Hi,

this code generate 4 values with gaussian distribution (mu=5, sigma=1):

import numpy as np
x = np.random.normal(5, 1, 4)
print(x)

Output:
[5.87879753 3.29162433 3.83024698 4.92997148]

I would like to round the output like this:

[6, 3, 4, 5]

What should I add to the code?

Thank you

j.

jo <jo@email.com> writes:
>I would like to round the output like this:
>[6, 3, 4, 5]
>What should I add to the code?

We are not supposed to do anything here that might be
homework, but maybe I am allowed to say that Python has
several facilites that allow one to map functions to entries
of a list (for example, higher-order map functions and "for"
comprehensions) and then convert the resulting iterable
object back to a list.

On 24/06/2021 16:23, jo wrote:
> Hi,
>
> this code generate 4 values with gaussian distribution (mu=5, sigma=1):
>
> import numpy as np
> x = np.random.normal(5, 1, 4)
> print(x)
>
> Output:
> [5.87879753 3.29162433 3.83024698 4.92997148]
>
> I would like to round the output like this:
>
> [6, 3, 4, 5]
>
> What should I add to the code?
>
> Thank you

Have a look at numpy.around:
<https://numpy.org/doc/stable/reference/generated/numpy.around.html>

HTH,

Julio

Il Thu, 24 Jun 2021 18:07:07 +0200, Julio Di Egidio ha scritto:

> On 24/06/2021 16:23, jo wrote:
>> Hi,
>>
>> this code generate 4 values with gaussian distribution (mu=5, sigma=1):
>>
>> import numpy as np x = np.random.normal(5, 1, 4)
>> print(x)
>>
>> Output:
>> [5.87879753 3.29162433 3.83024698 4.92997148]
>>
>> I would like to round the output like this:
>>
>> [6, 3, 4, 5]
>>
>> What should I add to the code?
>>
>> Thank you
>
> Have a look at numpy.around:
> <https://numpy.org/doc/stable/reference/generated/numpy.around.html>
>
> HTH,
>
> Julio

Yes, np.around() works fine.
Thank you.

This is the new code:

import numpy as np
x = np.random.normal(5, 1, 4)

y=np.around(x)

print(x)

print(y)

output:

[4.68551569 3.9610641 6.1119447 4.81012246]
[5. 4. 6. 5.]

Thank you very much,

j.

On Thu, 24 Jun 2021 16:27:58 +0000 (UTC), jo <jo@email.com> declaimed the
following:

>This is the new code:
>
>import numpy as np
>
>x = np.random.normal(5, 1, 4)
>
>y=np.around(x)
>
>print(x)
>
>print(y)
>
>
>output:
>
>[4.68551569 3.9610641 6.1119447 4.81012246]
>[5. 4. 6. 5.]

Ouch... importing the massive numpy library just to do rounding? Well,
no -- you did import it to generate your data... Still seems a big library
for such a small assignment.

Without numpy, you might want to explore the Python standard library.
https://docs.python.org/3/library/stdtypes.html#numeric-types-int-float-complex
https://docs.python.org/3/library/random.html#real-valued-distributions

Consider:
int(), round(), math.trunc(), math.floor(), math.ceil()

random.gauss(), random.normalvariate()

>>> import math
>>> import random
>>> x = [random.gauss(5, 1) for _ in range(4)]
>>> x
[4.679373663118109, 6.523100884104224, 5.320871577393969,
3.6448059793115313]
>>> yint = [int(v) for v in x]
>>> yint
[4, 6, 5, 3]
>>> yround = [round(v) for v in x]
>>> yround
[5, 7, 5, 4]
>>>

If you only need the integer values for output, then string formatting
can suffice...

>>> for v in x:
.... print("%d" % v, end="\t")
....
4 6 5 3
>>> for v in x:
.... print("%d" % (v+0.5), end="\t")
....
5 7 5 4
>>>

Note that those are TEXT strings, not integers, at point of output.

--
Wulfraed Dennis Lee Bieber AF6VN
wlfraed@ix.netcom.com http://wlfraed.microdiversity.freeddns.org/