On 16 March 2015 at 22:22, Colin Ross colin.ross@gmail.com 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
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,
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 d...@hashcollision.org wrote:
On Mon, Mar 16, 2015 at 2:55 PM, Colin Ross colin.ross@gmail.com
wrote:
What I am trying to
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
On Mon, Mar 16, 2015 at 2:55 PM, Colin Ross colin.ross@gmail.com 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)
On Mon, Mar 16, 2015 at 3:22 PM, Colin Ross colin.ross@gmail.com 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
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
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 need
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 fft().
On Fri, Mar 13, 2015 at 11:00 AM, Danny Yoo d...@hashcollision.org 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
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
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
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