added constraint description in docs, warning about constraint not being satisfied

Author: jonathan-taylor

selectiveInference/R/funs.inf.R

@@ -208,6 +208,10 @@ TG.limits = function(Z, A, b, eta, Sigma=NULL) {
 
     target_estimate = sum(as.numeric(eta) * as.numeric(Z))
 
+    if (max(A %*% as.numeric(Z) - b) > 0) {
+        warning('Contsraint not satisfied. A %*% Z should be elementwise less than or equal to b')
+    }
+
     if (is.null(Sigma)) {
         Sigma = diag(rep(1, n))
     }

selectiveInference/man/TG.interval.Rd

@@ -7,6 +7,7 @@ Truncated Gaussian confidence interval.
 \description{
 Compute truncated Gaussian interval of Lee et al. (2016) with
 arbitrary affine selection and covariance.
+Z should satisfy A %*% Z elementise less then or equal b.
 }
 \usage{
 TG.interval(Z, A, b, eta, Sigma=NULL, alpha=0.1, 

selectiveInference/man/TG.limits.Rd

@@ -7,6 +7,7 @@ Truncation limits and standard deviation.
 \description{
 Compute truncated limits and SD for use in computing
 p-values or confidence intervals of Lee et al. (2016).
+Z should satisfy A %*% Z elementise less then or equal b.
 }
 \usage{
 TG.limits(Z, A, b, eta, Sigma)  

selectiveInference/man/TG.pvalue.Rd

@@ -7,6 +7,7 @@ Truncated Gaussian p-value.
 \description{
 Compute truncated Gaussian p-value of Lee et al. (2016) with
 arbitrary affine selection and covariance.
+Z should satisfy A %*% Z elementise less then or equal b.
 }
 \usage{
 TG.pvalue(Z, A, b, eta, Sigma, null_value=0, bits=NULL)