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[英]Using Matplotlib and iPython, How to reset x and y axis limits to Autoscale?
[英]Matplotlib - fixing x axis scale and autoscale y axis
雖然Joe Kington在建議只繪制必要數據時提出了最明智的答案,但在某些情況下,最好繪制所有數據並僅縮放到某個部分。 此外,擁有一個只需要軸對象的“autoscale_y”函數會很好(即,不像這里的答案,它需要直接使用數據。)
這是一個僅根據可見 x 區域中的數據重新調整 y 軸的函數:
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)
這有點像黑客,可能在許多情況下都不起作用,但對於簡單的情節,它運行良好。
這是一個使用此函數的簡單示例:
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()
我已經建立在@DanHickstein's answer 的基礎上,涵蓋了用於縮放 x 或 y 軸的 plot、scatter 和 axhline/axvline 的情況。 它可以像autoscale()
一樣簡單地調用以在最近的軸上工作。 如果你想編輯它,請在 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
與其前身一樣,它有點老套,但這是必要的,因為集合和線具有不同的返回 xy 坐標的方法,並且因為 axhline/axvline 很難使用,因為它只有兩個數據點。
這是在行動:
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()
pandas
,這使得使用布爾索引選擇數據非常容易。x
和y
加載到 DataFrame 中,使用帶有pandas.Series.between(left, right, inclusive=True)
布爾選擇,並使用使用matplotlib
pandas.DataFrame.plot
直接繪圖。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))
我想補充@TomNorway 的好答案(這為我節省了很多時間)來處理一些藝術家完全由 NaN 組成的情況。
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
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