notebooks/demo_1d_data.ipynb

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   "source": [
    "# Demo 1D data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "import numpy as np\n",
    "from pyflint.pyflint import FlintSignal, Flint"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For this example we will use 1d data from a T2 experiment."
   ]
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   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_file = np.loadtxt(Path('./example_data') / \"T2decay.dat\")\n",
    "time_axis = data_file[:,0]\n",
    "signal_decay = data_file[:,1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Perform ILT"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Convert data to Flint signal format and initialise the Flint class. The ILT distribution is obtained by calling the `solve_flint` method. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "Lipschitz constant found: 4783.932712392043\n"
     ]
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    "signal = FlintSignal.load_from_data(signal_decay, time_axis, None)\n",
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    "              t1range = [1e-4, 10e0], \n",
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