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QUESTION
I'm fairly new to python so bare with me. I have plotted a histogram using some generated data. This data has many many points. I have defined it with the variable vals. I have then plotted a histogram with these values, though I have limited it so that only values between 104 and 155 are taken into account. This has been done as follows:
ANSWER
Answered 2021-Jun-06 at 17:59See the cumtrapz docs:
Returns: ... If initial is None, the shape is such that the axis of integration has one less value than y. If initial is given, the shape is equal to that of y.
So you are either to pass an initial value like
QUESTION
I got a sample data and i'm trying to obtain the parameters for two-parameter exponential function calculed based on maximum likelihood.
My sample:
...ANSWER
Answered 2021-May-31 at 20:02The two-parameter exponential function is an exponential function with a lower endpoint at xi. Finding MLEs of distributions with such sharp boundary points is a bit of a special case: the MLE for the boundary is equal to the minimum value observed in the data set (see e.g. this CrossValidated question). That makes the MLE of the two-parameter exponential equivalent to the MLE of the exponential distribution for x-xmin.
So the MLE of xi is
QUESTION
I am plotting curves for different distribution functions and I need to know the highest y-value for each curve. Later I will plot only the one curve, which is selected as the best fitting.
This is the function (it is a bit hard-coded, I am working on it):
...ANSWER
Answered 2021-Feb-01 at 17:06You could use purrr::map_dbl to map the function optimize over your densities if you rearrange your code slightly and you have an idea over what input values you want to find their maxima/the density exists.
You can set your densities with whatever your parameters are ahead of time, that way you can find their peak values using optimize and also pass them to the curve function.
As a small reproducible example:
QUESTION
I'm trying to match the generalized extreme value (GEV) distribution's probability density function (pdf) to the data' pdf. This histogram is function of bin. As adjust this bin, the result of the function fitting also changes. And curve_fit(func, x, y) is playing this role properly. but this function uses a "least squares estimation". What I want is to use maximum likelihood estimation (MLE). And it has good results with the stats.genextreme.fit(data)function. However, this function does not represent histogram shape changes according to bin. Just use the original data.
I'm trying to use MLE. And I succeeded in estimating the parameters of the standard normal distribution using MLE. However, it is based on the original data and does not change according to the bin. Even the parameters of the GEV could not be estimated with the original data.
I checked the source code of genextreme_gen, rv_continuous, etc. But, this code is too complicated. I couldn't accept the source code with my Python skills.
I would like to estimate the parameters of the GEV distribution through MLE. And I want to get the result that the estimate changes according to bin.
What should I do?
I am sorry for my poor English, and thank you for your help.
+)
...ANSWER
Answered 2020-Nov-26 at 17:47One way to do this is to convert bins to data. You can do so by counting number of data points in each bin and then repeating center of the bin this number of times.
I have also tried to sample uniform values from each bin, but using center of the bin and then repeating it seems to provide parameters with higher likelihood.
QUESTION
I am trying to recreate a plot and I have several lines in there, which are in the legend but next to this the plot also has some points. How could I put labels in this plot at the points. Note that the points are not in the data frame. My code looks like this now:
...ANSWER
Answered 2020-Sep-13 at 18:59To label the points you can add geom_text layers with point coordinates and the label.
Using mtcars as example data set try this:
QUESTION
I have a data file that looks like this, and the file type is a list.
...ANSWER
Answered 2020-Jun-23 at 05:53spectrum=[]
mass=[]
with open ('test.in') as m:
test=m.readlines()
for line in test:
if line[0] == '#':
continue
single_line=line.split('\t')
mass.append(float(single_line[0]))
spectrum.append(float(single_line[1]))
QUESTION
I have a python script that writes a file that is based on the scalers I apply to other files I call this file APtest.in . To make it easier for the user, I do not want the user to input their own file name rather, python writes the file name. For example, if all mumu, bquark, tau, and ww have a scalar value of .1 the output file name should be alone the lines of DMmodel_010mumu_010tau_010bquark_010ww.in
Thank you in advance!
...ANSWER
Answered 2020-Jun-23 at 04:25Something like below:
QUESTION
So I have a file that looks like this
mass (GeV) spectrum (1-100 GeV)
10 0.06751019803888393
20 0.11048827045815585
30 0.1399367785958526
40 0.1628781532692572
I want to multiply the spectrum by half or any percentage, then create a new file with the same data, but the spectrum is replaced with the new spectrum multiplied by the multiplier
...ANSWER
Answered 2020-Jun-11 at 06:51replace is a function that works on strings. f is not a string. (For that matter, neither is Spectrum or Spectrumnew.)
You need to construct the line you want in the output file as a string and then write it out. You already have string output working. To construct the output line, you can just concatenate the first number from the input, a tab character, and the product of the second number and the multiplier. You can convert a number to a string with the str() function and you can concatenate strings with the + operator.
There are several more specific answers on this site already that may be helpful, such as replacing text in a file with Python.
QUESTION
I want to minimize a metric d that includes GEV-distributed values.
Thus, I need to find a, b and c with optim(), such that d ideally converges to 0.
Here is a simplified excerpt from my code:
...ANSWER
Answered 2020-Jun-06 at 11:08One way to implement such a constraint is to have gev.score return a large number whenever the constraint is not met. You minimize, and so the algorithm will move away from points that violate the constraint. (The downside of the approach is that you introduce jumps into the objective function, and this may create new troubles.)
With only three parameters to optimize, you might also consider a grid search.
By the way, it would help if you created a small reproducible example.
QUESTION
I am trying to isolate only one plot among a 4-panel display of diagnostic plots using a GEV model.
This is what I tried to isolate the last plot of the 4 plots (i.e. the bottom-right plot):
...ANSWER
Answered 2020-Mar-27 at 19:19The plot method for class fevd has an argument type and the following is from its document:
Default is “primary”, which makes a 2 by 2 panel of plots including the QQ plot of the data quantiles against the fitted model quantiles (type “qq”), a QQ plot (“qq2”) of quantiles from model-simulated data against the data, a density plot of the data along with the model fitted density (type “density”) and a return level plot (type “rl”).
The fourth panel is the return level plot and you can extract it by
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