actually, that is technically incorrect. That only works for monotonically
increasing series, but not monotonically decreasing series.
diffs = np.diff(lon)
if np.all(diffs <= 0):
return True
if np.all(diffs >= 0):
return True
return False
provided that len(lon) >= 2, obviously (and it doesn't work right for 2 or
more dimensions).
Ben Root
On Fri, Jun 27, 2014 at 10:03 AM, Jason Swails <jason.swa...@gmail.com>
wrote:
> On Thu, 2014-06-26 at 23:14 -0700, billyi wrote:
> > Oh my, it WAS the meshgrid! Thank you so much!
> > When reading the coordinates like:
> > lat = FB.variables['lat'][:,:]
> > lon = FB.variables['lon'][:,:]
> >
> > And plotting (without meshgrid!):
> > m.pcolormesh(lon, lat, masked_fb, latlon=True)
> >
> > it works! Now I feel stupid.
> > And I think the longitudes and latitudes are not monotonic, but I don't
> know
> > the way to check this, other than checking the array like lon[:] in
> > terminal. Is there a better way?
>
> Yes. Consider:
>
> py> all(lon[:-1] <= lon[1:])
>
> If True, then lon is monotonically increasing. Otherwise it's not.
>
> Description:
>
> lon[:-1] is a slice that takes every element of lon except the last one.
> lon[1:] is a slice that takes every element of lon except the first one.
> The comparison operator will create a bool numpy array whose elements
> will be True for each element "i" if the i'th element is less than or
> equal to the i+1'th element. Applying the "all" (or numpy.all)
> functions to this bool array will return True if every element is true
> and False otherwise.
>
> Faster, easier, and less error-prone than printing out the array and
> checking it yourself. Of course you could do something more explicit:
>
> py> monotonic = True
> py> for i in range(len(lon)-1):
> py> if lon[i] > lon[i+1]:
> py> monotonic = False
> py> break
>
> HTH,
> Jason
>
>
>
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