matplotlib X 축에 공통 날짜가있는 여러 줄

Question

각 포트의 에포크 (초) 플러스 52 바이트 카운트의 2D 배열이 있습니다. 바이트 수를 초당 메가 비트로 마사지하여 " 분 "을 입력하십시오 :

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() 

이제 X 축에 타임 스탬프를 갖고 싶습니다. 다음 코드가 추가되었습니다.

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() 

타임 스탬프가 약간 비슷하더라도 모두 작동했습니다.

Answer 1

좋아, 그럼 다음 작품 :

# 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() 

그래서 선언하고있어 성공, 많은 감사합니다!