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    "# Creating (random) inter-trial intervals\n",
    "Inter-trial intervals (ITIs) are often of random duration to avoid e.g. habituation effects or to reset induced entrainment.\n",
    "\n",
    "Here we show how to create concatenated trials with random inter-trial intervals between them."
   ]
  },
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   "source": [
    "---"
   ]
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   "source": [
    "We start by importing the :py:class:`~thebeat.core.Sequence` class from *thebeat*. In addition we import *NumPy*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "636a2c03-5374-4d65-ae42-a09e719053a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "from thebeat import Sequence\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b12160c8-825f-4839-8081-54afe84c63a0",
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    "nbsphinx": "hidden",
    "tags": []
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   "source": [
    "# We suppress warnings, but let's hide that to avoid confusion\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "raw",
   "id": "b4c3ae9a-2a54-480c-ba82-f96b494c773a",
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   "source": [
    "When we have a :py:class:`~thebeat.core.Sequence` object, we can simply add a number to it which will be the ITI, like so:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "930395e3-9103-496f-b98e-6c4d9c402b3b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Object of type Sequence (ends with event)\n",
      "10 events\n",
      "IOIs: [500. 500. 500. 500. 777. 300. 300. 300. 300.]\n",
      "Onsets: [   0.  500. 1000. 1500. 2000. 2777. 3077. 3377. 3677. 3977.]\n",
      "Sequence name: Not provided\n",
      "\n"
     ]
    }
   ],
   "source": [
    "seq1 = Sequence.generate_isochronous(n_events=5, ioi=500)\n",
    "seq2 = Sequence.generate_isochronous(n_events=5, ioi=300)\n",
    "\n",
    "long_seq = seq1 + 777 + seq2  # Concatenate a Sequence with an ITI with a Sequence\n",
    "print(long_seq)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1879089-2c95-41b2-b1bb-48a3918be516",
   "metadata": {},
   "source": [
    "---"
   ]
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   "id": "e109b81f-9bc8-468a-af39-969313d8b458",
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   "source": [
    "If we want to have a random number there, we can use one of *NumPy*'s functions for generating one. For more info on *NumPy* random number generators, see [here](https://numpy.org/doc/stable/reference/random/generator.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2c3ecabc-c5e0-41ee-a958-1be76b2f1ddf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Object of type Sequence (ends with event)\n",
      "10 events\n",
      "IOIs: [500. 500. 500. 500. 873. 300. 300. 300. 300.]\n",
      "Onsets: [   0.  500. 1000. 1500. 2000. 2873. 3173. 3473. 3773. 4073.]\n",
      "Sequence name: Not provided\n",
      "\n"
     ]
    }
   ],
   "source": [
    "random_iti = np.random.default_rng().integers(low=200, high=1000)\n",
    "\n",
    "long_seq = seq1 + random_iti + seq2\n",
    "print(long_seq)"
   ]
  }
 ],
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