[Numpy-discussion] Numpy arrays and slicing comprehension issue

[paul.carrico at free.fr]

 Hi 

Once again I need your help to understand one topic concerning slicing
topic, or in other word I do not understand how it works in that
particular (but common) case; I'm trying to reassign the 4 first values
in an array: 

 	* If I use [:3] I'm expecting to have 4 values (index 0 to 3 included)
 	* Ditto with [0:3]
 	* If I use [3:] I have 2 values as expected (indexes 3 and 4)

Both code and results are presented here after, so this way of thinking
worked so far in other calculations, and it fails here? 

 Thanks 

 Paul 

ps : extraction from the doc
(https://docs.scipy.org/doc/numpy/reference/arrays.indexing.html) 

_[... all indices are zero-based ...]_ 

CODE: 

x = np.random.rand(5); print("x = ",x); 

## test 1 

print("partials =\n %s \nor %s \nor %s" %( x[:3], x[0:3], x[3:]) ) 

print("x[0] : ",x[0]); print("x[1] : ",x[1]); print("x[2] : ",x[2]);
print("x[3] : ",x[3]) 

## test 2 

y = np.ones(4); print("y = ",y) 

x[0:4] = y 

print("x final = ",x) 

PROVIDE: 

x =  [ 0.39921271  0.07097531  0.37044695  0.28078163  0.11590451] 

partials = 

 [ 0.39921271  0.07097531  0.37044695] 

or [ 0.39921271  0.07097531  0.37044695] 

or [ 0.28078163  0.11590451] 

x[0] :  0.39921271184 

x[1] :  0.0709753133926 

x[2] :  0.370446946245 

x[3] :  0.280781629 

y =  [ 1.  1.  1.  1.] 

x final =  [ 1.          1.          1.          1.          0.11590451]
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