From 4a34559c19524479137a943705f0e6a7a681fc44 Mon Sep 17 00:00:00 2001 From: Rob Zinkov Date: Sat, 4 Jan 2025 23:07:58 +0100 Subject: [PATCH] Updated marginalizing-models explain to use the model transformations --- examples/howto/marginalizing-models.ipynb | 540 ++++++++++++-------- examples/howto/marginalizing-models.myst.md | 23 +- 2 files changed, 341 insertions(+), 222 deletions(-) diff --git a/examples/howto/marginalizing-models.ipynb b/examples/howto/marginalizing-models.ipynb index a553fb80..21e077f9 100644 --- a/examples/howto/marginalizing-models.ipynb +++ b/examples/howto/marginalizing-models.ipynb @@ -112,7 +112,7 @@ "source": [ "mu = pt.as_tensor([-2.0, 2.0])\n", "\n", - "with pmx.MarginalModel() as explicit_mixture:\n", + "with pm.Model() as explicit_mixture:\n", " idx = pm.Bernoulli(\"idx\", 0.7)\n", " y = pm.Normal(\"y\", mu=mu[idx], sigma=1.0)" ] @@ -125,7 +125,7 @@ "outputs": [ { "data": { - "image/png": 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" ] @@ -170,7 +170,7 @@ "outputs": [ { "data": { - "image/png": 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+Zxx++OGNjjvooIPixz/+cdxyyy1RUVHRrD323HPPuP/+++Of/umfYvDgwY32cfTRR8cvf/nLuPDCC5u1PgAAAAAAhWnT25J0pJUrV8bixYvj3XffjR07dsSAAQNi2LBhMXz48KKsn81mY9GiRfH666/Hu+++G7vttlsMGDAgDjvssBgwYEBR9ohwWxLojJyXUJqcm1B6nJfQOm5LAl2H90xSkdRtSTrSkCFDYsiQIW22fiaTidGjR8fo0aPbbA8AAAAAABrmV6YAAAAAACRHuA0AAAAAQHKE2wAAAAAAJEe4DQAAAABAcoTbAAAAAAAkR7gNAAAAAEByhNsAAAAAACRHuA0AAAAAQHKE2wAAAAAAJEe4DQAAAABAcoTbAAAAAAAkR7gNAAAAAEByhNsAAAAAACRHuA0AAAAAQHKE2wAAAAAAJEe4DQAAAABAcoTbAAAAAAAkR7gNAAAAAEByhNsAAAAAACRHuA0AAAAAQHKE2wAAAAAAJEe4DQAAAABAcoTbAAAAAAAkR7gNAAAAAEByhNsAAAAAACRHuA0AAAAAQHKE2wAAAAAAJEe4DQAAAABAcoTbAAAAAAAkR7gNAAAAAEByhNsAAAAAACRHuA0AAAAAQHKE2wAAAAAAJEe4DQAAAABAcoTbAAAAAAAkR7gNAAAAAEByhNsAAAAAACRHuA0AAAAAQHKE2wAAAAAAJEe4DQAAAABAcoTbAAAAAAAkp7yjGwAAAAC6pvHH1XZ0C3lmz3INIEBKvGoDAAAAAJAc4TYAAAAAAMkRbgMAAAAAkBzhNgAAAAAAyRFuAwAAAACQHOE2AAAAAADJEW4DAAAAAJAc4TYAAAAAAMkRbgMAAAAAkBzhNgAAAAAAyRFuAwAAAACQHOE2AAAAAADJEW4DAAAAAJAc4TYAAAAAAMkRbgMAAAAAkBzhNgAAAAAAyRFuAwAAAACQHOE2AAAAAADJEW4DAAAAAJAc4TYAAAAAAMkRbgMAAAAAkBzhNgAAAAAAyRFuAwAAAACQHOE2AAAAAADJEW4DAAAAAJAc4TYAAAAAAMkRbgMAAAAAkBzhNgAAAAAAySnv6AYAAAAgNeOPq+3oFuqZPcv1awB0Ld75AAAAAABIjnAbAAAAAIDkCLcBAAAAAEhOu91ze+PGjbFkyZJYuHBhLFy4MBYtWhSrVq3KPb7ffvvFU0891aw1jz/++Lw1WuqGG26IL3zhCw0+9tZbb8XEiRNbtO6AAQPi2WefbU1rAAAAAAA0oM3D7XvvvTcefvjheOWVV6K2tvQ+cCMiolevXh3dAgAAAAAAzdDm4fa8efNi+fLlbbJ2t27dolu3bs2ak81m80L2Xr16xWc+85mC55eVlUUmkylobHl5u10YDwAAAADQpXRI+tqrV68YOXJkLF68ODZt2tTidWbOnNnsOffdd1/ccMMNufqkk06K3XffveD5//qv/9roLUwAAAAAAGgfbR5uV1RUxOjRo2PUqFExatSoOPTQQ+PAAw+MsrKyOP7441sVbrfEI488kldPmjSpXfcHAAAAAKD12jzcvuWWW9p6i4ItXbo0Xn755Vy93377xac+9akO7AgAAAAAgJYo6+gG2lPdq7bPOOOMgu+fDQAAAABA6egy4fb27dvj0UcfzdWZTMYtSQAAAAAAEtVlwu1nnnkm3n///Vw9bty4GDx4cAd2BAAAAABAS3WZcHvatGl5tau2AQAAAADS1eYfKFkK1q1bF08//XSu7tmzZ5x88sktWuv3v/99PPbYY/Hqq6/GunXroqKiIiorK2PYsGFxxBFHxCmnnBJ77713sVoHAAAAAKABXSLcnjFjRtTU1OTqk046KXr37t2itWbNmpVXb968Oaqrq+ONN96ImTNnxk9+8pP44he/GN/+9rdj9913b03bERGt/sDLnef78EwoDc5LKE3OTSg9zktonhTOk1LvsdT7g8Z4z6Sr6hLh9iOPPJJXt+UtSbZt2xYPPPBA/PGPf4yf//znMWTIkFatV1lZWZzGIqJv375FWwsoDucllCbnJpQe5yWl5/1dD2ln9X9+1GNzFfNncOgo3jPpSjp9uL1ixYp46aWXcvV+++0XRx11VLPXGT58eJxwwgkxbty4+MQnPhGVlZWRzWbjvffeixdffDGmTZsWzz77bG78a6+9Fl/72tfiwQcfjH79+hXluQAAAAAA8FedPtyue9X26aef3qw/z6isrIxf/epXMWbMmAYfHzRoUAwaNChOPfXUeOaZZ+If//EfY/369RERsXLlyrj++uvj5ptvbnH/1dXVLZ4b8dc/RfnoN3br16+PbDbbqvWA1nNeQmlybkLpcV5C87T258f2UOo9lnp/0BjvmaSi2H8h06nD7R07dsT06dNzdSaTafYtSXr37t1osF3XhAkT4s4774zzzz8/tm/fHhF/vd/3P/zDP8RBBx3UrH0/UswXo2w268UNSozzEkqTcxNKj/MSdi2Fc6TUeyz1/qAQ3jPpSso6uoG2NHv27FizZk2uHjduXOy///5tuucnP/nJOPPMM3N1NpuN3/3ud226JwAAAABAV9Opw+1p06bl1W35QZI7++IXv5hXz5kzp132BQAAAADoKjptuL1hw4Z48sknc3XPnj3j5JNPbpe9Dz300OjevXuufvvtt9tlXwAAAACArqLThtszZsyIrVu35uoTTzwxevfu3S57l5WV5d0cfd26de2yLwAAAABAV9Fpw+26tyT5whe+0K77b9myJfd1RUVFu+4NAAAAANDZdcpw+/XXX48FCxbk6n333TeOOuqodtt/3bp1sWHDhlzdv3//dtsbAAAAAKAr6JThdt2rtk8//fTIZDLttv+zzz6bVx988MHttjcAAAAAQFfQ6cLt2tra+M1vfpN3rD1vSVJTUxO/+MUv8o6NHz++3fYHAAAAAOgKOl24/fzzz8c777yTq8eNGxf7779/i9aqqqqK6urqgsfX1tbGD3/4w1ixYkXu2F577RWnnnpqi/YHAAAAAKBhnS7cfvjhh/PqSZMmtXitRYsWxfHHHx8/+tGPYsmSJU2OXbp0aUyePLne/ldddVX06tWrxT0AAAAAAFBfeVtvsGrVqjjxxBMbfGzHjh1540aMGNHguPvuuy+OPPLIXe714YcfxsyZM3N1z54945RTTmlmx/k2btwY99xzT9xzzz2x1157xYgRI2Lw4MGxxx57RDabjffffz9efPHFWL58eb25F154YbveEgUAAAAAoKto83A7m83mhdhNaWxcNpstaP7vf//72Lx5c64+8cQTo3fv3gXNLcSaNWvimWee2eW43XbbLa655po455xzirY3AAAAAAD/q83D7fY0bdq0vLq1V00PHz48vvzlL8fcuXPjtddei9ra2ibH77XXXjFp0qT4yle+EgMHDmzV3gAAAAAANK7Nw+1BgwbFsmXL2nqbiIiYOnVqUdcbPHhwXHvttRERsWnTpnjllVfirbfeivfeey82bdoUmUwm9thjj9hzzz1j5MiRMXjw4KLuDwAAAABAwzrVldttqVevXjF69OgYPXp0R7cCAAAAANDllXV0AwAAAAAA0FzCbQAAAAAAkiPcBgAAAAAgOcJtAAAAAACSI9wGAAAAACA5wm0AAAAAAJIj3AYAAAAAIDnCbQAAAAAAkiPcBgAAAAAgOcJtAAAAAACSI9wGAAAAACA5wm0AAAAAAJIj3AYAAAAAIDnCbQAAAAAAkiPcBgAAAAAgOcJtAAAAAACSI9wGAAAAACA5wm0AAAAAAJIj3AYAAAAAIDnCbQAAAAAAkiPcBgAAAAAgOcJtAAAAAACSI9wGAAAAACA5wm0AAAAAAJIj3AYAAAAAIDnCbQAAAAAAkiPcBgAAAAAgOcJtAAAAAACSI9wGAAAAACA5wm0AAAAAAJIj3AYAAAAAIDnCbQAAAAAAkiPcBgAAAAAgOcJtAAAAAACSI9wGAAAAACA5wm0AAAAAAJIj3AYAAAAAIDnCbQAAAAAAkiPcBgAAAAAgOcJtAAAAAACSI9wGAAAAACA5wm0AAAAAAJIj3AYAAAAAIDnCbQAAAAAAklPe0Q0AAAAAlKLxx9V2dAv1zJ7lOkWAj3hFBAAAAAAgOcJtAAAAAACSI9wGAAAAACA5wm0AAAAAAJIj3AYAAAAAIDnCbQAAAAAAkiPcBgAAAAAgOcJtAAAAAACSI9wGAAAAACA5wm0AAAAAAJIj3AYAAAAAIDnCbQAAAAAAkiPcBgAAAAAgOcJtAAAAAACSI9wGAAAAACA5wm0AAAAAAJIj3AYAAAAAIDnCbQAAAAAAkiPcBgAAAAAgOcJtAAAAAACSI9wGAAAAACA5wm0AAAAAAJIj3AYAAAAAIDnCbQAAAAAAkiPcBgAAAAAgOeUd3UCqFi5cGG+88UZUVVVFz549Y8CAATF69OgYMGBAR7cGAAAAANDptVu4vXHjxliyZEksXLgwFi5cGIsWLYpVq1blHt9vv/3iqaeeava6w4cPb3FPixcvjvLywr8F2Ww2pk6dGlOnTo0333yz3uNlZWVx9NFHxxVXXBGjRo1qcV8AAAAAADStzcPte++9Nx5++OF45ZVXora2tq23azPV1dVxxRVXxJw5cxodU1tbG7Nnz47nn38+vv3tb8fkyZPbr0EAAAAAgC6kzcPtefPmxfLly9t6m4iIyGQyUVZW+G3EM5lMQeNqamrim9/8ZsydOzd3rHv37nHsscfGgQceGBs3bowXXnghli1blht/ww03xB577BFnnnlm854EAAAAAAC71CH33O7Vq1eMHDkyFi9eHJs2bSraupdcckl885vfLNp6H7n11lvzgu2DDjoofvazn8WgQYPyxk2fPj2++93vRk1NTUREXHvttTF69OgYNmxY0XsCAAAAAOjK2jzcrqioiNGjR8eoUaNi1KhRceihh8aBBx4YZWVlcfzxxxc13G4LVVVVMXXq1Fzdv3//+K//+q/o169fvbGf//zno7a2Nr7zne9ExF+v4L7tttviP/7jP9qtXwAAAACArqDNw+1bbrmlrbdoU3fffXds3bo1V3/rW99qMNj+yBlnnBH//d//HfPmzYuIiJkzZ8by5cvjoIMOavNeAQAAAAC6isJvUN1FPf7447mv+/btG6eddtou55xzzjmNrgEAAAAAQOsJt5vw0ksvRVVVVa4+7rjjoqKiYpfzJk6cGN27d8/VTz75ZJv0BwAAAADQVQm3m/DCCy/k1WPGjClo3m677RYHH3xwrn755Zdjw4YNRe0NAAAAAKArE2434bXXXsurR4wYUfDcumPrrgUAAAAAQMu1+QdKtqfnn38+li5dGsuWLYu1a9dGeXl59OvXL4YMGRJHHHFEnHzyybH//vsXvF7dQHqfffYpeO6+++5bb63DDjus4PkAAAAAADSuU4Xb8+bNq3fsgw8+iJUrV8azzz4bt956a5xyyinx3e9+N/r377/L9Xa+33Z5eXl87GMfK7iXgQMH5tWrV68ueC4AAAAAAE3rVOH2ruzYsSMeffTRmDt3btxxxx0xevToJsdv3Lgx93XPnj2jrKzwu7jsvvvuefWmTZua1+z/k8lkWjSvofmtXQsoDucllCbnJpQe5yU0TwrnSan3WOr9RaTRI+3PeyZdVacIt4cMGRITJ06Mo446Kj7xiU/EnnvuGd26dYu1a9fGSy+9FI899lg8/vjjsWPHjoiIePfdd+Piiy+Ohx56qMnblGzevDn3dUVFRbN66tGjR17d0nC7srKyRfMa0rdv36KtBRSH8xJKk3MTSo/zktLzfkc3UE/9nx/12Fyl3l9EcXMCOifvmXQlyYfbd999dxxzzDEN/lZq4MCBMXDgwDjhhBNi8uTJcdlll8U777wTERHr1q2Lq6++On71q181uvaWLVtyX9cNq3el7vid1wIAAAAAoHWSD7fHjx9f0LjRo0fHPffcE2effXZs2LAhIiIWLFgQzzzzTEyYMKHBORUVFbmrt2tqaprV17Zt2+qt1RLV1dUtmveRTCaT+43d+vXrI5vNtmo9oPWcl1CanJtQepyX0Dyt/fmxPZR6j6XeX0QaPdL+vGeSimL/9Uny4XZzDB06NC6++OK4+eabc8dmzJjRaLjdq1evXLjd3Cuv64bbvXr1ama3f1XMF6NsNuvFDUqM8xJKk3MTSo/zEnYthXOk1Hss9f4i0uiRjuU9k66k8E9I7CTOPPPMvFuYzJkzp9GxOwfSmzdvbtYLw84fRll3LQAAAAAAWqfLhdv9+/ePwYMH5+p333230VuODBgwIPf19u3bY82aNQXvs3r16rx64MCBzewUAAAAAIDGdLlwO+KvAffOGrtf1dChQ/Pqjz6MshBvv/12k2sBAAAAANByXTLc/ug+2h9p7MMeDzzwwLx6yZIlBe9Rd6xwGwAAAACgeLpcuF1bW5t3VXX37t2jT58+DY4dN25cXr1gwYKC9tiyZUu8/PLLuXr48OGN7gEAAAAAQPN1uXB7/vz58cEHH+Tqgw8+uNGxhx56aN59t59++unYunXrLvd44okn8u7jPXHixBZ2CwAAAABAQ7pcuP2zn/0srx4/fnyjYzOZTJx00km5+oMPPohHH310l3v86le/yqs/97nPNbNLAAAAAACakmy4XV1dHVVVVc2a8+///u8xe/bsXL3bbrvFOeec0+Sciy66KHr06JGrb7755li3bl2j46dNmxbz5s3L1RMnTmzy6nAAAAAAAJov2XD7nXfeiRNOOCF++MMfxp/+9KfIZrONjn3zzTfj8ssvjzvuuCPv+EUXXZR325GGDBw4MM4999xc/f7778d5550Xb731Vr2x06dPj+9///u5unv37nH55ZcX+pQAAAAAAChQeVtvsGrVqjjxxBMbfGzHjh1540aMGNHguPvuuy+OPPLIese3bdsWDz74YDz44INRWVkZI0aMiI9//OPRp0+fKCsri3Xr1sVLL70Uixcvjtra2ry5p5xySlx66aUFPYcrr7wyFi5cGC+88EJERCxfvjxOPvnkmDBhQgwdOjQ2bdoU8+bNi2XLluXNu/baa2P48OEF7QEAAAAAQOHaPNzOZrN5IXZTGhvX1FXZH6muro7nnnsunnvuuSbHdevWLaZMmRLf+MY3IpPJFNRXjx494vbbb4/LL7885s6dGxERNTU18cQTTzQ4vry8PK666qo466yzClofAAAAAIDmSfa2JAMHDowLLrggRo4cGeXlu87o+/btG1/+8pfj0UcfjUsvvTS6devWrP323HPPuP/+++Of/umfYvDgwQ2OKSsri6OPPjp++ctfxoUXXtis9QEAAAAAKFybX7k9aNCgerfrKIZ+/frFNddcExF/vT3JK6+8Em+99Va8++67sXHjxqitrY0+ffpEZWVlDB8+PA488MCCr9RuTFlZWUyePDnOP//8WLRoUbz++uvx7rvvxm677RYDBgyIww47bJf38AYAAAAAoPXaPNxuDz169IgRI0Y0es/uYstkMjF69OgYPXp0u+wHAAAAAEC+ZG9LAgAAAABA1yXcBgAAAAAgOcJtAAAAAACSI9wGAAAAACA5wm0AAAAAAJIj3AYAAAAAIDnCbQAAAAAAkiPcBgAAAAAgOeUd3QAAAADUNf642o5uIc/sWa4NA4BS490ZAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOSUd3QDxbRmzZpYsWJFvPnmm/HBBx9EJpOJysrKGDx4cIwePTp69erV0S0CAAAAAFAE7RZub9y4MZYsWRILFy6MhQsXxqJFi2LVqlW5x/fbb7946qmnmrVmTU1NPPfcc/Hkk0/GH//4x1i5cmWjY8vLy+Ozn/1sfPWrX42xY8cWvMfzzz8f5513XrP6+sjYsWPjl7/8ZYvmAgAAAADQuDYPt++99954+OGH45VXXona2tqirbtx48b47Gc/G+vXry9o/Pbt22PmzJnxxBNPxLnnnhvf+c53onv37kXrBwAAAACA9tPm4fa8efNi+fLlRV93x44d9YLtTCYTw4YNi0MPPTT69+8f3bp1i7feeiv+8Ic/xLp16yIiIpvNxtSpU2Pt2rXxk5/8JMrKmnfb8bKysshkMgWNLS/vVHd9AQAAAAAoGR2Svvbq1StGjhwZixcvjk2bNrV6vYMOOijOOuusOO2002LPPfes9/jWrVvjF7/4Rdxxxx25q8dnzJgRY8eOjXPPPbdZe913333xqU99qtU9AwAAAADQcm0ebldUVMTo0aNj1KhRMWrUqDj00EPjwAMPjLKysjj++ONbFW4PGzYsrrjiijjhhBN22cOll14aH/vYx+Laa6/NHb/99tvj7LPPjh49erS4BwAAAAAA2l+bh9u33HJLm6zbu3fvmD59erNuK/J3f/d38Zvf/Cbmz58fERHV1dUxZ86cmDBhQpv0CAAAAABA22jeDadLSFlZWbPvlx0Rceqpp+bVixYtKlZLAAAAAAC0k2TD7Zbaf//98+r33nuvgzoBAAAAAKCluly4vXHjxry6vLxDPlMTAAAAAIBW6HLh9rJly/LqgQMHdlAnAAAAAAC0VJe6bDmbzcajjz6ad+yoo45q1hoPPvhg/Md//EesXLky1q9fH7169Yp+/frFIYccEkcccUT8zd/8TfTp06eYbQMAAAAAUEeXCrenTZsWf/nLX3L1/vvvHyNHjmzWGjNmzMirt2zZEmvXro1XX301Hn300bjpppvivPPOiylTpkT37t2L0jcAAAAAAPm6TLi9Zs2a+NGPfpR37JJLLolMJlPUfT788MO48847Y86cOXHnnXfGnnvu2ar1WtvfzvOL/VyBlnFeQmlybkLpcV5SSlL4f1CPrVfq/UWk0SPtz3smXVWXCLe3b98e3/rWt2LdunW5Y5/61Kfi9NNPL3iNMWPGxPHHHx+HH354DB06NPr06RM1NTWxZs2amD9/fvz617+O+fPn58YvWLAgpkyZEvfff39UVFS0uPfKysoWz62rb9++RVsLKA7nJZQm5yaUHudlV/R+RzeQp/7PZqXVX4Qei6HU+4sobk5A5+Q9k66kS4TbN954Yzz//PO5urKyMm688caCfpP18Y9/PB599NEYNmxYvcd69OgRu+++e3z84x+PL3zhC/HII4/EtddeG1u3bo2Ivwbcd955Z1x55ZXFezIAAAAAAHT+cPvuu++OqVOn5uru3bvHLbfcEvvuu29B8wcMGBADBgwoaOykSZOiR48ecdVVV+WO/dd//Vecf/75Lb49SXV1dYvmfSSTyeR+Y7d+/frIZrOtWg9oPecllCbnJpQe5yWlpLU/m7UHPbZeqfcXkUaPtD/vmaSi2H990qnD7UceeSRuuummXJ3JZOLGG2+Mo48+us32PPXUU+Phhx+O2bNnR0TEpk2b4qmnnoovfvGLLVqvmC9G2WzWixuUGOcllCbnJpQe5yUdLYX///TYeqXeX0QaPdKxvGfSlZR1dANt5Yknnojvfe97eSfzD37wgzjttNPafO+6QfacOXPafE8AAAAAgK6kU4bbc+bMiSuvvDJ27NiRO3b55ZfHV77ylXbZf8yYMXn122+/3S77AgAAAAB0FZ0u3F64cGFMmTIltm3bljv21a9+NaZMmdJuPdS9v/a6devabW8AAAAAgK6gU4Xby5Yti4suuig2bdqUO3b22WfHd77znXbtY8uWLXl1RUVFu+4PAAAAANDZdZpwe+XKlXHhhRfG+vXrc8dOO+20+Jd/+Zd27+Uvf/lLXt2/f/927wEAAAAAoDPrFOF2VVVVXHDBBbFmzZrcsYkTJ8aPfvSjKCtr/6f4zDPP5NUHH3xwu/cAAAAAANCZJR9ur1u3Li644IJYtWpV7tgxxxwTt956a5SXl7d7Pxs2bIipU6fmHfvMZz7T7n0AAAAAAHRmSYfbH374YVx00UXx6quv5o6NGzcu7rjjjujRo0er13/zzTdj8+bNBY/funVrXHHFFbF27drcsYMPPjiOOuqoVvcCAAAAAMD/Sjbc3rZtW0yZMiVeeuml3LFDDz00/vM//zN69uxZlD2eeuqpmDhxYvzHf/xHvP76602OnTdvXnzpS1+K2bNn546VlZXFNddcE5lMpij9AAAAAADwV21+345Vq1bFiSee2OBjO3bsyBs3YsSIBsfdd999ceSRR+Yd+/Of/xzPP/983rElS5bUG7crRxxxRNx///2NPv7+++/H7bffHrfffnvst99+ccghh8Q+++wTffr0ie3bt8eaNWti/vz58cYbb9Sb+/3vfz8+/elPN6sfAAAAAAB2rc3D7Ww2mxdiN6WxcdlstqBjtbW1zWuumXNWrVqVd2/vxlRWVsb111/faKgPAAAAAEDrtP8nLibkU5/6VJx55pkxb968ePPNN3c5ftCgQXH22WfH2WefHf369WuHDgEAAAAAuqY2D7cHDRoUy5YtK/q6n/rUp9pk3Z0dcsgh8W//9m8REbFhw4ZYsWJFvP322/Hee+/F5s2bo1u3btGnT5/42Mc+FqNGjYoBAwa0aT8AAAAAAPyVK7cLtMcee8TYsWNj7NixHd0KAAAAAECXV9bRDQAAAAAAQHMJtwEAAAAASI5wGwAAAACA5LjnNgAAAECixh9X29Et1DN7lmspgfbh1QYAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5JR3dAMAAAC0r/HH1XZ0C/XMnuXaKwCgefzrAQAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDklHd0A22hqqoqFi5cGFVVVbF58+YYMGBAHHDAATFq1Kii7bF8+fJYsWJFVFVVRVlZWQwcODBGjBgR+++/f9H2AAAAAACgYe0Wbm/cuDGWLFkSCxcujIULF8aiRYti1apVucf322+/eOqpp1q1x8KFC+O2226L5557Lmpra+s9PmTIkPj7v//7OPfccyOTybRoj+nTp8ddd90Vy5Yta/DxMWPGxCWXXBKf+cxnWrQ+AAAAAAC71ubh9r333hsPP/xwvPLKKw0GzsVy9913x09/+tPYvn17o2NWrlwZ119/fTz99NNxyy23RN++fQtef+vWrfFP//RPMWPGjCbHLViwIL72ta/FBRdcEFdffXWLQ3QAAAAAABrX5uH2vHnzYvny5W26x0MPPRQ//vGP844dcsghMW7cuOjZs2e8+uqr8eyzz+aC7z/84Q9x+eWXx1133RXl5YV9C773ve/lBduZTCaOOeaYGD58eNTU1MSiRYtiwYIFERGRzWbjnnvuiZ49e8Zll11WpGcJAAAAAMBHOuSe27169YqRI0fG4sWLY9OmTa1a6+WXX47rrrsuV/fo0SP+7d/+Lf72b/82b9xf/vKXmDJlSi5onzNnTtx+++1x5ZVX7nKPBx54IH7729/m6n322Sd+9rOfxSGHHJI37qPQfMOGDRERceedd8bYsWNj/PjxLX5+AAAAAADUV9bWG1RUVMTo0aPjK1/5Stx4443x6KOPxp/+9Kf4v//3/0a/fv1avf6tt94aNTU1ufr//J//Uy/YjogYPHhw3H///dG/f//csfvvvz/WrFnT5PqbN2+OO+64I+/53HvvvfWC7YiIY445Ju68887crUiy2Wz89Kc/bfZzAgAAAACgaW0ebt9yyy3x61//On74wx/GpEmTYtiwYVFWVpxtly5dGk8//XSuPuKII+KMM85odPyee+4ZV111Va7evHlz3HPPPU3u8dBDD8V7772Xqy+66KI44IADGh1/5JFHxuc///lcvXjx4rweAQAAAABovTYPt9vS448/nld/+ctf3uWcv/3bv40+ffrk6t///vdNjv/d736X+7pbt27xpS99aZd71O2jbp8AAAAAALRO0uH2U089lfu6e/fuMXHixF3OqaioiOOOOy5Xr1q1KpYuXdrg2LVr18aLL76Yq8eMGRMDBgzY5R6HH354DBw4MFfPmjUrduzYsct5AAAAAAAUJtlw+4MPPsh9OGRExIgRI6KioqKguYcffnhePW/evAbHzZ8/P2pra3P1mDFjCu5v5z2qq6tjxYoVBc8FAAAAAKBpyYbbr776al7d0Ac8NmbkyJFNrtXY8REjRrR4j9dee63guQAAAAAANC3ZcLtuWLzvvvsWPHefffZpcq3GjtedV4w9AAAAAABovmTD7aqqqry6kHthf2SvvfaKbt26NbpWY8d3vo/2rtQdu3r16oLnAgAAAADQtPKObqClNm7cmFf37t274LllZWXRs2fP+PDDDyMiYtOmTQXtsfvuuxe8R92xje2xK5lMpkXzGprf2rWA4nBeQmlybkLpcV52LaX+37jU+4vQYzGUen8ReqRh3jPpqpINtzdv3pxX9+jRo1nzKyoqcuF23RC7sT0K/cDKhsa2NNyurKxs0byG9O3bt2hrAcXhvITS5NyE0uO8LLb3O7qBeur/7FNaPZZ6fxF6LIZS7y8i1R5pT94z6UqSvS3Jli1b8urmhts7j9+6dWvR96g7tu5aAAAAAAC0XLJXbte9MrqmpqZZ87dt29boWk3tUWjAvfP6Te2xK9XV1S2a95FMJpP7jd369esjm822aj2g9ZyXUJqcm1B6nJddS2t/9mlrpd5fhB6LodT7i9AjDfOeSSqK/ZcdyYbbvXr1yqsbu/q6MTuPr7tWY8e3bNlScLhdt5/G9tiVYr4YZbNZL25QYpyXUJqcm1B6nJedX6n/9y31/iL0WAyl3l+EHtk175l0JcnelqRuWNzYfbMbUltbm3ebkELD7ebcN7tuPy0NtwEAAAAAqC/ZcHvAgAF59erVqwueu2bNmti+fXuuHjhwYEF7vPPOOwXvUbefxvYAAAAAAKD5kg23hw4dmle//fbbBc+tG1IfcMABBe3RnHC77ti6awEAAAAA0HLJhtsHHnhgXr106dKC5y5evLjJtRo7vmTJkqLvAQAAAABA8yUbbvft2zeGDRuWq5csWVLwh0ouWLAgrz7iiCMaHDd27NgoK/vfb1HdeU3585//nPu6srIyPvGJTxQ8FwAAAACApiUbbkdEHH/88bmva2pq4sknn9zlnK1bt8YzzzyTq/fdd98YMWJEg2P79+8fhx12WK5esGBBVFVV7XKPBQsW5N1ze8KECVFeXr7LeQAAAAAAFCbpcPvkk0/Oqx944IFdzvntb38bH3zwQa7+3Oc+V/AeO3bsiAcffHCXe/zyl79ssk8AAAAAAFon6XB7xIgRMWHChFw9b968mDZtWqPj165dGz/96U9z9W677RZf/epXm9zj7LPPjv79++fqu+66K15//fVGx8+dOzemT5+e1+NnP/vZJvcAAAAAAKB5kg63IyKuvPLKvFt+/OAHP4hHH3203ri//OUvcf7558f777+fO3beeefF3nvv3eT6vXr1iilTpuTqrVu3xgUXXNDgB1j+4Q9/iClTpkQ2m83rL5PJNOs5AQAAAADQtDa/EfSqVavixBNPbPCxHTt25I1r7N7X9913Xxx55JENPnbIIYfE97///fjnf/7niIjYtm1bfOtb34q77rorPvnJT8Zuu+0Wr776ajz77LOxffv23LwjjzwyLrvssoKew7nnnhvz58+PGTNmRETEO++8E5MmTYpjjjkmhg8fHtu3b4+FCxfW+8DJr3/963HssccWtAcAAAAAAIVr83A7m83mhdhNaWzczldCN+Scc86JDRs2xG233ZYLsJcuXdrg1dUREUcddVTcdttt0b1794L6ioi44YYbYseOHfH444/nepo9e3bMnj273thMJhPnnXdeXHHFFQWvDwAAAABA4ZK/LclHLr744njggQfi6KOPjrKyhp/W4MGD47vf/W7cd999UVlZ2az1Kyoq4rbbbosf/ehHcdBBBzU67vDDD4///M//jO9+97tuRwIAAAAA0Eba/MrtQYMGxbJly9p6m4iIOOyww+Lee++NqqqqePHFF6Oqqiq2bNkSe++9dxxwwAExevToVu9xxhlnxBlnnBHLli2LFStWRFVVVXTr1i323nvvGDlyZAwZMqQIzwQAAAAAgKa0ebjdEQYMGBAnnXRSm+4xfPjwGD58eJvuAQAAAABAwzrNbUkAAAAAAOg6hNsAAAAAACRHuA0AAAAAQHKE2wAAAAAAJEe4DQAAAABAcoTbAAAAAAAkR7gNAAAAAEByhNsAAAAAACRHuA0AAAAAQHKE2wAAAAAAJEe4DQAAAABAcoTbAAAAAAAkR7gNAAAAAEByhNsAAAAAACRHuA0AAAAAQHKE2wAAAAAAJEe4DQAAAABAcoTbAAAAAAAkR7gNAAAAAEByhNsAAAAAACRHuA0AAAAAQHKE2wAAAAAAJEe4DQAAAABAcoTbAAAAAAAkR7gNAAAAAEByhNsAAAAAACRHuA0AAAAAQHKE2wAAAAAAJEe4DQAAAABAcoTbAAAAAAAkR7gNAAAAAEByhNsAAAAAACRHuA0AAAAAQHKE2wAAAAAAJEe4DQAAAABAcoTbAAAAAAAkR7gNAAAAAEByhNsAAAAAACRHuA0AAAAAQHKE2wAAAAAAJEe4DQAAAABAcoTbAAAAAAAkR7gNAAAAAEByhNsAAAAAACRHuA0AAAAAQHLKO7oBAIC2Nv642gJHvt+mfexs9izXGAAAALSGn6oAAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOSUd3QDAAAAAHRe44+r7egW6pk9y/We0Bk4kwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASI5wGwAAAACA5Ai3AQAAAABIjnAbAAAAAIDkCLcBAAAAAEiOcBsAAAAAgOQItwEAAAAASE55RzfQWn//938fc+fObfU6l156aXzzm99s8LHhw4e3eN3FixdHeXny32YAaNT442o7uoV6Zs/y+3sAAIDOzk9+/0+vXr06ugUAAAAAAAqU/CXFZWVl0a1bt2bP27FjR+7rTCYTJ510UkHzMplMlJUV/juBTCbT7N4AAAAAAGha8uH2/fff3+w5M2fOjEsvvTRXf/KTn4zBgwcXNPeSSy5p9PYlAAAAAAC0j+TD7ZZ4+OGH8+pJkyZ1UCcAAH/l3uUAAADN0+V+Ylm7dm38z//8T67u1atXnHzyyR3YEQAAAAAAzdXlwu3f/va3UVNTk6tPOumk2H333TuwIwAAAAAAmqvLhduPPPJIXu2WJAAAAAAA6elS4fbLL78cS5cuzdX77bdffOpTn+rAjgAAAAAAaIkuFW5PmzYtrz799NMjk8l0TDMAAAAAALRYeUc30F62b98ev/3tb3N1JpNp0S1Jnn/++Vi6dGksW7Ys1q5dG+Xl5dGvX78YMmRIHHHEEXHyySfH/vvvX8zWAQAAAACoo8uE2//zP/8T7733Xq4eN25ci0LoefPm1Tv2wQcfxMqVK+PZZ5+NW2+9NU455ZT47ne/G/37929VzxHR6ivLd57vKnUoDc5LaHspnFt6hF3zntm1lPp/41LvL0KPxVDq/UXosVhS6LE5vGfSVXWZcLu9Pkhyx44d8eijj8bcuXPjjjvuiNGjR7dqvcrKyuI0FhF9+/Yt2lpAcTgv6Rze7+gG6qn//qnHlijmv0OgtbxnFlsKrzml1WOp9xehx2Io9f4i9FgsnfnfOd4z6Uq6RLhdXV0dTz/9dK7u2bNnnHzyyc1aY8iQITFx4sQ46qij4hOf+ETsueee0a1bt1i7dm289NJL8dhjj8Xjjz8eO3bsiIiId999Ny6++OJ46KGH3KYEAAAAAKDIukS4PWPGjNi2bVuuPumkk6J3794Fz7/77rvjmGOOafDPOgYOHBgDBw6ME044ISZPnhyXXXZZvPPOOxERsW7durj66qvjV7/6VYt7r66ubvHciL/+KcpHv7Fbv359ZLPZVq0HtJ7zEtpea98/24MeYde8Z3Ytpf6aU+r9ReixGEq9vwg9FksKPTaH90xSUey/mugS4fa0adPy6ubekmT8+PEFjRs9enTcc889cfbZZ8eGDRsiImLBggXxzDPPxIQJE5q150eK+WKUzWa9uEGJcV5C20jhvNIjNI/3zM6v1P/7lnp/EXoshlLvL0KPxZJCjy3lPZOupKyjG2hrr776aixcuDBX77fffnHUUUe12X5Dhw6Niy++OO/YjBkz2mw/AAAAAICuqNOH23U/SPL0009v80+NPfPMM/P2mDNnTpvuBwAAAADQ1XTqcLu2tjamT5+ed6y5tyRpif79+8fgwYNz9bvvvhs1NTVtvi8AAAAAQFfRqcPtP/zhD1FVVZWrx40bF/vvv3+77N2/f/+8urN9UAEAAAAAQEfq1OF2az9IsjU2b96cV1dUVLTb3gAAAAAAnV2nDbc//PDDeOKJJ3J1z54945RTTmmXvWtra+Ptt9/O1d27d48+ffq0y94AAAAAAF1Bpw23H3vssdiyZUuuPvHEE6N3797tsvf8+fPjgw8+yNUHH3xwu+wLAAAAANBVdNpw+5FHHsmrv/CFL7Tb3j/72c/y6vHjx7fb3gAAAAAAXUGnDLdXrlwZ8+fPz9X77rtvHHXUUc1ep7q6Ou8DKQvx7//+7zF79uxcvdtuu8U555zT7L0BAAAAAGhcpwy36161ffrpp0cmk2n2Ou+8806ccMIJ8cMf/jD+9Kc/RTabbXTsm2++GZdffnnccccdeccvuuiiGDBgQLP3BgAAAACgceUd3UCxZbPZmD59et6x1tySZNu2bfHggw/Ggw8+GJWVlTFixIj4+Mc/Hn369ImysrJYt25dvPTSS7F48eKora3Nm3vKKafEpZde2uK9AQAAAABoWKcLt59//vlYtWpVrh43blzsv//+RVm7uro6nnvuuXjuueeaHNetW7eYMmVKfOMb32jRFeMAAAAAADSt04Xb06ZNy6snTZrU4rUGDhwYF1xwQcydOzeWLVsW27dvb3J8375949RTT42///u/j6FDh7Z4XwAAAAAAmtbpwu0bb7wxbrzxxqKs1a9fv7jmmmsi4q+3J3nllVfirbfeinfffTc2btwYtbW10adPn6isrIzhw4fHgQce6EptAAAAAIB20OnC7bbSo0ePGDFiRIwYMaKjWwEAAAAA6PLKOroBAAAAAABoLuE2AAAAAADJEW4DAAAAAJAc4TYAAAAAAMkRbgMAAAAAkBzhNgAAAAAAyRFuAwAAAACQHOE2AAAAAADJEW4DAAAAAJAc4TYAAAAAAMkRbgMAAAAAkJzyjm4AAACgMxl/XG1Ht1DP7FmuawIAOh//wgEAAAAAIDnCbQAAAAAAkiPcBgAAAAAgOcJtAAAAAACSI9wGAAAAACA5wm0AAAAAAJIj3AYAAAAAIDnlHd0AANC08cfVdnQLeWbP8rvxrsr/iwAAQCnxEwEAAAAAAMkRbgMAAAAAkBzhNgAAAAAAyRFuAwAAAACQHOE2AAAAAADJEW4DAAAAAJAc4TYAAAAAAMkRbgMAAAAAkBzhNgAAAAAAyRFuAwAAAACQHOE2AAAAAADJEW4DAAAAAJAc4TYAAAAAAMkRbgMAAAAAkBzhNgAAAAAAyRFuAwAAAACQHOE2AAAAAADJEW4DAAAAAJAc4TYAAAAAAMkRbgMAAAAAkJzyjm4AADrS+ONqO7qFembP8rtnAAAA2BU/PQMAAAAAkBzhNgAAAAAAyRFuAwAAAACQHOE2AAAAAADJEW4DAAAAAJAc4TYAAAAAAMkRbgMAAAAAkBzhNgAAAAAAyRFuAwAAAACQHOE2AAAAAADJEW4DAAAAAJAc4TYAAAAAAMkRbgMAAAAAkBzhNgAAAAAAyRFuAwAAAACQHOE2AAAAAADJEW4DAAAAAJAc4TYAAAAAAMkRbgMAAAAAkBzhNgAAAAAAyRFuAwAAAACQHOE2AAAAAADJEW4DAAAAAJAc4TYAAAAAAMkRbgMAAAAAkBzhNgAAAAAAyRFuAwAAAACQHOE2AAAAAADJEW4DAAAAAJCc8o5uIGXLly+PFStWRFVVVZSVlcXAgQNjxIgRsf/++3d0awAAAAAAnVqnCbePP/74WLVqVYvm/n//3/8XQ4YMKXj89OnT46677oply5Y1+PiYMWPikksuic985jMt6gcAAAAAgKa5LUkzbN26Na666qr4x3/8x0aD7YiIBQsWxNe+9rX40Y9+FNlsth07BAAAAADoGjrNlds7y2QyUVZWeG6fyWQKGve9730vZsyYkTfvmGOOieHDh0dNTU0sWrQoFixYEBER2Ww27rnnnujZs2dcdtllzXsCAAAAAAA0qVOG22eccUbceOONRV3zgQceiN/+9re5ep999omf/exnccghh+SN+8Mf/hCXX355bNiwISIi7rzzzhg7dmyMHz++qP0AAAAAAHRlbktSgM2bN8cdd9yRqysqKuLee++tF2xHRBxzzDFx55135q4Gz2az8dOf/rTdegUAAAAA6AqE2wV46KGH4r333svVF110URxwwAGNjj/yyCPj85//fK5evHhxPP30023aIwAAAABAVyLcLsDvfve73NfdunWLL33pS7uc8+Uvfzmvfvzxx4veFwAAAABAVyXc3oW1a9fGiy++mKvHjBkTAwYM2OW8ww8/PAYOHJirZ82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" ] @@ -199,14 +199,16 @@ "output_type": "stream", "text": [ "Initializing NUTS using jitter+adapt_diag...\n", - "Multiprocess sampling (4 chains in 4 jobs)\n", - "NUTS: [y]\n" + "Multiprocess sampling (4 chains in 2 jobs)\n", + "NUTS: [y]\n", + "/home/zv/upstream/miniconda3/envs/pymc-dev/lib/python3.11/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n", + " self.pid = os.fork()\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "2610298041c0479c8253eff83c265d87", + "model_id": "eed05e43a889410ba40cf6d59bac8990", "version_major": 2, "version_minor": 0 }, @@ -217,6 +219,14 @@ "metadata": {}, "output_type": "display_data" }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/zv/upstream/miniconda3/envs/pymc-dev/lib/python3.11/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n", + " self.pid = os.fork()\n" + ] + }, { "data": { "text/html": [ @@ -227,11 +237,26 @@ "metadata": {}, "output_type": "display_data" }, + { + "data": { + "text/html": [ + "
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+       "
\n" + ], + "text/plain": [ + "\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, { "name": "stderr", "output_type": "stream", "text": [ - "Sampling 4 chains for 1_000 tune and 2_000 draw iterations (4_000 + 8_000 draws total) took 1 seconds.\n" + "Sampling 4 chains for 1_000 tune and 2_000 draw iterations (4_000 + 8_000 draws total) took 14 seconds.\n", + "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", + "The effective sample size per chain is smaller than 100 for some parameters. A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n" ] }, { @@ -269,15 +294,15 @@ " \n", " \n", " y\n", - " 0.775\n", - " 2.088\n", - " -3.117\n", - " 3.85\n", - " 0.092\n", - " 0.065\n", - " 664.0\n", - " 1956.0\n", - " 1.0\n", + " 0.854\n", + " 2.059\n", + " -3.214\n", + " 3.704\n", + " 0.137\n", + " 0.097\n", + " 288.0\n", + " 1919.0\n", + " 1.02\n", " \n", " \n", "\n", @@ -285,10 +310,10 @@ ], "text/plain": [ " mean sd hdi_3% hdi_97% mcse_mean mcse_sd ess_bulk ess_tail \\\n", - "y 0.775 2.088 -3.117 3.85 0.092 0.065 664.0 1956.0 \n", + "y 0.854 2.059 -3.214 3.704 0.137 0.097 288.0 1919.0 \n", "\n", " r_hat \n", - "y 1.0 " + "y 1.02 " ] }, "execution_count": 8, @@ -313,16 +338,18 @@ "name": "stderr", "output_type": "stream", "text": [ - "Multiprocess sampling (4 chains in 4 jobs)\n", + "Multiprocess sampling (4 chains in 2 jobs)\n", "CompoundStep\n", ">BinaryGibbsMetropolis: [idx]\n", - ">NUTS: [y]\n" + ">NUTS: [y]\n", + "/home/zv/upstream/miniconda3/envs/pymc-dev/lib/python3.11/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n", + " self.pid = os.fork()\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "e8acde4d31414bd7af3042776d0a2f00", + "model_id": "939c0be727cd4e2794601e6ffd9f7d93", "version_major": 2, "version_minor": 0 }, @@ -333,6 +360,14 @@ "metadata": {}, "output_type": "display_data" }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/zv/upstream/miniconda3/envs/pymc-dev/lib/python3.11/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n", + " self.pid = os.fork()\n" + ] + }, { "data": { "text/html": [ @@ -343,11 +378,25 @@ "metadata": {}, "output_type": "display_data" }, + { + "data": { + "text/html": [ + "
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+       "
\n" + ], + "text/plain": [ + "\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, { "name": "stderr", "output_type": "stream", "text": [ - "Sampling 4 chains for 1_000 tune and 2_000 draw iterations (4_000 + 8_000 draws total) took 1 seconds.\n", + "Sampling 4 chains for 1_000 tune and 2_000 draw iterations (4_000 + 8_000 draws total) took 19 seconds.\n", + "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "The effective sample size per chain is smaller than 100 for some parameters. A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n" ] }, @@ -386,27 +435,27 @@ " \n", " \n", " idx\n", - " 0.658\n", - " 0.475\n", - " 0.000\n", + " 0.738\n", + " 0.440\n", + " 0.00\n", " 1.000\n", - " 0.028\n", - " 0.020\n", - " 292.0\n", - " 292.0\n", - " 1.01\n", + " 0.027\n", + " 0.019\n", + " 263.0\n", + " 263.0\n", + " 1.02\n", " \n", " \n", " y\n", - " 0.633\n", - " 2.144\n", - " -3.297\n", - " 3.678\n", - " 0.117\n", - " 0.083\n", - " 433.0\n", - " 2054.0\n", - " 1.01\n", + " 0.953\n", + " 2.015\n", + " -3.18\n", + " 3.714\n", + " 0.116\n", + " 0.082\n", + " 404.0\n", + " 1229.0\n", + " 1.02\n", " \n", " \n", "\n", @@ -414,12 +463,12 @@ ], "text/plain": [ " mean sd hdi_3% hdi_97% mcse_mean mcse_sd ess_bulk ess_tail \\\n", - "idx 0.658 0.475 0.000 1.000 0.028 0.020 292.0 292.0 \n", - "y 0.633 2.144 -3.297 3.678 0.117 0.083 433.0 2054.0 \n", + "idx 0.738 0.440 0.00 1.000 0.027 0.019 263.0 263.0 \n", + "y 0.953 2.015 -3.18 3.714 0.116 0.082 404.0 1229.0 \n", "\n", " r_hat \n", - "idx 1.01 \n", - "y 1.01 " + "idx 1.02 \n", + "y 1.02 " ] }, "execution_count": 9, @@ -452,21 +501,17 @@ "name": "stderr", "output_type": "stream", "text": [ - "Initializing NUTS using jitter+adapt_diag...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Multiprocess sampling (4 chains in 4 jobs)\n", - "NUTS: [y]\n" + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (4 chains in 2 jobs)\n", + "NUTS: [y]\n", + "/home/zv/upstream/miniconda3/envs/pymc-dev/lib/python3.11/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n", + " self.pid = os.fork()\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "7eda66992bf94a3aacfcc817be8145af", + "model_id": "295d70c281df4c4389160d474cc924f5", "version_major": 2, "version_minor": 0 }, @@ -477,6 +522,14 @@ "metadata": {}, "output_type": "display_data" }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/zv/upstream/miniconda3/envs/pymc-dev/lib/python3.11/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n", + " self.pid = os.fork()\n" + ] + }, { "data": { "text/html": [ @@ -487,11 +540,24 @@ "metadata": {}, "output_type": "display_data" }, + { + "data": { + "text/html": [ + "
\n",
+       "
\n" + ], + "text/plain": [ + "\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, { "name": "stderr", "output_type": "stream", "text": [ - "Sampling 4 chains for 1_000 tune and 2_000 draw iterations (4_000 + 8_000 draws total) took 1 seconds.\n" + "Sampling 4 chains for 1_000 tune and 2_000 draw iterations (4_000 + 8_000 draws total) took 21 seconds.\n" ] }, { @@ -529,15 +595,15 @@ " \n", " \n", " y\n", - " 0.787\n", - " 2.095\n", - " -3.176\n", - " 3.843\n", - " 0.085\n", - " 0.06\n", - " 780.0\n", - " 2274.0\n", - " 1.01\n", + " 0.837\n", + " 2.062\n", + " -3.154\n", + " 3.711\n", + " 0.09\n", + " 0.063\n", + " 742.0\n", + " 2676.0\n", + " 1.0\n", " \n", " \n", "\n", @@ -545,10 +611,10 @@ ], "text/plain": [ " mean sd hdi_3% hdi_97% mcse_mean mcse_sd ess_bulk ess_tail \\\n", - "y 0.787 2.095 -3.176 3.843 0.085 0.06 780.0 2274.0 \n", + "y 0.837 2.062 -3.154 3.711 0.09 0.063 742.0 2676.0 \n", "\n", " r_hat \n", - "y 1.01 " + "y 1.0 " ] }, "execution_count": 10, @@ -557,8 +623,9 @@ } ], "source": [ - "explicit_mixture.marginalize([\"idx\"])\n", - "with explicit_mixture:\n", + "explicit_mixture_marginalized = pmx.marginalize(explicit_mixture, [\"idx\"])\n", + "\n", + "with explicit_mixture_marginalized:\n", " idata = pm.sample(draws=2000, chains=4, random_seed=rng)\n", "\n", "az.summary(idata)" @@ -581,7 +648,7 @@ "metadata": {}, "outputs": [], "source": [ - "explicit_mixture.recover_marginals(idata, random_seed=rng);" + "idata = pmx.recover_marginals(explicit_mixture_marginalized, idata, random_seed=rng);" ] }, { @@ -625,51 +692,51 @@ " \n", " \n", " y\n", - " 0.787\n", - " 2.095\n", - " -3.176\n", - " 3.843\n", - " 0.085\n", - " 0.060\n", - " 780.0\n", - " 2274.0\n", - " 1.01\n", + " 0.837\n", + " 2.062\n", + " -3.154\n", + " 3.711\n", + " 0.090\n", + " 0.063\n", + " 742.0\n", + " 2676.0\n", + " 1.00\n", " \n", " \n", " idx\n", - " 0.700\n", - " 0.458\n", + " 0.706\n", + " 0.456\n", " 0.000\n", " 1.000\n", - " 0.019\n", - " 0.014\n", - " 576.0\n", - " 576.0\n", + " 0.021\n", + " 0.015\n", + " 457.0\n", + " 457.0\n", " 1.01\n", " \n", " \n", " lp_idx[0]\n", - " -6.214\n", + " -6.303\n", " 5.195\n", - " -14.360\n", + " -14.387\n", " -0.000\n", - " 0.192\n", - " 0.136\n", - " 780.0\n", - " 2274.0\n", - " 1.01\n", + " 0.201\n", + " 0.142\n", + " 742.0\n", + " 2676.0\n", + " 1.00\n", " \n", " \n", " lp_idx[1]\n", - " -2.219\n", - " 3.969\n", - " -10.623\n", + " -2.109\n", + " 3.814\n", + " -10.204\n", " -0.000\n", - " 0.157\n", - " 0.111\n", - " 780.0\n", - " 2274.0\n", - " 1.01\n", + " 0.159\n", + " 0.113\n", + " 742.0\n", + " 2676.0\n", + " 1.00\n", " \n", " \n", "\n", @@ -677,16 +744,16 @@ ], "text/plain": [ " mean sd hdi_3% hdi_97% mcse_mean mcse_sd ess_bulk \\\n", - "y 0.787 2.095 -3.176 3.843 0.085 0.060 780.0 \n", - "idx 0.700 0.458 0.000 1.000 0.019 0.014 576.0 \n", - "lp_idx[0] -6.214 5.195 -14.360 -0.000 0.192 0.136 780.0 \n", - "lp_idx[1] -2.219 3.969 -10.623 -0.000 0.157 0.111 780.0 \n", + "y 0.837 2.062 -3.154 3.711 0.090 0.063 742.0 \n", + "idx 0.706 0.456 0.000 1.000 0.021 0.015 457.0 \n", + "lp_idx[0] -6.303 5.195 -14.387 -0.000 0.201 0.142 742.0 \n", + "lp_idx[1] -2.109 3.814 -10.204 -0.000 0.159 0.113 742.0 \n", "\n", " ess_tail r_hat \n", - "y 2274.0 1.01 \n", - "idx 576.0 1.01 \n", - "lp_idx[0] 2274.0 1.01 \n", - "lp_idx[1] 2274.0 1.01 " + "y 2676.0 1.00 \n", + "idx 457.0 1.01 \n", + "lp_idx[0] 2676.0 1.00 \n", + "lp_idx[1] 2676.0 1.00 " ] }, "execution_count": 12, @@ -714,7 +781,7 @@ "outputs": [ { "data": { - "image/png": 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", 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" ] @@ -783,9 +850,9 @@ "name": "stderr", "output_type": "stream", "text": [ - "/var/home/fonnesbeck/repos/pymc-examples/.pixi/envs/default/lib/python3.12/site-packages/pymc/model/core.py:1288: RuntimeWarning: invalid value encountered in cast\n", + "/home/zv/upstream/miniconda3/envs/pymc-dev/lib/python3.11/site-packages/pymc/model/core.py:1288: RuntimeWarning: invalid value encountered in cast\n", " data = convert_observed_data(data).astype(rv_var.dtype)\n", - "/var/home/fonnesbeck/repos/pymc-examples/.pixi/envs/default/lib/python3.12/site-packages/pymc/model/core.py:1302: ImputationWarning: Data in disasters contains missing values and will be automatically imputed from the sampling distribution.\n", + "/home/zv/upstream/miniconda3/envs/pymc-dev/lib/python3.11/site-packages/pymc/model/core.py:1302: ImputationWarning: Data in disasters contains missing values and will be automatically imputed from the sampling distribution.\n", " warnings.warn(impute_message, ImputationWarning)\n" ] } @@ -805,10 +872,10 @@ "# fmt: on\n", "years = np.arange(1851, 1962)\n", "\n", - "with pmx.MarginalModel() as disaster_model:\n", + "with pm.Model() as disaster_model:\n", " switchpoint = pm.DiscreteUniform(\"switchpoint\", lower=years.min(), upper=years.max())\n", - " early_rate = pm.Exponential(\"early_rate\", 1.0, initval=3)\n", - " late_rate = pm.Exponential(\"late_rate\", 1.0, initval=1)\n", + " early_rate = pm.Exponential(\"early_rate\", 1.0)\n", + " late_rate = pm.Exponential(\"late_rate\", 1.0)\n", " rate = pm.math.switch(switchpoint >= years, early_rate, late_rate)\n", " disasters = pm.Poisson(\"disasters\", rate, observed=disaster_data)" ] @@ -836,13 +903,15 @@ ">CompoundStep\n", ">>Metropolis: [switchpoint]\n", ">>Metropolis: [disasters_unobserved]\n", - ">NUTS: [early_rate, late_rate]\n" + ">NUTS: [early_rate, late_rate]\n", + "/home/zv/upstream/miniconda3/envs/pymc-dev/lib/python3.11/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n", + " self.pid = os.fork()\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "491dc32aa9ea4b9890293b998b737218", + "model_id": "16985d7e91914eb992eeddab48900b48", "version_major": 2, "version_minor": 0 }, @@ -853,6 +922,14 @@ "metadata": {}, "output_type": "display_data" }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/zv/upstream/miniconda3/envs/pymc-dev/lib/python3.11/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n", + " self.pid = os.fork()\n" + ] + }, { "data": { "text/html": [ @@ -863,26 +940,45 @@ "metadata": {}, "output_type": "display_data" }, + { + "data": { + "text/html": [ + "
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+       "
\n" + ], + "text/plain": [ + "\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, { "name": "stderr", "output_type": "stream", "text": [ - "Sampling 2 chains for 1_000 tune and 1_000 draw iterations (2_000 + 2_000 draws total) took 1 seconds.\n", + "Sampling 2 chains for 1_000 tune and 1_000 draw iterations (2_000 + 2_000 draws total) took 13 seconds.\n", "We recommend running at least 4 chains for robust computation of convergence diagnostics\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "The effective sample size per chain is smaller than 100 for some parameters. A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n", - "/var/home/fonnesbeck/repos/pymc-examples/.pixi/envs/default/lib/python3.12/site-packages/pymc_extras/model/marginal/marginal_model.py:174: UserWarning: There are multiple dependent variables in a FiniteDiscreteMarginalRV. Their joint logp terms will be assigned to the first RV: disasters_unobserved\n", - " warnings.warn(\n", + "/home/zv/upstream/pymc-extras/pymc_extras/model/marginal/distributions.py:297: NonSeparableLogpWarning: There are multiple dependent variables in a FiniteDiscreteMarginalRV. Their joint logp terms will be assigned to the first value: [4 5 4 0 1 ... 0 0 1 0 1].\n", + " warn_non_separable_logp(values)\n", + "/home/zv/upstream/pymc-extras/pymc_extras/model/marginal/distributions.py:297: NonSeparableLogpWarning: There are multiple dependent variables in a FiniteDiscreteMarginalRV. Their joint logp terms will be assigned to the first value: [4 5 4 0 1 ... 0 0 1 0 1].\n", + " warn_non_separable_logp(values)\n", + "/home/zv/upstream/pymc-extras/pymc_extras/model/marginal/distributions.py:297: NonSeparableLogpWarning: There are multiple dependent variables in a FiniteDiscreteMarginalRV. Their joint logp terms will be assigned to the first value: [4 5 4 0 1 ... 0 0 1 0 1].\n", + " warn_non_separable_logp(values)\n", "Multiprocess sampling (2 chains in 2 jobs)\n", "CompoundStep\n", - ">NUTS: [early_rate, late_rate]\n", - ">Metropolis: [disasters_unobserved]\n" + ">NUTS: [late_rate, early_rate]\n", + ">Metropolis: [disasters_unobserved]\n", + "/home/zv/upstream/miniconda3/envs/pymc-dev/lib/python3.11/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n", + " self.pid = os.fork()\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4229ae740a274482859d304f079434f0", + "model_id": "40d4acddd307467991eb13f288dd45b4", "version_major": 2, "version_minor": 0 }, @@ -893,6 +989,14 @@ "metadata": {}, "output_type": "display_data" }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/zv/upstream/miniconda3/envs/pymc-dev/lib/python3.11/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n", + " self.pid = os.fork()\n" + ] + }, { "data": { "text/html": [ @@ -903,12 +1007,26 @@ "metadata": {}, "output_type": "display_data" }, + { + "data": { + "text/html": [ + "
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+       "
\n" + ], + "text/plain": [ + "\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, { "name": "stderr", "output_type": "stream", "text": [ - "Sampling 2 chains for 1_000 tune and 1_000 draw iterations (2_000 + 2_000 draws total) took 4 seconds.\n", - "We recommend running at least 4 chains for robust computation of convergence diagnostics\n" + "Sampling 2 chains for 1_000 tune and 1_000 draw iterations (2_000 + 2_000 draws total) took 36 seconds.\n", + "We recommend running at least 4 chains for robust computation of convergence diagnostics\n", + "The effective sample size per chain is smaller than 100 for some parameters. A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n" ] } ], @@ -916,9 +1034,9 @@ "with disaster_model:\n", " before_marg = pm.sample(chains=2, random_seed=rng)\n", "\n", - "disaster_model.marginalize([\"switchpoint\"])\n", + "disaster_model_marginalized = pmx.marginalize(disaster_model, [\"switchpoint\"])\n", "\n", - "with disaster_model:\n", + "with disaster_model_marginalized:\n", " after_marg = pm.sample(chains=2, random_seed=rng)" ] }, @@ -963,39 +1081,39 @@ " \n", " \n", " early_rate\n", - " 3.100\n", - " 0.289\n", - " 2.547\n", - " 3.620\n", - " 0.008\n", - " 0.005\n", - " 1437.0\n", - " 1294.0\n", - " 1.00\n", + " 3.090\n", + " 0.278\n", + " 2.594\n", + " 3.630\n", + " 0.009\n", + " 0.006\n", + " 1022.0\n", + " 1049.0\n", + " 1.0\n", " \n", " \n", " late_rate\n", - " 0.940\n", - " 0.115\n", - " 0.713\n", - " 1.143\n", + " 0.937\n", + " 0.117\n", + " 0.718\n", + " 1.151\n", " 0.003\n", " 0.002\n", - " 1294.0\n", - " 1148.0\n", - " 1.00\n", + " 1239.0\n", + " 1443.0\n", + " 1.0\n", " \n", " \n", " switchpoint\n", - " 1889.406\n", - " 2.387\n", + " 1889.785\n", + " 2.581\n", " 1885.000\n", - " 1893.000\n", - " 0.214\n", - " 0.151\n", - " 127.0\n", - " 334.0\n", - " 1.02\n", + " 1894.000\n", + " 0.204\n", + " 0.145\n", + " 164.0\n", + " 275.0\n", + " 1.0\n", " \n", " \n", "\n", @@ -1003,14 +1121,14 @@ ], "text/plain": [ " mean sd hdi_3% hdi_97% mcse_mean mcse_sd \\\n", - "early_rate 3.100 0.289 2.547 3.620 0.008 0.005 \n", - "late_rate 0.940 0.115 0.713 1.143 0.003 0.002 \n", - "switchpoint 1889.406 2.387 1885.000 1893.000 0.214 0.151 \n", + "early_rate 3.090 0.278 2.594 3.630 0.009 0.006 \n", + "late_rate 0.937 0.117 0.718 1.151 0.003 0.002 \n", + "switchpoint 1889.785 2.581 1885.000 1894.000 0.204 0.145 \n", "\n", " ess_bulk ess_tail r_hat \n", - "early_rate 1437.0 1294.0 1.00 \n", - "late_rate 1294.0 1148.0 1.00 \n", - "switchpoint 127.0 334.0 1.02 " + "early_rate 1022.0 1049.0 1.0 \n", + "late_rate 1239.0 1443.0 1.0 \n", + "switchpoint 164.0 275.0 1.0 " ] }, "execution_count": 16, @@ -1063,26 +1181,26 @@ " \n", " \n", " early_rate\n", - " 3.098\n", - " 0.291\n", - " 2.539\n", - " 3.603\n", - " 0.007\n", + " 3.078\n", + " 0.284\n", + " 2.577\n", + " 3.653\n", + " 0.006\n", " 0.005\n", - " 1796.0\n", - " 1532.0\n", + " 2036.0\n", + " 1344.0\n", " 1.0\n", " \n", " \n", " late_rate\n", - " 0.930\n", - " 0.121\n", - " 0.704\n", - " 1.152\n", + " 0.929\n", + " 0.115\n", + " 0.714\n", + " 1.146\n", " 0.003\n", " 0.002\n", - " 1578.0\n", - " 1433.0\n", + " 1303.0\n", + " 1228.0\n", " 1.0\n", " \n", " \n", @@ -1091,12 +1209,12 @@ ], "text/plain": [ " mean sd hdi_3% hdi_97% mcse_mean mcse_sd ess_bulk \\\n", - "early_rate 3.098 0.291 2.539 3.603 0.007 0.005 1796.0 \n", - "late_rate 0.930 0.121 0.704 1.152 0.003 0.002 1578.0 \n", + "early_rate 3.078 0.284 2.577 3.653 0.006 0.005 2036.0 \n", + "late_rate 0.929 0.115 0.714 1.146 0.003 0.002 1303.0 \n", "\n", " ess_tail r_hat \n", - "early_rate 1532.0 1.0 \n", - "late_rate 1433.0 1.0 " + "early_rate 1344.0 1.0 \n", + "late_rate 1228.0 1.0 " ] }, "execution_count": 17, @@ -1131,7 +1249,7 @@ "metadata": {}, "outputs": [], "source": [ - "disaster_model.recover_marginals(after_marg);" + "after_marg = pmx.recover_marginals(disaster_model_marginalized, after_marg);" ] }, { @@ -1175,38 +1293,38 @@ " \n", " \n", " early_rate\n", - " 3.098\n", - " 0.291\n", - " 2.539\n", - " 3.603\n", - " 0.007\n", + " 3.078\n", + " 0.284\n", + " 2.577\n", + " 3.653\n", + " 0.006\n", " 0.005\n", - " 1796.0\n", - " 1532.0\n", + " 2036.0\n", + " 1344.0\n", " 1.0\n", " \n", " \n", " late_rate\n", - " 0.930\n", - " 0.121\n", - " 0.704\n", - " 1.152\n", + " 0.929\n", + " 0.115\n", + " 0.714\n", + " 1.146\n", " 0.003\n", " 0.002\n", - " 1578.0\n", - " 1433.0\n", + " 1303.0\n", + " 1228.0\n", " 1.0\n", " \n", " \n", " switchpoint\n", - " 1889.692\n", - " 2.444\n", + " 1889.812\n", + " 2.434\n", " 1885.000\n", " 1893.000\n", - " 0.076\n", - " 0.054\n", - " 965.0\n", - " 1637.0\n", + " 0.108\n", + " 0.077\n", + " 494.0\n", + " 1302.0\n", " 1.0\n", " \n", " \n", @@ -1215,14 +1333,14 @@ ], "text/plain": [ " mean sd hdi_3% hdi_97% mcse_mean mcse_sd \\\n", - "early_rate 3.098 0.291 2.539 3.603 0.007 0.005 \n", - "late_rate 0.930 0.121 0.704 1.152 0.003 0.002 \n", - "switchpoint 1889.692 2.444 1885.000 1893.000 0.076 0.054 \n", + "early_rate 3.078 0.284 2.577 3.653 0.006 0.005 \n", + "late_rate 0.929 0.115 0.714 1.146 0.003 0.002 \n", + "switchpoint 1889.812 2.434 1885.000 1893.000 0.108 0.077 \n", "\n", " ess_bulk ess_tail r_hat \n", - "early_rate 1796.0 1532.0 1.0 \n", - "late_rate 1578.0 1433.0 1.0 \n", - "switchpoint 965.0 1637.0 1.0 " + "early_rate 2036.0 1344.0 1.0 \n", + "late_rate 1303.0 1228.0 1.0 \n", + "switchpoint 494.0 1302.0 1.0 " ] }, "execution_count": 19, @@ -1250,7 +1368,7 @@ "outputs": [ { "data": { - "image/png": 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" ] @@ -1278,7 +1396,7 @@ "outputs": [ { "data": { - "image/png": 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SSy80NNT05IO7TVWuXbumjRs3mvpo1KiR2/b9/f315JNPGuXExERLfWlD/rF9+3Zjpo0kPfrooypcuLDH81q2bKkSJUoYZU+b+6R/MkGSunfv7rGPrl27mm5WeRovGJOQl3IjlrKSZPP399djjz1mOrZnzx635xBLyCu5NSa5Mn78eMXHx0uSunTpooiIiCy1IxFHyFu5FUs3btwwPeUaERHh1Wc9M9J/h/T19dVTTz3l8Zynn37aVLZSLJHcBmAZjjshBwUFeXWe42M97tbEXrFihakfbwaBzNi3b58pIfjXv/7V9Ai5K61atTLNaF23bt0dvS78ueR0LDm27+rROk99uIvVTZs2mRLorVu39qr9Nm3amMrEErLi9tqKt3k708bHx0cPPPCAUT527JiOHDnitG5KSop+/PFHo1y6dGnVqVPHYx9hYWGmG1E7d+7UH3/84bQuYxLyWm7EUlalf9JHkmkGnCNiCXkpL+Now4YNWrNmjaRbSzkOHz48U+enRxwhr+VWLK1du9a0ROSdzjlcunRJv/zyi1GOiIhQWFiYx/Pq1q2r8PBwo7xhwwbT2uP5GcltAJbhuNbamTNnvDrv9OnTxmubzaby5cu7rJt+w4VixYqpfv36mbxK97Zv324qezuzISgoSNWrVzfKBw8eNDZ8ADIrp2OpWLFiKlCggNPzMtOHu1jNaixVqFBBxYsXd9kO4A3HZLE3Pxhc1d26davTejExMcYSWZL3n3HJ/JRFamqqdu7c6bQeYxLyWm7EUlbd3kT5tvTJM0fEEvJSXsXRtWvXNG7cOKP86quvqlChQl6f74g4Ql7LrVhavXq18drX11ePPPKI1/14Y+fOnabJRln9DhkfH6+YmJg7eWk5huQ2AMto3ry5qXx7loA7CQkJpplvERERKlKkiNO6ly9f1vHjx41yjRo17tgax7cdPXrUVK5Ro4bX5zrWdWwL8FZOx5KPj4+aNm1qlM+fP+9VEnnbtm2Ki4szyi1atHBZNzuxlH4jlcuXL7udjQc447hJo7u13h05zkJztY6v43FnGwC5UrNmTa/6YExCXsuNWMqq9OvdS+6THMQS8lJexdG0adN09uxZSbc2pMvusgrEEfJabsSS3W43LXNVvnx5hYaGZuIqPXPsOzOx5Pgd0iqxRHIbgGV07txZJUuWNMpz5841PW7jKDk5WaNGjTLtVjxo0CCX9fft22cq33fffcbrHTt2aPTo0Wrbtq0efPBBNWjQQK1bt9bw4cP11VdfKSUlxav34Dg4lC5d2qvzJKlMmTJu2wK8ldOxJEnPPfec6ebQmDFj3G7eGBcXZ9qwpUiRIurZs6fL+uk//wEBAabZ2J4QS8guxx8h6WPDk/SzsSXvE8+On1t3HMeWY8eOedUHYxJyW27EUlZcv35d33//vVH28fFRw4YNXdYnlpCX8iKOdu/erc8++0zSraTea6+95nWfrhBHyGu5EUsnTpwwtVulShXj9cGDB/XWW2+pQ4cOatiwoerXr6/HHntMgwcP1rJly3Tjxg2vriU7seRY1yqxRHIbgGWEhITo3XffNe6KXr9+XT169NCUKVP066+/KjExUWlpaTp//rxWr16tJ598Ut99951x/tChQ02zSR05rotVvHhxXb58WcOGDdPTTz+t5cuXKyYmRlevXjVmeX/11VcaPny4Hn/8cW3ZssXje0i/jpyfn59p4wlP0q9/JUnnzp3z+lwgvZyOJUmqU6eOhg0bZpSPHj2qDh06aOHChTp16pRSUlKUnJys48ePa/78+erQoYPx5ERgYKCmTZvmNmGdPpbCwsLcrs/tyHH2HbGEzCpVqpSpnJlHNh3ruvr8OW7Y6jgGuOPteMGYhLyWG7GUFfPmzdP169eNcoMGDVSsWDGX9Ykl5KXcjqPk5GSNGTPGWPagf//+uueee7zu0xXiCHktN2LJWc4hMTFR48ePV8eOHbVgwQIdPHhQ8fHxunLlik6cOKHvvvtOY8aM0aOPPurVxq+58R0yv8n81tEAkIcaNGigyMhIjRo1SgcPHlRSUpLmzp2ruXPnSrq1DrDdbjedU65cOY0cOdLjhnOOd1ttNpt69+6dYWMJZ06cOKF+/fpp/Pjx6tSpk8t66ddvDA4OztSyJwULFjSV0//oAjIrJ2Pptn79+ik8PFyTJk3ShQsXdP78eY0fP17jx493ec6DDz6osWPHmtZOdHTz5k3T5iaOseFJSEiIqUwsIbMcNxjasGGDXnzxRY/nxcbG6tdffzUdc1zX19XxzHzOvR0vGJOQ13IjljLr8OHDmj17tumYp6eViCXkpdyOozlz5ujw4cOSpMqVK6tv376ZuFrXiCPktdyIJcecQ1BQkAYNGqSNGzd67CcuLk7Dhg3TyZMnNWDAAJf1cuM7ZH7DzG0AllOrVi19+eWXGj58uIKCgkx/c0zGNW7cWHPmzPEqGee48cicOXOMxPa9996rSZMmaePGjdq7d69+/PFHTZ061fQYUUpKisaMGWNaQ8tR+keJvNn9Oz3HNb+sMtAg/8qpWEqvXbt2Wrt2rdubPtKtZHr37t01a9Yst4ltKeNnn1hCbqtRo4ZpaZ/9+/frhx9+8HjenDlzMixj5erHj+Ojp9lZ99HVZ5wxCXktN2IpM65du6aXXnpJSUlJxrFOnTrpL3/5i9vziCXkpdyMo99++00ffvihUX799dczNT65Qxwhr+VGLDnmHFasWGEktkuWLKkxY8Zo3bp12rt3r6KjozVr1qwMG0JOnz7dtHSWI8fvkJmJJ2+/Q+Y3JLcBWM6uXbvUpUsXTZkyRTdv3nRbNzo6Wm3bttWIESMy3CV15PgP9+21sBo1aqQvv/xSnTp1UlhYmAICAlSqVCm1bdtWK1asMG16l5ycrLFjx7rsI/31ZvaLoGN9T+8d8CSnYim9qKgotW3bVlFRUW7r2e12ffbZZ2rRooU++OAD0w7fjrKz2Yuz+sQSMsvPz0/PPvus6dioUaPcrlW6atUqY33S9Bw/z7c5fi4z8zn39jPOmIS8lhux5K20tDSNGDHC9Mh4+fLlNWrUKI/nEkvIS7kVR3a7XWPHjjVu/nTu3NnjjZ/MII6Q13IjllzlHKpWrapVq1apR48eKleunAICAlSsWDG1atVKixcvVteuXU3nvfbaa3n6HTK/IbkNwFKioqLUo0cPY3Z0wYIF9dxzz2n58uXasWOH9u7dqw0bNujdd9817nCmpaVp1apV6tKli86fP++ybWf/6BctWlTTpk1TcHCwy3OmTJli2njh119/1ebNm53WT38nNDk52fMbTif9LCLHtoDMyslYkv73A+iVV14x1morW7asRo8erW+++Ua//PKLdu/erTVr1mjUqFEqW7aspFtf+KZPn67Bgwe73KjV8bNPLCEv9OzZ0/SUQVxcnJ588knNmjVLx44dU3Jysm7cuKFdu3bplVde0ciRI2W32zMsi1OgQAGn7Wfnc+7tZ5wxCflBTseStyZMmKB169YZ5dDQUP373//OsMGYM8QS8lpuxNGSJUu0fft2Sbc2/h45cuQdfQ/EEfKDnI4lZzmHgIAAzZgxw+XeDjabTWPHjlWtWrWMYxcuXNDKlSud1s+N75D5DcltAJaxc+dOjRo1ykh4lSlTRl988YVefvll1alTRyEhIQoICFDp0qX1xBNPaPHixXr++eeN848fP66hQ4e6nBHqbADq1q2b2w2EpFvr9/bq1ct0bP369R77yOxdUMeBJrs/4vDnldOxJElz587V0qVLjXKzZs20atUqPfPMM6pUqZKCgoIUHBysypUrq2fPnlq1apVpk8rvv/9eM2fOdNq242efWEJeCAwM1HvvvWfcmJFuPYI6Y8YMtWnTRrVq1VLdunXVtWtXRUVFyW63y8/PT5MnTza1U6hQIaftO34uMzMr1bGuq884YxLyg5yOJW+8//77WrRokemaZs2apWrVqnl1PrGEvJbTcRQbG6upU6ca5X/+858qWrToHX0PxBHyg9z+fidJf/vb31SpUiW31+Xr65thne3//ve/XvWRmXjy9jtkfkNyG4BljB8/3rSJ3IwZM1SxYkWX9W02m4YNG6aHH37YOLZjxw599913Tus722gh/ZIj7rRs2dJU3rlzp9N66QeHGzduZFjX2B3HdbusMtAg/8npWLp06ZLef/99o1yyZEnNmDEjw4yG9EJCQjRz5kzTOnfz5s1zOkM8KChIvr6+Rjmza8FdvXrVVCaWkFUVKlTQ8uXLvRorSpcurY8++kgPPPCA6bi3P34ys56wt+MFYxLyi5yMJU8+++wzvffee0bZz89P06ZNU4MGDbxug1hCfpCTcfTGG28YawU3aNBAnTt3zv4FOyCOkF/kZCxlJ+fQvHlz+fv7G+Vdu3Y5ref4+c/MbyWrxhLJbQCWcPjwYWNzR+nWOth16tTx6tznnnvOVHb1+E54eHiGY1WrVvWqjwoVKpg25HO1ZENYWJjxOiUlRXFxcV61L8lY2uE2Z9cLeJIbsbRmzRrTXf9u3bq5TWzfFhISom7duhnl5ORkrVmzxmndUqVKGa9jY2Mz9QMoNjbWVCaWkB3FixfXhx9+qKVLl+rZZ59V9erVVbRoUfn7+yssLEwNGzbUuHHjtHr1ajVu3FgXL140nV+5cmWn7aYfL6SMY4A73o4XjEnIT3IqltxZuXKl3nzzTaNss9k0YcIEtWrVKlPtEEvIL3IijrZv325sXufv769x48blyLUTR8hPcmpMyk7OITAwUBUqVDDK8fHxGZ5akDJ+hzx79qxX7UvWjSW/vL4AAPDGL7/8YipnZjZN3bp15e/vb6w1tXfvXqf17rvvPlM5ICDAlLD2pFChQsYjP/Hx8U7rVKpUyVirTro10KRP0rlz5syZDG0BmZUbsbR7925TuWHDhl734Xg9rvqoVKmS8UUtMTFRFy9eVIkSJbzqg1hCTqhbt67q1q3rsV5MTIypXLt2baf1HD+Xjp9bdxx/xLj6jDMmIT+607H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" ] @@ -1351,24 +1469,24 @@ "name": "stdout", "output_type": "stream", "text": [ - "Last updated: Sat Dec 14 2024\n", + "Last updated: Sat Jan 04 2025\n", "\n", "Python implementation: CPython\n", - "Python version : 3.12.5\n", - "IPython version : 8.27.0\n", + "Python version : 3.11.6\n", + "IPython version : 8.22.2\n", "\n", "pytensor: 2.26.4\n", - "xarray : 2024.7.0\n", + "xarray : 2024.3.0\n", "\n", - "pytensor : 2.26.4\n", - "arviz : 0.19.0\n", + "arviz : 0.18.0\n", "numpy : 1.26.4\n", - "pandas : 2.2.2\n", - "matplotlib : 3.9.2\n", - "pymc_extras: 0.2.0\n", + "pymc_extras: 0.2.1\n", + "matplotlib : 3.8.4\n", "pymc : 5.19.1\n", + "pytensor : 2.26.4\n", + "pandas : 2.2.2\n", "\n", - "Watermark: 2.5.0\n", + "Watermark: 2.4.3\n", "\n" ] } @@ -1390,7 +1508,7 @@ ], "metadata": { "kernelspec": { - "display_name": "default", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -1404,7 +1522,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.5" + "version": "3.11.6" }, "myst": { "substitutions": { diff --git a/examples/howto/marginalizing-models.myst.md b/examples/howto/marginalizing-models.myst.md index 48e41760..dc8e2554 100644 --- a/examples/howto/marginalizing-models.myst.md +++ b/examples/howto/marginalizing-models.myst.md @@ -5,7 +5,7 @@ jupytext: format_name: myst format_version: 0.13 kernelspec: - display_name: default + display_name: Python 3 (ipykernel) language: python name: python3 myst: @@ -75,7 +75,7 @@ There are two ways to specify the same model. One where the choice of mixture is ```{code-cell} ipython3 mu = pt.as_tensor([-2.0, 2.0]) -with pmx.MarginalModel() as explicit_mixture: +with pm.Model() as explicit_mixture: idx = pm.Bernoulli("idx", 0.7) y = pm.Normal("y", mu=mu[idx], sigma=1.0) ``` @@ -112,8 +112,9 @@ az.summary(idata) We can immediately see that the marginalized model has a higher ESS. Let's now marginalize out the choice and see what it changes in our model. ```{code-cell} ipython3 -explicit_mixture.marginalize(["idx"]) -with explicit_mixture: +explicit_mixture_marginalized = pmx.marginalize(explicit_mixture, ["idx"]) + +with explicit_mixture_marginalized: idata = pm.sample(draws=2000, chains=4, random_seed=rng) az.summary(idata) @@ -124,7 +125,7 @@ As we can see, the `idx` variable is gone now. We also were able to use the NUTS But {class}`MarginalModel ` has a distinct advantage. It still knows about the discrete variables that were marginalized out, and we can obtain estimates for the posterior of `idx` given the other variables. We do this using the {meth}`recover_marginals ` method. ```{code-cell} ipython3 -explicit_mixture.recover_marginals(idata, random_seed=rng); +idata = pmx.recover_marginals(explicit_mixture_marginalized, idata, random_seed=rng); ``` ```{code-cell} ipython3 @@ -179,10 +180,10 @@ disaster_data = pd.Series( # fmt: on years = np.arange(1851, 1962) -with pmx.MarginalModel() as disaster_model: +with pm.Model() as disaster_model: switchpoint = pm.DiscreteUniform("switchpoint", lower=years.min(), upper=years.max()) - early_rate = pm.Exponential("early_rate", 1.0, initval=3) - late_rate = pm.Exponential("late_rate", 1.0, initval=1) + early_rate = pm.Exponential("early_rate", 1.0) + late_rate = pm.Exponential("late_rate", 1.0) rate = pm.math.switch(switchpoint >= years, early_rate, late_rate) disasters = pm.Poisson("disasters", rate, observed=disaster_data) ``` @@ -193,9 +194,9 @@ We will sample the model both before and after we marginalize out the `switchpoi with disaster_model: before_marg = pm.sample(chains=2, random_seed=rng) -disaster_model.marginalize(["switchpoint"]) +disaster_model_marginalized = pmx.marginalize(disaster_model, ["switchpoint"]) -with disaster_model: +with disaster_model_marginalized: after_marg = pm.sample(chains=2, random_seed=rng) ``` @@ -214,7 +215,7 @@ As before, the ESS improved massively Finally, let us recover the `switchpoint` variable ```{code-cell} ipython3 -disaster_model.recover_marginals(after_marg); +after_marg = pmx.recover_marginals(disaster_model_marginalized, after_marg); ``` ```{code-cell} ipython3