def closset_match(check, arr, itr):
id_min = []
for ii in range(itr):
id_min_tmp = np.argmin( abs(arr - check) )
id_min.append(id_min_tmp)
arr[id_min_tmp] = float('-inf')
id_min = np.array(id_min)
return id_min
def get_match(arr1, arr2, tol, itr):
Hi all,
I have two spectra with wavelength, flux, and error on flux. I want to find out
the variability of these two spectra based on the 2 sample Chi-square test.
I am using following code:
def compute_chi2_var(file1,file2,zemi,vmin,vmax):
w1,f1,e1,c1,vel1 =
Dear All,
I am trying to fit a spectrum using a power law model. I am using
lmfit.minimizer. But the problem is that the value of parameter I am getting is
same as the initial value. Means minimizer is not working. Here is the part of
my code:
p = Parameters()
p.add('b', value=10)
Hello all,
Can anyone tell me how can I get the functional form of the fitted cubic spline
function on to my 2D array? For eg. when we fit the Gaussian on to an array so
we have the functional form with the parameters best fitted to my data likewise
how can we do for the cubic spline function?
On Wednesday, April 11, 2018 at 12:49:59 PM UTC+5:30, Christian Gollwitzer
wrote:
> Am 11.04.18 um 08:38 schrieb Priya Singh:
> > I have two 2D arrays one R and another T (which is also a 2D array).
> > Do you know how can I fit T with R in order to find central
> > c
On
On Wednesday, April 11, 2018 at 12:49:59 PM UTC+5:30, Christian Gollwitzer
wrote:
> Am 11.04.18 um 08:38 schrieb Priya Singh:
> > I have two 2D arrays one R and another T (which is also a 2D array).
> > Do you know how can I fit T with R in order to find central
>
Good morning.
I need some suggestion from you if you have encountered this problem ever.
I have two 2D arrays one R and another T (which is also a 2D array).
Do you know how can I fit T with R in order to find central
coordinate x0,y0 for T relative to R???
So the main question is do you know
