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Deprecate mlab functions #9151

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Merged
merged 5 commits into from
Feb 5, 2018
Merged

Deprecate mlab functions #9151

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e4114e7
Deprecate non-spectral mlab methods
dstansby Sep 8, 2017
4edc56a
Remove bivariate_norm from mpl3d test code
dstansby Dec 24, 2017
104e73a
Remove copy of less_simple_linear_interpolation
dstansby Dec 24, 2017
32a2f79
Remove bivariate_norm from examples
dstansby Dec 24, 2017
4c61a1d
Remove more mlab from examples
dstansby Dec 27, 2017
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Remove copy of less_simple_linear_interpolation
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@dstansby
dstansby committed Feb 2, 2018
commit 104e73a12cfe86b4a331ed633cc8c6c7aa459e7f
42 changes: 0 additions & 42 deletions lib/matplotlib/cbook/__init__.py
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Expand Up @@ -1594,48 +1594,6 @@ def simple_linear_interpolation(a, steps):
.reshape((len(x),) + a.shape[1:]))


def less_simple_linear_interpolation(x, y, xi, extrap=False):
"""
This function provides simple (but somewhat less so than
:func:`cbook.simple_linear_interpolation`) linear interpolation.
:func:`simple_linear_interpolation` will give a list of point
between a start and an end, while this does true linear
interpolation at an arbitrary set of points.

This is very inefficient linear interpolation meant to be used
only for a small number of points in relatively non-intensive use
cases. For real linear interpolation, use scipy.
"""
x = np.asarray(x)
y = np.asarray(y)
xi = np.atleast_1d(xi)

s = list(y.shape)
s[0] = len(xi)
yi = np.tile(np.nan, s)

for ii, xx in enumerate(xi):
bb = x == xx
if np.any(bb):
jj, = np.nonzero(bb)
yi[ii] = y[jj[0]]
elif xx < x[0]:
if extrap:
yi[ii] = y[0]
elif xx > x[-1]:
if extrap:
yi[ii] = y[-1]
else:
jj, = np.nonzero(x < xx)
jj = max(jj)

yi[ii] = (y[jj] +
(xx - x[jj]) / (x[jj + 1] - x[jj]) *
(y[jj + 1] - y[jj]))

return yi


@deprecated('2.1', alternative='shutil.rmtree')
def recursive_remove(path):
if os.path.isdir(path):
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