Matplotlib - 修复x轴比例和自动缩放y轴

Question

我只想绘制数组的一部分，修复x部分，但让y部分自动缩放。我试过如下所示，但没有成功。

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

虽然当他建议只绘制必要的数据时，Joe Kington肯定会提出最合理的答案，但在某些情况下，最好绘制所有数据并缩放到某个部分。另外，最好有一个只需要axes对象的“autoscale_y”函数（即，与需要直接使用数据的答案here不同）

下面是一个函数，它仅根据可见x区域中的数据重新缩放y轴：

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)

这是一个黑客，可能不会在很多情况下工作，但对于一个简单的情节，它工作得很好。

下面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

我以@DanHickstein的答案为基础，涵盖了plot、scatter和axhline/axvline缩放x轴或y轴的情况。它可以简单地称为autoscale()来处理最新的轴。如果你想编辑它，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

它和它的前身一样，有点老套，但这是必要的，因为集合和行有不同的返回xy坐标的方法，而且由于axhline/axvline只有两个数据点，所以很难使用。

这就是它的作用：

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 3

自动缩放始终使用全部数据范围，因此y轴按y数据的全部范围缩放，而不仅仅是x限制范围内的数据。

如果要显示数据的子集，则可能最容易仅绘制该子集：

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()