similar to: discrete passdb lookups for dovecot-auth

Hi, I have the following configuration in my dovecot.conf for Dovecot 2.2.21: passdb { driver = ldap args = /etc/dovecot/dovecot-ldap.conf.ext default_fields = allow_nets=local,127.0.0.1,10.255.1.0/24 } This triggers "auth: Panic" on POP3/IMAP logins as the below: Dec 22 14:57:39 localhost dovecot: auth: ldap(u0000,::1,<oiF8SHYngqsAAAAAAAAAAAAAAAAAAAAB>): allow_nets:

Hello, I'm trying to get `deliver` (the LDA) to function properly. I can get it to work without doing a user lookup, but for my own sense of sanity, I want to know what I'm doing wrong getting user lookups working. (I'm using dovecot 1.0.10). Here's what I have in the "auth default" section: auth default { mechanisms = plain login passdb ldap

Hello everyone, I'm trying to make dovecot do user authentication against a SQL database. The passwords (managed by Django) are stored as salted SHA1 encoded in hex. I monkey patched Django's password method so that the password hash is made with <password><salt> (Django does <salt><password>, the patched method was verified to return same value as

Hi, it would be nice to have an option to enable logging for timings without having to go with auth_verbose/auth_debug. If you try to track down if a slowdown for logging in comes from e.g. running out of login workers or if your auth backend is slow it would really help to get just a one line message per userdb/passdb with the timing for this lookup. something like:

hi- i'm using version 2.4.1, courtesy of debian testing, and noticed that in the web interface, the image for the battery voltage bar graph wasn't displaying. the other images (change, input, output, load) seem to be fine. the browser reports "500 internal server error", and apache reports "Premature end of script headers: upsimage.cgi, referer:

Hello to everybody, I'm in the process of setting up test mail server (Ubuntu 19.10 amd64 running as VM under Hyper-V) and got stuck on configuring master user authentication. I use GSSAPI authentication in parallel with PLAIN/LOGIN (pam backend that authenticates against my Active Directory domain) and this works as intended. I then tried adding simple static master passdb that simply

Dear all, I have a continuous variable that can take on values between 0 and 100, for example: x<-runif(100,0,100) I also have a second variable that defines a series of thresholds, for example: y<-c(3, 4.5, 6, 8) I would like to convert my continuous variable into a discrete one using the threshold variables: If x is between 0 and 3 the discrete variable should be 1 If x is between 3

Is there a package that will allow me to fit Brownian motion and Ornstein?Uhlenbeck models of evolution for discrete traits? I know that geiger and ouch have commands for fitting these models for continuous traits, but these aren't suitable for discrete trait evolution, correct? -- View this message in context:

Hi all, I am REALLY confused with the variance right now. for a discrete uniform distribution on [1,12] the mean is (1+12)/2=6.5 which is ok. y=1:12 mean(y) then var(y) gives me 13 1- on http://en.wikipedia.org/wiki/Uniform_distribution_%28discrete%29 wiki the variance is (12^2-1)/12=143/12 2-

Hi r-help, I have been using your RHmm package for some time and have recently had to try using the package for a new dataset. Basically I have a dataset with a number of discrete observation variables that change over time, and I would love to try modeling them using a HMM. Basically I was wondering if RHmm can be used to model a multivariate discrete HMM, i.e., the observations are a vector

Hello, I am using the mda package and in particular the fda routine to classify in term of gear a set of 20 trips. I preformed a flexible discriminant analysis (FDA) using a set of 151 trips. FDAT1 <- fda(as.factor(gear) ~ . , data =matrizR) A total of 22 predictors were considered. 20 of the predictors are "numeric" and 2 are "factors/discrete". The resulting FDA

Dear all, I am trying to simulate from discrete uniform distribution. But I could not find any in-built code in R. Could anyone help me please? Thanks in advance for the time and help. Cassie [[alternative HTML version deleted]]

On Wed, Sep 27, 2017 at 10:03 AM, Marcus Rueckert <darix at opensu.se> wrote: > On 2017-09-27 16:57:44 +0000, Mark Moseley wrote: > > I've been digging into the auth policy stuff with weakforced lately. > There > > are cases (IP ranges, so could be wrapped up in remote {} blocks) where > > it'd be nice to skip the auth policy (internal hosts that I can trust,

Hello list: I generate by simulation (using different procedures) two sample vectors of size N, each corresponding to a discrete variable and I want to text if these samples can be considered as having the same probability distribution (which is unknown). What is the best test for that? I've read that Kolmogorov-Smirnov and Anderson-Darling tests are restricted to continuous data

Hi everyone, We have been trying to construct a Lasso-cox model with discrete time. We conducted follow-up examinations on the epileptic attack after tumor surgical resection among glioma patients. The patients are followed-up in the 6/12/24 months after surgical resection, which makes the epilepsy-free time discrete (6/12/24 months). We calcluated many features from the T2-images

I want to create the mixture formulation of a discrete uniform ie, say f(x) = 1/10, for i = 1,2,3,4,5,6,7,8,9 and 10 and another discrete distribution which has the same values of x, but he probabilities can vary. Can this be done on any package in R? an if so, can the package estimate the 'probabilities' of each of the x value as well as the mixing proportion if I have the data?

The "tscount" package (see http://doi.org/10.18637/jss.v082.i05) comes with several count data time series. Maybe this is the kind of discrete data you were interested in? hth, Z On Tue, 2 Jan 2018, Eric Berger wrote: > Hi Rolf, > I looked at > https://docs.microsoft.com/en-us/azure/sql-database/sql-database-public-data-sets > > One of the first sets in the list is

What's the reommended way, in R, to determine the strength of association between a discrete variable and a continuous variable? Yes, I have read the manuals, trawled the archives, &c.

Hello, suppose one is forming a probability p(x,y), where the x,y axes are somewhat accidental and rotation is possible. I'm thinking about whether the discrete entropy H(x,y) should change if the probability is rotated in the x,y plane. My current conclusion is that it _does_ change, at least if the entropy is estimated via bins. As a simple example, suppose the probability mass is

Hello all, I'd like to announce the availability of a mailing list for a newly-formed SIG (Special Interest Group) dedicated to using R for Discrete Choice Modelling. This list is intended for discussion of issues revolving around the design and analysis of Discrete Choice (aka Stated Choice, Stated Preference or Choice-Based Conjoint) experiments. While R has good infrastructure for