marchwicka/signature_function
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity
be469ccc2f
signature_function/notebooks/main.ipynb

3682 lines
515 KiB
Plaintext
Raw Normal View History

add jupyter notebook
2020-11-09 09:34:33 +01:00
{
"cells": [
{
"cell_type": "code",
plots
2020-11-19 10:32:15 +01:00
"execution_count": 1,
add jupyter notebook
2020-11-09 09:34:33 +01:00
"metadata": {},
plots
2020-11-19 10:32:15 +01:00
"outputs": [],
add jupyter notebook
2020-11-09 09:34:33 +01:00
"source": [
"%matplotlib inline\n",
"%load_ext pycodestyle_magic\n",
"\n",
"\n",
"# display full output, not only last result, except ended with semicolon\n",
"from IPython.core.interactiveshell import InteractiveShell\n",
"InteractiveShell.ast_node_interactivity = 'all';\n",
"from IPython.display import Image, SVG\n",
"\n",
"\n",
"# magic functions that do not work in current ipython --version\n",
"# \n",
"# auto check each cell, E703 - \"statement ends with a semicolon\"\n",
"# %flake8_on --ignore E703\n"
]
},
{
"cell_type": "code",
plots
2020-11-19 10:32:15 +01:00
"execution_count": 2,
add jupyter notebook
2020-11-09 09:34:33 +01:00
"metadata": {},
"outputs": [],
"source": [
"import importlib\n",
"\n",
"def import_sage(module_name):\n",
" \n",
" importlib.invalidate_caches() \n",
" sage_name = module_name + \".sage\"\n",
" python_name = module_name + \".sage.py\"\n",
"\n",
" if os.path.isfile(sage_name):\n",
" os.system('sage --preparse {}'.format(sage_name));\n",
" os.system('mv {} {}.py'.format(python_name, module_name))\n",
" if module_name in sys.modules:\n",
" return importlib.reload(sys.modules[module_name]) \n",
" return importlib.import_module(module_name, package=None)\n",
"\n",
"cs = import_sage('cable_signature')\n",
"# sig = import_sage('signature')"
]
},
verbose option added
2020-11-19 06:47:52 +01:00
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Other cables"
]
},
{
"cell_type": "code",
plots
2020-11-19 10:32:15 +01:00
"execution_count": 3,
verbose option added
2020-11-19 06:47:52 +01:00
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"\n",
"\n",
"\n",
"########## T(2, 7; 2, 11) ##########\n",
"\n"
]
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
verbose option added
2020-11-19 06:47:52 +01:00
"T(2, 7; 2, 11), theta = 1\n",
"pp = -101/11, satellite_part = -4\n",
plots
2020-11-19 10:32:15 +01:00
"\n",
"sigma(T(2, 7; 2, 11)) = -145/11\n",
"\n",
"\n",
"\n",
"########## -T(2, 3; 2, 7; 2, 11) ##########\n",
"\n"
]
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
verbose option added
2020-11-19 06:47:52 +01:00
"-T(2, 3; 2, 7; 2, 11), theta = 1\n",
plots
2020-11-19 10:32:15 +01:00
"pp = 101/11, satellite_part = 8\n",
"\n",
"sigma(-T(2, 3; 2, 7; 2, 11)) = 189/11\n",
"****************************************************************************************************\n",
"Calculation summary for a cable sum:\n",
"T(2, 3; 2, 5; 2, 11) # -T(2, 5; 2, 11) # T(2, 7; 2, 11) # -T(2, 3; 2, 7; 2, 11)\n",
"2. T(2, 7; 2, 11)\n",
"Pattern part = -101/11\n",
"Satellite part = -4\n",
"Sigma = -145/11\n",
"\n",
"3. -T(2, 3; 2, 7; 2, 11)\n",
"Pattern part = 101/11\n",
"Satellite part = 8\n",
"Sigma = 189/11\n",
"\n",
verbose option added
2020-11-19 06:47:52 +01:00
"**********\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 1, 1] 4\n",
"\n",
"\n",
"\n",
"########## T(2, 7; 2, 11) ##########\n",
"\n"
]
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAEICAYAAABRSj9aAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/Il7ecAAAACXBIWXMAAAsTAAALEwEAmpwYAAAfx0lEQVR4nO3de3RU5b3/8fcXEhCQi7coihD0h8g9SADxguAVtJXW29EKQpVS2p+XrnMKhSKVHkUrWLuOrvqrVhGlqMULwvJW8bQcaxEkHAOCgogGBaUmKEEkkNv398ce0iHXSWYyk+x8XmvNYmb2fvbznWHmMzvPfmaPuTsiIhJerVJdgIiINC4FvYhIyCnoRURCTkEvIhJyCnoRkZBT0IuIhJyCvhkys75mlmNmlupaUsXMfmtmP6nH+pPM7K3GrCkVzCzTzNzM0lJdizRdCvomxsz2RV3Kzawo6vb1kdXuBO5zdzeztmb2mJltN7NvzCzXzMbWo79XK/VZbGbvxdj2NDNbZmb5ZvaVmf3FzHrXo++bIx9YB81sYaVlbczsOTPLiwTZqErN7wN+aWZtYu2vqTCzR8xsS+T/d1I92+aZ2YUJqiMlHxLxvm6k/hT0TYy7H3noAnwKfDfqvsVm1hUYDbwYaZIGfAacB3QGbgeWmFlmjP2NrdTnKuDZGMvtAiwHegPHA+8Ay2JsC/A5cBewoIblbwHjgV3V1P0FsBm4vB79JVUtAboe+Cnwv0kspynpQnyvG6kvd9eliV6APODCSvfdALxRR7sNwJUN6C8TKAMyo+57CZgRY/ujAQeOqWe/dwELa1m+AxhVzf2zgMdj7GMS8FbU7f8i+IDcC6wDzo3cfwKwP/oxAGcA+UB65PaNwAfA18BfgB5R6zrwf4GtwCd11PQWMKkez9MioBwoAvYB0yP/Zw5MJNgxKABmRbVpBcwAtgG7gSXA0ZFln0ba7otcRgCnAn+NrFsALAa6NPLrvEGvG11iv2iPvvkZAGypaaGZHQ+cBmxqwLZvAP7u7nmH7nD377j7b2JsPxLY5e67G9B3Q3wADGpg27VAFkHIPAU8a2ZHuPsuYCVwTdS6E4Bn3L3EzMYBvwSuAI4D/g48XWnb3wOGA30bWFu13H0Ch/+VNy9q8TkEe8gXAL8ysz6R+2+J1HMecCLBh9PvI8tGRv7tEtne24AB90TW7QOcDMypqSYz22Bme2q4PBTjQ0v266bFUdA3P12Ab6pbYGbpBHtgT7j75gZs+wZgYUOKMrNuBAHy7w1p30DfEDwf9ebuf3L33e5e6u6/BdoSBCXAEwRDRphZa+A6gr1pgKnAPe7+gbuXAncDWWbWI2rz97j7V+5e1JDaGujX7l7k7usJhoYOfQBOJdjD3+HuBwlC+6qahpXc/SN3X+HuB909H7if4EOiWu4+0N271HD5aV1Fp+h10+Io6Jufr4GOle80s1YEYVQM3FzfjZrZOQTDFs81oO1xwOvAQ+5eee+2MXUE9jSkoZn93Mw+MLNCM9tDcHzj2MjiZUBfM+sJXAQUuvs7kWU9gP86tNcKfEWwF3xS1OY/a0hNcYo+jrEfODJyvQewNKreDwiG546vbiNmdryZPWNmO81sL/An/vW8JFQKXzctjoK++dlAMDRTITLN8jGCN++V7l7SgO1OBF5w9331aWRmRxG8WZe7+9wG9BuPPgR7r/ViZucSjG9fAxzl7l2AQoLAxt0PEIxljycYtlkU1fwz4MeV9lzbufuqqHUa85Sw9d32Z8DYSvUe4e47a9jW3ZH7B7h7J4LnoMZpvGa2qdKsrejLH2ppl8rXTYujoG9+VgBnmNkRUff9P4LQ+251wwU1TE+MXt6OIPQWVrNspZnNqaFdJ4KDkf9w9xnVLB9lZjUGk5mlRR5Ha6C1mR0RPaQQmTp66HG2iSyPDp3zgFdjqbWSjkApwQHWNDP7FdCp0jpPEhzAvZzDg/4PwEwz6xfps7OZXR1DnxUiU0ePIAjQ9MjjahVZVutzBvwTOKUe3f0BmHtoaMnMjoscZ4Dg8ZdX2l5HggOzhWZ2EjCtto27ez+PmrVV6TK1ujZ1vW6kEaT6aLAuNV+oZtZN5P5ngX+LXO9BsAd2gH/NntgHXB9ZfjLBzJIaZzQQjEFvB6yaZduAi2poNzHS97eV+u4eWT6B4M1cU79zIu2jL3MqPf7KyzMjy7oSzMZpE2Otk4jMuiH4YFkQeV6+INi7r/JcE8yc+Z9qtjUBeC/S/jNgQdQyB/5PHf+vK6t5XKNifM7GERyQ3QP8nH/NukmrtP3JkeutCMa/txAc09gG3B217n8SBP4e4EygH8EspH1ALvAfwI4Ev65rfd3okviLRZ54aUbMrC/BAcNhXsd/oJmNB/q5+8wG9NMNWOLuZzWwzkeBZ939Lw1pX8e2fwtsc/eHIrfjqrWGPv4KPOXujyZqmzH02WjPmbRcCnqRapjZUIJhspPdvdpZTiLNhcboRSoxsyeAN4CfKeQlDLRHLyISctqjFxEJuZSc2vTYY4/1zMzMVHQtItJsrVu3rsDdj6tvu5QEfWZmJjk5OanoWkSk2TKz7Q1pp6EbEZGQU9CLiIScgl5EJOQU9CIiIaegFxEJuYQEvZmNifzY8UdmprPRiYg0IXEHfeQXeH4PjCX46bTrIifdEhGRJiAR8+iHAR+5+8cAZvYMwalU30/AtpukUaPi38bKlfFvQ6Ql0fuu4RIxdHMSh/902g4O/1k1AMxsipnlmFlOfn5+AroVEZFYJO2bse7+CPAIQHZ2drM+k1pL3SsQSSW97xouEXv0Owl+xeiQbpH7RESkCUhE0K8FeplZTzNrA1wLLE/AdkVEJAHiHrpx91Izu5ngx35bE/x+5qa4KxMRkYRIyBi9u78CvJKIbYmISGLpm7EiIiGnoBcRCTkFvYhIyCnoRURCTkEvIhJyCnoRkZBT0IuIhJyCXkQk5BT0IiIhp6AXEQk5Bb2ISMgp6EVEQk5BLyIScgp6EZGQU9CLiIScgl5EJOQU9CIiIaegFxEJOQW9iEjIKehFREJOQS8iEnIKehGRkFPQi4iEnIJeRCTk4gp6M7vazDaZWbmZZSeqKBERSZx49+g3AlcAbyagFhERaQRp8TR29w8AzCwx1YiISMIlbYzezKaYWY6Z5eTn5yerWxGRFq/OPXozewM4oZpFs9x9WawdufsjwCMA2dnZHnOFIiISlzqD3t0vTEYhIiLSODS9UkQk5OKdXvl9M9sBjABeNrO/JKYsERFJlHhn3SwFliaoFhERaQQauhERCTkFvYhIyCnoRURCTkEvIhJyCnoRkZBT0IuIhJyCXkQk5BT0IiIhp6AXEQk5Bb2ISMgp6EVEQk5BLyIScgp6EZGQU9CLiIScgl5EJOQU9CIiIaegFxEJOQW9iEjIKehFREJOQS8iEnIKehGRkFPQi4iEnIJeRCTkFPRyGHcnLy+Pp59+mrvuugt3T3VJIhKntHgam9l84LtAMbAN+KG770lAXZJExcXFrF+/njfffJMVK1bw1VdfceDAAU444QRuv/32VJcnInGKK+iBFcBMdy81s3uBmcAv4i9LGltBQQFr165lxYoVvP3227g7ZWVldO7cmYyMDPbs2UPv3r1TXaaIJEBcQe/ur0fdXA1cFV85LceoUcntz72coqKtFBau4uuv/0JR0TbMjP790+jSpQtpaYe/FIqKihg4cGByi5QmKdmv1ZqsXJnqCpqvePfoo90I/LmmhWY2BZgC0L179wR2K7HYvv3X5Oc/R6tW7Wjd+kjS04/HzDjmmOrXT0tLo1evXsktUkQahdV1sM3M3gBOqGbRLHdfFllnFpANXOExHL3Lzs72nJycBpQrDbVr1y5mzpzJhg0byMjIqLIHX9nOnTsZPnw4w4YNo1evXvTo0YMTTzyR1q1bJ6liEanMzNa5e3a928U7q8LMJgE/Bi5w9/2xtFHQp0ZpaSkPP/wwjz/+OEceeSQdO3ascd3i4mL27dvHgQMHSE9Pr5h907NnT/r27Uv//v3p2bMnPXr04KijjsLMkvUwRFqslAS9mY0B7gfOc/f8WNsp6FNr9erVzJw
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
verbose option added
2020-11-19 06:47:52 +01:00
"T(2, 7; 2, 11), theta = 2\n",
"pp = -85/11, satellite_part = -4\n",
"\n",
plots
2020-11-19 10:32:15 +01:00
"sigma(T(2, 7; 2, 11)) = -129/11\n",
"\n",
"\n",
"\n",
"########## -T(2, 3; 2, 7; 2, 11) ##########\n",
"\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
},
{
"data": {
plots
2020-11-19 10:32:15 +01:00
"image/png": "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
verbose option added
2020-11-19 06:47:52 +01:00
"text/plain": [
plots
2020-11-19 10:32:15 +01:00
"<Figure size 432x288 with 1 Axes>"
verbose option added
2020-11-19 06:47:52 +01:00
]
},
plots
2020-11-19 10:32:15 +01:00
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
before adding sigma
2020-11-10 17:55:29 +01:00
{
plots
2020-11-19 10:32:15 +01:00
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
before adding sigma
2020-11-10 17:55:29 +01:00
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"-T(2, 3; 2, 7; 2, 11), theta = 2\n",
"pp = 85/11, satellite_part = 8\n",
"\n",
"sigma(-T(2, 3; 2, 7; 2, 11)) = 173/11\n",
"****************************************************************************************************\n",
"Calculation summary for a cable sum:\n",
"T(2, 3; 2, 5; 2, 11) # -T(2, 5; 2, 11) # T(2, 7; 2, 11) # -T(2, 3; 2, 7; 2, 11)\n",
"2. T(2, 7; 2, 11)\n",
"Pattern part = -85/11\n",
"Satellite part = -4\n",
"Sigma = -129/11\n",
"\n",
"3. -T(2, 3; 2, 7; 2, 11)\n",
"Pattern part = 85/11\n",
"Satellite part = 8\n",
"Sigma = 173/11\n",
"\n",
"[0, 0, 2, 2] 4\n",
"\n",
"\n",
"\n",
"########## T(2, 7; 2, 11) ##########\n",
"\n"
before adding sigma
2020-11-10 17:55:29 +01:00
]
plots
2020-11-19 10:32:15 +01:00
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
before adding sigma
2020-11-10 17:55:29 +01:00
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"T(2, 7; 2, 11), theta = 3\n",
"pp = -73/11, satellite_part = -8\n",
"\n",
"sigma(T(2, 7; 2, 11)) = -161/11\n",
"\n",
"\n",
"\n",
"########## -T(2, 3; 2, 7; 2, 11) ##########\n",
"\n"
before adding sigma
2020-11-10 17:55:29 +01:00
]
},
{
"data": {
plots
2020-11-19 10:32:15 +01:00
"image/png": "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
before adding sigma
2020-11-10 17:55:29 +01:00
"text/plain": [
plots
2020-11-19 10:32:15 +01:00
"<Figure size 432x288 with 1 Axes>"
before adding sigma
2020-11-10 17:55:29 +01:00
]
},
plots
2020-11-19 10:32:15 +01:00
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
before adding sigma
2020-11-10 17:55:29 +01:00
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"-T(2, 3; 2, 7; 2, 11), theta = 3\n",
"pp = 73/11, satellite_part = 12\n",
"\n",
"sigma(-T(2, 3; 2, 7; 2, 11)) = 205/11\n",
"****************************************************************************************************\n",
"Calculation summary for a cable sum:\n",
"T(2, 3; 2, 5; 2, 11) # -T(2, 5; 2, 11) # T(2, 7; 2, 11) # -T(2, 3; 2, 7; 2, 11)\n",
"2. T(2, 7; 2, 11)\n",
"Pattern part = -73/11\n",
"Satellite part = -8\n",
"Sigma = -161/11\n",
"\n",
"3. -T(2, 3; 2, 7; 2, 11)\n",
"Pattern part = 73/11\n",
"Satellite part = 12\n",
"Sigma = 205/11\n",
"\n",
"[0, 0, 3, 3] 4\n",
"\n",
"\n",
"\n",
"########## T(2, 7; 2, 11) ##########\n",
"\n"
before adding sigma
2020-11-10 17:55:29 +01:00
]
},
{
"data": {
plots
2020-11-19 10:32:15 +01:00
"image/png": "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
before adding sigma
2020-11-10 17:55:29 +01:00
"text/plain": [
plots
2020-11-19 10:32:15 +01:00
"<Figure size 432x288 with 1 Axes>"
before adding sigma
2020-11-10 17:55:29 +01:00
]
},
plots
2020-11-19 10:32:15 +01:00
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
verbose option added
2020-11-19 06:47:52 +01:00
},
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"T(2, 7; 2, 11), theta = 4\n",
"pp = -65/11, satellite_part = -12\n",
"\n",
"sigma(T(2, 7; 2, 11)) = -197/11\n",
"\n",
"\n",
"\n",
"########## -T(2, 3; 2, 7; 2, 11) ##########\n",
"\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
},
{
"data": {
plots
2020-11-19 10:32:15 +01:00
"image/png": "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
verbose option added
2020-11-19 06:47:52 +01:00
"text/plain": [
plots
2020-11-19 10:32:15 +01:00
"<Figure size 432x288 with 1 Axes>"
verbose option added
2020-11-19 06:47:52 +01:00
]
},
plots
2020-11-19 10:32:15 +01:00
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
before adding sigma
2020-11-10 17:55:29 +01:00
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"-T(2, 3; 2, 7; 2, 11), theta = 4\n",
"pp = 65/11, satellite_part = 16\n",
"\n",
"sigma(-T(2, 3; 2, 7; 2, 11)) = 241/11\n",
"****************************************************************************************************\n",
"Calculation summary for a cable sum:\n",
"T(2, 3; 2, 5; 2, 11) # -T(2, 5; 2, 11) # T(2, 7; 2, 11) # -T(2, 3; 2, 7; 2, 11)\n",
"2. T(2, 7; 2, 11)\n",
"Pattern part = -65/11\n",
"Satellite part = -12\n",
"Sigma = -197/11\n",
"\n",
"3. -T(2, 3; 2, 7; 2, 11)\n",
"Pattern part = 65/11\n",
"Satellite part = 16\n",
"Sigma = 241/11\n",
"\n",
"[0, 0, 4, 4] 4\n",
"\n",
"\n",
"\n",
"########## T(2, 7; 2, 11) ##########\n",
"\n"
before adding sigma
2020-11-10 17:55:29 +01:00
]
plots
2020-11-19 10:32:15 +01:00
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
before adding sigma
2020-11-10 17:55:29 +01:00
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"T(2, 7; 2, 11), theta = 5\n",
"pp = -61/11, satellite_part = -12\n",
"\n",
"sigma(T(2, 7; 2, 11)) = -193/11\n",
"\n",
"\n",
"\n",
"########## -T(2, 3; 2, 7; 2, 11) ##########\n",
"\n"
before adding sigma
2020-11-10 17:55:29 +01:00
]
},
{
"data": {
plots
2020-11-19 10:32:15 +01:00
"image/png": "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
before adding sigma
2020-11-10 17:55:29 +01:00
"text/plain": [
plots
2020-11-19 10:32:15 +01:00
"<Figure size 432x288 with 1 Axes>"
before adding sigma
2020-11-10 17:55:29 +01:00
]
},
plots
2020-11-19 10:32:15 +01:00
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
before adding sigma
2020-11-10 17:55:29 +01:00
{
"data": {
plots
2020-11-19 10:32:15 +01:00
"image/png": "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
before adding sigma
2020-11-10 17:55:29 +01:00
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
plots
2020-11-19 10:32:15 +01:00
},
before adding sigma
2020-11-10 17:55:29 +01:00
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"-T(2, 3; 2, 7; 2, 11), theta = 5\n",
"pp = 61/11, satellite_part = 12\n",
"\n",
"sigma(-T(2, 3; 2, 7; 2, 11)) = 193/11\n",
"****************************************************************************************************\n",
"Calculation summary for a cable sum:\n",
"T(2, 3; 2, 5; 2, 11) # -T(2, 5; 2, 11) # T(2, 7; 2, 11) # -T(2, 3; 2, 7; 2, 11)\n",
"2. T(2, 7; 2, 11)\n",
"Pattern part = -61/11\n",
"Satellite part = -12\n",
"Sigma = -193/11\n",
"\n",
"3. -T(2, 3; 2, 7; 2, 11)\n",
"Pattern part = 61/11\n",
"Satellite part = 12\n",
"Sigma = 193/11\n",
"\n",
"[0, 0, 5, 5] 0\n",
"\n",
"\n",
"\n",
"########## T(2, 7; 2, 11) ##########\n",
"\n"
before adding sigma
2020-11-10 17:55:29 +01:00
]
},
{
"data": {
plots
2020-11-19 10:32:15 +01:00
"image/png": "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
before adding sigma
2020-11-10 17:55:29 +01:00
"text/plain": [
plots
2020-11-19 10:32:15 +01:00
"<Figure size 432x288 with 1 Axes>"
before adding sigma
2020-11-10 17:55:29 +01:00
]
},
plots
2020-11-19 10:32:15 +01:00
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
before adding sigma
2020-11-10 17:55:29 +01:00
},
{
verbose option added
2020-11-19 06:47:52 +01:00
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"T(2, 7; 2, 11), theta = 6\n",
"pp = -61/11, satellite_part = -12\n",
"\n",
"sigma(T(2, 7; 2, 11)) = -193/11\n",
"\n",
"\n",
"\n",
"########## -T(2, 3; 2, 7; 2, 11) ##########\n",
"\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
},
plots
2020-11-19 10:32:15 +01:00
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAEICAYAAABS0fM3AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/Il7ecAAAACXBIWXMAAAsTAAALEwEAmpwYAAAtX0lEQVR4nO3de3xU9Z3/8deHEMJdQEApQcAttXIRkAAiILcCARTcWrdYVKy6rt3a+rssVtdarda2arv91d26yiJLtVRXqpSIKF4REbCEgoAoCIIC3qKQcAuQkM/vj3NIh1wnyZAzybyfj8c8mPM953vOe4bJfOZ8z5k55u6IiEjqahJ1ABERiZYKgYhIilMhEBFJcSoEIiIpToVARCTFqRCIiKQ4FYIkZmYZZrbZzLpEnSUVmdmvzex7NVj+GjNbcSozRcHMepiZm1nTqLPIqaFCEBEze97MDoa3IjM7FjP9cLjYDcByd/8k7DPLzDaZ2QEz22Fms2qwvTFmttHM8s3sSzNbaGZd4+ybYWaPmtmH4bbXm9mkWj7Wg+Fj3Rhn36+Z2SIzyzOzvWa21MzOqcG2bzKzXDM7ambzysxrZmZ/MrOd4Rvd6DLdfwX8q5k1i3d7ySABz9lOM/tGgrJEVkTMLM3MfmZmH4ev23Vm1q6+czQEKgQRcfdJ7t7a3VsD84H7T0y7+43hYjcCj8d0M+BqoD2QDdxkZtPj3ORmYKK7twO+ArwP/GecfZsCu4BRwGnAj4GnzKxHPJ1jH2v4eFcCC+LcdjsgBzgHOAP4C7Aozr4AHwM/A+ZWMn8FcCXwaQW5PwHeA6bWYHv1qpI32HbU7TlrLH4KXAgMA9oCVwFHIk2UrNxdt4hvwDzgZ2XazgIKgaZV9HsQ+PdabC8D+AWwOabtVmBxDdaxAbisFtvuARwHesS0LQZujbN/B8CB02u43Z8B86qYvxsYXUH77cB/x7mNa4AVMdO/JSig+4G1wMiw/UzgcOxjAM4H8oD0cPpa4F1gH7AU6B6zrAPfJyjmOxL5nBF88CgJX3sHgVvC/zMHZgIfAV8At8f0aRK+frYDXwJPAR3CeR+FfQ+Gt2HA3wGvhst+QfBBqF1NX0vVPI724fb+LpHrbaw37REkr37AB+5eXNFMMzNgJPBOvCs0s7PMLJ/gj/xfgPtPzHP3X7r7xXGu5wzgazXZdoyrgTfcfWfMti9291/G2f8i4FN3/7IW266Nd4H+tey7BhhA8Eb8R2CBmTV390+BZcA/xCx7FfCkuxeZ2TTgX4FvAp2AN4Anyqz7UmAo0DuOHHE/Z+5+FcGb9yUe7MHdHzN7BMFexjjgJ2Z2btj+gzDPKIK9zX3A72K2DcEbfWt3X0WwZ/uLcNlzgW7AXZVlMrMN4ZBmRbeHKunWDygGvmVmn5rZVjP7fnWPP2VFXYl0q3SPYAawuoo+PwXeBjJqsb0OwI+AC2rRNx14GXiklo91G3BNLftmAnuAK2rRt7Z7BOMJCnI827iGmD2CCubvA/qH978NvBneTyMYmhoSTj8PXBfTrwnBHkT3cNqBsafqOQN2At+Ime4RbjMzpu0vwPTw/rvAuJh5XYAigiHFE32r2rO9FFhXm9dEFev8TrjdR4EWwHkEe1zjE7mdxnLTHkE9MrMZMQdMn69m8X1Am0rWcxPBJ+sp7n60pjncfS/we2BRTQ7imVkTgqGDY8BNNd2umY0gGBb5Uy36dgJeBB5y97Kfjk+lNkB+bTqa2b+Y2btmVhDuiZ0GdAxnLwJ6m1lPgmJT4O5/Ced1B3574lMvsJfgU3Tswf1dcWw/0c9Z7HGUw0DrmLwLY/K+SzD8d0Yluc4wsyfNbI+Z7Qf+wN+el0QpDP+9290L3X0D8CQwOcHbaRRUCOqRu8/3vx00re6smw1Az7Jv1GZ2LcF47Dh3312HOE2BzgQH0aoVDkU9SvDHfZm7F9VimzOBZ9z9YE06mVl7gje0HHe/txbbrYtzCfa8asTMRhKMr/8D0N6Dg/QFBG/ouPsRgrH0KwmGhWJPCtgF/JO7t4u5tXD3lTHLVPmzwXV8zmr6k8S7gEll8jZ39z2VrOvnYXs/d29L8BxYZSs3s3fKnHUWe3u4km4bKngs+qnlSqgQJKnwTX4bMOREm5nNIPgjGu/uH5TtY2bLzOyuitZnZt80s3PMrEn4SfHfCHbH94bz7zKzZVVE+k+CN8VL3L2w7MxKTr+Mnd+C4E1xXg1ztyU4WPqmu99awfzRZlbpH7iZNTWz5gTDL2lm1jy2uFpwamzzcLJZOD/2TWkUwVBNtVnLaEMwRp0HNDWzn1C+6D5GMJw0lZMLwcPAbWbWJ9zmaWZ2eRzbPJGxTs8Z8BlwdrzbC/Pea2bdw/V3Co9zQPD4S8qsrw3BgdwCC05hrvI0aHfvE/MBquztxkr6bCc4tnJ7+H98LjCd4MQEKUOFILk9QvBp8YSfAacDayr5RNQNeLOSdXUFXgAOABsJ/jj/Pp6+4R/4PxEc+Pw0ZtszwvndYtZbmUsJhlheq2BeVbn/HhgMfLfMJ8GzYvqurKQvBKe6FhLsRV0Z3v9xzPwtYVtXgjfPQoKhDiz4Il9v4M9xZo21lOD53gp8SHDa4knDOe7+JsH/w1/d/cOY9oXAfcCT4dDJJiDu721Q9+fsF8CPw6Gef4lje78lOF31RTM7AKwmOJCNux8G7gXeDNd3AcHxrfMJ9pCeA56pwWOriSsI/i+/DLdzh7u/coq21aBZeGBFkpCZZQDrCIaBPqlm2UzgKXe/sJbbWh9up8Zn45jZlUAfd7+tFn3rmnsOsMDdl9amfzXr/jWw3d0fCqfrlLWSbbwK/NHd5yRqnXFs85Q9Z9IwqRCIRMTMBgMvAd3c/UDUeSR1aWhIJAJm9nuC03D/l4qARE17BCIiKU57BCIiKS4pf1a2Y8eO3qNHj6hjiIg0GGvXrv3C3TvVpm9SFoIePXqQm5sbdQwRkQbDzD6sfqmKaWhIRCTFqRCIiKQ4FQIRkRSnQiAikuJUCEREUly1hcDMupnZa2a2Ofw52JsrWMbM7EEz22bB1YTOj5k308zeD28zE/0ARESkbuI5fbQY+L/u/lczawOsNbOX3H1zzDKTgF7hbSjBTxYPNbMOwJ1AFsFvga81sxx335fQRyEiIrVWbSEIf/Xyk/D+ATN7l+Ane2MLwTTgMQ9+r2K1mbULf8J3NPBSzG/evwRkU/76q1JPRo+OOoGksmXLok4gFanRMQIz6wEMBN4qM6srJ//W+u6wrbL2itZ9g5nlmlluXl5eTWKJiEgd1OR6ta2Bpwl+LXF/ooO4+2xgNkBWVpZ+Ce8U0ScyESkrrj0CM0snKALz3b2iqwntIbjq0QmZYVtl7SIikiTiOWvoxEXL33X3f6tksRzg6vDsoQuAgvDYwlJggpm1t+Bi2hPCNhERSRLxDA0NJ7hu7sbwcoYA/wqcBeDuDwNLgMkEF1s/DHw3nLfXzO4B1oT97j5x4FhERJJDPGcNrQCsmmUc+H4l8+YCc2uVTkRETjl9s1hEJMWpEIiIpDgVAhGRFKdCICKS4lQIRERSnAqBiEiKUyEQEUlxKgQiIilOhUBEJMWpEIiIpDgVAhGRFKdCICKS4lQIRERSnAqBiEiKUyEQEUlxKgQiIimu2gvTmNlc4GLgc3fvW8H8WcCMmPWdC3QKr062EzgAHAeK3T0rUcFFRCQx4tkjmAdkVzbT3R9w9wHuPgC4DXi9zOUox4TzVQRERJJQtYXA3ZcD8V5n+ArgiTolEhGRepWwYwRm1pJgz+HpmGYHXjSztWZ2QzX9bzCzXDPLzcvLS1QsERGpRiIPFl8CvFlmWGiEu58PTAK+b2YXVdbZ3We7e5a7Z3Xq1CmBsUREpCqJLATTKTMs5O57wn8/BxYCQxK4PRERSYCEFAIzOw0YBSyKaWtlZm1O3AcmAJsSsT0REUmceE4ffQIYDXQ0s93AnUA6gLs/HC7298CL7n4opusZwEIzO7GdP7r7C4mLLiIiiVBtIXD3K+JYZh7BaaaxbR8A/WsbTERE6oe+WSwikuJUCEREUpwKgYhIilMhEBFJcSoEIiIpToV
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
verbose option added
2020-11-19 06:47:52 +01:00
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"-T(2, 3; 2, 7; 2, 11), theta = 6\n",
"pp = 61/11, satellite_part = 12\n",
"\n",
"sigma(-T(2, 3; 2, 7; 2, 11)) = 193/11\n",
"****************************************************************************************************\n",
"Calculation summary for a cable sum:\n",
"T(2, 3; 2, 5; 2, 11) # -T(2, 5; 2, 11) # T(2, 7; 2, 11) # -T(2, 3; 2, 7; 2, 11)\n",
"2. T(2, 7; 2, 11)\n",
"Pattern part = -61/11\n",
"Satellite part = -12\n",
"Sigma = -193/11\n",
"\n",
"3. -T(2, 3; 2, 7; 2, 11)\n",
"Pattern part = 61/11\n",
"Satellite part = 12\n",
"Sigma = 193/11\n",
"\n",
"[0, 0, 6, 6] 0\n",
"\n",
"\n",
"\n",
"########## T(2, 7; 2, 11) ##########\n",
"\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
},
plots
2020-11-19 10:32:15 +01:00
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
verbose option added
2020-11-19 06:47:52 +01:00
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"T(2, 7; 2, 11), theta = 7\n",
"pp = -65/11, satellite_part = -12\n",
"\n",
"sigma(T(2, 7; 2, 11)) = -197/11\n",
"\n",
"\n",
"\n",
"########## -T(2, 3; 2, 7; 2, 11) ##########\n",
"\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
},
plots
2020-11-19 10:32:15 +01:00
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
verbose option added
2020-11-19 06:47:52 +01:00
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"-T(2, 3; 2, 7; 2, 11), theta = 7\n",
"pp = 65/11, satellite_part = 16\n",
"\n",
"sigma(-T(2, 3; 2, 7; 2, 11)) = 241/11\n",
"****************************************************************************************************\n",
"Calculation summary for a cable sum:\n",
"T(2, 3; 2, 5; 2, 11) # -T(2, 5; 2, 11) # T(2, 7; 2, 11) # -T(2, 3; 2, 7; 2, 11)\n",
"2. T(2, 7; 2, 11)\n",
"Pattern part = -65/11\n",
"Satellite part = -12\n",
"Sigma = -197/11\n",
"\n",
"3. -T(2, 3; 2, 7; 2, 11)\n",
"Pattern part = 65/11\n",
"Satellite part = 16\n",
"Sigma = 241/11\n",
"\n",
"[0, 0, 7, 7] 4\n",
"\n",
"\n",
"\n",
"########## T(2, 7; 2, 11) ##########\n",
"\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
},
plots
2020-11-19 10:32:15 +01:00
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
verbose option added
2020-11-19 06:47:52 +01:00
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"T(2, 7; 2, 11), theta = 8\n",
"pp = -73/11, satellite_part = -8\n",
"\n",
"sigma(T(2, 7; 2, 11)) = -161/11\n",
"\n",
"\n",
"\n",
"########## -T(2, 3; 2, 7; 2, 11) ##########\n",
"\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
},
plots
2020-11-19 10:32:15 +01:00
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
verbose option added
2020-11-19 06:47:52 +01:00
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"-T(2, 3; 2, 7; 2, 11), theta = 8\n",
"pp = 73/11, satellite_part = 12\n",
"\n",
"sigma(-T(2, 3; 2, 7; 2, 11)) = 205/11\n",
"****************************************************************************************************\n",
"Calculation summary for a cable sum:\n",
"T(2, 3; 2, 5; 2, 11) # -T(2, 5; 2, 11) # T(2, 7; 2, 11) # -T(2, 3; 2, 7; 2, 11)\n",
"2. T(2, 7; 2, 11)\n",
"Pattern part = -73/11\n",
"Satellite part = -8\n",
"Sigma = -161/11\n",
"\n",
"3. -T(2, 3; 2, 7; 2, 11)\n",
"Pattern part = 73/11\n",
"Satellite part = 12\n",
"Sigma = 205/11\n",
"\n",
"[0, 0, 8, 8] 4\n",
"\n",
"\n",
"\n",
"########## T(2, 7; 2, 11) ##########\n",
"\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
},
plots
2020-11-19 10:32:15 +01:00
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
verbose option added
2020-11-19 06:47:52 +01:00
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"T(2, 7; 2, 11), theta = 9\n",
"pp = -85/11, satellite_part = -4\n",
"\n",
"sigma(T(2, 7; 2, 11)) = -129/11\n",
"\n",
"\n",
"\n",
"########## -T(2, 3; 2, 7; 2, 11) ##########\n",
"\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
},
{
plots
2020-11-19 10:32:15 +01:00
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
verbose option added
2020-11-19 06:47:52 +01:00
},
{
plots
2020-11-19 10:32:15 +01:00
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
verbose option added
2020-11-19 06:47:52 +01:00
},
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"-T(2, 3; 2, 7; 2, 11), theta = 9\n",
"pp = 85/11, satellite_part = 8\n",
"\n",
"sigma(-T(2, 3; 2, 7; 2, 11)) = 173/11\n",
"****************************************************************************************************\n",
"Calculation summary for a cable sum:\n",
"T(2, 3; 2, 5; 2, 11) # -T(2, 5; 2, 11) # T(2, 7; 2, 11) # -T(2, 3; 2, 7; 2, 11)\n",
"2. T(2, 7; 2, 11)\n",
"Pattern part = -85/11\n",
"Satellite part = -4\n",
"Sigma = -129/11\n",
"\n",
"3. -T(2, 3; 2, 7; 2, 11)\n",
"Pattern part = 85/11\n",
"Satellite part = 8\n",
"Sigma = 173/11\n",
"\n",
"[0, 0, 9, 9] 4\n",
"\n",
"\n",
"\n",
"########## T(2, 7; 2, 11) ##########\n",
"\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
},
{
plots
2020-11-19 10:32:15 +01:00
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
verbose option added
2020-11-19 06:47:52 +01:00
},
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"T(2, 7; 2, 11), theta = 10\n",
"pp = -101/11, satellite_part = -4\n",
"\n",
"sigma(T(2, 7; 2, 11)) = -145/11\n",
"\n",
"\n",
"\n",
"########## -T(2, 3; 2, 7; 2, 11) ##########\n",
"\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
},
{
plots
2020-11-19 10:32:15 +01:00
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
verbose option added
2020-11-19 06:47:52 +01:00
},
{
plots
2020-11-19 10:32:15 +01:00
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAe0AAAEICAYAAAByPazKAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/Il7ecAAAACXBIWXMAAAsTAAALEwEAmpwYAAAoUUlEQVR4nO3de5xVdb3/8ddbLuJREBBQFBDqoEcxHXUO5S2x1NBzFLtYoCCYybHC7hkeK8m0vPzK0iwiQYFQU/NCdryVkhc0GRIveEWkBE1GQMC4CPj5/bHW4GKYPbOH2TN7FvN+Ph77MWt9L2t99p6Z/dnru75rL0UEZmZm1vrtUO4AzMzMrDhO2mZmZjnhpG1mZpYTTtpmZmY54aRtZmaWE07aZmZmOeGk3YpI2lHSc5J6lzuWtkjSTyR9sRHtx0h6pDljKgdJ/SWFpPbljsXMtuSk3UIk3S3pnfSxQdK7mfWJabOxwEMR8Uba59uSnpW0WtKrkr7diP0dI+kZSW9LWibpdkl7Fdl3R0mTJf093fc8SSds43N9J32uzxTZdx9Jd0qqlrRc0r2S9m3EvsdJqpK0XtL1teo6SrpV0qI0KQ2p1f3/Af8rqWOx+2sNSvCaLZJ0bIliKVvClzRJ0ouS3pM0po76r0v6p6RVkqZI2rGlYzRrKiftFhIRJ0TELhGxCzADuLxmPSLOSZudA0zPdBNwBtANGAqMkzS8yF0+B3wiIroCewIvA78qsm974DXgaGBX4LvAzZL6F9M5+1zT5zsbuKXIfXcFZgL7ArsDTwB3FtkX4HXgYmBKgfpHgJHAP+uI+w3gBeDkRuyvRRVIhl1p2mu2vXgK+BLwt9oVkj4BjAc+DuwNfAD4QYtGZ1YCTtqthKR+JG8kf60pi4jLI+JvEbExIl4keSM+opjtRcSbEfF6pmgT8O+Z/Y2XdFeBvv+KiAkRsSgi3ouIu4BXgUO34Xn1B44CpmXK7pI0vsC+n4iIyRGxPCI2AFcC+0rarZj9RcRtEXEHsKyOuncj4mcR8QjJ61GXWcB/FbOv2iT9XNJr6ZHcXElHpeV7SFqTfQ6SDkmPjDuk65+X9LykFemR8t6ZtiHpy5JeJvnwVft5bfNrJmk60A/4Qzoqcl6m+nRJ/5D0lqQLMn12SP9+XklHcW6W1D2tfij9+Xa6vcMkfVDSA2nbtyTNkNS1yJe1aBFxTUT8GVhXR/VoYHJEzI+IFcAPgTGljsGsuTlptx4fAhZGxMa6KiWJJPnNL3aDkvpJehtYC3wLuLymLiIujYj/LnI7uwP7NGbfGWcAD0fEosy+/zsiLi2y/0eBf0bEVkm4mTwPHLSNfecAFUB34AbgFkmdIuKfJB8GPptpOwq4KSI2SBoG/C/wKaAn8DBwY61tnwJ8GNi/iDiKfs0iYhTwD+CkdGTk8kz1kSRH7x8Hvi9pv7T83DSeo0lGcVYA12T2DdA13d5jJCNGP07b7gf0BSYUiknS0+lpnboevyzi+ddlEMmReI2ngN2L/TBo1lo4abceXYHV9dRPIPl9XVfsBiPiH+nweA+SIe4XGhtUeiQ4A5gaEY3uT5K0r9+GfkjqQ5IMvrEt/bfRapLfRaNFxG8jYlk6MvITYEeSpAcwlWRYHkntgBG8fyrkHODHEfF8+qHtR0BF9mg7rV8eEWvri6HEr9kPImJtRDxFkuRqPsycA1wQEYsjYj3J3+ZnCp3HjogFEXF/RKyPiGrgpyQJv04RcWBEdC3w+NI2PpddgJWZ9Zrlztu4PbOycNJuRpJOz0zGuruB5iso8AYiaRxJ8vuv9E2yUSJiOUnSuLMxE4Qk7UCSWN4FxjV2v5KOBPYAbt2Gvj2B+4BfRkTto87m1Bl4e1s6SvpWOsS9Mh3h2JXkAxMkpzb2lzQAOA5YGRFPpHV7Az+vOZoElpMcnWYnDr5WxP5L/Zplz/uvIUl8NfHenon3eZLTDbsXiGt3STdJWiJpFfBb3n9dWso7QJfMes1yfR+UzVodJ+1mFBEzMhOyGpp9/TQwoHZSlfR50gk0EbG4CeG0B3qx5RtXQelw/GSSN+JPp+dKG2s0cFtEvNOYTpK6kSSfmRFxyTbstyn2Y8th1KKk56/PIxkC75aOcKwkSb5ExDrgZpKj7VFsOeHwNeB/ah1R7hQRszNt6r0dXxNfs8be6u814IRa8XaKiCUFtvWjtPxDEdGF5DVQoY1Lmq8trz7IPiYW6teA+Wx52uMg4M0WPO1iVhJO2q1EmpAXAINryiSdTvKGd1xELKzdR9IsSRPq2p6kT0naN5001JNkSPLJ9KgbSRMkzaonpF+RJLCT6hqSVd2XTGXrdyJJYNc3Mu4uwL3AoxGx1WQ1SUMkFUwyktpL6gS0A9pJ6pT9IKTkcrZO6WrHtD6bQI4G7s60LxhrLZ2BjUA10F7S99n6A9I0kslPJ7Nl0p4InC9pULrPXSWdWsQ+a2Js0msGvEkyCbJYE4FLaobvJfVMz8tD8vzfq7W9ziRHuiuVXHZY76WLETEoe/VBrcc5hfopuaSvE8kHgg7p77bmPW4acJak/dNJcN9lG0/bmJWTk3br8muSo7AaFwO7AXMKHGn0BR4tsK29gHtIhv+eIXkj/WQxfdM34/8hmVT1z8y+T0/r+2a2W8gpJMPMD9ZRV1/cnwT+Eziz1hFWv0zf2QX6QvJmvJZkdGJkuvzdTP2LadleJIluLclwL0q+1GZ/4I4iY826l+T1fgn4O8kM5i2GtCPiUZLfw98i4u+Z8tuBy4Cb0uHjZ4Gir4un6a/Zj4HvpsPd3ypifz8nucTsPkmrgcdJJskREWuAS4BH0+19hOTSqkNIRh7+CNzWiOfWGPeR/D4PByalyx9N47qHZCLmgyQT7/4OXNhMcZg1G0U0dmTMmouSL3t4kmQo/I0G2vYBbo6Iw7dxX/PS/TR6eFDSSGBQRJy/DX2bGve1wC0Rce+29G9g2z8BXomIX6brTYq1wD4eAG6IiGtLtc0i9tlsr5mZtSwnbbMWIuk/gfuBvhHhCVBm1mgeHjdrAZKmAn8CvuaEbWbbykfaZmZmOeEjbTMzs5xolbfe69GjR/Tv37/cYZiZ5cbcuXPfioie5Y7DmlerTNr9+/enqqqq3GGYmeWGpL833MryzsPjZmZmOeGkbWZmlhNO2mZmZjnhpG1mZpYTTtpmZmY50WDSltRX0oOSnktvmffVOtpI0lWSFkh6WtIhmbrRkl5OH6NL/QTMzMzaimIu+doIfDMi/iapMzBX0v0R8VymzQnAwPTxYZLbOn5YUneSO+lUktxPd66kmRGxoqTPwszMrA1oMGmnd5t6I11eLel5ktsaZpP2MGBaJN+J+rikrultDocA92fu4Xw/MBS4saTPwoo2ZEi5I7C2bNasckdglm+NOqctqT9wMPDXWlV7seW9gxenZYXK69r2WElVkqqqq6sbE5aZmVmbUPQ3oknaBfg9yV2KVpU6kIiYRHLjeiorK30Xk2biIx0rhxUrVtC1a1dA5Q7FLNeKStqSOpAk7BkRcVsdTZYAfTPrfdKyJSRD5NnyWdsSqJnl12mnncaaNWv4yEc+whFHHEFFRQV9+/ZFchI3a4wGk7aS/6rJwPMR8dMCzWYC4yTdRDIRbWVEvCHpXuBHkrql7Y4Hzi9B3GaWI8ceeyzTpk3j4Ycf5oEHHkASu+yyC4cddhhHHnkkBx54IHvuuaeTuFkDGryftqQjgYeBZ4D30uL/BfoBRMTENLH/gmSS2RrgzIioSvt/Pm0PcElEXNdQUJWVleEbhphtPxYtWsSpp55Kr1692GGHZCrN+vXrWb16NZs2bQKga9euHHnkkRx22GEcdNBB9OrVq5wh546kuRFRWe44rHk1mLTLwUnbbPtz9tln89xzz9G9e/et6iKC9evXs2rVKiKCTZs2cfjhh3P11VeXIdJ8ctJuG/yNaGbWIkaOHMmGDRvqrJNEp06d6NWr1+akfvLJJ7dkeGa54KRtZi3iiCOOoEuXLqxdu7Zgm02bNlFdXc24ceM47rjjWjA6s3xw0jazFtG+fXtOO+00Vq5cWWd9RPDmm2/yyU9+kjFjxrRscGY
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
verbose option added
2020-11-19 06:47:52 +01:00
},
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"-T(2, 3; 2, 7; 2, 11), theta = 10\n",
"pp = 101/11, satellite_part = 8\n",
"\n",
"sigma(-T(2, 3; 2, 7; 2, 11)) = 189/11\n",
"****************************************************************************************************\n",
"Calculation summary for a cable sum:\n",
"T(2, 3; 2, 5; 2, 11) # -T(2, 5; 2, 11) # T(2, 7; 2, 11) # -T(2, 3; 2, 7; 2, 11)\n",
"2. T(2, 7; 2, 11)\n",
"Pattern part = -101/11\n",
"Satellite part = -4\n",
"Sigma = -145/11\n",
"\n",
"3. -T(2, 3; 2, 7; 2, 11)\n",
"Pattern part = 101/11\n",
"Satellite part = 8\n",
"Sigma = 189/11\n",
"\n",
"[0, 0, 10, 10] 4\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
},
{
plots
2020-11-19 10:32:15 +01:00
"data": {
"text/plain": [
"False"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cs = import_sage('cable_signature')\n",
"knot_formula = \"[[k[0], k[1], k[3]],\" + \\\n",
" \" [-k[1], -k[3]],\" + \\\n",
" \" [k[2], k[3]],\" + \\\n",
" \" [-k[0], -k[2], -k[3]]]\"\n",
"# q_vector = (3, 5, 7, 13)\n",
"q_vector = (3, 5, 7, 11)\n",
"\n",
"template = cs.CableTemplate(knot_formula, q_vector=q_vector, verbose=True)\n",
"cable = template.cable\n",
"# cable.plot_all_summands()\n",
"cable.is_function_big_for_all_metabolizers(invariant=cs.SIGMA)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Cables with 8 direct summands "
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"formula_1 = \"[[k[0], k[5], k[3]], \" + \\\n",
" \"[-k[1], -k[3]], \" + \\\n",
" \"[k[2], k[3]], \" + \\\n",
" \"[-k[0], -k[2], -k[3]]]\"\n",
"formula_2 = \"[[k[4], k[1], k[7]], \" + \\\n",
" \"[-k[5], -k[7]], \" + \\\n",
" \"[k[6], k[7]], \" + \\\n",
" \"[-k[4], -k[6], -k[7]]]\"\n",
"\n",
"\n",
"\n",
"cable_template_1 = cs.CableTemplate(knot_formula=formula_1)\n",
"cable_template_2 = cs.CableTemplate(knot_formula=formula_2)\n",
"cable_template = cable_template_1 + cable_template_2"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Relatively small cables "
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
verbose option added
2020-11-19 06:47:52 +01:00
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"T(2, 5; 2, 17; 2, 41) # -T(2, 13; 2, 41) # T(2, 19; 2, 41) # -T(2, 5; 2, 19; 2, 41) # T(2, 7; 2, 13; 2, 43) # -T(2, 17; 2, 43) # T(2, 23; 2, 43) # -T(2, 7; 2, 23; 2, 43)\n",
"T(2, 5; 2, 17; 2, 41) # -T(2, 13; 2, 41) # T(2, 19; 2, 41) # -T(2, 5; 2, 19; 2, 41) # T(2, 7; 2, 13; 2, 43) # -T(2, 17; 2, 43) # T(2, 23; 2, 43) # -T(2, 7; 2, 23; 2, 43)\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
plots
2020-11-19 10:32:15 +01:00
}
],
"source": [
"q_vector = (5, 13, 19, 41,\\\n",
" 7, 17, 23, 43)\n",
"cable_template.fill_q_vector(q_vector=q_vector)\n",
"cable = cable_template.cable\n",
"print(cable.knot_description)\n",
"\n",
"q_vector_small = (3, 7, 13, 19,\\\n",
" 5, 11, 17, 23)\n",
"cable_template.fill_q_vector(q_vector=q_vector)\n",
"cable = cable_template.cable\n",
"print(cable.knot_description)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"# cable.is_signature_big_for_all_metabolizers()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Slice candidate"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
verbose option added
2020-11-19 06:47:52 +01:00
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"T(2, 5; 2, 71; 2, 347) # -T(2, 67; 2, 347) # T(2, 61; 2, 347) # -T(2, 5; 2, 61; 2, 347) # T(2, 11; 2, 67; 2, 367) # -T(2, 71; 2, 367) # T(2, 79; 2, 367) # -T(2, 11; 2, 79; 2, 367)\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
plots
2020-11-19 10:32:15 +01:00
}
],
"source": [
"\n",
"cable_template.fill_q_vector()\n",
"# print(cable_template.q_vector)\n",
"# print(cable_template.knot_formula)\n",
"\n",
"slice_canidate = cable_template.cable\n",
"print(slice_canidate.knot_description)\n",
"sf = slice_canidate(4,4,4,4,0,0,0,0)\n",
"sf = slice_canidate(4,1,1,4,0,0,0,0)\n",
"\n",
"\n",
"# cable.is_signature_big_for_all_metabolizers()\n"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"\n",
"\n",
"# knot_formula = \"[[k[0], k[1], k[4]], [-k[1], -k[3]],\\\n",
"# [k[2], k[3]], [-k[0], -k[2], -k[4]]]\"\n",
"\n",
"# knot_formula = \"[[k[3]], [-k[3]],\\\n",
"# [k[3]], [-k[3]] ]\"\n",
"\n",
"# knot_formula = \"[[k[3], k[2], k[0]], [-k[2], -k[0]],\\\n",
"# [k[1], k[0]], [-k[3], -k[1], -k[0]]]\"\n",
"\n",
"# knot_formula = \"[[k[0], k[1], k[2]], [k[3], k[4]],\\\n",
"# [-k[0], -k[3], -k[4]], [-k[1], -k[2]]]\"\n",
"\n",
"# knot_formula = \"[[k[0], k[1], k[2]], [k[3]],\\\n",
"# [-k[0], -k[1], -k[3]], [-k[2]]]\""
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
verbose option added
2020-11-19 06:47:52 +01:00
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"T(2, 5; 2, 71; 2, 347) # -T(2, 67; 2, 347) # T(2, 61; 2, 347) # -T(2, 5; 2, 61; 2, 347) # T(2, 11; 2, 67; 2, 367) # -T(2, 71; 2, 367) # T(2, 79; 2, 367) # -T(2, 11; 2, 79; 2, 367)\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
},
plots
2020-11-19 10:32:15 +01:00
{
"data": {
"text/plain": [
"127349"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"formula_1 = \"[[k[0], k[5], k[3]], \" + \\\n",
" \"[-k[1], -k[3]], \" + \\\n",
" \"[k[2], k[3]], \" + \\\n",
" \"[-k[0], -k[2], -k[3]]]\"\n",
"formula_2 = \"[[k[4], k[1], k[7]], \" + \\\n",
" \"[-k[5], -k[7]], \" + \\\n",
" \"[k[6], k[7]], \" + \\\n",
" \"[-k[4], -k[6], -k[7]]]\"\n",
"\n",
"\n",
"\n",
"cable_template_1 = cs.CableTemplate(knot_formula=formula_1)\n",
"cable_template_2 = cs.CableTemplate(knot_formula=formula_2)\n",
"cable_template = cable_template_1 + cable_template_2\n",
"\n",
"cable_template.fill_q_vector()\n",
"# print(cable_template.q_vector)\n",
"# print(cable_template.knot_formula)\n",
"\n",
"slice_canidate = cable_template.cable\n",
"print(slice_canidate.knot_description)\n",
"sf = slice_canidate(4,4,4,4,0,0,0,0)\n",
"sf = slice_canidate(4,1,1,4,0,0,0,0)\n",
"\n",
"\n",
"slice_canidate.q_order\n",
"# slice_canidate.is_signature_big_for_all_metabolizers()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
verbose option added
2020-11-19 06:47:52 +01:00
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"T(2, 11; 2, 53; 2, 347) # -T(2, 53; 2, 347) # T(2, 61; 2, 347) # -T(2, 7; 2, 61; 2, 347) # T(2, 7; 2, 71; 2, 367) # -T(2, 71; 2, 367) # T(2, 79; 2, 367) # -T(2, 11; 2, 79; 2, 367)\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
},
plots
2020-11-19 10:32:15 +01:00
{
"data": {
"text/plain": [
"127349"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"text/plain": [
"-4"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"formula_1 = \"[[k[0], k[5], k[3]], \" + \\\n",
" \"[-k[5], -k[3]], \" + \\\n",
" \"[k[2], k[3]], \" + \\\n",
" \"[-k[4], -k[2], -k[3]]]\"\n",
"formula_2 = \"[[k[4], k[1], k[7]], \" + \\\n",
" \"[-k[1], -k[7]], \" + \\\n",
" \"[k[6], k[7]], \" + \\\n",
" \"[-k[0], -k[6], -k[7]]]\"\n",
"\n",
"\n",
"\n",
"\n",
"cable_template_1 = cs.CableTemplate(knot_formula=formula_1)\n",
"cable_template_2 = cs.CableTemplate(knot_formula=formula_2)\n",
"cable_template = cable_template_1 + cable_template_2\n",
"cable_template.fill_q_vector()\n",
"\n",
"slice_canidate = cable_template.cable\n",
"print(slice_canidate.knot_description)\n",
"\n",
"slice_canidate.q_order\n",
"# slice_canidate.is_signature_big_for_all_metabolizers()\n",
"sigma = slice_canidate.get_sigma_as_function_of_theta()\n",
"# sigma((0, 6, 6, 0, 0,0,0,0))\n",
"# 13450/83\n",
"sigma((9, 9, 9, 9, 0,0,0,0))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"\n",
"\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"scrolled": false
},
"outputs": [
verbose option added
2020-11-19 06:47:52 +01:00
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"T(2, 11; 2, 71; 2, 313) # -T(2, 61; 2, 313) # T(2, 313) # -T(2, 7; 2, 67; 2, 313) # T(2, 7; 2, 61; 2, 347) # -T(2, 347) # T(2, 67; 2, 347) # -T(2, 11; 2, 71; 2, 347)\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
plots
2020-11-19 10:32:15 +01:00
}
],
"source": [
"formula_1 = \"[[k[0], k[5], k[3]], \" + \\\n",
" \"[-k[1], -k[3]], \" + \\\n",
" \"[ k[3]], \" + \\\n",
" \"[-k[4], -k[6], -k[3]]]\"\n",
"\n",
"formula_2 = \"[[k[4], k[1], k[7]], \" + \\\n",
" \"[ -k[7]], \" + \\\n",
" \"[k[6], k[7]], \" + \\\n",
" \"[-k[0], -k[5], -k[7]]]\"\n",
"\n",
"\n",
"\n",
"\n",
"cable_template_1 = cs.CableTemplate(knot_formula=formula_1)\n",
"cable_template_2 = cs.CableTemplate(knot_formula=formula_2)\n",
"cable_template = cable_template_1 + cable_template_2\n",
"\n",
"cable_template.fill_q_vector()\n",
"# print(cable_template.q_vector)\n",
"# print(cable_template.knot_formula)\n",
"\n",
"slice_canidate = cable_template.cable\n",
"print(slice_canidate.knot_description)\n",
"sf = slice_canidate(4,4,4,4,0,0,0,0)\n",
"sf = slice_canidate(4,1,1,4,0,0,0,0)\n",
"# slice_canidate.is_signature_big_for_all_metabolizers()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"scrolled": false
},
"outputs": [
verbose option added
2020-11-19 06:47:52 +01:00
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"T(2, 43; 2, 191) # -T(2, 37; 2, 191) # T(2, 191) # -T(2, 5; 2, 41; 2, 191) # T(2, 5; 2, 37; 2, 211) # -T(2, 211) # T(2, 41; 2, 211) # -T(2, 43; 2, 211)\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
},
{
plots
2020-11-19 10:32:15 +01:00
"data": {
"text/plain": [
"40301"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"formula_1 = \" [ [k[5], k[3]], \" + \\\n",
" \" [ -k[1], -k[3]], \" + \\\n",
" \" [ k[3]], \" + \\\n",
" \"[-k[4], -k[6], -k[3]]]\"\n",
"\n",
"formula_2 = \"[[k[4], k[1], k[7]], \" + \\\n",
" \"[ -k[7]], \" + \\\n",
" \"[k[6], k[7]], \" + \\\n",
" \"[-k[5], -k[7]]]\"\n",
"\n",
"\n",
"\n",
"\n",
"cable_template_1 = cs.CableTemplate(knot_formula=formula_1)\n",
"cable_template_2 = cs.CableTemplate(knot_formula=formula_2)\n",
"cable_template = cable_template_1 + cable_template_2\n",
"\n",
"cable_template.fill_q_vector()\n",
"# print(cable_template.q_vector)\n",
"# print(cable_template.knot_formula)\n",
"\n",
"slice_canidate = cable_template.cable\n",
"print(slice_canidate.knot_description)\n",
"sf = slice_canidate(4,4,4,4,0,0,0,0)\n",
"sf = slice_canidate(4,1,1,4,0,0,0,0)\n",
"slice_canidate.q_order\n",
"# slice_canidate.is_signature_big_for_all_metabolizers()\n"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"sf = slice_canidate()\n",
"sf = sf[2]"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"sf.plot()"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
verbose option added
2020-11-19 06:47:52 +01:00
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"T(2, 17; 2, 83) # -T(2, 11; 2, 83) # T(2, 83) # -T(2, 13; 2, 83) # T(2, 11; 2, 103) # -T(2, 103) # T(2, 13; 2, 103) # -T(2, 17; 2, 103)\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
},
plots
2020-11-19 10:32:15 +01:00
{
"data": {
"text/plain": [
"8549"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"formula_1 = \"[ [k[5], k[3]], \" + \\\n",
" \"[ -k[1], -k[3]], \" + \\\n",
" \"[ k[3]], \" + \\\n",
" \"[ -k[6], -k[3]]]\"\n",
"\n",
"formula_2 = \"[[ k[1], k[7]], \" + \\\n",
" \"[ -k[7]], \" + \\\n",
" \"[ k[6], k[7]], \" + \\\n",
" \"[ -k[5], -k[7]]]\"\n",
"\n",
"\n",
"\n",
"\n",
"cable_template_1 = cs.CableTemplate(knot_formula=formula_1)\n",
"cable_template_2 = cs.CableTemplate(knot_formula=formula_2)\n",
"cable_template = cable_template_1 + cable_template_2\n",
"\n",
"cable_template.fill_q_vector()\n",
"# print(cable_template.q_vector)\n",
"# print(cable_template.knot_formula)\n",
"\n",
"slice_canidate = cable_template.cable\n",
"print(slice_canidate.knot_description)\n",
"sf = slice_canidate(4,4,4,4,0,0,0,0)\n",
"sf = slice_canidate(4,1,1,4,0,0,0,0)\n",
"slice_canidate.q_order"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": true
},
"outputs": [
verbose option added
2020-11-19 06:47:52 +01:00
{
"name": "stdout",
"output_type": "stream",
"text": [
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 2, 2, 0, 0, 0, 0] 0\n",
"[0, 0, 3, 3, 0, 0, 0, 0] 0\n",
"[0, 0, 4, 4, 0, 0, 0, 0] 4\n",
"[0, 0, 5, 5, 0, 0, 0, 0] 4\n",
"[0, 0, 6, 6, 0, 0, 0, 0] 4\n",
"[0, 0, 7, 7, 0, 0, 0, 0] 4\n",
"[0, 0, 8, 8, 0, 0, 0, 0] 4\n",
"[0, 0, 9, 9, 0, 0, 0, 0] 4\n",
"[0, 0, 10, 10, 0, 0, 0, 0] 8\n",
"[0, 2, 2, 0, 0, 0, 0, 0] 0\n",
"[0, 3, 3, 0, 0, 0, 0, 0] 0\n",
"[0, 4, 4, 0, 0, 0, 0, 0] 4\n",
"[0, 5, 5, 0, 0, 0, 0, 0] 4\n",
"[0, 6, 6, 0, 0, 0, 0, 0] 4\n",
"[0, 7, 7, 0, 0, 0, 0, 0] 4\n",
"[0, 8, 8, 0, 0, 0, 0, 0] 4\n",
"[0, 9, 9, 0, 0, 0, 0, 0] 4\n",
"[0, 10, 10, 0, 0, 0, 0, 0] 4\n",
"[0, 11, 11, 0, 0, 0, 0, 0] 4\n",
"[0, 12, 12, 0, 0, 0, 0, 0] 8\n",
"[0, 4, 4, 0, 0, 0, 0, 0] 4\n",
"[0, 6, 6, 0, 0, 0, 0, 0] 4\n",
"[0, 8, 8, 0, 0, 0, 0, 0] 4\n",
"[0, 10, 10, 0, 0, 0, 0, 0] 4\n",
"[0, 12, 12, 0, 0, 0, 0, 0] 8\n",
"[0, 6, 6, 0, 0, 0, 0, 0] 4\n",
"[0, 9, 9, 0, 0, 0, 0, 0] 4\n",
"[0, 12, 12, 0, 0, 0, 0, 0] 8\n",
"[0, 8, 8, 0, 0, 0, 0, 0] 4\n",
"[0, 12, 12, 0, 0, 0, 0, 0] 8\n",
"[0, 10, 10, 0, 0, 0, 0, 0] 4\n",
"[0, 15, 15, 0, 0, 0, 0, 0] 8\n",
"[0, 12, 12, 0, 0, 0, 0, 0] 8\n",
"[0, 14, 14, 0, 0, 0, 0, 0] 8\n",
"[0, 16, 16, 0, 0, 0, 0, 0] 8\n",
"[0, 18, 18, 0, 0, 0, 0, 0] 8\n",
"[0, 20, 20, 0, 0, 0, 0, 0] 12\n",
"[0, 22, 22, 0, 0, 0, 0, 0] 12\n",
"[2, 0, 0, 2, 0, 0, 0, 0] 0\n",
"[3, 0, 0, 3, 0, 0, 0, 0] -4\n",
"[4, 0, 0, 4, 0, 0, 0, 0] 0\n",
"[5, 0, 0, 5, 0, 0, 0, 0] 0\n",
"[6, 0, 0, 6, 0, 0, 0, 0] 0\n",
"[7, 0, 0, 7, 0, 0, 0, 0] 0\n",
"[8, 0, 0, 8, 0, 0, 0, 0] -4\n",
"[9, 0, 0, 9, 0, 0, 0, 0] -4\n",
"[10, 0, 0, 10, 0, 0, 0, 0] 0\n",
"[11, 0, 0, 11, 0, 0, 0, 0] 0\n",
"[12, 0, 0, 12, 0, 0, 0, 0] 0\n",
"[13, 0, 0, 13, 0, 0, 0, 0] -4\n",
"[14, 0, 0, 14, 0, 0, 0, 0] -4\n",
"[15, 0, 0, 15, 0, 0, 0, 0] -4\n",
"[16, 0, 0, 16, 0, 0, 0, 0] 0\n",
"[17, 0, 0, 17, 0, 0, 0, 0] 0\n",
"[18, 0, 0, 18, 0, 0, 0, 0] -4\n",
"[19, 0, 0, 19, 0, 0, 0, 0] -4\n",
"[20, 0, 0, 20, 0, 0, 0, 0] -4\n",
"[21, 0, 0, 21, 0, 0, 0, 0] -4\n",
"[22, 0, 0, 22, 0, 0, 0, 0] -8\n",
"[2, 2, 0, 0, 0, 0, 0, 0] 0\n",
"[3, 3, 0, 0, 0, 0, 0, 0] -4\n",
"[4, 4, 0, 0, 0, 0, 0, 0] 0\n",
"[5, 5, 0, 0, 0, 0, 0, 0] 0\n",
"[6, 6, 0, 0, 0, 0, 0, 0] 0\n",
"[7, 7, 0, 0, 0, 0, 0, 0] 0\n",
"[8, 8, 0, 0, 0, 0, 0, 0] -4\n",
"[9, 9, 0, 0, 0, 0, 0, 0] -4\n",
"[10, 10, 0, 0, 0, 0, 0, 0] -4\n",
"[11, 11, 0, 0, 0, 0, 0, 0] -4\n",
"[12, 12, 0, 0, 0, 0, 0, 0] 0\n",
"[13, 13, 0, 0, 0, 0, 0, 0] -4\n",
"[14, 14, 0, 0, 0, 0, 0, 0] -4\n",
"[15, 15, 0, 0, 0, 0, 0, 0] -4\n",
"[16, 16, 0, 0, 0, 0, 0, 0] -4\n",
"[17, 17, 0, 0, 0, 0, 0, 0] -4\n",
"[18, 18, 0, 0, 0, 0, 0, 0] -8\n",
"[2, 2, 2, 2, 0, 0, 0, 0] 0\n",
"[3, 3, 3, 3, 0, 0, 0, 0] -4\n",
"[4, 4, 4, 4, 0, 0, 0, 0] 4\n",
"[5, 5, 5, 5, 0, 0, 0, 0] 4\n",
"[6, 6, 6, 6, 0, 0, 0, 0] 4\n",
"[7, 7, 7, 7, 0, 0, 0, 0] 4\n",
"[8, 8, 8, 8, 0, 0, 0, 0] 0\n",
"[9, 9, 9, 9, 0, 0, 0, 0] 0\n",
"[10, 10, 10, 10, 0, 0, 0, 0] 4\n",
"[11, 11, 11, 11, 0, 0, 0, 0] 4\n",
"[12, 12, 12, 12, 0, 0, 0, 0] 8\n",
"[13, 13, 13, 13, 0, 0, 0, 0] 4\n",
"[14, 14, 14, 14, 0, 0, 0, 0] 4\n",
"[15, 15, 15, 15, 0, 0, 0, 0] 4\n",
"[16, 16, 16, 16, 0, 0, 0, 0] 8\n",
"[17, 17, 17, 17, 0, 0, 0, 0] 8\n",
"[18, 18, 18, 18, 0, 0, 0, 0] 4\n",
"[19, 19, 19, 19, 0, 0, 0, 0] 8\n",
"[20, 20, 20, 20, 0, 0, 0, 0] 8\n",
"[21, 21, 21, 21, 0, 0, 0, 0] 8\n",
"[22, 22, 22, 22, 0, 0, 0, 0] 4\n",
"[23, 23, 23, 23, 0, 0, 0, 0] 8\n",
"[24, 24, 24, 24, 0, 0, 0, 0] 8\n",
"[25, 25, 25, 25, 0, 0, 0, 0] 8\n",
"[26, 26, 26, 26, 0, 0, 0, 0] 8\n",
"[27, 27, 27, 27, 0, 0, 0, 0] 8\n",
"[28, 28, 28, 28, 0, 0, 0, 0] 8\n",
"[29, 29, 29, 29, 0, 0, 0, 0] 12\n",
"[2, 4, 4, 2, 0, 0, 0, 0] 4\n",
"[3, 6, 6, 3, 0, 0, 0, 0] 0\n",
"[4, 8, 8, 4, 0, 0, 0, 0] 4\n",
"[5, 10, 10, 5, 0, 0, 0, 0] 4\n",
"[6, 12, 12, 6, 0, 0, 0, 0] 8\n",
"[7, 14, 14, 7, 0, 0, 0, 0] 8\n",
"[8, 16, 16, 8, 0, 0, 0, 0] 4\n",
"[9, 18, 18, 9, 0, 0, 0, 0] 4\n",
"[10, 20, 20, 10, 0, 0, 0, 0] 12\n",
"[2, 6, 6, 2, 0, 0, 0, 0] 4\n",
"[3, 9, 9, 3, 0, 0, 0, 0] 0\n",
"[4, 12, 12, 4, 0, 0, 0, 0] 8\n",
"[5, 15, 15, 5, 0, 0, 0, 0] 8\n",
"[6, 18, 18, 6, 0, 0, 0, 0] 8\n",
"[7, 21, 21, 7, 0, 0, 0, 0] 12\n",
"[2, 8, 8, 2, 0, 0, 0, 0] 4\n",
"[3, 12, 12, 3, 0, 0, 0, 0] 4\n",
"[4, 16, 16, 4, 0, 0, 0, 0] 8\n",
"[5, 20, 20, 5, 0, 0, 0, 0] 12\n",
"[2, 10, 10, 2, 0, 0, 0, 0] 4\n",
"[3, 15, 15, 3, 0, 0, 0, 0] 4\n",
"[4, 20, 20, 4, 0, 0, 0, 0] 12\n",
"[2, 12, 12, 2, 0, 0, 0, 0] 8\n",
"[3, 18, 18, 3, 0, 0, 0, 0] 4\n",
"[4, 24, 24, 4, 0, 0, 0, 0] 12\n",
"[2, 14, 14, 2, 0, 0, 0, 0] 8\n",
"[3, 21, 21, 3, 0, 0, 0, 0] 8\n",
"[4, 28, 28, 4, 0, 0, 0, 0] 16\n",
"[2, 16, 16, 2, 0, 0, 0, 0] 8\n",
"[3, 24, 24, 3, 0, 0, 0, 0] 8\n",
"[4, 32, 32, 4, 0, 0, 0, 0] 16\n",
"[2, 18, 18, 2, 0, 0, 0, 0] 8\n",
"[3, 27, 27, 3, 0, 0, 0, 0] 12\n",
"[2, 20, 20, 2, 0, 0, 0, 0] 12\n",
"[2, 22, 22, 2, 0, 0, 0, 0] 12\n",
"[2, 24, 24, 2, 0, 0, 0, 0] 12\n",
"[2, 26, 26, 2, 0, 0, 0, 0] 12\n",
"[2, 28, 28, 2, 0, 0, 0, 0] 16\n",
"[2, 30, 30, 2, 0, 0, 0, 0] 16\n",
"[2, 32, 32, 2, 0, 0, 0, 0] 16\n",
"[2, 34, 34, 2, 0, 0, 0, 0] 20\n",
"[2, 36, 36, 2, 0, 0, 0, 0] 20\n",
"[4, 4, 0, 0, 0, 0, 0, 0] 0\n",
"[6, 6, 0, 0, 0, 0, 0, 0] 0\n",
"[8, 8, 0, 0, 0, 0, 0, 0] -4\n",
"[10, 10, 0, 0, 0, 0, 0, 0] -4\n",
"[12, 12, 0, 0, 0, 0, 0, 0] 0\n",
"[14, 14, 0, 0, 0, 0, 0, 0] -4\n",
"[16, 16, 0, 0, 0, 0, 0, 0] -4\n",
"[18, 18, 0, 0, 0, 0, 0, 0] -8\n",
"[4, 4, 2, 2, 0, 0, 0, 0] 0\n",
"[6, 6, 3, 3, 0, 0, 0, 0] 0\n",
"[8, 8, 4, 4, 0, 0, 0, 0] 0\n",
"[10, 10, 5, 5, 0, 0, 0, 0] 0\n",
"[12, 12, 6, 6, 0, 0, 0, 0] 4\n",
"[14, 14, 7, 7, 0, 0, 0, 0] 0\n",
"[16, 16, 8, 8, 0, 0, 0, 0] 0\n",
"[18, 18, 9, 9, 0, 0, 0, 0] -4\n",
"[20, 20, 10, 10, 0, 0, 0, 0] 4\n",
"[22, 22, 11, 11, 0, 0, 0, 0] 0\n",
"[24, 24, 12, 12, 0, 0, 0, 0] 0\n",
"[26, 26, 13, 13, 0, 0, 0, 0] 0\n",
"[28, 28, 14, 14, 0, 0, 0, 0] 0\n",
"[30, 30, 15, 15, 0, 0, 0, 0] 0\n",
"[32, 32, 16, 16, 0, 0, 0, 0] 0\n",
"[34, 34, 17, 17, 0, 0, 0, 0] 4\n",
"[36, 36, 18, 18, 0, 0, 0, 0] 4\n",
"[38, 38, 19, 19, 0, 0, 0, 0] 0\n",
"[40, 40, 20, 20, 0, 0, 0, 0] 0\n",
"[42, 42, 21, 21, 0, 0, 0, 0] 0\n",
"[44, 44, 22, 22, 0, 0, 0, 0] 0\n",
"[46, 46, 23, 23, 0, 0, 0, 0] 4\n",
"[48, 48, 24, 24, 0, 0, 0, 0] 8\n",
"[50, 50, 25, 25, 0, 0, 0, 0] 4\n",
"[52, 52, 26, 26, 0, 0, 0, 0] 8\n",
"[54, 54, 27, 27, 0, 0, 0, 0] 8\n",
"[56, 56, 28, 28, 0, 0, 0, 0] 8\n",
"[58, 58, 29, 29, 0, 0, 0, 0] 12\n",
"[4, 48, 36, 2, 0, 0, 0, 0] 20\n",
"[4, 66, 32, 2, 0, 0, 0, 0] 20\n",
"[4, 74, 22, 2, 0, 0, 0, 0] 20\n",
"[4, 76, 28, 2, 0, 0, 0, 0] 28\n",
"[6, 6, 0, 0, 0, 0, 0, 0] 0\n",
"[9, 9, 0, 0, 0, 0, 0, 0] -4\n",
"[12, 12, 0, 0, 0, 0, 0, 0] 0\n",
"[15, 15, 0, 0, 0, 0, 0, 0] -4\n",
"[18, 18, 0, 0, 0, 0, 0, 0] -8\n",
"[6, 6, 2, 2, 0, 0, 0, 0] 0\n",
"[9, 9, 3, 3, 0, 0, 0, 0] -4\n",
"[12, 12, 4, 4, 0, 0, 0, 0] 4\n",
"[15, 15, 5, 5, 0, 0, 0, 0] 0\n",
"[18, 18, 6, 6, 0, 0, 0, 0] -4\n",
"[21, 21, 7, 7, 0, 0, 0, 0] 0\n",
"[24, 24, 8, 8, 0, 0, 0, 0] -4\n",
"[27, 27, 9, 9, 0, 0, 0, 0] -4\n",
"[30, 30, 10, 10, 0, 0, 0, 0] 0\n",
"[33, 33, 11, 11, 0, 0, 0, 0] -4\n",
"[36, 36, 12, 12, 0, 0, 0, 0] 0\n",
"[39, 39, 13, 13, 0, 0, 0, 0] -4\n",
"[42, 42, 14, 14, 0, 0, 0, 0] -4\n",
"[45, 45, 15, 15, 0, 0, 0, 0] -4\n",
"[48, 48, 16, 16, 0, 0, 0, 0] 4\n",
"[51, 51, 17, 17, 0, 0, 0, 0] 0\n",
"[54, 54, 18, 18, 0, 0, 0, 0] 4\n",
"[57, 57, 19, 19, 0, 0, 0, 0] 4\n",
"[60, 60, 20, 20, 0, 0, 0, 0] 4\n",
"[63, 63, 21, 21, 0, 0, 0, 0] 8\n",
"[66, 66, 22, 22, 0, 0, 0, 0] 8\n",
"[69, 69, 23, 23, 0, 0, 0, 0] 12\n",
"[6, 20, 6, 2, 0, 0, 0, 0] -4\n",
"[9, 30, 9, 3, 0, 0, 0, 0] -4\n",
"[12, 40, 12, 4, 0, 0, 0, 0] 8\n",
"[15, 50, 15, 5, 0, 0, 0, 0] 8\n",
"[18, 60, 18, 6, 0, 0, 0, 0] 12\n",
"[6, 22, 28, 2, 0, 0, 0, 0] 20\n",
"[6, 44, 24, 2, 0, 0, 0, 0] 16\n",
"[6, 56, 38, 2, 0, 0, 0, 0] 24\n",
"[6, 58, 26, 2, 0, 0, 0, 0] 16\n",
"[6, 62, 34, 2, 0, 0, 0, 0] 24\n",
"[8, 8, 0, 0, 0, 0, 0, 0] -4\n",
"[12, 12, 0, 0, 0, 0, 0, 0] 0\n",
"[16, 16, 0, 0, 0, 0, 0, 0] -4\n",
"[20, 20, 0, 0, 0, 0, 0, 0] -4\n",
"[24, 24, 0, 0, 0, 0, 0, 0] -8\n",
"[8, 8, 2, 2, 0, 0, 0, 0] -4\n",
"[12, 12, 3, 3, 0, 0, 0, 0] 0\n",
"[16, 16, 4, 4, 0, 0, 0, 0] 0\n",
"[20, 20, 5, 5, 0, 0, 0, 0] 0\n",
"[24, 24, 6, 6, 0, 0, 0, 0] -4\n",
"[28, 28, 7, 7, 0, 0, 0, 0] -4\n",
"[32, 32, 8, 8, 0, 0, 0, 0] -8\n",
"[36, 36, 9, 9, 0, 0, 0, 0] -4\n",
"[40, 40, 10, 10, 0, 0, 0, 0] -4\n",
"[44, 44, 11, 11, 0, 0, 0, 0] -4\n",
"[48, 48, 12, 12, 0, 0, 0, 0] 0\n",
"[52, 52, 13, 13, 0, 0, 0, 0] 0\n",
"[56, 56, 14, 14, 0, 0, 0, 0] 0\n",
"[60, 60, 15, 15, 0, 0, 0, 0] 0\n",
"[64, 64, 16, 16, 0, 0, 0, 0] 8\n",
"[68, 68, 17, 17, 0, 0, 0, 0] 8\n",
"[72, 72, 18, 18, 0, 0, 0, 0] 8\n",
"[76, 76, 19, 19, 0, 0, 0, 0] 12\n",
"[8, 16, 14, 2, 0, 0, 0, 0] 8\n",
"[12, 24, 21, 3, 0, 0, 0, 0] 16\n",
"[8, 34, 10, 2, 0, 0, 0, 0] 0\n",
"[12, 51, 15, 3, 0, 0, 0, 0] 8\n",
"[16, 68, 20, 4, 0, 0, 0, 0] 24\n",
"[8, 50, 38, 2, 0, 0, 0, 0] 20\n",
"[8, 72, 12, 2, 0, 0, 0, 0] 8\n",
"[12, 108, 18, 3, 0, 0, 0, 0] 112\n",
"[10, 10, 0, 0, 0, 0, 0, 0] -4\n",
"[15, 15, 0, 0, 0, 0, 0, 0] -4\n",
"[20, 20, 0, 0, 0, 0, 0, 0] -4\n",
"[25, 25, 0, 0, 0, 0, 0, 0] -8\n",
"[10, 10, 2, 2, 0, 0, 0, 0] -4\n",
"[15, 15, 3, 3, 0, 0, 0, 0] -4\n",
"[20, 20, 4, 4, 0, 0, 0, 0] 0\n",
"[25, 25, 5, 5, 0, 0, 0, 0] -4\n",
"[30, 30, 6, 6, 0, 0, 0, 0] -4\n",
"[35, 35, 7, 7, 0, 0, 0, 0] -4\n",
"[40, 40, 8, 8, 0, 0, 0, 0] -8\n",
"[45, 45, 9, 9, 0, 0, 0, 0] -8\n",
"[50, 50, 10, 10, 0, 0, 0, 0] -4\n",
"[55, 55, 11, 11, 0, 0, 0, 0] 0\n",
"[60, 60, 12, 12, 0, 0, 0, 0] 0\n",
"[65, 65, 13, 13, 0, 0, 0, 0] 0\n",
"[70, 70, 14, 14, 0, 0, 0, 0] 4\n",
"[75, 75, 15, 15, 0, 0, 0, 0] 4\n",
"[80, 80, 16, 16, 0, 0, 0, 0] 8\n",
"[85, 85, 17, 17, 0, 0, 0, 0] 12\n",
"[10, 14, 10, 2, 0, 0, 0, 0] 8\n",
"[15, 21, 15, 3, 0, 0, 0, 0] 12\n",
"[10, 34, 8, 2, 0, 0, 0, 0] 0\n",
"[15, 51, 12, 3, 0, 0, 0, 0] 4\n",
"[20, 68, 16, 4, 0, 0, 0, 0] 20\n",
"[10, 46, 32, 2, 0, 0, 0, 0] 24\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[10, 74, 20, 2, 0, 0, 0, 0] 24\n",
"[10, 78, 26, 2, 0, 0, 0, 0] 36\n",
"[12, 12, 0, 0, 0, 0, 0, 0] 0\n",
"[18, 18, 0, 0, 0, 0, 0, 0] -8\n",
"[12, 12, 2, 2, 0, 0, 0, 0] 0\n",
"[18, 18, 3, 3, 0, 0, 0, 0] -8\n",
"[24, 24, 4, 4, 0, 0, 0, 0] -4\n",
"[30, 30, 5, 5, 0, 0, 0, 0] -4\n",
"[36, 36, 6, 6, 0, 0, 0, 0] -4\n",
"[42, 42, 7, 7, 0, 0, 0, 0] -8\n",
"[48, 48, 8, 8, 0, 0, 0, 0] -4\n",
"[54, 54, 9, 9, 0, 0, 0, 0] -4\n",
"[60, 60, 10, 10, 0, 0, 0, 0] 0\n",
"[66, 66, 11, 11, 0, 0, 0, 0] 4\n",
"[72, 72, 12, 12, 0, 0, 0, 0] 4\n",
"[78, 78, 13, 13, 0, 0, 0, 0] 8\n",
"[84, 84, 14, 14, 0, 0, 0, 0] 8\n",
"[90, 90, 15, 15, 0, 0, 0, 0] 8\n",
"[96, 96, 16, 16, 0, 0, 0, 0] 8\n",
"[102, 102, 17, 17, 0, 0, 0, 0] 8\n",
"[108, 108, 18, 18, 0, 0, 0, 0] 4\n",
"[114, 114, 19, 19, 0, 0, 0, 0] 4\n",
"[120, 120, 20, 20, 0, 0, 0, 0] 0\n",
"[126, 126, 21, 21, 0, 0, 0, 0] 0\n",
"[132, 132, 22, 22, 0, 0, 0, 0] 4\n",
"[138, 138, 23, 23, 0, 0, 0, 0] 8\n",
"[144, 144, 24, 24, 0, 0, 0, 0] 8\n",
"[150, 150, 25, 25, 0, 0, 0, 0] 12\n",
"[12, 54, 28, 2, 0, 0, 0, 0] 24\n",
"[12, 58, 30, 2, 0, 0, 0, 0] 24\n",
"[12, 72, 8, 2, 0, 0, 0, 0] 8\n",
"[18, 108, 12, 3, 0, 0, 0, 0] 104\n",
"[12, 76, 18, 2, 0, 0, 0, 0] 28\n",
"[14, 14, 0, 0, 0, 0, 0, 0] -4\n",
"[21, 21, 0, 0, 0, 0, 0, 0] -4\n",
"[28, 28, 0, 0, 0, 0, 0, 0] -8\n",
"[14, 14, 2, 2, 0, 0, 0, 0] -4\n",
"[21, 21, 3, 3, 0, 0, 0, 0] -4\n",
"[28, 28, 4, 4, 0, 0, 0, 0] -4\n",
"[35, 35, 5, 5, 0, 0, 0, 0] -4\n",
"[42, 42, 6, 6, 0, 0, 0, 0] -8\n",
"[49, 49, 7, 7, 0, 0, 0, 0] -4\n",
"[56, 56, 8, 8, 0, 0, 0, 0] -4\n",
"[63, 63, 9, 9, 0, 0, 0, 0] 0\n",
"[70, 70, 10, 10, 0, 0, 0, 0] 4\n",
"[77, 77, 11, 11, 0, 0, 0, 0] 8\n",
"[84, 84, 12, 12, 0, 0, 0, 0] 8\n",
"[91, 91, 13, 13, 0, 0, 0, 0] 4\n",
"[98, 98, 14, 14, 0, 0, 0, 0] 4\n",
"[105, 105, 15, 15, 0, 0, 0, 0] 0\n",
"[112, 112, 16, 16, 0, 0, 0, 0] 4\n",
"[119, 119, 17, 17, 0, 0, 0, 0] 4\n",
"[126, 126, 18, 18, 0, 0, 0, 0] 0\n",
"[133, 133, 19, 19, 0, 0, 0, 0] 0\n",
"[140, 140, 20, 20, 0, 0, 0, 0] 4\n",
"[147, 147, 21, 21, 0, 0, 0, 0] 8\n",
"[154, 154, 22, 22, 0, 0, 0, 0] 12\n",
"[14, 16, 8, 2, 0, 0, 0, 0] 4\n",
"[21, 24, 12, 3, 0, 0, 0, 0] 8\n",
"[28, 32, 16, 4, 0, 0, 0, 0] 12\n",
"[14, 38, 16, 2, 0, 0, 0, 0] 12\n",
"[14, 42, 24, 2, 0, 0, 0, 0] 20\n",
"[14, 48, 28, 2, 0, 0, 0, 0] 24\n",
"[14, 54, 20, 2, 0, 0, 0, 0] 16\n",
"[14, 72, 26, 2, 0, 0, 0, 0] 28\n",
"[16, 16, 0, 0, 0, 0, 0, 0] -4\n",
"[24, 24, 0, 0, 0, 0, 0, 0] -8\n",
"[16, 16, 2, 2, 0, 0, 0, 0] -4\n",
"[24, 24, 3, 3, 0, 0, 0, 0] -8\n",
"[32, 32, 4, 4, 0, 0, 0, 0] -8\n",
"[40, 40, 5, 5, 0, 0, 0, 0] -8\n",
"[48, 48, 6, 6, 0, 0, 0, 0] -4\n",
"[56, 56, 7, 7, 0, 0, 0, 0] -4\n",
"[64, 64, 8, 8, 0, 0, 0, 0] 0\n",
"[72, 72, 9, 9, 0, 0, 0, 0] 0\n",
"[80, 80, 10, 10, 0, 0, 0, 0] 4\n",
"[88, 88, 11, 11, 0, 0, 0, 0] 8\n",
"[96, 96, 12, 12, 0, 0, 0, 0] 4\n",
"[104, 104, 13, 13, 0, 0, 0, 0] 4\n",
"[112, 112, 14, 14, 0, 0, 0, 0] 0\n",
"[120, 120, 15, 15, 0, 0, 0, 0] -4\n",
"[128, 128, 16, 16, 0, 0, 0, 0] 0\n",
"[136, 136, 17, 17, 0, 0, 0, 0] 4\n",
"[144, 144, 18, 18, 0, 0, 0, 0] 4\n",
"[152, 152, 19, 19, 0, 0, 0, 0] 8\n",
"[160, 160, 20, 20, 0, 0, 0, 0] 12\n",
"[16, 24, 18, 2, 0, 0, 0, 0] 16\n",
"[16, 38, 14, 2, 0, 0, 0, 0] 12\n",
"[16, 50, 16, 2, 0, 0, 0, 0] 12\n",
"[16, 60, 32, 2, 0, 0, 0, 0] 28\n",
"[16, 66, 28, 2, 0, 0, 0, 0] 28\n",
"[16, 74, 24, 2, 0, 0, 0, 0] 32\n",
"[18, 2, 4, 2, 0, 0, 0, 0] 12\n",
"[18, 18, 0, 0, 0, 0, 0, 0] -8\n",
"[18, 18, 2, 2, 0, 0, 0, 0] -8\n",
"[27, 27, 3, 3, 0, 0, 0, 0] -8\n",
"[36, 36, 4, 4, 0, 0, 0, 0] -4\n",
"[45, 45, 5, 5, 0, 0, 0, 0] -8\n",
"[54, 54, 6, 6, 0, 0, 0, 0] -4\n",
"[63, 63, 7, 7, 0, 0, 0, 0] 0\n",
"[72, 72, 8, 8, 0, 0, 0, 0] 0\n",
"[81, 81, 9, 9, 0, 0, 0, 0] 4\n",
"[90, 90, 10, 10, 0, 0, 0, 0] 8\n",
"[99, 99, 11, 11, 0, 0, 0, 0] 4\n",
"[108, 108, 12, 12, 0, 0, 0, 0] 0\n",
"[117, 117, 13, 13, 0, 0, 0, 0] 0\n",
"[126, 126, 14, 14, 0, 0, 0, 0] -4\n",
"[135, 135, 15, 15, 0, 0, 0, 0] 0\n",
"[144, 144, 16, 16, 0, 0, 0, 0] 4\n",
"[153, 153, 17, 17, 0, 0, 0, 0] 8\n",
"[162, 162, 18, 18, 0, 0, 0, 0] 12\n",
"[18, 24, 16, 2, 0, 0, 0, 0] 12\n",
"[18, 48, 18, 2, 0, 0, 0, 0] 16\n",
"[18, 76, 12, 2, 0, 0, 0, 0] 20\n",
"[18, 78, 28, 2, 0, 0, 0, 0] 40\n",
"[20, 10, 6, 2, 0, 0, 0, 0] 8\n",
"[30, 15, 9, 3, 0, 0, 0, 0] 8\n",
"[40, 20, 12, 4, 0, 0, 0, 0] 8\n",
"[50, 25, 15, 5, 0, 0, 0, 0] 8\n",
"[60, 30, 18, 6, 0, 0, 0, 0] 12\n",
"[20, 20, 0, 0, 0, 0, 0, 0] -4\n",
"[30, 30, 0, 0, 0, 0, 0, 0] -8\n",
"[20, 20, 2, 2, 0, 0, 0, 0] -4\n",
"[30, 30, 3, 3, 0, 0, 0, 0] -8\n",
"[40, 40, 4, 4, 0, 0, 0, 0] -8\n",
"[50, 50, 5, 5, 0, 0, 0, 0] -8\n",
"[60, 60, 6, 6, 0, 0, 0, 0] -4\n",
"[70, 70, 7, 7, 0, 0, 0, 0] 0\n",
"[80, 80, 8, 8, 0, 0, 0, 0] 0\n",
"[90, 90, 9, 9, 0, 0, 0, 0] 4\n",
"[100, 100, 10, 10, 0, 0, 0, 0] 4\n",
"[110, 110, 11, 11, 0, 0, 0, 0] 0\n",
"[120, 120, 12, 12, 0, 0, 0, 0] -4\n",
"[130, 130, 13, 13, 0, 0, 0, 0] 0\n",
"[140, 140, 14, 14, 0, 0, 0, 0] 0\n",
"[150, 150, 15, 15, 0, 0, 0, 0] 4\n",
"[160, 160, 16, 16, 0, 0, 0, 0] 12\n",
"[20, 54, 14, 2, 0, 0, 0, 0] 12\n",
"[20, 68, 24, 2, 0, 0, 0, 0] 28\n",
"[20, 74, 10, 2, 0, 0, 0, 0] 16\n",
"[20, 76, 20, 2, 0, 0, 0, 0] 32\n",
"[22, 22, 0, 0, 0, 0, 0, 0] -8\n",
"[22, 22, 2, 2, 0, 0, 0, 0] -8\n",
"[33, 33, 3, 3, 0, 0, 0, 0] -12\n",
"[22, 26, 14, 2, 0, 0, 0, 0] 8\n",
"[33, 39, 21, 3, 0, 0, 0, 0] 16\n",
"[22, 36, 22, 2, 0, 0, 0, 0] 20\n",
"[22, 74, 4, 2, 0, 0, 0, 0] 4\n",
"[33, 111, 6, 3, 0, 0, 0, 0] 108\n",
"[24, 16, 4, 2, 0, 0, 0, 0] 0\n",
"[36, 24, 6, 3, 0, 0, 0, 0] -4\n",
"[48, 32, 8, 4, 0, 0, 0, 0] 0\n",
"[60, 40, 10, 5, 0, 0, 0, 0] 4\n",
"[72, 48, 12, 6, 0, 0, 0, 0] 4\n",
"[84, 56, 14, 7, 0, 0, 0, 0] -8\n",
"[96, 64, 16, 8, 0, 0, 0, 0] -44\n",
"[24, 24, 0, 0, 0, 0, 0, 0] -8\n",
"[24, 24, 2, 2, 0, 0, 0, 0] -8\n",
"[36, 36, 3, 3, 0, 0, 0, 0] -8\n",
"[48, 48, 4, 4, 0, 0, 0, 0] -4\n",
"[60, 60, 5, 5, 0, 0, 0, 0] -4\n",
"[72, 72, 6, 6, 0, 0, 0, 0] 0\n",
"[84, 84, 7, 7, 0, 0, 0, 0] 4\n",
"[96, 96, 8, 8, 0, 0, 0, 0] 0\n",
"[108, 108, 9, 9, 0, 0, 0, 0] -4\n",
"[120, 120, 10, 10, 0, 0, 0, 0] -4\n",
"[132, 132, 11, 11, 0, 0, 0, 0] 0\n",
"[144, 144, 12, 12, 0, 0, 0, 0] 0\n",
"[156, 156, 13, 13, 0, 0, 0, 0] 4\n",
"[168, 168, 14, 14, 0, 0, 0, 0] 8\n",
"[180, 180, 15, 15, 0, 0, 0, 0] 4\n",
"[192, 192, 16, 16, 0, 0, 0, 0] 4\n",
"[204, 204, 17, 17, 0, 0, 0, 0] 0\n",
"[216, 216, 18, 18, 0, 0, 0, 0] 0\n",
"[228, 228, 19, 19, 0, 0, 0, 0] 8\n",
"[240, 240, 20, 20, 0, 0, 0, 0] 8\n",
"[252, 252, 21, 21, 0, 0, 0, 0] 8\n",
"[264, 264, 22, 22, 0, 0, 0, 0] 8\n",
"[276, 276, 23, 23, 0, 0, 0, 0] 8\n",
"[288, 288, 24, 24, 0, 0, 0, 0] 4\n",
"[300, 300, 25, 25, 0, 0, 0, 0] 4\n",
"[312, 312, 26, 26, 0, 0, 0, 0] 12\n",
"[24, 42, 14, 2, 0, 0, 0, 0] 12\n",
"[24, 44, 6, 2, 0, 0, 0, 0] 0\n",
"[36, 66, 9, 3, 0, 0, 0, 0] 4\n",
"[48, 88, 12, 4, 0, 0, 0, 0] 44\n",
"[24, 68, 20, 2, 0, 0, 0, 0] 24\n",
"[24, 74, 16, 2, 0, 0, 0, 0] 24\n",
"[26, 22, 12, 2, 0, 0, 0, 0] 12\n",
"[26, 26, 0, 0, 0, 0, 0, 0] -8\n",
"[26, 26, 2, 2, 0, 0, 0, 0] -8\n",
"[39, 39, 3, 3, 0, 0, 0, 0] -12\n",
"[26, 34, 22, 2, 0, 0, 0, 0] 24\n",
"[26, 58, 6, 2, 0, 0, 0, 0] 0\n",
"[39, 87, 9, 3, 0, 0, 0, 0] 32\n",
"[26, 70, 24, 2, 0, 0, 0, 0] 32\n",
"[26, 72, 14, 2, 0, 0, 0, 0] 20\n",
"[26, 78, 10, 2, 0, 0, 0, 0] 24\n",
"[28, 22, 6, 2, 0, 0, 0, 0] 0\n",
"[42, 33, 9, 3, 0, 0, 0, 0] -4\n",
"[56, 44, 12, 4, 0, 0, 0, 0] 8\n",
"[70, 55, 15, 5, 0, 0, 0, 0] 8\n",
"[84, 66, 18, 6, 0, 0, 0, 0] 0\n",
"[98, 77, 21, 7, 0, 0, 0, 0] -32\n",
"[28, 28, 0, 0, 0, 0, 0, 0] -8\n",
"[28, 28, 2, 2, 0, 0, 0, 0] -8\n",
"[42, 42, 3, 3, 0, 0, 0, 0] -12\n",
"[28, 48, 14, 2, 0, 0, 0, 0] 12\n",
"[28, 54, 12, 2, 0, 0, 0, 0] 8\n",
"[42, 81, 18, 3, 0, 0, 0, 0] 28\n",
"[28, 66, 16, 2, 0, 0, 0, 0] 16\n",
"[28, 76, 4, 2, 0, 0, 0, 0] 8\n",
"[42, 114, 6, 3, 0, 0, 0, 0] 116\n",
"[28, 78, 18, 2, 0, 0, 0, 0] 32\n",
"[30, 30, 0, 0, 0, 0, 0, 0] -8\n",
"[30, 30, 2, 2, 0, 0, 0, 0] -8\n",
"[45, 45, 3, 3, 0, 0, 0, 0] -12\n",
"[30, 36, 20, 2, 0, 0, 0, 0] 20\n",
"[30, 58, 12, 2, 0, 0, 0, 0] 8\n",
"[45, 87, 18, 3, 0, 0, 0, 0] 44\n",
"[32, 32, 0, 0, 0, 0, 0, 0] -12\n",
"[32, 32, 2, 2, 0, 0, 0, 0] -12\n",
"[32, 46, 10, 2, 0, 0, 0, 0] 4\n",
"[48, 69, 15, 3, 0, 0, 0, 0] 16\n",
"[32, 50, 22, 2, 0, 0, 0, 0] 16\n",
"[32, 60, 16, 2, 0, 0, 0, 0] 12\n",
"[32, 66, 4, 2, 0, 0, 0, 0] -4\n",
"[48, 99, 6, 3, 0, 0, 0, 0] 64\n",
"[32, 80, 20, 2, 0, 0, 0, 0] 32\n",
"[34, 34, 0, 0, 0, 0, 0, 0] -8\n",
"[34, 34, 2, 2, 0, 0, 0, 0] -8\n",
"[51, 51, 3, 3, 0, 0, 0, 0] -12\n",
"[34, 36, 12, 2, 0, 0, 0, 0] 8\n",
"[51, 54, 18, 3, 0, 0, 0, 0] 12\n",
"[34, 56, 18, 2, 0, 0, 0, 0] 16\n",
"[34, 62, 6, 2, 0, 0, 0, 0] 0\n",
"[51, 93, 9, 3, 0, 0, 0, 0] 48\n",
"[36, 32, 8, 2, 0, 0, 0, 0] 0\n",
"[54, 48, 12, 3, 0, 0, 0, 0] 8\n",
"[72, 64, 16, 4, 0, 0, 0, 0] 16\n",
"[36, 34, 14, 2, 0, 0, 0, 0] 12\n",
"[36, 36, 2, 2, 0, 0, 0, 0] -8\n",
"[54, 54, 3, 3, 0, 0, 0, 0] -8\n",
"[72, 72, 4, 4, 0, 0, 0, 0] 0\n",
"[90, 90, 5, 5, 0, 0, 0, 0] 4\n",
"[108, 108, 6, 6, 0, 0, 0, 0] -4\n",
"[126, 126, 7, 7, 0, 0, 0, 0] -8\n",
"[144, 144, 8, 8, 0, 0, 0, 0] -4\n",
"[162, 162, 9, 9, 0, 0, 0, 0] 4\n",
"[180, 180, 10, 10, 0, 0, 0, 0] 4\n",
"[198, 198, 11, 11, 0, 0, 0, 0] -4\n",
"[216, 216, 12, 12, 0, 0, 0, 0] -4\n",
"[234, 234, 13, 13, 0, 0, 0, 0] 4\n",
"[252, 252, 14, 14, 0, 0, 0, 0] 4\n",
"[270, 270, 15, 15, 0, 0, 0, 0] 4\n",
"[288, 288, 16, 16, 0, 0, 0, 0] 0\n",
"[306, 306, 17, 17, 0, 0, 0, 0] 4\n",
"[324, 324, 18, 18, 0, 0, 0, 0] 8\n",
"[342, 342, 19, 19, 0, 0, 0, 0] 8\n",
"[360, 360, 20, 20, 0, 0, 0, 0] 4\n",
"[378, 378, 21, 21, 0, 0, 0, 0] 0\n",
"[396, 396, 22, 22, 0, 0, 0, 0] 8\n",
"[414, 414, 23, 23, 0, 0, 0, 0] 16\n",
"[36, 48, 4, 2, 0, 0, 0, 0] -4\n",
"[54, 72, 6, 3, 0, 0, 0, 0] 4\n",
"[72, 96, 8, 4, 0, 0, 0, 0] 60\n",
"[36, 78, 12, 2, 0, 0, 0, 0] 24\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[38, 38, 0, 0, 0, 0, 0, 0] -12\n",
"[38, 38, 2, 2, 0, 0, 0, 0] -12\n",
"[38, 42, 18, 2, 0, 0, 0, 0] 12\n",
"[38, 50, 8, 2, 0, 0, 0, 0] -4\n",
"[57, 75, 12, 3, 0, 0, 0, 0] 20\n",
"[38, 56, 6, 2, 0, 0, 0, 0] -4\n",
"[57, 84, 9, 3, 0, 0, 0, 0] 28\n",
"[38, 68, 14, 2, 0, 0, 0, 0] 12\n",
"[40, 40, 0, 0, 0, 0, 0, 0] -12\n",
"[40, 40, 2, 2, 0, 0, 0, 0] -12\n",
"[40, 54, 18, 2, 0, 0, 0, 0] 12\n",
"[40, 62, 16, 2, 0, 0, 0, 0] 12\n",
"[40, 76, 14, 2, 0, 0, 0, 0] 20\n",
"[42, 38, 4, 2, 0, 0, 0, 0] -8\n",
"[63, 57, 6, 3, 0, 0, 0, 0] -4\n",
"[84, 76, 8, 4, 0, 0, 0, 0] 0\n",
"[105, 95, 10, 5, 0, 0, 0, 0] -28\n",
"[42, 42, 0, 0, 0, 0, 0, 0] -12\n",
"[42, 42, 2, 2, 0, 0, 0, 0] -12\n",
"[42, 74, 8, 2, 0, 0, 0, 0] 8\n",
"[63, 111, 12, 3, 0, 0, 0, 0] 120\n",
"[42, 80, 18, 2, 0, 0, 0, 0] 28\n",
"[44, 44, 2, 2, 0, 0, 0, 0] -12\n",
"[44, 66, 10, 2, 0, 0, 0, 0] 4\n",
"[66, 99, 15, 3, 0, 0, 0, 0] 80\n",
"[44, 68, 6, 2, 0, 0, 0, 0] 0\n",
"[66, 102, 9, 3, 0, 0, 0, 0] 84\n",
"[44, 80, 22, 2, 0, 0, 0, 0] 32\n",
"[44, 82, 12, 2, 0, 0, 0, 0] 24\n",
"[46, 46, 2, 2, 0, 0, 0, 0] -12\n",
"[46, 58, 16, 2, 0, 0, 0, 0] 8\n",
"[69, 87, 24, 3, 0, 0, 0, 0] 52\n",
"[46, 64, 18, 2, 0, 0, 0, 0] 16\n",
"[48, 18, 4, 2, 0, 0, 0, 0] -4\n",
"[72, 27, 6, 3, 0, 0, 0, 0] -4\n",
"[96, 36, 8, 4, 0, 0, 0, 0] -52\n",
"[48, 26, 6, 2, 0, 0, 0, 0] -4\n",
"[72, 39, 9, 3, 0, 0, 0, 0] 0\n",
"[96, 52, 12, 4, 0, 0, 0, 0] -48\n",
"[48, 28, 12, 2, 0, 0, 0, 0] 8\n",
"[72, 42, 18, 3, 0, 0, 0, 0] 12\n",
"[48, 36, 18, 2, 0, 0, 0, 0] 16\n",
"[48, 48, 2, 2, 0, 0, 0, 0] -8\n",
"[72, 72, 3, 3, 0, 0, 0, 0] -4\n",
"[96, 96, 4, 4, 0, 0, 0, 0] 0\n",
"[120, 120, 5, 5, 0, 0, 0, 0] -8\n",
"[144, 144, 6, 6, 0, 0, 0, 0] -4\n",
"[168, 168, 7, 7, 0, 0, 0, 0] 4\n",
"[192, 192, 8, 8, 0, 0, 0, 0] -4\n",
"[216, 216, 9, 9, 0, 0, 0, 0] -8\n",
"[240, 240, 10, 10, 0, 0, 0, 0] 4\n",
"[264, 264, 11, 11, 0, 0, 0, 0] 4\n",
"[288, 288, 12, 12, 0, 0, 0, 0] -4\n",
"[312, 312, 13, 13, 0, 0, 0, 0] 4\n",
"[336, 336, 14, 14, 0, 0, 0, 0] 8\n",
"[360, 360, 15, 15, 0, 0, 0, 0] 0\n",
"[384, 384, 16, 16, 0, 0, 0, 0] 4\n",
"[408, 408, 17, 17, 0, 0, 0, 0] 12\n",
"[48, 58, 20, 2, 0, 0, 0, 0] 16\n",
"[48, 66, 8, 2, 0, 0, 0, 0] 4\n",
"[72, 99, 12, 3, 0, 0, 0, 0] 72\n",
"[50, 30, 8, 2, 0, 0, 0, 0] 0\n",
"[75, 45, 12, 3, 0, 0, 0, 0] 0\n",
"[100, 60, 16, 4, 0, 0, 0, 0] -52\n",
"[50, 40, 10, 2, 0, 0, 0, 0] 4\n",
"[75, 60, 15, 3, 0, 0, 0, 0] 4\n",
"[100, 80, 20, 4, 0, 0, 0, 0] -32\n",
"[50, 50, 2, 2, 0, 0, 0, 0] -12\n",
"[50, 74, 18, 2, 0, 0, 0, 0] 24\n",
"[52, 36, 16, 2, 0, 0, 0, 0] 16\n",
"[52, 52, 2, 2, 0, 0, 0, 0] -8\n",
"[78, 78, 3, 3, 0, 0, 0, 0] 0\n",
"[104, 104, 4, 4, 0, 0, 0, 0] 0\n",
"[130, 130, 5, 5, 0, 0, 0, 0] -4\n",
"[156, 156, 6, 6, 0, 0, 0, 0] 0\n",
"[182, 182, 7, 7, 0, 0, 0, 0] 0\n",
"[208, 208, 8, 8, 0, 0, 0, 0] -8\n",
"[234, 234, 9, 9, 0, 0, 0, 0] 0\n",
"[260, 260, 10, 10, 0, 0, 0, 0] 4\n",
"[286, 286, 11, 11, 0, 0, 0, 0] -4\n",
"[312, 312, 12, 12, 0, 0, 0, 0] 4\n",
"[338, 338, 13, 13, 0, 0, 0, 0] 8\n",
"[364, 364, 14, 14, 0, 0, 0, 0] -4\n",
"[390, 390, 15, 15, 0, 0, 0, 0] 0\n",
"[416, 416, 16, 16, 0, 0, 0, 0] 12\n",
"[52, 64, 20, 2, 0, 0, 0, 0] 24\n",
"[52, 78, 8, 2, 0, 0, 0, 0] 20\n",
"[54, 20, 12, 2, 0, 0, 0, 0] 12\n",
"[54, 28, 14, 2, 0, 0, 0, 0] 12\n",
"[54, 40, 4, 2, 0, 0, 0, 0] -4\n",
"[81, 60, 6, 3, 0, 0, 0, 0] -12\n",
"[54, 54, 2, 2, 0, 0, 0, 0] -8\n",
"[81, 81, 3, 3, 0, 0, 0, 0] 0\n",
"[108, 108, 4, 4, 0, 0, 0, 0] -4\n",
"[135, 135, 5, 5, 0, 0, 0, 0] -4\n",
"[162, 162, 6, 6, 0, 0, 0, 0] 4\n",
"[189, 189, 7, 7, 0, 0, 0, 0] -4\n",
"[216, 216, 8, 8, 0, 0, 0, 0] -8\n",
"[243, 243, 9, 9, 0, 0, 0, 0] 4\n",
"[270, 270, 10, 10, 0, 0, 0, 0] 4\n",
"[297, 297, 11, 11, 0, 0, 0, 0] 0\n",
"[324, 324, 12, 12, 0, 0, 0, 0] 4\n",
"[351, 351, 13, 13, 0, 0, 0, 0] 4\n",
"[378, 378, 14, 14, 0, 0, 0, 0] -4\n",
"[405, 405, 15, 15, 0, 0, 0, 0] 4\n",
"[432, 432, 16, 16, 0, 0, 0, 0] 8\n",
"[459, 459, 17, 17, 0, 0, 0, 0] 0\n",
"[486, 486, 18, 18, 0, 0, 0, 0] 12\n",
"[56, 24, 10, 2, 0, 0, 0, 0] 4\n",
"[84, 36, 15, 3, 0, 0, 0, 0] -4\n",
"[112, 48, 20, 4, 0, 0, 0, 0] -96\n",
"[56, 34, 4, 2, 0, 0, 0, 0] -4\n",
"[84, 51, 6, 3, 0, 0, 0, 0] -20\n",
"[56, 56, 2, 2, 0, 0, 0, 0] -8\n",
"[84, 84, 3, 3, 0, 0, 0, 0] 0\n",
"[112, 112, 4, 4, 0, 0, 0, 0] -4\n",
"[140, 140, 5, 5, 0, 0, 0, 0] -4\n",
"[168, 168, 6, 6, 0, 0, 0, 0] 4\n",
"[196, 196, 7, 7, 0, 0, 0, 0] -4\n",
"[224, 224, 8, 8, 0, 0, 0, 0] -4\n",
"[252, 252, 9, 9, 0, 0, 0, 0] 0\n",
"[280, 280, 10, 10, 0, 0, 0, 0] 0\n",
"[308, 308, 11, 11, 0, 0, 0, 0] 0\n",
"[336, 336, 12, 12, 0, 0, 0, 0] 8\n",
"[364, 364, 13, 13, 0, 0, 0, 0] -4\n",
"[392, 392, 14, 14, 0, 0, 0, 0] 0\n",
"[420, 420, 15, 15, 0, 0, 0, 0] 8\n",
"[448, 448, 16, 16, 0, 0, 0, 0] 0\n",
"[476, 476, 17, 17, 0, 0, 0, 0] 4\n",
"[504, 504, 18, 18, 0, 0, 0, 0] 12\n",
"[58, 30, 14, 2, 0, 0, 0, 0] 12\n",
"[58, 42, 8, 2, 0, 0, 0, 0] 4\n",
"[87, 63, 12, 3, 0, 0, 0, 0] -16\n",
"[58, 58, 2, 2, 0, 0, 0, 0] -8\n",
"[87, 87, 3, 3, 0, 0, 0, 0] 0\n",
"[116, 116, 4, 4, 0, 0, 0, 0] -8\n",
"[145, 145, 5, 5, 0, 0, 0, 0] 0\n",
"[174, 174, 6, 6, 0, 0, 0, 0] 0\n",
"[203, 203, 7, 7, 0, 0, 0, 0] -8\n",
"[232, 232, 8, 8, 0, 0, 0, 0] 0\n",
"[261, 261, 9, 9, 0, 0, 0, 0] 4\n",
"[290, 290, 10, 10, 0, 0, 0, 0] -4\n",
"[319, 319, 11, 11, 0, 0, 0, 0] 4\n",
"[348, 348, 12, 12, 0, 0, 0, 0] 4\n",
"[377, 377, 13, 13, 0, 0, 0, 0] -4\n",
"[406, 406, 14, 14, 0, 0, 0, 0] 4\n",
"[435, 435, 15, 15, 0, 0, 0, 0] 4\n",
"[464, 464, 16, 16, 0, 0, 0, 0] 4\n",
"[493, 493, 17, 17, 0, 0, 0, 0] 12\n",
"[58, 62, 22, 2, 0, 0, 0, 0] 24\n",
"[58, 78, 20, 2, 0, 0, 0, 0] 36\n",
"[60, 48, 6, 2, 0, 0, 0, 0] 0\n",
"[90, 72, 9, 3, 0, 0, 0, 0] -24\n",
"[60, 58, 10, 2, 0, 0, 0, 0] 4\n",
"[90, 87, 15, 3, 0, 0, 0, 0] 12\n",
"[60, 60, 2, 2, 0, 0, 0, 0] -8\n",
"[90, 90, 3, 3, 0, 0, 0, 0] 0\n",
"[120, 120, 4, 4, 0, 0, 0, 0] -8\n",
"[150, 150, 5, 5, 0, 0, 0, 0] 0\n",
"[180, 180, 6, 6, 0, 0, 0, 0] 0\n",
"[210, 210, 7, 7, 0, 0, 0, 0] -8\n",
"[240, 240, 8, 8, 0, 0, 0, 0] 0\n",
"[270, 270, 9, 9, 0, 0, 0, 0] 0\n",
"[300, 300, 10, 10, 0, 0, 0, 0] -4\n",
"[330, 330, 11, 11, 0, 0, 0, 0] 8\n",
"[360, 360, 12, 12, 0, 0, 0, 0] 0\n",
"[390, 390, 13, 13, 0, 0, 0, 0] 0\n",
"[420, 420, 14, 14, 0, 0, 0, 0] 8\n",
"[450, 450, 15, 15, 0, 0, 0, 0] 0\n",
"[480, 480, 16, 16, 0, 0, 0, 0] 4\n",
"[510, 510, 17, 17, 0, 0, 0, 0] 12\n",
"[62, 62, 2, 2, 0, 0, 0, 0] -4\n",
"[93, 93, 3, 3, 0, 0, 0, 0] -4\n",
"[124, 124, 4, 4, 0, 0, 0, 0] -8\n",
"[155, 155, 5, 5, 0, 0, 0, 0] 0\n",
"[186, 186, 6, 6, 0, 0, 0, 0] 0\n",
"[217, 217, 7, 7, 0, 0, 0, 0] -8\n",
"[248, 248, 8, 8, 0, 0, 0, 0] 4\n",
"[279, 279, 9, 9, 0, 0, 0, 0] -4\n",
"[310, 310, 10, 10, 0, 0, 0, 0] 0\n",
"[341, 341, 11, 11, 0, 0, 0, 0] 4\n",
"[372, 372, 12, 12, 0, 0, 0, 0] -4\n",
"[403, 403, 13, 13, 0, 0, 0, 0] 8\n",
"[434, 434, 14, 14, 0, 0, 0, 0] 4\n",
"[465, 465, 15, 15, 0, 0, 0, 0] -4\n",
"[496, 496, 16, 16, 0, 0, 0, 0] 12\n",
"[62, 64, 16, 2, 0, 0, 0, 0] 20\n",
"[62, 70, 8, 2, 0, 0, 0, 0] 12\n",
"[62, 72, 4, 2, 0, 0, 0, 0] 4\n",
"[93, 108, 6, 3, 0, 0, 0, 0] 52\n",
"[64, 12, 6, 2, 0, 0, 0, 0] 8\n",
"[96, 18, 9, 3, 0, 0, 0, 0] -52\n",
"[64, 46, 4, 2, 0, 0, 0, 0] -4\n",
"[96, 69, 6, 3, 0, 0, 0, 0] -52\n",
"[64, 50, 20, 2, 0, 0, 0, 0] 16\n",
"[64, 54, 22, 2, 0, 0, 0, 0] 20\n",
"[64, 70, 12, 2, 0, 0, 0, 0] 16\n",
"[66, 32, 18, 2, 0, 0, 0, 0] 16\n",
"[66, 42, 20, 2, 0, 0, 0, 0] 20\n",
"[66, 52, 26, 2, 0, 0, 0, 0] 24\n",
"[66, 60, 24, 2, 0, 0, 0, 0] 24\n",
"[68, 38, 12, 2, 0, 0, 0, 0] 8\n",
"[102, 57, 18, 3, 0, 0, 0, 0] -64\n",
"[68, 46, 22, 2, 0, 0, 0, 0] 20\n",
"[68, 66, 20, 2, 0, 0, 0, 0] 20\n",
"[68, 68, 2, 2, 0, 0, 0, 0] -4\n",
"[102, 102, 3, 3, 0, 0, 0, 0] -4\n",
"[136, 136, 4, 4, 0, 0, 0, 0] -4\n",
"[170, 170, 5, 5, 0, 0, 0, 0] 4\n",
"[204, 204, 6, 6, 0, 0, 0, 0] -8\n",
"[238, 238, 7, 7, 0, 0, 0, 0] 0\n",
"[272, 272, 8, 8, 0, 0, 0, 0] -4\n",
"[306, 306, 9, 9, 0, 0, 0, 0] -4\n",
"[340, 340, 10, 10, 0, 0, 0, 0] 4\n",
"[374, 374, 11, 11, 0, 0, 0, 0] -4\n",
"[408, 408, 12, 12, 0, 0, 0, 0] 8\n",
"[442, 442, 13, 13, 0, 0, 0, 0] 0\n",
"[476, 476, 14, 14, 0, 0, 0, 0] 0\n",
"[510, 510, 15, 15, 0, 0, 0, 0] 8\n",
"[544, 544, 16, 16, 0, 0, 0, 0] 0\n",
"[578, 578, 17, 17, 0, 0, 0, 0] 8\n",
"[612, 612, 18, 18, 0, 0, 0, 0] 4\n",
"[646, 646, 19, 19, 0, 0, 0, 0] 4\n",
"[680, 680, 20, 20, 0, 0, 0, 0] 8\n",
"[714, 714, 21, 21, 0, 0, 0, 0] 0\n",
"[748, 748, 22, 22, 0, 0, 0, 0] 12\n",
"[70, 48, 8, 2, 0, 0, 0, 0] 0\n",
"[105, 72, 12, 3, 0, 0, 0, 0] -76\n",
"[70, 64, 14, 2, 0, 0, 0, 0] 12\n",
"[70, 70, 2, 2, 0, 0, 0, 0] -4\n",
"[105, 105, 3, 3, 0, 0, 0, 0] -8\n",
"[140, 140, 4, 4, 0, 0, 0, 0] -4\n",
"[175, 175, 5, 5, 0, 0, 0, 0] 0\n",
"[210, 210, 6, 6, 0, 0, 0, 0] -8\n",
"[245, 245, 7, 7, 0, 0, 0, 0] 4\n",
"[280, 280, 8, 8, 0, 0, 0, 0] -4\n",
"[315, 315, 9, 9, 0, 0, 0, 0] 0\n",
"[350, 350, 10, 10, 0, 0, 0, 0] 0\n",
"[385, 385, 11, 11, 0, 0, 0, 0] 0\n",
"[420, 420, 12, 12, 0, 0, 0, 0] 8\n",
"[455, 455, 13, 13, 0, 0, 0, 0] -4\n",
"[490, 490, 14, 14, 0, 0, 0, 0] 4\n",
"[525, 525, 15, 15, 0, 0, 0, 0] 0\n",
"[560, 560, 16, 16, 0, 0, 0, 0] 8\n",
"[595, 595, 17, 17, 0, 0, 0, 0] 8\n",
"[630, 630, 18, 18, 0, 0, 0, 0] 4\n",
"[665, 665, 19, 19, 0, 0, 0, 0] 12\n",
"[72, 26, 12, 2, 0, 0, 0, 0] 4\n",
"[108, 39, 18, 3, 0, 0, 0, 0] -84\n",
"[72, 30, 6, 2, 0, 0, 0, 0] -4\n",
"[108, 45, 9, 3, 0, 0, 0, 0] -96\n",
"[72, 36, 10, 2, 0, 0, 0, 0] 4\n",
"[108, 54, 15, 3, 0, 0, 0, 0] -88\n",
"[72, 46, 16, 2, 0, 0, 0, 0] 12\n",
"[72, 62, 18, 2, 0, 0, 0, 0] 16\n",
"[72, 64, 24, 2, 0, 0, 0, 0] 24\n",
"[72, 72, 2, 2, 0, 0, 0, 0] -4\n",
"[108, 108, 3, 3, 0, 0, 0, 0] -8\n",
"[144, 144, 4, 4, 0, 0, 0, 0] -4\n",
"[180, 180, 5, 5, 0, 0, 0, 0] 0\n",
"[216, 216, 6, 6, 0, 0, 0, 0] -8\n",
"[252, 252, 7, 7, 0, 0, 0, 0] 0\n",
"[288, 288, 8, 8, 0, 0, 0, 0] -8\n",
"[324, 324, 9, 9, 0, 0, 0, 0] 0\n",
"[360, 360, 10, 10, 0, 0, 0, 0] 0\n",
"[396, 396, 11, 11, 0, 0, 0, 0] 4\n",
"[432, 432, 12, 12, 0, 0, 0, 0] 4\n",
"[468, 468, 13, 13, 0, 0, 0, 0] 0\n",
"[504, 504, 14, 14, 0, 0, 0, 0] 8\n",
"[540, 540, 15, 15, 0, 0, 0, 0] -4\n",
"[576, 576, 16, 16, 0, 0, 0, 0] 12\n",
"[74, 14, 6, 2, 0, 0, 0, 0] 0\n",
"[111, 21, 9, 3, 0, 0, 0, 0] -108\n",
"[74, 22, 18, 2, 0, 0, 0, 0] 12\n",
"[74, 48, 22, 2, 0, 0, 0, 0] 16\n",
"[74, 54, 10, 2, 0, 0, 0, 0] 0\n",
"[111, 81, 15, 3, 0, 0, 0, 0] -84\n",
"[74, 60, 28, 2, 0, 0, 0, 0] 20\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[74, 82, 16, 2, 0, 0, 0, 0] 28\n",
"[76, 12, 4, 2, 0, 0, 0, 0] 0\n",
"[114, 18, 6, 3, 0, 0, 0, 0] -124\n",
"[76, 18, 14, 2, 0, 0, 0, 0] 8\n",
"[114, 27, 21, 3, 0, 0, 0, 0] -104\n",
"[76, 28, 18, 2, 0, 0, 0, 0] 12\n",
"[76, 40, 12, 2, 0, 0, 0, 0] 4\n",
"[114, 60, 18, 3, 0, 0, 0, 0] -108\n",
"[76, 60, 22, 2, 0, 0, 0, 0] 16\n",
"[76, 62, 8, 2, 0, 0, 0, 0] 0\n",
"[114, 93, 12, 3, 0, 0, 0, 0] -68\n",
"[76, 66, 24, 2, 0, 0, 0, 0] 20\n",
"[76, 74, 6, 2, 0, 0, 0, 0] 4\n",
"[114, 111, 9, 3, 0, 0, 0, 0] -8\n",
"[152, 148, 12, 4, 0, 0, 0, 0] -8\n",
"[190, 185, 15, 5, 0, 0, 0, 0] -24\n",
"[78, 28, 4, 2, 0, 0, 0, 0] -12\n",
"[78, 32, 16, 2, 0, 0, 0, 0] 4\n",
"[117, 48, 24, 3, 0, 0, 0, 0] -116\n",
"[78, 36, 14, 2, 0, 0, 0, 0] 4\n",
"[117, 54, 21, 3, 0, 0, 0, 0] -120\n",
"[78, 72, 10, 2, 0, 0, 0, 0] 4\n",
"[117, 108, 15, 3, 0, 0, 0, 0] -28\n",
"[80, 22, 8, 2, 0, 0, 0, 0] -8\n",
"[120, 33, 12, 3, 0, 0, 0, 0] -148\n",
"[80, 26, 16, 2, 0, 0, 0, 0] 0\n",
"[120, 39, 24, 3, 0, 0, 0, 0] -132\n",
"[80, 42, 4, 2, 0, 0, 0, 0] -16\n",
"[80, 46, 6, 2, 0, 0, 0, 0] -12\n",
"[82, 12, 8, 2, 0, 0, 0, 0] 0\n",
"[123, 18, 12, 3, 0, 0, 0, 0] -156\n",
"[82, 38, 6, 2, 0, 0, 0, 0] -12\n",
"[82, 44, 14, 2, 0, 0, 0, 0] 0\n",
"[123, 66, 21, 3, 0, 0, 0, 0] -144\n",
"[82, 56, 20, 2, 0, 0, 0, 0] 8\n",
"[123, 84, 30, 3, 0, 0, 0, 0] -116\n",
"[82, 80, 26, 2, 0, 0, 0, 0] 28\n",
verbose option added
2020-11-19 06:47:52 +01:00
"\n",
"OK\n",
"[0, 0, 0, 0, 0, 0, 2, 2] 0\n",
"[0, 0, 0, 0, 0, 0, 3, 3] 0\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 0, 0, 4, 4] 0\n",
"[0, 0, 0, 0, 0, 0, 5, 5] 0\n",
"[0, 0, 0, 0, 0, 0, 6, 6] 0\n",
"[0, 0, 0, 0, 0, 0, 7, 7] 0\n",
"[0, 0, 0, 0, 0, 0, 8, 8] 0\n",
"[0, 0, 0, 0, 0, 0, 9, 9] 0\n",
"[0, 0, 0, 0, 0, 0, 10, 10] 4\n",
"[0, 0, 0, 0, 0, 0, 11, 11] 4\n",
"[0, 0, 0, 0, 0, 0, 12, 12] 0\n",
"[0, 0, 0, 0, 0, 0, 13, 13] 0\n",
"[0, 0, 0, 0, 0, 0, 14, 14] 0\n",
"[0, 0, 0, 0, 0, 0, 15, 15] 0\n",
"[0, 0, 0, 0, 0, 0, 16, 16] 4\n",
"[0, 0, 0, 0, 0, 0, 17, 17] 4\n",
"[0, 0, 0, 0, 0, 0, 18, 18] 4\n",
"[0, 0, 0, 0, 0, 0, 19, 19] 4\n",
"[0, 0, 0, 0, 0, 0, 20, 20] 0\n",
"[0, 0, 0, 0, 0, 0, 21, 21] 0\n",
"[0, 0, 0, 0, 0, 0, 22, 22] 4\n",
"[0, 0, 0, 0, 0, 0, 23, 23] 4\n",
"[0, 0, 0, 0, 0, 0, 24, 24] 4\n",
"[0, 0, 0, 0, 0, 0, 25, 25] 4\n",
"[0, 0, 0, 0, 0, 0, 26, 26] 4\n",
"[0, 0, 0, 0, 0, 0, 27, 27] 4\n",
"[0, 0, 0, 0, 0, 0, 28, 28] 4\n",
"[0, 0, 0, 0, 0, 0, 29, 29] 4\n",
"[0, 0, 0, 0, 0, 0, 30, 30] 4\n",
"[0, 0, 0, 0, 0, 0, 31, 31] 4\n",
"[0, 0, 0, 0, 0, 0, 32, 32] 4\n",
"[0, 0, 0, 0, 0, 0, 33, 33] 4\n",
"[0, 0, 0, 0, 0, 0, 34, 34] 8\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 0, 2, 2, 0] 0\n",
"[0, 0, 0, 0, 0, 3, 3, 0] 0\n",
"[0, 0, 0, 0, 0, 4, 4, 0] -4\n",
"[0, 0, 0, 0, 0, 5, 5, 0] -4\n",
"[0, 0, 0, 0, 0, 6, 6, 0] -4\n",
"[0, 0, 0, 0, 0, 7, 7, 0] -4\n",
"[0, 0, 0, 0, 0, 8, 8, 0] -4\n",
"[0, 0, 0, 0, 0, 9, 9, 0] -4\n",
"[0, 0, 0, 0, 0, 10, 10, 0] -4\n",
"[0, 0, 0, 0, 0, 11, 11, 0] -4\n",
"[0, 0, 0, 0, 0, 12, 12, 0] -8\n",
"[0, 0, 0, 0, 0, 4, 4, 0] -4\n",
"[0, 0, 0, 0, 0, 6, 6, 0] -4\n",
"[0, 0, 0, 0, 0, 8, 8, 0] -4\n",
"[0, 0, 0, 0, 0, 10, 10, 0] -4\n",
"[0, 0, 0, 0, 0, 12, 12, 0] -8\n",
"[0, 0, 0, 0, 0, 6, 6, 0] -4\n",
"[0, 0, 0, 0, 0, 9, 9, 0] -4\n",
"[0, 0, 0, 0, 0, 12, 12, 0] -8\n",
"[0, 0, 0, 0, 0, 8, 8, 0] -4\n",
"[0, 0, 0, 0, 0, 12, 12, 0] -8\n",
"[0, 0, 0, 0, 0, 10, 10, 0] -4\n",
"[0, 0, 0, 0, 0, 15, 15, 0] -8\n",
"[0, 0, 0, 0, 0, 12, 12, 0] -8\n",
"[0, 0, 0, 0, 0, 14, 14, 0] -8\n",
"[0, 0, 0, 0, 0, 16, 16, 0] -8\n",
"[0, 0, 0, 0, 0, 18, 18, 0] -8\n",
"[0, 0, 0, 0, 0, 20, 20, 0] -12\n",
"[0, 0, 0, 0, 0, 22, 22, 0] -12\n",
"[0, 0, 0, 0, 2, 0, 0, 2] 0\n",
"[0, 0, 0, 0, 3, 0, 0, 3] 0\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 4, 0, 0, 4] 4\n",
"[0, 0, 0, 0, 5, 0, 0, 5] 0\n",
"[0, 0, 0, 0, 6, 0, 0, 6] 0\n",
"[0, 0, 0, 0, 7, 0, 0, 7] 0\n",
"[0, 0, 0, 0, 8, 0, 0, 8] 0\n",
"[0, 0, 0, 0, 9, 0, 0, 9] 0\n",
"[0, 0, 0, 0, 10, 0, 0, 10] 4\n",
"[0, 0, 0, 0, 11, 0, 0, 11] 4\n",
"[0, 0, 0, 0, 12, 0, 0, 12] 4\n",
"[0, 0, 0, 0, 13, 0, 0, 13] 4\n",
"[0, 0, 0, 0, 14, 0, 0, 14] 4\n",
"[0, 0, 0, 0, 15, 0, 0, 15] 0\n",
"[0, 0, 0, 0, 16, 0, 0, 16] 4\n",
"[0, 0, 0, 0, 17, 0, 0, 17] 4\n",
"[0, 0, 0, 0, 18, 0, 0, 18] 4\n",
"[0, 0, 0, 0, 19, 0, 0, 19] 4\n",
"[0, 0, 0, 0, 20, 0, 0, 20] 4\n",
"[0, 0, 0, 0, 21, 0, 0, 21] 4\n",
"[0, 0, 0, 0, 22, 0, 0, 22] 8\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 2, 2, 0, 0] 0\n",
"[0, 0, 0, 0, 3, 3, 0, 0] 0\n",
"[0, 0, 0, 0, 4, 4, 0, 0] 0\n",
"[0, 0, 0, 0, 5, 5, 0, 0] -4\n",
"[0, 0, 0, 0, 6, 6, 0, 0] -4\n",
"[0, 0, 0, 0, 7, 7, 0, 0] -4\n",
"[0, 0, 0, 0, 8, 8, 0, 0] -4\n",
"[0, 0, 0, 0, 9, 9, 0, 0] -4\n",
"[0, 0, 0, 0, 10, 10, 0, 0] -4\n",
"[0, 0, 0, 0, 11, 11, 0, 0] -4\n",
"[0, 0, 0, 0, 12, 12, 0, 0] -4\n",
"[0, 0, 0, 0, 13, 13, 0, 0] -4\n",
"[0, 0, 0, 0, 14, 14, 0, 0] -4\n",
"[0, 0, 0, 0, 15, 15, 0, 0] -8\n",
"[0, 0, 0, 0, 2, 2, 2, 2] 0\n",
"[0, 0, 0, 0, 3, 3, 3, 3] 0\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 4, 4, 4, 4] 0\n",
"[0, 0, 0, 0, 5, 5, 5, 5] -4\n",
"[0, 0, 0, 0, 6, 6, 6, 6] -4\n",
"[0, 0, 0, 0, 7, 7, 7, 7] -4\n",
"[0, 0, 0, 0, 8, 8, 8, 8] -4\n",
"[0, 0, 0, 0, 9, 9, 9, 9] -4\n",
"[0, 0, 0, 0, 10, 10, 10, 10] 0\n",
"[0, 0, 0, 0, 11, 11, 11, 11] 0\n",
"[0, 0, 0, 0, 12, 12, 12, 12] -4\n",
"[0, 0, 0, 0, 13, 13, 13, 13] -4\n",
"[0, 0, 0, 0, 14, 14, 14, 14] -4\n",
"[0, 0, 0, 0, 15, 15, 15, 15] -8\n",
"[0, 0, 0, 0, 16, 16, 16, 16] -4\n",
"[0, 0, 0, 0, 17, 17, 17, 17] -4\n",
"[0, 0, 0, 0, 18, 18, 18, 18] -4\n",
"[0, 0, 0, 0, 19, 19, 19, 19] -4\n",
"[0, 0, 0, 0, 20, 20, 20, 20] -8\n",
"[0, 0, 0, 0, 21, 21, 21, 21] -8\n",
"[0, 0, 0, 0, 22, 22, 22, 22] -4\n",
"[0, 0, 0, 0, 23, 23, 23, 23] -4\n",
"[0, 0, 0, 0, 24, 24, 24, 24] -8\n",
"[0, 0, 0, 0, 25, 25, 25, 25] -8\n",
"[0, 0, 0, 0, 26, 26, 26, 26] -8\n",
"[0, 0, 0, 0, 27, 27, 27, 27] -8\n",
"[0, 0, 0, 0, 28, 28, 28, 28] -8\n",
"[0, 0, 0, 0, 29, 29, 29, 29] -8\n",
"[0, 0, 0, 0, 30, 30, 30, 30] -8\n",
"[0, 0, 0, 0, 31, 31, 31, 31] -8\n",
"[0, 0, 0, 0, 32, 32, 32, 32] -8\n",
"[0, 0, 0, 0, 33, 33, 33, 33] -12\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 2, 4, 4, 2] -4\n",
"[0, 0, 0, 0, 3, 6, 6, 3] -4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 4, 8, 8, 4] 0\n",
"[0, 0, 0, 0, 5, 10, 10, 5] -4\n",
"[0, 0, 0, 0, 6, 12, 12, 6] -8\n",
"[0, 0, 0, 0, 7, 14, 14, 7] -8\n",
"[0, 0, 0, 0, 8, 16, 16, 8] -8\n",
"[0, 0, 0, 0, 9, 18, 18, 9] -8\n",
"[0, 0, 0, 0, 10, 20, 20, 10] -8\n",
"[0, 0, 0, 0, 11, 22, 22, 11] -8\n",
"[0, 0, 0, 0, 12, 24, 24, 12] -8\n",
"[0, 0, 0, 0, 13, 26, 26, 13] -8\n",
"[0, 0, 0, 0, 14, 28, 28, 14] -12\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 2, 6, 6, 2] -4\n",
"[0, 0, 0, 0, 3, 9, 9, 3] -4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 4, 12, 12, 4] -4\n",
"[0, 0, 0, 0, 5, 15, 15, 5] -8\n",
"[0, 0, 0, 0, 6, 18, 18, 6] -8\n",
"[0, 0, 0, 0, 7, 21, 21, 7] -12\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 2, 8, 8, 2] -4\n",
"[0, 0, 0, 0, 3, 12, 12, 3] -8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 4, 16, 16, 4] -4\n",
"[0, 0, 0, 0, 5, 20, 20, 5] -12\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 2, 10, 10, 2] -4\n",
"[0, 0, 0, 0, 3, 15, 15, 3] -8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 4, 20, 20, 4] -8\n",
"[0, 0, 0, 0, 5, 25, 25, 5] -12\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 2, 12, 12, 2] -8\n",
"[0, 0, 0, 0, 3, 18, 18, 3] -8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 4, 24, 24, 4] -8\n",
"[0, 0, 0, 0, 5, 30, 30, 5] -16\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 2, 14, 14, 2] -8\n",
"[0, 0, 0, 0, 3, 21, 21, 3] -12\n",
"[0, 0, 0, 0, 2, 16, 16, 2] -8\n",
"[0, 0, 0, 0, 3, 24, 24, 3] -12\n",
"[0, 0, 0, 0, 2, 18, 18, 2] -8\n",
"[0, 0, 0, 0, 3, 27, 27, 3] -12\n",
"[0, 0, 0, 0, 2, 20, 20, 2] -12\n",
"[0, 0, 0, 0, 2, 22, 22, 2] -12\n",
"[0, 0, 0, 0, 2, 24, 24, 2] -12\n",
"[0, 0, 0, 0, 2, 26, 26, 2] -12\n",
"[0, 0, 0, 0, 2, 28, 28, 2] -16\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 2, 30, 30, 2] -16\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 2, 32, 32, 2] -16\n",
"[0, 0, 0, 0, 2, 34, 34, 2] -16\n",
"[0, 0, 0, 0, 2, 36, 36, 2] -20\n",
"[0, 0, 0, 0, 2, 38, 38, 2] -20\n",
"[0, 0, 0, 0, 4, 4, 0, 0] 0\n",
"[0, 0, 0, 0, 6, 6, 0, 0] -4\n",
"[0, 0, 0, 0, 8, 8, 0, 0] -4\n",
"[0, 0, 0, 0, 10, 10, 0, 0] -4\n",
"[0, 0, 0, 0, 12, 12, 0, 0] -4\n",
"[0, 0, 0, 0, 14, 14, 0, 0] -4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 16, 16, 0, 0] -8\n",
"[0, 0, 0, 0, 4, 4, 2, 2] 0\n",
"[0, 0, 0, 0, 6, 6, 3, 3] -4\n",
"[0, 0, 0, 0, 8, 8, 4, 4] -4\n",
"[0, 0, 0, 0, 10, 10, 5, 5] -4\n",
"[0, 0, 0, 0, 12, 12, 6, 6] -4\n",
"[0, 0, 0, 0, 14, 14, 7, 7] -4\n",
"[0, 0, 0, 0, 16, 16, 8, 8] -8\n",
"[0, 0, 0, 0, 18, 18, 9, 9] -8\n",
"[0, 0, 0, 0, 20, 20, 10, 10] -4\n",
"[0, 0, 0, 0, 22, 22, 11, 11] -4\n",
"[0, 0, 0, 0, 24, 24, 12, 12] -12\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 4, 22, 36, 2] -4\n",
"[0, 0, 0, 0, 6, 33, 54, 3] -16\n",
"[0, 0, 0, 0, 4, 24, 96, 2] -24\n",
"[0, 0, 0, 0, 4, 26, 56, 2] -8\n",
"[0, 0, 0, 0, 6, 39, 84, 3] -24\n",
"[0, 0, 0, 0, 4, 42, 102, 2] -44\n",
"[0, 0, 0, 0, 4, 48, 52, 2] -20\n",
"[0, 0, 0, 0, 4, 52, 80, 2] -24\n",
"[0, 0, 0, 0, 6, 6, 0, 0] -4\n",
"[0, 0, 0, 0, 9, 9, 0, 0] -4\n",
"[0, 0, 0, 0, 12, 12, 0, 0] -4\n",
"[0, 0, 0, 0, 15, 15, 0, 0] -8\n",
"[0, 0, 0, 0, 6, 6, 2, 2] -4\n",
"[0, 0, 0, 0, 9, 9, 3, 3] -4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 12, 12, 4, 4] -4\n",
"[0, 0, 0, 0, 15, 15, 5, 5] -8\n",
"[0, 0, 0, 0, 18, 18, 6, 6] -8\n",
"[0, 0, 0, 0, 21, 21, 7, 7] -8\n",
"[0, 0, 0, 0, 24, 24, 8, 8] -12\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 6, 14, 24, 2] 4\n",
"[0, 0, 0, 0, 9, 21, 36, 3] 0\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 12, 28, 48, 4] 0\n",
"[0, 0, 0, 0, 15, 35, 60, 5] -4\n",
"[0, 0, 0, 0, 18, 42, 72, 6] -8\n",
"[0, 0, 0, 0, 21, 49, 84, 7] -12\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 6, 26, 52, 2] -8\n",
"[0, 0, 0, 0, 9, 39, 78, 3] -16\n",
"[0, 0, 0, 0, 6, 36, 50, 2] -16\n",
"[0, 0, 0, 0, 6, 40, 34, 2] -16\n",
"[0, 0, 0, 0, 6, 56, 80, 2] -24\n",
"[0, 0, 0, 0, 8, 8, 0, 0] -4\n",
"[0, 0, 0, 0, 12, 12, 0, 0] -4\n",
"[0, 0, 0, 0, 16, 16, 0, 0] -8\n",
"[0, 0, 0, 0, 8, 8, 2, 2] -4\n",
"[0, 0, 0, 0, 12, 12, 3, 3] -4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 16, 16, 4, 4] -8\n",
"[0, 0, 0, 0, 20, 20, 5, 5] -8\n",
"[0, 0, 0, 0, 24, 24, 6, 6] -12\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 8, 16, 14, 2] -4\n",
"[0, 0, 0, 0, 12, 24, 21, 3] -4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 16, 32, 28, 4] -4\n",
"[0, 0, 0, 0, 20, 40, 35, 5] 0\n",
"[0, 0, 0, 0, 24, 48, 42, 6] -4\n",
"[0, 0, 0, 0, 28, 56, 49, 7] -4\n",
"[0, 0, 0, 0, 32, 64, 56, 8] 0\n",
"[0, 0, 0, 0, 36, 72, 63, 9] 4\n",
"[0, 0, 0, 0, 40, 80, 70, 10] 16\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 8, 18, 26, 2] 4\n",
"[0, 0, 0, 0, 12, 27, 39, 3] 0\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 16, 36, 52, 4] -4\n",
"[0, 0, 0, 0, 20, 45, 65, 5] -4\n",
"[0, 0, 0, 0, 24, 54, 78, 6] -8\n",
"[0, 0, 0, 0, 28, 63, 91, 7] -16\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 8, 34, 90, 2] -24\n",
"[0, 0, 0, 0, 8, 40, 60, 2] -12\n",
"[0, 0, 0, 0, 8, 42, 46, 2] -16\n",
"[0, 0, 0, 0, 8, 48, 94, 2] -32\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 8, 58, 76, 2] -16\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[0, 0, 0, 0, 10, 10, 0, 0] -4\n",
"[0, 0, 0, 0, 15, 15, 0, 0] -8\n",
"[0, 0, 0, 0, 10, 10, 2, 2] -4\n",
"[0, 0, 0, 0, 15, 15, 3, 3] -8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 20, 20, 4, 4] -8\n",
"[0, 0, 0, 0, 25, 25, 5, 5] -12\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 10, 14, 10, 2] 0\n",
"[0, 0, 0, 0, 15, 21, 15, 3] -4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 20, 28, 20, 4] 0\n",
"[0, 0, 0, 0, 25, 35, 25, 5] 0\n",
"[0, 0, 0, 0, 30, 42, 30, 6] 0\n",
"[0, 0, 0, 0, 35, 49, 35, 7] 0\n",
"[0, 0, 0, 0, 40, 56, 40, 8] 0\n",
"[0, 0, 0, 0, 45, 63, 45, 9] -4\n",
"[0, 0, 0, 0, 50, 70, 50, 10] 4\n",
"[0, 0, 0, 0, 55, 77, 55, 11] 8\n",
"[0, 0, 0, 0, 60, 84, 60, 12] 16\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 10, 24, 58, 2] 0\n",
"[0, 0, 0, 0, 15, 36, 87, 3] -16\n",
"[0, 0, 0, 0, 10, 30, 86, 2] -12\n",
"[0, 0, 0, 0, 10, 32, 102, 2] -32\n",
"[0, 0, 0, 0, 10, 34, 66, 2] -8\n",
"[0, 0, 0, 0, 15, 51, 99, 3] -36\n",
"[0, 0, 0, 0, 10, 38, 100, 2] -32\n",
"[0, 0, 0, 0, 10, 52, 62, 2] -12\n",
"[0, 0, 0, 0, 12, 12, 0, 0] -4\n",
"[0, 0, 0, 0, 18, 18, 0, 0] -8\n",
"[0, 0, 0, 0, 12, 12, 2, 2] -4\n",
"[0, 0, 0, 0, 18, 18, 3, 3] -8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 24, 24, 4, 4] -12\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 12, 28, 52, 2] 0\n",
"[0, 0, 0, 0, 18, 42, 78, 3] -8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 24, 56, 104, 4] -32\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 12, 32, 36, 2] -4\n",
"[0, 0, 0, 0, 18, 48, 54, 3] -8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 24, 64, 72, 4] 0\n",
"[0, 0, 0, 0, 30, 80, 90, 5] 4\n",
"[0, 0, 0, 0, 36, 96, 108, 6] -4\n",
"[0, 0, 0, 0, 42, 112, 126, 7] -24\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 12, 36, 34, 2] -4\n",
"[0, 0, 0, 0, 18, 54, 51, 3] -8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 24, 72, 68, 4] 8\n",
"[0, 0, 0, 0, 30, 90, 85, 5] 24\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 12, 38, 58, 2] -8\n",
"[0, 0, 0, 0, 18, 57, 87, 3] -16\n",
"[0, 0, 0, 0, 12, 40, 92, 2] -20\n",
"[0, 0, 0, 0, 12, 42, 64, 2] -8\n",
"[0, 0, 0, 0, 18, 63, 96, 3] -24\n",
"[0, 0, 0, 0, 12, 46, 88, 2] -20\n",
"[0, 0, 0, 0, 12, 48, 102, 2] -36\n",
"[0, 0, 0, 0, 12, 52, 68, 2] -8\n",
"[0, 0, 0, 0, 18, 78, 102, 3] -20\n",
"[0, 0, 0, 0, 12, 54, 60, 2] -8\n",
"[0, 0, 0, 0, 18, 81, 90, 3] -4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 24, 108, 120, 4] -16\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 12, 56, 100, 2] -32\n",
"[0, 0, 0, 0, 14, 14, 0, 0] -4\n",
"[0, 0, 0, 0, 21, 21, 0, 0] -8\n",
"[0, 0, 0, 0, 14, 14, 2, 2] -4\n",
"[0, 0, 0, 0, 21, 21, 3, 3] -8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 28, 28, 4, 4] -12\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 14, 16, 8, 2] 0\n",
"[0, 0, 0, 0, 21, 24, 12, 3] -4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 28, 32, 16, 4] 0\n",
"[0, 0, 0, 0, 35, 40, 20, 5] -4\n",
"[0, 0, 0, 0, 42, 48, 24, 6] 0\n",
"[0, 0, 0, 0, 49, 56, 28, 7] -4\n",
"[0, 0, 0, 0, 56, 64, 32, 8] 0\n",
"[0, 0, 0, 0, 63, 72, 36, 9] 4\n",
"[0, 0, 0, 0, 70, 80, 40, 10] 12\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 14, 26, 22, 2] 0\n",
"[0, 0, 0, 0, 21, 39, 33, 3] 0\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 28, 52, 44, 4] 0\n",
"[0, 0, 0, 0, 35, 65, 55, 5] 4\n",
"[0, 0, 0, 0, 42, 78, 66, 6] 16\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 14, 32, 76, 2] 0\n",
"[0, 0, 0, 0, 21, 48, 114, 3] -60\n",
"[0, 0, 0, 0, 14, 48, 84, 2] -12\n",
"[0, 0, 0, 0, 14, 54, 56, 2] -8\n",
"[0, 0, 0, 0, 21, 81, 84, 3] 8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 28, 108, 112, 4] 12\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 14, 60, 100, 2] -28\n",
"[0, 0, 0, 0, 16, 16, 0, 0] -8\n",
"[0, 0, 0, 0, 16, 16, 2, 2] -8\n",
"[0, 0, 0, 0, 24, 24, 3, 3] -12\n",
"[0, 0, 0, 0, 16, 18, 22, 2] 8\n",
"[0, 0, 0, 0, 24, 27, 33, 3] 8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 32, 36, 44, 4] 8\n",
"[0, 0, 0, 0, 40, 45, 55, 5] 4\n",
"[0, 0, 0, 0, 48, 54, 66, 6] 0\n",
"[0, 0, 0, 0, 56, 63, 77, 7] 0\n",
"[0, 0, 0, 0, 64, 72, 88, 8] -4\n",
"[0, 0, 0, 0, 72, 81, 99, 9] -12\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 16, 24, 18, 2] 0\n",
"[0, 0, 0, 0, 24, 36, 27, 3] 0\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 32, 48, 36, 4] 4\n",
"[0, 0, 0, 0, 40, 60, 45, 5] 4\n",
"[0, 0, 0, 0, 48, 72, 54, 6] 8\n",
"[0, 0, 0, 0, 56, 84, 63, 7] 20\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 16, 36, 80, 2] -8\n",
"[0, 0, 0, 0, 24, 54, 120, 3] -80\n",
"[0, 0, 0, 0, 16, 38, 70, 2] -4\n",
"[0, 0, 0, 0, 24, 57, 105, 3] -36\n",
"[0, 0, 0, 0, 16, 40, 100, 2] -28\n",
"[0, 0, 0, 0, 16, 52, 86, 2] -16\n",
"[0, 0, 0, 0, 16, 60, 84, 2] -12\n",
"[0, 0, 0, 0, 16, 64, 62, 2] -4\n",
"[0, 0, 0, 0, 24, 96, 93, 3] 20\n",
"[0, 0, 0, 0, 18, 18, 0, 0] -8\n",
"[0, 0, 0, 0, 18, 18, 2, 2] -8\n",
"[0, 0, 0, 0, 27, 27, 3, 3] -12\n",
"[0, 0, 0, 0, 18, 22, 24, 2] 8\n",
"[0, 0, 0, 0, 27, 33, 36, 3] 4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 36, 44, 48, 4] 4\n",
"[0, 0, 0, 0, 45, 55, 60, 5] 4\n",
"[0, 0, 0, 0, 54, 66, 72, 6] 4\n",
"[0, 0, 0, 0, 63, 77, 84, 7] 8\n",
"[0, 0, 0, 0, 72, 88, 96, 8] 4\n",
"[0, 0, 0, 0, 81, 99, 108, 9] -8\n",
"[0, 0, 0, 0, 90, 110, 120, 10] -24\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 18, 24, 16, 2] 0\n",
"[0, 0, 0, 0, 27, 36, 24, 3] 0\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 36, 48, 32, 4] 4\n",
"[0, 0, 0, 0, 45, 60, 40, 5] 4\n",
"[0, 0, 0, 0, 54, 72, 48, 6] 8\n",
"[0, 0, 0, 0, 63, 84, 56, 7] 20\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 18, 36, 96, 2] -20\n",
"[0, 0, 0, 0, 18, 42, 38, 2] -4\n",
"[0, 0, 0, 0, 27, 63, 57, 3] 0\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 36, 84, 76, 4] 24\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 18, 50, 74, 2] -8\n",
"[0, 0, 0, 0, 27, 75, 111, 3] -40\n",
"[0, 0, 0, 0, 18, 64, 58, 2] -4\n",
"[0, 0, 0, 0, 27, 96, 87, 3] 28\n",
"[0, 0, 0, 0, 18, 66, 88, 2] -12\n",
"[0, 0, 0, 0, 18, 68, 94, 2] -16\n",
"[0, 0, 0, 0, 20, 20, 0, 0] -8\n",
"[0, 0, 0, 0, 20, 20, 2, 2] -8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 30, 30, 3, 3] -12\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 20, 36, 30, 2] 0\n",
"[0, 0, 0, 0, 30, 54, 45, 3] 0\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 40, 72, 60, 4] 16\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 20, 38, 92, 2] -12\n",
"[0, 0, 0, 0, 20, 42, 82, 2] -8\n",
"[0, 0, 0, 0, 30, 63, 123, 3] -84\n",
"[0, 0, 0, 0, 20, 44, 60, 2] 0\n",
"[0, 0, 0, 0, 30, 66, 90, 3] -8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 40, 88, 120, 4] -44\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 20, 46, 22, 2] -8\n",
"[0, 0, 0, 0, 30, 69, 33, 3] 8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 40, 92, 44, 4] 36\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 20, 62, 96, 2] -20\n",
"[0, 0, 0, 0, 20, 66, 56, 2] 0\n",
"[0, 0, 0, 0, 30, 99, 84, 3] 40\n",
"[0, 0, 0, 0, 20, 74, 62, 2] 8\n",
"[0, 0, 0, 0, 30, 111, 93, 3] 56\n",
"[0, 0, 0, 0, 20, 80, 66, 2] 12\n",
"[0, 0, 0, 0, 22, 18, 16, 2] 12\n",
"[0, 0, 0, 0, 22, 22, 0, 0] -8\n",
"[0, 0, 0, 0, 22, 22, 2, 2] -8\n",
"[0, 0, 0, 0, 33, 33, 3, 3] -16\n",
"[0, 0, 0, 0, 22, 26, 14, 2] 0\n",
"[0, 0, 0, 0, 33, 39, 21, 3] -4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 44, 52, 28, 4] 0\n",
"[0, 0, 0, 0, 55, 65, 35, 5] 8\n",
"[0, 0, 0, 0, 66, 78, 42, 6] 16\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 22, 34, 26, 2] 4\n",
"[0, 0, 0, 0, 33, 51, 39, 3] 0\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 44, 68, 52, 4] 8\n",
"[0, 0, 0, 0, 55, 85, 65, 5] 24\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 22, 44, 80, 2] -4\n",
"[0, 0, 0, 0, 33, 66, 120, 3] -72\n",
"[0, 0, 0, 0, 22, 46, 20, 2] -8\n",
"[0, 0, 0, 0, 33, 69, 30, 3] 4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 44, 92, 40, 4] 36\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 22, 50, 28, 2] -4\n",
"[0, 0, 0, 0, 33, 75, 42, 3] 12\n",
"[0, 0, 0, 0, 22, 56, 94, 2] -16\n",
"[0, 0, 0, 0, 22, 60, 66, 2] 0\n",
"[0, 0, 0, 0, 33, 90, 99, 3] 4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 44, 120, 132, 4] -24\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 22, 62, 58, 2] 0\n",
"[0, 0, 0, 0, 33, 93, 87, 3] 24\n",
"[0, 0, 0, 0, 22, 74, 84, 2] 4\n",
"[0, 0, 0, 0, 33, 111, 126, 3] -28\n",
"[0, 0, 0, 0, 22, 80, 96, 2] -4\n",
"[0, 0, 0, 0, 33, 120, 144, 3] -72\n",
"[0, 0, 0, 0, 24, 14, 6, 2] 4\n",
"[0, 0, 0, 0, 36, 21, 9, 3] 4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 48, 28, 12, 4] 0\n",
"[0, 0, 0, 0, 60, 35, 15, 5] -4\n",
"[0, 0, 0, 0, 72, 42, 18, 6] -4\n",
"[0, 0, 0, 0, 84, 49, 21, 7] -16\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 24, 22, 18, 2] 8\n",
"[0, 0, 0, 0, 36, 33, 27, 3] 8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 48, 44, 36, 4] 4\n",
"[0, 0, 0, 0, 60, 55, 45, 5] 0\n",
"[0, 0, 0, 0, 72, 66, 54, 6] 4\n",
"[0, 0, 0, 0, 84, 77, 63, 7] 4\n",
"[0, 0, 0, 0, 96, 88, 72, 8] 0\n",
"[0, 0, 0, 0, 108, 99, 81, 9] -12\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 24, 24, 0, 0] -12\n",
"[0, 0, 0, 0, 24, 24, 2, 2] -12\n",
"[0, 0, 0, 0, 24, 44, 98, 2] -24\n",
"[0, 0, 0, 0, 24, 52, 22, 2] -8\n",
"[0, 0, 0, 0, 36, 78, 33, 3] 16\n",
"[0, 0, 0, 0, 24, 56, 68, 2] 0\n",
"[0, 0, 0, 0, 36, 84, 102, 3] -4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 48, 112, 136, 4] -56\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 24, 62, 64, 2] 0\n",
"[0, 0, 0, 0, 36, 93, 96, 3] 16\n",
"[0, 0, 0, 0, 24, 70, 38, 2] 4\n",
"[0, 0, 0, 0, 36, 105, 57, 3] 56\n",
"[0, 0, 0, 0, 24, 84, 60, 2] 20\n",
"[0, 0, 0, 0, 24, 86, 52, 2] 20\n",
"[0, 0, 0, 0, 24, 90, 100, 2] 4\n",
"[0, 0, 0, 0, 36, 135, 150, 3] -52\n",
"[0, 0, 0, 0, 26, 18, 8, 2] 4\n",
"[0, 0, 0, 0, 39, 27, 12, 3] 0\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 52, 36, 16, 4] 0\n",
"[0, 0, 0, 0, 65, 45, 20, 5] -4\n",
"[0, 0, 0, 0, 78, 54, 24, 6] -8\n",
"[0, 0, 0, 0, 91, 63, 28, 7] -16\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 26, 26, 0, 0] -12\n",
"[0, 0, 0, 0, 26, 26, 2, 2] -12\n",
"[0, 0, 0, 0, 26, 34, 22, 2] 0\n",
"[0, 0, 0, 0, 39, 51, 33, 3] 4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 52, 68, 44, 4] 8\n",
"[0, 0, 0, 0, 65, 85, 55, 5] 24\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 26, 44, 50, 2] 0\n",
"[0, 0, 0, 0, 39, 66, 75, 3] 4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 52, 88, 100, 4] 8\n",
"[0, 0, 0, 0, 65, 110, 125, 5] -24\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 26, 46, 38, 2] 0\n",
"[0, 0, 0, 0, 39, 69, 57, 3] 8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 52, 92, 76, 4] 36\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 26, 54, 94, 2] -16\n",
"[0, 0, 0, 0, 26, 58, 80, 2] -4\n",
"[0, 0, 0, 0, 39, 87, 120, 3] -48\n",
"[0, 0, 0, 0, 26, 62, 44, 2] 0\n",
"[0, 0, 0, 0, 39, 93, 66, 3] 36\n",
"[0, 0, 0, 0, 26, 64, 98, 2] -20\n",
"[0, 0, 0, 0, 26, 66, 64, 2] 4\n",
"[0, 0, 0, 0, 39, 99, 96, 3] 28\n",
"[0, 0, 0, 0, 26, 68, 48, 2] 4\n",
"[0, 0, 0, 0, 39, 102, 72, 3] 52\n",
"[0, 0, 0, 0, 26, 72, 86, 2] 0\n",
"[0, 0, 0, 0, 39, 108, 129, 3] -40\n",
"[0, 0, 0, 0, 26, 74, 90, 2] -4\n",
"[0, 0, 0, 0, 39, 111, 135, 3] -56\n",
"[0, 0, 0, 0, 26, 78, 46, 2] 12\n",
"[0, 0, 0, 0, 26, 86, 82, 2] 16\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 26, 88, 58, 2] 24\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 26, 96, 60, 2] 40\n",
"[0, 0, 0, 0, 28, 28, 0, 0] -12\n",
"[0, 0, 0, 0, 28, 28, 2, 2] -12\n",
"[0, 0, 0, 0, 28, 44, 34, 2] 4\n",
"[0, 0, 0, 0, 42, 66, 51, 3] 8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 56, 88, 68, 4] 32\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 28, 48, 44, 2] 0\n",
"[0, 0, 0, 0, 42, 72, 66, 3] 12\n",
"[0, 0, 0, 0, 28, 50, 22, 2] -4\n",
"[0, 0, 0, 0, 42, 75, 33, 3] 16\n",
"[0, 0, 0, 0, 28, 54, 30, 2] 0\n",
"[0, 0, 0, 0, 42, 81, 45, 3] 20\n",
"[0, 0, 0, 0, 28, 58, 100, 2] -20\n",
"[0, 0, 0, 0, 28, 68, 62, 2] 8\n",
"[0, 0, 0, 0, 42, 102, 93, 3] 40\n",
"[0, 0, 0, 0, 28, 76, 84, 2] 8\n",
"[0, 0, 0, 0, 42, 114, 126, 3] -16\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 28, 90, 78, 2] 28\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[0, 0, 0, 0, 30, 30, 2, 2] -12\n",
"[0, 0, 0, 0, 30, 36, 20, 2] 0\n",
"[0, 0, 0, 0, 45, 54, 30, 3] 0\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 60, 72, 40, 4] 12\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 30, 50, 70, 2] 4\n",
"[0, 0, 0, 0, 45, 75, 105, 3] -20\n",
"[0, 0, 0, 0, 30, 54, 28, 2] 0\n",
"[0, 0, 0, 0, 45, 81, 42, 3] 20\n",
"[0, 0, 0, 0, 30, 60, 52, 2] 4\n",
"[0, 0, 0, 0, 45, 90, 78, 3] 28\n",
"[0, 0, 0, 0, 30, 64, 78, 2] 4\n",
"[0, 0, 0, 0, 45, 96, 117, 3] -28\n",
"[0, 0, 0, 0, 30, 78, 48, 2] 16\n",
"[0, 0, 0, 0, 30, 84, 86, 2] 16\n",
"[0, 0, 0, 0, 30, 92, 96, 2] 16\n",
"[0, 0, 0, 0, 30, 94, 100, 2] 16\n",
"[0, 0, 0, 0, 30, 102, 54, 2] 52\n",
"[0, 0, 0, 0, 32, 32, 2, 2] -12\n",
"[0, 0, 0, 0, 32, 42, 34, 2] 8\n",
"[0, 0, 0, 0, 48, 63, 51, 3] 4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 64, 84, 68, 4] 28\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 32, 46, 90, 2] -8\n",
"[0, 0, 0, 0, 48, 69, 135, 3] -120\n",
"[0, 0, 0, 0, 32, 50, 48, 2] 4\n",
"[0, 0, 0, 0, 48, 75, 72, 3] 12\n",
"[0, 0, 0, 0, 32, 56, 46, 2] 4\n",
"[0, 0, 0, 0, 48, 84, 69, 3] 24\n",
"[0, 0, 0, 0, 32, 76, 92, 2] 4\n",
"[0, 0, 0, 0, 48, 114, 138, 3] -60\n",
"[0, 0, 0, 0, 32, 78, 74, 2] 16\n",
"[0, 0, 0, 0, 32, 88, 82, 2] 24\n",
"[0, 0, 0, 0, 32, 92, 50, 2] 36\n",
"[0, 0, 0, 0, 32, 96, 70, 2] 44\n",
"[0, 0, 0, 0, 32, 100, 88, 2] 40\n",
"[0, 0, 0, 0, 34, 34, 2, 2] -16\n",
"[0, 0, 0, 0, 34, 36, 12, 2] -8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 51, 54, 18, 3] -4\n",
"[0, 0, 0, 0, 68, 72, 24, 4] 8\n",
"[0, 0, 0, 0, 85, 90, 30, 5] 20\n",
"[0, 0, 0, 0, 34, 40, 6, 2] -16\n",
"[0, 0, 0, 0, 34, 42, 32, 2] 4\n",
"[0, 0, 0, 0, 51, 63, 48, 3] 4\n",
"[0, 0, 0, 0, 68, 84, 64, 4] 24\n",
"[0, 0, 0, 0, 34, 44, 28, 2] 0\n",
"[0, 0, 0, 0, 51, 66, 42, 3] 8\n",
"[0, 0, 0, 0, 68, 88, 56, 4] 28\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 34, 48, 88, 2] -8\n",
"[0, 0, 0, 0, 51, 72, 132, 3] -108\n",
"[0, 0, 0, 0, 34, 50, 100, 2] -20\n",
"[0, 0, 0, 0, 34, 52, 78, 2] 0\n",
"[0, 0, 0, 0, 51, 78, 117, 3] -52\n",
"[0, 0, 0, 0, 34, 54, 42, 2] 4\n",
"[0, 0, 0, 0, 51, 81, 63, 3] 20\n",
"[0, 0, 0, 0, 34, 58, 96, 2] -16\n",
"[0, 0, 0, 0, 34, 60, 64, 2] 4\n",
"[0, 0, 0, 0, 51, 90, 96, 3] 12\n",
"[0, 0, 0, 0, 34, 62, 80, 2] 0\n",
"[0, 0, 0, 0, 51, 93, 120, 3] -40\n",
"[0, 0, 0, 0, 34, 64, 36, 2] 4\n",
"[0, 0, 0, 0, 51, 96, 54, 3] 40\n",
"[0, 0, 0, 0, 34, 76, 68, 2] 16\n",
"[0, 0, 0, 0, 34, 80, 60, 2] 20\n",
"[0, 0, 0, 0, 34, 84, 62, 2] 24\n",
"[0, 0, 0, 0, 34, 96, 66, 2] 40\n",
"[0, 0, 0, 0, 36, 22, 4, 2] -4\n",
"[0, 0, 0, 0, 54, 33, 6, 3] -12\n",
"[0, 0, 0, 0, 36, 32, 12, 2] -4\n",
"[0, 0, 0, 0, 54, 48, 18, 3] -4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 72, 64, 24, 4] 4\n",
"[0, 0, 0, 0, 90, 80, 30, 5] 4\n",
"[0, 0, 0, 0, 108, 96, 36, 6] -8\n",
"[0, 0, 0, 0, 126, 112, 42, 7] -24\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 36, 36, 2, 2] -16\n",
"[0, 0, 0, 0, 36, 42, 36, 2] 4\n",
"[0, 0, 0, 0, 54, 63, 54, 3] 4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 72, 84, 72, 4] 24\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 36, 54, 64, 2] 4\n",
"[0, 0, 0, 0, 54, 81, 96, 3] 0\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 72, 108, 128, 4] -36\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 36, 64, 34, 2] 8\n",
"[0, 0, 0, 0, 54, 96, 51, 3] 40\n",
"[0, 0, 0, 0, 36, 72, 94, 2] -4\n",
"[0, 0, 0, 0, 54, 108, 141, 3] -88\n",
"[0, 0, 0, 0, 36, 76, 40, 2] 16\n",
"[0, 0, 0, 0, 36, 88, 90, 2] 16\n",
"[0, 0, 0, 0, 36, 94, 98, 2] 16\n",
"[0, 0, 0, 0, 36, 100, 46, 2] 48\n",
"[0, 0, 0, 0, 38, 38, 2, 2] -16\n",
"[0, 0, 0, 0, 38, 42, 18, 2] 0\n",
"[0, 0, 0, 0, 57, 63, 27, 3] 4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 76, 84, 36, 4] 20\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 38, 46, 26, 2] 4\n",
"[0, 0, 0, 0, 57, 69, 39, 3] 8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 76, 92, 52, 4] 32\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 38, 52, 50, 2] 4\n",
"[0, 0, 0, 0, 57, 78, 75, 3] 12\n",
"[0, 0, 0, 0, 38, 54, 72, 2] 4\n",
"[0, 0, 0, 0, 57, 81, 108, 3] -24\n",
"[0, 0, 0, 0, 38, 64, 94, 2] -8\n",
"[0, 0, 0, 0, 57, 96, 141, 3] -112\n",
"[0, 0, 0, 0, 38, 66, 54, 2] 8\n",
"[0, 0, 0, 0, 57, 99, 81, 3] 40\n",
"[0, 0, 0, 0, 38, 74, 88, 2] 4\n",
"[0, 0, 0, 0, 57, 111, 132, 3] -48\n",
"[0, 0, 0, 0, 38, 78, 100, 2] -4\n",
"[0, 0, 0, 0, 57, 117, 150, 3] -104\n",
"[0, 0, 0, 0, 38, 90, 58, 2] 32\n",
"[0, 0, 0, 0, 38, 94, 86, 2] 32\n",
"[0, 0, 0, 0, 40, 40, 2, 2] -16\n",
"[0, 0, 0, 0, 40, 56, 60, 2] 8\n",
"[0, 0, 0, 0, 60, 84, 90, 3] 8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 80, 112, 120, 4] -4\n",
"[0, 0, 0, 0, 100, 140, 150, 5] -60\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 40, 58, 74, 2] 4\n",
"[0, 0, 0, 0, 60, 87, 111, 3] -24\n",
"[0, 0, 0, 0, 40, 64, 50, 2] 8\n",
"[0, 0, 0, 0, 60, 96, 75, 3] 36\n",
"[0, 0, 0, 0, 40, 66, 44, 2] 8\n",
"[0, 0, 0, 0, 60, 99, 66, 3] 44\n",
"[0, 0, 0, 0, 40, 70, 76, 2] 12\n",
"[0, 0, 0, 0, 40, 76, 36, 2] 16\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 40, 78, 70, 2] 20\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 40, 80, 90, 2] 8\n",
"[0, 0, 0, 0, 60, 120, 135, 3] -36\n",
"[0, 0, 0, 0, 40, 82, 94, 2] 8\n",
"[0, 0, 0, 0, 60, 123, 141, 3] -52\n",
"[0, 0, 0, 0, 40, 84, 102, 2] 0\n",
"[0, 0, 0, 0, 60, 126, 153, 3] -92\n",
"[0, 0, 0, 0, 40, 86, 54, 2] 28\n",
"[0, 0, 0, 0, 40, 94, 66, 2] 40\n",
"[0, 0, 0, 0, 42, 42, 2, 2] -16\n",
"[0, 0, 0, 0, 42, 54, 34, 2] 8\n",
"[0, 0, 0, 0, 63, 81, 51, 3] 20\n",
"[0, 0, 0, 0, 42, 68, 86, 2] 4\n",
"[0, 0, 0, 0, 63, 102, 129, 3] -52\n",
"[0, 0, 0, 0, 42, 72, 98, 2] -8\n",
"[0, 0, 0, 0, 63, 108, 147, 3] -112\n",
"[0, 0, 0, 0, 42, 74, 76, 2] 16\n",
"[0, 0, 0, 0, 42, 92, 100, 2] 16\n",
"[0, 0, 0, 0, 44, 44, 2, 2] -20\n",
"[0, 0, 0, 0, 44, 48, 28, 2] 0\n",
"[0, 0, 0, 0, 66, 72, 42, 3] 12\n",
"[0, 0, 0, 0, 44, 58, 14, 2] -8\n",
"[0, 0, 0, 0, 66, 87, 21, 3] 20\n",
"[0, 0, 0, 0, 44, 62, 26, 2] 4\n",
"[0, 0, 0, 0, 66, 93, 39, 3] 36\n",
"[0, 0, 0, 0, 44, 64, 102, 2] -20\n",
"[0, 0, 0, 0, 44, 66, 40, 2] 8\n",
"[0, 0, 0, 0, 66, 99, 60, 3] 48\n",
"[0, 0, 0, 0, 44, 68, 80, 2] 4\n",
"[0, 0, 0, 0, 66, 102, 120, 3] -24\n",
"[0, 0, 0, 0, 44, 72, 70, 2] 12\n",
"[0, 0, 0, 0, 44, 76, 62, 2] 16\n",
"[0, 0, 0, 0, 44, 78, 54, 2] 16\n",
"[0, 0, 0, 0, 44, 100, 72, 2] 48\n",
"[0, 0, 0, 0, 44, 102, 52, 2] 52\n",
"[0, 0, 0, 0, 46, 42, 8, 2] -12\n",
"[0, 0, 0, 0, 46, 46, 2, 2] -20\n",
"[0, 0, 0, 0, 46, 56, 32, 2] 4\n",
"[0, 0, 0, 0, 69, 84, 48, 3] 20\n",
"[0, 0, 0, 0, 46, 60, 56, 2] 4\n",
"[0, 0, 0, 0, 69, 90, 84, 3] 24\n",
"[0, 0, 0, 0, 46, 66, 94, 2] -8\n",
"[0, 0, 0, 0, 69, 99, 141, 3] -108\n",
"[0, 0, 0, 0, 46, 70, 78, 2] 8\n",
"[0, 0, 0, 0, 69, 105, 117, 3] -12\n",
"[0, 0, 0, 0, 46, 74, 58, 2] 12\n",
"[0, 0, 0, 0, 46, 76, 70, 2] 16\n",
"[0, 0, 0, 0, 46, 78, 26, 2] 16\n",
"[0, 0, 0, 0, 46, 90, 80, 2] 28\n",
"[0, 0, 0, 0, 46, 94, 82, 2] 32\n",
"[0, 0, 0, 0, 46, 98, 30, 2] 44\n",
"[0, 0, 0, 0, 46, 100, 36, 2] 48\n",
"[0, 0, 0, 0, 46, 102, 84, 2] 48\n",
"[0, 0, 0, 0, 48, 50, 32, 2] 4\n",
"[0, 0, 0, 0, 72, 75, 48, 3] 12\n",
"[0, 0, 0, 0, 48, 58, 72, 2] 4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 72, 87, 108, 3] -16\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 48, 68, 26, 2] 8\n",
"[0, 0, 0, 0, 72, 102, 39, 3] 52\n",
"[0, 0, 0, 0, 48, 70, 98, 2] -12\n",
"[0, 0, 0, 0, 48, 78, 30, 2] 16\n",
"[0, 0, 0, 0, 48, 80, 86, 2] 12\n",
"[0, 0, 0, 0, 48, 82, 60, 2] 24\n",
"[0, 0, 0, 0, 48, 84, 92, 2] 12\n",
"[0, 0, 0, 0, 48, 86, 96, 2] 8\n",
"[0, 0, 0, 0, 72, 129, 144, 3] -44\n",
"[0, 0, 0, 0, 48, 90, 54, 2] 32\n",
"[0, 0, 0, 0, 50, 36, 6, 2] -12\n",
"[0, 0, 0, 0, 50, 44, 26, 2] 4\n",
"[0, 0, 0, 0, 75, 66, 39, 3] 4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 100, 88, 52, 4] 4\n",
"[0, 0, 0, 0, 125, 110, 65, 5] -24\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 50, 52, 38, 2] 4\n",
"[0, 0, 0, 0, 75, 78, 57, 3] 12\n",
"[0, 0, 0, 0, 50, 62, 100, 2] -16\n",
"[0, 0, 0, 0, 50, 64, 40, 2] 8\n",
"[0, 0, 0, 0, 75, 96, 60, 3] 40\n",
"[0, 0, 0, 0, 50, 68, 58, 2] 8\n",
"[0, 0, 0, 0, 75, 102, 87, 3] 40\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 50, 84, 50, 2] 24\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 50, 86, 70, 2] 28\n",
"[0, 0, 0, 0, 50, 88, 60, 2] 32\n",
"[0, 0, 0, 0, 50, 92, 32, 2] 36\n",
"[0, 0, 0, 0, 50, 96, 98, 2] 20\n",
"[0, 0, 0, 0, 50, 98, 102, 2] 20\n",
"[0, 0, 0, 0, 52, 26, 6, 2] -4\n",
"[0, 0, 0, 0, 78, 39, 9, 3] -16\n",
"[0, 0, 0, 0, 52, 28, 12, 2] 0\n",
"[0, 0, 0, 0, 78, 42, 18, 3] -8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 104, 56, 24, 4] -32\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 52, 48, 4, 2] -20\n",
"[0, 0, 0, 0, 52, 58, 56, 2] 4\n",
"[0, 0, 0, 0, 78, 87, 84, 3] 16\n",
"[0, 0, 0, 0, 52, 60, 30, 2] 4\n",
"[0, 0, 0, 0, 78, 90, 45, 3] 24\n",
"[0, 0, 0, 0, 52, 66, 76, 2] 8\n",
"[0, 0, 0, 0, 78, 99, 114, 3] -16\n",
"[0, 0, 0, 0, 52, 74, 60, 2] 16\n",
"[0, 0, 0, 0, 52, 82, 78, 2] 20\n",
"[0, 0, 0, 0, 52, 84, 66, 2] 24\n",
"[0, 0, 0, 0, 52, 94, 70, 2] 40\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 52, 102, 44, 2] 52\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 54, 66, 38, 2] 8\n",
"[0, 0, 0, 0, 81, 99, 57, 3] 40\n",
"[0, 0, 0, 0, 54, 74, 68, 2] 16\n",
"[0, 0, 0, 0, 54, 76, 86, 2] 8\n",
"[0, 0, 0, 0, 81, 114, 129, 3] -32\n",
"[0, 0, 0, 0, 54, 78, 44, 2] 16\n",
"[0, 0, 0, 0, 54, 82, 102, 2] -4\n",
"[0, 0, 0, 0, 81, 123, 153, 3] -104\n",
"[0, 0, 0, 0, 54, 86, 40, 2] 28\n",
"[0, 0, 0, 0, 54, 90, 48, 2] 32\n",
"[0, 0, 0, 0, 54, 102, 30, 2] 52\n",
"[0, 0, 0, 0, 56, 26, 4, 2] -8\n",
"[0, 0, 0, 0, 84, 39, 6, 3] -24\n",
"[0, 0, 0, 0, 56, 54, 14, 2] -8\n",
"[0, 0, 0, 0, 84, 81, 21, 3] 4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 112, 108, 28, 4] 8\n",
"[0, 0, 0, 0, 140, 135, 35, 5] -8\n",
"[0, 0, 0, 0, 168, 162, 42, 6] -20\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 56, 60, 46, 2] 4\n",
"[0, 0, 0, 0, 84, 90, 69, 3] 24\n",
"[0, 0, 0, 0, 56, 66, 20, 2] 0\n",
"[0, 0, 0, 0, 84, 99, 30, 3] 36\n",
"[0, 0, 0, 0, 56, 68, 16, 2] 0\n",
"[0, 0, 0, 0, 84, 102, 24, 3] 40\n",
"[0, 0, 0, 0, 56, 70, 74, 2] 8\n",
"[0, 0, 0, 0, 84, 105, 111, 3] 0\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 112, 140, 148, 4] -80\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 56, 78, 58, 2] 16\n",
"[0, 0, 0, 0, 56, 92, 64, 2] 36\n",
"[0, 0, 0, 0, 56, 96, 78, 2] 40\n",
"[0, 0, 0, 0, 58, 38, 12, 2] -8\n",
"[0, 0, 0, 0, 87, 57, 18, 3] -16\n",
"[0, 0, 0, 0, 58, 62, 22, 2] 0\n",
"[0, 0, 0, 0, 87, 93, 33, 3] 24\n",
"[0, 0, 0, 0, 58, 64, 18, 2] 0\n",
"[0, 0, 0, 0, 87, 96, 27, 3] 28\n",
"[0, 0, 0, 0, 58, 68, 50, 2] 8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 87, 102, 75, 3] 36\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 58, 70, 60, 2] 12\n",
"[0, 0, 0, 0, 58, 74, 46, 2] 12\n",
"[0, 0, 0, 0, 58, 78, 56, 2] 16\n",
"[0, 0, 0, 0, 58, 82, 58, 2] 20\n",
"[0, 0, 0, 0, 58, 84, 20, 2] 16\n",
"[0, 0, 0, 0, 58, 86, 88, 2] 16\n",
"[0, 0, 0, 0, 58, 88, 26, 2] 28\n",
"[0, 0, 0, 0, 58, 90, 38, 2] 32\n",
"[0, 0, 0, 0, 58, 94, 74, 2] 36\n",
"[0, 0, 0, 0, 60, 40, 8, 2] -12\n",
"[0, 0, 0, 0, 60, 44, 20, 2] -4\n",
"[0, 0, 0, 0, 90, 66, 30, 3] -8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 120, 88, 40, 4] -48\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 60, 54, 12, 2] -12\n",
"[0, 0, 0, 0, 60, 56, 40, 2] 4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 90, 84, 60, 3] 12\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 60, 70, 58, 2] 8\n",
"[0, 0, 0, 0, 90, 105, 87, 3] 36\n",
"[0, 0, 0, 0, 60, 74, 52, 2] 12\n",
"[0, 0, 0, 0, 60, 76, 74, 2] 12\n",
"[0, 0, 0, 0, 60, 80, 34, 2] 20\n",
"[0, 0, 0, 0, 60, 82, 48, 2] 20\n",
"[0, 0, 0, 0, 60, 84, 24, 2] 20\n",
"[0, 0, 0, 0, 60, 86, 68, 2] 28\n",
"[0, 0, 0, 0, 60, 88, 50, 2] 28\n",
"[0, 0, 0, 0, 60, 96, 26, 2] 40\n",
"[0, 0, 0, 0, 60, 98, 72, 2] 44\n",
"[0, 0, 0, 0, 60, 100, 92, 2] 36\n",
"[0, 0, 0, 0, 62, 52, 10, 2] -8\n",
"[0, 0, 0, 0, 93, 78, 15, 3] -12\n",
"[0, 0, 0, 0, 62, 64, 16, 2] 0\n",
"[0, 0, 0, 0, 93, 96, 24, 3] 20\n",
"[0, 0, 0, 0, 62, 68, 28, 2] 8\n",
"[0, 0, 0, 0, 93, 102, 42, 3] 36\n",
"[0, 0, 0, 0, 62, 74, 20, 2] 8\n",
"[0, 0, 0, 0, 93, 111, 30, 3] 52\n",
"[0, 0, 0, 0, 62, 76, 44, 2] 16\n",
"[0, 0, 0, 0, 62, 78, 94, 2] 4\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 93, 117, 141, 3] -84\n",
"[0, 0, 0, 0, 62, 84, 34, 2] 28\n",
"[0, 0, 0, 0, 62, 92, 68, 2] 40\n",
"[0, 0, 0, 0, 62, 94, 84, 2] 36\n",
"[0, 0, 0, 0, 62, 100, 86, 2] 44\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 64, 42, 12, 2] -8\n",
"[0, 0, 0, 0, 96, 63, 18, 3] -24\n",
"[0, 0, 0, 0, 64, 60, 34, 2] 8\n",
"[0, 0, 0, 0, 96, 90, 51, 3] 8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 128, 120, 68, 4] -8\n",
"[0, 0, 0, 0, 160, 150, 85, 5] -44\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 64, 62, 24, 2] 4\n",
"[0, 0, 0, 0, 96, 93, 36, 3] 12\n",
"[0, 0, 0, 0, 64, 66, 26, 2] 8\n",
"[0, 0, 0, 0, 96, 99, 39, 3] 24\n",
"[0, 0, 0, 0, 64, 86, 76, 2] 28\n",
"[0, 0, 0, 0, 64, 92, 56, 2] 36\n",
"[0, 0, 0, 0, 64, 102, 82, 2] 48\n",
"[0, 0, 0, 0, 66, 34, 10, 2] -4\n",
"[0, 0, 0, 0, 99, 51, 15, 3] -32\n",
"[0, 0, 0, 0, 66, 60, 22, 2] 0\n",
"[0, 0, 0, 0, 99, 90, 33, 3] 8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 132, 120, 44, 4] -24\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 66, 68, 90, 2] -4\n",
"[0, 0, 0, 0, 99, 102, 135, 3] -100\n",
"[0, 0, 0, 0, 66, 70, 62, 2] 12\n",
"[0, 0, 0, 0, 66, 72, 76, 2] 12\n",
"[0, 0, 0, 0, 66, 80, 20, 2] 12\n",
"[0, 0, 0, 0, 66, 84, 52, 2] 24\n",
"[0, 0, 0, 0, 66, 94, 40, 2] 40\n",
"[0, 0, 0, 0, 66, 96, 34, 2] 44\n",
"[0, 0, 0, 0, 68, 52, 12, 2] -12\n",
"[0, 0, 0, 0, 68, 56, 24, 2] 0\n",
"[0, 0, 0, 0, 102, 84, 36, 3] -8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 136, 112, 48, 4] -60\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 68, 72, 96, 2] -8\n",
"[0, 0, 0, 0, 102, 108, 144, 3] -128\n",
"[0, 0, 0, 0, 68, 74, 54, 2] 12\n",
"[0, 0, 0, 0, 68, 76, 34, 2] 16\n",
"[0, 0, 0, 0, 68, 80, 82, 2] 12\n",
"[0, 0, 0, 0, 68, 86, 60, 2] 28\n",
"[0, 0, 0, 0, 68, 88, 72, 2] 28\n",
"[0, 0, 0, 0, 68, 90, 94, 2] 16\n",
"[0, 0, 0, 0, 68, 92, 62, 2] 36\n",
"[0, 0, 0, 0, 70, 38, 16, 2] -4\n",
"[0, 0, 0, 0, 105, 57, 24, 3] -36\n",
"[0, 0, 0, 0, 70, 42, 24, 2] 0\n",
"[0, 0, 0, 0, 105, 63, 36, 3] -32\n",
"[0, 0, 0, 0, 70, 50, 30, 2] 0\n",
"[0, 0, 0, 0, 105, 75, 45, 3] -24\n",
"[0, 0, 0, 0, 70, 58, 42, 2] 4\n",
"[0, 0, 0, 0, 105, 87, 63, 3] -8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 140, 116, 84, 4] -68\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 70, 72, 44, 2] 8\n",
"[0, 0, 0, 0, 105, 108, 66, 3] 28\n",
"[0, 0, 0, 0, 70, 76, 46, 2] 12\n",
"[0, 0, 0, 0, 70, 78, 40, 2] 16\n",
"[0, 0, 0, 0, 70, 86, 50, 2] 24\n",
"[0, 0, 0, 0, 70, 92, 90, 2] 20\n",
"[0, 0, 0, 0, 70, 94, 52, 2] 36\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 70, 96, 32, 2] 40\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 70, 102, 96, 2] 32\n",
"[0, 0, 0, 0, 72, 56, 4, 2] -20\n",
"[0, 0, 0, 0, 72, 76, 94, 2] 0\n",
"[0, 0, 0, 0, 108, 114, 141, 3] -120\n",
"[0, 0, 0, 0, 72, 88, 68, 2] 32\n",
"[0, 0, 0, 0, 72, 92, 20, 2] 28\n",
"[0, 0, 0, 0, 72, 96, 88, 2] 32\n",
"[0, 0, 0, 0, 72, 98, 60, 2] 48\n",
"[0, 0, 0, 0, 72, 100, 44, 2] 48\n",
"[0, 0, 0, 0, 74, 50, 18, 2] -4\n",
"[0, 0, 0, 0, 111, 75, 27, 3] -40\n",
"[0, 0, 0, 0, 74, 58, 40, 2] 4\n",
"[0, 0, 0, 0, 111, 87, 60, 3] -24\n",
"[0, 0, 0, 0, 74, 70, 56, 2] 8\n",
"[0, 0, 0, 0, 111, 105, 84, 3] 0\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 148, 140, 112, 4] -76\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 74, 76, 60, 2] 16\n",
"[0, 0, 0, 0, 74, 78, 32, 2] 16\n",
"[0, 0, 0, 0, 74, 80, 102, 2] -8\n",
"[0, 0, 0, 0, 111, 120, 153, 3] -160\n",
"[0, 0, 0, 0, 74, 94, 58, 2] 36\n",
"[0, 0, 0, 0, 74, 102, 20, 2] 44\n",
"[0, 0, 0, 0, 76, 58, 8, 2] -16\n",
"[0, 0, 0, 0, 76, 70, 40, 2] 8\n",
"[0, 0, 0, 0, 114, 105, 60, 3] 0\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 152, 140, 80, 4] -44\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 76, 74, 42, 2] 12\n",
"[0, 0, 0, 0, 76, 82, 98, 2] -4\n",
"[0, 0, 0, 0, 114, 123, 147, 3] -136\n",
"[0, 0, 0, 0, 76, 86, 64, 2] 24\n",
"[0, 0, 0, 0, 76, 88, 18, 2] 20\n",
"[0, 0, 0, 0, 76, 92, 80, 2] 28\n",
"[0, 0, 0, 0, 78, 64, 30, 2] 0\n",
"[0, 0, 0, 0, 117, 96, 45, 3] -28\n",
"[0, 0, 0, 0, 78, 70, 46, 2] 4\n",
"[0, 0, 0, 0, 117, 105, 69, 3] -8\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 156, 140, 92, 4] -68\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 78, 82, 52, 2] 16\n",
"[0, 0, 0, 0, 78, 84, 96, 2] 0\n",
"[0, 0, 0, 0, 117, 126, 144, 3] -120\n",
"[0, 0, 0, 0, 78, 90, 28, 2] 24\n",
"[0, 0, 0, 0, 78, 92, 18, 2] 24\n",
"[0, 0, 0, 0, 78, 96, 56, 2] 36\n",
"[0, 0, 0, 0, 80, 52, 4, 2] -24\n",
"[0, 0, 0, 0, 80, 56, 6, 2] -20\n",
"[0, 0, 0, 0, 80, 58, 26, 2] 0\n",
"[0, 0, 0, 0, 120, 87, 39, 3] -52\n",
"[0, 0, 0, 0, 80, 62, 34, 2] 4\n",
"[0, 0, 0, 0, 120, 93, 51, 3] -44\n",
"[0, 0, 0, 0, 80, 68, 44, 2] 4\n",
"[0, 0, 0, 0, 120, 102, 66, 3] -28\n",
"[0, 0, 0, 0, 80, 82, 88, 2] 8\n",
"[0, 0, 0, 0, 120, 123, 132, 3] -96\n",
"[0, 0, 0, 0, 80, 88, 100, 2] 4\n",
"[0, 0, 0, 0, 120, 132, 150, 3] -140\n",
"[0, 0, 0, 0, 80, 90, 46, 2] 28\n",
"[0, 0, 0, 0, 80, 92, 76, 2] 32\n",
"[0, 0, 0, 0, 80, 98, 18, 2] 36\n",
"[0, 0, 0, 0, 82, 86, 26, 2] 20\n",
"[0, 0, 0, 0, 82, 88, 32, 2] 24\n",
"[0, 0, 0, 0, 82, 94, 46, 2] 32\n",
"[0, 0, 0, 0, 82, 102, 64, 2] 48\n",
"[0, 0, 0, 0, 84, 48, 14, 2] -16\n",
"[0, 0, 0, 0, 84, 60, 16, 2] -12\n",
"[0, 0, 0, 0, 84, 74, 22, 2] 0\n",
"[0, 0, 0, 0, 126, 111, 33, 3] -24\n",
"[0, 0, 0, 0, 84, 76, 28, 2] 4\n",
"[0, 0, 0, 0, 126, 114, 42, 3] -16\n",
"[0, 0, 0, 0, 84, 90, 92, 2] 12\n",
"[0, 0, 0, 0, 84, 94, 62, 2] 32\n",
"[0, 0, 0, 0, 84, 96, 102, 2] 8\n",
"[0, 0, 0, 0, 126, 144, 153, 3] -128\n",
"[0, 0, 0, 0, 84, 102, 46, 2] 44\n",
"[0, 0, 0, 0, 86, 30, 10, 2] -12\n",
"[0, 0, 0, 0, 86, 52, 16, 2] -16\n",
"[0, 0, 0, 0, 86, 68, 42, 2] 0\n",
"[0, 0, 0, 0, 129, 102, 63, 3] -56\n",
"[0, 0, 0, 0, 86, 72, 26, 2] 0\n",
"[0, 0, 0, 0, 129, 108, 39, 3] -44\n",
"[0, 0, 0, 0, 86, 76, 54, 2] 4\n",
"[0, 0, 0, 0, 129, 114, 81, 3] -36\n",
"[0, 0, 0, 0, 86, 80, 48, 2] 8\n",
"[0, 0, 0, 0, 129, 120, 72, 3] -16\n",
"[0, 0, 0, 0, 86, 84, 30, 2] 12\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 86, 94, 38, 2] 28\n",
verbose option added
2020-11-19 06:47:52 +01:00
"[0, 0, 0, 0, 86, 98, 96, 2] 16\n",
"[0, 0, 0, 0, 86, 100, 62, 2] 40\n",
"[0, 0, 0, 0, 86, 102, 98, 2] 20\n",
"[0, 0, 0, 0, 88, 46, 12, 2] -24\n",
plots
2020-11-19 10:32:15 +01:00
"[0, 0, 0, 0, 88, 66, 18, 2] -12\n",
"[0, 0, 0, 0, 88, 72, 88, 2] -12\n",
"[0, 0, 0, 0, 88, 74, 38, 2] 0\n",
"[0, 0, 0, 0, 132, 111, 57, 3] -48\n",
"[0, 0, 0, 0, 88, 82, 80, 2] 4\n",
"[0, 0, 0, 0, 132, 123, 120, 3] -92\n",
"[0, 0, 0, 0, 88, 86, 58, 2] 12\n",
"[0, 0, 0, 0, 88, 94, 90, 2] 12\n",
"[0, 0, 0, 0, 88, 96, 72, 2] 28\n",
"[0, 0, 0, 0, 88, 100, 32, 2] 36\n",
"[0, 0, 0, 0, 90, 34, 8, 2] -20\n",
"[0, 0, 0, 0, 90, 60, 6, 2] -28\n",
"[0, 0, 0, 0, 90, 74, 26, 2] 0\n",
"[0, 0, 0, 0, 135, 111, 39, 3] -56\n",
"[0, 0, 0, 0, 90, 76, 96, 2] -16\n",
"[0, 0, 0, 0, 90, 80, 40, 2] 8\n",
"[0, 0, 0, 0, 135, 120, 60, 3] -32\n",
"[0, 0, 0, 0, 90, 88, 36, 2] 16\n",
"[0, 0, 0, 0, 90, 92, 70, 2] 24\n",
"[0, 0, 0, 0, 90, 94, 88, 2] 16\n",
"[0, 0, 0, 0, 90, 98, 90, 2] 20\n",
"[0, 0, 0, 0, 92, 40, 12, 2] -24\n",
"[0, 0, 0, 0, 92, 76, 32, 2] 0\n",
"[0, 0, 0, 0, 138, 114, 48, 3] -64\n",
"[0, 0, 0, 0, 92, 82, 18, 2] 0\n",
"[0, 0, 0, 0, 138, 123, 27, 3] -40\n",
"[0, 0, 0, 0, 92, 84, 48, 2] 8\n",
"[0, 0, 0, 0, 138, 126, 72, 3] -32\n",
"[0, 0, 0, 0, 92, 90, 84, 2] 12\n",
"[0, 0, 0, 0, 92, 100, 60, 2] 36\n",
"[0, 0, 0, 0, 94, 48, 8, 2] -32\n",
"[0, 0, 0, 0, 94, 54, 26, 2] -16\n",
"[0, 0, 0, 0, 94, 56, 22, 2] -20\n",
"[0, 0, 0, 0, 94, 64, 38, 2] -12\n",
"[0, 0, 0, 0, 94, 66, 46, 2] -12\n",
"[0, 0, 0, 0, 94, 68, 18, 2] -16\n",
"[0, 0, 0, 0, 94, 72, 36, 2] -8\n",
"[0, 0, 0, 0, 141, 108, 54, 3] -88\n",
"[0, 0, 0, 0, 94, 76, 72, 2] -4\n",
"[0, 0, 0, 0, 141, 114, 108, 3] -116\n",
"[0, 0, 0, 0, 94, 78, 62, 2] 0\n",
"[0, 0, 0, 0, 141, 117, 93, 3] -80\n",
"[0, 0, 0, 0, 94, 82, 40, 2] 4\n",
"[0, 0, 0, 0, 141, 123, 60, 3] -48\n",
"[0, 0, 0, 0, 94, 90, 68, 2] 16\n",
"[0, 0, 0, 0, 96, 58, 34, 2] -16\n",
"[0, 0, 0, 0, 96, 62, 20, 2] -24\n",
"[0, 0, 0, 0, 96, 76, 90, 2] -20\n",
"[0, 0, 0, 0, 96, 80, 22, 2] -8\n",
"[0, 0, 0, 0, 144, 120, 33, 3] -68\n",
"[0, 0, 0, 0, 96, 84, 78, 2] 0\n",
"[0, 0, 0, 0, 144, 126, 117, 3] -120\n",
"[0, 0, 0, 0, 96, 86, 48, 2] 4\n",
"[0, 0, 0, 0, 144, 129, 72, 3] -44\n",
"[0, 0, 0, 0, 96, 92, 30, 2] 12\n",
"[0, 0, 0, 0, 96, 98, 86, 2] 16\n",
"[0, 0, 0, 0, 96, 102, 70, 2] 32\n",
"[0, 0, 0, 0, 98, 44, 24, 2] -24\n",
"[0, 0, 0, 0, 98, 64, 26, 2] -20\n",
"[0, 0, 0, 0, 98, 70, 48, 2] -16\n",
"[0, 0, 0, 0, 98, 72, 42, 2] -12\n",
"[0, 0, 0, 0, 98, 82, 76, 2] -4\n",
"[0, 0, 0, 0, 147, 123, 114, 3] -132\n",
"[0, 0, 0, 0, 98, 94, 36, 2] 12\n",
"[0, 0, 0, 0, 98, 96, 50, 2] 16\n",
"[0, 0, 0, 0, 98, 100, 20, 2] 16\n",
"[0, 0, 0, 0, 98, 102, 86, 2] 20\n",
"[0, 0, 0, 0, 100, 38, 10, 2] -32\n",
"[0, 0, 0, 0, 100, 40, 16, 2] -28\n",
"[0, 0, 0, 0, 100, 56, 12, 2] -36\n",
"[0, 0, 0, 0, 100, 58, 28, 2] -24\n",
"[0, 0, 0, 0, 100, 60, 14, 2] -32\n",
"[0, 0, 0, 0, 100, 78, 38, 2] -8\n",
"[0, 0, 0, 0, 150, 117, 57, 3] -104\n",
"[0, 0, 0, 0, 100, 80, 100, 2] -28\n",
"[0, 0, 0, 0, 100, 88, 80, 2] 0\n",
"[0, 0, 0, 0, 150, 132, 120, 3] -136\n",
"[0, 0, 0, 0, 100, 90, 24, 2] 4\n",
"[0, 0, 0, 0, 150, 135, 36, 3] -52\n",
"[0, 0, 0, 0, 100, 92, 42, 2] 12\n",
"[0, 0, 0, 0, 100, 94, 30, 2] 12\n",
"[0, 0, 0, 0, 102, 32, 10, 2] -32\n",
"[0, 0, 0, 0, 102, 42, 4, 2] -48\n",
"[0, 0, 0, 0, 102, 48, 12, 2] -40\n",
"[0, 0, 0, 0, 102, 62, 6, 2] -44\n",
"[0, 0, 0, 0, 102, 64, 44, 2] -24\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[0, 0, 0, 0, 102, 80, 74, 2] -12\n",
"[0, 0, 0, 0, 102, 82, 54, 2] -8\n",
"[0, 0, 0, 0, 153, 123, 81, 3] -104\n",
"[0, 0, 0, 0, 102, 84, 40, 2] -4\n",
"[0, 0, 0, 0, 153, 126, 60, 3] -88\n",
"[0, 0, 0, 0, 102, 96, 84, 2] 8\n",
"[0, 0, 0, 0, 153, 144, 126, 3] -128\n",
"[0, 0, 0, 0, 102, 98, 50, 2] 16\n",
"\n",
"OK\n"
verbose option added
2020-11-19 06:47:52 +01:00
]
plots
2020-11-19 10:32:15 +01:00
},
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
before adding sigma
2020-11-10 17:55:29 +01:00
}
],
"source": [
verbose option added
2020-11-19 06:47:52 +01:00
"slice_canidate.is_function_big_for_all_metabolizers(invariant=cs.SIGMA)"
]
},
{
"cell_type": "code",
plots
2020-11-19 10:32:15 +01:00
"execution_count": 18,
verbose option added
2020-11-19 06:47:52 +01:00
"metadata": {
"scrolled": true
},
plots
2020-11-19 10:32:15 +01:00
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[0, 0, 2, 2, 0, 0, 0, 0] 2\n",
"[0, 0, 3, 3, 0, 0, 0, 0] 2\n",
"[0, 0, 4, 4, 0, 0, 0, 0] -6\n",
"[0, 0, 5, 5, 0, 0, 0, 0] -6\n",
"[0, 0, 6, 6, 0, 0, 0, 0] -6\n",
"[0, 0, 7, 7, 0, 0, 0, 0] -8\n",
"[0, 2, 2, 0, 0, 0, 0, 0] 2\n",
"[0, 3, 3, 0, 0, 0, 0, 0] 2\n",
"[0, 4, 4, 0, 0, 0, 0, 0] -6\n",
"[0, 5, 5, 0, 0, 0, 0, 0] -6\n",
"[0, 6, 6, 0, 0, 0, 0, 0] -6\n",
"[0, 7, 7, 0, 0, 0, 0, 0] -6\n",
"[0, 8, 8, 0, 0, 0, 0, 0] -8\n",
"[0, 4, 4, 0, 0, 0, 0, 0] -6\n",
"[0, 6, 6, 0, 0, 0, 0, 0] -6\n",
"[0, 8, 8, 0, 0, 0, 0, 0] -8\n",
"[0, 6, 6, 0, 0, 0, 0, 0] -6\n",
"[0, 9, 9, 0, 0, 0, 0, 0] -8\n",
"[0, 8, 8, 0, 0, 0, 0, 0] -8\n",
"[0, 10, 10, 0, 0, 0, 0, 0] -8\n",
"[0, 12, 12, 0, 0, 0, 0, 0] -10\n",
"[0, 14, 14, 0, 0, 0, 0, 0] -10\n",
"[2, 0, 0, 2, 0, 0, 0, 0] 4\n",
"[3, 0, 0, 3, 0, 0, 0, 0] 8\n",
"[2, 2, 0, 0, 0, 0, 0, 0] 4\n",
"[3, 3, 0, 0, 0, 0, 0, 0] 8\n",
"[2, 2, 2, 2, 0, 0, 0, 0] 6\n",
"[3, 3, 3, 3, 0, 0, 0, 0] 10\n",
"[2, 4, 4, 2, 0, 0, 0, 0] -10\n",
"[2, 6, 6, 2, 0, 0, 0, 0] -10\n",
"[4, 4, 0, 0, 0, 0, 0, 0] 4\n",
"[6, 6, 0, 0, 0, 0, 0, 0] -4\n",
"[8, 8, 0, 0, 0, 0, 0, 0] 8\n",
"[4, 4, 2, 2, 0, 0, 0, 0] 6\n",
"[6, 6, 3, 3, 0, 0, 0, 0] -6\n",
"[8, 8, 4, 4, 0, 0, 0, 0] -6\n",
"[10, 10, 5, 5, 0, 0, 0, 0] -6\n",
"[12, 12, 6, 6, 0, 0, 0, 0] -8\n",
"[14, 14, 7, 7, 0, 0, 0, 0] 8\n",
"[16, 16, 8, 8, 0, 0, 0, 0] 6\n",
"[18, 18, 9, 9, 0, 0, 0, 0] 10\n",
"[8, 8, 0, 0, 0, 0, 0, 0] 8\n",
"[8, 8, 2, 2, 0, 0, 0, 0] 8\n",
"[12, 12, 3, 3, 0, 0, 0, 0] -6\n",
"[16, 16, 4, 4, 0, 0, 0, 0] 8\n",
"[20, 20, 5, 5, 0, 0, 0, 0] -8\n",
"[24, 24, 6, 6, 0, 0, 0, 0] 10\n",
"[10, 10, 0, 0, 0, 0, 0, 0] 8\n",
"[10, 10, 2, 2, 0, 0, 0, 0] 8\n",
"[15, 15, 3, 3, 0, 0, 0, 0] 10\n",
"[12, 12, 0, 0, 0, 0, 0, 0] -4\n",
"[18, 18, 0, 0, 0, 0, 0, 0] 8\n",
"[12, 12, 2, 2, 0, 0, 0, 0] -6\n",
"[18, 18, 3, 3, 0, 0, 0, 0] 10\n",
"[14, 14, 0, 0, 0, 0, 0, 0] 8\n",
"[14, 14, 2, 2, 0, 0, 0, 0] 10\n",
"[16, 16, 2, 2, 0, 0, 0, 0] 10\n",
"[24, 24, 0, 0, 0, 0, 0, 0] 8\n",
"[24, 24, 2, 2, 0, 0, 0, 0] 10\n",
"[52, 58, 0, 2, 0, 0, 0, 0] 10\n",
"\n",
"OK\n",
"[0, 0, 0, 0, 0, 0, 2, 2] -4\n",
"[0, 0, 0, 0, 0, 0, 3, 3] -4\n",
"[0, 0, 0, 0, 0, 0, 4, 4] -4\n",
"[0, 0, 0, 0, 0, 0, 5, 5] -4\n",
"[0, 0, 0, 0, 0, 0, 6, 6] -4\n",
"[0, 0, 0, 0, 0, 0, 7, 7] 4\n",
"[0, 0, 0, 0, 0, 0, 8, 8] -4\n",
"[0, 0, 0, 0, 0, 0, 9, 9] -4\n",
"[0, 0, 0, 0, 0, 0, 10, 10] -8\n",
"[0, 0, 0, 0, 0, 2, 2, 0] -2\n",
"[0, 0, 0, 0, 0, 3, 3, 0] -2\n",
"[0, 0, 0, 0, 0, 4, 4, 0] 6\n",
"[0, 0, 0, 0, 0, 5, 5, 0] 6\n",
"[0, 0, 0, 0, 0, 6, 6, 0] 6\n",
"[0, 0, 0, 0, 0, 7, 7, 0] 6\n",
"[0, 0, 0, 0, 0, 8, 8, 0] 8\n",
"[0, 0, 0, 0, 0, 4, 4, 0] 6\n",
"[0, 0, 0, 0, 0, 6, 6, 0] 6\n",
"[0, 0, 0, 0, 0, 8, 8, 0] 8\n",
"[0, 0, 0, 0, 0, 6, 6, 0] 6\n",
"[0, 0, 0, 0, 0, 9, 9, 0] 8\n",
"[0, 0, 0, 0, 0, 8, 8, 0] 8\n",
"[0, 0, 0, 0, 0, 10, 10, 0] 8\n",
"[0, 0, 0, 0, 0, 12, 12, 0] 10\n",
"[0, 0, 0, 0, 0, 14, 14, 0] 10\n",
"[0, 0, 0, 0, 0, 46, 36, 2] 10\n",
"[0, 0, 0, 0, 2, 0, 0, 2] -4\n",
"[0, 0, 0, 0, 3, 0, 0, 3] -4\n",
"[0, 0, 0, 0, 4, 0, 0, 4] -8\n",
"[0, 0, 0, 0, 2, 2, 0, 0] -2\n",
"[0, 0, 0, 0, 3, 3, 0, 0] -2\n",
"[0, 0, 0, 0, 4, 4, 0, 0] -2\n",
"[0, 0, 0, 0, 5, 5, 0, 0] 6\n",
"[0, 0, 0, 0, 6, 6, 0, 0] 6\n",
"[0, 0, 0, 0, 7, 7, 0, 0] 6\n",
"[0, 0, 0, 0, 8, 8, 0, 0] 6\n",
"[0, 0, 0, 0, 9, 9, 0, 0] 6\n",
"[0, 0, 0, 0, 10, 10, 0, 0] 8\n",
"[0, 0, 0, 0, 2, 2, 2, 2] -6\n",
"[0, 0, 0, 0, 3, 3, 3, 3] -6\n",
"[0, 0, 0, 0, 4, 4, 4, 4] -6\n",
"[0, 0, 0, 0, 5, 5, 5, 5] 10\n",
"[0, 0, 0, 0, 2, 4, 4, 2] 10\n",
"[0, 0, 0, 0, 2, 6, 6, 2] 10\n",
"[0, 0, 0, 0, 2, 12, 12, 2] 10\n",
"[0, 0, 0, 0, 2, 14, 14, 2] 10\n",
"[0, 0, 0, 0, 2, 16, 16, 2] 12\n",
"[0, 0, 0, 0, 2, 30, 22, 0] 10\n",
"[0, 0, 0, 0, 4, 4, 0, 0] -2\n",
"[0, 0, 0, 0, 6, 6, 0, 0] 6\n",
"[0, 0, 0, 0, 8, 8, 0, 0] 6\n",
"[0, 0, 0, 0, 10, 10, 0, 0] 8\n",
"[0, 0, 0, 0, 4, 4, 2, 2] -6\n",
"[0, 0, 0, 0, 6, 6, 3, 3] 10\n",
"[0, 0, 0, 0, 6, 6, 0, 0] 6\n",
"[0, 0, 0, 0, 9, 9, 0, 0] 6\n",
"[0, 0, 0, 0, 12, 12, 0, 0] 8\n",
"[0, 0, 0, 0, 6, 6, 2, 2] 10\n",
"[0, 0, 0, 0, 8, 8, 0, 0] 6\n",
"[0, 0, 0, 0, 12, 12, 0, 0] 8\n",
"[0, 0, 0, 0, 8, 8, 2, 2] 10\n",
"[0, 0, 0, 0, 10, 10, 0, 0] 8\n",
"[0, 0, 0, 0, 12, 12, 0, 0] 8\n",
"[0, 0, 0, 0, 14, 14, 0, 0] 8\n",
"[0, 0, 0, 0, 16, 16, 0, 0] 10\n",
"[0, 0, 0, 0, 18, 18, 0, 0] 10\n",
"[0, 0, 0, 0, 22, 30, 2, 0] 10\n",
"\n",
"OK\n"
]
},
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
verbose option added
2020-11-19 06:47:52 +01:00
"source": [
"slice_canidate.is_function_big_for_all_metabolizers(invariant=cs.SIGNATURE)"
]
},
{
"cell_type": "code",
plots
2020-11-19 10:32:15 +01:00
"execution_count": 19,
verbose option added
2020-11-19 06:47:52 +01:00
"metadata": {},
plots
2020-11-19 10:32:15 +01:00
"outputs": [
{
"data": {
"text/plain": [
"4"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"text/plain": [
"-4"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
verbose option added
2020-11-19 06:47:52 +01:00
"source": [
"sigma = slice_canidate.get_sigma_as_function_of_theta()\n",
"sigma((0, 6, 6, 0, 0,0,0,0))\n",
"sigma((9, 0, 0, 9, 0,0,0,0))"
]
},
{
"cell_type": "code",
plots
2020-11-19 10:32:15 +01:00
"execution_count": 20,
verbose option added
2020-11-19 06:47:52 +01:00
"metadata": {},
plots
2020-11-19 10:32:15 +01:00
"outputs": [
{
"data": {
"text/plain": [
"0: 0, 49/2822: -1, 1/34: 2, 61/1826: 1, 117/2822: -1, 1/22: -2, 105/1826: 1, 215/2822: -1, 3/34: 2, 283/2822: -1, 227/1826: 1, 381/2822: -1, 3/22: -2, 5/34: 2, 271/1826: 1, 449/2822: -1, 547/2822: -1, 7/34: 2, 393/1826: 1, 615/2822: -1, 5/22: -2, 437/1826: 1, 713/2822: -1, 9/34: 2, 781/2822: -1, 559/1826: 1, 879/2822: -1, 7/22: -2, 11/34: 2, 603/1826: 1, 947/2822: -1, 1045/2822: -1, 13/34: 2, 1113/2822: -1, 725/1826: 1, 9/22: -2, 769/1826: 1, 1211/2822: -1, 15/34: 2, 1279/2822: -1, 1543/2822: 1, 19/34: -2, 1611/2822: 1, 1057/1826: -1, 13/22: 2, 1101/1826: -1, 1709/2822: 1, 21/34: -2, 1777/2822: 1, 1875/2822: 1, 1223/1826: -1, 23/34: -2, 15/22: 2, 1943/2822: 1, 1267/1826: -1, 2041/2822: 1, 25/34: -2, 2109/2822: 1, 1389/1826: -1, 17/22: 2, 2207/2822: 1, 1433/1826: -1, 27/34: -2, 2275/2822: 1, 2373/2822: 1, 1555/1826: -1, 29/34: -2, 19/22: 2, 2441/2822: 1, 1599/1826: -1, 2539/2822: 1, 31/34: -2, 2607/2822: 1, 1721/1826: -1, 21/22: 2, 2705/2822: 1, 1765/1826: -1, 33/34: -2, 2773/2822: 1, 1: 0."
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
verbose option added
2020-11-19 06:47:52 +01:00
"source": [
"_, _, sf = slice_canidate((1, 1, 0, 0, 0,0,0,0))\n",
"sf"
]
},
{
"cell_type": "code",
plots
2020-11-19 10:32:15 +01:00
"execution_count": 21,
verbose option added
2020-11-19 06:47:52 +01:00
"metadata": {},
plots
2020-11-19 10:32:15 +01:00
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
verbose option added
2020-11-19 06:47:52 +01:00
"source": [
"cs = import_sage('cable_signature')\n",
"sg = import_sage('signature')\n",
"sg.SignaturePloter.plot(sf)"
]
},
{
"cell_type": "code",
plots
2020-11-19 10:32:15 +01:00
"execution_count": 22,
verbose option added
2020-11-19 06:47:52 +01:00
"metadata": {
"scrolled": true
},
plots
2020-11-19 10:32:15 +01:00
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"T_17_83_inv_T_11_83_T_83_inv_T_13_83_T_11_103_inv_T_103_T_13_103_inv_T_17_103\n"
]
},
{
"ename": "TypeError",
"evalue": "unable to convert [0, 4, 0, 4, 0, 0, 0, 0] to a rational",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-22-c4fd4acceb8f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0msg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mimport_sage\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'signature'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mslice_canidate\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot_sum_for_theta_vector\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mInteger\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mInteger\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m4\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mInteger\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mInteger\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m4\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mInteger\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mInteger\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mInteger\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mInteger\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msave_to_dir\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m/Users/Kasia/signature_function/cable_signature.py\u001b[0m in \u001b[0;36mplot_sum_for_theta_vector\u001b[0;34m(self, thetas, save_to_dir)\u001b[0m\n\u001b[1;32m 342\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 343\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mtheta\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mknot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mthetas\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mknot_summands\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 344\u001b[0;31m \u001b[0mknot\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot_summand_for_theta\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mthetas\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msave_path\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msave_path\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 345\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 346\u001b[0m \u001b[0;31m# pp, sp, sf = self.signature_as_function_of_theta(*thetas)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/Users/Kasia/signature_function/cable_signature.py\u001b[0m in \u001b[0;36mplot_summand_for_theta\u001b[0;34m(self, theta, save_path)\u001b[0m\n\u001b[1;32m 195\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 196\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mplot_summand_for_theta\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtheta\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msave_path\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 197\u001b[0;31m \u001b[0mpp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msignature_as_function_of_theta\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtheta\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 198\u001b[0m \u001b[0mtitle\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mknot_description\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m\", theta = \"\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtheta\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 199\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0msave_path\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/Users/Kasia/signature_function/cable_signature.py\u001b[0m in \u001b[0;36mget_summand_signture_function\u001b[0;34m(theta)\u001b[0m\n\u001b[1;32m 161\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 162\u001b[0m \u001b[0;31m# theta should not be larger than k for the pattern.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 163\u001b[0;31m \u001b[0mtheta\u001b[0m \u001b[0;34m%=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0m_sage_const_2\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mabs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpatt_k\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0m_sage_const_1\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 164\u001b[0m \u001b[0mtheta\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtheta\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_sage_const_2\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mabs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpatt_k\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0m_sage_const_1\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mtheta\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 165\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/Applications/SageMath-9.0.app/Contents/Resources/sage/local/lib/python3.7/site-packages/sage/rings/rational.pyx\u001b[0m in \u001b[0;36msage.rings.rational.Rational.__mod__ (build/cythonized/sage/rings/rational.c:23158)\u001b[0;34m()\u001b[0m\n\u001b[1;32m 2815\u001b[0m \u001b[0mcdef\u001b[0m \u001b[0mRational\u001b[0m \u001b[0mrat\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2816\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mRational\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2817\u001b[0;31m \u001b[0mrat\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mRational\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2818\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2819\u001b[0m \u001b[0mrat\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/Applications/SageMath-9.0.app/Contents/Resources/sage/local/lib/python3.7/site-packages/sage/rings/rational.pyx\u001b[0m in \u001b[0;36msage.rings.rational.Rational.__init__ (build/cythonized/sage/rings/rational.c:6392)\u001b[0;34m()\u001b[0m\n\u001b[1;32m 527\u001b[0m \"\"\"\n\u001b[1;32m 528\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 529\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__set_value\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbase\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 530\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 531\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__reduce__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/Applications/SageMath-9.0.app/Contents/Resources/sage/local/lib/python3.7/site-packages/sage/rings/rational.pyx\u001b[0m in \u001b[0;36msage.rings.rational.Rational.__set_value (build/cythonized/sage/rings/rational.c:8515)\u001b[0;34m()\u001b[0m\n\u001b[1;32m 683\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 684\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 685\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"unable to convert {!r} to a rational\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 686\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 687\u001b[0m \u001b[0mcdef\u001b[0m \u001b[0mvoid\u001b[0m \u001b[0mset_from_mpq\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mRational\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmpq_t\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mTypeError\u001b[0m: unable to convert [0, 4, 0, 4, 0, 0, 0, 0] to a rational"
]
}
],
verbose option added
2020-11-19 06:47:52 +01:00
"source": [
"cs = import_sage('cable_signature')\n",
"sg = import_sage('signature')\n",
"\n",
before adding sigma
2020-11-10 17:55:29 +01:00
"slice_canidate.plot_sum_for_theta_vector([0,4,0,4,0,0,0,0], save_to_dir=True)"
]
},
{
"cell_type": "code",
verbose option added
2020-11-19 06:47:52 +01:00
"execution_count": null,
before adding sigma
2020-11-10 17:55:29 +01:00
"metadata": {},
verbose option added
2020-11-19 06:47:52 +01:00
"outputs": [],
before adding sigma
2020-11-10 17:55:29 +01:00
"source": [
"sf.plot()\n"
]
},
verbose option added
2020-11-19 06:47:52 +01:00
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
add jupyter notebook
2020-11-09 09:34:33 +01:00
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "SageMath 9.0",
"language": "sage",
"name": "sagemath"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
Reference in New Issue Copy Permalink