diff options
Diffstat (limited to 'notebooks/plot_optim_OTreg.ipynb')
| -rw-r--r-- | notebooks/plot_optim_OTreg.ipynb | 799 |
1 files changed, 355 insertions, 444 deletions
diff --git a/notebooks/plot_optim_OTreg.ipynb b/notebooks/plot_optim_OTreg.ipynb index e3784df..34f42af 100644 --- a/notebooks/plot_optim_OTreg.ipynb +++ b/notebooks/plot_optim_OTreg.ipynb @@ -72,8 +72,6 @@ }, "outputs": [], "source": [ - "#%% parameters\n", - "\n", "n = 100 # nb bins\n", "\n", "# bin positions\n", @@ -106,18 +104,18 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "<Figure size 360x360 with 3 Axes>" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], "source": [ - "#%% EMD\n", - "\n", "G0 = ot.emd(a, b, M)\n", "\n", "pl.figure(3, figsize=(5, 5))\n", @@ -144,246 +142,245 @@ "name": "stdout", "output_type": "stream", "text": [ - "It. |Loss |Delta loss\n", - "--------------------------------\n", - " 0|1.760578e-01|0.000000e+00\n", - " 1|1.669467e-01|-5.457501e-02\n", - " 2|1.665639e-01|-2.298130e-03\n", - " 3|1.664378e-01|-7.572776e-04\n", - " 4|1.664077e-01|-1.811855e-04\n", - " 5|1.663912e-01|-9.936787e-05\n", - " 6|1.663852e-01|-3.555826e-05\n", - " 7|1.663814e-01|-2.305693e-05\n", - " 8|1.663785e-01|-1.760450e-05\n", - " 9|1.663767e-01|-1.078011e-05\n", - " 10|1.663751e-01|-9.525192e-06\n", - " 11|1.663737e-01|-8.396466e-06\n", - " 12|1.663727e-01|-6.086938e-06\n", - " 13|1.663720e-01|-4.042609e-06\n", - " 14|1.663713e-01|-4.160914e-06\n", - " 15|1.663707e-01|-3.823502e-06\n", - " 16|1.663702e-01|-3.022440e-06\n", - " 17|1.663697e-01|-3.181249e-06\n", - " 18|1.663692e-01|-2.698532e-06\n", - " 19|1.663687e-01|-3.258253e-06\n", - "It. |Loss |Delta loss\n", - "--------------------------------\n", - " 20|1.663682e-01|-2.741118e-06\n", - " 21|1.663678e-01|-2.624135e-06\n", - " 22|1.663673e-01|-2.645179e-06\n", - " 23|1.663670e-01|-1.957237e-06\n", - " 24|1.663666e-01|-2.261541e-06\n", - " 25|1.663663e-01|-1.851305e-06\n", - " 26|1.663660e-01|-1.942296e-06\n", - " 27|1.663657e-01|-2.092896e-06\n", - " 28|1.663653e-01|-1.924361e-06\n", - " 29|1.663651e-01|-1.625455e-06\n", - " 30|1.663648e-01|-1.641123e-06\n", - " 31|1.663645e-01|-1.566666e-06\n", - " 32|1.663643e-01|-1.338514e-06\n", - " 33|1.663641e-01|-1.222711e-06\n", - " 34|1.663639e-01|-1.221805e-06\n", - " 35|1.663637e-01|-1.440781e-06\n", - " 36|1.663634e-01|-1.520091e-06\n", - " 37|1.663632e-01|-1.288193e-06\n", - " 38|1.663630e-01|-1.123055e-06\n", - " 39|1.663628e-01|-1.024487e-06\n", - "It. |Loss |Delta loss\n", - "--------------------------------\n", - " 40|1.663627e-01|-1.079606e-06\n", - " 41|1.663625e-01|-1.172093e-06\n", - " 42|1.663623e-01|-1.047880e-06\n", - " 43|1.663621e-01|-1.010577e-06\n", - " 44|1.663619e-01|-1.064438e-06\n", - " 45|1.663618e-01|-9.882375e-07\n", - " 46|1.663616e-01|-8.532647e-07\n", - " 47|1.663615e-01|-9.930189e-07\n", - " 48|1.663613e-01|-8.728955e-07\n", - " 49|1.663612e-01|-9.524214e-07\n", - " 50|1.663610e-01|-9.088418e-07\n", - " 51|1.663609e-01|-7.639430e-07\n", - " 52|1.663608e-01|-6.662611e-07\n", - " 53|1.663607e-01|-7.133700e-07\n", - " 54|1.663605e-01|-7.648141e-07\n", - " 55|1.663604e-01|-6.557516e-07\n", - " 56|1.663603e-01|-7.304213e-07\n", - " 57|1.663602e-01|-6.353809e-07\n", - " 58|1.663601e-01|-7.968279e-07\n", - " 59|1.663600e-01|-6.367159e-07\n", - "It. |Loss |Delta loss\n", - "--------------------------------\n", - " 60|1.663599e-01|-5.610790e-07\n", - " 61|1.663598e-01|-5.787466e-07\n", - " 62|1.663596e-01|-6.937777e-07\n", - " 63|1.663596e-01|-5.599432e-07\n", - " 64|1.663595e-01|-5.813048e-07\n", - " 65|1.663594e-01|-5.724600e-07\n", - " 66|1.663593e-01|-6.081892e-07\n", - " 67|1.663592e-01|-5.948732e-07\n", - " 68|1.663591e-01|-4.941833e-07\n", - " 69|1.663590e-01|-5.213739e-07\n", - " 70|1.663589e-01|-5.127355e-07\n", - " 71|1.663588e-01|-4.349251e-07\n", - " 72|1.663588e-01|-5.007084e-07\n", - " 73|1.663587e-01|-4.880265e-07\n", - " 74|1.663586e-01|-4.931950e-07\n", - " 75|1.663585e-01|-4.981309e-07\n", - " 76|1.663584e-01|-3.952959e-07\n", - " 77|1.663584e-01|-4.544857e-07\n", - " 78|1.663583e-01|-4.237579e-07\n", - " 79|1.663582e-01|-4.382386e-07\n", - "It. |Loss |Delta loss\n", - "--------------------------------\n", - " 80|1.663582e-01|-3.646051e-07\n", - " 81|1.663581e-01|-4.197994e-07\n", - " 82|1.663580e-01|-4.072764e-07\n", - " 83|1.663580e-01|-3.994645e-07\n", - " 84|1.663579e-01|-4.842721e-07\n", - " 85|1.663578e-01|-3.276486e-07\n", - " 86|1.663578e-01|-3.737346e-07\n", - " 87|1.663577e-01|-4.282043e-07\n", - " 88|1.663576e-01|-4.020937e-07\n", - " 89|1.663576e-01|-3.431951e-07\n", - " 90|1.663575e-01|-3.052335e-07\n", - " 91|1.663575e-01|-3.500538e-07\n", - " 92|1.663574e-01|-3.063176e-07\n", - " 93|1.663573e-01|-3.576367e-07\n", - " 94|1.663573e-01|-3.224681e-07\n", - " 95|1.663572e-01|-3.673221e-07\n", - " 96|1.663572e-01|-3.635561e-07\n", - " 97|1.663571e-01|-3.527236e-07\n", - " 98|1.663571e-01|-2.788548e-07\n", - " 99|1.663570e-01|-2.727141e-07\n", - "It. |Loss |Delta loss\n", - "--------------------------------\n", - " 100|1.663570e-01|-3.127278e-07\n", - " 101|1.663569e-01|-2.637504e-07\n", - " 102|1.663569e-01|-2.922750e-07\n", - " 103|1.663568e-01|-3.076454e-07\n", - " 104|1.663568e-01|-2.911509e-07\n", - " 105|1.663567e-01|-2.403398e-07\n", - " 106|1.663567e-01|-2.439790e-07\n", - " 107|1.663567e-01|-2.634542e-07\n", - " 108|1.663566e-01|-2.452203e-07\n", - " 109|1.663566e-01|-2.852991e-07\n", - " 110|1.663565e-01|-2.165490e-07\n", - " 111|1.663565e-01|-2.450250e-07\n", - " 112|1.663564e-01|-2.685294e-07\n", - " 113|1.663564e-01|-2.821800e-07\n", - " 114|1.663564e-01|-2.237390e-07\n", - " 115|1.663563e-01|-1.992842e-07\n", - " 116|1.663563e-01|-2.166739e-07\n", - " 117|1.663563e-01|-2.086064e-07\n", - " 118|1.663562e-01|-2.435945e-07\n", - " 119|1.663562e-01|-2.292497e-07\n", - "It. |Loss |Delta loss\n", - "--------------------------------\n", - " 120|1.663561e-01|-2.366209e-07\n", - " 121|1.663561e-01|-2.138746e-07\n", - " 122|1.663561e-01|-2.009637e-07\n", - " 123|1.663560e-01|-2.386258e-07\n", - " 124|1.663560e-01|-1.927442e-07\n", - " 125|1.663560e-01|-2.081681e-07\n", - " 126|1.663559e-01|-1.759123e-07\n", - " 127|1.663559e-01|-1.890771e-07\n", - " 128|1.663559e-01|-1.971315e-07\n", - " 129|1.663558e-01|-2.101983e-07\n", - " 130|1.663558e-01|-2.035645e-07\n", - " 131|1.663558e-01|-1.984492e-07\n", - " 132|1.663557e-01|-1.849064e-07\n", - " 133|1.663557e-01|-1.795703e-07\n", - " 134|1.663557e-01|-1.624087e-07\n", - " 135|1.663557e-01|-1.689557e-07\n", - " 136|1.663556e-01|-1.644308e-07\n", - " 137|1.663556e-01|-1.618007e-07\n", - " 138|1.663556e-01|-1.483013e-07\n", - " 139|1.663555e-01|-1.708771e-07\n", - "It. |Loss |Delta loss\n", - "--------------------------------\n", - " 140|1.663555e-01|-2.013847e-07\n", - " 141|1.663555e-01|-1.721217e-07\n", - " 142|1.663554e-01|-2.027911e-07\n", - " 143|1.663554e-01|-1.764565e-07\n", - " 144|1.663554e-01|-1.677151e-07\n", - " 145|1.663554e-01|-1.351982e-07\n", - " 146|1.663553e-01|-1.423360e-07\n", - " 147|1.663553e-01|-1.541112e-07\n", - " 148|1.663553e-01|-1.491601e-07\n", - " 149|1.663553e-01|-1.466407e-07\n", - " 150|1.663552e-01|-1.801524e-07\n", - " 151|1.663552e-01|-1.714107e-07\n", - " 152|1.663552e-01|-1.491257e-07\n", - " 153|1.663552e-01|-1.513799e-07\n", - " 154|1.663551e-01|-1.354539e-07\n", - " 155|1.663551e-01|-1.233818e-07\n", - " 156|1.663551e-01|-1.576219e-07\n", - " 157|1.663551e-01|-1.452791e-07\n", - " 158|1.663550e-01|-1.262867e-07\n", - " 159|1.663550e-01|-1.316379e-07\n", - "It. |Loss |Delta loss\n", - "--------------------------------\n", - " 160|1.663550e-01|-1.295447e-07\n", - " 161|1.663550e-01|-1.283286e-07\n", - " 162|1.663550e-01|-1.569222e-07\n", - " 163|1.663549e-01|-1.172942e-07\n", - " 164|1.663549e-01|-1.399809e-07\n", - " 165|1.663549e-01|-1.229432e-07\n", - " 166|1.663549e-01|-1.326191e-07\n", - " 167|1.663548e-01|-1.209694e-07\n", - " 168|1.663548e-01|-1.372136e-07\n", - " 169|1.663548e-01|-1.338395e-07\n", - " 170|1.663548e-01|-1.416497e-07\n", - " 171|1.663548e-01|-1.298576e-07\n", - " 172|1.663547e-01|-1.190590e-07\n", - " 173|1.663547e-01|-1.167083e-07\n", - " 174|1.663547e-01|-1.069425e-07\n", - " 175|1.663547e-01|-1.217780e-07\n", - " 176|1.663547e-01|-1.140754e-07\n", - " 177|1.663546e-01|-1.160707e-07\n", - " 178|1.663546e-01|-1.101798e-07\n", - " 179|1.663546e-01|-1.114904e-07\n", - "It. |Loss |Delta loss\n", - "--------------------------------\n", - " 180|1.663546e-01|-1.064022e-07\n", - " 181|1.663546e-01|-9.258231e-08\n", - " 182|1.663546e-01|-1.213120e-07\n", - " 183|1.663545e-01|-1.164296e-07\n", - " 184|1.663545e-01|-1.188762e-07\n", - " 185|1.663545e-01|-9.394153e-08\n", - " 186|1.663545e-01|-1.028656e-07\n", - " 187|1.663545e-01|-1.115348e-07\n", - " 188|1.663544e-01|-9.768310e-08\n", - " 189|1.663544e-01|-1.021806e-07\n", - " 190|1.663544e-01|-1.086303e-07\n", - " 191|1.663544e-01|-9.879008e-08\n", - " 192|1.663544e-01|-1.050210e-07\n", - " 193|1.663544e-01|-1.002463e-07\n", - " 194|1.663543e-01|-1.062747e-07\n", - " 195|1.663543e-01|-9.348538e-08\n", - " 196|1.663543e-01|-7.992512e-08\n", - " 197|1.663543e-01|-9.558020e-08\n", - " 198|1.663543e-01|-9.993772e-08\n", - " 199|1.663543e-01|-8.588499e-08\n", - "It. |Loss |Delta loss\n", - "--------------------------------\n", - " 200|1.663543e-01|-8.737134e-08\n" + "It. |Loss |Relative loss|Absolute loss\n", + "------------------------------------------------\n", + " 0|1.760578e-01|0.000000e+00|0.000000e+00\n", + " 1|1.669467e-01|5.457501e-02|9.111116e-03\n", + " 2|1.665639e-01|2.298130e-03|3.827855e-04\n", + " 3|1.664378e-01|7.572776e-04|1.260396e-04\n", + " 4|1.664077e-01|1.811855e-04|3.015066e-05\n", + " 5|1.663912e-01|9.936787e-05|1.653393e-05\n", + " 6|1.663852e-01|3.555826e-05|5.916369e-06\n", + " 7|1.663814e-01|2.305693e-05|3.836245e-06\n", + " 8|1.663785e-01|1.760450e-05|2.929009e-06\n", + " 9|1.663767e-01|1.078011e-05|1.793559e-06\n", + " 10|1.663751e-01|9.525192e-06|1.584755e-06\n", + " 11|1.663737e-01|8.396466e-06|1.396951e-06\n", + " 12|1.663727e-01|6.086938e-06|1.012700e-06\n", + " 13|1.663720e-01|4.042609e-06|6.725769e-07\n", + " 14|1.663713e-01|4.160914e-06|6.922568e-07\n", + " 15|1.663707e-01|3.823502e-06|6.361187e-07\n", + " 16|1.663702e-01|3.022440e-06|5.028438e-07\n", + " 17|1.663697e-01|3.181249e-06|5.292634e-07\n", + " 18|1.663692e-01|2.698532e-06|4.489527e-07\n", + " 19|1.663687e-01|3.258253e-06|5.420712e-07\n", + "It. |Loss |Relative loss|Absolute loss\n", + "------------------------------------------------\n", + " 20|1.663682e-01|2.741118e-06|4.560349e-07\n", + " 21|1.663678e-01|2.624135e-06|4.365715e-07\n", + " 22|1.663673e-01|2.645179e-06|4.400714e-07\n", + " 23|1.663670e-01|1.957237e-06|3.256196e-07\n", + " 24|1.663666e-01|2.261541e-06|3.762450e-07\n", + " 25|1.663663e-01|1.851305e-06|3.079948e-07\n", + " 26|1.663660e-01|1.942296e-06|3.231320e-07\n", + " 27|1.663657e-01|2.092896e-06|3.481860e-07\n", + " 28|1.663653e-01|1.924361e-06|3.201470e-07\n", + " 29|1.663651e-01|1.625455e-06|2.704189e-07\n", + " 30|1.663648e-01|1.641123e-06|2.730250e-07\n", + " 31|1.663645e-01|1.566666e-06|2.606377e-07\n", + " 32|1.663643e-01|1.338514e-06|2.226810e-07\n", + " 33|1.663641e-01|1.222711e-06|2.034152e-07\n", + " 34|1.663639e-01|1.221805e-06|2.032642e-07\n", + " 35|1.663637e-01|1.440781e-06|2.396935e-07\n", + " 36|1.663634e-01|1.520091e-06|2.528875e-07\n", + " 37|1.663632e-01|1.288193e-06|2.143080e-07\n", + " 38|1.663630e-01|1.123055e-06|1.868347e-07\n", + " 39|1.663628e-01|1.024487e-06|1.704365e-07\n", + "It. |Loss |Relative loss|Absolute loss\n", + "------------------------------------------------\n", + " 40|1.663627e-01|1.079606e-06|1.796061e-07\n", + " 41|1.663625e-01|1.172093e-06|1.949922e-07\n", + " 42|1.663623e-01|1.047880e-06|1.743277e-07\n", + " 43|1.663621e-01|1.010577e-06|1.681217e-07\n", + " 44|1.663619e-01|1.064438e-06|1.770820e-07\n", + " 45|1.663618e-01|9.882375e-07|1.644049e-07\n", + " 46|1.663616e-01|8.532647e-07|1.419505e-07\n", + " 47|1.663615e-01|9.930189e-07|1.652001e-07\n", + " 48|1.663613e-01|8.728955e-07|1.452161e-07\n", + " 49|1.663612e-01|9.524214e-07|1.584459e-07\n", + " 50|1.663610e-01|9.088418e-07|1.511958e-07\n", + " 51|1.663609e-01|7.639430e-07|1.270902e-07\n", + " 52|1.663608e-01|6.662611e-07|1.108397e-07\n", + " 53|1.663607e-01|7.133700e-07|1.186767e-07\n", + " 54|1.663605e-01|7.648141e-07|1.272349e-07\n", + " 55|1.663604e-01|6.557516e-07|1.090911e-07\n", + " 56|1.663603e-01|7.304213e-07|1.215131e-07\n", + " 57|1.663602e-01|6.353809e-07|1.057021e-07\n", + " 58|1.663601e-01|7.968279e-07|1.325603e-07\n", + " 59|1.663600e-01|6.367159e-07|1.059240e-07\n", + "It. |Loss |Relative loss|Absolute loss\n", + "------------------------------------------------\n", + " 60|1.663599e-01|5.610790e-07|9.334102e-08\n", + " 61|1.663598e-01|5.787466e-07|9.628015e-08\n", + " 62|1.663596e-01|6.937777e-07|1.154166e-07\n", + " 63|1.663596e-01|5.599432e-07|9.315190e-08\n", + " 64|1.663595e-01|5.813048e-07|9.670555e-08\n", + " 65|1.663594e-01|5.724600e-07|9.523409e-08\n", + " 66|1.663593e-01|6.081892e-07|1.011779e-07\n", + " 67|1.663592e-01|5.948732e-07|9.896260e-08\n", + " 68|1.663591e-01|4.941833e-07|8.221188e-08\n", + " 69|1.663590e-01|5.213739e-07|8.673523e-08\n", + " 70|1.663589e-01|5.127355e-07|8.529811e-08\n", + " 71|1.663588e-01|4.349251e-07|7.235363e-08\n", + " 72|1.663588e-01|5.007084e-07|8.329722e-08\n", + " 73|1.663587e-01|4.880265e-07|8.118744e-08\n", + " 74|1.663586e-01|4.931950e-07|8.204723e-08\n", + " 75|1.663585e-01|4.981309e-07|8.286832e-08\n", + " 76|1.663584e-01|3.952959e-07|6.576082e-08\n", + " 77|1.663584e-01|4.544857e-07|7.560750e-08\n", + " 78|1.663583e-01|4.237579e-07|7.049564e-08\n", + " 79|1.663582e-01|4.382386e-07|7.290460e-08\n", + "It. |Loss |Relative loss|Absolute loss\n", + "------------------------------------------------\n", + " 80|1.663582e-01|3.646051e-07|6.065503e-08\n", + " 81|1.663581e-01|4.197994e-07|6.983702e-08\n", + " 82|1.663580e-01|4.072764e-07|6.775370e-08\n", + " 83|1.663580e-01|3.994645e-07|6.645410e-08\n", + " 84|1.663579e-01|4.842721e-07|8.056248e-08\n", + " 85|1.663578e-01|3.276486e-07|5.450691e-08\n", + " 86|1.663578e-01|3.737346e-07|6.217366e-08\n", + " 87|1.663577e-01|4.282043e-07|7.123508e-08\n", + " 88|1.663576e-01|4.020937e-07|6.689135e-08\n", + " 89|1.663576e-01|3.431951e-07|5.709310e-08\n", + " 90|1.663575e-01|3.052335e-07|5.077789e-08\n", + " 91|1.663575e-01|3.500538e-07|5.823407e-08\n", + " 92|1.663574e-01|3.063176e-07|5.095821e-08\n", + " 93|1.663573e-01|3.576367e-07|5.949549e-08\n", + " 94|1.663573e-01|3.224681e-07|5.364492e-08\n", + " 95|1.663572e-01|3.673221e-07|6.110670e-08\n", + " 96|1.663572e-01|3.635561e-07|6.048017e-08\n", + " 97|1.663571e-01|3.527236e-07|5.867807e-08\n", + " 98|1.663571e-01|2.788548e-07|4.638946e-08\n", + " 99|1.663570e-01|2.727141e-07|4.536791e-08\n", + "It. |Loss |Relative loss|Absolute loss\n", + "------------------------------------------------\n", + " 100|1.663570e-01|3.127278e-07|5.202445e-08\n", + " 101|1.663569e-01|2.637504e-07|4.387670e-08\n", + " 102|1.663569e-01|2.922750e-07|4.862195e-08\n", + " 103|1.663568e-01|3.076454e-07|5.117891e-08\n", + " 104|1.663568e-01|2.911509e-07|4.843492e-08\n", + " 105|1.663567e-01|2.403398e-07|3.998215e-08\n", + " 106|1.663567e-01|2.439790e-07|4.058755e-08\n", + " 107|1.663567e-01|2.634542e-07|4.382735e-08\n", + " 108|1.663566e-01|2.452203e-07|4.079401e-08\n", + " 109|1.663566e-01|2.852991e-07|4.746137e-08\n", + " 110|1.663565e-01|2.165490e-07|3.602434e-08\n", + " 111|1.663565e-01|2.450250e-07|4.076149e-08\n", + " 112|1.663564e-01|2.685294e-07|4.467159e-08\n", + " 113|1.663564e-01|2.821800e-07|4.694245e-08\n", + " 114|1.663564e-01|2.237390e-07|3.722040e-08\n", + " 115|1.663563e-01|1.992842e-07|3.315219e-08\n", + " 116|1.663563e-01|2.166739e-07|3.604506e-08\n", + " 117|1.663563e-01|2.086064e-07|3.470297e-08\n", + " 118|1.663562e-01|2.435945e-07|4.052346e-08\n", + " 119|1.663562e-01|2.292497e-07|3.813711e-08\n", + "It. |Loss |Relative loss|Absolute loss\n", + "------------------------------------------------\n", + " 120|1.663561e-01|2.366209e-07|3.936334e-08\n", + " 121|1.663561e-01|2.138746e-07|3.557935e-08\n", + " 122|1.663561e-01|2.009637e-07|3.343153e-08\n", + " 123|1.663560e-01|2.386258e-07|3.969683e-08\n", + " 124|1.663560e-01|1.927442e-07|3.206415e-08\n", + " 125|1.663560e-01|2.081681e-07|3.463000e-08\n", + " 126|1.663559e-01|1.759123e-07|2.926406e-08\n", + " 127|1.663559e-01|1.890771e-07|3.145409e-08\n", + " 128|1.663559e-01|1.971315e-07|3.279398e-08\n", + " 129|1.663558e-01|2.101983e-07|3.496771e-08\n", + " 130|1.663558e-01|2.035645e-07|3.386414e-08\n", + " 131|1.663558e-01|1.984492e-07|3.301317e-08\n", + " 132|1.663557e-01|1.849064e-07|3.076024e-08\n", + " 133|1.663557e-01|1.795703e-07|2.987255e-08\n", + " 134|1.663557e-01|1.624087e-07|2.701762e-08\n", + " 135|1.663557e-01|1.689557e-07|2.810673e-08\n", + " 136|1.663556e-01|1.644308e-07|2.735399e-08\n", + " 137|1.663556e-01|1.618007e-07|2.691644e-08\n", + " 138|1.663556e-01|1.483013e-07|2.467075e-08\n", + " 139|1.663555e-01|1.708771e-07|2.842636e-08\n", + "It. |Loss |Relative loss|Absolute loss\n", + "------------------------------------------------\n", + " 140|1.663555e-01|2.013847e-07|3.350146e-08\n", + " 141|1.663555e-01|1.721217e-07|2.863339e-08\n", + " 142|1.663554e-01|2.027911e-07|3.373540e-08\n", + " 143|1.663554e-01|1.764565e-07|2.935449e-08\n", + " 144|1.663554e-01|1.677151e-07|2.790030e-08\n", + " 145|1.663554e-01|1.351982e-07|2.249094e-08\n", + " 146|1.663553e-01|1.423360e-07|2.367836e-08\n", + " 147|1.663553e-01|1.541112e-07|2.563722e-08\n", + " 148|1.663553e-01|1.491601e-07|2.481358e-08\n", + " 149|1.663553e-01|1.466407e-07|2.439446e-08\n", + " 150|1.663552e-01|1.801524e-07|2.996929e-08\n", + " 151|1.663552e-01|1.714107e-07|2.851507e-08\n", + " 152|1.663552e-01|1.491257e-07|2.480784e-08\n", + " 153|1.663552e-01|1.513799e-07|2.518282e-08\n", + " 154|1.663551e-01|1.354539e-07|2.253345e-08\n", + " 155|1.663551e-01|1.233818e-07|2.052519e-08\n", + " 156|1.663551e-01|1.576219e-07|2.622121e-08\n", + " 157|1.663551e-01|1.452791e-07|2.416792e-08\n", + " 158|1.663550e-01|1.262867e-07|2.100843e-08\n", + " 159|1.663550e-01|1.316379e-07|2.189863e-08\n", + "It. |Loss |Relative loss|Absolute loss\n", + "------------------------------------------------\n", + " 160|1.663550e-01|1.295447e-07|2.155041e-08\n", + " 161|1.663550e-01|1.283286e-07|2.134810e-08\n", + " 162|1.663550e-01|1.569222e-07|2.610479e-08\n", + " 163|1.663549e-01|1.172942e-07|1.951247e-08\n", + " 164|1.663549e-01|1.399809e-07|2.328651e-08\n", + " 165|1.663549e-01|1.229432e-07|2.045221e-08\n", + " 166|1.663549e-01|1.326191e-07|2.206184e-08\n", + " 167|1.663548e-01|1.209694e-07|2.012384e-08\n", + " 168|1.663548e-01|1.372136e-07|2.282614e-08\n", + " 169|1.663548e-01|1.338395e-07|2.226484e-08\n", + " 170|1.663548e-01|1.416497e-07|2.356410e-08\n", + " 171|1.663548e-01|1.298576e-07|2.160242e-08\n", + " 172|1.663547e-01|1.190590e-07|1.980603e-08\n", + " 173|1.663547e-01|1.167083e-07|1.941497e-08\n", + " 174|1.663547e-01|1.069425e-07|1.779038e-08\n", + " 175|1.663547e-01|1.217780e-07|2.025834e-08\n", + " 176|1.663547e-01|1.140754e-07|1.897697e-08\n", + " 177|1.663546e-01|1.160707e-07|1.930890e-08\n", + " 178|1.663546e-01|1.101798e-07|1.832892e-08\n", + " 179|1.663546e-01|1.114904e-07|1.854694e-08\n", + "It. |Loss |Relative loss|Absolute loss\n", + "------------------------------------------------\n", + " 180|1.663546e-01|1.064022e-07|1.770049e-08\n", + " 181|1.663546e-01|9.258231e-08|1.540149e-08\n", + " 182|1.663546e-01|1.213120e-07|2.018080e-08\n", + " 183|1.663545e-01|1.164296e-07|1.936859e-08\n", + " 184|1.663545e-01|1.188762e-07|1.977559e-08\n", + " 185|1.663545e-01|9.394153e-08|1.562760e-08\n", + " 186|1.663545e-01|1.028656e-07|1.711216e-08\n", + " 187|1.663545e-01|1.115348e-07|1.855431e-08\n", + " 188|1.663544e-01|9.768310e-08|1.625002e-08\n", + " 189|1.663544e-01|1.021806e-07|1.699820e-08\n", + " 190|1.663544e-01|1.086303e-07|1.807113e-08\n", + " 191|1.663544e-01|9.879008e-08|1.643416e-08\n", + " 192|1.663544e-01|1.050210e-07|1.747071e-08\n", + " 193|1.663544e-01|1.002463e-07|1.667641e-08\n", + " 194|1.663543e-01|1.062747e-07|1.767925e-08\n", + " 195|1.663543e-01|9.348538e-08|1.555170e-08\n", + " 196|1.663543e-01|7.992512e-08|1.329589e-08\n", + " 197|1.663543e-01|9.558020e-08|1.590018e-08\n", + " 198|1.663543e-01|9.993772e-08|1.662507e-08\n", + " 199|1.663543e-01|8.588499e-08|1.428734e-08\n", + "It. |Loss |Relative loss|Absolute loss\n", + "------------------------------------------------\n", + " 200|1.663543e-01|8.737134e-08|1.453459e-08\n" ] }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "<Figure size 432x288 with 3 Axes>" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], "source": [ - "#%% Example with Frobenius norm regularization\n", - "\n", - "\n", "def f(G):\n", " return 0.5 * np.sum(G**2)\n", "\n", @@ -420,215 +417,124 @@ "name": "stdout", "output_type": "stream", "text": [ - "It. |Loss |Delta loss\n", - "--------------------------------\n", - " 0|1.692289e-01|0.000000e+00\n", - " 1|1.617643e-01|-4.614437e-02\n", - " 2|1.612639e-01|-3.102965e-03\n", - " 3|1.611291e-01|-8.371098e-04\n", - " 4|1.610468e-01|-5.110558e-04\n", - " 5|1.610198e-01|-1.672927e-04\n", - " 6|1.610130e-01|-4.232417e-05\n", - " 7|1.610090e-01|-2.513455e-05\n", - " 8|1.610002e-01|-5.443507e-05\n", - " 9|1.609996e-01|-3.657071e-06\n", - " 10|1.609948e-01|-2.998735e-05\n", - " 11|1.609695e-01|-1.569217e-04\n", - " 12|1.609533e-01|-1.010779e-04\n", - " 13|1.609520e-01|-8.043897e-06\n", - " 14|1.609465e-01|-3.415246e-05\n", - " 15|1.609386e-01|-4.898605e-05\n", - " 16|1.609324e-01|-3.837052e-05\n", - " 17|1.609298e-01|-1.617826e-05\n", - " 18|1.609184e-01|-7.080015e-05\n", - " 19|1.609083e-01|-6.273206e-05\n", - "It. |Loss |Delta loss\n", - "--------------------------------\n", - " 20|1.608988e-01|-5.940805e-05\n", - " 21|1.608853e-01|-8.380030e-05\n", - " 22|1.608844e-01|-5.185045e-06\n", - " 23|1.608824e-01|-1.279113e-05\n", - " 24|1.608819e-01|-3.156821e-06\n", - " 25|1.608783e-01|-2.205746e-05\n", - " 26|1.608764e-01|-1.189894e-05\n", - " 27|1.608755e-01|-5.474607e-06\n", - " 28|1.608737e-01|-1.144227e-05\n", - " 29|1.608676e-01|-3.775335e-05\n", - " 30|1.608638e-01|-2.348020e-05\n", - " 31|1.608627e-01|-6.863136e-06\n", - " 32|1.608529e-01|-6.110230e-05\n", - " 33|1.608487e-01|-2.641106e-05\n", - " 34|1.608409e-01|-4.823638e-05\n", - " 35|1.608373e-01|-2.256641e-05\n", - " 36|1.608338e-01|-2.132444e-05\n", - " 37|1.608310e-01|-1.786649e-05\n", - " 38|1.608260e-01|-3.103848e-05\n", - " 39|1.608206e-01|-3.321265e-05\n", - "It. |Loss |Delta loss\n", - "--------------------------------\n", - " 40|1.608201e-01|-3.054747e-06\n", - " 41|1.608195e-01|-4.198335e-06\n", - " 42|1.608193e-01|-8.458736e-07\n", - " 43|1.608159e-01|-2.153759e-05\n", - " 44|1.608115e-01|-2.738314e-05\n", - " 45|1.608108e-01|-3.960032e-06\n", - " 46|1.608081e-01|-1.675447e-05\n", - " 47|1.608072e-01|-5.976340e-06\n", - " 48|1.608046e-01|-1.604130e-05\n", - " 49|1.608020e-01|-1.617036e-05\n", - " 50|1.608014e-01|-3.957795e-06\n", - " 51|1.608011e-01|-1.292411e-06\n", - " 52|1.607998e-01|-8.431795e-06\n", - " 53|1.607964e-01|-2.127054e-05\n", - " 54|1.607947e-01|-1.021878e-05\n", - " 55|1.607947e-01|-3.560621e-07\n", - " 56|1.607900e-01|-2.929781e-05\n", - " 57|1.607890e-01|-5.740229e-06\n", - " 58|1.607858e-01|-2.039550e-05\n", - " 59|1.607836e-01|-1.319545e-05\n", - "It. |Loss |Delta loss\n", - "--------------------------------\n", - " 60|1.607826e-01|-6.378947e-06\n", - " 61|1.607808e-01|-1.145102e-05\n", - " 62|1.607776e-01|-1.941743e-05\n", - " 63|1.607743e-01|-2.087422e-05\n", - " 64|1.607741e-01|-1.310249e-06\n", - " 65|1.607738e-01|-1.682752e-06\n", - " 66|1.607691e-01|-2.913936e-05\n", - " 67|1.607671e-01|-1.288855e-05\n", - " 68|1.607654e-01|-1.002448e-05\n", - " 69|1.607641e-01|-8.209492e-06\n", - " 70|1.607632e-01|-5.588467e-06\n", - " 71|1.607619e-01|-8.050388e-06\n", - " 72|1.607618e-01|-9.417493e-07\n", - " 73|1.607598e-01|-1.210509e-05\n", - " 74|1.607591e-01|-4.392914e-06\n", - " 75|1.607579e-01|-7.759587e-06\n", - " 76|1.607574e-01|-2.760280e-06\n", - " 77|1.607556e-01|-1.146469e-05\n", - " 78|1.607550e-01|-3.689456e-06\n", - " 79|1.607550e-01|-4.065631e-08\n", - "It. |Loss |Delta loss\n", - "--------------------------------\n", - " 80|1.607539e-01|-6.555681e-06\n", - " 81|1.607528e-01|-7.177470e-06\n", - " 82|1.607527e-01|-5.306068e-07\n", - " 83|1.607514e-01|-7.816045e-06\n", - " 84|1.607511e-01|-2.301970e-06\n", - " 85|1.607504e-01|-4.281072e-06\n", - " 86|1.607503e-01|-7.821886e-07\n", - " 87|1.607480e-01|-1.403013e-05\n", - " 88|1.607480e-01|-1.169298e-08\n", - " 89|1.607473e-01|-4.235982e-06\n", - " 90|1.607470e-01|-1.717105e-06\n", - " 91|1.607470e-01|-6.148402e-09\n", - " 92|1.607462e-01|-5.396481e-06\n", - " 93|1.607461e-01|-5.194954e-07\n", - " 94|1.607450e-01|-6.525707e-06\n", - " 95|1.607442e-01|-5.332060e-06\n", - " 96|1.607439e-01|-1.682093e-06\n", - " 97|1.607437e-01|-1.594796e-06\n", - " 98|1.607435e-01|-7.923812e-07\n", - " 99|1.607420e-01|-9.738552e-06\n", - "It. |Loss |Delta loss\n", - "--------------------------------\n", - " 100|1.607419e-01|-1.022448e-07\n", - " 101|1.607419e-01|-4.865999e-07\n", - " 102|1.607418e-01|-7.092012e-07\n", - " 103|1.607408e-01|-5.861815e-06\n", - " 104|1.607402e-01|-3.953266e-06\n", - " 105|1.607395e-01|-3.969572e-06\n", - " 106|1.607390e-01|-3.612075e-06\n", - " 107|1.607377e-01|-7.683735e-06\n", - " 108|1.607365e-01|-7.777599e-06\n", - " 109|1.607364e-01|-2.335096e-07\n", - " 110|1.607364e-01|-4.562036e-07\n", - " 111|1.607360e-01|-2.089538e-06\n", - " 112|1.607356e-01|-2.755355e-06\n", - " 113|1.607349e-01|-4.501960e-06\n", - " 114|1.607347e-01|-1.160544e-06\n", - " 115|1.607346e-01|-6.289450e-07\n", - " 116|1.607345e-01|-2.092146e-07\n", - " 117|1.607336e-01|-5.990866e-06\n", - " 118|1.607330e-01|-3.348498e-06\n", - " 119|1.607328e-01|-1.256222e-06\n", - "It. |Loss |Delta loss\n", - "--------------------------------\n", - " 120|1.607320e-01|-5.418353e-06\n", - " 121|1.607318e-01|-8.296189e-07\n", - " 122|1.607311e-01|-4.381608e-06\n", - " 123|1.607310e-01|-8.913901e-07\n", - " 124|1.607309e-01|-3.808821e-07\n", - " 125|1.607302e-01|-4.608994e-06\n", - " 126|1.607294e-01|-5.063777e-06\n", - " 127|1.607290e-01|-2.532835e-06\n", - " 128|1.607285e-01|-2.870049e-06\n", - " 129|1.607284e-01|-4.892812e-07\n", - " 130|1.607281e-01|-1.760452e-06\n", - " 131|1.607279e-01|-1.727139e-06\n", - " 132|1.607275e-01|-2.220706e-06\n", - " 133|1.607271e-01|-2.516930e-06\n", - " 134|1.607269e-01|-1.201434e-06\n", - " 135|1.607269e-01|-2.183459e-09\n", - " 136|1.607262e-01|-4.223011e-06\n", - " 137|1.607258e-01|-2.530202e-06\n", - " 138|1.607258e-01|-1.857260e-07\n", - " 139|1.607256e-01|-1.401957e-06\n", - "It. |Loss |Delta loss\n", - "--------------------------------\n", - " 140|1.607250e-01|-3.242751e-06\n", - " 141|1.607247e-01|-2.308071e-06\n", - " 142|1.607247e-01|-4.730700e-08\n", - " 143|1.607246e-01|-4.240229e-07\n", - " 144|1.607242e-01|-2.484810e-06\n", - " 145|1.607238e-01|-2.539206e-06\n", - " 146|1.607234e-01|-2.535574e-06\n", - " 147|1.607231e-01|-1.954802e-06\n", - " 148|1.607228e-01|-1.765447e-06\n", - " 149|1.607228e-01|-1.620007e-08\n", - " 150|1.607222e-01|-3.615783e-06\n", - " 151|1.607222e-01|-8.668516e-08\n", - " 152|1.607215e-01|-4.000673e-06\n", - " 153|1.607213e-01|-1.774103e-06\n", - " 154|1.607213e-01|-6.328834e-09\n", - " 155|1.607209e-01|-2.418783e-06\n", - " 156|1.607208e-01|-2.848492e-07\n", - " 157|1.607207e-01|-8.836043e-07\n", - " 158|1.607205e-01|-1.192836e-06\n", - " 159|1.607202e-01|-1.638022e-06\n", - "It. |Loss |Delta loss\n", - "--------------------------------\n", - " 160|1.607202e-01|-3.670914e-08\n", - " 161|1.607197e-01|-3.153709e-06\n", - " 162|1.607197e-01|-2.419565e-09\n", - " 163|1.607194e-01|-2.136882e-06\n", - " 164|1.607194e-01|-1.173754e-09\n", - " 165|1.607192e-01|-8.169238e-07\n", - " 166|1.607191e-01|-9.218755e-07\n", - " 167|1.607189e-01|-9.459255e-07\n", - " 168|1.607187e-01|-1.294835e-06\n", - " 169|1.607186e-01|-5.797668e-07\n", - " 170|1.607186e-01|-4.706272e-08\n", - " 171|1.607183e-01|-1.753383e-06\n", - " 172|1.607183e-01|-1.681573e-07\n", - " 173|1.607183e-01|-2.563971e-10\n" + "It. |Loss |Relative loss|Absolute loss\n", + "------------------------------------------------\n", + " 0|1.692289e-01|0.000000e+00|0.000000e+00\n", + " 1|1.617643e-01|4.614437e-02|7.464513e-03\n", + " 2|1.612639e-01|3.102965e-03|5.003963e-04\n", + " 3|1.611291e-01|8.371098e-04|1.348827e-04\n", + " 4|1.610468e-01|5.110558e-04|8.230389e-05\n", + " 5|1.610198e-01|1.672927e-04|2.693743e-05\n", + " 6|1.610130e-01|4.232417e-05|6.814742e-06\n", + " 7|1.610090e-01|2.513455e-05|4.046887e-06\n", + " 8|1.610002e-01|5.443507e-05|8.764057e-06\n", + " 9|1.609996e-01|3.657071e-06|5.887869e-07\n", + " 10|1.609948e-01|2.998735e-05|4.827807e-06\n", + " 11|1.609695e-01|1.569217e-04|2.525962e-05\n", + " 12|1.609533e-01|1.010779e-04|1.626881e-05\n", + " 13|1.609520e-01|8.043897e-06|1.294681e-06\n", + " 14|1.609465e-01|3.415246e-05|5.496718e-06\n", + " 15|1.609386e-01|4.898605e-05|7.883745e-06\n", + " 16|1.609324e-01|3.837052e-05|6.175060e-06\n", + " 17|1.609298e-01|1.617826e-05|2.603564e-06\n", + " 18|1.609184e-01|7.080015e-05|1.139305e-05\n", + " 19|1.609083e-01|6.273206e-05|1.009411e-05\n", + "It. |Loss |Relative loss|Absolute loss\n", + "------------------------------------------------\n", + " 20|1.608988e-01|5.940805e-05|9.558681e-06\n", + " 21|1.608853e-01|8.380030e-05|1.348223e-05\n", + " 22|1.608844e-01|5.185045e-06|8.341930e-07\n", + " 23|1.608824e-01|1.279113e-05|2.057868e-06\n", + " 24|1.608819e-01|3.156821e-06|5.078753e-07\n", + " 25|1.608783e-01|2.205746e-05|3.548567e-06\n", + " 26|1.608764e-01|1.189894e-05|1.914259e-06\n", + " 27|1.608755e-01|5.474607e-06|8.807303e-07\n", + " 28|1.608737e-01|1.144227e-05|1.840760e-06\n", + " 29|1.608676e-01|3.775335e-05|6.073291e-06\n", + " 30|1.608638e-01|2.348020e-05|3.777116e-06\n", + " 31|1.608627e-01|6.863136e-06|1.104023e-06\n", + " 32|1.608529e-01|6.110230e-05|9.828482e-06\n", + " 33|1.608487e-01|2.641106e-05|4.248184e-06\n", + " 34|1.608409e-01|4.823638e-05|7.758383e-06\n", + " 35|1.608373e-01|2.256641e-05|3.629519e-06\n", + " 36|1.608338e-01|2.132444e-05|3.429691e-06\n", + " 37|1.608310e-01|1.786649e-05|2.873484e-06\n", + " 38|1.608260e-01|3.103848e-05|4.991794e-06\n", + " 39|1.608206e-01|3.321265e-05|5.341279e-06\n", + "It. |Loss |Relative loss|Absolute loss\n", + "------------------------------------------------\n", + " 40|1.608201e-01|3.054747e-06|4.912648e-07\n", + " 41|1.608195e-01|4.198335e-06|6.751739e-07\n", + " 42|1.608193e-01|8.458736e-07|1.360328e-07\n", + " 43|1.608159e-01|2.153759e-05|3.463587e-06\n", + " 44|1.608115e-01|2.738314e-05|4.403523e-06\n", + " 45|1.608108e-01|3.960032e-06|6.368161e-07\n", + " 46|1.608081e-01|1.675447e-05|2.694254e-06\n", + " 47|1.608072e-01|5.976340e-06|9.610383e-07\n", + " 48|1.608046e-01|1.604130e-05|2.579515e-06\n", + " 49|1.608020e-01|1.617036e-05|2.600226e-06\n", + " 50|1.608014e-01|3.957795e-06|6.364188e-07\n", + " 51|1.608011e-01|1.292411e-06|2.078211e-07\n", + " 52|1.607998e-01|8.431795e-06|1.355831e-06\n", + " 53|1.607964e-01|2.127054e-05|3.420225e-06\n", + " 54|1.607947e-01|1.021878e-05|1.643126e-06\n", + " 55|1.607947e-01|3.560621e-07|5.725288e-08\n", + " 56|1.607900e-01|2.929781e-05|4.710793e-06\n", + " 57|1.607890e-01|5.740229e-06|9.229659e-07\n", + " 58|1.607858e-01|2.039550e-05|3.279306e-06\n", + " 59|1.607836e-01|1.319545e-05|2.121612e-06\n", + "It. |Loss |Relative loss|Absolute loss\n", + "------------------------------------------------\n", + " 60|1.607826e-01|6.378947e-06|1.025624e-06\n", + " 61|1.607808e-01|1.145102e-05|1.841105e-06\n", + " 62|1.607776e-01|1.941743e-05|3.121889e-06\n", + " 63|1.607743e-01|2.087422e-05|3.356037e-06\n", + " 64|1.607741e-01|1.310249e-06|2.106541e-07\n", + " 65|1.607738e-01|1.682752e-06|2.705425e-07\n", + " 66|1.607691e-01|2.913936e-05|4.684709e-06\n", + " 67|1.607671e-01|1.288855e-05|2.072055e-06\n", + " 68|1.607654e-01|1.002448e-05|1.611590e-06\n", + " 69|1.607641e-01|8.209492e-06|1.319792e-06\n", + " 70|1.607632e-01|5.588467e-06|8.984199e-07\n", + " 71|1.607619e-01|8.050388e-06|1.294196e-06\n", + " 72|1.607618e-01|9.417493e-07|1.513973e-07\n", + " 73|1.607598e-01|1.210509e-05|1.946012e-06\n", + " 74|1.607591e-01|4.392914e-06|7.062009e-07\n", + " 75|1.607579e-01|7.759587e-06|1.247415e-06\n", + " 76|1.607574e-01|2.760280e-06|4.437356e-07\n", + " 77|1.607556e-01|1.146469e-05|1.843012e-06\n", + " 78|1.607550e-01|3.689456e-06|5.930984e-07\n", + " 79|1.607550e-01|4.065631e-08|6.535705e-09\n", + "It. |Loss |Relative loss|Absolute loss\n", + "------------------------------------------------\n", + " 80|1.607539e-01|6.555681e-06|1.053852e-06\n", + " 81|1.607528e-01|7.177470e-06|1.153798e-06\n", + " 82|1.607527e-01|5.306068e-07|8.529648e-08\n", + " 83|1.607514e-01|7.816045e-06|1.256440e-06\n", + " 84|1.607511e-01|2.301970e-06|3.700442e-07\n", + " 85|1.607504e-01|4.281072e-06|6.881840e-07\n", + " 86|1.607503e-01|7.821886e-07|1.257370e-07\n", + " 87|1.607480e-01|1.403013e-05|2.255315e-06\n", + " 88|1.607480e-01|1.169298e-08|1.879624e-09\n", + " 89|1.607473e-01|4.235982e-06|6.809227e-07\n", + " 90|1.607470e-01|1.717105e-06|2.760195e-07\n", + " 91|1.607470e-01|6.148402e-09|9.883374e-10\n" ] }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "<Figure size 360x360 with 3 Axes>" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], "source": [ - "#%% Example with entropic regularization\n", - "\n", - "\n", "def f(G):\n", " return np.sum(G * np.log(G))\n", "\n", @@ -665,30 +571,35 @@ "name": "stdout", "output_type": "stream", "text": [ - "It. |Loss |Delta loss\n", - "--------------------------------\n", - " 0|1.693084e-01|0.000000e+00\n", - " 1|1.610121e-01|-5.152589e-02\n", - " 2|1.609378e-01|-4.622297e-04\n", - " 3|1.609284e-01|-5.830043e-05\n", - " 4|1.609284e-01|-1.111407e-12\n" + "It. |Loss |Relative loss|Absolute loss\n", + "------------------------------------------------\n", + " 0|1.693084e-01|0.000000e+00|0.000000e+00\n", + " 1|1.610202e-01|5.147342e-02|8.288260e-03\n", + " 2|1.609508e-01|4.309685e-04|6.936474e-05\n", + " 3|1.609484e-01|1.524885e-05|2.454278e-06\n", + " 4|1.609477e-01|3.863641e-06|6.218444e-07\n", + " 5|1.609475e-01|1.433633e-06|2.307397e-07\n", + " 6|1.609474e-01|6.332412e-07|1.019185e-07\n", + " 7|1.609474e-01|2.950826e-07|4.749276e-08\n", + " 8|1.609473e-01|1.508393e-07|2.427718e-08\n", + " 9|1.609473e-01|7.859971e-08|1.265041e-08\n", + " 10|1.609473e-01|4.337432e-08|6.980981e-09\n" ] }, { "data": { - "image/png": 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AIqn86lc+3fyll6aOpHUdfDDsuitcdZVPXSRrKAGLpDB3Ltx2G3zzm36xKp+ZweWXw8cfqwquQwlYJIXrr/exH37849SRtI3DDlMVXA8lYJG2NmeOd806/vj8r34zMlXwtGkaqrIWJWCRtnbFFd4j4PLLU0fStg47zHtFXH65TzoqSsAiberDD73nw2mnwZZbpo6mbZn5TSeffqoxIiIlYJG2dNllPkjNT3+aOpI09trLZ1C+5hr44ovU0SSnBCzSVl5+2acbuvBCnz+tvfrlL/3W5J/9LHUkySkBi7SFykofI3fIEPjhD1NHk9b22/uUS7ff7rM/t2NKwCJt4dZbfdSzG2+ETp1SR5PelVf6kJVnndWu545TAhZpbZ9+6m2+Bx4IRx6ZOprs0KMHXHstvPqqT2PfTikBi7SmELzHQ3m5zxScD7NdtJTRo/2i3Pnnw+zZqaNJQglYpDXdey+MGQNXXw1bbZU6muxSUAB/+IP/czr1VP9n1c4oAYu0llmz4JxzYI89/FHWteWW3iviySc9GbczSsAiraGiAo47zns//PGPUFiYOqLsdfbZPhP02Wf7xKTtiBKwSGv40Y/glVf8rjc1PWxYQQHcdx906wbHHNOupi9SAhZpaQ8/7GP9nn66V8HSsH794P774f334bvfbTdd05SARVrSq6/Ct78Nu+/ufX6l8fbbz8eKePhh/wTRDhSlDkAkb3zwgc8CPGgQPPEElJamjij3XHABfPSRjxUxeDCccUbqiFqVErBIS3j/fa/gzPyKfu/eqSPKTWZwyy3eg+TMM/3i5amnpo6q1agJQqS5Jk3yq/jV1fDii7ro1lxFRfDIIz5+8Gmn+Q0seUoJWKQ5nnrK23vN4IUXYLvtUkeUHzp08JHjjjjCu6edfz5UVaWOqsUpAYtsjKoqv7vt8MP9ZoLXX4cvfSl1VPklk4TPOw9uugkOPdSnc8ojSsAiTTVtmjc5/OhH3m/15Zdh4MDUUeWnwkLvTXLHHX6ehw2Dxx9PHVWLUQIWaazly31Us+2283Fs77kHHngAunRJHVn+O+UUmDDB/9H9z/94+/CHH6aOqtmUgEUasnixd4vafHMfx/brX4f33vP+vhrdrO1stx2MGwfXXw//+pc/P/FE/13kKCVgkfpUVsI//wknneR3aV16Key6q99efP/9anJIpaTE+wp/+CGce663EW+/Pey9t093v3Bh6gibxEI7HAJO1jV8+PAwfvz41GGkU1XlN1K88or3ZnjmGViwwJsXvvlN7w61yy6po5S65s3zUdTuugumTPE24733hlGj/HGXXaBz51Y7vJlNCCEM3+jvVwIWaAcJuLzcq6N58+Dzz72j/4wZMHWqJ95Jk2DFCt92s81g//29rfGgg1r1DSwtJAR44w147DH4xz98+ifwJqKtt/YeKlttBWVlfqdiv34+MWqvXv773cimJCVgaRHD+/QJ4484ovUPtL6/t8z62q+HsO5SXe2PVVU1S2WlLxUVsHq1LytX+rJsGSxd6l/XZ+BA2GYb2GEHr5ZGjPA3rNp2c9sXX/i4HBMn+gXTDz7wf7bl5etuW1QEXbv60qkTdOzoXeA6dPAmj+Ji36awsGbp3x9uuEEJWFrG8JKSML6tpkpfX3LLrK/9utnaS0GBP9Z+MxQW+pukuLjmjdOxoy9du3ozQo8evvTpA337euIdONC3lfahuto//XzyiT/OneufihYu9H/SS5f6p6CVK2v+kZeX+z/2ysqaf/jV1T679TPPNDsBaywIcTvuCPncBCFSUOBND/36pY5kDfWCEBFJRAlYRCQRtQELAGa2FPggdRwN6A3MTx1EA3IhRsiNOHMhxm1CCF039pvVBiwZHzTnYkJbMLPxirFl5EKcuRJjc75fTRAiIokoAYuIJKIELBl3pA6gERRjy8mFOPM+Rl2EExFJRBWwiEgiSsAiIokoAbdzZnawmX1gZlPN7JLU8WSY2SAze8HM3jOzd83s3Li+l5k9a2ZT4mPPLIi10MwmmtmY+HxzMxsXz+mDZlaSOL4eZvaImb1vZpPNbLdsO49mdn78PU8yswfMrDQbzqOZ/cHM5prZpFrr6j135n4T433bzBocv1QJuB0zs0LgVuAQYDvgeDPLlml9K4ELQgjbASOBs2JslwDPhxC2Ap6Pz1M7F5hc6/m1wI0hhC2BhcDJSaKqcTPwdAhhW+DLeKxZcx7NbABwDjA8hLADUAgcR3acxz8BB9dZt75zdwiwVVxOBW5vcO8hBC3tdAF2A56p9fxS4NLUca0n1ieAA/C79frFdf3wG0hSxjUwvgn3A8YAht+9VVTfOU4QX3fgY+IF91rrs+Y8AgOAmUAv/OawMcBB2XIegTJgUkPnDvg9cHx9261vUQXcvmX+8DNmxXVZxczKgJ2BcUDfEMJn8aU5QN9EYWXcBFwEVMfnmwCLQgiV8Xnqc7o5MA/4Y2wmudPMOpNF5zGEMBu4HvgE+AxYDEwgu85jbes7d01+PykBS1Yzsy7Ao8B5IYQltV8LXmYk60dpZocDc0MIE1LF0AhFwC7A7SGEnYHl1GluyILz2BM4Av9n0R/ozLof+7NSc8+dEnD7NhsYVOv5wLguK5hZMZ587wsh/DWu/tzM+sXX+wFzU8UH7AH8t5lNB/6CN0PcDPQws8w4K6nP6SxgVghhXHz+CJ6Qs+k87g98HEKYF0KoAP6Kn9tsOo+1re/cNfn9pATcvr0BbBWvNpfgFz7+ljgmwK8oA3cBk0MIN9R66W/A6Pj1aLxtOIkQwqUhhIEhhDL83P0zhHAC8AJwdNwsdYxzgJlmtk1cNQp4jyw6j3jTw0gz6xR/75kYs+Y81rG+c/c34MTYG2IksLhWU0X9UjW8a8mOBTgU+BD4CPhR6nhqxbUn/tHubeCtuByKt7E+D0wBngN6pY41xrsPMCZ+PRR4HZgKPAx0SBzbTsD4eC4fB3pm23kErgDeByYBfwY6ZMN5BB7A26Ur8E8TJ6/v3OEXYG+N76V38F4dG9x/s25FNrOD8Y9chcCdIYRrNnpnIiLtzEYn4NiH9EO8a9As/OPs8SGE91ouPBGR/NWcAdm/CkwNIUwDMLO/4Fcy15uAe/fuHcrKyppxSGmuRYt88tdBg9ZeP2HChPkhhD6Z5wcUHKNRmkRqebb64fVM573xmpOA6+vzNqLuRmZ2Kn5XCIMHD2a8Zt5N6qKL4JZb1p0A2cxmpIlIpP1q9V4QIYQ7QgjDQwjD+/Tp0/A3SKuqqIDi4tRRiAg0LwFndR9SqV95OZQkHRpGRDKak4Cztg+prN+KFdC5c+ooRASa0QYcQqg0s+8Dz+Dd0P4QQni3xSKTVrFkCXTpkjoKEYFmTksfQngSeLKFYpE28MUXsMkmqaMQEdCtyO3O7Nmw2WapoxARUAJuV6qqYPp02GKL1JEkYNa0RaQNKAG3I5MmQWUl7LBD6khEBJrZBiy55aWX/HHvvdPGkRWsoM7TtaveUF3nRsBQXee5bhSU5lMF3I7cey9st926tyGLSBqqgNuJsWPhjTf8NuR2KVOx1mnfXVP5Ziri+NwK63x/piKOlXCo83yd44g0girgdqC8HM44A/r2hRNPTB2NiGSoAs5zIcCPfgRvvQWPPw7duqWOKLE1FWqmkvUaxAoylayXvlYYS+BMxVxQp824Om5fVeX7qYr7i8/XVMaqiGUDVAHnsRB89LPrr/cK+IgjUkckIrWpAs5TixfDOefAPffAWWfBb36TOqIss75KmFjBZirfOHScFcW3SmGsWer2oqiO31fhs6iHyviYea7KWOqhCjgPPf6493a491746U/9wluBftMiWUcVcB557TX45S/h73+HHXf0RPyVr6SOKstlKtEQ23JDnV4Sa76IX8VK2ErioMrFRWu/HvdnlXF/FRW+fvVqf15eEderMhZVwDmvqgoeewz22AN23x3+/W+4+mqf8ULJVyS7qQLOUZMnw4MPwn33wdSpUFbm7bzf+Y6Gm2yWWIGuqUzXrPb1mYolZPoLxwo4lPoo96E49p7ItPlkKuJyr3gLVpX7+pWr/OVVmcdYIVfWrYxVEeczJeAc8uGHnnQfesjHdTDz24qvugq+/vU1n45FJEfoLZvFli2Df/0LnnsOnn0W3nnHk+6ee/qFtaOOgn79UkeZpzKVcKxIM3fCVcdHq1OZWqx4Q4m/pao6eRtxdQeviNdUzPH7C1Z7hVu4zCvfgqUrfbtlK/yxbmWcqYir167MJbcpAWeRigoYN84T7vPP++3DlZU+h9see8BNN8HRR8OAAakjFZGWoASc0Ny5nnAzy2uvwfLlXuXuuitccAHsv78n344dU0fbzlVneknE3gor174TLvNYkKmcY0WcqYAruvhjZWmslDNNxZX+iy1a4bcoliz1XhJFC70iLly83LdfsswfV/r66tibQr0ncpsScBtZvdpvBx471pPt2LHw8cf+WmEhDBsGo0fDqFGwzz7Qq1fScEWkDSgBt4Jly+Dttz3hTpzoj2+/7YPigDchjBzptwePGOHVrmYqzhF12oYzo6JZpgKO6wtjP1+r6urbmf+Cqzp4BVze2duEKzr5Y4h32BWW+1uyeFkpAKWLvDIuned/PEXzvRIuXLTEv29ZrJBX12krVkWcE5SAm+nzz9dOtBMnwpQpNX//vXrBzjvDued6sh0xAgYOTBuziGQHJeBGWrkS3nvPeyLUXubMqdmmrMyT7QknwE47+dcDB2qKsbyWaRsur45P/bnFNlqLd8J1WB37AceKGDoAUNXB/zhWdfe1Kztn2pD9eeFqbywuWdwJgNL53mbc+fOe/vwz7zVROH+xf99ir4yrM/2MKzNtxaqIs5EScB1VVTBt2rqJdupUyIxAWFrqYy0cdFBNov3yl6FHj7Sxi0huadcJeO7cdRPtu+/CCi8qMPMZhIcNg+OO88dhw2DLLf3CmcgadduGM5VwbAsuiBVpSezXW7jC/1sXlsfuLcHfiiv8hjrKe8e23P5ewa403/+y5d6/eNEXvn2nz7107vypV9adZ/txiud4RcxCf6zOtBVXZPo1qz9xNmgXCXjFCk+sdZPt3Lk12/Tp48n1lFNqEu322+vimIi0nrxLwAsW+IWwN9+sefzww5omsNJSn5b9sMNqEu2wYT5dj0iLyVTEFd57oSrTSyJ2hSlY7h+zuizxttzipV7JFsUSeFmFvzVXFfp+em3mlWzfft4Lgi394bMl3kvis8+9Ai6d7W3FXWZ6Zd31k15xvbcNM3+Rx7V0KVCrP7Eq4iRyNgGHAJ9+um6y/eSTmm0GDYJddlm7+WCLLdR8ICLZIWcScHW1NyO8/LKPj/Dyy/DZZzWvb7017Labz/6w886+9O6dLl6RtcQKs3q1X8m12FZssW24NI4BUbwo9m5Y5EPaLVnibb4LV/r66iHePWL4ZjMB2LfPBwCs3ty3e2ux93F8e3Z/ABbN8Da0LjP6ANB9urc9d/zEK+DCeQsACEu9sq6ObdSqiNtG1ibgigqYMKEm2b7yCixc6K8NGOB3i40c6RXul78MXbtucHciIlknqxJwCD6g+D33+JCLS2Kz1dZb+3CLe+3lwy+WlalvreSo9fSWyMyUURAr0W4LYiU8Lz7G/r9LvvA23ee38LbehZv7+sP7vA3AgQPfAWBBP6+gn996OwCem7kNADM/9gq4y8e+nx7TvA25U6yIiz73irh6SWwjVkXcqhpMwGY2CLgH6AsE4I4Qws1m1gt4ECgDpgPHhhAWbkwQ06bBn//siXfaNO95cNRR8LWv+dCLm222MXsVEcluFhq4Q8bM+gH9QghvmllXYAJwJHASsCCEcI2ZXQL0DCFcvKF9DR8+PIwfP36tdb/+NVx4oVe0o0bBiSd6tavuX23LzCaEEIZnnh9QcIxunUohfrSzEu8NUdAlvhE28Up41WCvYBcP9deXbOEvd9jKPy4eUvYeAMf1HAfANsXe5vxprLQfW7KTP878MgBzp24CQNdpfmW6x0demXea4fuzWBGvucOuHfeaeLb64Rb/3N1gBRxC+Az4LH691MwmAwOAI4B94mZ3Ay8CG0zAdd1xhyffo46CG2/0XgsiIu1Fk9qAzawM2BkYB/SNyRlgDt5E0WgffwxE55M6AAAPjklEQVSnnw7Dh8P99/ug4yLtXqaNOI5uVpW5ky72Gy5d6JVo6Wfehtt1trfhLprl/Yj/usUIAF7ayjsKHzX4LQCO7TYRgIs3mbLW84cG7QzAI0P9cVZZ3O9HsY34I7+6namIC+dmek2oH3FLaPSsyGbWBXgUOC+EsKT2a8HbMer9yGpmp5rZeDMbP2/evDXrBw6Efff1/rtPPrlxwYuI5LIG24ABzKwYGAM8E0K4Ia77ANgnhPBZbCd+MYSwzYb2U7cNeOlSOOAAeOMNH9hm9Gg44gi/W03altqAc0SBt9UWlHi/X+vuFXDo6xXriiGxIt7CP9wuHeqV6aZbfgHA/wz6jz9288q4f7wr6YMKr8X+stAr6Keme++J1VN8f90+8sN3n+Z38pV+4nfU8YVfd18z1kRm0Os8HH2tNdqAG6yAzcyAu4DJmeQb/Q0YHb8eDTzR1IN37QpPPw0XX+xjMxx3nPd4OPVU7/ebGX1MRCQfNaYXxJ7Av4B3gExKvAxvB34IGAzMwLuhLdjQvurrBZFRVQUvvgh33w2PPuoD6PTs6d3Q9t7b+wDvsgsUFzflx5PGUgWcozIVcamPL1zQzdtsqzMV8WB/vmioV8TLNve3cPehXrmOGvihP3bz3hO9Cr0f8nurfebXMfN2BODNjwcD0OEj/3jabZr/eXT72OeoK5nt+wuZirj2eMR5Ug2n6gXxb2B9Bx7VUoEUFno3tFGj4Lbb4Ikn4IUX/E64v//dt+nUyW83ztyQ8dWvqruaiOSuRrUBt5QNVcAbMmeO3yGXGQfiP//xf6pmsM02Pu7DLrvUjAGhCS2bThVwnqhTEVtXvyMu9PE3xcohXhEvHuIfJZcNiXPaDfE23B0HfArATt1nAdChwHs5fLjc74YaP8f7ii6e4b0uun7sx+s23duaO0+Pc9bNjZXwosV5M19dkgo4G2y2GRx9tC8AixbBq6/6xbuJEz05P/BAzfZDhtQk5F128Vkr+vfX7csikl1yIgHX1aMHHHqoLxnz53syzixvvgmPP17zz7Znz5ohKXfc0R932EGD+EieyYy6lpnWJY7lUBDvZOsUxw3uNM3vqFs1wHs5LB3sbXnvDtoagAkDNgegR1/v79uv25K1HgtiW/KCjl4Jl3fzinpVj9hrYoa3FXeY3QmL7cKZGZzVd7hGTibg+vTu7V3aDjigZt3Spd5c8Z//eC+Lt9/28SZiH3LAB/apPTD7sGE++I8u9kleyCTkVTHZZSYLjSNdlc71xFs63RNpj838cfkAT6DL+3vTxZS+fit05SZ+Y0hhZ99PYSd/vqqff7ysLvYmicqO3gTStVsvOs32AYMK53rXNctMk6SJQ/MnAdena1fvRbHnnjXrQoAZM9adnuippyAOUEVJCWy77bqJWTMci0hLyusEXB8zr3rLyny0tYzVq+GDD7xKziTll16C++6r2aZHD2+2qNuU0a1bW/8UIhspVsRhtT9WxRsnbIlfPCue6zds9JwRmxI29Yp4VV8f/nJ53zhVUm//iFjePVatHeLuY0ZZlZkMoaCIqhKvsjt18heLM13mFnglHJavfRNHrl+sa4p2l4DXp0MHT6g77rj2+oULYdKktavl++6rGasYfJbkzPT0mcfNNlO1LCIbpgTcgJ49vd/xXnvVrAsBZs70avmtt3x580145JGabTbdtCYh77QT7LqrJ2olZckqdScPje2xFi/i2QK/gNZ5tndn69TdL+JV9PHnq3v7KFqrenjbb0UX/wOvioNrVRfC6u6ZP3qvfEsL/Qbckg6efgoW+MZhWZwWKdM2HAciyueLdUrAG8EMBg/25fDDa9YvXuxJeeJET8oTJ8INN/j0SuD9k0eM8GXkSL+RpGfPND+DiKSnBNyCundft1ouL4f33oPx42HcOBg71se/yDRvbb21J+MRI2D33b0JpKDRY9SJtLD1TJmUqUoLFnm7bfFc79lQ0s0r4c7dvZ23sqevL+/qbcSVnQrWtAuHWAhXdPVq2YK3KxfHP/iC4lgRF3klHFb4bc753DasBNzKSkpqmiG+9z1ft2SJJ+SxYz0pP/20d48D7063776w//5+W/bQoWq2EMlXSsAJdOsG++3nC9R0jXv5ZXj+eV8efthfKyurGSPj4IPVZCFtLFNthvX0J443V9gCb98t/jxWxp29uq3uUkpVF3+tuoNXvqFg7YqiqlPsdB8r4oJMxRGHyiRWwpmbStZUwnnQNqwEnAVqd4078UT/m//gg5pk/OijcNddfnPIgQfCscf6uMndu6eOXESaQwk4C5n5jSDbbgtnneVDdb7xhifihx6Cf/zDmzYOPtiT8VFHaRB7aWOZ/sSZx0zviZVerVq89dlKO1Cc+ePs6I+hNPZ6KInpJ1PxZtqfO8TB5qvX/qO2uF11ZnCfeHGbUL3W9+cSXe7JAYWFfqHuV7+C6dPhtdc8MU+YAN/6lg8+dOWV8MUXqSMVkabIieEopX7V1T5m8q9/7bdSd+wI3/0u/PCHnpSbQsNRSovKVLVWgMW2XIu9HCxOp0SHOGRmZuCVosK1vzeTm2J/4JAZxCdTAWd6R9TpsdFalXCSKYkkexUU+MW5J5+smdLpjjtgu+3gppu86UJEspcScJ7YYQf4wx9gyhTYZx84/3zvV/zuu6kjk3YpBF+qqwgV5YSKcqpXrqR65UqqliyjaskyqhcsistCqhcsJCxY5MuSpb4sX+lLeYVXv6Hal8JCX4qLobgYKyrypbDQq+2CuJhlfR9OJeA8M2QIjBkD998P06Z5En7lldRRiUh91AsiD5nB8cf7MJz77+9d1/72N2+uEEmmTp/idXpQZPr9WkF8HuvDzPq6t4hmpk0vWHs7I7P/zPbZ20tCFXAeGzTIb+4YOtSnc5o9O3VEIlKbEnCe69sXHnvMLxyfckpWFgHS3sX24lBZGZcKQmUF1atX+7JyFdUrVxFWrvRl1WpfMttXVdX0gACvoK0AKzCswNY8z8Y2YSXgdmDLLeHqq72r2gsvpI5GRDKUgNuJ00/34TBvuy11JCINyPSgqNWTguqqNZVupkIOFZVrLVRV+RJ7S4TqQKiu5yNfFlXCSsDtRGkpjB4NTzwBcQYYEUlMCbgdOfBAn3h07NjUkYhshPVUxutUyJk24Uy/4cyShZSA25HddvPH119PG4eIOPUDbke6d/deER99lDoSkVaQg118VAG3M2Vl8MknqaMQEVACbnd699awlSLZQgm4nenZExYuTB2FiEATErCZFZrZRDMbE59vbmbjzGyqmT1oZiWtF6a0lE6dIE5aICKJNaUCPheYXOv5tcCNIYQtgYXAyS0ZmLSO0lIlYJFs0agEbGYDgcOAO+NzA/YDHomb3A0c2RoBSssqLoaKioa3E5HW19gK+CbgItaM68YmwKIQQmV8PgsYUN83mtmpZjbezMbPmzevWcFK8xUV+c0YIpJegwnYzA4H5oYQJmzMAUIId4QQhocQhvfp02djdiEtqKCgZhhVEUmrMTdi7AH8t5kdCpQC3YCbgR5mVhSr4IGARpvNAUrAItmjwQo4hHBpCGFgCKEMOA74ZwjhBOAF4Oi42WjgiVaLUlqMWU7eMCSSl5rTD/hi4AdmNhVvE76rZUKS1qQELJI9mjQWRAjhReDF+PU04KstH5K0piwZBlVE0J1wIiLJKAG3M6qARbKHErCISCJKwCIiiSgBi4gkogQsIpKIErCISCJKwCIiiSgBi4gkogQsIpKIErCISCJKwCIiiSgBi4gkogQsIpKIErCISCJKwCIiiSgBi4gkogQsIpKIErCISCJKwCIiiSgBi4gkogQsIpKIErCISCJKwCIiiSgBi4gkogQsIpKIErCISCJKwCIiiSgBi4gkogQsIpKIErCISCKNSsBm1sPMHjGz981sspntZma9zOxZM5sSH3u2drAiIvmksRXwzcDTIYRtgS8Dk4FLgOdDCFsBz8fnIiLSSA0mYDPrDuwN3AUQQigPISwCjgDujpvdDRzZWkGKiOSjxlTAmwPzgD+a2UQzu9PMOgN9QwifxW3mAH3r+2YzO9XMxpvZ+Hnz5rVM1CIieaAxCbgI2AW4PYSwM7CcOs0NIYQAhPq+OYRwRwhheAhheJ8+fZobr4hI3mhMAp4FzAohjIvPH8ET8udm1g8gPs5tnRBFRPJTgwk4hDAHmGlm28RVo4D3gL8Bo+O60cATrRKhiEieKmrkdmcD95lZCTAN+A6evB8ys5OBGcCxrROiiEh+alQCDiG8BQyv56VRLRuOiEj7oTvhREQSUQIWEUlECVhEJBElYBGRRJSARUQSUQIWEUlECVhEJBElYBGRRJSARUQSUQIWEUlECVhEJBElYBGRRJSARUQSUQIWEUlECVhEJBElYBGRRJSARUQSUQIWEUlECVhEJBElYBGRRJSARUQSUQIWEUlECVhEJBElYBGRRJSARUQSUQIWEUlECVhEJBElYBGRRJSARUQSUQIWEUmkUQnYzM43s3fNbJKZPWBmpWa2uZmNM7OpZvagmZW0drAiIvmkwQRsZgOAc4DhIYQdgELgOOBa4MYQwpbAQuDk1gxURCTfNLYJogjoaGZFQCfgM2A/4JH4+t3AkS0fnohI/mowAYcQZgPXA5/giXcxMAFYFEKojJvNAgbU9/1mdqqZjTez8fPmzWuZqEVE8kBjmiB6AkcAmwP9gc7AwY09QAjhjhDC8BDC8D59+mx0oCIi+aYxTRD7Ax+HEOaFECqAvwJ7AD1ikwTAQGB2K8UoIpKXGpOAPwFGmlknMzNgFPAe8AJwdNxmNPBE64QoIpKfGtMGPA6/2PYm8E78njuAi4EfmNlUYBPgrlaMU0Qk7xQ1vAmEEH4G/KzO6mnAV1s8IhGRdkJ3womIJKIELCKSiBKwiEgiSsAiIokoAYuIJKIELCKSiBKwiEgiSsAiIokoAYuIJKIELCKSiBKwiEgiSsAiIokoAYuIJKIELCKSiBKwiEgiSsAiIokoAYuIJKIELCKSiBKwiEgiSsAiIokoAYuIJKIELCKSiBKwiEgiSsAiIokoAYuIJKIELCKSiBKwiEgiSsAiIokoAYuIJKIELCKSiBKwiEgiSsAiIokoAbczI0fCueemjkJEACyE0HYHM5sHzGizA0pTDAkh9EkdhEh70qYJWEREaqgJQkQkESVgEZFElIBFRBJRAhYRSUQJWEQkESVgEZFElIBFRBJRAhYRSUQJWEQkESVgEZFElIBFRBJRAhYRSUQJWEQkESVgEZFElIBFRBJRAhYRSUQJWEQkESVgEZFElIBFRBJRAhYRSUQJWEQkESVgEZFE/h/c57DeUKuRMAAAAABJRU5ErkJggg==\n", 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\n", "text/plain": [ "<Figure size 360x360 with 3 Axes>" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], "source": [ - "#%% Example with Frobenius norm + entropic regularization with gcg\n", - "\n", - "\n", "def f(G):\n", " return 0.5 * np.sum(G**2)\n", "\n", @@ -724,7 +635,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.5" + "version": "3.6.9" } }, "nbformat": 4, |