opening_hours tag is used in OpenStreetMap project to describe time ranges when a specific facility (for example, a cafe) is open. As it has pretty complex syntax which require special parsing and additional processing to extract some useful information (e.g. whether a facility is open at specific time, next time it's going to open/close, or a readable set of working hours), this library was written.
Examples of some complex real-life opening_hours values:
Mo,Tu,Th,Fr 12:00-18:00;Sa 12:00-17:00; Th[3] off; Th[-1] off
a library which works from 12:00 to 18:00 on workdays except Wednesday, and from 12:00 to 17:00 on Saturday. It also has breaks on third and last Thursday of each month.
00:00-24:00; Tu-Su 8:30-9:00 off; Tu-Su 14:00-14:30 off; Mo 08:00-13:00 off
around-the-clock shop with some breaks.
```javascript var oh = new opening_hours('We 12:00-14:00');
var from = new Date("01 Jan 2012"); var to = new Date("01 Feb 2012");
// high-level API { var intervals = oh.getOpenIntervals(from, to); for (var i in intervals) console.log('We are ' + (intervals[i][2] ? 'maybe ' : '') + 'open from ' + (intervals[i][3] ? '("' + intervals[i][3] + '") ' : '') + intervals[i][0] + ' till ' + intervals[i][1] + '.');
var duration_hours = oh.getOpenDuration(from, to).map(function(x) { return x / 1000 / 60 / 60 });
if (duration_hours[0])
console.log('For a given range, we are open for ' + duration_hours[0] + ' hours');
if (duration_hours[1])
console.log('For a given range, we are maybe open for ' + duration_hours[1] + ' hours');
}
// helper function function logState(startString, endString, oh, past) { if (past === true) past = 'd'; else past = '';
var output = '';
if (oh.getUnknown()) {
output += ' maybe open'
+ (oh.getComment() ? ' but that depends on: "' + oh.getComment() + '"' : '');
} else {
output += ' ' + (oh.getState() ? 'open' : 'close' + past)
+ (oh.getComment() ? ', comment "' + oh.getComment() + '"' : '');
}
console.log(startString + output + endString + '.');
}
// simple API { var state = oh.getState(); // we use current date var unknown = oh.getUnknown(); var comment = oh.getComment(); var nextchange = oh.getNextChange();
logState('We\'re', '', oh, true);
if (typeof nextchange === 'undefined')
console.log('And we will never ' + (state ? 'close' : 'open'));
else
console.log('And we will '
+ (oh.getUnknown(nextchange) ? 'maybe ' : '')
+ (state ? 'close' : 'open') + ' on ' + nextchange);
}
// iterator API { var iterator = oh.getIterator(from);
logState('Initially, we\'re', '', iterator, true);
while (iterator.advance(to))
logState('Then we', ' at ' + iterator.getDate(), iterator);
logState('And till the end we\'re', '', iterator, true);
} ```
javascript
var oh = new opening_hours('We 12:00-14:00');
Constructs openinghours object, given the openinghours tag value.
Throws an error string if the expression is malformed or unsupported.
javascript
var every_week_is_same = oh.isWeekSame();
Checks whether open intervals are same for every week. Useful for giving a user hint whether time table may change for another week.
Here and below, unless noted otherwise, all arguments are expected to be and all output will be in the form of Date objects.
javascript
var intervals = oh.getOpenIntervals(from, to);
Returns array of open intervals in a given range, in a form of [ [ from1, to1, unknown1, comment1 ], [ from2, to2, unknown2, comment2 ] ]
Intervals are cropped with the input range.
javascript
var duration = oh.getOpenDuration(from, to);
Returns an array with two durations for a given date range, in milliseconds. The first element is the duration for which the facility is open and the second is the duration for which the facility is maybe open (unknown is used).
This API is useful for one-shot checks, but for iteration over intervals you should use the more efficient Iterator API.
javascript
var is_open = oh.getState(date);
Checks whether the facility is open at the given date. You may omit date to use current date.
javascript
var unknown = oh.getUnknown();
Checks whether the opening state is conditional or unknown at the given date. You may omit date to use current date. Conditions can be expressed in comments. If unknown is true then is_open will be false since it is not sure if it is open.
javascript
var comment = oh.getComment();
Returns the comment (if one is specified) for the facility at the given date. You may omit date to use current date. Comments can be specified for any state.
If no comment is specified this function will return undefined.
javascript
var next_change = oh.getNextChange(date, limit);
Returns date of next state change. You may omit date to use current date.
Returns undefined if the next change cannot be found. This may happen if the state won't ever change (e.g. 24/7
) or if search goes beyond limit (which is date + ~5 years if omitted).
javascript
var iterator = oh.getIterator(date);
Constructs an iterator which can go through open/close points, starting at date. You may omit date to use current date.
javascript
var current_date = iterator.getDate();
Returns current iterator position.
javascript
var is_open = iterator.getState();
Returns whether the facility is open at the current iterator position in time.
javascript
var unknown = iterator.getUnknown();
Checks whether the opening state is conditional or unknown at the current iterator position in time.
javascript
var comment = iterator.getComment();
Returns the comment (if one is specified) for the facility at the current iterator position in time.
If no comment is specified this function will return undefined.
javascript
var had_advanced = iterator.advance(limit);
Advances an iterator to the next position, but not further that a limit (which is current position + ~5 years if omitted and is used to prevent infinite loop on non-periodic opening_hours, e.g. 24/7
), returns whether the iterator was moved.
For instance, returns false if the iterator would go beyond limit or if there's no next position (24/7
case).
Almost everything from openinghours definition is supported, as well as some extensions (indicated as EXT: below). For instance, the library is able to process 99.4% of all openinghours tags from Russia OSM data.
Mo 10:00-20:00; Tu 12:00-18:00
)off
keyword to indicate that the facility is closed at that time (Mo-Fr 10:00-20:00; 12:00-14:00 off
)Mo-Fr
, Jan-Feb
, week 2-10
, Jan 10-Feb 10
) and time (12:00-16:00
, 12:00-14:00,16:00-18:00
) conditionsMo-Fr 10:00-16:00; We 12:00-18:00
means that on Wednesday the facility is open from 12:00 till 18:00, not from 10:00 to 18:00.Jan 10-Feb 10: 07:30-12:00
) but this is not required. This was implemented to also parse the syntax proposed by Netzwolf10:00-12:00,14:00-16:00
)
10:00-26:00
, 10:00-02:00
)00:00-24:00
, so Mo-Fr 24/7
(though not really correct) is valid and will be handled correctlyMo-Fr; Tu off
)12.00-16.00
is valid (this is used quite widely)Mo 12:00-14:00,16:00-20:00
and Mo 12:00-14:00 16:00-20:00
are the same thing10:00-sunset
) (sunrise: '06:00', sunset: '18:00')10:00+
)Mo-We,Fr
)Fr-Mo
)Th[1,2-3]
, Fr[-1]
)Jan,Mar-Apr
)Dec-Jan
)Jan 01-Feb 03 10:00-20:00
)Jan 01-26 10:00-20:00
), with periods as well Jan 01-29/7 10:00-20:00
)Jan 23-31/3,Feb 1-12,Mar 1
)week 04-07 10:00-20:00
)week 2-53/2 10:00-20:00
)week 1,3-5,7-30/2 10:00-20:00
)Mo unknown; Th-Fr 09:00-18:00 open
)
Mo unknown "on appointment"; Th-Fr 09:00-18:00 open "female only"; Su closed "really"
)
"on appointment"
) which will result in unknown.Simple node.js based test framework is bundled. You can run it with node test.js
or with make test
.
Simple node.js based benchmark is bundled. You can run it with node benchmark.js
or with make benchmark
.
On author's Intel Core i5-2400 library allows ~20k/sec constructor calls and ~10k/sec openIntervals() calls with one week period. This may further improve in future.


{% extends '../tutorials/tutbaselayout.html' %} {% load static %} {% block content %}
A variable is nothing but a name given to a storage area that our programs can manipulate. Each variable in C has a specific type, which determines the size and layout of the variable's memory; the range of values that can be stored within that memory; and the set of operations that can be applied to the variable.
The name of a variable can be composed of letters, digits, and the underscore character. It must begin with either a letter or an underscore. Upper and lowercase letters are distinct because C is case-sensitive. Based on the basic types explained in the previous chapter, there will be the following basic variable types −
| Sr. No. | Types & Description |
|---|---|
| 1 | char Typically a single octet(one byte). This is an integer type. |
| 2 | int The most natural size of integer for the machine. |
| 3 | float A single-precision floating point value. |
| 4 | double A double-precision floating point value. |
| 5 | void Represents the absence of type. |
C programming language also allows to define various other types of variables, which we will cover in subsequent chapters like Enumeration, Pointer, Array, Structure, Union, etc. For this chapter, let us study only basic variable types.
variable definition tells the compiler where and how much storage to create for the variable. A variable definition specifies a data type and contains a list of one or more variables of that type as follows −
type variable_list;
Here, type must be a valid C data type including char, w_char, int, float, double, bool, or any user-defined object; and variable_list may consist of one or more identifier names separated by commas. Some valid declarations are shown here −
int i, j, k; char c, ch; float f, salary; double d;
The line int i, j, k; declares and defines the variables i, j, and k; which instruct the compiler to create variables named i, j and k of type int.
Variables can be initialized (assigned an initial value) in their declaration. The initializer consists of an equal sign followed by a constant expression as follows −
type variable_name = value;
Some examples are −
extern int d = 3, f = 5; // declaration of d and f. int d = 3, f = 5; // definition and initializing d and f. byte z = 22; // definition and initializes z. char x = 'x'; // the variable x has the value 'x'.
For definition without an initializer: variables with static storage duration are implicitly initialized with NULL (all bytes have the value 0); the initial value of all other variables are undefined.
A variable declaration provides assurance to the compiler that there exists a variable with the given type and name so that the compiler can proceed for further compilation without requiring the complete detail about the variable. A variable definition has its meaning at the time of compilation only, the compiler needs actual variable definition at the time of linking the program.
A variable declaration is useful when you are using multiple files and you define your variable in one of the files which will be available at the time of linking of the program. You will use the keyword extern to declare a variable at any place. Though you can declare a variable multiple times in your C program, it can be defined only once in a file, a function, or a block of code.
Try the following example, where variables have been declared at the top, but they have been defined and initialized inside the main function −
#include <stdio.h>
// Variable declaration:
extern int a, b;
extern int c;
extern float f;
int main () {
/* variable definition: */
int a, b;
int c;
float f;
/* actual initialization */
a = 10;
b = 20;
c = a + b;
printf("value of c : %d \n", c);
f = 70.0/3.0;
printf("value of f : %f \n" , f);
return 0;
}
When the above code is compiled and executed, it produces the following result −
value of c : 30 value of f : 23.333334
The same concept applies on function declaration where you provide a function name at the time of its declaration and its actual definition can be given anywhere else. For example −
// function declaration
int func();
int main() {
// function call
int i = func();
}
// function definition
int func() {
return 0;
}
There are two kinds of expressions in C −
lvalue − Expressions that refer to a memory location are called "lvalue" expressions. An lvalue may appear as either the left-hand or right-hand side of an assignment.
*rvalue − The term rvalue refers to a data value that is stored at some address in memory. An rvalue is an expression that cannot have a value assigned to it which means an rvalue may appear on the right-hand side but not on the left-hand side of an assignment.
Variables are lvalues and so they may appear on the left-hand side of an assignment. Numeric literals are rvalues and so they may not be assigned and cannot appear on the left-hand side. Take a look at the following valid and invalid statements −
int g = 20; // valid statement 10 = 20; // invalid statement; would generate compile-time error


{% extends "base.html" %} {% block basecontent %} Join Progrwiki. Create an Account Username person {{error_username}} Email (optional) email {{error_email}} Password lock_outline {{error_password}} Verify lock_outline {{error_verify}} {{error}} Remember Me Sign up Already have an account? Sign in. {% endblock %}
{{error_username}}
{{error_email}}
{{error_password}}
{{error_verify}}
{{error}}
Already have an account? Sign in.


public interface OnReadInlineContent
Callback interface for the deep insert read calls (read of
content).
Typically the receiveReadProperties(EntityProviderReadProperties, EdmNavigationProperty)
method is called
when an inline navigation property is found and will be read.
The handleReadEntry(ReadEntryResult)
and handleReadFeed(ReadFeedResult)
methods are called
after the inline navigation property was read and deliver the read (de-serialized) entity or list of entities.
If inlined navigation property is nullable
and not set a ReadEntryResult
is given with the
navigationPropertyName
and a NULL
entry set.
| Modifier and Type | Method and Description |
|---|---|
void |
handleReadEntry(ReadEntryResult readEntryResult)
Handles reading (de-serialization) entry result.
|
void |
handleReadFeed(ReadFeedResult readFeedResult)
Handles reading (de-serialization) entry result.
|
EntityProviderReadProperties |
receiveReadProperties(EntityProviderReadProperties readProperties,
EdmNavigationProperty navigationProperty)
Receive (request) to be used
EntityProviderReadProperties to read the found inline navigation property
(> ). |
EntityProviderReadProperties receiveReadProperties(EntityProviderReadProperties readProperties, EdmNavigationProperty navigationProperty) throws ODataApplicationException
EntityProviderReadProperties
to read the found inline navigation property
(>...
).readProperties
- read properties which are used to read enclosing parent entitynavigationProperty
- emd navigation property information of found inline navigation propertyODataApplicationException
void handleReadEntry(ReadEntryResult readEntryResult) throws ODataApplicationException
ReadEntryResult
object contains all contextual information
about the de-serialized inline navigation property and the entry as
ODataEntry
.readEntryResult
- with contextual information about and de-serialized
inlined navigation property as ODataEntry
ODataApplicationException
void handleReadFeed(ReadFeedResult readFeedResult) throws ODataApplicationException
ReadFeedResult
object contains all contextual information
about the de-serialized inline navigation property and the entry as
a list of ODataEntry
.readFeedResult
- with contextual information about and de-serialized
inlined navigation property as a list of ODataEntry
ODataApplicationException
Copyright © 2013-2017 The Apache Software Foundation. All Rights Reserved.


{% extends "layout.html" %} {% block body %}
Add a new user to the system. A password will be automatically generated.
Assign unassigned articles to coders. You can choose to assign the same n articles to all coders, n distinct articles to each coder, or assigns n articles to each coder, such that k users code each article.
Transfers articles which are in the queue of one or more coders into the queue of one or more other coders.
Assigns articles which have been coded by one or more coders to be coded by one or more other coders.
List each ID on a separate line.
| Remaining | Completed | |
|---|---|---|
| {{ ura[u]|capitalize }} | {{ coded[u]['remaining'] }} | {{ coded[u]['completed'] }} |


public abstract class RrdDbPool
extends java.lang.Object
The abstract wrapper for different implementations of the pools.
| Modifier and Type | Field and Description |
|---|---|
static int |
INITIAL_CAPACITY
Initial capacity of the pool i.e. maximum number of simultaneously open RRD files.
|
| Constructor and Description |
|---|
RrdDbPool() |
| Modifier and Type | Method and Description |
|---|---|
abstract int |
getCapacity()
Returns the maximum number of simultaneously open RRD files.
|
static RrdDbPool |
getInstance()
Creates a single instance of the class on the first call,
or returns already existing one.
|
abstract int |
getOpenCount(RrdDb rrdDb)
Returns the number of usage for a RRD.
|
abstract int |
getOpenCount(java.lang.String path)
Returns the number of usage for a RRD.
|
abstract int |
getOpenFileCount()
Returns the number of open RRD files.
|
abstract java.lang.String[] |
getOpenFiles()
Returns an array of open file names.
|
abstract void |
release(RrdDb rrdDb)
Releases RrdDb reference previously obtained from the pool.
|
abstract RrdDb |
requestRrdDb(RrdDef rrdDef)
Requests a RrdDb reference for the given RRD file definition object.
|
abstract RrdDb |
requestRrdDb(java.lang.String path)
Requests a RrdDb reference for the given RRD file path.
|
abstract RrdDb |
requestRrdDb(java.lang.String path,
java.lang.String sourcePath)
Requests a RrdDb reference for the given path.
|
abstract void |
setCapacity(int capacity)
Sets the maximum number of simultaneously open RRD files.
|
public static final int INITIAL_CAPACITY
public static RrdDbPool getInstance()
java.lang.RuntimeException
- Thrown if the default RRD backend is not derived from the RrdFileBackendFactory
public abstract RrdDb requestRrdDb(java.lang.String path) throws java.io.IOException
INITIAL_CAPACITY
, the file will be open and a new RrdDb reference will be returned.
If the file is not already open and the number of already open RRD files is equal to
INITIAL_CAPACITY
, the method blocks until some RRD file is closed.
path
- Path to existing RRD filejava.io.IOException
- Thrown in case of I/O errorpublic abstract RrdDb requestRrdDb(RrdDef rrdDef) throws java.io.IOException
INITIAL_CAPACITY
, a new RRD file will be created and a its RrdDb reference will be returned.
If the file is not already open and the number of already open RRD files is equal to
INITIAL_CAPACITY
, the method blocks until some RRD file is closed.
rrdDef
- Definition of the RRD file to be createdjava.io.IOException
- Thrown in case of I/O errorpublic abstract RrdDb requestRrdDb(java.lang.String path, java.lang.String sourcePath) throws java.io.IOException
INITIAL_CAPACITY
, a new RRD file will be created and a its RrdDb reference will be returned.
If the file is not already open and the number of already open RRD files is equal to
INITIAL_CAPACITY
, the method blocks until some RRD file is closed.
path
- Path to RRD file which should be createdsourcePath
- Path to external data which is to be converted to Rrd4j's native RRD file formatjava.io.IOException
- Thrown in case of I/O errorpublic abstract void release(RrdDb rrdDb) throws java.io.IOException
rrdDb
- RrdDb reference to be returned to the pooljava.io.IOException
- Thrown in case of I/O errorpublic abstract int getCapacity()
public abstract void setCapacity(int capacity)
capacity
- Maximum number of simultaneously open RRD files.public abstract java.lang.String[] getOpenFiles()
public abstract int getOpenFileCount()
public abstract int getOpenCount(RrdDb rrdDb) throws java.io.IOException
rrdDb
- RrdDb reference for which informations is needed.java.io.IOException
public abstract int getOpenCount(java.lang.String path) throws java.io.IOException
path
- RRD file for which informations is needed.java.io.IOException


anki_vector.exceptions¶
SDK-specific exception classes for Vector.
Functions
connection_error (rpc_error) |
Translates grpc-specific errors to user-friendly VectorConnectionException . |
Exceptions
VectorCameraFeedDisabledException |
Failed to render video because camera feed was disabled. |
VectorConnectionException (cause) |
|
VectorControlException (function) |
Unable to run a function which requires behavior control. |
VectorControlTimeoutException ([cause]) |
Failed to get control of Vector. |
VectorException |
Base class of all Vector SDK exceptions. |
VectorInvalidVersionException (…) |
Your SDK version is not compatible with Vector’s version. |
VectorNotFoundException ([cause]) |
Unable to establish a connection to Vector. |
VectorNotReadyException ([cause]) |
Vector tried to do something before it was ready. |
VectorTimeoutException (cause) |
Message took too long to complete. |
VectorUnauthenticatedException (cause) |
Failed to authenticate request. |
VectorUnavailableException (cause) |
Unable to reach Vector. |
VectorUnimplementedException (cause) |
Vector does not handle this message. |
-
exception
anki_vector.exceptions.
VectorCameraFeedDisabledException
¶ Failed to render video because camera feed was disabled.
-
exception
anki_vector.exceptions.
VectorConnectionException
(cause)¶
-
exception
anki_vector.exceptions.
VectorControlException
(function)¶ Unable to run a function which requires behavior control.
-
exception
anki_vector.exceptions.
VectorControlTimeoutException
(cause=None)¶ Failed to get control of Vector.
Please verify that Vector is connected to the internet, and consider trying to request a higher control level.
-
exception
anki_vector.exceptions.
VectorException
¶ Base class of all Vector SDK exceptions.
-
exception
anki_vector.exceptions.
VectorInvalidVersionException
(version_request, version_response)¶ Your SDK version is not compatible with Vector’s version.
-
exception
anki_vector.exceptions.
VectorNotFoundException
(cause=None)¶ Unable to establish a connection to Vector.
Make sure you’re on the same network, and Vector is connected to the internet.
-
exception
anki_vector.exceptions.
VectorNotReadyException
(cause=None)¶ Vector tried to do something before it was ready.
-
exception
anki_vector.exceptions.
VectorTimeoutException
(cause)¶ Message took too long to complete.
-
exception
anki_vector.exceptions.
VectorUnauthenticatedException
(cause)¶ Failed to authenticate request.
Unable to reach Vector.
-
exception
anki_vector.exceptions.
VectorUnimplementedException
(cause)¶ Vector does not handle this message.
-
anki_vector.exceptions.
connection_error
(rpc_error)¶ Translates grpc-specific errors to user-friendly
VectorConnectionException
.Return type: VectorConnectionException


---
layout: post
title: ATECC508A Embedded Crypto - Next Impressions setting up AWS
date: '2017-10-14T17:27:00.000-07:00'
author: gojimmypi
tags:
modified_time: '2017-10-24T12:28:51.219-07:00'
thumbnail: https://2.bp.blogspot.com/-5H7SafTQaCA/WeJU1oJ1woI/AAAAAAAAApY/Doh8cp8lytoVNIomUISsYsZ9WPm4D7JTQCLcBGAs/s72-c/provision-1.png
blogger_id: tag:blogger.com,1999:blog-4109066286647243251.post-3629881482231084760
blogger_orig_url: https://gojimmypi.blogspot.com/2017/10/atecc508a-embedded-crypto-next.html
---
The state of Internet of Things (IoT) Security is a disaster. Hardly a day goes by without news that some new product is discovered to also have some ridiculously glaring security problem. There's a potential solution: a "security in a chip" device for less that a buck, that could seriously change the landscape of IoT security.
In my
previous post, I took the MicroChip AT88CK590
for a brief initial test drive. Although cool in concept, I was initially frustrated and underwhelmed. I didn't even get around to posting my experience for a couple of months. (in part, as I never actually got it doing what I wanted) Note that was with completely different eval hardware.
This time around I am looking at the much more elaborate
Zero Touch Secure Provisioning Kit for AWS IoT. Be sure to pay attention to the "-B" suffix. A similar part number at mouser is marked as "End of Life: Scheduled for obsolescence and will be discontinued by the manufacturer." You can try this link
to see if they eventually carry the update.
However, when I did finally post that blog page and
tweeted it - I got the attention of the folks at MicroChip. In particular their response regarding the a new and interesting crypto chip AWS walk-through
that I had not seen:
http://microchipdeveloper.com/iot:ztpk
I starts out really quite interesting! The steps are very clearly documented regarding all the (less-than-intuitive) AWS setup details. At the end of the story though, right before the culmination of anticipated technical details, it abruptly ends. I was really hoping for a code walk-through as well. Alas there was just a single "Explore" bullet item:
- "Firmware that comes in the ZIP to see how the ARM SAM G55 communicates with the secure element (ATECC508A) and the Wi-Fi module WINC1500"
So, ok. I'm good with doing my own code analysis. Sometimes the comments are better than an external document walk-through anyhow.
There are a ton of links throughout the rather long instruction set. By the time you get to the end when reading, perhaps the
Zero Touch Secure Provisioning Kit Software Files was missed way up at step 2. I had see that, even clicked on it. But it initially looks like an ad, complete with the "Buy It Now" button in the upper right corner. But the software is there! Scroll to the bottom and click the "Getting Started
" tab:
Then click on the "Get the necessary code HERE" link:
I would have included the link, but it goes to a wonky "Software Copyright" page where you need to provide a name, email, company info. You can however, then immediately download the software. (unlike some sites where you need to wait for confirmation email, bla, bla).
I had a very difficult time with this: several times when I downloaded the file, it was less than 50KB and windows reported that it was correupt when trying to open it. Fortunately my twitter thread ended up with an
offer to talk with someone at MicroChip
! Later that day I had a great phone conversation with a rep from MicroChip that completely re-invigorated my interest in their crypto chip! He also helped with the download. What worked for me is copying the (apparently time-sensitive) link to clipboard... closing google chrome... and then pasting into a new chrome instance. I think there may have simply been a problem with the timing/loading of the javascript for the page. In any case the file starts downloading immediately. It is about 13MB in size.
The two main components of the zip are the (1) python scripts for setting up AWS and (2) a SAMG55 Atmel Studio Project called AWS_IoT_Zero_Touch_SAMG55.atsln
It is unfortunate that the code is "protected" behind a copyright notice. It really belongs as open source on github. Hopefully MicroChip will change that soon.
I suspect the folks at AWS are really quite happy to see they are the only IoT service listed! lol
The
microchipdeveloper site is of course still a work in progress. I hope to see a lot more providers in the future. I've always been wanting to use AWS for my MQTT data anyhow: In part, well, it is MY data. I had tried the very easy to use Adafruit.io - but some time back it was offline for a long stretch. (granted it was still beta) But also - it has limitations on number of devices (5) or pay $120/year for up to 60 devices (not yet available), and show stopper: the data was out of my control. The cool thing about adafruit.io was that I could use insecure
MQTT of plain HTTP with my ESP8266 (well, duh, back to the proliferation of insecure IoT, eh?) AWS is definitely more challenging in not even allowing anything but a secure connection.
One thing to point out about installing
AWS CLI
for Windows is that at the end of install, nothing happens. No new icons, no message of completion. Nothing. For me, the "AWS Tools for Windows" listed under Amazon Web Services in Windows 10 start menu - was something I installed last year.
To confirm AWS CLI installed correctly, simply pop into a DOS window and type "AWS":
{% include code_header.html %}
Microsoft Windows [Version 10.0.15063]
(c) 2017 Microsoft Corporation. All rights reserved.
C:\Users\gojimmypi>aws
usage: aws [options] <command> <subcommand> [<subcommand> ...] [parameters]
To see help text, you can run:
aws help
aws <command></command> help
aws <command></command> <subcommand> help
aws: error: too few arguments
C:\Users\gojimmypi>
The Python install is a little tricky for me. I already had V2.7 installed (for something that explicitly wanted that version)... and to add V3.6.3 to my path... well, I'm sure I'll bump into that at some unexpected point in the future. This is a good reason to perhaps have a VM for each development environment.
The comment "
May take a while to install." should not be underestimated for the pip install step! They should change the text to: "Takes a ridiculously long time, and may seem to stop at times!
" lol!
Another place to note a possible problem is on creating roles in Section III. I think the AWS console changed a little since the MicroChip instructions were created. Here's my AWS Console:
Note the "AWS Service" is selected (no radio button) and the service is called simply "Lambda" (not AWS Lambda). Next Step is actually labeled "Next: Permissions"
The final resultant JITR policy also looks a bit different from the walk-through.
My function "Author from Scratch" was also a bit different than instructions:
Instructions:
What I saw:
And here's what my actual code looks like in the function:
The instructions refer to "Rules"... it is now called "Act". Note there's an identical icon, just a different name (instructions on left; my AWS console on right):
The instructions also show running a python script as easily as if it were a batch file.  Argh! So a click of an option setting and VOILA! Success.
<happy dance>!!</happy dance>
Next, I will finally take a look at the code!
Check out my next post on
my first bizarre AWS costs
.
Copyright (c) gojimmypi all rights reserved. Blogger Image Move Cleaned: 5/3/2021 1:35:53 PM


bcrypt hashing for PicoLisp
17 Mar 2015You can get it on GitHub.
This library can be used to hash strings (ex: passwords) using bcrypt in PicoLisp.
bcrypt hashing for PicoLisp
Only the following functions are exported publicly, and namespaced with (symbols 'bcrypt)
(or the prefix: bcrypt~
):
- (gensalt Factor) generates a salt to be used for hashing a string
Factor
Number: a Number between 4 and 31, defaults to12
otherwise
- (hashpw Passwd Salt) hashes a string with the salt provided
Passwd
String: the String to be hashedSalt
String or Number (optional): a hash String or Number used as a cost Factor (will generate a salt automatically if a Number is provided)
- (compare Passwd Hash) a predicate which compares the password and hash. Returns
NIL
orT
.Passwd
String: the password StringHash
String: the hashed String of the password
- (timing Factor) calculates the timing of a password hashing, in seconds. Returns the factor in
car
and seconds incdr
Note: These functions are not namespace local symbols, which means they would redefine symbols with the same name in the
'pico
namespace.
Notes
- The default cost Factor is
12
. - As rule of thumb, when using bcrypt to hash passwords, it should take at least 1 second per hash. Adjust the cost Factor based on the result of a few (timing) runs.
- The
'InternalError
message will be thrown if there’s an error.
Examples
(gensalt Factor)
pil +
(load "bcrypt.l")
(symbols 'bcrypt)
(gensalt)
-> "$2a$12$mQn1fUDeEZFW74KD5kU6g."
(gensalt 14)
-> "$2a$14$kjOSmjZeLsBdru7NRPEmQu"
(hashpw Passwd Salt)
pil +
(load "bcrypt.l")
(symbols 'bcrypt)
(hashpw "changeme")
-> "$2a$12$mmxN/qk8yvfjCx./KXtgfuqnUFsXjYv1ZTZmkMtdQ94rTDngiXpsq"
(hashpw "changeme" 14)
-> "$2a$14$gZLc8eII8kCbXgFp2rUcv.PPr/oPioojVy0yP0HMU6z2La.v4pEnG"
(hashpw "changeme" "$2a$14$kjOSmjZeLsBdru7NRPEmQu")
-> "$2a$14$kjOSmjZeLsBdru7NRPEmQuL5eU5YN4Yb48bD1A0Pxzwu/3G/7kwBy"
(compare Passwd Hash)
pil +
(load "bcrypt.l")
(symbols 'bcrypt)
(compare "changeme" "$2a$14$kjOSmjZeLsBdru7NRPEmQuL5eU5YN4Yb48bD1A0Pxzwu/3G/7kwBy")
-> T
(compare "changeme" "$2a$12$2Lgk0P5s5VsxDUM2aa/HFu/6DwHce1lbUwJ1kTm092DwEeDRHHYBy")
-> NIL
(catch 'InternalError (compare "changeme" "I have no idea what i'm doing"))
-> (BcryptError . "Unable to hash password")
(timing Factor)
pil +
(load "bcrypt.l")
(symbols 'bcrypt)
(timing)
-> (12 . 0)
(timing 15)
-> (15 . 4)


# File test/view_operations_test.rb, line 4 def test_create_view Person.create(:first_name => 'John', :last_name => 'Doe', :ssn => '123456789') assert_nothing_raised do ActiveRecord::Base.connection.create_view(:v_people, 'select first_name, last_name, ssn from people', :force => true) do |v| v.column :f_name v.column :l_name v.column :social_security end end p = Person.find(:first) vp = VPerson.find(:first) assert_equal p.first_name, vp.f_name end
# File test/view_operations_test.rb, line 18 def test_drop_view assert_nothing_raised do ActiveRecord::Base.connection.create_view(:v_place, 'select address, city, cstate, country from places', :force => true) do |v| v.column :v_address v.column :v_city v.column :v_state v.column :v_country end ActiveRecord::Base.connection.drop_view(:v_place) end assert_raises(ActiveRecord::StatementInvalid) do ActiveRecord::Base.connection.execute "SELECT * FROM v_place" end end
# File test/view_operations_test.rb, line 33 def test_no_view_raises_error assert_raises(RuntimeError) { ActiveRecord::Base.connection.view_select_statement('foo') } end


Melville Theatre
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Applied data science tools and tactics to help Global quality department gain useful insight from data. Worked on various project of core machine learning, image analytics, quality control and causal inference
Leveraged data science tactics on blockchain while doing a Co-op with Amazing startup and helped in formulating deep learning architecture for great vision
Developed automation scripts and supported Web Domain of BNY mellons applications to help in reducing fintech web application projects turnaround and production performance
Learned various data science tools and tactics which can be leveraged to solve the real world data science challenge. Also co-founded IU Data Science Consulting club to help people with their data science challenges
Leared the foundation and fundamentals of advance computer world which laid a strong stepping stone to learn more advance concepts of data science
Grabbed the first position in project presentation at univeristy level. Presented the project of open sourcing of Amazon Elastic Map Reduce webservices
“Ankit is..”
Lalit Bhattacharya, Senior Lead“Ankit is..”
Ramesh Dwarkanath, Solution Architecture“Ankit...”
Daron Huffaker, Global Quality Data Science Manager


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Basis exchange matroids#
BasisExchangeMatroid
is an abstract class implementing default matroid functionality in terms of
basis exchange. Several concrete matroid classes are subclasses of this. They
have the following methods in addition to the ones provided by the parent
class Matroid
.
AUTHORS:
Rudi Pendavingh, Stefan van Zwam (2013-04-01): initial version
Methods#
- class sage.matroids.basis_exchange_matroid.BasisExchangeMatroid#
Bases:
Matroid
Class BasisExchangeMatroid is a virtual class that derives from Matroid. It implements each of the elementary matroid methods (
rank()
,max_independent()
,circuit()
,closure()
etc.), essentially by crawling the base exchange graph of the matroid. This is the graph whose vertices are the bases of the matroid, two bases being adjacent in the graph if their symmetric difference has 2 members.This base exchange graph is not stored as such, but should be provided implicitly by the child class in the form of two methods
__is_exchange_pair(x, y)
and__exchange(x, y)
, as well as an initial basis. At any moment, BasisExchangeMatroid keeps a current basis \(B\). The method__is_exchange_pair(x, y)
should return a boolean indicating whether \(B - x + y\) is a basis. The method__exchange(x, y)
is called when the current basis \(B\) is replaced by said \(B-x + y\). It is up to the child class to update its internal data structure to make information relative to the new basis more accessible. For instance, a linear matroid would perform a row reduction to make the column labeled by \(y\) a standard basis vector (and therefore the columns indexed by \(B-x+y\) would form an identity matrix).Each of the elementary matroid methods has a straightforward greedy-type implementation in terms of these two methods. For example, given a subset \(F\) of the groundset, one can step to a basis \(B\) over the edges of the base exchange graph which has maximal intersection with \(F\), in each step increasing the intersection of the current \(B\) with \(F\). Then one computes the rank of \(F\) as the cardinality of the intersection of \(F\) and \(B\).
The following matroid classes can/will implement their oracle efficiently by deriving from
BasisExchangeMatroid
:BasisMatroid
: keeps a list of all bases.__is_exchange_pair(x, y)
reduces to a query whether \(B - x + y\) is a basis.__exchange(x, y)
has no work to do.
LinearMatroid
: keeps a matrix representation \(A\) of the matroid so that \(A[B] = I\).__is_exchange_pair(x, y)
reduces to testing whether \(A[r, y]\) is nonzero, where \(A[r, x]=1\).__exchange(x, y)
should modify the matrix so that \(A[B - x + y]\) becomes \(I\), which means pivoting on \(A[r, y]\).
TransversalMatroid
(not yet implemented): If \(A\) is a set of subsets of \(E\), then \(I\) is independent if it is a system of distinct representatives of \(A\), i.e. if \(I\) is covered by a matching of an appropriate bipartite graph \(G\), with color classes \(A\) and \(E\) and an edge \((A_i,e)\) if \(e\) is in the subset \(A_i\). At any time you keep a maximum matching \(M\) of \(G\) covering the current basis \(B\).__is_exchange_pair(x, y)
checks for the existence of an \(M\)-alternating path \(P\) from \(y\) to \(x\).__exchange(x, y)
replaces \(M\) by the symmetric difference of \(M\) and \(E(P)\).
AlgebraicMatroid
(not yet implemented): keeps a list of polynomials in variables \(E - B + e\) for each variable \(e\) in \(B\).__is_exchange_pair(x, y)
checks whether the polynomial that relates \(y\) to \(E-B\) uses \(x\).__exchange(x, y)
make new list of polynomials by computing resultants.
All but the first of the above matroids are algebraic, and all implementations specializations of the algebraic one.
BasisExchangeMatroid internally renders subsets of the ground set as bitsets. It provides optimized methods for enumerating bases, nonbases, flats, circuits, etc.
- bases()#
Return the list of bases of the matroid.
A basis is a maximal independent set.
OUTPUT:
An iterable containing all bases of the matroid.
EXAMPLES:
sage: M = matroids.named_matroids.N1() sage: M.bases_count() 184 sage: len([B for B in M.bases()]) 184
- bases_count()#
Return the number of bases of the matroid.
A basis is an inclusionwise maximal independent set.
See also
OUTPUT:
Integer.
EXAMPLES:
sage: M = matroids.named_matroids.N1() sage: M.bases_count() 184
- basis()#
Return an arbitrary basis of the matroid.
A basis is an inclusionwise maximal independent set.
Note
The output of this method can change in between calls. It reflects the internal state of the matroid. This state is updated by lots of methods, including the method
M._move_current_basis()
.OUTPUT:
Set of elements.
EXAMPLES:
sage: M = matroids.named_matroids.Fano() sage: sorted(M.basis()) ['a', 'b', 'c'] sage: M.rank('cd') 2 sage: sorted(M.basis()) ['a', 'c', 'd']
- circuits()#
Return the list of circuits of the matroid.
OUTPUT:
An iterable containing all circuits.
See also
EXAMPLES:
sage: M = Matroid(matroids.named_matroids.NonFano().bases()) sage: sorted([sorted(C) for C in M.circuits()]) [['a', 'b', 'c', 'g'], ['a', 'b', 'd', 'e'], ['a', 'b', 'f'], ['a', 'c', 'd', 'f'], ['a', 'c', 'e'], ['a', 'd', 'e', 'f'], ['a', 'd', 'g'], ['a', 'e', 'f', 'g'], ['b', 'c', 'd'], ['b', 'c', 'e', 'f'], ['b', 'd', 'e', 'f'], ['b', 'd', 'f', 'g'], ['b', 'e', 'g'], ['c', 'd', 'e', 'f'], ['c', 'd', 'e', 'g'], ['c', 'f', 'g'], ['d', 'e', 'f', 'g']]
- cocircuits()#
Return the list of cocircuits of the matroid.
OUTPUT:
An iterable containing all cocircuits.
See also
EXAMPLES:
sage: M = Matroid(bases=matroids.named_matroids.NonFano().bases()) sage: sorted([sorted(C) for C in M.cocircuits()]) [['a', 'b', 'c', 'd', 'g'], ['a', 'b', 'c', 'e', 'g'], ['a', 'b', 'c', 'f', 'g'], ['a', 'b', 'd', 'e'], ['a', 'c', 'd', 'f'], ['a', 'e', 'f', 'g'], ['b', 'c', 'e', 'f'], ['b', 'd', 'f', 'g'], ['c', 'd', 'e', 'g']]
- coflats(r)#
Return the collection of coflats of the matroid of specified corank.
A coflat is a coclosed set.
INPUT:
r
– A natural number.
OUTPUT:
An iterable containing all coflats of corank
r
.See also
EXAMPLES:
sage: M = matroids.named_matroids.S8().dual() sage: M.f_vector() [1, 8, 22, 14, 1] sage: len(M.coflats(2)) 22 sage: len(M.coflats(8)) 0 sage: len(M.coflats(4)) 1
- components()#
Return an iterable containing the components of the matroid.
A component is an inclusionwise maximal connected subset of the matroid. A subset is connected if the matroid resulting from deleting the complement of that subset is
connected
.OUTPUT:
A list of subsets.
See also
EXAMPLES:
sage: from sage.matroids.advanced import setprint sage: M = Matroid(ring=QQ, matrix=[[1, 0, 0, 1, 1, 0], ....: [0, 1, 0, 1, 2, 0], ....: [0, 0, 1, 0, 0, 1]]) sage: setprint(M.components()) [{0, 1, 3, 4}, {2, 5}]
- dependent_r_sets(r)#
Return the list of dependent subsets of fixed size.
INPUT:
r
– a nonnegative integer.
OUTPUT:
An iterable containing all dependent subsets of size
r
.EXAMPLES:
sage: M = matroids.named_matroids.N1() sage: len(M.nonbases()) 68 sage: [len(M.dependent_r_sets(r)) for r in range(M.full_rank() + 1)] [0, 0, 0, 0, 9, 68]
- f_vector()#
Return the \(f\)-vector of the matroid.
The \(f\)-vector is a vector \((f_0, ..., f_r)\), where \(f_i\) is the number of flats of rank \(i\), and \(r\) is the rank of the matroid.
OUTPUT:
List of integers.
EXAMPLES:
sage: M = matroids.named_matroids.S8() sage: M.f_vector() [1, 8, 22, 14, 1]
- flats(r)#
Return the collection of flats of the matroid of specified rank.
A flat is a closed set.
INPUT:
r
– A natural number.
OUTPUT:
An iterable containing all flats of rank
r
.See also
EXAMPLES:
sage: M = matroids.named_matroids.S8() sage: M.f_vector() [1, 8, 22, 14, 1] sage: len(M.flats(2)) 22 sage: len(M.flats(8)) 0 sage: len(M.flats(4)) 1
- full_corank()#
Return the corank of the matroid.
The corank of the matroid equals the rank of the dual matroid. It is given by
M.size() - M.full_rank()
.OUTPUT:
Integer.
See also
EXAMPLES:
sage: M = matroids.named_matroids.Fano() sage: M.full_corank() 4 sage: M.dual().full_corank() 3
- full_rank()#
Return the rank of the matroid.
The rank of the matroid is the size of the largest independent subset of the groundset.
OUTPUT:
Integer.
EXAMPLES:
sage: M = matroids.named_matroids.Fano() sage: M.full_rank() 3 sage: M.dual().full_rank() 4
- groundset()#
Return the groundset of the matroid.
The groundset is the set of elements that comprise the matroid.
OUTPUT:
A set.
EXAMPLES:
sage: M = matroids.named_matroids.Fano() sage: sorted(M.groundset()) ['a', 'b', 'c', 'd', 'e', 'f', 'g']
- groundset_list()#
Return a list of elements of the groundset of the matroid.
The order of the list does not change between calls.
OUTPUT:
A list.
See also
EXAMPLES:
sage: M = matroids.named_matroids.Fano() sage: type(M.groundset()) <... 'frozenset'> sage: type(M.groundset_list()) <... 'list'> sage: sorted(M.groundset_list()) ['a', 'b', 'c', 'd', 'e', 'f', 'g'] sage: E = M.groundset_list() sage: E.remove('a') sage: sorted(M.groundset_list()) ['a', 'b', 'c', 'd', 'e', 'f', 'g']
- independent_r_sets(r)#
Return the list of size-
r
independent subsets of the matroid.INPUT:
r
– a nonnegative integer.
OUTPUT:
An iterable containing all independent subsets of the matroid of cardinality
r
.EXAMPLES:
sage: M = matroids.named_matroids.N1() sage: M.bases_count() 184 sage: [len(M.independent_r_sets(r)) for r in range(M.full_rank() + 1)] [1, 10, 45, 120, 201, 184]
- independent_sets()#
Return the list of independent subsets of the matroid.
OUTPUT:
An iterable containing all independent subsets of the matroid.
EXAMPLES:
sage: M = matroids.named_matroids.Fano() sage: I = M.independent_sets() sage: len(I) 57
- is_valid()#
Test if the data obey the matroid axioms.
This method checks the basis axioms for the class. If \(B\) is the set of bases of a matroid \(M\), then
\(B\) is nonempty
if \(X\) and \(Y\) are in \(B\), and \(x\) is in \(X - Y\), then there is a \(y\) in \(Y - X\) such that \((X - x) + y\) is again a member of \(B\).
OUTPUT:
Boolean.
EXAMPLES:
sage: from sage.matroids.advanced import * sage: M = BasisMatroid(matroids.named_matroids.Fano()) sage: M.is_valid() True sage: M = Matroid(groundset='abcd', bases=['ab', 'cd']) sage: M.is_valid() False
- nonbases()#
Return the list of nonbases of the matroid.
A nonbasis is a set with cardinality
self.full_rank()
that is not a basis.OUTPUT:
An iterable containing the nonbases of the matroid.
See also
EXAMPLES:
sage: M = matroids.named_matroids.N1() sage: binomial(M.size(), M.full_rank())-M.bases_count() # needs sage.symbolic 68 sage: len([B for B in M.nonbases()]) 68
- noncospanning_cocircuits()#
Return the list of noncospanning cocircuits of the matroid.
A noncospanning cocircuit is a cocircuit whose corank is strictly smaller than the corank of the matroid.
OUTPUT:
An iterable containing all nonspanning circuits.
See also
EXAMPLES:
sage: M = matroids.named_matroids.N1() sage: len(M.noncospanning_cocircuits()) 23
- nonspanning_circuits()#
Return the list of nonspanning circuits of the matroid.
A nonspanning circuit is a circuit whose rank is strictly smaller than the rank of the matroid.
OUTPUT:
An iterable containing all nonspanning circuits.
See also
EXAMPLES:
sage: M = matroids.named_matroids.N1() sage: len(M.nonspanning_circuits()) 23


--- layout: snippet title: "List group flush example" permalink: /examples/listgroup/flush/ sitemap: false ---


Admin Menu, Organized, but Still So Many Links!
Another view, listing them all on one page
That keeps going...
and going...
and going...
and going...
and going...
and this is a pretty simple site!
Same goes for the ckEditor.
So many options...
But really, only a few things are truly needed.
Who are our
Content Creators?
Common Additional Roles:
- Webmasters
- Editors
- Authors
Content Specific Roles such as:
Task Specific Roles such as:
Once we know who, we can start fighting for them.
Before we begin, let's talk about installing/uninstalling modules.
Using Drush
- drush dl -y module_name
- drush en -y module_name
- drush dis -y module_name
- drush pm-uninstall -y module_name
In the UI
Turn off (disable)
Uninstall (removes database bits)
Delete module folder by hand/in git
Theming the Drupal Administration UI
Administration Theme Options
- Choose a separate admin theme
- Use your front end theme
- Develop your own admin theme
Block System Applies to Admin Themes Too!
Global changes
Enable Admin Toolbar, Disable Overlay
- drush en -y admin_menu admin_menu_toolbar
- drush dis -y toolbar shortcut
- drush dis -y overlay
Content Type & Taxonomy Defaults
- Title Label
- Explanation or submission guidelines (Help)
- Administrative Description
- Default Publishing State, Revisions
- Author, Menu, Sitemap, (other modules), etc
Field Defaults
- Help text
- Default text format
- Module Settings (Linkit, Fences)
- Number of values for the field
- Images: File Directory, Types, Alt, etc
Field Group Types
- Fieldsets
- Horizontal tabs
- Vertical tabs
- Accordions
- Divs (Good for Grid Systems)
- HTML elements
Lots of modules that extend.
Dashboard(s)
There are many different ways to create a landing page for the logged in administrator.
- Default "content" screen
- Dashboard module
- Workbench Dashboard
- Custom Made Admin View
My suggestion is to choose one way, and make it great.
Common Tasks
- Add only relevant buttons needed for the field
- Exclude security risks (filters)
- Remove markup already in templates like H1, and add formats (classes).
- Configure Allowed content so classes aren't stripped, set height, etc.
- CKEditor 4.3+ Widgets -- Widgitizing Widgets by bneil.
Uploading Images in the WYSIWYG
- What types of files can be uploaded?
- What thumbnails are created for admin use?
- Where can they be uploaded?
ckFinder
- Set Different upload folders per Content Type.
- Make a Profile Type and Text Format for each Content Type.
IMCE
- Set Different upload folders per User Role.
- Can do user/userid or year/month (like Wordpress)
Scheduler
- Each content type can be scheduled.
- Which need to be?
- Who can?
- Set up external Cron
Workbench
- Each content type can have more statuses than Published. Workbench Moderation adds Draft and Needs Review by default, but can add custom ones you create.
- Workbench Access can restrict access to different sections of the site based on menu or taxonomies.
- Workbench Media adds integration with either the 1.x or 2.x of the Media Module!
Inline
Content Types, Fields, Blocks, Views, Panels, etc all provide places to enter descriptive and instructional text for administrative users
Content Types and fields allow for HTML, (link to…)
Google Docs/Dropbox/Company Intranet
- Keep a master copy, organized folder, shared with those who will help you maintain.
- Export PDF for users, shared with appropriately role'd users
- Authors can access author docs
- Editors can access author and editor docs
- Webmasters can access author, editor, and webmaster docs
- and so on.
Testing and Tweaking
Things change up to the last minute before a launch, and many times after that! Do not get stuck in the habit of just using the developer's administrator role.
- Use the site early and often as the Webmaster, Editor, and Author.
- Step through the documentation defined tasks, verify all can be done.
- Adjust permissions as you go.
How to be another
- Masquerade Module
- Create different accounts
- Gmail Users can use the plus trick
- jim+webmaster@
- jim+editor@
- jim+author@


--- layout: doc title: Documentation ---
This file documents version 4.6-git of Proof General, a generic Emacs interface for proof assistants.
Proof General 4.6-git has been tested with GNU Emacs 25.2 on Linux. It is supplied ready to use for the proof assistants Coq, EasyCrypt, qrhl-tool, and PhoX.
This document was generated on April 14, 2023 using texi2html 1.82.


Typically list packages and find public vulns
dpkg -l
Otherwise, script to enumerate all symlinks on system, and check whether those files still exist


Grant carries Bryant over Northern Vermont-Lyndon 116-67
SMITHFIELD, R.I. (AP) - Adam Grant had 21 points as Bryant romped past Northern Vermont-Lyndon 116-67 on Friday night.
Hall Elisias had 13 points and nine rebounds for Bryant (3-2). Benson Lin added 13 points. Charles Pride had 13 points.
It was the first time this season Bryant scored at least 100 points.
TOP STORIES
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Skeptics chuckle as climate activist Greta Thunberg sets sail for Europe on 'plastic yacht'
Damon Denteh had 16 points for the Hornets. Jahleel Gabriel added 12 points and 10 rebounds.
Bryant plays Niagara on the road on Monday.
For more AP college basketball coverage: https://apnews.com/Collegebasketball and http://twitter.com/AP_Top25
This was generated by Automated Insights, http://www.automatedinsights.com/ap, using data from STATS LLC, https://www.stats.com
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This is a service that can manage by adding a name to a bitcoin address.Touch the "GET MY ADDRESS" button to start.


{% extends 'base.html' %} {% block header %}
If you would like to override the default dependent variable title of {{ default_dep_var }}, please enter in a title below.
Please specify the width and height of the images. Note that all images will be cropped to the same size. We have gone ahead and parsed the dimensions of the first image found in the dataset and found it to be {{ default_x_dim[0] }} by {{ default_x_dim[1] }}. If left blank, this default value will be used.
The number of images to train the algorithm on simultaneously. Higher batch size means faster training, but at the cost of utilizing higher amounts of RAM. There are also some considerations to regularization and training stability. If left blank, the default value of {{ default_bs }} will be used.
The proportion of the images to be used for training versus validation versus testing. If left blank, the default split of {{ default_splits[0] }} for training, {{ default_splits[1] }} for validation, and {{ default_splits[2] }} for testing will be used.
This represents the number of times to iterate over the data set when training. Higher values mean training will take longer, but could yield better results. If left blank, a default value of {{ default_num_epochs }} will be used.


Design system
light blue bg, with dark text
white bg, with dark text
light blue bg at 20% opacity and white text


H1: Main page heading
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phase of the font in regular
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P: Paragraph text


The Funniest Way To Learn Or Improve Your Poker Skills
Why play it?
Seven Monkeys employs a variety of puzzles to help the player to understand and practice the rules and mathematics of Texas Hold'em Poker.
Meet The Monkeys
Unlock progressively each area to discover new puzzles guarded by monkeys which shows you a different poker concept to practice.
Poker Hands
Poker Positions
Best Hands
Flop Textures
Outs
Pot Odds
PreFlop strategy
Enjoy Practicing Your Poker skills
We would really appreciate if you can help us to spread the word and share Seven Monkeys with everyone to enjoy and learn poker.
Made with a lot of fun ＼(＾▽＾)／


Police to prosecute six FUTA students
by Peter DadaPeter Dada, Akure
Six students who allegedly brutalised a female student of the Federal University of Technology Akure will be prosecuted, according to the police in Ondo State.
Popoola Olaniyi, Faith Oluwadare, Jessica Nandi, Emmanuella Ajuwon, Emmanuel Taiwo and Cecilia Alao allegedly brutalised Boluwatife Adekunle for allegedly gossiping about one of them in one of the hostels outside the institution.
The school placed an indefinite suspension on the six students.
Spokesman for the police in the state Femi Joseph said the state Commissioner of Police Undie Adie had ordered the Divisional Police Officer in charge of the area to take up the matter.
Femi said, “We have watched the disgusting video of the incident and the CP has ordered that the six students should be prosecuted. So, whatever the university does on the matter the students will still face prosecution.
“What the students did to their fellow student was bad and they can’t go scot-free. That is why we are taking it up and we will get them.”
It was learnt that a disciplinary committee had been set up by the university to look into the case while the students would miss the second semester examination which began on Monday.
A source said, “If the students are found guilty, the penalty is expulsion.”
The Deputy Director of the Corporate Communications of the institution, Adegbenro Adebanjo, also confirmed that the students would face a disciplinary committee set up by the school.
He said, “The fate of the six students will depend on the outcome of the panel. They will be invited by the panel to defend themselves. But the suspended students cannot come near the campus until they are invited by the panel and all of them have been notified.”
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---
layout: home
search_exclude: true
image: images/index_page.png
---
### **Welcome to my [portfolio](https://enobongudoh.github.io/data-science-projects/) of data science projects, curated as part of my learning journey.**
![]({{site.baseurl}}/images/index_page.png "https://enobongudoh.github.io/data-science-projects/")
You can add me on linkedIn or email me
# **Posts**


This benchmark will teach you how to move the 3D viewpoint using the mouse.
The tab entitled Metrics measures your progress in an exercise where you have to place the viewpoint at a specific position and orientation. It also allows you to record your performance in the robotbenchmark database (if you are logged-in).
The tab entitled Instructions explains you how to use the mouse to control the viewpoint.
Move the viewpoint to get as close as possible to the top view depicted below. Note that you will not get the exact same view if you are using a different aspect ratio than the one in the picture, so you may need to resize your window to help you get a good result. The completion percentage displayed above indicates how close you are to the target viewpoint position and orientation. You need to achieve a positive performance (displayed in green) to be able to record it by pressing the "Record" button. The Instructions tab explains the mouse control details.


Everyone’s first program, “Hello World.”
Below you’ll find an example of the first use case from The C Programming Language. Ever since then people have been using it as a test phrase while developing, designing, or even hacking1.
Language: C
Everyone’s first program, “Hello World.”
Below you’ll find an example of the first use case from The C Programming Language. Ever since then people have been using it as a test phrase while developing, designing, or even hacking1.
Language: C


Successfully created with the name
Link to study:
Link to edit (Must be saved to make changes later):
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{% extends "base.html" %} {% block content %}
DOAJ would not be able to do the work that it does without the help of its volunteers. We are grateful for the hours that all our volunteers contribute by reviewing new applications and reapplications.
To coincide with Open Access Week 2015, DOAJ is launching a volunteer loyalty program. A certificate, signed by the Editor-in-Chief and the Managing Director, will be awarded to all volunteers for every 25 completed records (applications or reapplications) that result in an Accept/Reject decision. A new certificate will be awarded for every 25 records thereafter.
Take a look at our sample certificates in the New Service blog post.
We're also exploring the option of awarding Mozilla Open Badges so that a DOAJ volunteer can officially declare their work. We are considering hosting an annual virtual volunteer meeting to bring our volunteers together and give them the opportunity to network, exchange ideas or ask questions. Watch this space!
Finally, the names of all our active and working volunteers will be listed on this page.
For more information on how to volunteer, please take a look at our volunteer announcement and then, if you are interested in becoming a reviewer, apply here.
Our thanks goes to the following people who are actively working for DOAJ and who are making an active contribution to the quality and reputation of open access:
List being compiled now. Watch this space!
{% endblock %}


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Autodesk Vault
Browse the tree for files and click to display. Right-click the drawing for the tools menu


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PU2CLR PCF8574 Arduino Library
1.0.3
Arduino Library for PCF8574 Device - By Ricardo Lima Caratti
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It is a Library to control the PCF8574 device. More...
Functions | |
| void | PCF::setClock (long freq) |
| Sets I2C bus to a given frequency. More... | |
| uint8_t | PCF::lookForDevice () |
| Look for PCF8574 device I2C Address. More... | |
| void | PCF::setup (uint8_t i2c=DEFAULT_I2C_ADDRESS) |
| Starts the PCF8574. More... | |
It is a Library to control the PCF8574 device.
This library was built based on the Datasheet "PCF8574 8-Bit I/O Expander with Serial Interface" from Microchip
The PCF8574 device provides 8-bit, general purpose, parallel I/O expansion. It can be controlled via I²C bus applications. It is a great and inexpensive device that allow you to add more peripherals to be controlled by your Arduino board via I²C protocol.
Some Arduino projects may require more pins than the Arduino actually has. In these cases, you can use up to 8 PCF8574 devices using only the I²C bus (two Arduino pins) and add up to 64 input / output ports to your project.
This library can be freely distributed using the MIT Free Software model.
This library uses the I²C communication protocol and implements most important functions offered by PCF8574 device from MicroChip. It also has primitive functions that make it easier to implement commands that may not have been implemented yet. The main features implemented can be seen below:
1) GPIO individual control (8 I/O pins)
2) I²C address customization
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inline |
Sets I2C bus to a given frequency.
50000 = 50kHz; 100000 = 100kHz; etc
Plese check the property I2C bus frequency/speed of your board
| uint8_t PCF::lookForDevice | ( | ) |
Look for PCF8574 device I2C Address.
This method will look for a valid PCF8574 device adress between 0x20 and 0x27
| void PCF::setup | ( | uint8_t | i2c = DEFAULT_I2C_ADDRESS | ) |
Starts the PCF8574.
Starts the PCF8574 and sets the default values.
| i2c | I2C address |
| reset_pin | if you want to control the reset, select an Arduino pin to do that. |


Simple example app for the ngx-fabric-wrapper
This example only shows some of the available features, to see all check Fabric demos / documentation.
Settings
{{(type === "component") ? "Switch to directive" : "Switch to component"}}
Toggle disabled state
Add line object
Add text object
Add image object
Reset the canvas


Today, the Department of Justice, U.S. Immigration and Customs Enforcement’s Homeland Security Investigations (HSI), the U.S. Secret Service (USSS), the U.S. Postal Inspection Service (USPIS) and the U.S. Drug Enforcement Administration (DEA), announced the results of a yea...


Card 1
Kiwis are oval shaped with a brownish outer skin. The flesh is bright green and juicy with
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Kiwis are oval shaped with a brownish outer skin. The flesh is bright green and juicy with
Kiwis are oval shaped with a brownish outer skin. The flesh is bright green and juicy with
With supporting text below as a natural lead-in to additional content.
Go somewhere


More...
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| static Element | Append (Element el, DomObject o) |
| | Creates new DOM element(s) and appends them to el. More...
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| static Element | Append (Element el, string o) |
| | Creates new DOM element(s) and appends them to el. More...
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| static void | ApplyStyles (Element el, Dictionary< string, string > styles) |
| | Applies a style specification to an element. More...
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| static Element | InsertAfter (Element el, DomObject o) |
| | Creates new DOM element(s) and inserts them after el. More...
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| static Element | InsertAfter (Element el, string o) |
| | Creates new DOM element(s) and inserts them after el. More...
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| static Element | InsertBefore (Element el, DomObject o) |
| | Creates new DOM element(s) and inserts them before el. More...
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| static Element | InsertBefore (Element el, string o) |
| | Creates new DOM element(s) and inserts them before el. More...
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| static Element | InsertFirst (Element el, DomObject o) |
| | Creates new DOM element(s) and inserts them as the first child of el. More...
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| static Element | InsertFirst (Element el, string o) |
| | Creates new DOM element(s) and inserts them as the first child of el. More...
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| static Element | InsertHtml (InsertPosition where, Element el, string html) |
| | Inserts an HTML fragment into the DOM. More...
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| static Element | Overwrite (Element el, DomObject o) |
| | Creates new DOM element(s) and overwrites the contents of el with them. More...
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| static Element | Overwrite (Element el, string o) |
| | Creates new DOM element(s) and overwrites the contents of el with them. More...
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◆ Append() [1/2]
Creates new DOM element(s) and appends them to el.
- Parameters
-
| el | The context element |
| o | The DOM object spec (and children) or raw HTML blob |
◆ Append() [2/2]
| static Element Ext.Net.Mobile.DomHelper.Append |
( |
Element |
el, |
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string |
o |
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) |
| |
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inlinestatic |
Creates new DOM element(s) and appends them to el.
- Parameters
-
| el | The context element |
| o | Raw HTML blob |
◆ ApplyStyles()
| static void Ext.Net.Mobile.DomHelper.ApplyStyles |
( |
Element |
el, |
|
|
Dictionary< string, string > |
styles |
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) |
| |
|
inlinestatic |
Applies a style specification to an element.
- Parameters
-
| el | The element to apply styles to |
| styles | A style specification. |
◆ InsertAfter() [1/2]
Creates new DOM element(s) and inserts them after el.
- Parameters
-
| el | The context element |
| o | The DOM object spec (and children) |
◆ InsertAfter() [2/2]
| static Element Ext.Net.Mobile.DomHelper.InsertAfter |
( |
Element |
el, |
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|
string |
o |
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) |
| |
|
inlinestatic |
Creates new DOM element(s) and inserts them after el.
- Parameters
-
| el | The context element |
| o | The DOM object spec (and children) |
◆ InsertBefore() [1/2]
Creates new DOM element(s) and inserts them before el.
- Parameters
-
| el | The context element |
| o | The DOM object spec (and children) |
◆ InsertBefore() [2/2]
| static Element Ext.Net.Mobile.DomHelper.InsertBefore |
( |
Element |
el, |
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|
string |
o |
|
) |
| |
|
inlinestatic |
Creates new DOM element(s) and inserts them before el.
- Parameters
-
| el | The context element |
| o | The DOM object spec (and children) |
◆ InsertFirst() [1/2]
Creates new DOM element(s) and inserts them as the first child of el.
- Parameters
-
| el | The context element |
| o | The DOM object spec (and children) |
◆ InsertFirst() [2/2]
| static Element Ext.Net.Mobile.DomHelper.InsertFirst |
( |
Element |
el, |
|
|
string |
o |
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) |
| |
|
inlinestatic |
Creates new DOM element(s) and inserts them as the first child of el.
- Parameters
-
| el | The context element |
| o | The DOM object spec (and children) |
◆ InsertHtml()
Inserts an HTML fragment into the DOM.
- Parameters
-
| where | Where to insert the html in relation to el - BeforeBegin, AfterBegin, BeforeEnd, AfterEnd. |
| el | The context element |
| html | The HTML fragmenet |
◆ Overwrite() [1/2]
Creates new DOM element(s) and overwrites the contents of el with them.
- Parameters
-
| el | The context element |
| o | The DOM object spec (and children) |
◆ Overwrite() [2/2]
| static Element Ext.Net.Mobile.DomHelper.Overwrite |
( |
Element |
el, |
|
|
string |
o |
|
) |
| |
|
inlinestatic |
Creates new DOM element(s) and overwrites the contents of el with them.
- Parameters
-
| el | The context element |
| o | The DOM object spec (and children) |
The documentation for this class was generated from the following file:


In the natural sciences, data is often a finite set of measurements while the process of learning is usually achieved by confronting that data with scientific theories and models. The conclusion might ultimately be falsification of an hypothesis underlying a theory or a model. However, it will not be an ultimate determination of the truth of an hypothesis. More commonly, the conclusion might be an improved model that can be used for predictions of new phenomena. Thus, we are typically dealing with inductive inference.
This process of learning from data is fundamental to the scientific wheel of progress.
Thus, we will be able to study statistical inference methods for learning from data and use them in scientific applications. In particular, we will use Bayesian statistics. Simultaneously we will slowly develop a deeper understanding and probabilistic interpretation of machine learning algorithms through a statistical foundation.
Edwin Jaynes, in his influential How does the brain do plausible reasoning?, wrote:
One of the most familiar facts of our experience is this: that there is such a thing as common sense, which enables us to do plausible reasoning in a fairly consistent way. People who have the same background of experience and the same amount of information about a proposition come to pretty much the same conclusions as to its plausibility. No jury has ever reached a verdict on the basis of pure deductive reasoning. Therefore the human brain must contain some fairly definite mechanism for plausible reasoning, undoubtedly much more complex than that required for deductive reasoning. But in order for this to be possible, there must exist consistent rules for carrying out plausible reasoning, in terms of operations so definite that they can be programmed on the computing machine which is the human brain.
Jaynes went on to show that these "consistent rules" are just the rules of Bayesian probability theory, supplemented by Laplace's principle of indifference and, its generalization, Shannon's principle of maximum entropy. This key observation implies that a computer can be programmed to "reason", or, update probabilities based on data. Given some very minimal desiderata, the rules of Bayesian probability are the only ones which conform to what, intuitively, we recognize as rationality. Such probability update rules can be used recursively to impute causal relationships between observations, that is, a machine can be programmed to "learn".
Inference and machine learning, then, is the creative application of Bayesian probability to problems of rational inference and causal knowledge discovery based on data.
In this course we will focus in particular on the statistical foundation for being able to learn from data, in particular we will take the Bayesian viewpoint of extended logic. Although we aim for theoretical depth, we will still take a practical learning approach with many opportunities to apply the theories in practice using simple computer programs.
However, being this ambitious in teaching a theoretical foundation means that there will be less time to cover the plethora of machine learning methods, or to find examples from a very wide list of subfields in physics. We believe that striving for theoretical depth and obtaining your own computational experience will give the best preparation for being able to apply the knowledge in new situations and for real problems that will be encountered in future studies and work.
In particular, physics and astronomy students have a unique preparation:
During the last two decades there has been a swift and amazing development of Machine learning techniques and algorithms that impact many areas in not only Science and Technology but also the Humanities, Social Sciences, Medicine, Law, etc. Indeed, almost all possible disciplines are affected. The applications are incredibly many, from self-driving cars to solving high-dimensional differential equations or complicated quantum mechanical many-body problems. Machine learning is perceived by many as one of the main disruptive techniques nowadays.
Statistics, Data science and Machine learning form important fields of research in modern science. They describe how to learn and make predictions from data, as well as allowing us to extract important correlations about physical process and the underlying laws of motion in large data sets. The latter, big data sets, appear frequently in essentially all disciplines, from the traditional Science, Technology, Mathematics and Engineering fields to Life Science, Law, education research, the Humanities and the Social Sciences.
It has become more and more common to see research projects on big data in for example the Social Sciences where extracting patterns from complicated survey data is one of many research directions. Having a solid grasp of data analysis and machine learning is thus becoming central to scientific computing in many fields, and competences and skills within the fields of machine learning and scientific computing are nowadays strongly requested by many potential employers. The latter cannot be overstated, familiarity with machine learning has almost become a prerequisite for many of the most exciting employment opportunities, whether they are in bioinformatics, life science, physics or finance, in the private or the public sector. This author has had several students or met students who have been hired recently based on their skills and competences in scientific computing and data science, often with marginal knowledge of machine learning.
Machine learning is a subfield of computer science, and is closely related to computational statistics. It evolved from the study of pattern recognition in artificial intelligence (AI) research, and has made contributions to AI tasks like computer vision, natural language processing and speech recognition. Many of the methods we will study are also strongly rooted in basic mathematics and physics research.
Ideally, machine learning represents the science of giving computers the ability to learn without being explicitly programmed. The idea is that there exist generic algorithms which can be used to find patterns in a broad class of data sets without having to write code specifically for each problem. The algorithm will build its own logic based on the data. You should however always keep in mind that machines and algorithms are to a large extent developed by humans. The insights and knowledge we have about a specific system, play a central role when we develop a specific machine learning algorithm.
Machine learning is an extremely rich field, in spite of its young age. The increases we have seen during the last three decades in computational capabilities have been followed by developments of methods and techniques for analyzing and handling large date sets, relying heavily on statistics, computer science and mathematics. The field is rather new and developing rapidly. Popular software packages written in Python for machine learning like Scikit-learn, Tensorflow, PyTorch and Keras, all freely available at their respective GitHub sites, encompass communities of developers in the thousands or more. And the number of code developers and contributors keeps increasing. Not all the algorithms and methods can be given a rigorous mathematical justification, opening up thereby large rooms for experimenting and trial and error and thereby exciting new developments. However, a solid command of linear algebra, multivariate theory, probability theory, statistical data analysis, understanding errors and Monte Carlo methods are central elements in a proper understanding of many of algorithms and methods we will discuss.
The approaches to machine learning are many, but are often split into two main categories. In supervised learning we know the answer to a problem, and let the computer deduce the logic behind it. On the other hand, unsupervised learning is a method for finding patterns and relationship in data sets without any prior knowledge of the system. Some authours also operate with a third category, namely reinforcement learning. This is a paradigm of learning inspired by behavioral psychology, where learning is achieved by trial-and-error, solely from rewards and punishment.
Another way to categorize machine learning tasks is to consider the desired output of a system. What kind of inference are you hoping to see in your data? Is the aim to classify a result into categories, to predict a continuous value, or to simply observe patterns within the data? Let’s briefly introduce each class:
All methods have three main ingredients in common, irrespective of whether we deal with supervised or unsupervised learning.
Python plays a central role in the development of machine learning techniques and tools for data analysis. In particular, given the wealth of machine learning and data analysis libraries written in Python, easy-to-use libraries with immediate visualization (and the impressive galleries of existing examples), the popularity of the Jupyter notebook framework (with the possibility to run R codes, or simulation programs written in compiled languages), and much more made our choice of programming language for this series of lectures easy. However, since the focus here is not only on using existing Python libraries such as Scikit-Learn or Tensorflow, but also on developing your own algorithms and codes, we will as far as possible present many of these algorithms as Python codes.
The reason we also mention compiled languages (like C, C++ or Fortran), is that Python is still notoriously slow when we do not utilize highly streamlined computational libraries written in compiled languages. Therefore, analysis codes involving heavy Markov Chain Monte Carlo simulations and high-dimensional optimization of cost functions, tend to utilize C++/C or Fortran codes for the heavy lifting.
Presently thus, the community tends to let code written in C++/C or Fortran do the heavy duty numerical number crunching and leave the post-analysis of the data to the above mentioned Python modules or software packages. However, with the developments taking place in for example the Python community, and seen the changes during the last decade, the above situation may change in the not too distant future.
In most of the cases we will study, we will generate the data to analyze ourselves. However, this does not hinder us from developing a sound ethical attitude to the data we use, how we analyze the data and how we handle it.
The most immediate and simplest possible ethical aspects deal with our approach to the scientific process. Nowadays, with version control software like Git and various online repositories like Github, Gitlab etc, we can easily make our codes and data sets we have used, freely and easily accessible to a wider community. This helps us almost automagically in making our science reproducible. The large open-source development communities involved in say Scikit-Learn, Tensorflow, PyTorch and Keras, are all excellent examples of this. The codes can be tested and improved upon continuosly, helping thereby our scientific community at large in developing data analysis and machine learning tools. It is much easier today to gain traction and acceptance for making your science reproducible. From a societal stand, this is an important element since many of the developers are employees of large public institutions like universities and research labs.
However, this more mechanical aspect of the ethics of science (in particular the reproducibility of scientific results) is something which is obvious and everybody should do so as part of the dialectics of science.
Before we proceed, we should add a disclaimer. Even though we may dream of computers developing some kind of higher learning capabilities, at the end (even if the artificial intelligence community keeps touting our ears full of fancy futuristic avenues), it is we, yes you reading these lines, who end up constructing and instructing, via various algorithms, the machine learning approaches.
For self-driving vehicles, where the standard machine learning algorithms discussed here enter into the software, there are stages where we have to make choices. Yes, we, the humans who wrote a program for a specific brand of a self-driving car. As an example, all carmakers have as their utmost priority the security of the driver and the accompanying passengers. A famous European carmaker, which is one of the leaders in the market of self-driving cars, had if statements of the following type: suppose there are two obstacles in front of you and you cannot avoid to collide with one of them. One of the obstacles is a monstertruck while the other one is a kindergarten class trying to cross the road. The self-driving car algo would then opt for the hitting the small folks instead of the monstertruck, since the likelihood of surving a collision with our future citizens, is much higher.
This leads to serious ethical aspects. Why should we opt for such an option? Who decides and who is entitled to make such choices? Keep in mind that many of the algorithms you will encounter in this series of lectures or hear about later, are indeed based on simple programming instructions. And you are very likely to be one of the people who may end up writing such a code. Thus, developing a sound ethical attitude is much needed. The example of the self-driving cars is just one of infinitely many cases where we have to make choices. When you analyze data on economic inequalities, who guarantees that you are not weighting some data in a particular way, perhaps because you dearly want a specific conclusion which may support your political views?
We do not have the answers here, nor will we venture into a deeper discussions of these aspects, but we want you think over these topics in a more overarching way. A statistical data analysis with its dry numbers and graphs meant to guide the eye, does not necessarily reflect the truth, whatever that is. As a scientist, and after a university education, you are supposedly a better citizen, with an improved critical view and understanding of the scientific method, and perhaps some deeper understanding of the ethics of science at large. Use these insights. Be a critical citizen. You owe it to our society.
A first demonstration of machine learning in physics is shown in the accompanying jupyter notebook. We will show some of the strengths of packages like Scikit-Learn in fitting nuclear binding energies to specific models using linear regression.
See the Getting started guide on the course web page.
The development of this course would not have been possible without the knowledge that has been gained through the study of several excellent textbooks, most of which are listed as recommended course literature. Here is a short list of those references that I have found the most influential and inspirational:
The last statement extends obviously to the open source communities that make so many great computing tools publicly available. In this course we take much advantage of open-source python libraries.


CrimPapers
Articles published on 22 December 2018
On 22 December 2018, 9 new articles were published in 7 journals.
Book Review: From the War on Poverty to the War on Crime: the Making of Mass Incarceration in America by Becky Pettit
Beyond the Dichotomy: Incarceration Dosage and Mental Health by Lauren C. Porter,
laura M. Demarco
Which Source Possesses the Best Data on the Empirical Aspects of Criminal Events? A Theory of Opportunity and Necessary Conditions by Scott Jacques
“Economic Crisis and Poaching: Advice on Anti-Poaching Management From the Galician Shellfish Sector” by Hugo M. Ballesteros, Gonzalo Rodríguez-Rodríguez
Italian Adolescents’ Experience of Unwanted Online Attentions: Recognizing and Defining Behaviours by Laura de Fazio, Amanda Krause, Chiara Sgarbi
Meaning Attribution to Intimate Partner Violence By Counselors Who Support Women With Intimate Partner Violence Experiences in Greece by Anthi Argyroudi, Katerina Flora
Interpersonal Trauma Exposure and Depression in Young Adults: Considering the Role of World Assumptions by Jessica L. Schleider, Jacqueline Woerner, Cassie Overstreet, Ananda B. Amstadter, Carolyn E. Sartor
Evolutionary Approaches to Understanding Crime: Explaining the Gender Gap in Offending by Russil Durrant
Grading the Quality of Isis Videos: A Metric For Assessing the Technical Sophistication of Digital Video Propaganda by Mark D. Robinson, Cori E. Dauber


Class FileLogger
Assembly: DotNetHelper-Logger.dll
Syntax
public class FileLogger : IFileLogger, ILogger
Constructors
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FileLogger()
Declaration
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FileLogger(String, String)
Declaration
public FileLogger(string logFileFullPath, string errorsOnlyFileFullPath)
Parameters
| Type |
Name |
Description |
| String |
logFileFullPath |
|
| String |
errorsOnlyFileFullPath |
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Properties
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Encoding
Declaration
public Encoding Encoding { get; set; }
Property Value
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ErrorsOnlyFileEnable
If True Any Logged Errors That Is Executed Will Go To An Additional Log File Containing Only Errors
Declaration
public bool ErrorsOnlyFileEnable { get; set; }
Property Value
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ErrorsOnlyLogFile
Declaration
public FileObject ErrorsOnlyLogFile { get; set; }
Property Value
| Type |
Description |
| DotNetHelper_IO.FileObject |
|
|
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IsLoggingEnable
Declaration
public bool IsLoggingEnable { get; set; }
Property Value
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LogFile
Declaration
public FileObject LogFile { get; set; }
Property Value
| Type |
Description |
| DotNetHelper_IO.FileObject |
|
|
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MaxFileSize
Max Size In Bytes That Log Files Are Allow To Reach. Anything Zero Or Less Will Be Consider Infinite. Defaults To 10 MB
Declaration
public long MaxFileSize { get; set; }
Property Value
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MaxLifespan
if set invokes onMaxCreatedInterval
Declaration
public TimeSpan? MaxLifespan { get; set; }
Property Value
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Prefix
we use a function because if your prefix include DateTime.Now the value with be static therefore we invoke a function that returns a string
Declaration
public Func<string> Prefix { get; set; }
Property Value
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TruncateOnAppStart
Truncate All Logs On Application Start
Declaration
public bool TruncateOnAppStart { get; set; }
Property Value
Methods
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ConsoleAndLog(Exception, LogSeverity)
Declaration
public void ConsoleAndLog(Exception error, LogSeverity logSeverity = LogSeverity.Error)
Parameters
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ConsoleAndLog(String, LogSeverity)
Writes the message to the console and log file
Declaration
public void ConsoleAndLog(string message, LogSeverity logSeverity = LogSeverity.Information)
Parameters
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ConsoleWrite(String, LogSeverity)
Writes the message to the console
Declaration
public void ConsoleWrite(string message, LogSeverity logSeverity = LogSeverity.Information)
Parameters
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DebugWrite(String, LogSeverity)
Writes the message to the Diagnostic output
Declaration
public void DebugWrite(string message, LogSeverity logSeverity = LogSeverity.Information)
Parameters
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Log(String, LogSeverity)
Logs the content to the log file
Declaration
public void Log(string content, LogSeverity logSeverity = LogSeverity.Information)
Parameters
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LogError(Exception, LogSeverity)
Logs the exception to the log file
Declaration
public void LogError(Exception ex, LogSeverity logSeverity = LogSeverity.Error)
Parameters
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LogError(String, Exception, LogSeverity)
Logs the exception to the log file
Declaration
public void LogError(string notes, Exception ex, LogSeverity logSeverity = LogSeverity.Error)
Parameters
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OnMaxLifespanReached(FileObject)
Declaration
protected virtual void OnMaxLifespanReached(FileObject file)
Parameters
| Type |
Name |
Description |
| DotNetHelper_IO.FileObject |
file |
|
|
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OnMaxSizeReached(FileObject)
Declaration
protected virtual void OnMaxSizeReached(FileObject file)
Parameters
| Type |
Name |
Description |
| DotNetHelper_IO.FileObject |
file |
|
Events
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MaxLifespanReached
Declaration
public event EventHandler<FileObject> MaxLifespanReached
Event Type
|
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MaxSizeReached
Declaration
public event EventHandler<FileObject> MaxSizeReached
Event Type
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OnFailedLogAttempt
Declaration
public event EventHandler<Exception> OnFailedLogAttempt
Event Type
|
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OnProcessExit
Declaration
public event EventHandler<EventArgs> OnProcessExit
Event Type
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OnUnHandledException
Declaration
public event EventHandler<UnhandledExceptionEventArgs> OnUnHandledException
Event Type
Implements


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We're not even to beta yet, but we already have not one, but two 3rd party XAML viewers targeting existing versions of the .NET Framework. Wow.
[From Don "XML" (donxml.com)]


12Setting the “system” attribute from DOS on the critical files (e.g. everything in C:\LINUX) may help to protect them from being rearranged. However, the boot floppy should still be ready, just in case.


{% comment %} This file is intended to be used as a Django include file for the purpose of displaying the nothing-to-see-here message: {% include 'bom/nothing-to-see.html' required_privilege=PPP %} where UUU is the includee's user profile variable for the currently logged-in user and PPP is a string that denotes the role that user must have in order to gain access. {% endcomment %}
Nothing to see here 🙈 because you do not have {{ required_privilege }} privileges. Please contact {{ organization }}'s IndaBOM owner {{ profile.organization.owner.email }} for assistance


Some facts about me:
My name is Sasha Borysiuk
I am 17 years old
I am a student of the
VNTU
university
Links on my social pages:
Instagram
Beetroot
Vladymyr Malinovskyi
Mihail Gurin
Alex Klimchuk


'QuantLib' bindings are provided for R using 'Rcpp' and the header-only 'Quantuccia' variant (put together by Peter Caspers) offering an essential subset of 'QuantLib'. See the included file 'AUTHORS' for a full list of contributors to both 'QuantLib' and 'Quantuccia'.
| Version: | 0.0.2 |
| Imports: | Rcpp |
| LinkingTo: | Rcpp, BH |
| Published: | 2017-11-06 |
| Author: | Dirk Eddelbuettel; the authors and contributors of QuantLib RcppQuantuccia author details |
| Maintainer: | Dirk Eddelbuettel <edd at debian.org> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| Copyright: | see file COPYRIGHTS |
| NeedsCompilation: | yes |
| Materials: | README NEWS ChangeLog |
| In views: | Finance |
| CRAN checks: | RcppQuantuccia results |
| Reference manual: | RcppQuantuccia.pdf |
| Package source: | RcppQuantuccia_0.0.2.tar.gz |
| Windows binaries: | r-devel: RcppQuantuccia_0.0.2.zip, r-release: RcppQuantuccia_0.0.2.zip, r-oldrel: RcppQuantuccia_0.0.2.zip |
| OS X binaries: | r-release: RcppQuantuccia_0.0.2.tgz, r-oldrel: RcppQuantuccia_0.0.2.tgz |
| Old sources: | RcppQuantuccia archive |
Please use the canonical form https://CRAN.R-project.org/package=RcppQuantuccia to link to this page.


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--- layout: post title: New Kitchen Has Arrived! date: 2011-10-06 11:26:42.000000000 -04:00 categories: - Family Life - Renovations (Renos 101!) tags: - DIY kitchen - Flat pack kitchen - Kitset Kitchens - Ktichen Renovations - New kitchen status: publish type: post published: true meta: aktt_notify_twitter: 'no' _edit_last: '1' dsq_thread_id: '1188595476' author: login: cint email<EMAIL_ADDRESS>display_name: Jacinta first_name: Jacinta last_name: '' ---
The new kitchen arrived today, flat packed. Of course we were lead to believe that there would be two people unloading it, but no, just one. I ended up having to help unload lots of pieces, some pretty heavy, so I am feeling it tonight. I won't complain too much, as I have been looking forward to this dream kitchen for some time. Now for the fun part, putting the pieces together. It's one big jigsaw really. We are just hoping there are some instructions in one of the boxes! I'll leave that one for Greg and his dad to puzzle over.
[caption id="attachment_1219" align="aligncenter" width="600" caption="Some assembly required!!"][/caption]
It will be very interesting getting by without a kitchen for at least the next 2 1/2 weeks and with at least 7 people to cater for, I will hopefully continue to be creative with meals. Hmm, let's see.
Jacinta x


We have over 60+ retro arcade cabinets at any given time and cycle through the games
so that there's always something different to play. We even have pinball machines!
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