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FIX: styling of figure 15.
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albop committed Mar 30, 2018
1 parent 3c13378 commit 4e50b0e
Showing 1 changed file with 2 additions and 2 deletions.
4 changes: 2 additions & 2 deletions generate_graphs.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -116,7 +116,7 @@
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ZK9Fr8YwxVNfZKa+po6LGxvYN33DZxQO8Fl/9oHfv3vTu3bvFcbSXrFI+NnPmTG644QbA8RlHd5YtW8aCBQtOe76pbc5Uw33MnTvXa3HVmRMRoiMsJMdGkZ4UQ7iXzyiVw7Zt2/j1r3/NL37xC496oDdFu7sp1Yx58+YxZMgQBg4ciM1mY9asWQwePJgBAwZQV1fH7NmzGTp0KP37Ozp7REVFnRajf//+fPzxx4DjzOKXv/wlqampAEydOvWUde+8805GjRrF8uXLeeyxx8jLy+Pjjz+mY8eOLFq0iKqqKu666y4eeughrrvuOux2O3379qV9+/YsXboUi8VCaWkpe/fu5cknn+SKK67gtttuo7i4mISEBDZu3EifPn348ssvGTduHA899BA9e/aka9eu1NbWUlBQQFlZGbfffjs5OTmNfxWlQsrzzz/PgAEDsNlsJ8eHPlt6hqmUH1x33XUsWrSI2tpaDh8+TFRUFPfeey+bNm06bd3w8HBuueUWcnNzMcbQr18/fvSjHzFnzhzS0tJIS0tj+/btdOrUiUmTJjFhwgTee+89Zs+ezaRJk/jkk0/o1KkT8fHxHDp0iJycHKZNm8aBAwfIzMzk4osvpk8fR2/FjRs3kpuby4wZM1i+fDkAV199NVOmTOHbbxtfMVcq9GRlZVFWVobVauXyyy9vUSw9w1SqGRMmTDjZscVisZxyRhgeHn7KsquzyxPuvfdexo4dywsvvEB1dTXPP/88ubm5p613YlShE5+LBHj//feZMGECixYtokePHmRlZZ38jGVkZCSRkZHU1dXRoUMHrrjiCoqKikhOTiY5OfmUz02mpKQwf/58Mp29B3Nzc5k9ezZPPfUUY8aMoaam5uT6J/atVCi7916XwwSfHU8mzWzJI5QnXQ31SVGDZdJVXz980cby8vJOfl9WVub1+A2FcvyGsRu+Zt4SLG3MhPixzNfxQzl3YzxvZ3qGqZRqE9yMLnUTjgHYdxnHJwKUckvvYSrlhidD1CmHEHmtbsYxW8kCHPNhAkx2ftUuqqpZeoaplAsJCQls3boVwG3PV28J5fgNYyckJPhkH17WePSoSGPMEyLyCjCv8cqtZdQyX8cP5dzPhBZMpVzo3LkznTt3BhyfXRw0aJDP9hXK8X2du5e5mg9zsYg8DBx0tYHR+TADHtsf8T2lBVMp1SYY16NLPRWIXFRo0nuYSimllAdCsmCuWrWKgoKCU54rKChg1apVAcpIKaVUaxeSBbNbt27Mnz//ZNEsKChg/vz5dOvWLcCZKaWUaq1C5h5mdZ2NbYeOs+VgGfkHq9jTLofX3n6X0shkunz5Nddcd/3JGeKVUkopbwuJgrlpXym3zlzD4fIaACKtYWR2jiU2PpVOJdv5tq4rb7y1laGpxVyZ24VJI1KJsIbkybNSSqkgFfQFc9X2Yn729lri20Xwtx8Pom/XDqQlxrBn9y7mz/+KxJ49iThUxMjefVi2v57HPspj3tq9PHnjAHK6xQU6faWUUq1EUBfMjzfs54G56+iV1J63bhtOlzjHB6RP3LMcP348u3fv5qIxY5g/fz4vjh/P9qp2PPLhRq752yruviiDuy/K0LPNIORmmLIHATuOD5W/DjwHbAFqjDHPByxZpZQiiDv9vLV6F/e++x8GpXRk3h2jThZLgP379zN+/PiT9yzT09MZP348+/fv57J+nfn0gQu4+pxuPPfZNq55YRWbD5QF6tdQ7rkapizFGPMskAbUAwk4xvkscLG9Ukr5VVCeYb62cie//+dmLuvXmb/ePIiocMspPz/vvPNO2yY9Pf1kAY1vF8EzNw3k/+V25ZEPN3L9i6t5efIQLszq5Jf8lccaD1PW8Gsy8L4x5h0ReQH4qOGGOmRZcMQPliHLlPKHoCuYReXVPPmvfC7t25mXJg3Gajn7k+DL+nXmnJQ4pr6xhtvfWsOTN57DNQO7ezFb1QKuhikrFJH7gV1AJTBWRHoB3zXeWIcsC474wTJkmVL+EHQF84XPt1NvM/z6qr4tKpYnJMdGMeeOkfz0rbXcP3cdxypqmXqefvwk0NwMU/ZMo+XJKKVUkGi2IolIlojMFJFrGzz3lIjcLyI3ejOZwqOV/OObPUwYlkJaUozX4naICuet24ZzWd/O/PajPJ7+Vz6OOUOVUm2FiAwWkd+LyNMiEuN87lXnsWxsoPNTwa/ZgmmM2QrMbPT0ISAKiPRmMs/+exthItx3caY3wwIQFW7hxUmDmTgshec/387vPs7ToqlU2+Kqo9lBIBawuNlGqZPO6pKsMeYvACLyjIjMNcbUNfz52XTI2HfczgffVTE2LZwt//mKLR7mcqadDsYmGI6mWnlz1S6OHtzHdZkRXot9pkI9vlIh6JQOZsaYRwGcHcs+abyydi4LfGx/xPdUswVTRLoA44FoEYkDlgCXAylAbeNiCWfXIePOWd8SE1nHHyePISHGfRFr7Gw6HYwZY3jo/Y3MXVtIbp8Mbj+/l9din4lQj69UiHHV0exuHB9f2uNqA+1cFvjY/ojvqWYLpjHmIHBPo6ff9mYS6wtLWPz9Qe6/NPOMiuXZEhH+eH0ux2vq+f0/NxMbZeWmYT19vl+lVOC46Wj210DkokJTUPSSffJf+XRsF8600f7rvWoJE565aSDHa+p56IONxERa+dEAne1EKaWUawEf6efrnUdYua2Yuy/KIDYq3K/7jrCG8fJPhjA0tSMPzF3Hym2H/bp/pZRSoSPgBfP97/YSG2nlJyNTA7L/6AgLr08dRu9O7bnrne90GD2llFIuBbRg2uyGzzYXMaZP8mnD3/lTh6hw3rx1GO0jrdz65hoOlFYFLBellFLBKaAFc13hMY5U1HJZv86BTAOArnHRvDF1GMdr6rn1zTWUV5/W+VcppVQbFtCC+a+8Q1jDJGgGRe/XrQMvThrMtqLj/Hz2d9TbdWADpZRSDgEtmJ/mHWJkr0Tiov3b2acpF2R14k/X5bJyWzFv59XqaEBKKaWAABbMHYePs/NwRVBcjm1swrAU7r04gxV763lp+Y5Ap6OUUioIBKxgfpp3CIBLg7BgAjx4WRYju1r4y+J8Ptl4INDpKKWUCrCADVzw77xD5HTrQPf46ECl0CQR4bb+kdSGR/DA3HV0i49mYEp8oNNSSikVIAE5wyw+XsO3e45xad/gPLs8IcIivDplKMkdIrn9rbXsK9GPmyilVFsVkIL5+eYijCEo7182ltg+kjduGUZNvY1pM/XjJt7iZm7CB51zE053Lv+X87mRgc1WtQZu2pyIyJMicn+g81PBLyAF8195h+geH01Otw6B2P0Zy+wcy0uThrCt6Dj3/OM/1NvsgU6pNXA1N2GKMeZZIE1EcoDBQASg71KUN7hqc3cD8wOVkAotfr+HWVVr44vth7lpaAoi4u/dn7XRmUn8/tr+PPzBRh77KI/fXZMTUvkHKdPE13Cg0BjzuIi8gnNOwhN0nsLgiB8s8xSegZNtTEQSgEwgGcgVkZeMMTUNV9Z2FvjY/ojvKb8XzC+2F1NdZ+eyfl38vesWu3l4T3YVV/D3FTtJS4rx6+wqrZCruQkLnZfGdgEbgNtE5NfAqsYb6zyFwRE/WOYp9NApbQ4oMcZMF5E04NrGxRK0nQVDbH/E95TfC+aneQeJjbQyPD3B37v2iv++og+7j1Ty+3/mkdIxmstzQq/wBwM3cxM+02j5Pj+lo9oAN20OY8wu4Fm/J6RCjl/vYTYcbD3CGvCJUs5KmHMezQHd45g+Zx0b95YGOiWllFJ+4Neqlbe/jCMVtVzaN9mfu/W66AgLr94ylISYCG57a41+3EQppdoAvxbM9XtLABjcs6M/d+sTybFRvDF1GNW1Nm598xtKq7Qjp1JKtWZ+LZib9pUSFx1Oj47BObrPmcruEsvLk4dQUFzBHbPWUlNvC3RKSimlfMS/BXN/Kbnd41rVxzHOy0jiifHn8NXOo/zivQ3YdUowpZRqlZotmCKSJSIzReTaBs/dIiIzROR/PN1RTb2N/IPl9O8ed7a5Bq1rB3Xnv67I5qP1+/nz4i2BTkcppZQPNFswjTFbgZmNnh5ojHkKQEQ8GpF868Hj1NkMua2wYALcdWFvJo9M5e8rdjJzVUGg01FKKeVlLf0cpsvrj65Gx1hW6OgUU7F3M8uO5rdwtz8IptErLoozbEq28NhHeRQV7mB4l6Zf3rYyOoZSSrUGzRZMEekCjAeiRSQOWAKsE5EZAMaYksbbuBodY8kHG+kQtZ8br7zIq/cwg230ilHn2Zj8+te8urGEkYPP4YKsTl6NfyaCZXQMpZRqDZotmMaYg8A9jZ5+60x3tGlfKf1bWYcfV6IjLLw+dRg3/f1L7pj1Le/cPoIhqaH/MRqllGrr/NJLtrbeTv7B8lZ7/7KxuOhw3p42nOQOkdw2cw35B8sDnZJSSqkW8kvB3HqonFqbvVX2kHUnOTaKd6aNICo8jMmvf82eI5WBTkmpNs3NfJjjnfOuPhro/FTw80vB3LjPMd5qWznDPCEloR2zpo2g1mbnJ69/zYFSHUJPqQByNR/mZ0ACYAlQTiqE+GW2ko37SomNspKa2M4fuwsqWZ1jmXnrcH7y2tf8+NWvmfOzkXTuEBXotJRqq06Ze9UYcwx4SEQedrWyzocZ+Nj+iO8pvxTMTftK6d+t9Xf4cWdgSjxv3TaMKa9/w82vfsWcn44kWYumUv7mag7WGTjOLl2O16nzYQY+tj/ie8rnBdMAWw6UM/W8NF/vKqgNSU1g5m3DueUNZ9H82ahAp6RUm+JmPswnApGLCk0+v4dZZ6PNdfhxZ1haAm9OHcb+kmp+/OpXlNW03XFn3XTAeFBE7heR6c7lJBFZIiIDA5utUkr5oWDWOAcjb2sdftwZ0SuRN6YOo/BYJY+vqeJQWXWgUwoUVx0wUowxzwJpIhIO3AHMC0x6Sil1Kp9fkq2th8RIK6kJba/Djzujeify5tTh3PrGV9z48pfMvn0EKW3z9TFNfD0XCAcuARKBdQ031M4YwRE/WDpjKOUPvi+YdkNO9w6EhbXNDj/ujOqdyH8Ni+K59XWMf3k1s28fQUZybKDT8idXHTAKReR+YJcxZjmwXESm0qhYgnbGCJb4wdIZQyl/8H3BtOnlWHd6xVuYe8cwfvLaN0z4+1e8fdvwNnOv100HjGdcrDfTLwkppVQzfH4P00CbKQJno0+XDrx35yiiwy3c/MpXfL3zSKBTUkop5YJfRvrRM8ympSfF8N6do+jUIZLJr3/D/63bF+iUlFJKNeLzgilAWmKMr3cT8rrFR/PBXecysGc80+es44Wl2zGm7X7sRCmlgo3PC2akBe3w46H4dhHMmjacawZ244kl+Tz8wUbqbPZAp6WUUgo/dPqJsGixPBORVgvP3jSQngnt+Ovn29lXUsULkwbTISo80KkppVSb5vMzzPhILZhnSkSYcXk2f7lhAF/uOMK1f1vFtkM6p6ZSSgWSzwumXo09exOGpfCPn46krLqOa19YxaKNBwKdklIhy81wjD8XkUdF5LFA56eCn196yaqzNzw9gY/vPZ/MzrHcNfs7/rJ4Cza7dgZS6iycNhyjMeZF4M9Al8ClpUKFX6b3Ui3TJS6KuXeM5LcL83hx2Q427ivl6QkD6RQbGejUlAo1pwzDKCJRwB+AP7paWYdgDHxsf8T3lBbMEBFptfCn63MZ0COO3yz8niufW8lTE87hwqxOgU5NqVDhajjGucD3wOXAq4030CEYAx/bH/E9pQUzxNw8vCeDe3bk3ne/45Y3vuH20en88opsIq2WQKemVFBzMxzjNYHIRYWmZu9hurlR/qpz3sKxvk9RNZbdJZaF94xmyqhUXvuigOtfXM32ouOBTksppVo1Tzr9uJq38CAQC+hpTYBEhVv43TX9eXXKUPaXVHHV8yt5efkO6nWgA6WU8glPL8mecqPcGPMogIi8AHzSeOXWcqM8FG5khwO/GW5l1mY7jy/awpxVW5mWG0lKbFjQ3ChXSqnWwJOC6epG+d1AArDH1Qat5UZ5KN3Ivmas4ZONB/mf/9vEY19W8/OLMshtty8obpQrpVRr0GzBdHOj/K++SUedLRHhqgFdGdU7kd999D3Pf7aNLu0Ea/ciLsp7oNQrAAAKnElEQVRODnR6SikV8nTgglYmISaCZycOYuatwwC49c01TJu5hl3FFQHO7FRuOpM96OxMNl1E2ovIr0TkSREZH+h8lVJKC2YrNSY7md+PjubhK/vw1c4jXP7MCv6yeAvl1XWBTu0EV53JUowxzwJpxpjjxpg/AC8A/QKTolJK/UA/h9mKWcOEOy7szXWDuvP44i28uGwH736zh5+PyWDyqFSiwgPeydk09VVE0oB7gF813rC1dCwL9fjasUy1JVow24DkDlE8PWEgU89N44kl+fzhk828/kUB912SyY1DexBuCciFBledyQpF5H5gl4jEAR8Cs4GLgEUNN24tHctCPX6wjMCilD9owWxDBvSIZ9a0EXy54whPLNnCIx9u5O8rdnDnhb25fnB3v44W5KYz2TONlgf5KR2llGqW3sNsg0b1TuT9u87ltSlD6RAVzsMfbOT8Py/l78t3BNM9TqW8yk1HswkisizAqakQoQWzjRIRLu3XmYX3nMfs20eQ1TmWPy3awnmPf87ji7aw91hloFNUyttcTe81D1gXwJxUCNFLsm2ciHBeRhLnZSSxYW8JLy/fwSsrHI+L+3RmyqhURmckEaYzgavWoXEHsyZp57LAx/ZHfE9pwVQnDegRz4uThrCvpIp/fL2bOd8U8u/Nh0hPiuGBy7IYd063QKeoVEu46mg2BhgkIj81xuj0XkEY2x/xPaUFU52me3w0vxzbh/suyWTRxoO8/eUuKmrqA52WUi3ipqPZ586HUs3SgqncirRauHZQd64d1B1jPLqCpZRSrZZ2+lEeEWmb9zCNMdj1zYJSCi2YSjXpz4vzeWRlFbX1Os+oUm2dFkyl3CiprOWt1bs4WGn458b9gU5HKRVgWjCVcmP213uoqrMRHym8trJA7+Mq1cZpwVTKhdp6O2+t3sX5mUlcmxHO9/vL+HLnkUCnpZQKIC2YSrmwcP1+ispruP38XpzbzUpiTASvrSwIdFpKqQDSgqlUI8YYXlu5k+zOsVyQmUSERZg8KpXPtxSxvag80OkppQJEC6ZSjXyxvZgtB8uZdn76yY/TTB6ZSqQ1jNe/0LNMpdoqLZhKNfLqygI6xUZyzcAfhgJMbB/J9YN78P53+yg+XhPA7JRSgaIFU6kG8g+Ws2LrYW4ZlXra/KDTRqdTW2/nna92Byg7pVQgNTs0nogMBq7HMWDxo8aYChF5ELADxhjznI9zVK1Qc+0K+CvwF+AYsNYYs8Qfeb22cidR4WFMGpF62s8ykttzSZ9kZn25mzsv7E1UuP8m3FYtp8cy1VKejCV7M/AwcC6OOeQWACnGmAdE5BlfJqdateba1TnABmPM285ltwWzrKKSP89eTERyL4zdTmXeUsI79yKiUzrGVk/l5uVEdMkgPCkVU19L5ZaVRHTNIjwxBXtdDVX5XxDRrQ/Wjt1Ysm4XEzvu5ciBTDpmZFBaWsq6devo2bMnvXr14scDEwnfuYJH3xF6pKRSX1lK1Y41RPYcgLVDJ2wVJVQXfEtU6kAssYnYKo5RXfAdUemDscR0xFZ+hOrd64hKH4IlJp76ssOUbv0Pa8vaY4nuQH1pETWFG4nOGEFYVHvqSw5Ss/d7ojNHEhYZQ/2x/dTs20x01rmERURTd3Qftfu3EJ09mrDwSOqOFFJ7YCvt+pyPWCOoK95N2a5NfFedjFis1B4uoO7QTtr1uwgJC6O2aCd1RQXE9L8EgNpD26kr3kNMzsWO5QPbqDu2j5h+YwCo2Z+PrfQQ7fpeAMDBTbtYtfF12vU53/HzvXnYKo7RLvs8x3LhJuxVZURnnQtA9Z4NmJpKojNHOpZ3r8PU1xLdezgAt41OJy463FttrDE9lqkW8XTw9cZzyDU5p1xrmUMu1Od4C5Y55JrQXLty284atrGkrj34NO8Q2zfaEOyMjahka/EhdtrqsWDjsohK8osPUmCrJZx6LomoZPPhA+y2VxNJHRdFVPL94f0U2ivpaDXEhNWxYcMG9u7dS3V1NTabjfXr17Nnzx5qKitpZxVWbCvmUH4NHaSac8Mr+e7wXorsJcRLFSPDK1lbVEixOUqCVDI8vJJvivZw1BSTJBUMDa/kq6I9lJjDJIcdZ7DVzsIvd1NmougcVs4gayVfrN7FcRNJ17AyzrFWsnLVLipMBN3DSsm1VrJ8ZQFVhJMSVkKOtZKlK3ZQQzipYcfoa63ks+U7qMNKuuUo2RY77y7bjg0LvSxHyLJUsmTpNgxhZFiKybBUsvizbQBkWQ6TbqlkiXO5j6WIFEsFnzqX+1kO09VynM+cy/2tNjqFHWfpPsdyrrWYBKlk+V7H8jnWI8RJNSsKHcuDrEeJkVq+2ONYHmI9RqTUs3qXYzmlfi9J0T69U9Qmj2W+jh/KuZ8RY0yTD2AI8L/AU8A9OO57PgDcD9zX3PZZWVnGl5YuXRqSsVtDfByXSpttQ64ezbUr5/ITOM4Irmgqlr/bmN1uN/U2x8Nmsxu73e7V+N4Wyv8jLWljjR9t+Vjm6/ihnLsxnrezZs8wjes55PTyhWoRD9vVL/2UzhkRESxtc/KWkKbHMtVS2ktWKaWU8oAWTKWUUsoDWjCVUkopD2jBVEoppTygBVMppZTygBZMpZRSygNaMJVSSikPaMFUSimlPCCOQQ58uAORciDfh7tIAopDMHZriJ9tjIn1YXyPhHgbC/X4baKNgbazAMb2R3yP2pmnY8m2RL4xZqivgovIWl/F92Xs1hLfV7HPUMi2sVCP34baGGg7C0hsf8X3ZD29JKuUUkp5QAumUkop5QF/FMxXQjh+KOfeGuJ7KtR/z1COH8q5n6lQ/121HbQwvs87/SillFKtgV6SVUoppTzgs16yIjIYuB5oBzxqjKnwcvxrgYuAAuA546VTZRHJAh4BFgC1wCAgDvhvb+yjUfw0Z+y9xpjXvRD7fOBcoB+wBEjHu7k3jL8eiMVLubcgJ21nTcdOw4ttzBlf25kX21kotjEX8dMIoXZ2tm3Ml2eYNwO/xfFiXuaD+BVAJRCDF38PY8xWYKZz8TJjzB+ATcA5Poh/DDA4fgdvxF5pjPkzsB240Qe5N4wfixdzbwFtZ03H9mobc8bXduZdIdfGXMQPqXZ2tm3M15dkTaOv3gtszKfGmIeBzcCF3o7vapdeD2jMW8aY3wFWEenljZgi8mNgJ7Cr4a68EbthfGPMY97OvQW0nbkL5oM2BtrOvBo0xNsYhGY7O5s25suBC+bgeEfWDviNt4OLyBhgBI7T9F95MW4XYDwQDawQkUdwXAaY5e34IhIHdAO6A3u9EPtGYAqwGFjng9xPxheRW/Bi7i2g7ayJ2N5uY8742s68KBTbWOP4odbOzraNaS9ZpZRSygPaS1YppZTygBZMpZRSygNaMJVSSikPaMFUSimlPKAFUymllPKAFkyllFLKA1owvURELCJyX6DzUK2btjPla9rG3NOC6T03Ab1FxCvDTinlhrYz5Wvaxtzw5Ug/bU0M8LwxZkegE1GtmrYz5WvaxtzQM0zvEXwz+LdSDWk7U76mbcwNHRpPKaWU8oCeYSqllFIe0IKplFJKeUALplJKKeUBLZhKKaWUB7RgKqWUUh7QgqmUUkp5QAumUkop5QEtmEoppZQH/j+MGbf88GZRzQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f2c3ff7c400>"
"<matplotlib.figure.Figure at 0x7f6a7f640f28>"
]
},
"metadata": {},
Expand Down Expand Up @@ -1569,7 +1569,7 @@
"# plt.plot(dfs['E_gamma'], linestyle=linestyles[0])\n",
"plt.plot(df0['Gamma'], linestyle=linestyles[0])\n",
"plt.plot(tvec*dfs['Gamma'], linestyle=linestyles[1])\n",
"plt.plot(tvec*dfs['Gamma_s'], linestyle=linestyles[1])\n",
"plt.plot(tvec*dfs['Gamma_s'], linestyle=linestyles[2])\n",
"# plt.plot(dfs['Gamma_s'], linestyle=linestyles[2])\n",
"\n",
"plt.grid()\n",
Expand Down

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