While the team homework deadline is the same as usual, it’s highly recommended
that you form your team early so that you have plenty of time to propose.
The individual homework’s intent is give you an opportunity to review and
really understand your own teams’ apps made so far. If you already have a pretty good grasp
of your teams’ works along the way, this part should take less time. If you feel you are
behind a bit, please start early. Don’t wait until the weekend.
Requirements
Team
[X] Form a team of FOUR
[X] Write a proposal of a together app that integrates ideas from every team
member
Individual
[ ] Your personal repo should contain the same code of all the apps your teams
have developed and submitted up to this point. This may involve copying code and database
from your teams’ repos and making sure everything works.
[ ] Every link on the index page of your book (e.g.,
https://ucdd2-book.firebaseapp.com/)
should be working and will show the latest content.


API Reference¶
Changed in version 0.2.0: Interpolation of values in configuration files now works with default values from the specification.
Easy and simple configuration.
See also: Introduction
Overview¶
Special value for options that are not found and have no default. |
|
Special value for options without a value. |
|
Configuration class. |
|
Raised if there is a problem with the configuration. |
|
Raised if an option already exists in a section. |
|
Base Exception. |
|
Raised on an attempt to set a readonly option. |
|
Raised if there is a problem with the specification. |
|
For an explanation see the Introduction. |
|
Return a function that can be used as a converter. |
|
Return a converter function for logging levels. |
|
Return a converter function with a predicate. |
|
Return a function that can be used as a converter. |
-
easimpconf.
NOTFOUND
¶ Special value for options that are not found and have no default.
The truth value is
False
.
-
easimpconf.
NOVALUE
¶ Special value for options without a value (see Introduction).
The truth value is
True
-
class
easimpconf.
Config
(options, create_props, kwargs)[source]¶ Configuration class.
An instance of this class is returned by the function
configure()
.If
create_properties=True
it will have a property for each configuration option named as explained in the Introduction. For extra data this is just the name given in theadd()
method.Options can also be accessed like this:
config[secname, optname]
. To check if an option exists, thein
operator can be used:(secname, optname) in config
.For extra data either
None
must be used for the section name or only the name of the data, i.e.config[None, name]
andconfig[name]
are equivalent as are(None, name) in config
andname in config
.When a
Config
object is used as an iterator it yields 3-tuples for each option:(secname, optname, value)
.-
add
(key, value, readonly=True)[source]¶ Add extra data to configuration or an option to a section.
- Parameters
key – either a name of extra data or a tuple
('secname', 'optname')
value – the value of the data
readonly (bool) – if
True
the data cannot be changed
- Type
- Raises
DuplicateError – if an option already exists in a section
AttributeError – if an attribute with the same name already exists (only if
create_properties=True
)ConfigError – if
create_properties=True
andname
orsecname_optname
is not a valid Python identifier; the data can still be accessed withcfg['name']
orcfg['secname', 'optname']
-
extras
()[source]¶ Return names of extra data added with
add()
.- Returns
list with names of extra data
- Return type
-
write
(file, space_around_delimiters=True)[source]¶ Write a representation of the configuration to the specified file.
Extra data added with
add()
will be excluded.- Parameters
file (path-like object or text file opened for writing) – the file
space_around_delimiters (bool) – if
True
, delimiters between keys and values are surrounded by spaces
-
-
easimpconf.
configure
(conf, spec, *, create_properties=True, converters=None, **kwargs)[source]¶ For an explanation see the Introduction.
- Parameters
conf (path-like object or text file opened for reading or
ConfigParser
object) – the configurationspec (path-like object or text file opened for reading or
None
) – the specificationcreate_properties (bool) – if
True
properties will be created, else only item access with [sec,opt] can be usedconverters (dict) – same as the
converters
argument ofConfigParser
but used directly by this functionkwargs – arguments for the
ConfigParser
(ignored ifconf
is aConfigParser
object)
- Returns
configuration object
- Return type
- Raises
SpecError – if there is a problem with the specification
ConfigError – if there is a problem with the configuration
configparser.Error – from
ConfigParser
-
easimpconf.
convert_choice
(choices, *, converter=None, default=None)[source]¶ Return a function that can be used as a converter.
For an example see the source code of
convert_loglevel()
.- Parameters
choices – any container type that supports the
in
operator with acceptable valuesconverter – a callable that takes one string argument and returns an object of the desired type;
None
means no conversiondefault – a default value of the desired type or a subclass of
Exception
which will be raised
- Returns
converter function
- Return type
function(str)
-
easimpconf.
convert_loglevel
(default_level=None, *, numeric=False)[source]¶ Return a converter function for logging levels.
Valid values are the logging levels as defined in the
logging
module.- Parameters
- Raises
ValueError – if not a valid logging level and
default_level=None
- Returns
converter function
- Return type
function(str)
-
easimpconf.
convert_predicate
(predicate, *, converter=None, default=None)[source]¶ Return a converter function with a predicate.
>>> positive_float = convert_predicate(lambda x: x > 0.0, ... converter=float, default=0.0) >>> positive_float('1.2') 1.2 >>> positive_float('-1.2') 0.0
- Parameters
predicate – a callable that takes one argument of the desired type and returns
True
if it is acceptableconverter – a callable that takes one string argument and returns an object of the desired type;
None
means no conversiondefault – a default value of the desired type or a subclass of
Exception
which will be raised instead
- Returns
converter function
- Return type
function(str)
-
easimpconf.
convert_string
(*, start='|', newlines=True)[source]¶ Return a function that can be used as a converter.
The default converter
str
handles multiline values likeConfigParser
, i.e. preserving newlines but ignoring indentations (because nothing gets realy converted).A converter returned by this function can handle such values different.
>>> s = ''' ... |def add(a, b): ... | return a + b ''' >>> print(convert_string()(s)) def add(a, b): return a + b
- Parameters
- Raises
ValueError – if
start
is not a single character- Returns
converter function
- Return type
function(str)


This page is under construction. I haven't figure out what should be put here. So I just changed some information based on the theme author's introduction.
I am Ĉigo Esperisto, a freelance translator. I completed my four-year program in School of Foreign Languagee at Mianyang Normal University on July 2005.
My interests cover Translation, Esperanto, Linguistics, Dialetical Materialism and Historical Materialism , GTD and note-taking with Emacs and org mode , Science Fiction and Popular Science.
I'm a big fan of MAC, Git/esperisto, and Linux. In my free time, I read books on my interests, learn some new things, and take care of my lovely son.
{% for post in site.posts limit:3 %}
- {% capture y %}{{post.date | date:"%Y"}}{% endcapture %} {% assign d = post.date | date: "%d" %} {% assign m = post.date | date: "%B" %} {% case m %} {% when 'April' or 'May' or 'June' or 'July' %}{{ m }} {% when 'September' %}Sept {% else %}{{ post.date | date: "%b" }} {% endcase %} {% case d %} {% when '01' or '21' or '31' %}{{ %d }} {% when '02' or '22' %}{{ %d }} {% when '03' or '23' %}{{ %d }} {% else %}{{ %d }} {% endcase %}, {{ post.date | date: "%Y" }}{{ post.title }}
{% endfor %}


SUBROUTINE SLAED1( N, D, Q, LDQ, INDXQ, RHO, CUTPNT, WORK, IWORK, $ INFO ) * * -- LAPACK routine (version 3.1) -- * Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. * November 2006 * * .. Scalar Arguments .. INTEGER CUTPNT, INFO, LDQ, N REAL RHO * .. * .. Array Arguments .. INTEGER INDXQ( * ), IWORK( * ) REAL D( * ), Q( LDQ, * ), WORK( * ) * .. * * Purpose * ======= * * SLAED1 computes the updated eigensystem of a diagonal * matrix after modification by a rank-one symmetric matrix. This * routine is used only for the eigenproblem which requires all * eigenvalues and eigenvectors of a tridiagonal matrix. SLAED7 handles * the case in which eigenvalues only or eigenvalues and eigenvectors * of a full symmetric matrix (which was reduced to tridiagonal form) * are desired. * * T = Q(in) ( D(in) + RHO * Z*Z' ) Q'(in) = Q(out) * D(out) * Q'(out) * * where Z = Q'u, u is a vector of length N with ones in the * CUTPNT and CUTPNT + 1 th elements and zeros elsewhere. * * The eigenvectors of the original matrix are stored in Q, and the * eigenvalues are in D. The algorithm consists of three stages: * * The first stage consists of deflating the size of the problem * when there are multiple eigenvalues or if there is a zero in * the Z vector. For each such occurence the dimension of the * secular equation problem is reduced by one. This stage is * performed by the routine SLAED2. * * The second stage consists of calculating the updated * eigenvalues. This is done by finding the roots of the secular * equation via the routine SLAED4 (as called by SLAED3). * This routine also calculates the eigenvectors of the current * problem. * * The final stage consists of computing the updated eigenvectors * directly using the updated eigenvalues. The eigenvectors for * the current problem are multiplied with the eigenvectors from * the overall problem. * * Arguments * ========= * * N (input) INTEGER * The dimension of the symmetric tridiagonal matrix. N >= 0. * * D (input/output) REAL array, dimension (N) * On entry, the eigenvalues of the rank-1-perturbed matrix. * On exit, the eigenvalues of the repaired matrix. * * Q (input/output) REAL array, dimension (LDQ,N) * On entry, the eigenvectors of the rank-1-perturbed matrix. * On exit, the eigenvectors of the repaired tridiagonal matrix. * * LDQ (input) INTEGER * The leading dimension of the array Q. LDQ >= max(1,N). * * INDXQ (input/output) INTEGER array, dimension (N) * On entry, the permutation which separately sorts the two * subproblems in D into ascending order. * On exit, the permutation which will reintegrate the * subproblems back into sorted order, * i.e. D( INDXQ( I = 1, N ) ) will be in ascending order. * * RHO (input) REAL * The subdiagonal entry used to create the rank-1 modification. * * CUTPNT (input) INTEGER * The location of the last eigenvalue in the leading sub-matrix. * min(1,N) <= CUTPNT <= N/2. * * WORK (workspace) REAL array, dimension (4*N + N**2) * * IWORK (workspace) INTEGER array, dimension (4*N) * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if INFO = 1, an eigenvalue did not converge * * Further Details * =============== * * Based on contributions by * Jeff Rutter, Computer Science Division, University of California * at Berkeley, USA * Modified by Francoise Tisseur, University of Tennessee. * * ===================================================================== * * .. Local Scalars .. INTEGER COLTYP, CPP1, I, IDLMDA, INDX, INDXC, INDXP, $ IQ2, IS, IW, IZ, K, N1, N2 * .. * .. External Subroutines .. EXTERNAL SCOPY, SLAED2, SLAED3, SLAMRG, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 * IF( N.LT.0 ) THEN INFO = -1 ELSE IF( LDQ.LT.MAX( 1, N ) ) THEN INFO = -4 ELSE IF( MIN( 1, N / 2 ).GT.CUTPNT .OR. ( N / 2 ).LT.CUTPNT ) THEN INFO = -7 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'SLAED1', -INFO ) RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * * The following values are integer pointers which indicate * the portion of the workspace * used by a particular array in SLAED2 and SLAED3. * IZ = 1 IDLMDA = IZ + N IW = IDLMDA + N IQ2 = IW + N * INDX = 1 INDXC = INDX + N COLTYP = INDXC + N INDXP = COLTYP + N * * * Form the z-vector which consists of the last row of Q_1 and the * first row of Q_2. * CALL SCOPY( CUTPNT, Q( CUTPNT, 1 ), LDQ, WORK( IZ ), 1 ) CPP1 = CUTPNT + 1 CALL SCOPY( N-CUTPNT, Q( CPP1, CPP1 ), LDQ, WORK( IZ+CUTPNT ), 1 ) * * Deflate eigenvalues. * CALL SLAED2( K, N, CUTPNT, D, Q, LDQ, INDXQ, RHO, WORK( IZ ), $ WORK( IDLMDA ), WORK( IW ), WORK( IQ2 ), $ IWORK( INDX ), IWORK( INDXC ), IWORK( INDXP ), $ IWORK( COLTYP ), INFO ) * IF( INFO.NE.0 ) $ GO TO 20 * * Solve Secular Equation. * IF( K.NE.0 ) THEN IS = ( IWORK( COLTYP )+IWORK( COLTYP+1 ) )*CUTPNT + $ ( IWORK( COLTYP+1 )+IWORK( COLTYP+2 ) )*( N-CUTPNT ) + IQ2 CALL SLAED3( K, N, CUTPNT, D, Q, LDQ, RHO, WORK( IDLMDA ), $ WORK( IQ2 ), IWORK( INDXC ), IWORK( COLTYP ), $ WORK( IW ), WORK( IS ), INFO ) IF( INFO.NE.0 ) $ GO TO 20 * * Prepare the INDXQ sorting permutation. * N1 = K N2 = N - K CALL SLAMRG( N1, N2, D, 1, -1, INDXQ ) ELSE DO 10 I = 1, N INDXQ( I ) = I 10 CONTINUE END IF * 20 CONTINUE RETURN * * End of SLAED1 * END


Table of Contents
dll-path
and
hardcode-dll-paths
properties useful?
This is not possible, since Jamfile does not have "current" value of any
feature, be it toolset, build variant or anything else. For a single invocation of
bjam
, any given main target can be built with several property sets.
For example, user can request two build variants on the command line. Or one library
is built as shared when used from one application, and as static when used from another.
Obviously, Jamfile is read only once, so generally, there's no single value of a feature
you can access in Jamfile.
A feature has a specific value only when building a target, and there are two ways how you can use that value:


Linting demo
This is a sentence ,but the comma isn't in the right place.
Too-minor header
This is an image without alt text. You should obviously hover over the messages below to see where they occur.
>
The browser DOM serves its purpose—representing complex webpages—very well. But its huge scope and loose structure makes it difficult to make assumptions about. A document model that represents a smaller set of documents can be easier to reason about.
This demo implements a simple document linter that finds problems in your document, and makes it easy to fix them.
The full source code for this demo is here.
Next demo: change tracking.
<


Given a binary tree, determine whether it is a binary search tree or not.
Example, the tree given below should return False.
10
/ \
8 12
\
11
Considering the properties of a binary search tree, we can derive at the conclusion that for a binary tree to be a binary search tree, each node has a range of value that is allowed for it.
For example, the left child of the root can have values in the range (-infinity to root.value).
Similarly, right child of the root can have values in the range (root.value, +infinity).
Using this observation we can devise an algorithm such that for each node we pass a valid range for its value and check if it has a valid value or not.


--- layout: post published: true title: Numerai EDA mathjax: false featured: true comments: false categories: - Jupyter Notebook - Python - Data Science - EDA tags: 'Python, Jupyter Notebook, Data Science, EDA' ---


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---
layout: discography
title: MESS-GAME Vol.2
description: first HARD DANCE / HARDCORE Compilation
image: /img/works/album/messgame2.jpg
caption: MESS-GAME Vol.2 Cover Art
date: 2013.12.15
categories:
- Works
- Discography
tags:
- Regular
- Original
soundcloud: 116370362
playlist: none
youtube: none
---
Track List
- Asterios 'the starry firmament'
ATAS
- REPLICA
Aresynth
- Serpent
wigen
- GREMLIN EFFECT
RMHN a.k.a. RAVEN@TION
- Rudely Crimson Girl
SANY-ON
- Skadi
mzet:-P
- SPRINTER
Aresynth
- Nemesis
0492
- Chimere
Roy Mikelate
- Basilisk
SANY-ON
- VERONICA
RMHN
- Catalog Num
- HMDA-0004
- Release Date
- {{ page.date }}
- Producer
- RMHN
- Composer
- RMHN, SANY-ON, mzet:-P, Aresynth, 0492, wigen, ATAS, Roy Mikelate
- Mastering
- RMHN
- Designer
- BULUB, RMHN
- Price
- 15,000won
Buy


DEGreport.Rmd
Abstract
DEGreport package version: 1.17.5
Lorena Pantano Harvard TH Chan School of Public Health, Boston, US
library(DEGreport)
data(humanGender)
We are going to do a differential expression analysis with edgeR/DESeq2. We have an object that is coming from the edgeR package. It contains a gene count matrix for 85 TSI HapMap individuals, and the gender information. With that, we are going to apply the glmFit
function or DESeq2 to get genes differentially expressed between males and females.
library(DESeq2)
idx <- c(1:10, 75:85)
dds <- DESeqDataSetFromMatrix(assays(humanGender)[[1]][1:1000, idx],
colData(humanGender)[idx,], design=~group)
dds <- DESeq(dds)
res <- results(dds)
We need to extract the experiment design data.frame where the condition is Male or Female.
counts <- counts(dds, normalized = TRUE)
design <- as.data.frame(colData(dds))
A main assumption in library size factor calculation of edgeR and DESeq2 (and others) is that the majority of genes remain unchanged. Plotting the distribution of gene ratios between each gene and the average gene can show how true this is. Not super useful for many samples because the plot becomes crowed.
degCheckFactors(counts[, 1:6])
p-value distribution gives an idea on how well you model is capturing the input data and as well whether it could be some problem for some set of genes. In general, you expect to have a flat distribution with peaks at 0 and 1. In this case, we add the mean count information to check if any set of genes are enriched in any specific p-value range.
Variation (dispersion) and average expression relationship shouldn’t be a factor among the differentially expressed genes. When plotting average mean and standard deviation, significant genes should be randomly distributed.
In this case, it would be good to look at the ones that are totally outside the expected correlation.
You can put this tree plots together using degQC
.
degQC(counts, design[["group"]], pvalue = res[["pvalue"]])
Another important analysis to do if you have covariates is to calculate the correlation between PCs from PCA analysis to different variables you may think are affecting the gene expression. This is a toy example of how the function works with raw data, where clearly library size correlates with some of the PCs.
resCov <- degCovariates(log2(counts(dds)+0.5),
colData(dds))
Also, the correlation among covariates and metrics from the analysis can be tested. This is useful when the study has multiple variables, like in clinical trials. The following code will return a correlation table, and plot the correlation heatmap for all the covariates and metrics in a table.
cor <- degCorCov(colData(dds))
names(cor)
## [1] "cor" "corMat" "fdrMat" "plot"
A quick HTML report can be created with createReport
to show whether a DE analysis is biased to a particular set of genes. It contains the output of degQC,
degVB and degMB
.
createReport(colData(dds)[["group"]], counts(dds, normalized = TRUE),
row.names(res)[1:20], res[["pvalue"]], path = "~/Downloads")
Here, we show some useful plots for differentially expressed genes.
DEGSet
is a class to store the DE results like the one from results
function. DESeq2 offers multiple way to ask for contrasts/coefficients. With degComps
is easy to get multiple results in a single object:
degs <- degComps(dds, combs = "group",
contrast = list("group_Male_vs_Female",
c("group", "Female", "Male")))
names(degs)
## [1] "group_Male_vs_Female" "group_Female_vs_Male"
degs
contains 3 elements, one for each contrast/coefficient asked for. It contains the results output in the element raw
and the output of lfcShrink
in the element shrunken
. To obtain the results from one of them, use the method dge
:
deg(degs[[1]])
## log2 fold change (MAP): group Male vs Female
## Wald test p-value: group Male vs Female
## DataFrame with 1000 rows and 6 columns
## baseMean log2FoldChange lfcSE
## <numeric> <numeric> <numeric>
## ENSG00000067048 1025.03783081851 1.93948751981495 0.100694015277881
## ENSG00000012817<PHONE_NUMBER>88588 3.70056395376919 0.0989888483685393
## ENSG00000067646<PHONE_NUMBER>26402 3.32284568660191 0.0995193327364417
## ENSG00000005889<PHONE_NUMBER>30697 -0.489434740758985 0.092936309939388
## ENSG00000006757 92.6611112908156 -0.472926180708218 0.0992749166821469
## ... ... ... ...
## ENSG00000068120 1214.09670077803 -0.000114321924517496 0.0797226606999421
## ENSG00000072062<PHONE_NUMBER>58596 0.000559219142042069 0.0915352171745646
## ENSG00000076770 1019.79638067687 0.000850081845600191 0.101666325101382
## ENSG00000078967<PHONE_NUMBER>51996 0.000415745391578262 0.0959757955312269
## ENSG00000079246 5226.33895971623 0.000149584255113252 0.0926205100248813
## stat pvalue
## <numeric> <numeric>
## ENSG00000067048 23.9943800011737 3.1830203922112e-127
## ENSG00000012817 21.8045168852374 2.10213939599488e-105
## ENSG00000067646 15.4838473278579 4.45984434298121e-54
## ENSG00000005889 -5.26370810368133 1.41178536870763e-07
## ENSG00000006757 -4.75700569609359 1.96485627341598e-06
## ... ... ...
## ENSG00000068120 -0.00143399782360411 0.998855835668455
## ENSG00000072062 0.00610871981311749 0.995125977088407
## ENSG00000076770 0.00836192966137436 0.993328223175276
## ENSG00000078967 0.00432971042062787 0.99654540169618
## ENSG00000079246 0.00161499511902357 0.998711420888906
## padj
## <numeric>
## ENSG00000067048 3.1830203922112e-124
## ENSG00000012817 1.05106969799744e-102
## ENSG00000067646 1.48661478099374e-51
## ENSG00000005889 3.52946342176908e-05
## ENSG00000006757 0.000392971254683197
## ... ...
## ENSG00000068120 0.998855835668455
## ENSG00000072062 0.998855835668455
## ENSG00000076770 0.998855835668455
## ENSG00000078967 0.998855835668455
## ENSG00000079246 0.998855835668455
By default it would output the shrunken
table always, as defined by degDefault
, that contains the default table to get.
To get the original results table, use the parameter as this:
deg(degs[[1]], "raw", "tibble")
## # A tibble: 1,000 x 7
## gene baseMean log2FoldChange lfcSE stat pvalue padj
## * <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 ENSG00000067… 1025. 10.2 0.423 24.0 3.18e-127 3.18e-124
## 2 ENSG00000012… 412. 9.24 0.424 21.8 2.10e-105 1.05e-102
## 3 ENSG00000067… 170. 10.2 0.658 15.5 4.46e- 54 1.49e- 51
## 4 ENSG00000005… 671. -0.692 0.131 -5.26 1.41e- 7 3.53e- 5
## 5 ENSG00000006… 92.7 -0.767 0.161 -4.76 1.96e- 6 3.93e- 4
## 6 ENSG00000073… 220. -1.87 0.421 -4.44 8.89e- 6 1.48e- 3
## 7 ENSG00000005… 2027. -0.742 0.176 -4.21 2.59e- 5 3.69e- 3
## 8 ENSG00000005… 1234. 0.389 0.0952 4.08 4.44e- 5 5.56e- 3
## 9 ENSG00000003… 394. 0.680 0.177 3.85 1.17e- 4 1.31e- 2
## 10 ENSG00000069… 107. -1.63 0.459 -3.56 3.71e- 4 3.71e- 2
## # ... with 990 more rows
Note that the format of the output can be changed to tibble, or data.frame with a third parameter tidy
.
The table will be always sorted by padj.
And easy way to get significant genes is:
significants(degs[[1]], fc = 0, fdr = 0.05)
## [1] "ENSG00000012817" "ENSG00000067646" "ENSG00000067048"
## [4] "ENSG00000005889" "ENSG00000006757" "ENSG00000005302"
## [7] "ENSG00000003400" "ENSG00000073282" "ENSG00000005020"
## [10] "ENSG00000069702"
This function can be used as well for a list of comparisons:
significants(degs, fc = 0, fdr = 0.05)
## [1] "ENSG00000012817" "ENSG00000067646" "ENSG00000067048"
## [4] "ENSG00000005889" "ENSG00000006757" "ENSG00000005302"
## [7] "ENSG00000003400" "ENSG00000073282" "ENSG00000005020"
## [10] "ENSG00000069702"
And it can returns the full table for a list:
significants(degs, fc = 0, fdr = 0.05, full = TRUE)
## # A tibble: 10 x 7
## gene log2FoldChange padj log2FoldChange_… log2FoldChange_…
## <chr> <dbl> <dbl> <dbl> <dbl>
## 1 ENSG… 0.388 1.31e- 2 -0.494 0.388
## 2 ENSG… 0.319 5.56e- 3 -0.351 0.319
## 3 ENSG… 0.541 3.69e- 3 0.541 -0.425
## 4 ENSG… 0.573 3.53e- 5 0.573 -0.489
## 5 ENSG… 0.585 3.93e- 4 0.585 -0.473
## 6 ENSG… 3.70 1.05e-102 -5.01 3.70
## 7 ENSG… 1.94 3.18e-124 -3.63 1.94
## 8 ENSG… 3.32 1.49e- 51 -4.43 3.32
## 9 ENSG… 0.453 3.71e- 2 0.453 -0.260
## 10 ENSG… 0.582 1.48e- 3 0.582 -0.339
## # ... with 2 more variables: padj_group_Female_vs_Male <dbl>,
## # padj_group_Male_vs_Female <dbl>
Since log2FoldChange are shrunken, the method for DEGSet class now can plot these changes as follow:
degMA(degs[[1]], diff = 2, limit = 3)
The blue arrows indicate how foldchange is affected by this new feature.
As well, it can plot the original MA plot:
degMA(degs[[1]], diff = 2, limit = 3, raw = TRUE)
or the correlation between the original log2FoldChange and the new ones:
degMA(degs[[1]], limit = 3, correlation = TRUE)
Volcano plot using the output of DESeq2. It mainly needs data.frame with two columns (logFC and pVal). Specific genes can be plot using the option plot\_text
(subset of the previous data.frame with a 3rd column to be used to plot the gene name).
res[["id"]] <- row.names(res)
show <- as.data.frame(res[1:10, c("log2FoldChange", "padj", "id")])
degVolcano(res[,c("log2FoldChange", "padj")], plot_text = show)
Note that the function is compatible with DEGset. Using degVolcano(degs[[1]])
is valid.
Plot top genes coloring by group. Very useful for experiments with nested groups. xs
can be time
or WT
/KO
, and group
can be treated
/untreated
. Another classification can be added, like batch
that will plot points with different shapes.
degPlot(dds = dds, res = res, n = 6, xs = "group")
Another option for plotting genes in a wide format:
degPlotWide(dds, rownames(dds)[1:5], group="group")
Markers can be used to show whether different conditions are enriched in different markers. For instance, in this example, Females and Males show different total expression for chromosome X/Y markers
data(geneInfo)
degSignature(humanGender, geneInfo, group = "group")
If you have a DESeq2 object, you can use degResults to create a full report with markdown code inserted, including figures and table with top de-regulated genes, GO enrichment analysis and heatmaps and PCA plots. If you set , different files will be saved there.
resreport <- degResults(dds = dds, name = "test", org = NULL,
do_go = FALSE, group = "group", xs = "group",
path_results = NULL)
## ## Comparison: test {.tabset}
##
##
##
out of 1000 with nonzero total read count
adjusted p-value < 0.1
LFC > 0 (up) : 6, 0.6%
LFC < 0 (down) : 7, 0.7%
outliers [1] : 0, 0%
low counts [2] : 0, 0%
(mean count < 47)
[1] see 'cooksCutoff' argument of ?results
[2] see 'independentFiltering' argument of ?results

NULL
##
##
## Differential expression file at: test_de.csv
##
## Normalized counts matrix file at: test_log2_counts.csv
##
## ### MA plot plot
##
##
## ### Volcano plot
##
##
##
## ### QC for DE genes
##
##
## ### Most significants, FDR< 0.05 and log2FC > 0.1 : 10
##
##
##
## ### Plots top 9 most significants
##
##
##
## ### Top DE table
##
##
##
## baseMean log2FoldChange lfcSE stat pvalue padj absMaxLog2FC
## ---------------- ----------- --------------- ---------- ---------- ---------- ---------- -------------
## ENSG00000067048 1025.03783 10.1571705 0.4233146 23.994380 0.0000000 0.0000000 10.1571705
## ENSG00000012817 411.54387 9.2394007 0.4237379 21.804517 0.0000000 0.0000000 9.2394007
## ENSG00000067646 169.81477 10.1874916 0.6579432 15.483847 0.0000000 0.0000000 10.1874916
## ENSG00000005889 670.86191 -0.6919265 0.1314523 -5.263708 0.0000001 0.0000353 0.6919265
## ENSG00000006757 92.66111 -0.7666012 0.1611520 -4.757006 0.0000020 0.0003930 0.7666012
## ENSG00000073282 220.15603 -1.8685615 0.4206120 -4.442482 0.0000089 0.0014821 1.8685615
## ENSG00000005302 2026.54990 -0.7418952 0.1763412 -4.207157 0.0000259 0.0036943 0.7418952
## ENSG00000005020 1233.86316 0.3888370 0.0952312 4.083085 0.0000444 0.0055552 0.3888370
## ENSG00000003400 393.62677 0.6803243 0.1766475 3.851310 0.0001175 0.0130542 0.6803243
## ENSG00000069702 106.67010 -1.6323189 0.4585611 -3.559654 0.0003713 0.0371343 1.6323189
## ENSG00000010278 84.30823 1.2035871 0.3554857 3.385754 0.0007098 0.0645300 1.2035871
## ENSG00000023171 165.31692 -1.4022259 0.4236024 -3.310240 0.0009322 0.0776799 1.4022259
## ENSG00000072501 3694.76013 -0.5604815 0.1707989 -3.281529 0.0010325 0.0794200 0.5604815
## ENSG00000070018 119.89049 -1.0921227 0.3512409 -3.109327 0.0018751 0.1339388 1.0921227
## ENSG00000059377 131.98111 0.8405094 0.2744635 3.062372 0.0021959 0.1463935 0.8405094
## ENSG00000008277 377.43955 -0.6368732 0.2136506 -2.980910 0.0028739 0.1796208 0.6368732
## ENSG00000005059 479.12528 0.4225402 0.1492246 2.831571 0.0046320 0.2289281 0.4225402
## ENSG00000012963 1829.21224 0.2471040 0.0861859 2.867104 0.0041425 0.2289281 0.2471040
## ENSG00000038427 100.87217 -1.0743654 0.3810269 -2.819658 0.0048075 0.2289281 1.0743654
## ENSG00000068079 1035.17996 0.4075632 0.1415563 2.879160 0.0039874 0.2289281 0.4075632
In this section, we show how to detect pattern of expression. Mainly useful when data is a time course experiment. degPatterns
needs a expression matrix, the design experiment and the column used to group samples.
ma = assay(rlog(dds))[row.names(res)[1:100],]
res <- degPatterns(ma, design, time = "group")
This section shows some useful functions during DEG analysis.
degFilter
helps to filter genes with a minimum read count by group.
cat("gene in original count matrix: 1000")
gene in original count matrix: 1000
filter_count <- degFilter(counts(dds),
design, "group",
min=1, minreads = 50)
cat("gene in final count matrix", nrow(filter_count))
gene in final count matrix 940
This functions allows you to create colors for metadata columns to be used as annotation for columns in a heatmap figure.
library(ComplexHeatmap)
th <- HeatmapAnnotation(df = colData(dds),
col = degColors(colData(dds), TRUE))
Heatmap(log2(counts(dds) + 0.5)[1:10,],
top_annotation = th)
sessionInfo()
## R version 3.5.1 (2018-07-02)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS High Sierra 10.13.3
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] grid parallel stats4 stats graphics grDevices utils
## [8] datasets methods base
##
## other attached packages:
## [1] pheatmap_1.0.10 ComplexHeatmap_1.18.1
## [3] bindrcpp_0.2.2 quantreg_5.36
## [5] SparseM_1.77 DESeq2_1.20.0
## [7] SummarizedExperiment_1.10.1 DelayedArray_0.6.5
## [9] BiocParallel_1.14.2 matrixStats_0.54.0
## [11] Biobase_2.40.0 GenomicRanges_1.32.6
## [13] GenomeInfoDb_1.16.0 IRanges_2.14.11
## [15] S4Vectors_0.18.3 BiocGenerics_0.26.0
## [17] DEGreport_1.17.5 BiocStyle_2.8.2
##
## loaded via a namespace (and not attached):
## [1] colorspace_1.3-2 rjson_0.2.20
## [3] rprojroot_1.3-2 circlize_0.4.4
## [5] htmlTable_1.12 XVector_0.20.0
## [7] GlobalOptions_0.1.0 base64enc_0.1-3
## [9] ggdendro_0.1-20 fs_1.2.6
## [11] rstudioapi_0.7 roxygen2_6.1.0
## [13] MatrixModels_0.4-1 ggrepel_0.8.0
## [15] bit64_0.9-7 fansi_0.3.0
## [17] AnnotationDbi_1.42.1 xml2_1.2.0
## [19] splines_3.5.1 logging_0.7-103
## [21] mnormt_1.5-5 geneplotter_1.58.0
## [23] knitr_1.20 Formula_1.2-3
## [25] Nozzle.R1_1.1-1 broom_0.5.0
## [27] annotate_1.58.0 cluster_2.0.7-1
## [29] compiler_3.5.1 backports_1.1.2
## [31] assertthat_0.2.0 Matrix_1.2-14
## [33] lazyeval_0.2.1 cli_1.0.0
## [35] limma_3.36.3 lasso2_1.2-19
## [37] acepack_1.4.1 htmltools_0.3.6
## [39] tools_3.5.1 gtable_0.2.0
## [41] glue_1.3.0 GenomeInfoDbData_1.1.0
## [43] dplyr_0.7.6 Rcpp_0.12.18
## [45] pkgdown_1.1.0 nlme_3.1-137
## [47] psych_1.8.4 stringr_1.3.1
## [49] XML_3.98-1.16 edgeR_3.22.3
## [51] zlibbioc_1.26.0 MASS_7.3-50
## [53] scales_1.0.0 RColorBrewer_1.1-2
## [55] yaml_2.2.0 memoise_1.1.0
## [57] gridExtra_2.3 ggplot2_3.0.0
## [59] rpart_4.1-13 reshape_0.8.7
## [61] latticeExtra_0.6-28 stringi_1.2.4
## [63] RSQLite_2.1.1 highr_0.7
## [65] genefilter_1.62.0 desc_1.2.0
## [67] checkmate_1.8.5 shape_1.4.4
## [69] rlang_0.2.2 pkgconfig_2.0.2
## [71] commonmark_1.5 bitops_1.0-6
## [73] evaluate_0.11 lattice_0.20-35
## [75] purrr_0.2.5 bindr_0.1.1
## [77] labeling_0.3 htmlwidgets_1.2
## [79] cowplot_0.9.3 bit_1.1-14
## [81] tidyselect_0.2.4 plyr_1.8.4
## [83] magrittr_1.5 R6_2.2.2
## [85] Hmisc_4.1-1 DBI_1.0.0
## [87] withr_2.1.2 pillar_1.3.0
## [89] foreign_0.8-71 survival_2.42-6
## [91] RCurl_1.95-4.11 nnet_7.3-12
## [93] tibble_1.4.2 crayon_1.3.4
## [95] utf8_1.1.4 rmarkdown_1.10
## [97] GetoptLong_0.1.7 locfit_1.5-9.1
## [99] data.table_1.11.4 blob_1.1.1
## [101] ConsensusClusterPlus_1.44.0 digest_0.6.16
## [103] xtable_1.8-3 tidyr_0.8.1
## [105] munsell_0.5.0


This demo uses Cheetah for Web and the WebVoiceProcessor to:
Create an instance of Cheetah with the model file provided or default model file.
Acquire microphone (& ask permission) data stream and convert to voice
processing format (16kHz 16-bit linear PCM). The downsampled audio is
forwarded to the Cheetah engine. The audio does not leave the
browser: all processing is occurring via the Cheetah WebAssembly code.
Listen for real time transcription results from the Cheetah engines and
output them to the page.
After entering the AccessKey, click the "Start Cheetah" button.


Excludes Notes
The ICD-10-CM has two types of excludes notes. Each note has a different definition for use but they are both similar in that they indicate that codes excluded from each other are independent of each other.
Excludes1
A type 1 Excludes note is a pure excludes. It means 'NOT CODED HERE!' An Excludes1 note indicates that the code excluded should never be used at the same time as the code above the Excludes1 note. An Excludes1 is used when two conditions cannot occur together, such as a congenital form versus an acquired form of the same condition.
Excludes2
A type 2 excludes note represents 'Not included here'. An excludes2 note indicates that the condition excluded is not part of the condition it is excluded from but a patient may have both conditions at the same time. When an Excludes2 note appears under a code it is acceptable to use both the code and the excluded code together.
Code First/Use Additional Code notes (etiology/manifestation paired codes)
Certain conditions have both an underlying etiology and multiple body system manifestations due to the underlying etiology. For such conditions the ICD-10-CM has a coding convention that requires the underlying condition be sequenced first followed by the manifestation. Wherever such a combination exists there is a 'use additional code' note at the etiology code, and a 'code first' note at the manifestation code. These instructional notes indicate the proper sequencing order of the codes, etiology followed by manifestation.
In most cases the manifestation codes will have in the code title, 'in diseases classified elsewhere.' Codes with this title are a component of the etiology/ manifestation convention. The code title indicates that it is a manifestation code. 'In diseases classified elsewhere' codes are never permitted to be used as first listed or principal diagnosis codes. They must be used in conjunction with an underlying condition code and they must be listed following the underlying condition.
Code Also
A code also note instructs that 2 codes may be required to fully describe a condition but the sequencing of the two codes is discretionary, depending on the severity of the conditions and the reason for the encounter.
7th characters and placeholder X
For codes less than 6 characters that require a 7th character a placeholder X should be assigned for all characters less than 6. The 7th character must always be the 7th character of a code


If you are looking to give a gift with a personal touch, you have come to the right place. From milestone Birthday gifts to Wedding Anniversary keepsakes, has something for everyone and every occasion. Our designs are created and professionally engraved in house
please enter your name
input what type of the gift you wont to seaech for it
how much budget did you set


Meet Green Day at the Hollywood or Highland Hot Topic location on October 15th. To be able to have this opportunity, Guest list members are allowed to purchase Green Day's new album and a t-shirt bundle to recieve a wristband starting October 4th to meet Green Day October 15th.


--- title: The Antiviral Effect layout: post ---
Naturally, masses of people had uninstalled the app while it had been broken.
Sharecropping. Its not just for real anymore.


We're very sorry about that. Please contact support and let us know what you were trying to do when it happened, so we can get it fixed as soon as possible.
Thanks for helping us get the bugs out!


QALD is a series of evaluation campaigns on question answering over linked data. So far, it has been organized as an ESWC workshop and an ISWC workshop as well as a part of the Question Answering lab at CLEF.
While more and more structured data is published on the web, the question of how typical web users can access this body of knowledge becomes of crucial importance. Over the past years, there is a growing amount of research on interaction paradigms that allow end users to profit from the expressive power of Semantic Web standards while at the same time hiding their complexity behind an intuitive and easy-to-use interface. Especially natural language interfaces have received wide attention, as they allow users to express arbitrarily complex information needs in an intuitive fashion and, at least in principle, in their own language. Multilingualism has, in fact, become an issue of major interest for the Semantic Web community, as both the number of actors creating and publishing data all in languages other than English, as well as the amount of users that access this data and speak native languages other than English is growing substantially.
The key challenge is to translate the users' information needs into a form such that they can be evaluated using standard Semantic Web query processing and inferencing techniques. Over the past years, a range of approaches have been developed to address this challenge, showing significant advances towards answering natural language questions with respect to large, heterogeneous sets of structured data. However, only few systems yet address the fact that the structured data available nowadays is distributed among a large collection of interconnected datasets, and that answers to questions can often only be provided if information from several sources are combined. In addition, a lot of information is still available only in textual form, both on the web and in the form of labels and abstracts in linked data sources. Therefore approaches are needed that can not only deal with the specific character of structured data but also with finding information in several sources, processing both structured and unstructured information, and combining such gathered information into one answer.


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The New PhpVersions
Matt Trask • February 19, 2019
Read Time: 2 mins
new year new meAbout 2 ish years or so ago, I got access to the PhpVersions.info project started by my good friend Phil Sturgeon. There was always an open issue for a rewrite of the project. The reason being that the project was started in Jekyll to take advantage of Github's free hosting. That worked great for a few years, but it became obvious we should use PHP since the whole project was about getting people on to the latest and greatest PHP version.
I started to examine options out there, and there are some great options out there. Ultimately, I chose Laravel with Vue.Js, mainly because at the time that was the stack I was working full time in and knew I could get going with it fairly quickly. Say what you will about Laravel, and there is plenty to be said, one thing Laravel does great is "Rapid Application Development", in which you can get up and running in no time. It's pretty fantastic. Now, if you can at least plan for a little bit in the future,you can also future proof your application from growing stale with a framework. With that, I set out to write the project.
It wasn't til I was sitting at WordCamp Kent when I seriously put in the time to do it. I was speaking at the conference and the talks weren't really relevant to me so I just hung out working on it. I got the bulk down and then it was time to come back to reality. The project was worked on in between organizing a conference, speaking and other things. Finally, Colin O'Dell stepped up to helo manage the v1 instance pull requests so I could dedicate my time to the new stuff.
Tech Stack
As I mentioned above, the back end portion of the project is currently powered by Laravel. Will that remain the same as time passes I do not know. I'd like to think I wrote it in a way where we can start to remove the underlaying Laravel code after a while and move to packages. On the other hand, Laravel clearly is not going anywhere. I am not terribly concerned one way or another. The database is just MySQL. Woo. One of these days I need to get back to Postgres.
The front end is powered by Vue.js, a reactive front end framework started back in 2014. Its comparable to React, but has some really nice differences. I did a talk about Vue.js at Sunshine which was fun. The CSS framework is Tailwind CSS, which I have absolutely enjoyed using, the font is Questrial and the icon font is Zondicons.
It all runs on a Digital Ocean droplet with PHP 7.3 installed, and I absolutely plan on moving to 7.4 as soon as it is avaiable.
If you have questions, ideas or want to contribute check out the repository.
Cheers!


has-tabbed
Small library that adds CSS class to html when user starts tabbing,
and removes it if user clicks anywhere.
This enables you to have focus outline only when user is using keyboard.
Start using keyboard to navigate to see it in action.
Find documentation on GitHub.


{extend name="public/common" /} {block name="warp"}
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Quick and Easy Feijoada
Hearkens back to the mission. Note that I’ve modified this recipe a bit for personal preference. At the end, thicken with a cornstarch slurry as needed. Optionally use creole seasoning or similar instead of salt to add some further spice. Goes great with some sriracha or other hot sauce too.
Yields: 6
Preparation time: 15
Cooking time: 15
Ingredients
-
2 cups rice1 tablespoon olive oil1 medium onion6 strips of bacon, sliced into 1/2 inch pieces1/2 pound smoked pork or beef sausage, sliced into small rounds2 15 oz cans of unsalted black beans, do not drain2 cups chicken broth4 teaspoons garlic poder5-6 bay leaves2 teaspoon dried oreganosalt to taste
Directions
-
Prepare and cook the riceDice the onionHeat a large pot over medium heat. Add olive oil and heat.Saute the onions until tender, 5-7 minutes or edges start to brownAdd the bacon and sausage and sauté until brown and crispy, about 4 minutes.


Mander Plaza School
[60, 10]
|
the Hoddinott Motel
[61, 10]
|
the Morgane Building
[62, 10]
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the Toop Building
[63, 10]
|
St Anastasius's Church
[64, 10]
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Barling Boulevard Fire Station
[65, 10]
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Harbin Square
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Orders Crescent Police Dept
[67, 10]
|
a warehouse
[68, 10]
|
Abraham General Hospital
[69, 10]
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Holway Crescent
[60, 11]
|
Elwes Drive
[61, 11]
|
St Henry's Hospital
[62, 11]
|
Skarin Way Fire Station
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the Sawday Arms
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|
the Marshall Monument
[65, 11]
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Haggard Towers
[66, 11]
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Dimmock Square
[67, 11]
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Club Bellam
[68, 11]
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St Paschal's Church
[69, 11]
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St Athanasius's Church
[60, 12]
|
Mussabini Square
[61, 12]
|
the Harnett Building
[62, 12]
|
Bares Park
[63, 12]
|
wasteland
[64, 12]
|
St Paul's Church
[65, 12]
|
Southall Library
[66, 12]
|
Lovibond Towers
[67, 12]
|
a carpark
[68, 12]
|
Birt Crescent Fire Station
[69, 12]
|
St Irenaeus's Church
[60, 13]
|
St Irenaeus's Church
[61, 13]
|
St Juan's Church
[62, 13]
|
the Mansbridge Building
[63, 13]
|
the Goldsworthy Building
[64, 13]
|
Headford Way School
[65, 13]
|
a cemetery
[66, 13]
|
St Mary's Church
[67, 13]
|
Hanson Lane
[68, 13]
|
Morrow Lane
[69, 13]
|
the Cummings Building
[60, 14]
|
Farthing Way
[61, 14]
|
Club Markey
[62, 14]
|
the Vacher Building
[63, 14]
|
wasteland
[64, 14]
|
the Hasell Museum
[65, 14]
|
a factory
[66, 14]
|
Bant Lane
[67, 14]
|
Dullea Way
[68, 14]
|
Cambridge Walk
[69, 14]
|
the Stollery Arms
[60, 15]
|
a factory
[61, 15]
|
the Bertrand Building
[62, 15]
|
Minchinton Alley
[63, 15]
|
Moncrieffe Cinema
[64, 15]
|
St Romuald's Church
[65, 15]
|
Dunk Avenue
[66, 15]
|
the Heale Building
[67, 15]
|
Rollings Lane
[68, 15]
|
the Pattin Building
[69, 15]
|
Higgins Place
[60, 16]
|
Club Collyer
[61, 16]
|
Willmot Place
[62, 16]
|
Donegan Bank
[63, 16]
|
Pashen Way
[64, 16]
|
Webb Library
[65, 16]
|
the Jack Building
[66, 16]
|
Rowlings Row
[67, 16]
|
Simper Towers
[68, 16]
|
Wootton Square
[69, 16]
|
Sheehan Lane Police Dept
[60, 17]
|
the Pitcher Arms
[61, 17]
|
Fruin Alley
[62, 17]
|
Wey Row
[63, 17]
|
Sherwen Crescent
[64, 17]
|
the Halay Building
[65, 17]
|
the Dudridge Museum
[66, 17]
|
Freake Walk
[67, 17]
|
Mees Walk
[68, 17]
|
Burch Road School
[69, 17]
|
Club Jeffreys
[60, 18]
|
Peaty Avenue Railway Station
[61, 18]
|
Tabor Plaza
[62, 18]
|
Bastard Street
[63, 18]
|
the Hebditch Building
[64, 18]
|
Tindell Walk
[65, 18]
|
Chibbett Lane Fire Station
[66, 18]
|
Brendon Auto Repair
[67, 18]
|
Lyde Drive
[68, 18]
|
a carpark
[69, 18]
|
Ramsey Auto Repair
[60, 19]
|
Rousell Plaza
[61, 19]
|
Norie Bank
[62, 19]
|
the Fildes Building
[63, 19]
|
Templeton Bank
[64, 19]
|
Steed Crescent
[65, 19]
|
Meads Walk Railway Station
[66, 19]
|
Potts Bank
[67, 19]
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Wetherell Row School
[68, 19]
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FROM PRINCE ALEX DUKE TEL-234 80 33254029 Dear Greeting, In appreciation of your esteemed contact received through a reliable source and the choice of your country I wish to introduce myself . I am Prince Alex kishali duke the first son of His Royal Majesty, WIWA DUKE and the traditional ruler of Eleme Province in the oil area of Rivers State of Nigeria. I am making this contact to you in respect of US 45,000,000.00, which I inherited, from my late father. This funds was accumulated from royalties paid to my father as compensation by the oil firms located in our area as a result of oil presence on our land which hamper agriculture which is our major source of livelihood. Unfortunately my father died from protracted diabetes. But before his he called my attention and informed me that he lodged some funds with a security firm and Security Code Number was also revealed to me, he then advised me to look for a reliable business partner abroad, who will assist me in investing the funds in a lucrative business as a result of economic instability in Nigeria. I and my family have unanimously decided to give you 20% of the total funds, 2% for charity homes and 3% for expenses, which may arise during the transaction, fax and phone bills inclusive. The balance of 75% you will invest and manage for my family. I hereby guarantee you that this is not government funds, it is not drug funds and it is not fundsÂ from arms deal.I will give you all proof of deposit and existence of funds once urgedand fully satisfied with your capability and honesty. I hope this will be the beginning of a prosperous relationship between my family and your family. Nevertheless if you are for any reason not interest, kindly inform me immediately so that I will look for another contact. Reply me with this my private mail box (alex_duke@mail. az) Yours faithfully, PRINCE ALEX DUKE


(Web Authoring CMP1130M)
Designer, Developer, Director & Senior Lecturer
Last week we looked at
Variables
Loading script
Outputting in the console
Alert(), prompt(), console.log()
Writing a function
Targeting an element by ID
Getting an elements value
Variable Rules
Not using developer tools to check errors (actually reading them)
Encapsulation and Ordering
Variable scope
Getting and Setting
A variable is like a storage container inside the code.
Each variable has a name so the program can refer to it.
Variables can contain numbers, letters, special characters.
Contents can be changed freely.
Must start with a letter or an underscore, NOT A NUMBER
Can NOT have spaces in them.
var num = 31;
var boolean = true;
var string = 'wayne'
var array[item1, item2, item3];
var object= {firstname: wayne, lastname:christian}
window.onload = function() {
init();
}
function init(){
console.log('init fired');
}
// out side will execute first and break
var x = document.getElementById("demo");
x.style.color = "red";
JavaScript has two scopes – global and local. Any variable declared outside of a function belongs to the global scope, and is therefore accessible from anywhere in your code. Each function has its own scope, and any variable declared within that function is only accessible from that function and any nested functions
var name ="wayne";
window.onload = function() {
init();
getname();
}
function init(){
var surname ="christian"
console.log(name);
}
function getname(){
console.log(name, surname);
}
// will get an undefined as var surname is not accessible
The lifetime of a JavaScript variable starts when it is declared.
Local variables are deleted when the function is completed.
In a web browser, global variables are deleted when you close the browser window (or tab), but remains available to new pages loaded into the same window.
implications?
Syntax issues (but logical reasoning)
document.myid = "text";
var mynode = document.getElementById("id");
mynode="hello";
// this just targets the whole element and not an attribute.
So far we have only "get" or "set" DOM elements by ID
var mynode = document.getElementById("id") // get
mynode.style.color="red" //set
var mynode = document.getElementById("id").value //get input value
mynode.value = "hello" //set input value
anything wrong here?
Peer Reviews Recap
Mood boards.
Site Map / UX diagram
Wire frames
visuals / lofi mock ups
Customiser
A mood board is a collage or composition of images, visuals and other objects, often created for the purposes of design or presentation. Mood boards can help designers to figure out how to create unified styles or themes for a design project
Using a mood board for a Web design you might start to put together images that all fit a certain style, along with visuals that have colors or color schemes in common. Looking at the mood board gives me a kind of creative road map in terms of designing the final project.
Categorize / focus a few mood boards in an area for example:
Colour
Layout
Navigation
Typography
Experience
Customization
Why not create a pinterest wall?
Site maps are organized lists or flow chart diagrams that shows connections between web pages, web page trees, and website content. A visual site map is a very effective method for both planning and communicating ideas about a website’s structure. As a 2D representation of a website, site maps allow designers and developers to efficiently plan website projects by offering a bird’s-eye view of the entire project at one time
The physical structure of a site map may vary depending on its intended use. Typically site maps for project planning are visual 2D displays or images optimized for human reading. Pages are represented as blocks or cells connected by lines that represent a link or path by the user. This format is popular because of the ease and speed of human understanding.
Wire framing is an important step in any screen design process. It primarily allows you to define the information hierarchy of your design, making it easier for you to plan the layout according to how you want your user to process the information
Peer Review Objectives
Gain knowledge on how to provide useful, actionable feedback to peers.
Develop your understanding of evaluation and critical reflective practice.
Prepare for the milestone submission
You need:
Two peer review forms:
Your website must be evaluated by two peers from your
workshop group.
Personal reflection form:
You must reflect on your own design based on the criteria on the
peer review form.
All four items must be submitted as a single PDF on blackboard. Hand drawn items should be scanned and included into the report.
Feedback is a two-way process where comments and observations, both positive and negative, are made. Both positive and negative feedback is essential in helping you develop. However, people often don’t respond well to feedback, no matter how constructive it is.
Start with something positive.
If possible, sandwich a negative (area to improve) between two positives.
Be confined to the amount the recipient can use rather than the amount you would like to give. Focus on the big issues.
Be specific rather than general.
Be clear and precise, minimizing ambiguity and the potential for misinterpretation.
Offer alternatives, not criticism.
Offer observations rather than inferences.
Help to clarify the difference between current and desired performance.
Helps clarify what good performance is. Good feedback should help the individual to close the gap between current and desired performance.
Facilitates the development of self-assessment (reflection) in the person being given the feedback.
Encourages dialogue around the task, providing information that can be used to shape future development.
Encourages positive motivational belief and self-esteem.
Warning loud / explicit language!
| Comment Type | Phrasing | example |
|---|---|---|
| Instructions | “You should” | You should use better quality references. |
| Instructions | “You should” | You should use better quality references. |
| Advisory | “Better if” | It would be better if you explained this point in the introduction. |
| Observation | “You have” | You have discussed the topic of web standards. |
| Rhetorical | “What if?” | What if you explored this from an alternative target audience? |
| Criticism | “There is a problem” | There is a problem with your syntax, you need to be more precise |
| Praise | "Well done” | Your presentation is exceptional, well done! |
“External feedback can have a positive or negative effect on motivational beliefs and on self-esteem. It influences how students feel about themselves which, in turn, affects what and how they learn..”
–Juwah at al p12
Doing the above!
Additional
Introduction to
We will also look at:
Introduction to the Document Object Model (DOM)
Accessing elements in a HTML document using JavaScript.
Modifying the contents of an element.
Modifying elements.
Adding and deleting elements.
Special DOM objects.
The Document Object Model is a crossplatform and language neutral interface that will allow programs and scripts to dynamically access and update the content, structure and style of HTML, XHTML and XML documents.
Developers wished to have better integration with HTML and Java-script. Intention was to add interaction in various parts of the HTML code.
Developers used add-hoc ways to add interaction and dynamic behavior.
For those purposes W3C developed the DOM specification.
Each web document can be treated as a tree structured collection of objects, called the DOM tree
Objects can be accessed and manipulated using methods
The public interface of a DOM is specified by its application programming interface (API).
The HTML Document Object Model (DOM):
An API that defines a standard way of accessing and manipulating an HTML document.
It presents a HTML document as a tree-structure (a node tree) with elements, attributes and text.
allows programmers to build documents, navigate their structure, and add, modify, or delete elements and content.
Almost anything found in an HTML document can be accessed, changed, deleted, or added using the DOM (with a few exceptions).
<!doctype html>

<meta charset="UTF-8">
<title>Untitled Document</title>

A heading

There is more than one DOM
There are several DOMs in existence:
The Legacy DOM: introduced in early versions of JavaScript language.
It is well supported by all browsers, but allows access only to certain key portions of documents, such as forms, form elements, and images.
The IE4 DOM: This document object model was introduced in Version 4 of Microsoft's Internet Explorer browser.
IE 5 and later versions include support for most basic W3C DOM features.
The W3C DOM: allows access and modification of all document content and is standardised by the World Wide Web Consortium (W3C). This model is supported by almost all the modern browsers.
Core DOM currently at version 4 and uses Object Oriented concepts.
Objects (encapsulation of data and methods).
Methods (to access or change an object’s state).
Interfaces (declaration of a set of methods).
Each node in the tree is an object.
Root node is the document.
Objects in JavaScript, just as in many other programming languages, can be compared to objects in real life. The concept of objects in JavaScript can be understood with real life, tangible objects.
In JavaScript, an object is a standalone entity, with properties and type. Compare it with a cup, for example. A cup is an object, with properties. A cup has a color, a design, weight, a material it is made of, etc. The same way, JavaScript objects can have properties, which define their characteristics.
The browser is an object
The window is an object
The head is an object
The body is an object
body.style.color
So far we have only "get" or "set" DOM elements by ID
document.getElementById("id") // get
document.getElementById("id").value //get input value
Remember, an id can be defined in each HTML element start tag.
A

with an id can be used as a node for a dynamic subtree
A
with an id can be used as a dynamic inline element
Accessing nodes by ID is generally the preferred way to access DOM elements with JavaScript
Access to elements by their tag name. Typically, we have many elements with the same tag, e.g.

,
etc.
document.getElementsByTagName("tag")
Returns the collection of elements of the specified tag (type)
The collection has a length attribute
An item in the collection can be reached by its index, e.g. var x=document.getElementsByTagName("p")[0];
HTML

My form

<form>
ID: <input name="course" type="radio" value="ID">
CS: <input name="course" type="radio" value="CS">
<input type="button" onclick="myFunction()" value=“Run!">
</form>

JS
function myFunction()
{
var x=document.getElementsByName(“course");
alert(x.length);
}
Several elements can have the same name (e.g. in forms)
document.getElementsByName("name")
Returns the collection of elements of the specified name attribute
The collection has a length attribute
An item in the collection can be reached by its index, e.g. var x=document.getElementsByName(“name_attribute_value")[0];
HTML

An unordered list:

Han

Chewie

Luke

<input type="button" onclick=“myFunction()" value=“Run!">

JS
function myFunction()
{
var x=document.getElementsByTagName("li");
alert(x.length);
}
Traversal methods include:
childNodes: returns a collection of child nodes
Has a length attribute
Items can be reached by its index E.g. var body=html.childNodes[5];
parentNode: reference to parent node
firstChild: first child in list of child nodes
lastChild: last child in list of child nodes
previousSibling: reference to node preceding this node (if none, returns null)
nextSibling: reference to node after this node (if none, returns null)
hasChildNodes(): true if node has child nodes
document.getElementsByTagName("h2")[0]
document.getElementById(“myH2”)
document.childNodes[0].childNodes[1].childNodes[1].childNodes[1]
Need to name part of the DOM, then swap the text with some new stuff!
innerTEXT = complete textual content of element.
outerTEXT = (as above) but also replaces the tag as well when assignment made.
innerHTML = the complete content (including HTML tags).
outerHTML = complete content including elements itself.
HTML
<!DOCTYPE html>

Example 2

<button id="mybtn">Change Heading</button>

JS
document.getElementById("myBtn").onclick = changeHeading;
function changeHeading() {
var head=document.getElementById("heading");
var newHead= prompt("enter new header");
head.innerHTML = newHead;
}
We know how to access elements in the DOM as we are in control of the markup and assigning the relevenat ID's.
What if we want to add new elements?
What if the markup was generated dynamically?
document.write();
Using document.write()
after the page has fully loaded will delete all the existing HTML
Write HTML data to the document.
document.write("
Hello World!
”);
Write date from a function to the document.
document.write(Date());
Open a new window and add HTML to it.
var newWindow = window.open("", "newWindow", "width=50, height=50");
newWindow.document.write("
This is a new window!
”);
write() and writeln() are VERY different.
writln() is used when you want to add a new line after each statement.
window.onload = function()
{
var docWidth = window.innerWidth;
var docHeight = window.innerHeight;
var x =0;
var output-"";
while(x*width < docWidth)
{
var y =0;
while(y*height < docHeight)
{
console.log(x,y);
}
//
x++;
}
}
This week you will be working on a new exercise “body swap”. Which will help develop:
DOM Skills
Accessing Arrays[]
loops
Writing to the DOM


RoadForecast
Don't be surprised by the weather
RoadForecast
Welcome
Logout
Start
Forecast
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Contact
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Shearch results
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Number of searches


UofT
The University of Toronto is a globally recognized research university and has a huge prestige
on global educational markets. It comprises three campuses located in Scarborough, Mississauga,
and Downtown Toronto. With students from over 159 different countries and regions, U of T is
one of the most diversified institutions within Canada. It offers over 700 undergraduate and
300 graduate programs in a wide range of fields, which ensures that there is a suitable
program for everyone. The university has secured a top ranking in Canada for several consecutive
years and continues to be the hub of innovation, diversity, and knowledge.
- Location
- Map
- University of Toronto Scarborough
- University of Toronto St.George
- University of Toronto Mississauga
- Average Tuition:
- Tuition varies on the program
- Domestic tuition is $6,100 to $14,180 CAD
- International Tuition is $35,890 to $58,680 CAD
- Entry Requirements:
- Ontario Secondary School Diploma (OSSD) with six Grade 12 U/M subjects, including ENG4U
- MCV4U is required for programs with the Calculus prerequisite
- English Proficiency test is required for international students
- International rating:
- 20th
- Canadian rating:
- 1st
- Average class size:
- Approximately 300 students
University of Toronto
27 King’s College Circle
Toronto ON M5S 1A1
Tel:<PHONE_NUMBER>
Admissions:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
University of Toronto Mississauga:
Tel:<PHONE_NUMBER>
University of Toronto Scarborough:
Tel:<PHONE_NUMBER>
www.utoronto.ca


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Sign In to get full access and manage the database.
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--- layout: post title: Categories module version 1.5.2 released date: '2009-10-09T04:37:00+02:00' tags: - oldblogposts - labs - joomla tumblr_url: http://hussfelt.tumblr.com/post/28547584361/categories-module-version-1-5-2-released ---
Today we released a minor upgrade to the Categories module.
You now have the option to add the text “Article” or “Articles” (text depending if article count is larger then 1) after the article counter.
Also a minor bug was fixed where articles with state 0 was included in the counter.


Tokenomics
FAQ
Dashboard
MARKET DATA
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LIQUIDITY
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LIQUID MARKETCAP
PROTOCOL ACTIVITY
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EVENTS
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ARIA STAKED
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STAKED IDENTITIES
Identity 1
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Identity 3
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https://blockscout.com/poa/xdai/blocks/12102077/transactions
BRIDGE ACTIVITY
199,849,849
ARIA20 ON ETHEREUM
150,151
ARIA ON POA
2,000
30d BRIDGE VOLUME (ARIA)


--- title: SO3VectorField sidebar: documentation_sidebar permalink: SO3FunVectorField.html folder: documentation toc: false ---
SO3VectorField handles three-dimensional functions on the rotation group. For instance the gradient of an univariate SO3FunHarmonic
can return a SO3VectorFieldHarmonic.
Analogous to SO3FunHandle
we are able to define SO3VectorFields
by an anonymous function.
Note that the evaluations are of class vector3d
Definition via SO3VectorField
We can expand any SO3VectorField
in an SO3VectorFieldHarmonic
directly by the command SO3VectorFieldHarmonic
Definition via function values
At first we need some example rotations
{% highlight matlab %} nodes = equispacedSO3Grid(specimenSymmetry('1'),'points',1e3); nodes = nodes(:); {% endhighlight %}Next, we define function values for the rotations
{% highlight matlab %} y = vector3d.byPolar(sin(3*nodes.angle), nodes.phi2+pi/2); {% endhighlight %}Now the actual command to get SO3VF1
of type SO3VectorFieldHarmonic
Definition via function handle
If we have a function handle for the function we could create a S2VectorFieldHarmonic
via quadrature. At first lets define a function handle which takes rotation
as an argument and returns a vector3d
:
Now we can call the quadrature command to get SO3VF2
of type SO3VectorFieldHarmonic
Definition via SO3FunHarmonic
If we directly call the constructor with a multivariate SO3FunHarmonic
with three entries it will create a SO3VectorFieldHarmonic
with SO3F(1)
, SO3F(2)
, and SO3F(3)
the \(x\), \(y\), and \(z\) component.
Basic arithmetic operations
Again the basic mathematical operations are supported:
addition/subtraction of a vector field and a vector or addition/subtraction of two vector fields
{% highlight matlab %} SO3VF1 + SO3VF2; SO3VF1+vector3d(1, 0, 0); SO3VF1-SO3VF2; SO3VF2-vector3d(sqrt(2)/2, sqrt(2)/2, 0); {% endhighlight %}multiplication/division by a scalar or a SO3Fun
dot product with a vector or another vector field
{% highlight matlab %} dot(SO3VF1, SO3VF2); dot(SO3VF1, vector3d(0, 0, 1)); {% endhighlight %}cross product with a vector or another vector field
{% highlight matlab %} cross(SO3VF1, SO3VF2); cross(SO3VF1, vector3d(0, 0, 1)); {% endhighlight %}mean vector of the vector field
{% highlight matlab %} mean(SO3VF1); {% endhighlight %}rotation of the vector field
{% highlight matlab %} r = rotation.byEuler( [pi/4 0 0]); rotate(SO3VF1, r); {% endhighlight %}pointwise norm of the vectors
{% highlight matlab %} norm(SO3VF1); {% endhighlight %}One can use the default plot
-command
or the 3D plot of the rotation group with the vectors on itself
{% highlight matlab %} clf; quiver3(SO3VF2); {% endhighlight %} {% highlight plaintext %} Warning: Setting the "WindowButtonDownFcn" property is not permitted while this mode is active. Warning: Setting the "WindowButtonUpFcn" property is not permitted while this mode is active. Warning: Setting the "KeyPressFcn" property is not permitted while this mode is active. Warning: Setting the "WindowScrollWheelFcn" property is not permitted while this mode is active. {% endhighlight %}


GCDAsyncSocketDelegate Protocol Reference
| Declared in | GCDAsyncSocket.h |
Tasks
-
– newSocketQueueForConnectionFromAddress:onSocket:
This method is called immediately prior to socket:didAcceptNewSocket:.
It optionally allows a listening socket to specify the socketQueue for a new accepted socket.
If this method is not implemented, or returns NULL, the new accepted socket will create its own default queue. -
– socket:didAcceptNewSocket:
Called when a socket accepts a connection.
Another socket is automatically spawned to handle it. -
– socket:didConnectToHost:port:
Called when a socket connects and is ready for reading and writing.
The host parameter will be an IP address, not a DNS name. -
– socket:didReadData:withTag:
Called when a socket has completed reading the requested data into memory.
Not called if there is an error. -
– socket:didReadPartialDataOfLength:tag:
Called when a socket has read in data, but has not yet completed the read.
This would occur if using readToData: or readToLength: methods.
It may be used to for things such as updating progress bars. -
– socket:didWriteDataWithTag:
Called when a socket has completed writing the requested data. Not called if there is an error.
-
– socket:didWritePartialDataOfLength:tag:
Called when a socket has written some data, but has not yet completed the entire write.
It may be used to for things such as updating progress bars. -
– socket:shouldTimeoutReadWithTag:elapsed:bytesDone:
Called if a read operation has reached its timeout without completing.
This method allows you to optionally extend the timeout.
If you return a positive time interval (> 0) the read’s timeout will be extended by the given amount.
If you don’t implement this method, or return a non-positive time interval (<= 0) the read will timeout as usual. -
– socket:shouldTimeoutWriteWithTag:elapsed:bytesDone:
Called if a write operation has reached its timeout without completing.
This method allows you to optionally extend the timeout.
If you return a positive time interval (> 0) the write’s timeout will be extended by the given amount.
If you don’t implement this method, or return a non-positive time interval (<= 0) the write will timeout as usual. -
– socketDidCloseReadStream:
Conditionally called if the read stream closes, but the write stream may still be writeable.
-
– socketDidDisconnect:withError:
Called when a socket disconnects with or without error.
-
– socketDidSecure:
Called after the socket has successfully completed SSL/TLS negotiation.
This method is not called unless you use the provided startTLS method.
Instance Methods
newSocketQueueForConnectionFromAddress:onSocket:
This method is called immediately prior to socket:didAcceptNewSocket:.
It optionally allows a listening socket to specify the socketQueue for a new accepted socket.
If this method is not implemented, or returns NULL, the new accepted socket will create its own default queue.
- (dispatch_queue_t)newSocketQueueForConnectionFromAddress:(NSData *)address onSocket:(GCDAsyncSocket *)sock
Discussion
This method is called immediately prior to socket:didAcceptNewSocket:.
It optionally allows a listening socket to specify the socketQueue for a new accepted socket.
If this method is not implemented, or returns NULL, the new accepted socket will create its own default queue.
Since you cannot autorelease a dispatch_queue,
this method uses the “new” prefix in its name to specify that the returned queue has been retained.
Thus you could do something like this in the implementation:
return dispatch_queue_create(“MyQueue”, NULL);
If you are placing multiple sockets on the same queue,
then care should be taken to increment the retain count each time this method is invoked.
For example, your implementation might look something like this:
dispatch_retain(myExistingQueue);
return myExistingQueue;
Declared In
GCDAsyncSocket.h
socket:didAcceptNewSocket:
Called when a socket accepts a connection.
Another socket is automatically spawned to handle it.
- (void)socket:(GCDAsyncSocket *)sock didAcceptNewSocket:(GCDAsyncSocket *)newSocket
Discussion
Called when a socket accepts a connection.
Another socket is automatically spawned to handle it.
You must retain the newSocket if you wish to handle the connection.
Otherwise the newSocket instance will be released and the spawned connection will be closed.
By default the new socket will have the same delegate and delegateQueue.
You may, of course, change this at any time.
Declared In
GCDAsyncSocket.h
socket:didConnectToHost:port:
Called when a socket connects and is ready for reading and writing.
The host parameter will be an IP address, not a DNS name.
- (void)socket:(GCDAsyncSocket *)sock didConnectToHost:(NSString *)host port:(uint16_t)port
Discussion
Called when a socket connects and is ready for reading and writing.
The host parameter will be an IP address, not a DNS name.
Declared In
GCDAsyncSocket.h
socket:didReadData:withTag:
Called when a socket has completed reading the requested data into memory.
Not called if there is an error.
- (void)socket:(GCDAsyncSocket *)sock didReadData:(NSData *)data withTag:(long)tag
Discussion
Called when a socket has completed reading the requested data into memory.
Not called if there is an error.
Declared In
GCDAsyncSocket.h
socket:didReadPartialDataOfLength:tag:
Called when a socket has read in data, but has not yet completed the read.
This would occur if using readToData: or readToLength: methods.
It may be used to for things such as updating progress bars.
- (void)socket:(GCDAsyncSocket *)sock didReadPartialDataOfLength:(NSUInteger)partialLength tag:(long)tag
Discussion
Called when a socket has read in data, but has not yet completed the read.
This would occur if using readToData: or readToLength: methods.
It may be used to for things such as updating progress bars.
Declared In
GCDAsyncSocket.h
socket:didWriteDataWithTag:
Called when a socket has completed writing the requested data. Not called if there is an error.
- (void)socket:(GCDAsyncSocket *)sock didWriteDataWithTag:(long)tag
Discussion
Called when a socket has completed writing the requested data. Not called if there is an error.
Declared In
GCDAsyncSocket.h
socket:didWritePartialDataOfLength:tag:
Called when a socket has written some data, but has not yet completed the entire write.
It may be used to for things such as updating progress bars.
- (void)socket:(GCDAsyncSocket *)sock didWritePartialDataOfLength:(NSUInteger)partialLength tag:(long)tag
Discussion
Called when a socket has written some data, but has not yet completed the entire write.
It may be used to for things such as updating progress bars.
Declared In
GCDAsyncSocket.h
socket:shouldTimeoutReadWithTag:elapsed:bytesDone:
Called if a read operation has reached its timeout without completing.
This method allows you to optionally extend the timeout.
If you return a positive time interval (> 0) the read’s timeout will be extended by the given amount.
If you don’t implement this method, or return a non-positive time interval (<= 0) the read will timeout as usual.
- (NSTimeInterval)socket:(GCDAsyncSocket *)sock shouldTimeoutReadWithTag:(long)tag elapsed:(NSTimeInterval)elapsed bytesDone:(NSUInteger)length
Discussion
Called if a read operation has reached its timeout without completing.
This method allows you to optionally extend the timeout.
If you return a positive time interval (> 0) the read’s timeout will be extended by the given amount.
If you don’t implement this method, or return a non-positive time interval (<= 0) the read will timeout as usual.
The elapsed parameter is the sum of the original timeout, plus any additions previously added via this method.
The length parameter is the number of bytes that have been read so far for the read operation.
Note that this method may be called multiple times for a single read if you return positive numbers.
Declared In
GCDAsyncSocket.h
socket:shouldTimeoutWriteWithTag:elapsed:bytesDone:
Called if a write operation has reached its timeout without completing.
This method allows you to optionally extend the timeout.
If you return a positive time interval (> 0) the write’s timeout will be extended by the given amount.
If you don’t implement this method, or return a non-positive time interval (<= 0) the write will timeout as usual.
- (NSTimeInterval)socket:(GCDAsyncSocket *)sock shouldTimeoutWriteWithTag:(long)tag elapsed:(NSTimeInterval)elapsed bytesDone:(NSUInteger)length
Discussion
Called if a write operation has reached its timeout without completing.
This method allows you to optionally extend the timeout.
If you return a positive time interval (> 0) the write’s timeout will be extended by the given amount.
If you don’t implement this method, or return a non-positive time interval (<= 0) the write will timeout as usual.
The elapsed parameter is the sum of the original timeout, plus any additions previously added via this method.
The length parameter is the number of bytes that have been written so far for the write operation.
Note that this method may be called multiple times for a single write if you return positive numbers.
Declared In
GCDAsyncSocket.h
socketDidCloseReadStream:
Conditionally called if the read stream closes, but the write stream may still be writeable.
- (void)socketDidCloseReadStream:(GCDAsyncSocket *)sock
Discussion
Conditionally called if the read stream closes, but the write stream may still be writeable.
This delegate method is only called if autoDisconnectOnClosedReadStream has been set to NO.
See the discussion on the autoDisconnectOnClosedReadStream method for more information.
Declared In
GCDAsyncSocket.h
socketDidDisconnect:withError:
Called when a socket disconnects with or without error.
- (void)socketDidDisconnect:(GCDAsyncSocket *)sock withError:(NSError *)err
Discussion
Called when a socket disconnects with or without error.
If you call the disconnect method, and the socket wasn’t already disconnected,
this delegate method will be called before the disconnect method returns.
Declared In
GCDAsyncSocket.h
socketDidSecure:
Called after the socket has successfully completed SSL/TLS negotiation.
This method is not called unless you use the provided startTLS method.
- (void)socketDidSecure:(GCDAsyncSocket *)sock
Discussion
Called after the socket has successfully completed SSL/TLS negotiation.
This method is not called unless you use the provided startTLS method.
If a SSL/TLS negotiation fails (invalid certificate, etc) then the socket will immediately close,
and the socketDidDisconnect:withError: delegate method will be called with the specific SSL error code.
Declared In
GCDAsyncSocket.h


Understanding the principles benefits people because imagination and action are linked and engage the same part of the brain. So practising one actually improves the other one. In studies it has been proven that mentally imagining practising a physical skill can actually have almost similar effects as physically practising that skill. Understanding that mental practice is a good way to prepare for physical skills is beneficial to people to reach their full capabilities.
I would engage with the principles of neuroplasticity for my own benefit by repeatedly practising programming so that the neural networks and pathways shape themselves around it, which would aid in increasing my programming skills.
Bio Neuroplasticity and Learning - It was one of the videos in the lesson, but I found it very interesting and learnt new things about neuroplasticity that I never knew before.
A growth mindset is when students believe they can get smarter, they understand that effort makes them better. Therefore, they put in more time and effort, and that leads to higher achievement. It is relevant because it will help you with not just learning skills at Dev Academy but any skill in life. Having a fixed mindset will make things more difficult for yourself and you might not make the best of your full potential.
Before this exploration I had heard of growth mindsets but I didn’t know too much about it. So after knowing more about it now, it surprises me that most of the times in recent memory that I’ve gotten better at a particular skill have been times when I’ve tried to believe that I can do better.
I would integrate a growth mindset into my learning journey by trying to consciously make an effort to try to think that I can do something by believing it. Rather than putting up a brick wall by thinking I suck at something so therefore I can’t do it
Mindset Works - I thought this website was quite useful about growth mindsets. I also found the Brain Pickings website in the optional resources part of the page very informative.
Exploring neuroplasticity and growth mindsets has been beneficial and they will help me going forward with programming.
With growth mindsets I think I had been doing it occasionally a bit in the past year or so and was actually really helpful, but I just never realized that it had a name for it. Now that I know more about it I would definitely like to add it to my learning strategy. I will try to believe that I can do it, particularly when I am faced with a difficult programming problem instead of thinking this is too hard and I can’t.
I think engaging with ways of neuroplasticity would help me as well, since I’m a firm believer in practice makes perfect! So if repeatedly practising things helps neural networks and pathways in your brain then I will try to do more of that.


Discription
Pallet Town (also called Alabastia) is a small town in the west of Kanto, so to speak, a village, standing next to a hill and forest. There, Professor Oak is distributing Starter Pokémon. It is the hometown of Ash Ketchum, Gary Oak, Red, Blue and Green. The sun shines there very often. It was there that Ash returned after his travels in different regions.


$ git feature myfeature
switched to branch 'feature/rofl'
$ ...
$ git checkout develop
$ git feature finish myfeature
merging 'feature/rofl' into develop
deleted branch 'feature/rofl'
Also git-bug
and git-refactor
.
$ git delete-merged-branches
# hint: do `git remote prune origin` after
$ git create-branch development
$ git delete-branch development
$ git fresh-branch gh-pages
$ git summary # repo age, commits, active days, etc
$ git impact # impact graph
$ git effort # commits per file
$ git fork strongloop/express
# sync your fork with the original repository:
$ git remote add upstream https://github.com/ORIGINAL_OWNER/ORIGINAL_REPOSITORY.git
$ git fetch upstream; git merge upstream/master
Assumes that changes will not be committed.


7. LINK EXPORT¶
At this point, links have ben created and possibly improved. Now, interesting questions are:
-
Could these links be exported for external usage?
-
In what format are there available for export?
-
What metadata can be exported in combination with the links?
-
Can the linktype be modified prior to an export?
All these questions will be answered here.
7.1 Export Structure¶
The Lenticular Lens design imposes to itself and motivates its users to provide as much documentation as possible for explaining why (understandability) and how (reproducibility) a set of links is generated. This metadata in the Lenticular Lens can be organised into Generic and Specific metadata. A generic metadata is the annotation that applies to a set of links as a whole while a specific metadata applies to individual links. Indeed, all links residing in the Lenticular Lens can be exported. However, prior to doing that, one has to choose whether the metadata is to be included or not and if it is to be included, should it include Generic and/or Specific metadata?
Identity Set in the Default Graph. In the Example-1, using the turtle RDF syntax, we present a standard identity linkset where equivalent resources are linked with the well known linktype owl:sameAs.
Linkset in the default graph.
hero:BlackWidow owl:sameAs person:Nat .
hero:BlackWidow owl:sameAs person:Romanoff .
hero:BlackWidow owl:sameAs person:Natalia-Romanova .
hero:BlackWidow owl:sameAs person:Natasha .
hero:Spiderman owl:sameAs person:Peter-parker .
hero:Spiderman owl:sameAs person:Tom-Holland .
hero:Superman owl:sameAs person:Clark-Kent .
hero:Superman owl:sameAs person:Joseph .
hero:Superman owl:sameAs person:Kal-El .
Identity Set in a Named Graph. In Example-2, the set of links illustrated in Example-1 as triples populating the default graph can now be referred to as the graph with IRI ex:heroes-Identity. This IRI can now be used to document any generic information deemed relevant such as the source and target datasets, the aligning method…
Linkset in a named graph syntax.
ex:heroes-Identity
{
hero:BlackWidow owl:sameAs person:Nat .
hero:BlackWidow owl:sameAs person:Romanoff .
hero:BlackWidow owl:sameAs person:Natalia-Romanova .
hero:BlackWidow owl:sameAs person:Natasha .
hero:Spiderman owl:sameAs person:Peter-parker .
hero:Spiderman owl:sameAs person:Tom-Holland .
hero:Superman owl:sameAs person:Clark-Kent .
hero:Superman owl:sameAs person:Joseph .
hero:Superman owl:sameAs person:Kal-El .
}
Example-3 illustrates the complete structure of linksets and lenses in the Lenticular Lens. Here, by default, a linkset/lens is annotated with both, generic and specific metadata.
Generic Metadata. As shown in Example-3, the generic annotation associated with the superheroes identity linkset is composed of 14 triples, which are all element of the default graph (triple without a specific named graph). Among others, these triples convey information such as the type, subjects, license, description, format, number of triples, number of distinct entities, number of identity clusters… of the set.
Specific Metadata. This type of metadata remains in the linkset’s graph (applicable to a lens). It enable the reification of specific triples. One can for example provide the confidence strength of each of linkset’s statement. As illustrated in Example-3, the hero:Spiderman owl:sameAs person:Tom-Holland
is annotated as a non valid statement followed by the rational supporting its rejection. Such annotation enable the selection of specific triples. For example, on can select the 8 validated triples or the 7 triples validated as correct.
Separation of Concern. The linkset and lens presentation enable separation of concern in the sense that it provides the user with a number of options: Flat Representation: non reified triples optionally within a named graph; Partial Representation: the choice of exclusively including only the generic or the specific metadata; Full Representation: as intended in the Lenticular Lens, the linkset comes along with its generic and specific metadata if applicable.
Default RDF* turtle syntax annotation structure of a linkset in the the Lenticular Lens.
ex:heroes-Identity
a void:Linkset ;
dcterms:description "Identifying Marvel's superheroes" ;
dcterms:license law:odc-public-domain-dedication-and-licence ;
dcterms:subject <http://example.org/resource/Person> ;
dcterms:subject <http://example.org/resource/Hero> ;
void:subjectsTarget dataset:Fictive-Persons ;
void:objectsTarget dataset:Superheroes ;
void:feature format:Turtle ;
void:linkPredicate owl:sameAs ;
void:triples 9 ;
void:entities 12 ;
void:distinctSubjects 3 ;
void:distinctObjects 9 ;
voidPlus:clusters 3 ;
validation:count 8 ;
validation:accepted 7 ;
validation:rejected 1 ;
validation:remains 1 ;
ex:heroes-Identity
{
<<hero:BlackWidow owl:sameAs person:Nat>> validation:status "True" .
<<hero:BlackWidow owl:sameAs person:Romanoff>> validation:status "True" .
<<hero:BlackWidow owl:sameAs person:Natalia-Romanova>>
validation:status "True" .
<<hero:BlackWidow owl:sameAs person:Natasha>> validation:status "True" .
<<hero:Spiderman owl:sameAs person:Peter-parker>> validation:status "True" .
<<hero:Spiderman owl:sameAs person:Tom-Holland>>
validation:status "False" .
validation:Rational "Tom-Holland does not have Spiderman properties
which Peter-parker (fictitious) a.k.a Spiderman has." .
<<hero:Superman owl:sameAs person:Clark-Kent>> validation:status "True" .
<<hero:Superman owl:sameAs person:Joseph>> validation:status "True" .
hero:Superman owl:sameAs person:Kal-El .
}
7.2 Export Restrictions¶
As addressed in the previous section, link annotation provides the user with export options as described below.
Restrictions.
• All : Export all links
• Accepted : Export only accepted links.
• Rejected : Export only rejected links.
• Validated : Export rejected or validated links
• Not Validated : Export links with no accepted or rejected annotation.
• Threshold : Export links that pass a predefined threshold condition.
This feature applies to links annotated with confidence values.
7.3 Export Formats¶
Indeed, all links residing in the Lenticular Lens can be exported. For that, one is provided with three syntax options: CSV (Example-4), JSON-LD (Example-5), RDF Turtle (Example-6), and RDF* Turtle (Example-3).
CSV OUTPUT. In our attend to export a linkset/lens with its complete metadata, in a CSV format, the Lenticular Lens generates two CSV tables. As available in Example-4, the first table is an illustration of the metadata table while the second table is an illustration of the superheroes identity linkset.
Linkset in a CSV format.
Keep in mind that the table below are a visual representation of a CSV table
--------------------
-- METADATA TABLE --
--------------------
---------------------------------------------------------------------------------------------------------
| Vocabulary Value |
---------------------------------------------------------------------------------------------------------
http://www.w3.org/ns/sparql-service-description#namedGraph http://example.org/#heroesIdentity
http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://rdfs.org/ns/void#Linkset
http://purl.org/dc/terms/description Identifying Marvel's superheroes
http://purl.org/dc/terms/license law:odc-public-domain-dedication-and-licence
http://purl.org/dc/terms/subject http://example.org/resource/Person
http://purl.org/dc/terms/subject http://example.org/resource/Hero
http://rdfs.org/ns/void#subjectsTarget dataset:Fictive-Persons
http://rdfs.org/ns/void#objectsTarget dataset:Superheroes
http://rdfs.org/ns/void#feature format:Turtle
http://rdfs.org/ns/void#linkPredicate owl:sameAs
http://rdfs.org/ns/void#triples 9
http://rdfs.org/ns/void#entities 12
http://rdfs.org/ns/void#distinctSubjects 3
http://rdfs.org/ns/void#distinctObjects 9
http://vocabulary/voidPlus#clusters 3
http://vocabulary/validation#count 8
http://vocabulary/validation#accepted 7
http://vocabulary/validation#rejected 1
http://vocabulary/validation#remains 1
------------------------
-- LINKSET/LENS TABLE --
------------------------
------------------------------------------------------------------------------------------------------------------------------------------------
| NamedGraph Source Target ValStatus ValRational |
------------------------------------------------------------------------------------------------------------------------------------------------
http://example.org/#heroesIdentity http://example.org/hero#BlackWidow http://example.org/person#Nat True
http://example.org/#heroesIdentity http://example.org/hero#BlackWidow http://example.org/person#Romanoff True
http://example.org/#heroesIdentity http://example.org/hero#BlackWidow http://example.org/person#Natalia-Romanova True
http://example.org/#heroesIdentity http://example.org/hero#BlackWidow http://example.org/person#Natasha True
http://example.org/#heroesIdentity http://example.org/hero#Spiderman http://example.org/person#Peter-parker True
http://example.org/#heroesIdentity http://example.org/hero#Spiderman http://example.org/person#Tom-Holland False Tom-Holland does not have Spiderman properties which Peter-parker (fictitious) a.k.a Spiderman has.
http://example.org/#heroesIdentity http://example.org/hero#Superman http://example.org/person#Clark-Kent True
http://example.org/#heroesIdentity http://example.org/hero#Superman http://example.org/person#Joseph True
http://example.org/#heroesIdentity http://example.org/hero#Superman http://example.org/person#Kal-El True
JSON-LD OUTPUT. TODO....
Linkset in a JSON-LD format.
{
"@context":
{
"name": "http://xmlns.com/foaf/0.1/name",
"homepage":
{
"@id": "http://xmlns.com/foaf/0.1/workplaceHomepage",
"@type": "@id"
},
"Person": "http://xmlns.com/foaf/0.1/Person"
},
"@id": "https://me.example.com",
"@type": "Person",
"name": "John Smith",
"homepage": "https://www.example.com/"
}
RDF TURTLE OUTPUT. Our preference goes to an RDF* Turtle Output as illustrated in Example-3. However, because RDF* is not deployed on all triple stores, we provide the singleton representation alternative as well. An example of this representation in available in Example-6.
Linkset in an RDF Turtle format using singletons.
Default RDF turtle syntax annotation structure of a linkset in the the Lenticular Lens.
ex:heroes-Identity
a void:Linkset ;
dcterms:description "Identifying Marvel's heroes" ;
dcterms:license law:odc-public-domain-dedication-and-licence ;
dcterms:subject <http://example.org/resource/Person> ;
dcterms:subject <http://example.org/resource/Hero> ;
void:subjectsTarget dataset:Fictive-Persons ;
void:objectsTarget dataset:Superheroes ;
void:feature format:Turtle ;
void:linkPredicate owl:sameAs ;
void:triples 9 ;
void:entities 12 ;
void:distinctSubjects 3 ;
void:distinctObjects 9 ;
voidPlus:clusters 3 ;
validation:count 8 ;
validation:accepted 7 ;
validation:rejected 1 ;
validation:remains 1 ;
ex:heroes-Identity
{
hero:BlackWidow singleton:sameAs-1 person:Nat .
hero:BlackWidow singleton:sameAs-2 person:Romanoff .
hero:BlackWidow singleton:sameAs-3 person:Natalia-Romanova .
hero:BlackWidow singleton:sameAs-4 person:Natasha .
hero:Spiderman singleton:sameAs-5 person:Peter-parker .
hero:Spiderman singleton:sameAs-6 person:Tom-Holland .
hero:Superman singleton:sameAs-7 person:Clark-Kent .
hero:Superman singleton:sameAs-8 person:Joseph .
hero:Superman singleton:sameAs-9 person:Kal-El .
}
7.4 Default Export Table¶
Example-7 summarises the various options for exporting a linkset or lens. In each set of selection category, a default selection is checked in. This means that, by default, an exported linkset or lens comes along with all its links and its complete annotation in a CSV format.
Export Table
----------------------------------------------------------------
| RESTRICTIONS STRUCTURE FORMAT |
----------------------------------------------------------------
[x] All [x] Complete [x] CSV
[ ] Accepted [ ] Partial:Generic [ ] JSON-LD
[ ] Rejected [ ] Partial:Specific [ ] RDF-TURTLE
[ ] Validated [ ] RDF*-TURTLE
[ ] Not Validated
[ ] Threshold


[gecode-users] circuit constraint: differences between ICL_DOM and ICL_VAL
Kish Shen
kisshen at cisco.com
Wed Aug 26 20:30:28 CEST 2015
I am writing more unit tests for our Gecode interface, and for the
circuit constraint (without costs), I would like to write tests for the
supported propagation levels (ICL_DOM and ICL_VAL), and see some
difference between the two levels, but I am unable to do so:
I tried with circuits with up to 7 nodes, and then assigning a value to
one of the nodes. For both ICL_DOM and ICL_VAL, and both seem to produce
the same domains for the variables. Is this expected? If so, what do I
need to do to get a difference between the two propagations?
If the propagation is supposed to be different, this may indicate there
is a problem in the interface and the constraint is not actually posted
with the stated propagation levels...
Thanks and cheers,
Kish
More information about the users
mailing list


const val IS_DISABLED: Boolean
The default setting for whether the command is disabled, set as false (commands default to enabled).


Contact John Brosius for more information.
WEST HIGH SCHOOL 3505 West Locust Street Davenport, Iowa 52804 Phone:<PHONE_NUMBER>; Fax:<PHONE_NUMBER>


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Oculo uses GreenSock Animation Platform (GSAP) to handle its animation and benefits from GSAP's features and performance.
After you download Oculo, add the necessary files to the page.

Create HTML elements that correspond to your camera and scene.

My first scene...

Activate your camera by creating an instance with the desired options, adding and setting the scene, and rendering it.
var camera = new Oculo.Camera({
view: '#camera',
width: 500,
height: 250,
dragToMove: true,
wheelToZoom: true
}).addScene('scene1', '#scene');
camera.setScene('scene1');
camera.render();
// You can also create a scene like this:
camera.addScene('scene2', new Oculo.Scene('#scene2', 800, 400));
To see your new camera in action, call one of the animation methods.
camera.zoomTo(2, 1, { ease: Power2.easeOut });
Creating reusable animations can make working with your camera a breeze. Simply add your animation to your camera and play it in the future. If you create an animation without a defined starting point, it will play from the current camera state.
camera.addAnimation('zoomInOut', {
keyframes: [{
zoom: 2,
duration: 1,
options: {
ease: Power2.easeIn
}
}, {
zoom: 1,
duration: 1,
options: {
ease: Power2.easeOut
}
}]
});
//Play your animation in the future
camera.play('zoomInOut');
If you want an animation to consistently play from a defined starting point, just set the first keyframe's duration to 0.
camera.addAnimation('zoomIn', {
keyframes: [{
zoom: 1,
duration: 0,
}, {
zoom: 2,
duration: 1,
options: {
ease: Power2.easeOut
}
}]
});