pooya changes #246

pooyaravari · 2018-11-02T22:07:16Z

Some changes to the text. Responds to #196

jlperla · 2018-11-04T03:15:54Z

rst_files/_static/includes/lecture_howto_jl.raw

@@ -1,6 +1,6 @@
 How to read this lecture...

 * If using QuantEcon lectures for the first time on a computer, execute ``] add InstantiateFromURL`` inside of a notebook or the REPL
-* For some notebooks, enable content with "Trust" on the command tab of Jupyter lab
+* For some notebooks, enable content with "Trust" on the command tab of Jupyter lab (It is not clear!)


NOTE: We can't have things like this in the notes, or we will forget about them.

jlperla · 2018-11-04T03:16:22Z

rst_files/julia_by_example.rst


 Level
 -------

 Our approach is aimed at those who already have at least some knowledge of programming --- perhaps experience with Python, MATLAB, Fortran, C or similar

-In particular, we assume you have some familiarity with fundamental programming concepts such as
+In particular, we assume you have some familiarity with fundamental programming concepts such as:


We can't add on colons, it is not the style of the lectures.

Suggested change

In particular, we assume you have some familiarity with fundamental programming concepts such as:

In particular, we assume you have some familiarity with fundamental programming concepts such as

jlperla · 2018-11-04T03:16:50Z

rst_files/julia_by_example.rst

@@ -88,7 +86,7 @@ There are three ways to install packages and versions (where the first two metho

 #. directly ``add`` the packages directly into your global installation (e.g. ``Pkg.add("MyPackage")`` or ``] add MyPackage``)  
 #. download an ``Project.toml`` and ``Manifest.toml`` file in the same directory as the notebook (i.e. from the ``@__DIR__`` argument), and then call ``using Pkg; Pkg.activate(@__DIR__);``
-#. use the ``InstantiateFromURL`` package
+#. use the ``InstantiateFromURL`` package (like below):


I am not sure we need this comment.

jlperla · 2018-11-04T03:17:15Z

rst_files/julia_by_example.rst


-In particular, the easiest way to install and precompile all of the Julia packages used in the QuantEcon notes is to go ``] add InstantiateFromURL`` and then work in a Jupyter notebook, as described :ref:`here <jl_jupyter>`
+In particular, the easiest way to install and precompile all of the Julia packages used in the QuantEcon notes is to go ``] add InstantiateFromURL`` and then work in a Jupyter notebook, as described [here](getting_started.ipynb)


I think this is markdown rather than RST links

Suggested change

In particular, the easiest way to install and precompile all of the Julia packages used in the QuantEcon notes is to go ``] add InstantiateFromURL`` and then work in a Jupyter notebook, as described [here](getting_started.ipynb)

In particular, the easiest way to install and precompile all of the Julia packages used in the QuantEcon notes is to go ``] add InstantiateFromURL`` and then work in a Jupyter notebook, as described ` here <getting_started>`_

jlperla · 2018-11-04T03:17:52Z

rst_files/julia_by_example.rst

@@ -145,17 +143,17 @@ The other packages ``LinearAlgebra`` and ``Statistics`` are base Julia libraries

 The arguments to ``plot`` are the numbers ``1,2, ..., n`` for the x-axis, a vector ``ϵ`` for the y-axis, and (optional) settings

-The function ``randn(n)`` returns a column vector ``n`` random draws from a normal distribution mean 0 and variance 1
+The function ``randn(n)`` returns a column vector with *n* random draws from a normal distribution mean 0 and variance 1


That is markdown or something similar.

The Markdown and rST syntax actually agree on this one (italics)

jlperla · 2018-11-04T03:18:39Z

rst_files/julia_by_example.rst

@@ -247,27 +244,25 @@ In Julia you can also loop directly over arrays themselves, like so
        end
        ϵ_mean = ϵ_sum / m

-where ``ϵ[1:m]`` returns the elements of the vector at indices ``1`` to ``m``


I thought this was useful. Not sure why you removed it?

jlperla · 2018-11-04T03:20:46Z

rst_files/julia_by_example.rst


 Using a Function
 ---------------------

-The first problem with this setup is that it depends on being sequently run--which can be easily remedied with a function
+The first problem with this setup is that it depends on being sequently run. Therefore, it can be easily remedied with a function:


This runs against the style of the lectures, which have no periods or multiple sentences without newline.

jlperla · 2018-11-04T03:20:56Z

rst_files/julia_by_example.rst


-Furthermore, a default value may be enabled--so the named parameter ``iv`` is required while ``tolerance`` and ``maxiter`` have default values
+Furthermore, a default value may be enabled. So the named parameter ``iv`` is required while ``tolerance`` and ``maxiter`` have default values


Against the style

jlperla · 2018-11-04T03:21:04Z

rst_files/julia_by_example.rst


-The return type of the function also has named fields, ``value, normdiff,`` and ``iter``--all accessed intuitively using ``.``
+The return type of the function also has named fields, ``value, normdiff,`` and ``iter``. All accessed intuitively using ``.``


Against the style.

jlperla · 2018-11-04T03:21:41Z

rst_files/julia_by_example.rst


-In particular, we can use the ``Anderson acceleration`` with a memory of 5 iterations, by changing a setting
+For instance, we can use the ``Anderson Acceleration`` (it is a method to calculate fixed points) with a memory of 5 iterations by changing a setting:


I would prefer to write this a different way.

This reverts commit 849efa0.

arnavs

Thanks so much @PooyaFa, these fixes (typos, links, language, etc.) are exactly what we need.

arnavs · 2018-11-02T23:13:41Z

rst_files/_static/includes/lecture_howto_jl.raw

@@ -1,6 +1,6 @@
 How to read this lecture...

 * If using QuantEcon lectures for the first time on a computer, execute ``] add InstantiateFromURL`` inside of a notebook or the REPL
-* For some notebooks, enable content with "Trust" on the command tab of Jupyter lab
+* For some notebooks, enable content with "Trust" on the command tab of Jupyter lab (It is not clear!)


Hey @PooyaFa, what's not clear here? The goal is to really make sure that these PRs are ready to be turned into HTML.

rst_files/julia_by_example.rst

rst_files/julia_essentials.rst

arnavs · 2018-11-07T22:30:57Z

rst_files/_static/includes/lecture_howto_jl.raw

@@ -1,6 +1,6 @@
 How to read this lecture...

 * If using QuantEcon lectures for the first time on a computer, execute ``] add InstantiateFromURL`` inside of a notebook or the REPL
-* For some notebooks, enable content with "Trust" on the command tab of Jupyter lab
+* For some notebooks, enable content with "Trust" on the command tab of Jupyter lab (It is not clear!)


Suggested change

* For some notebooks, enable content with "Trust" on the command tab of Jupyter lab (It is not clear!)

* For some notebooks, enable content with "Trust" on the command tab of Jupyter lab

arnavs · 2018-11-07T22:31:08Z

rst_files/julia_by_example.rst


 Level
 -------

 Our approach is aimed at those who already have at least some knowledge of programming --- perhaps experience with Python, MATLAB, Fortran, C or similar

-In particular, we assume you have some familiarity with fundamental programming concepts such as
+In particular, we assume you have some familiarity with fundamental programming concepts such as:


Suggested change

In particular, we assume you have some familiarity with fundamental programming concepts such as:

In particular, we assume you have some familiarity with fundamental programming concepts such as

arnavs · 2018-11-07T22:32:00Z

rst_files/julia_by_example.rst


-In particular, the easiest way to install and precompile all of the Julia packages used in the QuantEcon notes is to go ``] add InstantiateFromURL`` and then work in a Jupyter notebook, as described :ref:`here <jl_jupyter>`
+In particular, the easiest way to install and precompile all of the Julia packages used in the QuantEcon notes is to go ``] add InstantiateFromURL`` and then work in a Jupyter notebook, as described [here](getting_started.ipynb)


Suggested change

In particular, the easiest way to install and precompile all of the Julia packages used in the QuantEcon notes is to go ``] add InstantiateFromURL`` and then work in a Jupyter notebook, as described [here](getting_started.ipynb)

In particular, the easiest way to install and precompile all of the Julia packages used in the QuantEcon notes is to go ``] add InstantiateFromURL`` and then work in a Jupyter notebook, as described ` here <getting_started>`_

arnavs · 2018-11-07T22:32:14Z

rst_files/julia_by_example.rst

@@ -88,7 +88,7 @@ There are three ways to install packages and versions (where the first two metho

 #. directly ``add`` the packages directly into your global installation (e.g. ``Pkg.add("MyPackage")`` or ``] add MyPackage``)  
 #. download an ``Project.toml`` and ``Manifest.toml`` file in the same directory as the notebook (i.e. from the ``@__DIR__`` argument), and then call ``using Pkg; Pkg.activate(@__DIR__);``
-#. use the ``InstantiateFromURL`` package
+#. use the ``InstantiateFromURL`` package (like below):


Suggested change

#. use the ``InstantiateFromURL`` package (like below):

#. use the ``InstantiateFromURL`` package

arnavs · 2018-11-07T22:33:07Z

rst_files/julia_by_example.rst

@@ -145,17 +143,17 @@ The other packages ``LinearAlgebra`` and ``Statistics`` are base Julia libraries

 The arguments to ``plot`` are the numbers ``1,2, ..., n`` for the x-axis, a vector ``ϵ`` for the y-axis, and (optional) settings

-The function ``randn(n)`` returns a column vector ``n`` random draws from a normal distribution mean 0 and variance 1
+The function ``randn(n)`` returns a column vector with *n* random draws from a normal distribution mean 0 and variance 1


The Markdown and rST syntax actually agree on this one (italics)

arnavs · 2018-11-07T22:36:37Z

rst_files/julia_by_example.rst

@@ -591,7 +587,7 @@ Passing a Function

 The chief issue is that the algorithm (finding a fixed point) is reusable and generic, while the function we calculate ``p + β * v`` is specific to our problem

-A key feature of languages like Julia, is the ability to efficiently handle functions passed to other functions
+A key feature of languages like Julia is the ability to efficiently handle functions passed to other functions:


Suggested change

A key feature of languages like Julia is the ability to efficiently handle functions passed to other functions:

A key feature of languages like Julia is the ability to efficiently handle functions passed to other functions

arnavs · 2018-11-07T22:36:48Z

rst_files/julia_by_example.rst


-Furthermore, a default value may be enabled--so the named parameter ``iv`` is required while ``tolerance`` and ``maxiter`` have default values
+Furthermore, a default value may be enabled. So the named parameter ``iv`` is required while ``tolerance`` and ``maxiter`` have default values


Suggested change

Furthermore, a default value may be enabled. So the named parameter ``iv`` is required while ``tolerance`` and ``maxiter`` have default values

Furthermore, a default value may be enabled

So the named parameter ``iv`` is required while ``tolerance`` and ``maxiter`` have default values

arnavs · 2018-11-07T22:37:03Z

rst_files/julia_by_example.rst


-The return type of the function also has named fields, ``value, normdiff,`` and ``iter``--all accessed intuitively using ``.``
+The return type of the function also has named fields, ``value, normdiff,`` and ``iter``. All accessed intuitively using ``.``


Suggested change

The return type of the function also has named fields, ``value, normdiff,`` and ``iter``. All accessed intuitively using ``.``

The return type of the function also has named fields, ``value, normdiff,`` and ``iter``

All can be accessed intuitively using ``.``

arnavs · 2018-11-07T22:37:12Z

rst_files/julia_by_example.rst

@@ -675,7 +671,7 @@ To show the flexibilty of this code, we can use it to find a fixed-point of the
 Using a Package
 ----------------------------

-But best of all is to avoid writing code altogether
+But best of all is to avoid writing code altogether:


Suggested change

But best of all is to avoid writing code altogether:

But best of all is to avoid writing code altogether

arnavs · 2018-11-07T22:37:57Z

rst_files/julia_by_example.rst


-In particular, we can use the ``Anderson acceleration`` with a memory of 5 iterations, by changing a setting
+For instance, we can use the ``Anderson Acceleration`` (it is a method to calculate fixed points) with a memory of 5 iterations by changing a setting:


Suggested change

For instance, we can use the ``Anderson Acceleration`` (it is a method to calculate fixed points) with a memory of 5 iterations by changing a setting:

The default is an algorithm called ``Anderson acceleration``, with a memory parameter of 5

pooya changes

6e91481

pooyaravari requested a review from arnavs November 2, 2018 22:07

QA julia_by_example

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jlperla reviewed Nov 4, 2018

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pooyaravari added 8 commits November 3, 2018 21:59

Revert "Fixed typo"

9c9bbaa

This reverts commit 849efa0.

some reverting stuff

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Quality Assurance

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Merge

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merge-second

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wrong

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Quality_Assurance_New

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correction

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arnavs approved these changes Nov 7, 2018

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arnavs self-assigned this Nov 7, 2018

Arnav Sood added 5 commits November 7, 2018 14:29

Update rst_files/julia_by_example.rst

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Merge branch 'master' into pooya

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arnavs merged commit ecd2c4e into master Nov 7, 2018

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pooya changes #246

pooya changes #246

pooyaravari commented Nov 2, 2018

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	In particular, we assume you have some familiarity with fundamental programming concepts such as:
	In particular, we assume you have some familiarity with fundamental programming concepts such as


		In particular, the easiest way to install and precompile all of the Julia packages used in the QuantEcon notes is to go ``] add InstantiateFromURL`` and then work in a Jupyter notebook, as described :ref:`here <jl_jupyter>`
		In particular, the easiest way to install and precompile all of the Julia packages used in the QuantEcon notes is to go ``] add InstantiateFromURL`` and then work in a Jupyter notebook, as described [here](getting_started.ipynb)


		Furthermore, a default value may be enabled--so the named parameter ``iv`` is required while ``tolerance`` and ``maxiter`` have default values
		Furthermore, a default value may be enabled. So the named parameter ``iv`` is required while ``tolerance`` and ``maxiter`` have default values


		The return type of the function also has named fields, ``value, normdiff,`` and ``iter``--all accessed intuitively using ``.``
		The return type of the function also has named fields, ``value, normdiff,`` and ``iter``. All accessed intuitively using ``.``


		In particular, we can use the ``Anderson acceleration`` with a memory of 5 iterations, by changing a setting
		For instance, we can use the ``Anderson Acceleration`` (it is a method to calculate fixed points) with a memory of 5 iterations by changing a setting:

	* For some notebooks, enable content with "Trust" on the command tab of Jupyter lab (It is not clear!)
	* For some notebooks, enable content with "Trust" on the command tab of Jupyter lab

	#. use the ``InstantiateFromURL`` package (like below):
	#. use the ``InstantiateFromURL`` package

	A key feature of languages like Julia is the ability to efficiently handle functions passed to other functions:
	A key feature of languages like Julia is the ability to efficiently handle functions passed to other functions

	But best of all is to avoid writing code altogether:
	But best of all is to avoid writing code altogether

	For instance, we can use the ``Anderson Acceleration`` (it is a method to calculate fixed points) with a memory of 5 iterations by changing a setting:
	The default is an algorithm called ``Anderson acceleration``, with a memory parameter of 5

pooya changes #246

pooya changes #246

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pooyaravari commented Nov 2, 2018

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