Efficiency in connecting two subplot.

Hi all,

I have a gridspec plot and one of the subplot is a zoom on the part over which
the mouse hovers on another subplot.

It works, but I think the way I implemented it is not very efficient, since each
time I use it, I see one CPU go to 100%.
Here is the code that does implement the zoom. Any idea on how to make it
(more) efficient or changes that I should implement welcome.

Thanks.

def plot(self):
        gs = gridspec.GridSpec(6, 2)
        ax1 = plt.subplot(gs[1:, 0])
        plt1 = ax1.imshow(self.data, vmin=self.dataminzs, vmax=self.datamaxzs)
        ax1.set_label('AX1')
        self.ax2 = plt.subplot(gs[0:3, 1])
        zoomeddata = self.data[np.int(self.data.shape[0]/
2)-50:np.int(self.data.shape[0]/2)+50, np.int(self.data.shape[1]/
2)-50:np.int(self.data.shape[1]/2)+50]
        self.plt2 = self.ax2.imshow(zoomeddata, vmin=self.dataminzs,
vmax=self.datamaxzs)
        ax1.figure.canvas.mpl_connect('motion_notify_event', self._on_move)

    def _on_move(self, event):
        zoom1 = 100
        if event.inaxes:

            ax = event.inaxes # the axes instance
            if 'AX1' in ax.get_label():
                # Mouse is in subplot 1.
                xinf2 = np.int(event.xdata - zoom1)
                xsup2 = np.int(event.xdata + zoom1)
                yinf2 = np.int(event.ydata - zoom1)
                ysup2 = np.int(event.ydata + zoom1)
                ax2data = self.data[yinf2:ysup2, xinf2:xsup2]
                self.plt2.set_data(ax2data)
                self.ax2.figure.canvas.draw()

···

--
Un clavier azerty en vaut deux
----------------------------------------------------------
?ric Depagne

Hi ?ric,

I am not very used to play with interactive events, but I guess some
blitting could help you with performance:

···

-
https://stackoverflow.com/questions/29277080/efficient-matplotlib-redrawing
-
https://matplotlib.org/users/event_handling.html#draggable-rectangle-exercise
(see the extra credit example)

See the attached script that is inspired from your code and seems to
less stress my CPU.

Hopefully this helps.

Best,
Adrien

On 02/16/2018 01:36 AM, ?ric Depagne wrote:

Hi all,

I have a gridspec plot and one of the subplot is a zoom on the part over which
the mouse hovers on another subplot.

It works, but I think the way I implemented it is not very efficient, since each
time I use it, I see one CPU go to 100%.
Here is the code that does implement the zoom. Any idea on how to make it
(more) efficient or changes that I should implement welcome.

Thanks.

def plot(self):
         gs = gridspec.GridSpec(6, 2)
         ax1 = plt.subplot(gs[1:, 0])
         plt1 = ax1.imshow(self.data, vmin=self.dataminzs, vmax=self.datamaxzs)
         ax1.set_label('AX1')
         self.ax2 = plt.subplot(gs[0:3, 1])
         zoomeddata = self.data[np.int(self.data.shape[0]/
2)-50:np.int(self.data.shape[0]/2)+50, np.int(self.data.shape[1]/
2)-50:np.int(self.data.shape[1]/2)+50]
         self.plt2 = self.ax2.imshow(zoomeddata, vmin=self.dataminzs,
vmax=self.datamaxzs)
         ax1.figure.canvas.mpl_connect('motion_notify_event', self._on_move)

     def _on_move(self, event):
         zoom1 = 100
         if event.inaxes:

             ax = event.inaxes # the axes instance
             if 'AX1' in ax.get_label():
                 # Mouse is in subplot 1.
                 xinf2 = np.int(event.xdata - zoom1)
                 xsup2 = np.int(event.xdata + zoom1)
                 yinf2 = np.int(event.ydata - zoom1)
                 ysup2 = np.int(event.ydata + zoom1)
                 ax2data = self.data[yinf2:ysup2, xinf2:xsup2]
                 self.plt2.set_data(ax2data)
                 self.ax2.figure.canvas.draw()

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Le vendredi 16 f?vrier 2018, 21:41:07 SAST vincent.adrien at gmail.com a ?crit :
Hi Adrien,

Thanks for the answer, I'll have a look and will try to get things working a
bit more efficiently.

Cheers,
?ric.

···

Hi ?ric,

I am not very used to play with interactive events, but I guess some
blitting could help you with performance:
-
https://stackoverflow.com/questions/29277080/efficient-matplotlib-redrawing
-
https://matplotlib.org/users/event_handling.html#draggable-rectangle-exercis
e (see the extra credit example)

See the attached script that is inspired from your code and seems to
less stress my CPU.

Hopefully this helps.

Best,
Adrien

On 02/16/2018 01:36 AM, ?ric Depagne wrote:
> Hi all,
>
> I have a gridspec plot and one of the subplot is a zoom on the part over
> which the mouse hovers on another subplot.
>
> It works, but I think the way I implemented it is not very efficient,
> since each time I use it, I see one CPU go to 100%.
> Here is the code that does implement the zoom. Any idea on how to make it
> (more) efficient or changes that I should implement welcome.
>
> Thanks.
>
> def plot(self):
> gs = gridspec.GridSpec(6, 2)
> ax1 = plt.subplot(gs[1:, 0])
> plt1 = ax1.imshow(self.data, vmin=self.dataminzs,
> vmax=self.datamaxzs)
> ax1.set_label('AX1')
> self.ax2 = plt.subplot(gs[0:3, 1])
> zoomeddata = self.data[np.int(self.data.shape[0]/
>
> 2)-50:np.int(self.data.shape[0]/2)+50, np.int(self.data.shape[1]/
> 2)-50:np.int(self.data.shape[1]/2)+50]
>
> self.plt2 = self.ax2.imshow(zoomeddata, vmin=self.dataminzs,
>
> vmax=self.datamaxzs)
>
> ax1.figure.canvas.mpl_connect('motion_notify_event',
> self._on_move)
>
> def _on_move(self, event):
> zoom1 = 100
>
> if event.inaxes:
> ax = event.inaxes # the axes instance
>
> if 'AX1' in ax.get_label():
> # Mouse is in subplot 1.
> xinf2 = np.int(event.xdata - zoom1)
> xsup2 = np.int(event.xdata + zoom1)
> yinf2 = np.int(event.ydata - zoom1)
> ysup2 = np.int(event.ydata + zoom1)
> ax2data = self.data[yinf2:ysup2, xinf2:xsup2]
> self.plt2.set_data(ax2data)
> self.ax2.figure.canvas.draw()

--
Un clavier azerty en vaut deux
----------------------------------------------------------
?ric Depagne

You might want to consider not having the limits change at *every* mouse
motion over the axes. You can add a function state variable and maybe have
it refresh every other motion or so.

    def _on_move(self, event):
        zoom1 = 100
        if event.inaxes:

            ax = event.inaxes  # the axes instance
            if 'AX1' in ax.get_label():
                _on_move.counter += 1
                if _on_move.counter % 2:
                    return
                # Mouse is in subplot 1.
                xinf2 = np.int(event.xdata - zoom1)
                xsup2 = np.int(event.xdata + zoom1)
                yinf2 = np.int(event.ydata - zoom1)
                ysup2 = np.int(event.ydata + zoom1)
                ax2data = self.data[yinf2:ysup2, xinf2:xsup2]
                self.plt2.set_data(ax2data)
                self.ax2.figure.canvas.draw()
    _on_move.counter = 0

Another approach could be done where you capture the timestamp of when this
function was last used for updating the limits, and only do a new limit
update if a certain amount of time passed, such as half a second or so.

Cheers!
Ben Root

···

On Mon, Feb 19, 2018 at 9:37 AM, ?ric Depagne <eric at depagne.org> wrote:

Le vendredi 16 f?vrier 2018, 21:41:07 SAST vincent.adrien at gmail.com a
?crit :
Hi Adrien,

Thanks for the answer, I'll have a look and will try to get things working
a
bit more efficiently.

Cheers,
?ric.
> Hi ?ric,
>
> I am not very used to play with interactive events, but I guess some
> blitting could help you with performance:
> -
> https://stackoverflow.com/questions/29277080/efficient-
matplotlib-redrawing
> -
> https://matplotlib.org/users/event_handling.html#draggable-
rectangle-exercis
> e (see the extra credit example)
>
> See the attached script that is inspired from your code and seems to
> less stress my CPU.
>
> Hopefully this helps.
>
> Best,
> Adrien
>
> On 02/16/2018 01:36 AM, ?ric Depagne wrote:
> > Hi all,
> >
> > I have a gridspec plot and one of the subplot is a zoom on the part
over
> > which the mouse hovers on another subplot.
> >
> > It works, but I think the way I implemented it is not very efficient,
> > since each time I use it, I see one CPU go to 100%.
> > Here is the code that does implement the zoom. Any idea on how to make
it
> > (more) efficient or changes that I should implement welcome.
> >
> > Thanks.
> >
> > def plot(self):
> > gs = gridspec.GridSpec(6, 2)
> > ax1 = plt.subplot(gs[1:, 0])
> > plt1 = ax1.imshow(self.data, vmin=self.dataminzs,
> > vmax=self.datamaxzs)
> > ax1.set_label('AX1')
> > self.ax2 = plt.subplot(gs[0:3, 1])
> > zoomeddata = self.data[np.int(self.data.shape[0]/
> >
> > 2)-50:np.int(self.data.shape[0]/2)+50, np.int(self.data.shape[1]/
> > 2)-50:np.int(self.data.shape[1]/2)+50]
> >
> > self.plt2 = self.ax2.imshow(zoomeddata, vmin=self.dataminzs,
> >
> > vmax=self.datamaxzs)
> >
> > ax1.figure.canvas.mpl_connect('motion_notify_event',
> > self._on_move)
> >
> > def _on_move(self, event):
> > zoom1 = 100
> >
> > if event.inaxes:
> > ax = event.inaxes # the axes instance
> >
> > if 'AX1' in ax.get_label():
> > # Mouse is in subplot 1.
> > xinf2 = np.int(event.xdata - zoom1)
> > xsup2 = np.int(event.xdata + zoom1)
> > yinf2 = np.int(event.ydata - zoom1)
> > ysup2 = np.int(event.ydata + zoom1)
> > ax2data = self.data[yinf2:ysup2, xinf2:xsup2]
> > self.plt2.set_data(ax2data)
> > self.ax2.figure.canvas.draw()

--
Un clavier azerty en vaut deux
----------------------------------------------------------
?ric Depagne

_______________________________________________
Matplotlib-users mailing list
Matplotlib-users at python.org
https://mail.python.org/mailman/listinfo/matplotlib-users

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Le vendredi 16 f?vrier 2018, 21:41:07 SAST vincent.adrien at gmail.com a ?crit :
Hi Adrien,

Many thanks for your code, I've modified mine in order to take advantage of the
blitting, and it works beautifully.

?ric.

···

Hi ?ric,

I am not very used to play with interactive events, but I guess some
blitting could help you with performance:
-
https://stackoverflow.com/questions/29277080/efficient-matplotlib-redrawing
-
https://matplotlib.org/users/event_handling.html#draggable-rectangle-exercis
e (see the extra credit example)

See the attached script that is inspired from your code and seems to
less stress my CPU.

Hopefully this helps.

Best,
Adrien

On 02/16/2018 01:36 AM, ?ric Depagne wrote:
> Hi all,
>
> I have a gridspec plot and one of the subplot is a zoom on the part over
> which the mouse hovers on another subplot.
>
> It works, but I think the way I implemented it is not very efficient,
> since each time I use it, I see one CPU go to 100%.
> Here is the code that does implement the zoom. Any idea on how to make it
> (more) efficient or changes that I should implement welcome.
>
> Thanks.
>
> def plot(self):
> gs = gridspec.GridSpec(6, 2)
> ax1 = plt.subplot(gs[1:, 0])
> plt1 = ax1.imshow(self.data, vmin=self.dataminzs,
> vmax=self.datamaxzs)
> ax1.set_label('AX1')
> self.ax2 = plt.subplot(gs[0:3, 1])
> zoomeddata = self.data[np.int(self.data.shape[0]/
>
> 2)-50:np.int(self.data.shape[0]/2)+50, np.int(self.data.shape[1]/
> 2)-50:np.int(self.data.shape[1]/2)+50]
>
> self.plt2 = self.ax2.imshow(zoomeddata, vmin=self.dataminzs,
>
> vmax=self.datamaxzs)
>
> ax1.figure.canvas.mpl_connect('motion_notify_event',
> self._on_move)
>
> def _on_move(self, event):
> zoom1 = 100
>
> if event.inaxes:
> ax = event.inaxes # the axes instance
>
> if 'AX1' in ax.get_label():
> # Mouse is in subplot 1.
> xinf2 = np.int(event.xdata - zoom1)
> xsup2 = np.int(event.xdata + zoom1)
> yinf2 = np.int(event.ydata - zoom1)
> ysup2 = np.int(event.ydata + zoom1)
> ax2data = self.data[yinf2:ysup2, xinf2:xsup2]
> self.plt2.set_data(ax2data)
> self.ax2.figure.canvas.draw()

--
Un clavier azerty en vaut deux
----------------------------------------------------------
?ric Depagne

Le lundi 19 f?vrier 2018, 17:04:28 SAST Benjamin Root a ?crit :
Hi Ben,

Thanks for the idea.
I'll see how my code runs on a slower computer than mine, and I'll implement
it should I find my current solution too slow.

?ric.

···

You might want to consider not having the limits change at *every* mouse
motion over the axes. You can add a function state variable and maybe have
it refresh every other motion or so.

    def _on_move(self, event):
        zoom1 = 100
        if event.inaxes:

            ax = event.inaxes  # the axes instance
            if 'AX1' in ax.get_label():
                _on_move.counter += 1
                if _on_move.counter % 2:
                    return
                # Mouse is in subplot 1.
                xinf2 = np.int(event.xdata - zoom1)
                xsup2 = np.int(event.xdata + zoom1)
                yinf2 = np.int(event.ydata - zoom1)
                ysup2 = np.int(event.ydata + zoom1)
                ax2data = self.data[yinf2:ysup2, xinf2:xsup2]
                self.plt2.set_data(ax2data)
                self.ax2.figure.canvas.draw()
    _on_move.counter = 0

Another approach could be done where you capture the timestamp of when this
function was last used for updating the limits, and only do a new limit
update if a certain amount of time passed, such as half a second or so.

Cheers!
Ben Root

On Mon, Feb 19, 2018 at 9:37 AM, ?ric Depagne <eric at depagne.org> wrote:
> Le vendredi 16 f?vrier 2018, 21:41:07 SAST vincent.adrien at gmail.com a
> ?crit :
> Hi Adrien,
>
> Thanks for the answer, I'll have a look and will try to get things working
> a
> bit more efficiently.
>
> Cheers,
> ?ric.
>
> > Hi ?ric,
> >
> > I am not very used to play with interactive events, but I guess some
> > blitting could help you with performance:
> > -
> > https://stackoverflow.com/questions/29277080/efficient-> >
> matplotlib-redrawing
>
> > -
> > https://matplotlib.org/users/event_handling.html#draggable-> >
> rectangle-exercis
>
> > e (see the extra credit example)
> >
> > See the attached script that is inspired from your code and seems to
> > less stress my CPU.
> >
> > Hopefully this helps.
> >
> > Best,
> > Adrien
> >
> > On 02/16/2018 01:36 AM, ?ric Depagne wrote:
> > > Hi all,
> > >
> > > I have a gridspec plot and one of the subplot is a zoom on the part
>
> over
>
> > > which the mouse hovers on another subplot.
> > >
> > > It works, but I think the way I implemented it is not very efficient,
> > > since each time I use it, I see one CPU go to 100%.
> > > Here is the code that does implement the zoom. Any idea on how to make
>
> it
>
> > > (more) efficient or changes that I should implement welcome.
> > >
> > > Thanks.
> > >
> > > def plot(self):
> > > gs = gridspec.GridSpec(6, 2)
> > > ax1 = plt.subplot(gs[1:, 0])
> > > plt1 = ax1.imshow(self.data, vmin=self.dataminzs,
> > > vmax=self.datamaxzs)
> > > ax1.set_label('AX1')
> > > self.ax2 = plt.subplot(gs[0:3, 1])
> > > zoomeddata = self.data[np.int(self.data.shape[0]/
> > >
> > > 2)-50:np.int(self.data.shape[0]/2)+50, np.int(self.data.shape[1]/
> > > 2)-50:np.int(self.data.shape[1]/2)+50]
> > >
> > > self.plt2 = self.ax2.imshow(zoomeddata, vmin=self.dataminzs,
> > >
> > > vmax=self.datamaxzs)
> > >
> > > ax1.figure.canvas.mpl_connect('motion_notify_event',
> > > self._on_move)
> > >
> > > def _on_move(self, event):
> > > zoom1 = 100
> > >
> > > if event.inaxes:
> > > ax = event.inaxes # the axes instance
> > >
> > > if 'AX1' in ax.get_label():
> > > # Mouse is in subplot 1.
> > > xinf2 = np.int(event.xdata - zoom1)
> > > xsup2 = np.int(event.xdata + zoom1)
> > > yinf2 = np.int(event.ydata - zoom1)
> > > ysup2 = np.int(event.ydata + zoom1)
> > > ax2data = self.data[yinf2:ysup2, xinf2:xsup2]
> > > self.plt2.set_data(ax2data)
> > > self.ax2.figure.canvas.draw()
>
> --
> Un clavier azerty en vaut deux
> ----------------------------------------------------------
> ?ric Depagne
>
>
> _______________________________________________
> Matplotlib-users mailing list
> Matplotlib-users at python.org
> https://mail.python.org/mailman/listinfo/matplotlib-users

--
Un clavier azerty en vaut deux
----------------------------------------------------------
?ric Depagne

Hello.

Can you post the final code for us ?

Christophe BAL
Enseignant Agr?g? de Math?matiques
Programmeur Python Amateur

Le 20 f?vr. 2018 09:01, "?ric Depagne" <eric at depagne.org> a ?crit :

Le lundi 19 f?vrier 2018, 17:04:28 SAST Benjamin Root a ?crit :
Hi Ben,

Thanks for the idea.
I'll see how my code runs on a slower computer than mine, and I'll
implement
it should I find my current solution too slow.

?ric.

> You might want to consider not having the limits change at *every* mouse
> motion over the axes. You can add a function state variable and maybe
have
> it refresh every other motion or so.
>
> ```
> def _on_move(self, event):
> zoom1 = 100
> if event.inaxes:
>
> ax = event.inaxes # the axes instance
> if 'AX1' in ax.get_label():
> _on_move.counter += 1
> if _on_move.counter % 2:
> return
> # Mouse is in subplot 1.
> xinf2 = np.int(event.xdata - zoom1)
> xsup2 = np.int(event.xdata + zoom1)
> yinf2 = np.int(event.ydata - zoom1)
> ysup2 = np.int(event.ydata + zoom1)
> ax2data = self.data[yinf2:ysup2, xinf2:xsup2]
> self.plt2.set_data(ax2data)
> self.ax2.figure.canvas.draw()
> _on_move.counter = 0
> ```
> Another approach could be done where you capture the timestamp of when
this
> function was last used for updating the limits, and only do a new limit
> update if a certain amount of time passed, such as half a second or so.
>
> Cheers!
> Ben Root
>
> > Le vendredi 16 f?vrier 2018, 21:41:07 SAST vincent.adrien at gmail.com a
> > ?crit :
> > Hi Adrien,
> >
> > Thanks for the answer, I'll have a look and will try to get things
working
> > a
> > bit more efficiently.
> >
> > Cheers,
> > ?ric.
> >
> > > Hi ?ric,
> > >
> > > I am not very used to play with interactive events, but I guess some
> > > blitting could help you with performance:
> > > -
> > > https://stackoverflow.com/questions/29277080/efficient-> >
> > matplotlib-redrawing
> >
> > > -
> > > https://matplotlib.org/users/event_handling.html#draggable-> >
> > rectangle-exercis
> >
> > > e (see the extra credit example)
> > >
> > > See the attached script that is inspired from your code and seems to
> > > less stress my CPU.
> > >
> > > Hopefully this helps.
> > >
> > > Best,
> > > Adrien
> > >
> > > > Hi all,
> > > >
> > > > I have a gridspec plot and one of the subplot is a zoom on the part
> >
> > over
> >
> > > > which the mouse hovers on another subplot.
> > > >
> > > > It works, but I think the way I implemented it is not very
efficient,
> > > > since each time I use it, I see one CPU go to 100%.
> > > > Here is the code that does implement the zoom. Any idea on how to
make
> >
> > it
> >
> > > > (more) efficient or changes that I should implement welcome.
> > > >
> > > > Thanks.
> > > >
> > > > def plot(self):
> > > > gs = gridspec.GridSpec(6, 2)
> > > > ax1 = plt.subplot(gs[1:, 0])
> > > > plt1 = ax1.imshow(self.data, vmin=self.dataminzs,
> > > > vmax=self.datamaxzs)
> > > > ax1.set_label('AX1')
> > > > self.ax2 = plt.subplot(gs[0:3, 1])
> > > > zoomeddata = self.data[np.int(self.data.shape[0]/
> > > >
> > > > 2)-50:np.int(self.data.shape[0]/2)+50, np.int(self.data.shape[1]/
> > > > 2)-50:np.int(self.data.shape[1]/2)+50]
> > > >
> > > > self.plt2 = self.ax2.imshow(zoomeddata,
vmin=self.dataminzs,
> > > >
> > > > vmax=self.datamaxzs)
> > > >
> > > > ax1.figure.canvas.mpl_connect('motion_notify_event',
> > > > self._on_move)
> > > >
> > > > def _on_move(self, event):
> > > > zoom1 = 100
> > > >
> > > > if event.inaxes:
> > > > ax = event.inaxes # the axes instance
> > > >
> > > > if 'AX1' in ax.get_label():
> > > > # Mouse is in subplot 1.
> > > > xinf2 = np.int(event.xdata - zoom1)
> > > > xsup2 = np.int(event.xdata + zoom1)
> > > > yinf2 = np.int(event.ydata - zoom1)
> > > > ysup2 = np.int(event.ydata + zoom1)
> > > > ax2data = self.data[yinf2:ysup2, xinf2:xsup2]
> > > > self.plt2.set_data(ax2data)
> > > > self.ax2.figure.canvas.draw()
> >
> > --
> > Un clavier azerty en vaut deux
> > ----------------------------------------------------------
> > ?ric Depagne
> >
> >
> > _______________________________________________
> > Matplotlib-users mailing list
> > Matplotlib-users at python.org
> > https://mail.python.org/mailman/listinfo/matplotlib-users

--
Un clavier azerty en vaut deux
----------------------------------------------------------
?ric Depagne

_______________________________________________
Matplotlib-users mailing list
Matplotlib-users at python.org
https://mail.python.org/mailman/listinfo/matplotlib-users

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···

> On Mon, Feb 19, 2018 at 9:37 AM, ?ric Depagne <eric at depagne.org> wrote:
> > > On 02/16/2018 01:36 AM, ?ric Depagne wrote:

Hi Christophe,

I am not sure it's what Ben had in mind (if not, I'm happy to know how it
should have been done), but here is the way I did it.

(my _on_move() method is a member of a class)
I added this to the __init__() :
self.counter = 0

Then I added the following lines to _on_move():
self.counter += 1
if self.counter %2 :
        return
[snip all the details of the update of the plots)
self.counter = 0

And it updates the plot every other move.

?ric.

···

--
Un clavier azerty en vaut deux
----------------------------------------------------------
?ric Depagne

Thanks

Christophe BAL
Enseignant Agr?g? de Math?matiques
Programmeur Python Amateur

Le 20 f?vr. 2018 20:02, "?ric Depagne" <eric at depagne.org> a ?crit :

Hi Christophe,

I am not sure it's what Ben had in mind (if not, I'm happy to know how it
should have been done), but here is the way I did it.

(my _on_move() method is a member of a class)
I added this to the __init__() :
self.counter = 0

Then I added the following lines to _on_move():
self.counter += 1
if self.counter %2 :
        return
[snip all the details of the update of the plots)
self.counter = 0

And it updates the plot every other move.

?ric.

--
Un clavier azerty en vaut deux
----------------------------------------------------------
?ric Depagne

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Yup, that's pretty much it. Since you have it all in a class, then doing
`self.counter` makes a lot of sense. You can also tune it accordingly to do
only every 3rd, 4th, 5th or what-have-you.

Cheers!
Ben Root

···

On Tue, Feb 20, 2018 at 3:03 PM, Christophe Bal <projetmbc at gmail.com> wrote:

Thanks

Christophe BAL
Enseignant Agr?g? de Math?matiques
Programmeur Python Amateur

Le 20 f?vr. 2018 20:02, "?ric Depagne" <eric at depagne.org> a ?crit :

Hi Christophe,

I am not sure it's what Ben had in mind (if not, I'm happy to know how it
should have been done), but here is the way I did it.

(my _on_move() method is a member of a class)
I added this to the __init__() :
self.counter = 0

Then I added the following lines to _on_move():
self.counter += 1
if self.counter %2 :
        return
[snip all the details of the update of the plots)
self.counter = 0

And it updates the plot every other move.

?ric.

--
Un clavier azerty en vaut deux
----------------------------------------------------------
?ric Depagne

_______________________________________________
Matplotlib-users mailing list
Matplotlib-users at python.org
https://mail.python.org/mailman/listinfo/matplotlib-users

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It looks like you are redrawing the _whole_ figure every time.

You can use blitting (see
https://matplotlib.org/api/animation_api.html#funcanimation for details) to
only re-draw the axes that is changing.

Tom

···

On Tue, Feb 20, 2018 at 3:28 PM Benjamin Root <ben.v.root at gmail.com> wrote:

Yup, that's pretty much it. Since you have it all in a class, then doing
`self.counter` makes a lot of sense. You can also tune it accordingly to do
only every 3rd, 4th, 5th or what-have-you.

Cheers!
Ben Root

On Tue, Feb 20, 2018 at 3:03 PM, Christophe Bal <projetmbc at gmail.com> > wrote:

Thanks

Christophe BAL
Enseignant Agr?g? de Math?matiques
Programmeur Python Amateur

Le 20 f?vr. 2018 20:02, "?ric Depagne" <eric at depagne.org> a ?crit :

Hi Christophe,

I am not sure it's what Ben had in mind (if not, I'm happy to know how
it
should have been done), but here is the way I did it.

(my _on_move() method is a member of a class)
I added this to the __init__() :
self.counter = 0

Then I added the following lines to _on_move():
self.counter += 1
if self.counter %2 :
        return
[snip all the details of the update of the plots)
self.counter = 0

And it updates the plot every other move.

?ric.

--
Un clavier azerty en vaut deux
----------------------------------------------------------
?ric Depagne

_______________________________________________
Matplotlib-users mailing list
Matplotlib-users at python.org
https://mail.python.org/mailman/listinfo/matplotlib-users

_______________________________________________
Matplotlib-users mailing list
Matplotlib-users at python.org
https://mail.python.org/mailman/listinfo/matplotlib-users

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