multidimensional-array

Fortran 90 doesn't keep lower/upper array bounds after copy to another allocatable array

孤者浪人 提交于 2021-01-27 12:21:26
问题 This doesn't work program main implicit none integer :: nx = 3 integer :: ny = 5 integer :: nz = 8 real, allocatable, dimension(:,:,:) :: A real, allocatable, dimension(:,:) :: B allocate(A(nx,0:ny,nz) ) ! ...do something with array A and at some point cope a slice of A to B: B = A(:,:,1) ! in this case B is (1:nx, 1: ny+1) end program main The code above automatically allocates B and copies A(:,:,1) to B. However it doesn't keep the lower/upper bound of 0/ny, instead B has its lower bound to

Convert 2D array to 3D numpy array

我们两清 提交于 2021-01-27 11:31:42
问题 I have a created a numpy array, each element of the array contains an array of the same shape (9,5). What I want is a 3D array. I've tried using np.stack. data = list(map(lambda x: getKmers(x, 9), data)) # getKmers creates a # list of list from a pandas dataframe data1D = np.array(data) # shape (350,) data2D = np.stack(data1D) data1D: array([list([ pdbID AtomNo Type Eta Theta 0 1a9l.pdb 2.0 G 169.225 212.838 1 1a9l.pdb 3.0 G 168.439 206.785 2 1a9l.pdb 4.0 U 170.892 205.845 3 1a9l.pdb 5.0 G

Convert 2D array to 3D numpy array

ぃ、小莉子 提交于 2021-01-27 11:30:57
问题 I have a created a numpy array, each element of the array contains an array of the same shape (9,5). What I want is a 3D array. I've tried using np.stack. data = list(map(lambda x: getKmers(x, 9), data)) # getKmers creates a # list of list from a pandas dataframe data1D = np.array(data) # shape (350,) data2D = np.stack(data1D) data1D: array([list([ pdbID AtomNo Type Eta Theta 0 1a9l.pdb 2.0 G 169.225 212.838 1 1a9l.pdb 3.0 G 168.439 206.785 2 1a9l.pdb 4.0 U 170.892 205.845 3 1a9l.pdb 5.0 G

using array_walk_recursive() for stdClass objects

天涯浪子 提交于 2021-01-27 05:40:48
问题 I have looked through a few answers on here but that don't seem to utilise this method? I have an array of items, and the items are objects. The object can have a key which is 'children' and 'children' is an array of objects etc. Is there a way to achieve this? Example: Array ( [1] => stdClass Object ( [id] => 1 [name] => Steve King [image] => upload/shop/fe7a66254e4249af2b0093efca75a914.jpg [parent] => 0 [children] => Array ( ) ) [2] => stdClass Object ( [id] => 2 [name] => Eden Hall [image]

using array_walk_recursive() for stdClass objects

风流意气都作罢 提交于 2021-01-27 05:40:43
问题 I have looked through a few answers on here but that don't seem to utilise this method? I have an array of items, and the items are objects. The object can have a key which is 'children' and 'children' is an array of objects etc. Is there a way to achieve this? Example: Array ( [1] => stdClass Object ( [id] => 1 [name] => Steve King [image] => upload/shop/fe7a66254e4249af2b0093efca75a914.jpg [parent] => 0 [children] => Array ( ) ) [2] => stdClass Object ( [id] => 2 [name] => Eden Hall [image]

what is uninitialized data in pytorch.empty function

笑着哭i 提交于 2021-01-27 05:33:13
问题 i was going through pytorch tutorial and came across pytorch.empty function. it was mentioned that empty can be used for uninitialized data . But, when i printed it, i got a value. what is the difference between this and pytorch.rand which also generates data(i know that rand generates between 0 and 1). Below is the code i tried a = torch.empty(3,4) print(a) Output: tensor([[ 8.4135e-38, 0.0000e+00, 6.2579e-41, 5.4592e-39], [-5.6345e-08, 2.5353e+30, 5.0447e-44, 1.7020e-41], [ 1.4000e-38, 5

what is uninitialized data in pytorch.empty function

倾然丶 夕夏残阳落幕 提交于 2021-01-27 05:32:23
问题 i was going through pytorch tutorial and came across pytorch.empty function. it was mentioned that empty can be used for uninitialized data . But, when i printed it, i got a value. what is the difference between this and pytorch.rand which also generates data(i know that rand generates between 0 and 1). Below is the code i tried a = torch.empty(3,4) print(a) Output: tensor([[ 8.4135e-38, 0.0000e+00, 6.2579e-41, 5.4592e-39], [-5.6345e-08, 2.5353e+30, 5.0447e-44, 1.7020e-41], [ 1.4000e-38, 5

2D Array extension Swift 3.1.1

怎甘沉沦 提交于 2021-01-27 04:56:23
问题 I am trying to make an Array extension in Swift 3.1.1 that supports the addition of an object to a certain index in a 2D Array even if the array hasn't been populated yet . The extension should also provide the ability to get an object at certain indexPath . I have the code for this in Swift 2 but I don't seem to be able to migrate it to Swift 3. This is the Swift 2 code: extension Array where Element: _ArrayProtocol, Element.Iterator.Element: Any { mutating func addObject(_ anObject :

Is accessing an element of a multidimensional array out of bounds undefined behavior?

纵然是瞬间 提交于 2021-01-27 04:13:10
问题 Pardon the confusing question title, but I was unsure how to phrase it more clearly. In C, accessing an array out of bounds is classified as undefined behavior. However, array elements are guaranteed to be laid out contiguously in memory, and the array subscript operator is syntactic sugar for pointer arithmetic (e.g x[3] == *(x + 3) ). Therefore, I would personally expect the behavior of the code below to be well-defined: int array[10][10]; int i = array[0][15]; // i == array[1][5]? If my

Numpy trim_zeros in 2D or 3D

此生再无相见时 提交于 2021-01-22 10:14:55
问题 How to remove leading / trailing zeros from a NumPy array? Trim_zeros works only for 1D. 回答1: The following function works for any dimension: def trim_zeros(arr, margin=0): ''' Trim the leading and trailing zeros from a N-D array. :param arr: numpy array :param margin: how many zeros to leave as a margin :returns: trimmed array :returns: slice object ''' s = [] for dim in range(arr.ndim): start = 0 end = -1 slice_ = [slice(None)]*arr.ndim go = True while go: slice_[dim] = start go = not np