text:
/* Base rules are the defaults. They are almost exclusively single element selectors but it could include attribute selectors, pseudo-class selectors, child selectors or sibling selectors. Essentially, a base style says that wherever this element is on the page, it should look like this. */

* {
  font-family: 'Source Sans Pro', 'Helvetica Neue', Helvetica, Arial, sans-serif;
  box-sizing: border-box;
}

body {
  padding: 0;
  margin: 0;
}

/* header specific styles */

header {
  height: auto;
  width: 100%;
  padding: 10px;
  position: fixed;
  top: 0;
  left: 0;
  background-color: rgba(0,0,0,0.7);
  z-index: 1000;
}

nav {
  width: 100%;
  display: inline-block;
  text-align: center;
}

nav a {
  font-weight: 200;
  margin: 0 10px;
  text-align: center;
  text-transform: uppercase;
  font-size: 2em;
}

/* page-wide styles */

a, a:link, a:visited {
  color: #bbb;
  text-decoration: none;
}

a:hover, a:active {
  font-weight: 400px;
}

h1, h2, h3, h4, h5, h6, p {
  color: white;
  font-weight: 200;
  text-align: left;
  text-transform: uppercase;
  margin: 0;
  padding: 0;
}

h1 { /* site title in welcome page */
  font-size: 5em;
  letter-spacing: -1px;
  margin-bottom: 10px;
}

h2 { /* welcome blurb */
  font-size: 2em;
  text-transform: none;
  margin-bottom: 20px;
  line-height: 1.5em;
  text-align: justify;
 }

h3 { /* name/about headers in footer */
  font-size: 3em;
  margin: 10px 0;
}

h4 { /* saved location header */
  font-size: 3em;
  margin: 0;
  padding-bottom: 20px;
  border: none;
  color: white;
  text-transform: uppercase;
  font-weight: 200;
}

h5 { /* saved location names */
  font-size: 3em;
  text-align: left;
  margin: 0 auto;
  color: white;
  font-weight: 300;
  line-height: 1.5em;
  text-transform: none;

}

h6 { /* delete link */
  font-size: 1em;
  text-transform: none;
  color: #000;
  font-weight: 300;
}

p {
  font-size: 2em;
}

hgroup {
  margin: 0 auto;
  padding: 0px;
}

img {
  width: 100%;
  height: auto;
  padding: 0;
  margin: 0;
}

section {
  /* min-height to be set with jquery to be 100% of window height */
  height: 100%;
  background-position: center;
  background-size: cover;
  background-repeat: no-repeat;
  padding: 70px 20px 20px 20px;
}

#welcome {
  padding-top: 270px;
}

#dashboard {
  padding: 40px;
}

/* form specific styles */

form{
  width: 100%;
  margin: 0 0 50px 0;
  padding: 0;
  border: none;

}

fieldset {
  margin: 0;
  padding: 0;
  border: none;
}

legend {
  font-size: 3em;
  margin: 0;
  padding: 0 0 20px 0;
  border: none;
  color: white;
  text-transform: uppercase;
  font-weight: 200;
}

label {
  font-size: 2em;
  width: 120px;
  margin-right: 10px;
  text-align: right;
  color: white;
  text-transform: uppercase;
  display: inline-block;
  font-weight: 300;
}

input {
  background-color: transparent;
  font-size: 2em;
  border: none;
  border-bottom: 2px solid white !important;
  display: inline-block;
  width: calc(100% - 133px);
  color: white;
}

textarea:focus,
input:focus,
.uneditable-input:focus {
  border-color: transparent;
  box-shadow: none;
  outline: 0 none;
}

address p {
  text-transform: none;
  font-size: 2em;
}

/* footer specific styles */

footer {
  width: 100%;
  height: 100%;
  padding: 50px 30px !important;
  background-color: #333333;
}

footer article {
  margin-top: 30px;
}

footer .greyscale {
  filter: grayscale(100%);
  -webkit-filter: grayscale(100%);
}

footer p {
  font-size: 2em;
  color: white;
  text-transform: none;
  margin-bottom: 20px;
}

license: MIT

license_type: permissive

branch_name: refs/heads/master

gha_language: JavaScript

extension: css


text:
@article{Marsh-2018-Multi-objective,
    title = "Multi-objective unstructured triangular mesh generation for use in hydrological and land surface models",
    author = "Marsh, Christopher B.  and
      Spiteri, Raymond J.  and
      Pomeroy, John W.  and
      Wheater, Howard S.",
    journal = "Computers {\&} Geosciences, Volume 119",
    volume = "119",
    year = "2018",
    publisher = "Elsevier BV",
    url = "https://aclanthology.org/G18-78001",
    doi = "10.1016/j.cageo.2018.06.009",
    pages = "49--67",
    abstract = "Abstract Unstructured triangular meshes are an efficient and effective landscape representation that are suitable for use in distributed hydrological and land surface models. Their variable spatial resolution provides similar spatial performance to high-resolution structured grids while using only a fraction of the number of elements. Many existing triangulation methods either sacrifice triangle quality to introduce variable resolution or maintain well-formed uniform meshes at the expense of variable triangle resolution. They are also generally constructed to only fulfil topographic constraints. However, distributed hydrological and land surface models require triangles of varying resolution to provide landscape representations that accurately represent the spatial heterogeneity of driving meteorology, physical parameters and process operation in the simulation domain. As such, mesh generators need to constrain the unstructured mesh to not only topography but to other important surface and sub-surface features. This work presents novel multi-objective unstructured mesh generation software that allows mesh generation to be constrained to an arbitrary number of important features while maintaining a variable spatial resolution. Triangle quality is supported as well as a smooth gradation from small to large triangles. Including these additional constraints results in a better representation of spatial heterogeneity than from classic topography-only constraints.",
}

repository: gwf-uwaterloo/gwf-publications

repo_name: gwf-uwaterloo/gwf-publications

branch_name: refs/heads/main

gha_language: Python

extension: bib


text:
@InProceedings{taghipour12,
  title = {Lifted Variable Elimination with Arbitrary Constraints},
  author = {Nima Taghipour and Daan Fierens and Jesse Davis and Hendrik Blockeel},
  pages = {1194--1202},
  abstract = {Lifted probabilistic inference algorithms exploit regularities in the structure of graphical models to perform inference more efficiently. More specifically, they identify groups of interchangeable variables and perform inference once for each group, as opposed to once for each variable. The groups are defined by means of constraints, so the flexibility of the grouping is determined by the expressivity of the constraint language. Existing approaches for exact lifted inference rely on (in)equality constraints. We show how inference methods can be generalized to work with arbitrary constraints. This allows them to capture a broader range of symmetries, leading to more opportunities for lifting. We empirically demonstrate that this improves inference efficiency with orders of magnitude, allowing exact inference in cases where until now only approximate inference was feasible.},
  pdf = {http://jmlr.org/proceedings/papers/v22/taghipour12/taghipour12.pdf},
}

repository: mreid/papersite

repo_name: mreid/papersite

gha_license_id: MIT

gha_language: TeX


text:
require linaro-image-common.inc

DESCRIPTION = "A small SDK based image for Linaro development work."

IMAGE_INSTALL += "${SDK_IMAGE_INSTALL}"

IMAGE_FEATURES += "\
	dev-pkgs \
	staticdev-pkgs \
	tools-debug \
	tools-sdk \
	"

repository: liyaoshi/meta-linaro

repo_name: liyaoshi/meta-linaro

gha_language: BitBake

extension: bb


text:
CAMNAME = "oscam-experimental"
DESCRIPTION = "${CAMNAME} ${PV} Open Source Softcam"
RDEPENDS = "${CAMNAME}"
RCONFLICTS = "enigma2-plugin-softcams-${CAMNAME}-cs enigma2-plugin-softcams-oscam-stable-cs enigma2-plugin-softcams-oscam-unstable-cs"
PACKAGE_ARCH = "all"
PN = "enigma2-plugin-softcams-${CAMNAME}"
PV = "1.20"
PR = "r4.${INC_PR}"

require softcamoscam.inc

gha_language: C


text:
@Book{xie2015,
  title = {Dynamic Documents with {R} and knitr},
  author = {Yihui Xie},
  publisher = {Chapman and Hall/CRC},
  address = {Boca Raton, Florida},
  year = {2015},
  edition = {2nd},
  note = {ISBN 978-1498716963},
  url = {http://yihui.name/knitr/},
}

@article{Anderson08,author ={Chris Anderson},
  title ={The end of theory: The data deluge makes the scientific method   obsolete},
  journal ={Wired magazine},
  volume ={16},
  year ={2008},
  number ={7},
  pages ={16--07},
  howpublished ={Available at\url{https://www.wired.com/2008/06/pb-theory/}}
  }

repository: GeoDaCenter/spatialinsights

repo_name: GeoDaCenter/spatialinsights


text:
body {
	padding: 0;
	/*margin: 20px;*/
	margin: 0;
	font-size: .9em;
	font-family: Arial;
	line-height: 1.5em;
}

.box {
	background-color: #CCC;
	border: solid 1px #999;
	text-align: center;
	padding: 10px 0;
}

.block-group .block-group .box {
	background-color: #CDF;
}


text:
.underground-form-container{
    width: 100%;
    text-align: center;
}

.underground-form-container form{
    width: 100%;
    display: flex;
    flex-wrap: wrap;
    justify-content: center;
}

@media(min-width: 560px){
    .underground-form-container form{
        flex-direction: column;
        align-items:center;
    }
}

.underground-form-container p{
    max-width: 269px;
    width: 100%;
    border: 1px solid black;
    padding: 7px;
    margin-top: 0px;
}

.input-container input{
    max-width: 280px;
    width: 87%;
    height: 35px;
    margin-bottom: 20px;
    text-align: center;
}

.input-container input:last-of-type{
    margin-bottom: 0px;
}

.postNews-container input::placeholder{
    text-align: center;
    font-size: 22px;
    border-radius: 15px;
    padding-right: 5px;
}

.postNews-container textarea::placeholder{
    text-align: center;
    padding-right: 5px;
    padding-top: 30px;
    font-size: 22px;
}

.post-underground-textarea{
    max-width: 280px;
    width: 86%;
    height: 120px;
    margin-bottom: 20px;
}

.counter{
    max-width: 284px;
    width: 88%;
    display: flex;
    justify-content: flex-end;
    transform: translateY(-20px);
    font-size: 14px;
    font-weight: 700;
    font-family: 'Alegreya Sans', 'serif';
}

@media(min-width: 560px){
    .counter{
        transform: translateY(-40px)
    }
}

  .post-underground-header{
    font-family: 'Alegreya Sans', 'serif';
    display: inline-block;
    color: white;
}

.select-container{
    display: flex;
    flex-wrap: wrap;
    justify-content: space-evenly;
    width: 100%;
    align-items: center;
    font-family: 'Alegreya Sans', 'serif';
    max-width: 300px;
}

.select-container select{
    height: 40px;
    min-width: 120px;
}

.input-container button{
    max-width: 280px;
    width: 88%;
    padding: 8px;
    margin-bottom: 20px;
}

repository: mariannas-web/front-end

repo_name: mariannas-web/front-end


text:
# - Try to find libattr
# Once done this will define
#  LibAttr_FOUND - System has libattr
#  LibAttr_INCLUDE_DIRS - The libattr include directories
#  LibAttr_LIBRARIES - The libraries needed to use libattr

FIND_LIBRARY(LibAttr_LIBRARIES
    NAMES attr
)

FIND_PATH(LibAttr_INCLUDE_DIRS
    NAMES attr/libattr.h
)

INCLUDE(FindPackageHandleStandardArgs)
FIND_PACKAGE_HANDLE_STANDARD_ARGS(LibAttr DEFAULT_MSG
    LibAttr_LIBRARIES
    LibAttr_INCLUDE_DIRS
)

# Hide these vars from ccmake GUI
MARK_AS_ADVANCED(
	LibAttr_LIBRARIES
	LibAttr_INCLUDE_DIRS
)

repository: akesandgren/mpifileutils

repo_name: akesandgren/mpifileutils

extension: cmake


text:
@book{Xbook,
author = " Bird, Steven and Klein, Erwan and Loper, Edward",
title = "{N}atural {L}anguage {P}rocessing with {P}ython",
publisher = "O'REILLY",
year = ""
}

@misc{website:Stop_words,
author = "Wikipedia",
title = "Stop words",
month = "January",
year = "2015",
url = "http://en.wikipedia.org/wiki/Stop_words"
}

@misc{website:tfidf,
author = "Wikipedia",
title = "tf–idf",
month = "February",
year = "2015",
url = "http://en.wikipedia.org/wiki/Tf%E2%80%93idf"
}

@misc{website:Naive_Bayes_classifier,
author = "",
title = "Naive Bayes classifier",
month = "February",
year = "2015",
url = "http://www.ic.unicamp.br/~rocha/teaching/2011s2/mc906/aulas/naive-bayes-classifier.pdf"
}

@misc{website:data_set,
author = "",
title = "The Twitter Political Corpus",
month = "February",
year = "2015",
url = "http://www.usna.edu/Users/cs/nchamber/data/twitter/"
}

@techreport{Maximum_Entropy_for_text_Classification,
author = "Kamal Nigam and John Laffety and Andrew McCallum",
title = "Using Maximum Entropy for text Classification",
institution = "School of computer Science Carnegie Mellon University Pittsburgh",
year = "",
}

@techreport{Maximum_Entropy_for_text_Classification(2),
author = "Hai Leong Chieu and Hwee Tou Ng",
title = "Named Entity Recognition: A Maximum Entropy Approach
Using Global Information",
institution = "DSO National Laboratories. Department of Computer Science School of Computing National University of Singapore",
name = "",
year = "",
}

@techreport{Why_We_Twitter,
author = "Akshay Java and Xiaodan Song and Tim Finin and Belle Tseng",
title = "Why We Twitter: Understanding Microblogging Usage and Communities",
institution = "University of Maryland Baltimore County, NEC Laboratories America",
name = "",
year = "",
}

@techreport{Short_Text_Feature_Selection,
author = "Zitao Liu and Wenchao Yu and Wei Chen and Shuran Wang and Fengyi Wu",
title = "Short Text Feature Selection for Micro-blog Mining",
institution = "International School of Software Wuhan University Wuhan, China. School of Electronics and Information Engineering Sichuan University Chengdu, China",
name = "",
year = "",
}

@techreport{Sentiment_Analysis,
author = "Julie Kane Ahkter and Steven Soria",
title = "Sentiment Analysis: Facebook Status Messages",
institution = "",
name = "",
year = "",
}

@techreport{Sentiment_Analysis(2),
author = "Alec Go and Richa Bhayani and Lei Huang",
title = "Twitter Sentiment Classification using Distant Supervision",
institution = "Stanford University",
name = "",
year = "",

}

repository: HaythemSahbani/Text-Mining

repo_name: HaythemSahbani/Text-Mining


text:
SUMMARY = "PRU Ethernet firmware for AM65x SR1.0"

require recipes-bsp/ti-linux-fw/ti-linux-fw.inc

PV = "${PRUETH_FW_AM65X_VERSION}"
PR = "${INC_PR}.0"

CLEANBROKEN = "1"

COMPATIBLE_MACHINE = "am65xx"

PACKAGE_ARCH = "${MACHINE_ARCH}"

S = "${WORKDIR}/git"

TARGET = " \
    am65x-pru0-prueth-fw.elf \
    am65x-pru1-prueth-fw.elf \
    am65x-rtu0-prueth-fw.elf \
    am65x-rtu1-prueth-fw.elf \
"

do_install() {
	install -d ${D}${nonarch_base_libdir}/firmware/ti-pruss
	for f in ${TARGET}; do
		install -m 0644 ${S}/ti-pruss/$f ${D}${nonarch_base_libdir}/firmware/ti-pruss/$f
	done
}

FILES:${PN} = "${nonarch_base_libdir}/firmware"

INSANE_SKIP:${PN} = "arch"

repository: YoeDistro/meta-ti

repo_name: YoeDistro/meta-ti


text:
@article{Rizzi:2012b,
 abstract = {This paper explores the inference of small-scale, atomistic parameters, based on the specification of large, or macroscale, observables. Specifically, we focus on estimating a set of force-field parameters for the four-site, TIP4P, water model, based on a synthetic problem involving isothermal, isobaric molecular dynamics (MD) simulations of water at ambient conditions. We exploit the polynomial chaos (PC) expansions developed in Part I as surrogate representations of three macroscale observables, namely density, self-diffusion, and enthalpy, as a function of the force-field parameters. We analyze and discuss the use of two different PC representations in a Bayesian framework for the inference of atomistic parameters, based on synthetic observations of three macroscale observables. The first surrogate is a deterministic PC representation, constructed in Part I using nonintrusive spectral projection (NISP). An alternative strategy exploits a nondeterministic PC representation obtained using Bayesian inference of PC coefficients. We analyze the sensitivity of selected force-field parameters to the macroscale data, namely by exploiting the surrogate models to derive suitable “response” surfaces in the space of random parameters. The performance of both inference strategies is then examined in light of this analysis. The results show that each parameter is very sensitive to certain observables, while being only minimally affected by others. We show that a suitable choice of the observables allows us to recover the presumed “true” set of parameters with high accuracy even with low-order surrogate models.},
 author = {F. Rizzi and O.M. Knio and H.N. Najm and B.J. Debusschere
and K. Sargsyan and M. Salloum and H. Adalsteinsson},
 doi = {10.1137/110853170},
 journal = {SIAM J. Multiscale Model. Simul},
 month = {december},
 number = {4},
 pages = {1460-1492},
 title = {Uncertainty Quantification in MD Simulations. Part II:
Inference of force-field parameters},
 volume = {10},
 year = {2012}
}


text:
@Manual{R_Markdown_介紹,
  title = {R Markdown 介紹},
  author = {林茂廷},
  year = {2017},
  url = {https://bookdown.org/tpemartin/rmarkdown_intro/#markdown},
}

@Manual{Authoring_Books,
  title = {bookdown: Authoring Books and Technical Documents with R Markdown},
  author = {Yihui Xie},
  year = {2019},
  url = {https://bookdown.org/yihui/bookdown/},
}

@Manual{Minimal,
  title = {A Minimal Book Example},
  author = {Ben Marwick},
  year = {2016},
  url = {https://benmarwick.github.io/bookdown-ort/mods.html},
}
@Manual{NTU,
  title = {NTU thesis},
  author = {廖永賦},
  year = {2019},
  url = {https://yongfu.name/ntuthesis/doc/},
}


text:
@article{example3,
  title = {Comparison of Minimally Invasive Tissue Sampling With Conventional Autopsy to Detect Pulmonary Pathology Among Respiratory Deaths in a Resource-Limited Setting},
  author={Drucilla J Roberts, Henry N Njuguna, Barry Fields, Corinne L Fligner, Sherif R Zaki, M Kelly Keating, Emily Rogena, Edwin Walong, Andrew K Gachii, Elizabeth Maleche-Obimbo, Grace Irimu, John Mathaiya, Noelle Orata, Rosemarie Lopokoiyit, Jackson Michuki, Gideon O Emukule, Clayton O Onyango, Stella Gikunju, Collins Owuor, Peter K Muturi, Milka Bunei, Marc-Alain Widdowson, Joshua A Mott, Sandra S ChavesD},
  journal = {American Journal of Clinical Pathology},
  year    = 2019,
  volume  = 152,
  number  = 1
  pages = 36–49
}

repository: DCollinsOwuor/website

repo_name: DCollinsOwuor/website


text: @article{Cardoso06Poseidon,	author = {Cardoso, Jorge},	date-added = {2018-04-25 20:02:07 +0000},	date-modified = {2018-04-25 20:02:07 +0000},	journal = {International Journal of Cooperative Information Systems (IJCIS)},	number = {1},	owner = {Jorge Cardoso},	pages = {23-55},	refid = {23},	timestamp = {2010.08.26},	title = {Poseidon: A framework to assist Web process design based on business cases},	url = {http://www.worldscinet.com/ijcis/},	volume = {15},	webpdf = {/Papers/JA-2006-007-IJ-Coop-IS-Poseidon-15(1)-2006.pdf},	year = {2006},	Bdsk-Url-1 = {http://www.worldscinet.com/ijcis/}}


cell_type: markdown

source: This script will go into a folder of your choice and update the data in all the csv files in that folder. Mainly it will check for certain conditions in rows of certain columns and delete rows.

source: 1. Analyse csv files in a certain 'input folder':

source: * a) if they dont match a given structure those csv files will be moved to a 'bad column structure' folder.

source: * b) if they match the structure they will stay in the 'input folder'.

source: * a) Read the csv file into a new 'processed' file and then delete rows that don't contain any data.

source: * c) Count and delete 'Quality Assurance (QA)' Rows from the processed file. Note: QA rows are defined as rows without anything in the 'LOCATIONCODE' column AND they contain EITHER 'Blind Dup A' OR 'Field Blank' in the 'LocationDescription' column.

source: * d) Create a new file (NoSPT file) from the 'processed file' leaving only the rows without SPT codes. Remove the rows without SPT codes from the 'processed' file. A csv with the original filename with appended tag '-NoSPT' is created for the data with this issue.

source: * e) Create a new file (Retests file) from the 'processed file' leaving only the rows that are retests. Note: retests are defined as rows with the same location, date-time, and test methods; but have a different result. Remove the rows that are retests from the 'processed' file. A csv with the original filename with appended tag '-Retests' is created for the data with this issue.

source: * f) Create an Excel file for the counts of issues in each file that is analysed.

source: * a) the input file where all the csv's you wish to process live (Input_path_CSVs)

source: * b) Output file where all the csv's with unreadable column stuctures will be placed (Output_path_bad_structure)

source: * c) Output file where all the csv's  with only retests will be placed (Output_path_processed_csv)

source: * d) Output file where all the csv's  without SPT codes will be placed (Output_path_processed_csv)

source: * e) Output file where all the processed csv's will be placed (Output_path_processed_csv)

source: 2. Set the file paths for 1) under 'Input Variables' cell below. Also choose the filepath where you want the generated Report to be placed (Output_path_Report)

source: 3. Set the delimiter 'Input Variables'. Generally csv files use a comma (,) but I have it set to pipe (|) as default

cell_type: code

source:
import pandas as pd
import numpy as np
import os
import re
import glob
import csv

source: # Directory of the csv files you want to process

source: # Can change to xlsx if needed, other changes will be nessesary to code

source: # Csv files seperator for input and output files..generally (,) or (|)

source: # Output path of CSV Files with Structure that can't be Analysed

source: # Output path of Report on Analysed files

source: ### Save CSV Filenames in a List and Dataframe

source: filenames = [i for i in glob.glob('*.{}'.format(Extension))]

source: print(NumFiles, 'files will be processed')

source: ### Find which files dont have 'LOCATIONCODE' or 'LocationDescription' columns

source: # Save an individual file as a DataFrame Object to analyse

source: df_file = pd.read_csv(filename, sep=Delimiter, index_col=False, engine='python')

source: if ('LOCATIONCODE' in df_file.columns) and ('LocationDescription' in df_file.columns):

source: print('Number of Files that can be Analysed:')

source: print("Number of Files that can't be Analysed:")

source: ### Move Files with Weird Column Structure to Weird Folder

source: ### Loop though each file and Process it, Create Excel Report on Changes Made

source: #Create an Empty Dataframe for Report Numbers

source: List_Columns = ['Filename', 'Total Rows', 'Duplicates', 'Retests', 'QA Data', 'No SPT Code']

source: # Loop through each csv file in the input directory

source: # Set File Identifiers to Not Guilty untill proven guilty

source: # Delete Rows with everything missing in the row

source: df_file = df_file.dropna(axis='index', how='all')

source: # Check and Find if Blanks exist in Location Code Rows

source: # Check and Find if Blanks exist in Location Description Rows

source: Series_Loc_Desc = Series_Loc_Desc.fillna(' ')

source: bools_bd = Series_Loc_Desc == 'Blind Dup A'

source: bools_bd = np.logical_and(bools_ml, bools_bd)

source: bools_fb = Series_Loc_Desc == 'Field Blank'

source: bools_fb = np.logical_and(bools_ml, bools_fb)

source: bools_qa = np.logical_or(bools_bd, bools_fb)

source: # Fixing QA Data and update DataFrame object if neccesary

source: # Filter Out Quality Control Data from DataFrame Object

source: # Check if SPT's still don't exist in Location Code Rows

source: Array_Loc_Codes = bools_good_sptz = df_file['LOCATIONCODE']

source: # Create Array of Loc-Codes and Fill Blank Locations with a space so that we can check if it begins with SPT

source: Array_Loc_Codes = Array_Loc_Codes.fillna(' ')

source: # Generate Array of Booleans for rows that have SPT's

source: # Save bad SPT codes in data to a new dataframe

source: # Create dataframe for stuff that can't load

source: # Leave only Bad SPT data in 'df_cant_load' Dataframe

source: # Filter Orginal Dataframe 'df_file' to delete SPT rows that won't load

source: String_Row =  str(row['LOCATIONCODE']) + str(row['SAMPLEDATE']) + str(row['TEST_KEY_CODE']) + str(row['RESULT'])

source: # Append the row to the list of Rows to Check for Duplicates

source: # Create Array of Rows from List of Rows

source: # Decide if there are any exact duplicates

source: if len(np.unique(Array_Raw_Items_Results)) != len(Array_Raw_Items_Results):

source: # Find the rows where the exact duplicates live

source: # Create a dictionary of duplicate checker keys vs numvber of duplicates

source: unique, counts = np.unique(Array_Raw_Items_Results, return_counts=True)

source: Dict_Unique_Counts = dict(zip(unique, counts))

source: #Create a list of keys for duplicates only

source: List_Duplicate_Keys = ([key for key, val in Dict_Unique_Counts.items() if val > 1])

source: # Find which Row Strings are exact duplicates and add their Index to a list

source: # Get the row index's of the duplicate Key

source: List_Indexes = [i for i, j in enumerate(List_Row_Key) if j == key]

source: # Remove Fist Duplicate from List because we let the first one load

source: # Count the number of Duplicates that will be deleted for Report

source: # Print feedback on Rows that are being deleted

source: print('Deleting Duplicate Rows from:', filename)

source: # Delete the rows that are duplicates from dataframe df_file

source: # Append the Row String Item to the list of Rows

source: # Create a dictionary of Row Strings to number of Retests

source: List_Retest_Keys = ([key for key, val in Dict_Unique_Counts.items() if val > 1])

source: # Find which Row Indexes are exact duplicates and add their Index to a list

source: # Convert the list of Bools to a Numpy Array

source: # Create a new dataframe 'df_Retests' for only Retests

source: # Delete the rows that are Retests from dataframe df_file

source: List_Row_Report = [filename, Int_Total_Rows, Int_Dup_Rows, Int_Retest_Rows, Int_QA_Rows, Int_Bad_SPTz]

source: df_Temp_Report = pd.DataFrame([List_Row_Report], columns=List_Columns)

source: df_Report = df_Report.append(df_Temp_Report, ignore_index=True)

source: # Create New Processed File if 1 or more rows

source: new_filename = filename[:-4] + '-processed' + filename[-4:]

source: Output_filename = Output_path_processed_csv + new_filename

source: # Create New Bad File for fixes that can't be made

source: new_filename = filename[:-4] + '-NoSPTs' + filename[-4:]

source: Output_filename = Output_path_badSPT + new_filename

source: new_filename = filename[:-4] + '-Retests' + filename[-4:]

source: Output_filename = Output_path_Retests + new_filename

source: Report_path_filename = Output_path_Report + 'Report.xlsx'

display_name: Python 3

python

file_extension: .py

mimetype: text/x-python

nbconvert_exporter: python

extension: script


text:
require x42-plugins.inc

SUMMARY = "stereo DJ X-fade plugin"

LICENSE = "GPLv2"
LIC_FILES_CHKSUM = "file://COPYING;md5=b234ee4d69f5fce4486a80fdaf4a4263"

DEPENDS = "lv2"

SRCREV = "06b27468de9689d53e9bfe24734ebd91a344b71e"
SRC_URI = "git://github.com/x42/xfade.lv2.git \
           file://0001-lv2-update-modgui-and-.TTL-resources.patch \
           file://0001-lv2-update-modgui-and-.TTL-resources.tgz \
           "


text:
DESCRIPTION = "RTC alarm handling library for GPE"
SECTION = "gpe/libs"
PRIORITY = "optional"
LICENSE = "LGPL"
PR = "r4"

DEPENDS = "glib-2.0 sqlite"

inherit autotools pkgconfig gpe

do_stage () {
autotools_stage_all
}

repository: Terentyev/familiar-linux

repo_name: Terentyev/familiar-linux


text:
DESCRIPTION = "Evince is a document viewer for document formats like pdf, ps, djvu."
LICENSE = "GPL"
SECTION = "x11/office"
DEPENDS = "nautilus gnome-icon-theme tiff libxt espgs gnome-doc-utils poppler libxml2 gtk+ gconf libglade gnome-keyring "
DEPENDS += "gnome-doc-utils-native"

RDEPENDS_${PN} = "espgs gnome-icon-theme"
PR = "r2"

inherit gnome pkgconfig gtk-icon-cache

SRC_URI += "file://cross-compile-fix.patch"

SRC_URI[archive.md5sum] = "a55f1997891a64157286b6f6b00f8458"
SRC_URI[archive.sha256sum] = "36dfee4e973421f15cb51c9b1c84784523592dc81feb6465fb59f87b8f7f8bf7"

EXTRA_OECONF = "  \
                 --enable-thumbnailer \
                 --enable-nautilus \
                 --disable-scrollkeeper \
                 --enable-djvu \
                 --enable-pixbuf \
		 "

do_install_append() {
	sed -i "s/NoDisplay=true//" ${D}${datadir}/applications/evince.desktop
	sed -i "s/;Viewer;/;Viewer;Office;/" ${D}${datadir}/applications/evince.desktop
	install -d install -d ${D}${datadir}/pixmaps
	install -m 0755 ${S}/data/icons/48x48/apps/evince.png ${D}${datadir}/pixmaps/
}

FILES_${PN}-dbg += " \
                    ${libdir}/evince/1/backends/.debug \
                    ${libdir}/evince/2/backends/.debug \
                   "

PACKAGES =+ "evince-nautilus-extension"

FILES_evince-nautilus-extension = "${libdir}/nautilus/*/*so"

repository: overo/overo-oe-natty

repo_name: overo/overo-oe-natty

branch_name: HEAD


text:
LICENSE = "GPL"
DESCRIPTION = "GPE bluetooth support"
SECTION = "gpe"
PRIORITY = "optional"
MAINTAINER = "Florian Boor <florian.boor@kernelconcepts.de>"

DEPENDS = "gtk+ libdisplaymigration libgpewidget openobex libgpevtype bluez-libs sqlite dbus libglade blueprobe bluez-utils-dbus libcontactsdb"
RDEPENDS = "bluez-utils-dbus blueprobe"

GPE_TARBALL_SUFFIX= "bz2"
inherit gpe autotools

FILES_${PN} += '${datadir}/bluez-pin'

repository: BackupTheBerlios/openslug-svn

repo_name: BackupTheBerlios/openslug-svn


text:
@article{peixoto_graph-tool_2014,
         title = {The graph-tool python library},
         url = {http://figshare.com/articles/graph_tool/1164194},
         doi = {10.6084/m9.figshare.1164194},
         urldate = {2014-09-10},
         journal = {figshare},
         author = {Peixoto, Tiago P.},
         year = {2014},
         keywords = {all, complex networks, graph, network, other}}

repository: AntonieV/RADSeq

repo_name: AntonieV/RADSeq

extension: bibtex


text:
@MISC{Ukrop2011,
  author = {Lubo\v{s} Ukrop},
  title = {New approaches in graph visualization},
  url = {http://vgg.fiit.stuba.sk/wordpress/2011-03/new-approaches-in-graph-visualization-lubos-ukrop/},
  year = {2011},
  note = {retrieved 18-JUN-2011}
}

repository: vis-au/treevisnet

repo_name: vis-au/treevisnet


text:
DESCRIPTION = "This provides a recipe for running run-benchmark and \
               browserperfdash-benchmark perf test scripts"

SRCREV = "f48310dcbab76037985cc0b2eeb3caa69e5b4c45"
SRC_URI = "git://github.com/Igalia/browserperfrunner.git;protocol=https;branch=master"

S = "${WORKDIR}/git"

LICENSE = "BSD-2-Clause"
LIC_FILES_CHKSUM = "file://browserperfdash-benchmark;md5=0447dc08401181d17386fac95e7524f7"

PACKAGES = "${PN}"

# Note: this recipe depends on meta-openembedded/meta-python for python-psutil
# And the dromaeo test needs the crc32 binary that is provided by libarchive-zip-perl
RDEPENDS:${PN} = " curl make patch perl procps psmisc python python-misc \
                   python-modules python-psutil python-setuptools \
                   gobject-introspection python-pygobject gtk+3 ruby \
                   subversion libarchive-zip-perl"

# This recipe still requires python2.
# So on Yocto dunfell and later its needed to use meta-python2
# Port to python3 tracked at https://github.com/Igalia/browserperfrunner/issues/3
inherit ${@bb.utils.contains("BBFILE_COLLECTIONS", "meta-python2", "python-dir", "", d)}

python() {
    if "meta-python2" not in d.getVar("BBFILE_COLLECTIONS").split():
        raise bb.parse.SkipRecipe("Requires meta-python2 to be present.")
}

do_install() {
    install -d ${D}${bindir}
    install -d ${D}${PYTHON_SITEPACKAGES_DIR}
    install -m 0755 ${S}/browserperfdash-benchmark ${D}${bindir}
    install -m 0755 ${S}/run-benchmark ${D}${bindir}
    cp -dr --preserve=mode,timestamp ${S}/webkitpy ${D}${PYTHON_SITEPACKAGES_DIR}/
}

FILES:${PN} = "${bindir}/* ${PYTHON_SITEPACKAGES_DIR}/*"

repository: YoeDistro/meta-webkit

repo_name: YoeDistro/meta-webkit


text:
SECTION = "x11/wm"
DESCRIPTION = "Matchbox window manager common files"
LICENSE = "GPL"
DEPENDS = "libmatchbox"
PR = "r2"

SRC_URI = "http://projects.o-hand.com/matchbox/sources/${PN}/0.9/${PN}-${PV}.tar.gz \
           file://no-utilities-category.patch;patch=1 \
           file://add-media-category.patch;patch=1"

inherit autotools  pkgconfig

EXTRA_OECONF = "--enable-pda-folders"

FILES_${PN} = "${bindir} \
	       ${datadir}/matchbox/vfolders \
	       ${datadir}/pixmaps"

repository: jdegges/gumstix-pip-oe

repo_name: jdegges/gumstix-pip-oe


text:
require xorg-doc-common.inc
PE = "1"

FILES_${PN} += " /usr/share/X11/sgml"

SRC_URI[archive.md5sum] = "f930e5be117922f0841614c8d43f1ae8"
SRC_URI[archive.sha256sum] = "4def78f2e0e002f5693b61b53ab4325fbc150d3614fe53818e8df9b365a4dbea"


text:
@article{Darwiche2011,
author = {Darwiche, Adnan},
doi = {10.5591/978-1-57735-516-8/IJCAI11-143},
file = {:Users/sholtzen/Documents/Mendeley Desktop/Darwiche/IJCAI International Joint Conference on Artificial Intelligence/143.pdf:pdf},
isbn = {9781577355120},
issn = {10450823},
journal = {IJCAI International Joint Conference on Artificial Intelligence},
keywords = {Knowledge Representation, Reasoning, and Logic},
pages = {819--826},
title = {{SDD: A new canonical representation of propositional knowledge bases}},
year = {2011}
}

@article{Vlasselaer,
author = {Vlasselaer, Jonas and Renkens, Joris and Broeck, Guy Van Den and Raedt, Luc De},
file = {:Users/sholtzen/Documents/Mendeley Desktop/Vlasselaer et al/Unknown/plp{\_}sdd.pdf:pdf},
title = {{Compiling Probabilistic Logic Programs into Sentential Decision Diagrams}}
}

repository: SHoltzen/verified-sdd

repo_name: SHoltzen/verified-sdd


text:
@inproceedings{2016-ZNFB,
 abstract = {In this work we present a new local, vertex-level measure of community change. Our measure detects vertices that change community membership due to the actions (edges) of a vertex itself and not only due to global community shifts. The local nature of our measure is important for analyzing real graphs because communities may change to a large degree from one snapshot in time to the next. Using both real and synthetic graphs, we compare our measure to an alternative, global approach. Both approaches detect community switching vertices in a synthetic example with little overall community change. However, when communities do not evolve smoothly over time, the global approach flags a very large number of vertices, while our local method does not.},
 address = {Los Alamitos, CA},
 author = {Anita Zakrzewska and Eisha Nathan and James P. Fairbanks and David A. Bader},
 bibsource = {dblp computer science bibliography, https://dblp.org},
 biburl = {https://dblp.org/rec/bib/conf/asunam/ZakrzewskaNFB16},
 booktitle = {2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016, San Francisco, CA, USA, August 18-21, 2016},
 doi = {10.1109/ASONAM.2016.7752257},
 groups = {Edited},
 pages = {349--353},
 publisher = {IEEE Computer Society},
 timestamp = {Tue, 23 May 2017 01:00:00 +0200},
 title = {A local measure of community change in dynamic graphs},
 url = {https://doi.org/10.1109/ASONAM.2016.7752257},
 year = {2016}
}

gha_language: Shell


text:
@article{frank1957perceptron,
  title={The perceptron a perceiving and recognizing automaton},
  author={Rosenblatt, Frank},
  journal={tech. rep., Technical Report 85-460-1},
  year={1957},
  publisher={Cornell Aeronautical Laboratory}
}

@article{Rosenblatt1958,
  title={The perceptron: a probabilistic model for information storage and organization in the brain.},
  author={Rosenblatt, Frank},
  journal={Psychological review},
  volume={65},
  number={6},
  pages={386},
  year={1958},
  publisher={American Psychological Association}
}

@misc{hebb1949organization,
  title={The organization of behavior: A neuropsychological theory},
  author={Hebb, Donald O and others},
  year={1949},
  publisher={New York: Wiley}
}

@article{stone2010opencl,
  title={OpenCL: A parallel programming standard for heterogeneous computing systems},
  author={Stone, John E and Gohara, David and Shi, Guochun},
  journal={Computing in science \& engineering},
  volume={12},
  number={3},
  pages={66--73},
  year={2010},
  publisher={IEEE}
}

@article{DBLP:journals/corr/abs-1211-5590,
  author    = {Fr{\'{e}}d{\'{e}}ric Bastien and
               Pascal Lamblin and
               Razvan Pascanu and
               James Bergstra and
               Ian J. Goodfellow and
               Arnaud Bergeron and
               Nicolas Bouchard and
               David Warde{-}Farley and
               Yoshua Bengio},
  title     = {Theano: new features and speed improvements},
  journal   = {CoRR},
  volume    = {abs/1211.5590},
  year      = {2012},
  url       = {http://arxiv.org/abs/1211.5590},
  archivePrefix = {arXiv},
  eprint    = {1211.5590},
  timestamp = {Wed, 07 Jun 2017 14:40:20 +0200},
  biburl    = {http://dblp.org/rec/bib/journals/corr/abs-1211-5590},
  bibsource = {dblp computer science bibliography, http://dblp.org}
}

@inproceedings{shastri2017emergence,
  title={Emergence of Neuromorphic Photonics},
  author={Shastri, Bhavin J and de Lima, Thomas Ferreira and Tait, Alexander and Nahmias, Mitchell A and Prucnal, Paul R},
  booktitle={Photonics in Switching},
  pages={PTu3C--4},
  year={2017},
  organization={Optical Society of America}
}

@article{sciamHBP,
 ISSN = {00368733, 19467087},
 URL = {http://www.jstor.org/stable/26014516},
 author = {Henry Markram},
 journal = {Scientific American},
 number = {6},
 pages = {50-55},
 publisher = {Scientific American, a division of Nature America, Inc.},
 title = {THE HUMAN BRAIN PROJECT},
 volume = {306},
 year = {2012}
}

@INPROCEEDINGS{roadDetection,
author={M. Foedisch and A. Takeuchi},
booktitle={Proceedings. The 7th International IEEE Conference on Intelligent Transportation Systems (IEEE Cat. No.04TH8749)},
title={Adaptive real-time road detection using neural networks},
year={2004},
volume={},
number={},
pages={167-172},
keywords={feature extraction;image colour analysis;learning (artificial intelligence);neural nets;object detection;road vehicles;adaptive real time road detection;automatic adaptation system;autonomous driving;color feature algorithm;color histograms;manual road annotations reduction;network training;neural networks;road images;Adaptive systems;Feature extraction;Focusing;Histograms;Intelligent networks;Intelligent systems;NIST;Neural networks;Real time systems;Roads},
doi={10.1109/ITSC.2004.1398891},
ISSN={},
month={Oct},}

@article{soman2016recent,
  title={Recent trends in neuromorphic engineering},
  author={Soman, Sumit and Suri, Manan and others},
  journal={Big Data Analytics},
  volume={1},
  number={1},
  pages={15},
  year={2016},
  publisher={BioMed Central}
}

@article{de2017progress,
  title={Progress in neuromorphic photonics},
  author={de Lima, Thomas Ferreira and Shastri, Bhavin J and Tait, Alexander N and Nahmias, Mitchell A and Prucnal, Paul R},
  journal={Nanophotonics},
  volume={6},
  number={3},
  pages={577--599},
  year={2017},
  publisher={De Gruyter}
}

@article{priem2005optical,
  title={Optical bistability and pulsating behaviour in Silicon-On-Insulator ring resonator structures.},
  author={Priem, Gino and Dumon, Pieter and Bogaerts, Wim and Van Thourhout, Dries and Morthier, Geert and Baets, Roel},
  journal={Optics express},
  volume={13},
  number={23},
  pages={9623--9628},
  year={2005},
  publisher={Optical Society of America}
}

@article{van2017advances,
  title={Advances in photonic reservoir computing},
  author={Van der Sande, Guy and Brunner, Daniel and Soriano, Miguel C},
  journal={Nanophotonics},
  volume={6},
  number={3},
  pages={561--576},
  year={2017},
  publisher={De Gruyter}
}

@article{dejonckheere2014all,
  title={All-optical reservoir computer based on saturation of absorption},
  author={Dejonckheere, Antoine and Duport, Fran{\c{c}}ois and Smerieri, Anteo and Fang, Li and Oudar, Jean-Louis and Haelterman, Marc and Massar, Serge},
  journal={Optics express},
  volume={22},
  number={9},
  pages={10868--10881},
  year={2014},
  publisher={Optical Society of America}
}

@article{haynes2015reservoir,
  title={Reservoir computing with a single time-delay autonomous Boolean node},
  author={Haynes, Nicholas D and Soriano, Miguel C and Rosin, David P and Fischer, Ingo and Gauthier, Daniel J},
  journal={Physical Review E},
  volume={91},
  number={2},
  pages={020801},
  year={2015},
  publisher={APS}
}

@phdthesis{mancinelli2013linear,
  title={Linear and non linear coupling effects in sequence of microresonators},
  author={Mancinelli, Mattia Mancinelli},
  year={2013},
  school={University of Trento}
}

@phdthesis{borghi2016linear,
  title={Linear, nonlinear and quantum optics in Silicon Photonics},
  author={Borghi, Massimo},
  year={2016},
  school={University of Trento}
}

@article{chen2012bistability,
  title={Bistability and self-pulsation phenomena in silicon microring resonators based on nonlinear optical effects},
  author={Chen, Shaowu and Zhang, Libin and Fei, Yonghao and Cao, Tongtong},
  journal={Optics Express},
  volume={20},
  number={7},
  pages={7454--7468},
  year={2012},
  publisher={Optical Society of America}
}

@article{testa2016design,
  title={Design and implementation of an integrated reconfigurable silicon photonics switch matrix in IRIS project},
  author={Testa, Francesco and Oton, Claudio J and Kopp, Christophe and Lee, Jong-Moo and Ortu{\~n}o, Rub{\'e}n and Enne, Reinhard and Tondini, Stefano and Chiaretti, Guido and Bianchi, Alberto and Pintus, Paolo and others},
  journal={IEEE Journal of Selected Topics in Quantum Electronics},
  volume={22},
  number={6},
  pages={155--168},
  year={2016},
  publisher={IEEE}
}

@article{Tait2017,
  title={Neuromorphic photonic networks using silicon photonic weight banks},
  author={Tait, Alexander N and Lima, Thomas Ferreira and Zhou, Ellen and Wu, Allie X and Nahmias, Mitchell A and Shastri, Bhavin J and Prucnal, Paul R},
  journal={Scientific Reports},
  volume={7},
  number={1},
  pages={7430},
  year={2017},
  publisher={Nature Publishing Group}
}

@article{Nawrocki2016a,
  title={A mini review of neuromorphic architectures and implementations},
  author={Nawrocki, Robert A and Voyles, Richard M and Shaheen, Sean E},
  journal={IEEE Transactions on Electron Devices},
  volume={63},
  number={10},
  pages={3819--3829},
  year={2016},
  publisher={IEEE}
}

@article{Godfrey1993,
  title={The computer as von Neumann planned it},
  author={Godfrey, Michael D and Hendry, David F},
  journal={IEEE Annals of the History of Computing},
  volume={15},
  number={1},
  pages={11--21},
  year={1993},
  publisher={IEEE}
}

@article{Rochester1956,
  title={Tests on a cell assembly theory of the action of the brain, using a large digital computer},
  author={Rochester, Nathaniel and Holland, J and Haibt, L and Duda, W},
  journal={IRE Transactions on information Theory},
  volume={2},
  number={3},
  pages={80--93},
  year={1956},
  publisher={IEEE}
}

@article{Farley1954,
  title={Simulation of self-organizing systems by digital computer},
  author={Farley, BWAC and Clark, W},
  journal={Transactions of the IRE Professional Group on Information Theory},
  volume={4},
  number={4},
  pages={76--84},
  year={1954},
  publisher={IEEE}
}

@article{Farley1954,
  title={Simulation of self-organizing systems by digital computer},
  author={Farley, BWAC and Clark, W},
  journal={Transactions of the IRE Professional Group on Information Theory},
  volume={4},
  number={4},
  pages={76--84},
  year={1954},
  publisher={IEEE}
}

@article{Shen2017,
  title={Deep learning with coherent nanophotonic circuits},
  author={Shen, Yichen and Harris, Nicholas C and Skirlo, Scott and Prabhu, Mihika and Baehr-Jones, Tom and Hochberg, Michael and Sun, Xin and Zhao, Shijie and Larochelle, Hugo and Englund, Dirk and others},
  journal={Nature Photonics},
  volume={11},
  number={7},
  pages={441},
  year={2017},
  publisher={Nature Publishing Group}
}

@article{minski1969perceptrons,
  title={Perceptrons: an introduction to computational geometry},
  author={Minski, Marvin L and Papert, Seymour A},
  journal={MA: MIT Press, Cambridge},
  year={1969}
}

@article{McCulloch1943,
  title={A logical calculus of the ideas immanent in nervous activity},
  author={McCulloch, Warren S and Pitts, Walter},
  journal={The bulletin of mathematical biophysics},
  volume={5},
  number={4},
  pages={115--133},
  year={1943},
  publisher={Springer}
}

@article{johnson2006self,
  title={Self-induced optical modulation of the transmission through a high-Q silicon microdisk resonator},
  author={Johnson, Thomas J and Borselli, Matthew and Painter, Oskar},
  journal={Optics express},
  volume={14},
  number={2},
  pages={817--831},
  year={2006},
  publisher={Optical Society of America}
}

@inproceedings{krizhevsky2012imagenet,
  title={Imagenet classification with deep convolutional neural networks},
  author={Krizhevsky, Alex and Sutskever, Ilya and Hinton, Geoffrey E},
  booktitle={Advances in neural information processing systems},
  pages={1097--1105},
  year={2012}
}

@inproceedings{johnson2017generating,
  title={Generating polyphonic music using tied parallel networks},
  author={Johnson, Daniel D},
  booktitle={International Conference on Evolutionary and Biologically Inspired Music and Art},
  pages={128--143},
  year={2017},
  organization={Springer}
}

@article{briot2017deep,
  title={Deep Learning Techniques for Music Generation-A Survey},
  author={Briot, Jean-Pierre and Hadjeres, Ga{\"e}tan and Pachet, Fran{\c{c}}ois},
  journal={arXiv preprint arXiv:1709.01620},
  year={2017}
}

@article{ignatov2017wespe,
  title={WESPE: Weakly supervised photo enhancer for digital cameras},
  author={Ignatov, Andrey and Kobyshev, Nikolay and Timofte, Radu and Vanhoey, Kenneth and Van Gool, Luc},
  journal={arXiv preprint arXiv:1709.01118},
  year={2017}
}

@inproceedings{li2014medical,
  title={Medical image classification with convolutional neural network},
  author={Li, Qing and Cai, Weidong and Wang, Xiaogang and Zhou, Yun and Feng, David Dagan and Chen, Mei},
  booktitle={Control Automation Robotics \& Vision (ICARCV), 2014 13th International Conference on},
  pages={844--848},
  year={2014},
  organization={IEEE}
}


text:
@InProceedings{papailiopoulos13,
  pdf = {http://jmlr.org/proceedings/papers/v28/papailiopoulos13.pdf},
  number = {3},
  section = {cycle-3},
  title = {Sparse PCA through Low-rank Approximations},
  author = {Papailiopoulos, Dimitris and Dimakis, Alexandros and Korokythakis, Stavros},
  pages = {747-755},
  abstract = {We introduce a novel algorithm that computes the $k$-sparse principal component of a positive semidefinite matrix $A$.  Our algorithm is combinatorial and operates by examining a discrete set of special vectors lying in a low-dimensional eigen-subspace of $A$.  We obtain provable approximation guarantees that depend on the spectral profile of the matrix: the faster the eigenvalue decay, the better the quality of our approximation.  For example, if the eigenvalues of $A$ follow a power-law decay, we obtain a polynomial-time approximation   algorithm for any desired accuracy.   We implement our algorithm and test it on multiple artificial and real data sets. Due to   a feature elimination step, it is possible to perform sparse PCA on data sets consisting of millions of entries in a few minutes.   Our experimental evaluation shows that our scheme is nearly optimal   while finding very sparse vectors.  We compare to the prior state of the art and show that our scheme matches or outperforms previous algorithms   in all tested data sets. },
}


text:
require xorg-proto-common.inc
PE = "1"
PR = "${INC_PR}.0"

SRC_URI[archive.md5sum] = "6281344d656d4e0c8e9db4918efe3d1d"
SRC_URI[archive.sha256sum] = "6013d1ca63b2b7540f6f99977090812b899852acfbd9df123b5ebaa911e30003"

CONFLICTS = "compositeext"

repository: trini/openembedded

repo_name: trini/openembedded


text:
# Copyright (c) 2017, Kai Wolf. All rights reserved.
# Use of this source code is governed by a personal license that can be
# found in the LICENSE file in the top directory.

find_program(CPPCHECK_EXE NAMES cppcheck cppcheck.exe
  DOC "Path to cppcheck executable")

if(CPPCHECK_EXE)
  set(CMAKE_C_CPPCHECK "${CPPCHECK_EXE};--std=c++11")
  set(CMAKE_CXX_CPPCHECK "${CPPCHECK_EXE};--std=c++11")
else()
  message(WARNING "No cppcheck executable found. Skipping checks...")
endif()

repository: dreamplayerzhang/Paramount

repo_name: dreamplayerzhang/Paramount