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' : [2.480152e+03, 1.467584e+03, 2.327553e+02, 4.951104e+01, 8.776186e-01],
     '_Analysis.yoda.gz' : [1.183660e+04, -4.127316e+01, 2.582630e+02, -1.237648e+01, 1.344768e+00],
    '__Analysis.yoda.gz' : [-8.685924e+03, 1.440717e+03, 1.870412e+02, 4.481354e+01, 1.104926e+00],
}

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' : [
                              [7.245280e+02, 1.533866e+02, 2.784285e+01, 8.347521e+00, 2.988919e-01],
                              [7.245280e+02, 1.533866e+02, 2.784285e+01, 8.347521e+00, 2.988919e-01],
                           ],
     '_Analysis.yoda.gz' : [
                              [1.419657e+04, 2.340246e+02, 6.164501e+02, 1.355959e+01, 6.815927e-01],
                              [1.419657e+04, 2.340246e+02, 6.164501e+02, 1.355959e+01, 6.815927e-01],
                           ],
    '__Analysis.yoda.gz' : [
                              [1.116089e+04, 1.831625e+02, 4.345165e+01, 5.091461e+00, 1.548746e-01],
                              [1.116089e+04, 1.831625e+02, 4.345165e+01, 5.091461e+00, 1.548746e-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' : [6.573422e-01, 8.932343e-01, 7.117899e-01, 9.002007e-01, 5.850791e-01],
     '_Analysis.yoda.gz' : [3.137185e+00, -2.512061e-02, 7.897951e-01, -2.250269e-01, 8.965120e-01],
    '__Analysis.yoda.gz' : [-2.302127e+00, 8.768819e-01, 5.719914e-01, 8.147916e-01, 7.366173e-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' : [
                              [1.920297e-01, 9.335764e-02, 8.514633e-02, 1.517731e-01, 1.992613e-01],
                              [1.920297e-01, 9.335764e-02, 8.514633e-02, 1.517731e-01, 1.992613e-01],
                           ],
     '_Analysis.yoda.gz' : [
                              [3.762674e+00, 1.424374e-01, 1.885169e+00, 2.465380e-01, 4.543951e-01],
                              [3.762674e+00, 1.424374e-01, 1.885169e+00, 2.465380e-01, 4.543951e-01],
                           ],
    '__Analysis.yoda.gz' : [
                              [2.958094e+00, 1.114805e-01, 1.328797e-01, 9.257202e-02, 1.032497e-01],
                              [2.958094e+00, 1.114805e-01, 1.328797e-01, 9.257202e-02, 1.032497e-01],
                           ],
}

ratio0_variation_vals = {
}

ratio_band_edges = {
}