Using numpy.min to get minimum value in a float64 type numpy array but got error 'numpy.float64' object cannot be interpreted as an index

Question

I was trying to get the minimum value between tr_loss and val_loss using numpy.min.

np.min(np.min(tr_loss), np.min(val_loss))

The tr_loss and val_loss are numpy arrays that returned from model.fit in keras.

'tr_loss': [0.84579472304284575, 0.77913203762769701, 0.76625978895127778, 0.75814685845822094, 0.75486504282504319, 0.74989902700781819, 0.74833822523653504, 0.74695981823652979, 0.74483485338091848, 0.74150521695762872]

'val_loss': [0.76307238261103627, 0.75163262798049202, 0.74257619685517573, 0.75038179922993964, 0.72936564083517463, 0.73233943380595634, 0.72518632964207708, 0.74037907492741795, 0.7237680551772061, 0.73257833277079065]}

But I keep getting this error

TypeError                                 Traceback (most recent call last)
<ipython-input-35-e82cb24a3b5d> in <module>()
      3 
      4 
----> 5 y_ax_min = np.min(np.min(tr_loss), np.min(val_loss)) - .1
      6 y_ax_max = np.max(np.max(tr_loss), np.max(val_loss)) + .1
      7 plt.figure(figsize=(8, 8),dpi=500)

D:\Anaconda\envs\py27\lib\site-packages\numpy\core\fromnumeric.pyc in 
amin(a, axis, out, keepdims)
   2347             pass
   2348         else:
-> 2349             return amin(axis=axis, out=out, **kwargs)
   2350 
   2351     return _methods._amin(a, axis=axis,

D:\Anaconda\envs\py27\lib\site-packages\numpy\core\_methods.pyc in _amin(a, 
axis, out, keepdims)
     27 
     28 def _amin(a, axis=None, out=None, keepdims=False):
---> 29     return umr_minimum(a, axis, None, out, keepdims)
     30 
     31 def _sum(a, axis=None, dtype=None, out=None, keepdims=False):

TypeError: 'numpy.float64' object cannot be interpreted as an index

Does anyone know where is the problem?

Start by reading help(numpy.min). You aren't calling it as intended. The second argument should be an axis. It's not like the built in min function. — ChrisP
– ChrisP, Commented Apr 14, 2017 at 20:16
When comparing two elements, numpy.minimum should be used instead of numpy.min. @ChrisP Thanks. — Jiaying Li
– Jiaying Li, Commented Apr 14, 2017 at 20:34

lemon · Accepted Answer · 2022-06-02 12:26:19Z

3

When comparing two elements, numpy.minimum should be used instead of numpy.min.

The comments on this question helped me. Thanks to all those who commented.

edited Jun 2, 2022 at 12:26

lemon

15.6k6 gold badges23 silver badges42 bronze badges

answered May 30, 2022 at 4:50

Bhanu Prakash

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