{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", " \n", "
\n", "\n", "# Ctypes Example\n", "Author(s): Paul Miles, Joel Kulesza | Date Created: June 28, 2018\n", "\n", "In this example, we demonstrate how to use a model written in C++ within the context of using [pymcmcstat](https://github.com/prmiles/pymcmcstat/wiki). In this case we consider a linear model.\n", "\n", "$$y(x;q) = m x + b + \\epsilon, \\quad \\epsilon\\sim N(0,\\sigma^2), \\quad q = [m, b]$$\n", "\n", "but note that the model can be arbitrarily complex. Similar work can be performed with Fortran using the `iso_c_binding` module." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'divide': 'warn', 'over': 'warn', 'under': 'ignore', 'invalid': 'warn'}" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import numpy as np\n", "from pymcmcstat.MCMC import MCMC\n", "import matplotlib.pyplot as plt\n", "import ctypes\n", "from numpy.ctypeslib import ndpointer\n", "np.seterr(over='ignore')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Define data set\n", "To define our data set, we generate a set of points along the line, $y = 2x - 3$, and add some random noise to the response. We have plotted the data with and without the random noise added to it." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Define data set\n", "nds = 100\n", "x = np.linspace(2, 3, num=nds)\n", "x = x.reshape(nds, 1)\n", "m = 2 # slope\n", "b = -3 # offset\n", "noise = 0.1*np.random.standard_normal(x.shape)\n", "y = m*x + b + noise\n", "\n", "# plot data\n", "plt.figure(dpi=100, figsize=(4, 4))\n", "plt.plot(x, y, '.k', label='With noise');\n", "plt.plot(x, m*x + b, '-r', label='Without noise');\n", "plt.legend();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Define C++ Model\n", "We define our C++ model in the file `linear_model.cpp`.\n", "```cpp\n", "#include \n", "#include \n", "\n", "extern \"C\" {\n", " double* linear_model(float slope, float offset, double *x, int nx) {\n", " double* y = new double[nx];\n", " for (int ii = 0; ii < nx; ii++) {\n", " y[ii] = slope*x[ii] + offset;\n", " }\n", " return y;\n", " }\n", "}```\n", "You must compile the code in your terminal in order to generate an object to be called within Python. In this case, we output the compiled program to `linear_model.so`.\n", "```bash\n", "g++ -fPIC -shared -o linear_model.so linear_model.cpp\n", "```\n", "Note that `.so` is a common Linux convention for \"shared object\". On macOS this might be referred to as a dynamic library (`.dylib`) and on Windows this is usually called a dynamic-link library (`.dll`). Such objects can be inspected with the `nm` command on the macOS or Linux command line.\n", "\n", "Within our Python script, we now utilize the `ctypes` package to make the C++ program callable within our routine. The compiled library is loaded, and the `linear_model` is assigned to the variable `cpplm`. The `restype` tells Python what type of variable to expect from the C++ code, and the `artypes` tells Python what data types to send to the C++ code. For more details, see the `ctypes` documentation: https://docs.python.org/3/library/ctypes.html" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "lib = ctypes.cdll.LoadLibrary('./linear_model.so')\n", "cpplm = lib.linear_model\n", "cpplm.restype = ndpointer(dtype = ctypes.c_double, shape=(nds,))\n", "cpplm.argtypes = [ctypes.c_float, ctypes.c_float, ndpointer(ctypes.c_double), ctypes.c_int]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Define Sum-of-Squares Function\n", "At this point we can define our sum-of-squares function and access the C++ code for model evaluation. Note, the C++ model is inputted to the function by including it in the `user_defined_object` of the `data` structure." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "def test_ssfun(theta, data):\n", " xdata = data.xdata[0]\n", " ydata = data.ydata[0]\n", " linear_model = data.user_defined_object[0]\n", " nx = len(xdata)\n", " # eval model c++ model\n", " ymodel = linear_model(theta[0], theta[1], xdata, nx)\n", " # calc sos\n", " ss = sum((ymodel[:] - ydata[:, 0])**2)\n", " return ss" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Setup MCMC Simulation\n", "We can now setup our MCMC simulation as we would for any other problem. Note, the C++ model has been added to the `data` structure." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Sampling these parameters:\n", " name start [ min, max] N( mu, sigma^2)\n", " m: 1.70 [ -10.00, 10.00] N( 0.00e+00, inf)\n", " b: 2.50 [ -10.00, 100.00] N( 0.00e+00, inf)\n", " [-----------------100%-----------------] 10000 of 10000 complete in 4.1 sec" ] } ], "source": [ "# Initialize MCMC object\n", "mcstat = MCMC()\n", "# Add data\n", "mcstat.data.add_data_set(x, y, user_defined_object=cpplm)\n", "# initialize parameter array\n", "mcstat.parameters.add_model_parameter(\n", " name='m',\n", " theta0=1.7,\n", " minimum=-10,\n", " maximum=10)\n", "mcstat.parameters.add_model_parameter(\n", " name='b',\n", " theta0=2.5,\n", " minimum=-10,\n", " maximum=100)\n", "# update simulation options\n", "mcstat.simulation_options.define_simulation_options(\n", " nsimu=int(10.0e3),\n", " updatesigma=True,\n", " method='dram',\n", " adaptint=100,\n", " verbosity=1,\n", " waitbar=True)\n", "# update model settings\n", "mcstat.model_settings.define_model_settings(sos_function=test_ssfun)\n", "# Run mcmcrun\n", "mcstat.run_simulation()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Extract Results and Display Chain Statistics/Plots\n", "We take the results of the MCMC simulation, remove the first half of the chain to account for burnin, and perform our analysis on the remaining part of the chain.\n", "\n", "Plots:\n", "- Marginal posterior densities\n", "- Sampling chains\n", "- Pairwise correlation" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "---------------------\n", "name : mean std MC_err tau geweke\n", "m : 1.9350 0.0335 0.0027 26.4498 0.9978\n", "b : -2.8400 0.0845 0.0068 25.5539 0.9960\n", "---------------------\n" ] }, { "data": { "image/png": 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\n", 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\n", 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Extract results\n", "results = mcstat.simulation_results.results\n", "chain = results['chain']\n", "s2chain = results['s2chain']\n", "sschain = results['sschain']\n", "names = results['names']\n", "# define burnin\n", "burnin = int(results['nsimu']/2)\n", "# display chain statistics\n", "mcstat.chainstats(chain[burnin:,:], results)\n", "# generate mcmc plots\n", "mcpl = mcstat.mcmcplot # initialize plotting methods\n", "mcpl.plot_density_panel(chain[burnin:, :], names,\n", " figsizeinches=(4, 4))\n", "mcpl.plot_chain_panel(chain[burnin:, :], names,\n", " figsizeinches=(4, 4))\n", "mcpl.plot_pairwise_correlation_panel(chain[burnin:, :], names,\n", " figsizeinches=(4, 4));" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Generate/Plot Prediction Intervals\n", "The C++ model can also be used in generating credible/prediction intervals." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Generating credible/prediction intervals:\n", "\n", "\n", "Interval generation complete\n", "\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# generate prediction intervals\n", "def pred_modelfun(preddata, theta):\n", " return cpplm(theta[0], theta[1], preddata.xdata[0], nds)\n", "mcstat.PI.setup_prediction_interval_calculation(\n", " results=results,\n", " data=mcstat.data,\n", " modelfunction=pred_modelfun)\n", "mcstat.PI.generate_prediction_intervals()\n", "mcstat.PI.plot_prediction_intervals(adddata=True, figsizeinches=(6, 6));" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.6.8" }, "latex_envs": { "LaTeX_envs_menu_present": true, "autoclose": false, "autocomplete": true, "bibliofile": "biblio.bib", "cite_by": "apalike", "current_citInitial": 1, "eqLabelWithNumbers": true, "eqNumInitial": 1, "hotkeys": { "equation": "Ctrl-E", "itemize": "Ctrl-I" }, "labels_anchors": false, "latex_user_defs": false, "report_style_numbering": true, "user_envs_cfg": false }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": true } }, "nbformat": 4, "nbformat_minor": 2 }