Hello,
Is there a way to get the data value at a specific longitude/latitude
from an array that has been projected and smoothed with basemap and
transform_scalar to a higher grid density?
My original data is a global lat,lon array (73,144) that I process by
hemisphere with a polar centered 'laea'
Hello,
I am hoping that there is a way to use matplotlib to process a sea level
pressure field and extract the closed contours therein so that I have a
collection of lists with the (lon,lat) pairs that define the perimeter of
each closed contour. At the very least I would like a perimeter list of
Howdy All,
I'm hoping someone can give me a quick solution to a couple of
problems. I think I'm just missing an idea or two.
Problem 1: I'm creating a map using the 'llc' lambert conformal
projection and pcolormesh. Here is a sampling of the source.
self.m = Basemap(lat_0=self.lat_0,
Hello,
Quick note. I'm making plots with hexbin and everything works
correctly until I try to use the norm='Normalize' option at which
point I get:
Traceback (most recent call last):
File "diff_engine_v2tmp.py", line 731, in
kept_and_discards)
File "diff_engine_v2tmp.py", line 605
I've been testing matplotlib and basemap (0.98.x and 0.99.x via svn source)
and python 2.6 (via svn) on ubuntu 8.04 (AMD-64).
I noticed that calling basemap in a loop results in a fairly steep linear
increase in memory use; I burn though 6 Gb in a minute.
Putting a loop in plotmap.py from the pro
Howdy,
I'm a recent refugee from GMT (Generic Mapping Tools) and am very
happy to have found matplotlib.
I've been having one nagging issue however that I must resolve as I
require this ability. Basically, I need to mask 2d arrays and plot
the result with pcolor via basemap.
From the docu
Howdy,
I'm a recent refugee from GMT (Generic Mapping Tools) and am very happy to
have found matplotlib.
I've been having one nagging issue however that I must resolve as I require
this ability. Basically, I need to mask 2d arrays and plot the result with
pcolor via basemap.
>From the documentat
