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From: Sourish B. <sou...@gm...> - 2015-06-08 22:39:17
|
<html>
<head>
<meta content="text/html; charset=utf-8" http-equiv="Content-Type">
</head>
<body bgcolor="#FFFFFF" text="#000000">
<div class="moz-cite-prefix"><br>
On 06/05/2015 03:57 PM, Joe Kington wrote:<br>
</div>
<blockquote
cite="mid:CAC...@ma..."
type="cite">
<p dir="ltr">Not to plug one of my own answers to much, but here's
a basic example. <a moz-do-not-send="true"
href="http://stackoverflow.com/questions/20144529/shifted-colorbar-matplotlib">http://stackoverflow.com/questions/20144529/shifted-colorbar-matplotlib</a></p>
<p dir="ltr">I've been meeting to submit a PR with a more full
featured version for a few years now, but haven't.</p>
</blockquote>
<br>
This is great, but it has a slightly bothersome side effect on the
colorbar ticks. In your original example, I changed the line 'data =
10 * (data - 0.8)' to 'data = 10 * (data - 0.85)', so that the
numbers are now in between -8.5 and +1.5. As a result, when the
colorbar is drawn, you get a tick at -8, as well as one at -9
(similarly at +1 and +2). Example attached. As in, the colorbar
method seems intent on adding those tick marks at -9 and +2. The
result is not aesthetically pleasing.<br>
<br>
In one of my real-data example, the minimum value of the data
happened to be -4.003, and as a result there was a tick label at -4
and an overlapping tick label at -5. Why does this happen only when
I specify 'norm' in imshow? How do I get matplotlib to not do that?<br>
<br>
Thanks,<br>
Sourish<br>
<br>
<blockquote
cite="mid:CAC...@ma..."
type="cite">
<div class="gmail_quote">On Jun 5, 2015 4:45 PM, "Sourish Basu"
<<a moz-do-not-send="true"
href="mailto:sou...@gm...">sou...@gm...</a>>
wrote:<br type="attribution">
<blockquote class="gmail_quote" style="margin:0 0 0
.8ex;border-left:1px #ccc solid;padding-left:1ex">
<div bgcolor="#FFFFFF" text="#000000">
<div>On 06/05/2015 01:20 PM, Eric Firing wrote: </div>
<blockquote type="cite">
<pre>Reminder: in matplotlib, color mapping is done with the combination of a
colormap and a norm. This allows one to design a norm to handle the
mapping, including any nonlinearity or difference between the handling
of positive and negative values. This is more general than customizing
a colormap; once you have a norm to suit your purpose, you can use it
with any colormap.
Maybe this is actually what you are already doing, but I wanted to point
it out here in case some readers are not familiar with this
colormap+norm strategy.</pre>
</blockquote>
<br>
Actually, I didn't use norms because I never quite figured
out how to use them or how to make my own. If there's a way
to create a norm with a custom mid-point, I'd love to
know/use that.<br>
<br>
-Sourish<br>
<br>
<blockquote type="cite">
<pre>
Eric
------------------------------------------------------------------------------
_______________________________________________
Matplotlib-users mailing list
<a moz-do-not-send="true" href="mailto:Mat...@li..." target="_blank">Mat...@li...</a>
<a moz-do-not-send="true" href="https://lists.sourceforge.net/lists/listinfo/matplotlib-users" target="_blank">https://lists.sourceforge.net/lists/listinfo/matplotlib-users</a>
</pre>
</blockquote>
<br>
<br>
<div>-- <br>
<b>Q:</b> What if you strapped C4 to a boomerang? Could
this be an effective weapon, or would it be as stupid as
it sounds?<br>
<b>A:</b> Aerodynamics aside, I’m curious what tactical
advantage you’re expecting to gain by having the high
explosive fly back at you if it misses the target.<br>
</div>
</div>
<br>
------------------------------------------------------------------------------<br>
<br>
_______________________________________________<br>
Matplotlib-users mailing list<br>
<a moz-do-not-send="true"
href="mailto:Mat...@li...">Mat...@li...</a><br>
<a moz-do-not-send="true"
href="https://lists.sourceforge.net/lists/listinfo/matplotlib-users"
target="_blank">https://lists.sourceforge.net/lists/listinfo/matplotlib-users</a><br>
<br>
</blockquote>
</div>
</blockquote>
<br>
<br>
<div class="moz-signature">-- <br>
<b>Q:</b> What if you strapped C4 to a boomerang? Could this be an
effective weapon, or would it be as stupid as it sounds?<br>
<b>A:</b> Aerodynamics aside, I’m curious what tactical advantage
you’re expecting to gain by having the high explosive fly back at
you if it misses the target.<br>
</div>
</body>
</html>
|
|
From: Jody K. <jk...@uv...> - 2015-06-08 21:26:56
|
Hi Ben, My idea was to just make the notebook the “example”. But nbconvert-ing the notebook makes static images that then need to be checked into the repository, and take space, so I wasn’t sure how desirable that was. It would be fun to have the documentation script accept ipython notebooks and run nbconvert on them. Being able to save state as you work through examples is quite nice, versus creating five or six standalone *.py files that then get run at build time. Of course you are adding a dependency to anyone who has wants to build the docs. Thanks, Jody > On 8 Jun 2015, at 13:35 PM, Benjamin Root <ben...@ou...> wrote: > > No, there isn't an accepted way to do that AFAIK. However, it doesn't seem like it is all that far off. Our doc-build process will create the images from the examples automatically, so you don't need to include the image tag. It is sort of a way to make sure the examples work and that the image matches the code correctly. > > On Mon, Jun 8, 2015 at 1:06 PM, Jody Klymak <jk...@uv... <mailto:jk...@uv...>> wrote: > > Hi all, > > If I want to contribute *.rst files to the matplotlib documentation, I can see a few styles already contributed, at least one of which makes extensive use of ipython (http://matplotlib.org/users/image_tutorial.html <http://matplotlib.org/users/image_tutorial.html>). However, even it makes use of `.. sourcecode:: python` and `.. plot::` blocks. > > If I convert an ipython notebook to rst, it formats as: `.. code:: python` and instead of making plots it loads images: > `.. image:: MyExample_files/MyExample_1_0.png` > > So, is there an acceptable way to directly make matplotlib documentation directly from a notebook? I didn’t see anything, but wanted to check, as that would by far be the easiest way to make a *.rst that had structured text, code, and plots. > > Thanks, Jody > > -- > Jody Klymak > http://web.uvic.ca/~jklymak/ <http://web.uvic.ca/~jklymak/> > > > > > > > ------------------------------------------------------------------------------ > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... <mailto:Mat...@li...> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users <https://lists.sourceforge.net/lists/listinfo/matplotlib-users> > -- Jody Klymak http://web.uvic.ca/~jklymak/ |
|
From: Benjamin R. <ben...@ou...> - 2015-06-08 20:36:05
|
No, there isn't an accepted way to do that AFAIK. However, it doesn't seem like it is all that far off. Our doc-build process will create the images from the examples automatically, so you don't need to include the image tag. It is sort of a way to make sure the examples work and that the image matches the code correctly. On Mon, Jun 8, 2015 at 1:06 PM, Jody Klymak <jk...@uv...> wrote: > > Hi all, > > If I want to contribute *.rst files to the matplotlib documentation, I can > see a few styles already contributed, at least one of which makes extensive > use of ipython (http://matplotlib.org/users/image_tutorial.html). > However, even it makes use of `.. sourcecode:: python` and `.. plot::` > blocks. > > If I convert an ipython notebook to rst, it formats as: `.. code:: python` > and instead of making plots it loads images: > `.. image:: MyExample_files/MyExample_1_0.png` > > So, is there an acceptable way to directly make matplotlib documentation > directly from a notebook? I didn’t see anything, but wanted to check, as > that would by far be the easiest way to make a *.rst that had structured > text, code, and plots. > > Thanks, Jody > > -- > Jody Klymak > http://web.uvic.ca/~jklymak/ > > > > > > > > ------------------------------------------------------------------------------ > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > |
|
From: Benjamin R. <ben...@ou...> - 2015-06-08 20:32:50
|
By the way, if you want quick-n-easy plotting of shapefiles, I suggest using GeoPandas, which makes it dead simple. On Mon, Jun 8, 2015 at 1:49 PM, Ronquillo, Edgar Nahum <ero...@la...> wrote: > Hello, > I am currently working with Basemap to plot a shapefile on the map. > However, I am confused on how to initialize llcrnrx and llcrnry and same > for the upper corner. I currently have both latitudes and longitudes for > lower and upper corners in degrees. Does this mean I have to convert from > degrees to x,y coordinates? I tried using llcrnrlon and llcrnrlat but it > doesn't seem to like this. Please help me clarify this, any help would be > great. > > Thank You > > > ------------------------------------------------------------------------------ > > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > > |
|
From: Paul H. <pmh...@gm...> - 2015-06-08 19:29:09
|
Edgar, You feed lat/lon (float) values. See this example here: http://matplotlib.org/basemap/users/cea.html And a whole collection of setting up maps in other projection here: http://matplotlib.org/basemap/users/mapsetup.html You also need to make sure that all of inputs make sense together (e.g., you're not specifying any corners beyond the range of your specific projection) -p On Mon, Jun 8, 2015 at 10:49 AM, Ronquillo, Edgar Nahum <ero...@la... > wrote: > Hello, > I am currently working with Basemap to plot a shapefile on the map. > However, I am confused on how to initialize llcrnrx and llcrnry and same > for the upper corner. I currently have both latitudes and longitudes for > lower and upper corners in degrees. Does this mean I have to convert from > degrees to x,y coordinates? I tried using llcrnrlon and llcrnrlat but it > doesn't seem to like this. Please help me clarify this, any help would be > great. > > Thank You > > > ------------------------------------------------------------------------------ > > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > > |
|
From: Ronquillo, E. N. <ero...@la...> - 2015-06-08 17:49:32
|
Hello, I am currently working with Basemap to plot a shapefile on the map. However, I am confused on how to initialize llcrnrx and llcrnry and same for the upper corner. I currently have both latitudes and longitudes for lower and upper corners in degrees. Does this mean I have to convert from degrees to x,y coordinates? I tried using llcrnrlon and llcrnrlat but it doesn't seem to like this. Please help me clarify this, any help would be great. Thank You |
|
From: Jody K. <jk...@uv...> - 2015-06-08 17:07:01
|
Hi all, If I want to contribute *.rst files to the matplotlib documentation, I can see a few styles already contributed, at least one of which makes extensive use of ipython (http://matplotlib.org/users/image_tutorial.html). However, even it makes use of `.. sourcecode:: python` and `.. plot::` blocks. If I convert an ipython notebook to rst, it formats as: `.. code:: python` and instead of making plots it loads images: `.. image:: MyExample_files/MyExample_1_0.png` So, is there an acceptable way to directly make matplotlib documentation directly from a notebook? I didn’t see anything, but wanted to check, as that would by far be the easiest way to make a *.rst that had structured text, code, and plots. Thanks, Jody -- Jody Klymak http://web.uvic.ca/~jklymak/ |
|
From: Jan H. <jan...@gm...> - 2015-06-08 08:51:31
|
I put the data into a list of lists of numpy arrays. The following script
generated a plot similar to what Juan attached:
import matplotlib.pyplot as plt
import numpy as np
def model(t, ii, jj):
"""
Returns some numbers according to the independent variable, t, and
parameters of the model, ii and jj.
"""
return (jj*6+ii)*np.ones_like(t)
### generate data (i.e. model + some random values)
t = np.linspace(-2.5, 2.5, 11)
data = [
[model(t, ii, jj) + np.random.rand(len(t)) - .5
for ii in range(6)] # different sessions
for jj in range(2)] # accuracy/speed
### do the plotting
colors = ['b', 'r']
titles = ['Accuracy emphasis', 'Speed emphasis']
fig, big_axes = plt.subplots(figsize=(16, 6), nrows=2, ncols=1, sharey=True)
for row, big_ax in enumerate(big_axes):
big_ax.set_ylabel('RT distributions')
big_ax.set_xlabel('Response time [s]')
big_ax.set_title(titles[row])
big_ax.tick_params(labelcolor=(1.,1.,1.,0.), top='off', bottom='off',
left='off', right='off')
big_ax._frameon = False
for jj, emph_data in enumerate(data):
for ii, iidata in enumerate(emph_data):
ax = fig.add_subplot(len(data), len(emph_data),
jj*len(emph_data)+ii+1)
# plot bars:
ax.bar(t, iidata,
color=colors[jj],
width=(max(t)-min(t))/(len(t)-1), # for non-overlapping bars
linewidth=0) # no outlines
# plot models:
ax.plot(t, model(t, ii, jj), 'k', linewidth=2)
# annotate axes etc.
ax.set_xticks((-2.5, 0., 2.5))
ax.set_ylim((-.1, 12.8))
ax.annotate('Session {}'.format(ii+1), xy=(-2.4, 11.8))
plt.tight_layout()
plt.show()
How to add the centered titles for each row is described here :
http://stackoverflow.com/questions/27426668/row-titles-for-matplotlib-subplot
Jan
On 8 June 2015 at 03:27, Paul Hobson <pmh...@gm...> wrote:
> (apologies if the list receives this twice)
>
> On Fri, Jun 5, 2015 at 9:14 AM, Juan Wu <wuj...@gm...> wrote:
>>
>>> Hi, Experts,
>>>
>>> My colleagues and I have a question, how we can make a plot via python
>>> like below. According to a guy's original paper, "Each panel shows the
>>> normalized histograms of the observed data (bar plots) and the model
>>> prediction (black lines) ".
>>>
>>> I believe that people can make it with Matplotlib. Any code suggestion
>>> (with simple example data) would be much appreciated.
>>>
>>> (I am more comfortable with Matlab, but now the python code is
>>> preferred).
>>>
>>> J
>>>
>>
>
> Juan,
>
> It is, of course, very difficult to give any concrete advice without
> knowing how your data are stored.
>
> In any case, seaborn builds on matplotlib to provide some very advanced
> visualization with a very concise API.
>
> I recommend you look into the seaborn.distplot function and
> seaborn.FacetGrid class.
> http://web.stanford.edu/~mwaskom/software/seaborn/
>
> -Paul
>
>
> ------------------------------------------------------------------------------
>
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>
|
|
From: Paul H. <pmh...@gm...> - 2015-06-08 01:27:36
|
(apologies if the list receives this twice) On Fri, Jun 5, 2015 at 9:14 AM, Juan Wu <wuj...@gm...> wrote: > >> Hi, Experts, >> >> My colleagues and I have a question, how we can make a plot via python >> like below. According to a guy's original paper, "Each panel shows the >> normalized histograms of the observed data (bar plots) and the model >> prediction (black lines) ". >> >> I believe that people can make it with Matplotlib. Any code suggestion >> (with simple example data) would be much appreciated. >> >> (I am more comfortable with Matlab, but now the python code is preferred). >> >> J >> > Juan, It is, of course, very difficult to give any concrete advice without knowing how your data are stored. In any case, seaborn builds on matplotlib to provide some very advanced visualization with a very concise API. I recommend you look into the seaborn.distplot function and seaborn.FacetGrid class. http://web.stanford.edu/~mwaskom/software/seaborn/ -Paul |
