Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Fixed grammar mistakes and make reading concise #27

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
Open

Fixed grammar mistakes and make reading concise #27

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
34 changes: 17 additions & 17 deletions README.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,7 @@ Nicolas P. Rougier
:depth: 1

Sources are available from
`github <https://github.com/rougier/matplotlib-tutorial>`_
`GitHub <https://github.com/rougier/matplotlib-tutorial>`_

All code and material is licensed under a `Creative Commons
Attribution-ShareAlike 4.0
Expand All @@ -25,24 +25,24 @@ You can test your installation before the tutorial using the `check-installation

See also:

* `From Python to Numpy <http://www.labri.fr/perso/nrougier/from-python-to-numpy/>`_
* `100 Numpy exercices <https://github.com/rougier/numpy-100>`_
* `From Python to NumPy <http://www.labri.fr/perso/nrougier/from-python-to-numpy/>`_
* `100 NumPy exercises <https://github.com/rougier/numpy-100>`_
* `Ten simple rules for better figures <http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003833>`_


Introduction
============

matplotlib is probably the single most used Python package for 2D-graphics. It
provides both a very quick way to visualize data from Python and
matplotlib use Python package for 2D-graphics. It
provides data visualization from Python and
publication-quality figures in many formats. We are going to explore
matplotlib in interactive mode covering most common cases.

IPython
-------

`IPython <http://ipython.org/>`_ is an enhanced interactive Python shell that
has lots of interesting features including named inputs and outputs, access to
that include named inputs and outputs, access to
shell commands, improved debugging and much more. It allows
interactive matplotlib sessions that have Matlab/Mathematica-like functionality.

Expand All @@ -61,7 +61,7 @@ Simple plot
===========

In this section, we want to draw the cosine and sine functions on the same
plot. Starting from the default settings, we'll enrich the figure step by step
plot. In default settings, we'll enrich the figure step by step
to make it nicer.

The first step is to get the data for the sine and cosine functions:
Expand Down Expand Up @@ -97,10 +97,10 @@ Using defaults
:target: scripts/exercice_1.py

Matplotlib comes with a set of default settings that allow customizing all
kinds of properties. You can control the defaults of almost every property in
kinds of properties. You can control the defaults of every property in
matplotlib: figure size and dpi, line width, color and style, axes, axis and
grid properties, text and font properties and so on. While matplotlib defaults
are rather good in most cases, you may want to modify some properties for
are good in most cases, you may want to modify some properties for
specific cases.


Expand Down Expand Up @@ -144,8 +144,8 @@ Changing colors and line widths
:align: right
:target: scripts/exercice_3.py

As a first step, we want to have the cosine in blue and the sine in red and a
slightly thicker line for both of them. We'll also slightly alter the figure
As a first step, we want cosine in blue and the sine in red and a
slightly thicker line for both. We'll also alter the figure
size to make it more horizontal.


Expand Down Expand Up @@ -227,7 +227,7 @@ Setting tick labels
:align: right
:target: scripts/exercice_6.py

Ticks are now properly placed but their label is not very explicit. We could
Ticks are fixed but their label is not very explicit. We could
guess that 3.142 is π but it would be better to make it explicit. When we set
tick values, we can also provide a corresponding label in the second argument
list. Note that we'll use latex to allow for nice rendering of the label.
Expand Down Expand Up @@ -527,7 +527,7 @@ Animation
=========

For quite a long time, animation in matplotlib was not an easy task and was
done mainly through clever hacks. However, things have started to change since
done through clever hacks. However, things have started to change since
version 1.1 and the introduction of tools for creating animation very
intuitively, with the possibility to save them in all kind of formats (but don't
expect to be able to run very complex animations at 60 fps though).
Expand All @@ -536,15 +536,15 @@ expect to be able to run very complex animations at 60 fps though).

* See `Animation <http://matplotlib.org/api/animation_api.html>`_

The most easy way to make an animation in matplotlib is to declare a
The easiest way to make an animation in matplotlib is to declare a
FuncAnimation object that specifies to matplotlib what is the figure to
update, what is the update function and what is the delay between frames.


Drip drop
---------

A very simple rain effect can be obtained by having small growing rings
Rain effect can be obtained by having small growing rings
randomly positioned over a figure. Of course, they won't grow forever since the
wave is supposed to damp with time. To simulate that, we can use a more and
more transparent color as the ring is growing, up to the point where it is no
Expand Down Expand Up @@ -603,7 +603,7 @@ is almost transparent.

Now, we need to write the update function for our animation. We know that at
each time step each ring should grow and become more transparent while the
largest ring should be totally transparent and thus removed. Of course, we won't
largest ring should be transparent and thus removed. Of course, we won't
actually remove the largest ring but re-use it to set a new ring at a new random
position, with nominal size and color. Hence, we keep the number of rings
constant.
Expand Down Expand Up @@ -725,7 +725,7 @@ can handle. Fortunately, there is the `basemap
of the `cartopy <https://scitools.org.uk/cartopy/docs/latest/>`_ project) that is really
simple to install and to use. First step is to define a projection to draw the
earth onto a screen (there exists many different projections) and we'll stick
to the `mill` projection which is rather standard for non-specialist like me.
to the `mill` projection which is standard for non-specialist like me.


.. code:: python
Expand Down