Python is a wonderfully powerful programming language that created a stir in the programming world after it is launched. Programmers are skeptical after its launched to either use it or not, but today, it is the core of programming. Be it web applications or website pages, Python covers all. Even many beginners are also trying to excel in it. When you work on many projects on daily basis, it is obvious to encounter errors. You may experience a ‘valueerror: zero-size array to reduction operation maximum which has no identity’ error warning.
Every programmer gets irritated when they are programming and the error warning pops up. You don’t need to panic as you are here, and we leave no stone unturned when it comes to helping you resolve the error. Before going to the solution section, have a look at how the error pops up
How the error warning shows up
When you design a table project in Python, you end up with the error warning. Have look at the code
# cl1 is the upper left corner
# cl2 is the bottom right corner
############# FOR THE SATELLITE IMAGE
cl1_x_sat = np.zeros(dim_sat, dtype = 'int')
cl1_y_sat = np.zeros(dim_sat, dtype = 'int')
cl2_x_sat = np.zeros(dim_sat, dtype = 'int')
cl2_y_sat = np.zeros(dim_sat, dtype = 'int')
for i in range(0, dim_sat):
cl1_x_sat[i] = np.round(iceberg_sat['py x min'][i])
cl1_y_sat[i] = np.round(iceberg_sat['py y min'][i])
cl2_x_sat[i] = np.round(iceberg_sat['py x max'][i])
cl2_y_sat[i] = np.round(iceberg_sat['py y max'][i])
sat = T11_april15
gnd = gpri_april15
ice_sat_max = np.zeros(dim_sat)
cl_sat_max = np.zeros(dim_sat)
cl_sat_mean = np.zeros(dim_sat)
for i in range(dim_sat):
ice_sat_max[i] = sat[x_sat[i],y_sat[i]]
cl_sat_mean[i] = np.mean(sat[cl1_x_sat[i]:cl2_x_sat[i],cl1_y_sat[i]:cl2_y_sat[i]])
cl_sat_max[i] = np.max(sat[cl1_x_sat[i]:cl2_x_sat[i],cl1_y_sat[i]:cl2_y_sat[i]])
# we evalute the target to clutter ratio using the mean or the max of the clutter
TCR_sat_mean = ice_sat_max/cl_sat_mean
TCR_sat_max = ice_sat_max/cl_sat_max
Once you run the code, the error warning pops up
Traceback (most recent call last):
File "<ipython-input-5-2483c16a03b9>", line 12, in <module>
cl_sat_max[i] = np.max(sat[cl1_x_sat[i]:cl2_x_sat[i],cl1_y_sat[i]:cl2_y_sat[i]])
File "<__array_function__ internals>", line 6, in amax
File "C:\Users\job2\AppData\Local\Continuum\anaconda3\lib\site-packages\numpy\core\fromnumeric.py", line 2668, in amax
keepdims=keepdims, initial=initial, where=where)
File "C:\Users\job2\AppData\Local\Continuum\anaconda3\lib\site-packages\numpy\core\fromnumeric.py", line 90, in _wrapreduction
return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
ValueError: zero-size array to reduction operation maximum which has no identity
That’s exactly how you land up in an error warning.
Solutions to Fix the Error experience ‘valueerror: zero-size array to reduction operation maximum which has no identity’
The cause of the error is sometimes the gaps in the data. If the ranges added have been plotted with no data, then you get the error as well. In that case, if you use the .min function, then also you end up with the error. You can fix the issue in a few simple ways. Check out the solutions
Solution 1 – Disregard the exception you catch
The solution to fix the error is to disregard the exception you catch. You can have a look at the sample code for reference
Scenario code
ax.set_ylim([y.min()-0.05, y.max()+0.05])
Solution 2 – Check the Dimension
The dimensions you used in the program code should be checked. Missing a range or dimension can return the error warning. Make sure to use the first as well as the second dimension correctly to avoid the error warning.
Conclusion
We have discussed the solutions to fix the error ‘valueerror: zero-size array to reduction operation maximum which has no identity’. Although the error seems tough, solutions to fix it are quite simple.
I hope you find it helpful! I wish you luck!
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Reference Source: https://www.geeksforgeeks.org/python-initialize-empty-array-of-given-length/