diff --git a/python/examples/ipython/interface_usage.ipynb b/python/examples/ipython/interface_usage.ipynb
index e70f0871b..e716db7a9 100644
--- a/python/examples/ipython/interface_usage.ipynb
+++ b/python/examples/ipython/interface_usage.ipynb
@@ -1,515 +1,517 @@
 {
  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "# Using LAMMPS with iPython and Jupyter"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "LAMMPS can be run interactively using iPython easily. This tutorial shows how to set this up."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Installation"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "1. Download the latest version of LAMMPS into a folder (we will calls this `$LAMMPS_DIR` from now on)\n",
-    "2. Compile LAMMPS as a shared library and enable PNG support\n",
+    "2. Compile LAMMPS as a shared library and enable exceptions and PNG support\n",
     "   ```bash\n",
     "   cd $LAMMPS_DIR/src\n",
-    "   python2 Make.py -m mpi -png -a file\n",
+    "   python Make.py -m mpi -png -s exceptions -a file\n",
     "   make mode=shlib auto\n",
     "   ```\n",
     "\n",
     "3. Create a python virtualenv\n",
     "   ```bash\n",
     "   virtualenv testing\n",
     "   source testing/bin/activate\n",
     "   ```\n",
     "\n",
     "4. Inside the virtualenv install the lammps package\n",
     "   ```\n",
     "   (testing) cd $LAMMPS_DIR/python\n",
     "   (testing) python install.py\n",
     "   (testing) cd   # move to your working directory\n",
     "   ```\n",
     "\n",
     "5. Install jupyter and ipython in the virtualenv\n",
     "   ```bash\n",
     "   (testing) pip install ipython jupyter\n",
     "   ```\n",
     "\n",
     "6. Run jupyter notebook\n",
     "   ```bash\n",
     "   (testing) jupyter notebook\n",
     "   ```"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Example"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "from lammps import IPyLammps"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L = IPyLammps()"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "# 3d Lennard-Jones melt\n",
     "\n",
     "L.units(\"lj\")\n",
     "L.atom_style(\"atomic\")\n",
     "L.atom_modify(\"map array\")\n",
     "\n",
     "L.lattice(\"fcc\", 0.8442)\n",
     "L.region(\"box block\", 0, 4, 0, 4, 0, 4)\n",
     "L.create_box(1, \"box\")\n",
     "L.create_atoms(1, \"box\")\n",
     "L.mass(1, 1.0)\n",
     "\n",
     "L.velocity(\"all create\", 1.44, 87287, \"loop geom\")\n",
     "\n",
     "L.pair_style(\"lj/cut\", 2.5)\n",
     "L.pair_coeff(1, 1, 1.0, 1.0, 2.5)\n",
     "\n",
     "L.neighbor(0.3, \"bin\")\n",
     "L.neigh_modify(\"delay 0 every 20 check no\")\n",
     "\n",
     "L.fix(\"1 all nve\")\n",
     "\n",
     "L.variable(\"fx atom fx\")\n",
     "\n",
     "L.run(10)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.image(zoom=1)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Queries about LAMMPS simulation"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.system"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.system.natoms"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.communication"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.fixes"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.computes"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.dumps"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.groups"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Working with LAMMPS Variables"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.variable(\"a index 2\")"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.variables"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.variable(\"t equal temp\")"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.variables"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "import sys\n",
     "\n",
     "if sys.version_info < (3, 0):\n",
     "    # In Python 2 'print' is a restricted keyword, which is why you have to use the lmp_print function instead.\n",
     "    x = float(L.lmp_print('\"${a}\"'))\n",
     "else:\n",
     "    # In Python 3 the print function can be redefined.\n",
     "    # x = float(L.print('\"${a}\"')\")\n",
     "    \n",
     "    # To avoid a syntax error in Python 2 executions of this notebook, this line is packed into an eval statement\n",
     "    x = float(eval(\"L.print('\\\"${a}\\\"')\"))\n",
     "x"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.variables['t'].value"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.eval(\"v_t/2.0\")"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.variable(\"b index a b c\")"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.variables['b'].value"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.eval(\"v_b\")"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.variables['b'].definition"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.variable(\"i loop 10\")"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.variables['i'].value"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.next(\"i\")\n",
     "L.variables['i'].value"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.eval(\"ke\")"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Accessing Atom data"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.atoms[0]"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "[x for x in dir(L.atoms[0]) if not x.startswith('__')]"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.atoms[0].position"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.atoms[0].id"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.atoms[0].velocity"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.atoms[0].force"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.atoms[0].type"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
+   "outputs": [],
    "source": [
     "L.variables['fx'].value"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Accessing thermo data"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.runs"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.runs[0]"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.runs[0].thermo"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.runs[0].thermo.Temp"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Saving session to as LAMMPS input file"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.write_script(\"in.output\")"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": []
   }
  ],
  "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"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 0
 }
diff --git a/python/examples/ipython/interface_usage_bonds.ipynb b/python/examples/ipython/interface_usage_bonds.ipynb
index d34b992b8..f6a4adcb3 100644
--- a/python/examples/ipython/interface_usage_bonds.ipynb
+++ b/python/examples/ipython/interface_usage_bonds.ipynb
@@ -1,498 +1,498 @@
 {
  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "# Using LAMMPS with iPython and Jupyter"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "LAMMPS can be run interactively using iPython easily. This tutorial shows how to set this up."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Installation"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "1. Download the latest version of LAMMPS into a folder (we will calls this `$LAMMPS_DIR` from now on)\n",
-    "2. Compile LAMMPS as a shared library and enable PNG support\n",
+    "2. Compile LAMMPS as a shared library and enable exceptions and PNG support\n",
     "   ```bash\n",
     "   cd $LAMMPS_DIR/src\n",
     "   make yes-molecule\n",
-    "   python2 Make.py -m mpi -png -a file\n",
+    "   python Make.py -m mpi -png -s exceptions -a file\n",
     "   make mode=shlib auto\n",
     "   ```\n",
     "\n",
     "3. Create a python virtualenv\n",
     "   ```bash\n",
     "   virtualenv testing\n",
     "   source testing/bin/activate\n",
     "   ```\n",
     "\n",
     "4. Inside the virtualenv install the lammps package\n",
     "   ```\n",
     "   (testing) cd $LAMMPS_DIR/python\n",
     "   (testing) python install.py\n",
     "   (testing) cd   # move to your working directory\n",
     "   ```\n",
     "\n",
     "5. Install jupyter and ipython in the virtualenv\n",
     "   ```bash\n",
     "   (testing) pip install ipython jupyter\n",
     "   ```\n",
     "\n",
     "6. Run jupyter notebook\n",
     "   ```bash\n",
     "   (testing) jupyter notebook\n",
     "   ```"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Example"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "from lammps import IPyLammps"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L = IPyLammps()"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "# 2d circle of particles inside a box with LJ walls\n",
     "import math\n",
     "\n",
     "b = 0\n",
     "x = 50\n",
     "y = 20\n",
     "d = 20\n",
     "\n",
     "# careful not to slam into wall too hard\n",
     "\n",
     "v = 0.3\n",
     "w = 0.08\n",
     "                \n",
     "L.units(\"lj\")\n",
     "L.dimension(2)\n",
     "L.atom_style(\"bond\")\n",
     "L.boundary(\"f f p\")\n",
     "\n",
     "L.lattice(\"hex\", 0.85)\n",
     "L.region(\"box\", \"block\", 0, x, 0, y, -0.5, 0.5)\n",
     "L.create_box(1, \"box\", \"bond/types\", 1, \"extra/bond/per/atom\", 6)\n",
     "L.region(\"circle\", \"sphere\", d/2.0+1.0, d/2.0/math.sqrt(3.0)+1, 0.0, d/2.0)\n",
     "L.create_atoms(1, \"region\", \"circle\")\n",
     "L.mass(1, 1.0)\n",
     "\n",
     "L.velocity(\"all create 0.5 87287 loop geom\")\n",
     "L.velocity(\"all set\", v, w, 0, \"sum yes\")\n",
     "\n",
     "L.pair_style(\"lj/cut\", 2.5)\n",
     "L.pair_coeff(1, 1, 10.0, 1.0, 2.5)\n",
     "\n",
     "L.bond_style(\"harmonic\")\n",
     "L.bond_coeff(1, 10.0, 1.2)\n",
     "\n",
     "L.create_bonds(\"all\", \"all\", 1, 1.0, 1.5)\n",
     "\n",
     "L.neighbor(0.3, \"bin\")\n",
     "L.neigh_modify(\"delay\", 0, \"every\", 1, \"check yes\")\n",
     "\n",
     "L.fix(1, \"all\", \"nve\")\n",
     "\n",
     "L.fix(2, \"all wall/lj93 xlo 0.0 1 1 2.5 xhi\", x, \"1 1 2.5\")\n",
     "L.fix(3, \"all wall/lj93 ylo 0.0 1 1 2.5 yhi\", y, \"1 1 2.5\")"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.image(zoom=1.8)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.thermo_style(\"custom step temp epair press\")\n",
     "L.thermo(100)\n",
     "output = L.run(40000)\n",
     "L.image(zoom=1.8)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Queries about LAMMPS simulation"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.system"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.system.natoms"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.system.nbonds"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.system.nbondtypes"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.communication"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.fixes"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.computes"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.dumps"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.groups"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Working with LAMMPS Variables"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.variable(\"a index 2\")"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.variables"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.variable(\"t equal temp\")"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.variables"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "import sys\n",
     "\n",
     "if sys.version_info < (3, 0):\n",
     "    # In Python 2 'print' is a restricted keyword, which is why you have to use the lmp_print function instead.\n",
     "    x = float(L.lmp_print('\"${a}\"'))\n",
     "else:\n",
     "    # In Python 3 the print function can be redefined.\n",
     "    # x = float(L.print('\"${a}\"')\")\n",
     "    \n",
     "    # To avoid a syntax error in Python 2 executions of this notebook, this line is packed into an eval statement\n",
     "    x = float(eval(\"L.print('\\\"${a}\\\"')\"))\n",
     "x"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.variables['t'].value"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.eval(\"v_t/2.0\")"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.variable(\"b index a b c\")"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.variables['b'].value"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.eval(\"v_b\")"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.variables['b'].definition"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.variable(\"i loop 10\")"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.variables['i'].value"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.next(\"i\")\n",
     "L.variables['i'].value"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.eval(\"ke\")"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Accessing Atom data"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.atoms[0]"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "[x for x in dir(L.atoms[0]) if not x.startswith('__')]"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.atoms[0].position"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.atoms[0].id"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.atoms[0].velocity"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.atoms[0].force"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.atoms[0].type"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": []
   }
  ],
  "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"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 0
 }
diff --git a/python/examples/ipython/simple.ipynb b/python/examples/ipython/simple.ipynb
index 0a585629d..838288432 100644
--- a/python/examples/ipython/simple.ipynb
+++ b/python/examples/ipython/simple.ipynb
@@ -1,152 +1,152 @@
 {
  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "# Using LAMMPS with iPython and Jupyter"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "LAMMPS can be run interactively using iPython easily. This tutorial shows how to set this up."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Installation"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "1. Download the latest version of LAMMPS into a folder (we will calls this `$LAMMPS_DIR` from now on)\n",
-    "2. Compile LAMMPS as a shared library and enable PNG support\n",
+    "2. Compile LAMMPS as a shared library and enable exceptions and PNG support\n",
     "   ```bash\n",
     "   cd $LAMMPS_DIR/src\n",
-    "   python2 Make.py -m mpi -png -a file\n",
+    "   python Make.py -m mpi -png -s exceptions -a file\n",
     "   make mode=shlib auto\n",
     "   ```\n",
     "\n",
     "3. Create a python virtualenv\n",
     "   ```bash\n",
     "   virtualenv testing\n",
     "   source testing/bin/activate\n",
     "   ```\n",
     "\n",
     "4. Inside the virtualenv install the lammps package\n",
     "   ```\n",
     "   (testing) cd $LAMMPS_DIR/python\n",
     "   (testing) python install.py\n",
     "   (testing) cd   # move to your working directory\n",
     "   ```\n",
     "\n",
     "5. Install jupyter and ipython in the virtualenv\n",
     "   ```bash\n",
     "   (testing) pip install ipython jupyter\n",
     "   ```\n",
     "\n",
     "6. Run jupyter notebook\n",
     "   ```bash\n",
     "   (testing) jupyter notebook\n",
     "   ```"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Example"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "from lammps import IPyLammps"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L = IPyLammps()"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "import math\n",
     "\n",
     "# 3d Lennard-Jones melt\n",
     "\n",
     "L.units(\"lj\")\n",
     "L.atom_style(\"atomic\")\n",
     "L.atom_modify(\"map array\")\n",
     "\n",
     "L.lattice(\"fcc\", 0.8442)\n",
     "L.region(\"box\", \"block\", 0, 4, 0, 4, 0, 4)\n",
     "L.create_box(1, \"box\")\n",
     "L.create_atoms(1, \"box\")\n",
     "L.mass(1, 1.0)\n",
     "\n",
     "L.velocity(\"all\", \"create\", 1.44, 87287, \"loop geom\")\n",
     "\n",
     "L.pair_style(\"lj/cut\", 2.5)\n",
     "L.pair_coeff(1, 1, 1.0, 1.0, 2.5)\n",
     "\n",
     "L.neighbor(0.3, \"bin\")\n",
     "L.neigh_modify(\"delay\", 0, \"every\", 20, \"check no\")\n",
     "\n",
     "L.fix(\"1 all nve\")\n",
     "\n",
     "L.variable(\"fx atom fx\")\n",
     "\n",
     "L.info(\"all\")\n",
     "\n",
     "L.run(10)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "L.image(zoom=1.0)"
    ]
   }
  ],
  "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"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 0
 }