diff options
Diffstat (limited to 'numpy/ma/tests/test_extras.py')
| -rw-r--r-- | numpy/ma/tests/test_extras.py | 26 |
1 files changed, 13 insertions, 13 deletions
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_) |