def test_view_simple_dtype(self): (mrec, a, b, arr) = self.data ntype = (float, 2) test = mrec.view(ntype) assert_(isinstance(test, ma.MaskedArray)) assert_equal(test, np.array(list(zip(a, b)), dtype=float)) assert_(test[3, 1] is ma.masked)
def test_pickling_subbaseclass(self): # Test pickling w/ a subclass of ndarray a = masked_array(np.matrix(list(range(10))), mask=[1, 0, 1, 0, 0] * 2) a_pickled = pickle.loads(a.dumps()) assert_equal(a_pickled._mask, a._mask) assert_equal(a_pickled, a) assert_(isinstance(a_pickled._data, np.matrix))
def test_masked_binary_operations2(self): # Tests domained_masked_binary_operation (x, mx) = self.data xmx = masked_array(mx.data.__array__(), mask=mx.mask) assert_(isinstance(divide(mx, mx), MMatrix)) assert_(isinstance(divide(mx, x), MMatrix)) assert_equal(divide(mx, mx), divide(xmx, xmx))
def test_compressed(self): a = masked_array(np.matrix([1, 2, 3, 4]), mask=[0, 0, 0, 0]) b = a.compressed() assert_equal(b, a) assert_(isinstance(b, np.matrix)) a[0, 0] = masked b = a.compressed() assert_equal(b, [[2, 3, 4]])
def test_view(self): # Test view w/ flexible dtype iterator = list(zip(np.arange(10), np.random.rand(10))) data = np.array(iterator) a = masked_array(iterator, dtype=[('a', float), ('b', float)]) a.mask[0] = (1, 0) test = a.view((float, 2), np.matrix) assert_equal(test, data) assert_(isinstance(test, np.matrix)) assert_(not isinstance(test, MaskedArray))
def test_byview(self): # Test creation by view base = self.base mbase = base.view(mrecarray) assert_equal(mbase.recordmask, base.recordmask) assert_equal_records(mbase._mask, base._mask) assert_(isinstance(mbase._data, recarray)) assert_equal_records(mbase._data, base._data.view(recarray)) for field in ('a', 'b', 'c'): assert_equal(base[field], mbase[field]) assert_equal_records(mbase.view(mrecarray), mbase)
def test_fromtextfile(self): # Tests reading from a text file. fcontent = ("""# 'One (S)','Two (I)','Three (F)','Four (M)','Five (-)','Six (C)' 'strings',1,1.0,'mixed column',,1 'with embedded "double quotes"',2,2.0,1.0,,1 'strings',3,3.0E5,3,,1 'strings',4,-1e-10,,,1 """) with temppath() as path: with open(path, 'w') as f: f.write(fcontent) mrectxt = fromtextfile(path, delimitor=',', varnames='ABCDEFG') assert_(isinstance(mrectxt, MaskedRecords)) assert_equal(mrectxt.F, [1, 1, 1, 1]) assert_equal(mrectxt.E._mask, [1, 1, 1, 1]) assert_equal(mrectxt.C, [1, 2, 3.e+5, -1e-10])
def test_view_flexible_type(self): (mrec, a, b, arr) = self.data alttype = [('A', float), ('B', float)] test = mrec.view(alttype) assert_(isinstance(test, MaskedRecords)) assert_equal_records(test, arr.view(alttype)) assert_(test['B'][3] is masked) assert_equal(test.dtype, np.dtype(alttype)) assert_(test._fill_value is None)
def test_flat(self): # Test that flat can return items even for matrices [#4585, #4615] # test simple access test = masked_array(np.matrix([[1, 2, 3]]), mask=[0, 0, 1]) assert_equal(test.flat[1], 2) assert_equal(test.flat[2], masked) assert_(np.all(test.flat[0:2] == test[0, 0:2])) # Test flat on masked_matrices test = masked_array(np.matrix([[1, 2, 3]]), mask=[0, 0, 1]) test.flat = masked_array([3, 2, 1], mask=[1, 0, 0]) control = masked_array(np.matrix([[3, 2, 1]]), mask=[1, 0, 0]) assert_equal(test, control) # Test setting test = masked_array(np.matrix([[1, 2, 3]]), mask=[0, 0, 1]) testflat = test.flat testflat[:] = testflat[[2, 1, 0]] assert_equal(test, control) testflat[0] = 9 # test that matrices keep the correct shape (#4615) a = masked_array(np.matrix(np.eye(2)), mask=0) b = a.flat b01 = b[:2] assert_equal(b01.data, np.array([[1., 0.]])) assert_equal(b01.mask, np.array([[False, False]]))
def test_get(self): # Tests fields retrieval base = self.base.copy() mbase = base.view(mrecarray) # As fields.......... for field in ('a', 'b', 'c'): assert_equal(getattr(mbase, field), mbase[field]) assert_equal(base[field], mbase[field]) # as elements ....... mbase_first = mbase[0] assert_(isinstance(mbase_first, mrecarray)) assert_equal(mbase_first.dtype, mbase.dtype) assert_equal(mbase_first.tolist(), (1, 1.1, b'one')) # Used to be mask, now it's recordmask assert_equal(mbase_first.recordmask, nomask) assert_equal(mbase_first._mask.item(), (False, False, False)) assert_equal(mbase_first['a'], mbase['a'][0]) mbase_last = mbase[-1] assert_(isinstance(mbase_last, mrecarray)) assert_equal(mbase_last.dtype, mbase.dtype) assert_equal(mbase_last.tolist(), (None, None, None)) # Used to be mask, now it's recordmask assert_equal(mbase_last.recordmask, True) assert_equal(mbase_last._mask.item(), (True, True, True)) assert_equal(mbase_last['a'], mbase['a'][-1]) assert_((mbase_last['a'] is masked)) # as slice .......... mbase_sl = mbase[:2] assert_(isinstance(mbase_sl, mrecarray)) assert_equal(mbase_sl.dtype, mbase.dtype) # Used to be mask, now it's recordmask assert_equal(mbase_sl.recordmask, [0, 1]) assert_equal_records( mbase_sl.mask, np.array([(False, False, False), (True, True, True)], dtype=mbase._mask.dtype)) assert_equal_records(mbase_sl, base[:2].view(mrecarray)) for field in ('a', 'b', 'c'): assert_equal(getattr(mbase_sl, field), base[:2][field])
def test_hardmask(self): # Test hardmask base = self.base.copy() mbase = base.view(mrecarray) mbase.harden_mask() assert_(mbase._hardmask) mbase.mask = nomask assert_equal_records(mbase._mask, base._mask) mbase.soften_mask() assert_(not mbase._hardmask) mbase.mask = nomask # So, the mask of a field is no longer set to nomask... assert_equal_records(mbase._mask, ma.make_mask_none(base.shape, base.dtype)) assert_(ma.make_mask(mbase['b']._mask) is nomask) assert_equal(mbase['a']._mask, mbase['b']._mask)
def test_allany_onmatrices(self): x = np.array([[0.13, 0.26, 0.90], [0.28, 0.33, 0.63], [0.31, 0.87, 0.70]]) X = np.matrix(x) m = np.array( [[True, False, False], [False, False, False], [True, True, False]], dtype=np.bool_) mX = masked_array(X, mask=m) mXbig = (mX > 0.5) mXsmall = (mX < 0.5) assert_(not mXbig.all()) assert_(mXbig.any()) assert_equal(mXbig.all(0), np.matrix([False, False, True])) assert_equal(mXbig.all(1), np.matrix([False, False, True]).T) assert_equal(mXbig.any(0), np.matrix([False, False, True])) assert_equal(mXbig.any(1), np.matrix([True, True, True]).T) assert_(not mXsmall.all()) assert_(mXsmall.any()) assert_equal(mXsmall.all(0), np.matrix([True, True, False])) assert_equal(mXsmall.all(1), np.matrix([False, False, False]).T) assert_equal(mXsmall.any(0), np.matrix([True, True, False])) assert_equal(mXsmall.any(1), np.matrix([True, True, False]).T)
def test_maskedarray_subclassing(self): # Tests subclassing MaskedArray (x, mx) = self.data assert_(isinstance(mx._data, np.matrix))
def test_masked_unary_operations(self): # Tests masked_unary_operation (x, mx) = self.data with np.errstate(divide='ignore'): assert_(isinstance(log(mx), MMatrix)) assert_equal(log(x), np.log(x))
def test_masked_binary_operations(self): # Tests masked_binary_operation (x, mx) = self.data # Result should be a MMatrix assert_(isinstance(add(mx, mx), MMatrix)) assert_(isinstance(add(mx, x), MMatrix)) # Result should work assert_equal(add(mx, x), mx + x) assert_(isinstance(add(mx, mx)._data, np.matrix)) assert_(isinstance(add.outer(mx, mx), MMatrix)) assert_(isinstance(hypot(mx, mx), MMatrix)) assert_(isinstance(hypot(mx, x), MMatrix))
def test_matrix_indexing(self): # Tests conversions and indexing x1 = np.matrix([[1, 2, 3], [4, 3, 2]]) x2 = masked_array(x1, mask=[[1, 0, 0], [0, 1, 0]]) x3 = masked_array(x1, mask=[[0, 1, 0], [1, 0, 0]]) x4 = masked_array(x1) # test conversion to strings str(x2) # raises? repr(x2) # raises? # tests of indexing assert_(type(x2[1, 0]) is type(x1[1, 0])) assert_(x1[1, 0] == x2[1, 0]) assert_(x2[1, 1] is masked) assert_equal(x1[0, 2], x2[0, 2]) assert_equal(x1[0, 1:], x2[0, 1:]) assert_equal(x1[:, 2], x2[:, 2]) assert_equal(x1[:], x2[:]) assert_equal(x1[1:], x3[1:]) x1[0, 2] = 9 x2[0, 2] = 9 assert_equal(x1, x2) x1[0, 1:] = 99 x2[0, 1:] = 99 assert_equal(x1, x2) x2[0, 1] = masked assert_equal(x1, x2) x2[0, 1:] = masked assert_equal(x1, x2) x2[0, :] = x1[0, :] x2[0, 1] = masked assert_(allequal(getmask(x2), np.array([[0, 1, 0], [0, 1, 0]]))) x3[1, :] = masked_array([1, 2, 3], [1, 1, 0]) assert_(allequal(getmask(x3)[1], masked_array([1, 1, 0]))) assert_(allequal(getmask(x3[1]), masked_array([1, 1, 0]))) x4[1, :] = masked_array([1, 2, 3], [1, 1, 0]) assert_(allequal(getmask(x4[1]), masked_array([1, 1, 0]))) assert_(allequal(x4[1], masked_array([1, 2, 3]))) x1 = np.matrix(np.arange(5) * 1.0) x2 = masked_values(x1, 3.0) assert_equal(x1, x2) assert_( allequal(masked_array([0, 0, 0, 1, 0], dtype=MaskType), x2.mask)) assert_equal(3.0, x2.fill_value)
def test_view_by_itself(self): (mrec, a, b, arr) = self.data test = mrec.view() assert_(isinstance(test, MaskedRecords)) assert_equal_records(test, mrec) assert_equal_records(test._mask, mrec._mask)