回答此问题可获得 20 贡献值,回答如果被采纳可获得 50 分。
<p>我有一个由<code>xdata</code>和<code>ydata</code>组成的数据集,我想对其拟合多项式,但出于某种原因,拟合结果取决于数据集的<code>dtype</code>,即使数据的实际值保持<em>不变</em>。我理解,如果您将<code>dtype</code>例如从<code>float</code>更改为<code>int</code>,可能会丢失一些信息,但在这种情况下,我将从<code>'f4'</code>转换为<code>'f8'</code>,因此不会丢失任何信息,这就是我感到困惑的原因。这是怎么回事</p>
<pre><code>import numpy as np
from numpy.polynomial import polynomial
x32 = np.array([
1892.8972, 1893.1168, 1893.1626, 1893.4313, 1893.4929, 1895.6392,
1895.7642, 1896.4286, 1896.5693, 1897.313, 1898.4648
], dtype='f4')
y32 = np.array([
510.83655, 489.91592, 486.4508, 469.21814, 465.7902, 388.65576,
385.37637, 369.07236, 365.8301, 349.7118, 327.4062
], dtype='f4')
x64 = x32.astype('f8')
y64 = y32.astype('f8')
a, residuals1, _, _, _ = np.polyfit(x32, y32, 2, full=True)
b, residuals2, _, _, _ = np.polyfit(x64, y64, 2, full=True)
c, (residuals3, _, _, _) = polynomial.polyfit(x32, y32, 2, full=True)
d, (residuals4, _, _, _) = polynomial.polyfit(x64, y64, 2, full=True)
print(residuals1, residuals2, residuals3, residuals4) # [] [195.86309188] [] [195.86309157]
print(a) # [ 3.54575804e+00 -1.34738721e+04 1.28004924e+07]
print(b) # [-8.70836523e-03 7.50419309e-02 3.15525483e+04]
print(c[::-1]) # [ 3.54575804e+00 -1.34738721e+04 1.28004924e+07]
print(d[::-1]) # [-8.7083541e-03 7.5099051e-02 3.1552398e+04 ]
</code></pre>
<p>我也注意到了这个问题,因为我也对残差值感兴趣,结果它们是空的,这导致了我的程序崩溃</p>