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This is a paragraph wich contains instructions, laws or any descripcion of an electronic service. Normaly, the content is difficult to understand, specialy the terms tlike this one: (DNI). All these paragraphs can be large and has a lot of content.
This is a paragraph wich contains instructions, laws or any descripcion of an electronic service. Normaly, the content is difficult to understand, specialy the terms tlike this one: (DNI). All these paragraphs can be large and has a lot of content.
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This is a paragraph which contains a sample form that can be filled with the support of CDV. The highligted fields can be filled with data stored in CDV or its values can be stored in CDV for next usage.


Examples of native Check Boxes (unstyled) and the required mark-up pattern to create custom radio buttons that still utilize the native HTML element.
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with a
.form-row
class for consistent form element layout.
Examples of native Radio Buttons (unstyled) and the required mark-up pattern to create custom radio buttons that still utilize the native HTML element.
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New variable type named ‘var’ in Java 10
? Have we started turning into JavaScript anarchists? Has its very substance been polluted by Kotlin enthusiasts? Should we all worry by this new “feature” (are we sure its not a bug?) or could there be any benefits from using ‘var’ in our code?
Var is used for type inference in Java and helps reduce the verbosity of the language. This means you are able to omit variables’ type, as it will be inferred by the compiler by looking at the right hand part of the assignment. To make things a bit clearer checkout the following example:
Since Java 10 the following declaration
String firstName = "Iakovos";
is the same as:
var firstName = "Iakovos";
Compiler detects that the value on the right is of type String and without explicitly making the declaration, it infers the ‘firstName’ type. Meaning firstName is instanceof String.
You might think that var is a reserved keyword but that’s not the case since doing so would break backwards compatibility, instead it is a reserved type name just like int, long, double etc. .
Type inference is not new, since it was first introduced with Java 7
List<String> currencyList = new ArrayList<>();
instead of Java 6 and prior
List<String> currencyList = new ArrayList<String>();
Then we saw it in Java 8
Prior to java 8
Predicate<String> authorList = (String authors) -> authors.contains("Iakovos");
Java 8 onwards
Predicate<String> authorList = authors -> authors.contains("Iakovos");
Common QA would go something like this:
- What is the scope of the variable? Can you also have class variables of type var?
No, absolutely not, only method scope.
- Is it necessary to initialize var with a value all the time?
Yes the following is forbidden
var firstName = null
A simple rule to remember, is that the compiler should be able to infer the variable type when it is declared. For this to happen, it looks at the value on the right to get some clues. In the example above someone would argue the case of assigning type Object to firstName, but that would be too vague and without a point as everything derives from Object type, var included. Also that would mean that java is not a statically typed language anymore.
- OK, so how will this piece of code actually help us?
When using it we reduce verbosity from type declarations as shown below.
ex.
var nameAppender = new StringBuffer();
var delimiter = "+";
var endingCharacter = "-";
- Will it cause any confusions?
Well it can, but that highly depends on the way you code.
ex.
var prettinessLevel = myPrettyClass.increasePrettiness(1);
or maybe something like..
var result = myPrettyMethod();
In any case, var like most things in life can be a knife. You can either write sexier code or make other people’s eyes bleed.
- If I initialize var with String, can I then go ahead and reassign a value of type int?
Nope doing something like var name = "Iakovos";
and then reassign name = 3;
will fail with compilation error.
Upon initialization var has type String and that cannot change later in the code, meaning type safety is intact (in other words no, Java hasn’t turned into JavaScript).
- How is var represented in my generated.class files?
Well if you run decompiler ex. javap -c main.class
for your classes you will see that the generated types don’t include var but the infer types instead.
- Can you declare an array of type var?
Nope doing so won’t work. Trying it out on IntelliJ IDEA, I received the following error: Array initializer is not allowed here
//won't work!
var t = {1,2};
- When you assign an arithmetic value to a variable of type var, how will it be autoboxed?
Good question, let see what happens. If you have a small value lets say 1, var will be of type int not short.
Now, if you try something like var a = Integer.MAX_VALUE + 15;
variable ‘a’ won’t be autoboxed to long, but will be of type int instead and an overflow will occur
. Meaning ‘a’ will have a value of -2147483634
Playing around a bit with Intellij I found the following:
- Classes with name var are prohibited
- Interfaces with name var are prohibited
- You can declare a method with name var
//don't try this at home
var x = var();
public static int var(){
return 1;
}
- You can declare a variable with name var
String var = "2";
- You can declare a package named var //for the love of God don’t..
If you want o see the var feature in more depth, please check out this article from Oracle. Apart from being very educational there is a great section on how to use “Type Inference with Non-Denotable Types”.


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--- layout: default title: Team description: "People in the lab" group: navigation navorder: 2 undergrads: - Over Acuna - Chelsy Fraga - Kevin Garcia - Nathaline Germain - Tiana Lanier - Abigail Martinez - Aleymi Perez - Javier Perez - Vanessa Rodriguez - Diego Sanchez - Sharieka Savage - Amelia Vega - Kathleen Won - Salman Zubair --- {% include JB/setup %} {% assign temp = site.categories.team | reverse %} {% assign current = "" | split: "" %} {% assign alumni = "" | split: "" %} {% for member in temp %} {% if member.alumni != true %} {% assign current = current | push: member %} {% else %} {% assign alumni = alumni | push: member %} {% endif %} {% endfor %}


{% extends "base.html" %} {% block content %}
| #1 - If anyone has anything negative to say about design... they can shove it. Or they can do it themselves. |
| #2 - The Wednesday before the game, the spread will be locked in according to Barstool |
| #3 - After the spread has been locked, each player will choose whether Nebraska will COVER or NOT COVER |
| #4 - One point will be earned for picking the correct outcome, a second point will be earned for picking the spread correctly |
| #5 - The most points win |
| #6 - First Tiebreaker is number of spreads chosen correctly |
| #7 - Second Tiebreaker is closest prediction to the number of total points for Nebraska |


ID: {[{details.pk}]}
Created Date: {[{details.fields.creation_date | date : 'fullDate'}]}
User: {[{details.fields.user}]}
Content: {[{details.fields.content}]}
Palindrome: This message is a palindrome.
Palindrome: This message is not a palindrome.


| DOSE: |
5.0 g |
oral |
Kratom |
(powder / crystals) |
I write this, about 20 minutes after a terrible end,...
I got the Kratom on advice from the seller at the local SmartShop.
I asked for a relaxing tea, I had bought and tried Passionflower tea about 6 weeks earlier, but I just added hot water rather then boiling it, so it was just a very relaxing, but nasty tasting tea.
He said he didn't have anything really tea like, only brew things.
But, he said, he had something he uses himself when he needs a nice calm.
He showed me a 10 gram pack of Kratom, explaining that he takes 5 gram mixed with yoghurt in the evening.
I already read about Kratom, and knew it had nauseating side-effects, so I asked whether there were any bad or strange side effects, besides the calming down.
Where he replied there were none.
I trusted him, thinking 5 grams of a 10 gram, which should be the full dose, is a light dose and probably just relaxing, like the Passion Tea.
I got time to try it with yoghurt that friday evening.
But it totally failed, it tasted so bad I couldn't get in more then 3 small spoons of it.
The next week, now that is.
I decided to try it with some juice, as described on the website of the store, and other places.
T+0:00
I had put the remaining 5 grams in a large glass and filled it up with chocolate milk, at first the powder floated on top.
But after stirring a lot and waiting, it settled through the chocolate milk and became drinkable.
It had a bit of a bad taste but not super awful.
T+0:10
When I had finished drinking it up, I looked through some music and made a relaxing playlist to chill on.
T+0:30
I lay down in bed, my hands were cold from working behind my computer, so I warmed them up.
After my hands were warm, I relaxed, closed my eyes and felt sleepy, I was relaxed and tired, even without the Kratom.
All that comes now could as well 've been placebo,... very likely actually.
T+0:45
With my eyes closed, I was very able to visualize lots and lots of imaginative things, pictures, moving to the music.
I usually do this anyways, but it went extra good, seen I was very relaxed.
T+1:00
It got boring after a while, opened my eyes, looked at my video arcade cabinet and decided I wanted the music from there, as well as the winamp visuals displaying in the screen.
I got out of bed, a bit wobbly in my legs, probably placebo, I had this with Passion Flower tea too, but not with mushrooms.
Started opening the cabinet and working on it.
T+2:00
As I was messing with getting stuff installed, I felt a nausea coming up.
I sat down and I started moving my leg neurotically, it made the nauseous feel go away, but it didn't make me feel any better.
My mood wasn't really relaxed, my hands were shaking and I knew it was going kind of wrong.
Was just a matter of waiting till it went away, then go to bed or write this experience thing.

I paused my typing and I knew I was gonna throw up, I looked around my room, to decide where to leave my stomach fillings.
The floor was the best place, my garbage bin was full, and I had linoleum, or well, easily cleanable floor covering, so no real problem.
I bended forward from my chair and waited till I actually had to puke, avoiding unnecessary moaning sounds.
After 3 throws I was done, I didn't feel nauseous anymore.
Cleaned up, and talked to the guy on msn again.
Floor is still smelly.

Not for a retry!
It could've been miscellaneous things that contributed to the nausea, but it's mainly the kratom.
Because I barely throw up,... even if I'm VERY sick, nauseous, dizzy from a boat ride, or bustour that's taking ages, I just have a nasty feeling in my belly, and sit that out for as long as it takes.
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.


WITNESS LIST Appropriations Committee (Subcommittee on Regulatory Agencies) February 6, 1997-8:00A Budget Overview / Regulatory For: Boston, Nancy (Bd of Nurse Examiners) Gilchrist, Alfred (TX Med Assn) Gofortti, William Pres (Bd of Podiatric Examin) Hanna, Mark (Podiatric Medical Assn) Hymans, Allen (Bd of Podiatric Examin) Lankford, Wallace (Bd of Med Examiners) Lowrance, Kenneth (Bd of Nurse Examiners) Thomas, Katherine (Bd of Nurse Examiners) Willmann, James (TX Nurses Assn) On: Alonzo,Janie (Bd of Podiatric Examin) Beram, Douglas (Bd of Dental Examiners) Bronk, Marjorie (Bd of Vocational Nurse) Castro, Allan (LBB) Davies, Kathleen (Bd of Vocational Nurse) Deter, Dwight (Bd of PA Examiners) DeWolfe, Kevin (Optometry Bd) Ewald, Lois (Optometry Bd) Ferguson, Kelly (LBB) Hall, Hadley (Bd of Dental Examiners) Hill, Jeffry (Bd of Dental Examiners) Jenkins, Brenda (PUC) Kent, Linda (Bd of Vocational Nurse) King, Judy (LBb) Levy, Bruce (Bd of Medical Examiners) Levy, Bruce (Health Profession Cncl) McFarland, Jane (Health Professions Cncl) McKeever, Robin (PUC) McPherson, Carol (Bd of Dental Examiners) Milligan, Maureen (LBB) Parker, Glenn (Bd of Nurse Examiners) Priest, Paul (LBB) Rice, William (Bd of Vocational Nurse) Riddering, Hannah (TX NOW) Serna, Santos (Bd of Dental Examiners) Sweeney, LaVeta (Bd of Vocational Nurse) Wood, Patrick Henry (PUC)


Somany Ceramics share price rises 9% on robust Q2 numbers
Earnings before interest, tax, depreciation and amortisation (EBITDA) was up 68.2 percent at Rs 44.7 crore, while EBITDA margin was up 280 bps at 10.6 percent.
Shares of Somany Ceramics rose 9 percent intraday on November 7 after the company posted robust numbers in the quarter ended September 2019.
The company has reported 41.7 percent YoY jump in its Q2 profit to Rs 6.5 crore versus Rs 4.6 crore, while revenue was up 7.9 percent at Rs 422.2 crore versus Rs 391.4 crore.
The profit included a one-time loss at Rs 26.8 crore.
Earnings before interest, tax, depreciation and amortisation (EBITDA) was up 68.2 percent at Rs 44.7 crore, while EBITDA margin was up 280 bps at 10.6 percent.
At 1217 hrs, Somany Ceramics was quoting at Rs 187.85, up Rs 8.55, or 4.77 percent on the BSE.
The share touched its 52-week high Rs 472 and 52-week low Rs 174.50 on 08 April, 2019 and 09 October, 2019, respectively.
Currently, it is trading 60.18 percent below its 52-week high and 7.71 percent above its 52-week low.Special Thursday Expiry on 10th 7th Nov
Early Closure to The Great Diwali Discount. Last Chance to get Moneycontrol PRO for a year @ Rs. 289/- only
Coupon code: DIWALI


WHO DECIDES WAR by MRDR BRVDO Explores Conflict & Sustainability in SSENSE Drop
The eight-piece collection comes from former Virgil Abloh collaborator, Everand Best.
by Eric BrainWHO DECIDES WAR by MRDR BRVDO is a new collection of streetwear-indebted pieces to exclusively launch on SSENSE, designed by former Virgil Abloh-collaborator Everand Best.
The eight-piece Fall/Winter 2019 collection brings an aesthetic comprised of DIY, utilitarian and tactical aesthetics through garments such as the harness strap trousers and the vest.
WHO DECIDES WAR by MRDR BRVDO has a focus on sustainability and delivers a line of clothing that is purposely unfinished with raw hems and the use of raw, untreated Italian silks and cotton canvases, which are treated with coffee and tea dyes for a natural, washed finish.
The brand’s message is to celebrate the good in the world — something highlighted via its anti-666 logo – and it focuses on exploring the intricacies of conflict. Pieces such as the black flag hoodie, the matching T-shirt, and the messaging behind the use of harnesses and utilitarian designs further explore this. Take a look at all eight pieces from the WHO DECIDES WAR by MRDR BRVDO collection, and shop everything online now at SSENSE.
In other news, the French skateboarding brand Hélas has released its FW19 collection.


Preparation time
less than 30 mins
Cooking time
10 to 30 mins
Serves
Serves 4
For the parsnip purée and parsnip chips, heat the vegetable oil in a deep-fat fryer to 180C/355F (CAUTION: hot oil can be dangerous - do not leave unattended) and preheat the oven to 210C/410F/Gas 7.
Roughly chop three of the parsnips, place them in a saucepan and cover with the water and milk. Season with salt and sugar, to taste, and bring to the boil.
Reduce the heat and simmer for 10-12 minutes, or until tender.
Drain the parsnips well, then place in a food processor with a little of the cooking liquid and blend to a purée.
Place the parsnips into a clean saucepan and add enough cream to create a smooth creamy purée. Season with more salt and sugar, to taste.
Using a vegetable peeler, peel long strips along the length of the remaining parsnip.
Carefully place the parsnip shavings into the hot oil and fry until golden-brown. Remove the parsnips using a metal slotted spoon and drain on kitchen paper. Sprinkle lightly with salt.
For the shallot and black pepper sauce, place the red wine and shallots into a saucepan and bring to the boil.
Simmer for 3-4 minutes, until reduced by half, then add the black pepper and leave to cool.
For the tuna, season the tuna loin with salt and freshly ground black pepper, and heat the olive oil in a frying pan. Fry the tuna on both sides until lightly coloured.
Place the tuna onto a rack on a small roasting tray and transfer to the oven to cook for 2-3 minutes.
Remove the tuna from the oven, turn it over on the rack and leave in a warm place to continue heating through for about five minutes. Leave the oven on.
Slice each tuna steak in half diagonally at 45 degrees, turn each piece flesh side up on the rack and then place back in the oven for 30 seconds. Remove the tuna from the oven.
To serve, place a large spoon of parsnip purée in the middle of each of four plates and spread slightly. Arrange the tuna on top, flesh side up. Spoon over the shallot and black pepper sauce, and top with the fried parsnip.


Chapter 5 Dynamic Spatio-Temporal Models
This chapter talks about dynamic approach to spatio-temporal data, whereas we talked about descriptive approach in the last chapter. In descriptive approach, we fit mean and covariance function for the true process. This makes it more difficult to analyze spatio-temporal data because specifying the covariance function is not a easy thing to do. This chapter focuses on more realistic approach. Acually, we can witness some spatio-temporal dynamics, e.g., dynamically varying weather or people’s log data which accumulates everyday, everytime whenever you use smart phones or surfing internet.
This chapter mainly focuses on the linear dynamic spatio-temporal models (DSTMs) in the univariate context. Although it is reasonable and realistic to consider precesses to be continuous in time, we focus on the more practical case where time has been discretized. Continuous time models such as stochastic differential equations are beyond our scope, so please refer to the papers if you’re interested in tem.
5.1 General Dynamic Spatio-Temporal Models
We consider the hierarchical modeling perspective for DSTM, which means we should specify data model and process model inside the data model. Also, process model specifies the dynamic evolution of the spatio-temporal process, similar to what we did before. This section gives a general overview of hierarchical modeling in the context of a DSTM.
Let temporal domain be \(D_t = \{0,1,2 ... \}\), where the time increment is \(\Delta_t = 1\). The potential data is denoted by \(\{ Z_t (s): \; s \in D_s; t=0,1,\cdots \}\) and the latent process as \(\{ Y_t (s): \; s \in D_s; t=0,1,\cdots \}\). We want to make inference on \(Y_{t_0}(s_0)\) under the situation that there is no \(Z_{t_0}(s_0)\). The relationship between these process is expressed as below in DSTM
\[\begin{equation} Z_t(\cdot) = \mathcal{H}_h (Y_t(\cdot), \theta_{d,t}, \epsilon_t(\cdot)) \tag{1} \end{equation}\]
\(\theta_{d,t}\) is data-model parameters which could vary on time and spatial domains. One important assumption to note is that the data process is independent conditioned on the true process and data parameters, i.e.,
\[\begin{equation} \{ Z_t(\cdot) \}^T_{t=1} \mid \{ Y_t(\cdot) \}^T{t=1}, \{ \theta_{d,t} \}^T_{t=1} = \prod^T_{t=1}[Z_t(\cdot) \mid Y_t(\cdot), \theta_{d,t}] \tag{2} \end{equation}\]
5.1.1 Process Model
The most important part of a DSTM is the decomposition of the joint distribution of the process in terms of conditional distributions that respect the time evolution of the spatial process. We can always decompose joint distribution as products of conditional distributions as
\[\begin{equation} [Y_0, Y_1, \cdots, Y_T] = [Y_T \mid Y_{T-1}, \cdots, Y_0] \\ \times [Y_{T-1} \mid Y_{T-2}, \cdots, Y_0] \times \cdots \\ \times [Y_1 \mid Y_0] \times [Y_0] \tag{3} \end{equation}\]
If we assume Markov assumption on (2), the joint distribution would be simplified as
\[\begin{equation} [Y_0, Y_1, \cdots, Y_T \mid \theta_{p,t}] = \prod^T_{t=1}[Y_t \mid Y_{t-1}, \theta_{p,t}] [Y_0 \mid \theta_{p,0}] \tag{4} \end{equation}\]
- is the second key assumption, with first key assumption in specified in (2). The first-order-Markov assumption that is usually made for DSTMs holds when \(Y_t(\cdot)\) follows a dynamic model of the form,
\[\begin{equation} Y_t(\cdot) = \mathcal{M}(Y_{t-1}, \theta_{p,t}, \eta_t), \; t=1,2,\cdots \tag{5} \end{equation}\]
where
- \(\theta_{p,t}\) denotes parameters related with the process model (spatial or temporal dependence would be possible).
- \(\mathcal{M}\) is the evolution operator.
- \(\eta_t\) is a spatial noise process independent in time
- Model (5) can be linear or non linear, Gaussian or non-Gaussian
- Dependending on the situation, we can assume higher orders of markov, but first order is usually sufficient.
5.1.2 Parameters
Note that the parameters in Bayesian Hierarchical Models (BHM) we specify just before. In descriptive spatio-temporal modeling, the parameters consist of the \(\beta\) in fixed effect and the parameters in the covariance function for the spatio-temporal random effect. However, in dynamic models, we do not specify covariance function any more, which is cumbersome to do so in descriptive modeling. Instead, we have parameters as \(\theta_{d,t}, \theta_{p,t}\), where subscript \(d, p\) denote data and process model respectively. With this parameterization, we reduce the parameter space efficiently which will be discussed later. However, for many cases, it would be sufficient to model with Empirical Hierarchical Model (EHM), so be cautious to select the proper models.
5.2 Latent Linear Gaussian DSTMs
We consider the simplest DSTM where the assumed first makrov process model in (2) have additive **Gaussian error distributions* and the evolution operator \(\mathcal{M}\) is assumed to be linear. Suppose we are interested in the latent process \(Y_t(s_i), \; i=1, \cdots, n\) and we have data at locations \(r_{jt}\; j=1, \cdots, m_t\). That is, based on the \(r_{jt}\) data at space, time index with \(j,t\) we want to predict values on \(n\) locations.
5.2.1 Linear Data Model with Additive Gaussian Error
At time point \(t\), suppose we have \(m_t\) dimensional data vector, \(Z_t = (Z_t(r_{1t}), \cdots, Z_t(r_{m_tt}))'\) and we want to infer on \(n\) dimensional latent process vector, \(Y_t \equiv ( Y_t(s_1), \cdots, Y_t(s_n) )'\). For the \(j\)th observation at time \(t\), the linear data model with additive Gaussian error is written as
\[\begin{equation} Z_t(r_{jt}) = b_t(r_{jt}) + \sum^n_{i=1} h_{t,ji}Y_t(s_i) + \epsilon_t(r_{jt}) \tag{6} \end{equation}\]
for \(t=1,\cdots,T\). Note model (6) is when time \(t\) at the location \(j\). That is, model (6) tries to explain the observed data point at time \(t\) and location \(r_{jt}\) by linearly combining \(n\) latent process. In matrix notation, we can write
\[\begin{equation} Z_t = b_t + H_t Y_t + \epsilon_t, \; \epsilon \sim Gau(0, C_{\epsilon, t}) \tag{7} \end{equation}\]
where \(H_t\) is \(m_t \times n\) mapping matrix and \(C_{\epsilon,t}\) is \(m_t \times m_t\) covariance matrix. We will briefly look at each of them
Latent Spatio-Temporal Dynamic Process
\(Y_t\) represents the latent dynamic spatio-temporal process. We assume this model as first-order Markovian for simplicity yet powerful.
Additive Offset Term
It is used when we want to assume zero-mean for the latent process or to adjust potential bias between data model and process model. We may assume additive offset term as constant, in terms of covariates and another spatial or temporal random processes with hierarchy.
Observation Mapping Function (or Matrix)
\(h_{t,ji}\) serve weights for data point at \(j\). That is, setting these weights properly, we can associate each data point with one or more of the process locations. This is especially useful when the location of process is close with the that of observed data. For example, if we set \(h_{t,j} = (0.2, 0.8, 0)\), we set the highest weight on the second location and no weight on the third location, because the third location is far away from the location \(j\). However, it is hard to pre-specify the locations at which one is interested in modeling the process.
Error Covariance Matrix
In the linear Gaussian DSTM, the Gaussian additive error process \(\epsilon_t\) is assumed to have mean zero and can have dependence in space or time, i.e., \(C_{\epsilon,t}\). In practice, we assume that most of the dependence structure is expressed by the DSTM and assume independence in error process. However, depending on the situation, one could specify other forms of covariance matrix.
Process Model
For given present time and location, linear markovian spatio-temporal process models generally assume that the value is made up of a weighted combination throughout spatial domain of previous time. It is continuous spatial context where we consider integro-difference equation (IDE). Specifically, a first order spatio-temporal IDE process model is given by
\[\begin{equation} Y_t(s) = \int_{D_s} m(s,x; \theta_p)Y_{t-1}(x)dx + \eta_t(s) \tag{8} \end{equation}\]
Note that the process in current time, i.e, \(Y_t(s)\) is influenced by other spatial points in previous time, i.e., \(Y_{t-1}(\cdot)\). In reality, we do not know every spatial point so we cannot do the integral. Therefore, the first-order IDE evolution process model in (8) is expressed as the stochastic difference equation,
\[\begin{equation} Y_t(s_i) = \sum^n_{j=1} m_{ij}(\theta_p) Y_{t-1}(s_j) + \eta_t(s_i) \tag{9} \end{equation}\]
Finally, in matrix notation, we can rewrite (9) as
\[\begin{equation} Y_t = MY_{t-1} + \eta_t \tag{10} \end{equation}\]
with additive spatial error process, \(\eta_t\) which is independent of \(Y_{t-1}\) and with spatial covariance matrix \(C_\eta\).
Usually, \(M, C_\eta\) are parameterized as \(\theta_p, \theta_\eta\) that has to be estimated, which is one of the most difficult tasks. We can do this through EHM when \(n\) is small and \(T >> n\).
5.3 Process and Parameter Dimension Reduction
As stated above, parameters in \(M, C_\eta\) can be estimated when \(n\) is small enough. However, this rarely happens in real data. So, we need to reduce the number of free parameters or reduce the dimension of the spatio-temporal dynamic process. That is, there are two ways to reduce computation in simple linear DSTM.
To reduce free parameters, we assume simple covariance structure such that \(C_\eta = \sigma^2_\eta I, M = diag(\theta_p)\), which are much simpler than before. Moreover, we can consider some of the neighbors at the loction \(s_0\) of interest, not considering all of the data. That is,
\[\begin{equation} Y_t(s_i) = \sum_{s_j \in \mathcal{N}_i} m_{ij} Y_{t-1}(s_j) + \eta_t(s_i) \tag{10} \end{equation}\]
To reduce dimension in the process model, we usually consider basis functions to represent the dynamic process. That is,
\[\begin{equation} Y_t(s) = x_t(s)'\beta + \sum^{n_\alpha}_{i=1} \phi_i (s) \alpha_{i,t} + \sum^{n_\xi}_{j=1} \psi_j(s) \xi_{j,t} + \nu_t(s) \tag{11} \end{equation}\]
where \(\xi_{j,t}\) are typically non-dynamic or at least contain simple temporal behavior and \(\alpha_{i,t}\) are dynamically evolving random effects.


The Tale of Tommy Fox
by Arthur Scott Bailey
Chapter 4: “Mother Grouse’s Children”
Additional Information
- Year Published: 1917
- Language: English
- Country of Origin: United States of America
- Source: Bailey, A. S. (1917). The Tale of Tommy Fox. New York: Grosset and Dunlap.
-
Readability:
- Flesch–Kincaid Level: 4.0
- Word Count: 695
- Genre: Fantasy
- Keywords: 20th century literature, american literature, children's stories, sleepy-time tales
- ✎ Cite This
Downloads
The very next day after his first lesson in hunting, when his mother had brought home the live woodchuck, Tommy Fox went off into the woods alone. He had made up his mind that he would surprise his mother by bringing home some nice tidbit for dinner—a rabbit, perhaps, or maybe a squirrel. He wasn’t quite sure what it would be, because you know when hunting you have to take what you find—if you can catch it.
Tommy Fox hadn’t been long in the woods before he had even better luck than he had expected. He was creeping through a thicket, making no noise at all, when what should he see but that sly old Mother Grouse, with all her eleven children! They were very young, were old Mother Grouse’s children; and they hadn’t yet learned to fly. And there they were, all on the ground, with the proud old lady in their midst.
Tommy Fox was so pleased that he almost laughed out loud. He tried to keep still; but he couldn’t help snickering a little. And old Mother Grouse heard him. She started to fly. But instead of tearing off out of danger, she lighted on the ground quite near Tommy.
 “I’ll just catch the old lady first, and then get the youngsters afterward. They can’t fly away.”
So Tommy made a leap for old Mother Grouse. He just missed her.
She rose in the nick of time and slipped away from him. But she didn’t fly far. So Tommy followed. And he stole up very slyly; and once more, when he was quite near the old lady, he sprang at her.
It was really very annoying. For again old Mother Grouse just escaped. Again she flew a little further away, lighted on the ground, and seemed to forget that Tommy Fox was so near.
That same thing happened as many as a dozen times. And the twelfth time that Mrs. Grouse rose before one of Tommy’s rushes she didn’t come down again. She lighted in a tree. And since it appeared to Tommy that she had no intention of leaving her safe perch, he gave up in disgust. He was very angry because he hadn’t caught old Mother Grouse. But there was her family! He would get them —the whole eleven of them! And he turned back toward the place where he had first come upon them.
Now, sly old Mother Grouse had played a trick on Tommy Fox. If he had just left her alone he could have caught every one of her children. But she had tempted him to follow her. And every time she rose from the ground and flew a short distance, she led Tommy further away from her little ones.
Tommy had some trouble in finding the exact spot where he had stumbled upon Mrs. Grouse and her children. But he found it again, at last. And little good it did him; for not a trace of those eleven young grouse could he discover. They had all disappeared—every single one of them! They knew what to do when their mother led Tommy Fox away. Each of them found a safe hiding-place. Some of them burrowed beneath the fallen leaves; some of them hid behind old stumps; some of them crept into a hollow log. And try as he would, Tommy Fox was unable to find so much as one downy feather.
He was so disappointed—and so ashamed—that he went home and stayed there. But he had learned something. Yes! Tommy Fox knew that if he ever met old Mother Grouse and her family again he would catch her children first. Afterward he would try to capture the sly old lady herself. But he didn’t believe, just then, that he would ever be able to catch her. You see, Tommy realized that he wasn’t quite so clever as he had thought.


[Gecode] Static post methods again...
Gabor Szokoli
szokoli at ps.uni-sb.de
Thu Nov 20 10:45:07 CET 2003
Hello! A weeks traffic just arrived :-/
Christian Schulte wrote:
>Dear all,
>
>I am not yet convinced that the introduction for static post method for each
>class really makes sense: in many cases the simplification of propagators
>according to certain variable domains will be done anyway upon first
>invocation of the propagator.
>
I'm not sure myself sometimes...
The justification was this:
1,
Propagators have to take advantage of variable equality among parameters
in a one-shot, posting time manner, because variables can not be unified
and it is a waste to check for this in the propagate method. It is often
possible to use a simpler propagator with less arguments based on the
equality information.
Possible places to put this logic:
-Constructor (dunno, why not?)
-API function in post.cc (Christian was against calling those from
propagate methods for self-replacement)
-something in between (static void post)
2, If an inline static void post does nothing just instantiates the
propagator, it'll be optimised away by the compiler.
3, If there is a well-defined point to put the var_same based smartness,
that increases the chances of it being actually implemented :-)
> So putting this decision making again in the
>post method will lead to a code blowup while it is not likely that
>performance will noticable imptove (it might decrease do to increasing code
>size).
>
>
>
Probably no performace gain for well-crafted examples, but real life
users sometimes formulate problems in some fsckd up ways :-)
>So I suggest that while this is not yet clear we refrain from adding this
>stuff without feeling a clear necessitiy to do so.
>
>
>
Acknoledged. Too bad I added a dozen since you wrote this. Was the list
server down, or is it just me who got everything late?
I'll look at the issues you mention in your previous mail.
Gabor Szokoli
More information about the gecode-users
mailing list


What is "Dependency Injection" and how this design pattern can improve my code ?
No matter the size of your app you'll require Resources (or Services) to be available: the database connection, the Cache manager etc. To be simple, you could load all these objects in a file called
services.phpand include it everytime you need to access some of these resources. However this is not recommended because you would have probably loaded unused resources, making your app not efficient (i.e costly).
Dependency Injection tries to solve this problem by letting the developer describe all its resources (Definitions) in a _Container_. A Definition is the way to tell the Container how to instanciate a resource. This makes Resources available "on demand" easily!


Source Streaming
Akka HTTP supports completing a request with an Akka Source[T, _], which makes it possible to easily build and consume streaming end-to-end APIs which apply back-pressure throughout the entire stack.
It is possible to complete requests with raw Source[ByteString, _], however often it is more convenient to stream on an element-by-element basis, and allow Akka HTTP to handle the rendering internally - for example as a JSON array, or CSV stream (where each element is separated by a new-line).
In the following sections we investigate how to make use of the JSON Streaming infrastructure, however the general hints apply to any kind of element-by-element streaming you could imagine.
JSON Streaming
JSON Streaming is a term refering to streaming a (possibly infinite) stream of element as independent JSON objects as a continuous HTTP request or response. The elements are most often separated using newlines, however do not have to be. Concatenating elements side-by-side or emitting "very long" JSON array is also another use case.
In the below examples, we'll be refering to the Tweet and Measurement case classes as our model, which are defined as:
case class Tweet(uid: Int, txt: String)
case class Measurement(id: String, value: Int)
And as always with spray-json, we provide our (Un)Marshaller instances as implicit values using the jsonFormat## method to generate them statically:
object MyJsonProtocol
extends akka.http.scaladsl.marshallers.sprayjson.SprayJsonSupport
with spray.json.DefaultJsonProtocol {
implicit val tweetFormat = jsonFormat2(Tweet.apply)
implicit val measurementFormat = jsonFormat2(Measurement.apply)
}
Responding with JSON Streams
In this example we implement an API representing an infinite stream of tweets, very much like Twitter's Streaming API.
Firstly, we'll need to get some additional marshalling infrastructure set up, that is able to marshal to and from an Akka Streams Source[T,_]. One such trait, containing the needed marshallers is SprayJsonSupport, which uses spray-json (a high performance json parser library), and is shipped as part of Akka HTTP in the akka-http-spray-json-experimental module.
Once the general infrastructure is prepared we import our model's marshallers, generated by spray-json (Step 1), and enable JSON Streaming by making an implicit EntityStreamingSupport instance available (Step 2). Akka HTTP pre-packages JSON and CSV entity streaming support, however it is simple to add your own, in case you'd like to stream a different content type (for example plists or protobuf).
The final step is simply completing a request using a Source of tweets, as simple as that:
// [1] import "my protocol", for marshalling Tweet objects:
import MyJsonProtocol._
// [2] pick a Source rendering support trait:
// Note that the default support renders the Source as JSON Array
implicit val jsonStreamingSupport: JsonEntityStreamingSupport = EntityStreamingSupport.json()
val route =
path("tweets") {
// [3] simply complete a request with a source of tweets:
val tweets: Source[Tweet, NotUsed] = getTweets
complete(tweets)
}
// tests ------------------------------------------------------------
val AcceptJson = Accept(MediaRange(MediaTypes.`application/json`))
val AcceptXml = Accept(MediaRange(MediaTypes.`text/xml`))
Get("/tweets").withHeaders(AcceptJson) ~> route ~> check {
responseAs[String] shouldEqual
"""[""" +
"""{"uid":1,"txt":"#Akka rocks!"},""" +
"""{"uid":2,"txt":"Streaming is so hot right now!"},""" +
"""{"uid":3,"txt":"You cannot enter the same river twice."}""" +
"""]"""
}
// endpoint can only marshal Json, so it will *reject* requests for application/xml:
Get("/tweets").withHeaders(AcceptXml) ~> route ~> check {
handled should ===(false)
rejection should ===(UnacceptedResponseContentTypeRejection(Set(ContentTypes.`application/json`)))
}
The reason the EntityStreamingSupport has to be enabled explicitly is that one might want to configure how the stream should be rendered. We'll dicuss this in depth in the next section though.
Customising response rendering mode
Since it is not always possible to directly and confidently answer the question of how a stream of T should look on the wire, the EntityStreamingSupport traits come into play and allow fine-tuning the streams rendered representation.
For example, in case of JSON Streaming, there isn't really one standard about rendering the response. Some APIs prefer to render multiple JSON objects in a line-by-line fashion (Twitter's streaming APIs for example), while others simply return very large arrays, which could be streamed as well.
Akka defaults to the second one (streaming a JSON Array), as it is correct JSON and clients not expecting a streaming API would still be able to consume it in a naive way if they'd want to.
The line-by-line aproach however is also pretty popular even though it is not valid JSON. It's relatively simplicity for client-side parsing is a strong point in case to pick this format for your Streaming APIs. Below we demonstrate how to reconfigure the support trait to render the JSON as
import MyJsonProtocol._
// Configure the EntityStreamingSupport to render the elements as:
// {"example":42}
// {"example":43}
// ...
// {"example":1000}
val start = ByteString.empty
val sep = ByteString("\n")
val end = ByteString.empty
implicit val jsonStreamingSupport = EntityStreamingSupport.json()
.withFramingRenderer(Flow[ByteString].intersperse(start, sep, end))
val route =
path("tweets") {
// [3] simply complete a request with a source of tweets:
val tweets: Source[Tweet, NotUsed] = getTweets
complete(tweets)
}
// tests ------------------------------------------------------------
val AcceptJson = Accept(MediaRange(MediaTypes.`application/json`))
Get("/tweets").withHeaders(AcceptJson) ~> route ~> check {
responseAs[String] shouldEqual
"""{"uid":1,"txt":"#Akka rocks!"}""" + "\n" +
"""{"uid":2,"txt":"Streaming is so hot right now!"}""" + "\n" +
"""{"uid":3,"txt":"You cannot enter the same river twice."}"""
}
Another interesting feature is parallel marshalling. Since marshalling can potentially take much time, it is possible to marshal multiple elements of the stream in parallel. This is simply a configuration option on EntityStreamingSupport and is configurable like this:
import MyJsonProtocol._
implicit val jsonStreamingSupport: JsonEntityStreamingSupport =
EntityStreamingSupport.json()
.withParallelMarshalling(parallelism = 8, unordered = false)
path("tweets") {
val tweets: Source[Tweet, NotUsed] = getTweets
complete(tweets)
}
The above shown mode perserves ordering of the Source's elements, which may sometimes be a required property, for example when streaming a strictly ordered dataset. Sometimes the contept of strict-order does not apply to the data being streamed though, which allows us to exploit this property and use an unordered rendering.
This also is a configuration option and is used as shown below. Effectively this will allow Akka's marshalling infrastructure to concurrently marshallup to parallelism elements and emit the first which is marshalled onto the HttpResponse:
import MyJsonProtocol._
implicit val jsonStreamingSupport: JsonEntityStreamingSupport =
EntityStreamingSupport.json()
.withParallelMarshalling(parallelism = 8, unordered = true)
path("tweets" / "unordered") {
val tweets: Source[Tweet, NotUsed] = getTweets
complete(tweets)
}
This allows us to _potentially_ render elements faster onto the HttpResponse, since it can avoid "head of line blocking", in case one element in front of the stream takes a long time to marshall, yet others after it are very quick to marshall.
Consuming JSON Streaming uploads
Sometimes the client may be sending a streaming request, for example an embedded device initiated a connection with the server and is feeding it with one line of measurement data.
In this example, we want to consume this data in a streaming fashion from the request entity, and also apply back-pressure to the underlying TCP connection, if the server can not cope with the rate of incoming data (back-pressure will be applied automatically thanks to using Akka HTTP/Streams).
// [1] import "my protocol", for unmarshalling Measurement objects:
import MyJsonProtocol._
// [2] enable Json Streaming
implicit val jsonStreamingSupport = EntityStreamingSupport.json()
// prepare your persisting logic here
val persistMetrics = Flow[Measurement]
val route =
path("metrics") {
// [3] extract Source[Measurement, _]
entity(asSourceOf[Measurement]) { measurements =>
// alternative syntax:
// entity(as[Source[Measurement, NotUsed]]) { measurements =>
val measurementsSubmitted: Future[Int] =
measurements
.via(persistMetrics)
.runFold(0) { (cnt, _) => cnt + 1 }
complete {
measurementsSubmitted.map(n => Map("msg" -> s"""Total metrics received: $n"""))
}
}
}
// tests ------------------------------------------------------------
// uploading an array or newline separated values works out of the box
val data = HttpEntity(
ContentTypes.`application/json`,
"""
|{"id":"temp","value":32}
|{"id":"temp","value":31}
|
""".stripMargin)
Post("/metrics", entity = data) ~> route ~> check {
status should ===(StatusCodes.OK)
responseAs[String] should ===("""{"msg":"Total metrics received: 2"}""")
}
// the FramingWithContentType will reject any content type that it does not understand:
val xmlData = HttpEntity(
ContentTypes.`text/xml(UTF-8)`,
"""|<data id="temp" value="32"/>
|<data id="temp" value="31"/>""".stripMargin)
Post("/metrics", entity = xmlData) ~> route ~> check {
handled should ===(false)
rejection should ===(UnsupportedRequestContentTypeRejection(Set(ContentTypes.`application/json`)))
}
Simple CSV streaming example
Akka HTTP provides another EntityStreamingSupport out of the box, namely csv (comma-separated values). For completeness, we demonstrate its usage in the below snippet. As you'll notice, switching betweeen streaming modes is fairly simple, one only has to make sure that an implicit Marshaller of the requested type is available, and that the streaming support operates on the same Content-Type as the rendered values. Otherwise you'll see an error during runtime that the marshaller did not expose the expected content type and thus we can not render the streaming response).
// [1] provide a marshaller to ByteString
implicit val tweetAsCsv = Marshaller.strict[Tweet, ByteString] { t =>
Marshalling.WithFixedContentType(ContentTypes.`text/csv(UTF-8)`, () => {
val txt = t.txt.replaceAll(",", ".")
val uid = t.uid
ByteString(List(uid, txt).mkString(","))
})
}
// [2] enable csv streaming:
implicit val csvStreaming = EntityStreamingSupport.csv()
val route =
path("tweets") {
val tweets: Source[Tweet, NotUsed] = getTweets
complete(tweets)
}
// tests ------------------------------------------------------------
val AcceptCsv = Accept(MediaRange(MediaTypes.`text/csv`))
Get("/tweets").withHeaders(AcceptCsv) ~> route ~> check {
responseAs[String] shouldEqual
"1,#Akka rocks!" + "\n" +
"2,Streaming is so hot right now!" + "\n" +
"3,You cannot enter the same river twice."
}
Implementing custom EntityStreamingSupport traits
The EntityStreamingSupport infrastructure is open for extension and not bound to any single format, content type or marshalling library. The provided JSON support does not rely on Spray JSON directly, but uses Marshaller[T, ByteString] instances, which can be provided using any JSON marshalling library (such as Circe, Jawn or Play JSON).
When implementing a custom support trait, one should simply extend the EntityStreamingSupport abstract class, and implement all of it's methods. It's best to use the existing implementations as a guideline.
Contents


Code 201 Fundamentals
Learning new information can be challenging. Learning new information that is the equivalent to the drops of water that fall over the edge of Niagara Falls is overwhelming.
We made an app to help! We've created a quiz that allows users to practice some of the vocabulary and logic that they've been learning in the Code Fellows 201 bootcamp.


public class PackedInteger
extends java.lang.Object
Most applications should use the classes in the com.sleepycat.bind.tuple
package rather than using this class directly.
| Modifier and Type | Field and Description |
|---|---|
static int |
MAX_LENGTH
The maximum number of bytes needed to store an int value (5).
|
static int |
MAX_LONG_LENGTH
The maximum number of bytes needed to store a long value (9).
|
| Constructor and Description |
|---|
PackedInteger() |
| Modifier and Type | Method and Description |
|---|---|
static int |
getReadIntLength(byte[] buf,
int off)
Returns the number of bytes that would be read by
readInt(byte[], int) . |
static int |
getReadLongLength(byte[] buf,
int off)
Returns the number of bytes that would be read by
readLong(byte[], int) . |
static int |
getReadSortedIntLength(byte[] buf,
int off)
Returns the number of bytes that would be read by
readSortedInt(byte[], int) . |
static int |
getReadSortedLongLength(byte[] buf,
int off)
Returns the number of bytes that would be read by
readSortedLong(byte[], int) . |
static int |
getWriteIntLength(int value)
Returns the number of bytes that would be written by
writeInt(byte[], int, int) . |
static int |
getWriteLongLength(long value)
Returns the number of bytes that would be written by
writeLong(byte[], int, long) . |
static int |
getWriteSortedIntLength(int value)
Returns the number of bytes that would be written by
writeSortedInt(byte[], int, int) . |
static int |
getWriteSortedLongLength(long value)
Returns the number of bytes that would be written by
writeSortedLong(byte[], int, long) . |
static int |
readInt(byte[] buf,
int off)
Reads a packed integer at the given buffer offset and returns it.
|
static long |
readLong(byte[] buf,
int off)
Reads a packed long integer at the given buffer offset and returns it.
|
static int |
readSortedInt(byte[] buf,
int off)
Reads a sorted packed integer at the given buffer offset and returns it.
|
static long |
readSortedLong(byte[] buf,
int off)
Reads a sorted packed long integer at the given buffer offset and
returns it.
|
static int |
writeInt(byte[] buf,
int offset,
int value)
Writes a packed integer starting at the given buffer offset and returns
the next offset to be written.
|
static int |
writeLong(byte[] buf,
int offset,
long value)
Writes a packed long integer starting at the given buffer offset and
returns the next offset to be written.
|
static int |
writeSortedInt(byte[] buf,
int offset,
int value)
Writes a packed sorted integer starting at the given buffer offset and
returns the next offset to be written.
|
static int |
writeSortedLong(byte[] buf,
int offset,
long value)
Writes a packed sorted long integer starting at the given buffer offset
and returns the next offset to be written.
|
public static final int MAX_LENGTH
public static final int MAX_LONG_LENGTH
public static int readInt(byte[] buf, int off)
buf
- the buffer to read from.off
- the offset in the buffer at which to start reading.public static long readLong(byte[] buf, int off)
buf
- the buffer to read from.off
- the offset in the buffer at which to start reading.public static int getReadIntLength(byte[] buf, int off)
readInt(byte[], int)
.
Because the length is stored in the first byte, this method may be called with only the first byte of the packed integer in the given buffer. This method only accesses one byte at the given offset.
buf
- the buffer to read from.off
- the offset in the buffer at which to start reading.public static int getReadLongLength(byte[] buf, int off)
readLong(byte[], int)
.
Because the length is stored in the first byte, this method may be called with only the first byte of the packed integer in the given buffer. This method only accesses one byte at the given offset.
buf
- the buffer to read from.off
- the offset in the buffer at which to start reading.public static int writeInt(byte[] buf, int offset, int value)
buf
- the buffer to write to.offset
- the offset in the buffer at which to start writing.value
- the integer to be written.public static int writeLong(byte[] buf, int offset, long value)
buf
- the buffer to write to.offset
- the offset in the buffer at which to start writing.value
- the long integer to be written.public static int getWriteIntLength(int value)
writeInt(byte[], int, int)
.value
- the integer to be written.public static int getWriteLongLength(long value)
writeLong(byte[], int, long)
.value
- the long integer to be written.public static int readSortedInt(byte[] buf, int off)
buf
- the buffer to read from.off
- the offset in the buffer at which to start reading.public static long readSortedLong(byte[] buf, int off)
buf
- the buffer to read from.off
- the offset in the buffer at which to start reading.public static int getReadSortedIntLength(byte[] buf, int off)
readSortedInt(byte[], int)
.
Because the length is stored in the first byte, this method may be called with only the first byte of the packed integer in the given buffer. This method only accesses one byte at the given offset.
buf
- the buffer to read from.off
- the offset in the buffer at which to start reading.public static int getReadSortedLongLength(byte[] buf, int off)
readSortedLong(byte[], int)
.
Because the length is stored in the first byte, this method may be called with only the first byte of the packed integer in the given buffer. This method only accesses one byte at the given offset.
buf
- the buffer to read from.off
- the offset in the buffer at which to start reading.public static int writeSortedInt(byte[] buf, int offset, int value)
buf
- the buffer to write to.offset
- the offset in the buffer at which to start writing.value
- the integer to be written.public static int writeSortedLong(byte[] buf, int offset, long value)
buf
- the buffer to write to.offset
- the offset in the buffer at which to start writing.value
- the long integer to be written.public static int getWriteSortedIntLength(int value)
writeSortedInt(byte[], int, int)
.value
- the integer to be written.public static int getWriteSortedLongLength(long value)
writeSortedLong(byte[], int, long)
.value
- the long integer to be written.Copyright (c) 1996, 2016 Oracle and/or its affiliates. All rights reserved.


|
entity - entity handle
range# - range of pick area around entity |
|
Returns the nearest entity 'ahead' of the specified entity. An entity must have a non-zero EntityPickMode to be pickable.
See also: EntityPick, LinePick, CameraPick, EntityPickMode. |


SUDO(8) MAINTENANCE COMMANDS SUDO(8) NAME sudo, sudoedit - execute a command as another user SYNOPSIS sudo -h | -K | -k | -V sudo -v [-AknS] [-g group name|#gid] [-p prompt] [-u user name|#uid] sudo -l[l] [-AknS] [-g group name|#gid] [-p prompt] [-U user name] [-u user name|#uid] [command] sudo [-AbEHnPS] [-C fd] [-g group name|#gid] [-p prompt] [-r role] [-t type] [-u user name|#uid] [VAR=value] [-i | -s] [command] sudoedit [-AnS] [-C fd] [-g group name|#gid] [-p prompt] [-u user name|#uid] file ... DESCRIPTION sudo allows a permitted user to execute a command as the superuser or another user, as specified by the security policy. The real and effective uid and gid are set to match those of the target user, as specified in the password database, and the group vector is initialized based on the group database (unless the -P option was specified). sudo supports a plugin architecture for security policies and input/output logging. Third parties can develop and distribute their own policy and I/O logging modules to work seamlessly with the sudo front end. The default security policy is sudoers, which is configured via the file /etc/sudoers, or via LDAP. See the PLUGINS section for more information. The security policy determines what privileges, if any, a user has to run sudo. The policy may require that users authenticate themselves with a password or another authentication mechanism. If authentication is required, sudo will exit if the user's password is not entered within a configurable time limit. This limit is policy-specific; the default password prompt timeout for the sudoers security policy is unlimited. Security policies may support credential caching to allow the user to run sudo again for a period of time without requiring authentication. The sudoers policy caches credentials for 15 minutes, unless overridden in sudoers(5). By running sudo with the -v option, a user can update the cached credentials without running a command. When invoked as sudoedit, the -e option (described below), is implied. Security policies may log successful and failed attempts to use sudo. If an I/O plugin is configured, the running command's input and output may be logged as well. OPTIONS sudo accepts the following command line options: -A Normally, if sudo requires a password, it will read it from the user's terminal. If the -A (askpass) option is specified, a (possibly graphical) helper program is executed to read the user's password and output the password to the standard output. If the SUDO_ASKPASS environment variable is set, it specifies the path to the helper program. Otherwise, if /etc/sudo.conf contains a line specifying the askpass program, that value will be used. For example: # Path to askpass helper program Path askpass /usr/X11R6/bin/ssh-askpass If no askpass program is available, sudo will exit with an error. -b The -b (background) option tells sudo to run the given command in the background. Note that if you use the -b option you cannot use shell job control to manipulate the process. Most interactive commands will fail to work properly in background mode. -C fd Normally, sudo will close all open file descriptors other than standard input, standard output and standard error. The -C (close from) option allows the user to specify a starting point above the standard error (file descriptor three). Values less than three are not permitted. The security policy may restrict the user's ability to use the -C option. The sudoers policy only permits use of the -C option when the administrator has enabled the closefrom_override option. -E The -E (preserve environment) option indicates to the security policy that the user wishes to preserve their existing environment variables. The security policy may return an error if the -E option is specified and the user does not have permission to preserve the environment. -e The -e (edit) option indicates that, instead of running a command, the user wishes to edit one or more files. In lieu of a command, the string "sudoedit" is used when consulting the security policy. If the user is authorized by the policy, the following steps are taken: 1. Temporary copies are made of the files to be edited with the owner set to the invoking user. 2. The editor specified by the policy is run to edit the temporary files. The sudoers policy uses the SUDO_EDITOR, VISUAL and EDITOR environment variables (in that order). If none of SUDO_EDITOR, VISUAL or EDITOR are set, the first program listed in the editor sudoers(5) option is used. 3. If they have been modified, the temporary files are copied back to their original location and the temporary versions are removed. If the specified file does not exist, it will be created.  If, for some reason, sudo is unable to update a file with its edited version, the user will receive a warning and the edited copy will remain in a temporary file. -g group Normally, sudo runs a command with the primary group set to the one specified by the password database for the user the command is being run as (by default, root). The -g (group) option causes sudo to run the command with the primary group set to group instead. To specify a gid instead of a group name, use #gid. When running commands as a gid, many shells require that the '#' be escaped with a backslash ('\'). If no -u option is specified, the command will be run as the invoking user (not root). In either case, the primary group will be set to group. -H The -H (HOME) option requests that the security policy set the HOME environment variable to the home directory of the target user (root by default) as specified by the password database. Depending on the policy, this may be the default behavior. -h The -h (help) option causes sudo to print a short help message to the standard output and exit. -i [command] The -i (simulate initial login) option runs the shell specified by the password database entry of the target user as a login shell. This means that login-specific resource files such as .profile or .login will be read by the shell. If a command is specified, it is passed to the shell for execution via the shell's -c option. If no command is specified, an interactive shell is executed. sudo attempts to change to that user's home directory before running the shell. The security policy shall initialize the environment to a minimal set of variables, similar to what is present when a user logs in. The Command Environment section in the sudoers(5) manual documents how the -i option affects the environment in which a command is run when the sudoers policy is in use. -K The -K (sure kill) option is like -k except that it removes the user's cached credentials entirely and may not be used in conjunction with a command or other option. This option does not require a password. Not all security policies support credential caching. -k [command] When used alone, the -k (kill) option to sudo invalidates the user's cached credentials. The next time sudo is run a password will be required. This option does not require a password and was added to allow a user to revoke sudo permissions from a .logout file. Not all security policies support credential caching. When used in conjunction with a command or an option that may require a password, the -k option will cause sudo to ignore the user's cached credentials. As a result, sudo will prompt for a password (if one is required by the security policy) and will not update the user's cached credentials. -l[l] [command] If no command is specified, the -l (list) option will list the allowed (and forbidden) commands for the invoking user (or the user specified by the -U option) on the current host. If a command is specified and is permitted by the security policy, the fully-qualified path to the command is displayed along with any command line arguments. If command is specified but not allowed, sudo will exit with a status value of 1. If the -l option is specified with an l argument (i.e. -ll), or if -l is specified multiple times, a longer list format is used. -n The -n (non-interactive) option prevents sudo from prompting the user for a password. If a password is required for the command to run, sudo will display an error messages and exit. -P The -P (preserve group vector) option causes sudo to preserve the invoking user's group vector unaltered. By default, the sudoers policy will initialize the group vector to the list of groups the target user is in. The real and effective group IDs, however, are still set to match the target user. -p prompt The -p (prompt) option allows you to override the default password prompt and use a custom one. The following percent (`%') escapes are supported by the sudoers policy: %H expanded to the host name including the domain name (on if the machine's host name is fully qualified or the fqdn option is set in sudoers(5)) %h expanded to the local host name without the domain name %p expanded to the name of the user whose password is being requested (respects the rootpw, targetpw and runaspw flags in sudoers(5)) %U expanded to the login name of the user the command will be run as (defaults to root unless the -u option is also specified) %u expanded to the invoking user's login name %% two consecutive % characters are collapsed into a single % character The prompt specified by the -p option will override the system password prompt on systems that support PAM unless the passprompt_override flag is disabled in sudoers. -r role The -r (role) option causes the new (SELinux) security context to have the role specified by role. -S The -S (stdin) option causes sudo to read the password from the standard input instead of the terminal device. The password must be followed by a newline character. -s [command] The -s (shell) option runs the shell specified by the SHELL environment variable if it is set or the shell as specified in the password database. If a command is specified, it is passed to the shell for execution via the shell's -c option. If no command is specified, an interactive shell is executed. -t type The -t (type) option causes the new (SELinux) security context to have the type specified by type. If no type is specified, the default type is derived from the specified role. -U user The -U (other user) option is used in conjunction with the -l option to specify the user whose privileges should be listed. The security policy may restrict listing other users' privileges. The sudoers policy only allows root or a user with the ALL privilege on the current host to use this option. -u user The -u (user) option causes sudo to run the specified command as a user other than root. To specify a uid instead of a user name, use #uid. When running commands as a uid, many shells require that the '#' be escaped with a backslash ('\'). Security policies may restrict uids to those listed in the password database. The sudoers policy allows uids that are not in the password database as long as the targetpw option is not set. Other security policies may not support this. -V The -V (version) option causes sudo to print its version string and the version string of the security policy plugin and any I/O plugins. If the invoking user is already root the -V option will display the arguments passed to configure when sudo was built and plugins may display more verbose information such as default options. -v When given the -v (validate) option, sudo will update the user's cached credentials, authenticating the user's password if necessary. For the sudoers plugin, this extends the sudo timeout for another 15 minutes (or whatever the timeout is set to in sudoers) but does not run a command. Not all security policies support cached credentials. -- The -- option indicates that sudo should stop processing command line arguments. Environment variables to be set for the command may also be passed on the command line in the form of VAR=value, e.g. LD_LIBRARY_PATH=/usr/local/pkg/lib. Variables passed on the command line are subject to the same restrictions as normal environment variables with one important exception. If the setenv option is set in sudoers, the command to be run has the SETENV tag set or the command matched is ALL, the user may set variables that would otherwise be forbidden. See sudoers(5) for more information. PLUGINS Plugins are dynamically loaded based on the contents of the /etc/sudo.conf file. If no /etc/sudo.conf file is present, or it contains no Plugin lines, sudo will use the traditional sudoers security policy and I/O logging, which corresponds to the following /etc/sudo.conf file. # # Default /etc/sudo.conf file # # Format: # Plugin plugin_name plugin_path plugin_options ... # Path askpass /path/to/askpass # Path noexec /path/to/sudo_noexec.so # Debug sudo /var/log/sudo_debug all@warn # Set disable_coredump true # # The plugin_path is relative to /usr/libexec unless # fully qualified. # The plugin_name corresponds to a global symbol in the plugin # that contains the plugin interface structure. # The plugin_options are optional. # Plugin policy_plugin sudoers.so Plugin io_plugin sudoers.so A Plugin line consists of the Plugin keyword, followed by the symbol_name and the path to the shared object containing the plugin. The symbol_name is the name of the struct policy_plugin or struct io_plugin in the plugin shared object. The path may be fully qualified or relative. If not fully qualified it is relative to the /usr/libexec directory. Any additional parameters after the path are passed as arguments to the plugin's open function. Lines that don't begin with Plugin, Path, Debug or Set are silently ignored. For more information, see the sudo_plugin(8) manual. PATHS A Path line consists of the Path keyword, followed by the name of the path to set and its value. E.g. Path noexec /usr/lib/sudo/sudo_noexec.so Path askpass /usr/X11R6/bin/ssh-askpass The following plugin-agnostic paths may be set in the /etc/sudo.conf file. askpass The fully qualified path to a helper program used to read the user's password when no terminal is available. This may be the case when sudo is executed from a graphical (as opposed to text-based) application. The program specified by askpass should display the argument passed to it as the prompt and write the user's password to the standard output. The value of askpass may be overridden by the SUDO_ASKPASS environment variable. noexec The fully-qualified path to a shared library containing dummy versions of the execv(), execve() and fexecve() library functions that just return an error. This is used to implement the noexec functionality on systems that support LD_PRELOAD or its equivalent. Defaults to /usr/lib/sudo/sudo_noexec.so. DEBUG FLAGS sudo versions 1.8.4 and higher support a flexible debugging framework that can help track down what sudo is doing internally if there is a problem. A Debug line consists of the Debug keyword, followed by the name of the program to debug (sudo, visudo, sudoreplay), the debug file name and a comma-separated list of debug flags. The debug flag syntax used by sudo and the sudoers plugin is subsystem@priority but the plugin is free to use a different format so long as it does not include a command ,. For instance: Debug sudo /var/log/sudo_debug all@warn,plugin@info would log all debugging statements at the warn level and higher in addition to those at the info level for the plugin subsystem. Currently, only one Debug entry per program is supported. The sudo Debug entry is shared by the sudo front end, sudoedit and the plugins. A future release may add support for per-plugin Debug lines and/or support for multiple debugging files for a single program. The priorities used by the sudo front end, in order of decreasing severity, are: crit, err, warn, notice, diag, info, trace and debug. Each priority, when specified, also includes all priorities higher than it. For example, a priority of notice would include debug messages logged at notice and higher. The following subsystems are used by sudo: all matches every subsystem args command line argument processing conv user conversation edit sudoedit exec command execution main sudo main function netif network interface handling pcomm communication with the plugin plugin plugin configuration pty pseudo-tty related code selinux SELinux-specific handling util utility functions utmp utmp handling RETURN VALUES Upon successful execution of a program, the exit status from sudo will simply be the exit status of the program that was executed. Otherwise, sudo exits with a value of 1 if there is a configuration/permission problem or if sudo cannot execute the given command. In the latter case the error string is printed to the standard error. If sudo cannot stat(2) one or more entries in the user's PATH, an error is printed on stderr. (If the directory does not exist or if it is not really a directory, the entry is ignored and no error is printed.) This should not happen under normal circumstances. The most common reason for stat(2) to return "permission denied" is if you are running an automounter and one of the directories in your PATH is on a machine that is currently unreachable. SECURITY NOTES sudo tries to be safe when executing external commands. To prevent command spoofing, sudo checks "." and "" (both denoting current directory) last when searching for a command in the user's PATH (if one or both are in the PATH). Note, however, that the actual PATH environment variable is not modified and is passed unchanged to the program that sudo executes. Please note that sudo will normally only log the command it explicitly runs. If a user runs a command such as sudo su or sudo sh, subsequent commands run from that shell are not subject to sudo's security policy. The same is true for commands that offer shell escapes (including most editors). If I/O logging is enabled, subsequent commands will have their input and/or output logged, but there will not be traditional logs for those commands. Because of this, care must be taken when giving users access to commands via sudo to verify that the command does not inadvertently give the user an effective root shell. For more information, please see the PREVENTING SHELL ESCAPES section in sudoers(5). To prevent the disclosure of potentially sensitive information, sudo disables core dumps by default while it is executing (they are re-enabled for the command that is run). To aid in debugging sudo crashes, you may wish to re-enable core dumps by setting "disable_coredump" to false in the /etc/sudo.conf file. Set disable_coredump false Note that by default, most operating systems disable core dumps from setuid programs, which includes sudo. To actually get a sudo core file you may need to enable core dumps for setuid processes. On BSD and Linux systems this is accomplished via the sysctl command, on Solaris the coreadm command can be used. ENVIRONMENT sudo utilizes the following environment variables. The security policy has control over the content of the command's environment. EDITOR Default editor to use in -e (sudoedit) mode if neither SUDO_EDITOR nor VISUAL is set MAIL In -i mode or when env_reset is enabled in sudoers, set to the mail spool of the target user HOME Set to the home directory of the target user if -i or -H are specified, env_reset or always_set_home are set in sudoers, or when the -s option is specified and set_home is set in sudoers PATH May be overridden by the security policy. SHELL Used to determine shell to run with -s option SUDO_ASKPASS Specifies the path to a helper program used to read the password if no terminal is available or if the -A option is specified. SUDO_COMMAND Set to the command run by sudo SUDO_EDITOR Default editor to use in -e (sudoedit) mode SUDO_GID Set to the group ID of the user who invoked sudo SUDO_PROMPT Used as the default password prompt SUDO_PS1 If set, PS1 will be set to its value for the program being run SUDO_UID Set to the user ID of the user who invoked sudo SUDO_USER Set to the login of the user who invoked sudo USER Set to the target user (root unless the -u option is specified) VISUAL Default editor to use in -e (sudoedit) mode if SUDO_EDITOR is not set FILES /etc/sudo.conf sudo front end configuration EXAMPLES Note: the following examples assume a properly configured security policy. To get a file listing of an unreadable directory: $ sudo ls /usr/local/protected To list the home directory of user yaz on a machine where the file system holding ~yaz is not exported as root: $ sudo -u yaz ls ~yaz To edit the index.html file as user www: $ sudo -u www vi ~www/htdocs/index.html To view system logs only accessible to root and users in the adm group: $ sudo -g adm view /var/log/syslog To run an editor as jim with a different primary group: $ sudo -u jim -g audio vi ~jim/sound.txt To shutdown a machine: $ sudo shutdown -r +15 "quick reboot" To make a usage listing of the directories in the /home partition. Note that this runs the commands in a sub-shell to make the cd and file redirection work. $ sudo sh -c "cd /home ; du -s * | sort -rn > USAGE" SEE ALSO grep(1), su(1), stat(2), passwd(5), sudoers(5), sudo_plugin(8), sudoreplay(8), visudo(8) AUTHORS Many people have worked on sudo over the years; this version consists of code written primarily by: Todd C. Miller See the CONTRIBUTORS file in the sudo distribution (http://www.sudo.ws/sudo/contributors.html) for a list of people who have contributed to sudo. HISTORY See the HISTORY file in the sudo distribution (http://www.sudo.ws/sudo/history.html) for a brief history of sudo. CAVEATS There is no easy way to prevent a user from gaining a root shell if that user is allowed to run arbitrary commands via sudo. Also, many programs (such as editors) allow the user to run commands via shell escapes, thus avoiding sudo's checks. However, on most systems it is possible to prevent shell escapes with the sudoers(5) module's noexec functionality. It is not meaningful to run the cd command directly via sudo, e.g., $ sudo cd /usr/local/protected since when the command exits the parent process (your shell) will still be the same. Please see the EXAMPLES section for more information. Running shell scripts via sudo can expose the same kernel bugs that make setuid shell scripts unsafe on some operating systems (if your OS has a /dev/fd/ directory, setuid shell scripts are generally safe). BUGS If you feel you have found a bug in sudo, please submit a bug report at http://www.sudo.ws/sudo/bugs/ SUPPORT Limited free support is available via the sudo-users mailing list, see http://www.sudo.ws/mailman/listinfo/sudo-users to subscribe or search the archives. DISCLAIMER sudo is provided ``AS IS'' and any express or implied warranties, including, but not limited to, the implied warranties of merchantability and fitness for a particular purpose are disclaimed. See the LICENSE file distributed with sudo or http://www.sudo.ws/sudo/license.html for complete details. 1.8.5 March 15, 2012 SUDO(8)


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A Zero Trust strategy requires that you verify explicitly, use least privileged access principles, and assume breach. Azure Active Directory can act as the policy decision point to enforce your access policies based on user, device, target resource, and environment insights.
To do this, we need to put Azure Active Directory in the path of every access request—connecting every user and every app or resource through this identity control plane. In addition to productivity gains and improved user experiences from single sign-on (SSO) and consistent policy guardrails, connecting all users and apps provides Azure AD with the signal to make the best possible decisions about the authentication/authorization risk.
Maintaining a healthy pipeline of your employees’ identities as well as the necessary security artifacts (groups for authorization and devices for extra access policy controls) puts you in the best place to use consistent identities and controls, which your on-premises and in the cloud users already benefit from. We strongly prefer an authentication method that primarily uses Azure AD (to provide you the best brute force, DDoS, and password spray protection).
SSO is not only a convenient feature for users, but it’s also a security posture, as it prevents users from leaving copies of their credentials in various apps and helps them avoid getting used to surrendering their credentials due to excessive prompting.
View a video version of the interactive guide (captions available in more languages).
Be sure to click the full-screen option in the video player. When you're done, use the Back arrow in your browser to come back to this page.
Once you have your users’ identities in Azure AD, you can use Azure AD to automate provisioning those user identities into your various cloud applications. G
Be sure to analyze the logs from Azure AD either in Azure or using a SIEM system of choice.
Once you have the Azure AD foundation in order, you can begin enacting the principles of Zero Trust.
First principle--verify explicitly--provide Azure AD with a rich set of credentials and controls that it can use to verify users:
Second principle--use least privilege access--use the following tools to give the right access at the right time:
Third principle--assume breach--consider configuring the following tools to protect your organization:
Within your organization, consider creating a Conditional Access policy requiring Azure Active Directory Multi-Factor Authentication for administrators for quick wins in your journey towards Zero Trust. To create a Conditional Access policy:
Within Azure AD, create a new Conditional Access policy with Directory roles targeted.
If your organization has a “break-glass” global administrator account, remember to add the account to the Exclude section. In the following screenshot, the global administrator role is selected. Consider also adding these roles:
For Cloud apps or actions, select All cloud apps:
Then under Conditions > Client apps (Preview), select Yes to also target apps that don’t use Modern Authentication:
Under Access controls, set Grant Access to Require Multi-factor authentication:
To enable Azure AD Identity Protection User risk and Sign-in risk policies to allow access but require self-service password reset or multi-factor authentication:
To create an Intune Mobile Application Management (MAM) without enrollment policy to protect organization data on mobile devices:
Within the Intune portal, select Client Apps -> App protection policies -> + Create policy -> your targeted platform:
After naming the policy, select from the list of available applications:
Under Data protection, select the controls you would like to implement. If the applications are already being used on mobile devices, consider limiting the amount of controls to reduce the amount of help-desk calls.
For iOS devices, consider the following settings:
Policy-managed apps are the ones selected in the previous step.
Note
“Encrypt org data” is set to Require by default, which will prompt a user to create a PIN (and enable TouchID/FaceID) to unlock their device if they have not done so already.
Under Access requirements, you can configure a PIN or sign-in for accessing the targeted applications, as well as a timeout to recheck for the PIN/sign-in:
Finally, configure conditional launch settings that further protect the data on the device. Consider leaving the default options.
Once all of the MAM protection settings have been configured, you must target Users who will receive the policy. With MAM policies, there is no end-user configuration required. The policy will automatically be applied when a user logs in to a targeted application on their mobile device. The end user will just see a notification that the application is protected:


In addition to holding office hours, I am also a Peer Tutor for SCI.
Below is a list of classes I tutor in:
(Per request, I will try my best to aid in other classes not on the list)
Private Tutoring
CS 0007: Introduction to Java Programming
CMPINF 0401: Intermediate Java Programming
CS 0441: Discrete Structures for CS
CS 0449: Introduction to Systems Software
CS 1501: Algorithms and Data Structures II
CS 1550: Introduction to Operating Systems
ECON 0100: Introduction to Microeconomic Theory
ECON 1100: Intermediate Microeconomics
ECON 1160: Financial Econometrics
STAT 1000: Applied Statistical Methods
STAT 1221: Applied Regression
STAT 1361: Statistical Learning and Data Science
MATH 0220: Analytical Geometry and Calculus I
MATH 0230: Analytical Geometry and Calculus II
MATH 0240: Analytical Geometry and Calculus III
MATH 0280/1180: Linear Algebra
MATH 0413: Introduction to Theoretical Mathematics
MATH 0420: Introduction to Theoretical 1-Variable Calculus
CMPINF 0401: Intermediate Java Programming
CS 0441: Discrete Structures for CS
CS 0449: Introduction to Systems Software
CS 1501: Algorithms and Data Structures II
CS 1550: Introduction to Operating Systems
ECON 0100: Introduction to Microeconomic Theory
ECON 1100: Intermediate Microeconomics
ECON 1160: Financial Econometrics
STAT 1000: Applied Statistical Methods
STAT 1221: Applied Regression
STAT 1361: Statistical Learning and Data Science
MATH 0220: Analytical Geometry and Calculus I
MATH 0230: Analytical Geometry and Calculus II
MATH 0240: Analytical Geometry and Calculus III
MATH 0280/1180: Linear Algebra
MATH 0413: Introduction to Theoretical Mathematics
MATH 0420: Introduction to Theoretical 1-Variable Calculus
Method of Communication:
Location:
I hold peer tutor hours at the following times:
TuTh: 10-11AM, 2:30-4:00PM, F: 1-3PM, SatSun: 4-6PM (Virtual on Zoom)
TuTh: 10-11AM, 2:30-4:00PM, F: 1-3PM, SatSun: 4-6PM (Virtual on Zoom)
Peer Tutor Hours are held in the CRC.
Zoom: https://pitt.zoom.us/s/4813388358
Zoom: https://pitt.zoom.us/s/4813388358
Send me an email:
<EMAIL_ADDRESS>Please note, that I may not respond immediately.
Be wary to not send messages after 12AM.
(I have school too!)
Be wary to not send messages after 12AM.
(I have school too!)


Protect the Antarctic Peninsula — before it’s too late
This article written by previous HB explorers (C.J. Hogg et al), proposes that banning fishing in warming coastal waters and limiting tourism and construction on land will help to protect marine mammals and seabirds. 289 HB participants were co-signatories to this article.


Man followed toddler to Berkeley library, tried to kidnap him, police say
by Katie DowdPublished 10:27 am PST, Thursday, November 21, 2019
A man has been charged with attempted kidnapping after trailing a toddler into a Berkeley library, police say.
As first reported by Berkeleyside, court records allege a nanny and a toddler under her care were at Bateman Park in Berkeley on Nov. 13 when they were approached by Marcus Deberry Jr., 28. Police told Berkeleyside the nanny took the boy to the Claremont branch of the Berkeley Public Library, but Deberry continued to follow them.
According to a library employee, Deberry said, "that's my baby" as he attempted to grab the child. He then allegedly left the library and was found by police who viewed surveillance video from the library.
MORE NEWS: Hundreds of protesters demonstrate in Berkeley against Ann Coulter appearance
Berkeleyside reports Deberry was already on probation for felony burglary.
Jail records indicate Deberry is in custody at the Santa Rita Jail. His bail is set at $105,000 and his plea hearing is scheduled for Nov. 27.
Katie Dowd is an SFGATE Senior Digital Editor. Contact<EMAIL_ADDRESS>| Twitter: @katiedowd


Class Jacobian
source code
Estimate Jacobian matrix, with error estimate
Parameters
----------
fun : callable
function to differentiate.
n : Integer from 1 to 4 defining derivative order. (Default 1)
order : Integer from 1 to 4 defining order of basic method used.
For 'central' methods, it must be from the set [2,4]. (Default 2)
method : Method of estimation. Valid options are:
'central', 'forward' or 'backward'. (Default 'central')
romberg_terms : Number of Romberg terms used in the extrapolation.
Must be an integer from 0 to 3. (Default 2)
Note: 0 disables the Romberg step completely.
step_fix : If not None, it will define the maximum excursion from step_nom
that is used and prevent the adaptive logic from working.
This will be considerably faster, but not necessarily
as accurate as allowing the adaptive logic to run.
(Default: None)
step_max : Maximum allowed excursion from step_nom as a multiple of it. (Default 4)
step_nom : Nominal step. default maximum(x0, 0.02)
step_ratio: Ratio used between sequential steps in the estimation
of the derivative (Default 2)
The steps used h_i = step_nom[i]*step_max*step_ratio**(-arange(steps_num))
step_num : integer
if not specified it will be set according to the following rules:
step_num = 26 if step_fix is None
step_num = 3.+ np.ceil(self.n/2.) + self.order + self.romberg_terms +4 otherwise
vectorized : True - if your function is vectorized.
False - loop over the successive function calls (default).
Uses a semi-adaptive scheme to provide the best estimate of the
derivative by its automatic choice of a differencing interval. It uses
finite difference approximations of various orders, coupled with a
generalized (multiple term) Romberg extrapolation. This also yields the
error estimate provided. See the document DERIVEST.pdf for more explanation
of the algorithms behind the parameters.
Note on order: higher order methods will generally be more accurate,
but may also suffer more from numerical problems. First order
methods would usually not be recommended.
Note on method: Central difference methods are usually the most accurate,
but sometimes one can only allow evaluation in forward or backward
direction.
The Jacobian matrix is the matrix of all first-order partial derivatives
of a vector-valued function.
Assumptions
-----------
fun : (vector valued)
analytical function to differentiate.
fun must be a function of the vector or array x0.
x0 : vector location at which to differentiate fun
If x0 is an N x M array, then fun is assumed to be
a function of N*M variables.
Examples
--------
>>> import numpy as np
>>> import numdifftools as nd
#(nonlinear least squares)
>>> xdata = np.reshape(np.arange(0,1,0.1),(-1,1))
>>> ydata = 1+2*np.exp(0.75*xdata)
>>> fun = lambda c: (c[0]+c[1]*np.exp(c[2]*xdata) - ydata)**2
>>> Jfun = nd.Jacobian(fun)
>>> h = Jfun([1., 2., 0.75]) # should be numerically zero
>>> np.abs(h) < 1e-14
array([[ True, True, True],
[ True, True, True],
[ True, True, True],
[ True, True, True],
[ True, True, True],
[ True, True, True],
[ True, True, True],
[ True, True, True],
[ True, True, True],
[ True, True, True]], dtype=bool)
>>> np.abs(h) <= 2 * Jfun.error_estimate
array([[ True, True, True],
[ True, True, True],
[ True, True, True],
[ True, True, True],
[ True, True, True],
[ True, True, True],
[ True, True, True],
[ True, True, True],
[ True, True, True],
[ True, False, True]], dtype=bool)
See also
--------
Gradient,
Derivative,
Hessdiag,
Hessian
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jacobian(self,
x00)
Return Jacobian matrix of a vector valued function of n variables |
source code
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Inherited from _Derivative :
__init__
Inherited from _Derivative (private):
_backward ,
_central ,
_check_params ,
_derivative ,
_fda_mat ,
_fder ,
_forward ,
_initialize ,
_romb_extrap ,
_set_delta ,
_set_difference_function ,
_set_fda_rule ,
_set_romb_qr ,
_trim_estimates
Inherited from object :
__delattr__ ,
__format__ ,
__getattribute__ ,
__hash__ ,
__new__ ,
__reduce__ ,
__reduce_ex__ ,
__repr__ ,
__setattr__ ,
__sizeof__ ,
__str__ ,
__subclasshook__
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_jacob_txt = ' \n Parameters\n ----------\n fun : call ...
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__doc__ = '''Estimate Jacobian matrix, with error estima...
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Inherited from object :
__class__
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Return Jacobian matrix of a vector valued function of n variables
Parameter
---------
x0 : vector
location at which to differentiate fun.
If x0 is an nxm array, then fun is assumed to be
a function of n*m variables.
Member variable used
--------------------
fun : (vector valued) analytical function to differentiate.
fun must be a function of the vector or array x0.
Returns
-------
jac : array-like
first partial derivatives of fun. Assuming that x0
is a vector of length p and fun returns a vector
of length n, then jac will be an array of size (n,p)
err - vector
of error estimates corresponding to each partial
derivative in jac.
See also
--------
Derivative,
Gradient,
Hessian,
Hessdiag
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_jacob_txt
- Value:
'''
Parameters
----------
fun : callable
function to differentiate.
n : Integer from 1 to 4 defining derivative order. (Default 1)
order : Integer from 1 to 4 defining order of basic method used.
For \'central\' methods, it must be from the set [2,4]. (D
...
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__doc__
- Value:
'''Estimate Jacobian matrix, with error estimate
'''+ _jacob_txt+ '''
The Jacobian matrix is the matrix of all first-order partial deriv
atives
of a vector-valued function.
Assumptions
...
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