"If These Walls Could Talk 2" (2000) Reviewed by Christian Pyle Directed by Jane Anderson, Martha Coolidge, and Anne Heche Written by Jane Anderson, Sylvia Sichel, and Anne Heche Starring Vanessa Redgrave, Michelle Williams, Chloe Sevigny, Sharon Stone, and Ellen DeGeneres Grade: C
HBO's "If These Walls Could Talk 2" is an anthology of three films, each set in the same house in a different year, each concerning a lesbian romance. It's not a sequel in any conventional sense. Its only link to "If These Walls Could Talk" is format; the first film told three stories about abortion that occurred in the same house in different years. (Oh, and Anne Heche acted in "Walls 1" and writes and directs one of the segments in "Walls 2.") I didn't like "Walls 1"; even though I agreed with it politically I found it overly manipulative and one-sided. On the other hand, its three parts fit together into a coherent whole. Although "Walls 2" is more pleasant to watch, its segments seem unrelated to each other.
The first segment is the only one with a Message. It's 1961, a time before terms like "significant other" and "spousal equivalent" were coined. To most people who know them, Edith (Vanessa Redgrave) and Abby (Marian Seldes) are just two elderly friends who live together. We meet them at the movies, where they're watching "The Children's Hour." The movie is about two schoolteachers whose lives are ruined by a rumor that they're lesbians. In the scene we see, Shirley MacLaine confesses to Audrey Hepburn that she is "guilty." The scene reminds us that "coming out of the closet" was not an option for Edith and Abby.
That night Abby has a stroke. She dies alone; because Edith isn't "family" she can't be in Abby's room after visiting hours. After the funeral Abby's nephew Ted (Paul Giamatti) and his wife Alice (Elizabeth Perkins) start making plans to sell the house that Abby and Edith bought together, and they box up Abby's belongings without any regard for Edith's feelings. Vanessa Redgrave gives a magnificent performance as a woman who is silently going through Hell. Although Abby and Edith lived for decades like a married couple, Edith cannot claim any right to her home, and no one understands the extent of her loss.
1972 finds a group of lesbian college students living in the house. They've just been ousted from the feminist collective they helped found because the other women are concerned about being known as a "lesbian group." On a lark Linda (Michelle Williams) and her pals go to a lesbian bar where they receive a cold reception from the middle-aged women dressed as men. There Linda meets Amy (Chloe Sevigny), a tough young woman in a button-down shirt and necktie. Linda's friends mock the "butch" look and question whether Linda can be a real lesbian if she's attracted to someone who looks like a man. The romance between Linda and Amy seems a variation on a familiar formula: the "girl next door" and the "rebel without a cause." Amy even has the requisite t-shirt and motorcycle.
Although on first glance "1972" would seem to have less to say than "1961," I found "1972" the most intriguing segment. The schisms between different groups of lesbians and between lesbians and feminists presents a complex portrait of a subculture in transition. However, these issues only serve as background for the romance, which has its own areas that I wish were explored more fully. Director Martha Coolidge and writer Sylvia Sichel present Amy as self-assured and in touch with her inner self. But what is that self? Any woman who straps down her breasts would seem to have self-acceptance problems. Does she see herself as a man? If so, what are the implications of that for Linda's lesbian identity? Or does Amy see herself as genderless? If so, why masquerade as a male? These are questions Coolidge and Sichel refuse to address.
The final segment takes us to the present day in 2000. The house is now shared by life partners Fran (Sharon Stone) and Kal (Ellen DeGeneres). Fran is trying to get pregnant, so the ladies are in search of a sperm donor. The tone is light-hearted, and the love Fran and Kal share is sweet and endearing. In contrast to the two previous segments, the present seems a utopia of equality and freedom, yet that doesn't seem an accurate reflection of reality. I was hoping that the third segment would take up the issues raised by the first two, but the plights of Edith, with no legal or social recognition of her marriage, and Linda, caught between warring factions, seem only distant memories.
Bottom line: If these walls could talk, would they say anything?
© 2000 Christian L. Pyle
Read my reviews and others at the Mad Review: http://www.madreview.com/main.html
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
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Related links: index of all rec.arts.movies.reviews reviews


| Interface and Description |
|---|
| com.smartsheet.api.AssociatedAttachmentResources
As of release 2.0
|
| com.smartsheet.api.AssociatedDiscussionResources
As of release 2.0
|
| com.smartsheet.api.AttachmentResources
As of release 2.0
This interface provides methods to access Attachment resources by their id. Thread Safety: Implementation of this interface must be thread safe. |
| com.smartsheet.api.ColumnResources
As of release 2.0
This interface provides methods to access Column resources. Thread Safety: Implementation of this interface must be thread safe. |
| com.smartsheet.api.CommentResources
As of release 2.0
|
Copyright © 2014–2021 Smartsheet. All rights reserved.


Tianzhu Qin
Future Data Scientist
<EMAIL_ADDRESS>© 2022
Reinforcement Learning in a Game
Dynamic-Programming
Monte-Carlo
TD
SARSA
Apr 30, 2019


A computer is a programmed machine that runs through the sequence of its instruction set. If the instruction is to boot the machine turns on. If the instruction is to launch an application it launches an application. If the instruction is to learn the machine learns.
This instruction set, usually called a program, is put on an electronic device called computer memory. Depending upon the type of storage needed there are different types of memories
To execute its programs a computer needs to find a way to access it first. For different types of programs there are different access strategies. A program running on a computer however has little understanding of how its instructions will actually be run. In other words the details of a program execution are abstracted from the program . This abstraction is called an operating system.
All running computers have a supervisor application running in the background (again an operating system) that determines how all of the other programs are going to be run.
So?
When a computer executes the set of instructions it becomes what is called a state machine. A state machine is simply a device that moves from one state to another when certain input is applied to it. Consider the following scenario as an example.
Now consider a computer that is already turned on and run through the following steps:-
In the first case the computer itself changes state from a machine at rest to a running system. In the second case an application changes state from being a program at rest to a running program.
Your entire session on a computer is basically a series of state changes. A movement of applications and programs from one state to another.
So?
With that definition we can try to understand what a computer is. A very simple definition -- a computer is simply an electronic state machine with devices that change the state of its programs. But if all computer did was to transition from a series of predefined states it would be pretty much useless. Imagine how lame it would be if your browser could only navigate one website? Or if your word processor could only edit a single document?
A computer is useful because it moves through not only predefined states but also user defined states. An example of a predefined state is the boot sequence. All you have to do to turn on the computer is to press the power button. The rest it does on its own.
An example of a user defined state machine could be your resume present in your documents directory. When you click to open your resume it starts a document processor , then it loads the contents on your file making it ready for editing. In this example the state of the document processor is stored in a file which is in turn stored on the hard disk.
As a user you create countless state machines that are executed on your behalf. In most programs these states are grouped under "settings" that can be tweaked. So that when a program starts it looks for these settings and loads them up to launch an environment that you prefer.
Oh!
Yeah!
sparvk is a portable distribution of open source operating systems that allow you to save your states in a detachable storage medium that can be plugged it inside any computer to start your session right where you left it off. Giving each one of your machines multiple dimensions.


A ring modulation actor
Ring modulation multiplies two signals together, sample by sample.
The two inputs of this actor are called the "Input" and the "Modulation Input".
The ModInput defaults to an internally-generated sine wave (whose
frequency is called the "Carrier Frequency").
But for more complex spectral effects the ModInput may be a sound coming from another actor.
The amplitude of the modulating signal is scaled by the "Modulation Index".
The output contains only those frequencies which are the sum and difference
of frequencies present in the two inputs.
So, for a narrow-band input
bandlimited source with sinewave modulation, ring modulation is like
frequency shifting: the input spectrum is shifted to appear symmetrically, above and
below the carrier frequency, with the input spectrum itself above the carrier, and the
mirror-image of the input spectrum below it.
To use the ring modulation actor, load ring.so and create an actor of type RingModActor.
RingModActor messages
In addition to the messages understood by all generator actors, the RingModActor understands the following messages:
- SetModFreq hActor x
- Set the default modulation frequency for new instances created by this actor to x.
- SetAllModFreq hActor x time
- Set the modulation frequency of all children to x, and set the default carrier frequency for all future children. If time is specified, children will modulate to the new carrier frequency over the specified duration. Default carrier frequency is always set immediately regardless of time.
- SetModIndex hActor x
- Set the default modulation index for new instances created by this actor to x.
- SetAllModIndex hActor x time
- Set the modulation index of all children to x, and set the default modulation index for all future children. If time is specified, children will modulate to the new modulation index over the specified duration. Default modulation index is always set immediately regardless of time.
RingModActor handler messages
In addition to the messages understood by all handlers, the handler for the RingModActor algorithm understands the following messages:
- SetInput hSound hHandler
- Set the input to come from the handler hHandler.
- SetInput hSound
- Set the input to zero (i.e., silence the input).
- SetModInput hSound hHandler
- Set the modulation input to come from the handler hHandler.
- SetModInput hSound
- Set the modulation input back to the internal sine wave generator.
- SetModFreq hSound x time
- Set the modulation frequency to x. If time is specified, modulate to the new carrier frequency over the specified duration.
- SetModIndex hSound x time
- Set the modulation index to x. If time is specified, modulate to the new modulation index over the specified duration.


“Karotha buddhasāsanaṁ, yaṁ katvā nānutappati; Khippaṁ pādāni dhovitvā, ekamante nisīdathā”ti.
Do the Buddha’s bidding, you won’t regret it. Having quickly washed your feet, sit in a discreet place to meditate.
… Visākhā therī ….


waveform:
sine
sawtooth
square
triangle
frequency:
440
Hz
volume in:
100
%
volume out:
0
%
trigger:
off
up
down
trigger level:
0
time:
2.27
ms
persistence:
2.27
ms
points:
100


In my last posting on the MSDN Briefing I outlined, that I migrated a sample that uses ASP.NET Membership API and Roles API for authenticating and authorizing users. Unfortunately the ASP.NET Membership and Roles API database as we know it does not work with SQL Azure as it uses some features not supported on SQL Azure.
Microsoft fortunately released updated scripts that you can use for creating a Membership and Roles API database that works with SQL Azure and with classic SQL Server:


|
| Data.THash | | Portability | non-portable (requires STM) | | Stability | experimental | | Maintainer | Edward Kmett<EMAIL_ADDRESS>|
|
|
|
|
|
| Description |
| A simple STM based transactional linear hash table based on Witold 1980.
This wraps a Data.THash.THT in an simple container. It may be
more appropriate to use the underlying THT structure directly if you are
nesting these. The performance hit hasn't yet been measured.
|
|
| Synopsis |
|
|
|
| Documentation |
|
| data THash k v |
| A hash with keys of type k to values of type v
|
|
|
| new :: (k -> Int) -> STM (THash k v) |
| Build an empty hash table
|
|
| newH :: Hashable k => STM (THash k v) |
| Build an empty hash table using the default hash function for the key type.
|
|
| fromList :: Eq k => (k -> Int) -> [(k, v)] -> STM (THash k v) |
| Build a hash table from a list of (key,value) pairs
|
|
| insert :: Eq k => THash k v -> k -> v -> STM Bool |
| Insert a value into the hash table. If a value with the key is present
then nothing is changed and False is returned.
|
|
| update :: Eq k => THash k v -> k -> v -> STM () |
| Insert a value into the hash table, replacing any value with the same key that is present.
|
|
| modify :: Eq k => THash k v -> k -> (Maybe v -> v) -> STM () |
| Update a value in the hash table using the supplied function.
|
|
| delete :: Eq k => THash k v -> k -> STM Bool |
| Remove a value from the hash table. Returns True to indicate success.
|
|
| lookup :: Eq k => THash k v -> k -> STM (Maybe v) |
| Lookup a value in the hash table.
|
|
| mapH :: ((k, v) -> r) -> THash k v -> STM [r] |
| Map a function over all (key,value) functions in the hash table.
|
|
| each :: THash k v -> STM [(k, v)] |
| each = mapH id and returns all (key,value) pairs in the hash.
|
|
| keys :: THash k v -> STM [k] |
| each = mapH fst and returns all keys in the hash.
|
|
| values :: THash k v -> STM [v] |
| each = mapH snd and returns all values present in the hash.
|
|
| hashInt :: Int -> Int |
| Thomas Wang's 32 bit mix function; more effective than a prime modulus for
declustering a linear hash, but not good against an adversary, since its easily
reversed.
|
|
| Produced by Haddock version 0.7 |


{% extends "main/base.html" %}
{% block title %} detailview {% endblock title %}
{% block content %}
{{object.user}}
posts
{{object.get_posts_no}}
likes given
{{object.get_likes_given_no}}
likes received
{{object.get_likes_received_no}}
friends
{{object.get_friends_no}}
{% if object.user not in rel_receiver and object.user not in rel_sender %}
{% endif %}
{% if object.user in rel_receiver and request.user not in object.friends.all %}
{% endif %}
{% if request.user in object.friends.all %}
{% endif %}


Annotate variant calls with context information
This tool is designed to annotate variant calls based on their context (as opposed to functional annotation). Various annotation modules are available; see the documentation for a complete list.
A variant set to annotate and optionally one or more BAM files.

This tool can be run in multi-threaded mode using this option.
This tool uses a sliding window on the reference.
All tools inherit arguments from the GATK Engine' "CommandLineGATK" argument collection, which can be used to modify various aspects of the tool's function. For example, the -L argument directs the GATK engine to restrict processing to specific genomic intervals; or the -rf argument allows you to apply certain read filters to exclude some of the data from the analysis.
This table summarizes the command-line arguments that are specific to this tool. For more details on each argument, see the list further down below the table or click on an argument name to jump directly to that entry in the list.
| Argument name(s) | Default value | Summary | |
|---|---|---|---|
| Required Inputs | |||
| --variant -V |
NA | Input VCF file | |
| Optional Inputs | |||
| --comp |
NA | Comparison VCF file | |
| --dbsnp -D |
NA | dbSNP file | |
| --resource |
NA | External resource VCF file | |
| --snpEffFile |
NA | SnpEff file from which to get annotations | |
| Optional Outputs | |||
| --out -o |
NA | File to which variants should be written | |
| Optional Parameters | |||
| --annotation -A |
NA | One or more specific annotations to apply to variant calls | |
| --excludeAnnotation -XA |
NA | One or more specific annotations to exclude | |
| --expression -E |
NA | One or more specific expressions to apply to variant calls | |
| --group -G |
NA | One or more classes/groups of annotations to apply to variant calls | |
| --MendelViolationGenotypeQualityThreshold -mvq |
0.0 | GQ threshold for annotating MV ratio | |
| Optional Flags | |||
| --alwaysAppendDbsnpId |
NA | Add dbSNP ID even if one is already present | |
| --list -ls |
NA | List the available annotations and exit | |
| --resourceAlleleConcordance -rac |
NA | Check for allele concordances when using an external resource VCF file | |
| --useAllAnnotations -all |
NA | Use all possible annotations (not for the faint of heart) |
Arguments in this list are specific to this tool. Keep in mind that other arguments are available that are shared with other tools (e.g. command-line GATK arguments); see Inherited arguments above.
Add dbSNP ID even if one is already present
By default, a dbSNP ID is added only when the ID field in the variant record is empty (not already annotated).
This argument allows you to override that behavior, and appends the new ID to the existing one. This is used
in conjunction with the -dbsnp argument.
Boolean
One or more specific annotations to apply to variant calls
See the --list argument to view available annotations.
List[String]
Comparison VCF file
If a record in the 'variant' track overlaps with a record from the provided comp track, the INFO field will be
annotated as such in the output with the track name (e.g. -comp:FOO will have 'FOO' in the INFO field).
Records that are filtered in the comp track will be ignored. Note that 'dbSNP' has been special-cased
(see the --dbsnp argument).
--comp binds reference ordered data. This argument supports ROD files of the following types: BCF2, VCF, VCF3
List[RodBinding[VariantContext]]
dbSNP file
rsIDs from this file are used to populate the ID column of the output. Also, the DB INFO flag will be set when appropriate.
--dbsnp binds reference ordered data. This argument supports ROD files of the following types: BCF2, VCF, VCF3
RodBinding[VariantContext]
One or more specific annotations to exclude
Note that this argument has higher priority than the -A or -G arguments,
so annotations will be excluded even if they are explicitly included with the other options.
List[String]
One or more specific expressions to apply to variant calls
This option enables you to add annotations from one VCF to another.
For example, if you want to annotate your callset with the AC field value from a VCF file named
'resource_file.vcf', you tag it with '-resource:my_resource resource_file.vcf' (see the -resource argument, also
documented on this page) and you specify '-E my_resource.AC'. In the resulting output VCF, any records for
which there is a record at the same position in the resource file will be annotated with 'my_resource.AC=N'.
INFO field data, ID, ALT, and FILTER fields may be used as expression values.
Note that if there are multiple records in the resource file that overlap the given position, one is chosen
randomly.
Set[String]
One or more classes/groups of annotations to apply to variant calls
If specified, all available annotations in the group will be applied. See the VariantAnnotator -list argument
to view available groups. Keep in mind that RODRequiringAnnotations are not intended to be used as a group,
because they require specific ROD inputs.
List[String]
List the available annotations and exit
Note that the --list argument requires a fully resolved and correct command-line to work. As an alternative,
you can use ListAnnotations (see Help Utilities).
Boolean
GQ threshold for annotating MV ratio
The genotype quality (GQ) threshold above which the mendelian violation ratio should be annotated.
double [ [ -∞ ∞ ] ]
File to which variants should be written
VariantContextWriter
External resource VCF file
An external resource VCF file or files from which to annotate.
Use this option to add annotations from a resource file to the output.
For example, if you want to annotate your callset with the AC field value from a VCF file named
'resource_file.vcf', you tag it with '-resource:my_resource resource_file.vcf' and you additionally specify
'-E my_resource.AC' (-E is short for --expression, also documented on this page). In the resulting output
VCF, any records for which there is a record at the same position in the resource file will be annotated with
'my_resource.AC=N'. Note that if there are multiple records in the resource file that overlap the given
position, one is chosen randomly. Check for allele concordance if using --resourceAlleleConcordance, otherwise
the match is based on position only.
--resource binds reference ordered data. This argument supports ROD files of the following types: BCF2, VCF, VCF3
List[RodBinding[VariantContext]]
Check for allele concordances when using an external resource VCF file
If this argument is specified, add annotations (specified by --expression) from an external resource
(specified by --resource) to the input VCF (specified by --variant) only if the alleles are
concordant between input and the resource VCFs. Otherwise, always add the annotations.
Boolean
SnpEff file from which to get annotations
The INFO field will be annotated with information on the most biologically significant effect
listed for each variant in the SnpEff file.
--snpEffFile binds reference ordered data. This argument supports ROD files of the following types: BCF2, VCF, VCF3
RodBinding[VariantContext]
Use all possible annotations (not for the faint of heart)
You can use the -XL argument in combination with this one to exclude specific annotations.Note that some
annotations may not be actually applied if they are not applicable to the data provided or if they are
unavailable to the tool (e.g. there are several annotations that are currently not hooked up to
HaplotypeCaller). At present no error or warning message will be provided, the annotation will simply be
skipped silently. You can check the output VCF header to see which annotations were actually applied (although
this does not guarantee that the annotation was applied to all records in the VCF, since some annotations have
additional requirements, e.g. minimum number of samples or heterozygous sites only -- see the documentation
for individual annotations' requirements).
Boolean
Input VCF file
Variants from this VCF file are used by this tool as input.
The file must at least contain the standard VCF header lines, but
can be empty (i.e., no variants are contained in the file).
--variant binds reference ordered data. This argument supports ROD files of the following types: BCF2, VCF, VCF3
R RodBinding[VariantContext]


Chapter 7 One Sample t-Test
Now that we have gone over the simple linear regression and how the simple linear regression is written and interpreted identically to the GLM (in addition to its standardized counterpart, the correlation), we can begin covering the other statistical analyses in the order they are typically taught.
Let’s now go over the one-sample t-test, which compares a sample mean to a population mean (or an a priori value).
For example, let’s say we were interested in determining if the salary of professors was significantly different than the national U.S. median income of $50,221 in 2009.
For this example, we will again be using the datasetSalaries
dataset.
7.1 Null and research hypotheses
7.1.1 Traditional Approach
\[H_0: \mu = \$50,221\] \[H_1: \mu \ne \$50,221\]
where \(\mu\) represents the population mean
The null hypothesis states that there is no difference between the sample and population mean, or equivalently the sample and population mean are equal. The research hypothesis states that there is a difference between the sample and population mean, or equivalently the sample and population mean are not equal.
7.1.2 GLM Approach
\[Model: Salary = \beta_0 + \varepsilon\] \[H_0: \beta_0 = \$50,221\] \[H_1: \beta_0 \ne \$50,221\]
where \(\beta_{0}\) represents the intercept, \(\varepsilon\) represents the population error, \(H_0\) represents the null hypothesis, and \(H_1\) represents the research hypothesis.
In this particular case, we will not be using the nil hypothesis as we have an a priori comparison of $50,221.
In the model, when there is no other predictor, the intercept will be the mean. This is because without any other information, the single best number to describe the data is the mean. Thus, the null hypothesis states the intercept (or the mean of 9-month academic salary of professors) is equal to $50,221. The research hypothesis states that the intercept (or the mean 9-month academic salary of professors) is not equal to $50,221.
7.2 Statistical analysis
7.2.1 Traditional Approach
To perform the traditional one-sample t-test, we can use the t.test()
function. The first input is the DV of salary
, which is again prefixed by the name of the dataset and the dollar sign. The second input is the a priori value (or population value, \(\mu\)) that we are interested in testing (i.e., $50,221).
##
## One Sample t-test
##
## data: datasetSalaries$salary
## t = 41.762, df = 396, p-value < 2.2e-16
## alternative hypothesis: true mean is not equal to 50221
## 95 percent confidence interval:
## 110717.9 116695.1
## sample estimates:
## mean of x
## 113706.5
From this output, we can see that the t-statistic (t
) is 41.762
, degrees of freedom (df
) is 396
, and the p-value
is 2.2e-16
, with professor’s mean salary at $113,706.50. Therefore, professors earn a significantly higher salary compared with the national U.S. median income of $50,221 in 2009.
The t-statistic and its respective p-value can be interpreted as we previously saw in the simple linear regression chapter. We will spend more time explaining these values in the next section.
7.2.2 GLM Approach
Since we have an a priori hypothesis (i.e., median income of $50,221), we will need to first manipulate the DV by point deviating from this a priori value. To do this, we will need to subtract $50,221 from each salary score. Luckily, we can do that directly within the lm()
fucntion. We have to point-deviate because the lm()
function always tests regression estimates including the intercept against 0 (\(H_0 = 0\)). By point deviating from $50,221, we are now asking if the mean of the new point deviated scores is different than 0, where 0 now equals $50,221. To test the intercept, we simply place a 1
as the predictor.
We will again only look at the coefficients table using the summary()
function for this test and subsequent t-tests. Although, the ANOVA source table is not typically associated with this test, we could always examine it if desired using the Anova()
function.
##
## Call:
## lm(formula = salary - 50221 ~ 1, data = datasetSalaries)
##
## Residuals:
## Min 1Q Median 3Q Max
## -55906 -22706 -6406 20479 117839
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 63486 1520 41.76 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 30290 on 396 degrees of freedom
Notice that in both approaches that the values are identical with respect to the place of rounding. The t-statistic is 41.76
with 396
degrees of freedom (df), and the p-value is <2e-16
. However, the estimate of the GLM approach is now the sample mean of the point deviated scores. Thus, we if add back $50,221
, we will obtain the same sample mean of $113,707
8.
Let’s go over the t-statistic and p-value to reinforce these concepts.
Remember that the t-statistic represents the systematic difference compared to the unsystematic difference. In this case, the systematic difference is the difference between professor’s mean salary and U.S. median income (i.e., $113,707 - $50,221) and the unsystematic difference is standard error of the mean of the sample (in other words, random variability in the sample).
Also, the p-value represents the probability of finding a particular t-statistic or t-statistic more extreme assuming that the null hypothesis is true. In this case, the probability of finding a t-statistic of 41.76
or more extreme is <2.2e-16
, which is extremely small and not likely to occur by chance.
7.3 Statistical decision
Given that the p-value of 2.2e-16
is smaller the alpha level (\(\alpha\)) of 0.05
, we will reject the null hypothesis.
7.4 APA statement
A one sample t-test was performed to test if the salary of professors was different than the national U.S. median of $50,221. Professor salaries (M = $113,706, SD = $30,289) were significantly higher than the national U.S. median income, t(396) = 41.76, p < .001.
7.5 Visualization
# calculate descriptive statistics along with the 95% CI
dataset_summary <- datasetSalaries %>%
dplyr::summarize(
mean = mean(salary),
sd = sd(salary),
n = n(),
sem = sd / sqrt(n),
tcrit = abs(qt(0.05 / 2, df = n - 1)),
ME = tcrit * sem,
LL95CI = mean - ME,
UL95CI = mean + ME
)
# plot
ggplot(datasetSalaries, mapping = aes("", salary)) +
geom_jitter(alpha = 0.1, width = 0.1) +
geom_hline(
yintercept = 50221,
alpha = .5,
linetype = "dashed"
) +
geom_errorbar(
data = dataset_summary,
aes(
y = mean,
ymin = LL95CI,
ymax = UL95CI
),
width = 0.01,
color = "#3182bd"
) +
geom_point(
data = dataset_summary, aes("", mean),
size = 2,
color = "#3182bd"
) +
labs(
x = "0",
y = "9-Month Salary (USD)"
) +
theme_classic() +
scale_y_continuous(labels = scales::dollar)
\(M = \$63,486+\$50,221=\$113,707\)↩


The Odyssey, Book I
A story by Homer
Tell me, O muse, of that ingenious hero who travelled far and wide after he had sacked the famous town of Troy. Many cities did he visit, and many were the nations with whose manners and customs he was acquainted; moreover he suffered much by sea while trying to save his own life and bring his men safely home; but do what he might he could not save his men, for they perished through their own sheer folly in eating the cattle of the Sun-god Hyperion; so the god prevented them from ever reaching home. Tell me, too, about all these things, O daughter of Jove, from whatsoever source you may know them.
Somewhere in the middle, another header appeared
So now all who escaped death in battle or by shipwreck had got safely home except Ulysses, and he, though he was longing to return to his wife and country, was detained by the goddess Calypso, who had got him into a large cave and wanted to marry him. But as years went by, there came a time when the gods settled that he should go back to Ithaca; even then, however, when he was among his own people, his troubles were not yet over; nevertheless all the gods had now begun to pity him except Neptune, who still persecuted him without ceasing and would not let him get home.
Some text set in a recursive


nips nips2002 nips2002-52 nips2002-52-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Olivier Chapelle, Jason Weston, Bernhard SchĂślkopf
Abstract: We propose a framework to incorporate unlabeled data in kernel classifier, based on the idea that two points in the same cluster are more likely to have the same label. This is achieved by modifying the eigenspectrum of the kernel matrix. Experimental results assess the validity of this approach. 1
[1] A. Blum and T. Mitchell. Combining labeled and unlabeled data with co-training. In COLT: Proceedings of the Workshop on Computational Learning Theory. Morgan Kaufmann Publishers, 1998.
[2] O. Chapelle, V. Vapnik, O. Bousquet, and S. Mukherjee. Choosing multiple parameters for support vector machines. Machine Learning, 46(1-3):131-159, 2002.
[3] T. Jaakkola and D. Haussler. Exploiting generative models in discriminative classifiers. In Advances in Neural Information Processing, volume 11, pages 487-493. The MIT Press, 1998.
[4] T. Joachims. Transductive inference for text classification using support vector machines. In Proceedings of the 16th International Conference on Machine Learning, pages 200- 209. Morgan Kaufmann, San Francisco, CA, 1999.
[5] A. Y. Ng, M. I. Jordan, and Y. Weiss. On spectral clustering: Analysis and an algorithm. In Advances in Neural Information Processing Systems, volume 14, 200l.
[6] K Nigam, A. K McCallum, S. Thrun, and T. M. Mitchell. Learning to classify text from labeled and unlabeled documents. In Proceedings of AAAI-9S, 15th Conference of the American Association for Artificial Intelligence, pages 792- 799, Madison, US, 1998. AAAI Press, Menlo Park, US.
[7] B. Scholkopf, J. Shawe-Taylor, A. J. Smola, and R. C. Williamson. Generalization bounds via eigenvalues of the Gram matrix. Technical Report 99-035 , NeuroColt, 1999.
[8] B. Scholkopf, A. Smola, and K-R. Muller. Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation, 10:1299- 1310, 1998.
[9] M. Seeger. Covariance kernels from Bayesian generative models. In Advances in Neural Information Processing Systems, volume 14, 200l.
[10] M. Seeger. Learning with labeled and unlabeled data. Technical report , Edinburgh University, 200l.
[11] M. Szummer and T. Jaakkola. Partially labeled classification with markov random walks. In Advances in Neural Information Processing Systems, volume 14, 200l.
[12] K Tsuda, T. Kin, and K Asai. Marginalized kernels for biological sequences. Bioinformatics , 2002. To appear. Also presented at ICMB 2002.
[13] Y. Weiss. Segmentation using eigenvectors: A unifying view. In International Conference on Computer Vision, pages 975- 982 , 1999.


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AP PHOTOS: How ‘The Crown’ actors compare to real royals
by The Associated PressThe third season of “The Crown” welcomes a new cast as it tells the story of the modern British monarchy.
The series starts off in the swinging 1960s of London and Olivia Colman is Queen Elizabeth II. Helena Bonham Carter is Princess Margaret and Tobias Menzies is royal spouse Prince Philip.
Josh O’Connor and Erin Doherty join the cast as Charles and Anne, the grown offspring of Elizabeth and Philip. Casting and costuming were almost as crucial as the scripts by Peter Morgan.
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The Associated Press has created a photo gallery to illustrate how some of the actors compare to the real figures.
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Skinnydip London Has Dropped a Disney Villains Collection and You'd Be a Poor, Unfortunate Soul if You Didn’t Shop It, TBH
We love a Disney fashion collaboration as much as the next person, however, one thing they almost all seem to have in common is that that fail to acknowledge some of the Disney fam’s most iconic characters: the villains.
Whether you love them or still love to hate them, there’s no denying the likes of Cruella de Vil, Ursula, and Maleficent are responsible for some of the most fabulously savage quotes of our childhood. I, for one, am still not over the time Maleficent called her subjects “poor, simple fools” and dubbed herself The Mistress of Evil. I mean, power move or what?
So what better way to celebrate these characters than with some snazzy-themed accessories? Skinnydip London just launched a capsule range of neat phone cases and makeup bags, available online and in stores today, inspired by three of the sassiest baddies of all time.
Whether you’re on the hunt for the perfect Christmas present or you just want to treat yourself, these affordably priced goodies are set to be utterly enchanting additions to your cart.
Scroll through to see the collection...


Snookes1516.github.io
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{% extends 'base.html' %} {% block content %}
March 2018
Small defense game I created while learning game development in Unity. Take control of the Knight faction to defend yourself from the attacking Samurai!
-- Stack --
C# Unity
February 2018
Little Pokedex I made to learn and practice using PHP.
-- Stack --
PHP HTML/CSS
December 2017
Have you ever wanted to own your own monster horde? Cryptomonsters is a card collecting app that uses blockchain technology to let users 'mine' for monsters with unique attributes.
-- Stack --
Python Django Bootstrap AWS
November 2017
Space Rocks is a data visualization site for the NASA N.E.O (Near Earth Objects) API in an attempt to make information, like what's floating above us, easily accessible and fun to look at.
-- Stack --
Python Pyramid Bokeh PostgreSQL HTML5 CSS
October 2017
A website for anyone who has ever been in an accident. Easily recreate the accident and send an email off to your insurance rep.
-- Stack --
JavaScript jQuery Express Node.js HTML5 CSS


--- layout: post title: "Win a ticket to Progressive.Net Tutorials" comments: true ---
Thanks to Skillsmatter, I have been given some tickets to give away to the Progressive.Net tutorials at Skillsmatter, London between September 5th and 7th.
This is an event I have very fortunate to be presenting at. The event schedule can be found on the event page.
In order to be in for a chance to win a ticket, you will need to send me a mail answering the following question:
Why are you interested in going to the Progressive.Net Tutorials and what do you hope to learn from the event?
*COMPETITION IS NOW CLOSED!


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Uganda, is a country in East-Central Africa. It is bordered to the east by Kenya, to the north by South Sudan, to the west by the Democratic Republic of the Congo, to the south-west by Rwanda, and to the south by Tanzania. The southern part of the country includes a substantial portion of Lake Victoria, shared with Kenya and Tanzania. Uganda is in the African Great Lakes region. Uganda also lies within the Nile basin, and has a varied but generally a modified equatorial climate.
“The Pearl of Africa” is synonymous with Uganda. Winston Churchill dubbed Uganda “The Pearl of Africa” in 1907 while just a young Member of Parliament, saying:
“The kingdom of Uganda is a fairy-tale. You climb up … and at the end there is a wonderful new world. The scenery is different, the vegetation is different, the climate is different, and, most of all, the people are different from anything elsewhere to be seen in the whole range of Africa … I say: ‘Concentrate on Uganda’. For magnificence, for variety of form and colour, for profusion of brilliant life – bird, insect, reptile, beast – for vast scale — Uganda is truly the pearl of Africa.”
Jinja is famed for its adrenaline inducing activities thereby obtaining its title as East Africa’s adrenaline capital. Get your fix white water rafting, kayaking, bungee jumping, quad biking, horse riding and mountain biking through the colonial town and through the villages to appreciate the sunset over the mighty river Nile. Stand in the spot John Speke was when he ‘discovered’ the source of the Nile, feel like a true explorer that you are!
Murchison Falls Conservation Area ( MFCA ) comprises of Murchison Falls National Park, Bugungu and Karuma Falls Wildlife Reserves. This is where the Nile explodes through a narrow gorge and cascades down to become a placid river whose banks are thronged with hippos and crocodiles, waterbucks and buffaloes. The vegetation is characterised by savannah, riverine forest and woodland. Wildlife includes lions, leopards, elephants, giraffes, hartebeests, oribis, Uganda kobs, chimpanzees, and many bird species. The waters of the Nile force their way through a small slit within the rocks, which is just 7 meters or 23 feet wide, and topples to 43 meters or 141 feet below with a thunderous roar forming a residual water stray that forms a beautiful rainbow; the view is very breathtaking!
Queen Elizabeth National Park is understandably Uganda’s most popular tourist destination. The park’s diverse ecosystems, which include sprawling savanna, shady, humid forests, sparkling lakes and fertile wetlands, make it the ideal habitat for classic big game, ten primate species including chimpanzees and over 600 species of birds. Set against the backdrop of the jagged Rwenzori Mountains, the park’s magnificent vistas include dozens of enormous craters carved dramatically into rolling green hills, panoramic views of the Kazinga Channel with its banks lined with hippos, buffalo and elephants, and the endless Ishasha plains, whose fig trees hide lions ready to pounce on herds of unsuspecting Uganda ko
Gorilla trekking is the biggest draw and the highlight of all visits in Uganda. Gorillas are one of the rarest and most intriguing apes and the fact that Uganda has their biggest population in the world makes gorilla trekking a must-do activity. In Uganda, gorilla trekking can be done in Bwindi Impenetrable Forest and Mgahinga National Park, marvel at the unique gorillas in this once in a lifetime experience.
Like the mountains, Uganda has plenty of lakes formed in a volcanic crater or caldera. The ones in dormant volcanoes like Lake Kyaninga in Fort Portal in western Uganda have fresh waters. A swim in the Crater Lake in Kyaninga before lunch at Kyaninga Lodge is something some ought to do while in Uganda. The serenity of Lake Kyaninga is as inviting as it’s ominous, with steep banks at most edges, she hides her 220 metre depth well. The swim across looks doable by the average swimmer, with the constant foreboding that a prehistoric monster will rise out of his murky depth and make a quick lunch of one, adding to the excitement!


examplify is a jQuery plugin for turning live JavaScript into working in-page code examples.
If you've ever written about code, either in your blog, in your documentation, or in example pages like this, you've run into situations where you wanted to display a working code example in the page.
Your first instinct may be to write the script, and then copy and paste it into a pre
tag in the
page for display.
However, after doing that a few times, you'll realize that every time you change your code or your example (like to fix a bug), you have to edit your code in two places: once in your real code, and once in the example code.
(Either that, or you're forgetting to update your example, meaning it's out of sync with your working code and will confuse the hell out of your users when they cut-and-paste the example from your page and it doesn't work.)
examplify solves that problem.
With examplify, you simply write your examples as regular JavaScript, in regular script
tags. Examplify takes
each script and injects it into the page as HTML, so the examples your users see are identical to the ones that
are being executed on the page.
Using examplify is easy.
First, include jQuery and examplify at the top of the page. Make sure jQuery is included first.
Then, write each of your code examples in separate script
tags, preferably in the body of the page.
Give each script
tag a unique id, prefixed with "examplify".
It doesn't matter what the id is, as long as it starts with the prefix, and it's unique. Could be "examplify-some-example-name" or "examplifySomeExampleName" or "examplify_someExampleName" or whatever convention you prefer.
Then, simply call $.examplify()
inside $(document).ready()
, and you're done. Whatever code
is in your examplify script
tags will be spit out into the page inside a pre
tag (by default).
The best part about examplify is that all your code is live JavaScript, so everything is fully executable as code examples/demos in your page.
(To see how these examples are implemented, simply view the source of this page.)
Once you've got the basics down, check out the Advanced Usage page to see how you can configure and customize examplify to suit your needs.
If you have any questions or issues, please submit them via the Github Issues section so everyone can benefit from the answer.


Themes
-
Theme protocol: the base of all themes.
ThemeKit makes available, without any further coding:
- a
LightTheme
(the default macOS theme) - a
DarkTheme
(the dark macOS theme, usingNSAppearanceNameVibrantDark
) - a
SystemTheme
(which dynamically resolve to eitherLightTheme
or `DarkTheme depending on the macOS preference at System Preferences > General > Appearance)
You can choose wheter or not to use these, and you can also implement your custom themes by:
- implementing native
Theme
classes conforming to this protocol andNSObject
- provide user themes (
UserTheme
) with.theme
files
Please check the provided Demo.app project for sample implementations of both.
See moreDeclaration
Swift
@objc(TKTheme) public protocol Theme : NSObjectProtocol
- a
-
System theme.
Will dynamically resolve to either
See moreThemeManager.lightTheme
orThemeManager.darkTheme
, depending on the macOS preference at System Preferences > General > Appearance.Declaration
Swift
@objc(TKSystemTheme) public class SystemTheme : NSObject, Theme
-
A
Theme
class wrapping a user provided theme file (.theme
).To enable user themes, set theme folder on
ThemeManager.userThemesFolderURL
.Notes about
.theme
files:- lines starting with
#
or//
will be treated as comments, thus, ignored; - non-comment lines consists on simple variable/value assignments (eg,
variable = value
); variable
name can contain characters[a-zA-Z0-9_-.]+
;- custom variables can be specified (eg,
myBackgroundColor = ...
); - theming properties match the class methods of
ThemeColor
,ThemeGradient
andThemeImage
(eg,labelColor
); - variables can be referenced by prefixing them with
$
(eg,mainBorderColor = $commonBorderColor
); - colors are defined using
rgb(255, 255, 255)
orrgba(255, 255, 255, 1.0)
(case insensitive); - gradients are defined using
linear-gradient(color1, color2)
(where colors are defined as above; case insensitive); - pattern images are defined using
pattern(named:xxxx)
(named images) orpattern(file:../dddd/xxxx.yyy)
(filesystem images); - images are defined using
image(named:xxxx)
(named images) orimage(file:../dddd/xxxx.yyy)
(filesystem images); ThemeManager.themes
property is automatically updated when there are changes on the user themes folder;- file changes are applied on-the-fly, if it corresponds to the currently applied theme.
Example
.theme
file:// ************************* Theme Info ************************* // displayName = My Theme 1 identifier = com.luckymarmot.ThemeKit.MyTheme1 darkTheme = true // ********************* Colors & Gradients ********************* // # define color for `ThemeColor.brandColor` brandColor = $blue # define a new color for `NSColor.labelColor` (overriding) labelColor = rgb(11, 220, 111) # define gradient for `ThemeGradient.brandGradient` brandGradient = linear-gradient($orange.sky, rgba(200, 140, 60, 1.0)) // ********************* Images & Patterns ********************** // # define pattern image from named image "paper" for color `ThemeColor.contentBackgroundColor` contentBackgroundColor = pattern(named:paper) # define pattern image from filesystem (relative to user themes folder) for color `ThemeColor.bottomBackgroundColor` bottomBackgroundColor = pattern(file:../some/path/some-file.png) # use named image "apple" namedImage = image(named:apple) # use image from filesystem (relative to user themes folder) fileImage = image(file:../some/path/some-file.jpg) // *********************** Common Colors ************************ // blue = rgb(0, 170, 255) orange.sky = rgb(160, 90, 45, .5) // ********************** Fallback Assets *********************** // fallbackForegroundColor = rgb(255, 10, 90, 1.0) fallbackBackgroundColor = rgb(255, 200, 190) fallbackGradient = linear-gradient($blue, rgba(200, 140, 60, 1.0))
With the exception of system overrided named colors (e.g.,
See morelabelColor
), which defaults to the original system provided named color, unimplemented properties on theme file will default to-fallbackForegroundColor
,-fallbackBackgroundColor
,-fallbackGradient
and-fallbackImage
, for foreground color, background color, gradients and images, respectively.Declaration
Swift
@objc(TKUserTheme) public class UserTheme : NSObject, Theme
- lines starting with


You name it! E-Commerce, E-Learning, i've already been there and have experience building Single Page Applications.
React Native is the main framework used today for building mobile apps, you can deliver Android and iOS apps in no time with Native experience and performance for your users.
If you need a backend developer that can maintain your node.js or typescript code you are looking in the right direction.
We will talk about each other, get to know us better, and i will get your project idea and try to explain it to you in simple words. If i understood correctly then we are good to go!
In this step I will show you some mocks and ideas that i have for your project, you can share your mocks and ideas too! we will use this as a base to start defining your project's logic.
For my work I feel very comfortable with scrum, you will know every day the project status checking at my trello board. I like to keep things very well organized and have communication with you almost every day!, and also don't forget about the weekly demos :)
Deploy the servers, deploy the code, upload the android and iOS apps and give you the control of everything!, i will be with you in this process making hotfixes and make sure that everything runs smoothly.
Fullstack Engineer
Building apps, teaching other people how to code, making your ideas come true is what i'm truly passionate about.


argocd app
Command-line interface to manage applications by Argo CD.
More information: home page
- List applications:
argocd app list --output json|yaml|wide
- Get application details:
argocd app get app_name --output json|yaml|wide
- Deploy application internally (to the same cluster that Argo CD is running in):
argocd app create app_name --repo git_repo_url --path path/to/repo --dest-server https://kubernetes.default.svc --dest-namespace ns
- Delete an application:
argocd app delete app_name
- Enable application auto-sync:
argocd app set app_name --sync-policy auto --auto-prune --self-heal
- Preview app synchronization without affecting cluster:
argocd app sync app_name --dry-run --prune
- Show application deployment history:
argocd app history app_name --output wide|id
- Rollback application to a previous deployed version by history ID (deleting unexpected resources):
argocd app rollback app_name history_id --prune


|
| int | enet_address_get_host (const ENetAddress *address, char *name, size_t nameLength) |
| | Attempts to do a reverse lookup of the host field in the address parameter. More...
|
| |
| int | enet_address_get_host_ip (const ENetAddress *address, char *name, size_t nameLength) |
| | Gives the printable form of the IP address specified in the address parameter. More...
|
| |
| int | enet_address_set_host (ENetAddress *address, const char *name) |
| | Attempts to resolve the host named by the parameter hostName and sets the host field in the address parameter if successful. More...
|
| |
| int | enet_address_set_host_ip (ENetAddress *address, const char *name) |
| | Attempts to parse the printable form of the IP address in the parameter hostName and sets the host field in the address parameter if successful. More...
|
| |
| void | enet_deinitialize (void) |
| | Shuts down ENet globally. More...
|
| |
| enet_uint32 | enet_host_random_seed (void) |
| |
| int | enet_initialize (void) |
| | Initializes ENet globally. More...
|
| |
| ENetSocket | enet_socket_accept (ENetSocket socket, ENetAddress *address) |
| |
| int | enet_socket_bind (ENetSocket socket, const ENetAddress *address) |
| |
| int | enet_socket_connect (ENetSocket socket, const ENetAddress *address) |
| |
| ENetSocket | enet_socket_create (ENetSocketType type) |
| |
| void | enet_socket_destroy (ENetSocket socket) |
| |
| int | enet_socket_get_address (ENetSocket socket, ENetAddress *address) |
| |
| int | enet_socket_get_option (ENetSocket socket, ENetSocketOption option, int *value) |
| |
| int | enet_socket_listen (ENetSocket socket, int backlog) |
| |
| int | enet_socket_receive (ENetSocket socket, ENetAddress *address, ENetBuffer *buffers, size_t bufferCount) |
| |
| int | enet_socket_send (ENetSocket socket, const ENetAddress *address, const ENetBuffer *buffers, size_t bufferCount) |
| |
| int | enet_socket_set_option (ENetSocket socket, ENetSocketOption option, int value) |
| |
| int | enet_socket_shutdown (ENetSocket socket, ENetSocketShutdown how) |
| |
| int | enet_socket_wait (ENetSocket socket, enet_uint32 *condition, enet_uint32 timeout) |
| |
| int | enet_socketset_select (ENetSocket maxSocket, ENetSocketSet *readSet, ENetSocketSet *writeSet, enet_uint32 timeout) |
| |
| enet_uint32 | enet_time_get (void) |
| | Returns the wall-time in milliseconds. More...
|
| |
| void | enet_time_set (enet_uint32 newTimeBase) |
| | Sets the current wall-time in milliseconds. More...
|
| |
ENet Unix system specific functions.


Automatic Scaling¶
The auto-scale button (to the right of Media Set) enables/disables automatic scaling of the scatterplot axes when points are hidden or filtered out (these two mechanisms are mutually exclusive, see Selection Action and Filtering). As points are removed, the locations of the remaining points shift to span the available space and the axes are redrawn to reflect the reduced value range. The mapping between point colors and the values shown in the legend is also modified to reflect the reduced value range (i.e. the new maximum value is now mapped to the brightest red and the new minimum value maps to the deepest blue, maximizing the color distinctions between the remaining points). Compare the scatterplots in Figure 40 and Figure 41 to see the effects of using auto-scaling.
This feature is especially useful if a variable’s value range is skewed by a few anomalous points. For example, imagine a data set where most points have x-coordinates in the range from 0 to 1, but a few points have extreme values of 10,000. Including the extreme points means that most of the plot consists of empty space, while the majority of points are drawn on top of one another near the origin. By filtering and rescaling, you can remove the extreme points and have the remaining points fill the plot. Note that automatic scaling is enabled as the default, indicated by the darkened state of the button (Figure 41).


For the evening, I made plans for myself and all of my friends to go to Javier's ceremony, and everybody agreed. However, when the time to go came, all of them changed their minds. I too felt tired, and would have stayed home if I had the slightest excuse to do so. I talked to Javier about the possibility of staying home, but he insisted on me going. I even mentioned the possibility of going just for a healing, without drinking, but he said that it would be better to drink. I decided to listen to him and just go.
There were about 12 people who were going, but they all had something in common. It was a great group, with many friends. I was happy to be part of it.
The ceremony itself was the most amazing I ever had. I understood a lot about the nature of the universe, and about the power of love. I felt like I communicated with God. I could hear spirits all around me, singing along with Javier and his disciples. It was easy to pick out the voices of the female spirits, because I knew there were no women sitting beside me, but whether there were any male spirits singing, I don't know. The spirits knew all of the words of the songs, and sang flawlessly. The first woman had a sort of lazy voice that was slightly out of tune, but the woman who sang after was extremely energetic and sang beautifully. For a while, I just sat and listened.
I had visions and insights about human beings, about how we live, about our ignorance, and about our potential. At a particular moment, I thought about Ninfa. Then I realized that thinking about her may be distracting, so I stopped that thought after a split second. However, it was too late, already the thought had an effect. I felt her come and sit next to me, on my right. It felt beautiful. Then Kirill and Alex came and sat on my left. We were all there together! Throughout the night, I felt many spirits coming and sitting or standing next to me.
I thought about divorce, and people who marry and divorce three times. Something like that cannot be normal. And I realized that people don't know what they are looking for. They have material success, but not happiness. Yet they keep chasing after more material success. What they don't realize is that if you drink salt water and it doesn't clench your thirst, it is of no use to drink more of it.
I saw in a vision how poor people live. The 3 by 3 meter room in which Karina lives with her aging mother came vividly to mind. “These people don't have anything”, I thought. “They are so poor, it's unbelievable.” Maybe Karina met me when she did for a reason. Maybe she really needed some financial help for her birthday. I decided right there that I would give her another 20 dollars as a present. It was clear to me that if one gives, one will receive. I decided to give what I can.
As my trance deepened, Life itself was presented before me. I contemplated it in awe. Every second, life continued. Yet every second was a great mystery. I focused on my breath and tried to stay centered. Realizations came to me, many of which I have now forgotten. For example, I had an idea for a book that would have really helped people to see the spiritual truth of this world. However, later on, when I though about it, I couldn't remember anything I wanted to write.
I saw in my visions that anything that helps life, that allows life and makes us experience it more fully is good and enlightening, while anything that denies life is a sin. Therefore, losing consciousness after drinking alcohol is against life. The more I drink, the less aware I become. The same is true about philosophy. I can write anything I want about philosophy, but if I am not living, what use is any writing?  I saw this in a vision. These realizations about life had a very Buddhist feel about them. I understood the importance of doing things properly. One thing at a time is enough.
As I sat there, just breathing, I felt that I was in direct contact with life. My heart was filled with love for everyone. Everything came back to me, and I saw myself as a central focal figure in this thing called life. I saw each family unit as a basic trinity. The sacred love between the man and the woman, and the presence of the child all had mystical significance. The stories of Adam and Eve and others came to my mind, but not as myths or historical facts. Everything every true religion was talking about was right here, right now.
Soon, very intense cleansing began, and I started to vomit chunks of stuff. It was difficult work. With a lot of force, I expelled one after another huge chunks of stuff. The entire process lasted for about 2 or 3 hours. By the end of it, a chunk got stuck in my throat, and I could feel it with my fingers from the outside. Inside, I felt a pain each time I swallowed. On the way home, I continued throwing up and coughing up small chunks of this piece of phlegm that was stuck in my throat. It looked white and sticky, and I was only able to get rid of tiny pieces of it at a time. The effects of the medicine were gone, but my stomach continued working, collecting old energies to be purged.
We returned home with Lyla, and found the front door locked and the bell disabled. We banged on the door, and tried to climb over several times, but with no effect. Finally, we went downtown and found Alan's number. After dawn, we returned to Alan's house in San Lorenzo and called him, asking him to open the door for us. I then went to the shower, where I sat for a while enjoying the hot water and spitting the remains of the phlegm in my throat.
During the ceremony, I took off my shirt and walked around without it. I was sweating profusely, so it helped a little bit.
Javier also told me several times that I will be a very famous painter. He said that I will be great, and I was very happy to hear it. I could see it myself in a vision after he said it. I saw that the first thing I needed to do was double my prices, and I also saw that I would sell some paintings. The next morning, I indeed doubled the prices.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Ronin A film review by Marty Mapes Copyright 1998 Marty Mapes
*** (out of 4) RONIN tries to be a thinking man's thriller. It doesn't succeed in that endeavor, but it approaches the action with such vigor and confidence that it ends up being an excellent flick.
Sam (Robert DeNiro), an American freelance mercenary, meets his contact in a French café. He has been hired by an Irish agent (Natascha McElhone) to acquire a certain briefcase. Joining Sam are Vincent (Jean Reno), the French acquirer; Gregor (Stellan Skarsgård), the possibly-German agent with catlike reflexes; and Spence (Sean Bean), the overeager young Englishman.
The contents of the briefcase are secret, even to the audience. This was one of Frankenheimer's devices to increase the depth of the film. The idea is that without knowing what they are fighting for, these mercenaries must carefully examine their motives and loyalties. But when Sam is told he can't know the contents, he ups his price and ends the conversation. So much for the thought- provoking device. Actually, it doesn't detract from the film at all, it just doesn't have the importance that Frankenheimer had obviously hoped for.
Before they begin their mission, the crew stocks up on weapons and technology. The scene of the weapons buy introduces us to the movie's intricately planned, paranoid action scenes. First Sam gets a funny feeling that something isn't right. Then Spence notices that only some of the shipment has been delivered. The dealers try to lure the mercenaries into a trap, giving them their first taste of danger on a mission destined to be filled with it.
If I were to see the movie again, I might appreciate the way this scene makes the characters question their loyalty to an unknown cause. But because the tension and action were so deftly handled, I was too engrossed to be thinking about the big picture. Ironically, that also contributes to why I say Frankenheimer didn't fully succeed in what he intended.
The mysterious case is now in Italy, and our anti-heroes plan their attack. The level of detail in their plan is fascinating. The 30 minutes or so that goes into setting up the big grab is as cunning as the best caper, heist, or spy movie. The plan culminates in an outstanding action sequence full of amazing stunts and adrenalin-pumping car chases.
Admittedly, the chase scene has a few hackneyed moments - the Construction-on-the-Roadway, the Fish Cart, and that timeless classic, the Vegetable Stand With Stacked Boxes. Seems like it shouldn't be so difficult to think up some new obstacles, but maybe the filmmakers were paying homage to the great cinematic tradition that is the car chase.
Regardless, Frankenheimer can be forgiven some clichés, because he avoided the use of digital effects in the car chase scenes. It's an expensive decision, but the results are worth it. When a stunt is real, it is a feat worthy of the medium - an amazing act of ingenuity and bravery immortalized on film. When a stunt is computer-generated, (or faked by sound effects and deceptive editing) the gut-level excitement and tension just isn't there. In RONIN, it's there, thanks to some of the best car chases on film. Needless to say, Sam and company do not retrieve the case (the movie's only half over). The second half of the movie has them tracking the case as before, but this half lacks the cleverness and intricate planning introduced earlier. There is more action and as much tension, but it doesn't have the finesse of the first hour, and its absence is felt.
The second half of the film reintroduces the question of loyalty and explains the film's title. The Ronin, we are told, were a group of samurai whose master was betrayed and killed. They banded together, lordless, to exact their revenge. When the Ronin executed the traitor, they still didn't have a master and they no longer had a crusade, so they committed ritual suicide. "They chose honor, they chose myth," says Jean-Pierre (Michael Lonsdale, who is very good in this marginal role). "They chose wrong," retorts Sam, reinforcing the film's easy answer to the its own questions about loyalty.
Like the device of the mystery case, this scene is an attempt to add a level of depth to the film. But like the device of the mystery case, it doesn't succeed.
Even without Sam's curt response, the scene doesn't add much, because the movie goes out of its way to introduce Jean-Pierre.  Instead of this keystone metaphor arising from the action, it feels as though it has been carefully placed on top of the action.
After they leave Jean-Pierre, the mercenaries head back to France, hot on the trail of the prized case. One final breathtaking car chase (the one that will be remembered) keeps the film's pace brisk, right up to the obligatory twist ending.
The ultimate ending, the one that explains the significance of the mission, seems like one final contrivance, one last attempt by Frankenheimer to make this action movie appear smarter than it really is. Nevertheless, the addition of this (and the other) devices never really hurt the movie. That's because as a pure action-thriller, RONIN is far above average.
Check out more current movie reviews at http://www.indra.com/~mmapes/
-- Marty Mapes Movie Habit<EMAIL_ADDRESS>http://net.indra.com/~mmapes
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


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infection
A mutation testing framework for PHP.
More information: home page
- Analyze code using the configuration file (or create one if it does not exist):
infection
- Use a specific number of threads:
infection --threads number_of_threads
- Specify a minimum Mutation Score Indicator (MSI):
infection --min-msi percentage
- Specify a minimum covered code MSI:
infection --min-covered-msi percentage
- Use a specific test framework (defaults to PHPUnit):
infection --test-framework phpunit|phpspec
- Only mutate lines of code that are covered by tests:
infection --only-covered
- Display the mutation code that has been applied:
infection --show-mutations
- Specify the log verbosity:
infection --log-verbosity default|all|none


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And now a link to follow and another.
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Returns clean record object
getCleanRecord([strict])
Returns object.
| strict |
boolan, if true, it will remove all fields from record object that are not in fields array |
Description
This method cleans record and returns it. Clean record is the one that has just ids for enum/list/combo fields and not the object with { id, text } values. Also, if you suply strict as true, it will remove all fields from record that are not described in fields array.
If you have following form:
You can do:


Hello! My name is YU JI EUN. I study in YongIn University. My major is Information Management. So I can learn about programming and management.
I like to listening to music. But I don't remember singers,the song's name, lyrics. Because I usually listen to the melody. So I have a hard time of searching the song I want to listen. For that reason, the singer and song i remeber become my favorite singer,song. I recommend singers on next page. I wish you enjoy it.


Use the form below to calculate the amount of XP and evolutions achievable for pokemon evolutions. The calculator takes in to account the number of candies that are gained durring each evolution. This allows for more accurate preperation for lucky egg grinds or XP gains.
| Pokemon | Evos | EXP Gained | Extra Candy | Est. Time (Min) | New Pokemon | Lucky Egg |
|---|


Team Singapore
Team Singapore is a shared identity for all Singaporeans, and is one big family inspiring one another through sport. It is a relationship that extends beyond the sporting fraternity, and beyond the major Games.
Team Singapore is about living better lives as we embody values inherent in sport: a winning spirit, an appreciation for teamwork, a commitment to purpose, the importance of ethical behaviour and a love for our country.
Taken from - https://www.myactivesg.com/Team-Singapore/About-Us16 June, 1995
Male
born and raised in Singapore, being a fourth-generation Singaporean. Joseph Schooling is the only child of May and Colin Schooling,and is of Eurasian ethnicity.
26 December, 2000
Female
I grew to love being in the water and trained for competitive swimming. I am a proud Singaporean, and being a Team Singapore athlete allows me to exercise my patriotism.
27 January, 1997
Female
My family and the team are my source of strength and motivation, and I know I want to do better so I can make them proud! I like to socialise almost anywhere, as long as my friends are there, and the food is good.
09 August, 1998
Female
My love for this sport started because it was and still is a great outlet for your daily frustrations and it lets you take your mind off things.
13 August, 1997
Male
Irfan started his career at the National Football Academy (Singapore). In 2013, Irfan was named as one of Goal.com's Top 20 Southeast Asian Rising Stars. In 2014, he was named as one of The Guardian's 40 best young talents in world football.
09 April, 1999
Male
Ikhsan Fandi Ahmad is a Singaporean professional footballer who plays as a forward for Norwegian First Division club Raufoss IL.
29 May, 1962
Male
My love for this sport started because it was and still is a great outlet for your daily frustrations and it lets you take your mind off things.
22 September, 1991
Male
He is known for being a technical player with good pace, excellent reading of the game and ball-playing capabilities. He also has a knack for scoring goals.
25 February, 1991
Female
I started getting interested in Silat when I watched my brother fight. That was when I knew I wanted to compete and prove that girls can fight just as well as the boys can, Graduated from Ngee Ann Poly
18 June, 2001
Female
Sometimes, I feel that Silat and I were meant to be - I fell in love at my first kick! I'm very grateful for the opportunity to be a Team Singapore athlete because through it, I get the opportunity to represent the country and to bring up my family name.
08 March, 1996
Male
My father was a world and SEA Games champion numerous times over. Since I have coach in such close proximity, it was a logical move to follow in his footsteps.
29 October, 1996
Male
When my sister got into the Singapore Sports School, I was so envious and I wanted to do better than her - it’s this really positive spin on sibling rivalry that got me to where I am in the sport!


By using capture on your event listeners you can make sure the events are also passed in as usual to the built in camera controls. This can be selectively disabled by calling stopPropagation() on the event.
This is one of many possible implementations of panning around a model, including the ability to set the target by clicking. It is left as an example here as there are too many possible variations to make a reasonable API around. It also tends to be confusing to users in cases where it is not necessary.
Using shift-drag or two-finger drag on mobile, one can rotate the skybox to see how the environment would cast light onto the object from different angles.


[§613-4] Annual report. The center shall submit a report on its activities to the legislature at least twenty days prior to the convening of each regular legislative session. [L 1989, c 346, pt of §2; am L 1991, c 131, §1]


siliconmotion
Section: Devices and Network Interfaces (4)Updated: xf86-video-siliconmotion 1.7.5
Index Return to Main Contents
NAME
siliconmotion - Silicon Motion video driverSYNOPSIS
Section N'34'DeviceN'34'Identifier N'34'devnameN'34'
Driver N'34'siliconmotionN'34'
...
[ Option "optionname" ["optionvalue"]]
EndSection
DESCRIPTION
siliconmotion is an Xorg driver for Silicon Motion based video cards. The driver is fully accelerated, and provides support for the following framebuffer depths: 8, 16, and 24. All visual types are supported for depth 8, and TrueColor visuals are supported for the other depths.SUPPORTED HARDWARE
The siliconmotion driver supports PCI and AGP video cards based on the following Silicon Motion chips:- Lynx
- SM910
- LynxE
- SM810
- Lynx3D
- SM820
- LynxEM
- SM710
- LynxEM+
- SM712
- Lynx3DM
- SM720
- Cougar3DR
- SM731
- MSOC
- SM501,SM502
CONFIGURATION DETAILS
Please refer to xorg.conf(5) for general configuration details. This section only covers configuration details specific to this driver. All options names are case and white space insensitive when parsed by the server, for example, "lynxe" and "LynxE" are equivalent.Multihead mode configuration is done through the RandR1.2 interface (see xorg.conf(5) and xrandr(1) for further information). Hardware accelerated screen rotation and framebuffer resizing are only supported with the EXA acceleration architecture (see the AccelMethod option below).
The driver auto-detects the chipset type, but the following ChipSet names may optionally be specified in the config file N'34'DeviceN'34' section, and will override the auto-detection:
- "lynx", "lynxe", "lynx3d", "lynxem", "lynxem+", "lynx3dm", "cougar3dr", "msoc".
The following Cursor Options are supported:
- Option N'34'HWCursorN'34' N'34'booleanN'34'
- Enable or disable the HW cursor. Default: on.
- Option N'34'SWCursorN'34' N'34'booleanN'34'
-
Inverse of "HWCursor". Default: off.
The following display Options are supported:
- Option N'34'VideoKeyN'34' N'34'integerN'34'
- Set the video color key.
- Option N'34'ByteSwapN'34' N'34'booleanN'34'
- Turn on byte swapping for capturing using SMI demo board. Default: off.
- Option N'34'InterlacedN'34' N'34'booleanN'34'
- Turn on interlaced video capturing. Default: off.
- Option N'34'UseBIOSN'34' N'34'booleanN'34'
- Use the BIOS to set the modes. This is used for custom panel timings. Default: off for SM72x and SM5xx, otherwise on.
- Option N'34'DualheadN'34' N'34'booleanN'34'
- Enable dualhead mode. Currently not all chips are supported and hardware video overlay (XV) support may have some limitations. Default: off.
- Option N'34'PanelSizeN'34' N'34'widthxheightN'34'
- Override LCD panel dimension autodetection.
- Option N'34'UseFBDevN'34' N'34'booleanN'34'
- Don't actually program the hardware mode registers, but leave it as set by the operating system. Only available on MSOC chips. Default: off.
- Option N'34'CSCVideoN'34' N'34'booleanN'34'
- CSC video uses color space conversion to render video directly to the framebuffer, without using an overlay. Only available on MSOC chips. Default: on.
The following video memory Options are supported:
- Option N'34'mclkN'34' N'34'integerN'34'
- Sets the memory clock. You must specify the units. For example 50Mhz is the same as 50000Khz or 50000000Hz. On MSOC chips this is the main clock source for all functional blocks, such as the 2D engine, GPIO, Video Engine, and DMA Engine. This option is only used for debugging purposes on MSOC chips. Default: probe the memory clock value, and use it at server start.
- Option N'34'mxclkN'34' N'34'integerN'34'
- Sets the memory clock. You must specify the units. For example 50Mhz is the same as 50000Khz or 50000000Hz. Clock source for the local SDRAM controller. This option is only available on MSOC chips and used only for debugging purposes. Default: probe the memory clock value, and use it at server start.
The following acceleration and graphics engine Options are supported:
- Option N'34'NoAccelN'34'
- Disable acceleration. Very useful for determining if the driver has problems with drawing and acceleration routines. This is the first option to try if your server runs but you see graphic corruption on the screen. Using it decreases performance, as it uses software emulation for drawing operations the video driver can accelerate with hardware. Default: acceleration is enabled.
- Option N'34'AccelMethodN'34' N'34'stringN'34'
-
Chooses between available acceleration architectures. Valid options are
XAA
and
EXA.
XAA is the traditional acceleration architecture and support for it is very
stable. EXA is a newer acceleration architecture with better performance for
the Render and Composite extensions, but the rendering code for it is newer and
possibly unstable. The default is
XAA.
The following PCI bus Options are supported:
- Option N'34'PciBurstN'34' N'34'booleanN'34'
- will enable PCI burst mode. This should work on all but a few broken PCI chipsets, and will increase performance. Default: on.
- Option N'34'PciRetryN'34' N'34'booleanN'34'
-
will allow the driver to rely on PCI Retry to program the registers.
PciBurst
must be enabled for this to work.
This will increase performance, especially for small fills/blits,
because the driver does not have to poll the card before sending it
commands to make sure it is ready. It should work on most
recent PCI chipsets. Default: value of
PciBurst
option.
SEE ALSO
Xorg(1), xorg.conf(5), Xserver(1), X(7)SUPPORT
For assistance with this driver, or Xorg in general, check the web site at http://www.x.org/. If you find a problem with Xorg or have a question not answered in the FAQ please use our bug report form available on the web site or send mail to<EMAIL_ADDRESS>When reporting problems with the driver send as much detail as possible, including chipset type, a server output log, and operating system specifics.AUTHORS
Kevin Brosius, Matt Grossman, Harald Koenig, Sebastien Marineau, Mark Vojkovich, Frido Garritsen, Corvin Zahn.
Index
This document was created by man2html, using the manual pages.
Time: 05:33:53 GMT, December 24, 2015


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- Unordered list option 1
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| Total net profit | -56.02 | Gross profit | 0.0 | Gross loss | -56.02 |
| Profit factor | 0.0 | Expected payoff | -1.19 | ||
| Absolute drawdown | -56.02 | Maximal drawdown (%) | 55.25 (-7175.32%) | ||
| Total trades | 47 | Profit trades (% of total) | 0 (0.0%) | Loss trades (% of total) | 47 (100.0%) |
| Long positions (won %) | 23 (0.0%) | Short positions (won %) | 24 (0.0%) | ||
| Largest | profit trade | -0.39 | loss trade | -2.53 | |
| Average | profit trade | 0.0 | loss trade | -1.19 | |
| Minimum | profit trade | 0.0 | loss trade | -0.39 | |
| Maximum | take profit in pips | 530.9 | stop loss in pips | -1393.0 | |
| Average | take profit in pips | 260.1 | stop loss in pips | -311.6 | |
| Minimum | take profit in pips | -188.8 | stop loss in pips | -91.8 | |
| Maximum | Reward-Risk | 5.8 | Duration in minutes | 21428 | |
| Average | Reward-Risk | 1.6 | Duration in minutes | 1312.7 | |
| Minimum | Reward-Risk | 0.0 | Duration in minutes | 0 | |
| Maximum | consecutive wins (profit in money) | 0.0 (0.0) | consecutive losses (loss in money) | 47.0 (-56.02) | |
| Average | consecutive wins | 0.0 | consecutive losses | 47.0 |
| Total net profit | -34.32 | Gross profit | 0.0 | Gross loss | -34.32 |
| Profit factor | 0.0 | Expected payoff | -1.49 | ||
| Absolute drawdown | -34.32 | Maximal drawdown (%) | 33.55 (-4357.14%) | ||
| Total trades | 23 | Profit trades (% of total) | 0 (0.0%) | Loss trades (% of total) | 23 (100.0%) |
| Largest | profit trade | 0.0 | loss trade | -2.53 | |
| Average | profit trade | 0.0 | loss trade | -1.49 | |
| Minimum | profit trade | 0.0 | loss trade | -0.47 | |
| Maximum | take profit in pips | 354.7 | stop loss in pips | -652.8 | |
| Average | take profit in pips | 137.4 | stop loss in pips | -386.4 | |
| Minimum | take profit in pips | -188.8 | stop loss in pips | -138.9 | |
| Maximum | Reward-Risk | 2.2 | Duration in minutes | 5246.0 | |
| Average | Reward-Risk | 0.6 | Duration in minutes | 1495.8 | |
| Minimum | Reward-Risk | 0.0 | Duration in minutes | 8.0 | |
| Maximum | consecutive wins (profit in money) | 0.0 (0.0) | consecutive losses (loss in money) | 23.0 (-34.32) | |
| Average | consecutive wins | 0.0 | consecutive losses | 23.0 |
| Total net profit | -21.7 | Gross profit | 0.0 | Gross loss | -21.7 |
| Profit factor | 0.0 | Expected payoff | -0.9 | ||
| Absolute drawdown | -21.7 | Maximal drawdown (%) | 21.09 (-3457.38%) | ||
| Total trades | 24 | Profit trades (% of total) | 0 (0.0%) | Loss trades (% of total) | 24 (100.0%) |
| Largest | profit trade | 0.0 | loss trade | -2.35 | |
| Average | profit trade | 0.0 | loss trade | -0.9 | |
| Minimum | profit trade | 0.0 | loss trade | -0.39 | |
| Maximum | take profit in pips | 530.9 | stop loss in pips | -1393.0 | |
| Average | take profit in pips | 377.5 | stop loss in pips | -240.0 | |
| Minimum | take profit in pips | 33.7 | stop loss in pips | -91.8 | |
| Maximum | Reward-Risk | 5.8 | Duration in minutes | 21428.0 | |
| Average | Reward-Risk | 2.6 | Duration in minutes | 1137.2 | |
| Minimum | Reward-Risk | Duration in minutes | 0.0 | ||
| Maximum | consecutive wins (profit in money) | 0.0 (0.0) | consecutive losses (loss in money) | 24.0 (-21.7) | |
| Average | consecutive wins | 0.0 | consecutive losses | 24.0 |


Rolling Islanders turn wild rally into shootout win
by Associated PressAnthony Beauvillier scored twice during a three-goal, third-period rally, and the Islanders beat the Flyers 4-3 in a shootout Saturday night in Philadelphia.
Beauvillier and Mathew Barzal combined to erase a 3-0 deficit in the final 13 minutes of regulation, and Jordan Eberle and Barzal scored in the shootout.
The Islanders are on a 13-0-1 roll that has vaulted them into second place in the Metropolitan Division behind Washington. It’s their longest stretch without a regulation loss since a 15-game run in 1982.
After getting stymied by goaltender Brian Elliott for most of the evening, the Islanders broke through when Beauvillier took advantage of the Flyers’ sloppy line change before beating Elliott.
Barzal slammed one past Elliott on a power play with 6:22 left, and Beauvillier got his fourth goal in two games with 2:04 left.
Thomas Greiss stopped 28 shots and turned away Sean Couturier and Claude Giroux in the shootout.
Couturier got the game’s first goal on a wrist shot that deflected off defenseman Nick Leddy’s stick in the first period.
Ivan Provorov scored on a power play with 24 seconds left in the first. He one-timed Couturier’s feed for his fourth goal of the season.
Oskar Lindblom added his ninth of the season midway through the second period.


greenpaint
greenpaint is an in-browser crossword solver, written in vue.js. It’s easy to integrate into your own website.
Try the demo puzzle or an instance of greenpaint where you can upload your own puzzle.
Features
- Customizable keybinds
- 37 built-in themes (courtesy of emacs-doom-themes)
- All the basic crossword features (checking square/word/grid, clearing, revealing square/word/grid, stopwatch, rebus, etc)
- JSON or puz input
Installation and setup
Installing greenpaint
- Download the latest build from the Releases page
Add the following HTML to your website:

You can stop at this point if you don’t want to specify a puzzle to play. If greenpaint can’t find a valid JSON or puz file, it loads in “upload” mode, which means that the user can upload their own puzzle to play.
Using puz files
greenpaint can read puzzle data from puz binaries. I have implemented puz parsing with the help of the source code from AcrossLiteToText and Phil. If you want to use a puz, simply put its path where the code snippet says "path/to/json/or/puz"
. Users can also upload their own puz files in upload mode.
The puz parser has not been rigorously tested. If your puzzle doesn’t work, especially if it contains rebuses or circles or other fancy things, try the JSON method.
Using JSON files
greenpaint can read puzzle data from the JSONs produced by AcrossLiteToText. First, download the latest release of AcrossLiteToText and unzip it.
Converting a single .puz on Mac:
- Install Homebrew if you don’t have it
- Run
brew install dotnet
in Terminal - Type
cd
in Terminal, then a space, then drag and drop the AcrossLiteToText folder you downloaded - Run
dotnet AcrossLiteToText.dll [from] [to] [filename]
. All three seem to be required for JSON export.[from]
is the path to your .puz file,[to]
is the location where you want your JSON file to go, and[filename]
is what you want the converted file to be named. The instructions for AcrossLiteToText claim that[to]
and[filename]
are optional, but it seems to be required for JSON export. So, for example, if I have a file calledpuzzle.puz
in the same directory as myAcrossLiteToText.dll
, and I want to save the JSON in the same directory, and I want the JSON to be calledpuzzle.json
, I run the following command:dotnet AcrossLiteToText.dll puzzle.puz . puzzle
. The period in the middle means “the current directory”. - Delete the vestigial .txt and .xml files
This is annoying if you have a whole folder of puz files you want to convert. I wrote a script to convert a whole folder to JSON automatically. To use it (on Mac or Linux):
- Download the script
- Move it to the same folder as your
AcrossLiteToText.dll
- In the Terminal, navigate to that folder (
cd /path/to/your/acrosslitetotext/folder
) - In the Terminal, run
chmod +x convertjson.sh
- In the Terminal, run
zsh convertjson.sh [from] [to]
[from]
is the folder containing your puz files. [to]
is the folder where you want the JSONs to go.
Loading your puzzles in greenpaint
Now that you have a puzzle (either puz or JSON), all you need to do is let greenpaint find it. greenpaint looks for an element with the "puzzlepath"
id, and looks at the body of the element to read where the file is.
- Upload the file to your server in whatever way your setup requires.
Add the element to the page you’re loading greenpaint in (I use
script
tags):…  …
Note that the path must be enclosed in quotes (otherwise, Javascript thinks it’s a regular expression). I recommend using an absolute path (like
"https://yourwebsite.com/path/to/json"
), since then you avoid the headaches endemic to relative paths in websites.
Usage
Setting keybinds
My primary motivation for making greenpaint was so that I could have my own keybindings for grid movement. So, greenpaint allows you to define custom keybinds. Here’s a table of the default bindings:
| Function | Intuitive bind | Emacs-inspired bind |
|---|---|---|
| move right by square | ArrowRight |
Ctrl-f |
| move left by square | ArrowLeft |
Ctrl-b |
| move up by square | ArrowUp |
Ctrl-p |
| move down by square | ArrowDown |
Ctrl-n |
| delete square | Backspace |
Ctrl-d |
| move right by word | Tab , Enter |
|
| move left by word | Shift-Tab , Shift-Enter |
|
| move to start of word | Ctrl-a |
|
| move to end of word | Ctrl-e |
|
| delete rest of word | Ctrl-k |
|
| switch direction | Space |
You can change the keybinds by going to the Settings tab. Click on a keybind to delete it, or enter a new one in the box to add it.
You can bind the following keys by themselves: Tab
, Space
, Backspace
, ArrowRight
, ArrowLeft
, ArrowUp
, ArrowDown
, and Enter
. Additionally, you can prepend Ctrl-
or Shift-
to any of that list, as well as an alphanumeric (but you can’t bind a letter by itself; sorry vimmers). You can bind multiple keys at a time by separating them with a comma (with no space), like this: ArrowRight,Ctrl-f
.
Hit enter to add the bind, and click apply to apply it.
Changing themes
My other motivation was having dark themes. You can change to any of the 37 themes included in greenpaint. These themes are from the emacs-doom-themes project (MIT), maintained by the nonpareil Henrik Lissner. Caveat emptor: with some dark themes, it’s hard to read the letter under point.
Some dark themes that work particularly well are: oceanic next, ephemeral (defualt), dracula, challenger dark, and fairy floss.
Limitations and bugs
- Rebuses are weird. Hit enter after inputting a rebus instead of clicking the rebus button
- It’s not responsive, so Sundays might be a little hard to read
- Doesn’t work on mobile
Licensing 🥱
greenpaint is released under the MIT License. Use it for whatever you want.


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