diff options
| -rw-r--r-- | numpy/core/umath_tests.py | 15 | ||||
| -rw-r--r-- | numpy/lib/histograms.py | 55 | ||||
| -rw-r--r-- | numpy/testing/decorators.py | 8 | ||||
| -rw-r--r-- | numpy/testing/noseclasses.py | 9 | ||||
| -rw-r--r-- | numpy/testing/nosetester.py | 8 | ||||
| -rw-r--r-- | numpy/testing/utils.py | 8 |
6 files changed, 61 insertions, 42 deletions
diff --git a/numpy/core/umath_tests.py b/numpy/core/umath_tests.py new file mode 100644 index 000000000..28e325b98 --- /dev/null +++ b/numpy/core/umath_tests.py @@ -0,0 +1,15 @@ +""" +Shim for _umath_tests to allow a deprecation period for the new name. + +""" +from __future__ import division, absolute_import, print_function + +import warnings + +# 2018-04-04, numpy 1.15.0 +warnings.warn(("numpy.core.umath_tests is an internal NumPy " + "module and should not be imported. It will " + "be removed in a future NumPy release."), + category=DeprecationWarning, stacklevel=2) + +from ._umath_tests import * diff --git a/numpy/lib/histograms.py b/numpy/lib/histograms.py index 66e2ccda1..a0346f6c5 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): """ @@ -693,7 +697,7 @@ 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 +745,12 @@ 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) @@ -873,7 +877,7 @@ def histogramdd(sample, bins=10, range=None, normed=False, weights=None): raise ValueError('range argument must have one entry per dimension') # Create edge arrays - for i in np.arange(D): + for i in _range(D): if np.ndim(bins[i]) == 0: if bins[i] < 1: raise ValueError( @@ -894,21 +898,20 @@ def histogramdd(sample, bins=10, range=None, normed=False, weights=None): nbin[i] = len(edges[i]) + 1 # includes an outlier on each end dedges[i] = np.diff(edges[i]) - nbin = np.asarray(nbin) - # 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): @@ -918,35 +921,21 @@ 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, np.intp) - 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),) @@ -955,7 +944,7 @@ 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/testing/decorators.py b/numpy/testing/decorators.py index 1988afd29..68c1554b5 100644 --- a/numpy/testing/decorators.py +++ b/numpy/testing/decorators.py @@ -3,9 +3,13 @@ Back compatibility decorators module. It will import the appropriate set of tools """ +from __future__ import division, absolute_import, print_function + import warnings -warnings.warn("Import from numpy.testing, not numpy.testing.decorators", - ImportWarning) +# 2018-04-04, numpy 1.15.0 +warnings.warn("Importing from numpy.testing.decorators is deprecated, " + "import from numpy.testing instead.", + DeprecationWarning, stacklevel=2) from ._private.decorators import * diff --git a/numpy/testing/noseclasses.py b/numpy/testing/noseclasses.py index dde62e825..e0e728a32 100644 --- a/numpy/testing/noseclasses.py +++ b/numpy/testing/noseclasses.py @@ -2,10 +2,13 @@ Back compatibility noseclasses module. It will import the appropriate set of tools """ +from __future__ import division, absolute_import, print_function + import warnings -warnings.warn("Import from numpy.testing, not numpy.testing.noseclasses", - ImportWarning) +# 2018-04-04, numpy 1.15.0 +warnings.warn("Importing from numpy.testing.noseclasses is deprecated, " + "import from numpy.testing instead", + DeprecationWarning, stacklevel=2) from ._private.noseclasses import * - diff --git a/numpy/testing/nosetester.py b/numpy/testing/nosetester.py index 772bff305..c8c7d6e68 100644 --- a/numpy/testing/nosetester.py +++ b/numpy/testing/nosetester.py @@ -3,10 +3,14 @@ Back compatibility nosetester module. It will import the appropriate set of tools """ +from __future__ import division, absolute_import, print_function + import warnings -warnings.warn("Import from numpy.testing, not numpy.testing.nosetester", - ImportWarning) +# 2018-04-04, numpy 1.15.0 +warnings.warn("Importing from numpy.testing.nosetester is deprecated, " + "import from numpy.testing instead.", + DeprecationWarning, stacklevel=2) from ._private.nosetester import * diff --git a/numpy/testing/utils.py b/numpy/testing/utils.py index 3cd89e639..78cf405cf 100644 --- a/numpy/testing/utils.py +++ b/numpy/testing/utils.py @@ -3,10 +3,14 @@ Back compatibility utils module. It will import the appropriate set of tools """ +from __future__ import division, absolute_import, print_function + import warnings -warnings.warn("Import from numpy.testing, not numpy.testing.utils", - ImportWarning) +# 2018-04-04, numpy 1.15.0 +warnings.warn("Importing from numpy.testing.utils is deprecated, " + "import from numpy.testing instead.", + ImportWarning, stacklevel=2) from ._private.utils import * |