Skip to main content

Resolve a multi dimensional array into fully specified endpoints

I need to turn each end-point in a multi-dimensional array (of any dimension) into a row containing the all the descendant nodes using PHP. In other words, I want to resolve each complete branch in the array. I am not sure how to state this more clearly, so maybe the best way is to give an example.

If I start with an array like:

$arr = array(
 'A'=>array(
    'a'=>array(
        'i'=>1, 
        'j'=>2),
    'b'=>3
 ),
 'B'=>array(
    'a'=>array(
        'm'=>4, 
        'n'=>5),
    'b'=>6
 )
);

There are 6 end points, namely the numbers 1 to 6, in the array and I would like to generate the 6 rows as:

  1. A,a,i,1
  2. A,a,j,2
  3. A,b,2
  4. B,a,m,3
  5. B,a,n,4
  6. B,b,2

Each row contains full path of descendants to the end-point. As the array can have any number of dimensions, this suggested a recursive PHP function and I tried:

function array2Rows($arr, $str='', $out='') {
  if (is_array($arr)) {
    foreach ($arr as $att => $arr1) {
        $str .= ((strlen($str)? ',': '')) . $att;
        $out = array2Rows($arr1, $str, $out);
    }
    echo '<hr />';
  } else {
    $str .= ((strlen($str)? ',': '')) . $arr;
    $out .= ((strlen($out)? '<br />': '')) . $str;
  }
  return $out;
}

The function was called as follows:

echo '<p>'.array2Rows($arr, '', '').'</p>';

The output from this function is:

  1. A,a,i,1
  2. A,a,i,j,2
  3. A,a,b,3
  4. A,B,a,m,4
  5. A,B,a,m,n,5
  6. A,B,a,b,6

Which apart from the first value is incorrect because values on some of the nodes are repeated. I have tried a number of variations of the recursive function and this is the closest I can get.

I will welcome any suggestions for how I can get a solution to this problem and apologize if the statement of the problem is not very clear.



source https://stackoverflow.com/questions/70147772/resolve-a-multi-dimensional-array-into-fully-specified-endpoints

Comments

Popular posts from this blog

ValueError: X has 10 features, but LinearRegression is expecting 1 features as input

So, I am trying to predict the model but its throwing error like it has 10 features but it expacts only 1. So I am confused can anyone help me with it? more importantly its not working for me when my friend runs it. It works perfectly fine dose anyone know the reason about it? cv = KFold(n_splits = 10) all_loss = [] for i in range(9): # 1st for loop over polynomial orders poly_order = i X_train = make_polynomial(x, poly_order) loss_at_order = [] # initiate a set to collect loss for CV for train_index, test_index in cv.split(X_train): print('TRAIN:', train_index, 'TEST:', test_index) X_train_cv, X_test_cv = X_train[train_index], X_test[test_index] t_train_cv, t_test_cv = t[train_index], t[test_index] reg.fit(X_train_cv, t_train_cv) loss_at_order.append(np.mean((t_test_cv - reg.predict(X_test_cv))**2)) # collect loss at fold all_loss.append(np.mean(loss_at_order)) # collect loss at order plt.plot(np.log(al...

Sorting large arrays of big numeric stings

I was solving bigSorting() problem from hackerrank: Consider an array of numeric strings where each string is a positive number with anywhere from to digits. Sort the array's elements in non-decreasing, or ascending order of their integer values and return the sorted array. I know it works as follows: def bigSorting(unsorted): return sorted(unsorted, key=int) But I didnt guess this approach earlier. Initially I tried below: def bigSorting(unsorted): int_unsorted = [int(i) for i in unsorted] int_sorted = sorted(int_unsorted) return [str(i) for i in int_sorted] However, for some of the test cases, it was showing time limit exceeded. Why is it so? PS: I dont know exactly what those test cases were as hacker rank does not reveal all test cases. source https://stackoverflow.com/questions/73007397/sorting-large-arrays-of-big-numeric-stings

How to load Javascript with imported modules?

I am trying to import modules from tensorflowjs, and below is my code. test.html <!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <title>Document</title </head> <body> <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@2.0.0/dist/tf.min.js"></script> <script type="module" src="./test.js"></script> </body> </html> test.js import * as tf from "./node_modules/@tensorflow/tfjs"; import {loadGraphModel} from "./node_modules/@tensorflow/tfjs-converter"; const MODEL_URL = './model.json'; const model = await loadGraphModel(MODEL_URL); const cat = document.getElementById('cat'); model.execute(tf.browser.fromPixels(cat)); Besides, I run the server using python -m http.server in my command prompt(Windows 10), and this is the error prompt in the console log of my browser: Failed to loa...