Toolkit
Module: deeprai.tools.toolkit
This module provides a collection of utility functions designed for numpy arrays. These functions offer various operations like verification, rounding, normalization, reshaping, and others, enhancing usability and information retrieval from numpy arrays.
1. verify_inputs(array)
Description:
Verify if the given input is a numpy array.
Parameters:
- array: The input to be checked.
Returns:
- bool: True if the input is a numpy array, otherwise False.
Example:
from deeprai.tools.toolkit import verify_inputs
result = verify_inputs(np.array([1, 2, 3]))
print(result) # True
2. round_out(array, a=2)
Description:
Round the elements of a numpy array and set specific print options.
Parameters:
-
array (
np.ndarray): The input numpy array. -
a (
int, optional): Decimal places to round to. Defaults to 2.
Returns:
- np.ndarray: The rounded numpy array.
Example:
from deeprai.tools.toolkit import round_out
rounded_array = round_out(np.array([1.12345, 2.6789]))
print(rounded_array) # [1.12, 2.68]
3. normalize(array)
Description:
Normalize the elements of the numpy array to the range [0, 1].
Parameters:
- array (
np.ndarray): The input array.
Returns:
- np.ndarray: The normalized array.
Example:
from deeprai.tools.toolkit import normalize
norm_array = normalize(np.array([10, 20, 30, 40]))
print(norm_array)
4. reshape_to_2d(array)
Description:
Reshape the numpy array to a 2D format if it's not already in that shape.
Parameters:
- array (
np.ndarray): The input array.
Returns:
- np.ndarray: The reshaped 2D array.
Example:
from deeprai.tools.toolkit import reshape_to_2d
reshaped_array = reshape_to_2d(np.array([1, 2, 3, 4]))
print(reshaped_array)
5. is_square_matrix(array)
Description:
Check if the given numpy array is a square matrix.
Parameters:
- array (
np.ndarray): The input array.
Returns:
- bool: True if the array is a square matrix, otherwise False.
Example:
from deeprai.tools.toolkit import is_square_matrix
result = is_square_matrix(np.array([[1, 2], [3, 4]]))
print(result) # True
6. sum_along_axis(array, axis=0)
Description:
Compute the sum of elements of the numpy array along a specified axis.
Parameters:
-
array (
np.ndarray): The input array. -
axis (
int, optional): Axis along which the sum is computed. Defaults to 0.
Returns:
- np.ndarray: The sum along the specified axis.
Example:
from deeprai.tools.toolkit import sum_along_axis
summed_array = sum_along_axis(np.array([[1, 2], [3, 4]]))
print(summed_array) # [4, 6]
7. array_info(array)
Description:
Retrieve essential information about the numpy array.
Parameters:
- array (
np.ndarray): The input array.
Returns:
- dict: A dictionary containing shape, data type, minimum and maximum values.
Example:
from deeprai.tools.toolkit import array_info
info = array_info(np.array([[1, 2], [3, 4]]))
print(info)
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