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material/1_mon/envs/envs_handout.html

@@ -753,7 +753,7 @@ <h3 class="anchored" data-anchor-id="adding-dependencies">Adding dependencies</h
 <dl class="code-annotation-container-hidden code-annotation-container-grid">
 <dt data-target-cell="annotated-cell-5" data-target-annotation="1">1</dt>
 <dd>
-<span data-code-lines="3" data-code-annotation="1" data-code-cell="annotated-cell-5">let’s directly add a compat entry for ProgressMeter</span>
+<span data-code-annotation="1" data-code-cell="annotated-cell-5" data-code-lines="3">let’s directly add a compat entry for ProgressMeter</span>
 </dd>
 </dl>
 </section>
@@ -786,23 +786,23 @@ <h3 class="anchored" data-anchor-id="compat-entries">Compat entries</h3>
 <dl class="code-annotation-container-hidden code-annotation-container-grid">
 <dt data-target-cell="annotated-cell-6" data-target-annotation="1">1</dt>
 <dd>
-<span data-code-lines="2" data-code-annotation="1" data-code-cell="annotated-cell-6">[1.0.0-2)</span>
+<span data-code-annotation="1" data-code-cell="annotated-cell-6" data-code-lines="2">[1.0.0-2)</span>
 </dd>
 <dt data-target-cell="annotated-cell-6" data-target-annotation="2">2</dt>
 <dd>
-<span data-code-lines="3" data-code-annotation="2" data-code-cell="annotated-cell-6">[1.5.0-2)</span>
+<span data-code-annotation="2" data-code-cell="annotated-cell-6" data-code-lines="3">[1.5.0-2)</span>
 </dd>
 <dt data-target-cell="annotated-cell-6" data-target-annotation="3">3</dt>
 <dd>
-<span data-code-lines="4" data-code-annotation="3" data-code-cell="annotated-cell-6">[1.5.3-2)</span>
+<span data-code-annotation="3" data-code-cell="annotated-cell-6" data-code-lines="4">[1.5.3-2)</span>
 </dd>
 <dt data-target-cell="annotated-cell-6" data-target-annotation="4">4</dt>
 <dd>
-<span data-code-lines="5" data-code-annotation="4" data-code-cell="annotated-cell-6">[1.5.6]</span>
+<span data-code-annotation="4" data-code-cell="annotated-cell-6" data-code-lines="5">[1.5.6]</span>
 </dd>
 <dt data-target-cell="annotated-cell-6" data-target-annotation="5">5</dt>
 <dd>
-<span data-code-lines="7" data-code-annotation="5" data-code-cell="annotated-cell-6">[0.2.3 - 0.3)</span>
+<span data-code-annotation="5" data-code-cell="annotated-cell-6" data-code-lines="7">[0.2.3 - 0.3)</span>
 </dd>
 </dl>
 <p>As you can see, develop version (<code>version &lt; 1</code>) are treated a bit special in Julia, and different to <code>semver</code>. <a href="https://pkgdocs.julialang.org/v1/compatibility/#compat-pre-1.0">Read more here</a></p>
@@ -834,7 +834,7 @@ <h3 class="anchored" data-anchor-id="internals-of-a-package">Internals of a pack
 <dl class="code-annotation-container-hidden code-annotation-container-grid">
 <dt data-target-cell="annotated-cell-7" data-target-annotation="1">1</dt>
 <dd>
-<span data-code-lines="2" data-code-annotation="1" data-code-cell="annotated-cell-7">We use GLMakie as a simple example as you need it on Wednesday again anyway - it does take a while to install though!</span>
+<span data-code-annotation="1" data-code-cell="annotated-cell-7" data-code-lines="2">We use GLMakie as a simple example as you need it on Wednesday again anyway - it does take a while to install though!</span>
 </dd>
 </dl>
 <p>Now we are ready to use the package from a different environment</p>

material/1_mon/firststeps/tasks.html

@@ -428,8 +428,8 @@ <h2 class="anchored" data-anchor-id="wait---how-do-i-even-run-things-in-juliavsc
 <h2 class="anchored" data-anchor-id="the-exercise">The exercise</h2>
 <ol type="1">
 <li><p>Open a new script <code>statistic_functions.jl</code> in VSCode in a folder of your choice.</p></li>
-<li><p>implement a function called <code>rse_sum</code><a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a>. This function should return <code>true</code> if provided with the following test: <code>res_sum(1:36) == 666</code>. You should further make use of a for-loop.</p></li>
-<li><p>implement a second function called <code>rse_mean</code>, which calculates the mean of the provided vector. Make sure to use the <code>rse_sum</code> function! Test it using <code>res_mean(-15:17) == 1</code></p></li>
+<li><p>implement a function called <code>rse_sum</code><a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a>. This function should return <code>true</code> if provided with the following test: <code>rse_sum(1:36) == 666</code>. You should further make use of a for-loop.</p></li>
+<li><p>implement a second function called <code>rse_mean</code>, which calculates the mean of the provided vector. Make sure to use the <code>rse_sum</code> function! Test it using <code>rse_mean(-15:17) == 1</code></p></li>
 <li><p>Next implement a standard deviation function <code>rse_std</code>: <span class="math inline">\(\sqrt{\frac{\sum((x-mean(x))^2)}{n-1}}\)</span>, this time you should use elementwise/broadcasting operators. Test it with <code>rse_std(1:3) == 1</code></p></li>
 <li><p>Finally, we will implement <code>rse_tstat</code>, returning the t-value with <code>length(x)-1</code> DF, that the provided Array actually has a mean of 0. The formula is <span class="math inline">\(\frac{mean(x)}{std(x) / (sqrt(x))}\)</span> Test it with <code>rse_tstat(2:3) == 5</code>. Add the keyword argument <code>σ</code> that allows the user to optionally provide a pre-calculated standard deviation.</p></li>
 </ol>

material/3_wed/vis/handout.html

@@ -568,7 +568,7 @@ <h2 class="anchored" data-anchor-id="bonus-makie-interactivity">Bonus: Makie Int
 <dl class="code-annotation-container-hidden code-annotation-container-grid">
 <dt data-target-cell="annotated-cell-5" data-target-annotation="1">1</dt>
 <dd>
-<span data-code-lines="5" data-code-cell="annotated-cell-5" data-code-annotation="1"><code>@lift</code> does the heavy lifting (hrhr) here. It adds a listener to <code>obs_ix</code>, whenever that value is changed, the value of the output of <code>@lift</code> is changed as well ## Task 2: Interactivity <a href="../../../material/3_wed/vis/tasks.html#2">Click here for the next task</a></span>
+<span data-code-annotation="1" data-code-cell="annotated-cell-5" data-code-lines="5"><code>@lift</code> does the heavy lifting (hrhr) here. It adds a listener to <code>obs_ix</code>, whenever that value is changed, the value of the output of <code>@lift</code> is changed as well ## Task 2: Interactivity <a href="../../../material/3_wed/vis/tasks.html#2">Click here for the next task</a></span>
 </dd>
 </dl>
 </section>

material/3_wed/vis/tasks.html

@@ -707,7 +707,7 @@ <h2 class="anchored" data-anchor-id="rotate-the-labels">Rotate the labels</h2>
 <dl class="code-annotation-container-hidden code-annotation-container-grid">
 <dt data-target-cell="annotated-cell-4" data-target-annotation="1">1</dt>
 <dd>
-<span data-code-lines="1" data-code-cell="annotated-cell-4" data-code-annotation="1">Note the <code>;</code> before xlims, this enforces that a <code>NamedTuple</code> is created</span>
+<span data-code-annotation="1" data-code-lines="1" data-code-cell="annotated-cell-4">Note the <code>;</code> before xlims, this enforces that a <code>NamedTuple</code> is created</span>
 </dd>
 </dl>
 

search.json

@@ -480,7 +480,7 @@
     "href": "material/1_mon/firststeps/tasks.html",
     "title": "Task 1",
     "section": "",
-    "text": "Typically, you work in a Julia script ending in scriptname.jl\nYou concurrently have a REPL open, to not reload all packages etc. everytime. Further you typically have Revise.jl running in the background to automatically update your custom Packages / Modules (more to that later).\nYou can mark some code and execute it using ctrl + enter - you can also generate code-blocks using #--- and run a whole code-block using alt+enter\n\n\n\n\nOpen a new script statistic_functions.jl in VSCode in a folder of your choice.\nimplement a function called rse_sum1. This function should return true if provided with the following test: res_sum(1:36) == 666. You should further make use of a for-loop.\nimplement a second function called rse_mean, which calculates the mean of the provided vector. Make sure to use the rse_sum function! Test it using res_mean(-15:17) == 1\nNext implement a standard deviation function rse_std: \\(\\sqrt{\\frac{\\sum((x-mean(x))^2)}{n-1}}\\), this time you should use elementwise/broadcasting operators. Test it with rse_std(1:3) == 1\nFinally, we will implement rse_tstat, returning the t-value with length(x)-1 DF, that the provided Array actually has a mean of 0. The formula is \\(\\frac{mean(x)}{std(x) / (sqrt(x))}\\) Test it with rse_tstat(2:3) == 5. Add the keyword argument σ that allows the user to optionally provide a pre-calculated standard deviation.\n\nWell done! You now have all functions defined with which we will continue our journey.\n\n\n\n\n\n\nBonus Task ProgressMeter\n\n\n\nfor very large sums we might want to add a progressmeter. To do so:\n]add ProgressMeter\nusing ProgressMeter\n...\n@showprogress for ...\n\n\nAnd that’s it! You should have a nice progress bar now"
+    "text": "Typically, you work in a Julia script ending in scriptname.jl\nYou concurrently have a REPL open, to not reload all packages etc. everytime. Further you typically have Revise.jl running in the background to automatically update your custom Packages / Modules (more to that later).\nYou can mark some code and execute it using ctrl + enter - you can also generate code-blocks using #--- and run a whole code-block using alt+enter\n\n\n\n\nOpen a new script statistic_functions.jl in VSCode in a folder of your choice.\nimplement a function called rse_sum1. This function should return true if provided with the following test: rse_sum(1:36) == 666. You should further make use of a for-loop.\nimplement a second function called rse_mean, which calculates the mean of the provided vector. Make sure to use the rse_sum function! Test it using rse_mean(-15:17) == 1\nNext implement a standard deviation function rse_std: \\(\\sqrt{\\frac{\\sum((x-mean(x))^2)}{n-1}}\\), this time you should use elementwise/broadcasting operators. Test it with rse_std(1:3) == 1\nFinally, we will implement rse_tstat, returning the t-value with length(x)-1 DF, that the provided Array actually has a mean of 0. The formula is \\(\\frac{mean(x)}{std(x) / (sqrt(x))}\\) Test it with rse_tstat(2:3) == 5. Add the keyword argument σ that allows the user to optionally provide a pre-calculated standard deviation.\n\nWell done! You now have all functions defined with which we will continue our journey.\n\n\n\n\n\n\nBonus Task ProgressMeter\n\n\n\nfor very large sums we might want to add a progressmeter. To do so:\n]add ProgressMeter\nusing ProgressMeter\n...\n@showprogress for ...\n\n\nAnd that’s it! You should have a nice progress bar now"
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   {
     "objectID": "material/1_mon/firststeps/tasks.html#wait---how-do-i-even-run-things-in-juliavscode",
@@ -494,7 +494,7 @@
     "href": "material/1_mon/firststeps/tasks.html#the-exercise",
     "title": "Task 1",
     "section": "",
-    "text": "Open a new script statistic_functions.jl in VSCode in a folder of your choice.\nimplement a function called rse_sum1. This function should return true if provided with the following test: res_sum(1:36) == 666. You should further make use of a for-loop.\nimplement a second function called rse_mean, which calculates the mean of the provided vector. Make sure to use the rse_sum function! Test it using res_mean(-15:17) == 1\nNext implement a standard deviation function rse_std: \\(\\sqrt{\\frac{\\sum((x-mean(x))^2)}{n-1}}\\), this time you should use elementwise/broadcasting operators. Test it with rse_std(1:3) == 1\nFinally, we will implement rse_tstat, returning the t-value with length(x)-1 DF, that the provided Array actually has a mean of 0. The formula is \\(\\frac{mean(x)}{std(x) / (sqrt(x))}\\) Test it with rse_tstat(2:3) == 5. Add the keyword argument σ that allows the user to optionally provide a pre-calculated standard deviation.\n\nWell done! You now have all functions defined with which we will continue our journey.\n\n\n\n\n\n\nBonus Task ProgressMeter\n\n\n\nfor very large sums we might want to add a progressmeter. To do so:\n]add ProgressMeter\nusing ProgressMeter\n...\n@showprogress for ...\n\n\nAnd that’s it! You should have a nice progress bar now"
+    "text": "Open a new script statistic_functions.jl in VSCode in a folder of your choice.\nimplement a function called rse_sum1. This function should return true if provided with the following test: rse_sum(1:36) == 666. You should further make use of a for-loop.\nimplement a second function called rse_mean, which calculates the mean of the provided vector. Make sure to use the rse_sum function! Test it using rse_mean(-15:17) == 1\nNext implement a standard deviation function rse_std: \\(\\sqrt{\\frac{\\sum((x-mean(x))^2)}{n-1}}\\), this time you should use elementwise/broadcasting operators. Test it with rse_std(1:3) == 1\nFinally, we will implement rse_tstat, returning the t-value with length(x)-1 DF, that the provided Array actually has a mean of 0. The formula is \\(\\frac{mean(x)}{std(x) / (sqrt(x))}\\) Test it with rse_tstat(2:3) == 5. Add the keyword argument σ that allows the user to optionally provide a pre-calculated standard deviation.\n\nWell done! You now have all functions defined with which we will continue our journey.\n\n\n\n\n\n\nBonus Task ProgressMeter\n\n\n\nfor very large sums we might want to add a progressmeter. To do so:\n]add ProgressMeter\nusing ProgressMeter\n...\n@showprogress for ...\n\n\nAnd that’s it! You should have a nice progress bar now"
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