From 08eafa5387df05fd13fc209d79dc49c22d7badd1 Mon Sep 17 00:00:00 2001 From: EtienneCmb Date: Fri, 5 Jul 2024 13:33:15 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20brainets?= =?UTF-8?q?/hoi@7f5e6d0961d998efa60a06a61ee2948dd3ca6e8a=20=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../auto_examples_python.zip | Bin 75868 -> 75869 bytes .../plot_oinfo.ipynb | 4 +- .../auto_examples_jupyter.zip | Bin 110194 -> 110197 bytes .../plot_oinfo.py | 2 +- auto_examples/it/plot_entropies.html | 2 +- auto_examples/it/plot_entropies_mvar.html | 2 +- auto_examples/it/plot_mi.html | 2 +- auto_examples/it/plot_tutorial_core.html | 2 +- auto_examples/it/sg_execution_times.html | 10 ++--- auto_examples/metrics/plot_infotopo.html | 20 +++++----- auto_examples/metrics/plot_oinfo.html | 37 +++++++++--------- auto_examples/metrics/plot_rsi.html | 32 +++++++-------- auto_examples/metrics/plot_syn_phiID.html | 10 ++--- auto_examples/metrics/sg_execution_times.html | 10 ++--- .../miscellaneous/plot_inspect_results.html | 16 ++++---- auto_examples/miscellaneous/plot_jax.html | 6 +-- .../miscellaneous/sg_execution_times.html | 6 +-- .../statistics/plot_bootstrapping.html | 2 +- .../statistics/sg_execution_times.html | 4 +- auto_examples/tutorials/plot_ml_vs_it.html | 2 +- auto_examples/tutorials/plot_sim_red_syn.html | 32 +++++++-------- .../tutorials/sg_execution_times.html | 6 +-- searchindex.js | 2 +- sg_execution_times.html | 28 ++++++------- 24 files changed, 118 insertions(+), 119 deletions(-) diff --git a/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip b/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip index e5e393d76e03b1629187bc2ed09960803b2d4859..aab7c722f90b025ee6abb744374bb92063d45769 100644 GIT binary patch delta 342 zcmca}f#vQ67M=iaW)=|!5O|Zlk;jmS>1+08d!8M_OmDI`|CHAeU}DMHtZq;%%EX(q zd70}m0VbiG&3R!3;=IB+Pa{sX%@aAI#=vl7^XuFkk;zBwL^fwNWeG9y=WM<<#axt0 zA!jrHs`o-nvN@afy6`fI=4^I5Sx_ z1hjejO(2(vWz}SXy`s~3)EPmpn697>6#KddD5kC*;LXS+!VK}dD9|(Qh8*gGQVa|r ztN;!X2(hHmdin%)Mtz{Orym6BXY87OPn}T*==$kA8bI#9>6#jhx@;R&7=h{mc~WM5 delta 365 zcmcb6f#uEx7M=iaW)=|!5Lg(!k;jmSX;t)Qd!8M_Obeqo|CHAeVA>wNS>2#kl<83P z=4GzO1elIRZ_W!V5a&G}{WM}`PZZ~2H3o*mn_uVVh)iyrF1$IrDNBgyNc86GQ_Mw~ zE=O+`SoL0r>0I)fiYRRGolytqr|G;JKzIC|uBE}K L%eFy<5vU3Pp;vIh diff --git a/_downloads/2d62e710e011551b615a935858a62b71/plot_oinfo.ipynb b/_downloads/2d62e710e011551b615a935858a62b71/plot_oinfo.ipynb index aa373694..33eb9ac6 100644 --- a/_downloads/2d62e710e011551b615a935858a62b71/plot_oinfo.ipynb +++ b/_downloads/2d62e710e011551b615a935858a62b71/plot_oinfo.ipynb @@ -115,7 +115,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### S-information\nFinally, the S-information is defined as the sum of the TC and DTC :\n\n" + "### S-information\nFinally, the S-information is defined as the sum of the TC and DTC :\n\n\\begin{align}\\Omega(X^{n}) &= TC(X^{n}) + DTC(X^{n}) \\\\\n &= nH(X^{n}) + \\sum_{j=1}^{n} [H(X_{j}) + H(\n X_{-j}^{n})]\\end{align}\n\n" ] }, { @@ -126,7 +126,7 @@ }, "outputs": [], "source": [ - "# .. math::\n# \\Omega(X^{n}) &= TC(X^{n}) + DTC(X^{n}) \\\\\n# &= nH(X^{n}) + \\sum_{j=1}^{n} [H(X_{j}) + H(\n# X_{-j}^{n})]\n\n# compute hoi using the S-information :\nmodel = Sinfo(x)\nhoi = model.fit(method=\"gc\", minsize=3, maxsize=3)\n\n# get the multiplets with largest values of hoi\nprint(get_nbest_mult(hoi, model))" + "# compute hoi using the S-information :\nmodel = Sinfo(x)\nhoi = model.fit(method=\"gc\", minsize=3, maxsize=3)\n\n# get the multiplets with largest values of hoi\nprint(get_nbest_mult(hoi, model))" ] }, { diff --git a/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip b/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip index 49575f7c189842aaf5326d0b4a4a94c9ad45aa6b..6adb6212d1678fa9aa8fe763f488a9ce62c83209 100644 GIT binary patch delta 359 zcmex#hwbYfHl6@)W)=|!5O|Zlk>{Tf6HCr!9^r%1OkcA%pV#{(!o-`i`LuJXG!uW$ zW~X>pNhaZ(&7Bo@-nTpwC%!oX0wxo8Hr)MUGLI+N2k3s0_HCq8-dW}V5$ z)(KC(w@zkq^-k^S4mpeyCfhF&+Wcd)tR$0A&SvqmX|ha;Ih*TW$;mP)EhWN*LT!FWXx$e6x%6{9=Qfz!XOV)OtyaJs{4MjN05 zr`N4!bOt(b`r*|;dEuPtJZl&|P#riuaSfv-(Aw#9)&R}to4#`mqbkt$=?{Qhrm|O) z`(MdTms!im19ZuBt+k9Y%+uHzr*B|q)Z`2BW@Hj!h6Isp&h!SLB;$|ibJsE&0o^$L gB8WSG`n$D^`XC3&uLE+=O}AOcXu!5;6(cZI0YAEaJOBUy delta 450 zcmex*hwalHHl6@)W)=|!5Lg(!k>{Tf)As1iJi-U1nN~$_KCkyngy~T9=F`rl(o9F9 zH#^0R83VM19xrrqiR#q{2 z$_gMb*=L>HnHHi%4~u#RQ&*_m z=*>;9UuIQjNX2$gYk+YkTHG3Dn@sp zyQlwL#pnTa_jKpgj5a`bPj6h!=nQoC^kb`m^2ej6^RHp_Ky~-@lr@Z&Kx?PZU&AQF z$US|}8b($5D?pzq^gqAzOoo90gnwLmSCr+cksG?%{!)Us&a zJFPTj1_lrYA~;ym_;vb%wTwpcvw?~>IDX*x=)u4M!U}LD3=B&e=S=^&mQi1RAyAQG c-Liz4iVO@OEQ_M(^mO}mj0SA;S1|&G0ehUAW&i*H diff --git a/_downloads/f089696c3572cc479d2da98315c1bf83/plot_oinfo.py b/_downloads/f089696c3572cc479d2da98315c1bf83/plot_oinfo.py index 8c6fbdd2..44be15d6 100644 --- a/_downloads/f089696c3572cc479d2da98315c1bf83/plot_oinfo.py +++ b/_downloads/f089696c3572cc479d2da98315c1bf83/plot_oinfo.py @@ -145,7 +145,7 @@ # S-information # ^^^^^^^^^^^^^ # Finally, the S-information is defined as the sum of the TC and DTC : - +# # .. math:: # \Omega(X^{n}) &= TC(X^{n}) + DTC(X^{n}) \\ # &= nH(X^{n}) + \sum_{j=1}^{n} [H(X_{j}) + H( diff --git a/auto_examples/it/plot_entropies.html b/auto_examples/it/plot_entropies.html index b8a4c321..90692c04 100644 --- a/auto_examples/it/plot_entropies.html +++ b/auto_examples/it/plot_entropies.html @@ -606,7 +606,7 @@

Entropy of data sampled from an exponential distributionplt.show() -Comparison of entropy estimators when the data are sampled from a exponential distribution

Total running time of the script: (0 minutes 17.860 seconds)

+Comparison of entropy estimators when the data are sampled from a exponential distribution

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 -2-dimensional multivariate normal, 4-dimensional multivariate normal, 6-dimensional multivariate normal, 8-dimensional multivariate normal

Total running time of the script: (0 minutes 26.034 seconds)

+2-dimensional multivariate normal, 4-dimensional multivariate normal, 6-dimensional multivariate normal, 8-dimensional multivariate normal

Total running time of the script: (0 minutes 26.454 seconds)

 -Comparison of MI estimators when the data are sampled from a normal distribution

Total running time of the script: (0 minutes 17.125 seconds)

+Comparison of MI estimators when the data are sampled from a normal distribution

Total running time of the script: (0 minutes 17.317 seconds)