I can take the first element of this array to manually convert it to a 1D array: b = np.reshape(a, (1,np.product(a.shape)))[0] but this requires me to know how many dimensions the original array has (and concatenate [0]'s when working with higher dimensions)

Sep 25, 2012 · I want to convert a 1-dimensional array into a 2-dimensional array by specifying the number of columns in the 2D array. Something that would work like this: > import numpy as np > A = np.arr...

May 11, 2011 · In case of 1D numpy array (rank-1 array) the shape and strides are 1-element tuples and cannot be swapped, and the transpose of such an 1D array returns it unchanged. Instead, you can transpose a "row-vector" (numpy array of shape (1, n)) into a "column-vector" (numpy array of shape (n, 1)). To achieve this you have to first convert your 1D ...

Hi, Thanks for the answer. This is the way I tried the first time, but may be I was not able to explain my question properly. The plot it draws is a continuous lines made by connecting points in ar. I have an 1-D array of 800 data values distributed in (-1,6).

Oct 3, 2009 · @AndersonGreen As I said there's no such thing as a variable declaration in Python. You would create a multidimensional list by taking an empty list and putting other lists inside it or, if the dimensions of the list are known at write-time, you could just write it as a literal like this: my_2x2_list = [[a, b], [c, d]].

Late response and just for the record. You can partition a 1D array using Ckmeans.1d.dp. This method guarantees optimality and it is O(n^2), where n is the num of observations. The implementation is in C++ and there is a wrapper in R.

When growing an array for a significant amount of samples it would be better to either pre-allocate the array (if the total size is known) or to append to a list and convert to an array afterward. Using np.append: b = np.array([0]) for k in range(int(10e4)): b = np.append(b, k) 1.2 s ± 16.1 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

There are several possibilities for concatenating 1D arrays, e.g., import numpy as np np.r_[a, a] np.stack([a, a]).reshape(-1) np.hstack([a, a]) np.concatenate([a, a])

Oct 29, 2022 · If what you are interested is that the flatten array still prints in 3 lines, well, no. You can see here that people who want to do that start with the exact reverse operation: reshape the 1d array into a 2d one. That is a printing problem. Array's value is not how it prints. A 1d array value does not contain the line breaks.

If you wish to combine two 10 element one-dimensional arrays into a two-dimensional array, np.vstack((tp, fp)).T will do it. np.vstack((tp, fp)) will return an array of shape (2, 10), and the T attribute returns the transposed array with shape (10, 2) (i.e., with the two one-dimensional arrays forming columns rather than rows).