import numpy as np
from numpy import nan, inf

add_legend_handle = [
  'Data',
  'Analysis.yoda.gz',
  '_Analysis.yoda.gz',
  '__Analysis.yoda.gz'
]

xpoints = {
                  'Data' : [2.400000e-04, 1.000000e-03, 3.300000e-03, 7.500000e-03, 5.500000e-02],
      'Analysis.yoda.gz' : [2.400000e-04, 1.000000e-03, 3.300000e-03, 7.500000e-03, 5.500000e-02],
     '_Analysis.yoda.gz' : [2.400000e-04, 1.000000e-03, 3.300000e-03, 7.500000e-03, 5.500000e-02],
    '__Analysis.yoda.gz' : [2.400000e-04, 1.000000e-03, 3.300000e-03, 7.500000e-03, 5.500000e-02],
}

xedges = {
                  'Data' : [8.000000e-05, 4.000000e-04, 1.600000e-03, 5.000000e-03, 1.000000e-02,
                            1.000000e-01],
      'Analysis.yoda.gz' : [8.000000e-05, 4.000000e-04, 1.600000e-03, 5.000000e-03, 1.000000e-02,
                            1.000000e-01],
     '_Analysis.yoda.gz' : [8.000000e-05, 4.000000e-04, 1.600000e-03, 5.000000e-03, 1.000000e-02,
                            1.000000e-01],
    '__Analysis.yoda.gz' : [8.000000e-05, 4.000000e-04, 1.600000e-03, 5.000000e-03, 1.000000e-02,
                            1.000000e-01],
}

ref_xerrs = [
  [abs(xpoints['Data'][i]   - xedges['Data'][i]) for i in range(len(xpoints['Data']))],
  [abs(xedges['Data'][i+1] - xpoints['Data'][i]) for i in range(len(xpoints['Data']))]
]

yvals = {
                  'Data' : [3.773000e+03, 1.643000e+03, 3.270000e+02, 5.500000e+01, 1.500000e+00],
      'Analysis.yoda.gz' : [3.598547e+03, 1.311667e+03, 2.413431e+02, 3.740026e+01, 7.717863e-01],
     '_Analysis.yoda.gz' : [-8.450294e+02, 9.011878e+02, 2.446802e+02, 4.374406e+01, 1.878500e+00],
    '__Analysis.yoda.gz' : [1.346407e+03, 9.827205e+02, 2.839038e+02, 3.830356e+01, 9.552111e-01],
}

xerrs = {
                  'Data' : [
                              [1.600000e-04, 6.000000e-04, 1.700000e-03, 2.500000e-03, 4.500000e-02],
                              [1.600000e-04, 6.000000e-04, 1.700000e-03, 2.500000e-03, 4.500000e-02],
                           ],
      'Analysis.yoda.gz' : [
                              [1.600000e-04, 6.000000e-04, 1.700000e-03, 2.500000e-03, 4.500000e-02],
                              [1.600000e-04, 6.000000e-04, 1.700000e-03, 2.500000e-03, 4.500000e-02],
                           ],
     '_Analysis.yoda.gz' : [
                              [1.600000e-04, 6.000000e-04, 1.700000e-03, 2.500000e-03, 4.500000e-02],
                              [1.600000e-04, 6.000000e-04, 1.700000e-03, 2.500000e-03, 4.500000e-02],
                           ],
    '__Analysis.yoda.gz' : [
                              [1.600000e-04, 6.000000e-04, 1.700000e-03, 2.500000e-03, 4.500000e-02],
                              [1.600000e-04, 6.000000e-04, 1.700000e-03, 2.500000e-03, 4.500000e-02],
                           ],
}

yerrs = {
                  'Data' : [
                              [9.580632e+02, 1.867619e+02, 5.341348e+01, 2.195450e+01, 7.071068e-01],
                              [8.082605e+02, 2.280022e+02, 5.108816e+01, 1.421267e+01, 5.385165e-01],
                           ],
      'Analysis.yoda.gz' : [
                              [3.728563e+02, 8.503664e+01, 1.771049e+01, 5.817921e+00, 1.146236e-01],
                              [3.728563e+02, 8.503664e+01, 1.771049e+01, 5.817921e+00, 1.146236e-01],
                           ],
     '_Analysis.yoda.gz' : [
                              [2.901941e+03, 2.055132e+02, 4.026933e+01, 5.864106e+00, 3.836117e-01],
                              [2.901941e+03, 2.055132e+02, 4.026933e+01, 5.864106e+00, 3.836117e-01],
                           ],
    '__Analysis.yoda.gz' : [
                              [1.197232e+03, 2.115410e+02, 3.249008e+01, 6.422312e+00, 3.959586e-01],
                              [1.197232e+03, 2.115410e+02, 3.249008e+01, 6.422312e+00, 3.959586e-01],
                           ],
}

variation_yvals = {
}



# lists for ratio plot
ratio0_yvals = {
                  'Data' : [1.000000e+00, 1.000000e+00, 1.000000e+00, 1.000000e+00, 1.000000e+00],
      'Analysis.yoda.gz' : [9.537628e-01, 7.983366e-01, 7.380523e-01, 6.800047e-01, 5.145242e-01],
     '_Analysis.yoda.gz' : [-2.239675e-01, 5.485014e-01, 7.482575e-01, 7.953465e-01, 1.252333e+00],
    '__Analysis.yoda.gz' : [3.568532e-01, 5.981257e-01, 8.682073e-01, 6.964284e-01, 6.368074e-01],
}

ratio0_yerrs = {
                  'Data' : [
                              [2.539261e-01, 1.136713e-01, 1.633440e-01, 3.991727e-01, 4.714045e-01],
                              [2.142222e-01, 1.387719e-01, 1.562329e-01, 2.584122e-01, 3.590110e-01],
                           ],
      'Analysis.yoda.gz' : [
                              [9.882224e-02, 5.175693e-02, 5.416052e-02, 1.057804e-01, 7.641573e-02],
                              [9.882224e-02, 5.175693e-02, 5.416052e-02, 1.057804e-01, 7.641573e-02],
                           ],
     '_Analysis.yoda.gz' : [
                              [7.691336e-01, 1.250841e-01, 1.231478e-01, 1.066201e-01, 2.557411e-01],
                              [7.691336e-01, 1.250841e-01, 1.231478e-01, 1.066201e-01, 2.557411e-01],
                           ],
    '__Analysis.yoda.gz' : [
                              [3.173157e-01, 1.287529e-01, 9.935804e-02, 1.167693e-01, 2.639724e-01],
                              [3.173157e-01, 1.287529e-01, 9.935804e-02, 1.167693e-01, 2.639724e-01],
                           ],
}

ratio0_variation_vals = {
}

ratio_band_edges = {
}