distribution

问题 I am trying to prepare my app for distribution to the app store and am getting the following warning in Xcode which is causing an error in ApplicationLoader. I know this is a common problem from searching but I have yet to find a proper solution? I went thru Apple's steps for distribution on the iOS provisioning portal and still get this error. My distribution profile is set on my Target. "Application failed codesign verification. The signature was invalid, or it was not signed with an Apple

问题 I developed a program consisting of a package which is executable (i.e. two files x/__init__.py and x/__main__.py ), so I can execute it using python -m x , if the package resides in the python path. I never tried to distribute Python packages/modules and I don't have any experience in that field (yet)... I already noticed that there are many different systems and now I have three questions: Which system is appropiate for a Python 3(.2) program? distribute? distutils? setuptools? How can I

问题 I have been trying to create my own discrete distribution in Visual Studio (C++). I kept getting the same error. I then tried the example code from: http://www.cplusplus.com/reference/random/discrete_distribution/discrete_distribution/. Again, the same error appeared with this example code. The line of code (from the link) that is giving me an error is: std::discrete_distribution second(init.begin(), init.end()); Particularly, init.begin() is underlined in red. The 2 errors are as follows:

问题 The algorithm Wikipedia gives for generating Poisson-distributed random variables using the inverse transform method is: init: Let x ← 0, p ← e^−λ, s ← p. Generate uniform random number u in [0,1]. while u > s do: x ← x + 1. p ← p * λ / x. s ← s + p. return x. I implemented it in R: f<-function(lambda) { x<-0 p<-exp(-lambda) s<-p u<-runif(1) while (u>s ) { x<-x+1 p<-p*lambda/x s<-s+p } return(x) } but I don't understand how this generates values of this random variable, and I also think the

问题 I've been having problems withe getting setup.py to do the sdist thing correctly. I boiled it down to this. I have the following directory structure: my_package\ my_subpackage\ __init__.py deep_module.py __init__.py module.py setup.py And here's what I have in setup.py : #!/usr/bin/env python from distutils.core import setup import distutils setup( name='a', version='0.1', description='a', author='a', author_email='a@a.com', url='http://a.org', packages=['my_package','my_package.my_subpackage

问题 i have successfully created provisioning and distribution certificates and ready to upload my app. but, while posting i can't access to select the distribution profile? 回答1: @NeerajNeeru: Firstly, Make sure that you download a new copy of distribution provisioning profile for App Store from the account you want to submit the application with and install the same profile by double clicking it. Once you do that select it under your Project Settings and Target Settings under the Release section.

问题 I'm trying to estimate the Almalki and Yuan's modified Weibull distribution (NMW) parameters, but I'm encountering the following error: The value of the AIC is giving negative ONLY VERY NEGATIVE. Something is wrong. I know that in the literature the AIC may be negative, but I believe that some error in the estimation or the functions is happening. Can the bug be in the estimation, fitdist or something like that? Somebody help me? ARTICLE https://www.sciencedirect.com/science/article/pii

问题 I have a list of pre aggregated tuples: [{'target_y_n': 0, 'value': 0.5, 'count':1000},{'target_y_n': 1, 'value': 1, 'count':10000}, ...] How can I visualize the distributions (https://seaborn.pydata.org/generated/seaborn.distplot.html) or get frequency plots without re-expanding the aggregated representation to k copies of each value, but still re-using as much as possible from existing tools like distplot, countplot ? edit In R http://www.amitsharma.in/post/cumulative-distribution-plots-for

问题 I have a dataset consisting of a large collection of points in three dimensional euclidian space. In this collection of points, i am trying to find the point that is nearest to the area with the highest density of points. So my problem consists of two steps: 1: Determine where density of the distribution of points is at its highest 2: Determine which point is nearest to the point found in 1 Point 2 i can manage, but i'm not sure how to solve point 1. I know there are a lot of functions for

问题 Closed . This question is opinion-based. It is not currently accepting answers. Want to improve this question? Update the question so it can be answered with facts and citations by editing this post. Closed 4 years ago . I try to visualise the difference between two histograms of distribution functions such as the difference in following two curves : When the difference is big, you could just plot two curves on top of each other and fill the difference as denoted above, though when the