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    "*This problem sheet contains some extra material which is not graded! You don't have to turn this problem sheet in.*"
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    "---"
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   "source": [
    "# Introduction to Data Science\n",
    "## Lab 5: Magic commands"
   ]
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   "source": [
    "### Part A: Assessing runtime of code snippets"
   ]
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   "source": [
    "In this part we learn how to assess different ways to implement the same operations."
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    "We generate two one-dimensional random arrays `x` and `y` using two different ways:\n",
    "- `x` should be generated by directly calling `np.random.rand()` with the correct shape\n",
    "- `y` should be generated by first creating a list with random variables using \n",
    "\n",
    "        [np.random.rand() for _ in range(n)]\n",
    "        \n",
    "  and converting this list into an array by wrapping the function `np.array()` around\n",
    "\n",
    "Both arrays should contain `n = 1000000` elements."
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    "import numpy as np\n",
    "n = 1000000\n",
    "\n",
    "# YOUR CODE HERE\n",
    "raise NotImplementedError()"
   ]
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    "Next, we use the magic command `%timeit` to measure the **mean execution time** of the two different ways to generate `x` and `y`.\n",
    "\n",
    "Simply prefix the `%timeit` command to assess the runtime, e.g.\n",
    "\n",
    "        %timeit np.random.rand(n)\n",
    "\n",
    "*Note*: Learn more about magic commands [here](https://ipython.readthedocs.io/en/stable/interactive/magics.html)."
   ]
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    "print('Direct method:')\n",
    "\n",
    "# YOUR CODE HERE\n",
    "raise NotImplementedError()\n",
    "\n",
    "print('Indirect method:')\n",
    "\n",
    "# YOUR CODE HERE\n",
    "raise NotImplementedError()"
   ]
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   "source": [
    "**Task**: Compare the runtime of three different ways to add the arrays `x` and `y`:\n",
    "- `x + y`\n",
    "- `np.array([x[i] + y[i] for i in range(n)])`\n",
    "- `np.add(x,y)`\n",
    "\n",
    "What do you observe?"
   ]
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    "print('Direct way:')\n",
    "\n",
    "# YOUR CODE HERE\n",
    "raise NotImplementedError()\n",
    "print('Numpy function np.add:')\n",
    "\n",
    "# YOUR CODE HERE\n",
    "raise NotImplementedError()\n",
    "print('Loop over elements:')\n",
    "\n",
    "# YOUR CODE HERE\n",
    "raise NotImplementedError()"
   ]
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   "source": [
    "### Part B: Further useful magic commands"
   ]
  },
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   "source": [
    "Try to find out what the following magic commands will do:\n",
    "- `%who_ls`(Add description here!)\n",
    "- `%whos` (Add description here!)\n",
    "- `%time` (Add description here!)\n",
    "- `%system` in connection with system commands, e.g., `%system ls ..`\n",
    "\n",
    "*Note*: Magic commands follow their own syntax, e.g., you cannot call\n",
    "\n",
    "    print(%who_ls)\n",
    "    \n",
    "However, you can do the following\n",
    "    \n",
    "    a = %who_ls\n",
    "    print(a)"
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    "# YOUR CODE HERE\n",
    "raise NotImplementedError()"
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