Drawing: Matplotlib

Used to draw some data graph, the classmate recommended, very useful. Very good official documents: http://matplotlib.org/contents.html

0. Installation

Can be directly pip install, there are some dependencies follow the prompts, specifically also forget.

1. Basic Drawing

Import= [1,2,3,4= [1,2,3,4]plt.plot (XS, YS) plt.show ()

XS represents the x-coordinate of the point, Ys represents the y-coordinate of the point, the point that is drawn is (Xs[i], ys[i]), and by default, the dots are connected in turn by line. You can see a popup with a straight line that has a slope of 1 at the origin point. Note that after show, you can't show again, you need to plot again. Indicates that the plot module is stateful.

2. Scatter point

You can set the drawing point mode (markers), connect the dots without using a straight line, and just draw a scatter point:

Import= [1,2,3,4= [1,2,3,4]plt.plot (XS, YS, "ob");p lt.show ()

What you see at this point is a few discrete points. Here "OB" means to use the marker of the circle and the color is blue, where filled_markers can be:

' O '-dots, ' V '-inverted triangles, ' ^ '-deltoid, ' < '-left triangle, ' > '-Right triangle, ' 8 ', ' s '-square, ' p '-convex pentagon, ' * '-pentagram, ' h ', ' h ', ' d '-rhombus, ' d '-Flat Diamond

All possible markers is defined here:

Marker	Description
”.”	Point
”,”	Pixel
"O"	Circle
"V"	Triangle_down
^	Triangle_up
"<"	Triangle_left
">"	Triangle_right
"1"	Tri_down
"2"	Tri_up
"3"	Tri_left
"4"	Tri_right
"8"	Octagon
"S"	Square
"P"	Pentagon
“*”	Star
"H"	Hexagon1
H	Hexagon2
+	Plus
"X"	X
D	Diamond
"D"	Thin_diamond
|	VLine
“_”	Hline
Tickleft	Tickleft
Tickright	Tickright
Tickup	Tickup
Tickdown	Tickdown
Caretleft	Caretleft
Caretright	Caretright
Caretup	Caretup
Caretdown	Caretdown
"None"	Nothing
None	Nothing
” “	Nothing
“”	Nothing
' $...$ '	Render the string using Mathtext.
Verts	A list of (x, y) pairs used for Path vertices. The center of the marker is located at (0,0) and the size is normalized.
Path	A Path instance.
(numsides, style, angle)	See below

Http://matplotlib.org/api/markers_api.html#module-matplotlib.markers

3. Populating the data

Can be combined with numpy to quickly fill the data, draw a graph

>>> Import NumPy as NP
>>> Import Matplotlib.pyplot as Plt
>>> x=np.arange (0, 4, 0.05)>>>Xarray ([0. ,  0.05, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4 ,        0.45, 0.5, 0.55, 0.6, 0.65, 0.7, 0.75, 0.8, 0.85,        0.9, 0.95, 1. , 1.05, 1.1, 1.15, 1.2, 1.25, 1.3 ,        1.35, 1.4, 1.45, 1.5, 1.55, 1.6, 1.65, 1.7, 1.75,        1.8, 1.85, 1.9, 1.95, 2. , 2.05, 2.1, 2.15, 2.2 ,        2.25, 2.3, 2.35, 2.4, 2.45, 2.5, 2.55, 2.6, 2.65,        2.7, 2.75, 2.8, 2.85, 2.9, 2.95, 3. , 3.05, 3.1 ,        3.15, 3.2, 3.25, 3.3, 3.35, 3.4, 3.45, 3.5, 3.55,        3.6, 3.65, 3.7, 3.75, 3.8, 3.85, 3.9, 3.95])>>> plt.plot (x, Np.sin (0.5 * Np.pi *x)) [<matplotlib.lines.line2d Object at 0x11314a810>]>>> Plt.show ()

4. Line Style

Controlling Line Properties

Lines has many attributes that can set:linewidth, dash style, antialiased, etc; See Matplotlib.lines.Line2D. There is several ways to set line properties

• use keyword args:

   plt. (xy Linewidth=2.0)       

• use the setter methods of THE&NBSP;line2d  instance. plot  returns a list of Lines E.G.,&NBSP;line1, line2  = plot (x1,y1,x2,y2) . Below I has only one line so it is a list of length 1. I use a tuple unpacking in the line, =  plot (X, y,  ' O ')  to Get the first element of the list:

  Lineplt.  Plot(xy'-')line.  set_antialiased(False# Turn off antialising         

• Use the setp () command. The example below uses a Matlab-style command to set multiple properties on a list of lines. SETPworks transparently with a list of objects or a single object. You can either use Python keyword arguments or matlab-style string/value pairs:

  Lines=Plt.Plot(X1,y1x2y2 # use keyword Argsplt. Setp (linescolor=  ' R ' linewidth=2.0 ) # or MATLAB style string value Pairsplt. Setp (lines ' color '  ' R '  ' linewidth ' 2.0 )               /span>                

Here is the available line2d properties.

Property

	Value Type
Alpha	Float
Animated	[True | False]
antialiased or AA	[True | False]
Clip_box	A Matplotlib.transform.Bbox instance
clip_on	[True | False]
Clip_path	A Path instance and a Transform instance, a Patch
Color or C	Any matplotlib color
Contains	The hit testing function
Dash_capstyle	[' Butt ' | ' Round ' | ' projecting ']
Dash_joinstyle	[' miter ' | ' Round ' | ' bevel ']
Dashes	Sequence of On/off ink in points
Data	(Np.array xdata, Np.array ydata)
Figure	A Matplotlib.figure.Figure instance
Label	Any string
LineStyle or LS	[ '-' | '---' | '-. ' | ': ' | ' Steps ' | ...]
LineWidth or LW	Float value in points
Lod	[True | False]
Marker	[ ' + ' | ', ' | '. ' | ' 1 ' | ' 2 ' | ' 3 ' | ' 4 ' ]
Markeredgecolor or MEC	Any matplotlib color
Markeredgewidth or Mew	Float value in points
Markerfacecolor or MFC	Any matplotlib color
Markersize or MS	Float
Markevery	[None | integer | (Startind, Stride)]
Picker	Used in interactive line selection
Pickradius	The line pick selection radius
Solid_capstyle	[' Butt ' | ' Round ' | ' projecting ']
Solid_joinstyle	[' miter ' | ' Round ' | ' bevel ']
Transform	A Matplotlib.transforms.Transform instance
Visible	[True | False]
XData	Np.array
Ydata	Np.array
ZOrder	Any number

Drawing: Matplotlib