{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Computing things!\n",
        "\n",
        "<hr>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "tags": []
      },
      "outputs": [],
      "source": [
        "import numpy as np"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "<hr >\n",
        "\n",
        "You may remember that we worked with a Numpy array:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "tags": []
      },
      "outputs": [],
      "source": [
        "x = np.array(\n",
        "    [\n",
        "        1828, 2131, 1851, 2030, 1930, 1660, 1721, 1740, 1752, 1863, 2141,\n",
        "        1701, 1661, 1712, 1749, 1642, 1882, 1821, 1800, 1692, 1680, 1671,\n",
        "        1683, 1833, 1800, 1930, 1910, 1821, 1840, 1787, 1683, 1809, 1951,\n",
        "        1892, 1731, 1751, 1802, 1912, 1781, 2091, 1852, 1792, 2061, 1683\n",
        "    ],\n",
        "    dtype=float\n",
        ")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Those numbers are actually from a data set from [Harvey and Orbidans, PLoS One, 2011](https://doi.org/10.1371/journal.pone.0025840) on the cross-sectional area of *C. elegans* eggs. \n",
        "\n",
        "Now we would like to compute the diameter of the egg from the cross-sectional area. Write a function that takes in an array of cross-sectional areas and returns an array of diameters. Recall that the diameter $d$ and cross-sectional area $A$ are related by $A = \\pi d^2/4$. There should be no `for` loops in your function! The call signature is\n",
        "\n",
        "```python\n",
        "xa_to_diameter(x)\n",
        "```\n",
        "\n",
        "Use your function to compute the diameters of the eggs."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "<br />"
      ]
    }
  ],
  "metadata": {
    "anaconda-cloud": {},
    "kernelspec": {
      "display_name": "Python 3 (ipykernel)",
      "language": "python",
      "name": "python3"
    },
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      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
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      "pygments_lexer": "ipython3",
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