面向对象绘图

# Matplotlib中图像的结构

atplotlib图像中最重要的三个对象分别是figure(画布)，ax(坐标系)，axis (坐标轴)。一个figure中可以有多个 ax（多个子图），figure可以设置图像的尺寸，背景色，像素等。一个ax中一般有多个 axis，如xaxis，yaxis。ax可以设置子图的大小，标题，数据的呈现形式，线型，颜色等。axis又有label，tick等对象，可以设置坐标轴刻度，坐标轴标签，坐标轴标题等。

面向对象绘图一般自上而下： 0，绘图前设置绘图风格等全局参数，例如style，font等。

1，开始绘图时，首先是figure对象布局，包括大小size，像素dpi等。

2，接着是axes对象规划，包括图形(如点线柱饼)，axes区域(如背景颜色，栅格，图例)等。

3，然后是axis对象设置，包括坐标轴，刻度线，标签等。

4，最后是添加文字信息，包括标题，数据标注，其他文字说明等。

绘图前设置绘图风格等全局参数

例如style，font等。

# 查看可用的绘图风格
print(plt.style.available)

# 选择绘图风格
plt.style.use('bmh')

# 用来正常显示中文标签
plt.rcParams['font.sans-serif'] = ['FangSong'] # 指定默认字体
# 解决符号‘-’显示为方块的问题
plt.rcParams['axes.unicode_minus'] = False

# 设置全局默认字体属性
font = {'weight': 'bold', 'size': 15}
plt.rc('font', **font)

1，开始绘图时，首先是figure对象布局，包括大小figsize,像素dpi等。

参考

fig = plt.figure()

2，接着是axes对象规划，包括图形(如点线柱饼),axes区域(如背景颜色,栅格,图例)等。

ax = fig.add_subplot(111, facecolor=(0, 1, 0, 0.3))
# ax.figure(dpi=600)
ax.plot(x, y,
        label='$sin(x)$',
        color='r',
        linestyle="-",
        linewidth=3,
        marker="o", markeredgecolor='g', markersize=8,
        markerfacecolor='red',
        alpha=0.8)
# 网格设置
ax.grid(color='b', linestyle=':', linewidth=1)
# 图例设置
ax.legend(loc='best', fontsize=18, frameon=True)
plt.show()

3，然后是axis对象设置，包括坐标轴，刻度线，标签等。

# 坐标轴的范围
ax.axis([-0.5, 6.5, -1.1, 1.1])

# 设置刻度
ax.xaxis.set_ticks([0, np.pi / 2, np.pi, 3 * np.pi / 2, 2 * np.pi])
# 设置刻度标签
ax.xaxis.set_ticklabels(['$0$', '$\\frac{\pi}{2}$',
                         '$\pi$', '$\\frac{3\pi}{2}$',
                         '$2\,\pi$'

                         ])
# ax.set_xticks()
# ax.set_xticklabels()
# ax.xaxis.set_major_locator()
# ax.xaxis.set_major_formatter()

# 设置坐标轴标题
ax.set_xlabel('X ', fontsize=20)
ax.set_ylabel('Y ', fontsize=20, rotation=0)
# ax.xaxis.set_label_text('X',fontsize = 20)
# ax.yaxis.set_label_text('y',fontsize = 20,rotation =0)

# 设置坐标轴。标签的位置
ax.xaxis.set_label_coords(1,-0.05)
ax.yaxis.set_label_coords(-0.05,1)

# 设置坐标轴是否可见
ax.spines['right'].set_visible(False)

#设置坐标轴颜色，当颜色为 none 时，坐标轴不可见
ax.spines['top'].set_color('none')
ax.spines['bottom'].set_color('red')

# 移动坐标轴的位置
ax.spines['left'].set_position(("data",0))
ax.spines['bottom'].set_position(("data",0))

4，最后是添加文字信息，包括标题，数据标注，其他文字说明等。

# 设置标题
ax.set_title(u'正弦曲线',color='black',fontsize=20)

# ax.annotate(-3.7, 3, r'$This\ is\ the\ some\ text. \mu\ \sigma_i\ \alpha_t$',
#          )
# ax.text(0.85,0.75,'matplotlib\n plot',fontsize=20,
#         horizontalalignment='center',
#         verticalalignment='center',
#         transform= ax.transAxes,
#         bbox=dict(facecolor='green',alpha=0.6))


fig.savefig(u'02020202.png',dpi=600)

其它方法;

formatter = ticker.FormatStrFormatter('$%1.2f')
ax.yaxis.set_major_formatter(formatter)

case 1

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker

# Fixing random state for reproducibility
np.random.seed(19680801)

fig, ax = plt.subplots()
ax.plot(100*np.random.rand(20))

formatter = ticker.FormatStrFormatter('$%1.2f')
ax.yaxis.set_major_formatter(formatter)

for tick in ax.yaxis.get_major_ticks():
    tick.label1.set_visible(False)
    tick.label2.set_visible(True)
    tick.label2.set_color('green')
# ax.yaxis.get_major_ticks() 返回两个纵轴的坐标，label1，label2分别表示不同的轴

plt.show()

Formatters and Locators

'Axis.get_major_formatter'        Get the formatter of the major ticker
'Axis.get_major_locator'        Get the locator of the major ticker
'Axis.get_minor_formatter'        Get the formatter of the minor ticker
'Axis.get_minor_locator    '        Get the locator of the minor ticker
'Axis.set_major_formatter'        Set the formatter of the major ticker.
'Axis.set_major_locator    '        Set the locator of the major ticker.
'Axis.set_minor_formatter'        Set the formatter of the minor ticker.
'Axis.set_minor_locator'        Set the locator of the minor ticker.

from matplotlib.ticker import NullFormatter, FixedLocator
ax.grid(True)
ax.set_xlim([-180, 180])
ax.yaxis.set_minor_formatter(NullFormatter())
ax.yaxis.set_major_locator(FixedLocator(np.arange(-90, 90, 30)))

主、副刻度密度的设置

ax.xaxis.set_major_locator(MultipleLocator(20))  # 设置20倍数
ax.xaxis.set_major_formatter(FormatStrFormatter('%5.1f'))  # 设置文本格式

# y轴
ax.yaxis.set_major_locator(MultipleLocator(100))  # 设置100倍数
ax.yaxis.set_major_formatter(FormatStrFormatter('%1.2f'))  # 设置文本格式

# 设置轴的副刻度
# x轴
ax.xaxis.set_minor_locator(MultipleLocator(5))  # 设置10倍数
# ax.xaxis.set_minor_formatter(FormatStrFormatter('%2.1f'))  # 设置文本格式

# y轴
ax.yaxis.set_minor_locator(MultipleLocator(50))  # 设置50倍数
# ax.yaxis.set_minor_formatter(FormatStrFormatter('%1.0f'))  # 设置文本格式

Axis Label

'Axis.set_label_coords'        Set the coordinates of the label.
'Axis.set_label_position'    Set the label position (top or bottom)
'Axis.set_label_text'        Set the text value of the axis label.
'Axis.get_label_position'    Return the label position (top or bottom)
'Axis.get_label_text'        Get the text of the label

Ticks, tick labels and Offset text

'Axis.grid'                    Configure the grid lines.
'Axis.set_tick_params'        Set appearance parameters for ticks, ticklabels, and gridlines.
'Axis.axis_date'            Sets up axis ticks and labels treating data along this axis as dates.

axis.Axis.set_tick_params

Set appearance parameters for ticks, ticklabels, and gridlines.

参数：Matplotlib：tick_params matplotlib.axes.Axes.tick_params

axes.Axes.set_title

Axes.set_title(self, label, 
               fontdict=None, 
               loc=None, pad=None, 
               *, y=None, **kwargs)

参数：

label : str Text to use for the title
fontdict :dict A dictionary controlling the appearance of the title text, the default fontdict is:

{'fontsize': rcParams['axes.titlesize'], 'fontweight': rcParams['axes.titleweight'], 'color': rcParams['axes.titlecolor'], 'verticalalignment': 'baseline', 'horizontalalignment': loc}
loc: {'center', 'left', 'right'}, default: rcParams["axes.titlelocation"] (default: 'center')which title to set.
y: float, default: rcParams["axes.titley"] (default: None)

Vertical axes loation for the title (1.0 is the top). If None (the default), y is determined automatically to avoid decorators on the axes.
pad :float, default: rcParams["axes.titlepad"] (default: 6.0)

The offset of the title from the top of the axes, in points.

返回值：

Text

The matplotlib text instance representing the title

Discouraged

'Axis.set_ticklabels'    Set the text values of the tick labels.
'Axis.set_ticks'    Set the locations of the tick marks from sequence ticks

双Y轴

ax2 = ax1.twinx()  # instantiate a second axes that shares the same x-axis

ax2.tick_params(axis='y', labelcolor=color)
# 刻度和标签设置

matplotlib.axes.Axes.tick_params

设置刻度线和刻度标签的位置 matplotlib.axis.YAxis.set_ticks_position

axis.Axis.set_ticks()

设置刻度和标签

Axis.set_ticks(self, ticks, minor=False)
        ticks : sequence of floats
        minor : bool
设置刻度和标签

Axis.set_ticks_position(self, position)

设置刻度和标签的位置

YAxis.set_ticks_position(self, position)

Parameters:    
position : {'left', 'right', 'both', 'default', 'none'}

如果时y轴的，可以设置参数为上面的

# loc 表示位置，spine表示当前位置的对象
for loc, spine in ax.spines.items():
       print(loc)
       print(spine)

left
Spine
right
Spine
bottom
Spine
top
Spine

spines.Spine.set_position()

设置 X，Y,轴分离开：

1.spines.Spine.set_position
.set_position(self, position)

spine.set_position(('outward', 10))  # outward by 10 points

2. .set_color(self, c)

3. .set_smart_bounds(self, value)

Spine Placement Demo:

fig = plt.figure()
x = np.linspace(-np.pi, np.pi, 100)
y = 2 * np.sin(x)

ax = fig.add_subplot(2, 2, 1)
ax.set_title('centered spines')
ax.plot(x, y)
ax.spines['left'].set_position('center')
ax.spines['right'].set_color('none')
ax.spines['bottom'].set_position('center')
ax.spines['top'].set_color('none')
ax.spines['left'].set_smart_bounds(True)
ax.spines['bottom'].set_smart_bounds(True)
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')

ax = fig.add_subplot(2, 2, 2)
ax.set_title('zeroed spines')
ax.plot(x, y)
ax.spines['left'].set_position('zero')
ax.spines['right'].set_color('none')
ax.spines['bottom'].set_position('zero')
ax.spines['top'].set_color('none')
ax.spines['left'].set_smart_bounds(True)
ax.spines['bottom'].set_smart_bounds(True)
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')

ax = fig.add_subplot(2, 2, 3)
ax.set_title('spines at axes (0.6, 0.1)')
ax.plot(x, y)
ax.spines['left'].set_position(('axes', 0.6))
ax.spines['right'].set_color('none')
ax.spines['bottom'].set_position(('axes', 0.1))
ax.spines['top'].set_color('none')
ax.spines['left'].set_smart_bounds(True)
ax.spines['bottom'].set_smart_bounds(True)
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')

ax = fig.add_subplot(2, 2, 4)
ax.set_title('spines at data (1, 2)')
ax.plot(x, y)
ax.spines['left'].set_position(('data', 1))
ax.spines['right'].set_color('none')
ax.spines['bottom'].set_position(('data', 2))
ax.spines['top'].set_color('none')
ax.spines['left'].set_smart_bounds(True)
ax.spines['bottom'].set_smart_bounds(True)
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')

```python import matplotlib.pyplot as plt import numpy as np

def adjust_spines(ax,spines): for loc, spine in ax.spines.items(): if loc in spines: spine.set_position(('outward', 10)) # outward by 10 points else: spine.set_color('none') # don't draw spine

# turn off ticks where there is no spine
if 'left' in spines:
    ax.yaxis.set_ticks_position('left')
else:
    # no yaxis ticks
    ax.yaxis.set_ticks([])

if 'bottom' in spines:
    ax.xaxis.set_ticks_position('bottom')
else:
    # no xaxis ticks
    ax.xaxis.set_ticks([])

fig = plt.figure()

x = np.linspace(0,2np.pi,100) y = 2np.sin(x)

ax = fig.add_subplot(2,2,1) ax.plot(x,y) adjust_spines(ax,['left'])

ax = fig.add_subplot(2,2,2) ax.plot(x,y) adjust_spines(ax,[])

ax = fig.add_subplot(2,2,3) ax.plot(x,y) adjust_spines(ax,['left','bottom'])

ax = fig.add_subplot(2,2,4) ax.plot(x,y) adjust_spines(ax,['bottom'])

plt.show()

```

...... 更多参考官方文档：https://matplotlib.org/api/axis_api.html

面向对象绘图

面向对象绘图

绘图前设置绘图风格等全局参数

1，开始绘图时，首先是figure对象布局，包括大小figsize,像素dpi等。

2，接着是axes对象规划，包括图形(如点线柱饼),axes区域(如背景颜色,栅格,图例)等。

3，然后是axis对象设置，包括坐标轴，刻度线，标签等。

4，最后是添加文字信息，包括标题，数据标注，其他文字说明等。

Formatters and Locators

Axis Label

Ticks, tick labels and Offset text

axis.Axis.set_tick_params

axes.Axes.set_title

Discouraged

axis.Axis.set_ticks()

Axis.set_ticks_position(self, position)

spines.Spine.set_position()

results matching ""

No results matching ""