def geo_corr(ds, enabled):
global DEFAULT_SAMPLE_TO_DETECTOR_DISTANCE
global DEGREE_RAD_COEFFICIENT
sdd = DEFAULT_SAMPLE_TO_DETECTOR_DISTANCE
try:
sdd = ds.sample_to_detector_distance
except:
pass
sdds = sdd ** 2
stth = ds.stth
if not hasattr(stth, '__len__') :
stth = [stth]
is_fixed_stth = True
if math.fabs(stth[0] - stth[-1]) > 1e-3:
is_fixed_stth = False
currentStth = stth[0] / DEGREE_RAD_COEFFICIENT
sinStth = math.sin(currentStth)
cosStth = math.cos(currentStth)
y_len = ds.axes[-2].size - 1
x_len = ds.axes[-1].size - 1
if enabled:
d_shape = [y_len, x_len]
pixel_2theta = array.instance([y_len, x_len + 1], dtype = float)
if is_fixed_stth :
res = dataset.instance(ds.shape, dtype = float)
y_bounds = ds.axes[-2].__iArray__
y_centres = AxisRecord.createCentres(y_bounds)
x_bounds = ds.axes[-1].__iArray__
GeometryCorrection.calculateTwoThetaPixel(sdd, sdds, x_bounds, cosStth, sinStth, \
y_centres, pixel_2theta.__iArray__)
axis_2theta = array.instance([x_len + 1], dtype = float)
GeometryCorrection.calculateTwoThetaAxis(sdd, sdds, x_bounds, cosStth, \
sinStth, axis_2theta.__iArray__)
relocateLeftIndexArray = array.instance(d_shape, dtype = int)
relocateRightIndexArray = array.instance(d_shape, dtype = int)
relocateLeftRateArray = array.instance(d_shape, dtype = float)
relocateRightRateArray = array.instance(d_shape, dtype = float)
relocateCounterArray = array.instance(d_shape, dtype = float)
for i in xrange(ds.shape[0]):
GeometryCorrection.rebinWithTwoTheta(ds[i].__iArray__, ds[i].var.__iArray__, \
res[i].__iArray__, res[i].var.__iArray__, pixel_2theta.__iArray__, \
axis_2theta.__iArray__, relocateLeftIndexArray.__iArray__, \
relocateRightIndexArray.__iArray__, relocateLeftRateArray.__iArray__, \
relocateRightRateArray.__iArray__, relocateCounterArray.__iArray__, \
i == 0)
res.axes[0] = ds.axes[0]
res.axes[1] = ds.axes[1]
res.axes[2] = axis_2theta
res.axes[2].title = 'two theta'
res.copy_metadata_shallow(ds)
res.append_log('Processed with: geometry curve correction')
res.append_log('Processed with: calculating two theta on LDS=%.1f mm' % sdd)
else:
res = dataset.instance(ds.shape, dtype = float)
y_bounds = ds.axes[-2].__iArray__
y_centres = AxisRecord.createCentres(y_bounds)
x_bounds = ds.axes[-1].__iArray__
two_theta_axes = array.instance([ds.shape[0], x_len + 1], dtype = float)
for i in xrange(ds.shape[0]):
currentStth = stth[i] / DEGREE_RAD_COEFFICIENT
sinStth = math.sin(currentStth)
cosStth = math.cos(currentStth)
pixel_2theta = array.instance([y_len, x_len + 1], dtype = float)
GeometryCorrection.calculateTwoThetaPixel(sdd, sdds, x_bounds, cosStth, sinStth, \
y_centres, pixel_2theta.__iArray__)
axis_2theta = array.instance([x_len + 1], dtype = float)
GeometryCorrection.calculateTwoThetaAxis(sdd, sdds, x_bounds, cosStth, \
sinStth, axis_2theta.__iArray__)
two_theta_axes[i] = axis_2theta
relocateLeftIndexArray = array.instance(d_shape, dtype = int)
relocateRightIndexArray = array.instance(d_shape, dtype = int)
relocateLeftRateArray = array.instance(d_shape, dtype = float)
relocateRightRateArray = array.instance(d_shape, dtype = float)
relocateCounterArray = array.instance(d_shape, dtype = float)
GeometryCorrection.rebinWithTwoTheta(ds[i].__iArray__, ds[i].var.__iArray__, \
res[i].__iArray__, res[i].var.__iArray__, pixel_2theta.__iArray__, \
axis_2theta.__iArray__, relocateLeftIndexArray.__iArray__, \
relocateRightIndexArray.__iArray__, relocateLeftRateArray.__iArray__, \
relocateRightRateArray.__iArray__, relocateCounterArray.__iArray__, \
True)
res.axes[0] = ds.axes[0]
res.axes[1] = ds.axes[1]
res.axes[2] = two_theta_axes[0]
res.axes[2].title = 'two theta'
res.copy_metadata_shallow(ds)
res.two_theta_axes = two_theta_axes
res.append_log('Processed with: geometry curve correction')
res.append_log('Processed with: calculating two theta on LDS=%.1f mm' % sdd)
return res
else:
x_bounds = ds.axes[2].__iArray__
two_theta_axes = array.instance([ds.shape[0], x_len + 1], dtype = float)
for i in xrange(ds.shape[0]):
currentStth = stth[i] / DEGREE_RAD_COEFFICIENT
sinStth = math.sin(currentStth)
cosStth = math.cos(currentStth)
axis_2theta = array.instance([x_len + 1], dtype = float)
GeometryCorrection.calculateTwoThetaAxis(sdd, sdds, x_bounds, cosStth, \
sinStth, axis_2theta.__iArray__)
two_theta_axes[i] = axis_2theta
ds.axes[2] = two_theta_axes[0]
ds.axes[2].title = 'two theta'
ds.two_theta_axes = two_theta_axes
ds.append_log('Processed with: calculating two theta on LDS=%.1f mm' % sdd)
return ds
def v_intg(ds, masks):
if len(masks) > 0 :
is_fixed_stth = True
if len(ds) > 1 and math.fabs(ds.stth[0] - ds.stth[-1]) > 1e-3:
is_fixed_stth = False
if is_fixed_stth:
x_axis = ds.axes[-1]
y_axis = ds.axes[-2]
res = dataset.instance([ds.shape[0], ds.shape[2]], float('NaN'), dtype=float)
for mask in masks:
y_iMin = int((mask.minY - y_axis[0]) / (y_axis[-1] - y_axis[0]) \
* (y_axis.size - 1))
if y_iMin < 0 :
y_iMin = 0
if y_iMin >= y_axis.size:
continue
y_iMax = int((mask.maxY - y_axis[0]) / (y_axis[-1] - y_axis[0]) \
* (y_axis.size - 1)) + 1
if y_iMax < 0:
continue
x_iMin = int((mask.minX - x_axis[0]) / (x_axis[-1] - x_axis[0]) \
* (x_axis.size - 1))
if x_iMin < 0:
x_iMin = 0;
if x_iMin >= x_axis.size:
continue
x_iMax = int((mask.maxX - x_axis[0]) / (x_axis[-1] - x_axis[0]) \
* (x_axis.size - 1)) + 1
if x_iMax < 0:
continue
res[:, x_iMin : x_iMax] = ds[:, y_iMin : y_iMax, x_iMin : x_iMax].intg(1)
res.axes[0] = ds.axes[0]
res.axes[1] = ds.axes[2]
mask = masks[0]
res.copy_metadata_shallow(ds)
res.append_log('Processed with: apply mask y in [' + str(mask.minY) + ',' \
+ str(mask.maxY) + '], x in [' + str(mask.minX) + ',' + str(mask.maxX) + ']')
return res
else :
y_axis = ds.axes[-2]
res = dataset.instance([ds.shape[0], ds.shape[2]], float('NaN'), dtype=float)
for i in xrange(len(ds)):
x_axis = ds.two_theta_axes[i]
for mask in masks:
y_iMin = int((mask.minY - y_axis[0]) / (y_axis[-1] - y_axis[0]) \
* (y_axis.size - 1))
if y_iMin < 0 :
y_iMin = 0
if y_iMin >= y_axis.size:
continue
y_iMax = int((mask.maxY - y_axis[0]) / (y_axis[-1] - y_axis[0]) \
* (y_axis.size - 1)) + 1
if y_iMax < 0:
continue
x_iMin = int((mask.minX - x_axis[0]) / (x_axis[-1] - x_axis[0]) \
* (x_axis.size - 1))
if x_iMin < 0:
x_iMin = 0;
if x_iMin >= x_axis.size:
continue
x_iMax = int((mask.maxX - x_axis[0]) / (x_axis[-1] - x_axis[0]) \
* (x_axis.size - 1)) + 1
if x_iMax < 0:
continue
res[i, x_iMin : x_iMax] = ds[i, y_iMin : y_iMax, x_iMin : x_iMax].intg(0)
res.axes[0] = ds.axes[0]
res.axes[1] = ds.axes[2]
mask = masks[0]
if hasattr(ds, 'two_theta_axes'):
res.two_theta_axes = ds.two_theta_axes
res.copy_metadata_shallow(ds)
res.append_log('Processed with: apply mask y in [' + str(mask.minY) + ',' \
+ str(mask.maxY) + '], x in [' + str(mask.minX) + ',' + str(mask.maxX) + ']')
return res
else:
return ds.intg(1)