Generate a generic 2D Gaussian like array?
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# Generate a generic 2D Gaussian like array?

Generate a generic 2D Gaussian like array

## Recipe Objective

2D Gaussian distribution is very similar to a normal function but in place of x we use square-roots of squares of 1D variables.

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

## Step 1 - Import the library

``` 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.

## Step 2 - Generating a 2D gaussian array

``` 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.

## Step 3 - Printing Output

``` print(g) ```

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

## Step 4 - Lets look at our dataset now

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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