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I want automatically create some pairs based on the data stored as numpy arrays. In fact, the numbers in my first arrays are numbers of some lines. I want to connect the lines and create surfaces using created pairs. This is the array of lines:

line_no= np.arange (17, 25)

These lines are in two perpendicular directions. I uploaded a fig to show it (they are as blue and red colors). I know where the direction of my lines change and call it as sep.

sep=20

Another data which should be useable is the number of points creating lines. I call it rep.

rep = np.array([3,3,1])

Then, I used the following code to achieve my goal but it is not correct:

start =line_no[0]
N_x = len(rep) - 1
N_y = max(rep) - 1
grid = np.zeros((N_y + 1, N_x + 1, 2))
kxs = [0] + [min(rep[i], rep[i+1]) for i in range(len(rep)-1)]
T_x = sum(kxs)
T_y = sum(rep) - len(rep)
T_total = T_x + T_y
lines = np.arange(start, start+T_total)
lines_before = 0
for i in range(N_x):
    for j in range(N_y, -1, -1):
        if j >= kxs[i+1]:
            continue
        grid[j,i,0] = lines[lines_before]
        lines_before += 1
for i in range(N_x+1):
    for j in range(N_y-1, -1, -1):
        if j < rep[i] - 1:
            grid[j,i,1] = lines[lines_before]
            lines_before += 1
joints=np.array([])
for i in range(N_x - 1):
    for j in range(N_y - 1):
        square = np.append(grid[j:j+2, i, 0], grid[j, i:i+2, 1])
        if all(square):
            new_joints = square
            joints=np.append (new_joints,joints)

In my fig I have two scenarios: A (rep = np.array([3,3,1])) and B (rep = np.array([1,3,3])). For A I want to have the following pairs:

17, 21, 18, 23
18, 22, 19, 24

And for B:

18, 21, 19, 23
19, 22, 20, 24

In reality the distribution of my lines can change. For example, in scenario A, the last line is not creating any surface and in B the first one is not in any surface and in case I may have several lines that are not part of any surface. For example I may have another red line bellow line number 21 which do not make any surface. Thanks for paying attention to my problem. I do appreciate any help in advance.

enter image description here

A more complicated case is also shown in the following. In scenario C I have:

line_no= np.arange (17, 42)
sep=29
rep = np.array([5,4,4,2,2,1])

In scenario D I have:

line_no= np.arange (17, 33)
sep=24
rep = np.array([1,3,4,4])

enter image description here

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1 Answer 1

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Sorry, but I couldn't go through your implementation. Tip for next time onwards- please try to comment your code, it helps.

Anyway, here is somewhat of a readable implementation that gets the job done. But, I advice you to check with more scenarios to verify the scripts validity before making any conclusions.

import numpy as np

line_no = np.arange(17, 25)
sep = 20  # this information is redundant for the problem
nodes = np.array(np.array([1,3,4,4]))

# for generalised implementation hlines start from 0 and vlines start where hlines end
# offset parameter can be used to change the origin or start number of hlines and hence changed the vlines also
offset = 17

# calculate the number of horizontal lines and vertical lines in sequence
hlines = np.array([min(a, b) for a, b in zip(nodes[:-1], nodes[1:])])
# vlines = np.array([max(a, b) - 1 for a, b in zip(nodes[:-1], nodes[1:])])
vlines = nodes - 1

print(f"hlines: {hlines}, vlines: {vlines}")
# nodes = np.array([3, 3, 1]) ---> hlines: [3, 1], vlines: [2, 2]
# nodes = np.array([1, 3, 3]) ---> hlines: [1, 3], vlines: [2, 2]

hlines_no = list(range(sum(hlines)))
vlines_no = list(range(sum(hlines), sum(hlines)+sum(vlines)))

print(f"hlines numbers: {hlines_no}, vlines numbers: {vlines_no}")
# nodes = np.array([3, 3, 1]) ---> hlines numbers: [0, 1, 2, 3], vlines numbers: [4, 5, 6, 7]
# nodes = np.array([1, 3, 3]) ---> hlines numbers: [0, 1, 2, 3], vlines numbers: [4, 5, 6, 7]

cells = []  # to store complete cell tuples
hidx = 0    # to keep track of horizontal lines index
vidx = 0    # to keep track of vertical lines index
previous_cells = 0
current_cells = 0

for LN, RN in zip(nodes[:-1], nodes[1:]):
    # if either the left or right side nodes is equal to 1, implies only 1 horizontal line exists
    # and the horizontal index is updated
    if LN == 1 or RN == 1:
        hidx += 1
    else:
        # to handle just a blank vertical line
        if LN - RN == 1:
            vidx += 1
        # iterate 'cell' number of times
        # number of cells are always 1 less than the minimum of left and right side nodes
        current_cells = min(LN, RN)-1
        if previous_cells != 0 and previous_cells > current_cells:
            vidx += previous_cells - current_cells
        for C in range(current_cells):
            cell = (offset + hlines_no[hidx],
                    offset + vlines_no[vidx],
                    offset + hlines_no[hidx+1],
                    offset + vlines_no[vidx+current_cells])
            hidx += 1
            vidx += 1
            cells.append(cell)
        # skip the last horizontal line in a column
        hidx += 1
        previous_cells = min(LN, RN)-1

print(cells)

Results

# nodes = np.array([3, 3, 1]) ---> [(17, 21, 18, 23), (18, 22, 19, 24)]

# nodes = np.array([1, 3, 3]) ---> [(18, 21, 19, 23), (19, 22, 20, 24)]

# nodes = np.array([5,4,4,2,2,1]) ---> [(17, 31, 18, 34), 
#                                       (18, 32, 19, 35), 
#                                       (19, 33, 20, 36), 
#                                       (21, 34, 22, 37), 
#                                       (22, 35, 23, 38), 
#                                       (23, 36, 24, 39), 
#                                       (25, 39, 26, 40), 
#                                       (27, 40, 28, 41)]

# nodes = np.array([1,3,4,4]) ---> [(18, 25, 19, 27), 
#                                   (19, 26, 20, 28), 
#                                   (21, 27, 22, 30), 
#                                   (22, 28, 23, 31), 
#                                   (23, 29, 24, 32)]

Edit: Updated the code to account for the special case scenarios

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9 Comments

Dear @sai, I do appreciate your solution. Sorry for my late feedback. At the time I was not in front of my desktop and I could not check it. I have just two issues. When I add another line in scenario A bellow the 21, and nodes = np.array([4, 3, 1]), I do not have correct result. And also in reality surfaces do not create on column, they create a grid. For example, in scenario A you can think that there are also two other surfaces in the right hand side of existing two ones: line_no=np.arange(17, 31), sep=23 and nodes = np.array([4, 4, 2, 1]). Thanks for being that much supportive.
Can you add(pictures) other edge case scenarios that the script should satisfy? More information would help me and anyone else on SO to get a complete picture and provide a complete solution.
Dear @sai, I updated my post to show what I want. In advance, I appreciate any contribution.
Dear @sai. I really do appreciate your help. The pooint is that for other cases I am facing errors. For example, let say in scenario D, I remove the first horizontal line (number 17). Then I will have line_no = np.arange(18, 25), sep = 24 and nodes = np.array(np.array([3,4,4])) and still I should have the same surfaces but I face a error : IndexError: list index out of range
Try with vlines = nodes - 1
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