Python中的 Matplotlib.pyplot.fill_betweenx()

Matplotlib 是Python中用于数组二维图的惊人可视化库。 Matplotlib 是一个基于 NumPy 数组构建的多平台数据可视化库，旨在与更广泛的 SciPy 堆栈配合使用。

matplotlib.pyplot.fill_betweenx()

matplotlib.pyplot.fill_betweenx()用于填充两条垂直曲线之间的区域。两个点 (x1, y) 和 (x2, y) 定义曲线。这将创建一个或多个描述填充区域的多边形。 'where' 参数可用于选择性地填充某些区域。默认情况下，边直接连接给定的点。如果填充需要是阶跃函数，则使用“阶跃”参数。

Syntax: matplotlib.pyplot.fill_betweenx(y, x1, x2=0, where=None, step=None, interpolate=False, *, data=None, **kwargs)
Parameters: 
 

• y: It is array of length N. These are the y coordinates of the nodes that define the curves. 
   
• x1:It is an array of length N or a scalar. This represents the x coordinates of the nodes that define the first curve. 
   
• x2: It is an array of length N and is optional in nature. Its default value is 0. This represents the x coordinates of the nodes that define the second curve. 
   
• where: it is an array of boolean values of length N. It is defined if there is a need to exclude some vertical regions from being filled. It is important to note that this definition means that an isolated true value in between two two false values is where it will not do the filling. Adjacent False values results in not filling both sides of the True value. 
   
• interpolate: It is an optional parameter that accepts boolean values. It is only relevant if where is used and two curves are crossing each other. Semantically where if generally used for x1>x2 or similar cases. By default the filled regions will be placed at the y-array positions defining a filled polygonal area. The section of y that has the intersection are simply clipped. Setting this parameter to True results in calculation of the actual point of intersection and extends to the filled regions till the points. 
   
• step: This is an optional parameter that accepts one of the three values namely, ‘pre’, ‘post’ and ‘mid’. This is used to specify where the steps will occur. 
  • pre: From every x position the y value is continued constantlyto the left, ie, the interval (x[i-1], x[i]) has the value y[i]. 
     
  • post:From every x position the y value is continued constantly to the right, ie, the interval (x[i], x[i+1]) has the value y[i]. 
     
  • mid: Half way between the x positions these steps occur. 
     

Returns: It returns a plotted polygon from the PolyCollection.
 

其他参数： **kwargs 包含来自控制多边形属性的 PolyCollection 的关键字；

Property	Description
agg_filter	a filter function that takes a (m, n, 3) float array and a dpi value that returns a (m, n, 3) array
alpha	float or None
animated	bool
array	ndarray
capstyle	{‘butt’, ’round’, ‘projecting’}
clim	a length 2 sequence of floats; may be overridden in methods that have vmin and vmax kwargs.
cmap	colormap or registered colormap
antialiased or aa or antialiaseds	bool or sequence of bools
clip_box	Bbox
clip_on	bool
clip_path	[(Path, Transform)|Patch|None]
color	color or sequence of rgba tuples
contains	callable
edgecolor or ec or edgecolors	color or sequence of colors or ‘face’
facecolor or fc or facecolors	color or sequence of colors
figure	figure
gid	str
hatch	{‘/’, ‘\’, ‘|’, ‘-‘, ‘+’, ‘x’, ‘o’, ‘O’, ‘.’, ‘*’}
in_layout	bool
joinstyle	{‘miter’, ’round’, ‘bevel’}
linestyle or ls or linestyles or dashes	{‘-‘, ‘–‘, ‘-.’, ‘:’, ”, (offset, on-off-seq), …}
linewidth or linewidths or lw	float or sequence of floats
norm	Normalize
offset_position	{‘screen’, ‘data’}
offsets	float or sequence of floats
path_effects	AbstractPathEffect
picker	None or bool or float or callable
pickradius	unknown
path_effects	AbstractPathEffect
picker	float or callable[[Artist, Event], Tuple[bool, dict]]
pickradius	float
rasterized	bool or None
sketch_params	(scale: float, length: float, randomness: float)
snap	bool or None
transform	matplotlib.transforms.Transform
url	str
urls	List[str] or None
visible	bool
xdata	1D array
zorder	float

示例 1：

Python3

import matplotlib.pyplot as plt
import numpy as np
 
a = np.linspace(0,2*3.14,50)
b = np.sin(a)
 
plt.fill_betweenx(a, b, 0,
                  where = (a > -0.5) & (a <= 1),
                  color='g')
 
plt.plot(a, b)

输出：

示例 2：

Python3

import pylab as plt
import numpy as np
 
N  = np.linspace(0,3,200)
A1 = N**2 + 3
A2 = np.exp(N) + 2
A3 = np.cos(N)
 
plt.plot(N, A1, lw = 3)
plt.plot(N, A2, lw = 3)
plt.plot(N, A3, lw = 3)
 
plt.fill_betweenx(N, A1, A2,
                  color = 'r',
                  alpha = .5)
plt.fill_betweenx(N, A1, A3,
                  color = 'g',
                  alpha = .5)
 
plt.show()

输出：