python - How to setup the same scale for X axis (timestamp) in multiple graphs using matplotlib -


i using python , matplotlib try generate following: 4 charts plotting amount of messages received in system vs delay in processing these messages, in given period of time, in intervals of 5 minutes.

that is, x axis shows time moment a moment b (in format "%y-%m-%d %h:%m") in intervals of 5 minutes, while left y axis shows amount of messages received @ given moment, , right y axis shows delays in processing these messages.

now, got plotting both x axes in chart, need timestamps same every graph, is, must start , end @ same point in time, if there no events in times of charts (e.g., chart#1 starts @ 15:50 of 10/5/2015 , stopped @ 14:00 11/5/2015, if in 1 of them events start happening @ 17:00 of 10/5). , that's killer.

does know how can this? lot

does know how can this?

yes.

if stack overflow allow non-mcve posts in questions, simplistic answers, saying "yes", spring off box, bring no real experience great community stackoverflow undoubtedly is.

think while & point. way no 1 appreciate.

q: how...?

you may re-use of formatting tricks. might have experienced, matplotlib's complex structure sort-of sensitive, formatting takes place in figure processing. things work "before" plotting data, "after" plotting data-points/lines. not hesitate test/reorder sections & feel wish have within reasonable time spent on these polishing touches ( real-value typically in data-related insights & phenomena-related experience converted new, strategic value called knowlege, isn't it? ).

so few cents:

#---------------------------------------------------- # x-axis formatting          aplotax.set_xlim( x_min, x_max )                      # x-axis limits ---      #lt.gca().xaxis.set_major_locator(      matplotlib.ticker.fixedlocator( secs ) ) #lt.gca().xaxis.set_major_formatter(    matplotlib.ticker.funcformatter( lambda pos, _: time.strftime( "%d-%m-%y %h:%m:%s", time.localtime( pos ) ) ) )  aplotax.xaxis.set_major_locator(   autodatelocator() ) aplotax.xaxis.set_minor_locator(       hourlocator() ) #plotax.xaxis.set_minor_locator(     minutelocator() ) # if not dense  aplotax.xaxis.set_major_formatter( dateformatter( '%y-%m-%d %h:%m' ) )  # -------------------------------------------------------------------- x-format #----------------------------------------------- # 90-deg x-tick-labels try:     plt.setp( plt.gca().get_xticklabels(),  rotation            = 90,                                             horizontalalignment = 'right'                                             ) except:     print "debug: exc() on plt.setp( plt.gca().get_xticklabels(),  rotation = 90, ... )"  # --------------------------------------------- # "tight"-en layout  try:     plt.tight_layout() except:     print "debug: exc() on plt.tight_layout()" ''' pre-save_as-configuration(s) |||||||||||||||||||||||||||||||||||||||||||||  #fig.set_figwidth(  1600.0 ) #fig.set_figheight( 1400.0 ) #                   facecolor = 'k',                  # inverse colourscheme #                   edgecolor = 'w', afig = plt.figure(  figsize   = ( 5, 5 ), dpi = 100 ) # size not in [inch], in [spatial-units] 100-px-each...  #lt .savefig( <afilename.png>, transparent = true, dpi = 300 )                      # .png alpha-channel background                        std-[px]-size 800x600 @ dpi  #lt .savefig( <afilename.svg>, transparent = true, dpi = 300 )                      # .svg alpha-channel background                        std-[px]-size 800x600 @ dpi #lt .savefig( <afilename.000>, transparent = true, dpi = 300, format = "svg" )      # .svg alpha-channel background                        std-[px]-size 800x600 @ dpi  #lt .savefig( <afilename.pdf>, transparent = true, dpi = 300 )                      # .pdf alpha-channel background                        std-[px]-size 800x600 @ dpi  # matplotlib.backends.backend_pdf import pdfpages                              # .pdf-multi-page document # pdf_pages = pdfpages('barcharts.pdf') # afig = plt.figure... # plt.plot... # pdf_pages.savefig( afig )     # .closes apdfpage # ...plot # pdf_pages.savefig( afig )     # .closes apdfpage # pdf_pages.close()             # finally: fileio on disk

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