Jonas Kersulis kersulis

## dbode.jl
"""
LTC model used by [Baghsorkhi2015](http://deepblue.lib.umich.edu/handle/2027.42/113584)
(see section 5.3.2).
"""
type DBODE
    "index of bus whose voltage is regulated"
    bus::Int64
    "index of line whose tap is influenced"
    line::Int64
    "voltage setpoint [pu]"

## .block
heigh: 800

## pvec2mat.jl
"""
Given a permutation vector, return the corresponding permutation matrix such that
`A[p,:] = P*A`.
See [Wikipedia](https://en.wikipedia.org/wiki/Permutation_matrix#Definition).
"""
function pvec2mat(p)
    n = length(p)
    P = zeros(n,n)
    for i in 1:n
        P[i,:] = ej(n,p[i])

## naive_lu.jl
"""
Naive LU decomposition (no pivoting) from
[Bindel's CS6210 class notes](http://www.cs.cornell.edu/~bindel/class/cs6210-f12/notes/lec09.pdf).

Beware A[1,1] = 0...
"""
function mylu(A)
    m,n = size(A)
    for j = 1:n-1
        A[j+1:n,j] = A[j+1:n,j]/A[j,j]

## eigenimages.py
import ipywidgets as ipw
from pylab import *

def classify_image(tst,trn,k):
    """  Input:
    tst: a n x T vector corresponding to T images that are to be classified
    trn: n x m x 10  matrix containing m training samples for each digit
    k: integer between 1 and n
    """
    n,T = tst.shape

## createY.jl
"""
    createY(f,t,x [,r,b]) -> Y
Create an admittance matrix for AC power flow.
All inputs are real. The output matrix is real if no line
resistances are provided (DC case), and complex otherwise.

* `f`,`t`: vectors encoding all lines (fi,ti)
* `x`: per-unit reactance xi for all lines
* `r`: per-unit resistance ri for all lines
* `b`: per-unit susceptance bi for all lines

## isf.jl
"""
Calculate injection shift factor matrix.
Each row corresponds to a line in the network.
Each column corresponds to a node.
Credit to Jonathon Martin for derivation.

Inputs:
* `Y`: full admittance matrix
* `lines`: vector of tuples; each tuple encodes a line as (i,j)
* `ref`: index of angle reference bus

## surfer.jl
using Requests, Graphs, ProgressMeter

function surfer(root,n=100)
    # Crawling mechanics: hyperlink regex and
    # filter used for skipping certain links
    rexp = r"https?://[^\"|<|>|;|'|)| |…]+"
    # Focus on links that contribute to the graph by skipping
    # all links that contain the following strings:
    skip = [".gif";".jpg";".jpeg";".pdf";".css";".js";".asp";".mwc";".ram";
        ".cgi";"lmscadsi";"cybernet";"w3.org";"google";"yahoo";

## NotebookNirvana.ipynb

      
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              November 20, 2020 11:37
            
              
                Python 2 and Python 3, Julia 0.3 (release) and 0.4 (dev), plus bash, all in Jupyter notebook on Ubuntu.
              
          
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## MatpowerCases.jl.cov
        - module MatpowerCases
        - using MAT
        -
        - export loadcase,casenames
        -
        - """ Return a Dict containing power system data
        - in MATPOWER's format.
        - Return this list of cases by running casenames().
        - """
        - function loadcase(caseName::ASCIIString; describe=true)
	"""
	LTC model used by [Baghsorkhi2015](http://deepblue.lib.umich.edu/handle/2027.42/113584)
	(see section 5.3.2).
	"""
	type DBODE
	"index of bus whose voltage is regulated"
	bus::Int64
	"index of line whose tap is influenced"
	line::Int64
	"voltage setpoint [pu]"
	"""
	Given a permutation vector, return the corresponding permutation matrix such that
	`A[p,:] = P*A`.
	See [Wikipedia](https://en.wikipedia.org/wiki/Permutation_matrix#Definition).
	"""
	function pvec2mat(p)
	n = length(p)
	P = zeros(n,n)
	for i in 1:n
	P[i,:] = ej(n,p[i])
	"""
	Naive LU decomposition (no pivoting) from
	[Bindel's CS6210 class notes](http://www.cs.cornell.edu/~bindel/class/cs6210-f12/notes/lec09.pdf).

	Beware A[1,1] = 0...
	"""
	function mylu(A)
	m,n = size(A)
	for j = 1:n-1
	A[j+1:n,j] = A[j+1:n,j]/A[j,j]
	import ipywidgets as ipw
	from pylab import *

	def classify_image(tst,trn,k):
	""" Input:
	tst: a n x T vector corresponding to T images that are to be classified
	trn: n x m x 10 matrix containing m training samples for each digit
	k: integer between 1 and n
	"""
	n,T = tst.shape
	"""
	createY(f,t,x [,r,b]) -> Y
	Create an admittance matrix for AC power flow.
	All inputs are real. The output matrix is real if no line
	resistances are provided (DC case), and complex otherwise.

	* `f`,`t`: vectors encoding all lines (fi,ti)
	* `x`: per-unit reactance xi for all lines
	* `r`: per-unit resistance ri for all lines
	* `b`: per-unit susceptance bi for all lines
	"""
	Calculate injection shift factor matrix.
	Each row corresponds to a line in the network.
	Each column corresponds to a node.
	Credit to Jonathon Martin for derivation.

	Inputs:
	* `Y`: full admittance matrix
	* `lines`: vector of tuples; each tuple encodes a line as (i,j)
	* `ref`: index of angle reference bus
	using Requests, Graphs, ProgressMeter

	function surfer(root,n=100)
	# Crawling mechanics: hyperlink regex and
	# filter used for skipping certain links
	rexp = r"https?://[^\"\|<\|>\|;\|'\|)\| \|…]+"
	# Focus on links that contribute to the graph by skipping
	# all links that contain the following strings:
	skip = [".gif";".jpg";".jpeg";".pdf";".css";".js";".asp";".mwc";".ram";
	".cgi";"lmscadsi";"cybernet";"w3.org";"google";"yahoo";
	- module MatpowerCases
	- using MAT
	-
	- export loadcase,casenames
	-
	- """ Return a Dict containing power system data
	- in MATPOWER's format.
	- Return this list of cases by running casenames().
	- """
	- function loadcase(caseName::ASCIIString; describe=true)