distribution

问题 I'm trying to use crashlytics distribution for android app with multiple flavors. Everything worked fine when there were no flavors, but as soon as I've added two flavors I'm receiving *'Task 'crashlyticsUploadDistributionRelease' not found in root project'* Am I missing something? 回答1: Ohh, I did miss something.. Don't forget to add your flavor name to: crashlyticsUploadDistribution<FLAVOR>Release 来源： https://stackoverflow.com/questions/27383732/crashlytics-distribution-for-app-with-multiple

问题 I have a single series of values (i.e. one column of data), and I would like to create a plot with the range of data values on the x-axis and the frequency that each value appears in the data set on the y-axis. What I would like is very close to a Kernel Density Plot: # Kernel Density Plot d <- density(mtcars$mpg) # returns the density data plot(d) # plots the results and Frequency distribution in R on stackoverflow. However, I would like frequency (as opposed to density) on the y-axis.

问题 I followed the stepped to create a ad hoc carefully: Added the testers team devices to the devices list in iOs Provisioning profile page Created a new distribution profile for ad-hoc In xcode I chose the project and clicked on product->archive. I sent both the archive (ipa file) and mobile provision to the testers team. The application failed to install. I saw an answer of a developer to set in build settings the provisioning file to Code Signing Identities to the distribution profile here In

问题 I am trying to write a Winbugs/Jags model for modeling multi grain topic models (exactly this paper -> http://www.ryanmcd.com/papers/mg_lda.pdf) Here I would like to choose a different distribution based on a particular value. For Eg: I would like to do something like `if ( X[i] > 0.5 ) { Z[i] ~ dcat(theta-gl[D[i], 1:K-gl]) W[i] ~ dcat(phi-gl[z[i], 1:V]) } else { Z[i] ~ dcat(theta-loc[D[i], 1:K-loc]) W[i] ~ dcat(phi-loc[z[i], 1:V]) } ` Is this possible to be done in Winbugs/JAGS? 回答1: Winbugs

问题 I'm trying to superimpose a mixed distribution plot with a plot of identified component distributions , using ggplot2 package and a user-defined function for its stat_function() . I have tried two approaches . The distribution identification is normal in both cases: number of iterations= 11 summary of normalmixEM object: comp 1 comp 2 lambda 0.348900 0.65110 mu 2.019878 4.27454 sigma 0.237472 0.43542 loglik at estimate: -276.3643 A) However, in the first approach , the output contains the

问题 We have have a certain amount e.g. 300 units. This amount should be as evenly as possible distributed over 40 "slots" or "bins". It would be easy if each slot would be the same - so it would be 7,5 at each slot. However, the slots vary in size and we cannot "fill in" there more than its "size" allows for e.g. if its only 4. What we cannot "fill in" more than 4. Hence, we have to distribute more over the other ones. Lets assume that there is another limitation: A general filling in limit of e

问题 I'm currently developing an OpenCL-application for a very heterogeneous set of computers (using JavaCL to be specific). In order to maximize performance I want to use a GPU if it's available otherwise I want to fall back to the CPU and use SIMD-instructions. My plan is to implement the OpenCL-code using vector-types because my understanding is that this allows CPUs to vectorize the instructions and use SIMD-instructions. My question however is regarding which OpenCL-implementation to use. E.g

问题 I'm currently developing an OpenCL-application for a very heterogeneous set of computers (using JavaCL to be specific). In order to maximize performance I want to use a GPU if it's available otherwise I want to fall back to the CPU and use SIMD-instructions. My plan is to implement the OpenCL-code using vector-types because my understanding is that this allows CPUs to vectorize the instructions and use SIMD-instructions. My question however is regarding which OpenCL-implementation to use. E.g

问题 I'm a newbie to distutils and I have a problem that really has me stuck. I am compiling a package that requires an extension, so I make the extension thus: a_module = Extension( "amodule", ["initmodule.cpp"], library_dirs=libdirs, extra_objects = [ "unix/x86_64/lib/liba.so" "unix/x86_64/lib/lib.so", "unix/x86_64/lib/libc.so"], ) I then run the setup method: setup(name="apackage", version="7.2", package_dir = {'':instdir+'/a/b/python'}, packages=['apackage','package.tests'], ext_modules=[hoc

问题 I am facing some issues related with iOS Developer program and iOS Enterprise Program. One of my client ask me to suggest one of them. Please answer my questions related to iOS Enterprise Program- If i purchase an iOS Enterprise account so when it is available for in-house application distribution? How many device i have on which i can install my app? Do i need UDID of all devices? What if i want to add some new devices? If it is same Ad-hoc distribution the what is the expiry date of Ad-hoc