On 16 March 2015 at 22:22, Colin Ross wrote:
>
> Yes, thank you, they were suppose to both be E_out.
Hi Colin,
I'm not sure if that means that your problem is fixed or not but I
thought I would point something out that helps in fixing this kind of
problem.
You're using ipython which has an exce
On Mon, Mar 16, 2015 at 3:22 PM, Colin Ross wrote:
> Yes, thank you, they were suppose to both be E_out.
>
> And to answer your last question, I do not. Can you please explain?
The article:
http://en.wikipedia.org/wiki/Unit_testing
may help.
As a brief intro: we treat each interesting fun
Yes, thank you, they were suppose to both be E_out.
And to answer your last question, I do not. Can you please explain?
On Mon, Mar 16, 2015 at 7:19 PM, Danny Yoo wrote:
> On Mon, Mar 16, 2015 at 2:55 PM, Colin Ross
> wrote:
> > What I am trying to do is calculate the non-colinear autocorrel
On Mon, Mar 16, 2015 at 2:55 PM, Colin Ross wrote:
> What I am trying to do is calculate the non-colinear autocorrelation:
>
> G(t_d) = \int_{-\infty}^{+\infty} |E(t)|^2 * |E(t - t_d)|^2 dt
>
> So I need to loop through an array of t_d values (len = 376) and calculate
> G(t_d) for as many t values
What I am trying to do is calculate the non-colinear autocorrelation:
G(t_d) = \int_{-\infty}^{+\infty} |E(t)|^2 * |E(t - t_d)|^2 dt
So I need to loop through an array of t_d values (len = 376) and calculate
G(t_d) for as many t values as possible to eliminate sampling issues.
Colin
On Mon, Mar
HI Danny,
Here is a simplified version:
import numpy as np
import pylab
from pylab import *
import matplotlib.pyplot as plt
import scipy
from scipy.integrate import quad
from scipy.fftpack import fft, ifft, fftfreq
#
> What does fft expect to receive as an argument? We can read the following:
>
>
> http://docs.scipy.org/doc/scipy/reference/generated/scipy.fftpack.fft.html#scipy.fftpack.fft
>
> Since fft is erroring out: there's only one possibility: E_(x) is not
> providing a value that's appropriate to f
> Thanks for the help! As you mentioned, using scipy.special.erfc was a much
> better idea. Below is a copy of my program and the stack trace, showing a
> new error. It seems that the first auto correlation works, however the
> second fails.
At this point, the program is large enough that we nee
Hi Danny,
Thanks for the help! As you mentioned, using scipy.special.erfc was a much
better idea. Below is a copy of my program and the stack trace, showing a
new error. It seems that the first auto correlation works, however the
second fails.
###
# Autocorrelation p
On Fri, Mar 13, 2015 at 11:00 AM, Danny Yoo wrote:
>> The error I am recieving is as follows:
>>
>> TypeError: only length-1 arrays can be converted to Python scalars
>
>
> Hi Colin,
>
> Do you have a more informative "stack trace" of the entire error?
> Providing this will help localize the probl
> The error I am recieving is as follows:
>
> TypeError: only length-1 arrays can be converted to Python scalars
Hi Colin,
Do you have a more informative "stack trace" of the entire error?
Providing this will help localize the problem. As is, it's clear
there's a type error... somewhere... :P
Hi all,
I am attempting to optimize the parameters I_0 and w_0 in the function
(func(x,I_0,w_0) shown below) to fit a set of data. However when I run this
code I recieve the error shown below. Any suggestions would be greatly
appreciated.
Code:
import numpy as np
import math
from math import *
12 matches
Mail list logo
