{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Poisson likelihood and Gamma prior\n",
    "\n",
    "This is a simple model where our discrete data, $y$, is modelled as a Poisson RV with Gamma prior, which is a conjugate prior model.\n",
    "\n",
    "$L(x) = p(y | x) = \\mathcal{P}[y \\mid x]$\n",
    "\n",
    "and\n",
    "\n",
    "$p(x) = \\Gamma[x \\mid k, \\theta]$.\n",
    "\n",
    "The analytic evidence for this model is,\n",
    "\n",
    "$Z = p(y) = \\int_\\mathcal{X} L(x) p(x) \\,\\mathrm{d} x =  \\mathcal{P}[y \\mid 1] \\frac{\\Gamma[1 \\mid k, \\theta]}{\\Gamma[1 \\mid k', \\theta']}$\n",
    "\n",
    "The posterior is also a Gamma distribution,\n",
    "\n",
    "$p(x \\mid y) = \\Gamma[x \\mid k', \\theta']$\n",
    "\n",
    "where\n",
    "\n",
    "$k' = k + \\sum_i y_i$\n",
    "\n",
    "and\n",
    "\n",
    "$\\theta' = \\frac{\\theta}{(\\theta \\sum_i y_i + 1)}$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-25T09:52:23.442949Z",
     "start_time": "2024-09-25T09:52:18.216677Z"
    },
    "execution": {
     "iopub.execute_input": "2024-09-25T13:31:45.632776Z",
     "iopub.status.busy": "2024-09-25T13:31:45.632583Z",
     "iopub.status.idle": "2024-09-25T13:31:46.932942Z",
     "shell.execute_reply": "2024-09-25T13:31:46.932370Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/albert/miniconda3/envs/jaxns_py/lib/python3.11/site-packages/jaxns/internals/mixed_precision.py:14: UserWarning: JAX x64 is not enabled. Setting it now. Check for errors.\n",
      "  warnings.warn(\"JAX x64 is not enabled. Setting it now. Check for errors.\")\n",
      "INFO:jax._src.xla_bridge:Unable to initialize backend 'cuda': \n",
      "INFO:jax._src.xla_bridge:Unable to initialize backend 'rocm': module 'jaxlib.xla_extension' has no attribute 'GpuAllocatorConfig'\n",
      "INFO:jax._src.xla_bridge:Unable to initialize backend 'tpu': INTERNAL: Failed to open libtpu.so: libtpu.so: cannot open shared object file: No such file or directory\n",
      "WARNING:jax._src.xla_bridge:An NVIDIA GPU may be present on this machine, but a CUDA-enabled jaxlib is not installed. Falling back to cpu.\n"
     ]
    }
   ],
   "source": [
    "\n",
    "import numpy as np\n",
    "import pylab as plt\n",
    "import tensorflow_probability.substrates.jax as tfp\n",
    "from jax import random, numpy as jnp\n",
    "\n",
    "from jaxns import resample\n",
    "\n",
    "tfpd = tfp.distributions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-25T09:52:23.466456Z",
     "start_time": "2024-09-25T09:52:23.450135Z"
    },
    "execution": {
     "iopub.execute_input": "2024-09-25T13:31:46.935153Z",
     "iopub.status.busy": "2024-09-25T13:31:46.934944Z",
     "iopub.status.idle": "2024-09-25T13:31:46.938810Z",
     "shell.execute_reply": "2024-09-25T13:31:46.938390Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Taking 10 samples from a Poisson distribution as data.\n"
     ]
    }
   ],
   "source": [
    "# Generate data\n",
    "np.random.seed(42)\n",
    "\n",
    "num_samples = 10\n",
    "\n",
    "true_k = 0.5\n",
    "true_theta = 1.\n",
    "_gamma = np.random.gamma(true_k, true_theta, size=num_samples)\n",
    "print(f\"Taking {num_samples} samples from a Poisson distribution as data.\")\n",
    "data = jnp.asarray(np.random.poisson(_gamma, size=num_samples))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-25T09:52:39.497623Z",
     "start_time": "2024-09-25T09:52:23.471359Z"
    },
    "execution": {
     "iopub.execute_input": "2024-09-25T13:31:46.941169Z",
     "iopub.status.busy": "2024-09-25T13:31:46.941004Z",
     "iopub.status.idle": "2024-09-25T13:31:50.636118Z",
     "shell.execute_reply": "2024-09-25T13:31:50.635513Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:jaxns:Sanity check...\n",
      "INFO:jaxns:Sanity check passed\n"
     ]
    }
   ],
   "source": [
    "\n",
    "from jaxns.internals.mixed_precision import mp_policy\n",
    "from jaxns import Prior, Model\n",
    "\n",
    "# Build model\n",
    "prior_k = 100.\n",
    "\n",
    "# Note if prior_theta is chosen too large 32-bit will be insufficient\n",
    "prior_theta = 0.1\n",
    "\n",
    "\n",
    "def prior_model():\n",
    "    lamda = yield Prior(\n",
    "        tfpd.Gamma(concentration=jnp.asarray(prior_k, mp_policy.measure_dtype),\n",
    "                   rate=1. / jnp.asarray(prior_theta, mp_policy.measure_dtype)),\n",
    "        name='lamda')\n",
    "    return lamda\n",
    "\n",
    "\n",
    "def log_likelihood(lamda):\n",
    "    \"\"\"\n",
    "    Poisson likelihood.\n",
    "    \"\"\"\n",
    "    _log_prob = jnp.sum(tfpd.Poisson(rate=lamda).log_prob(data))\n",
    "    return _log_prob\n",
    "\n",
    "\n",
    "model = Model(prior_model=prior_model, log_likelihood=log_likelihood)\n",
    "\n",
    "model.sanity_check(random.PRNGKey(0), S=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-25T09:52:40.413817Z",
     "start_time": "2024-09-25T09:52:39.502661Z"
    },
    "execution": {
     "iopub.execute_input": "2024-09-25T13:31:50.638414Z",
     "iopub.status.busy": "2024-09-25T13:31:50.638156Z",
     "iopub.status.idle": "2024-09-25T13:31:50.866189Z",
     "shell.execute_reply": "2024-09-25T13:31:50.865648Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True Evidence = -69.31472389012055\n",
      "True posterior concentration (k) = 100.0\n",
      "True posterior rate (1/theta) = 20.0\n",
      "True posterior lamda = 5.0\n"
     ]
    }
   ],
   "source": [
    "# Evidence and posterior are analytic\n",
    "def log_gamma_prob(lamda, k, theta):\n",
    "    return tfpd.Gamma(concentration=k, rate=1. / theta).log_prob(lamda)\n",
    "    # return (k-1) * jnp.log(gamma)  - gamma / theta - gammaln(k) - k * jnp.log(theta)\n",
    "\n",
    "\n",
    "true_post_k = prior_k + jnp.sum(data)\n",
    "true_post_theta = prior_theta / (num_samples * prior_theta + 1.)\n",
    "\n",
    "true_post_mean_gamma = true_post_theta * true_post_k\n",
    "\n",
    "true_logZ = log_likelihood(1.) + log_gamma_prob(1., prior_k, prior_theta) - log_gamma_prob(1., true_post_k,\n",
    "                                                                                           true_post_theta)\n",
    "print(f\"True Evidence = {true_logZ}\")\n",
    "print(f\"True posterior concentration (k) = {true_post_k}\")\n",
    "print(f\"True posterior rate (1/theta) = {1. / true_post_theta}\")\n",
    "print(f\"True posterior lamda = {true_post_mean_gamma}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-25T09:52:40.433009Z",
     "start_time": "2024-09-25T09:52:40.422293Z"
    },
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2024-09-25T13:31:50.868056Z",
     "iopub.status.busy": "2024-09-25T13:31:50.867896Z",
     "iopub.status.idle": "2024-09-25T13:31:50.870544Z",
     "shell.execute_reply": "2024-09-25T13:31:50.870148Z"
    }
   },
   "outputs": [],
   "source": [
    "from jaxns import NestedSampler\n",
    "\n",
    "# Run the nested sampling\n",
    "ns = NestedSampler(model=model, verbose=False, init_efficiency_threshold=0.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-25T09:53:24.759883Z",
     "start_time": "2024-09-25T09:52:40.437218Z"
    },
    "execution": {
     "iopub.execute_input": "2024-09-25T13:31:50.872289Z",
     "iopub.status.busy": "2024-09-25T13:31:50.872135Z",
     "iopub.status.idle": "2024-09-25T13:32:01.287613Z",
     "shell.execute_reply": "2024-09-25T13:32:01.287065Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------\n",
      "Termination Conditions:\n",
      "Small remaining evidence\n",
      "--------\n",
      "likelihood evals: 135128\n",
      "samples: 1260\n",
      "phantom samples: 0\n",
      "likelihood evals / sample: 107.2\n",
      "phantom fraction (%): 0.0%\n",
      "--------\n",
      "logZ=-68.26 +- 0.89\n",
      "max(logL)=-27.77\n",
      "H=-20.08\n",
      "ESS=72\n",
      "--------\n",
      "lamda: mean +- std.dev. | 10%ile / 50%ile / 90%ile | MAP est. | max(L) est.\n",
      "lamda: 4.74 +- 0.5 | 4.05 / 4.79 / 5.33 | 4.95 | 2.78\n",
      "--------\n"
     ]
    }
   ],
   "source": [
    "term_reason, state = ns(random.PRNGKey(3452345))\n",
    "results = ns.to_results(termination_reason=term_reason, state=state)\n",
    "# ns.plot_diagnostics(results)\n",
    "ns.summary(results)\n",
    "# ns.plot_cornerplot(results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-25T09:53:27.890740Z",
     "start_time": "2024-09-25T09:53:24.764626Z"
    },
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2024-09-25T13:32:01.289430Z",
     "iopub.status.busy": "2024-09-25T13:32:01.289271Z",
     "iopub.status.idle": "2024-09-25T13:32:01.946141Z",
     "shell.execute_reply": "2024-09-25T13:32:01.945697Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/albert/miniconda3/envs/jaxns_py/lib/python3.11/site-packages/jaxns/plotting.py:45: UserWarning: Found samples with zero likelihood evaluations.\n",
      "  warnings.warn(\"Found samples with zero likelihood evaluations.\")\n",
      "/home/albert/miniconda3/envs/jaxns_py/lib/python3.11/site-packages/jaxns/plotting.py:49: RuntimeWarning: divide by zero encountered in divide\n",
      "  1. / num_likelihood_evaluations_per_sample\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 800x1200 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ns.plot_diagnostics(results)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-25T09:53:49.109234Z",
     "start_time": "2024-09-25T09:53:45.530758Z"
    },
    "execution": {
     "iopub.execute_input": "2024-09-25T13:32:01.948000Z",
     "iopub.status.busy": "2024-09-25T13:32:01.947816Z",
     "iopub.status.idle": "2024-09-25T13:32:02.737777Z",
     "shell.execute_reply": "2024-09-25T13:32:02.737197Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Comparing samples to true posterior\n",
    "\n",
    "samples = resample(random.PRNGKey(43083245), results.samples, results.log_dp_mean, S=1000)\n",
    "\n",
    "plt.hist(samples['lamda'], bins='auto', ec='blue', alpha=0.5, density=True, fc='none')\n",
    "\n",
    "_gamma = np.random.gamma(true_post_k, true_post_theta, size=100000)\n",
    "\n",
    "plt.hist(_gamma, bins='auto', ec='orange', alpha=0.5, density=True, fc='none')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-25T09:53:49.122370Z",
     "start_time": "2024-09-25T09:53:49.116801Z"
    },
    "collapsed": false
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}