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Compute cross-correlation of two given NumPy arrays
Learn, how can we compute cross-correlation of two given NumPy arrays?
Submitted by Pranit Sharma, on March 20, 2023
Cross correlate 1d arrays
Correlation refers to a process for establishing the relationships between two variables. This function computes the correlation as generally defined in signal-processing texts:
Suppose that we are given two 1D arrays, and we need to find the cross-correlation between them.
To compute cross-correlation of two arrays, we can simply use the numpy.correlate2d() method.
Parameter(s)
- a, v: input arrays
- mode: it is a string which represent the mode of output. There are different modes like full, valid, and same.
Let us understand with the help of an example,
Python code to compute cross-correlation of two given NumPy arrays
# Import numpy
import numpy as np
# Creating two numpy arrays
arr1 = np.array([1,2,3])
arr2 = np.array([4,5,6])
# Display original arrays
print("Original array 1:\n",arr1,"\n")
print("Original array 2:\n",arr2,"\n")
# Finding cross correlation
res = np.correlate(arr1,arr2)
# Display result
print("Result:\n",res,"\n")
Output
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