Sur d’autres sites (11775)

• Exceeded GA’s 10M hits data limit, now what ?

  21 juin 2019, par Joselyn Khor
  Exceeded GA’s 10M hits data limit, now what ? Matomo has the answers

  “Your data volume (1XXM hits) exceeds the limit of 10M hits per month as outlined in our Terms of Service. If you continue to exceed the limit, we will stop processing new data on XXX 21, 2019. Learn more about possible solutions.”

  Yikes. Alarm bells were ringing when a Google Analytics free user came to us faced with this notice. Let’s call him ‘Mark’. Mark had reached the limits on the data he could collect through Google Analytics and was shocked by the limited options available to fix the problem, without blowing the budget. The thoughts racing through his head were :

  • “What happens to all my data ?”
  • “What if Google starts charging USD150K now ?”

  Then he came across Matomo and decided to get in touch with our support team …

  “Can you fix this issue ?” he asked us.

  “Absolutely !” we said.

  We’ll get back to helping Mark in a minute. For now let’s go over why this was such a dilemma for him.

  In order to resolve this data limits issue, one of the solutions was for him to upgrade to Google Analytics 360, which meant shelling out USD150,000 per year for their 1 billion hits per month option. Going from free to USD150,000 was too much of a stretch for a growing company.

  “Your data volume (1XXM hits) exceeds the limit of 10M hits per month …”, what did this message mean ?

  With the free version, Mark could collect up to 10 million “hits” per month, per account. Going over meant Google Analytics could stop collecting any more data for free as outlined in their Terms.

  Google Analytics’ Terms of Service (2018, sec. 2) states, “Subject to Section 15, the Service is provided without charge to You for up to 10 million Hits per month per account.”[1]

  In general, what’s a "hit" ?

  Data being sent to Google Analytics. It can be a transaction, event, social interaction or pageview - these all produce what Google calls a “hit”.

  

  And their Analytics Help Data Limits (n.d.) support page makes clear that : “If a property sends more hits per month to Analytics than allowed by the Analytics Terms of Service, there is no assurance that the excess hits will be processed. If the property’s hit volume exceeds this limit, a warning may be displayed in the user interface and you may be prevented from accessing reports.”[2]

  

  Possible solutions

  So the possible solutions given by Google Analytics’ Data Limits support page were (also shown in image below) :

  • To pay USD150K to upgrade to Google Analytics 360
  • To send fewer hits by setting up sampling
  • Or choose the slightly less relevant option to upgrade mobile app tracking to Google Analytics for Firebase.

  Without the means to pay, the free version was fast becoming inaccessible for Mark as he was facing a future where he risked no longer having access to up-to-date data used in his business’ reporting.

  Mark was facing a problem that potentially didn’t have a cost-effective solution.

  

  So what can you really do about it ?

  This is where we can help provide some assistance. If you’re reading this article, we’ll assume you can relate to Mark and share with you the advice on options we gave him.

  Options :

  One option posed by Google is for you to send fewer hits by auditing your data collection processes

  If you really don’t have the budget, you’ll need to reassess your data collection priorities and go over your strategies to see what is necessary to track, and what isn’t.

  • Make sure you know what you’re tracking and why. Look at what websites are being tracked by Google and into what properties.
  • Go through what data you’re tracking and decide what is or isn’t of value.
  • Set up data sampling, this however, will lead to inaccurate data.

  From here you can start to course correct. If you’ve found data you’re not using for analysis, get rid of these events/pageviews in your Google Analytics.

  But the limitations here are that eventually, you’re going to run out of irrelevant metrics and everything you’re tracking will be essential. So you’ll hit another brick wall and return to the same situation.

  Option 2 – Ignore and continue using the free version of Google Analytics

  With this option, you’ll have to bear the business risks involved by basing decisions off of analytics reports that may or may not be updated. In this case, you may still get contacted about exceeding the limits. As the free service is provided for only up to 10 million hits, once you’ve gone over them, you’re violating what’s stipulated in the Terms of Service. 

  There’s also the warning that “… you may be prevented from accessing reports” (Data limits, n.d.). So while we may not know for certain what Google Analytics will do, in this case it may be better to be safe rather than sorry by acting quickly to resolve it. 

  Option 3 –The Matomo solution. Upgrade to a web analytics platform that can handle your demanding data requirements

  Save money while continuing to gain valuable insights by moving over to Matomo Analytics (recommended)

  This is where you can save up to USD130,000 a year. As well as that, the transition from Google Analytics to the Matomo Cloud is a seamless experience as setup and maintenance is taken care of by our experts.

  For example, you can get up to 15M pageviews for USD1,612.50/month (or USD19,350/year) on the Essentials plan.

  Or even 25M pageviews for USD2400/month (or USD24000/year) on the Business plan – which offers additional web analytics and conversion optimization resources.

  Matomo Cloud is a great option if you’re looking for a secure, cost-effective and powerful analytics solution. You also get what Google Analytics could never offer you : full control and ownership of your own data and privacy. 

  No need to worry about losing your Google Analytics data because …

  Now you can import your historic Google Analytics data directly into your Matomo with the Google Analytics Importer tool. Simply follow the step-by-step guide to get started for free.

  Along with savings you can get :

  • A solution for the data limits issue forever. You choose the right plan to suit your data needs and adapt as you continue growing
  • 100% accurate data (no data sampling)
  • 100% data ownership of all your information without signing away your data to a third party
  • Powerful web analytics and conversion optimization features
  • Matomo Tag Manager
  • Easy setup
  • Support from Matomo’s specialists

  Learn more about Matomo Cloud pricing.

  

  Or go for Matomo On-Premise

  If you have the in-house infrastructure to support self-hosting Matomo on your own servers then there’s also the option of Matomo On-Premise. Here you’ll get full security knowing the data is on your own servers. 

  Setup will also require technical knowledge. There will also be costs associated with acquiring your own servers, and keeping up with regular maintenance and updates. With On-Premise you get maximum flexibility, with no data limits whatsoever. But if you’re coming over from Google Analytics and don’t have the infrastructure and team to host On-Premise, the Matomo Cloud could be right for you.

  Learn more about Matomo On-Premise.

  Where do you go from here ?

  Getting 10 millions hits per month is no small feat, it’s actually pretty fantastic. But if it means having to shell out USD150,000 just to be able to continue with Google Analytics, we feel your problem could be fixed with Matomo Cloud. You could then put the rest of the money you save to better use.

  If you choose Matomo, you now have the option to : 

  • Raise your data limits for a fraction of Google Analytics 360’s price
  • Get a comprehensive range of analytics features for the most impactful insights to ensure your website continues excelling
  • Get data that’s not sampled – meaning 100% accuracy in your reports
  • Migrate your data easily with the help of Matomo’s support team

  We’ll have you covered. 

  By sharing with you the options and advice we gave to Mark, we hope you’ll be able to find a solution that makes your life easier and solves the issue of data restrictions forever.

  The team at Matomo is here to help you every step of the way to ensure a stress-free transition from Google Analytics if that is what works best for you.

  For next steps, why not check out our pricing page to see what could suit your needs !

  References :

  [1] Terms of Service. (2018, July 24). In Google Analytics Terms of Service. Retrieved June 12, 2019, from https://www.google.com/analytics/terms/us.html

  [2] Data limits. (n.d.). In Analytics Help Data limits. Retrieved June 12, 2019, from https://support.google.com/analytics/answer/1070983?hl=en

• How can fix CalledProcessError : in ffmpeg

  7 décembre 2020, par Mario

  I hope someone can help to troubleshoot this problem. I'm trying to save the loss plots out of Keras in the form of the following animation.

  



  

  



  but I have been facing the following error, and ultimately I can't save the animation :

  



  MovieWriter stderr:&#xA;[h264_v4l2m2m @ 0x55a67176f430] Could not find a valid device&#xA;[h264_v4l2m2m @ 0x55a67176f430] can&#x27;t configure encoder&#xA;Error initializing output stream 0:0 -- Error while opening encoder for output stream #0:0 - maybe incorrect parameters such as bit_rate, rate, width or height&#xA;&#xA;---------------------------------------------------------------------------&#xA;BrokenPipeError                           Traceback (most recent call last)&#xA;~/anaconda3/envs/CR7/lib/python3.6/site-packages/matplotlib/animation.py in saving(self, fig, outfile, dpi, *args, **kwargs)&#xA;    229         try:&#xA;--> 230             yield self&#xA;    231         finally:&#xA;&#xA;~/anaconda3/envs/CR7/lib/python3.6/site-packages/matplotlib/animation.py in save(self, filename, writer, fps, dpi, codec, bitrate, extra_args, metadata, extra_anim, savefig_kwargs, progress_callback)&#xA;   1155                             frame_number &#x2B;= 1&#xA;-> 1156                     writer.grab_frame(**savefig_kwargs)&#xA;   1157 &#xA;&#xA;~/anaconda3/envs/CR7/lib/python3.6/site-packages/matplotlib/animation.py in grab_frame(self, **savefig_kwargs)&#xA;    383         self.fig.savefig(self._frame_sink(), format=self.frame_format,&#xA;--> 384                          dpi=self.dpi, **savefig_kwargs)&#xA;    385 &#xA;&#xA;~/anaconda3/envs/CR7/lib/python3.6/site-packages/matplotlib/figure.py in savefig(self, fname, transparent, **kwargs)&#xA;   2179 &#xA;-> 2180         self.canvas.print_figure(fname, **kwargs)&#xA;   2181 &#xA;&#xA;~/anaconda3/envs/CR7/lib/python3.6/site-packages/matplotlib/backend_bases.py in print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, **kwargs)&#xA;   2081                     bbox_inches_restore=_bbox_inches_restore,&#xA;-> 2082                     **kwargs)&#xA;   2083             finally:&#xA;&#xA;~/anaconda3/envs/CR7/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py in print_raw(self, filename_or_obj, *args, **kwargs)&#xA;    445                 cbook.open_file_cm(filename_or_obj, "wb") as fh:&#xA;--> 446             fh.write(renderer._renderer.buffer_rgba())&#xA;    447 &#xA;&#xA;BrokenPipeError: [Errno 32] Broken pipe&#xA;&#xA;During handling of the above exception, another exception occurred:&#xA;&#xA;CalledProcessError                        Traceback (most recent call last)&#xA; in <module>&#xA;     17 print(f&#x27;{model_type.upper()} Train Time: {Timer} sec&#x27;)&#xA;     18 &#xA;---> 19 create_loss_animation(model_type, hist.history[&#x27;loss&#x27;], hist.history[&#x27;val_loss&#x27;], epoch)&#xA;     20 &#xA;     21 evaluate(model, trainX, trainY, testX, testY, scores_train, scores_test)&#xA;&#xA; in create_loss_animation(model_type, loss_hist, val_loss_hist, epoch)&#xA;     34 &#xA;     35     ani = matplotlib.animation.FuncAnimation(fig, animate, fargs=(l1, l2, loss, val_loss, title), repeat=True, interval=1000, repeat_delay=1000)&#xA;---> 36     ani.save(f&#x27;loss_animation_{model_type}_oneDataset.mp4&#x27;, writer=writer)&#xA;&#xA;~/anaconda3/envs/CR7/lib/python3.6/site-packages/matplotlib/animation.py in save(self, filename, writer, fps, dpi, codec, bitrate, extra_args, metadata, extra_anim, savefig_kwargs, progress_callback)&#xA;   1154                             progress_callback(frame_number, total_frames)&#xA;   1155                             frame_number &#x2B;= 1&#xA;-> 1156                     writer.grab_frame(**savefig_kwargs)&#xA;   1157 &#xA;   1158         # Reconnect signal for first draw if necessary&#xA;&#xA;~/anaconda3/envs/CR7/lib/python3.6/contextlib.py in __exit__(self, type, value, traceback)&#xA;     97                 value = type()&#xA;     98             try:&#xA;---> 99                 self.gen.throw(type, value, traceback)&#xA;    100             except StopIteration as exc:&#xA;    101                 # Suppress StopIteration *unless* it&#x27;s the same exception that&#xA;&#xA;~/anaconda3/envs/CR7/lib/python3.6/site-packages/matplotlib/animation.py in saving(self, fig, outfile, dpi, *args, **kwargs)&#xA;    230             yield self&#xA;    231         finally:&#xA;--> 232             self.finish()&#xA;    233 &#xA;    234 &#xA;&#xA;~/anaconda3/envs/CR7/lib/python3.6/site-packages/matplotlib/animation.py in finish(self)&#xA;    365     def finish(self):&#xA;    366         &#x27;&#x27;&#x27;Finish any processing for writing the movie.&#x27;&#x27;&#x27;&#xA;--> 367         self.cleanup()&#xA;    368 &#xA;    369     def grab_frame(self, **savefig_kwargs):&#xA;&#xA;~/anaconda3/envs/CR7/lib/python3.6/site-packages/matplotlib/animation.py in cleanup(self)&#xA;    409         if self._proc.returncode:&#xA;    410             raise subprocess.CalledProcessError(&#xA;--> 411                 self._proc.returncode, self._proc.args, out, err)&#xA;    412 &#xA;    413     @classmethod&#xA;&#xA;CalledProcessError: Command &#x27;[&#x27;/usr/bin/ffmpeg&#x27;, &#x27;-f&#x27;, &#x27;rawvideo&#x27;, &#x27;-vcodec&#x27;, &#x27;rawvideo&#x27;, &#x27;-s&#x27;, &#x27;720x720&#x27;, &#x27;-pix_fmt&#x27;, &#xA;&#x27;rgba&#x27;, &#x27;-r&#x27;, &#x27;5&#x27;, &#x27;-loglevel&#x27;, &#x27;error&#x27;, &#x27;-i&#x27;, &#x27;pipe:&#x27;, &#x27;-vcodec&#x27;, &#x27;h264&#x27;, &#x27;-pix_fmt&#x27;, &#x27;yuv420p&#x27;, &#x27;-b&#x27;, &#x27;800k&#x27;, &#x27;-y&#x27;, &#xA;&#x27;loss_animation_CNN_oneDataset.mp4&#x27;]&#x27; returned non-zero exit status 1.&#xA;</module>

  



  I tried to ignore the error by this answer but it seems it's not the case. I also checked similar case but its answer for getting a static git binary is not my cas as well since not especial converting PNG to MP4 !

  



  My code is as follows :

  



  plt.rcParams['animation.ffmpeg_path'] = '/usr/bin/ffmpeg'

def animate(i, data1, data2, line1, line2):
    temp1 = data1.iloc[:int(i+1)]
    temp2 = data2.iloc[:int(i+1)]

    line1.set_data(temp1.index, temp1.value)
    line2.set_data(temp2.index, temp2.value)

    return (line1, line2)


def create_loss_animation(model_type, data1, data2):
    fig = plt.figure()
    plt.title(f'Loss on Train & Test', fontsize=25)
    plt.xlabel('Epoch', fontsize=20)
    plt.ylabel('Loss MSE for Sx-Sy & Sxy', fontsize=20)
    plt.xlim(min(data1.index.min(), data2.index.min()), max(data1.index.max(), data2.index.max()))
    plt.ylim(min(data1.value.min(), data2.value.min()), max(data1.value.max(), data2.value.max()))

    l1, = plt.plot([], [], 'o-', label='Train Loss', color='b', markevery=[-1])
    l2, = plt.plot([], [], 'o-', label='Test Loss', color='r', markevery=[-1])
    plt.legend(loc='center right', fontsize='xx-large')

    Writer = animation.writers['ffmpeg']
    writer = Writer(fps=5, bitrate=1800)

    ani = matplotlib.animation.FuncAnimation(fig, animate, fargs=(data1, data2, l1, l2), repeat=True, interval=1000, repeat_delay=1000)
    ani.save(f'{model_type}.mp4', writer=writer)

# create datasets
x = np.linspace(0,150,50)
y1 = 41*np.exp(-x/20)
y2 = 35*np.exp(-x/50)

my_data_number_1 = pd.DataFrame({'x':x, 'value':y1}).set_index('x')
my_data_number_2 = pd.DataFrame({'x':x, 'value':y2}).set_index('x')

create_loss_animation('test', my_data_number_1, my_data_number_2)


  


• How can I get neighbour frames when implementing my own ffmpeg filter ?

  10 septembre 2019, par Aaron

  I’m implementing a custom FFmpeg filter. When frame N is processing, I hope I can also get the information of frame N-1 and frame N+1. Is there any FFmpeg function I could use for some help ?

  In my custom FFmpeg filter, the filter_frame function provides an AVFrame object, which is the Nth frame, but how can I get the former and the latter AVFrame object.

  static int filter_frame(AVFilterLink *link, AVFrame *in)