Matplotlib - 修复 x 轴比例和自动缩放 y 轴

Question

我想只绘制数​​组的一部分，固定 x 部分，但让 y 部分自动缩放。我尝试了如下所示，但它不起作用。

有什么建议吗？

import numpy as np
import matplotlib.pyplot as plt

data=[np.arange(0,101,1),300-0.1*np.arange(0,101,1)]

plt.figure()

plt.scatter(data[0], data[1])
plt.xlim([50,100])
plt.autoscale(enable=True, axis='y')

plt.show()

Answer 1

自动缩放始终使用完整的数据范围，因此 y 轴按 y 数据的完整范围进行缩放，而不仅仅是 x 范围内的内容。

如果您想显示数据的子集，那么只绘制该子集可能是最简单的：

import numpy as np
import matplotlib.pyplot as plt

x, y = np.arange(0,101,1) ,300 - 0.1*np.arange(0,101,1)
mask = (x >= 50) & (x <= 100)

fig, ax = plt.subplots()
ax.scatter(x[mask], y[mask])

plt.show()

Answer 2

虽然Joe Kington 在建议只绘制必要的数据时肯定提出了最明智的答案，但在某些情况下最好绘制所有数据并放大到某个部分。此外，最好有一个只需要轴对象的“autoscale_y”函数（即，不像答案here，它需要直接使用数据。）

这是一个仅根据可见 x 区域中的数据重新调整 y 轴的函数：

def autoscale_y(ax,margin=0.1):
    """This function rescales the y-axis based on the data that is visible given the current xlim of the axis.
    ax -- a matplotlib axes object
    margin -- the fraction of the total height of the y-data to pad the upper and lower ylims"""

    import numpy as np

    def get_bottom_top(line):
        xd = line.get_xdata()
        yd = line.get_ydata()
        lo,hi = ax.get_xlim()
        y_displayed = yd[((xd>lo) & (xd<hi))]
        h = np.max(y_displayed) - np.min(y_displayed)
        bot = np.min(y_displayed)-margin*h
        top = np.max(y_displayed)+margin*h
        return bot,top

    lines = ax.get_lines()
    bot,top = np.inf, -np.inf

    for line in lines:
        new_bot, new_top = get_bottom_top(line)
        if new_bot < bot: bot = new_bot
        if new_top > top: top = new_top

    ax.set_ylim(bot,top)

这有点像 hack，在很多情况下可能都行不通，但对于一个简单的情节来说，它运行良好。

下面是一个使用这个函数的简单例子：

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(-100,100,1000)
y = x**2 + np.cos(x)*100

fig,axs = plt.subplots(1,2,figsize=(8,5))

for ax in axs:
    ax.plot(x,y)
    ax.plot(x,y*2)
    ax.plot(x,y*10)
    ax.set_xlim(-10,10)

autoscale_y(axs[1])

axs[0].set_title('Rescaled x-axis')
axs[1].set_title('Rescaled x-axis\nand used "autoscale_y"')

plt.show()

Answer 3

我以@DanHickstein 的回答为基础，涵盖了绘图、散点图和 axhline/axvline 的情况，用于缩放 x 或 y 轴。可以像 autoscale() 一样简单地调用它来处理最新的轴。如果您想编辑它，请fork it on gist。

def autoscale(ax=None, axis='y', margin=0.1):
    '''Autoscales the x or y axis of a given matplotlib ax object
    to fit the margins set by manually limits of the other axis,
    with margins in fraction of the width of the plot

    Defaults to current axes object if not specified.
    '''
    import matplotlib.pyplot as plt
    import numpy as np
    if ax is None:
        ax = plt.gca()
    newlow, newhigh = np.inf, -np.inf

    for artist in ax.collections + ax.lines:
        x,y = get_xy(artist)
        if axis == 'y':
            setlim = ax.set_ylim
            lim = ax.get_xlim()
            fixed, dependent = x, y
        else:
            setlim = ax.set_xlim
            lim = ax.get_ylim()
            fixed, dependent = y, x

        low, high = calculate_new_limit(fixed, dependent, lim)
        newlow = low if low < newlow else newlow
        newhigh = high if high > newhigh else newhigh

    margin = margin*(newhigh - newlow)

    setlim(newlow-margin, newhigh+margin)

def calculate_new_limit(fixed, dependent, limit):
    '''Calculates the min/max of the dependent axis given 
    a fixed axis with limits
    '''
    if len(fixed) > 2:
        mask = (fixed>limit[0]) & (fixed < limit[1])
        window = dependent[mask]
        low, high = window.min(), window.max()
    else:
        low = dependent[0]
        high = dependent[-1]
        if low == 0.0 and high == 1.0:
            # This is a axhline in the autoscale direction
            low = np.inf
            high = -np.inf
    return low, high

def get_xy(artist):
    '''Gets the xy coordinates of a given artist
    '''
    if "Collection" in str(artist):
        x, y = artist.get_offsets().T
    elif "Line" in str(artist):
        x, y = artist.get_xdata(), artist.get_ydata()
    else:
        raise ValueError("This type of object isn't implemented yet")
    return x, y

与其前身一样，它有点 hacky，但这是必要的，因为集合和线条有不同的方法来返回 xy 坐标，并且因为 axhline/axvline 只有两个数据点，所以使用起来很棘手。

它在行动：

fig, axes = plt.subplots(ncols = 4, figsize=(12,3))
(ax1, ax2, ax3, ax4) = axes

x = np.linspace(0,100,300)
noise = np.random.normal(scale=0.1, size=x.shape)
y = 2*x + 3 + noise

for ax in axes:
    ax.plot(x, y)
    ax.scatter(x,y, color='red')
    ax.axhline(50., ls='--', color='green')
for ax in axes[1:]:
    ax.set_xlim(20,21)
    ax.set_ylim(40,45)

autoscale(ax3, 'y', margin=0.1)
autoscale(ax4, 'x', margin=0.1)

ax1.set_title('Raw data')
ax2.set_title('Specificed limits')
ax3.set_title('Autoscale y')
ax4.set_title('Autoscale x')
plt.tight_layout()

Answer 4

我想补充一下@TomNorway 的出色答案（这为我节省了很多时间），以处理一些艺术家部分由完全由 NaN 组成的情况。

我所做的所有更改都在里面

if len(fixed) > 2:

干杯！

def autoscale(ax=None, axis='y', margin=0.1):
    '''Autoscales the x or y axis of a given matplotlib ax object
    to fit the margins set by manually limits of the other axis,
    with margins in fraction of the width of the plot

    Defaults to current axes object if not specified.
    '''

    
    if ax is None:
        ax = plt.gca()
    newlow, newhigh = np.inf, -np.inf

    for artist in ax.collections + ax.lines:
        x,y = get_xy(artist)
        if axis == 'y':
            setlim = ax.set_ylim
            lim = ax.get_xlim()
            fixed, dependent = x, y
        else:
            setlim = ax.set_xlim
            lim = ax.get_ylim()
            fixed, dependent = y, x

        low, high = calculate_new_limit(fixed, dependent, lim)
        newlow = low if low < newlow else newlow
        newhigh = high if high > newhigh else newhigh

    margin = margin*(newhigh - newlow)

    setlim(newlow-margin, newhigh+margin)

def calculate_new_limit(fixed, dependent, limit):
    '''Calculates the min/max of the dependent axis given 
    a fixed axis with limits
    '''
    if len(fixed) > 2:
        mask = (fixed>limit[0]) & (fixed < limit[1]) & (~np.isnan(dependent)) & (~np.isnan(fixed))
        window = dependent[mask]
        try:
            low, high = window.min(), window.max()
        except ValueError:  # Will throw ValueError if `window` has zero elements
            low, high = np.inf, -np.inf
    else:
        low = dependent[0]
        high = dependent[-1]
        if low == 0.0 and high == 1.0:
            # This is a axhline in the autoscale direction
            low = np.inf
            high = -np.inf
    return low, high

def get_xy(artist):
    '''Gets the xy coordinates of a given artist
    '''
    if "Collection" in str(artist):
        x, y = artist.get_offsets().T
    elif "Line" in str(artist):
        x, y = artist.get_xdata(), artist.get_ydata()
    else:
        raise ValueError("This type of object isn't implemented yet")
    return x, y

Answer 5

• 最简单的方法可能是使用pandas，这使得使用Boolean indexing 选择数据非常容易。
• 将x和y加载到DataFrame中，使用pandas.Series.between(left, right, inclusive=True)进行布尔选择，使用pandas.DataFrame.plot直接绘图，使用matplotlib。

import numpy as np  # for the test data
import pandas as pd

# load the data into the dataframe; there are many ways to do this
df = pd.DataFrame({'x': np.arange(0,101,1), 'y': 300-0.1*np.arange(0,101,1)})

# select and plot the data
ax = df[df.x.between(50, 100)].plot(x='x', y='y', kind='scatter', figsize=(5, 4))