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Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/ma/core.py | 32 |
1 files changed, 32 insertions, 0 deletions
diff --git a/numpy/ma/core.py b/numpy/ma/core.py index 90f852e5c..3ab307c53 100644 --- a/numpy/ma/core.py +++ b/numpy/ma/core.py @@ -7096,6 +7096,38 @@ def diag(v, k=0): -------- numpy.diag : Equivalent function for ndarrays. + Examples + -------- + + Create an array with negative values masked: + + >>> import numpy as np + >>> x = np.array([[11.2, -3.973, 18], [0.801, -1.41, 12], [7, 33, -12]]) + >>> masked_x = np.ma.masked_array(x, mask=x < 0) + >>> masked_x + masked_array( + data=[[11.2, --, 18.0], + [0.801, --, 12.0], + [7.0, 33.0, --]], + mask=[[False, True, False], + [False, True, False], + [False, False, True]], + fill_value=1e+20) + + Isolate the main diagonal from the masked array: + + >>> np.ma.diag(masked_x) + masked_array(data=[11.2, --, --], + mask=[False, True, True], + fill_value=1e+20) + + Isolate the first diagonal below the main diagonal: + + >>> np.ma.diag(masked_x, -1) + masked_array(data=[0.801, 33.0], + mask=[False, False], + fill_value=1e+20) + """ output = np.diag(v, k).view(MaskedArray) if getmask(v) is not nomask: |