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  {
   "cell_type": "markdown",
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   "source": [
    "# Simple Examples\n",
    "\n",
    "These examples show some basic functions of PySwarming, like target, aggregation, and repulsion.\n",
    "\n",
    "For more examples, you can see the [notebooks](https://github.com/mrsonandrade/pyswarming/tree/main/notebooks) and [examples](https://github.com/mrsonandrade/pyswarming/tree/main/examples) directories of PySwarming."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Target behavior"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "051ef3c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "# importing the swarm creator\n",
    "import pyswarming.swarm as ps\n",
    "\n",
    "# creating the swarm\n",
    "my_swarm = ps.Swarm(n = 10, # number of robots\n",
    "                    linear_speed = 0.5, # linear speed of each robot\n",
    "                    dT = 1.0, # sampling time\n",
    "                    deployment_point_limits = [[0.0, 0.0, 0.0], [5.0, 5.0, 0.0]], # lower and upper limits for the position deployment\n",
    "                    deployment_orientation_limits = [[0.0, 0.0, 0.0], [0.0, 0.0, 2*3.1415]], # lower and upper limits for the orientation deployment\n",
    "                    distribution_type =  'uniform', # type of distribution used to deploy the robots\n",
    "                    plot_limits = [[-50.0, 50.0], [-50.0, 50.0]], # plot limits x_lim, y_lim\n",
    "                    behaviors = ['target']) # list of behaviors\n",
    "my_swarm.behaviors_dict['r_out']['target']['T'] = [-40, -40, 0] # setting the target position [x, y, z]\n",
    "anim = my_swarm.simulate(mode='anim')\n",
    "\n",
    "from IPython.display import HTML\n",
    "HTML(anim.to_jshtml())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35bcb062",
   "metadata": {},
   "source": [
    "## Aggregation behavior"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "32e10bb6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# importing the swarm creator\n",
    "import pyswarming.swarm as ps\n",
    "\n",
    "# creating the swarm\n",
    "my_swarm = ps.Swarm(n = 10, # number of robots\n",
    "                    linear_speed = 0.5, # linear speed of each robot\n",
    "                    dT = 1.0, # sampling time\n",
    "                    deployment_point_limits = [[-40.0, -40.0, 0.0], [40.0, 40.0, 0.0]], # lower and upper limits for the position deployment\n",
    "                    deployment_orientation_limits = [[0.0, 0.0, 0.0], [0.0, 0.0, 2*3.1415]], # lower and upper limits for the orientation deployment\n",
    "                    distribution_type =  'uniform', # type of distribution used to deploy the robots\n",
    "                    plot_limits = [[-50.0, 50.0], [-50.0, 50.0]], # plot limits x_lim, y_lim\n",
    "                    behaviors = ['aggregation']) # list of behaviors\n",
    "anim = my_swarm.simulate(mode='anim')\n",
    "\n",
    "from IPython.display import HTML\n",
    "HTML(anim.to_jshtml())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d6c573c",
   "metadata": {},
   "source": [
    "## Repulsion behavior"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "014abcee",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "# importing the swarm creator\n",
    "import pyswarming.swarm as ps\n",
    "\n",
    "# creating the swarm\n",
    "my_swarm = ps.Swarm(n = 10, # number of robots\n",
    "                    linear_speed = 0.5, # linear speed of each robot\n",
    "                    dT = 1.0, # sampling time\n",
    "                    deployment_point_limits = [[0.0, 0.0, 0.0], [5.0, 5.0, 0.0]], # lower and upper limits for the position deployment\n",
    "                    deployment_orientation_limits = [[0.0, 0.0, 0.0], [0.0, 0.0, 2*3.1415]], # lower and upper limits for the orientation deployment\n",
    "                    distribution_type =  'uniform', # type of distribution used to deploy the robots\n",
    "                    plot_limits = [[-50.0, 50.0], [-50.0, 50.0]], # plot limits x_lim, y_lim\n",
    "                    behaviors = ['repulsion']) # list of behaviors\n",
    "anim = my_swarm.simulate(mode='anim')\n",
    "\n",
    "from IPython.display import HTML\n",
    "HTML(anim.to_jshtml())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50eca133",
   "metadata": {},
   "source": [
    "## Aggregation + Repulsion + Target behaviors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "983c7cd3",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "# importing the swarm creator\n",
    "import pyswarming.swarm as ps\n",
    "\n",
    "# creating the swarm\n",
    "my_swarm = ps.Swarm(n = 10, # number of robots\n",
    "                    linear_speed = 0.5, # linear speed of each robot\n",
    "                    dT = 1.0, # sampling time\n",
    "                    deployment_point_limits = [[0.0, 0.0, 0.0], [5.0, 5.0, 0.0]], # lower and upper limits for the position deployment\n",
    "                    deployment_orientation_limits = [[0.0, 0.0, 0.0], [0.0, 0.0, 2*3.1415]], # lower and upper limits for the orientation deployment\n",
    "                    distribution_type =  'uniform', # type of distribution used to deploy the robots\n",
    "                    plot_limits = [[-50.0, 50.0], [-50.0, 50.0]], # plot limits x_lim, y_lim\n",
    "                    behaviors = ['aggregation', 'repulsion', 'target']) # list of behaviors\n",
    "my_swarm.behaviors_dict['r_out']['target']['T'] = [-20, -20, 0] # setting the target position [x, y, z]\n",
    "anim = my_swarm.simulate(mode='anim')\n",
    "\n",
    "from IPython.display import HTML\n",
    "HTML(anim.to_jshtml())"
   ]
  }
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