diff options
Diffstat (limited to 'numpy/lib')
28 files changed, 426 insertions, 409 deletions
diff --git a/numpy/lib/__init__.py b/numpy/lib/__init__.py index cc05232a2..d764cdc7e 100644 --- a/numpy/lib/__init__.py +++ b/numpy/lib/__init__.py @@ -46,6 +46,6 @@ __all__ += financial.__all__ __all__ += nanfunctions.__all__ __all__ += histograms.__all__ -from numpy.testing import _numpy_tester -test = _numpy_tester().test -bench = _numpy_tester().bench +from numpy.testing._private.pytesttester import PytestTester +test = PytestTester(__name__) +del PytestTester diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index 9ccbfafa2..a4516c276 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -145,7 +145,7 @@ def rot90(m, k=1, axes=(0,1)): return flip(transpose(m, axes_list), axes[1]) -def flip(m, axis): +def flip(m, axis=None): """ Reverse the order of elements in an array along the given axis. @@ -157,9 +157,16 @@ def flip(m, axis): ---------- m : array_like Input array. - axis : integer - Axis in array, which entries are reversed. + axis : None or int or tuple of ints, optional + Axis or axes along which to flip over. The default, + axis=None, will flip over all of the axes of the input array. + If axis is negative it counts from the last to the first axis. + + If axis is a tuple of ints, flipping is performed on all of the axes + specified in the tuple. + .. versionchanged:: 1.15.0 + None and tuples of axes are supported Returns ------- @@ -175,46 +182,60 @@ def flip(m, axis): Notes ----- flip(m, 0) is equivalent to flipud(m). + flip(m, 1) is equivalent to fliplr(m). + flip(m, n) corresponds to ``m[...,::-1,...]`` with ``::-1`` at position n. + flip(m) corresponds to ``m[::-1,::-1,...,::-1]`` with ``::-1`` at all + positions. + + flip(m, (0, 1)) corresponds to ``m[::-1,::-1,...]`` with ``::-1`` at + position 0 and position 1. + Examples -------- >>> A = np.arange(8).reshape((2,2,2)) >>> A array([[[0, 1], [2, 3]], - [[4, 5], [6, 7]]]) - >>> flip(A, 0) array([[[4, 5], [6, 7]], - [[0, 1], [2, 3]]]) - >>> flip(A, 1) array([[[2, 3], [0, 1]], - [[6, 7], [4, 5]]]) - + >>> np.flip(A) + array([[[7, 6], + [5, 4]], + [[3, 2], + [1, 0]]]) + >>> np.flip(A, (0, 2)) + array([[[5, 4], + [7, 6]], + [[1, 0], + [3, 2]]]) >>> A = np.random.randn(3,4,5) >>> np.all(flip(A,2) == A[:,:,::-1,...]) True """ if not hasattr(m, 'ndim'): m = asarray(m) - indexer = [slice(None)] * m.ndim - try: - indexer[axis] = slice(None, None, -1) - except IndexError: - raise ValueError("axis=%i is invalid for the %i-dimensional input array" - % (axis, m.ndim)) - return m[tuple(indexer)] + if axis is None: + indexer = (np.s_[::-1],) * m.ndim + else: + axis = _nx.normalize_axis_tuple(axis, m.ndim) + indexer = [np.s_[:]] * m.ndim + for ax in axis: + indexer[ax] = np.s_[::-1] + indexer = tuple(indexer) + return m[indexer] def iterable(y): diff --git a/numpy/lib/histograms.py b/numpy/lib/histograms.py index aa067a431..d2a398a0a 100644 --- a/numpy/lib/histograms.py +++ b/numpy/lib/histograms.py @@ -10,6 +10,10 @@ from numpy.compat.py3k import basestring __all__ = ['histogram', 'histogramdd', 'histogram_bin_edges'] +# range is a keyword argument to many functions, so save the builtin so they can +# use it. +_range = range + def _hist_bin_sqrt(x): """ @@ -163,12 +167,22 @@ def _hist_bin_fd(x): def _hist_bin_auto(x): """ Histogram bin estimator that uses the minimum width of the - Freedman-Diaconis and Sturges estimators. + Freedman-Diaconis and Sturges estimators if the FD bandwidth is non zero + and the Sturges estimator if the FD bandwidth is 0. The FD estimator is usually the most robust method, but its width - estimate tends to be too large for small `x`. The Sturges estimator - is quite good for small (<1000) datasets and is the default in the R - language. This method gives good off the shelf behaviour. + estimate tends to be too large for small `x` and bad for data with limited + variance. The Sturges estimator is quite good for small (<1000) datasets + and is the default in the R language. This method gives good off the shelf + behaviour. + + .. versionchanged:: 1.15.0 + If there is limited variance the IQR can be 0, which results in the + FD bin width being 0 too. This is not a valid bin width, so + ``np.histogram_bin_edges`` chooses 1 bin instead, which may not be optimal. + If the IQR is 0, it's unlikely any variance based estimators will be of + use, so we revert to the sturges estimator, which only uses the size of the + dataset in its calculation. Parameters ---------- @@ -184,10 +198,13 @@ def _hist_bin_auto(x): -------- _hist_bin_fd, _hist_bin_sturges """ - # There is no need to check for zero here. If ptp is, so is IQR and - # vice versa. Either both are zero or neither one is. - return min(_hist_bin_fd(x), _hist_bin_sturges(x)) - + fd_bw = _hist_bin_fd(x) + sturges_bw = _hist_bin_sturges(x) + if fd_bw: + return min(fd_bw, sturges_bw) + else: + # limited variance, so we return a len dependent bw estimator + return sturges_bw # Private dict initialized at module load time _hist_bin_selectors = {'auto': _hist_bin_auto, @@ -436,7 +453,7 @@ def histogram_bin_edges(a, bins=10, range=None, weights=None): below, :math:`h` is the binwidth and :math:`n_h` is the number of bins. All estimators that compute bin counts are recast to bin width using the `ptp` of the data. The final bin count is obtained from - ``np.round(np.ceil(range / h))`. + ``np.round(np.ceil(range / h))``. 'Auto' (maximum of the 'Sturges' and 'FD' estimators) A compromise to get a good value. For small datasets the Sturges @@ -693,7 +710,7 @@ def histogram(a, bins=10, range=None, normed=False, weights=None, # large arrays, it is actually faster (for example for a 10^8 array it # is 2x as fast) and it results in a memory footprint 3x lower in the # limit of large arrays. - for i in np.arange(0, len(a), BLOCK): + for i in _range(0, len(a), BLOCK): tmp_a = a[i:i+BLOCK] if weights is None: tmp_w = None @@ -741,12 +758,12 @@ def histogram(a, bins=10, range=None, normed=False, weights=None, # Compute via cumulative histogram cum_n = np.zeros(bin_edges.shape, ntype) if weights is None: - for i in np.arange(0, len(a), BLOCK): + for i in _range(0, len(a), BLOCK): sa = np.sort(a[i:i+BLOCK]) cum_n += _search_sorted_inclusive(sa, bin_edges) else: zero = np.zeros(1, dtype=ntype) - for i in np.arange(0, len(a), BLOCK): + for i in _range(0, len(a), BLOCK): tmp_a = a[i:i+BLOCK] tmp_w = weights[i:i+BLOCK] sorting_index = np.argsort(tmp_a) @@ -779,10 +796,18 @@ def histogramdd(sample, bins=10, range=None, normed=False, weights=None): Parameters ---------- - sample : array_like - The data to be histogrammed. It must be an (N,D) array or data - that can be converted to such. The rows of the resulting array - are the coordinates of points in a D dimensional polytope. + sample : (N, D) array, or (D, N) array_like + The data to be histogrammed. + + Note the unusual interpretation of sample when an array_like: + + * When an array, each row is a coordinate in a D-dimensional space - + such as ``histogramgramdd(np.array([p1, p2, p3]))``. + * When an array_like, each element is the list of values for single + coordinate - such as ``histogramgramdd((X, Y, Z))``. + + The first form should be preferred. + bins : sequence or int, optional The bin specification: @@ -791,9 +816,12 @@ def histogramdd(sample, bins=10, range=None, normed=False, weights=None): * The number of bins for all dimensions (nx=ny=...=bins). range : sequence, optional - A sequence of lower and upper bin edges to be used if the edges are - not given explicitly in `bins`. Defaults to the minimum and maximum - values along each dimension. + A sequence of length D, each an optional (lower, upper) tuple giving + the outer bin edges to be used if the edges are not given explicitly in + `bins`. + An entry of None in the sequence results in the minimum and maximum + values being used for the corresponding dimension. + The default, None, is equivalent to passing a tuple of D None values. normed : bool, optional If False, returns the number of samples in each bin. If True, returns the bin density ``bin_count / sample_count / bin_volume``. @@ -849,69 +877,54 @@ def histogramdd(sample, bins=10, range=None, normed=False, weights=None): # bins is an integer bins = D*[bins] - # Select range for each dimension - # Used only if number of bins is given. - if range is None: - # Handle empty input. Range can't be determined in that case, use 0-1. - if N == 0: - smin = np.zeros(D) - smax = np.ones(D) - else: - smin = np.atleast_1d(np.array(sample.min(0), float)) - smax = np.atleast_1d(np.array(sample.max(0), float)) - else: - if not np.all(np.isfinite(range)): - raise ValueError( - 'range parameter must be finite.') - smin = np.zeros(D) - smax = np.zeros(D) - for i in np.arange(D): - smin[i], smax[i] = range[i] - - # Make sure the bins have a finite width. - for i in np.arange(len(smin)): - if smin[i] == smax[i]: - smin[i] = smin[i] - .5 - smax[i] = smax[i] + .5 - # avoid rounding issues for comparisons when dealing with inexact types if np.issubdtype(sample.dtype, np.inexact): edge_dt = sample.dtype else: edge_dt = float + + # normalize the range argument + if range is None: + range = (None,) * D + elif len(range) != D: + raise ValueError('range argument must have one entry per dimension') + # Create edge arrays - for i in np.arange(D): - if np.isscalar(bins[i]): + for i in _range(D): + if np.ndim(bins[i]) == 0: if bins[i] < 1: raise ValueError( - "Element at index %s in `bins` should be a positive " - "integer." % i) - nbin[i] = bins[i] + 2 # +2 for outlier bins - edges[i] = np.linspace(smin[i], smax[i], nbin[i]-1, dtype=edge_dt) - else: + '`bins[{}]` must be positive, when an integer'.format(i)) + smin, smax = _get_outer_edges(sample[:,i], range[i]) + edges[i] = np.linspace(smin, smax, bins[i] + 1, dtype=edge_dt) + elif np.ndim(bins[i]) == 1: edges[i] = np.asarray(bins[i], edge_dt) - nbin[i] = len(edges[i]) + 1 # +1 for outlier bins - dedges[i] = np.diff(edges[i]) - if np.any(np.asarray(dedges[i]) <= 0): + # not just monotonic, due to the use of mindiff below + if np.any(edges[i][:-1] >= edges[i][1:]): + raise ValueError( + '`bins[{}]` must be strictly increasing, when an array' + .format(i)) + else: raise ValueError( - "Found bin edge of size <= 0. Did you specify `bins` with" - "non-monotonic sequence?") + '`bins[{}]` must be a scalar or 1d array'.format(i)) - nbin = np.asarray(nbin) + nbin[i] = len(edges[i]) + 1 # includes an outlier on each end + dedges[i] = np.diff(edges[i]) # Handle empty input. if N == 0: return np.zeros(nbin-2), edges # Compute the bin number each sample falls into. - Ncount = {} - for i in np.arange(D): - Ncount[i] = np.digitize(sample[:, i], edges[i]) + Ncount = tuple( + np.digitize(sample[:, i], edges[i]) + for i in _range(D) + ) # Using digitize, values that fall on an edge are put in the right bin. # For the rightmost bin, we want values equal to the right edge to be # counted in the last bin, and not as an outlier. - for i in np.arange(D): + for i in _range(D): # Rounding precision mindiff = dedges[i].min() if not np.isinf(mindiff): @@ -921,35 +934,21 @@ def histogramdd(sample, bins=10, range=None, normed=False, weights=None): on_edge = (np.around(sample[:, i], decimal) == np.around(edges[i][-1], decimal)) # Shift these points one bin to the left. - Ncount[i][np.nonzero(on_edge & not_smaller_than_edge)[0]] -= 1 - - # Flattened histogram matrix (1D) - # Reshape is used so that overlarge arrays - # will raise an error. - hist = np.zeros(nbin, float).reshape(-1) + Ncount[i][on_edge & not_smaller_than_edge] -= 1 # Compute the sample indices in the flattened histogram matrix. - ni = nbin.argsort() - xy = np.zeros(N, int) - for i in np.arange(0, D-1): - xy += Ncount[ni[i]] * nbin[ni[i+1:]].prod() - xy += Ncount[ni[-1]] + # This raises an error if the array is too large. + xy = np.ravel_multi_index(Ncount, nbin) # Compute the number of repetitions in xy and assign it to the # flattened histmat. - if len(xy) == 0: - return np.zeros(nbin-2, int), edges - - flatcount = np.bincount(xy, weights) - a = np.arange(len(flatcount)) - hist[a] = flatcount + hist = np.bincount(xy, weights, minlength=nbin.prod()) # Shape into a proper matrix - hist = hist.reshape(np.sort(nbin)) - for i in np.arange(nbin.size): - j = ni.argsort()[i] - hist = hist.swapaxes(i, j) - ni[i], ni[j] = ni[j], ni[i] + hist = hist.reshape(nbin) + + # This preserves the (bad) behavior observed in gh-7845, for now. + hist = hist.astype(float, casting='safe') # Remove outliers (indices 0 and -1 for each dimension). core = D*(slice(1, -1),) @@ -958,7 +957,7 @@ def histogramdd(sample, bins=10, range=None, normed=False, weights=None): # Normalize if normed is True if normed: s = hist.sum() - for i in np.arange(D): + for i in _range(D): shape = np.ones(D, int) shape[i] = nbin[i] - 2 hist = hist / dedges[i].reshape(shape) diff --git a/numpy/lib/npyio.py b/numpy/lib/npyio.py index 0f338d781..29688f73d 100644 --- a/numpy/lib/npyio.py +++ b/numpy/lib/npyio.py @@ -758,7 +758,7 @@ def _getconv(dtype): elif issubclass(typ, np.floating): return floatconv elif issubclass(typ, complex): - return lambda x: complex(asstr(x)) + return lambda x: complex(asstr(x).replace('+-', '-')) elif issubclass(typ, np.bytes_): return asbytes elif issubclass(typ, np.unicode_): @@ -1377,7 +1377,8 @@ def savetxt(fname, X, fmt='%.18e', delimiter=' ', newline='\n', header='', for number in row: row2.append(number.real) row2.append(number.imag) - fh.write(format % tuple(row2) + newline) + s = format % tuple(row2) + newline + fh.write(s.replace('+-', '-')) else: for row in X: try: @@ -1719,7 +1720,7 @@ def genfromtxt(fname, dtype=float, comments='#', delimiter=None, try: while not first_values: first_line = _decode_line(next(fhd), encoding) - if names is True: + if (names is True) and (comments is not None): if comments in first_line: first_line = ( ''.join(first_line.split(comments)[1:])) @@ -1733,8 +1734,9 @@ def genfromtxt(fname, dtype=float, comments='#', delimiter=None, # Should we take the first values as names ? if names is True: fval = first_values[0].strip() - if fval in comments: - del first_values[0] + if comments is not None: + if fval in comments: + del first_values[0] # Check the columns to use: make sure `usecols` is a list if usecols is not None: diff --git a/numpy/lib/tests/test__datasource.py b/numpy/lib/tests/test__datasource.py index a9cb157f3..32812990c 100644 --- a/numpy/lib/tests/test__datasource.py +++ b/numpy/lib/tests/test__datasource.py @@ -5,9 +5,7 @@ import sys from tempfile import mkdtemp, mkstemp, NamedTemporaryFile from shutil import rmtree -from numpy.testing import ( - run_module_suite, assert_, assert_equal, assert_raises, SkipTest, - ) +from numpy.testing import assert_, assert_equal, assert_raises, SkipTest import numpy.lib._datasource as datasource if sys.version_info[0] >= 3: @@ -342,7 +340,3 @@ class TestOpenFunc(object): fp = datasource.open(local_file) assert_(fp) fp.close() - - -if __name__ == "__main__": - run_module_suite() diff --git a/numpy/lib/tests/test__iotools.py b/numpy/lib/tests/test__iotools.py index 54fac8da4..5f6c29a4d 100644 --- a/numpy/lib/tests/test__iotools.py +++ b/numpy/lib/tests/test__iotools.py @@ -6,7 +6,7 @@ from datetime import date import numpy as np from numpy.testing import ( - run_module_suite, assert_, assert_equal, assert_allclose, assert_raises, + assert_, assert_equal, assert_allclose, assert_raises, ) from numpy.lib._iotools import ( LineSplitter, NameValidator, StringConverter, @@ -346,6 +346,3 @@ class TestMiscFunctions(object): dt = np.dtype([(("a", "A"), "f8"), (("b", "B"), "f8")]) dt_flat = flatten_dtype(dt) assert_equal(dt_flat, [float, float]) - -if __name__ == "__main__": - run_module_suite() diff --git a/numpy/lib/tests/test__version.py b/numpy/lib/tests/test__version.py index 993c9d507..8e66a0c03 100644 --- a/numpy/lib/tests/test__version.py +++ b/numpy/lib/tests/test__version.py @@ -3,7 +3,7 @@ """ from __future__ import division, absolute_import, print_function -from numpy.testing import assert_, run_module_suite, assert_raises +from numpy.testing import assert_, assert_raises from numpy.lib import NumpyVersion @@ -64,7 +64,3 @@ def test_dev0_a_b_rc_mixed(): def test_raises(): for ver in ['1.9', '1,9.0', '1.7.x']: assert_raises(ValueError, NumpyVersion, ver) - - -if __name__ == "__main__": - run_module_suite() diff --git a/numpy/lib/tests/test_arraypad.py b/numpy/lib/tests/test_arraypad.py index fce4c451d..8be49ce67 100644 --- a/numpy/lib/tests/test_arraypad.py +++ b/numpy/lib/tests/test_arraypad.py @@ -1090,7 +1090,3 @@ class TestTypeError1(object): kwargs = dict(mode='mean', stat_length=(3, )) assert_raises(TypeError, pad, arr, ((2, 3, 4), (3, 2)), **kwargs) - - -if __name__ == "__main__": - np.testing.run_module_suite() diff --git a/numpy/lib/tests/test_arraysetops.py b/numpy/lib/tests/test_arraysetops.py index 8286834a4..76c36c53e 100644 --- a/numpy/lib/tests/test_arraysetops.py +++ b/numpy/lib/tests/test_arraysetops.py @@ -6,9 +6,7 @@ from __future__ import division, absolute_import, print_function import numpy as np import sys -from numpy.testing import ( - run_module_suite, assert_array_equal, assert_equal, assert_raises, - ) +from numpy.testing import assert_array_equal, assert_equal, assert_raises from numpy.lib.arraysetops import ( ediff1d, intersect1d, setxor1d, union1d, setdiff1d, unique, in1d, isin ) @@ -504,7 +502,3 @@ class TestUnique(object): assert_array_equal(uniq[:, inv], data) msg = "Unique's return_counts=True failed with axis=1" assert_array_equal(cnt, np.array([2, 1, 1]), msg) - - -if __name__ == "__main__": - run_module_suite() diff --git a/numpy/lib/tests/test_arrayterator.py b/numpy/lib/tests/test_arrayterator.py index 64ad7f4de..2ce4456a5 100644 --- a/numpy/lib/tests/test_arrayterator.py +++ b/numpy/lib/tests/test_arrayterator.py @@ -46,7 +46,3 @@ def test(): # Check that all elements are iterated correctly assert_(list(c.flat) == list(d.flat)) - -if __name__ == '__main__': - from numpy.testing import run_module_suite - run_module_suite() diff --git a/numpy/lib/tests/test_financial.py b/numpy/lib/tests/test_financial.py index c5e92dbc0..524915041 100644 --- a/numpy/lib/tests/test_financial.py +++ b/numpy/lib/tests/test_financial.py @@ -4,9 +4,8 @@ from decimal import Decimal import numpy as np from numpy.testing import ( - run_module_suite, assert_, assert_almost_equal, assert_allclose, - assert_equal, assert_raises -) + assert_, assert_almost_equal, assert_allclose, assert_equal, assert_raises + ) class TestFinancial(object): @@ -339,7 +338,3 @@ class TestFinancial(object): Decimal('0'), [Decimal('0'), Decimal('0'), Decimal('1'), 'end', 'begin']), [Decimal('-74.998201'), Decimal('-75.62318601'), Decimal('-75.62318601'), Decimal('-76.88882405'), Decimal('-76.88882405')], 4) - - -if __name__ == "__main__": - run_module_suite() diff --git a/numpy/lib/tests/test_format.py b/numpy/lib/tests/test_format.py index d3bd2cef7..38a9b8000 100644 --- a/numpy/lib/tests/test_format.py +++ b/numpy/lib/tests/test_format.py @@ -1,5 +1,6 @@ from __future__ import division, absolute_import, print_function +# doctest r''' Test the .npy file format. Set up: @@ -275,18 +276,17 @@ Test the header writing. "v\x00{'descr': [('x', '>i4', (2,)), ('y', '>f8', (2, 2)), ('z', '|u1')],\n 'fortran_order': False,\n 'shape': (2,)} \n" "\x16\x02{'descr': [('x', '>i4', (2,)),\n ('Info',\n [('value', '>c16'),\n ('y2', '>f8'),\n ('Info2',\n [('name', '|S2'),\n ('value', '>c16', (2,)),\n ('y3', '>f8', (2,)),\n ('z3', '>u4', (2,))]),\n ('name', '|S2'),\n ('z2', '|b1')]),\n ('color', '|S2'),\n ('info', [('Name', '>U8'), ('Value', '>c16')]),\n ('y', '>f8', (2, 2)),\n ('z', '|u1')],\n 'fortran_order': False,\n 'shape': (2,)} \n" ''' - import sys import os import shutil import tempfile import warnings +import pytest from io import BytesIO import numpy as np from numpy.testing import ( - run_module_suite, assert_, assert_array_equal, assert_raises, raises, - dec, SkipTest + assert_, assert_array_equal, assert_raises, raises, SkipTest ) from numpy.lib import format @@ -477,7 +477,7 @@ def test_long_str(): assert_array_equal(long_str_arr, long_str_arr2) -@dec.slow +@pytest.mark.slow def test_memmap_roundtrip(): # Fixme: test crashes nose on windows. if not (sys.platform == 'win32' or sys.platform == 'cygwin'): @@ -628,7 +628,7 @@ def test_version_2_0(): assert_raises(ValueError, format.write_array, f, d, (1, 0)) -@dec.slow +@pytest.mark.slow def test_version_2_0_memmap(): # requires more than 2 byte for header dt = [(("%d" % i) * 100, float) for i in range(500)] @@ -832,8 +832,9 @@ def test_large_file_support(): assert_array_equal(r, d) -@dec.slow -@dec.skipif(np.dtype(np.intp).itemsize < 8, "test requires 64-bit system") +@pytest.mark.skipif(np.dtype(np.intp).itemsize < 8, + reason="test requires 64-bit system") +@pytest.mark.slow def test_large_archive(): # Regression test for product of saving arrays with dimensions of array # having a product that doesn't fit in int32. See gh-7598 for details. @@ -851,7 +852,3 @@ def test_large_archive(): new_a = np.load(f)["arr"] assert_(a.shape == new_a.shape) - - -if __name__ == "__main__": - run_module_suite() diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py index c28257c6d..6653b5ba1 100644 --- a/numpy/lib/tests/test_function_base.py +++ b/numpy/lib/tests/test_function_base.py @@ -4,15 +4,16 @@ import operator import warnings import sys import decimal +import pytest import numpy as np from numpy import ma from numpy.testing import ( - run_module_suite, assert_, assert_equal, assert_array_equal, - assert_almost_equal, assert_array_almost_equal, assert_raises, - assert_allclose, assert_array_max_ulp, assert_warns, assert_raises_regex, - dec, suppress_warnings, -) + assert_, assert_equal, assert_array_equal, assert_almost_equal, + assert_array_almost_equal, assert_raises, assert_allclose, + assert_array_max_ulp, assert_warns, assert_raises_regex, suppress_warnings, + HAS_REFCOUNT, + ) import numpy.lib.function_base as nfb from numpy.random import rand from numpy.lib import ( @@ -21,7 +22,7 @@ from numpy.lib import ( histogram, histogramdd, i0, insert, interp, kaiser, meshgrid, msort, piecewise, place, rot90, select, setxor1d, sinc, split, trapz, trim_zeros, unwrap, unique, vectorize -) + ) from numpy.compat import long @@ -103,9 +104,10 @@ class TestRot90(object): class TestFlip(object): def test_axes(self): - assert_raises(ValueError, np.flip, np.ones(4), axis=1) - assert_raises(ValueError, np.flip, np.ones((4, 4)), axis=2) - assert_raises(ValueError, np.flip, np.ones((4, 4)), axis=-3) + assert_raises(np.AxisError, np.flip, np.ones(4), axis=1) + assert_raises(np.AxisError, np.flip, np.ones((4, 4)), axis=2) + assert_raises(np.AxisError, np.flip, np.ones((4, 4)), axis=-3) + assert_raises(np.AxisError, np.flip, np.ones((4, 4)), axis=(0, 3)) def test_basic_lr(self): a = get_mat(4) @@ -172,6 +174,35 @@ class TestFlip(object): assert_equal(np.flip(a, i), np.flipud(a.swapaxes(0, i)).swapaxes(i, 0)) + def test_default_axis(self): + a = np.array([[1, 2, 3], + [4, 5, 6]]) + b = np.array([[6, 5, 4], + [3, 2, 1]]) + assert_equal(np.flip(a), b) + + def test_multiple_axes(self): + a = np.array([[[0, 1], + [2, 3]], + [[4, 5], + [6, 7]]]) + + assert_equal(np.flip(a, axis=()), a) + + b = np.array([[[5, 4], + [7, 6]], + [[1, 0], + [3, 2]]]) + + assert_equal(np.flip(a, axis=(0, 2)), b) + + c = np.array([[[3, 2], + [1, 0]], + [[7, 6], + [5, 4]]]) + + assert_equal(np.flip(a, axis=(1, 2)), c) + class TestAny(object): @@ -2143,7 +2174,7 @@ class TestBincount(object): "must not be negative", lambda: np.bincount(x, minlength=-1)) - @dec._needs_refcount + @pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts") def test_dtype_reference_leaks(self): # gh-6805 intp_refcount = sys.getrefcount(np.dtype(np.intp)) @@ -2987,14 +3018,10 @@ class TestAdd_newdoc_ufunc(object): class TestAdd_newdoc(object): - @dec.skipif(sys.flags.optimize == 2) + @pytest.mark.skipif(sys.flags.optimize == 2, reason="Python running -OO") def test_add_doc(self): # test np.add_newdoc tgt = "Current flat index into the array." assert_equal(np.core.flatiter.index.__doc__[:len(tgt)], tgt) assert_(len(np.core.ufunc.identity.__doc__) > 300) assert_(len(np.lib.index_tricks.mgrid.__doc__) > 300) - - -if __name__ == "__main__": - run_module_suite() diff --git a/numpy/lib/tests/test_histograms.py b/numpy/lib/tests/test_histograms.py index 4f7af214c..06daacbdc 100644 --- a/numpy/lib/tests/test_histograms.py +++ b/numpy/lib/tests/test_histograms.py @@ -4,11 +4,10 @@ import numpy as np from numpy.lib.histograms import histogram, histogramdd, histogram_bin_edges from numpy.testing import ( - run_module_suite, assert_, assert_equal, assert_array_equal, - assert_almost_equal, assert_array_almost_equal, assert_raises, - assert_allclose, assert_array_max_ulp, assert_warns, assert_raises_regex, - dec, suppress_warnings, HAS_REFCOUNT, -) + assert_, assert_equal, assert_array_equal, assert_almost_equal, + assert_array_almost_equal, assert_raises, assert_allclose, + assert_array_max_ulp, assert_warns, assert_raises_regex, suppress_warnings, + ) class TestHistogram(object): @@ -444,6 +443,24 @@ class TestHistogramOptimBinNums(object): assert_equal(len(a), numbins, err_msg="{0} estimator, " "No Variance test".format(estimator)) + def test_limited_variance(self): + """ + Check when IQR is 0, but variance exists, we return the sturges value + and not the fd value. + """ + lim_var_data = np.ones(1000) + lim_var_data[:3] = 0 + lim_var_data[-4:] = 100 + + edges_auto = histogram_bin_edges(lim_var_data, 'auto') + assert_equal(edges_auto, np.linspace(0, 100, 12)) + + edges_fd = histogram_bin_edges(lim_var_data, 'fd') + assert_equal(edges_fd, np.array([0, 100])) + + edges_sturges = histogram_bin_edges(lim_var_data, 'sturges') + assert_equal(edges_sturges, np.linspace(0, 100, 12)) + def test_outlier(self): """ Check the FD, Scott and Doane with outliers. @@ -643,7 +660,3 @@ class TestHistogramdd(object): range=[[0.0, 1.0], [0.25, 0.75], [0.25, np.inf]]) assert_raises(ValueError, histogramdd, vals, range=[[0.0, 1.0], [np.nan, 0.75], [0.25, 0.5]]) - - -if __name__ == "__main__": - run_module_suite() diff --git a/numpy/lib/tests/test_index_tricks.py b/numpy/lib/tests/test_index_tricks.py index 0520ce580..f934e952a 100644 --- a/numpy/lib/tests/test_index_tricks.py +++ b/numpy/lib/tests/test_index_tricks.py @@ -2,9 +2,8 @@ from __future__ import division, absolute_import, print_function import numpy as np from numpy.testing import ( - run_module_suite, assert_, assert_equal, assert_array_equal, - assert_almost_equal, assert_array_almost_equal, assert_raises, - assert_raises_regex + assert_, assert_equal, assert_array_equal, assert_almost_equal, + assert_array_almost_equal, assert_raises, assert_raises_regex ) from numpy.lib.index_tricks import ( mgrid, ndenumerate, fill_diagonal, diag_indices, diag_indices_from, @@ -285,71 +284,77 @@ def test_c_(): assert_equal(a, [[1, 2, 3, 0, 0, 4, 5, 6]]) -def test_fill_diagonal(): - a = np.zeros((3, 3), int) - fill_diagonal(a, 5) - yield (assert_array_equal, a, - np.array([[5, 0, 0], - [0, 5, 0], - [0, 0, 5]])) - - #Test tall matrix - a = np.zeros((10, 3), int) - fill_diagonal(a, 5) - yield (assert_array_equal, a, - np.array([[5, 0, 0], - [0, 5, 0], - [0, 0, 5], - [0, 0, 0], - [0, 0, 0], - [0, 0, 0], - [0, 0, 0], - [0, 0, 0], - [0, 0, 0], - [0, 0, 0]])) - - #Test tall matrix wrap - a = np.zeros((10, 3), int) - fill_diagonal(a, 5, True) - yield (assert_array_equal, a, - np.array([[5, 0, 0], - [0, 5, 0], - [0, 0, 5], - [0, 0, 0], - [5, 0, 0], - [0, 5, 0], - [0, 0, 5], - [0, 0, 0], - [5, 0, 0], - [0, 5, 0]])) - - #Test wide matrix - a = np.zeros((3, 10), int) - fill_diagonal(a, 5) - yield (assert_array_equal, a, - np.array([[5, 0, 0, 0, 0, 0, 0, 0, 0, 0], - [0, 5, 0, 0, 0, 0, 0, 0, 0, 0], - [0, 0, 5, 0, 0, 0, 0, 0, 0, 0]])) - - # The same function can operate on a 4-d array: - a = np.zeros((3, 3, 3, 3), int) - fill_diagonal(a, 4) - i = np.array([0, 1, 2]) - yield (assert_equal, np.where(a != 0), (i, i, i, i)) +class TestFillDiagonal(object): + def test_basic(self): + a = np.zeros((3, 3), int) + fill_diagonal(a, 5) + assert_array_equal( + a, np.array([[5, 0, 0], + [0, 5, 0], + [0, 0, 5]]) + ) + + def test_tall_matrix(self): + a = np.zeros((10, 3), int) + fill_diagonal(a, 5) + assert_array_equal( + a, np.array([[5, 0, 0], + [0, 5, 0], + [0, 0, 5], + [0, 0, 0], + [0, 0, 0], + [0, 0, 0], + [0, 0, 0], + [0, 0, 0], + [0, 0, 0], + [0, 0, 0]]) + ) + + def test_tall_matrix_wrap(self): + a = np.zeros((10, 3), int) + fill_diagonal(a, 5, True) + assert_array_equal( + a, np.array([[5, 0, 0], + [0, 5, 0], + [0, 0, 5], + [0, 0, 0], + [5, 0, 0], + [0, 5, 0], + [0, 0, 5], + [0, 0, 0], + [5, 0, 0], + [0, 5, 0]]) + ) + + def test_wide_matrix(self): + a = np.zeros((3, 10), int) + fill_diagonal(a, 5) + assert_array_equal( + a, np.array([[5, 0, 0, 0, 0, 0, 0, 0, 0, 0], + [0, 5, 0, 0, 0, 0, 0, 0, 0, 0], + [0, 0, 5, 0, 0, 0, 0, 0, 0, 0]]) + ) + + def test_operate_4d_array(self): + a = np.zeros((3, 3, 3, 3), int) + fill_diagonal(a, 4) + i = np.array([0, 1, 2]) + assert_equal(np.where(a != 0), (i, i, i, i)) def test_diag_indices(): di = diag_indices(4) a = np.array([[1, 2, 3, 4], - [5, 6, 7, 8], - [9, 10, 11, 12], - [13, 14, 15, 16]]) + [5, 6, 7, 8], + [9, 10, 11, 12], + [13, 14, 15, 16]]) a[di] = 100 - yield (assert_array_equal, a, - np.array([[100, 2, 3, 4], - [5, 100, 7, 8], - [9, 10, 100, 12], - [13, 14, 15, 100]])) + assert_array_equal( + a, np.array([[100, 2, 3, 4], + [5, 100, 7, 8], + [9, 10, 100, 12], + [13, 14, 15, 100]]) + ) # Now, we create indices to manipulate a 3-d array: d3 = diag_indices(2, 3) @@ -357,12 +362,12 @@ def test_diag_indices(): # And use it to set the diagonal of a zeros array to 1: a = np.zeros((2, 2, 2), int) a[d3] = 1 - yield (assert_array_equal, a, - np.array([[[1, 0], - [0, 0]], - - [[0, 0], - [0, 1]]])) + assert_array_equal( + a, np.array([[[1, 0], + [0, 0]], + [[0, 0], + [0, 1]]]) + ) def test_diag_indices_from(): @@ -394,7 +399,3 @@ def test_ndindex(): # Make sure 0-sized ndindex works correctly x = list(ndindex(*[0])) assert_equal(x, []) - - -if __name__ == "__main__": - run_module_suite() diff --git a/numpy/lib/tests/test_io.py b/numpy/lib/tests/test_io.py index a0f256726..84aca9915 100644 --- a/numpy/lib/tests/test_io.py +++ b/numpy/lib/tests/test_io.py @@ -4,15 +4,16 @@ import sys import gzip import os import threading -from tempfile import NamedTemporaryFile import time import warnings import gc import io +import re +import pytest +from tempfile import NamedTemporaryFile from io import BytesIO, StringIO from datetime import datetime import locale -import re import numpy as np import numpy.ma as ma @@ -20,10 +21,10 @@ from numpy.lib._iotools import ConverterError, ConversionWarning from numpy.compat import asbytes, bytes, unicode, Path from numpy.ma.testutils import assert_equal from numpy.testing import ( - run_module_suite, assert_warns, assert_, SkipTest, - assert_raises_regex, assert_raises, assert_allclose, - assert_array_equal, temppath, tempdir, dec, IS_PYPY, suppress_warnings, -) + assert_warns, assert_, SkipTest, assert_raises_regex, assert_raises, + assert_allclose, assert_array_equal, temppath, tempdir, IS_PYPY, + HAS_REFCOUNT, suppress_warnings, + ) class TextIO(BytesIO): @@ -156,7 +157,7 @@ class RoundtripTest(object): a = np.array([1, 2, 3, 4], int) self.roundtrip(a) - @dec.knownfailureif(sys.platform == 'win32', "Fail on Win32") + @pytest.mark.skipif(sys.platform == 'win32', reason="Fails on Win32") def test_mmap(self): a = np.array([[1, 2.5], [4, 7.3]]) self.roundtrip(a, file_on_disk=True, load_kwds={'mmap_mode': 'r'}) @@ -168,7 +169,7 @@ class RoundtripTest(object): a = np.array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')]) self.check_roundtrips(a) - @dec.slow + @pytest.mark.slow def test_format_2_0(self): dt = [(("%d" % i) * 100, float) for i in range(500)] a = np.ones(1000, dtype=dt) @@ -200,8 +201,8 @@ class TestSavezLoad(RoundtripTest): self.arr_reloaded.fid.close() os.remove(self.arr_reloaded.fid.name) - @dec.skipif(not IS_64BIT, "Works only with 64bit systems") - @dec.slow + @pytest.mark.skipif(not IS_64BIT, reason="Needs 64bit platform") + @pytest.mark.slow def test_big_arrays(self): L = (1 << 31) + 100000 a = np.empty(L, dtype=np.uint8) @@ -277,7 +278,8 @@ class TestSavezLoad(RoundtripTest): fp.seek(0) assert_(not fp.closed) - @dec.skipif(IS_PYPY, "context manager required on PyPy") + #FIXME: Is this still true? + @pytest.mark.skipif(IS_PYPY, reason="Missing context manager on PyPy") def test_closing_fid(self): # Test that issue #1517 (too many opened files) remains closed # It might be a "weak" test since failed to get triggered on @@ -466,6 +468,26 @@ class TestSaveTxt(object): [b'(3.142e+00+2.718e+00j) (3.142e+00+2.718e+00j)\n', b'(3.142e+00+2.718e+00j) (3.142e+00+2.718e+00j)\n']) + def test_complex_negative_exponent(self): + # Previous to 1.15, some formats generated x+-yj, gh 7895 + ncols = 2 + nrows = 2 + a = np.zeros((ncols, nrows), dtype=np.complex128) + re = np.pi + im = np.e + a[:] = re - 1.0j * im + c = BytesIO() + np.savetxt(c, a, fmt='%.3e') + c.seek(0) + lines = c.readlines() + assert_equal( + lines, + [b' (3.142e+00-2.718e+00j) (3.142e+00-2.718e+00j)\n', + b' (3.142e+00-2.718e+00j) (3.142e+00-2.718e+00j)\n']) + + + + def test_custom_writer(self): class CustomWriter(list): @@ -540,15 +562,17 @@ class LoadTxtBase(object): assert_array_equal(res, wanted) # Python2 .open does not support encoding - @dec.skipif(MAJVER == 2) + @pytest.mark.skipif(MAJVER == 2, reason="Needs Python version >= 3") def test_compressed_gzip(self): self.check_compressed(gzip.open, ('.gz',)) - @dec.skipif(MAJVER == 2 or not HAS_BZ2) + @pytest.mark.skipif(not HAS_BZ2, reason="Needs bz2") + @pytest.mark.skipif(MAJVER == 2, reason="Needs Python version >= 3") def test_compressed_gzip(self): self.check_compressed(bz2.open, ('.bz2',)) - @dec.skipif(MAJVER == 2 or not HAS_LZMA) + @pytest.mark.skipif(not HAS_LZMA, reason="Needs lzma") + @pytest.mark.skipif(MAJVER == 2, reason="Needs Python version >= 3") def test_compressed_gzip(self): self.check_compressed(lzma.open, ('.xz', '.lzma')) @@ -599,11 +623,11 @@ class LoadTxtBase(object): class TestLoadTxt(LoadTxtBase): loadfunc = staticmethod(np.loadtxt) - def setUp(self): + def setup(self): # lower chunksize for testing self.orig_chunk = np.lib.npyio._loadtxt_chunksize np.lib.npyio._loadtxt_chunksize = 1 - def tearDown(self): + def teardown(self): np.lib.npyio._loadtxt_chunksize = self.orig_chunk def test_record(self): @@ -912,6 +936,26 @@ class TestLoadTxt(LoadTxtBase): res = np.loadtxt(c, dtype=complex) assert_equal(res, tgt) + def test_complex_misformatted(self): + # test for backward compatability + # some complex formats used to generate x+-yj + a = np.zeros((2, 2), dtype=np.complex128) + re = np.pi + im = np.e + a[:] = re - 1.0j * im + c = BytesIO() + np.savetxt(c, a, fmt='%.16e') + c.seek(0) + txt = c.read() + c.seek(0) + # misformat the sign on the imaginary part, gh 7895 + txt_bad = txt.replace(b'e+00-', b'e00+-') + assert_(txt_bad != txt) + c.write(txt_bad) + c.seek(0) + res = np.loadtxt(c, dtype=complex) + assert_equal(res, a) + def test_universal_newline(self): with temppath() as name: with open(name, 'w') as f: @@ -1007,7 +1051,8 @@ class TestLoadTxt(LoadTxtBase): dt = np.dtype([('x', int), ('a', 'S10'), ('y', int)]) np.loadtxt(c, delimiter=',', dtype=dt, comments=None) # Should succeed - @dec.skipif(locale.getpreferredencoding() == 'ANSI_X3.4-1968') + @pytest.mark.skipif(locale.getpreferredencoding() == 'ANSI_X3.4-1968', + reason="Wrong preferred encoding") def test_binary_load(self): butf8 = b"5,6,7,\xc3\x95scarscar\n\r15,2,3,hello\n\r"\ b"20,2,3,\xc3\x95scar\n\r" @@ -1272,6 +1317,13 @@ M 33 21.99 assert_(w[0].category is np.VisibleDeprecationWarning) assert_equal(test, ctrl) + def test_names_and_comments_none(self): + # Tests case when names is true but comments is None (gh-10780) + data = TextIO('col1 col2\n 1 2\n 3 4') + test = np.genfromtxt(data, dtype=(int, int), comments=None, names=True) + control = np.array([(1, 2), (3, 4)], dtype=[('col1', int), ('col2', int)]) + assert_equal(test, control) + def test_autonames_and_usecols(self): # Tests names and usecols data = TextIO('A B C D\n aaaa 121 45 9.1') @@ -1984,7 +2036,6 @@ M 33 21.99 # encoding of io.open. Will need to change this for PyTest, maybe # using pytest.mark.xfail(raises=***). try: - import locale encoding = locale.getpreferredencoding() utf8.encode(encoding) except (UnicodeError, ImportError): @@ -2189,9 +2240,9 @@ M 33 21.99 assert_equal(test['f2'], 1024) +@pytest.mark.skipif(Path is None, reason="No pathlib.Path") class TestPathUsage(object): # Test that pathlib.Path can be used - @dec.skipif(Path is None, "No pathlib.Path") def test_loadtxt(self): with temppath(suffix='.txt') as path: path = Path(path) @@ -2200,7 +2251,6 @@ class TestPathUsage(object): x = np.loadtxt(path) assert_array_equal(x, a) - @dec.skipif(Path is None, "No pathlib.Path") def test_save_load(self): # Test that pathlib.Path instances can be used with savez. with temppath(suffix='.npy') as path: @@ -2210,7 +2260,6 @@ class TestPathUsage(object): data = np.load(path) assert_array_equal(data, a) - @dec.skipif(Path is None, "No pathlib.Path") def test_savez_load(self): # Test that pathlib.Path instances can be used with savez. with temppath(suffix='.npz') as path: @@ -2218,8 +2267,7 @@ class TestPathUsage(object): np.savez(path, lab='place holder') with np.load(path) as data: assert_array_equal(data['lab'], 'place holder') - - @dec.skipif(Path is None, "No pathlib.Path") + def test_savez_compressed_load(self): # Test that pathlib.Path instances can be used with savez. with temppath(suffix='.npz') as path: @@ -2229,7 +2277,6 @@ class TestPathUsage(object): assert_array_equal(data['lab'], 'place holder') data.close() - @dec.skipif(Path is None, "No pathlib.Path") def test_genfromtxt(self): with temppath(suffix='.txt') as path: path = Path(path) @@ -2238,7 +2285,6 @@ class TestPathUsage(object): data = np.genfromtxt(path) assert_array_equal(a, data) - @dec.skipif(Path is None, "No pathlib.Path") def test_ndfromtxt(self): # Test outputting a standard ndarray with temppath(suffix='.txt') as path: @@ -2250,7 +2296,6 @@ class TestPathUsage(object): test = np.ndfromtxt(path, dtype=int) assert_array_equal(test, control) - @dec.skipif(Path is None, "No pathlib.Path") def test_mafromtxt(self): # From `test_fancy_dtype_alt` above with temppath(suffix='.txt') as path: @@ -2262,7 +2307,6 @@ class TestPathUsage(object): control = ma.array([(1.0, 2.0, 3.0), (4.0, 5.0, 6.0)]) assert_equal(test, control) - @dec.skipif(Path is None, "No pathlib.Path") def test_recfromtxt(self): with temppath(suffix='.txt') as path: path = Path(path) @@ -2276,7 +2320,6 @@ class TestPathUsage(object): assert_(isinstance(test, np.recarray)) assert_equal(test, control) - @dec.skipif(Path is None, "No pathlib.Path") def test_recfromcsv(self): with temppath(suffix='.txt') as path: path = Path(path) @@ -2364,7 +2407,7 @@ def test_npzfile_dict(): assert_('x' in z.keys()) -@dec._needs_refcount +@pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts") def test_load_refcount(): # Check that objects returned by np.load are directly freed based on # their refcount, rather than needing the gc to collect them. @@ -2384,6 +2427,3 @@ def test_load_refcount(): finally: gc.enable() assert_equal(n_objects_in_cycles, 0) - -if __name__ == "__main__": - run_module_suite() diff --git a/numpy/lib/tests/test_mixins.py b/numpy/lib/tests/test_mixins.py index 94f06c336..f2d915502 100644 --- a/numpy/lib/tests/test_mixins.py +++ b/numpy/lib/tests/test_mixins.py @@ -5,9 +5,7 @@ import operator import sys import numpy as np -from numpy.testing import ( - run_module_suite, assert_, assert_equal, assert_raises - ) +from numpy.testing import assert_, assert_equal, assert_raises PY2 = sys.version_info.major < 3 @@ -213,7 +211,3 @@ class TestNDArrayOperatorsMixin(object): np.frexp(ArrayLike(2 ** -3)), expected) _assert_equal_type_and_value( np.frexp(ArrayLike(np.array(2 ** -3))), expected) - - -if __name__ == "__main__": - run_module_suite() diff --git a/numpy/lib/tests/test_nanfunctions.py b/numpy/lib/tests/test_nanfunctions.py index 3d362fc6e..1f403f7b8 100644 --- a/numpy/lib/tests/test_nanfunctions.py +++ b/numpy/lib/tests/test_nanfunctions.py @@ -4,8 +4,8 @@ import warnings import numpy as np from numpy.testing import ( - run_module_suite, assert_, assert_equal, assert_almost_equal, - assert_no_warnings, assert_raises, assert_array_equal, suppress_warnings + assert_, assert_equal, assert_almost_equal, assert_no_warnings, + assert_raises, assert_array_equal, suppress_warnings ) @@ -886,7 +886,3 @@ class TestNanFunctions_Percentile(object): megamat = np.ones((3, 4, 5, 6)) assert_equal(np.nanpercentile(megamat, perc, axis=(1, 2)).shape, (2, 3, 6)) - - -if __name__ == "__main__": - run_module_suite() diff --git a/numpy/lib/tests/test_packbits.py b/numpy/lib/tests/test_packbits.py index 965cbf67c..fde5c37f2 100644 --- a/numpy/lib/tests/test_packbits.py +++ b/numpy/lib/tests/test_packbits.py @@ -1,9 +1,7 @@ from __future__ import division, absolute_import, print_function import numpy as np -from numpy.testing import ( - assert_array_equal, assert_equal, assert_raises, run_module_suite -) +from numpy.testing import assert_array_equal, assert_equal, assert_raises def test_packbits(): @@ -268,7 +266,3 @@ def test_unpackbits_large(): assert_array_equal(np.packbits(np.unpackbits(d, axis=1), axis=1), d) d = d.T.copy() assert_array_equal(np.packbits(np.unpackbits(d, axis=0), axis=0), d) - - -if __name__ == "__main__": - run_module_suite() diff --git a/numpy/lib/tests/test_polynomial.py b/numpy/lib/tests/test_polynomial.py index 03915cead..7f6fca4a4 100644 --- a/numpy/lib/tests/test_polynomial.py +++ b/numpy/lib/tests/test_polynomial.py @@ -1,15 +1,13 @@ -from __future__ import division, absolute_import, print_function - ''' >>> p = np.poly1d([1.,2,3]) >>> p -poly1d([ 1., 2., 3.]) +poly1d([1., 2., 3.]) >>> print(p) 2 1 x + 2 x + 3 >>> q = np.poly1d([3.,2,1]) >>> q -poly1d([ 3., 2., 1.]) +poly1d([3., 2., 1.]) >>> print(q) 2 3 x + 2 x + 1 @@ -30,23 +28,23 @@ poly1d([ 3., 2., 1.]) 86.0 >>> p * q -poly1d([ 3., 8., 14., 8., 3.]) +poly1d([ 3., 8., 14., 8., 3.]) >>> p / q -(poly1d([ 0.33333333]), poly1d([ 1.33333333, 2.66666667])) +(poly1d([0.33333333]), poly1d([1.33333333, 2.66666667])) >>> p + q -poly1d([ 4., 4., 4.]) +poly1d([4., 4., 4.]) >>> p - q poly1d([-2., 0., 2.]) >>> p ** 4 -poly1d([ 1., 8., 36., 104., 214., 312., 324., 216., 81.]) +poly1d([ 1., 8., 36., 104., 214., 312., 324., 216., 81.]) >>> p(q) -poly1d([ 9., 12., 16., 8., 6.]) +poly1d([ 9., 12., 16., 8., 6.]) >>> q(p) -poly1d([ 3., 12., 32., 40., 34.]) +poly1d([ 3., 12., 32., 40., 34.]) >>> np.asarray(p) -array([ 1., 2., 3.]) +array([1., 2., 3.]) >>> len(p) 2 @@ -54,16 +52,16 @@ array([ 1., 2., 3.]) (3.0, 2.0, 1.0, 0) >>> p.integ() -poly1d([ 0.33333333, 1. , 3. , 0. ]) +poly1d([0.33333333, 1. , 3. , 0. ]) >>> p.integ(1) -poly1d([ 0.33333333, 1. , 3. , 0. ]) +poly1d([0.33333333, 1. , 3. , 0. ]) >>> p.integ(5) -poly1d([ 0.00039683, 0.00277778, 0.025 , 0. , 0. , - 0. , 0. , 0. ]) +poly1d([0.00039683, 0.00277778, 0.025 , 0. , 0. , + 0. , 0. , 0. ]) >>> p.deriv() -poly1d([ 2., 2.]) +poly1d([2., 2.]) >>> p.deriv(2) -poly1d([ 2.]) +poly1d([2.]) >>> q = np.poly1d([1.,2,3], variable='y') >>> print(q) @@ -75,13 +73,15 @@ poly1d([ 2.]) 1 lambda + 2 lambda + 3 >>> np.polydiv(np.poly1d([1,0,-1]), np.poly1d([1,1])) -(poly1d([ 1., -1.]), poly1d([ 0.])) +(poly1d([ 1., -1.]), poly1d([0.])) ''' +from __future__ import division, absolute_import, print_function + import numpy as np from numpy.testing import ( - run_module_suite, assert_, assert_equal, assert_array_equal, - assert_almost_equal, assert_array_almost_equal, assert_raises, rundocs + assert_, assert_equal, assert_array_equal, assert_almost_equal, + assert_array_almost_equal, assert_raises, rundocs ) @@ -243,7 +243,3 @@ class TestDocs(object): p.coeffs[2] += 10 assert_equal(p.coeffs, [1, 2, 3]) - - -if __name__ == "__main__": - run_module_suite() diff --git a/numpy/lib/tests/test_recfunctions.py b/numpy/lib/tests/test_recfunctions.py index bc9f8d7b6..219ae24fa 100644 --- a/numpy/lib/tests/test_recfunctions.py +++ b/numpy/lib/tests/test_recfunctions.py @@ -1,12 +1,12 @@ from __future__ import division, absolute_import, print_function +import pytest + import numpy as np import numpy.ma as ma from numpy.ma.mrecords import MaskedRecords from numpy.ma.testutils import assert_equal -from numpy.testing import ( - run_module_suite, assert_, assert_raises, dec - ) +from numpy.testing import assert_, assert_raises from numpy.lib.recfunctions import ( drop_fields, rename_fields, get_fieldstructure, recursive_fill_fields, find_duplicates, merge_arrays, append_fields, stack_arrays, join_by @@ -687,7 +687,7 @@ class TestJoinBy(object): b = np.ones(3, dtype=[('c', 'u1'), ('b', 'f4'), ('a', 'i4')]) assert_raises(ValueError, join_by, ['a', 'b', 'b'], a, b) - @dec.knownfailureif(True) + @pytest.mark.xfail(reason="See comment at gh-9343") def test_same_name_different_dtypes_key(self): a_dtype = np.dtype([('key', 'S5'), ('value', '<f4')]) b_dtype = np.dtype([('key', 'S10'), ('value', '<f4')]) @@ -829,6 +829,3 @@ class TestAppendFieldsObj(object): control = np.array([(obj, 1.0, 10), (obj, 2.0, 20)], dtype=[('A', object), ('B', float), ('C', int)]) assert_equal(test, control) - -if __name__ == '__main__': - run_module_suite() diff --git a/numpy/lib/tests/test_regression.py b/numpy/lib/tests/test_regression.py index d96d3422d..4c46bc46b 100644 --- a/numpy/lib/tests/test_regression.py +++ b/numpy/lib/tests/test_regression.py @@ -5,8 +5,8 @@ import sys import numpy as np from numpy.testing import ( - run_module_suite, assert_, assert_equal, assert_array_equal, - assert_array_almost_equal, assert_raises, _assert_valid_refcount, + assert_, assert_equal, assert_array_equal, assert_array_almost_equal, + assert_raises, _assert_valid_refcount, ) from numpy.compat import unicode @@ -252,7 +252,3 @@ class TestRegression(object): raise AssertionError() finally: out.close() - - -if __name__ == "__main__": - run_module_suite() diff --git a/numpy/lib/tests/test_shape_base.py b/numpy/lib/tests/test_shape_base.py index d0afeefd9..080fd066d 100644 --- a/numpy/lib/tests/test_shape_base.py +++ b/numpy/lib/tests/test_shape_base.py @@ -8,8 +8,7 @@ from numpy.lib.shape_base import ( vsplit, dstack, column_stack, kron, tile, expand_dims, ) from numpy.testing import ( - run_module_suite, assert_, assert_equal, assert_array_equal, assert_raises, - assert_warns + assert_, assert_equal, assert_array_equal, assert_raises, assert_warns ) @@ -569,7 +568,3 @@ class TestMayShareMemory(object): def compare_results(res, desired): for i in range(len(desired)): assert_array_equal(res[i], desired[i]) - - -if __name__ == "__main__": - run_module_suite() diff --git a/numpy/lib/tests/test_stride_tricks.py b/numpy/lib/tests/test_stride_tricks.py index 0599324d7..3c2ca8b87 100644 --- a/numpy/lib/tests/test_stride_tricks.py +++ b/numpy/lib/tests/test_stride_tricks.py @@ -1,14 +1,13 @@ from __future__ import division, absolute_import, print_function import numpy as np -from numpy.core.test_rational import rational +from numpy.core._rational_tests import rational from numpy.testing import ( - run_module_suite, assert_equal, assert_array_equal, - assert_raises, assert_ + assert_equal, assert_array_equal, assert_raises, assert_ ) from numpy.lib.stride_tricks import ( as_strided, broadcast_arrays, _broadcast_shape, broadcast_to -) + ) def assert_shapes_correct(input_shapes, expected_shape): # Broadcast a list of arrays with the given input shapes and check the @@ -432,7 +431,3 @@ def test_reference_types(): actual, _ = broadcast_arrays(input_array, np.ones(3)) assert_array_equal(expected, actual) - - -if __name__ == "__main__": - run_module_suite() diff --git a/numpy/lib/tests/test_twodim_base.py b/numpy/lib/tests/test_twodim_base.py index 8183f7ca6..d3a072af3 100644 --- a/numpy/lib/tests/test_twodim_base.py +++ b/numpy/lib/tests/test_twodim_base.py @@ -4,14 +4,14 @@ from __future__ import division, absolute_import, print_function from numpy.testing import ( - run_module_suite, assert_equal, assert_array_equal, assert_array_max_ulp, + assert_equal, assert_array_equal, assert_array_max_ulp, assert_array_almost_equal, assert_raises, ) from numpy import ( - arange, add, fliplr, flipud, zeros, ones, eye, array, diag, - histogram2d, tri, mask_indices, triu_indices, triu_indices_from, - tril_indices, tril_indices_from, vander, + arange, add, fliplr, flipud, zeros, ones, eye, array, diag, histogram2d, + tri, mask_indices, triu_indices, triu_indices_from, tril_indices, + tril_indices_from, vander, ) import numpy as np @@ -244,32 +244,32 @@ class TestHistogram2d(object): def test_binparameter_combination(self): x = array( - [0, 0.09207008, 0.64575234, 0.12875982, 0.47390599, + [0, 0.09207008, 0.64575234, 0.12875982, 0.47390599, 0.59944483, 1]) y = array( - [0, 0.14344267, 0.48988575, 0.30558665, 0.44700682, + [0, 0.14344267, 0.48988575, 0.30558665, 0.44700682, 0.15886423, 1]) edges = (0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1) H, xe, ye = histogram2d(x, y, (edges, 4)) answer = array( - [[ 2., 0., 0., 0.], - [ 0., 1., 0., 0.], - [ 0., 0., 0., 0.], - [ 0., 0., 0., 0.], - [ 0., 1., 0., 0.], - [ 1., 0., 0., 0.], - [ 0., 1., 0., 0.], - [ 0., 0., 0., 0.], - [ 0., 0., 0., 0.], - [ 0., 0., 0., 1.]]) + [[2., 0., 0., 0.], + [0., 1., 0., 0.], + [0., 0., 0., 0.], + [0., 0., 0., 0.], + [0., 1., 0., 0.], + [1., 0., 0., 0.], + [0., 1., 0., 0.], + [0., 0., 0., 0.], + [0., 0., 0., 0.], + [0., 0., 0., 1.]]) assert_array_equal(H, answer) assert_array_equal(ye, array([0., 0.25, 0.5, 0.75, 1])) H, xe, ye = histogram2d(x, y, (4, edges)) answer = array( - [[ 1., 1., 0., 1., 0., 0., 0., 0., 0., 0.], - [ 0., 0., 0., 0., 1., 0., 0., 0., 0., 0.], - [ 0., 1., 0., 0., 1., 0., 0., 0., 0., 0.], - [ 0., 0., 0., 0., 0., 0., 0., 0., 0., 1.]]) + [[1., 1., 0., 1., 0., 0., 0., 0., 0., 0.], + [0., 0., 0., 0., 1., 0., 0., 0., 0., 0.], + [0., 1., 0., 0., 1., 0., 0., 0., 0., 0.], + [0., 0., 0., 0., 0., 0., 0., 0., 0., 1.]]) assert_array_equal(H, answer) assert_array_equal(xe, array([0., 0.25, 0.5, 0.75, 1])) @@ -288,11 +288,11 @@ def test_tril_triu_ndim2(): a = np.ones((2, 2), dtype=dtype) b = np.tril(a) c = np.triu(a) - yield assert_array_equal, b, [[1, 0], [1, 1]] - yield assert_array_equal, c, b.T + assert_array_equal(b, [[1, 0], [1, 1]]) + assert_array_equal(c, b.T) # should return the same dtype as the original array - yield assert_equal, b.dtype, a.dtype - yield assert_equal, c.dtype, a.dtype + assert_equal(b.dtype, a.dtype) + assert_equal(c.dtype, a.dtype) def test_tril_triu_ndim3(): @@ -314,10 +314,11 @@ def test_tril_triu_ndim3(): ], dtype=dtype) a_triu_observed = np.triu(a) a_tril_observed = np.tril(a) - yield assert_array_equal, a_triu_observed, a_triu_desired - yield assert_array_equal, a_tril_observed, a_tril_desired - yield assert_equal, a_triu_observed.dtype, a.dtype - yield assert_equal, a_tril_observed.dtype, a.dtype + assert_array_equal(a_triu_observed, a_triu_desired) + assert_array_equal(a_tril_observed, a_tril_desired) + assert_equal(a_triu_observed.dtype, a.dtype) + assert_equal(a_tril_observed.dtype, a.dtype) + def test_tril_triu_with_inf(): # Issue 4859 @@ -484,12 +485,12 @@ class TestVander(object): [16, -8, 4, -2, 1], [81, 27, 9, 3, 1]]) # Check default value of N: - yield (assert_array_equal, v, powers[:, 1:]) + assert_array_equal(v, powers[:, 1:]) # Check a range of N values, including 0 and 5 (greater than default) m = powers.shape[1] for n in range(6): v = vander(c, N=n) - yield (assert_array_equal, v, powers[:, m-n:m]) + assert_array_equal(v, powers[:, m-n:m]) def test_dtypes(self): c = array([11, -12, 13], dtype=np.int8) @@ -497,7 +498,7 @@ class TestVander(object): expected = np.array([[121, 11, 1], [144, -12, 1], [169, 13, 1]]) - yield (assert_array_equal, v, expected) + assert_array_equal(v, expected) c = array([1.0+1j, 1.0-1j]) v = vander(c, N=3) @@ -506,8 +507,4 @@ class TestVander(object): # The data is floating point, but the values are small integers, # so assert_array_equal *should* be safe here (rather than, say, # assert_array_almost_equal). - yield (assert_array_equal, v, expected) - - -if __name__ == "__main__": - run_module_suite() + assert_array_equal(v, expected) diff --git a/numpy/lib/tests/test_type_check.py b/numpy/lib/tests/test_type_check.py index ce8ef2f15..2982ca31a 100644 --- a/numpy/lib/tests/test_type_check.py +++ b/numpy/lib/tests/test_type_check.py @@ -3,7 +3,7 @@ from __future__ import division, absolute_import, print_function import numpy as np from numpy.compat import long from numpy.testing import ( - assert_, assert_equal, assert_array_equal, run_module_suite, assert_raises + assert_, assert_equal, assert_array_equal, assert_raises ) from numpy.lib.type_check import ( common_type, mintypecode, isreal, iscomplex, isposinf, isneginf, @@ -440,7 +440,3 @@ class TestArrayConversion(object): # other numpy function assert_raises(TypeError, asfarray, np.array([1, 2, 3]), dtype=np.array(1.0)) - - -if __name__ == "__main__": - run_module_suite() diff --git a/numpy/lib/tests/test_ufunclike.py b/numpy/lib/tests/test_ufunclike.py index 128ce37ab..ad006fe17 100644 --- a/numpy/lib/tests/test_ufunclike.py +++ b/numpy/lib/tests/test_ufunclike.py @@ -4,7 +4,7 @@ import numpy as np import numpy.core as nx import numpy.lib.ufunclike as ufl from numpy.testing import ( - run_module_suite, assert_, assert_equal, assert_array_equal, assert_warns + assert_, assert_equal, assert_array_equal, assert_warns ) @@ -91,6 +91,3 @@ class TestUfunclike(object): out = np.array(0.0) actual = np.fix(x, out=out) assert_(actual is out) - -if __name__ == "__main__": - run_module_suite() diff --git a/numpy/lib/tests/test_utils.py b/numpy/lib/tests/test_utils.py index 92bcdc238..c27c3cbf5 100644 --- a/numpy/lib/tests/test_utils.py +++ b/numpy/lib/tests/test_utils.py @@ -1,10 +1,10 @@ from __future__ import division, absolute_import, print_function import sys +import pytest + from numpy.core import arange -from numpy.testing import ( - run_module_suite, assert_, assert_equal, assert_raises_regex, dec - ) +from numpy.testing import assert_, assert_equal, assert_raises_regex from numpy.lib import deprecate import numpy.lib.utils as utils @@ -14,7 +14,7 @@ else: from StringIO import StringIO -@dec.skipif(sys.flags.optimize == 2) +@pytest.mark.skipif(sys.flags.optimize == 2, reason="Python running -OO") def test_lookfor(): out = StringIO() utils.lookfor('eigenvalue', module='numpy', output=out, @@ -65,7 +65,3 @@ def test_byte_bounds(): def test_assert_raises_regex_context_manager(): with assert_raises_regex(ValueError, 'no deprecation warning'): raise ValueError('no deprecation warning') - - -if __name__ == "__main__": - run_module_suite() |