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Copy file name to clipboardExpand all lines: docs/v2/v2.0.rst
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@@ -128,8 +128,7 @@ Data type encoding
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~~~~~~~~~~~~~~~~~~
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Simple data types are encoded within the array metadata as a string,
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following the :ref:`NumPy array protocol type string (typestr) format
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<numpy:arrays.interface>`. The format
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following the `NumPy array protocol type string (typestr) format <https://numpy.org/doc/stable/reference/arrays.interface.html#the-array-interface-protocol>`_. The format
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consists of 3 parts:
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* One character describing the byteorder of the data (``"<"``: little-endian;
@@ -147,14 +146,12 @@ The byte order MUST be specified. E.g., ``"<f8"``, ``">i4"``, ``"|b1"`` and
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For datetime64 ("M") and timedelta64 ("m") data types, these MUST also include the
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units within square brackets. A list of valid units and their definitions are given in
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the :ref:`NumPy documentation on Datetimes and Timedeltas
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<numpy:arrays.dtypes.dateunits>`.
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the `NumPy documentation on Datetimes and Timedeltas <https://numpy.org/doc/stable/reference/arrays.datetime.html#datetime-units>`_.
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For example, ``"<M8[ns]"`` specifies a datetime64 data type with nanosecond time units.
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Structured data types (i.e., with multiple named fields) are encoded
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as a list of lists, following :ref:`NumPy array protocol type descriptions
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(descr)
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<numpy:arrays.interface>`. Each
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as a list of lists, following `NumPy array protocol type descriptions
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(descr) <https://numpy.org/doc/stable/reference/arrays.interface.html#the-array-interface-protocol>`_. Each
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sub-list has the form ``[fieldname, datatype, shape]`` where ``shape``
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is optional. ``fieldname`` is a string, ``datatype`` is a string
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specifying a simple data type (see above), and ``shape`` is a list of
@@ -532,13 +529,13 @@ initially published to clarify ambiguities and add some missing information.
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* The specification now describes how bytes fill values should be encoded and
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decoded for arrays with a fixed-length byte string data type (`#165
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