numpy.source

numpy.c_

# Indexing routines¶

Indexing

## Generating index arrays¶

 `c_` Translates slice objects to concatenation along the second axis. `r_` Translates slice objects to concatenation along the first axis. `s_` A nicer way to build up index tuples for arrays. `nonzero`(a) Return the indices of the elements that are non-zero. `where`(condition, [x, y]) Return elements, either from x or y, depending on condition. `indices`(dimensions[, dtype]) Return an array representing the indices of a grid. `ix_`(*args) Construct an open mesh from multiple sequences. `ogrid` nd_grid instance which returns an open multi-dimensional “meshgrid”. `ravel_multi_index`(multi_index, dims[, mode, …]) Converts a tuple of index arrays into an array of flat indices, applying boundary modes to the multi-index. `unravel_index`(indices, dims[, order]) Converts a flat index or array of flat indices into a tuple of coordinate arrays. `diag_indices`(n[, ndim]) Return the indices to access the main diagonal of an array. `diag_indices_from`(arr) Return the indices to access the main diagonal of an n-dimensional array. `mask_indices`(n, mask_func[, k]) Return the indices to access (n, n) arrays, given a masking function. `tril_indices`(n[, k, m]) Return the indices for the lower-triangle of an (n, m) array. `tril_indices_from`(arr[, k]) Return the indices for the lower-triangle of arr. `triu_indices`(n[, k, m]) Return the indices for the upper-triangle of an (n, m) array. `triu_indices_from`(arr[, k]) Return the indices for the upper-triangle of arr.

## Indexing-like operations¶

 `take`(a, indices[, axis, out, mode]) Take elements from an array along an axis. `take_along_axis`(arr, indices, axis) Take values from the input array by matching 1d index and data slices. `choose`(a, choices[, out, mode]) Construct an array from an index array and a set of arrays to choose from. `compress`(condition, a[, axis, out]) Return selected slices of an array along given axis. `diag`(v[, k]) Extract a diagonal or construct a diagonal array. `diagonal`(a[, offset, axis1, axis2]) Return specified diagonals. `select`(condlist, choicelist[, default]) Return an array drawn from elements in choicelist, depending on conditions. `lib.stride_tricks.as_strided`(x[, shape, …]) Create a view into the array with the given shape and strides.

## Inserting data into arrays¶

 `place`(arr, mask, vals) Change elements of an array based on conditional and input values. `put`(a, ind, v[, mode]) Replaces specified elements of an array with given values. `put_along_axis`(arr, indices, values, axis) Put values into the destination array by matching 1d index and data slices. `putmask`(a, mask, values) Changes elements of an array based on conditional and input values. `fill_diagonal`(a, val[, wrap]) Fill the main diagonal of the given array of any dimensionality.

## Iterating over arrays¶

 `nditer` Efficient multi-dimensional iterator object to iterate over arrays. `ndenumerate`(arr) Multidimensional index iterator. `ndindex`(*shape) An N-dimensional iterator object to index arrays. `nested_iters` Create nditers for use in nested loops `flatiter` Flat iterator object to iterate over arrays. `lib.Arrayterator`(var[, buf_size]) Buffered iterator for big arrays.