<br><br>On Wednesday, October 4, 2017, Charles Cossé <<a href="mailto:ccosse@gmail.com">ccosse@gmail.com</a>> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div><div>Hi Kirby,<br><br></div>A good Python + math investigation could be to use Python to generate some type of simulated event data (network, physics, pure math, etc), not limited to just 2 parameters per event, and then use plotting software to appreciate how different the same data can look in various representations (ie, time-series, xy, 2d scatter, 3d scatter, 1d histo, 2d histo, cell plot, etc). Idk ... just a thought, just throwing it out there. Sounds like fun!</div></div></blockquote><div><br></div><div>Ideas for simulation data</div><div><br></div><div>## Bank transactions:</div><div>(id, desc, [location], amount)</div><div><br></div><div><a href="https://github.com/westurner/pypfi/blob/develop/pypfi/datagenerator.py">https://github.com/westurner/pypfi/blob/develop/pypfi/datagenerator.py</a><br></div><div><a href="https://github.com/westurner/pypfi/blob/develop/pypfi/pypfi.py">https://github.com/westurner/pypfi/blob/develop/pypfi/pypfi.py</a> (a bunch of pivot tables in static HTML; no charts/graphs yet)<br></div><div><br></div><div>## particle collisions</div><div><a href="https://en.wikipedia.org/wiki/Particle_accelerator">https://en.wikipedia.org/wiki/Particle_accelerator</a><br></div><div><a href="https://en.wikipedia.org/wiki/Collider">https://en.wikipedia.org/wiki/Collider</a><br></div><div><a href="https://en.wikipedia.org/wiki/Large_Hadron_Collider">https://en.wikipedia.org/wiki/Large_Hadron_Collider</a><br></div><div>(<a href="https://en.wikipedia.org/wiki/CERN">https://en.wikipedia.org/wiki/CERN</a> LHC)</div><div><br></div><div><a href="http://opendata.cern.ch/">http://opendata.cern.ch/</a><br></div><div><br></div><div><a href="https://home.cern/about/computing/processing-what-record">https://home.cern/about/computing/processing-what-record</a> <br></div><div><div>> The raw data per event is around one million bytes (1 Mb), produced at a rate of about 600 million events per second.</div><div>> […]</div><div>> In the first stage of the selection, the number of events is filtered from the 600 million or so per second picked up by detectors to 100,000 per second sent for digital reconstruction. In a second stage, more specialized algorithms further process the data, leaving only 100 or 200 events of interest per second.</div><div><br></div><div><div><a href="http://opendata.cern.ch/getting-started/CMS">http://opendata.cern.ch/getting-started/CMS</a><br></div><div><a href="http://opendata.cern.ch/about/CMS-Physics-Objects">http://opendata.cern.ch/about/CMS-Physics-Objects</a><br></div></div><div><a href="https://twiki.cern.ch/twiki/bin/view/CMSPublic/WorkBookDataFormats">https://twiki.cern.ch/twiki/bin/view/CMSPublic/WorkBookDataFormats</a><br></div><div>- RECO</div><div>- AOD</div><div>- [ ] find an example actual RECO or AOD file</div><div> - [ ] open it in Notepad++/ViM/Emacs</div><div> - would it make sense to store this in git? as a torrent web seed?</div><div><br></div><div>- <a href="https://en.wikipedia.org/wiki/Signal-to-noise_ratio">https://en.wikipedia.org/wiki/Signal-to-noise_ratio</a></div><div>- <a href="https://en.wikipedia.org/wiki/Dimensionality_reduction">https://en.wikipedia.org/wiki/Dimensionality_reduction</a></div><div><br></div><div><br></div></div><div><br></div><div>## object collisions</div><div>(origin_x, origin_y, t, object_id)</div><div>(object_id, […], radius)</div><div><br></div><div>Distance</div><div>- <a href="https://en.wikipedia.org/wiki/Euclidean_distance">https://en.wikipedia.org/wiki/Euclidean_distance</a></div><div>- <a href="https://en.wikipedia.org/wiki/Minkowski_distance">https://en.wikipedia.org/wiki/Minkowski_distance</a></div><div><br></div><div><a href="https://en.wikipedia.org/wiki/Collision_detection">https://en.wikipedia.org/wiki/Collision_detection</a><br></div><div>- class SceneGraph(OrderedDict)</div><div><br></div><div> </div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">-Charles<br><div><br> <br></div></div><div class="gmail_extra"><br><div class="gmail_quote">On Mon, Oct 2, 2017 at 2:35 AM, kirby urner <span dir="ltr"><<a href="javascript:_e(%7B%7D,'cvml','kirby.urner@gmail.com');" target="_blank">kirby.urner@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div><div><div><div><br></div>Given I'm spending 3-4 days a week with 5th & 6th graders, teaching them Python, I'm looking for ways to sync with what Common Core says they should be learning math-wise.<br></div><div><br></div><div>They general strategy here is to look for topics already in the curriculum and develop coding skills around those topics.</div><div><br></div>Turns out that prime versus composite is important at that age, and the classic algorithm used to teach that is the Sieve of Eratosthenes. Most coders have written at least one of those.</div><div><br></div><div>Since we're transitioning from block-based MIT Scratch with not much keyboarding, to full-fledged lexical Python, I'm thinking to assess facility with keyboarding (typing) by having them hand-enter a Sieve, and running it to check for any syntax errors.<br></div><div><br></div><div>While we're still doing natural and whole numbers it makes sense to look at other number series as well, ones we can explore using very simple Python. <br></div><div><br></div><div>Triangular and square numbers, then polyhedral number sequences, such as successive shells around a nucleus. 1, 12, 42, 92...</div><div><br></div><div><a href="http://oeis.org/A005901" target="_blank">http://oeis.org/A005901</a> (note link to my website under links)<br></div><div><a href="https://github.com/4dsolutions/Python5/blob/master/STEM%20Mathematics.ipynb" target="_blank">https://github.com/4dsolutions<wbr>/Python5/blob/master/STEM%<wbr>20Mathematics.ipynb</a></div><div><br></div><div>Pascal's Triangle is an important hub for studying number sequences. It even embeds the Fibonacci Numbers.</div><div><br></div><div>These are the kinds of ideas I've been circling for some years. <br></div><div><a href="http://4dsolutions.net/ocn/numeracy0.html" target="_blank">http://4dsolutions.net/ocn/num<wbr>eracy0.html</a><br></div><div><br></div><div>What's new is I'm getting more opportunities to test them in real world classrooms. Coding with Kids is keeping me busy.<br></div><div><br></div><div>With my adult students, I'm looking at what I call the "Five Dimensions of Python" wherein they expand their awareness of the language, from keywords (dimension 0) to 3rd party ecosystem (dimension 4).</div><div><br></div><div><a href="http://mybizmo.blogspot.com/2017/09/five-dimensions-of-python.html" target="_blank">http://mybizmo.blogspot.com/20<wbr>17/09/five-dimensions-of-pytho<wbr>n.html</a></div><div>(links to another Jupyter Notebook)<br></div><div><br></div>I've finally figured out that Codesters (<a href="http://codesters.com" target="_blank">codesters.com</a>) is about Python 2.7, not Python 3.x. I've been confused on that score.</div><div><br></div><div>Given cryptography is playing a more important role in everyday eCommerce, it makes sense to beef up some of the Number and Group Theory aspects of K-12.</div><div><br></div><div>I've been arguing on math-teach that right when we introduce primes versus composites, we should likewise introduce Fermat's primality test.</div><div><br></div><div><a href="http://mathforum.org/kb/message.jspa?messageID=10241002" target="_blank">http://mathforum.org/kb/messag<wbr>e.jspa?messageID=10241002</a></div><div><a href="http://mathforum.org/kb/thread.jspa?threadID=2883906" target="_blank">http://mathforum.org/kb/thread<wbr>.jspa?threadID=2883906</a><span><font color="#888888"><br></font></span></div><span><font color="#888888"><div><br></div>Kirby<br><br></font></span></div>
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