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| author | Allan Haldane <allan.haldane@gmail.com> | 2015-01-16 23:53:41 -0500 |
|---|---|---|
| committer | Allan Haldane <allan.haldane@gmail.com> | 2015-01-22 17:36:43 -0500 |
| commit | 1bd0b4e8f176cd80e81b5f50832db5f8ba1ee1e9 (patch) | |
| tree | fce876400e049c7927cfe4b62ee4d1ca00a8ed7b /doc/source/reference/internals.code-explanations.rst | |
| parent | b69035e8ea28bd759b929822aaba544d3c5f8c30 (diff) | |
| download | numpy-1bd0b4e8f176cd80e81b5f50832db5f8ba1ee1e9.tar.gz | |
DOC: improve record/structured array nomenclature & guide
This update adds a section better describing record arrays in the user
guide (numpy/doc/structured_arrays.py).
It also corrects nomenclature, such that "structured array" refers to
ndarrays with structured dtype, "record array" refers to modified
ndarrays as created by np.rec.array, and "recarray" refers to ndarrays
viewed as np.recarray. See the note at the end of the structured
array user guide.
Diffstat (limited to 'doc/source/reference/internals.code-explanations.rst')
| -rw-r--r-- | doc/source/reference/internals.code-explanations.rst | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/doc/source/reference/internals.code-explanations.rst b/doc/source/reference/internals.code-explanations.rst index 580661cb3..f01300e25 100644 --- a/doc/source/reference/internals.code-explanations.rst +++ b/doc/source/reference/internals.code-explanations.rst @@ -74,9 +74,9 @@ optimizations that by-pass this mechanism, but the point of the data- type abstraction is to allow new data-types to be added. One of the built-in data-types, the void data-type allows for -arbitrary records containing 1 or more fields as elements of the +arbitrary structured types containing 1 or more fields as elements of the array. A field is simply another data-type object along with an offset -into the current record. In order to support arbitrarily nested +into the current structured type. In order to support arbitrarily nested fields, several recursive implementations of data-type access are implemented for the void type. A common idiom is to cycle through the elements of the dictionary and perform a specific operation based on @@ -184,7 +184,7 @@ The array scalars also offer the same methods and attributes as arrays with the intent that the same code can be used to support arbitrary dimensions (including 0-dimensions). The array scalars are read-only (immutable) with the exception of the void scalar which can also be -written to so that record-array field setting works more naturally +written to so that structured array field setting works more naturally (a[0]['f1'] = ``value`` ). |