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// method for calculating the pseudo-Inverse as recommended by Eigen developers | |
template<typename _Matrix_Type_> | |
_Matrix_Type_ pseudoInverse(const _Matrix_Type_ &a, double epsilon = std::numeric_limits<double>::epsilon()) | |
{ | |
Eigen::JacobiSVD< _Matrix_Type_ > svd(a ,Eigen::ComputeFullU | Eigen::ComputeFullV); | |
// For a non-square matrix | |
// Eigen::JacobiSVD< _Matrix_Type_ > svd(a ,Eigen::ComputeThinU | Eigen::ComputeThinV); | |
double tolerance = epsilon * std::max(a.cols(), a.rows()) *svd.singularValues().array().abs()(0); | |
return svd.matrixV() * (svd.singularValues().array().abs() > tolerance).select(svd.singularValues().array().inverse(), 0).matrix().asDiagonal() * svd.matrixU().adjoint(); |
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#include "position.h" | |
#include "plucker.h" | |
int main() { | |
} |
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#!/bin/bash | |
# stop script on returned error code | |
set -e | |
# SCRIPT PARAMETERS | |
topdir=$HOME/aurora_build | |
compile_cores=20 | |
# GLOBAL VARS |
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import openmc | |
# constants | |
l = 1.0 | |
h = 1.0 | |
model = openmc.model.Model() | |
# materials |
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#!/usr/bin/env python | |
import numpy as np | |
from progressbar import progressbar | |
import openmc | |
import openmc.lib | |
# main parameters | |
n_axial = 500 |
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#! /bin/env python | |
from argparse import ArgumentParser | |
from pymoab import core, types | |
_VALID_GEOM_TYPES = ("Group", "Volume", "Surface", "Curve", "Vertex") | |
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#!/usr/bin/env python | |
import numpy as np | |
import argparse | |
from pymoab import core, types | |
# some convenience functions | |
def get_category(mbi, category): |