my input is texture2d which is 4 channel one so i have to divide the 2 parts of it kind of slicing how can??
i have tried it creating other mat and tex and copied till half of the texture
Mat slice = imageMat.submat(0,0,image.height, 330);
byte[]…
I am trying slicing but I have the following error message: slice indices must be integers or None or have an __index__ method
descriptors = numpy.fft.fftshift(descriptors)
center_index = len(descriptors) / 2
descriptors = descriptors[center_index -…
Consider the following:
import numpy as np
arr = np.arange(3 * 4 * 5).reshape((3, 4, 5))
If I slice arr using slices, I get, e.g.:
arr[:, 0:2, :].shape
# (3, 2, 5)
If now I slice arr using a mixture of slice() and tuple(), I get:
arr[:, (0, 1),…
I have a 2D array of (10,24) and a 1D array of (10,) shape.
I want to slice a 2D array using 1D array such that my resultant array will be (10,24) but the values are sliced from indices in 1D array onwards.
import numpy as np
x1 =…
I have a multidimensional array of this shape:
(2, 200, 2, 3, 3, 114)
I would like to extract a specific set of values from it using this command:
pab[0][:][0][0][0][i]
So basically I need each value iterated over the second dimension for fixes…
I have a data frame as follows,
df2 = pd.DataFrame({'a' : ['one', 'one', 'two', 'three', 'two', 'one', 'six'],
'b' : ['x', 'y', 'y', 'x', 'y', 'x', 'x'],
'c' : np.random.randn(7)})
I want to select data from…
I'm operating on a numpy 2-d array and trying to find some way to access different slices per row. Preferably exploiting numpy broadcasting in such a way that I pass an array of slices like follows:
A =…
I have 2 lists of x and y coordinate that are independently generated, with a/h amount of points between 0 and a.
x = np.linspace(0, a, a/h)
y = np.linspace(0, d, d/h)
when a/h is such that 0 increases to a in steps of integers i.e. [0,1,2,..,a].…
I have a bunch of numpy arrays that can differ in shape:
[[1, 1, 1, 1, 1],
[1, 1, 1, 1, 1],
[1, 1, 1, 1, 1],
[1, 1, 1, 1, 1]]
I need to select and store the indices into a variable so that I can change the array into:
[[1, 1, 1, 1, 1],
[1, 1,…
I'm working with a 3D array of which the index array is a 200x200 binary array (for classification). This array contains either 0 or 1 and I need to use this array select a random 1000 locations of 0 and a random 1000 locations of 1 in the 3D array.…
Here I have a matrix a=np.array([[1,2,3,4,5],[6,7,8,9,10],[11,12,13,14,15]])
I want to select all rows, but the column I want to select is from the first to the third one.
It should be [[1,2,3],[6,7,8],[11,12,13]]
However, I have ever tried…
Why is slicing using "colon and comma" different than using a collection of indexes?
Here is an example of what I expected to yield the same result but but it does not:
import numpy as np
a =…
I have a 3d array in numpy that I would like to index on two of these axes. For one of the axes I am using a simple integer index, whereas on the other axis I use a list indexing. If I apply the indexes separately, the result is different from when…
I'm looking for the most idiomatic and performant way to slice an array of dimension N with an array of dimension N-1 that represents the index of the last dimension to slice. The output would have dimension N-1.
As an example:
import numpy as…