diff --git a/tools/plotting/fastnnlo_pdfunc.py b/tools/plotting/fastnnlo_pdfunc.py index 363465d94b73fe0f4846ed6dd192ff02f1ff8180..526ed73debaaa041b3a98693f40e418bcc235cef 100755 --- a/tools/plotting/fastnnlo_pdfunc.py +++ b/tools/plotting/fastnnlo_pdfunc.py @@ -179,8 +179,10 @@ def plotting(x_axis, xmin, xmax, xs_all, rel_pdf_unc, abs_pdf_unc, dxsr_cn, nost # else: ax1.set_xscale('linear') # if logy: ax1.set_yscale('log', nonposy='clip') # else: ax1.set_yscale('linear') - ax1.set_xscale('log', nonposx='clip') # Will become nonpositive= in matplotlib 3.3.x - ax1.set_yscale('log', nonposy='clip') # Will become nonpositive= in matplotlib 3.3.x + # ax1.set_xscale('log', nonposx='clip') # Will become nonpositive= in matplotlib 3.3.x + # ax1.set_yscale('log', nonposy='clip') # Will become nonpositive= in matplotlib 3.3.x + ax1.set_xscale('log', nonpositive='clip') + ax1.set_yscale('log', nonpositive='clip') # Set label on x axis on coupled axis from lower plot # ax1.set_xlabel(r'%s' %xlabel, horizontalalignment='right', x=1.0, verticalalignment='top', y=1.0) ax1.set_ylabel(r'%s' % ylabel, horizontalalignment='right', x=1.0, @@ -620,8 +622,7 @@ def main(): xs_list_tmp.append(fnlo.GetCrossSection()) ### Get PDF uncertainties ### - rel_pdf_unc_item = np.array(fnlo.GetPDFUncertaintyVec( - fastnlo.kLHAPDF6)) # Now calculated for order n + rel_pdf_unc_item = np.array(fnlo.GetPDFUncertaintyVec(fastnlo.kLHAPDF6)) # Now calculated for order n rel_unc_list_tmp.append(rel_pdf_unc_item) if verb: print('[fastnnlo_pdfunc]: \n') diff --git a/tools/plotting/fastnnlo_scaleunc.py b/tools/plotting/fastnnlo_scaleunc.py index 3f43ab3d5450c638d908f841b9f80a5741332939..6b9f209e4d17f58f6fce6829360f25d5a0206984 100755 --- a/tools/plotting/fastnnlo_scaleunc.py +++ b/tools/plotting/fastnnlo_scaleunc.py @@ -154,10 +154,10 @@ def plotting(x_axis, xmin, xmax, xs_all, rel_scale_unc, abs_scale_unc, dxsr_cn, # axfmt = LogFormatter(labelOnlyBase=False, minor_thresholds=(2, 0.4)) # ax1.get_xaxis().set_minor_formatter(axfmt) # ax1.get_xaxis().set_minor_formatter(NullFormatter()) - # ax1.set_xscale('log', nonposx='clip') - # ax1.set_yscale('log', nonposy='clip') - ax1.set_xscale('log', nonpositive='clip') # Will become nonpositive= in matplotlib 3.3.x - ax1.set_yscale('log', nonpositive='clip') # Will become nonpositive= in matplotlib 3.3.x + # ax1.set_xscale('log', nonposx='clip') # Will become nonpositive= in matplotlib 3.3.x + # ax1.set_yscale('log', nonposy='clip') # Will become nonpositive= in matplotlib 3.3.x + ax1.set_xscale('log', nonpositive='clip') + ax1.set_yscale('log', nonpositive='clip') # Set label on x axis on coupled axis from lower plot # ax1.set_xlabel(r'%s' %xlabel, horizontalalignment='right', x=1.0, verticalalignment='top', y=1.0) ax1.set_ylabel(r'%s' % ylabel, horizontalalignment='right', x=1.0, @@ -593,8 +593,7 @@ def main(): # Up to NLO, it is possible to use HOPPET with fixed-scale tables # fnlo.UseHoppetScaleVariations(True) # Calculate this already for all accessible orders in any case - rel_scale_unc_item = np.array( - fnlo.GetScaleUncertaintyVec(scale_var_type)) + rel_scale_unc_item = np.array(fnlo.GetScaleUncertaintyVec(scale_var_type)) rel_unc_list.append(rel_scale_unc_item) if verb: print('[fastnnlo_scaleunc]: \n')