smarty assign multidimensional array

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Smarty assign and display two dimensional array

I want to get a two dimensional array's data and display it in a html file using smarty: The idea is as following: my array contains several arrays everyone contains the category name in the first offset and the attached links to this category

2-file html

2 Answers 2

Assuming you use Smarty 3 (you haven't mentioned anything about Smarty 2) you can use the following code:

Output for this will be:

As you mentioned in comment you want solution for Smarty 2 you need to use in you Smarty template file:

This will give you output:

(exactly the same as the one in Smarty 3)

Thanks it is a great solution would like to mark it as accepted answer it's only I need a solution for smarty 2.6... my mistake I know since I haven't mentioned the smarty version in my question – Amani Ben Azzouz Sep 17, 2014 at 8:37

I'd refactor the data array to use the category name as a key.

Then you can use it easily in Smarty

It is much easier to use that way.

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Need help with PHP Smarty Multi Dimensional Array

I am really in mess as I am unable to solve problem with Smarty Multi Dimension array.

Below is the way I want to execute Smarty.

First of all I will list all customers. Than I want list of all items purchased by that customer. I have two tables inside mysql (customer, sale). In Customer table only information related to his name and email is stored. While in sale table information related to item, price and customer is sold.

Below is the way I will execute my smarty.

John -Item1 -Item2 -Item3

David -Item5 -Item2 -Item7

In PHP File I have added below things.

In class file I am fetching content through below script for item list inside each customer

In .tpl file below code is their.

So, what is your problem anyway? Is it that the template display incorrect data, or errors occur?

We're a friendly, industry-focused community of developers, IT pros, digital marketers, and technology enthusiasts meeting, networking, learning, and sharing knowledge.

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The N-dimensional array ( ndarray ) #

An ndarray is a (usually fixed-size) multidimensional container of items of the same type and size. The number of dimensions and items in an array is defined by its shape , which is a tuple of N non-negative integers that specify the sizes of each dimension. The type of items in the array is specified by a separate data-type object (dtype) , one of which is associated with each ndarray.

As with other container objects in Python, the contents of an ndarray can be accessed and modified by indexing or slicing the array (using, for example, N integers), and via the methods and attributes of the ndarray .

Different ndarrays can share the same data, so that changes made in one ndarray may be visible in another. That is, an ndarray can be a “view” to another ndarray, and the data it is referring to is taken care of by the “base” ndarray. ndarrays can also be views to memory owned by Python strings or objects implementing the buffer or array interfaces.

A 2-dimensional array of size 2 x 3, composed of 4-byte integer elements:

The array can be indexed using Python container-like syntax:

For example slicing can produce views of the array:

Constructing arrays #

New arrays can be constructed using the routines detailed in Array creation routines , and also by using the low-level ndarray constructor:

Indexing arrays #

Arrays can be indexed using an extended Python slicing syntax, array[selection] . Similar syntax is also used for accessing fields in a structured data type .

Array Indexing .

Internal memory layout of an ndarray #

An instance of class ndarray consists of a contiguous one-dimensional segment of computer memory (owned by the array, or by some other object), combined with an indexing scheme that maps N integers into the location of an item in the block. The ranges in which the indices can vary is specified by the shape of the array. How many bytes each item takes and how the bytes are interpreted is defined by the data-type object associated with the array.

A segment of memory is inherently 1-dimensional, and there are many different schemes for arranging the items of an N -dimensional array in a 1-dimensional block. NumPy is flexible, and ndarray objects can accommodate any strided indexing scheme . In a strided scheme, the N-dimensional index $(n_0, n_1, ..., n_{N-1})$ corresponds to the offset (in bytes):

from the beginning of the memory block associated with the array. Here, $s_k$ are integers which specify the strides of the array. The column-major order (used, for example, in the Fortran language and in Matlab ) and row-major order (used in C) schemes are just specific kinds of strided scheme, and correspond to memory that can be addressed by the strides:

where $d_j$ = self.shape[j] .

Both the C and Fortran orders are contiguous , i.e., single-segment, memory layouts, in which every part of the memory block can be accessed by some combination of the indices.

Contiguous arrays and single-segment arrays are synonymous and are used interchangeably throughout the documentation.

While a C-style and Fortran-style contiguous array, which has the corresponding flags set, can be addressed with the above strides, the actual strides may be different. This can happen in two cases:

If self.shape[k] == 1 then for any legal index index[k] == 0 . This means that in the formula for the offset $n_k = 0$ and thus $s_k n_k = 0$ and the value of $s_k$ = self.strides[k] is arbitrary. If an array has no elements ( self.size == 0 ) there is no legal index and the strides are never used. Any array with no elements may be considered C-style and Fortran-style contiguous.

Point 1. means that self and self.squeeze() always have the same contiguity and aligned flags value. This also means that even a high dimensional array could be C-style and Fortran-style contiguous at the same time.

An array is considered aligned if the memory offsets for all elements and the base offset itself is a multiple of self.itemsize . Understanding memory-alignment leads to better performance on most hardware.

It does not generally hold that self.strides[-1] == self.itemsize for C-style contiguous arrays or self.strides[0] == self.itemsize for Fortran-style contiguous arrays is true.

NPY_RELAXED_STRIDES_DEBUG=1 can be used to help find errors when incorrectly relying on the strides in C-extension code (see below warning).

Data in new ndarrays is in the row-major (C) order, unless otherwise specified, but, for example, basic array slicing often produces views in a different scheme.

Several algorithms in NumPy work on arbitrarily strided arrays. However, some algorithms require single-segment arrays. When an irregularly strided array is passed in to such algorithms, a copy is automatically made.

Array attributes #

Array attributes reflect information that is intrinsic to the array itself. Generally, accessing an array through its attributes allows you to get and sometimes set intrinsic properties of the array without creating a new array. The exposed attributes are the core parts of an array and only some of them can be reset meaningfully without creating a new array. Information on each attribute is given below.

Memory layout #

The following attributes contain information about the memory layout of the array:

Data type #

Data type objects

The data type object associated with the array can be found in the dtype attribute:

Other attributes #

Array interface #.

The array interface protocol .

ctypes foreign function interface #

Array methods #.

An ndarray object has many methods which operate on or with the array in some fashion, typically returning an array result. These methods are briefly explained below. (Each method’s docstring has a more complete description.)

For the following methods there are also corresponding functions in numpy : all , any , argmax , argmin , argpartition , argsort , choose , clip , compress , copy , cumprod , cumsum , diagonal , imag , max , mean , min , nonzero , partition , prod , ptp , put , ravel , real , repeat , reshape , round , searchsorted , sort , squeeze , std , sum , swapaxes , take , trace , transpose , var .

Array conversion #

Shape manipulation #.

For reshape, resize, and transpose, the single tuple argument may be replaced with n integers which will be interpreted as an n-tuple.

Item selection and manipulation #

For array methods that take an axis keyword, it defaults to None . If axis is None , then the array is treated as a 1-D array. Any other value for axis represents the dimension along which the operation should proceed.

Calculation #

Many of these methods take an argument named axis . In such cases,

If axis is None (the default), the array is treated as a 1-D array and the operation is performed over the entire array. This behavior is also the default if self is a 0-dimensional array or array scalar. (An array scalar is an instance of the types/classes float32, float64, etc., whereas a 0-dimensional array is an ndarray instance containing precisely one array scalar.)

If axis is an integer, then the operation is done over the given axis (for each 1-D subarray that can be created along the given axis).

Example of the axis argument

A 3-dimensional array of size 3 x 3 x 3, summed over each of its three axes

The parameter dtype specifies the data type over which a reduction operation (like summing) should take place. The default reduce data type is the same as the data type of self . To avoid overflow, it can be useful to perform the reduction using a larger data type.

For several methods, an optional out argument can also be provided and the result will be placed into the output array given. The out argument must be an ndarray and have the same number of elements. It can have a different data type in which case casting will be performed.

Arithmetic, matrix multiplication, and comparison operations #

Arithmetic and comparison operations on ndarrays are defined as element-wise operations, and generally yield ndarray objects as results.

Each of the arithmetic operations ( + , - , * , / , // , % , divmod() , ** or pow() , << , >> , & , ^ , | , ~ ) and the comparisons ( == , < , > , <= , >= , != ) is equivalent to the corresponding universal function (or ufunc for short) in NumPy. For more information, see the section on Universal Functions .

Comparison operators:

Truth value of an array ( bool() ):

Truth-value testing of an array invokes ndarray.__bool__ , which raises an error if the number of elements in the array is larger than 1, because the truth value of such arrays is ambiguous. Use .any() and .all() instead to be clear about what is meant in such cases. (If the number of elements is 0, the array evaluates to False .)

Unary operations:

Arithmetic:

Any third argument to pow is silently ignored, as the underlying ufunc takes only two arguments.

Because ndarray is a built-in type (written in C), the __r{op}__ special methods are not directly defined.

The functions called to implement many arithmetic special methods for arrays can be modified using __array_ufunc__ .

Arithmetic, in-place:

In place operations will perform the calculation using the precision decided by the data type of the two operands, but will silently downcast the result (if necessary) so it can fit back into the array. Therefore, for mixed precision calculations, A {op}= B can be different than A = A {op} B . For example, suppose a = ones((3,3)) . Then, a += 3j is different than a = a + 3j : while they both perform the same computation, a += 3 casts the result to fit back in a , whereas a = a + 3j re-binds the name a to the result.

Matrix Multiplication:

Matrix operators @ and @= were introduced in Python 3.5 following PEP 465 , and the @ operator has been introduced in NumPy 1.10.0. Further information can be found in the matmul documentation.

Special methods #

For standard library functions:

Basic customization:

Container customization: (see Indexing )

Conversion; the operations int() , float() and complex() . They work only on arrays that have one element in them and return the appropriate scalar.

String representations:

Utility method for typing:

multidimensional-array

looping through a multi-dimensional array in Smarty

I have a multi-dimensional array generated in PHP:

Is there a way to loop through this using Smarty?

I've gotten so far:

Try changing the second loop:

Multidimensional Arrays

A multidimensional array in MATLAB® is an array with more than two dimensions. In a matrix, the two dimensions are represented by rows and columns.

Each element is defined by two subscripts, the row index and the column index. Multidimensional arrays are an extension of 2-D matrices and use additional subscripts for indexing. A 3-D array, for example, uses three subscripts. The first two are just like a matrix, but the third dimension represents pages or sheets of elements.

Creating Multidimensional Arrays

You can create a multidimensional array by creating a 2-D matrix first, and then extending it. For example, first define a 3-by-3 matrix as the first page in a 3-D array.

Now add a second page. To do this, assign another 3-by-3 matrix to the index value 2 in the third dimension. The syntax A(:,:,2) uses a colon in the first and second dimensions to include all rows and all columns from the right-hand side of the assignment.

The cat function can be a useful tool for building multidimensional arrays. For example, create a new 3-D array B by concatenating A with a third page. The first argument indicates which dimension to concatenate along.

Another way to quickly expand a multidimensional array is by assigning a single element to an entire page. For example, add a fourth page to B that contains all zeros.

Accessing Elements

To access elements in a multidimensional array, use integer subscripts just as you would for vectors and matrices. For example, find the 1,2,2 element of A , which is in the first row, second column, and second page of A .

Use the index vector [1 3] in the second dimension to access only the first and last columns of each page of A .

To find the second and third rows of each page, use the colon operator to create your index vector.

Manipulating Arrays

Elements of multidimensional arrays can be moved around in many ways, similar to vectors and matrices. reshape , permute , and squeeze are useful functions for rearranging elements. Consider a 3-D array with two pages.

Reshaping a multidimensional array can be useful for performing certain operations or visualizing the data. Use the reshape function to rearrange the elements of the 3-D array into a 6-by-5 matrix.

reshape operates columnwise, creating the new matrix by taking consecutive elements down each column of A , starting with the first page then moving to the second page.

Permutations are used to rearrange the order of the dimensions of an array. Consider a 3-D array M .

Use the permute function to interchange row and column subscripts on each page by specifying the order of dimensions in the second argument. The original rows of M are now columns, and the columns are now rows.

When working with multidimensional arrays, you might encounter one that has an unnecessary dimension of length 1. The squeeze function performs another type of manipulation that eliminates dimensions of length 1. For example, use the repmat function to create a 2-by-3-by-1-by-4 array whose elements are each 5, and whose third dimension has length 1.

Use the squeeze function to remove the third dimension, resulting in a 3-D array.

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How to append to a multidimensional array in a smarty template?

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Multidimensional Arrays in Java

Array-Basics in Java Multidimensional Arrays can be defined in simple words as array of arrays. Data in multidimensional arrays are stored in tabular form (in row major order).

data_type [1st dimension][2nd dimension][]..[Nth dimension] array_name = new data_type [size1][size2]….[sizeN];

Size of multidimensional arrays : The total number of elements that can be stored in a multidimensional array can be calculated by multiplying the size of all the dimensions.

For example: The array int[][] x = new int[10][20] can store a total of (10*20) = 200 elements. Similarly, array int[][][] x = new int[5][10][20] can store a total of (5*10*20) = 1000 elements.

Application of Multi-Dimensional Array

● Multidimensional arrays are used to store the data in a tabular form. For example, storing the roll number and marks of a student can be easily done using multidimensional arrays. Another common usage is to store the images in 3D arrays.

● In dynamic programming questions, multidimensional arrays are used which are used to represent the states of the problem.

● Apart from these, they also have applications in many standard algorithmic problems like: Matrix Multiplication, Adjacency matrix representation in graphs, Grid search problems

Two – dimensional Array (2D-Array)

Two – dimensional array is the simplest form of a multidimensional array. A two – dimensional array can be seen as an array of one – dimensional array for easier understanding.

Indirect Method of Declaration:

Example: Implementing 2D array with by default values with 4*4 matrix

Explanation:.

Direct Method of Declaration: Syntax:

Example:

Accessing Elements of Two-Dimensional Arrays

Elements in two-dimensional arrays are commonly referred by x[i][j] where ‘i’ is the row number and ‘j’ is the column number.

For example:

The above example represents the element present in first row and first column. Note : In arrays if size of array is N. Its index will be from 0 to N-1. Therefore, for row_index 2, actual row number is 2+1 = 3. Example:

Representation of 2D array in Tabular Format:

A two – dimensional array can be seen as a table with ‘x’ rows and ‘y’ columns where the row number ranges from 0 to (x-1) and column number ranges from 0 to (y-1). A two – dimensional array ‘x’ with 3 rows and 3 columns is shown below:

Print 2D array in tabular format:

To output all the elements of a Two-Dimensional array, use nested for loops. For this two for loops are required, One to traverse the rows and another to traverse columns.

Example: Implementation of 2D array with User input

Three – dimensional Array (3D-Array)

Three – dimensional array is a complex form of a multidimensional array. A three – dimensional array can be seen as an array of two – dimensional array for easier understanding.

Accessing Elements of Three-Dimensional Arrays

Elements in three-dimensional arrays are commonly referred by x[i][j][k] where ‘i’ is the array number, ‘j’ is the row number and ‘k’ is the column number.

The above example represents the element present in the first row and first column of the first array in the declared 3D array.

Note : In arrays if size of array is N. Its index will be from 0 to N-1. Therefore, for row_index 2, actual row number is 2+1 = 3.

Representation of 3D array in Tabular Format:

A three – dimensional array can be seen as a tables of arrays with ‘x’ rows and ‘y’ columns where the row number ranges from 0 to (x-1) and column number ranges from 0 to (y-1). A three – dimensional array with 3 array containing 3 rows and 3 columns is shown below:

Print 3D array in tabular format:

To output all the elements of a Three-Dimensional array, use nested for loops. For this three for loops are required, One to traverse the arrays, second to traverse the rows and another to traverse columns.

Inserting a Multi-dimensional Array during Runtime:

This topic is forced n taking user-defined input into a multidimensional array during runtime. It is focused on the user first giving all the input to the program during runtime and after all entered input, the program will give output with respect to each input accordingly. It is useful when the user wishes to make input for multiple Test-Cases with multiple different values first and after all those things done, program will start providing output. As an example, let’s find the total number of even and odd numbers in an input array. Here, we will use the concept of a 2-dimensional array.

Here are a few points that explain the use of the various elements in the upcoming code:

Implementation:

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array of array

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Related code examples

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how to sort products based on price in prestashop

I need to sort based on products price low and high.

Display other products in the same category in below location

\modules\productscategory\productscategory.tpl

function in \modules\productscategory\productscategory.php

how to sort products based on price ?

Share a link to this question

Correct answer.

You can sort product by passing sorting information to the getProducts member function. Change your below code :

to the following code

After numbre of products (in your case it is 100), you can pass Order By (in the above code it is price, you can pass other options also like position, name, id_product etc) argument and then Order Way argument (in the above example, it is ASC, you can also use DESC)

Array Declarations in Java (Single and Multidimensional)

Arrays in Java | Introduction

One Dimensional Array :

It is a collection of variables of same type which is used by a common name.

Examples: One dimensional array declaration of variable:

We can write it in any way.

Now, if you declare your array like below:

Now, suppose we want to write multiple declaration of array variable then we can use it like this.

When we are declaring multiple variable of same time at a time, we have to write variable first then declare that variable except first variable declaration. There is no restriction for the first variable.

Now, when we are creating array it is mandatory to pass the size of array; otherwise we will get compile time error. You can use new operator for creating an array.

Printing array :

Two Dimensional Array

Suppose, you want to create two dimensional array of int type data. So you can declare two dimensional array in many of the following ways:

Now, Suppose we want to write multiple declarations of array variable then you can use it like this.

Creating one dimensional array and two dimensional array without new operator:

Creating one dimensional array and two dimensional array using new operator:

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Java-Arrays

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COMMENTS

php
I can see that you can pass an array to smarty and then loop over it in the template but I essentially need to pass a multidimensional array, 1 array for each sequence node. php smarty Share Follow edited Mar 8, 2013 at 11:59 asked Mar 8, 2013 at 11:50 Mike Rifgin 10.3k 20 74 111 Add a comment 2 Answers Sorted by: 1
Smarty assign and display two dimensional array
I want to get a two dimensional array's data and display it in a html file using smarty: The idea is as following: my array contains several arrays everyone contains the category name in the first offset and the attached links to this category 1-file php
Smarty :: View topic
assigning multidimensional arrays? Smarty Forum Index-> General: View previous topic ...
multidimensional arrays passed to Smarty?
Does Smarty support assigning multidimensional arrays? I've tried to get it working, but just can't get it. can someone help me? this is what I have in my php file: $side_bar = array ('link' => array ( 'index.php', 'estate.php', 'text' => array ( 'Home', 'Real Estate'))); $smarty->assign ("side_bar", $side_bar);
Need help with PHP Smarty Multi Dimensional Array
10 Years Ago. I am really in mess as I am unable to solve problem with Smarty Multi Dimension array. Below is the way I want to execute Smarty. First of all I will list all customers. Than I want list of all items purchased by that customer. I have two tables inside mysql (customer, sale). In Customer table only information related to his name ...
The N-dimensional array (ndarray)
An ndarray is a (usually fixed-size) multidimensional container of items of the same type and size. The number of dimensions and items in an array is defined by its shape , which is a tuple of N non-negative integers that specify the sizes of each dimension.
looping through a multi-dimensional array in Smarty
I have a multi-dimensional array generated in PHP: array( 'Requirements' => array( 'export_requirements' => array('value'=> 1, 'label'=> 'Export'), 'add_requirements ...
Multidimensional Arrays
A multidimensional array in MATLAB® is an array with more than two dimensions. In a matrix, the two dimensions are represented by rows and columns. Each element is defined by two subscripts, the row index and the column index. Multidimensional arrays are an extension of 2-D matrices and use additional subscripts for indexing.
How to append to a multidimensional array in a smarty template?
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Multidimensional Arrays in C / C++
A multi-dimensional array can be termed as an array of arrays that stores homogeneous data in tabular form. Data in multidimensional arrays are stored in row-major order. The general form of declaring N-dimensional arrays is: data_type array_name [size1] [size2].... [sizeN]; data_type: Type of data to be stored in the array.
Multidimensional Arrays in Java
Application of Multi-Dimensional Array Multidimensional arrays are used to store the data in a tabular form. For example, storing the roll number and marks of a student can be easily done using multidimensional arrays. Another common usage is to store the images in 3D arrays.
array
String[][] arrays = new String[][] { array1, array2, array3, array4, array5 };
how to sort products based on price in prestashop
I need to sort based on products price low and high. Display other products in the same category in below location \modules\productscategory\productscategory.tpl
Array Declarations in Java (Single and Multidimensional)
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