matplotlib Brief Tutorial

• Introduction
  • Features
    • basic function
      • Introduction to use
      • Pyplot example
      • The type of graph
      • Picture example
      • An example of a complete plot of
      • Using style sheets and a control format rcParams
        • style sheets
        • rcParams
    • Intermediate function
      • Artist Tutorials
      • legend Tutorial
      • cycler Tutorial
      • Figure layout change
      • Layout Tutorial
      • Pictures direction control
    • Advanced Features
      • path
      • Path effect
      • Conversion coordinate system
    • colour
      • Specify the color
      • Custom Colorbars
      • Custom colormap
      • colormap distribution
      • Select colormap
    • text
      • Matplotlib Plots text
      • Attributes and text layout
      • Note
      • Mathematical expression
      • Use latex rendering text
• actual use

Introduction

Official Tutorial
Chinese Tutorial

Features

basic function

Introduction to use

• Basic concepts
  Legend, marker; Figure, axes, Axis; Spines
  Artist (text, Line2D, Collection, Patch ...)
• Data type
  array
• Namespace
  matplotlib.pyplotwith numpyuse (pylab deprecated)
• FIG generating a plurality of
  plt.subplots(row, col) may generate a plurality of axes
• Interactive mode
  plt.draw()if you do not appear on the screen, call the function

• Convenient features
  simplified segments:
  by path.simplifyand path.simplify_threshold
  simplifying the Marker:
  by markevery plt.plot(x, y, markevery=10)referring before Markevery Demo
  line block:
  mpl.rcParams['agg.path.chunksize'] = 0
  Use Rapid Format:
  In order to avoid other formats are changed, at the end of call can not change other settings
  import matplotlib.style as mplstyle
mplstyle.use('fast')

  Pyplot example

• Line charts, scatter plots, histograms
• Color scattergram shown, FIG.
• FIG plurality of drawing
• Insert text
• Insert mathematical formulas
• Insert comment text

• Axis will automatically adapt to different data: linear, exponential, etc.

The type of graph

• line plot()
• FIG plurality of sub subplot()
• display image imshow()
• Pseudo-color and contour pcolormesh(),contour()
• Histogram hist()
• path matplotlib.path
• 3D 3D plotting
• Flow chart streamplot()
• Oval for certain specific tasks ..
• Bar chart bar()
• Pie pie()
• form table()
• Scatter scatter()
• Filling curve fill()
• Time series data matplotlib.tickerandmatplotlib.dates
• Index semilogx(), semilogy()andloglog()
• Polar plot polar()
• Icon legend()
• tex text matplotlib.mathtext;usetex

Picture example

• Importing Pictures module import matplotlib.image as mpimg; can be used Pillow library, Matplotlibonly support PNG
• Read picture img = mpimg.imread('../../doc/_static/stinkbug.png')
• display image imgplot = plt.imshow(img)
• Color bar plt.colorbar()
• Different picture mode (set display range, etc.)

An example of a complete plot of

• data
• Download Data
• 控制格式 plt.style.use('fivethirtyeight') plt.rcParams.update({'figure.autolayout': True})
  tips: Customizing Matplotlib with style sheets and rcParams
• Plt change attributes, change more than once pyplot.setp()
• FIG resizing fig, ax = plt.subplots(figsize=(8, 4))
• Format Axis Control ax.xaxis.set_major_formatter(formatter) ticker.FuncFormatter
• save Picture figure.Figure.savefig()

Using style sheets and a control format rcParams

style sheets

• The optional format plt.style.available
• Define your own format mpl_configdir/stylelib/presentation.mplstyle
• Format Combination plt.style.use(['dark_background', 'presentation'])
• Temporary format with plt.style.context('dark_background'):

rcParams

• Directly matplotlib.rcParamsmodify the formatting, such asmpl.rcParams['lines.linewidth'] = 2
• Using matplotlib.rc()modified form, such asmpl.rc('lines', linewidth=4, color='g')
• Use matplotlib.rcdefaults()restore the default configuration
• The default configuration in matplotlibrcfile

Intermediate function

Artist Tutorials

Three-tier structure:

1. Drawing area matplotlib.backend_bases.FigureCanvas
2. Drawing Methods matplotlib.backend_bases.Renderer
3. Used rendererin canvasthe drawing on thematplotlib.artist.Artist

Artist divided into two categories:

1. primitives include: Line2D, Rectangle, Text, AxesImage, etc
2. containers include: Axis, AxesandFigure

Axes are usually distributed in rows and columns, use add_axes()in any position to create axes

legend Tutorial

legend entry: Each legend by one or more of legend entryconfiguration
legend key: left tag or color modes
legend label: text description of the handle
legend handle: The handle described

cycler Tutorial

Data processing cycle ps.

Figure layout change

subplots(): Create Layout and axes
GridSpec: Reset figure layout
SubplotSpec: a given layout, create a sub-graph
subplot2grid(): create a child within the grid of FIG.

Layout Tutorial

• constrained_layout = ture Avoid the coordinates, text overlap
• The impact colorbars, Suptitle, Legends layout
• Manual layout
• Another option tight_layout()

Pictures direction control

Through originthe extent kwargsaxes of the picture parameter control

Advanced Features

path

Draw a path path

Path effect

Set Path WordArt effect

Conversion coordinate system

Offset?

colour

Specify the color

Set the color method

• RGB or RGBA float through 0-1 (0.1, 0.2, 0.5) or (0.1, 0.2, 0.5, 0.3)
• RGB or RGBA strings #0f0f0for#0f0f0f80
• 0-1 a floating point number gradation 0.5
• Color abbreviation {'b', 'g', 'r', 'c', 'm', 'y', 'k', 'w'}
• X11 / CSS4 color name black
• xkcd color xkcd:sky blue
• Uppercase C with digital C0according to style changes, with the highest number do not know how much ... (seaborn six colors axes.prop_cycle: cycler('color', ['4C72B0', '55A868', 'C44E52', '8172B2', 'CCB974', '64B5CD']))

Custom Colorbars

• Substantially continuous colorbar
• colorbar discrete intervals
• Setting the length of the colorbar

Custom colormap

Get the value of the colormap changes; providing a plurality of colormap

colormap distribution

Generally linear profile, need to be adjusted in some cases

Select colormap

Select colormap color mode

text

Matplotlib Plots text

Basic Commands

• The text axes anywhere to add text
• Annotate anywhere on the annotate axes, an optional arrow
• xlabel axes of the x-axis labels
• ylabel axes y-axis labels
• title axes title
• On figtext figure anywhere to add text
• suptitle figure add title

x- and y- axis-axis text format

• Distribution location
• Font format text parameters
• Spacer pad

title

• Distribution location
• Spacer pad

Scale and the scale labels

• Main scale, minor division
• Range scale display
• Scale display format

Attributes and text layout

• alpha transparency
• color color
• position location
• rotation rotation

Coordinate transformation?
Non-Latin characters?

Note

• Text styles
• Arrow format (which may be round, block, various arrows, etc.)
  PS. Highlight annotation data is realized by the marker

Mathematical expression

• Support latex plot mathematical expressions
  ps. Use mathtype edit, export it

Use latex rendering text

no need..

actual use

According to the official document example + API documentation modify and use as needed

Use figure.Figure.savefig()Save as PDF