Using numpy.random

Question

I'm having a little bit of trouble using numpy.random.normal. At the bottom of this link (http://docs.scipy.org/doc/numpy/reference/generated/numpy.random.normal.html) there's a graph which shows standard deviations. I'm a little confused about this, because it doesn't look like 0.1, 0.2, 0.3 etc. standard deviations. It also doesn't look like 1, 2, or 3 standard deviations.

What I'm trying to do is to add noise to an image at specific standard deviations. However, the results I get are honestly pretty weird. My code (in Python) is shown below:

poisson = float((raw_input("Noise standard deviation: ")))
.
.
.
name = t+'PHOTO'+s+str(i)+'.fits'

    im = pf.open(name)
    isinstance(im,list)
    im0 = im[0]
    poissonNoise = np.random.normal(0,poisson/1000, im0.data.shape).astype(float)
    test = im0.data + poissonNoise
    im0.data = test
    stringee = 'NOISE'
    pf.writeto(stringee+str(poisson)+name, data=test, clobber=True, header=im0.header)
print poisson

If you notice, I divide "poisson" by 1000 in order to get meaningful results. So what is the real value of the standard deviation, and how do I use it? All I want to do is to be able to input 1, 2, 3, etc. standard deviations and create that much noise.

In the example you linked, 0.1 was specified as the standard deviation of the desired distribution, so the values 0.1, 0.2, 0.3 on the X axis correspond to 1, 2, and 3 standard deviations. (Also, poissonNoise seems like a confusing variable name, when you're using a Gaussian distribution.) — Jim Lewis
– Jim Lewis, Commented Nov 3, 2013 at 8:15

Developer · Accepted Answer · 2013-11-03 08:47:39Z

2

It seems you're mixing things together. On the figure of discussion in the question

enter image description here

X axis is just X values not Standard Deviations. Remember that, for one distribution (here, Normal) there is only one single value standard deviation which can be computed easily, numpy.std.

BTW, your code is not quiet Python code. What is this: isinstance(im,list) for? Also remember that, indentation is heart of Python.

answered Nov 3, 2013 at 8:47

Developer

8,4108 gold badges51 silver badges61 bronze badges

Sign up to request clarification or add additional context in comments.

Collectives™ on Stack Overflow

Using numpy.random

1 Answer 1

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

Comments

Your Answer

Sign up or log in

Post as a guest

Related