diff options
Diffstat (limited to 'numpy/ma')
| -rw-r--r-- | numpy/ma/core.py | 3 | ||||
| -rw-r--r-- | numpy/ma/extras.py | 18 | ||||
| -rw-r--r-- | numpy/ma/mrecords.py | 3 | ||||
| -rw-r--r-- | numpy/ma/tests/test_extras.py | 26 | ||||
| -rw-r--r-- | numpy/ma/tests/test_mrecords.py | 10 |
5 files changed, 37 insertions, 23 deletions
diff --git a/numpy/ma/core.py b/numpy/ma/core.py index 8e1e71e0a..1f5f84f19 100644 --- a/numpy/ma/core.py +++ b/numpy/ma/core.py @@ -1354,7 +1354,8 @@ class MaskedArray(numeric.ndarray): # raise IndexError, msg if isinstance(indx, basestring): ndarray.__setitem__(self._data,indx, getdata(value)) - warnings.warn("The mask is NOT affected!") + warnings.warn("MaskedArray.__setitem__ on fields: "\ + "The mask is NOT affected!") return #.... if value is masked: diff --git a/numpy/ma/extras.py b/numpy/ma/extras.py index d44921b9e..fce070df5 100644 --- a/numpy/ma/extras.py +++ b/numpy/ma/extras.py @@ -16,14 +16,15 @@ __all__ = ['apply_along_axis', 'atleast_1d', 'atleast_2d', 'atleast_3d', 'column_stack','compress_cols','compress_rowcols', 'compress_rows', 'count_masked', 'dot','dstack', - 'expand_dims', + 'ediff1d','expand_dims', 'flatnotmasked_contiguous','flatnotmasked_edges', 'hsplit','hstack', 'mask_cols','mask_rowcols','mask_rows','masked_all','masked_all_like', - 'median','mediff1d','mpolyfit','mr_','mvander', + 'median','mr_', 'notmasked_contiguous','notmasked_edges', + 'polyfit', 'row_stack', - 'vstack', + 'vander','vstack', ] from itertools import groupby @@ -579,7 +580,7 @@ def dot(a,b, strict=False): return masked_array(d, mask=m) #............................................................................... -def mediff1d(array, to_end=None, to_begin=None): +def ediff1d(array, to_end=None, to_begin=None): """Return the differences between consecutive elements of an array, possibly with prefixed and/or appended values. @@ -826,7 +827,7 @@ def notmasked_contiguous(a, axis=None): #---- Polynomial fit --- #####-------------------------------------------------------------------------- -def mvander(x, n=None): +def vander(x, n=None): """%s Notes ----- @@ -839,7 +840,7 @@ def mvander(x, n=None): return _vander -def mpolyfit(x, y, deg, rcond=None, full=False): +def polyfit(x, y, deg, rcond=None, full=False): """%s Notes @@ -874,7 +875,7 @@ def mpolyfit(x, y, deg, rcond=None, full=False): if scale != 0 : x = x / scale # solve least squares equation for powers of x - v = mvander(x, order) + v = vander(x, order) c, resids, rank, s = _lstsq(v, y.filled(0), rcond) # warn on rank reduction, which indicates an ill conditioned matrix if rank != order and not full: @@ -892,8 +893,7 @@ def mpolyfit(x, y, deg, rcond=None, full=False): _g = globals() for nfunc in ('vander', 'polyfit'): - mfunc = "m%s" % nfunc - _g[mfunc].func_doc = _g[mfunc].func_doc % getattr(np,nfunc).__doc__ + _g[nfunc].func_doc = _g[nfunc].func_doc % getattr(np,nfunc).__doc__ diff --git a/numpy/ma/mrecords.py b/numpy/ma/mrecords.py index c4975d56b..e38ea3803 100644 --- a/numpy/ma/mrecords.py +++ b/numpy/ma/mrecords.py @@ -349,6 +349,9 @@ The fieldname base is either `_data` or `_mask`.""" def __setitem__(self, indx, value): "Sets the given record to value." MaskedArray.__setitem__(self, indx, value) + if isinstance(indx, basestring): + self._fieldmask[indx] = ma.getmaskarray(value) + #............................................ def __setslice__(self, i, j, value): "Sets the slice described by [i,j] to `value`." diff --git a/numpy/ma/tests/test_extras.py b/numpy/ma/tests/test_extras.py index 74e89f03f..6612e83a1 100644 --- a/numpy/ma/tests/test_extras.py +++ b/numpy/ma/tests/test_extras.py @@ -282,37 +282,37 @@ class Test2DFunctions(NumpyTestCase): c = dot(b,a,False) assert_equal(c, N.dot(b.filled(0),a.filled(0))) - def test_mediff1d(self): + def test_ediff1d(self): "Tests mediff1d" x = masked_array(N.arange(5), mask=[1,0,0,0,1]) difx_d = (x._data[1:]-x._data[:-1]) difx_m = (x._mask[1:]-x._mask[:-1]) - dx = mediff1d(x) + dx = ediff1d(x) assert_equal(dx._data, difx_d) assert_equal(dx._mask, difx_m) # - dx = mediff1d(x, to_begin=masked) + dx = ediff1d(x, to_begin=masked) assert_equal(dx._data, N.r_[0,difx_d]) assert_equal(dx._mask, N.r_[1,difx_m]) - dx = mediff1d(x, to_begin=[1,2,3]) + dx = ediff1d(x, to_begin=[1,2,3]) assert_equal(dx._data, N.r_[[1,2,3],difx_d]) assert_equal(dx._mask, N.r_[[0,0,0],difx_m]) # - dx = mediff1d(x, to_end=masked) + dx = ediff1d(x, to_end=masked) assert_equal(dx._data, N.r_[difx_d,0]) assert_equal(dx._mask, N.r_[difx_m,1]) - dx = mediff1d(x, to_end=[1,2,3]) + dx = ediff1d(x, to_end=[1,2,3]) assert_equal(dx._data, N.r_[difx_d,[1,2,3]]) assert_equal(dx._mask, N.r_[difx_m,[0,0,0]]) # - dx = mediff1d(x, to_end=masked, to_begin=masked) + dx = ediff1d(x, to_end=masked, to_begin=masked) assert_equal(dx._data, N.r_[0,difx_d,0]) assert_equal(dx._mask, N.r_[1,difx_m,1]) - dx = mediff1d(x, to_end=[1,2,3], to_begin=masked) + dx = ediff1d(x, to_end=[1,2,3], to_begin=masked) assert_equal(dx._data, N.r_[0,difx_d,[1,2,3]]) assert_equal(dx._mask, N.r_[1,difx_m,[0,0,0]]) # - dx = mediff1d(x._data, to_end=masked, to_begin=masked) + dx = ediff1d(x._data, to_end=masked, to_begin=masked) assert_equal(dx._data, N.r_[0,difx_d,0]) assert_equal(dx._mask, N.r_[1,0,0,0,0,1]) @@ -362,24 +362,24 @@ class TestPolynomial(NumpyTestCase): # On ndarrays x = numpy.random.rand(10) y = numpy.random.rand(20).reshape(-1,2) - assert_almost_equal(mpolyfit(x,y,3),numpy.polyfit(x,y,3)) + assert_almost_equal(polyfit(x,y,3),numpy.polyfit(x,y,3)) # ON 1D maskedarrays x = x.view(MaskedArray) x[0] = masked y = y.view(MaskedArray) y[0,0] = y[-1,-1] = masked # - (C,R,K,S,D) = mpolyfit(x,y[:,0],3,full=True) + (C,R,K,S,D) = polyfit(x,y[:,0],3,full=True) (c,r,k,s,d) = numpy.polyfit(x[1:], y[1:,0].compressed(), 3, full=True) for (a,a_) in zip((C,R,K,S,D),(c,r,k,s,d)): assert_almost_equal(a, a_) # - (C,R,K,S,D) = mpolyfit(x,y[:,-1],3,full=True) + (C,R,K,S,D) = polyfit(x,y[:,-1],3,full=True) (c,r,k,s,d) = numpy.polyfit(x[1:-1], y[1:-1,-1], 3, full=True) for (a,a_) in zip((C,R,K,S,D),(c,r,k,s,d)): assert_almost_equal(a, a_) # - (C,R,K,S,D) = mpolyfit(x,y,3,full=True) + (C,R,K,S,D) = polyfit(x,y,3,full=True) (c,r,k,s,d) = numpy.polyfit(x[1:-1], y[1:-1,:], 3, full=True) for (a,a_) in zip((C,R,K,S,D),(c,r,k,s,d)): assert_almost_equal(a, a_) diff --git a/numpy/ma/tests/test_mrecords.py b/numpy/ma/tests/test_mrecords.py index cb550a9aa..910bd4234 100644 --- a/numpy/ma/tests/test_mrecords.py +++ b/numpy/ma/tests/test_mrecords.py @@ -120,6 +120,16 @@ class TestMRecords(NumpyTestCase): 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 test_set_mask(self): base = self.base.copy() |