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October 13, 2016 22:32
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{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [], | |
"source": [ | |
"import flavio\n", | |
"import flavio.statistics.fits\n", | |
"import flavio.plots\n", | |
"import numpy as np\n", | |
"import matplotlib\n", | |
"import matplotlib.pyplot as plt\n", | |
"%matplotlib inline\n", | |
"plt.rc('text', usetex=True)\n", | |
"plt.rcParams['savefig.dpi'] = 100\n", | |
"plt.rc('font', **{'family': 'serif', 'serif': ['Computer Modern']})" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 2, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [ | |
"def wc_fct(C9, C10):\n", | |
" return { 'C9_bsmumu': C9, 'C10_bsmumu': C10, }" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 3, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [], | |
"source": [ | |
"observables = {}\n", | |
"\n", | |
"observables['Bs->mumu'] = [ 'BR(Bs->mumu)' ]\n", | |
"\n", | |
"observables['B->K*mumu'] = [\n", | |
" ('<FL>(B0->K*mumu)', 1, 2),\n", | |
" ('<FL>(B0->K*mumu)', 1.1, 2.5),\n", | |
" ('<FL>(B0->K*mumu)', 2, 4.3),\n", | |
" ('<FL>(B0->K*mumu)', 2.5, 4),\n", | |
" ('<FL>(B0->K*mumu)', 4, 6),\n", | |
" ('<FL>(B0->K*mumu)', 4.3, 6),\n", | |
" ('<FL>(B0->K*mumu)', 15, 19),\n", | |
" ('<FL>(B0->K*mumu)', 16, 19),\n", | |
" ('<S3>(B0->K*mumu)', 1.1, 2.5),\n", | |
" ('<S3>(B0->K*mumu)', 2.5, 4),\n", | |
" ('<S3>(B0->K*mumu)', 4, 6),\n", | |
" ('<S3>(B0->K*mumu)', 15, 19),\n", | |
" ('<S4>(B0->K*mumu)', 1.1, 2.5),\n", | |
" ('<S4>(B0->K*mumu)', 2.5, 4),\n", | |
" ('<S4>(B0->K*mumu)', 4, 6),\n", | |
" ('<S4>(B0->K*mumu)', 15, 19),\n", | |
" ('<S5>(B0->K*mumu)', 1.1, 2.5),\n", | |
" ('<S5>(B0->K*mumu)', 2.5, 4),\n", | |
" ('<S5>(B0->K*mumu)', 4, 6),\n", | |
" ('<S5>(B0->K*mumu)', 15, 19),\n", | |
" ('<dBR/dq2>(B+->K*mumu)', 2.0, 4.0),\n", | |
" ('<dBR/dq2>(B+->K*mumu)', 4.0, 6.0),\n", | |
" ('<dBR/dq2>(B+->K*mumu)', 15.0, 19.0),\n", | |
" ('<dBR/dq2>(B0->K*mumu)', 1.1, 2.5),\n", | |
" ('<dBR/dq2>(B0->K*mumu)', 2.5, 4.0),\n", | |
" ('<dBR/dq2>(B0->K*mumu)', 4.0, 6.0),\n", | |
" ('<dBR/dq2>(B0->K*mumu)', 15.0, 19.0),\n", | |
"]\n", | |
"observables['Bs->phimumu'] = [\n", | |
" ('<FL>(Bs->phimumu)', 1.0, 6.0),\n", | |
" ('<FL>(Bs->phimumu)', 2.0, 5.0),\n", | |
" ('<FL>(Bs->phimumu)', 15.0, 19.0),\n", | |
" ('<S3>(Bs->phimumu)', 2.0, 5.0),\n", | |
" ('<S3>(Bs->phimumu)', 15.0, 19.0),\n", | |
" ('<S4>(Bs->phimumu)', 2.0, 5.0),\n", | |
" ('<S4>(Bs->phimumu)', 5.0, 8.0),\n", | |
" ('<S4>(Bs->phimumu)', 15.0, 19.0),\n", | |
" ('<dBR/dq2>(Bs->phimumu)', 1.0, 6.0),\n", | |
" ('<dBR/dq2>(Bs->phimumu)', 15.0, 19.0),\n", | |
"]\n", | |
"observables['B->Kmumu'] = [\n", | |
" ('<dBR/dq2>(B+->Kmumu)', 1.1, 2.0),\n", | |
" ('<dBR/dq2>(B+->Kmumu)', 2.0, 3.0),\n", | |
" ('<dBR/dq2>(B+->Kmumu)', 3.0, 4.0),\n", | |
" ('<dBR/dq2>(B+->Kmumu)', 4.0, 5.0),\n", | |
" ('<dBR/dq2>(B+->Kmumu)', 5.0, 6.0),\n", | |
" ('<dBR/dq2>(B+->Kmumu)', 15.0, 22.0),\n", | |
" ('<dBR/dq2>(B0->Kmumu)', 2.0, 4.0),\n", | |
" ('<dBR/dq2>(B0->Kmumu)', 4.0, 6.0),\n", | |
" ('<dBR/dq2>(B0->Kmumu)', 15.0, 22.0),\n", | |
"]\n", | |
"\n", | |
"observables['global'] = [x for k, v in observables.items() for x in v ] # all the above" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 4, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [], | |
"source": [ | |
"fit={}\n", | |
"for name in observables:\n", | |
" fit[name] = flavio.statistics.fits.FastFit('C9-C10 fit bs ' + name,\n", | |
" par_obj = flavio.default_parameters,\n", | |
" fit_parameters = [],\n", | |
" nuisance_parameters = flavio.default_parameters.all_parameters,\n", | |
" observables = observables[name],\n", | |
" fit_wc_names = wc_fct.__code__.co_varnames,\n", | |
" fit_wc_function = wc_fct,\n", | |
" input_scale = 4.8,\n", | |
" )" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 5, | |
"metadata": { | |
"collapsed": false, | |
"scrolled": false | |
}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"CPU times: user 45min 13s, sys: 596 ms, total: 45min 14s\n", | |
"Wall time: 45min 13s\n" | |
] | |
} | |
], | |
"source": [ | |
"%%time\n", | |
"for name in observables:\n", | |
" fit[name].make_measurement(N=200)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 6, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [], | |
"source": [ | |
"red = flavio.plots.colors.set1[0]\n", | |
"red_list = [ (red[0]*(1-i/4)+i/4, red[1]*(1-i/4)+i/4, red[2]*(1-i/4)+i/4) for i in range(5) ]" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 7, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"CPU times: user 10min 32s, sys: 1min 39s, total: 12min 12s\n", | |
"Wall time: 10min 21s\n" | |
] | |
}, | |
{ | |
"data": { | |
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twSkfqESjKIkmpSQ6dx7l/xyPvmEDrt69yH3kYVw9utsdmqLUK+9pgwlO/gAZCiF8PrvD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| |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x7f80af02f710>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"%%time\n", | |
"steps=20\n", | |
"plt.figure(figsize=(4.2,4.2))\n", | |
"flavio.plots.band_plot(fit['global'].log_likelihood, -2.45, 0.55, -1, 2, n_sigma=(1,2,3,4), steps=steps,\n", | |
" interpolation_factor=3,\n", | |
" contourf_args={'alpha': 0.5, 'colors': red_list},\n", | |
" contour_args={'colors': red_list[0]})\n", | |
"flavio.plots.flavio_branding(x=0.05, y=0.09)\n", | |
"plt.axhline(0, c='k', lw=0.2)\n", | |
"plt.axvline(0, c='k', lw=0.2)\n", | |
"plt.xlabel(r'$\\text{Re}\\, C_9^\\text{NP}$')\n", | |
"plt.ylabel(r'$\\text{Re}\\, C_{10}^\\text{NP}$')\n", | |
"plt.tight_layout()\n", | |
"plt.savefig('C9-C10.pdf')" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 9, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"CPU times: user 11min 46s, sys: 3min 1s, total: 14min 47s\n", | |
"Wall time: 11min 22s\n" | |
] | |
}, | |
{ | |
"data": { | |
"image/png": 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Kc4qPjyc0NJScnBzy8vL4/vd7K9ZhfYcOHeozwSQkJFgswVjqXo5OPckoimJXwcHBNlt4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\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x7f80ae327780>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"%%time\n", | |
"steps=20\n", | |
"plt.figure(figsize=(4.2,4.2))\n", | |
"flavio.plots.band_plot(fit['B->K*mumu'].log_likelihood, -3.5, 0.5, -1.5, 2.5, n_sigma=1, steps=steps, col=1,\n", | |
" interpolation_factor=3, label=r'$B\\to K^*\\mu^+\\mu^-$')\n", | |
"flavio.plots.band_plot(fit['Bs->phimumu'].log_likelihood, -3.5, 0.5, -1.5, 2.5, n_sigma=1, steps=steps, col=2,\n", | |
" interpolation_factor=3, label=r'$B_s\\to \\phi\\mu^+\\mu^-$')\n", | |
"flavio.plots.band_plot(fit['B->Kmumu'].log_likelihood, -3.5, 0.5, -1.5, 2.5, n_sigma=1, steps=steps, col=3,\n", | |
" interpolation_factor=1, label=r'$B\\to K\\mu^+\\mu^-$')\n", | |
"flavio.plots.flavio_branding(x=0.1, y=0.09)\n", | |
"plt.axhline(0, c='k', lw=0.2)\n", | |
"plt.axvline(0, c='k', lw=0.2)\n", | |
"plt.legend()\n", | |
"plt.xlabel(r'$\\text{Re}\\, C_9^\\text{NP}$')\n", | |
"plt.ylabel(r'$\\text{Re}\\, C_{10}^\\text{NP}$')\n", | |
"plt.tight_layout()\n", | |
"plt.savefig('C9-C10-modes.pdf')" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python 3", | |
"language": "python", | |
"name": "python3" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 3 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython3", | |
"version": "3.5.2" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 1 | |
} |
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