SIX Network
- Value: ~$2
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Welcome to airdrops.io, a free source that presents the world’s most current and legitimate cryptocurrency airdrops. We verify and aggregate airdrops and bounties daily to bring you the most recent and profitable earning opportunities. Choose an airdrop and follow the instructions provided to claim free crypto tokens, or vote for your favorite projects!
Welcome to airdrops.io, a free source that presents the world’s most current and legitimate cryptocurrency airdrops. We verify and aggregate airdrops and bounties daily to bring you the most recent and profitable earning opportunities. Choose an airdrop and follow the instructions provided to claim free crypto tokens, or vote for your favorite projects!


Batch normalization.
tf.compat.v2.nn.batch_norm_with_global_normalization
tf.nn.batch_norm_with_global_normalization( input, mean, variance, beta, gamma, variance_epsilon, scale_after_normalization, name=None )
This op is deprecated. See tf.nn.batch_normalization
.
input
: A 4D input Tensor.mean
: A 1D mean Tensor with size matching the last dimension of t.
This is the first output from tf.nn.moments,
or a saved moving average thereof.variance
: A 1D variance Tensor with size matching the last dimension of t.
This is the second output from tf.nn.moments,
or a saved moving average thereof.beta
: A 1D beta Tensor with size matching the last dimension of t.
An offset to be added to the normalized tensor.gamma
: A 1D gamma Tensor with size matching the last dimension of t.
If "scale_after_normalization" is true, this tensor will be multiplied
with the normalized tensor.variance_epsilon
: A small float number to avoid dividing by 0.scale_after_normalization
: A bool indicating whether the resulted tensor
needs to be multiplied with gamma.name
: A name for this operation (optional).A batch-normalized t
.


| # | File | Line | Problem |
| 1 |
ChangePasswordControllerTest.cls |
5 |
@isTest(seeAllData=true) should not be used in Apex unit tests because it opens up the existing database data for unexpected modification by tests |
| 2 |
ForgotPasswordControllerTest.cls |
5 |
@isTest(seeAllData=true) should not be used in Apex unit tests because it opens up the existing database data for unexpected modification by tests |
| 3 |
HttpFormBuilder.cls |
3 |
Variables that are final and static should be all capitals, 'Boundary' is not all capitals. |
| 4 |
HttpFormBuilder.cls |
8 |
Method names should not start with capital letters |
| 5 |
HttpFormBuilder.cls |
15 |
Method names should not start with capital letters |
| 6 |
HttpFormBuilder.cls |
35 |
Method names should not start with capital letters |
| 7 |
HttpFormBuilder.cls |
45 |
Method names should not start with capital letters |
| 8 |
HttpFormBuilder.cls |
77 |
Method names should not start with capital letters |
| 9 |
HttpFormBuilder.cls |
98 |
Variables that are final and static should be all capitals, 'Cr' is not all capitals. |
| 10 |
HttpFormBuilder.cls |
99 |
Variables that are final and static should be all capitals, 'CrLf' is not all capitals. |
| 11 |
HttpFormBuilder.cls |
100 |
Variables that are final and static should be all capitals, 'None' is not all capitals. |
| 12 |
JWT.cls |
1 |
This class has too many public methods and attributes |
| 13 |
JWTBearerFlow.cls |
5 |
Only variables that are final should contain underscores (except for underscores in standard prefix/suffix), 'access_token' is not final. |
| 14 |
MyProfilePageControllerTest.cls |
7 |
@isTest(seeAllData=true) should not be used in Apex unit tests because it opens up the existing database data for unexpected modification by tests |
| 15 |
SendMassEmail.cls |
13 |
Validate CRUD permission before SOQL/DML operation |
| 16 |
SiteLoginController.cls |
4 |
Avoid using global modifier |
| 17 |
SiteLoginControllerTest.cls |
4 |
Avoid using global modifier |
| 18 |
SiteLoginControllerTest.cls |
5 |
@isTest(seeAllData=true) should not be used in Apex unit tests because it opens up the existing database data for unexpected modification by tests |
| 19 |
SiteRegisterController.cls |
7 |
Only variables that are final should contain underscores (except for underscores in standard prefix/suffix), 'PORTAL_ACCOUNT_ID' is not final. |
| 20 |
SiteRegisterController.cls |
7 |
Variables should start with a lowercase character, 'PORTAL_ACCOUNT_ID' starts with uppercase character. |
| 21 |
SiteRegisterControllerTest.cls |
5 |
@isTest(seeAllData=true) should not be used in Apex unit tests because it opens up the existing database data for unexpected modification by tests |
| 22 |
SubmitCaseController.cls |
1 |
Apex classes should declare a sharing model if DML or SOQL is used |
| 23 |
SubmitCaseController.cls |
12 |
Validate CRUD permission before SOQL/DML operation |
| 24 |
SubmitCaseController.cls |
22 |
Validate CRUD permission before SOQL/DML operation |
| 25 |
SubmitCaseController.cls |
32 |
Validate CRUD permission before SOQL/DML operation |
| 26 |
Vision.cls |
3 |
Only variables that are final should contain underscores (except for underscores in standard prefix/suffix), 'VISION_API' is not final. |
| 27 |
Vision.cls |
3 |
Variables should start with a lowercase character, 'VISION_API' starts with uppercase character. |
| 28 |
Vision.cls |
4 |
Variables should start with a lowercase character, 'PREDICT' starts with uppercase character. |
| 29 |
Vision.cls |
6 |
Only variables that are final should contain underscores (except for underscores in standard prefix/suffix), 'access_token' is not final. |
| 30 |
Vision.cls |
10 |
Only variables that are final should contain underscores (except for underscores in standard prefix/suffix), 'access_token' is not final. |
| 31 |
Vision.cls |
14 |
Only variables that are final should contain underscores (except for underscores in standard prefix/suffix), 'access_token' is not final. |
| 32 |
Vision.cls |
18 |
Avoid long parameter lists |
| 33 |
Vision.cls |
18 |
Only variables that are final should contain underscores (except for underscores in standard prefix/suffix), 'access_token' is not final. |
| 34 |
Vision.cls |
44 |
Consider using named credentials for authenticated callouts |
| 35 |
Vision.cls |
60 |
Deeply nested if..else statements are hard to read |
| 36 |
VisionController.cls |
1 |
Apex classes should declare a sharing model if DML or SOQL is used |
| 37 |
VisionController.cls |
10 |
Only variables that are final should contain underscores (except for underscores in standard prefix/suffix), 'access_token' is not final. |
| 38 |
VisionController.cls |
22 |
Only variables that are final should contain underscores (except for underscores in standard prefix/suffix), 'access_token' is not final. |
| 39 |
VisionController.cls |
36 |
Only variables that are final should contain underscores (except for underscores in standard prefix/suffix), 'access_token' is not final. |
| 40 |
myWeb2LeadExtension.cls |
1 |
Apex classes should declare a sharing model if DML or SOQL is used |
| 41 |
myWeb2LeadExtension.cls |
1 |
Class names should begin with an uppercase character |


| Sweave2knitr {knitr} | R Documentation |
This function converts an Sweave document to a knitr-compatible document.
Sweave2knitr( file, output = gsub("[.]([^.]+)$", "-knitr.\\1", file), text = NULL )
file |
Path to the Rnw file (must be encoded in UTF-8). |
output |
Output file path. By default, ‘file.Rnw’ produces
‘file-knitr.Rnw’); if |
text |
An alternative way to provide the Sweave code as a character
string. If |
The pseudo command \SweaveInput{file.Rnw} is converted to a code
chunk header <<child='file.Rnw'>>=
.
Similarly \SweaveOpts{opt = value} is converted to a code chunk
opts_chunk$set(opt = value) with the chunk option include =
FALSE
; the options are automatically fixed in the same way as local chunk
options (explained below).
The Sweave package \usepackage{Sweave} in the preamble is removed because it is not required.
Chunk options are updated if necessary: option values true
and
false
are changed to TRUE
and FALSE
respectively;
fig=TRUE
is removed because it is not necessary for knitr (plots
will be automatically generated); fig=FALSE
is changed to
fig.keep='none'
; the devices pdf/jpeg/png/eps/tikz=TRUE
are
converted to dev='pdf'/'jpeg'/'png'/'postscript'/'tikz'
;
pdf/jpeg/png/eps/tikz=FALSE
are removed;
results=tex/verbatim/hide
are changed to
results='asis'/'markup'/'hide'
; width/height
are changed to
fig.width/fig.height
; prefix.string
is changed to
fig.path
; print/term/prefix=TRUE/FALSE
are removed; most of the
character options (e.g. engine
and out.width
) are quoted;
keep.source=TRUE/FALSE
is changed to tidy=FALSE/TRUE
(note the
order of values).
If a line @
(it closes a chunk) directly follows a previous
@
, it is removed; if a line @
appears before a code chunk and
no chunk is before it, it is also removed, because knitr only uses one
@ after <<>>= by default (which is not the original Noweb
syntax but more natural).
If text
is NULL
, the output
file is written and
NULL
is returned. Otherwise, the converted text string is returned.
If \SweaveOpts{} spans across multiple lines, it will not be
fixed, and you have to fix it manually. The LaTeX-style syntax of Sweave
chunks are ignored (see ?SweaveSyntaxLatex
); only the Noweb syntax
is supported.
The motivation of the changes in the syntax: https://yihui.org/knitr/demo/sweave/
Sweave2knitr(text = "<<echo=TRUE>>=") # this is valid Sweave2knitr(text = "<<png=true>>=") # dev='png' Sweave2knitr(text = "<<eps=TRUE, pdf=FALSE, results=tex, width=5, prefix.string=foo>>=") Sweave2knitr(text = "<<,png=false,fig=TRUE>>=") Sweave2knitr(text = "\\SweaveOpts{echo=false}") Sweave2knitr(text = "\\SweaveInput{hello.Rnw}") # Sweave example in utils testfile = system.file("Sweave", "Sweave-test-1.Rnw", package = "utils") Sweave2knitr(testfile, output = "Sweave-test-knitr.Rnw") if (interactive()) knit("Sweave-test-knitr.Rnw") # or knit2pdf() directly unlink("Sweave-test-knitr.Rnw")


PIFCONFIG
Section: [FIXME: manual] (8)Updated: 07/19/2011
Index Return to Main Contents
NAME
pifconfig - display information about a network interfaceSYNOPSIS
DESCRIPTION
This script mimic ifconfig behavior, but is written purely in python and python module ethtool.
OPTIONS
INTERFACE
- Display information about only this interface. If no interface is given then all interfaces are displayed.
-h, --help
- Show help message and exit.
SEE ALSO
ifconfig(8)
AUTHORS
Arnaldo Carvalho de Melo<EMAIL_ADDRESS>Man page written by Miroslav Suchý<EMAIL_ADDRESS>Index
This document was created by man2html, using the manual pages.
Time: 05:34:28 GMT, December 24, 2015


Music Album Organiser
+ New Album
Filter by
1
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Album title
Artist
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Condition
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In the system-tab, the group ARE handles the functionalities for connecting to and communicating with the ARE.
Connect to ARE connects the ACS with the ARE. The location of the ARE is extracted from the URL of the WebACS (assuming it is hosted on the ARE's webservice) or - if the WebACS is not hosted - the ARE is assumed at "localhost:8081". The possibility to edit this value has yet to be implemented.
Disconnect from ARE closes the connection to the ARE.
Upload Model transmits the currently selected model from the ACS to the ARE. The model on the ARE will be overwritten. Uploading the model to the ARE does not start the model on the ARE.
Download Model transmits the active model from the ARE to the ACS. A new model tab will be opened for this.
Download Component Collection transmits the bundel description (describing the components) from the connected ARE to the ACS. These bundel descrptions will be set for the currently selected model only and will be available as components in the components-tab.
The group ARE Storage deals with the storage of models on the ARE. Once a model has been stored on the ARE it can be activated using the ARE interface.
Store Model on ARE transmits the currently selected model from the ACS to the ARE storage. A dialog appears to set the filename.
Load Model from Storage transmits a model from the ARE storage to the ACS (a new model tab will be opened for this). A dialog appears to choose which model to download.
Activate a Stored Model: A dialog appears to select the filename of a model in the ARE storage. This model will be set active in the ARE and also will be started.
Delete a Stored Model deletes a model from the ARE storage using a file dialog.
Set as Autorun sets the currently selected model as autorun model. This model will be started automatically when the ARE starts.
Starting and stopping a model can be done with the buttons in the group Model.


Namespace for the rules for associations
- Source:
Methods
-
(static) allNonEmpty() → {Array}
-
Function to check all fields contained in this set have a value
- Source:
Returns:
Array of invalidField objects for the fields without a value or an empty array if none- Type
- Array
-
(static) allValid() → {Array}
-
Function to check all fields contained in the association are valid
- Source:
Returns:
Array of invalidField objects for each invalid member or an empty array if none- Type
- Array
-
(static) dateOfBirthOrExcuse() → {Array}
-
Function to check if a valid date of birth is provided or a valid excuse
- Source:
Returns:
Array of invalidFields for each invalid date field or an empty array if none- Type
- Array
-
(static) fieldsetOrExcuse() → {Array}
-
Function to check if the fieldset or its excuse section are valid
- Source:
Returns:
Array containing either the invalidField objects for any broken fieldset rules or an empty array if all are valid or if a valid excuse is provided- Type
- Array


---
# Feel free to add content and custom Front Matter to this file.
# To modify the layout, see https://jekyllrb.com/docs/themes/#overriding-theme-defaults
title: "index"
layout: default
---
{% for post in site.posts %}
{% include post_thumb.html %}
{% endfor %}


If you've edited a {_program}, and you want to store it under the same program number, you can do that from any screen by {_long-press long-pressing} the {Program_Info_button} (the second button in the {Navigation_bar}, and then {_tap tapping} the "store" button. Even easier, just hit S on the keyboard.
But if you wish to store a program under a new number, you have to do that from the Programs screen. You long-press the button of the desired program location to display the {Program_popup}, and then tap the "store" button.
Occasionally, it's useful to exchange the current program with a stored program. This is done from the same popup by tapping the "exchange" button. When you do this, the current program number doesn't change. Repeating the function exchanges them again, getting back to where you started, although {Undo_Redo_buttons Undo} (or pressing U on the keyboard) is easier.


The concept of a carbon budget involves multiple dynamic, interrelated components of the global carbon cycle and can be defined in a number of ways. As a figure of merit, we define an atmospheric flux ratio ( RAF) as the ratio of net CO 2 emissions (anthropogenic sources minus artificial sinks) to net CO 2 uptake by natural sinks (that is, plant, soil and ocean systems).
The atmospheric flux ratio characterizes annual changes in the atmospheric carbon burden. Atmospheric flux ratios greater than unity ( RAF>1) indicate increasing atmospheric carbon concentrations, associated radiative forcing and temperatures. Ratio values between zero and unity (0< RAF<1) indicate net negative atmospheric carbon flux due to net ocean and land sink uptake, an important milestone on the path to climate stabilization. Finally, values below zero ( RAF<0) indicate net negative anthropogenic emissions—that is, the achievement of the COP carbon emissions target. We calculate recent historical values of RAF on the basis of data from the Intergovernmental Panel on Climate Change (IPCC) 3 and use the FeliX model to project RAF through 2100 for all scenarios.
Based on the most recent available IPCC data for global atmospheric carbon flux, we calculate RAF=1.9±0.2 for the period 2002–2011 ( cf. Fig. 1). This value is in good agreement with FeliX model results, which estimate RAF=2.1±0.2, indicating that net anthropogenic carbon emissions are roughly double the combined net uptake by plants, soil and oceans. Looking in more detail at year 2015 of the FeliX model, primary energy consumption totals nearly 600 EJ per year ( cf. Fig. 2) and net emissions from the energy and LULUCF sectors total 10.4 and 1.0 PgC, respectively ( cf. Figs 3a and 4a). In the same year, the carbon content of the atmosphere increases by 6.3 PgC and the ocean and land sinks each take up 2.7 PgC ( cf. Fig. 5).
Carbon uptake by natural sinks is dependent on anthropogenic emissions via climactic and chemical feedback mechanisms 45. In decarbonization scenarios, net carbon uptake by the land and ocean systems approaches zero as anthropogenic emissions also decrease to zero and this dynamic relationship makes a moving target of net negative atmospheric carbon flux. In this section, we present FeliX scenario results and use RAF to evaluate energy and LULUCF transition pathways relative to the COP targets.
The baseline scenario projects an increase in anthropogenic emissions an additional 20% beyond the absorptive capacity of natural sinks by 2100 ( RAF=2.3±0.6) ( cf. Fig. 1). In the nominal energy pathway, REs (that is, solar, wind and biomass) grow at an average annual rate of 4.0% from 2013 through 2100, causing a decline in the total market share of fossil fuels from 90% (2015) to 60% (2100) of primary energy supply. In absolute terms, however, consumption of conventional fuels grows until 2060 to meet growing primary energy demand ( cf. Fig. 2b). Fossil fuel emissions peak at 12.7–14.5 PgC per year around 2055, then decrease to 10.9–12.6 PgC per year by 2100. Emissions from REs increase from 0.1 PgC per year in 2015 to 0.5–0.7 PgC per year in 2100, reflecting the costs of bioenergy harvesting, transportation and processing ( cf. Fig. 3).
In the LULUCF sector, emissions mitigation from the continuation of recent progress combating deforestation is completely offset by emissions from anticipated conversion of natural forests to managed forests and plantations for bioenergy production 67. Net LULUCF emissions decrease to 0.4–1.3 PgC per year in 2100 ( cf. Fig. 4).
Overall, annual anthropogenic emissions in the BAU scenario peak at 13.5–15.6 PgC per year around 2054, then decline modestly over the second half of the century ( cf.Fig. 5a). Annual ocean CO 2 flux increases to a peak of 3.2–3.4 PgC per year around 2065, after which point ocean flux stabilizes as the chemical and temperature feedbacks cancel each other out. Net carbon flux into the land sink peaks at the same magnitude (3.1–3.4 PgC per year) around 2046 and declines to 2.3–2.9 by 2100 due to the temperature feedback ( cf.Fig. 5).
Relative to the twentieth century, cumulative anthropogenic emissions increase 225–246% (1,250–1,419 PgC) in the present century ( cf.Fig. 6b). The BAU energy emissions pathway leads to CA=684–743 p.p.m. and Δ T=3.1–3.3 °C in 2100. To contextualize these endogenous results using IPCC benchmarks, we note that the energy and LULUCF sectors, as modelled in the BAU scenario, generate cumulative carbon emissions and temperature anomalies similar to Representative Concentration Pathway (RCP) 6.0, one of the IPCC's four benchmark concentration pathways for CO 2 and other greenhouse gases 67.
The Fossil Fuels scenario projects an increase in anthropogenic emissions to at least 2.5 times the absorptive capacity of natural sinks by 2100 ( RAF=2.6±0.7) ( cf.Fig. 1). In the nominal energy pathway, REs grow at an average annual rate of 2.2% from 2013 through 2100. The primary energy market share of fossil fuels remains steady near 90% over the course of the century, whereas absolute fossil fuel consumption increases to 847–1097 EJ per year by 2100 ( cf.Fig. 2a). Fossil fuel emissions peak at 16.0–20.1 PgC per year close to the end of the century, whereas emissions from REs do not exceed 0.2 PgC per year ( cf.Fig. 3). LULUCF emissions fall relative to the baseline due to the eventual depletion of easily deforested areas and because diminished bioenergy demand reduces conversion of forests to managed forests and plantations ( cf.Fig. 4).
Annual anthropogenic emissions in the Fossil Fuels scenario peak at 16.0–20.7 PgC per year around 2100. Net CO 2 flux into the ocean peaks at 3.5–3.8 PgC per year around 2088 and net carbon flux into the land sink peaks at 3.4–3.9 PgC per year around 2065 ( cf.Fig. 5). Cumulative anthropogenic emissions reach 1,435–1,642 PgC (a 250–300% increase over twentieth century emissions) CA=749–823 p.p.m. and Δ T=3.4–3.6 °C in 2100 ( cf.Fig. 6a–d).
The RE-Low scenario, constructed along the lines of moderate climate action scenarios 8, projects persistent anthropogenic emissions at least two times larger than the absorptive capacity of natural sinks by 2100 ( RAF=2.1±0.5) ( cf.Fig. 1). In the nominal energy pathway, REs grow at an annual rate of 4.4% from 2013 through 2100, driving the market share of conventional fuels below half of primary energy supply in 2100.
Although absolute fossil fuel consumption does not begin to decline until after midcentury, it peaks lower (590–688 EJ per year around 2054) and declines more rapidly (to 455–583 EJ per year in 2100) than in the baseline ( cf.Fig. 2c). Annual fossil fuel emissions peak in 2050 at 11.1–12.8 PgC per year and decrease to 8.3–10.7 PgC per year in 2100, and emissions from REs grow to 0.7–1.1 PgC per year in 2100 ( cf.Fig. 3).
Assuming a global, concerted effort to achieve the COP targets, policies driving decarbonization of the energy sector in the RE-Low scenario are linked by construction with land-use change restrictions eliminating ‘unnecessary' deforestation or forest loss resulting from poverty, conflict, poor governance, lack of knowledge and other sub-optimal uses of land 9. FeliX calculates unnecessary deforestation endogenously as the difference between fallow agricultural land and cumulative deforestation after 2011. This optimization of land use offsets emissions from forest conversion to managed forests and plantations, causing annual LULUCF emissions to decrease to 0.1–0.3 PgC per year in 2100 ( cf.Fig. 4a).
In total, net anthropogenic emissions peak at 12.2–13.2 PgC per year in 2048 and subsequently decline to 9.3–12.0 PgC per year by 2100 ( cf.Fig. 5a). In response, cumulative ocean and land sink carbon fluxes over the same period decrease by 7% and 10%, respectively, relative to BAU. These pathways generate a 13% reduction in cumulative emissions relative to the baseline for the period 2011–2100. Although they represent progress in terms of atmospheric carbon ( CA=633−686 p.p.m.) and surface temperature anomaly (Δ T=2.9−3.1 °C), the energy and LULUCF transitions in the RE-Low scenario fall short of global emissions and warming targets by 2100 ( cf.Fig. 6).
The RE-High scenario describes an accelerated transition to REs in line with aggressive climate action scenarios 8. In this pathway, anthropogenic emissions remain at least 50% higher than natural sink flux ( RAF=1.7±0.6), but this ratio belies significant progress towards the COP targets.
From 2013 to 2100, REs grow at 5.0% annually, causing absolute fossil fuel consumption to peak as soon as 2022 at 523–532 EJ per year, then decline to less than a fifth of primary energy supply (166–233 EJ per year) by 2100 ( cf.Fig. 2). Energy sector emissions peak at 10.3–10.5 PgC per year in 2023 and fall to 4.0–5.7 PgC per year in 2100 ( cf.Fig. 3). With the elimination of unnecessary deforestation, net LULUCF emissions fall to 0.2–0.4 PgC per year in 2100 or slightly greater than the corresponding RE-Low value due to land-use change in support of expanded bioenergy production ( cf.Fig. 4).
Summing these effects, net anthropogenic emissions peak at 11.5–11.7 PgC per year in 2022 then decrease to 4.2–6.1 PgC per year in 2100. In response, cumulative carbon uptakes by the ocean and land sinks decrease by 23% and 35%, respectively, relative to BAU from 2011 to 2100 ( cf.Fig. 5). Cumulative emissions decrease by 42% relative to BAU over the same period. At the end of the century, CA=532–563 p.p.m. and Δ T=2.5–2.6 °C ( cf.Fig. 6), making the RE-High scenario an approximation of IPCC benchmark RCP 4.5 (refs 6, 7).
Taken together, the Fossil Fuels, BAU, RE-Low and RE-High scenarios define a range of plausible energy-emissions pathways. As we have seen, however, even 5% annual growth in REs sustained through the twenty-first century fails to achieve critical benchmarks for both RAF and Δ T. Global transformations of the energy and LULUCF sectors need to be even more ambitious than in the RE-High scenario to achieve the COP targets, suggesting that additional socioeconomic and technological shifts must be considered.
CCS is implemented as a mitigation wedge within the RE-Low and RE-High scenarios to quantify the additional emissions mitigation necessary to achieve the COP targets. As variations on the energy and LULUCF sector transitions already discussed, we model the effects of CCS technologies scaled up after 2020 to 50% (
To achieve these capture rates while keeping up with primary energy demand growth, the
In the RE-Low scenario with
With CCS applied to the entire energy sector, the RE-Low+CCS scenario achieves RAF=−4.1±5.4, where the outsized error is due to the vanishing denominator, representing natural sinks ( cf.Fig. 5b,c). CCS infrastructures eliminate up to 12.6 PgC per year, with 776–981 PgC in storage by 2100. At the end of the century, CA=393–405 p.p.m. and Δ T=1.6–1.7 °C, making RE-Low+CCS an approximation of IPCC benchmark RCP 2.6 (refs 6, 7).
Finally, RAF rises again to RAF=−2.1±1.0 in RE-High+CCS, as the removal of carbon from the atmosphere reverses the sign of the chemical coupling between the ocean and land reservoirs and the atmosphere, transforming them into net sources of carbon ( cf.Fig. 5b,c). In this scenario, CCS eliminates up to 11.2 PgC per year and stores a cumulative total of 620–844 PgC by 2100 ( cf.Fig. 3b). At the end of the century, CA=328–363 p.p.m. and Δ T=1.2–1.4 °C, making this scenario the only one consistent with global warming below 1.5 °C and beginning a return to pre-industrial atmospheric carbon concentration ( cf.Fig. 6).
Errors on RAF are calculated by propagating uncertainties on each of the component fluxes, as estimated by the IPCC and discussed in the Methods section of this analysis, into the final figure of merit ( cf.Supplementary Table 1).
Within each scenario, we have reported CA, Δ T as numerical ranges in the text and as shaded regions in all figures, to indicate the sensitivity of the results to alternative primary energy demand projections. Primary energy demand shifts are the cumulative effect of exogenous ±0.2% annual increments in per capita energy demand after 2015, while market share of each fuel is held near constant ( cf.Fig. 2). The effect of this shift ranges from Δ CA±16 p.p.m. in RE-High (2100) to Δ CA±37 p.p.m. in Fossil Fuels (2100).
Future population growth is the leading socio-economic source of uncertainty, whereas the initial net primary productivity (NPP), land sink carbon residence time and equilibrium climate sensitivity (ECS; or the global temperature increase resulting from a doubling of the atmospheric carbon load) are the leading biogeophysical sources of uncertainty in emissions and warming pathways 11. High and low shifts from the nominal value of these and other fundamental model parameters are used to determine the sensitivity of the BAU scenario ( cf.Supplementary Table 2).


Welcome to stensig.net
The website is currently under construction. Until such a time as it is more presentable, important files can be found underneath.


Home
Welcome! I plan to use this site to do some writing (mainly about typed functional programming) as well as show off some projects.
Welcome! I plan to use this site to do some writing (mainly about typed functional programming) as well as show off some projects.


subject
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2019-20 Holden Astra, Commodore recalled
An issue with the crossmember on the base of the rear seat frame has forced 131 cars back to the dealer.
by Scott Collie- shares
Holden has recalled the 2019-20 Commodore and Astra, over concerns about a problem with the rear seat crossmember.
According to the company, the rear seat crossmember could have been improperly welded to the seat frame. If a car with the issue is involved in a rear-end accident, there's an increased risk passengers will be injured.
A total of 131 cars are included in the campaign – a VIN list is attached here.
Holden will contact owners of the affected cars and advise them to organise a free fix with their nearest dealer.
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2019-20 Holden Astra, Commodore recalled


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int | shifter |
| |
|
int | blocks |
| |
|
int | sps |
| |
|
int | threadBlocks |
| |
|
int | blockSize |
| |
|
int | threadsPerIntersection |
| |
|
int | logThreadsPerInter |
| |
|
int | numberInterPerBlock |
| |
|
triangle_t * | triPerVertex |
| |
|
vid_t | nv |
| |
|
off_t | ne |
| |
The documentation for this struct was generated from the following file:
- /home/fbusata3/HornetAlg/include/Static/TriangleCounting/triangle.cuh


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|
JavaTM 2 Platform Standard Ed. 5.0 |
|||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object java.util.regex.Matcher
public final class Matcher
An engine that performs match operations on a character sequence
by interpreting a
Pattern
.
A matcher is created from a pattern by invoking the pattern's matcher
method. Once created, a matcher can be used to
perform three different kinds of match operations:
The matches
method attempts to match the entire
input sequence against the pattern.
The lookingAt
method attempts to match the
input sequence, starting at the beginning, against the pattern.
The find
method scans the input sequence looking for
the next subsequence that matches the pattern.
Each of these methods returns a boolean indicating success or failure. More information about a successful match can be obtained by querying the state of the matcher.
A matcher finds matches in a subset of its input called the
region. By default, the region contains all of the matcher's input.
The region can be modified via theregion
method and queried
via the regionStart
and regionEnd
methods. The way that the region boundaries interact with some pattern
constructs can be changed. See useAnchoringBounds
and useTransparentBounds
for more details.
This class also defines methods for replacing matched subsequences with
new strings whose contents can, if desired, be computed from the match
result. The appendReplacement
and appendTail
methods can be used in tandem in order to collect
the result into an existing string buffer, or the more convenient replaceAll
method can be used to create a string in which every
matching subsequence in the input sequence is replaced.
The explicit state of a matcher includes the start and end indices of the most recent successful match. It also includes the start and end indices of the input subsequence captured by each capturing group in the pattern as well as a total count of such subsequences. As a convenience, methods are also provided for returning these captured subsequences in string form.
The explicit state of a matcher is initially undefined; attempting to
query any part of it before a successful match will cause an IllegalStateException
to be thrown. The explicit state of a matcher is
recomputed by every match operation.
The implicit state of a matcher includes the input character sequence as
well as the append position, which is initially zero and is updated
by the appendReplacement
method.
A matcher may be reset explicitly by invoking its reset()
method or, if a new input sequence is desired, its reset(CharSequence)
method. Resetting a
matcher discards its explicit state information and sets the append position
to zero.
Instances of this class are not safe for use by multiple concurrent threads.
| Method Summary | |
|---|---|
Matcher |
appendReplacement(StringBuffer sb,
String replacement)
Implements a non-terminal append-and-replace step. |
StringBuffer |
appendTail(StringBuffer sb)
Implements a terminal append-and-replace step. |
int |
end()
Returns the offset after the last character matched. |
int |
end(int group)
Returns the offset after the last character of the subsequence captured by the given group during the previous match operation. |
boolean |
find()
Attempts to find the next subsequence of the input sequence that matches the pattern. |
boolean |
find(int start)
Resets this matcher and then attempts to find the next subsequence of the input sequence that matches the pattern, starting at the specified index. |
String |
group()
Returns the input subsequence matched by the previous match. |
String |
group(int group)
Returns the input subsequence captured by the given group during the previous match operation. |
int |
groupCount()
Returns the number of capturing groups in this matcher's pattern. |
boolean |
hasAnchoringBounds()
Queries the anchoring of region bounds for this matcher. |
boolean |
hasTransparentBounds()
Queries the transparency of region bounds for this matcher. |
boolean |
hitEnd()
Returns true if the end of input was hit by the search engine in the last match operation performed by this matcher. |
boolean |
lookingAt()
Attempts to match the input sequence, starting at the beginning of the region, against the pattern. |
boolean |
matches()
Attempts to match the entire region against the pattern. |
Pattern |
pattern()
Returns the pattern that is interpreted by this matcher. |
static String |
quoteReplacement(String s)
Returns a literal replacement String for the specified
String . |
Matcher |
region(int start,
int end)
Sets the limits of this matcher's region. |
int |
regionEnd()
Reports the end index (exclusive) of this matcher's region. |
int |
regionStart()
Reports the start index of this matcher's region. |
String |
replaceAll(String replacement)
Replaces every subsequence of the input sequence that matches the pattern with the given replacement string. |
String |
replaceFirst(String replacement)
Replaces the first subsequence of the input sequence that matches the pattern with the given replacement string. |
boolean |
requireEnd()
Returns true if more input could change a positive match into a negative one. |
Matcher |
reset()
Resets this matcher. |
Matcher |
reset(CharSequence input)
Resets this matcher with a new input sequence. |
int |
start()
Returns the start index of the previous match. |
int |
start(int group)
Returns the start index of the subsequence captured by the given group during the previous match operation. |
MatchResult |
toMatchResult()
Returns the match state of this matcher as a MatchResult . |
String |
toString()
Returns the string representation of this matcher. |
Matcher |
useAnchoringBounds(boolean b)
Sets the anchoring of region bounds for this matcher. |
Matcher |
usePattern(Pattern newPattern)
Changes the Pattern that this Matcher uses to find matches with. |
Matcher |
useTransparentBounds(boolean b)
Sets the transparency of region bounds for this matcher. |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
| Method Detail |
|---|
public Pattern pattern()
public MatchResult toMatchResult()
MatchResult
.
The result is unaffected by subsequent operations performed upon this
matcher.
MatchResult
with the state of this matcherpublic Matcher usePattern(Pattern newPattern)
This method causes this matcher to lose information about the groups of the last match that occurred. The matcher's position in the input is maintained and its last append position is unaffected.
newPattern
- The new pattern used by this matcher
IllegalArgumentException
- If newPattern is nullpublic Matcher reset()
Resetting a matcher discards all of its explicit state information and sets its append position to zero. The matcher's region is set to the default region, which is its entire character sequence. The anchoring and transparency of this matcher's region boundaries are unaffected.
public Matcher reset(CharSequence input)
Resetting a matcher discards all of its explicit state information and sets its append position to zero. The matcher's region is set to the default region, which is its entire character sequence. The anchoring and transparency of this matcher's region boundaries are unaffected.
input
- The new input character sequence
public int start()
start
in interface MatchResult
IllegalStateException
- If no match has yet been attempted,
or if the previous match operation failedpublic int start(int group)
Capturing groups are indexed from left to right, starting at one. Group zero denotes the entire pattern, so the expression m.start(0) is equivalent to m.start().
start
in interface MatchResult
group
- The index of a capturing group in this matcher's pattern
IllegalStateException
- If no match has yet been attempted,
or if the previous match operation failed
IndexOutOfBoundsException
- If there is no capturing group in the pattern
with the given indexpublic int end()
end
in interface MatchResult
IllegalStateException
- If no match has yet been attempted,
or if the previous match operation failedpublic int end(int group)
Capturing groups are indexed from left to right, starting at one. Group zero denotes the entire pattern, so the expression m.end(0) is equivalent to m.end().
end
in interface MatchResult
group
- The index of a capturing group in this matcher's pattern
IllegalStateException
- If no match has yet been attempted,
or if the previous match operation failed
IndexOutOfBoundsException
- If there is no capturing group in the pattern
with the given indexpublic String group()
For a matcher m with input sequence s, the expressions m.group() and s.substring(m.start(), m.end()) are equivalent.
Note that some patterns, for example a*, match the empty string. This method will return the empty string when the pattern successfully matches the empty string in the input.
group
in interface MatchResult
IllegalStateException
- If no match has yet been attempted,
or if the previous match operation failedpublic String group(int group)
For a matcher m, input sequence s, and group index g, the expressions m.group(g) and s.substring(m.start(g), m.end(g)) are equivalent.
Capturing groups are indexed from left to right, starting at one. Group zero denotes the entire pattern, so the expression m.group(0) is equivalent to m.group().
If the match was successful but the group specified failed to match any part of the input sequence, then null is returned. Note that some groups, for example (a*), match the empty string. This method will return the empty string when such a group successfully matches the empty string in the input.
group
in interface MatchResult
group
- The index of a capturing group in this matcher's pattern
IllegalStateException
- If no match has yet been attempted,
or if the previous match operation failed
IndexOutOfBoundsException
- If there is no capturing group in the pattern
with the given indexpublic int groupCount()
Group zero denotes the entire pattern by convention. It is not included in this count.
Any non-negative integer smaller than or equal to the value returned by this method is guaranteed to be a valid group index for this matcher.
groupCount
in interface MatchResult
public boolean matches()
If the match succeeds then more information can be obtained via the start, end, and group methods.
public boolean find()
This method starts at the beginning of this matcher's region, or, if a previous invocation of the method was successful and the matcher has not since been reset, at the first character not matched by the previous match.
If the match succeeds then more information can be obtained via the start, end, and group methods.
public boolean find(int start)
If the match succeeds then more information can be obtained via the
start, end, and group methods, and subsequent
invocations of the find()
method will start at the first
character not matched by this match.
IndexOutOfBoundsException
- If start is less than zero or if start is greater than the
length of the input sequence.public boolean lookingAt()
Like the matches
method, this method always starts
at the beginning of the region; unlike that method, it does not
require that the entire region be matched.
If the match succeeds then more information can be obtained via the start, end, and group methods.
public static String quoteReplacement(String s)
String
for the specified
String
.
This method produces a String
that will work
use as a literal replacement s
in the
appendReplacement
method of the Matcher
class.
The String
produced will match the sequence of characters
in s
treated as a literal sequence. Slashes ('\') and
dollar signs ('$') will be given no special meaning.
s
- The string to be literalized
public Matcher appendReplacement(StringBuffer sb, String replacement)
This method performs the following actions:
It reads characters from the input sequence, starting at the
append position, and appends them to the given string buffer. It
stops after reading the last character preceding the previous match,
that is, the character at index start()
- 1.
It appends the given replacement string to the string buffer.
It sets the append position of this matcher to the index of
the last character matched, plus one, that is, to end()
.
The replacement string may contain references to subsequences
captured during the previous match: Each occurrence of
$g will be replaced by the result of
evaluating group
(g).
The first number after the $ is always treated as part of
the group reference. Subsequent numbers are incorporated into g if
they would form a legal group reference. Only the numerals '0'
through '9' are considered as potential components of the group
reference. If the second group matched the string "foo", for
example, then passing the replacement string "$2bar" would
cause "foobar" to be appended to the string buffer. A dollar
sign ($) may be included as a literal in the replacement
string by preceding it with a backslash (\$).
Note that backslashes (\) and dollar signs ($) in the replacement string may cause the results to be different than if it were being treated as a literal replacement string. Dollar signs may be treated as references to captured subsequences as described above, and backslashes are used to escape literal characters in the replacement string.
This method is intended to be used in a loop together with the
appendTail
and find
methods. The
following code, for example, writes one dog two dogs in the
yard to the standard-output stream:
Pattern p = Pattern.compile("cat"); Matcher m = p.matcher("one cat two cats in the yard"); StringBuffer sb = new StringBuffer(); while (m.find()) { m.appendReplacement(sb, "dog"); } m.appendTail(sb); System.out.println(sb.toString());
sb
- The target string bufferreplacement
- The replacement string
IllegalStateException
- If no match has yet been attempted,
or if the previous match operation failed
IndexOutOfBoundsException
- If the replacement string refers to a capturing group
that does not exist in the patternpublic StringBuffer appendTail(StringBuffer sb)
This method reads characters from the input sequence, starting at
the append position, and appends them to the given string buffer. It is
intended to be invoked after one or more invocations of the appendReplacement
method in order to copy the
remainder of the input sequence.
sb
- The target string buffer
public String replaceAll(String replacement)
This method first resets this matcher. It then scans the input
sequence looking for matches of the pattern. Characters that are not
part of any match are appended directly to the result string; each match
is replaced in the result by the replacement string. The replacement
string may contain references to captured subsequences as in the appendReplacement
method.
Note that backslashes (\) and dollar signs ($) in the replacement string may cause the results to be different than if it were being treated as a literal replacement string. Dollar signs may be treated as references to captured subsequences as described above, and backslashes are used to escape literal characters in the replacement string.
Given the regular expression a*b, the input "aabfooaabfooabfoob", and the replacement string "-", an invocation of this method on a matcher for that expression would yield the string "-foo-foo-foo-".
Invoking this method changes this matcher's state. If the matcher is to be used in further matching operations then it should first be reset.
replacement
- The replacement string
public String replaceFirst(String replacement)
This method first resets this matcher. It then scans the input
sequence looking for a match of the pattern. Characters that are not
part of the match are appended directly to the result string; the match
is replaced in the result by the replacement string. The replacement
string may contain references to captured subsequences as in the appendReplacement
method.
Given the regular expression dog, the input "zzzdogzzzdogzzz", and the replacement string "cat", an invocation of this method on a matcher for that expression would yield the string "zzzcatzzzdogzzz".
Invoking this method changes this matcher's state. If the matcher is to be used in further matching operations then it should first be reset.
replacement
- The replacement string
NullPointerException
- if replacement
is null.
subsequences as neededpublic Matcher region(int start, int end)
start
parameter and end at the
index specified by the end
parameter.
Depending on the transparency and anchoring being used (see
useTransparentBounds
and
useAnchoringBounds
), certain constructs such
as anchors may behave differently at or around the boundaries of the
region.
start
- The index to start searching at (inclusive)end
- The index to end searching at (exclusive)
IndexOutOfBoundsException
- If start or end is less than zero, if
start is greater than the length of the input sequence, if
end is greater than the length of the input sequence, or if
start is greater than end.public int regionStart()
regionStart
(inclusive) and
regionEnd
(exclusive).
public int regionEnd()
regionStart
(inclusive) and
regionEnd
(exclusive).
public boolean hasTransparentBounds()
This method returns true if this matcher uses transparent bounds, false if it uses opaque bounds.
See useTransparentBounds
for a
description of transparent and opaque bounds.
By default, a matcher uses opaque region boundaries.
useTransparentBounds(boolean)
public Matcher useTransparentBounds(boolean b)
Invoking this method with an argument of true will set this matcher to use transparent bounds. If the boolean argument is false, then opaque bounds will be used.
Using transparent bounds, the boundaries of this matcher's region are transparent to lookahead, lookbehind, and boundary matching constructs. Those constructs can see beyond the boundaries of the region to see if a match is appropriate.
Using opaque bounds, the boundaries of this matcher's region are opaque to lookahead, lookbehind, and boundary matching constructs that may try to see beyond them. Those constructs cannot look past the boundaries so they will fail to match anything outside of the region.
By default, a matcher uses opaque bounds.
b
- a boolean indicating whether to use opaque or transparent
regions
hasTransparentBounds()
public boolean hasAnchoringBounds()
This method returns true if this matcher uses anchoring bounds, false otherwise.
See useAnchoringBounds
for a
description of anchoring bounds.
By default, a matcher uses anchoring region boundaries.
useAnchoringBounds(boolean)
public Matcher useAnchoringBounds(boolean b)
Invoking this method with an argument of true will set this matcher to use anchoring bounds. If the boolean argument is false, then non-anchoring bounds will be used.
Using anchoring bounds, the boundaries of this matcher's region match anchors such as ^ and $.
Without anchoring bounds, the boundaries of this matcher's region will not match anchors such as ^ and $.
By default, a matcher uses anchoring region boundaries.
b
- a boolean indicating whether or not to use anchoring bounds.
hasAnchoringBounds()
public String toString()
Returns the string representation of this matcher. The
string representation of a Matcher
contains information
that may be useful for debugging. The exact format is unspecified.
toString
in class Object
public boolean hitEnd()
Returns true if the end of input was hit by the search engine in the last match operation performed by this matcher.
When this method returns true, then it is possible that more input would have changed the result of the last search.
public boolean requireEnd()
Returns true if more input could change a positive match into a negative one.
If this method returns true, and a match was found, then more input could cause the match to be lost. If this method returns false and a match was found, then more input might change the match but the match won't be lost. If a match was not found, then requireEnd has no meaning.
|
JavaTM 2 Platform Standard Ed. 5.0 |
|||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
Copyright © 2004, 2010 Oracle and/or its affiliates. All rights reserved. Use is subject to license terms. Also see the documentation redistribution policy.


Before Change
word_reps = LSTM.transduce([LOOKUP[x] for x in words])
// Softmax scores
W, b = dy.parameter(W_sm, b_sm)
scores = [dy.affine_transform([b, W, x]) for x in word_reps]
return scores
After Change
// Transduce all batch elements with an LSTM
fwd_init = fwdLSTM.initial_state()
fwd_word_reps = fwd_init.transduce(word_embs)
bwd_init = bwdLSTM.initial_state()
bwd_word_reps = bwd_init.transduce(reversed(word_embs))
combined_word_reps = [dy.concatenate([f, b]) for f, b in zip(fwd_word_reps, reversed(bwd_word_reps))]
// Softmax scores
W = dy.parameter(W_sm)
b = dy.parameter(b_sm)


The ScaleOut hServer® Java API library integrates a Hadoop MapReduce execution engine with ScaleOut hServer’s in-memory data grid (IMDG). This open source library [1] consists of several components: a Hadoop MapReduce execution engine, which runs MapReduce jobs in memory without using Hadoop job trackers or task trackers, and four I/O components to pass data between the IMDG and a MapReduce job. The I/O components include the Named Map Input Format, the Named Cache Input Format, and the Grid Output Format, which together allow MapReduce applications to use the IMDG as a data source and/or result storage for MapReduce jobs. In addition, the Dataset Input Format accelerates the performance of MapReduce jobs by caching HDFS datasets in the IMDG.
Using ScaleOut hServer, developers can write and run standard Hadoop MapReduce applications in Java, and these applications can be executed stand-alone by ScaleOut hServer’s execution engine. The Apache Hadoop distribution does not need to be installed to run MapReduce programs; optionally, it can be installed to make use of other Hadoop components, such as the Hadoop Distributed File System (HDFS). (If HDFS is used to store data sets analyzed by MapReduce, ScaleOut hServer should be installed on the same cluster of servers to minimize network overhead.) ScaleOut hServer supports standard Apache Hadoop as well as third party distributions by Hortonworks and Cloudera. ScaleOut hServer’s execution engine offers very fast job scheduling (measured in milliseconds), highly optimized data combining and shuffling, in-memory storage of intermediate key/value pairs within the IMDG, optional use of sorting, and fast, pipelined access to in-memory data within the IMDG for analysis. In addition, ScaleOut hServer automatically sets the number of splits, partitions, and slots for IMDG-based data. Lastly, the performance of the Hadoop MapReduce engine automatically scales as servers are added to the cluster, and IMDG-based data is automatically redistributed across the cluster as needed.
Developers can use ScaleOut hServer’s Java APIs [2] to create, read, update, and delete objects within the IMDG. This enables MapReduce applications to input "live" data sets which are stored and updated within the IMDG. Complex IMDG-based objects can be stored within a named cache, which provides comprehensive semantics, such as object timeouts, dependency relationships, pessimistic locking, and access by remote IMDGs. These objects are input to MapReduce applications using the Named Cache input format. Alternatively, large populations of small key/value pairs can be efficiently stored within a named map, which provides highly efficient memory usage and streamlined semantics following the Java concurrent map model. These objects can be input to MapReduce applications using the Named Map input format. The Grid output format can be used to output objects from MapReduce applications to a named cache or a named map.
Note that some advanced features of the Java APIs, such as event handling, parallel query and parallel method invocation are only available under a full ScaleOut StateServer® or ScaleOut ComputeServer™ license.
This programming guide is intended to be a supplement to the Java API documentation and the ScaleOut StateServer (SOSS) Help File included with ScaleOut hServer. It focuses on the Java components used with Hadoop MapReduce applications.
Please refer to the ScaleOut StateServer help file for instructions on installing the IMDG service on a cluster of servers. ScaleOut hServer installs the ScaleOut StateServer grid service on all servers. When a MapReduce job is started, ScaleOut hServer automatically starts Java Virtual Machines (JVMs) on all servers (called an invocation grid) to implement its scalable Hadoop MapReduce engine.
The following "quick start" instructions for installing the IMDG on Linux will get you started. For each server in the cluster:
- Download the RPM file from the ScaleOut Software web site.
-
Install the RPM:
sudo rpm -ivh soss-5.4.1-253.el6.x86_64.rpm
(It will be installed into /usr/local/soss5.) -
Verify the daemon is running:
soss query
-
Configure the network settings to bind the grid service to the desired network, for example:
soss set net_interface=<IP_ADDRESS> subnet_mask=<IP_ADDRESS>
(You also can edit the soss_params.txt file in the installation directory and restart the daemon.) -
Join this server to the cluster of IMDG servers:
soss join
To install ScaleOut StateServer on Windows, download the appropriate installer from the the ScaleOut Software web site and follow the installation instructions. The server is installed as a Windows service and can be configured by using the SOSS Management Console.
The IMDG servers will automatically discover each other and balance the storage workload among all servers.
Sufficient physical memory should be provisioned for the IMDG to hold all data set objects and their associated replicas following the best practices described in the SOSS Help File. By default, named cache objects have one replica on a different server to ensure high availability in case a server fails. For example, if a 100GB data set is to be stored in the IMDG, this will require approximately 200GB of aggregate memory for the data set and its replicas (using the default parameters). If the cluster has four servers, this will require 50GB per server. Note that additional memory is required for object metadata and other data structures used by the IMDG. To maximize the performance of MapReduce applications, named map objects and intermediate key/value pairs do not use replicas; replicas optionally can be enabled for named maps (described below).
For MapReduce applications which input data from HDFS and store results in HDFS, the IMDG’s memory is only used to store intermediate results sent from the mappers to the reducers. If multiple grid servers are added to the cluster, their memory automatically is combined to store very large sets of intermediate results. Replicas are not used for intermediate results, and these results are cleared when a MapReduce job completes.
The Java API library for ScaleOut hServer can be found in soss-hserver-5.4-*.jar, and the Java API library for creating, reading, updating, and deleting objects can be found in soss-jnc-5.4.jar.
These jars and their dependencies are located in the java_api subdirectory of the ScaleOut StateServer installation directory.
ScaleOut hServer runs with several Hadoop environments, including those configured to run MapReduce on YARN, and it can serve as a MapReduce execution engine for Apache Hive (see configuration instructions).
If the MapReduce job running in ScaleOut hServer uses HDFS as the data input and/or output, it is necessary for the set of
library JARs on the client classpath to match the distribution of Hadoop used to run the HDFS data node(s) and name node(s).
Apache Hadoop 2.4.1 distribution-specific JARs are located in the ScaleOut hServer installation directory under java_api/hslib/hadoop-2.4.1
. Additional distribution-specific JARs can be downloaded from the website at: http://www.scaleoutsoftware.com/support/support-downloads/. For convenience, a shell script to automatically download the JARs from the website is located in the ScaleOut hServer installation
directory under java_api/hslib/
(please see the included README for usage instructions). After downloading the JARs, move them to the installation folder
under java_api/hslib/
. To run a ScaleOut hServer MapReduce job, the libraries in java_api/*
and java_api/lib/*
, and the distribution specific JARs should be included in the classpath on the invoking client.
ScaleOut hServer ships with support for the following Hadoop distributions:
| Distribution | Library path for java_api (JavaApi on Windows) |
|---|---|
Apache Hadoop 1.2.1 |
hslib/hadoop-1.2.1 |
Apache Hadoop 2.4.1 |
hslib/hadoop-2.4.1 |
CDH 4.4.0 |
hslib/cdh4.4.0 |
CDH 5 (MR1) |
hslib/cdh5.0.2 |
CDH 5 (YARN) |
hslib/cdh5.0.2-yarn |
CDH 5.2 (MR1) |
hslib/cdh5.2.1 |
CDH 5.2 (YARN) |
hslib/cdh5.2.1-yarn |
HDP 2.1 (YARN) |
hslib/hdp2.1-yarn |
HDP 2.2 (YARN) |
hslib/hdp2.2-yarn |
IBM BigInsights 3.0 |
hslib/ibm-bi-3.0.0 |
[1] The open source ScaleOut hServer Java API library (soss-hserver-5.4-*.jar) is licensed under the Apache License, Version 2.0 (http://www.apache.org/licenses/LICENSE-2.0).
[2] The ScaleOut StateServer Java API library (soss-jnc-5.4.jar) is licensed under the ScaleOut StateServer End User License Agreement.


National Climate Assessment: The colors on the map show temperature changes over the past 22 years (1991-2012) compared to the 1901-1960 average … . The bars on the graphs show the average temperature changes by decade for 1901-2012 (relative to the 1901-1960 average) for each region. The far right bar in each graph (2000s decade) includes 2011 and 2012. The period from 2001 to 2012 was warmer than any previous decade in every region. (Figure source: NOAA NCDC / CICS-NC). Source.


Review: Corsair iCUE LS100 Monitor Back Lighting Kit 19 Nov 2019, 11:19 by Hilbert Hagedoorn Today we're presenting the Corsair iCUE LS100, a kit that brings some smooth and vibrant lighting to the back of your monitors for an immersive experience, you might even call it a bit of ambi-lighting. Read the full review here. Related Stories


Takes a character
/text
string and evaluates it as if it was code (an R expression). parse()
returns the text as if it was code. eval
then runs/evaluates the code afterwards.
evalparse(x)
| x | A |
|---|
Simplistically, the purpose of this idea is to get into the realm of code that can write code, but this is dependent on either the input parameters or the data, so not automatic. The purpose of this specific function, however, is for saving on typing: eval(parse(text = x))
VS evalparse(x)
.
eval
, parse
if(runif(n = 1) >= 0.5){ vec <- c("mickey mouse", "bambi", "herbert hoover") } else { vec <- c(12.6548, 13.21549, 84.946562) } my_string <- sprintf( "as.%s( substring( trimws(vec, which = 'left') , first = 1 , last = 4 ) )" , class(vec) ) evalparse(my_string)#> [1] 12.6 13.2 84.9


Display resizable geo polyline on a map
This example displays a polyline object, which can be resized by dragging its vertices.
There is a main H.map.Group
container, which contains resizable H.map.Polyline
and another container containing markers
(H.map.Marker
) as polyline's vertices (corners) used for resizing. Markers, shown as small red circles,
are hidden by default and shown only when mouse position is over the main group object, or is touched on touch device
(pointerenter
event). In order to listen to drag
event, object's draggable
property must be set to true. In order to have smoother resizing, the object's volatility
property should be set to true.