numpy.isfortran() in Python Last Updated : 29 Nov, 2018 Comments Improve Suggest changes Like Article Like Report numpy.isfortran(array) : This is a logical function that checks whether array is Fortran contiguous or not. Order : [C-contiguous, F-contiguous, A-contiguous; optional] C-contiguous order in memory(last index varies the fastest). C order means that operating row-rise on the array will be slightly quicker. FORTRAN-contiguous order in memory (first index varies the fastest). F order means that column-wise operations will be faster. ‘A’ means to read / write the elements in Fortran-like index order if, array is Fortran contiguous in memory, C-like order otherwise. Parameters : array : [array_like]Input array Return : True, if array is Fortran; else False Code 1 : Python # Python program explaining # isfortran() function import numpy as np in_array = np.array([[1, 2, 3], [4, 5, 6]], order='C') print ("Input array : \n", in_array) exp2_values = np.exp2(in_array) print ("\nisfortran : ", np.isfortran(in_array)) Output : Input array : [[1 2 3] [4 5 6]] isfortran : False Code 2 : Python # Python program explaining # isfortran() function import numpy as np in_array = np.array([[1, 2, 3], [4, 5, 6]], order='F') print ("Input array : \n", in_array) exp2_values = np.exp2(in_array) print ("\nisfortran : ", np.isfortran(in_array)) Output : Input array : [[1 2 3] [4 5 6]] isfortran : True References : https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.isfortran.html#numpy.isfortran . Comment More infoAdvertise with us Next Article numpy.isfortran() in Python M mohit gupta_omg :) Follow Improve Article Tags : Python Python-numpy Python numpy-Logic Functions Practice Tags : python Similar Reads numpy.isnan() in Python The numpy.isnan() function tests element-wise whether it is NaN or not and returns the result as a boolean array. Syntax : numpy.isnan(array [, out]) Parameters : array : [array_like]Input array or object whose elements, we need to test for infinity out : [ndarray, optional]Output array placed wit 2 min read numpy.isreal() in Python numpy.isreal() tests element-wise whether each value in the input array is a real number (i.e., not complex). It returns a Boolean result as a boolean array. Example:Pythonimport numpy as np a = np.array([1+0j, 2+3j, 5, 4.5, 7j]) res = np.isreal(a) print(res)Output[ True False True True False] Expla 2 min read numpy.isinf() in Python numpy.isinf() test element-wise whether a value is positive or negative infinity. It returns a Boolean array with True where the input is either +inf or -inf and False otherwise. Example:Pythonimport numpy as np a = np.array([1, np.inf, -np.inf, 0, np.nan]) res = np.isinf(a) print(res)Output[False T 2 min read numpy.isfinite() in Python The numpy.isfinite() function tests element-wise whether it is finite or not(not infinity or not Not a Number) and return the result as a boolean array. Syntax : numpy.isfinite(array [, out]) Parameters : array : [array_like]Input array or object whose elements, we need to test for infinity out : 2 min read numpy.isposinf() in Python The numpy.isposinf() function tests element-wise whether it is positive infinity or not and returns the result as a boolean array. Syntax : numpy.isposinf(array, y = None) Parameters:  array : [array_like]Input array or object whose elements, we need to test for infinity. y : [array_like]A boolea 2 min read Like