Remove mlab.prctile and mlab.prctile_rank

dstansby · dstansby · commit 61467cf76261 · 2018-09-29T11:05:05.000+01:00
diff --git a/doc/api/next_api_changes/2018-09-18-DS.rst b/doc/api/next_api_changes/2018-09-18-DS.rst
@@ -12,4 +12,6 @@ in Matplotlib 2.2 has been removed. See below for a list:
 - `mlab.longest_contiguous_ones`
 - `mlab.longest_ones`
 - `mlab.PCA`
+- `mlab.prctile` (use numpy.percentile instead)
+- `mlab.prctile_rank`
 - `mlab.donothing_callback`
diff --git a/lib/matplotlib/mlab.py b/lib/matplotlib/mlab.py
@@ -1194,72 +1194,6 @@ def cohere(x, y, NFFT=256, Fs=2, detrend=detrend_none, window=window_hanning,
     return Cxy, f
 
 
-@cbook.deprecated('2.2', 'numpy.percentile')
-def prctile(x, p=(0.0, 25.0, 50.0, 75.0, 100.0)):
-    """
-    Return the percentiles of *x*.  *p* can either be a sequence of
-    percentile values or a scalar.  If *p* is a sequence, the ith
-    element of the return sequence is the *p*(i)-th percentile of *x*.
-    If *p* is a scalar, the largest value of *x* less than or equal to
-    the *p* percentage point in the sequence is returned.
-    """
-
-    # This implementation derived from scipy.stats.scoreatpercentile
-    def _interpolate(a, b, fraction):
-        """Returns the point at the given fraction between a and b, where
-        'fraction' must be between 0 and 1.
-        """
-        return a + (b - a) * fraction
-
-    per = np.array(p)
-    values = np.sort(x, axis=None)
-
-    idxs = per / 100 * (values.shape[0] - 1)
-    ai = idxs.astype(int)
-    bi = ai + 1
-    frac = idxs % 1
-
-    # handle cases where attempting to interpolate past last index
-    cond = bi >= len(values)
-    if per.ndim:
-        ai[cond] -= 1
-        bi[cond] -= 1
-        frac[cond] += 1
-    else:
-        if cond:
-            ai -= 1
-            bi -= 1
-            frac += 1
-
-    return _interpolate(values[ai], values[bi], frac)
-
-
-@cbook.deprecated('2.2')
-def prctile_rank(x, p):
-    """
-    Return the rank for each element in *x*, return the rank
-    0..len(*p*).  e.g., if *p* = (25, 50, 75), the return value will be a
-    len(*x*) array with values in [0,1,2,3] where 0 indicates the
-    value is less than the 25th percentile, 1 indicates the value is
-    >= the 25th and < 50th percentile, ... and 3 indicates the value
-    is above the 75th percentile cutoff.
-
-    *p* is either an array of percentiles in [0..100] or a scalar which
-    indicates how many quantiles of data you want ranked.
-    """
-
-    if not np.iterable(p):
-        p = np.arange(100.0/p, 100.0, 100.0/p)
-    else:
-        p = np.asarray(p)
-
-    if p.max() <= 1 or p.min() < 0 or p.max() > 100:
-        raise ValueError('percentiles should be in range 0..100, not 0..1')
-
-    ptiles = prctile(x, p)
-    return np.searchsorted(ptiles, x)
-
-
 @cbook.deprecated('2.2')
 def center_matrix(M, dim=0):
     """
diff --git a/lib/matplotlib/pylab.py b/lib/matplotlib/pylab.py
@@ -236,7 +236,7 @@
     fftsurr, frange, get_sparse_matrix, get_xyz_where, griddata,
     identity, inside_poly, is_closed_polygon, ispower2, isvector, l1norm,
     l2norm, log2, movavg, norm_flat,
-    path_length, poly_below, poly_between, prctile, prctile_rank,
+    path_length, poly_below, poly_between,
     rec2csv, rec_append_fields, rec_drop_fields, rec_join, rk4, rms_flat,
     segments_intersect, slopes, stineman_interp, vector_lengths,
     window_hanning, window_none)
diff --git a/lib/matplotlib/tests/test_mlab.py b/lib/matplotlib/tests/test_mlab.py
@@ -20,32 +20,6 @@
 '''
 
 
-@pytest.mark.parametrize('input', [
-    # test odd lengths
-    [1, 2, 3],
-    # test even lengths
-    [1, 2, 3, 4],
-    # derived from email sent by jason-sage to MPL-user on 20090914
-    [1, 1, 2, 2, 1, 2, 4, 3, 2, 2, 2, 3, 4, 5, 6, 7, 8, 9, 7, 6, 4, 5, 5],
-],
-ids=[
-    'odd length',
-    'even length',
-    'custom data',
-])
-@pytest.mark.parametrize('percentile', [
-    0,
-    50,
-    75,
-    100,
-    [0, 75, 100],
-])
-def test_prctile(input, percentile):
-    with pytest.warns(MatplotlibDeprecationWarning):
-        assert_allclose(mlab.prctile(input, percentile),
-                        np.percentile(input, percentile))
-
-
 class TestStride(object):
     def get_base(self, x):
         y = x
