Update documentation

health-data-science-OR · Sep 20, 2024 · 8813b08 · 8813b08
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diff --git a/.buildinfo b/.buildinfo
@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 078edd53628af2d11d0ae886ac4b415f
+config: e906d2457507cec8a093e957d9d93bf5
 tags: 645f666f9bcd5a90fca523b33c5a78b7
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diff --git a/_images/f63623785475b00101240dc9b15a56f6c2f16785c1f11979a82aa1ad928b0760.png b/_images/f63623785475b00101240dc9b15a56f6c2f16785c1f11979a82aa1ad928b0760.png
diff --git a/_images/package_versus_project.png b/_images/package_versus_project.png
diff --git a/_images/release.png b/_images/release.png
diff --git a/_images/test_pypi2.png b/_images/test_pypi2.png
diff --git a/_images/test_pypi3.png b/_images/test_pypi3.png
diff --git a/_images/testpypi.png b/_images/testpypi.png
diff --git a/_sources/content/001_setup/contributing.md b/_sources/content/001_setup/contributing.md
@@ -34,9 +34,9 @@ The book will evolve over time. I'd greatly welcome feedback, via Github issues,
 For new content requests please
 
 * Detail the requested content including description and lists of any relevant packages
-* Provide a case why this content relevant to health data scientist
+* Explain why this content is relevant to health data scientists
 * Optional: provide an example 
-* Label the issue an an `enhancement`
+* Label the issue as an `enhancement`
 
 ### General feedback
 

diff --git a/_sources/content/001_setup/docker.md b/_sources/content/001_setup/docker.md
diff --git a/_sources/content/001_setup/prereq/02_dicts.ipynb b/_sources/content/001_setup/prereq/02_dicts.ipynb
@@ -32,7 +32,7 @@
     "A few things to notice: \n",
     "\n",
     "* A `dict` uses `{}` \n",
-    "* Key and item pairs are separated by a semi colon\n",
+    "* Key and item pairs are separated by a colon\n",
     "* The data type of the keys and items do not need to be consistent.  It can be any type you require.\n",
     "\n",
     "> My recommendation is that you keep the data type for the **key** consistent. This simplification avoids silly mistakes.  Flexibility isn't always your friend! \n",
@@ -333,7 +333,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.12"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,

diff --git a/_sources/content/01_algorithms/03_numpy/01_performance.ipynb b/_sources/content/01_algorithms/03_numpy/01_performance.ipynb
@@ -138,7 +138,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "4.51 ms ± 195 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
+      "4.51 ms ± 145 μs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
      ]
     }
    ],
@@ -156,7 +156,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "382 µs ± 2.41 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
+      "215 μs ± 16.2 μs per loop (mean ± std. dev. of 7 runs, 1,000 loops each)\n"
      ]
     }
    ],
@@ -205,7 +205,7 @@
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-7-d7ebd5f93b3a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmy_arr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m7\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "Cell \u001b[0;32mIn[7], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mmy_arr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mappend\u001b[49m(\u001b[38;5;241m7\u001b[39m)\n",
       "\u001b[0;31mAttributeError\u001b[0m: 'numpy.ndarray' object has no attribute 'append'"
      ]
     }
@@ -237,7 +237,7 @@
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-8-e9bed3bd39fc>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmy_arr\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'Zero'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "Cell \u001b[0;32mIn[8], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mmy_arr\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mZero\u001b[39m\u001b[38;5;124m'\u001b[39m\n",
       "\u001b[0;31mValueError\u001b[0m: invalid literal for int() with base 10: 'Zero'"
      ]
     }
@@ -297,7 +297,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -311,7 +311,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,

diff --git a/_sources/content/01_algorithms/03_numpy/05_statistics.ipynb b/_sources/content/01_algorithms/03_numpy/05_statistics.ipynb
@@ -754,7 +754,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -768,7 +768,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.12"
+   "version": "3.8.8"
   }
  },
  "nbformat": 4,

diff --git a/_sources/content/01_algorithms/04_exercises/01_science_funcs.ipynb b/_sources/content/01_algorithms/04_exercises/01_science_funcs.ipynb
@@ -137,12 +137,79 @@
   },
   {
    "cell_type": "markdown",
-   "id": "84b24f22",
+   "id": "fc913e7c-de34-4b5d-aa9e-91f0fbc3365a",
    "metadata": {},
    "source": [
     "---\n",
     "## Exercise 3\n",
     "\n",
+    "A classic **M**arkovian model for representing the steady state performance of queuing and service system is the **M**/**M**/1.  \n",
+    "\n",
+    "In the Markovian model \"customers\" arrive to the model following a Poisson process with rate parameter $\\lambda$ (e.g. an average of 5 arrivals per hour). The M/M/1 is a first come first served system with a single server. Service time is exponentially distributed with mean $1/\\mu$ i.e. customers are served at rate $\\mu$.\n",
+    "\n",
+    "The equation for calculating the average waiting time to be served ($W_q$) in an M/M/1 queue is:\n",
+    "\n",
+    "$$W_q = \\dfrac{\\lambda}{\\mu\\left(\\mu-\\lambda\\right)}$$\n",
+    "\n",
+    "While the probability that there are $n$ customers in the system ($P_n$) is given by:\n",
+    "\n",
+    "$$P_n = \\left(1 - \\dfrac{\\lambda}{\\mu}\\right)\\left(\\dfrac{\\lambda}{\\mu}\\right)^n$$\n",
+    "\n",
+    "\n",
+    "**Example:**\n",
+    "\n",
+    "Given:\n",
+    "\n",
+    "$$\\lambda = 2 \\textnormal{ per hour}$$\n",
+    "$$\\mu = 3 \\textnormal{ per hour}$$\n",
+    "\n",
+    "Calculate $W_q$ and $P_0, P_1$\n",
+    "\n",
+    "$$W_q = \\dfrac{2}{3\\left(3 - 2\\right)} = \\dfrac{2}{3} \\textnormal{ per hour}$$\n",
+    "\n",
+    "\n",
+    "$$P_0 =  \\left(1 - \\dfrac{\\lambda}{\\mu}\\right) = 1 - \\dfrac{2}{3} = \\dfrac{1}{3}$$\n",
+    "\n",
+    "$$P_1 =  \\left(\\dfrac{1}{3}\\right)\\left(\\dfrac{2}{3}\\right) = \\dfrac{2}{9}$$\n",
+    "\n",
+    "**Task:**\n",
+    "\n",
+    "Code functions in python to calculate $W_q$ and $P_n$ for the M/M/1 queue model.\n",
+    "\n",
+    "**Test data:**\n",
+    "\n",
+    "```python\n",
+    "arrival_rate = 2.0\n",
+    "service_rate = 3.0\n",
+    "expected_wq = 2/3\n",
+    "expected_p0 = 1/3\n",
+    "expected_p1 = 2/9\n",
+    "expected_p2 = 4/27\n",
+    "```\n",
+    "\n",
+    "\n",
+    "**Hints:**\n",
+    "* Note that the word \"lambda\" is a special word in Python and should not be used as a variable name. When naming a variable options are to use `_lambda` or `arrival_rate`\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5952f2c3-bc8a-43a7-a398-3c8068a53274",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# your code here..."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "84b24f22",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "## Exercise 4\n",
+    "\n",
     "(source: hackerrank.com)\n",
     "\n",
     "A left rotation operation on an array shifts each of the array's elements unit to the left. \n",
@@ -222,7 +289,7 @@
    "metadata": {},
    "source": [
     "---\n",
-    "## Exercise 4\n",
+    "## Exercise 5\n",
     "\n",
     "The Fibonacci numbers, denoted $F_n$, form a sequence, called the **Fibonacci sequence**, such that each number is the sum of the two preceding ones, starting from 0 and 1. That is\n",
     "\n",
@@ -261,7 +328,7 @@
    "metadata": {},
    "source": [
     "---\n",
-    "## Exercise 5\n",
+    "## Exercise 6\n",
     "\n",
     "(source hackerrank.com)\n",
     "\n",
@@ -339,7 +406,7 @@
    "metadata": {},
    "source": [
     "---\n",
-    "## Exercise 6\n",
+    "## Exercise 7\n",
     "\n",
     "The longest increasing subsequence problem is to find a subsequence of a given sequence in which the subsequence's elements are in sorted order, lowest to highest, and in which the subsequence is as long as possible.\n",
     "\n",
@@ -372,7 +439,7 @@
    "metadata": {},
    "source": [
     "---\n",
-    "## Exercise 7:\n",
+    "## Exercise 8:\n",
     "\n",
     "(source: hackerrank.com)\n",
     "\n",
@@ -500,7 +567,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.8"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,

diff --git a/_sources/content/01_algorithms/04_exercises/02_array.ipynb b/_sources/content/01_algorithms/04_exercises/02_array.ipynb
@@ -308,7 +308,7 @@
    "source": [
     "## Exercise 8\n",
     "\n",
-    "You can think of the 3 dimensional array constructed in the last exercise as an array of two $10 \\times 2$ sub-matricies (indexed 0 to 1).  Each matrix is comprised of 10 sub vectors (indexed 0 to 9).\n",
+    "Remember one  way to get to grips with slicing a 3D array is to look at the shape and think about how it all links together. In the last exercise the array td has a shape $(2, 10, 5)$. I think of this as 2 rows, each of which contains 10 sub vectors of length 5\n",
     "\n",
     "Using the 3 dimensional array constructed in exercise 7 take the following **slices** and if necessary make the updates to the **original** data:\n",
     "\n",
@@ -386,7 +386,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.12"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,