Jeff,
Here's a quick snippet. I've looked at the test.py file provided with the
basemap examples. What I am unclear on are the different ways in which nx
and ny are defined. I would like to have this 'automatically' defined, based
solely on variables from my input object.. say for example a netcdf file
that has len and lon dimensions defined.
Below is my crude stab at it, but I am clearly having some problems. I guess
the point is, maybe it's not possible to have a Basemap instance with
extents beyond the imshow object. Then perhaps I need to make sure that when
I set up the Basemap instance, I pass the H.outlon0 to llcrnrlon for
example. But is that necessary?
Thanks!
#!/usr/bin/env python
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
import numpy as np
def plot_imshow_custom(H,transform=True ):
"""
function to automagically plot an mxn array of arbitrary lats/lons
"""
data = H.data
print data.shape
m =
Basemap(projection='npstere',boundinglat=10,lon_0=270,resolution='l')
fig = plt.figure()
ax = fig.gca()
print "Preparing to plot %s with dimensions:" % H.name
print "lon0, numx, dx:"
print H.outlon0, H.numxgrid, H.dxout
print "lat0, numy, dy:"
print H.outlat0, H.numygrid, H.dyout
## set up transformations for the data array
## THIS IS WHERE I NEED SOME HELP:
if m.projection not in ['cyl','merc','mill']:
lats = np.arange( H.outlat0, ( H.outlat0 + ( H.numygrid*H.dyout ) ),
H.dyout )[:-1]
lons = np.arange( H.outlon0, ( H.outlon0 + ( H.numxgrid*H.dxout ) ),
H.dxout )[:-1]
data = data[:-1,:-1]
else:
lats = np.arange( H.outlat0, ( H.outlat0 + ( H.numygrid*H.dyout ) ),
H.dyout )
lons = np.arange( H.outlon0, ( H.outlon0 + ( H.numxgrid*H.dxout ) ),
H.dxout )
print data.shape
## transform to nx x ny regularly spaced native projection grid
if transform:
if m.projection not in ['cyl','merc','mill']:
dx = 2.*np.pi*m.rmajor/len(lons)
dy = 2.*np.pi*m.rminor/len(lats)
else:
dx = len(lons)
dy = len(lats)
nx = int((m.xmax-m.xmin)/dx)+1;
ny = int((m.ymax-m.ymin)/dy)+1
print nx
if nx is 1:
topodat = data
else:
topodat = m.transform_scalar(data,lons,lats,nx,ny)
else:
topodat = data
## Get the current axes, and properties for use later
pos = ax.get_position()
l, b, w, h = pos.bounds
## Set up the IMAGE
colmap = plt.get_cmap('gist_ncar')
im = m.imshow(topodat,cmap=colmap)
m.drawcoastlines()
return fig
class SuperDict(dict):
"""just so I can use . notation"""
def __getattr__(self, attr):
return self[attr]
def __setattr__(self, attr, value):
self[attr] = value
if __name__ == "__main__":
H = SuperDict()
H.name = 'working example'
H.outlat0 = -90
H.numygrid = 180
H.dyout = 1.
H.outlon0 = -179
H.numxgrid = 360
H.dxout = 1.0
H.data = np.random.rand(H.numygrid,H.numxgrid)
print H.data.shape
fig = plot_imshow_custom(H,transform=True)
plt.show()
print 'it worked'
try:
H.name = 'Not working example'
H.outlat0 = 40
H.numygrid = 100
H.dyout = 0.5
H.outlon0 = -179
H.numxgrid = 110
H.dxout = 0.5
H.data = np.random.rand(H.numygrid,H.numxgrid)
fig = plot_imshow_custom(H)
print 'huh?'
plt.show()
except:
print "As I said, it's not working..."
Jeff Whitaker wrote:
>
> John [H2O] wrote:
>> I'm trying to 'automate' a few components within basemap. I have a pretty
>> complicated, and assuredly poorly written, set of functions that allow me
>> to
>> 'dynamically' plot a grid of data (lon,lat).
>>
>> Here is one section where I try to deal with transforming the data based
>> on
>> the projection. 'data' is a grid, often of size 720x360 or 720x180,
>> representing full globe or hemisphere at 0.5 degree resolution.
>> 'outlon0',
>> outlat0', and 'd*out' are the llcrnr coordinates and step. 'transform' is
>> an
>> option, that is set to True by default:
>>
>> 1680 ## set up transformations for the data array
>> 1681 if m.projection not in ['cyl','merc','mill']:
>> 1682 lats = np.arange( outlat0, ( outlat0 + ( numygrid*dyout ) ),
>> dyout )[:-1]
>> 1683 lons = np.arange( outlon0, ( outlon0 + ( numxgrid*dxout ) ),
>> dxout )[:-1]
>> 1684 data = data[:-1,:-1]
>> 1685 else:
>> 1686 lats = np.arange( outlat0, ( outlat0 + ( numygrid*dyout ) ),
>> dyout )
>> 1687 lons = np.arange( outlon0, ( outlon0 + ( numxgrid*dxout ) ),
>> dxout )
>> 1688
>> 1689 ## transform to nx x ny regularly spaced native projection grid
>> 1690 if transform:
>> 1691 dx = 2.*np.pi*m.rmajor/len(lons)
>> 1692 nx = int((m.xmax-m.xmin)/dx)+1; ny =
>> int((m.ymax-m.ymin)/dx)+1
>> 1693 if nx is 1:
>> 1694 topodat = data
>> 1695 else:
>> 1696 topodat = m.transform_scalar(data,lons,lats,nx,ny)
>> 1697 else:
>> 1698 topodat = data
>>
>> The problem is, when I use the approach with a 'cyl' grid, then
>> subsequently
>> try to draw the lsmask, I get a failure. Is this approach incorrect? I
>> had
>> to use the if nx is 1 statement because it was crashing with zero
>> division
>> error in some cases.
>>
>> Thanks.
>>
> John: Please supply us with a self-contained example triggering the
> error that we can run.
>
> -Jeff
>
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