Charlie Charlie - 4 years ago 194
Python Question

Test of equality between arrays using in1d function

Before I ask my question, I provide you with the code.

Code



from scipy import *
x = randn(10)
cum_x = cumsum(x)
#The objective is to recover x using cum_x and the diff function.
y = append(cum_x[0],diff(cum_x))
#Now, y should be equal to x but this is not confirmed by the function in1d
test = in1d(x,y)


The variable
test
does not return an array of "True" boolean values even if y and x are clearly the same. What is the problem here?

Thank you in advance.

Answer Source

if you use set_printoptions to increase precision you will see some differences:

from scipy import *
set_printoptions(30)
x = randn(10)
cum_x = cumsum(x)

#The objective is to recover x using cum_x and the diff function.
y = append(cum_x[0], diff(cum_x))
print(x)
print("\n")
print(y)
#Now, y should be equal to x but this is not confirmed by the function in1d
test = in1d(x, y)
print(test)

Output:

[ 0.54816314147543721002620031868   0.14319052613251953554041051575
  0.489110961092741158839913850898 -0.093011827554544138085823590245
 -0.58370623188476589149331630324  -0.40395493550429123486011917521
  0.387387395892057895263604905267  1.001637373359834937147638811439
 -1.486778459872974744726548124163  1.446772274227251076084144187917]


[ 0.54816314147543721002620031868   0.143190526132519591051561747008
  0.48911096109274110332876261964  -0.093011827554544179719187013688
 -0.58370623188476589149331630324  -0.40395493550429123486011917521
  0.387387395892057895263604905267  1.001637373359834937147638811439
 -1.486778459872974744726548124163  1.446772274227251076084144187917]
[ True False False False  True  True  True  True  True  True]

What you probably want is allclose but interestingly setting the dtype to np.float128 or np.longdouble on my ubuntu system does not lose precision and in1d returns True.

 cum_x = cumsum(x,dtype=np.longdouble)
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