numpy.array_equal#

numpy.array_equal(a1,a2,equal_nan=False)[source]#

True if two arrays have the same shape and elements, False otherwise.

Parameters:

a1, a2array_like

Input arrays.

equal_nanbool

Whether to compare NaN’s as equal. If the dtype of a1 and a2 iscomplex, values will be considered equal if either the real or theimaginary component of a given value isnan.

Returns:

bbool

Returns True if the arrays are equal.

See also

allclose

Returns True if two arrays are element-wise equal within a tolerance.

array_equiv

Returns True if input arrays are shape consistent and all elements equal.

Examples

>>>importnumpyasnp

>>>np.array_equal([1,2],[1,2])True

>>>np.array_equal(np.array([1,2]),np.array([1,2]))True

>>>np.array_equal([1,2],[1,2,3])False

>>>np.array_equal([1,2],[1,4])False

>>>a=np.array([1,np.nan])>>>np.array_equal(a,a)False

>>>np.array_equal(a,a,equal_nan=True)True

Whenequal_nan is True, complex values with nan components areconsidered equal if either the realor the imaginary components are nan.

>>>a=np.array([1+1j])>>>b=a.copy()>>>a.real=np.nan>>>b.imag=np.nan>>>np.array_equal(a,b,equal_nan=True)True