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-rw-r--r--numpy/add_newdocs.py88
1 files changed, 0 insertions, 88 deletions
diff --git a/numpy/add_newdocs.py b/numpy/add_newdocs.py
index 62b63454e..a882bf1e0 100644
--- a/numpy/add_newdocs.py
+++ b/numpy/add_newdocs.py
@@ -7256,94 +7256,6 @@ add_newdoc('numpy.core.multiarray', 'datetime_data',
numpy.datetime64('2010-01-01T00:00:00','25s')
""")
-##############################################################################
-#
-# nd_grid instances
-#
-##############################################################################
-
-add_newdoc('numpy.lib.index_tricks', 'mgrid',
- """
- `nd_grid` instance which returns a dense multi-dimensional "meshgrid".
-
- An instance of `numpy.lib.index_tricks.nd_grid` which returns an dense
- (or fleshed out) mesh-grid when indexed, so that each returned argument
- has the same shape. The dimensions and number of the output arrays are
- equal to the number of indexing dimensions. If the step length is not a
- complex number, then the stop is not inclusive.
-
- However, if the step length is a **complex number** (e.g. 5j), then
- the integer part of its magnitude is interpreted as specifying the
- number of points to create between the start and stop values, where
- the stop value **is inclusive**.
-
- Returns
- ----------
- mesh-grid `ndarrays` all of the same dimensions
-
- See Also
- --------
- numpy.lib.index_tricks.nd_grid : class of `ogrid` and `mgrid` objects
- ogrid : like mgrid but returns open (not fleshed out) mesh grids
- r_ : array concatenator
-
- Examples
- --------
- >>> np.mgrid[0:5,0:5]
- array([[[0, 0, 0, 0, 0],
- [1, 1, 1, 1, 1],
- [2, 2, 2, 2, 2],
- [3, 3, 3, 3, 3],
- [4, 4, 4, 4, 4]],
- [[0, 1, 2, 3, 4],
- [0, 1, 2, 3, 4],
- [0, 1, 2, 3, 4],
- [0, 1, 2, 3, 4],
- [0, 1, 2, 3, 4]]])
- >>> np.mgrid[-1:1:5j]
- array([-1. , -0.5, 0. , 0.5, 1. ])
-
- """)
-
-add_newdoc('numpy.lib.index_tricks', 'ogrid',
- """
- `nd_grid` instance which returns an open multi-dimensional "meshgrid".
-
- An instance of `numpy.lib.index_tricks.nd_grid` which returns an open
- (i.e. not fleshed out) mesh-grid when indexed, so that only one dimension
- of each returned array is greater than 1. The dimension and number of the
- output arrays are equal to the number of indexing dimensions. If the step
- length is not a complex number, then the stop is not inclusive.
-
- However, if the step length is a **complex number** (e.g. 5j), then
- the integer part of its magnitude is interpreted as specifying the
- number of points to create between the start and stop values, where
- the stop value **is inclusive**.
-
- Returns
- ----------
- mesh-grid `ndarrays` with only one dimension :math:`\\neq 1`
-
- See Also
- --------
- np.lib.index_tricks.nd_grid : class of `ogrid` and `mgrid` objects
- mgrid : like `ogrid` but returns dense (or fleshed out) mesh grids
- r_ : array concatenator
-
- Examples
- --------
- >>> from numpy import ogrid
- >>> ogrid[-1:1:5j]
- array([-1. , -0.5, 0. , 0.5, 1. ])
- >>> ogrid[0:5,0:5]
- [array([[0],
- [1],
- [2],
- [3],
- [4]]), array([[0, 1, 2, 3, 4]])]
-
- """)
-
##############################################################################
#