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# Generate a generic 2D Gaussian like array using numpy

This recipe helps you generate a generic 2D Gaussian like array using numpy

So this recipe is a short example on how to generate a generic 2D Gaussian-like array. Let's get started.

```
import numpy as np
```

Let's pause and look at these imports. Numpy is generally helpful in data manipulation while working with arrays. It also helps in performing mathematical operation.

```
x, y = np.meshgrid(np.linspace(-1,1,10), np.linspace(-1,1,10))
d = np.sqrt(x*x+y*y)
sigma, mu = 1.0, 0.0
g = np.exp(-( (d-mu)**2 / ( 2.0 * sigma**2 ) ) )
```

Let's have a loop at each step one by one. One first step, we have created two, 2D arrays, using meshgrid and linespace function. Meshgrid basically creates a rectangular grid out of two given one-dimensional array. Linespace returns number spaces evenly w.r.t interval. In 2nd step, we are calculating the square-roots of squares of s and y. Finally, using exp function, we are genearating the guassian array.

```
print(g)
```

Simply using print function, we have print our gaussian array.

Once we run the above code snippet, we will see:

Scroll down to the ipython file below to visualize the output.

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