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NumPy: Logic functions routines

Logic functions routines

Truth value testing
Name Description Syntax
all() Test whether all array elements along a given axis evaluate to True. numpy.all(a, axis=None, out=None, keepdims=<no value>)
any() Test whether any array element along a given axis evaluates to True. numpy.any(a, axis=None, out=None, keepdims=<no value>)
Array contents
Name Description Syntax
isfinite() Test element-wise for finiteness (not infinity or not Not a Number). numpy.isfinite(x, /, out=None, *, where=True, casting='same_kind', order='K',
dtype=None, subok=True[, signature, extobj]) = <ufunc 'isfinite'>
isinf() Test element-wise for positive or negative infinity. numpy.isinf(x, /, out=None, *, where=True, casting='same_kind',
order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'isinf'>
isnan() Test element-wise for NaN and return result as a boolean array. numpy.isnan(x, /, out=None, *, where=True, casting='same_kind', order='K',
dtype=None, subok=True[, signature, extobj]) = <ufunc 'isnan'>
isnat() Test element-wise for NaT (not a time) and return result as a boolean array. numpy.isnat(x, /, out=None, *, where=True, casting='same_kind',
order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'isnat'>
isneginf() Test element-wise for negative infinity, return result as bool array. numpy.isneginf(x, out=None)
isposinf() Test element-wise for positive infinity, return result as bool array. numpy.isposinf(x, out=None)
Array type testing
Name Description Syntax
iscomplex() Returns a bool array, where True if input element is complex. numpy.iscomplex(x)
iscomplexobj() Check for a complex type or an array of complex numbers. numpy.iscomplexobj(x)
isfortran() Returns True if the array is Fortran contiguous but not C contiguous. numpy.isfortran(a)
isreal() Returns a bool array, where True if input element is real. numpy.isreal(x)
isrealobj() Return True if x is a not complex type or an array of complex numbers. numpy.isrealobj(x)
isscalar() Returns True if the type of num is a scalar type. numpy.isscalar(num)
Logical operations
Name Description Syntax
logical_and() Compute the truth value of x1 AND x2 element-wise. numpy.logical_and(x1, x2, /, out=None, *, where=True, casting='same_kind',
order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'logical_and'>
logical_or() Compute the truth value of x1 OR x2 element-wise. numpy.logical_or(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K',
dtype=None, subok=True[, signature, extobj]) = <ufunc 'logical_or'>
logical_not() Compute the truth value of NOT x element-wise. numpy.logical_not(x, /, out=None, *, where=True, casting='same_kind',
order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'logical_not'>
logical_xor() Compute the truth value of x1 XOR x2, element-wise. numpy.logical_xor(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K',
dtype=None, subok=True[, signature, extobj]) = <ufunc 'logical_xor'>
Comparison
Name Description Syntax
allclose() Returns True if two arrays are element-wise equal within a tolerance. numpy.allclose(a, b, rtol=1e-05, atol=1e-08, equal_nan=False)
isclose() Returns a boolean array where two arrays are element-wise equal within a tolerance. numpy.isclose(a, b, rtol=1e-05, atol=1e-08, equal_nan=False)
array_equal() True if two arrays have the same shape and elements, False otherwise. numpy.array_equal(a1, a2)
array_equiv() Returns True if input arrays are shape consistent and all elements equal. numpy.array_equiv(a1, a2)
greater() Return the truth value of (x1 > x2) element-wise. numpy.greater(x1, x2, /, out=None, *, where=True, casting='same_kind',
order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'greater'>
greater_equal() Return the truth value of (x1 >= x2) element-wise. numpy.greater_equal(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K',
dtype=None, subok=True[, signature, extobj]) = <ufunc 'greater_equal'>
less() Return the truth value of (x1 < x2) element-wise. numpy.less(x1, x2, /, out=None, *, where=True, casting='same_kind',
order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'less'>
less_equal() Return the truth value of (x1 =< x2) element-wise. numpy.less_equal(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K',
dtype=None, subok=True[, signature, extobj]) = <ufunc 'less_equal'>
equal() Return (x1 == x2) element-wise. numpy.equal(x1, x2, /, out=None, *, where=True, casting='same_kind',
order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'equal'>
not_equal() Return (x1 != x2) element-wise. numpy.not_equal(x1, x2, /, out=None, *, where=True, casting='same_kind',
order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'not_equal'>

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