2.10. WMI – Make request to WMI¶
The WmiManager
is accessible via windows.system.wmi
Note
See sample WMI
2.10.1. WmiManager¶
-
class
windows.winobject.wmi.
WmiManager
[source]¶ The main WMI class exposed, used to list and access differents WMI namespace, can be used as a dict to access
WmiNamespace
by name- Example:
>>> windows.system.wmi["root\SecurityCenter2"] <WmiNamespace "root\SecurityCenter2">
-
namespaces
¶ The list of available WMI namespaces
-
query
¶ WmiRequester.query()
for default WMI namespace ‘root\cimv2’
-
select
¶ WmiRequester.select()
for default WMI namespace ‘root\cimv2’
2.10.2. WmiNamespace¶
-
class
windows.winobject.wmi.
WmiNamespace
(namespace)[source]¶ Bases:
windows.generated_def.interfaces.IWbemServices
,windows.winobject.wmi.WmiComInterface
An object to perform wmi request to a given
namespace
-
DEFAULT_ENUM_FLAGS
= 48L¶ The defauls flags used for enumeration.
(WBEM_FLAG_RETURN_IMMEDIATELY | WBEM_FLAG_FORWARD_ONLY)
-
classes
¶ The list of classes in the namespace. This a a wrapper arround
create_class_enum()
.Returns: [ WmiObject
] - A list ofWmiObject
-
classmethod
connect
(namespace, user=None, password=None)[source]¶ Connect to
namespace
usinguser
andpassword
for authentification if givenReturns: WmiNamespace
- The connectedWmiNamespace
-
create_class_enum
(superclass, flags=48L, deep=True)[source]¶ Enumerate the classes in the
namespace
that matchsuperclass
. ifsuperclass
is None will enumerate all top-level class.deep
allow to returns all subclassesReturns: WmiEnumeration
-
create_instance_enum
(clsname, flags=48L, deep=True)[source]¶ Enumerate the instances of
clsname
. Deep allows to enumerate the instance of subclasses as wellReturns: WmiEnumeration
- Example:
>>> windows.system.wmi["root\subscription"].create_instance_enum("__EventConsumer", deep=False).all() [] >>> windows.system.wmi["root\subscription"].create_instance_enum("__EventConsumer", deep=True).all() [<WmiObject instance of "NTEventLogEventConsumer">]
-
exec_method
(obj, method, inparam, flags=0)[source]¶ Exec method named on
object
withinparam
.params obj: The WmiObject
or path of the object the call apply toparams method: The name of the method to call on the object params inparam: The WmiObject
representing the input parameters and retrieve usingWmiObject.get_method()
Returns: WmiCallResult
(object)
if flag WBEM_FLAG_RETURN_IMMEDIATELY was passedReturns: WmiObject
the outparam object if flag WBEM_FLAG_RETURN_IMMEDIATELY was NOT passedNote
This API will lakely change to better wrap with WmiObject/inparam/Dict & co
-
exec_query
(query, flags=48L, ctx=None)[source]¶ Execute a WQL query with custom flags and returns a :
WmiEnumeration
that can be used to iter the result with timeoutsReturns: WmiEnumeration
-
get_object
(path)[source]¶ Return the object matching
path
. Ifpath
is a class name return the class object``Returns: WmiObject
-
put_instance
(instance, flags=tag_WBEM_CHANGE_FLAG_TYPE.WBEM_FLAG_CREATE_ONLY(0x2L))[source]¶ Creates or updates an instance of an existing class in the namespace
Returns: WmiCallResult
(string)
- Used to retrieve the string representing the path of the object created/updated
-
query
(query)[source]¶ Return the list of
WmiObject
matchingquery
.This API is the simple one, if you need timeout or complexe feature see
exec_query()
Returns: [ WmiObject
] - A list ofWmiObject
-
select
(clsname, deep=True)[source]¶ Return the list of
WmiObject
that are instance ofclsname
. Deep has the same meaning as increate_instance_enum()
.This API is the simple one, if you need timeout or complexe feature see
create_instance_enum()
Returns: [ WmiObject
] - A list ofWmiObject
-
value
¶ current value
-
2.10.3. WmiObject¶
-
class
windows.winobject.wmi.
WmiObject
[source]¶ Bases:
windows.generated_def.interfaces.IWbemClassObject
,windows.winobject.wmi.WmiComInterface
The WmiObject (which wrap
IWbemClassObject
) contains and manipulates both class definitions and class object instances. Can be used as a mapping to access properties.-
__getitem__
(name)¶ Return the value of the property
name
. The return value depends of the type of the property and can vary
-
__setitem__
(name, value)¶ Set the property
name
tovalue
-
genus
¶ The genus of the object.
Returns: WBEM_GENUS_CLASS(0x1L)
if theWmiObject
is a Class andWBEM_GENUS_INSTANCE(0x2L)
for instances and events.
-
get
(name)[source]¶ Return the value of the property
name
. The return value depends of the type of the property and can vary
-
get_properties
(system_properties=False)[source]¶ Return the list of properties names available for the current object. If
system_properties
isFalse
property names begining with_
are ignored.Returns: [ str
] – A list of string
-
properties
¶ The properties of the object (exclude system properties)
-
spawn_instance
()[source]¶ Create a new object of the class represented by the current
WmiObject
Returns: WmiObject
-
value
¶ current value
-
2.10.4. WmiCallResult¶
-
class
windows.winobject.wmi.
WmiCallResult
(result_type=None, namespace_name=None)[source]¶ Bases:
windows.generated_def.interfaces.IWbemCallResult
,windows.winobject.wmi.WmiComInterface
The result of a WMI call/query. Real result value type depends of the context
-
get_call_status
(timeout=tag_WBEM_TIMEOUT_TYPE.WBEM_INFINITE(0xffffffffL))[source]¶ The status of the call
-
get_result_object
(timeout=tag_WBEM_TIMEOUT_TYPE.WBEM_INFINITE(0xffffffffL))[source]¶ The result as a
WmiObject
(returned byWmiNamespace.exec_method()
)
-
get_result_service
(timeout=tag_WBEM_TIMEOUT_TYPE.WBEM_INFINITE(0xffffffffL))[source]¶ The result as a
WmiNamespace
(not used yet)
-
get_result_string
(timeout=tag_WBEM_TIMEOUT_TYPE.WBEM_INFINITE(0xffffffffL))[source]¶ The result as a
WmiObject
(returned byWmiNamespace.put_instance()
)
-
result
¶ The result of the correct type based on
self.result_type
-
value
¶ current value
-
2.10.5. WmiEnumeration¶
-
class
windows.winobject.wmi.
WmiEnumeration
[source]¶ Bases:
windows.generated_def.interfaces.IEnumWbemClassObject
,windows.winobject.wmi.WmiComInterface
Represent an enumeration of object that can be itered
-
DEFAULT_TIMEOUT
= tag_WBEM_TIMEOUT_TYPE.WBEM_INFINITE(0xffffffffL)¶ The default timeout
-
all
()[source]¶ Return all elements in the enumeration as a list
Returns: [ WmiObject
] - A list ofWmiObject
-
next
(timeout=None)[source]¶ Return the next object in the enumeration with timeout.
Raises: WindowsError(WBEM_S_TIMEDOUT)
if timeout expireReturns: WmiObject
-
value
¶ current value
-


{% extends 'base.html'%} {% block content %}
What 8 letter word can have a letter taken away and it still makes a word. Take another letter away and it still makes a word. Keep on doing that until you have one letter left. What is the word?
Upvote {{isUp}}No Idea Is So Outlandish That It Should Not Be Considered With A Searching But At The Same Time A Steady Eye.
Upvote {{isUp}}The harder you work for something, the greater you’ll feel when you achieve it.
Upvote {{isUp}}If two wrongs don't make a right, try three.
Upvote {{isUp}}Our prayers are sometimes answered without us realizing.
Upvote {{isUp}}You know you're in love when you can't fall asleep because reality is finally better than your dreams.
Upvote {{isUp}}


I remember buying the shrooms from my dealer and as I was leaving he said 'be careful man, 1 gram of this is like 3 grams liberty' I thought yeah right and resolved to take all 4.5 grams as the sun came up over my farm.
Anyway a little back-story, a couple months ago I was diagnosed with atypical bipolar, it was hell, I wouldn't sleep for 4 days at a time and as a result I would get all sorts of messed up paranoid hallucinations, no fun. Anyways, ever since I'd been taking 5 mg of Risperidone a day and they had disappeared, but I digress. The next day at 4:30 a.m. I and a friend got together, I took the shrooms and he dropped about 3 hits of acid. I knew I was in for a royal asskicking when I was having full blown visuals within 15-20 minutes, I mean hieroglyphics in the sky, pissing blue, the whole spiel.
I saw beautiful alien landscapes where the inhabitants lived in a harmonious perpetual dance of life and death. One of the aliens came over to me and took my risperidone dumping it on the ground where the hundreds of pills turned into spiders and scurried away. The whole time I was experiencing full blown auditory hallucinations and was covered in sweat, not exactly pleasant. I struggled through the experience, rolling with the hits and letting my ego be shattered over and over again.
When I was finally coherent after about 3.5 hours I awoke completely calm, I had never felt so at peace, I resolved to stop taking my meds and have been off them for 2.5 months with absolutely no relapse, mushrooms truly are mystical beings. Oh yeah, the next week I found out from a good friend that those had been legitimate flying saucers, which explained the intensity. I had done several Ayahuasca trips prior and they didn't hold a candle to this. It certainly helped me.
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.


I have spent the last 2 months using FreeBSD - a true Unix ecosystem. However, bit by bit I felt that its system management practices are simply too archaic for me. I also realized that using heavy components (Eclipse, desktop environments, etc.) can bloat even something as lightweight as FreeBSD. Not to mention the many weekend world and kernel rebuilding sessions (I know, I should have been running a regular release, not a development snapshot). Those 2 months made me realize where FreeBSD really shines – on servers and workstations (where X11 is somewhat redundant or a minimal windowing session is sufficient). Sadly, it does not seem I am serious enough for FreeBSD yet. Therefore, I made a 180-degree turn and returned to Fedora Linux. However, with a different attitude altogether.
I am finally beginning to appreciate the many improvements and utilities the Fedora community is working on and actively promoting. Of course, my stance on systemd,
GNOME3 and the likes remains unchanged, however since I'm not forced to interact with them directly, I don't mind Fedora shipping them. FreeBSD taught me a different,
more focused approach to computing. Hating brings about only negative emotions and nothing more. It is utterly unproductive. Frankly, I DO like some of GNOME3's
features, like gnome-sushi
which allows the user to briefly visit file content without physically opening the file (be it an image, video, document,
etc.). MacOS X has a similar feature and it is extremely useful! I am actually planning on testing Fedora on my laptop as well!
Some of Fedora's features make it an attractive choice as the main OS:
To sum up, Fedora's goals and policies are noble and honest. I finally understood I cannot blame Fedora for Red Hat’s approach to the Linux ecosystem. Recent outcries of the Fedora community made me realize that. It is clear that no Linux distribution wants to act as a lab rat. Therefore, I will do my best to enjoy Linux and improve my attitude!


compute Computes the descriptors for a set of keypoints detected in an image or image set.
[descriptors, keypoints] = obj.compute(img, keypoints)
[descriptors, keypoints] = obj.compute(imgs, keypoints)
Input
- img Image (first variant), 8-bit grayscale image.
- imgs Image set (second variant), cell array of images.
- keypoints Input collection of keypoints. Keypoints for
which a descriptor cannot be computed are removed.
Sometimes new keypoints can be added, for example: cv.SIFT
duplicates keypoint with several dominant orientations
(for each orientation). In the first variant, this is a
struct-array of detected keypoints. In the second variant,
it is a cell-array, where
keypoints{i}
is a set of keypoints
detected in images{i}
(a struct-array like before).
Output
- descriptors Computed descriptors. In the second variant of
the method
descriptors{i}
are descriptors computed for a
keypoints{i}
. Row j
in descriptors
(or
descriptors{i}
) is the descriptor for j
-th keypoint.
- keypoints Optional output with possibly updated keypoints.


30 Days in April: Day 25
I might have already written something about this before, but I'm hoping not.
In the very first week of activities in The Artist's Way, Cameron implores you to take the bad things that you tell yourself about your creativity and turn them into affirmations. It's a simple technique--just writing out, say, "I am a bad writer" if you feel that way and then changing it to "I'm an excellent writer," and so on. This method goes right along with the fact that Cameron sort of frames this process as your "artist's recovery."
Anyway, the weird thing for me was how many of these things came out rather quickly the next time I wrote after reading it. I began bracketing them with <> in my paper journal and then writing the affirming starements right after them.
Now, I've gotta say, a lot of Cameron's recovery language really feels over the top to me, because I feel more like I am cleaning out the cruft than that I am spiritually exorcising demons of self-doubt. But while I think of myself as someone who totally supports people as creators--"Dude, if you're writing, you're a writer, PLUS, you're an artist," that sort of thing-- I'm finding, through this exercise, that, as always, I'm better at supporting others than at taking my own supportive advice.
So I'm working on it. This project has taken up enough of that late night "free time" that I've dropped the daily morning pages and weekly exercises of TAW, to pick them back up in May. But I will keep thinking about (and discovering how much I limit myself, so that hopefully, I'll stop doing it so much.
30 Days in April: Day 24
Today's art brought to you by the letter tired and the number queasy.
I like cameraphone shots also.
30 Days in April: Day 23
Music as
unbelievable
busting bursting at the seams
thirsting catching dreams
I can just write and write and write but I never know if it really is what I really want it to be
Seeming to me like
bad poetry
"It's the process," he used to say with a laugh.
It's the process.
30 Days in April: Day 22
Foot (2009)
Ask five friends to measure their feet.
Pick the person who has a foot closest to twelve inches in length.
Take a photo of that person's foot.
Print the photo to actual size.
Hang it on a wall where you live, with the caption "Standard of Measurement" below it.


Commentary: Here’s what’s wrong with a homework curfew
by June YongNews of the Chinese government imposing a curfew on schoolchildren doing homework suggest disturbing, deep-seated issues which have parallels in Singapore, says mum June Yong.
SINGAPORE: Recent news of the Chinese government considering a 9pm and 10pm homework curfew for primary and secondary schoolchildren respectively has sparked a huge debate about the country’s education system in the country.
Considering the heavy workload that Chinese children have, coupled with endless enrichment activities, it isn’t difficult to see why the Chinese government would feel a need to step in.
READ: Homework curfew for Chinese children sparks heated debate
It may be hard to imagine that such a practice be imposed in Singapore, but one can never rule out the possibility.
Thinking about it worries me, as it does not appear to be focusing on the right problem.
Instead of legislating the time kids should go to bed, should it ever come down to that situation, we should be asking ourselves, how did childhood get so hectic in the first place?
Are children being ferried from class to class, and only able to do their homework after dinner?
Are parents busy making ends meet and only able to coach their kids after hours?
In this context, a homework curfew may be a sledgehammer but does not solve any of the underlying problems when a child has to do homework late into the night.
TACKLE THE PROBLEM OF TOO MUCH HOMEWORK
First, it’s worth tackling the problem of too much homework head on.
Singaporean students aged 15 clocked the third-longest time spent on homework, at 9.4 hours a week, according to an OECD survey conducted in 2012, which is the latest survey on the subject. They are behind students in Shanghai (13.8 hours) and Russia (9.7 hours).
Is the homework load in Singapore that unmanageable? Not really.
My Primary Four daughter occasionally gets a heavy workload which may take her two hours to complete but this thankfully occurs only once or twice a month. Most days, she’s in bed by 8.30pm.
In this, educators play a key role. In my daughter’s school, teachers try to coordinate homework load to avoid overloading on any given day.
This helps ensure that homework does not morph into a mountain that students have to chip away at. (That is, unless the various tuition classes are adding to the load.)
READ: Commentary: Teachers love their jobs and feel valued but face immense challenges
READ: Commentary: Should parents help their kids with homework?
Second, instead of imposing a curfew, parents should refrain from packing their kids schedules.
We made a conscious choice to keep tuition for our daughter to a minimum (1.5 hours a week), and reserve her weekday afternoons for schoolwork, revision and free play. She also goes for violin and art lessons, interests she chose for herself.
Even then although she seems to have a balanced schedule, we still pick up heightened stress signals over weekends when she has a test looming or Chinese spelling to prepare for.
So even what a parent thinks is a sensible lifestyle may not be one for a child.
There is no hard-and-fast rules that can be applied to every child. A high ability and energetic child may crave greater levels of intellectual stimulation or physical activity.
For a parent to know when it is too much, we must tune in to the child’s emotions, and provide a safe space for them to voice out.

Do they have sensible work habits? Or do they count on parents to nag at them before opening up assignments?
Parents know two children of equal ability can achieve very different test scores because of work habits.
One may procrastinate and distract himself with gadgets and other less urgent tasks, while the other is organised and has advanced planning skills so he knows exactly what needs to get done when.
So do we instill in our children that homework is their responsibility, and that how long they take to complete tasks is something they must be aware of and plan accordingly?
Or do we allow them to abdicate accountability and carry the weight of the homework responsibility ourselves as parents?
Little do we know that the more we worry, the less the child is bothered. But if we spend the first two years of formal education instilling good work habits in our children, the chances of homework battles will be markedly reduced.
A better solution is to establish a homework routine, and use visual cues to remind the child, for example, a homework chart placed above the study desk they can tick off daily.
After homework is completed, the child gets to choose their next preferred activity, be it reading a book or playing with his mates.
READ: Commentary: Thanks mum for not being a helicopter parent
READ: Commentary: Streaming out. Subject-based banding in. How are parents reacting?
If your child is struggling with some hard concepts, try asking how they want to receive help. Maybe a few sessions with his teacher would suffice, or he could message a friend.
Where both parents work late, try finding other options for homework help, such as a reliable student care, a nearby tuition centre that offers a space for students to study outside classroom hours or even a trusted neighbour.
READ: Commentary: The dangers of leaving our kids with a childcare centre or babysitter – how real are the risks?
WHAT A DISCIPLINED LIFE REALLY LOOKS LIKE
Fourth, some parents have argued kids need to keep up their academic rigour and stay ahead of the competition, so they put in the hours.

But arguably, such discipline should also apply to other areas of life. A child needs a balanced life, which includes nutrition, work, rest, and play to be at his best.
If they prefer downtime in the afternoons and can cope with homework later, this could be their optimal rhythm.
But if bedtime gets pushed to the point where the child cannot concentrate the next day, it may create a vicious cycle where schoolwork gets harder when the child isn’t able to absorb during lessons.
SHOOT FOR BALANCE
The pressure to achieve in this modern age is ever-constant, but so is the need to reflect and change.
We all want our kids to succeed, but the science is telling us that we’ve been focusing on the wrong things.
As guardians of our children’s well-being, we need to switch gears to avoid raising a generation of burnt out youths. Instead of aiming for achievement, we should aim for balance, agency and self-discipline. The achievement will follow.
We must not get into a situation where we have to resort to curfews.
June Yong is a mother of three, an educational therapist and owner of Mama Wear Papa Shirt , a blog that discusses parenting and education in Singapore.


Gecode::MiniModel::Matrix< A > Class Template Reference
[Matrix interface for arrays]
#include <minimodel.hh>
Detailed Description
template<class A>
class Gecode::MiniModel::Matrix< A >
Matrix-interface for arrays.
This class allows for wrapping some array and accessing it as a matrix.
- Note:
- This is a light-weight wrapper, and is not intended for storing variables directly instead of in an array.
Definition at line 837 of file minimodel.hh.
Public Types | |
| typedef ArrayTraits< A >::value_type | value_type |
| The type of elements of this array. | |
| typedef ArrayTraits< A >::args_type | args_type |
| The type of the Args-array type for value_type values. | |
Public Member Functions | |
| Matrix (A a, unsigned int w, unsigned int h) | |
| Basic constructor. | |
| Matrix (A a, unsigned int n) | |
| Basic constructor. | |
| unsigned int | width (void) const |
| Return the width of the matrix. | |
| unsigned int | height (void) const |
| Return the height of the matrix. | |
| args_type const | get_array (void) |
| Return an Args-array of the contents of the matrix. | |
| value_type & | operator() (unsigned int c, unsigned int r) |
| Access element (c, r) of the matrix. | |
| Slice | slice (unsigned int fc, unsigned int tc, unsigned int fr, unsigned int tr) |
| Access slice of the matrix. | |
| args_type | row (int r) |
| Access row r. | |
| args_type | col (int c) |
| Access column c. | |
Classes | |
| class | Slice |
| A slice of a matrix. More... |
Member Typedef Documentation
|
|
The type of elements of this array.
Definition at line 840 of file minimodel.hh. |
|
|
The type of the Args-array type for value_type values.
Definition at line 842 of file minimodel.hh. |
Constructor & Destructor Documentation
|
|
Basic constructor. Constructs a Matrix from the array a, using w and h as the width and height of the matrix. The elements in the wrapped array a are accessed in row-major order.
Definition at line 62 of file matrix.icc. |
|
|
Basic constructor. Constructs a square Matrix from the array a, using n as the length of the sides. The elements in the wrapped array a are accessed in row-major order.
Definition at line 70 of file matrix.icc. |
Member Function Documentation
|
|
Return the width of the matrix.
Definition at line 78 of file matrix.icc. |
|
|
Return the height of the matrix.
Definition at line 81 of file matrix.icc. |
|
|
Return an Args-array of the contents of the matrix.
Definition at line 84 of file matrix.icc. |
|
|
Access element (c, r) of the matrix.
Definition at line 90 of file matrix.icc. |
|
|
Access slice of the matrix. This function allows accessing a slice of the matrix, located at columns and rows . The result of this function is an object that can be converted into either a Matrix<args_type> or into args_type. For further information, see Slice. Definition at line 99 of file matrix.icc. |
|
|
Access row r.
Definition at line 106 of file matrix.icc. |
|
|
Access column c.
Definition at line 112 of file matrix.icc. |
The documentation for this class was generated from the following files:
- gecode/minimodel.hh (Revision: 3579)
- gecode/minimodel/matrix.icc (Revision: 3513)


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| Philosophical: | why is it a revolutionary idea |
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Registration for the July 2021 virtual DESC Meeting
Monday - Friday, July 19 - July 23, 2021
There is no registration fee for this meeting.
Please join the LSSTC Slack channel #desc-collab-meeting to keep updated on chats, discussions, and announcements during the meeting.
You can find the the details of the schedule on this confluence page.
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Guillaume Calmettes
Statistical significance
Would the observed result be surprising if the
observed phenomenon
was only governed by random chance?
Hypothesis testing for one proportion
How likely would we observe such an extreme
proportion of successes under the null hypothesis (=random chance)?
Based on these data, can we say that the UCLA Bruins are better than the USC Trojans at Basketball?
What are the observational units?
Each UCLA-USC basketball game
What is the variable measured?
Is it Categorical or Quantitative?
Whether or not UCLA won the game (categorical)
We are interested in investigating whether the UCLA Bruins are better
than the USC Trojans at
basketball, and we think they are.
Alternative hypothesis:When they are playing against
the Trojans, the Bruins are more likely to win a game
($\pi>0.5$).
What is the null hypothesis in this investigation?
UCLA and USC are equally likely to win a game ($\pi=0.5$).
The recorded proportion of victories of the Bruins over the 249 games
could be explained by chance alone.
We know that the Bruins won 140 out of 249 games against USC.
What is the observed statistic?:
Proportion of UCLA wins:
$\overset{\hat{}}{p}=\frac{140}{249}=0.562$
If UCLA and USC were equally likely to win a game, would it be surprising to observe $\overset{\hat{}}{p}\geq0.562$ for UCLA over 249 games?
We can use simulations to investigate whether this provides us with strong enough evidence against the null and if the proportion of victories of the Bruins over the Trojans is statistically significant.
Single simulation?
249 random drawings of 0 or 1
Statistic of interest?
proportion of 1 (win) in the sample
Number of simulations?
10000
We know that the Bruins won 140 out of 249 games against USC.
What is the observed statistic?:
Proportion of UCLA wins:
$\overset{\hat{}}{p}=\frac{140}{249}=0.562$
If UCLA and USC were equally likely to win a game, would it be surprising to observe $\overset{\hat{}}{p}\geq0.562$ for UCLA over 249 games?
10000 simulations
of 249 game outcomes
(win, $\pi=0.5$)
| Simulation # | Random sample ($n=249$) | sample $\overset{\hat{}}{p}$ | |||||||
|---|---|---|---|---|---|---|---|---|---|
| 1 | 1 | 0 | 0 | ... | 1 | 0 | 0 | 1 | 0.504 |
| 2 | 0 | 0 | 0 | ... | 0 | 1 | 0 | 0 | 0.531 |
| 3 | 1 | 1 | 0 | ... | 0 | 1 | 1 | 1 | 0.486 |
| ... | ... | ... | |||||||
| 9999 | 0 | 1 | 1 | ... | 0 | 0 | 0 | 1 | 0.497 |
| 10000 | 0 | 1 | 1 | ... | 0 | 1 | 1 | 0 | 0.519 |
Where is it centered?
$\pi=0.5$
(null hypothesis)
What do we need to count?
How many simulations have $\overset{\hat{}}{p}\geq0.562$
Out of the 10000 simulations, 272
resulted in $\overset{\hat{}}{p}\geq0.562$
$\textrm{p-value}=\frac{272}{10000}=0.00272$
=> We have strong evidence against the chance model
So far we've looked at a measure of the strength of evidence (p-value). However, we've not yet formally looked at what factors impact the strength of evidence.
In other words, why is the strength of evidence (measured by p-value) sometimes strong and sometimes weak or non-existant?
Difference between the observed statistic and the null hypothesis parameter value ($\overset{\hat{}}{p}-\pi_0$)
What if instead of 140 wins out of the 249 games, UCLA had won 155 games of those games? Or what if they only had won 135 of those games?
How would the number of UCLA wins in the sample impact our strength of evidence against the null?
=> Intuitively, the more extreme the observed statistic, the more evidence there is against the null hypothesis.
If UCLA had won 155 games that is a success rate of
$\overset{\hat{}}{p}=\frac{155}{249}=0.622$
$0$ simulations
(p-value < 0.0001)
If UCLA had only won 135 games that is a success rate of
$\overset{\hat{}}{p}=\frac{135}{249}=0.542$
$10005$ simulations
(p-value = 0.1)
The further away the observed statistic is from the mean of the null distribution, the more evidence there is against the null hypothesis.
So far we've looked at a measure of the strength of evidence (p-value). However, we've not yet formally looked at what factors impact the strength of evidence.
In other words, why is the strength of evidence (measured by p-value) sometimes strong and sometimes weak or non-existant?
Difference between the observed statistic and the null hypothesis parameter value ($\overset{\hat{}}{p}-\pi_0$)
Sample size
What if the relative proportion of basketball wins of UCLA over USC (0.562) was the result of 124 games instead of 249? Or what if it was obtained from 498 games (twice as many)?
How would the sample size, for the same observed statistic, impact the strength of evidence against the null?
Do you think that increasing the sample size would:
=> Intuitively, it seems reasonable to think that as we increase the sample size, the strength of evidence against the null hypothesis will increase. If the same proportion of UCLA wins had been observed over more games, we would have more knowledge about the truth.
Effect of changing the sample size (number of UCLA-USC games played)
on the null distribution.
The greater the sample size, the less variability in the sample
statistic
sample size decreased to 124 ($\simeq$ half as many)
original observation
sample size 249
sample size increased to 498 (twice as many)
As the sample size increases (and the value of the observed statistic stays the same), the strength of evidence against the null hypothesis increases.
The bigger the sample size, the more reliable ("trustable") the observed statistic will be (less variability in the sample statistic from sample to sample)
If you are trying to pass a true/false test (let's say 60% or higher) but know NOTHING about what is going to be on the test, would you rather have more questions or fewer questions on the test?
As the sample size changes, the observed statistic will likely change as well
Importantly, we can't automatically assume that if we collect more data and have a bigger sample size the strength of evidence will increase (smaller p-value), because if we collect more data, our observed statistic will almost always change as well.
If UCLA and USC are playing more games, the proportion of wins by UCLA won't be exactly 0.562 forever.
So far we've looked at a measure of the strength of evidence (p-value). However, we've not yet formally looked at what factors impact the strength of evidence.
In other words, why is the strength of evidence (measured by p-value) sometimes strong and sometimes weak or non-existant?
Difference between the observed statistic and the null hypothesis parameter value ($\overset{\hat{}}{p}-\pi_0$)
Sample size
Whether we do a one- or two-sided test
What if we were wrong and instead of UCLA being better than USC at basketball, it was USC that was better?
Currently, as we've stated our null and alternative hypotheses
we haven't allowed for this possibility:
$\pi=0.5$
$\pi>0.5$
$\pi<0.5$
for UCLA
This type of alternative hypothesis is called "one-sided" because it only looks at one of the two possible ways that the null hypothesis could be wrong.
If we only consider the possibility that UCLA can win, this way of formulating our altenative hypothesis could be considered too narrow and too biased towards assuming that we are correct ahead of time.
A more objective approach would be to conduct a "two-sided" test, which allow all the possibility of the null hypothesis to be wrong.
In this case our hypothesis would be:
$\pi=0.5$
$\pi\neq0.5$
We create the randomization distribution
by assuming the null hypothesis is true.
The alternative hypothesis does not play any role in this process
as the randomization samples depend only on the null hypothesis.
However, the alternative hypothesis is important
in determining the p-value because it determines
which tail(s) to use to calculate the p-value.
If the alternative hypothesis specifies a particular direction, we refer to these as right-tailed or left-tailed tests, depending on whether the alternative hypothesis is greater than or less than, respectively.
Otherwise, we are only looking to see if there is a difference without specifying in advance in which direction it might lie. These are called two-tailed tests.
The definition of “more extreme” to compute a p-value depends on whether the alternative hypothesis yields a test that is right-, left-, or two-tailed.
Because the p-value for a two-sided test
is about twice as large
as that for a one-sided test, two-sided tests provide less evidence against
the null hypothesis.
However, note that two-sided tests are used more often in
scientific practice.
1) Lots of factors can influence the p-value
Difference between the observed statistic and the null hypothesis parameter value ($\overset{\hat{}}{p}-\pi_0$)
Sample size
Whether we do a one- or two-sided test
2) The p-value does not give information about how much different from the null our observed statistics is
A small p-value provides evidence against the null hypothesis (strength of evidence), but does not tell anything about the true value of the population parameter from which we obtained our sample
Statistical inference is the process of using data from a sample to gain information about the population.
What we really want to know, is how close to the true population parameter
the statistic we calculated from the sample is.
We want to know about the population parameter, not the sample statistic.
If we had strong evidence that the probability of UCLA to win a game against USC was larger than 0.5, what we would really want to know would be "how much larger than 0.5?", not just "is it different from 0.5?"
In our case, we did not find strong evidence that UCLA was more
likely than USC to win a game (two-tailed p-value >0.05).
But at least it would be interesting to know about
the true probability
for UCLA to win a game against USC.
In other words, if UCLA and USC
were to play an infinite number of basketball games,
what parameter $\pi$ would we observe on the long-run?
How could we get an idea about the true value of the probability of UCLA to win a game against USC?
We know how to test our statistic against a specific parameter value for our null hypothesis (0.5).
What if we were testing against a different null-hypothesis parameter value? Or over a full range of null hypothesis parameters?
| $\overset{\hat{}}{p}$ | 0.562 | ||||||
| $\pi_0$ | 0.48 | 0.5 | 0.55 | 0.58 | 0.6 | 0.62 | 0.65 |
| $\overset{\hat{}}{p}$ | 0.562 | ||||||
| $\pi_0$ | 0.48 | 0.5 | 0.55 | 0.58 | 0.6 | 0.62 | 0.65 |
| Simulation # | Random sample ($n=249$) | sample $\overset{\hat{}}{p}$ | |||||||
|---|---|---|---|---|---|---|---|---|---|
| 1 | 0 | 1 | 0 | ... | 1 | 0 | 0 | 1 | 0.476 |
| 2 | 1 | 1 | 1 | ... | 0 | 1 | 1 | 0 | 0.498 |
| 3 | 1 | 1 | 0 | ... | 0 | 1 | 1 | 1 | 0.482 |
| ... | ... | ... | |||||||
| 9999 | 0 | 1 | 0 | ... | 0 | 1 | 0 | 1 | 0.481 |
| 10000 | 0 | 1 | 0 | ... | 0 | 1 | 1 | 0 | 0.509 |
| Simulation # | Random sample ($n=249$) | sample $\overset{\hat{}}{p}$ | |||||||
|---|---|---|---|---|---|---|---|---|---|
| 1 | 1 | 0 | 1 | ... | 1 | 0 | 1 | 1 | 0.649 |
| 2 | 0 | 1 | 1 | ... | 0 | 1 | 0 | 0 | 0.682 |
| 3 | 1 | 1 | 1 | ... | 0 | 0 | 0 | 1 | 0.628 |
| ... | ... | ... | |||||||
| 9999 | 0 | 0 | 1 | ... | 0 | 0 | 1 | 1 | 0.617 |
| 10000 | 1 | 1 | 1 | ... | 0 | 1 | 1 | 0 | 0.696 |
| $\overset{\hat{}}{p}$ | 0.562 | ||||||
| $\pi_0$ | 0.48 | 0.5 | 0.55 | 0.58 | 0.6 | 0.62 | 0.65 |
Our observed statistic
would be plausible if our sample had been drawn from
population distributions with parameter $\pi$
ranging at least from $0.5$ to $0.62$
=> null hypothesis not rejected
at the two-tailed 0.05 level.
The long-run probability $\pi$ for UCLA to win a game against USC is in this range estimate.
Key idea:
This interval of plausible values we just
obtained is called a
95% confidence interval for $\pi$, the
long-run probability for UCLA to win a game against USC. The 95% value
is called the confidence level, and is a
measure of how confident we are about our interval containing the
true population parameter.
Note:
We can also actually use the 95%
confidence interval as a
measure of the strength of evidence!
=> if the parameter of the
null distribution is in the interval, then we cannot
reject the null hypothesis (we cannot reject that $\pi=\pi_0$)
Right now, we only have a rough idea of the boundaries of the 95% confidence interval (we only tested a limited quantity of plausible values).
The bootstrap is
a resampling method that uses only the data in the original sample
(the only data we know about).
It can be used for estimating the variability
of a statistic and to approximate
a sampling distribution using just the
information in that one sample.
Think about it:
The sample is the only information we know to be true about
the population it has been drawn from.
=> The best estimate for a population parameter ($\pi$) is the relevant sample
statistic ($\overset{\hat{}}{p}$).
=> We can expand this idea and consider the sample as our best
estimate for the underlying population.
Ideally, we’d like to sample repeatedly from the population to create a sampling distribution
=> reapeatedly randomly draw 249 other
UCLA-USC games from the population and
calculate another value for our statistic
How can we make the sample data look like data from the entire population?
We assume that the population of all the UCLA-USC basketball games is basically just many, many copies of the games in our original sample (n=249).
In practice, instead of actually making many copies of the sample and
sampling from that, we use a sampling technique that is equivalent:
=> we sample with replacement from the original sample.
Once a UCLA-USC game has been selected from the sample,
it is still available to be selected again.
=> Each UCLA-USC game in the original sample actually represents
many other games with a similar outcome (win or loss).
Each sample selected in this way, with replacement from the original
sample, is called a bootstrap sample.
Note: Recall that the variability of a sample statistic depends on the size of the sample. Because we are trying to uncover the variability of the sample statistic, it is important that each bootstrap sample is the same size as the original sample (n=249).
data sample (n=249)
$140$ ones & $109$ zeros
$P(1)=0.562$
$P(0)=0.438$
| 1 | 1 | 0 | 0 | 0 | 1 | ... | 1 | 0 | 1 | 1 | 0 | 1 |
$\overset{\hat{}}{p}=0.562$
Now that we have our Bootstrap sampling distribution, we can compute the confidence intervals at the 95% level.
Where is it centered?
centered at $\overset{\hat{}}{p}$
(original observed statistic)
How do we compute the 95% confidence intervals or our population parameter?
We consider the central 95% of the bootstrap statistics
(discard the 2.5% more extreme cases on each side)
We are 95% confident that the true probability of the Bruins to win a game against the Trojans (parameter $\pi$) is lying in the interval $[0.498-0.622]$
A bootstrap confidence interval at the alpha level, is computed by considering the central (1-alpha) bootstrap statistics of the bootstrap sampling distribution we constructed.
In the sorted array of bootstrap statistics, this corresponds to the statistics at positions:
If we were were able to get an unlimited number of original samples from the population of UCLA-USC basketball games, and were computing the $alpha$-% confidence interval from each of them, the true probability of UCLA winning a game against USC would be in $alpha$-% of these calculated intervals.
Confidence intervals provide information about both:
- strength of evidence
(Is the parameter value we want to test against,
in the interval or not? => 95% confidence interval)
- estimate of the true
parameter value
($alpha$-% of the time our interval will include our true parameter)
In that sense, reporting the $alpha$-% confidence intervals is better than just reporting a p-value, since what we really want to know is the true value of our population parameter, not just if our true parameter is different or not from a particular value.
Bootstrap regression analysis


|
Hermanos Enemigos (Brothers/enemies)
Hermanos Enemigos (Brothers/enemies) is a serie by Atelier Morales that addresses the themes of greed, violence, hate and envy between
brothers.
It stretches from the family privacy to wars and massacres between peoples.
Examples are as old as the story of Cain and Abel and as actual as the ever going conflicts
between Israel and Palestine; Fatha and Hamas in Gaza, Catholics and Protestants in Northern Ireland; Cubans in Miami and Havana; Basque separatists and Spaniards;
Uigures and the Han in Xinjiang; Tutsis and Hutus in Ruanda; Sindis and Sijs in India, Serbian and Albanians in Kosovo, pachtounes and mujahidin’s in Afghanistan;
radical and moderates pro-Islamic in Algeria among many others.
With each image there is a myth that has been updated by the artists, Juan Luis Morales and Teresa Ayuso, who conform the duo Atelier Morales.
Hermanos Enemigos (Brothers/enemies) is a very touching and humane work of investigation and art, based on moral and history. It makes us reflect upon our values an actions from ancient to contemporary time, as well as consider that evil exists because goodness and righteousness exist as well. The Atelier Morales images, based on legends and myths, are poetic, beautiful and dramatic.
Text by Atelier Morales in collaboration with Nina Menocal
|


|
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|
Skills
|
I here by declare that, the information given above is correct to best of my knowledge.
|
Date: ___________
Place: __________
|
(Signature){{preview.basicInfo.firstName | uppercase}} {{preview.basicInfo.lastName | uppercase}} |


The callback interprets the result of got.
The returned value of the callback will be used to trigger
further crawls. The current CrawlOptions object will be
merged with the returned value. See the examples
or the function which converts callback results to an array of crawlOptions
to understand the merging mechanism.
The callback interprets the result of got. The returned value of the callback will be used to trigger further crawls. The current CrawlOptions object will be merged with the returned value. See the examples or the function which converts callback results to an array of crawlOptions to understand the merging mechanism.


My name is Philip Wawazi and I am a Software Developer that specializes in fullstack development.
Some of the languages that I am fluent in include JavaScript, Python, PHP and C#. As for the frameworks that I am quite familiar with in include Laravel, Symphony, Vue, React, Flask, Django and ASP.NET Core
You can contact me at the email and phone number below


SGF_STD EMail List
An email list has been set up for discussion of the standard.
EMail list<EMAIL_ADDRESS>There's an archive of the email list.
Click to subscribe to sgf-std
Or send an email to<EMAIL_ADDRESS>Who should join the list?
- programmers of applications dealing with SGF files
- people maintaining large (public) archives of SGF files
- anyone interested in creating the new standard
What is the list about?
The list is for discussing the new SGF standard and implementation
issues.
Thus one should have extensive experience with the current SGF standard.
This list is NOT for answering newbie questions or
answering questions about single applications.


K Clustering
Problem
We have set of objects $U = \{o_1, o_2, …\}$, and we want to split them into k clusters.
We also have following definition for distance function.
- $\forall_{i,j} dist(p_i, p_j) = dist(p_j, p_j)$
- $\forall_{i,j} dist(p_i, p_i) = 0$
- $\forall_{i,j} dist(p_i, p_j) > 0$.
At the end, we should have $C = \{C_1, C_2, … C_K\}$.
Let’s define spacing to be the minimum dist between clusters. Our goal is to find the k-clustering with maximum spacing.
Algorithm
Kruskal’s Algorithm
- Sort the edges using dist as edge weight
- In each iteration, pick the min edge that doesn’t form cycle
- The connected component = cluster
- Connecting (merge) two clusters with new edge = single-link clustering
- Stops when we have k components
- equivalent of stop before adding last k - 1 edges for Kruskal’s Algorithm
Below is picture of single-linked clusters with k = 3.
Analyzing Algorithm
Claim: The components $C_1, C_2, …, C_k$ formed by deleting the k − 1 most expensive edges of the minimum spanning tree T constitute a k-clustering of maximum spacing.
Proof:
- $\mathbb{C} = \{C_1, C_2, …, C_k\}$
- $d^{*} = (k - 1)$ most expensive edge (since algorithm stops here)
- Assume there is $\mathbb{C’} = \{C’_1, C’_2, …, C’_k\}$
- $\exists C_r$ that contains $p_i$ and $p_j$
- S.T. $C_r \subsetneq C’_s$ and $C_r\subsetneq C’_t$
- $p_i \in C’_s$, $p_j \in C’_t$ and $s \neq t$
- Since $p_i$ and $p_j \in C_r$, there is path between them
- On Kruskal’s algorithm, all these edges in the path are at most d*
- Assume $p \in C’s$ and $p’ \in C’t$ that were connected before
- p - p’ was one of the edges, $d(p, p’) \leq d*$
- Spacing $\mathbb{C’} \leq d*$


Introduction
This documentation aims to provide all the information you need to work with our API.
API para controlar las ordenes de compra de clientes recurrentes. La API permite crear eventos en el calendario de Google para guardar recordatorios, próximas entregas y todo lo que necesites para dar a tus clientes la mejor atención.
Base URL
http://apirest.boxcode.com.mx
Authenticating requests
This API is not authenticated.
Endpoints
Create User.
Example request:
curl -X POST \
"http://apirest.boxcode.com.mx/api/createuser" \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-d '{"name":"Michelle Marquez","email":"michelle_m@gmail.com","password":"admin123","type":"A"}'
Example response:
{
"message": "Success",
"data": {
"name": "Michelle Marquez",
"email"<EMAIL_ADDRESS>"type": "A",
"id": 4
},
"token": "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpc3MiOiJodHRwOlwvXC8xMjcuMC4wLjE6ODAwMFwvYXBpXC9jcmVhdGV1c2VyIiwiaWF0IjoxNjE3OTI2MzYwLCJleHAiOjE2MTc5Mjk5NjAsIm5iZiI6MTYxNzkyNjM2MSwianRpIjoiQlZEUTVabDFCNVFoajJsZiIsInN1YiI6NCwicHJ2IjoiMjNiZDVjODk0OWY2MDBhZGIzOWU3MDFjNDAwODcyZGI3YTU5NzZmNyJ9.zGFLotKWjEFsiV4TgPzv1h4jzDUfGTf6zS7K1Ks57Zk"
}
Received response:
Request failed with error:
Authenticate.

Example request:
curl -X GET \
-G "http://apirest.boxcode.com.mx/api/getevents" \
-H "Content-Type: application/json" \
-H "Accept: application/json"
Example response:
[
{
"googleEvent": {
"anyoneCanAddSelf": null,
"attendeesOmitted": null,
"colorId": null,
"created": "2021-04-09T00:28:22.000Z",
"description": null,
"endTimeUnspecified": null,
"etag": "\"3235856205850000\"",
"eventType": "default",
"guestsCanInviteOthers": null,
"guestsCanModify": null,
"guestsCanSeeOtherGuests": null,
"hangoutLink": null,
"htmlLink": "https://www.google.com/calendar/event?eid=Ymw5Y3FuYTJmbTJ1a2c3MzhrNTEzZ3RnZTQgYzh0ZzZjdW8xbjc1bzFkMGY5MTVkdjNjdTRAZw",
"iCalUID"<EMAIL_ADDRESS>"id": "bl9cqna2fm2ukg738k513gtge4",
"kind": "calendar#event",
"location": null,
"locked": null,
"privateCopy": null,
"recurrence": null,
"recurringEventId": null,
"sequence": 0,
"status": "confirmed",
"summary": "Nuevo pedido",
"transparency": null,
"updated": "2021-04-09T00:28:22.925Z",
"visibility": null,
"creator": {
"displayName": null,
"email"<EMAIL_ADDRESS>"id": null,
"self": null
},
"organizer": {
"displayName": "Orders",
"email"<EMAIL_ADDRESS>"id": null,
"self": true
},
"start": {
"date": null,
"dateTime": "2021-04-08T19:28:22-05:00",
"timeZone": null
},
"end": {
"date": null,
"dateTime": "2021-04-08T20:28:22-05:00",
"timeZone": null
},
"reminders": {
"useDefault": true
}
}
}
]
Received response:
Request failed with error:
Create Events Calendar.
Example request:
curl -X POST \
"http://apirest.boxcode.com.mx/api/createcalendarevent" \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-d '{"nameEvent":"Nuevo pedido"}'
Example response:
{
"message": "Sucess",
"data": {
"googleEvent": {
"anyoneCanAddSelf": null,
"attendeesOmitted": null,
"colorId": null,
"created": null,
"description": null,
"endTimeUnspecified": null,
"etag": null,
"eventType": null,
"guestsCanInviteOthers": null,
"guestsCanModify": null,
"guestsCanSeeOtherGuests": null,
"hangoutLink": null,
"htmlLink": null,
"iCalUID": null,
"id": null,
"kind": null,
"location": null,
"locked": null,
"privateCopy": null,
"recurrence": null,
"recurringEventId": null,
"sequence": null,
"status": null,
"summary": "Nuevo pedido",
"transparency": null,
"updated": null,
"visibility": null,
"start": {
"date": null,
"dateTime": "2021-04-09T00:28:22+00:00",
"timeZone": {
"timezone_type": 3,
"timezone": "UTC"
}
},
"end": {
"date": null,
"dateTime": "2021-04-09T01:28:22+00:00",
"timeZone": {
"timezone_type": 3,
"timezone": "UTC"
}
}
}
}
}
Received response:
Request failed with error:
Get authenticated User.
Example request:
curl -X POST \
"http://apirest.boxcode.com.mx/api/user" \
-H "Content-Type: application/json" \
-H "Accept: application/json"
Example response:
{
"user": {
"id": 4,
"name": "Michelle Marquez",
"email"<EMAIL_ADDRESS>"email_verified_at": null,
"type": "A",
"created_at": null,
"updated_at": null
}
}
Received response:
Request failed with error:
Show list Users.
Example request:
curl -X GET \
-G "http://apirest.boxcode.com.mx/api/getusers" \
-H "Content-Type: application/json" \
-H "Accept: application/json"
Example response:
{
"message": "Success",
"data": [
{
"id": 2,
"name": "Mario",
"email"<EMAIL_ADDRESS>"email_verified_at": null,
"type": "B",
"created_at": "2021-04-07 23:19:55",
"updated_at": "2021-04-08 00:21:10"
},
{
"id": 4,
"name": "Michelle Marquez",
"email"<EMAIL_ADDRESS>"email_verified_at": null,
"type": "A",
"created_at": null,
"updated_at": null
}
]
}
Received response:
Request failed with error:
Update User.
Example request:
curl -X POST \
"http://apirest.boxcode.com.mx/api/updateuser" \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-d '{"idUser":2,"name":"Mario Alberto","email":"mario_a@gmail.com","type":"B"}'
Example response:
{
"message": "Success",
"data": {
"id": 2,
"name": "Mario Alberto",
"email"<EMAIL_ADDRESS>"email_verified_at": null,
"type": "B",
"created_at": "2021-04-07 23:19:55",
"updated_at": "2021-04-08 00:21:10"
}
}
Received response:
Request failed with error:
Remove User.
Example request:
curl -X POST \
"http://apirest.boxcode.com.mx/api/deleteuser" \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-d '{"idUser":12}'
Example response:
{
"message": "Success"
}
Received response:
Request failed with error:
Create Product.
Example request:
curl -X POST \
"http://apirest.boxcode.com.mx/api/createproduct" \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-d '{"name":"Tenis deportivos","code":"3434332231","price":"1299.70"}'
Example response:
{
"message": "Success",
"data": {
"name": "Tenis deportivos",
"code": "3434332231",
"price": "1299.70",
"id": 3
}
}
Received response:
Request failed with error:
Show list Products.
Example request:
curl -X GET \
-G "http://apirest.boxcode.com.mx/api/getproducts" \
-H "Content-Type: application/json" \
-H "Accept: application/json"
Example response:
{
"message": "Success",
"data": [
{
"id": 1,
"name": "Gorra fly one",
"code": "2354678904",
"price": 599.89,
"created_at": "2021-04-08 04:36:45",
"updated_at": "2021-04-08 04:36:45"
},
{
"id": 3,
"name": "Tenis deportivos",
"code": "3434332231",
"price": 1299.7,
"created_at": null,
"updated_at": null
}
]
}
Received response:
Request failed with error:
Update Product.
Example request:
curl -X POST \
"http://apirest.boxcode.com.mx/api/updateproduct" \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-d '{"idProduct":12,"name":"voluptate","code":"et","price":"sit"}'
Example response:
{
"message": "Success",
"data": {
"id": 1,
"name": "Gorra fly one",
"code": "2354678904",
"price": "499.89",
"created_at": "2021-04-08 04:36:45",
"updated_at": "2021-04-08 04:36:45"
}
}
Received response:
Request failed with error:
Remove Product.
Example request:
curl -X POST \
"http://apirest.boxcode.com.mx/api/deleteproduct" \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-d '{"idProduct":5}'
Example response:
{
"message": "Success"
}
Received response:
Request failed with error:
Create Order.
Example request:
curl -X POST \
"http://apirest.boxcode.com.mx/api/createorder" \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-d '{"idProduct":19}'
Example response:
{
"message": "Success",
"data": {
"idUser": 4,
"idProduct": "1",
"completed": "0",
"date": "2021-04-09",
"id": 4
}
}
Received response:
Request failed with error:
Remove Order.
@bodyParam idOrder integer required ID of order delete
Example request:
curl -X POST \
"http://apirest.boxcode.com.mx/api/deleteorder" \
-H "Content-Type: application/json" \
-H "Accept: application/json"
-d '{"idOrder":4}'
Example response:
{
"message": "Success"
}
Received response:
Request failed with error:
Show list Orders.
Example request:
curl -X GET \
-G "http://apirest.boxcode.com.mx/api/getorders" \
-H "Content-Type: application/json" \
-H "Accept: application/json"
Example response:
{
"message": "Success",
"data": [
{
"idOrder": 1,
"nameProduct": "Gorra fly one",
"completed": "0",
"price": 499.89,
"nameUser": "Michelle Marquez"
},
{
"idOrder": 2,
"nameProduct": "Tenis deportivos",
"completed": "0",
"price": 1299.7,
"nameUser": "Michelle Marquez"
}
]
}
Received response:
Request failed with error:
Update status completed.
Example request:
curl -X POST \
"http://apirest.boxcode.com.mx/api/completedorder" \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-d '{"idOrder":4}'
Example response:
{
"message": "Success"
}
Received response:
Request failed with error:


2 - https://www.football-data.org/
3 - https://www.spotrac.com/epl/afc-bournemouth/payroll/
5 - http://financialfootballnews.com/wolves-fcs-2018-finances-financial-fosun-play/
6 - https://startbootstrap.com/templates/simple-sidebar/
8 - https://www.chartjs.org/samples/latest/charts/combo-bar-line.html
Image 1
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Image 4


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Here's the plan:
On June 26th, small business owners and Internet users from across the country will meet directly with their House members in DC. Face-to-face meetings in the Capitol are one of the most effective ways to influence lawmakers' positions and counter the power of telecom lobbyists. Before the event, you'll receive an info packet with everything you need to know. Then, on the morning of your meetings, our friends at Public Knowledge will host an orientation and share insight on how to be effective in these meetings. Participants will be paired with a guide to show you where to go on Capitol Hill to meet key lawmakers. If you can't make it to DC, join us by getting involved locally.
How to get there:
Travel stipends are available for people who want to come to DC to meet with legislators but need support with a plane or train ticket. Stipends are limited, so apply here. And if you’re driving or looking for a ride, check the carpool forum.
Where to stay:
We recommend booking a hotel or AirBnB as soon as possible. If you can't afford one, let us know. There are a limited number of spots available for those traveling from outside of DC to participate. Again, if you can’t make it to DC, there are important ways to get involved locally.
But how will we win?
On June 11th the FCC’s undemocratic repeal of net neutrality officially kicked in. Going forward, there is nothing legally preventing Internet providers like Comcast from censoring websites, blocking apps and services, and charging users extra fees to access online content. But net neutrality isn’t dead yet—not by a long shot.
On May 16th we pulled off a historic bipartisan victory when the Senate voted to overturn the FCC’s repeal 52-47. Now we need 218 lawmakers in the House of Representatives--including 25 Republicans--to sign a “discharge petition” and to force a vote past leadership to the floor. This is going to be an uphill battle, and the only thing that can save net neutrality is a groundswell of constituents directly pressuring our members of Congress to block the FCC’s repeal.
Sign up!
Join us in Washington, DC to meet directly with
lawmakers on Tuesday, June 26th.


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Allocation of CUDA mapped zero-copy memory.
More...
|
| bool | cudaAllocMapped (void **cpuPtr, void **gpuPtr, size_t size) |
| | Allocate ZeroCopy mapped memory, shared between CUDA and CPU. More...
|
| |
| bool | cudaAllocMapped (void **ptr, size_t size) |
| | Allocate ZeroCopy mapped memory, shared between CUDA and CPU. More...
|
| |
| bool | cudaAllocMapped (void **ptr, size_t width, size_t height, imageFormat format) |
| | Allocate ZeroCopy mapped memory, shared between CUDA and CPU. More...
|
| |
| bool | cudaAllocMapped (void **ptr, const int2 &dims, imageFormat format) |
| | Allocate ZeroCopy mapped memory, shared between CUDA and CPU. More...
|
| |
| template<typename T > |
| bool | cudaAllocMapped (T **ptr, size_t width, size_t height) |
| | Allocate ZeroCopy mapped memory, shared between CUDA and CPU. More...
|
| |
| template<typename T > |
| bool | cudaAllocMapped (T **ptr, const int2 &dims) |
| | Allocate ZeroCopy mapped memory, shared between CUDA and CPU. More...
|
| |
Allocation of CUDA mapped zero-copy memory.
◆ cudaAllocMapped() [1/6]
| bool cudaAllocMapped |
( |
void ** |
cpuPtr, |
|
|
void ** |
gpuPtr, |
|
|
size_t |
size |
|
) |
| |
|
inline |
Allocate ZeroCopy mapped memory, shared between CUDA and CPU.
- Note
- although two pointers are returned, one for CPU and GPU, they both resolve to the same physical memory.
- Parameters
-
| [out] | cpuPtr | Returned CPU pointer to the shared memory. |
| [out] | gpuPtr | Returned GPU pointer to the shared memory. |
| [in] | size | Size (in bytes) of the shared memory to allocate. |
- Returns
true
if the allocation succeeded, false
otherwise.
◆ cudaAllocMapped() [2/6]
| bool cudaAllocMapped |
( |
void ** |
ptr, |
|
|
size_t |
size |
|
) |
| |
|
inline |
Allocate ZeroCopy mapped memory, shared between CUDA and CPU.
- Note
- this overload of cudaAllocMapped returns one pointer, assumes that the CPU and GPU addresses will match (as is the case with any recent CUDA version).
- Parameters
-
| [out] | ptr | Returned pointer to the shared CPU/GPU memory. |
| [in] | size | Size (in bytes) of the shared memory to allocate. |
- Returns
true
if the allocation succeeded, false
otherwise.
◆ cudaAllocMapped() [3/6]
| bool cudaAllocMapped |
( |
void ** |
ptr, |
|
|
size_t |
width, |
|
|
size_t |
height, |
|
|
imageFormat |
format |
|
) |
| |
|
inline |
Allocate ZeroCopy mapped memory, shared between CUDA and CPU.
This overload is for allocating images from an imageFormat type and the image dimensions. The overall size of the allocation will be calculated with the imageFormatSize() function.
- Parameters
-
| [out] | ptr | Returned pointer to the shared CPU/GPU memory. |
| [in] | width | Width (in pixels) to allocate. |
| [in] | height | Height (in pixels) to allocate. |
| [in] | format | Format of the image. |
- Returns
true
if the allocation succeeded, false
otherwise.
◆ cudaAllocMapped() [4/6]
| bool cudaAllocMapped |
( |
void ** |
ptr, |
|
|
const int2 & |
dims, |
|
|
imageFormat |
format |
|
) |
| |
|
inline |
Allocate ZeroCopy mapped memory, shared between CUDA and CPU.
This overload is for allocating images from an imageFormat type and the image dimensions. The overall size of the allocation will be calculated with the imageFormatSize() function.
- Parameters
-
| [out] | ptr | Returned pointer to the shared CPU/GPU memory. |
| [in] | dims | int2 vector where width=dims.x and height=dims.y |
| [in] | format | Format of the image. |
- Returns
true
if the allocation succeeded, false
otherwise.
◆ cudaAllocMapped() [5/6]
template<typename T >
| bool cudaAllocMapped |
( |
T ** |
ptr, |
|
|
size_t |
width, |
|
|
size_t |
height |
|
) |
| |
|
inline |
Allocate ZeroCopy mapped memory, shared between CUDA and CPU.
This is a templated version for allocating images from vector types like uchar3, uchar4, float3, float4, ect. The overall size of the allocation will be calculated as width * height * sizeof(T)
.
- Parameters
-
| [out] | ptr | Returned pointer to the shared CPU/GPU memory. |
| [in] | width | Width (in pixels) to allocate. |
| [in] | height | Height (in pixels) to allocate. |
- Returns
true
if the allocation succeeded, false
otherwise.
◆ cudaAllocMapped() [6/6]
template<typename T >
| bool cudaAllocMapped |
( |
T ** |
ptr, |
|
|
const int2 & |
dims |
|
) |
| |
|
inline |
Allocate ZeroCopy mapped memory, shared between CUDA and CPU.
This is a templated version for allocating images from vector types like uchar3, uchar4, float3, float4, ect. The overall size of the allocation will be calculated as dims.x * dims.y * sizeof(T)
.
- Parameters
-
| [out] | ptr | Returned pointer to the shared CPU/GPU memory. |
| [in] | dims | int2 vector where width=dims.x and height=dims.y |
- Returns
true
if the allocation succeeded, false
otherwise.


--- layout: post status: publish published: true title: 'Podcast #22 - 9/12/09' author: display_name: Corey Fineran login: Corey email<EMAIL_ADDRESS>url: '' author_login: Corey author_email<EMAIL_ADDRESS>wordpress_id: 1456 wordpress_url: http://ivyenvy.com/?p=1456 date: '2009-09-12 19:47:57 +0000' date_gmt: '2009-09-13 01:47:57 +0000' categories: - Podcast tags: - Podcast comments: [] ---
Corey, Andy and Kurt try to figure out what went wrong in 2009 and we discuss what role the Cubs are playing in our lives right now.


|
Mackey
V3.1
A C++ library for computing RO(G) graded homology
|
#include <Graph.hpp>
Public Types | |
| typedef graph_t::node_t | node_t |
| Public Types inherited from Dikjstra< graph_t, policy_t > | |
| typedef graph_t::node_t | node_t |
| typedef graph_t::neighborhood_t::const_iterator | edge_iter_t |
Public Member Functions | |
| minimize_length (const graph_t &G) | |
| size_t | path_length (node_t i) const |
| Public Member Functions inherited from Dikjstra< graph_t, policy_t > | |
| bool | operator() (node_t a, node_t b) const |
| void | print_path (std::ostream &os, node_t i) const |
| void | compute_with_root (node_t new_root) |
Friends | |
| class | Dikjstra< graph_t, minimize_length< graph_t > > |
Additional Inherited Members | |
| Public Attributes inherited from Dikjstra< graph_t, policy_t > | |
| std::vector< std::vector< edge_iter_t > > | paths |
| std::vector< node_t > | root_per_path |
| std::vector< size_t > | distance_policy |
| Protected Member Functions inherited from Dikjstra< graph_t, policy_t > | |
| Dikjstra (const graph_t &G) | |
| Protected Attributes inherited from Dikjstra< graph_t, policy_t > | |
| std::vector< std::pair< node_t, edge_iter_t > > | previous |
| node_t | current |
| node_t | root |
| const graph_t & | G |
| typedef graph_t::node_t node_t |
| minimize_length | ( | const graph_t & | G | ) |
| size_t path_length | ( | node_t | i | ) | const |
|
friend |


GIG GUIDE
What's on: Tipperary going out guide
by Niamh DillonDancing
Dancing at the Racket Hall, Roscrea on Saturday, November 23 to Michael English. Doors open at 9pm. Tickets cost €15.
Dancing in The Premier Ballroom Thurles on Sunday night, December 1, to Pat Daly. Dancing is from 8.30pm to 11.30pm with tea served at 10pm. Admission price is €9.
Concert
Now in its 12th record breaking year Christmas Crooners is jam packed with festive favourites including the Christmas hits of Bing Crosby, Nat King Cole and Frank Sinatra. This fantastic cast of West End singers are backed by the superb and talented swing band The Jazz- All-Stars and they perform over 30 well known Christmas hits. Christmas Crooners comes to Nenagh Arts Centre on Saturday, December 7 at 8pm. Tickets €20.
The children of Two Mile Borris NS will host the In Tune for Life Orchestra and the McGrath School of Dance for a Christmas Concert in The Dome on December 19 at 7:30pm. This promises to be a memorable night for our school, local community and wider Thurles area. Following on from their sell out performance with Phil Coulter in July, the In Tune for Life Orchestra will perform a range of Irish traditional music with the children of Two Mile Borris NS joining them for a range of festive hits on the night.
Drama
Lorrha Variety Group present the John B. Keane play ‘Sharon’s Grave’ for three nights, on November 22, 23 and 24 in Lorrha Community Hall. Directed by Phil Quigley, the doors open at 8pm. This year is booking only by phoning<PHONE_NUMBER>. Lines open 6pm to 9pm every evening. Adults €10, students €5.
On November 19 to 23, St. Mary's Choral Society, Clonmel will stage Dick Meany's Christmas pantomime Mother Goose. Evening performances will commence at 7.30pm with a matinée performance on Saturday 23 at 2.30pm. Tickets for evening performances are priced at €15 and €12 for the matinée performance. Family tickets are priced at €50 (four tickets).
Castleiney Drama Group present Pull the Other One in Castleiney Parish Hall on November 22, 23, 24. Tickets available in Nolan’s Shop Castleiney or by calling<PHONE_NUMBER>.
Event
Comedian and actor Pat Shortt is gearing up for a return to his native town of Thurles with a huge night of entertainment, comedy, and music as he pays tribute to the Tipperary senior hurling team on Saturday, December 14. Tickets are €40. Doors open at 7.30pm, with the show at starting at 8pm. More information at www.eventbrite.ie
Christmas
The Cloughjordan Christmas Festival will be launched on Sunday, December 8 with the switching on of the Christmas Lights at 5.30pm by members of the Tipperary hurling team. Proceedings commence at 5pm with a parade led by the local fire brigade followed by the children on their bikes, tractors, go-carts and prams. Prizes for the best turned out entrant in the parade.
Comedy
Street Performance World Champions, unlikely heroes of smash hit RIOT and Britain's Got Talent favourites, Lords of Strut deliver their greatest show to date at Nenagh Arts Centre on Saturday, November 23 at 8pm. Tickets: €8/ family of four costs €28.


Employment
Geneva, Switzerland
- Research into the CUDA-based implementation of physics based garment simulation software.
- Development of a real-time virtual fashion platform, Virtual Try On.
- Maintenance of and support for in-house VR/AR engine VHD++
- Contributing author to several EU and Swiss National research proposals.
- Lab representative in EU funded research projects SERVIVE and 3DLife.
- Member of 3DLife’s Network Steering Board.
- Assistance in the organization of the CGI 2010 conference in Singapore.
Geneva, Switzerland
- Management of all (>1000) research paper submissions from initial submission to publication.
- Assistance in the scheduling of each monthly issue including special issues.
Visiting Researcher at Nanyang Technological University
Singapore
- Assistance during the CGI 2010 conference in Singapore.
- Various demonstrations of VTO technology to academic and commercial visitors.
- Technology exchange with IMI related to the MIRALab’s Virtual Try On technology.


Love learning. Fresh knowledge makes me feel high. These days I'm so into distributed systems and cloud computing worlds!
Love Game of Thrones, staying updated on the latest episode of them.
Love socializing. Especially having a nice dinner with friends is the best!
Seoul, South Korea
Bachelor of Science in Computer Science
March 2012 - February 2017
Pittsburgh, PA, United States
Masters in Information Systems Management
August 2017 - Current
Algorithms and Information Security Lab,
Computer Science,
Ewha Womans University
Master Company,
Seoul, South Korea
SAMSUNG SDS,
Seoul, South Korea
[Certificate]
Won first place in the contest organized by The Korea Federation of Womans Science&Technology Associations.
Won second place in the nationwide application development challenge which was organized by Ministry of Science,ICT&Future Planning.
Got a business proposal from the biggest startup incubator&accelerator Primer.
Developed an android application which helps working Moms communicate with their babysitters and let families share their memories by uploading photos, posting notes, and writing comments.
Role: planning, android client side developer, database construction
Demo video (English scripts are added.)


| Tetrapropenylsuccinic Anhydride General Information
-
| Synonyms: |
DDSA; Dihydro-3-(tetrapropenyl)-2,5-furandione; 2,5-Furandione, 3-(dodecenyl)dihydro-; 3-((2E)dodec-2-enyl)-3,4-dihydrofuran-2,5-dione |
| Molecular Formula: |
C16H26O3 |
| CAS Registry No.: |
26544-38-7 |
| Chemical Category: |
Others |
Usage and Performance Characteristics
-
| Manufacturer: |
Lonza Group Ltd. |
| Outstanding Properties: |
Enhancement of flexibility |
| Used for Polymeric Materials: |
Epoxy resins |
Physical Properties
-
| Aggregate State at 25°C: |
Liquid |
Optical Properties
-
| Color: |
Clear, light yellow |
| Refractive Index: |
1.475 (n20D) |
Hazard-Related Data
-
| OSHA Hazard Class: |
Not considered a hazardous substance |
| Flash Point Temperature, °C: |
177 |
Environmental Parameters
-
| Octanol-Water Partition Coeff., log Kow: |
6.41 |
| Theoretical Oxygen Demand, ThOD, g/g: |
2.52 |
Animal Toxicity
-
| Rabbit Dermal, LD50, mg/kg: |
6,200 |
| Rat Oral, LD50, mg/kg: |
2,550 |
Plasticizers Database (2nd Electronic Edition) Copyright © 2004 by ChemTec Publishing |


Days of Heaven (1978)
Grade: 93
The documentary "Visions of Light: The Art of Cinematography" lavished more screen time on "Days of Heaven" than on any other film, even going so far as to use the theme as the final credits rolled. It is easy to see why "Days of Heaven" was so honored: it is a great argument for cinematography rather than script or story as the most important element of a film (I still believe that the script is the most important element).
"Days of Heaven" has a minimalist script and relies upon the camerawork to flesh out the plot. There are many distant shots of lush wheatfields, of migrant farm workers earning their day's wages, of steam trains and thrashers. There are also many close-ups, not just of the beautiful cast (then unknowns) but even of grasshoppers munching. The slow pace allows the cinematography to tell the story. The shots become redundant only when depicting a wheatfield fire.
"Days of Heaven" takes place in the Texas panhandle area during World War I. Richard Gere stars as a hotheaded itinerant worker. His lover is Brooke Adams, but for some reason they tell others they are brother and sister. They work on the immense wheat farm of Sam Shephard, who has been told he has but one year to live. Shephard falls in love with Adams. Gere tells Adams to marry Shephard, with the intention of both inheriting his wealth after his impending demise. It would seem that all sides benefit from this arrangement, except that Shephard isn't getting sicker, and suspects that Gere and Adams aren't as they appear to be.
"Days of Heaven" was a project that took place over several years. One reason for this was the scenes included all four seasons, another was that most filming took place at dusk due to favorable lighting.
The cast, direction, cinematography and story are all excellent and mark "Days of Heaven" as one of the most important American films of the 1970s.
http://members.tripod.com/~Brian_Koller/movies.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.
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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Loading images¶
Many image data sets are too large to be loaded into memory entirely and need to be processed lazily. This is the main reason for using nuts-ml. Otherwise, pre-processing data sets via scikit-learn or NumPy is more efficient and simpler.
The common strategy in nuts-ml to deal with large image data is to use samples that contain image file paths and meta-data such as labels, and load images on demand. For instance, the ReadImage() nut reads images from a given path and returns Numpy arrays. Here a simple example
>>> samples = [('nut_color.jpg', 'color'), ('nut_grayscale.jpg', 'gray')]
>>> imagepath = 'tests/data/img_formats/*'
>>> samples >> ReadImage(0, imagepath) >> PrintColType() >> Consume()
item 0: <tuple>
0: <ndarray> shape:213x320x3 dtype:uint8 range:0..248
1: <str> color
item 1: <tuple>
0: <ndarray> shape:213x320 dtype:uint8 range:18..235
1: <str> gray
where samples are composed of the image filename and a (class) label (‘color’, ‘gray’).
ReadImage(0, imagepath)
takes a sample, extracts the image filename from column 0
of the sample, constructs the full file path by replacing *
in imagepath
by
the image name, loads the image and replaces the image name by the actual image data.
Color images are loaded as Numpy arrays with shape (H, W, 3)
and gray scale
images with shape (H, W)
both with data type uint8
. In this example
the images are of size 213x320(x3) and range
list the smallest and
largest value of the image – as printed by PrintColType()
.
PrintColType()
displays the data types of sample columns. Here, the first sample
(item 0
) is a tuple and contains a Numpy array (the loaded image) in column 0
and the class label as a string in column 1.
Similarly, the second sample (item 1
) contains the loaded image as a Numpy array
and the class label.
If the image filepaths are directly provided - and not stored in a column of a tuple -,
setting the column to None
in ReadImage()
enables loading those images:
>>> imagenames = ['nut_color', 'nut_grayscale']
>>> imagepath = 'tests/data/img_formats/*.jpg'
>>> imagenames >> ReadImage(None, imagepath) >> PrintColType() >> Consume()
item 0: <tuple>
0: <ndarray> shape:213x320x3 dtype:uint8 range:0..248
item 1: <tuple>
0: <ndarray> shape:213x320 dtype:uint8 range:18..235
Note that ReadImage()
still returns tuples, though, with the image as
element in column 0 (<image>,)
and not just the images.
Instead of providing a base image path and image file names within samples it is also possible to directly provide the full file path within the sample:
>>> images = ['tests/data/img_formats/nut_color.gif']
>>> images >> ReadImage(None) >> PrintColType() >> Consume()
item 0: <tuple>
0: <ndarray> shape:213x320x3 dtype:uint8 range:0..255
Furthermore ReadImage()
allows to read multiple images at the same time,
e.g. for samples that contain an image and a mask. In the following example we
read color images and their gray-scale version as pairs
>>> samples = [('color.jpg', 'grayscale.jpg'), ('color.png', 'grayscale.png')]
>>> imagepath = 'tests/data/img_formats/nut_*'
>>> samples >> ReadImage((0,1), imagepath) >> PrintType() >> Consume()
(<ndarray> 213x320x3:uint8, <ndarray> 213x320:uint8)
(<ndarray> 213x320x3:uint8, <ndarray> 213x320:uint8)
where ReadImage((0,1), ...)
specifies that the image names are in columns
0 and 1 of the samples. Note that we moved the common prefix nut_
of the
image file names to the image path.
The printout of PrintType
confirms that we loaded
color images with 3 color channels (shape:213x320x3) and gray-scale images
that have no channel axis (shape:213x320) as pairs in tuple format.
The next section will show how to display loaded images conveniently.


{% extends 'base_layout.html' %} {% load static %} {% block content %}
A webscraper that compares the prices of your shopping basket across the UK's largest supermarkets.
Created by Ramon Williams


Michigan State exhibit showcases black travelers’ green book
EAST LANSING, Mich. (AP) - A new exhibit at Michigan State University is built around a 20th century guidebook that black motorists relied on during the segregation era to find places where they could safely sleep, eat, shop or find services while traveling.
The exhibit for “The Negro Motorist Green Book” runs until the end of November. It also introduces the guide’s publisher, Victor H. Green, a postal carrier in the Harlem section of New York whose book helped generations of African Americans travel. Though segregation by law persisted in the south until the 1960s, there was also segregation by practice in Detroit.
“The city was even more segregated then than it is now,” said Ken Coleman, a Detroit author, historian and journalist. “A publication like the Green Book would be very helpful to someone, if they were visiting from another part of the country and happened to be African-American. It was really a road map to where you could find entertainment and lodging and a good restaurant to have dinner.”
From 1936 to 1966, the guide cumulatively listed 86 black-friendly businesses in Detroit and five in Lansing. The exhibit presents side-by-side, before-and-after pictures of the businesses, showcasing how they looked 50 to 80 years ago and today. The historical display follows the 2018 release of “Green Book,” an Oscar-winning film highlighting the guide that African-Americans consulted when traveling in the South during the Jim Crow era.
Green was moved to write the book in part by the discrimination he and his wife faced on trips to her racially segregated hometown of Richmond, Virginia. He also got inspiration from a Jewish associate who showed him a similar travel guide for Jews.
Green eventually expanded his book to include the Jim Crow South and then harshly segregated areas of the north, extending beyond New York.
The guide became so popular, he later quit his day job.
“The book is a guide to freedom, so they wouldn’t be humiliated when they got turned away, and so forth. They could carry that book and say, look, I’m free now, to stop where I wish because there are places that will accept me,” said Joe Darden, a professor of geography, environment and spatial sciences at Michigan State. “Victor H. Green has not gotten the credit that he deserves, in the consideration of civil rights.”
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Tea Leaves is a web app I put together with my friend Dan a few months ago.
It invites users to make predictions on world events. We have ideas about how it might be refined or expanded, but haven't what direction it will go in.
The idea first came to me five or six years ago while I was in law school.
I was reading dozens of newspapers from cover to cover and thinking it would be more fun if I could make predictions on the issues I was reading about. After deciding to become a programmer, this seemed like a good app to start with.
Since Dan and I started working on this, a few comparable applications have cropped up.
Predict It, for example, allows users to make predictions on political events, but they are focused on users betting money on outcomes.
Called It and Sage encourage preditions without getting money involved, which I like. But, they embrace any and all postings. This not only leads to predictions on sports and celebrities, which Dan and I are not interested in, but they also lead to users submitting ridiculous predictions just to be funny. Like one Called It user predicted "YOLO will be the leading cause of death in 2016." While I wholeheartedly agree with that prediction, Dan and I don't care to create a forum for that kind of thing.
-
With those thoughts in mind, we started developing Tea Leaves (as in, you can read tea leaves to predict the future).
-
It helped me to appreciate more diverse aspects of application design, development, and operations. Even market analysis and project management.
It is also really fun to think in detail about practical business challenges like trying to develop features that would differentiate our app in the market. And about collaborating with my co-founder throughout the development process.
If you think it's worth it for us to continue building on it, let me know!


This map shows the first high resolution swath radar collected in Antarctica, a technology that allows us to measure the land features under glacial ice in very high detail. The sensitivity of the overlying ice to changes in the climate, is dependent on bed topography and the bed composition that the ice moves over. Improving our understanding of the bed significantly improves our ability to understand how the ice in the area is flowing, and how this will affect the future of Thwaites Glacier. Using the slider on the map the viewer can compare the higher resolution data on the surface layer of the map, to the basemap below. The new data reveals significantly more about the shape and features of the land under the ice. Be sure to see how this high resolution surface map links to the accompanying map titled Identifying subglacial bed type in this section of the App.
surface features or shape of the land
What is this map about? Ice interacts with the bed below, both creating land features as it moves across the landscape, and being influenced by the land below in its flow. Our understanding of how different ice processes generate landscape features has been developed from studying exposed landscapes around the world many years after any ice has melted away. Landforms that were once under the ice have been studied with high precision instruments using techniques such as lidar to measure land surface elevation and topography and multibeam swath bathymetry to collect equivalent data on the ocean floor. Models of how the ice interacted with, and contributed to the development of the landscape, have been developed from these data. However, new techniques were needed to measure the forms hidden under the ice with the same high resolution imagery that would match that of our surface topography. This is now possible using swath radar processing. Thwaites Glacier was the first area in Antarctica where this technique was used.
Light Detection and Ranging, is a remote sensing method using light in the form of a pulsed laser
an echosounder or type of sonar that is used to map the seabed using acoustic waves
How can we look under the ice? For information on this we refer you back to the information page for the map called A Look Under the Antarctic Ice Sheet in the App. There we review how a combination of geophysical tools can be used to image through the ice to better understand the land surface below. There we also review some of the many things we can learn from looking under the ice, and broad questions we can answer by interacting with the data. The more developed the technology, and the more detailed the data we collect, the more specific the questions that can be asked and answered, helping us to push forward our understanding of ice/landscape interactions.
What is swath processing? Conventional techniques for measuring and characterizing the land surface under the ice includes the use of seismic and nadir-focused radar. Seismic measurements use small explosions that when detonated send sound reverberations that are then measured to provide information on the depth to the bed and on its surface material. Nadir-focused radar measures the timing of the travel of radar waves collected directly below the source. Traditionally radar lines are collected at spacing that is kilometers apart, and the areas that fall in between are 'smoothed' to connect the data. Swath radar collects data not just directly below but all along a fan shaped strip spreading out on either side from the nadir, creating higher resolution, three-dimensional maps of the features below. For the data shown in this map the swaths were ~ 2km wide, and subglacial land features were imaged at~ 25 meter resolution, which allowed land features to be retained and identified clearly in the data.
the direction pointing directly below the radar focus
Why is this high resolution data important, or what can I learn from this map? See for yourself how much more information is available in this new map layer. Use the slider on the bottom of the page to ‘pull back’ the overlying layer and look for features to match up between the overlying layer and the layer below. You can also see how much more detail is in the new layer. It is amazing to see the differences, like improving our eyeglass prescription! It is this new level of detail that allows us to identify features in the landscape beneath the ice that tell us how the ice has created the landscape below. Look for the high areas that block the ice flow as it moves across the landscape. Now find the depressions or low areas that form around the high landforms as the ice moves across the landscape. Find the deepest area in these newly imaged areas, how deep are they? Think of the power of the ice as it carves across the landscape, scraping across and digging out areas of the surface as it goes.
What has this work allowed us to do? This work on Thwaites has shown how the ice has carved over the surface below digging out troughs or moats on the sides of more resistant landforms and then dropping a trail of softer sediments behind as it continues to flow. Swath radar is improving our understanding of the surface beneath the ice, yet it is not possible to use this approach to measure large areas like the vast millions of square kilometers of hidden landscape under Antarctic ice. It is, however, extremely beneficial in targeted areas like Thwaites region, where we are seeking very specific information on glacier movement and acceleration: (1) in areas along glacier flow to better understand ice/bed interactions; and (2) at the grounding line where the ice detaches from the land below.
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| Kendall-package | Kendall correlation and trend tests. |
| GuelphP | Phosphorous Concentrations in Speed River, Monthly |
| Kendall | Kendall rank correlation |
| MannKendall | Mann-Kendall trend test |
| PrecipGL | Annual precipitation, inches, Great Lakes, 1900-1986 |
| print.Kendall | print Method for Class 'Kendall' |
| SeasonalMannKendall | Mann-Kendall trend test for monthly environmental time series |
| summary.Kendall | summary Method for Class 'Kendall' |


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audio
namespace audio
Public Properties
stopOnAudioError: boolean = true
boolean
Specify either to stop on audio loading error or not
if true, melonJS will throw an exception and stop loading
if false, melonJS will disable sounds and output a warning message
in the console
Public Methods
enable() → {}
enable audio output
only useful if audio supported and previously disabled through
fade(sound_name: string, from: number, to: number, duration: number, id: number) → {}
Fade a currently playing sound between two volumee.
| Name | Type | Attributes | Description |
|---|---|---|---|
| sound_name | string |
audio clip name - case sensitive |
|
| from | number |
Volume to fade from (0.0 to 1.0). |
|
| to | number |
Volume to fade to (0.0 to 1.0). |
|
| duration | number |
Time in milliseconds to fade. |
|
| id | number |
<optional> |
the sound instance ID. If none is passed, all sounds in group will fade. |
getCurrentTrack() → {string}
returns the current track Id
| Type | Description |
|---|---|
| string |
audio track name |
getVolume() → {number}
get the default global volume
| Type | Description |
|---|---|
| number |
current volume value in Float [0.0 - 1.0] . |
hasAudio() → {boolean}
check if audio (HTML5 or WebAudio) is supported
| Type | Description |
|---|---|
| boolean |
return true if audio (HTML5 or WebAudio) is supported |
hasFormat(codec: "mp3" | "mpeg" | "opus" | "ogg" | "oga" | "wav" | "aac" | "caf" | "m4a" | "m4b" | "mp4" | "weba" | "webm" | "dolby" | "flac") → {boolean}
check if the given audio format is supported
| Name | Type | Description |
|---|---|---|
| codec | "mp3" | "mpeg" | "opus" | "ogg" | "oga" | "wav" | "aac" | "caf" | "m4a" | "m4b" | "mp4" | "weba" | "webm" | "dolby" | "flac" |
the audio format to check for support |
| Type | Description |
|---|---|
| boolean |
return true if the given audio format is supported |
init(format: string) → {boolean}
Initialize and configure the audio support.
For a maximum browser coverage the recommendation is to use at least two of them,
typically default to webm and then fallback to mp3 for the best balance of small filesize and high quality,
webm has nearly full browser coverage with a great combination of compression and quality, and mp3 will fallback gracefully for other browsers.
It is important to remember that melonJS selects the first compatible sound based on the list of extensions and given order passed here.
So if you want webm to be used before mp3, you need to put the audio format in that order.
// initialize the "sound engine", giving "webm" as default desired audio format, and "mp3" as a fallback
if (!me.audio.init("webm,mp3")) {
alert("Sorry but your browser does not support html 5 audio !");
return;
}
| Name | Type | Attributes | Default | Description |
|---|---|---|---|---|
| format | string |
<optional> |
"mp3" |
audio format to prioritize ("mp3"|"mpeg"|"opus"|"ogg"|"oga"|"wav"|"aac"|"caf"|"m4a"|"m4b"|"mp4"|"weba"|"webm"|"dolby"|"flac") |
| Type | Description |
|---|---|
| boolean |
Indicates whether audio initialization was successful |
load(sound: loader.Asset, onloadcb: Function, onerrorcb: Function) → {number}
Load an audio file
| Name | Type | Attributes | Description |
|---|---|---|---|
| sound | loader.Asset | ||
| onloadcb | Function |
<optional> |
function to be called when the resource is loaded |
| onerrorcb | Function |
<optional> |
function to be called in case of error |
| Type | Description |
|---|---|
| number |
the amount of asset loaded (always 1 if successfull) |
mute(sound_name: string, id: number, mute: boolean) → {}
mute or unmute the specified sound, but does not pause the playback.
// mute the background music
me.audio.mute("awesome_music");
| Name | Type | Attributes | Default | Description |
|---|---|---|---|---|
| sound_name | string |
audio clip name - case sensitive |
||
| id | number |
<optional> |
the sound instance ID. If none is passed, all sounds in group will mute. |
|
| mute | boolean |
<optional> |
true |
True to mute and false to unmute |
muted() → {boolean}
Returns true if audio is muted globally.
| Type | Description |
|---|---|
| boolean |
true if audio is muted globally |
pause(sound_name: string, id: number) → {}
pause the specified sound on all channels
this function does not reset the currentTime property
me.audio.pause("cling");
| Name | Type | Attributes | Description |
|---|---|---|---|
| sound_name | string |
audio clip name - case sensitive |
|
| id | number |
<optional> |
the sound instance ID. If none is passed, all sounds in group will pause. |
play(sound_name: string, loop: boolean, onend: Function, volume: number) → {number}
play the specified sound
// play the "cling" audio clip
me.audio.play("cling");
// play & repeat the "engine" audio clip
me.audio.play("engine", true);
// play the "gameover_sfx" audio clip and call myFunc when finished
me.audio.play("gameover_sfx", false, myFunc);
// play the "gameover_sfx" audio clip with a lower volume level
me.audio.play("gameover_sfx", false, null, 0.5);
| Name | Type | Attributes | Default | Description |
|---|---|---|---|---|
| sound_name | string |
audio clip name - case sensitive |
||
| loop | boolean |
<optional> |
false |
loop audio |
| onend | Function |
<optional> |
Function to call when sound instance ends playing. |
|
| volume | number |
<optional> |
default |
Float specifying volume (0.0 - 1.0 values accepted). |
| Type | Description |
|---|---|
| number |
the sound instance ID. |
playTrack(sound_name: string, volume: number) → {number}
play the specified audio track
this function automatically set the loop property to true
and keep track of the current sound being played.
me.audio.playTrack("awesome_music");
| Name | Type | Attributes | Default | Description |
|---|---|---|---|---|
| sound_name | string |
audio track name - case sensitive |
||
| volume | number |
<optional> |
default |
Float specifying volume (0.0 - 1.0 values accepted). |
| Type | Description |
|---|---|
| number |
the sound instance ID. |
rate(sound_name: string, rate: number, id: number) → {number}
get or set the rate of playback for a sound.
// get the playback rate of the background music
let rate = me.audio.rate("dst-gameforest");
// speed up the playback of the background music
me.audio.rate("dst-gameforest", 2.0);
| Name | Type | Attributes | Description |
|---|---|---|---|
| sound_name | string |
audio clip name - case sensitive |
|
| rate | number |
<optional> |
playback rate : 0.5 to 4.0, with 1.0 being normal speed. |
| id | number |
<optional> |
the sound instance ID. If none is passed, all sounds in group will be changed. |
| Type | Description |
|---|---|
| number |
return the current playback rate (if no extra parameters were given) |
resume(sound_name: string, id: number) → {}
resume the specified sound on all channels
// play a audio clip
let id = me.audio.play("myClip");
...
// pause it
me.audio.pause("myClip", id);
...
// resume
me.audio.resume("myClip", id);
| Name | Type | Attributes | Description |
|---|---|---|---|
| sound_name | string |
audio clip name - case sensitive |
|
| id | number |
<optional> |
the sound instance ID. If none is passed, all sounds in group will resume. |
resumeTrack() → {}
resume the previously paused audio track
// play an awesome music
me.audio.playTrack("awesome_music");
// pause the audio track
me.audio.pauseTrack();
// resume the music
me.audio.resumeTrack();
seek(sound_name: string, seek: number, id: number) → {number}
get/set the position of playback for a sound.
// return the current position of the background music
let current_pos = me.audio.seek("dst-gameforest");
// set back the position of the background music to the beginning
me.audio.seek("dst-gameforest", 0);
| Name | Type | Attributes | Description |
|---|---|---|---|
| sound_name | string |
audio clip name - case sensitive |
|
| seek | number |
<optional> |
the position to move current playback to (in seconds). |
| id | number |
<optional> |
the sound instance ID. If none is passed, all sounds in group will changed. |
| Type | Description |
|---|---|
| number |
return the current seek position (if no extra parameters were given) |
setVolume(volume: number) → {}
set the default global volume
| Name | Type | Description |
|---|---|---|
| volume | number |
Float specifying volume (0.0 - 1.0 values accepted). |
stop(sound_name: string, id: number) → {}
stop the specified sound on all channels
me.audio.stop("cling");
| Name | Type | Attributes | Description |
|---|---|---|---|
| sound_name | string |
<optional> |
audio clip name (case sensitive). If none is passed, all sounds are stopped. |
| id | number |
<optional> |
the sound instance ID. If none is passed, all sounds in group will stop. |
stopTrack() → {}
stop the current audio track
// play a awesome music
me.audio.playTrack("awesome_music");
// stop the current music
me.audio.stopTrack();
unload(sound_name: string) → {boolean}
unload specified audio track to free memory
me.audio.unload("awesome_music");
| Name | Type | Description |
|---|---|---|
| sound_name | string |
audio track name - case sensitive |
| Type | Description |
|---|---|
| boolean |
true if unloaded |
unmute(sound_name: string, id: number) → {}
unmute the specified sound
| Name | Type | Attributes | Description |
|---|---|---|---|
| sound_name | string |
audio clip name |
|
| id | number |
<optional> |
the sound instance ID. If none is passed, all sounds in group will unmute. |


Copyright Peri Coleman, Delta Environmental Consulting
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