_cutoff)
counts.__delslice__(0, k_i_cutbin)
counts_err2.__delslice__(0, k_i_cutbin)
Q.__delslice__(0, k_i_cutbin)
Q_err2.__delslice__(0, k_i_cutbin)
E_t.__delslice__(0, k_i_cutbin)
E_t_err2.__delslice__(0, k_i_cutbin)
x_1.__delslice__(0, k_i_cutbin)
x_2.__delslice__(0, k_i_cutbin)
x_3.__delslice__(0, k_i_cutbin)
x_4.__delslice__(0, k_i_cutbin)
dT.__delslice__(0, k_i_cutbin)
zero_vec.__delslice__(0, k_i_cutbin)
try:
if inst_name == "BSS":
((Q_1, E_t_1), (Q_2, E_t_2), (Q_3, E_t_3),
(Q_4, E_t_4)) = dr_lib.calc_BSS_EQ_verticies(
(E_t, E_t_err2), (Q, Q_err2), x_1, x_2, x_3, x_4, dT, dh,
zero_vec)
else:
raise RuntimeError("Do not know how to calculate (Q_i, "\
+"E_t_i) verticies for instrument %s" \
% inst_name)
except IndexError:
# All the data got Q filtered, move on
continue
try:
(y_2d, y_2d_err2, area_new,
bin_count_new) = axis_manip.rebin_2D_quad_to_rectlin(
Q_1, E_t_1, Q_2, E_t_2, Q_3, E_t_3, Q_4, E_t_4, counts,
counts_err2, so_dim.axis[0].val, so_dim.axis[1].val)
except IndexError, e:
# Get the offending index from the error message
index = int(str(e).split()[1].split('index')[-1].strip('[]'))
print "Id:", map_so.id
print "Index:", index
print "Verticies: %f, %f, %f, %f, %f, %f, %f, %f" % (
Q_1[index], E_t_1[index], Q_2[index], E_t_2[index], Q_3[index],
E_t_3[index], Q_4[index], E_t_4[index])
raise IndexError(str(e))
# Add in together with previous results
(so_dim.y,
so_dim.var_y) = array_manip.add_ncerr(so_dim.y, so_dim.var_y, y_2d,
y_2d_err2)
(area_sum,
area_sum_err2) = array_manip.add_ncerr(area_sum, area_sum_err2,
area_new, area_sum_err2)
if configure.dump_pix_contrib or configure.scale_sqe:
if inst_name == "BSS":
dOmega = dr_lib.calc_BSS_solid_angle(map_so, inst)
(bin_count_new, bin_count_err2) = array_manip.mult_ncerr(
bin_count_new, bin_count_err2, dOmega, 0.0)
(bin_count, bin_count_err2) = array_manip.add_ncerr(
bin_count, bin_count_err2, bin_count_new, bin_count_err2)
else:
del bin_count_new
def init_scatt_wavevector_to_scalar_Q(initk, scattk, **kwargs):
"""
This function takes an initial wavevector and a scattered wavevector as a
C{tuple} and a C{SOM}, a C{tuple} and a C{SO} or two C{tuple}s and
calculates the quantity scalar Q units of I{1/Angstroms}. The C{SOM}
principle axis must be in units of I{1/Angstroms}. The C{SO}s and
C{tuple}(s) is(are) assumed to be in units of I{1/Angstroms}. The polar
angle must be provided if one of the initial arguments is not a C{SOM}. If
a C{SOM} is passed, by providing the polar angle at the function call time,
the polar angle carried in the C{SOM} instrument will be overridden.
@param initk: Object holding the initial wavevector
@type initk: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@param scattk: Object holding the scattered wavevector
@type scattk: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword polar: The polar angle and its associated error^2
@type polar: C{tuple} or C{list} of C{tuple}s
@keyword units: The expected units for this function. The default for this
function is I{1/Angstroms}.
@type units: C{string}
@return: Object converted to scalar Q
@rtype: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@raise TypeError: The C{SOM}-C{SOM} operation is attempted
@raise TypeError: The C{SOM}-C{SO} operation is attempted
@raise TypeError: The C{SO}-C{SOM} operation is attempted
@raise TypeError: The C{SO}-C{SO} operation is attempted
@raise RuntimeError: The C{SOM} x-axis units are not I{1/Angstroms}
@raise RuntimeError: A C{SOM} is not passed and no polar angle is provided
@raise RuntimeError: No C{SOM.Instrument} is provided in a C{SOM}
"""
# import the helper functions
import hlr_utils
# set up for working through data
(result, res_descr) = hlr_utils.empty_result(initk, scattk)
(i_descr, s_descr) = hlr_utils.get_descr(initk, scattk)
# error checking for types
if i_descr == "SOM" and s_descr == "SOM":
raise TypeError("SOM-SOM operation not supported")
elif i_descr == "SOM" and s_descr == "SO":
raise TypeError("SOM-SO operation not supported")
elif i_descr == "SO" and s_descr == "SOM":
raise TypeError("SO-SOM operation not supported")
elif i_descr == "SO" and s_descr == "SO":
raise TypeError("SO-SO operation not supported")
else:
pass
# Setup keyword arguments
try:
polar = kwargs["polar"]
except KeyError:
polar = None
try:
units = kwargs["units"]
except KeyError:
units = "1/Angstroms"
result = hlr_utils.copy_som_attr(result, res_descr, initk, i_descr, scattk,
s_descr)
if res_descr == "SOM":
index = hlr_utils.one_d_units(result, units)
result = hlr_utils.force_units(result, units, index)
result.setAxisLabel(index, "scalar wavevector transfer")
result.setYUnits("Counts/A-1")
result.setYLabel("Intensity")
else:
pass
if polar is None:
if i_descr == "SOM":
try:
initk.attr_list.instrument.get_primary()
inst = initk.attr_list.instrument
except RuntimeError:
raise RuntimeError("A detector was not provided!")
elif s_descr == "SOM":
try:
scattk.attr_list.instrument.get_primary()
inst = scattk.attr_list.instrument
except RuntimeError:
raise RuntimeError("A detector was not provided!")
else:
raise RuntimeError("If no SOM is provided, then polar "\
+"information must be given.")
else:
p_descr = hlr_utils.get_descr(polar)
# iterate through the values
import axis_manip
for i in xrange(hlr_utils.get_length(initk, scattk)):
val1 = hlr_utils.get_value(initk, i, i_descr, "x")
err2_1 = hlr_utils.get_err2(initk, i, i_descr, "x")
val2 = hlr_utils.get_value(scattk, i, s_descr, "x")
err2_2 = hlr_utils.get_err2(scattk, i, s_descr, "x")
map_so = hlr_utils.get_map_so(initk, scattk, i)
if polar is None:
(angle,
angle_err2) = hlr_utils.get_parameter("polar", map_so, inst)
else:
angle = hlr_utils.get_value(polar, i, p_descr)
angle_err2 = hlr_utils.get_err2(polar, i, p_descr)
value = axis_manip.init_scatt_wavevector_to_scalar_Q(
val1, err2_1, val2, err2_2, angle, angle_err2)
hlr_utils.result_insert(result, res_descr, value, map_so, "x")
return result
def init_scatt_wavevector_to_scalar_Q(initk, scattk, **kwargs):
"""
This function takes an initial wavevector and a scattered wavevector as a
C{tuple} and a C{SOM}, a C{tuple} and a C{SO} or two C{tuple}s and
calculates the quantity scalar Q units of I{1/Angstroms}. The C{SOM}
principle axis must be in units of I{1/Angstroms}. The C{SO}s and
C{tuple}(s) is(are) assumed to be in units of I{1/Angstroms}. The polar
angle must be provided if one of the initial arguments is not a C{SOM}. If
a C{SOM} is passed, by providing the polar angle at the function call time,
the polar angle carried in the C{SOM} instrument will be overridden.
@param initk: Object holding the initial wavevector
@type initk: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@param scattk: Object holding the scattered wavevector
@type scattk: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword polar: The polar angle and its associated error^2
@type polar: C{tuple} or C{list} of C{tuple}s
@keyword units: The expected units for this function. The default for this
function is I{1/Angstroms}.
@type units: C{string}
@return: Object converted to scalar Q
@rtype: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@raise TypeError: The C{SOM}-C{SOM} operation is attempted
@raise TypeError: The C{SOM}-C{SO} operation is attempted
@raise TypeError: The C{SO}-C{SOM} operation is attempted
@raise TypeError: The C{SO}-C{SO} operation is attempted
@raise RuntimeError: The C{SOM} x-axis units are not I{1/Angstroms}
@raise RuntimeError: A C{SOM} is not passed and no polar angle is provided
@raise RuntimeError: No C{SOM.Instrument} is provided in a C{SOM}
"""
# import the helper functions
import hlr_utils
# set up for working through data
(result, res_descr) = hlr_utils.empty_result(initk, scattk)
(i_descr, s_descr) = hlr_utils.get_descr(initk, scattk)
# error checking for types
if i_descr == "SOM" and s_descr == "SOM":
raise TypeError("SOM-SOM operation not supported")
elif i_descr == "SOM" and s_descr == "SO":
raise TypeError("SOM-SO operation not supported")
elif i_descr == "SO" and s_descr == "SOM":
raise TypeError("SO-SOM operation not supported")
elif i_descr == "SO" and s_descr == "SO":
raise TypeError("SO-SO operation not supported")
else:
pass
# Setup keyword arguments
try:
polar = kwargs["polar"]
except KeyError:
polar = None
try:
units = kwargs["units"]
except KeyError:
units = "1/Angstroms"
result = hlr_utils.copy_som_attr(result, res_descr, initk, i_descr,
scattk, s_descr)
if res_descr == "SOM":
index = hlr_utils.one_d_units(result, units)
result = hlr_utils.force_units(result, units, index)
result.setAxisLabel(index, "scalar wavevector transfer")
result.setYUnits("Counts/A-1")
result.setYLabel("Intensity")
else:
pass
if polar is None:
if i_descr == "SOM":
try:
initk.attr_list.instrument.get_primary()
inst = initk.attr_list.instrument
except RuntimeError:
raise RuntimeError("A detector was not provided!")
elif s_descr == "SOM":
try:
scattk.attr_list.instrument.get_primary()
inst = scattk.attr_list.instrument
except RuntimeError:
raise RuntimeError("A detector was not provided!")
else:
raise RuntimeError("If no SOM is provided, then polar "\
+"information must be given.")
else:
p_descr = hlr_utils.get_descr(polar)
# iterate through the values
import axis_manip
for i in xrange(hlr_utils.get_length(initk, scattk)):
val1 = hlr_utils.get_value(initk, i, i_descr, "x")
err2_1 = hlr_utils.get_err2(initk, i, i_descr, "x")
val2 = hlr_utils.get_value(scattk, i, s_descr, "x")
err2_2 = hlr_utils.get_err2(scattk, i, s_descr, "x")
map_so = hlr_utils.get_map_so(initk, scattk, i)
if polar is None:
(angle, angle_err2) = hlr_utils.get_parameter("polar", map_so,
inst)
else:
angle = hlr_utils.get_value(polar, i, p_descr)
angle_err2 = hlr_utils.get_err2(polar, i, p_descr)
value = axis_manip.init_scatt_wavevector_to_scalar_Q(val1, err2_1,
val2, err2_2,
angle, angle_err2)
hlr_utils.result_insert(result, res_descr, value, map_so, "x")
return result
def calc_substrate_trans(obj, subtrans_coeff, substrate_diam, **kwargs):
"""
This function calculates substrate transmission via the following formula:
T = exp[-(A + B * wavelength) * d] where A is a constant with units of
cm^-1, B is a constant with units of cm^-2 and d is the substrate
diameter in units of cm.
@param obj: The data object that contains the TOF axes to calculate the
transmission from.
@type obj: C{SOM.SOM} or C{SOM.SO}
@param subtrans_coeff: The two coefficients for substrate transmission
calculation.
@type subtrans_coeff: C{tuple} of two C{float}s
@param substrate_diam: The diameter of the substrate.
@type substrate_diam: C{float}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword pathlength: The pathlength and its associated error^2
@type pathlength: C{tuple} or C{list} of C{tuple}s
@keyword units: The expected units for this function. The default for this
function is I{microsecond}.
@type units: C{string}
@return: The calculate transmission for the given substrate parameters
@rtype: C{SOM.SOM} or C{SOM.SO}
@raise TypeError: The object used for calculation is not a C{SOM} or a
C{SO}
@raise RuntimeError: The C{SOM} x-axis units are not I{microsecond}
@raise RuntimeError: A C{SOM} does not contain an instrument and no
pathlength was provided
@raise RuntimeError: No C{SOM} is provided and no pathlength given
"""
# import the helper functions
import hlr_utils
# set up for working through data
(result, res_descr) = hlr_utils.empty_result(obj)
o_descr = hlr_utils.get_descr(obj)
if o_descr == "number" or o_descr == "list":
raise TypeError("Do not know how to handle given type: %s" % o_descr)
else:
pass
# Setup keyword arguments
try:
pathlength = kwargs["pathlength"]
except KeyError:
pathlength = None
try:
units = kwargs["units"]
except KeyError:
units = "microsecond"
# 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
if pathlength is not None:
p_descr = hlr_utils.get_descr(pathlength)
else:
if o_descr == "SOM":
try:
obj.attr_list.instrument.get_primary()
inst = obj.attr_list.instrument
except RuntimeError:
raise RuntimeError("A detector was not provided")
else:
raise RuntimeError("If no SOM is provided, then pathlength "\
+"information must be provided")
result = hlr_utils.copy_som_attr(result, res_descr, obj, o_descr)
if res_descr == "SOM":
result.setYLabel("Transmission")
# iterate through the values
import array_manip
import axis_manip
import nessi_list
import utils
import math
len_obj = hlr_utils.get_length(obj)
for i in xrange(len_obj):
val = hlr_utils.get_value(obj, i, o_descr, "x", axis)
err2 = hlr_utils.get_err2(obj, i, o_descr, "x", axis)
map_so = hlr_utils.get_map_so(obj, None, i)
if pathlength is None:
(pl, pl_err2) = hlr_utils.get_parameter("total", map_so, inst)
else:
pl = hlr_utils.get_value(pathlength, i, p_descr)
pl_err2 = hlr_utils.get_err2(pathlength, i, p_descr)
value = axis_manip.tof_to_wavelength(val, err2, pl, pl_err2)
value1 = utils.calc_bin_centers(value[0])
del value
# Convert Angstroms to centimeters
value2 = array_manip.mult_ncerr(value1[0], value1[1],
subtrans_coeff[1]*1.0e-8, 0.0)
del value1
# Calculate the exponential
value3 = array_manip.add_ncerr(value2[0], value2[1],
subtrans_coeff[0], 0.0)
del value2
value4 = array_manip.mult_ncerr(value3[0], value3[1],
-1.0*substrate_diam, 0.0)
del value3
# Calculate transmission
trans = nessi_list.NessiList()
len_trans = len(value4[0])
for j in xrange(len_trans):
trans.append(math.exp(value4[0][j]))
trans_err2 = nessi_list.NessiList(len(trans))
hlr_utils.result_insert(result, res_descr, (trans, trans_err2), map_so)
return result
def tof_to_scalar_Q(obj, **kwargs):
"""
This function converts a primary axis of a C{SOM} or C{SO} from
time-of-flight to scalarQ. The time-of-flight axis for a C{SOM} must be in
units of I{microseconds}. The primary axis of a C{SO} is assumed to be in
units of I{microseconds}. A C{tuple} of C{(time-of-flight,
time-of-flight_err2)} (assumed to be in units of I{microseconds}) can be
converted to C{(scalar_Q, scalar_Q_err2)}.
@param obj: Object to be converted
@type obj: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword polar: The polar angle and its associated error^2
@type polar: C{tuple} or C{list} of C{tuple}s
@keyword pathlength: The pathlength and its associated error^2
@type pathlength: C{tuple} or C{list} of C{tuple}s
@keyword angle_offset: A constant offset for the polar angle and its
associated error^2. The units of the offset should
be in radians.
@type angle_offset: C{tuple}
@keyword lojac: A flag that allows one to turn off the calculation of the
linear-order Jacobian. The default action is True for
histogram data.
@type lojac: C{boolean}
@keyword units: The expected units for this function. The default for this
function is I{microseconds}.
@type units: C{string}
@return: Object with a primary axis in time-of-flight converted to scalar Q
@rtype: C{SOM.SOM}, C{SOM.SO} or C{tuple}
@raise TypeError: The incoming object is not a type the function recognizes
@raise RuntimeError: A C{SOM} is not passed and no polar angle is provided
@raise RuntimeError: The C{SOM} x-axis units are not I{microseconds}
"""
# import the helper functions
import hlr_utils
# set up for working through data
(result, res_descr) = hlr_utils.empty_result(obj)
o_descr = hlr_utils.get_descr(obj)
if o_descr == "list":
raise TypeError("Do not know how to handle given type: %s" % \
o_descr)
else:
pass
# Setup keyword arguments
try:
polar = kwargs["polar"]
except KeyError:
polar = None
try:
pathlength = kwargs["pathlength"]
except KeyError:
pathlength = None
try:
units = kwargs["units"]
except KeyError:
units = "microseconds"
try:
lojac = kwargs["lojac"]
except KeyError:
lojac = hlr_utils.check_lojac(obj)
try:
angle_offset = kwargs["angle_offset"]
except KeyError:
angle_offset = None
# 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)
if res_descr == "SOM":
result = hlr_utils.force_units(result, "1/Angstroms", axis)
result.setAxisLabel(axis, "scalar wavevector transfer")
result.setYUnits("Counts/A-1")
result.setYLabel("Intensity")
else:
pass
if pathlength is None or polar is None:
if o_descr == "SOM":
try:
obj.attr_list.instrument.get_primary()
inst = obj.attr_list.instrument
except RuntimeError:
raise RuntimeError("A detector was not provided")
else:
if pathlength is None and polar is None:
raise RuntimeError("If no SOM is provided, then pathlength "\
+"and polar angle information must be "\
+"provided")
elif pathlength is None:
raise RuntimeError("If no SOM is provided, then pathlength "\
+"information must be provided")
elif polar is None:
raise RuntimeError("If no SOM is provided, then polar angle "\
+"information must be provided")
else:
raise RuntimeError("If you get here, see Steve Miller for "\
+"your mug.")
else:
pass
if pathlength is not None:
p_descr = hlr_utils.get_descr(pathlength)
else:
pass
if polar is not None:
a_descr = hlr_utils.get_descr(polar)
else:
pass
# iterate through the values
import axis_manip
if lojac:
import utils
for i in xrange(hlr_utils.get_length(obj)):
val = hlr_utils.get_value(obj, i, o_descr, "x", axis)
err2 = hlr_utils.get_err2(obj, i, o_descr, "x", axis)
map_so = hlr_utils.get_map_so(obj, None, i)
if pathlength is None:
(pl, pl_err2) = hlr_utils.get_parameter("total", map_so, inst)
else:
pl = hlr_utils.get_value(pathlength, i, p_descr)
pl_err2 = hlr_utils.get_err2(pathlength, i, p_descr)
if polar is None:
(angle,
angle_err2) = hlr_utils.get_parameter("polar", map_so, inst)
else:
angle = hlr_utils.get_value(polar, i, a_descr)
angle_err2 = hlr_utils.get_err2(polar, i, a_descr)
if angle_offset is not None:
angle += angle_offset[0]
angle_err2 += angle_offset[1]
value = axis_manip.tof_to_scalar_Q(val, err2, pl, pl_err2, angle,
angle_err2)
if lojac:
y_val = hlr_utils.get_value(obj, i, o_descr, "y")
y_err2 = hlr_utils.get_err2(obj, i, o_descr, "y")
counts = utils.linear_order_jacobian(val, value[0], y_val, y_err2)
else:
pass
if o_descr != "number":
value1 = axis_manip.reverse_array_cp(value[0])
value2 = axis_manip.reverse_array_cp(value[1])
rev_value = (value1, value2)
else:
rev_value = value
if map_so is not None:
if not lojac:
map_so.y = axis_manip.reverse_array_cp(map_so.y)
map_so.var_y = axis_manip.reverse_array_cp(map_so.var_y)
else:
map_so.y = axis_manip.reverse_array_cp(counts[0])
map_so.var_y = axis_manip.reverse_array_cp(counts[1])
else:
pass
hlr_utils.result_insert(result, res_descr, rev_value, map_so, "x",
axis)
return result
def apply_sas_correct(obj):
"""
This function applies the following corrections to SAS TOF data:
- Multiply counts by the following formula:
(sin(polar) * cos(polar)) / (1 + tan^2(polar))
@param obj: The data to apply the corrections to
@type obj: C{SOM.SOM} or C{SOM.SO}
@return: The data after corrections have been applied
@rtype: C{SOM.SOM} or C{SOM.SO}
@raise TypeError: The object being rebinned is not a C{SOM} or a C{SO}
"""
# import the helper functions
import hlr_utils
# set up for working through data
o_descr = hlr_utils.get_descr(obj)
if o_descr == "number" or o_descr == "list":
raise TypeError("Do not know how to handle given type: %s" % \
o_descr)
else:
pass
if o_descr == "SOM":
inst = obj.attr_list.instrument
else:
inst = None
(result, res_descr) = hlr_utils.empty_result(obj)
result = hlr_utils.copy_som_attr(result, res_descr, obj, o_descr)
# iterate through the values
import array_manip
import math
len_obj = hlr_utils.get_length(obj)
for i in xrange(len_obj):
val = hlr_utils.get_value(obj, i, o_descr, "y")
err2 = hlr_utils.get_err2(obj, i, o_descr, "y")
map_so = hlr_utils.get_map_so(obj, None, i)
polar = hlr_utils.get_parameter("polar", map_so, inst)
sin_pol = math.sin(polar[0])
cos_pol = math.cos(polar[0])
tan_pol = math.tan(polar[0])
scale = (sin_pol * cos_pol) / (1.0 + (tan_pol * tan_pol))
value = array_manip.mult_ncerr(val, err2, scale, 0.0)
hlr_utils.result_insert(result, res_descr, value, map_so, "y")
return result