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authorB. Watson <yalhcru@gmail.com>2020-10-11 16:10:57 -0400
committerWilly Sudiarto Raharjo <willysr@slackbuilds.org>2020-10-17 09:36:43 +0700
commit2c3623e58a45e056122804dbcc875d9d7f08f126 (patch)
treeb57f3442aa9e53f98fc2ccd7867fdb7e7f9e4752 /academic/dakota
parentc4b8c52a0783e0e8d0a994b5c1f508f46f22cb60 (diff)
academic/dakota: Fix README.
Signed-off-by: B. Watson <yalhcru@gmail.com> Signed-off-by: Willy Sudiarto Raharjo <willysr@slackbuilds.org>
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diff --git a/academic/dakota/README b/academic/dakota/README
index 452cf802eab69..3a0d5dbe15acb 100644
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The Dakota toolkit provides a flexible, extensible interface between
analysis codes and iteration methods. Dakota contains algorithms for
optimization with gradient and nongradient-based methods; uncertainty
-quantification with sampling, reliability, stochastic expansion, and
-epistemic methods; parameter estimation with nonlinear least squares
-methods; and sensitivity/variance analysis with design of experiments
-and parameter study capabilities. These capabilities may be used on
-their own or as components within advanced strategies such as
-surrogate-based optimization, mixed integer nonlinear programming, or
-optimization under uncertainty.
+quantification with sampling, reliability, stochastic expansion,
+and epistemic methods; parameter estimation with nonlinear least
+squares methods; and sensitivity/variance analysis with design of
+experiments and parameter study capabilities. These capabilities may
+be used on their own or as components within advanced strategies such
+as surrogate-based optimization, mixed integer nonlinear programming,
+or optimization under uncertainty.
-Optional dependency: openmpi (for distributed memory parallel capabilities)
+Optional dependency: openmpi (for distributed memory parallel
+capabilities)
-You can build with multiple jobs by setting the MAKEFLAGS environment variable.
+You can build with multiple jobs by setting the MAKEFLAGS environment
+variable.