我的问题是,是否有任何方法可以使用带有log xscale的matplotlib日期刻度标签。
每当我尝试set_xscale('log')
时,我就会发现它只是擦除了标签而实际上并未记录xscale ......
示例代码:
import datetime
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import matplotlib.cbook as cbook
years = mdates.YearLocator() # every year
months = mdates.MonthLocator() # every month
yearsFmt = mdates.DateFormatter('%Y')
# Load a numpy record array from yahoo csv data with fields date, open, close,
# volume, adj_close from the mpl-data/example directory. The record array
# stores the date as an np.datetime64 with a day unit ('D') in the date column.
with cbook.get_sample_data('goog.npz') as datafile:
r = np.load(datafile)['price_data'].view(np.recarray)
# Matplotlib works better with datetime.datetime than np.datetime64, but the
# latter is more portable.
date = r.date.astype('O')
fig, ax = plt.subplots()
ax.plot(date, r.adj_close)
# format the ticks
ax.xaxis.set_major_locator(years)
ax.xaxis.set_major_formatter(yearsFmt)
ax.xaxis.set_minor_locator(months)
datemin = datetime.date(date.min().year, 1, 1)
datemax = datetime.date(date.max().year + 1, 1, 1)
ax.set_xlim(datemin, datemax)
# format the coords message box
def price(x):
return '$%1.2f' % x
ax.format_xdata = mdates.DateFormatter('%Y-%m-%d')
ax.format_ydata = price
ax.grid(True)
# rotates and right aligns the x labels, and moves the bottom of the
# axes up to make room for them
fig.autofmt_xdate()
ax.set_xscale('log')
plt.show()
答案 0 :(得分:0)
尝试使用ScalarFormatter:
from matplotlib.ticker import ScalarFormatter
ax.xaxis.set_major_formatter(ScalarFormatter())