| Author: | Hans Petter Langtangen |
|---|---|
| Date: | Jun 29, 2013 |
Table of Contents
WARNING: This quick reference is very incomplete!
Mission. Enable writing documentation with much mathematics and computer code once, in one place and include it in traditional LaTeX books, thesis, and reports, and without extra efforts also make professionally looking web versions with Sphinx or HTML. Other outlets include Google's blogger.com, Wikipedia/Wikibooks, IPython notebooks, plus a wide variety of formats for documents without mathematics and code.
Doconce currently translates files to the following formats:
- LaTeX (format latex and pdflatex)
- HTML (format html)
- reStructuredText (format rst)
- plain (untagged) ASCII (format plain)
- Sphinx (format sphinx)
- IPython notebook (format ipynb)
- MediaWiki (format mwiki)
- (Pandoc extended) Markdown (format pandoc)
- Googlecode wiki (format gwiki)
- Creoloe wiki (format cwiki)
- Epydoc (format epydoc)
- StructuredText (format st)
For documents with much code and mathematics, the best (and most supported) formats are latex, pdflatex, sphinx, and html; and to a slightly less extent mwiki and pandoc. The HTML format supports blogging on Google and Wordpress.
The file .doconce-mode.el in the Doconce source distribution gives a "Doconce Editing Mode" in Emacs. Store the file in the home directory and add (load-file "~/.doconce-mode.el") to the .emacs file.
Besides syntax highlighting of Doconce documents, this Emacs mode provides a lot of shortcuts for setting up many elements in a document:
| Emacs key | Action |
|---|---|
| Ctrl+c f | figure |
| Ctrl+c v | movie/video |
| Ctrl+c h1 | heading level 1 (section/h1) |
| Ctrl+c h2 | heading level 2 (subsection/h2) |
| Ctrl+c h3 | heading level 2 (subsection/h3) |
| Ctrl+c hp | heading for paragraph |
| Ctrl+c me | math environment: !bt equation !et |
| Ctrl+c ma | math environment: !bt align !et |
| Ctrl+c ce | code environment: !bc !ec |
| Ctrl+c cf | code from file: @@@CODE |
| Ctrl+c table2 | table with 2 columns |
| Ctrl+c table3 | table with 3 columns |
| Ctrl+c table4 | table with 4 columns |
| Ctrl+c exer | exercise outline |
| Ctrl+c slide | slide outline |
| Ctrl+c help | print this table |
A typical example of giving a title, a set of authors, a date, and an optional table of contents reads:
TITLE: On an Ultimate Markup Language AUTHOR: H. P. Langtangen at Center for Biomedical Computing, Simula Research Laboratory & Dept. of Informatics, Univ. of Oslo AUTHOR: Kaare Dump Email<EMAIL_ADDRESS>at Segfault, Cyberspace Inc. AUTHOR: A. Dummy Author DATE: today TOC: on
The entire title must appear on a single line. The author syntax is:
name Email<EMAIL_ADDRESS>at institution1 & institution2
where the email is optional, the "at" keyword is required if one or more institutions are to be specified, and the & keyword separates the institutions (the keyword and works too). Each author specification must appear on a single line. When more than one author belong to the same institution, make sure that the institution is specified in an identical way for each author.
The date can be set as any text different from today if not the current date is wanted, e.g., Feb 22, 2016.
The table of contents is removed by writing TOC: off.
| Section type | Syntax |
|---|---|
| chapter | ========= Heading ======== (9 =) |
| section | ======= Heading ======= (7 =) |
| subsection | ===== Heading ===== (5 =) |
| subsubsection | === Heading === (3 =) |
| paragraph | __Heading.__ (2 _) |
| abstract | __Abstract.__ Running text... |
| appendix | ======= Appendix: heading ======= (7 =) |
| appendix | ===== Appendix: heading ===== (5 =) |
| exercise | ======= Exercise: heading ======= (7 =) |
| exercise | ===== Exercise: heading ===== (5 =) |
Note that abstracts are recognized by starting with __Abstract.__ or __Summary.__ at the beginning of a line and ending with three or more = signs of the next heading.
The Exercise: keyword kan be substituted by Problem: or Project:. A recommended convention is that an exercise is tied to the text, a problem can stand on its own, and a project is a comprehensive problem.
Words surrounded by * are emphasized: *emphasized words* becomes emphasized words. Similarly, an underscore surrounds words that appear in boldface: _boldface_ becomes boldface. Colored words are also possible: the text:
`color{red}{two red words}`
becomes two red words.
There are three types of lists: bullet lists, where each item starts with *, enumeration lists, where each item starts with o and gets consqutive numbers, and description lists, where each item starts with - followed by a keyword and a colon:
Here is a bullet list: * item1 * item2 * subitem1 of item2 * subitem2 of item2 * item3 Note that sublists are consistently indented by one or more blanks.. Here is an enumeration list: o item1 o item2 may appear on multiple lines o subitem1 of item2 o subitem2 of item2 o item3 And finally a description list: - keyword1: followed by some text over multiple lines - keyword2: followed by text on the next line - keyword3: and its description may fit on one line
The code above follows.
Here is a bullet list:
- item1
- item2
- subitem1 of item2
- subitem2 of item2
- item3
Note that sublists are indented. Here is an enumeration list:
- subitem1 of item2
- subitem2 of item2
And finally a description list:
- keyword1:
- followed by some text over multiple lines
- keyword2:
- followed by text on the next line
- keyword3:
- and its description may fit on one line
Lines starting with # are treated as comments in the document and translated to the proper syntax for comments in the output document. Such comment lines should not appear before LaTeX math blocks, verbatim code blocks, or lists if the formats rst and sphinx are desired.
Comment lines starting with ## are not propagated to the output document and can be used for comments that are only interest in the Doconce file.
Large portions of text can be left out using Preprocess. Just place # #ifdef EXTRA and # #endif around the text. The command line option -DEXTRA will bring the text alive again.
When using the Mako preprocessor one can also place comments in the Doconce source file that will be removed by Mako before Doconce starts processing the file.
Inline comments meant as messages or notes, to authors during development in particular, are enabled by the syntax:
[name: running text]
where name is the name or ID of an author or reader making the comment, and running text is the comment. Here goes an example. (hpl 1: There must be a space after the colon, but the running text can occupy multiple lines.) The inline comments have simple typesetting in most formats, typically boldface name and everything surrounded by parenthesis, but with LaTeX output and the -DTOTONOTES option to ptex2tex or doconce ptex2tex, colorful margin or inline boxes (using the todonotes package) make it very easy to spot the comments.
Running:
doconce format html mydoc.do.txt --skip_inline_comments
removes all inline comments from the output. This feature makes it easy to turn on and off notes to authors during the development of the document.
All inline comments to readers can also be physically removed from the Doconce source by:
doconce remove_inline_comments mydoc.do.txt
Inline verbatim code is typeset within back-ticks, as in:
Some sentence with `words in verbatim style`.
resulting in Some sentence with words in verbatim style.
Multi-line blocks of verbatim text, typically computer code, is typeset in between !bc xxx and !ec directives, which must appear on the beginning of the line. A specification xxx indicates what verbatim formatting style that is to be used. Typical values for xxx are nothing, cod for a code snippet, pro for a complete program, sys for a terminal session, dat for a data file (or output from a program), Xpro or Xcod for a program or code snipped, respectively, in programming X, where X may be py for Python, cy for Cython, sh for Bash or other Unix shells, f for Fortran, c for C, cpp for C++, m for MATLAB, pl for Perl. For output in latex one can let xxx reflect any defined verbatim environment in the ptex2tex configuration file (.ptex2tex.cfg). For sphinx output one can insert a comment:
# sphinx code-blocks: pycod=python cod=fortran cppcod=c++ sys=console
that maps environments (xxx) onto valid language types for Pygments (which is what sphinx applies to typeset computer code).
The xxx specifier has only effect for latex and sphinx output. All other formats use a fixed monospace font for all kinds of verbatim output.
Here is an example of computer code (see the source of this document for exact syntax):
from numpy import sin, cos, exp, pi def f(x, y, z, t): return exp(-t)*sin(pi*x)*sin(pi*y)*cos(2*pi*z)
Computer code can also be copied from a file:
@@@CODE doconce_program.sh @@@CODE doconce_program.sh fromto: doconce clean@^doconce split_rst @@@CODE doconce_program.sh from-to: doconce clean@^doconce split_rst
The @@@CODE identifier must appear at the very beginning of the line. The first specification copies the complete file doconce_program.sh. The second specification copies from the first line matching the regular expression doconce clean up to, but not including the line matching the regular expression ^doconce split_rst. The third specification behaves as the second, but the line matching the first regular expression is not copied (aimed at copying text between begin-end comment pair in the file).
The copied line from file are in this example put inside !bc shpro and !ec directives, if a complete file is copied, while the directives become !bc shcod and !ec when a code snippet is copied from file. In general, for a filename extension .X, the environment becomes !bc Xpro or !bc Xcod for a complete program or snippet, respectively. The enivorments (Xcod and Xpro) are only active for latex and sphinx outout.
Important warnings:
- A code block must come after some plain sentence (at least for successful output in reStructredText), not directly after a section/paragraph heading, table, comment, figure, or movie.
- Verbatim code blocks inside lists can be ugly typeset in some output formats. A more robust approach is to replace the list by paragraphs with headings.
Doconce supports inline mathematics and blocks of mathematics, using standard LaTeX syntax. The output formats html, sphinx, latex, pdflatex`, pandoc, and mwiki work with this syntax while all other formats will just display the raw LaTeX code.
Inline expressions are written in the standard LaTeX way with the mathematics surrounded by dollar signs, as in Ax=b. To help increase readability in other formats than sphinx, latex, and pdflatex, inline mathematics may have a more human readable companion expression. The syntax is like:
$\sin(\norm{\bf u})$|$sin(||u||)$
That is, the LaTeX expression appears to the left of a vertical bar (pipe symbol) and the more readable expression appears to the right. Both expressions are surrounded by dollar signs.
Blocks of LaTeX mathematics are written within !bt and !et (begin/end TeX) directives starting on the beginning of a line:
!bt \begin{align*} \nabla\cdot \pmb{u} &= 0,\\ \nabla\times \pmb{u} &= 0. \end{align*} !et
This LaTeX code gets rendered as:
\begin{align*} \nabla\cdot \pmb{u} &= 0,\\ \nabla\times \pmb{u} &= 0. \end{align*}
Here is a single equation:
!bt \[ \frac{\partial\pmb{u}}{\partial t} + \pmb{u}\cdot\nabla\pmb{u} = 0.\] !et
which results in:
\[ \frac{\partial\pmb{u}}{\partial t} + \pmb{u}\cdot\nabla\pmb{u} = 0.\]
Any LaTeX syntax is accepted, but if output in the sphinx, pandoc, mwiki, html, or ipynb formats is also important, one should follow these rules:
- Use only the equation environments \[, \], equation, equation*, align, and align*.
- MediaWiki (mwiki) does not support references to equations.
(Doconce performs extensions to sphinx and other formats such that labels in align environments work well.)
Note
LaTeX supports lots of fancy formatting, for example, multiple plots in the same figure, footnotes, margin notes, etc. Allowing other output formats, such as sphinx, makes it necessary to only utilze very standard LaTeX and avoid, for instance, more than one plot per figure. However, one can use preprocessor if-tests on the format (typically if FORMAT in ("latex", "pdflatex")) to include special code for latex and pdflatex output and more straightforward typesetting for other formats. In this way, one can also allow advanced LaTeX features and fine tuning of resulting PDF document.
LaTeX Newcommands. The author can define newcommand statements in files with names newcommands*.tex. Such commands should only be used for mathematics (other LaTeX constructions are only understood by LaTeX itself). The convention is that newcommands_keep.tex contains the newcommands that are kept in the document, while those in newcommands_replace.tex will be replaced by their full LaTeX code. This conventions helps make readable documents in formats without LaTeX support. For html, sphinx, latex, pdflatex, mwiki, ipynb, and pandoc, the mathematics in newcommands is rendered nicely anyway.
Links use either a link text or the raw URL:
Here is some "some link text": "http://some.net/address" (as in "search google": "http://google.com") or just the raw address: URL: "http://google.com". Links to files typeset in verbatim mode applies backtics: "`myfile.py`": "http://some.net/some/place/myfile.py". Mail addresses works too: send problems to<EMAIL_ADDRESS><EMAIL_ADDRESS>or just "send mail"<EMAIL_ADDRESS>Figures and movies have almost equal syntax:
FIGURE: [relative/path/to/figurefile, width=500 frac=0.8] Here goes the caption which must be on a single line. label{some:fig:label} MOVIE: [relative/path/to/moviefile, width=500] Here goes the caption which must be on a single line. label{some:fig:label}
Note three important syntax details:
- A mandatory comma after the figure/movie filename,
- no comments between width, height, and frac and no spaces around the = characters,
- all of the command must appear on a single line,
- there must be a blank line after the command.
The figure file can be listed without extension. Doconce will then find the version of the file with the most appropriate extension for the chosen output format. If not suitable version is found, Doconce will convert another format to the needed one.
The caption is optional. If omitted, the figure will be inlined (meaning no use of any figure environment in HTML or LaTeX formats). The width and height parameters affect HTML formats (html, rst, sphinx), while frac is the width of the image as a fraction of the total text width in the latex and pdflatex formats.
Movie files can either be a video or a wildcard expression for a series of frames. In the latter case, a simple device in an HTML page will display the individual frame files as a movie.
Combining several image files into one can be done by the:
doconce combine_images image1 image2 ... output_image
This command applies montage or PDF-based tools to combine the images to get the highest quality.
YouTube and Vimeo movies will be embedded in html and sphinx documents and otherwise be represented by a link. The syntax is:
MOVIE: [http://www.youtube.com/watch?v=_O7iUiftbKU, width=420 height=315] YouTube movie. MOVIE: [http://vimeo.com/55562330, width=500 height=278] Vimeo movie.
The latter results in
Vimeo movie.The table in the section Section Types was written with this syntax:
|----------------c--------|------------------c--------------------| | Section type | Syntax | |----------------l--------|------------------l--------------------| | chapter | `========= Heading ========` (9 `=`) | | section | `======= Heading =======` (7 `=`) | | subsection | `===== Heading =====` (5 `=`) | | subsubsection | `=== Heading ===` (3 `=`) | | paragraph | `__Heading.__` (2 `_`) | |-----------------------------------------------------------------|
Note that
- Each line begins and ends with a vertical bar (pipe symbol).
- Column data are separated by a vertical bar (pipe symbol).
- There may be horizontal rules, i.e., lines with dashes for indicating the heading and the end of the table, and these may contain characters 'c', 'l', or 'r' for how to align headings or columns. The first horizontal rule may indicate how to align headings (center, left, right), and the horizontal rule after the heading line may indicate how to align the data in the columns (center, left, right).
- If the horizontal rules are without alignment information there should be no vertical bar (pipe symbol) between the columns. Otherwise, such a bar indicates a vertical bar between columns in LaTeX.
- Many output formats are so primitive that heading and column alignment have no effect.
The command-line option --tables2csv (to doconce format) makes Doconce dump each table to CSV format in a file table_X.csv, where X is the table number. This feature makes it easy to load tables into spreadsheet programs for further analysis.
The notion of labels and references (as well as bibliography and index) is adopted from LaTeX with a very similar syntax. As in LaTeX, a label can be inserted anywhere, using the syntax:
label{name}
with no backslash preceding the label keyword. It is common practice to choose name as some hierarchical name, say a:b:c, where a and b indicate some abbreviations for a section and/or subsection for the topic and c is some name for the particular unit that has a label.
A reference to the label name is written as:
ref{name}
again with no backslash before ref.
Use labels for sections and equations only, and preceed the reference by "Section" or "Chapter", or in case of an equation, surround the reference by parenthesis.
Single citations are written as:
cite{name}
where name is a logical name of the reference (again, LaTeX writers must not insert a backslash). Bibliography citations often have name on the form Author1_Author2_YYYY, Author_YYYY, or Author1_etal_YYYY, where YYYY is the year of the publication. Multiple citations at once is possible by separating the logical names by comma:
cite{name1,name2,name3}
The bibliography is specified by a line BIBFILE: papers.pub, where papers.pub is a publication database in the Publish format. BibTeX .bib files can easily be combined to a Publish database (which Doconce needs to create bibliographies in other formats than LaTeX).
There is a generalized referencing feature in Doconce that allows a reference with ref to have one formulation if the label is in the same document and another formulation if the reference is to an item in an external document. This construction makes it easy to work with many small, independent documents in parallel with a book assembly of some of the small elements. The syntax of a generalized reference is:
ref[internal][cite][external] # Example: As explained in ref[Section ref{subsec:ex}][in cite{testdoc:12}][a "section": "testdoc.html#___sec2" in the document "A Document for Testing Doconce": "testdoc.html" cite{testdoc:12}], Doconce documents may include movies.
The output from a generalized reference is the text internal if all label`_` references in ``internal are references to labels in the present document. Otherwise, if cite is non-empty and the format is latex or pdflatex one assumes that the references in internal are to external documents declared by a comment line # Externaldocuments: testdoc, mydoc (usually after the title, authors, and date). In this case the output text is internal cite and the LaTeX package xr is used to handle the labels in the external documents. If none of the two situations above applies, the external text will be the output.
Doconce supports creating an index of keywords. A certain keyword is registered for the index by a syntax like (no backslash!):
index{name}
It is recommended to place any index of this type outside running text, i.e., after (sub)section titles and in the space between paragraphs. Index specifications placed right before paragraphs also gives the doconce source code an indication of the content in the forthcoming text. The index is only produced for the latex, pdflatex, rst, and sphinx formats.
The doconce program can be used for a number of purposes besides transforming a .do.txt file to some format. Here is the list of capabilities:
Usage: doconce command [optional arguments] commands: format help sphinx_dir subst replace replace_from_file clean spellcheck ptex2tex expand_commands combine_images guess_encoding change_encoding gwiki_figsubst md2html remove_inline_comments grab remove remove_exercise_answers split_rst split_html slides_html slides_beamer latin2html latex_header latex_footer bbl2rst html_colorbullets list_labels teamod sphinxfix_localURLs make_figure_code_links latex_exercise_toc insertdocstr old2new_format latex2doconce latex_dislikes pygmentize makefile diff gitdiff fix_bibtex4publish csv2table # transform doconce file to another format doconce format html|latex|pdflatex|rst|sphinx|plain|gwiki|mwiki|cwiki|pandoc|st|epytext file.do.txt # substitute a phrase by another using regular expressions doconce subst [-s -m -x --restore] regex-pattern regex-replacement file1 file2 ... (-s is the re.DOTALL modifier, -m is the re.MULTILINE modifier, -x is the re.VERBOSE modifier, --restore copies backup files back again) # replace a phrase by another literally doconce replace from-text to-text file1 file2 ... (exact text substutition) # doconce replace using from and to phrases from file doconce replace_from_file file-with-from-to file1 file2 ... (exact text substitution, but a set of from-to relations) # gwiki format requires substitution of figure file names by URLs doconce gwiki_figsubst file.gwiki URL-of-fig-dir # remove all inline comments in a doconce file doconce remove_inline_comments file.do.txt # create a directory for the sphinx format doconce sphinx_dir author='John Doe' title='Long title' \ short_title="Short title" version=0.1 \ dirname=sphinx-rootdir theme=default logo=mylogo.png \ do_file [do_file2 do_file3 ...] (requires sphinx version >= 1.1) # replace latex-1 (non-ascii) characters by html codes doconce latin2html file.html # walk through a directory tree and insert doconce files as # docstrings in *.p.py files doconce insertdocstr rootdir # remove all files that the doconce format can regenerate doconce clean # print the header (preamble) for latex file doconce latex_header # print the footer for latex files doconce latex_footer # change encoding doconce change_encoding utf-8 latin1 filename # guess the encoding in a text doconce guess_encoding filename # transform a .bbl file to a .rst file with reST bibliography format doconce bbl2rst file.bbl # split a sphinx/rst file into parts doconce format sphinx complete_file doconce split_rst complete_file # !split delimiters doconce sphinx_dir complete_file python automake_sphinx.py # edit URLs to local files and place them in _static doconce sphinxfix_local_URLs file.rst # split an html file into parts according to !split commands doconce split_html complete_file.html # create HTML slides from a (doconce) html file doconce slides_html slide_type complete_file.html # create LaTeX Beamer slides from a (doconce) latex/pdflatex file doconce slides_beamer complete_file.tex # replace bullets in lists by colored bullets doconce html_colorbullets file1.html file2.html ... # grab selected text from a file doconce grab --from[-] from-text [--to[-] to-text] somefile # remove selected text from a file doconce remove --from[-] from-text [--to[-] to-text] somefile # run spellcheck on a set of files doconce spellcheck [-d .mydict.txt] *.do.txt # transform ptex2tex files (.p.tex) to ordinary latex file # and manage the code environments doconce ptex2tex mydoc -DMINTED pycod=minted sys=Verbatim \ dat=\begin{quote}\begin{verbatim};\end{verbatim}\end{quote} # make HTML file via pandoc from Markdown (.md) file doconce md2html file # make LaTeX file via pandoc from Markdown (.md) file doconce md2latex file # expand short cut commands to full form in files doconce expand_commands file1 file2 ... # combine several images into one doconce combine_images image1 image2 ... output_file # insert a table of exercises in a latex file myfile.p.tex doconce latex_exercise_toc myfile # list all labels in a document (for purposes of cleaning them up) doconce list_labels myfile # translate a latex document to doconce (requires usually manual fixing) doconce latex2doconce latexfile # check if there are problems with translating latex to doconce doconce latex_dislikes latexfile # typeset a doconce document with pygments (for pretty print of doconce itself) doconce pygmentize myfile [pygments-style] # generate a make.sh script for translating a doconce file to various formats doconce makefile docname doconcefile [html sphinx pdflatex ...] # fix common problems in bibtex files for publish import doconce fix_bibtex4publish file1.bib file2.bib ... # find differences between two files doconce diff file1.do.txt file2.do.txt [diffprog] (diffprog can be difflib, diff, pdiff, latexdiff, kdiff3, diffuse, ...) # find differences between the last two Git versions of several files doconce gitdiff file1 file2 file3 ... # convert csv file to doconce table format doconce csv2table somefile.csv
Doconce supports Exercise, Problem, Project, and Example. These are typeset as ordinary sections and referred to by their section labels. Exercise, problem, project, or example sections contains certain elements:
- a headline at the level of a subsection containing one of the words "Exercise:", "Problem:", "Project:", or "Example:", followed by a title (required)
- a label (optional)
- a solution file (optional)
- name of file with a student solution (optional)
- main exercise text (required)
- a short answer (optional)
- a full solution (optional)
- one or more hints (optional)
- one or more subexercises (subproblems, subprojects), which can also contain a text, a short answer, a full solution, name student file to be handed in, and one or more hints (optional)
A typical sketch of a a problem without subexercises goes as follows:
===== Problem: Derive the Formula for the Area of an Ellipse ===== label{problem:ellipsearea1} file=ellipse_area.pdf solution=ellipse_area1_sol.pdf Derive an expression for the area of an ellipse by integrating the area under a curve that defines half of the allipse. Show each step in the mathematical derivation. !bhint Wikipedia has the formula for the curve. !ehint !bhint "Wolframalpha": "http://wolframalpha.com" can perhaps compute the integral. !ehint
If the exercise type (Exercise, Problem, Project, or Example) is enclosed in braces, the type is left out of the title in the output. For example, the if the title line above reads:
===== {Problem}: Derive the Formula for the Area of an Ellipse =====
the title becomes just "Derive the ...".
An exercise with subproblems, answers and full solutions has this setup-up:
===== Exercise: Determine the Distance to the Moon ===== label{exer:moondist} Intro to this exercise. Questions are in subexercises below. !bsubex Subexercises are numbered a), b), etc. file=subexer_a.pdf !bans Short answer to subexercise a). !eans !bhint First hint to subexercise a). !ehint !bhint Second hint to subexercise a). !ehint !esubex !bsubex Here goes the text for subexercise b). file=subexer_b.pdf !bhint A hint for this subexercise. !ehint !bsol Here goes the solution of this subexercise. !esol !esubex !bremarks At the very end of the exercise it may be appropriate to summarize and give some perspectives. The text inside the !bremarks-!eremarks directives is always typeset at the end of the exercise. !eremarks !bsol Here goes a full solution of the whole exercise. !esol
By default, answers, solutions, and hints are typeset as paragraphs. The command-line arguments --without_answers and --without_solutions turn off output of answers and solutions, respectively, except for examples.
Doconce environments start with !benvirname and end with !eenvirname, where envirname is the name of the environment. Here is a listing of the environments:
c: computer code (or verbatim text)
t: math blocks with LaTeX syntax
subex: sub-exercise
ans: short answer to exercise or sub-exercise
sol: full solution to exercise or sub-exercise
quote: indented text
- notice, summary, warning, question, hint: admonition boxes with
custom title, special icon, and (frequently) background color
pop: text to gradually pop up in slide presentations
slidecell: indication of cells in a grid layout for elements on a slide
Doconce documents may utilize a preprocessor, either preprocess and/or mako. The former is a C-style preprocessor that allows if-tests and including other files (but not macros with arguments). The mako preprocessor is much more advanced - it is actually a full programming language, very similar to Python.
The command doconce format first runs preprocess and then mako. Here is a typical example on utilizing preprocess to include another document, "comment out" a large portion of text, and to write format-specific constructions:
# #include "myotherdoc.do.txt" # #if FORMAT in ("latex", "pdflatex") \begin{table} \caption{Some words... label{mytab}} \begin{tabular}{lrr} \hline\noalign{\smallskip} \multicolumn{1}{c}{time} & \multicolumn{1}{c}{velocity} & \multicolumn{1}{c}{acceleration} \\ \hline 0.0 & 1.4186 & -5.01 \\ 2.0 & 1.376512 & 11.919 \\ 4.0 & 1.1E+1 & 14.717624 \\ \hline \end{tabular} \end{table} # #else |--------------------------------| |time | velocity | acceleration | |--l--------r-----------r--------| | 0.0 | 1.4186 | -5.01 | | 2.0 | 1.376512 | 11.919 | | 4.0 | 1.1E+1 | 14.717624 | |--------------------------------| # #endif # #ifdef EXTRA_MATERIAL ....large portions of text... # #endif
With the mako preprocessor the if-else tests have slightly different syntax. An example document contains some illustrations on how to utilize mako (clone the GitHub project and examine the Doconce source and the doc/src/make.sh script).
- Excellent "Sphinx Tutorial" by C. Reller: "http://people.ee.ethz.ch/~creller/web/tricks/reST.html"


Python ApplicationsPython is known for its general purpose nature that makes it applicable in almost each domain of software development. Python as a whole can be used in any sphere of development. Here, we are specifing applications areas where python can be applied. 1) Web ApplicationsWe can use Python to develop web applications. It provides libraries to handle internet protocols such as HTML and XML, JSON, Email processing, request, beautifulSoup, Feedparser etc. It also provides Frameworks such as Django, Pyramid, Flask etc to design and delelop web based applications. Some important developments are: PythonWikiEngines, Pocoo, PythonBlogSoftware etc. 2) Desktop GUI ApplicationsPython provides Tk GUI library to develop user interface in python based application. Some other useful toolkits wxWidgets, Kivy, pyqt that are useable on several platforms. The Kivy is popular for writing multitouch applications. 3) Software DevelopmentPython is helpful for software development process. It works as a support language and can be used for build control and management, testing etc. 4) Scientific and NumericPython is popular and widely used in scientific and numeric computing. Some useful library and package are SciPy, Pandas, IPython etc. SciPy is group of packages of engineering, science and mathematics. 5) Business ApplicationsPython is used to build Bussiness applications like ERP and e-commerce systems. Tryton is a high level application platform. 6) Console Based ApplicationWe can use Python to develop console based applications. For example: IPython. 7) Audio or Video based ApplicationsPython is awesome to perform multiple tasks and can be used to develop multimedia applications. Some of real applications are: TimPlayer, cplay etc. 8) 3D CAD ApplicationsTo create CAD application Fandango is a real application which provides full features of CAD. 9) Enterprise ApplicationsPython can be used to create applications which can be used within an Enterprise or an Organization. Some real time applications are: OpenErp, Tryton, Picalo etc. 10) Applications for ImagesUsing Python several application can be developed for image. Applications developed are: VPython, Gogh, imgSeek etc. There are several such applications which can be developed using Python
Next TopicHow To Install Python
|
Python ApplicationsPython is known for its general purpose nature that makes it applicable in almost each domain of software development. Python as a whole can be used in any sphere of development. Here, we are specifing applications areas where python can be applied. 1) Web ApplicationsWe can use Python to develop web applications. It provides libraries to handle internet protocols such as HTML and XML, JSON, Email processing, request, beautifulSoup, Feedparser etc. It also provides Frameworks such as Django, Pyramid, Flask etc to design and delelop web based applications. Some important developments are: PythonWikiEngines, Pocoo, PythonBlogSoftware etc. 2) Desktop GUI ApplicationsPython provides Tk GUI library to develop user interface in python based application. Some other useful toolkits wxWidgets, Kivy, pyqt that are useable on several platforms. The Kivy is popular for writing multitouch applications. 3) Software DevelopmentPython is helpful for software development process. It works as a support language and can be used for build control and management, testing etc. 4) Scientific and NumericPython is popular and widely used in scientific and numeric computing. Some useful library and package are SciPy, Pandas, IPython etc. SciPy is group of packages of engineering, science and mathematics. 5) Business ApplicationsPython is used to build Bussiness applications like ERP and e-commerce systems. Tryton is a high level application platform. 6) Console Based ApplicationWe can use Python to develop console based applications. For example: IPython. 7) Audio or Video based ApplicationsPython is awesome to perform multiple tasks and can be used to develop multimedia applications. Some of real applications are: TimPlayer, cplay etc. 8) 3D CAD ApplicationsTo create CAD application Fandango is a real application which provides full features of CAD. 9) Enterprise ApplicationsPython can be used to create applications which can be used within an Enterprise or an Organization. Some real time applications are: OpenErp, Tryton, Picalo etc. 10) Applications for ImagesUsing Python several application can be developed for image. Applications developed are: VPython, Gogh, imgSeek etc. There are several such applications which can be developed using Python
Next TopicHow To Install Python
|
Python ApplicationsPython is known for its general purpose nature that makes it applicable in almost each domain of software development. Python as a whole can be used in any sphere of development. Here, we are specifing applications areas where python can be applied. 1) Web ApplicationsWe can use Python to develop web applications. It provides libraries to handle internet protocols such as HTML and XML, JSON, Email processing, request, beautifulSoup, Feedparser etc. It also provides Frameworks such as Django, Pyramid, Flask etc to design and delelop web based applications. Some important developments are: PythonWikiEngines, Pocoo, PythonBlogSoftware etc. 2) Desktop GUI ApplicationsPython provides Tk GUI library to develop user interface in python based application. Some other useful toolkits wxWidgets, Kivy, pyqt that are useable on several platforms. The Kivy is popular for writing multitouch applications. 3) Software DevelopmentPython is helpful for software development process. It works as a support language and can be used for build control and management, testing etc. 4) Scientific and NumericPython is popular and widely used in scientific and numeric computing. Some useful library and package are SciPy, Pandas, IPython etc. SciPy is group of packages of engineering, science and mathematics. 5) Business ApplicationsPython is used to build Bussiness applications like ERP and e-commerce systems. Tryton is a high level application platform. 6) Console Based ApplicationWe can use Python to develop console based applications. For example: IPython. 7) Audio or Video based ApplicationsPython is awesome to perform multiple tasks and can be used to develop multimedia applications. Some of real applications are: TimPlayer, cplay etc. 8) 3D CAD ApplicationsTo create CAD application Fandango is a real application which provides full features of CAD. 9) Enterprise ApplicationsPython can be used to create applications which can be used within an Enterprise or an Organization. Some real time applications are: OpenErp, Tryton, Picalo etc. 10) Applications for ImagesUsing Python several application can be developed for image. Applications developed are: VPython, Gogh, imgSeek etc. There are several such applications which can be developed using Python
Next TopicHow To Install Python
|
Python ApplicationsPython is known for its general purpose nature that makes it applicable in almost each domain of software development. Python as a whole can be used in any sphere of development. Here, we are specifing applications areas where python can be applied. 1) Web ApplicationsWe can use Python to develop web applications. It provides libraries to handle internet protocols such as HTML and XML, JSON, Email processing, request, beautifulSoup, Feedparser etc. It also provides Frameworks such as Django, Pyramid, Flask etc to design and delelop web based applications. Some important developments are: PythonWikiEngines, Pocoo, PythonBlogSoftware etc. 2) Desktop GUI ApplicationsPython provides Tk GUI library to develop user interface in python based application. Some other useful toolkits wxWidgets, Kivy, pyqt that are useable on several platforms. The Kivy is popular for writing multitouch applications. 3) Software DevelopmentPython is helpful for software development process. It works as a support language and can be used for build control and management, testing etc. 4) Scientific and NumericPython is popular and widely used in scientific and numeric computing. Some useful library and package are SciPy, Pandas, IPython etc. SciPy is group of packages of engineering, science and mathematics. 5) Business ApplicationsPython is used to build Bussiness applications like ERP and e-commerce systems. Tryton is a high level application platform. 6) Console Based ApplicationWe can use Python to develop console based applications. For example: IPython. 7) Audio or Video based ApplicationsPython is awesome to perform multiple tasks and can be used to develop multimedia applications. Some of real applications are: TimPlayer, cplay etc. 8) 3D CAD ApplicationsTo create CAD application Fandango is a real application which provides full features of CAD. 9) Enterprise ApplicationsPython can be used to create applications which can be used within an Enterprise or an Organization. Some real time applications are: OpenErp, Tryton, Picalo etc. 10) Applications for ImagesUsing Python several application can be developed for image. Applications developed are: VPython, Gogh, imgSeek etc. There are several such applications which can be developed using Python
Next TopicHow To Install Python
|


i've found the only true way to learn is by reflecting.
this page was inspired by derek sivers.
i highly recommend:
click to view my notes:
my goal is to have in-depth notes for each of the following
and all futures books i read. this will take time.
In progress...

Good overview of mutual fund investing by one of the most respected companies in the business, Morningstar .
Historical fiction of resistance in Nazi Germany. I found it anticlimactic.
Understanding the stock market and investing over the long run. The book that many of the greatest investors started with.
WWII historical fiction. A touching story, although I didn't find it as enthralling as most reviewers did.
A brief history of the universe starting with the big bang, told wonderfully by David Christian.
An unbelievable story of a German boy involed in the resistance against the Nazis. Nearly read in one sitting, I couldn't put it down.
A must-read for business owners and for those interested in how Ray Dalio thinks.
Good for understanding leveraged buyouts through the story of one of the largest in history.
Broadened perspective on the lives of those less fortunate. Similar lessons to The Glass Castle. Incredible page-turner.
Compelling story about how meditation and mindfulness can be life-changing.
Love him or hate him, Elon has changed the world. Unsurprisingly, this book is already outdated. Nevertheless, he's an inspiration and we need to clone him.
Everyone should understand the Great Recession. Michael Lewis does an incredibly entertaining job of doing so.
If you're new to investing or haven't started, this is a quick read with the basics.
Incredible true story about a Jewish man's life in a concentration camp. We are so lucky.
Jordan Peterson is incredibly interesting and offers good tips for a fulfilling life. Although, I found his opinions too strong and verbose.
Excellent discussion on the state of healthcare in the U.S. and problems with how we treat our elderly. Atul Gawanda is a true role model.
Broadened perspective on the lives of those less fortunate. Incredible read that I could not put down.
Biography of one of the most incredible men in known history. Those who can find intersections of thought have the greatest chance of success.
Highly hypothetical story about the future of A.I. Entertaining, scary, and insightful.
The story of Steve Jobs, one of the world's greatest visionaries.
America's issues with housing and poverty, set in Milwaukee, WI.
Great life advice on wielding influence over others with a simple shift of perspective.
sorted in chronological order, from most recently read to least recently
read


Let's start with the facts
Notwithstanding the first creation of a computer program being attributed to a woman (Ada Lovelace) and the next wave of computer history being dominated by female coders (ENAIC), this summer has seen a plethora of gender diversity stats from global tech giants and the results are not good. Across the board, it appears that woman represent only 30% of the workforce. Read more...


The settingsService is used to register settings tabs to be displayed in the Settings Modal.
settingsService


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SlowDown Algorithmic Regularization (SDAR)
Algorithmic Regularization with slowdown method for integrating few-body motions
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#include <binary_tree.h>
Public Types | |
| template<class T > | |
| using | ProcessFunctionLeaf = void(*)(T &, Tptcl *&) |
| iteratively leaf processing function template More... | |
| template<class T > | |
| using | ProcessFunctionRoot = T(*)(T &, BinaryTree< Tptcl > &) |
| iteratively root processing function template More... | |
| template<class T , class Tr > | |
| using | ProcessFunctionTree = Tr(*)(T &, const Tr &, const Tr &, BinaryTree< Tptcl > &) |
| iteratively tree processing function template More... | |
Public Member Functions | |
| BinaryTree () | |
| void | getherBinaryTreeIter (BinaryTree< Tptcl > _bin[]) |
| collect BinaryTree data iteratively and save to a BinaryTree array More... | |
| void | calcCenterOfMass () |
| calculate center-of-mass from members More... | |
| void | calcOrbit (const Float _G) |
| calculate Kepler orbit from members More... | |
| int | calcMemberN () |
| calc total number of members More... | |
| int | getMemberN () const |
| get total number of members More... | |
| int | calcMemberNIter () |
| calc total number of members iteratively More... | |
| template<class T > | |
| void | processLeafIter (T &_dat, ProcessFunctionLeaf< T > _f) |
| Process (bottom) leaf data with extra dat iteratively (from left to right) More... | |
| template<class T > | |
| T | processRootIter (T &_dat, ProcessFunctionRoot< T > _f) |
| Process root data and return result iteratively. More... | |
| template<class Troot , class Tleaf > | |
| Troot | processRootLeafIter (Troot &_dat_root, ProcessFunctionRoot< Troot > _f_root, Tleaf &_dat_leaf, ProcessFunctionLeaf< Tleaf > _f_leaf) |
| Process root and leaf data and return result iteratively. More... | |
| template<class T , class Tr > | |
| Tr | processTreeIter (T &_dat, const Tr &_res1, const Tr &_res2, ProcessFunctionTree< T, Tr > _f) |
| Process tree data with extra dat iteratively (from bottom to top) More... | |
| int | copyDataIter (BinaryTree< Tptcl > _bin_out[], const int _i) |
| copy a binary tree to a binaryTree array iteratively More... | |
| void | setMembers (Tptcl *_p1, Tptcl *_p2, const int _i1, const int _i2) |
| set members More... | |
| Tptcl * | getMember (const size_t i) const |
| get member More... | |
| BinaryTree< Tptcl > * | getMemberAsTree (const size_t i) const |
| get member as tree More... | |
| int | getMemberIndex (const size_t i) const |
| get member index More... | |
| bool | isMemberTree (const size_t i) const |
| Tptcl * | getLeftMember () const |
| get left member More... | |
| BinaryTree< Tptcl > * | getLeftMemberAsTree () const |
| get left member as tree More... | |
| Tptcl * | getRightMember () const |
| get right member More... | |
| BinaryTree< Tptcl > * | getRightMemberAsTree () const |
| get right member as tree More... | |
| void | printColumn (std::ostream &_fout, const int _width=20) |
| print data of class members using column style More... | |
| void | writeAscii (std::ostream &_fout) const |
| write class data to file with ASCII format More... | |
| void | readAscii (std::istream &_fin) |
| read class data to file with ASCII format More... | |
| void | printColumnIter (std::ostream &_fout, const int _width=20) |
| print function More... | |
| Public Member Functions inherited from COMM::Binary | |
| template<class Tptcl > | |
| void | calcOrbit (const Tptcl &_p1, const Tptcl &_p2, const Float _G) |
| calculate kepler Orbit from particles More... | |
| template<class Tptcl > | |
| void | calcParticles (Tptcl &_p1, Tptcl &_p2, const Float _G) |
| calculate two components from kepler Orbit More... | |
| template<class Tptcl > | |
| void | calcParticlesEcca (Tptcl &_p1, Tptcl &_p2, const Float _ecca, const Float _G) const |
| calculate two components from kepler Orbit with input eccentricity anomaly More... | |
| void | evolve (const Float _dt) |
| Solve kepler motion for dt. More... | |
| void | print (std::ostream &_os) const |
| void | printColumn (std::ostream &_fout, const int _width=20) |
| print data of class members using column style More... | |
| void | writeBinary (FILE *_fp) const |
| write class data to file with binary format More... | |
| void | readBinary (FILE *_fin) |
| read class data to file with binary format More... | |
| void | writeAscii (std::ostream &_fout) const |
| write class data to file with ASCII format More... | |
| void | readAscii (std::istream &_fin) |
| read class data to file with ASCII format More... | |
Static Public Member Functions | |
| static void | generateBinaryTree (BinaryTree< Tptcl > _bins[], int _ptcl_list[], const int _n, Tptcl *_ptcl, const Float _G) |
| Generate kepler binary tree for a group of particles. More... | |
| static void | printColumnTitle (std::ostream &_fout, const int _width=20) |
| print titles of class members using column style More... | |
| Static Public Member Functions inherited from COMM::Binary | |
| template<class Tptcl > | |
| static void | orbitToParticle (Tptcl &_p1, Tptcl &_p2, const Binary &_bin, const Float &_ecca, const Float _G) |
| Orbit to position and velocity. More... | |
| template<class Tptcl > | |
| static void | particleToOrbit (Binary &_bin, const Tptcl &_p1, const Tptcl &_p2, const Float _G) |
| position velocity to orbit More... | |
| template<class Tpi , class Tpj > | |
| static void | particleToSemiEcc (Float &_semi, Float &_ecc, Float &_r, Float &_rv, const Tpi &_p1, const Tpj &_p2, const Float _G) |
| position velocity to orbit semi-major axis and eccentricity More... | |
| static Float | calcEccAnomaly (const Float _mean_anomaly, const Float _ecc) |
| calculate eccentricy anomaly from mean anomaly More... | |
| static void | solveKepler (Binary &_bin, const Float _dt) |
| solve kepler orbit after dt More... | |
| static void | printColumnTitle (std::ostream &_fout, const int _width=20) |
| print titles of class members using column style More... | |
Additional Inherited Members | |
| Public Attributes inherited from COMM::Binary | |
| Float | semi |
| Float | ecc |
| Float | incline |
| Float | rot_horizon |
| Float | rot_self |
| Float | t_peri |
| Float | period |
| Float | ecca |
| Float | m1 |
| Float | m2 |
| Float | r |
| Vector3< Float > | am |
Binary tree cell.
| using COMM::BinaryTree< Tptcl >::ProcessFunctionLeaf = void (*) (T&, Tptcl* &) |
iteratively leaf processing function template
| using COMM::BinaryTree< Tptcl >::ProcessFunctionRoot = T (*) (T&, BinaryTree<Tptcl>& ) |
iteratively root processing function template
| using COMM::BinaryTree< Tptcl >::ProcessFunctionTree = Tr (*) (T&, const Tr&, const Tr&, BinaryTree<Tptcl>& ) |
iteratively tree processing function template
|
inline |
|
inline |
calculate center-of-mass from members
|
inline |
calc total number of members
|
inline |
calc total number of members iteratively
|
inline |
calculate Kepler orbit from members
|
inline |
copy a binary tree to a binaryTree array iteratively
| [in] | _bin_out | BinaryTree array to store the data |
| [in] | _i | index in _bin_out for copying the current tree cell |
|
inlinestatic |
Generate kepler binary tree for a group of particles.
|
inline |
collect BinaryTree data iteratively and save to a BinaryTree array
The member number should be correct
| [out] | _bin | binarytree array to store the data (should be size of n_members-1), the root is put last (n_members-1) |
|
inline |
get left member
|
inline |
get left member as tree
|
inline |
get member
|
inline |
get member as tree
|
inline |
get member index
|
inline |
get total number of members
|
inline |
get right member
|
inline |
get right member as tree
|
inline |
|
inline |
print data of class members using column style
print data of class members in one line for column style. Notice no newline is printed at the end
| [out] | _fout | std::ostream output object |
| [in] | _width | print width (defaulted 20) |
|
inline |
print function
|
inlinestatic |
print titles of class members using column style
! copy operator = *! Copy the data and member address. If member address point to a particle (id>0), copy address; else if it is a binary tree, copy the address and also correct the address difference, this assume the whole BinaryTree is stored in a continuing array, thus correct address difference also make the new binary tree have consistent member address in new array.
print titles of class members in one line for column style
| [out] | _fout | std::ostream output object |
| [in] | _width | print width (defaulted 20) |
|
inline |
Process (bottom) leaf data with extra dat iteratively (from left to right)
| [in] | _dat | data for processing loop from left to right |
| [in] | _f | function to process root information |
|
inline |
Process root data and return result iteratively.
The process go from top root to leafs from left to right
| [in] | _dat | data return from upper level processing function |
| [in] | _f | function to process root information |
|
inline |
Process root and leaf data and return result iteratively.
The process go from top root to leafs from left to right
| [in] | _dat | data return from upper level processing function |
| [in] | _f | function to process root information |
|
inline |
Process tree data with extra dat iteratively (from bottom to top)
| [in] | _dat | general data type for process using |
| [in] | _return_1 | return from branch 1 |
| [in] | _return_2 | return from branch 2 |
| [in] | _f | function to process root information |
|
inline |
read class data to file with ASCII format
| [in] | _fin | std::istream file for input |
|
inline |
set members
| [in] | _p1 | particle 1 |
| [in] | _p2 | particle 2 |
| [in] | _i1 | particle 1 index (should be >=0 if it is not binary tree) |
| [in] | _i2 | particle 2 index (should be >=0 if it is not binary tree) |
|
inline |
write class data to file with ASCII format
| [in] | _fout | std:osteram file for output |


|
ActiveTcl User Guide
|
||
Copyright © 1989-1994 The Regents of the University of California. Copyright © 1994 The Australian National University Copyright © 1994-1998 Sun Microsystems, Inc. Copyright © 1998-2000 Scriptics Corporation. Copyright © 1999 Scriptics Corportation Copyright © 2000 Ajuba Solutions. Copyright © 2002 ActiveState Corporation. Copyright © 1995-1997 Roger E. Critchlow Jr.


{% load static %}
BACK
Hey, are you sure you want to delete {{ object.imagename }}?
{% csrf_token %}
Yes, I'm sure.


1. Choose *.msg file...
2. MSG info (
)
From
To
Date (from Headers, example)
Subject
Body
HTML Body
Attachments
Sorry, the file you selected is not MSG type
Sorry, your browser isn't supported


Add to Slack
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Don't let the scary techy buzzword put you off! Buy and own your own profitable casino game today! Let us walk you through the process. You will need some Ether or Matic to start with. You could even get some for free at coinbase!
Don't let the scary techy buzzword put you off! Buy and own your own profitable casino game today! Let us walk you through the process. You will need some Ether or Matic to start with. You could even get some for free at coinbase!
The first People's Casino © casinos are on sale through OpenSea. Once you own a casino, you will need to top it up with a kitty to balance any bets. The more money you put in, the higher the bets and profits you can make. Any money you deposit in to the casino can be withdrawn at any time.
Your earnings can be withdrawn from the casino at anytime through the casino portal. You must be logged in with the owners account to do so.
Since this is an open source decentralized application, you can
check all the code for yourself:
Smart Contract
After each bet, a link is available to see the transaction and
prove that the result was acquired fairly.
Yes indeed! In fact, you can even sell your casino for many more times than the amount you bought it! NFT's today can sell for millions of dollars.
All the earnings put in to the casino, stay with the casino. So if the casino has a new owner, they own the profit! Make sure you withdrawal the kitty before trading!
Anybody who has access to your casino's url, and some Ether or Matic can play your casino game. Perhaps recommend your friends get some for free at coinbase!
ONE HUNDRED PERCENT!! That's right! When you own a People's Casino © casino, all the earnings from the game go straight back into your casino. These earnings can be withdrawn at any time. The house edge for each casino is 4%.
For any other questions, or feedback, feel free to join our friendly Discord community: JOIN


I love solving complex problems, both alone and with others, that require learning and synthesizing lots of different information.
I recently discovered the world of machine learning and NLP, and am learning as much about data science and machine learning engineering as I can.
In a previous life, I worked in content development and project management for computer-based, online-administered educational assessments before pivoting my career into tech via code school.
I've also earned a BA in Linguistics and Japanese Language and Literature, and an MA in International Affairs.
I have also been known to play the piano and clarinet, tutor ESL, pretend to speak Japanese and French on occasion, and can easily be convinced to geek out over something new and exciting or old and cherished.
Some of the tools I develop with:


Google Trials A 'Clear' Button For Search
by Tegan JonesNo more manual deletion.
Google has begun trialling a 'clear' button in search that will allow users to move onto a new query without having to manually delete their current text.
According to 9ToGoogle, this experiment seems to be restricted to only some Google accounts. It's currently unclear if any Australian users are part of the UI trial.
Anyone who does get a chance to use it will see a rectangle 'clear' button on the far right of the main search box. It doesn't appear to currently be working with most other result tabs such as 'news'.
It's not a huge change, but if rolled out properly it would be a nifty little feature that will certainly help save some search time.


--- layout: post title: 'Watching @samsoffes talking about Reusing Your Code with libs #mxnash' date: 2010-03-27 17:36:40.000000000 -07:00 type: post published: true status: publish categories: [] tags: [] meta: {} author: ---
Sent via iPidgeon


My name is Musthafa Thamyeez and I am trying to make
180 websites in 180 days
I was inspired by Jennifer Dewalt and her story about how she created 180 websites in 180 days! It inspired me so much that I am going to give that a try and see how far I can go.
You can follow the project here and on the blog


// Modify here, bug causes nav to spill behind body on ultra large resolutions
In this guide you will be able to visualize the share of students who are on track to graduate on time after ninth grade by high school and by their on-track status after tenth grade.
The College-Going Pathways series is a set of guides, code, and sample data about policy-relevant college-going topics. Browse this and other guides in the series for ideas about ways to investigate student pathways through high school and college. Each guide includes several analyses in the form of charts together with Stata analysis and graphing code to generate each chart.
Once you’ve identified analyses that you want to try to replicate or modify, click the “Download” buttons to download Stata code and sample data. You can make changes to the charts using the code and sample data, or modify the code to work with your own data. If you’re familiar with Github, you can click “Go to Repository” and clone the entire College-Going Pathways repository to your own computer.
The data visualizations in the College-Going Pathways series use a synthetically generated college-going analysis sample data file which has one record per student. Each high school student is assigned to a ninth-grade cohort, and each student record includes demographic and program participation information, annual GPA and on-track status, high school graduation outcomes, and college enrollment information. The Connect guide (coming soon) will provide guidance and example code which will help you build a college-going analysis file using data from your own school system.
Research suggests that academic performance in ninth grade strongly predicts the likelihood of a student dropping out of high school. In this section, you examine patterns of student retention and on-time transitions from ninth to tenth grade. This information can provide an early warning to an agency with students at-risk of dropping out, and might benefit from targeted support early in their high school careers.
One of the most important decisions in running each analysis is defining the sample. Each analysis corresponds to a different part of the education pipeline and as a result requires different cohorts of students.
If you are using the synthetic data we have provided, the sample restrictions have been predefined and are included below. If you run this code using your own agency data, change the sample restrictions based on your data. Note that you will have to run these sample restrictions at the beginning of your do file so they will feed into the rest of your code.
// Sample Restrictions
// Agency name
global agency_name "Agency"
// Ninth grade cohorts you can observe persisting to the second year of college
global chrt_ninth_begin_persist_yr2 = 2004
global chrt_ninth_end_persist_yr2 = 2006
// Ninth grade cohorts you can observe graduating high school on time
global chrt_ninth_begin_grad = 2004
global chrt_ninth_end_grad = 2006
// Ninth grade cohorts you can observe graduating high school one year late
global chrt_ninth_begin_grad_late = 2004
global chrt_ninth_end_grad_late = 2006
// High school graduation cohorts you can observe enrolling in college the fall after graduation
global chrt_grad_begin = 2007
global chrt_grad_end = 2009
// High school graduation cohorts you can observe enrolling in college two years after hs graduation
global chrt_grad_begin_delayed = 2007
global chrt_grad_end_delayed = 2009
Based on the sample data, you will have three cohorts (sometimes only two) for analysis. If you are using your own agency data, you may decide to aggregate results for more or fewer cohorts to report your results. This decision depends on 1) how much historical data you have available and 2) what balance to strike between reliability and averaging away information on recent trends. We suggest you average results for the last three cohorts to take advantage of larger sample sizes and improve reliability. However, if you have data for more than three cohorts, you may decide to not average data out for fear of losing information about trends and recent changes in your agency.
This guide is an open-source document hosted on Github and generated using the Stata Webdoc package. We welcome feedback, corrections, additions, and updates. Please visit the OpenSDP college-going pathways repository to read our contributor guidelines.
Purpose: This analysis illustrates what percent of students are on-track after ninth grade graduate from each high school and the agency as a whole. Different levels of on-track for graduation are distinguished by high school.
Required Analysis File Variables:
sid
chrt_ninth
first_hs-Name
first_hs_code
ontrack_endyr1*
cum_gpa_yr1
Analysis-Specific Sample Restrictions: Keep students in ninth grade cohorts you can observe graduating high school on time AND are part of the on-track sample (attended the first semester of ninth grade and never transferred into or out of the system).
Ask Yourself
Possible Next Steps or Action Plans: Overall school-level results can be disaggregated by student subgroups of interest, (race, FRPL status, and eighth grade academic achievement).
Analytic Technique: Calculate the proportion of students on-track at each school, and across the agency.
// Proportion of Students On-Track by High School
// Step 1: Load the college-going analysis file into Stata
use "$data/college_going_analysis", clear
// Step 2: Keep students in ninth grade cohorts you can observe graduating high school on time AND are part of the on-track sample
local chrt_ninth_begin = ${chrt_ninth_begin_grad}
local chrt_ninth_end = ${chrt_ninth_end_grad}
keep if (chrt_ninth >= `chrt_ninth_begin' & chrt_ninth <= `chrt_ninth_end')
keep if ontrack_sample == 1
// Step 3: Create on-track categories that account for studentsҠcredits earned (already captured in the ontrack_endyr1 variable) and GPA after ninth grade
gen ontrack_endyr1_1 = 0
replace ontrack_endyr1_1 = 1 if ontrack_endyr1 == 1
label var ontrack_endyr1_1 "Off-Track to Graduate"
gen ontrack_endyr1_2 = 0
replace ontrack_endyr1_2 = 1 if ontrack_endyr1 == 2 & cum_gpa_yr1 < 3.0
label var ontrack_endyr1_2 "On-Track to Graduate, GPA < 3.0"
gen ontrack_endyr1_3 = 0
replace ontrack_endyr1_3 = 1 if ontrack_endyr1 == 2 & cum_gpa_yr1 >= 3.0 & ///
!mi(cum_gpa_yr1)
label var ontrack_endyr1_3 "On-Track to Graduate, GPA >= 3.0"
assert ontrack_endyr1_1 + ontrack_endyr1_2 + ontrack_endyr1_3 == 1
// Step 4: Obtain the agency average for the key variables
preserve
collapse (mean) ontrack_endyr1_? (count) N=sid
tempfile agency_level
save `agency_level'
restore
// Step 5: Obtain mean rates for each school and append the agency average
collapse (mean) ontrack_endyr1_? (count) N=sid, by(first_hs_name first_hs_code)
append using `agency_level'
// Step 6: Provide a hs name label for the appended agency average and shorten hs name
replace first_hs_code = 0 if first_hs_code == .
replace first_hs_name = "${agency_name} AVERAGE" if mi(first_hs_name)
replace first_hs_name = subinstr(first_hs_name, " High School", "", .)
// Step 7: For students who are off-track upon completion of their first year of high school, convert the values to be negative for ease of visualization in the graph
replace ontrack_endyr1_1 = -ontrack_endyr1_1
// Step 8: Multiply the average of each outcome by 100 for graphical representation of the rates. Create a variable equal to the sum of the two on-track status variables for easier sorting
foreach var of varlist ontrack_endyr1_1 ontrack_endyr1_2 ontrack_endyr1_3 {
replace `var' = (`var' * 100)
format `var' %9.1f
}
gen ontrack_endyr1_sum = ontrack_endyr1_2 + ontrack_endyr1_3
// Step 9: Prepare to graph the results
// Generate a cohort label to be used in the footnote for the graph
local temp_begin = `chrt_ninth_begin'-1
local temp_end = `chrt_ninth_end'-1
if `chrt_ninth_begin'==`chrt_ninth_end' {
local chrt_label "`temp_begin'-`chrt_ninth_begin'"
}
else {
local chrt_label "`temp_begin'-`chrt_ninth_begin' through `temp_end'-`chrt_ninth_end'"
}
// Step 10: Graph the results
#delimit ;
graph bar ontrack_endyr1_3 ontrack_endyr1_2 ontrack_endyr1_1,
over(first_hs_name, gap(20) sort(ontrack_endyr1_sum) label(angle(40)labsize(small)))
blabel(bar, position(inside) size(2) format(%8.0f))
bar(3, fcolor(maroon*.6) lcolor(maroon*.6))
bar(1, fcolor(navy*.5) lcolor(navy*.5))
bar(2, fcolor(navy*.8) lcolor(navy*.8)) stack
title("Proportion of Students On-Track to Graduate by School", size(medium))
subtitle("End of Ninth Grade On-Track Status" "By High School")
legend(region(lcolor(white)) position(11) ring(0) order(2 1 3)
label(3 "Off Track to Graduate")
label(1 "On Track, GPA <3.0")
label(2 "On Track, GPA>=3.0")
symxsize(5) symysize(2) cols(1) size(vsmall))
yline(0, lcolor(black) lwidth(vvthin))
ytitle("Percent of Ninth Graders") yscale(range(-80(20)80)) ylabel(-80(20)80, nogrid)
graphregion(color(white) fcolor(white) lcolor(white))
plotregion(color(white) fcolor(white) lcolor(white))
note(" " "Sample: `chrt_label' ${agency_name} first-time ninth graders. Students who transferred into or out of ${agency_name} are excluded" "from the sample. All data from ${agency_name} administrative records.", span size(vsmall));
#delimit cr
graph export "figures/B1_OnTrack_Ninth_by_HS.png", replace width(1600) height(1200)
Purpose: This analysis explores how on-track status after ninth grade (the horizontal axis) predicts ontrack status in tenth grade (the vertical axis). This analysis is useful for developing early dropout warning indicators for at-risk students as early as the second semester of ninth grade.
Required Analysis File Variables:
sid
chrt_ninth
first_hs_name
first_hs_code
ontrack_endyr1*
cum_gpa_yr1*
Analysis-Specific Sample Restrictions: Keep students in ninth grade cohorts you can observe graduating high school on time AND are part of the on-track sample (attended the first semester of ninth grade and never transferred into or out of the system).
Ask Yourself:
Possible Next Steps or Action Plans: Identify additional risk factors, (chronic absenteeism, prior academic achievement etc.) which can be incorporated into analyses like the one above. This could be used to further understand which students struggle, why they struggle, and interventions to keep them enrolled and engaged.
// Ninth To Tenth Grade Transition by On-Track Status
// Step 1: Load the college-going analysis file into Stata
use "$data/college_going_analysis", clear
// Step 2: Keep students in ninth grade cohorts you can observe graduating high school on time AND are part of the on-track sample
local chrt_ninth_begin = ${chrt_ninth_begin_grad}
local chrt_ninth_end = ${chrt_ninth_end_grad}
keep if (chrt_ninth >= `chrt_ninth_begin' & chrt_ninth <= `chrt_ninth_end')
keep if ontrack_sample == 1
// Step 3: Create on-track categories that account for studentsҠcredits earned (already captured in the ontrack_endyr1 variable) and GPA after ninth grade
gen ontrack_endyr1_gpa = .
replace ontrack_endyr1_gpa = 1 if ontrack_endyr1 == 1
replace ontrack_endyr1_gpa = 2 if ontrack_endyr1 == 2 & cum_gpa_yr1 < 3.0
replace ontrack_endyr1_gpa = 3 if ontrack_endyr1 == 2 & cum_gpa_yr1 >= 3.0 & !mi(cum_gpa_yr1)
assert !mi(ontrack_endyr1_gpa) if !mi(ontrack_endyr1) & !mi(cum_gpa_yr1)
label define ot 1 "Off-Track to Graduate" 2 "On-Track, GPA<3.00" 3 "On-Track, GPA>=3.00"
label val ontrack_endyr1_gpa ot
// Step 4: Create indicators for students upon completion of their second year of high school
gen ontrack_endyr2_1 = 0
replace ontrack_endyr2_1 = 1 if ontrack_endyr2 == 0
label var ontrack_endyr2_1 "Off-Track to Graduate Yr2"
gen ontrack_endyr2_2 = 0
replace ontrack_endyr2_2 = 1 if ontrack_endyr2 == 1 & cum_gpa_yr2 < 3.0 & !mi(cum_gpa_yr2)
label var ontrack_endyr2_2 "On-Track, GPA < 3.0"
gen ontrack_endyr2_3 = 0
replace ontrack_endyr2_3 = 1 if ontrack_endyr2 == 1 & cum_gpa_yr2 >= 3.0 & !mi(cum_gpa_yr2)
label var ontrack_endyr2_3 "On-Track, GPA >= 3.0"
gen ontrack_endyr2_4 = 0
replace ontrack_endyr2_4 = 1 if status_after_yr2==3 | status_after_yr2==4
label var ontrack_endyr2_4 "Dropout/Disappear"
//assert ontrack_endyr2_1 + ontrack_endyr2_2 + ontrack_endyr2_3 + ontrack_endyr2_4 == 1
// Step 5: Determine the agency average for each of the indicators created in step 4.
collapse (mean) ontrack_endyr2_1 ontrack_endyr2_2 ontrack_endyr2_3 ontrack_endyr2_4, ///
by(ontrack_endyr1_gpa)
foreach var of varlist ontrack_endyr2_1 ontrack_endyr2_2 ontrack_endyr2_3 ontrack_endyr2_4 {
replace `var' = ( `var' * 100)
format `var' %9.1f
}
// Step 6: For students who are off-track upon completion of their second year of high school, convert the values to be negative for ease of visualization in the graph.
replace ontrack_endyr2_1 = ontrack_endyr2_1 * -1
replace ontrack_endyr2_4 = ontrack_endyr2_4 * -1
// Step 7: Prepare to graph the results
// Generate a cohort label to be used in the footnote for the graph
local temp_begin = `chrt_ninth_begin'-1
local temp_end = `chrt_ninth_end'-1
if `chrt_ninth_begin'==`chrt_ninth_end' {
local chrt_label "`temp_begin'-`chrt_ninth_begin'"
}
else {
local chrt_label "`temp_begin'-`chrt_ninth_begin' through `temp_end'-`chrt_ninth_end'"
}
// Step 8: Graph the results
#delimit ;
graph bar ontrack_endyr2_1 ontrack_endyr2_4 ontrack_endyr2_2 ontrack_endyr2_3 ,
over(ontrack_endyr1_gpa, label(labsize(vsmall)) gap(50)) outergap(50)
bar(1, fcolor(maroon*.4) lcolor(maroon*.4))
bar(2, fcolor(maroon*.8) lcolor(maroon*.8))
bar(3, fcolor(navy*.5) lcolor(navy*.5))
bar(4, fcolor(navy*.8) lcolor(navy*.8)) stack
blabel(bar, size(2) format(%8.0f) position(inside))
legend(symxsize(2) symysize(2) rows(4) size(2)
region(lcolor(white)) position(2) order(4 3 1 2)
label(1 "Off-Track to Graduate")
label(2 "Dropout/Disappear")
label(3 "On-Track to" "Graduate, GPA<3.0")
label(4 "On-Track to" "Graduate, GPA>=3.0")
title("End of Tenth Grade" "On-Track Status", size(small)))
title("End of Tenth Grade On-Track Status", size(medium))
subtitle("by End of Ninth Grade Status", size(small))
ytitle("Percent of Tenth Grade Students" "by Ninth Grade Status" " " " ", size(small))
yscale(range(-40(20)100))
ylabel(-40(20)100, nogrid labsize(small))
ylabel(-40 "40" -20 "20" 0 "0" 20 "20" 40 "40" 60 "60" 80 "80" 100 "100")
yline(0, lcolor(black) lwidth(vvthin))
text(-130 60 "Ninth Grade On-Track Status", size(small))
graphregion(color(white) fcolor(white) lcolor(white))
plotregion(color(white) fcolor(white) lcolor(white))
note(" " " " "Sample: `chrt_label' ${agency_name} first-time ninth graders. Students who transferred into or out of ${agency_name} are excluded" "from the sample. All data from ${agency_name} administrative records.", span size(vsmall));
#delimit cr
graph export "figures/B2_OnTrack_Tenth_by_OnTrack_Ninth.png", replace width(1600) height(1200)


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 Perhaps you are holding it in your hand, stealing glances at it as you weave through traffic.
You have arrived at the website for E.LIT / NET.ART
, a gallery of electronic literature and Internet art curated by Jeffrey Moro.
Would you like to see the gallery
?
Would you like to learn about the course
?
Would you like to explore the screening
?
Or would you like to learn more about
the project?


WELCOME TO UOR COOKI STAND
Delivering Cookies Safely To Your Door
VISIT US IN OUR LOCATIONS
- SEATTLE
- TOKYO
- DUBAI
- PARIS
- LIMA
OUR CONTACT INFORMATION
- Number :<PHONE_NUMBER>5
- Facebook<EMAIL_ADDRESS>- Fax :<PHONE_NUMBER>
- Delivery / 78-906563061
We Open At
6AM - 7:00PMThe Cookie Shop
Monday-Friday


The auto-discovery process found the Adaire Theatre, in Dublin VA, on EventBrite.
Here is the proposed entry for the Dublin, VA, hub.
{ "url" : "http://www.eventbrite.com/org/2432005700", "feedurl" : "http://elmcity.cloudapp.net/ics_from_eventbrite_organizer?organizer=Adaire%20Theatre%20&elmcity_id=DublinVA", "source" : "Adaire Theatre (eventbrite)", "category" : "eventbrite" }
I'll add it to the hub like so, adding only the tag 'theater'


SimulationRobot module¶
-
class
SimulationRobot.
SimulationRobot
(robot_params)¶ Class describing a robot in SimulationWorld
-
__init__
(robot_params)¶ Initialises the robot class from a dictionary containing all key robot parameters
Parameters: robot_params (dict) – Dictionary containing all key robot parameters
-
control_update
(dt, world=None)¶ Updates the robot’s velocity and rotation according to the alogorithm set in the robot_params dict
Parameters: - dt (float) – The time difference since the last control update
- world (SimulationWorld) – The world this robot exists within. Used to detect other objects in the world such as other robots and barriers
-
get_neighbours
(distance_matrix)¶ Returns the robot’s neighbours via their robot_index
Nebighbourhood params are dictated by neighbourhood_mode, neighbourhood_size and neighbourhood_distance in robot_params
Parameters: distance_matrix (np.array) – NxN array for a world with N robots in it. Represents the distance between every robot in the array Returns: Neighbour indexes Return type: list
-
movement_update
(dt)¶ Updates the robots position based on its current position and velocity
Parameters: dt (float) – The time difference since the last movement update
-
on_sim_start
()¶ Initialises the robot depending on the alogorithm set in the robot_params dict
Executed during the init position log of the SimulationWorld class, so should be executed just before the first time step
-
-
SimulationRobot.
sample_distro
(distro_tuple)¶ Samples a certain probability distrobution function (PDF) described by a tuple of parameters
Parameters: distro_tuple (tuple (distrobution_name, arg1,arg2...)) – The PDF to sample from Returns: the number generated from the PDF Return type: float


sklearn.impute
.MICEImputer¶
-
class
sklearn.impute.
MICEImputer
(missing_values='NaN', imputation_order='ascending', n_imputations=100, n_burn_in=10, predictor=None, n_nearest_features=None, initial_strategy='mean', min_value=None, max_value=None, verbose=False, random_state=None)[source]¶ MICE transformer to impute missing values.
Basic implementation of MICE (Multivariate Imputations by Chained Equations) package from R. This version assumes all of the features are Gaussian.
Read more in the User Guide.
Parameters: missing_values : int or “NaN”, optional (default=”NaN”)
The placeholder for the missing values. All occurrences of
missing_values
will be imputed. For missing values encoded as np.nan, use the string value “NaN”.imputation_order : str, optional (default=”ascending”)
The order in which the features will be imputed. Possible values:
- “ascending”
From features with fewest missing values to most.
- “descending”
From features with most missing values to fewest.
- “roman”
Left to right.
- “arabic”
Right to left.
- “random”
A random order for each round.
n_imputations : int, optional (default=100)
Number of MICE rounds to perform, the results of which will be used in the final average.
n_burn_in : int, optional (default=10)
Number of initial MICE rounds to perform the results of which will not be returned.
predictor : estimator object, default=BayesianRidge()
The predictor to use at each step of the round-robin imputation. It must support
return_std
in itspredict
method.n_nearest_features : int, optional (default=None)
Number of other features to use to estimate the missing values of the each feature column. Nearness between features is measured using the absolute correlation coefficient between each feature pair (after initial imputation). Can provide significant speed-up when the number of features is huge. If
None
, all features will be used.initial_strategy : str, optional (default=”mean”)
Which strategy to use to initialize the missing values. Same as the
strategy
parameter insklearn.preprocessing.Imputer
Valid values: {“mean”, “median”, or “most_frequent”}.min_value : float, optional (default=None)
Minimum possible imputed value. Default of
None
will set minimum to negative infinity.max_value : float, optional (default=None)
Maximum possible imputed value. Default of
None
will set maximum to positive infinity.verbose : int, optional (default=0)
Verbosity flag, controls the debug messages that are issued as functions are evaluated. The higher, the more verbose. Can be 0, 1, or 2.
random_state : int, RandomState instance or None, optional (default=None)
The seed of the pseudo random number generator to use when shuffling the data. If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is the random number generator; If None, the random number generator is the RandomState instance used by
np.random
.Attributes
initial_imputer_ (object of class sklearn.preprocessing.Imputer
’) The imputer used to initialize the missing values.imputation_sequence_ (list of tuples) Each tuple has (feat_idx, neighbor_feat_idx, predictor)
, wherefeat_idx
is the current feature to be imputed,neighbor_feat_idx
is the array of other features used to impute the current feature, andpredictor
is the trained predictor used for the imputation.Notes
The R version of MICE does not have inductive functionality, i.e. first fitting on
X_train
and then transforming anyX_test
without additional fitting. We do this by storing each feature’s predictor during the round-robinfit
phase, and predicting without refitting (in order) during thetransform
phase.Features which contain all missing values at
fit
are discarded upontransform
.Features with missing values in transform which did not have any missing values in fit will be imputed with the initial imputation method only.
References
[R105105] Stef van Buuren, Karin Groothuis-Oudshoorn (2011). “mice: Multivariate Imputation by Chained Equations in R”. Journal of Statistical Software 45: 1-67. Methods
fit
(X[, y])Fits the imputer on X and return self. fit_transform
(X[, y])Fits the imputer on X and return the transformed X. get_params
([deep])Get parameters for this estimator. set_params
(**params)Set the parameters of this estimator. transform
(X)Imputes all missing values in X. -
__init__
(missing_values='NaN', imputation_order='ascending', n_imputations=100, n_burn_in=10, predictor=None, n_nearest_features=None, initial_strategy='mean', min_value=None, max_value=None, verbose=False, random_state=None)[source]¶
-
fit
(X, y=None)[source]¶ Fits the imputer on X and return self.
Parameters: X : array-like, shape (n_samples, n_features)
Input data, where “n_samples” is the number of samples and “n_features” is the number of features.
y : ignored
Returns: self : object
Returns self.
-
fit_transform
(X, y=None)[source]¶ Fits the imputer on X and return the transformed X.
Parameters: X : array-like, shape (n_samples, n_features)
Input data, where “n_samples” is the number of samples and “n_features” is the number of features.
y : ignored.
Returns: Xt : array-like, shape (n_samples, n_features)
The imputed input data.
-
get_params
(deep=True)[source]¶ Get parameters for this estimator.
Parameters: deep : boolean, optional
If True, will return the parameters for this estimator and contained subobjects that are estimators.
Returns: params : mapping of string to any
Parameter names mapped to their values.
-
set_params
(**params)[source]¶ Set the parameters of this estimator.
The method works on simple estimators as well as on nested objects (such as pipelines). The latter have parameters of the form
<component>__<parameter>
so that it’s possible to update each component of a nested object.Returns: self
-
transform
(X)[source]¶ Imputes all missing values in X.
Note that this is stochastic, and that if random_state is not fixed, repeated calls, or permuted input, will yield different results.
Parameters: X : array-like, shape = [n_samples, n_features]
The input data to complete.
Returns: Xt : array-like, shape (n_samples, n_features)
The imputed input data.


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Magnitude as position on common scale
Identity as color hue
Magnitude as Area
Identity as Spatial region


--- layout: page # Experience --- {% for job in site.data.resume_info.experience_list %}
{{ job.company }} {{ job.start }} - {{ job.end }}


{% comment %} The navbar is located directly under the topbar. It provides the user with links to the various sections in the documentation, e.g. Home, Guides, Reference and so on. The navbar itself is hard coded. {% endcomment %}


test
username:
pwd:
pick a food:
Potato chips
Popcorn
Peanuts
Nachos
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what do you do in your spare time? Play sport
Play computer games
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Tell me a story:
some text


Is Chinese Bitcoin Mining Firm Canaan’s $400M IPO a Desperate Move?
by Ali RazaChinese bitcoin mining hardware maker, Canaan, plans to raise $400 million through public sale of its stocks. But will the IPO ride be smooth or bumpy?
Volatility is usual for bitcoin and crypto market participants. However, traditional stock market traders and investors are used to a bit more stability when it comes to their investments.
The $400 Million Bitcoin Mining Firm IPO
Canaan Creative is an Hangzhou-based firm, engaged in the business of manufacturing professional industry grade equipment required in large scale bitcoin and cryptocurrency mining activities.
The Bitmain rival was originally supposed to conduct its first-ever public stock sale on the 28th of last month. But now fresh reports point out that Canaan Creative is set to go live with its big IPO day on November 20. The intended amount to be raised is a humongous $400 million, but there’s some ambiguity as to how the individual shares will be priced for buyers.
Canaan’s stock listing on Nasdaq comes after the firm’s fair share of failed attempts to be listed on other stock exchanges in Hong Kong and mainland China. Rival Bitmain, which also faced a similar fate in Hong Kong, is said to have secretly filed a U.S. IPO as well, sponsored by Deutsche Bank.
A Desperate IPO?
It seems Canaan has a boot load of debts to clear off its balance sheet. Additionally, the bitcoin mining manufacturer seems to be running out of funds for research, which is why after it approached Nasdaq in desperation. Many were found to be intrigued by this decision as US restrictions for small Chinese firms are quite large.
As for the firm’s net revenue, it is definitely not at the top of its game. According to recent data, the company’s net registered revenue of around $137 million (959 mullion yuan), from 2019 beginning to September, was less than half of what it was during the same period in 2018. Even the bottom line sees a major loss, equal to around 223 million yuan. However, the mining equipment manufacturing firm itself is not completely responsible, as BTC price swings had a large impact, too.
According to experts, a bitcoin price rebound might lift demands and allow Canaan to perform better. Also, recovery is also predicted due to a surge in prepayments to Taiwan’s TSMC, which is the firm’s official chipmaker. For now, it can only be said, that the IPO seems like a desperate move.
What do you think about Canaan’s IPO plans? Let us know your thoughts in the comments below.
Image via Shutterstock
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Barberton golfers drive among the daisies for local tourism
About 76 golfers pitted their skills against one another on the course.
by Enver WesselsEstablished in 1894, Barberton Golf Club has earned its place in the annals of the town’s rich history. On Saturday, the club hosted the second Dynamite and Daisies Golf Day.
Barberton Mines and Barberton Community Tourism (BCT) banded together, in an effort to promote tourism in the area.Norman Hartman, head of local economic development at Barberton Mines, explained that the initiative was kick-started to boost the tourism sector as a means of giving back to the community and creating an alternative
economy to mining.
ALSO READ: World champs coming to Mpumalanga next year
“The mines have been in operation for the past 130 years and there is no guarantee that we’ll be mining for another 130 years. The Barberton Mines leadership has a vision which is to make sure that the community has a future after mining operations have ceased. This is so that we have another sector to take over from mining once we are
done.
“Barberton Adventures is a company we want to use as a platform to market the legacy and heritage of mining in
Barberton to promote tourism. Our mining life is 20 years old and it is better to start sooner than losing the opportunity while we can do it today,” he said.
ALSO READ: Springboks, our world champions
According to Astrid Christianson, marketing manager of BCT, about 76 golfers pitted their skills against one another on the course.
“We’re going from strength to strength and it’s been a communal effort,”she said.
ALSO READ: KNP tourist dies in Johannesburg hospital
The BCT director, Lionel Meyer, said the event started after BCT knocked on a few doors for funding and the mine manager suggested hosting a golf day to assist the local tourism entity with funds.
“This year we approached them again, and the mine manager has shown his commitment to being involved in tourism in Barberton. The reaction from the public has been overwhelming and their support has been extremely encouraging,” he said.
ALSO READ: Protesting Elandshoek residents shut down N4 for almost five hours
Once the formalities were handled on the course, it was time to retire to the clubhouse for a bite to eat and the prize-giving ceremony to reward the players who deserved it.
Team Kal Tire scooped top honours and Werner van Vuuren, Donovan Whelan and Milas Motubatse accepted the award. They were followed by the Barberton Mines team of Norman Hartman, Werner van Vuuren, Nicky Geere and Paul du Plooy in second place. Following hot on their heels in third, were the Westvaal team of Norman Hartman, Chris Groenewald, Wayne Gebhard, Johan van Wyk, and Francois Storm.
Van Vuuren put in a notable performance and landed closest to the pin.


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Faculty Research Programs
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David D. Ackerly —
Associate Professor,
Integrative Biology
Ackerly Lab
Plant ecology and evolution
Research in my lab addresses
the functional diversity
of terrestrial plants,
with a particular focus on
the California flora. Current
research is focused on
three areas: analysis of the
adaptive value of plant
functional traits; the study of community
assembly processes, based on distributions
of plant traits; and macro-evolutionary
studies of trait evolution, based on the synthesis
of ecological data, recent advances
in phylogenetics, and the development of
new comparative methods. I am particularly
interested in development and analysis
of regional and global databases for
plant ecological traits, including the new
Ecological Flora of California.
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Bruce G. Baldwin —
Professor,
Integrative Biology
Baldwin Lab
Systematics and evolution of vascular
plants
My research program
encompasses
vascular plant
systematics,
floristics, and
conservation biology,
with an
emphasis on biosystematic
and
phylogenetic studies. I am particularly interested
in systematic questions that address
evolutionary processes, historical
biogeography and ecology, and relationships
of California plants and their descendant
lineages elsewhere (e.g., Hawaii).
The rich diversity of the California flora
and the extensive literature from evolutionary
research on California plants pose
well-defined and important systematics research
problems for graduate study.
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Paul Fine —
Assistant Professor,
Integrative Biology
Fine Lab
Tropical plant ecology and evolution
My research investigates the origin and maintenance of Amazonian
rain forest tree diversity. I am especially interested in the role
that biotic interactions and environmental heterogeneity play in the
morphological, functional, and genetic diversity of tropical trees,
and how these factors influence the distribution and speciation of
plants. Current projects include studies of Protium (Burseraceae),
assembly of Amazonian plant communities and the diversification of
the sister families Anacardiaceae and Burseraceae.
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Brent D. Mishler —
Professor,
Integrative Biology
Mishler Lab
Bryology, systematics, and evolutionary
biology
My personal
research interests
can be
grouped into
two main areas:
(1) empirical
studies
of ecology,
phylogeny, systematics, genomics,
and development of mosses, and (2) the
theoretical basis of systematic and evolutionary
biology including the nature of species,
methods for phylogenetic reconstruction,
and principles of rank-free phylogenetic
classification. My graduate students
are currently involved in research projects
on a broad front including: systematic
studies of mosses, ferns, and angiosperms,
the ecology of reproduction and water
stress, biogeography of the South Pacific,
comparative genomics, and ethnobotany.
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Chelsea Specht — Associate Professor,
Plant and Microbial Biology
Specht Lab
Plant systematics, development, and evolution
My research interests center
on the processes and patterns
involved in the evolution
and diversification of plants, especially
the monocots. I use a phylogenetic framework
to test hypotheses of morphological
evolution and to analyze temporal and spatial
patterns of plant speciation. All projects
in my lab emphasize the use of systematics
in comparative plant biology. Current
projects focus on (1) the evolution of developmental
genes and the role of differential
gene expression in generating floral diversity
of monocots, (2) systematics and rates
of diversification in tropical gingers, (3) coradiation
of plants and their pollinators, and
(4) conservation genetics and the use of genetic
tools to illucidate patterns of gene flow
that enable us to trace historical migrations
and distributions and to predict future threats
to genetic diversity of extant plant populations.
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John W. Taylor — Professor,
Plant and Microbial Biology
Taylor Lab
Systematics, development, and evolution of fungi
My research focuses on the evolution of fungi, including fungal phylogenetic relationships, the timing of deep fungal divergences, species recognition, speciation, species maintenance, selection, and accounting for genetic variation in genomic studies.
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