def produce(self, spectrum):
bin_boundaries = spectrum.binning()
n_bins = len(bin_boundaries) - 1
row = newtables.BaseRow()
row.append(newtables.CellString(spectrum.latex_title))
i_left = self.binning.index(bin_boundaries[0])
i_right = self.binning.index(bin_boundaries[-1])
for i in xrange(i_left):
row.append(newtables.CellString('-'))
if self.normalize: incl_xs = self.get_incl_xs(spectrum)
for i_scan, scan in enumerate(spectrum.scans):
left = bin_boundaries[i_scan]
right = bin_boundaries[i_scan + 1]
up = scan.unc.right_error
down = scan.unc.left_error
cell = CellSymmRelativeUncs(-abs(down), up)
cell.span = self.binning.index(right) - self.binning.index(left)
row.append(cell)
for i in xrange(i_right, n_bins):
row.append(newtables.CellString('-'))
return row
def produce_from_hist(self, H):
row = newtables.BaseRow()
row.append(newtables.CellString(H.title))
for i in xrange(H.n_bins):
cell = CellSymmRelativeUncs(-abs(H.errs_down[i]), H.errs_up[i])
row.append(cell)
return row
def produce_binning_row(self, title=''):
self.int_binning_where_possible()
row = newtables.BaseRow()
row.append(newtables.CellString(title))
for left, right in zip(self.binning[:-1], self.binning[1:]):
if right == 10000. or (self.last_bin_is_overflow
and right == self.binning[-1]):
row.append(newtables.CellString('$>${0}'.format(left)))
else:
row.append(newtables.CellString('{0}-{1}'.format(left, right)))
return row
def produce(self, spectrum):
bin_boundaries = spectrum.binning()
n_bins = len(bin_boundaries) - 1
row = newtables.BaseRow()
row.append(newtables.CellString(spectrum.latex_title))
if self.do_xs:
CellAsymmUncCrossSection.scientific_notation = True
CellAsymmUncCrossSection.n_decimals = 3
i_left = self.binning.index(bin_boundaries[0])
i_right = self.binning.index(bin_boundaries[-1])
for i in xrange(i_left):
row.append(newtables.CellString('-'))
if self.normalize: incl_xs = self.get_incl_xs(spectrum)
for i_scan, scan in enumerate(spectrum.scans):
left = bin_boundaries[i_scan]
right = bin_boundaries[i_scan + 1]
center = scan.unc.x_min
up = scan.unc.right_error
down = scan.unc.left_error
if self.do_xs:
xs = spectrum.smxs[i_scan]
bin_width = right - left
if self.normalize:
center *= xs * bin_width / incl_xs
up *= xs * bin_width / incl_xs
down *= xs * bin_width / incl_xs
else:
center *= xs
up *= xs
down *= xs
cell = CellAsymmUncCrossSection(center, up, -abs(down))
cell.span = self.binning.index(right) - self.binning.index(left)
row.append(cell)
for i in xrange(i_right, n_bins):
row.append(newtables.CellString('-'))
return row
def produce_row_given_labels(self, labels):
row = newtables.BaseRow()
for label in labels:
row.append(newtables.CellString(label))
return row