Fix incompatibility with MyBinder in notebooks

models/exercise/plot_two_strain_bd.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["#################################################################\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t   #<br>\n", "Basic plot for two-strain SIR model:<br>\n", "Bifurcation diagram for one parameter<br>\n", "##################################################################"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["import sys\n", "import numpy as np\n", "import matplotlib as mpl\n", "mpl.use('TkAgg')\n", "from matplotlib.font_manager import FontProperties \n", "import matplotlib.pyplot as plt\n", "from two_strain import *"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Run parameters"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["run_num = 1  # sys.argv[1]\n", "end_time = 1000*365\n", "output_interval = 365.0  # if not 365., need to adjust strobe interval\n", "step_size = 1.0\n", "sweep_par = \"beta[0]\"  # e.g., \"beta[0]\", \"a[1]\", \"alpha[0]\"\n", "par_min = 1.0/7.0\n", "par_max = 7.0/7.0\n", "n_points = 40  # number of points in parameter range\n", "n_strobes = 50  # number of years to sample"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Strain parameters, including initial conditions"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["beta = np.array([5, 5])/7.0\n", "epsilon = 0.1\n", "gamma = np.array([1, 1])/7.0\n", "mu = 1/(10*365.0)\n", "alpha = np.array([1., 1.])\n", "a = np.array([1., 1.])\n", "omega = 2*np.pi/365.\n", "obs_sd = 0.01"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["NSS = 0.2\n", "NIS = 1e-3\n", "NRS = 0.02\n", "NRI = 0.0\n", "NSI = 1e-3\n", "NSR = 0.02\n", "NIR = 0.0"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Organize and run simulations"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["SI = np.array([NSS, NIS, NRS, NRI, NSI, NSR, NIR], dtype=\"object\")\n", "ic = np.array([NSS, NIS, NRS, NRI, NSI, NSR, NIR, 1-np.sum(SI)], dtype=\"object\")\n", "par_vals = np.linspace(par_min, par_max, n_points)\n", "bif_vals = np.zeros((len(par_vals), n_strobes))\n", "for i in range(len(par_vals)):\n", "    print('Running value %d of %d' % (i+1,len(par_vals)))\n", "    exec(sweep_par + \" = par_vals[i]\")\n", "    params = np.array([gamma, mu, alpha, a, omega, beta, epsilon], dtype=\"object\")\n", "    output = run_two_strain(end_time, output_interval, step_size, params, ic)\n", "    I = output[:, 1] + output[:, 6]  # NIS + NIR\n", "    bif_vals[i, :] = I[-n_strobes:len(I)]"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Plot output"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["plt.plot(par_vals, bif_vals, '.k')\n", "plt.xlabel(sweep_par)\n", "plt.ylabel(\"NIS + NIR\")\n", "plt.xlim([par_min, par_max])\n", "plt.show()\n", "plt.savefig(\"bifurcation_\" + sweep_par + \".png\")\n", "plt.close()"]}], "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": "3.6.4"}}, "nbformat": 4, "nbformat_minor": 2}
+{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["#################################################################\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t   #<br>\n", "Basic plot for two-strain SIR model:<br>\n", "Bifurcation diagram for one parameter<br>\n", "##################################################################"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["import sys\n", "import numpy as np\n", "import matplotlib as mpl\n", "from matplotlib.font_manager import FontProperties \n", "import matplotlib.pyplot as plt\n", "from two_strain import *"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Run parameters"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["run_num = 1  # sys.argv[1]\n", "end_time = 1000*365\n", "output_interval = 365.0  # if not 365., need to adjust strobe interval\n", "step_size = 1.0\n", "sweep_par = \"beta[0]\"  # e.g., \"beta[0]\", \"a[1]\", \"alpha[0]\"\n", "par_min = 1.0/7.0\n", "par_max = 7.0/7.0\n", "n_points = 40  # number of points in parameter range\n", "n_strobes = 50  # number of years to sample"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Strain parameters, including initial conditions"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["beta = np.array([5, 5])/7.0\n", "epsilon = 0.1\n", "gamma = np.array([1, 1])/7.0\n", "mu = 1/(10*365.0)\n", "alpha = np.array([1., 1.])\n", "a = np.array([1., 1.])\n", "omega = 2*np.pi/365.\n", "obs_sd = 0.01"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["NSS = 0.2\n", "NIS = 1e-3\n", "NRS = 0.02\n", "NRI = 0.0\n", "NSI = 1e-3\n", "NSR = 0.02\n", "NIR = 0.0"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Organize and run simulations"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["SI = np.array([NSS, NIS, NRS, NRI, NSI, NSR, NIR], dtype=\"object\")\n", "ic = np.array([NSS, NIS, NRS, NRI, NSI, NSR, NIR, 1-np.sum(SI)], dtype=\"object\")\n", "par_vals = np.linspace(par_min, par_max, n_points)\n", "bif_vals = np.zeros((len(par_vals), n_strobes))\n", "for i in range(len(par_vals)):\n", "    print('Running value %d of %d' % (i+1,len(par_vals)))\n", "    exec(sweep_par + \" = par_vals[i]\")\n", "    params = np.array([gamma, mu, alpha, a, omega, beta, epsilon], dtype=\"object\")\n", "    output = run_two_strain(end_time, output_interval, step_size, params, ic)\n", "    I = output[:, 1] + output[:, 6]  # NIS + NIR\n", "    bif_vals[i, :] = I[-n_strobes:len(I)]"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Plot output"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["plt.plot(par_vals, bif_vals, '.k')\n", "plt.xlabel(sweep_par)\n", "plt.ylabel(\"NIS + NIR\")\n", "plt.xlim([par_min, par_max])\n", "plt.show()\n", "plt.savefig(\"bifurcation_\" + sweep_par + \".png\")\n", "plt.close()"]}], "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": "3.6.4"}}, "nbformat": 4, "nbformat_minor": 2}

models/exercise/plot_two_strain_ts.ipynb

@@ -20,7 +20,6 @@
     "import csv\n",
     "import numpy as np\n",
     "import matplotlib as mpl\n",
-    "mpl.use('TkAgg')\n",
     "from matplotlib.font_manager import FontProperties \n",
     "import matplotlib.pyplot as plt\n",
     "from two_strain import *"