Matplotlib - 固定 x 轴比例和自动缩放 y 轴

Question

我只想绘制数组的一部分，固定 x 部分，但让 y 部分自动缩放。 我尝试如下所示，但它不起作用。

有什么建议？

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

虽然Joe Kington在建议只绘制必要数据时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仅缩放到某个部分。 此外，拥有一个只需要轴对象的“autoscale_y”函数会很好（即，不像这里的答案，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)

这有点像黑客，可能在许多情况下都不起作用，但对于简单的情节，它运行良好。

这是一个使用此函数的简单示例：

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 2

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

如果您想显示数据的一个子集，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 3

我已经建立在@DanHickstein's answer 的基础上，涵盖了用于缩放 x 或 y 轴的 plot、scatter 和 axhline/axvline 的情况。 它可以像autoscale()一样简单地调用以在最近的轴上工作。 如果你想编辑它，请在 gist 上 fork 。

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，它有点老套，但这是必要的，因为集合和线具有不同的返回 xy 坐标的方法，并且因为 axhline/axvline 很难使用，因为它只有两个数据点。

这是在行动：

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

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

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))

Answer 5

我想补充@TomNorway 的好答案（这为我节省了很多时间）来处理一些艺术家完全由 NaN 组成的情况。

我所做的所有更改都在

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