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‎slides/anatomy.pdf‎

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‎slides/beamerouterthemenoslideno.sty‎

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\defbeamertemplate*{footline}{noslidenum theme}
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{
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\leavevmode%
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\hbox{%
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\begin{beamercolorbox}[wd=.3\paperwidth,ht=2.25ex,dp=1ex,center]{author in head/foot}%
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\usebeamerfont{author in head/foot}\insertshortauthor~~\beamer@ifempty{\insertshortinstitute}{}{(\insertshortinstitute)}
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\end{beamercolorbox}%
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\begin{beamercolorbox}[wd=.4\paperwidth,ht=2.25ex,dp=1ex,center]{title in head/foot}%
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\usebeamerfont{title in head/foot}\insertshorttitle
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\end{beamercolorbox}%
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\begin{beamercolorbox}[wd=.3\paperwidth,ht=2.25ex,dp=1ex,right]{date in head/foot}%
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\usebeamerfont{date in head/foot}\insertshortdate{}\hspace*{2em}
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\end{beamercolorbox}}%
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\vskip0pt%
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}

‎slides/slides.org‎

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#+OPTIONS: ':nil *:t -:t ::t <:t H:2 \n:nil ^:t arch:headline
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#+OPTIONS: author:t c:nil creator:comment d:nil date:t e:t email:nil
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#+OPTIONS: f:t inline:t num:t p:nil pri:nil prop:nil stat:t tags:t
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#+OPTIONS: tasks:t tex:t timestamp:t toc:nil todo:t |:t
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#+TITLE: Interactive Matplotlib Tutorial
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#+EMAIL: tcaswell@bnl.gov
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#+DATE: 2017-11-06
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#+AUTHOR: Thomas A Caswell
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#+DESCRIPTION:
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#+KEYWORDS:
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#+LANGUAGE: en
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#+INFOJS_OPT: view:nil toc:nil ltoc:t mouse:underline buttons:0 path:http://orgmode.org/org-info.js
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#+EXPORT_SELECT_TAGS: export
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#+EXPORT_EXCLUDE_TAGS: noexport
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#+LINK_UP:
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#+LINK_HOME:
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#+startup: beamer
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#+LaTeX_CLASS: beamer
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#+LaTeX_CLASS_OPTIONS: [x11names]
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#+LATEX_HEADER: \usemintedstyle{emacs}
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#+BEAMER_HEADER: \institute[BNL]{Brookhaven National Labratory}
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#+latex_header: \setbeamertemplate{navigation symbols}{}%remove navigation symbols
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#+latex_header: \usepackage{multicol}
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#+latex_header: \mode<beamer>{\usetheme{Madrid}} \setbeamertemplate{navigation symbols}{} \usepackage{color} \useoutertheme{noslideno} \useinnertheme{default}
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#+BEAMER_COLOR_THEME: seahorse
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#+BEAMER_THEME: Madrid
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#+BEAMER_INNER_THEME: default
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#+BEAMER_HEADER_EXTRA: \includeonlyframes{current}
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#+COLUMNS: %40ITEM %10BEAMER_env(Env) %9BEAMER_envargs(Env Args) %4BEAMER_col(Col) %10BEAMER_extra(Extra)
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#+PROPERTY: BEAMER_col_ALL 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 :ETC
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* 00 Introduction to OO Matplotlib
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** Parts of a Figure
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[[./anatomy.pdf]]
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https://matplotlib.org/tutorials/introductory/usage.html#parts-of-a-figure
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** Matplotlib Layers
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- =Renderer= :: Internal, handles final 'on screen' or 'on disk' version
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- =Canvas= :: Manages a =Figure= and and a =Renderer=
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- Transforms :: between coord systems {'data', 'axes', 'figure', 'screen'}
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- Artists :: 'middle layer', given a =Renderer= can draw self
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- =Axes= and =Figure= methods :: create =Artists= and add to draw-tree
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- =pyplot= :: create =Artists= and add to draw-tree
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\hline
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- UI events :: mouse/keyboard events
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** =pyplot=
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- =pyplot= is intentionally very close to MATLAB ploting API
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- pro: easy for people switching from MATLAB
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- pro: =pyplot= is much terser
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- con: makes some interesting design choices
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- con: has buckets of global state
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- Everything in =pyplot= implemented in terms of =00=
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** =Axes= and =Figure= methods
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These classes manage:
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- manage the draw tree (hold that thought)
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- manage figure size, dpi, axes layout, view limits, axis scales
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- namespace for plotting functions
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- =ax.plot=
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- =ax.hist=
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- =ax.imshow=
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- ...
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https://matplotlib.org/api/axes_api.html
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** =Aritsts=
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- Everything that you see in the figure is an =Artist= (because it draws
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on the =Canvas=)
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- text, marks, images, spines, background patches
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- responsible for translating internal state -> to =Renderer= method calls
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- can mutate everything and re-draw
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- =obj.set_*= and =obj.get_*= methodsy
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** draw via visitor pattern
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#+BEGIN_SRC python
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class Canvas:
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def draw(self):
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render = self.get_renderer()
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self.figure.draw(renderer)
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class Figure:
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def draw(self, renderer):
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self.patch.draw(renderer)
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for artist in self.get_children():
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artist.draw(renderer)
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class Line2D:
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def draw(self, renderer):
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renderer.draw_path(self.verticies, ...)
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#+END_SRC
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** =Tansforms= and coordinate systems
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+-----------+-----------------------------+-----------------------------------+
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|Coords |Transformation object |Description |
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+-----------+-----------------------------+-----------------------------------+
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|"data" | ax.transData |The coordinate system for the data,|
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| | |controlled by xlim and ylim. |
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+-----------+-----------------------------+-----------------------------------+
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|"axes" | ax.transAxes |The coordinate system of the |
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| | |Axes; (0, 0) is bottom left of |
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| | | and (1, 1) is top right |
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+-----------+-----------------------------+-----------------------------------+
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|"figure" | fig.transFigure |The coordinate system of the |
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| | |Figure; (0, 0) is bottom left |
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| | | and (1, 1) is top right. |
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+-----------+-----------------------------+-----------------------------------+
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|"display" | IdentityTransform() |The pixel coordinate system of the |
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| | |display; (0, 0) is bottom left |
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| | |and (width, height) is top right |
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| | |in pixels. |
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+-----------+-----------------------------+-----------------------------------+
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https://matplotlib.org/tutorials/advanced/transforms_tutorial.html
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** =Canvas=
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- holds a =Figure= instance
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- knows how to make a =Renderer= instance
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- for GUI backends typically uses MI and *is* the native GUI widget
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https://matplotlib.org/gallery/index.html#embedding-matplotlib-in-graphical-user-interfaces
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** =Renderer=
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Takes low-level data and renders to output
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Minimal set of methods:
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#+BEGIN_SRC python
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class Renderer:
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def draw_path(self, ...):
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...
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def draw_image(self, ...):
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...
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def draw_text(self, ...):
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...
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def get_text_width_height_descent(self, ...):
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...
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#+END_SRC
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May have other methods to allow for optimizations
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Typically should not have to know this exists (unless implementing a
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new backend).
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** UI events on =Canvas=
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+-----------------------+----------------------------------------+
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|Event name | Description |
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+-----------------------+----------------------------------------+
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|`button_press_event' | mouse button is pressed |
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|`button_release_event' | mouse button is released |
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|`draw_event' | canvas draw (but before screen update) |
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|`key_press_event' | key is pressed |
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|`key_release_event' | key is released |
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|`motion_notify_event' | mouse motion |
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|`pick_event' | an object in the canvas is selected |
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|`resize_event' | figure canvas is resized |
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|`scroll_event' | mouse scroll wheel is rolled |
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|`figure_enter_event' | mouse enters a new figure |
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|`figure_leave_event' | mouse leaves a figure |
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|`axes_enter_event' | mouse enters a new axes |
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|`axes_leave_event' | mouse leaves an axes |
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+-----------------------+----------------------------------------+
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- =cid = canvas.mpl_connect(event_name, callback)=
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* 00 Installation
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** installation
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=conda create mpl_tut -c anaconda matplotlib pandas pytables ipython python=3.6=

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