wpoely86

#!/usr/bin/perl -w
use strict;

### Identify instruction sets used in a binary file. ###

# Tavis Ormandy <[email protected]> 2003
# Improvments by Will Woods <[email protected]>
# Perl convertion by Georgi Georgiev <[email protected]>
# Updated by Ryan Hill <[email protected]>
# Updated by Ward Poelmans <[email protected]> 2009

wpoely86

diff -urN libspatialite-4.1.1.orig/configure.ac libspatialite-4.1.1/configure.ac
--- libspatialite-4.1.1.orig/configure.ac	2013-06-29 08:53:15.000000000 +0200
+++ libspatialite-4.1.1/configure.ac	2014-04-02 11:37:56.484423000 +0200
@@ -263,7 +263,7 @@
   LIBS="$GEOS_LDFLAGS"
   AC_SEARCH_LIBS(GEOSTopologyPreserveSimplify,geos_c,,AC_MSG_ERROR([could not find libgeos_c - you may need to specify the directory of a geos-config file using --with-geosconfig]))
   LIBS="$LIBS_SAVE"
-  LIBS=$LIBS$GEOS_LDFLAGS' -lgeos_c'
+  LIBS="$LIBS $GEOS_LDFLAGS -lgeos_c"
 

wpoely86

double arpackDiagonalize()
{
    // dimension of the matrix
    int n = dim;

    // number of eigenvalues to calculate
    int nev = 1;

    // reverse communication parameter, must be zero on first iteration
    int ido = 0;

wpoely86

/**
 * Helper for exact diagonalization: diagonalize the matrix given in mat with dimension dim, stores
 * the eigenvalues in eigs and optionally the eigenvectors in mat
 * @param dim the dimension of the matrix
 * @param mat the actual matrix (size: dim*dim)
 * @param eigs array of size dim to store eigenvalues
 * @param calc_eigenvectors whether or not the calculate the eigenvectors
 */
void Diagonalize(int dim, double *mat, double *eigs, bool calc_eigenvectors)
{

wpoely86

#!/usr/bin/env python3
"""
Generates all Clebsh Gordan coefficients starting from a given j1 and j2 and
outputs a html file. How to use:
./Clebsch-Gordan.py 0.5 0.5 > output.html
Ward Poelmans <[email protected]> (2014)
"""

import sys
import numpy as np

wpoely86

molecule BH {
    B 0 0 0.0
    H 0 0 2.328898308325
#    symmetry c1
    units au
}

set {
# exact ERI
    SCF_TYPE PK

wpoely86

#include <libplugin/plugin.h>
#include "psi4-dec.h"
#include <libparallel/parallel.h>
#include <liboptions/liboptions.h>
#include <libmints/mints.h>
#include <libpsio/psio.h>
#include <hdf5.h>
#include <boost/algorithm/string.hpp>
#include <boost/lexical_cast.hpp>

wpoely86

Diverging Stacked Bar Chart

We create a diverging stacked bar chart to plot a 5 point Likert scale. There a lots of ways to plot a Likert scale but according to Robbins & Heiberger, a diverging stacked bar chart is the best and I agree.

I've used D3.js. There is also an R package by Robbins & Heiberger.

The original can be found at github

wpoely86

    -----------------------------------------------------------------------
          PSI4: An Open-Source Ab Initio Electronic Structure Package
                              PSI 4.0.0-beta5 Driver

    J. M. Turney, A. C. Simmonett, R. M. Parrish, E. G. Hohenstein,
    F. A. Evangelista, J. T. Fermann, B. J. Mintz, L. A. Burns, J. J. Wilke,
    M. L. Abrams, N. J. Russ, M. L. Leininger, C. L. Janssen, E. T. Seidl,
    W. D. Allen, H. F. Schaefer, R. A. King, E. F. Valeev, C. D. Sherrill,
    and T. D. Crawford, WIREs Comput. Mol. Sci., (2011) (doi: 10.1002/wcms.93)

wpoely86

#include <libplugin/plugin.h>
#include "psi4-dec.h"
#include <libparallel/parallel.h>
#include <liboptions/liboptions.h>
#include <libmints/mints.h>
#include <libmints/sointegral_twobody.h>
#include <libpsio/psio.h>

#include <hdf5.h>