Python手册(Visualise)--matplotlib

matplotlib摘要

Matplotlib

import matploblib.pyplot as plt

Parts of Figure

一般通过get_<part>方法获得组件属性，set_<part>方法重设组件。

Workflow

Step 1 Prepare data
Step 2 Create figure
Step 3 Add axes
Step 4 Customize plot
Step 5 Save plot
Step 6 Show plot

>>> import matplotlib.pyplot as plt 
>>> x = [1,2,3,4] 
>>> y = [10,20,25,30] 
>>> fig = plt.figure() 
>>> ax = fig.add_subplot(111) 
>>> ax.plot(x, y, color='lightblue', linewidth=3)
>>> ax.set_xlim(1, 6.5) 
>>> plt.savefig('foo.png') 
>>> plt.show()

Figure and Axes

plt.subplots
plt.subplots(nrows=1, ncols=1, sharex=False, sharey=False,...) Create a figure and a set of subplots

Parameters:
nrows, ncols : (int) 分割figure行数和列数
sharex, sharey : bool or {‘none’, ‘all’, ‘row’, ‘col’}, 是否共享坐标轴

>>> fig, ax = plt.subplots() 
>>> f, (ax1, ax2) = plt.subplots(1, 2, sharey=True)

Create Figure

plt.figure(num=None, figsize=None, dpi=None, facecolor=None, edgecolor,...)

Parameters:
num : (integer or string) figure编号
figsize : (tuple of integers) figure尺寸
dpi : (integer) 分辨率

Add Axes

fig.add_subplot(nrows, ncols, plot_number)

nrows, ncols, plot_number: 分割figure行数和列数，axes的位置

fig.add_axes(rect) 可以添加图中图

Parameters:
rect : [left, bottom, width, height]
projection : [‘aitoff’ | ‘hammer’ | ‘lambert’ | ‘mollweide’ | ‘polar’ | ‘rectilinear’], optional
polar : boolean, optional

plt.subplot2grid(shape, loc, rowspan=1, colspan=1) 建造不规则axes

Parameters:
shape: figue分割
loc: 原点位置，基于shape分割结果
rowspan, colspan: 行或列的跨度

ax1 = plt.subplot2grid((3,3), (0,0), colspan=3)  
ax2 = plt.subplot2grid((3,3), (1,0), colspan=2)  
ax3 = plt.subplot2grid((3,3), (1, 2), rowspan=2)  
ax4 = plt.subplot2grid((3,3), (2, 0))  
ax5 = plt.subplot2grid((3,3), (2, 1))  
plt.suptitle("subplot2grid")

subplot2grid

Parts of Axes

Axis(x axis)	说明
ax.set_xlabel(xlabel, fontdict=None, labelpad=None)	x轴标签
ax.set_xticks(ticks, minor=False)	刻度
ax.set_xticklabels(labels, fontdict=None, minor=False)	x轴刻度标签
ax.set_xlim(left=None, right=None)	x轴限制
ax.set_title(label, fontdict=None, loc=’center’)	loc : {‘center’, ‘left’, ‘right’}, str, optional

# x轴刻度标签属性设置，其他组件属性设置基本相同
xlabel=ax.get_xticklabels()
label.set_fontsize(...)
label.set_bbox(...)

Spines

ax.spines['left'].set_color('b') # 左侧线条修改为蓝色
ax.spines['top'].set_visible(False) # 使顶层线条不可见
ax.spines['bottom'].set_position(('outward',10) # 使底层线条外移10

spines: {left,right,top,bottom}

Legend
ax.legend(loc='best', handles,labels)

handles:图例控制对象
labels:图例标签
loc: string or 0:10

Grid
ax.grid(b=None, which='major', axis='both')

Parameters:
which: ‘major’ (default), ‘minor’, or ‘both’
axis: ‘both’ (default), ‘x’, or ‘y’

annotate and Text

ax.annotate()

Parameters:
s : str
xy : iterable
xytext : iterable, optional
xycoords : str, Artist, Transform, callable or tuple, optional
textcoords : str, Artist, Transform, callable or tuple, optional
fontsize:
arrowprops : dict, optional

ax.text(x, y, s, fontdict=None, withdash=False)

Plot

常用图形	说明
plot(x,y,data)	默认折线图
scatter(x, y, s, c, marker, cmap)	散点图{s:size,c:color}
hist(x, bins)	直方图
bar(x, height, width, fill)	柱状图
barh(y, height, width, fill)	横向柱状图
boxplot(y)	箱线图
violinplot(y)
contourf(X,Y,Z,N,cmap)	等高线填充
contour(X,Y,Z,N)	等高线线条
imshow()	热图
quiver()	矢量场
pie(x, explode, labels, colors)	饼图

Parameters:
Alpha
Colors, Color Bars & Color Maps
Markers: marker , size
Line: linestyle, linewidth

Axes3D

from matplotlib import cm
from mpl_toolkits.mplot3d import Axes3D

X = np.arange(-5, 5, 0.25)
Y = np.arange(-5, 5, 0.25)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X**2 + Y**2)
Z = np.sin(R)

fig = plt.figure()
ax = Axes3D(fig)
ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.viridis)
plt.show()

Animation

import matplotlib.animation as animation

fig, ax = plt.subplots()
x = np.arange(0, 2*np.pi, 0.01)
line, = ax.plot(x, np.sin(x))
def init():  # only required for blitting to give a clean slate.
    line.set_ydata([np.nan] * len(x))
    return line,
def animate(i):
    line.set_ydata(np.sin(x + i / 100))  # update the data.
    return line,
ani = animation.FuncAnimation(
    fig, animate, init_func=init, interval=2, blit=True, save_count=50)
plt.show()

Save and Show

fig.savefig(fname) # or plt.savefig
fig.show(warn=True) # or plt.show