def test_testPut2(self): # Test of put d = arange(5) x = array(d, mask=[0, 0, 0, 0, 0]) z = array([10, 40], mask=[1, 0]) assert_(x[2] is not masked) assert_(x[3] is not masked) x[2:4] = z assert_(x[2] is masked) assert_(x[3] is not masked) assert_(eq(x, [0, 1, 10, 40, 4])) d = arange(5) x = array(d, mask=[0, 0, 0, 0, 0]) y = x[2:4] z = array([10, 40], mask=[1, 0]) assert_(x[2] is not masked) assert_(x[3] is not masked) y[:] = z assert_(y[0] is masked) assert_(y[1] is not masked) assert_(eq(y, [10, 40])) assert_(x[2] is masked) assert_(x[3] is not masked) assert_(eq(x, [0, 1, 10, 40, 4]))
def test_matching_named_fields(self): # Test combination of arrays w/ matching field names (_, x, _, z) = self.data zz = np.array([('a', 10., 100.), ('b', 20., 200.), ('c', 30., 300.)], dtype=[('A', '|S3'), ('B', float), ('C', float)]) test = stack_arrays((z, zz)) control = ma.array([('A', 1, -1), ('B', 2, -1), ('a', 10., 100.), ('b', 20., 200.), ('c', 30., 300.)], dtype=[('A', '|S3'), ('B', float), ('C', float)], mask=[(0, 0, 1), (0, 0, 1), (0, 0, 0), (0, 0, 0), (0, 0, 0)]) assert_equal(test, control) assert_equal(test.mask, control.mask) test = stack_arrays((z, zz, x)) ndtype = [('A', '|S3'), ('B', float), ('C', float), ('f3', int)] control = ma.array([('A', 1, -1, -1), ('B', 2, -1, -1), ('a', 10., 100., -1), ('b', 20., 200., -1), ('c', 30., 300., -1), (-1, -1, -1, 1), (-1, -1, -1, 2)], dtype=ndtype, mask=[(0, 0, 1, 1), (0, 0, 1, 1), (0, 0, 0, 1), (0, 0, 0, 1), (0, 0, 0, 1), (1, 1, 1, 0), (1, 1, 1, 0)]) assert_equal(test, control) assert_equal(test.mask, control.mask)
def test_testAverage2(self): # More tests of average. w1 = [0, 1, 1, 1, 1, 0] w2 = [[0, 1, 1, 1, 1, 0], [1, 0, 0, 0, 0, 1]] x = arange(6) assert_(allclose(average(x, axis=0), 2.5)) assert_(allclose(average(x, axis=0, weights=w1), 2.5)) y = array([arange(6), 2.0 * arange(6)]) assert_(allclose(average(y, None), np.add.reduce(np.arange(6)) * 3. / 12.)) assert_(allclose(average(y, axis=0), np.arange(6) * 3. / 2.)) assert_(allclose(average(y, axis=1), [average(x, axis=0), average(x, axis=0)*2.0])) assert_(allclose(average(y, None, weights=w2), 20. / 6.)) assert_(allclose(average(y, axis=0, weights=w2), [0., 1., 2., 3., 4., 10.])) assert_(allclose(average(y, axis=1), [average(x, axis=0), average(x, axis=0)*2.0])) m1 = zeros(6) m2 = [0, 0, 1, 1, 0, 0] m3 = [[0, 0, 1, 1, 0, 0], [0, 1, 1, 1, 1, 0]] m4 = ones(6) m5 = [0, 1, 1, 1, 1, 1] assert_(allclose(average(masked_array(x, m1), axis=0), 2.5)) assert_(allclose(average(masked_array(x, m2), axis=0), 2.5)) assert_(average(masked_array(x, m4), axis=0) is masked) assert_equal(average(masked_array(x, m5), axis=0), 0.0) assert_equal(count(average(masked_array(x, m4), axis=0)), 0) z = masked_array(y, m3) assert_(allclose(average(z, None), 20. / 6.)) assert_(allclose(average(z, axis=0), [0., 1., 99., 99., 4.0, 7.5])) assert_(allclose(average(z, axis=1), [2.5, 5.0])) assert_(allclose(average(z, axis=0, weights=w2), [0., 1., 99., 99., 4.0, 10.0])) a = arange(6) b = arange(6) * 3 r1, w1 = average([[a, b], [b, a]], axis=1, returned=1) assert_equal(shape(r1), shape(w1)) assert_equal(r1.shape, w1.shape) r2, w2 = average(ones((2, 2, 3)), axis=0, weights=[3, 1], returned=1) assert_equal(shape(w2), shape(r2)) r2, w2 = average(ones((2, 2, 3)), returned=1) assert_equal(shape(w2), shape(r2)) r2, w2 = average(ones((2, 2, 3)), weights=ones((2, 2, 3)), returned=1) assert_(shape(w2) == shape(r2)) a2d = array([[1, 2], [0, 4]], float) a2dm = masked_array(a2d, [[0, 0], [1, 0]]) a2da = average(a2d, axis=0) assert_(eq(a2da, [0.5, 3.0])) a2dma = average(a2dm, axis=0) assert_(eq(a2dma, [1.0, 3.0])) a2dma = average(a2dm, axis=None) assert_(eq(a2dma, 7. / 3.)) a2dma = average(a2dm, axis=1) assert_(eq(a2dma, [1.5, 4.0]))
def test_masked_flexible(self): # Test recursive_fill_fields on masked flexible-array a = ma.array([(1, 10.), (2, 20.)], mask=[(0, 1), (1, 0)], dtype=[('A', int), ('B', float)]) b = ma.zeros((3, ), dtype=a.dtype) test = recursive_fill_fields(a, b) control = ma.array([(1, 10.), (2, 20.), (0, 0.)], mask=[(0, 1), (1, 0), (0, 0)], dtype=[('A', int), ('B', float)]) assert_equal(test, control)
def test_wmasked_arrays(self): # Test merge_arrays masked arrays (_, x, _, _) = self.data mx = ma.array([1, 2, 3], mask=[1, 0, 0]) test = merge_arrays((x, mx), usemask=True) control = ma.array([(1, 1), (2, 2), (-1, 3)], mask=[(0, 1), (0, 0), (1, 0)], dtype=[('f0', int), ('f1', int)]) assert_equal(test, control) test = merge_arrays((x, mx), usemask=True, asrecarray=True) assert_equal(test, control) assert_(isinstance(test, MaskedRecords))
def test_checktitles(self): # Test using titles in the field names adtype = [(('a', 'A'), int), (('b', 'B'), bool), (('c', 'C'), float)] a = ma.array([(1, 2, 3)], mask=[(0, 1, 0)], dtype=adtype) bdtype = [(('a', 'A'), int), (('b', 'B'), bool), (('c', 'C'), float)] b = ma.array([(4, 5, 6)], dtype=bdtype) test = stack_arrays((a, b)) control = ma.array([(1, 2, 3), (4, 5, 6)], mask=[(0, 1, 0), (0, 0, 0)], dtype=bdtype) assert_equal(test, control) assert_equal(test.mask, control.mask)
def test_tolist(self): # Test tolist. _a = ma.array([1, 2, 3], mask=[0, 0, 1], dtype=int) _b = ma.array([1.1, 2.2, 3.3], mask=[0, 0, 1], dtype=float) _c = ma.array(['one', 'two', 'three'], mask=[1, 0, 0], dtype='|S8') ddtype = [('a', int), ('b', float), ('c', '|S8')] mrec = fromarrays([_a, _b, _c], dtype=ddtype, fill_value=(99999, 99999., 'N/A')) assert_equal(mrec.tolist(), [(1, 1.1, None), (2, 2.2, b'two'), (None, None, b'three')])
def test_fromarrays(self): _a = ma.array([1, 2, 3], mask=[0, 0, 1], dtype=int) _b = ma.array([1.1, 2.2, 3.3], mask=[0, 0, 1], dtype=float) _c = ma.array(['one', 'two', 'three'], mask=[0, 0, 1], dtype='|S8') (mrec, nrec, _) = self.data for (f, l) in zip(('a', 'b', 'c'), (_a, _b, _c)): assert_equal(getattr(mrec, f)._mask, l._mask) # One record only _x = ma.array( [1, 1.1, 'one'], mask=[1, 0, 0], ) assert_equal_records(fromarrays(_x, dtype=mrec.dtype), mrec[0])
def test_testScalarArithmetic(self): xm = array(0, mask=1) #TODO FIXME: Find out what the following raises a warning in r8247 with np.errstate(divide='ignore'): assert_((1 / array(0)).mask) assert_((1 + xm).mask) assert_((-xm).mask) assert_((-xm).mask) assert_(maximum(xm, xm).mask) assert_(minimum(xm, xm).mask) assert_(xm.filled().dtype is xm._data.dtype) x = array(0, mask=0) assert_(x.filled() == x._data) assert_equal(str(xm), str(masked_print_option))
def setup(self): x = np.array([1., 1., 1., -2., pi/2.0, 4., 5., -10., 10., 1., 2., 3.]) y = np.array([5., 0., 3., 2., -1., -4., 0., -10., 10., 1., 0., 3.]) a10 = 10. m1 = [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0] m2 = [0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1] xm = array(x, mask=m1) ym = array(y, mask=m2) z = np.array([-.5, 0., .5, .8]) zm = array(z, mask=[0, 1, 0, 0]) xf = np.where(m1, 1e+20, x) s = x.shape xm.set_fill_value(1e+20) self.d = (x, y, a10, m1, m2, xm, ym, z, zm, xf, s)
def test_testCopySize(self): # Tests of some subtle points of copying and sizing. n = [0, 0, 1, 0, 0] m = make_mask(n) m2 = make_mask(m) assert_(m is m2) m3 = make_mask(m, copy=1) assert_(m is not m3) x1 = np.arange(5) y1 = array(x1, mask=m) assert_(y1._data is not x1) assert_(allequal(x1, y1._data)) assert_(y1.mask is m) y1a = array(y1, copy=0) # For copy=False, one might expect that the array would just # passed on, i.e., that it would be "is" instead of "==". # See gh-4043 for discussion. assert_(y1a._mask.__array_interface__ == y1._mask.__array_interface__) y2 = array(x1, mask=m3, copy=0) assert_(y2.mask is m3) assert_(y2[2] is masked) y2[2] = 9 assert_(y2[2] is not masked) assert_(y2.mask is m3) assert_(allequal(y2.mask, 0)) y2a = array(x1, mask=m, copy=1) assert_(y2a.mask is not m) assert_(y2a[2] is masked) y2a[2] = 9 assert_(y2a[2] is not masked) assert_(y2a.mask is not m) assert_(allequal(y2a.mask, 0)) y3 = array(x1 * 1.0, mask=m) assert_(filled(y3).dtype is (x1 * 1.0).dtype) x4 = arange(4) x4[2] = masked y4 = resize(x4, (8,)) assert_(eq(concatenate([x4, x4]), y4)) assert_(eq(getmask(y4), [0, 0, 1, 0, 0, 0, 1, 0])) y5 = repeat(x4, (2, 2, 2, 2), axis=0) assert_(eq(y5, [0, 0, 1, 1, 2, 2, 3, 3])) y6 = repeat(x4, 2, axis=0) assert_(eq(y5, y6))
def test_xtestCount(self): # Test count ott = array([0., 1., 2., 3.], mask=[1, 0, 0, 0]) assert_(count(ott).dtype.type is np.intp) assert_equal(3, count(ott)) assert_equal(1, count(1)) assert_(eq(0, array(1, mask=[1]))) ott = ott.reshape((2, 2)) assert_(count(ott).dtype.type is np.intp) assert_(isinstance(count(ott, 0), np.ndarray)) assert_(count(ott).dtype.type is np.intp) assert_(eq(3, count(ott))) assert_(getmask(count(ott, 0)) is nomask) assert_(eq([1, 2], count(ott, 0)))
def test_filled(self): # Test filling the array _a = ma.array([1, 2, 3], mask=[0, 0, 1], dtype=int) _b = ma.array([1.1, 2.2, 3.3], mask=[0, 0, 1], dtype=float) _c = ma.array(['one', 'two', 'three'], mask=[0, 0, 1], dtype='|S8') ddtype = [('a', int), ('b', float), ('c', '|S8')] mrec = fromarrays([_a, _b, _c], dtype=ddtype, fill_value=(99999, 99999., 'N/A')) mrecfilled = mrec.filled() assert_equal(mrecfilled['a'], np.array((1, 2, 99999), dtype=int)) assert_equal(mrecfilled['b'], np.array((1.1, 2.2, 99999.), dtype=float)) assert_equal(mrecfilled['c'], np.array(('one', 'two', 'N/A'), dtype='|S8'))
def test_set_fields(self): # Tests setting fields. base = self.base.copy() mbase = base.view(mrecarray) mbase = mbase.copy() mbase.fill_value = (999999, 1e20, 'N/A') # Change the data, the mask should be conserved mbase.a._data[:] = 5 assert_equal(mbase['a']._data, [5, 5, 5, 5, 5]) assert_equal(mbase['a']._mask, [0, 1, 0, 0, 1]) # Change the elements, and the mask will follow mbase.a = 1 assert_equal(mbase['a']._data, [1] * 5) assert_equal(ma.getmaskarray(mbase['a']), [0] * 5) # Use to be _mask, now it's recordmask assert_equal(mbase.recordmask, [False] * 5) assert_equal( mbase._mask.tolist(), np.array([(0, 0, 0), (0, 1, 1), (0, 0, 0), (0, 0, 0), (0, 1, 1)], dtype=bool)) # Set a field to mask ........................ mbase.c = masked # Use to be mask, and now it's still mask ! assert_equal(mbase.c.mask, [1] * 5) assert_equal(mbase.c.recordmask, [1] * 5) assert_equal(ma.getmaskarray(mbase['c']), [1] * 5) assert_equal(ma.getdata(mbase['c']), [b'N/A'] * 5) assert_equal( mbase._mask.tolist(), np.array([(0, 0, 1), (0, 1, 1), (0, 0, 1), (0, 0, 1), (0, 1, 1)], dtype=bool)) # Set fields by slices ....................... mbase = base.view(mrecarray).copy() mbase.a[3:] = 5 assert_equal(mbase.a, [1, 2, 3, 5, 5]) assert_equal(mbase.a._mask, [0, 1, 0, 0, 0]) mbase.b[3:] = masked assert_equal(mbase.b, base['b']) assert_equal(mbase.b._mask, [0, 1, 0, 1, 1]) # Set fields globally.......................... ndtype = [('alpha', '|S1'), ('num', int)] data = ma.array([('a', 1), ('b', 2), ('c', 3)], dtype=ndtype) rdata = data.view(MaskedRecords) val = ma.array([10, 20, 30], mask=[1, 0, 0]) rdata['num'] = val assert_equal(rdata.num, val) assert_equal(rdata.num.mask, [1, 0, 0])
def addfield(mrecord, newfield, newfieldname=None): """Adds a new field to the masked record array Uses `newfield` as data and `newfieldname` as name. If `newfieldname` is None, the new field name is set to 'fi', where `i` is the number of existing fields. """ _data = mrecord._data _mask = mrecord._mask if newfieldname is None or newfieldname in reserved_fields: newfieldname = 'f%i' % len(_data.dtype) newfield = ma.array(newfield) # Get the new data. # Create a new empty recarray newdtype = np.dtype(_data.dtype.descr + [(newfieldname, newfield.dtype)]) newdata = recarray(_data.shape, newdtype) # Add the existing field [newdata.setfield(_data.getfield(*f), *f) for f in _data.dtype.fields.values()] # Add the new field newdata.setfield(newfield._data, *newdata.dtype.fields[newfieldname]) newdata = newdata.view(MaskedRecords) # Get the new mask # Create a new empty recarray newmdtype = np.dtype([(n, bool_) for n in newdtype.names]) newmask = recarray(_data.shape, newmdtype) # Add the old masks [newmask.setfield(_mask.getfield(*f), *f) for f in _mask.dtype.fields.values()] # Add the mask of the new field newmask.setfield(getmaskarray(newfield), *newmask.dtype.fields[newfieldname]) newdata._mask = newmask return newdata
def test_testArrayMethods(self): a = array([1, 3, 2]) assert_(eq(a.any(), a._data.any())) assert_(eq(a.all(), a._data.all())) assert_(eq(a.argmax(), a._data.argmax())) assert_(eq(a.argmin(), a._data.argmin())) assert_(eq(a.choose(0, 1, 2, 3, 4), a._data.choose(0, 1, 2, 3, 4))) assert_(eq(a.compress([1, 0, 1]), a._data.compress([1, 0, 1]))) assert_(eq(a.conj(), a._data.conj())) assert_(eq(a.conjugate(), a._data.conjugate())) m = array([[1, 2], [3, 4]]) assert_(eq(m.diagonal(), m._data.diagonal())) assert_(eq(a.sum(), a._data.sum())) assert_(eq(a.take([1, 2]), a._data.take([1, 2]))) assert_(eq(m.transpose(), m._data.transpose()))
def test_addfield(self): # Tests addfield (mrec, nrec, ddtype) = self.data (d, m) = ([100, 200, 300], [1, 0, 0]) mrec = addfield(mrec, ma.array(d, mask=m)) assert_equal(mrec.f3, d) assert_equal(mrec.f3._mask, m)
def test_find_duplicates(self): # Test find_duplicates a = ma.array([(2, (2., 'B')), (1, (2., 'B')), (2, (2., 'B')), (1, (1., 'B')), (2, (2., 'B')), (2, (2., 'C'))], mask=[(0, (0, 0)), (0, (0, 0)), (0, (0, 0)), (0, (0, 0)), (1, (0, 0)), (0, (1, 0))], dtype=[('A', int), ('B', [('BA', float), ('BB', '|S1')])]) test = find_duplicates(a, ignoremask=False, return_index=True) control = [0, 2] assert_equal(sorted(test[-1]), control) assert_equal(test[0], a[test[-1]]) test = find_duplicates(a, key='A', return_index=True) control = [0, 1, 2, 3, 5] assert_equal(sorted(test[-1]), control) assert_equal(test[0], a[test[-1]]) test = find_duplicates(a, key='B', return_index=True) control = [0, 1, 2, 4] assert_equal(sorted(test[-1]), control) assert_equal(test[0], a[test[-1]]) test = find_duplicates(a, key='BA', return_index=True) control = [0, 1, 2, 4] assert_equal(sorted(test[-1]), control) assert_equal(test[0], a[test[-1]]) test = find_duplicates(a, key='BB', return_index=True) control = [0, 1, 2, 3, 4] assert_equal(sorted(test[-1]), control) assert_equal(test[0], a[test[-1]])
def test_w_singlefield(self): # Test single field test = merge_arrays( (np.array([1, 2]).view([('a', int)]), np.array([10., 20., 30.])), ) control = ma.array([(1, 10.), (2, 20.), (-1, 30.)], mask=[(0, 0), (0, 0), (1, 0)], dtype=[('a', int), ('f1', float)]) assert_equal(test, control)
def test_testAverage1(self): # Test of average. ott = array([0., 1., 2., 3.], mask=[1, 0, 0, 0]) assert_(eq(2.0, average(ott, axis=0))) assert_(eq(2.0, average(ott, weights=[1., 1., 2., 1.]))) result, wts = average(ott, weights=[1., 1., 2., 1.], returned=1) assert_(eq(2.0, result)) assert_(wts == 4.0) ott[:] = masked assert_(average(ott, axis=0) is masked) ott = array([0., 1., 2., 3.], mask=[1, 0, 0, 0]) ott = ott.reshape(2, 2) ott[:, 1] = masked assert_(eq(average(ott, axis=0), [2.0, 0.0])) assert_(average(ott, axis=1)[0] is masked) assert_(eq([2., 0.], average(ott, axis=0))) result, wts = average(ott, axis=0, returned=1) assert_(eq(wts, [1., 0.]))
def test_autoconversion(self): # Tests autoconversion adtype = [('A', int), ('B', bool), ('C', float)] a = ma.array([(1, 2, 3)], mask=[(0, 1, 0)], dtype=adtype) bdtype = [('A', int), ('B', float), ('C', float)] b = ma.array([(4, 5, 6)], dtype=bdtype) control = ma.array([(1, 2, 3), (4, 5, 6)], mask=[(0, 1, 0), (0, 0, 0)], dtype=bdtype) test = stack_arrays((a, b), autoconvert=True) assert_equal(test, control) assert_equal(test.mask, control.mask) try: test = stack_arrays((a, b), autoconvert=False) except TypeError: pass else: raise AssertionError
def test_testCI(self): # Test of conversions and indexing x1 = np.array([1, 2, 4, 3]) x2 = array(x1, mask=[1, 0, 0, 0]) x3 = array(x1, mask=[0, 1, 0, 1]) x4 = array(x1) # test conversion to strings str(x2) # raises? repr(x2) # raises? assert_(eq(np.sort(x1), sort(x2, fill_value=0))) # tests of indexing assert_(type(x2[1]) is type(x1[1])) assert_(x1[1] == x2[1]) assert_(x2[0] is masked) assert_(eq(x1[2], x2[2])) assert_(eq(x1[2:5], x2[2:5])) assert_(eq(x1[:], x2[:])) assert_(eq(x1[1:], x3[1:])) x1[2] = 9 x2[2] = 9 assert_(eq(x1, x2)) x1[1:3] = 99 x2[1:3] = 99 assert_(eq(x1, x2)) x2[1] = masked assert_(eq(x1, x2)) x2[1:3] = masked assert_(eq(x1, x2)) x2[:] = x1 x2[1] = masked assert_(allequal(getmask(x2), array([0, 1, 0, 0]))) x3[:] = masked_array([1, 2, 3, 4], [0, 1, 1, 0]) assert_(allequal(getmask(x3), array([0, 1, 1, 0]))) x4[:] = masked_array([1, 2, 3, 4], [0, 1, 1, 0]) assert_(allequal(getmask(x4), array([0, 1, 1, 0]))) assert_(allequal(x4, array([1, 2, 3, 4]))) x1 = np.arange(5) * 1.0 x2 = masked_values(x1, 3.0) assert_(eq(x1, x2)) assert_(allequal(array([0, 0, 0, 1, 0], MaskType), x2.mask)) assert_(eq(3.0, x2.fill_value)) x1 = array([1, 'hello', 2, 3], object) x2 = np.array([1, 'hello', 2, 3], object) s1 = x1[1] s2 = x2[1] assert_equal(type(s2), str) assert_equal(type(s1), str) assert_equal(s1, s2) assert_(x1[1:1].shape == (0,))
def test_testToPython(self): assert_equal(1, int(array(1))) assert_equal(1.0, float(array(1))) assert_equal(1, int(array([[[1]]]))) assert_equal(1.0, float(array([[1]]))) assert_raises(TypeError, float, array([1, 1])) assert_raises(ValueError, bool, array([0, 1])) assert_raises(ValueError, bool, array([0, 0], mask=[0, 1]))
def test_append_on_flex(self): # Test append_fields on flexible type arrays z = self.data[-1] test = append_fields(z, 'C', data=[10, 20, 30]) control = ma.array( [('A', 1., 10), ('B', 2., 20), (-1, -1., 30)], mask=[(0, 0, 0), (0, 0, 0), (1, 1, 0)], dtype=[('A', '|S3'), ('B', float), ('C', int)], ) assert_equal(test, control)
def test_append_double(self): # Test simple case (_, x, _, _) = self.data test = append_fields(x, ('A', 'B'), data=[[10, 20, 30], [100, 200]]) control = ma.array( [(1, 10, 100), (2, 20, 200), (-1, 30, -1)], mask=[(0, 0, 0), (0, 0, 0), (1, 0, 1)], dtype=[('f0', int), ('A', int), ('B', int)], ) assert_equal(test, control)
def test_append_single(self): # Test simple case (_, x, _, _) = self.data test = append_fields(x, 'A', data=[10, 20, 30]) control = ma.array( [(1, 10), (2, 20), (-1, 30)], mask=[(0, 0), (0, 0), (1, 0)], dtype=[('f0', int), ('A', int)], ) assert_equal(test, control)
def test_testAddSumProd(self): # Test add, sum, product. (x, y, a10, m1, m2, xm, ym, z, zm, xf, s) = self.d assert_(eq(np.add.reduce(x), add.reduce(x))) assert_(eq(np.add.accumulate(x), add.accumulate(x))) assert_(eq(4, sum(array(4), axis=0))) assert_(eq(4, sum(array(4), axis=0))) assert_(eq(np.sum(x, axis=0), sum(x, axis=0))) assert_(eq(np.sum(filled(xm, 0), axis=0), sum(xm, axis=0))) assert_(eq(np.sum(x, 0), sum(x, 0))) assert_(eq(np.product(x, axis=0), product(x, axis=0))) assert_(eq(np.product(x, 0), product(x, 0))) assert_(eq(np.product(filled(xm, 1), axis=0), product(xm, axis=0))) if len(s) > 1: assert_(eq(np.concatenate((x, y), 1), concatenate((xm, ym), 1))) assert_(eq(np.add.reduce(x, 1), add.reduce(x, 1))) assert_(eq(np.sum(x, 1), sum(x, 1))) assert_(eq(np.product(x, 1), product(x, 1)))
def test_append_on_nested(self): # Test append_fields on nested fields w = self.data[0] test = append_fields(w, 'C', data=[10, 20, 30]) control = ma.array( [(1, (2, 3.0), 10), (4, (5, 6.0), 20), (-1, (-1, -1.), 30)], mask=[(0, (0, 0), 0), (0, (0, 0), 0), (1, (1, 1), 0)], dtype=[('a', int), ('b', [('ba', float), ('bb', int)]), ('C', int)], ) assert_equal(test, control)
def test_testPut(self): # Test of put d = arange(5) n = [0, 0, 0, 1, 1] m = make_mask(n) m2 = m.copy() x = array(d, mask=m) assert_(x[3] is masked) assert_(x[4] is masked) x[[1, 4]] = [10, 40] assert_(x.mask is m) assert_(x[3] is masked) assert_(x[4] is not masked) assert_(eq(x, [0, 10, 2, -1, 40])) x = array(d, mask=m2, copy=True) x.put([0, 1, 2], [-1, 100, 200]) assert_(x.mask is not m2) assert_(x[3] is masked) assert_(x[4] is masked) assert_(eq(x, [-1, 100, 200, 0, 0]))
def setup(self): x = np.array([8.375, 7.545, 8.828, 8.5, 1.757, 5.928, 8.43, 7.78, 9.865, 5.878, 8.979, 4.732, 3.012, 6.022, 5.095, 3.116, 5.238, 3.957, 6.04, 9.63, 7.712, 3.382, 4.489, 6.479, 7.189, 9.645, 5.395, 4.961, 9.894, 2.893, 7.357, 9.828, 6.272, 3.758, 6.693, 0.993]) X = x.reshape(6, 6) XX = x.reshape(3, 2, 2, 3) m = np.array([0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0]) mx = array(data=x, mask=m) mX = array(data=X, mask=m.reshape(X.shape)) mXX = array(data=XX, mask=m.reshape(XX.shape)) self.d = (x, X, XX, m, mx, mX, mXX)