Using_em38.Rmd
library(em38)
library(sf)
library(dplyr)
library(tidyr)
library(ggplot2)
options(stringsAsFactors = FALSE)
em38 offers an R-based alternative to the ‘DAT38MK2’ software that accompanies the Geonics EM38-MKII Ground Conductivity meter. The package can take in the *.n38 binary files produced by the device and its accompanying datalogger and either produce an sf
-style point dataset or a replicate of the *.m38 plain-text logfile. The package also contains intermediate functions that step through the process of decoding the *.n38 binary files, hopefully demystifying the process somewhat.
This package allows users to incorporate EM38-MKII data into a fully reproducible workflow, and also makes it possible for non-Windows users to easily work with an EM38-MKII.
em38
requires only an *.n38 file as input, and can complete a one-line conversion with em38_from_file()
. This will return a list containing the file header information, plus a processed list of survey lines. If GPS data is available for a survey line dataset, it will have sfc_POINT
geometry and can be written to file using a vector spatial file format like GeoPackage. If no GPS data is available, the data can be written to *.csv.
demo_survey <-
em38_from_file(path = system.file("extdata", "em38_demo.N38",
package = "em38"),
hdop_filter = 3)
sl1 <- demo_survey$survey_lines[[1]]
plot(sl1[sl1$mode == 'Vertical', 'cond_05'], pch = 20,
main = 'Conductivity, Vertical Dipole Mode, Coil Separation 1.0m')
head(sf::st_set_geometry(sl1, NULL)[, c('ID', 'cond_05', 'date_time')])
#> ID cond_05 date_time
#> 1 1 146.9004 2018-03-16 13:00:23
#> 2 2 144.0879 2018-03-16 13:00:23
#> 3 3 146.0801 2018-03-16 13:00:23
#> 4 4 143.4239 2018-03-16 13:00:23
#> 5 5 138.8536 2018-03-16 13:00:23
#> 6 6 139.3614 2018-03-16 13:00:24
If you want to visualise your decoded track data in R the same way DAT38MK2 does, some recipes follow using ggplot2
.
Firstly, a basic graph of all the data. Drop the geometry, condense the dataset into two columns, and then plot with appropriate data grouping settings:
dat <- sf::st_set_geometry(sl1, NULL) %>%
dplyr::select(-indicator, -marker, -date_time) %>%
tidyr::gather('key', 'value', -ID, -mode) %>%
tidyr::unite('key', mode, key)
ggplot(dplyr::filter(dat, between(ID, 0, 500))) +
geom_path(aes(x = ID, y = value, group = key, col = key), size = 1) +
ggtitle('Decoded track, first 100 records') +
theme_minimal()
# the operator must have put the machine down, because a couple of
# points are in horizontal mode:
ggplot(dplyr::filter(dat, between(ID, 1250, 1350))) +
geom_path(aes(x = ID, y = value, group = key, col = key), size = 1) +
ggtitle('Decoded track, first 100 records') +
theme_minimal()
Since conductivity and temperature readings are on very different scales, it is preferable to facet the plot. Below, an additional ‘measurement type’ grouping variable is added before plotting, and used to split the data into separate panels.
# better grouping - split out by measurement type
dat <- dat %>%
dplyr::mutate(TYPE =
dplyr::case_when(grepl('cond', key) ~ 'Conductivity',
grepl('IP', key) ~ 'In Phase',
grepl('temp', key) ~ 'Temperature'))
ggplot(dplyr::filter(dat, ID <= 500) %>% dplyr::filter(TYPE != 'INPHASE')) +
geom_path(aes(x = ID, y = value, group = key, col = key), size = 1) +
facet_wrap(~TYPE, scales = 'free_y') +
ggtitle('Decoded track, first 500 records') +
theme_minimal()
If you want more control over plot aesthetics, patchwork
is helpful:
# devtools::install_github("thomasp85/patchwork")
library(patchwork)
# common plot aesthetics
thm <- theme_minimal() +
theme(legend.position = 'bottom',
legend.title = element_blank(),
axis.title.x = element_blank())
cond <- ggplot(dplyr::filter(dat, ID <= 500) %>%
dplyr::filter(TYPE == 'Conductivity')) +
geom_path(aes(x = ID, y = value, group = key, col = key), size = 1) +
scale_y_continuous(limits = c(0, 250)) +
thm
temp <- ggplot(dplyr::filter(dat, ID <= 500) %>%
dplyr::filter(TYPE == 'Temperature')) +
geom_path(aes(x = ID, y = value, group = key, col = key), size = 1) +
scale_y_continuous(limits = c(33, 36)) +
labs(y = 'Temperature (C)') +
thm
cond + temp + plot_annotation(title = 'Decoded track, first 500 records')


Gateway
BOT
06-Jul-18 06:44 PM
[dscrdeql] <CombatWombat> haha hey daylight
[dscrdeql] <MySoulisNotForSale> @CombatWombat they say anything to get selected
[dscrdeql] <MySoulisNotForSale> @CombatWombat they need to prove to their handlers how loyal they are at lying to the public
[dscrdeql] <CombatWombat> yeah don't have much good to say about politicians
[dscrdeql] <donaldmathers> He’s delivered on almost every single campaign promise
[dscrdeql] <CombatWombat> @donaldmathers why isn't hillary in jail?
[dscrdeql] <DaylightHours> @CombatWombat funny
[dscrdeql] <AndronicusBass-Founder> Everything is a madhouse.
[dscrdeql] <AndronicusBass-Founder> It's all. Big show. Also many people brainwashed from msm.
[dscrdeql] <CombatWombat> yep
[dscrdeql] <donaldmathers> That’s why I said ALMOST every promise lol
[dscrdeql] <MySoulisNotForSale> @AndronicusBass-Founder produced he Hollywood (pedowood)
[dscrdeql] <MySoulisNotForSale> *by
[dscrdeql] <CombatWombat> @donaldmathers he has done some decent thing for america i got family there my uncle is all for him his daughter not so much lol
[dscrdeql] <SwimedDragon> Oh sorry guy's
[dscrdeql] <SwimedDragon> Need to remove it?
[dscrdeql] <CombatWombat> but his middle east policies still suck and didn't help situations but made them worse
[dscrdeql] <MySoulisNotForSale> @donaldmathers he;s done a good job at giving ISIS more weapons . .
[dscrdeql] <donaldmathers> He demolished ISIS lol
[dscrdeql] <MySoulisNotForSale> @donaldmathers yeah right. . turn off the news
[dscrdeql] <AndronicusBass-Founder> Gonna allow gifs in here again, but not too Spammy.
[dscrdeql] <AndronicusBass-Founder> Russia demolished Isis
[dscrdeql] <MySoulisNotForSale> @AndronicusBass-Founder and the Syrian Army, and Hezbollah
[dscrdeql] <CombatWombat> Russia took them out from the air which gave the army and allies ability to do ground work
[dscrdeql] <MySoulisNotForSale> @AndronicusBass-Founder I almost spit out my beer when he said "He demolished ISIS lol"
[dscrdeql] <CombatWombat> like bass said it's a madhouse
[dscrdeql] <AndronicusBass-Founder> It's all a distraction.
[dscrdeql] <AndronicusBass-Founder> You have to look at the bigger picture
[dscrdeql] <DaylightHours> . So funny brainwashing..
[dscrdeql] <donaldmathers> So general Mattie never bombed them?
[dscrdeql] <donaldmathers> Mattis
[dscrdeql] <MySoulisNotForSale> ^^^ lol
[dscrdeql] <MySoulisNotForSale> they told them where the bombs were dropping first
[dscrdeql] <MySoulisNotForSale> let's not mention our second best allies (Saudi Arabia) is doing in Yemen .. .
[dscrdeql] <AndronicusBass-Founder> Global economy, everything is bubbles, derivatives markets, most countries in debt, overheating money presses, lowest interest rates in history etc etc
[dscrdeql] <MySoulisNotForSale> @AndronicusBass-Founder ironic how the countries who don't rely on the petro dollar seem to get "bombs of liberty"
[dscrdeql] <MySoulisNotForSale> @AndronicusBass-Founder thank you for being awake. . . gotta go bro's
[dscrdeql] <AndronicusBass-Founder> I need some sleep. Have to be up in a few hours.
[dscrdeql] <AndronicusBass-Founder> OK no prob peace
[dscrdeql] <SwimedDragon> Have a good night, sleep well
[dscrdeql] <CombatWombat> night bass
[dscrdeql] <donaldmathers> Goodnight !!
[dscrdeql] <Catalyst> Good night guys.. :)
[dscrdeql] <donaldmathers> Goodnight to all that are leaving
[dscrdeql] <Catalyst> And thanks for the awesome rain
[dscrdeql] <Catalyst> @donaldmathers thanks man :)
[dscrdeql] <donaldmathers> No problem


Did your math just bring you here? Let me help you. A black hole has been generated to break through time and space to redirect you to the home page.
You will be redirected to the home page in 5 seconds.


kulife: Datasets and functions from the (now non-existing) Faculty of
Life Sciences, University of Copenhagen
Provides various functions and data sets from experiments at the Faculty of Life Sciences, University of Copenhagen. This package will be discontinued and archived, and the functions and datasets will be maintained and updated in the MESS package
| Version: |
0.1-14 |
| Suggests: |
lme4, XML |
| Published: |
2013-10-01 |
| Author: |
Claus Ekstrom, Ib M. Skovgaard, Torben Martinussen |
| Maintainer: |
Claus Ekstrom <ekstrom at sund.ku.dk> |
| License: |
GPL-2 |
| NeedsCompilation: |
no |
| CRAN checks: |
kulife results |
Downloads:
Reverse dependencies:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=kulife
to link to this page.


William Putra Pangestu
About Me
Solo Challenge
Wireframe
Blog
Contact
Solo Challenges
First Solo Challenge
Second Solo Challenge


FIERCE CREATURES A film review by John R. Mellby Copyright 1997 John R. Mellby
John Cleese, Jamie Lee Curtis, Kevin Klein, Michael Palin Directed by Robert Young, Produced by Michael Shamberg, Steve Abbot http://www.fierce-creatures.com/
As I watched this film it struck me that there aren't many funny movies being made any more. Oh, we have comedies (some of them even good) such as Steve Martin's films, and we have silly films (a painful lot of silly films), but not very many movies which are just trying to be funny. I can't remember a funny film I saw since "A Fish called Wanda", which brings us back here.
Some nice friends gave us tickets to a preview of FC. This unites the cast, producer, and some writers of "A Fish called Wanda". This movie isn't a sequel but a totally new, and *very* funny picture. The stars, along with a fierce supporting cast (love the lemurs), along with some great actors, in running a zoo.
The film centers upon a pair of twits. No, this isn't a misprint referring to Jamie Lee Curtis, although her twits (oops, er ummm, you know what I mean) do have a few prominent scenes. We have a ruthless New Zealand Twit (Kevin Klein) running a business empire where everything makes 20% profit or it get destroyed, and his son, a hapless twit (also Kevin Klein) who pretty much stumbles through life. The son, Jamie Lee Curtis, and John Cleese all try to run an English zoo.
First Cleese trys to make the zoo popular through violence. "All the creatures must be fierce", hence the title. This fails with many comic problems. Next, Kevin Klein trys a marketeering approach where Celebrities sponsor the animals. (I couldn't see who Saddam Hussain sponsored, so if anyone figures it out, please tell me.)
Along the way, mishaps lead them to think that John Cleese is sleeping with 3-4 women (and animals) at a time, which attracts Jamie Lee, and disgusts (and impresses) Klein. The naked tarantula scene was almost painful to watch.
The take old ideas (people trapped in a hotel room trying to escape the notice of the real occupants, and do them astoundingly well. You think they have escaped, and at the last minute they don't get out. They they almost escape again, and ... well, you get the picture.
Overall Cleese is as funny as ever. Michael Palin is oddly wedged in, as if they wrote the movie and discovered they hadn't a role for him, so they patched him into random scenes. Still he is funny. The supporting actors (too many to name) are good (even if they occasionally the bundle so many into a scene that it just gets too busy).
IMHO this is the funniest movie I've seen in several years.
P.S.
John R. Mellby
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
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Related links: index of all rec.arts.movies.reviews reviews


Blackfoot River Brewing Company State Criterium Championships
Fifty Five Riders, Hot, Clean, Fun.
Senior Men 1/2/3:
- Jamul Hahn, Northern Rockies
- Jason Dykstra, Share the Roads
- Joe Arnone, Unnattached
- Dan Dahlberg, Northern Rockies
- John Weyrich, Five Valley Velo
- Scott Herzig, Montana Velo
- Dave Landstrom, Northern Rockies
- Jeff Caton, Napa Valley Velo
- Marcel Vangarderen, Gallatin Valley Bicycle Club
- John Behrens, Northern Rockies, 1st Category 3
- Jeff Penrod, Northern Rockies, 2nd Category 3
- Dustin Phillips, Northern Rockies
DNF, Alex Gallego
DNF, Thomas Bass
DNF, Rankin Holmes
DNF, Kale Keltz
DNF, Brock P Boring
DNF, Will Schneider
DNF, Chad Devall
DNF, Dave Hartman
DNF, Mark Legg
Senior Men, 4/5:
- Steve Coen, Montana Velo
- Sean Cavanaugh, Round House Racing
- Even Lawrence, Team Big Sky
- Jason Hobson, Five Valley Velo
- Dave Havlick, Ecology Center Cycling
- Brian Wirak, Montana Velo
- Shane Mundt, Great Divide Cycling Team
- Nathan Grovom, Montana Velo
- Tejay Vangarderen, Gallatin Valley Bicycle Club
- Brad Houle, Echelon Cycling Club
- Phill Hess, Great Divide Cycling Club
- Mike Beltz, Ecology Center Cycling
- Doug Hawes-Davis, Ecology Center Cycling
- Chase Carter, Montana Velo
- Keith Carparelli, Great Divide Cycling Team
Senior Women:
- Joanna Bieri, Northern Arizona University
- Sara Halvorson, Five Valley Velo, State Champion
- Debbie Borden, Share the Roads
- Christine Wicke, Great Divide Cycling Team
- Kathy McGann, Five Valley Velo, 1st Masters Women
Women 2/3
> Place LIcense# Club
> 1-Lynn Brotzman 1-day DeFeet
> 2-Nancy Wright 1480 BBC
> 3-Elia Meza 586 Mako/Silks
>
> Women 4
> 1-Marcia Reed 1898 Nova/Sycip
> 2-Meredith Neilson 76 VSRT
> 3-Judy Lyons 2148 VSRT
Junior Men:
- Luke Juras, Echelon Cycling Club
- Dave McCullough, Echelon Cycling Club
Masters Men 35+:
- Tim Gaertner, Flathead Valley Velo, 1st Masters 35-39
- Rich West, Echelon Cycling Club, 1st Masters 40-44
- Joel Gerhart, Great Divide Cycling Team, 2nd Masters 35-39
- John Juras, Echelon Cycling Club, 2nd Masters 40-44
- Scott Boyles, Great Divide Cycling Team, 3rd Masters 35-39
- Craig Lammey, Gallatin Valley Velo,
- Ernie Lapp, Christiance Cyclery
- Scott Fisk, Great Divide Cycling Club, 3rd Masters 40-44
Masters Men 45+:
- Michael Longmire, Northern Rockies
- Jeff Penrod, Northern Rockies
- Steve Muller, Northern Rockies
- Tom Arnone, Unattached, 1st Masters 60+


Court warns DSS on consequences of refusal to release Sowore, Bakare
by https://www.facebook.com/CheerfulpraiseEric Ikhilae, Abuja
The Federal High Court in Abuja has warned the Director-General of the Department of State Services (DSS) on the consequences of the continued detention the convener of RevolutionNow, Omoyele Sowore and his associate, Olawale Bakare (Mandate).
The court’s warning is contained in a Form 48 issued by the Registrar and served on the DSS on November 25, 2019.
The document sighted by The Nation in Abuja on Monday reads: “Notice of consequences of disobedience to order of court.
“Take notice that unless you obey the direction contained in the order of the Federal High Court of Justice, Abuja made on the 6th November, 2019, which ordered you to release the defendants/Applicants in suit no: FHC/ABJ/CR/235/2019 forthwith, you will be guilty of contempt of court and will be liable to be committed to prison.
Read Also: Sowore’s incarceration should end, family tells DSS
“A copy of the said order of court earlier served on you is hereby annexed for your on-the spot reference.
“This court has been informed that even as at today, Tuesday the 12th November, 2019 you are yet to comply with the lawful order of the Federal High Court by refusing to release the defendants/applicants namely: Omoyele Stephen Sowore and Olawale Adebayo Bakare (Mandate) in your custody.
“You are hereby directed to comply with the court order forthwith or you will be guilty of contempt of court.”
It was learnt yesterday the document was received at the DSS headquarters by Tina James.


|
Threesomesaka three-way, menage a troisLast stop before Freakville! The classic threesome arguably represents your best chance at having a classy erotic sort of experience, while still pushing the bounds of sexual taboo.As a sexual fantasy, the girl-girl-guy three-way ranks near the top of most male fantasy hierarchies, while the guy-guy-girl combo rates significantly lower. It's more difficult to generalize about women's attitudes toward the concept. Fantasy aside, somewhere between 5 and 20 percent of Americans will admit to a pollster that they've been in a three-way -- depending on who's asking, who's answering and how you're defining your terms. For instance, something like 16 percent of men polled will admit to having taken part in a threesome, as opposed to 8 percent of women. There's clearly a margin of error at work here. But the bottom line is that there are more Americans who have taken part in a threesome than there are -- just to pick a for-instance -- practicing Jews. The odds are pretty good that someone within your circle of friends has been part of a three-way, although they may not have chosen to share this information with you (for fear of giving you ideas). One of the most favored configurations for a three-way is one man and two women. There are two major reasons for this (and a host of minor ones).
The competition factor is perhaps even more inhibiting. First off, there's the "size of the waves" issue.  What if it has superior girth? What if it's more aesthetically pleasing? If all this wasn't enough, there's the "motion of the ocean" issue. What if he can go longer? What if she likes his technique better? Then there's everything else, including things that never occur to men except in this situation, things like "Does my semen taste better than the next guy's?" and "Do I make enough noise?" The homophobia and competition factors eliminate probably 80-90% of men from taking part in hot guy-guy-girl action. Men who have an abundance of self-esteem and self-awareness are the most likely to have rewarding experience. Oddly, men who have a extreme lack of self-esteem and self-awareness also seem to do all right. The guy-guy-girl also tends to be more sordid than the reverse (although this can be avoided with an assiduous effort). Why? Because there are more guys involved, of course! Beware of high-fives and spunk flying everywhere. And don't even get us started on the guy-guy-guy configuration. Let's just say dropcloths will save you a lot of trouble later.
|


0"> The playground has {{totalSandboxes}} sandboxed component{{totalSandboxes > 1 ? 's' : ''}}
Get started - create your first sandbox! Click here.
{{key}}
{{shortcut.description}}


Come and enjoy the relaxing beaches and beautiful sunsets.
Stay at a relaxing hotel and enjoy the SPA treatments here.
Come here to this peaceful town and the fresh air and enjoy the beautiful mountains.


Across: 1. Cleverly built epic closet which folds into itself (10) 7,18dn. Paris overpass near 11 24 ended life at, leading 10s at 19 (4 2 1'4) 9. Island setting of teriyaki rib, a Timorese offering (8) 10. Appeared down with two wheeler (5) 11. Nun let loose to violate court order? (6) 12. Chauffeur initially smoked charras, but heaps of booze can also cause this (3 5) 13. They should learn from dangerous escapades involving drive outside (8) 15. Checking dimension is inverted with inner energy (6) 17. Disputed later parts of life stud rued (6) 19. Early parts being gone, spin developed (8) 21.  Small gain in little bird as tasty morsel (6) 25. Musicians Orbison, Green and King perhaps (5) 26. Releasing mad king to go making branches on the family tree (8) 27.  Saints sat about with secular leader they helped (10) Down: 2.  Hydration product of the idiotically naive? (5) 4. Comic hero, a player loved in numerous leads (7) 5. Embracing next leader costs ... a loss few managed in this 25 role (8 2 5) 6. They were used for shooting a merc, as wrecked (7) 7. Spinning "Pizza Rap", a popular piece which the press use widely (9) 8. They wore nothing and drove outside into the sunrise (5) 14. Wealthy Egyptian party accompanying 24, if a dusky love could, finally? (4 5) 16. Not paying enough attention and killing one unfortunate genial gent (9) 18. see 7 across 20. Carries on, but looks after old lover first (7) 22. Freight vehicle to depart (5) 24. Could I, an anarchist, embrace popular 5? (5)


Basic terminologies and concepts in computer world
Iam writing this blog just to bring back all the memories of the basic concepts and terminologies that we learnt in our high school. I am going to discuss several topics in random manner and you can use this blog as your own personal notes just to have quick overview.
Procedural and non-procedural languages
Note — Network layer (IP) is responsible for getting data from one node to another. Whereas the transport layer (TCP or UDP) is responsible for ensuring that data reaches the right application running on those nodes.
In short, it means to start from nothing and follow a series of steps to arrive at a fully operational system.


Issue 32
-
Introducing the Hamilton library
The hamilton library is on Hackage! It was mostly a proof-of-concept toy experiment to simulate motion on Bezier curves, but it became usable enough and accurate enough (to my surprise, admittedly) that I finished up some final touches to make it complete and put it on Hackage as a general-purpose physics simulator.
-
Dhall: A non-Turing-complete configuration language
I’m releasing a new configuration language named Dhall with Haskell bindings. Even if you don’t use Haskell you might still find this language interesting. This language started out as an experiment to answer common objections to programmable configuration files. Almost all of these objections are, at their root, criticisms of Turing-completeness.
-
The goals of this little hack, called Hyper, is to make use of row polymorphism and other tasty type system features in PureScript to enforce correctly stacked middleware in HTTP server applications. All effects of middleware should be reflected in the types to ensure that otherwise common mistakes cannot be made.
-
The problem is that even on my machine
ghc --make -j3
works better thanghc --make -j8
and I could not get more than 1.5x speedup. I’d like to see 8x speedup. Another problem is quick performance degradation once you exceed number of CPUs. Runningghc --make -j20
on my machine makes things seriously worse: compilation time is longer than in non-parallel mode! -
The HaLVM status report, issue 1
One of the things we’re trying to get better about, here at HaLVM headquarters, is communicating with the wider HaLVM and unikernel communities. In particular, during those periods when we’re slowing building out upgrades, documents, or other things for the HaLVM, we tend to go silent.
-
Golang’s real-time GC in theory and practice
The system we have been building is a pub/sub message bus with an in-memory store of published messages. This version in Go is a rewrite of our first implementation in Haskell. We stopped work on our Haskell version in May, after discovering fundamental latency problems with GHC’s garbage collector.
-
Two years ago, I wrote a series of blog posts inspired by Oliver Charles’ 24 Days of Hackage, to highlight some of the great work which was being done in the PureScript community. That original series focused on library development, but this year I’ve decided to write a series of short blog posts to highlight some of the work being done on the compiler itself.
Thanks for reading! Let us know on Twitter if you liked this issue. Open an issue on GitHub if you think it could be better.


The maha khel in Maharashtra: A timeline
How the month-long political impasse ended dramatically on Saturday morning as Devendra Fadnavis returned as the chief minister -- backed by the Sharad Pawar-led NCP.
Maharashtra woke up on Saturday morning to a massive surprise as BJP's Devendra Fadnavis returned as the chief minister with NCP leader Ajit Pawar his deputy.
The month-long political impasse ended dramatically after Devendra Fadnavis took oath as the CM, backed by the Sharad Pawar-led NCP. Governor Bhagat Singh Koshyari administered the oath at the Raj Bhavan here at around 7.30 am. Live Updates here
What happened and how: Let's take a look
Sometime around 11.45 night - Ajit Pawar-BJP Deal finalised.
11.55 pm Friday - Fadnavis speaks to Party and requests for swearing-in before anyone in Sena-NCP-Congress comes to know and stakes claim.
12.30 am Saturday - Governor who was to travel out of Mumbai to New Delhi, cancels his travel
2.10 am - Secy to Governor told to submit revocation order at 5.47 and arrange swearing in at 6.30 a.m.
2.30 am - Secy informs he will submit file within two hours and advises 7.30 a.m. for swearing in as arrangements have to be made early on Saturday.
11.45 pm -on Friday till Saturady 9 a.m. - Ajit Pawar stays put with Fadnavis, not to go back till sworn in.
5.30 am - both Ajit and Fadnavis arrive at Raj Bhavan
President's Rule revoked at 5.47 am, but announced at 9 am.
7.50 am - Swearing in starts by Governor B.S. Koshyari
8.10 am - Big news breaks
8.40 am - PM Modi congratulates new CM and Dy CM
8.10 am - Reactions start pouring in


Tony Voorhees
is a multidisciplinary designer with a focus on producing web-based products and user-centered experiences. His areas of expertise include creative direction, interactive design, and UI/UX. He has worked in both agencies and startups, with brands such as DraftKings, NFL, NBA, MLB, UFC, Nascar, Dewars, Champion, Hanes, BBC, Chase, and Lincoln Finacial.


Introduction¶
puppet-php is a module for managing PHP using puppet.
Why Use puppet-php¶
- it’s very fast to install, a few minutes tops.
- it supports all PHP SAPIs out of the box.
- it supports a lot of PHP extensions out of the box.
- it’s is very flexible and has tons of configuration options, and sane defaults.
- it aims to stay out of your way, and if it happens to get in your way, you can change the undesired behavior very easily.
- it removes the boilerplate code from your manifests, which mean less code to maintain, and less code to spend time unit testing.
- it uses the MIT license.
Source code¶
The source can be found at github.com/jippi/puppet-php
License¶
The project is released under the permissive MIT license.
Bugs¶
If you happen to stumble upon a bug, please feel free to create a pull request with a fix (optionally with a test), and a description of the bug and how it was resolved.
You can also create an issue with a description to raise awareness of the bug.
Features¶
If you have a good idea for a feature, please join us on IRC and let’s discuss it. Pull requests are always more than welcome.
Support / Questions¶
You can find me on IRC in the #puppet channel on irc.freenode.net for any support or questions. My alias is Jippi


TEAM PROFILE
Montgomery Scott
Manager
Employee ID: 1
Email:
<EMAIL_ADDRESS>Office Number:<PHONE_NUMBER>
Geordi LaForge
Engineer
Employee ID: 2
Email:
<EMAIL_ADDRESS>GitHub:
chiefengineer1701D
B’elanna Torres
Engineer
Employee ID: 3
Email:
<EMAIL_ADDRESS>GitHub:
voyagerchief
Charles Tucker III
Engineer
Employee ID: 4
Email:
<EMAIL_ADDRESS>GitHub:
Tripnx01
Wesley Crusher
Intern
Employee ID: 5
Email:
<EMAIL_ADDRESS>School: Starfleet Academy


Steam pours from SpaceX Starship after model explodes during pressure testing
by Tim PearceSpaceX blew the top off its first Starship rocket while pressure testing it in Texas.
Steam poured from the busted prototype after it failed on Wednesday, sending its nose sailing through the air. The aerospace company, owned by Elon Musk, said that the result of the testing, while a minor setback, was not surprising.
"The purpose of today’s test was to pressurize systems to the max, so the outcome was not completely unexpected. There were no injuries, nor is this a serious setback," SpaceX said in a statement.
After the explosion, Musk said on Twitter that SpaceX would be moving away from the Mk1 design that failed pressure testing to the Mk3.
"This had some value as a manufacturing pathfinder, but flight design is quite different," Musk said.
SpaceX launched the Starship project to build a space shuttle capable of carrying as many as 100 people. The ship will be designed to travel to the moon and Mars and to be able to land and take off multiple times.
Musk said he plans to use the finished rocket to carry people to the moon and Mars to create colonies for humanity. The Starship was scheduled to begin test flights soon after the pressure test, but the explosion has delayed flight testing as company engineers create a better model.
SpaceX is currently constructing two other model Starships in a Florida facility.


Although, the performance of archiver I/O is not quite as critical as log file I/O, because it is performed in the background by ARCn, each log file must nevertheless be able to be archived comfortably within the amount of time that it takes LGWR to fill the remaining log files. Otherwise, redo generation will be suspended, which would be disastrous for performance.
The twin tuning strategies to prevent archival backlogs are
Archiver writes are logically sequential. However, unless redo generation is light, it is unwise to rely on archive writes being physically sequential as well. This is because LGWR can write faster than a single ARCn process can archive, and so it is often necessary to have multiple ARCn processes writing into the archive destination file systems at the same time. This makes the logically sequential I/O appear pseudo-random at the disk level.
There are lots of reasons why LGWR has an unfair advantage over ARCn. LGWR reads from memory, whereas ARCn has to read from disk. Also LGWR can write to raw log files, whereas ARCn must write to a file system. This often means that LGWR can perform asynchronous writes, but ARCn cannot. Also LGWR overwrites an existing file, whereas ARCn must continually extend the file it is writing. This involves significant file system space management overheads, which more than double the time taken to write the file.
So, if the rate of redo generation is moderate or heavy, it is easy for LGWR to write faster than ARCn can copy, even if ARCn is just copying the log files to a single archive destination. But ARCn's workload may be even greater if it needs to archive the log files to multiple destinations. This is because each log file is copied to all the archive destinations by a single ARCn process, even if multiple ARCn processes are available.
The key to configuring the archive destination file systems for fast archival is to use an extent-based file system mounted for direct I/O on dedicated striped and mirrored disks. The file systems must be extent-based and mounted for direct I/O to ensure that large writes are not normally split, and to minimize the impact of the file system space management overheads. Alternately, if a block-based file system must be used, the largest possible file system block size should be used.
If redo generation is light or moderate, a small stripe element size can be used to maximize the transfer rate of individual archive writes. This is based on the assumption that there will only rarely be more than one ARCn process active. In this case, the archive destinations should also be on dedicated disks, to preserve the sequential nature of the I/O when possible. If redo generation is heavy, such that there will commonly be more than one ARCn process active, then the stripe element size must be large relative to the size of archive writes (_log_archive_buffer_size) to maximize concurrency.
Where possible, data protection should be provided by hardware mirroring in order to minimize its impact. However, multiple archive destinations may be necessary if the files are being transmitted to a hot standby database. Multiple archive destinations should not however be preferred merely because it facilitates the taking of duplicate tape backups of the archived log files. With proper configuration, all modern backup solutions can be configured to take multiple tape backups of the archived log files from a single mirrored source.
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Enduro is extreme dirt bike racing, and David Knight has dominated the body and spirit-breaking
sport. This is his action-packed story, as determination turns ambition into World Championship
victory.
Enduro is extreme dirt bike racing, and David Knight has dominated the body and spirit-breaking sport.
This is his action-packed story, as determination turns ambition into World Championship victory.


Most lenders actually use a different way of calculating interest, called compound interest. In compound interest, rather than just taking a percentage of the amount once, interest is calculated regularly - every day, month, year, or some other unit of time. This causes interest to accumulate more rapidly, since you are taking a percentage not just of the original amount, but also of any interest that has already been added on.
in-context


Maya Hawke & Katherine Langford Show Off Their Stylish Sides at AMAs 2019!
Maya Hawke is all smiles as she arrives at the 2019 American Music Awards on Sunday (November 24) at the Microsoft Theater in Los Angeles.
The 21-year-old Stranger Things actress looked pretty in a black, sheer gown as she hit the red carpet.
PHOTOS: Check out the latest pics of Maya Hawke
Also in attendance was 13 Reasons Why star Katherine Langford, who wowed in a red gown for the awards show.
During the awards show, Katherine took to the stage with Knives Out co-star Jamie Lee Curtis to present the award for Collaboration of the Year to Shawn Mendes and Camila Cabello.
FYI: Katherine is wearing a Rodarte dress, Stuart Weitzman shoes, and Beladora jewelry. Maya is wearing Dior.
10+ pictures inside of Katherine Langford and Maya Hawke arriving at the awards show…


Introduction¶
Welcome to Mysterious Messenger, a messenger game created in Ren’Py. This guide was created to help users understand how the program works together, and how to take advantage of the various functions.
This guide is best used by navigating to the sections with the information you need as you need it rather than reading it from start-to-finish. Most sections have a line at the top that says “Example files to look at”; these will usually show the features described in the guide in action in the program itself. As much as possible, the code has been annotated to help you understand what’s happening in the program. Additionally, you’ll find plenty of code excerpts in this guide itself. They look like this:
## Sample code here
Most of these code excerpts are taken directly from the program itself and can be copied in to use for your own test purposes. Some sections will also have a “quick-start” guide at the beginning; they look like this:
A brief overview of the steps required (more detail below):
Step 1
Step 2
Step 2a
If you just need a quick reminder of what to do to get some code up and running, you can refer to this. If you need more detail, however, the rest of that section will explain further.
If you haven’t already, you should also play through the Tutorial Day in the program at least once to get a feel for what the program is capable of. Then, if you’re new to Ren’Py and/or to programming, you should take a look at the Beginner’s Guide, which will take you through the steps to make the first chatroom of a new route playable.


Roberto Ierusalimschy, Associate Professor, Computer Science Department, PUC-Rio.
Noemi Rodriguez, Associate Professor, Computer Science Department, PUC-Rio.
Ana Lúcia de Moura, Adjunct Professor, Computer Science Department, PUC-Rio.
Fabio Mascarenhas, Assistant Professor, Computer Science Department, UFRJ.
Francisco Sant'Anna, Ph.D., Post-doc at the Computer Science Department, PUC-Rio.
Hisham Muhammad, Ph.D. student at the Computer Science Department, PUC-Rio.
Hugo Gualandi, Ph.D. student at the Computer Science Department, PUC-Rio.
Pedro Tammela, undergraduate student (Computer Science) at PUC-Rio.
Anamaria Martins Moreira, Associate Professor, Computer Science Department, UFRJ.
Sérgio Medeiros, Adjunct Professor, School of Science and Technology, UFRN.
Bruno Silvestre, Adjunct Professor, UFG
André Murbach Maidl, Adjunct Professor, PUC-PR.
Adriano Branco, Ph.D., Post-doc at the Computer Sience Department, PUC-Rio.
Renato Maia, Ph.D., PUC-Rio.
Alexandre Skyrme, Ph.D., PUC-Rio.
Lourival Pereira Vieira Neto, M.Sc., PUC-Rio.
Tomás Guisasola, M.Sc., PUC-Rio.
Pablo Musa, M.Sc., PUC-Rio.
Etiene Dalcol, Software Engineering student at ENSTA Bretagne and PUC-Rio.
Alexandra Barros, M.Sc., PUC-Rio.
Marcelo Oikawa, M.Sc., PUC-Rio.
Felix Ribeiro, M.Sc. student at the Computer Science Department, PUC-Rio.
Leonardo Kaplan, undergraduate student (Computer Science) at PUC-Rio.
Ian Baldo, undergraduate student (Computer Engineering) at PUC-Rio.
Miguel Boing, undergraduate student (Computer Engineering) at PUC-Rio.
Handel Scholze, undergraduate student (Computer Engineering) at PUC-Rio.


Jose Mourinho 'gives rousing speech to Tottenham Hotspur squad'
Jose Mourinho reportedly gave a rousing speech in the dressing room after becoming Tottenham Hotspur manager on Wednesday.
by Leo NieboerThe 56-year-old returned to the Premier League after almost a year out of the game following the club's decision to part ways with Mauricio Pochettino.
Ahead of facing West Ham United at the London Stadium on Saturday, Mourinho took his first training session with the Spurs squad on Wednesday afternoon.
According to Record, Mourinho made a point of giving the players an impassioned speech ahead of the trip to East London.
The Portuguese boss is said to have told players that he would be "your father, friend, girlfriend, whatever you want."
Moreover, Mourinho emphasised to the players that they were a lot better than their standing of 14th in the Premier League table suggests.
body check tags ::


{% extends "base.html" %} {% block content %}
| List of Orders (ID) |
|---|
| / |
| / |
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy
text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book.
It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged.
It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages,
and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy
text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book.
It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged.
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book.


Storing key-value pairs in Butler
The key-value (=KV) feature in Butler is a basic variant of the more complex KV databases available out there, with etcd, Apache Ignite and memcached being popular open source options. All the major cloud providers also have their own KV database products.
Butler’s KV features are basic, yet very useful in the context of Qlik Sense. The only assumptions are:
- You have a value you want to store for some time outside of your Sense app.
- There is a unique key for each value you want to store.
Put differently: Think of Butler’s KV store as a way to stash away some values, then get them back later when they are needed again.
Each KV pair is associated with a namespace. Namespaces are simply a way to categorize KV pairs.
Remember
Both key and value are strings in Butler’s KV store. You must thus make sure to convert your data to strings before creating or updating a KV pair.There is also an optional, per KV-pair Time To Live (TTL) feature. If used it will auto-delete the KV pair when a certain time has passed from the KV-pair’s last update.
The API docs shows what methods are available to work with KV pairs.
How can a key-value store be used in Sense apps?
As mentioned above - A KV store can be useful whenever you need to stash data away for a while and then get it back. I.e. keeping track of the state of something.
For example
-
Easily pass parameters beteen apps in a reload chain Let’s assume data is created when appA reloads as part of an hourly reload schedule. That data is needed in appB, which is triggered to reload when appA finishes its reload. But how do you get the data from appA to appB?
Historically you solve this by writing the data to a temporary QVD or CSV file. This still works of course, but if it’s only some dimensional value that needs to be passed, a KV store might be a cleaner option.
-
Keep a time limited state The TTL feature is useful to keep things tidy. If you know for sure that your KV pair only needs to be stored for a limited time, it’s good practice to either delete it when its no longer needed, or set a TTL when the KV pair is first created.
This way you keep the KV namespaces relevant and reasonable in size.
-
Use app IDs as namespace names If you need to keep state between successive reloads of a particular app, you can use the app ID as namespace. That way it will be very clear which a specific KV pair belongs to.
-
Keep track of what users should be notified after an app reload is complete Let’s say you have a button in an app that when clicked kicks of a reload of the app (or some other app). Let’s also assume several users might be interested in triggering a refresh of this dataset.
By pushing each user’s username to a KV namespace when they request the data refresh (by clicking that button in the app), it’s possible to notify them using Teams, Slack, email etc as the last step of the app’s reload script (i.e. when the app ist just about done refreshing the data).
The effect is a solution where users can request a data refresh and be notified when the new data is available.
-
Keeping state in visualisation extensions Extensions are built using Javascript, and they can thus also make use of the KV store.
There might be times when several extension instances in an app need to keep in sync or share some state - a KV store might be useful there.
The KV store could even allow an extension to share state with its siblings in other Sense apps.
Persistence of key-value data
As of current Butler version (v4.0), KV pairs are not persisted to disk.
Is this good or bad? It depends:
- Good as it reduces complexity in Butler.
- Bad as all KV pairs are lost when Butler is restarted. Now, Butler tends to be very stable, so spontaneous restarts are usually not a problem. But the flushing of all KV data is still something to consider when for example upgrading Butler to new versions.


By Roel Verbunt | Project GitHub
User Stories: I can submit a FormData object that includes a file upload. When I submit something, I will receive the file size in bytes within the JSON response
{ }


Preparation time
overnight
Cooking time
1 to 2 hours
Serves
Serves 4
These gently spiced deep-fried crabs make a fantastic starter - especially with zingy homemade lime pickle.
For the lime pickle, toss the lime wedges with the salt in a large bowl. Cover the bowl and chill in the fridge for 48 hours, stirring occasionally.
When the limes have cured, heat the oil in a large frying pan over a high heat. Add the mustard seeds. (Caution: The mustard seeds will pop - keep eyes and face well clear.)
When the mustard seeds start popping, add the garlic and ginger and stir-fry for 1-2 minutes.
Add the cumin, coriander, asafoetida and chilli powder and stir-fry for a further 1-2 minutes, then add the sugar and continue to cook until it melts.
Add the cured limes and all of the juices from the bowl to the pan. Cover with the white wine vinegar and 200ml/7fl oz of cold water.
Bring the pan contents to the boil, then reduce the heat until the mixture is simmering and simmer gently for 1½ hours until the mixture has thickened and the limes are very soft. Set aside to cool slightly.
Blend the cooled lime pickle in a food processor for 20 seconds, or until the pieces of lime are quite small. Spoon the pickle into sterilised jars until needed.
For the crab, mix all of the crab ingredients except the crabs and vegetable oil in a large bowl until well combined as a thick paste.
Add the crabs and mix again until the crabs are coated in the spicy mixture. Cover the bowl and chill in the fridge for at least two hours.
Before cooking, remove the crabs from the fridge and return to room temperature.
Heat the vegetable oil in a deep fat fryer to 160C/315F. Alternatively, heat the vegetable oil in a deep, heavy-based sauté pan until a breadcrumb sizzles and turns brown when dropped into it. (Caution: Hot oil can be dangerous. Do not leave unattended.)
Fry the spiced crabs (in batches if necessary) in the hot oil for 1-2 minutes, or until cooked through. Remove from the oil using a slotted spoon, then set aside to drain on kitchen paper. Season with a little salt.
Serve the spiced soft-shell crabs with dollops of the lime pickle.


8MM
Reviewed by Harvey Karten, Ph.D. Columbia Pictures Director: Joel Schumacher Writer: Andrew Kevin Walker Cast: Nicolas Cage, Joaquin Phoenix, James Gandolfini, Peter Stomare, Anthony Heald, Catherine Keener
If you found a porno tape discarded in the trash, would you take it home and screen it? Destroy it so that no one could do so? Would you instead take it right to the police? Would you simply pass it by? The chances are that whatever you answer, you could not justifiably be labeled a pervert for your curiosity. But now take another situation. You see in the trash what looks like a snuff film. What would you do? For the more pristine among us, let it be known that a snuff film takes s&m to its extreme. Such a work depicts the actual brutalization and murder of a woman at the hands of one or more sadistic men. From what I hear, the vast majority and perhaps all snuff films in existence are fakes. Given the ability of today's movie technology to do just about anything you want it to, it would be no difficult matter to feign a sadistic killing and to pay the "victim" for her role. After all, why show the real thing if nobody can really take a fake from the McCoy? Simple: there are people out there willing to pay big bucks to witness actual murders close up, and then to pocket the film for future viewing.
After you see this new psychological thriller featuring Nicolas Cage and directed by Joel Schumacher ("The Client," "A Time to Kill"), you could not be blamed if you decided to do absolutely nothing but to get as far away from a snuff clip as you can. Tom Welles (Nicolas Cage), a private investigator, chose otherwise, and got himself and a number of others into a heap of trouble, almost destroying his marriage and losing his life in the bargain. Though he emerges a hero, he treads way over the line of duty. Any rational person in his shoes would have turned his situation over to the police, but in this taut story penned by Andrew Kevin Walker ("Seven"), Welles becomes obsessed with what is easily the most exotic and dangerous case he has handled.
The first person who should have let sleeping dogs lie is the fabulously wealthy Mrs. Christian (Myra Carter) who upon her husband's death discovers a small reel of 8 millimeter film in his wall safe. The film depicts the violent death of a 16-old-girl by a masked sadist, who beats her and then plunges a knife into her chest in order to capture the girl's look of absolute terror at the moment of impact. (Yes, Virginia, apparently there are people who get off on this sort of thing.) The wheelchair-bound widow hasn't the foggiest idea what the film is doing in her late husband's possession, and hires Welles to find out whether the murder was actual or simulated. Treating the situation as a missing persons case, Welles discovers the identity of the victim, interviews the girl's mother, Mrs. Mathews (Amy Morton), travels from his Harrisburg, Pennsylvania home to the runaway teen's Hollywood destination, and becomes immersed in every level of the porno industry. He buddies up with a smart, adult bookstore clerk, Max California (Joaquin Phoenix), and ultimately exchanges details of the case with some of the sleaziest individuals seen on the screen since scripter Andrew Kevin Walker's depravity-bathed movie "Seven."
"8mm" starts calmly as though Tom Welles were a modern Perry Mason rationally investigating a predicament, but director Joel Schumacher steadily turns on the tension as the obsessed Welles sinks deeply into the muck of the underground porn distributors. As Welles meets such dirt bags as Dino Velvet (Peter Stomare), the artistic director of the snuff works; Eddie Poole (James Gandolfini), whose studio deals in the films; and Machine (Chris Bauer), a black- hooded individual who performs the alleged murders--we in the audience are left to ponder Welles' motivation for risking his neck over a complete stranger who may not even be dead. Does he see his own baby daughter, or even his concerned and frightened wife Amy (Catherine Keener) as a potential victim of these vermin? Or does he become himself turned on by the intrigue of the seedy industry?
"8mm" is for an audience that relished David Fincher's 1995 movie "Seven," which featured a striking cast including Brad Pitt, Morgan Freeman, Kevin Spacey and Gwyneth Paltrow. "8mm" s not as well crafted as screenwriter Walker's previous film, which was exceptionally organized as a search for a serial killer out to punish those who commit one or more of the seven deadly sins. But it's virtually as unsettling, considerably more violent, and likewise appears to wallow in human depravity. Nicolas Cage, whose career took off after portrayals of eccentric characters in offbeat movies like "Raising Arizona" and "Moonstruck," is appropriately called one of the great actors of his generation (he's 34). Said to have had two of his teeth pulled for his role in "Birdy," swallowed a live cockroach for his part in "Vampire's Kills," and slashed his arm while preparing to take on "Racing with the Moon," he is the ideal choice to portray the intensity of a man obsessed with finding a killer and making the acquaintance of men on whose sight you'd not hesitate to cross the street. He is ably paired with the California porn industry's only good-guy, played by Joaquim Phoenix as a guy who reluctantly takes a gig selling sleaze but who reads Truman Capote disguised within a porno paperback cover.
Cage becomes as violent as Mel Gibson's Porter in Brian Helgeland's "Payback," and features one off-the-wall filmmaker played by Peter Stomare (an expert with the crossbow who takes pride in directing teen murder) and the owner of a film company played by James Gandolfini who self-destructively curses a man bent on revenge, daring him to pull the trigger. As though the on-screen violence is insufficient to get the audience juices flowing, Mychael Danna raises the intensity with an unusual score featuring Middle Eastern music at one point. Photographer Robert Elswit keeps us in the dark a good deal of the time, particularly when demonstrating the nitty gritty, but puts outdoor Hollywood in a coarse light to signal its spunkier side.
Those of us who want to see a major statement promulgated by the film will point to the latest incidents of man's inhumanity to man--in Kosovo, in Bosnia, in Sierra Leone--butchery that appears to be done for its own sake, for the pleasure it brings to the killers. Others will see "8mm" as a popcorn flick, yet another effective and furious product from Hollywood's dream factory. In either case, consider leaving grandma home this time around.
Rated R. Running Time: 122 minutes. (C) 1999 Harvey Karten
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netcdf − Unidata’s Network Common Data Form (netCDF) library interface
#include "netcdf.h"
cc ... -lnetcdf -lhdf5_hl -lhdf5 -lz -lm
Complete documentation for the netCDF libraries can be found at the netCDF website: http://www.unidata.ucar.edu/software/netcdf/.
This document describes versions 3 and 4 of Unidata netCDF data-access interface for the C programming language.
|
const char* nc_inq_libvers() |
Returns a string identifying the version of the netCDF library, and when it was built, like: "3.1a of Aug 22 1996 12:57:47 $".
The RCS ident(1) command will find a string like "$Id: @(#) netcdf library version 3.1a of Sep 6 1996 15:56:26 $" in the library. The SCCS what(1) command will find a string like "netcdf library version 3.1a of Aug 23 1996 16:07:40 $".
All netCDF functions (except nc_inq_libvers() and nc_strerror()) return an integer status.
If this returned status value is not equal to NC_NOERR (zero), it indicates that an error occurred. The possible status values are defined in system include file <errno.h> and in "netcdf.h".
|
const char* nc_strerror(int status) |
Returns a string textual translation of the status value, like "Attribute or variable name contains illegal characters" or "No such file or directory".
|
int nc_create(const char path[], int cmode, int* ncid) |
Creates a new netCDF dataset at path, returning a netCDF ID in ncid. The argument cmode may include the bitwise-or of the following flags: NC_NOCLOBBER to protect existing datasets (default silently blows them away), NC_SHARE for synchronous dataset updates for classic format files (default is to buffer accesses),
When a netCDF dataset is created, is is opened NC_WRITE. The new netCDF dataset is in define mode. NC_64BIT_OFFSET. to create a file in the 64-bit offset format (as opposed to classic format, the default). NC_TRUE to create a netCDF-4/HDF5 file, and NC_CLASSIC_MODEL to guarantee that netCDF-4/HDF5 files maintain compatibility with the netCDF classic data model.
|
int nc__create(const char path[], int cmode, size_t initialsize, size_t* chunksize, int* ncid) |
Like nc_create() but has additional performance tuning parameters.
The argument initialsize sets the initial size of the file at creation time.
See nc__open() below for an explanation of the chunksize parameter.
|
int nc_open(const char path[], int mode, int* ncid) |
(Corresponds to ncopen() in version 2)
Opens a existing netCDF dataset at path returning a netCDF ID in ncid. The type of access is described by the mode parameter, which may include the bitwise-or of the following flags: NC_WRITE for read-write access (default read-only), NC_SHARE for synchronous dataset updates (default is to buffer accesses), and NC_LOCK (not yet implemented).
As of NetCDF version 4.1, and if TRUE support was enabled when the NetCDF library was built, the path parameter may specify a TRUE URL. In this case, the access mode is forced to be read-only.
|
int nc__open(const char path[], int mode, size_t* chunksize, int* ncid) |
Like nc_open() but has an additional performance tuning parameter.
The argument referenced by chunksize controls a space versus time tradeoff, memory allocated in the netcdf library versus number of system calls. Because of internal requirements, the value may not be set to exactly the value requested. The actual value chosen is returned by reference. Using the value NC_SIZEHINT_DEFAULT causes the library to choose a default. How the system choses the default depends on the system. On many systems, the "preferred I/O block size" is available from the stat() system call, struct stat member st_blksize. If this is available it is used. Lacking that, twice the system pagesize is used. Lacking a call to discover the system pagesize, we just set default chunksize to 8192.
The chunksize is a property of a given open netcdf descriptor ncid, it is not a persistent property of the netcdf dataset.
As with nc__open(), the path parameter may specify a TRUE URL, but the tuning parameters are ignored.
|
int nc_redef(int ncid) |
(Corresponds to ncredef() in version 2)
Puts an open netCDF dataset into define mode, so dimensions, variables, and attributes can be added or renamed and attributes can be deleted.
|
int nc_enddef(int ncid) |
(Corresponds to ncendef() in version 2)
Takes an open netCDF dataset out of define mode. The changes made to the netCDF dataset while it was in define mode are checked and committed to disk if no problems occurred. Some data values may be written as well, see "VARIABLE PREFILLING" below. After a successful call, variable data can be read or written to the dataset.
|
int nc__enddef(int ncid, size_t h_minfree, size_t v_align, size_t v_minfree, size_t r_align) |
Like nc_enddef() but has additional performance tuning parameters.
Caution: this function exposes internals of the netcdf version 1 file format. It may not be available on future netcdf implementations.
The current netcdf file format has three sections, the "header" section, the data section for fixed size variables, and the data section for variables which have an unlimited dimension (record variables). The header begins at the beginning of the file. The index (offset) of the beginning of the other two sections is contained in the header. Typically, there is no space between the sections. This causes copying overhead to accrue if one wishes to change the size of the sections, as may happen when changing names of things, text attribute values, adding attributes or adding variables. Also, for buffered i/o, there may be advantages to aligning sections in certain ways.
The minfree parameters allow one to control costs of future calls to nc_redef(), nc_enddef() by requesting that minfree bytes be available at the end of the section. The h_minfree parameter sets the pad at the end of the "header" section. The v_minfree parameter sets the pad at the end of the data section for fixed size variables.
The align parameters allow one to set the alignment of the beginning of the corresponding sections. The beginning of the section is rounded up to an index which is a multiple of the align parameter. The flag value NC_ALIGN_CHUNK tells the library to use the chunksize (see above) as the align parameter. The v_align parameter controls the alignment of the beginning of the data section for fixed size variables. The r_align parameter controls the alignment of the beginning of the data section for variables which have an unlimited dimension (record variables).
The file format requires mod 4 alignment, so the align parameters are silently rounded up to multiples of 4. The usual call, nc_enddef(ncid) is equivalent to nc__enddef(ncid, 0, 4, 0, 4).
The file format does not contain a "record size" value, this is calculated from the sizes of the record variables. This unfortunate fact prevents us from providing minfree and alignment control of the "records" in a netcdf file. If you add a variable which has an unlimited dimension, the third section will always be copied with the new variable added.
|
int nc_sync(int ncid) |
(Corresponds to ncsync() in version 2)
Unless the NC_SHARE bit is set in nc_open() or nc_create(), accesses to the underlying netCDF dataset are buffered by the library. This function synchronizes the state of the underlying dataset and the library. This is done automatically by nc_close() and nc_enddef().
|
int nc_abort(int ncid) |
(Corresponds to ncabort() in version 2)
You don’t need to call this function. This function is called automatically by nc_close() if the netCDF was in define mode and something goes wrong with the commit. If the netCDF dataset isn’t in define mode, then this function is equivalent to nc_close(). If it is called after nc_redef(), but before nc_enddef(), the new definitions are not committed and the dataset is closed. If it is called after nc_create() but before nc_enddef(), the dataset disappears.
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int nc_close(int ncid) |
(Corresponds to ncclose() in version 2)
Closes an open netCDF dataset. If the dataset is in define mode, nc_enddef() will be called before closing. After a dataset is closed, its ID may be reassigned to another dataset.
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int nc_inq(int ncid, int* ndims, int* nvars, int* natts, int* unlimdimid) | |
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int nc_inq_ndims(int ncid, int* ndims) | |
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int nc_inq_nvars(int ncid, int* nvars) | |
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int nc_inq_natts(int ncid, int* natts) | |
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int nc_inq_unlimdim(int ncid, int* unlimdimid) | |
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int nc_inq_format(int ncid, int* formatn) |
Use these functions to find out what is in a netCDF dataset. Upon successful return, ndims will contain the number of dimensions defined for this netCDF dataset, nvars will contain the number of variables, natts will contain the number of attributes, and unlimdimid will contain the dimension ID of the unlimited dimension if one exists, or -1 otherwise. formatn will contain the version number of the dataset <format>, one of NC_FORMAT_CLASSIC, NC_FORMAT_64BIT, NC_FORMAT_NETCDF4, or NC_FORMAT_NETCDF4_CLASSIC. If any of the return parameters is a NULL pointer, then the corresponding information will not be returned; hence, no space need be allocated for it.
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int nc_def_dim(int ncid, const char name[], size_t len, int* dimid) |
(Corresponds to ncdimdef() in version 2)
Adds a new dimension to an open netCDF dataset, which must be in define mode. name is the dimension name. If dimid is not a NULL pointer then upon successful completion dimid will contain the dimension ID of the newly created dimension.
Users many define types for a netCDF-4/HDF5 file (unless the NC_CLASSIC_MODEL was used when the file was creates). Users may define compound types, variable length arrays, enumeration types, and opaque types.
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int nc_def_compound(int ncid, size_t size, const char name[], int* typeidp) |
Define a compound type.
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int nc_insert_compound(int ncid, nc_type , const char name[], size_t offset, nc_type field_typeid) |
Insert an element into a compound type. May not be done after type has been used, or after the type has been written by an enddef.
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int nc_insert_array_compound(int ncid, nc_type , const char name[], size_t offset, nc_type field_typeid, int ndims, const int dim_sizes[]) |
Insert an array into a compound type.
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int nc_inq_type(int ncid, nc_type , char name[], size_t* sizep) |
Learn about a type.
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int nc_inq_compound(int ncid, nc_type , char name[], size_t* sizep, size_t* nfieldsp) | |
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int nc_inq_compound_name(int ncid, nc_type , char name[]) | |
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int nc_inq_compound_size(int ncid, nc_type , size_t* sizep) | |
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int nc_inq_compound_nfields(int ncid, nc_type , size_t* nfieldsp) | |
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int nc_inq_compound_fieldname(int ncid, nc_type , int fieldid, char name[]) | |
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int nc_inq_compound_fieldindex(int ncid, nc_type , const char name[], int* fieldidp) | |
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int nc_inq_compound_fieldoffset(int ncid, nc_type , int fieldid, size_t* offsetp) | |
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int nc_inq_compound_fieldtype(int ncid, nc_type , int fieldid, nc_type* field_typeid) | |
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int nc_inq_compound_fieldndims(int ncid, nc_type , int fieldid, int* ndims) | |
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int nc_inq_compound_fielddim_sizes(int ncid, nc_type , int fieldid, int dim_sizes[]) |
Learn about a compound type.
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int nc_def_vlen(int ncid, const char name[], nc_type base_typeid, nc_type* xtypep) |
Create a varaible length array type.
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int nc_inq_vlen(int ncid, nc_type , char name[], size_t* datum_sizep, nc_type* base_nc_typep) |
Learn about a varaible length array type.
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int nc_free_vlen(nc_vlen_t *vl) |
Free memory comsumed by reading data of a varaible length array type.
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int nc_put_vlen_element(int ncid, nc_type , void * vlen_element, size_t len, void * data) |
Write one VLEN.
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int nc_get_vlen_element(int ncid, nc_type , void ** vlen_element, size_t len, void ** data) |
Read one VLEN.
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int nc_free_string(size_t len, char **data) |
Free memory comsumed by reading data of a string type.
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int nc_inq_user_type(int ncid, nc_type , char name[], size_t* , nc_type* , size_t* , int* ) |
Learn about a user define type.
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int nc_def_enum(int ncid, nc_type base_typeid, const char name[], nc_type* typeidp) |
Define an enumeration type.
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int nc_insert_enum(int ncid, nc_type base_typeid, const char name[], const void *value) |
Insert a name-value pair into enumeration type.
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int nc_inq_enum_member(int ncid, nc_type xtype, int idx, char name[], void *value) | |
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int nc_inq_enum_ident(int ncid, nc_type xtype, int idx, long long value, char identifier[]) |
Learn about a name-value pair into enumeration type.
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int nc_def_opaque(int ncid, size_t size, const char name[], nc_type* xtypep) |
Create an opaque type.
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int nc_inq_opaque(int ncid, nc_type xtype, char name[], size_t* sizep) |
Learn about opaque type.
Users may organize data into hierarchical groups in netCDF-4/HDF5 files (unless NC_CLASSIC_MODEL was used when creating the file).
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int nc_inq_grps(int ncid, int* numgrps, int ncids[]) |
Learn how many groups (and their ncids) are available from the group represented by ncid.
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int nc_inq_grpname(int ncid, char name[]) | |
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int nc_inq_grpname_full(int ncid, size_t* len, char name[]) | |
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int nc_inq_grpname_len(int ncid, size_t* len) | |
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int nc_inq_grp_parent(int ncid, int* ncid) | |
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int nc_inq_grp_ncid(int ncid, char name[], int* ncid) | |
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int nc_inq_full_ncid(int ncid, char name[], int* ncid) |
Learn about a group.
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int nc_inq_varids(int ncid, int* nvars, int* ) |
Get the varids in a group.
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int nc_inq_dimids(int ncid, int* ndims, int* dimids, int include_parents) |
Get the dimids in a group and (potentially) its parents.
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int nc_inq_typeids(int ncid, int* ntypes, int typeids[]) |
Get the typeids of user-defined types in a group.
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int nc_def_grp(int ncid, char name[], int* ncid) |
Create a group.
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int nc_inq_dimid(int ncid, const char name[], int* dimid) |
(Corresponds to ncdimid() in version 2)
Given a dimension name, returns the ID of a netCDF dimension in dimid.
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int nc_inq_dim(int ncid, int dimid, char name[], size_t* len) | |
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int nc_inq_dimname(int ncid, int dimid, char name[]) | |
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int nc_inq_dimlen(int ncid, int dimid, size_t* len) |
Use these functions to find out about a dimension. If either the name argument or len argument is a NULL pointer, then the associated information will not be returned. Otherwise, name should be big enough (NC_MAX_NAME) to hold the dimension name as the name will be copied into your storage. The length return parameter, len will contain the size of the dimension. For the unlimited dimension, the returned length is the current maximum value used for writing into any of the variables which use the dimension.
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int nc_rename_dim(int ncid, int dimid, const char name[]) |
(Corresponds to ncdimrename() in version 2)
Renames an existing dimension in an open netCDF dataset. If the new name is longer than the old name, the netCDF dataset must be in define mode. You cannot rename a dimension to have the same name as another dimension.
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int nc_def_var(int ncid, const char name[], nc_type xtype, int ndims, const int dimids[], int* varid) |
(Corresponds to ncvardef() in version 2)
Adds a new variable to a netCDF dataset. The netCDF must be in define mode. If not NULL, then varid will be set to the netCDF variable ID.
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int nc_inq_varid(int ncid, const char name[], int* varid) |
(Corresponds to ncvarid() in version 2)
Returns the ID of a netCDF variable in varid given its name.
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int nc_inq_var(int ncid, int varid, char name[], nc_type* xtype, int* ndims, int dimids[], int* natts) | |
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int nc_inq_varname(int ncid, int varid, char name[]) | |
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int nc_inq_vartype(int ncid, int varid, nc_type* xtype) | |
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int nc_inq_varndims(int ncid, int varid, int* ndims) | |
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int nc_inq_vardimid(int ncid, int varid, int dimids[]) | |
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int nc_inq_varnatts(int ncid, int varid, int* natts) |
Returns information about a netCDF variable, given its ID. If any of the return parameters (name, xtype, ndims, dimids, or natts) is a NULL pointer, then the corresponding information will not be returned; hence, no space need be allocated for it.
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int nc_rename_var(int ncid, int varid, const char name[]) |
(Corresponds to ncvarrename() in version 2)
Changes the name of a netCDF variable. If the new name is longer than the old name, the netCDF must be in define mode. You cannot rename a variable to have the name of any existing variable.
The following functions may only be used on variables in a netCDF-4/HDF5 data file. These functions must be called after the variable is defined, but before an enddef call.
int nc_def_var_deflate(int ncid, int varid, int shuffle, int deflate, int deflate_level)
Turn on compression and/or shuffle filter. (Shuffle filter is only useful for integer data.)
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int nc_inq_var_deflate(int ncid, int varid, int* shufflep, int* deflatep, int* deflate_levelp) |
Learn about a variable’s deflate settings.
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int nc_def_var_fletcher32(int ncid, int varid, int fletcher32) |
Turn on checksumming for a variable.
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int nc_inq_var_fletcher32(int ncid, int varid, int* fletcher32) |
Learn about checksumming for a variable.
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int nc_def_var_chunking(int ncid, int varid, int storage, const size_t chunksizesp[]) |
Set chunksizes for a variable.
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int nc_inq_var_chunking(int ncid, int varid, int* storagep, size_t chunksizesp[]) |
Learn about chunksizes for a variable.
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int nc_def_var_fill(int ncid, int varid, int no_fill, const size_t chunksizesp[]) |
Set a fill value for a variable.
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int nc_inq_var_fill(int ncid, int varid, int* storagep, size_t chunksizesp[]) |
Learn the fill value for a variable.
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int nc_def_var_endian(int ncid, int varid, int endian) |
Set endianness of variable.
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int nc_inq_var_endian(int ncid, int varid, int* endianp) |
Learn the endianness of a variable.
Writes an entire netCDF variable (i.e. all the values). The netCDF dataset must be open and in data mode. The type of the data is specified in the function name, and it is converted to the external type of the specified variable, if possible, otherwise an NC_ERANGE error is returned. Note that rounding is not performed during the conversion. Floating point numbers are truncated when converted to integers.
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int nc_get_var_text(int ncid, int varid, char in[]) | |
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int nc_get_var_uchar(int ncid, int varid, unsigned char in[]) | |
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int nc_get_var_schar(int ncid, int varid, signed char in[]) | |
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int nc_get_var_short(int ncid, int varid, short in[]) | |
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int nc_get_var_int(int ncid, int varid, int in[]) | |
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int nc_get_var_long(int ncid, int varid, long in[]) | |
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int nc_get_var_float(int ncid, int varid, float in[]) | |
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int nc_get_var_double(int ncid, int varid, double in[]) | |
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int nc_get_var_ubyte(int ncid, int varid, unsigned char in[]) | |
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int nc_get_var_ushort(int ncid, int varid, unsigned short in[]) | |
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int nc_get_var_uint(int ncid, int varid, unsigned int in[]) | |
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int nc_get_var_int64(int ncid, int varid, long long in[]) | |
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int nc_get_var_uint64(int ncid, int varid, unsigned long long in[]) | |
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int nc_get_var_string(int ncid, int varid, char * in[]) |
Reads an entire netCDF variable (i.e. all the values). The netCDF dataset must be open and in data mode. The data is converted from the external type of the specified variable, if necessary, to the type specified in the function name. If conversion is not possible, an NC_ERANGE error is returned.
Puts a single data value into a variable at the position index of an open netCDF dataset that is in data mode. The type of the data is specified in the function name, and it is converted to the external type of the specified variable, if possible, otherwise an NC_ERANGE error is returned.
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int nc_get_var1_text(int ncid, int varid, const size_t index[], char* in) | |
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int nc_get_var1_uchar(int ncid, int varid, const size_t index[], unsigned char* in) | |
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int nc_get_var1_schar(int ncid, int varid, const size_t index[], signed char* in) | |
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int nc_get_var1_short(int ncid, int varid, const size_t index[], short* in) | |
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int nc_get_var1_int(int ncid, int varid, const size_t index[], int* in) | |
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int nc_get_var1_long(int ncid, int varid, const size_t index[], long* in) | |
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int nc_get_var1_float(int ncid, int varid, const size_t index[], float* in) | |
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int nc_get_var1_double(int ncid, int varid, const size_t index[], double* in) | |
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int nc_get_var1_ubyte(int ncid, int varid, const size_t index[], unsigned char* in) | |
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int nc_get_var1_ushort(int ncid, int varid, const size_t index[], unsigned short* in) | |
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int nc_get_var1_uint(int ncid, int varid, const size_t index[], unsigned int* in) | |
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int nc_get_var1_int64(int ncid, int varid, const size_t index[], long long* in) | |
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int nc_get_var1_uint64(int ncid, int varid, const size_t index[], unsigned long long* in) | |
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int nc_get_var1_string(int ncid, int varid, const size_t index[], char ** in) |
Gets a single data value from a variable at the position index of an open netCDF dataset that is in data mode. The data is converted from the external type of the specified variable, if necessary, to the type specified in the function name. If conversion is not possible, an NC_ERANGE error is returned.
Writes an array section of values into a netCDF variable of an open netCDF dataset, which must be in data mode. The array section is specified by the start and count vectors, which give the starting index and count of values along each dimension of the specified variable. The type of the data is specified in the function name and is converted to the external type of the specified variable, if possible, otherwise an NC_ERANGE error is returned.
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int nc_get_vara_text(int ncid, int varid, const size_t start[], const size_t count[], char in[]) | |
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int nc_get_vara_uchar(int ncid, int varid, const size_t start[], const size_t count[], unsigned char in[]) | |
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int nc_get_vara_schar(int ncid, int varid, const size_t start[], const size_t count[], signed char in[]) | |
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int nc_get_vara_short(int ncid, int varid, const size_t start[], const size_t count[], short in[]) | |
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int nc_get_vara_int(int ncid, int varid, const size_t start[], const size_t count[], int in[]) | |
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int nc_get_vara_long(int ncid, int varid, const size_t start[], const size_t count[], long in[]) | |
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int nc_get_vara_float(int ncid, int varid, const size_t start[], const size_t count[], float in[]) | |
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int nc_get_vara_double(int ncid, int varid, const size_t start[], const size_t count[], double in[]) | |
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int nc_get_vara_ubyte(int ncid, int varid, const size_t start[], const size_t count[], unsigned char in[]) | |
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int nc_get_vara_ushort(int ncid, int varid, const size_t start[], const size_t count[], unsigned short in[]) | |
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int nc_get_vara_uint(int ncid, int varid, const size_t start[], const size_t count[], unsigned int in[]) | |
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int nc_get_vara_int64(int ncid, int varid, const size_t start[], const size_t count[], long long in[]) | |
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int nc_get_vara_uint64(int ncid, int varid, const size_t start[], const size_t count[], unsigned long long in[]) | |
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int nc_get_vara_string(int ncid, int varid, const size_t start[], const size_t count[], char * in[]) |
Reads an array section of values from a netCDF variable of an open netCDF dataset, which must be in data mode. The array section is specified by the start and count vectors, which give the starting index and count of values along each dimension of the specified variable. The data is converted from the external type of the specified variable, if necessary, to the type specified in the function name. If conversion is not possible, an NC_ERANGE error is returned.
These functions are used for strided output, which is like the array section output described above, except that the sampling stride (the interval between accessed values) is specified for each dimension. For an explanation of the sampling stride vector, see COMMON ARGUMENTS DESCRIPTIONS below.
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int nc_get_vars_text(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], char in[]) | |
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int nc_get_vars_uchar(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], unsigned char in[]) | |
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int nc_get_vars_schar(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], signed char in[]) | |
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int nc_get_vars_short(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], short in[]) | |
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int nc_get_vars_int(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], int in[]) | |
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int nc_get_vars_long(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], long in[]) | |
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int nc_get_vars_float(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], float in[]) | |
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int nc_get_vars_double(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], double in[]) | |
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int nc_get_vars_ubyte(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], unsigned char in[]) | |
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int nc_get_vars_ushort(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], unsigned short in[]) | |
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int nc_get_vars_uint(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], unsigned int in[]) | |
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int nc_get_vars_int64(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], long long in[]) | |
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int nc_get_vars_uint64(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], unsigned long long in[]) | |
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int nc_get_vars_string(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], char * in[]) |
These functions are used for strided input, which is like the array section input described above, except that the sampling stride (the interval between accessed values) is specified for each dimension. For an explanation of the sampling stride vector, see COMMON ARGUMENTS DESCRIPTIONS below.
These functions are used for mapped output, which is like strided output described above, except that an additional index mapping vector is provided to specify the in-memory arrangement of the data values. For an explanation of the index mapping vector, see COMMON ARGUMENTS DESCRIPTIONS below.
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int nc_get_varm_text(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], imap, char in[]) | |
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int nc_get_varm_uchar(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], imap, unsigned char in[]) | |
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int nc_get_varm_schar(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], imap, signed char in[]) | |
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int nc_get_varm_short(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], imap, short in[]) | |
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int nc_get_varm_int(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], imap, int in[]) | |
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int nc_get_varm_long(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], imap, long in[]) | |
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int nc_get_varm_float(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], imap, float in[]) | |
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int nc_get_varm_double(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], imap, double in[]) | |
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int nc_get_varm_ubyte(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], imap, unsigned char in[]) | |
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int nc_get_varm_ushort(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], imap, unsigned short in[]) | |
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int nc_get_varm_uint(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], imap, unsigned int in[]) | |
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int nc_get_varm_int64(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], imap, long long in[]) | |
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int nc_get_varm_uint64(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], imap, unsigned long long in[]) | |
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int nc_get_varm_string(int ncid, int varid, const size_t start[], const size_t count[], const size_t stride[], imap, char * in[]) |
These functions are used for mapped input, which is like strided input described above, except that an additional index mapping vector is provided to specify the in-memory arrangement of the data values. For an explanation of the index mapping vector, see COMMON ARGUMENTS DESCRIPTIONS below.
Unlike variables, attributes do not have separate functions for defining and writing values. This family of functions defines a new attribute with a value or changes the value of an existing attribute. If the attribute is new, or if the space required to store the attribute value is greater than before, the netCDF dataset must be in define mode. The parameter len is the number of values from out to transfer. It is often one, except that for nc_put_att_text() it will usually be strlen(out).
For these functions, the type component of the function name refers to the in-memory type of the value, whereas the xtype argument refers to the external type for storing the value. An NC_ERANGE error results if a conversion between these types is not possible. In this case the value is represented with the appropriate fill-value for the associated external type.
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int nc_inq_attname(int ncid, int varid, int attnum, char name[]) |
Gets the name of an attribute, given its variable ID and attribute number. This function is useful in generic applications that need to get the names of all the attributes associated with a variable, since attributes are accessed by name rather than number in all other attribute functions. The number of an attribute is more volatile than the name, since it can change when other attributes of the same variable are deleted. The attributes for each variable are numbered from 0 (the first attribute) to nvatts-1, where nvatts is the number of attributes for the variable, as returned from a call to nc_inq_varnatts(). If the name parameter is a NULL pointer, no name will be returned and no space need be allocated.
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int nc_inq_att(int ncid, int varid, const char name[], nc_type* xtype, size_t* len) | |
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int nc_inq_attid(int ncid, int varid, const char name[], int* attnum) | |
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int nc_inq_atttype(int ncid, int varid, const char name[], nc_type* xtype) | |
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int nc_inq_attlen(int ncid, int varid, const char name[], size_t* len) |
These functions return information about a netCDF attribute, given its variable ID and name. The information returned is the external type in xtype and the number of elements in the attribute as len. If any of the return arguments is a NULL pointer, the specified information will not be returned.
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int nc_copy_att(int ncid, int varid_in, const char name[], int ncid_out, int varid_out) |
Copies an attribute from one netCDF dataset to another. It can also be used to copy an attribute from one variable to another within the same netCDF. ncid_in is the netCDF ID of an input netCDF dataset from which the attribute will be copied. varid_in is the ID of the variable in the input netCDF dataset from which the attribute will be copied, or NC_GLOBAL for a global attribute. name is the name of the attribute in the input netCDF dataset to be copied. ncid_out is the netCDF ID of the output netCDF dataset to which the attribute will be copied. It is permissible for the input and output netCDF ID’s to be the same. The output netCDF dataset should be in define mode if the attribute to be copied does not already exist for the target variable, or if it would cause an existing target attribute to grow. varid_out is the ID of the variable in the output netCDF dataset to which the attribute will be copied, or NC_GLOBAL to copy to a global attribute.
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int nc_rename_att(int ncid, int varid, const char name[], const char newname[]) |
Changes the name of an attribute. If the new name is longer than the original name, the netCDF must be in define mode. You cannot rename an attribute to have the same name as another attribute of the same variable. name is the original attribute name. newname is the new name to be assigned to the specified attribute. If the new name is longer than the old name, the netCDF dataset must be in define mode.
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int nc_del_att(int ncid, int varid, const char name[]) |
Deletes an attribute from a netCDF dataset. The dataset must be in define mode.
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int nc_get_att_text(int ncid, int varid, const char name[], char in[]) | |
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int nc_get_att_uchar(int ncid, int varid, const char name[], unsigned char in[]) | |
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int nc_get_att_schar(int ncid, int varid, const char name[], signed char in[]) | |
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int nc_get_att_short(int ncid, int varid, const char name[], short in[]) | |
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int nc_get_att_int(int ncid, int varid, const char name[], int in[]) | |
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int nc_get_att_long(int ncid, int varid, const char name[], long in[]) | |
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int nc_get_att_float(int ncid, int varid, const char name[], float in[]) | |
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int nc_get_att_double(int ncid, int varid, const char name[], double in[]) | |
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int nc_get_att_ubyte(int ncid, int varid, const char name[], unsigned char in[]) | |
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int nc_get_att_ushort(int ncid, int varid, const char name[], unsigned short in[]) | |
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int nc_get_att_uint(int ncid, int varid, const char name[], unsigned int in[]) | |
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int nc_get_att_int64(int ncid, int varid, const char name[], long long in[]) | |
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int nc_get_att_uint64(int ncid, int varid, const char name[], unsigned long long in[]) | |
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int nc_get_att_string(int ncid, int varid, const char name[], char * in[]) |
Gets the value(s) of a netCDF attribute, given its variable ID and name. Converts from the external type to the type specified in the function name, if possible, otherwise returns an NC_ERANGE error. All elements of the vector of attribute values are returned, so you must allocate enough space to hold them. If you don’t know how much space to reserve, call nc_inq_attlen() first to find out the length of the attribute.
In this section
we define some common arguments which are used in the
"FUNCTION DESCRIPTIONS" section.
int ncid
is the netCDF ID returned from a previous, successful call to nc_open() or nc_create()
char name[]
is the name of a dimension, variable, or attribute. The names of dimensions, variables and attributes consist of arbitrary sequences of alphanumeric characters (as well as underscore ’_’, period ’.’ and hyphen ’-’), beginning with a letter or underscore. (However names commencing with underscore are reserved for system use.) Case is significant in netCDF names. A zero-length name is not allowed. As an input argument, it shall be a pointer to a 0-terminated string; as an output argument, it shall be the address of a buffer in which to hold such a string. The maximum allowable number of characters (excluding the terminating 0) is NC_MAX_NAME.
nc_type xtype
specifies the external data type of a netCDF variable or attribute and is one of the following: NC_BYTE, NC_CHAR, NC_SHORT, NC_INT, NC_FLOAT, or NC_DOUBLE. These are used to specify 8-bit integers, characters, 16-bit integers, 32-bit integers, 32-bit IEEE floating point numbers, and 64-bit IEEE floating-point numbers, respectively. (NC_INT corresponds to NC_LONG in version 2, to specify a 32-bit integer).
int dimids[]
is a vector of dimension ID’s and defines the shape of a netCDF variable. The size of the vector shall be greater than or equal to the rank (i.e. the number of dimensions) of the variable (ndims). The vector shall be ordered by the speed with which a dimension varies: dimids[ndims-1] shall be the dimension ID of the most rapidly varying dimension and dimids[0] shall be the dimension ID of the most slowly varying dimension. The maximum possible number of dimensions for a variable is given by the symbolic constant NC_MAX_VAR_DIMS.
int dimid
is the ID of a netCDF dimension. netCDF dimension ID’s are allocated sequentially from the non-negative integers beginning with 0.
int ndims
is either the total number of dimensions in a netCDF dataset or the rank (i.e. the number of dimensions) of a netCDF variable. The value shall not be negative or greater than the symbolic constant NC_MAX_VAR_DIMS.
int varid
is the ID of a netCDF variable or (for the attribute-access functions) the symbolic constant NC_GLOBAL, which is used to reference global attributes. netCDF variable ID’s are allocated sequentially from the non-negative integers beginning with 0.
int* natts
is the number of global attributes in a netCDF dataset for the nc_inquire() function or the number of attributes associated with a netCDF variable for the nc_varinq() function.
const size_t index[]
specifies the indicial coordinates of the netCDF data value to be accessed. The indices start at 0; thus, for example, the first data value of a two-dimensional variable is (0,0). The size of the vector shall be at least the rank of the associated netCDF variable and its elements shall correspond, in order, to the variable’s dimensions.
const size_t start[]
specifies the starting point for accessing a netCDF variable’s data values in terms of the indicial coordinates of the corner of the array section. The indices start at 0; thus, the first data value of a variable is (0, 0, ..., 0). The size of the vector shall be at least the rank of the associated netCDF variable and its elements shall correspond, in order, to the variable’s dimensions.
const size_t count[]
specifies the number of indices selected along each dimension of the array section. Thus, to access a single value, for example, specify count as (1, 1, ..., 1). Note that, for strided I/O, this argument must be adjusted to be compatible with the stride and start arguments so that the interaction of the three does not attempt to access an invalid data co-ordinate. The elements of the count vector correspond, in order, to the variable’s dimensions.
const size_t stride[]
specifies the sampling interval along each dimension of the netCDF variable. The elements of the stride vector correspond, in order, to the netCDF variable’s dimensions (stride[0]) gives the sampling interval along the most slowly varying dimension of the netCDF variable). Sampling intervals are specified in type-independent units of elements (a value of 1 selects consecutive elements of the netCDF variable along the corresponding dimension, a value of 2 selects every other element, etc.). A NULL stride argument is treated as (1, 1, ... , 1).
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imap |
specifies the mapping between the dimensions of a netCDF variable and the in-memory structure of the internal data array. The elements of the index mapping vector correspond, in order, to the netCDF variable’s dimensions (imap[0] gives the distance between elements of the internal array corresponding to the most slowly varying dimension of the netCDF variable). Distances between elements are specified in type-independent units of elements (the distance between internal elements that occupy adjacent memory locations is 1 and not the element’s byte-length as in netCDF 2). A NULL pointer means the memory-resident values have the same structure as the associated netCDF variable. |
By default, the netCDF interface sets the values of all newly-defined variables of finite length (i.e. those that do not have an unlimited, dimension) to the type-dependent fill-value associated with each variable. This is done when nc_enddef() is called. The fill-value for a variable may be changed from the default value by defining the attribute ‘_FillValue’ for the variable. This attribute must have the same type as the variable and be of length one.
Variables with an unlimited dimension are also prefilled, but on an ‘as needed’ basis. For example, if the first write of such a variable is to position 5, then positions 0 through 4 (and no others) would be set to the fill-value at the same time.
This default prefilling of data values may be disabled by or’ing the NC_NOFILL flag into the mode parameter of nc_open() or nc_create(), or, by calling the function nc_set_fill() with the argument NC_NOFILL. For variables that do not use the unlimited dimension, this call must be made before nc_enddef(). For variables that use the unlimited dimension, this call may be made at any time.
One can obtain increased performance of the netCDF interface by using this feature, but only at the expense of requiring the application to set every single data value. The performance enhancing behavior of this function is dependent on the particulars of the implementation and dataset format. The flag value controlled by nc_set_fill() is per netCDF ID, not per variable or per write. Allowing this to change affects the degree to which a program can be effectively parallelized. Given all of this, we state that the use of this feature may not be available (or even needed) in future releases. Programmers are cautioned against heavy reliance upon this feature.
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int nc_setfill(int ncid, int fillmode, int* old_fillemode) |
(Corresponds to ncsetfill() in version 2)
Determines whether or not variable prefilling will be done (see above). The netCDF dataset shall be writable. fillmode is either NC_FILL to enable prefilling (the default) or NC_NOFILL to disable prefilling. This function returns the previous setting in old_fillmode.
Additional functions for use on SGI/Cray MPP machines (_CRAYMPP). These are used to set and inquire which PE is the base for MPP for a particular netCDF. These are only relevant when using the SGI/Cray ‘‘global’’ Flexible File I/O layer and desire to have only a subset of PEs to open the specific netCDF file. For technical reasons, these functions are available on all platforms. On a platform other than SGI/Cray MPP, it is as if only processor available were processor 0.
To use this feature, you need to specify a communicator group and call glio_group_mpi() or glio_group_shmem() prior to the netCDF nc_open() and nc_create() calls.
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int nc__create_mp(const char path[], int cmode, size_t initialsize, int pe, size_t* chunksize, int* ncid) |
Like nc__create() but allows the base PE to be set.
The argument pe sets the base PE at creation time. In the MPP environment, nc__create() and nc_create() set the base PE to processor zero by default.
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int nc__open_mp(const char path[], int mode, int pe, size_t* chunksize, int* ncid) |
Like nc__open() but allows the base PE to be set. The argument pe sets the base PE at creation time. In the MPP environment, nc__open() and nc_open() set the base PE to processor zero by default.
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int nc_inq_base_pe(int ncid, int* pe) |
Inquires of the netCDF dataset which PE is being used as the base for MPP use. This is safe to use at any time.
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int nc_set_base_pe(int ncid, int pe) |
Resets the base PE for the netCDF dataset. Only perform this operation when the affected communicator group synchronizes before and after the call. This operation is very risky and should only be contemplated under only the most extreme cases.
NETCDF_FFIOSPEC
Specifies the Flexible File I/O buffers for netCDF I/O when executing under the UNICOS operating system (the variable is ignored on other operating systems). An appropriate specification can greatly increase the efficiency of netCDF I/O -- to the extent that it can actually surpass FORTRAN binary I/O. This environment variable has been made a little more generalized, such that other FFIO option specifications can now be added. The default specification is bufa:336:2, unless a current FFIO specification is in operation, which will be honored. See UNICOS Flexible File I/O for more information.
Both a mailing list and a digest are available for discussion of the netCDF interface and announcements about netCDF bugs, fixes, and enhancements. To begin or change your subscription to either the mailing-list or the digest, send one of the following in the body (not the subject line) of an email message to<EMAIL_ADDRESS>Use your email address in place of<EMAIL_ADDRESS>To subscribe to the netCDF mailing list:
subscribe netcdfgroup<EMAIL_ADDRESS>To unsubscribe from the netCDF mailing list:
unsubscribe netcdfgroup<EMAIL_ADDRESS>To subscribe to the netCDF digest:
subscribe netcdfdigest<EMAIL_ADDRESS>To unsubscribe from the netCDF digest:
unsubscribe netcdfdigest<EMAIL_ADDRESS>To retrieve the general introductory information for the mailing list:
info netcdfgroup
To get a synopsis of other majordomo commands:
help
ncdump(1), ncgen(1), netcdf(3).
netCDF User’s Guide, published by the Unidata Program Center, University Corporation for Atmospheric Research, located in Boulder, Colorado.
NetCDF home page at http:/www.unidata.ucar.edu/netcdf.


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