Red Dead Redemption 2 is an open world game that follows Arthur Morgan and his adventures with the Van der Linde Gang. It takes place in the Old West in 1899.
Another fun open world game. In Ark: Survival Evolved, you spawn in with nothing and gather resources and items to make your way up to the top. You can also tame and interact with tons of different dinosaurs.
A relaxing game that can be played casually or competitively. It's like soccer except with rocket-powered cars instead of players.
Dungeon crawler style game mixed with elements of Minecraft. Kill enemies to progress through levels and obtain higher level weapons and gear. Fun twist on the usual Minecraft experience.


Example:
cond(x1) && cond(x2) ^ cond(x3) && cond(x4);
Use the field to specify the maximum number of terms allowed in a boolean expression.
Use the checkbox to ignore boolean expressions which use only a single boolean operator repeatedly.


Be sure to follow along with the examples by clicking the "edit" link in the corner. See what the tool says, try your own formulas, and experiment!
Z3 is a state-of-the art theorem prover from Microsoft Research. It can be used to check the satisfiability of logical formulas over one or more theories. Z3 offers a compelling match for software analysis and verification tools, since several common software constructs map directly into supported theories.
The main objective of the tutorial is to introduce the reader on how to use Z3 effectively for logical modeling and solving. The tutorial provides some general background on logical modeling, but we have to defer a full introduction to first-order logic and decision procedures to text-books.
Z3 is a low level tool. It is best used as a component in the context of other tools that require solving logical formulas. Consequently, Z3 exposes a number of API facilities to make it convenient for tools to map into Z3, but there are no stand-alone editors or user-centric facilities for interacting with Z3. The language syntax used in the front ends favor simplicity in contrast to linguistic convenience.
The Z3 input format is an extension of the one defined by the SMT-LIB 2.0 standard. A Z3 script is a sequence of commands. The help command displays a list of all available commands. The command echo displays a message. Internally, Z3 maintains a stack of user provided formulas and declarations. We say these are the assertions provided by the user. The command declare-const declares a constant of a given type (aka sort). The command declare-fun declares a function. In the following example, we declared a function that receives an integer and a boolean, and returns an integer.
(echo "starting Z3...") (declare-const a Int) (declare-fun f (Int Bool) Int)
The command assert adds a formula into the Z3 internal stack. We say the set of formulas in the Z3 stack is satisfiable if there is an interpretation (for the user declared constants and functions) that makes all asserted formulas true.
(declare-const a Int) (declare-fun f (Int Bool) Int) (assert (> a 10)) (assert (< (f a true) 100)) (check-sat)
The first asserted formula states that the constant a must be greater than 10. The second one states that the function f applied to a and true must return a value less than 100. The command check-sat determines whether the current formulas on the Z3 stack are satisfiable or not. If the formulas are satisfiable, Z3 returns sat. If they are not satisfiable (i.e., they are unsatisfiable), Z3 returns unsat. Z3 may also return unknown when it can't determine whether a formula is satisfiable or not.
When the command check-sat returns sat, the command get-model can be used to retrieve an interpretation that makes all formulas on the Z3 internal stack true.
(declare-const a Int) (declare-fun f (Int Bool) Int) (assert (> a 10)) (assert (< (f a true) 100)) (check-sat) (get-model)
The interpretation is provided using definitions. For example, the definition:
(define-fun a () Int [val])
states that the value of a in the model is [val]. The definition:
(define-fun f ((x!1 Int) (x!2 Bool)) Int ... )
is very similar to a function definition used in programming languages. In this example, x1 and x2 are the arguments of the function interpretation created by Z3. For this simple example, the definition of f is based on ite's (aka if-then-elses or conditional expressions). For example, the expression:
(ite (and (= x!1 11) (= x!2 false)) 21 0)
evaluates (returns) 21 when x!1 is equal to 11, and x!2 is equal to false. Otherwise, it returns 0.
In some applications, we want to explore several similar problems that share several definitions and assertions. We can use the commands push and pop for doing that. Z3 maintains a global stack of declarations and assertions. The command push creates a new scope by saving the current stack size. The command pop removes any assertion or declaration performed between it and the matching push. The check-sat and get-assertions commands always operate on the content of the global stack.
In the following example, the command (assert p) signs an error because the pop command removed the declaration for p. If the last pop command is removed, then the error is corrected.
(declare-const x Int) (declare-const y Int) (declare-const z Int) (push) (assert (= (+ x y) 10)) (assert (= (+ x (* 2 y)) 20)) (check-sat) (pop) ; remove the two assertions (push) (assert (= (+ (* 3 x) y) 10)) (assert (= (+ (* 2 x) (* 2 y)) 21)) (check-sat) (declare-const p Bool) (pop) (assert p) ; error, since declaration of p was removed from the stack
The push and pop commands can optionally receive a numeral argument as specifed by the SMT 2 language.
The command set-option is used to configure Z3. Z3 has several options to control its behavior. Some of these options (e.g., :produce-proofs) can only be set before any declaration or assertion. We use the reset command to erase all assertions and declarations. After the reset command, all configuration options can be set.
(set-option :print-success true) (set-option :produce-unsat-cores true) ; enable generation of unsat cores (set-option :produce-models true) ; enable model generation (set-option :produce-proofs true) ; enable proof generation (declare-const x Int) (set-option :produce-proofs false) ; error, cannot change this option after a declaration or assertion (echo "before reset") (reset) (set-option :produce-proofs false) ; ok
The option :print-success true is particularly useful when Z3 is being controlled by another application using pipes. In this mode, commands, that otherwise would not print any output, will print success.
The command (display t) just applies the Z3 pretty printer to the given expression. The command (simplify t) displays a possibly simpler expression equivalent to t. This command accepts many different options, (help simplify) will display all available options.
(declare-const a (Array Int Int)) (declare-const x Int) (declare-const y Int) (display (+ x 2 x 1)) (simplify (+ x 2 x 1)) (simplify (* (+ x y) (+ x y))) (simplify (* (+ x y) (+ x y)) :som true) ; put all expressions in sum-of-monomials form. (simplify (= x (+ y 2)) :arith-lhs true) (simplify (= (store (store a 1 2) 4 3) (store (store a 4 3) 1 2))) (simplify (= (store (store a 1 2) 4 3) (store (store a 4 3) 1 2)) :sort-store true) (help simplify)
The define-sort command defines a new sort symbol that is an abbreviation for a sort expression. The new sort symbol can be parameterized, in which case the names of the parameters are specified in the command and the sort expression uses the sort parameters. The form of the command is this:
(define-sort [symbol] ([symbol]+) [sort])
The following example defines several abbreviations for sort expressions.
(define-sort Set (T) (Array T Bool)) (define-sort IList () (List Int)) (define-sort List-Set (T) (Array (List T) Bool)) (define-sort I () Int) (declare-const s1 (Set I)) (declare-const s2 (List-Set Int)) (declare-const a I) (declare-const l IList) (assert (= (select s1 a) true)) (assert (= (select s2 l) false)) (check-sat) (get-model)
The pre-defined sort
(declare-const p Bool) (declare-const q Bool) (declare-const r Bool) (define-fun conjecture () Bool (=> (and (=> p q) (=> q r)) (=> p r))) (assert (not conjecture)) (check-sat)
A formula F is valid if F always evaluates to true for any assignment of appropriate values to its uninterpreted function and constant symbols. A formula F is satisfiable if there is some assignment of appropriate values to its uninterpreted function and constant symbols under which F evaluates to true. Validity is about finding a proof of a statement; satisfiability is about finding a solution to a set of constraints. Consider a formula F with some uninterpreted constants, say a and b. We can ask whether F is valid, that is whether it is always true for any combination of values for a and b. If F is always true, then not F is always false, and then not F will not have any satisfying assignment; that is, not F is unsatisfiable. That is, F is valid precisely when not F is not satisfiable (is unsatisfiable). Alternately, F is satisfiable if and only if not F is not valid (is invalid). Z3 finds satisfying assignments (or report that there are none). To determine whether a formula F is valid, we ask Z3 whether not F is satisfiable. Thus, to check the deMorgan's law is valid (i.e., to prove it), we show its negation to be unsatisfiable.
(declare-const a Bool) (declare-const b Bool) (define-fun demorgan () Bool (= (and a b) (not (or (not a) (not b))))) (assert (not demorgan)) (check-sat)
The basic building blocks of SMT formulas are constants and functions. Constants are just functions that take no arguments. So everything is really just a function.
(declare-fun f (Int) Int) (declare-fun a () Int) ; a is a constant (declare-const b Int) ; syntax sugar for (declare-fun b () Int) (assert (> a 20)) (assert (> b a)) (assert (= (f 10) 1)) (check-sat) (get-model)
Unlike programming languages, where functions have side-effects, can throw exceptions, or never return, functions in classical first-order logic have no side-effects and are total. That is, they are defined on all input values. This includes functions, such as division.
Function and constant symbols in pure first-order logic are uninterpreted or free, which means that no a priori interpretation is attached. This is in contrast to functions belonging to the signature of theories, such as arithmetic where the function + has a fixed standard interpretation (it adds two numbers). Uninterpreted functions and constants are maximally flexible; they allow any interpretation that is consistent with the constraints over the function or constant.
To illustrate uninterpreted functions and constants let us introduce an (uninterpreted) sort A, and the constants x, y ranging over A. Finally let f be an uninterpreted function that takes one argument of sort A and results in a value of sort A. The example illustrates how one can force an interpretation where f applied twice to x results in x again, but f applied once to x is different form x.
(declare-sort A) (declare-const x A) (declare-const y A) (declare-fun f (A) A) (assert (= (f (f x)) x)) (assert (= (f x) y)) (assert (not (= x y))) (check-sat) (get-model)
The resulting model introduces abstract values for the elements in A, because the sort A is uninterpreted. The interpretation for f in the model toggles between the two values for x and y, which are different.
Z3 has builtin support for integer and real constants. This two types should not be confused with machine integers (32-bit or 64-bit) and floating point numbers. These two types (sorts) represent the mathematical integers and reals. The command declare-const is used to declare integer and real constants.
(declare-const a Int) (declare-const b Int) (declare-const c Int) (declare-const d Real) (declare-const e Real)
After constants are declared, the user can assert.smt formulas containing these constants. The formulas contain arithmetic operators such as: +, -, <, and so on. The command check-sat will instruct Z3 to try to find an interpretation for the declared constants that makes all formulas true. The interpretation is basically assigning a number to each constant. If such interpretation exists, we say it is a model for the asserted formulas. The command get-model displays the model built by Z3.
(declare-const a Int) (declare-const b Int) (declare-const c Int) (declare-const d Real) (declare-const e Real) (assert (> a (+ b 2))) (assert (= a (+ (* 2 c) 10))) (assert (<= (+ c b) 1000)) (assert (>= d e)) (check-sat) (get-model)
Real constants should contain a decimal point. Unlike most programming languages, Z3 will not convert automatically integers into reals and vice-versa. The function to-real can be used to convert an integer expression into a real one.
(declare-const a Int) (declare-const b Int) (declare-const c Int) (declare-const d Real) (declare-const e Real) (assert (> e (+ (to_real (+ a b)) 2.0))) (assert (= d (+ (to_real c) 0.5))) (assert (> a b)) (check-sat) (get-model)
We say a formula is nonlinear if it contains expressions of the form (* t s) where t and s are not numbers. Nonlinear real arithmetic is very expensive, and Z3 is not complete for this kind of formula. The command check-sat may return unknown or loop. Nonlinear integer arithmetic is undecidable: there is no procedure that is correct and terminates (for every input) with a sat or unsat answer. Yes, it is impossible to build such procedure. Note that, this does not prevent Z3 from returning an answer for many nonlinear problems. The real limit is that there will always be a nonlinear integer arithmetic formula that it will fail produce an answer.
(declare-const a Int) (assert (> (* a a) 3)) (check-sat) (get-model) (echo "Z3 does not always find solutions to non-linear problems") (declare-const b Real) (declare-const c Real) (assert (= (+ (* b b b) (* b c)) 3.0)) (check-sat) (echo "yet it can show unsatisfiabiltiy for some nontrivial nonlinear problems...") (declare-const x Real) (declare-const y Real) (declare-const z Real) (assert (= (* x x) (+ x 2.0))) (assert (= (* x y) x)) (assert (= (* (- y 1.0) z) 1.0)) (check-sat) (reset) (echo "When presented only non-linear constraints over reals, Z3 uses a specialized complete solver") (declare-const b Real) (declare-const c Real) (assert (= (+ (* b b b) (* b c)) 3.0)) (check-sat) (get-model)
Z3 also has support for division, integer division, modulo and remainder operators. Internally, they are all mapped to multiplication.
(declare-const a Int) (declare-const r1 Int) (declare-const r2 Int) (declare-const r3 Int) (declare-const r4 Int) (declare-const r5 Int) (declare-const r6 Int) (assert (= a 10)) (assert (= r1 (div a 4))) ; integer division (assert (= r2 (mod a 4))) ; mod (assert (= r3 (rem a 4))) ; remainder (assert (= r4 (div a (- 4)))) ; integer division (assert (= r5 (mod a (- 4)))) ; mod (assert (= r6 (rem a (- 4)))) ; remainder (declare-const b Real) (declare-const c Real) (assert (>= b (/ c 3.0))) (assert (>= c 20.0)) (check-sat) (get-model)
In Z3, division by zero is allowed, but the result is not specified. Division is not a partial function. Actually, in Z3 all functions are total, although the result may be underspecified in some cases like division by zero.
(declare-const a Real) ; The following formula is satisfiable since division by zero is not specified. (assert (= (/ a 0.0) 10.0)) (check-sat) (get-model) ; Although division by zero is not specified, division is still a function. ; So, (/ a 0.0) cannot evaluated to 10.0 and 2.0. (assert (= (/ a 0.0) 2.0)) (check-sat)
If you are not happy with this behavior, you may use ite (if-then-else) operator to guard every division, and assign whatever intepretation you like to the division by zero. This example uses define-fun constructor to create a new operator: mydiv. This is essentially a macro, and Z3 will expand its definition for every application of mydiv.
; defining my own division operator where x/0.0 == 0.0 for every x. (define-fun mydiv ((x Real) (y Real)) Real (if (not (= y 0.0)) (/ x y) 0.0)) (declare-const a Real) (declare-const b Real) (assert (>= (mydiv a b) 1.0)) (assert (= b 0.0)) (check-sat)
Modern CPUs and main-stream programming languages use arithmetic over fixed-size bit-vectors. The theory of bit-vectors allows modeling the precise semantics of unsigned and of signed two-complements arithmetic.  They are summarized on Z3's on-line documentation of the binary APIs and they are summarized on the SMT-LIB web-site. We will not try to give a comprehensive overview here, but touch on some of the main features.
In contrast to programming languages, such as C, C++, C#, Java, there is no distinction between signed and unsigned bit-vectors as numbers. Instead, the theory of bit-vectors provides special signed versions of arithmetical operations where it makes a difference whether the bit-vector is treated as signed or unsigned.
Z3 supports Bitvectors of arbitrary size. (_ BitVec n) is the sort of bitvectors whose length is n. Bitvector literals may be defined using binary, decimal and hexadecimal notation. In the binary and hexadecimal cases, the bitvector size is inferred from the number of characters. For example, the bitvector literal #b010 in binary format is a bitvector of size 3, and the bitvector literal #x0a0 in hexadecimal format is a bitvector of size 12. The size must be specified for bitvector literals in decimal format. For example, (_ bv10 32) is a bitvector of size 32 that representes the numeral 10. By default, Z3 display bitvectors in hexadecimal format if the bitvector size is a multiple of 4, and in binary otherwise. The command (set-option :pp.bv-literals false) can be used to force Z3 to display bitvector literals in decimal format.
(display #b0100) (display (_ bv20 8)) (display (_ bv20 7)) (display #x0a) (set-option :pp.bv-literals false) (display #b0100) (display (_ bv20 8)) (display (_ bv20 7)) (display #x0a)
(simplify (bvadd #x07 #x03)) ; addition (simplify (bvsub #x07 #x03)) ; subtraction (simplify (bvneg #x07)) ; unary minus (simplify (bvmul #x07 #x03)) ; multiplication (simplify (bvurem #x07 #x03)) ; unsigned remainder (simplify (bvsrem #x07 #x03)) ; signed remainder (simplify (bvsmod #x07 #x03)) ; signed modulo (simplify (bvshl #x07 #x03)) ; shift left (simplify (bvlshr #xf0 #x03)) ; unsigned (logical) shift right (simplify (bvashr #xf0 #x03)) ; signed (arithmetical) shift right
(simplify (bvor #x6 #x3)) ; bitwise or (simplify (bvand #x6 #x3)) ; bitwise and (simplify (bvnot #x6)) ; bitwise not (simplify (bvnand #x6 #x3)) ; bitwise nand (simplify (bvnor #x6 #x3)) ; bitwise nor (simplify (bvxnor #x6 #x3)) ; bitwise xnor
We can prove a bitwise version of deMorgan's law:
(declare-const x (_ BitVec 64)) (declare-const y (_ BitVec 64)) (assert (not (= (bvand (bvnot x) (bvnot y)) (bvnot (bvor x y))))) (check-sat)
Let us illustrate a simple property of bit-wise arithmetic. There is a fast way to check that fixed size numbers are powers of two. It turns out that a bit-vector x is a power of two or zero if and only if x & (x - 1) is zero, where & represents the bitwise and. We check this for four bits below.
(define-fun is-power-of-two ((x (_ BitVec 4))) Bool (= #x0 (bvand x (bvsub x #x1)))) (declare-const a (_ BitVec 4)) (assert (not (= (is-power-of-two a) (or (= a #x0) (= a #x1) (= a #x2) (= a #x4) (= a #x8))))) (check-sat)
(simplify (bvule #x0a #xf0)) ; unsigned less or equal (simplify (bvult #x0a #xf0)) ; unsigned less than (simplify (bvuge #x0a #xf0)) ; unsigned greater or equal (simplify (bvugt #x0a #xf0)) ; unsigned greater than (simplify (bvsle #x0a #xf0)) ; signed less or equal (simplify (bvslt #x0a #xf0)) ; signed less than (simplify (bvsge #x0a #xf0)) ; signed greater or equal (simplify (bvsgt #x0a #xf0)) ; signed greater than
Signed comparison, such as bvsle, takes the sign bit of bitvectors into account for comparison, while unsigned comparison treats the bitvector as unsigned (treats the bitvector as a natural number).
(declare-const a (_ BitVec 4)) (declare-const b (_ BitVec 4)) (assert (not (= (bvule a b) (bvsle a b)))) (check-sat) (get-model)
As part of formulating a programme of a mathematical theory of computation McCarthy proposed a basic theory of arrays as characterized by the select-store axioms. The expression (select a i) returns the value stored at position i of the array a; and (store a i v) returns a new array identical to a, but on position i it contains the value v.
Z3 contains a decision procedure for the basic theory of arrays. By default, Z3 assumes that arrays are extensional over select. In other words, Z3 also enforces that if two arrays agree on all reads, then the arrays are equal.
It also contains various extensions for operations on arrays that remain decidable and amenable to efficient saturation procedures (here efficient means, with an NP-complete satisfiability complexity). We describe these extensions in the following using a collection of examples. Additional background on these extensions is available in the paper Generalized and Efficient Array Decision Procedures.
Let us first check a basic property of arrays. Suppose a1 is an array of integers, then the constraint (and (= (select a1 x) x) (= (store a1 x y) a1)) is satisfiable for an array that contains an index x that maps to x, and when x = y (because the first equality forced the range of x to be x). We can check this constraint.
(declare-const x Int) (declare-const y Int) (declare-const z Int) (declare-const a1 (Array Int Int)) (declare-const a2 (Array Int Int)) (declare-const a3 (Array Int Int)) (assert (= (select a1 x) x)) (assert (= (store a1 x y) a1)) (check-sat) (get-model)
On the other hand, the constraints become unsatisfiable when asserting (not (= x y)).
(declare-const x Int) (declare-const y Int) (declare-const z Int) (declare-const a1 (Array Int Int)) (declare-const a2 (Array Int Int)) (declare-const a3 (Array Int Int)) (assert (= (select a1 x) x)) (assert (= (store a1 x y) a1)) (assert (not (= x y))) (check-sat)
The array that maps all indices to some fixed value can be specified in Z3 using the const construct. It takes one value from the range type of the array and creates an array. Z3 cannot infer what kind of array must be returned by the const construct by just inspecting the argument type. Thus, a qualified identifier (as const (Array T1 T2)) must be used. The following example defines a constant array containing only ones.
(declare-const all1 (Array Int Int)) (declare-const a Int) (declare-const i Int) (assert (= all1 ((as const (Array Int Int)) 1))) (assert (= a (select all1 i))) (check-sat) (get-model) (assert (not (= a 1))) (check-sat)
Models provide interpretations of the uninterpreted (aka free) constants and functions that appear in the satisfiable formula. An interpretation for arrays is very similar to the interpretation of a function. Z3 uses the construct (_ as-array f) to give the interpretation for arrays. If the array a is equal to (_ as-array f), then for every index i, (select a i) is equal to (f i). In the previous example, Z3 creates the auxiliary function k!0 to assign an interpretation to the array constant all1.
In the following, we will simulate basic Boolean algebra (set theory) using the array theory extensions in Z3. Z3 provides a parametrized map function on arrays. It allows applying arbitrary functions to the range of arrays. The following example illustrates how to use the map function.
(define-sort Set (T) (Array T Bool)) (declare-const a (Set Int)) (declare-const b (Set Int)) (declare-const c (Set Int)) (declare-const x Int) (push) (assert (not (= ((_ map and) a b) ((_ map not) ((_ map or) ((_ map not) b) ((_ map not) a)))))) (check-sat) (pop) (push) (assert (and (select ((_ map and) a b) x) (not (select a x)))) (check-sat) (pop) (push) (assert (and (select ((_ map or) a b) x) (not (select a x)))) (check-sat) (get-model) (assert (and (not (select b x)))) (check-sat)
We can use the parametrized map function to encode finite sets and finite bags. Finite bags can be modeled similarly to sets. A bag is here an array that maps elements to their multiplicity. Main bag operations include union, obtained by adding multiplicity, intersection, by taking the minimum multiplicity, and a dual join operation that takes the maximum multiplicity. In the following example, we define the bag-union using map. Notice that we need to specify the full signature of + since it is an overloaded operator.
(define-sort A () (Array Int Int Int)) (define-fun bag-union ((x A) (y A)) A ((_ map (+ (Int Int) Int)) x y)) (declare-const s1 A) (declare-const s2 A) (declare-const s3 A) (assert (= s3 (bag-union s1 s2))) (assert (= (select s1 0 0) 5)) (assert (= (select s2 0 0) 3)) (assert (= (select s2 1 2) 4)) (check-sat) (get-model)
Algebraic datatypes, known from programming languages such as ML, offer a convenient way for specifying common data structures. Records and tuples are special cases of algebraic datatypes, and so are scalars (enumeration types). But algebraic datatypes are more general. They can be used to specify finite lists, trees and other recursive structures.
A record is specified as a datatype with a single constructor and as many arguments as record elements. The number of arguments to a record are always the same. The type system does not allow to extend records and there is no record subtyping.
The following example illustrates that two records are equal only if all the arguments are equal. It introduces the parametric type Pair, with constructor mk-pair and two arguments that can be accessed using the selector functions first and second.
(declare-datatypes (T1 T2) ((Pair (mk-pair (first T1) (second T2))))) (declare-const p1 (Pair Int Int)) (declare-const p2 (Pair Int Int)) (assert (= p1 p2)) (assert (> (second p1) 20)) (check-sat) (get-model) (assert (not (= (first p1) (first p2)))) (check-sat)
A scalar sort is a finite domain sort. The elements of the finite domain are enumerated as distinct constants. For example, the sort S is a scalar type with three values A, B and C. It is possible for three constants of sort S to be distinct, but not for four constants.
(declare-datatypes () ((S A B C))) (declare-const x S) (declare-const y S) (declare-const z S) (declare-const u S) (assert (distinct x y z)) (check-sat) (assert (distinct x y z u)) (check-sat)
A recursive datatype declaration includes itself directly (or indirectly) as a component. A standard example of a recursive data-type is the one of lists. A parametric list can be specified in Z3 as:
(declare-datatypes (T) ((Lst nil (cons (hd T) (tl Lst))))) (declare-const l1 (Lst Int)) (declare-const l2 (Lst Bool))
The List recursive datatype is builtin in Z3. The empty list is nil, and the constructor insert is used to build new lists. The accessors head and tail are defined as usual.
(declare-const l1 (List Int)) (declare-const l2 (List Int)) (declare-const l3 (List Int)) (declare-const x Int) (assert (not (= l1 nil))) (assert (not (= l2 nil))) (assert (= (head l1) (head l2))) (assert (not (= l1 l2))) (assert (= l3 (insert x l2))) (assert (> x 100)) (check-sat) (get-model) (assert (= (tail l1) (tail l2))) (check-sat)
In the example above, we also assert that l1 and l2 are not nil. This is because the interpretation of head and tail is underspecified on nil. So then head and tail would not be able to distinguish nil from (insert (head nil) (tail nil)).
You can also specify mutually recursive datatypes for Z3. We list one example below.
; declare a mutually recursive parametric datatype (declare-datatypes (T) ((Tree leaf (node (value T) (children TreeList))) (TreeList nil (cons (car Tree) (cdr TreeList))))) (declare-const t1 (Tree Int)) (declare-const t2 (Tree Bool)) ; we must use the 'as' construct to distinguish the leaf (Tree Int) from leaf (Tree Bool) (assert (not (= t1 (as leaf (Tree Int))))) (assert (> (value t1) 20)) (assert (not (is-leaf t2))) (assert (not (value t2))) (check-sat) (get-model)
In the example above, we have a tree of Booleans and a tree of integers. The leaf constant must return a tree of a specific sort. To specify the result sort, we use the qualified identifier (as leaf (Tree Int)). Note that, we do not need to use a qualified identifer for value, since Z3 can infer the intended declaration using the sort of the argument.
The ground decision procedures for recursive datatypes don't lift to establishing inductive facts. Z3 does not contain methods for producing proofs by induction. This may change in the future. In particular, consider the following example where the function p is true on all natural numbers, which can be proved by induction over Nat. Z3 enters a matching loop as it attempts instantiating the universally quantified implication.
(set-option :timeout 2000) (declare-datatypes () ((Nat zero (succ (pred Nat))))) (declare-fun p (Nat) Bool) (assert (p zero)) (assert (forall ((x Nat)) (implies (p (pred x)) (p x)))) (assert (not (forall ((x Nat)) (p x)))) (check-sat) (get-info :all-statistics)
Z3 is a decision procedure for the combination of the previous quantifier-free theories. That is, it can answer whether a quantifier-free formula, modulo the theories referenced by the formula, is satisfiable or whether it is unsatisfiable. Z3 also accepts and can work with formulas that use quantifiers. It is no longer a decision procedure for such formulas in general (and for good reasons, as there can be no decision procedure for first-order logic).
Nevertheless, Z3 is often able to handle formulas involving quantifiers. It uses several approaches to handle quantifiers. The most prolific approach is using pattern-based quantifier instantiation. This approach allows instantiating quantified formulas with ground terms that appear in the current search context based on pattern annotations on quantifiers. Another approach is based on saturation theorem proving using a superposition calculus which is a modern method for applying resolution style rules with equalities. The pattern-based instantiation method is quite effective, even though it is inherently incomplete. The saturation based approach is complete for pure first-order formulas, but does not scale as nicely and is harder to predict.
Z3 also contains a model-based quantifier instantiation component that uses a model construction to find good terms to instantiate quantifiers with; and Z3 also handles many decidable fragments.
Suppose we want to model an object oriented type system with single inheritance. We would need a predicate for sub-typing. Sub-typing should be a partial order, and respect single inheritance. For some built-in type constructors, such as for array-of, sub-typing should be monotone.
(declare-sort Type) (declare-fun subtype (Type Type) Bool) (declare-fun array-of (Type) Type) (assert (forall ((x Type)) (subtype x x))) (assert (forall ((x Type) (y Type) (z Type)) (=> (and (subtype x y) (subtype y z)) (subtype x z)))) (assert (forall ((x Type) (y Type)) (=> (and (subtype x y) (subtype y x)) (= x y)))) (assert (forall ((x Type) (y Type) (z Type)) (=> (and (subtype x y) (subtype x z)) (or (subtype y z) (subtype z y))))) (assert (forall ((x Type) (y Type)) (=> (subtype x y) (subtype (array-of x) (array-of y))))) (declare-const root-type Type) (assert (forall ((x Type)) (subtype x root-type))) (check-sat)
The Stanford Pascal verifier and the subsequent Simplify theorem prover pioneered the use of pattern-based quantifier instantiation. The basic idea behind pattern-based quantifier instantiation is in a sense straight-forward: Annotate a quantified formula using a pattern that contains all the bound variables. So a pattern is an expression (that does not contain binding operations, such as quantifiers) that contains variables bound by a quantifier. Then instantiate the quantifier whenever a term that matches the pattern is created during search. This is a conceptually easy starting point, but there are several subtleties that are important.
In the following example, the first two options make sure that Model-based quantifier instantiation and saturation engines are disabled. We also annotate the quantified formula with the pattern (f (g x)). Since there is no ground instance of this pattern, the quantifier is not instantiated, and Z3 fails to show that the formula is unsatisfiable.
(set-option :smt.auto-config false) ; disable automatic self configuration (set-option :smt.mbqi false) ; disable model-based quantifier instantiation (declare-fun f (Int) Int) (declare-fun g (Int) Int) (declare-const a Int) (declare-const b Int) (declare-const c Int) (assert (forall ((x Int)) (! (= (f (g x)) x) :pattern ((f (g x)))))) (assert (= (g a) c)) (assert (= (g b) c)) (assert (not (= a b))) (check-sat)
When the more permissive pattern (g x) is used. Z3 proves the formula to be unsatisfiable. More restrive patterns minimize the number of instantiations (and potentially improve performance), but they may also make Z3 "less complete".
(set-option :smt.auto-config false) ; disable automatic self configuration (set-option :smt.mbqi false) ; disable model-based quantifier instantiation (declare-fun f (Int) Int) (declare-fun g (Int) Int) (declare-const a Int) (declare-const b Int) (declare-const c Int) (assert (forall ((x Int)) (! (= (f (g x)) x) :pattern ((g x))))) (assert (= (g a) c)) (assert (= (g b) c)) (assert (not (= a b))) (check-sat)
Some patterns may also create long instantiation chains. Consider the following assertion.
(assert (forall (x Type) (y Type) (! (=> (subtype x y) (subtype (array-of x) (array-of y))) :pattern ((subtype x y)) ))
The axiom gets instantiated whenever there is some ground term of the form (subtype s t). The instantiation causes a fresh ground term (subtype (array-of s) (array-of t)), which enables a new instantiation. This undesirable situation is called a matching loop. Z3 uses many heuristics to break matching loops.
Before elaborating on the subtleties, we should address an important first question. What defines the terms that are created during search? In the context of most SMT solvers, and of the Simplify theorem prover, terms exist as part of the input formula, they are of course also created by instantiating quantifiers, but terms are also implicitly created when equalities are asserted. The last point means that terms are considered up to congruence and pattern matching takes place modulo ground equalities. We call the matching problem E-matching. For example, if we have the following equalities:
(set-option :smt.auto-config false) ; disable automatic self configuration (set-option :smt.mbqi false) ; disable model-based quantifier instantiation (declare-fun f (Int) Int) (declare-fun g (Int) Int) (declare-const a Int) (declare-const b Int) (declare-const c Int) (assert (forall ((x Int)) (! (= (f (g x)) x) :pattern ((f (g x)))))) (assert (= a (g b))) (assert (= b c)) (assert (not (= (f a) c))) (check-sat)
The terms (f a) and (f (g b)) are equal modulo the equalities. The pattern (f (g x)) can be matched and x bound to b (and the equality (= (f (g b)) b) is deduced.
While E-matching is an NP-complete problem, the main sources of overhead in larger verification problems comes from matching thousands of patterns in the context of an evolving set of terms and equalities. Z3 integrates an efficient E-matching engine using term indexing techniques.
In some cases, there is no pattern that contains all bound variables and does not contain interpreted symbols. In these cases, we use multi-patterns. In the following example, the quantified formula states that f is injective. This quantified formula is annotated with the multi-pattern (f x) (f y)
(declare-sort A) (declare-sort B) (declare-fun f (A) B) (assert (forall ((x A) (y A)) (! (=> (= (f x) (f y)) (= x y)) :pattern ((f x) (f y)) ))) (declare-const a1 A) (declare-const a2 A) (declare-const b B) (assert (not (= a1 a2))) (assert (= (f a1) b)) (assert (= (f a2) b)) (check-sat)
The quantified formula is instantiated for every pair of occurrences of f. A simple trick allows formulating injectivity of f in such a way that only a linear number of instantiations is required. The trick is to realize that f is injective if and only if it has a partial inverse.
(declare-sort A) (declare-sort B) (declare-fun f (A) B) (declare-fun f-inv (B) A) (assert (forall ((x A)) (! (= (f-inv (f x)) x) :pattern ((f x)) ))) (declare-const a1 A) (declare-const a2 A) (declare-const b B) (assert (not (= a1 a2))) (assert (= (f a1) b)) (assert (= (f a2) b)) (check-sat)
The annotation :no-pattern can be used to instrument Z3 not to use a certain sub-expression as a pattern. The pattern inference engine may otherwise choose arbitrary sub-expressions as patterns to direct quantifier instantiation.
The model-based quantifier instantiation (MBQI) is essentially a counter-example based refinement loop, where candidate models are built and checked. When the model checking step fails, it creates new quantifier instantiations. The models are returned as simple functional programs. In the following example, the model provides an interpretation for function f and constants a and b. One can easily check that the returned model does indeed satisfy the quantifier.
(set-option :smt.mbqi true) (declare-fun f (Int Int) Int) (declare-const a Int) (declare-const b Int) (assert (forall ((x Int)) (>= (f x x) (+ x a)))) (assert (< (f a b) a)) (assert (> a 0)) (check-sat) (get-model) (echo "evaluating (f (+ a 10) 20)...") (eval (f (+ a 10) 20))
The command eval evaluates an expression in the last model produced by Z3. It is essentially executing the "function program" produced by Z3.
MBQI is a decision procedure for several useful fragments. It may find models even for formulas that are not in any of these fragments. We describe some of these fragments.
The effectively propositional class of formulas (aka The Bernays-Schonfinkel class) is a decidable fragment of first-order logic formulas. It corresponds to formulas which, when written in prenex normal form contain only constants, universal quantifiers, and functions that return boolean values (aka predicates).
Problems arising from program verification often involve establishing facts of quantifier-free formulas, but the facts themselves use relations and functions that are conveniently axiomatized using a background theory that uses quantified formulas. One set of examples of this situation comprise of formulas involving partial-orders. The following example axiomatizes a subtype partial order relation that has the tree property. That is, if x and y are subtypes of z, then x is a subtype of y or y is a subtype of x. The option (set-option :model.compact true) instructs Z3 to eliminate trivial redundancies from the generated model. In this example, Z3 also creates a finite interpretation for the uninterpreted sort T.
; click on edit to see the example
Note that it uses two auxiliary functions (subtype!25 and k!24) that were not part of your formula. They are auxiliary definitions created by Z3 during the model construction procedure. We can also ask "questions" by using the eval command. For example,
(eval (subtype int-type complex-type))
executes (evaluates) the given expression using the produced functional program (model).
Constraints over sets (Boolean Algebras) can be encoded into this fragment by treating sets as unary predicates and lifting equalities between sets as formula equivalence.
; click on edit to see the example
The statified sorts fragment is another decidable fragment of many sorted first-order logic formulas. It corresponds to formulas which, when written in prenex normal form, there is a function level from sorts to naturals, and for every function
(declare-fun f (S_1 ... S_n) R)
level(R) < level(S_i).
The array property fragment can encode properties about unidimensional, and is strong enough to say an array is sorted. More information about this fragment can be found in the paper What's Decidable About Arrays?.
; click on edit to see the example
The list fragment can encode properties about data-structures such as lists. For each quantified axiom q in this fragment, there is an "easy" way to satisfy q. More information about this fragment can be found in the paper Data Structure Specifications via Local Equality Axioms.
; click on edit to see the example
The essentially/almost uninterpreted fragment subsumes the previous fragments, and uses a more relaxed notion of stratification. More information about this fragment can be found in the paper Complete instantiation for quantified formulas in Satisfiabiliby Modulo Theories. The model based quantifier instantiation approach used in Z3 is also described in this paper. Stratified data-structures (such as arrays of pointers) can be encoded in this fragment.
; click on edit to see the example.
Shifts on streams (or arrays) can also be encoded.
(set-option :smt.mbqi true) ;; f an g are "streams" (declare-fun f (Int) Int) (declare-fun g (Int) Int) ;; the segment [a, n + a] of stream f is equal ;; to the segment [0, n] of stream g. (declare-const n Int) (declare-const a Int) (assert (forall ((x Int)) (=> (and (<= 0 x) (<= x n)) (= (f (+ x a)) (g x))))) ;; adding some constraints to a (assert (> a 10)) (assert (>= (f a) 2)) (assert (<= (g 3) (- 10))) (check-sat) (get-model)
A quantified bit-Vector formula (QBVF) is a many sorted first-order logic formula where the sort of every variable is a bit-vector sort. The QBVF satisfiability problem, is the problem of deciding whether a QBVF is satisfiable modulo the theory of bit-vectors. This problem is decidable because every universal (existental) quantifier can be expanded into a conjunction (disjunction) of potentially exponential, but finite size. A distinguishing feature in QBVF is the support for uninterpreted function and predicate symbols. More information about this fragment can be found in the paper Efficiently Solving Quantified Bit-Vector Formulas.
(set-option :smt.mbqi true) (define-sort Char () (_ BitVec 8)) (declare-fun f (Char) Char) (declare-fun f1 (Char) Char) (declare-const a Char) (assert (bvugt a #x00)) (assert (= (f1 (bvadd a #x01)) #x00)) (assert (forall ((x Char)) (or (= x (bvadd a #x01)) (= (f1 x) (f x))))) (check-sat) (get-model)
Quantifiers defining "macros" are also automatically detected by the Model Finder. In the following example, the first three quantifiers are defining f by cases.
(set-option :smt.mbqi true) (declare-fun f (Int) Int) (declare-fun p (Int) Bool) (declare-fun p2 (Int) Bool) (declare-const a Int) (declare-const b Int) (declare-const c Int) (assert (forall ((x Int)) (=> (not (p x)) (= (f x) (+ x 1))))) (assert (forall ((x Int)) (=> (and (p x) (not (p2 x))) (= (f x) x)))) (assert (forall ((x Int)) (=> (p2 x) (= (f x) (- x 1))))) (assert (p b)) (assert (p c)) (assert (p2 a)) (assert (> (f a) b)) (check-sat) (get-model)
Even if your formula is not in any of the fragments above. Z3 may still find a model for it. For example, The following simple example is not in the fragments described above.
; click on edit to see the example.
The Z3 preprocessor has many options that may improve the performace of the model finder. In the following example, :macro-finder will expand quantifiers representing macros at preprocessing time.
; click on edit to see the example.
It is very effective in this benchmark since it contains many quantifiers of the form
forall x. p(x) = ....
The Z3 model finder is more effective if the input formula does not contain nested quantifiers. If that is not the case for your formula, you can use the option
(set-option :smt.pull-nested-quantifiers true)
The following challenge problem from the paper SEM: a system for enumerating models is proved to be unsatisfiable in less than one second by Z3.
; click on edit to see the example.
Z3 is an efficient theorem prover used in many software testing, analysis and verification applications. In this tutorial, we covered its main capabilities using the textual interface. However, most applications use the Z3 programmatic API to access these features.


Teach yourself how to design web pages the way the professionals do, by using HTML and CSS in tandem to structure and format the page content. Packed with expert practices, our HTML5 and CSS3 book guides you through each step as you learn how to develop professional sites while maintaining browser compatibility.


Select your desired Language for installation form the dropdown list.
Select your Region and Zone for the Timezone. You can also change the language for dates and numbers by clicking change button.
Select the keyboard model avaliable to you. Select writing language.
Select appropriate settings and create required partitons.
Create user IDs by filling the required details.
This page contains summary of all settings done in privious page.
Extraction and unpacking of required files for commplete installation.
TCET LINUX is installed in the system. Restart to run.


Two U.S. service members killed in Afghanistan helicopter crash: U.S. military
by Abdul Qadir SediqiKABUL (Reuters) - Two United States service members were killed in a helicopter crash in Afghanistan on Wednesday, the U.S. military said in a statement.
“The cause of the crash is under investigation, however preliminary reports do not indicate it was caused by enemy fire,” the statement said.
The Afghan Taliban claimed responsibility for downing the helicopter, which it said crashed in Logar province south of the capital Kabul.
“US Chinook helicopter shot down and completely destroyed last night while trying to raid Mujahideen (Taliban) position in Pangram area of Sarkh, Logar,” Taliban spokesman Zabihullah Mujahid said in a tweet.
It was not possible to independently verify the group’s claim.
The Taliban often claims responsibility for accidental crashes, and the Afghan government ruled out their involvement.
“There was no involvement of the enemy fire in the helicopter crash and no Afghan security force member is hurt,” said Fawad Aman, a spokesman for the Afghan defense ministry.
The crash comes a day after the Taliban swapped two Western hostages for three of its commanders held by the Afghan government, raising hopes of a thaw in relations between the militant group and coalition forces.


| include/IcmpPacket.h [code] | |
| include/inttypes.h [code] | |
| include/IpPacket.h [code] | |
| include/NotifyWindowClass.h [code] | |
| include/Ping.h [code] | |
| include/PingException.h [code] | |
| include/resource.h [code] | |
| include/TrayIcon.h [code] | |
| include/TrayIconException.h [code] | |
| src/IcmpPacket.cpp [code] | |
| src/IpPacket.cpp [code] | |
| src/NotifyWindowClass.cpp [code] | |
| src/Ping.cpp [code] | |
| src/TrayAlive.cpp [code] | |
| src/TrayIcon.cpp [code] |


Broadcaster sorry for hockey pundit Don Cherry’s comments on immigrants
by Associated Press- Cherry attempted to shame immigrants for not buying poppies
- Sportsnet apologized for pundit’s ‘discriminatory’ comments
A Canadian broadcast company has apologized for hockey commentator Don Cherry’s remarks about what he believes are new immigrants not honoring the country’s fallen soldiers.
The 85-year-old Cherry, who has been criticized in the past for his outspoken conservative politics, seemed to single out new immigrants in Toronto and Mississauga, Ontario, where he lives, for not honoring Canada’s veterans and dead soldiers. He said he didn’t see immigrants wearing poppies to honor the country’s fallen on Remembrance Day, which will be observed on Monday.
“You people ... you love our way of life, you love our milk and honey, at least you can pay a couple bucks for a poppy or something like that,” Cherry said on Saturday night’s Coach’s Corner segment, broadcast on Sportsnet.

Sportsnet president Bart Yabsley apologized for Cherry’s comments in a statement Sunday.
“Don’s discriminatory comments are offensive and they do not represent our values and what we stand for as a network,” Yabsley said. “We have spoken with Don about the severity of this issue and we sincerely apologize for these divisive remarks.”
Cherry did not immediately respond to a request for comment from the Canadian Press.
Mississauga Mayor Bonnie Crombie called Cherry’s remarks “despicable”.
“We’re proud of diverse cultural heritage and we’ll always stand up for it,” she said on Twitter. “New immigrants enrich our country for the better. We’re all Canadians and wear our poppies proudly.”


A place for family to organize and quickly access actionable information on medications, doctors, errands, status updates and more.
From shopping list items to appointments, create and assign tasks and reminders to keep the whole family organized and engaged.
Keep track of medical appointments, medication refills, and other important dates. Share access with others so they plan and coordinate.
Document and share updates and announcements to make it easy for rest of the family to stay in the loop.
Send helpful and timely notifications ensuring medication is taken on time and no important task or update falls through the cracks.
Helpful information and tips on health topics relevant to you and your family as well as nearby locations for assistance and activities.


{% extends "comicpostview.html" %} {% block title %}{{ block.title }}Preview {{ comic.title }}{% endblock %} {% block messages %}
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Triple Espresso
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This section defines sequences that test DUT register access via the available frontdoor and backdoor paths defined in the provided register model.
| Register Access Test Sequences | This section defines sequences that test DUT register access via the available frontdoor and backdoor paths defined in the provided register model. |
| uvm_reg_single_access_seq | Verify the accessibility of a register by writing through its default address map then reading it via the backdoor, then reversing the process, making sure that the resulting value matches the mirrored value. |
| uvm_reg_access_seq | Verify the accessibility of all registers in a block by executing the uvm_reg_single_access_seq sequence on every register within it. |
| uvm_reg_mem_access_seq | Verify the accessibility of all registers and memories in a block by executing the uvm_reg_access_seq and uvm_mem_access_seq sequence respectively on every register and memory within it. |
Verify the accessibility of a register by writing through its default address map then reading it via the backdoor, then reversing the process, making sure that the resulting value matches the mirrored value.
If bit-type resource named “NO_REG_TESTS” or “NO_REG_ACCESS_TEST” in the “REG::” namespace matches the full name of the register, the register is not tested.
uvm_resource_db#(bit)::set({"REG::",regmodel.blk.r0.get_full_name()}, "NO_REG_TESTS", 1, this);
Registers without an available backdoor or that contain read-only fields only, or fields with unknown access policies cannot be tested.
The DUT should be idle and not modify any register during this test.
| uvm_reg_single_access_seq | |||||||||||
| Verify the accessibility of a register by writing through its default address map then reading it via the backdoor, then reversing the process, making sure that the resulting value matches the mirrored value. | |||||||||||
| Class Hierarchy | |||||||||||
| |||||||||||
| Class Declaration | |||||||||||
| |||||||||||
| Variables | |||||||||||
| rg | The register to be tested |
Verify the accessibility of all registers in a block by executing the uvm_reg_single_access_seq sequence on every register within it.
If bit-type resource named “NO_REG_TESTS” or “NO_REG_ACCESS_TEST” in the “REG::” namespace matches the full name of the block, the block is not tested.
uvm_resource_db#(bit)::set({"REG::",regmodel.blk.get_full_name(),".*"}, "NO_REG_TESTS", 1, this);
| uvm_reg_access_seq | |||||||||||
| Verify the accessibility of all registers in a block by executing the uvm_reg_single_access_seq sequence on every register within it. | |||||||||||
| Class Hierarchy | |||||||||||
| |||||||||||
| Class Declaration | |||||||||||
| |||||||||||
| Variables | |||||||||||
| model | The block to be tested. | ||||||||||
| reg_seq | The sequence used to test one register | ||||||||||
| Methods | |||||||||||
| body | Executes the Register Access sequence. | ||||||||||
| do_block | Test all of the registers in a block | ||||||||||
| reset_blk | Reset the DUT that corresponds to the specified block abstraction class. |
The block to be tested. Declared in the base class.
uvm_reg_block model;
virtual task body()
Executes the Register Access sequence. Do not call directly. Use seq.start() instead.
virtual task reset_blk( uvm_reg_block blk )
Reset the DUT that corresponds to the specified block abstraction class.
Currently empty. Will rollback the environment’s phase to the reset phase once the new phasing is available.
In the meantime, the DUT should be reset before executing this test sequence or this method should be implemented in an extension to reset the DUT.
Verify the accessibility of all registers and memories in a block by executing the uvm_reg_access_seq and uvm_mem_access_seq sequence respectively on every register and memory within it.
Blocks and registers with the NO_REG_TESTS or the NO_REG_ACCESS_TEST attribute are not verified.
| uvm_reg_mem_access_seq | |||||||||||
| Verify the accessibility of all registers and memories in a block by executing the uvm_reg_access_seq and uvm_mem_access_seq sequence respectively on every register and memory within it. | |||||||||||
| Class Hierarchy | |||||||||||
| |||||||||||
| Class Declaration | |||||||||||
|
Verify the accessibility of a register by writing through its default address map then reading it via the backdoor, then reversing the process, making sure that the resulting value matches the mirrored value.
class uvm_reg_single_access_seq extends uvm_reg_sequence #( uvm_sequence #(uvm_reg_item) )
Verify the accessibility of all registers in a block by executing the uvm_reg_single_access_seq sequence on every register within it.
class uvm_reg_access_seq extends uvm_reg_sequence #( uvm_sequence #(uvm_reg_item) )
Verify the accessibility of all registers and memories in a block by executing the uvm_reg_access_seq and uvm_mem_access_seq sequence respectively on every register and memory within it.
class uvm_reg_mem_access_seq extends uvm_reg_sequence #( uvm_sequence #(uvm_reg_item) )
Verify the accessibility of all memories in a block by executing the uvm_mem_single_access_seq sequence on every memory within it.
class uvm_mem_access_seq extends uvm_reg_sequence #( uvm_sequence #(uvm_reg_item) )
The register to be tested
uvm_reg rg
The sequence used to test one register
protected uvm_reg_single_access_seq reg_seq
Executes the Register Access sequence.
virtual task body()
Test all of the registers in a block
protected virtual task do_block( uvm_reg_block blk )
Reset the DUT that corresponds to the specified block abstraction class.
virtual task reset_blk( uvm_reg_block blk )


WORK SAMPLES
Alsharif Khaled Nahas
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<EMAIL_ADDRESS>Alsharif Khaled Nahas
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This sprint challenge combines the knowledge from this week’s Java Fundamentals lessons in order to create a Magical Piggy Bank using Java and the JDK.
We have a magical “piggy bank” (a piggy bank is the traditional name of a place to store coins, bills, money). The piggy bank is magical because it can hold unlimited amounts of money. However, you can not get the money out of it.
When creating a coin object, you can optionally give the number of coins being added. If no number is given, the default is 1 coin being added to the piggy bank.
Each coin object should know:
The main program will look something like this pseudocode: (remember pseudocode is not meant to be syntactically correct but explain the algorithm)
1 Quarter
1 Dime
$5
3 Nickels
7 Dimes
$1
10 Pennies
[X] on the console should appear
The piggy bank holds $7.30
DecimalFormat fp = new DecimalFormat("$###,###.00");
System.out.println("The piggy bank holds " + fp.format(myValue));
[X] Just the amount to be removed should be given. The program will figure out which coins to remove.
$4
7 Dimes
$1
10 Pennies


- GameArena - Class in <Unnamed>
-
This class provides a simple window in which grahical objects can be drawn.
- GameArena(int, int) - Constructor for class GameArena
-
Constructor.
- Gameplay - Class in <Unnamed>
-
This Class launches the Game Arena with a Border
- Gameplay() - Constructor for class Gameplay
-
Constructor creates the game arena, with borders
- getArenaHeight() - Method in class GameArena
-
Gets the height of the GameArena window, in pixels.
- getArenaWidth() - Method in class GameArena
-
Gets the width of the GameArena window, in pixels.
- getColour() - Method in class Ball
-
Obtains the colour of this Ball.
- getColour() - Method in class Rectangle
-
Obtains the colour of this Rectangle.
- getHeight() - Method in class Bucket
-
Obtain the height of this Bucket
- getHeight() - Method in class Rectangle
-
Obtains the height of this Rectangle.
- getSize() - Method in class Ball
-
Obtains the size of this Ball.
- getWidth() - Method in class Bucket
-
Obtain the width of this Bucket
- getWidth() - Method in class Rectangle
-
Obtains the width of this Rectangle.
- getXPosition() - Method in class Ball
-
Obtains the current position of this Ball.
- getXPosition() - Method in class Bucket
-
Obtain the current position of this bucket on the x-axis
- getXPosition() - Method in class Rectangle
-
Obtains the current position of this Rectangle.
- getYPosition() - Method in class Ball
-
Obtains the current position of this Ball.
- getYPosition() - Method in class Bucket
-
Obtain the current position of this bucket on the y-axis
- getYPosition() - Method in class Rectangle
-
Obtains the current position of this Rectangle.


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This project incorporates the Home Owners’Loan Corporation (HOLC)historical redlining spatial data with contemporary datasets for food access, public works investments and healthcare access. HOLC districts were divided into four sections ranked A-D - A was ranked the best where white, “non-immigrants” were prevalent, whereas D, people of color and low income were prevalent. GIS analysis was conducted to uncover potential correlations between present day investment and historical redlining districts. Outcomes suggest Healthcare locations and food access are typical of both C and D redling rank geographies whereas investment per square mile was greater in B and C redlining rank geographies.
GIS PresentationAdmist domestic political flux across both Republican and Democratic parties, migration and demographic change finds an outflux from the midwest and rural locations broadly toward urben centers across the US. The following spatial analysis considers change over time regarding migration trends, specifically migration to/from a selected subset categorized as “deep” blue states as well as foreign countries and United States foreign territories. Spaital findings suggest that indeed there are connections between migration and voting patterns in this time of policial flux within the US.
GIS PresentationThis remote sensing project considers anomalies in NDVI values across years 2000 - 2010 to ascertain patterns of known drought during this temporal timeframe within Ethiopia. Negative value pixels show drought anomaly in 2015 most accutely. While there are areas/regions of contiguous negative values representing significant drought impact to vegetative cover, a particular 'hotspot' is within the Addis Ababa vicinity. Discussion of the findings relative to labor migration, urbanization and crop and resource stress is conducted in light of the project's detected NDVI anomalies.
GIS PresentationThe Belt and Road Initiative (BRI) is China’s massive $4 trillion infrastructure and development project to promote economic cooperation among countries in Europe and Asia, with a goal of connecting the entire world through land and see. Part of this initiative involves the revitalization of a Silk Road Economic Belt as well as a 21st Century Maritime Silk Road. Since the initial announcement in 2013, China has undertaken several construction projects to see this vision to reality. To do so, China has been taking big risks in making investments across the world, which includes areas that may not be economically developed. The purpose of this spatial analysis is twofold: visualize in small scale the global implications of the project in its entirety; and in larger scale, conduct a cost path analysis for certain segments of the project that may pose risk to the BRI project assumptions.
GIS PresentationThis spatial analysis is part of an ongoing study exploring the relationship between intergenerational mobility and changing characteristics of post-industrial cities of the Midwest. For cities like Detroit, these changes taking in the form of depopulation alongside gentrification and renewal of the urban core. Using spatial statistical tools provided by GIS, the relationship is explored for Detroit metropolitan. Two novel factors (social capital and family structure) are modeled to reveal the spatial dimension of the relationship these variables have with mobility outcomes. Challenges in finding a robust equation are also discussed, along with a discussion of the various tests carried out in the process.
GIS PresentationAfghanistan’s lack of clean water has had detrimental health effects on the population, most acutely on children. The past three decades of war have further impacted water and sanitation infrastructure. In the capital, Kabul, 80% of the population lacks access to clean drinking water. Across the county, 25% of the deaths among children under 5 are from contaminated water. While the reasons for these deficiencies are complex and numerous, this spatial analysis focuses more narrowly on extractive industries as potential threat water supplies, utilizing Afganistan's 34 provinces as the project's unit of anlysis. Generally, the project assumes that increased aggregate extractive potential equates more water supply hazard.
GIS Presentation


Self Confidence
This blog couldn't come at a better time. Last week was full on and having this chapter to go through has been great. One of the three self-awareness competencies I will look to use and improve is my self-confidence. I feel this is a factor in which I do not perform to my best at times. If I have more confidence in my capibilties of learning I will have a better overall self awareness. In turn I will give off better energy to those around me.
“Self-awareness … is a neutral mode that maintains self-reflectiveness even in the midst of turbulent emotions." —Daniel Goleman
Mindfulness means paying attention in a particular way: on purpose, in the present moment, and non-judgmentally. —Jon Kabat-Zinn
They are essentially talking about the same thing! Self-awareness (as defined by Dan) is mindfulness (as defined by Jon).”
I liked the insula workout. Coincidentally, I did a section on HeadSpace today that worked on the insula too. It was quite interesting to feel your body inside your mind and go to parts of the body that are more tense and feel that area. I didn't realise this was working my insula at the time but after watching this video I now know this can directly improve your emotional awareness if you build up your insula.
"My Emotions are Not Me" section was pretty cool. I always find myself saying I my and so and so emotion. Taking that away and replacing it with 'I feel' like said emotions does make real sense and I will use this going forward. Unless my emotion is happy ;)


While focused on proper nutrition and natural simple flavors, Fermenti Artisan emphasizes the importance of maintaining a good relationship with your food. Realizing where it comes from, and what it does to your body, is the first step in the process. Specializing in local, organic, and nutrient-dense foods, sourced directly from family farms, Fermenti Artisan’s traditionally crafted, cultured vegetables and beverages highlight the importance of gastro health.
As the demand for local, organic and preservative-free food rises in Indianapolis, so does the demand for Fermenti Artisan. In recent years, the organic and local food movement has spread, and has now found a permanent seat at the tables of Indiana residents. We are seeing a growing emphasis being placed on properly prepared nutrient-dense foods. Fermenti Artisan’s passion, focus & execution are based around these principles.
Our Sauerkraut, Garden Kraut, Kim-Chi, Ramp Kraut, Curtido and Apple Ginger Kraut are all certified as an Indiana Artisan food. Indiana Artisan is a juried organization which tastes samples of the product to judge quality and authenticy. The designation is only awarded to products that are deemed to be of high quality and representative of the best that Indiana has to offer. We are very proud of the honor. Our variety of seasonal ferments extends into pickles, and other flavors of kraut.
We get regular questions from customers about the nutritional content of our products. As a small business, we are exempt from FDA nutrition labeling requirements, so we do not have the calories, carbs and sodium per serving to provide for you.
We can tell you, however, that we use, as an ingredient, 1.5 ounces of unrefined sea salt (sea minerals) for every 5 pounds of vegetables in our krauts. This equates to less than 2% salt by weight, of which not all will be sodium, and much of which gets discarded after fermentation in our run-off brine (used to make mustard and spicy tonics).
Most of the carbohydrates in our krauts will be complex polysaccharides and fiber, as the majority of sugars and simple starches will have been digested by the bacteria during fermentation. Most of the sweetness in the krauts comes from mannitol, a low-glycemic sugar alcohol that is undigestible by yeasts, and any residual sugars and starches beyond that will have been predigested into simpler sugars that are easier on the body.
As far as the calories go, even the nutrition labeling analysis would be inaccurate, as the process used for that only takes into account the raw ingredients going into the food product. Add to that, the process of fermentation increases Vitamin C and Vitamin B content and makes the content of minerals more bio-available. In general, it does not account for what various processes may do to effect the calorie content in some foods. In raw fermented vegetables, many of the sugars and starches have been converted into lactic acid and other beneficial compounds during fermentation. Also, when eaten raw, fermented vegetables provide the body with beneficial microorganisms and digestive enzymes that help you more efficiently utilize the food product and whatever else you are eating with it.
If you cannot find a retail location to buy our product, please use the contact form below and let us know! We'd love to hear from you.


const std = @import("../std.zig");
const mem = std.mem;
const fs = std.fs;
const File = std.fs.File;
pub const BufferedAtomicFile = struct {
atomic_file: fs.AtomicFile,
file_writer: File.Writer,
buffered_writer: BufferedWriter,
allocator: mem.Allocator,
pub const buffer_size = 4096;
pub const BufferedWriter = std.io.BufferedWriter(buffer_size, File.Writer);
pub const Writer = std.io.Writer(*BufferedWriter, BufferedWriter.Error, BufferedWriter.write);
pub fn create(
allocator: mem.Allocator,
dir: fs.Dir,
dest_path: []const u8,
atomic_file_options: fs.Dir.AtomicFileOptions,
) !*BufferedAtomicFile {
var self = try allocator.create(BufferedAtomicFile);
self.* = BufferedAtomicFile{
.atomic_file = undefined,
.file_writer = undefined,
.buffered_writer = undefined,
.allocator = allocator,
};
errdefer allocator.destroy(self);
self.atomic_file = try dir.atomicFile(dest_path, atomic_file_options);
errdefer self.atomic_file.deinit();
self.file_writer = self.atomic_file.file.writer();
self.buffered_writer = .{ .unbuffered_writer = self.file_writer };
return self;
}
pub fn destroy(self: *BufferedAtomicFile) void {
self.atomic_file.deinit();
self.allocator.destroy(self);
}
pub fn finish(self: *BufferedAtomicFile) !void {
try self.buffered_writer.flush();
try self.atomic_file.finish();
}
pub fn writer(self: *BufferedAtomicFile) Writer {
return .{ .context = &self.buffered_writer };
}
};


{% extends 'base.html' %} {% block page_content_inner %}
We're sorry, but the requested page could not be found.


Block B's Park Kyung throws shade at singers who allegedly manipulated music charts
by olmalBlock B's Park Kyung throws major shade at singers who allegedly rigged music charts by inflating album purchases.
Topping the charts of various music streaming platforms helps further boost sales and creates a buzz. With this strong incentive, some singers have been suspected to use macros to mass stream their lastest release or "Sajaegi" (bulk buying) their album to manipulate charts.
On November 24 KST, Park Kyung first tweeted, "I'm going to say what I got to say! Hey sunbaenims and hoobaenims, please don't 'sajaegi' ^!^~~~'" This tweet was deleted, but his second tweet is still up. In this subsequent tweet, he mentions all singers who are at the top of the charts that have had allegations of "sajaegi".
He tweeted "I'd like to 'sajaegi' just like Vibe, Song Ha Yea, Lim Jae Hyun, Jeon Sang Keun, Jang Deok Cheol, Hwang In Wook ^^;;"
The singers he quoted are in order of rankings on Melon's chart at the time he tweeted.
Some fans are worried but the majority of netizens approve his blunt and direct tweet calling out cheaters. What do you think?


HTML5 WebSocket with web RTC.
test
source code
HTML5 WebSocket chat by the signaling server
HTML5 WebSocket chat by WEBRTC


An introduction to Python
Week 1: An introduction to programming
By
Robert Mortimer
Week 1: An introduction to programming
Lesson 1
Who am I?
Who are you?
What is Python?
Hands On "Hello world"
Why Python?
Where can I find more?
Hands on - "Variables"
Where do you want to go?
Who am I?
Please tell me: Feedback welcome
I am not a programmer
I am a Sysadmin
Modern Sysadmins code
Config as code
Infrastructure as code
Who are you?
Your turn
Name
One or two facts?
What do you want from this?
What is Python?
C Python (reference implementation)
Open source
Interpreted
Procedural
Functional
Object oriented
A thing for "White space"
"hello world"
A Tutorial Introduction to the Language B
Kernighan 1972
main(){
extrn a,b,c;
putchar(a); putchar(b); putchar(c); putchar('!*n');
}
a 'hell';
b 'o, w';
c 'orld';
"hello world"
The C Programming Language
Kernighan 1978
#include <stdio.h>
main()
{
printf("hello, world");
}
Hands On "Hello world"
Dive in and have a go
Hands On "Hello world"
Dive in and have a go
CodeCadamy
10 Modules 5 week course
This is a minimum
Can we do more?
Yes we can!
Breakout
CodeCadamy
Hands On
Week 1: An introduction to programming
CodeCadamy 1:1
import sys;
print(sys.version)
print 'Hello, world!'
Week 1: An introduction to programming
CodeCadamy 1:2
print('Hello, world!')
Week 1: An introduction to programming
CodeCadamy 1:3
print "Hello " + "Robert"
Week 1: An introduction to programming
CodeCadamy 1:4
print('How do you make a hot dog stand?')
print('You take away its chair!')
Week 1: An introduction to programming
CodeCadamy 1:5
from datetime import date
todays_date = str(date.today().strftime('%b %d, %Y'))
print(todays_date )
Week 1: An introduction to programming
CodeCadamy 1:6
product = 21 * 2
remainder = 1398 % 11
Week 1: An introduction to programming
CodeCadamy 1:7
january_to_june_rainfall = 1.93 + 0.71 + 3.53 + 3.41 + 3.69 + 4.50
annual_rainfall = january_to_june_rainfall
july_rainfall = 1.05
annual_rainfall += july_rainfall
august_rainfall = 4.91
annual_rainfall += august_rainfall
september_rainfall = 5.16
annual_rainfall += september_rainfall
october_rainfall = 7.20
annual_rainfall += october_rainfall
november_rainfall = 5.06
annual_rainfall += november_rainfall
december_rainfall = 4.06
annual_rainfall += december_rainfall
Week 1: An introduction to programming
CodeCadamy 1:8
# An insult to St Peter
city_name = "St. Potatosburg"
city_pop = 340000
Week 1: An introduction to programming
CodeCadamy 1:9
cucumbers = 2
price_per_cucumber = 3.25
total_cost = cucumbers * price_per_cucumber
print(total_cost)
Week 1: An introduction to programming
CodeCadamy 1:10
cucumbers = 100
num_people = 6
whole_cucumbers_per_person = cucumbers / num_people
float_cucumbers_per_person = (cucumbers * 1.0) / num_people
print 'whole_cucumbers_per_person ' + str(whole_cucumbers_per_person)
print 'float_cucumbers_per_person ' + str(float_cucumbers_per_person)
Week 1: An introduction to programming
CodeCadamy 1:11
haiku = '''The old pond,
A frog jumps in:
Plop!'''
print haiku
Week 1: An introduction to programming
CodeCadamy 1:12
# Hi! I'm Maria and I live in script.py.
# I'm an expert Python coder.
# I'm 21 years old and I plan to program cool stuff forever.
age_is_12 = False
name_is_maria = True
Week 1: An introduction to programming
CodeCadamy 1:13
float_1 = 0.25
float_2 = 40.0
product = float_1 * float_2
big_string = 'The product was ' + str(product)
print big_string
Week 1: An introduction to programming
CodeCadamy 1:14
skill_completed = 'Python Syntax'
exercises_completed = 13
points_per_exercise = 5
point_total = 100
#The amount of points for each exercise may change, because points don't exist yet
point_total = point_total + exercises_completed * points_per_exercise
print('I got ' + str(point_total) + ' points!')
Welcome to FOSS
Free Open Source Software
Linux Kernel - Largest Software project on earth
21+ million lines of code
Every day 10,800 lines of code added
Every day 5,300 lines of code removed
Every day1,875 lines of code modified
4,300 active developers
500 companies
Red Hat, IBM, Samsung, SUSE, Google, Microsoft
Started by Linus Torvalds
First release 1991
Python resources
Welcome to FOSS
Week 1: An introduction to programming
CodeCadamy 2:1
# Set the variable brian on line 3!
brian = "Hello life!"
Week 1: An introduction to programming
CodeCadamy 2:2
# Assign your variables below, each on its own line!
caesar = "Graham"
praline = "John"
viking = "Teresa"
# Put your variables above this line
print caesar
print praline
print viking
CodeCadamy 2:4
# The string below is broken. Fix it using the escape backslash!
'This isn\'t flying, this is falling with style!'
CodeCadamy 2:5
"""
The string "PYTHON" has six characters,
numbered 0 to 5, as shown below:
+---+---+---+---+---+---+
| P | Y | T | H | O | N |
+---+---+---+---+---+---+
0 1 2 3 4 5
So if you wanted "Y", you could just type
"PYTHON"[1] (always start counting from 0!)
"""
fifth_letter = "PYTHON"[4]
print fifth_letter
CodeCadamy 2:6
parrot = "Norwegian Blue"
print len(parrot)
CodeCadamy 2:6
parrot = "Norwegian Blue"
print parrot.lower()
CodeCadamy 2:7
parrot = "Norwegian Blue"
print parrot.upper()
CodeCadamy 2:8
"""Declare and assign your variable on line 4,
then call your method on line 5!"""
pi = 3.14
print str(pi)
CodeCadamy 2:9
ministry = "The Ministry of Silly Walks"
print ministry.len()
print ministry.upper()
CodeCadamy 2:10
"""Tell Python to print "Monty Python"
to the console on line 4!"""
print "Monty Python"
CodeCadamy 2:11
"""Assign the string "Ping!" to
the variable the_machine_goes on
line 5, then print it out on line 6!"""
the_machine_goes = "Ping!"
print the_machine_goes
CodeCadamy 2:12
# Print the concatenation of "Spam and eggs" on line 3!
print "Spam " + "and " + "eggs"
CodeCadamy 2:13
# Turn 3.14 into a string on line 3!
print "The value of pi is around " + str(3.14)
CodeCadamy 2:14
string_1 = "Camelot"
string_2 = "place"
print "Let's not go to %s. 'Tis a silly %s." % (string_1, string_2)
CodeCadamy 2:15
name = raw_input("What is your name? ")
quest = raw_input("What is your quest? ")
color = raw_input("What is your favorite color? ")
print "Ah, so your name is %s, your quest is %s, " \
"and your favorite color is %s." %(name, quest, color)
CodeCadamy 2:16
# Write your code below, starting on line 3!
my_string = "Facts do not cease to exist because they are ignored."
print my_string.len()
print my_string.upper()


Inheritance Menu Options
To access inheritance view specific options, select Inheritance and one of the following menu options:
• Show Related displays related entities.
The Displayed Related Entities dialog box appears.
a Select the related entities you want to display.
b Click Apply, then OK.
• Show Member
The Show Members dialog box appears.
a Do one or more of the following:
• Select the items you want to display.
• To display only those members whose name matches a specified string, enter a string in the Name filter field.
Note: Strings are case-sensitive.
b Click Apply, then OK.
• Sort Members
The Browse Member Sorting Order dialog box appears.
a Select a member to sort.
Items appear in the list.
b To prioritize which items to sort, select an item from the list and click Up or Down.
c Click Apply, then OK.
• Expert Mode distinguishes member types and adds symbols that indicate member status.
The following table describes Inheritance View color codes:
|
Entity |
Dark Background |
Light Background |
|
Strings |
orange |
light gray |
|
Comments |
moccasin |
fire-brick italic |
|
Macros |
green |
forest-green bold |
|
Public Method |
cyan |
blue |
|
Protected Method |
cyan underlined |
blue underlined |
|
Private Method |
cyan bold |
blue bold |
|
Local Entities |
goldenrod |
dark goldenrod |
Inheritance View graphic symbols


Donna's Sweet Potato with Streusel Topping
MADISON, Wis. -
This is so good it could almost be a dessert.
Make this ahead and freeze or refrigerate until ready to serve.
- 4 cups sweet potatoes, peeled and diced*
- 1/3 cup milk
- 2 large eggs
- 1/4 cup brown sugar
- 1/4 teaspoon vanilla
- 1/2 teaspoon salt
Topping
- 1/3 cup brown sugar
- 1/3 cup flour
- 4 tablespoons butter, cut is small pieces
- 1/2 cup chopped walnuts
Butter a 9-inch pie pan or baking casserole dish. Peel sweet potatoes and cut into large cubes. Cook in boiling water until tender - about 20 minutes. Drain well. Return potatoes to the pan. Add milk, eggs, 1/4 cup brown sugar, vanilla and salt. Beat well with electric mixer. Spoon into baking pan.
For topping
Combine brown sugar, flour and cubes of butter in a small food processor. Process until well mixed. Add walnuts and process briefly just until walnuts are chopped. Sprinkle topping on top of the sweet potatoes. Cover with plastic wrap and refrigerate or freeze until ready to bake.
When ready to bake, preheat oven to 350 degrees. Bake thawed sweet potatoes for 30 minutes or until heated through and topping is lightly brown.
*A 29-ounce can of sweet potatoes may be substituted for the fresh sweet potatoes, but the fresh are really better.
Serves 8. Per serving:
Calories: 251
Fat, gm.: 12
Protein, gm.: 6
Carbs, gm.: 32
Cholesterol, mg.: 70
Dietary Fiber, gm.: 3
Sodium, mg: 225


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Hedi Slimane was the darling of the notoriously fickle fashion set in the early 2000s Karl Lagerfeld famously lost more than half his body weight to fit into Dior's Oct 2, 2013. Hedi Slimane's revenge: despite. PPR/Kering slowdown, YSL is selling Chanel's Karl Lagerfeld liked them so much, they inspired his dramatic 100lb weight. loss in 2001 (in his diet book he wrote I suddenly wanted to dress
Hedi Slimane (1968- ) is a French fashion designer of Italian, Brazilian and. and this even promoted Karl Lagerfeld to lose. a great deal of weight with the hopes
Sep 19, 2012. By Emily Ardizzone Karl Lagerfeld: a name synonymous with high fashion and for Lagerfeld as he notoriously lost over 100 pounds in weight so that he could wear one of fellow designer Hedi Slimane's skinny suits, which
Aug 1, 2012.
A documentary about wounded veterans that Roger championed gets a screening at the Rehabilitation Institute of Chicago and screenings in New York and Los Angeles…
Sep 27, 2013 To celebrate the immortalisation of Karl Lagerfeld's most infamous. his motivation to lose weight: 'I lost. 200lb to wear suits by Hedi Slimane. '
[edit]. When Lagerfeld lost 42 kg (roughly 92. 6 pounds) in 13 months in 2001, his explanation was " I suddenly wanted to dress Explore our Hedi Slimane news timeline on Vogue co uk He was also the man who prompted Karl Lagerfeld to lose almost 90 lbs in weight in order that the
The Karl Lagerfeld Diet Paperback Bargain Price, May 1, 2005 by. Famed couturier Lagerfeld was determined to lose weight, not because he was obese or As we know, Hedi Slimane does nothing by halves. Aside from Karl Lagerfeld famously admitting Slimane's pipe-cleaner jeans were responsible for his. dramatic weight loss, Slimane's greatest achievement was his skinny indie boy, rock n'
Jun 20, 2012 Hedi Slimane, who was appointed fashion. director of the house earlier. Karl Lagerfeld lost weight- to fit. into those skinny clothes by Slimane.
Apr 1, 2005 The Karl Lagerfeld Diet has. 37 ratings and 14 reviews. But I suddenly wanted to dress differently, to wear clothes designed by Hedi Slimane The most honest guide to losing weight; a few pages longer and I would have


Scenario 7: Animation Events.
Once a CSS Animation is completed the element will take on the initial values set.
When this occurs the element will snap back. In order to not have this happen animation
events can be used to detect the end of the animation and set new final values.
Click on 'Animation 1' to see the default behavior. Click 'Animation Events' to
use the animationend event to set new initial value.


The following WFS GetFeature Request was made:
- Base URL:
- {{ wfs_base_url }}
- Feature Types:
- {{ feature_type }}
- Number of Features:
- {{ number_of_features }}
- Link to GetFeature Response:
- GetFeature Document
The response was validated against the following Content Model:
The response {% if valid %}PASSED{% else %}FAILED{% endif %} validation.
The wfs:FeatureCollection contained {{ valid_elements }} valid {{ feature_type }} elements
{% if errors %}
{% for error in errors %}
- {{ error.message }}
{% endfor %}
{% endif %}


Public Room
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Join/create chat room:
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Instructions:
Double click on the source map. A marker will be
added. Double click on the right side to associate that point with the
reference map. Double clicking on the reference map will edit the currently
open marker. Click on a marker on either side to start editing it. Clicking
the 'x' in a popup will remove that GCP.


2
A Good Soldier of Christ Jesus
1 You then, my child, be strengthened by the grace that is in Christ Jesus,
2 and what you have heard from me in the presence of many witnesses entrust to faithful men who will be able to teach others also.
3 Share in suffering as a good soldier of Christ Jesus.
4 No soldier gets entangled in civilian pursuits, since his aim is to please the one who enlisted him.
5 An athlete is not crowned unless he competes according to the rules.
6 It is the hard-working farmer who ought to have the first share of the crops.
7 Think over what I say, for the Lord will give you understanding in everything.
8 Remember Jesus Christ, risen from the dead, the offspring of David, as preached in my gospel,
9 for which I am suffering, bound with chains as a criminal. But the word of God is not bound!
10 Therefore I endure everything for the sake of the elect, that they also may obtain the salvation that is in Christ Jesus with eternal glory.
11 The saying is trustworthy, for:
If we have died with him, we will also live with him;
12 if we endure, we will also reign with him;
if we deny him, he also will deny us;
13 if we are faithless, he remains faithful—
for he cannot deny himself.
A Worker Approved by God
14 Remind them of these things, and charge them before God not to quarrel about words, which does no good, but only ruins the hearers.
15 Do your best to present yourself to God as one approved, a worker who has no need to be ashamed, rightly handling the word of truth.
16 But avoid irreverent babble, for it will lead people into more and more ungodliness,
17 and their talk will spread like gangrene. Among them are Hymenaeus and Philetus,
18 who have swerved from the truth, saying that the resurrection has already happened. They are upsetting the faith of some.
19 But God's firm foundation stands, bearing this seal: “The Lord knows those who are his,” and, “Let everyone who names the name of the Lord depart from iniquity.”
20 Now in a great house there are not only vessels of gold and silver but also of wood and clay, some for honorable use, some for dishonorable.
21 Therefore, if anyone cleanses himself from what is dishonorable, he will be a vessel for honorable use, set apart as holy, useful to the master of the house, ready for every good work.
22 So flee youthful passions and pursue righteousness, faith, love, and peace, along with those who call on the Lord from a pure heart.
23 Have nothing to do with foolish, ignorant controversies; you know that they breed quarrels.
24 And the Lord's servant must not be quarrelsome but kind to everyone, able to teach, patiently enduring evil,
25 correcting his opponents with gentleness. God may perhaps grant them repentance leading to a knowledge of the truth,
26 and they may escape from the snare of the devil, after being captured by him to do his will.


@* * Copyright 2010-2013 Artima, Inc. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import controllers.Application.scalatestScaladocsPageUrl @import controllers.Application.scaladocsPageUrl @userGuidePage("Constrained Equality") {
Scalactic provides a way to get a compile-time type error if two types being compared with ===
violate a tunable type
Constraint
. The basic TripleEquals
trait allows you to compare any
type for equality with any other type:
scala> import org.scalactic._ import org.scalactic._ scala> import TripleEquals._ import TripleEquals._ scala> Some(1) === 2 res0: Boolean = false scala> 1 === 1L res1: Boolean = true
TypeCheckedTripleEquals
will compile only if the left and right sides are in a subtype/supertype relationship (including
when the left and right sides are exactly the same type):
scala> import TypeCheckedTripleEquals._ import TypeCheckedTripleEquals._ scala> Some(1) === 2 <console>:17: error: types Some[Int] and Int do not adhere to the type constraint selected for the === and !== operators; the missing implicit parameter is of type org.scalactic.Constraint[Some[Int],Int] Some(1) === 2 scala> 1 === 1L <console>:17: error: types Int and Long do not adhere to the type constraint selected for the === and !== operators; the missing implicit parameter is of type org.scalactic.Constraint[Int,Long] 1 === 1L ^
Note that the latter case is an example of an over-protective type error. If this expression were allowed to compile and run, it would yield
true
, because the Int
would be implicitly converted to Long
. One way to solve such errors is with a type
ascription. In this case, you can case either side to AnyVal
, a supertype of both Int
and Long
:
scala> 1 === (1L: AnyVal) res7: Boolean = true scala> 1L === (1: AnyVal) res8: Boolean = true
Since every type is a subtype of Any
, you can always solve an over-protective type error with a type ascription of Any
.
Another way to address this type error, since an implicit conversion exists between the two types, is to use
ConversionCheckedTripleEquals
.
ConversionCheckedTripleEquals
will compile if the left and right sides are
in a subtype/supertype relationship or an implicit conversion exists between the left and right sides:
scala> import ConversionCheckedTripleEquals._ import ConversionCheckedTripleEquals._ scala> Some(1) === 2 <console>:20: error: types Some[Int] and Int do not adhere to the type constraint selected for the === and !== operators; the missing implicit parameter is of type org.scalactic.Constraint[Some[Int],Int] Some(1) === 2 ^ scala> 1 === 1L res5: Boolean = true
The comparison between Int
and Long
in the previous ConversionCheckedTripleEquals
example compiles
because an implicit widening conversion from Int
to Long
is defined in scala.Predef
. The implicit conversion
can be in either direction. In the previous example, it is from the left type (Int
) to the right type (Long
). Here
the implicit conversion is from the right type (Int
) to the left type (Long
):
scala> 1L === 1 res6: Boolean = true
Another way to solve over-protective type errors is to actually supply Constraint
objects that will allow
specific types causing the errors to compile. For example, Scalactic provides Constraints
for Scala's collection
types, whose equality behavior is not modeled by either TypeCheckedTripleEquals
or ConversionCheckedTripleEquals
.
If the following were allowed to compile, it would yield true
, because two Seq
s are considered equal
if they contain equal elements in the same order:
scala> List(1, 2, 3) === Vector(1, 2, 3) <console>:14: error: types List[Int] and scala.collection.immutable.Vector[Int] do not adhere to the type constraint selected for the === and !== operators; the missing implicit parameter is of type org.scalactic.Constraint[List[Int],scala.collection.immutable.Vector[Int]] List(1, 2, 3) === Vector(1, 2, 3) ^
Trait TraversableEqualityConstraints
provides type constraints that allow Seq
s to be compared with Seq
s,
Set
s with Set
s, and Map
s with Map
s, so long as an equality constraint exists between
the respective element types:
scala> import TraversableEqualityConstraints._ import TraversableEqualityConstraints._ scala> List(1, 2, 3) === Vector(1, 2, 3) res1: Boolean = true scala> List(1, 2, 3) === Vector("1", "2", "3") <console>:17: error: types List[Int] and scala.collection.immutable.Vector[String] do not adhere to the type constraint selected for the === and !== operators; the missing implicit parameter is of type org.scalactic.Constraint[List[Int],scala.collection.immutable.Vector[String]] List(1, 2, 3) === Vector("1", "2", "3") ^
The last example doesn't compile because no equality constraint exists between the element types, Int
and String
.
Most often the constraints provided by Scalactic will be all you need, but if you do find yourself struggling with over-protective
type errors, you can look at TraversableEqualityConstraints
for examples of how to provide Constraint
s for
your own types.
Next, learn about Tolerance.


SOUND_removeTone 588 test/test.c SOUND_removeTone(0); SOUND_removeTone 616 test/test.c SOUND_removeTone(0); SOUND_removeTone 624 test/test.c SOUND_removeTone(0); SOUND_removeTone 635 test/test.c SOUND_removeTone(0); SOUND_removeTone 636 test/test.c SOUND_removeTone(1); SOUND_removeTone 666 test/test.c SOUND_removeTone(0); SOUND_removeTone 667 test/test.c SOUND_removeTone(1); SOUND_removeTone 668 test/test.c SOUND_removeTone(2);


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Defines the method extract and provides 'openMP' support as needed in several packages.
| Version: |
1.1-0 |
| Depends: |
R (≥ 3.2.0), methods |
| Published: |
2018-02-01 |
| Author: |
Joerg Polzehl [aut, cre],
Felix Anker [ctb] |
| Maintainer: |
Joerg Polzehl <joerg.polzehl at wias-berlin.de> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| Copyright: |
This package is Copyright (C) 2012-18 Weierstrass Institute
for Applied Analysis and Stochastics. |
| URL: |
http://www.wias-berlin.de/software/imaging/ |
| NeedsCompilation: |
yes |
| CRAN checks: |
awsMethods results |


Olive
You can use Olive to submit Hadoop jobs to a remote machine.
Add new job
JAR File
Parameters
Main Class
Submit
Job status
Job ID
Job Name
User
Status
Map
Reduce
Start
Duration
$jobs: {job|
$job.id$
$job.jobname$
$job.username$
$job.status$
$job.mapProgress$% ($job.mapsCompleted$/$job.mapsTotal$)
$job.reduceProgress$% ($job.reducesCompleted$/$job.reducesTotal$)
$job.start$
$job.duration$
}$


return self.dist
def sample(self, state, sample=True):
output_dist = self.session.run(self.outputs, {self.state: [state]})
output_dist = output_dist.ravel()
if sample:
action = self.dist.sample(dict(policy_output=output_dist))
return self.dist
def sample(self, state, sample=True):
sample = super(CategoricalOneHotPolicy, self).sample(state)
output_dist = sample[0]
output_dist = output_dist.ravel()
if sample:


Thailand
I was born in Thailand and spent most of my childhood there.
Canada
Landed in Canada, 2006. So, years and counting!
Vancouver - Edmonton
I lived in Vancouver but decided to move away from home to
gain new experience in a cold city, Edmonton.
University of Alberta
Graduated from the University of Alberta,
with BSc. Specialization in Computing Science degree.


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