概述
【Python坑系列】
为了节约空间，使用numpy数组时候采用了float16，结果发现精度远远不达标
默认的floar64是最接近原本浮点数的
a
Out[206]:
array([ 0.00010002,0.00010002,0.00010002],dtype=float16)a = 0.0001 * np.ones(10,np.float32)
a
Out[208]:
array([ 9.99999975e-05,9.99999975e-05,9.99999975e-05],dtype=float32)a = 0.0001 * np.ones(10,np.float64)
a
Out[210]:
array([ 0.0001,0.0001,0.0001])a = 0.9999 * np.ones(10,np.float64)
a
Out[212]:
array([ 0.9999,0.9999,0.9999])
a = 0.0001 * np.ones(10,np.float32)
a
Out[208]:
array([ 9.99999975e-05,9.99999975e-05,9.99999975e-05],dtype=float32)
a = 0.0001 * np.ones(10,np.float64)
a
Out[210]:
array([ 0.0001,0.0001,0.0001])
a = 0.9999 * np.ones(10,np.float64)
a
Out[212]:
array([ 0.9999,0.9999,0.9999])
a = 0.0001 * np.ones(10,np.float32)
a
Out[208]:
array([ 9.99999975e-05,9.99999975e-05,9.99999975e-05],dtype=float32)
a = 0.0001 * np.ones(10,np.float64)
a
Out[210]:
array([ 0.0001,0.0001,0.0001])
a = 0.9999 * np.ones(10,np.float64)
a
Out[212]:
array([ 0.9999,0.9999,0.9999])
总结
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