Revision: 5806
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5806&view=rev
Author: jswhit
Date: 2008-07-22 02:17:09 +0000 (Tue, 22 Jul 2008)
Log Message:
-----------
added griddata function (left out in previous commit)
Modified Paths:
--------------
trunk/matplotlib/lib/matplotlib/mlab.py
Modified: trunk/matplotlib/lib/matplotlib/mlab.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/mlab.py 2008-07-22 01:52:12 UTC (rev
5805)
+++ trunk/matplotlib/lib/matplotlib/mlab.py 2008-07-22 02:17:09 UTC (rev
5806)
@@ -90,6 +90,12 @@
import matplotlib.nxutils as nxutils
import matplotlib.cbook as cbook
+try:
+ import mpl_tookits._natgrid as _natgrid
+ _use_natgrid = True
+except ImportError:
+ import matplotlib.delaunay as delaunay
+ _use_natgrid = False
# set is a new builtin function in 2.4; delete the following when
# support for 2.3 is dropped.
@@ -2691,3 +2697,55 @@
in zip(funcs, row, rowmask, mvals)])
if opened:
fh.close()
+
+def griddata(x,y,z,xi,yi):
+ """
+ zi = griddata(x,y,z,xi,yi) fits a surface of the form z = f(x,y)
+ to the data in the (usually) nonuniformly spaced vectors (x,y,z).
+ griddata interpolates this surface at the points specified by (xi,yi)
+ to produce zi. xi and yi must describe a regular grid, can be
+ either 1D or 2D, but must be monotonically increasing.
+
+ A masked array is returned if any grid points are outside convex
+ hull defined by input data (no extrapolation is done).
+
+ Uses natural neighbor interpolation based on Delaunay triangulation.
+ """
+ if xi.ndim != yi.ndim:
+ raise TypeError("inputs xi and yi must have same number of dimensions
(1 or 2)")
+ if xi.ndim != 1 and xi.ndim != 2:
+ raise TypeError("inputs xi and yi must be 1D or 2D.")
+ if _use_natgrid: # use natgrid toolkit if available.
+ if xi.ndim == 2:
+ xi = xi[0,:]
+ yi = yi[:,0]
+ # override default natgrid internal parameters.
+ _natgrid.seti('ext',0)
+ _natgrid.setr('nul',np.nan)
+ # cast input arrays to doubles (this makes a copy)
+ x = x.astype(np.float)
+ y = y.astype(np.float)
+ z = z.astype(np.float)
+ xo = xi.astype(np.float)
+ yo = yi.astype(np.float)
+ if min(xo[1:]-xo[0:-1]) < 0 or min(yo[1:]-yo[0:-1]) < 0:
+ raise ValueError, 'output grid defined by xi,yi must be monotone
increasing'
+ # allocate array for output (buffer will be overwritten by nagridd)
+ zo = np.empty((yo.shape[0],xo.shape[0]), np.float)
+ _natgrid.natgridd(x,y,z,xo,yo,zo)
+ else: # use Robert Kern's delaunay package from scikits (default)
+ if xi.ndim != yi.ndim:
+ raise TypeError("inputs xi and yi must have same number of
dimensions (1 or 2)")
+ if xi.ndim != 1 and xi.ndim != 2:
+ raise TypeError("inputs xi and yi must be 1D or 2D.")
+ if xi.ndim == 1:
+ xi,yi = np.meshgrid(xi,yi)
+ # triangulate data
+ tri = delaunay.Triangulation(x,y)
+ # interpolate data
+ interp = tri.nn_interpolator(z)
+ zo = interp(xi,yi)
+ # mask points on grid outside convex hull of input data.
+ if np.any(np.isnan(zo)):
+ zo = np.ma.masked_where(np.isnan(zo),zo)
+ return zo
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