Reshape Array (DP_RSH)

This function takes an input array of data and reshapes it into a time series format. The resulting time series data can be used for time-based analysis, modeling, and forecasting.

Reshaping Arrays is a functionality used in data processing to transform data into a different shape. This can be useful when working with data that needs to be reorganized to be used in an analysis or modeling. The reshaping operation involves changing the number of dimensions, the size of each dimension, or both, of an input array to obtain a new output array with a different shape.

To reshape an array, you need to specify the input array and the desired shape of the output array. The shape of the output array can be defined using a tuple or a list of integers representing the size of each dimension.

Sample Request

This request reshapes the passed data to a specified dimension

{
    "project_id": 41,
    "block_id": 10,
    "parent_id": 9,
    "function_code": "DP_RSH",
    "args": {
        "data": "",
        "dimensions": [2, 21000]
    }
}

Reshaping Arrays

Reshapes an array based on specified dimensions

POST https://autogon.ai/api/v1/engine/start

Request Body

Name	Type	Description
project_id*	int	current project ID
parent_id*	int	parent block ID
block_id*	int	current block ID
function_code*	String	block's function code
data*	String	The input data to be reshaped. This can be a URL to a CSV file
args	object	block arguments
dimensions*	Array	The new dimensions to reshape the input data to. The number of dimensions must be the same as the number of axes in the input data.

200: OK Reshape Array Successful

{
    "status": "true",
    "message": {
        "id": 3,
        "project": 1,
        "block_id": 7,
        "parent_id": 6,
        "dataset_url": "",
        "x_value_url": "",
        "y_value_url": ""
    }
}

Python

// Some code

Node

projectId = 1
parentId = 6
blockId = 7

client.array_reshaping(projectId, parentId, blockId, {