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L2_QR_factorisation.html

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<p>The <a class="reference internal" href="cla_utils.html#cla_utils.exercises2.GS_classical" title="cla_utils.exercises2.GS_classical"><code class="xref py py-func docutils literal notranslate"><span class="pre">cla_utils.exercises2.GS_classical()</span></code></a> function has been
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left unimplemented. It should implement the classical Gram-Schmidt
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algorithm above, using Numpy slice notation so that only one Python
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for loop is used. The function should work “in place” by making a
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copy of <span class="math notranslate nohighlight">\(A\)</span> and then changing the values in the copy, without
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introducing additional intermediate arrays (you will need to create
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a new array to store <span class="math notranslate nohighlight">\(R\)</span>). The test script <code class="docutils literal notranslate"><span class="pre">test_exercises2.py</span></code>
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in the <code class="docutils literal notranslate"><span class="pre">test</span></code> directory will test this function.</p>
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for loop is used. The function should work “in place” by changing
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the values in <span class="math notranslate nohighlight">\(A\)</span>, without introducing additional intermediate
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arrays (you will need to create a new array to store <span class="math notranslate nohighlight">\(R\)</span>). The test
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script <code class="docutils literal notranslate"><span class="pre">test_exercises2.py</span></code> in the <code class="docutils literal notranslate"><span class="pre">test</span></code> directory will test
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this function.</p>
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</div></div></section>
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<section id="projector-interpretation-of-gram-schmidt">
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<h2><span class="section-number">2.3. </span>Projector interpretation of Gram-Schmidt<a class="headerlink" href="#projector-interpretation-of-gram-schmidt" title="Permalink to this headline"></a></h2>
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algorithm above, using Numpy slice notation where possible.
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What is the minimal number of Python
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<p>The function should work “in place” by making a
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copy of <span class="math notranslate nohighlight">\(A\)</span> and then changing those values, without introducing
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additional intermediate arrays. The test script
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<p>The function should work “in place” by changing the values of <span class="math notranslate nohighlight">\(A\)</span>,
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without introducing additional intermediate arrays. The test script
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<code class="docutils literal notranslate"><span class="pre">test_exercises2.py</span></code> in the <code class="docutils literal notranslate"><span class="pre">test</span></code> directory will test this
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function.</p>
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</div></div><div class="proof proof-type-exercise" id="id6">
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done so, you will need to modified
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<a class="reference internal" href="cla_utils.html#cla_utils.exercises3.householder" title="cla_utils.exercises3.householder"><code class="xref py py-func docutils literal notranslate"><span class="pre">cla_utils.exercises3.householder()</span></code></a> to use the <code class="docutils literal notranslate"><span class="pre">kmax</span></code>
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argument. You may make use of the built-in triangular solve
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algorithm <a class="reference external" href="http://scipy.github.io/devdocs/reference/generated/scipy.linalg.solve_triangular.html#scipy.linalg.solve_triangular" title="(in SciPy v1.8.0.dev0+1767.0785d6f)"><code class="xref py py-func docutils literal notranslate"><span class="pre">scipy.linalg.solve_triangular()</span></code></a> (we shall consider
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algorithm <a class="reference external" href="http://scipy.github.io/devdocs/reference/generated/scipy.linalg.solve_triangular.html#scipy.linalg.solve_triangular" title="(in SciPy v1.8.0.dev0+1859.14341ea)"><code class="xref py py-func docutils literal notranslate"><span class="pre">scipy.linalg.solve_triangular()</span></code></a> (we shall consider
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triangular matrix algorithms briefly later). The test script
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<code class="docutils literal notranslate"><span class="pre">test_exercises3.py</span></code> in the <code class="docutils literal notranslate"><span class="pre">test</span></code> directory will also test this
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appropriate augmented matrix <span class="math notranslate nohighlight">\(\hat{A}\)</span>, calling
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<a class="reference internal" href="cla_utils.html#cla_utils.exercises3.householder" title="cla_utils.exercises3.householder"><code class="xref py py-func docutils literal notranslate"><span class="pre">cla_utils.exercises3.householder()</span></code></a> and extracting appropriate
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subarrays using slice notation, before using
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<a class="reference external" href="http://scipy.github.io/devdocs/reference/generated/scipy.linalg.solve_triangular.html#scipy.linalg.solve_triangular" title="(in SciPy v1.8.0.dev0+1767.0785d6f)"><code class="xref py py-func docutils literal notranslate"><span class="pre">scipy.linalg.solve_triangular()</span></code></a> to solve the resulting upper triangular
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<a class="reference external" href="http://scipy.github.io/devdocs/reference/generated/scipy.linalg.solve_triangular.html#scipy.linalg.solve_triangular" title="(in SciPy v1.8.0.dev0+1859.14341ea)"><code class="xref py py-func docutils literal notranslate"><span class="pre">scipy.linalg.solve_triangular()</span></code></a> to solve the resulting upper triangular
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system, before returning the solution <span class="math notranslate nohighlight">\(x\)</span>. The test script
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<code class="docutils literal notranslate"><span class="pre">test_exercises3.py</span></code> in the <code class="docutils literal notranslate"><span class="pre">test</span></code> directory will also test this
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function.</p>

_modules/cla_utils/exercises1.html

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<meta charset="utf-8" />
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<title>cla_utils.exercises1 &#8212; Computational linear algebra course 2020.0 documentation</title>
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<script async="async" src="https://cdn.jsdelivr.net/npm/mathjax@2/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script>
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<div class="viewcode-block" id="rank2"><a class="viewcode-back" href="../../cla_utils.html#cla_utils.exercises1.rank2">[docs]</a><span class="k">def</span> <span class="nf">rank2</span><span class="p">(</span><span class="n">u1</span><span class="p">,</span> <span class="n">u2</span><span class="p">,</span> <span class="n">v1</span><span class="p">,</span> <span class="n">v2</span><span class="p">):</span>
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<span class="sd">&quot;&quot;&quot;</span>
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<span class="sd"> Return the rank2 matrix A = u1*v2^* + u2*v2^*.</span>
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<span class="sd"> Return the rank2 matrix A = u1*v1^* + u2*v2^*.</span>
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<span class="sd"> :param u1: m-dimensional numpy array</span>
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<span class="sd"> :param u2: m-dimensional numpy array</span>
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</div>
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<div class="footer" role="contentinfo">
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&#169; Copyright 2020, Colin J. Cotter.
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Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.4.3.
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Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.2.0.
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</html>

_modules/cla_utils/exercises2.html

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<span class="k">raise</span> <span class="ne">NotImplementedError</span>
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<span class="k">return</span> <span class="n">Q</span><span class="p">,</span> <span class="n">R</span></div>
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<span class="k">return</span> <span class="n">R</span></div>
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<div class="viewcode-block" id="GS_modified"><a class="viewcode-back" href="../../cla_utils.html#cla_utils.exercises2.GS_modified">[docs]</a><span class="k">def</span> <span class="nf">GS_modified</span><span class="p">(</span><span class="n">A</span><span class="p">):</span>
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<span class="sd">&quot;&quot;&quot;</span>

_sources/L2_QR_factorisation.rst.txt

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The :func:`cla_utils.exercises2.GS_classical` function has been
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left unimplemented. It should implement the classical Gram-Schmidt
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algorithm above, using Numpy slice notation so that only one Python
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for loop is used. The function should work "in place" by making a
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copy of `A` and then changing the values in the copy, without
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introducing additional intermediate arrays (you will need to create
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a new array to store `R`). The test script ``test_exercises2.py``
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in the ``test`` directory will test this function.
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for loop is used. The function should work "in place" by changing
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the values in `A`, without introducing additional intermediate
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arrays (you will need to create a new array to store `R`). The test
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script ``test_exercises2.py`` in the ``test`` directory will test
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this function.
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Projector interpretation of Gram-Schmidt
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----------------------------------------
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What is the minimal number of Python
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copy of `A` and then changing those values, without introducing
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additional intermediate arrays. The test script
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The function should work "in place" by changing the values of `A`,
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without introducing additional intermediate arrays. The test script
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``test_exercises2.py`` in the ``test`` directory will test this
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_sources/errata.rst.txt

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Here we'll list all the updates to the exercises and coursework Classroom
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repositories for Autumn 2021. An up to date version is in the
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`public repository <https://github.com/comp-lin-alg/comp-lin-alg-course>`_.
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1. The docstring for :code:`cla_utils.rank2` was updated to show the
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correct indices. Now reads: "Return the rank2 matrix A = u_1v_1^* +
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u_2*v_2^*." See the code on the course website for the up-to-date
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version.
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2. The skeleton code for exercises2.GS_classical was amended as the
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function should just return R, not Q and R.

_sources/exercises.rst.txt

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As you do the exercises, **commit your code** to your repository. This
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will build up your computational exercise solution sets. You should
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commit code early and often - small commits are easier to understand
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and debug than large ones. **Never** commit back to the ``master``
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branch of your fork, that should always remain a clean copy of the
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main repository.
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Pull requests for feedback
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--------------------------
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#. Click on the ``New pull request`` button at the top of your
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repository page on GitHub.
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#. Make sure **left** dropdown box ("base") is set to ``master``.
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#. Make sure **right** dropdown box ("compare") is set to ``implementation``.
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#. Type a suitable title in the title box. For example
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``Request for feedback 30/1/19``.
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#. If you have any comments you would like to pass on to the lecturer
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(for example questions about how you should have done a particular
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exercise) then type these in the ``Description`` box.
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#. Click ``Create pull request``.
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and debug than large ones. **Do not commit to the feedback branch**
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This branch is just there so that we can provide feedback on your
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changes to the main branch.
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Testing your work

cla_utils.html

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<dl class="py function">
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<dt class="sig sig-object py" id="cla_utils.exercises1.rank2">
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<span class="sig-prename descclassname"><span class="pre">cla_utils.exercises1.</span></span><span class="sig-name descname"><span class="pre">rank2</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">u1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">u2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">v1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">v2</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/cla_utils/exercises1.html#rank2"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#cla_utils.exercises1.rank2" title="Permalink to this definition"></a></dt>
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<dd><p>Return the rank2 matrix A = u1*v2^* + u2*v2^*.</p>
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<dd><p>Return the rank2 matrix A = u1*v1^* + u2*v2^*.</p>
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<dl class="field-list simple">
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<dt class="field-odd">Parameters</dt>
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errata.html

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<p>Here we’ll list all the updates to the exercises and coursework Classroom
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<a class="reference external" href="https://github.com/comp-lin-alg/comp-lin-alg-course">public repository</a>.</p>
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<ol class="arabic simple">
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<li><p>The docstring for <code class="code docutils literal notranslate"><span class="pre">cla_utils.rank2</span></code> was updated to show the
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correct indices. Now reads: “Return the rank2 matrix A = u_1v_1^* +
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u_2*v_2^*.” See the code on the course website for the up-to-date
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version.</p></li>
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<li><p>The skeleton code for exercises2.GS_classical was amended as the
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function should just return R, not Q and R.</p></li>
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</ol>
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exercises.html

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<p>As you do the exercises, <strong>commit your code</strong> to your repository. This
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will build up your computational exercise solution sets. You should
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commit code early and often - small commits are easier to understand
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and debug than large ones. <strong>Never</strong> commit back to the <code class="docutils literal notranslate"><span class="pre">master</span></code>
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branch of your fork, that should always remain a clean copy of the
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main repository.</p>
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</section>
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<section id="pull-requests-for-feedback">
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<h2>Pull requests for feedback<a class="headerlink" href="#pull-requests-for-feedback" title="Permalink to this headline"></a></h2>
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<ol class="arabic simple">
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<li><p>Click on the <code class="docutils literal notranslate"><span class="pre">New</span> <span class="pre">pull</span> <span class="pre">request</span></code> button at the top of your
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repository page on GitHub.</p></li>
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<li><p>Make sure <strong>left</strong> dropdown box (“base”) is set to <code class="docutils literal notranslate"><span class="pre">master</span></code>.</p></li>
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<li><p>Make sure <strong>right</strong> dropdown box (“compare”) is set to <code class="docutils literal notranslate"><span class="pre">implementation</span></code>.</p></li>
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<li><p>Type a suitable title in the title box. For example
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<code class="docutils literal notranslate"><span class="pre">Request</span> <span class="pre">for</span> <span class="pre">feedback</span> <span class="pre">30/1/19</span></code>.</p></li>
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<li><p>If you have any comments you would like to pass on to the lecturer
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(for example questions about how you should have done a particular
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exercise) then type these in the <code class="docutils literal notranslate"><span class="pre">Description</span></code> box.</p></li>
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<li><p>Click <code class="docutils literal notranslate"><span class="pre">Create</span> <span class="pre">pull</span> <span class="pre">request</span></code>.</p></li>
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</ol>
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and debug than large ones. <strong>Do not commit to the feedback branch</strong>
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This branch is just there so that we can provide feedback on your
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changes to the main branch.</p>
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</section>
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<section id="testing-your-work">
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<h2>Testing your work<a class="headerlink" href="#testing-your-work" title="Permalink to this headline"></a></h2>

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