Class: Sass::Script::Lexer
- Inherits:
-
Object
- Object
- Sass::Script::Lexer
- Includes:
- Sass::SCSS::RX
- Defined in:
- /usr/local/google-old/home/code/sass-site/.sass/lib/sass/script/lexer.rb
Overview
The lexical analyzer for SassScript. It takes a raw string and converts it to individual tokens that are easier to parse.
Direct Known Subclasses
Defined Under Namespace
Classes: Token
Constant Summary
Instance Method Summary (collapse)
-
- (Boolean) after_interpolation?
Whether or not the last token lexed was
:end_interpolation
. -
- (Boolean) done?
Whether or not there’s more source text to lex.
-
- expected!(name)
Raise an error to the effect that
name
was expected in the input stream and wasn’t found. -
- (Lexer) initialize(str, line, offset, options)
constructor
A new instance of Lexer.
-
- (Fixnum) line
The line number of the lexer’s current position.
-
- (Token) next
Moves the lexer forward one token.
-
- (Fixnum) offset
The number of bytes into the current line of the lexer’s current position (1-based).
-
- (Token) peek
Returns the next token without moving the lexer forward.
-
- (String) str { ... }
Records all non-comment text the lexer consumes within the block and returns it as a string.
-
- unpeek!
Rewinds the underlying StringScanner to before the token returned by #peek.
-
- (Boolean) whitespace?(tok = @tok)
Returns whether or not there’s whitespace before the next token.
Methods included from Sass::SCSS::RX
Constructor Details
- (Lexer) initialize(str, line, offset, options)
Returns a new instance of Lexer
147 148 149 150 151 152 153 154 |
# File '/usr/local/google-old/home/code/sass-site/.sass/lib/sass/script/lexer.rb', line 147
def initialize(str, line, offset, options)
@scanner = str.is_a?(StringScanner) ? str : Sass::Util::MultibyteStringScanner.new(str)
@line = line
@offset = offset
@options = options
@interpolation_stack = []
@prev = nil
end
|
Instance Method Details
- (Boolean) after_interpolation?
Returns Whether or not the last token lexed was :end_interpolation
.
202 203 204 |
# File '/usr/local/google-old/home/code/sass-site/.sass/lib/sass/script/lexer.rb', line 202
def after_interpolation?
@prev && @prev.type == :end_interpolation
end
|
- (Boolean) done?
Returns Whether or not there’s more source text to lex.
196 197 198 199 |
# File '/usr/local/google-old/home/code/sass-site/.sass/lib/sass/script/lexer.rb', line 196
def done?
whitespace unless after_interpolation? && @interpolation_stack.last
@scanner.eos? && @tok.nil?
end
|
- expected!(name)
Raise an error to the effect that name
was expected in the input stream and wasn’t found.
This calls #unpeek! to rewind the scanner to immediately after the last returned token.
214 215 216 217 |
# File '/usr/local/google-old/home/code/sass-site/.sass/lib/sass/script/lexer.rb', line 214
def expected!(name)
unpeek!
Sass::SCSS::Parser.expected(@scanner, name, @line)
end
|
- (Fixnum) line
The line number of the lexer’s current position.
29 30 31 32 |
# File '/usr/local/google-old/home/code/sass-site/.sass/lib/sass/script/lexer.rb', line 29
def line
return @line unless @tok
@tok.source_range.start_pos.line
end
|
- (Token) next
Moves the lexer forward one token.
159 160 161 162 163 164 |
# File '/usr/local/google-old/home/code/sass-site/.sass/lib/sass/script/lexer.rb', line 159
def next
@tok ||= read_token
@tok, tok = nil, @tok
@prev = tok
tok
end
|
- (Fixnum) offset
The number of bytes into the current line of the lexer’s current position (1-based).
38 39 40 41 |
# File '/usr/local/google-old/home/code/sass-site/.sass/lib/sass/script/lexer.rb', line 38
def offset
return @offset unless @tok
@tok.source_range.start_pos.offset
end
|
- (Token) peek
Returns the next token without moving the lexer forward.
181 182 183 |
# File '/usr/local/google-old/home/code/sass-site/.sass/lib/sass/script/lexer.rb', line 181
def peek
@tok ||= read_token
end
|
- (String) str { ... }
Records all non-comment text the lexer consumes within the block and returns it as a string.
224 225 226 227 228 229 |
# File '/usr/local/google-old/home/code/sass-site/.sass/lib/sass/script/lexer.rb', line 224
def str
old_pos = @tok ? @tok.pos : @scanner.pos
yield
new_pos = @tok ? @tok.pos : @scanner.pos
@scanner.string[old_pos...new_pos]
end
|
- unpeek!
Rewinds the underlying StringScanner to before the token returned by #peek.
187 188 189 190 191 192 193 |
# File '/usr/local/google-old/home/code/sass-site/.sass/lib/sass/script/lexer.rb', line 187
def unpeek!
if @tok
@scanner.pos = @tok.pos
@line = @tok.source_range.start_pos.line
@offset = @tok.source_range.start_pos.offset
end
end
|
- (Boolean) whitespace?(tok = @tok)
Returns whether or not there’s whitespace before the next token.
169 170 171 172 173 174 175 176 |
# File '/usr/local/google-old/home/code/sass-site/.sass/lib/sass/script/lexer.rb', line 169
def whitespace?(tok = @tok)
if tok
@scanner.string[0...tok.pos] =~ /\s\Z/
else
<EMAIL_ADDRESS>1] =~ /^\s/ ||
<EMAIL_ADDRESS>- 1, 1] =~ /\s\Z/
end
end
|


The Table component has seven predefined styles:
Table
You can set these styles to the Table using the stylename attribute either in the XML descriptor or in the screen controller using constants from HaloTheme class.
stylename
HaloTheme


fundManageR
— R’s Investment Management Toolkit
Because the Industry Must Liberate Itself from the Chains of Excel
Outside of a few isolated pockets, the participants in the $67,0000,000,000 + United States investment management are trapped in Excel-centric universe. This is a dangerous state of being
Whether you are talking about Private Equity, Venture Capital, Real Estate Private Equity or Hedge Funds, industry professionals are executing important business functions dangerously and inefficiently through a maze of Excel spreadsheets.
The purpose of this package is to provide R proficient industry professionals a generalized framework that provides out-of-the-box access to functions that perform many standardizable industry pertinent calculations.
As an added bonus this package also wraps access to a growing array of data silos, including the first full wrapper of the SEC’s Investment Adviser Public Disclosure database in any of the major programming languages. It’s my hope that this package’s data acquisition functionality will be of use to industry professionals, academics, journalists, or anyone who enjoys exploring interesting data sets.
Excel, while convenient for some, is poorly suited for important data analysis and modelling. Billions of dollars have been lost throughout the investment management universe as a direct result of uncaught Excel errors. Here are few examples:
Further more, for many of the most common calculations, there is countless duplication of methods to perform common calculations, and in many cases formulas are left unchecked and errors end up having extreme consequences down the line.
Though in its extreme infancy, fundManageR
is my attempt to provide an easy to use framework for these calculations to be performed in R, through an open and readable API, consistent with Hadley Wickham’s tidy tools manifesto. These calculations have fault checks to ensure accuracy and designed for iteration which allows for complex calculations that Excel would be unable to execute.
The package’s other motive is to provide easy access to the financial industry’s dark data, hidden and public APIs. This should enable better transparency around one of the United States’ most vital industries. As the old saying goes, when in doubt Follow the Money
, fundManageR
should help to do this.
In order for this package to work you need the packages listed below must be installed. You can run the code snippet to install them if necessary.
For pdftools
you may need to follow the installation instructions here.
packages <- c("curl", "curlconverter", "dplyr", "formattable", "httr", "jsonlite", 'devtools', "lazyeval", "lubridate", "magrittr", "pdftools", "purrr", "readr", 'quantmod', "readxl", "rvest", "stringi", "stringr", "tibble", "tidyr", 'tidyverse', "xml2", "") lapply(packages, install.packages)
devtools::install_github("abresler/fundManageR")
fundManageR
is built around 2 full function families and another with 1 usable, but powerful, with many more on the way.
calculate_
– this function family performs common industry specific and generalized calculations.visualize_
– this function family performs pre-packaged visualizations geared towards the data this package brings in or helps the user to create.calculate_
Functionscalculate_cash_flow_dates
– Calculates summary cash flows for a specified dates and cash flowscalculate_irr_periods
– Calculates interal rate of return for specified dates and cash flowscalculate_cash_flows_returns
– Calculates investment returns for specified dates and cash flowscalculate_cash_flow_waterfall
– Calculates a cash flow waterfall given specified dates, cash flows and promote structurecalculate_cash_flow_waterfall_partnership
– Calculates partnership level returns and waterfall given specified equity splits, promote structure, and cash flows.calculate_loan_payment
– Calculates loan repayment data given specified parameterscalculate_residual_valuation_ebitda_multiples
– Calculates residual values given specified EBITDA and EBITDA Multiples
calculate_residual_valuation_cap_rates
– Calculates residual value given specified Net Operating Income and Capitalization Rates
calculate_leverage_metrics
– Caluclates crude leveraged cash flow metrics for a given set of inputs. Ideal for back of the envelope type calculations of a potential leveraged asset purchase.calculate_valuation_post_money
– Calculates entity ownership post investmentcalculate_days_accrued_pref
– Calculates accrued preference/interest for a specified period.This package now supports parallel computing for all iterative functions. In order to utilize this just run `future::plan
with your selected method.
For example to use muiltiprocess.
library(fundManageR) library(future) plan(multiprocess) fred_symbols(symbols = c("DGS10", "DGS2", "DGS30"))
adv_period_urls
– Retrieves all possible ADV summary periods.adv_managers_current_period_summary
– Retrieves summary data for ADV filing managers from the most recent monthly filing period.adv_managers_periods_summaries
– Retrieves summary ADV filings for specified periods and filing type. By default the files will be saved to and loaded from a temporary directory however a user can override this default by specifying a file directory. If you specify a file directory you can also specify folder name, if you don’t do this the folder adv_data
is created by default. You can also tell the function to delete the folders and empty the trash by setting remove_files
and empty_trash
to TRUE.sec_adv_manager_sitemap
– Retrieves a data frame with the possible detailed ADV sections and their descriptions.adv_managers_metadata
– Retrieves metadata for specified search name or CRD ID; fastest way to search for managers you may wish to explore further.adv_managers_filings
– Retrieves detailed ADV filing for specified Central Registration Depository ID adv_managers_brochures
– Retrieves and OCRs for SEC mandated annual Uniform Requirements for the Investment Adviser Brochure and Brochure Supplements for specified CRDs and/or company names.visualize_
Functionsvisualize_tibble
– This function allows the user to visualize a data frame object to better understand the structure and contents of a data frame. The function utlizes the fantastic listviewer package which wraps Jos de Jong’s JSON Editor projectlibrary(fundManageR) recent_period_summary <- adv_managers_current_period_summary(file_directory = NULL)
test_manager <- fundManageR::adv_managers_filings( search_names = 'EJF Capital', crd_ids = 156663, all_sections = T, assign_to_environment = T )
ycombinator_alumni <- fundManageR::ycombinator_alumni() ycombinator_alumni %>% visualize_tibble(edit = F) ## visualize it
library(dplyr) dates <- c("2015-10-09", "2016-09-26") %>% lubridate::ymd() land_purchase_price <- -1000000 %>% formattable::currency() land_sale_price <- 1300000 %>% formattable::currency() cash_flows <- c(land_purchase_price, land_sale_price) fundManageR::calculate_irr_periods(dates = dates, cash_flows = cash_flows, return_wide = T)


There were doors all round th∫`e hall, but they were all locked
Alice had been all the way down one side and up the other, trying every door, she walked sadly down the middle, wondering how she was ever to get out again
There were doors all round th∫`e hall, but they were all locked
Alice had been all the way down one side and up the other, trying every door, she walked sadly down the middle, wondering how she was ever to get out again


And if these weird noises are supposed to be Romantic music, then I’d say they’re a little off.


Quick Release Clamp
My favorite project at Instron was designing this Quick-Release Clamp meant to secure 2 k-cup shaped specimen to a peel fixture. It was a great opportunity explore different materials and finishes while considering price point, usability, and manufacturability.
Challenges + Action
- High Volume Testing - I modeled the base part after a bike collar, and added a cam lever to reduce setup in between tests.
- Multiple Specimen Sizes - Shaped the cavity of collar to allow the less rigid of the samples to sit comfortably, but force the more rigid sample to bite into the rubber lining of the collar.
- Mounting to Fixture - I opted to mount the lever by its side rather than in the middle to make it easier to close.
Skills/Tools Developed
- Solidworks FEA Tool - Though I'd used the tool extensively throughout my co-op to determine if parts/systems were safe or in danger of breaking, this was my first time using it to get displacement information.


About
This is a web interface to query the Universal Natural Products Database (UNPD) originally obtained from http://pkuxxj.pku.edu.cn/UNPD. As the original resource was no longer available, we figured it would be useful to host the data online again. We obtained the data from Pierre Marie Allard's (http://oolonek.github.io/ISDB/).
The UNPD structures are freely available and the source code of this webserver are open source under the BSD license. Use it as you please!


| Interface | Description |
|---|---|
| Command |
A basic interface for executable bot commands.
|
| DiskParser | Deprecated |
| Parser |
| Class | Description |
|---|---|
| BotScheduler |
A class for bot shift management.
|
| BotScheduler.DaySchedule |
A wrapper class for an array of shifts for a single day.
|
| BotScheduler.MonthSchedule |
A wrapper class for a HashMap mapping Day of the Week IDs (int) to DaySchedule type
map wrappers, which contain shift information for a given day of the week in that month.
|
| BotScheduler.PermanentPositionMap |
A wrapper class for a String to Integer HashMap used for mapping command strings to
constant bot indices.
|
| BotScheduler.Position |
A class containing information for a position - a set of command strings which a bot
assigned to the position is responsible for as well as a unique index.
|
| BotScheduler.Shift |
A class containing information for a single shift.
|
| CommandAdapter |
An abstract class implementing the less commonly used Command methods as either
empty methods or general methods.
|
| CommandQueue |
A deque wrapper for bot commands.
|
| GreetingQueue |
A deque wrapper for objects containing information about user joining guild events (ie.
|
| MessageListener |
A simple listener that can be registered to a JDABuilder for a bot to screen all
messages sent to a channel for potential commands and send them to the ParseCore.
|
| MessageQueue |
A deque wrapper for objects containing information about message events (ie.
|
| ParseCore | |
| Response | |
| ResponseCard | |
| ResponseQueue | |
| SchedulerConstructionTest | |
| TransientBlacklist |


UPDATE: Statue presumed stolen from Armstrong cemetery to be returned
by Parker CrookA North Okanagan teen eagerly awaiting the return of a missing angel will have it returned before celebrating her 17th birthday.
Mother Robin Lessard said her daughter Corrina was distraught after the angel, painted by one of her aunts and placed upon her grandfather’s grave 10 years ago, went missing from the Armstrong Spallumcheen Cemetery.
“We just want the angel back as it has a lot of sentimental value to the family,” said Lessard. “They were very close. Her grandpa was her rock up until the day he died. He was the only person who could calm her down immediately when she was little and she is very distraught that someone has taken it.”
Lessard said the ceramic angel is about two-feet-tall and is hand-painted with a blue body and wings. The angel’s hands are together to hold a candle. Up until its disappearance, it rested upon the headstone of James Sweet.
Originally presumed stolen, Armstrong Cemetery caretaker Mike Hodge said the item was removed for safe-keeping.
"That one was removed because we didn't want it to get damaged," Hodge said.
Lessard said her daughter can't wait for the angel to be returned.
“It’s my daughter’s 17th birthday on the 30th, so it was very upsetting that her grandpa’s angel (went missing) right before her birthday, as it had been there for ten years,” Lessard said. “It means everything to her.”
Hodge said the cemetery has been in contact with the family and has arranged pick up of the angel.
-This story was updated at 6:20 p.m. to include information from the Armstrong Cemetery.


WITNESS LIST Corrections Committee April 13, 1999-2:00P HB 1315 For: Reeves, Linda (Texas Inmate Families Assoc. (TIFA)) Woodford, Suzy (Self and Common Cause Texas) Against: Hubbarth, William "Rusty" (Self and Justice For All) On: Rodriguez, Victor (Tx Board of Pardons and Paroles) HB 3250 For: Reeves, Linda (Texas Inmate Families Assoc. (TIFA)) On: Briscoe, Judy (Texas Youth Commission) HB 3362 For: Clements, Dianne (Self and Justice For All) Cotellesse, Suzan J. (Self and Justice For All) Hubbarth, William R. (Self and Justice For All) Kahan, Andy (Self and Harris County Victim Advisory Council) LeMay, Karen Y. (Self and Justice For All) Semander, Harriett (Self and Justice For All) Windlinger, Kelly (Justice For All) Against: Reeves, Linda ((Texas Inmate Families Assoc. (TIFA)) On: Rodriguez, Victor (Tx Board of Pardons and Paroles) Overview of Special Needs Parole On: Fabelo, Ph.D, Tony (Criminal Justice Policy Council) Kifowit, Dee (Tx Council on Offenders with Mental Impairments)


FILM TITLE: ANTONIA'S LINE DIRECTOR: MARLEEN GORRIS COUNTRY: THE NEDERLANDS 1995 CINEMATOGRAPHY: WILLY STASSEN MUSIC: ILONA SEKACZ CAST: Willeke van Ammelrooy, Els Dottermans, Jan Decleir, Marina de Graaf, Mil Seghers SUPER FEATURES: Great story. Excellent moments. Funny.
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
It is films like this that redefine what films are made for. And it typifies the attitude that is the European community, versus the American style of action pictures that are vacuous. They may have a lot of clever things in it, but they have little substance.
ANTONIA'S LINE may not have much action, the film is very slow, but it does have charm, character, passion, and beauty, and on top of it, a magnificent story, and outline. Antonia has moved back into town, because her mother is on her final days. She has come into town without a husband, and with a daughter of marrying age. They both immediately become the talk of the town and the immediate attention of all the members that want to mix with the two women. But, unlucky for them, both women are independent and do not spend much time at the usual lifestyle of mating and making children, which seems all that the whole community has to live for.
The town is an incredible hodgepodge of characters, that are totaly out there, which makes the film even more enjoyable. And how they all blend in is rather funny. Antonia's daughter, one day decides that she wants a child, but does not want a husband. They end up in the city, where her daughter visits a brothel and gets together with a man who is one of the owner's favorite lovers, and probable father of at least one of her children. Of course, the daughter gets pregnant and this starts the film on chapter two. We find that the daughter is gay, and she now lives with her friend. And other matches are made in the village, including one young man who is a bit slow. And eventually, Antonia also gets in the mood, and takes on a lover, a man about her age, who has a miriad of sons, and no wife to help him raise his children. She has not allowed anything to come to pass between her and him, for years. And when it finally happens, the film is all aglow. Everyone is happy, and everyone has a lover/wife/husband and the there are no worries anywhere.
And then the film turns. Antonia's grandchild grows to be a young woman that is head and shoulders above most of anyone, and has a tutor, who is the town's lonely man, always buried in his books and studies. In school the young lady even embarrasses a teacher because he is not capable and intelligent enough to see what is happening. The whole class ends up leaving the room, after the girl's lead.
But this girl, one day meets a rather somber moment in life.  And this is dealt with in a very harsh manner, but considering what he did, it may be thought of as some sort of justice.
The film progresses, and ends on a somber note. The town's tutor, is a sad, disappointed man, who apparently had fallen in love with Antonia, but she did not respond. He has his only smile in the whole film in the beginning when she returns to the village. This kinda brings the film to an end. Antonia's grandgranddaughter, is the one telling us the story, and we finally notice why the characters are so strange. They are basically seen through a child's eyes, and the punishments, and the events all come and go with the same horrific flavor that this film brings forth. It seems that the events are all very important, and they all have serious consequences as to the chain of events.
But none, take away from the enjoyment of this film.  By the style of directing and story telling, the film is not about anything in particular. It covers three generations, and it displays problems that each of these generations has had with its own growth and time. But these problems never stop the growth of it all. and as the film says in the end, nothing "has come to an end".... except this fine film, with so many excellent moments.
Of special interest and fun here, are the priest and his turn around. He is probably set up, because he is a dirty old fart anyway, but it is all for the best. And who he ends up with is a treat. One could say that there are meanings here and there, but all in all, these are understated as a part of the whole picture, which is the whole film. Yes, we can say that there are pointed moments, and statements, but when one does that, this film loses some of its really precious moments. Like Antonia's daughter and grand daughter always seeing things happening... in the oddest of moments... and these bits are so enjoyable that it is hard to fault a film for anything else.
Well thought out, beautifully written, and worth seeing.
4 GIBLOONS out of 5
Reviewed by Pedro Sena. Copyright (c) Pedro Sena 1997. All Rights Reserved.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Traits to statically extract information of a (mathematical) vector. More...
#include <dune/xt/common/float_cmp_internal.hh>
Public Types | |
| typedef VecType | VectorType |
| typedef VecType | ScalarType |
| typedef VecType | RealType |
| typedef Dune::FieldTraits < VecType >::field_type | S |
| typedef Dune::FieldTraits < VecType >::real_type | R |
Static Public Member Functions | |
| static void | create (const size_t) |
| static void | create (const size_t, const ScalarType &) |
Static Public Attributes | |
| static constexpr bool | is_vector = false |
| static constexpr bool | has_static_size = false |
| static constexpr size_t | static_size = std::numeric_limits<size_t>::max() |
Traits to statically extract information of a (mathematical) vector.
If you want your vector class to benefit from the operators defined in this header you have to manually specify a specialization of this class in your code with is_vector defined to true and the appropriate static methods and members (see the specializations below).
| typedef Dune::FieldTraits<VecType>::real_type Dune::XT::Common::VectorAbstraction< VecType >::R |
| typedef VecType Dune::XT::Common::VectorAbstraction< VecType >::RealType |
| typedef Dune::FieldTraits<VecType>::field_type Dune::XT::Common::VectorAbstraction< VecType >::S |
| typedef VecType Dune::XT::Common::VectorAbstraction< VecType >::ScalarType |
| typedef VecType Dune::XT::Common::VectorAbstraction< VecType >::VectorType |
|
inlinestatic |
Referenced by Dune::XT::Common::create(), and Dune::XT::Common::internal::from_string().
|
inlinestatic |
|
static |
|
static |
|
static |


To raise awareness of humanitarian crises around the world, we will partner with various NGOs to create education toy sets, allowing kids to engage in creative play and learn about various natural disasters and humanitarian issues from an early age.
Each toy will be developed to promote educational play and awareness from an early age among children, but also among the parents.
Moreover, certain part of profits from the toys will be donated to the projects that seek funding.
Since the earthquake in 2015, 5000.000 homes need to be reconstructed in Nepal. Build up Nepal is rebuilding houses in over 100 communities using CSEB technology. They combine innovative construction technologies, local materials and entrepreneurship to rebuild safe, affordable houses.
However, they lack constant funds flow and awareness of the community & partners to have a sustainable development


{{ country }}
{{ latest.confirmed }}
Confirmed Cases
{{ latest.deaths }}
Deaths
{{ latest.recovered }}
Recovered
Date
Confirmed
Deaths
Recovered
{{ name }}
{{ cols }}


{% extends 'Sacher/base.html' %} {% block content %}
Your password has been set. You may go ahead and sign in now.


{{ partial "head.html" . }}
{{ partial "nav.html" . }}
{{ partial "footer.html" . }}
{{ partial "scripts.html" . }}


Welcome to my website article write up. I have chosen two good websites and one bad website. please enjoy!


| 1037 | (A) | and Titus seges the town there tene es on honde |
| 1041 | (C) | Thanne tytus besegedde þe town . & þer sorowe was on hande |
| 1024 | (D) | And Tytus segis þan þe toune þer tene is in honde |
| 1004 | (E) | & tytus seegeth þe town . where wo begynnetħ |
| (Ex) | ---- no text ---- | |
| 1062 | (L) | Now tytus segyþ þe toun þer tene is on hande |
| 977 | (P) | ? ????? ????? ?? ???? þaire tene es on hande |
| 1015 | (U) | And Titus seges the toun / tene is in honde |
| 102 | (V) | Titus seges þe town . her tene is on honde |


Cool button
Leoni's webpage
Welcome to my wepbage!
Who is Leoni?
I am a 21 year old aspiring programmer. Web design is my passion.


You finished level 0 with 0 explosions and earned 0 points. Your longest chain reaction was 0 explosions. Your total score is now: .


A Cheat Sheet for JavaScript Objects
Objects in JavaScript are composed of attributes. If an attribute contains a function, it is considered to be a method of the object, otherwise the attribute is considered a property.
Object Properties
Object properties can be any of the three primitive data types, or any of the abstract data types, such as another object. Object properties are usually variables that are used internally in the object's methods, but can also be globally visible variables that are used throughout the page.
The syntax for adding a property to an object is −
objectName.objectProperty = propertyValue;
For example − The following code gets the document title using the "title" property of the document object.
var str = document.title;
Object Methods
Methods are the functions that let the object do something or let something be done to it. There is a small difference between a function and a method – at a function is a standalone unit of statements and a method is attached to an object and can be referenced by the this keyword.
Methods are useful for everything from displaying the contents of the object to the screen to performing complex mathematical operations on a group of local properties and parameters.
For example − Following is a simple example to show how to use the write() method of document object to write any content on the document.
document.write("This is test");
User-Define Objects
All user-defined objects and built-in objects are descendants of an object called Object.
The new Operator
The new operator is used to create an instance of an object. To create an object, the new operator is followed by the constructor method. In the following example, the constructor methods are Object(), Array(), and Date(). These constructors are built-in JavaScript functions.
var employee = new Object();
var books = new Array("C++", "Perl", "Java");
var day = new Date("August 15, 1947");
The Object() Constructor
A constructor is a function that creates and initializes an object. JavaScript provides a special constructor function called Object() to build the object. The return value of the Object() constructor is assigned to a variable. The variable contains a reference to the new object. The properties assigned to the object are not variables and are not defined with the var keyword.


Sir Bailey HiBird
His
favorite
hobbies include:
Sleeping anywhere and everywhere
Swimming
in any
body of water
Hiking and taking long walks
Chasing squirrels and bunnies
Selfie
View Bailey's family tree:
HiBird Kennels
.
© A. Larson, 2018


{% extends "base.html" %} {% block title %}
Medieval catalogues > UNIVERSITY AND COLLEGE LIBRARIES OF CAMBRIDGE > Donor documents > Will of Robert Fitzhugh, 15 June 1434; University
{% endif %}2 identified entries found.
All data was derived from the List of Identifications by Professor Richard Sharpe.
{% if not printing %}
A key to codes used in the List is available (opens in new tab).{% endif %}


To get access to all our exclusive access to all our deals (not showcased here), please request invite
Get notified on new hot deals


Members
(constant) databaseRules
Rules for updateDatabaseIssues to check against the database
(constant) objectQuestions
Templates to use for dynamic prompt generation
(constant) prompt
Encapsulates inquirer prompt
Methods
app()
Runs the mainmenu method to init the program
(async) filterMenu(arg_table)
Prompts the user with visible available columns as set by columnsMenu, where "Revert" will clear the filter. Then upon selection of a column, the user is prompted for an operation and a value to be
passed to viewInformationMenu to assemble into the query.
Parameters:
| Name | Type | Description |
|---|---|---|
arg_table |
String | Name of a table from the database in the format `tableName`_table |
(async) mainMenu()
Prompts the user with the options "View Information", "Update Information", "Validate Database", "Exit". The method awaits on calls to the menu functions viewInformationMenu, updateMenu, and updateDatabaseIssues; it will loops until the user selects exit.
(async) updateDataIds()
Replace id references in the data and supplied fields with their database values
(async) viewInformationMenu()
Presents users with options to view Department, Employee, or Role tables. After selecting an option, the user can use "Select a different table" to reach this prompt again. After the user's selection, this method displays the data using tableRenderer, prompting the user to alter the view using the menu functions filterMenu, searchMenu, sortMenu, and columnsMenu.
Function loops through alter view prompts until the user selects "Select a Different table", and then offers the view table prompt until it returns to mainMenu upon selection of the option "Return to Main Menu".


Welcome to newbody! The project owned by Urban Aleksey
This Privacy Policy regulates the relationship between Urban Aleksey, the owner of the website appnewbody.com and newbody mobile App and individuals using newbody mobile App. newbody strives to protect and respect your privacy. newbody takes your privacy seriously and will only use your Personal information to provide Services after you have given your consent to the collection and processing of your Personal Data under the terms set out below.
This Privacy Policy explains when, where, how, and why newbody collects Personal information about you, how it uses this information, the conditions under which newbody may disclose it to others, your rights with your Personal information and how newbody keeps it secure.
This Privacy Policy is an integral part of newbody User Agreement. These Terms of Use (the «Terms») and the Privacy Policy apply to all visitors, users and others who access the Services. Your continued use of any part of newbody after the publication of the updated Privacy Policy will constitute your full ACCEPTANCE of any changes.
newbody reserves the right to change this Privacy Policy. This may happen from time to time. If newbody makes any significant changes, newbody will notify you by email (if you provide an email address), through the website, through the App or by submitting a new version of this Privacy Policy to you so that you accept it if newbody, for example, adds new processing actions or collects some additional Personal Data from you. All Personal Data collected by newbody will be processed according to the Privacy Policy in effect at the time of collection of this information. If the Privacy Policy changes significantly during this time, newbody will not use your Personal Data without your permission in a manner inconsistent with the Privacy Policy in effect at the time your information was collected.
newbody collects the following Personal Data about you:
- General Personal Data
- Contact information such as name, user ID, email address, mobile phone number.
- Information about preferences that you provide, such as product or content interests, communication or marketing preferences.
- Usage information about how you interact with newbody, such as your purchase history, content you viewed and areas of newbody you visited.
- Device and usage information, which may include data related to your mobile device (for example, ID, brand, model, type, operating system, advertising ID and similar information); information about your use of features or notifications on the device; signal level related to Wi-Fi or Bluetooth, temperature, battery level, and similar technical data; mobile operator.
- Demographic information such as age and gender.
- Your IP address and cookies when you visit the website.
- Photos that you provide when using the App, using your camera or camera roll (if you have given newbody permission to access your camera or camera roll). newbody only gets those specific images that you choose to change using the App; newbody does not collect your photo albums, even if you grant access to them. newbody encrypts every photo you upload using the App. The encryption key is stored locally on your device. This means that the only device that can view the photo is the device from which the photo was uploaded using the app – the user's device. Note that while newbody does not require or request any metadata attached to the photos you upload, metadata (including, for example, geotags) can be associated with your photos by default. newbody takes steps to remove any metadata that may be associated with the photo you provided while using the App.
Personal information about your physical condition and well-being
Information about your fitness or well-being, such as your weight, height, and other details
- Analysis, operation, maintenance and improvement the App and marketing activities, and addendum new features and services to the App.
- Evaluation your needs to identify suitable products or services.
- Sending product updates or warranty information.
- Respond to your comments, questions, and requests and provide customer service.
- Sending you push notifications, both internal and external.
- Sending you marketing messages through various channels such as email, push messages, pop-ups, etc.
- Improvement our App and marketing efforts.
- Conducting research and analysis, including for scientific and academic research purposes.
- For any other purposes disclosed to you at the time of newbody's collection of Personal Data, or for any other purposes specified in this Privacy Policy. If newbody decides to change the processing purposes set out above, newbody will notify you of such changes before using your personal information for the new purposes and request your separate consent.
You are responsible for ensuring the accuracy of your Personal Data that you submit to newbody. Inaccurate information will affect your experience using newbody's Services, as well as newbody's ability to contact you. If you think that your Personal Data is inaccurate, you have the right to contact newbody and ask newbody to correct such Personal Data by contacting<EMAIL_ADDRESS>newbody gives you the ability to access and update Personal Data in the App and your account settings.
If you think that your Personal Data is no longer necessary in connection with the purposes for which it was collected or otherwise processed, or in cases where you have withdrawn your consent or object to the processing of your Personal Data, or in cases where the processing of your Personal Data otherwise does not comply with applicable law, you have the right to contact newbody and ask newbody to delete such Personal Data.
In some cases, you may object to the processing of your Personal Data. Please be aware that the deletion of certain Personal Data inserted by you may affect your ability to use the Services.


--- layout: post permalink: celebritysilver.html Tags: Array NameOfCoupon: Celebrity Silver Cash Back Summary: See our Celebrity Silver Coupon Code, Celebrity Silver Rebate, Celebrity Silver Promo Code, Celebrity Silver Discount, Celebrity Silver Coupon Cash Back Rebate here. MetaKeywords: Celebrity Silver Coupon Code, Celebrity Silver Rebate, Celebrity Silver Promo Code, Celebrity Silver Cash Back Rebate, Celebrity Silver Discount, Celebrity Silver Coupon Image: images/19691.jpg LinkURL: http://www.shareasale.com/r.cfm?b=148374&u=412002&m=19691 affiliate_url_link: http://www.icouponblog.com/jane.php?id=1467 thesis_readmore: See the Celebrity Silver Coupon thesis_thumb: http://www.icouponblog.com/tn.php?merchantURL=celebritysilver.com Title: Save 6% - Celebrity Silver Coupon Code for celebritysilver.com. Celebrity Silver Rebate & Discount thesis_description: Our Celebrity Silver Discount Coupon Code for celebritysilver.com. We have the best Celebrity Silver Rebate anywhere. thesis_keywords: Celebrity Silver, Celebrity Silver Coupon Code, Celebrity Silver Discount, Celebrity Silver Rebate product_name: Celebrity Silver hop_url: http://www.icouponblog.com/hop.php?id=1467 ---
Stand out, look stunning, get the designs and styles of celebrities without the hassle of being one. Celebrity Silver is the place to visit for beautiful, unique, sterling silver jewelry. Celebrity Silver is a celebrity inspired one of its kinds, top internet store for costume jewelry at affordable prices. Buy the top quality sterling silver jewelry and cubic Zirconium at an amazing price. Use our discount coupon for the best prices on Celebrity Silver.
Celebrity Silver has the hottest styles of jewelry available . If you are looking for red carpet fashion jewelry, celebrity or custom jewelry Celebrity Silver is the best place for the most elegant, stylish and unique pendants, necklaces, bracelets etc. Check out Celebrity Silver and get the best product in the best price range. You can get wedding jewelry, bridal jewelry designer and celebrity inspired. Use our cash back rebate coupons to strike the best deal on Celebrity Silver.
Celebrity Silver has the best designs and styles in the most affordable price range. If you are still looking to buy that beautiful silver ring for that special someone in your life, look no further. Check out online Celebrity Silver its user friendly website will help you navigate and find the products according to you taste and need. You can select from new arrivals, best sellers to top rated jewelry. Check it out. Buy what your heart desires at a great price. Don’t forget to use our cash back rebate coupons for the best deals on Celebrity Silver.


Sun is setting in the backyard. We have created a sacred protection circle on our stripey rug, chris' san pedro cactus form the points of a pentegram and i offer a glass bowl full of clear crystals and water to appease the water aspect of the dmt spirit. Some burning of amber and a circle of salt also purify the space and i meditate for a few moments on a protective bubble surrounding our space supported by heavenly and earthly energies.
Chris arrives with the pipe and dmt and i sit before him as he inhales the smoke. I am closely watching the expressions that pass over his face which range from wonder and awe to ecstacy and bliss. I notice an interference vibration in his energy field, moving rapidly and surrounding him. He is laughing and swaying in rythmic spirals. I try not to distract him from his trip too much and just offer him energetic support and i think to myself 'this is right, the time is right'. Chris 'returns' and tells me of how beautiful it is. I don't ask too many questions because i am quite eager to find out for myself.
I place myself in the middle of the sacred circle as chris fetches my dose, about 25-40mg He offers to light it for me so i take the pipe in my lips and wait for it to heat before i enhale. I enhale as deep as I can and hold it before releasing. Again I enhale and am surprised that I don't find the smoke overly unpleasant, it is the smell from the smoke coming from the end of the pipe that I notice more than any taste or burning sensation.
I again enhale as deeply as i can and as i pull away from the pipe notice my hands are starting to look rather strange, like the light and dark are patchy.   As my hands remove my glasses then caress my closed eyes and fall to my cross legged lap i am now a kaledioscopic mandala buddah for in warm reds and browns.
I exhale and go 'oooohh' and all sound takes on the rythym of a beautifully composed song. I open my eyes and look around to see a world quite different to any i've ever seen before. Around me is a dimension where everything seems to be weaved into a beautiful psycheadelic environment that at first seem to be big blocks of solid colour but on closer inspection are intricately patterned with infomation.
I lie on my back and become aware of what was once my backyard now appearing to me as these huge planes of living tapestry. I marvel at the beauty of it, repeating my enthralled 'oooohhh's as i exhale. I am enraptured and i like this place, i sit up rapidly to look around more and see the trees and chris lying in the grass. Then i think 'that's not chris- this is another dimension' and as i look at him he smiles and all his teeth are different, flourescent colours and each dreadlock looks as if it's made of many colourful beads.
 His skin is also made up of many segments of colours that flash into other colours, so many beautiful, festive colours, like a pinata at a spanish fiesta. I become aware of the presence of a female, the one who lives in the temple behind chris, she seems to be like cleopatra.
I realise I am this feminine presence and i lie back on the pillow behind me and roll over and as i do this it too changes colours like it is being flipped through the spectrum. It occurs to me at this point that i am actually a person who has taken a drug and is now experiencing this induced reality. I notice the grass the rug is on and it seems like it is made up of many little propped up planes, like props for a theater production, bright green and plastic looking. The giant heleconia plant over me also looks like it is cut out of plastic or cardboard but it all seems very alive, like that is what it's nature is. The cubby house looks like a beach house that is constantly changing colours and I feel like i am on a tropical island. Then i notice the cluster palms beside the house and they emit such a warm, pink, glowing light. I tell chris to look at how beautiful it is.
Now that I am aware that i'm actually on a drug I begin to look around at things and figure out what they actually all are. So even though i am begining to become aware again of things in 'normal' reality, i see them as all beautifully connected by webs of energy and surrounded by crystalline structures of glowing light.
 Chris attracts my attention again, and although residual colours still streak his face he is no longer so solidly made out of hallucinations and i welcome him into the circle and we embrace and i feel so lucky to be sharing this with him, realising he was expriening this state of consiousness while i was still in totally straight in front of him, with no idea of what was going on. Behing him i see dried leaves floating on the surface of the grass forming an exqisite, organic net that leads to a form that sits under a big glossy green plant.
I adjust my eyes to try and see what it is and realise it is an entity. I ask Chris if he can see it, which he cannot, and i decide not to try to find my glasses to see it clearly. I accept it's presence and it's form turns into a coiled, golden serpent, sitting patiently under this plant. As I realise this form i see it moving it's tail languidly, it watches me knowingly and although not threatened by it, i sense it's power. 'it's chicchan' i tell chris, who shares this sign of the mayan calendar with me as his galactic signature.
We talk and share our experiences as the sun continues to set and i reach a state closer to base line. All up, i was out for only about 5-7 minutes, but a sense of wonder and appreciative euphoria stayed with me untill i went to bed. Truly a profound and beautiful experience, unlike anything i could have imagined or expected.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


This is where you select a burger
This is where you provide necessary information
Full name
Email
Payment method Swish Klarna Credit card
Gender Male Female Do not wish to provide
Burgers: {{burgers}}
Name: {{name}}
Email: {{email}}
Deliver to: {{details.x}} x / {{details.y}} y
payment method: {{paymentMethod}}
Gender: {{gender}}


org.apache.commons.io.output
Classes
ByteArrayOutputStream
CountingOutputStream
DeferredFileOutputStream
DemuxOutputStream
LockableFileWriter
NullOutputStream
NullWriter
ProxyOutputStream
ProxyWriter
TeeOutputStream
ThresholdingOutputStream


arcgis.raster.analytics module¶
Functions for calling the Raster Analysis Tools. The RasterAnalysisTools service is used by ArcGIS Server to provide distributed raster analysis.
get_datastores¶
-
arcgis.raster.analytics.
get_datastores
(gis=None)¶ Returns a helper object to manage raster analytics datastores in the GIS. If a gis isn’t specified, returns datastore manager of arcgis.env.active_gis
is_supported¶
-
arcgis.raster.analytics.
is_supported
(gis=None)¶ Returns True if the GIS supports raster analytics. If a gis isn’t specified, checks if arcgis.env.active_gis supports raster analytics
generate_raster¶
-
arcgis.raster.analytics.
generate_raster
(raster_function, function_arguments=None, output_raster_properties=None, output_name=None, *, gis=None, **kwargs)¶ raster_function : Required, see http://resources.arcgis.com/en/help/rest/apiref/israsterfunctions.html
function_arguments : Optional, for specifying input Raster alone, portal Item can be passed
output_raster_properties : Optional
- output_name : Optional. If not provided, an Image Service is created by the method and used as the output raster.
You can pass in an existing Image Service Item from your GIS to use that instead.
Alternatively, you can pass in the name of the output Image Service that should be created by this method to be used as the output for the tool.
A RuntimeError is raised if a service by that name already exists
gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.
output_raster : Image layer item
interpolate_points¶
-
arcgis.raster.analytics.
interpolate_points
(input_point_features, interpolate_field, optimize_for='BALANCE', transform_data=False, size_of_local_models=None, number_of_neighbors=None, output_cell_size=None, output_prediction_error=False, output_name=None, *, gis=None, **kwargs)¶ This tool allows you to predict values at new locations based on measurements from a collection of points. The tool takes point data with values at each point and returns a raster of predicted values:
- An air quality management district has sensors that measure pollution levels. Interpolate Points can be used to
- predict pollution levels at locations that don’t have sensors, such as locations with at-risk populations- schools or hospitals, for example.
- Predict heavy metal concentrations in crops based on samples taken from individual plants.
- Predict soil nutrient levels (nitrogen, phosphorus, potassium, and so on) and other indicators (such as electrical
- conductivity) in order to study their relationships to crop yield and prescribe precise amounts of fertilizer for each location in the field.
- Meteorological applications include prediction of temperatures, rainfall, and associated variables (such as acid
- rain).
- input_point_features : Required point layer containing locations with known values
- The point layer that contains the points where the values have been measured.
- interpolate_field : Required string - field to interpolate
- Choose the field whose values you wish to interpolate. The field must be numeric.
- optimize_for : Optional string - Choose your preference for speed versus accuracy.
- More accurate predictions take longer to calculate. This parameter alters the default values of several other parameters of Interpolate Points in order to optimize speed of calculation, accuracy of results, or a balance of the two. By default, the tool will optimize for balance. One of the following: [‘SPEED’, ‘BALANCE’, ‘ACCURACY’]
- transform_data : Optional bool - Choose whether to transform your data to the normal distribution.
- Interpolation is most accurate for data that follows a normal (bell-shaped) distribution. If your data does not appear to be normally distributed, you should perform a transformation.
- size_of_local_models : Optional int - Size of local models
- Interpolate Points works by building local interpolation models that are mixed together to create the final prediction map. This parameter controls how many points will be contained in each local model. Smaller values will make results more local and can reveal small-scale effects, but it may introduce some instability in the calculations. Larger values will be more stable, but some local effects may be missed. The value can range from 30 to 500, but typical values are between 50 and 200.
- number_of_neighbors : Optional int - Number of Neighbors
- Predictions are calculated based on neighboring points. This parameter controls how many points will be used in the calculation. Using a larger number of neighbors will generally produce more accurate results, but the results take longer to calculate. This value can range from 1 to 64, but typical values are between 5 and 15.
- output_cell_size : Optional LinearUnit - Output cell size
- Enter the cell size and unit for the output rasters. The available units are Feet, Miles, Meters, and Kilometers.
- output_prediction_error : Optional bool - Output prediction error
- Choose whether you want to create a raster of standard errors for the predicted values. Standard errors are useful because they provide information about the reliability of the predicted values. A simple rule of thumb is that the true value will fall within two standard errors of the predicted value 95 percent of the time. For example, suppose a new location gets a predicted value of 50 with a standard error of 5. This means that this tool’s best guess is that the true value at that location is 50, but it reasonably could be as low as 40 or as high as 60. To calculate this range of reasonable values, multiply the standard error by 2, add this value to the predicted value to get the upper end of the range, and subtract it from the predicted value to get the lower end of the range.
- output_name : Optional. If not provided, an Image Service is created by the method and used as the output raster.
- You can pass in an existing Image Service Item from your GIS to use that instead. Alternatively, you can pass in the name of the output Image Service that should be created by this method to be used as the output for the tool. A RuntimeError is raised if a service by that name already exists
gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.
named tuple with name values being :
- output_raster (the output_raster item description is updated with the process_info),
- process_info (if run in a non-Jupyter environment, use process_info.data to get the HTML data) and
- output_error_raster (if output_prediction_error is set to True).
create_viewshed¶
-
analytics.
create_viewshed
(input_elevation_surface, input_observer_features, optimize_for=None, maximum_viewing_distance=None, maximum_viewing_distance_field=None, minimum_viewing_distance=None, minimum_viewing_distance_field=None, viewing_distance_is_3d=None, observers_elevation=None, observers_elevation_field=None, observers_height=None, observers_height_field=None, target_height=None, target_height_field=None, above_ground_level_output_name=None, output_name=None, *, gis=None, **kwargs)¶ Compute visibility for an input elevation raster using geodesic method.
input_elevation_surface : Required string
input_observer_features : Required FeatureSet
- optimize_for : Optional string
- One of the following: [‘SPEED’, ‘ACCURACY’]
maximum_viewing_distance : Optional LinearUnit
maximum_viewing_distance_field : Optional string
minimum_viewing_distance : Optional LinearUnit
minimum_viewing_distance_field : Optional string
viewing_distance_is_3d : Optional bool
observers_elevation : Optional LinearUnit
observers_elevation_field : Optional string
observers_height : Optional LinearUnit
observers_height_field : Optional string
target_height : Optional LinearUnit
target_height_field : Optional string
above_ground_level_output_name : Optional string
- output_name : Optional. If not provided, an Image Service is created by the method and used as the output raster.
- You can pass in an existing Image Service Item from your GIS to use that instead. Alternatively, you can pass in the name of the output Image Service that should be created by this method to be used as the output for the tool. A RuntimeError is raised if a service by that name already exists
gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.
- dict with the following keys:
- “output_raster” : layer “output_above_ground_level_raster” : layer
summarize_raster_within¶
-
analytics.
summarize_raster_within
(input_zone_layer, input_raster_layer_to_summarize, zone_field='Value', statistic_type='Mean', ignore_missing_values=True, output_name=None, *, gis=None, **kwargs)¶ - input_zone_layer : Required layer - area layer to summarize a raster layer within defined boundaries.
- The layer that defines the boundaries of the areas, or zones, that will be summarized. The layer can be a raster or feature data. For rasters, the zones are defined by all locations in the input that have the same cell value. The areas do not have to be contiguous.
- input_raster_layer_to_summarize : Required - raster layer to summarize.
- The raster cells in this layer will be summarized by the areas (zones) that they fall within.
- zone_field : Required string - field to define the boundaries. This is the attribute of the layer that will be used
- to define the boundaries of the areas. For example, suppose the first input layer defines the management unit boundaries, with attributes that define the region, the district, and the parcel ID of each unit. You also have a raster layer defining a biodiversity index for each location. With the field you select, you can decide to calculate the average biodiversity at local, district, or regional levels.
- statistic_type : Optional string - statistic to calculate.
- You can calculate statistics of any numerical attribute of the points, lines, or areas within the input area layer. The available statistics types when the selected field is integer are Mean, Maximum, Median, Minimum, Minority, Range, Standard deviation(STD), Sum, and Variety. If the field is floating point, the options are Mean, Maximum, Minimum, Range, Standard deviation, and Sum. One of the following: [‘Mean’, ‘Majority’, ‘Maximum’, ‘Median’, ‘Minimum’, ‘Minority’, ‘Range’, ‘STD’, ‘SUM’, ‘Variety’]
- ignore_missing_values : Optional bool.
- If you choose to ignore missing values, only the cells that have a value in the layer to be summarized will be used in determining the output value for that area. Otherwise, if there are missing values anywhere in an area, it is deemed that there is insufficient information to perform statistical calculations for all the cells in that zone, and that area will receive a null (NoData) value in the output.
- output_name : Optional. If not provided, an Image Service is created by the method and used as the output raster.
- You can pass in an existing Image Service Item from your GIS to use that instead. Alternatively, you can pass in the name of the output Image Service that should be created by this method to be used as the output for the tool. A RuntimeError is raised if a service by that name already exists
gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.
output_raster : Image layer item
calculate_density¶
-
analytics.
calculate_density
(input_point_or_line_features, count_field=None, search_distance=None, output_area_units=None, output_cell_size=None, output_name=None, *, gis=None, **kwargs)¶ Density analysis takes known quantities of some phenomenon and creates a density map by spreading these quantities across the map. You can use this tool, for example, to show concentrations of lightning strikes or tornadoes, access to health care facilities, and population densities.
This tool creates a density map from point or line features by spreading known quantities of some phenomenon (represented as attributes of the points or lines) across the map. The result is a layer of areas classified from least dense to most dense.
For point input, each point should represent the location of some event or incident, and the result layer represents a count of the incident per unit area. A larger density value in a new location means that there are more points near that location. In many cases, the result layer can be interpreted as a risk surface for future events. For example, if the input points represent locations of lightning strikes, the result layer can be interpreted as a risk surface for future lightning strikes.
For line input, the line density surface represents the total amount of line that is near each location. The units of the calculated density values are the length of line-per-unit area. For example, if the lines represent rivers, the result layer will represent the total length of rivers that are within the search radius. This result can be used to identify areas that are hospitable to grazing animals.
Other use cases of this tool include the following:
- Creating crime density maps to help police departments properly allocate resources to high crime areas.
- Calculating densities of hospitals within a county. The result layer will show areas with high and low accessibility to hospitals, and this information can be used to decide where new hospitals should be built.
- Identifying areas that are at high risk of forest fires based on historical locations of forest fires.
- Locating communities that are far from major highways in order to plan where new roads should be constructed.
- input_point_or_line_features : Required feature layer - The input point or line layer that will be used to calculate
- the density layer.
- count_field : Optional string - count field
- Provide a field specifying the number of incidents at each location. For example, if you have points that represent cities, you can use a field representing the population of the city as the count field, and the resulting population density layer will calculate larger population densities near cities with larger populations. If the default choice of None is used, then each location will be assumed to represent a single count.
- search_distance : Optional LinearUnit - Search distance
- Enter a distance specifying how far to search to find point or line features when calculating density values. For example, if you provide a search distance of 10,000 meters, the density of any location in the output layer is calculated based on features that are within 10,000 meters of the location. Any location that does not have any incidents within 10,000 meters will receive a density value of zero. If no distance is provided, a default will be calculated that is based on the locations of the input features and the values in the count field (if a count field is provided).
- output_area_units : Optional string - Output area units
- Specify the output area unit. Density is count divided by area, and this parameter specifies the unit of the area in the density calculation. The available areal units are Square Miles and Square Kilometers.
- output_cell_size : Optional LinearUnit - Output cell size
- Enter the cell size and unit for the output rasters.
- output_name : Optional. If not provided, an Image Service is created by the method and used as the output raster.
- You can pass in an existing Image Service Item from your GIS to use that instead. Alternatively, you can pass in the name of the output Image Service that should be created by this method to be used as the output for the tool. A RuntimeError is raised if a service by that name already exists
gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.
output_raster : Image layer item
classify¶
-
analytics.
classify
(input_raster, input_classifier_definition, additional_input_raster=None, output_name=None, *, gis=None, **kwargs)¶ input_raster : Required string
input_classifier_definition : Required string
additional_input_raster : Optional string
- output_name : Optional. If not provided, an Image Service is created by the method and used as the output raster.
- You can pass in an existing Image Service Item from your GIS to use that instead. Alternatively, you can pass in the name of the output Image Service that should be created by this method to be used as the output for the tool. A RuntimeError is raised if a service by that name already exists
gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.
output_raster : Image layer item
segment¶
-
analytics.
segment
(input_raster, spectral_detail=15.5, spatial_detail=15, minimum_segment_size_in_pixels=20, band_indexes=[0, 1, 2], remove_tiling_artifacts=False, output_name=None, *, gis=None, **kwargs)¶ Groups together adjacent pixels having similar spectral and spatial characteristics into segments, known as objects.
Argument Description input_raster Required ImageryLayer object spectral_detail Optional float. Default is 15.5. Set the level of importance given to the spectral differences of features in your imagery. Valid values range from 1.0 to 20.0. A high value is appropriate when you have features you want to classify separately but have somewhat similar spectral characteristics. Smaller values create spectrally smoother outputs.
For example, setting a higher spectral detail value for a forested scene, will preserve greater discrimination between the different tree species, resulting in more segments.
spatial_detail Optional float. Default is 15. Set the level of importance given to the proximity between features in your imagery. Valid values range from 1 to 20. A high value is appropriate for a scene where your features of interest are small and clustered together. Smaller values create spatially smoother outputs.
For example, in an urban scene, you could classify an impervious surface using a smaller spatial detail, or you could classify buildings and roads as separate classes using a higher spatial detail.
minimum_segment_size_in_pixels Optional float. Default is 20. Merge segments smaller than this size with their best fitting neighbor segment. This is related to the minimum mapping unit for a mapping project. Units are in pixels. band_indexes Optional List of integers. Default is [0,1,2] Define which 3 bands are used in segmentation. Choose the bands that visually discriminate your features of interest best. remove_tiling_artifacts Optional Bool. Default is False. If False, the tool will not run to remove tiling artifacts after segmentation. The result may seem blocky at some tiling boundaries. output_name Optional String. If specified, an Imagery Layer of given name is created. Else, an Image Service is created by the method and used as the output raster. You can pass in an existing Image Service Item from your GIS to use that instead. Alternatively, you can pass in the name of the output Image Service that should be created by this method to be used as the output for the tool. A RuntimeError is raised if a service by that name already exists gis Optional GIS object. If not speficied, the currently active connection is used. Returns: output_raster : Imagery Layer item
train_classifier¶
-
analytics.
train_classifier
(input_raster, input_training_sample_json, classifier_parameters, segmented_raster=None, segment_attributes='COLOR;MEAN', *, gis=None, **kwargs)¶ input_raster : Required string
input_training_sample_json : Required string
segmented_raster : Optional string
classifier_parameters : Required string
segment_attributes : Required string
gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.
output_classifier_definition
convert_feature_to_raster¶
-
analytics.
convert_feature_to_raster
(input_feature, output_cell_size, value_field=None, output_name=None, *, gis=None, **kwargs)¶ Creates a new raster dataset from an existing feature dataset. Any feature class containing point, line, or polygon features can be converted to a raster dataset. The cell center is used to decide the value of the output raster pixel. The input field type determines the type of output raster. If the field is integer, the output raster will be integer; if it is floating point, the output will be floating point.
input_feature : Required. The input feature layer to convert to a raster dataset.
- output_cell_size : Required LinearUnit. The cell size and unit for the output rasters.
- The available units are Feet, Miles, Meters, and Kilometers. eg - {“distance”:60,”units”:meters}
value_field : Optional string. The field that will be used to assign values to the output raster.
- output_name : Optional. The name of the layer that will be created in My Content.
- If not provided, an Image Service is created by the method and used as the output raster. You can pass in an existing Image Service Item from your GIS to use that instead. Alternatively, you can pass in the name of the output Image Service that should be created by this method to be used as the output for the tool. A RuntimeError is raised if a service by that name already exists
gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.
output_raster : Image layer item
convert_raster_to_feature¶
-
analytics.
convert_raster_to_feature
(input_raster, field='Value', output_type='Polygon', simplify=True, output_name=None, *, gis=None, **kwargs)¶ This service tool converts imagery data to feature class vector data.
input_raster : Required. The input raster that will be converted to a feature dataset.
- field : Optional string - field that specifies which value will be used for the conversion.
- It can be any integer or a string field. A field containing floating-point values can only be used if the output is to a point dataset. Default is “Value”
- output_type : Optional string
- One of the following: [‘Point’, ‘Line’, ‘Polygon’]
- simplify : Optional bool, This option that specifies how the features should be smoothed. It is
- only available for line and polygon output. True, then the features will be smoothed out. This is the default. if False, then The features will follow exactly the cell boundaries of the raster dataset.
- output_name : Optional. If not provided, an Feature layer is created by the method and used as the output .
- You can pass in an existing Feature Service Item from your GIS to use that instead. Alternatively, you can pass in the name of the output Feature Service that should be created by this method to be used as the output for the tool. A RuntimeError is raised if a service by that name already exists
gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.
output_features : Image layer item
copy_raster¶
-
analytics.
copy_raster
(input_raster, output_cellsize=None, resampling_method='NEAREST', clip_setting=None, output_name=None, *, gis=None, **kwargs)¶ input_raster : Required string
output_cellsize : Optional string
- resampling_method : Optional string
- One of the following: [‘NEAREST’, ‘BILINEAR’, ‘CUBIC’, ‘MAJORITY’]
clip_setting : Optional string
- output_name : Optional. If not provided, an Image Service is created by the method and used as the output raster.
- You can pass in an existing Image Service Item from your GIS to use that instead. Alternatively, you can pass in the name of the output Image Service that should be created by this method to be used as the output for the tool. A RuntimeError is raised if a service by that name already exists
gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.
output_raster : Image layer item
create_image_collection¶
-
analytics.
create_image_collection
(image_collection, input_rasters, raster_type_name, raster_type_params=None, out_sr=None, context=None, *, gis=None, **kwargs)¶ Create a collection of images that will participate in the ortho-mapping project. Provides provision to use input rasters by reference and to specify image collection properties through context parameter.
Argument Description image_collection Required, the name of the image collection to create.
The image collection can be an existing image service, in which the function will create a mosaic dataset and the existing hosted image service will then point to the new mosaic dataset.
If the image collection does not exist, a new multi-tenant service will be created.
This parameter can be the Item representing an existing image_collection or it can be a string representing the name of the image_collection (either existing or to be created.)
input_rasters Required, the list of input rasters to be added to the image collection being created. This parameter can be any one of the following: - List of portal Items of the images - An image service URL - Shared data path (this path must be accessible by the server) - Name of a folder on the portal raster_type_name Required, the name of the raster type to use for adding data to the image collection. raster_type_params Optional, additional raster_type specific parameters.
The process of add rasters to the image collection can be controlled by specifying additional raster type arguments.
The raster type parameters argument is a dictionary.
out_sr Optional, additional parameters of the service.
The following additional parameters can be specified: - Spatial reference of the image_collection; The well-known ID of the spatial reference or a spatial reference dictionary object for the input geometries. If the raster type name is set to “UAV/UAS”, the spatial reference of the output image collection will be determined by the raster type parameters defined.
context - Optional, The context parameter is used to provide additional input parameters
{“image_collection_properties”: {“imageCollectionType”:”Satellite”},”byref”:True}
use image_collection_properties key to set value for imageCollectionType. Note: the “imageCollectionType” property is important for image collection that will later on be adjusted by orthomapping system service. Based on the image collection type, the orthomapping system service will choose different algorithm for adjustment. Therefore, if the image collection is created by reference, the requester should set this property based on the type of images in the image collection using the following keywords. If the imageCollectionType is not set, it defaults to “UAV/UAS”
If byref is set to True, the data will not be uploaded. If it is not set, the default is False
gis Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used. Returns: The imagery layer item
add_image¶
-
analytics.
add_image
(image_collection, input_rasters, raster_type_name=None, raster_type_params=None, context=None, *, gis=None, **kwargs)¶ Add a collection of images to an existing image_collection. Provides provision to use input rasters by reference and to specify image collection properties through context parameter.
It can be used when new data is available to be included in the same orthomapping project. When new data is added to the image collection the entire image collection must be reset to the original state.
Argument Description input_rasters Required, the list of input rasters to be added to the image collection being created. This parameter can be any one of the following: - List of portal Items of the images - An image service URL - Shared data path (this path must be accessible by the server) - Name of a folder on the portal image_collection Required, the item representing the image collection to add input_rasters to.
The image collection must be an existing image collection. This is the output image collection (mosaic dataset) item or url or uri
raster_type_name Required, the name of the raster type to use for adding data to the image collection. raster_type_params Optional, additional raster_type specific parameters.
The process of add rasters to the image collection can be controlled by specifying additional raster type arguments.
The raster type parameters argument is a dictionary.
context - Optional, The context parameter is used to provide additional input parameters
{“image_collection_properties”: {“imageCollectionType”:”Satellite”},”byref”:True}
use image_collection_properties key to set value for imageCollectionType. Note: the “imageCollectionType” property is important for image collection that will later on be adjusted by orthomapping system service. Based on the image collection type, the orthomapping system service will choose different algorithm for adjustment. Therefore, if the image collection is created by reference, the requester should set this property based on the type of images in the image collection using the following keywords. If the imageCollectionType is not set, it defaults to “UAV/UAS”
If byref is set to True, the data will not be uploaded. If it is not set, the default is False
gis Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used. Returns: The imagery layer item
delete_image¶
-
analytics.
delete_image
(image_collection, where, *, gis=None, **kwargs)¶ delete_image allows users to remove existing images from the image collection (mosaic dataset). The function will only delete the raster item in the mosaic dataset and will not remove the source image.
Argument Description image_collection Required, the input image collection from which to delete images This can be the ‘itemID’ of an exisiting portal item or a url to an Image Service or a uri where Required string, a SQL ‘where’ clause for selecting the images to be deleted from the image collection gis Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used. Returns: The imagery layer url
delete_image_collection¶
-
analytics.
delete_image_collection
(image_collection, *, gis=None, **kwargs)¶ Delete the image collection. This service tool will delete the image collection image service, that is, the portal-hosted image layer item. It will not delete the source images that the image collection references.
Argument Description image_collection Required, the input image collection to delete.
The image_collection can be a portal Item or an image service URL or a URI.
The image_collection must exist.
gis Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used. Returns: Boolean value indicating whether the deletion was successful or not
list_datastore_content¶
-
analytics.
list_datastore_content
(datastore, filter=None, *, gis=None, **kwargs)¶ List the contents of the datastore registered with the server (fileShares, cloudStores, rasterStores).
Argument Description datastore Required. fileshare, rasterstore or cloudstore datastore from which the contents are to be listed. It can be a string specifying the datastore path eg “/fileShares/SensorData”, “/cloudStores/testcloud”, “/rasterStores/rasterstore” or it can be a Datastore object containing a fileshare, rasterstore or a cloudstore path. eg: ds=analytics.get_datastores() ds_items =ds.search() ds_items[1] ds_items[1] may be specified as input for datastore filter Optional. To filter out the raster contents to be displayed gis Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used. Returns: List of contents in the datastore
build_footprints¶
-
analytics.
build_footprints
(image_collection, computation_method='RADIOMETRY', value_range=None, context=None, *, gis=None, **kwargs)¶ Computes the extent of every raster in a mosaic dataset.
- image_collection : Required. The input image collection.The image_collection can be a
- portal Item or an image service URL or a URI. The image_collection must exist.
- computation_method : Optional. Refine the footprints using one of the following methods:
- RADIOMETRY, GEOMETRY Default: RADIOMETRY
value_range: Optional. Parameter to specify the value range.
- context : Optional dictionary. Can be used to specify values for keys like:
- whereClause, minValue, maxValue, numVertices, shrinkDistance, maintainEdge, skipDerivedImages, updateBoundary, requestSize, minRegionSize, simplification, edgeTorelance, maxSliverSize, minThinnessRatio
gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.
output_raster : Image layer item
build_overview¶
-
analytics.
build_overview
(image_collection, cell_size=None, context=None, *, gis=None, **kwargs)¶ - image_collection : Required. The input image collection.The image_collection can be a
- portal Item or an image service URL or a URI. The image_collection must exist.
cell_size : optional float or int, to set the cell size for overview.
context : optional dictionary
gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.
output_raster : Image layer item
calculate_statistics¶
-
analytics.
calculate_statistics
(image_collection, skip_factors=None, context=None, *, gis=None, **kwargs)¶ Calculates statistics for an image collection
- image_collection : Required. The input image collection.The image_collection can be a
- portal Item or an image service URL or a URI. The image_collection must exist.
- skip_factors : optional dictionary, Controls the portion of the raster that is used when calculating the statistics.
- eg: {“x”:5,”y”:5} x value represents - the number of horizontal pixels between samples
- y value represents - the number of vertical pixels between samples.
- context : optional dictionary. Can be used to specify parameters for calculating statistics. Keys can be
- ignoreValues, skipExisting, areaOfInterest
gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.
output_raster : Image layer item
optimum_travel_cost_network¶
-
analytics.
optimum_travel_cost_network
(input_regions_raster, input_cost_raster, output_optimum_network_name=None, output_neighbor_network_name=None, context=None, *, gis=None, **kwargs)¶ calculates the optimum cost network from a set of input regions.
- input_regions_raster : The layer that defines the regions to find the optimum travel cost netork for.
- The layer can be raster or feature.
input_cost_raster : A raster defining the impedance or cost to move planimetrically through each cell.
- output_optimum_network_name : Optional. If not provided, a feature layer is created by the method and used as the output.
- You can pass in an existing feature layer Item from your GIS to use that instead. Alternatively, you can pass in the name of the output feature layer that should be created by this method to be used as the output for the tool. A RuntimeError is raised if a service by that name already exists
output_neighbor_network_name : Optional. This is the name of the output neighbour network feature layer that will be created.
context: Context contains additional settings that affect task execution.gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.
output_raster : Image layer item
determine_travel_costpath_as_polyline¶
-
analytics.
determine_travel_costpath_as_polyline
(input_source_data, input_cost_raster, input_destination_data, path_type='BEST_SINGLE', output_polyline_name=None, *, gis=None, **kwargs)¶ Calculates the least cost polyline path between sources and known destinations.
Argument Description input_source_data The layer that identifies the cells to determine the least costly path from. This parameter can have either a raster input or a feature input. input_cost_raster A raster defining the impedance or cost to move planimetrically through each cell.
The value at each cell location represents the cost-per-unit distance for moving through the cell. Each cell location value is multiplied by the cell resolution while also compensating for diagonal movement to obtain the total cost of passing through the cell.
The values of the cost raster can be an integer or a floating point, but they cannot be negative or zero as you cannot have a negative or zero cost.
input_destination_data The layer that defines the destinations used to calculate the distance. This parameter can have either a raster input or a feature input. path_type A keyword defining the manner in which the values and zones on the input destination data will be interpreted in the cost path calculations.
A string describing the path type, which can either be BEST_SINGLE, EACH_CELL, or EACH_ZONE.
BEST_SINGLE: For all cells on the input destination data, the least-cost path is derived from the cell with the minimum of the least-cost paths to source cells. This is the default.
EACH_CELL: For each cell with valid values on the input destination data, at least-cost path is determined and saved on the output raster. With this option, each cell of the input destination data is treated separately, and a least-cost path is determined for each from cell.
EACH_ZONE: For each zone on the input destination data, a least-cost path is determined and saved on the output raster. With this option, the least-cost path for each zone begins at the cell with the lowest cost distance weighting in the zone.
output_polyline_name Optional. If not provided, a feature layer is created by the method and used as the output.
You can pass in an existing feature layer Item from your GIS to use that instead.
Alternatively, you can pass in the name of the output feature layer that should be created by this method to be used as the output for the tool. A RuntimeError is raised if a service by that name already exists
gis Optional GIS. the GIS on which this tool runs. If not specified, the active GIS is used. Returns: The imagery layer url


• Client ID: This is the ID of your application. It can be obtained from the Discord Developer
Portal
Note:
The name of this application directly affects the name of the RP
• Start & Stop Times: These will be the start and stop times of the RP. Just write the
start time to get 'elapsed' time and write both to get 'remaining' time
Note:
These time stamps are in Unix Epoch and are in
Milliseconds
• Image Keys: These should be filled in with the asset keys that you set in Discord Developer Portal
• Image Texts: These texts will appear when you hover over the large and small images respectively
• Party ID: This will be the ID of the party. It can be left
empty
Note:
You can
fill this in with a random string if you want to show the 'Ask to join' button
• Party Size & Max: The number of people curently in the party and the maximum party size respectively
• Join Secret: This will be the Join Secret of the party. It can be left
empty
Note:
You can
fill this in with a random string if you want to show the 'Ask to join' button


waitForCompositionComplete(): Promise
Allows the transaction owner to wait for the completion of all child compositions.
Returns
A promise that resolves when all child compositions are done.
waitForCompositionComplete(): Promise
Allows the transaction owner to wait for the completion of all child compositions.


The maximum number of containers that this provider is allowed to run in total (value is independent of the template/image).
Note that also containers, which have not been created by Jenkins, are counted as well.
Defaulted to 100, if not specified otherwise.
A value of zero (0) disables provisioning of containers altogether. If you want to disable this limit, enter a non-reachable high value, such as<PHONE_NUMBER>.


Taf-siri
Home
About
Contact
Sign-up
Profile
Stressed up and broke start saving.
Track your expenses!


&; growth climate vertical flushing species trait OpenUrl models Figure leaf traits model phenotypic range local adaptation radial survival tree plasticity variation beech Table future trial two-trait provenance distribution populations values variables Appendix Information current interaction predictions response sylvatica using growth, European S., predicted CrossRef S). trees (Supporting change one-trait phenology individual precipitation related Benito Forest common conditions included spatial total used Ecology Fagus View interactions mortality provenances site trials variable Biology climatic differences different low northern ranges represent (Fagus BIO, best co-variate co-variation environmental fitness-related fixed gardens high new patterns southern (Julian (a) (b) Garzón, Global Robson data effects fitness geographical height latitude likely lines potential random Download L.) Spatial age based change. driven explained higher measurements occurrence performed photoperiod range. responses trial; Age Environmental Garzón Robson, Science Search Trait Tree analysis case clinal color considered estimate explain following forest function gradients increase late linear maximal number projection projections second selected study temperature understand Agricultural Beech BeechCOSTe Change Chuine, However, Montgomery, PCA Pet University Web Zavala, at: attributed better combination combined component considering contribution database driest extent graph). graphs growth-leaf high, important large mainly maps marginal margins model. models) models, month package particularly period planted showed temperate wettest (c) (cm), (cm; (d) (green) (i) (ii) (iii) (inferred (maps (mm), (red) ... Abstract Arndt Available BIOGECO Biogeography, Biology, Black, Bordeaux, Cov Data Duputié, Evolution, France Gárate-Escamilla Hampe Homero INRA Körner, Laughlin, Marta Matthew Meteorology, Morris, Natalia Pessac, Range-wide Science, Supporting UMR Variation Vizcaíno-Palomar Wang, addition, beech, capacity climate. confidence contemporary corresponding dark data) days). delimit depicts display eastern edge evapotranspiration global gradient gradients, grey grey, growth; https://doi.org/./gcb. https://doi.org/./j.agrformet... implications importance indicated intervals. left), light longitude measured medium meteorological migration mixed-effect models. models: parts predict probability prov: provenance; quantify range, range-wide recorded results seeds selection significant similar single strongly temperatures trees. trial, variance warming winter year


1355 Market St #900,
San Francisco, CA 94103, United States
Phone: +65-123-4567-890
Email<EMAIL_ADDRESS>|
INVOICE TO:
1355 Market St #900,
Phone: +65-123-4567-890 |
TOTAL DUE$ 1200.00 |
| # | PRODUCT | DETAILS | QNT | DISCOUNT | TOTAL |
|---|---|---|---|---|---|
| 1 |
Item Name 1Medium |
2 | 0 | $1000 | |
| 2 |
Item Name 2Medium |
4 | 0 | $1000 |
Happy to serve! |
|


|
| Value |
Description |
Notes |
|
| 01 |
Publisher |
|
| 02 |
Co-publisher |
Use where two or more publishers co-publish the exact same product, either under a single ISBN (in which case both publishers
are co-publishers), or under different ISBNs (in which case the publisher of THIS ISBN is the publisher and the publishers
of OTHER ISBNs are co-publishers. Note this is different from publication of 'co-editions'.
|
| 03 |
Sponsor |
|
| 04 |
Publisher of original-language version |
Of a translated work. |
| 05 |
Host/distributor of electronic content |
|
| 06 |
Published for/on behalf of |
|
| 07 |
Published in association with |
Use also for “Published in cooperation with”. |
| 08 |
Published on behalf of |
DEPRECATED: use code 06. |
| 09 |
New or acquiring publisher |
When ownership of a product or title is transferred from one publisher to another. |
| 10 |
Publishing group |
The group to which a publisher (publishing role 01) belongs: use only if a publisher has been identified with role code 01. |
| 11 |
Publisher of facsimile original |
The publisher of the edition of which a product is a facsimile. |
| 12 |
Repackager of prebound edition |
The repackager of a prebound edition that has been assigned its own identifier. (In the US, a ‘prebound edition’ is a book
that was previously bound, normally as a paperback, and has been rebound with a library-quality hardcover binding by a supplier
other than the original publisher.) Required when the <EditionType> is coded PRB. The original publisher should be named as
the ‘publisher’.
|
| 13 |
Former publisher |
When ownership of a product or title is transferred from one publisher to another (complement of code 09). |
|


osmo_jupyter.simulate package¶
Submodules¶
osmo_jupyter.simulate.do_and_temp_meshgrid module¶
-
osmo_jupyter.simulate.do_and_temp_meshgrid.
get_meshgrid_of_do_and_temp
(fn_of_do_and_temp)¶ Get values that correspond to the (global) DO and temperature meshgrids
- Params:
fn_of_do_and_temp: Function which takes DO and temperature positional arguments (in that order)
- Returns:
- 2d np.array of values from fn_of_do_and_temp
dimension 0 will iterate over DO dimension 1 will iterate over temperatures
this meshgrid will be appropriate to use on the Z axis of a plotly Surface where DO_MESHGRID is on the X axis and TEMPERATURE_MESHGRID is on the Y axis.
-
osmo_jupyter.simulate.do_and_temp_meshgrid.
plot_fn_of_do_and_temp_as_surface
(fn_of_do_and_temp, title, z_axis_title)¶ Create a surface plot of a DO- and temperature-dependent function.
- Args:
- fn_of_do_and_temp: a function which takes DO saturation and temperature as positional arguments (in that order).
This function will be used with DO_MESHGRID and TEMPERATURE_MESHGRID to compute values at a standard range of temperature and DO values.
title: title to use on the resulting chart z_axis_title: label for the Z axis - what does your function describe?
- Returns:
plotly FigureWidget for your viewing pleasure
-
osmo_jupyter.simulate.do_and_temp_meshgrid.
plot_meshgrid_of_do_and_temp_as_surface
(meshgrid_of_do_and_temp, title, z_axis_title)¶ Create a surface plot of a DO- and temperature-dependent function.
- Args:
meshgrid_of_do_and_temp: a meshgrid corresponding to DO_MESHGRID and TEMPERATURE_MESHGRID. title: title to use on the resulting chart z_axis_title: label for the Z axis - what does your function describe?
- Returns:
plotly FigureWidget for your viewing pleasure
osmo_jupyter.simulate.do_patch module¶
-
osmo_jupyter.simulate.do_patch.
get_optical_reading_normalized
(do_pct_sat, temperature, min_value=0, max_value=1)¶ Get a normalized optical reading between a min and max value, with DO and temperature relationship from a precalculated, hardcoded fit.
- Args:
do_pct_sat: Dissolved Oxygen in percent saturation temperature: Temperature in degrees Celcius min_value: Optional (default=0). Minimum value for the normalized range max_value: Optional (default=1). Maximum value for the nomralized range
- Returns:
An optical reading normalized to be within (optional) min_value and max_value.
-
osmo_jupyter.simulate.do_patch.
get_optical_reading_plot
()¶ Quick plot of a single-patch optical reading over a range of temperatures and DO values, using a precalculated, hardcoded fit.
osmo_jupyter.simulate.do_ratiometric module¶
-
osmo_jupyter.simulate.do_ratiometric.
get_ratiometric_reading_plot
()¶ Quick plot of a spatial ratiometric optical reading over a range of temperatures and DO values.
-
osmo_jupyter.simulate.do_ratiometric.
simulate_spatial_ratiometric_reading
(do, temperature, sealed_patch_do=0, sealed_patch_kwargs={}, unsealed_patch_kwargs={})¶ Simulate a “spatial ratiometric” reading using a sealed DO patch as the ratiometric reference
- Args:
do: Dissolved Oxygen in percent saturation in the unsealed patch temperature: Temperature in degrees Celcius sealed_patch_do: Optional (default=0). Dissolved Oxygen in percent saturation in the sealed patch sealed_patch_kwargs: Optional. Additional args passed to get_optical_reading_normalized for the sealed patch unsealed_patch_kwargs: Optional. Additional args passed to get_optical_reading_normalized for the unsealed patch
- Returns:
A spatial ratiometric result: the ratio between normalized optical readings of the unsealed and sealed patches


BOOKWARS A film review by Christopher Null Copyright 2000 filmcritic.com filmcritic.com
There are a million stories in the naked city, and a new documentary from Jason Rosette does a remarkable job at ferreting out one of them -- and where you'd least expect it.
BookWars examines the strange and unexpectedly intense world of street booksellers in Manhattan -- specifically, a little stretch of 4th Street near NYU, where otherwise unemployed types set up an 8-foot table, covered with treasures of the printed word.
Rosette tells the story from the inside, having spent three years on 4th, selling precious volumes of Dostoyevsky, Kerouac, and Kierkegaard. We meet his colleagues, who range from surprisingly well adjusted to almost completely insane. And we discover the origins of the books -- estate sales, libraries, the trash, and even other street sellers when they inevitably wash out.
But Rosette's tale is especially remarkable from several perspectives. First, the streetwise merchandising tactics you learn in BookWars' 79 minutes teach you more about business than any MBA program. Second, the socio-political microscope the booksellers find themselves under when Giuliani's "Quality of Life" program is introduced (thus attempting to whisk them off the sidewalks) makes a powerful statement about who programs like these are really helping out. Corporate America and academia are the understated targets as the independent street booksellers are gradually given less and less "official" space in which to operate.
While Rosette's over-earnest narration can get thick at times and the finale feels a tad dismissive, his story is never short of enthralling. Altogether, it's a fresh break from more sanitized documentary filmmaking, giving us a unique look into a part of life I've always wondered about.
RATING: ***1/2
|------------------------------| \ ***** Perfection \ \ **** Good, memorable film \ \ *** Average, hits and misses \ \ ** Sub-par on many levels \ \ * Unquestionably awful \ |------------------------------|
MPAA Rating: NR
Director: Jason Rosette Producer: Jason Rosette Writer: Jason Rosette Starring: Jason Rosette
http://www.camerado.com --- Christopher Null -<EMAIL_ADDRESS>- http://www.filmcritic.com
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews