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-rw-r--r--numpy/lib/tests/test__iotools.py5
-rw-r--r--numpy/lib/tests/test_arraysetops.py41
-rw-r--r--numpy/lib/tests/test_index_tricks.py11
-rw-r--r--numpy/lib/tests/test_shape_base.py92
-rw-r--r--numpy/lib/tests/test_ufunclike.py4
5 files changed, 150 insertions, 3 deletions
diff --git a/numpy/lib/tests/test__iotools.py b/numpy/lib/tests/test__iotools.py
index 5f6c29a4d..b4888f1bd 100644
--- a/numpy/lib/tests/test__iotools.py
+++ b/numpy/lib/tests/test__iotools.py
@@ -53,6 +53,11 @@ class TestLineSplitter(object):
test = LineSplitter(',')(strg)
assert_equal(test, ['1', '2', '3', '4', '', '5'])
+ # gh-11028 bytes comment/delimiters should get encoded
+ strg = b" 1,2,3,4,,5 % test"
+ test = LineSplitter(delimiter=b',', comments=b'%')(strg)
+ assert_equal(test, ['1', '2', '3', '4', '', '5'])
+
def test_constant_fixed_width(self):
"Test LineSplitter w/ fixed-width fields"
strg = " 1 2 3 4 5 # test"
diff --git a/numpy/lib/tests/test_arraysetops.py b/numpy/lib/tests/test_arraysetops.py
index 984a3b15e..dace5ade8 100644
--- a/numpy/lib/tests/test_arraysetops.py
+++ b/numpy/lib/tests/test_arraysetops.py
@@ -32,7 +32,46 @@ class TestSetOps(object):
assert_array_equal(c, ed)
assert_array_equal([], intersect1d([], []))
-
+
+ def test_intersect1d_indices(self):
+ # unique inputs
+ a = np.array([1, 2, 3, 4])
+ b = np.array([2, 1, 4, 6])
+ c, i1, i2 = intersect1d(a, b, assume_unique=True, return_indices=True)
+ ee = np.array([1, 2, 4])
+ assert_array_equal(c, ee)
+ assert_array_equal(a[i1], ee)
+ assert_array_equal(b[i2], ee)
+
+ # non-unique inputs
+ a = np.array([1, 2, 2, 3, 4, 3, 2])
+ b = np.array([1, 8, 4, 2, 2, 3, 2, 3])
+ c, i1, i2 = intersect1d(a, b, return_indices=True)
+ ef = np.array([1, 2, 3, 4])
+ assert_array_equal(c, ef)
+ assert_array_equal(a[i1], ef)
+ assert_array_equal(b[i2], ef)
+
+ # non1d, unique inputs
+ a = np.array([[2, 4, 5, 6], [7, 8, 1, 15]])
+ b = np.array([[3, 2, 7, 6], [10, 12, 8, 9]])
+ c, i1, i2 = intersect1d(a, b, assume_unique=True, return_indices=True)
+ ui1 = np.unravel_index(i1, a.shape)
+ ui2 = np.unravel_index(i2, b.shape)
+ ea = np.array([2, 6, 7, 8])
+ assert_array_equal(ea, a[ui1])
+ assert_array_equal(ea, b[ui2])
+
+ # non1d, not assumed to be uniqueinputs
+ a = np.array([[2, 4, 5, 6, 6], [4, 7, 8, 7, 2]])
+ b = np.array([[3, 2, 7, 7], [10, 12, 8, 7]])
+ c, i1, i2 = intersect1d(a, b, return_indices=True)
+ ui1 = np.unravel_index(i1, a.shape)
+ ui2 = np.unravel_index(i2, b.shape)
+ ea = np.array([2, 7, 8])
+ assert_array_equal(ea, a[ui1])
+ assert_array_equal(ea, b[ui2])
+
def test_setxor1d(self):
a = np.array([5, 7, 1, 2])
b = np.array([2, 4, 3, 1, 5])
diff --git a/numpy/lib/tests/test_index_tricks.py b/numpy/lib/tests/test_index_tricks.py
index 089a7589a..315251daa 100644
--- a/numpy/lib/tests/test_index_tricks.py
+++ b/numpy/lib/tests/test_index_tricks.py
@@ -6,7 +6,7 @@ from numpy.testing import (
assert_array_almost_equal, assert_raises, assert_raises_regex
)
from numpy.lib.index_tricks import (
- mgrid, ndenumerate, fill_diagonal, diag_indices, diag_indices_from,
+ mgrid, ogrid, ndenumerate, fill_diagonal, diag_indices, diag_indices_from,
index_exp, ndindex, r_, s_, ix_
)
@@ -156,6 +156,15 @@ class TestGrid(object):
assert_array_almost_equal(d[1, :, 1] - d[1, :, 0],
0.2*np.ones(20, 'd'), 11)
+ def test_sparse(self):
+ grid_full = mgrid[-1:1:10j, -2:2:10j]
+ grid_sparse = ogrid[-1:1:10j, -2:2:10j]
+
+ # sparse grids can be made dense by broadcasting
+ grid_broadcast = np.broadcast_arrays(*grid_sparse)
+ for f, b in zip(grid_full, grid_broadcast):
+ assert_equal(f, b)
+
class TestConcatenator(object):
def test_1d(self):
diff --git a/numpy/lib/tests/test_shape_base.py b/numpy/lib/tests/test_shape_base.py
index a35d90b70..c95894f94 100644
--- a/numpy/lib/tests/test_shape_base.py
+++ b/numpy/lib/tests/test_shape_base.py
@@ -2,16 +2,106 @@ from __future__ import division, absolute_import, print_function
import numpy as np
import warnings
+import functools
from numpy.lib.shape_base import (
apply_along_axis, apply_over_axes, array_split, split, hsplit, dsplit,
- vsplit, dstack, column_stack, kron, tile, expand_dims,
+ vsplit, dstack, column_stack, kron, tile, expand_dims, take_along_axis,
+ put_along_axis
)
from numpy.testing import (
assert_, assert_equal, assert_array_equal, assert_raises, assert_warns
)
+def _add_keepdims(func):
+ """ hack in keepdims behavior into a function taking an axis """
+ @functools.wraps(func)
+ def wrapped(a, axis, **kwargs):
+ res = func(a, axis=axis, **kwargs)
+ if axis is None:
+ axis = 0 # res is now a scalar, so we can insert this anywhere
+ return np.expand_dims(res, axis=axis)
+ return wrapped
+
+
+class TestTakeAlongAxis(object):
+ def test_argequivalent(self):
+ """ Test it translates from arg<func> to <func> """
+ from numpy.random import rand
+ a = rand(3, 4, 5)
+
+ funcs = [
+ (np.sort, np.argsort, dict()),
+ (_add_keepdims(np.min), _add_keepdims(np.argmin), dict()),
+ (_add_keepdims(np.max), _add_keepdims(np.argmax), dict()),
+ (np.partition, np.argpartition, dict(kth=2)),
+ ]
+
+ for func, argfunc, kwargs in funcs:
+ for axis in list(range(a.ndim)) + [None]:
+ a_func = func(a, axis=axis, **kwargs)
+ ai_func = argfunc(a, axis=axis, **kwargs)
+ assert_equal(a_func, take_along_axis(a, ai_func, axis=axis))
+
+ def test_invalid(self):
+ """ Test it errors when indices has too few dimensions """
+ a = np.ones((10, 10))
+ ai = np.ones((10, 2), dtype=np.intp)
+
+ # sanity check
+ take_along_axis(a, ai, axis=1)
+
+ # not enough indices
+ assert_raises(ValueError, take_along_axis, a, np.array(1), axis=1)
+ # bool arrays not allowed
+ assert_raises(IndexError, take_along_axis, a, ai.astype(bool), axis=1)
+ # float arrays not allowed
+ assert_raises(IndexError, take_along_axis, a, ai.astype(float), axis=1)
+ # invalid axis
+ assert_raises(np.AxisError, take_along_axis, a, ai, axis=10)
+
+ def test_empty(self):
+ """ Test everything is ok with empty results, even with inserted dims """
+ a = np.ones((3, 4, 5))
+ ai = np.ones((3, 0, 5), dtype=np.intp)
+
+ actual = take_along_axis(a, ai, axis=1)
+ assert_equal(actual.shape, ai.shape)
+
+ def test_broadcast(self):
+ """ Test that non-indexing dimensions are broadcast in both directions """
+ a = np.ones((3, 4, 1))
+ ai = np.ones((1, 2, 5), dtype=np.intp)
+ actual = take_along_axis(a, ai, axis=1)
+ assert_equal(actual.shape, (3, 2, 5))
+
+
+class TestPutAlongAxis(object):
+ def test_replace_max(self):
+ a_base = np.array([[10, 30, 20], [60, 40, 50]])
+
+ for axis in list(range(a_base.ndim)) + [None]:
+ # we mutate this in the loop
+ a = a_base.copy()
+
+ # replace the max with a small value
+ i_max = _add_keepdims(np.argmax)(a, axis=axis)
+ put_along_axis(a, i_max, -99, axis=axis)
+
+ # find the new minimum, which should max
+ i_min = _add_keepdims(np.argmin)(a, axis=axis)
+
+ assert_equal(i_min, i_max)
+
+ def test_broadcast(self):
+ """ Test that non-indexing dimensions are broadcast in both directions """
+ a = np.ones((3, 4, 1))
+ ai = np.arange(10, dtype=np.intp).reshape((1, 2, 5)) % 4
+ put_along_axis(a, ai, 20, axis=1)
+ assert_equal(take_along_axis(a, ai, axis=1), 20)
+
+
class TestApplyAlongAxis(object):
def test_simple(self):
a = np.ones((20, 10), 'd')
diff --git a/numpy/lib/tests/test_ufunclike.py b/numpy/lib/tests/test_ufunclike.py
index ad006fe17..5604b3744 100644
--- a/numpy/lib/tests/test_ufunclike.py
+++ b/numpy/lib/tests/test_ufunclike.py
@@ -55,6 +55,10 @@ class TestUfunclike(object):
obj.metadata = self.metadata
return obj
+ def __array_finalize__(self, obj):
+ self.metadata = getattr(obj, 'metadata', None)
+ return self
+
a = nx.array([1.1, -1.1])
m = MyArray(a, metadata='foo')
f = ufl.fix(m)
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