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-rw-r--r--numpy/lib/tests/test_arraysetops.py7
-rw-r--r--numpy/lib/tests/test_histograms.py37
-rw-r--r--numpy/lib/tests/test_index_tricks.py65
-rw-r--r--numpy/lib/tests/test_utils.py32
4 files changed, 131 insertions, 10 deletions
diff --git a/numpy/lib/tests/test_arraysetops.py b/numpy/lib/tests/test_arraysetops.py
index 4b61726d2..fef06ba53 100644
--- a/numpy/lib/tests/test_arraysetops.py
+++ b/numpy/lib/tests/test_arraysetops.py
@@ -388,6 +388,13 @@ class TestSetOps(object):
a = np.array((), np.uint32)
assert_equal(setdiff1d(a, []).dtype, np.uint32)
+ def test_setdiff1d_unique(self):
+ a = np.array([3, 2, 1])
+ b = np.array([7, 5, 2])
+ expected = np.array([3, 1])
+ actual = setdiff1d(a, b, assume_unique=True)
+ assert_equal(actual, expected)
+
def test_setdiff1d_char_array(self):
a = np.array(['a', 'b', 'c'])
b = np.array(['a', 'b', 's'])
diff --git a/numpy/lib/tests/test_histograms.py b/numpy/lib/tests/test_histograms.py
index 561f5f938..1b5a71d0e 100644
--- a/numpy/lib/tests/test_histograms.py
+++ b/numpy/lib/tests/test_histograms.py
@@ -119,6 +119,13 @@ class TestHistogram(object):
h, b = histogram(a, bins=8, range=[1, 9], weights=w)
assert_equal(h, w[1:-1])
+ def test_arr_weights_mismatch(self):
+ a = np.arange(10) + .5
+ w = np.arange(11) + .5
+ with assert_raises_regex(ValueError, "same shape as"):
+ h, b = histogram(a, range=[1, 9], weights=w, density=True)
+
+
def test_type(self):
# Check the type of the returned histogram
a = np.arange(10) + .5
@@ -141,6 +148,23 @@ class TestHistogram(object):
counts_hist, xedges, yedges = np.histogram2d(x, y, bins=100)
assert_equal(counts_hist.sum(), 3.)
+ def test_bool_conversion(self):
+ # gh-12107
+ # Reference integer histogram
+ a = np.array([1, 1, 0], dtype=np.uint8)
+ int_hist, int_edges = np.histogram(a)
+
+ # Should raise an warning on booleans
+ # Ensure that the histograms are equivalent, need to suppress
+ # the warnings to get the actual outputs
+ with suppress_warnings() as sup:
+ rec = sup.record(RuntimeWarning, 'Converting input from .*')
+ hist, edges = np.histogram([True, True, False])
+ # A warning should be issued
+ assert_equal(len(rec), 1)
+ assert_array_equal(hist, int_hist)
+ assert_array_equal(edges, int_edges)
+
def test_weights(self):
v = np.random.rand(100)
w = np.ones(100) * 5
@@ -225,6 +249,12 @@ class TestHistogram(object):
assert_raises(ValueError, histogram, vals, range=[np.nan,0.75])
assert_raises(ValueError, histogram, vals, range=[0.25,np.inf])
+ def test_invalid_range(self):
+ # start of range must be < end of range
+ vals = np.linspace(0.0, 1.0, num=100)
+ with assert_raises_regex(ValueError, "max must be larger than"):
+ np.histogram(vals, range=[0.1, 0.01])
+
def test_bin_edge_cases(self):
# Ensure that floating-point computations correctly place edge cases.
arr = np.array([337, 404, 739, 806, 1007, 1811, 2012])
@@ -241,6 +271,13 @@ class TestHistogram(object):
hist, edges = np.histogram(arr, bins=30, range=(-0.5, 5))
assert_equal(hist[-1], 1)
+ def test_bin_array_dims(self):
+ # gracefully handle bins object > 1 dimension
+ vals = np.linspace(0.0, 1.0, num=100)
+ bins = np.array([[0, 0.5], [0.6, 1.0]])
+ with assert_raises_regex(ValueError, "must be 1d"):
+ np.histogram(vals, bins=bins)
+
def test_unsigned_monotonicity_check(self):
# Ensures ValueError is raised if bins not increasing monotonically
# when bins contain unsigned values (see #9222)
diff --git a/numpy/lib/tests/test_index_tricks.py b/numpy/lib/tests/test_index_tricks.py
index 33b98629d..76d9b403e 100644
--- a/numpy/lib/tests/test_index_tricks.py
+++ b/numpy/lib/tests/test_index_tricks.py
@@ -5,7 +5,8 @@ import pytest
import numpy as np
from numpy.testing import (
assert_, assert_equal, assert_array_equal, assert_almost_equal,
- assert_array_almost_equal, assert_raises, assert_raises_regex
+ assert_array_almost_equal, assert_raises, assert_raises_regex,
+ assert_warns
)
from numpy.lib.index_tricks import (
mgrid, ogrid, ndenumerate, fill_diagonal, diag_indices, diag_indices_from,
@@ -16,6 +17,33 @@ from numpy.lib.index_tricks import (
class TestRavelUnravelIndex(object):
def test_basic(self):
assert_equal(np.unravel_index(2, (2, 2)), (1, 0))
+
+ # test backwards compatibility with older dims
+ # keyword argument; see Issue #10586
+ with assert_warns(DeprecationWarning):
+ # we should achieve the correct result
+ # AND raise the appropriate warning
+ # when using older "dims" kw argument
+ assert_equal(np.unravel_index(indices=2,
+ dims=(2, 2)),
+ (1, 0))
+
+ # test that new shape argument works properly
+ assert_equal(np.unravel_index(indices=2,
+ shape=(2, 2)),
+ (1, 0))
+
+ # test that an invalid second keyword argument
+ # is properly handled
+ with assert_raises(TypeError):
+ np.unravel_index(indices=2, hape=(2, 2))
+
+ with assert_raises(TypeError):
+ np.unravel_index(2, hape=(2, 2))
+
+ with assert_raises(TypeError):
+ np.unravel_index(254, ims=(17, 94))
+
assert_equal(np.ravel_multi_index((1, 0), (2, 2)), 2)
assert_equal(np.unravel_index(254, (17, 94)), (2, 66))
assert_equal(np.ravel_multi_index((2, 66), (17, 94)), 254)
@@ -336,6 +364,19 @@ class TestFillDiagonal(object):
i = np.array([0, 1, 2])
assert_equal(np.where(a != 0), (i, i, i, i))
+ def test_low_dim_handling(self):
+ # raise error with low dimensionality
+ a = np.zeros(3, int)
+ with assert_raises_regex(ValueError, "at least 2-d"):
+ fill_diagonal(a, 5)
+
+ def test_hetero_shape_handling(self):
+ # raise error with high dimensionality and
+ # shape mismatch
+ a = np.zeros((3,3,7,3), int)
+ with assert_raises_regex(ValueError, "equal length"):
+ fill_diagonal(a, 2)
+
def test_diag_indices():
di = diag_indices(4)
@@ -365,11 +406,23 @@ def test_diag_indices():
)
-def test_diag_indices_from():
- x = np.random.random((4, 4))
- r, c = diag_indices_from(x)
- assert_array_equal(r, np.arange(4))
- assert_array_equal(c, np.arange(4))
+class TestDiagIndicesFrom(object):
+
+ def test_diag_indices_from(self):
+ x = np.random.random((4, 4))
+ r, c = diag_indices_from(x)
+ assert_array_equal(r, np.arange(4))
+ assert_array_equal(c, np.arange(4))
+
+ def test_error_small_input(self):
+ x = np.ones(7)
+ with assert_raises_regex(ValueError, "at least 2-d"):
+ diag_indices_from(x)
+
+ def test_error_shape_mismatch(self):
+ x = np.zeros((3, 3, 2, 3), int)
+ with assert_raises_regex(ValueError, "equal length"):
+ diag_indices_from(x)
def test_ndindex():
diff --git a/numpy/lib/tests/test_utils.py b/numpy/lib/tests/test_utils.py
index c27c3cbf5..2723f3440 100644
--- a/numpy/lib/tests/test_utils.py
+++ b/numpy/lib/tests/test_utils.py
@@ -56,10 +56,34 @@ def test_safe_eval_nameconstant():
utils.safe_eval('None')
-def test_byte_bounds():
- a = arange(12).reshape(3, 4)
- low, high = utils.byte_bounds(a)
- assert_equal(high - low, a.size * a.itemsize)
+class TestByteBounds(object):
+
+ def test_byte_bounds(self):
+ # pointer difference matches size * itemsize
+ # due to contiguity
+ a = arange(12).reshape(3, 4)
+ low, high = utils.byte_bounds(a)
+ assert_equal(high - low, a.size * a.itemsize)
+
+ def test_unusual_order_positive_stride(self):
+ a = arange(12).reshape(3, 4)
+ b = a.T
+ low, high = utils.byte_bounds(b)
+ assert_equal(high - low, b.size * b.itemsize)
+
+ def test_unusual_order_negative_stride(self):
+ a = arange(12).reshape(3, 4)
+ b = a.T[::-1]
+ low, high = utils.byte_bounds(b)
+ assert_equal(high - low, b.size * b.itemsize)
+
+ def test_strided(self):
+ a = arange(12)
+ b = a[::2]
+ low, high = utils.byte_bounds(b)
+ # the largest pointer address is lost (even numbers only in the
+ # stride), and compensate addresses for striding by 2
+ assert_equal(high - low, b.size * 2 * b.itemsize - b.itemsize)
def test_assert_raises_regex_context_manager():
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