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所以我有一个 Epoch（秒）的 2D 数组加上每个交换机端口的 52 个字节计数，我可以将字节计数转换为每秒兆位，并将它们与数据集中的“分钟”相对应：

import sys
import time
import math
import MySQLdb as mdb
import numpy
import matplotlib
matplotlib.use('MacOSX')
import matplotlib.pyplot as plt
plt.grid(True)
plt.ylabel('Megabits Per Second')
plt.xlabel('Minutes')
DBconn = mdb.connect('minotaur', 'root', '<password>', 'Monitoring')
cursor = DBconn.cursor()
sql = "select * from OfficeSwitchBytes where ComputerTime >= (unix_timestamp(now())-(60*60))"
cursor.execute(sql)
A = numpy.fromiter(cursor.fetchall(), count=-1, dtype=[('', numpy.uint32)]*53)
A = A.view(numpy.uint32).reshape(-1, 53)
(samples,ports)=A.shape
#  NO NO NO  plt.axis(xmax=samples)
print samples,ports
plotme=numpy.zeros((samples,ports-1))
for y in range(ports-1):
    for x in range(samples-1):
        seconds = A[x+1,0]-A[x,0]
        if A[x+1,y+1]>=A[x,y+1]:
            plotme[x,y] = ((A[x+1,y+1]-A[x,y+1])*8/seconds)/1e6
        else:
            print'#'
            plotme[x,y] = None
    plotme[samples-1,y] = None

plt.plot(plotme)
plt.show()

所以现在我想在 X 轴上有一个时间戳。添加了以下代码：

epoch = A[:,0]
dts = map(datetime.datetime.fromtimestamp,epoch)
fdts = matplotlib.dates.date2num(dts)
hfmt = matplotlib.dates.DateFormatter('%m/%d %H:%M')
plt.gca().xaxis.set_major_formatter(hfmt)
plt.gca().xaxis.set_major_locator(matplotlib.dates.HourLocator())
plt.plot(fdts,plotme)
plt.gcf().autofmt_xdate()
plt.show()

即使时间戳有点接近，也使一切正常。

4

1 回答 1

0

好的，所以以下工作：

# pull data from sql, plot using matplotlib
# see http://stackoverflow.com/questions/18663746/matplotlib-multiple-lines-with-common-date-on-x-axis-solved
#
# rev 1.0 09/07/2013 WPNS cleanup from various previous hacks, first 'release'
# rev 1.1 09/07/2013 WPNS rename A to Raw
# rev 1.2 09/07/2013 WPNS make plotme the same size as Raw, so the X axis can be time
# rev 1.3 09/07/2013 WPNS add stuff from stackoverflow above
# rev 1.4 09/07/2013 WPNS cleanup, reformat
# rev 1.5 09/07/2013 WPNS combine formatted-date-time-stamp and formatting lines

import sys
import time
import math
import datetime
import MySQLdb as mdb
import numpy

# so matplotlib has to have some of the setup parameters _before_ pyplot
import matplotlib
matplotlib.use('MacOSX')
matplotlib.rcParams['figure.dpi'] = 100
matplotlib.rcParams['figure.figsize'] = [10.24, 7.68]
matplotlib.rcParams['lines.linewidth'] = 0.5
matplotlib.rcParams['axes.color_cycle'] = ['r','g','b','k']

import matplotlib.pyplot as plt

print "GraphOfficeSwitch.py V1.4 09/07/2013 WPNS",time.asctime()

# open the database connection, read the last <many> seconds of data, put them in a Numpy array called Raw
DBconn = mdb.connect('minotaur', 'root', '<password>', 'Monitoring')
cursor = DBconn.cursor()
sql = "select * from OfficeSwitchBytes where ComputerTime >= (unix_timestamp(now())-(60*60*24))"
cursor.execute(sql)
Raw = numpy.fromiter(cursor.fetchall(), count=-1, dtype=[('', numpy.uint32)]*53)
Raw = Raw.view(numpy.uint32).reshape(-1, 53)
(samples,ports)=Raw.shape
print 'Samples: {}, Ports: {}'.format(samples,ports)
plotme=numpy.zeros((samples,ports-1)) # make an array the same shape minus the epoch numbers

for y in range(ports-1):
    for x in range(samples-1):  # can't do last one, there's no delta from previous sample
        seconds = Raw[x+1,0]-Raw[x,0]
        # if the number didn't overflow the counter
        if Raw[x+1,y+1]>=Raw[x,y+1]:
            plotme[x,y] = ((Raw[x+1,y+1]-Raw[x,y+1])*8/seconds) # convert delta bytes per sample (usually a minute) to bits per second

            # convert to log scale (if zero, don't plot it)
            if plotme[x,y] > 0:
                plotme[x,y] = math.log10(plotme[x,y])
            else:
                plotme[x,y] = None

        else:
            print'#' # if the number did overflow the counter, show me
            plotme[x,y] = None # could convert it, but just don't plot for now.

    plotme[samples-1,y] = None # set last sample to "do not plot"

# get an array of adatetime objects (askewchan from stackoverflow, above)
dts = map(datetime.datetime.fromtimestamp, Raw[:,0])

plt.grid(True)
plt.ylabel('Log of Bits Per Second, 2=100bps, 9=1Gbps')
plt.axis(ymax=9,ymin=2)
plt.xlabel('Time')

plt.gca().xaxis.set_major_formatter(matplotlib.dates.DateFormatter('%m/%d %H:%M'))
plt.gca().xaxis.set_major_locator(matplotlib.dates.HourLocator())
plt.plot(dts,plotme)
plt.gcf().autofmt_xdate()
plt.show()

所以我宣布成功，非常感谢！

于 2013-09-07T22:25:40.977 回答