adding new packages

2019-01-14 20:20:56 -05:00
parent 623f928cf1
commit 23d14c0393
172 changed files with 23324 additions and 3314 deletions
@@ -6,6 +6,7 @@ Automatically generated HTML file from DocOnce source
 <head>
 <meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
 <meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
+<meta name="viewport" content="width=device-width, initial-scale=1.0" />
 <meta name="description" content="Data Analysis and Machine Learning: Getting started, our first data and Machine Learning encounters">

 <title>Data Analysis and Machine Learning: Getting started, our first data and Machine Learning encounters</title>
@@ -43,22 +44,23 @@ Automatically generated HTML file from DocOnce source
 'sections': [('Introduction', 2, None, '___sec0'),
              ('Software and needed installations', 2, None, '___sec1'),
              ('Python installers', 2, None, '___sec2'),
-              ('Installing R, C++, cython or Julia', 2, None, '___sec3'),
-              ('Installing R, C++, cython, Numba etc', 2, None, '___sec4'),
+              ('Useful Python packages', 2, None, '___sec3'),
+              ('Installing R, C++, cython or Julia', 2, None, '___sec4'),
+              ('Installing R, C++, cython, Numba etc', 2, None, '___sec5'),
              ('Simple linear regression model using _scikit-learn_',
               2,
               None,
-               '___sec5'),
-              ('Non-Linear Least squares in R', 2, None, '___sec6'),
-              ('Examples', 2, None, '___sec7'),
-              ('Ecoli lab experiment', 3, None, '___sec8'),
-              ('Predator-Prey model from ecology', 3, None, '___sec9'),
-              ('Simulating financial transactions', 3, None, '___sec10'),
+               '___sec6'),
+              ('Non-Linear Least squares in R', 2, None, '___sec7'),
+              ('Examples', 2, None, '___sec8'),
+              ('Ecoli lab experiment', 3, None, '___sec9'),
+              ('Predator-Prey model from ecology', 3, None, '___sec10'),
+              ('Simulating financial transactions', 3, None, '___sec11'),
              ('Particle in one dimension and velocity distribution',
               3,
               None,
-               '___sec11'),
-              ('Random walk model', 3, None, '___sec12')]}
+               '___sec12'),
+              ('Random walk model', 3, None, '___sec13')]}
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 <body>
@@ -99,16 +101,17 @@ MathJax.Hub.Config({
     <!-- navigation toc: --> <li><a href="#___sec0" style="font-size: 80%;"><b>Introduction</b></a></li>
     <!-- navigation toc: --> <li><a href="#___sec1" style="font-size: 80%;"><b>Software and needed installations</b></a></li>
     <!-- navigation toc: --> <li><a href="#___sec2" style="font-size: 80%;"><b>Python installers</b></a></li>
-     <!-- navigation toc: --> <li><a href="#___sec3" style="font-size: 80%;"><b>Installing R, C++, cython or Julia</b></a></li>
-     <!-- navigation toc: --> <li><a href="#___sec4" style="font-size: 80%;"><b>Installing R, C++, cython, Numba etc</b></a></li>
-     <!-- navigation toc: --> <li><a href="#___sec5" style="font-size: 80%;"><b>Simple linear regression model using <b>scikit-learn</b></b></a></li>
-     <!-- navigation toc: --> <li><a href="#___sec6" style="font-size: 80%;"><b>Non-Linear Least squares in R</b></a></li>
-     <!-- navigation toc: --> <li><a href="#___sec7" style="font-size: 80%;"><b>Examples</b></a></li>
-     <!-- navigation toc: --> <li><a href="#___sec8" style="font-size: 80%;">&nbsp;&nbsp;&nbsp;Ecoli lab experiment</a></li>
-     <!-- navigation toc: --> <li><a href="#___sec9" style="font-size: 80%;">&nbsp;&nbsp;&nbsp;Predator-Prey model from ecology</a></li>
-     <!-- navigation toc: --> <li><a href="#___sec10" style="font-size: 80%;">&nbsp;&nbsp;&nbsp;Simulating financial transactions</a></li>
-     <!-- navigation toc: --> <li><a href="#___sec11" style="font-size: 80%;">&nbsp;&nbsp;&nbsp;Particle in one dimension and velocity distribution</a></li>
-     <!-- navigation toc: --> <li><a href="#___sec12" style="font-size: 80%;">&nbsp;&nbsp;&nbsp;Random walk model</a></li>
+     <!-- navigation toc: --> <li><a href="#___sec3" style="font-size: 80%;"><b>Useful Python packages</b></a></li>
+     <!-- navigation toc: --> <li><a href="#___sec4" style="font-size: 80%;"><b>Installing R, C++, cython or Julia</b></a></li>
+     <!-- navigation toc: --> <li><a href="#___sec5" style="font-size: 80%;"><b>Installing R, C++, cython, Numba etc</b></a></li>
+     <!-- navigation toc: --> <li><a href="#___sec6" style="font-size: 80%;"><b>Simple linear regression model using <b>scikit-learn</b></b></a></li>
+     <!-- navigation toc: --> <li><a href="#___sec7" style="font-size: 80%;"><b>Non-Linear Least squares in R</b></a></li>
+     <!-- navigation toc: --> <li><a href="#___sec8" style="font-size: 80%;"><b>Examples</b></a></li>
+     <!-- navigation toc: --> <li><a href="#___sec9" style="font-size: 80%;">&nbsp;&nbsp;&nbsp;Ecoli lab experiment</a></li>
+     <!-- navigation toc: --> <li><a href="#___sec10" style="font-size: 80%;">&nbsp;&nbsp;&nbsp;Predator-Prey model from ecology</a></li>
+     <!-- navigation toc: --> <li><a href="#___sec11" style="font-size: 80%;">&nbsp;&nbsp;&nbsp;Simulating financial transactions</a></li>
+     <!-- navigation toc: --> <li><a href="#___sec12" style="font-size: 80%;">&nbsp;&nbsp;&nbsp;Particle in one dimension and velocity distribution</a></li>
+     <!-- navigation toc: --> <li><a href="#___sec13" style="font-size: 80%;">&nbsp;&nbsp;&nbsp;Random walk model</a></li>

        </ul>
      </li>
@@ -142,7 +145,7 @@ MathJax.Hub.Config({
 <center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
 <br>
 <p>
-<center><h4>May 30, 2018</h4></center> <!-- date -->
+<center><h4>Jan 14, 2019</h4></center> <!-- date -->
 <br>
 <p>
 </div> <!-- end jumbotron -->
@@ -256,7 +259,10 @@ distribution for scientific and analytic computing distribution and
 analysis environment, available for free and under a commercial
 license.

-<h2 id="___sec3" class="anchor">Installing R, C++, cython or Julia </h2>
+<h2 id="___sec3" class="anchor">Useful Python packages </h2>
+Here we list several useful Python packages.
+
+<h2 id="___sec4" class="anchor">Installing R, C++, cython or Julia </h2>

 <p>
 You will also find it convenient to utilize R. Although we will mainly
@@ -274,7 +280,7 @@ texts.
 To install <b>R</b> with Jupyter notebook 
 <a href="https://mpacer.org/maths/r-kernel-for-ipython-notebook" target="_self">follow the link here</a>

-<h2 id="___sec4" class="anchor">Installing R, C++, cython, Numba etc </h2>
+<h2 id="___sec5" class="anchor">Installing R, C++, cython, Numba etc </h2>

 <p>
 For the C++ aficionados, Jupyter/IPython notebook allows you also to
@@ -308,7 +314,7 @@ Finally, if you wish to use the light mark-up language
 <a href="https://github.com/hplgit/doconce" target="_self">doconce</a> you can convert a standard ascii text file into various HTML 
 formats, ipython notebooks, latex files, pdf files etc with minimal edits.

-<h2 id="___sec5" class="anchor">Simple linear regression model using <b>scikit-learn</b> </h2>
+<h2 id="___sec6" class="anchor">Simple linear regression model using <b>scikit-learn</b> </h2>

 <p>
 We start with perhaps our simplest possible example, using <b>scikit-learn</b> to perform linear regression analysis on a data set produced by us. 
@@ -596,7 +602,7 @@ plt<span style="color: #666666">.</span>show()
 Similarly, using <b>R</b>, we can perform similar studies. The following <b>R</b> code illustrates this.
 (more details on <b>R</b> will be inserted later).

-<h2 id="___sec6" class="anchor">Non-Linear Least squares in R  </h2>
+<h2 id="___sec7" class="anchor">Non-Linear Least squares in R  </h2>
 <div class="panel panel-default">
 <div class="panel-body">
 <p> <!-- subsequent paragraphs come in larger fonts, so start with a paragraph -->
@@ -647,7 +653,7 @@ data_pandas <span style="color: #666666">=</span> pd<span style="color: #666666"
 display(data_pandas)
 </pre></div>

-<h2 id="___sec7" class="anchor">Examples </h2>
+<h2 id="___sec8" class="anchor">Examples </h2>

 <p>
 We present here several examples, with pertinent Python codes that we
@@ -664,7 +670,7 @@ Another model from the life sciences is the so-called predator-prey model from e
 a simple model for financial transactions before moving to a random walk model and ending with 
 the simulation of velocities of a non-interacting atom or molecule confined to move in  a one-dimensional region.

-<h3 id="___sec8" class="anchor">Ecoli lab experiment </h3>
+<h3 id="___sec9" class="anchor">Ecoli lab experiment </h3>

 <p>
 A typical pattern seen in population models is that the population grows faster and faster. <a href="http://www.zo.utexas.edu/courses/Thoc/PopGrowth.html" target="_self">Why? Is there an underlying (general) mechanism</a>?
@@ -785,7 +791,7 @@ plt<span style="color: #666666">.</span>show()
 We can then change the parameter \( r \) in the program and play around to make a better fit. By now we know that this
 'search bythe eye' approach is not the most optimal one.

-<h3 id="___sec9" class="anchor">Predator-Prey model from ecology </h3>
+<h3 id="___sec10" class="anchor">Predator-Prey model from ecology </h3>

 <p>
 The population dynamics of a simple predator-prey system is a
@@ -1087,7 +1093,7 @@ confint(linearMod)
 predict(linearMod,<span style="color: #B00040">data.frame</span>(Year<span style="color: #666666">=</span><span style="color: #B00040">c</span>(<span style="color: #666666">1910</span>,<span style="color: #666666">1914</span>,<span style="color: #666666">1920</span>)),interval<span style="color: #666666">=</span><span style="color: #BA2121">&quot;confidence&quot;</span>)
 </pre></div>

-<h3 id="___sec10" class="anchor">Simulating financial transactions </h3>
+<h3 id="___sec11" class="anchor">Simulating financial transactions </h3>

 <p>
 The aim here is to simulate financial transactions among financial agents
@@ -1262,7 +1268,7 @@ $$
  equilibrium distributions and compare these with the Gibbs distribution. We will use this model to 
 extract a parametrization of the above curves, see for example <a href="http://www.sciencedirect.com/science/article/pii/S0378437104004327" target="_self">Patriarca and collaborators</a>.

-<h3 id="___sec11" class="anchor">Particle in one dimension and velocity distribution </h3>
+<h3 id="___sec12" class="anchor">Particle in one dimension and velocity distribution </h3>

 <p>

@@ -1312,7 +1318,7 @@ plt<span style="color: #666666">.</span>grid(<span style="color: #008000">True</
 plt<span style="color: #666666">.</span>show()
 </pre></div>

-<h3 id="___sec12" class="anchor">Random walk model </h3>
+<h3 id="___sec13" class="anchor">Random walk model </h3>

 <p>

@@ -1423,7 +1429,7 @@ plt<span style="color: #666666">.</span>show()


 <center style="font-size:80%">
-<!-- copyright --> &copy; 1999-2018, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
+<!-- copyright --> &copy; 1999-2019, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
 </center>