python - 如何将主要刻度线显示为每个月的第一天，将次要刻度线显示为每天？

Question

我试图跟随 matplotlib documentation为股票创建价量图。我有一个关于如何将主要刻度设置为每个月的第一天和每天的次要刻​​度的问题。我试着关注 http://matplotlib.org/examples/pylab_examples/date_demo2.html ，但就是无法让它工作。以下是我目前能得到的最好的。有什么帮助吗？!

#!/usr/bin/env python

import matplotlib.pyplot as plt
from matplotlib.dates import DateFormatter, WeekdayLocator, MonthLocator, DayLocator, MONDAY
from matplotlib.finance import quotes_historical_yahoo, candlestick2, volume_overlay
from matplotlib import gridspec
from matplotlib.dates import num2date, IndexDateFormatter
from matplotlib.ticker import  IndexLocator, FuncFormatter

from operator import itemgetter

# (Year, month, day) tuples suffice as args for quotes_historical_yahoo
date1 = (2010, 2, 1)
date2 = (2011, 2, 1)

symbol = 'TSLA'

quotes = quotes_historical_yahoo(symbol, date1, date2)

if len(quotes) == 0:
    raise SystemExit

ds, opens, closes, highs, lows, volumes = zip(*quotes)

def get_locator():
    """
    the axes cannot share the same locator, so this is a helper
    function to generate locators that have identical functionality
    """
    return IndexLocator(10, 1)

formatter =  IndexDateFormatter(ds, '%b %d %y')

def millions(x, pos):
    'The two args are the value and tick position'
    return '%1.1fM' % (x*1e-6)

def thousands(x, pos):
    'The two args are the value and tick position'
    return '%1.1fK' % (x*1e-3)

millionformatter = FuncFormatter(millions)
thousandformatter = FuncFormatter(thousands)

#fig = plt.figure(figsize=(8, 6)) 

fig = plt.figure()
fig.subplots_adjust(bottom=0.15)
fig.subplots_adjust(hspace=0)
fig.suptitle(symbol, fontsize=24, fontweight='bold')

gs = gridspec.GridSpec(2, 1, height_ratios=[4, 1]) 

ax0 = plt.subplot(gs[0])

#candlestick(ax0, quotes, width=0.6)
candles = candlestick2(ax0, opens, closes, highs, lows, width=1, colorup='g')

ax0.xaxis.set_major_locator( get_locator() )
ax0.xaxis.set_major_formatter(formatter)
ax0.set_ylabel('Price', fontsize=16)

#ax0.xaxis_date()
#ax0.autoscale_view()

ax1 = plt.subplot(gs[1], sharex=ax0)

#vc = volume_overlay3(ax1, quotes, colorup='k', colordown='r', width=4, alpha=1.0)
#volume_overlay(ax1, opens, closes, volumes, colorup='g', alpha=0.5, width=1)
#ax1.set_xticks(ds)

vc = volume_overlay(ax1, opens, closes, volumes, colorup='g', alpha=0.5, width=1)
ax1.add_collection(vc)

#ax1.format_xdata = DateFormatter('%Y-%m-%d')

#maxvolume = max(quotes,key=itemgetter(5))[5]

#ax1.set_ylim([0, maxvolume])

ax1.xaxis.set_major_locator(get_locator())
ax1.xaxis.set_major_formatter(formatter)
ax1.yaxis.set_major_formatter(millionformatter)
ax1.yaxis.tick_right()
ax1.set_ylabel('Volume', fontsize=16)

#ax1.xaxis_date()
#ax1.autoscale_view()

plt.setp(ax0.get_xticklabels(), visible=False)
plt.setp(ax1.get_xticklabels(), rotation=90, horizontalalignment='left')

plt.show()

而我得到的图片如下:

Answer 1

只为子孙后代:

import matplotlib.dates as dt
import matplotlib.ticker as ticker
ax.xaxis.set_major_locator(dt.MonthLocator())
ax.xaxis.set_major_formatter(dt.DateFormatter('%d %b'))
ax.xaxis.set_minor_locator(dt.DayLocator())
ax.xaxis.set_minor_formatter(ticker.NullFormatter())