Re: Problem with assignment. Python error or mine?

2017-12-22 Thread Tim Williams 
On Friday, December 22, 2017 at 8:41:29 AM UTC-5, Tim Williams wrote:
> On Thursday, December 21, 2017 at 12:18:11 PM UTC-5, MarkA wrote:
> > On Thu, 21 Dec 2017 07:05:33 -0800, rafaeltfreire wrote:
> > From docs.python.org:
> > 
> > 8.10. copy — Shallow and deep copy operations
> > 
> > Source code: Lib/copy.py
> > 
> > Assignment statements in Python do not copy objects, they create bindings 
> > between a target and an object. For collections that are mutable or 
> > contain mutable items, a copy is sometimes needed so one can change one 
> > copy without changing the other. This module provides generic shallow and 
> > deep copy operations (explained below)...
> > 
> > 
> > > Dear community, I am having the following problem when I am assigning
> > > the elements of a vector below a certain number to zero or any other
> > > value.
> > > I am creating a new variable but Python edits the root variable. Why?
> > > 
> > > import numpy as np
> > > 
> > > X=np.arange(1, 1, 1) #root variable x1=X x1[x1<1]=0
> > > 
> > > print(X)
> > > Out[1]: array([ 0.,  0.,  0., ...,  0.,  0.,  0.])
> > > 
> > > Why? It is supposed to be the original value Thank you for your
> > > time Rafael
> > 
> > 
> > 
> > -- 
> > MarkA
> > 
> > We hang petty theives, and appoint the great theives to public office
> >   -- Aesop
> 
> Shouldn't the OP just create a list for what he want's to do?
> 
> X = list(np.arange(1, 1, 1)) #root variable x1=X x1[x1<1]=0
> 
> Then I think his other statements would do what he expects, no?

Disregard what I just posted. I didn't think this through enough. 
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Re: Problem with assignment. Python error or mine?

2017-12-22 Thread Tim Williams 
On Thursday, December 21, 2017 at 12:18:11 PM UTC-5, MarkA wrote:
> On Thu, 21 Dec 2017 07:05:33 -0800, rafaeltfreire wrote:
> From docs.python.org:
> 
> 8.10. copy — Shallow and deep copy operations
> 
> Source code: Lib/copy.py
> 
> Assignment statements in Python do not copy objects, they create bindings 
> between a target and an object. For collections that are mutable or 
> contain mutable items, a copy is sometimes needed so one can change one 
> copy without changing the other. This module provides generic shallow and 
> deep copy operations (explained below)...
> 
> 
> > Dear community, I am having the following problem when I am assigning
> > the elements of a vector below a certain number to zero or any other
> > value.
> > I am creating a new variable but Python edits the root variable. Why?
> > 
> > import numpy as np
> > 
> > X=np.arange(1, 1, 1) #root variable x1=X x1[x1<1]=0
> > 
> > print(X)
> > Out[1]: array([ 0.,  0.,  0., ...,  0.,  0.,  0.])
> > 
> > Why? It is supposed to be the original value Thank you for your
> > time Rafael
> 
> 
> 
> -- 
> MarkA
> 
> We hang petty theives, and appoint the great theives to public office
>   -- Aesop

Shouldn't the OP just create a list for what he want's to do?

X = list(np.arange(1, 1, 1)) #root variable x1=X x1[x1<1]=0

Then I think his other statements would do what he expects, no?
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Re: Problem with assignment. Python error or mine?

2017-12-21 Thread duncan smith 
On 21/12/17 19:06, John Ladasky wrote:
> On Thursday, December 21, 2017 at 7:37:39 AM UTC-8, MRAB wrote:
> 
>> Python never makes a copy unless you ask it to.
>>
>> What x1=X does is make the name x1 refer to the same object that X 
>> refers to. No copying.
> 
> Well, except with very simple, mutable data types like scalars... compare 
> this:
> 
 x=5
 y=x
 x,y
> (5, 5)
 x+=1
 x,y
> (6, 5)
> 
> To this:
> 
 a=[1,2,3]
 b=a
 a,b
> ([1, 2, 3], [1, 2, 3])
 a[1]=9
 a,b
> ([1, 9, 3], [1, 9, 3])
> 

Except ints aren't mutable and there's still no copying.

For

x += 1

(where x is e.g. an int) read

x = x + 1

Duncan
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Re: Problem with assignment. Python error or mine?

2017-12-21 Thread Kirill Balunov 
2017-12-21 22:06 GMT+03:00 John Ladasky :

> On Thursday, December 21, 2017 at 7:37:39 AM UTC-8, MRAB wrote:
>
> > Python never makes a copy unless you ask it to.
> >
> > What x1=X does is make the name x1 refer to the same object that X
> > refers to. No copying.
>
> Well, except with very simple, mutable data types like scalars... compare
> this:
>

No copy means no copy, it is the rule! What you see is really new binding
operation under the hood.
'x=1; x += 1', means calculate x+1 and bind it to the same name. Compare it
to this example:


>>> tpl = ((1,2),(3,4))
>>> tpl += ((1,2),)
>>> tpl

((1, 2), (3, 4), (1, 2))


No copy, new binding to the same name :)


With kind regards, -gdg
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Re: Problem with assignment. Python error or mine?

2017-12-21 Thread John Ladasky 
On Thursday, December 21, 2017 at 7:37:39 AM UTC-8, MRAB wrote:

> Python never makes a copy unless you ask it to.
> 
> What x1=X does is make the name x1 refer to the same object that X 
> refers to. No copying.

Well, except with very simple, mutable data types like scalars... compare this:

>>> x=5
>>> y=x
>>> x,y
(5, 5)
>>> x+=1
>>> x,y
(6, 5)

To this:

>>> a=[1,2,3]
>>> b=a
>>> a,b
([1, 2, 3], [1, 2, 3])
>>> a[1]=9
>>> a,b
([1, 9, 3], [1, 9, 3])

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Re: Problem with assignment. Python error or mine?

2017-12-21 Thread MarkA 
On Thu, 21 Dec 2017 07:05:33 -0800, rafaeltfreire wrote:
From docs.python.org:

8.10. copy — Shallow and deep copy operations

Source code: Lib/copy.py

Assignment statements in Python do not copy objects, they create bindings 
between a target and an object. For collections that are mutable or 
contain mutable items, a copy is sometimes needed so one can change one 
copy without changing the other. This module provides generic shallow and 
deep copy operations (explained below)...


> Dear community, I am having the following problem when I am assigning
> the elements of a vector below a certain number to zero or any other
> value.
> I am creating a new variable but Python edits the root variable. Why?
> 
> import numpy as np
> 
> X=np.arange(1, 1, 1) #root variable x1=X x1[x1<1]=0
> 
> print(X)
> Out[1]: array([ 0.,  0.,  0., ...,  0.,  0.,  0.])
> 
> Why? It is supposed to be the original value Thank you for your
> time Rafael



-- 
MarkA

We hang petty theives, and appoint the great theives to public office
  -- Aesop
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Re: Problem with assignment. Python error or mine?

2017-12-21 Thread MRAB 

On 2017-12-21 15:05, rafaeltfre...@gmail.com wrote:

Dear community, I am having the following problem when I am assigning the 
elements of a vector below a certain number to zero or any other value.
I am creating a new variable but Python edits the root variable. Why?

import numpy as np

X=np.arange(1, 1, 1) #root variable
x1=X
x1[x1<1]=0

print(X)
Out[1]: array([ 0.,  0.,  0., ...,  0.,  0.,  0.])

Why? It is supposed to be the original value
Thank you for your time
Rafael


Python never makes a copy unless you ask it to.

What x1=X does is make the name x1 refer to the same object that X 
refers to. No copying.


As you're using numpy, you can use the .copy method:

x1 = X.copy()

This makes the name x1 refer to a new copy of the object that X refers to.
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Re: Problem with assignment. Python error or mine?

2017-12-21 Thread rafaeltfreire 
Em quinta-feira, 21 de dezembro de 2017 16:21:57 UTC+1, Neil Cerutti  escreveu:
> On 2017-12-21, rafaeltfre...@gmail.com  wrote:
> > Dear community, I am having the following problem when I am
> > assigning the elements of a vector below a certain number to
> > zero or any other value. I am creating a new variable but
> > Python edits the root variable. Why?
> >
> > import numpy as np
> >
> > X=np.arange(1, 1, 1) #root variable
> 
> np.arange creates an object. The assignment makes X refer to that
> object.
> 
> > x1=X 
> 
> X refers to the previous object, and then the assignment makes x1
> refer to that same object.
> 
> -- 
> Neil Cerutti

Ok, great thank you. I am kind of new in python. I use to program in MATLAB but 
I am trying to migrate. 
So, to fix it what should I do? because my X is an NMR spectrum of many 
samples. 
Thank you very much!
Rafael
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Re: Problem with assignment. Python error or mine?

2017-12-21 Thread Neil Cerutti 
On 2017-12-21, rafaeltfre...@gmail.com  wrote:
> Dear community, I am having the following problem when I am
> assigning the elements of a vector below a certain number to
> zero or any other value. I am creating a new variable but
> Python edits the root variable. Why?
>
> import numpy as np
>
> X=np.arange(1, 1, 1) #root variable

np.arange creates an object. The assignment makes X refer to that
object.

> x1=X 

X refers to the previous object, and then the assignment makes x1
refer to that same object.

-- 
Neil Cerutti

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Problem with assignment. Python error or mine?

2017-12-21 Thread rafaeltfreire 
Dear community, I am having the following problem when I am assigning the 
elements of a vector below a certain number to zero or any other value. 
I am creating a new variable but Python edits the root variable. Why?

import numpy as np

X=np.arange(1, 1, 1) #root variable
x1=X 
x1[x1<1]=0

print(X)
Out[1]: array([ 0.,  0.,  0., ...,  0.,  0.,  0.])

Why? It is supposed to be the original value
Thank you for your time
Rafael
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