wat_example.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import zarr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# local storage\n",
    "results = zarr.open('/path/to/local/storage/wat.zarr', mode='a')\n",
    "\n",
    "\n",
    "def compute_wat(pop_query: str, sample_size: int, random_seed: int):\n",
    "    \n",
    "    # argument hash\n",
    "    result_path = f'{pop_query}_{sample_size}_{random_seed}'\n",
    "    \n",
    "    if result_path in results:\n",
    "        # load previously computed array into memory\n",
    "        wat = results[result_path][:]\n",
    "        return wat\n",
    "    \n",
    "    else:\n",
    "        # run the computation to compute wat - N.B., wat should be a numpy array\n",
    "        # ...\n",
    "        \n",
    "        # store results, assuming wat is a numpy array\n",
    "        results.create_dataset(result_path, data=wat)\n",
    "        \n",
    "        # if wat was a dask array, you would do...\n",
    "        destination = results.empty(results_path, shape=wat.shape, dtype=wat.dtype)\n",
    "        wat.store(destination, lock=False)\n",
    "        \n",
    "        return wat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_wat(pop_query):\n",
    "    for sample_size in range(20, 100, 5):\n",
    "        for random_seed in range(5):\n",
    "            wat = compute_wat(pop_query, sample_size, random_seed)"
   ]
  }
 ],
 "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}