SourceForge logo
SourceForge logo
Menu

matplotlib-users — Discussion related to using matplotlib

You can subscribe to this list here.

2003 Jan
Feb
Mar
Apr
May
(3)
Jun
Jul
Aug
(12)
Sep
(12)
Oct
(56)
Nov
(65)
Dec
(37)
2004 Jan
(59)
Feb
(78)
Mar
(153)
Apr
(205)
May
(184)
Jun
(123)
Jul
(171)
Aug
(156)
Sep
(190)
Oct
(120)
Nov
(154)
Dec
(223)
2005 Jan
(184)
Feb
(267)
Mar
(214)
Apr
(286)
May
(320)
Jun
(299)
Jul
(348)
Aug
(283)
Sep
(355)
Oct
(293)
Nov
(232)
Dec
(203)
2006 Jan
(352)
Feb
(358)
Mar
(403)
Apr
(313)
May
(165)
Jun
(281)
Jul
(316)
Aug
(228)
Sep
(279)
Oct
(243)
Nov
(315)
Dec
(345)
2007 Jan
(260)
Feb
(323)
Mar
(340)
Apr
(319)
May
(290)
Jun
(296)
Jul
(221)
Aug
(292)
Sep
(242)
Oct
(248)
Nov
(242)
Dec
(332)
2008 Jan
(312)
Feb
(359)
Mar
(454)
Apr
(287)
May
(340)
Jun
(450)
Jul
(403)
Aug
(324)
Sep
(349)
Oct
(385)
Nov
(363)
Dec
(437)
2009 Jan
(500)
Feb
(301)
Mar
(409)
Apr
(486)
May
(545)
Jun
(391)
Jul
(518)
Aug
(497)
Sep
(492)
Oct
(429)
Nov
(357)
Dec
(310)
2010 Jan
(371)
Feb
(657)
Mar
(519)
Apr
(432)
May
(312)
Jun
(416)
Jul
(477)
Aug
(386)
Sep
(419)
Oct
(435)
Nov
(320)
Dec
(202)
2011 Jan
(321)
Feb
(413)
Mar
(299)
Apr
(215)
May
(284)
Jun
(203)
Jul
(207)
Aug
(314)
Sep
(321)
Oct
(259)
Nov
(347)
Dec
(209)
2012 Jan
(322)
Feb
(414)
Mar
(377)
Apr
(179)
May
(173)
Jun
(234)
Jul
(295)
Aug
(239)
Sep
(276)
Oct
(355)
Nov
(144)
Dec
(108)
2013 Jan
(170)
Feb
(89)
Mar
(204)
Apr
(133)
May
(142)
Jun
(89)
Jul
(160)
Aug
(180)
Sep
(69)
Oct
(136)
Nov
(83)
Dec
(32)
2014 Jan
(71)
Feb
(90)
Mar
(161)
Apr
(117)
May
(78)
Jun
(94)
Jul
(60)
Aug
(83)
Sep
(102)
Oct
(132)
Nov
(154)
Dec
(96)
2015 Jan
(45)
Feb
(138)
Mar
(176)
Apr
(132)
May
(119)
Jun
(124)
Jul
(77)
Aug
(31)
Sep
(34)
Oct
(22)
Nov
(23)
Dec
(9)
2016 Jan
(26)
Feb
(17)
Mar
(10)
Apr
(8)
May
(4)
Jun
(8)
Jul
(6)
Aug
(5)
Sep
(9)
Oct
(4)
Nov
Dec
2017 Jan
(5)
Feb
(7)
Mar
(1)
Apr
(5)
May
Jun
(3)
Jul
(6)
Aug
(1)
Sep
Oct
(2)
Nov
(1)
Dec
2018 Jan
Feb
Mar
Apr
(1)
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2020 Jan
Feb
Mar
Apr
May
(1)
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2025 Jan
(1)
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
S M T W T F S



1
2
(1)
3
4
(1)
5
6
(1)
7
(12)
8
(6)
9
(16)
10
(2)
11
12
13
14
(1)
15
16
17
(1)
18
(1)
19
20
(2)
21
22
(4)
23
(2)
24
25
26
(1)
27
(6)
28
(1)
29
(6)
30
(3)
31
(4)

Showing 6 results of 6

From: klo uo <kl...@gm...> - 2014年01月29日 23:53:44
IMHO that's the most straightforward approach.
He can use masked array for empty blocks (if contour data doesn't
already contain the holes as masked array) and apply inpainting, then
draw the land.
For more details about inpainting: http://stackoverflow.com/a/17125125/992005
On Wed, Jan 29, 2014 at 6:22 PM, Eric Firing <ef...@ha...> wrote:
> On 2014年01月29日 5:41 AM, A Short wrote:
>> Is there any work around so it looks like the below image?
>
> It looks like with any reasonable contouring algorithm, this would
> require interpolating into land regions, contouring, and then plotting
> the land on top. The key is the interpolation, not the plotting. The
> example you show might have been interpolated to a finer grid
> everywhere, not just in the missing value regions.
From: Eric F. <ef...@ha...> - 2014年01月29日 17:22:33
On 2014年01月29日 5:41 AM, A Short wrote:
> Is there any work around so it looks like the below image?
It looks like with any reasonable contouring algorithm, this would 
require interpolating into land regions, contouring, and then plotting 
the land on top. The key is the interpolation, not the plotting. The 
example you show might have been interpolated to a finer grid 
everywhere, not just in the missing value regions.
I can't comment on the file itself.
Eric
>
> Could anyone confirm that this would be the correct grib file for The North
> Atlantic..?
> ftp://ftpprd.ncep.noaa.gov/pub/data/nccf/com/wave/prod/wave.20140129/nww3.t06z.grib.grib2
>
> Thanks for all the help
>
> <http://matplotlib.1069221.n5.nabble.com/file/n42798/figure_1.png>
>
>
>
>
>
> --
> View this message in context: http://matplotlib.1069221.n5.nabble.com/Plotting-NOAA-grib2-data-in-basemap-tp42698p42798.html
> Sent from the matplotlib - users mailing list archive at Nabble.com.
>
> ------------------------------------------------------------------------------
> WatchGuard Dimension instantly turns raw network data into actionable
> security intelligence. It gives you real-time visual feedback on key
> security issues and trends. Skip the complicated setup - simply import
> a virtual appliance and go from zero to informed in seconds.
> http://pubads.g.doubleclick.net/gampad/clk?id=123612991&iu=/4140/ostg.clktrk
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
From: Eric F. <ef...@ha...> - 2014年01月29日 17:17:53
On 2014年01月28日 11:40 PM, Ian Thomas wrote:
> On 29 January 2014 03:21, Eric Firing <ef...@ha...
> <mailto:ef...@ha...>> wrote:
>
> On 2014年01月28日 10:01 AM, A Short wrote:
> > Hi - Ive now improved my code and confirmed the use of the right
> grib file
> > but i cant for the life of me figure out the missing data near the
> > coastline..? Could anyone help?
>
> The present contouring algorithm works with rectangular blocks, and if
> any corner has missing data, nothing is filled for that block.
>
>
> This will improve shortly, cutting off the corners of some of those
> empty blocks. I am currently testing the new algorithm for this prior to
> submitting it for others' approval.
Ian,
I'm glad to hear that! One possibility would be to use a temporary 
rcParam (temporary in that it might be phased out after a couple 
releases) to allow switching between the two algorithms. This would 
make it much easier to test, and it would also allow a transition during 
which people could reproduce results obtained with earlier mpl. It 
would also be a safety measure, in case someone hits a corner case which 
the new algorithm doesn't handle but the old one does--not that I'm 
expecting such cases to arise.
Eric
>
> Ian
From: A S. <sur...@ho...> - 2014年01月29日 15:41:12
Is there any work around so it looks like the below image?
Could anyone confirm that this would be the correct grib file for The North
Atlantic..? 
ftp://ftpprd.ncep.noaa.gov/pub/data/nccf/com/wave/prod/wave.20140129/nww3.t06z.grib.grib2
Thanks for all the help
<http://matplotlib.1069221.n5.nabble.com/file/n42798/figure_1.png> 
--
View this message in context: http://matplotlib.1069221.n5.nabble.com/Plotting-NOAA-grib2-data-in-basemap-tp42698p42798.html
Sent from the matplotlib - users mailing list archive at Nabble.com.
From: Ian T. <ian...@gm...> - 2014年01月29日 09:40:16
On 29 January 2014 03:21, Eric Firing <ef...@ha...> wrote:
> On 2014年01月28日 10:01 AM, A Short wrote:
> > Hi - Ive now improved my code and confirmed the use of the right grib
> file
> > but i cant for the life of me figure out the missing data near the
> > coastline..? Could anyone help?
>
> The present contouring algorithm works with rectangular blocks, and if
> any corner has missing data, nothing is filled for that block.
>
This will improve shortly, cutting off the corners of some of those empty
blocks. I am currently testing the new algorithm for this prior to
submitting it for others' approval.
Ian
From: Eric F. <ef...@ha...> - 2014年01月29日 03:28:29
On 2014年01月28日 10:01 AM, A Short wrote:
> Hi - Ive now improved my code and confirmed the use of the right grib file
> but i cant for the life of me figure out the missing data near the
> coastline..? Could anyone help?
The present contouring algorithm works with rectangular blocks, and if 
any corner has missing data, nothing is filled for that block.
Eric
>
> `import Nio
> from mpl_toolkits.basemap import Basemap
> import matplotlib.pyplot as plt
> import numpy as np
>
> f = Nio.open_file('nww3.t12z.grib(2).grib2')
> lons = f.variables['lon_0'][:]
> lats = f.variables['lat_0'][::-1] # flip latitudes so data goes S-->N
> times = f.variables['forecast_time0'][:]
> ntime = 5
> data = f.variables['HTSGW_P0_L1_GLL0'][ntime,::-1]
>
> fig = plt.figure(figsize=(16,16))
> m = Basemap(llcrnrlon=-35.,llcrnrlat=42.,urcrnrlon=5.,urcrnrlat=65.,
> projection='lcc',lat_1=10.,lat_2=15.,lon_0=10.,
> resolution ='h',area_thresh=1000.)
>
> x, y = m(*np.meshgrid(lons, lats))
> m.fillcontinents(color='#477519')
> m.drawcoastlines(linewidth=0.5, color='k', antialiased=1, ax=None,
> zorder=None )
>
> m.contourf(x, y, data, np.arange(0,9.9,0.1))
> plt.show() `
>
> Resulting plot is here
> <http://matplotlib.1069221.n5.nabble.com/file/n42790/figure_7.png>
>
>
>
> --
> View this message in context: http://matplotlib.1069221.n5.nabble.com/Plotting-NOAA-grib2-data-in-basemap-tp42698p42790.html
> Sent from the matplotlib - users mailing list archive at Nabble.com.
>
> ------------------------------------------------------------------------------
> WatchGuard Dimension instantly turns raw network data into actionable
> security intelligence. It gives you real-time visual feedback on key
> security issues and trends. Skip the complicated setup - simply import
> a virtual appliance and go from zero to informed in seconds.
> http://pubads.g.doubleclick.net/gampad/clk?id=123612991&iu=/4140/ostg.clktrk
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Showing 6 results of 6

Want the latest updates on software, tech news, and AI?
Get latest updates about software, tech news, and AI from SourceForge directly in your inbox once a month.
Thanks for helping keep SourceForge clean.
X





Briefly describe the problem (required):
Upload screenshot of ad (required):
Select a file, or drag & drop file here.
Screenshot instructions:

Click URL instructions:
Right-click on the ad, choose "Copy Link", then paste here →
(This may not be possible with some types of ads)

More information about our ad policies

Ad destination/click URL:

AltStyle によって変換されたページ (->オリジナル) /