擅长:python、mysql、java
<p>尝试以下操作:</p>
<pre class="lang-py prettyprint-override"><code>Gausslist = []
model, params = None, None
for i, peak in enumerate(peak_data[1]):
comp = models.GaussianModel(prefix='g{}_'.format(i))
pars = comp.make_params(center=center_val, amplitude=peak[0]) #Hm, maybe?
if model is None:
model = comp
params = pars
else:
model += comp
params.update(pars)
</code></pre>
<p>现在您应该了解如何使用<code>model</code>,无论<code>peak_data[1]</code>序列中有多少峰值</p>
<p>FWIW,我可能会建议存储峰值数据的<code>x</code>和<code>y</code>值,以便您可以执行以下操作:</p>
<pre class="lang-py prettyprint-override"><code>pars = comp.make_params(center=peak[0], amplitude=peak[1], sigma=1)
</code></pre>
<p>因为这可能会给出更好的起始值</p>