numpy.dtype — NumPy v1.11 Manual (original) (raw)
Create a data type object.
A numpy array is homogeneous, and contains elements described by a dtype object. A dtype object can be constructed from different combinations of fundamental numeric types.
| Parameters: | obj Object to be converted to a data type object. align : bool, optional Add padding to the fields to match what a C compiler would output for a similar C-struct. Can be True only if obj is a dictionary or a comma-separated string. If a struct dtype is being created, this also sets a sticky alignment flag isalignedstruct. copy : bool, optional Make a new copy of the data-type object. If False, the result may just be a reference to a built-in data-type object. |
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Examples
Using array-scalar type:
np.dtype(np.int16) dtype('int16')
Structured type, one field name ‘f1’, containing int16:
np.dtype([('f1', np.int16)]) dtype([('f1', '<i2')])
Structured type, one field named ‘f1’, in itself containing a structured type with one field:
np.dtype([('f1', [('f1', np.int16)])]) dtype([('f1', [('f1', '<i2')])])
Structured type, two fields: the first field contains an unsigned int, the second an int32:
np.dtype([('f1', np.uint), ('f2', np.int32)]) dtype([('f1', '<u4'), ('f2', '<i4')])
Using array-protocol type strings:
np.dtype([('a','f8'),('b','S10')]) dtype([('a', '<f8'), ('b', '|S10')])
Using comma-separated field formats. The shape is (2,3):
np.dtype("i4, (2,3)f8") dtype([('f0', '<i4'), ('f1', '<f8', (2, 3))])
Using tuples. int is a fixed type, 3 the field’s shape. voidis a flexible type, here of size 10:
np.dtype([('hello',(np.int,3)),('world',np.void,10)]) dtype([('hello', '<i4', 3), ('world', '|V10')])
Subdivide int16 into 2 int8‘s, called x and y. 0 and 1 are the offsets in bytes:
np.dtype((np.int16, {'x':(np.int8,0), 'y':(np.int8,1)})) dtype(('<i2', [('x', '|i1'), ('y', '|i1')]))
Using dictionaries. Two fields named ‘gender’ and ‘age’:
np.dtype({'names':['gender','age'], 'formats':['S1',np.uint8]}) dtype([('gender', '|S1'), ('age', '|u1')])
Offsets in bytes, here 0 and 25:
np.dtype({'surname':('S25',0),'age':(np.uint8,25)}) dtype([('surname', '|S25'), ('age', '|u1')])
Attributes
| base | |
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| descr | Array-interface compliant full description of the data-type. |
| fields | Dictionary of named fields defined for this data type, or None. |
| hasobject | Boolean indicating whether this dtype contains any reference-counted objects in any fields or sub-dtypes. |
| isalignedstruct | Boolean indicating whether the dtype is a struct which maintains field alignment. |
| isbuiltin | Integer indicating how this dtype relates to the built-in dtypes. |
| isnative | Boolean indicating whether the byte order of this dtype is native to the platform. |
| metadata | |
| name | A bit-width name for this data-type. |
| names | Ordered list of field names, or None if there are no fields. |
| shape | Shape tuple of the sub-array if this data type describes a sub-array, and () otherwise. |
| str | The array-protocol typestring of this data-type object. |
| subdtype | Tuple (item_dtype, shape) if this dtype describes a sub-array, and None otherwise. |
Methods
| newbyteorder([new_order]) | Return a new dtype with a different byte order. |
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