uproot.interpretation.library.NumPy — Uproot documentation

# uproot.interpretation.library.NumPy

Defined in uproot.interpretation.library on line 169.

Inheritance order:
uproot.interpretation.library.Library

class uproot.interpretation.library.NumPy

  A uproot.interpretation.library.Library that presents `TBranch` data as NumPy arrays. The standard name for this library is `"np"`.

  The single-`TBranch` form for this library is a `numpy.ndarray`. If the data are non-numerical, they will be converted into Python objects and stored in an array with `dtype="O"`. This is inefficient, but it is the minimal-dependency option for Python.

  The “group” behavior for this library is:

  - `how=dict` or `how=None`: a dict of str → array, mapping the names to arrays.

  - `how=tuple`: a tuple of arrays, in the order requested. (Names are lost.)

  - `how=list`: a list of arrays, in the order requested. (Names are lost.)

  Since NumPy arrays are not indexed, `global_index` has no effect.

## imported

Inherited from uproot.interpretation.library.Library.

NumPy.imported

## empty

Inherited from uproot.interpretation.library.Library.

NumPy.empty(shape, dtype)
  Parameters:

    - shape (tuple of int) – NumPy array `shape`. (The first item must be zero.)

    - dtype (`numpy.dtype` or its constructor argument) – NumPy array `dtype`.

  Returns an empty NumPy-like array.

## zeros

Inherited from uproot.interpretation.library.Library.

NumPy.zeros(shape, dtype)
  Parameters:

    - shape (tuple of int) – NumPy array `shape`. (The first item must be zero.)

    - dtype (`numpy.dtype` or its constructor argument) – NumPy array `dtype`.

  Returns a NumPy-like array of zeros.

## finalize

Inherited from uproot.interpretation.library.Library.

NumPy.finalize(array, branch, interpretation, entry_start, entry_stop)
  Parameters:

    - array (array) – Internal, temporary, trimmed array. If this is a NumPy array, it may be identical to the output array.

    - branch (uproot.TBranch) – The `TBranch` that is represented by this array.

    - interpretation (uproot.interpretation.Interpretation) – The interpretation that produced the `array`.

    - entry_start (int) – First entry that is included in the output.

    - entry_stop (int) – FIrst entry that is excluded (one greater than the last entry that is included) in the output.

  Create a library-appropriate output array for this temporary `array`.

  This array would represent one `TBranch` (i.e. not a “group”).

## group

Inherited from uproot.interpretation.library.Library.

NumPy.group(arrays, expression_context, how)
  Parameters:

    - arrays (dict of str → array) – Mapping from names to finalized array objets to combine into a group.

    - expression_context (list of (str, dict) tuples) – Expression strings and a dict of metadata about each.

    - how (None, str, or container type) – Library-dependent instructions for grouping. The only recognized container types are `tuple`, `list`, and `dict`. Note that the container type itself must be passed as `how`, not an instance of that type (i.e. `how=tuple`, not `how=()`).

  Combine the finalized `arrays` into a library-appropriate group type.

## global_index

Inherited from uproot.interpretation.library.Library.

NumPy.global_index(array, global_offset)
  Parameters:

    - array (array) – The library-appropriate array whose global index needs adjustment.

    - global_offset (int) – A number to add to the global index of `array` to correct it.

  Apply in-place corrections to the global index of `array` by adding `global_offset`.

  Even though the operation is performed in-place, this method returns the `array`.

## concatenate

Inherited from uproot.interpretation.library.Library.

NumPy.concatenate(all_arrays)
  Parameters:

    all_arrays (list of arrays) – A list of library-appropriate arrays that need to be concatenated.

  Returns a concatenated version of `all_arrays`.