On 11/25/19 12:31 PM, Machiel Kolstein wrote:
> Okay, I found some answer myself: use scipy.optimize.curve_fit
> However, I still find it strange that I have to define a gauss function
> myself instead of it being readily available. I did this:
>
> # Define model function to be used to fit to the
Okay, I found some answer myself: use scipy.optimize.curve_fit
However, I still find it strange that I have to define a gauss function myself
instead of it being readily available. I did this:
# Define model function to be used to fit to the data
def gauss(x, *p):
A, mu, sigma = p
retur
If I have an array with values, which are distributed according to a Gaussian
function, then I can fit with:
(fit_mu, fit_sigma) = stats.norm.fit(x_array)
However, now, I have one array with values for the xbins (e.g., 0.0, 0.1, 0.2,
0.3, ..., up till 1.0) and one value for the correspondin
