The amplitude is one volt for all sine wave frequencies.The requirement is to generate a sine wave with frequencies ranging from 1 Hz to 10 Hz. Is it possible to loop over these two lists of dictionaries together within the same task, whilst also allowing the regex replacements to reference a value of the first loop? I sort of imagine building a data structure that has all of these things created and then just looping over that. This works fine, but it is a little bit inelegant split out across multiple files, not to mention it's not the easiest to control those regex replacements - would be good if they could be held in a separate variable. I'm currently achieving this the following way, in playbook.yml: - name: Perform replacements with loop over sitesĪ_tasks: replacements.ymlĪnd the contents of replacements.yml: - name: Perform replacements The only problem is, the list of replacements needs to use a value found within the sites dictionary. I want to perform a loop over lineinfile with both these sites, and a list of regex/replacements to try.
#Gamma cdf series#
For each site, I want to perform a series of replacements on a config file within the site using lineinfile (the path to the config file is determined from information in the sites dictionary) I'm trying to loop over a list of sites - which are individual dictionaries. I've looked at similar questions and although I've solved the problem, I don't think it's the most elegant solution. I have made the modifications here /path_to_anaconda/anaconda3/envs/p圓9tf26cpu/lib/python3.9/site-packages/tensorflow/python/keras/engine
#Gamma cdf code#
However, the changes do not seem to be getting picked up when I run my code which imports tensorflow. TESTING!!!!"īasically I added some extra log here just to see how this works. I have modified line 1233 "Your input ran out of data interrupting training." with "Your input ran out of data interrupting training. Is there any extra step to work on? To be concrete Unfortunately I am not able to simply modify the python file and run, as the changes are not getting picked up. Therefore I want to modify the tensorflow code base to print some values so I see exactly what is going wrong. I am trying to debug a use-case and the error messages that are given by tensorflow are cryptic. If you have the raw data (instead of the empirical CDF), you may be better off using the. These two are different and the results are expected to be different. fit() method, is a maximum likelihood method. Now, keep in mind that your are essentially doing a least square minimization to fit empirical CDF to the Gamma CDF. Return sum((gamma.cdf(x, para, scale=para)-y)**2)/2 So you should change your function to: def loss_func(para, x, y): So as the result, res.x return the location and res.x returns shape, which is not quite what you want. Para becomes a and hence shape parameter and para becomes loc, which is the location parameter.
cdf(x, a, loc=0, scale=1), with your function: def loss_func(para, x, y): See the documentation for scipy.stats for cumulative distribution function method.
No, I don't think you are getting it right.
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