Numpy-array-attributes
提供:Dev Guides
NumPy-配列属性
この章では、NumPyのさまざまな配列属性について説明します。
ndarray.shape
この配列属性は、配列の次元で構成されるタプルを返します。 配列のサイズ変更にも使用できます。
例1
import numpy as np
a = np.array([[print a.shape
出力は次のとおりです-
(2, 3)
例2
# this resizes the ndarray
import numpy as np
a = np.array([[a.shape = (3,2)
print a
出力は次のとおりです-
[[Example 3
NumPy also provides a reshape function to resize an array.
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numpy as np a = np.array([[b = a.reshape(3,2)print bとしてインポート
The output is as follows −
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[[ndarray.ndim
この配列属性は、配列の次元数を返します。
例1
# an array of evenly spaced numbers
import numpy as np
a = np.arange(24)
print a
出力は次のとおりです-
[0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23]
例2
# this is one dimensional array
import numpy as np
a = np.arange(24)
a.ndim
# now reshape it
b = a.reshape(2,4,3)
print b
# b is having three dimensions
出力は次のとおりです-
[[numpy.itemsize
This array attribute returns the length of each element of array in bytes.
==== Example 1
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#配列のdtypeはint8(1バイト)numpyをインポートnp x = np.array([1,2,3,4,5]、dtype = np.int8)print x.itemsize
The output is as follows −
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1
==== Example 2
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#配列のdtypeはfloat32(4バイト)になりましたnpとしてインポートnumpy = np.array([1,2,3,4,5]、dtype = np.float32)print x.itemsize
The output is as follows −
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4
=== numpy.flags
The ndarray object has the following attributes. Its current values are returned by this function.
[width="100%",cols="50%,50%",options="header",]
|===
|Sr.No. |Attribute & Description
|1 a|
*C_CONTIGUOUS (C)*
The data is in a single, C-style contiguous segment
|2 a|
*F_CONTIGUOUS (F)*
The data is in a single, Fortran-style contiguous segment
|3 a|
*OWNDATA (O)*
The array owns the memory it uses or borrows it from another object
|4 a|
*WRITEABLE (W)*
The data area can be written to. Setting this to False locks the data, making it read-only
|5 a|
*ALIGNED (A)*
The data and all elements are aligned appropriately for the hardware
|6 a|
*UPDATEIFCOPY (U)*
This array is a copy of some other array. When this array is deallocated, the base array will be updated with the contents of this array
|===
==== Example
The following example shows the current values of flags.
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numpyをnp x = np.array([1,2,3,4,5])としてインポートx.flagsを出力
The output is as follows −
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C_CONTIGUOUS:True F_CONTIGUOUS:True OWNDATA:True WRITEABLE:True ALIGNED:True UPDATEIFCOPY:False