diff --git a/docs/Basic Usage.ipynb b/docs/Basic Usage.ipynb index 1fa3e07..6820df3 100644 --- a/docs/Basic Usage.ipynb +++ b/docs/Basic Usage.ipynb @@ -26,7 +26,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ @@ -54,7 +54,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ @@ -80,7 +80,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 25, "metadata": {}, "outputs": [ { @@ -113,36 +113,17 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "INFO:autora.theorist.bms.regressor:BMS fitting started\n" - ] - }, - { - "ename": "KeyboardInterrupt", - "evalue": "", - "output_type": "error", - "traceback": [ - "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m", - "\u001B[1;31mKeyboardInterrupt\u001B[0m Traceback (most recent call last)", - "Cell \u001B[1;32mIn[6], line 7\u001B[0m\n\u001B[0;32m 4\u001B[0m darts_theorist \u001B[39m=\u001B[39m DARTSRegressor()\n\u001B[0;32m 6\u001B[0m \u001B[39m#Fit theorists\u001B[39;00m\n\u001B[1;32m----> 7\u001B[0m bms_theorist\u001B[39m.\u001B[39;49mfit(X,ground_truth(X))\n\u001B[0;32m 8\u001B[0m bsr_theorist\u001B[39m.\u001B[39mfit(X,ground_truth(X))\n\u001B[0;32m 9\u001B[0m darts_theorist\u001B[39m.\u001B[39mfit(X,ground_truth(X))\n", - "File \u001B[1;32mc:\\Users\\cwill\\GitHub\\virtualEnvs\\autoraEnv\\lib\\site-packages\\autora\\theorist\\bms\\regressor.py:133\u001B[0m, in \u001B[0;36mBMSRegressor.fit\u001B[1;34m(self, X, y, num_param, root, custom_ops, seed)\u001B[0m\n\u001B[0;32m 120\u001B[0m \u001B[39mself\u001B[39m\u001B[39m.\u001B[39madd_primitive(root)\n\u001B[0;32m 121\u001B[0m \u001B[39mself\u001B[39m\u001B[39m.\u001B[39mpms \u001B[39m=\u001B[39m Parallel(\n\u001B[0;32m 122\u001B[0m Ts\u001B[39m=\u001B[39m\u001B[39mself\u001B[39m\u001B[39m.\u001B[39mts,\n\u001B[0;32m 123\u001B[0m variables\u001B[39m=\u001B[39m\u001B[39mself\u001B[39m\u001B[39m.\u001B[39mvariables,\n\u001B[1;32m (...)\u001B[0m\n\u001B[0;32m 131\u001B[0m seed\u001B[39m=\u001B[39mseed,\n\u001B[0;32m 132\u001B[0m )\n\u001B[1;32m--> 133\u001B[0m \u001B[39mself\u001B[39m\u001B[39m.\u001B[39mmodel_, \u001B[39mself\u001B[39m\u001B[39m.\u001B[39mloss_, \u001B[39mself\u001B[39m\u001B[39m.\u001B[39mcache_ \u001B[39m=\u001B[39m utils\u001B[39m.\u001B[39;49mrun(\u001B[39mself\u001B[39;49m\u001B[39m.\u001B[39;49mpms, \u001B[39mself\u001B[39;49m\u001B[39m.\u001B[39;49mepochs)\n\u001B[0;32m 134\u001B[0m \u001B[39mself\u001B[39m\u001B[39m.\u001B[39mmodels_ \u001B[39m=\u001B[39m \u001B[39mlist\u001B[39m(\u001B[39mself\u001B[39m\u001B[39m.\u001B[39mpms\u001B[39m.\u001B[39mtrees\u001B[39m.\u001B[39mvalues())\n\u001B[0;32m 136\u001B[0m _logger\u001B[39m.\u001B[39minfo(\u001B[39m\"\u001B[39m\u001B[39mBMS fitting finished\u001B[39m\u001B[39m\"\u001B[39m)\n", - "File \u001B[1;32mc:\\Users\\cwill\\GitHub\\virtualEnvs\\autoraEnv\\lib\\site-packages\\autora\\theorist\\bms\\utils.py:35\u001B[0m, in \u001B[0;36mrun\u001B[1;34m(pms, num_steps, thinning)\u001B[0m\n\u001B[0;32m 33\u001B[0m desc_len, model, model_len \u001B[39m=\u001B[39m [], pms\u001B[39m.\u001B[39mt1, np\u001B[39m.\u001B[39minf\n\u001B[0;32m 34\u001B[0m \u001B[39mfor\u001B[39;00m n \u001B[39min\u001B[39;00m tqdm(\u001B[39mrange\u001B[39m(num_steps)):\n\u001B[1;32m---> 35\u001B[0m pms\u001B[39m.\u001B[39;49mmcmc_step()\n\u001B[0;32m 36\u001B[0m pms\u001B[39m.\u001B[39mtree_swap()\n\u001B[0;32m 37\u001B[0m \u001B[39mif\u001B[39;00m num_steps \u001B[39m%\u001B[39m thinning \u001B[39m==\u001B[39m \u001B[39m0\u001B[39m: \u001B[39m# sample less often if we thin more\u001B[39;00m\n", - "File \u001B[1;32mc:\\Users\\cwill\\GitHub\\virtualEnvs\\autoraEnv\\lib\\site-packages\\autora\\theorist\\bms\\parallel.py:102\u001B[0m, in \u001B[0;36mParallel.mcmc_step\u001B[1;34m(self, verbose, p_rr, p_long)\u001B[0m\n\u001B[0;32m 99\u001B[0m p_rr \u001B[39m=\u001B[39m \u001B[39m0.0\u001B[39m\n\u001B[0;32m 100\u001B[0m \u001B[39mfor\u001B[39;00m T, tree \u001B[39min\u001B[39;00m \u001B[39mlist\u001B[39m(\u001B[39mself\u001B[39m\u001B[39m.\u001B[39mtrees\u001B[39m.\u001B[39mitems()):\n\u001B[0;32m 101\u001B[0m \u001B[39m# MCMC step\u001B[39;00m\n\u001B[1;32m--> 102\u001B[0m tree\u001B[39m.\u001B[39;49mmcmc_step(verbose\u001B[39m=\u001B[39;49mverbose, p_rr\u001B[39m=\u001B[39;49mp_rr, p_long\u001B[39m=\u001B[39;49mp_long)\n\u001B[0;32m 103\u001B[0m \u001B[39mself\u001B[39m\u001B[39m.\u001B[39mt1 \u001B[39m=\u001B[39m \u001B[39mself\u001B[39m\u001B[39m.\u001B[39mtrees[\u001B[39m\"\u001B[39m\u001B[39m1.0\u001B[39m\u001B[39m\"\u001B[39m]\n", - "File \u001B[1;32mc:\\Users\\cwill\\GitHub\\virtualEnvs\\autoraEnv\\lib\\site-packages\\autora\\theorist\\bms\\mcmc.py:1251\u001B[0m, in \u001B[0;36mTree.mcmc_step\u001B[1;34m(self, verbose, p_rr, p_long)\u001B[0m\n\u001B[0;32m 1249\u001B[0m sf \u001B[39m=\u001B[39m \u001B[39mlen\u001B[39m(\u001B[39mself\u001B[39m\u001B[39m.\u001B[39met_space[ofin])\n\u001B[0;32m 1250\u001B[0m \u001B[39m# Probability of acceptance\u001B[39;00m\n\u001B[1;32m-> 1251\u001B[0m dE, dEB, dEP, par_valuesNew, nif, nfi \u001B[39m=\u001B[39m \u001B[39mself\u001B[39;49m\u001B[39m.\u001B[39;49mdE_et(\n\u001B[0;32m 1252\u001B[0m target, new, verbose\u001B[39m=\u001B[39;49mverbose\n\u001B[0;32m 1253\u001B[0m )\n\u001B[0;32m 1254\u001B[0m \u001B[39mtry\u001B[39;00m:\n\u001B[0;32m 1255\u001B[0m paccept \u001B[39m=\u001B[39m (\n\u001B[0;32m 1256\u001B[0m \u001B[39mfloat\u001B[39m(nif) \u001B[39m*\u001B[39m omegai \u001B[39m*\u001B[39m sf \u001B[39m*\u001B[39m np\u001B[39m.\u001B[39mexp(\u001B[39m-\u001B[39mdEB \u001B[39m/\u001B[39m \u001B[39mself\u001B[39m\u001B[39m.\u001B[39mBT \u001B[39m-\u001B[39m dEP \u001B[39m/\u001B[39m \u001B[39mself\u001B[39m\u001B[39m.\u001B[39mPT)\n\u001B[0;32m 1257\u001B[0m ) \u001B[39m/\u001B[39m (\u001B[39mfloat\u001B[39m(nfi) \u001B[39m*\u001B[39m omegaf \u001B[39m*\u001B[39m si)\n", - "File \u001B[1;32mc:\\Users\\cwill\\GitHub\\virtualEnvs\\autoraEnv\\lib\\site-packages\\autora\\theorist\\bms\\mcmc.py:886\u001B[0m, in \u001B[0;36mTree.dE_et\u001B[1;34m(self, target, new, verbose)\u001B[0m\n\u001B[0;32m 884\u001B[0m old \u001B[39m=\u001B[39m [target\u001B[39m.\u001B[39mvalue, [o\u001B[39m.\u001B[39mvalue \u001B[39mfor\u001B[39;00m o \u001B[39min\u001B[39;00m target\u001B[39m.\u001B[39moffspring]]\n\u001B[0;32m 885\u001B[0m \u001B[39m# replace\u001B[39;00m\n\u001B[1;32m--> 886\u001B[0m added \u001B[39m=\u001B[39m \u001B[39mself\u001B[39;49m\u001B[39m.\u001B[39;49met_replace(target, new, update_gof\u001B[39m=\u001B[39;49m\u001B[39mTrue\u001B[39;49;00m, verbose\u001B[39m=\u001B[39;49mverbose)\n\u001B[0;32m 887\u001B[0m bicNew \u001B[39m=\u001B[39m \u001B[39mself\u001B[39m\u001B[39m.\u001B[39mbic\n\u001B[0;32m 888\u001B[0m par_valuesNew \u001B[39m=\u001B[39m deepcopy(\u001B[39mself\u001B[39m\u001B[39m.\u001B[39mpar_values)\n", - "File \u001B[1;32mc:\\Users\\cwill\\GitHub\\virtualEnvs\\autoraEnv\\lib\\site-packages\\autora\\theorist\\bms\\mcmc.py:596\u001B[0m, in \u001B[0;36mTree.et_replace\u001B[1;34m(self, target, new, update_gof, verbose)\u001B[0m\n\u001B[0;32m 594\u001B[0m \u001B[39mif\u001B[39;00m update_gof:\n\u001B[0;32m 595\u001B[0m \u001B[39mself\u001B[39m\u001B[39m.\u001B[39msse \u001B[39m=\u001B[39m \u001B[39mself\u001B[39m\u001B[39m.\u001B[39mget_sse(verbose\u001B[39m=\u001B[39mverbose)\n\u001B[1;32m--> 596\u001B[0m \u001B[39mself\u001B[39m\u001B[39m.\u001B[39mbic \u001B[39m=\u001B[39m \u001B[39mself\u001B[39;49m\u001B[39m.\u001B[39;49mget_bic(verbose\u001B[39m=\u001B[39;49mverbose)\n\u001B[0;32m 597\u001B[0m \u001B[39m# Done\u001B[39;00m\n\u001B[0;32m 598\u001B[0m \u001B[39mreturn\u001B[39;00m added\n", - "File \u001B[1;32mc:\\Users\\cwill\\GitHub\\virtualEnvs\\autoraEnv\\lib\\site-packages\\autora\\theorist\\bms\\mcmc.py:722\u001B[0m, in \u001B[0;36mTree.get_bic\u001B[1;34m(self, reset, fit, verbose)\u001B[0m\n\u001B[0;32m 720\u001B[0m \u001B[39mreturn\u001B[39;00m \u001B[39m0\u001B[39m\n\u001B[0;32m 721\u001B[0m \u001B[39m# Get the sum of squared errors (fitting, if required)\u001B[39;00m\n\u001B[1;32m--> 722\u001B[0m sse \u001B[39m=\u001B[39m \u001B[39mself\u001B[39;49m\u001B[39m.\u001B[39;49mget_sse(fit\u001B[39m=\u001B[39;49mfit, verbose\u001B[39m=\u001B[39;49mverbose)\n\u001B[0;32m 723\u001B[0m \u001B[39m# Calculate the BIC\u001B[39;00m\n\u001B[0;32m 724\u001B[0m parameters \u001B[39m=\u001B[39m \u001B[39mset\u001B[39m([p\u001B[39m.\u001B[39mvalue \u001B[39mfor\u001B[39;00m p \u001B[39min\u001B[39;00m \u001B[39mself\u001B[39m\u001B[39m.\u001B[39mets[\u001B[39m0\u001B[39m] \u001B[39mif\u001B[39;00m p\u001B[39m.\u001B[39mvalue \u001B[39min\u001B[39;00m \u001B[39mself\u001B[39m\u001B[39m.\u001B[39mparameters])\n", - "File \u001B[1;32mc:\\Users\\cwill\\GitHub\\virtualEnvs\\autoraEnv\\lib\\site-packages\\autora\\theorist\\bms\\mcmc.py:628\u001B[0m, in \u001B[0;36mTree.get_sse\u001B[1;34m(self, fit, verbose)\u001B[0m\n\u001B[0;32m 619\u001B[0m dic: \u001B[39mdict\u001B[39m \u001B[39m=\u001B[39m \u001B[39mdict\u001B[39m(\n\u001B[0;32m 620\u001B[0m {\n\u001B[0;32m 621\u001B[0m \u001B[39m\"\u001B[39m\u001B[39mfac\u001B[39m\u001B[39m\"\u001B[39m: scipy\u001B[39m.\u001B[39mspecial\u001B[39m.\u001B[39mfactorial,\n\u001B[1;32m (...)\u001B[0m\n\u001B[0;32m 625\u001B[0m \u001B[39m*\u001B[39m\u001B[39m*\u001B[39m\u001B[39mself\u001B[39m\u001B[39m.\u001B[39mcustom_ops\n\u001B[0;32m 626\u001B[0m )\n\u001B[0;32m 627\u001B[0m \u001B[39mtry\u001B[39;00m:\n\u001B[1;32m--> 628\u001B[0m flam \u001B[39m=\u001B[39m lambdify(\n\u001B[0;32m 629\u001B[0m variables \u001B[39m+\u001B[39;49m parameters,\n\u001B[0;32m 630\u001B[0m ex,\n\u001B[0;32m 631\u001B[0m [\n\u001B[0;32m 632\u001B[0m \u001B[39m\"\u001B[39;49m\u001B[39mnumpy\u001B[39;49m\u001B[39m\"\u001B[39;49m,\n\u001B[0;32m 633\u001B[0m dic,\n\u001B[0;32m 634\u001B[0m ],\n\u001B[0;32m 635\u001B[0m )\n\u001B[0;32m 636\u001B[0m \u001B[39mexcept\u001B[39;00m (\u001B[39mSyntaxError\u001B[39;00m, \u001B[39mKeyError\u001B[39;00m):\n\u001B[0;32m 637\u001B[0m \u001B[39mself\u001B[39m\u001B[39m.\u001B[39msse \u001B[39m=\u001B[39m \u001B[39mdict\u001B[39m([(ds, np\u001B[39m.\u001B[39minf) \u001B[39mfor\u001B[39;00m ds \u001B[39min\u001B[39;00m \u001B[39mself\u001B[39m\u001B[39m.\u001B[39mx])\n", - "File \u001B[1;32mc:\\Users\\cwill\\GitHub\\virtualEnvs\\autoraEnv\\lib\\site-packages\\sympy\\utilities\\lambdify.py:830\u001B[0m, in \u001B[0;36mlambdify\u001B[1;34m(args, expr, modules, printer, use_imps, dummify, cse, docstring_limit)\u001B[0m\n\u001B[0;32m 828\u001B[0m \u001B[39mfor\u001B[39;00m k \u001B[39min\u001B[39;00m m:\n\u001B[0;32m 829\u001B[0m user_functions[k] \u001B[39m=\u001B[39m k\n\u001B[1;32m--> 830\u001B[0m printer \u001B[39m=\u001B[39m Printer({\u001B[39m'\u001B[39;49m\u001B[39mfully_qualified_modules\u001B[39;49m\u001B[39m'\u001B[39;49m: \u001B[39mFalse\u001B[39;49;00m, \u001B[39m'\u001B[39;49m\u001B[39minline\u001B[39;49m\u001B[39m'\u001B[39;49m: \u001B[39mTrue\u001B[39;49;00m,\n\u001B[0;32m 831\u001B[0m \u001B[39m'\u001B[39;49m\u001B[39mallow_unknown_functions\u001B[39;49m\u001B[39m'\u001B[39;49m: \u001B[39mTrue\u001B[39;49;00m,\n\u001B[0;32m 832\u001B[0m \u001B[39m'\u001B[39;49m\u001B[39muser_functions\u001B[39;49m\u001B[39m'\u001B[39;49m: user_functions})\n\u001B[0;32m 834\u001B[0m \u001B[39mif\u001B[39;00m \u001B[39misinstance\u001B[39m(args, \u001B[39mset\u001B[39m):\n\u001B[0;32m 835\u001B[0m sympy_deprecation_warning(\n\u001B[0;32m 836\u001B[0m \u001B[39m \u001B[39m\u001B[39m\"\"\"\u001B[39;00m\n\u001B[0;32m 837\u001B[0m \u001B[39mPassing the function arguments to lambdify() as a set is deprecated. This\u001B[39;00m\n\u001B[1;32m (...)\u001B[0m\n\u001B[0;32m 842\u001B[0m active_deprecations_target\u001B[39m=\u001B[39m\u001B[39m\"\u001B[39m\u001B[39mdeprecated-lambdify-arguments-set\u001B[39m\u001B[39m\"\u001B[39m,\n\u001B[0;32m 843\u001B[0m )\n", - "File \u001B[1;32mc:\\Users\\cwill\\GitHub\\virtualEnvs\\autoraEnv\\lib\\site-packages\\sympy\\printing\\numpy.py:56\u001B[0m, in \u001B[0;36mNumPyPrinter.__init__\u001B[1;34m(self, settings)\u001B[0m\n\u001B[0;32m 52\u001B[0m \u001B[39mself\u001B[39m\u001B[39m.\u001B[39mprintmethod \u001B[39m=\u001B[39m \u001B[39m\"\u001B[39m\u001B[39m_\u001B[39m\u001B[39m{}\u001B[39;00m\u001B[39mcode\u001B[39m\u001B[39m\"\u001B[39m\u001B[39m.\u001B[39mformat(\u001B[39mself\u001B[39m\u001B[39m.\u001B[39m_module)\n\u001B[0;32m 54\u001B[0m \u001B[39mself\u001B[39m\u001B[39m.\u001B[39m_kf \u001B[39m=\u001B[39m {\u001B[39m*\u001B[39m\u001B[39m*\u001B[39mPythonCodePrinter\u001B[39m.\u001B[39m_kf, \u001B[39m*\u001B[39m\u001B[39m*\u001B[39m\u001B[39mself\u001B[39m\u001B[39m.\u001B[39m_kf}\n\u001B[1;32m---> 56\u001B[0m \u001B[39msuper\u001B[39;49m()\u001B[39m.\u001B[39;49m\u001B[39m__init__\u001B[39;49m(settings\u001B[39m=\u001B[39;49msettings)\n", - "File \u001B[1;32mc:\\Users\\cwill\\GitHub\\virtualEnvs\\autoraEnv\\lib\\site-packages\\sympy\\printing\\pycode.py:99\u001B[0m, in \u001B[0;36mAbstractPythonCodePrinter.__init__\u001B[1;34m(self, settings)\u001B[0m\n\u001B[0;32m 88\u001B[0m _operators \u001B[39m=\u001B[39m {\u001B[39m'\u001B[39m\u001B[39mand\u001B[39m\u001B[39m'\u001B[39m: \u001B[39m'\u001B[39m\u001B[39mand\u001B[39m\u001B[39m'\u001B[39m, \u001B[39m'\u001B[39m\u001B[39mor\u001B[39m\u001B[39m'\u001B[39m: \u001B[39m'\u001B[39m\u001B[39mor\u001B[39m\u001B[39m'\u001B[39m, \u001B[39m'\u001B[39m\u001B[39mnot\u001B[39m\u001B[39m'\u001B[39m: \u001B[39m'\u001B[39m\u001B[39mnot\u001B[39m\u001B[39m'\u001B[39m}\n\u001B[0;32m 89\u001B[0m _default_settings \u001B[39m=\u001B[39m \u001B[39mdict\u001B[39m(\n\u001B[0;32m 90\u001B[0m CodePrinter\u001B[39m.\u001B[39m_default_settings,\n\u001B[0;32m 91\u001B[0m user_functions\u001B[39m=\u001B[39m{},\n\u001B[1;32m (...)\u001B[0m\n\u001B[0;32m 96\u001B[0m standard\u001B[39m=\u001B[39m\u001B[39m'\u001B[39m\u001B[39mpython3\u001B[39m\u001B[39m'\u001B[39m,\n\u001B[0;32m 97\u001B[0m )\n\u001B[1;32m---> 99\u001B[0m \u001B[39mdef\u001B[39;00m \u001B[39m__init__\u001B[39m(\u001B[39mself\u001B[39m, settings\u001B[39m=\u001B[39m\u001B[39mNone\u001B[39;00m):\n\u001B[0;32m 100\u001B[0m \u001B[39msuper\u001B[39m()\u001B[39m.\u001B[39m\u001B[39m__init__\u001B[39m(settings)\n\u001B[0;32m 102\u001B[0m \u001B[39m# Python standard handler\u001B[39;00m\n", - "\u001B[1;31mKeyboardInterrupt\u001B[0m: " + "INFO:autora.theorist.bms.regressor:BMS fitting started\n", + "INFO:autora.theorist.bms.regressor:BMS fitting finished\n", + "INFO:autora.theorist.darts.regressor:Starting fit initialization\n", + "INFO:autora.theorist.darts.regressor:Starting fit.\n" ] } ], @@ -172,12 +153,12 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 26, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -207,12 +188,12 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 27, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -249,7 +230,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 29, "metadata": {}, "outputs": [ { @@ -257,11 +238,11 @@ "output_type": "stream", "text": [ "New datapoints:\n", - "[[-3.]\n", - " [ 4.]\n", - " [ 5.]\n", - " [ 6.]\n", - " [ 1.]]\n" + "[[6.]\n", + " [5.]\n", + " [4.]\n", + " [3.]\n", + " [2.]]\n" ] } ], @@ -283,12 +264,33 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['Proposed Datapoints', [None, None, None, None]]" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "labels = ['Proposed Datapoints',[None]*(len(sampler_proposal)-1)]\n", + "labels" + ] + }, + { + "cell_type": "code", + "execution_count": 31, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -298,8 +300,13 @@ } ], "source": [ + "#Set proposal labels\n", + "labels = [None]*len(sampler_proposal)\n", + "labels[0] = 'Proposed Datapoints'\n", + "\n", + "#Plot data and proposals\n", "plt.plot(X, ground_truth(X), 'o', alpha = .5, label = 'Original Datapoints')\n", - "plt.plot(sampler_proposal, ground_truth(sampler_proposal), 'o', alpha = .5, label = 'Proposed Datapoints')\n", + "[plt.axvline(condition, color = '#ff7f0e', linestyle = '--', alpha = .5, label = labels[index]) for index,condition in enumerate(sampler_proposal)]\n", "plt.legend()\n", "plt.show()" ] diff --git a/src/autora/experimentalist/sampler/model_disagreement/__init__.py b/src/autora/experimentalist/sampler/model_disagreement/__init__.py index 51c1f5d..0934b65 100644 --- a/src/autora/experimentalist/sampler/model_disagreement/__init__.py +++ b/src/autora/experimentalist/sampler/model_disagreement/__init__.py @@ -4,7 +4,7 @@ from autora.utils.deprecation import deprecated_alias -def model_disagreement_sample(X: np.array, models: List, num_samples: int = 1): +def model_disagreement_sample(condition_pool: np.array, models: List, num_samples: int = 1): """ A sampler that returns selected samples for independent variables for which the models disagree the most in terms of their predictions. @@ -17,10 +17,10 @@ def model_disagreement_sample(X: np.array, models: List, num_samples: int = 1): Returns: Sampled pool """ - if isinstance(X, Iterable): - X = np.array(list(X)) + if isinstance(condition_pool, Iterable): + condition_pool = np.array(list(condition_pool)) - X_predict = np.array(X) + X_predict = np.array(condition_pool) if len(X_predict.shape) == 1: X_predict = X_predict.reshape(-1, 1)