{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Constant Likelihood\n",
    "\n",
    "Managing plateaus in nested sampling is tricky because the measure of enclosed prior volume is assumed to be monotonically decreasing. In this simple model, the model is simply,\n",
    "\n",
    "$L(x) = P(y | x) = 1$\n",
    "\n",
    "and\n",
    "\n",
    "$P(x) = \\mathcal{U}[x \\mid 0, 1]$.\n",
    "\n",
    "The analytic evidence for this model is,\n",
    "\n",
    "$Z = P(y) = \\int_\\mathcal{X} L(x) p(x) \\,\\mathrm{d} x = 1$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-23T21:20:48.996658Z",
     "iopub.status.busy": "2024-09-23T21:20:48.996129Z",
     "iopub.status.idle": "2024-09-23T21:20:49.942805Z",
     "shell.execute_reply": "2024-09-23T21:20:49.942188Z"
    }
   },
   "outputs": [],
   "source": [
    "\n",
    "import tensorflow_probability.substrates.jax as tfp\n",
    "from jax import random\n",
    "\n",
    "tfpd = tfp.distributions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-23T21:20:49.945404Z",
     "iopub.status.busy": "2024-09-23T21:20:49.945127Z",
     "iopub.status.idle": "2024-09-23T21:20:50.857367Z",
     "shell.execute_reply": "2024-09-23T21:20:50.856726Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/albert/miniconda3/envs/jaxns_py/lib/python3.11/site-packages/jaxns/internals/mixed_precision.py:15: 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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True log(Z)=0.0\n"
     ]
    }
   ],
   "source": [
    "\n",
    "from jaxns import Prior, Model\n",
    "\n",
    "\n",
    "def log_likelihood(theta):\n",
    "    return 0.\n",
    "\n",
    "\n",
    "def prior_model():\n",
    "    x = yield Prior(tfpd.Uniform(0., 1.), name='x')\n",
    "    return x\n",
    "\n",
    "\n",
    "model = Model(prior_model=prior_model,\n",
    "              log_likelihood=log_likelihood)\n",
    "\n",
    "log_Z_true = 0.\n",
    "print(f\"True log(Z)={log_Z_true}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-23T21:20:50.859905Z",
     "iopub.status.busy": "2024-09-23T21:20:50.859521Z",
     "iopub.status.idle": "2024-09-23T21:20:56.849652Z",
     "shell.execute_reply": "2024-09-23T21:20:56.849070Z"
    },
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/albert/miniconda3/envs/jaxns_py/lib/python3.11/site-packages/jaxns/internals/mixed_precision.py:61: UserWarning: Expected integer type, got bool, at public.py:173 in to_results -> sharded_static.py:475 in _to_results -> mixed_precision.py:105 in cast_to_count -> mixed_precision.py:67 in _cast_integer_to -> tree.py:61 in map -> tree_util.py:321 in tree_map -> tree_util.py:321 in <genexpr> -> mixed_precision.py:61 in conditional_cast.\n",
      "  warnings.warn(f\"Expected integer type, got {x.dtype}, {get_grandparent_info()}.\")\n"
     ]
    }
   ],
   "source": [
    "from jaxns import NestedSampler\n",
    "\n",
    "# Create the nested sampler class. In this case without any tuning.\n",
    "exact_ns = NestedSampler(model=model, max_samples=1e4)\n",
    "\n",
    "termination_reason, state = exact_ns(random.PRNGKey(42))\n",
    "results = exact_ns.to_results(termination_reason=termination_reason, state=state)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-23T21:20:56.852297Z",
     "iopub.status.busy": "2024-09-23T21:20:56.851883Z",
     "iopub.status.idle": "2024-09-23T21:20:57.459569Z",
     "shell.execute_reply": "2024-09-23T21:20:57.458738Z"
    },
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------\n",
      "Termination Conditions:\n",
      "All live-points are on a single plateau (potential numerical errors, consider 64-bit)\n",
      "--------\n",
      "likelihood evals: 30\n",
      "samples: 45\n",
      "phantom samples: 0\n",
      "likelihood evals / sample: 0.7\n",
      "phantom fraction (%): 0.0%\n",
      "--------\n",
      "logZ=-0.034 +- 0.023\n",
      "max(logL)=0.0\n",
      "H=-0.03\n",
      "ESS=20\n",
      "--------\n",
      "x: mean +- std.dev. | 10%ile / 50%ile / 90%ile | MAP est. | max(L) est.\n",
      "x: 0.51 +- 0.3 | 0.13 / 0.47 / 0.96 | 0.5 | 0.5\n",
      "--------\n"
     ]
    }
   ],
   "source": [
    "# We can use the summary utility to display results\n",
    "exact_ns.summary(results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-23T21:20:57.462897Z",
     "iopub.status.busy": "2024-09-23T21:20:57.462327Z",
     "iopub.status.idle": "2024-09-23T21:20:59.060012Z",
     "shell.execute_reply": "2024-09-23T21:20:59.059383Z"
    },
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/albert/miniconda3/envs/jaxns_py/lib/python3.11/site-packages/jaxns/plotting.py:48: 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:52: RuntimeWarning: divide by zero encountered in divide\n",
      "  1. / num_likelihood_evaluations_per_sample\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x1200 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# We plot useful diagnostics and a distribution cornerplot\n",
    "exact_ns.plot_diagnostics(results)\n",
    "exact_ns.plot_cornerplot(results)"
   ]
  }
 ],
 "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
}