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Just a thought:
Shouldn't the bars terminate with a arc rather then a straight line? What value should one reading this diagram look at? The one at the center of the "bar" or the "corners" these values can be quite different. 
Sent from my iPhone
On Mar 19, 2013, at 8:00 PM, Paul Hobson <pmh...@gm...> wrote:
> On Tue, Mar 19, 2013 at 2:22 AM, Sudheer Joseph <sud...@ya...> wrote:
>> Dear users,
>> Attached is a windrose diagram created by using https://sourceforge.net/project/showfiles.php?group_id=239240&package_id=290902 . Can any one tell me if the numbers displayed in the attached plot is % of wind directions in each category? or are they represent some other numbers?
>> 
>> http://3.bp.blogspot.com/_4ZlrnfU7IT8/TPxpftZGzfI/AAAAAAAAADA/uq9cF3PTpR8/s1600/Wind_rose_plot.jpg
> 
> Sudheer, 
> 
> That's correct. The total length of the bars is the percentage of time that the wind is blowing *from* that direction. 
> See my implementation here: https://github.com/phobson/python-metar/blob/master/metar/graphics.py#L135
> 
> Side note, you're emails are consistently formatted pretty strangely and can be difficult to read. Perhaps stick with the same font that is in your email signature?
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On Tue, Mar 19, 2013 at 11:30 AM, Paul Hobson <pmh...@gm...> wrote:
> On Mon, Mar 18, 2013 at 8:34 PM, Mark Lawrence <bre...@ya...>wrote:
>
>> Matplotlib 1.2.0, Windows Vista, Python 3.3.0. I want the first major
>> xtick label aligned with the first date that's plotted. This never
>> happens with the value of day below set in the range zero to six. The
>> first major tick label actually occurs as follows.
>>
>> Day Label date
>> 0 25/03/2013
>> 1 02/04/2013
>> 2 10/04/2013
>> 3 21/03/2013
>> 4 29/03/2013
>> 5 06/04/2013
>> 6 17/03/2013
>>
>> What am I doing wrong?
>>
>> If day is set to seven then no xticks are displayed but labels for
>> 14/03/2013 and 13/03/2014 are displayed. I expected a ValueError or
>> similar using this number. Could you explain this behaviour please?
>>
>> import matplotlib.pyplot as plt
>> from matplotlib.ticker import FormatStrFormatter, MultipleLocator
>> from matplotlib.dates import DateFormatter, WeekdayLocator
>> import datetime
>>
>> dates = [datetime.date(2013, 3, 14), datetime.date(2014, 3, 13)]
>> values = [0, 1]
>> plt.ylabel('Balance')
>> plt.grid()
>> ax = plt.subplot(111)
>> plt.plot_date(dates, values, fmt = 'rx-')
>> plt.axis(xmin=dates[0], xmax=dates[-1])
>> day = ?
>> ax.xaxis.set_major_locator(WeekdayLocator(byweekday=day, interval=4))
>> ax.xaxis.set_minor_locator(WeekdayLocator(byweekday=day))
>> ax.xaxis.set_major_formatter(DateFormatter('%d/%m/%y'))
>> ax.yaxis.set_major_formatter(FormatStrFormatter('£%0.2f'))
>> ax.yaxis.set_minor_locator(MultipleLocator(5))
>> plt.setp(plt.gca().get_xticklabels(), rotation = 45, fontsize = 10)
>> plt.setp(plt.gca().get_yticklabels(), fontsize = 10)
>> plt.show()
>>
>>
> Mark,
>
> I've found that rotation_mode='anchor' works best when rotation != 0
>
> So that makes it:
> plt.setp(plt.gca().get_xticklabels(), rotation = 45, fontsize = 10,
> rotation_mode='anchor' )
>
> HTH,
> -paul
>
I misread your question. Try setting your x-axis limits after defining the
locators and formatters.
-p

On Mon, Mar 18, 2013 at 8:34 PM, Mark Lawrence <bre...@ya...>wrote:
> Matplotlib 1.2.0, Windows Vista, Python 3.3.0. I want the first major
> xtick label aligned with the first date that's plotted. This never
> happens with the value of day below set in the range zero to six. The
> first major tick label actually occurs as follows.
>
> Day Label date
> 0 25/03/2013
> 1 02/04/2013
> 2 10/04/2013
> 3 21/03/2013
> 4 29/03/2013
> 5 06/04/2013
> 6 17/03/2013
>
> What am I doing wrong?
>
> If day is set to seven then no xticks are displayed but labels for
> 14/03/2013 and 13/03/2014 are displayed. I expected a ValueError or
> similar using this number. Could you explain this behaviour please?
>
> import matplotlib.pyplot as plt
> from matplotlib.ticker import FormatStrFormatter, MultipleLocator
> from matplotlib.dates import DateFormatter, WeekdayLocator
> import datetime
>
> dates = [datetime.date(2013, 3, 14), datetime.date(2014, 3, 13)]
> values = [0, 1]
> plt.ylabel('Balance')
> plt.grid()
> ax = plt.subplot(111)
> plt.plot_date(dates, values, fmt = 'rx-')
> plt.axis(xmin=dates[0], xmax=dates[-1])
> day = ?
> ax.xaxis.set_major_locator(WeekdayLocator(byweekday=day, interval=4))
> ax.xaxis.set_minor_locator(WeekdayLocator(byweekday=day))
> ax.xaxis.set_major_formatter(DateFormatter('%d/%m/%y'))
> ax.yaxis.set_major_formatter(FormatStrFormatter('£%0.2f'))
> ax.yaxis.set_minor_locator(MultipleLocator(5))
> plt.setp(plt.gca().get_xticklabels(), rotation = 45, fontsize = 10)
> plt.setp(plt.gca().get_yticklabels(), fontsize = 10)
> plt.show()
>
>
Mark,
I've found that rotation_mode='anchor' works best when rotation != 0
So that makes it:
plt.setp(plt.gca().get_xticklabels(), rotation = 45, fontsize = 10,
 rotation_mode='anchor' )
HTH,
-paul

On Tue, Mar 19, 2013 at 2:22 AM, Sudheer Joseph <sud...@ya...>wrote:
> Dear users,
> Attached is a windrose diagram created by using
> https://sourceforge.net/project/showfiles.php?group_id=239240&package_id=290902. Can any one tell me if the numbers displayed in the attached plot is % of
> wind directions in each category? or are they represent some other numbers?
>
>
> http://3.bp.blogspot.com/_4ZlrnfU7IT8/TPxpftZGzfI/AAAAAAAAADA/uq9cF3PTpR8/s1600/Wind_rose_plot.jpg
>
>
Sudheer,
That's correct. The total length of the bars is the percentage of time that
the wind is blowing *from* that direction.
See my implementation here:
https://github.com/phobson/python-metar/blob/master/metar/graphics.py#L135
Side note, you're emails are consistently formatted pretty strangely and
can be difficult to read. Perhaps stick with the same font that is in your
email signature?

It would be easier if there were some code to reproduce the problem - it
wouldn't have to be the actual data you are using.
I wasn't able to reproduce the problem with the following code:
import mpl_toolkits.basemap as bm
import matplotlib.pyplot as plt
# Geotiff from http://earthobservatory.nasa.gov/IOTD/view.php?id=49687
# FROM gdalinfo
#Corner Coordinates:
#Upper Left ( -11.1339000, 55.8714000) ( 11d 8' 2.04"W, 55d52'17.04"N)
#Lower Left ( -11.1339000, 50.9251367) ( 11d 8' 2.04"W, 50d55'30.49"N)
#Upper Right ( -4.8622296, 55.8714000) ( 4d51'44.03"W, 55d52'17.04"N)
#Lower Right ( -4.8622296, 50.9251367) ( 4d51'44.03"W, 50d55'30.49"N)
#Center ( -7.9980648, 53.3982684) ( 7d59'53.03"W, 53d23'53.77"N)
im = plt.imread('ireland_amo_2010284_geo.tif')
# extent = [left, right, bottom, top]
extent = [-11.1339000, -4.8622296, 50.9251367, 55.8714000]
m = bm.Basemap(projection='cyl',
 llcrnrlon=extent[0], urcrnrlon=extent[1],
 llcrnrlat=extent[2], urcrnrlat=extent[3],
 resolution='i')
plt.imshow(im, extent=extent)
m.drawcoastlines()
plt.show()
[image: Inline images 1]
Your data appears to be a long way off. Are you certain of the bounds that
you are setting? Are you using plt.imshow or doing some other operation to
draw (e.g. contour)?
Cheers,
On 12 March 2013 15:00, Hearne, Mike <mh...@us...> wrote:
> The relevant code is:
> It's kind of hard to post code that's reproducible (lots of
> dependencies on code and data), but I'll attach an image at high
> latitudes that demonstrates the problem.
>
> The image is a shaded relief of topography, and the coastlines are
> drawn in black.
>
> The topography is cut from a large ESRI format BIL (Band Interleaved
> by Line) file, and it's bounds define the boundaries of the map. The
> image data is NOT projected (it's in lat/lon).
>
> --Mike
>
> On Tue, Mar 12, 2013 at 3:46 AM, Phil Elson <pel...@gm...> wrote:
> > Hi Mike,
> >
> > Do you have any code or an image to show the problem?
> >
> > Cheers,
> >
> >
> > On 11 March 2013 20:44, Hearne, Mike <mh...@us...> wrote:
> >>
> >> I have an issue with basemap.imshow() at higher latitudes - namely the
> >> image (high-res topography, in this case) becomes distorted with
> >> respect to the coastlines the higher I go. I assume it has to do
> >> with the image pixels becoming more non-square the higher I go in
> >> latitude.
> >>
> >> I found this discussion:
> >> http://matplotlib.1069221.n5.nabble.com/Basemap-and-imshow-td14115.html
> >>
> >> where Jeff indicates that the user is using a non-rectangular map
> >> projection. I'm thinking that is perhaps my problem (I'm using
> >> Transverse Mercator), but I'm not sure which projections Basemap
> >> supports that *are* rectangular.
> >>
> >> Or perhaps it's something else entirely.
> >>
> >> Any hints?
> >>
> >> Thanks,
> >>
> >> Mike Hearne
> >>
> >>
> >>
> ------------------------------------------------------------------------------
> >> Symantec Endpoint Protection 12 positioned as A LEADER in The Forrester
> >> Wave(TM): Endpoint Security, Q1 2013 and "remains a good choice" in the
> >> endpoint security space. For insight on selecting the right partner to
> >> tackle endpoint security challenges, access the full report.
> >> http://p.sf.net/sfu/symantec-dev2dev
> >> _______________________________________________
> >> Matplotlib-users mailing list
> >> Mat...@li...
> >> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> >
> >
>

That's really weird. @mdboom, do you have any idea what the difference is
when drawing a Path which has a clip path? (I've looked at anti-aliasing &
snapping without success)
On 12 March 2013 17:17, Andrew Dawson <da...@at...> wrote:
> I tried this and although it sort-of works, it doesn't really do what I
> need. I tried using this:
>
> import matplotlib.pyplot as plt
> import matplotlib.path as mpath
> import numpy as np
> import copy
>
> # create figure and axes
> fig = plt.figure(figsize=(6, 6))
> ax = fig.add_axes([.1, .1, .8, .8])
> ax.set_xlim([-3, 3])
> ax.set_ylim([-3, 3])
>
> # a circle at the origin with radius 1
> circle = plt.Circle((0, 0), 1, transform=ax.transData,
> edgecolor='k', facecolor='none')
>
> # from Phil's example
> exterior = mpath.Path.unit_rectangle()
> interior = circle.get_path()
> exterior = mpath.Path(copy.deepcopy(exterior.vertices),
> copy.deepcopy(exterior.codes[:]))
> interior.vertices = interior.vertices[::-1]
> exterior.vertices *= 6
> exterior.vertices -= 3
> clip_path = mpath.Path(vertices=np.concatenate([exterior.vertices,
> interior.vertices]),
> codes=np.concatenate([exterior.codes,
> interior.codes]))
>
> # lines from the origin dividing the axes into 8 sectors
> end_coords = [(3, 0), (3, 3), (0, 3), (-3, 3),
> (-3, 0), (-3, -3), (0, -3), (3, -3)]
> for x, y in end_coords:
> line, = ax.plot((x, 0), (y, 0), color='k')
> line.set_clip_path(clip_path, ax.transData)
>
> ax.add_artist(circle)
>
> plt.show()
>
> and the result is the attached image with_clipping.png. You should see
> that the circle is no longer circular, and also there are weird line width
> issues. What I want it basically exactly like the attached
> without_clipping.png but with paths inside the circle removed.
>
> Thanks
>
>
>
> On 12 March 2013 16:43, Phil Elson <pel...@gm...> wrote:
>
>> You could just use paths which have holes in them, making the exterior so
>> broad that you wouldn't notice the edge of the clipping. I've put together
>> an example of doing just that:
>>
>> import matplotlib.pyplot as plt
>> import matplotlib.path as mpath
>> import matplotlib.collections as mcol
>> import numpy as np
>> import copy
>>
>>
>> exterior = mpath.Path.unit_rectangle()
>> exterior = mpath.Path(copy.deepcopy(exterior.vertices),
>> copy.deepcopy(exterior.codes[:]))
>> exterior.vertices *= 4
>> exterior.vertices -= 2
>> interior = mpath.Path.unit_circle()
>> interior.vertices = interior.vertices[::-1]
>> clip_path = mpath.Path(vertices=np.concatenate([exterior.vertices,
>> interior.vertices]),
>> codes=np.concatenate([exterior.codes,
>> interior.codes]))
>>
>> star = mpath.Path.unit_regular_star(6)
>> star.vertices *= 2.6
>>
>>
>> ax = plt.subplot(321)
>> col = mcol.PathCollection([clip_path], facecolor='yellow')
>> ax.add_collection(col)
>> ax.set_title('Clip path')
>> ax.set_xlim([-3, 3])
>> ax.set_ylim([-3, 3])
>>
>>
>> ax = plt.subplot(322)
>> col = mcol.PathCollection([star], facecolor='red')
>> ax.add_collection(col)
>> ax.set_title('Target polygon')
>> ax.set_xlim([-3, 3])
>> ax.set_ylim([-3, 3])
>>
>>
>> ax = plt.subplot2grid((3, 2), (1, 0), colspan=2, rowspan=2)
>> col = mcol.PathCollection([star])
>> col.set_clip_path(clip_path, ax.transData)
>> ax.add_collection(col)
>>
>> ax.set_title('Target polygon clipped by clip_path')
>> ax.set_xlim([-3, 3])
>> ax.set_ylim([-3, 3])
>>
>> plt.tight_layout()
>>
>> plt.show()
>>
>> [image: Inline images 1]
>>
>>
>>
>> There are other options if this doesn't cut the mustard.
>>
>> HTH,
>>
>>
>>
>>
>>
>>
>>
>> On 12 March 2013 15:37, Andrew Dawson <da...@at...> wrote:
>>
>>> Hi
>>>
>>> I'd like to be able to clip a line so that the portion of it lying
>>> outside of a given polygon remains visible and the part that lies inside of
>>> the polygon is not visible. What I want is basically the opposite of:
>>>
>>> line.set_clip_path(polygon)
>>>
>>> which leaves only the part of the line inside the polygon visible. Is
>>> this possible?
>>>
>>> I know I can just fill the polygon with the background color or
>>> something but this gets messy when there are other lines on the plot that
>>> don't need to be clipped.
>>>
>>> Thanks,
>>> Andrew
>>>
>>>
>>> ------------------------------------------------------------------------------
>>> Symantec Endpoint Protection 12 positioned as A LEADER in The Forrester
>>> Wave(TM): Endpoint Security, Q1 2013 and "remains a good choice" in the
>>> endpoint security space. For insight on selecting the right partner to
>>> tackle endpoint security challenges, access the full report.
>>> http://p.sf.net/sfu/symantec-dev2dev
>>> _______________________________________________
>>> Matplotlib-users mailing list
>>> Mat...@li...
>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>
>>>
>>
>
>
> --
> Dr Andrew Dawson
> Atmospheric, Oceanic & Planetary Physics
> Clarendon Laboratory
> Parks Road
> Oxford OX1 3PU, UK
> Tel: +44 (0)1865 282438
> Email: da...@at...
> Web Site: http://www2.physics.ox.ac.uk/contacts/people/dawson
>

Dear users,
             Attached is a windrose diagram created by using https://sourceforge.net/project/showfiles.php?group_id=239240&package_id=290902 . Can any one tell me if the numbers displayed in the attached plot is % of wind directions in each category? or are they represent some other numbers?
http://3.bp.blogspot.com/_4ZlrnfU7IT8/TPxpftZGzfI/AAAAAAAAADA/uq9cF3PTpR8/s1600/Wind_rose_plot.jpg
 
***************************************************************
Sudheer Joseph 
Indian National Centre for Ocean Information Services
Ministry of Earth Sciences, Govt. of India
POST BOX NO: 21, IDA Jeedeemetla P.O.
Via Pragathi Nagar,Kukatpally, Hyderabad; Pin:5000 55
Tel:+91-40-23886047(O),Fax:+91-40-23895011(O),
Tel:+91-40-23044600(R),Tel:+91-40-9440832534(Mobile)
E-mail:sjo...@gm...;sud...@ya...
Web- http://oppamthadathil.tripod.com
***************************************************************

Matplotlib 1.2.0, Windows Vista, Python 3.3.0. I want the first major 
xtick label aligned with the first date that's plotted. This never 
happens with the value of day below set in the range zero to six. The 
first major tick label actually occurs as follows.
Day	Label date
0	25/03/2013
1	02/04/2013
2	10/04/2013
3	21/03/2013
4	29/03/2013
5	06/04/2013
6	17/03/2013
What am I doing wrong?
If day is set to seven then no xticks are displayed but labels for 
14/03/2013 and 13/03/2014 are displayed. I expected a ValueError or 
similar using this number. Could you explain this behaviour please?
import matplotlib.pyplot as plt
from matplotlib.ticker import FormatStrFormatter, MultipleLocator
from matplotlib.dates import DateFormatter, WeekdayLocator
import datetime
dates = [datetime.date(2013, 3, 14), datetime.date(2014, 3, 13)]
values = [0, 1]
plt.ylabel('Balance')
plt.grid()
ax = plt.subplot(111)
plt.plot_date(dates, values, fmt = 'rx-')
plt.axis(xmin=dates[0], xmax=dates[-1])
day = ?
ax.xaxis.set_major_locator(WeekdayLocator(byweekday=day, interval=4))
ax.xaxis.set_minor_locator(WeekdayLocator(byweekday=day))
ax.xaxis.set_major_formatter(DateFormatter('%d/%m/%y'))
ax.yaxis.set_major_formatter(FormatStrFormatter('£%0.2f'))
ax.yaxis.set_minor_locator(MultipleLocator(5))
plt.setp(plt.gca().get_xticklabels(), rotation = 45, fontsize = 10)
plt.setp(plt.gca().get_yticklabels(), fontsize = 10)
plt.show()
-- 
Cheers.
Mark Lawrence